Drawing on recent advances in modern fascial anatomy and biomechanics， this paper interprets the biomechanical implications of yin-yang balance at the physical level from the perspective of holistic force lines. It posits that holistic force lines represent the functional expression of mechanical load transmission and integration within the myofascial network； the channel sinews system and myofascial chains exhibit significant similarities in terms of their distribution， functional attributes， and principles of holistic regulation， and can thus be understood as structural-functional carriers of yin-yang balance. Accordingly， this paper provides a biomechanical interpretation of the yin-yang relationship from four aspects， including interdependence， mutual restriction， dynamic balance through waxing and waning， and mutual transformation， proposing that in a healthy state， the body relies on the continuous integration， distribution， and readjustment of the myofascial tension network to maintain overall coordination， whereas disease states are often associated with compensatory transmission of local tension abnormalities along holistic force lines， the accumulation of imbalances， and structural rigidity. The holistic force-line perspective provides a biomechanical explanatory framework for the theory of yin-yang balance and offers a new theoretical basis for clinical diagnosis and treatment to shift from empirical holistic balancing toward holistic force-line balancing based on posture， function， and tension transmission pathways.

Objective: To investigate the current status of iron metabolism among apheresis donors in Guangzhou and analyze the improvement effects of health education on iron deficiency in frequent apheresis donors. Methods: Using a generalized linear mixed model (GLMM), a 180-day follow-up was conducted on 261 eligible apheresis donors at the Guangzhou Blood Center from January to July 2024. Hemoglobin (Hb), serum ferritin (SF), unsaturated iron-binding capacity (UIBC), total iron-binding capacity (TIBC), and transferrin saturation (TS) were selected as outcome variables. The effects of gender, age group, and number of donations within 180 days on these outcomes were analyzed and modeled. A general linear model (GLM) with repeated measures was applied to 55 donors who received health education interventions, comparing changes in Hb and iron metabolism-related indicators before and after follow-up and health education. Results: No significant difference in Hb levels was observed between first-time and regular apheresis donors, but SF levels were significantly higher in first-time donors (F=6.195, P<0.05). The GLMM revealed that female donors exhibited more significant reductions in Hb (T=-12.546) and SF (T=-5.829)(P<0.05 for both). Age group showed no interactive effects on Hb or SF changes. While number of donations within 180 days had no interactive effect on Hb, SF levels significantly decreased with increased number of donations (using ≥9 donations as the reference group; P<0.05 for all groups). After health education, Hb levels remained unchanged, but SF increased compared to pre-intervention levels (mean difference: -18.571, P<0.05), though a declining trend persisted compared to baseline (mean difference from baseline to post-intervention: 23.068,P<0.05). Conclusion: Female and number of donations are primary factors contributing to SF reduction in apheresis donors. Health education interventions promote SF recovery. Extending donation intervals and reinforcing iron deficiency-related health education may improve iron status in donors.

Objective To explore the association of diabetes status with the development of tuberculosis (TB) among the community population in Shanghai, and to provide evidence for the formulation of tuberculosis prevention and control strategies. Methods This population-based cohort study was based on Shanghai Suburban Adult Cohort and Biobank (SSACB) in China. The baseline data were acquired by questionnaires, physical examinations and blood biochemistry tests. TB incidence was obtained by matching with TB management information system data. A Cox proportional risk model was established to assess the risk of tuberculosis. Results A total of 36 014 research subjects were included, with an average age of 56.3±11.3 years, of which 14 587 (40.5%) were male. Over 6 years of follow-up, 47 individuals progressed to tuberculosis (incidence rate: 19.8 per 100 000 person-year, 95% CI: 14.6 -26.4). An increased risk of TB was observed in participants with newly diagnosed diabetes compared with those without diabetes (adjusted hazard ratio [aHR], 2.73; 95% CI, 1.19 - 6.28). Conclusion The risk of tuberculosis in newly diagnosed diabetic patients is significantly increased, and strengthening tuberculosis screening for this population should be considered in practical work.

