Diabetic kidney disease（DKD） is a chronic kidney structural and functional disorder caused by diabetes. With the global prevalence of diabetes continuing to rise， DKD has gradually become a major cause of chronic kidney disease and end-stage renal disease（ESRD）， posing a serious threat to patients' quality of life and long-term health outcomes. Studies have shown that apoptosis plays a pivotal role in the development and progression of DKD， with its mechanisms involving abnormal activation of multiple signaling pathways such as Toll-like receptor 4（TLR4）/nuclear transcription factor-κB（NF-κB）/B-cell lymphoma-2（Bcl-2）/cysteinyl aspartate-specific proteinase（Caspase）-3， protein kinase R-like endoplasmic reticulum kinase（PERK）/eukaryotic initiation factor 2α（eIF2α）/activating transcript factor 4（ATF4）/CCAAT enhancer-binding protein homologous protein（CHOP）， phosphatidylinositol 3-kinase（PI3K）/protein kinase B（Akt）/glycogen synthase kinase-3β（GSK-3β）， Janus kinase 2（JAK2）/signal transducer and activator of transcription 3（STAT3）， adenosine monophosphate-activated protein kinase（AMPK）/mammalian target of rapamycin（mTOR） and silent information regulator 1（SIRT1）/tumor suppressor protein 53（p53）， thereby accelerating renal pathological damage in DKD. Extensive evidence-based medical studies have confirmed that traditional Chinese medicine（TCM）， leveraging its unique therapeutic advantages of multi-target， multi-component and multi-pathway approaches， has demonstrated remarkable efficacy and favorable safety profiles in treating DKD. Recent studies have demonstrated that active components of TCM can specifically target and modulate key effectors in apoptotic signaling pathways. Meanwhile， traditional compound formulations exert synergistic effects through multiple approaches such as replenishing deficiency and activating blood circulation， detoxifying and dredging collaterals， tonifying kidney essence， and removing stasis and purging turbidity， thereby comprehensively regulating critical pathological processes including endoplasmic reticulum stress and mitochondrial apoptosis pathways. This combined therapeutic approach of molecular targeting and holistic regulation provides novel strategies for delaying the progression of DKD. Based on this， this paper provides an in-depth analysis of key apoptotic signaling pathways and their regulatory mechanisms， while systematically summarizing recent research advances regarding the therapeutic effects of TCM active components， compound formulations， and proprietary Chinese medicines on DKD through modulation of these pathways， with particular emphasis on their underlying molecular mechanisms. These findings not only elucidate the modern scientific connotation and theoretical basis of TCM in treating DKD but also establish a solid theoretical and practical foundation for promoting the wider clinical application and further research of TCM in the field of DKD treatment.

Objective: To investigate the associations between 24 hour activity and the quality of life (QoL) in children with autism spectrum disorder (ASD), and to explore their isotemporal substitution effects, providing a reference for developing intervention strategies of their QoL. Methods: From March to June 2025, 288 children with ASD from 7 special education schools in Jinan were selected by using a cluster random sampling method. The 24 hour activity was measured by using ActiGraph wGT3X-BT triaxial accelerometers, and their QoL was assessed by applying a parent proxy Pediatric Quality of Life Inventory. Multiple linear regression was employed to analyze the associations between 24 hour activity and QoL in children with ASD. Isotemporal substitution analysis was applied to analyze the dose response relationship of 24 hour activity time and the QoL scores in children with ASD. Results: Within the 24 hour activities of children with ASD, the daily time spent in sleep, sedentary behavior (SB), light physical activity (LPA), and moderate to vigorous physical activity (MVPA) were 610.49，605.80，195.49，28.22 minutes, respectively. Multiple linear regression analysis showed that, after controlling for confounding factors such as gender, age, and parental education level, the proportion of time spent in MVPA was positively associated with QoL scores ( β =1.75) in children with ASD, whereas the proportion of time spent in SB was negatively associated with QoL scores ( β =-1.00)(both P <0.01). In the dose response relationship, reallocating time from sleep, SB, and LPA to MVPA was associated with an improvement in QoL in children with ASD, with increased scores of 1.38, 1.55, 1.47, respectively; conversely, the reverse substitution was associated with a decline in QoL, and the scores decreased by 2.31, 2.99 and 2.68, respectively, with the latter demonstrating a more pronounced effect(all P <0.05). Conclusions Enhancing the QoL for children with ASD should be grounded in the overall balance of 24 hour activity. Time reallocation strategies should be implemented with an emphasis on relatively increasing MVPA and reducing SB.

