A risk prediction model for delayed bleeding after ESD for gastric precancerous lesions.

OBJECTIVE: To investigate the risk factors for delayed postoperative bleeding after endoscopic submucosal dissection (ESD) in patients with gastric precancerous lesions and to construct a risk prediction model. METHODS: This retrospective analysis included clinical data from patients with gastric precancerous lesions who underwent ESD at Wuhan University People's Hospital between November 2016 and June 2022. An XGBoost model was built to predict delayed bleeding after ESD using risk factors identified by univariable and multivariate logistic regression analysis. The model was evaluated using receiver operating characteristic curves (ROC), and SHapely Additive exPlanations (SHAP) analysis was used to interpret the model. RESULTS: Seven factors were statistically associated with delayed postoperative bleeding in gastric precancerous lesions after ESD: age, low-grade intraepithelial neoplasia, hypertension, lesion size ≥ 40 mm, operative time ≥ 120 min, female, and nonuse of hemoclips. A risk prediction model was established. In the training cohort, the model achieved an AUC of 0.97 (0.96-0.98), a sensitivity of 0.90, a specificity of 0.94, and an F1 score of 0.91. In the validation cohort, the AUC was 0.94(0.90-0.98), with a sensitivity of 0.85, a specificity of 0.89, and an F1 score of 0.85. In the test cohort, the AUC was 0.94 (0.89-0.99), the sensitivity was 0.80, the specificity was 0.92, and the F1 score was 0.84, indicating strong predictive capability. CONCLUSION: In this study, an XGBoost prediction model for assessing the risk of delayed postoperative bleeding after ESD in patients with gastric precancerous lesions was developed and validated. This model can be applied in clinical practice to effectively predict the risk of post-ESD bleeding for individual patients.

Identification of Hub Genes Correlated with the Initiation and Development in Chronic Kidney Disease via Bioinformatics Analysis.

INTRODUCTION: Chronic kidney disease (CKD) is a major public health issue worldwide, which is characterized by irreversible loss of nephron and renal function. However, the molecular mechanism of CKD remains underexplored. METHODS: This study integrated three transcriptional profile datasets to investigate the molecular mechanism of CKD. The differentially expressed genes (DEGs) between Sham control (Con) and unilateral ureteral obstruction (UUO)-operated mice were analyzed by utilizing the limma package in R. The shared DEGs were analyzed by Gene Ontology and functional enrichment. Protein-protein interactions (PPIs) were constructed by utilizing the STRING database. Hub genes were analyzed by MCODE and Cytohubba. We further validated the gene expression by using the other dataset and mouse UUO model. RESULTS: A total of 315 shared DEGs between Con and UUO samples were identified. Gene function and KEGG pathway enrichment revealed that DEGs were mainly enriched in inflammatory response, immune system process, and chemokine signaling pathway. Two modules were clustered based on PPI network analysis. Module 1 contained 13 genes related to macrophage activation, migration, and chemotaxis. Ten hub genes were identified by PPI network analysis. Subsequently, the expression levels of hub genes were validated with the other dataset. Finally, these four validated hub genes were further confirmed by our UUO mice. Three validated hub genes, Gng2, Pf4, and Ccl9, showed significant response to UUO. CONCLUSION: Our study reveals the coordination of genes during UUO and provides a promising gene panel for CKD treatment. GNG2 and PF4 were identified as potential targets for developing CKD drugs.

A New Risk Score to Predict Intensive Care Unit Admission for Patients with Acute Pancreatitis 48 Hours After Admission: Multicenter Study.

