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Photoreduction of CO2 into value‐added chemicals and fuels is a promising green technology for solar‐to‐chemical conversion. Owing to the atomic utilization, unique metal‐support interaction, and unsaturated coordination active sites, single‐atom catalysts (SACs) have been attracting great attention in achieving high activity and selectivity of CO2 photoreduction reactions. On the other hand, carbon nitride (C3N4) with abundant periodically unsaturated coordination of nitrogen atoms can serve as an excellent support for anchoring metal single atoms. In this context, extensive research efforts have been paid in C3N4‐based SACs for CO2 photoreduction in recent years. In this review, we report the recent advances in C3N4 supported SACs for CO2 photoreduction. We start from the introduction of synthetic strategies of various C3N4 supported metal SACs. Secondly, the main advanced characterization techniques and calculation methods for identifying the single‐atoms and their coordination environments of C3N4‐based SACs are summarized. Thirdly, some state‐of‐the‐art works on the rational design of C3N4‐based SACs and their applications in CO2 photoreduction are introduced. Lastly, we briefly summarize the main challenges and propose important perspectives of C3N4‐based SACs in CO2 photoreduction. This review is expected to provide some useful guidelines for the development of efficient and stable C3N4‐based SACs for CO2 photoreduction. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to develop and validate a predictive model for osteoporotic vertebral fractures (OVFs) risk by integrating demographic, bone mineral density (BMD), CT imaging, and deep learning radiomics features from CT images. Methods: A total of 169 osteoporosis-diagnosed patients from three hospitals were randomly split into OVFs (n = 77) and Non-OVFs (n = 92) groups for training (n = 135) and test (n = 34). Demographic data, BMD, and CT imaging details were collected. Deep transfer learning (DTL) using ResNet-50 and radiomics features were fused, with the best model chosen via logistic regression. Cox proportional hazards models identified clinical factors. Three models were constructed: clinical, radiomics-DTL, and fusion (clinical-radiomics-DTL). Performance was assessed using AUC, C-index, Kaplan–Meier, and calibration curves. The best model was depicted as a nomogram, and clinical utility was evaluated using decision curve analysis (DCA). Results: BMD, CT values of paravertebral muscles (PVM), and paravertebral muscles' cross-sectional area (CSA) significantly differed between OVFs and Non-OVFs groups (P < 0.05). No significant differences were found between training and test cohort. Multivariate Cox models identified BMD, CT values of PVM, and CSAPS reduction as independent OVFs risk factors (P < 0.05). The fusion model exhibited the highest predictive performance (C-index: 0.839 in training, 0.795 in test). DCA confirmed the nomogram's utility in OVFs risk prediction. Conclusion: This study presents a robust predictive model for OVFs risk, integrating BMD, CT data, and radiomics-DTL features, offering high sensitivity and specificity. The model's visualizations can inform OVFs prevention and treatment strategies. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Aim: This study investigated the depot‐ and sex‐specific associations of adiposity indicators with incident multimorbidity and comorbidity pairs. Materials and Methods: We selected 382 678 adults without multimorbidity (≥2 chronic diseases) at baseline from the UK Biobank. General obesity, abdominal obesity and body fat percentage indices were measured. Results: Cox proportional hazard regression analyses of general obesity indices revealed that for every one‐unit increase in body mass index, the risk of incident multimorbidity increased by 5.2% (95% confidence interval 5.0%‐5.4%). A dose‐response relationship was observed between general obesity degrees and incident multimorbidity. The analysis of abdominal obesity indices showed that for every 0.1 increment in waist‐to‐height ratio and waist‐to‐hip ratio, the risk of incident multimorbidity increased by 42.0% (37.9%‐46.2%) and 27.9% (25.7%‐30.0%), respectively. Central obesity, as defined by waist circumference, contributed to a 23.2% increased risk of incident multimorbidity. Hip circumference and hip‐to‐height ratio had protective effects on multimorbidity onset. Consistent findings were observed for males and females. Body fat percentage elevated 3% (0.2%‐5.9%) and 5.3% (1.1%‐9.7%) risks of incident multimorbidity in all adults and females, respectively. Arm fat percentages elevated 5.3% (0.8%‐9.9%) and 19.4% (11.0%‐28.5%) risks of incident multimorbidity in all adults and males, respectively. The general obesity indices, waist circumference, waist‐to‐height ratio, waist‐to‐hip ratio and central obesity increased the onset of comorbidity pairs, whereas hip circumference and hip‐to‐height ratio decreased the onset of comorbidity pairs. These adiposity indicators mainly affect diabetes mellitus‐related comorbidity onset in males and hypertensive‐related comorbidity onset in females. Conclusions: Adiposity indicators are predictors of multimorbidity and comorbidity pairs and represent a promising approach for intervention. [ABSTRACT FROM AUTHOR]

