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Abstract The etiology of primary open angle glaucoma is constituted by both intraocular pressure-dependent and intraocular pressure-independent mechanisms. However, GWASs of traits affecting primary open angle glaucoma through mechanisms independent of intraocular pressure remains limited. Here, we address this gap by subtracting the genetic effects of a GWAS for intraocular pressure from a GWAS for primary open angle glaucoma to reveal the genetic contribution to primary open angle glaucoma via intraocular pressure-independent mechanisms. Seventeen independent genome-wide significant SNPs were associated with the intraocular pressure-independent component of primary open angle glaucoma. Of these, 7 are located outside known normal tension glaucoma loci, 11 are located outside known intraocular pressure loci, and 2 are novel primary open angle glaucoma loci. The intraocular pressure-independent genetic component of primary open angle glaucoma is associated with glaucoma endophenotypes, while the intraocular pressure-dependent component is associated with blood pressure and vascular permeability. A genetic risk score for the intraocular pressure-independent component of primary open angle glaucoma is associated with 26 different retinal micro-vascular features, which contrasts with the genetic risk score for the intraocular pressure-dependent component. Increased understanding of these intraocular pressure-dependent and intraocular pressure-independent components provides insights into the pathogenesis of glaucoma.

Abstract Alzheimer's disease (AD) has emerged as the most prevalent and complex neurodegenerative disorder among the elderly population. However, the genetic comorbidity etiology for AD remains poorly understood. In this study, we conducted pleiotropic analysis for 41 AD phenotypic comorbidities, identifying ten genetic comorbidities with 16 pleiotropy genes associated with AD. Through biological functional and network analysis, we elucidated the molecular and functional landscape of AD genetic comorbidities. Furthermore, leveraging the pleiotropic genes and reported biomarkers for AD genetic comorbidities, we identified 50 potential biomarkers for AD diagnosis. Our findings deepen the understanding of the occurrence of AD genetic comorbidities and provide new insights for the search for AD diagnostic markers. Graphical Abstract Study pipeline.

Abstract Questions of unfairness and inequity pose critical challenges to the successful deployment of artificial intelligence (AI) in healthcare settings. In AI models, unequal performance across protected groups may be partially attributable to the learning of spurious or otherwise undesirable correlations between sensitive attributes and disease-related information. Here, we introduce the Attribute Neutral Framework, designed to disentangle biased attributes from disease-relevant information and subsequently neutralize them to improve representation across diverse subgroups. Within the framework, we develop the Attribute Neutralizer (AttrNzr) to generate neutralized data, for which protected attributes can no longer be easily predicted by humans or by machine learning classifiers. We then utilize these data to train the disease diagnosis model (DDM). Comparative analysis with other unfairness mitigation algorithms demonstrates that AttrNzr outperforms in reducing the unfairness of the DDM while maintaining DDM’s overall disease diagnosis performance. Furthermore, AttrNzr supports the simultaneous neutralization of multiple attributes and demonstrates utility even when applied solely during the training phase, without being used in the test phase. Moreover, instead of introducing additional constraints to the DDM, the AttrNzr directly addresses a root cause of unfairness, providing a model-independent solution. Our results with AttrNzr highlight the potential of data-centered and model-independent solutions for fairness challenges in AI-enabled medical systems.

Activity of bc1 complex kinase (ABC1K) is an atypical protein kinase (aPK) that plays a crucial role in plant mitochondrial and plastid stress responses, but little is known about the responses of ABC1Ks to stress in cotton (Gossypium spp.). Here, we identified 40 ABC1Ks in upland cotton (Gossypium hirsutum L.) and found that the GhABC1Ks were unevenly distributed across 17 chromosomes. The GhABC1K family members included 35 paralogous gene pairs and were expanded by segmental duplication. The GhABC1K promoter sequences contained diverse cis-acting regulatory elements relevant to hormone or stress responses. The qRT-PCR results revealed that most GhABC1Ks were upregulated by exposure to different stresses. GhABC1K2-A05 and GhABC1K12-A07 expression levels were upregulated by at least three stress treatments. These genes were further functionally characterized by virus-induced gene silencing (VIGS). Compared with the controls, the GhABC1K2-A05- and GhABC1K12-A07-silenced cotton lines exhibited higher malondialdehyde (MDA) contents, lower catalase (CAT), peroxidase (POD) and superoxide dismutase (SOD) activities and reduced chlorophyll and soluble sugar contents under NaCl and PEG stress. In addition, the expression levels of six stress marker genes (GhDREB2A, GhSOS1, GhCIPK6, GhSOS2, GhWRKY33, and GhRD29A) were significantly downregulated after stress in the GhABC1K2-A05- and GhABC1K12-A07-silenced lines. The results indicate that knockdown of GhABC1K2-A05 and GhABC1K12-A07 make cotton more sensitive to salt and PEG stress. These findings can provide valuable information for intensive studies of GhABC1Ks in the responses and resistance of cotton to abiotic stresses.

Abstract Backgrounds Most significant findings from the Global Tuberculosis (TB) Report 2023 indicate that India, Indonesia, China, the Philippines, Pakistan, Nigeria, Bangladesh, and the Democratic Republic of the Congo (DRC) collectively contribute to approximately two-thirds of global TB cases. This study aims to provide crucial data-driven insights and references to improve TB control measures through a comprehensive analysis of these eight high-burden countries. Methods The eight high-burden TB countries analyzed in this study include India, Indonesia, China, the Philippines, Pakistan, Nigeria, Bangladesh, and the DRC. Age-standardized incidence rates (ASIR) of TB were derived from the Global Burden of Diseases Study 2021 data. Temporal trends were analyzed using Joinpoint regression. An age-period-cohort model was applied to examine the risk ratios (RR) of TB across diverse age groups, periods, and birth cohorts. A Bayesian age-period-cohort framework was employed to predict the ASIR of TB by 2030. Results The study found that the Philippines (average annual percentage change = 3.1%, P

Abstract From both economic and environmental perspectives, ethylene glycol, the principal constituent in the degradation of PET, emerges as an optimal feedstock for microbial cell factories. Traditional methods for constructing Escherichia coli chassis cells capable of utilizing ethylene glycol as a non-sugar feedstock typically involve overexpressing the genes fucO and aldA. However, these approaches have not succeeded in enabling the exclusive use of ethylene glycol as the sole source of carbon and energy for growth. Through ultraviolet radiation-induced mutagenesis and subsequent laboratory adaptive evolution, an EG02 strain emerged from E. coli MG1655 capable of utilizing ethylene glycol as its sole carbon and energy source, demonstrating an uptake rate of 8.1 ± 1.3 mmol/gDW h. Comparative transcriptome analysis guided reverse metabolic engineering, successfully enabling four wild-type E. coli strains to metabolize ethylene glycol exclusively. This was achieved through overexpression of the gcl, hyi, glxR, and glxK genes. Notably, the engineered E. coli chassis cells efficiently metabolized the 87 mM ethylene glycol found in PET enzymatic degradation products following 72 h of fermentation. This work presents a practical solution for recycling ethylene glycol from PET waste degradation products, demonstrating that simply adding M9 salts can effectively convert them into viable raw materials for E. coli cell factories. Our findings also emphasize the significant roles of genes associated with the glycolate and glyoxylate degradation I pathway in the metabolic utilization of ethylene glycol, an aspect frequently overlooked in previous research.

