Genome analysis of the mpox (formerly monkeypox) virus and characterization of core/variable regions.

Since smallpox was eradicated in 1980, the monkeypox virus (MPXV) has emerged as the most threatening orthopoxvirus in the world. In this study, we conducted a comprehensive analysis of the currently published complete genome sequences of the monkeypox virus. The core/variable regions were identified through core-pan analysis of MPXV. Besides single-nucleotide polymorphisms, our study also revealed that specific genes, multi-copy genes, repeat sequences, and recombination fragments are primarily distributed in the variable region. This result suggests that variable regions are not only more susceptible to single-base mutations, but also to events such as gene loss or gain, as well as recombination. Taken together, our results demonstrate the genomic characteristics of the core/variable regions of MPXV, and contribute to our understanding of the evolution of MPXV.

Brain functional gradient and structure features in adolescent and adult autism spectrum disorders.

Understanding how function and structure are organized and their coupling with clinical traits in individuals with autism spectrum disorder (ASD) is a primary goal in network neuroscience research for ASD. Atypical brain functional networks and structures in individuals with ASD have been reported, but whether these associations show heterogeneous hierarchy modeling in adolescents and adults with ASD remains to be clarified. In this study, 176 adolescent and 74 adult participants with ASD without medication or comorbidities and sex, age matched healthy controls (HCs) from 19 research groups from the openly shared Autism Brain Imaging Data Exchange II database were included. To investigate the relationship between the functional gradient, structural changes, and clinical symptoms of brain networks in adolescents and adults with ASD, functional gradient and voxel-based morphometry (VBM) analyses based on 1000 parcels defined by Schaefer mapped to Yeo's seven-network atlas were performed. Pearson's correlation was calculated between the gradient scores, gray volume and density, and clinical traits. The subsystem-level analysis showed that the second gradient scores of the default mode networks and frontoparietal network in patients with ASD were relatively compressed compared to adolescent HCs. Adult patients with ASD showed an overall compression gradient of 1 in the ventral attention networks. In addition, the gray density and volumes of the subnetworks showed no significant differences between the ASD and HC groups at the adolescent stage. However, adults with ASD showed decreased gray density in the limbic network. Moreover, numerous functional gradient parameters, but not VBM parameters, in adolescents with ASD were considerably correlated with clinical traits in contrast to those in adults with ASD. Our findings proved that the atypical changes in adolescent ASD mainly involve the brain functional network, while in adult ASD, the changes are more related to brain structure, including gray density and volume. These changes in functional gradients or structures are markedly correlated with clinical traits in patients with ASD. Our study provides a novel understanding of the pathophysiology of the structure-function hierarchy in ASD.

Early Predictive Value of Different Indicators for Persistent Organ Failure in Acute Pancreatitis: A Systematic Review and Network Meta-Analysis.

GOALS: In this study, we conducted this network meta-analysis (based on the ANOVA model) to evaluate the predictive efficacy of each early predictor. BACKGROUND: Persistent organ failure (POF) is one of the determining factors in patients with acute pancreatitis (AP); however, the diagnosis of POF has a long-time lag (>48 h). It is of great clinical significance for the early noninvasive prediction of POF. STUDY: We conducted a comprehensive and systematic search in PubMed, Cochrane library, Embase, and Web of Science to identify relevant clinical trials, case-control studies, or cohort studies, extracted the early indicators of POF in studies, and summarized the predictive efficacy of each indicator through network meta-analysis. The diagnostic odds ratio (DOR) was used to rank the prediction efficiency of each indicator. RESULTS: We identified 23 studies in this network meta-analysis, including 10,393 patients with AP, of which 2014 patients had POF. A total of 10 early prediction indicators were extracted. The mean and 95% CI lower limit of each predictive indicator were greater than 1.0. Albumin had the largest diagnostic odds ratio, followed by high-density lipoprotein-cholesterol (HDL-C), Ranson Score, beside index for severity in acute pancreatitis Score, acute physiology and chronic health evaluation II, C-reactive protein (CRP), Interleukin 6 (IL-6), Interleukin 8 (IL-8), Systemic Inflammatory Response Syndrome (SIRS) and blood urea nitrogen. CONCLUSIONS: Albumin, high-density lipoprotein-cholesterol, Ranson Score, and beside index for severity in acute pancreatitis Score are effective in the early prediction of POF in patients with AP, which can provide evidence for developing effective prediction systems. However, due to the limitations of the extraction method of predictive indicators in this study, some effective indicators may not be included in this meta-analysis.