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 FROM AUTHOR]

This article discusses effective strategies for creating self-compatible Brassica rapa (Chinese cabbage) plants by introducing mutated SRK and SCR/SP11 genes from Brassica napus (rapeseed). Self-incompatibility (SI) is a common trait in Brassica vegetable crops, but it hinders the development and propagation of inbred lines. The manipulation of SI genes, such as SRK and SCR/SP11, can lead to the creation of self-compatible materials. The researchers used CRISPR/Cas9 technology to mutate the BnSRK-1 gene in B. napus and then employed distant hybridization to introduce the mutated gene into B. rapa, resulting in the generation of self-compatible materials. This research has important implications for improving the breeding process of Brassica vegetable crops. [Extracted from the article]

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 FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

In this study, a computer-aided diagnosis (CAD) system for whole-slide images (WSIs) with breast cancer was proposed to achieve lesion detection and classification. Different from the previously proposed works that performed segmentation directly and applied the segmentation metrics for performance evaluation, here we computed the accuracy in patch-level, region-level, and slide-level to access our proposed framework to meet the clinical requirements, instead of simply regarding it as an AI segmentation task. To achieve that for WSIs, lesion detection was conducted at high magnification (× 40) first for region proposal by patching using the modified AlexNet model; and then, several patches were sampled from the detected regions at lower magnification (× 10) to observe cells' patterns for lesion classification by the model of ResNet50. With such fashion, the deep features being distinguishing in lesion classification from the convolutional neural networks (CNN) were further analyzed in this work to provide comprehensive interpretability for the proposed CAD system based on pathological knowledge. For our experiments, a total of 186 slides of WSIs were collected and classified into three categories: Non-Carcinoma, Ductal Carcinoma in Situ (DCIS), and Invasive Ductal Carcinoma (IDC). The slide-level accuracy rate for the three-category classification reached 90.8% (99/109) through a fivefold cross-validation and achieved 94.8% (73/77) on the testing set. In addition, the learned features reflect the clinical insights in lesion classification for explainable AI, which enhanced the reliability and validity of our proposed system. [ABSTRACT FROM AUTHOR]

The amine-based cobalt phthalocyanine loaded titanium dioxide nanocomposite (α-nBACoPc/TiO2) was synthesized utilizing a one-pot method. Afterward, a thorough analysis of the nanocomposites' structural and optical properties was conducted. The crystalline character of the composite is shown by X-ray powder diffraction. The successful synthesis of α-nBACoPc/TiO2 nanomaterials was validated by infrared spectroscopy. The samples' optical studies reveal a gradual diminution of the composites' optical band gap. Nanocomposites were used in the degradation of synthetic dyes (rhodamine B), and it was discovered that after 150 min of simulating sunlight exposure, the composite α-nBACoPc/TiO2 (2:100) exhibited the best degradation; about 90% of the organic material had been broken down. This may be due to the synergistic action of α-nBACoPc and TiO2, which significantly increases the efficiency of light utilization. The ideal properties of positive catalytic activity of the central ion and high specific surface area of the composite accelerate charge transport and reduce charge complexation. Cycling experiments have demonstrated the good stability of the nanocomposite. The potential of nanocomposites (α-nBACoPc/TiO2) in the area of industrial waste dye degradation is thus confirmed by this investigation. [ABSTRACT FROM AUTHOR]

