Objective: To explore the impact of donor reentry experience, specifically among those with a single reactive serological result who completed the reentry process, on their willingness to return for future blood donation, and to examine the mediating roles of blood donation knowledge and trait anxiety. Methods: A cross-sectional survey was conducted between November and December 2025. A total of 386 blood donors from the Changsha Blood Center were categorized into a reentry group (n=123) and a control group (n=263). Data on demographic characteristics, blood donation knowledge (BDKQ), trait anxiety (STAI-T), and blood donation return intention (BDRIS) were collected via questionnaires. SPSS 27.0 and AMOS 28.0 were used for statistical analyses, including independent-samples t-test, one-way ANOVA, multiple linear regression, and path analysis for mediating effect testing. Results: There were statistically significant differences in age, occupation, education level, monthly income and donation frequency between the reentry group and the control group (all P<0.05). The reentry group scored significantly higher in blood donation knowledge and blood donation return intention than the control group (both P<0.05). The mean BDRIS score was 11.51±3.62, indicating a relatively high intention to return. Blood donation knowledge was significantly negatively correlated with trait anxiety (r=-0.15, P<0.05) and positively correlated with blood donation return intention (r=0.19, P<0.05); trait anxiety was significantly negatively correlated with blood donation return intention (r=-0.33, P<0.05). Significant differences in BDRIS scores were found based on group (reentry vs control), age, and number of previous donations (all P<0.05). Multiple linear regression showed that BDKQ positively predicted BDRIS (β=0.11, P<0.05), while STAI-T negatively predicted BDRIS (β=-0.27, P<0.05). Path analysis further revealed that the reentry experience had no direct effect on the intention to return. However, it exerted a positive influence through two indirect pathways: 1) a simple mediating effect via increased blood donation knowledge (β=0.17, accounting for 25.0% of the total effect), and 2) a chain mediating effect through "increased blood donation knowledge → decreased trait anxiety" (β=0.05, accounting for 8.1% of the total effect). The model fit indices reached the ideal fitting criteria. Conclusion: The donor reentry experience does not directly enhance the intention to return for blood donation. Rather, it may exert an indirect positive influence by increasing blood donation knowledge and through the sequential pathway of "increased knowledge → decreased trait anxiety". Blood collection institutions should leverage the reentry process as an opportunity for education and psychological support to improve donor retention rate.

Exercise fatigue is a complex physiological and psychological phenomenon that includes peripheral fatigue in the muscles and central fatigue in the brain. Peripheral fatigue refers to the loss of force caused at the distal end of the neuromuscular junction, whereas central fatigue involves decreased motor output from the primary motor cortex, which is associated with modulations at anatomical sites proximal to nerves that innervate skeletal muscle. The central regulatory failure reflects a progressive decline in the central nervous system’s capacity to recruit motor units during sustained physical activity. Emerging evidence highlights the critical involvement of central neurochemical regulation in fatigue development, particularly through neurotransmitter-mediated modulation. Alterations in neurotransmitter release and receptor activity could influence excitatory and inhibitory signal pathways, thus modulating the perception of fatigue and exercise performance. Increased serotonin (5-HT) could increase perception of effort and lethargy, reduce motor drive to continue exercising, and contribute to exercise fatigue. Decreased dopamine (DA) and noradrenaline (NE) neurotransmission can negatively impact arousal, mood, motivation, and reward mechanisms and impair exercise performance. Furthermore, the serotonergic and dopaminergic systems interact with each other; a low 5-HT/DA ratio enhances motor motivation and improves performance, and a high 5-HT/DA ratio heightens fatigue perception and leads to decreased performance. The expression and activity of neurotransmitter receptors would be changed during prolonged exercise to fatigue, affecting the transmission of nerve signals. Prolonged high-intensity exercise causes excess 5-HT to overflow from the synaptic cleft to the axonal initial segment and activates the 5-HT1A receptor, thereby inhibiting the action potential of motor neurons and affecting the recruitment of motor units. During exercise to fatigue, the DA secretion is decreased, which blocks the binding of DA to D1 receptor in the caudate putamen and inhibits the activation of the direct pathway of the basal ganglia to suppress movement, meanwhile the binding of DA to D2 receptor is restrained in the caudate putamen, which activates the indirect pathway of the basal ganglia to influence motivation. Furthermore, other neurotransmitters and their receptors, such as adenosine (ADO), glutamic acid (Glu), and γ‑aminobutyric acid (GABA) also play important roles in regulating neurotransmitter balance and fatigue. The occurrence of central fatigue is not the result of the action of a single neurotransmitter system, but a comprehensive manifestation of the interaction between multiple neurotransmitters. This review explores the important role of neurotransmitters and their receptors in central motor fatigue, reveals the dynamic changes of different neurotransmitters such as 5-HT, DA, NE, and ADO during exercise, and summarizes the mechanisms by which these neurotransmitters and their receptors regulate fatigue perception and exercise performance through complex interactions. Besides, this study presents pharmacological evidence that drugs such as agonists, antagonists, and reuptake inhibitors could affect exercise performance by regulating the metabolic changes of neurotransmitters. Recently, emerging interventions such as dietary bioactive components intake and transcranial electrical stimulation may provide new ideas and strategies for the prevention and alleviation of exercise fatigue by regulating neurotransmitter levels and receptor activity. Overall, this work offers new theoretical insights into the understanding of exercise central fatigue, and future research should further investigate the relationship between neurotransmitters and their receptors and exercise fatigue.

