Knowledge, attitude, and practice toward sleep disorders and sleep hygiene among perimenopausal women.

This cross-sectional study aimed to explore the knowledge, attitude and practice (KAP) toward sleep disorders and sleep hygiene among perimenopausal women, who were enrolled in Dezhou region of Shandong Province between July and September 2023. A total of 720 valid questionnaires were collected (mean age: 51.28 ± 4.32 years old), and 344 (47.78%) reported experiencing insomnia. The mean scores for knowledge, attitude, practice, and Dysfunctional Beliefs and Attitudes about Sleep (DBAS) were 15.73 ± 7.60 (possible range: 0-36), 29.35 ± 3.15 (possible range: 10-50), 28.54 ± 4.03 (possible range: 10-50), and 6.79 ± 1.90 (possible range: 0-10), respectively. Path analysis showed that knowledge had direct effects on attitude (ß = 0.04, 95% CI 0.01-0.07, P = 0.001), and DBAS (ß = 0.04, 95% CI 0.02-0.05, P < 0.001). Knowledge had direct effects (ß = 0.11, 95% CI 0.08-0.15, P < 0.001) and indirect (ß = 0.02, 95% CI 0.00-0.03, P = 0.002) effect on practice. Moreover, attitude also had a direct impact on practice (ß = 0.34, 95% CI 0.25-0.43, P < 0.001). In conclusion, perimenopausal women exhibited insufficient knowledge, negative attitude, inactive practice toward sleep disorders and sleep hygiene, and unfavorable DBAS, emphasizing the need for targeted healthcare interventions.

Development and validation of a nomogram for predicting in-hospital mortality of intensive care unit patients with liver cirrhosis.

BACKGROUND: Liver cirrhosis patients admitted to intensive care unit (ICU) have a high mortality rate. AIM: To establish and validate a nomogram for predicting in-hospital mortality of ICU patients with liver cirrhosis. METHODS: We extracted demographic, etiological, vital sign, laboratory test, comorbidity, complication, treatment, and severity score data of liver cirrhosis patients from the Medical Information Mart for Intensive Care IV (MIMIC-IV) and electronic ICU (eICU) collaborative research database (eICU-CRD). Predictor selection and model building were based on the MIMIC-IV dataset. The variables selected through least absolute shrinkage and selection operator analysis were further screened through multivariate regression analysis to obtain final predictors. The final predictors were included in the multivariate logistic regression model, which was used to construct a nomogram. Finally, we conducted external validation using the eICU-CRD. The area under the receiver operating characteristic curve (AUC), decision curve, and calibration curve were used to assess the efficacy of the models. RESULTS: Risk factors, including the mean respiratory rate, mean systolic blood pressure, mean heart rate, white blood cells, international normalized ratio, total bilirubin, age, invasive ventilation, vasopressor use, maximum stage of acute kidney injury, and sequential organ failure assessment score, were included in the multivariate logistic regression. The model achieved AUCs of 0.864 and 0.808 in the MIMIC-IV and eICU-CRD databases, respectively. The calibration curve also confirmed the predictive ability of the model, while the decision curve confirmed its clinical value. CONCLUSION: The nomogram has high accuracy in predicting in-hospital mortality. Improving the included predictors may help improve the prognosis of patients.

Significant elevation of serum CA19-9 and CA242 levels induced by dulaglutide.

The use of dulaglutide, a common medication for managing type 2 diabetes, rarely causes elevated pancreatic tumour markers. Here, we report the case of a woman in her mid-60s with diabetes for over 10 years. The patient presented with markedly elevated serum CA19-9 and CA242 levels revealed during a routine health examination despite being asymptomatic. She had been receiving dulaglutide injections for 16 months. Imaging and interventional assessments did not reveal any hepatobiliary, gastrointestinal or pancreatic neoplasm. After excluding alternate diagnoses, the patient was determined to exhibit an adverse reaction to dulaglutide use. Management involved the discontinuation of dulaglutide, which resulted in normalisation of serum CA19-9 and CA242 levels within 6 weeks. This case underscores the importance of discontinuing dulaglutide and monitoring changes in the biomarker levels in asymptomatic patients receiving dulaglutide, rather than immediately resorting to imaging and endoscopic examinations.

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.

