Conectar
by Chengya Feng, Xiaohe Lu, Zimian Fan, Xinxing Wang
BackgroundHuman papillomavirus (HPV) is the most prevalent sexually transmitted infection. Copper is essential for immune function, but its association with HPV infection remains unclear. This study aims to investigate the relationship between dietary copper intake and HPV infection.
MethodsThis cross-sectional study analyzed 8,071 participants from the National Health and Nutrition Examination Survey (2003–2016). Copper intake was assessed using two 24-hour recalls, and HPV status was confirmed by DNA testing. Weighted multivariable logistic regression and restricted cubic splines (RCS) were used.
ResultsAfter adjusting for multiple confounders, dietary copper intake was significantly inversely associated with vaginal HPV infection (odds ratio [OR], 0.79; 95% confidence interval [CI], 0.67–0.92). Compared with women in the lowest quartile of dietary copper intake, those in the highest quartile had a lower adjusted OR for vaginal HPV infection (OR, 0.60; 95% CI, 0.48–0.73). RCS analysis revealed an L-shaped association with a threshold at 1.2 mg/day of copper intake. Subgroup analyses showed that marital status moderated the association between copper intake and HPV infection (P for interaction Conclusion
An L-shaped association was observed between copper intake and HPV infection, suggesting that maintaining an optimal level of copper intake may be associated with reduced risk of HPV infection and related diseases.
by Haoyang Zhou, Jinfeng Yang, Na Li, Jinying Li, Jianxin Ran, Yan Zheng, Yifan Long, Fang Cheng, Yuanpeng Liao
BackgroundSarcopenia is an age-associated disorder characterized by a progressive decline in skeletal muscle mass, strength, and physical function. The condition is linked to low levels of anabolic hormones such as insulin-like growth factor 1 (IGF-1), with its downstream phosphatidylinositol 3 kinase (PI3K)/ protein kinase B (AKT)/ forkhead box protein O3 (FOXO3) signaling pathway. There is growing evidence that resistance training (RT) or vibration training (VT) could improve physical functioning in individuals with sarcopenia. However, the related physiological influence of exercise on sarcopenia remains elusive.
MethodThis prospective randomized controlled trial will be conducted among 96 participants, aged between 65 and 80 years. In participants, sarcopenia diagnosis will be confirmed based on the Asian Working Group for Sarcopenia criteria, and participants will be randomized into either control, RT, VT, or RVT (combined RT and VT) groups. The intervention will last 12 weeks, with assessments performed at baseline, 12 weeks (after intervention), and 24 weeks (follow-up). The primary outcomes will include skeletal muscle mass, handgrip strength, and gait speed. Secondary outcomes comprise IGF-1 concentrations, PI3K/AKT and FOXO3 protein activity, quality of life, and timed-up-and-go test performance assessments.
DiscussionThis clinical study aims to elucidate the potential modulation of molecular mechanisms in vivo for combined RT and VT in sarcopenia patients and to identify the effects of the intervention on physical function.
Trial registrationChiCTR, ChiCTR2400083643. Registered on April 29, 2024.
by Ruilan Lin, Ru Qin, Yunlong Zhang, Yao Guan, Boheng Wu, Shangyang Li, Shenhong Qu, Yulin Yuan
BackgroundThis study aims to assess the diagnostic value of the Epstein-Barr virus (EBV) BNLF2b antibody(P85-Ab), alone or in combination with VCA-IgA, Rta-IgG, and Zta-IgA antibodies, in the context of nasopharyngeal carcinoma (NPC).
MethodsThe study included 100 NPC patients and 100 healthy controls. Chemiluminescent microparticle immunoassay was utilized to measure P85-Ab levels in the serum samples of both NPC patients and healthy controls. Additionally, the ELISA method was employed to detect serum levels of VCA-IgA, Rta-IgG, and Zta-IgA antibodies. The study analyzed the roles of serum P85-Ab in conjunction with VCA-IgA, Rta-IgG, and Zta-IgA antibodies in the diagnosis of NPC.