AIMS: The objective of this study was to develop and validate an easy-to-use risk score (APRS) to predict which patients with acute pancreatitis (AP) will need intensive care unit (ICU) treatment within 48 h post-hospitalization on the basis of the ubiquitously available clinical records. METHODS: Patients with acute pancreatitis were retrospectively included from three independent institutions (RM cohort, 5280; TJ cohort, 262; SN cohort, 196), with 56 candidate variables collected within 48 h post-hospitalization. The RM cohort was randomly divided into a training set (N = 4220) and a test set (N = 1060). The most predictive features were extracted by LASSO from the RM cohort and entered into multivariate analysis. APRS was constructed using the coefficients of the statistically significant variables weighted by the multivariable logistic regression model. The APRS was validated by RM, TJ, and SN cohorts. The C-statistic was employed to evaluate the APRS's discrimination. DeLong test was used to compare area under the receiver operating characteristic curve (AUC) differences. RESULTS: A total of 5738 patients with AP were enrolled. Eleven variables were selected by LASSO and entered into multivariate analysis. APRS was inferred using the above five factors (pleural effusion, ALT/AST, ALB/GLB, urea, and glucose) weighted by their regression coefficients in the multivariable logistic regression model. The C-statistics of APRS were 0.905 (95% CI 0.82-0.98) and 0.889 (95% CI 0.81-0.96) in RM and TJ validation. An online APRS web-based calculator was constructed to assist the clinician to earlier assess the clinical outcomes of patients with AP. CONCLUSION: APRS could effectively stratify patients with AP into high and low risk of ICU admission within 48 h post-hospitalization, offering clinical value in directing management and personalize therapeutic selection for patients with AP.

CircRNA_0040705 promotes the progression of hepatocellular carcinoma.

Circular RNAs (circRNAs) are involved in cancer progression. Nonetheless, the role and mechanism of circ_0040705 in hepatocellular carcinoma (HCC) are unclear. The aberrantly expressed circRNAs and microRNAs (miRNAs) in HCC tissues were screened by bioinformatics. Circ_0040705, miR-557, SRY-box transcription factor 2 (SOX2), E-cadherin, and N-cadherin expressions were determined using quantitative real-time polymerase chain reaction (qRT-PCR) or Western blot. Cell counting kit-8 (CCK-8), 5-ethynyl-2'-deoxyuridine (EdU), and Transwell experiments were utilized to examine the changes in HCC cell growth, migration, and invasion after circ_0040475 was overexpressed or knocked down. Lung metastasis assay was used to validate the effects of circRNA_0040705 on the lung metastasis of HCC cells in vivo. Binding sequences between circ_0040705 and miR-557 and between miR-557 and SOX2 were verified using dual-luciferase reporter gene experiments. The expression levels of circ_0040705 and SOX2 mRNA were markedly increased in HCC tissues, but miR-557 expression was down-regulated. Circ_0040705 overexpression enhanced the growth, migration, invasion, and the expressions of E-cadherin and N-cadherin of HCC cells and promoted lung metastasis in vivo, whereas circ_0040705 knockdown exerted the opposite effects in HCC cells. Circ_0040705 worked as a sponge for miR-557 to down-modulate miR-557 expression, and miR-557 could specifically down-modulate SOX2 expression. Circ_0040705 facilitates HCC cell growth, migration, and invasion by down-modulating miR-557 expression and up-modulating SOX2 expression.

Machine learning model identifies aggressive acute pancreatitis within 48 h of admission: a large retrospective study.

