Objective: To establish a risk assessment system for infectious disease prevention and control in schools in Shangcheng District, Hangzhou and determine risk levels for each school, and propose corresponding risk management measures, so as to provide a scientific reference for infectious disease prevention and control in primary and secondary schools. Methods: Based on the Failure Mode and Effects Analysis (FMEA) method, potential failure analysis and current situation investigation of infectious disease prevention and control risks were conducted in 110 primary and secondary schools from 2022 to 2024 in Shangcheng District, Hangzhou. Risk levels were classified using K-Means cluster analysis. Results: Through expert panel discussions using FMEA, 6 first level indicators and 28 second level indicators were identified. The top three risk priority numbers were implementation of required prevention and control measures for clustered infectious disease outbreaks in schools in the past three years ( 189.00 ), student morning/afternoon health checks (168.00), and reporting status of clustered infectious disease outbreaks in schools in the past three years (144.00). The comprehensive prevention scores of schools ranged from 61.00 to 98.00 (mean: 87.40 ). There were no statistically significant differences in the average scores(primary school: 88.17±7.39, nine year consistent education: 86.26±7.68, junior high school: 85.55±8.20, and high school: 88.72±4.91) and risk level distribution of schools with different educational stages( F/H=0.95,1.47, P >0.05).K-Means cluster analysis divided the schools into 5 risk levels with cluster centers at 93.25, 85.78, 79.69, 70.29, 61.00 ( F=309.21, P <0.05), with 80% of schools classified as low risk or below. Conclusion The infectious disease prevention and control risk assessment system for primary and secondary schools can be established, and hierarchical management can be conducted according to school risk levels, thereby improving the efficiency and effectiveness of school infectious disease prevention and control, and enhancing the precision and sustainability of prevention efforts.

ObjectivePrimary liver cancer, predominantly hepatocellular carcinoma (HCC), is a significant global health issue, ranking as the sixth most diagnosed cancer and the third leading cause of cancer-related mortality. Accurate and early diagnosis of HCC is crucial for effective treatment, as HCC and non-HCC malignancies like intrahepatic cholangiocarcinoma (ICC) exhibit different prognoses and treatment responses. Traditional diagnostic methods, including liver biopsy and contrast-enhanced ultrasound (CEUS), face limitations in applicability and objectivity. The primary objective of this study was to develop an advanced, light-weighted classification network capable of distinguishing HCC from other non-HCC malignancies by leveraging the automatic analysis of brightness changes in CEUS images. The ultimate goal was to create a user-friendly and cost-efficient computer-aided diagnostic tool that could assist radiologists in making more accurate and efficient clinical decisions. MethodsThis retrospective study encompassed a total of 161 patients, comprising 131 diagnosed with HCC and 30 with non-HCC malignancies. To achieve accurate tumor detection, the YOLOX network was employed to identify the region of interest (ROI) on both B-mode ultrasound and CEUS images. A custom-developed algorithm was then utilized to extract brightness change curves from the tumor and adjacent liver parenchyma regions within the CEUS images. These curves provided critical data for the subsequent analysis and classification process. To analyze the extracted brightness change curves and classify the malignancies, we developed and compared several models. These included one-dimensional convolutional neural networks (1D-ResNet, 1D-ConvNeXt, and 1D-CNN), as well as traditional machine-learning methods such as support vector machine (SVM), ensemble learning (EL), k-nearest neighbor (KNN), and decision tree (DT). The diagnostic performance of each method in distinguishing HCC from non-HCC malignancies was rigorously evaluated using four key metrics: area under the receiver operating characteristic (AUC), accuracy (ACC), sensitivity (SE), and specificity (SP). ResultsThe evaluation of the machine-learning methods revealed AUC values of 0.70 for SVM, 0.56 for ensemble learning, 0.63 for KNN, and 0.72 for the decision tree. These results indicated moderate to fair performance in classifying the malignancies based on the brightness change curves. In contrast, the deep learning models demonstrated significantly higher AUCs, with 1D-ResNet achieving an AUC of 0.72, 1D-ConvNeXt reaching 0.82, and 1D-CNN obtaining the highest AUC of 0.84. Moreover, under the five-fold cross-validation scheme, the 1D-CNN model outperformed other models in both accuracy and specificity. Specifically, it achieved accuracy improvements of 3.8% to 10.0% and specificity enhancements of 6.6% to 43.3% over competing approaches. The superior performance of the 1D-CNN model highlighted its potential as a powerful tool for accurate classification. ConclusionThe 1D-CNN model proved to be the most effective in differentiating HCC from non-HCC malignancies, surpassing both traditional machine-learning methods and other deep learning models. This study successfully developed a user-friendly and cost-efficient computer-aided diagnostic solution that would significantly enhances radiologists’ diagnostic capabilities. By improving the accuracy and efficiency of clinical decision-making, this tool has the potential to positively impact patient care and outcomes. Future work may focus on further refining the model and exploring its integration with multimodal ultrasound data to maximize its accuracy and applicability.

