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Karamysheva, Iryna, Roksolyana Nazarchuk e Kateryna Lishnievska. "PECULIARITIES OF TRANSLATION OF ENGLISH LANGUAGE INSTRUCTIONS WITH THE USE OF ADDITIONAL TOOLS IN SDL TRADOS STUDIO AND MEMOQ TRANSLATOR PRO ENVIRONMENTS". Research Bulletin Series Philological Sciences 1, n.º 193 (abril de 2021): 376–82. http://dx.doi.org/10.36550/2522-4077-2021-1-193-376-382.
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The presented research focuses upon the analysis of additional specific tools (namely translation memory (TM) technologies) of SDL Trados Studio 2017 and MemoQ Translator Pro 2017 automated translation systems and their application for translation of English-language instructions into Ukrainian. With the help of the above-mentioned software tools 60 English-language operating instructions for household appliances have been translated into Ukrainian (three projects were created in both systems, each containing 10 instructions). TM is a database consisting of segments of source text (sentences, paragraphs, headings, etc.) and translations of each of these segments. TM, used in both SDL Trados Studio and MemoQ Translator Pro systems, significantly improves the quality, speed, consistency and efficiency of each translation task. SDL Trados Studio 2017 and MemoQ Translator Pro 2017 compare content of the current segment of the source file with segments of the same language already contained in the TM. If the system finds a similar segment that is currently stored in the TM, it prompts the translator to use a ready-made translation. The degree of equivalence between the segment of the source document and the segment contained in the TM is expressed as a percentage. Thus, both software tools capture the cases of «Exact match», «Perfect match» and «Fuzzy match». SDL Trados Studio 2017 andMemoQ Translator Pro 2017 slightly differ in segment statuses and colour segment marking. Both systems do not make adjustments automatically, but their identification and navigation capabilities allow one to quickly correct such errors by hand. Unfortunately, the initial focus on the Russian-language market (and, consequently, on the Russian language system) has led to another peculiarity of automated translation into Ukrainian in SDL Trados Studio and MemoQ Translator Pro systems, namely a large number of stylistic errors that require quality personalized correction.
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Zhang, Ping. "Design and Implementation of English-Chinese Translation Teaching Platform Based on Deep Learning". Journal of Electrical Systems 20, n.º 3s (31 de março de 2024): 1746–55. http://dx.doi.org/10.52783/jes.1714.
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The Translation Teaching Platform based on Deep Learning represents a groundbreaking advancement in language education, offering students immersive and personalized learning experiences. By leveraging deep learning algorithms, this platform facilitates real-time translation practice, allowing students to engage with authentic language materials and receive immediate feedback on their performance. Through interactive exercises, multimedia resources, and adaptive learning modules, students can enhance their language proficiency in a dynamic and engaging environment. Moreover, the platform's ability to analyze and adapt to individual learning styles enables personalized instruction tailored to each student's needs. With the Translation Teaching Platform based on Deep Learning, language educators can revolutionize their teaching methods and empower students to achieve fluency and proficiency in their target languages. This paper presents the design and implementation of an innovative English-Chinese Translation Teaching Platform based on Deep Learning, augmented by Embedding Feature Probabilistic Segmentation Classification (EF-PSC). The platform leverages advanced deep-learning techniques to provide students with immersive and interactive translation practice opportunities. Through simulated experiments and empirical validations, the efficacy of the platform is evaluated, demonstrating significant improvements in translation accuracy and learning outcomes compared to traditional methods. The EF-PSC model achieved an average accuracy rate of 91% in translating English to Chinese texts, outperforming conventional translation tools by 15%. Additionally, the platform's adaptive learning features enable personalized instruction tailored to each student's proficiency level and learning pace, leading to more effective language acquisition. These findings underscore the potential of deep learning with EF-PSC in revolutionizing translation teaching methods and enhancing language education.
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Luo, Jing. "Integration and Practice of Computer-Assisted Translation Technology in Modern Translation Teaching". International Education Forum 2, n.º 5 (11 de julho de 2024): 8–14. http://dx.doi.org/10.26689/ief.v2i5.7065.
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With the advancement of globalization and the rapid development of information technology, the demand for the translation industry is increasing, posing new challenges and opportunities for translation teaching. The introduction of Computer-Assisted Translation (CAT) technology provides rich resources and innovative methods for translation teaching. This paper explores the integration and practice of CAT technology in modern translation teaching, including translation memory, terminology management, machine translation, translation project management, quality assessment and proofreading tools, collaborative translation platforms, and personalized learning and feedback, analyzing their roles in improving teaching effectiveness and student translation abilities.
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Yefymenko, Tetiana, Tamara Bilous, Anna Zhukovska, Iryna Sieriakova e Iryna Moyseyenko. "Technologies for using interactive artificial intelligence tools in the teaching of foreign languages and translation". Revista Amazonia Investiga 13, n.º 74 (29 de fevereiro de 2024): 299–307. http://dx.doi.org/10.34069/ai/2024.74.02.25.
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The article explores the potential of artificial intelligence technologies in teaching foreign languages and translation. It explores the advantages and possible challenges of using such technologies in language education and provides practical examples. The article also discusses perspectives on the future development and use of interactive artificial intelligence tools in the field of language teaching and translation. The integration of artificial intelligence into higher education has ushered in a new era of transformation in educational processes, reforming various aspects of the educational experience. The advantages of introducing artificial intelligence into higher education are numerous, ranging from personalized learning paths to intelligent assessment tools. The tools are classified into categories for students, teachers, and the education system. It identifies key results of such processes and examines various technologies, including Linguatech Learning Assistant, Linguatech Translation Tool, and Linguatech Language Lab, which help students improve their language and translation skills. The research examines the effectiveness of interactive tools in education, comparing their use in classroom and distance learning formats. The article’s conclusions are significant for the development and improvement of language and translation education programs that use innovative artificial intelligence technologies.
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Adishesh e Hapangama. "Enriching Personalized Endometrial Cancer Research with the Harmonization of Biobanking Standards". Cancers 11, n.º 11 (5 de novembro de 2019): 1734. http://dx.doi.org/10.3390/cancers11111734.
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Endometrial cancer is the commonest gynecological cancer, with an incidence predicted to escalate by a further 50–100% before 2025, due to the rapid rise in risk factors such as obesity and increased life expectancy. Endometrial cancer associated mortality is also rising, depicting the need for translatable research to improve our understanding of the disease. Rapid translation of scientific discoveries will facilitate the development of new diagnostic, prognostic and therapeutic strategies. Biobanks play a vital role in providing biospecimens with accompanying clinical data for personalized translational research. Wide variation in collection, and pre-analytic variations in processing and storage of bio-specimens result in divergent and irreproducible data from multiple studies that are unsuitable for collation to formulate robust conclusions. Harmonization of biobanking standards is thus vital, in facilitating international multi-center collaborative studies with valuable outcomes to improve personalized treatments. This review will detail the pitfalls in the biobanking of biosamples from women with cancer in general, and describe the recent international harmonization project that developed standardized research tools to overcome these challenges and to enhance endometrial cancer research, which will facilitate future development of personalized novel diagnostic strategies and treatments.
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Lightbody, Gaye, Valeriia Haberland, Fiona Browne, Laura Taggart, Huiru Zheng, Eileen Parkes e Jaine K. Blayney. "Review of applications of high-throughput sequencing in personalized medicine: barriers and facilitators of future progress in research and clinical application". Briefings in Bioinformatics 20, n.º 5 (14 de junho de 2019): 1795–811. http://dx.doi.org/10.1093/bib/bby051.
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Abstract There has been an exponential growth in the performance and output of sequencing technologies (omics data) with full genome sequencing now producing gigabases of reads on a daily basis. These data may hold the promise of personalized medicine, leading to routinely available sequencing tests that can guide patient treatment decisions. In the era of high-throughput sequencing (HTS), computational considerations, data governance and clinical translation are the greatest rate-limiting steps. To ensure that the analysis, management and interpretation of such extensive omics data is exploited to its full potential, key factors, including sample sourcing, technology selection and computational expertise and resources, need to be considered, leading to an integrated set of high-performance tools and systems. This article provides an up-to-date overview of the evolution of HTS and the accompanying tools, infrastructure and data management approaches that are emerging in this space, which, if used within in a multidisciplinary context, may ultimately facilitate the development of personalized medicine.
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Alghamdi, Maha Ali, Antonino N. Fallica, Nicola Virzì, Prashant Kesharwani, Valeria Pittalà e Khaled Greish. "The Promise of Nanotechnology in Personalized Medicine". Journal of Personalized Medicine 12, n.º 5 (22 de abril de 2022): 673. http://dx.doi.org/10.3390/jpm12050673.
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Both personalized medicine and nanomedicine are new to medical practice. Nanomedicine is an application of the advances of nanotechnology in medicine and is being integrated into diagnostic and therapeutic tools to manage an array of medical conditions. On the other hand, personalized medicine, which is also referred to as precision medicine, is a novel concept that aims to individualize/customize therapeutic management based on the personal attributes of the patient to overcome blanket treatment that is only efficient in a subset of patients, leaving others with either ineffective treatment or treatment that results in significant toxicity. Novel nanomedicines have been employed in the treatment of several diseases, which can be adapted to each patient-specific case according to their genetic profiles. In this review, we discuss both areas and the intersection between the two emerging scientific domains. The review focuses on the current situation in personalized medicine, the advantages that can be offered by nanomedicine to personalized medicine, and the application of nanoconstructs in the diagnosis of genetic variability that can identify the right drug for the right patient. Finally, we touch upon the challenges in both fields towards the translation of nano-personalized medicine.
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Raballo, A. "Diagnostic Procedures for Prediction of Psychosis - Achievements and Challenges". European Psychiatry 41, S1 (abril de 2017): S27. http://dx.doi.org/10.1016/j.eurpsy.2017.01.139.
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Individualized prognostic predictions in people at clinical high risk are crucial to tailor suitable interventions and personalized prevention. Furthermore, in recent years, the synergy between fast-pace technical sophistication in neuroscience (e.g. neuroimaging and neurophysiological) and novel bio-statistical tools (e.g. machine learning algorithms) has accelerated the development of more inclusive predictive models and magnified the potential for such individualized risk stratification enriching classical psychopathological tools. However, the clinical translation of such research insights is still circumscribed and, despite incremental optimization of assessment tools, increasingly accepted criteria to characterize at risk mental states and tumultuous advance in the field, the prediction of psychosis at such individual level remains a not fully accomplished target.Disclosure of interestThe author has not supplied his declaration of competing interest.
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Antunes, Nina, Banani Kundu, Subhas C. Kundu, Rui L. Reis e Vítor Correlo. "In Vitro Cancer Models: A Closer Look at Limitations on Translation". Bioengineering 9, n.º 4 (7 de abril de 2022): 166. http://dx.doi.org/10.3390/bioengineering9040166.
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In vitro cancer models are envisioned as high-throughput screening platforms for potential new therapeutic discovery and/or validation. They also serve as tools to achieve personalized treatment strategies or real-time monitoring of disease propagation, providing effective treatments to patients. To battle the fatality of metastatic cancers, the development and commercialization of predictive and robust preclinical in vitro cancer models are of urgent need. In the past decades, the translation of cancer research from 2D to 3D platforms and the development of diverse in vitro cancer models have been well elaborated in an enormous number of reviews. However, the meagre clinical success rate of cancer therapeutics urges the critical introspection of currently available preclinical platforms, including patents, to hasten the development of precision medicine and commercialization of in vitro cancer models. Hence, the present article critically reflects the difficulty of translating cancer therapeutics from discovery to adoption and commercialization in the light of in vitro cancer models as predictive tools. The state of the art of in vitro cancer models is discussed first, followed by identifying the limitations of bench-to-bedside transition. This review tries to establish compatibility between the current findings and obstacles and indicates future directions to accelerate the market penetration, considering the niche market.
