OBJECTIVES: To establish a prognostic model for primary liver cancer (PLC) using bioinformatics methods. METHODS: Based on the data from 404 patients in the Cancer Genome Atlas (TCGA) database, we constructed a prognostic model integrating the differentially expressed genes, anoikis, and immune-related genes (DAIs) using univariate Cox regression and the LASSO-Cox approach. The predictive ability of the model was evaluated using Kaplan-Meier method and receiver-operating characteristic curves, and a nomogram was developed to facilitate its clinical applications. Gene set enrichment analysis (GSEA) was performed to explore the associated pathways and relationship between the DAIs and the tumor immune microenvironment, and the half-maximal inhibitory concentration (IC₅₀) of liver cancer drugs was calculated using the "pRRophetic" R package. We also detected the expression of SEMA7A in paired tumor and adjacent tissues from liver cancer patients. RESULTS: We constructed and validated a prognostic model based on 7 DAIs (NR4A3, SEMA7A, IL11, AR, BIRC5, EGF, and SPP1), and obtained consistent results in both the TCGA training cohort and GEO validation cohort (GSE14520), where the patients in the low-risk group were characterized by more favorable clinical outcomes and immune status. By integrating this prognostic signature with clinical information, a composite nomogram was generated. Somatic mutation analysis showed that TTN, TP53, and CTNNB1 mutations accounted for the largest proportion of total mutations, and the patients in the low-risk-low-TMB group had higher survival rate. Drug sensitivity analysis revealed differences in sensitivity to chemotherapeutic agents between high- and low-risk groups and between TP53 mutations and non-mutations. In clinical tissue specimens, SEMA7A expression was significantly higher in liver cancer tissues than in the adjacent tissues. CONCLUSIONS We established a new prognostic model based on DAIs for predicting clinical outcomes and therapeutic response of patients with primary liver cancer.
Humans ; Liver Neoplasms/diagnosis* ; Prognosis ; Anoikis ; Nomograms ; Computational Biology ; Tumor Microenvironment ; Semaphorins/metabolism*

ObjectiveTo investigate the clinical features of patients with acute-on-chronic liver failure （ACLF）， and to construct a risk scoring table that can accurately predict the prognosis of patients in the early stage. MethodsA retrospective analysis was performed for the clinical data of 502 patients with ACLF who were admitted to Tangdu Hospital， Air Force Medical University， from January 1， 2010 to December 31， 2020 （training set）， and the influencing factors for 28-day mortality rate were identified. The 69 ACLF patients who were admitted to Tangdu Hospital， Air Force Medical University， from January 1 to December 31， 2021 were enrolled as the validation set. The independent-samples t test or the Mann-Whitney U test was used for comparison of continuous data between two groups， and the chi-square test or the Fisher’s exact test was used for comparison of categorical data between two groups. A univariate Cox regression analysis was used to obtain the early warning indicators associated with the 28-day prognosis of ACLF patients， and variance inflation factors were used to assess multicollinearity among predictors； a multivariate Cox regression analysis was used to construct a risk model for ACLF prognosis （mortality）. A risk scoring table for ACLF prognosis （mortality） was developed based on regression coefficients （β） from the model equation and weight assignments in the nomogram. Internal validation and comparison were performed for the risk model for ACLF prognosis （mortality）， the scoring table for ACLF prognosis （mortality）， and other scoring models （Child-Turcotte-Pugh ［CTP］ score， Model for End-Stage Liver Disease ［MELD］ score， MELD combined with serum sodium concentration ［MELD-Na］ score， and integrated MELD ［iMELD］ score） in the training set， while external validation and comprehensive evaluation of the scoring table and the other scoring models were performed in the validation set. The Nagelkerke’s R² test and the Hosmer-Lemeshow test were used to assess the degree of fitting of the risk model for ACLF prognosis （mortality）， the scoring table for ACLF prognosis （mortality）， and other scoring models， and fitting curves were plotted. C-index was used to assess the discriminatory ability of the scoring table for ACLF prognosis （mortality） and the other scoring