OBJECTIVE To explore the transformation of the dispensing and drug pickup process in traditional Chinese medicine pharmacy （TCM Pharmacy） in our hospital based on data-intelligence-driven， aiming to improve pharmacists’ work efficiency and patients’ drug pickup experience. METHODS Value stream mapping and journey mapping were used to systematically identify non-value-added links in pharmacists’ dispensing process and key pain points in patients’ drug pickup under the traditional process. An intelligent dispensing and drug pickup system for the TCM Pharmacy was developed based on the C# and Android television platforms， and a machine-learning model was adopted to predict patients’ drug pickup waiting time. A comprehensive evaluation was performed from three perspectives： system performance， prediction accuracy， and satisfaction of pharmacists and patients. RESULTS The system successfully streamlined non-value-added links such as “waiting for writing on the board” and “searching for drugs”， and realized multimodal dynamic prompts of dispensing status through auditory （number calling） and visual （television terminal） channels. The constructed model for predicting drug pickup waiting time exhibited good fitting degree and generalization ability （mean absolute error＝4.28 min， R 2 ＝0.882）. The comprehensive satisfaction scores of pharmacists and patients in the traditional mode were significantly increased from （70.99±1.74） and （73.58±1.98） to （90.02±1.30） and （88.61±2.08） in the new system， respectively （ P ＜0.01）. CONCLUSIONS The transformation of the intelligent drug dispensing and pickup system for TCM pharmacy based on data-intelligence-driven effectively improves the efficiency of pharmacists’ dispensing work， realizes process transparency and waiting time predictability， and significantly enhances patients’ drug pickup experience.

Background Neck-related work-related musculoskeletal disorders (WMSDs) are a major type of musculoskeletal disorders with a relatively high proportion. Shanghai has a large number of occupational populations; however, the occurrence of WMSDs at neck among the occupational populations across industries in this city has not been reported, and needs to be addressed. Objective To understand the occurrence of neck-related WMSDs and their influencing factors among occupational populations in 8 industries in Shanghai, and to provide a scientific basis for the prevention and control of WMSDs in this population. Methods From February 2024 to February 2025, a cross-sectional survey employed stratified cluster sampling to select 7829 employed workers from 48 enterprises across 8 industries in Shanghai. The study investigated the occurrence of neck-related WMSDs among the participants over the preceding 12 months. Logistic regression analysis was employed to examine the relationships between WMSDs and various occupational factors. Results A total of 7770 questionnaires were collected, yielding an effective response rate of 99.2%. Overall, the positive rate of neck-related WMSDs among the participants was 11.89% (924/7770). Among different industries, the environmental sanitation industry (19.48%), pharmaceutical manufacturing industry (14.57%), and cigarette manufacturing industry (13.66%) had higher prevalence of neck-related WMSDs. Univariate analysis showed that the risk of neck-related WMSDs was higher in the following groups: those with a job tenure ≥5 years in the current position (OR=1.50–1.70), females (OR=1.77), those with higher education levels (master’s degree or above, OR=2.27), and those with worse self-rated health (very poor health, OR=4.38) (P＜0.05). Multivariate logistic regression analysis identified the following independent risk factors for neck WMSDs: environmental sanitation industry (OR=7.30, 95%CI: 4.72, 