Objective To understand the current situation of breastfeeding duration in children aged 0-5 years in Yunnan Province,and to explore the influencing factors of breastfeeding duration.Methods Using the data of the 6th National Health Service Survey in Yunnan Province,1582 children aged 0～5 years in Yunnan Province were selected as the research subjects,and the Kaplan-Meier method and Cox regression were used to analyze the influencing factors of breastfeeding duration.Results The mean duration of breastfeeding for children aged 0～5 years in Yunnan Province was 9.29 months,and region,time of complementary food addition,time of suckling and family income were the main factors influencing the duration of breastfeeding.Conclusion The duration of breastfeeding for children aged 0～5 years in Yunnan Province deviates significantly from the recommendations provided by both the World Health Organization(WHO)and China's child breastfeeding guidelines.Given the current situation,the relevant departments must enhance their focus on this issue.

Objective:To assess the predictive value of dosiomics in predicting the occurrence of bone marrow suppression (BMS) in patients with pelvic tumors during radiotherapy.Methods:A retrospective analysis was conducted on the clinical data and radiotherapy planning documents of 129 patients with pelvic region tumors who underwent radiotherapy at the First Affiliated Hospital of Nanjing Medical University from January 2019 to January 2023. The region of interest (ROI) was outlined for bone marrow in the pelvic region by Accu Contour software in planning CT, and the ROI was exported together with the dose distribution file. According to a stratified randomization grouping method, the patients were divided into the training set and test set in an 8 vs. 2 ratio. The dosiomic features were extracted from the ROI, and the two independent samples t-test and the least absolute shrinkage and selection operator (LASSO) algorithm was employed to identify the best predictive characteristics. Subsequently, the dosiomic scores were calculated. Clinical predictors were identified through both univariant and multivariate logistic regression analyses. Predictive models were constructed by using clinical predictors alone and combining clinical predictors and dosiomic scores. The efficacy of predictive model was assessed by plotting the receiver operating characteristic (ROC) curve and evaluating its performance through the area under the ROC curve (AUC), the calibration curve, and decision curve analysis (DCA). Results:Fourteen dosiomic features that showed a strong correlation with the occurrence of BMS were screened and utilized to calculate the dosiomic scores. Based on both univariant and multivariate logistic regression analyses, chemotherapy, planning target volume (PTV) and V 5 Gy were identified as clinical predictors. According to the combined model, the AUC values for the training set and test set were 0.911 and 0.868, surpassing those of the clinical model (AUC=0.878 and 0.824). Furthermore, the analysis of both the calibration curve and DCA suggested that the combined model had higher calibration and net clinical benefit. Conclusion:The combined model has a high diagnostic value for predicting BMS in patients with pelvic tumors during radiotherapy.

Objective:To investigate the prevalence of dental caries of 4-year-old children in Miyun District of Beijing by international caries detection and assessment system(ICDAS),to detect the caries activity Cariostat value and to analyze the correlation between the Cariostat value and dental caries.Methods:Totally 815 children aged 4 years in 7 kindergartens in Miyun District of Beijing were recrui-ted.The clinical examination of all children was conducted by one examiner using ICDAS.The oral de-birs and plaques were collected by one doctor who recorded the Cariostat scores.The results of clinical examination were compared between genders.At the same time,the prevalence of dental caries,the mean d3-6ft/d3_6fs and d1-6ft/d1-6fs among high Cariostat scores group(2.0-3.0),medium Cariostat scores group(1.5)and low Cariostat scores group(0-1.0)were compared.The distributions of incipi-ent caries in different Cariostat scores groups were compared among children with incipient caries only.Results:All the children had incipient caries,and 78.3％of the children had cavitated caries with ICDAS score of 3 or above.The mean d1-2t scores were 9.76±3.65,the mean d3-6ft scores was 4.64±4.43 and the mean d1-6ft scores were 14.41±3.42.The incipient caries with ICDAS score of 1-2 were widely distributed,accounting for 67.7％of the total numbers of caries.There was no significant diffe-rence in caries prevalence and caries experience between genders(P＞0.05).The proportion of children with high Cariostat scores in boys(43.6％)was higher than that in girls(33％)and the difference was statistically significant(P＜0.05).With the increase of Cariostat scores,the prevalence of cavitated caries,the mean d3-6ft/d3-6fs and d1-6ft/d,_6fs scores in children was on the increase and the difference among the three groups was statistically significant(P＜0.05).For children with incipient caries only,the distribution of incipient caries in different Cariostat scores groups was no significant difference(P＞0.05).Conclusion:ICDAS can detect early enamel demineralization of deciduous teeth in children.The prevalence of dental caries among 815 4-year-old children in Miyun District of Beijing is more serious,and incipient caries is widely distributed in children.Cariostat value reflects the status of cavi-tated caries and has no correlation with the distribution of incipient caries.Therefore,the combined ap-plication of ICDAS and Cariostat caries activity detection method is helpful for the detection of incipient caries and screening of caries high-risk children,which has great significance for the comprehensive ma-nagement of caries in children and the formulation of early preventive measures.