Abstract Radish exhibits significant variation in color, particularly in sprouts, leaves, petals, fleshy roots, and other tissues, displaying a range of hues such as green, white, red, purple, and black. Although extensive research has been conducted on the color variation of radish, the underlying mechanism behind the variation in radish flower color remains unclear. To date, there is a lack of comprehensive research investigating the variation mechanism of radish sprouts, leaves, fleshy roots, and flower organs. This study aims to address this gap by utilizing transcriptome sequencing to acquire transcriptome data for white and purple radish flowers. Additionally, the published transcriptome data of sprouts, leaves, and fleshy roots were incorporated to conduct a systematic analysis of the regulatory mechanisms underlying anthocyanin biosynthesis in these four radish tissues. The comparative transcriptome analysis revealed differential expression of the anthocyanin biosynthetic pathway genes DFR, UGT78D2, TT12 and CPC in the four radish tissues. Additionally, the WGCNA results identified RsDFR.9c and RsUGT78D2.2c as hub genes responsible for regulating anthocyanin biosynthesis. By integrating the findings from the comparative transcriptome analysis, WGCNA, and anthocyanin biosynthetic pathway-related gene expression patterns, it is hypothesized that genes RsDFR.9c and RsUGT78D2.2c may serve as pivotal regulators of anthocyanins in the four radish tissues. Furthermore, the tissue-specific expression of the four copies of RsPAP1 is deemed crucial in governing anthocyanin synthesis and accumulation. Our results provide new insights into the molecular mechanism of anthocyanin biosynthesis and accumulation in different tissues of radish.

Summary: Intraocular pressure (IOP) is closely correlated with blood pressure (BP), and while BP has been linked to brain volumes, the effect of IOP on brain volumes remains unclear. This study analyzed participants from the UK Biobank with MRI-measured brain volumes. Observational analyses included 8,634 participants for IOP and 36,069 for BP, followed by Mendelian randomization (MR) analyses of 37,410 participants. Observational analyses revealed that each 10-mmHg increase in diastolic BP was linked to a 0.13 mL larger white matter hyperintensity (WMH) after adjusting for covariates. Associations between IOP and brain volumes were more pronounced in younger individuals or those without hypertension. MR analyses confirmed significant relationships between diastolic BP and WMH, and each 5-mmHg increase in IOP reduced gray matter volumes by 3.24 mL. The study suggests that targeting IOP and BP could help prevent brain volume reduction.

Abstract The crucial role of TIR1‐receptor‐mediated gene transcription regulation in auxin signaling has long been established. In recent years, the significant role of protein phosphorylation modifications in auxin signal transduction has gradually emerged. To further elucidate the significant role of protein phosphorylation modifications in auxin signaling, a phosphoproteomic analysis in conjunction with auxin treatment has identified an auxin activated Mitogen‐activated Protein Kinase Kinase Kinase (MAPKKK) VH1‐INTERACTING Kinase (VIK), which plays an important role in auxin‐induced lateral root (LR) development. In the vik mutant, auxin‐induced LR development is significantly attenuated. Further investigations show that VIK interacts separately with the positive regulator of LR development, LATERAL ORGAN BOUNDARIES‐DOMAIN18 (LBD18), and the negative regulator of LR emergence, Ethylene Responsive Factor 13 (ERF13). VIK directly phosphorylates and stabilizes the positive transcription factor LBD18 in LR formation. In the meantime, VIK directly phosphorylates the negative regulator ERF13 at Ser168 and Ser172 sites, causing its degradation and releasing the repression by ERF13 on LR emergence. In summary, VIK‐mediated auxin signaling regulates LR development by enhancing the protein stability of LBD18 and inducing the degradation of ERF13, respectively.

Abstract Background Dihydroxyacetone (DHA) stands as a crucial chemical material extensively utilized in the cosmetics industry. DHA production through the dephosphorylation of dihydroxyacetone phosphate, an intermediate product of the glycolysis pathway in Escherichia coli, presents a prospective alternative for industrial production. However, insights into the pivotal enzyme, dihydroxyacetone phosphate dephosphorylase (HdpA), remain limited for informed engineering. Consequently, the development of an efficient tool for high-throughput screening of HdpA hypermutants becomes imperative. Results This study introduces a methylglyoxal biosensor, based on the formaldehyde-responding regulator FrmR, for the selection of HdpA. Initial modifications involved the insertion of the FrmR binding site upstream of the −35 region and into the spacer region between the −10 and −35 regions of the constitutive promoter J23110. Although the hybrid promoter retained constitutive expression, expression of FrmR led to complete repression. The addition of 350 μM methylglyoxal promptly alleviated FrmR inhibition, enhancing promoter activity by more than 40-fold. The methylglyoxal biosensor system exhibited a gradual increase in fluorescence intensity with methylglyoxal concentrations ranging from 10 to 500 μM. Notably, the biosensor system responded to methylglyoxal spontaneously converted from added DHA, facilitating the separation of DHA producing and non-producing strains through flow cytometry sorting. Subsequently, the methylglyoxal biosensor was successfully applied to screen a library of HdpA mutants, identifying two strains harboring specific mutants 267G > T and D110G/G151C that showed improved DHA production by 68% and 114%, respectively. Expressing of these two HdpA mutants directly in a DHA-producing strain also increased DHA production from 1.45 to 1.92 and 2.29 g/L, respectively, demonstrating the enhanced enzyme properties of the HdpA mutants. Conclusions The methylglyoxal biosensor offers a novel strategy for constructing genetically encoded biosensors and serves as a robust platform for indirectly determining DHA levels by responding to methylglyoxal. This property enables efficiently screening of HdpA hypermutants to enhance DHA production.

Abstract Background Studies have revealed the effects of childhood adversity, anxiety, and negative coping on sleep quality in older adults, but few studies have focused on the association between childhood adversity and sleep quality in rural older adults and the potential mechanisms of this influence. In this study, we aim to evaluate sleep quality in rural older adults, analyze the impact of adverse early experiences on their sleep quality, and explore whether anxiety and negative coping mediate this relationship. Methods Data were derived from a large cross-sectional study conducted in Deyang City, China, which recruited 6,318 people aged 65 years and older. After excluding non-agricultural household registration and lack of key information, a total of 3,873 rural older adults were included in the analysis. Structural equation modelling (SEM) was used to analyze the relationship between childhood adversity and sleep quality, and the mediating role of anxiety and negative coping. Results Approximately 48.15% of rural older adults had poor sleep quality, and older adults who were women, less educated, widowed, or living alone or had chronic illnesses had poorer sleep quality. Through structural equation model fitting, the total effect value of childhood adversity on sleep quality was 0.208 (95% CI: 0.146, 0.270), with a direct effect value of 0.066 (95% CI: 0.006, 0.130), accounting for 31.73% of the total effect; the total indirect effect value was 0.142 (95% CI: 0.119, 0.170), accounting for 68.27% of the total effect. The mediating effects of childhood adversity on sleep quality through anxiety and negative coping were significant, with effect values of 0.096 (95% CI: 0.078, 0.119) and 0.024 (95% CI: 0.014, 0.037), respectively. The chain mediating effect of anxiety and negative coping between childhood adversity and sleep quality was also significant, with an effect value of 0.022 (95% CI: 0.017, 0.028). Conclusions Anxiety and negative coping were important mediating factors for rural older adult’s childhood adversity and sleep quality. This suggests that managing anxiety and negative coping in older adults may mitigate the negative effects of childhood adversity on sleep quality.