Depression is a prevalent mental illness worldwide, its multifaceted pathogenesis is still in the exploratory stage. MicroRNA (miRNA), as a crucial epigenetic regulator, plays an important role in depression. miR-124 is one of the most abundant miRNAs in the central nervous system including neurons and microglia, and involved in various biological events like neuron development and differentiation, synaptic and axonal growth, neural plasticity, inflammation and autophagy. Recent studies have reported abnormal expression of miR-124 in both depression patients and animal models. Most of the studies showed that miR-124 is upregulated in the hippocampus or prefrontal cortex in stress-induced rodent depression animal models such as CUMS, CSDS, CORT, CRS and LH but some evidence for divergence. Upregulation of miR-124 expression may be involved in depression-like behavior via CREB/BDNF/TrkB pathway, GR pathway, SIRT1 pathway, apoptosis and autophagy pathways by directly targeting these genes including Creb, Bdnf, Sirt1, Nr3c1, Ezh2 and Stat3. The downregulation of miR-124 expression in neurons is mainly involved in the neurogenesis and neuroplasticity impairments in depression by targeting the Notch signaling pathway and DDIT4/TSC1/2/mTORC1 pathway. The downregulation of miR-124 expression also was found in the activated microglia in the stress-induced models, and resulted in neuroinflammation. In summary, the abnormal expression of miR-124 in the brain of depression-related models and its related mechanisms are complex and even contradictory, and still need further research. This review provides a summary of the research progress of miR-124 in depression.

Objective To design a key nursing technique training platform for emergency response caregivers of nuclear,chemical and biological rescue.Methods The platform designed with B/S architecture used C# language for developing the server,HTML5 technology for building the user interface and JavaScript language for writing the logic of interaction,which was composed of three functional modules for video classroom,post-test and simulation training.Results The platform deve-loped realized training and assessment of key nursing techniques for nuclear,chemical and biological rescue without the restriction by time,space and teacher,and was of significance for enhancing the training efficacy.Conclusion The platform developed meets the needs of emergency response caregivers for key nursing techniques of nuclear,chemical and biological rescue.[Chinese Medical Equipment Journal,2024,45(1):37-41]

Hypoxia-inducible factor (HIF-1α), a core transcription factor responding to changes in cellular oxygen levels, is closely associated with a wide range of physiological and pathological conditions. However, its differential impacts on vascular cell types and molecular programs modulating human vascular homeostasis and regeneration remain largely elusive. Here, we applied CRISPR/Cas9-mediated gene editing of human embryonic stem cells and directed differentiation to generate HIF-1α-deficient human vascular cells including vascular endothelial cells, vascular smooth muscle cells, and mesenchymal stem cells (MSCs), as a platform for discovering cell type-specific hypoxia-induced response mechanisms. Through comparative molecular profiling across cell types under normoxic and hypoxic conditions, we provide insight into the indispensable role of HIF-1α in the promotion of ischemic vascular regeneration. We found human MSCs to be the vascular cell type most susceptible to HIF-1α deficiency, and that transcriptional inactivation of ANKZF1, an effector of HIF-1α, impaired pro-angiogenic processes. Altogether, our findings deepen the understanding of HIF-1α in human angiogenesis and support further explorations of novel therapeutic strategies of vascular regeneration against ischemic damage.
Humans ; Vascular Endothelial Growth Factor A/metabolism* ; Endothelial Cells/metabolism* ; Transcription Factors/metabolism* ; Gene Expression Regulation ; Hypoxia/metabolism* ; Cell Hypoxia/physiology*