BACKGROUND: Acute pancreatitis (AP) with critical illness is linked to increased morbidity and mortality. Current risk scores to identify high-risk AP patients have certain limitations. OBJECTIVE: To develop and validate a machine learning tool within 48 h after admission for predicting which patients with AP will develop critical illness based on ubiquitously available clinical, laboratory, and radiologic variables. METHODS: 5460 AP patients were enrolled. Clinical, laboratory, and imaging variables were collected within 48 h after hospital admission. Least Absolute Shrinkage Selection Operator with bootstrap method was employed to select the most informative variables. Five different machine learning models were constructed to predictive likelihood of critical illness, and the optimal model (APCU) was selected. External cohort was used to validate APCU. APCU and other risk scores were compared using multivariate analysis. Models were evaluated by area under the curve (AUC). The decision curve analysis was employed to evaluate the standardized net benefit. RESULTS: Xgboost was constructed and selected as APCU, involving age, comorbid disease, mental status, pulmonary infiltrates, procalcitonin (PCT), neutrophil percentage (Neu%), ALT/AST, ratio of albumin and globulin, cholinesterase, Urea, Glu, AST and serum total cholesterol. The APCU performed excellently in discriminating AP risk in internal cohort (AUC = 0.95) and external cohort (AUC = 0.873). The APCU was significant for biliogenic AP (OR = 4.25 [2.08-8.72], P < 0.001), alcoholic AP (OR = 3.60 [1.67-7.72], P = 0.001), hyperlipidemic AP (OR = 2.63 [1.28-5.37], P = 0.008) and tumor AP (OR = 4.57 [2.14-9.72], P < 0.001). APCU yielded the highest clinical net benefit, comparatively. CONCLUSION: Machine learning tool based on ubiquitously available clinical variables accurately predicts the development of AP, optimizing the management of AP.

Gastrointestinal Symptoms Onset in COVID-19 Patients in Wuhan, China.

BACKGROUND: Early detection is critical in limiting the spread of 2019 novel coronavirus (COVID-19). Although previous data revealed characteristics of GI symptoms in COVID-19, for patients with only GI symptoms onset, their diagnostic process and potential transmission risk are still unclear. METHODS: We retrospectively reviewed 205 COVID-19 cases from January 16 to March 30, 2020, in Renmin Hospital of Wuhan University. All patients were confirmed by virus nuclei acid tests. The clinical features and laboratory and chest tomographic (CT) data were recorded and analyzed. RESULTS: A total of 171 patients with classic symptoms (group A) and 34 patients with only GI symptoms (group B) were included. In patients with classical COVID-19 symptoms, GI symptoms occurred more frequently in severe cases compared to non-severe cases (20/43 vs. 91/128, respectively, p < 0.05). In group B, 91.2% (31/34) patients were non-severe, while 73.5% (25/34) patients had obvious infiltrates in their first CT scans. Compared to group A, group B patients had a prolonged time to clinic services (5.0 days vs. 2.6 days, p < 0.01) and a longer time to a positive viral swab normalized to the time of admission (6.9 days vs. 3.3 days, respectively, p < 0.01). Two patients in group B had family clusters of SARS-CoV-2 infection. CONCLUSION: Patients with only GI symptoms of COVID-19 may take a longer time to present to healthcare services and receive a confirmed diagnosis. In areas where infection is rampant, physicians must remain vigilant of patients presenting with acute gastrointestinal symptoms and should do appropriate personal protective equipment.

Glandular orientation and shape determined by computational pathology could identify aggressive tumor for early colon carcinoma: a triple-center study.

BACKGROUND: Identifying the early-stage colon adenocarcinoma (ECA) patients who have lower risk cancer vs. the higher risk cancer could improve disease prognosis. Our study aimed to explore whether the glandular morphological features determined by computational pathology could identify high risk cancer in ECA via H&E images digitally. METHODS: 532 ECA patients retrospectively from 2 independent data centers, as well as 113 from The Cancer Genome Atlas (TCGA), were enrolled in this study. Four tissue microarrays (TMAs) were constructed across ECA hematoxylin and eosin (H&E) stained slides. 797 quantitative glandular morphometric features were extracted and 5 most prognostic features were identified using minimum redundancy maximum relevance to construct an image classifier. The image classifier was evaluated on D2/D3 = 223, D4 = 46, D5 = 113. The expression of Ki67 and serum CEA levels were scored on D3, aiming to explore the correlations between image classifier and immunohistochemistry data and serum CEA levels. The roles of clinicopathological data and ECAHBC were evaluated by univariate and multivariate analyses for prognostic value. RESULTS: The image classifier could predict ECA recurrence (accuracy of 88.1%). ECA histomorphometric-based image classifier (ECAHBC) was an independent prognostic factor for poorer disease-specific survival [DSS, (HR = 9.65, 95% CI 2.15-43.12, P = 0.003)]. Significant correlations were observed between ECAHBC-positive patients and positivity of Ki67 labeling index (Ki67Li) and serum CEA. CONCLUSION: Glandular orientation and shape could predict the high risk cancer in ECA and contribute to precision oncology. Computational pathology is emerging as a viable and objective means of identifying predictive biomarkers for cancer patients.