Abstract 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.

Abstract 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.

The application of a male-sterile line is an ideal approach for hybrid seed production in non-heading Chinese cabbage (Brassica rapa ssp. chinensis). However, the molecular mechanisms underlying male sterility in B. rapa are still largely unclear. We previously obtained the natural male sterile line WS24-3 of non-heading Chinese cabbage and located the male sterile locus, Bra2Ms, on the A2 chromosome. Cytological observations revealed that the male sterility of WS24-3 resulted from disruption of the meiosis process during pollen formation. Fine mapping of Bra2Ms delimited the locus within a physical distance of about 129 kb on the A2 chromosome of B. rapa. The Bra039753 gene encodes a plant homeodomain (PHD)-finger protein and is considered a potential candidate gene for Bra2Ms. Bra039753 was significantly downregulated in sterile line WS24-3 compared to the fertile line at the meiotic anther stage. Sequence analysis of Bra039753 identified a 369 bp fragment insertion in the first exon in male sterile plants, which led to an amino acid insertion in the Bra039753 protein. In addition, the 369 bp fragment insertion was found to cosegregate with the male sterility trait. This study identified a novel locus related to male sterility in non-heading Chinese cabbage, and the molecular marker obtained in this study will be beneficial for the marker-assisted selection of excellent sterile lines in non-heading Chinese cabbage and other Brassica crops.

Early identification of neonatal jaundice (NJ) appears to be essential to avoid bilirubin encephalopathy and neurological sequelae. The interaction between gut microbiota and metabolites plays an important role in early life. It is unclear whether the composition of the gut microbiota and metabolites can be used as an early indicator of NJ or to aid clinical decision-making. This study involved a total of 196 neonates and conducted two rounds of “discovery-validation” research on the gut microbiome-metabolome. It utilized methods of machine learning, causal inference, and clinical prediction model evaluation to assess the significance of gut microbiota and metabolites in classifying neonatal jaundice (NJ), as well as the potential causal relationships between corresponding clinical variables and NJ. In the discovery stage, NJ-associated gut microbiota, network modules, and metabolite composition were identified by gut microbiome-metabolome association analysis. The NJ-associated gut microbiota was closely related to bile acid metabolites. By Lasso machine learning assessment, we found that the gut bacteria were associated with abnormal bile acid metabolism. The machine learning-causal inference approach revealed that gut bacteria affected serum total bilirubin and NJ by influencing bile acid metabolism. NJ-associated gut bile acids are potential biomarkers of NJ, and clinical prediction models constructed based on these biomarkers have some clinical effects and the model may be used for disease risk prediction. In the validation stage, it was found that intestinal metabolites can predict NJ, and the machine learning-causal inference approach revealed that bile acid metabolites affected NJ itself by affecting the total bilirubin content. Intestinal bile acid metabolites are potential biomarkers of NJ. By applying machine learning-causal inference methods to gut microbiome-metabolome association studies, we found NJ-associated intestinal bacteria and their network modules and bile acid metabolite composition. The important role of intestinal bacteria and bile acid metabolites in NJ was determined, which can predict the risk of NJ.

A comprehensive evaluation of the relationship between the densities of various cell types in the breast cancer tumor microenvironment and patient prognosis is currently lacking. Additionally, the absence of a large patch-level whole slide imaging (WSI) dataset of breast cancer with annotated cell types hinders the ability of artificial intelligence to evaluate cell density in breast cancer WSI. We first employed Lasso-Cox regression to build a breast cancer prognosis assessment model based on cell density in a population study. Pathology experts manually annotated a dataset containing over 70,000 patches and used transfer learning based on ResNet152 to develop an artificial intelligence model for identifying different cell types in these patches. The results showed that significant prognostic differences were observed among breast cancer patients stratified by cell density score (P = 0.0018), with the cell density score identified as an independent prognostic factor for breast cancer patients (P < 0.05). In the validation cohort, the predictive performance for overall survival (OS) was satisfactory, with area under the curve (AUC) values of 0.893 (OS) at 1-year, 0.823 (OS) at 3-year, and 0.861 (OS) at 5-year intervals. We trained a robust model based on ResNet152, achieving over 99% classification accuracy for different cell types in patches. These achievements offer new public resources and tools for personalized treatment and prognosis assessment.

Abstract Due to rapid homogenization in habitat types as a result of urbanization, some urban birds adapt their nesting strategies to changes in local habitat characteristics. Bird nesting decisions might have been mainly linked to resource constraints and ensuring reproductive success. In this study, we examined patterns of nesting behavior by spotted doves (Spilopelia chinensis) in a rapidly urbanizing area of Nanchang, China using ArcGIS 10.8, satellite tracking, camera traps, and field survey. To explore the mechanisms underlying nesting behavior in urban habitats, we assessed the correlations between nest reuse and reproductive success, and between nest reuse and nest predation. From December 2018 to December 2021, a total of 302 breeding nests were surveyed. The results revealed that the nest reuse rate was 38.08% (n = 115). Nests closer to trunk, with lower nest position and higher large‐scale urbanization score tended to have higher reuse rate. In addition, nests with the higher the nest height and percent of canopy cover, and the lower small‐scale urbanization score were more likely to reproduce successfully, and the reused nests also reproduce more successfully. The reproductive success associated with nest reuse was significantly higher than that associated with new nests (χ2 = 8.461, p = .004). High degree of urbanization promoted nest reuse of spotted doves (large‐scale urbanization score, z = 2.094, p = .036), which apparently enhanced their reproductive success (nest reuse, z = 2.737, p = .006). In conclusion, a nest structure with good permeability is the material basis for the nest reuse in spotted dove, while the relatively low risk of predation in urban habitat and the scarcity of nest site resources due to urbanization increase the tendency of birds to reuse old nests, which is associated with their reproductive success and evolutionary fitness.