Objective To investigate the attributable risk(AR)of Acinetobacter baumannii(AB)infection in criti-cally ill patients.Methods A multicenter retrospective cohort study was conducted among adult patients in inten-sive care unit(ICU).Patients with AB isolated from sterile body fluid and confirmed with AB infection in each cen-ter were selected as the infected group.According to the matching criteria that patients should be from the same pe-riod,in the same ICU,as well as with similar APACHE Ⅱ score(±5 points)and primary diagnosis,patients who did not infect with AB were selected as the non-infected group in a 1:2 ratio.The AR was calculated.Results The in-hospital mortality of patients with AB infection in sterile body fluid was 33.3％,and that of non-infected group was 23.1％,with no statistically significant difference between the two groups(P=0.069).The AR was 10.2％(95％CI:-2.3％-22.8％).There is no statistically significant difference in mortality between non-infected pa-tients and infected patients from whose blood,cerebrospinal fluid and other specimen sources AB were isolated(P＞0.05).After infected with AB,critically ill patients with the major diagnosis of pulmonary infection had the high-est AR.There was no statistically significant difference in mortality between patients in the infected and non-infec-ted groups(P＞0.05),or between other diagnostic classifications.Conclusion The prognosis of AB infection in critically ill patients is highly overestimated,but active healthcare-associated infection control for AB in the ICU should still be carried out.

Influenza virus causes serious threat to human life and health. Due to the inherent high variability of influenza virus, clinically resistant mutant strains of currently approved anti-influenza virus drugs have emerged. Therefore, it is urgent to develop antiviral drugs with new targets or mechanisms of action. RNA-dependent RNA polymerase is directly responsible for viral RNA transcription and replication, and plays key roles in the viral life cycle, which is considered an important target of anti-influenza drug design. From the point of view of medicinal chemistry, this review summarizes current advances in diverse small-molecule inhibitors targeting influenza virus RNA-dependent RNA polymerase, hoping to provide valuable reference for development of novel antiviral drugs.

Objective To compare the pharmacokinetic profiles of the two teriflunomide tablets in healthy Chinese subjects under fasting and fed conditions and to evaluate their bioequivalence and safety.Methods A randomized,open,single-dose,parallel trial design was used to enroll 31 and 32 healthy Chinese male subjects in the fasting and fed groups,who were randomized to a single oral dose of 14 mg of either reference or test preparation of teriflunomide tablets.The plasma concentrations of teriflunomide were determined using liquid chromatography-tandem mass spectrometry method,and Phoenix WinNonlin 8.1 software was used to calculate pharmacokinetic parameters and perform bioequivalence analysis.Results Subjects received a single oral dose of the reference and test formulations of teriflunomide.The main pharmacokinetic parameters of teriflunomide in the fasting group were as follows:Cmax were(2.14±0.27)and(2.27±0.33)μg·mL-1,AUC0-72h were(105.70±11.20)and(107.72±11.77)μg·mL-1·h,tmax was 1.49 and 0.99 h;the main pharmacokinetic parameters of teriflunomide in the fed group were as follows:Cmaxwere(1.83±0.17)and(1.75±0.22)μg·mL-1,AUC0-72h were(102.66±9.18)and(101.57±13.01)μg·mL-1·h,tmax was 4.01 and 4.99 h.The 90％confidence intervals for the geometric means of Cmax and AUC0-72h for reference and test preparations in the fasting and fed groups were in the range of 80％to 125％.Conclusion The pharmacokinetic characteristics of the 2 formulations were similar under fasting and fed administration conditions,with good bioequivalence and safety;Postprandial administration may delay the time to peak of the drug.