models， and the Z-test was used for comparison of C-index between different models. The decision curve analysis was used to compare the clinical benefits of the scoring table for ACLF prognosis （mortality） and the other scoring models. ResultsThe multivariate Cox regression analysis showed that age （hazard ratio ［HR］=1.027， 95% confidence interval ［CI］： 1.015 — 1.039， P<0.001）， hepatic encephalopathy grade （grade 1： HR=2.928， 95%CI： 1.463 — 5.858， P=0.002； grade 2： HR=3.811， 95%CI： 2.078 — 6.988， P<0.001； grade 3： HR=3.916， 95%CI： 1.917 — 8.001， P<0.001； grade 4： HR=6.966， 95%CI： 4.559 — 10.644， P<0.001）， an increase in total bilirubin （TBil） by ≥17.1 μmol/L per day （HR=1.771， 95%CI： 1.248 — 2.513， P=0.001）， creatinine （HR=1.005， 95%CI： 1.004 — 1.006， P<0.001）， neutrophil count （HR=1.092， 95%CI： 1.060 — 1.126， P<0.001）， and international normalized ratio （HR=1.298， 95%CI： 1.187 — 1.418， P<0.001） were independent risk factors associated with the 28-day mortality rate of ACLF patients， and a risk scoring table was constructed for ACLF prognosis （mortality）. The Nagelkerke’s R² test showed that the risk scoring table for ACLF prognosis （mortality） had an R² value of 0.599 in the training set and 0.722 in the validation set， which were higher than the R² values of CTP， MELD， MELD-Na， and iMELD scores. The Hosmer-Lemeshow test showed that the risk scoring table for ACLF prognosis （mortality） had a P value of 0.280 in the training set and 0.788 in the validation set. The C-index analysis showed that the scoring table had a higher C-index than the other scoring models in the validation set （all P<0.001）， as well as a higher C-index than CTP score in the training set （P<0.001）. The decision curve analysis showed that the risk scoring table for ACLF prognosis （mortality） had higher clinical net benefits than the other scoring models. ConclusionCompared with other scoring models currently used in clinical practice， the novel risk scoring table for ACLF prognosis （mortality） constructed based on the six predictive factors of age， hepatic encephalopathy grade， an increase in TBil by ≥17.1 μmol/L per day， creatinine， neutrophil count， and international normalized ratio has a relatively high value in predicting the 28-day prognosis of ACLF patients.

The objective of this study is to assess the current status of vaccination against respiratory disease among the elderly aged ≥60 and analyze the factors influencing vaccination rates at both service provider and recipient levels in Zhejiang Province. Using a stratified random sampling method, a questionnaire survey was conducted from September 2022 to January 2023 among elderly people aged ≥60 in 30 townships/streets in Zhejiang Province, as well as immunization planning staff at the provincial, municipal, county/district, and township/street levels. Logistic regression models were used to analyze the factors related to vaccination among elderly people in Zhejiang Province. Based on the Zhejiang Provincial Comprehensive Management Information System for Vaccine and Vaccination, the systematic coverage rates of influenza vaccine and pneumonia vaccine for the elderly were 21.76% and 4.57%, respectively. Multivariate logistic regression analysis indicated that advanced age ( OR=1.74, 95% CI: 1.51-1.99), knowing that influenza is more severe than the common cold ( OR=1.67, 95% CI: 1.37-2.04) and having heard of the influenza vaccine ( OR=9.78, 95% CI: 7.03-13.59) were motivating factors for elderly to receive influenza vaccines. Advanced age ( OR=1.71, 95% CI: 1.43-2.06), knowing the serious consequences of pneumonia in the elderly ( OR=1.93, 95% CI: 1.47-2.55) and knowing that pneumonia vaccines can prevent pneumonia ( OR=6.36, 95% CI: 4.84-8.36) were motivating factors for elderly to receive pneumonia vaccines. Zhejiang Immunization Program staff believed that the main reasons why the elderly aged ≥60 would not be vaccinated against influenza or pneumonia were that they felt they would not get sick (55.52% and 56.35% respectively), it would not be serious if get sick (47.73% and 37.46% respectively), lacking trust in vaccine efficacy and safety (38.31% and 43.69% respectively). Vaccination rates for influenza and pneumonia vaccines among the elderly aged ≥60 in Zhejiang Province are suboptimal. Advanced age, awareness of the severity of respiratory diseases and awareness of vaccines against such diseases are related factors for elderly individuals to receive influenza and pneumonia vaccines.

