Combining association with linkage mapping to dissect the phenolamides metabolism of the maize kernel.

Phenolamides are important secondary metabolites in plant species. They play important roles in plant defense responses against pathogens and insect herbivores, protection against UV irradiation and floral induction and development. However, the accumulation and variation in phenolamides content in diverse maize lines and the genes responsible for their biosynthesis remain largely unknown. Here, we combined genetic mapping, protein regulatory network and bioinformatics analysis to further enhance the understanding of maize phenolamides biosynthesis. Sixteen phenolamides were identified in multiple populations, and they were all significantly correlated with one or several of 19 phenotypic traits. By linkage mapping, 58, 58, 39 and 67 QTLs, with an average of 3.9, 3.6, 3.6 and 4.2 QTLs for each trait were mapped in BBE1, BBE2, ZYE1 and ZYE2, explaining 9.47%, 10.78%, 9.51% and 11.40% phenotypic variation for each QTL on average, respectively. By GWAS, 39 and 36 significant loci were detected in two different environments, 3.3 and 2.8 loci for each trait, explaining 10.00% and 9.97% phenotypic variation for each locus on average, respectively. Totally, 58 unique candidate genes were identified, 31% of them encoding enzymes involved in amine and derivative metabolic processes. Gene Ontology term analysis of the 358 protein-protein interrelated genes revealed significant enrichment in terms relating to cellular nitrogen metabolism, amine metabolism. GRMZM2G066142, GRMZM2G066049, GRMZM2G165390 and GRMZM2G159587 were further validated involvement in phenolamides biosynthesis. Our results provide insights into the genetic basis of phenolamides biosynthesis in maize kernels, understanding phenolamides biosynthesis and its nutritional content and ability to withstand biotic and abiotic stress.

The effect of white grub (Maladera Verticalis) larvae feeding on rhizosphere microbial characterization of aerobic rice (Oryza sativa L.) in Puer City, Yunnan Province, China.

BACKGROUND: Rhizosphere microorganisms are vital in plants' growth and development and these beneficial microbes are recruited to the root-zone soil when experiencing various environmental stresses. However, the effect of white grub (Maladera verticalis) larvae feeding on the structure and function of rhizosphere microbial communities of aerobic rice (Oryza sativa L.) is unclear. RESULTS: In this study, we compared physicochemical properties, enzyme activities, and microbial communities using 18 samples under healthy and M. verticalis larvae-feeding aerobic rice rhizosphere soils at the Yunnan of China. 16 S rRNA and ITS amplicons were sequenced using Illumina high throughput sequencing. M. verticalis larvae feeding on aerobic rice can influence rhizosphere soil physicochemical properties and enzyme activities, which also change rhizosphere microbial communities. The healthy and M. verticalis larvae-feeding aerobic rice rhizosphere soil microorganisms had distinct genus signatures, such as possible_genus_04 and Knoellia genera in healthy aerobic rice rhizosphere soils and norank_f__SC - I-84 and norank_f__Roseiflexaceae genera in M. verticalis larvae-feeding aerobic rice rhizosphere soils. The pathway of the metabolism of terpenoids and polyketides and carbohydrate metabolism in rhizosphere bacteria were significantly decreased after M. verticalis larvae feeding. Fungal parasite-wood saprotroph and fungal parasites were significantly decreased after M. verticalis larvae feeding, and plant pathogen-wood saprotroph and animal pathogen-undefined saprotroph were increased after larvae feeding. Additionally, the relative abundance of Bradyrhizobium and Talaromyces genera gradually increased with the elevation of the larvae density. Bacterial and fungal communities significantly correlated with soil physicochemical properties and enzyme activities, respectively. CONCLUSIONS: Based on the results we provide new insight for understanding the adaptation of aerobic rice to M. verticalis larvae feeding via regulating the rhizosphere environment, which would allow us to facilitate translation to more effective measures.

Population pharmacokinetic model for oral ORIN1001 in Chinese patients with advanced solid tumors.

