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Добірка наукової літератури з теми "TRANSLATIONAL BIOMEDICAL SCIENCES"

Автор: Grafiati
Опубліковано: 11 березня 2023

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Статті в журналах з теми "TRANSLATIONAL BIOMEDICAL SCIENCES"

1

Ackerman, Sara L., Katherine Weatherford Darling, Sandra Soo-Jin Lee, Robert A. Hiatt, and Janet K. Shim. "The Ethics of Translational Science: Imagining Public Benefit in Gene-Environment Interaction Research." Engaging Science, Technology, and Society 3 (June 29, 2017): 351. http://dx.doi.org/10.17351/ests2017.152.

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Анотація:
Biomedical research is increasingly informed by expectations of “translation,” which call for the production of scientific knowledge that can be used to create services and products that improve health outcomes. In this paper, we ask how translation, in particular the idea of social responsibility, is understood and enacted in the post-genomic life sciences. Drawing on theories examining what constitutes “good science,” and interviews with 35 investigators who study the role of gene-environment interactions in the etiology of cancer, diabetes, and cardiovascular disease, we describe the dynamic and unsettled ethics of translational science through which the expected social value of scientific knowledge about complex disease causation is negotiated. To describe how this ethics is formed, we first discuss the politics of knowledge production in interdisciplinary research collectives. Researchers described a commitment to working across disciplines to examine a wide range of possible causes of disease, but they also pointed to persistent disciplinary and ontological divisions that rest on the dominance of molecular conceptions of disease risk. The privileging of molecular-level causation shapes and constrains the kinds of knowledge that can be created about gene-environment interactions. We then turn to scientists’ ideas about how this knowledge should be used, including personalized prevention strategies, targeted therapeutics, and public policy interventions. Consensus about the relative value of these anticipated translations was elusive, and many scientists agreed that gene-environment interaction research is part of a shift in biomedical research away from considering important social, economic, political and historical causes of disease and disease disparities. We conclude by urging more explicit engagement with questions about the ethics of translational science in the post-genomic life sciences. This would include a consideration of who will benefit from emerging scientific knowledge, how benefits will accrue, and the ways in which normative assumptions about the public good come to be embedded in scientific objects and procedures.
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2

Engebretsen, Eivind, Gina Fraas Henrichsen, and John Ødemark. "Towards a translational medical humanities: introducing the cultural crossings of care." Medical Humanities 46, no. 2 (April 27, 2020): e2-e2. http://dx.doi.org/10.1136/medhum-2019-011751.

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In this introductory essay, we will present a translational medical humanities approach where the humanities are not only an auxiliary to medical science and practice, but also an interdisciplinary space where both medicine and the humanities mutually challenge and inform each other. First, we explore how medicine’s attempt to tackle the nature–culture divide is emblematically expressed in the concept and practice of knowledge translation (hereinafter KT). Second, we compare and contrast KT as an epistemic ideology and a socio-medical practice, with concepts and practices of translation developed in the human sciences. In particular, we emphasise Derrida’s understanding of translation as inherent in all meaning making, as a fundamentally textual process and as a process necessarily creating difference rather than semantic equivalence. Finally, we analyse a case from clinical medicine showing how a more refined notion of translation can enlighten the interaction between biomedical and cultural factors. Such a translational medical humanities approach also requires a rethinking of the concept of evidence in medicine.
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3

Haynes, Brittany, Kyle Brimacombe, Christy Hare, and Jessica Faupel-Badger. "The National Center for Advancing Translational Sciences’ Intramural Training Program and Fellow Career Outcomes." CBE—Life Sciences Education 19, no. 4 (December 2020): ar51. http://dx.doi.org/10.1187/cbe.20-03-0048.

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Анотація:
The translational scientist skill sets are consistent with those currently being emphasized in biomedical research to prepare trainees for various career options. The framework of the National Center for Advancing Translational Sciences intramural research program and the career outcomes of its alumni will be of interest to those involved in the career preparedness of early-career scientists.
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4

Gouripeddi, Ram, Danielle Groat, Samir E. Abdelrahman, Tom Cheatham, Mollie Cummins, Karen Eilbeck, Bernie LaSalle, Katherine Sward, and Julio C. Facelli. "3339 Development of a Competency-based Informatics Course for Translational Researchers." Journal of Clinical and Translational Science 3, s1 (March 2019): 66–67. http://dx.doi.org/10.1017/cts.2019.156.

