Objective:To explore the characteristics of gray matter volume (GMV) and structural covariant network (SCN) in patients with cerebral small vessel disease (CSVD) related cognitive impairment.Methods:This was a cross-sectional study. Ninety-eight patients with CSVD who attended Wuxi People′s Hospital of Nanjing Medical University between October 2021 and December 2022 were prospectively included. The patients were evaluated using the cognitive status assessment scale and were categorized into 57 cases in the CSVD with cognitive impairment group and 41 cases in the CSVD without cognitive impairment group according to the presence or absence of cognitive impairment. 3D-T 1WI structural image data were collected, and GMV differences between the two groups were compared by SPM 12 toolbox and CAT12 toolkit. At the same time, Pearson correlation analysis was also performed to analyze the GMV of differences between the 2 groups and cognitive status assessment scale scores. The BCT software package based on MATLAB platform was used to construct the GMV-related structural covariant network (SCN), and the graph theory method was utilized for SCN analysis to calculate the area under the curve (AUC) of the global and local parameters within the set sparsity range, and the permutation test was used to compare the differences in the AUC of the 2 groups. Results:In the CSVD with cognitive impairment group, GMV in bilateral hippocampus, parahippocampal gyrus, fusiform gyrus, and left amygdala was significantly lower than that in the CSVD without cognitive impairment group (family wise error corrected P<0.05), and the GMV in these regions had correlation with cognitive status assessment scale ( P<0.05). At the global network level of the SCN, the area under the curve (AUC) of the characteristic path length was significantly higher in the CSVD with cognitive impairment group than in the CSVD without cognitive impairment group ( P=0.023), while the AUC of global efficiency was significantly lower in CSVD with cognitive impairment group than in the CSVD without cognitive impairment group ( P=0.005). At the local level, the nodal degree and nodal efficiency of the left putamen were significantly decreased in the CSVD with cognitive impairment group compared to the CSVD without cognitive impairment group (false discovery rate corrected P<0.05). Conclusions:GMV reduce in patients of CSVD with cognitive impairment in the bilateral hippocampus, parahippocampal gyrus, fusiform gyrus, and left amygdala. In the structural covariance network, characteristic path length increase while global efficiency reduce, and node degree and nodal efficiency of the left putamen reduce.

ObjectiveTo investigate the influence of triglyceride （TG）/high-density lipoprotein cholesterol （HDL-C） ratio on the onset of primary liver cancer. MethodsA prospective cohort study was conducted. Physical examination data were collected from 99 750 cases of on-the-job and retired employees of Kailuan Group who participated health examination from July 2006 to December 2007， and they were followed up till December 31， 2021 to observe the onset of primary liver cancer. A one-way analysis of variance was used for comparison of normally distributed continuous data between multiple groups， and the Kruskal-Wallis H test was used for comparison of continuous data with skewed distribution between multiple groups； the chi-square test was used for comparison of categorical data between groups. According to the tertiles of TG/HDL-C ratio， the subjects were divided into Q1， Q2， and Q3 groups， and the incidence density of primary liver cancer was calculated for each group. The Kaplan-Meier method was used to calculate the cumulative incidence rate of primary liver cancer in each group， and the log-rank test was used to compare the difference in cumulative incidence rate between groups. The Cox proportional hazards model was used to analyze the influence of TG/HDL-C ratio on the onset of primary liver cancer. ResultsThere were significant differences between the three groups in age， proportion of male subjects， waist circumference， body mass index， fasting blood glucose， systolic pressure， diastolic pressure， triglyceride， total cholesterol， HDL-C， low-density lipoprotein cholesterol， alanine aminotransferase， high-sensitivity C-reactive protein， chronic liver diseases， hypertension， diabetes， the family history of malignant tumor， drinking， smoking， physical exercise， and educational level （P<0.05）. During the mean follow-up time of 14.06±2.71 years， there were 484 cases of new-onset liver cancer， among whom there were 446 male subjects and 38 female subjects. The incidence density of primary liver cancer was 0.39/1 000 person-years in the Q1 group， 0.35/1 000 person-years in the Q2 group， and 0.30/1 000 person-years in the Q3 group， and the cumulative incidence rates of primary liver cancer in the three groups were 6.03‰， 5.28‰， and 4.49‰， respectively， with a significant difference between the three groups based on the long-rank test （χ²=6.06， P=0.048）. After adjustment for the confounding factors considered， the Cox proportional hazards model showed that compared with the Q3 group， the Q1 group had a hazard ratio of 2.04 （95% confidence interval ［CI］： 1.61‍ ‍—‍ ‍2.58， P_{for trend}<0.05）， and the Q2 group had a hazard ratio of 1.53 （95%CI： 1.21‍ ‍—‍ ‍1.92， P_{for trend}<0.05）. ConclusionThe reduction in TG/HDL-C ratio is associated with an increase in the rask of primary liver cancer， especially in people with chronic liver diseases.

