Shared genetic aetiology of Alzheimer's disease and age-related macular degeneration by APOC1 and APOE genes.

Background: Alzheimer's disease (AD) and age-related macular degeneration (AMD) share similar pathological features, suggesting common genetic aetiologies between the two. Investigating gene associations between AD and AMD may provide useful insights into the underlying pathogenesis and inform integrated prevention and treatment for both diseases. Methods: A stratified quantile-quantile (QQ) plot was constructed to detect the pleiotropy among AD and AMD based on genome-wide association studies data from 17 008 patients with AD and 30 178 patients with AMD. A Bayesian conditional false discovery rate-based (cFDR) method was used to identify pleiotropic genes. UK Biobank was used to verify the pleiotropy analysis. Biological network and enrichment analysis were conducted to explain the biological reason for pleiotropy phenomena. A diagnostic test based on gene expression data was used to predict biomarkers for AD and AMD based on pleiotropic genes and their regulators. Results: Significant pleiotropy was found between AD and AMD (significant leftward shift on QQ plots). APOC1 and APOE were identified as pleiotropic genes for AD-AMD (cFDR <0.01). Network analysis revealed that APOC1 and APOE occupied borderline positions on the gene co-expression networks. Both APOC1 and APOE genes were enriched on the herpes simplex virus 1 infection pathway. Further, machine learning-based diagnostic tests identified that APOC1, APOE (areas under the curve (AUCs) >0.65) and their upstream regulators, especially ZNF131, ADNP2 and HINFP, could be potential biomarkers for both AD and AMD (AUCs >0.8). Conclusion: In this study, we confirmed the genetic pleiotropy between AD and AMD and identified APOC1 and APOE as pleiotropic genes. Further, the integration of multiomics data identified ZNF131, ADNP2 and HINFP as novel diagnostic biomarkers for AD and AMD.

Heterogeneous effects of hospital competition on inpatient quality: an analysis of five common diseases in China.

BACKGROUND: Many countries has introduced pro-competition policies in the delivery of healthcare to improve medical quality, including China. With the increasing intensity of competition in China's healthcare market, there are rising concerns among policymakers about the impact of hospital competition on quality. This study investigated heterogeneous effects of hospital competition on inpatient quality. METHODS: We analyzed the inpatient discharge dataset and selected chronic obstructive pulmonary disease (COPD), ischemic stroke, pneumonia, hemorrhagic stroke, and acute myocardial infarction (AMI) as representative diseases. A total of 561,429 patients in Sichuan Province in 2017 and 2019 were included. The outcomes of interest were in-hospital mortality and 30-day unplanned readmissions. The Herfindahl-Hirschman Index was calculated using predicted patient flows to measure hospital competition. To address the spatial correlations of hospitals and the structure of the dataset, the multiple membership multiple classification model was employed for analysis. RESULTS: Amid intensifying competition in the hospital market, our study discerned no marked statistical variance in the risk of inpatient quality across most diseases examined. Amplified competition exhibited a positive correlation with heightened in-hospital mortality for both COPD and pneumonia patients. Elevated competition escalated the risk of 30-day unplanned readmissions for COPD patients, while inversely affecting the risk for AMI patients. CONCLUSIONS: There is the heterogeneous impact of hospital competition on quality across various diseases in China. Policymakers who intend to leverage hospital competition as a tool to enhance healthcare quality must be cognizant of the possible influences of it.

Exploring deep learning radiomics for classifying osteoporotic vertebral fractures in X-ray images.

