We performed four cardiovascular tests of autonomic function (deep breathing, lying to standing, Valsalva manoeuvre, postural hypotension) and simultaneous 24h recordings of blood pressure (BP) and ECG in 35 normotensive diabetic subjects. Autoregressive power spectrum analysis of RR interval variability was applied to 24h ECG recordings to obtain for day and night periods power of low- (0.03-0.15 Hz, LF) and high-frequency (0.18- 0.40 Hz, HF) components, relative markers of sympathetic and vagal activity respectively, and their ratio (LF/HF), assumed as index of sympathovagal balance. Eighteen patients showed normal cardiovascular tests, 6 patients one abnormal heart rate test, 5 patients two abnormal heart rate tests, and 6 patients also abnormal postural hypotension test. In diabetic patients with increasing degree of autonomic neuropathy, there was a progressive reduction of day-night change in systolic BP (p < 0.01), of LF during the day (p < 0.01), of HF during the night (p < 0.04), of day-night change in HF (p < 0.02), and of day-night change in HF/LF (p < 0.03). Day-night change in systolic BP was related to postural hypotension (p < 0.001) and to deep breathing (p < 0.01). Day LF was related to lying to standing (p < 0.001), to postural hypotension (p < 0.005) and to deep breathing (p < 0.007). Night HF was related to deep breathing (p < 0.0002) and to lying to standing (p < 0.02). Day-night change in HF/LF was slightly related to deep breathing, lying to standing, and to postural hypotension (p < 0.04). In a multiple regression analysis including age, diabetes duration, and cardiovascular tests as independent variables, day-night change in BP and day LF were only related to postural hypotension, whereas night HF was related to deep breathing. In conclusion, in diabetic patients with increasing autonomic damage, there is a progressive impairment of nocturnal fall of BP and of sympathetic activity during the day, blunted nocturnal increase of vagal activity and lower circadian variation in sympathovagal balance. The significant but not very close correlation of day-night pattern of BP and sympathovagal activity to standard cardiovascular reflex tests, supports the independent usefulness of 24h BP monitoring and spectral analysis of heart rate variability in diabetic neuropathy.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1042/cs0910105supp | DOI Listing |
Sensors (Basel)
December 2024
School of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, China.
Coronary artery stenosis detection remains a challenging task due to the complex vascular structure, poor quality of imaging pictures, poor vessel contouring caused by breathing artifacts and stenotic lesions that often appear in a small region of the image. In order to improve the accuracy and efficiency of detection, a new deep-learning technique based on a coronary artery stenosis detection framework (DCA-YOLOv8) is proposed in this paper. The framework consists of a histogram equalization and canny edge detection preprocessing (HEC) enhancement module, a double coordinate attention (DCA) feature extraction module and an output module that combines a newly designed loss function, named adaptive inner-CIoU (AICI).
View Article and Find Full Text PDFPlant Physiol
January 2025
Institute of Biology, Biotechnology and Environmental Protection, Faculty of Natural Sciences, University of Silesia, Katowice, Poland.
Global climate change leads to the increased occurrence of environmental stress (including drought and heat stress) during the vegetative and reproductive stages of cereal crop development. Thus, more attention should be given to developing new cereal cultivars with improved tolerance to environmental stress. However, during the development of new stress-tolerant cereal cultivars, the balance between improved stress responses (which occur at the expense of growth) and plant yield needs to be maintained.
View Article and Find Full Text PDFJ Comput Assist Tomogr
November 2024
From the Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, Kumamoto, Japan.
Objective: This preliminary study aims to assess the image quality of enhanced-resolution deep learning reconstruction (ER-DLR) in magnetic resonance cholangiopancreatography (MRCP) and compare it with non-ER-DLR MRCP images.
Methods: Our retrospective study incorporated 34 patients diagnosed with biliary and pancreatic disorders. We obtained MRCP images using a single breath-hold MRCP on a 3T MRI system.
Eur J Radiol Open
June 2025
Department of Radiology, Charité - Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany.
Background: Deep learning (DL) accelerated controlled aliasing in parallel imaging results in higher acceleration (CAIPIRINHA)-volumetric interpolated breath-hold examination (VIBE), provides high spatial resolution T1-weighted imaging of the upper abdomen. We aimed to investigate whether DL-CAIPIRINHA-VIBE can improve image quality, vessel conspicuity, and lesion detectability compared to a standard CAIPIRINHA-VIBE in renal imaging at 3 Tesla.
Methods: In this prospective study, 50 patients with 23 solid and 45 cystic renal lesions underwent MRI with clinical MR sequences, including standard CAIPIRINHA-VIBE and DL-CAIPIRINHA-VIBE sequences in the nephrographic phase at 3 Tesla.
Med Phys
January 2025
National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Background: Respiratory motion during radiotherapy (RT) may reduce the therapeutic effect and increase the dose received by organs at risk. This can be addressed by real-time tracking, where respiration motion prediction is currently required to compensate for system latency in RT systems. Notably, for the prediction of future images in image-guided adaptive RT systems, the use of deep learning has been considered.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!