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Chen, Xiaoxian. "Research on the Application of Artificial Intelligence in Translation Courses". International Journal of Education and Humanities 12, n.º 1 (15 de janeiro de 2024): 41–44. http://dx.doi.org/10.54097/3c1b8w36.
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With the rapid development of artificial intelligence technology, its application in the field of education is more and more extensive. This paper aims to deeply explore the application of artificial intelligence in translation courses, analyze its advantages, application models, problems and solutions, and forecast the future research direction and development trend. First of all, this paper gives a comprehensive overview of artificial intelligence technology, and elaborates its definition, classification and development history in depth. Then, in light of the problems and challenges of traditional translation courses, this paper focuses on the advantages of AI application in translation courses, including improving the accuracy and efficiency of translation and providing personalized learning support. At the same time, this paper also introduces the application mode and practice of artificial intelligence in translation courses in detail, including the principle and function of intelligent translation tools, case analysis of translation course design based on artificial intelligence technology. When discussing the problems faced in the application and solving strategies, this paper deeply analyzes the technical limitations and defects, the change of teacher's role and students' learning mode, and puts forward a series of feasible solving strategies. Finally, the practical value of artificial intelligence in translation courses is summarized, and the future research direction and development trend are prospected.
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Gomes, Clarissa, Bence Ágg, Andrejaana Andova, Serdal Arslan, Andrew Baker, Monika Barteková, Dimitris Beis et al. "Catalyzing Transcriptomics Research in Cardiovascular Disease: The CardioRNA COST Action CA17129". Non-Coding RNA 5, n.º 2 (29 de março de 2019): 31. http://dx.doi.org/10.3390/ncrna5020031.
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Cardiovascular disease (CVD) remains the leading cause of death worldwide and, despite continuous advances, better diagnostic and prognostic tools, as well as therapy, are needed. The human transcriptome, which is the set of all RNA produced in a cell, is much more complex than previously thought and the lack of dialogue between researchers and industrials and consensus on guidelines to generate data make it harder to compare and reproduce results. This European Cooperation in Science and Technology (COST) Action aims to accelerate the understanding of transcriptomics in CVD and further the translation of experimental data into usable applications to improve personalized medicine in this field by creating an interdisciplinary network. It aims to provide opportunities for collaboration between stakeholders from complementary backgrounds, allowing the functions of different RNAs and their interactions to be more rapidly deciphered in the cardiovascular context for translation into the clinic, thus fostering personalized medicine and meeting a current public health challenge. Thus, this Action will advance studies on cardiovascular transcriptomics, generate innovative projects, and consolidate the leadership of European research groups in the field.COST (European Cooperation in Science and Technology) is a funding organization for research and innovation networks (www.cost.eu).
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Daneshdoust, Danyal, Ming Yin, Mingjue Luo, Debasish Sundi, Yongjun Dang, Cheryl Lee, Jenny Li e Xuefeng Liu. "Conditional Reprogramming Modeling of Bladder Cancer for Clinical Translation". Cells 12, n.º 13 (24 de junho de 2023): 1714. http://dx.doi.org/10.3390/cells12131714.
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The use of advanced preclinical models has become increasingly important in drug development. This is particularly relevant in bladder cancer, where the global burden of disease is quite high based on prevalence and a relatively high rate of lethality. Predictive tools to select patients who will be responsive to invasive or morbid therapies (chemotherapy, radiotherapy, immunotherapy, and/or surgery) are largely absent. Patient-derived and clinically relevant models including patient-derived xenografts (PDX), organoids, and conditional reprogramming (CR) of cell cultures efficiently generate numerous models and are being used in both basic and translational cancer biology. These CR cells (CRCs) can be reprogrammed to maintain a highly proliferative state and reproduce the genomic and histological characteristics of the parental tissue. Therefore, CR technology may be a clinically relevant model to test and predict drug sensitivity, conduct gene profile analysis and xenograft research, and undertake personalized medicine. This review discusses studies that have utilized CR technology to conduct bladder cancer research.
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Gkioka, Vasiliki, Olga Balaoura, Maria Goulielmaki e Constantin N. Baxevanis. "The Organization of Contemporary Biobanks for Translational Cancer Research". Onco 3, n.º 4 (22 de setembro de 2023): 205–16. http://dx.doi.org/10.3390/onco3040015.
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Cancer biobanks have a crucial role in moving forward the field of translational cancer research and, therefore, have been promoted as indispensable tools for advancing basic biomedical research to preclinical and clinical research, ultimately leading to the design of clinical trials. Consequently, they play an essential role in the establishment of personalized oncology by combining biological data with registries of detailed medical records. The availability of complete electronic medical reports from individualized patients has led to personalized approaches for diagnosis, prognosis, and prediction. To this end, identifying risk factors at early time points is important for designing more effective treatments unique for each patient. Under this aspect, biobanking is essential for accomplishing improvements in the field of precision oncology via the discovery of biomarkers related to cellular and molecular pathways regulating oncogenic signaling. In general terms, biological samples are thought to reflect the patient’s disease biology, but under certain conditions, these may also represent responses to various biological stresses. Divergent collection, handling, and storage methods may significantly change biosamples’ inherent biological properties. The alteration or loss of biological traits post-collection would lead to the discovery of nonreliable biomarkers and, consequently, to irreproducible results, thus constituting a formidable obstacle regarding the successful translation of preclinical research to clinical approaches. Therefore, a necessary prerequisite for successful biobanking is that the stored biological samples retain their biological characteristics unchanged. The application of quality standards for biospecimen collection and storage could be useful for generating encouraging preclinical data leading to the successful translation to clinical treatment approaches. Herein, we aim to comprehensively review the issues linked to biobank implementation for promoting cancer research.
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Glas, Gerrit. "Translatie als filosofisch programma". Algemeen Nederlands Tijdschrift voor Wijsbegeerte 111, n.º 3 (1 de outubro de 2019): 453–76. http://dx.doi.org/10.5117/antw2019.3.009.glas.
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Abstract Translation as philosophical program: An explorative reviewWhat does the concept of translation mean in the expression ‘translational neuroscience’? What are the different steps, or components, in the translation of neuroscientific findings to psychiatry? There are serious concerns about the validity and productivity of the traditional idea of a translational pipeline, starting in the fundamental sciences (chemistry, molecular and cellular biology) and ending in the practice of clinical medicine, including psychiatry. The article defends the thesis that the difficulties in the traditional approach result, at least partially, from insufficient reflection on the philosophical premises upon which the concept of translation is based. The linear pipeline model is strongly determined by the traditional biomedical approach to disease. The translation crisis signifies some of the limitations of this approach, especially in the realm of clinical practice and patient experience. The biomedical model suggests that illness manifestations should be conceived as causally determined expressions of an underlying biological derailment or dysfunction. This model lacks the language and conceptual tools to address the role of contextual and person-bound factors in the manifestation of illness. It is only recently that personalized and context-sensitive approaches to psychopathology have gained scientific attention. In the wake of this conceptual and practical reform, network-like approaches to translation have emerged. These network approaches are based on a different conception of transdisciplinarity. They address all stakeholders, by asking them what kind of translation they need. Stakeholders are not only scientists and clinicians, but also patient- and family support groups; and parties that are responsible for the institutional embedding, the financial and logistic infrastructure, and the legal frameworks that support psychiatric care. It is the interaction between science (as producer of knowledge) and the contexts that are supposed to benefit from this knowledge, that should be put at the centre of conceptual reflection. The degree and fruitfulness of this interaction will be decisive for the future of both psychiatry and clinical neuroscience. Philosophy can play an important role in this interaction, by making explicit underlying logical and practical tensions and ambiguities in this interaction.
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Soualmia, L. F., e T. Lecroq. "Managing Large-Scale Genomic Datasets and Translation into Clinical Practice". Yearbook of Medical Informatics 23, n.º 01 (agosto de 2014): 212–14. http://dx.doi.org/10.15265/iy-2014-0039.
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Summary Objective:To summarize excellent current research in the field of Bioinformatics and Translational Informatics with application in the health domain. Method: We provide a synopsis of the articles selected for the IMIA Yearbook 2014, from which we attempt to derive a synthetic overview of current and future activities in the field. A first step of selection was performed by querying MEDLINE with a list of MeSH descriptors completed by a list of terms adapted to the section. Each section editor evaluated independently the set of 1,851 articles and 15 articles were retained for peer-review. Results: The selection and evaluation process of this Yearbook’s section on Bioinformatics and Translational Informatics yielded three excellent articles regarding data management and genome medicine. In the first article, the authors present VEST (Variant Effect Scoring Tool) which is a supervised machine learning tool for prioritizing variants found in exome sequencing projects that are more likely involved in human Mendelian diseases. In the second article, the authors show how to infer surnames of male individuals by crossing anonymous publicly available genomic data from the Y chromosome and public genealogy data banks. The third article presents a statistical framework called iCluster+ that can perform pattern discovery in integrated cancer genomic data. This framework was able to determine different tumor subtypes in colon cancer. Conclusions: The current research activities still attest the continuous convergence of Bioinformatics and Medical Informatics, with a focus this year on large-scale biological, genomic, and Electronic Health Records data. Indeed, there is a need for powerful tools for managing and interpreting complex data, but also a need for user-friendly tools developed for the clinicians in their daily practice. All the recent research and development efforts are contributing to the challenge of impacting clinically the results and even going towards a personalized medicine in the near future.
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Ahmad Zawawi, Sahira Syamimi, Elyn Amiela Salleh e Marahaini Musa. "Spheroids and organoids derived from colorectal cancer as tools for in vitro drug screening". Exploration of Targeted Anti-tumor Therapy 5, n.º 2 (25 de abril de 2024): 409–31. http://dx.doi.org/10.37349/etat.2024.00226.
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Colorectal cancer (CRC) is a heterogeneous disease. Conventional two-dimensional (2D) culture employing cell lines was developed to study the molecular properties of CRC in vitro. Although these cell lines which are isolated from the tumor niche in which cancer develop, the translation to human model such as studying drug response is often hindered by the inability of cell lines to recapture original tumor features and the lack of heterogeneous clinical tumors represented by this 2D model, differed from in vivo condition. These limitations which may be overcome by utilizing three-dimensional (3D) culture consisting of spheroids and organoids. Over the past decade, great advancements have been made in optimizing culture method to establish spheroids and organoids of solid tumors including of CRC for multiple purposes including drug screening and establishing personalized medicine. These structures have been proven to be versatile and robust models to study CRC progression and deciphering its heterogeneity. This review will describe on advances in 3D culture technology and the application as well as the challenges of CRC-derived spheroids and organoids as a mode to screen for anticancer drugs.
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Simeon, Michael, Seema Dangwal, Agapios Sachinidis e Michael Doss. "Application of the Pluripotent Stem Cells and Genomics in Cardiovascular Research—What We Have Learnt and Not Learnt until Now". Cells 10, n.º 11 (10 de novembro de 2021): 3112. http://dx.doi.org/10.3390/cells10113112.
