Application study of apnea-hypopnea duration for assessing adult obstructive sleep apnea.

BACKGROUND: Obstructive sleep apnea (OSA) is a common sleep disordered breathing disorder, which can cause serious damage to multiple human systems. Although polysomnography (PSG) is the current gold standard for diagnosis, it is complex and expensive. Therefore, it is of great significance to find a simple, economical and rapid primary screening and diagnosis method to replace PSG for the diagnosis of OSA. OBJECTIVE: The purpose of this study is to propose a new method for the diagnosis and classification of OSA, which is used to automatically detect the duration of sleep apnea hypopnea events (AHE), so as to estimate the ratio(S) of the total duration of all-night AHE to the total sleep time only based on the sound signal of sleep respiration, and to identify OSA. METHODS: We performed PSG tests on participants and extracted relevant sleep breathing sound signal data. This study is carried out in two stages. In the first stage, the relevant PSG report data of eligible subjects were recorded, the total duration of AHE in each subject's data was extracted, and the S value was calculated to evaluate the severity of OSA. In the second stage, only the sleep breath sound signal data of the same batch of subjects were used for automatic detection, and the S value in the sleep breath sound signal was extracted, and the S value was compared with the PSG diagnosis results to calculate the accuracy of the experimental method. RESULTS: Among 225 subjects. Using PSG as the reference standard, the S value extracted from the PSG diagnostic data report can accurately diagnose OSA(accuracy rate 99.56%) and distinguish its severity (accuracy rate 95.11%). The accuracy of the S value detected in the sleep breathing sound signal in the diagnosis of severe OSA reached 100%. CONCLUSION: The results show that the experimental parameter S value is feasible in OSA diagnosis and classification. OSA can be identified and evaluated only by sleep breathing sounds. This method helps to simplify the diagnostic grading of traditional OSA and lays a foundation for the subsequent development of simple diagnostic grading equipment.

The effect of the re-segmentation method on improving the performance of rectal cancer image segmentation models.

BACKGROUND: Rapid and accurate segmentation of tumor regions from rectal cancer images can better understand the patientâs lesions and surrounding tissues, providing more effective auxiliary diagnostic information. However, cutting rectal tumors with deep learning still cannot be compared with manual segmentation, and a major obstacle to cutting rectal tumors with deep learning is the lack of high-quality data sets. OBJECTIVE: We propose to use our Re-segmentation Method to manually correct the model segmentation area and put it into training and training ideas. The data set has been made publicly available. Methods: A total of 354 rectal cancer CT images and 308 rectal region images labeled by experts from Jiangxi Cancer Hospital were included in the data set. Six network architectures are used to train the data set, and the region predicted by the model is manually revised and then put into training to improve the ability of model segmentation and then perform performance measurement. RESULTS: In this study, we use the Resegmentation Method for various popular network architectures. CONCLUSION: By comparing the evaluation indicators before and after using the Re-segmentation Method, we prove that our proposed Re-segmentation Method can further improve the performance of the rectal cancer image segmentation model.

Exploring the relationship between brain white matter change and higher degree of invisible hand tremor with computer technology.

BACKGROUND: At present, the clinical diagnosis of white matter change (WMC) patients depends on cranial magnetic resonance imaging (MRI) technology. This diagnostic method is costly and does not allow for large-scale screening, leading to delays in the patient's condition due to inability to receive timely diagnosis. OBJECTIVE: To evaluate whether the burden of WMC is associated with the degree of invisible hand tremor in humans. METHODS: Previous studies have shown that tremor is associated with WMC, however, tremor does not always have imaging of WMC. Therefore, to confirm that the appearance of WMC causes tremor, which are sometimes invisible to the naked eye, we achieved an optical-based computer-aided diagnostic device by detecting the invisible hand tremor, and we proposed a calculation method of WMC volume by using the characteristics of MRI images. RESULTS: Statistical analysis results further clarified the relationship between WMC and tremor, and our devices are validated for the detection of tremors with WMC. CONCLUSIONS: The burden of WMC volume is positive factor for degree of invisible hand tremor in the participants without visible hand tremor. Detection technology provides a more convenient and low-cost evaluating method before MRI for tremor diseases.