Purpose To investigate the differential diagnosis of diffusion-weighted imaging(DWI),perfusion-weighted imaging(PWI)and DWI combined with PWI in supratentorial pilocytic astrocytoma(PA)and WHO grade 2 pleomorphic xanthoastrocytoma(PXA).Materials and Methods The conventional MRI,DWI and PWI data of 23 cases of supratentorial PA and 11 cases of PXA(WHO grade 2)in the First Affiliated Hospital of Fujian Medical University from January 2010 to February 2022 were retrospectively analyzed.Supratentorial PA was further divided into lobar PA and non-lobar PA based on the lesion location.The basic data(gender,age,cystic degeneration,homogeneous enhancement,lesion size and meningeal involvement),minimum apparent diffusion coefficient,relative apparent diffusion coefficient and relative maximum cerebral blood volume were compared and analyzed between the two groups.Results The probability of leptomeningeal involvement in PXA(WHO grade 2)(36.3%)was higher than that in supratentorial PA(4.3%,P=0.029).Compared with supratentorial PA and lobar PA,PXA(WHO grade 2)had lower minimum apparent diffusion coefficient,relative apparent diffusion coefficient and higher relative maximum cerebral blood volume(t=-4.398-5.828,all P<0.05).The threshold value of minimum apparent diffusion coefficient to discriminate between supratentorial PA and PXA(WHO grade 2)was 1.09×10-3 mm2/s,and its sensitivity,specificity and area under the curve were 90.91%,83.33%and 0.947,respectively.When the differential diagnosis threshold of relative maximum cerebral blood volume was 1.79,its sensitivity,specificity and area under the curve were 90.00%,100.00%and 0.950,respectively.The area under the curve of DWI combined with PWI was 0.993,which did not significantly improve the diagnostic performance compared with DWI and PWI respectively(Z=1.371,0.928,both P>0.05).In subgroup analysis,the area under the curve of DWI combined with PWI in lobar PA and PXA(WHO grade 2)was 0.988,which did not improve the diagnostic performance compared with DWI and PWI respectively(Z=1.322,0.882,both P>0.05).Conclusion DWI and PWI are helpful in the differential diagnosis of PXA(WHO grade 2)from supratentorial PA and lobar PA,but combining DWI and PWI does not significantly improve the efficacy of differential diagnosis.

Objective To explore the effectiveness of the peripheral arterial calcification scoring system(PACSS)based on computed tomography angiography(CTA)in assessing renal function in patients with peripheral arterial disease(PAD).Methods The clinical data,CTA imaging data,and laboratory results from PAD patients who underwent lower limb artery CTA examination were retrospectively collected.The PACSS was utilized to score the calcification in both lower limb arteries.Participants were categorized into three groups based on their estimated glomerular filtration rate(eGFR)(normal group:eGFR≥90 mL/min;mild renal dysfunction group:eGFR 60-89 mL/min,and moderate to severe renal dysfunction group:eGFR＜60 mL/min).The demographic data,clinical symptoms,and comorbidities among the three groups were compared by analysis of variance(ANOVA).The Spearman correlation coefficient was employed to evaluate the relationship between eGFR,cystatin C,and PACSS score.Results The age(P＜0.001)and PACSS score(P＜0.05)of patients with renal dysfunction were significantly higher than those of patients with normal renal function.However,there were no significant differences in gender,prevalence of diabetes,hypertension,or severe limb ischemia.Spearman correlation analysis showed that eGFR was negatively correlated with PACSS score(r=-0.18 in the right lower limb,P=0.037,r=-0.24 in the left lower limb,P=0.006).In contrast,cystatin C was positively correlated with PACSS score(r=0.26 in the right lower limb,P＜0.001,r=0.22 in the left lower limb,P=0.002).Conclusion The PACSS score of lower limb artery in PAD patients is corre-lated with the severity of renal dysfunction.This finding may facilitate early warning and clinical intervention for PAD patients with renal dysfunction.