Purpose: To develop and validate a deep learning radiomics (DLR) model that uses X-ray images to predict the classification of osteoporotic vertebral fractures (OVFs). Material and methods: The study encompassed a cohort of 942 patients, involving examinations of 1076 vertebrae through X-ray, CT, and MRI across three distinct hospitals. The OVFs were categorized as class 0, 1, or 2 based on the Assessment System of Thoracolumbar Osteoporotic Fracture. The dataset was divided randomly into four distinct subsets: a training set comprising 712 samples, an internal validation set with 178 samples, an external validation set containing 111 samples, and a prospective validation set consisting of 75 samples. The ResNet-50 architectural model was used to implement deep transfer learning (DTL), undergoing -pre-training separately on the RadImageNet and ImageNet datasets. Features from DTL and radiomics were extracted and integrated using X-ray images. The optimal fusion feature model was identified through least absolute shrinkage and selection operator logistic regression. Evaluation of the predictive capabilities for OVFs classification involved eight machine learning models, assessed through receiver operating characteristic curves employing the "One-vs-Rest" strategy. The Delong test was applied to compare the predictive performance of the superior RadImageNet model against the ImageNet model. Results: Following pre-training separately on RadImageNet and ImageNet datasets, feature selection and fusion yielded 17 and 12 fusion features, respectively. Logistic regression emerged as the optimal machine learning algorithm for both DLR models. Across the training set, internal validation set, external validation set, and prospective validation set, the macro-average Area Under the Curve (AUC) based on the RadImageNet dataset surpassed those based on the ImageNet dataset, with statistically significant differences observed (P<0.05). Utilizing the binary "One-vs-Rest" strategy, the model based on the RadImageNet dataset demonstrated superior efficacy in predicting Class 0, achieving an AUC of 0.969 and accuracy of 0.863. Predicting Class 1 yielded an AUC of 0.945 and accuracy of 0.875, while for Class 2, the AUC and accuracy were 0.809 and 0.692, respectively. Conclusion: The DLR model, based on the RadImageNet dataset, outperformed the ImageNet model in predicting the classification of OVFs, with generalizability confirmed in the prospective validation set.

Epidemiologic association and shared genetic architecture between cataract and hearing difficulties among middle-aged and older adults.

Age-related cataract and hearing difficulties are major sensory disorders that often co-exist in the global-wide elderly and have a tangible influence on the quality of life. However, the epidemiologic association between cataract and hearing difficulties remains unexplored, while little is known about whether the two share their genetic etiology. We first investigated the clinical association between cataract and hearing difficulties using the UK Biobank covering 502,543 individuals. Both unmatched analysis (adjusted for confounders) and a matched analysis (one control matched for each patient with cataract according to confounding factors) were undertaken and confirmed that cataract was associated with hearing difficulties (OR, 2.12; 95% CI, 1.98-2.27; OR, 2.03; 95% CI, 1.86-2.23, respectively). Furthermore, we explored and quantified the shared genetic architecture of these two complex sensory disorders at the common variant level using the bivariate causal mixture model (MiXeR) and conditional/conjunctional false discovery rate method based on the largest available genome-wide association studies of cataract (N = 585,243) and hearing difficulties (N = 323,978). Despite detecting only a negligible genetic correlation, we observe polygenic overlap between cataract and hearing difficulties and identify 6 shared loci with mixed directions of effects. Follow-up analysis of the shared loci implicates candidate genes QKI, STK17A, TYR, NSF, and TCF4 likely contribute to the pathophysiology of cataracts and hearing difficulties. In conclusion, this study demonstrates the presence of epidemiologic association between cataract and hearing difficulties and provides new insights into the shared genetic architecture of these two disorders at the common variant level.

Genomic survey and expression analysis of cellulose synthase superfamily and COBRA-like gene family in Zanthoxylum bungeanum stipule thorns.

The Cellulose Synthase gene (CS) superfamily and COBRA-like (COBL) gene family are essential for synthesizing cellulose and hemicellulose, which play a crucial role in cell wall biosynthesis and the hardening of plant tissues. Our study identified 126 ZbCS and 31 ZbCOBL genes from the Zanthoxylum bungeanum (Zb) genome. Phylogenetic analysis and conservative domain analysis unfolded that ZbCS and ZbCOBL genes were divided into seven and two subfamilies, respectively. Gene duplication data suggested that more than 75% of these genes had tandem and fragment duplications. Codon usage patterns analysis indicated that the ZbCS and ZbCOBL genes prefer ending with A/T base, with weak codon preference. Furthermore, seven key ZbCS and five key ZbCOBL genes were identified based on the content of cellulose and hemicellulose and the expression characteristics of ZbCS and ZbCOBL genes in various stages of stipule thorns. Altogether, these results improve the understanding of CS and COBL genes and provide valuable reference data for cultivating Zb with soft thorns. Supplementary Information: The online version contains supplementary material available at 10.1007/s12298-024-01432-x.

Preparation and adjuvanticity against PCV2 of Viola philippica polysaccharide loaded in Chitosan-Gold nanoparticle.