Characteristics of disease progress in patients with coronavirus disease 2019 in Wuhan, China.

Coronavirus disease 2019 (COVID-19) patients were classified into four clinical stages (uncomplicated illness, mild, severe and critical pneumonia) depending on disease severity. We aim to investigate the corresponding clinical, radiological and laboratory characteristics between different clinical stages. A retrospective, single-centre study of 101 confirmed patients with COVID-19 at Renmin Hospital of Wuhan University from 2 January to 28 January 2020 was enrolled; follow-up endpoint was on 8 February 2020. Clinical data were collected and compared during the course of illness. The median age of the 101 patients was 51.0 years and 33.6% were medical staff. Fever (68%), cough (50%) and fatigue (23%) are the most common symptoms. About 26% patients underwent the mechanical ventilation and 98% patients were treated with antibiotics. Thirty-seven per cent patients were cured and 11 died. On admission, the number of patients with uncomplicated illness, mild, severe and critical pneumonia were 2 [2%], 86 [85%], 11 [11%] and 2 [2%]. Forty-four of the 86 mild pneumonia progressed to severe illness within 4 days, with nine patients worsened due to critical pneumonia within 4 days. Two of the 11 severe patients improved to mild condition while three others deteriorated. Significant differences were observed among groups of different clinical stages in numbers of influenced pulmonary segments (6 vs. 12 vs. 17, P < 0.001). A significantly upward trend was witnessed in ground-glass opacities overlapped with striped shadows (33% vs. 42% vs. 55% vs. 80%, P < 0.001), while pure ground-glass opacities gradually decreased as disease progressed (45% vs. 35% vs. 24% vs. 13%, P < 0.001) within 12 days. Lymphocytes, prealbumin and albumin showed a downtrend as disease progressed from mild to severe or critical condition, an uptrend was found in white blood cells, C-reactive protein, neutrophils and lactate dehydrogenase. The proportions of serum amyloid A > 300 mg/l in mild, severe and critical conditions were 18%, 46% and 71%, respectively.

Nuclear shape, architecture and orientation features from H&E images are able to predict recurrence in node-negative gastric adenocarcinoma.

BACKGROUND: Identifying intestinal node-negative gastric adenocarcinoma (INGA) patients with high risk of recurrence could help perceive benefit of adjuvant therapy for INGA patients following surgical resection. This study evaluated whether the computer-extracted image features of nuclear shapes, texture, orientation, and tumor architecture on digital images of hematoxylin and eosin stained tissue, could help to predict recurrence in INGA patients. METHODS: A tissue microarrays cohort of 160 retrospectively INGA cases were digitally scanned, and randomly selected as training cohort (D1 = 60), validation cohort (D2 = 100 and D3 = 100, D2 and D3 are different tumor TMA spots from the same patient), accompanied with immunohistochemistry data cohort (D3' = 100, a duplicate cohort of D3) and negative controls data cohort (D5 = 100, normal adjacent tissues). After nuclear segmentation by watershed-based method, 189 local nuclear features were captured on each TMA core and the top 5 features were selected by Wilcoxon rank sum test within D1. A morphometric-based image classifier (NGAHIC) was composed across the discriminative features and predicted the recurrence in INGA on D2. The intra-tumor heterogeneity was assessed on D3. Manual nuclear atypia grading was conducted on D1 and D2 by two pathologists. The expression of HER2 and Ki67 were detected by immunohistochemistry on D3 and D3', respectively. The association between manual grading and INGA outcome was analysis. RESULTS: Independent validation results showed the NGAHIC achieved an AUC of 0.76 for recurrence prediction. NGAHIC-positive patients had poorer overall survival (P = 0.017) by univariate survival analysis. Multivariate survival analysis, controlling for T-stage, histology stage, invasion depth, demonstrated NGAHIC-positive was a reproducible prognostic factor for poorer disease-specific survival (HR = 17.24, 95% CI 3.93-75.60, P < 0.001). In contrast, human grading was only prognostic for one reader on D2. Moreover, significant correlations were observed between NGAHIC-positive patients and positivity of HER2 and Ki67 labeling index. CONCLUSIONS: The NGAHIC could provide precision oncology, personalized cancer management.

