Association of serum five heavy metals level with all-cause and cause-specific mortality: a large population-based cohort study.

The study aimed to explore the association between five heavy metals exposure (Cadmium, Lead, Mercury, Manganese, and Selenium) and mortality [all-cause, cardiovascular disease (CVD), and cancer-related]. We integrated the data into the National Health and Nutrition Examination Survey from 2011 to 2018 years. A total of 16,092 participants were recruited. The link between heavy metals exposure and mortality was analyzed by constructing a restricted cubic spline (RCS) curve, Cox proportional hazard regression model, and subgroup analysis. The RCS curve was used to show a positive linear relationship between Cadmium, Lead, and all-cause mortality. In contrast, there was a negative linear correlation between Mercury and all-cause mortality. Additionally, Manganese and Selenium also had a J-shaped and L-shaped link with all-cause mortality. The positive linear, positive linear, negative liner, J-shaped, and L-shaped relationships were observed for Cadmium, Lead, Mercury, Manganese, and Selenium and CVD mortality, respectively. Cadmium, Lead, Mercury, and Selenium were observed to exhibit positive linear, U-shaped, negative linear, and L-shaped relationships with cancer-related mortality, respectively. There was an increase and then a decrease in the link between Manganese and cancer-related morality. This study revealed the correlation between the content of different elements and different types of mortality in the U.S. general population.

Identification of key biomarkers for predicting CAD progression in inflammatory bowel disease via machine-learning and bioinformatics strategies.

The study aimed to identify the biomarkers for predicting coronary atherosclerotic lesions progression in patients with inflammatory bowel disease (IBD). Related transcriptome datasets were seized from Gene Expression Omnibus database. IBD-related modules were identified via Weighted Gene Co-expression Network Analysis. The 'Limma' was applied to screen differentially expressed genes between stable coronary artery disease (CAD) and acute myocardial infarction (AMI). Subsequently, we employed protein-protein interaction (PPI) network and three machine-learning strategies to further screen for candidate hub genes. Application of the receiver operating characteristics curve to quantitatively evaluate candidates to determine key diagnostic biomarkers, followed by a nomogram construction. Ultimately, we performed immune landscape analysis, single-gene GSEA and prediction of target-drugs. 3227 IBD-related module genes and 570 DEGs accounting for AMI were recognized. Intersection yielded 85 shared genes and mostly enriched in immune and inflammatory pathways. After filtering through PPI network and multi-machine learning algorithms, five candidate genes generated. Upon validation, CTSD, CEBPD, CYP27A1 were identified as key diagnostic biomarkers with a superior sensitivity and specificity (AUC > 0.8). Furthermore, all three genes were negatively correlated with CD4+ T cells and positively correlated with neutrophils. Single-gene GSEA highlighted the importance of pathogen invasion, metabolism, immune and inflammation responses during the pathogenesis of AMI. Ten target-drugs were predicted. The discovery of three peripheral blood biomarkers capable of predicting the risk of CAD proceeding into AMI in IBD patients. These identified biomarkers were negatively correlated with CD4+ T cells and positively correlated with neutrophils, indicating a latent therapeutic target.

Magnetosheath jets at Jupiter and across the solar system.

The study of jets in the Earth's magnetosheath has been a subject of extensive investigation for over a decade due to their profound impact on the geomagnetic environment and their close connection with shock dynamics. While the variability of the solar wind and its interaction with Earth's magnetosphere provide valuable insights into jets across a range of parameters, a broader parameter space can be explored by examining the magnetosheath of other planets. Here we report the existence of anti-sunward and sunward jets in the Jovian magnetosheath and show their close association with magnetic discontinuities. The anti-sunward jets are possibly generated by a shock-discontinuity interaction. Finally, through a comparative analysis of jets observed at Earth, Mars, and Jupiter, we show that the size of jets scales with the size of bow shock.

