Journal articles: 'Pathways Approach'

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Kati, Yassine EL, Shu-Lin Wang, and Fouad Kharroubi. "A Novel Approach for Detecting Driver Mutated Pathways in Glioblastoma Multiform." International Journal of Pharma Medicine and Biological Sciences 8, no. 1 (January 2019): 17–21. http://dx.doi.org/10.18178/ijpmbs.8.1.17-21.

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Ganova-Iolovska, Milka, and Max Geraedts. "Clinical pathways – the Bulgarian approach." Journal of Public Health 17, no. 3 (December 19, 2008): 225–30. http://dx.doi.org/10.1007/s10389-008-0239-0.

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Lee, Yu Ra, Bark Lynn Lew, Woo Young Sim, Jongki Hong, and Bong Chul Chung. "Alterations in Pattern Baldness According to Sex: Hair Metabolomics Approach." Metabolites 11, no. 3 (March 18, 2021): 178. http://dx.doi.org/10.3390/metabo11030178.

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Pattern baldness has been associated with the male hormone, dihydrotestosterone. In this study, we tried to determine how the overall metabolic pathways of pattern baldness differ in patients and in normal controls. Our study aimed to identify alterations in hair metabolomic profiles in order to identify possible markers of pattern baldness according to sex. Untargeted metabolomics profiling in pattern baldness patients and control subjects was conducted using ultra-performance liquid chromatography-mass spectrometry. To identify significantly altered metabolic pathways, partial least squares discriminant analysis was performed. Our analysis indicated differences in steroid biosynthesis pathway in both males and females. However, there was a remarkable difference in the androgen metabolic pathway in males, and the estrogen metabolic and arachidonic acid pathways in females. For the first time, we were able to confirm the metabolic pathway in pattern baldness patients using hair samples. Our finding improves understanding of pattern baldness and highlights the need to link pattern baldness and sex-related differences.

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Moffa, Giusi, Gerrit Erdmann, Oksana Voloshanenko, Christian Hundsrucker, Mohammad J. Sadeh, Michael Boutros, and Rainer Spang. "Refining Pathways: A Model Comparison Approach." PLOS ONE 11, no. 6 (June 1, 2016): e0155999. http://dx.doi.org/10.1371/journal.pone.0155999.

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Buhrs, Ton, and Graeme Aplin. "Pathways Towards Sustainability: The Australian Approach." Journal of Environmental Planning and Management 42, no. 3 (May 1999): 315–40. http://dx.doi.org/10.1080/09640569911118.

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Schroder, Patricia J. "Psychiatric Clinical Pathways: An Interdisciplinary Approach." Journal of Psychosocial Nursing and Mental Health Services 37, no. 1 (January 1999): 22. http://dx.doi.org/10.3928/0279-3695-19990101-12.

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Jones, Keith, Api Desai, Mark Mulville, and Aled Jones. "Asset management using a hybrid backcasting/forecasting approach." Facilities 33, no. 11/12 (August 3, 2015): 701–15. http://dx.doi.org/10.1108/f-11-2014-0090.

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Purpose – The purpose of this paper is to present an alternative approach to facilities and built asset management adaptation planning to climate change based on a hybrid backcasting/forecasting model. Backcasting envisions a future state and examines alternative “pathways of approach” by looking backwards from the future state to the present day. Each pathway is examined in turn to identify interventions required for that pathway to achieve the future state. Each pathway is reviewed using forecasting tools and the most appropriate is selected. This paper describes the application of this approach to the integration of climate change adaptation plans into facilities and built asset management. Design/methodology/approach – The researchers worked with various stakeholders as part of a participatory research team to identify climate change adaptations that may be required to ensure the continued performance of a new educational building over its life cycle. The team identified 2020, 2040 and 2080 year end-goals and assessed alternative pathways of approach. The most appropriate pathways were integrated into the facilities and built asset management plan. Findings – The paper outlines a conceptual framework for formulating long term facilities and built asset management strategies to address adaptation to climate change. Research limitations/implications – The conceptual framework is validated by a single research case study, and further examples are needed to ensure validity of the approach in different facilities management contexts. Originality/value – This is the first paper to explore backcasting principles as part of facilities and built asset management planning.

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Williams, Sharon, and Zoe Radnor. "An integrative approach to improving patient care pathways." International Journal of Health Care Quality Assurance 31, no. 7 (August 13, 2018): 810–21. http://dx.doi.org/10.1108/ijhcqa-07-2017-0132.

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Purpose Globally, healthcare managers continue to struggle with increasing demands for their services being delivered with limited or shrinking resources. It is, therefore, clear that systems, processes and practices need to change to meet these challenges. The purpose of this paper is to assess how integrating two improvement technologies, Lean and integrated care pathways (ICP) might help. Design/methodology/approach Lean and ICP in healthcare provide a platform to develop conceptual frameworks for integrating two approaches. Findings A conceptual integrated framework is provided to assist care pathway designers and implementers to consider the synergistic benefits of combining approaches to improvement. Research limitations/implications The authors provide a conceptual framework that requires empirically testing. Practical implications This research provides a conceptual framework to aid practitioners to improve healthcare design and delivery. Originality/value For the first time, the authors bring together two approaches to improving patient care pathway design and consider how these are linked in relation to improving healthcare delivery.

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Qiao, Bo, Yueying Wu, Xiaoya Li, Zhenyuan Xu, Weigang Duan, Yanan Hu, Wenqing Jia, Qiuyang Fan, and Haijing Xing. "A Network Pharmacology Approach to Explore the Potential Mechanisms of Yifei Sanjie Formula in Treating Pulmonary Fibrosis." Evidence-Based Complementary and Alternative Medicine 2020 (November 30, 2020): 1–15. http://dx.doi.org/10.1155/2020/8887017.

