Objective Objective To analyze the potential spatial factors affecting the genetic differentiation of Oncomelania hupensis robertsoni in Yunnan Province. Methods A total of 13 administrative villages were selected from schistosomiasis-endemic areas of Yunnan Province as O. hupensis snail sampling sites. At least 200 snails were collected in each site, and the spatial variable data of each site were recorded, including longitude, latitude and altitude. Thirty active and Schistosoma japonicum uninfected O. hupensis snails were selected from each sampling site by means of the crawling method and the cercarial shedding method. Genomic DNA was extracted from O. hupensis snails. Following PCR amplification, purification of PCR amplification products and sequencing, the gene sequences of O. hupensis snail samples were spliced and edited using the DNAstar software and the NCBI database to yield the complete mitochondrial sequences of O. hupensis snails at each sampling site, and the mitochondrial genetic distance matrix of O. hupensis robertsoni was calculated at each sampling site. The geographical coordinates of each sampling site were marked using the software ArcGIS 10.2, and the straight-line geographical distance between each sampling site was calculated. The altitude difference, longitude difference and latitude difference between each sampling site were calculated using the Excel software, and the correlation between the mitochondrial genetic distance matrix of O. hupensis robertsoni and each spatial variable matrix was examined by using the Mantel test at 13 sampling sites in Yunnan Province. Results Among the 13 O. hupensis snail sampling sites in Yunnan Province, the largest mitochondrial genetic distance of O. hupensis robertsoni snail populations was seen between Anding Village, Nanjian Yi Autonomous County and Caizhuang Village, Midu County (26.244 2), and the largest geographical distance was seen between Dongyuan Village, Gucheng District and Cangling Village, Chuxiong County (272.64 km). The highest altitude difference was seen between Anding Village, Nanjian Yi Autonomous County and Dongyuan Village, Gucheng District (1 086.10 m), and the largest longitude difference was found between Qiandian Village, Eryuan County and Cangling Village, Chuxiong County (1.86°), while the largest latitude difference was measured between Leqiu Village, Nanjian Yi Autonomous County and Dongyuan Village, Gucheng District (1.81°). In addition, the mitochondrial genetic distance of O. hupensis robertsoni snail populations was positively correlated with altitude at 13 snail sampling sites in Yunnan Province (r = 0.542 8, P < 0.001), and showed no significant correlations with geographical distance (r = 0.093 4, P > 0.05), longitude (r = −0.199 5, P > 0.05) or latitude (r = 0.205 7, P > 0.05). Conclusion Altitude may be a potential spatial factor affecting the genetic differentiation of O. hupensis robertsoni in Yunnan Province.

A prediction model for the risk of childhood allergic asthma was established through the analysis of public datasets. By using bioinformatics analysis methods, two datasets, GSE40732 and GSE40888, were selected, which included the whole-genome expression profile data of 222 children. Among them, GSE40732 was used as the training dataset to detect differentially expressed genes in peripheral blood mononuclear cells of children with the disease, and the master regulator analysis (MRA) algorithm was used to screen the master regulator genes in the inflammation-related pathway (GO: 0006954). After obtaining the master regulator genes, the expression of these master regulator genes in the GSE40732 and GSE40888 datasets was detected, and a prediction model was constructed through logistic regression, based on which risk scores were assigned to children. By comparing the risk scores of healthy children and children with the disease, the area under the curve (AUC) was used to evaluate the classification performance of the model. The average value of the risk scores of all children with the disease output by the model was calculated as the threshold. According to this threshold, the children with the disease in the two datasets were divided into high-risk and low-risk groups. The CIBERSORT algorithm was applied to analyze the infiltration of immune cells in the high-risk and low-risk groups, and the enrichment analysis of signaling pathways was completed using the msigdbr package in R software. The results showed that compared with healthy children, there were 377 up-regulated genes and 255 down-regulated genes in the peripheral blood mono-nuclear cells of children with the disease. The MRA algorithm analysis showed that there were five genes ( MUC5B, CST4, CCR7, TNF-α, and THBS1) that were the master regulator genes in the regulatory network. Risk score= MUC5B×3.47 +CST4×2.17 +CCR7×0.59 +TNF- α×0.54 +THBS1×1.67. The AUC in the GSE40732 and GSE40888 datasets were 0.874 and 0.682, respectively. Compared with the low-risk group, the resting memory CD4 +T cells and regulatory T cells in the peripheral blood of children with the disease in the high-risk group significantly decreased ( P<0.05), and both the IL-33 and IL-13 pathways were highly enriched. In conclusion, the model constructed in this study has a good predictive efficiency for the risk of allergic asthma and also has a certain effect on risk stratification.

