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Heart rate dynamics for cognitive load estimation in a driving simulation task.
Sci Rep
December 2024
Harman International, HarmanX Neurosense, 30001 Cabot Dr, Novi, MI, 48377, USA.
Cognitive load (CL) is one of the leading factors moderating states and performance among drivers. Heavily increased CL may contribute to the development of mental stress. Averaged heart rate (HR) and heart rate variability (HRV) indices are shown to reflect CL levels in different tasks.
View Article and Find Full Text PDFWhole slide image based prognosis prediction in rectal cancer using unsupervised artificial intelligence.
BMC Cancer
December 2024
Department of Radiology, The Sixth Affiliated Hospital, Sun Yat-sen University, No. 26, Yuancunerheng Road, Guangzhou, Guangdong, 510655, China.
Background: Rectal cancer is a common cancer worldwide and lacks effective prognostic markers. The development of prognostic markers by computational pathology methods has attracted increasing attention. This paper aims to construct a prognostic signature from whole slide images for predicting progression-free survival (PFS) of rectal cancer through an unsupervised artificial intelligence algorithm.
View Article and Find Full Text PDFLocation and function of TDP-43 in platelets, alterations in neurodegenerative diseases and arising considerations for current plasma biobank protocols.
Sci Rep
September 2024
Kansas City University, 1750 Independence Ave, Kansas City, MO, 64106, USA.
The TAR DNA Binding Protein 43 (TDP-43) has been implicated in the pathogenesis of human neurodegenerative diseases and exhibits hallmark neuropathology in amyotrophic lateral sclerosis (ALS). Here, we explore its tractability as a plasma biomarker of disease and describe its localization and possible functions in the cytosol of platelets. Novel TDP-43 immunoassays were developed on three different technical platforms and qualified for specificity, signal-to-noise ratio, detection range, variation, spike recovery and dilution linearity in human plasma samples.
View Article and Find Full Text PDFCombining blood pressure variability and heart rate variability to analyze the autonomic nervous function of rotenone induced Parkinson's rat model.
J Neurosci Methods
September 2024
School of Medical Engineering of Xinxiang Medical University, Xinxiang, China; Engineering Technology Research Center of Neurosense and Control of Henan Province, Xinxiang, People's Republic of China; Henan Engineering Laboratory of Combinatorial Technique for Clinical and Biomedical Big Data, Xinxiang, China; Henan International Joint Laboratory of Neural Information Analysis and Drug Intelligent Design, Xinxiang, China; The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China; Henan Collaborative Innovation Center of Prevention and treatment of mental disorder, Xinxiang, China. Electronic address:
Background: Parkinson's patients have significant autonomic dysfunction, early detect the disorder is a major challenge. To assess the autonomic function in the rat model of rotenone induced Parkinson's disease (PD), Blood pressure and ECG signal acquisition are very important.
New Method: We used telemetry to record the electrocardiogram and blood pressure signals from awake rats, with linear and nonlinear analysis techniques calculate the heart rate variability (HRV) and blood pressure variability (BPV).
Recent Progress in Mass Spectrometry-Based Single-Cell Metabolic Analysis.
Small Methods
March 2024
Department of Clinical Laboratory Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, P. R. China.
Single-cell analysis enables the measurement of biomolecules at the level of individual cells, facilitating in-depth investigations into cellular heterogeneity and precise interpretation of the related biological mechanisms. Among these biomolecules, cellular metabolites exhibit remarkable sensitivity to environmental and biochemical changes, unveiling a hidden world underlying cellular heterogeneity and allowing for the determination of cell physiological states. However, the metabolic analysis of single cells is challenging due to the extremely low concentrations, substantial content variations, and rapid turnover rates of cellular metabolites.
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