Performance Evaluation of Newly-Developed Tumor Markers Assay Kit Based on Flow Fluorescence Assay.

BACKGROUND: The purpose of this study is to evaluate the performance of recently developed tumor marker clinical kits in China, with the aim of encouraging local medical technology innovation and thus narrowing the research and development gap with foreign kits. METHODS: The newly established reagent kits were analyzed on the TESMI F3999-Luminex200 flow lattice instrument to verify precision, sensitivity (blank limit), linearity, anti-interference ability, carry-over contamination rate, hook effect, and reference interval verification. Additionally, the newly established reagent kits were compared to other commercially available detection kits (reference reagent kits) to analyze the correlation between the two types of kits. RESULTS: The intra-assay and inter-assay precision had coefficients of variations (CVs) less than 3.50% and 6.91%, respectively. The tumor marker blank limits were lower than the manufacturer's statement. The newly established reagent kits demonstrated excellent linearity (r > 0.99). Rheumatoid factor, triglycerides, bilirubin, and hemoglobin did not have significant interference with the determination of tumor markers. The carry-over contamination rates were all much lower than 3%. At extremely high concentrations of AFP (277,335 ng/mL and 1,031,424 ng/mL), the measured tumor marker values were higher than the upper limit of the linear range and no hook effect occurred. The reference interval was suitable for use in clinical laboratory settings. Correlation analysis indicated a satisfactory relevance and consistency between the newly developed reagent kits and reference reagent kits, with correlation coefficients of r > 0.967 among 654 patients and healthy individuals. CONCLUSIONS: The newly developed reagent kits for tumor markers performed well in all evaluated parameters, having the potential for clinical promotion and application.

The burden of mental disorders in Asian countries, 1990-2019: an analysis for the global burden of disease study 2019.

Mental disorders are the leading contributors to the globally nonfatal burden of disease. This study was aimed to estimate the burden of mental disorders in Asian countries. Based on GBD 2019, the prevalence and disability-adjusted life of years (DALYs) rates with 95% uncertainty intervals (UI) were estimated in Asian countries. Predictions for the future burden of 8 selected countries, ranks of the burden of mental disorders and correlations with Sociodemographic Index (SDI) were also estimated. During the past 3 decades, while the number of DALYs of mental disorders increased from 43.9 million (95% UI: 32.5-57.2) to 69.0 million (95% UI: 51.0-89.7), the age-standardized rates of DALYs of mental disorders remained largely consistent from 1452.2 (95% UI: 1080.16-1888.53) per 100,000 population in 1990 to 1434.82 (95% UI: 1065.02-1867.27) per 100,000 population in 2019, ranked as the eighth most significant disease burden in Asia in 2019. Depressive disorders (37.2%) were the leading contributors to the age-standardized DALY rates of mental disorders in Asia, followed by anxiety disorders (21.5%). The age-standardized DALY rates in females were higher than their male counterparts, both peaked at 30-34 years. The age-standardized DALY rates were predicted to remain stable, with the number of DALYs presented an upward trend in the future. There was no significant correlation between the burden of mental disorders and SDI. All mental disorders ranked higher in 2019, compared in 1990. To reduce this burden, urgent measures for prevention, treatment, and rehabilitation for mental disorders need to be taken by Asian governments.

Antibiotic resistance genes profile in the surface sediments of typical aquaculture areas across 15 major lakes in China.

Aquatic farming is considered as a major source of antibiotic resistant bacteria (ARB) and antibiotic resistance genes (ARGs) for the natural environment of the lakes. ARB and ARGs in the natural environment have increased quickly because of the human activities. Here, we have profiled the diversity and abundance of ARGs in sediments from the typical aquaculture areas around 15 major lakes in China using PCR and qPCR, and further assessed the risk factor shaping the occurrence and distribution of ARGs. And class 1, 2 and 3 integrons were initially detected by PCR with specific primers. ARGs were widely distributed in the lakes: Weishan Lake and Poyang Lake showed high diversity of ARGs, followed by Dongting Lake, Chao Lake and Tai Lake. Generally, the ARGs in the Middle-Lower Yangtze Plain were more abundant than those in the Qinghai-Tibet Plateau. Tetracycline resistance genes (tet(C), tet(A) & tet(M)) were prominent in sediments, and the next was AmpC ß-lactamase gene group BIL/LAT/CMY, and the last was the genes resistance to aminoglycoside (strA-strB). Partial least squares path modeling analysis (PLS-PMA) revealed that livestock had a significant direct effect on the distribution of ARGs in lakes, and population might indirectly influence the profiles of ARGs by affecting the scale of livestock and aquaculture. The detectable rate of class 1, 2 and 3 integrons were 80%, 100% and 46.67%, respectively. The prevalence of integrons might play a key role in promoting more frequent horizontal gene transfer (HGT) events, resulting in the environmental mobilization and dissemination of ARGs between bacteria.