ResultsSerum levels of P85-Ab, VCA-IgA, Rta-IgG, and Zta-IgA antibodies in NPC patients were significantly higher than those in the normal control group (P Conclusion
The combined detection of P85-Ab with VCA-IgA, Rta-IgG, and Zta-IgA antibodies demonstrates high diagnostic value for nasopharyngeal carcinoma. Serum P85-Ab may serve as a potential marker for the diagnosis of NPC.
by Mengqi Yuan, Yajing Yuan, Xiangqun Zhang, Zhenghao Zhu, Chenxi Zhao, Xiangqian Gao, Genyuan Du
Millimeter-wave (mmWave) radar has become an important research direction in the field of object detection because of its characteristics of all-time, low cost, strong privacy and not affected by harsh weather conditions. Therefore, the research on millimeter wave radar object detection is of great practical significance for applications in the field of intelligent security and transportation. However, in the multi-target detection scene, millimeter wave radar still faces some problems, such as unable to effectively distinguish multiple objects and poor performance of detection algorithm. Focusing on the above problems, a new target detection and classification framework of S2DB-mmWave YOLOv8n, based on deep learning, is proposed to realize more accuracy. There are three main improvements. First, a novel backbone network was designed by incorporating new convolutional layers and the Simplified Spatial Pyramid Pooling - Fast (SimSPPF) module to strengthen feature extraction. Second, a dynamic up-sampling technique was introduced to improve the model’s ability to recover fine details. Finally, a bidirectional feature pyramid network (BiFPN) was integrated to optimize feature fusion, leveraging a bidirectional information transfer mechanism and an adaptive feature selection strategy. A publicly available 5-class object mmWave radar heatmap dataset, including 2,500 annotated images, were selected for data modeling and method evaluation. The results show that the mean average precision (mAP), precision and recall of the S2DB-mmWave YOLOv8n model were 93.1% mAP@0.5, 55.8% mAP@0.5:0.95, 89.4% and 90.6%, respectively, which is 3.3, 1.6, 4.5 and 7.7 percentage points higher than the baseline YOLOv8n network without increasing the parameter count.by Chenyu Zheng, Ming Fang, Yue Zhang, Xinyu Liu, Zhihuan Huang
Exposure to natural landscapes has been shown to affect both physiological and psychological well-being, with the extent of these effects varying across different landscape types. However, the underlying mechanisms remain poorly understood. The association among stress reduction, environments characteristics and individual differences requires further investigation, particularly considering the complexity of landscape attributes and the variability of personal responses. In this study, 98 university students participated in a survey to evaluate the effects of different landscape types on visual preference and fatigue recovery. Physiological data (blood pressure, heart rate), psychological data (Perceived Restorative Scale), and visual preferences were analyzed before and after participants viewed the images of eight representative landscape space types: mountain, field, waterscape, lawn, desert, forest, artificial nature, plant. The results indicated that landscape type significantly influenced both physiological responses and emotional states, as well as participants’ perceived recovery from stress. Among the eight landscape spaces, water features and forests were reported to be the most restorative. Compared to freshmen, juniors exhibited greater improvements in physical and psychological recovery, alongside more positive evaluations of the environments. Notably, the desert landscape elicited varied responses depending on participants’ grade level and gender, suggesting that restoration effects may be modulated by individual characteristics. This may reflect an evolutionary predisposition to prefer natural features that enhance survival. These findings contribute to environmental psychology and provide valuable insights for educational practice and environmental design.by Ruibo Sha, Zhifeng Zhang, Xiao Cui, Qingzheng Mu