Background: ORIN1001, a first-in-class oral IRE1-α endoribonuclease inhibitor to block the activation of XBP1, is currently in clinical development for inhibiting tumor growth and enhancing the effect of chemical or targeted therapy. Early establishment of a population pharmacokinetic (PopPK) model could characterize the pharmacokinetics (PK) of ORIN1001 and evaluate the effects of individual-specific factors on PK, which will facilitate the future development of this investigational drug. Methods: Non-linear mixed effect model was constructed by Phoenix NLME software, utilizing the information from Chinese patients with advanced solid tumors in a phase I clinical trial (Register No. NCT05154201). Statistically significant PK covariates were screened out by a stepwise process. The final model, after validating by the goodness-of-fit plots, non-parametric bootstrap, visual predictive check and test of normalized prediction distribution errors, was further applied to simulate and evaluate the impact of covariates on ORIN1001 exposure at steady state up to 900 mg per day as a single agent. Results: A two-compartment model with first-order absorption (with lag-time)/elimination was selected as the best structural model. Total bilirubin (TBIL) and lean body weight (LBW) were considered as the statistically significant covariates on clearance (CL/F) of ORIN1001. They were also confirmed to exert clinically significant effects on ORIN1001 steady-state exposure after model simulation. The necessity of dose adjustments based on these two covariates remains to be validated in a larger population. Conclusion: The first PopPK model of ORIN1001 was successfully constructed, which may provide some important references for future research.

Targeting the IRE1α-XBP1s axis confers selective vulnerability in hepatocellular carcinoma with activated Wnt signaling.

Liver-specific Ern1 knockout impairs tumor progression in mouse models of hepatocellular carcinoma (HCC). However, the mechanistic role of IRE1α in human HCC remains unclear. In this study, we show that XBP1s, the major downstream effector of IRE1α, is required for HCC cell survival both in vitro and in vivo. Mechanistically, XBP1s transactivates LEF1, a key co-factor of ß-catenin, by binding to its promoter. Moreover, XBP1s physically interacts with LEF1, forming a transcriptional complex that enhances classical Wnt signaling. Consistently, the activities of XBP1s and LEF1 are strongly correlated in human HCC and with disease prognosis. Notably, selective inhibition of XBP1 splicing using an IRE1α inhibitor significantly repressed the viability of tumor explants as well as the growth of tumor xenografts derived from patients with distinct Wnt/LEF1 activities. Finally, machine learning algorithms developed a powerful prognostic signature based on the activities of XBP1s/LEF1. In summary, our study uncovers a key mechanistic role for the IRE1α-XBP1s pathway in human HCC. Targeting this axis could provide a promising therapeutic strategy for HCC with hyperactivated Wnt/LEF1 signaling.

Machine Learning-Based Clinical Prediction Models for Acute Ischemic Stroke Based on Serum Xanthine Oxidase Levels.

OBJECTIVE: Early prediction of the onset, progression and prognosis of acute ischemic stroke (AIS) is helpful for treatment decision-making and proactive management. Although several biomarkers have been found to predict the progression and prognosis of AIS, these biomarkers have not been widely used in routine clinical practice. Xanthine oxidase (XO) is a form of xanthine oxidoreductase (XOR), which is widespread in various organs of the human body and plays an important role in redox reactions and ischemia‒reperfusion injury. Our previous studies have shown that serum XO levels on admission have certain clinical predictive value for AIS. The purpose of this study was to utilize serum XO levels and clinical data to establish machine learning models for predicting the onset, progression, and prognosis of AIS. METHODS: We enrolled 328 consecutive patients with AIS and 107 healthy controls from October 2020 to September 2021. Serum XO levels and stroke-related clinical data were collected. We established 5 machine learning models-the logistic regression (LR), support vector machine (SVM), decision tree, random forest, and K-nearest neighbor (KNN) models-to predict the onset, progression, and prognosis of AIS. The area under the receiver operating characteristic curve (AUROC), accuracy, sensitivity, specificity, negative predictive value, and positive predictive value were used to evaluate the predictive performance of each model. RESULTS: Among the 5 machine learning models predicting AIS onset, the AUROC values of 4 prediction models were over 0.7, while that of the KNN model was lower (AUROC = 0.6708, 95% CI 0.576-0.765). The LR model showed the best AUROC value (AUROC = 0.9586, 95% CI 0.927-0.991). Although the 5 machine learning models showed relatively poor predictive value for the progression of AIS (all AUROCs <0.7), the LR model still showed the highest AUROC value (AUROC = 0.6543, 95% CI 0.453-0.856). We compared the value of 5 machine learning models in predicting the prognosis of AIS, and the LR model showed the best predictive value (AUROC = 0.8124, 95% CI 0.715-0.910). CONCLUSIONS: The tested machine learning models based on serum levels of XO could predict the onset and prognosis of AIS. Among the 5 machine learning models, we found that the LR model showed the best predictive performance. Machine learning algorithms improve accuracy in the early diagnosis of AIS and can be used to make treatment decisions.