The objective of this study is to assess the current status of vaccination against respiratory disease among the elderly aged ≥60 and analyze the factors influencing vaccination rates at both service provider and recipient levels in Zhejiang Province. Using a stratified random sampling method, a questionnaire survey was conducted from September 2022 to January 2023 among elderly people aged ≥60 in 30 townships/streets in Zhejiang Province, as well as immunization planning staff at the provincial, municipal, county/district, and township/street levels. Logistic regression models were used to analyze the factors related to vaccination among elderly people in Zhejiang Province. Based on the Zhejiang Provincial Comprehensive Management Information System for Vaccine and Vaccination, the systematic coverage rates of influenza vaccine and pneumonia vaccine for the elderly were 21.76% and 4.57%, respectively. Multivariate logistic regression analysis indicated that advanced age ( OR=1.74, 95% CI: 1.51-1.99), knowing that influenza is more severe than the common cold ( OR=1.67, 95% CI: 1.37-2.04) and having heard of the influenza vaccine ( OR=9.78, 95% CI: 7.03-13.59) were motivating factors for elderly to receive influenza vaccines. Advanced age ( OR=1.71, 95% CI: 1.43-2.06), knowing the serious consequences of pneumonia in the elderly ( OR=1.93, 95% CI: 1.47-2.55) and knowing that pneumonia vaccines can prevent pneumonia ( OR=6.36, 95% CI: 4.84-8.36) were motivating factors for elderly to receive pneumonia vaccines. Zhejiang Immunization Program staff believed that the main reasons why the elderly aged ≥60 would not be vaccinated against influenza or pneumonia were that they felt they would not get sick (55.52% and 56.35% respectively), it would not be serious if get sick (47.73% and 37.46% respectively), lacking trust in vaccine efficacy and safety (38.31% and 43.69% respectively). Vaccination rates for influenza and pneumonia vaccines among the elderly aged ≥60 in Zhejiang Province are suboptimal. Advanced age, awareness of the severity of respiratory diseases and awareness of vaccines against such diseases are related factors for elderly individuals to receive influenza and pneumonia vaccines.

ObjectiveTo investigate the clinical features of patients with acute-on-chronic liver failure （ACLF） and bacterial infection and early warning indicators associated with multidrug-resistant infections. MethodsA retrospective analysis was performed for 130 patients with ACLF and bacterial infection who attended The Second Affiliated Hospital of Air Force Medical University from January 1， 2010 to December 31， 2021， and according to the drug susceptibility results， the patients were divided into multidrug-resistant （MDR） bacterial infection group with 80 patients and non-MDR bacterial infection group with 50 patients. General information and laboratory examination results were compared between the two groups to screen for the early warning indicators associated with MDR bacterial infection. The Student’s t-test was used for comparison of normally distributed continuous data with homogeneity of variance between two groups， and the Mann-Whitney U test was used for comparison of non-normally distributed continuous data or continuous data with heterogeneity of variance between two groups； the chi-square test or the Fisher’s exact test was used for comparison of categorical data between two groups. The binary logistic regression analysis and the receiver operating characteristic （ROC） curve were used to assess the predictive value of early warning indicators. ResultsAmong the 130 patients with ACLF and bacterial infection， sputum （27.7%） was the most common specimen for detection， followed by blood （24.6%）， urine （18.5%）， and ascites （17.7%）. Bacterial infections were dominated by Gram-negative bacteria （58.5%）. Of all bacteria， Escherichia coli （18.5%）， Klebsiella