Sewer pipeline defect detection is a critical task for ensuring the normal operation of urban infrastructure. However, the sewer environment often presents challenges such as multi-scale defects, complex backgrounds, lighting changes, and diverse defect morphologies. To address these issues, this paper proposes a lightweight cross-scale feature fusion model based on YOLOv8. First, the C2f module in the backbone network is replaced with the C2f-FAM module to enhance multi-scale feature extraction capabilities. Second, the HS-BiFPN module is adopted to replace the original structure, leveraging cross-layer semantic fusion and feature re-weighting mechanisms to improve the model’s ability to distinguish complex backgrounds and diverse defect morphologies. Finally, DySample is introduced to replace traditional sampling operations, enhancing the model’s ability to capture details in complex environments. This study uses the Sewer-ML dataset to train and evaluate the model, selecting 1,158 images containing six types of typical defects (CK, PL, SG, SL, TL, ZW), and expanding the dataset to 1,952 images through data augmentation. Experimental results show that compared to the YOLOv8n model, the improved model achieves a 3.8% increase in mAP, while reducing the number of parameters by 35%, floating-point operations by 21%, and model size by 33%. By improving detection accuracy while achieving model lightweighting, the model demonstrates potential for application in pipeline defect detection.by Jing Guo, Wenshuang Wang, Xiaoxue Zhang, Yulin Zheng, Xinran Wang
Frailty is a common multifactorial clinical syndrome in older patients that seriously affects their prognosis. However, most studies to date have ignored the dynamics of frailty. Therefore, we employed a one-month observational longitudinal study to explore frailty trajectories using a latent class growth model. In total, 155 older patients who underwent abdominal surgery involving the digestive system were assessed preoperatively, at discharge, and at the one-month follow-up, and multiple logistic regression analysis was conducted to identify factors influencing frailty trajectories. Four frailty trajectory patterns were identified: no frailty (13.5%), frailty exacerbation (40.0%), frailty improvement (20.0%), and persistent frailty (26.5%). Logistic regression analysis revealed that body mass index, the Charlson comorbidity index score, the type of surgery, the intraoperative drainage tube retention time (drainage time), the first time the patient got out of bed after surgery, the time of the first oral feed after surgery, postoperative complications, mobility, nutritional risk, and anxiety were associated with frailty trajectories. We identified four frailty trajectories in older patients undergoing abdominal surgery involving the digestive system and found that these trajectories were influenced by multiple factors. Focusing on individual specificity is conducive to accurately addressing frailty-associated clinical problems and guiding relevant nursing decisions.by Lin Chen, Jiayao Chen, Jindong Wan, Muqing Shao, Caiyu Chen, Shuo Zheng, Fuwei Zhang, Jian Yang
The angiotensin converting enzyme 2/angiotensin-(1–7)/Mas receptor axis plays an important role in the regulation of blood pressure. G protein-coupled receptor kinase 4 (GRK4) has attracted more attentions by modulating G protein-coupled receptors and blood pressure. However, it remains unknown whether renal Mas receptor is regulated by GRK4 and its role in the pathogenesis of hypertension. Compared with Wistar-Kyoto (WKY) rats, spontaneously hypertensive rats (SHRs) exhibited impaired Mas receptor-mediated diuresis and natriuresis, which was accompanied with increased phosphorylation levels of Mas receptors. Similarly, the phosphorylation of renal Mas receptor was increased and its-induced renal effects were decreased in human (h) GRK4γ 142V transgenic mice relative to wild-type littermates. There was a colocalization and a direct interaction of renal Mas receptor and GRK4, which were increased in SHRs and confirmed by rigid protein–protein docking. In vitro studies found that treatment with the Mas receptor agonist AVE0991 inhibited Na+-K+-ATPase activity in WKY renal proximal tubule (RPT) cells, which was failed in SHR cells. GRK4 silencing decreased the phosphorylation of Mas receptor and improved the impaired Mas receptor-mediated inhibition of Na+-K+-ATPase activity in SHR RPT cells. Further study showed that ultrasound-targeted microbubble destruction-targeted renal GRK4 depletion decreased Mas receptor phosphorylation and improved its-induced diuresis and natriuresis in SHRs. These suggest that GRK4 contributes to increased renal Mas receptor phosphorylation and dysfunction in hypertension, indicating that targeting GRK4 may be a viable therapeutic approach for hypertension.by Diane C. Lim, Cheng-Bang Chen, Ankita Paul, Yujie Wang, Jinyoung Kim, Soonhyun Yook, Emily Y. Kim, Edison Q. Kim, Anup Das, Medhi Wangpaichitr, Virend K. Somers, Chi Hang Lee, Phyllis C. Zee, Toshihiro Imamura, Hosung Kim
ObjectiveTo quantitate hypoxemia severity.