Prevalence, characteristics, and risk factors of venous thromboembolism in patients with brain tumor undergoing craniotomy: a meta-analysis.

BACKGROUND: Brain tumor patients undergoing craniotomy are significantly associated with the development of venous thromboembolism (VTE), while the contributing factors remains controversial. Our study aimed to investigate the prevalence and risk factors for VTE in postoperational brain tumor patients. METHODS: We searched the PubMed, Embase, Web of Science, Medline, and Cochrane Library databases from their inception to July 2023. Article selection, data extraction, and study quality assessment were performed independently by two reviewers. Publication bias was assessed using Egger's and Begg's tests. Stata 15.0 software was used for data analysis. RESULTS: A total of 25 studies were considered, with a total of 49,620 brain tumor individuals. The pooled prevalence of VTE during hospitalization in postoperational brain tumor patients was 9% [95% CI: (0.08, 0.10)]. Moreover, our results demonstrated that patients with VTE were older than those without VTE [mean difference [MD] = 8.14, 95% CI: (4.97, 11.30)]. The following variables were significantly associated with VTE: prior history of VTE [OR = 7.81, 95% CI: (3.62, 16.88)], congestive heart failure [OR = 2.33, 95% CI: (1.08-5.05)], diabetes [OR = 1.87, 95% CI: (1.12-3.10)], hypertension [OR = 1.27, 95% CI: (1.07-1.50)], steroid use [OR = 1.63, 95% CI: (1.41, 1.88)], high white blood cells counts [MD = 0.32, 95% CI: (0.01, 0.63)], and high fibrinogen levels [MD = 0.19, 95% CI: (0.08, 0.30)]. CONCLUSION: This meta-analysis identified risk factors for postoperational VTE in patients with brain tumor, which can serve as a theoretical foundation for medical staff to manage and treat VTE. TRIAL REGISTRATION: CRD42023357459.

Development and application of a nomogram model for the prediction of carbapenem-resistant Klebsiella pneumoniae infection in neuro-ICU patients.

IMPORTANCE: Patients in neuro-ICU are at a high risk of developing nosocomial CRKP infection owing to complex conditions, critical illness, and frequent invasive procedures. However, studies focused on constructing prediction models for assessing the risk of CRKP infection in neurocritically ill patients are lacking at present. Therefore, this study aims to establish a simple-to-use nomogram for predicting the risk of CRKP infection in patients admitted to the neuro-ICU. Three easily accessed variables were included in the model, including the number of antibiotics used, surgery, and the length of neuro-ICU stay. This nomogram might serve as a useful tool to facilitate early detection and reduction of the CRKP infection risk of neurocritically ill patients.

Prediction Models for Dysphagia in Intensive Care Unit after Mechanical Ventilation: A Systematic Review and Meta-analysis.

OBJECTIVE: Dysphagia is a common condition that can independently lead to death in patients in the intensive care unit (ICU), particularly those who require mechanical ventilation. Despite extensive research on the predictors of dysphagia development, consistency across these studies is lacking. Therefore, this study aimed to identify predictors and summarize existing prediction models for dysphagia in ICU patients undergoing invasive mechanical ventilation. METHODS: We searched five databases: PubMed, EMBASE, Web of Science, Cochrane Library, and the China National Knowledge Infrastructure. Studies that developed a post-extubation dysphagia risk prediction model in ICU were included. A meta-analysis of individual predictor variables was performed with mixed-effects models. The risk of bias was assessed using the prediction model risk of bias assessment tool (PROBAST). RESULTS: After screening 1,923 references, we ultimately included nine studies in our analysis. The most commonly identified risk predictors included in the final risk prediction model were the length of indwelling endotracheal tube ≥72 h, Acute Physiology and Chronic Health Evaluation (APACHE) II score ≥15, age ≥65 years, and duration of gastric tube ≥72 h. However, PROBAST analysis revealed a high risk of bias in the performance of these prediction models, mainly because of the lack of external validation, inadequate pre-screening of variables, and improper treatment of continuous and categorical predictors. CONCLUSIONS: These models are particularly susceptible to bias because of numerous limitations in their development and inadequate external validation. Future research should focus on externally validating the existing model in ICU patients with varying characteristics. Moreover, assessing the acceptance and effectiveness of the model in clinical practice is needed. LEVEL OF EVIDENCE: NA Laryngoscope, 134:517-525, 2024.

