Identifying Predictors of Successful Conversion from OREF Grants to Extramural Federal Funding Among Orthopaedic Surgeons.

Background: Musculoskeletal diseases are a major contributor to global human disability, but research in this area of medicine contends with chronic underfunding in the United States, receiving <2% of the National Institutes of Health (NIH) budget. The Orthopaedic Research and Education Foundation (OREF) serves as a vital nongovernmental organization, providing essential support for orthopaedic research. This study investigated the translation of various OREF grants into successful extramural federal funding discerning the clinician demographics and OREF award characteristics associated with increased chances of securing federal grants.

Alternative splicing expands the antiviral IFITM repertoire in Chinese rufous horseshoe bats.

Species-specific interferon responses are shaped by the virus-host arms race. The human interferon-induced transmembrane protein (IFITM) family consists of three antiviral IFITM genes that arose by gene duplication. These genes restrict virus entry and are key players in antiviral interferon responses.

Differential effects of stimulation waveform and intensity on the neural structures activated by lumbar transcutaneous spinal cord stimulation.

Introduction: Lumbar transcutaneous spinal cord stimulation (TSS) evokes synchronized muscle responses, termed spinally evoked motor response (sEMR). Whether the structures TSS activates to evoke sEMRs differ when TSS intensity and waveform are varied is unknown.

Methods: In 15 participants (9F:6M), sEMRs were evoked by TSS over L1-L3 (at sEMR threshold and suprathreshold intensities) using conventional (one 400-µs biphasic pulse) or high-frequency burst (ten 40-µs biphasic pulses at 10 kHz) stimulus waveforms in vastus medialis (VM), tibialis anterior (TA) and medial gastrocnemius (MG) muscles.

surtvep: An R package for estimating time-varying effects.

The surtvep package is an open-source software designed for estimating time-varying effects in survival analysis using the Cox non-proportional hazards model in R. With the rapid increase in large-scale time-to-event data from national disease registries, detecting and accounting for time-varying effects in medical studies have become crucial. Current software solutions often face computational issues such as memory limitations when handling large datasets.