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Abstract Background Evidence suggests that insulin resistance (IR) is an autonomous risk factor for cardiovascular disease (CVD). Nevertheless, the association between estimated glucose disposal rate (eGDR), a novel indicator of IR, and incident CVD and mortality in chronic kidney disease (CKD) patients without diabetes remains uncertain. Methods The study included 19,906 participants from the UK Biobank who had an estimated glomerular filtration rate (eGFR)

Abstract Perioperative anesthetic management entails a multitude of decision-making processes within complex medical scenarios. These demand the continuous and dynamic execution of precise decisions which poses significant challenges. In the age of big data, the exponential growth in data volume from diverse sources has revolutionized many fields, including healthcare, finance, and marketing. Machine learning has emerged as a powerful tool for analyzing big data, enabling the handling of large datasets and uncovering intricate patterns and relationships. The application of big data and artificial intelligence algorithms is gradually being integrated, enabling effective task completion in various stages of perioperative management, including risk prediction, decision support, and auxiliary examination. Through in-depth analysis of big data, healthcare professionals can gain insights into patient prognoses. This review provides a comprehensive overview of the distinctive features of perioperative big data and its applications in anesthesia management during the perioperative period.

Abstract As a Brassica crop, Brassica napus typically has single flowers that contain four petals. The double-flower phenotype of rapeseed has been a desirable trait in China because of its potential commercial value in ornamental tourism. However, few double-flowered germplasms have been documented in B. napus, and knowledge of the underlying genes is limited. Here, B. napus D376 was characterized as a double-flowered strain that presented an average of 10.92 ± 1.40 petals and other normal floral organs. F1, F2 and BC1 populations were constructed by crossing D376 with a single-flowered line reciprocally. Genetic analysis revealed that the double-flower trait was a recessive trait controlled by multiple genes. To identify the key genes controlling the double-flower trait, bulk segregant analysis sequencing (BSA-seq) and RNA-seq analyses were conducted on F2 individual bulks with opposite extreme phenotypes. Through BSA-seq, one candidate interval was mapped at the region of chromosome C05: 14.56–16.17 Mb. GO and KEGG enrichment analyses revealed that the DEGs were significantly enriched in carbohydrate metabolic processes, notably starch and sucrose metabolism. Interestingly, five and thirty-six DEGs associated with floral development were significantly up- and down-regulated, respectively, in the double-flowered plants. A combined analysis of BSA-seq and RNA-seq data revealed that five genes were candidates associated with the double flower trait, and BnaC05.ERS2 was the most promising gene. These findings provide novel insights into the breeding of double-flowered varieties and lay a theoretical foundation for unveiling the molecular mechanisms of floral development in B. napus.

Abstract Background Cancer-associated fibroblasts (CAFs) are the prominent cell type in the tumor microenvironment (TME), and CAF subsets have been identified in various tumors. However, how CAFs spatially coordinate other cell populations within the liver TME to promote cancer progression remains unclear. Methods We combined multi-region proteomics (6 patients, 24 samples), 10X Genomics Visium spatial transcriptomics (11 patients, 25 samples), and multiplexed imaging (92 patients, 264 samples) technologies to decipher the expression heterogeneity, functional diversity, spatial distribution, colocalization, and interaction of fibroblasts. The newly identified CAF subpopulation was validated by cells isolated from 5 liver cancer patients and in vitro functional assays. Results We identified a liver CAF subpopulation, marked by the expression of COL1A2, COL4A1, COL4A2, CTGF, and FSTL1, and named F5-CAF. F5-CAF is preferentially located within and around tumor nests and colocalizes with cancer cells with higher stemness in hepatocellular carcinoma (HCC). Multiplexed staining of 92 patients and the bulk transcriptome of 371 patients demonstrated that the abundance of F5-CAFs in HCC was associated with a worse prognosis. Further in vitro experiments showed that F5-CAFs isolated from liver cancer patients can promote the proliferation and stemness of HCC cells. Conclusions We identified a CAF subpopulation F5-CAF in liver cancer, which is associated with cancer stemness and unfavorable prognosis. Our results provide potential mechanisms by which the CAF subset in the TME promotes the development of liver cancer by supporting the survival of cancer stem cells.

