Objective: To systematically evaluate the application effectiveness of the full disinfection process in blood stations, identify key optimization links, and provide a scientific evidence for the formulation of specialized disinfection and hygiene standards for blood collection and supply institutions. Methods: On-site microbiological monitoring was conducted using techniques such as the plate settling method and cotton swab method. Stratified random sampling was performed on eight key control points: including evironmental air, hand hygiene, skin disinfection, blood transport boxes, pressure steam sterilization, sewage treatment, ultraviolet disinfection, and sterile swabs. Statistical analysis was performed using SPSS 20.0. Measurement data were expressed as mean ± standard deviation(x-±s), and inter-group comparisons were conducted using t-tests or analysis of variance (ANOVA). Count data were expressed as rates, and inter-group comparisons were conducted using the χ test. Trend analysis was performed using the Cochran-Armitage test, with a significance level of α=0.05. Results: The colony removal rate of plasma air disinfection machines (94.2%±0.8%) was significantly higher than that of the ultraviolet group (P<0.05). The qualification rate of quick-drying disinfectant hand was 100% within 30 days after opening the bottle, but decreased to 93.3% after 40 days (P<0.01). The qualification rate of disinfection for blood transport boxes using 500 mg/L chlorine-containing disinfectant (100%) was significant higher 75% alcohol (60%, P< 0.05). Skin disinfection with 2% alcoholic chlorhexidine gluconate balanced effectiveness and user experience (satisfaction score 4.8±0.3). The qualification rates for core procedures such as pressure steam sterilization and sewage treatment were both 100%. Conclusion: The current disinfection procedures in blood collection and supply institutions are reliable. The effective usage period of hand disinfectants, disinfection methods for transport boxes, and usage duration of sterile swabs are the main points for optimization. It is recommended that the opened hand disinfectants be used for ≤30 days and that chlorine-containing disinfectants be prioritized for wiping transport boxes, providing empirical support for the revision of protocols and the formulation of standards.

Wound repair and infection have long posed significant challenges in clinical medicine.Am-phibians,adapting to complex environments through long-term natural selection,have evolved skin sys-tems with remarkable abilities to resist external damage and promote rapid wound healing,making them an important source for discovering candidate molecules for wound healing.In this study,a novel peptide composed of 22 amino acids,with the sequence"VGKAGLETAACKATNSCFNIDW"and a molecular weight of 2299.6 D,was screened from the cDNA library of Odorrana tormota and named PN-VW22.The peptide was synthesized by solid-phase synthesis,and its effects on cell proliferation were evaluated using the CCK-8 assay and scratch wound healing assay in human keratinocytes(HaCaT)and mouse em-bryonic fibroblasts(NIH3T3).Antibacterial activity was assessed by determining the minimum inhibitory concentration(MIC).Results showed that PN-VW22 at various concentrations had no significant effect on the cell viability in NIH3T3 cells(P＞0.05),but significantly enhanced HaCaT cell viability at 0.5μmol/L(P＜0.001).Meanwhile,PN-VW22 induced cell proliferation and promoted wound healing in HaCaT cells,with a healing rate of 64.44％after 24 h incubation at 0.5 μmol/L.Furthermore,PN-VW22 exhibited antibacterial activity against Staphylococcus aureus with an MIC value of 13.92 μmol/L.In sum,this study identified PN-VW22 as a novel bifunctional peptide with both wound repair and anti-infective properties,providing a new toxin peptide template for the development of wound healing drugs.