Trends of hospitalisation among new admission inpatients with oesophagogastric variceal bleeding in cirrhosis from 2014 to 2019 in the Affiliated Hospital of Southwest Medical University: a single-centre time-series analysis.

OBJECTIVES: This study aimed to assess the internal law and time trend of hospitalisation for oesophagogastric variceal bleeding (EGVB) in cirrhosis and develop an effective model to predict the trend of hospitalisation time. DESIGN: We used a time series covering 72 months to analyse the hospitalisation for EGVB in cirrhosis. The number of inpatients in the first 60 months was used as the training set to establish the autoregressive integrated moving average (ARIMA) model, and the number over the next 12 months was used as the test set to predict and observe their fitting effect. SETTING AND DATA: Case data of patients with EGVB between January 2014 and December 2019 were collected from the Affiliated Hospital of Southwest Medical University. OUTCOME MEASURES: The number of monthly hospitalised patients with EGVB in our hospital. RESULTS: A total of 877 patients were included in the analysis. The proportion of EGVB in patients with cirrhosis was 73% among men and 27% among women. The peak age at hospitalisation was 40-60 years. The incidence of EGVB varied seasonally with two peaks from January to February and October to November, while the lowest number was observed between April and August. Time-series analysis showed that the number of inpatients with EGVB in our hospital increased annually. The sequence after the first-order difference was a stationary series (augmented Dickey-Fuller test p=0.02). ARIMA (0,1,0) (0,1,1)12 with a minimum Akaike Information Criterion value of 260.18 could fit the time trend of EGVB inpatients and had a good short-term prediction effect. The root mean square error and mean absolute error were 2.4347 and 1.9017, respectively. CONCLUSIONS: The number of hospitalised patients with EGVB at our hospital is increasing annually, with seasonal changes. The ARIMA model has a good prediction effect on the number of hospitalised patients with EGVB in cirrhosis.

Bortezomib modulated the autophagy-lysosomal pathway in a TFEB-dependent manner in multiple myeloma.

OBJECTIVE: To explore the involvement of TFEB-mediated autophagy-lysosomal mechanisms in multiple myeloma (MM) during bortezomib treatment. METHODS: MM cells were exposed to bortezomib or subjected to TFEB knockdown. CCK assay was used to assess the cell proliferation. Western blotting and fluorescent staining were conducted to examine autophagy and lysosomes. The TFEB expression pattern was analyzed, and whole transcriptome sequencing was carried out. Additionally, TFEB target genes were predicted using the GTRD(http://gtrd.biouml.org/) website, and pathway analysis was performed. RESULTS: Bortezomib demonstrated a dose-dependent and time dependent inhibition of cell proliferation. In MM cells treated with bortezomib, LC3B, Beclin-1, TFEB, and Lamp1 exhibited upregulation in a time- and concentration-dependent manner. LysoTracker dye labeling showed an increase in lysosomes in the bortezomib-treated group. Moreover, bortezomib elevated the expression of lysosome-associated factor Lamp1. Bortezomib promoted the nuclear translocation of TFEB, leading to decreased cytoplasmic TFEB and increased nuclear TFEB. TFEB gene silencing reversed bortezomib's inhibitory effect on MM cell lines, significantly reducing autophagosome expression and lysosome numbers. Furthermore, bioinformatic analysis identified the MAPK pathway as a potential downstream target of TFEB. CONCLUSION: Bortezomib effectively inhibits MM cell proliferation and induces autophagy, partly through TFEB-mediated mechanisms, with potential involvement of the MAPK pathway.

Global trends and hotspots in the field of mitochondrial dynamics and hepatocellular carcinoma: A bibliometric analysis from 2007 to 2023.