Objective To investigate the effect of paeoniflorin on aerobic glycolysis of macrophages induced by resiquimod.Methods THP-1 cells were treated with phorbol ester(PM A)to differentiate into macrophages.The cells were divided into control group,model group and low,medium,high dose experimental group.The cells in the control group were cultured normally;in the model group,2 μg·mL-1 resiquimod was used to stimulate macrophages for 24 h to induce aerobic glycolysis.The low,medium and high dose experimental groups were treated with 1,10 and 100 μmol·L-1 paeoniflorin for 24 h on the basis of the model group.Cell activity was detected by cell counting kit-8(CCK-8)method.Lactate and glucose determination kit were used to detect lactate secretion and glucose consumption of cells in each group.The protein and mRNA expression levels of(PKM2)and(LDHA)were detected by Western blot and real-time fluorescence quantitative polynucleotide chain reaction(q-PCR)respectively.Immunofluorescence method was used to compare the fluorescence intensity of PKM2 in each group.Results After 24 h stimulation of THP-1 cells with 2 μg·mL-1 resiquimod,the glucose contents in cell culture supernatants of control group,model group and low,medium and high dose experimental groups were(14.70±0.44),(9.83±0.43),(10.68±0.29),(11.79±0.33)and(13.63±0.74)mmol·L-1;the lactate secreted by cells were(6.17±0.48),(11.94±0.55),(9.08±0.55),(7.79±0.66)and(6.50±0.55)mmol·L-1;the protein expression levels of PKM2 in cells were 1.00±0.00,1.33±0.18,1.02±0.17,0.74±0.17 and 0.73±0.18;the protein expression levels of LDHA were 1.00±0.00,1.20±0.09,0.90±0.14,0.76±0.12 and 0.78±0.17;the PKM2 mRNA levels were 1.00±0.09,2.11±0.23,1.98±0.31,1.38±0.25 and 0.93±0.32;the LDHA mRNA levels were 1.00±0.13,1.85±0.25,1.44±0.21,0.91±0.24 and 0.96±0.14;the average fluorescence intensities of PKM2 were 136.41±33.63,217.94±5.33,210.27±1.03,204.14±3.27 and 186.79±14.03.Compared with control group,the above indicators in model group showed statistically significant differences(P＜0.05,P＜0.01);compared with model group,the differences in the above indicators in medium and high dose experimental group were all statistically significant(P＜0.05,P＜0.01).Conclusion Paeoniflorin can inhibit the aerobic glycolysis of macrophages induced by resiquimod.

Objective:To further improve the understanding of paroxysmal nocturnal hemoglobinuria (PNH), we retrospectively analyzed and summarized the clinical characteristics, treatment status, and survival status of patients with PNH in Zhejiang Province.Methods:This study included 289 patients with PNH who visited 20 hospitals in Zhejiang Province. Their clinical characteristics, comorbidity, laboratory test results, and medications were analyzed and summarized.Results:Among the 289 patients with PNH, 148 males and 141 females, with a median onset age of 45 (16-87) years and a peak onset age of 20-49 years (57.8% ). The median lactic dehydrogenase (LDH) level was 1 142 (604-1 925) U/L. Classified by type, 70.9% (166/234) were classical, 24.4% (57/234) were PNH/bone marrow failure (BMF), and 4.7% (11/234) were subclinical. The main clinical manifestations included fatigue or weakness (80.8%, 235/289), dizziness (73.4%, 212/289), darkened urine color (66.2%, 179/272), and jaundice (46.2%, 126/270). Common comorbidities were hemoglobinuria (58.7% ), renal dysfunction (17.6% ), and thrombosis (15.0% ). Moreover, 82.3% of the patients received glucocorticoid therapy, 70.9% required blood transfusion, 30.7% used immunosuppressive agents, 13.8% received anticoagulant therapy, and 6.3% received allogeneic hematopoietic stem cell transplantation. The 10-year overall survival (OS) rate was 84.4% (95% CI 78.0% -91.3% ) . Conclusion:Patients with PNH are more common in young and middle-aged people, with a similar incidence rate between men and women. Common clinical manifestations include fatigue, hemoglobinuria, jaundice, renal dysfunction, and recurrent thrombosis. The 10-year OS of this group is similar to reports from other centers in China.