An artificial intelligence-generated model predicts 90-day survival in alcohol-associated hepatitis: A global cohort study.

BACKGROUND AND AIMS: Alcohol-associated hepatitis (AH) poses significant short-term mortality. Existing prognostic models lack precision for 90-day mortality. Utilizing artificial intelligence in a global cohort, we sought to derive and validate an enhanced prognostic model. APPROACH AND RESULTS: The Global AlcHep initiative, a retrospective study across 23 centers in 12 countries, enrolled patients with AH per National Institute for Alcohol Abuse and Alcoholism criteria. Centers were partitioned into derivation (11 centers, 860 patients) and validation cohorts (12 centers, 859 patients). Focusing on 30 and 90-day postadmission mortality, 3 artificial intelligence algorithms (Random Forest, Gradient Boosting Machines, and eXtreme Gradient Boosting) informed an ensemble model, subsequently refined through Bayesian updating, integrating the derivation cohort's average 90-day mortality with each center's approximate mortality rate to produce posttest probabilities. The ALCoholic Hepatitis Artificial INtelligence Ensemble score integrated age, gender, cirrhosis, and 9 laboratory values, with center-specific mortality rates. Mortality was 18.7% (30 d) and 27.9% (90 d) in the derivation cohort versus 21.7% and 32.5% in the validation cohort. Validation cohort 30 and 90-day AUCs were 0.811 (0.779-0.844) and 0.799 (0.769-0.830), significantly surpassing legacy models like Maddrey's Discriminant Function, Model for End-Stage Liver Disease variations, age-serum bilirubin-international normalized ratio-serum Creatinine score, Glasgow, and modified Glasgow Scores ( p < 0.001). ALCoholic Hepatitis Artificial INtelligence Ensemble score also showcased superior calibration against MELD and its variants. Steroid use improved 30-day survival for those with an ALCoholic Hepatitis Artificial INtelligence Ensemble score > 0.20 in both derivation and validation cohorts. CONCLUSIONS: Harnessing artificial intelligence within a global consortium, we pioneered a scoring system excelling over traditional models for 30 and 90-day AH mortality predictions. Beneficial for clinical trials, steroid therapy, and transplant indications, it's accessible at: https://aihepatology.shinyapps.io/ALCHAIN/ .

Corticocortical connections of the rostral forelimb area in rats: a quantitative tract-tracing study.

The rostral forelimb area (RFA) in the rat is a premotor cortical region based on its dense efferent projections to primary motor cortex. This study describes corticocortical connections of RFA and the relative strength of connections with other cortical areas. The goal was to provide a better understanding of the cortical network in which RFA participates, and thus, determine its function in sensorimotor behavior. The RFA of adult male Long-Evans rats (n = 6) was identified using intracortical microstimulation techniques and injected with the tract-tracer, biotinylated dextran amine (BDA). In post-mortem tissue, locations of BDA-labeled terminal boutons and neuronal somata were plotted and superimposed on cortical field boundaries. Quantitative estimates of terminal boutons in each region of interest were based on unbiased stereological methods. The results demonstrate that RFA has dense connections with primary motor cortex and frontal cortex medial and lateral to RFA. Moderate connections were found with insular cortex, primary somatosensory cortex (S1), the M1/S1 overlap zone, and lateral somatosensory areas. Cortical connections of RFA in rat are strikingly similar to cortical connections of the ventral premotor cortex in non-human primates, suggesting that these areas share similar functions and allow greater translation of rodent premotor cortex studies to primates.

Epigenetic Induction of Smooth Muscle Cell Phenotypic Alterations in Aortic Aneurysms and Dissections.

