Association of Oral Microbiome Diversity and All-Cause Mortality in the General US Population and in Individuals With Chronic Diseases: A Prospective Cohort Study.

AIM: To investigate whether oral microbiome diversity is associated with all-cause mortality in the general US population and in individuals with chronic diseases. MATERIALS AND METHODS: We included 8224 individuals with oral microbiome diversity data from the National Health and Nutrition Examination Survey (2009-2012), representing 164,000,205 US adults, using a survey-weighted analysis method. Cox regression analyses were performed to identify the association between oral microbiome diversity and all-cause mortality. RESULTS: During a survey-weighted mean follow-up period of 8.86 years, 429 all-cause deaths (survey-weighted number: 7,124,920) occurred in 8224 participants. Cox regression analysis revealed that higher oral microbiome diversity was significantly associated with a lower all-cause mortality risk. Significant differences in all-cause mortality risk were observed among the different clusters based on oral microbiome ß-diversity (log-rank p < 0.001). Subgroup analyses revealed that the oral microbiome diversity was independently associated with all-cause mortality in individuals with diabetes mellitus and hypertension. A multivariate logistic regression model showed that current smoking and antibiotic use were significantly associated with lower oral microbiome α diversity. CONCLUSIONS: Higher oral microbiome diversity was significantly associated with a lower all-cause mortality risk in the general US population and in individuals with diabetes mellitus and hypertension.

Os(II) phosphors with near-infrared emission induced by ligand-to-ligand charge transfer transition.

Heating of Os3(CO)12 with 6 equiv of 2-(3-(trifluoromethyl)-1H-1,2,4-triazol-5-yl) pyridine (fptzH) in refluxing diethylene glycol monomethyl ether, followed by sequential treatment with stoichiometric Me3NO and addition of PPhMe2, afforded two isomeric mixtures of red-emitting [Os(fptz)2(PPhMe2)2] (1T and 1C), for which the notations T and C stand for the trans and cis-oriented fptz chelates, respectively. Alternatively, preparation of Os(II) complex using a 1:1 mixture of 5,5'-di(trifluoromethyl)-3,3'-di-1,2,4-triazole (dttzH2) and 2,2'-bipyridine (bpy), instead of fptzH, gave isolation of a mononuclear Os(II) complex [Os(bpy)(dttz)(CO)2] (2) in moderate yield. Replacement of CO with PPhMe2 on 2 afforded near-infrared (NIR)-emitting Os(II) complex [Os(bpy)(dttz)(PPhMe2)2] (3). The single-crystal X-ray structural analyses were executed on 1C, 2, and 3 to reveal the structural influence imposed by the various chelates. The photophysical and electrochemical properties were measured and discussed using the results of density functional theory (DFT) and time-dependent DFT calculations. Complex 3 is selected as the dopant to probe its electroluminescent properties by fabrication of the NIR emitting organic light-emitting diodes.

An integrated machine learning framework for developing and validating a diagnostic model of major depressive disorder based on interstitial cystitis-related genes.

BACKGROUND: Major depressive disorder (MDD) and interstitial cystitis (IC) are two highly debilitating conditions that often coexist with reciprocal effect, significantly exacerbating patients' suffering. However, the molecular underpinnings linking these disorders remain poorly understood. METHODS: Transcriptomic data from GEO datasets including those of MDD and IC patients was systematically analyzed to develop and validate our model. Following removal of batch effect, differentially expressed genes (DEGs) between respective disease and control groups were identified. Shared DEGs of the conditions then underwent functional enrichment analyses. Additionally, immune infiltration analysis was quantified through ssGSEA. A diagnostic model for MDD was constructed by exploring 113 combinations of 12 machine learning algorithms with 10-fold cross-validation on the training sets following by external validation on test sets. Finally, the "Enrichr" platform was utilized to identify potential drugs for MDD. RESULTS: Totally, 21 key genes closely associated with both MDD and IC were identified, predominantly involved in immune processes based on enrichment analyses. Immune infiltration analysis revealed distinct profiles of immune cell infiltration in MDD and IC compared to healthy controls. From these genes, a robust 11-gene (ABCD2, ATP8B4, TNNT1, AKR1C3, SLC26A8, S100A12, PTX3, FAM3B, ITGA2B, OLFM4, BCL7A) diagnostic signature was constructed, which exhibited superior performance over existing MDD diagnostic models both in training and testing cohorts. Additionally, epigallocatechin gallate and 10 other drugs emerged as potential targets for MDD. CONCLUSION: Our work developed a diagnostic model for MDD employing a combination of bioinformatic techniques and machine learning methods, focusing on shared genes between MDD and IC.