The present Porcine circovirus type 2 virus (PCV2) vaccine adjuvants suffer from numerous limitations, such as adverse effects, deficient cell-mediated immune responses, and inadequate antibody production. In this study, we explored the potential of a novel nanoparticle (CS-Au NPs) based on gold nanoparticles (Au NPs) and chitosan (CS) that modified Viola philippica polysaccharide (VPP) as efficient adjuvants for PCV2 vaccine. The characterization demonstrated that CS-Au-VPP NPs had a mean particle size of 507.42 nm and a zeta potential value of -21.93 mV. CS-Au-VPP NPs also exhibited good dispersion and a stable structure, which did not alter the polysaccharide properties. Additionally, the CS-Au-VPP NPs showed easy absorption and utilization by the organism. To investigate their immune-enhancing potential, mice were immunized with a mixture of CS-Au-VPP NPs and PCV2 vaccine. The evaluation of relevant immunological indicators, including specific IgG antibodies and their subclasses, cytokines, and T cell subpopulations, confirmed their immune-boosting effects. The in vivo experiments revealed that the medium-dose CS-Au-VPP NPs significantly elevated the levels of specific IgG antibodies and their subclasses, cytokines, and T cell subpopulations in PCV2-immunized mice. These findings suggest that CS-Au-VPP NPs can serve as a promising vaccine adjuvant due to their stable structure and immunoenhancement capabilities.

Evaluating the hypolipidemic effect of garlic essential oil encapsulated in a novel double-layer delivery system.

The limited application of garlic essential oil (GEO) is attributed to its pungent taste, poor water solubility and low bioavailability. Liposomes are nontoxic, biodegradable and biocompatible, and ß-cyclodextrin can inhibit undesirable odors and improve the stability and bioavailability. Thus a promising dual-layer GEO ß-cyclodextrin inclusion compound liposome (GEO-DCL) delivery system with both advantages was designed and prepared in this study. Experimental results indicated that the encapsulation efficiency of GEO-DCLs was 5% higher than that of GEO liposomes (GEO-CLs), reaching more than 88%. In vitro release experiment showed that the release rate of GEO in GEO-DCLs was 40% lower than that of GEO-CLs after incubation in gastric juice for 6-h, indicating that the stability of GEO-DCLs was better than GEO-CLs. Evaluation of the effects of GEO-DCLs on lowering blood lipid levels in hypercholesterolemia mice. GEO-DCLs could reduce the weight and fat deposition in hypercholesterolemia mice. Inhibiting the increase of TC, LDL-C, and decrease of HDL-C in mice. The degree of liver injury was decreased, the number of round lipid droplets in liver cytoplasm was reduced, and the growth of fat cells was inhibited. The lipid-lowering effects of GEO-DCLs were dose-dependent. GEO-DCL can improve the bioavailability of GEO and improve dyslipidemia. Based on GEO's efficacy in lowering blood lipids, this study developed a kind of GEO-DCL compound pomegranate juice beverage with good taste, miscibility and double effect of reducing blood lipids. This study lays a foundation for the application of GEO in the field of functional food.

Mismatch repair protein deficiency and its implications on distant metastasis in colorectal cancer: A comprehensive analysis.

BACKGROUND: While previous studies have indicated variability in distant metastatic potential among different mismatch repair (MMR) states in colorectal cancer (CRC), their findings remain inconclusive, especially considering potential differences across various ethnic backgrounds. Furthermore, the gene regulatory networks and the underlying mechanisms responsible for these variances in metastatic potential across MMR states have yet to be elucidated. METHODS: We collected 2058 consecutive primary CRC samples from the South West of China and assessed the expression of MMR proteins (MLH1, MSH2, MSH6, and PMS2) using immunohistochemistry. To explore the inconsistencies between different MMR statuses and recurrence, we performed a meta-analysis. To delve deeper, we employed Weighted Gene Co-expression Network Analysis (WGCNA), ClueGo, and iRegulon, pinpointing gene expression networks and key regulatory molecules linked to metastasis and recurrence in CRC. Lastly, both univariate and multivariate Cox regression analyses were applied to determine the impact of core regulatory molecules on metastasis. RESULTS: Of the samples, 8.2% displayed deficient MMR (dMMR), with losses of MLH1 and PSM2 observed in 40.8% and 63.9%, respectively. A unique 24.3% isolated loss of PMS2 without concurrent metastasis was identified, a result that diverges from established literature. Additionally, our meta-analysis further solidifies the reduced recurrence likelihood in dMMR CRC samples compared to proficient MMR (pMMR). Two gene expression networks tied to distant metastasis and recurrence were identified, with a majority of metastasis-related genes located on chromosomes 8 and 18. An IRF1 positive feedback loop was discerned in the metastasis-related network, and IRF1 was identified as a predictive marker for both recurrence-free and distant metastasis-free survival across multiple datasets. CONCLUSION: Geographical and ethnic factors might influence peculiarities in MMR protein loss. Our findings also highlight new gene expression networks and crucial regulatory molecules in CRC metastasis, enhancing our comprehension of the mechanisms driving distant metastasis.

