Abstract Adverse childhood experiences (ACEs) exposure is a pressing and severe global public health issue. Children and adolescents exposed to multiple ACEs are highly susceptible to toxic stress and impaired physiological functioning, which significantly jeopardize their physical and mental health. Effective prevention and intervention strategies can reduce the prevalence of ACEs and mitigate their severe impacts, thereby minimizing the long term detrimental consequences on future outcomes. The review provides a comprehensive review of intervention strategies across four dimensions: individual, family, school, and public services/policy, so as to establish a theoretical foundation for implementing effective interventions for children and adolescents exposed to adverse childhood experiences.

Bacillus velezensis DJ1 exhibits broad-spectrum antagonistic activity against diverse phytopathogenic fungi, while its biocontrol mechanisms against Fusarium graminearum, the causal agent of maize stalk rot, remain poorly characterized. In this study, we integrated genomics and transcriptomics to elucidate the antifungal mechanisms of strain DJ1. The results demonstrated that DJ1 inhibited F. graminearum with the efficacy of 64.4%, while its polyketide crude extract achieved the control efficacy of 55% in pot experiments against this disease. Whole-genome sequencing revealed a single circular chromosome (3 929 792 bp, GC content of 47%) harboring 12 biosynthetic gene clusters for secondary metabolites, six of which encoded known antimicrobial compounds (macrolactin H, bacillaene, difficidin, surfactin, fengycin, and bacilysin). Transcriptomic analysis identified 243 differentially expressed genes (152 upregulated and 91 downregulated, P < 0.05), which were potentially associated with the antagonistic activity against F. graminearum. KEGG enrichment analysis highlighted activation (P < 0.05) of cysteine/methionine metabolism, pentose phosphate pathway, and polyketide biosynthesis pathways, indicating that DJ1 employed synergistic strategies involving antimicrobial compound synthesis, energy metabolism enhancement, and nutrient competition to suppress pathogens. This study provides a theoretical foundation for developing novel microbial resources and application technologies to combat phytopathogenic fungi.
Fusarium/drug effects* ; Bacillus/metabolism* ; Plant Diseases/prevention & control* ; Antifungal Agents/pharmacology* ; Genomics ; Zea mays/microbiology* ; Transcriptome ; Gene Expression Profiling ; Antibiosis ; Multigene Family ; Multiomics

Objective To investigate the therapeutic mechanism of Dingkun Dan(DKD)in polycystic ovary syndrome(PCOS)by examining the effects of microRNA-30d-5p on ovarian granulosa cells(GCs).Methods A PCOS rat model was established using dehydroepiandrosterone(DHEA).Normal rat GCs and PCOS rat GCs were cultured in vitro and divided into four groups:blank control group,model group,low-dose DKD group,and high-dose DKD group.After grouping,GCs viability was assessed using the methyl thiazolyl tetrazolium(MTT)assay,GCs apoptosis was analyzed by flow cytometry,and the gene expression of transforming growth factor β1(TGF-β1),Smad2,Smad3,and microRNA-30d-5p in GCs was measured by real-time polymerase chain reaction(RT-PCR),protein expression of TGF-β1,Smad2,and Smad3 in GCs was detected by Western Blot.Results Compared with the blank control group,the model group exhibited significantly decreased GCs viability,increased GCs apoptosis,upregulated mRNA and protein expression of TGF-β1,Smad2,and Smad3,and downregulated microRNA-30d-5p expression,the differences were statistically significant(P＜0.01).Compared with the model group,both low-and high-dose DKD groups showed increased GCs viability,reduced GCs apoptosis,downregulated mRNA and protein levels of TGF-β1 Smad2 and Smad3,elevated microRNA-30d-5p expression,and the differences were statistically significant(P＜0.05 or P＜0.01).Conclusion DKD promotes GCs proliferation by targeting Smad2 via microRNA-30d-5p,suggesting a potential therapeutic role in PCOS-related ovulatory dysfunction.

The nursing experience of buttonhole cannulation for an autogenous arteriovenous fistula with an Eluvia drug-eluting stent in a patient undergoing maintenance hemodialysis was summarized.Key nursing points included:developing a scientific and rational buttonhole cannulation plan for the autogenous arteriovenous fistula stent based on its characteristics post-stent implantation;conducting preoperative ultrasonic evaluations of the arteriovenous fistula and stent;establishing and maintaining a buttonhole tunnel at the stent site;regularly monitoring and following up on the cannulation site and the condition of the autogenous arteriovenous fistula;strengthening the observation and prevention of potential complications.Through rigorous and standardized assessments,procedures,and nursing care,the patient maintained good autogenous arteriovenous fistula function without stent-related complications such as fracture,stenosis,or infection over a 14-month follow-up period.