Background: Mitochondria are dynamic organelles, and mitochondrial dynamics are important for the maintenance of mitochondrial inheritance and function. Recently, an increasing number of studies have shown that mitochondrial dynamics play an important role in the occurrence and development of hepatocellular carcinoma (HCC). However, bibliometric analyses of mitochondrial dynamics in HCC are scarce. Therefore, we conducted a bibliometric analysis to explore the current global research status and trends in mitochondrial dynamics and HCC. Methods: Global publications on mitochondrial dynamics and HCC published between 2007 and May 2023 were retrieved from the Web of Science Core Collection (WoSCC) database. Bibliometric analysis was performed using Bibliometrix, VOSviewer, and CiteSpace to analyze the numbers, citations, countries, institutions, authors, journals, references, and keywords. Results: A total of 518 publications were retrieved fromthe WoSCC database. China and The Fourth Military Medical University were the most productive countries and institutions. Zorzano, A published the most literature whereas Chen, HC was the author with the highest number of co-citations. Plos One was the most popular journal, whereas the Journal of Biological Chemistry had the highest number of co-citations. The most frequently used keyword was "mitochondria". Further analysis of the references and keywords showed that the molecular mechanisms linking them to drug therapy targets should be the focus of future studies. Conclusions: Research on mitochondrial dynamics in HCC has received much attention, and many studies have been published. However, research on mitochondrial dynamics and HCC has been limited by insufficient regional development imbalances and global cooperation. Nevertheless, future research on mitochondrial dynamics and HCC is promising, especially regarding the molecular mechanisms of mitochondrial fission and fusion and how to link the currently known molecular mechanisms with drug therapy targets for HCC.

Role of sestrins in metabolic and aging-related diseases.

Sestrins are a type of highly conserved stress-inducing protein that has antioxidant and mTORC1 inhibitory functions. Metabolic dysfunction and aging are the main risk factors for development of human diseases, such as diabetes, neurodegenerative diseases, and cancer. Sestrins have important roles in regulating glucose and lipid metabolism, anti-tumor functions, and aging by inhibiting the reactive oxygen species and mechanistic target of rapamycin complex 1 pathways. In this review, the structure and biological functions of sestrins are summarized, and how sestrins are activated and contribute to regulation of the downstream signal pathways of metabolic and aging-related diseases are discussed in detail with the goal of providing new ideas and therapeutic targets for the treatment of related diseases.

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.

FANCD2 as a novel prognostic biomarker correlated with immune and drug therapy in Hepatitis B-related hepatocellular carcinoma.

BACKGROUND: Ferroptosis is related to the immunosuppression of tumors and plays a critical role in cancer progression. Fanconi anemia complementation group D2 (FANCD2) is a vital gene that regulates ferroptosis. However, the mechanism of action of FANCD2 in Hepatitis B-related hepatocellular carcinoma (HCC) remains unknown. In this study, we investigated the prognostic significance and mechanism of action of FANCD2 in Hepatitis B-related HCC. METHODS: The expression of FANCD2 in Hepatitis B-related HCC was explored using The Cancer Genome Atlas (TCGA) and validated using the Gene Expression Omnibus (GEO) database. Univariate and multivariate Cox regression analyses and Kaplan-Meier survival curves were used to analyze the relationship between FANCD2 expression and the overall survival of patients with Hepatitis B-related HCC. Protein-protein interaction networks for FANCD2 were built using the STRING website. In addition, correlations between FANCD2 expression and the dryness index, tumor mutational burden, microsatellite instability (MSI), immune pathways, genes involved in iron metabolism, and sorafenib chemotherapeutic response were analyzed. RESULTS: Our results indicated that FANCD2 was significantly overexpressed in Hepatitis B-related HCC and demonstrated a strong predictive ability for diagnosis (Area Under Curve, 0.903) and prognosis of the disease. High FANCD2 expression was associated with poor prognosis, high-grade tumors, high expression of PDL-1, high MSI scores, and low sorafenib IC50 in Hepatitis B-related HCC. BRCA1, BRCA2, FAN1, and FANCC were vital proteins interacting with FANCD2. The expression level of FANCD2 significantly correlated with the infiltration levels of Treg cells, B cells, CD8 + T cells, CD4 + T cells, neutrophils, macrophages, myeloid dendritic cells, and NK cells in Hepatitis B-related HCC. FANCD2 was positively correlated with the tumor proliferation signature pathway, DNA repair, and cellular response to hypoxia. CONCLUSION: Our study indicated that FANCD2 was a potential novel biomarker and immunotherapeutic target against Hepatitis B-related HCC, which might be related to the chemotherapeutic response to sorafenib.