Validation of COPD Population Screener Questionnaire in Chinese Population: A National Multicenter Study.

INTRODUCTION: Chronic obstructive pulmonary disease (COPD) is highly prevalent and underdiagnosed worldwide. The validity and reliability of COPD Population Screening (COPD-PS) questionnaire are not properly known in a large-sample Chinese population. METHODS: This is a national multicenter prospective study that enrolled 1,824 outpatients from 12 hospital sites in China. Scores of the Chinese version of COPD-PS questionnaire, demographic data, and clinical information were collected. The validity and the test-retest reliability were evaluated. RESULTS: 1,824 participants were involved in this study, and 404 (22.1%) were diagnosed with COPD. The overall area under the curve (AUC) of the receiver operating characteristic (ROC) for COPD-PS questionnaire was 0.761 (95% CI: 0.734-0.787). A cut-off point of 4 was recommended, corresponding to a sensitivity of 74.50% and a specificity of 64.37%. The COPD-PS questionnaire showed an overall Pearson's correlation of 0.88. CONCLUSIONS: The COPD-PS questionnaire can be used in screening COPD patients from the general Chinese population with respiratory symptoms.

Inhibition of METTL3 alleviated LPS-induced alveolar epithelial cell apoptosis and acute lung injury via restoring neprilysin expression.

AIMS: To investigate the role and mechanisms of methyltransferase-like 3 (METTL3) in the pathogenesis of lipopolysaccharide (LPS)-induced acute lung injury (ALI). MAIN METHODS: LPS intratracheally instillation was applied in alveolar epithelial cell METTL3 conditional knockout (METTL3-CKO) mice and their wild-type littermates. In addition, METTL3 inhibitor STM2457 was used. LPS treatment on mouse lung epithelial 12 (MLE-12) cell was applied to establish an in vitro model of LPS-induced ALI. H&E staining, lung wet-to-dry ratio, and total broncho-alveolar lavage fluid (BALF) concentrations were used to evaluate lung injury. Overall, the m6A level was determined with the m6A RNA Methylation Quantification Kit and dot blot assay. Expression of METTL3 and neprilysin were measured with immunohistochemistry, immunofluorescence, immunofluorescence-fluorescence in situ hybridization, and western blot. Apoptosis was detected with TUNEL, western blot, and flow cytometry. The interaction of METTL3 and neprilysin was determined with RIP-qPCR and MeRIP. KEY FINDINGS: METTL3 expression and apoptosis were increased in alveolar epithelial cells of mice treated with LPS, and METTL3-CKO or METTL3 inhibitor STM2457 could alleviate apoptosis and LPS-induced ALI. In MLE-12 cells, LPS-Induced METTL3 expression and apoptosis. Knockdown of METTL3 alleviated, while overexpression of METTL3 exacerbated LPS-induced apoptosis. LPS treatment reduced neprilysin expression, the intervention of neprilysin expression negatively regulated apoptosis without affecting METTL3 expression, and mitigated the promoting effect of METTL3 on LPS-induced apoptosis. Additionally, METTL3 could bind to the mRNA of neprilysin, and reduce its expression. SIGNIFICANCE: Our findings revealed that inhibition of METTL3 could exert anti-apoptosis and ALI-protective effects via restoring neprilysin expression.

miR-146a-3p as a potential novel therapeutic by targeting MBD2 to mediate Th17 differentiation in Th17 predominant neutrophilic severe asthma.