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Анотація:
OBJECTIVES/SPECIFIC AIMS: Translational researchers often require the use of informatics methods in their work. Lack of an understanding of key informatics principles and methods limits the abilities of translational researchers to successfully implement Findable, Accessible, Interoperable, Reusable (FAIR) principles in grant proposal submissions and performed studies. In this study we describe our work in addressing this limitation in the workforce by developing a competency-based, modular course in informatics to meet the needs of diverse translational researchers. METHODS/STUDY POPULATION: We established a Translational Research Informatics Education Collaborative (TRIEC) consisting of faculty at the University of Utah (UU) with different primary expertise in informatics methods, and working in different tiers of the translational spectrum. The TRIEC, in collaboration with the Foundation of Workforce Development of the Utah Center for Clinical and Translational Science (CCTS), gathered informatics needs of early investigators by consolidating requests for informatics services, assistance provided in grant writing, and consultations. We then reviewed existing courses and literature for informatics courses that focused on clinical and translational researchers [3–9]. Using the structure and content of the identified courses, we developed an initial draft of a syllabus for a Translational Research Informatics (TRI) course which included key informatics topics to be covered and learning activities, and iteratively refined it through discussions. The course was approved by the UU Department of Biomedical Informatics, UU Graduate School and the CCTS. RESULTS/ANTICIPATED RESULTS: The TRI course introduces informatics PhD students, clinicians, and public health practitioners who have a demonstrated interest in research, to fundamental principles and tools of informatics. At the completion of the course, students will be able to describe and identify informatics tools and methods relevant to translational research and demonstrate inter-professional collaboration in the development of a research proposal addressing a relevant translational science question that utilizes the state-of-the-art in informatics. TRI covers a diverse set of informatics content presented as modules: genomics and bioinformatics, electronic health records, exposomics, microbiomics, molecular methods, data integration and fusion, metadata management, semantics, software architectures, mobile computing, sensors, recruitment, community engagement, secure computing environments, data mining, machine learning, deep learning, artificial intelligence and data science, open source informatics tools and platforms, research reproducibility, and uncertainty quantification. The teaching methods for TRI include (1) modular didactic learning consisting of presentations and readings and face-to-face discussions of the content, (2) student presentations of informatics literature relevant to their final project, and (3) a final project consisting of the development, critique and chalk talk and formal presentations of informatics methods and/or aims of an National Institutes of Health style K or R grant proposal. For (3), the student presents their translational research proposal concept at the beginning of the course, and works with members of the TRIEC with corresponding expertise. The final course grade is a combination of the final project, paper presentations and class participation. We offered TRI to a first cohort of students in the Fall semester of 2018. DISCUSSION/SIGNIFICANCE OF IMPACT: Translational research informatics is a sub-domain of biomedical informatics that applies and develops informatics theory and methods for translational research. TRI covers a diverse set of informatics topics that are applicable across the translational spectrum. It covers both didactic material and hands-on experience in using the material in grant proposals and research studies. TRI’s course content, teaching methodology and learning activities enable students to initially learn factual informatics knowledge and skills for translational research correspond to the ‘Remember, Understand, and Apply’ levels of the Bloom’s taxonomy [10]. The final project provides opportunity for applying these informatics concepts corresponding to the ‘Analyze, Evaluate, and Create’ levels of the Bloom’s taxonomy [10]. This inter-professional, competency-based, modular course will develop an informatics-enabled workforce trained in using state-of-the-art informatics solutions, increasing the effectiveness of translational science and precision medicine, and promoting FAIR principles in research data management and processes. Future work includes opening the course to all Clinical and Translational Science Award hubs and publishing the course material as a reference book. While student evaluations for the first cohort will be available end of the semester, true evaluation of TRI will be the number of trainees taking the course and successful grant proposal submissions. References: 1. Wilkinson MD, Dumontier M, et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci Data. 2016 Mar 15. 2. National Center for Advancing Translational Sciences. Translational Science Spectrum. National Center for Advancing Translational Sciences. 2015 [cited 2018 Nov 15]. Available from: https://ncats.nih.gov/translation/spectrum 3. Hu H, Mural RJ, Liebman MN. Biomedical Informatics in Translational Research. 1 edition. Boston: Artech House; 2008. 264 p. 4. Payne PRO, Embi PJ, Niland J. Foundational biomedical informatics research in the clinical and translational science era: a call to action. J Am Med Inform Assoc JAMIA. 2010;17(6):615–6. 5. Payne PRO, Embi PJ, editors. Translational Informatics: Realizing the Promise of Knowledge-Driven Healthcare. Softcover reprint of the original 1st ed. 2015 edition. Springer; 2016. 196 p. 6. Richesson R, Andrews J, editors. Clinical Research Informatics. 2nd ed. Springer International Publishing; 2019. (Health Informatics). 7. Robertson D, MD GHW, editors. Clinical and Translational Science: Principles of Human Research. 2 edition. Amsterdam: Academic Press; 2017. 808 p. 8. Shen B, Tang H, Jiang X, editors. Translational Biomedical Informatics: A Precision Medicine Perspective. Softcover reprint of the original 1st ed. 2016 edition. S.l.: Springer; 2018. 340 p. 9. Valenta AL, Meagher EA, Tachinardi U, Starren J. Core informatics competencies for clinical and translational scientists: what do our customers and collaborators need to know? J Am Med Inform Assoc. 2016 Jul 1;23(4):835–9. 10. Anderson LW, Krathwohl DR, Airasian PW, Cruikshank KA, Mayer RE, Pintrich PR, Raths J, Wittrock MC. A Taxonomy for Learning, Teaching, and Assessing: A Revision of Bloom’s Taxonomy of Educational Objectives, Abridged Edition. 1 edition. New York: Pearson; 2000.
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5