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Objective. Yifei Sanjie Formula (YFSJF) is an effective formula on pulmonary fibrosis (PF), which has been used in clinic for more than 30 years. In order to investigate the molecular mechanism of YFSJF in treating PF, network pharmacology was used to predict the cooperative ingredients and associated pathways. Methods. Firstly, we collected potential active ingredients of YFSJF by TCMSP databases. Secondly, we obtained PF-associated targets through OMIM and Genecards database. Finally, metascape was applied for the analysis of GO terms and KEGG pathways. Results. We screened out 76 potential active ingredients and 98 associated proteins. A total of 5715 items were obtained by GO enrichment analysis ( P < 0.05 ), including 4632 biological processes, 444 cellular components, and 639 molecular functions. A total of 143 related KEGG pathways were enriched ( P < 0.05 ), including IL-17 signaling pathway, T cell receptor signaling pathway, TNF signaling pathway, calcium signaling pathway, TH17 cell differentiation, HIF-1 signaling pathway, and PI3K-Akt signaling pathway. Conclusion. YFSJF can interfere with immune and inflammatory response through multiple targets and pathways, which has a certain role in the treatment of PF. This study lays a foundation for future experimental research.

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Sen, A. K. "Calculation of control coefficients of metabolic pathways. A flux-oriented graph-theoretic approach." Biochemical Journal 279, no. 1 (October 1, 1991): 55–65. http://dx.doi.org/10.1042/bj2790055.

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Within the premises of the flux-oriented theory of Crabtree & Newsholme [(1987) Biochem. J. 247, 113-120], I have used a graph-theoretic approach for calculating the Control Coefficients of metabolic pathways. It is shown that a directed graph representing the control structure of a metabolic pathway can be constructed in a heuristic manner directly from the reaction diagram of the pathway, without the necessity of writing down the governing equations for the Control Coefficients. The Control Coefficients are derived from an analysis of the topology of the directed graph. The graph-theoretic approach also provides a visual framework for analysing the functional relationships of the individual enzymes. The control structures of the following pathways are examined here: (a) a simple unbranched pathway with four enzymes, (b) a simple branched pathway with three enzymes, and (c) a branched pathway with both carbon and energy (ATP) fluxes.

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Cocco, Nicoletta, Mercè Llabrés, Mariana Reyes-Prieto, and Marta Simeoni. "MetNet: A two-level approach to reconstructing and comparing metabolic networks." PLOS ONE 16, no. 2 (February 12, 2021): e0246962. http://dx.doi.org/10.1371/journal.pone.0246962.

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Metabolic pathway comparison and interaction between different species can detect important information for drug engineering and medical science. In the literature, proposals for reconstructing and comparing metabolic networks present two main problems: network reconstruction requires usually human intervention to integrate information from different sources and, in metabolic comparison, the size of the networks leads to a challenging computational problem. We propose to automatically reconstruct a metabolic network on the basis of KEGG database information. Our proposal relies on a two-level representation of the huge metabolic network: the first level is graph-based and depicts pathways as nodes and relations between pathways as edges; the second level represents each metabolic pathway in terms of its reactions content. The two-level representation complies with the KEGG database, which decomposes the metabolism of all the different organisms into “reference” pathways in a standardised way. On the basis of this two-level representation, we introduce some similarity measures for both levels. They allow for both a local comparison, pathway by pathway, and a global comparison of the entire metabolism. We developed a tool, MetNet, that implements the proposed methodology. MetNet makes it possible to automatically reconstruct the metabolic network of two organisms selected in KEGG and to compare their two networks both quantitatively and visually. We validate our methodology by presenting some experiments performed with MetNet.

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Chen, Lina, Liangcai Zhang, Yan Zhao, Liangde Xu, Yukui Shang, Qian Wang, Wan Li, Hong Wang, and Xia Li. "Prioritizing risk pathways: a novel association approach to searching for disease pathways fusing SNPs and pathways." Bioinformatics 25, no. 2 (November 24, 2008): 237–42. http://dx.doi.org/10.1093/bioinformatics/btn613.

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Fields, Karen K., Hatem Hussein Soliman, Eliot Lawrence Friedman, Rachel V. Lee, Maria Czarina Acelajado, Diana Tamondong-Lachica, and John W. Peabody. "Measuring clinical pathway compliance using a simulated patient approach with clinical performance and value (CPV) vignettes." Journal of Clinical Oncology 31, no. 31_suppl (November 1, 2013): 96. http://dx.doi.org/10.1200/jco.2013.31.31_suppl.96.

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96 Background: Although clinical pathways have the promise to improve the quality of care, they have had limited success changing practice or standardizing care. Moffitt Cancer Center (MCC) has > 40 pathways incorporating interdisciplinary care strategies linked to evidence and decision support tools. Methods: To improve compliance with pathways we used an innovative measure to quantify quality of care, CPV vignettes. CPV vignettes are validated, simulated clinical scenarios constructed so that adherence to pathways is clear-cut. Providers care for identical cases so there is no need for case mix adjustment. After completing each case, providers are given personalized feedback. Twelve breast cancer (ca) vignettes were developed by MCC breast medical oncologists and surgeons and QURE, a healthcare measurement company. The cases were developed using MCC pathways, other evidence and core issues such as diagnostic work-up. The vignettes were randomized at the department level and given to all MCC providers who care for breast ca patients. A total of 18 providers took 34 CPVs: 7 medical oncologists, 6 advanced practitioners and 5 surgeons. QURE-trained physician abstractors blinded to the CPV-taker’s identity scored each vignette and provided confidential feedback. Results: Total scores for providers averaged 55.4%, s.d. 12.5%, a typical score for a CPV baseline study. Adherence to pathways varied by area with the highest concordance for radiation and hormonal therapy and the lowest for management of axillary lymph nodes (see Table). Conclusions: Adherence to pathways varied among providers and by clinical domain. Ongoing efforts will evaluate the impact of serial CPV measurement on pathway adherence. Simulations simplified the task of determining pathway adherence making pathway compliance at the physician level a reasonable expectation and standardization at the group level scientifically rigorous and feasible. [Table: see text]

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Ferguson, Laura B., Shruti Patil, Bailey A. Moskowitz, Igor Ponomarev, Robert A. Harris, Roy D. Mayfield, and Robert O. Messing. "A Pathway-Based Genomic Approach to Identify Medications: Application to Alcohol Use Disorder." Brain Sciences 9, no. 12 (December 16, 2019): 381. http://dx.doi.org/10.3390/brainsci9120381.