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 FROM AUTHOR]

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 FROM AUTHOR]

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 FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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 FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Colorectal cancer (CRC) is the most prevalent malignancy of the digestive system. Glucose metabolism plays a crucial role in CRC development. However, the heterogeneity of glucose metabolic patterns in CRC is not well characterized. Here, we classified CRC into specific glucose metabolic subtypes and identified the key regulators. 2228 carbohydrate metabolism‐related genes were screened out from the GeneCards database, 202 of them were identified as prognosis genes in the TCGA database. Based on the expression patterns of the 202 genes, three metabolic subtypes were obtained by the non‐negative matrix factorization clustering method. The C1 subtype had the worst survival outcome and was characterized with higher immune cell infiltration and more activation in extracellular matrix pathways than the other two subtypes. The C2 subtype was the most prevalent in CRC and was characterized by low immune cell infiltration. The C3 subtype had the smallest number of individuals and had a better prognosis, with higher levels of NRF2 and TP53 pathway expression. Secreted frizzled‐related protein 2 (SFRP2) and thrombospondin‐2 (THBS2) were confirmed as biomarkers for the C1 subtype. Their expression levels were elevated in high glucose condition, while their knockdown inhibited migration and invasion of HCT 116 cells. The analysis of therapeutic potential found that the C1 subtype was more sensitive to immune and PI3K‐Akt pathway inhibitors than the other subtypes. To sum up, this study revealed a novel glucose‐related CRC subtype, characterized by SFRP2 and THBS2, with poor prognosis but possible therapeutic benefits from immune and targeted therapies. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. Highlights: CBD2 integrates biomarkers derived from diverse biological sources and clinical applications, employing a standardized approach for annotation and classification.CBD2 facilitates precision medicine in colorectal cancer by providing abundant data, including drug–target information and visualized network analysis functions.With its user‐friendly interface, CBD2 aids in the identification and development of biomarkers for colorectal cancer. [ABSTRACT FROM AUTHOR]

Based on the classic Keynesian theory of money demand and city panel data, in this study, we investigate the impacts of different money demand motives on urban household consumption in China, and provide ideas for promoting sustainable growth in household consumption in China. The results of this study show the following: First, in general, the theory of money demand motivation can adequately explain household consumption in large and medium-sized cities in China. Second, the CPI time series has a significant adverse effect on the real money demand of most households. Third, residents significantly reduce food consumption to satisfy speculative money demand for financial instruments, and the lower the income level, the keener households are to invest in high-risk stocks. Fourth, even for high-income households, the precautionary money demand generated via the purchase of commercial insurance still has a significant crowding-out effect on their total consumption. Social security spending, which reduces the precautionary money demand of households, has a much more positive impact on high-income households. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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 FROM AUTHOR]

The relationship between climate change and extreme precipitation is extremely complex. From a probabilistic perspective, a proper understanding of the response of extreme precipitation to climate change is of significant importance. This study was based on daily precipitation provided by CMIP6 climate models and employed copula functions to construct joint distributions of precipitation amount and precipitation intensity indices at different quantile levels. A spatial–temporal assessment of the susceptibility areas for extreme precipitation in the Yellow River Basin was conducted while considering bivariate return periods and design values. The results indicate that there were significant spatial differences in the bivariate return periods. Taking the R90P-SDII (90) index for a 20a return period as an example, the difference between the maximum and minimum joint return periods within the Yellow River Basin was 1.4 times, while the co-occurring return period was 7.0 times, and the Kendall return period was 4 times. Moreover, this difference increased with the increase in the return period. The magnitude order of the four return periods is as follows: TAnd > TKendall > TSingle-variable > TOr. Joint return periods (Or) and co-occurring return periods (And) could be considered as the extreme cases under single-variable return periods, serving as an estimation interval for actual return periods. Under the influence of climate change, the bivariate design values for future periods exhibited a variability increase of 6.76–28.8% compared to historical periods, and this increase grew with higher radiative forcing scenarios, ranking as SSP126 < SSP245 < SSP585. The bivariate design values showed a noticeable difference in variability compared to the single-variable design values, ranging from −0.79% to 18.67%. This difference increased with higher quantile values, with R95P-SDII (95) > R90P-SDII (90) > PRCPTOT-SDII. [ABSTRACT FROM AUTHOR]