MethodsWe developed the Weighted Hypoxemia Index to be adapted to different clinical settings by applying 5 steps to the oxygen saturation curve: (1) Identify desaturation/resaturation event i by setting the upper threshold; (2) Exclude events as artifact by setting a lower threshold; (3) Calculate weighted area for each i, as (Δi × Φi); (4) Calculate a normalization factor Ω for each subject; (5) Calculate the Weighted Hypoxemia Index as the summation of all weighted areas multiplied by Ω. We assessed the Weighted Hypoxemia Index predictive value for all-cause mortality and cardiovascular mortality using the Sleep Heart Health Study (enrollment 1995–1998, 11.1 years mean follow-up).
ResultsWe set varying upper thresholds at 92%, 90%, 88%, and 86%, a lower threshold of 50%, calculated area under the curve and area above the curve, with and without a linear weighted factor (duration of each event i), and used the same normalization factor of total sleep time Conclusion
The Weighted Hypoxemia Index offers a versatile and clinically relevant method for quantifying hypoxemia severity, with potential applications to evaluate mechanisms and outcomes across various patient populations.
by Zhihao Zheng, Jianguang Zhao, Jingjing Fan
Uav target detection is a key technology in low altitude security, disaster relief and other fields. However, in practical application scenarios, there are many complex and highly uncertain factors, such as extreme weather changes, large scale and span of the target, complex background interference, motion ambiguity, etc., which makes accurate and real-time UAV target detection still a great challenge. In order to reduce the interference of these situations in real detection scenes and improve the accuracy of UAV detection, a Global Edge Information Enhance (GEIE)module is proposed in this paper, which enables edge information to be fused into features extracted at various scales. It can improve the attention of the network to the edge information of the object. In addition, special weather conditions can greatly reduce the detection accuracy of the target, this paper proposes a Multiscale Edge Feature Enhance(MEFE) module to extract features from different scales and highlight edge information, which can improve the model’s perception of multi-scale features. Finally, we propose a Lightweight layered Shared Convolutional BN(LLSCB) Detection Head based on LSCD, so that the detection heads share the convolutional layer, and the BN is calculated independently, which improves the detection accuracy and reduces the number of parameters. A high performance YOLO detector (YOLO-GML) based on YOLO11 model is proposed. Experimental results show that Compared with YOLO11s, YOLO-GML can improve AP50 by 2.3% to 73.6% on the challenging UAV detection dataset HazyDet, achieving a better balance between accuracy and inference efficiency compared to the most advanced detection algorithms. YOLO-GML also showed good performance improvement in the SODA-A and VisDrone-2019 datasets, demonstrating the generalization of the model.by Zhixuan Huang, Jian Liu, Hui Li, Hengjun Huang, Yangwen Ai, Dongyue Zhou
BackgroundEvodia rutaecarpa is a traditional Chinese herbal medicine known for its potential benefits in the treatment of cardiovascular and cerebrovascular diseases. Despite its recognized effects, the effects of Evodia rutaecarpa on ischemic stroke (IS), along with the primary active compounds and precise mechanisms of action, require elucidation.
MethodsNetwork pharmacology analyses and molecular docking were performed to integrate information related to Evodia rutaecarpa and IS. Cell oxygen–glucose deprivation (OGD) and rat middle cerebral artery occlusion (MCAO) models were established to simulate cerebral ischemic injury. The effects of rutaecarpine on these models were evaluated to assess its effect on IS.