Objective To investigate and validate the expression profiles of Ppp3cb and Ppm1g through differential proteomic analysis of hippocampal tissue in NHE1 gene knockout mice with proteomic analysis.Method ① Six 2-week-old NHE1 knockout mice were selected as the model group,and 6 wild-type mice of the same age served as the control group,and their genotypes were detected by agar-gel electrophoresis.Open field test and forced swimming test were used to evaluate the behaviors of mice in the model group and control group,and epileptic seizure was graded according to Racine scoring.② Tandem mass spectrometry was employed to screen the differential proteins in the hippocampus tissues from the model group and the control group.Then the obtained differential proteins were annotated and enriched in the Gene Ontology(GO)database.Search tool for the retrieval of interesting genes(STRING)database was used to analyze protein-protein interaction(PPI)among different proteins.③ The transcriptional and translational levels of Ppp3cb and Ppm1g were detected by qPCR and Western blotting,respectively,and their expression levels in the tissues were observed with immunohistochemistry.Results ① NHE1 was not expressed in the model group.The mice of the model group had shorter total movement distance(P=0.007 3)and less crossing cells(P＜0.000 1)in open field test,and longer period of immobility in forced swimming test(P＜0.000 1)when compared with those from the control group.② When fold change ≥1.2 times and P＜0.05 were set as the significant threshold for differential expression,845 differentially expressed protein sites were detected in the hippocampus,among which 9 proteins(including Ppm1g)were up-regulated and 7 ones(including Ppp3cb)were down-regulated.Gene Ontology(GO)functional analysis showed that after NHE1 knockout,the most significant differences were observed in the concentration of molecular function(MF)related to protein serine/threonine phosphatase activity,concentration of cellular component(CC)related to the plasma membrane,and concentration of biological process(BP)related to negative regulation of biological processes and immune system processes.STRING analysis indicated that the differential proteins Ppp3cb and Slc9a1 directly acted,Ppm1g indirectly acted through Ppp3cb and Slc9a1,and Ppp3cb and Ppm1g interacted.③The transcriptional and translational levels of Ppp3cb were decreased,and its expression level was reduced in the tissues,while those of Ppm1g were increased,and its expression was elevated in the tissues(P＜0.05).Conclusion In the hippocampus of NHE1 gene knockout mice,the expression of differential protein Ppp3cb is down-regulated and that of Ppm1g is up-regulated,which provide a basis for further study on their involvement in the pathogenesis of epilepsy.

