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2508 citation(s) found for "Xu, Yang".

Ontokeeper-Desktop: A Semiotic Driven Ontology Evaluation Tool for Biomedical Ontologies
Amith, Muhammad, Hao, Xubing, Gong, Yang, Cui, Licong, Tao, Cui, Amith, Muhammad , Hao, Xubing , Gong, Yang, Cui, Licong , Tao, Cui

2026 IEEE 14th International Conference on Healthcare Informatics (ICHI) | August 12, 2026 | Volume: No volume available | Issue: No issue available | Pages: 113-117

10.1109/ichi69079.2026.00025 Get It

TEENSAVE: Teen Organ Donation Support via AI and Vicrtual Engagement
Yang, Isabel, Li, Fang, Li, Jianfu, Tao, Cui, Li, Jianfu, Tao, Cui

2026 IEEE 14th International Conference on Healthcare Informatics (ICHI) | August 12, 2026 | Volume: No volume available | Issue: No issue available | Pages: 1297-1298

10.1109/ichi69079.2026.00182 Get It

Enhancing Lung Cancer Treatment Outcome Prediction through Semantic Feature Engineering Using Large Language Models
Lee, MunHwan, Chowdhury, Shaika , Klee, Eric W. , Yang, Ping, Sio, Terence, Wang, Liewei , Zong, Nansu , Li, Xiaodi , Rajaganapathy, Sivaraman , Cerhan, James R.

2026 IEEE 14th International Conference on Healthcare Informatics (ICHI) | August 12, 2026 | Volume: No volume available | Issue: No issue available | Pages: 386-395

10.1109/ichi69079.2026.00057 Get It

Combined FAK and MEK inhibition suppresses chromosome 8 gain malignant peripheral nerve sheath tumors
Wang, Guangfeng , Wang, Jiawan , Zhang, Xiaochun, Yang, Liuzhan , Oztosun, Gorkem, Sears, James J., Xiao, Ke , Garana, Belinda B., Zoberi, Mark I., Bektas, Aaron U., Coma, Silvia, Pachter, Jonathan A. , Gosline, Sara JC, Pratilas, Christine A. , Szymanski, Jeffrey J. , Borcherding, Dana C. , Zhang, Xiaochun, Oztosun, Gorkem , Sears, James J. , Garana, Belinda B. , Rathore, Richa , Coma, Silvia, Gosline, Sara J.C. , Hirbe, Angela C.

Journal of Clinical Investigation | August 11, 2026 | Volume: No volume available | Issue: No issue available | Pages: No page available

10.1172/jci201331 | PMID 42579369 Get It

Aneuploidy is a hallmark of cancer often associated with inferior prognosis. Copy number gains of chromosome 8 (chr8) are recurrent in multiple cancers, including breast, prostate, colorectal cancers, and sarcomas such as malignant peripheral nerve sheath tumors (MPNSTs). MPNSTs are aggressive, hard-to-treat sarcomas frequently linked to the Neurofibromatosis type 1 (NF1) cancer predisposition syndrome. To investigate the role of chr8 gain in MPNST pathogenesis, we performed a CRISPR knockout screen and identified 58 essential genes on chr8, including PTK2, which encodes focal adhesion kinase (FAK). We evaluated FAK as a therapeutic target and tested small-molecule FAK inhibitors (FAKi) alone or combined with RAF/MEK inhibitors (RAF/MEKi), a class of agents relevant to NF1-deficient tumors with ERK pathway hyperactivation. Both pharmacological and genetic inhibition of FAK reduced MPNST cell proliferation in vitro and tumor growth in vivo. Combined FAKi and RAF/MEKi treatment further suppressed phosphorylation of FAK, STAT3, and AKT while increasing cleaved caspase-3 and PARP-1, indicating enhanced apoptosis. In MPNST patient-derived xenograft (PDX) models, combination therapy significantly reduced tumor growth, showing superior efficacy, particularly in chr8 gain MPNST-PDX. These results support FAK/RAF/MEK co-targeting as a promising therapeutic strategy for chr8 gain MPNST and related tumors.
Cellular Viability of Whole Blood Specimens Is a Sensitive Indicator of Transport Conditions
Ennis, Scott M, Yang, Yifei , Akha, Amir A. Sadighi, Kumánovics, Attila, Sadighi Akha, Amir A , Kumánovics, Attila

