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arXiv 2024年

作者： Wu, Ethan Ellington, Caleb Lengerich, Ben Xing, Eric P. Medical Scientist Training Program Pitt School of Medicine United States Carnegie Mellon University United States University of Wisconsin Madison United States MBZUAI CMU Petuum Inc United States

Tuberculosis (TB) is a major global health challenge, and is compounded by co-morbidities such as HIV, diabetes, and anemia, which complicate treatment outcomes and contribute to heterogeneous patient responses. Traditional models of TB often overlook this heterogeneity by focusing on broad, pre-defined patient groups, thereby missing the nuanced effects of individual patient contexts. We propose moving beyond coarse subgroup analyses by using contextualized modeling, a multi-task learning approach that encodes patient context into personalized models of treatment effects, revealing patient-specific treatment benefits. Applied to the TB Portals dataset with multi-modal measurements for over 3,000 TB patients, our model reveals structured interactions between co-morbidities, treatments, and patient outcomes, identifying anemia, age of onset, and HIV as influential for treatment efficacy. By enhancing predictive accuracy in heterogeneous populations and providing patient-specific insights, contextualized models promise to enable new approaches to personalized treatment. © 2024, CC BY.

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Long noncoding RNA(lncRNA)H19:An essential developmental regulator with expanding roles in cancer,stem cell differentiation,and metabolic diseases

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Genes & Diseases 2023年第4期10卷 1351-1366页

作者： Junyi Liao Bowen Chen Zhenglin Zhu Chengcheng Du Shengqiang Gao Guozhi Zhao Piao Zhao Yonghui Wang Annie Wang Zander Schwartz Lily Song Jeffrey Hong William Wagstaff Rex CHaydon Hue HLuu Jiaming Fan Russell RReid Tong-Chuan He Lewis Shi Ning Hu Wei Huang Departments of Orthopedic Surgery and Urology The First Affiliated Hospital of Chongqing Medical UniversityChongqing 400016China Orthopedic Research Center Chongqing Medical UniversityChongqing 400016China Molecular Oncology Laboratory Department of Orthopaedic Surgery and Rehabilitation MedicineThe University of Chicago Medical CenterChicagoIL 60637USA Department of Clinical Laboratory Medicine Shanghai Jiaotong University School of MedicineShanghai 200000China School of Biomedical Engineering Vanderbilt UniversityNashvilleTN 37235USA The Medical Scientist Training Program The University of Chicago Pritzker School of MedicineChicagoIL 60637USA Ministry of Education Key Laboratory of Diagnostic Medicine Department of Clinical BiochemistryThe School of Laboratory MedicineChongqing Medical UniversityChongqing 400016China Laboratory of Craniofacial Suture Biology and Development Department of Surgery Section of Plastic SurgeryThe University of Chicago Medical CenterChicagoIL 60637USA

Recent advances in deep sequencing technologies have revealed that,while less than 2%of the human genome is transcribed into mRNA for protein synthesis,over 80%of the genome is transcribed,leading to the production of large amounts of noncoding RNAs(ncRNAs).It has been shown that ncRNAs,especially long non-coding RNAs(lncRNAs),may play crucial regulatory roles in gene *** one of the first isolated and reported lncRNAs,H19 has gained much attention due to its essential roles in regulating many physiological and/or pathological processes including embryogenesis,development,tumorigenesis,osteogen-esis,and ***,H19 mediates diverse regulatory functions by serving as competing endogenous RNAs(CeRNAs),Igf2/H19 imprinted tandem gene,modular scaffold,cooperating with H19 antisense,and acting directly with other mRNAs or ***,we summarized the current understanding of H19 in embryogenesis and development,cancer development and progression,mesenchymal stem cell lineage-specific differentiation,and metabolic *** discussed the potential regulatory mechanisms underlying H19’s func-tions in those processes although more in-depth studies are warranted to delineate the exact molecular,cellular,epigenetic,and genomic regulatory mechanisms underlying the physiolog-ical and pathological roles of ***,these lines of investigation may lead to the development of novel therapeutics for human diseases by exploiting H19 functions.