Objective To explore the changes of resting-state degree centrality(DC)in elderly patients with chronic insomnia disorder(CID).Methods Resting-state functional magnetic resonance imaging(rs-fMRI)data were collected from 26 untreated elderly patients with CID(CID group)and 45 healthy controls(HC)(HC group).Two-sample t-test was conducted to compare the intergroup differences in whole-brain DC values,and the correlation between DC values in different brain regions and clinical indicators were analyzed,and logistic regression analysis was performed to verify the diagnostic efficacy of changes in DC values for elderly CID.Results Compared with the HC group,the DC values of the right insula,left rolandic operculum,and opercular part of right inferior frontal gyrus in the elderly CID group decreased[P＜0.05,false discovery rate(FDR)corrected],while the DC values of the right middle frontal gyrus increased(P＜0.05,FDR corrected).And the DC values of the opercular part of right inferior frontal gyrus in the elderly CID group were positively correlated with sleep efficiency(r=0.504,P=0.009)and self-rating depression scale(SDS)(r=0.401,P=0.042),respectively.The sensitivity of DC value in the opercular part of right inferior frontal gyrus for diagnosing elderly CID was 0.822,the specificity was 0.615,and the accuracy was 0.701.Conclusion Elderly CID patients have abnormal DC values in the right insula,left rolandic operculum,opercular part of right inferior frontal gyrus and right middle frontal gyrus,which may provide imaging evidence for exploring the pathogenesis of CID and clinical diagnosis and treatment.

Purpose: Although obesity is associated with numerous diseases, the risks of disease may depend on metabolically healthy status. Nevertheless, it is unclear to whether metabolically healthy status affects risk of gastrointestinal (GI) cancer in general Chinese population. Materials and Methods: A total of 114,995 participants who met the criteria were included from the Kailuan Study. The study participants were divided into four groups according to body mass index (BMI)/waist circumference (WC) and metabolic status. Incident of GI cancer (esophageal cancer, gastric cancer, liver cancer, biliary cancer, pancreatic cancer, and colorectal cancer) during 2006-2020 were confirmed by review of medical records. The Cox proportional hazard regression models were used to assess the association metabolically healthy status with the risk of GI cancer by calculating the hazard ratios (HR) and 95% confidence interval (CI). Results: During a mean 13.76 years of follow-up, we documented 2,311 GI cancers. Multivariate Cox regression analysis showed that compared with the metabolically healthy normal-weight group, metabolically healthy obese (MHO) participants demonstrated an increased risk of developing GI cancer (HR, 1.54; 95% CI, 1.11 to 2.13) by BMI categories. However, such associations were not found for WC category. These associations were moderated by age, sex, and anatomical site of the tumor. Individuals with metabolic unhealthy normal-weight or metabolic unhealthy obesity phenotype also have an increased risk of GI cancer. Conclusion MHO phenotype was associated with increased risk of GI cancer. Moreover, individuals who complicated by metabolic unhealthy status have an increased risk of developing GI cancer. Hence, clinicians should consider the risk of incident GI cancer in people with abnormal metabolically healthy status and counsel them about metabolic fitness and weight control.

Purpose: This study aimed to identify the altered pathways and genes associated with freezing damage in human sperm during cryopreservation by multiomics analysis. Materials and Methods: Fifteen fresh human semen samples were collected for transcriptomic analysis, and another 5 fresh human semen samples were obtained for metabolomic analysis. For each semen sample, 1 mL was cryopreserved, and another 1 mL was left untreated for paired design. The results were then combined with previously published proteomic results to identify key genes/pathways. Results: Cryopreservation significantly reduced sperm motility and mitochondrial structure. Transcriptomic analysis revealed altered mitochondrial function, including changes in tRNA-methyltransferase activity and adenosine tri-phosphate/adenosine di-phosphate transmembrane transporter activity. Metabolomic analysis showed that the citrate cycle in mitochondria was significantly altered. Combining transcriptomic, proteomic, and metabolomic analyses revealed 346 genes that were altered in at least two omics analyses. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed that metabolic pathways were significantly altered and strongly associated with mitochondria. Five genes were altered in all three omics analyses: COL11A1, COL18A1, LPCAT3, NME1, and NNT. Conclusions Five genes were identified by multiomics analysis in human cryopreserved sperm. These genes might have specific functions in cryopreservation. Explorations of the functions of these genes will be helpful for sperm cryopreservation and sperm motility improvement or even for reproduction in the future.