Aristolochic acid (AA), extracted from Aristolochiaceae plants, plays an essential role in traditional herbal medicines and is used for different diseases. However, AA has been found to be nephrotoxic and is known to cause aristolochic acid nephropathy (AAN).AA-induced acute kidney injury (AKI) is a syndrome in AAN with a high morbidity that manifests mitochondrial damage as a key part of its pathological progression. Melatonin primarily serves as a mitochondria-targeted antioxidant. However, its mitochondrial protective role in AA-induced AKI is barely reported. In this study, mice were administrated 2.5 mg/kg AA to induce AKI. Melatonin reduced the increase in Upro and Scr and attenuated the necrosis and atrophy of renal proximal tubules in mice exposed to AA. Melatonin suppressed ROS generation, MDA levels and iNOS expression and increased SOD activities in vivo and in vitro. Intriguingly, the in vivo study revealed that melatonin decreased mitochondrial fragmentation in renal proximal tubular cells and increased ATP levels in kidney tissues in response to AA. In vitro, melatonin restored the mitochondrial membrane potential (MMP) in NRK-52E and HK-2 cells and led to an elevation in ATP levels. Confocal immunofluorescence data showed that puncta containing Mito-tracker and GFP-LC3A/B were reduced, thereby impeding the mitophagy of tubular epithelial cells. Furthermore, melatonin decreased LC3A/B-II expression and increased p62 expression. The apoptosis of tubular epithelial cells induced by AA was decreased. Therefore, our findings revealed that melatonin could prevent AA-induced AKI by attenuating mitochondrial damage, which may provide a potential therapeutic method for renal AA toxicity.

OBJECTIVE: To analyze the risk factors of in-hospital death in patients with sepsis in the intensive care unit (ICU) based on machine learning, and to construct a predictive model, and to explore the predictive value of the predictive model. METHODS: The clinical data of patients with sepsis who were hospitalized in the ICU of the Affiliated Hospital of Jining Medical University from April 2015 to April 2021 were retrospectively analyzed,including demographic information, vital signs, complications, laboratory examination indicators, diagnosis, treatment, etc. Patients were divided into death group and survival group according to whether in-hospital death occurred. The cases in the dataset (70%) were randomly selected as the training set for building the model, and the remaining 30% of the cases were used as the validation set. Based on seven machine learning models including logistic regression (LR), K-nearest neighbor (KNN), support vector machine (SVM), decision tree (DT), random forest (RF), extreme gradient boosting (XGBoost) and artificial neural network (ANN), a prediction model for in-hospital mortality of sepsis patients was constructed. The receiver operator characteristic curve (ROC curve), calibration curve and decision curve analysis (DCA) were used to evaluate the predictive performance of the seven models from the aspects of identification, calibration and clinical application, respectively. In addition, the predictive model based on machine learning was compared with the sequential organ failure assessment (SOFA) and acute physiology and chronic health evaluation II (APACHE II) models. RESULTS: A total of 741 patients with sepsis were included, of which 390 were discharged after improvement, 351 died in hospital, and the in-hospital mortality was 47.4%. There were significant differences in gender, age, APACHE II score, SOFA score, Glasgow coma score (GCS), heart rate, oxygen index (PaO₂/FiO₂), mechanical ventilation ratio, mechanical ventilation time, proportion of norepinephrine (NE) used, maximum NE, lactic acid (Lac), activated partial thromboplastin time (APTT), albumin (ALB), serum creatinine (SCr), blood urea nitrogen (BUN), blood uric acid (BUA), pH value, base excess (BE), and K⁺ between the death group and the survival group. ROC curve analysis showed that the area under the curve (AUC) of RF, XGBoost, LR, ANN, DT, SVM, KNN models, SOFA score, and APACHE II score for predicting in-hospital mortality of sepsis patients were 0.871, 0.846, 0.751, 0.747, 0.677, 0.657, 0.555, 0.749 and 0.760, respectively. Among all the models, the RF model had the highest precision (0.750), accuracy (0.785), recall (0.773), and F1 score (0.761), and best discrimination. The calibration curve showed that the RF model performed best among the seven machine learning models. DCA curve showed that the RF model exhibited greater net benefit as well as threshold probability compared to other models, indicating that the RF model was the best model with good clinical utility. CONCLUSIONS The machine learning model can be used as a reliable tool for predicting in-hospital mortality in sepsis patients. RF models has the best predictive performance, which is helpful for clinicians to identify high-risk patients and implement early intervention to reduce mortality.
Humans ; Hospital Mortality ; Retrospective Studies ; ROC Curve ; Prognosis ; Sepsis/diagnosis* ; Intensive Care Units