METTL3-mediated m6 A methylation of TRAF5 inhibits lung adenocarcinoma cell metastasis via activation of the PI3K/AKT/NF-κB signaling pathway.

Tumor necrosis factor receptor-associated factor 5 (TRAF5) has been implicated in the pathogenesis of human malignancies. This work aimed to clarify the role of TRAF5 in lung adenocarcinoma (LUAD) progression. Herein, we uncovered that TRAF5 level was reduced in LUAD tissues. Low TRAF5 expression correlated with dismal prognosis in LUAD patients. Moreover, upregulated TRAF5 impeded cell viability, migration, and invasion, induced apoptosis in vitro, as well as impaired tumorigenicity in vivo. However, depletion of TRAF5 revealed opposing results. Moreover, TRAF5 was identified as the downstream target of methyltransferase-like 3 (METTL3)-elicited N6 -methyladenosine (m6 A) modification. METTL3 stabilized TRAF5 mRNA and positively modulated TRAF5 level. Further, TRAF5 depletion relieved the repressive phenotype caused by METTL3 addition. In addition, it was manifested that the METTL3/TRAF5 axis served as an inhibitor in LUAD through the PI3K/AKT/Nuclear Factor-Kappa B (NF-κB) signaling. Collectively, we propose that METTL3-mediated TRAF5 m6 A modification exerted as a vital tumor inhibitory function in LUAD development. The METTL3/TRAF5 axis may be a critical effector of LUAD progression.

Hepatoprotective Effect of Tea Composite Solid Beverage on Alcohol-Caused Rat Liver Injury.

Alcoholic liver disease (ALD) remains a major cause of liver-related morbidity and mortality worldwide. Tea polyphenols (TPs) possess strong antioxidant activity; cassia seed extract (CSE) has the effect of brightening the eyes; and Ampelopsis grossedentata extract (AGE) has the function of protecting the liver. However, the synergistic hepatoprotective effect of TP, AGE and CSE as a joint formulation is unknown. This study aimed to investigate the role of a tea solid beverage, composed of TP, AGE and CSE, on chronic alcoholic liver injury in rats and its underlying mechanisms via the analysis of transcriptomics and gut microbiota. The histopathological findings revealed that the tea solid beverage could reduce the production of fat vacuoles and inflammatory cell infiltration. Additionally, the tea solid beverage was found to effectively relieve the increase in the AST (from 424.85 U/L to 180.17 U/L), ALT (from 139.95 U/L to 85.88 U/L) and LDH (from 21.16 U/L to 13.35 U/L) enzyme activities and the expression of the inflammatory factors TNF-α (from 394.02 pg/mL to 214.44 pg/mL) and IL-6 (from 208.46 pg/mL to 116.59 pg/mL) caused by alcohol consumption. Further, it significantly enhanced the GSH concentration (from 4.53 pg/mL to 8.08 pg/mL) and SOD activity (from 84.70 U/mL to 156.94 U/mL) and decreased the MDA (from 58.61 mmol/mL to 36.58 mmol/mL) and TG (from 7.07 mmol/L to 3.43 mmol/L)) concentrations in the liver of rats. The analysis and identification of transcriptomics showed that the tea solid beverage intervention primarily protected the liver of rats with chronic alcoholic injury by up-regulating the differential gene Hmgcs1 in order to increase the synthesis of ketone bodies and by down-regulating the differential gene Pfkfb1 for the purpose of decreasing the glucose metabolism. Additionally, it was found that the tea solid beverage could significantly change the composition of intestinal flora in drinking rats by regulating mineral absorption, the pathways of bile secretion, the adipocytokine signaling pathway and the peroxisome balance of the intestinal flora, in order to protect alcohol-drinking rats' livers. In conclusion, the tea solid beverage, consisting of TP, AGE and CSE, is a functional drink that prevents ketone metabolism, glucose metabolism and microbiome disorders induced by alcohol intake.

Estimation of life history traits and stock status for Scomber japonicus based on data-limited method.