Background The decline of physical activity in the elderly due to aging may increase the risk of sarcopenia. Currently, there is a lack of evidence from large natural populations on the relationship between PA and sarcopenia. Objective To explore the relationship between PA and sarcopenia in the elderly aged 60 years and above in 10 provinces (autonomous regions) of China. Methods Data were retrieved from the 2022—2023 round of the China Development and Nutrition Health Impact Cohort. Personal basic information and PA data were collected by questionnaire survey. Skeletal muscle mass was measured by bio-electrical impedance analysis, muscle strength was measured using a grip dynamometer, and physical performance was reflected by 6-meter walk speed. The Asian Working Group for Sarcopenia (AWGS) 2019 criteria were used to diagnose sarcopenia. Light physical activity (LPA) duration, moderate-to-vigorous physical activity (MVPA) duration, and total physical activity volume were calculated. A total of 3326 residents aged ≥60 years with complete data were selected as the survey participants. Multiple logistic regression models and restricted cubic splines (RCS) were used to assess the association between PA duration/volume and sarcopenia. Results In 10 provinces (autonomous regions) of China, the prevalence of sarcopenia in the elderly aged 60 years and above was 5.5% (95%CI: 4.7%, 6.2%). The logistic regression analysis showed that compared with the elderly reporting 0-7.0 h·week⁻¹ in LPA duration, the risk of sarcopenia in the elderly with LPA duration of >14.0-21.0 h·week⁻¹ was reduced by 51% (OR=0.49, 95%CI: 0.26, 0.96). Compared with the elderly with total physical activity ≥15.0 metabolic equivalent of task (MET)-h·week⁻¹, those with <7.5 MET-h·week⁻¹ had a 2.24-fold increased risk of sarcopenia (OR=2.24, 95%CI: 1.17, 4.29). The RCS results found that LPA duration and total physical activity volume each showed a nonlinear dose-response relationship with the risk of sarcopenia (P_overall<0.05, P_non-linear<0.05). Compared with the elderly with an LPA duration of 0 h· week⁻¹, the risk of sarcopenia in the elderly with an LPA duration of 12.6 h· week⁻¹ was the lowest (OR=0.42, 95%CI: 0.21, 0.83). Compared with the elderly with a total physical activity volume of 15.0 MET-h· week⁻¹, the elderly with a total physical activity volume of 46.0 MET-h· week⁻¹ had the lowest risk of sarcopenia (OR=0.57, 95%CI: 0.38, 0.84). There was no statistically significant association between weekly MVPA duration and the risk of sarcopenia (P>0.05). Conclusion Increasing weekly LPA duration and total physical activity volume would help to reduce the risk of sarcopenia.

Intravitreal injection of anti-vascular endothelial growth factor(VEGF)agents has become the primary treatment for macular edema associated with retinal vascular disease such as diabetic retinopathy and retinal vein occlusion, but there are limitations such as variable treatment efficacy and insufficient durability of therapeutic effects. As the first bispecific antibody applied in ophthalmic treatment, Faricimab achieves favorable outcomes by simultaneously targeting both VEGF-A and angiopoietin-2(Ang-2)pathways. Based on evidence from recent clinical trials and real-world studies, this article reviews the research progress on Faricimab for the treatment of diabetic macular edema(DME), retinal vein occlusion-associated macular edema(RVO-ME)and refractory macular edema compared to the therapeutic effects of other agents. Additionally, based on Faricimab's safety characteristics and future potential, its therapeutic prospects for macular edema associated with retinal vascular diseases are discussed. This review aims to provide evidence-based references for optimizing clinical treatment strategies, thereby contributing to mitigating the risk of vision loss due to macular edema.