Background: The function of CD69 expressed on T cells in chronic hepatitis B (CHB) remains unclear. We aimed to elucidate the roles of CD69 on T cells in the disease process and in antiviral therapy for CHB. Methods: We enrolled 335 treatment-naive patients with CHB and 93 patients with CHB on antiviral therapy. CD69, antiviral cytokine production by T cells, T-helper (Th) cells, and inhibitory molecules of T cells were measured using flow cytometry, and clinical-virological characteristics were examined dynamically during antiviral therapy. Results: CD69 expression on CD3+, CD4+, and CD8+ T cells was the lowest in the immune-active phase and was negatively correlated with liver transaminase activity, fibrosis features, inflammatory cytokine production by T cells, and Th-cell frequencies but positively with inhibitory molecules on T cells. CD69 expression on CD3+, CD4+, and CD8+ T cells decreased after 48 weeks of antiviral therapy, and patients with hepatitis B e antigen (HBeAg) seroconversion in week 48 showed lower CD69 expression on T cells at baseline and week 48. The area under the ROC curve of CD69 expression on T cells at baseline for predicting HBeAg seroconversion in week 48 was 0.870, the sensitivity was 0.909, and the specificity was 0.714 (P = 0.002). Conclusions CD69 negatively regulates T-cell immunity during CHB, and its expression decreases with antiviral therapy. CD69 expression predicts HBeAg seroconversion in week 48. CD69 may play an important negative role in regulating T cells and affect the efficacy of antiviral therapy.

A prediction model for the risk of childhood allergic asthma was established through the analysis of public datasets. By using bioinformatics analysis methods, two datasets, GSE40732 and GSE40888, were selected, which included the whole-genome expression profile data of 222 children. Among them, GSE40732 was used as the training dataset to detect differentially expressed genes in peripheral blood mononuclear cells of children with the disease, and the master regulator analysis (MRA) algorithm was used to screen the master regulator genes in the inflammation-related pathway (GO: 0006954). After obtaining the master regulator genes, the expression of these master regulator genes in the GSE40732 and GSE40888 datasets was detected, and a prediction model was constructed through logistic regression, based on which risk scores were assigned to children. By comparing the risk scores of healthy children and children with the disease, the area under the curve (AUC) was used to evaluate the classification performance of the model. The average value of the risk scores of all children with the disease output by the model was calculated as the threshold. According to this threshold, the children with the disease in the two datasets were divided into high-risk and low-risk groups. The CIBERSORT algorithm was applied to analyze the infiltration of immune cells in the high-risk and low-risk groups, and the enrichment analysis of signaling pathways was completed using the msigdbr package in R software. The results showed that compared with healthy children, there were 377 up-regulated genes and 255 down-regulated genes in the peripheral blood mono-nuclear cells of children with the disease. The MRA algorithm analysis showed that there were five genes ( MUC5B, CST4, CCR7, TNF-α, and THBS1) that were the master regulator genes in the regulatory network. Risk score= MUC5B×3.47 +CST4×2.17 +CCR7×0.59 +TNF- α×0.54 +THBS1×1.67. The AUC in the GSE40732 and GSE40888 datasets were 0.874 and 0.682, respectively. Compared with the low-risk group, the resting memory CD4 +T cells and regulatory T cells in the peripheral blood of children with the disease in the high-risk group significantly decreased ( P<0.05), and both the IL-33 and IL-13 pathways were highly enriched. In conclusion, the model constructed in this study has a good predictive efficiency for the risk of allergic asthma and also has a certain effect on risk stratification.