Healthcare as a kind of service is closely related to human health, but its uneven distribution among regions could affect the equity of residents' access to the service and lead to the unbalanced development of healthcare levels. Therefore, this article establishes an integrated model by means of the stochastic frontier analysis method to evaluate regional healthcare efficiency and analyse its influencing factors. Specifically, the distribution and change trend of healthcare technical output (TO) efficiency and health output (HO) efficiency are investigated from the temporal and spatial perspectives, and then the influencing factors of the two types of healthcare efficiency are explored, respectively. Taking China as a case study, the results show that there are obvious regional differences in TO efficiency as a whole, where the values of the eastern and central regions are significantly higher, while the western and northeast regions have lower TO efficiency. Economic, social, and regional factors have a significant influence on both TO efficiency and HO efficiency, among which the impacts of population density on the two types of efficiency are opposite. Accordingly, some policy recommendations have been put forward for improving regional healthcare efficiency. [ABSTRACT FROM AUTHOR]

Centipedegrass (Eremochloa ophiuroides (Munro.) Hack.) is a species originating in China and is an excellent warm-season turfgrass. As a native species in southern China, it is naturally distributed in the phosphorus-deficient and aluminum-toxic acid soil areas. It is important to research the molecular mechanism of centipedegrass responses to phosphorus-deficiency and/or aluminum-toxicity stress. Quantitative Real-Time PCR (qRT-PCR) is a common method for gene expression analysis, and the accuracy of qRT-PCR results depends heavily on the stability of internal reference genes. However, there are still no reported stable and effective reference genes for qRT-PCR analysis of target genes under the acid-soil-related stresses in different organs of centipedegrass. For scientific rigor, the gene used as a reference for any plant species and/or any stress conditions should be first systematically screened and evaluated. This study is the first to provide a group of reliable reference genes to quantify the expression levels of functional genes of Eremochloa ophiuroides under multiple stresses of P deficiency and/or aluminum toxicity. In this study, centipedegrass seedlings of the acid-soil-resistant strain 'E041' and acid-soil-sensitive strain 'E089' were used for qRT-PCR analysis. A total of 11 candidate reference genes (ACT, TUB, GAPDH, TIP41, CACS, HNR, EP, EF1α, EIF4α, PP2A and actin) were detected by qRT-PCR technology, and the stability of candidate genes was evaluated with the combination of four internal stability analysis software programs. The candidate reference genes exhibited differential stability of expression in roots, stems and leaves under phosphorus-deficiency and/or aluminum-toxicity stress. On the whole, the results showed that GAPDH, TIP41 and HNR were the most stable in the total of samples. In addition, for different tissues under various stresses, the selected reference genes were also different. CACS and PP2A were identified as two stable reference genes in roots through all three stress treatments (phosphate deficiency, aluminum toxicity, and the multiple stress treatment of aluminum toxicity and phosphate deficiency). Moreover, CACS was also stable as a reference gene in roots under each treatment (phosphate deficiency, aluminum toxicity, or multiple stresses of aluminum toxicity and phosphate deficiency). In stems under all three stress treatments, GAPDH and EIF4α were the most stable reference genes; for leaves, PP2A and TIP41 showed the two highest rankings in all three stress treatments. Finally, qRT-PCR analysis of the expression patterns of the target gene ALMT1 was performed to verify the selected reference genes. The application of the reference genes identified as internal controls for qRT-PCR analysis will enable accurate analysis of the target gene expression levels and expression patterns in centipedegrass under acid-soil-related stresses. [ABSTRACT FROM AUTHOR]

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. Dietary patterns have been linked to a limited number of major chronic diseases. Here, the authors show greater adherence to healthy dietary patterns, especially Alternate Mediterranean Diet, is associated with a lower risk of most of the 48 tested chronic diseases. [ABSTRACT FROM AUTHOR]