关键词： Cancer Epigenetic regulation H19 LncRNA Long-noncoding RNA Metabolic diseases Stem cell differentiation

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An intracranial mass causing tumor-induced osteomalacia (TIO): Rapid and complete resolution of severe osteoporosis after surgical resection

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Radiology Case Reports 2020年第5期15卷 492-497页

作者： Colazo, Juan M. Thompson, Reid C. Covington, Natalie V. Dahir, Kathryn M. Medical Scientist Training Program Vanderbilt University Medical Center 2nd Floor Eskind Biomedical Library and Learning Center Vanderbilt University School of Medicine 2209 Garland Avenue Nashville 37240 TN United States Department of Biomedical Engineering Vanderbilt University 2301 Vanderbilt Place PMB351826 Nashville 37235 TN United States Department of Neurological Surgery Vanderbilt University Medical Center T-4224F Medical Center North 1161 21st Avenue South Nashville 37232 TN United States Hearing and Speech Sciences Vanderbilt University Medical Center Nashville TN United States Vanderbilt University Medical Center Program for Metabolic Bone Disorders at Vanderbilt Endocrinology and Diabetes 8210 Medical Center East 1215 21st Avenue South Nashville 37232 TN United States

Tumor-induced osteomalacia (TIO) is a rare disease in which patients suffer from fractures and progressive disabling bone pain and muscle weakness. TIO is caused by the hypersecretion of Fibroblast Growth Factor 23 (FGF23) from rare neoplasms of mesenchymal origin. This case report describes a 29-year-old male with 2 years of low back/hip pain, gait changes, proximal muscle weakness, and multiple stress fractures. Bone densitometry was remarkable for severe osteoporosis, hypophosphatemia was seen on routine labs, and advanced labs demonstrated an “inappropriately normal” FGF23 level. A 68Ga-DOTATATE scan and MRI showed a 1.3 × 1.1 × 1.0 cm intracranial mass. The patient underwent tumor resection by Neurosurgery. Shortly after, laboratory levels normalized, and the patient's symptoms improved drastically. This case exemplifies the notion that TIO can be caused by FGF23 levels within normal limits, the role of 68-Ga DOTATATE imaging for establishing a diagnosis, and that these tumors can arise anywhere—even intracranially. We also review current surgical and nonsurgical treatment options, as well as emerging novel therapeutics. © 2020

关键词： 68Ga-DOTATATE Burosumab DXA Fibroblast growth factor 23 MRI Paraneoplastic syndrome TIO Tumor-induced osteomalacia

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Relative Sparsity for medical Decision Problems

arXiv

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arXiv 2022年

作者： Weisenthal, Samuel J. Thurston, Sally W. Ertefaie, Ashkan Department of Biostatistics and Computational Biology University of Rochester School of Medicine and Dentistry RochesterNY United States Medical Scientist Training Program University of Rochester School of Medicine and Dentistry RochesterNY United States

Existing statistical methods can estimate a policy, or a mapping from covariates to decisions, which can then instruct decision makers (e.g., whether to administer hypotension treatment based on covariates blood pressure and heart rate). There is great interest in using such data-driven policies in healthcare. However, it is often important to explain to the healthcare provider, and to the patient, how a new policy differs from the current standard of care. This end is facilitated if one can pinpoint the aspects of the policy (i.e., the parameters for blood pressure and heart rate) that change when moving from the standard of care to the new, suggested policy. To this end, we adapt ideas from Trust Region Policy Optimization (TRPO). In our work, however, unlike in TRPO, the difference between the suggested policy and standard of care is required to be sparse, aiding with interpretability. This yields "relative sparsity," where, as a function of a tuning parameter, λ, we can approximately control the number of parameters in our suggested policy that differ from their counterparts in the standard of care (e.g., heart rate only). We propose a criterion for selecting λ, perform simulations, and illustrate our method with a real, observational healthcare dataset, deriving a policy that is easy to explain in the context of the current standard of care. Our work promotes the adoption of data-driven decision aids, which have great potential to improve health outcomes. © 2022, CC BY.