The age-structure data is usually unavailable for most traditional fishery species in the East China Sea. The data-limited method is thus particularly important to understand life history and population dynamics of commercial fishes. At the offshore waters of southern Zhejiang, Chub mackerel (Scomber japonicus) is one of the dominant economic species. Based on fork length data from 2016 to 2020, we estimated its life history traits with the data-limited method, including the growth parameters and mortality coefficients. We further evaluated the status of Chub mackerel by the yield per recruitment (YPR) model. The results showed that the relationship between fork length (L) and body weight (W) based on 1606 samples was estimated to be W=4.18×10-3L3.28(R2=0.96). The asymptotic fork length L∞ of Chub mackerel was 28.34 cm, the growth rate was 0.36 a-1, and the initial theoretical age was -0.40 a. The total mortality was estimated as 1.67 a-1, and the estimated natural mortality (M) was 0.85 a-1. The fishing mortality (F) was 0.82 a-1, and the development rate was 0.49. The current capture age was estimated to be 1.78 a, while the capture fork length was 15.44 cm. The YPR model results showed YPR value showed a trend of increasing and then decreasing with the increases of F. The values of biological reference points F0.1 and Fmax were 0.97 a-1 and 4.55 a-1, respectively, which were higher than the value of current F. The sensitivity analysis showed that the uncertainty of M greatly influenced the estimation results of YPR and biological reference points. A decrease in M significantly increased the YPR value, but F0.1 and Fmax decreased. The status of Chub mackerel stock at the offshore waters of southern Zhejiang is in good condition. However, the miniaturization of catch is intensifying. It is recommended to extend the capture fork length to 20 cm (the impact point age) to improve the quality of the catch, which would sustainably use the Chub mackerel resources.

Systematical analysis of underlying markers associated with Marfan syndrome via integrated bioinformatics and machine learning strategies.

Marfan syndrome (MFS) is a hereditary disease with high mortality. This study aimed to explore peripheral blood potential markers and underlying mechanisms in MFS via a series bioinformatics and machine learning analysis. First, we downloaded two MFS datasets from the GEO database. A total of 215 differentially expressed genes (DEGs) and 78 differentially expressed miRNAs (DEMs) were identified via "Limma" package. 60 DEGs, mainly enriched in abnormal transportation of structure and energy substances, were selected after protein-protein interaction (PPI) network construction, of which 20 were chosen for machine learning after three algorithms (betweenness, closeness, and degree) filtration using Cytoscape. Four overlapping DEGs (ACTN1, CFTR, GCKR, LAMA3) were finally selected as the candidate markers based on three machine-learning approaches (Lasso, random forest, and support vector machine-recursive feature elimination). Furthermore, we collected peripheral blood from MFS patients and healthy control to validate the findings and the results showed that compared with the control, the expression of the four DEGs was all statistically different in MFS patients validated by qRT-PCR. Besides, the area under the receiver operating characteristics curve was greater than 0.8 for each DEG. Single-sample gene-set enrichment analysis showed that the four DEGs were strongly associated with inflammation and myogenesis pathway. Finally, we constructed the mRNA-miRNA network based on the intersection of DEMs and predicted miRNAs targeting DEGs. In conclusion, our study partially provided four potential markers for MFS pathogenesis.Communicated by Ramaswamy H. Sarma.

Effects of waterlogging at different growth stages on the photosynthetic characteristics and grain yield of sorghum (Sorghum bicolor L.).