Objective:To investigate the predictive value of thrombus enhancement (TE) and thrombus permeability in cardioembolic thrombus with acute middle cerebral artery occlusion based on CT.Methods:The clinical and image data of 93 patients with acute middle cerebral artery occlusion who were admitted to the First Affiliated Hospital of Soochow University within 12 hours after onset from January 2020 to July 2022 were retrospectively analyzed. According to the TOAST criteria, the patients were divided into the cardioembolism (CE) group (43 cases) and the large artery atherosclerosis (LAA) group (50 cases). All patients received noncontrast CT and CT angiography, and then thrombus permeability [thrombus attenuation increase (TAI), void fraction (ε)] and TE were assessed. Independent sample t-test, Mann-Whitney U test and χ2 test were used in univariable analysis between two groups. Multivariable logistic regression analysis was used to explore the independent influencing factors for cardioembolic stroke and establish a logistic model. The receiver operating characteristic (ROC) curve and the area under the curve (AUC) were used to evaluate the predictive value of TAI, ε, TE and the logistic model in cardioembolic thrombus with acute middle cerebral artery occlusion. Results:There were statistically significant differences in sex, atrial fibrillation, hypertension, diabetes mellitus, smoking, baseline National Institutes of health stroke scale (NIHSS), TAI, ε and TE between the CE group and the LAA group ( P<0.05). Binary logistics regression analysis showed that TAI (OR=1.300, 95%CI 1.147-1.473, P<0.001), hypertension (OR=0.116, 95%CI 0.025-0.535, P=0.006) and baseline NIHSS (OR=1.165, 95%CI 1.040-1.304, P=0.008) were independent influencing factors for cardioembolic thrombus. The ROC curve indicated that the logistic model predicted cardioembolic thrombus with the highest AUC of 0.907 (95%CI 0.848-0.966). TE predicted cardioembolic thrombus with the highest sensitivity of 90.7%. Conclusion:TE and thrombus permeability have application value for predicting cardioembolic thrombus with acute middle cerebral artery occlusion based on CT.

Objective:To explore the predictive value of deep learning (DL)-based coronary artery calcification score (CACS) for obstructive coronary artery disease (CAD) and noncalcified plaque/mixed plaque in type 2 diabetes mellitus (T2DM).Methods:Forty hundred and twenty-four consecutive T2DM patients who accepted CACS scan and coronary CT angiography (CCTA) from December 2012 to December 2019 were included retrospectively, with clinical risk factors and plaque features collected. Plaque composition was classified as calcified, non-calcified or mixed plaque. Obstructive CAD was defined as maximum diameter stenosis≥50%. CACS was calculated with a fully automated method based on DL. Univariate and multivariate logistic regressions were applied to select statistically significant factors and the odds ratios(ORs) were measured. Receiver operating characteristic (ROC) curve was evaluated to assess the predictive performance.Results:Increased CACS was associated with a significantly higher odds of obstructive CAD in CCTA (adjusted ORs were 2.22, 6.18 and 16.98 for CACS=1-99, 100-299, 300-999 vs. CACS=0, and P values were 0.009,<0.001,<0.001 respectively). The area under ROC curve (AUC) of CACS to predict obstructive CAD was 0.764. Compared with 0, increased CACS was associated with increased risk of non-calcified/mixed plaque (adjusted ORs were 2.75, 4.76, 5.29 for CACS=1-99, 100-299, 300-999 respectively and P values were 0.001,<0.001,<0.001 respectively). The AUC of CACS to predict non-calcified/mixed plaque was 0.688. It took 1.17 min to perform automated measurement of CACS based on DL in total, which was significantly less than manual measurement of 1.73 min ( P<0.001). Conclusion:DL-based CACS can predict obstructive CAD and non-calcified plaque/mixed plaque in T2DM, which is economical and efficient, and has important value for clinical diagnosis and treatment.