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.

Global burden of early-onset colorectal cancer among people aged 40-49 years from 1990 to 2019 and predictions to 2030.

PURPOSE: To explore the disease burden of early-onset colorectal cancer (EO-CRC) in individuals aged 40-49 years and provide baseline evidence for routine recommended age adjustment for CRC screening and other clinical decision-making. METHODS: We collected data stratified by sex, risk factors, and socio-demographic index (SDI) from the Global Burden of Disease Study 2019 Data Resources. Trends in disease burden were analyzed by estimated annual percentage change. The Bayesian age-period-cohort model predicted the burden over the following 10 years. RESULTS: In 2019, the global rates of incidence, mortality, prevalence, and disability-adjusted life year (DALY) of EO-CRC in people aged 40-44 years were 11.48 (95% uncertainty interval: 10.50-12.59), 4.35 (4.01-4.70), 72.63 (66.48-79.52), 209.82 (193.55-226.59) per 100,000 population. For people aged 45-49 years, the rates of these four estimates were 19.63 (17.97-21.54), 7.76 (7.16-8.41), 121.73 (110.99-133.84), and 335.83 (310.14-362.91), respectively. The incidence and prevalence rates for both age groups increased while the mortality and DALY rates remained stable from 1990 to 2019. In 2019, high-income North America had the highest incidence and prevalence rates. A low milk diet accounted for the largest proportion of global DALYs in EO-CRC, and there was a tendency for the DALY rate first to increase and then decrease with increasing SDI. The incidence and mortality rates were predicted to increase in the next 10 years. CONCLUSION: The current and future burden of EO-CRC among people aged 40-49 years is heavy. Substantial variation exists in disease burden across regions and countries. Urgent screening actions and policies are needed.

Development and Validation of a Dynamic Nomogram for Predicting in-Hospital Mortality in Patients with Acute Pancreatitis: A Retrospective Cohort Study in the Intensive Care Unit.

Purpose: The aim of this study is to develop and validate a predictive model for the prediction of in-hospital mortality in patients with acute pancreatitis (AP) based on the intensive care database. Patients and Methods: We analyzed the data of patients with AP in the Medical Information Mart for Intensive Care-IV (MIMIC-IV) database and Electronic Intensive Care Unit Collaborative Research Database (eICU-CRD). Then, patients from MIMIC-IV were divided into a development group and a validation group according to the ratio of 8:2, and eICU-CRD was assigned as an external validation group. Univariate logistic regression and least absolute shrinkage and selection operator regression were used for screening the best predictors, and multivariate logistic regression was used to establish a dynamic nomogram. We evaluated the discrimination, calibration, and clinical efficacy of the nomogram, and compared the performance of the nomogram with Acute Physiology and Chronic Health Evaluation II (APACHE-II) score and Bedside Index of Severity in AP (BISAP) score. Results: A total of 1030 and 514 patients with AP in MIMIC-IV database and eICU-CRD were included in the study. After stepwise analysis, 8 out of a total of 37 variables were selected to construct the nomogram. The dynamic nomogram can be obtained by visiting https://model.sci-inn.com/KangZou/. The area under receiver operating characteristic curve (AUC) of the nomogram was 0.859, 0.871, and 0.847 in the development, internal, and external validation set respectively. The nomogram had a similar performance with APACHE-II (AUC = 0.841, p = 0.537) but performed better than BISAP (AUC = 0.690, p = 0.001) score in the validation group. Moreover, the calibration curve presented a satisfactory predictive accuracy, and the decision curve analysis suggested great clinical application value of the nomogram. Conclusion: Based on the results of internal and external validation, the nomogram showed favorable discrimination, calibration, and clinical practicability in predicting the in-hospital mortality of patients with AP.

Multi-criteria assessment and triple-objective optimization of a bio-anode microfluidic microbial fuel cell.