Abstract Background Accurate measurement of hemoglobin concentration is essential for various medical scenarios, including preoperative evaluations and determining blood loss. Traditional invasive methods are inconvenient and not suitable for rapid, point-of-care testing. Moreover, current models, due to their complex parameters, are not well-suited for mobile medical settings, which limits the ability to conduct frequent and rapid testing. This study aims to introduce a novel, compact, and efficient system that leverages deep learning and smartphone technology to accurately estimate hemoglobin levels, thereby facilitating rapid and accessible medical assessments. Methods The study employed a smartphone application to capture images of the eye, which were subsequently analyzed by a deep neural network trained on data from invasive blood test data. Specifically, the EGE-Unet model was utilized for eyelid segmentation, while the DHA(C3AE) model was employed for hemoglobin level prediction. The performance of the EGE-Unet was evaluated using statistical metrics including mean intersection over union (MIOU), F1 Score, accuracy, specificity, and sensitivity. The DHA(C3AE) model’s performance was assessed using mean absolute error (MAE), mean-square error (MSE), root mean square error (RMSE), and R^2. Results The EGE-Unet model demonstrated robust performance in eyelid segmentation, achieving an MIOU of 0.78, an F1 Score of 0.87, an accuracy of 0.97, a specificity of 0.98, and a sensitivity of 0.86. The DHA(C3AE) model for hemoglobin level prediction yielded promising outcomes with an MAE of 1.34, an MSE of 2.85, an RMSE of 1.69, and an R^2 of 0.34. The overall size of the model is modest at 1.08 M, with a computational complexity of 0.12 FLOPs (G). Conclusions This system presents a groundbreaking approach that eliminates the need for supplementary devices, providing a cost-effective, swift, and accurate method for healthcare professionals to enhance treatment planning and improve patient care in perioperative environments. The proposed system has the potential to enable frequent and rapid testing of hemoglobin levels, which can be particularly beneficial in mobile medical settings. Trial Registration The clinical trial was registered on the Chinese Clinical Trial Registry (No. ChiCTR2100044138) on 20/02/2021.

Runoff prediction plays a crucial role in hydropower generation and flood prevention, enhancing prediction accuracy in hydrology. This study proposes an extreme forecast index (EFI)-driven runoff prediction approach using stacking ensemble learning to improve prediction performance. EFI is introduced as an input into four machine learning models (Support Vector Regression, Multi-layer Perceptron, Gradient Boosting Decision Tree, and Ridge Regression) for runoff prediction with lead times of 24 h, 48 h, and 72 h. The stacking ensemble learning framework comprises four base-models and a meta-model, and model hyperparameters are re-optimized using the particle swarm optimization algorithm. The approach focuses on predicting the inflow processes of the Geheyan Reservoir in the Qing River using EFI and runoff time series. Results demonstrate that the EFI-runoff simulation can improve runoff prediction capability due to EFI’s higher sensitivity to observed runoff, and the proposed stacking ensemble learning model outperforms the individual model in predicting runoff with all lead times. The relative flood peak error, mean relative error, root mean square error, and Nash-Sutcliffe efficiency coefficient of the model’s one-day-ahead prediction are 7.987%, 22.421%, 632.871 m3/s, and 0.771, respectively. Therefore, this approach can be effectively utilized to improve accuracy in short-term runoff prediction applications.