Abstract The fibrillation of amyloid‐β (Aβ) is the critical causal factor in Alzheimer's disease (AD), the dissolution and clearance of which are promising for AD therapy. Although many Aβ inhibitors are developed, their low Aβ‐binding affinity results in unsatisfactory effect. To solve this challenge, the Aβ sequence‐matching strategy is proposed to tail‐design dissociable nanosystem (B6‐PNi NPs). Herein, B6‐PNi NPs aim to improve Aβ‐binding affinity for effective dissolution of amyloid fibrils, as well as to interfere with the in vivo fate of amyloid for Aβ clearance. Results show that B6‐PNi NPs decompose into small nanostructures and expose Aβ‐binding sites in response to AD microenvironment, and then capture Aβ via multiple interactions, including covalent linkage formed by nucleophilic substitution reaction. Such high Aβ‐binding affinity disassembles Aβ fibrils into Aβ monomers, and induces the reassembly of Aβ&nanostructure composite, thereby promoting microglial Aβ phogocytosis/clearance via Aβ receptor‐mediated endocytosis. After B6‐PNi NPs treatment, the Aβ burden, neuroinflammation and cognitive impairments are relieved in AD transgenic mice. This work provides the Aβ sequence‐matching strategy for Aβ inhibitor design in AD treatment, showing meaningful insight in biomedicine.

Abstract 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

Abstract 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.

Phosphate removal is crucial for eutrophication control and water quality improvement. Electro-assisted adsorption, an eco-friendly electrosorption process, exhibited a promising potential for wastewater treatment. However, there are few works focused on phosphate electrosorption, and reported electrodes cannot attach satisfactory removal capacities and rates. Herein, electro-assisted adsorption of phosphate via in-situ construction of La active centers on hierarchically porous carbon (LaPC) has been originally demonstrated. The resulted LaPC composite not only possessed a hierarchically porous structure with uniformly dispersed La active sites, but also provided good conductivity for interfacial electron transfer. The LaPC electrode achieved an ultrahigh phosphate electrosorption capability of 462.01 mg g−1 at 1 V, outperforming most existing electrodes. The superior phosphate removal performance originates from abundant active centers formed by the coupling of electric field and capture sites. Besides, the stability and selectivity toward phosphate capture were maintained well even under comprehensive conditions. Moreover, a series of kinetics and isotherms models were employed to validate the electrosorption process. This work demonstrates a deep understanding and promotes a new level of phosphate electrosorption.

Abstract Background Multimorbidity is better prevented in younger ages than in older ages. This study aims to identify the differences in comorbidity patterns in middle-aged inpatients from China and the United Kingdom (UK). Methods We utilized 184,133 and 180,497 baseline hospitalization records in middle-aged populations (40–59 years) from Shaanxi, China, and UK Biobank. Logistic regression was used to calculate odds ratios and P values for 43,110 unique comorbidity patterns in Chinese inpatients and 21,026 unique comorbidity patterns in UK inpatients. We included the statistically significant (P values adjusted by Bonferroni correction) and common comorbidity patterns (the pattern with prevalence > 1/10,000 in each dataset) and employed network analysis to construct multimorbidity networks and compare feature differences in multimorbidity networks for Chinese and UK inpatients, respectively. We defined hub diseases as diseases having the top 10 highest number of unique comorbidity patterns in the multimorbidity network. Results We reported that 57.12% of Chinese inpatients had multimorbidity, substantially higher than 30.39% of UK inpatients. The complete multimorbidity network for Chinese inpatients consisted of 1367 comorbidities of 341 diseases and was 2.93 × more complex than that of 467 comorbidities of 215 diseases in the UK. In males, the complexity of the multimorbidity network in China was 2.69 × more than their UK counterparts, while the ratio was 2.63 × in females. Comorbidities associated with hub diseases represented 68.26% of comorbidity frequencies in the complete multimorbidity network in Chinese inpatients and 55.61% in UK inpatients. Essential hypertension, dyslipidemia, type 2 diabetes mellitus, and gastritis and duodenitis were the hub diseases in both populations. The Chinese inpatients consistently demonstrated a higher frequency of comorbidities related to circulatory and endocrine/nutritional/metabolic diseases. In the UK, aside from these comorbidities, comorbidities related to digestive and genitourinary diseases were also prevalent, particularly the latter among female inpatients. Conclusions Chinese inpatients exhibit higher multimorbidity prevalence and more complex networks compared to their UK counterparts. Multimorbidity with circulatory and endocrine/nutritional/metabolic diseases among both Chinese and UK inpatients necessitates tailored surveillance, prevention, and intervention approaches. Targeted interventions for digestive and genitourinary diseases are warranted for the UK.

Background The health effects of particulate matter with an aerodynamic diameter ≤2.5 μm (PM2.5) might differ depending on compositional variations. Little is known about the joint effect of PM2.5 constituents on metabolic syndrome and cardiovascular disease (CVD). This study aims to evaluate the combined associations of PM2.5 components with CVD, identify the most detrimental constituent, and further quantify the mediation effect of metabolic syndrome. Methods and Results A total of 14 427 adults were included in a cohort study in Sichuan, China, and were followed to obtain the diagnosis of CVD until 2021. Metabolic syndrome was defined by the simultaneous occurrence of multiple metabolic disorders measured at baseline. The concentrations of PM2.5 chemical constituents within a 1‐km2 grid were derived based on satellite‐ and ground‐based detection methods. Cox proportional hazard models showed that black carbon, organic matter (OM), nitrate, ammonium, chloride, and sulfate were positively associated with CVD risks, with hazard ratios (HRs) ranging from 1.24 to 2.11 (all P

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 0.65) 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.

Abstract 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.

PurposeTo 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 methodsThe 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.ResultsFollowing 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

Abstract It is unclear regarding associations of dietary patterns with a wide range of chronic diseases and which dietary score is more predictive of major chronic diseases. Using the UK Biobank, we examine associations of four individual healthy dietary scores with the risk of 48 individual chronic diseases. Higher Alternate Mediterranean Diet score is associated with a lower risk of 32 (all 8 cardiometabolic disorders, 3 out of 10 types of cancers, 7 out of 10 psychological/neurological disorders, 5 out of 6 digestive disorders, and 9 out of 14 other chronic diseases). Alternate Healthy Eating Index-2010 and Healthful Plant-based Diet Index are inversely associated with the risk of 29 and 23 individual chronic diseases, respectively. A higher Anti-Empirical Dietary Inflammatory Index is associated with a lower risk of 14 individual chronic diseases and a higher incidence of two diseases. Our findings support dietary guidelines for the prevention of most chronic diseases.

