Association between cardiovascular health and serum vitamin D and its interaction with prediabetes and diabetes.

BACKGROUND: Prediabetes and diabetes are common and serious public health problems, and high blood glucose can lead to serious cardiovascular complications. The purpose of this article was to explore the link between CVH levels and the incidence of prediabetes and diabetes in people over 20 years old, and whether serum vitamin D status could alter this relationship. MATERIALS AND METHODS: Data, from six consecutive cycles of the NHANES database from 2007 to 2018 were combined, eligible participants were aged ≥20 years. After excluding missing data, a total of 19,992 subjects were enrolled in the study. Significant risk factors for prediabetes and diabetes were analyzed using univariate and multivariate logistic regression. Exploring the interaction of VD and CVH on prediabetes and diabetes based on multifactorial regression analysis. RESULTS: The prevalence of prediabetes among all participants was 36.15% and the prevalence of diabetes was 16.39%. CVH and vitamin D levels are influential factors in prediabetes and diabetes, and are negatively associated with the risk of developing prediabetes and diabetes. Compared with normoglycemia, poorer CVH and vitamin D deficiency only had a synergistic multiplicative interaction on the development of diabetes, and no significant interaction was observed for the development of prediabetes. Compared with prediabetes, poorer CVH and vitamin D deficiency still had a synergistic additive interaction on the development of diabetes. CONCLUSIONS: Although the cross-sectional study only determine the association and do not prove causality, the current results can be used to prompt people to improve their lifestyle and risk factors to prevent prediabetes or diabetes through higher CVH and adequate Vitamin D.

USP7 Promotes TGF-ß1 Signaling by De-Ubiquitinating Smad2/Smad3 in Pulmonary Fibrosis.

BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is a long-term, progressive, and irreversible pulmonary interstitial disease. The activation of Smad family member 2 (Smad2) and Smad3 transcription factors by transforming growth factor ß-1 (TGF-ß1) is a critical event in the pathogenesis of IPF. However, there is still a lack of understanding regarding the molecular mechanisms governing Smad2 and Smad3 proteins. Ubiquitin-specific protease 7 (USP7) is a deubiquitinase that plays a vital role in regulating protein stability within cells. However, its regulation of the TGF-ß signaling pathway and its significance in IPF remain undiscovered. This study aims to clarify the function of USP7 in the TGF-ß signaling pathway, while simultaneously exploring the specific molecular mechanisms involved. Additionally, this study seeks to evaluate the therapeutic potential of targeted USP7 inhibitors in IPF, thereby providing novel insights for the diagnosis and management of IPF. METHODS: We first detected the expression of USP7 in lung tissues of mice with Bleomycin (BLM)-induced pulmonary fibrosis and in Beas-2B cells treated with or without TGF-ß1 through Western blot analysis. Subsequently, we explored the influence of USP7 on fibrotic processes and the TGF-ß1 signaling pathway, utilizing in vitro and in vivo studies. Finally, we assessed the effectiveness of USP7-specific inhibitors in an IPF murine model. RESULTS: In the present study, USP7 was found to de-ubiquitinate Smad2 and Smad3, consequently increasing their stability and promoting the TGF-ß1-induced production of profibrotic proteins including α-smooth muscle actin (α-SMA) and fibronectin 1 (FN-1). Inhibition or knockdown of USP7 resulted in decreased levels of Smad2 and Smad3 proteins, leading to reduced expression of FN-1, Collagen Type I Alpha 1 Chain (Col1A1), and α-SMA induced by TGF-ß1 in human pulmonary epithelial cells. These findings demonstrate that overexpression of USP7 reduces Smad2/3 ubiquitination, whereas inhibition or knockdown of USP7 enhances their ubiquitination. USP7 is abundantly expressed in IPF lungs. The expressions of USP7, Smad2, and Smad3 were upregulated in bleomycin-induced lung injury. The USP7 inhibitor P22077 reduced the expression of FN-1 and type I collagen as well as Smad2/3 and collagen deposition in lung tissue in a model of pulmonary fibrosis induced by bleomycin. CONCLUSIONS: This study demonstrates that USP7 promotes TGF-ß1 signaling by stabilizing Smad2 and Smad3. The contribution of USP7 to the progression of IPF indicates it may be a viable treatment target.