Introduction: The early diagnosis of kidney injury in type 2 diabetes (T2DM) is important to prevent the long-term damaging effects of kidney loss and is decisive for patient outcomes. While SIRT2 is implicated in diabetes pathogenesis, its correlation with diabetic nephropathy remains unexplored. This study was designed to evaluate the association of urine SIRT2 levels with diabetic kidney injury, as well as potential underlying mechanisms. Methods: In T2DM patients, db/db mice, and high glucose plus palmitic acid treated HK2 cell models, ELISA, Immunoturbidimetry, Immunohistochemistry, Western blot, and Quantitative real-time polymerase chain reaction were used to detect SIRT2 levels and kidney damage. According to urinary albumin/creatinine ratio (UACR), 163 T2DM patients were divided into three groups. Spearman correlation analysis was used to investigate the relationship between urinary sirtuin2/creatinine ratio (USCR) and biomarkers of kidney injury. The influencing factors of albuminuria in T2DM patients were analyzed by logistic regression model. Results: In our findings, the Macro group exhibited the highest USCR levels as UACR increased. There was a positive association between USCR and UACR, α1-microglobulin/creatinine ratio (UαCR), β2-microglobulin/creatinine ratio (UβCR), and retinol-binding protein/creatinine ratio (URCR), with a negative correlation observed with eGFR. Logistic ordered multiclassification regression analysis, adjusting for confounding variables, confirmed that USCR remained a significant risk factor for the severity of albuminuria in T2DM patients. In the db/db mice kidney SIRT2 protein level increased significantly. Increased SIRT2 protein levels were also observed in renal tubular epithelial cells treated with high glucose plus palmitic acid. Moreover, SIRT2 promotes the expression of proinflammatory factors TNF-α and IL-6 by modulating the phosphorylation of p38 MAPK and p-JNK in renal tubular cells induced by high glucose and palmitic acid. Conclusion: Urinary SIRT2 is closely related to eGFR, renal tubule injury, and urinary albumin excretion in T2DM patients, which is expected to be an important indicator to comprehensively reflect renal injury.

BackgroundThe mpox pandemic has caused widespread public concern around the world. The spread of misinformation through the internet and social media could lead to an infodemic that poses challenges to mpox control. ObjectiveThis review aims to summarize mpox-related infodemiology studies to determine the characteristics, influence, prevention, and control measures of the mpox infodemic and propose prospects for future research. MethodsThe scoping review was conducted based on a structured 5-step methodological framework. A comprehensive search for mpox-related infodemiology studies was performed using PubMed, Web of Science, Embase, and Scopus, with searches completed by April 30, 2024. After study selection and data extraction, the main topics of the mpox infodemic were categorized and summarized in 4 aspects, including a trend analysis of online information search volume, content topics of mpox-related online posts and comments, emotional and sentiment characteristics of online content, and prevention and control measures for the mpox infodemic. ResultsA total of 1607 articles were retrieved from the databases according to the keywords, and 61 studies were included in the final analysis. After the World Health Organization’s declaration of an mpox public health emergency of international concern in July 2022, the number of related studies began growing rapidly. Google was the most widely used search engine platform (9/61, 15%), and Twitter was the most used social media app (32/61, 52%) for researchers. Researchers from 33 countries were concerned about mpox infodemic–related topics. Among them, the top 3 countries for article publication were the United States (27 studies), India (9 studies), and the United Kingdom (7 studies). Studies of online information search trends showed that mpox-related online search volume skyrocketed at the beginning of the mpox outbreak, especially when the World Health Organization provided important declarations. There was a large amount of misinformation with negative sentiment and discriminatory and hostile content against gay, bisexual, and other men who have sex with men. Given the characteristics of the mpox infodemic, the studies provided several positive prevention and control measures, including the timely and active publishing of professional, high-quality, and easy-to-understand information online; strengthening surveillance and early warning for the infodemic based on internet data; and taking measures to protect key populations from the harm of the mpox infodemic. ConclusionsThis comprehensive summary of evidence from previous mpox infodemiology studies is valuable for understanding the characteristics of the mpox infodemic and for formulating prevention and control measures. It is essential for researchers and policy makers to establish prediction and early warning approaches and targeted intervention methods for dealing with the mpox infodemic in the future.