Automated image analysis of nuclear atypia in high-power field histopathological image.

AIMS: We developed a computer-aided technique to study nuclear atypia classification in high-power field haematoxylin and eosin stained images. METHODS AND RESULTS: An automated technique for nuclear atypia score (NAS) calculation is proposed. The proposed technique uses sophisticated digital image analysis and machine-learning methods to measure the NAS for haematoxylin and eosin stained images. The proposed technique first segments all nuclei regions. A set of morphology and texture features is extracted from presegmented nuclei regions. The histogram of each feature is then calculated to characterize the statistical information of the nuclei. Finally, a support vector machine classifier is applied to classify a high-power field image into different nuclear atypia classes. A set of 1188 digital images was analysed in the experiment. We successfully differentiated the high-power field image with NAS1 versus non-NAS1, NAS2 versus non-NAS2 and NAS3 versus non-NAS3, with area under receiver-operating characteristic curve of 0.90, 0.86 and 0.87, respectively. In three classes evaluation, the average classification accuracy was 78.79%. We found that texture-based feature provides best performance for the classification. CONCLUSION: The automated technique is able to quantify statistical features that may be difficult to be measured by human and demonstrates the future potentials of automated image analysis technique in histopathology analysis.

MDR1 C3435T polymorphism and inflammatory bowel disease risk: a meta-analysis.

The C3435T polymorphism of the multidrug resistance gene (MDR1) has been implicated in inflammatory bowel disease (IBD) risk, but the reported results are inconsistent. Here we performed a meta-analysis to evaluate the association between C3435T polymorphism and the risk of IBD using all case-control studies published before February 2013 according to PubMed and Web of Science. A total of 13 case-control studies, including 6,757 cases and 4,295 controls, were included. Pooled odds ratio (OR) with 95 % confidence interval (CI) was calculated using fixed- or random-effects model. Overall, no evidence has indicated that the C3435T polymorphism was associated with the susceptibility to IBD (dominant model: OR = 1.05, 95 % CI: 0.96-1.16; CT vs. CC: OR = 1.06, 95 % CI: 0.95-1.17; TT vs. CC: OR = 1.04, 95 % CI: 0.92-1.17; recessive model: OR = 0.99, 95 % CI: 0.90-1.09). Besides, stratified analysis by clinical type also indicated that no significant association between MDR1 C3435T and the risk of Crohn's disease and ulcerative colitis was observed. This meta-analysis indicated that the C3435T polymorphism of MDR1 may not confer susceptibility to IBD.

Adiponectin polymorphisms and non-alcoholic fatty liver disease risk: a meta-analysis.