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Chronic, excessive alcohol use alters brain gene expression patterns, which could be important for initiating, maintaining, or progressing the addicted state. It has been proposed that pharmaceuticals with opposing effects on gene expression could treat alcohol use disorder (AUD). Computational strategies comparing gene expression signatures of disease to those of pharmaceuticals show promise for nominating novel treatments. We reasoned that it may be sufficient for a treatment to target the biological pathway rather than lists of individual genes perturbed by AUD. We analyzed published and unpublished transcriptomic data using gene set enrichment of Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways to identify biological pathways disrupted in AUD brain and by compounds in the Library of Network-based Cellular Signatures (LINCS L1000) and Connectivity Map (CMap) databases. Several pathways were consistently disrupted in AUD brain, including an up-regulation of genes within the Complement and Coagulation Cascade, Focal Adhesion, Systemic Lupus Erythematosus, and MAPK signaling, and a down-regulation of genes within the Oxidative Phosphorylation pathway, strengthening evidence for their importance in AUD. Over 200 compounds targeted genes within those pathways in an opposing manner, more than twenty of which have already been shown to affect alcohol consumption, providing confidence in our approach. We created a user-friendly web-interface that researchers can use to identify drugs that target pathways of interest or nominate mechanism of action for drugs. This study demonstrates a unique systems pharmacology approach that can nominate pharmaceuticals that target pathways disrupted in disease states such as AUD and identify compounds that could be repurposed for AUD if sufficient evidence is attained in preclinical studies.

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Jiang, Yu, Yuan Huang, Yinhao Du, Yinjun Zhao, Jie Ren, Shuangge Ma, and Cen Wu. "Identification of Prognostic Genes and Pathways in Lung Adenocarcinoma Using a Bayesian Approach." Cancer Informatics 16 (January 2017): 117693511668482. http://dx.doi.org/10.1177/1176935116684825.

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Lung cancer is the leading cause of cancer-associated mortality in the United States and the world. Adenocarcinoma, the most common subtype of lung cancer, is generally diagnosed at the late stage with poor prognosis. In the past, extensive effort has been devoted to elucidating lung cancer pathogenesis and pinpointing genes associated with survival outcomes. As the progression of lung cancer is a complex process that involves coordinated actions of functionally associated genes from cancer-related pathways, there is a growing interest in simultaneous identification of both prognostic pathways and important genes within those pathways. In this study, we analyse The Cancer Genome Atlas lung adenocarcinoma data using a Bayesian approach incorporating the pathway information as well as the interconnections among genes. The top 11 pathways have been found to play significant roles in lung adenocarcinoma prognosis, including pathways in mitogen-activated protein kinase signalling, cytokine-cytokine receptor interaction, and ubiquitin-mediated proteolysis. We have also located key gene signatures such as RELB, MAP4K1, and UBE2C. These results indicate that the Bayesian approach may facilitate discovery of important genes and pathways that are tightly associated with the survival of patients with lung adenocarcinoma.

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De Haan, Fjalar, and Briony Rogers. "The Multi-Pattern Approach for Systematic Analysis of Transition Pathways." Sustainability 11, no. 2 (January 10, 2019): 318. http://dx.doi.org/10.3390/su11020318.

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Pathways have become a central notion in various areas of research, amongst which are the studies of transitions to sustainability. Though various typologies and concepts are available, a framework for systematic analysis of transition pathways is lacking. We present the Multi-Pattern Approach (MPA) to fill this lacuna and provide a step-by-step manual for its application. The MPA addresses a range of traditional challenges of transitions’ pathway analysis, such as temporal and functional system demarcation and the unravelling of complex, interrelated systemic storylines. The approach provides an oft-called for rigour which allows a diagrammatic and formulaic representation of transitions’ pathways. Because of these qualities, the approach allows systematic cross-case comparison and provides a bridge between narrative-based and computational transitions research. The approach is demonstrated with an in-depth empirical case study of water management in Melbourne, Australia over the last 180 years. The article first presents a high-level mapping of the system’s evolution over time and a detailed analysis of the uptake and phasing out of specific servicing technologies and practices.

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Kim, Sung Hee. "Approach to pupillary abnormalities via anatomical pathways." Yeungnam University Journal of Medicine 34, no. 1 (June 30, 2017): 11–18. http://dx.doi.org/10.12701/yujm.2017.34.1.11.

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Gingerich, Barbara Stover. "Pathways to Publishing: a How-to Approach." Home Health Care Management & Practice 16, no. 4 (June 2004): 286–89. http://dx.doi.org/10.1177/1084822303262338.

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Gerard, Matias F., Georgina Stegmayer, and Diego H. Milone. "An evolutionary approach for searching metabolic pathways." Computers in Biology and Medicine 43, no. 11 (November 2013): 1704–12. http://dx.doi.org/10.1016/j.compbiomed.2013.08.017.

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Francis, Helen, Julie Boulton, Michael Barnett, and Robert Kirby. "Transforming Breast Cancer Pathways – A Multidisciplinary Approach." European Journal of Surgical Oncology 45, no. 11 (November 2019): 2226. http://dx.doi.org/10.1016/j.ejso.2019.09.172.

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Yelmame, Ganesh B., and SHRIKANT B. JAGTAP. "Review on Perimidines: A synthetic Pathways Approach." Material Science Research India 18, no. 1 (April 30, 2021): 14–26. http://dx.doi.org/10.13005/msri/180103.