Objective To design an intelligent airborne soldier physical training system based on human body composition analysis to solve the problems in diversity of training mode,targeted training plan and high incidence of military training-related injuries.Methods The intelligent airborne military physical training system was designed with B/S architecture and developed with Python language,which was composed of four functional modules for airborne soldier information acquisition,trainee physical fitness state assessment,physical fitness training program recommendation and airborne soldier physical fitness training program evaluation.The airborne soldier information acquisition module collected and analyzed the trainee physiological parameter information with a human body composition analyzer,clarified the parameter characteristics related to physical training with considerations on military physical training requirements and constructed a trainee physical fitness assessment parameter model;the trainee physical fitness state assessment module established an evaluation model based on machine learning to realize stage-by-stage physical fitness evaluation for airborne soldiers;the physical fitness training program recommendation module was constructed based on the physical training feature similarity algorithm and graph embedding theory to provide decision making assistance for program development of airborne military physical training;the airborne soldier physical fitness training program evaluation module compared the physical fitness and evaluation results before and after training by means of list and chart,and updated the training program based on the evaluation results by calling the physical training program recommendation module.Results The intelligent airborne soldier physical training system contributed to forming an individualized physical fitness training recommendation mechanism after trainee body evaluation,modifying training program based on comparison and feedback for stage-by-stage training evaluation,so as to decrease the incidence of military training-related injuries while increasing the training efficiency.Conclusion The system developed improves airborne soldier physical training in rationality and reliability,and provides references for intelligent military training of the PLA.[Chinese Medical Equipment Journal,2025,46(2):16-23]

Blood from a case of group B epidemic cerebrospinal meningitis identified in February 2024 in Ganzhou City,Jiangxi Province,and throat swabs from close contacts were collected for isolation and culture.The isolates were subjected to serogrouping,drug sensitivity testing,and whole genome sequencing and analysis,to provide a basis for epidemiological inves-tigation and clinical drug use.One strain of Neisseria meningitidis was isolated from the blood of the case and denoted group B.The MLST type was ST-7962,with no clonal group attribution.The phylogenetic tree showed that it was genetically close to the 1977 Shanghai carrier isolate(id-52231).Drug sensitivity results indicated that the strain was sensitive to 8 drugs:azithro-mycin,cefotaxime,minocycline,ceftriaxone,chloramphenicol,meropenem,rifampicin,and benzylpenicillin;resistant to cot-rimoxazole,levofloxacin,and ciprofloxacin;and showed an intermediate response to penicillin.This report describes the first case of ST-7962 group B meningoencephalitis found in Jiangxi Province.Monitoring of Neisseria meningitidis carriage,drug re-sistance,and molecular characteristics of strains in the healthy population in this region should be strengthened,to provide la-boratory support for the clinical use of medications,traceability,and control of the pathogen underlying meningoencephalitis infection.

Objective:To develop a convolutional neural network model of whole slide imaging of cerebrospinal fluid cells for rapid and accurate identification and classification of tumor cells in cerebrospinal fluid.Methods:A total of 8 692 cerebrospinal fluid cytology smears from Huashan Hospital Affiliated to Fudan University from January 2nd, 2019, to December 27th, 2024. As randomly assigned, the training set included 4 941 benign and 1 745 malignant samples, while the validation set comprised of 1 368 benign and 638 malignant samples. Whole-slide digital images were acquired using a cytopathology scanner, cells (clusters) were annotated for classification, and a deep learning model was constructed via tiled image patches for cell detection and classification. Model performance was evaluated using accuracy, sensitivity, specificity, and other indicators. The classification efficiency of manual microscopy was compared.Results:The model achieved a mean precision of 96.75% for cerebrospinal fluid cell classification. For malignant tumor cells, the classification accuracy was 96.61% (mAP=98.36%, AUC=0.97). Subtype classification accuracies for epithelial/epithelioid tumors and small round cell tumors were 97.13% (AUC=0.98) and 95.58% (AUC=0.93), respectively. Compared with manual microscopy, which took (9.70±0.82) minutes for classifying 200 cells, (18.27±1.21) minutes for 500 cells, and often exceeded 60 minutes or infeasible for full slides, the AI model took (3.46±0.49) seconds for 200 cells, (6.76±0.82) seconds for 500 cells, and a median of 48.57 seconds for full slides ( P<0.001), representing an efficiency improvement of approximately 161-170 times, significantly enhancing diagnostic efficiency. Conclusion:This fully automated hierarchical deep learning model enables efficient and accurate tumor cell identification and classification in CSF, providing an effective auxiliary tool for the rapid diagnosis of meningeal carcinomatosis.