Various plants, including sorghum (Sorghum bicolor L.), are exposed to waterlogging; however, little is known about the effects of waterlogging at different growth stages on sorghum. A pot experiment was conducted using two sorghum hybrids, Jinuoliang 01 (JN01) and Jinza 31 (JZ31), to investigate the effects of waterlogging at different growth stages on the photosynthesis enzyme activity, chlorophyll content, malondialdehyde (MDA) content, photosynthetic parameters, dry matter accumulation, and grain yield. The experiment was conducted using waterlogging treatments implemented at the five-leaf stage (T1), flowering stage (T2), and filling stage (T3), using standard management (no waterlogging) as a control (CK). The adverse effects of waterlogging on sorghum growth varied with the waterlogging timing, with the maximum impact at T1, followed by T2 and T3. JZ31 was more sensitive to waterlogging compared to JN01. Waterlogged conditions inhibited the photosynthetic enzyme activity and reduced the chlorophyll content and photosynthesis, ultimately lowering the biomass yield and grain yield. The maximum yield loss was observed with the T1 waterlogging treatment; the grain yield of JN01 and JZ31 decreased by 52.01-54.58% and 69.52-71.97%, respectively, compared with CK. Furthermore, the decline in grain yield in T1 was associated with reducing grain number per panicle. These findings indicate that sorghum is sensitive to waterlogging at the five-leaf stage and JZ31 is more sensitive to waterlogging than JN01, which may provide a basis for selecting genotypes and management measures to cope with waterlogging in sorghum.

Association between Cardiovascular Response and Inflammatory Cytokines in Non-Small Cell Lung Cancer Patients.

Cardiovascular disease is an essential comorbidity in patients with non-small cell lung cancer (NSCLC) and represents an independent risk factor for increased mortality. Therefore, careful monitoring of cardiovascular disease is crucial in the healthcare of NSCLC patients. Inflammatory factors have previously been associated with myocardial damage in NSCLC patients, but it remains unclear whether serum inflammatory factors can be utilized to assess the cardiovascular health status in NSCLC patients. A total of 118 NSCLC patients were enrolled in this cross-sectional study, and their baseline data were collected through a hospital electronic medical record system. Enzyme-linked immunosorbent assay (ELISA) was used to measure the serum levels of leukemia inhibitory factor (LIF), interleukin (IL)-18, IL-1ß, transforming growth factor-ß1 (TGF-ß1), and connective tissue growth factor (CTGF). Statistical analysis was performed using the SPSS software. Multivariate and ordinal logistic regression models were constructed. The data revealed an increased serum level of LIF in the group using tyrosine kinase inhibitor (TKI)-targeted drugs compared to non-users (p < 0.001). Furthermore, serum TGF-ß1 (area under the curve, AUC: 0.616) and cardiac troponin T (cTnT) (AUC: 0.720) levels were clinically evaluated and found to be correlated with pre-clinical cardiovascular injury in NSCLC patients. Notably, the serum levels of cTnT and TGF-ß1 were found to indicate the extent of pre-clinical cardiovascular injury in NSCLC patients. In conclusion, the results suggest that serum LIF, as well as TGFß1 together with cTnT, are potential serum biomarkers for the assessment of cardiovascular status in NSCLC patients. These findings offer novel insights into the assessment of cardiovascular health and underscore the importance of monitoring cardiovascular health in the management of NSCLC patients.

Identification and validation of diagnostic biomarkers of coronary artery disease progression in type 1 diabetes via integrated computational and bioinformatics strategies.

OBJECTIVE: Our study aimed to identify early peripheral blood diagnostic biomarkers and elucidate the immune mechanisms of coronary artery disease (CAD) progression in patients with type 1 diabetes mellitus (T1DM). METHODS: Three transcriptome datasets were retrieved from the Gene Expression Omnibus (GEO) database. Gene modules associated with T1DM were selected with weighted gene co-expression network analysis. Differentially expressed genes (DEGs) between CAD and acute myocardial infarction (AMI) peripheral blood tissues were identified using limma. Candidate biomarkers were selected with functional enrichment analysis, node gene selection from a constructed protein-protein interaction (PPI) network, and 3 machine learning algorithms. Candidate expression was compared, and the receiver operating characteristic curve (ROC) and nomogram were constructed. Immune cell infiltration was assessed with the CIBERSORT algorithm. RESULTS: A total of 1283 genes comprising 2 modules were detected as the most associated with T1DM. In addition, 451 DEGs related to CAD progression were identified. Among them, 182 were common to both diseases and mainly enriched in immune and inflammatory response regulation. The PPI network yielded 30 top node genes, and 6 were selected using the 3 machine learning algorithms. Upon validation, 4 genes (TLR2, CLEC4D, IL1R2, and NLRC4) were recognized as diagnostic biomarkers with the area under the curve (AUC) > 0.7. All 4 genes were positively correlated with neutrophils in patients with AMI. CONCLUSION: We identified 4 peripheral blood biomarkers and provided a nomogram for early diagnosing CAD progression to AMI in patients with T1DM. The biomarkers were positively associated with neutrophils, indicating potential therapeutic targets.