Exploration of resting-state brain functional connectivity as preclinical markers for arousal prediction in prolonged disorders of consciousness: A pilot study based on functional near-infrared spectroscopy.

BACKGROUND: There is no diagnostic assessment procedure with moderate or strong evidence of use, and evidence for current means of treating prolonged disorders of consciousness (pDOC) is sparse. This may be related to the fact that the mechanisms of pDOC have not been studied deeply enough and are not clear enough. Therefore, the aim of this study was to explore the mechanism of pDOC using functional near-infrared spectroscopy (fNIRS) to provide a basis for the treatment of pDOC, as well as to explore preclinical markers for determining the arousal of pDOC patients. METHODS: Five minutes resting-state data were collected from 10 pDOC patients and 13healthy adults using fNIRS. Based on the concentrations of oxyhemoglobin (HbO) and deoxyhemoglobin (HbR) in the time series, the resting-state cortical brain functional connectivity strengths of the two groups were calculated, and the functional connectivity strengths of homologous and heterologous brain networks were compared at the sensorimotor network (SEN), dorsal attention network (DAN), ventral attention network (VAN), default mode network (DMN), frontoparietal network (FPN), and visual network (VIS) levels. Univariate binary logistic regression analyses were performed on brain networks with statistically significant differences to identify brain networks associated with arousal in pDOC patients. The receiver operating characteristic (ROC) curves were further analyzed to determine the cut-off value of the relevant brain networks to provide clinical biomarkers for the prediction of arousal in pDOC patients. RESULTS: The results showed that the functional connectivity strengths of oxyhemoglobin (HbO)-based SEN∼SEN, VIS∼VIS, DAN∼DAN, DMN∼DMN, SEN∼VIS, SEN∼FPN, SEN∼DAN, SEN∼DMN, VIS∼FPN, VIS∼DAN, VIS∼DMN, HbR-based SEN∼SEN, and SEN∼DAN were significantly reduced in the pDOC group and were factors that could reflect the participants' state of consciousness. The cut-off value of resting-state functional connectivity strength calculated by ROC curve analysis can be used as a potential preclinical marker for predicting the arousal state of subjects. CONCLUSION: Resting-state functional connectivity strength of cortical networks is significantly reduced in pDOC patients. The cut-off values of resting-state functional connectivity strength are potential preclinical markers for predicting arousal in pDOC patients.

Analysis of the occurrence and liver function characteristics of arsenic-associated liver injury during the treatment of pediatric patients with acute promyelocytic leukemia.

Liver injury during arsenic treatment for acute promyelocytic leukemia was previously reported in adults, but not comprehensively in children until now. This study aims to investigate liver injury in pediatric patients with APL, changes in liver function during treatment, and compare the effects of Arsenic trioxide (ATO) and Realgar-Indigo naturalis formula (RIF) on liver function. One hundred and eighty-six patients with 3076 patient tests were analyzed, who were enrolled in the Chinese Children's Leukemia Group (CCLG)-APL2016 Protocol database between November 2016 and November 2018 in 38 hospitals across China(ChiCTR-OIN-17011227). Twenty of 164 patients (12.2%) suffered from liver injury after treatment with arsenic. In addition, sixteen (80%) cases of liver injury occurred during the induction period of treatment. What's not disheartening was that 18 (90%) cases of liver injury were transient, occurring at a median time of 17 days after exposure to arsenic. More importantly, the risk of liver injury associated with RIF was not higher than that associated with ATO (RR = 0.854, 95% CI: 0.292-2.495). Otherwise, the ALP of 18 cases of liver injury was not higher than the ULN of ALP. Thus, the incidence of liver injury associated with arsenic in pediatric patients with APL was similar to that in adult patients and the risk of liver injury associated with RIF was not higher than that associated with ATO. Since ALP was not higher in pediatric APL patients with liver injury, further research is needed to explore whether ALP is an index of liver injury in children.