Acute Pancreatitis in Pregnancy: A Propensity Score Matching Analysis and Dynamic Nomogram for Risk Assessment.

BACKGROUND: Acute pancreatitis is easily confused with abdominal pain symptoms, and it could lead to serious complications for pregnant women and fetus, the mortality was as high as 3.3% and 11.6-18.7%, respectively. However, there is still lack of sensitive laboratory markers for early diagnosis of APIP and authoritative guidelines to guide treatment. OBJECTIVE: The purpose of this study was to explore the risk factors of acute pancreatitis in pregnancy, establish, and evaluate the dynamic prediction model of risk factors in acute pancreatitis in pregnancy patients. STUDY DESIGN: Clinical data of APIP patients and non-pregnant acute pancreases patients who underwent regular antenatal check-ups during the same period were collected. The dataset after propensity matching was randomly divided into training set and verification set at a ratio of 7:3. The model was constructed using Logistic regression, least absolute shrinkage and selection operator regression, R language and other methods. The training set model was used to construct the diagnostic nomogram model and the validation set was used to validate the model. Finally, the accuracy and clinical practicability of the model were evaluated. RESULTS: A total of 111 APIP were included. In all APIP patients, hyperlipidemic pancreatitis was the most important reason. The levels of serum amylase, creatinine, albumin, triglyceride, high-density lipoprotein cholesterol, and apolipoprotein A1 were significantly different between the two groups. The propensity matching method was used to match pregnant pancreatitis patients and pregnant non-pancreatic patients 1:1 according to age and gestational age, and the matching tolerance was 0.02. The multivariate logistic regression analysis of training set showed that diabetes, triglyceride, Body Mass Index, white blood cell, and C-reactive protein were identified and entered the dynamic nomogram. The area under the ROC curve of the training set was 0.942 and in validation set was 0.842. The calibration curve showed good predictive in training set, and the calibration performance in the validation set was acceptable. The calibration curve showed the consistency between the nomogram model and the actual probability. CONCLUSION: The dynamic nomogram model we constructed to predict the risk factors of acute pancreatitis in pregnancy has high accuracy, discrimination, and clinical practicability.

Comparing clinical outcomes of peroral endoscopic myotomy for achalasia between Eastern and Western countries: a systematic review and meta-analysis.

Peroral endoscopic myotomy (POEM) has revolutionized the therapeutic strategy for achalasia with promising results. We conducted this meta-analysis to compare clinical outcomes between Eastern and Western countries. A comprehensive literature search was conducted in PubMed, EMBASE, Web of Science and Cochrane Library databases to query for studies that assessed the efficacy of POEM for achalasia. All articles published from inception to December 31, 2021 were included. The primary outcome was the pooled clinical success rate. The secondary outcomes included the pooled technical success rate, incidence of adverse events, procedure time and hospital stay. Eighteen Eastern studies involving 5962 patients and 11 Western studies involving 1651 patients were included. The pooled clinical success rate and technical success rate for POEM was equal in the Eastern studies compared to Western studies. The pooled incidence of procedure adverse events for POEM was a little lower in the Eastern studies compared to Western studies (6.6% vs. 8.7%). Similarly, the incidence of reflux-related adverse events was lower in Eastern studies than that in Western studies. The pooled procedure time of POEM was shorter in Eastern studies compared to Western studies (61 minutes vs. 80 minutes), while the length of hospital stay was longer in Eastern studies compared to Western studies (5.8 days vs. 2.4 days). Overall, Eastern countries have the similar POEM outcomes compared to Western countries. However, Eastern countries still need to do more to reduce the length of hospital stay.