ResultsNetwork pharmacological analysis indicated that rutaecarpine from Evodia rutaecarpa showed therapeutic effects against IS. The mechanism underlying these effects mainly involved the mitogen-activated protein kinase (MAPK), and targets such as matrix metalloproteinase (MMP)-9, caspase 3 and MMP-2 may be activated to exert these effects. In vitro studies showed that rutaecarpine significantly improved the mitochondrial membrane potential of HT22 cells, reduced the production of reactive oxygen species, and reversed OGD-induced cytotoxicity. In the MCAO rat model, pretreatment with rutaecarpine significantly reduced neuronal death, decreased infarct volume, and improved neurological functional deficits. In addition, rutaecarpine alleviated damage to the blood–brain barrier in the brain tissue. These effects may be related to the regulation of the MAPK-mediated MMPs pathway.
ConclusionThis study revealed the neuroprotective effects and molecular mechanisms of rutaecarpine on IS, providing a new theoretical basis for the clinical application of Evodia rutaecarpa.
by Yu-Peng Ye, Guo-You Qin, Xinyu Zhang, Shan-Shan Han, Bo Li, Ning Zhou, Qi Liu, Chen-xi Li, Yang-Sheng Zhang, Qian-qian Shao
ObjectiveThis study aims to explore the impact of physical exercise on university students’ life satisfaction and analyses the chain mediation effect of general self-efficacy and health literacy, providing empirical reference and theoretical foundation for the comprehensive enhancement and optimization of students’ mental health.
MethodBased on data from the “China University Student Physical Activity and Health Tracking Survey” (CPAHLS-CS) 2024, the measurement scales used included the Physical Activity Rating Scale (PARS-3), the Satisfaction with Life Scale (SWLS), the General Self-Efficacy Scale (GSES), and the 9-item Short Form Health Literacy Scale (HLS-SF9). A total of 4575 valid samples were analyzed.
ResultsA significant positive correlation was found between physical exercise and life satisfaction (r = 0.137, P Conclusion
University students’ life satisfaction is closely related to physical exercise, general self-efficacy, and health literacy. General self-efficacy and health literacy play a full mediating role in the effect of physical exercise on life satisfaction.
by Hong Lu, Ziyong Mao, Mengyao Zheng, Min Zhang, Heqing Huang, Yiling Chen, Long Lv, Zutao Chen
Metabolic dysfunction-associated steatotic liver disease (MASLD) is a heterogeneous disease caused by multiple etiologies. It is characterized by excessive fat accumulation in the liver. Without intervention, MASLD can progress from steatosis to metabolic dysfunction-associated steatohepatitis (MASH), fibrosis and even to cirrhosis and hepatocellular carcinoma. However, the pathogenesis of MASH and the mechanism underlying the development of fibrosis remain poorly understood, posing challenges for accurate diagnosis of MASH and fibrosis. In this study, we analyzed tissue RNA-seq data and clinical information of healthy individuals and MASLD patients from multiple datasets, the key genes and pathways involved in the occurrence and progression of MASLD, MASH, and fibrosis were screened respectively. Our findings reveal that the development of MASLD, MASH and fibrosis is associated with lipid metabolism processes. Based on the RNA expression profiles of identified hub genes, we established three alternative diagnostic models for MASLD, MASH, and fibrosis. These models demonstrated excellent performance in the diagnosis of MASLD, MASH, and fibrosis, with AUC values exceeding 0.9, implicating its potential clinical values in disease diagnosis.by Xi Cao, Bi-ting Zhu, Cai-peng Xie, Jing-yue Cai, Ding-guo Dong, Miao-ting Chen, Cheng-zhao Huang, Yong-chun Lin