Evaluation of the Observational Associations and Shared Genetics Between Glaucoma With Depression and Anxiety.

Purpose: Glaucoma, a leading cause of blindness worldwide, is suspected to exhibit a notable association with psychological disturbances. This study aimed to investigate epidemiological associations and explore shared genetic architecture between glaucoma and mental traits, including depression and anxiety. Methods: Multivariable logistic regression and Cox proportional hazards regression models were employed to investigate longitudinal associations based on UK Biobank. A stepwise approach was used to explore the shared genetic architecture. First, linkage disequilibrium score regression inferred global genetic correlations. Second, MiXeR analysis quantified the number of shared causal variants. Third, specific shared loci were detected through conditional/conjunctional false discovery rate (condFDR/conjFDR) analysis and characterized for biological insights. Finally, two-sample Mendelian randomization (MR) was conducted to investigate bidirectional causal associations. Results: Glaucoma was significantly associated with elevated risks of hospitalized depression (hazard ratio [HR] = 1.54; 95% confidence interval [CI], 1.01-2.34) and anxiety (HR = 2.61; 95% CI, 1.70-4.01) compared to healthy controls. Despite the absence of global genetic correlations, MiXeR analysis revealed 300 variants shared between glaucoma and depression, and 500 variants shared between glaucoma and anxiety. Subsequent condFDR/conjFDR analysis discovered 906 single-nucleotide polymorphisms (SNPs) jointly associated with glaucoma and depression and two associated with glaucoma and anxiety. The MR analysis did not support robust causal associations but indicated the existence of pleiotropic genetic variants influencing both glaucoma and depression. Conclusions: Our study enhances the existing epidemiological evidence and underscores the polygenic overlap between glaucoma and mental traits. This observation suggests a correlation shaped by pleiotropic genetic variants rather than being indicative of direct causal relationships.

The Silencing of GhPIP5K2 and GhPIP5K22 Weakens Abiotic Stress Tolerance in Upland Cotton (Gossypium hirsutum).

Phosphatidylinositol 4-phosphate 5-kinases (PIP5Ks), essential enzymes in the phosphatidylinositol signaling pathway, are crucial for the abiotic stress responses and the overall growth and development of plants. However, the GhPIP5Ks had not been systematically studied, and their function in upland cotton was unknown. This study identified a total of 28 GhPIP5Ks, and determined their chromosomal locations, gene structures, protein motifs and cis-acting elements via bioinformatics analysis. A quantitative real-time PCR (qRT‒PCR) analysis showed that most GhPIP5Ks were upregulated under different stresses. A virus-induced gene silencing (VIGS) assay indicated that the superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT) activities were significantly decreased, while malondialdehyde (MDA) content were significantly increased in GhPIP5K2- and GhPIP5K22-silenced upland cotton plants under abiotic stress. Furthermore, the expression of the stress marker genes GhHSFB2A, GhHSFB2B, GhDREB2A, GhDREB2C, GhRD20-1, GhRD29A, GhBIN2, GhCBL3, GhNHX1, GhPP2C, GhCBF1, GhSnRK2.6 and GhCIPK6 was significantly decreased in the silenced plants after exposure to stress. These results revealed that the silencing of GhPIP5K2 and GhPIP5K22 weakened the tolerance to abiotic stresses. These discoveries provide a foundation for further inquiry into the actions of the GhPIP5K gene family in regulating the response and resistance mechanisms of cotton to abiotic stresses.

Inhibition of CISD1 alleviates mitochondrial dysfunction and ferroptosis in mice with acute lung injury.