BackgroundType VI secretion system (T6SS) is widely present in Gram-negative bacteria and directly mediates antagonistic prokaryote interactions. PAAR (proline-alanine-alanine-arginine repeats) proteins have been proven essential for T6SS-mediated secretion and target cell killing. Although PAAR proteins are commonly found in A. baumannii, their biological functions are not fully disclosed yet. In this study, we investigated the functions of a PAAR protein termed TagP (T6SS-associated-gene PAAR), encoded by the gene ACX60_RS09070 outside the core T6SS locus of A. baumannii strain ATCC 17978.MethodsIn this study, tagP null and complement A. baumannii ATCC 17978 strains were constructed. The influence of TagP on T6SS function was investigated through Hcp detection and bacterial competition assay; the influence on environmental fitness was studied through in vitro growth, biofilm formation assay, surface motility assay, survivability in various simulated environmental conditions; the influence on pathogenicity was explored through cell adhesion and invasion assays, intramacrophage survival assay, serum survival assay, and G. melonella Killing assays. Quantitative transcriptomic and proteomic analyses were utilized to observe the global impact of TagP on bacterial status.ResultsCompared with the wildtype strain, the tagP null mutant was impaired in several tested phenotypes such as surface motility, biofilm formation, tolerance to adverse environments, adherence to eukaryotic cells, endurance to serum complement killing, and virulence to Galleria melonella. Notably, although RNA-Seq and proteomics analysis revealed that many genes were significantly down-regulated in the tagP null mutant compared to the wildtype strain, there is no significant difference in their antagonistic abilities. We also found that Histone-like nucleoid structuring protein (H-NS) was significantly upregulated in the tagP null mutant at both mRNA and protein levels.ConclusionsThis study enriches our understanding of the biofunction of PAAR proteins in A. baumannii. The results indicates that TagP involved in a unique modulation of fitness and virulence control in A. baumannii, it is more than a classic PAAR protein involved in T6SS, while how TagP play roles in the fitness and virulence of A. baumannii needs further investigation to clarify.

Abstract Background Epigenetic modifications that exhibit circadian oscillations also promote circadian oscillations of gene expression. Brassica napus is a heterozygous polyploid species that has undergone distant hybridization and genome doubling events and has a young and distinct species origin. Studies incorporating circadian rhythm analysis of epigenetic modifications can offer new insights into differences in diurnal oscillation behavior among subgenomes and the regulation of diverse expressions of homologous gene rhythms in biological clocks. Results In this study, we created a high-resolution and multioscillatory gene expression dataset, active histone modification (H3K4me3, H3K9ac), and RNAPII recruitment in Brassica napus. We also conducted the pioneering characterization of the diurnal rhythm of transcription and epigenetic modifications in an allopolyploid species. We compared the evolution of diurnal rhythms between subgenomes and observed that the Cn subgenome had higher diurnal oscillation activity in both transcription and active histone modifications than the An subgenome. Compared to the A subgenome in Brassica rapa, the An subgenome of Brassica napus displayed significant changes in diurnal oscillation characteristics of transcription. Homologous gene pairs exhibited a higher proportion of diurnal oscillation in transcription than subgenome-specific genes, attributed to higher chromatin accessibility and abundance of active epigenetic modification types. We found that the diurnal expression of homologous genes displayed diversity, and the redundancy of the circadian system resulted in extensive changes in the diurnal rhythm characteristics of clock genes after distant hybridization and genome duplication events. Epigenetic modifications influenced the differences in the diurnal rhythm of homologous gene expression, and the diurnal oscillation of homologous gene expression was affected by the combination of multiple histone modifications. Conclusions Herein, we presented, for the first time, a characterization of the diurnal rhythm characteristics of gene expression and its epigenetic modifications in an allopolyploid species. Our discoveries shed light on the epigenetic factors responsible for the diurnal oscillation activity imbalance between subgenomes and homologous genes’ rhythmic expression differences. The comprehensive time-series dataset we generated for gene expression and epigenetic modifications provides a valuable resource for future investigations into the regulatory mechanisms of protein-coding genes in Brassica napus.

