The association between systemic inflammation markers and paroxysmal atrial fibrillation.

BACKGROUND: Systemic inflammation markers have recently been identified as being associated with cardiac disorders. However, limited research has been conducted to estimate the pre-diagnostic associations between these markers and paroxysmal atrial fibrillation (PAF). Our aim is to identify potential biomarkers for early detection of PAF. METHODS: 91 participants in the PAF group and 97 participants in the non-PAF group were included in this study. We investigated the correlations between three systemic inflammation markers, namely the systemic immune inflammation index (SII), system inflammation response index (SIRI), and aggregate index of systemic inflammation (AISI), and PAF. RESULTS: The proportion of patients with PAF gradually increased with increasing logSII, logSIRI, and logAISI tertiles. Compared to those in the lowest tertiles, the PAF risks in the highest logSII and logSIRI tertiles were 3.2-fold and 2.9-fold, respectively. Conversely, there was no significant correlation observed between logAISI and PAF risk within the highest tertile of logAISI. The restricted cubic splines (RCS) analysis revealed a non-linear relationship between the elevation of systemic inflammation markers and PAF risk. Specifically, the incidence of PAF is respectively increased by 56%, 95%, and 150% for each standard deviation increase in these variables. The ROC curve analysis of logSII, logSIRI and logAISI showed that they had AUC of 0.6, 0.7 and 0.6, respectively. It also demonstrated favorable sensitivity and specificity of these systemic inflammation markers in detecting the presence of PAF. CONCLUSIONS: In conclusion, our study reveals significant positive correlations between SII, SIRI, and AISI with the incidence of PAF.

Serum uric acid, body mass index, and cardiovascular diseases: A multiple two-step Mendelian randomization study.

BACKGROUND AND AIMS: A number of health issues, including high serum uric acid (SUA) and cardiovascular disease (CVD), have been linked to obesity based on observational evidence, though it's currently unclear how these issues are causally related. In order to determine whether obesity mediates this association, we set out to investigate the causal relationship between SUA, obesity, and CVD. METHODS AND RESULTS: From publicly available genome-wide association studies, we acquired instrumental variables that had a strong correlation to SUA and body mass index (BMI). We employed multiple two-step Mendelian randomization (MR) analyses, using genetic and clinical data from various publicly available biological databases. The mediating role of BMI was examined through mediation analysis. SUA was genetically correlated with BMI [OR = 1.080, 95% CI: 1.024-1.139, P = 0.005]. There was a positive causal effect of SUA on AF [OR = 0.892, 95% CI: 0.804-0.990, P = 0.032], CAD [OR = 0.942, 95% CI: 0.890-0.997, P = 0.037], and EHT [OR = 1.080, 95% CI: 1.024-1.139, P = 0.005]. Among them, BMI mediated the effects of SUA on AF (42.2%; 95% CI, 35.3%-51.9%), CAD (76.3%; 95% CI, 63.4%-92.0%), and EHT (10.0%; 95% CI, 0%-20.0%). CONCLUSION: Our research revealed a causal relationship between high SUA exposure and an increased risk of obesity. Additionally, a high SUA level was linked to an increased risk of various CVDs. Given that individuals with high SUA are more likely to be susceptible to AF, CAD, and EHT, attention must be given to their weight status.

The association between systemic inflammation markers and the prevalence of hypertension.

BACKGROUND: We conducted a large-scale epidemiological analysis to investigate the associations between systemic inflammation markers and hypertension prevalence. Our aim is to identify potential biomarkers for early detection of hypertension. METHODS: A cross-sectional study with 119664 individuals from the National Health and Nutrition Examination Survey was performed. We investigated the associations between three systemic inflammation markers, namely the systemic immune inflammation index (SII), system inflammation response index (SIRI), and aggregate index of systemic inflammation (AISI), and the prevalence of hypertension. RESULTS: The prevalence rates of hypertension gradually increased with increasing logSII, logSIRI, and logAISI quartiles. In continuous analyses, each unit increase in logSII, logSIRI, and logAISI was associated with a 20.3%, 20.1%, and 23.7% increased risk of hypertension. Compared to those in the lowest quartiles, the hypertension risks for subjects in the highest logSII, logSIRI, and logAISI quartiles were 1.114-fold,1.143-fold, and 1.186-fold. The restricted cubic splines (RCS) analysis revealed a non-linear relationship between the elevation of systemic inflammation markers and hypertension prevalence. Specifically, a per standard deviation increase in any of these variables is associated with a respective 9%, 16%, and 11% increase in hypertension prevalence. CONCLUSION: Our cross-sectional study reveals significant positive correlations between SII, SIRI, and AISI with the prevalence of hypertension.