Hutchins, B. Ian, Matthew T. Davis, Rebecca A. Meseroll, and George M. Santangelo. "Predicting translational progress in biomedical research." PLOS Biology 17, no. 10 (October 10, 2019): e3000416. http://dx.doi.org/10.1371/journal.pbio.3000416.

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6

Bano, Rahmat, Sushma Gupta, and Chander Shekhar. "Translational research in biomedical sciences in India: Challenges, observations & national perspectives." Indian Journal of Medical Research 152, no. 4 (2020): 335. http://dx.doi.org/10.4103/ijmr.ijmr_1296_19.

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7

Bezerra, Italla Maria Pinheiro. "Translational medicine and its contribution to public health." Journal of Human Growth and Development 27, no. 1 (April 13, 2017): 6. http://dx.doi.org/10.7322/jhgd.127642.

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Анотація:
Translational medicine is a new paradigm that propitiates the transfer of knowledge built in the experimental laboratory to clinical practice and correlates with the field of Public Health, although there are still challenges. However, several professionals from different fields of knowledge, from researchers and managers of health care area as well as students of the exact sciences, have been conducting research with this focus, from the knowledge generated in the biomedical laboratories or not, correlating to those produced in basic and applied sciences, focusing on the improvement of health services.
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8

Bodenreider, O., and A. Burgun. "Accessing and Integrating Data and Knowledge for Biomedical Research." Yearbook of Medical Informatics 17, no. 01 (August 2008): 91–101. http://dx.doi.org/10.1055/s-0038-1638588.