Behind the Non-Uniform Breakup of Bubble Slug in Y-Shaped Microchannel: Dynamics and Mechanisms.

Bubble flow in confined geometries is a problem of fundamental and technological significance. Among all the forms, bubble breakup in bifurcated microchannels is one of the most commonly encountered scenarios, where an in-depth understanding is necessary for better leveraging the process. This study numerically investigates the non-uniform breakup of a bubble slug in Y-shaped microchannels under different flow ratios, Reynolds numbers, and initial bubble volumes. Overall, the bubble can either breakup or non-breakup when passing through the bifurcation and shows different forms depending on flow regimes. The flow ratio-Reynolds number phase diagrams indicate a power-law transition line of breakup and non-breakup. The bubble takes longer to break up with rising flow ratios yet breaks earlier with higher Reynolds numbers and volumes. Non-breakup takes less time than the breakup patterns. Flow ratio is the origin of non-uniform breakup. Both the Reynolds number and initial volume influence the bubble states when reaching the bifurcation and thus affect subsequent processes. Bubble neck dynamics are analyzed to describe the breakup further. The volume distribution after breaking up is found to have a quadratic relation with the flow ratio. Our study is hoped to provide insights for practical applications related to non-uniform bubble breakups.

PEI functionalized cell membrane for tumor targeted and glutathione responsive gene delivery.

Polyethylenimine (PEI) is a broadly exploited cationic polymer due to its remarkable gene-loading capacity. However, the high cytotoxicity caused by its high surface charge density has been reported in many cell lines, limiting its application significantly. In this study, two different molecular weights of PEI (PEI10k and PEI25k) were crosslinked with red blood cell membranes (RBCm) via disulfide bonds to form PEI derivatives (RMPs) with lower charge density. Furthermore, the targeting molecule folic acid (FA) molecules were further grafted onto the polymers to obtain FA-modified PEI-RBCm copolymers (FA-RMP25k) with tumor cell targeting and glutathione response. In vitro experiments showed that the FA-RMP25k/DNA complex had satisfactory uptake efficiency in both HeLa and 293T cells, and did not cause significant cytotoxicity. Furthermore, the uptake and transfection efficiency of the FA-RMP25k/DNA complex was significantly higher than that of the PEI25k/DNA complex, indicating that FA grafting can increase transfection efficiency by 15 %. These results suggest that FA-RMP25k may be a promising non-viral gene vector with potential applications in gene therapy.

Preparation of Sn-Doped Ga2O3 Thin Films and MSM Ultraviolet Detectors Using Magnetron Co-Sputtering.

Sn-doped Ga2O3 thin films and metal-semiconductor-metal (MSM) ultraviolet detectors were prepared using the co-sputtering method to enhance their photoelectric performance. The results revealed that Sn doping can effectively change the optical and electrical properties of thin films, greatly improving the photoelectric responsiveness of the devices. Through microstructure testing results, all of the thin film structures were determined to be monoclinic beta phase gallium oxide. At a DC power of 30 W, the thickness of the Sn-doped thin film was 430 nm, the surface roughness of the thin film was 4.94 nm, and the carrier concentration, resistivity, and mobility reached 9.72 × 1018 cm-3, 1.60 × 10-4 Ω·cm, and 45.05 cm3/Vs, respectively. The optical results show that Sn doping clearly decreases the transmission of thin films and that the bandgap can decrease to 3.91 eV. Under 30 W DC power, the photo dark current ratio of the detector can reach 101, time responses of tr = 31 s and tf = 22.83 s were obtained, and the spectral responsivity reached 19.25 A/W.

