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FHIR PIT: a geospatial and spatiotemporal data integration pipeline to support subject-level clinical research.
BMC Med Inform Decis Mak
January 2025
Renaissance Computing Institute, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Background: Environmental exposures such as airborne pollutant exposures and socio-economic indicators are increasingly recognized as important to consider when conducting clinical research using electronic health record (EHR) data or other sources of clinical data such as survey data. While numerous public sources of geospatial and spatiotemporal data are available to support such research, the data are challenging to work with due to inconsistencies in file formats and spatiotemporal resolutions, computational challenges with large file sizes, and a lack of tools for patient- or subject-level data integration.
Results: We developed FHIR PIT (HL7® Fast Healthcare Interoperability Resources Patient data Integration Tool) as an open-source, modular, data-integration software pipeline that consumes EHR data in FHIR® format and integrates the data at the level of the patient or subject with environmental exposures data of varying spatiotemporal resolutions and file formats.
Impact of a new case-based payment scheme on volume distribution across public hospitals in Zhejiang, China: does 'Same disease, same price' matter.
Int J Equity Health
January 2025
Department of Health Policy and Management, School of Public Health, Hangzhou Normal University, Hangzhou, China.
Background: With the implementation of the hierarchical medical system (HMS) in China, Zhejiang Province introduced an innovative payment scheme called "payment method by disease types with point counting". This scheme was initially adopted in Jinhua in July 2017, and was later integrated with the "same disease, same price" policy in Hangzhou in January 2020. This study aimed to investigate the impact of these reforms on the distribution of health service volume.
View Article and Find Full Text PDFDynamic X-ray Microtomography vs. Laser-Doppler Vibrometry: A Comparative Study.
J Assoc Res Otolaryngol
January 2025
Department of Otorhinolaryngology, Head and Neck Surgery, Inselspital, Bern University Hospital, University of Bern, 3010, Freiburgstrasse, Bern, Switzerland.
Purpose: There are challenges in understanding the biomechanics of the human middle ear, and established methods for studying this system show significant limitations. In this study, we evaluate a novel dynamic imaging technique based on synchrotron X-ray microtomography designed to assess the biomechanical properties of the human middle ear by comparing it to laser-Doppler vibrometry (LDV).
Methods: We examined three fresh-frozen temporal bones (TB), two donated by white males and one by a Black female, using dynamic synchrotron-based X-ray microtomography for 256 and 512 Hz, stimulated at 110 dB and 120 dB sound pressure level (SPL).
Enantioselective OTUD7B fragment discovery through chemoproteomics screening and high-throughput optimisation.
Commun Chem
January 2025
Molecular Structure of Cell Signalling Laboratory, The Francis Crick Institute, London, UK.
Deubiquitinating enzymes (DUBs) are key regulators of cellular homoeostasis, and their dysregulation is associated with several human diseases. The ovarian tumour protease (OTU) family of DUBs are biochemically well-characterised and of therapeutic interest, yet only a few tool compounds exist to study their cellular function and therapeutic potential. Here we present a chemoproteomics fragment screening platform for identifying novel DUB-specific hit matter, that combines activity-based protein profiling with high-throughput chemistry direct-to-biology optimisation to enable rapid elaboration of initial fragment hits against OTU DUBs.
View Article and Find Full Text PDFDifferentiation between multiple sclerosis and neuromyelitis optic spectrum disorders with multilevel fMRI features: A machine learning analysis.
Sci Rep
January 2025
Department of Radiology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, 330006, Jiangxi, China.
The conventional statistical approach for analyzing resting state functional MRI (rs-fMRI) data struggles to accurately distinguish between patients with multiple sclerosis (MS) and those with neuromyelitis optic spectrum disorders (NMOSD), highlighting the need for improved diagnostic efficacy. In this study, multilevel functional metrics including resting state functional connectivity, amplitude of low frequency fluctuation (ALFF), and regional homogeneity (ReHo) were calculated and extracted from 116 regions of interest in the anatomical automatic labeling atlas. Subsequently, classifiers were developed using different combinations of these selected features to distinguish between MS and NMOSD.
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