Purpose: Although immunotherapy improves clinical outcomes in several types of malignancies, as an immunologically 'cold' tumor, pancreatic ductal adenocarcinoma (PDAC) is arrantly resistant to immunotherapy. However, the role of N6-methyladenosine (m6A) modification in the immune microenvironment of PDAC is still poorly understood. Methods: The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets were used to identify differentially expressed m6A related enzymes. The biological role and mechanism of METTL3 in PDAC growth and metastasis were determined in vitro and in vivo. RNA-sequencing and bioinformatics analysis were used to identify signaling pathways involved in METTL3. Western blot, m6A dot blot assays, co-immunoprecipitation, immunofluorescence, and flow cytometry were used to explore the molecular mechanism. Results: Here, we demonstrate that METTL3, the key regulator of m6A modification, is downregulated in PDAC, and negatively correlates with PDAC malignant features. Elevated METTL3 suppresses PDAC growth and overcomes resistance to immune checkpoint blockade. Mechanistically, METTL3 promotes the accumulation of endogenous double-stranded RNA (dsRNA) through protecting m6A-transcripts from further Adenosine-to-inosine (A-to-I) editing. The dsRNA stress activates RIG-I-like receptors (RLRs) to enhance anti-tumor immunity, finally suppressing PDAC progression. Conclusion: Our findings indicate that tumor cell-intrinsic m6A modification participates in the regulation of tumor immune landscape. Adjusting the m6A level may be an effective strategy to overcome the resistance to immunotherapy and increase responsiveness to immunotherapy in PDAC. [ABSTRACT FROM AUTHOR]

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 FROM AUTHOR]

The venting of methane from coal mining is China's main source of methane emissions. Accurate and up-to-date methane emission factors for coal mines are significant for reporting and controlling methane emissions in China. This study takes a typical coal mine in Shanxi Province as the research object and divides the coal mine into different zones based on the occurrence structure of methane in Shanxi Province. The methane emission characteristics of underground coal mine types and monitoring modes were studied. The emissions of methane from coal seams and ventilation methane of six typical coal mine groups in Shanxi Province were monitored. The measured methane concentration data were corrected by substituting them into the methane emission formula, and the future methane emissions were predicted by the coal production and methane emission factors. The results show that the number of methane mines and predicted reserves in Zone I of Shanxi Province are the highest. The average methane concentration emitted from coal and gas outburst mines is about 22.52%, and the average methane concentration emitted from high-gas mines is about 10.68%. The methane emissions from coal and gas outburst mines to the atmosphere account for about 64% of the total net methane emissions. The predicted methane emission factor for Shanxi coal mines is expected to increase from 8.859 m3/t in 2016 to 9.136 m3/t in 2025, and the methane emissions from Shanxi coal mines will reach 8.43 Tg in 2025. [ABSTRACT FROM AUTHOR]

The R2R3-MYB genes in plants play an essential role in the drought-responsive signaling pathway. Plenty of R2R3-MYB S21 and S22 subgroup genes in Arabidopsis have been implicated in dehydration conditions, yet few have been covered in terms of the role of the S21 and S22 subgroup genes in poplar under drought. PdMYB2R089 and PdMYB2R151 genes, respectively belonging to the S21 and S22 subgroups of NL895 (Populus deltoides × P. euramericana cv. 'Nanlin895′), were selected based on the previous expression analysis of poplar R2R3-MYB genes that are responsive to dehydration. The regulatory functions of two target genes in plant responses to drought stress were studied and speculated through the genetic transformation of Arabidopsis thaliana. PdMYB2R089 and PdMYB2R151 could promote the closure of stomata in leaves, lessen the production of malondialdehyde (MDA), enhance the activity of the peroxidase (POD) enzyme, and shorten the life cycle of transgenic plants, in part owing to their similar conserved domains. Moreover, PdMYB2R089 could strengthen root length and lateral root growth. These results suggest that PdMYB2R089 and PdMYB2R151 genes might have the potential to improve drought adaptability in plants. In addition, PdMYB2R151 could significantly improve the seed germination rate of transgenic Arabidopsis, but PdMYB2R089 could not. This finding provides a clue for the subsequent functional dissection of S21 and S22 subgroup genes in poplar that is responsive to drought. [ABSTRACT FROM AUTHOR]