An interfacial host-guest inclusion complex regulated supramolecular nanocomposite hydrogel showing tunable mechanical strength, self-healing, strain sensitivity and NIR responsiveness.

The development of supramolecular nanocomposite hydrogels with good mechanical properties and multifunctional characteristics remains challenging. The reinforced role of interfacial weak interactions is important for the mechanical properties of nanocomposite hydrogels. Here, a dynamic host-guest inclusion complex from the host molecule CB[7] and guest units was employed to prepare Fe3O4 hybrid supramolecular nanocomposite hydrogels. The results show that the as-obtained hydrogel with a porous structure was prepared. The CB[7]-modified Fe3O4 (Fe3O4@CB[7]) nanoparticles severed as a cross-linker for fabricating the hydrogel's network. By changing the Fe3O4@CB[7] content, their tensile stress ranged from 0.102 to 0.403 MPa and their compression stress ranged (70% compression strain) from 0.059 to 0.775 MPa. By changing the guest units, their tensile stress ranged from 0.3 MPa to 0.403 MPa. The self-healing efficiency of the hydrogels was 99% after 48 h at room temperature. The as-obtained hydrogels with strain sensitivity can be applied for detecting the movement of an elbow and finger. The supramolecular hydrogel exhibits NIR responsiveness, self-healing, injectability, tunable mechanical strength and conductive ability, and can be used in flexible electronics.

A review on over-sampling techniques in classification of multi-class imbalanced datasets: insights for medical problems.

There has been growing attention to multi-class classification problems, particularly those challenges of imbalanced class distributions. To address these challenges, various strategies, including data-level re-sampling treatment and ensemble methods, have been introduced to bolster the performance of predictive models and Artificial Intelligence (AI) algorithms in scenarios where excessive level of imbalance is present. While most research and algorithm development have been focused on binary classification problems, in health informatics there is an increased interest in the field to address the problem of multi-class classification in imbalanced datasets. Multi-class imbalance problems bring forth more complex challenges, as a delicate approach is required to generate synthetic data and simultaneously maintain the relationship between the multiple classes. The aim of this review paper is to examine over-sampling methods tailored for medical and other datasets with multi-class imbalance. Out of 2,076 peer-reviewed papers identified through searches, 197 eligible papers were chosen and thoroughly reviewed for inclusion, narrowing to 37 studies being selected for in-depth analysis. These studies are categorised into four categories: metric, adaptive, structure-based, and hybrid approaches. The most significant finding is the emerging trend toward hybrid resampling methods that combine the strengths of various techniques to effectively address the problem of imbalanced data. This paper provides an extensive analysis of each selected study, discusses their findings, and outlines directions for future research.

Hydrogenation of CO2 to formate catalyzed by a Ru catalyst supported on a copolymerized porous organic polymer.

The catalytic hydrogenation of carbon dioxide to formate is of great interest due to its significant role in CO2 utilization. In this study, a novel heterogeneous Ru(III) catalyst was prepared by immobilizing RuCl3 on a porous organic polymer (POP) obtained from 1,4-phthalaldehyde (PTA) and 4,4'-biphenyldicarboxaldehyde (BPDA) with melamine. A copolymerization strategy utilizing monomers of varying lengths was employed to prepare the POP-supported Ru catalyst with adjustable porosity. The optimization of the framework porosity resulted in enhanced CO2 affinity, accelerated mass transfer, and a remarkable enhancement in catalytic activity. A high turnover number (TON) of 2458 was achieved for the CO2 hydrogenation to formate in 2 h with catalyst Cat-3 under 3 MPa (CO2/H2 = 1 : 1) at 120 °C in 1 M Et3N aqueous solution. Moreover, the Cat-3 demonstrated good recyclability and was able to be reused for five consecutive runs, resulting in a high total TON of 9971.

Synthesis and biological evaluation of sulfonamide derivatives containing imidazole moiety as ALK5 inhibitors.