BACKGROUND: Smooth muscle cell (SMC) phenotypic switching has been increasingly detected in aortic aneurysm and dissection (AAD) tissues. However, the diverse SMC phenotypes in AAD tissues and the mechanisms driving SMC phenotypic alterations remain to be identified. METHODS: We examined the transcriptomic and epigenomic dynamics of aortic SMC phenotypic changes in mice with angiotensin II-induced AAD by using single-cell RNA sequencing and single-cell sequencing assay for transposase-accessible chromatin. SMC phenotypic alteration in aortas from patients with ascending thoracic AAD was examined by using single-cell RNA sequencing analysis. RESULTS: Single-cell RNA sequencing analysis revealed that aortic stress induced the transition of SMCs from a primary contractile phenotype to proliferative, extracellular matrix-producing, and inflammatory phenotypes. Lineage tracing showed the complete transformation of SMCs to fibroblasts and macrophages. Single-cell sequencing assay for transposase-accessible chromatin analysis indicated that these phenotypic alterations were controlled by chromatin remodeling marked by the reduced chromatin accessibility of contractile genes and the induced chromatin accessibility of genes involved in proliferation, extracellular matrix, and inflammation. IRF3 (interferon regulatory factor 3), a proinflammatory transcription factor activated by cytosolic DNA, was identified as a key driver of the transition of aortic SMCs from a contractile phenotype to an inflammatory phenotype. In cultured SMCs, cytosolic DNA signaled through its sensor STING (stimulator of interferon genes)-TBK1 (tank-binding kinase 1) to activate IRF3, which bound and recruited EZH2 (enhancer of zeste homolog 2) to contractile genes to induce repressive H3K27me3 modification and gene suppression. In contrast, double-stranded DNA-STING-IRF3 signaling induced inflammatory gene expression in SMCs. In Sting-/- mice, the aortic stress-induced transition of SMCs into an inflammatory phenotype was prevented, and SMC populations were preserved. Finally, profound SMC phenotypic alterations toward diverse directions were detected in human ascending thoracic AAD tissues. CONCLUSIONS: Our study reveals the dynamic epigenetic induction of SMC phenotypic alterations in AAD. DNA damage and cytosolic leakage drive SMCs from a contractile phenotype to an inflammatory phenotype.

Association between preoperative anxiety states and postoperative complications in patients with esophageal cancer and COPD: a retrospective cohort study.

BACKGROUND: Esophageal cancer brings emotional changes, especially anxiety to patients. Co-existing anxiety makes the surgery difficult and may cause complications. This study aims to evaluate effects of anxiety in postoperative complications of esophageal cancer patients with chronic obstructive pulmonary disease (COPD). METHODS: Patients with esophageal cancer and co-existing COPD underwent tumor excision. Anxiety was measured using Hospital Anxiety and Depression Scale (HAD) before surgery. Clavien-Dindo criteria were used to grade surgical complications. A multiple regression model was used to analyze the relationship between anxiety and postoperative complications. The chi-square test was used to compare the differences in various types of complications between the anxiety group and the non-anxiety group. A multinomial logistic regression model was used to analyze the influencing factors of mild and severe complications. RESULTS: This study included a total of 270 eligible patients, of which 20.7% had anxiety symptoms and 56.6% experienced postoperative complications. After evaluation by univariate analysis and multivariate logistic regression models, the risk of developing complications in anxious patients was 4.1 times than non-anxious patients. Anxious patients were more likely to develop pneumonia, pyloric obstruction, and arrhythmia. The presence of anxiety, surgical method, higher body mass index (BMI), and lower preoperative oxygen pressure may increase the incidence of minor complications. The use of surgical methods, higher COPD assessment test (CAT) scores, and higher BMI may increase the incidence of major complications, while anxiety does not affect the occurrence of major complications (P = 0.054). CONCLUSION: Preoperative anxiety is associated with postoperative complications in esophageal cancer patients with co-existing COPD. Anxiety may increase the incidence of postoperative complications, especially minor complications in patient with COPD and esophageal cancer.

Aortic Stress Activates an Adaptive Program in Thoracic Aortic Smooth Muscle Cells That Maintains Aortic Strength and Protects Against Aneurysm and Dissection in Mice.

BACKGROUND: When aortic cells are under stress, such as increased hemodynamic pressure, they adapt to the environment by modifying their functions, allowing the aorta to maintain its strength. To understand the regulation of this adaptive response, we examined transcriptomic and epigenomic programs in aortic smooth muscle cells (SMCs) during the adaptive response to AngII (angiotensin II) infusion and determined its importance in protecting against aortic aneurysm and dissection (AAD). METHODS: We performed single-cell RNA sequencing and single-cell sequencing assay for transposase-accessible chromatin (scATAC-seq) analyses in a mouse model of sporadic AAD induced by AngII infusion. We also examined the direct effects of YAP (yes-associated protein) on the SMC adaptive response in vitro. The role of YAP in AAD development was further evaluated in AngII-infused mice with SMC-specific Yap deletion. RESULTS: In wild-type mice, AngII infusion increased medial thickness in the thoracic aorta. Single-cell RNA sequencing analysis revealed an adaptive response in thoracic SMCs characterized by upregulated genes with roles in wound healing, elastin and collagen production, proliferation, migration, cytoskeleton organization, cell-matrix focal adhesion, and PI3K-PKB/Akt (phosphoinositide-3-kinase-protein kinase B/Akt) and TGF-ß (transforming growth factor beta) signaling. ScATAC-seq analysis showed increased chromatin accessibility at regulatory regions of adaptive genes and revealed the mechanical sensor YAP/transcriptional enhanced associate domains as a top candidate transcription complex driving the expression of these genes (eg, Lox, Col5a2, Tgfb2). In cultured human aortic SMCs, cyclic stretch activated YAP, which directly bound to adaptive gene regulatory regions (eg, Lox) and increased their transcript abundance. SMC-specific Yap deletion in mice compromised this adaptive response in SMCs, leading to an increased AAD incidence. CONCLUSIONS: Aortic stress triggers the systemic epigenetic induction of an adaptive response (eg, wound healing, proliferation, matrix organization) in thoracic aortic SMCs that depends on functional biomechanical signal transduction (eg, YAP signaling). Our study highlights the importance of the adaptive response in maintaining aortic homeostasis and preventing AAD in mice.