Idiopathic pulmonary fibrosis (IPF) is a fatal interstitial lung disease characterized by chronic, progressive, and fibrotic lung injury. Although remarkable progress has been made toward understanding the pathogenesis of PF, finding more effective treatments for this fatal disease remains a challenge. In this study, we describe an innovative macrophage‐based approach to deliver anti‐fibrotic protein to the lung and inhibit PF in a mouse model of bleomycin (BLM)‐induced lung injury. We engineered macrophages to continuously secrete three types of proteins: interleukin‐10, which prevents inflammation; TGFRcFc, a soluble truncated TGF‐βR2 that blocks TGF‐β; and CD147, which induces matrix metalloproteinases (MMPs) and causes collagen degradation. Infusing these engineered macrophages into the lungs of BLM‐induced PF mouse models in an optimal pattern significantly ameliorated PF in mice. Specifically, the most effective therapeutic outcome was achieved by infusing IL‐10‐secreting macrophages on day 1, followed by TGFRcFc‐secreting macrophages on day 7 and CD147‐secreting macrophages on day 14 into the same mice after BLM treatment. Our data suggest that macrophage‐based delivery of anti‐fibrotic proteins to the lungs is a promising therapy for fibrotic lung disorders. [ABSTRACT FROM AUTHOR]

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. Base editing technology has great potential in treating pathogenic single-nucleotide variations. Using a dual-AAV base editing system, Wu et al. restored visual functions in a mouse model of retinitis pigmentosa. [ABSTRACT FROM AUTHOR]

Inappropriate vegetation reconstruction in the Loess Plateau region has led to a significant increase in regional evapotranspiration and water consumption, further aggravating the shortage of soil water resources in the Loess Plateau region. The Jing River basin is a typical area for vegetation reconstruction in the Loess Plateau region. A thorough understanding of changes in hydrological processes in the Jing River basin is of significant scientific importance for efficient utilization of soil water resources and sustainable vegetation restoration in the region. In this study, the physically based Water and Energy Transfer Processes (WEP) distributed hydrological model was used to simulate key hydrological processes in the Jing River Basin during different periods before and after the implementation of cropland conversion to forest and grassland from 1980 to 2019. The results showed that after the implementation of cropland conversion to forest and grassland from 2000 to 2019, the average runoff volume in the Jing River Basin decreased by 20.91%. The most significant decrease in average runoff occurred in the central and northern parts of the basin, with a maximum reduction of 48.6%. The decrease in runoff in flood season is more obvious. The peak discharge decreased by 24.91%, and the most significant decrease occurred in the northern and central parts of the basin, ranging from 10.3% to 50.2%. The spatial distribution pattern of average soil moisture in the 0–0.8 m soil layer showed more moisture in the south and less in the north, with the minimum value occurring in certain areas in the eastern part of the basin. Overall, the implementation of cropland conversion to forest and grassland led to a certain degree of decrease in soil moisture in the basin. After the implementation of cropland conversion to forest and grassland, reference evapotranspiration fluctuated only in specific areas of the basin with no significant overall change. [ABSTRACT FROM AUTHOR]

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. Genetic dissection of hybrids is more difficult than inbreds as nonadditive effects are involved. Here, the authors report a pipeline for joint analysis of phenotypes, effects, and generations and demonstrate its usefulness in identification of loci associated with quality traits and improving predict accuracy in genomic selection of hybrid rice. [ABSTRACT FROM AUTHOR]