pneumoniae （14.6%）， and Enterococcus faecium （13.8%） were the most common pathogens. Gram-positive bacteria had a high resistance rate to the antibacterial drugs such as erythromycin （72.2%）， penicillin （57.4%）， ampicillin （55.6%）， and ciprofloxacin （53.7%）， while Gram-negative bacteria had a high resistance rate to the antibacterial drugs such as ampicillin （73.3%）， cefazolin （50.0%）， and cefepime （47.4%）. The patients with ACLF and bacterial infection had a relatively high rate of MDR bacterial infection （61.5%）. Comparison of clinical data between the two groups showed that compared with the patients with non-MDR bacterial infection， the patients with MDR bacterial infection had significantly higher levels of alanine aminotransferase （Z=2.089， P=0.037）， aspartate aminotransferase （Z=2.063， P=0.039）， white blood cell count （Z=2.207， P=0.027）， and monocyte count （Z=4.413， P<0.001）. The binary logistic regression analysis showed that monocyte count was an independent risk factor for MDR bacterial infection （odds ratio=7.120， 95% confidence interval ［CI］： 2.478‍ ‍—‍ ‍20.456，P<0.001） and had an area under the ROC curve of 0.686 （95%CI： 0.597‍ ‍—‍ ‍0.776） in predicting ACLF with MDR bacterial infection（P<0.001）， with the optimal cut-off value of 0.50×10⁹/L， a sensitivity of 0.725， and a specificity of 0.400. ConclusionACLF combined with bacterial infections is mainly caused by Gram-negative bacteria， with the common pathogens of Escherichia coli and Klebsiella pneumoniae and a relatively high MDR rate in clinical practice. An increase in monocyte count can be used as an early warning indicator to distinguish MDR bacterial infection from non-MDR bacterial infection.

Objective: To determine the association between the intake of five major types of prepackaged foods and the growth and development of school aged children, so as to provide a theoretical basis for guiding school aged children and their parents to make healthy prepackaged food choices. Methods: Based on data from the South West China Childhood Nutrition and Growth Cohort (SCCNG), 381 children (6-11 years of age) were selected by stratified cluster sampling. Dietary intake and pubertal development were collected using questionnaires, and anthropometric measurements were obtained. Children were followed up until November 2022. Binary Logistic regression models were used to analyze the prospective association between prepackaged food intake and the growth and development of school aged children. Results: The total intake of the five major types of prepackaged foods was 316.1 (197.1,501.4) g/d. After 2 years of follow up evaluations, 16.5% of school aged children were shown to be overweight and obese. Early spermarche occurred in 12.6% of boys and early menarche occurred in 15.4% of girls. The following findings were suggested after adjusting for the mothers education level, average gross monthly family income, whether or not the family had one child only, geographic area of residence, body mass index Z score, average duration of daily exercise, and total dietary energy intake: convenience food intake might increase the risk of early spermarche ( OR =9.37); fruit and vegetable intake might decrease the risk of early spermarche and menarche ( OR =0.33,0.17); and fish, poultry, meat, and egg intake might increase the risk of early menarche ( OR =7.59)( P <0.05). Intake of the five types of prepackaged foods was not associated with being overweight or obese after adjusting for confounders ( OR =1.40, 0.57, 0.73, 1.33,1.57, P >0.05). Conclusions The relationship between intake of the five major types of prepackaged foods and pubertal development is inconsistent and no significant correlation was detected between the intake of prepackaged foods and overweight or obese children. Nutrition education should be strengthened to help children and their parents choose healthy prepackaged foods.