Abstract Background Dietary patterns are crucial for maintaining cognitive health among older people and can be modified through lifestyle interventions. We investigated the associations between dietary patterns, changes in these patterns over time, and cognitive function. Methods This cohort study utilized data from the Chinese Longitudinal Healthy Longevity Survey conducted between 2005 and 2014. The sample included 7472 participants (mean age: 81.45 ± 10.88 years). Dietary patterns were derived using cluster analysis. Cognitive function was assessed using the Mini‐Mental State Examination (MMSE). The relationships between dietary patterns/changes, MMSE scores, changes in MMSE scores, and cognitive impairment were analyzed using the generalized estimating equation method, linear regression, and logistic regression. Results Cluster analysis identified three major dietary patterns: balanced diet, relatively balanced diet, and unbalanced diet. Mean MMSE scores decreased from 24.71 ± 7.24 in 2005 to 22.22 ± 9.29 in 2008, then increased to 24.10 ± 7.76 in 2014. Participants who adhered to balanced diet patterns exhibited significantly higher MMSE scores (1.56; 95% confidence interval: 1.34, 1.78) than those who followed unbalanced diet patterns. This association was particularly prominent among older individuals, women, individuals with no education, and underweight individuals. Participants with relatively balanced or balanced diets showed a significantly lower risk of cognitive impairment (adjusted odds ratio (OR) = 0.72, 95% CI: 0.65, 0.80; OR = 0.47, 95% CI: 0.42, 0.53, respectively) than those with unbalanced diets. Transitioning from an unhealthy diet to a healthy diet was associated with a smaller decline in MMSE scores and reduced risk of cognitive impairment. Conclusions These findings emphasize the importance of balanced or relatively balanced diets in preserving cognitive health in older individuals. These patterns relate to better MMSE scores and reduced cognitive impairment risk. Shifting from unhealthy to healthy diets is linked to improved MMSE scores and lower cognitive impairment risk. These results underscore the importance of dietary interventions in mitigating cognitive decline in older adults. Further research is warranted to understand the underlying mechanisms and develop targeted strategies for promoting healthy dietary habits in this population.

Abstract Fasting blood glucose (FBG) and glycosylated hemoglobin (HbA1c) are key indicators reflecting blood glucose control in type 2 diabetes mellitus (T2DM) patients. The purpose of this study is to establish a predictive model for blood glucose changes in T2DM patients after 3 months of treatment, achieving personalized treatment.A retrospective study was conducted on type 2 diabetes mellitus real-world medical data from 4 cities in Sichuan Province, China from January 2015 to December 2020. After data preprocessing, data inputting, data sampling, and feature screening, 16 kinds of machine learning methods were used to construct prediction models, and 5 prediction models with the best prediction performance were screened respectively. A total of 100,000 cases were included to establish the FBG model, and 2,169 cases were established to establish the HbA1c model. The best prediction model both of FBG and HbA1c finally obtained are realized by ensemble learning and modified random forest inputting, the AUC values are 0.819 and 0.970, respectively. The most important indicators of the FBG and HbA1c prediction model were FBG and HbA1c. Medication compliance, follow-up outcome, dietary habits, BMI, and waist circumference also had a greater impact on FBG levels. The prediction accuracy of the models of the two blood glucose control indicators is high and has certain clinical applicability.HbA1c and FBG are mutually important predictors, and there is a close relationship between them.

Abstract Background Healthy China is a nationwide health strategy aiming at improving health from diverse dimensions, and strengthening high-quality assessment is essential for its stimulation. However, there is limited evidence in the surveillance of the actual performance of the initiative at regional levels. This study innovatively proposes a two-step surveillance process which comprehensively monitors Healthy China Initiative based on regional realities, thus provides guidance for policymaking. Methods A flexible indicator system was firstly developed basing on Delphi survey and focus group discussions. And then the Analysis Hierarchical Process and the TOPSIS method were used to determine the weights of indicators and calculate comprehensive indexes as the surveillance outcomes. A pilot study was conducted in a typical area in China to verify the applicability of the process. Results Following the surveillance process and basing on the implementation of Healthy China Initiative in the target region, an indicator system comprised of 5 domains and 23 indicators with weights was first developed specifically for the pilot area. Then 1848 interagency data of the study area were collected from 8 provincial institutions/departments to calculate the indexes and ranks of the five domains which were health level, healthy living, disease prevention and control, health service, and healthy environment. The outcomes showed that Healthy China Initiative in the pilot area had been constantly improved since the strategy proposed, while there were still issues to be tackled such as the deficient monitoring mechanisms and unevenly development progress. Conclusions This study proposed a pragmatic surveillance process with indicators which could be tailored for specific context of target regions and produce meaningful surveillance outcomes to inform decision-making for policymakers, and also provided a theoretical foundation as well as empirical evidence for further health strategies and plannings assessment studies.

Nucleic acid amphiphiles, referring to nucleic acids modified with large hydrophobic groups, have been widely used in programmable bioengineering. Since nucleic acids are intrinsically hydrophilic, the hydrophobic groups endow nucleic acid amphiphiles with unique properties, such as self-assembling, interactions with artificial or biological membranes, and transmembrane transport. Importantly, the hybridization or target binding capability of oligonucleotide itself supplies nucleic acid amphiphiles with excellent programmability. As a result, this type of molecule has attracted considerable attention in academic studies and has enormous potential for further applications. For a comprehensive understanding of nucleic acid amphiphiles, we review the reported research on nucleic acid amphiphiles from their molecular design to final applications, in which we summarize the synthetic strategies for nucleic acid amphiphiles and draw much attention to their unique properties in different contexts. Finally, a summary of the applications of nucleic acid amphiphiles in drug development, bioengineering, and bioanalysis are critically discussed.

With the increase in port throughput and the development of the trend of large-scale ships, selecting applicable anchor positions for ships and ensuring the rational and comprehensive utilization of anchorage areas have become a key issue in utilizing the rate of anchorage resources, ensuring the safety of ships anchoring operations and promoting the development of the shipping industry. Existing anchor position selection and detection algorithm studies are limited to a two-dimensional plane for ship anchor position selection, with few studies considering intelligent detection algorithms for safe ship anchoring water depths based on three-dimensional space, considering conditions such as wind and waves. By considering water depth conditions and the objectives of anchorage safety issues, this study proposes an intelligent detection method for ship anchor detection to find the ship’s ideal anchor location in the anchorages by applying the Monte Carlo algorithm. In the processing step, in combination with the Monte Carlo random plane anchor position detection algorithm and Monte Carlo random sampling water depth detection method, the anchor position circle radius model, safe spacing model, anchoring area detection model and safe water depth model are used for examining the anchorage area for awaiting the ship in three-dimensions. To verify the accuracy of the proposed model, based on the scale of common ship types and considering the most conservative parameters, a series of simulation experiments are conducted to check whether the water depth meets the requirements and fully ensure the safety of the experimental results. The research results indicate that the detection almost cover the whole anchorage area and obtain safe water depth restrictions. This method helps to improve the efficiency of ship anchoring and makes actual anchoring operations safer. Under the premise of ensuring sufficient safe spacing between ships, the anchorage ground can accommodate more ships and simulate multi-type ship anchor position detection operations concerning various ship-type parameters to further ensure the safety of ship anchoring.