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Summary Objectives To review the issues that have arisen with the advent of translational research in terms of integration of data and knowledge, and survey current efforts to address these issues. MethodsUsing examples form the biomedical literature, we identified new trends in biomedical research and their impact on bioinformatics. We analyzed the requirements for effective knowledge repositories and studied issues in the integration of biomedical knowledge. Results New diagnostic and therapeutic approaches based on gene expression patterns have brought about new issues in the statistical analysis of data, and new workflows are needed are needed to support translational research. Interoperable data repositories based on standard annotations, infrastructures and services are needed to support the pooling and meta-analysis of data, as well as their comparison to earlier experiments. High-quality, integrated ontologies and knowledge bases serve as a source of prior knowledge used in combination with traditional data mining techniques and contribute to the development of more effective data analysis strategies. Conclusion As biomedical research evolves from traditional clinical and biological investigations towards omics sciences and translational research, specific needs have emerged, including integrating data collected in research studies with patient clinical data, linking omics knowledge with medical knowledge, modeling the molecular basis of diseases, and developing tools that support in-depth analysis of research data. As such, translational research illustrates the need to bridge the gap between bioinformatics and medical informatics, and opens new avenues for biomedical informatics research.
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9

Paul, Mari. "Translational investigators: life sciences' application engineers." Nature Biotechnology 25, no. 7 (July 2007): 817–18. http://dx.doi.org/10.1038/nbt0707-817.

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CHANCE, BRITTON, and SHOKO NIOKA. "HISTORY AND PRESENT STATE OF TRANSLATIONAL ELECTRO-OPTICAL APPLICATIONS TO MEDICINE." Journal of Innovative Optical Health Sciences 01, no. 01 (June 2008): 1–15. http://dx.doi.org/10.1142/s1793545808000170.

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Анотація:
This paper reviews the history of the optoelectric devices applied to biomedical sciences in 20th century. It describes history of Vacuum tubes and Spectroscopies with the author's personal experiences, especially doublebeam spectroscopy. Further, the present developments of Near Infra Red (NIR) devices are described in translational biomedical applications. It includes particulary micro optoelectronics developments and present status of NIR breast cancer detection. Lastly, intrinsic molecular biomarkers are discussed especially NIR measurements of angiogenensis, hypermetabolism and heat production for cancer detection.
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Дисертації з теми "TRANSLATIONAL BIOMEDICAL SCIENCES"

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Yang, Kun. "An Intelligent Analysis Framework for Clinical-Translational MRI Research." Case Western Reserve University School of Graduate Studies / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=case1592254585828664.

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Chen, Yang. "DEVELOPMENT OF COMPUTATIONAL APPROACHES FOR MEDICAL IMAGE RETRIEVAL, DISEASE GENE PREDICTION, AND DRUG DISCOVERY." Case Western Reserve University School of Graduate Studies / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=case1435601642.

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Garcia, Krystine. "Bioinformatics Pipeline for Improving Identification of Modified Proteins by Neutral Loss Peak Filtering." Ohio University / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1440157843.

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Sahoo, Satya Sanket. "Semantic Provenance: Modeling, Querying, and Application in Scientific Discovery." Wright State University / OhioLINK, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=wright1282847715.

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5

Fiorini, Zeno. "IMMOBILIZED KINASE ACTIVITY BIOSENSORS FOR ABL KINASE IN CHRONIC MYELOID LEUKEMIA." Doctoral thesis, 2016. http://hdl.handle.net/11562/939238.