Archives of Pathology & Laboratory Medicine | August 8, 2026 | Volume: No volume available | Issue: No issue available | Pages: No page available

10.5858/arpa.2026-0046-oa | PMID 42567537 Get It

Context.— Transporting specimens can expose them to uncontrolled environmental factors. Whole blood viability is a commonly used preanalytic marker of quality for analysis of white blood cells. Objective.— To evaluate whole blood viability as a marker for transportation and specimen integrity for lymphocyte subset evaluation. Design.— More than 9000 whole blood specimens, transported during a 4-year period, and their lymphocyte subset evaluation results were analyzed retrospectively. Viability was measured by using Cellaca MX imaging cytometer, and lymphocyte and lymphocyte subset counts were determined with flow cytometry. Specimen cell viability results were stratified based on different transportation factors to discern their potential effects. Lymphocyte subset evaluation results from specimens with lower viability were compared with those from optimal viability specimens. Results.— Cell viability of transported specimens exhibited seasonal variation, decreasing during the warm summer months (median, 77.0% versus 83.4% in other seasons). The decline in viability negatively correlated with ambient temperature during transportation ( r = −0.7876). Longer transportation time (>60 hours) also caused a decrease in viability (median, 64.0%). While we observed a decrease in absolute cell counts for CD45 + lymphocytes, CD3 + T cells, CD8 + T cells, and CD19 + B cells in specimens with low viability (50%–80%), the differences were well within the assay’s total allowable error. Conclusions.— Control of preanalytic factors is critical for laboratory testing. Whole blood viability is a sensitive indicator of transport conditions and time, but it is not a specific predictor of quality for the main lymphocyte populations in cellular immunology testing.
Generative AI, foundation models and large language models in radiation therapy physics: Clinical applications, challenges, and future directions
Qi, X. Sharon, Wang, Yi, Yang, Xiaofeng, Ren, Lei , Liu, Wei, Benedict, Stanley , Xiao, Ying , Xing, Lei , Naqa, Issam M. El, Qi, X. Sharon , Qi, X. Sharon, Yang, Xiaofeng

Medical Physics | August 7, 2026 | Volume: 53 | Issue: 8 | Pages: No page available

10.1002/mp.70616 | PMID 42563397 Get It

Abstract Generative AI (Gen AI), Foundation Models (FMs), and Large Language Models (LLMs) are powerful emerging technologies that demonstrate exceptional capabilities in processing vast amounts of unstructured and structured data, including text, voice, images, video and other formats, and adapting to a wide range of specific tasks. Their immense potential to drive meaningful improvements in treatment outcomes is increasingly evident. The advent of these technologies has marked a transformative era in healthcare, including the fields of radiation oncology and medical physics. Specifically, these powerful technologies offer unprecedented opportunities to analyze domain‐specific data, process and synthesize medical images, automate routine tasks, support clinical decision‐making, optimize and streamline clinical workflows, and enhance the quality of clinical trials. While these emerging technologies present new opportunities to revolutionize radiation therapy practice, their implementation also raises important educational, ethical, and regulatory considerations. This scoping review highlights benefits, promises, risks, and challenges, such as interpretability, data privacy, regulatory compliance, reproducibility, hallucination, and integration into existing clinical workflow. Finally, emerging opportunities are outlined to guide future research directions. This review paper provides a timely overview of Gen AI, FMs and LLMs, aiming to inform medical physicists, clinicians, and researchers of the evolving role of these disruptive technologies in shaping the future of radiation therapy.
With no lysine kinase 1 in hepatic stellate cells promotes mouse and human liver fibrosis through glycolytic triosephosphate isomerase 1
Firdaus, Zeba , Khanal, Shalil , Washington, Alexander M. , Solverson, Jasper K. , Doskey, Luke C. , Xiao, Yang, Yaqubi, Mehdi, Heimbach, Julie, Taner, Timuçin, Krueger, Eugene W., Shah, Vijay H., Starlinger, Patrick P., Schellenberg, Matthew J. , Heimbach, Julie K. , Pereyra, David , Heimbach, Julie K , Taner, Timucin , Krueger, Eugene W , Huang, Chou-Long , Starlinger, Patrick , Razidlo, Gina L , Schellenberg, Matthew , Kostallari, Enis , Washington, Alexander M , Pereyra, David , Taner, Timuçin , Krueger, Eugene W. , Huang, Chou‐Long , Shah, Vijay H , Starlinger, Patrick , Razidlo, Gina L. , Kostallari, Enis