Wound repair and infection have long posed significant challenges in clinical medicine.Am-phibians,adapting to complex environments through long-term natural selection,have evolved skin sys-tems with remarkable abilities to resist external damage and promote rapid wound healing,making them an important source for discovering candidate molecules for wound healing.In this study,a novel peptide composed of 22 amino acids,with the sequence"VGKAGLETAACKATNSCFNIDW"and a molecular weight of 2299.6 D,was screened from the cDNA library of Odorrana tormota and named PN-VW22.The peptide was synthesized by solid-phase synthesis,and its effects on cell proliferation were evaluated using the CCK-8 assay and scratch wound healing assay in human keratinocytes(HaCaT)and mouse em-bryonic fibroblasts(NIH3T3).Antibacterial activity was assessed by determining the minimum inhibitory concentration(MIC).Results showed that PN-VW22 at various concentrations had no significant effect on the cell viability in NIH3T3 cells(P＞0.05),but significantly enhanced HaCaT cell viability at 0.5μmol/L(P＜0.001).Meanwhile,PN-VW22 induced cell proliferation and promoted wound healing in HaCaT cells,with a healing rate of 64.44％after 24 h incubation at 0.5 μmol/L.Furthermore,PN-VW22 exhibited antibacterial activity against Staphylococcus aureus with an MIC value of 13.92 μmol/L.In sum,this study identified PN-VW22 as a novel bifunctional peptide with both wound repair and anti-infective properties,providing a new toxin peptide template for the development of wound healing drugs.

Aim To study the mechanism of adipose mesenchymal stem cell exosomes(ASC-exo)inhibition of fluorescein isothiocyanate(FITC)-induced atopic dermatitis(AD).Methods The mouse age,extrac-tion method,and the concentration of a solution of typeⅠ collagen enzyme and other conditions were compared to study the effects on the morphology and quantity of adipose mesenchymal stem cells(ASCs)after extrac-ted.FITC-induced mouse model in vivo was estab-lished and different doses of ASC-exo were given to measure ear thickness,ear weight and ear scratching times of mice.HE staining was used to observe the pathological changes of ear tissue of mice.The non-toxicity of ASC-exo was detected.IgE,IL-5,IL-13 and other cytokines were detected by ELISA.The gene ex-pressions of TSLP,IL-33,occludin,Claudin-1(CLDN-1)and E-cadherin were detected by RT-qPCR.The protein expression was detected by immunohistochemis-try.Results An efficient method for extracting ASCs was established.Compared with the blank group,mice in the model group showed obvious AD symptoms.Compared with the model group,ASC-exo administra-tion group significantly reduced the number of ear scratches,epidermal thickening,inflammatory cell infil-tration and the secretion of Th2 cytokines IL-5 and IL-13.Meanwhile,ASC-exo administration group signifi-cantly increased the expression of structural proteins CLDN-1 and occludin in epithelial cells and decreased the expression of TSLP and IL-33.Conclusions ASC-exo can significantly improve Th2 skin inflamma-tion in AD mice,and its mechanism may be through in-creasing the expression of tight junction proteins and adhesion link protein in epithelial cells,repairing the skin barrier,and inhibiting the key promoters of allergy TSLP and IL-33.