The NET family member, CDGSH iron-sulfur domain-containing protein 1 (CISD1), is located in theoutermembrane of mitochondria, where it regulates energy and iron metabolism. CISD1 has vital functions in certain human diseases; however, its function in acute lung injury (ALI) is unknown. ALI pathogenesis critically involves mitochondrial dysfunction and ferroptosis, which might be regulated by CISD1. Therefore, we investigated CISD1's function in mitochondrial dysfunction and ferroptosis regulation in lipopolysaccharide (LPS)-induced ALI. We found that CISD1 was upregulated in LPS-induced ALI,and silencing Cisd1 prevented cell apoptosis and increased cell viability. When CISD1was inhibited by mitoNEET ligand-1 (NL-1) there was a significant mitigation of pathological injury and lung edema, and reduced numbers of total cells, polymorphonuclear leukocytes, and a decreased protein content in the bronchoalveolar lavage fluid (BALF). Moreover, inhibition of CISD1 markedly decreased the interleukin (IL)6, IL-1ß, and tumor necrosis factor alpha (TNF-α) levels in the lungs and BALF of ALI-model mice. Silencing of Cisd1 prevented LPS-induced mitochondrial membrane potential depolarization, cellular ATP reduction, and reactive oxygen species (ROS) accumulation, suggesting mitochondrial protection. ALI activated ferroptosis, as evidenced by the increased lipid-ROS, intracellular Fe2+ level, reduced Gpx4 (glutathione peroxidase 4) expression, and the glutathione/glutathione disulfide ratio. Interestingly, inhibition of CISD1 reduced LPS-induced ferroptosis in vivo and in vitro. In conclusion, inhibition of CISD1 alleviated mitochondrial dysfunction and ferroptosis in LPS-induced ALI, identifying CISD1 as possible target for therapy of LPS-induced ALI.

GhBRX.1, GhBRX.2, and GhBRX4.3 improve resistance to salt and cold stress in upland cotton.

Introduction: Abiotic stress during growth readily reduces cotton crop yield. The different survival tactics of plants include the activation of numerous stress response genes, such as BREVIS RADIX (BRX). Methods: In this study, the BRX gene family of upland cotton was identified and analyzed by bioinformatics method, three salt-tolerant and cold-resistant GhBRX genes were screened. The expression of GhBRX.1, GhBRX.2 and GhBRXL4.3 in upland cotton was silenced by virus-induced gene silencing (VIGS) technique. The physiological and biochemical indexes of plants and the expression of related stress-response genes were detected before and after gene silencing. The effects of GhBRX.1, GhBRX.2 and GhBRXL4.3 on salt and cold resistance of upland cotton were further verified. Results and discussion: We discovered 12, 6, and 6 BRX genes in Gossypium hirsutum, Gossypium raimondii and Gossypium arboreum, respectively. Chromosomal localization indicated that the retention and loss of GhBRX genes on homologous chromosomes did not have a clear preference for the subgenomes. Collinearity analysis suggested that segmental duplications were the main force for BRX gene amplification. The upland cotton genes GhBRX.1, GhBRX.2 and GhBRXL4.3 are highly expressed in roots, and GhBRXL4.3 is also strongly expressed in the pistil. Transcriptome data and qRT‒PCR validation showed that abiotic stress strongly induced GhBRX.1, GhBRX.2 and GhBRXL4.3. Under salt stress and low-temperature stress conditions, the activities of superoxide dismutase (SOD), peroxidase (POD) and catalase (CAT) and the content of soluble sugar and chlorophyll decreased in GhBRX.1-, GhBRX.2- and GhBRXL4.3-silenced cotton plants compared with those in the control (TRV: 00). Moreover, GhBRX.1-, GhBRX.2- and GhBRXL4.3-silenced cotton plants exhibited greater malondialdehyde (MDA) levels than did the control plants. Moreover, the expression of stress marker genes (GhSOS1, GhSOS2, GhNHX1, GhCIPK6, GhBIN2, GhSnRK2.6, GhHDT4D, GhCBF1 and GhPP2C) decreased significantly in the three target genes of silenced plants following exposure to stress. These results imply that the GhBRX.1, GhBRX.2 and GhBRXL4.3 genes may be regulators of salt stress and low-temperature stress responses in upland cotton.

Global prevalence and burden of multidrug-resistant tuberculosis from 1990 to 2019.