Clinical success of anti-infective combination therapy compare to monotherapy in patients with carbapenem-resistant Pseudomonas aeruginosa infection: a 10-years retrospective study.

BACKGROUND: Carbapenem-resistant Pseudomonas aeruginosa (CRPA) infection has become a major public health concern. The recommendations for monotherapy and combination therapy in the current guidelines lack sufficient evidence to support them. The primary objective of this study is to determine the effectiveness of anti-Infective combination therapy compared to monotherapy in achieving clinical success in patients with CRPA infection and risk factors of clinical failure of monotherapy. METHODS: A retrospective study from Medical Information Mart for Intensive Care IV (MIMIC-IV) was conducted. We included adults with infections caused by CRPA. The outcomes of this study were clinical success, complete clinical success, and 28-day all-cause mortality. RESULTS: A total of 279 subjects were finally enrolled. The rate of clinical success for combination therapy was higher than that for monotherapy (73.1% versus 60.4%, p=0.028). Compared to clinical failure patients, patients in the clinical success group were more likely to die within 28 days after CRPA was found (48.3% versus 3.6%, p<0.001). In a multivariate logistic regression analysis, monotherapy was found to be significantly correlated with clinical success (OR, 0.559, 95% CI, 0.321-0.976; p = 0.041). CONCLUSION: Combination therapy is more effective for CRPA infection patients, especially those whose SOFA score is ≥ 2 or whose Charlson comorbidity index is ≥ 6.

Association between trough serum vancomycin concentration and vancomycin-associated acute kidney injury and 30-day mortality in critically ill elderly adults.

BACKGROUND: Vancomycin-associated acute kidney injury (VA-AKI) is the most clinically relevant side effect of vancomycin. The objective of this study was to investigate the association between VTC and VA-AKI as well as 30-day mortality in critically ill elderly adults. METHOD: Elderly patients with trough serum vancomycin concentration records(VTC) in the Medical Information Mart-IV (MIMIC-IV) and eICU databases were retrospectively studied. RESULTS: A total of 3,146 critically ill elderly adults were finally enrolled. The incidence of VA-AKI in the elderly population was 76.5%. Logistic regression analysis revealed significant relationships between VA-AKI and various factors, including VTC, comorbidities, and laboratory indicators, and SOFA, and GCS score. For each mg/L increase, the OR for VA-AKI increased by 2.5%. The association between VTC and 30-day mortality was found to be statistically significant (odds ratio (OR): 1.021, 95% CI: 1.010-1.031), P < 0.001). The Restricted cubic splines (RCS) curves revealed that VTC ranged of 19.67 to 35.72 mg/l for AKI and 19.17 to 42.86 mg/l for 30-day mortality exhibit OR with 95% CI above 1, indicating statistically significant associations with an increased risk of AKI and 30-day mortality, respectively. In the subgroup analysis, VTC was identified as a risk factor for VA-AKI in specific patient groups, including white individuals, female patients, those with shock, patients with SOFA > 6, patients with baseline creatinine > 1.2 mg/dl and patients with or without exposed to other nephrotoxic medications. CONCLUSION: This study found the significant association between VTC and the incidence of VA-AKI and 30-day mortality in critically ill elderly adults. The RCS curves indicated concentration ranges for AKI (19.67-35.72 mg/L) and 30-day mortality (19.17-42.86 mg/L), signifying increased risk.