Objective:To investigate the value of number of negative lymph nodes (NLNs) in predicting the prognosis of patients with esophageal cancer after neoadjuvant therapy and the construction of nomogram prodiction model.Methods:The retrospective cohort study was conducted. The clinicopathological data of 1 924 patients with esophageal cancer after neoadjuvant therapy uploaded to the Surveillance, Epidemiology, and End Results Database of the National Cancer Institute from 2004 to 2015 were collected. There were 1 624 males and 300 females, aged 63 (range, 23?85)years. All 1 924 patients were randomly divided into the training dataset of 1 348 cases and the validation dataset of 576 cases with a ratio of 7:3 based on random number method in the R software (3.6.2 version). The training dataset was used to constructed the nomogram predic-tion model, and the validation dataset was used to validate the performance of the nomogrram prediction model. The optimal cutoff values of number of NLNs and number of examined lymph nodes (ELNs) were 8, 14 and 10, 14, respectively, determined by the X-tile software (3.6.1 version), and then data of NLNs and ELNs were converted into classification variables. Observation indicators: (1) clinicopathological characteristics of patients in the training dataset and the validation dataset; (2) survival of patients in the training dataset and the validation dataset; (3) prognostic factors analysis of patients in the training dataset; (4) survival of patients in subgroup of the training dataset; (5) prognostic factors analysis in subgroup of the training dataset; (6) construction of nomogram prediction model and calibration curve. Measurement data with normal distribution were represented as Mean± SD, and comparison between groups was conducted using the t test. Measurement data with skewed distribution were represented as M(range), and comparison between groups was conducted using the Mann-Whitney U test. Count data were described as absolute numbers, and comparison between groups was conducted using the chi-square test. The Kaplan-Meier method was used to draw survival curve and Log-Rank test was used for survival analysis. The COX proportional hazard model was used for univariate and multivariate analyses. Based on the results of multivariate analysis, the nomogram prediction model was constructed. The prediction efficacy of nomogram prediction model was evaluated using the area under curve (AUC) of the receiver operating characteristic curve and the Harrell′s c index. Errors of the nomogram prediction model in predicting survival of patients for the training dataset and the validation dataset were evaluated using the calibration curve. Results:(1) Clinicopathological characteristics of patients in the training dataset and the validation dataset. There was no significant difference in clinicopatholo-gical characteristics between the 1 348 patients of the training dataset and the 576 patients of the validation dataset ( P>0.05). (2) Survival of patients in the training dataset and the validation dataset. All 1 924 patients were followed up for 50(range, 3?140)months, with 3-year and 5-year cumulative survival rate as 59.4% and 49.5%, respectively. The 3-year cumulative survival rate of patients with number of NLNs as <8, 8?14 and >14 in the training dataset was 46.7%, 62.0% and 66.0%, respectively, and the 5-year cumulative survival rate was 38.1%, 52.1% and 59.7%, respectively. There was a significant difference in the survival of these patients in the training dataset ( χ2=33.70, P<0.05). The 3-year cumulative survival rate of patients with number of NLNs as <8, 8?14 and >14 in the validation dataset was 51.1%, 54.9% and 71.2%, respectively, and the 5-year cumulative survival rate was 39.3%, 42.5% and 55.7%, respectively. There was a significant difference in the survival of these patients in the validation dataset ( χ2=14.49, P<0.05). The 3-year cumulative survival rate of patients with number of ELNs as <10, 10?14 and >14 in the training