Background With economic development and globalization, shift work has become prevalent across industries. Its relationship with type 2 diabetes mellitus (T2DM) attracts increasing attention. Objective To thoroughly explore the relationship between shift work and T2DM, and analyze the impacts of specific shift patterns on T2DM, so as to provide a basis for formulating reasonable shift schedules. Methods We conducted a 1:2 matched case-control study among adults (20-60 years) who ordered occupational health examinations at the Wuxi No.8 People's Hospital from November to December 2023. The case group comprised 200 T2DM patients, while the controls were 400 age-stratified matched non-diabetic individuals. General demographic characteristics, behavioral habits, medical history, and shift work exposure data (including shift patterns, frequency, and length of service) 5 years prior to diagnosis were collected through standardized questionnaires. Logistic regression adjusted for selected confounders was employed to evaluate the association between shift work and T2DM. Results The logistic regression analysis demonstrated that shift work was associated with an increased risk of T2DM. After adjusting for confounding factors, shift workers had a 3.55 times higher risk of being diagnosed T2DM compared to non-shift workers (OR=3.55, 95%CI: 1.026, 12.263). The risk varied across different shift patterns, and the three-shift two-rotation system showed the highest risk (OR=4.17, 95%CI: 1.921, 9.035), followed by the two-shift system (OR=2.94, 95%CI: 2.016, 4.281) and four-shift three-rotation system (OR=2.66, 95%CI: 1.611, 6.093). Workers with more than 3 monthly shift days had a 2.74-fold increased risk (95%CI: 1.658, 4.512) compared to non-shift workers. Additionally, working more than 8 h daily (OR=1.74, 95%CI: 1.185, 2.562) and having more than 20 years of service (OR=2.51, 95%CI: 1.581, 3.976) were both significantly associated with a higher T2DM risk. The trend tests revealed that each incremental increase in monthly shift days and length of service elevated T2DM risk by 2.61 times (95%CI: 1.813, 3.765) and 1.49 times (95%CI: 1.147, 1.931), respectively (P<0.05). Conclusion Shift work is an independent risk factor for T2DM, with three-shift two-rotation system posing the highest risk. Shift frequency, daily working hours, and length of service are all significant factors affecting the risk of T2DM. These findings support industry-specific shift policy reform and targeted glucose monitoring and health interventions are recommended for workers engaged in high-risk shift patterns (e.g., three-shift two-rotation system, frequent shifts) and those with prolonged shift work history (>20 years).

Objective Auditory brainstem response(ABR)is an objective electrophysiological test that evalu-ates a patient's hearing,and the ABR is interpreted primarily by recognizing the latency of waves Ⅰ through Ⅴ.The latency of wave Ⅰ to wave Ⅴ has important reference value for clinicians to judge the status of patients' auditory neu-ral pathways,so accurate interpretation of the results of this examination is particularly important.However,the a-nalysis of the result of the ABR entirely depends on the auditory teacher's ability to recognize and interpret the hu-man eye,which makes it difficult for inexperienced auditory teachers to interpret ABR waveforms.In order to solve this problem,many scholars proposed to use machine learning(ML)model to objectively interpret ABR results.ML has strong learning ability and can independently complete an objective and accurate interpretation of ABR re-sults,which brings the dawn for the objective and accurate interpretation of ABR results.

Objective To investigate the relationship between high DNA stainability(HDS)and routine semen parameters.Methods Semen samples were collected from 396 men of childbearing age who were admitted to our department.Correlations of HDS with routine semen parameters and age were analyzed.Multiple linear regression analysis was performed to identify the routine semen parameters that had the greatest influence on HDS.The correlation of HDS and DNA fragmentation index(DFI)with routine semen parameters and age in 244 patients with teratozoospermia was analyzed.The 244 patients were divided into extremely severe,severe,moderate,and mild teratozoospermia groups,and differences in HDS,DFI,and routine semen parameters were compared among the four groups.Results HDS was negatively correlated with total sperm count,sperm concentration,sperm progressive motility,and normal sperm morphology rate(NSMR)(P<0.01).After adjusting for potential confounders,including total sperm count,sperm concentration,sperm progressive motility,NSMR,and DFI,NSMR had the most significant negative effect on HDS(P<0.05).In the 244 patients with teratozoospermia,HDS was negatively correlated with NSMR(P<0.01)and positively correlated with the percentage of sperm head and tail abnormalities(P<0.05),while DFI was positively correlated with the percentage of sperm tail abnormalities(P<0.01).There was a significant difference in the percentage of sperm head abnormalities among the four teratozoospermia groups.The more severe the malfor-mation,the higher the percentage of sperm head abnormalities was(P<0.001).HDS in the extremely severe teratozoospermia group was significantly higher than that in the mild and moderate teratozoospermia groups(P<0.05).No significant differences in DFI were found among the four groups(P>0.05).Conclusion HDS was closely correlated with routine semen parameters and was a crucial biomarker for assessing sperm quality,particularly the extent of sperm head abnormalities.