Long term all-cause mortality after myocardial infarction with non-obstructed vs obstructed coronary artery disease: a meta-analysis of adjusted data.

BACKGROUND: The difference in the long-term outcomes of myocardial infarction in patients with non-obstructed coronary arteries (MINOCA) and patients with myocardial infarction with obstructed coronary artery disease (MI-CAD) is not clear. The current study aimed to pool adjusted data to compare long-term outcomes of MINOCA vs MI-CAD. METHODS: Electronic literature search of PubMed, Embase, CENTRAL, and Google Scholar databases was done for publications up to 18th June 2023. Only studies reporting multivariable-adjusted data with > 1 year of follow-up were included. RESULTS: Sixteen studies met the inclusion criteria. Our meta-analysis revealed no statistically significant difference in the risk of all-cause mortality between MINOCA and MI-CAD patients (HR: 0.90 95% CI 0.68, 1.19 I2 = 94% p = 0.48). Analysis of the limited data showed a reduced combined risk of all-cause mortality and MI (HR: 0.54 95% CI 0.39, 0.76 I2 = 72% p = 0.003) and major adverse cardiac events (MACE) (HR: 0.66 95% CI 0.51, 0.84 I2 = 51% p = 0.0009) in patients with MINOCA vs MI-CAD, and no difference in the risk of cardiovascular mortality (HR: 0.81 95% CI 0.54, 1.22 I2 = 0% p = 0.31) and readmission between the two groups (HR: 0.85 95% CI 0.61, 1.19 I2 = 90% p = 0.35). CONCLUSION: A pooled analysis of adjusted outcomes from the available studies indicated that MINOCA and MI-CAD patients have similar long-term all-cause mortality risk. Our conclusions on the risk of cardiovascular mortality, MACE and readmission rates need to be taken with caution due to a lack of adequate studies. Further research is needed to strengthen the evidence on this important subject.

Differential associations of fine and coarse particulate air pollution with cause-specific pneumonia mortality: A nationwide, individual-level, case-crossover study.

BACKGROUND: The connections between fine particulate matter (PM2.5) and coarse particulate matter (PM2.5-10) and daily mortality of viral pneumonia and bacterial pneumonia were unclear. OBJECTIVES: To distinguish the connections between PM2.5 and PM2.5-10 and daily mortality due to viral pneumonia and bacterial pneumonia. METHODS: Using a comprehensive national death registry encompassing all areas of mainland China, we conducted a case-crossover investigation from 2013 to 2019 at an individual level. Residential daily particle concentrations were evaluated using satellite-based models with a spatial resolution of 1 km. To analyze the data, we employed the conditional logistic regression model in conjunction with polynomial distributed lag models. RESULTS: We included 221,507 pneumonia deaths in China. Every interquartile range (IQR) elevation in concentrations of PM2.5 (lag 0-2 d, 37.6 µg/m3) was associated with higher magnitude of mortality for viral pneumonia (3.03%) than bacterial pneumonia (2.14%), whereas the difference was not significant (p-value for difference = 0.38). An IQR increase in concentrations of PM2.5-10 (lag 0-2 d, 28.4 µg/m3) was also linked to higher magnitude of mortality from viral pneumonia (3.06%) compared to bacterial pneumonia (2.31%), whereas the difference was not significant (p-value for difference = 0.52). After controlling for gaseous pollutants, their effects were all stable; however, with mutual adjustment, the associations of PM2.5 remained, and those of PM2.5-10 were no longer statistically significant. Greater magnitude of associations was noted in individuals aged 75 years and above, as well as during the cold season. CONCLUSION: This nationwide study presents compelling evidence that both PM2.5 and PM2.5-10 exposures could increase pneumonia mortality of viral and bacterial causes, highlighting the more robust effects of PM2.5 and somewhat higher sensitivity of viral pneumonia.

Risk factors associated with functional decline in older hospital survivors with acute lower respiratory tract infections: a prospective cohort study.

