Objectives: To compare heart rate variability (HRV) among adult Hypertensive and Normotensive subjects in supine position.
Methods: It was an analytical cross sectional study conducted on two study groups. The cases (n=60) comprised of outpatients (males and females in the age group 20-50 yrs) attending the Medicine OPD of Medical Collage, Kolkata, who were newly diagnosed as cases of hypertension according to JNC seven criteria while the control group (n=50) comprised of age and sex-matched adult normotensive subjects, who were non-smokers, non-alcoholics and were not suffering from any major cardiac, neurological or chronic illnesses. HRV profiling through short-term (5 min) ECG recording of each subject was carried out in the supine position with the help of a digital ECG recording machine (RMS-Polyrite D), with a sampling rate of 256 Hz. From the data so collected, various HRV parameters - both time domain (SDNN, RMSSD, NN50 and pNN50) and frequency domain (VLF, LF and HF) were calculated. Analysis of these parameters revealed the pattern of autonomic influence (sympathetic or parasympathetic predominance) prevalent among the subjects of the study and control groups.
Results: An overall reduction of the time domain parameters SDNN and RMSSD (considered more as markers of sympathetic activity) and frequency domain parameters (total power, LF and HF, all expressed in ms), which are markers of parasympathetic activity, was noted among the hypertensive subjects. However, the reduction in frequency domain parameters was much more (highly significantly) than that of time domain parameters. Also, both age and hypertension had significant independent effects on HRV but their 3-way interaction was found to be statistically insignificant.
Conclusions: The findings of the study thus points towards an autonomic dysregulation (characterized by decreased vagal activity and increased sympathetic activity), as an underlying basis (i.e. an important factor, among others) for hypertension.
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http://dx.doi.org/10.1515/jbcpp-2024-0051 | DOI Listing |
Radiol Artif Intell
March 2025
Department of Radiology, Duke University Hospital, 2301 Erwin Rd, Durham, NC 27710.
Purpose To develop and evaluate an automated system for extracting structured clinical information from unstructured radiology and pathology reports using open-weights language models (LMs) and retrieval augmented generation (RAG) and to assess the effects of model configuration variables on extraction performance. Materials and Methods This retrospective study utilized two datasets: 7,294 radiology reports annotated for Brain Tumor Reporting and Data System (BT-RADS) scores and 2,154 pathology reports annotated for mutation status (January 2017 to July 2021). An automated pipeline was developed to benchmark the performance of various LMs and RAG configurations for structured data extraction accuracy from reports.
View Article and Find Full Text PDFNanomaterials (Basel)
February 2025
Department of Basic and Applied Sciences, A'Sharqiyah University, P.O. Box 42, Ibra 400, Oman.
This study investigates the thermal pinning and depinning behaviors of vortex domain walls (VWs) in constricted magnetic nanowires, focusing on the influence of intrinsic magnetic properties on VW stability under thermal stress. Using micromagnetic simulations, we analyze the roles of saturation magnetization (Ms), uniaxial magnetic anisotropy (Ku), and nanowire geometry in determining VW thermal stability. The modeled nanowire has dimensions of 200 nm (width), 30 nm (thickness), and a 50 nm constriction length, chosen based on the dependence of VW formation on nanowire geometry.
View Article and Find Full Text PDFThis study presents a novel deep learning approach for surface electromyography (sEMG) gesture recognition using stacked autoencoder neural network (SAE)s. The method leverages hierarchical representation learning to extract meaningful features from raw sEMG signals, enhancing the precision and robustness of gesture classification.•Feature Extraction and Classification MODWT Decomposition: The sEMG signals were decomposed using the MODWT DECOMPOSITION(Maximal Overlap Discrete Wavelet Transform) to capture various frequency components.
View Article and Find Full Text PDFACS Electrochem
March 2025
Institute of Physical Chemistry, University of Innsbruck, Innrain 52c, A-6020 Innsbruck, Austria.
Solid oxide cell technologies play a crucial role in climate change mitigation by enabling the reversible storage of renewable energy. Understanding the electrochemical high-temperature reaction mechanisms and the catalytic role of the electrode and electrolyte materials is essential for advancing power-to-H technologies. Despite its significance, limited spectroscopic research focusing on nickel and yttria-stabilized zirconia (Ni/YSZ) is available.
View Article and Find Full Text PDFFront Immunol
March 2025
R&D Laboratory, Diagnosticum Zrt, Budapest, Hungary.
Antigen specific humoral immunity can be characterized by the analysis of serum antibodies. While serological assays for the measurement of specific antibody levels are available, these are not quantitative in the biochemical sense. Yet, understanding humoral immune responses quantitatively on the systemic level would need a universal, complete, quantitative, comparable measurement method of antigen specific serum antibodies of selected immunoglobulin classes.
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