Four series of sulfonamide derivatives (13a-b, 14a-d, 15a-b, and 16a-d) were synthesized and evaluated for their activin receptor-like kinase 5 (ALK5) inhibitory activities. Of these, compounds 13b (IC50 = 0.130 µM) and 15a (IC50 = 0.130 µM) showed the highest inhibitory activities against ALK5 kinase, with activities similar to the positive control LY-2157299. Notably, we discovered that introduction of sulfonamide group at the 2-position of the central imidazole ring significantly increased ALK5 inhibitory activity. Compounds 13b and 15a did not show toxicity in A549 cells up to the maximum concentration of 50 µM, and effectively inhibited TGF-ß1-induced Smad-signaling and cell motility in A549 cells. The results indicate that compounds 13b and 15a are worth of further development as anticancer agents.

No-Reference Image Quality Assessment Combining Swin-Transformer and Natural Scene Statistics.

No-reference image quality assessment aims to evaluate image quality based on human subjective perceptions. Current methods face challenges with insufficient ability to focus on global and local information simultaneously and information loss due to image resizing. To address these issues, we propose a model that combines Swin-Transformer and natural scene statistics. The model utilizes Swin-Transformer to extract multi-scale features and incorporates a feature enhancement module and deformable convolution to improve feature representation, adapting better to structural variations in images, apply dual-branch attention to focus on key areas, and align the assessment more closely with human visual perception. The Natural Scene Statistics compensates information loss caused by image resizing. Additionally, we use a normalized loss function to accelerate model convergence and enhance stability. We evaluate our model on six standard image quality assessment datasets (both synthetic and authentic), and show that our model achieves advanced results across multiple datasets. Compared to the advanced DACNN method, our model achieved Spearman rank correlation coefficients of 0.922 and 0.923 on the KADID and KonIQ datasets, respectively, representing improvements of 1.9% and 2.4% over this method. It demonstrated outstanding performance in handling both synthetic and authentic scenes.

Gene signatures of copper metabolism related genes may predict prognosis and immunity status in Ewing's sarcoma.

Background: Cuproptosis is copper-induced cell death. Copper metabolism related genes (CMRGs) were demonstrated that used to assess the prognosis out of tumors. In the study, CMRGs were tested for their effect on TME cell infiltration in Ewing's sarcoma (ES). Methods: The GEO and ICGC databases provided the mRNA expression profiles and clinical features for downloading. In the GSE17674 dataset, 22prognostic-related copper metabolism related genes (PR-CMRGs) was identified by using univariate regression analysis. Subsequently, in order to compare the survival rates of groups with high and low expression of these PR-CMRGs,Kaplan-Meier analysis was implemented. Additionally, correlations among them were examined. The study employed functional enrichment analysis to investigate probable underlying pathways, while GSVA was applied to evaluate enriched pathways in the ES (Expression Set). Through an unsupervised clustering algorithm, samples were classified into two clusters, revealing significant differences in survival rates and levels of immune infiltration. Results: Using Lasso and step regression methods, five genes (TFRC, SORD, SLC11A2, FKBP4, and AANAT) were selected as risk signatures. According to the Kaplan-Meier survival analysis, the high-risk group had considerably lower survival rates than the low-risk group(p=6.013e-09). The area under the curve (AUC) values for the receiver operating characteristic (ROC) curve were 0.876, 0.883, and 0.979 for 1, 3, and 5 years, respectively. The risk model was further validated in additional datasets, namely GSE63155, GSE63156, and the ICGC datasets. To aid in outcome prediction, a nomogram was developed that incorporated risk levels and clinical features. This nomogram's performance was effectively validated through calibration curves.Additionally, the study evaluated the variations in immune infiltration across different risk groups, as well as high-expression and low-expression groups. Importantly, several drugs were identified that displayed sensitivity, offering potential therapeutic options for ES. Conclusion: The findings above strongly indicate that CMRGs play crucial roles in predicting prognosis and immune status in ES.