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La leucemia mieloide cronica (CML) è un tumore del sangue che colpisce ogni anno più di 4500 pazienti negli Stati Uniti e più di 7500 in Europa. La CML è causata da un riarrangiamento cromosomico che si traduce nella creazione di BCR/ABL1, una chinasi costituticamente attiva. L'attività incontrollata di questa chinasi determina l'accumulo di cellule mieloidi immature e la riduzione dei globuli rossi e piastrine nel sangue. Questi cambiamenti compromettono la funzione del sistema immunitario, di erogazione di ossigeno e coagulazione. Questa malattia rimane spesso silenziosa per molti anni in fase cronica (CP), ma se non trattata, procede alla fase più aggressiva e meno curabile, la fase blastica (BP). L'intervento con un regime terapeutico efficace nel più breve tempo possibile è quindi di fondamentale importanza. L'odierno approccio clinico prevede l'individuazione di mutazioni del dominio di BCR-ABL1 chinasi solo nei pazienti con una prima risposta inadeguata agli inibitori tirosin chinasici (Resistenza primaria). La mancanza di risposta iniziale può essere rilevata solo dopo un minimo di 3-12 mesi dalla diagnosi.La capacità di capire come i pazienti rispondono ai farmaci al momento della diagnosi, con una semplice analisi del sangue periferico potrebbe aiutare i medici a prescrivere trattamenti su misura per il paziente diminuendo l'insorgenza di future resistenze ai farmaci. Il test che proponiamo si basa sull'utilizzo di un peptide sintetico con elevata specificità per BCR-ABL1. Il test utilizza anticorpi per rilevare la fosforilazione del peptide che avviene usando lisati di sangue periferico o midollo osseo.
Chronic Myelogenous Leukemia (CML) is a blood cancer that affects each yearmore than 4500 patients in USA and more than 7500 in Europe. CML is caused byan acquired chromosomal rearrangement that results in the creation of BCR-ABL1, an abnormally active kinase. The uncontrolled activity of this kinasedetermines the accumulation of immature myeloid cells and the reduction of redblood cells and platelets in the blood stream. These changes compromise thefunction of immune system, oxygen delivery and coagulation. This diseaseremains often silent for many years in a so-called chronic phase (CP), but if leftuntreated, it proceeds to the more aggressive and least treatable accelerating(AP) and blastic phases (BP). Intervening with an effective therapeutic regimenin the shortest time possible is therefore of paramount importance.The standard clinical approach prescribes the detection of BCR-ABL1 kinasedomain mutations only in patients with an inadequate initial response to TKIs(primary resistance). The lack of initial response can be detected only after aminimum of 3-12 months from the diagnosis.The ability to understand how patients respond to drugs at diagnosis with asimple analysis of peripheral blood would help clinicians to prescribe morepatient-tailored treatments decreasing the insurgence of future drug resistance.The test assay we are proposing is based on an immobilized syntheticallyoptimized peptide with a high specificity for BCR-ABL1. The test uses antibodiesto detect the occurred peptide phosphorylation from appropriately preparedperipheral blood or bone marrow cell lysates.
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Книги з теми "TRANSLATIONAL BIOMEDICAL SCIENCES"

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Intelligent surfaces in biotechnology: Scientific and engineering concepts, enabling technologies, and translation to bio-oriented applications. Hoboken, N.J: John Wiley & Sons, 2012.

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2

Dennis, Cosmatos, and Chow Shein-Chung 1955-, eds. Translational medicine: Strategies and statistical methods. Boca Raton: Chapman & Hall/CRC, 2009.

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3

Barker, Richard. The accelerating pace of biomedical advance. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780198737780.003.0002.

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Bioscience has progressed exponentially, in scientific advances and enabling technology. From quicker and much cheaper gene sequencing to the emergence of data-mining tools, the last 20 years has been unprecedented in exploitable advances brought by research. We have the tools and insights to trace disease from underlying genetics and epigenetics, through proteins that represent intervention options, to ways to create molecules, diagnostics, and devices based on those insights. The life sciences enterprise, once largely confined to Europe, the USA, and Japan, is now seeing major investment from emerging economies. We should be poised to reap the benefits of this rising tide of research with lives transformed and health systems revolutionized. However, the two million biological science papers published annully results in about 14 000 patents, only 5000 drugs in the pipeline, and a mere 30 or so actual medicines. Translation of life sciences research into usable products is hugely inefficient.
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4

Nanoparticles in Translational Science and Medicine Progress in Molecular Biology Translational Science. Academic Press, 2011.

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5

Martin, Wehling, ed. Translational science in medicine: From bench to bedside. Cambridge: Cambridge University Press, 2009.

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6

Barker, Richard. The gaps in translating biomedical advance into patient benefit. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780198737780.003.0003.