Microfluidic microbial fuel cell has lower costs and greater potential than typical microbial fuel cell due to the elimination of proton exchange membrane. However, the development has mostly relied on experiments, and there has been little research on numerical simulations. Based on experimental validation, a reliable and universal model for microfluidic microbial fuel cell without quantifying the biomass concentration is proposed. Subsequently, the primary work is to study the output performance and energy efficiency of the microfluidic microbial fuel cell under different operating conditions and to comprehensively optimize the cell performance by employing the multi-objective particle swarm algorithm. Compared the optimal case with the base case, the increase ratios of maximum current density, power density, fuel utilization and exergy efficiency are 40.96%, 20.87%, 61.58% and 32.19%, respectively. On the basis of improving energy efficiency, the maximum power density and current density can reach 1.193 W/m2 and 3.51 A/m2.

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.

Bioinformatics Analysis of Differentially Expressed Genes and Related Pathways in Acute Pancreatitis.

OBJECTIVES: The aim of this study was to investigate differentially expressed genes (DEGs) in the acute pancreatitis (AP). METHODS: Microarray datasets GSE3644, GSE65146, and GSE109227 were downloaded from Gene Expression Omnibus database. Then, a comprehensive analysis of these genes was performed using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis, protein-protein interaction network analysis, core gene correlation analysis, and transcription factor prediction. Finally, the differences in the expression of hub genes in human organs and survival analysis in pancreatic carcinoma were evaluated. RESULTS: A total of 137 DEGs were screened, 128 genes were upregulated, and 9 genes were downregulated. Functional enrichment analysis demonstrated that these genes were mostly enriched in biological processes such as positive regulation of macroautophagy, cellular component such as focal adhesion, molecular function such as cadherin binding involved in cell-cell adhesion, and multiple pathways including tight junction. CDH1 and VCL were identified as hub DEGs, close interactions with MAZ, were expressed in human pancreas organs in various degrees. The high expression of CDH1 and VCL was significantly associated with poor prognosis in pancreatic carcinoma. CONCLUSIONS: The core genes CDH1 and VCL may play a key role in AP through regulation by MAZ.

Multiplexed Target Enrichment Enables Efficient and In-Depth Analysis of Antimicrobial Resistome in Metagenomes.

Antibiotic resistance genes (ARGs) pose a serious threat to public health and ecological security in the 21st century. However, the resistome only accounts for a tiny fraction of metagenomic content, which makes it difficult to investigate low-abundance ARGs in various environmental settings. Thus, a highly sensitive, accurate, and comprehensive method is needed to describe ARG profiles in complex metagenomic samples. In this study, we established a high-throughput sequencing method based on targeted amplification, which could simultaneously detect ARGs (n = 251), mobile genetic element genes (n = 8), and metal resistance genes (n = 19) in metagenomes. The performance of amplicon sequencing was compared with traditional metagenomic shotgun sequencing (MetaSeq). A total of 1421 primer pairs were designed, achieving extremely high coverage of target genes. The amplicon sequencing significantly improved the recovery of target ARGs (~9 × 104-fold), with higher sensitivity and diversity, less cost, and computation burden. Furthermore, targeted enrichment allows deep scanning of single nucleotide polymorphisms (SNPs), and elevated SNPs detection was shown in this study. We further performed this approach for 48 environmental samples (37 feces, 20 soils, and 7 sewage) and 16 clinical samples. All samples tested in this study showed high diversity and recovery of targeted genes. Our results demonstrated that the approach could be applied to various metagenomic samples and served as an efficient tool in the surveillance and evolution assessment of ARGs. Access to the resistome using the enrichment method validated in this study enabled the capture of low-abundance resistomes while being less costly and time-consuming, which can greatly advance our understanding of local and global resistome dynamics. IMPORTANCE ARGs, an increasing global threat to human health, can be transferred into health-related microorganisms in the environment by horizontal gene transfer, posing a serious threat to public health. Advancing profiling methods are needed for monitoring and predicting the potential risks of ARGs in metagenomes. Our study described a customized amplicon sequencing assay that could enable a high-throughput, targeted, in-depth analysis of ARGs and detect a low-abundance portion of resistomes. This method could serve as an efficient tool to assess the variation and evolution of specific ARGs in the clinical and natural environment.