Multiple Exposures to Sevoflurane General Anesthesia During Pregnancy Inhibit CaMKII/CREB Axis by Downregulating HCN2 to Induce an Autism-Like Phenotype in Offspring Mice.

The objective of this investigation was to examine the impact of multiple exposures to general anesthesia (GA) with sevoflurane on the offspring of pregnant mice, as well as to elucidate the underlying mechanism. Neurodevelopmental assessments, including various reflexes and behavioral tests, were conducted on the offspring in the GA group to evaluate neuronal cell development. Furthermore, neonatal mouse neuronal cells were isolated and transfected with a high-expression CREB vector (pcDNA3.1-CREB), followed by treatment with sevoflurane (0.72 mol/L), ZD7288 (50 µmol/L), and KN-62 (10 µmol/L), or a combination of these compounds. The expression of relevant genes was then analyzed using qRT-PCR and western blot techniques. In comparison to the sham group, neonatal mice in the GA group exhibited significantly prolonged latencies in surface righting reflex, geotaxis test, and air righting reflex. Furthermore, there was a notable deceleration in the development of body weight and tail in the GA group. These mice also displayed impairments in social ability, reduced reciprocal social interaction behaviors, diminished learning capacity, and heightened levels of anxious behaviors. Additionally, synaptic trigger malfunction was observed, along with decreased production of c-Fos and neurotrophic factors. Sevoflurane was found to notably decrease cellular c-Fos and neurotrophic factor production, as well as the expression of HCN2 and CaMKII/CREB-related proteins. The inhibitory effects of sevoflurane on HCN2 or CaMKII channels were similar to those observed with ZD7288 or KN-62 inhibition. However, overexpression of CREB mitigated the impact of sevoflurane on neuronal cells. Repetitive exposure to sevoflurane general anesthesia while pregnant suppresses the CaMKII/CREB pathway, leading to the development of autism-like characteristics in offspring mice through the reduction of HCN2 expression.

Ficus hirta Vahl. ameliorates liver fibrosis by triggering hepatic stellate cell ferroptosis through GSH/GPX4 pathway.

ETHNOPHARMACOLOGICAL RELEVANCE: Ficus hirta Vahl., a traditional Chinese medicine commonly used in the Lingnan region, has been extensively used for liver disease treatment in China. Its notable antioxidant and anti-inflammatory properties have been reported in previous studies. However, its potential effect and underlying mechanism on liver fibrosis remains unclear. AIM OF STUDY: This study was aimed to investigate the effect and its underlying mechanism of Ficus hirta Vahl on liver fibrosis in vitro and in vivo. MATERIALS AND METHODS: The main components of Ficus hirta Vahl in blood were investigated by using UPLC-Q/TOF-MS/MS. Two animal models of liver fibrosis, the CCl4 and MCD induced mice, were used to assess the efficacy of Ficus hirta Vahl on liver fibrosis. Metabolomics was used to detect the level of metabolites in the serum of liver fibrosis mice after Ficus hirta Vahl treatment. Furthermore, the mechanism was validated in vitro using the human liver stellate cell line LX-2. The binding affinities of the active ingredients of Ficus hirta Vahl to the main targets of liver fibrosis were also determined. Finally, we identified the key active ingredients responsible for the treatment of liver fibrosis in vivo. RESULTS: Fibrosis and inflammatory markers were significant down-regulation in both CCl4 and MCD induced liver fibrosis mice after Ficus hirta Vahl administration in a dose-dependent manner. We found that Ficus hirta Vahl may primarily exert its effect on liver fibrosis through the glutathione metabolic pathway. Importantly, the glutathione metabolic pathway is closely associated with ferroptosis, and our subsequent in vitro experiments provided evidence supporting this association. Ficus hirta Vahl was found to modulate the GSH/GPX4 pathway, ultimately leading to the amelioration of liver fibrosis. Moreover, using serum pharmacochemistry and molecular docking, we successfully identified apigenin as a probable efficacious monomer for the management of liver fibrosis and subsequently validated its efficacy in mice with CCl4-induced hepatic fibrosis. CONCLUSION: Ficus hirta Vahl triggered the ferroptosis of hepatic stellate cell by regulating the GSH/GPX4 pathway, thereby alleviating liver fibrosis in mice. Moreover, apigenin is a key compound in Ficus hirta Vahl responsible for the effective treatment of liver fibrosis.