The accuracy of long-term runoff models can be increased through the input of local weather variables and global climate indices. However, existing methods do not effectively extract important information from complex input factors across various temporal and spatial dimensions, thereby contributing to inaccurate predictions of long-term runoff. In this study, local–global–temporal attention mechanisms (LGTA) were proposed for capturing crucial information on global climate indices on monthly, annual, and interannual time scales. The graph attention network (GAT) was employed to extract geographical topological information of meteorological stations, based on remotely sensed elevation data. A long-term runoff prediction model was established based on long-short-term memory (LSTM) integrated with GAT and LGTA, referred to as GAT–LGTA–LSTM. The proposed model was compared to five comparative models (LGTA–LSTM, GAT–GTA–LSTM, GTA–LSTM, GAT–GA–LSTM, GA–LSTM). The models were applied to forecast the long-term runoff at Luning and Pingshan stations in China. The results indicated that the GAT–LGTA–LSTM model demonstrated the best forecasting performance among the comparative models. The Nash–Sutcliffe Efficiency (NSE) of GAT–LGTA–LSTM at the Luning and Pingshan stations reached 0.87 and 0.89, respectively. Compared to the GA–LSTM benchmark model, the GAT–LGTA–LSTM model demonstrated an average increase in NSE of 0.07, an average increase in Kling–Gupta Efficiency (KGE) of 0.08, and an average reduction in mean absolute percent error (MAPE) of 0.12. The excellent performance of the proposed model is attributed to the following: (1) local attention mechanism assigns a higher weight to key global climate indices at a monthly scale, enhancing the ability of global and temporal attention mechanisms to capture the critical information at annual and interannual scales and (2) the global attention mechanism integrated with GAT effectively extracts crucial temporal and spatial information from precipitation and remotely-sensed elevation data. Furthermore, attention visualization reveals that various global climate indices contribute differently to runoff predictions across distinct months. The global climate indices corresponding to specific seasons or months should be selected to forecast the respective monthly runoff.

Background: tRNA-derived small RNAs (tsRNAs) are an emerging class of small noncoding RNAs derived from tRNA cleavage. Summary: With the development of high-throughput sequencing, various biological roles of tsRNAs have been gradually revealed, including regulation of mRNA stability, transcription, translation, direct interaction with proteins and as epigenetic factors, etc. Recent studies have shown that tsRNAs are also closely related to renal disease. In clinical acute kidney injury (AKI) patients and preclinical AKI models, the production and differential expression of tsRNAs in renal tissue and plasma were observed. Decreased expression of tsRNAs was also found in urine exosomes from chronic kidney disease patients. Dysregulation of tsRNAs also appears in models of nephrotic syndrome and patients with lupus nephritis. And specific tsRNAs were found in high glucose model in vitro and in serum of diabetic nephropathy patients. In addition, tsRNAs were also differentially expressed in patients with kidney cancer and transplantation. Key Messages: In the present review, we have summarized up-to-date works and reviewed the relationship and possible mechanisms between tsRNAs and kidney diseases.

Abstract Yellow-seed trait is a desirable breeding characteristic of rapeseed (Brassica napus) that could greatly improve seed oil yield and quality. However, the underlying mechanisms controlling this phenotype in B. napus plants are difficult to discern because of their complexity. Here, we assemble high-quality genomes of yellow-seeded (GH06) and black-seeded (ZY821). Combining in-depth fine mapping of a quantitative trait locus (QTL) for seed color with other omics data reveal BnA09MYB47a, encoding an R2R3-MYB-type transcription factor, as the causal gene of a major QTL controlling the yellow-seed trait. Functional studies show that sequence variation of BnA09MYB47a underlies the functional divergence between the yellow- and black-seeded B. napus. The black-seed allele BnA09MYB47aZY821, but not the yellow-seed allele BnA09MYB47aGH06, promotes flavonoid biosynthesis by directly activating the expression of BnTT18. Our discovery suggests a possible approach to breeding B. napus for improved commercial value and facilitates flavonoid biosynthesis studies in Brassica crops.