Objective To investigate the in vitro antiviral effects of Blumea balsamifera(L.)DC.extract against Coxsackievirus B5(CVB5).Methods A series of dilutions of Coxsackievirus were prepared and co-cultured with RD cells to determine the TCID50 value.Subsequently,different concentrations of the extract were added to a 96-well plate containing RD cells to evaluate their impact on cell viability.The ability of Blumea balsamifera extract to inhibit Coxsackievirus was further observed in the 96-well plate containing RD cells and the extract.Results The TCID50 value of Coxsackie virus solution was 10-7.67.The inhibition rate of Blumea balsamifera extract against Coxsackievirus increased with concentration,with an IC50 value of 7.26 mg/L.At a concen-tration of 50 mg/L,the extract caused a decrease in RD cell viability(P＜0.05),but within the concentration range of 6.25 to 50 mg/L,it increased the viability of virus-infected RD cells(P＜0.05),with a selectivity index(SI)exceeding 6.89.Conclusion Blumea balsamifera(L.)DC.extract exhibits in vitro activity against Coxsackievirus.

Working memory is an executive memory process that includes encoding, maintenance, and retrieval. These processes can be modulated by transcranial alternating current stimulation (tACS) with sinusoidal waves. However, little is known about the impact of the rate of current change on working memory. In this study, we aimed to investigate the effects of two types of tACS with different rates of current change on working memory performance and brain activity. We applied a randomized, single-blind design and divided 81 young participants who received triangular wave tACS, sinusoidal wave tACS, or sham stimulation into three groups. Participants performed n-back tasks, and electroencephalograms were recorded before, during, and after active or sham stimulation. Compared to the baseline, working memory performance (accuracy and response time) improved after stimulation under all stimulation conditions. According to drift-diffusion model analysis, triangular wave tACS significantly increased the efficiency of non-target information processing. In addition, compared with sham conditions, triangular wave tACS reduced alpha power oscillations in the occipital lobe throughout the encoding period, while sinusoidal wave tACS increased theta power in the central frontal region only during the later encoding period. The brain network connectivity results showed that triangular wave tACS improved the clustering coefficient, local efficiency, and node degree intensity in the early encoding stage, and these parameters were positively correlated with the non-target drift rate and decision starting point. Our findings on how tACS modulates working memory indicate that triangular wave tACS significantly enhances brain network connectivity during the early encoding stage, demonstrating an improvement in the efficiency of working memory processing. In contrast, sinusoidal wave tACS increased the theta power during the later encoding stage, suggesting its potential critical role in late-stage information processing. These findings provide valuable insights into the potential mechanisms by which tACS modulates working memory.
Humans ; Memory, Short-Term/physiology* ; Male ; Female ; Young Adult ; Transcranial Direct Current Stimulation/methods* ; Brain/physiology* ; Adult ; Electroencephalography ; Single-Blind Method