BACKGROUND: Tuberculosis(TB) remains a pressing public health challenge, with multidrug-resistant tuberculosis (MDR-TB) emerging as a major threat. And healthcare authorities require reliable epidemiological evidence as a crucial reference to address this issue effectively. The aim was to offer a comprehensive epidemiological assessment of the global prevalence and burden of MDR-TB from 1990 to 2019. METHODS: Estimates and 95% uncertainty intervals (UIs) for the age-standardized prevalence rate (ASPR), age-standardized incidence rate (ASIR), age-standardized disability-adjusted life years rate (ASR of DALYs), and age-standardized death rate (ASDR) of MDR-TB were obtained from the Global Burden of Disease (GBD) 2019 database. The prevalence and burden of MDR-TB in 2019 were illustrated in the population and regional distribution. Temporal trends were analyzed by using Joinpoint regression analysis to calculate the annual percentage change (APC), average annual percentage change (AAPC) and its 95% confidence interval(CI). RESULTS: The estimates of the number of cases were 687,839(95% UIs: 365,512 to 1223,262), the ASPR were 8.26 per 100,000 (95%UIs: 4.61 to 15.20), the ASR of DALYs were 52.38 per 100,000 (95%UIs: 22.64 to 97.60) and the ASDR were 1.36 per 100,000 (95%UIs: 0.54 to 2.59) of MDR-TB at global in 2019. Substantial burden was observed in Africa and Southeast Asia. Males exhibited higher ASPR, ASR of DALYs, and ASDR than females across most age groups, with the burden of MDR-TB increasing with age. Additionally, significant increases were observed globally in the ASIR (AAPC = 5.8; 95%CI: 5.4 to 6.1; P < 0.001), ASPR (AAPC = 5.9; 95%CI: 5.4 to 6.4; P < 0.001), ASR of DALYs (AAPC = 4.6; 95%CI: 4.2 to 5.0; P < 0.001) and ASDR (AAPC = 4.4; 95%CI: 4.0 to 4.8; P < 0.001) of MDR-TB from 1990 to 2019. CONCLUSIONS: This study underscored the persistent threat of drug-resistant tuberculosis to public health. It is imperative that countries and organizations worldwide take immediate and concerted action to implement measures aimed at significantly reducing the burden of TB.

Efficacy of immune checkpoint inhibitors in SMARCA4-deficient and TP53 mutant undifferentiated lung cancer.

The present study was conducted to characterize the clinicopathologic characteristics, immunohistochemical staining results, and immune checkpoint inhibitors (ICIs) efficacy in patients with SMARCA4-deficient/TP53 mutant lung cancer. Patients diagnosed with advanced or metastatic undifferentiated lung cancer harboring SMARCA4-deficient and TP53 mutations, however, without targetable sensitive mutations were retrieved from the electronic medical record system. Descriptive statistics were used to describe the baseline characteristics and clinical features including age, gender, eastern cooperative oncology group performance status, disease stage, smoking status, chief complaint, site of the primary mass, tumor size, gross type, symptoms, local invasion, and metastatic sizes. Immunological markers and potential drive genes were detected by immunohistochemical staining and next generation sequencing. Efficacy and safety profile of ICIs in included patients was evaluated with progression-free survival and overall survival. Between January 2019 and September 2022, there were 4 patients included within the inclusion criteria in the present study. Biomarkers including CK, CK7, and integrase interactor 1 were detected positive, however, other immunological markers including CK20, CD56, P63, P40, NapsinA, TTF-1, CgA, Syn, BRG1, or PD-L1 were detected negative among them. Results of next generation sequencing panel were failed to discover any targetable sensitive mutations. A total of 4 mutation types of TP53, including p.C141Y, p.S240G, p.E339X (terminator acquired), and p.L130F detected for the patients, respectively. Microsatellite stability status, as well as low tumor mutation burden was identified among all the patients. Median progression-free survival for ICIs as first line treatment and median overall survival were 3.25 months (range from 1.3 to 6.8 months), and 6.0 months (range from 2.7 to 9.6 months), respectively. Our results indicated that advanced lung cancer patients harboring co-occurring SMARCA4-deficient/TP53 mutations might respond to ICIs treatment, though within negative programmed cell death-ligand 1 expression or low tumor mutation burden. However, hyperprogressive disease by ICIs may also happen for such patients. The mutation types of TP53 might play a role during the exposure of ICIs, however, need further identification in basic experiments.

Leading determinants of incident dementia among individuals with and without the apolipoprotein E ε4 genotype: a retrospective cohort study.