Abstract Purpose The association of NUCB-2/Nesfatin-1 with nasopharyngeal carcinoma (NPC) remains unclear. We clarified the role of NUCB-2/Nesfatin-1 in the development, progression and diagnosis of NPC. Materials and methods In nasopharyngeal carcinoma cell lines (5-8 F, 6-10B, CNE1, CNE2 and NP69), western blotting, MTT, EdU and other techniques were performed to investigate the role of NUCB-2 in nasopharyngeal carcinoma. 70 tissue samples (39 NPC and 31 rhinitis) and 140 serum samples (including NPC, rhinitis, other head and neck tumors and healthy control) were included to explore the expression of NUCB-2 and its metabolite Nesfatin-1 in tissues or serum of patients with nasopharyngeal carcinoma. Results NUCB-2 level in NPC tissue was higher than that in rhinitis tissue (P

Abstract Mitochondrial genomes (mitogenomes) of flowering plants vary greatly in structure and size, which can lead to frequent gene mutation, rearrangement, or recombination, then result in the cytoplasmic male sterile (CMS) mutants. In tobacco (Nicotiana tabacum), suaCMS lines are widely used in heterosis breeding; however, the related genetic regulations are not very clear. In this study, the cytological observation indicated that the pollen abortion of tobacco suaCMS(HD) occurred at the very early stage of the stamen primordia differentiation. In this study, the complete mitochondrial genomes of suaCMS(HD) and its maintainer HD were sequenced using the PacBio and Illumina Hiseq technology. The total length of the assembled mitogenomes of suaCMS(HD) and HD was 494,317 bp and 430,694 bp, respectively. Comparative analysis indicated that the expanded 64 K bases in suaCMS(HD) were mainly located in noncoding regions, and 23 and 21 big syntenic blocks (>5000 bp) were found in suaCMS(HD) and HD with a series of repeats. Electron transport chain‐related genes were highly conserved in two mitogenomes, except five genes (ATP4, ATP6, COX2, CcmFC, and SDH3) with substantial substitutions. Three suaCMS(HD)‐specific genes, orf261, orf291, and orf433, were screened. Sequence analysis and RT‐PCR verification showed that they were unique to suaCMS(HD). Further gene location analysis and protein property prediction indicated that all the three genes were likely candidates for suaCMS(HD). This study provides new insight into understanding the suaCMS mechanism and is useful for improving tobacco breeding.

Hepatopulmonary syndrome (HPS) is a severe lung injury caused by chronic liver disease, with limited understanding of the disease pathology. Exosomes are important mediators of intercellular communication that modulates various cellular functions by transferring a variety of intracellular components to target cells. Our recent studies have indicated that a new long noncoding RNA (lncRNA), PICALM-AU1, is mainly expressed in cholangiocytes, and is dramatically induced in the liver during HPS. However, the mechanism by which cholangiocyte-derived PICALM-AU1 regulates Endothelial-mesenchymal transition (EndMT) in HPS remains unclear. Here, we observed that PICALM-AU1 was synthesized in the cholangiocytes of the liver and then, secreted as exosomes into the serum; serum exosomal PICALM-AU1 levels were positively correlated with the severity of HPS in a rat model and in human patients. PICALM-AU1 carrying serum exosomes induced the EndMT of pulmonary microvascular endothelial cells (PMVECs) and promoted lung injury in vivo and in vitro. Furthermore, PICALM-AU1 acted as a molecular sponge for microRNA 144-3p (miR144-3p), resulting in the up-regulation of Zinc Finger E-Box Binding Homeobox 1 (ZEB1), a known target of EndMT and enhancement of EndMT, proliferation and migration of PMVECs. Taken together, our findings indicate that the cholangiocyte-derived exosomal lncRNA PICALM-AU1 plays a critical role in the EndMT in HPS lungs. Thus, it represents a potential therapeutic target for the treatment of HPS.

Background Congenital heart disease (CHDs) is the major cause of mortality from birth defects, affecting up to 1% of live births worldwide. However, the relationship between aluminum (Al) and iron (Fe) levels and the risk of CHDs has yielded inconsistent results. Methods We conducted a pair-matched case–control study that included 97 CHDs and 194 non-CHDs to investigate the association and interaction between Al/Fe exposure and the risk of CHDs in a birth cohort study in Lanzhou, China. Results Higher concentrations of cord blood Al were associated with a greater risk of total CHDs (aOR = 2.826, 95% CI [1.009–7.266]) and isolated CHDs (aOR = 10.713, 95% CI [1.017–112.851]) compared to the lowest Al level. Both in maternal blood and cord blood, a significant dose-effect was observed between Al level and total CHDs (Ptrend < 0.05), but a similar pattern was not observed for Fe. High Al in addition to high Fe appeared to elicit a stronger association with CHDs than both lowest tertile of Al and Fe level in umbilical cord blood, particularly for multiple CHDs, septal defects and patent ductus arteriosus. Conclusions Our study suggests that exposure to Al during pregnancy (≥2,408 μg/L) is significantly associated with an increased risk of CHDs in offspring, especially septal defects, and that high levels of Al and Fe are strongly correlated with fetal heart development. Further research is needed to understand the underlying mechanisms.