dataset was 53.9%, 60.0% and 62.7%, respectively, and the 5-year cumulative survival rate was 44.7%, 49.1% and 56.9%, respectively. There was a significant difference in the survival of these patients in the training dataset ( χ2=9.88, P<0.05). The 3-year cumulative survival rate of patients with number of ELNs as <10, 10?14 and >14 in the validation dataset was 56.2%, 47.9% and 69.3%, respectively, and the 5-year cumula-tive survival rate was 44.9%, 38.4% and 51.9%, respectively. There was a significant difference in the survival of these patients in the validation dataset ( χ2=9.30, P<0.05). (3) Prognostic factors analysis of patients in the training dataset. Results of multivariate analysis showed that gender, neoadjuvant pathological (yp) T staging, ypN staging (stage N1, stage N2, stage N3) and number of NLNs (8?14, >14) were independent influencing factors for the prognosis of patients with esophageal cancer after neoadjuvant therapy ( hazard ratio=0.65, 1.44, 1.96, 2.41, 4.12, 0.69, 0.56, 95% confidence interval as 0.49?0.87, 1.17?1.78, 1.59?2.42, 1.84?3.14, 2.89?5.88, 0.56?0.86, 0.45?0.70, P<0.05). (4) Survival of patients in subgroup of the training dataset. Of the patients with NLNs in the training dataset, the 3-year cumulative survival rate of patients with number of NLNs as <8, 8?14 and >14 was 61.1%, 71.6% and 76.8%, respectively, and the 5-year cumulative survival rate was 50.7%, 59.9% and 70.1%, respectively. There was a significant difference in the survival of these patients in the training dataset ( χ2=12.66, P<0.05). Of the patients with positive lymph nodes in the training dataset, the 3-year cumulative survival rate of patients with number of NLNs as <8, 8?14 and >14 was 26.1%, 42.9% and 44.7%, respectively, and the 5-year cumulative survival rate was 20.0%, 36.5% and 39.3%, respectively. There was a significant difference in the survival of these patients in the training dataset ( χ2=20.39, P<0.05). (5) Prognostic factors analysis in subgroup of the training dataset. Results of multivariate analysis in patients with NLNs in the training dataset showed that gender, ypT staging and number of NLNs (>14) were independent influencing factors for the prognosis of patients with esophageal cancer after neoadju-vant therapy ( hazard ratio=0.67, 1.44, 0.56, 95% confidence interval as 0.47?0.96, 1.09?1.90, 0.41?0.77, P<0.05). Results of multi-variate analysis in patients with positive lymph nodes in the training dataset showed that race as others, histological grade as G2, ypN staging as stage N3 and number of NLNs (8?14, >14) were independent influencing factors for the prognosis of patients with esophageal cancer after neoadjuvant therapy ( hazard ratio=2.73, 0.70, 2.08, 0.63, 0.59, 95% confidence interval as 1.43?5.21, 0.54?0.91, 1.44?3.02, 0.46?0.87, 0.44?0.78, P<0.05). (6) Construction of nomogram prediction model and calibration curve. Based on the multivariate analysis of prognosis in patients of the training dataset ,the nomogram prediction model for the prognosis of patients with esophageal cancer after neoadju-vant treatment was constructed based on the indicators of gender, ypT staging, ypN staging and number of NLNs. The AUC of nomogram prediction model in predicting the 3-, 5-year cumulative survival rate of patients in the training dataset and the validation dataset was 0.70, 0. 70 and 0.71, 0.71, respectively. The Harrell′s c index of nomogram prediction model of patients in the training dataset and the validation dataset was 0.66 and 0.63, respectively. Results of calibration curve showed that the predicted value of the nomogram prediction model of patients in the training dataset and the validation dataset was in good agreement with the actual observed value. Conclusion:The number of NLNs is an independent influencing factor for the prognosis of esophageal cancer patients after neoadjuvant therapy, and the nomogram prediction model based on number of NLNs can predict the prognosis of esophageal cancer patients after neoadjuvant therapy.