Objectives: To evaluate the intra-cavity left ventricular (LV) blood flow kinetic energy (KE) parameters using four-dimensional (4D) flow cardiovascular magnetic resonance (CMR) in patients with hypertension (HTN). Methods: Forty-two HTN patients and twenty age-/gender-matched healthy controls who underwent CMR including cines, pre-/post-T1 mapping, and whole-heart 4D flow imaging were retrospectively evaluated. HTN patients were further divided into two subgroups: with preserved ejection fraction (HTN-pEF) and with reduced ejection fraction (HTN-rEF). KE parameters were indexed to LV end-diastolic volume (EDV) to obtain averaged LV, minimal, systolic, diastolic, peak E-wave, peak A-wave, E-wave, and A-wave KEiEDV, as well as the proportion of in-plane LV KE (%), the time difference (TD). These parameters were compared between the HTN group and healthy controls, also between two subgroups. The correlation of LV blood flow KE parameters with LV function and extracellular volume fraction (ECV) were analyzed in the HTN group using multivariate regression analysis. Results: Peak E-wave KEiEDV in the HTN group was significantly lower (p = 0.01), while in-plane KE and TD were significantly higher (all p < 0.01) than those in healthy controls. Compared to the HTN-pEF subgroup, the proportion of in-plane KE and TD was significantly increased in the HTN-rEF subgroup (all p < 0.01). Only the proportion of in-plane KE demonstrated an independent correlation with ECV (β* = 0.59, p < 0.01). Conclusions: The decreased peak E-wave KEiEDV and the increased proportion of in-plane KE, TD reflected the alterations of LV blood flow in HTN patients, and the proportion of in-plane KE was independently associated with ECV. Key Points: • 4D flow CMR demonstrated that the peak E-wave KEiEDV was decreased, while the in-plane KE and time difference (TD) were increased in hypertensive (HTN) patients. • The proportion of in-plane KE and TD was further increased in HTN patients with reduced ejection fraction than in HTN patients with preserved ejection fraction, and the proportion of in-plane KE was independently associated with extracellular volume fraction in HTN patients. • 4D flow CMR intra-cavity blood flow KE parameters might reveal the LV hemodynamic status in preclinical HTN patients. [ABSTRACT FROM AUTHOR]

Cuprous oxide (Cu2O) has attracted tremendous attention in the field of photocatalytic CO2 conversion due to excellent optical character and carrier separation efficiency. However, photocatalytic CO2 conversion is a multiple proton-coupled electron transfer process that usually produces various products, and it is still a major challenge for improving the yield and selectivity of CO2 to a single product. Herein, a low-temperature deposition method combined with the dynamic hydrogen bubble template method was used to synthesize a Ag/Cu2O photocatalyst to tackle this problem. The Ag/Cu2O photocatalyst has porous nanostructures and exhibits excellent performance in photocatalytic CO2 reduction. The CO yield of Ag/Cu2O-0.04 is 22.52 nmol cm–2 h–1 (43.04 μmol g–1 h–1), which is about 1.5 times that of the original sample. For the selectivity of CO, Ag/Cu2O was increased by 22% compared with Cu2O, reaching 82.9%. Combined with density functional theory and Fourier transform infrared spectroscopy, it is found that Ag loading changes the adsorption configuration of CO2 on the catalyst from bidentate carbonate to monodentate carbonate, improving the selectivity of CO. In addition, the Ag/Cu2O Schottky junction accelerates the surface reaction kinetics due to acceleration of the separation and transportation of photogenerated carriers. Therefore, this work provides an idea to develop a high-efficient photocatalyst for photocatalytic CO2 reduction. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Against the background of global warming and frequent extreme precipitation events, the changes in drought characteristics in the middle reaches of the Yellow River Basin (YRMB) have been particularly pronounced in recent years. Under the new situation, it is necessary to further our understanding of drought risk in the basin and its response mechanisms to climate change. In this study, YRMB was utilized as the research area. Based on the precipitation (P) and potential evapotranspiration (PET) data under four emission scenarios (historical and future), five timescales (SPEI-1, SPEI-3, SPEI-6, SPEI-9, and SPEI-12) of SPEI drought indices were estimated in this study. Drought events were identified using the run-length theory, and the spatial distribution values of drought frequency, duration, intensity, and severity were also examined. Based on the preferred copula function, the two-dimensional joint distribution of drought variables was established, and the two-dimensional return period of drought indices in the historical (1901–2014) and future (2022–2100 under SSP245 and SSP585 emission scenarios) periods were calculated. The results show that the SPEI index in the middle reaches of the YRMB is increasing in the future period and the basin tends to be more humid. Under the SSP245 and SSP585 scenarios, the frequency of long drought durations, high drought intensities, or severe drought events in the basin may be higher. The univariate return period is always higher than the joint return period, but lower than the co-occurrence return period, and both types of return periods can be used to assess range estimations in the future. The research results can provide support for understanding the spatiotemporal distribution characteristics of drought in the YRMB and improving the accuracy of drought decision making. [ABSTRACT FROM AUTHOR]