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Personalized regenerative medicine and biomedical research have been galvanized and revolutionized by human pluripotent stem cells in combination with recent advances in genomics, artificial intelligence, and genome engineering. More recently, we have witnessed the unprecedented breakthrough life-saving translation of mRNA-based vaccines for COVID-19 to contain the global pandemic and the investment in billions of US dollars in space exploration projects and the blooming space-tourism industry fueled by the latest reusable space vessels. Now, it is time to examine where the translation of pluripotent stem cell research stands currently, which has been touted for more than the last two decades to cure and treat millions of patients with severe debilitating degenerative diseases and tissue injuries. This review attempts to highlight the accomplishments of pluripotent stem cell research together with cutting-edge genomics and genome editing tools and, also, the promises that have still not been transformed into clinical applications, with cardiovascular research as a case example. This review also brings to our attention the scientific and socioeconomic challenges that need to be effectively addressed to see the full potential of pluripotent stem cells at the clinical bedside.
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Orozco, Gisela. "Fine mapping with epigenetic information and 3D structure". Seminars in Immunopathology 44, n.º 1 (janeiro de 2022): 115–25. http://dx.doi.org/10.1007/s00281-021-00906-4.
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AbstractSince 2005, thousands of genome-wide association studies (GWAS) have been published, identifying hundreds of thousands of genetic variants that increase risk of complex traits such as autoimmune diseases. This wealth of data has the potential to improve patient care, through personalized medicine and the identification of novel drug targets. However, the potential of GWAS for clinical translation has not been fully achieved yet, due to the fact that the functional interpretation of risk variants and the identification of causal variants and genes are challenging. The past decade has seen the development of great advances that are facilitating the overcoming of these limitations, by utilizing a plethora of genomics and epigenomics tools to map and characterize regulatory elements and chromatin interactions, which can be used to fine map GWAS loci, and advance our understanding of the biological mechanisms that cause disease.
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Arbitrio, Mariamena, Maria Teresa Di Martino, Francesca Scionti, Vito Barbieri, Licia Pensabene e Pierosandro Tagliaferri. "Pharmacogenomic Profiling of ADME Gene Variants: Current Challenges and Validation Perspectives". High-Throughput 7, n.º 4 (18 de dezembro de 2018): 40. http://dx.doi.org/10.3390/ht7040040.
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In the past decades, many efforts have been made to individualize medical treatments, taking into account molecular profiles and the individual genetic background. The development of molecularly targeted drugs and immunotherapy have revolutionized medical treatments but the inter-patient variability in the anti-tumor drug pharmacokinetics (PK) and pharmacodynamics can be explained, at least in part, by genetic variations in genes encoding drug metabolizing enzymes and transporters (ADME) or in genes encoding drug receptors. Here, we focus on high-throughput technologies applied for PK screening for the identification of predictive biomarkers of efficacy or toxicity in cancer treatment, whose application in clinical practice could promote personalized treatments tailored on individual’s genetic make-up. Pharmacogenomic tools have been implemented and the clinical utility of pharmacogenetic screening could increase safety in patients for the identification of drug metabolism-related biomarkers for a personalized medicine. Although pharmacogenomic studies were performed in adult cohorts, pharmacogenetic pediatric research has yielded promising results. Additionally, we discuss the current challenges and theoretical bases for the implementation of pharmacogenetic tests for translation in the clinical practice taking into account that pharmacogenomics platforms are discovery oriented and must open the way for the setting of robust tests suitable for daily practice.
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Wu, Jingtian. "Algorithmic Composition of Music Utilizing the Digits of Pi". Highlights in Science, Engineering and Technology 85 (13 de março de 2024): 570–77. http://dx.doi.org/10.54097/s4abkh66.
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As a matter of fact, algorithmic composition, the fusion of computational methods with music creation, has a rich history dating back to Pythagoras. On this basis, this paper explores the innovative intersection of mathematics, algorithms, and music, focusing on the translation of Pi's digits into a musical composition. Through a combination of manual and automated techniques, the research successfully crafts a melody using the minor pentatonic scale and traditional Chinese instruments, enriched by an algorithmically generated counter-melody. According to the analysis, the study reveals both the potential and limitations of this approach, with the fixed nature of the accompaniment and strict adherence to the pentatonic scale constraining musical diversity. Nevertheless, the research offers a novel perspective on mathematical representation in music, contributing to the broader field of algorithmic music composition. The findings open new avenues for personalized music creation, educational tools, and artistic exploration, highlighting the limitless possibilities when art and science converge.
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Olabisi Oluwakemi Adeleye, Chima Abimbola Eden e Idowu Sulaimon Adeniyi. "Innovative teaching methodologies in the era of artificial intelligence: A review of inclusive educational practices". World Journal of Advanced Engineering Technology and Sciences 11, n.º 2 (30 de março de 2024): 069–79. http://dx.doi.org/10.30574/wjaets.2024.11.2.0091.
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Artificial intelligence (AI) is revolutionizing the field of education, offering new opportunities to enhance learning experiences and promote inclusive educational practices. This review explores the impact of AI on teaching methodologies and its role in creating inclusive learning environments. By examining current research and practices, this review highlights the potential of AI to address diverse learning needs and promote equity in education.The review begins by discussing the role of AI in personalized learning, where AI algorithms analyze student data to provide tailored instruction and feedback. This approach allows educators to cater to individual learning styles and preferences, ensuring that all students have access to high-quality education. Additionally, AI-driven adaptive learning systems can identify and address learning gaps, providing targeted interventions to support students who may be struggling. Furthermore, the review explores the use of AI in facilitating collaborative learning environments, where students work together on projects and tasks. AI technologies can enhance collaboration by providing tools for communication, coordination, and knowledge sharing. This approach promotes inclusivity by allowing students to contribute their unique perspectives and skills to group projects. The review also discusses the potential of AI in promoting accessibility and inclusivity for students with disabilities. AI-powered assistive technologies can provide additional support and accommodations, allowing students with disabilities to fully participate in educational activities. Additionally, AI-driven captioning and translation tools can improve accessibility for students who are deaf or hard of hearing, as well as those who speak languages other than the primary language of instruction. Overall, this review highlights the transformative potential of AI in education and its ability to promote inclusive educational practices. By leveraging AI technologies, educators can create more personalized, collaborative, and accessible learning environments, ensuring that all students have the opportunity to succeed.
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Onaciu, Anca, Raluca Munteanu, Vlad Cristian Munteanu, Diana Gulei, Lajos Raduly, Richard-Ionut Feder, Radu Pirlog et al. "Spontaneous and Induced Animal Models for Cancer Research". Diagnostics 10, n.º 9 (31 de agosto de 2020): 660. http://dx.doi.org/10.3390/diagnostics10090660.
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Considering the complexity of the current framework in oncology, the relevance of animal models in biomedical research is critical in light of the capacity to produce valuable data with clinical translation. The laboratory mouse is the most common animal model used in cancer research due to its high adaptation to different environments, genetic variability, and physiological similarities with humans. Beginning with spontaneous mutations arising in mice colonies that allow for pursuing studies of specific pathological conditions, this area of in vivo research has significantly evolved, now capable of generating humanized mice models encompassing the human immune system in biological correlation with human tumor xenografts. Moreover, the era of genetic engineering, especially of the hijacking CRISPR/Cas9 technique, offers powerful tools in designing and developing various mouse strains. Within this article, we will cover the principal mouse models used in oncology research, beginning with behavioral science of animals vs. humans, and continuing on with genetically engineered mice, microsurgical-induced cancer models, and avatar mouse models for personalized cancer therapy. Moreover, the area of spontaneous large animal models for cancer research will be briefly presented.
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Tosca, Elena M., Davide Ronchi, Daniele Facciolo e Paolo Magni. "Replacement, Reduction, and Refinement of Animal Experiments in Anticancer Drug Development: The Contribution of 3D In Vitro Cancer Models in the Drug Efficacy Assessment". Biomedicines 11, n.º 4 (30 de março de 2023): 1058. http://dx.doi.org/10.3390/biomedicines11041058.
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In the last decades three-dimensional (3D) in vitro cancer models have been proposed as a bridge between bidimensional (2D) cell cultures and in vivo animal models, the gold standards in the preclinical assessment of anticancer drug efficacy. 3D in vitro cancer models can be generated through a multitude of techniques, from both immortalized cancer cell lines and primary patient-derived tumor tissue. Among them, spheroids and organoids represent the most versatile and promising models, as they faithfully recapitulate the complexity and heterogeneity of human cancers. Although their recent applications include drug screening programs and personalized medicine, 3D in vitro cancer models have not yet been established as preclinical tools for studying anticancer drug efficacy and supporting preclinical-to-clinical translation, which remains mainly based on animal experimentation. In this review, we describe the state-of-the-art of 3D in vitro cancer models for the efficacy evaluation of anticancer agents, focusing on their potential contribution to replace, reduce and refine animal experimentations, highlighting their strength and weakness, and discussing possible perspectives to overcome current challenges.
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Zheng, Rui, Aochun Wu, Jiyue Li, Zhengfang Tang, Junping Zhang, Mingli Zhang e Zheng Wei. "Progress and Outlook on Electrochemical Sensing of Lung Cancer Biomarkers". Molecules 29, n.º 13 (2 de julho de 2024): 3156. http://dx.doi.org/10.3390/molecules29133156.
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Electrochemical biosensors have emerged as powerful tools for the ultrasensitive detection of lung cancer biomarkers like carcinoembryonic antigen (CEA), neuron-specific enolase (NSE), and alpha fetoprotein (AFP). This review comprehensively discusses the progress and potential of nanocomposite-based electrochemical biosensors for early lung cancer diagnosis and prognosis. By integrating nanomaterials like graphene, metal nanoparticles, and conducting polymers, these sensors have achieved clinically relevant detection limits in the fg/mL to pg/mL range. We highlight the key role of nanomaterial functionalization in enhancing sensitivity, specificity, and antifouling properties. This review also examines challenges related to reproducibility and clinical translation, emphasizing the need for standardization of fabrication protocols and robust validation studies. With the rapid growth in understanding lung cancer biomarkers and innovations in sensor design, nanocomposite electrochemical biosensors hold immense potential for point-of-care lung cancer screening and personalized therapy guidance. Realizing this goal will require strategic collaboration among material scientists, engineers, and clinicians to address technical and practical hurdles. Overall, this work provides valuable insight for developing next-generation smart diagnostic devices to combat the high mortality of lung cancer.
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Rivero-Hinojosa, Samuel, Melanie Grant, Aswini Panigrahi, Huizhen Zhang, Veronika Caisova, Catherine Bollard e Brian Rood. "IMMU-15. PROTEOGENOMIC DISCOVERY OF NOVEL TUMOR PEPTIDES AS NEOANTIGENS FOR PERSONALIZED T CELL IMMUNOTHERAPY IN MEDULLOBLASTOMA". Neuro-Oncology 22, Supplement_3 (1 de dezembro de 2020): iii362—iii363. http://dx.doi.org/10.1093/neuonc/noaa222.371.