Monomeric C-reactive protein evokes TCR Signaling-dependent bystander activation of CD4+ T cells.

Bystander activation of T cells is defined as induction of effector responses by innate cytokines in the absence of cognate antigens and independent of T cell receptor (TCR) signaling. Here we show that C-reactive protein (CRP), a soluble pattern-recognition receptor assembled noncovalently by five identical subunits, can instead trigger bystander activation of CD4 + T cells by evoking allosteric activation and spontaneous signaling of TCR in the absence of cognate antigens. The actions of CRP depend on pattern ligand-binding induced conformational changes that result in the generation of monomeric CRP (mCRP). mCRP binds cholesterol in plasma membranes of CD4 + T cells, thereby shifting the conformational equilibrium of TCR to the cholesterol-unbound, primed state. The spontaneous signaling of primed TCR leads to productive effector responses manifested by upregulation of surface activation markers and release of IFN-γ. Our results thus identify a novel mode of bystander T cell activation triggered by allosteric TCR signaling, and reveal an interesting paradigm wherein innate immune recognition of CRP transforms it to a direct activator that evokes immediate adaptive immune responses.

Association of Systemic Immune Inflammation Index with All-Cause, Cardiovascular Disease, and Cancer-Related Mortality in Patients with Cardiovascular Disease: A Cross-Sectional Study.

Objective: Our research was designed to investigate the relationship between systemic immune inflammation (SII) index and all-cause, cardiovascular disease (CVD), and cancer-related mortality in patients with CVD. Methods: We used the National Health and Nutrition Examination Survey data from 1999 to 2018 to conduct this study. The association between SII index and all-cause, CVD, and cancer-related mortality in patients with CVD was examined using restricted cubic splines (RCS), Cox proportional hazard models, and subgroup analysis, respectively. CVD was defined as a composite of five outcomes of CVD, including coronary heart disease (CHD), congestive heart failure (CHF), angina pectoris, myocardial infarction, and stroke. Additionally, the link between SII index and all-cause, CVD, and cancer-related mortality in patients with a composite of five outcomes of CVD was also explored. Results: In total, 5329 participants were included. The RCS also showed a U-curve correlation between SII index and the all-cause, CVD, and cancer-related mortality in patients with CVD. As compared with the individuals with lowest quartile of SII index, hazard ratios with 95% confidence intervals for all-cause, CVD, and cancer-related mortality across the quartiles were (1.202 (0.981, 1.474), 1.184 (0.967, 1.450), and 1.365 (1.115, 1.672)), (1.116 (0.815, 1.527), 1.017 (0.740, 1.398), and 1.220 (0.891, 1.670)), and (1.202 (0.981, 1.474), 1.184 (0.967, 1.450), and 1.365 (1.115, 1.672)), respectively, in the full-adjusted model. The SII index also had a U-shaped relationship with all-cause, CVD, and cancer-related mortality in patients with CHD, angina, and myocardial infarction. Additionally, the U-shaped relationship between SII index and all-cause, and cancer-related mortality also exists in CHF, and stroke. However, there was a positive linear correlation between SII index and CVD mortality in patients with CHF, and stroke. Conclusion: In the United States general population, the correlation between SII index and all-cause, CVD, and cancer-related mortality showed a U-shaped curve in patients with CVD.

