This study evaluated the validity and test-retest reliability of a resistance training device Jueying (Beijing, China) for Smith machine back squat exercise. Twelve male participants completed two test sessions with an interval of one week. In each test session, participants completed 30%, 45%, 60%, and 75% of 1RM back squats on a Smith machine equipped with Jueying and a linear position transducer GymAware (Canberra, Australia), which measured the velocity and power during the movement simultaneously. Results showed that Jueying was both valid (Pearson correlation coefficient [r] = 0.896-0.999, effect size [ES] = 0.004-0.192) when compared with GymAware and consistent between two tests in terms of reliability (intraclass correlation coefficient [ICC] = 0.79-0.95) to assess speed and power within all exercises. The device could be applied to provide athletes and coaches with effective and reliable data in actual application.
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http://dx.doi.org/10.1016/j.isci.2023.108582 | DOI Listing |
Cancer Cell
December 2024
Department of Epigenetics, Van Andel Institute, Grand Rapids, MI 49503, USA. Electronic address:
Molecular subtypes, such as defined by The Cancer Genome Atlas (TCGA), delineate a cancer's underlying biology, bringing hope to inform a patient's prognosis and treatment plan. However, most approaches used in the discovery of subtypes are not suitable for assigning subtype labels to new cancer specimens from other studies or clinical trials. Here, we address this barrier by applying five different machine learning approaches to multi-omic data from 8,791 TCGA tumor samples comprising 106 subtypes from 26 different cancer cohorts to build models based upon small numbers of features that can classify new samples into previously defined TCGA molecular subtypes-a step toward molecular subtype application in the clinic.
View Article and Find Full Text PDFAlzheimers Dement
December 2024
University of Florida, Gainesville, FL, USA.
Background: Remote administration of well-established neuropsychological instruments (TeleNeuropsychological or TeleNP) can reduce assessment wait times and expand access to cognitive assessments for medically compromised and socially disadvantaged patients. A major limitation in the widespread uptake of TeleNP relates to the need for more normative data compared to in-person assessments. This presentation describes a novel ascertainment strategy used in Florida's Older Adults TeleNeuropsychology (FLOAT) project to identify and recruit "cognitively healthy" older adults to norm well-established neuropsychological instruments administered remotely.
View Article and Find Full Text PDFJ Bone Miner Res
January 2025
Departments of Medicine and Radiology, University of Manitoba, Winnipeg, Canada.
Vertebral fracture assessment (VFA) images from bone density machines enable the automated machine learning assessment of abdominal aortic calcification (ML-AAC), a marker of cardiovascular disease (CVD) risk. The objective of this study was to describe the risk of a major adverse cardiovascular event (MACE, from linked health records) in patients attending routine bone mineral density (BMD) testing and meeting specific criteria based on age, BMD, height loss, or glucocorticoid use have a VFA in the Manitoba Bone Mineral Density Registry. The cohort included 10 250 individuals (mean 75.
View Article and Find Full Text PDFPharmacotherapy
January 2025
Department of Clinical and Administrative Pharmacy, University of Georgia College of Pharmacy, Athens, Georgia, USA.
Background: Fluid overload (FO) in the intensive care unit (ICU) is common, serious, and may be preventable. Intravenous medications (including administered volume) are a primary cause for FO but are challenging to evaluate as a FO predictor given the high frequency and time-dependency of their use and other factors affecting FO. We sought to employ unsupervised machine learning methods to uncover medication administration patterns correlating with FO.
View Article and Find Full Text PDFBrain
January 2025
Department of Neurosurgery, University of Utah, Salt Lake City, UT 84132, USA.
Brain stimulation has, for many decades, been considered as a potential solution for the unmet needs of the many people living with drug-resistant epilepsy. Clinically, there are several different approaches in use, including vagus nerve stimulation (VNS), deep brain stimulation of the thalamus, and responsive neurostimulation (RNS). Across populations of patients, all deliver reductions in seizure load and SUDEP risk, yet do so variably, and the improvements seem incremental rather than transformative.
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