Eutrophication driven macrophyte-derived organic matter decomposition to methane emission relates to co-metabolism effect in freshwater sediments.

Lakes and wetlands play pivotal roles in global organic matter storage, receiving significant inputs of organic material. However, the co-metabolic processes governing the decomposition of these organic materials and their impact on greenhouse gas emissions remain inadequately understood. This study aims to assess the effects of mixed decomposition involving macrophytes and cyanobacteria on carbon emissions. A series of microcosms was established to investigate the decomposition of macrophyte residues and algae over a period of 216 days. A two-component kinetic model was utilized to estimate methane (CH4) production rates. Gas isotope technology was employed to discern the contributions of CH4 produced by macrophyte residues or algae. Quantitative PCR and analysis of 16S rRNA gene amplicons were employed to assess changes in functional genes and microbial communities. There were significant differences in the cumulative carbon release from the decomposition of different plant types due to the addition of carbon sources. After adding algae, the cumulative emission of CH4 increased significantly. The δ13C-CH4 partitioning indicated that CH4 originated exclusively from the fresh organic carbon of macrophyte residues, while it shifted to algae source after adding algae. The synergistic effect of the mixed decomposition on the CH4 emissions was greater than the sum of the individual decompositions. The microbial community richness was higher in the single plant residue treatment compared to the mixed treatment with algae addition, while microbial evenness in the sediment increased steadily in each treatment. Our findings emphasize the pronounced co-metabolic effect observed during the mixed decomposition of macrophytes and cyanobacteria.

Experimental and Numerical Investigation Integrated with Machine Learning (ML) for the Prediction Strategy of DP590/CFRP Composite Laminates.

This study unveils a machine learning (ML)-assisted framework designed to optimize the stacking sequence and orientation of carbon fiber-reinforced polymer (CFRP)/metal composite laminates, aiming to enhance their mechanical properties under quasi-static loading conditions. This work pioneers the expansion of initial datasets for ML analysis in the field by uniquely integrating the experimental results with finite element simulations. Nine ML models, including XGBoost and gradient boosting, were assessed for their precision in predicting tensile and bending strengths. The findings reveal that the XGBoost and gradient boosting models excel in tensile strength prediction due to their low error rates and high interpretability. In contrast, the decision trees, K-nearest neighbors (KNN), and random forest models show the highest accuracy in bending strength predictions. Tree-based models demonstrated exceptional performance across various metrics, notably for CFRP/DP590 laminates. Additionally, this study investigates the impact of layup sequences on mechanical properties, employing an innovative combination of ML, numerical, and experimental approaches. The novelty of this study lies in the first-time application of these ML models to the performance optimization of CFRP/metal composites and in providing a novel perspective through the comprehensive integration of experimental, numerical, and ML methods for composite material design and performance prediction.

Roles of Mitochondrial Dysfunction in Diabetic Kidney Disease: New Perspectives from Mechanism to Therapy.

Diabetic kidney disease (DKD) is a common microvascular complication of diabetes and the main cause of end-stage renal disease around the world. Mitochondria are the main organelles responsible for producing energy in cells and are closely involved in maintaining normal organ function. Studies have found that a high-sugar environment can damage glomeruli and tubules and trigger mitochondrial dysfunction. Meanwhile, animal experiments have shown that DKD symptoms are alleviated when mitochondrial damage is targeted, suggesting that mitochondrial dysfunction is inextricably linked to the development of DKD. This article describes the mechanisms of mitochondrial dysfunction and the progression and onset of DKD. The relationship between DKD and mitochondrial dysfunction is discussed. At the same time, the progress of DKD treatment targeting mitochondrial dysfunction is summarized. We hope to provide new insights into the progress and treatment of DKD.