To explore the risk factors influencing vancomycin trough concentration (Cvg−min) overexposure in critically ill patients with mechanical ventilation and rank the factors, the medical records of 194 mechanically ventilated critically ill patients hospitalized from 12/10/2021–06/10/2024 were analyzed. Among 194 critically ill patients, 77.83% were male and 22.17% were female. Univariate analysis showed that oxygenation index (OI), activated partial thromboplastin time (APTT), urea nitrogen (UN), septic shock, heart disease, congestive heart failure (CHF), moderate/severe chronic kidney disease (CKD), etc. were statistically different (P P P CI) and consistency ratio (CR) of analytic hierarchy process (AHP) was 0.0796 and 0.0885, respectively, which meets the consistency test standard. The contributions of APTT, OI, CHF and moderate to severe CKD to the overexposure of Cvg−min were 0.0584, 0.1899, 0.1614 and 0.5902, respectively. The overexposure rates of Cvg−min in patients with moderate/severe CKD and CHF were 95.12% and 95.23%, respectively. With regard to OI, when the cutoff value of OI was less than 245, the Cvg−min overexposure rate was 83%, otherwise, the overexposure rate was 60.97%. The risk factors for excessive exposure of Cvg−min in critically ill patients with mechanical ventilation were ranked as follows: moderate/severe CKD > OI > CHF > APTT.by Hengyu Su, Di Wu, Song Chen, Kaiyang Guo, Huifang Xie
This study investigates the correlation, impact, and hysteresis effect of joint exposure to the Temperature-Humidity Index (THI), Air Quality Index (AQI), and Black Carbon (BC) on respiratory disease mortality (RDM) in urban areas of the southwest basin of China, characterized by a subtropical monsoon climate. Dose-response analysis of THI, AQI, BC using a non-restrictive cubic spline model, a time series analysis was conducted to assess the relative risk (RR) of death from respiratory diseases using the distributed lag nonlinear model (DLNM) and the generalized additive model (GAM) based on the quasi-Poisson distribution. The RCS curve of THI exhibits a ‘U’ shape, with THI=67 representing the lowest point of mortality risk. The RCS curves for BC and AQI are linear and demonstrate a positive correlation with mortality outcomes. The peak mortality risk associated with the AQI typically occurs at Lag 2-3, with T3A3 (THI ≥ 75 and AQI ≥ P90) contributing to the highest excess mortality [excess increased risk rate (ER) = 0.55, 95% CI: 0.20, 0.81]. The peak risk of mortality associated with BC occurs at Lag0, with the highest excess mortality resulting from T3B3 (THI ≥ 75 and BC ≥ P90) combined events (ER=0.28, 95% CI: 0.10, 0.58). The cumulative relative risk (CRR) was highest in T3, with the peak CRR of 3.99 (95% CI: 1.26, 7.11) observed in definition T3A3. The relative risk of interaction (RERI) reveals varying degrees of positive additive interactions (RERI > 0) among AQI, BC, and THI.by Xin Zhang, Zijian Xi, Min Yang, Xiuqin Zhang, Ruikai Wu, Shuang Li, Lu Pan, Yuan Fang, Peng Lv, Yan Ma, Haiping Duan, Bingling Wang, Kunzheng Lv
BackgroundIt is crucial to comprehend the interplay between air pollution and meteorological conditions in relation to population health within the framework of "dual-carbon" targets. The purpose of this study was to investigate the impact of intricate environmental factors, encompassing both meteorological conditions and atmospheric pollutants, on respiratory disease (RD) mortality in Qingdao, a representative coastal city in China.
MethodsThe RD mortality cases were collected from the Chronic Disease Surveillance Monitoring System in Qingdao during Jan 1st, 2014 and Dec 31st, 2020. The distributed-lag nonlinear model and generalized additivity model were used to assess the association between daily mean temperature (DMT), air pollutant exposure and RD mortality. To ascertain the robustness of the model and further investigate this relationship, a stratified analysis and sensitivity analysis were conducted to mitigate potential confounding factors.