Effect of dapagliflozin on left ventricular structure and function in patients with non-ischemic dilated cardiomyopathy: An observational study.

Non-ischemic dilated cardiomyopathy (NIDCM) is characterized by left ventricular dilatation and contractile dysfunction with severe morbidity and mortality. Sodium glucose cotransporter type 2 (SGLT2) inhibitors significantly reduce cardiovascular events for heart failure patients. We performed to investigate the impact of combined administration of SGLT2 inhibitors on cardiac structure and function in NIDCM patients undergoing conventional therapy. A total of 50 newly diagnosed NIDCM patients received conventional medical therapy, with 23 receiving dapagliflozin 10mg/day in addition (SGLT2i group) and the remaining 27 only receiving conventional therapy (non-SGLT2i group). After 12 months outpatient follow-up, NIDCM patients treated with conventional therapy alone showed a significant reduction of left ventricular end-diastolic dimensions (LVEDd), left ventricular end-systolic dimensions (LVESd), left ventricular end-diastolic volumes (LVEDV), left ventricular end-systolic volumes (LVESV), left ventricular end-diastolic volume index (LVEDVi) and left ventricular end-systolic volume index (LVESVi), while an increase in fractional shortening (FS) and left ventricular ejection fraction (LVEF). Patients receiving dapagliflozin combined with conventional treatment also demonstrated a significant reduction in left ventricular dimensions and volumes, and a marked increase in cardiac function. In non-SGLT2i groups, the % change in LVEDd, LVESd, LVEDV, LVESV, LVEDVi, LVESVi, FS and LVEF was -2.8%, -4.6%, -6.2%, -10.1%, -6.1%, -10.1%, +9.7%, +11%. A greater absolute % fall in left ventricular volume in SGLT2i groups compared to non-SGLT2i groups resulted in a significant improvement in cardiac function. The results showed that SGLT2i combined with conventional therapy has a better beneficial effect on left ventricular volumes and cardiac function in NIDCM patients.

Zero-shot stance detection based on multi-expert collaboration.

Zero-shot stance detection is pivotal for autonomously discerning user stances on novel emerging topics. This task hinges on effective feature alignment transfer from known to unseen targets. To address this, we introduce a zero-shot stance detection framework utilizing multi-expert cooperative learning. This framework comprises two core components: a multi-expert feature extraction module and a gating mechanism for stance feature selection. Our approach involves a unique learning strategy tailored to decompose complex semantic features. This strategy harnesses the expertise of multiple specialists to unravel and learn diverse, intrinsic textual features, enhancing transferability. Furthermore, we employ a gating-based mechanism to selectively filter and fuse these intricate features, optimizing them for stance classification. Extensive experiments on standard benchmark datasets demonstrate that our model significantly surpasses existing baseline models in performance.

Molecular mechanism of NAD+ and NMN binding to the Nudix homology domains of DBC1.

Deleted in breast cancer 1 (DBC1) is a human nuclear protein that modulates the activities of various proteins involved in cell survival and cancer progression. Oxidized form of nicotinamide adenine dinucleotide (NAD+) is suggested to bind to the Nudix homology domains (NHDs) of DBC1, thereby regulating DBC1-Poly (ADP-ribose) polymerase 1 (PARP1) interactions, resulting in the restoration of DNA repair. Using Nuclear Magnetic Resonance (NMR) and Isothermal Titration Calorimetry (ITC), we confirmed NAD+ and its precursor nicotinamide mononucleotide (NMN) both bind the NHD domain of DBC1 (DBC1354-396). NAD+ likely interacts with DBC1354-396 through hydrogen bonding, with a binding affinity (8.99 µM) nearly twice that of NMN (17.0 µM), and the key binding sites are primarily residues E363 and D372, in the agreement with Molecular Docking experiments. Molecular Dynamics (MD) simulation further demonstrated E363 and D372's anchoring role in the binding process. Additional mutagenesis experiments of E363 and D372 confirmed their critical involvement of ligand-protein interactions. These findings lead to a better understanding of how NAD+ and NMN regulate DBC1, thereby offering insights for the development of targeted therapies and drug research focused on DBC1-associated tumors.