关键词： Blood pressure

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The Hippo Pathway in Liver Homeostasis and Pathophysiology

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Pathology: Mechanisms of Disease 1000年第1期16卷 299-322页

作者： Jordan H. Driskill Duojia Pan 2Medical Scientist Training Program University of Texas Southwestern Medical Center Dallas Texas 75390 USA 1Department of Physiology Howard Hughes Medical Institute University of Texas Southwestern Medical Center Dallas Texas 75390 USA email: Jordan.Driskill@UTSouthwestern.eduDuojia.Pan@UTSouthwestern.edu

Studies of the regenerative capacity of the liver have converged on the Hippo pathway, a serine/threonine kinase cascade discovered in Drosophila and conserved from unicellular organisms to mammals. Genetic studies of mouse and rat livers have revealed that the Hippo pathway is a key regulator of liver size, regeneration, development, metabolism, and homeostasis and that perturbations in the Hippo pathway can lead to the development of common liver diseases, such as fatty liver disease and liver cancer. In turn, pharmacological targeting of the Hippo pathway may be utilized to boost regeneration and to prevent the development and progression of liver diseases. We review current insights provided by the Hippo pathway into liver pathophysiology. Furthermore, we present a path forward for future studies to understand how newly identified components of the Hippo pathway may control liver physiology and how the Hippo pathway is regulated in the liver.

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Inference for relative sparsity

arXiv

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arXiv 2023年

In healthcare, there is much interest in estimating policies, or mappings from covariates to treatment decisions. Recently, there is also interest in constraining these estimated policies to the standard of care, which generated the observed data. A relative sparsity penalty was proposed to derive policies that have sparse, explainable differences from the standard of care, facilitating justification of the new policy. However, the developers of this penalty only considered estimation, not inference. Here, we develop inference for the relative sparsity objective function, because characterizing uncertainty is crucial to applications in medicine. Further, in the relative sparsity work, the authors only considered the single-stage decision case;here, we consider the more general, multi-stage case. Inference is difficult, because the relative sparsity objective depends on the unpenalized value function, which is unstable and has infinite estimands in the binary action case. Further, one must deal with a non-differentiable penalty. To tackle these issues, we nest a weighted Trust Region Policy Optimization function within a relative sparsity objective, implement an adaptive relative sparsity penalty, and propose a sample-splitting framework for post-selection inference. We study the asymptotic behavior of our proposed approaches, perform extensive simulations, and analyze a real, electronic health record dataset. © 2023, CC BY.

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Systems genetic dissection of Alzheimer's disease brain gene expression networks

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Alzheimer's & dementia : the journal of the Alzheimer's Association 2021年第S2期17卷 e058716页

作者： Zhao, Pinghan Mangleburg, Carl Grant Al-Ramahi, Ismael Botas, Juan Shulman, Joshua M. Baylor College of Medicine TX Houston United States Jan and Dan Duncan Neurological Research Institute Texas Children's Hospital TX Houston United States Baylor College of Medicine Neuroscience Program TX Houston United States Baylor College of Medicine Medical Scientist Training Program TX Houston United States