11.87), higher educational attainment (master’s degree or above: OR=2.16, 95%CI: 1.36, 3.35), worse self-rated health status (very poor: OR=1.95, 95%CI: 1.31, 2.85), work performed in a single workshop (OR=1.36, 95%CI: 1.13, 1.64), understaffing (OR=1.46, 95%CI: 1.25, 1.70), slight neck forward flexion (OR=1.64, 95%CI: 1.32, 2.06), severe neck forward flexion (OR=2.55, 95%CI: 1.97, 3.30), and maintaining a fixed neck posture for a prolonged period (OR=2.28, 95%CI: 1.93, 2.70). Conversely, work rotation (OR=0.75, 95%CI: 0.65, 0.87), adequate rest (OR=0.70, 95%CI: 0.60, 0.82), and severe back flexion (OR=0.63, 95%CI: 0.46, 0.85) were protective factors against neck-related WMSDs. For the nomogram, the area under the curve (AUC)=0.75 (95%CI: 0.74, 0.77), Hosmer-Lemeshow test P=0.764, and Brier score=0.094, indicating that the model had good discrimination and calibration. Conclusion Among the occupational populations in Shanghai, the environmental sanitation industry, pharmaceutical manufacturing industry, and cigarette manufacturing industry are identified as high-risk industries for neck-related WMSDs. Industry affiliation, educational level, work organization patterns, and awkward neck working postures are confirmed as the core influencing factors for the development of neck-related WMSDs. Targeted and comprehensive intervention measures should be formulated focusing on the aforementioned high-risk industries and key influencing factors. Multi-dimensional collaborative efforts, including ergonomic optimization, improvement of labor management systems, and strengthened health education and promotion, should be implemented to effectively control the risk of neck-related WMSDs in the occupational population, and to provide robust statistical evidence for the advancement of regional occupational health prevention and control strategies.

ObjectiveThe nucleolar protein PES1 (Pescadillo homolog 1) plays critical roles in ribosome biogenesis and cell cycle regulation, yet its involvement in cellular senescence remains poorly understood. This study aimed to comprehensively investigate the functional consequences of PES1 suppression in cellular senescence and elucidate the molecular mechanisms underlying its regulatory role. MethodsInitially, we assessed PES1 expression patterns in two distinct senescence models: replicative senescent mouse embryonic fibroblasts (MEFs) and doxorubicin-induced senescent human hepatocellular carcinoma HepG2 cells. Subsequently, PES1 expression was specifically downregulated using siRNA-mediated knockdown in these cell lines as well as additional relevant cell types. Cellular proliferation and senescence were assessed by EdU incorporation and SA-β-gal staining assays, respectively. The expression of senescence-associated proteins (p53, p21, and Rb) and SASP factors (IL-6, IL-1β, and IL-8) were analyzed by Western blot or qPCR. Furthermore, Northern blot and immunofluorescence were employed to evaluate pre-rRNA processing and nucleolar morphology. ResultsPES1 expression was significantly downregulated in senescent MEFs and HepG2 cells. PES1 knockdown resulted in decreased EdU-positive cells and increased SA‑β‑gal-positive cells, indicating proliferation inhibition and senescence induction. Mechanistically, PES1 suppression activated the p53-p21 pathway without affecting Rb expression, while upregulating IL-6, IL-1β, and IL-8 production. Notably, PES1 depletion impaired pre-rRNA maturation and induced nucleolar stress, as evidenced by aberrant nucleolar morphology. ConclusionOur findings demonstrate that PES1 deficiency triggers nucleolar stress and promotes p53-dependent (but Rb-independent) cellular senescence, highlighting its crucial role in maintaining nucleolar homeostasis and regulating senescence-associated pathways.