OBJECTIVE: To evaluate the dynamics of basic activity of daily living (BADL) in older patients with acute lower respiratory tract infections (LRTIs) during acute phase and to investigate risk factors associated with decreased physical function at discharge. METHODS: We conducted a prospective cohort study of patients aged 65 years and older who were hospitalized for acute LRTIs between April 15, 2020 and January 15, 2023. All patients received geriatric assessment at admission, including emotion, cognition, frailty, physical function status and so on. The BADL was also evaluated by the Barthel Index (BI) at two weeks before admission by recall (baseline status), at admission and at discharge. Based on the BI grades at baseline and at discharge, patients were classified into two groups: ADL decline and no ADL decline. Multivariable adjusted logistic regression models were used to evaluate the risk factors of decreased physical function. RESULTS: A total of 364 older survivors with LRTIs were included in the analysis. The median age was 74 years (IQR 61.0-82.0), 231 (62.6%) were male, the median length of stay was 10 days. In the geriatric assessment, 139 patients (38.2%) were classified as frailty, 137 patients (37.6%) experienced insomnia, 60 patients (16.5%) exhibited cognitive impairments, and 37 patients (10.2%) were defined as malnutrition. Additionally, 30 patients (8.2%) dealt with emotional disorders. On average, patients were taking 3 medications, and Charlson Comorbidity Index score was 4. 72 patients (19.8%) had function decline at discharge. In the multivariable analysis, frailty status had an odds ratio of 4.25 (95% CI 1.31-19.26) for decreased physical function and cognitive impairment had an odds ratio of 2.58 (95% CI 1.27-5.19). CONCLUSIONS: About 20% older patients with LRTIs experienced functional decline at discharge. Compared to age, severity of diseases and length of stay, frailty and cognitive impairment performed better at predicting the function decline. The apply of geriatric assessment may contribute to enhance the quality of management and treatment for patients with the older with LRTIs.

Catalytic Degradation of Lignin over Sulfonyl-Chloride-Modified Lignin-Based Porous Carbon-Supported Metal Phthalocyanine: Effect of Catalyst Concentrations.

A sulfonyl-chloride-modified lignin-based porous carbon-supported metal phthalocyanine catalyst was prepared and used to replace the traditional Fenton's reagent for lignin degradation. The catalyst underwent a detailed characterization analysis in terms of functional group distributions, surface area, morphological structure, via FT-IR, XPS, BET, and SEM. The catalyst possessed a specific surface area of 638.98 m2/g and a pore volume of 0.291 cm3/g. The prepared catalyst was studied for its ability of oxidative degradation of lignin under different reaction conditions. By optimizing the reaction conditions, a maximum liquid product yield of 38.94% was obtained at 135 °C with 3.5 wt% of catalyst and 15 × 10-2 mol/L H2O2; at the same time, a maximum phenols selectivity of 32.58% was achieved. The compositions and properties of liquid products obtained from lignin degradation using different catalyst concentrations were studied comparatively via GC-MS, FT-IR, 1H-NMR, and EA. Furthermore, the structure changes of solid residues are also discussed.

Identifying dynamical persistent biomarker structures for rare events using modern integrative machine learning approach.

The evolution of omics and computational competency has accelerated discoveries of the underlying biological processes in an unprecedented way. High throughput methodologies, such as flow cytometry, can reveal deeper insights into cell processes, thereby allowing opportunities for scientific discoveries related to health and diseases. However, working with cytometry data often imposes complex computational challenges due to high-dimensionality, large size, and nonlinearity of the data structure. In addition, cytometry data frequently exhibit diverse patterns across biomarkers and suffer from substantial class imbalances which can further complicate the problem. The existing methods of cytometry data analysis either predict cell population or perform feature selection. Through this study, we propose a "wisdom of the crowd" approach to simultaneously predict rare cell populations and perform feature selection by integrating a pool of modern machine learning (ML) algorithms. Given that our approach integrates superior performing ML models across different normalization techniques based on entropy and rank, our method can detect diverse patterns existing across the model features. Furthermore, the method identifies a dynamic biomarker structure that divides the features into persistently selected, unselected, and fluctuating assemblies indicating the role of each biomarker in rare cell prediction, which can subsequently aid in studies of disease progression.

Second Heart Field-Derived Cells Contribute to Angiotensin II-Mediated Ascending Aortopathies.