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Perimidines are available in an assortment of drugs and general use industrial structures and perimidines are also significant primary theme because of their extraordinary method of physiological activity. Thus the underlying significance of perimidine moiety has evoked a lot of interest in the field of natural blend and compound science to build up some better than ever amalgamation of this atomic skeleton. In this review, we have depicted a modern outline on the new advances in the different manufactured approaches of perimidine. The review covers the essential applied and down to earth synergist blend like, green methodologies, metal catalysed responses, microwave illumination, grinding and so forth which are critical for developing perimidine skeleton. This review will fulfill the assumptions for peruses who are keen on the advancement of the field and searching for an update. It will animate analysts to grow new and innovative manufactured admittance to this heterocyclic framework, which will be instrumental in the headway of perimidine science. This review provides an overview of various synthetic methodologies for the synthesis of a wide range of perimidine derivatives with applications in material chemistry, drug discovery, polymer chemistry, photo sensors, dye chemistry, and other fields.

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Kirk, Ann, and Jocolyn Thompson. "Practical pathways: A multidisciplinary approach to asthma." Paediatric Nursing 10, no. 2 (March 1, 1998): 18–20. http://dx.doi.org/10.7748/paed.10.2.18.s19.

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Zhang, Shoude, Lei Shan, Qiao Li, Xia Wang, Shiliang Li, Yuan Zhang, Jianjun Fu, Xiaofeng Liu, Honglin Li, and Weidong Zhang. "Systematic Analysis of the Multiple Bioactivities of Green Tea through a Network Pharmacology Approach." Evidence-Based Complementary and Alternative Medicine 2014 (2014): 1–11. http://dx.doi.org/10.1155/2014/512081.

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During the past decades, a number of studies have demonstrated multiple beneficial health effects of green tea. Polyphenolics are the most biologically active components of green tea. Many targets can be targeted or affected by polyphenolics. In this study, we excavated all of the targets of green tea polyphenolics (GTPs) though literature mining and target calculation and analyzed the multiple pharmacology actions of green tea comprehensively through a network pharmacology approach. In the end, a total of 200Homo sapienstargets were identified for fifteen GTPs. These targets were classified into six groups according to their related disease, which included cancer, diabetes, neurodegenerative disease, cardiovascular disease, muscular disease, and inflammation. Moreover, these targets mapped into 143 KEGG pathways, 26 of which were more enriched, as determined though pathway enrichment analysis and target-pathway network analysis. Among the identified pathways, 20 pathways were selected for analyzing the mechanisms of green tea in these diseases. Overall, this study systematically illustrated the mechanisms of the pleiotropic activity of green tea by analyzing the corresponding “drug-target-pathway-disease” interaction network.

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Ghedira, Kais, Soumaya Kouidhi, Yosr Hamdi, Houcemeddine Othman, Sonia Kechaou, Sadri Znaidi, Sghaier Haïtham, and Imen Rabhi. "Pathway Maps of Orphan and Complex Diseases Using an Integrative Computational Approach." BioMed Research International 2020 (November 27, 2020): 1–11. http://dx.doi.org/10.1155/2020/4280467.

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Orphan diseases (ODs) are progressive genetic disorders, which affect a small number of people. The principal fundamental aspects related to these diseases include insufficient knowledge of mechanisms involved in the physiopathology necessary to access correct diagnosis and to develop appropriate healthcare. Unlike ODs, complex diseases (CDs) have been widely studied due to their high incidence and prevalence allowing to understand the underlying mechanisms controlling their physiopathology. Few studies have focused on the relationship between ODs and CDs to identify potential shared pathways and related molecular mechanisms which would allow improving disease diagnosis, prognosis, and treatment. We have performed a computational approach to studying CDs and ODs relationships through (1) connecting diseases to genes based on genes-diseases associations from public databases, (2) connecting ODs and CDs through binary associations based on common associated genes, and (3) linking ODs and CDs to common enriched pathways. Among the most shared significant pathways between ODs and CDs, we found pathways in cancer, p53 signaling, mismatch repair, mTOR signaling, B cell receptor signaling, and apoptosis pathways. Our findings represent a reliable resource that will contribute to identify the relationships between drugs and disease-pathway networks, enabling to optimise patient diagnosis and disease treatment.

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Brandes, Ulrik, Tim Dwyer, and Falk Schreiber. "Visual Understanding of Metabolic Pathways Across Organisms Using Layout in Two and a Half Dimensions." Journal of Integrative Bioinformatics 1, no. 1 (December 1, 2004): 11–26. http://dx.doi.org/10.1515/jib-2004-2.

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Summary We propose a method for visualizing a set of related metabolic pathways across organisms using 2 1/2 dimensional graph visualization. Interdependent, twodimensional layouts of each pathway are stacked on top of each other so that biologists get a full picture of subtle and significant differences among the pathways. The (dis)similarities between pathways are expressed by the Hamming distances of the underlying graphs which are used to compute a stacking order for the pathways. Layouts are determined by a global layout of the union of all pathway graphs using a variant of the proven Sugiyama approach for layered graph drawing. Our variant layout approach allows edges to cross if they appear in different graphs.

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Kotelnikova, Ekaterina, Marti Bernardo-Faura, Gilad Silberberg, Narsis A. Kiani, Dimitris Messinis, Ioannis N. Melas, Laura Artigas, et al. "Signaling networks in MS: A systems-based approach to developing new pharmacological therapies." Multiple Sclerosis Journal 21, no. 2 (August 11, 2014): 138–46. http://dx.doi.org/10.1177/1352458514543339.

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The pathogenesis of multiple sclerosis (MS) involves alterations to multiple pathways and processes, which represent a significant challenge for developing more-effective therapies. Systems biology approaches that study pathway dysregulation should offer benefits by integrating molecular networks and dynamic models with current biological knowledge for understanding disease heterogeneity and response to therapy. In MS, abnormalities have been identified in several cytokine-signaling pathways, as well as those of other immune receptors. Among the downstream molecules implicated are Jak/Stat, NF-Kb, ERK1/3, p38 or Jun/Fos. Together, these data suggest that MS is likely to be associated with abnormalities in apoptosis/cell death, microglia activation, blood-brain barrier functioning, immune responses, cytokine production, and/or oxidative stress, although which pathways contribute to the cascade of damage and can be modulated remains an open question. While current MS drugs target some of these pathways, others remain untouched. Here, we propose a pragmatic systems analysis approach that involves the large-scale extraction of processes and pathways relevant to MS. These data serve as a scaffold on which computational modeling can be performed to identify disease subgroups based on the contribution of different processes. Such an analysis, targeting these relevant MS-signaling pathways, offers the opportunity to accelerate the development of novel individual or combination therapies.