OBJECTIVE To retrospectively analyze the clinical efficacy of Qingchi San in the treatment of mild-to-moderate ul-cerative colitis.METHODS A retrospective analysis was conducted on 221 ulcerative colitis patients treated at the Gastroenterology Department of First Teaching Hospital of Tianjin University of Traditional Chinese Medicine from December 2014 to February 2024.Participants were divided into an observation group(n=121)and a control group(n=100).The control group received oral me-salazine,while the observation group received Qingchi San enema in addition to the control group's treatment.Both groups received a 4-week course of treatment.The two groups were compared in terms of clinical efficacy,clinical remission rate,TCM syndrome score,time to intestinal bleeding remission,and changes in inflammatory markers(C-reactive protein,erythrocyte sedimentation rate,and white blood cells)and coagulation markers(platelets and D-dimer).RESULTS After treatment,the total effective rate and clinical remission rate in the observation group were significantly higher than those in the control group(P<0.05,P<0.01).The TCM syn-drome scores for each item(diarrhea,abdominal pain,bloody stools with mucus,and tenesmus)in the observation group were signifi-cantly improved compared with those in the control group(P<0.01).The time to intestinal bleeding remission in the observation group was significantly shorter than that in the control group(P<0.01).C-reactive protein,erythrocyte sedimentation rate,and white blood cell count in the observation group were significantly decreased compared with those in the control group(P<0.05,P<0.01).There was no statistically significant difference in coagulation markers(platelets and D-dimer)between the two groups(P>0.05).No signif-icant treatment-related adverse reactions,such as liver and kidney damage,were observed during treatment.CONCLUSION Qing-chi San enema can improve the clinical efficacy of patients with mild-to-moderate ulcerative colitis,improve clinical symptoms,short-en bleeding time,and reduce inflammatory markers.

Objective To evaluate the effectiveness of a blended teaching model integrating the HBOPPPS framework(Hybrid Bridge-in,Objectives,Pre-assessment,Participatory learning,Post-assessment,Summary)and the"Cloud-based PAD Class"(Presentation-Assimilation-Discussion)in online clinical clerkship teaching for palliative oncology.Methods A self-con-trolled trial was conducted in October 2023,involving 41 undergraduate students majoring in Food Hygiene and Nutrition(Grade 2021)from Kunming Medical University.Phase 1 implemented conventional online teaching(control group),while Phase 2 adopted the"HBOPPPS+Cloud-based PAD Class"blended approach(experimental group).Teaching effectiveness was assessed via post-class examination scores,classroom participation rates,and satisfaction surveys.Results The experimental group dem-onstrated significantly higher outcomes than the control group:examination scores(86.34±4.19 vs.80.02±3.63,P＜0.05),classroom participation(51.2％vs.12.2％,P＜0.05),and teaching satisfaction(95.1％vs.80.5％,P＜0.05).Conclu-sionThe"HBOPPPS+Cloud-based PAD Class"blended teaching model effectively enhances online clinical clerkship outcomes in palliative oncology,significantly improving students' learning initiative,engagement,and classroom participation.

