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.

Objective To construct an artificial intelligence assisted diagnosis model based on deep learning for dynamically recognizing gastric lesions and their locations under gastroscopy in real time,and to evaluate its ability to detect and recognize gastric lesions and their locations.Methods The gastroscopy videos of 104 patients in our hospital was retrospectively analyzed,and the video frames were manually annotated.The annotated picture frames of lesion category were divided into the training set and the validation set according to the ratio of 8∶2,and the annotated picture frames of location category were divided into the training set and the validation set according to the patient sources at the ratio of 8∶2.These sets were utilized for training and validating the respective models.YoloV4 model was used for the training of lesion recognition,and ResNet152 model was used for the training of location recognition.The accuracy,sensitivity,specificity,positive predictive value,negative predictive value and location recognition accuracy of the auxiliary diagnostic model were evaluated.Results A total of 68 351 image frames were annotated,with 54 872 frames used as the training set,including 41 692 frames for lesion categories and 13 180 frames for location categories.The validation set consisted of 13 479 frames,comprising 10 422 frames for lesion categories and 3 057 frames for location categories.The lesion recognition model achieved an overall accuracy of 98.8%,with a sensitivity of 96.6%,specificity of 99.3%,positive predictive value of 96.3%,and negative predictive value of 99.3% in validation set.Meanwhile,the location recognition model demonstrated an top-5 accuracy of 87.1% .Conclusion The artificial intelligence assisted diagnosis model based on deep learning for real-time dynamic recognition of gastric lesions and their locations under gastroscopy has good ability in lesion detection and location recognition,and has great clinical application prospects.

Objective:To evaluate the gene mutation profile and prognostic significance of adult cytogenetically normal acute myeloid leukemia (CN-AML) with CEBPA-bZIP mutation. Methods:Targeted sequencing was implemented on the diagnostic bone marrow DNA samples of 141 adult CN-AML subjects with CEBPA-bZIP mutation. The nomogram model for leukemia-free survival (LFS) rate was generated by combining genetic abnormalities and clinical data. Risk stratification was conducted based on prognostic variables and the effect of risk-adjusted consolidation therapy was investigated by Kaplan-Meier method. Results:Four variables were finally included in our nomogram model after multivariate Cox analysis,and an equation for risk score calculation was obtained,risk score=1.3002×white blood cell (WBC) (≥18.77×109/L)+1.4065×CSF3R mutation positive+2.6489×KMT2A mutation positive+1.0128×DNA methylation-related genes mutation positive. According to the nomogram model,patients were further divided into low-risk group (score=0,n=46) and high-risk group (score>0,n=95). Prognostic analysis showed that the 5-year LFS rate,5-year overall survival (OS) rate,and 5-year cumulative incidence of relapse (CIR) of patients who received allogeneic hematopoietic stem cell transplantation (allo-HSCT) in the high-risk group were 93.5％,97.1％,and 3.5％,while those in patients who received maintenance chemotherapy were 32.9％,70.5％,and 63.4％,respectively. The differences were statistically significant (all P<0.05). Allo-HSCT could significantly improve the prognosis of patients in high-risk group. However,no corresponding benefit was observed in the low-risk group. Conclusion:Adult CN-AML with CEBPA-bZIP mutation has a complex co-mutation pattern. The nomogram model based on mutations of CFS3R,KMT2A and DNA methylation-related genes together with WBC count can further divide this subset of patients into a relatively low-risk group and a relatively high-risk group. For individuals in the high-risk group,allo-HSCT is proposed as post-remission therapy. The above data will benefit the prognosis estimation and treatment decision for adult CN-AML with CEBPA-bZIP mutation.