BACKGROUND: Little is known regarding the leading risk factors for dementia/Alzheimer's disease (AD) in individuals with and without APOE4. The identification of key risk factors for dementia/Alzheimer's disease (AD) in individuals with and without the APOE4 gene is of significant importance in global health. METHODS: Our analysis included 110,354 APOE4 carriers and 220,708 age- and sex-matched controls aged 40-73 years at baseline (between 2006-2010) from UK Biobank. Incident dementia was ascertained using hospital inpatient, or death records until January 2021. Individuals of non-European ancestry were excluded. Furthermore, individuals without medical record linkage were excluded from the analysis. Moderation analysis was tested for 134 individual factors. RESULTS: During a median follow-up of 11.9 years, 4,764 cases of incident all-cause dementia and 2065 incident AD cases were documented. Hazard ratios (95% CIs) for all-cause dementia and AD associated with APOE4 were 2.70(2.55-2.85) and 3.72(3.40-4.07), respectively. In APOE4 carriers, the leading risk factors for all-cause dementia included low self-rated overall health, low household income, high multimorbidity risk score, long-term illness, high neutrophil percentage, and high nitrogen dioxide air pollution. In non-APOE4 carriers, the leading risk factors included high multimorbidity risk score, low overall self-rated health, low household income, long-term illness, high microalbumin in urine, high neutrophil count, and low greenspace percentage. Population attributable risk for these individual risk factors combined was 65.1%, and 85.8% in APOE4 and non-APOE4 carriers, respectively. For 20 risk factors including multimorbidity risk score, unhealthy lifestyle habits, and particulate matter air pollutants, their associations with incident dementia were stronger in non-APOE4 carriers. For only 2 risk factors (mother's history of dementia, low C-reactive protein), their associations with incident all-cause dementia were stronger in APOE4 carriers. CONCLUSIONS: Our findings provide evidence for personalized preventative approaches to dementia/AD in APOE4 and non-APOE4 carriers. A mother's history of dementia and low levels of C-reactive protein were more important risk factors of dementia in APOE4 carriers whereas leading risk factors including unhealthy lifestyle habits, multimorbidity risk score, inflammation and immune-related markers were more predictive of dementia in non-APOE4 carriers.

Metabolomic age and risk of 50 chronic diseases in community-dwelling adults: A prospective cohort study.

It is unclear how metabolomic age is associated with the risk of a wide range of chronic diseases. Our analysis included 110,692 participants (training: n = 27,673; testing: n = 27,673; validating: n = 55,346) aged 39-71 years at baseline (2006-2010) from the UK Biobank. Incident chronic diseases were identified using inpatient records, or death registers until January 2021. Predicted metabolomic age was trained and tested based on 168 metabolomics. Metabolomic age was linked to the risk of 50 diseases in the validation dataset. The median follow-up duration for individual diseases ranged from 11.2 years to 11.9 years. After controlling for false discovery rate, chronological age-adjusted age gap (CAAG) was significantly associated with the incidence of 25 out of 50 chronic diseases. After adjustment for full covariates, associations with 15 chronic diseases remained significant. Greater CAAG was associated with increased risk of eight cardiometabolic disorders (including cardiovascular diseases and diabetes), some cancers, alcohol use disorder, chronic obstructive pulmonary disease, chronic kidney disease, chronic liver disease and age-related macular degeneration. The association between CAAG and risk of peripheral vascular disease, other cardiac diseases, fracture, cataract and thyroid disorder was stronger among individuals with unhealthy diet than in those with healthy diet. The association between CAAG and risk of some conditions was stronger in younger individuals, those with metabolic disorders or low education. Metabolomic age plays an important role in the development of multiple chronic diseases. Healthy diet and high education may mitigate the risk for some chronic diseases due to metabolomic age acceleration.

Entropy-Regulated Cathode with Low Strain and Constraint Phase-Change Toward Ultralong-Life Aqueous Al-Ion Batteries.

During multivalent ions insertion processes, intense electrostatic interaction between charge carriers and host makes the high-performance reversible Al3+ storage remains an elusive target. On account of the strong electrostatic repulsion and poor robustness, Prussian Blue analogues (PBAs) suffer severely from the inevitable and large strain and phase change during reversible Al3+ insertion. Herein, we demonstrate an entropy-driven strategy to realize ultralong life aqueous Al-ion batteries (AIBs) based on medium entropy PBAs (ME-PBAs) host. By multiple redox active centers introduction, the intrinsic poor conductivity can be enhanced simultaneously, resulting in outstanding capabilities of electrochemical Al3+ storage. Meanwhile, the co-occupation at metal sites in PBA frameworks can also increase the M-N bond intensity, which is beneficial for constraining the phase change during consecutive Al3+ reversible insertion, to realize an extended lifespan over 10,000 cycles. Based on the calculation at different operation states, the fluctuation of ME-PBA lattice parameters is only 1.2 %. Assembled with MoO3 anodes, the full cells can also deliver outstanding electrochemical properties. The findings highlight that, the entropy regulation strategy could uncover the isochronous constraint on both strain and phase transition for long-term reversible Al3+ storage, providing a promising design for advanced electrode materials for aqueous multivalent ions batteries.

Comparison of prediction models for soy protein isolate hydrolysates bitterness built using sensory, spectrofluorometric and chromatographic data from varying enzymes and degree of hydrolysis.