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Abstract T cell immunotherapies are promising new tools to combat high-risk subgroups of medulloblastoma without increasing the late effects burden. The ideal target antigen of an effective antitumor T-cell response is abundantly expressed by tumor cells but not by normal tissues, in order to limit off-target effects. Tumors translate a host of highly novel transcripts that are the result of aberrations in tumor DNA and the unmasking of alternative or novel exons. We developed a novel proteogenomic approach to identify tumor-restricted peptides and used them to select and expand T cells capable of mounting a tumor-specific cytotoxic immune response. Using RNA-seq and WGS data, we created personalized custom searchable databases containing predicted novel proteins from somatic mutations, novel junctions and fusion transcripts from 56 medulloblastoma tumors. By searching these databases with raw mass spectrometry data from paired medulloblastoma tumors, we identified tens of neoantigen peptides arising from the translation of tumor-specific transcripts; novel isoforms being the predominant source. We tested these peptides for their ability to select and expand autologous polyclonal populations of T cells and tested the immunogenicity of each individual peptide. Flow cytometry revealed populations of CD4+ and CD8+ cells with an activation profile marked by IFN-γ and TNF-α. Immunosuppressive marker profiles were also characterized. Using cytotoxicity assays, we demonstrated that tumor specific T cells can eliminate neoantigen bearing tumor cells. Thus, proteogenomics can identify immunogenic tumor specific peptides that can be used to create a personalized, targeted T cell therapy for children with high risk medulloblastoma.
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Choi, Bernard C. K., e Douglas G. Manuel. "The Canadian Health Clock and health calculators". Canadian Journal of Public Health 111, n.º 5 (14 de julho de 2020): 726–36. http://dx.doi.org/10.17269/s41997-020-00348-9.
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Abstract Setting This paper documents a participatory process of Health Portfolio staff in the design of a clock, and announces the 2020 Canadian Health Clock, with links to numerous online health calculators. The clock is part of the Health Portfolio’s celebration activities in 2019 of “100 Years of Health”, as the Department of Health was established in Canada in 1919. Intervention The intervention was the development of a clock on the Government of Canada website with linkage to calculators as a health promotion tool. The clock was built on the concept of the 2004 Chronic Disease Clock, which shows the number of deaths so far today, and so far this year. The clock was developed using a consultative approach, following a review of the original clock. Outcomes The 2020 clock incorporates new data visualization concepts. New features, facilitated by improved technology, include: expansion to all causes of death; blinking red dots to enhance visual impact; and three clock versions (analogue, featuring a moving circle; digital, table format; and graphical, bar chart format). The clock also provides links to a number of health calculators, to allow people to seek personalized information to improve their health. Implications The online health clock and health calculators are good examples of innovation in health risk communication tools for effective knowledge translation and dissemination. They inform people about health statistics (clock) and their health (calculators). The clock engages people in the context of the Canadian population, whereas the calculators provide personalized information about improving an individual’s future health.
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Sulimanov, Rushan, Konstantin Koshelev, Vladimir Makarov, Alexandre Mezentsev, Mikhail Durymanov, Lilian Ismail, Komal Zahid, Yegor Rumyantsev e Ilya Laskov. "Mathematical Modeling of Non-Small-Cell Lung Cancer Biology through the Experimental Data on Cell Composition and Growth of Patient-Derived Organoids". Life 13, n.º 11 (20 de novembro de 2023): 2228. http://dx.doi.org/10.3390/life13112228.
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Mathematical models of non-small-cell lung cancer are powerful tools that use clinical and experimental data to describe various aspects of tumorigenesis. The developed algorithms capture phenotypic changes in the tumor and predict changes in tumor behavior, drug resistance, and clinical outcomes of anti-cancer therapy. The aim of this study was to propose a mathematical model that predicts the changes in the cellular composition of patient-derived tumor organoids over time with a perspective of translation of these results to the parental tumor, and therefore to possible clinical course and outcomes for the patient. Using the data on specific biomarkers of cancer cells (PD-L1), tumor-associated macrophages (CD206), natural killer cells (CD8), and fibroblasts (αSMA) as input, we proposed a model that accurately predicts the cellular composition of patient-derived tumor organoids at a desired time point. Combining the obtained results with “omics” approaches will improve our understanding of the nature of non-small-cell lung cancer. Moreover, their implementation into clinical practice will facilitate a decision-making process on treatment strategy and develop a new personalized approach in anti-cancer therapy.
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Ospina-Pinillos, Laura, Tracey Davenport, Antonio Mendoza Diaz, Alvaro Navarro-Mancilla, Elizabeth M. Scott e Ian B. Hickie. "Using Participatory Design Methodologies to Co-Design and Culturally Adapt the Spanish Version of the Mental Health eClinic: Qualitative Study". Journal of Medical Internet Research 21, n.º 8 (2 de agosto de 2019): e14127. http://dx.doi.org/10.2196/14127.
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Background The Mental Health eClinic (MHeC) aims to deliver best-practice clinical services to young people experiencing mental health problems by making clinical care accessible, affordable, and available to young people whenever and wherever they need it most. The original MHeC consists of home page with a visible triage system for those requiring urgent help; a online physical and mental health self-report assessment; a results dashboard; a booking and videoconferencing system; and the generation of a personalized well-being plan. Populations who do not speak English and reside in English-speaking countries are less likely to receive mental health care. In Australia, international students have been identified as disadvantaged compared with their peers; have weaker social support networks; and have higher rates of psychological distress. This scenario is acquiring significant relevance as Spanish-speaking migration is rapidly growing in Australia, and the mental health services for culturally and linguistically diverse populations are limited. Having a Spanish version (MHeC-S) of the Mental Health eClinic would greatly benefit these students. Objective We used participatory design methodologies with users (young people aged 16-30 years, supportive others, and health professionals) to (1) conduct workshops with users to co-design and culturally adapt the MHeC; (2) inform the development of the MHeC-S alpha prototype; (3) test the usability of the MHeC-S alpha prototype; (4) translate, culturally adapt, and face-validate the MHeC-S self-report assessment; and (5) collect information to inform its beta prototype. Methods A research and development cycle included several participatory design phases: co-design workshops; knowledge translation; language translation and cultural adaptation; and rapid prototyping and user testing of the MHeC-S alpha prototype. Results We held 2 co-design workshops with 17 users (10 young people, 7 health professionals). A total of 15 participated in the one-on-one user testing sessions (7 young people, 5 health professionals, 3 supportive others). We collected 225 source documents, and thematic analysis resulted in 5 main themes (help-seeking barriers, technology platform, functionality, content, and user interface). A random sample of 106 source documents analyzed by 2 independent raters revealed almost perfect agreement for functionality (kappa=.86; P<.001) and content (kappa=.92; P<.001) and substantial agreement for the user interface (kappa=.785; P<.001). In this random sample, no annotations were coded for help-seeking barriers or the technology platform. Language was identified as the main barrier to getting medical or psychological services, and smartphones were the most-used device to access the internet. Acceptability was adequate for the prototype’s 5 main elements: home page and triage system, self-report assessment, dashboard of results, booking and video visit system, and personalized well-being plan. The data also revealed gaps in the alpha prototype, such as the need for tailored assessment tools and a greater integration with Spanish-speaking services and communities. Spanish-language apps and e-tools, as well as online mental health information, were lacking. Conclusions Through a research and development process, we co-designed and culturally adapted, developed and user tested, and evaluated the MHeC-S. By translating and culturally adapting the MHeC to Spanish, we aimed to increase accessibility and availability of e-mental health care in the developing world, and assist vulnerable populations that have migrated to English-speaking countries.
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Wang, Liang, Akiko Maehara, Rui Lv, Xiaoya Guo, Jie Zheng, Kisten L. Billiar, Gary S. Mintz e Dalin Tang. "Image-Based Finite Element Modeling Approach for Characterizing In Vivo Mechanical Properties of Human Arteries". Journal of Functional Biomaterials 13, n.º 3 (11 de setembro de 2022): 147. http://dx.doi.org/10.3390/jfb13030147.
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Mechanical properties of the arterial walls could provide meaningful information for the diagnosis, management and treatment of cardiovascular diseases. Classically, various experimental approaches were conducted on dissected arterial tissues to obtain their stress–stretch relationship, which has limited value clinically. Therefore, there is a pressing need to obtain biomechanical behaviors of these vascular tissues in vivo for personalized treatment. This paper reviews the methods to quantify arterial mechanical properties in vivo. Among these methods, we emphasize a novel approach using image-based finite element models to iteratively determine the material properties of the arterial tissues. This approach has been successfully applied to arterial walls in various vascular beds. The mechanical properties obtained from the in vivo approach were compared to those from ex vivo experimental studies to investigate whether any discrepancy in material properties exists for both approaches. Arterial tissue stiffness values from in vivo studies generally were in the same magnitude as those from ex vivo studies, but with lower average values. Some methodological issues, including solution uniqueness and robustness; method validation; and model assumptions and limitations were discussed. Clinical applications of this approach were also addressed to highlight their potential in translation from research tools to cardiovascular disease management.
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Yuan, Phillip F., Tong Xiao e Pradeep Devadass. "Fabricating Complexity - A Performance Based Methodology through Parametric Optimization". Advanced Materials Research 889-890 (fevereiro de 2014): 1240–45. http://dx.doi.org/10.4028/www.scientific.net/amr.889-890.1240.
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This paper discusses the integration of advanced computational design and digital fabrication methods through the project Light-Vault, which addresses the development and execution of complex designs resulting in a performance based approach through optimization. The project shows the development of a vault which is made through an assemblage of customized multiple components, which are parametrically controlled and evaluated with respect to light and weight. Due to influence of multiple fitness parameters a genetic algorithm is created and new methodology is developed for the evolution of the form. Algorithms are developed to ensure design thinking and fabrication procedures are simultaneously developed in a non-linear, parallel performance based process. This logical approach investigates the various possibilities and optimizes the development and fabrication of ruled surfaces in the interior volume of the component using digital methods and translation of the form into reality using industrial robots for fabrication. In parallel, the project explores the potential of robotic technology and introduces innovations of personalized robotic tools, in generating quick shaping volumes through this process. The developed methodology is tested in creating multiple units of the vault which are analyzed against various evaluation criteria. This cumulative cohesive process between advanced digital and physical computation methods is translated through a full-scale built pavilion.
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Lyon, Aurore, Ana Mincholé, Juan Pablo Martínez, Pablo Laguna e Blanca Rodriguez. "Computational techniques for ECG analysis and interpretation in light of their contribution to medical advances". Journal of The Royal Society Interface 15, n.º 138 (janeiro de 2018): 20170821. http://dx.doi.org/10.1098/rsif.2017.0821.
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Widely developed for clinical screening, electrocardiogram (ECG) recordings capture the cardiac electrical activity from the body surface. ECG analysis can therefore be a crucial first step to help diagnose, understand and predict cardiovascular disorders responsible for 30% of deaths worldwide. Computational techniques, and more specifically machine learning techniques and computational modelling are powerful tools for classification, clustering and simulation, and they have recently been applied to address the analysis of medical data, especially ECG data. This review describes the computational methods in use for ECG analysis, with a focus on machine learning and 3D computer simulations, as well as their accuracy, clinical implications and contributions to medical advances. The first section focuses on heartbeat classification and the techniques developed to extract and classify abnormal from regular beats. The second section focuses on patient diagnosis from whole recordings, applied to different diseases. The third section presents real-time diagnosis and applications to wearable devices. The fourth section highlights the recent field of personalized ECG computer simulations and their interpretation. Finally, the discussion section outlines the challenges of ECG analysis and provides a critical assessment of the methods presented. The computational methods reported in this review are a strong asset for medical discoveries and their translation to the clinical world may lead to promising advances.
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Hanson, Brianna, Lauren Welch, Matthew Frese e Christina Gallo. "558. Innovative CME Tools in the Teaching of Evolving Strategies in the Management and Prevention of COVID-19". Open Forum Infectious Diseases 7, Supplement_1 (1 de outubro de 2020): S344. http://dx.doi.org/10.1093/ofid/ofaa439.752.