Th17 (T-helper 17) cells subtype of non-T2 (non-type 2) asthma is related to neutrophilic infiltration and resistance to inhaled corticosteroids (ICS), so is also known as severe asthma. Methyl-CpG binding domain protein 2 (MBD2) regulates the differentiation of the Th17 cells, tending to show a therapeutic target in severe asthma. miR-146a-3p is associated with anti-inflammatory characteristics and immunity. Moreover, bioinformatic analysis showed that MBD2 may be a target gene of miR-146a-3p. However, the role of miR-146a-3p in the differentiation of Th17 cells via MBD2 in severe asthma remains unknown. Here, we aimed to explore how miR-146a-3p interacts with MBD2 and affects the differentiation of Th17 cells in severe asthma. First, we recruited 30 eligible healthy people and 30 patients with severe asthma to detect the expression of miR-146a-3p in peripheral blood mononuclear cells (PBMCs) by qRT-PCR. Then, we established a HDM/LPS (house dust mite/lipopolysaccharide) exposure model of bronchial epithelial cells (BECs) to evaluate the expression of miR-146a-3p, the interaction between miR-146a-3p and MBD2 using western blot and luciferase reporter analysis and the effect of miR-146a-3p regulated Th17 cells differentiation by flow cytometry in BECs in vitro. Finally, we constructed a mouse model of Th17 predominant neutrophilic severe asthma to assess the therapeutic potential of miR-146a-3p in severe asthma and the effect of miR-146a-3p regulated Th17 cells differentiation via MBD2 in vivo. Decreased miR-146a-3p expression was noted in severe asthma patients, in the BECs and in the animal severe asthma models. Moreover, we demonstrated that miR-146a-3p suppressed Th17 cells differentiation by targeting the MBD2. miR-146a-3p overexpression significantly reduced airway hyperresponsiveness, airway inflammation and airway mucus secretion, while also inhibiting Th17 cells response in vivo, which relieved severe asthma. By targeting MBD2 to suppress Th17 cells differentiation, miR-146a-3p provides a potential novel therapeutic for Th17 predominant neutrophilic severe asthma.

lncRNA CRNDE Affects Th17/IL-17A and Inhibits Epithelial-Mesenchymal Transition in Lung Epithelial Cells Reducing Asthma Signs.

Background: Asthma treatment is difficult due to disease heterogeneity and comorbidities. In addition, the development of drugs targeting the underlying mechanisms of asthma remains slow. We planned to identify the most upregulated differentially expressed long noncoding RNA in asthma to explore its regulatory patterns and pathways in asthma. Methods: We sensitized mice using a mixture of ovalbumin, house dust mites, and lipopolysaccharide to establish an asthma mouse model. We also sensitized asthma cells with TGF-ß1 in an in vitro model. We performed a microarray analysis to identify the lncRNA with the differential expression level in model mice. We applied hematoxylin and eosin and Masson's trichrome stainings to mouse tissues to quantify the tissue damage extent. Next, we assess the levels of lncRNA CRNDE, miR-29a-3p, TGF-ß1, MCL-1, E-cadherin, vimentin, and snail. We counted the percentages of Th17 cells using flow cytometry. Finally, we performed a dual-luciferase reporter assay to assess the association between lncRNA CRNDE and miR-29a-3p. Results: We successfully established asthma mouse/cell models and selected the lncRNA CRNDE for our study. Transfection of si-CRNDE reduced the degree of injury and inflammation in the mouse model and reversed the TGF-ß1-induced epithelial-mesenchymal transition (EMT) in the cell model. Moreover, the E-cadherin level was upregulated, and the levels of IL-17A, vimentin, snail, and α-SMA were downregulated. We also discovered that lncRNA CRNDE negatively regulated miR-29a-3p and that this one in turn inhibited MCL-1 in mice. After lncRNA CRNDE expression downregulation, the level of miR-29a-3p was increased, and we detected reduced levels of MCL-1 and EMTs. Conclusions: lncRNA CRNDE expression downregulation led to reduced inflammation and reduced lung damage in mice with induced asthma, it inhibited the EMTs of lung epithelial cells via the miR-29a-3p/MCL-1 pathway, and it reduced the levels of Th17/IL-17A cells to reduce asthma signs.

Different clinical characteristics of current smokers and former smokers with asthma: a cross-sectional study of adult asthma patients in China.