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There are no less than five major gaps in translation in the long journey from discovery to practical patient benefit. Insufficient understanding of disease mechanisms (T0), limited skills and motivation in turning lab discoveries into potential products (T1), huge wastage in bringing promising products to market (T2), disappointingly slow adoption by doctors and adherence by patients (T3), and failure to learn from past experience (T4): all cripple the productivity of life sciences. T2 is a particular challenge, especially in medicines, with a high attrition rate in costly clinical trials and increasing difficulties in persuading health technology assessment (HTA) agencies of the added-value of new technologies, combined with HTA differences across countries. Major cultural barriers between academia, practical medicine, and industry make matters worse, as mismatched incentives and mutual suspicion impede collaboration. The net result is poor yield at every stage in the innovation process and therefore very poor translation overall.
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David, Robertson, and Gordon H. Williams. Clinical and Translational Science: Principles of Human Research. Elsevier Science & Technology Books, 2016.

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8

Clinical and Translational Science: Principles of Human Research. Elsevier Science & Technology Books, 2008.

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9

Barker, Richard. Introduction: The growing innovation gap in life sciences. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780198737780.003.0001.

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We live in a world caught up in ever more rapid technological advance. Every week brings new IT products and services. Sectors as diverse as transport, energy, communications, and food are all bringing forward new ways to satisfy human need. However, biomedical innovation remains stubbornly slow and unproductive, as measured by output (benefit to patients) over input (investment). In fact, pharmaceutical innovation follows ‘Eroom’s Law’– an exponential decline in productivity that is the very reverse of Moore’s Law. This is despite very rapid progress in the underlying science. This ‘innovation gap’ puts at risk the very enterprise of life sciences, in which society and investors place so much faith. We need a scientific study of the gaps in translation and radical thinking to bridge them.
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Reis, Rui L., J. Miguel Oliveira, Sandra Pina, and Julio San Roman. Osteochondral Tissue Engineering: Nanotechnology, Scaffolding-Related Developments and Translation. Springer, 2018.

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Частини книг з теми "TRANSLATIONAL BIOMEDICAL SCIENCES"

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Sobti, R. C., Jagdish Rai, and Anand Prakash. "Introduction to Emerging Technologies in Biomedical Sciences." In Biomedical Translational Research, 1–22. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-4345-3_1.

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Suri, Vanita, and Ritu Aggarwal. "Biomedical Science and Women’s Health." In Biomedical Translational Research, 465–75. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-8845-4_23.

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3

Afzal, Zubair, Saber A. Akhondi, Herman H. H. B. M. van Haagen, Erik M. van Mulligen, and Jan A. Kors. "Concept Recognition in French Biomedical Text Using Automatic Translation." In Lecture Notes in Computer Science, 162–73. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-44564-9_13.

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4

Ezhergina, Elizaveta, Mariia Fedorova, Valentin Malykh, and Daria Petrova. "Findings of Biomedical Russian to English Machine Translation Competition." In Communications in Computer and Information Science, 95–101. Cham: Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-23372-2_9.

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Carrero, Francisco, José Carlos Cortizo, and José María Gómez. "Building a Spanish MMTx by Using Automatic Translation and Biomedical Ontologies." In Lecture Notes in Computer Science, 346–53. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-88906-9_44.

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6

Cimino, James J. "The Biomedical Translational Research Information System: Clinical Data Integration at the National Institutes of Health." In Lecture Notes in Computer Science, 92. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-31040-9_9.

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7

Devare, Medha, Elizabeth Arnaud, Erick Antezana, and Brian King. "Governing Agricultural Data: Challenges and Recommendations." In Towards Responsible Plant Data Linkage: Data Challenges for Agricultural Research and Development, 201–22. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-13276-6_11.

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AbstractThe biomedical domain has shown that in silico analyses over vast data pools enhances the speed and scale of scientific innovation. This can hold true in agricultural research and guide similar multi-stakeholder action in service of global food security as well (Streich et al. Curr Opin Biotechnol 61:217–225. Retrieved from https://doi.org/10.1016/j.copbio.2020.01.010, 2020). However, entrenched research culture and data and standards governance issues to enable data interoperability and ease of reuse continue to be roadblocks in the agricultural research for development sector. Effective operationalization of the FAIR Data Principles towards Findable, Accessible, Interoperable, and Reusable data requires that agricultural researchers accept that their responsibilities in a digital age include the stewardship of data assets to assure long-term preservation, access and reuse. The development and adoption of common agricultural data standards are key to assuring good stewardship, but face several challenges, including limited awareness about standards compliance; lagging data science capacity; emphasis on data collection rather than reuse; and limited fund allocation for data and standards management. Community-based hurdles around the development and governance of standards and fostering their adoption also abound. This chapter discusses challenges and possible solutions to making FAIR agricultural data assets the norm rather than the exception to catalyze a much-needed revolution towards “translational agriculture”.
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Farabaugh, P. J. "Translational Control and Fidelity☆." In Reference Module in Biomedical Sciences. Elsevier, 2016. http://dx.doi.org/10.1016/b978-0-12-801238-3.99221-3.