This study aimed to explore the therapeutic mechanisms of Colquhounia Root Tablets(CRT) in treating diabetic kidney disease(DKD) by integrating biomolecular network mining with animal model verification. By analyzing clinical transcriptomics data, an interaction network was constructed between candidate targets of CRT and DKD-related genes. Based on the topological eigenvalues of network nodes, 101 core network targets of CRT against DKD were identified. These targets were found to be closely related to multiple pathways associated with type 2 diabetes, immune response, and metabolic reprogramming. Given that immune-inflammatory imbalance driven by metabolic reprogramming is one of the key pathogenic mechanisms of DKD, and that many core network targets of CRT are involved in this pathological process, receptor for advanced glycation end products(RAGE)-reactive oxygen species(ROS)-phosphatidylinositol 3-kinase(PI3K)-protein kinase B(AKT)-nuclear factor-κB(NF-κB)-NOD-like receptor family pyrin domain containing 3(NLRP3) signaling axis was selected as a candidate target for in-depth research. Further, a rat model of DKD induced by a high-sugar, high-fat diet and streptozotocin was established to evaluate the pharmacological effects of CRT and verify the expression of related targets. The experimental results showed that CRT could effectively correct metabolic disturbances in DKD, restore immune-inflammatory balance, and improve renal function and its pathological changes by inhibiting the activation of the RAGE-ROS-PI3K-AKT-NF-κB-NLRP3 signaling axis. In conclusion, this study reveals that CRT alleviates the progression of DKD through dual regulation of metabolic reprogramming and immune-inflammatory responses, providing strong experimental evidence for its clinical application in DKD.
Animals ; Diabetic Nephropathies/metabolism* ; Receptor for Advanced Glycation End Products/genetics* ; NF-kappa B/genetics* ; Signal Transduction/drug effects* ; Rats ; NLR Family, Pyrin Domain-Containing 3 Protein/genetics* ; Proto-Oncogene Proteins c-akt/genetics* ; Drugs, Chinese Herbal/administration & dosage* ; Male ; Phosphatidylinositol 3-Kinases/genetics* ; Reactive Oxygen Species/metabolism* ; Humans ; Plant Roots/chemistry* ; Rats, Sprague-Dawley ; Tablets/administration & dosage*

Blood from a case of group B epidemic cerebrospinal meningitis identified in February 2024 in Ganzhou City,Jiangxi Province,and throat swabs from close contacts were collected for isolation and culture.The isolates were subjected to serogrouping,drug sensitivity testing,and whole genome sequencing and analysis,to provide a basis for epidemiological inves-tigation and clinical drug use.One strain of Neisseria meningitidis was isolated from the blood of the case and denoted group B.The MLST type was ST-7962,with no clonal group attribution.The phylogenetic tree showed that it was genetically close to the 1977 Shanghai carrier isolate(id-52231).Drug sensitivity results indicated that the strain was sensitive to 8 drugs:azithro-mycin,cefotaxime,minocycline,ceftriaxone,chloramphenicol,meropenem,rifampicin,and benzylpenicillin;resistant to cot-rimoxazole,levofloxacin,and ciprofloxacin;and showed an intermediate response to penicillin.This report describes the first case of ST-7962 group B meningoencephalitis found in Jiangxi Province.Monitoring of Neisseria meningitidis carriage,drug re-sistance,and molecular characteristics of strains in the healthy population in this region should be strengthened,to provide la-boratory support for the clinical use of medications,traceability,and control of the pathogen underlying meningoencephalitis infection.

Objective To design an intelligent airborne soldier physical training system based on human body composition analysis to solve the problems in diversity of training mode,targeted training plan and high incidence of military training-related injuries.Methods The intelligent airborne military physical training system was designed with B/S architecture and developed with Python language,which was composed of four functional modules for airborne soldier information acquisition,trainee physical fitness state assessment,physical fitness training program recommendation and airborne soldier physical fitness training program evaluation.The airborne soldier information acquisition module collected and analyzed the trainee physiological parameter information with a human body composition analyzer,clarified the parameter characteristics related to physical training with considerations on military physical training requirements and constructed a trainee physical fitness assessment parameter model;the trainee physical fitness state assessment module established an evaluation model based on machine learning to realize stage-by-stage physical fitness evaluation for airborne soldiers;the physical fitness training program recommendation module was constructed based on the physical training feature similarity algorithm and graph embedding theory to provide decision making assistance for program development of airborne military physical training;the airborne soldier physical fitness training program evaluation module compared the physical fitness and evaluation results before and after training by means of list and chart,and updated the training program based on the evaluation results by calling the physical training program recommendation module.Results The intelligent airborne soldier physical training system contributed to forming an individualized physical fitness training recommendation mechanism after trainee body evaluation,modifying training program based on comparison and feedback for stage-by-stage training evaluation,so as to decrease the incidence of military training-related injuries while increasing the training efficiency.Conclusion The system developed improves airborne soldier physical training in rationality and reliability,and provides references for intelligent military training of the PLA.[Chinese Medical Equipment Journal,2025,46(2):16-23]