OBJECTIVE To explore the isolation rates,drug resistance and molecular epidemiological characteristics of carbapenem-resistant gram-negative bacilli(CRGNB)isolated from intensive care units(ICU)of a tertiary hos-pital so as to provide bases for prevention and control of the nosocomial infections caused by CRGNB.METHODS The environmental surfaces that were high frequently contacted by the patients with CRGNB infections[carbapen-em-resistant Klebsiella pneumoniae(CRKP),carbapenem-resistant Acinetobacter baumannii(CRAB),carbap-enem-resistant Pseudomonas aeruginosa(CRPA)]and their hands were randomly sampled from the ICU of a ter-tiary three-A hospital from Apr.2024 to Aug.2024.Multilocus sequence typing(MLST)and detection of drug re-sistance genes were performed by means of complete genome sequencing technique and bioinformatics,and the ho-mology between the CRGNB strains isolated from the patients and the strains isolated from their surrounding was observed.RESULTS Totally 30(7.85％)strains of CRGNB were isolated,23(6.02％)of which were CRKP,7(1.83％)were CRAB,and no strain of CRPA was detected.The molecular subtyping showed that ST 11(93.33％)was dominant among the CRKP strains,and ST2(69.23％)was dominant among the CRAB strains.The phylogenetic analysis indicated that there were clonal transmission tendencies of CRKP-ST11 and CRAB-ST2.The analysis of drug resistance genes showed that the CRAB strains mainly carried ant(3")-lla(100％),blaOXA-23(92.31％)and amvA(92.31％);blaOXA-23 and blaOXA-66 were the major carbapenems resistance genes;the CRKP strains mainly carried the drug resistance genes emrDh,rmtB1,fosA and kdeA(all were 96.67％),followed by the carbapenems resistance gene blaKPC-2(90.00％).CONCLUSIONS ST11 is the predomi-nant molecular subtype for CRGNB among the CRKP strains isolated from the ICU,anf ST2 predominant among the CRAB strains;the carrying rates of drug resistance genes are high.There is risk of clonal transmission.It is necessary to strengthen the monitoring and take comprehensive infection control measures so as to reduce the incidence of nosocomial infections.

Objective:To establish a practical patient-based internal quality control method for valproic acid drug concentration monitoring.Methods:Observational Study. A PBRTQC model based on the exponentially weighted moving average (EWMA) method was established using Python. All results of a total of 28, 757 valproic acid concentration data from February 1, 2023 to January 31, 2024 were collected and split into training set and validation set at a ratio of 80% and 20% respectively. The truncation limit (TL) was optimized by using the winsorized mean method and the trimmed mean method. Different weighting coefficients λ were set. Different TL and different λ were combined with the EWMA algorithm into different patient-based real-time quality control (PBRTQC) models. The optimized models were verified by introducing simulated constant errors (CE) and proportional errors (PE) respectively. The false positive alarm rate (FAR) was used to evaluate specificity, and the average number of patients before error detection (ANPed) was used to evaluate sensitivity. According to the daily test volume and quality target requirements, we comprehensively judged whether the performance evaluation indicators of FAR and ANPed meet the laboratory requirements. Bias detection curve was used for determination of the best model.Results:The parameters of the best PBRTQC model for valproic acid drug concentration monitoring are: trimmed mean method with 1.5 standard deviations (i.e., truncating data outside 1.5 standard deviations of the data mean), λ=0.01. The performance verification result shows that ANPed of CE and PE of this model are both less than 100. The comparison between the EQA results and the EWMA results show that the EWMA method results are comparable to the EQA results.Conclusion:A PBRTQC model for the valproic acid drug concentration monitoring project based on the EWMA method has been successfully established. It is comparable with both IQC and EQA results, which means PBRTQC may be used as a supplement to the quality control of daily quality control products.

Objective: To analyze the temporal variation patterns of sickness absenteeism among primary and secondary school students in Shanghai, so as to explore models suitable for predicting peaks and intensity of absenteeism rates. Methods: The seasonal and trend decomposition using loess (STL) method was used to analyze the seasonal and long term trend changes in sickness absenteeism among primary and secondary school students from September 1 in 2010 to June 30 in 2018, in Shanghai. A hierarchical clustering method based on Dynamic Time Warping (DTW) was employed to classify absenteeism symptoms with similar temporal patterns. Based on historical data, the study constructed and evaluated different time series algorithms and machine learning models to optimize the accuracy of predicting the trend of sickness absenteeism. Results: During the research period, the average new absenteeism rate due to illness was 16.86 per 10 000 person day for every academic year, and the trend of sickness absenteeism exhibited both seasonality and a long term upward trend, reaching its highest point in the 2017 academic year (22.47 per 10 000 person day). The symptoms of absenteeism were divided into three categories: high incidence in winter and spring (respiratory symptoms, fever and general discomfort, etc.), high incidence in summer (eye symptoms, nosebleeds, etc.) and those without obvious seasonality (skin symptoms, accidental injuries, etc.).The constructed time series models effectively predicted the trend of absenteeism due to illness, although the accuracy of predicting peak intensity was relatively low. Among them, the multi layer perceptron (MLP) model performed the best, with an root mean squared error (RMSE) of 8.96 and an mean absolute error (MAE) of 4.37, reducing 36.51% and 39.02% compared to the baseline model. Conclusion Time series models and machine learning algorithms could effectively predict the trend of sickness absenteeism, and corresponding prevention and control measures can be taken for absenteeism caused by different symptoms during peak periods.