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Li, Meina, and Alastair G. Stewart. "Translational Pharmacology and Clinical Trials." In Reference Module in Biomedical Sciences. Elsevier, 2021. http://dx.doi.org/10.1016/b978-0-12-820472-6.00028-1.

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Dent, Paul. "Cell Signaling and Translational Developmental Therapeutics." In Reference Module in Biomedical Sciences. Elsevier, 2021. http://dx.doi.org/10.1016/b978-0-12-820472-6.99997-3.

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Тези доповідей конференцій з теми "TRANSLATIONAL BIOMEDICAL SCIENCES"

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"Aligning Biomedical Informatics with Clinical and Translational Science." In 2009 42nd Hawaii International Conference on System Sciences. IEEE, 2009. http://dx.doi.org/10.1109/hicss.2009.54.

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2

Апарцин, Константин, and Konstantin Apartsin. "The results of fundamental and translational research carried out In the Department of Biomedical Research and Technology of the SBRAS INC in 2012-2016." In Topical issues of translational medicine: a collection of articles dedicated to the 5th anniversary of the day The creation of a department for biomedical research and technology of the Irkutsk Scientific Center Siberian Branch of RAS. Москва: INFRA-M Academic Publishing LLC., 2017. http://dx.doi.org/10.12737/conferencearticle_58be81eca22ad.

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The results of basic and translational research of the Department of Biomedical Research and Technology of Irkutsk Scientific Center of the Siberian Branch of the Russian Academy of Sciences in 2012–2016 The paper presents the results of interdisciplinary research carried out in 2012–2016. The review includes the study of molecular mechanisms of pathogenesis of reparative regeneration, experimental substantiation of methods of diagnosis and prognosis of systemic disturbances of regeneration process, carrying out clinical trials of medicinal products and the formation of observational studies in the field of personalized medicine, the preparation of practical recommendations on the testing of previously developed surgical methods of prevention or correction of postoperative recovery disorders. New data are obtained on the role of the MAP-kinase cascade in the process of regeneration of muscle tissue. It has been established, that with a significant increase of VEGF concentration at the site of the repair of ischemic myocardium, progenitor cells with the CD34+CD45+ phenotype appear, which opens up prospects for the development of biotechnology to restore the damaged myocardium with its own pool of progenitor cells. The new data on the role of growth factors in the post-infarction remodeling are found. It has been revealed, that in local increase of selenium concentration low intensity of mineralization of forming callus in the area of the damage is observed and the formation of bone regeneration slows down. Prospects for the use of nanocomposites of elemental selenium for modulation of reparative response are marked. The dynamics of the level of free circulating mitochondrial DNA (mtDNA) of blood in the early stages of experimental dyslipidemia has been studied. Atherogenic blood factors do not have a significant effect on the release of the mtDNA from dyslipidemia target cells. On the model of acute small-focal myocardial ischemia, we revealed the increase in the mtDNA levels. Prospects of broadcast of diagnostic mtDNA monitoring technology in myocardial ischemia have been marked. The mtDNA monitoring was first tested as a molecular risk pattern in acute coronary syndrome. In survived patients, the concentration of freely circulating mtDNA in blood plasma was 164 times lower. The probability of death of the patient with a high level of mtDNA (over 4000 copies/mL) was 50 % (logit analysis). Methodological level of translational research in the ISC SB RAS has increased due to effective participation in international multi-center clinical trials of drugs, mainly direct anticoagulants: fondaparinux, edoksabana, betriksabana. “Feedback broadcast” of the results of clinical trials of p38-kinase inhibitor, was carried out in the process of changing the model (initially – neuropathic pain) for coronary atherosclerosis. Technologies of pharmacogenetic testing and personalized treatment of diseases in the employees of the Irkutsk Scientific Center were applied. Step T2. Previously developed at the Irkutsk State Medical University and the Irkutsk Scientific Center of Surgery and Traumatologies approaches to surgical prevention and medicinal correction of postoperative hyposplenism were translated into practical health care. Thus, these results obtained in different areas of translational medicine will determine scientific topics of the department in future research cycle.
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Park, Sang Mok, and Young L. Kim. "Spectral super-resolution spectroscopy for biomedical applications." In Advanced Chemical Microscopy for Life Science and Translational Medicine 2021, edited by Garth J. Simpson, Ji-Xin Cheng, and Wei Min. SPIE, 2021. http://dx.doi.org/10.1117/12.2577799.