Purpose: Long non-coding RNAs (lncRNAs) may act as oncogenes in small-cell lung cancer (SCLC). Exosomes containing lncRNAs released from cancer-associated fibroblasts (CAF) accelerate tumorigenesis and confer chemoresistance. This study aimed to explore the action mechanism of the CAF-derived lncRNA maternally expressed gene 3 (MEG3) on cisplatin (DDP) chemoresistance and cell processes in SCLC. Materials and Methods: Quantitative real-time PCR was conducted to determine the expression levels of MEG3, miR-15a-5p, and CCNE1. Cell viability and metastasis were measured by 3-(4, 5-dimethyl-2-thiazolyl)-2, 5-diphenyl-2-h-tetrazolium bromide and invasion assays, respectively. A xenograft tumor model was developed to confirm the effect of MEG3 overexpression on SCLC progression in vivo. Relationships between miR-15a-5p and MEG3/CCNE1 were predicted using StarBase software and validated by dual luciferase reporter assay. Western blotting was used to determine protein levels. A co-culture model was established to explore the effects of exosomes on MEG3 expression in SCLC cell lines. Results: MEG3 was overexpressed in SCLC tissues and cells. MEG3 silencing significantly repressed cell viability and metastasis in SCLC. High expression of MEG3 was observed in CAF-derived conditioned medium (CM) and exosomes, and promoted chemoresistance and cancer progression. Additionally, MEG3 was found to serve as a sponge of miR-15a-5p to mediate CCNE1 expression. Overexpression of miR-15a-5p and knockout of CCNE1 reversed the effects of MEG3 overexpression on cell viability and metastasis. Conclusion MEG3 lncRNA released from CAF-derived exosomes promotes DDP chemoresistance via regulation of a miR-15a-5p/CCNE1 axis. These findings may provide insight into SCLC therapy.

Objective To study the change and characterization of metabolic profile of intestinal contents of the neonatal rats with necrotizing enterocolitis (NEC) using metabolomics approach,in order to figure out potential biomarkers of NEC.Method Twenty rats with three-postnatal day-old fed with special formula were assigned to control group (n =8) and NEC group (n =12) randomly.Experimental NEC of rats in NEC group were induced by exposing to cold stimulation at 4 degrees Celsius for 10 minutes and to hypoxia at 95％ nitrogen for 10 minutes,three times a day for three consecutive days.All the rats were sacrificed after model preparation.Segments of the ileum of all the rats were collected for hematoxylin-eosin staining and subsequent pathological damage evaluation.The intestinal contents of the ileum and colon were collected by perfusion,followed by lyophilization and analyzed by UHPLC-QE-MS in order to conduct the non-target metabolomic determination.The information of the metabolites determined was calculated by multivariable analysis using SIMCA software.Result The pathological damage scores of NEC group were higher than those of the control group [(3.13 ± 0.83) vs.(0.25 ± 0.46),P ＜ 0.001].The results of orthogonal partial least squares discriminant analysis (OPLS-DA) model showed that in the ESI + mode,R2(x) =0.604,R2(y) =0.583,Q2 =0.960,while in the ESI-mode,the OPLS-DA model R2(x) =0.828,R2(y) =0.999,and Q2 =0.713,indicating that there is a significant difference in the intestinal content metabolic profile between the control group and the NEC group.Forty-eight differential metabolites related to NEC were identified.In ESI-mode,there were 22 differential metabolites,including L-isoisoleucine (+ 221％) and D-phenylalanine (+ 230％),L-histidine (+ 284％),xanthine (+ 207％),glutamyl leucine (+ 246％),allose (-70％),myristic acid (-57％) and pentadecanoic acid (-35％).What is more,in the ESI + mode,26 other differential metabolites were identified,including ornithine (+ 268％),D-leucine (+ 176％),L-iso Leucine (+ 213％),acetylcholine (+ 195％),nicotinamide adenine dinucleotide (+ 199％),citrulline (+ 158％),cytosine (-58％),xanthoic acid (-64％).These metabolites were reflected to 33 different metabolic pathways in KEGG databases.The pathway enrichment analysis and pathway topology analysis with MetaboAnalyst indicated that the arginine and proline metabolic pathways,histidine metabolic pathways,and glutathione metabolic pathways were the top altered pathways in the condition of NEC.Conclusion The metabolic profile of intestinal contents in NEC rats was significantly different from that in normal rats,which was characterized by amino acid accumulation,mainly involving the metabolic pathways of arginine,proline,histidine and glutathione.The detection of intestinal contents metabolic profile,especially amino acid metabolize group may be of great significance for the diagnosis of NEC,and improving intestinal microenvironment may be the key strategy for the prevention and treatment of NEC.