Objective To investigate the research hotspot and development trend of noise-induced hearing loss(NIHL)in the past 30 years.Methods The CNKI(China national knowledge infrastructure)database,Wanfang Medical network and VIP database.NoteExpress were used for literature screening.CiteSpace 6.1.R6 software were used for bibliometric analysis and data visualization.Results A total of 3 823 articles were included for analy-sis.The top 3 keywords were:"noise","hearing loss",and"noise-induced deafness".A total of 358 literatures were published on the pathogenesis of NIHL.The pathogenesis included oxidative stress,genetic susceptibility,mechanical damage,microcirculation disturbance,calcium overload,etc.Conclusion The number of papers pub-lished in the field of NIHL has increased year by year,and the overall development can be divided into three stages:exploration of the influence of noise,research on etiology,and prevention and assessment of occupational noise-in-duced hearing loss.In terms of pathogenesis,the oxidative stress mechanism has been widely recognized by schol-ars,and genetic susceptibility has become a research hotspot.

Objective To analyze the imaging features of cerebral small vessel disease in patients with type 2 diabetes mellitus by multimodal MRI.Methods The clinical data of 160 patients with cerebral small vessel disease admitted to our hospital from January to December 2020 were retrospectively analyzed.According to whether they were complicated with type 2 diabetes mellitus,they were divided into the diabetic group and the non-diabetic group,with 80 cases in each group.Both groups underwent multimodal MRI scans.And the severity of lacunar infarction,the severity of subcortical and periventricular white matter lesions,white matter integral and cerebral microbleeds of patients in the two groups were compared.Results The severity of lacunar infarction(χ2=34.076,P=0.001),subcortical white matter lesions(χ2=25.000,P=0.001),periventricular white matter lesions(χ2=22.895,P=0.001)and white matter integral(t=12.370,P=0.001)of patients in the diabetic group were significantly higher than those in the non-diabetic group.No cerebral microbleeds were detected in either group of patients.Conclusion Patients with cerebral small vessel disease and type 2 diabetes mellitus show characteristic multimodal MRI changes.The increase in the number of lacunar infarction lesions and the aggravation of white matter lesions can be used as the characteristic imaging basis for the diagnosis of type 2 diabetes mellitus related cerebral small vessel disease.

Objective This study aims to explore the diagnostic value of medical indicators in identifying diuretic resistance(DR)among patients with heart failure(HF)using machine learning methods such as Least Absolute Shrinkage and Selection Operator(LASSO)regression.An early recognition model for diuretic resistance in heart failure patients is constructed to provide clinicians with timely intervention opportunities and reduce hospitalization duration.Methods 267 heart failure patients from Tianjin Chest Hospital were included in the study.Standard urine output and DR status were employed as dependent factors,whereas 64 clinical indicators were gathered as independent variables.Depending on the kind of dependent variable,two modeling strategies were used.The first method used LASSO regression to fit the model,and 10-fold cross-validation was used to find the ideal regularization parameter.Standard urine output was used to predict diuretic resistance in the test set.Root mean square error(RMSE),coefficient of determination(R2),and classification accuracy were employed to assess the model's performance.In the second method,the most pertinent subset of features in relation to DR status was selected utilizing the max-relevance and min-redundancy(mRMR)algorithm.After that,three machine learning classifiers were used for classification:support vector machines(SVM),random forests(RF),and logistic regression(LR).Accuracy,precision,recall,area under the receiver operating characteristic curve(AUC),and F1-score were used to evaluate the model's performance.Results The optimal LASSO parameter was 0.0161.On the test set,the RMSE was 0.3489,the R2 was 0.7200,and the classification accuracy was 91.36%.The AUCs for mRMR+LR,mRMR+RF,and mRMR+SVM were 0.94,0.89,and 0.95,respectively.Their accuracies were 0.86,0.77,and 0.90;precisions were 0.87,0.80,and 0.90;recalls were 0.86,0.75,and 0.90;and F1-scores were 0.86,0.75,and 0.90,respectively.In the validation set,the LASSO regression model outperformed the other machine learning methods in predictive performance.Conclusion Diuretic resistance in heart failure patients was successfully detected by both the LASSO regression model and mRMR-based machine learning classifiers.The LASSO regression model performed better than the mRMR-based classifiers,providing more accurate scientific evidence for early clinical intervention.