Objective:To investigate the genomic manifestation and pathogenesis of osteosarcoma with different relapse pattens, which were respectively initially presented with bone metastasis or pulmonary metastasis.Methods:From May 1, 2021 to October 1, 2021, 38 fresh tumor specimens and some paraffin-embedded specimens of high-grade osteosarcoma were collected in Peking University People's Hospital, including 29 males and 9 females, aged 19.6±2.2 years (range, 6-61 years). Among the 38 cases, 12 cases had initial bone metastasis (group A) and 26 cases had initial lung metastasis (group B), of which 15 cases (40%, 15/38) had paired specimens of primary and metastatic lesions. Based on Illumina NovaSeq 6000, we analyzed whole-exome sequencing (WES) as well as transcriptome for osteosarcoma with paired samples in different relapse patterns. During all their treatment courses, we also collected their paired samples to reveal these tumors' evolution. We sought to redefine disease subclassifications for osteosarcoma based on genetic alterations and correlate these genetic profiles with clinical treatment courses to elucidate potential evolving cladograms.Results:We found that osteosarcoma in group A mainly carried single-nucleotide variations (83%, 10/12), displaying higher tumor mutation burden [4.9 (2.8, 12.0) & 2.4 (1.4, 4.5), P=0.010] and neoantigen load [743.0 (316.5, 1,034.5) & 128.5 (49.0, 200.5), P=0.003], while those in group B mainly exhibit structural variants (58%, 15/26). The mutation spectrum showed that there was a significant difference in age-related gene imprinting 1 between the bone metastasis group and the lung metastasis group ( P=0.005). Samples were randomly selected from group A (3 patients) to investigate immunologic landscape by multiplex immunohistochemistry, from which we noticed tertiary lymphatic structure from one patient from group A. High conservation of reported genetic sequencing over time was found in their evolving cladograms. Conclusion:Osteosarcoma with mainly single-nucleotide variations other than structural variants might exhibit biological behavior predisposing toward bone metastases with older in age as well as better immunogenicity in tumor microenvironment.

Objective:To investigate psychological resilience of inpatients with extracranial arteriovenous malformation (AVM) and analyze the related factors, in order to provide scientific basis for improving the psychological resilience of patients.Methods:A cross-sectional study was conducted to include patients with extracranial AVM who were hospitalized in the Ninth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine from October 2020 to December 2021. The general information questionnaire, Cornor-Davidon resilience scale, Herth hope index, medical coping modes questionnaire and family APGAR scale were used to investigate them. SPSS 21.0 software was used. The t-test, one-way ANOVA, Pearson correlation analysis and multiple linear regression analysis were used for statistical analysis. Results:In total, 177 patients with extracranial AVM were included in our study. The total mean score of the resilience scale was 65.94±13.90, and the mean scores of the three dimensions of resilience, optimism and strength were 33.02±7.67, 10.38±2.75 and 22.54±4.67. The mean scores of Herth hope index was 37.50±3.56, positive coping style was 24.89±6.65, and family APGAR scale was 8.19±2.41. In univariate analysis, gender, ethnicity and family relationship had significant differences in psychological resilience (all P<0.05). Among these patients, female’s mental resilience score was significantly lower than that of male’s. Correlation analysis showed that the scores of the Herth hope index, positive coping style, and family APGAR scale were positively correlated with the total scores of resilience and the scores of each dimension (all P<0.01). Multiple linear regression analysis showed that gender, the scores of Herth hope index, positive coping mode, family APGAR scale were main influencing factors of resilience ( P<0.05). Conclusion:Female patients with extracranial AVM need more attention to their psychological problems and psychological reactions. Herth hope, positive coping mode, family-centered care are the protective factors of resilience of patients with extracranial AVM.

Objective:To investigate psychological resilience of inpatients with extracranial arteriovenous malformation (AVM) and analyze the related factors, in order to provide scientific basis for improving the psychological resilience of patients.Methods:A cross-sectional study was conducted to include patients with extracranial AVM who were hospitalized in the Ninth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine from October 2020 to December 2021. The general information questionnaire, Cornor-Davidon resilience scale, Herth hope index, medical coping modes questionnaire and family APGAR scale were used to investigate them. SPSS 21.0 software was used. The t-test, one-way ANOVA, Pearson correlation analysis and multiple linear regression analysis were used for statistical analysis. Results:In total, 177 patients with extracranial AVM were included in our study. The total mean score of the resilience scale was 65.94±13.90, and the mean scores of the three dimensions of resilience, optimism and strength were 33.02±7.67, 10.38±2.75 and 22.54±4.67. The mean scores of Herth hope index was 37.50±3.56, positive coping style was 24.89±6.65, and family APGAR scale was 8.19±2.41. In univariate analysis, gender, ethnicity and family relationship had significant differences in psychological resilience (all P<0.05). Among these patients, female’s mental resilience score was significantly lower than that of male’s. Correlation analysis showed that the scores of the Herth hope index, positive coping style, and family APGAR scale were positively correlated with the total scores of resilience and the scores of each dimension (all P<0.01). Multiple linear regression analysis showed that gender, the scores of Herth hope index, positive coping mode, family APGAR scale were main influencing factors of resilience ( P<0.05). Conclusion:Female patients with extracranial AVM need more attention to their psychological problems and psychological reactions. Herth hope, positive coping mode, family-centered care are the protective factors of resilience of patients with extracranial AVM.