Objective To investigate the epidemiological characteristics of dengue fever in Shenzhen City in 2024, so as to provide insights into formulation of the preventive and control measures for dengue fever. Methods The epidemiological data of dengue cases reported in Shenzhen City in 2024 were extracted from the China Disease Prevention and Control Information System and field epidemiological survey data of dengue fever in Shenzhen City, and the temporal, regional and population distributions of dengue fever cases, source of acquire dengue virus infections, disease diagnosis and treatment and outbreaks were analyzed. The dengue virus nucleic acid was tested and the serotypes of dengue virus were characterized using real-time quantitative reverse transcription PCR (RT-qPCR) assay, and the dengue virus gene was sequenced using next-generation sequencing (NGS). In addition, the surveillance on the density of Aedes albopictus was performed using Breteau index (BI) and mosquito oviposition index (MOI). Results A total of 1 735 dengue fever cases were reported in Shenzhen City in 2024, including 952 local cases and 783 imported cases. Most imported dengue fever cases acquired infections from eight cities of Foshan, Guangzhou, Zhongshan, Jiangmen, Dongguan, Zhaoqing, Huizhou, and Zhuhai in the Pearl River Delta region (664 cases, 84.8% of total imported cases) into Baoan, Longgang, and Nanshan districts. The epidemic exhibited an early onset and rapid progression, peaking during the period between September and November (1 632 cases, 94.1% of total cases), and dengue fever cases were distributed across 73 subdistricts in 10 districts, with most cases reported in densely populated central and western regions. The dengue fever cases had a male-to-female ratio of 1.9∶1.0, and a median age of 37 (21) years, with a higher median age among local cases than among imported cases [40 (20) years vs. 33(15) years; Z = -10.30, P < 0.05]. Housework, unemployment, workers, and business service were predominant occupations (1 405 cases, 81.0% of total cases), and there was a significant difference in the constituent ratio of occupations between local and imported cases (χ² = 92.30, P < 0.05). Among the 1 735 dengue fever cases, the median duration from onset to definitive diagnosis was 3.3 (2.9) days, and 1 686 cases (97.2%) were identified in healthcare facilities, with a low rate of hospitalization and isolation seen in 1 701 inpatients with available epidemiological data (485 cases, 28.5% of total inpatients). A total of 29 outbreaks of dengue fever occurred in Shenzhen City across 2024, which primarily in construction sites (27 outbreaks, 93.1% of total). Dengue virus type I was the dominant serotype causing dengue fever in Shenzhen City in 2024. Sequencing showed that the genomes of dengue virus from multiple dengue fever cases in Shenzhen City shared a high sequence homology with those from cities neighboring Shenzhen City, and there might be intra-city transmission of dengue virus among multiple construction sites in Shenzhen City. The Aedes albopictus density was significantly higher in Shenzhen City in 2024 than in 2023, peaking from May to September. The annual MOI values ranged from 0.9 to 14.0, and the BI values ranged from 0.6 to 6.0. Conclusions The overall epidemic of dengue fever was severe in Shenzhen City in 2024, which was greatly affected by case importation from neighboring cities, construction sites-centered local transmission, and the effectives of routine mosquito vector control was not satisfactory. Integrated dengue fever control measures should be implemented, focusing on regional joint prevention and control mechanisms, capacity building for mosquito vector control, addressing challenges in epidemic containment at construction sites, and strengthening case detection and management systems.

Objective Using network pharmacology research methods and animal pharmacology experiments,explore the mechanism of antidepressant effects of traditional Chinese medicine Citron and Bergamot.Methods Using the Traditional Chinese Medicine System Pharmacology Database and Analysis Platform(TCMSP),ETCM,Symmap,Swiss Target Prediction,and Uniprot data platforms,screen the active ingredients and corresponding gene targets of Citron and Bergamot.Obtain depression gene targets using OMIM,TTD,and Cenecards data platforms.Using Venny 2.1 online software,draw Venn diagrams of the intersection of active ingredients and gene targets.Draw network diagrams between drugs,active ingredients,targets,and diseases using Cytoscape 3.7.2 software.Construct a protein-protein interaction(PPI)network diagram using the STRING data platform for intersecting genes.Using the Metascape data platform,perform gene ontology(GO)function and Kyoto Encyclopedia of Genesand and Genomes(KEGG)pathway enrichment analysis.A rat depression model was established using chronic unpredictable mild stress(CUMS)combined with