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Wang, Tusheng, Yuanyuan Yang, Kai Zhang, Mingqing Wang, Jun Zhao, Lisa Xu, and Jianguo Zhang. "e-Science platform for translational biomedical imaging research: running, statistics, and analysis." In SPIE Medical Imaging, edited by Tessa S. Cook and Jianguo Zhang. SPIE, 2015. http://dx.doi.org/10.1117/12.2082516.

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Zhang, Jianguo, Tusheng Wang, Mingqing Wang, Kia Zhang, Yuanyuan Yang, Jianyong Sun, Tonghui Ling, Qiu Huang, and Lisa Xu. "Image communication, storage and computing in e-science platform for translational biomedical imaging research." In SPIE Medical Imaging, edited by Maria Y. Law and William W. Boonn. SPIE, 2013. http://dx.doi.org/10.1117/12.2007238.

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Cheng, Ji-Xin. "Label-free chemical microscopy for Life science and translational medicine (Conference Presentation)." In Label-free Biomedical Imaging and Sensing (LBIS) 2020, edited by Natan T. Shaked and Oliver Hayden. SPIE, 2020. http://dx.doi.org/10.1117/12.2543556.

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Cimino, James J., Wayne H. Liang, Jelai Wang, Dongmei Sun, John D. Osborne, Amy Y. Wang, S. Louis Bridges, Matt Wyatt, and Jake Y. Chen. "Empowering Team Science Across the Translational Spectrum with the UAB Biomedical Research Infrastructure Technology Enhancement (U-BRITE)." In 2020 IEEE 21st International Conference on Information Reuse and Integration for Data Science (IRI). IEEE, 2020. http://dx.doi.org/10.1109/iri49571.2020.00035.

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Van Huizen, Laura M., Teodora Radonic, Frank van Mourik, Daniëlle Seinstra, Chris Dickhoff, Johannes M. A. Daniels, Idris Bahce, Jouke T. Annema, and Marie Louise Groot. "Translation of third and second harmonic generation microscopy into the clinic for the assessment of fresh lung tumor tissue." In Multiphoton Microscopy in the Biomedical Sciences XXI, edited by Ammasi Periasamy, Peter T. So, and Karsten König. SPIE, 2021. http://dx.doi.org/10.1117/12.2578174.

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Watanabe, Kaoru, Masahiro Yagi, Atsuhiro Shintani, Shigeki Nankaku, Katsuhiko Onishi, Masanao Koeda, Hiroshi Noborio, Masanori Kon, Kousuke Matsui, and Masaki Kaibori. "A new 2D depth-depth matching algorithm whose translation and rotation freedoms are separated." In 2015 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS). IEEE, 2015. http://dx.doi.org/10.1109/iciibms.2015.7439546.

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Звіти організацій з теми "TRANSLATIONAL BIOMEDICAL SCIENCES"

1

Schneider, Sallie, Rong Shao, Lawrence Schwartz, and D. Joseph Jerry. Pioneer Valley Life Sciences Institute Translational Biomedical Research. Office of Scientific and Technical Information (OSTI), September 2012. http://dx.doi.org/10.2172/1054883.

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