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Inferring demographic and selective histories from population genomic data using a two-step approach in species with coding-sparse genomes: an application to human data.
G3 (Bethesda)
January 2025
School of Life Sciences, Center for Evolution & Medicine, Arizona State University, Tempe, AZ 85281, USA.
The demographic history of a population, and the distribution of fitness effects (DFE) of newly arising mutations in functional genomic regions, are fundamental factors dictating both genetic variation and evolutionary trajectories. Although both demographic and DFE inference has been performed extensively in humans, these approaches have generally either been limited to simple demographic models involving a single population, or, where a complex population history has been inferred, without accounting for the potentially confounding effects of selection at linked sites. Taking advantage of the coding-sparse nature of the genome, we propose a 2-step approach in which coalescent simulations are first used to infer a complex multi-population demographic model, utilizing large non-functional regions that are likely free from the effects of background selection.
View Article and Find Full Text PDFNovel genetic insight for psoriasis: integrative genome-wide analyses in 863 080 individuals and proteome-wide Mendelian randomization.
Brief Bioinform
November 2024
Department of Dermatology, Daping Hospital, Army Medical University, No. 10, Changjiang Branch Road, Yuzhong District, Chongqing 400042, China.
Psoriasis affects a significant proportion of the worldwide population and causes an extremely heavy psychological and physical burden. The existing therapeutic schemes have many deficiencies such as limited efficacies and various side effects. Therefore, novel ways of treating psoriasis are urgently needed.
View Article and Find Full Text PDFA model of care redesign within rheumatology: A mixed methods approach integrating nurse practitioners and physician assistants.
J Am Assoc Nurse Pract
January 2025
Division of Cardiology, Department of Medicine, Duke Health Integrated Practice, Duke University Health System, Durham, North Carolina.
Background: Increasing patient demand and clinician burnout in rheumatology practices have highlighted the need for more efficient models of care (MOC). Interprofessional collaboration is essential for improving patient outcomes and clinician satisfaction.
Local Problem: Our current MOC lacks standardization and formal integration of Nurse Practitioners (NPs) and Physician Assistants (PAs), resulting in reduced clinician satisfaction and limited patient access.
The diagnostic performance and optimal strategy of cone beam CT-assisted bronchoscopy for peripheral pulmonary lesions: A systematic review and meta-analysis.
Pulmonology
December 2025
Guangzhou Institute of Respiratory Health, State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, National Center for Respiratory Medicine, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China.
Cone-beam computed tomography (CBCT) assisted bronchoscopy shows prospective advantages in diagnosing peripheral pulmonary lesions (PPLs), but its diagnostic value and potential influencing factors remain unclear. What is the clinical value and optimal strategy of CBCT-assisted bronchoscopy in diagnosing PPLs? The references were searched from PubMed, EmBase, and Web of Science. Studies reporting diagnostic yield and potential influencing factors of CBCT-assisted bronchoscopy were included.
View Article and Find Full Text PDFUsing Large Language Models to Detect and Understand Drug Discontinuation Events in Web-Based Forums: Development and Validation Study.
J Med Internet Res
January 2025
Department of Industrial and Systems Engineering, The University of Florida, GAINESVILLE, FL, United States.
Background: The implementation of large language models (LLMs), such as BART (Bidirectional and Auto-Regressive Transformers) and GPT-4, has revolutionized the extraction of insights from unstructured text. These advancements have expanded into health care, allowing analysis of social media for public health insights. However, the detection of drug discontinuation events (DDEs) remains underexplored.
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