solitary care,and animal experiments were conducted to verify the BDNF/TrkB/CREB signaling pathway obtained from network pharmacology research.Results The research results of network pharmacology methods show that there are 57 antidepressant active ingredients in Citron,65 antidepressant active ingredients in Bergamot,and important active ingredients include Acetic acid,3,4,7-trimethoxycoumarin and Citric acid,etc.Through the data platform,2717 depression targets and 430 intersection targets were identified.Through PPI network analysis,key gene targets for antidepressant effects in Citron and Bergamot were identified,including TP53,Protein kinase B1,CREB-binding protein,Brain derived neurotrophic factor,etc.Through KEGG analysis,it was found that important signaling pathways include pathways in cancer,PI3K-Akt signaling pathway,Neurotrophin signaling pathway,etc.By observing the neurotrophic factor BDNF/TrkB/CREB signaling pathway in depressed rats,the results showed that the medium dose groups of Citron and Bergamot could significantly increase serum BDNF content(P<0.05),and each treatment group could improve the damage of hippocampal neurons in rats.The high and medium dose groups of Citron and Bergamot significantly increased the expression of BDNF protein in the hippocampal CA1 region(P<0.05,P<0.01).Except for the low-dose group,which showed no difference in TrkB mRNA gene expression,all other treatment groups significantly increased the mRNA gene expression levels of hippocampal BDNF,TrkB and CREB(P<0.01).The medium dose group of Citron and Bergamot increased the expression of BDNF protein in the hippocampus(P<0.01),while the medium and low dose groups significantly increased the relative expression of TrkB protein in the hippocampus(P<0.05).The medium dose group showed an increasing trend in the relative expression of CREB protein.Conclusion Traditional Chinese medicine Citron and Bergamot have therapeutic effects on depression models in rats,and the mechanism of action may be related to the BDNF/TrkB/CREB signaling pathway.

Objective Exploring the mechanism of"Wushen acupuncture"in alleviating chronic fatigue in rats from the perspective of mitophagy.Methods Forty male Wistar rats were randomly allocated into a normal group and a modeling group,where the latter employed a protocol combining exhaustive swimming with tail-clamping stimuli to induce a rat model of chronic fatigue.Post-modeling,the normal group was subdivided randomly into a blank group and a presumed control group with specifics requiring clarification.Meanwhile,the modeling group was further randomized into a model group,a"Wushen acupuncture"group that underwent acupuncture at the Baihui and Sishencong points,and a non-acupoint control group,in which acupuncture was applied to 5 mm behind houshencong which is non-meridian,non-acupoint sites on the rats' heads and necks.The modeling and treatment outcomes in rats are assessed via the tail suspension test.Protein relative expression levels of adenosine 5'-monophosphate-activated protein kinase(AMPK),mammalian target of rapamycin(mTOR),and peroxisome proliferator-activated receptor γ coactivator 1-alpha(PGC-1α)in rat skeletal muscle were detected using Western blot.Meanwhile,the relative mRNA expression levels of PTEN induced putative kinase 1(PINK1)and Parkin were measured by Real-Time PCR.Results In contrast to the baseline cohort,rats in the induced fatigue model displayed a reduction in struggles,struggle duration,swaying frequency,and swaying duration(P<0.05).When juxtaposed against the fatigue-induced model group,the"Wushen acupuncture"intervention cohort manifested a substantial increase in these behavioral parameters(P<0.05).Furthermore,relative to the"Wushen acupuncture"intervention group,the non-acupoint control cohort showed a decrease in struggles,struggle duration,swaying frequency,and swaying duration(P<0.05).Versus the baseline group,the fatigue-induced model cohort demonstrated a marked decrease in the relative expression levels of AMPK,PGC-1α,PINK1,and Parkin mRNA in skeletal muscle tissue(P<0.05),alongside an increase in mTOR protein expression(P<0.05).Compared to the fatigue-induced model group,the"Wushen acupuncture"intervention led to an increase in the relative expression levels of AMPK,PGC-1α,PINK1,and Parkin mRNA(P<0.05),and a decrease in mTOR protein expression(P<0.05).When juxtaposed against the"Wushen acupuncture"intervention group,the non-acupoint control cohort showed decreased relative expression levels of AMPK,PGC-1α,PINK1,and Parkin mRNA(P<0.05),and increased mTOR protein expression(P<0.05).Conclusion The"Wushen acupuncture"have been shown to enhance the alleviation of chronic fatigue symptoms in rat models and modulate the functionality of mitochondrial autophagy.This therapeutic effect is believed to be mechanistically linked to the regulation of both the PINK1/Parkin pathway and the AMPK/mTOR signaling cascade.