The impact of atrial fibrillation on accuracy of oscillometric blood pressure measurement: effect of ventricular rate.

This study evaluated the impact of ventricular rate (VR) in atrial fibrillation (AF) patients with oscillometric BP measurements. This study included 138 patients with AF and 112 patients with sinus rhythm (SR) who underwent coronary angiography. Left arm BP was measured three times with an oscillometric device, and the average was recorded as the final oscillometric value. At the same time, the average of three intra-aortic BP readings was used as invasive values. Delta BP was the difference between intra-aortic and oscillometric BP. Meanwhile, the BP percentage difference (PD-BP) was calculated with the following formula: PD-BP = (delta BP/intra-aortic BP) × 100%. Based on the VR, four subgroups of AF and SR patients, <80, 80-99, 100-120, and >120 bpm, were created, and the mean PD-BP for both systolic blood pressure (SBP) and diastolic blood pressure (DBP) was significantly higher in the AF group than in the SR group. Moreover, the mean PD-SBP values gradually increased as VR increased in both groups. More importantly, the difference in PD-SBP between the AF and SR groups increased as VR increased: when VR was <80 bpm, the levels were similar (-2.0 ± 3.5 vs. -1.4 ± 2.7 mm Hg, NS), but these values in AF patients were significantly higher when VR was 80-99 bpm (-3.7 ± 5.0 vs. -1.8 ± 2.3 mm Hg, p < 0.05), 100-120 bpm (-6.1 ± 4.3 vs. -2.3 ± 1.9 mm Hg, p < 0.05) and >120 bpm (-7.8 ± 4.9 vs. -2.9 ± 1.7 mm Hg, p < 0.05). The accuracy of oscillometric BP measurements are dependent on the ventricular rate in AF patients even after three measurements, and a higher ventricular rate may result in larger underestimations of oscillometric BP.

Regulation and metabolic engineering strategies for permeases of Saccharomyces cerevisiae.

Microorganisms have evolved permeases to incorporate various essential nutrients and exclude harmful products, which assists in adaptation to different environmental conditions for survival. As permeases are directly involved in the utilization of and regulatory response to nutrient sources, metabolic engineering of microbial permeases can predictably influence nutrient metabolism and regulation. In this mini-review, we have summarized the mechanisms underlying the general regulation of permeases, and the current advancements and future prospects of metabolic engineering strategies targeting the permeases in Saccharomyces cerevisiae. The different types of permeases and their regulatory mechanisms have been discussed. Furthermore, methods for metabolic engineering of permeases have been highlighted. Understanding the mechanisms via which permeases are meticulously regulated and engineered will not only facilitate research on regulation of global nutrition and yeast metabolic engineering, but can also provide important insights for future studies on the synthesis of valuable products and elimination of harmful substances in S. cerevisiae.

Three-dimensional measuring technique for surface topography using a light-sectioning microscope.

Three-dimensional (3D) surface topographic analysis, measurement, and assessment techniques have raised great interest not only among researchers but also among industrial users. Many industrial processes and applications are directly influenced by the small-scale roughness of surface finishes. This paper describes the development and implementation of a noncontact, three-dimensional, microtopography measuring system. The instrument is formed by combining a modified light-sectioning microscope subsystem with a computer subsystem. In particular, optical system characteristics of the light-sectioning microscope are investigated, and a textured steel sheet is measured to demonstrate good practical outcomes. Details of measuring processes and image processing algorithms are provided, such as procedures for measurement, image edge extraction, and 3D topography reconstruction. After the 3D topography of the measured surface has been reconstructed, the topography field description parameters are calculated. A standard roughness block was used for calibration of the surface microtopography measuring system. Results obtained showed the measurement method output has good agreement with the actual asperity (unevenness or roughness) of the surface. The computer subsystem is used to process and control asperity measurements and image generation, and for image acquisition and presentation.