Objective: To explore the differences in the gut microbiota of primary school students with different levels of sugar sweetened beverage intake, so as to provide scientific evidence for better identification of health risks in children and the development of targeted health policies. Methods: In June 2022, a total of 192 healthy primary school students from Chengdu were selected using a stratified cluster random sampling method. The sugar sweetened beverage intake was assessed through a dietary frequency questionnaire. Based on the median daily sugar sweetened beverage intake, primary school students were categorized into a low intake group ( n =96) and a high intake group ( n =96). The gut microbiota in fresh fecal samples from the two groups of primary school students was analyzed using 16S rRNA high throughput sequencing, and the diversity and community structure differences in the gut microbiota were compared. Results: Children in the low intake group had a sugar sweetened beverage intake of (21.3±1.6) mL/d, while the high intake group had an intake of (269.6±37.3) mL/d. Diversity analysis results showed that there were no statistically significant differences between the low intake and the high intake group in terms of α diversity metrics: Observed_otus index [298.50 (259.75, 342.25), 305.50 (244.25, 367.75)], Goods_coverage index [1.00 (1.00, 1.00), 1.00 (1.00, 1.00)], Chao index [304.18 (260.75, 348.78), 305.88 (245.68, 370.88)], Shannon index [5.88 (5.29, 6.45), 5.71 (4.89, 6.28)] and Simpson index [0.95 (0.91, 0.97), 0.94 (0.88, 0.97)] ( Z =-0.64, -0.76, -0.54, -1.76, -1.67, P >0.05). Furthermore, no statistically significant difference was observed in β diversity between the two groups ( R 2=0.006, P >0.05). At the genus level, the abundance of Blautia [0.033 (0.018, 0.055)] and Fusicatenibacter [0.009 (0.005, 0.015)] were higher in the low intake group compared to the high intake group [0.024 (0.013, 0.041),0.006 (0.003, 0.011)]and differences were statistically significant ( Z =-2.52, -2.81, P <0.05). LEfSe analysis highlighted intergroup differences primarily in Blautia, Fusicatenibacter and Sarcina( LDA= 3.56,3.12,3.53, P <0.05). Conclusions There is no significant difference in the diversity and overall structure of the gut microbiota in primary school students with different levels of sugar sweetened beverage intake. However, there are species variations at the genus level. The information can serve as a scientific basis for identifying health risks in primary school students and formulating targeted health strategies.

The automatic detection of tuberculosis lesions based on medical imaging has become a research hotspot in medical image processing.A comprehensive review of relevant researches and applications pertaining to deep learning in tuberculosis lesion detection is provided,which elucidates the experimental benchmarks in tuberculosis analysis,covering public datasets of pulmonary medical images and recent research advancements in tuberculosis detection and classification competitions,introduces emerging trends in deep learning methods and applications in tuberculosis detection,and analyzes the challenges existing in tuberculosis diagnosis using deep learning.The review summarizes and provides insights into the research advances and challenges of these technologies from the aspects of technical characteristics,performance advantages,and application prospects.

Objective:To analyze the clinical features and immunotherapy responsiveness of patients with myelin oligodendrocyte glycoprotein immunoglobulin G-antibody associated disease (MOGAD) with epilepsy, and display the risk factors of epilepsy in MOGAD.Methods:Eighty-nine patients with MOGAD diagnosed at the First Affiliated Hospital of Zhengzhou University between October 2019 and May 2023 were enrolled and classified into 2 groups upon MOGAD with ( n=29) or without epilepsy ( n=60). The Expanded Disability Status Scale (EDSS) and Clinical Assessment Scale for Autoimmune Encephalitis (CASE) were used for evaluation of severity, and EDSS or CASE scores on the 30th day after first-line immunotherapy initiation lower than that on admission were defined