BACKGROUND AND AIM: The adiponectin polymorphism has been implicated in susceptibility to non-alcoholic fatty liver disease (NAFLD), but the results remain inconclusive. The aim of this meta-analysis is to investigate the association between adiponectin polymorphisms and NAFLD risk. METHODS: All eligible case-control studies published up to September 2013 were identified by searching PubMed, Web of Science, and CNKI. Effect sizes of odds ratio (OR) and 95% confidence interval (95% CI) were calculated by using a fixed- or random-effect model. RESULTS: A total of 10 case-control studies were included; of those, there were nine studies (1223 cases and 1580 controls) for +45T>G polymorphism, seven studies (876 cases and 989 controls) for +276G>T polymorphism, and three studies (299 cases and 383 controls) for -11337C>G polymorphism. Overall, a significantly increased risk was found for +45T>G and -11377C>G polymorphism (+45T>G: OR = 1.45, 95% CI: 1.06-2.00 for recessive model, OR = 1.48, 95% CI: 1.07-2.06 for GG vs TT; -11377C>G: OR = 1.52, 95% CI: 1.10-2.09 for dominant model, OR = 3.88, 95% CI: 1.29-11.68 for GG vs CC), while for +276G>T polymorphism, we found a significantly decreased risk between them (OR = 0.65, 95% CI: 0.45-0.94 for recessive model, OR = 0.58, 95% CI: 0.40-0.84 for TT vs GG). In subgroup analysis by ethnicity, significant association was detected among Asians for +276G>T polymorphism, but not for +45T>G polymorphism. Besides, none of the three adiponectin polymorphisms was associated with the serum adiponectin levels. CONCLUSION: This meta-analysis suggests that adiponectin +45T>G and -11377C>G polymorphisms might be a risk factor for NAFLD, while +276G>T polymorphism may be a protective factor for NAFLD among Asians.

AhR Activation Ameliorates Intestinal Barrier Damage in Immunostressed Piglets by Regulating Intestinal Flora and Its Metabolism.

The primary factor leading to elevated rates of diarrhea and decreased performance in piglets is immunological stress. The regulation of immune stress through the intestinal flora is a crucial mechanism to consider. In total, 30 weaned piglets were randomly allocated to five groups: the basal diet group (Control), basal diet + lipopolysaccharides group (LPS), basal diet + 250 µg/kg 6-Formylindolo [3,2-b] carbazole + LPS group (FICZ), basal diet + 3mg/kg Cardamonin + LPS group (LCDN), and basal diet + 6mg/kg Cardamonin + LPS group (HCDN/CDN). The results showed that compared with those of the LPS group, the expression of tight junction proteins (occludin; claudin-1) in the FICZ group was significantly increased, and the mRNA levels of IL-1ß and TNF-α were significantly reduced (p < 0.05). HCDN treatment had a better effect on LPS-induced intestinal barrier damage in this group than it did in the LCDN group. HCDN treatment leads to a higher villus height (VH), a higher ratio of villi height to crypt depth (V/C), higher tight junction proteins (ZO-1; occludin), and higher short-chain fatty acids (SCFAs). In addition, correlation analyses showed that Succinivibrio was positively correlated with several SCFAs and negatively correlated with prostaglandin-related derivatives in the FICZ group and CDN group (p < 0.05). In summary, Cardamonin alleviates intestinal mucosal barrier damage and inflammatory responses by regulating the intestinal microbiota and its metabolism.

Double-nylon purse-string suture in closing postoperative wounds following endoscopic resection of large (≥ 3 cm) gastric submucosal tumors.

BACKGROUND: Endoscopic full-thickness resection (EFTR) of gastric submucosal tumors (SMTs) is safe and effective; however, postoperative wound management is equally important. Literature on suturing following EFTR for large (≥ 3 cm) SMTs is scarce and limited. AIM: To evaluate the efficacy and clinical value of double-nylon purse-string suture in closing postoperative wounds following EFTR of large (≥ 3 cm) SMTs. METHODS: We retrospectively analyzed the data of 85 patients with gastric SMTs in the fundus of the stomach or in the lesser curvature of the gastric body whose wounds were treated with double-nylon purse-string sutures after successful tumor resection at the Endoscopy Center of Renmin Hospital of Wuhan University. The operative, postoperative, and follow-up conditions of the patients were evaluated. RESULTS: All tumors were completely resected using EFTR. 36 (42.35%) patients had tumors located in the fundus of the stomach, and 49 (57.65%) had tumors located in the body of the stomach. All patients underwent suturing with double-nylon sutures after EFTR without laparoscopic assistance or further surgical treatment. Postoperative fever and stomach pain were reported in 13 (15.29%) and 14 (16.47%) patients, respectively. No serious adverse events occurred during the intraoperative or postoperative periods. A postoperative review of all patients revealed no residual or recurrent lesions. CONCLUSION: Double-nylon purse-string sutures can be used to successfully close wounds that cannot be completely closed with a single nylon suture, especially for large (≥ 3 cm) EFTR wounds in SMTs.