BACKGROUND: The ascending aorta is a common location for aneurysm and dissection. This aortic region is populated by a mosaic of medial and adventitial cells that are embryonically derived from either the second heart field (SHF) or the cardiac neural crest. SHF-derived cells populate areas that coincide with the spatial specificity of thoracic aortopathies. The purpose of this study was to determine whether and how SHF-derived cells contribute to ascending aortopathies. METHODS: Ascending aortic pathologies were examined in patients with sporadic thoracic aortopathies and angiotensin II (AngII)-infused mice. Ascending aortas without overt pathology from AngII-infused mice were subjected to mass spectrometry-assisted proteomics and molecular features of SHF-derived cells were determined by single-cell transcriptomic analyses. Genetic deletion of either Lrp1 (low-density lipoprotein receptor-related protein 1) or Tgfbr2 (transforming growth factor-ß receptor type 2) in SHF-derived cells was conducted to examine the effect of SHF-derived cells on vascular integrity. RESULTS: Pathologies in human ascending aortic aneurysmal tissues were predominant in outer medial layers and adventitia. This gradient was mimicked in mouse aortas after AngII infusion that was coincident with the distribution of SHF-derived cells. Proteomics indicated that brief AngII infusion before overt pathology occurred evoked downregulation of smooth muscle cell proteins and differential expression of extracellular matrix proteins, including several LRP1 ligands. LRP1 deletion in SHF-derived cells augmented AngII-induced ascending aortic aneurysm and rupture. Single-cell transcriptomic analysis revealed that brief AngII infusion decreased Lrp1 and Tgfbr2 mRNA abundance in SHF-derived cells and induced a unique fibroblast population with low abundance of Tgfbr2 mRNA. SHF-specific Tgfbr2 deletion led to embryonic lethality at E12.5 with dilatation of the outflow tract and retroperitoneal hemorrhage. Integration of proteomic and single-cell transcriptomics results identified PAI1 (plasminogen activator inhibitor 1) as the most increased protein in SHF-derived smooth muscle cells and fibroblasts during AngII infusion. Immunostaining revealed a transmural gradient of PAI1 in both ascending aortas of AngII-infused mice and human ascending aneurysmal aortas that mimicked the gradient of medial and adventitial pathologies. CONCLUSIONS: SHF-derived cells exert a critical role in maintaining vascular integrity through LRP1 and transforming growth factor-ß signaling associated with increases of aortic PAI1.

Accounting for total variation and robustness in profiling health care providers.

Monitoring outcomes of health care providers, such as patient deaths, hospitalizations, and hospital readmissions, helps in assessing the quality of health care. We consider a large database on patients being treated at dialysis facilities in the United States, and the problem of identifying facilities with outcomes that are better than or worse than expected. Analyses of such data have been commonly based on random or fixed facility effects, which have shortcomings that can lead to unfair assessments. A primary issue is that they do not appropriately account for variation between providers that is outside the providers' control due, for example, to unobserved patient characteristics that vary between providers. In this article, we propose a smoothed empirical null approach that accounts for the total variation and adapts to different provider sizes. The linear model provides an illustration that extends easily to other non-linear models for survival or binary outcomes, for example. The empirical null method is generalized to allow for some variation being due to quality of care. These methods are examined with numerical simulations and applied to the monitoring of survival in the dialysis facility data.

Influenza Epidemic Trend Surveillance and Prediction Based on Search Engine Data: Deep Learning Model Study.

BACKGROUND: Influenza outbreaks pose a significant threat to global public health. Traditional surveillance systems and simple algorithms often struggle to predict influenza outbreaks in an accurate and timely manner. Big data and modern technology have offered new modalities for disease surveillance and prediction. Influenza-like illness can serve as a valuable surveillance tool for emerging respiratory infectious diseases like influenza and COVID-19, especially when reported case data may not fully reflect the actual epidemic curve. OBJECTIVE: This study aimed to develop a predictive model for influenza outbreaks by combining Baidu search query data with traditional virological surveillance data. The goal was to improve early detection and preparedness for influenza outbreaks in both northern and southern China, providing evidence for supplementing modern intelligence epidemic surveillance methods. METHODS: We collected virological data from the National Influenza Surveillance Network and Baidu search query data from January 2011 to July 2018, totaling 3,691,865 and 1,563,361 respective samples. Relevant search terms related to influenza were identified and analyzed for their correlation with influenza-positive rates using Pearson correlation analysis. A distributed lag nonlinear model was used to assess the lag correlation of the search terms with influenza activity. Subsequently, a predictive model based on the gated recurrent unit and multiple attention mechanisms was developed to forecast the influenza-positive trend. RESULTS: This study revealed a high correlation between specific Baidu search terms and influenza-positive rates in both northern and southern China, except for 1 term. The search terms were categorized into 4 groups: essential facts on influenza, influenza symptoms, influenza treatment and medicine, and influenza prevention, all of which showed correlation with the influenza-positive rate. The influenza prevention and influenza symptom groups had a lag correlation of 1.4-3.2 and 5.0-8.0 days, respectively. The Baidu search terms could help predict the influenza-positive rate 14-22 days in advance in southern China but interfered with influenza surveillance in northern China. CONCLUSIONS: Complementing traditional disease surveillance systems with information from web-based data sources can aid in detecting warning signs of influenza outbreaks earlier. However, supplementation of modern surveillance with search engine information should be approached cautiously. This approach provides valuable insights for digital epidemiology and has the potential for broader application in respiratory infectious disease surveillance. Further research should explore the optimization and customization of search terms for different regions and languages to improve the accuracy of influenza prediction models.