Tumors still perform glycolysis in the aerobic environment to accelerate the uptake of glucose and produce a large amount of lactic acid in tumor microenvironment, provide biomolecular precursors of nucleotides, lipids, and proteins for tumor cell proliferation, and inhibit the function of immune cells and promote the metastasis of tumor cells in acidic environment. Gluconeogenesis, as the reverse reaction of glycolysis, is inhibited in hepatocellular carcinoma, especially the downregulated expression of the four key rate-limiting enzymes pyruvate carboxylase, phosphoenolpyruvate carboxykinase, fructose-1, 6-diphosphate 1, and glucose-6-phosphatase 4, which promotes the growth and proliferation of hepatocellular carcinoma by promoting aerobic glycolysis and its branched pathways, and meanwhile, it is also associated with the overall survival time and prognosis of patients with hepatocellular carcinoma and is considered an inhibitor for hepatocellular carcinoma. Therefore, this review summarizes the changes and mechanism of action of the key enzymes of gluconeogenesis in the development and progression of hepatocellular carcinoma and analyzes the shortcomings and future directions of related research in hepatocellular carcinoma, so as to provide new ideas for the treatment of hepatocellular carcinoma.

Purpose: The influence of fasting blood glucose (FBG) and cholesterolemia primary liver cancer (PLC) in china was analyzed via a large prospective cohort study based on a community population, and the combined effects between them were investigated. Materials and Methods: Overall, 98,936 staff from the Kailuan Group who participated in and finished physical examinations between 2006 and 2007 were included in the cohort study. Their medical information was collected and they were followed up after examination. The correlations of serum FBG or TC with PLC were analyzed. Then, we categorized all staff into four groups: normal FBG/ non-hypocholesterolemia, normal FBG/hypocholesterolemia, elevated FBGon-hypocholesterolemia, elevated FBG/hypocholesterolemia and normal FBG/ non-hypocholesterolemia was used as a control group. The combined effects of elevated FBG and hypocholesterolemia with PLC were analyzed using the Age-scale Cox proportional hazard regression model. Results: During 1,134,843.68 person*years follow up, a total of 388 PLC cases occured. We found the elevated FBG and hypocholesterolemia increases the risk for PLC, respectively. Compared with the non-hypocholesterolemiaormal FBG group, the risk of PLC was significantly increased in the non-hypocholesterolemia/elevated FBG group (HR=1.19,95%CI 0.88–1.62) and hypocholesterolemiaormal FBG group (HR=1.53,95%CI 1.19–1.97), and in the hypocholesterolemia/elevated FBG group (HR=3.16 95%CI2.13-4.69). And, a significant interaction effect was found of FBG and TC on PLC. All results were independent from the influence of liver disease. Conclusion Elevated serum FBG and hypocholesterolemia are risk factors for PLC, especially when combined. Thus, for the prevention and treatment of PLC, serum FBG and TC levels should be investigated.

The clinical data of 288 patients with gastrointestinal perforation undergoing surgical treatment from Jul 2014 to Jul 2017 were retrospectively analyzed,among whom the surgical incision infection occurred in 112 patients(38.9％).The risk factors of the incision infections were examined with logistic regression analysis.The univariate analysis showed that preoperative albumin level (≤30 g/L),body mass index (＞24.0 kg/m2),duration of abdominal pain(＞24 h),extension of incision,preoperative shock,colostomy,preoperative antibiotic use and the operation time were associated with incision infections(P＜0.05),while the gender,age,preoperative hemoglobin level,diabetes,incision length were not associated with the incision infections(P＞0.05).The multivariate logistic regression analysis showed that the body mass index(OR=1.61,P＜0.01),gastrointestinal perforation site(colon and rectum,OR=5.60,P＜0.01),extension of incision (OR=3.94,P＜0.01) and operation time(OR=1.04,P=0.02)were independent risk factors of theincision infection.The results suggest that the full preoperative preparation,intensive treatment of underlying diseases,avoiding incision extension and shortening operation time may be able to reduce the surgical incision infections for patients with the gastrointestinal perforation.