OBJECTIVE:Nowadays,machine learning algorithms are gradually being applied to predict stroke and cardiovascular disease.Compared with traditional regression models,machine learning can learn from data to achieve high prediction accuracy by exploring the flexible relationship between a large number of predictive features and outcome variables,providing a new method for the formulation of individualized treatment and rehabilitation programs.This study aims to systematically evaluate stroke functional recovery and prognosis prediction models based on machine learning,comprehensively assessing their predictive performance and clinical application potential to provide references for the development,application,and promotion of related predictive models.METHODS:This review was conducted following the PRISMA(Preferred Reporting Items for Systematic Reviews and Meta-Analyses)guidelines.Relevant literature on stroke prognosis prediction using machine learning methods was selected by searching PubMed,EMbase,Web of Science Core Collection,CNKI,WanFang,and the China Biomedical Literature Database,with the search period from January 1,2014,to July 1,2024.Two researchers independently screened the literature and extracted data based on inclusion and exclusion criteria,using the Prediction model Risk Of Bias ASsessment Tool(PROBAST)to assess model quality.RESULTS:(1)A total of 3 126 articles were obtained in the preliminary search.After screening and exclusion,18 articles were finally included.150 prediction models were constructed using 13 machine learning methods.The three most frequently used methods are Logistic Regression,Random Forest,and Extreme Gradient Boosting(XGBoost).Only one study was externally validated.Eight studies reported how the missing data were handled.(2)In terms of outcome indicators,8 studies used the combination of clinical data and imaging data to build models,9 studies only used clinical data to build models,and 1 study only used imaging data to build models.(3)Each of the 18 studies gave the most important characteristics of the study,with the most mentioned being the National Institute of Health Stroke Scale and age.All studies reported area under curve values ranging from 0.74 to 0.96,with the highest area under curve being 0.96.The overall risk of bias in all models was high.The high risk of bias in the field of model analysis was the main reason for the high risk of overall bias in all models.(4)The results of meta-analysis showed that age and National Institute of Health Stroke Scale score had significant influence on stroke prognosis,with age[MD=8.49,95％CI(6.24,10.75),P＜0.01]and National Institute of Health Stroke Scale score[MD=4.78,95％CI(2.56,7.00),P＜0.01].CONCLUSION:This study systematically evaluated the predictive model of functional recovery and prognosis of stroke based on machine learning,and all the models have good predictive potential.However,future studies should increase the sample size of the included model,adopt prospective studies,and add external validation of the model to improve the stability and prediction accuracy of the model,control the risk of bias,and contribute to the validation and promotion of the model in practical clinical applications.At the same time,the interpolation of missing values is more transparent and accurate.Although existing machine learning models show good predictive performance,it is also important to focus on the functionality and usability of the model,and the inclusion of features will reduce ease of use.We should develop easy to use model interfaces and user-friendly clinical tools to enable medical staff to better apply the model for clinical decision.

Objective:To determine the detection rate of myopia among primary and secondary school students in Hunan Province in 2022 and to analyze the influencing factors at both the school and individual levels, thereby providing a scientific basis for developing myopia prevention and control strategies.Methods:From October to November 2022, a multi-stage stratified cluster random sampling method was employed to select students from Year 4 of primary school to Year 3 of senior high school across 14 prefecture-level (autonomous prefecture) cities in Hunan Province for vision screening and questionnaire surveys. A multilevel regression model was utilized to analyze the influencing factors of myopia at both the school and individual levels.Results:A total of 189 343 primary and secondary school students were included in this study. The overall myopia detection rate was 55.56%, with a significantly higher prevalence observed in female students (60.49%) compared to males (51.03%) and in urban students (59.12%) versus those from rural areas (53.50%). A marked upward trend in myopia prevalence was identified with advancing grade levels (trend test χ2=16 246.13, P<0.001). Multilevel regression analysis revealed that at the individual level, female gender, higher grade level, parental myopia history, daily homework duration ≥2 hours after school, improper reading/writing postures, and taking breaks only after more than 15 minutes of near work were associated with an increased risk of myopia. Conversely, adequate sleep duration, outdoor activity ≥2 hours, and outdoor breaks during recess demonstrated protective effects. At the school level, non-compliant blackboard illumination uniformity emerged as a significant risk factor for myopia development. Conclusions:The detection rate of myopia among primary and secondary school students in Hunan Province remains relatively high and is associated with multiple factors at both the school and individual levels. Targeted interventions should be implemented at different levels to mitigate the risk of myopia.