Objective: To preliminarily develop a multidimensional blood donor role scale based on role theory and systematically compare the psychosocial characteristic differences between award-winning donors and first-time donors in Guangzhou, and to provide an empirical reference for formulating differentiated donor retention strategies. Methods: A cross-sectional survey design was adopted. A random sample of award-winning donors and concurrently sampled first-time donors yielding 1 361 valid responses collected (721 from the award group, 640 from the first-time group). Exploratory factor analysis was used to assess the scale structure. Data were post-stratified and weighted according to the gender and age distributions of the general donor population. Independent samples t-tests, multivariate analysis of covariance (MANCOVA), and generalized linear models were employed to compare dimensional scores between the two groups. A paired t-test was conducted to analyze the annual donation frequency of award-winning donors before and after receiving the award. Results: Exploratory factor analysis yielded a 5-factor structure, including Role Identity and Expectations, Role Adaptation and Maintenance, Role Environment and Experience, Role Relationships and Conflict, and Role Incentives and Rewards, with a cumulative variance contribution rate of 56.43%. The scale demonstrated good internal consistency reliability (Cronbach's α=0.906). Known-group validity test showed that award-winning donors scored significantly higher than first-time donors on Role Identity and Expectations (t=4.366, P<0.001, d=0.240), Role Adaptation and Maintenance (t=5.436, P<0.001, d=0.500), and Role Relationships and Conflict (t=4.844, P<0.001, d=0.220). These differences remained significant after controlling for selected demographic variables (MANCOVA, Wilks' λ=0.943, P<0.001). Generalized linear models suggested that donation frequency was an independent predictor for these dimensions. Additionally, the annual donation frequency of award-winning donors was slightly higher after receiving the award than before (t=2.007, P=0.045). Conclusion: The preliminary blood donor role scale demonstrates acceptable reliability and validity and can effectively distinguish groups with different donation behavior characteristics. The study reveals that award-winning donors exhibit more positive psychological characteristics across multiple role identity dimensions and maintain their donation behavior after receiving an award. External incentives and internal role identity may jointly contribute to behavioral persistence. The findings provide a preliminary reference for further exploring the formation pathways of donor role identity and developing differentiated donor retention strategies.

[Objective] To analyze the influencing factors of repeat blood donor lapsing using a zero-inflated poisson regression model (ZIP). [Methods] The blood donation behavior of 12 498 whole blood donors from 2020 was tracked until December 31, 2023. The factors influencing the frequency of blood donations in a given year was analyzed using ZIP, and donors with 0 blood donation in that year were considered to have lapsed. The changes in relevant influencing factors associated with each blood donation were measured and modeled for analysis. [Results] The zero-inflated part of ZIP showed that the risk of lapsing of male blood donors was 2.24 times that of female blood donors (OR 95% CI:1.864-2.696, P<0.001); the risk of lapsing of the 35-44 age group and over 45 age group was respectively 40% (OR 95% CI:0.455-0.790, P<0.001) and 61%(OR 95% CI:0.268-0.578, P<0.001) lower than that of the under 25 age group; the risk of lapsing for those who have donated blood twice and ≥3 times was respectively 50% (OR 95% CI:0.405-0.609, P<0.001) and 81% (OR 95% CI:0.154-0.225, P<0.001) lower than that of first-time donors; the risk of lapsing of those with junior high or high school education was 1.2 times that of those with a college degree or higher (OR 95% CI:1.033-1.384, P<0.05); the risk of lapsing for the divorced group was 2.02 times that of the married group (OR 95% CI:1.445-2.820, P<0.001); the risk of lapsing for those with an income (Yuan) of 10 000 to 50 000, 50 000 to 100 000 and more than 100 000 was respectively 0.67 (OR 95% CI:0.552-0.818, P<0.001), 0.72 (OR 95% CI:0.591-0.884, P=0.002) and 0.67 (OR 95% CI:0.535-0.834, P<0.001) times that of those with an income (Yuan) of less than 10 000. The results of the Poisson part are consistent with the results of the zero-inflated part in terms of age and education level. [Conclusion] Blood donor lapsing is overall related to factors such as gender, age, donation frequency, education, marital status and family income. It's essential to care for those blood donors prone to lapse to retain more regular blood donors.

Pulpitis is a prevalent inflammatory disease in dentistry, and root canal therapy remains the primary clinical treatment for it. However, pulp removal leads to reduced tooth fracture resistance and complications such as secondary infection and tooth fracture. As a potential alternative, vital pulp therapy (VPT) relies on precise assessment of pulp status; yet current clinical diagnostic methods lack specificity. The establishment of appropriate animal models for pulpitis is crucial for investigating its pathogenesis, developing specific diagnostic biomarkers, and optimizing VPT strategies. This review systematically summarizes experimental animals selection based on anatomical compatibility and pathological similarity, as well as model construction methods and multimodal evaluation systems for pulpitis animal models, aiming to provide insights for related researches.