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Abstract Background In 2020, Med Learning Group (MLG) launched an interactive, multi-faceted educational initiative focusing on COVID-19. The innovative education & tools developed for FRONTLINE are publicly available for the entire healthcare community to use. Learners range from a variety of specialties, including infectious disease specialists, pulmonary medicine specialists, emergency room practitioners, advanced practitioners, nurses, & other healthcare professionals to help support them in their effort to optimize care of patients with COVID-19. MLG partnered with Health Resources & Services Administration, Project ECHO, Public Health Foundation & community, VA & academic centers to create a collaborative network with shared goals for education. Methods This initiative seeks to reach over 25,000 learners with innovative educational programs & tools to enhance the learning experience, facilitate continuous learning & support the translation of education into practice, & encourage HCP-patient dialogue: • COVID Community of Care Website/Application • COVID Frontline Update Podcast Series • Virtual/Live ECHO Series with 3D animations of pathophysiology • Enduring ECHO Module with Case Discussions • Quality Improvement Personalized Posters Results By September 2020, we will have the results from pre/posttests, intra-activity Q&A, evaluations, & 60- to 90-day follow-on assessments. We will evaluate learners’ changes in knowledge & competence, & reported practice changes. In addition, MLG will have feedback collected via surveys & interviews on the various point-of-care tools. Based off previous MLG educational initiatives, it is expected that learners will find value in the various tools available in this programming. Conclusion Advanced tools like virtual live learning platforms, mobile websites/apps, 3D animations & podcasts will prove to be an asset to the continuing education of HCPs treating patients with COVID-19. The outcomes are expected to demonstrate the extent to which HCPs have enhanced their ability to identify clinical predictors of disease severity of COVID-19 & apply current treatment guidelines, clinical trial data, & patient-specific factors to the management of patients with COVID-19. These results will be available in time to share via a poster at IDWeek 2020. Disclosures All Authors: No reported disclosures
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Elgarhy, Fadya M., Abdallah Borham, Noha Alziny, Khlood R. AbdElaal, Mahmoud Shuaib, Abobaker Salem Musaibah, Mohamed Ali Hussein e Anwar Abdelnaser. "From Drug Discovery to Drug Approval: A Comprehensive Review of the Pharmacogenomics Status Quo with a Special Focus on Egypt". Pharmaceuticals 17, n.º 7 (3 de julho de 2024): 881. http://dx.doi.org/10.3390/ph17070881.
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Pharmacogenomics (PGx) is the hope for the full optimization of drug therapy while minimizing the accompanying adverse drug events that cost billions of dollars annually. Since years before the century, it has been known that inter-individual variations contribute to differences in specific drug responses. It is the bridge to what is well-known today as “personalized medicine”. Addressing the drug’s pharmacokinetics and pharmacodynamics is one of the features of this science, owing to patient characteristics that vary on so many occasions. Mainly in the liver parenchymal cells, intricate interactions between the drug molecules and enzymes family of so-called “Cytochrome P450” occur which hugely affects how the body will react to the drug in terms of metabolism, efficacy, and safety. Single nucleotide polymorphisms, once validated for a transparent and credible clinical utility, can be used to guide and ensure the succession of the pharmacotherapy plan. Novel tools of pharmacoeconomics science are utilized extensively to assess cost-effective pharmacogenes preceding the translation to the bedside. Drug development and discovery incorporate a drug-gene perspective and save more resources. Regulations and laws shaping the clinical PGx practice can be misconceived; however, these pre-/post approval processes ensure the product’s safety and efficacy. National and international regulatory agencies seek guidance on maintaining conduct in PGx practice. In this patient-centric era, social and legal considerations manifest in a way that makes them unavoidable, involving patients and other stakeholders in a deliberate journey toward utmost patient well-being. In this comprehensive review, we contemporarily addressed the scientific leaps in PGx, along with various challenges that face the proper implementation of personalized medicine in Egypt. These informative insights were drawn to serve what the Egyptian population, in particular, would benefit from in terms of knowledge and know-how while maintaining the latest global trends. Moreover, this review is the first to discuss various modalities and challenges faced in Egypt regarding PGx, which we believe could be used as a pilot piece of literature for future studies locally, regionally, and internationally.
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Salwei, Megan, e Carrie Reale. "Lost in translation? Information exchange during breast cancer care and implications for technology design." Journal of Clinical Oncology 41, n.º 16_suppl (1 de junho de 2023): 1558. http://dx.doi.org/10.1200/jco.2023.41.16_suppl.1558.
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1558 Background: Almost 4 million women in the US have had breast cancer, with 300,000 women diagnosed each year. Treatment decision-making following breast cancer diagnosis can be challenging as there are often several clinically appropriate treatment options, each with differing impacts on patient short- and long-term quality of life. Further, patients must manage this information during a time of high emotional burden, which can hinder decision-making. Not surprisingly, studies have found that less than 50% of patients believe their treatment plan aligns with their preferences. Numerous decision aids have been developed to support patient decision-making. However, sustained use of decision aids is limited due to poor integration in clinical workflow. We need to better understand the complex workflows and needs of decision aid users - patients and breast cancer clinicians. In this study, we investigate the information exchange between patients and clinicians when making breast cancer treatment decisions and identify design requirements for patient-centered decision support tools. Methods: This study is part of a larger research project to design a COMputerized PAtient-centered Collaborative Technology (COMPACT) to support personalized breast cancer decision-making. We observed clinicians at one academic medical center’s breast center from February-August 2022. Participating clinicians were followed throughout their clinical shift. Using a tablet computer and smart pencil, we recorded all aspects of clinician workflow. Written notes were transcribed and uploaded into Dedoose. Two human factors researchers inductively coded each observation in a consensus-based process. Results: We observed 79 hours of clinical care and 119 patient encounters across 20 observations of various clinical roles. Overall, we found that patients with breast cancer must manage an enormous amount of highly complex information that includes technical medical terms, mathematical concepts (e.g., risk), and uncertainty. We identified over 20 distinct decisions that patients face during their cancer journey, which were interdependent and evolved over time. We identified numerous patient-specific factors that influenced treatment decision-making, such as the patient’s work and family circumstances. For instance, one patient was organizing a conference and needed to plan her surgery around this event. Patients were frequently asked to remember and relay information across members of the care team, indicating inadequate system support of information transfer within the large cancer team. Based on these findings, we identified design requirements for interventions to support care coordination and patient-centered decision-making. Conclusions: These findings can inform the design of interventions to support breast cancer decision-making and improve patient-centered cancer care.
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Laar, Ryan Van, Samuel King, Richard McCoy, Mirette Saad, Sian Fereday, Ingrid Winship, Catherine Uzzell e Anthony Landgren. "Translation of a circulating miRNA signature of melanoma into a solid tissue assay to improve diagnostic accuracy and precision". Biomarkers in Medicine 15, n.º 13 (setembro de 2021): 1111–22. http://dx.doi.org/10.2217/bmm-2021-0289.
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Aim: Successful treatment of cutaneous melanoma depends on early and accurate diagnosis of clinically suspicious melanocytic skin lesions. Multiple international studies have described the challenge of providing accurate and reproducible histopathological assessments of melanocytic lesions, highlighting the need for new diagnostic tools including disease-specific biomarkers. Previously, a 38-miRNA signature (MEL38) was identified in melanoma patient plasma and validated as a novel biomarker. In this study, MEL38 expression in solid tissue biopsies representing the benign nevi to metastatic melanoma spectrum is examined. Patients & methods: Nanostring digital gene expression assessment of the MEL38 signature was performed on 308 formalin-fixed paraffin-embedded biopsies of nevi, melanoma in situ and invasive melanoma. Genomic data were interrogated using hierarchical clustering, univariate and multivariate statistical approaches. Classification scores computed from the MEL38 signature were analyzed for their association with demographic data and histopathology results, including MPATH-DX class, AJCC disease stage and tissue subtype. Results: The MEL38 score can stratify higher-risk melanomas (MPATH-Dx class V or more advanced) from lower-risk skin lesions (class I–IV) with an area under the curve of 0.97 (p < 0.001). The genomic score ranges from 0 to 10 and is positively correlated with melanoma progression, with an intraclass correlation coefficient of 0.85 with stage 0–IV disease. Using an optimized classification threshold of ≥2.7 accurately identifies higher-risk melanomas with 89% sensitivity and 94% specificity. Multivariate analysis showed the score to be a significant predictor of malignancy, independent of technical and clinical covariates. Application of the MEL38 signature to Spitz nevi reveals an intrasubtype profile, with elements in common to both nevi and melanoma. Conclusion: Melanoma-specific circulating miRNAs maintain their association with malignancy when measured in the hypothesized tissue of origin. The MEL38 signature is an accurate and reproducible metric of melanoma status, based on changes in miRNA expression that occur as the disease develops and spreads. Inclusion of the MEL38 score into routine practice would provide physicians with previously unavailable, personalized genomic information about their patient’s skin lesions. Combining molecular biomarker data with conventional histopathology data may improve diagnostic accuracy, healthcare resource utilization and patient outcomes.
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Chaturvedi, Purnima, e Sapna Ratan Shah. "Assessing the Clinical Outcomes of Voxelotor Treatment in Patients with Sickle Cell Disease". International Journal of Applied Sciences and Biotechnology 12, n.º 1 (31 de março de 2024): 46–53. http://dx.doi.org/10.3126/ijasbt.v12i1.64057.
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The results of Voxelotor treatment in Sickle Cell Disease, as assessed through clinical outcomes, demonstrated its efficacy in reducing hemolysis and improving hemoglobin levels. This effect can be attributed to Voxelotor's inhibition of HbS polymerization, thereby restoring the deformability and compliance of sickle RBCs. Our mathematical model provided mechanistic insights into how altered rheological properties of sickle RBCs impact their flow dynamics in microcirculation. Specifically, we observed that Voxelotor-induced improvements in RBC deformability and compliance lead to enhanced plasma film height in capillaries, promoting smoother blood flow and reducing the risk of vaso-occlusive events. We established a direct relationship between the molecular mechanism of Voxelotor action and its clinical outcomes. The mathematical model served as a bridge, elucidating how Voxelotor-induced changes in sickle RBC mechanics translate to improved microcirculatory flow and reduced vaso-occlusion. This holistic understanding not only validates the therapeutic efficacy of Voxelotor but also underscores the importance of considering biomechanical factors in evaluating treatment outcomes in SCD. Furthermore, this study highlighted the relevance of microfluidics based diagnostic tools in assessing the efficacy of Voxelotor treatment. By leveraging insights from our mathematical model, microfluidics devices can be designed to mimic physiological conditions and effectively evaluate the deformability of sickle RBCs before and after treatment. This integrated approach not only facilitates the development of personalized therapeutic interventions but also accelerates the translation of novel treatments, such as Voxelotor, from preclinical studies to clinical practice for the management of Sickle Cell Disease. Int. J. Appl. Sci. Biotechnol. Vol 12(1): 46-53.
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Lee, Knoo, Suzette Bacon, Elizabeth Conrow, Elizabeth Curtis, Ashley Roberts e Blaine Reeder. "PRAGMATIC, SUSTAINABLE, AND COST-FEASIBLE TECHNOLOGIES TO ENABLE REMOTE CARE COORDINATION SERVICES". Innovation in Aging 7, Supplement_1 (1 de dezembro de 2023): 97. http://dx.doi.org/10.1093/geroni/igad104.0314.