Association between ambient sulfur dioxide pollution and asthma mortality: Evidence from a nationwide analysis in China.

There is a lack of research on the effects of acute exposure to ambient sulfur dioxide (SO2) on mortality caused by asthma, especially nationwide research in China. To explore the acute effect of exposure to ambient SO2 on asthma mortality using nationwide dataset in China from 2015 to 2020 and further evaluate the associations in subgroups with different geographical and demographic characteristics. We used data from China's Disease Surveillance Points system with 29,553 asthma deaths in China during 2015-2020. The exposure variable was the daily mean concentrations of SO2 from the ChinaHighSO2 10 km × 10 km daily grid dataset. Bilinear interpolation was used to estimate each individual's exposure to air pollutants and meteorological variables. We used a time-stratified case crossover design at the individual level to analyze the exposure response relationship between short-term exposure to SO2 and asthma mortality. Stratified analyses were carried out by sex, age group, marital status, warm season and cold season, urbanicity and region. Significant associations between short-term exposure to ambient SO2 and increased asthma mortality were found in this nationwide study. The excess risk (ER) for each 10 µg/m3 increase in SO2 concentrations at lag07 was 7.78 % (95 % CI, 4.16-11.52 %). Season appeared to significantly modify the association. The associations were stronger in cold season (ER 9.78 %, 95 % CI:5.82 -13.89 %). The association remained consistent using different lag periods, adjusting for other pollutants, and in the analysis during pre-Corona Virus Disease 2019 (COVID-19) period. Our study indicates increased risk of asthma mortality with acute exposures to SO2 in Chinese population. The current study lends support for greater awareness of the harmful effect of SO2 in China and other countries with high SO2 pollution.

Effect of moisture content, aeration rate, and C/N on maturity and gaseous emissions during kitchen waste rapid composting.

To determine factors affecting compost maturity and gaseous emissions during the rapid composting of kitchen waste, an orthogonal test was conducted with three factors: moisture content (MC) (55%, 60%, 65%), aeration rate (AR) (0.3,0.6 and 0.9 L·kg-1DM·min-1) and C/N ratio (21, 24, 27). The results showed that the importance of factors affecting compost maturity was: C/N > AR > MC, optimal conditions were: C/N of 24, AR of 0.3 L·kg-1DM·min-1and MC of 65%. For gaseous emissions, the sequence of essential factors affecting NH3 emissions was: C/N > MC > AR, and the optimal parameters for NH3 reduction were: C/N of 27, MC of 65%, and AR of L·kg-1DM·min-1. The important factors affecting N2O and H2S emissions are both: MC > C/N > AR, while their best parameters were different. The optimal parameters for N2O emission reduction were MC of 60%, AR of 0.3 L·kg-1DM·min-1 and C/N of 24, while these for H2S were MC of 55%, AR of 0.3 L·kg-1DM·min-1 and C/N of 21. The C/N mainly affected the compost maturity and AR further affected the maturity and pollutant gas emissions by influencing the temperature and O2 content. Considering comprehensively the maturity and gaseous reduction, the optimal control parameters were: MC of 60%-65%, AR of L·kg-1DM·min-1, and C/N of 24-27.

[MicroRNA-22-3p Regulates the Expression of Kruppel-like Factor 6 to Affect the Cardiomyocyte-like Differentiation of Bone Marrow Mesenchymal Stem Cell].