Deep learning reveals lung shape differences on baseline chest CT between mild and severe COVID-19: A multi-site retrospective study.

Severe COVID-19 can lead to extensive lung disease causing lung architectural distortion. In this study we employed machine learning and statistical atlas-based approaches to explore possible changes in lung shape among COVID-19 patients and evaluated whether the extent of these changes was associated with COVID-19 severity. On a large multi-institutional dataset (N = 3443), three different populations were defined; a) healthy (no COVID-19), b) mild COVID-19 (no ventilator required), c) severe COVID-19 (ventilator required), and the presence of lung shape differences between them were explored using baseline chest CT. Significant lung shape differences were observed along mediastinal surfaces of the lungs across all severity of COVID-19 disease. Additionally, differences were seen on basal surfaces of the lung when compared between healthy and severe COVID-19 patients. Finally, an AI model (a 3D residual convolutional network) characterizing these shape differences coupled with lung infiltrates (ground-glass opacities and consolidation regions) was found to be associated with COVID-19 severity.

Early prediction of acute pancreatitis with acute kidney injury using abdominal contrast-enhanced CT features.

Early prediction of acute pancreatitis (AP) with acute kidney injury (AKI) using abdominal contrast-enhanced CT could effectively reduce the mortality and the economic burden on patients and society. However, this challenge is limited by the imaging manifestations of early-stage AP that are not clearly visible to the naked eye. To address this, we developed a machine learning model using imperceptible variations in the structural changes of pancreas and peripancreatic region, extracted by radiomics and artificial intelligence technology, to screen and stratify the high-risk AP patients at the early stage of AP. The results demonstrate that the machine learning model could screen the high-risk AP with AKI patients with an area under the curve (AUC) of 0.82 for the external cohort, superior to the human radiologists. This finding confirms the significant potential of machine learning in the screening of acute pancreatitis and contributes to personalized treatment and management for AP patients.

Dietary emodin alleviates lipopolysaccharide-induced intestinal mucosal barrier injury by regulating gut microbiota in piglets.

This study was to determine the effects of dietary emodin (ED) on the intestinal mucosal barrier, nuclear factor kappa-B (NF-κB) pathways, and gut microbial flora in lipopolysaccharide (LPS)-induced piglets. Twenty-four weaned piglets were chosen and 4 treatments were created by randomly distributing piglets into CON, ED, LPS, and ED_LPS groups. Experiments were done in a 2 × 2 factorial arrangement and maintained for 21 d. Dietary treatment (a basal diet or 300 mg/kg ED) and immunological challenge (LPS or sterile saline) were 2 major factors. Intraperitoneal injections of LPS or sterilized saline were given to piglets on d 21. Six hours after the LPS challenge, all piglets were euthanized for sample collection and analysis. The results showed that piglets of the ED_LPS group had higher (P < 0.05) villus height to crypt depth ratio (VCR), and lower (P < 0.05) plasma D-lactate and diamine oxidase (DAO) than the LPS group. Furthermore, ED inhibited (P < 0.05) the decrease of glutathione peroxidase (GSH-Px) and catalase (CAT) activities and increase of malonaldehyde level (P < 0.05) in jejunal mucosa induced by LPS. The mRNA levels of pro-inflammatory cytokine genes (IL-6, IL-1ß, and TNF-α) were significantly reduced (P < 0.05), and the mRNA levels of antioxidant enzyme genes (GPX-1, SOD2 and CAT), as well as protein and mRNA levels of tight junction proteins (occludin, claudin-1, and ZO-1), were also significantly increased (P < 0.05) by ED addition in LPS-induced piglets. Meanwhile, ED supplementation significantly decreased the LPS-induced protein levels of cyclooxygenase-2 and phosphorylation levels of NF-κB p65 and IκBα in jejunal mucosa. Emodin had a significant effect on the composition of gut microbial flora at various taxonomic positions as indicated by 16S RNA sequencing. The acetic acid, isobutyric acid, valeric acid, and isovaleric acid concentrations in the cecum were also increased by ED addition in pigs (P < 0.05). Furthermore, the correlation analysis revealed that some intestinal microbiota had a potential relationship with jejunal VCR, plasma D-lactate and DAO, jejunal mucosa GSH-Px and CAT activity, and cecal short-chain fatty acid concentration. These data suggest that ED is effective in alleviating LPS-induced intestinal mucosal barrier injury by modulating gut microbiota in piglets.