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Li, Chaoxing, Li Liu, and Valentin Dinu. "Pathways of topological rank analysis (PoTRA): a novel method to detect pathways involved in hepatocellular carcinoma." PeerJ 6 (April 9, 2018): e4571. http://dx.doi.org/10.7717/peerj.4571.

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Complex diseases such as cancer are usually the result of a combination of environmental factors and one or several biological pathways consisting of sets of genes. Each biological pathway exerts its function by delivering signaling through the gene network. Theoretically, a pathway is supposed to have a robust topological structure under normal physiological conditions. However, the pathway’s topological structure could be altered under some pathological condition. It is well known that a normal biological network includes a small number of well-connected hub nodes and a large number of nodes that are non-hubs. In addition, it is reported that the loss of connectivity is a common topological trait of cancer networks, which is an assumption of our method. Hence, from normal to cancer, the process of the network losing connectivity might be the process of disrupting the structure of the network, namely, the number of hub genes might be altered in cancer compared to that in normal or the distribution of topological ranks of genes might be altered. Based on this, we propose a new PageRank-based method called Pathways of Topological Rank Analysis (PoTRA) to detect pathways involved in cancer. We use PageRank to measure the relative topological ranks of genes in each biological pathway, then select hub genes for each pathway, and use Fisher’s exact test to test if the number of hub genes in each pathway is altered from normal to cancer. Alternatively, if the distribution of topological ranks of gene in a pathway is altered between normal and cancer, this pathway might also be involved in cancer. Hence, we use the Kolmogorov–Smirnov test to detect pathways that have an altered distribution of topological ranks of genes between two phenotypes. We apply PoTRA to study hepatocellular carcinoma (HCC) and several subtypes of HCC. Very interestingly, we discover that all significant pathways in HCC are cancer-associated generally, while several significant pathways in subtypes of HCC are HCC subtype-associated specifically. In conclusion, PoTRA is a new approach to explore and discover pathways involved in cancer. PoTRA can be used as a complement to other existing methods to broaden our understanding of the biological mechanisms behind cancer at the system-level.

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Xie, Xiaoman, Matthew C. Kendzior, Xiyu Ge, Liudmila S. Mainzer, and Saurabh Sinha. "VarSAn: associating pathways with a set of genomic variants using network analysis." Nucleic Acids Research 49, no. 15 (July 27, 2021): 8471–87. http://dx.doi.org/10.1093/nar/gkab624.

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Abstract There is a pressing need today to mechanistically interpret sets of genomic variants associated with diseases. Here we present a tool called ‘VarSAn’ that uses a network analysis algorithm to identify pathways relevant to a given set of variants. VarSAn analyzes a configurable network whose nodes represent variants, genes and pathways, using a Random Walk with Restarts algorithm to rank pathways for relevance to the given variants, and reports P-values for pathway relevance. It treats non-coding and coding variants differently, properly accounts for the number of pathways impacted by each variant and identifies relevant pathways even if many variants do not directly impact genes of the pathway. We use VarSAn to identify pathways relevant to variants related to cancer and several other diseases, as well as drug response variation. We find VarSAn's pathway ranking to be complementary to the standard approach of enrichment tests on genes related to the query set. We adopt a novel benchmarking strategy to quantify its advantage over this baseline approach. Finally, we use VarSAn to discover key pathways, including the VEGFA-VEGFR2 pathway, related to de novo variants in patients of Hypoplastic Left Heart Syndrome, a rare and severe congenital heart defect.

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Colaprico, Antonio, Claudia Cava, Gloria Bertoli, Gianluca Bontempi, and Isabella Castiglioni. "Integrative Analysis with Monte Carlo Cross-Validation Reveals miRNAs Regulating Pathways Cross-Talk in Aggressive Breast Cancer." BioMed Research International 2015 (2015): 1–17. http://dx.doi.org/10.1155/2015/831314.

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In this work an integrated approach was used to identify functional miRNAs regulating gene pathway cross-talk in breast cancer (BC). We first integrated gene expression profiles and biological pathway information to explore the underlying associations between genes differently expressed among normal and BC samples and pathways enriched from these genes. For each pair of pathways, a score was derived from the distribution of gene expression levels by quantifying their pathway cross-talk. Random forest classification allowed the identification of pairs of pathways with high cross-talk. We assessed miRNAs regulating the identified gene pathways by a mutual information analysis. A Fisher test was applied to demonstrate their significance in the regulated pathways. Our results suggest interesting networks of pathways that could be key regulatory of target genes in BC, including stem cell pluripotency, coagulation, and hypoxia pathways and miRNAs that control these networks could be potential biomarkers for diagnostic, prognostic, and therapeutic development in BC. This work shows that standard methods of predicting normal and tumor classes such as differentially expressed miRNAs or transcription factors could lose intrinsic features; instead our approach revealed the responsible molecules of the disease.

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Jaeger, Savina, Junxia Min, Florian Nigsch, Miguel Camargo, Janna Hutz, Allen Cornett, Stephen Cleaver, Alan Buckler, and Jeremy L. Jenkins. "Causal Network Models for Predicting Compound Targets and Driving Pathways in Cancer." Journal of Biomolecular Screening 19, no. 5 (February 11, 2014): 791–802. http://dx.doi.org/10.1177/1087057114522690.