Objective To explore the effect of microRNA-22-3p (miR-22-3p) regulating the expression of Kruppel-like factor 6 (KLF6) on the cardiomyocyte-like differentiation of bone marrow mesenchymal stem cell (BMSC). Methods Rat BMSC was isolated and cultured,and the third-generation BMSC was divided into a control group,a 5-azacytidine(5-AZA)group,a mimics-NC group,a miR-22-3p mimics group,a miR-22-3p mimics+pcDNA group,and a miR-22-3p mimics+pcDNA-KLF6 group.Real-time fluorescent quantitative PCR (qRT-PCR) was carried out to determine the expression of miR-22-3p and KLF6 in cells.Immunofluorescence staining was employed to detect the expression of Desmin,cardiac troponin T (cTnT),and connexin 43 (Cx43).Western blotting was employed to determine the protein levels of cTnT,Cx43,Desmin,and KLF6,and flow cytometry to detect the apoptosis of BMSC.The targeting relationship between miR-22-3p and KLF6 was analyzed by dual luciferase reporter gene assay. Results Compared with the control group,5-AZA up-regulated the expression of miR-22-3p (q=7.971,P<0.001),Desmin (q=7.876,P<0.001),cTnT (q=10.272,P<0.001),and Cx43 (q=6.256,P<0.001),increased the apoptosis rate of BMSC (q=12.708,P<0.001),and down-regulated the mRNA (q=20.850,P<0.001) and protein (q=11.080,P<0.001) levels of KLF6.Compared with the 5-AZA group and the mimics-NC group,miR-22-3p mimics up-regulated the expression of miR-22-3p (q=3.591,P<0.001;q=11.650,P<0.001),Desmin (q=5.975,P<0.001;q=13.579,P<0.001),cTnT (q=7.133,P<0.001;q=17.548,P<0.001),and Cx43 (q=4.571,P=0.037;q=11.068,P<0.001),and down-regulated the mRNA (q=7.384,P<0.001;q=28.234,P<0.001) and protein (q=4.594,P=0.036;q=15.945,P<0.001) levels of KLF6.The apoptosis rate of miR-22-3p mimics group was lower than that of 5-AZA group (q=8.216,P<0.001).Compared with the miR-22-3p mimics+pcDNA group,miR-22-3p mimics+pcDNA-KLF6 up-regulated the mRNA(q=23.891,P<0.001) and protein(q=13.378,P<0.001)levels of KLF6,down-regulated the expression of Desmin (q=9.505,P<0.001),cTnT (q=10.985,P<0.001),and Cx43 (q=8.301,P<0.001),and increased the apoptosis rate (q=4.713,P=0.029).The dual luciferase reporter gene experiment demonstrated that KLF6 was a potential target gene of miR-22-3p. Conclusion MiR-22-3p promotes cardiomyocyte-like differentiation of BMSC by inhibiting the expression of KLF6.

Programmed cell death in aortic aneurysm and dissection: A potential therapeutic target.

Rupture of aortic aneurysm and dissection (AAD) remains a leading cause of death. Progressive smooth muscle cell (SMC) loss is a crucial feature of AAD that contributes to aortic dysfunction and degeneration, leading to aortic aneurysm, dissection, and, ultimately, rupture. Understanding the molecular mechanisms of SMC loss and identifying pathways that promote SMC death in AAD are critical for developing an effective pharmacologic therapy to prevent aortic destruction and disease progression. Cell death is controlled by programmed cell death pathways, including apoptosis, necroptosis, pyroptosis, and ferroptosis. Although these pathways share common stimuli and triggers, each type of programmed cell death has unique features and activation pathways. A growing body of evidence supports a critical role for programmed cell death in the pathogenesis of AAD, and inhibitors of various types of programmed cell death represent a promising therapeutic strategy. This review discusses the different types of programmed cell death pathways and their features, induction, contributions to AAD development, and therapeutic potential. We also highlight the clinical significance of programmed cell death for further studies.

A gene-level methylome-wide association analysis identifies novel Alzheimer's disease genes.

MOTIVATION: Transcriptome-wide association studies (TWAS) have successfully facilitated the discovery of novel genetic risk loci for many complex traits, including late-onset Alzheimer's disease (AD). However, most existing TWAS methods rely only on gene expression and ignore epigenetic modification (i.e., DNA methylation) and functional regulatory information (i.e., enhancer-promoter interactions), both of which contribute significantly to the genetic basis of AD. RESULTS: We develop a novel gene-level association testing method that integrates genetically regulated DNA methylation and enhancer-target gene pairs with genome-wide association study (GWAS) summary results. Through simulations, we show that our approach, referred to as the CMO (cross methylome omnibus) test, yielded well controlled type I error rates and achieved much higher statistical power than competing methods under a wide range of scenarios. Furthermore, compared with TWAS, CMO identified an average of 124% more associations when analyzing several brain imaging-related GWAS results. By analyzing to date the largest AD GWAS of 71,880 cases and 383,378 controls, CMO identified six novel loci for AD, which have been ignored by competing methods. AVAILABILITY: Software: https://github.com/ChongWuLab/CMO. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.