Exosomal noncoding RNAs: decoding their role in thyroid cancer progression.

Exosomes, as pivotal entities within the tumor microenvironment, orchestrate intercellular communication through the transfer of diverse molecules, among which non-coding RNAs (ncRNAs) such as miRNAs, lncRNAs, and circRNAs play a crucial role. These ncRNAs, endowed with regulatory functions, are selectively incorporated into exosomes. Emerging evidence underscores the significance of exosomal ncRNAs in modulating key oncogenic processes in thyroid cancer (TC), including proliferation, metastasis, epithelial-mesenchymal transition (EMT), angiogenesis, and immunoediting. The unique composition of exosomes shields their cargo from enzymatic and chemical degradation, ensuring their integrity and facilitating their specific expression in plasma. This positions exosomal ncRNAs as promising candidates for novel diagnostic and prognostic biomarkers in TC. Moreover, the potential of exosomes in the therapeutic landscape of TC is increasingly recognized. This review aims to elucidate the intricate relationship between exosomal ncRNAs and TC, fostering a deeper comprehension of their mechanistic involvement. By doing so, it endeavors to propel forward the exploration of exosomal ncRNAs in TC, ultimately paving the way for innovative diagnostic and therapeutic strategies predicated on exosomes and their ncRNA content.

The association between diabetes mellitus and prostate cancer: a meta-analysis and Mendelian randomization.

BACKGROUND: Prostate cancer is one of the most common types of cancer in the US, and it has a high mortality rate. Diabetes mellitus is also a dangerous health condition. While some studies have examined the relationship between diabetes mellitus and the risk of prostate cancer, there is still some debate on the matter. This study aims to carefully assess the relationship between prostate cancer and diabetes from both real-world and genetic-level data. METHODS: This meta-analysis was conducted following the PRISMA 2020 reporting guidelines. The study searched three databases including Medline, Embase and Cochrane. The studies about the incidence risk of prostate cancer with diabetes mellitus were included and used to evaluate the association. The odds ratio (OR), risk ratio (RR) and 95% confidence intervals (95% CI) were estimated using Random Effects models and Fixed Effects models. Mendelian randomization study using genetic variants was also conducted. RESULTS: A total of 72 articles were included in this study. The results showed that risk of prostate cancer decreased in diabetes patients. And the influence was different in different regions. This study also estimated the impact of body mass index (BMI) in the diabetes populations and found that the risk decreased in higher BMI populations. The MR analysis found that diabetes mellitus exposure reduced the risk of prostate cancer in the European population and Asia populations. Conclusions The diabetes mellitus has a protective effect on prostate cancer. And the influence of obesity in diabetes mellitus plays an important role in this effect.

Benthic clade II-type nitrous oxide reducers suppress nitrous oxide emissions in shallow lakes.

Shallow lakes, recognized as hotspots for nitrogen cycling, contribute to the emission of the potent greenhouse gas nitrous oxide (N2O), but the current emission estimates for this gas have a high degree of uncertainty. However, the role of N2O-reducing bacteria (N2ORB) as N2O sinks and their contribution to N2O reduction in aquatic ecosystems in response to N2O dynamics have not been determined. Here, we investigated the N2O dynamics and microbial processes in the nitrogen cycle, which included both N2O production and consumption, in five shallow lakes spanning approximately 500 km. The investigated sites exhibited N2O oversaturation, with excess dissolved N2O concentrations (ΔN2O) ranging from 0.55 ± 0.61 to 53.17 ± 15.75 nM. Sediment-bound N2O (sN2O) was significantly positively correlated with the nitrate concentration in the overlying water (p < 0.05), suggesting that nitrate accumulation contributes to benthic N2O generation. High N2O consumption activity (RN2O) corresponded to low ΔN2O. In addition, a significant negative correlation was found between RN2O and nir/nosZ, showing that bacteria encoding nosZ contributed to N2O consumption in the benthic sediments. Redundancy analysis indicated that benthic functional genes effectively reflected the variations in RN2O and ∆N2O. qPCR analysis revealed that the clade II nosZ gene was more sensitive to ΔN2O than the clade I nosZ gene. Furthermore, four novel genera of potential nondenitrifying N2ORB were identified based on metagenome-assembled genome analysis. These genera, which are affiliated with clade II, lack genes responsible for N2O production. Collectively, benthic N2ORB, especially for clade II-type N2ORB, harnesses N2O consumption activity leading to low N2O emissions from shallow lakes. This study advances our knowledge of the role of benthic clade II-type N2ORB in regulating N2O emissions in shallow lakes.