Objective:To investigate the application value of risk prediction model for acute kidney injury (AKI) after donation of cardiac death (DCD) liver transplantation based on machine learning algorithm.Methods:The retrospective cohort study was conducted. The clinicopathological data of 1 001 pairs of DCD liver transplant donors and recipients at five hospitals, including The First Affiliated Hospital of Zhejiang University School of Medicine et al, in the Chinese Liver Transplan-tation Registry from January 2015 to December 2023 were collected. Of the donors, there were 825 males and 176 females. Of the recipients, there were 806 males and 195 females, aged 52 (range, 18-75)years. There were 281 recipients included using oversampling technique, and all 1 282 recipients were divided to the training set of 897 recipients and the validation set of 385 recipients by a ratio of 7∶3 using computer-generated random numbers. Seven prediction models, including Random Forest (RF), Extreme Gradient Boosting (XGBoost), Support Vector Machine (SVM), Logistic Regression (LR), Decision Tree (DT), K-Nearest Neighbors (KNN), and Categorical Boosting (CatBoost), were constructed for AKI after liver transplantation based on machine learning algorithm. Observation indicators: (1) comparison of clinicopathological characteristics between recipients with and without AKI and donors; (2) follow-up and survival of recipients with and without AKI; (3) construction and validation of nomogram prediction model of AKI after liver transplantation; (4) construction and validation of machine learning prediction model of AKI after liver transplantation. Comparison of measurement data with normal distribution between groups was conducted using the independent sample t test. Comparison of measurement data with skewed distribution between groups was conducted using the Mann-Whitney U test, and comparison among groups was conducted using the Kruskal-Wallis H test. Comparison of count data between groups was conducted using the chi-square test or corrected chi-square test. Kaplan-Meier method was used to calculate survival rates and plot survival curves. Logistic regression model was performed for univariate and multivariate analyses. The receiver operating characteristic (ROC) curve was plotted to calculate area under curve (AUC) and 95% confidence interval ( CI). The performance of prediction model was evaluated using DeLong test, accuracy, sensitivity, specificity. The calibration curve was plotted to evaluate the performance of predicted probability and actual probability. The interpretability analysis of machine learning algorithm and SHapley Additive exPlanations was used to explain the model decision separately. Results:(1) Comparison of clinicopathological characteristics between recipients with and without AKI and donors. Of 1 001 recipients, there were 360 cases with AKI and 641 cases without AKI after liver transplantation. There were significant differences in body mass index (BMI), hepatic encepha-lopathy, hepatitis B surfact antigen (HBsAg), hepatorenal syndrome (HRS) and donor diabetes, donor blood urea nitrogen, donor alanine aminotransferase, donor aspartate aminotransferase, mass of graft, volume of blood loss during liver transplantation, warm ischema time of donor liver, and operation time between recipients with and without AKI ( Z=-4.337, χ2=9.751, 9.088, H=11.142, χ2=5.286, Z=-3.360, -2.539, -3.084, -1.730, -3.497, -1.996, -2.644, P<0.05). (2) Follow-up and survival of recipients with and without AKI. All the 1 001 recipients received follow-up. The recipients with AKI after liver transplantation were followed up for 18.6(range, 0-102.3)months, and recipients without AKI after liver transplantation were followed up for 31.9(range, 0.1-105.5)months. The 1-, 3-, and 5-year overall survival rates were 72.1%, 63.5%, and 59.3% of recipients with AKI, versus 86.7%, 76.7%, and 72.5% of recipients without AKI, respectively, showing a significant difference in overall survival between them ( χ2=26.028, P<0.05). (3) Construction and validation of nomogram predic-tion model of AKI after liver transplantation. Results of multivariate analysis showed that recipient BMI, recipient creatinine, recipient HBsAg, recipient HRS, donor blood urea nitrogen, donor crea-tinine, anhepatic phase and volume of blood loss during liver transplantation were independent risk factors for AKI of recipients after liver transplantation ( odds ratio=1.113, 0.998, 0.605, 1.580, 1.047, 0.998, 1.006, 1.157, 95% CI as 1.070-1.157, 0.996-1.000, 0.450-0.812, 1.021-2.070, 1.021-1.074, 0.996-0.999, 1.000-1.012, 1.045-1.281, P<0.05). The nomogram prediction model of AKI after liver transplantation was constructed based on the results of multivariate analysis. Results of ROC curve showed that the AUC of 0.666 (95% CI as 0.637-0.696). (4) Construction and validation of machine learning prediction model of AKI after liver transplantation. Based on the Lasso regression analysis, seven machine learning algorithm prediction models, including RF, XGBoost, SVM, LR, DT, KNN, and CatBoost, were constructed, with ROC curves of the validation set plotted. The AUC of above models were 0.863, 0.841, 0.721, 0.637, 0.620, 0.708, 0.731, accuracies were 0.764, 0.782, 0.701, 0.592, 0.605, 0.605, 0.681, sensitivities were 0.764, 0.789, 0.719, 0.588, 0.694, 0.694, 0.704, specificities were 0.763, 0.774, 0.683, 0.597, 0.511, 0.511, 0.656, respectively. Delong test showed that the RF model with the highest AUC of 0.863(95% CI as 0.828-0.899). Calibration curve analysis showed the predicted probability closest to the actual probability of RF model, indicating the model with a good validation value. Further sorting of SHAP of different clinical factors based on RF model showed that recipient BMI, donor blood urea nitrogen, volume of blood loss during liver transplantation, donor age had large effects on the output outcomes. Conclusion:The nomogram prediction model and seven machine learning algorithm prediction models for AKI after DCD liver transplantation are constructed, and the RF model based on machine learning has a better predictive performance.