Objective:To observe any effect of electroacupuncture pretreatment (EP) on the function of cerebral microvascular endothelial cells in mice with middle cerebral artery obstruction (MCAO), and to explore the role of miRNA-155 RNA and the p53 pathway in determining it.Methods:Forty-two mice were randomly divided into a sham operation group, a model group, an EP group, an miR-155 inhibitor (MI) group, an miR-155 agonist (MA) group, an miR-155 inhibitor negative control (MIN) group and an miR-155 agonist negative control (MAN) group. Each group had 6 rats. All except the sham-operated and model groups received EP, followed by injecting into the corresponding lateral ventricles inhibitor and agonist in groups MI and MA, and placebos in group MIN and MAN. All 7 groups were subjected to MCAO modeling 48 hours after the EP. Twenty-four and 72 hours after the modeling, neurological deficits were quantified using modified neurological severity scoring (mNSS). All of the mice were then sacrificed and any brain tissue damage was observed using hematoxylin-eosin (HE) staining. Terminal deoxynucleotidyl transferase mediated dUTP nick-end labeling (TUNEL) was used to observe any apoptosis of endothelial cells, and enzyme-linked immunosorbent assays (ELISA) were employed to detect the level of intercellular cell adhesion molecule-1 (ICAM-1) in the serum. Apoptotic endothelial cells in the cerebral microbleed and ICAM-1, Bcl-2 and Bax positive cells were detected using immunofluorescence. Quantitative real-time polymerase chain reactions (qRT-PCR) were carried to observe the expressions of miRNA-155 RNA and YY1 and p53 proteins in the ischemia/reperfusion (I/R) region.Results:Twenty-four and 72 hours after the MCAO the average mNSS score of the EP group was significantly lower than the model group′s average. HE staining showed that the cell morphology of the EP group was more regular. The number of apoptotic cells, the expression of ICAM-1, the relative expression of ICAM-1, the Bax/Bcl-2 ratio, as well as the relative expression of miRNA-155 RNA and YY1 and p53 proteins were all then significantly lower in the EP group than in the model group, on average.The expression of miRNA-155 RNA, p53 protein and ICAM-1, as well as the Bax to Bcl-2 ratio in the MI group was then significantly lower than in the MIN group, on average.Conclusion:Electroacupuncture pretreatment improves microvascular endothelial cell functioning in the cerebrum after ischemia and reperfusion (at least in mice) and may attenuate cerebral cell injury by down-regulating the miRNA-155-mediated YY1/p53 pathway.

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.

The patient,a male newborn,was admitted to the hospital 2 hours after birth due to prematurity(gestational age 27+5 weeks)and respiratory distress occurring 2 hours postnatally.After admission,the infant developed fever and elevated C-reactive protein levels.On the fourth day after birth,metagenomic next-generation sequencing of cerebrospinal fluid indicated a positive result for Mycoplasma hominis(9 898 reads).On the eighth day,a retest of cerebrospinal fluid metagenomics confirmed Mycoplasma hominis(56 806 reads).The diagnosis of purulent meningitis caused by Mycoplasma hominis was established,and the antibiotic treatment was switched to moxifloxacin[5 mg/(kg·day)]administered intravenously for a total of 4 weeks.After treatment,the patient's cerebrospinal fluid tests returned to normal,and he was discharged as cured on the 76th day after birth.This article focuses on the diagnosis and treatment of neonatal Mycoplasma hominis purulent meningitis,introducing the multidisciplinary diagnosis and treatment of the condition in extremely preterm infants.[Chinese Journal of Contemporary Pediatrics,2024,26(4):432-436]

Objective To investigate the incidence rate,clinical characteristics,and prognosis of neonatal stroke in Shenzhen,China.Methods Led by Shenzhen Children's Hospital,the Shenzhen Neonatal Data Collaboration Network organized 21 institutions to collect 36 cases of neonatal stroke from January 2020 to December 2022.The incidence,clinical characteristics,treatment,and prognosis of neonatal stroke in Shenzhen were analyzed.Results The incidence rate of neonatal stroke in 21 hospitals from 2020 to 2022 was 1/15 137,1/6 060,and 1/7 704,respectively.Ischemic stroke accounted for 75％(27/36);boys accounted for 64％(23/36).Among the 36 neonates,31(86％)had disease onset within 3 days after birth,and 19(53％)had convulsion as the initial presentation.Cerebral MRI showed that 22 neonates(61％)had left cerebral infarction and 13(36％)had basal ganglia infarction.Magnetic resonance angiography was performed for 12 neonates,among whom 9(75％)had involvement of the middle cerebral artery.Electroencephalography was performed for 29 neonates,with sharp waves in 21 neonates(72％)and seizures in 10 neonates(34％).Symptomatic/supportive treatment varied across different hospitals.Neonatal Behavioral Neurological Assessment was performed for 12 neonates(33％,12/36),with a mean score of(32±4)points.The prognosis of 27 neonates was followed up to around 12 months of age,with 44％(12/27)of the neonates having a good prognosis.Conclusions Ischemic stroke is the main type of neonatal stroke,often with convulsions as the initial presentation,involvement of the middle cerebral artery,sharp waves on electroencephalography,and a relatively low neurodevelopment score.Symptomatic/supportive treatment is the main treatment method,and some neonates tend to have a poor prognosis.