Smoking is a trigger for asthma, which has led to an increase in asthma incidence in China. In smokers, asthma management starts with smoking cessation. Data on predictors of smoking cessation in Chinese patients with asthma are scarce. The objective of this study was to find the differences in clinical characteristics between current smokers and former smokers with asthma in order to identify factors associated with smoking cessation. Eligible adults with diagnosed asthma and smoking from the hospital outpatient clinics (n = 2312) were enrolled and underwent a clinical evaluation, asthma control test (ACT), and pulmonary function test. Information on demographic and sociological data, lung function, laboratory tests, ACT and asthma control questionnaire (ACQ) scores was recorded. Patients were divided into a current smokers group and a former smokers group based on whether they had quit smoking. Logistic regression analysis was used to analyze the factors associated with smoking cessation. Of all patients with asthma, 34.6% were smokers and 65.4% were former smokers, and the mean age was 54.5 ± 11.5 years. Compared with current smokers, the former smokers were older, had longer duration of asthma, had higher ICS dose, had more partially controlled and uncontrolled asthma, had more pack-years, had smoked for longer, and had worse asthma control. The logistic regression model showed that smoking cessation was positively correlated with age, female sex, pack-years, years of smoking, partially controlled asthma, uncontrolled asthma, and body mass index (BMI), but was negatively correlated with ACT, FEV1, FEV1%predicted, and widowed status. More than 30% of asthma patients in the study were still smoking. Among those who quit smoking, many quit late, often not realizing they need to quit until they have significant breathing difficulties. The related factors of smoking cessation identified in this study indicate that there are still differences between continuing smokers and former smokers, and these factors should be focused on in asthma smoking cessation interventions to improve the prognosis of patients with asthma.

Prediction of Catheter-Associated Urinary Tract Infections Among Neurosurgical Intensive Care Patients: A Decision Tree Analysis.

BACKGROUND: Catheter-associated urinary tract infections (CAUTIs) are the most common device-associated infections in hospitals and can be prevented. To identify the risk factors and develop a risk prediction model for CAUTIs among neurosurgical intensive care unit (NICU) patients. METHODS: All patients admitted to the NICU of a tertiary hospital between January 2019 and January 2020 were enrolled. Two decision tree models were applied to analyze the risk factors associated with CAUTIs in NICU patients. The performance of the decision tree model was evaluated. RESULTS: A total of 537 patients admitted to the NICU with indwelling catheters were recruited for this study. The rate of CAUTIs was 4.44 per 1000 catheter days, and Escherichia coli was the predominant pathogen causing CAUTIs among indwelling catheter patients. The classification and regression tree model displayed good power of prediction (area under the curve : 0.920). Nine CAUTI risk factors (age ≥60 years (P = 0.004), Glasgow Coma Scale score ≤8 (P = 0.009), epilepsy at admission (P = 0.007), admission to the hospital during the summer (P < 0.001), ventilators use (P = 0.007), receiving less than 2 types of antibiotics (P < 0.001), albumin level <35 g/L (P = 0.002), female gender (P = 0.002), and having an indwelling catheter for 7-14 days (P = 0.001) were also identified. CONCLUSION: We developed a novel scoring model for predicting the risk of CAUTIs in patients with neuro-critical illness in daily clinical practice. This model identified several risk factors for CAUTI among NICU patients, novel factors including epilepsy and admission during the summer, can be used to help providers prevent and reduce the risk of CAUTI among vulnerable groups.

Association between subjective cognitive complaints, balance impairment and disability among middle-aged and older adults: Evidence from a population-based cohort study.

AIM: To quantify the association between subjective cognitive complaints and balance impairment in relation to the occurrence of disability. METHODS: In total, 6885 adults aged ≥45 who participated in the China Health and Retirement Longitudinal Study (CHARLS) were followed for 7 years. Subjective cognitive complaints were evaluated by self-reported memory problems. Balance impairment was tested by side-by-side stand, semi-tandem stand and full tandem stand. Disability was measured by activities of daily living (ADL) and instrumental activities of daily living (IADL). Multivariate logistic regression models were applied to test the joint effect between baseline subjective cognitive complaints and balance impairment on disability. The multiplicative interaction was examined. RESULTS: A joint effect of experiencing both subjective cognitive complaints and balance impairment was identified, showing a 1.63-fold higher risk of ADL and IADL disability than those experienced by neither of the two (odds ratio = 1.63, 95% confidence interval: 1.36-1.95). There was evidence of multiplicative interaction (P = 0.004). CONCLUSIONS: Among middle-aged and older people, the coexistence of subjective cognitive complaints and balance impairment may lead to a higher disability risk, which is much higher than the simple sum of the two individual effects. Future interventions are required to target these symptoms simultaneously to reduce the risks of disability. Geriatr Gerontol Int 2022; 22: 1025-1031.