Hepatology | August 6, 2026 | Volume: No volume available | Issue: No issue available | Pages: No page available

10.1097/hep.0000000000001833 | PMID 42560363 Get It

Background and Aims: Liver fibrosis and cirrhosis are major global health burdens with limited treatments. Activated HSCs drive fibrosis through increased proliferation, migration, collagen deposition and glycolysis. The aim of this study is to elucidate the signaling events that lead to enhanced glycolysis, subsequent HSC activation, and liver fibrosis. Approach and Results: Utilizing a phospho-kinase array, we identified with no lysine kinase 1 (WNK1) as a new kinase in primary human HSCs activated by the profibrotic PDGF-B. PDGF-mediated glycolysis in HSCs was attenuated by the WNK1 selective inhibitor, WNK-IN-11, as measured by live-cell metabolic assay, Glifon-300 fluorescence, Glucose-Glo assay, and glucose transporter 1 immunofluorescence. To understand how WNK1 promotes glycolysis, we employed chemical genetics where an engineered WNK1 carrying threonine 301 to glycine mutation (WNK1 T301G ) mutant with a modified ATP pocket accommodated a specific ATP-γ-S analogue to thio-phosphorylate its substrates. Thio-phosphorylated proteins were analyzed by mass spectrometry, which identified the glycolytic protein, triosephosphate isomerase 1 (TPI1), as a novel WNK1 direct substrate. TPI1 interacted with WNK1 in condensates, membrane-less phase separation structures. Condensate disruption and knockdown of TPI1 or WNK1 reduced HSC proliferation and migration in vitro. In vivo, pharmacological or genetic WNK1 inhibition significantly attenuated liver fibrosis in carbon tetrachloride and high-fat, choline-deficient, L -amino acid diet mouse models. Finally, WNK1 inhibition reduced fibrogenesis ex vivo in human precision-cut liver slices. Conclusions: These findings identify WNK1 as a previously unrecognized kinase that promotes HSC activation and liver fibrosis via TPI1-mediated glycolysis, highlighting the WNK1-TPI1 axis as a potential therapeutic target.
A Shared Systemic Metabolic Signature Across the Neurological Disease Spectrum: A Summary-Level Analysis of 274,241 UK Biobank Participants
Yang, Likun, Lin, Wei , Mirsattari, Seyed M., Mirsattari, Seyed M.

Biomedicines | August 6, 2026 | Volume: 14 | Issue: 8 | Pages: 1773

10.3390/biomedicines14081773 | PMID 42652156 Get It

Background: Neurological diseases share overlapping systemic and molecular features, but the specificity and interpretation of cross-disease metabolomic signatures remain uncertain. Methods: We analyzed summary-level Nightingale NMR metabolomic and genetic data from 274,241 UK Biobank participants across eight neurological endpoints. The disease rankings used here were derived from baseline plasma metabolites predicting future incident disease rather than from contemporaneous diagnostic case–control contrasts. Results: Among 57 priority metabolites with genome-wide significant instruments (2472 SNPs; mean F = 162.4), nine ranked in the top 30 for at least seven of the eight endpoints, defining a shared pre-diagnostic neurological signature confirmed as non-random cross-endpoint convergence by permutation testing (p < 0.0001). Because we did not perform a quantitative non-neurological disease control analysis, this signature should not be interpreted as neurologically specific and may partly reflect systemic morbidity, renal function, body composition, or frailty-related physiology. Forward Mendelian randomization across 45 metabolite–disease pairs found no Bonferroni-significant causal effects; three nominal protective associations are consistent with the number of false-positive findings expected under multiple testing and require replication. Conclusions: These results support a shared systemic, pre-diagnostic metabolic signature across the neurological disease spectrum, while the null MR findings and specificity limitations favor interpretation as a biomarker or prodromal downstream signal rather than a proven causal mechanism. External prospective validation is essential.
Clinical Functional Assignment of TPMT and NUDT15 Alleles by the Clinical Pharmacogenetics Implementation Consortium Pharmacogene Curation Expert Panel
Tibben, Bailey M. , Maillard, Maud , Pratt, Victoria M. , Moyer, Ann M. , Figueroa, Debbie M. , Gaedigk, Andrea , Stocco, Gabriele , Schwab, Matthias , Caudle, Kelly E. , Whirl-Carrillo, Michelle , Gaedigk, Andrea , Stocco, Gabriele , Schwab, Matthias , Caudle, Kelly E , Yang, Jun J.J. , Maillard, Maud , Figueroa, Debbie M , Whirl‐Carrillo, Michelle