Objective To address the personalized differences in motion gait between stroke patients and healthy older adults,as well as the issue of abnormal gait recognition,a deep learning fusion-based approach is proposed to effectively improve the accuracy of abnormal gait recognition.Methods A model fusing convolutional neural networks(CNN)and bidirectional long short-term memory networks(BiLSTM)was adopted,with the introduction of a residual network(ResNet).Unilateral ankle joint movement data at different walking speeds within a comfortable range were collected from healthy older adults and stroke patients.Signals from inertial sensors and electromyography sensors were used as inputs,while gait features were analyzed and gait differences between the two groups were compared.The effectiveness of the model was validated by comparing the classification performance of traditional deep learning models and CNN-ResNet-BiLSTM models with different layer combinations in terms of abnormal gait recognition accuracy.Results The CNN-ResNet-BiLSTM model,which introduced residual connectivity,performed excellently in abnormal gait recognition.Compared with traditional deep learning models such as the gated recurrent unit(GRU)and long short-term memory network(LSTM),its prediction accuracy was improved by 13.6％and 8.36％,respectively.Additionally,compared with other model combinations,this model achieved an overall accuracy of 97.78％.Conclusions The algorithm proposed in this study can be applied to stroke-related abnormal gait detection,providing technique support for the early diagnosis and precise monitoring of such diseases.

Objective To evaluate the cost-effectiveness of inclisiran injection treatment in patients with atherosclerotic heart disease(ASCVD)in China.Methods From the perspective of China's health system,according to the Markov model,patients with ASCVD were divided into inclisilan injection group and placebo group,and both groups were treated with convention-al lipid-lowering drugs.The study period was 25 years.The rate parameters,cost parameters,and effectiveness parameters were de-rived from the ORION-18 trial and other literature.Effects were expressed as quality-adjusted life-years(QALYs).The incremental cost-effectiveness ratio(ICER)was used to evaluate the economy of inclisilan injection.One-way sensitivity analysis and probabil-ity sensitivity analysis were used to verify the reliability of the results.Results The treatment effect of the inclisilan injection group was higher(10.02 QALYs),and the cost of the placebo group was lower(255 179 yuan).The ICER of the two groups was 137 850 yuan per QALY gained,and using 257 094 yuan per capita by 2022 as the threshold,the treatment would be economically advantageous.Sensitivity analysis supported this result.Conclusion At present,the additional use of inclisilan injection can get a better treatment effect,and it has economic advantages under the threshold of three times GDP per capita in China.

Objective:To conduct a scoping review on the critical values for lifestyle risk factors in young and middle-aged patients with prediabetes progressing to diabetes, so as to provide a reference for clinical screening, prevention, intervention, and patient self-management.Methods:Guided by the scoping review methodology and framework developed by Arksey et al., research questions were identified. Through systematic searches of Chinese and English literature databases, studies on risk factors in young and middle-aged patients with prediabetes progressing to diabetes published from the establishment of the database to August 11, 2024 were screened. Studies examining critical values for lifestyle risk factors were selected for data extraction, summary of findings, and qualitative analysis.Results:A total of 19 articles were ultimately included. Lifestyle risk factors encompassed diet, exercise, smoking, drinking, and step count. Specific indicators included daily sugar intake >25 grams, weekly exercise time <150 min, daily exercise time <30 min, weekly drinking ≥3 times with ≥180 ml of clear liquor per session, and daily step count <5 000 steps.Conclusions:There are different characteristics and critical values of the influence of various factors on the progress of diabetes. Future research should further standardize criteria and conduct large-scale, multicenter, long-term follow-up studies to establish optimal critical values for lifestyle factors, thereby providing evidence for diabetes screening, prevention, and intervention.