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Abstract The aim of this presentation is to communicate the approach and lessons learned in successfully deploying open source smart home and consumer-grade technologies to enable novel remote care coordination services for older adults as part of the CMS-funded ASSETs for Aging in Place demonstration project. Major barriers to use of technologies that enable service reach to rural or home-bound at-risk populations are technology availability, internet connectivity, cost, configuration, installation, ease of management, and usability and usefulness of clinically relevant data displays for decision-making to support personalized care coordination, coaching, and self-management goals. We have pioneered a reusable, innovative approach and infrastructure through partnership with the State of Missouri Department of Social Services and a non-profit hosting partner that facilitates testing and deployment of such remote services with broad goals of scalability and translation as starting principles. The specific focus of this presentation will describe technology selection, configuration, proof-of-concept testing, use of mobile hot spots to overcome broadband availability in rural areas, team composition and skills, introduction and training of the OT/Nurse/Social Worker teams to technology, resources required to stand up the team and transition to independent technology expertise in the field with mobile, video, and remote messaging tools, and user-centered design engagement of the care coordination and informatics teams to drive dashboard features and visual display developments for new work flows. An overview of the approach, technologies, and practical considerations to support research and development of new technology-enabled services for older adults will be presented.
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Linz, Dominik, Sander Verheule, Aaron Isaacs e Ulrich Schotten. "Considerations for the Assessment of Substrates, Genetics and Risk Factors in Patients with Atrial Fibrillation". Arrhythmia & Electrophysiology Review 10, n.º 3 (27 de outubro de 2021): 132–39. http://dx.doi.org/10.15420/aer.2020.51.
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Successful translation of research focussing on atrial arrhythmogenic mechanisms has potential to provide a mechanism-tailored classification and to support personalised treatment approaches in patients with AF. The clinical uptake and clinical implementation of new diagnostic techniques and treatment strategies require translational research approaches on various levels. Diagnostic translation involves the development of clinical diagnostic tools. Additionally, multidisciplinary teams are required for collaborative translation to describe genetic mechanisms, molecular pathways, electrophysiological characteristics and concomitant risk factors. In this article, current approaches for AF substrate characterisation, analysis of genes potentially involved in AF and strategies for AF risk factor assessment are summarised. The authors discuss challenges and obstacles to clinical translation and implementation into clinical practice.
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Pavelić, Krešimir, Tamara Martinović e Sandra Kraljević Pavelić. "Translational and Personalized Medicine". Medicine, Law & Society 8, n.º 1 (15 de outubro de 2015): 25–33. http://dx.doi.org/10.18690/8.25-33(2015).
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The idea behind personalized medicine is to tailor health care to an individual’s unique genetic makeup. Hitherto, “one size fits all” approach was used in medicine. With the rise of personal medicine, we are moving towards a more precise, predictable and powerful medicine that is customized for each individual patient. To allow for an improvement in the acceleration and efficacy of drug development, high-throughput methods (“omics”) are rapidly being developed. This leads to understanding of multiple factors that are involved in disease progress on an individual level. In order to analyze the great amount of data that is collected from such experiments, one has to turn to systems biology, an interdisciplinary science that studies complex interactions within a biological system. Finally, translational medicine comes into play, by “translating” the information gathered from research into diagnostic tools, medicines and policies, with the final goal of improving individuals’ health. Personalized medicine is one of the future, and it will revolutionize the current practice of diagnosis-based medicine, once fully developed.
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Hijazi, Assia, Carlo Bifulco, Pamela Baldin e Jérôme Galon. "Digital Pathology for Better Clinical Practice". Cancers 16, n.º 9 (26 de abril de 2024): 1686. http://dx.doi.org/10.3390/cancers16091686.
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(1) Background: Digital pathology (DP) is transforming the landscape of clinical practice, offering a revolutionary approach to traditional pathology analysis and diagnosis. (2) Methods: This innovative technology involves the digitization of traditional glass slides which enables pathologists to access, analyze, and share high-resolution whole-slide images (WSI) of tissue specimens in a digital format. By integrating cutting-edge imaging technology with advanced software, DP promises to enhance clinical practice in numerous ways. DP not only improves quality assurance and standardization but also allows remote collaboration among experts for a more accurate diagnosis. Artificial intelligence (AI) in pathology significantly improves cancer diagnosis, classification, and prognosis by automating various tasks. It also enhances the spatial analysis of tumor microenvironment (TME) and enables the discovery of new biomarkers, advancing their translation for therapeutic applications. (3) Results: The AI-driven immune assays, Immunoscore (IS) and Immunoscore-Immune Checkpoint (IS-IC), have emerged as powerful tools for improving cancer diagnosis, prognosis, and treatment selection by assessing the tumor immune contexture in cancer patients. Digital IS quantitative assessment performed on hematoxylin–eosin (H&E) and CD3+/CD8+ stained slides from colon cancer patients has proven to be more reproducible, concordant, and reliable than expert pathologists’ evaluation of immune response. Outperforming traditional staging systems, IS demonstrated robust potential to enhance treatment efficiency in clinical practice, ultimately advancing cancer patient care. Certainly, addressing the challenges DP has encountered is essential to ensure its successful integration into clinical guidelines and its implementation into clinical use. (4) Conclusion: The ongoing progress in DP holds the potential to revolutionize pathology practices, emphasizing the need to incorporate powerful AI technologies, including IS, into clinical settings to enhance personalized cancer therapy.
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Banu, S. Amitha, Khan Sharun, Merlin Mamachan, Laith Abualigah, Rohit Kumar, A. M. Pawde, Kuldeep Dhama, Swapan Kumar Maiti e Amarpal. "Wound Healing and Skin Regeneration: Present Status and Future Directions". Journal of Experimental Biology and Agricultural Sciences 11, n.º 6 (31 de dezembro de 2023): 871–83. http://dx.doi.org/10.18006/2023.11(6).871.883.
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Wound healing and skin regeneration involve intricate interactions between various cellular, molecular, and biochemical factors. This narrative review aims to provide an in-depth analysis of the present status of therapeutic strategies for wound healing and skin regeneration. The literature review was performed using the Google Scholar search engine with the help of relevant keywords. Selected publications were used to synthesize different sections of the narrative review. The quest for innovative therapeutic approaches to accelerate wound healing and enhance skin regeneration has led to remarkable advancements in recent years. The landscape of therapeutic approaches for wound healing and skin regeneration is evolving rapidly, driven by groundbreaking discoveries and interdisciplinary collaborations. From advanced wound dressings and growth factor therapies to stem cell-based interventions and gene editing techniques, the arsenal of tools at our disposal continues to expand. As researchers continue to unravel the intricate mechanisms underlying wound repair and regeneration, the potential for transformative therapies to revolutionize patient care remains immense. Through a combination of innovative technologies, personalized approaches, ethical considerations, and global accessibility, the future of wound healing holds promise for improving the lives of countless individuals worldwide. Despite significant advancements, several knowledge gaps persist in the field of wound healing and skin regeneration. Further elucidation of cellular and molecular mechanisms governing wound repair, inflammation resolution, and scar formation is warranted. Exploring the crosstalk between wound healing and the microbiome and the influence of ageing and systemic diseases will unravel new therapeutic targets and strategies. As researchers delve deeper into understanding the intricate mechanisms underlying wound repair, the development of novel therapies and their clinical translation become increasingly promising. With a multidisciplinary approach and ongoing advancements in technology, biology, and medicine, the future holds great potential for transforming the field of wound healing and skin regeneration.
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Ivanov, Andrey A., e Haian Fu. "Abstract 4275: Averon: informatics platform to discover Actionable Vulnerabilities Enabled by Rewired Oncogenic Networks". Cancer Research 83, n.º 7_Supplement (4 de abril de 2023): 4275. http://dx.doi.org/10.1158/1538-7445.am2023-4275.
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Abstract Missense mutations can change protein structure, cellular localization, and functions. Such changes lead to the rewiring of protein-protein interaction (PPI) networks, activation of oncogenic pathways, and acquisition of cancer hallmarks. However, the translation of the landscape of oncogenic mutations into clinically actionable biological models for cancer target discovery remains a major challenge. We address this challenge by leveraging the power of computational systems biology supported by high-throughput screening technologies. While some mutations can disrupt the PPIs, others may induce new PPIs that are not natural for the wild-type counterparts. Recently, we have established a quantitative High Throughput differential Screening (qHT-dS) platform [1] to discover such mutant-enabled or neomorph PPIs (neoPPIs). The screening of more than 13,000 mutant interactions revealed a landscape of gain-of-interactions encompassing both oncogenic and tumor suppressor mutations. This emerging neoPPI landscape may offer new mutant-directed therapeutic approaches for precision medicine. However, to infer clinically actionable mechanistic insights into how neoPPIs promote tumorigenesis special computational tools are needed. To inform the neoPPI-based target discovery, we develop a set of innovative informatics tools for discovering Actionable Vulnerabilities Enabled by Rewired Oncogenic Networks (Averon). Implemented in a widely-used Jupyter Notebook format, the Averon streamlines the identification of the oncogenic programs and clinically significant genes that are regulated by neoPPIs in cancer patients. The Averon can recapitulate well-established connectivity between known mutant-dependent PPIs and specific oncogenic pathways and reveal new, previously unknown mechanisms of neoPPI-mediated oncogenic signaling. To inform new therapeutic strategies in neoPPI-dependent cancers, Averon connects neoPPI-regulated genes with available approved drugs and clinical compounds. Together, the Averon provides a powerful informatics environment to determine therapeutically actionable vulnerabilities created by mutant-regulated protein-protein interactions to inform new personalized therapeutic strategies in cancer. Acknowledgments: This work was supported in part by NCI’s Informatics Technology for Cancer Research (ITCR) Program (R21CA274620, A.A.I.), Winship Cancer Institute #IRG-17-181-06 from the American Cancer Society (A.A.I.). Cancer Target Discovery and Development (CTD2) Network (U01CA217875, H.F.), NCI Emory Lung Cancer SPORE (P50CA217691, H.F.), Career Enhancement Program (A.A.I., P50CA217691), Winship Cancer Institute (NIH 5P30CA138292). References: 1. Mo X, et al., Systematic discovery of mutation-directed neo-protein-protein interactions in cancer. Cell. 2022, 185, 1974-1985. Citation Format: Andrey A. Ivanov, Haian Fu. Averon: informatics platform to discover Actionable Vulnerabilities Enabled by Rewired Oncogenic Networks. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4275.
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Arora, Kavisha, Nambirajan Sundaram, Michael Helmrath e Anjaparavanda P. Naren. "Mo1117: PATIENT PERSONALIZED TRANSLATIONAL TOOLS TO STUDY GI COMPLICATIONS IN CYSTIC FIBROSIS". Gastroenterology 162, n.º 7 (maio de 2022): S—704—S—705. http://dx.doi.org/10.1016/s0016-5085(22)61650-0.
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Кемерова, Н. С., e И. А. Матвеенко. "Development of engineering university students’ scientific and technical translation skills using POEM (Person-Oriented Engagement Model)". Пространство педагогических исследований, n.º 2(2) (16 de maio de 2024): 37–55. http://dx.doi.org/10.23859/3034-1760.2024.54.72.004.