Degradation performance and potential protection mechanism of the anammox consortia in response to capecitabine.

The potential risks of anti-cancer drugs such as capecitabine have attracted considerable attention due to their continuous release. Understanding the response of removal performance and protective mechanism to the presence of emerging contaminants is crucial for the application of anammox techniques in wastewater treatment. Capecitabine affected the nitrogen removal performance slightly in the activity experiment. Due to bio-adsorption and biodegradation, up to 64-70% of the capecitabine can be removed effectively. However, 10 mg/L of capecitabine significantly decreased the removal efficiency of capecitabine and total nitrogen at repeated load of capecitabine. Metabolomic analysis revealed the metabolites 5'-deoxy-5-fluorocytidine and alpha-fluoro-beta-alanine, while metagenomic analysis confirmed the biodegradation pathway and underlying gene distribution. The potentially protective mechanisms of the system against capecitabine were the increased heterotrophic bacteria and secretion of sialic acid. Blast analysis confirmed the presence of potential genes involved in the complete biosynthesis pathway of sialic acid in anammox bacteria, some of which are also found in Nitrosomonas, Thauera, and Candidatus Promineofilum.

The Diagnostic and Prognostic Value of Cardiac Magnetic Resonance Strain Analysis in Heart Failure with Preserved Ejection Fraction.

Background: Strain analysis of cardiac magnetic resonance (CMR) is critical for the diagnosis and prognosis of heart failure (HF) with preserved ejection fraction (HFpEF). Our study aimed to identify the diagnostic and prognostic value of strain analysis revealed by CMR in HFpEF. Methods: Participants in HFpEF and control were recruited according to the guideline. Baseline information, clinical parameters, blood samples were collected, and echocardiography and CMR examination were performed. Various parameters, including global longitudinal strain, global circumferential strain (GCS) and global radial strain in left ventricle (LV), right ventricle (RV), and left atrium, were measured from CMR. Receiver operator curve (ROC) was established to evaluate the diagnostic and prognostic value of strains in HFpEF. Results: Seven strains, with the exception of RVGCS, were employed to generate ROC curves after t-test. All strains had significant diagnostic value for HFpEF. The area under curve (AUC) of LV strains was greater than 0.7 and the AUC of the combined analysis of LV strains was 0.858 (95% confidence interval (CI): 0.798-0.919, sensitivity: 0.713, specificity: 0.875, P < 0.001), indicating that they had a higher diagnostic value than individual LV strains. However, individual strains had no predictive value in identifying end-point events in HFpEF, the AUC of coanalysis of LV strains was 0.722 (95% CI: 0.573-0.872, sensitivity: 0.500, specificity: 0.959, P = 0.004), indicating its prognostic relevance. Conclusion: Individual strain analysis in CMR may be useful for diagnosing HFpEF, the combination of LV strain analysis had the highest diagnostic value. Moreover, the prognostic value of individual strain analysis in predicting HFpEF outcome was not satisfactory while the combined usage of LV strain analysis was prognostically valuable in HFpEF outcome prediction.

Effects of Exogenous Auxin on Mesocotyl Elongation of Sorghum.

The length of sorghum mesocotyl plays a vital role in seed emergence from the soil, which is the foundation of healthy growth. In this study, we aimed to understand how exogenous auxin (IAA) promoted mesocotyl elongation of sorghum and its physiology mechanism. The results presented that exogenous IAA significantly promoted mesocotyl elongation in MS24B (short mesocotyl inbred line) by increasing the cell length, while with extra exogenous NPA (IAA inhibitor) application, the mesocotyl length presented a significant short phenotype. In Z210 (long mesocotyl inbred line), exogenous IAA had a slight effect on mesocotyl length elongation, while the NPA treatment decreased the mesocotyl length considerably. In MS24B, IAA treatment increased the activity of amylase to degrade starch to soluble sugar, and the activity of hexokinase was improved to consume the increased soluble sugar to offer more energy. The energy will help to increase the activity of PM H+-ATPase and the expression of expansin-related genes, which ultimately will promote the acidification of the plasma membrane in MS24B for cell elongation. Overall, the exogenous IAA functioned on the activation of energy metabolism, which in turn, inducted the acidification of the plasma membrane for mesocotyl elongation.