Objective: To investigate the bacterial species, characteristics and differences of oral bacteria flora of saliva in the longevous elderly between in Bama county and in Debao county in Guangxi, in order to explore the relationship between longevity and oral salivary bacteria flora in the elderly. Methods: The saliva was taken from the longevous elderly in Bama county(BM group)and people aged over 60 years in Debao county(BS group)separately, and the total DNA was extracted.The 16S rDNA-V4 region was amplified by PCR and analyzed by sequencing.The main species and diversity of bacterial colonies were recorded for difference analysis. Results: A total of 14 saliva samples were collected from 7 cases in BM group and 7 cases in BS group.A total of 369 OTUs were generated by cluster analysis of 14 samples.At the genus level, the dominant salivary bacteria flora were Ctinomyces, Capnocytophaga, Chryseobacterium, Fusobacterium, Haemophilus, Lactobacillus, Leptotrichia, Neisseria, Porphyromonas, Prevotella, Rothia, Streptococcus, Veillonella in both BM group and BS group.The OTU PCA analysis showed that some evidence for indeterminate differences was found, but statistically significant differences did not exist in the dominant components of oral flora between the two groups(P>0.05). Also, the same tendency toward the diversity(P>0.05)was presented.Similarly, the species annotation analysis and the heat map showed that there were no significant differences(P>0.05)in oral salivary flora composition between the two groups.Lactobacillu was always the prevailing flora in the Phylume, Class, Order, Family and Genus, but the abundance ratio was different between the two groups as following: Lactobacillus abundance in salivary bacteria flora was higher in BM Group than in the BS group, while Mycoplasma abundance was lower in BM Group than in the BS group(P<0.05). Conclusions The dominant salivary bacteria flora is Lactobacillus in both BM and BS group, while, the abundance of Lactobacillus is higher in the BM group than in the BS group, which indicates that the longevity of population in Bama county may be related to Lactobacillus.

Objective:To investigate the clinical value of glypican-3 (GPC3) detection in the diagnosis and therapy-monitoring of primary hepatocellular carcinoma (HCC).Methods:From March 2018 to May 2019, the patients with HCC were enrolled as the experimental group( n=166)from Fudan University Shanghai Cancer Centre, while the specimens from health control group( n=94) and benign control group ( n=50) were analyzed. The serum of GPC3 and alpha fetoprotein (AFP)levels were respectively detected by ELISA and chemiluminescence. GPC3 detections combined with AFP etc. in accuracy of HCC diagnosis were explored by using Logistic regression analysis. Results:The serum GPC3 level in patients with HCC ［0.210 (0.048, 0.801)mg/L］ ［Median (quartile Q1, Q3)］ was significantly higher than those in healthy controls ［0.029(0.019, 0.052)mg/L］ and benign controls ［0.033(0.021, 0.043) mg/L］ ( Z=-7.69, P<0.001).The serum levels of aspartate aminotransferase (AST), alanine aminotransferase (ALT) and AFP were significantly different among the three groups ( Z=-7.02, -6.85, -8.36 respectively, P<0.001). Among the serological indicators, it was related to ALT and AST ( Z=-3.77, -4.09 respectively, P<0.001).The Cut-off level of GPC3 was determined as 0.077 mg/L by ROC curve. The sensitivity of the combined detection of serum GPC3 with AFP for HCC was up to 87.82%, the specificity was 77.86%, the negative predictive value was 84.29%, and the positive predictive value was 82.53%.The HCC-GPC3 model was constructed by using Logistic regression analysis. The area under the ROC curve was 0.882, the total sensitivity was 91.10%, and the total specificity was 72.73%. Further analysis showed that the serum GPC3 of patients with HCC was significantly lower ［0.454(0.019, 0.286) mg/L］ than that before surgery［0.608(0.039, 0.554）mg/L］( Z=-7.32, P<0.001). Conclusion:The detection of serum GPC3 can be applied to aid diagnosis and therapy-monitoring of HCC.The combination of GPC3 and AFP can improve the diagnostic efficiency of HCC.