The bitterness of soy protein isolate hydrolysates prepared using five proteases at varying degree of hydrolysis (DH) and its relation to physicochemical properties, i.e., surface hydrophobicity (H0), relative hydrophobicity (RH), and molecular weight (MW), were studied and developed for predictive modelling using machine learning. Bitter scores were collected from sensory analysis and assigned as the target, while the physicochemical properties were assigned as the features. The modelling involved data pre-processing with local outlier factor; model development with support vector machine, linear regression, adaptive boosting, and K-nearest neighbors algorithms; and performance evaluation by 10-fold stratified cross-validation. The results indicated that alcalase hydrolysates were the most bitter, followed by protamex, flavorzyme, papain, and bromelain. Distinctive correlation results were found among the physicochemical properties, influenced by the disparity of each protease. Among the features, the combination of RH-MW fitted various classification models and resulted in the best prediction performance.

A GAPDH serotonylation system couples CD8+ T cell glycolytic metabolism to antitumor immunity.

Apart from the canonical serotonin (5-hydroxytryptamine [5-HT])-receptor signaling transduction pattern, 5-HT-involved post-translational serotonylation has recently been noted. Here, we report a glyceraldehyde-3-phosphate dehydrogenase (GAPDH) serotonylation system that promotes the glycolytic metabolism and antitumor immune activity of CD8+ T cells. Tissue transglutaminase 2 (TGM2) transfers 5-HT to GAPDH glutamine 262 and catalyzes the serotonylation reaction. Serotonylation supports the cytoplasmic localization of GAPDH, which induces a glycolytic metabolic shift in CD8+ T cells and contributes to antitumor immunity. CD8+ T cells accumulate intracellular 5-HT for serotonylation through both synthesis by tryptophan hydroxylase 1 (TPH1) and uptake from the extracellular compartment via serotonin transporter (SERT). Monoamine oxidase A (MAOA) degrades 5-HT and acts as an intrinsic negative regulator of CD8+ T cells. The adoptive transfer of 5-HT-producing TPH1-overexpressing chimeric antigen receptor T (CAR-T) cells induced a robust antitumor response. Our findings expand the known range of neuroimmune interaction patterns by providing evidence of receptor-independent serotonylation post-translational modification.

Identification of a novel m6A-related lncRNAs signature and immunotherapeutic drug sensitivity in pancreatic adenocarcinoma.

BACKGROUND: Pancreatic adenocarcinoma (PDAC) ranks as the fourth leading cause for cancer-related deaths worldwide. N6-methyladenosine (m6A) and long non-coding RNAs (lncRNAs) are closely related with poor prognosis and immunotherapeutic effect in PDAC. The aim of this study is to construct and validate a m6A-related lncRNAs signature and assess immunotherapeutic drug sensitivity in PDAC. METHODS: RNA-seq data for 178 cases of PDAC patients and 167 cases of normal pancreatic tissue were obtained from TCGA and GTEx databases, respectively. A set of 21 m6A-related genes were downloaded based on the previous report. Co-expression network was conducted to identify m6A-related lncRNAs in PDAC. Cox analyses and least absolute shrinkage and selection operator (Lasso) regression model were used to construct a risk prognosis model. The relationship between signature genes and immune function was explored by single-sample GSEA (ssGSEA). The tumor immune dysfunction and exclusion (TIDE) score and tumor mutation burden (TMB) were utilized to evaluate the response to immunotherapy. Furthermore, the expression levels of 4 m6A-related lncRNAs on PDAC cell lines were measured by the quantitative real-time PCR (qPCR). The drug sensitivity between the high- and low-risk groups was validated using PDAC cell lines by Cell-Counting Kit 8 (CCK8). RESULTS: The risk prognosis model was successfully constructed based on 4 m6A-related lncRNAs, and PDAC patients were divided into the high- and low-risk groups. The overall survival (OS) of the high-risk groups was more unfavorable compared with the low-risk groups. Receiver operating characteristic (ROC) curves demonstrated that the risk prognosis model reasonably predicted the 2-, 3- and 5-year OS of PDAC patients. qPCR analysis confirmed the decreased expression levels of 4 m6A-related lncRNAs in PDAC cells compared to the normal pancreatic cells. Furthermore, CCK8 assay revealed that Phenformin exhibited higher sensitivity in the high-risk groups, while Pyrimethamine exhibited higher sensitivity in the low-risk groups. CONCLUSION: The prognosis of patients with PDAC were well predicted in the risk prognosis model based on m6A-related lncRNAs, and selected immunotherapy drugs have potential values for the treatment of pancreatic cancer.