Objective:To investigate the value of pericoronary adipose tissue histogram parameters based on coronary CT angiography (CTA) images for the differentiation of acute coronary syndrome and stable coronary artery disease.Methods:The clinical data and CTA images of 93 patients with coronary CTA examination in Suzhou Kowloon Hospital from 2013 to 2018 were analyzed retrospectively. There were 39 patients with acute coronary syndrome (acute coronary syndrome group) and 54 patients with stable coronary artery disease (stable coronary artery disease group). A region of interest (ROI) was drawn around the stenosis of the coronary arteries, with CT attenuation ranging from-190 to -30 HU to exclude non-adipose tissue. The CT attenuation of ROI excluding non-adipose were measured and histogram analysis was performed. The obtained parameters included the mean value, median value and the 5th, 10th, 45th, 55th, 70th and 95th percentiles. The differences in histogram parameters between the two groups were compared, and then the value of each parameter in differentiating acute coronary syndrome and stable coronary artery disease was evaluated based on receiver operating characteristic (ROC) analysis. The stepwise regression of multivariate logistic regression analysis was used to identify the useful features and establish the final prediction model. The ROC curve of the final model was calculated and its value was analyzed.Results:The mean, median and the 5th, 10th, 45th, 55th,70th and 95th percentile differences between the acute coronary syndrome group and the stable coronary artery disease group were statistically significant (all P<0.05). The ROC curve for the median and the 95th percentile had the same area under curve (AUC) of 0.73. The sensitivity, specificity and AUC of the diagnostic model established by multiple logistic regression were 82.1%, 89.1% and 0.90 respectively. Conclusion:CT attenuation histogram of pericoronary adipose tissue is of high value in differentiating acute coronary syndrome from stable coronary artery disease.

Identification of genetic variants via high-throughput sequencing (HTS) technologies has been essential for both fundamental and clinical studies. However, to what extent the genome sequence composition affects variant calling remains unclear. In this study, we identified 63,897 multi-copy sequences (MCSs) with a minimum length of 300 bp, each of which occurs at least twice in the human genome. The 151,749 genomic loci (multi-copy regions, or MCRs) harboring these MCSs account for 1.98％of the genome and are distributed unevenly across chromosomes. MCRs containing the same MCS tend to be located on the same chromosome. Gene Ontology (GO) anal-yses revealed that 3800 genes whose UTRs or exons overlap with MCRs are enriched for Golgi-related cellular component terms and various enzymatic activities in the GO biological function cat-egory. MCRs are also enriched for loci that are sensitive to neocarzinostatin-induced double-strand breaks. Moreover, genetic variants discovered by genome-wide association studies and recorded indbSNP are significantly underrepresented in MCRs. Using simulated HTS datasets, we show that false variant discovery rates are significantly higher in MCRs than in other genomic regions. These results suggest that extra caution must be taken when identifying genetic variants in the MCRs via HTS technologies.