BACKGROUND: Alzheimer's disease (AD) is the most prevalent cause of dementia. Large RNA-Sequencing data sets have provided detailed molecular profiles of AD, but they cannot differentiate causal vs. non-causal gene expression changes. METHOD: We combined bioinformatic prioritization of human data with genetic screens in Drosophila melanogaster to identify human brain transcriptional changes that exacerbate or ameliorate neurodegeneration induced by Tau or amyloid-β (Aβ), the proteins which form the hallmark pathologic aggregates that define AD. First, we used large, AD-associated coexpression networks derived from Accelerating Medicines Partnership (AMP)-AD human brain RNA-Seq data to nominate candidate AD drivers based on multiple bioinformatic criteria. We then tested nominated drivers for modification of Tau- or Aβ-induced neurodegeneration in vivo using a locomotor assay in Drosophila. For one module of our interest, PHGbrown, we analyzed its overlap with published differentially expressed gene (DEG) sets from mouse models to explore its potential functional roles in AD. Finally, we used the L1000 Connectivity Map database of perturbation-associated gene expression changes to select small molecules which either reverse or promote the implicated AD-associated gene expression signatures that are causally linked with disease progression. RESULT: Through our screen, we identified a module, PHGbrown, with 14 of its 27 prioritized genes (51.9%) significantly modifying Tau/Aβ neurotoxicity in our screen. We integrated our screen data with PHGbrown's module structure to identify a subnetwork containing genes involved in synaptic function including GRIN2A, GRIN2B, KCNJ6, GABRB2, and GABRB3. This synaptic subnetwork is downregulated in human AD and contains multiple loss-of-function suppressors of Tau/Aβ neurotoxicity. Interestingly, PHGbrown shows overlap and concordant down-regulation with published mouse models of excitotoxicity. Our results suggest that PHGbrown down-

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Editorial Commentary: Preventing Malaria in HIV-Infected Pregnant Women

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Clinical Infectious Diseases 2014年第5期58卷 660-662页

作者： Bulterys, Philip L. Kaplan, Jonathan E. Gutman, Julie UCLA-Caltech Medical Scientist Training Program David Geffen School of Medicine University of California Los Angeles Division of Global HIV/AIDS Division of Parasitic Diseases and Malaria Center for Global Health Centers for Disease Control and Prevention Atlanta Georgia

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NF-κB memory coordinates transcriptional responses to dynamic inflammatory stimuli

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Cell Reports 2022年第7期40卷 000-000页

作者： Wang, Andrew G. Son, Minjun Kenna, Emma Thom, Nicholas Tay, Savaş Pritzker School of Molecular Engineering University of Chicago Chicago 60637 IL United States Medical Scientist Training Program University of Chicago Chicago 60637 IL United States

Many scenarios in cellular communication require cells to interpret multiple dynamic signals. It is unclear how exposure to inflammatory stimuli alters transcriptional responses to subsequent stimulus. Using high-throughput microfluidic live-cell analysis, we systematically profile the NF-κB response to different signal sequences in single cells. We find that NF-κB dynamics store the short-term history of received signals: depending on the prior pathogenic or cytokine signal, the NF-κB response to subsequent stimuli varies from no response to full activation. Using information theory, we reveal that these stimulus-dependent changes in the NF-κB response encode and reflect information about the identity and dose of the prior stimulus. Small-molecule inhibition, computational modeling, and gene expression profiling show that this encoding is driven by stimulus-dependent engagement of negative feedback modules. These results provide a model for how signal transduction networks process sequences of inflammatory stimuli to coordinate cellular responses in complex dynamic environments. © 2022 The Authors

关键词： cellular memory CP: Immunology inflammation information theory innate immune signaling live-cell imaging mathematical modeling microfluidics NF-κB pathogen-associated molecular patterns signaling dynamics

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Personalized Taste and Cuisine Preference Modeling via Images

arXiv

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arXiv 2020年

作者： Nag, Nitish Rajanna, Bindu Jain, Ramesh Donald Bren School of Information and Computer Science University of California Irvine United States Department of Computer Science PES University Medical Scientist Training Program School of Medicine University of California Irvine United States

— With the exponential growth in the usage of social media to share live updates about life, taking pictures has become an unavoidable phenomenon. Individuals unknowingly create a unique knowledge base with these images. The food images, in particular, are of interest as they contain a plethora of information. From the image metadata and using computer vision tools, we can extract distinct insights for each user to build a personal profile. Using the underlying connection between cuisines and their inherent tastes, we attempt to build such a profile for an individual based solely on the images of his food. Our study provides insights about an individual’s inclination towards a certain cuisine. Interpreting these insights can lead to the development of a more precise recommendation system. Such a system would avoid the generic approach in favor of a personalized system. Copyright © 2020, The Authors. All rights reserved.

关键词： Knowledge based systems

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