Objective To observe the effects of melatonin on autophagy in cortical neurons of neonatal rats with hypoxic-ischemic brain damage(HIBD)and to explore its mechanisms via the PI3K/AKT signaling pathway,aiming to provide a basis for the clinical application of melatonin.Methods Seven-day-old Sprague-Dawley neonatal rats were randomly divided into a sham operation group,an HIBD group,and a melatonin group(n=9 each).The neonatal rat HIBD model was established using the classic Rice-Vannucci method.Neuronal morphology in the neonatal rat cerebral cortex was observed with hematoxylin-eosin staining and Nissl staining.Autophagy-related protein levels of microtubule-associated protein 1 light chain 3(LC3)and Beclin-1 were detected by immunofluorescence staining and Western blot analysis.Phosphorylated phosphoinositide 3-kinase(p-PI3K)and phosphorylated protein kinase B(p-AKT)protein expression levels were measured by immunohistochemistry and Western blot.The correlation between autophagy and the PI3K pathway in the melatonin group and the HIBD group was analyzed using Pearson correlation analysis.Results Twenty-four hours post-modeling,neurons in the sham operation group displayed normal size and orderly arrangement.In contrast,neurons in the HIBD group showed swelling and disorderly arrangement,while those in the melatonin group had relatively normal morphology and more orderly arrangement.Nissl bodies were normal in the sham operation group but distorted in the HIBD group;however,they remained relatively intact in the melatonin group.The average fluorescence intensity of LC3 and Beclin-1 was higher in the HIBD group compared to the sham operation group,but was reduced in the melatonin group compared to the HIBD group(P<0.05).The number of p-PI3K+and p-AKT+cells decreased in the HIBD group compared to the sham operation group but increased in the melatonin group compared to the HIBD group(P<0.05).LC3 and Beclin-1 protein expression levels were higher,and p-PI3K and p-AKT levels were lower in the HIBD group compared to the sham operation group(P<0.05);however,in the melatonin group,LC3 and Beclin-1 levels decreased,and p-PI3K and p-AKT increased compared to the HIBD group(P<0.05).The correlation analysis results showed that the difference of the mean fluorescence intensity of LC3 and Beclin-1 protein in the injured cerebral cortex between the melatonin and HIBD groups was negatively correlated with the difference of the number of p-PI3K+and p-AKT+cells between the two groups(P<0.05).Conclusions Melatonin can inhibit excessive autophagy in cortical neurons of neonatal rats with HIBD,thereby alleviating HIBD.This mechanism is associated with the PI3K/AKT pathway.

Objective To investigate the clinical phenotypes and genotypes of children with congenital fibrinogen disorder(CFD).Methods A retrospective analysis was conducted on the clinical data of 16 children with CFD.Polymerase chain reaction was used to amplify all exons and flanking sequences of the FGA,FGB,and FGG genes,and sequencing was performed to analyze mutation characteristics.Results Among the 16 children,there were 9 boys(56%)and 7 girls(44%),with a median age of 4 years at the time of attending the hospital.Among these children,9(56%)attended the hospital due to bleeding events,and 7(44%)were diagnosed based on preoperative examination.The children with bleeding events had a significantly lower fibrinogen activity than those without bleeding events(P<0.05).Genetic testing was conducted on 12 children and revealed a total of 12 mutations,among which there were 4 novel mutations,i.e.,c.80T>C and c.1368delC in the FGA gene and c.1007T>A and C.1053C>A in the FGG gene.There were 2 cases of congenital afibrinogenemia caused by null mutations of the FGA gene,with relatively severe bleeding symptoms.There were 7 cases of congenital dysfibrinogenemia mainly caused by heterozygous missense mutations of the FGG and FGA genes,and their clinical phenotypes ranged from asymptomatic phenotype to varying degrees of bleeding.Conclusions The clinical phenotypes of children with CFD are heterogeneous,and the severity of bleeding is associated with the level of fibrinogen activity,but there is a weak association between clinical phenotype and genotype.