Association of Systemic Immune Inflammation Index with Estimated Pulse Wave Velocity, Atherogenic Index of Plasma, Triglyceride-Glucose Index, and Cardiovascular Disease: A Large Cross-Sectional Study.

In the U.S. general population, there is a lack of understanding regarding the association between the systemic immune inflammation (SII) index and estimated pulse wave velocity (ePWV), atherogenic index of plasma (AIP), and triglyceride-glucose (TyG) index and cardiovascular disease (CVD). As a result, the objective of our research was to investigate the association between the SII index and ePWV, AIP, and TyG index and incident CVD. We used the National Health and Nutrition Examination Survey (NHANES) data from 1999 to 2018 to conduct this study. The correlation between the SII index and ePWV, AIP, and TyG index was examined using generalized additive models with smooth functions. In addition, the association between SII index and triglyceride (TC), high-density lipoprotein cholesterol (HDL-C), and fast glucose (FBG) also were explored. Finally, we further performed multivariable logistic regression analysis, restricted cubic spline (RCS) plots, and subgroup analysis to study the connection between the SII index and CVD. Our analysis included 17389 subjects from the NHANES database. A substantial positive association existed between SII, WV, and the TyG index. In addition, with the increase of the SII index, AIP showed a trend of decreasing first, then rising, and then decreasing. The SII index was inversely and linearly associated with triglyceride (TG), while positively and linearly associated with fast glucose (FBG). However, high-density lipoprotein cholesterol (HDL-C) had a tendency of first declining, then climbing, and finally falling with the rise in the SII index. After adjusting for potential confounders, compared with the lowest quartiles, the odds ratios with 95% confidence intervals for CVD across the quartiles were 0.914 (0.777, 1.074), 0.935 (0.779, 1.096), and 1.112 (0.956, 1.293) for SII index. The RCS plot showed an inverse U-shaped curve relationship between the SII index and CVD. Overall, this study found a strong correlation between a higher SII index and ePWV and the TyG index. Additionally, these cross-sectional data also revealed a U-shaped connection between the SII index and CVD.

Immune-associated biomarkers identification for diagnosing carotid plaque progression with uremia through systematical bioinformatics and machine learning analysis.

BACKGROUND: Uremia is one of the most challenging problems in medicine and an increasing public health issue worldwide. Patients with uremia suffer from accelerated atherosclerosis, and atherosclerosis progression may trigger plaque instability and clinical events. As a result, cardiovascular and cerebrovascular complications are more likely to occur. This study aimed to identify diagnostic biomarkers in uremic patients with unstable carotid plaques (USCPs). METHODS: Four microarray datasets (GSE37171, GSE41571, GSE163154, and GSE28829) were downloaded from the NCBI Gene Expression Omnibus database. The Limma package was used to identify differentially expressed genes (DEGs) in uremia and USCP. Weighted gene co-expression network analysis (WGCNA) was used to determine the respective significant module genes associated with uremia and USCP. Moreover, a protein-protein interaction (PPI) network and three machine learning algorithms were applied to detect potential diagnostic genes. Subsequently, a nomogram and a receiver operating characteristic curve (ROC) were plotted to diagnose USCP with uremia. Finally, immune cell infiltrations were further analyzed. RESULTS: Using the Limma package and WGCNA, the intersection of 2795 uremia-related DEGs and 1127 USCP-related DEGs yielded 99 uremia-related DEGs in USCP. 20 genes were selected as candidate hub genes via PPI network construction. Based on the intersection of genes from the three machine learning algorithms, three hub genes (FGR, LCP1, and C5AR1) were identified and used to establish a nomogram that displayed a high diagnostic performance (AUC: 0.989, 95% CI 0.971-1.000). Dysregulated immune cell infiltrations were observed in USCP, showing positive correlations with the three hub genes. CONCLUSION: The current study systematically identified three candidate hub genes (FGR, LCP1, and C5AR1) and established a nomogram to assist in diagnosing USCP with uremia using various bioinformatic analyses and machine learning algorithms. Herein, the findings provide a foothold for future studies on potential diagnostic candidate genes for USCP in uremic patients. Additionally, immune cell infiltration analysis revealed that the dysregulated immune cell proportions were identified, and macrophages could have a critical role in USCP pathogenesis.