In September 2023， the Measures for Scientific and Technological Ethics Review （Trial Implementation） was issued， revising the provisions related to the simplified procedure for ethical review in Chapter 3， Section 3. This revision of these provisions provides systematic guarantees for further optimizing ethical review work， ensuring that ethical review procedure is well-regulated， and improving scientific research efficiency. The “simplified procedure” does not mean reducing the quality and requirements of the review. Instead， based on always following internationally recognized ethical standards and emphasizing not violating national laws and regulations， improving the efficiency of ethical review and subsequent research work， and promoting the development of life sciences and medical research involving humans. In practical work， it introduces numerous new opportunities and challenges for the improvement of ethics review ability， such as new tests on the judgment and decision-making power of ethics committees， how to ensure the reliability and controllability of the conditions related to the simplified review procedure， and how to determine the basic conditions for adopting the simplified review procedure for review. Therefore， to actively respond to the challenges and possible risks brought by the simplified procedure review， efforts should be made to achieve three “unifications”， including the unification of researchers’ moral autonomy and the heteronomy of supervision implemented by relevant departments； the unification of the standard formulation of the simplified procedure review and the review work in practice； and the unification of ethical responsibility and legal responsibility.

OBJECTIVE To build a Tibetan-language medication service platform based on"internet+"and evaluate its effect on improving medication compliance and safety of Tibetan patients with chronic disease.METHODS Medication guidance contents of commonly used drugs in the outpatient department were summarized,translated and recorded in Tibetan-language or video to form a"text-audio-video"multi-dimensional"internet+"Tibetan-language medication service platform.A total of 387 Tibetan outpatients with chronic disease in our hospital after the implementation of"internet+"Tibetan-language medication service platform(from January 2024 to June 2024)in our hospital were selected as the intervention group,and 387 Tibetan outpatients before the implementation(from January 2023 to June 2023)were selected as the control group.Patients in the control group received conventional window-based Chinese-language medication services,while patients in the intervention group received both conventional window-based Chinese-language medication service and"internet+"Tibetan-language medication service.The medication compliance of patients was evaluated using the 12-item Medication Compliance Scale.A six-level causality assessment was conducted as the principles for analyzing adverse drug reactions(ADR)set by the National Center for ADR Monitoring.Additionally,statistics were compiled on the occurrence of ADR that were assessed as"definite""probable"or"possible"in the causality assessment.RESULTS The proportion(31.0%)of patients with good medication compliance and compliance scores[39.0(37.0,42.0)]of patients in the intervention group were significantly better than control group[7.0%,21.0(19.0,23.0)](P＜0.05).There were no statistically significant differences in the incidence of various types of ADR or the overall incidence between the two groups(P＞0.05).CONCLUSIONS The"internet+"Tibetan-language medication service platform is constructed successfully;the service can effectively improve the medication compliance of Tibetan-language patients,but its effect on improving the medication safety of patients is limited.

OBJECTIVE:Nowadays,machine learning algorithms are gradually being applied to predict stroke and cardiovascular disease.Compared with traditional regression models,machine learning can learn from data to achieve high prediction accuracy by exploring the flexible relationship between a large number of predictive features and outcome variables,providing a new method for the formulation of individualized treatment and rehabilitation programs.This study aims to systematically evaluate stroke functional recovery and prognosis prediction models based on machine learning,comprehensively assessing their predictive performance and clinical application potential to provide references for the development,application,and promotion of related predictive models.METHODS:This review was conducted following the PRISMA(Preferred Reporting Items for Systematic Reviews and Meta-Analyses)guidelines.Relevant literature on stroke prognosis prediction using machine learning methods was selected by searching PubMed,EMbase,Web of Science Core Collection,CNKI,WanFang,and the China Biomedical Literature Database,with the search period from January 1,2014,to July 1,2024.Two researchers independently screened the literature and extracted data based on inclusion and exclusion criteria,using the Prediction model Risk Of Bias ASsessment Tool(PROBAST)to assess model quality.RESULTS:(1)A total of 3 126 articles were obtained in the preliminary search.After screening and exclusion,18 articles were finally included.150 prediction models were constructed using 13 machine learning methods.The three most frequently used methods are Logistic Regression,Random Forest,and Extreme Gradient Boosting(XGBoost).Only one study was externally validated.Eight studies reported how the missing data were handled.(2)In terms of outcome indicators,8 studies used the combination of clinical data and imaging data to build models,9 studies only used clinical data to build models,and 1 study only used imaging data to build models.(3)Each of the 18 studies gave the most important characteristics of the study,with the most mentioned being the National Institute of Health Stroke Scale and age.All studies reported area under curve values ranging from 0.74 to 0.96,with the highest area under curve being 0.96.The overall risk of bias in all models was high.The high risk of bias in the field of model analysis was the main reason for the high risk of overall bias in all models.(4)The results of meta-analysis showed that age and National Institute of Health Stroke Scale score had significant influence on stroke prognosis,with age[MD=8.49,95％CI(6.24,10.75),P＜0.01]and National Institute of Health Stroke Scale score[MD=4.78,95％CI(2.56,7.00),P＜0.01].CONCLUSION:This study systematically evaluated the predictive model of functional recovery and prognosis of stroke based on machine learning,and all the models have good predictive potential.However,future studies should increase the sample size of the included model,adopt prospective studies,and add external validation of the model to improve the stability and prediction accuracy of the model,control the risk of bias,and contribute to the validation and promotion of the model in practical clinical applications.At the same time,the interpolation of missing values is more transparent and accurate.Although existing machine learning models show good predictive performance,it is also important to focus on the functionality and usability of the model,and the inclusion of features will reduce ease of use.We should develop easy to use model interfaces and user-friendly clinical tools to enable medical staff to better apply the model for clinical decision.