Aims The objective of this study is to examine the impact of inhibiting Sphingosine 1-phosphate receptor 2 (S1PR2) on liver inflammation, fibrogenesis, and changes of gut microbiome in the context of cholestasis-induced conditions. Methods The cholestatic liver injury model was developed by common bile duct ligation (CBDL). Sprague-Dawley rats were randomly allocated to three groups, sham operation, CBDL group and JTE-013 treated CBDL group. Biochemical and histological assessments were conducted to investigate the influence of S1PR2 on the modulation of fibrogenic factors and inflammatory infiltration. We conducted an analysis of the fecal microbiome by using 16S rRNA sequencing. Serum bile acid composition was evaluated through the utilization of liquid chromatography-mass spectrometry techniques. Results In the BDL rat model, the study findings revealed a significant increase in serum levels of conjugated bile acids, accompanied by an overexpression of S1PR2. Treatment with the specific inhibitor of S1PR2, known as JTE-013, resulted in a range of specific effects on the BDL rats. These effects included the improvement of liver function, reduction of liver inflammation, inhibition of hepatocyte apoptosis, and suppression of NETosis. These effects are likely mediated through the TCA/S1PR2/NOX2/NLRP3 pathway. Furthermore, the administration of JTE-013 resulted in an augmentation of the diversity of the bacterial community’s diversity, facilitating the proliferation of advantageous species while concurrently inhibiting the prevalence of detrimental bacteria. Conclusions The results of our study suggest that the administration of JTE-013 may have a beneficial effect in alleviating cholestatic liver disease and restoring the balance of intestinal flora.

Air pollution is a serious global public health problem. Air pollutants, especially fine particulate matter (PM2.5), are associated with increased risks of various diseases. In recent years, studies have confirmed that PM2.5 is closely related to chronic kidney disease, secondary kidney disease, and end-stage renal disease. This review summarized the effects of PM2.5 and its components on kidney diseases, and the potential mechanism of kidney injury induced by PM2.5 exposure from the aspects of inflammatory injury and oxidative stress, renal hemodynamic changes, and DNA damage and methylation, aiming to provide an insight for further mechanism research and the prevention and control of air pollution-induced kidney damage.

Abstract Activating transcription factor 4 (ATF4) is one of the key effectors of endoplasmic reticulum stress (ERS), ATF4/CHOP pathway-mediated ERS plays an important role in the progression of acute kidney disease (AKI). We have previously reported that Vitamin D receptor (VDR) exert renoprotection in rodent AKI models. However, whether ATF4, as well as ERS, is involved in the protective effect of VDR in ischemia-reperfusion (I/R) induced AKI is unknown. Herein, we showed that VDR agonist paricalcitol and VDR overexpression alleviated I/R-induced renal injury and cells apoptosis with decreased ATF4 and attenuated ERS, while VDR deletion significantly resulted in further increased ATF4, more drastic ERS and renal injury in I/R mice models. In addition, paricalcitol remarkably reduced Tunicamycin (TM) induced ATF4 and ERS with attenuated renal injury, while VDR deletion aggravated the above changes in TM mice models. Moreover, overexpression of ATF4 partially abolished the effect of paricalcitol against TM-induced ERS and apoptosis, while inhibition of ATF4 enhanced the protective effect of paricalcitol. Bioinformatics analysis indicated potential VDR binding sites on ATF4 promotor sequence which were further confirmed by ChIP-qPCR and dual-luciferase reporter gene assay. In conclusion, VDR attenuated I/R-induced AKI by suppressing ERS partly via transcriptional regulation of ATF4.