Background: while most gut microbiota research has focused on term infants, the health outcomes of preterm infants are equally important. Very-low-birth-weight (VLBW) or extremely-low-birth-weight (ELBW) preterm infants have a unique gut microbiota structure, and probiotics have been reported to somewhat accelerate the maturation of the gut microbiota and reduce intestinal inflammation in very-low preterm infants, thereby improving their long-term outcomes. The aim of this study was to investigate the structure of gut microbiota in ELBW neonates to facilitate the early identification of different types of low-birth-weight (LBW) preterm infants. Methods: a total of 98 fecal samples from 39 low-birth-weight preterm infants were included in this study. Three groups were categorized according to different birth weights: ELBW (n = 39), VLBW (n = 39), and LBW (n = 20). The gut microbiota structure of neonates was obtained by 16S rRNA gene sequencing, and microbiome analysis was conducted. The community state type (CST) of the microbiota was predicted, and correlation analysis was conducted with clinical indicators. Differences in the gut microbiota composition among ELBW, VLBW, and LBW were compared. The value of gut microbiota composition in the diagnosis of extremely low birth weight was assessed via a random forest-machine learning approach. Results: we briefly analyzed the structure of the gut microbiota of preterm infants with low birth weight and found that the ELBW, VLBW, and LBW groups exhibited gut microbiota with heterogeneous compositions. Low-birth-weight preterm infants showed five CSTs dominated by Enterococcus, Staphylococcus, Klebsiella, Streptococcus, Pseudescherichia, and Acinetobacter. The birth weight and clinical indicators related to prematurity were associated with the CST. We found the composition of the gut microbiota was specific to the different types of low-birth-weight premature infants, namely, ELBW, VLBW, and LBW. The ELBW group exhibited significantly more of the potentially harmful intestinal bacteria Acinetobacter relative to the VLBW and LBW groups, as well as a significantly lower abundance of the intestinal probiotic Bifidobacterium. Based on the gut microbiota’s composition and its correlation with low weight, we constructed random forest model classifiers to distinguish ELBW and VLBW/LBW infants. The area under the curve of the classifiers constructed with Enterococcus, Klebsiella, and Acinetobacter was found to reach 0.836 by machine learning evaluation, suggesting that gut microbiota composition may be a potential biomarker for ELBW preterm infants. Conclusions: the gut bacteria of preterm infants showed a CST with Enterococcus, Klebsiella, and Acinetobacter as the dominant genera. ELBW preterm infants exhibit an increase in the abundance of potentially harmful bacteria in the gut and a decrease in beneficial bacteria. These potentially harmful bacteria may be potential biomarkers for ELBW preterm infants.

Abstract Base editing technology is an ideal solution for treating pathogenic single-nucleotide variations (SNVs). No gene editing therapy has yet been approved for eye diseases, such as retinitis pigmentosa (RP). Here, we show, in the rd10 mouse model, which carries an SNV identified as an RP-causing mutation in human patients, that subretinal delivery of an optimized dual adeno-associated virus system containing the adenine base editor corrects the pathogenic SNV in the neuroretina with up to 49% efficiency. Light microscopy showed that a thick and robust outer nuclear layer (photoreceptors) was preserved in the treated area compared with the thin, degenerated outer nuclear layer without treatment. Substantial electroretinogram signals were detected in treated rd10 eyes, whereas control treated eyes showed minimal signals. The water maze experiment showed that the treatment substantially improved vision-guided behavior. Together, we construct and validate a translational therapeutic solution for the treatment of RP in humans. Our findings might accelerate the development of base-editing based gene therapies.

Abstract Genetic improvement of grain quality is more challenging in hybrid rice than in inbred rice due to additional nonadditive effects such as dominance. Here, we describe a pipeline developed for joint analysis of phenotypes, effects, and generations (JPEG). As a demonstration, we analyze 12 grain quality traits of 113 inbred lines (male parents), five tester lines (female parents), and 565 (113×5) of their hybrids. We sequence the parents for single nucleotide polymorphisms calling and infer the genotypes of the hybrids. Genome-wide association studies with JPEG identify 128 loci associated with at least one of the 12 traits, including 44, 97, and 13 loci with additive effects, dominant effects, and both additive and dominant effects, respectively. These loci together explain more than 30% of the genetic variation in hybrid performance for each of the traits. The JEPG statistical pipeline can help to identify superior crosses for breeding rice hybrids with improved grain quality.

Abstract Background Upregulation of the PD-L1 (CD274) immune checkpoint ligand on the tumor surface facilitates tumor immune escape and limits the application of immunotherapy in various cancers, including breast cancer. However, the mechanisms underlying high PD-L1 levels in cancers are still poorly understood. Methods Bioinformatics analyses and in vivo and in vitro experiments were carried out to assess the association between CD8+ T lymphocytes and TIMELESS (TIM) expression, and to discover the mechanisms of TIM, the transcription factor c-Myc, and PD-L1 in breast cancer cell lines. Results The circadian gene TIM enhanced PD-L1 transcription and facilitated the aggressiveness and progression of breast cancer through the intrinsic and extrinsic roles of PD-L1 overexpression. Bioinformatic analyses of our RNA sequencing data in TIM-knockdown breast cancer cells and public transcriptomic datasets showed that TIM might play an immunosuppressive role in breast cancer. We found that TIM expression was inversely associated with CD8+ T lymphocyte infiltration in human breast cancer samples and subcutaneous tumor tissues. In vivo and in vitro experiments demonstrated that TIM knockdown increased CD8+ T lymphocyte antitumor activity. Furthermore, our results showed that TIM interacts with c-Myc to enhance the transcriptional capability of PD-L1 and facilitates the aggressiveness and progression of breast cancer through the intrinsic and extrinsic roles of PD-L1 overexpression. Moreover, public database analysis suggested that high TIM levels were positively related to PD-L1 inhibitor therapeutic response. Conclusions Mechanistically, we first found that TIM could upregulate PD-L1 by interacting with c-Myc to enhance the transcriptional capability of c-Myc to PD-L1. Altogether, our findings not only provide a novel therapeutic strategy to treat breast cancer by targeting the oncogenic effect of TIM but also indicate that TIM is a promising biomarker for predicting the benefit of anti-PD-L1 immunotherapy.

Glucosinolates (GSLs) and their hydrolytic products contribute to the quality traits of rapeseed flowering stalk tissues, such as taste, flavor and anticarcinogenic properties (Glucoraphanin). However, little is known about the genetic mechanisms of GSL accumulation in rapeseed flowering stalks. In this study, the variation and genetic architecture of GSL metabolites in flowering stalk tissues were investigated for the first time among a panel of 107 accessions. All GSL compounds exhibited continuous and wide variations in the present population. Progoitrin, glucobrassicanapin and gluconapin were the most abundant GSL compounds. Five quantitative trait loci (QTL) significantly associated with three GSL compounds were identified by genome-wide association study. GRA_C04 was under selected during modern breeding, in which the ratio of lower GSL haplotype (HAP2) in the accessions bred before 1990 (52.56%) was significantly lower than that after 1990 (78.95%). Four candidate genes, BnaA01. SOT16, BnaA06. SOT17, BnaA06. MYB51a, and BnaA06. MYB51b, were identified in the GTL_A01 and 4OH_A06 regions. These findings provide new insights into GSL biosynthesis in flowering stalk tissues and facilitate quality improvement in rapeseed flowering stalks.