Objective:To synthesize a hydrolysis-resistant urushiol-modified monomer(UMM)to improve the hydrolysis resistance of light-cured composite resin,while reducing the volume shrinkage rate(VS),increasing the double bond conversion rate(DC),and mitigating the potential biosafety concerns of bisphenol A glycidyl methacrylate(Bis-GMA)monomer.Methods:UMM was synthesized by modifying urushiol via an acyl chloride reaction,and its structure was analyzed and characterized using Fourier transform infrared spectroscopy(FT-IR).Control group was consisted of Bis-GMA/triethylene glycol dimethacrylate(TEGDMA)without UMM,while 10%UMM,15%UMM,and 20%UMM groups were prepared by partially replacing Bis-GMA with UMM at mass fractions of 10%,15%,and 20%,respectively.The viscosity of UMM was measured using a rheometer.The DC of light-cured composite resin in various groups was detected by FT-IR spectroscopy,and the VS was calculated.The contact angle of light-cured composite resin in various groups was measured using the sessile drop method,and the water sorption and solubility values were calculated.The mechanical properties of light-cured composite resin in various groups were tested.The in vitro cytotoxicity of light-cured composite resin in various groups was evaluated using the cell counting kit-8(CCK-8)assay.Results:The FT-IR spectra results showed that the absorption peak of the hydroxyl group at 3 402 cm-1 disappeared,while characteristic absorption peaks of-C=O and-C=C appeared at 1 745 and 1 637 cm-1,indicating that urushiol successfully reacted with acryloyl chloride to form UMM.The viscosity of UMM ranged from 25.14 to 29.43 Pa·s.Compared with control group,the DC of light-cured composite resin in 10%UMM,15%UMM,and 20%UMM groups was significantly increased(P<0.05),while the VS was significantly decreased(P<0.05),both in a dose-dependent manner.Compared with control group,the contact angle of light-cured composite resin in 10%UMM,15%UMM,and 20%UMM groups was significantly increased(P<0.05).Compared with 10%UMM group,the contact angle of light-cured composite resin in 15%UMM and 20%UMM groups was further increased(P<0.05).Compared with control group,the water sorption and solubility values of light-cured composite resin in 10%UMM,15%UMM,and 20%UMM groups were significantly decreased(P<0.05),showing a dose-dependent trend.After 24 h of water immersion,compared with control group,the flexural strength(FS)and elastic modulus(EM)of light-cured composite resin in 10%UMM,15%UMM,and 20%UMM groups were significantly decreased(P<0.05),also in a dose-dependent manner.After 7 d of water immersion,compared with control group,the FS of light-cured composite resin in 10%UMM group was significantly increased(P<0.05),while that in 20%UMM group was significantly decreased(P<0.05).Compared with 10%UMM group,the FS of light-cured composite resin in 15%UMM and 20%UMM groups was significantly decreased(P<0.05),exhibiting a dose-dependent trend.Compared with control group,the EM of light-cured composite resin in 15%UMM and 20%UMM groups was significantly decreased(P<0.05),also in a dose-dependent manner.The relative growth rate(RGR)of the L929 cells in control,10%UMM,15%UMM,and 20%UMM groups was above 90%,with no statistically significant differences among groups(P>0.05),and all cytotoxicity results were qualified.Conclusion:A novel low-viscosity monomer UMM is successfully synthesized in this study.All UMM-containing light-cured composite resin formulations exhibit higher DC,lower VS,reduced water sorption and solubility values,improved hydrolysis resistance,and low cytotoxicity.UMM can serve as a potential resin monomer to enhance the hydrolysis resistance of light-cured composite resin.