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Gene-expression data are often used to infer pathways regulating transcriptional responses. For example, differentially expressed genes (DEGs) induced by compound treatment can help characterize hits from phenotypic screens, either by correlation with known drug signatures or by pathway enrichment. Pathway enrichment is, however, typically computed with DEGs rather than “upstream” nodes that are potentially causal of “downstream” changes. Here, we present graph-based models to predict causal targets from compound-microarray data. We test several approaches to traversing network topology, and show that a consensus minimum-rank score (SigNet) beat individual methods and could highly rank compound targets among all network nodes. In addition, larger, less canonical networks outperformed linear canonical interactions. Importantly, pathway enrichment using causal nodes rather than DEGs recovers relevant pathways more often. To further validate our approach, we used integrated data sets from the Cancer Genome Atlas to identify driving pathways in triple-negative breast cancer. Critical pathways were uncovered, including the epidermal growth factor receptor 2–phosphatidylinositide 3-kinase–AKT–MAPK growth pathway and ATR–p53–BRCA DNA damage pathway, in addition to unexpected pathways, such as TGF–WNT cytoskeleton remodeling, IL12-induced interferon gamma production, and TNFR–IAP (inhibitor of apoptosis) apoptosis; the latter was validated by pooled small hairpin RNA profiling in cancer cells. Overall, our approach can bridge transcriptional profiles to compound targets and driving pathways in cancer.

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Lodovichi, Samuele, Tiziana Cervelli, Achille Pellicioli, and Alvaro Galli. "Inhibition of DNA Repair in Cancer Therapy: Toward a Multi-Target Approach." International Journal of Molecular Sciences 21, no. 18 (September 12, 2020): 6684. http://dx.doi.org/10.3390/ijms21186684.

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Alterations in DNA repair pathways are one of the main drivers of cancer insurgence. Nevertheless, cancer cells are more susceptible to DNA damage than normal cells and they rely on specific functional repair pathways to survive. Thanks to advances in genome sequencing, we now have a better idea of which genes are mutated in specific cancers and this prompted the development of inhibitors targeting DNA repair players involved in pathways essential for cancer cells survival. Currently, the pivotal concept is that combining the inhibition of mechanisms on which cancer cells viability depends is the most promising way to treat tumorigenesis. Numerous inhibitors have been developed and for many of them, efficacy has been demonstrated either alone or in combination with chemo or radiotherapy. In this review, we will analyze the principal pathways involved in cell cycle checkpoint and DNA repair focusing on how their alterations could predispose to cancer, then we will explore the inhibitors developed or in development specifically targeting different proteins involved in each pathway, underscoring the rationale behind their usage and how their combination and/or exploitation as adjuvants to classic therapies could help in patients clinical outcome.

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Aghdasi, Nava, Mark Whipple, Ian M. Humphreys, Kris S. Moe, Blake Hannaford, and Randall A. Bly. "Automated Surgical Approach Planning for Complex Skull Base Targets: Development and Validation of a Cost Function and Semantic At-las." Surgical Innovation 25, no. 5 (June 27, 2018): 476–84. http://dx.doi.org/10.1177/1553350618782287.

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Successful multidisciplinary treatment of skull base pathology requires precise preoperative planning. Current surgical approach (pathway) selection for these complex procedures depends on an individual surgeon’s experiences and background training. Because of anatomical variation in both normal tissue and pathology (eg, tumor), a successful surgical pathway used on one patient is not necessarily the best approach on another patient. The question is how to define and obtain optimized patient-specific surgical approach pathways? In this article, we demonstrate that the surgeon’s knowledge and decision making in preoperative planning can be modeled by a multiobjective cost function in a retrospective analysis of actual complex skull base cases. Two different approaches— weighted-sum approach and Pareto optimality—were used with a defined cost function to derive optimized surgical pathways based on preoperative computed tomography (CT) scans and manually designated pathology. With the first method, surgeon’s preferences were input as a set of weights for each objective before the search. In the second approach, the surgeon’s preferences were used to select a surgical pathway from the computed Pareto optimal set. Using preoperative CT and magnetic resonance imaging, the patient-specific surgical pathways derived by these methods were similar (85% agreement) to the actual approaches performed on patients. In one case where the actual surgical approach was different, revision surgery was required and was performed utilizing the computationally derived approach pathway.

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Lee, Garam, Yonghyan Nam, Manu Shivakumar, Apoorva Joshi, Weixuan Fu, Rebecca Anne Simmons, Paul Wang, Dokyoon Kim, and Sara Elizabeth Pinney. "A Novel Graph Based Semi-Supervised Learning Approach to Identify Pathways Contributing to the Development of Diabetes and Obesity." Journal of the Endocrine Society 5, Supplement_1 (May 1, 2021): A656—A657. http://dx.doi.org/10.1210/jendso/bvab048.1339.

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Abstract Background: Gestational diabetes (GDM) has profound effects on the intrauterine metabolic milieu, induces marked abnormalities in fetal glucose and insulin secretion and is linked to obesity and diabetes in the offspring, but the mechanisms remain largely unknown. Epigenetic modifications in stems cells may be one mechanism by which an in utero exposure can lead to the development of diabetes and obesity later in life. Objective: To identify novel pathways contributing to the development of diabetes and obesity in offspring exposed to GDM in utero by integrating data generated from transcriptome and methylome analysis from second trimester human amniocytes exposed to GDM in utero. Methods: We analyzed RNAseq and genome wide DNA methylation data (ERRBS) generated from second trimester amniocytes obtained from women with GDM (n=14). Amniocytes have stem cells-like characteristics and are derived from the fetus. Expression data of 22,271 genes were retrieved from RNAseq data. CpGs with significant changes in DNA methylation were mapped into 20,028 genes by collapsing methylation probes into promoter and gene regions. To better understand the associations among diverse gene sets or among gene sets and GDM,we first constructed two weighted co-expression networks from RNAseq and DNA methylation data, respectively. Then, two co-expression networks were integrated using a linear combination. With the integrated co-expression network, graph-based label propagation algorithm was employed to prioritize GDM-associated genes. Results: From the differential expression analysis between GDM and control, the top 20 query genes, including 11 genes and 9 methylated genes, were selected for label propagation. Finally, the top 100 genes were picked up for the pathway enrichment testusing an over-representation analysis approach. Significantly enriched pathways included: Interferon Signaling, N-glycan Antennae Elongation, Sphingolipid Pathway and Metabolism, Classical Complement Pathway, Complement and Coagulation Cascades, Tryptophan Metabolism, Peroxisomal Protein Import, Unsaturated Fatty Acid Metabolism, Complement Activation, Human Innate Immune Response, Ceramide Metabolism, Fertilization Pathway, Keratan Sulfate Biosynthesis Pathway, Transport to the Golgi and Modification Pathway (FDR q<0.05 for all pathways). Conclusion: Using a novel bioinformatic approach to synthesize transcriptome and methylome data derived from human amniocytes exposed to GDM in utero, we identified potential pathways involved in programming of diabetes and obesity in offspring including pathways involving the immune response, complex lipid metabolism, the complement pathway, and protein transport and processing. Further investigation of these pathways may yield new mechanisms contributing to diabetes and obesity.