Pancreatic ductal adenocarcinoma (PDAC) is insidious and highly malignant with extremely poor prognosis and drug resistance to current chemotherapies. Therefore, there is a critical need to investigate the molecular mechanism underlying PDAC progression to develop promising diagnostic and therapeutic interventions. In parallel, vacuolar protein sorting (VPS) proteins, involved in the sorting, transportation, and localization of membrane proteins, have gradually attracted the attention of researchers in the development of cancers. Although VPS35 has been reported to promote carcinoma progression, the specific molecular mechanism is still unclear. Here, we determined the impact of VPS35 on the tumorigenesis of PDAC and explored the underlying molecular mechanism. We performed a pan-cancer analysis of 46 VPS genes using RNAseq data from GTEx (control) and TCGA (tumor) and predicted potential functions of VPS35 in PDAC by enrichment analysis. Furthermore, cell cloning experiments, gene knockout, cell cycle analysis, immunohistochemistry, and other molecular and biochemical experiments were used to validate the function of VPS35. Consequently, VPS35 was found overexpressed in multiple cancers and correlated with the poor prognosis of PDAC. Meanwhile, we verified that VPS35 could modulate the cell cycle and promote tumor cell growth in PDAC. Collectively, we provide solid evidence that VPS35 facilitates the cell cycle progression as a critical novel target in PDAC clinical therapy. [ABSTRACT FROM AUTHOR]

This study focuses on exploring equity among regions regarding public service delivery. An analytical framework is established to measure the level of public service delivery considering input (resources) and output (results), and an equity analysis is conducted from temporal and spatial perspectives. The results show that there are disparities in the level of public service delivery among regions in China (mainly due to inequality in resources), and within-region inequality has a greater influence on overall regional inequality than between-region inequality. The proposed analytical framework can help governments make better decisions about public service delivery. [ABSTRACT FROM AUTHOR]

In recent decades, the massive emission of greenhouse gases, such as carbon dioxide and methane, into the atmosphere has had a serious impact on the ecological environment. The dry reforming of carbon dioxide and methane to syngas cannot only realize the resource utilization of methane and carbon dioxide but also reduce global climate change. It is of great significance in carbon emission reduction. Owing to the dry reforming of methane (DRM) being a strongly endothermic reaction, it needs to be carried out under high-temperature conditions. It makes the catalyst have problems of the sintering of metal, carbon deposition, and poisoning. This article revolves around the problem of catalyst deactivation during the DRM reaction. It expands upon the thermodynamics and mechanisms of the DRM reaction, analyzes the causes of metal catalyst deactivation due to carbon deposition, sintering, and poisoning, and summarizes how the active components, supports, and additives of metal catalysts restrain the DRM catalyst deactivation during the reaction. The analysis revealed that changing the type and size of the active metal, adjusting the properties of the support, and adding additives can further regulate the dispersion of the active component, the interaction between the active component and the support, the oxygen vacancies of the support, and the acidity and basicity of the catalyst surface, ultimately achieving control over the metal catalyst's resistance to sintering, carbon deposition, and sulfur poisoning. In addition, it discusses the application of metal catalysts in photothermal and plasma-catalyzed DRM. Finally, it outlines the prospects for research on metal catalysts for the DRM. [ABSTRACT FROM AUTHOR]