Objective To explore the association between dynamic indexes of maternal progesterone in early pregnancy and the average level and growth rate of fetal head circumference(HC)in mid-and late pregnancy.Methods This study adopted a retrospective cohort design and included 255 singleton pregnant women in the maternal and infant cohort of The First Affiliated Hospital of Xi'an Jiaotong University from January 2015 to December 2024.The progesterone levels of their early venous blood were detected and divided into two groups of progesterone trajectories,namely,fluctuating type and increasing type,by morphology.The dynamic indicators of progesterone in early pregnancy were constructed:cumulative dynamic deviation index in the first trimester(CDDI-P1T),gestational age at progesterone peak(GA-PP),and maximal relative progesterone decline in the first trimester(MRD-P1T).The average head circumference level and linear growth rate of the fetuses in the middle and late pregnancy were calculated.Generalized linear regression(GLM)was used to analyze the linear association between progesterone dynamic indicators and head circumference development.The key gestational weeks of progesterone affecting fetal head development were explored by linear regression of gestational weeks.Ordinary least squares(OLS)regression and restricted cubic spline(RCS)plots were used to draw the nonlinear association between progesterone dynamic indicators and head circumference.Results Among the 255 pregnant women included,92.5％of the progesterone trajectories in early pregnancy were fluctuating,and 7.5％were increasing.The growth rates of the increasing progesterone trajectory group were higher in the second and third trimesters than in the fluctuating group,but the differences were not statistically significant(all P＞0.05).GLM analysis showed that for every 1 unit increase in CDDI-P1T,the head circumference in the middle and late pregnancy increased significantly by 1.574 cm and 1.193 cm(Z=3.714,2.885,P＜0.01).The delay of GA-PP was negatively correlated with the head circumference in the middle pregnancy(β=-0.190 cm,95％CI:-0.339--0.041,P=0.010)but positively correlated with the head circumference growth rate in the late pregnancy(β=0.022 cm/week,95％CI:0.003-0.041,P=0.025).A 10％decrease in the decline of CDDI-P1T increased the head circumference in the middle pregnancy by 0.200 cm(95％CI:0.016-0.384,P=0.033),and a 100％decrease in the decline increased the head circumference growth rate in the late pregnancy by 0.201 cm/week(95％CI:0.002-0.399,P=0.048).The analysis of the key time window showed that for every 20 nmol/L increase in progesterone during 9.5-13 weeks of pregnancy,the mid-term head circumference increased by 0.035-0.166 cm(Z=2.452-3.517,allP＜0.05),and the late-term head circumference increased by 0.767 cm during 9-13 weeks of pregnancy(Z=2.452-3.517,all P＜0.05).When progesterone increased during 9.5-10.5 weeks of pregnancy,the growth rate of mid-term head circumference increased by 0.013-0.023 cm/week(Z=2.074-2.243,all P＜0.01).When progesterone increased during 8.5-10.5 weeks of pregnancy,the growth rate of late-term head circumference increased by 0.010-0.026 cm/week(Z=2.061-3.137,all P＜0.05).Conclusion Progesterone dynamic index is a new sensitive tool for evaluating fetal head circumference development.There is a stage-specific window period for progesterone regulation.9.5-13 weeks of pregnancy is the critical period for progesterone to affect head circumference growth,and 9.5-10.5 weeks of pregnancy is the core window for regulating the growth rate of head circumference.Therefore,it is necessary to combine progesterone dynamic index and time window for individualized intervention to promote the transformation of prenatal care from pregnancy maintenance to eugenics intervention.