ResultsA total of 19,905 mortalities from RD were recorded. The minimum mortality temperature (MMT) was determined to be 23.5°C, and DMT and RD mortality showed an N-shaped relationship. At the MMT of 23.5°C, the cumulative relative risk (cumRR) for mortality within a lag period of 0–14 days from the highest temperature (31°C) was estimated at 2.114 (95% confidence interval [CI]: 1.475 ~ 3.028). The effect value of particulate matter (PM) also increased with a longer cumulative lag time. In the single pollutant model, the highest risk of RD mortality was observed on the lag1-day of per 10 μg/m3 increase in PM2.5 exposure, with an excess risk ratio (ER) of 0.847% (95% CI: 0.335% ~ 1.362%). The largest cumulative effect was found at a lag of 8 days, with an ER of 1.546% (95% CI: 0.483% ~ 2.621%). A similar trend was found for PM10. For O3 exposure, the highest risk was observed on the lag1-day of per 10 μg/m3 increase, with an ER of 1.073% (95% CI: 0.502% ~ 1.647%), and the largest cumulative effect occurred at a lag of 2 days with an ER of 1.113% (95%CI: 0.386% ~ 1.844%). Results from the dual-pollutants model demonstrated that the effect of PM on the risk of RD mortality remained significant and slightly increased in magnitude. Moreover, composite pollutants exhibited a higher risk effect, reaching its peak after one week; however, there was a decrease in single-day cumulative effects as more pollutant types were included. Subgroup analysis showed that females, elderly individuals, and those exposed during warm seasons demonstrated greater susceptibility to PM exposure.
ConclusionThe present study revealed a significant association between short-term exposure to high temperature, PM2.5, PM10 and O3 and the risk of RD mortality in Qingdao, even in dual- and composite-pollutants models. Furthermore, our findings indicate that females, the elderly population, and warm seasons exhibit heightened sensitivity to PM exposure.
by Zenglei Liu, Ailian Gao, Hui Sheng, Xueling Wang
Diabetic retinopathy, a retinal disorder resulting from diabetes mellitus, is a prominent cause of visual degradation and loss among the global population. Therefore, the identification and classification of diabetic retinopathy are of utmost importance in the clinical diagnosis and therapy. Currently, these duties are extensively carried out by manual examination utilizing the human visual system. Nevertheless, manual examination is sometimes arduous, time-consuming, and prone to errors. Deep learning-based methods have recently demonstrated encouraging results in several areas, such as image categorization and natural language mining. The majority of deep learning techniques developed for medical image analysis rely on convolutional modules to extract the inherent structure of images within a certain local receptive field. Furthermore, transformer-based models have been utilized to tackle medical image processing problems by capitalizing on global connections among distant pixels in the images. Considering these analyses, this work presents a comprehensive deep learning model that combines convolutional neural network and vision mamba models. This model is designed to accurately identify and classify diabetic retinopathy lesions displayed in fundus images. Furthermore, the vision mamba component incorporates the bidirectional state space method and positional embedding to enable the location sensitivity of visual data samples and meet the conditions for global relationship context. An evaluation of the suggested method was carried out by comparison experiments between state-of-the-art algorithms and the proposed methodology. Empirical findings demonstrate that the suggested methodology surpasses the most advanced algorithms on the datasets that are accessible openly. Hence, the suggested approach may be regarded as a helpful tool for therapeutic processes.by Bin Li, Yating Chen, Maoxiang Zhao, Zhijie Chen, Zhuhui Lin, Jie Liu, Xueping Wang, Jiancheng Zhang, Yang Li