Clinical Pharmacology & Therapeutics | August 6, 2026 | Volume: No volume available | Issue: No issue available | Pages: No page available

10.1002/cpt.70433 | PMID 42560154 Get It

The Clinical Pharmacogenetics Implementation Consortium (CPIC) TPMT/NUDT15 Pharmacogene Curation Expert Panel (PCEP) conducted a comprehensive review of clinical, laboratory, and computational evidence to determine the clinical function assignments for TPMT and NUDT15 star alleles. These genes are critical for the metabolism of thiopurines, which are widely used in the treatment of cancer and autoimmune disorders. Standardized allele function assignment is essential for predicting metabolizer phenotypes and pharmacogenetics‐guided thiopurine dosing. The work presented here includes the first designation of decreased function alleles for both TPMT and NUDT15 , reflecting new clinical data that demonstrate partial loss of enzymatic activity and reduced dose tolerance. The panel also reclassified several alleles previously assigned uncertain or unknown function. The functional assignments were informed by a standardized framework incorporating clinical data, such as thiopurine tolerance and toxicity, as well as in vitro protein activity, ex vivo enzymatic measurements, and in silico variant effect prediction tools. These updates enhance the precision of genotype‐to‐phenotype mapping and support more personalized thiopurine therapy across diverse patient populations.
TNK1 is a targetable JAK-independent driver of STAT signaling and inflammation
Scott, Samuel, Vaughan, Alec , Egbert, Christina M., Chan, Tsz‐Yin, Bustos, Yaphet , Ashworth, Spencer, Truman, Jacob M., Moreno, Angela Per, Tsang, Tsz‐Ming, Jayatunge, Dasun N., Yang, Jingshu, Nelson, Paige, Al-Sudani, Fatima, Tarara, Madelyn, Kohler, Emmalee, Mendiola, Nelson E. Pereira, Soderblom, Erik J. , Kolasangiani, Reza , Dobish, Kasidy K., Knobel, Beate, Buckley, Shannon M., Bidone, Tamara C., Morawe, Mareen , Armacki, Milena , Andersen, Joshua L., Stewart, Paul A , Smoot, Rory L , López-Palacios, Tania P. , Madhusanka, Deshan , Scott, Samuel M., Egbert, Christina M. , Truman, Jacob, Jayatunge, Dasun , Nelson, Paige, Stubben, Chris , Buckley, Shannon M. , Bidone, Tamara C. , Smoot, Rory L. , Uchida, Amiko M. , Andersen, Joshua L.

Genes & Development | August 3, 2026 | Volume: No volume available | Issue: No issue available | Pages: No page available

10.1101/gad.353368.125 | PMID 42547268 Get It

Deregulated inflammatory signaling via STAT family transcription factors, particularly STAT1, underlies a variety of immune-related diseases, including inflammatory bowel disease. Whereas activation of STATs by JAKs via canonical receptor-driven JAK–STAT signaling is well understood, little is known about JAK-independent mechanisms of STAT activation. Here, we identify the understudied nonreceptor tyrosine kinase TNK1 as a therapeutically targetable, JAK-independent activator of STAT signaling. Using a multiomics approach, we mapped a network of TNK1 substrates associated with protein condensates and proinflammatory signaling, including STAT1. We found that TNK1, but not its sister kinase ACK1, directly phosphorylates STATs at well described STAT-activating JAK sites. In cells, TNK1-mediated STAT1 phosphorylation and activation occurs independently of JAKs. Imaging and interactomics data suggest that TNK1 interacts with STAT1 in cytosolic condensates, which likely compartmentalize TNK1-substrate interactions. We show that an intrinsically disordered proline-rich region in TNK1, which includes a 14-3-3 docking phosphorylation site, is required for the formation of kinase-active TNK1 condensates and STAT1 phosphorylation. Mutations within the proline-rich region that eliminate 14-3-3 binding increase formation of TNK1 condensates, suggesting a model in which 14-3-3 acts as a clamp that constrains the flexible PRR to inhibit condensate formation and STAT1 activation. Finally, we show that TNK1 is a targetable driver of STAT1-mediated inflammation in the gut as inhibition of TNK1 reduces active STAT1 in the colon and ameliorates colitis symptoms in mice.