Hypoxia-responsive lncRNA G077640 promotes ESCC tumorigenesis via the H2AX-HIF1α-glycolysis axis.

Long noncoding RNAs (lncRNAs) contribute to esophageal squamous cell carcinoma (ESCC) progression, but the underlying mechanisms remain elusive. In this study, we verified a hitherto uncharacterized hypoxia-responsive lncRNA, G077640, which is upregulated in human ESCC cells and tissues, supporting the proliferation and migration of ESCC cells. Mechanistically, G077640 prevented hypoxia-inducible factor-1α (HIF1α) from being degraded by directly interacting with histone H2AX and further modulated the interaction of HIF1α and H2AX. In addition, G077640 reprogrammed glycolytic metabolism by regulating the expression of glucose transporter 4 (GLUT4), hexokinase 2 (HK2) and pyruvate dehydrogenase kinase 1 (PDK1) for ESCC proliferation and migration. Clinically, G077640 was associated with poor prognosis in ESCC patients. Taken together, our findings identified a hypoxia-responsive lncRNA that contributes to ESCC cells proliferation and migration, and targeting G077640 and its pathway might be a potential therapeutic strategy for ESCC.

Gender differences of authors of major Hepatology society guidelines during the past 15 years.

BACKGROUND AND OBJECTIVE: Recent studies have shown that women are underrepresented as authors of medical research and clinical practice guidelines. This study aimed to evaluate gender disparities of authors of major hepatology guidelines. METHODS: We reviewed the hepatology guidelines published by the following major gastroenterology societies from January 2008 to September 2022: the American Gastroenterological Association (AGA), American College of Gastroenterology (ACG), American Association for the Study of Liver Diseases (AASLD), Asian-Pacific Association for the Study of the Liver (APASL), British Society of Gastroenterology (BSG), European Association for the Study of the Liver (EASL) and Korean Association for the Study of the Liver (KASL). We determined the topic and the gender of all authors of each guideline. The numbers of men authors, women authors and total authors were collected. The trends of women first authors, women senior authors and total women authors were assessed. A logistic regression analysis was performed to analyse the relationship between the gender of the first or senior author and related factors. RESULTS: We identified 103 hepatology guidelines published between January 2008 and September 2022 published by the AGA, ACG, AASLD, APASL, BSG, EASL, and KASL. The gender of 1096 of 1100 (99.6%) authors was determined. Therefore, a total of 1096 authors were included: 223 (20.3%) authors were women and 873 (79.7%) authors were men. Women comprised 14.6% of all first authors, and 20.4% of all senior authors were women. Only the AASLD had writing committees comprising more than 30% total women authors. The proportions of women senior authors and total women authors increased significantly during the study period (p < .05). Women first authors and women senior authors were more likely to publish guidelines with more women authors. Women first authors were less likely to be co-authors with men authors. CONCLUSIONS: Over the course of the past decade, the proportion of women authors of major hepatology guidelines has been low; however, this gender gap appears to be closing.

States and hotspots in Helicobacter pylori research from 2002 to 2021: A bibliometric analysis.

BACKGROUND: Recently, numerous publications on Helicobacter pylori (H. pylori) have been published, but bibliometric analyses on this research field are scarce. To address this gap, we conducted a bibliometric analysis to provide a comprehensive overview and to explore the current research states and hotspots in this field. MATERIALS AND METHODS: Publications on H. pylori from 2002 to 2021 were retrieved from the Web of Science Core Collection database (WoSCC). Trends in publications and citations were analyzed using Excel 2021. VOSviewer and Citespace were used to perform bibliometrics analysis. RESULTS: 36,266 publications on H. pylori were retrieved from the WoSCC database. In general, we observed an increasing trend in the number of publications over the past 20 years. The United States was the most productive and influential country, with the largest proportion of both publications and total citations. Helicobacter, US Department of Veterans Affairs, and Graham, David were the most productive journals, institutions and authors, respectively. Further analysis the co-occurrence and burst detection of keywords revealed that the most common keywords were "Helicobacter pylori," "gastric cancer," and "gastritis," all keywords were divided into eight main clusters, and the most important current research hotspot was the relationship between H. pylori infection and the changes of gut microbiota. CONCLUSIONS: The United States has been the most productive and influential country on H. pylori research, and H. pylori-related research remains an active research field. The relationship between H. pylori infection and the changes of gut microbiota is a research hotspot attracting significant attention.