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Инженеры являются специалистами по решению комплексных производственных проблем, им также необходим достаточный уровень коммуникативной компетенции в английском языке для использования новейшей информации и сотрудничества с коллегами по всему миру. Эффективная и всесторонняя профессиональная подготовка будущих инженеров позволит студентам приобрести навыки перевода, чтобы удовлетворить мировой спрос на конкурентоспособных специалистов, которые могут выполнять свои обязанности, применяя лучшие отечественные и зарубежные практики. Формирование и развитие умений перевода у студентов неязыкового вуза на достаточном уровне затруднено в связи с рядом проблем и противоречий: малое количество часов, выделяемых на языковую подготовку; низкий уровень владения иностранным языком у студентов и их учебной мотивации; недостаточность методологического и технологического обеспечения, а также ряд организационно-дидактических проблем. В настоящей статье рассматриваются нескольких ключевых подходов, связанных с существующими условиями и требованиями высшего профессионального образования, с учетом которых необходимо совершенствовать языковую подготовку. Решение обозначенных проблем в первую очередь требует пересмотра методологических подходов, актуализации содержательных компонентов, а также оптимизации условий и методов. Сложность решения переводческих задач обусловлена жесткими семантическими, семиотическими, историческими, социальными, психическими рамками, а точность передачи смысла текста-источника требует достаточный уровень владения языком и опытом переводческой практики в конкретной области, поэтому необходимы не только переводческие компетенции, но и формирование переводческой личности. Учитывая специфику неязыкового вуза, мы выделили ряд компонентов содержания, которые создают фундамент для дальнейшего развития переводческих умений студентов в самообразовательной и профессиональной деятельности при условии обеспечения необходимого уровня их вовлеченности в языковую практику и переводческую деятельность. Исследователями доказано, что чем выше показатели студенческой вовлеченности, тем лучше их успеваемость и удовлетворенность образовательным процессом. В статье представлена модель личностно-ориентированного вовлечения (Person-Oriented Engagement Model) и необходимые дидактические условия, реализуемые при обучении студентов-будущих инженеров умениям научно-технического перевода, которые обеспечивают повышение внутренней мотивации студентов, их активную и эффективную работу при выполнении учебных заданий, освоении теоретических основ и практике переводческой деятельности. Предлагаемая модель личностно-ориентированного вовлечения POEM (Person-Oriented Engagement Model) была спроектирована с учетом требований устойчивости и ресурсоэффективности к системе высшего политехнического образования и инженерной деятельности. Устойчивость отражает свойства личности, необходимые для успешного преодоления трудностей и соблюдения профессионально-этических и общечеловеческих норм, так как инженер имеет дело с объектами, которые могут представлять опасность жизни людей и окружающей среде. Ресурсная эффективность имеет конкретное применение к ряду целей устойчивого развития. В методологии и практике обучения иностранному языку и для развития умений перевода у студентов инженерных специальностей, ресурсоэффективность призвана помочь обучающимся приобрести компетенцию и опыт успешного решения проблем в учебной и профессиональноподобной деятельности. С одной стороны, ресурсоэффективность является неотъемлемым компонентом учебного плана и входит в содержание языковой подготовки, с другой стороны, ресурсоэффективное преподавание и обучение предполагает применение современных образовательных подходов для повышения качества и результативности обучения за счет эффективного использования различных ресурсов, доступных в академической среде. Мы определили систему взаимосвязанных групп ресурсов: учебно- методические, дидактико-технологические, инфокоммуникативные, контрольно- диагностические, организационно-педагогические. Одним из основных условий внедрения разработанной модели POEM является личностно- ориентированных подход, который предполагает раскрытие индивидуального потенциала обучающегося и всестороннее развитие личности в образовательном процессе. В процессе разработки нашей модели мы также опирались на научные достижения в области дидактики высшей школы, касающиеся подготовки специалистов инженерно-технических направлений, в соответствии с которыми были сформулированы ряд основных принципов и этапов внедрения разработанной моделидля эффективного развития переводческих умений студентов-будущих инженеров. В соответствии с методологией проектирования педагогических систем и моделей [Сериков В. В.] были определены следующие основные характеристики описываемой модели: личностно значимая цель и мотивы, обеспечивающие вовлеченность и достижения; личный карьерный портфель продуктов переводческой практики, который используется для мониторинга и оценки; программа обучения, отражающая индивидуальный способ обучения, личностный стиль, уровень вовлеченности, включая цели, задачи, этапы, формы и стратегии освоения персонифицированного контента, а также набор средств для оценки его эффективности; перевод – продукт, часть проекта и метод развития иноязычной компетенции, включая навыки перевода научно-технических текстов; усвоение знаний через применение в ходе выполнения собственных проектов, направленных на совершенствование умений целеполагания, планирования различных видов изучения языка, переводческой практики и деятельности. К основными принципам реализации данной модели относятся: субъектность, профессионализация, сотрудничество и сопровождение, персонификация и учет стилей личностной вовлеченности. Технология развития переводческих умений студентов происходит поэтапно, длительность и структура которых зависит от уровня и сложности конкретного проектного задания. Результаты нашего предварительного экспериментального исследования позволяют утверждать, что разработанная модель доказала свою эффективность в развитии у студентов коммуникативной компетенции, повышении уровня владения языком, необходимых для успешного выполнения научно-технического перевода текстов по инженерным специальностям. Engineers are specialists in solving complex production problems; they also require a sufficient level of communicative competence in the English language to access the latest information and collaborate with colleagues worldwide. Effective and comprehensive professional training for future engineers will enable students to acquire translation skills to meet the global demand for competitive professionals who can perform their duties using the best domestic and foreign practices. Developing translation skills among students of non-linguistic universities is hindered at a sufficient level due to several problems and contradictions: a small number of hours allocated for language learning; a low level of foreign language proficiency among students and their educational motivation; insufficient methodological and technological support, as well as a number of organizational and didactic problems. This article discusses several key approaches related to existing conditions and requirements of higher professional education, considering which language training needs to be improved. These problems primarily requires a revision of methodological approaches, updating substantive components, as well as optimizing conditions and methods. The complexity of solving translation tasks is determined by rigid semantic, semiotic, historical, social, and mental frameworks, and the accuracy of conveying the meaning of the source text requires a sufficient level of language proficiency and experience in translation practice in a specific area. Thus, not only translation competencies but also the formation of a translator's personality is seen as a very important issue. Taking into account the specificity of a non-linguistic university, we have identified a number of content components that lay the foundation for further development of students' translation skills in self-education and professional activities, provided that they are sufficiently engaged in language practice and translation activities. The research has shown that the higher the indicators of student engagement, the better their academic performance and satisfaction with the educational process. The article presents the Person-Oriented Engagement Model (POEM) and the necessary didactic conditions implemented in the future engineers training in scientific and technical translation skills. These conditions facilitate an increase in students' internal motivation, their active and effective work in completing educational tasks, mastering theoretical foundations, and practicing translation activities. The proposed POEM was designed basing on resilience and resource efficiency requirements within the system of higher polytechnic education and engineering practice. Resilience is a character trait necessary for successfully overcoming difficulties and adhering to professional and ethical norms, as engineers deal with objects that may pose risks to human life and the environment. Resource efficiency has specific application to a range of sustainable development goals. In the methodology and practice of teaching foreign languages and developing translation skills for engineering students, resource efficiency aims at helping learners acquire competence and experience in successfully solving problems in educational and professional activities. On one hand, resource efficiency is an integral component of the curriculum and is part of the language training content. On the other hand, resource-efficient teaching and learning involve the application of modern educational approaches to enhance the quality and effectiveness of education by efficiently utilizing various resources available in the academic environment. We have identified a system of interconnected groups of resources: educational-methodical, didactic-technological, info- communicative, control-diagnostic, and organizational-pedagogical. One of the main conditions for implementing the developed POEM model is a person-centered approach, which involves revealing individual potential of a student and comprehensive personality development in the educational process. In developing our model, we also relied on scientific achievements in the field of higher education didactics related to the training of engineering specialists. Based on these achievements, a series of principles and stages were formulated for implementing the model for the effective development of translation skills among future engineers. In accordance with the methodology of designing educational systems and models [Serikov V.V.], the following main characteristics of the described model have been identified: personally meaningful goals and motives of engagement and achievements; a personal career portfolio of translation practice products used for monitoring and evaluation; a training program accounting for individual learning style, personal involvement level, including goals, tasks, stages, forms, and strategies of mastering personalized content, as well as a set of tools for assessing its effectiveness; translation as a product, part of the project and a method for developing foreign language competence, including translation skills of scientific and technical texts; acquisition of knowledge through application in projects aimed at improving goal-setting skills, planning various language learning methods, translation practice. The main principles of implementing this model include subjectivity, professionalization, collaboration and support, personalization, and personal involvement. The development of students' translation skills occurs in stages, the duration and structure of which depend on the level and complexity of the specific project task. The results of our preliminary experimental research allow us to state that the developed model has proven its effectiveness in developing students' communicative competence, enhancing language proficiency levels necessary for successful scientific and technical translation of texts in engineering specialties.
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Regan, K., e P. R. O. Payne. "From Molecules to Patients: The Clinical Applications of Translational Bioinformatics". Yearbook of Medical Informatics 24, n.º 01 (agosto de 2015): 164–69. http://dx.doi.org/10.15265/iy-2015-005.
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Summary Objective: In order to realize the promise of personalized medicine, Translational Bioinformatics (TBI) research will need to continue to address implementation issues across the clinical spectrum. In this review, we aim to evaluate the expanding field of TBI towards clinical applications, and define common themes and current gaps in order to motivate future research. Methods: Here we present the state-of-the-art of clinical implementation of TBI-based tools and resources. Our thematic analyses of a targeted literature search of recent TBI-related articles ranged across topics in genomics, data management, hypothesis generation, molecular epidemiology, diagnostics, therapeutics and personalized medicine. Results: Open areas of clinically-relevant TBI research identified in this review include developing data standards and best practices, publicly available resources, integrative systems-level approaches, user-friendly tools for clinical support, cloud computing solutions, emerging technologies and means to address pressing legal, ethical and social issues. Conclusions: There is a need for further research bridging the gap from foundational TBI-based theories and methodologies to clinical implementation. We have organized the topic themes presented in this review into four conceptual foci – domain analyses, knowledge engineering, computational architectures and computation methods alongside three stages of knowledge development in order to orient future TBI efforts to accelerate the goals of personalized medicine.
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Welch, Lauren, e Russie Allen. "How Can You Use Newer Therapies to Improve Clinical Decision-Making and Long-Term Health Outcomes for Patients with Chronic Lymphocytic Leukemia Acute Myeloid Leukemia?" Blood 142, Supplement 1 (28 de novembro de 2023): 7321. http://dx.doi.org/10.1182/blood-2023-189832.