as well treatment responsiveness. The differences of general data, clinical manifestations, cerebrospinal fluid (CSF) and peripheral blood biochemical examination results, and immunotherapy reactivity between the 2 groups were thoroughly explicated. In addition, the risk factors of epilepsy in MOGAD were analyzed by univariate and multivariate Logistic regression analysis. Results:Compared with patients with MOGAD without epilepsy, patients with MOGAD with epilepsy were characterized by lower age of onset [24.5(10.3, 34.0) years vs 11.0(6.5, 20.0) years, Z=-2.348, P=0.019], higher percentage of male patients [43.3%(26/60) vs 75.9%(22/29), χ 2=8.326, P=0.004], higher virus infection rate [28.3%(17/60) vs 51.7%(15/29), χ 2=4.645, P=0.031], higher incidence of prodromal symptoms [11.7%(7/60) vs 34.5%(10/29), χ 2=6.586, P=0.010], higher blood-brain barrier breakdown rate [35.0%(21/60) vs 58.6%(17/29), χ 2=4.458, P=0.035], higher percentage of CSF albumin level>450 mg/L [48.3%(29/60) vs 75.9%(22/29), χ 2=6.056, P=0.014] and higher creatine kinase level [45.50(28.50, 69.75) U/L vs 57.50(41.75, 97.25) U/L, Z=-2.349, P=0.019]; more epilepsy [0(0) vs 29/29 (100.0%), χ 2=89.000, P<0.001] and disturbance of consciousness [0(0) vs 6/29(20.7%), χ 2=10.224, P=0.001] as clinical manifestations, and more cerebral cortex lesions [30/60(50.0%) vs 25/29(86.2%), χ 2=10.856, P=0.001] on magnetic resonance imaging. Nevertheless, the patients with MOGAD without epilepsy were featured with more visual impairment [23/60(38.3%) vs 3/29(10.3%), χ 2=7.406, P=0.007], limb weakness [18/60(30.0%) vs 1/29(3.4%), χ 2=8.209, P=0.004], sensory disturbance [15/60(25.0%) vs 0(0), Fisher exact probability test, P=0.002] and more cervical cord lesions [22/60(36.7%) vs 4/29(13.8%), χ 2=4.946, P=0.026] on magnetic resonance imaging. Immunotherapy responsiveness was relatively poor in the MOGAD with epilepsy group [EDSS score lower than that on admission: 15/29(51.7%) vs 46/60(76.7%), χ 2=5.641, P=0.018; CASE score lower than that on admission: 16/29(55.2%) vs 47/60(78.3%), χ 2=5.072, P=0.024] compared with the MOGAD without epilepsy group. Male was the independent risk factor of epilepsy in MOGAD ( OR=7.078, 95% CI 1.709-29.326, P=0.007). Conclusions:Compared with patients with MOGAD without epilepsy, patients with MOGAD with epilepsy reported more male patients, lower age of onset and higher incidence of prodromal symptoms, blood-brain barrier dysfunction rate, virus infection rate, CSF albumin level and creatine kinase level; clinical phenotypes were mainly meningoencephalitis and more cerebral cortex lesions were shown on magnetic resonance imaging. MOGAD with epilepsy was closely related to poor immunotherapy responsiveness, and gender was found to be the independent risk factor for epilepsy in MOGAD.

Rabies is a zoonotic disease that poses a global public health threat.Rabies virus(RABV)is neurotropic and can cause severe neurological disorders and behavioral abnormalities in host,with a fatality rate nearly 100％.In order to identify the key genes for RABV affecting neuronal cell function,we established and analyzed the mRNA expression profile of Neuro-2a(N2a)cell in-fected with challenge virus standard(CVS)-11 by RNA sequencing(RNA-seq).Biological func-tions of differentially expressed genes(DEGs)were determined by GO and KEGG enrichment a-nalysis.The results showed that there were 415 differentially expressed genes in N2a infected with CVS-11 strain,of which 89 were up-regulated and 326 were down-regulated.These genes were re-lated to a variety of biological processes,such as axon guidance pathway,cholesterol metabolism pathway,nitrogen metabolism pathway,and glycosphingolipid biosynthesis pathway,many of them have been shown to be closely associated with RABV infection.A total of 12 DEGs related to axon conduction,antigen processing and presentation pathways were selected and detected by real-time PCR,and their expression trends were consistent with the RNA-seq results.The genomic tran-scriptomic data on N2a cell under RABV infection will provide new clues for probing the mecha-nisms of RABV infection and transmission in the nervous system in the future.