A new perspective: deciphering the aberrance and clinical implication of disulfidptosis signatures in clear cell renal cell carcinoma.

Recent research has discovered disulfidptosis as a form of programmed cell death characterized by disulfide stress. However, its significance in clear cell renal cell carcinoma (ccRCC) remains unclear. To investigate this, data from The Cancer Genome Atlas were collected and used to identify ccRCC subgroups. Unsupervised clustering was employed to determine ccRCC heterogeneity. The mutation landscape and immune microenvironment of the subgroups were analyzed. The Disulfidptosis-Related Score was calculated using the LASSO-penalized Cox regression algorithm. The E-MATB-1980 cohort was used to validate the signature. The role of SLC7A11 in ccRCC metastasis was explored using western blotting and Transwell assays. Disulfidptosis-related genes are commonly downregulated in cancers and are linked to hypermethylation and copy number variation. The study revealed that ccRCC is divided into two sub-clusters: the disulfidptosis-desert sub-cluster, which is associated with a poor prognosis, a higher mutation frequency, and an immunosuppressive microenvironment. A 14-gene prognostic model was developed using differentially expressed genes and was validated in the E-MATB-1980 cohort. The low-risk group demonstrated longer overall and disease-free survival and responded better to targeted immunotherapy. Results from in vitro experiments identified SLC7A11 as a key participant in ccRCC metastasis.

An Integrated Machine Learning Framework Identifies Prognostic Gene Pair Biomarkers Associated with Programmed Cell Death Modalities in Clear Cell Renal Cell Carcinoma.

BACKGROUND: Clear cell renal cell carcinoma (ccRCC) is a common and lethal urological malignancy for which there are no effective personalized therapeutic strategies. Programmed cell death (PCD) patterns have emerged as critical determinants of clinical prognosis and immunotherapy responses. However, the actual clinical relevance of PCD processes in ccRCC is still poorly understood. METHODS: We screened for PCD-related gene pairs through single-sample gene set enrichment analysis (ssGSEA), consensus cluster analysis, and univariate Cox regression analysis. A novel machine learning framework incorporating 12 algorithms and 113 unique combinations were used to develop the cell death-related gene pair score (CDRGPS). Additionally, a radiomic score (Rad_Score) derived from computed tomography (CT) image features was used to classify the CDRGPS status as high or low. Finally, we conclusively verified the function of PRSS23 in ccRCC. RESULTS: The CDRGPS was developed through an integrated machine learning approach that leveraged 113 algorithm combinations. CDRGPS represents an independent prognostic biomarker for overall survival and demonstrated consistent performance between training and external validation cohorts. Moreover, CDRGPS showed better prognostic accuracy compared to seven previously published cell death-related signatures. In addition, patients classified as high-risk by CDRGPS exhibited increased responsiveness to tyrosine kinase inhibitors (TKIs), mammalian Target of Rapamycin (mTOR) inhibitors, and immunotherapy. The Rad_Score demonstrated excellent discrimination for predicting high versus low CDRGPS status, with an area under the curve (AUC) value of 0.813 in the Cancer Imaging Archive (TCIA) database. PRSS23 was identified as a significant factor in the metastasis and immune response of ccRCC, thereby validating experimental in vitro results. CONCLUSIONS: CDRGPS is a robust and non-invasive tool that has the potential to improve clinical outcomes and enable personalized medicine in ccRCC patients.

Utilization of chitosan nanocomposites loaded with quantum dots enables efficient and traceable DNA delivery.

Chitosan is widely employed in gene carriers due to its excellent gene loading capacity, ease of modification, and exceptional biodegradability. However, low gene delivery efficiency, high cytotoxicity, and lack of tracer biomimetic properties limit its clinical use. To address these issues, a novel biomimetic tracking gene delivery carrier, RBCm-C50kQT, was constructed by using the design scheme of cell membrane coated carbon quantum dots/chitosan. This carrier improves stability and tracking performance while embedding the cell membrane enhances biosafety. RBCm-C50kQT effectively carries and protects DNA, improving uptake and transfection efficiency with reduced cytotoxicity. It maintains strong fluorescence tracking and shows high uptake efficiencies of 83.62 % and 77.45 % in 293 T and HeLa cells, respectively, with maximum transfection efficiencies of 68.80 % and 45.47 %. This advancement supports gene therapy improvements and paves the way for future clinical applications.