MBD2 mediates Th17 cell differentiation by regulating MINK1 in Th17-dominant asthma.

Objectives: .Asthma is a highly heterogeneous disease, and T-helper cell type 17 (Th17) cells play a pathogenic role in the development of non-T2 severe asthma. Misshapen like kinase 1 (MINK1) is involved in the regulation of Th17 cell differentiation, but its effect on severe asthma remains unclear. Our previous studies showed that methyl-CpG binding domain protein 2 (MBD2) expression was significantly increased in patients with Th17 severe asthma and could regulate Th17 cell differentiation. The aim of this study was to investigate how MBD2 interacts with MINK1 to regulate Th17 cell differentiation in Th17-dominant asthma. Materials and methods: Female C57BL/6 mice and bronchial epithelial cells (BECs) were used to establish mouse and cell models of Th17-dominant asthma, respectively. Flow cytometry was used to detect Th17 cell differentiation, and the level of IL-17 was detected by enzyme-linked immunosorbent assay (ELISA). Western blot and quantitative real-time PCR (qRT-PCR) were used to detect MBD2 and MINK1 expression. To investigate the role of MBD2 and MINK1 in Th17 cell differentiation in Th17-dominant asthma, the MBD2 and MINK1 genes were silenced or overexpressed by small interfering RNA and plasmid transfection. Results: Mouse and BEC models of Th17-dominant asthma were established successfully. The main manifestations were increased neutrophils in BALF, airway hyperresponsiveness (AHR), activated Th17 cell differentiation, and high IL-17 levels. The expression of MBD2 in lung tissues and BECs from the Th17-dominant asthma group was significantly increased, while the corresponding expression of MINK1 was significantly impaired. Through overexpression or silencing of MBD2 and MINK1 genes, we have concluded that MBD2 and MINK1 regulate Th17 cell differentiation and IL-17 release. Interestingly, MBD2 was also found to negatively regulate the expression of MINK1. Conclusion: Our findings have revealed new roles for MBD2 and MINK1, and provide new insights into epigenetic regulation of Th17-dominant asthma, which is dominated by neutrophils and Th17 cells. This study could lead to new therapeutic targets for patients with Th17-dominant asthma.

Regenerated Silk Nanofibers for Robust and Cyclic Adsorption-Desorption on Anionic Dyes.

In recent years, adsorption-based membranes have been widely investigated to remove and separate textile pollutants. However, cyclic adsorption-desorption to reuse a single adsorbent and clear scientific evidence for the adsorption-desorption mechanism remains challenging. Herein, silk nanofibers were used to assess the adsorption potential for the typical anionic dyes from an aqueous medium, and they show great potential toward the removal of acid dyes from the aqueous solution with an adsorption rate of ∼98% in a 1 min interaction. Further, we measured the filtration proficiency of a silk nanofiber membrane in order to propose a continuous mechanism for the removal of acid blue dye, and a complete rejection was observed with a maximum permeability rate of ∼360 ± 5 L·m-2·h-1. The Fourier transform infrared spectroscopy and X-ray photoelectron spectroscopy studies demonstrate that this fast adsorption occurs due to multiple interactions between the dye molecule and the adsorbent substrate. The as-prepared material also shows remarkable results in desorption. A 50-time cycle exhibits complete adsorption and desorption ability, which not only facilitates high removal aptitude but also produces less solid waste than other conventional adsorbents. Additionally, fluorescent 2-bromo-2-methyl-propionic acid (abbreviated as EtOxPY)-silk nanofibers can facilitate to illustrate a clear adsorption and desorption mechanism. Therefore, the above-prescribed results make electrospun silk nanofibers a suitable choice for removing anionic dyes in real-time applications.

The association between healthy aging index and trajectories of disability: a population-based cohort study.