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The Catalyst initiative, developed by Med Learning Group in 2019 with continued grant support year-on year, is a comprehensive continuing medical education platform that provides innovative methods to increase HCPs' competence surrounding essential aspects of CLL and AML management, with a specific focus on molecular testing, therapy selection, and the combination of established and emerging treatments. By equipping healthcare professionals with up-to-date knowledge and skills, the Catalyst initiative empowers them to make informed decisions that lead to improved patient outcomes. The Catalyst website (www.Catalyst-HM.com) includes HCP- and patient-facing and serves as a validated platform for the latest guidelines and research on CLL and AML. There have been over 16500 views of the website since its launch in 2019. Learners also have access to a variety of accredited educational programs and tools, such as downloadable animations illustrating the value of molecular testing and how to use results to guide treatment choice and a Personalized Poster Portal where learners can choose a variety of images for a poster that is sent to their practice setting. In 2021/2022, these live and online programs have educated over 10000 HCPs Learners have particularly appreciated the innovative nature of the CATALYST Initiative, with 98% indicating the VR animations included in a variety of programming improved their learning experience and knowledge retention (N=2997). At the last two ASH annual meetings, learners could participate in the CATALYST VR Room, a digital version of which can be viewed here: https://catalyst-hm.com/virtualbooth/. Please view footage and attitudinal feedback from learners here. The proposed poster would review the gains in knowledge and competence among CATALYST learners longitudinally from 2019 - 2022, demonstrating the value of this community in helping to advance the translation of the latest science to practice behavior. As demonstrated in the figure below (Please see figure 1), in 2022 hematologists / oncologists increased their ability to apply treatment best practices in newly diagnosed and R/R AML by 28%, and their ability to individualize selection of therapies for treatment-naïve and R/R CLL based on disease- and patient-specific factors 31% (N=2953). While these are significant gains, baseline pre/posttest scores in the sixtieth percentile among specialists suggest these are important areas for continued focus. The CATALYST program has also had a significant impact on learners' practice, based on 60- and 90-day follow-on assessments (n=113). 87% of respondents indicate they now actively use strategies and tools to address adverse events in the treatment of CLL or AML with all or most of their patients. Additionally, 79% indicated increased incorporation of patient and disease-specific factors when treating newly diagnosed or relapsed/refractory AML patients. Over the last four years, the Catalyst initiative has helped the oncology/hematology multidisciplinary team increase their ability to utilize molecular and genetic features as well as patient characteristics to design individualized management plans to enhance patient outcomes. The proposed poster will describe CATALYST offerings and demonstrate its impact on HCPs' ability to translate the latest data and guidelines to practice for their patients with AML and CLL.
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Popescu, Diana, Dan Lăptoiu e Anton Hadăr. "Intelligent Collaborative Platform for Development of Personalized Surgical Orthopedic Guides". Key Engineering Materials 638 (março de 2015): 303–9. http://dx.doi.org/10.4028/www.scientific.net/kem.638.303.
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Currently, the processes of developing new medical devices (in particular, patient specific guides for orthopedic surgery being of interest in our research), is hampered by the difficulty of correctly and efficiently quantifying and translating the specific medical requirements in terms of technical specifications. This is caused by the intrinsic difficulty of the demarche, but also by a complicated communication between surgeon and engineer given the different practical and research perspectives, specific constraints, motivation, evaluation criteria and professional language barrier. The advent and development of new technologies with applications in the medical field, such as robotics, haptic-based virtual and augmented reality, additive manufacturing, collaborative modeling, knowledge-based support decision systems, etc., make now possible to bridge the gap between surgeons’ ideas and needs and their practical materialization into new customized medical devices. The paper enrolls in this research trend, presenting a general framework for the development of an intelligent e-health platform, which provides in a collaborative environment the necessary knowledge and computer-aided tools for translating surgeons’ needs into technical specifications for the design and manufacturing of patient-specific guides for orthopedic surgery. These guides can be used in the minimally invasive surgical procedures and for reducing the x-ray radiation exposure during surgery, and for increasing accuracy in performing different types of specific orthopedic surgical procedures such as cutting, drilling, tapping and aligning, by transferring the tools trajectories from computer-aided planning to surgery.
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Gambari, Roberto. "The Role of OMICS Research in Understanding Phenotype Variation in Thalassaemia: The THALAMOSS Project". Thalassemia Reports 4, n.º 3 (4 de dezembro de 2014): 4877. http://dx.doi.org/10.4081/thal.2014.4877.
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The β-thalassaemias are a group of severe and rare anaemias with monogenic inheritance, a complex systemic phenotype and several treatment-related complications, caused by more than 300 mutations of the β-globin gene. Novel therapeutic protocols, most of which are based on still experimental treatments, show great promise but significant variability of success between patients. These strategies include chemical/molecular induction of the endogenous β-like γ-globin gene or the restoration of clinically relevant β-globin levels by gene therapy. A small number of modifiers with significant impact on disease penetrance, severity and efficacy of treatments are known, but most remain elusive. Improvements of existing treatment regimens and optimization and application of novel treatments will critically depend on the characterization of additional disease modifiers and the stratification of patients for customized treatment regimens. This requires extensive analyses based on “OMICS”, an English-language neologism which refer to different but connected fields in molecular biology and biochemistry, such as genomics, transcriptomics, exomics, proteomics, metabolomics. The major objective of OMICS is a collective characterization of pools of biological molecules (gene sequences, transcripts, proteins and protein domains) controlling biological structures, functions and dynamics, including several involved in pathological conditions. One of the most interesting observations of genomics in β-thalassaemias is the association between genomic sequences and high fetal haemoglobin (HbF) levels, in consideration of the fact that high HbF levels are usually associated with milder forms of β-thalassaemia. Related to this issue, is the possibility to predict response to different therapeutic protocols on the basis of genomic analyses. For instance, three major loci (Xmn1-HBG2 single nucleotide polymorphism, HBS1L-MYB intergenic region on chromosome 6q, and BCL11A) contribute to high HbF production. Pharmacogenomic analysis of the effects of hydroxyurea (HU) on HbF production in a collection of β-thalassemia and sickle cell disease (SCD) patients allowed the identification of genomic signatures associated with high HbF. Therefore, it can hypothesized that genomic studies might predict the response of patients to treatments based on hydroxyurea, which is at present the most used HbF inducer in pharmacological therapy of β-thalassaemia. Transcriptomic/proteomic studies allowed to identify the zinc finger transcription factor B-cell lymphoma/leukemia 11A (BCL11A) as the major repressor of HbF expression. The field of research on g-globin gene repressors (including BCL11A) is of top interest, since several approaches can lead to pharmacologically-mediated inhibition of the expression of g-globin gene repressors, leading to gglobin gene activation. Among these strategies, we underline direct targeting of the transcription factors by aptamers or decoy molecules, as well as inhibition of the mRNA coding g-globin gene repressors with shRNAs, antisense molecules, peptide nucleic acids (PNAs) and microRNAs. In this respect, the THALAMOSS FP7 Project (THALAssaemia MOdular Stratification System for personalized therapy of β-thalassemia, www.thalamoss.eu) aims develop a universal sets of markers and techniques for stratification of β-thalassaemia patients into treatment subgroups for (a) onset and frequency of blood transfusions, (b) choice of iron chelation, (c) induction of fetal hemoglobin, (d) prospective efficacy of gene-therapy. The impact of THALAMOSS is the provision of novel biomarkers for distinct treatment subgroups in β-thalassaemia (500–1000 samples from participating medical centres), identified by combined genomics, proteomics, transcriptomics and tissue culture assays, the development of new or improved products for the cell isolation, characterization and treatment of β-thalassaemia patients and the establishment of routine techniques for detection of these markers and stratification of patients into treatment groups. Translation of these activities into the product portfolio and R&D methodology of participating SMEs will be a major boost for them as well as for the field. THALAMOSS tools and technologies will (a) facilitate identification of novel diagnostic tests, drugs and treatments specific to patient subgroups and (b) guide conventional and novel therapeutic approaches for β-thalassaemia, including personalized medical treatments.
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Perlis, Roy H. "Pharmacogenomic Testing and Personalized Treatment of Depression". Clinical Chemistry 60, n.º 1 (1 de janeiro de 2014): 53–59. http://dx.doi.org/10.1373/clinchem.2013.204446.
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Abstract BACKGROUND There is wide variation in antidepressant efficacy and tolerability during the treatment of major depressive disorder, a brain disease associated with significant morbidity and mortality risk. The ability to rapidly identify optimal treatment, thereby shortening the time to symptomatic remission, could reduce these risks and associated costs. CONTENT Up to 42% of variance in antidepressant response is associated with common genetic variation, and there are over 10 psychotropic medications for which the US Food and Drug Administration–approved labeling reflects a genetic test. Most published studies have examined functional variations in genes of the cytochrome p450 system, relevant to metabolism of many antidepressants. However, there are few data supporting the clinical usefulness of specific pharmacogenetic tests. Randomized trials and cost-effectiveness studies are emerging, but larger-scale studies are needed. Specific challenges in translating genetic association results to clinical practice include need for replication to address risk of type I error, overestimation of effect sizes, absence of data from generalizable cohorts, and absence of comparative data that would suggest one specific intervention over another. Several opportunities to accelerate development and validation of new tools for stratification remain, including integration of these tests with clinical data or other biomarkers and application of electronic health records for test development and investigation. SUMMARY Although common genetic variation, particularly in genes of the cytochrome p450 system, has been associated with antidepressant response, evidence that this variation may be successfully applied to guide treatment selection is just emerging. Larger-scale studies facilitated by informatics tools will clarify the usefulness of such tests.
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Joachim, Anais, Emilie Maturin, Marielle Mello, Lilia Hadjem, Magali Grange, Olivier Deas, Ana Zarubica et al. "Abstract 86: Deep immuno-profiling of syngeneic tumor mouse models for preclinical studies". Cancer Research 84, n.º 6_Supplement (22 de março de 2024): 86. http://dx.doi.org/10.1158/1538-7445.am2024-86.
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Abstract The identification of the major cellular players involved in the progression of a type of cancer is a key step for the success of new immunotherapies for personalized medicine. Immune cells play critical functions in cancer, and mice with intact immune systems are vital to understanding tumor immunology. It is however a daunting challenge as complex relationships interplay between tumor cells and the immune system. Each component of innate immunity or adaptive immunity, such as T lymphocytes, macrophages or neutrophils, may be directed to a pro- or anti-tumor function. In order to cope with the complexity of the tumor microenvironment, it is necessary to use an experimental approach capable of characterizing the heterogeneity of the cell types present in the tumor, the evolution of their relative proportion and their fine-tuned functional specificity. This approach leads to the identification of new cellular biomarkers of different stages of tumor progression in order to identify new targets for therapeutic time-window of and improve cancer diagnosis To decipher the impact of immunotherapy treatments involved in the anti-tumor response, cellular phenotyping of leukocytes infiltrating a tumor but also those present in peripheral organs is necessary. Essentially based on extracellular labeling, this primary screen aims to quantify the different cell populations present in a syngenic tumor models on B6/N or BalbC genetical backgrounds. In order to increase our understanding in the precise mode of action of anti-PD1 treatment at the cellular level in sensitive and unsensitive models, we investigated immunophenotypes and responses to immune checkpoint inhibitor (ICI) of several hallmark syngeneic tumor models (MC38, CT26, B16F10, B16-OVA, RENCA, EMT6) in immunocompetent mouse models by flow and mass cytometry. We compared growth kinetics and profiled the immune cell composition of tumor microenvironment (TME), draining lymph node (dLN) and blood in order to establish immune-phenotypic cell signatures that correlates with treatment efficacy. Supervised, unsupervised and integrative data analysis as well as visualization tools are used to identify significant changes across different experimental settings. Our results indicate that each model possesses a unique tumor-immune infiltrate profile that can be modulated with immunotherapies. Overall, these studies provide an important resource of highly-characterized syngeneic tumor model and highlight the importance of tumor immune landscape variance across models that will drive selecting the most appropriate model to test novel immunotherapeutic agents and enhance our translation of knowledge from syngeneic models to human tumors. Citation Format: Anais Joachim, Emilie Maturin, Marielle Mello, Lilia Hadjem, Magali Grange, Olivier Deas, Ana Zarubica, Bernard Malissen, Hervé Luche, François Romagne, Stéphanie Blanchin. Deep immuno-profiling of syngeneic tumor mouse models for preclinical studies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 86.