Leveraging cell death patterns to predict metastasis in prostate adenocarcinoma and targeting PTGDS for tumor suppression.

Metastasis is the major cause of treatment failure in patients with prostate adenocarcinoma (PRAD). Diverse programmed cell death (PCD) patterns play an important role in tumor metastasis and hold promise as predictive indicators for PRAD metastasis. Using the LASSO Cox regression method, we developed PCD score (PCDS) based on differentially expressed genes (DEGs) associated with PCD. Clinical correlation, external validation, functional enrichment analysis, mutation landscape analysis, tumor immune environment analysis, and immunotherapy analysis were conducted. The role of Prostaglandin D2 Synthase (PTGDS) in PRAD was examined through in vitro experiments, single-cell, and Mendelian randomization (MR) analysis. PCDS is elevated in patients with higher Gleason scores, higher T stage, biochemical recurrence (BCR), and higher prostate-specific antigen (PSA) levels. Individuals with higher PCDS are prone to metastasis, metastasis after BCR, BCR, and castration resistance. Moreover, PRAD patients with low PCDS responded positively to immunotherapy. Random forest analysis and Mendelian randomization analysis identified PTGDS as the top gene associated with PRAD metastasis and in vitro experiments revealed that PTGDS was considerably downregulated in PRAD cells against normal prostate cells. Furthermore, the overexpression of PTGDS was found to suppress the migration, invasion, proliferationof DU145 and LNCaP cells. To sum up, PCDS may be a useful biomarker for forecasting the possibility of metastasis, recurrence, castration resistance, and the efficacy of immunotherapy in PRAD patients. Additionally, PTGDS was identified as a viable therapeutic target for the management of PRAD.

Prognostic impact of malnutrition in patients with coronary artery disease: a systematic review and meta-analysis.

CONTEXT: Conflicting predictions of malnutrition for the long-term prognosis of coronary artery disease (CAD) exist. OBJECTIVE: This study aimed to investigate the relationship between malnutrition and long-term prognosis of patients with CAD. DATA SOURCES: Four databases were searched for articles from February 11, 1936, to September 10, 2022. DATA EXTRACTION: Cohort studies adjusting for multiple cardiovascular risk factors with data on CAD and malnutrition were included. Malnutrition was measured and defined by different nutritional evaluation tools. The hazard ratios (HRs) and confidence intervals (CIs) for all-cause mortality and major adverse cardiovascular events (MACEs) were synthesized. Subgroup analyses were performed based on study design, assessment tools, ethnicity/race, follow-up, sample size, and types of CAD. Meta-regression was used to compare whether the effect sizes of the 2 subgroups were statistically significant. DATA ANALYSIS: A total of 30 cohort studies were included, totaling 81 361 participants with CAD. Nutritional evaluation tools, including the Geriatric Nutritional Risk Index (GNRI), Controlling Nutritional Status (CONUT), Nutritional Risk Screening 2002, Mini-Nutritional Assessment, and Prognostic Nutritional Index, were used. Malnutrition increased all-cause mortality (HR = 1.72; 95% CI: 1.53, 1.93) and MACEs (HR = 1.47; 95% CI: 1.35, 1.60) in patients with CAD. Subgroup analysis revealed the results were consistent across study design, ethnicity/race, follow-up, sample size, and types of CAD. Subgroup analyses and meta-regression revealed that malnutrition was associated with a higher risk of all-cause mortality (HR = 2.26; 95% CI: 1.91, 2.68) and MACEs (HR = 2.28; 95% CI: 1.69, 3.08) in patients with stable CAD than those with other types of CAD. Meta-regression revealed that the GNRI (HR = 2.20; 95% CI: 1.65, 2.93) was more effective than CONUT (HR = 1.47; 95% CI: 1.21, 1.78) in predicting all-cause mortality. CONCLUSION: Malnutrition independently increased all-cause mortality by 72% and MACEs by 47% in patients with CAD, especially with stable CAD. The GNRI is a more effective nutritional evaluation tool than CONUT in predicting all-cause mortality.