BACKGROUND: Healthy aging index (HAI) could predict adverse health consequences including mortality and disability independent of age and comorbidity. We investigated the role of HAI on trajectories of disability throughout later life based on a nationally representative sample. METHODS: We examined 1733 participants aged over 60 years from the China Health and Retirement Longitudinal Study (CHARLS) followed for 7 years/4 waves repeatedly. Systolic blood pressure [SBP], cognitive function, cystatin C, peak expiratory flow [PEF], and fasting glucose were categorized using tertile or clinical reference range, and scored as 0 (healthiest), 1 (less healthy) and 2 (least healthy) respectively to further generate HAI summary scores (range 0-10). Disability was defined as the sum of impaired activities of daily living (ADL) and instrumental activities of daily living (IADL). We used linear mixed-effects model to study the association between HAI and trajectories of disability. RESULTS: A total of 10.5% of participants represented in the healthiest group and 22.5% ended up as the least healthy. After adjusting for all potential confounders, disability progression was significantly faster (ß = 0.27, 95% CI 0.11-0.42) in the least healthy group when comparing with the healthiest. CONCLUSION: Our findings suggest that HAI is associated with disability progression among adults aged over 60 years old. It might be beneficial for future interventions to specifically target older adults with high HAI scores as a means of reducing disability.

Inhibiting the IRE1α Axis of the Unfolded Protein Response Enhances the Antitumor Effect of AZD1775 in TP53 Mutant Ovarian Cancer.

Targeting the G2/M checkpoint mediator WEE1 has been explored as a novel treatment strategy in ovarian cancer, but mechanisms underlying its efficacy and resistance remains to be understood. Here, it is demonstrated that the WEE1 inhibitor AZD1775 induces endoplasmic reticulum stress and activates the protein kinase RNA-like ER kinase (PERK) and inositol-required enzyme 1α (IRE1α) branches of the unfolded protein response (UPR) in TP53 mutant (mtTP53) ovarian cancer models. This is facilitated through NF-κB mediated senescence-associated secretory phenotype. Upon AZD1775 treatment, activated PERK promotes apoptotic signaling via C/EBP-homologous protein (CHOP), while IRE1α-induced splicing of XBP1 (XBP1s) maintains cell survival by repressing apoptosis. This leads to an encouraging synergistic antitumor effect of combining AZD1775 and an IRE1α inhibitor MKC8866 in multiple cell lines and preclinical models of ovarian cancers. Taken together, the data reveal an important dual role of the UPR signaling network in mtTP53 ovarian cancer models in response to AZD1775 and suggest that inhibition of the IRE1α-XBP1s pathway may enhance the efficacy of AZD1775 in the clinics.

MBD2 as a Potential Novel Biomarker for Identifying Severe Asthma With Different Endotypes.

Background: Studies have shown that methyl-CpG binding domain protein 2 (MBD2) expression is significantly elevated in a neutrophil-dominant severe asthma mouse model. It also regulates Th17 cell differentiation. The objective of this study was to investigate the relationship between serum MBD2 levels in patients with severe asthma with different endotypes. Methods: Eligible adults with confirmed asthma (n = 63) underwent a clinical assessment, asthma control test and pulmonary function test and were classified as having mild, moderate or severe asthma. Severe asthma endotypes were defined according to the percentage of Th2 and Th17 cells in the peripheral blood and by the type of inflammation. The percentage of Th2 and Th17 cells in the peripheral blood was determined by flow cytometry. Serum MBD2, eosinophilic cationic protein and myeloperoxidase were measured by enzyme-linked immunosorbent assay. Correlations of MBD2 expression with clinical parameters were evaluated using Spearman's rank correlation analysis. Results: Serum MBD2 levels were upregulated in patients with severe asthma compared to healthy controls and patients with mild to moderate asthma. MBD2 was also significantly increased in patients with Th17 severe asthma compared to patients with type 2 severe asthma. Furthermore, MBD2 was positively correlated with MPO and Th17 cells but negatively correlated with ECP and Th2 cells in patients with severe asthma. Conclusions: These findings suggest that serum MBD2 may be a potential new biomarker for identifying severe asthma, Th17 severe asthma and the type of airway inflammation. However, these findings are still preliminary and need to be further investigated.