Prediction of in-hospital Mortality of Intensive Care Unit Patients with Acute Pancreatitis Based on an Explainable Machine Learning Algorithm.

BACKGROUND AND AIM: Acute pancreatitis (AP) is potentially fatal. Therefore, early identification of patients at a high mortality risk and timely intervention are essential. This study aimed to establish an explainable machine-learning model for predicting in-hospital mortality of intensive care unit (ICU) patients with AP. METHODS: Data on patients with AP, including demographics, vital signs, laboratory tests, comorbidities, treatment, complication, and severity scores, were extracted from the Medical Information Mart for Intensive Care IV (MIMIC-IV) and the eICU collaborative research database (eICU-CRD). Based on the data from MIMIC-IV, we used the least absolute shrinkage and selection operator algorithm to select variables and then established 9 machine-learning models and screened the optimal model. Data from the eICU-CRD were used for external validation. The area under the receiver operating characteristic curve (AUC), sensitivity, specificity, accuracy, decision curve, and calibration plots were used to assess the models' efficacy. Shapley's additive explanation values were used to explain the model. RESULTS: Gaussian naive Bayes (GNB) model had the best performance on the data from MIMIC-IV, with an AUC, accuracy, sensitivity, and specificity of 0.840, 0.787, 0.839, and 0.792, respectively. The GNB model also performed well on the data from the eICU-CRD, with an AUC, accuracy, sensitivity, and specificity of 0.862, 0.833, 0.848, and 0.763, respectively. According to Shapley's additive explanation values, the top 4 predictive factors were maximum red cell distribution width, minimum saturation of blood oxygen, maximum blood urea nitrogen, and the Sequential Organ Failure Assessment score. CONCLUSION: The GNB model demonstrated excellent performance and generalizability in predicting mortality in ICU patients with AP. Therefore, it can identify patients at a high mortality risk.

Application of a Machine Learning Predictive Model for Recurrent Acute Pancreatitis.

BACKGROUND AND AIM: Acute pancreatitis is the main cause of hospitalization for pancreatic disease. Some patients tend to have recurrent episodes after experiencing an episode of acute pancreatitis. This study aimed to construct predictive models for recurrent acute pancreatitis (RAP). METHODS: A total of 531 patients who were hospitalized for the first episode of acute pancreatitis at the Affiliated Hospital of Southwest Medical University from January 2018 to December 2019 were enrolled in the study. We confirmed whether the patients had a second episode until December 31, 2021, through an electronic medical record system and telephone or WeChat follow-up. Clinical and follow-up data of patients were collected and randomly allocated to the training and test sets at a ratio of 7:3. The training set was used to select the best model, and the selected model was tested with the test set. The area under the receiver operating characteristic curves, sensitivity, specificity, positive predictive value, negative predictive value, accuracy, decision curve, and calibration plots were used to assess the efficacy of the models. Shapley additive explanation values were used to explain the model. RESULTS: Considering multiple indices, XGBoost was the best model. The area under the receiver operating characteristic curves, accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of the XGBoost model in the test set were 0.779, 0.763, 0.883, 0.647, 0.341, and 0.922, respectively. According to the Shapley additive explanation values, drinking, smoking, higher levels of triglyceride, and the occurrence of ANC are associated with RAP. CONCLUSION: The XGBoost model shows good performance in predicting RAP, which may help identify high-risk patients.