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Jiang, Yuexu, Yanchun Liang, Duolin Wang, Dong Xu, and Trupti Joshi. "A dynamic programing approach to integrate gene expression data and network information for pathway model generation." Bioinformatics 36, no. 1 (June 6, 2019): 169–76. http://dx.doi.org/10.1093/bioinformatics/btz467.

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Abstract Motivation As large amounts of biological data continue to be rapidly generated, a major focus of bioinformatics research has been aimed toward integrating these data to identify active pathways or modules under certain experimental conditions or phenotypes. Although biologically significant modules can often be detected globally by many existing methods, it is often hard to interpret or make use of the results toward pathway model generation and testing. Results To address this gap, we have developed the IMPRes algorithm, a new step-wise active pathway detection method using a dynamic programing approach. IMPRes takes advantage of the existing pathway interaction knowledge in Kyoto Encyclopedia of Genes and Genomes. Omics data are then used to assign penalties to genes, interactions and pathways. Finally, starting from one or multiple seed genes, a shortest path algorithm is applied to detect downstream pathways that best explain the gene expression data. Since dynamic programing enables the detection one step at a time, it is easy for researchers to trace the pathways, which may lead to more accurate drug design and more effective treatment strategies. The evaluation experiments conducted on three yeast datasets have shown that IMPRes can achieve competitive or better performance than other state-of-the-art methods. Furthermore, a case study on human lung cancer dataset was performed and we provided several insights on genes and mechanisms involved in lung cancer, which had not been discovered before. Availability and implementation IMPRes visualization tool is available via web server at http://digbio.missouri.edu/impres. Supplementary information Supplementary data are available at Bioinformatics online.

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Wang, Shuyuan, Peng Xia, Li Zhang, Lei Yu, Hui Liu, Qianqian Meng, Siyao Liu, et al. "Systematical Identification of Breast Cancer-Related Circular RNA Modules for Deciphering circRNA Functions Based on the Non-Negative Matrix Factorization Algorithm." International Journal of Molecular Sciences 20, no. 4 (February 20, 2019): 919. http://dx.doi.org/10.3390/ijms20040919.

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Circular RNA (circRNA), a kind of special endogenous RNA, has been shown to be implicated in crucial biological processes of multiple cancers as a gene regulator. However, the functional roles of circRNAs in breast cancer (BC) remain to be poorly explored, and relatively incomplete knowledge of circRNAs handles the identification and prediction of BC-related circRNAs. Towards this end, we developed a systematic approach to identify circRNA modules in the BC context through integrating circRNA, mRNA, miRNA, and pathway data based on a non-negative matrix factorization (NMF) algorithm. Thirteen circRNA modules were uncovered by our approach, containing 4164 nodes (80 circRNAs, 2703 genes, 63 miRNAs and 1318 pathways) and 67,959 edges in total. GO (Gene Ontology) function screening identified nine circRNA functional modules with 44 circRNAs. Within them, 31 circRNAs in eight modules having direct relationships with known BC-related genes, miRNAs or disease-related pathways were selected as BC candidate circRNAs. Functional enrichment results showed that they were closely related with BC-associated pathways, such as ‘KEGG (Kyoto Encyclopedia of Genes and Genomes) PATHWAYS IN CANCER’, ‘REACTOME IMMUNE SYSTEM’ and ‘KEGG MAPK SIGNALING PATHWAY’, ‘KEGG P53 SIGNALING PATHWAY’ or ‘KEGG WNT SIGNALING PATHWAY’, and could sever as potential circRNA biomarkers in BC. Comparison results showed that our approach could identify more BC-related functional circRNA modules in performance. In summary, we proposed a novel systematic approach dependent on the known disease information of mRNA, miRNA and pathway to identify BC-related circRNA modules, which could help identify BC-related circRNAs and benefits treatment and prognosis for BC patients.

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Morrens, Manuel, and Sophie Erhardt. "Uncovering immune pathways in schizophrenia – A multidisciplinary approach." Neurology, Psychiatry and Brain Research 29 (September 2018): 17. http://dx.doi.org/10.1016/j.npbr.2018.01.089.

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Gannon, Theresa, Mariamne R. Rose, and Tony Ward. "Pathways to female sexual offending: approach or avoidance?" Psychology, Crime & Law 16, no. 5 (June 2010): 359–80. http://dx.doi.org/10.1080/10683160902754956.

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Breitenecker, Felix, Tamara Vobruba, Andreas Körner, and Nikolas Popper. "Pathways of Migrants and Refugees – a Simulation Approach." SNE Simulation Notes Europe 27, no. 4 (December 2017): 191–202. http://dx.doi.org/10.11128/sne.27.tn.10394.

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Takano, Hajime, Jai-Yoon Sul, Mary L. Mazzanti, Robert T. Doyle, Philip G. Haydon, and Marc D. Porter. "Micropatterned Substrates: Approach to Probing Intercellular Communication Pathways." Analytical Chemistry 74, no. 18 (September 2002): 4640–46. http://dx.doi.org/10.1021/ac0257400.

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Endacott, R., S. Cooper, R. Sheaff, J. Padmore, and G. Blakely. "Improving emergency care pathways: an action research approach." Emergency Medicine Journal 28, no. 3 (June 26, 2010): 203–7. http://dx.doi.org/10.1136/emj.2009.082859.