Synthesis of amide derivatives containing the imidazole moiety and evaluation of their anti-cardiac fibrosis activity.

Three series of N-{[4-([1,2,4]triazolo[1,5-α]pyridin-6-yl)-5-(6-methylpyridin-2-yl)-1H-imidazol-2-yl]methyl}acetamides (14a-d, 15a-n, and 16a-f) were synthesized and evaluated for activin receptor-like kinase 5 (ALK5) inhibitory activities in an enzymatic assay. The target compounds showed high ALK5 inhibitory activity and selectivity. The half maximal inhibitory concentration (IC50) for phosphorylation of ALK5 of 16f (9.1 nM), the most potent compound, was 2.7 times that of the clinical candidate EW-7197 (vactosertib) and 14 times that of the clinical candidate LY-2157299. The selectivity index of 16f against p38α mitogen-activated protein kinase was >109, which was much higher than that of positive controls (EW-7197: >41, and LY-2157299: 4). Furthermore, a molecular docking study provided the interaction modes between the target compounds and ALK5. Compounds 14c, 14d, and 16f effectively inhibited the protein expression of α-smooth muscle actin (α-SMA), collagen I, and tissue inhibitor of metalloproteinase 1 (TIMP-1)/matrix metalloproteinase 13 (MMP-13) in transforming growth factor-ß-induced human umbilical vein endothelial cells. Compounds 14c and 16f showed especially high activity at low concentrations, which suggests that these compounds could inhibit myocardial cell fibrosis. Compounds 14c, 14d, and 16f are potential preclinical candidates for the treatment of cardiac fibrosis.

The expression of CTLA-4 in hepatic alveolar echinococcosis patients and blocking CTLA-4 to reverse T cell exhaustion in Echinococcus multilocularis-infected mice.

Alveolar echinococcosis (AE) is a zoonotic parasitic disease caused by the infection of Echinococcus multilocularis (E. multilocularis) larvae. Cytotoxic T-lymphocyte antigen 4 (CTLA-4) produces inhibitory signals and induces T cell exhaustion, thereby inhibiting the parasiticidal efficacy of the liver immune system. Therefore, the purpose of this study is to explore how T-cell exhaustion contributes to AE and whether blocking CTLA-4 could reverse T cell exhaustion. Here we discovered that the expression of CTLA-4 was increased in the infiltrating margin around the lesion of the liver from AE patients by using western blot and immunohistochemistry assay. Multiple fluorescence immunohistochemistry identified that CTLA-4 and CD4/CD8 molecules were co-localized. For in vitro experiments, it was found that the sustained stimulation of E. multilocularis antigen could induce T cell exhaustion, blocking CTLA-4-reversed T cell exhaustion. For in vivo experiments, the expression of CTLA-4 was increased in the liver of E. multilocularis-infected mice, and the CTLA-4 and CD4/CD8 molecules were co-localized. Flow cytometry analysis demonstrated that the percentages of both CD4+ T cells and CD8+ T cells in the liver and peripheral blood were significantly increased and induced T exhaustion. When the mice were treated with anti-CTLA-4 antibodies, the number and weight of the lesions decreased significantly. Meanwhile, the flow cytometry results suggested that blocking CTLA-4 could effectively reverse T cell exhaustion and reactivate immune function. Our work reveals that blocking CTLA-4 could effectively reverse the T cell exhaustion caused by E. multilocularis and could be used as a novel target for the treatment of AE.