ObjectivesIt is easy to produce buckling distortion when welding thin plate butt joints, which affects the construction period, cost and performance, but this can be controlled by applying external restraints. MethodsFirst, a butt welding test of a thin plate under external restraints is carried out, and the out-of-plane deformation is measured by the optical surface scanning method. At the same time, finite element (FE) models in a free state and external restraint state are established, and the thermal mechanical phenomena of the two models are subjected to thermal-elastic-plastic FE analysis (TEP FE). The influence of different external restraint distributions on the welding buckling distortion of the joints is then studied, and reasons for controlling welding buckling distortion are analyzed from the perspective of longitudinal plastic strain and longitudinal contraction force.ResultsThe out-of-plane deformation of the corresponding model is in good agreement with the measured results, and milder than the out-of-plane deformation of the model in a free state. When external restraints are applied, the longitudinal plastic strain of the weld and its adjacent metal decreases, and the longitudinal contraction force of the thin plate also decreases.ConclusionsThe results verify that external restraints can effectively control welding buckling distortion, and the control effects are different depending on the external restraint distribution.

Background The role of inflammation in the pathogenesis of type 2 diabetes mellitus (T2DM) is well established. Lyn, a member of the nonreceptor protein tyrosine kinase Src family, has been reported to modulate inflammatory signaling pathways.Methods Lyn expression was assessed in kidney biopsies of 11 patients with diabetic kidney disease (DKD) and in kidney tissues of streptozotocin (STZ)-induced DKD mice. 102 recruited T2DM patients were divided into three groups: normoalbuminuria, microalbuminuria and macroalbuminuria. Twenty-one healthy volunteers were recruited as a control group. Clinical data, blood and urine samples of all individuals were collected for analysis.Results Lyn expression was augmented in the kidneys of DKD patients and STZ-induced diabetic mice. Compared with control and normoalbuminuria groups, both mRNA and protein expression of Lyn in peripheral blood mononuclear cells (PBMCs) in the macroalbuminuria group were significantly increased (p

AbstractPurpose The purpose of this study was to investigate the association between serum proprotein convertase subtilisin/kexin type 9 (PCSK9) levels and renal function impairment in type 2 diabetes mellitus (T2DM) patients.Methods PCSK9 levels were measured in T2DM patients, streptozotocin plus high-fat diet (STZ + HFD) mice, human proximal tubular epithelial (HK-2) cells treated with high glucose plus palmitic acid (HGPA) and the corresponding control groups. The T2DM patients were further divided into three groups according to serum PCSK9 levels. An analysis of clinical data was conducted, and a binary logistic regression model was used to test the relationship between potential predictors and urine albumin/urine creatinine ratio (UACR) and estimated glomerular filtration rate (eGFR).Results PCSK9 levels were higher in the DM group than in the control group in humans, mice and HK-2 cells. The systolic blood pressure (SBP), serum creatinine (Scr), blood urea nitrogen (BUN), triglyceride (TG), and urine α1-MG/urine creatinine ratio (UαCR) values in PCSK9 tertile 3 were significantly higher than those in PCSK9 tertile 1 (p

S14G-humanin (HNG), an analog of the mitochondria-derived peptide humanin, has demonstrated protective effects against various cardiovascular diseases. However, the specific pharmacological effects of HNG in heart failure (HF) have not been previously reported. Therefore, in this study, we aimed to investigate the potential protective effect of HNG in HF using a mouse model. HF was induced in mice through intraperitoneal injection of isoproterenol or transverse aortic constriction, followed by separate administration of HNG to assess its therapeutic impact. Our results revealed that HNG treatment significantly delayed the onset of cardiac dysfunction and structural remodeling in the HF mouse model. Furthermore, HNG administration was associated with reduced infiltration of inflammatory cells, improved myocardial fibrosis, and attenuation of cardiomyocyte apoptosis in the treated cardiac tissues. Additionally, we identified the involvement of the transforming growth factor-beta signaling pathway in the beneficial effects of HNG in isoproterenol-induced HF mice. Collectively, these findings underscore the therapeutic potential of HNG in preventing the progression of HF, as demonstrated in two distinct HF mouse models.