Objective To identify determinants of subtherapeutic voriconazole(VRCZ)concentrations in allogeneic hematopoietic stem cell transplantation(allo-HSCT)recipients and to develop/validate a nomogram-based risk prediction model.Methods This study retrospectively analyzed 310 VRCZ therapeutic drug monitoring(TDM)measurements from allo-HSCT recipients at 310 patients who under went allo-HSCT surgery at Hebei Yanda Ludaopei Hospital from October 2022 to October 2024 and received VRCZ for the prevention and treatment of invasive fungal infections before transplantion were selected as the study subjects.Cases were stratified into target-concentration group(0.5～5.0μg/ml)and subtherapeutic group(<0.5μg/ml).Through single factor and multiple factor Logistic regression analysis,indeipendent predictive factors forvecz plasma concentration non-compliance were screened,and a column chart prediction model(NPM)was constructed.The performance of the model was evaluateding area under the receiver operating characteristic curve(AUC),Hosmer-Lemeshow(H-L)goodness-of-fit test,and decision curve analysis(DCA).Results Among 310 VRCZ-TDM measurements,71.61%(222/310)achieved target concentrations.Multivariate analysis showed that CYP2C19 intermediate metabolite,daily dose of cyclosporine A(CSA),daily dose of VRCZ,creatinine(Cr)>97 μmol/L,albumin(Alb)and C-reactive protein(CRP)were independent influencing factors for VRCZ blood drug concentration non-compliance(Wald χ2=4.046～13.221,all P＜0.05).The nomogram demonstrated excellent discrimination,calibration(H-L goodness of fit test χ2=2.663,P=0.954),and clinical utility with net benefit across 0.05～0.96 risk thresholds.Conclusion The nomogram incorporating CYP2C19 gene phenotype,daily CSA dosing,daily VRCZ dosing,Cr levels,Alb and CRP provides a validated tool for optimizing VRCZ therapy in allo-HSCT recipients,enabling precision dosing strategies.