Cumulative remnant cholesterol predicts cardiovascular outcomes in elderly patients with atherosclerotic cardiovascular disease.

AIMS: Remnant cholesterol (RC) reportedly mediates residual cardiovascular risk in atherosclerotic cardiovascular diseases (ASCVD). However, few studies have characterized long-term cumulative RC exposure among elderly people. The study aimed to evaluate the association between cumulative exposure to RC and incident major adverse cardiovascular events (MACE) by analysing a cohort of elderly patients with ASCVD. METHODS AND RESULTS: This retrospective multicentre cohort study enrolled ASCVD participants aged ≥75 years with baseline visits occurring from 2006 to 2012 followed by four in-person visits. Cumulative RC was estimated as the area under the curve using measurements from the first to fourth visits by using 9-year data. The time-weighted average (TWA) RC was expressed as cumulative exposure to RC averaged by years. All outcomes were follow-up from the fourth visit to the year 2021. Outcomes included a composite of MACE (stroke, unstable angina pectoris, myocardial infarction, and cardiac death). We included 4,680 participants (73.1% male, mean age 79.3 ± 2.5 years). The median follow-up duration was 6.1 years (interquartile range: 3.4-6.6 years). In the multivariable model adjusted for traditional cardiovascular risk factors, low-density lipoprotein cholesterol level, and most recent RC level, the hazard ratios for MACE that compared the high and low tertiles of the RC variables were 1.30 [95% confidence interval (CI), 1.16-1.44] for cumulative RC and 1.36 (95% CI, 1.23-1.52) for TWA RC. Consistent significant associations were observed among most propensity score analyses. CONCLUSIONS: Long-term cumulative RC was independently associated with incident MACE in elderly participants with ASCVD, suggesting that achieving and maintaining optimal RC levels later in life may still improve cardiovascular outcomes.

This retrospective multicentre cohort study, enrolling 4680 participants aged ≥75 years with pre-existing atherosclerotic cardiovascular diseases (ASCVD), found that greater cumulative exposure to remnant cholesterol (RC) across a 9-year span was independently associated with an increased incidence of cardiovascular events, suggesting that cumulative RC may be a powerful predictor of cardiovascular outcomes in patients with ASCVD.

LDHA-mediated metabolic reprogramming promoted cardiomyocyte proliferation by alleviating ROS and inducing M2 macrophage polarization.

AIMS: Metabolic switching during heart development contributes to postnatal cardiomyocyte (CM) cell cycle exit and loss of regenerative capacity in the mammalian heart. Metabolic control has potential for developing effective CM proliferation strategies. We sought to determine whether lactate dehydrogenase A (LDHA) regulated CM proliferation by inducing metabolic reprogramming. METHODS AND RESULTS: LDHA expression was high in P1 hearts and significantly decreased during postnatal heart development. CM-specific LDHA knockout mice were generated using CRISPR/Cas9 technology. CM-specific LDHA knockout inhibited CM proliferation, leading to worse cardiac function and a lower survival rate in the neonatal apical resection model. In contrast, CM-specific overexpression of LDHA promoted CM proliferation and cardiac repair post-MI. The α-MHC-H2B-mCh/CAG-eGFP-anillin system was used to confirm the proliferative effect triggered by LDHA on P7 CMs and adult hearts. Metabolomics, proteomics and Co-IP experiments indicated that LDHA-mediated succinyl coenzyme A reduction inhibited succinylation-dependent ubiquitination of thioredoxin reductase 1 (Txnrd1), which alleviated ROS and thereby promoted CM proliferation. In addition, flow cytometry and western blotting showed that LDHA-driven lactate production created a beneficial cardiac regenerative microenvironment by inducing M2 macrophage polarization. CONCLUSIONS: LDHA-mediated metabolic reprogramming promoted CM proliferation by alleviating ROS and inducing M2 macrophage polarization, indicating that LDHA might be an effective target for promoting cardiac repair post-MI.