Obesity is associated with abnormal repolarization manifested by QT interval prolongation, and oxidative stress is an important link between obesity and arrhythmias. However, the underlying electrophysiological and molecular mechanisms remain unclear. The aim of this study is to evaluate the role of obesity in potassium current in ventricular myocytes and the potential mechanism of NADPH oxidase 2 (Nox2). We investigated the effect of Nox2 on cardiac repolarization without compromising its expression and function in other systems using mice with conditional cardiac-specific deletions of Nox2 (knockout [KO]). Wild-type, KO, and Flox littermate mice were randomized to either the control or high-fat diet (HFD) groups. Surface electrocardiograms were recorded to analyze repolarization in vivo. Whole-cell patch-clamp techniques were used to evaluate the electrophysiological phenotype of isolated myocytes in vitro. Western blotting was performed to assess protein expression levels. Compared with the control mice, the HFD group had a prolonged QTc. The consequences of an HFD were not attributed to delayed rectifier K+ and inward-rectifier K+ currents but were associated with reduced peak outward KV and fast transient outward K+ currents. Downregulated expression of KV4.2 and KChIP2, comprising functional Ito channel pore-forming (α) and accessory (β) subunits, was detected in HFD mice. Nox2-KO reversed the effect of obesity on Ipeak and Ito amplitude. Our data demonstrate that obesity mediates impaired cardiac repolarization in mice, manifested by QTc at the whole organism level and action potential duration at the cellular level, and correlated with Nox2. The electrophysiological and molecular aspects of this phenomenon were mediated by repolarizing outward K+ currents.by Ting Cheng, Dongdong Yu, Geng Li, Xiankun Chen, Li Zhou, Zehuai Wen
BackgroundFurther evidence is required regarding the influence of metal mixture exposure on mortality. Therefore, we employed diverse statistical models to evaluate the associations between eight urinary metals and the risks of all-cause and cardiovascular mortality.
MethodsWe measured the levels of 8 metals in the urine of adults who participated in the National Health and Nutrition Examination Survey (NHANES) from 1999 to 2018. Based on follow-up data, we determined whether they died and the reasons for their deaths. We estimated the association between urine metal exposure and all-cause mortality using Cox regression, weighted quantile sum (WQS) regression, and Bayesian kernel machine regression (BKMR) models. Additionally, we used a competing risk model to estimate the relationship between metal exposure and cardiovascular mortality.
ResultsAmong the 14,305 individuals included in our final analysis, there were 2,066 deaths, with 1,429 being cardiovascular-related. Cox regression analysis showed that cobalt (Co) (HR: 1.21; 95% CI: 1.13, 1.30) and antimony (Sb) (HR: 1.26; 95% CI: 1.12, 1.40) were positively associated with all-cause mortality (all P for trend P for trend Conclusions
Combining all models, it is possible that Sb may have a more stable impact on all-cause and cardiovascular mortality. Meaningful metal effects in individual statistical models still require careful attention.
by Bin Li, Jinjin Wang, Jianlong Ge, Meijie Liao, Xiaojun Rong, Jinyan Wang, Yingeng Wang, Zheng Zhang, Chunyuan Wang, Yongxiang Yu
In order to study the optimal use of Lactobacillus plantarum in sea cucumber (Apostichopus japonicus), 49 days feeding trial was conducted to determine the influence of immersion bathing in different concentrations of Lactobacillus plantarum CLY-05 on body weight gain rate and non-specific immune activities. The potential effect of CLY-05 on gut microbiota was also analyzed during the immersion bathing at the optimum concentration. The results showed that the body weight growth rate of all bathing groups was higher than that of control. The highest specific growth rate (4.58%) and weight gain rate (25.35%) was achieved at the bacterial concentration of 1×103 CFU/mL. The activities of non-specific immune enzymes (ACP, AKP, SOD and LZM) of all bathing groups increased after immersion bathing, and the enzyme activities of groups bathed with the bacterium at 1×103 and 1×104 CFU/mL reached the highest. Therefore, 1×103 CFU/mL was considered as the optimum concentration of L. plantarum CLY-05 for A. japonicus pond culture. The results of gut microbiota analysis showed that the gut microbiota changed with the addition of L. plantarum CLY-05, and the richness and diversity of the gut microbiota peaked on day 14 and day 21, respectively. The correlation analysis revealed that the non-specific immune enzyme activities were significantly correlated to some gut bacteria (in the phyla Proteobacteria, Firmicutes) after immersion bathing in L. plantarum CLY-05. These findings provide the theoretical foundation for probiotic application in sea cucumber farming.
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