Thymoquinone inhibits growth and augments 5-fluorouracil-induced apoptosis in gastric cancer cells both in vitro and in vivo.

Thymoquinone (TQ), a component derived from the bioactive constituent of black seed (Nigella sativa), has been shown to exert biological activity on various types of human cancers. However, there are few studies addressing its effects on gastric cancer. Here, we present the first report describing the chemosensitizing effect of thymoquinone and 5-fluorouracil (5-FU) on gastric cancer cells both in vitro and in vivo. Studies have shown that pretreatment with TQ significantly increased the apoptotic effects induced by 5-FU in gastric cancer cell lines in vitro. Moreover, we found that TQ enhanced the 5-FU-induced killing of gastric cancer cells by mediating the downregulation of the anti-apoptotic protein bcl-2, the upregulation of the pro-apoptotic protein bax, and the activation of both caspase-3 and caspase-9. In addition to the in vitro results, it has been shown that the combined treatment of TQ with 5-FU represents a significantly more effective antitumor agent than either agent alone in a xenograft tumor mouse model. These data suggest that the TQ/5-FU combined treatment induces apoptosis by enhancing the activation of both caspase-3 and caspase-9 in gastric cancer cells. These results, which provide molecular evidence both in vitro and in vivo, support our conclusion that thymoquinone can activate caspase-3 and caspase-9 and thus result in the chemosensitisation of gastric cancer cells to 5-FU-induced cell death.

Thymoquinone prevents and ameliorates dextran sulfate sodium-induced colitis in mice.

BACKGROUND: Thymoquinone (TQ), an active ingredient of the seed oil extract of Nigella sativa Linn, has previously been shown to possess antitumor, antioxidant, and anti-inflammatory bioactivity. Whether TQ has any effect on colitis remains controversial. AIM: The aim of this study was to determine whether treatment with TQ prevents and ameliorates colonic inflammation in a mouse model of inflammatory bowel disease. METHODS: C57BL/6 murine colitis was induced by the administration of dextran sodium sulfate (DSS) (3 % W/V) in the drinking water supplied to the mice for 7 consecutive days. The mice with colitis were treated with 5, 10, or 25 mg/kg TQ orally, and changes in body weight and macroscopic and microscopic colitis scores were examined. In addition, biochemical analyses were conducted. RESULTS: The treatment of mice with TQ prevented and significantly reduced the appearance of diarrhea and body weight loss. These results were associated with amelioration of colitis-related damage, as measured by macroscopic and microscopic colitis scores. In addition, there was a significant reduction in colonic myeloperoxidase activity and malondialdehyde levels and an increase in glutathione levels. CONCLUSIONS: These results indicate that TQ administration can prevent and improve murine DSS-induced colitis. These findings suggest that TQ could serve as a potential therapeutic agent for the treatment of patients with inflammatory bowel disease.