Inhibition of soluble epoxide hydrolase regulates monocyte/macrophage polarization and improves neurological outcome in a rat model of ischemic stroke.

It is generally understood that continuing neuroinflammation after ischemic stroke can exacerbate the brain damage. During the inflammatory hematogenous recruitment process, the monocytes and macrophages are activated into proinflammatory M1 and anti-inflammatory M2 cell types. Inhibition of soluble epoxide hydrolase (sEH) activity has been reported to regulate monocytes/macrophages, and attenuates neuroinflammation. This study aimed to evaluate whether a selective sEH inhibitor, 12-(3-adamantan-1-yl-ureido)-dodecanoic acid (AUDA), can regulate monocyte/macrophage polarization and improve motor function in the rats with ischemic stroke induced by middle cerebral artery occlusion. We measured the infarct volume with 2,3,5-triphenyltetrazolium chloride staining and used the rotarod test to assess motor performance in rats. The monocyte/macrophage activation and mRNA expression of proinflammatory mediators were measured by flow cytometry and reverse-transcription quantitative PCR, respectively. Our results showed better neurological function and less infarct volume in the rats treated with AUDA. Compared with the vehicle group, the AUDA-treated group showed a reduction in M1 monocyte/macrophage activation and proinflammatory mRNA expressions in the infarct cortex of rats. Our data suggest that the sEH inhibition may regulate monocyte/macrophage polarization and improve neurological outcome after ischemic stroke.

Development of a Modified Surgical Technique for Simulating Ischemic Cerebral Cortex Injury in Rats.

BACKGROUND/AIM: Middle cerebral artery occlusion (MCAO) in rodents is an essential animal model for research focusing on ischemic stroke. To date, several kinds of surgical methods for MCAO have been developed and the craniotomy method has the advantage of direct visualization of the middle cerebral artery (MCA). MCAO at a more proximal site produces better surgical results, but it is a more invasive technique. The aim of this study was to evolve the surgical technique for simulating ischemic cerebral cortex injury in rats. MATERIALS AND METHODS: To approach proximal MCA with a less invasive procedure, a modified surgical technique for MCAO in rats was developed. Besides, rats receiving the modified and conventional method were compared with regard to infarct volume and by behavioral tests. RESULTS: Following craniotomy, we proposed that the inferior edge of the craniotomy should be enlarged with fine forceps. This modified surgical method induces larger infarct volume, significant behavioral impairment and can induce ischemic stroke. Additionally, it does not significantly increase the operation time, and has produced no obvious complications. CONCLUSION: This modified surgical technique may serve as a practical method for performing MCAO.

Soluble epoxide hydrolase inhibition enhances anti-inflammatory and antioxidative processes, modulates microglia polarization, and promotes recovery after ischemic stroke.

BACKGROUND: Ischemic stroke triggers inflammatory responses and oxidative stress in the brain, and microglia polarization affects the degree of neuroinflammation. It has been reported that the inhibition of soluble epoxide hydrolase (sEH) activity protects brain tissue. However, the anti-inflammatory and antioxidative effects of sEH inhibition in the ischemic brain are not fully understood. This study aimed to investigate the effects of a selective sEH inhibitor, 12-(3-adamantan-1-yl-ureido)-dodecanoic acid (AUDA), after ischemic stroke. METHODS: Adult male rats with middle cerebral artery occlusion (MCAO) were administered with AUDA or a vehicle. Behavioral outcome, infarct volume, microglia polarization, and gene expression were assessed. RESULTS: Rats treated with AUDA showed better behavioral outcomes and smaller infarct volumes after MCAO. After AUDA treatment, a reduction of M1 microglia and an increase of M2 microglia occurred at the ischemic cortex of rats. Additionally, there was an increase in the mRNA expressions of antioxidant enzymes and anti-inflammatory interleukin-10, and pro-inflammatory mediators were decreased after AUDA administration. Heme oxygenase-1 was mainly expressed by neurons, and AUDA was found to improve the survival of neurons. CONCLUSION: The results of this study provided novel and significant insights into how AUDA can improve outcomes and modulate inflammation and oxidative stress after ischemic stroke.