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Gifford, Eric, Mark Johnson, and Chun-che Tsai. "A graph-theoretic approach to modeling metabolic pathways." Journal of Computer-Aided Molecular Design 5, no. 4 (August 1991): 303–22. http://dx.doi.org/10.1007/bf00126665.

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Schultz, Emeric. "A guided discovery approach for learning metabolic pathways." Biochemistry and Molecular Biology Education 33, no. 1 (January 2005): 1–7. http://dx.doi.org/10.1002/bmb.2005.494033010433.

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Willis, Sharon. "Integrated Care Pathways: A practical approach to implementation." Nursing Management 9, no. 7 (November 1, 2002): 37. http://dx.doi.org/10.7748/nm.9.7.37.s13.

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Hamilton, Stephen F. "We need a systemic approach to career pathways." Phi Delta Kappan 101, no. 4 (November 25, 2019): 38–42. http://dx.doi.org/10.1177/0031721719892973.

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Current career pathways initiatives recapitulate in many ways both the issues motivating the school-to-work movement of the 1980s and 1990s and its recommended solutions, notably more work-based learning, especially apprenticeship. But that movement’s energy dissipated in the face of college for all. Nonetheless, some of its achievements and many of its advocates persisted. Stephen Hamilton explains what the current movement can learn from the past while embracing some contemporary developments, including the goal of college and career readiness, the practice of dual enrollment, and reduced reliance on federal leadership.

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Beggs, Jean D., and David Tollervey. "Crosstalk between RNA metabolic pathways: an RNOMICS approach." Nature Reviews Molecular Cell Biology 6, no. 5 (May 2005): 423–29. http://dx.doi.org/10.1038/nrm1648.

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Francis, Helen, Julie Boulton, Robert Kirby, and Mike Barnett. "P021: Transforming breast cancer pathways - A multidisciplinary approach." European Journal of Surgical Oncology 46, no. 6 (June 2020): e16. http://dx.doi.org/10.1016/j.ejso.2020.03.060.

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McSweeney, Peter A., Carlos Bachier, Jesus G. Berdeja, Hana Safah, Mohammed M. Elayan, Charles F. LeMaistre, Rocky Billups, and Tonya Cox. "A Network Approach to Standardization of BMT Pathways." Biology of Blood and Marrow Transplantation 21, no. 2 (February 2015): S359. http://dx.doi.org/10.1016/j.bbmt.2014.11.574.

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Liu, Yang, Wei Sun, Alexander P. Reiner, Charles Kooperberg, and Qianchuan He. "Statistical inference of genetic pathway analysis in high dimensions." Biometrika 106, no. 3 (July 13, 2019): 651. http://dx.doi.org/10.1093/biomet/asz033.

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Summary Genetic pathway analysis has become an important tool for investigating the association between a group of genetic variants and traits. With dense genotyping and extensive imputation, the number of genetic variants in biological pathways has increased considerably and sometimes exceeds the sample size $n$. Conducting genetic pathway analysis and statistical inference in such settings is challenging. We introduce an approach that can handle pathways whose dimension $p$ could be greater than $n$. Our method can be used to detect pathways that have nonsparse weak signals, as well as pathways that have sparse but stronger signals. We establish the asymptotic distribution for the proposed statistic and conduct theoretical analysis on its power. Simulation studies show that our test has correct Type I error control and is more powerful than existing approaches. An application to a genome-wide association study of high-density lipoproteins demonstrates the proposed approach.

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Ooi, Beng Guat, and Michael J. Sanger. ""Which Pathway Am I?" Using a Game Approach To Teach Students about Biochemical Pathways." Journal of Chemical Education 86, no. 4 (April 2009): 454. http://dx.doi.org/10.1021/ed086p454.

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Eisen, Andrea, Jasmin Soobrian, Ashley Tyrrell, Clement Li, Derek Muradali, Margaret F. Forbes, Angelika Gollnow, Jillian Ross, and Claire Holloway. "Using a disease pathway management approach to improve the quality of breast cancer care in Ontario." Journal of Clinical Oncology 34, no. 7_suppl (March 1, 2016): 109. http://dx.doi.org/10.1200/jco.2016.34.7_suppl.109.

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109 Background: Disease Pathway Management (DPM) is used by Cancer Care Ontario (CCO) to set priorities for cancer control, plan cancer services, and improve the quality of care in Ontario by promoting standardization. The DPM approach applies a framework to examine the performance of the entire system from prevention to end of life care, and to identify any gaps within the system. In 2014, DPM began its breast cancer pathway initiative by mapping the patient journey, depicting evidence-based best practice along the breast cancer care continuum, identifying where further guidance is needed for clinical decision making, and identifying gaps in quality of care and performance measurement indicators. Objective: To evaluate the impact of DPM on quality assessment of breast cancer care in Ontario. Methods: DPM convened a multidisciplinary breast cancer working group (WG) of 40 experts from across Ontario. The WG held 12 meetings and used guidelines developed by CCO’s Program in Evidence Based Care (or other sources as needed) to generate pathways for the prevention, screening and diagnosis, treatment, and follow-up care for breast cancer. The pathways were used as a framework to review the existing inventory of provincial breast cancer quality indicators, and to identify areas where evidence based guidance is needed. The pathways were subjected to an extensive review process before publication. Results: The expert WG identified 28 priority areas, including opportunities to develop guidance in areas where it is lacking (e.g. role of perioperative breast MRI; indications for contralateral prophylactic mastectomy) and system barriers that may hinder optimal care (e.g. biomarker assessment). The WG also used the pathways as a framework for evaluating performance measurement indicators by mapping 48 existing quality indicators for breast cancer to the pathway. Conclusions: The CCO DPM Breast Cancer pathways facilitated a province-wide, multidisciplinary process to promote quality standards, to identify gaps and overlaps in performance and quality measurement, and to recommend additional indicators more relevant to the quality of breast cancer care in Ontario.

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Journal articles on the topic 'Pathways Approach'

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