Abstract The rapidly evolving landscape of biomarkers for colorectal cancer (CRC) necessitates an integrative, updated repository. In response, we constructed the Colorectal Cancer Biomarker Database (CBD), which collected and displayed the curated biomedicine information for 870 CRC biomarkers in the previous study. Building on CBD, we have now developed CBD2, which includes information on 1569 newly reported biomarkers derived from different biological sources (DNA, RNA, protein, and others) and clinical applications (diagnosis, treatment, and prognosis). CBD2 also incorporates information on nonbiomarkers that have been identified as unsuitable for use as biomarkers in CRC. A key new feature of CBD2 is its network analysis function, by which users can investigate the visible and topological network between biomarkers and identify their relevant pathways. CBD2 also allows users to query a series of chemicals, drug combinations, or multiple targets, to enable multidrug, multitarget, multipathway analyses, toward facilitating the design of polypharmacological treatments for CRC. CBD2 is freely available at http://www.eyeseeworld.com/cbd.

IntroductionAbiotic 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).MethodsIn 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 discussionWe 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.

BackgroundData regarding the association between antioxidant supplementation and incident dementia are limited.MethodsWe included 494,632 adults (54.5% females) aged 40–71 years at baseline from the United Kingdom Biobank in the final analysis. Incident dementia was ascertained using hospital inpatient and death records up to January 2021.ResultsOver a median follow-up of 11.9 years, 7,128 new cases of all-cause dementia, 2,772 cases of Alzheimer’s disease, and 1,397 cases of vascular dementia were recorded. The hazard ratio (95% CI) for incident dementia associated with zinc supplementation was 0.84 (0.74–0.96), and the association remained significant after adjusting for all confounders (0.84 (0.74–0.96)). In the full model, zinc supplementation was associated with a reduced risk of Alzheimer’s disease [HR (95% CI): 0.71 (0.57–0.88)]. There was no significant association between zinc supplementation and the risk of vascular dementia. No significant associations with incident dementia were observed for other antioxidant supplementation. The association between zinc supplementation and incident dementia was significant among individuals with [HR (95% CI): 0.34 (0.15–0.77)] and without cataract [0.87 (0.77–0.99)] but it was stronger among those with cataract (p value for interaction = 0.0271).ConclusionOur findings suggest that zinc supplementation may help reduce the risk of all-cause dementia and Alzheimer’s disease in middle-aged or older adults, especially among those with cataracts.

Objectives: The purpose of this study is to describe the current situation and forecast the trends of co-infection between the human immunodeficiency virus (HIV) and drug-susceptible tuberculosis (DS-TB) in different countries, across various age groups and genders. Methods: We obtained data on the number of cases, age-standardized incidence rate, age-standardized prevalence rate, age-standardized rate of disability-adjusted life years (DALYs), and age-standardized death rate from the Global Burden of Disease (GBD) 2019 database. These data were used to describe the distribution and burden of co-infection between the human immunodeficiency virus (HIV) and DS-TB in different regions, genders, and age groups. We employed joinpoint regression analysis to analyze the temporal trends from 1990 to 2019. Additionally, an age-period-cohort model was established to forecast the future trends of co-infection up to 2040. Results: The prevalence and burden of co-infection varied across different age groups and genders. The territories with the higher disease burden were distributed in some Asian and African countries. In terms of temporal trends, the age-standardized incidence rate and age-standardized prevalence rate of HIV and DS-TB co-infection exhibited an overall increasing trend from 1990 to 2019, and the prediction indicated a slow downward trend from 2019 to 2040. Conclusions: The co-infection of HIV and DS-TB posed a grave threat to public health and economic development. What’s more, there existed a significant disparity between the actual state of co-infection and the desired goals for prevention and control.

BackgroundIschemic stroke has the characteristics of high morbidity, mortality, and recurrence rate. This study aimed to describe and assess the burden of ischemic stroke in Asia based on the global burden of disease (GBD) 2019 data and provide a crucial scientific foundation for the prevention and control of this life-threatening disease.MethodThis study used the GBD 2019 data to assess the burden of ischemic stroke. The indicators used in this study were derived from the following methods: (i) the incidence of ischemic stroke was estimated using the disability model for the global burden of disease study-mixed effects regression (DisMod-MR), a Bayesian meta-regression disease modeling tool; (ii) the non-specific codes of all available data on mortality were corrected and used to estimate mortality rates for ischemic stroke and the cause of death ensemble model was used to estimate mortality rates; and (iii) the disability-adjusted life years (DALYs) is the sum of years lived with disability (YLD) and the years of life lost (YLL), which quantifies the health loss due to specific diseases and injuries. In addition, the joinpoint regression model was adopted to analyze the temporal trend of ischemic stroke from 1990 to 2019 in Asia.ResultThis study found an increase in the burden of ischemic stroke in 2019 compared to 1990. Moreover, the age-standardized incidence rate (ASIR) of ischemic stroke showed a gradual upward trend over the specific period. The age-standardized mortality rate (ASMR) showed a downward trend in Asia from 1990 to 2019. The burden of ischemic stroke was more concentrated on older age groups, particularly those older than 65 years. East Asia had the highest burden of ischemic stroke compared to other regions in Asia. Particularly, China, India, Indonesia, and Japan had the highest burdens of ischemic stroke among the Asian countries and regions. However, the population with the highest burden of ischemic stroke was still the elderly group.ConclusionBased on our study, it is evident that the burden of ischemic stroke exists substantially and exhibits variations in the aspects of age, gender, and geographical region in Asia. Without targeted implementation of population-wide primary strategies for prevention and control, the burden of ischemic stroke is likely to worsen significantly in the future.

BackgroundClonorchis sinensis (C. sinensis) is a epidemiologically significant food-borne parasite, causing several hepatobiliary diseases. Biliary microbiota community structure might be influenced by infection with pathogens. However, the biliary microbiome of biliary obstruction patients infected with C. sinensis is still an unexplored aspect.MethodsA total of 50 biliary obstruction patients were enrolled, including 24 infected with C. sinensis and 26 non-infected subjects. The bile samples were collected by Endoscopic Retrograde Cholangiopancretography. Biliary microbiota alteration was analyzed through high-throughput 16S ribosomal RNA (rRNA) gene sequencing.ResultsOur findings revealed that there was significant increase in both richness and diversity, as well as changes in the taxonomic composition of the biliary microbiota of C. sinensis infected patients. At the phylum level, C. sinensis infection induced Proteobacteria increased and Firmicutes reduced. At the genus level, the relative abundance of Pseudomonas and Staphylococcus increased significantly, while Enterococcus decreased prominently in infected groups (P < 0.05). The PICRUSt analysis further showed remarkably different metabolic pathways between the two groups.ConclusionC. sinensis infection could modify the biliary microbiota, increasing the abundance and changing the phylogenetic composition of bacterial in biliary obstruction patients. This study may help deepen the understanding of the host-biliary microbiota interplay with C. sinensis infection on the background of biliary obstruction and provide new insights into understanding the pathogenesis of clonorchiasis.

Abstract C-to-G base editors have been successfully constructed recently, but limited work has been done on concurrent C-to-G and A-to-G base editing. In addition, there is also limited data on how chromatin-associated factors affect the base editing. Here, we test a series of chromatin-associated factors, and chromosomal protein HMGN1 was found to enhance the efficiency of both C-to-G and A-to-G base editing. By fusing HMGN1, GBE and ABE to Cas9, we develop a CRISPR-based dual-function A-to-G and C-to-G base editor (GGBE) which is capable of converting simultaneous A and C to G conversion with substantial editing efficiency. Accordingly, the HMGN1 role shown in this work and the resulting GGBE tool further broaden the genome manipulation capacity of CRISPR-directed base editors.