The sodium new houttuyfonate suppresses NSCLC via activating pyroptosis through TCONS-14036/miR-1228-5p/PRKCDBP pathway.

Several studies have suggested the potential value of Houttuynia cordata as a therapeutic agent in lung cancer, but direct evidence is still lacking. The study aimed to determine the regulatory impact of a major H. cordata constituent derivative (sodium new houttuyfonate [SNH]) on lncRNA networks in non-small cell lung cancer (NSCLC) to identify new potential therapeutic targets. After exposing NSCLC cells to SNH, we analysed the following: cell death (via flow cytometry, TUNEL and ASC speck formation assays), immune factors (via ELISA), gene transcription (via RT-qPCR), subcellular localisation (via FISH), gene-gene and gene-protein interactions (via dual-luciferase reporter and RNA immunoprecipitation assays, respectively) and protein expression and distribution (via western blotting and immunocytochemistry or immunohistochemistry). In addition, statistical analysis (via one-way ANOVA or unpaired t-tests) was performed. Exposure to SNH promoted NSCLC cell pyroptosis, concomitant with significant up-regulation of TCONS-14036, a novel lncRNA. Mechanistic research demonstrated that TCONS-14036 functions as a competing endogenous (ce)RNA by sequestering microRNA (miR)-1228-5p, thereby up-regulating PRKCDBP-encoding transcript levels. Indeed, PRKCDBP promoted pyroptosis by activating the NLRP3 inflammasome, resulting in CASP1, IL-1ß and GSDMD cleavage. Our findings elucidate the potential molecular mechanisms underlying the ability of SNH to suppress NSCLC growth through activation of pyroptosis via the TCONS-14036/miR-1228-5p/PRKCDBP pathway. Thus, we identify a new potential therapeutic targets for NSCLC.

Positive feedback loop of miR-320 and CD36 regulates the hyperglycemic memory-induced diabetic diastolic cardiac dysfunction.

Intensive glycemic control is insufficient for reducing the risk of heart failure among patients with diabetes mellitus (DM). While the "hyperglycemic memory" phenomenon is well documented, little is known about its underlying mechanisms. In this study, a type 1 DM model was established in C57BL/6 mice using streptozotocin (STZ). Leptin receptor-deficient (db/db) mice were used as a model of type 2 DM. A type 9 adeno-associated virus was used to overexpress or knock down miR-320 in vivo. Diastolic dysfunction was observed in the type 1 DM mice with elevated miR-320 expression. However, glycemic control using insulin failed to reverse diastolic dysfunction. miR-320 knockdown protected against STZ-induced diastolic dysfunction. Similar results were observed in the type 2 DM mice. In vitro, we found that miR-320 promoted CD36 expression, which in turn induced further miR-320 expression. CD36 was rapidly induced by hyperglycemia at protein level compared with the much slower induction of miR-320, suggesting a positive feedback loop of CD36/miR-320 with CD36 protein induction as the initial triggering event. In conclusion, in DM-induced cardiac injury, miR-320 and CD36 mutually enhance each other's expression, leading to a positive feedback loop and a sustained hyperlipidemic state in the heart.