Abstract Colonocyte metabolism shapes the microbiome. Metabolites are the main mediators of information exchange between intestine and microbial communities. Arachidonic acid (AA) is an essential polyunsaturated fatty acid and its role in colorectal cancer (CRC) remains unexplored. In this study, we show that AA feeding promotes tumor growth in AOM/DSS and intestinal specific Apc −/− mice via modulating the intestinal microecology of increased gram-negative bacteria. Delta-5 desaturase (FADS1), a rate-limiting enzyme, is upregulated in CRC and effectively mediates AA synthesis. Functionally, FADS1 regulates CRC tumor growth via high AA microenvironment-induced enriched gram-negative microbes. Elimination of gram-negative microbe abolishes FADS1 effect. Mechanistically, gram-negative microbes activate TLR4/MYD88 pathway in CRC cells that contributes FADS1-AA axis to metabolize to prostaglandin E2 (PGE2). Cumulatively, we report a potential cancer-promoting mechanism of FADS1-AA axis in CRC that converts raising synthesized AA to PGE2 via modulating the intestinal microecology of gram-negative.

There is no targeted therapy for KRAS proto‐oncogene, GTPase (KRAS)‐mutant metastatic colorectal cancer (mCRC) because the underlying mechanism remains obscure. Based on bioinformatic analysis, this study aims to elucidate a potential gene target for which an approved drug is available, and to reveal the function as well as the underlying mechanism of the candidate gene. Here, we identified that ryanodine receptor 2 (RyR2) expression was upregulated in KRAS‐mutant mCRC, and that this promoted cancer cell metastasis. S107, an approved drug to inhibit calcium release from RyR2 in the clinic, inhibited cancer cell metastasis both in vitro and in vivo. High expression of RyR2 predicts poor survival in our patient cohort. CRC patients with serosa invasion and vascular tumor thrombus are characterized by high RyR2 expression. Analysis of expression profiles upon RyR2 knockdown and inhibition, revealed a set of metastasis‐related molecules, and identified BTB domain and CNC homolog 1 (BACH1) as the main transcription factor regulated by RyR2. RyR2 regulates cellular reactive oxygen species (ROS) levels, which activates nuclear factor erythroid 2‐related factor 2 (Nrf2; also known as NFE2L2) and HMOX1 expression, and thus BACH1 accumulation. Collectively, this study provides evidence that the RyR2/ROS/BACH1 axis may be a potential intervention target for CRC metastasis.

Abstract Background We evaluated the diagnostic efficacy of deep learning radiomics (DLR) and hand-crafted radiomics (HCR) features in differentiating acute and chronic vertebral compression fractures (VCFs). Methods A total of 365 patients with VCFs were retrospectively analysed based on their computed tomography (CT) scan data. All patients completed MRI examination within 2 weeks. There were 315 acute VCFs and 205 chronic VCFs. Deep transfer learning (DTL) features and HCR features were extracted from CT images of patients with VCFs using DLR and traditional radiomics, respectively, and feature fusion was performed to establish the least absolute shrinkage and selection operator. The MRI display of vertebral bone marrow oedema was used as the gold standard for acute VCF, and the model performance was evaluated using the receiver operating characteristic (ROC).To separately evaluate the effectiveness of DLR, traditional radiomics and feature fusion in the differential diagnosis of acute and chronic VCFs, we constructed a nomogram based on the clinical baseline data to visualize the classification evaluation. The predictive power of each model was compared using the Delong test, and the clinical value of the nomogram was evaluated using decision curve analysis (DCA). Results Fifty DTL features were obtained from DLR, 41 HCR features were obtained from traditional radiomics, and 77 features fusion were obtained after feature screening and fusion of the two. The area under the curve (AUC) of the DLR model in the training cohort and test cohort were 0.992 (95% confidence interval (CI), 0.983-0.999) and 0.871 (95% CI, 0.805-0.938), respectively. While the AUCs of the conventional radiomics model in the training cohort and test cohort were 0.973 (95% CI, 0.955-0.990) and 0.854 (95% CI, 0.773-0.934), respectively. The AUCs of the features fusion model in the training cohort and test cohort were 0.997 (95% CI, 0.994-0.999) and 0.915 (95% CI, 0.855-0.974), respectively. The AUCs of nomogram constructed by the features fusion in combination with clinical baseline data were 0.998 (95% CI, 0.996–0.999) and 0.946 (95% CI, 0.906–0.987) in the training cohort and test cohort, respectively. The Delong test showed that the differences between the features fusion model and the nomogram in the training cohort and the test cohort were not statistically significant (P values were 0.794 and 0.668, respectively), and the differences in the other prediction models in the training cohort and the test cohort were statistically significant (P

The Loess Plateau region of China suffers from severe soil erosion, and the selection of effective slope-protection vegetation is essential to prevent soil and water loss. This study focused on individual plants of common species in the Loess Plateau, such as Caragana korshinski Kom., Hippophae rhamnoides Linn., Pinus tabuliformis Carr., Robinia Pseudoacacia Linn., Populus tomentosa Carr., Prunus armeniaca Lam. The root spatial distribution, geometric morphology, and fractal characteristics of these plants were measured using the whole-root-excavation method, and the vertical pull-out force of their root systems was quantified using the in situ whole-plant root-pulling method. The results showed that H. rhamnoides dominates in the vertical spatial distribution of its root system through a larger number of inclined roots. C. korshinskii, P. tomentosa, R. pseudoacacia, and P. armeniaca dominate in the horizontal spatial distribution of their root systems through a greater number of horizontal roots. P. tabuliformis, on the other hand, achieves a relatively balanced distribution in both horizontal and vertical spaces through its well-developed taproot and numerous lateral roots. In terms of the geometric morphology and fractal characteristics of their root systems, H. rhamnoides and C. korshinskii exhibit a larger number of fine roots and complex branching, resulting in a higher total-root length, total-root surface area, and root fractal dimension. The soil-stabilizing ability of H. rhamnoides, C. korshinskii, and R. pseudoacacia was stronger, mainly influenced by their total-root length, total-root surface area, and inclined root quantity, and these species can be prioritized as typical vegetation for soil and water conservation in the construction of Loess Plateau vegetation. From the perspective of slope stabilization and soil conservation alone, we strongly recommend planting shrub vegetation in the Chinese Loess Plateau.

A modified plastic Burgers model considering cohesion decay is proposed for frozen soils. A series of triaxial compression and creep tests were conducted on a kind of frozen silty clay for obtaining the model parameters. According to typical triaxial creep strain curves with only a decaying creep stage, a deformation parameter calibration method for a plastic Burgers model is proposed, and the validity of the method was further verified. When the original plastic Burgers model was incorporated with a cohesion decay function, it was shown that the successive development process of frozen soil creep strain from the decaying to non-decaying stage could be described reasonably. The modified model is applicable to frozen ground engineering cases with non-decaying creep involved.