Small dense low-density lipoprotein cholesterol (sdLDL-C) concentration was useful in the assessment of the presence of cardiovascular diseases (CVD) and its severity. We examined whether SdLDL-C is more closely associated with carotid artery intima-media thickness (CA-IMT), a surrogate measure of atherosclerosis, than LDL-C and traditional CVD risk factors in Chinese healthy subjects. We measured CA-IMT, blood pressure (BP), sdLDL-C, glucose metabolism and lipid in 183 native Chinese healthy subjects. CA-IMT was assessed by ultrasonography, and sdLDL-C concentrations were measured by a homogenous assay. Pearson's correlation coefficient analyses and Multiple regression analyses were used to examine the relationships between CA-IMT values and other clinical variables. The sdLDL-C level was significantly higher in males than in females (p <0.05) and there was an age effect on sdLDL-C (p <0.05). When the effects of age, gender and other traditional CVD risk factors were adjusted using multiple regression analysis. CA-IMT remained significantly associated with sdLDL-C(β = 0.437, p <0.001). There are gender and age differences in sdLDL-C levels among a healthy Chinese population. Moreover, we found adjusted traditional CVD risk factors such as higher age, male sex, and other traditional CVD risk factors, the association between CA-IMT and SdLDL-C remained significant. sdLDL-C is may be a useful predictor in the assessment of CA-IMT in Chinese population.

This longitudinal study investigated small dense low-density lipoprotein cholesterol (sdLDL-C) and its discordance with ‌low-density lipoprotein cholesterol (LDL-C) as predictors of hypertension (HTN) incidence in a Chinese population. Sampson’s equation was used to calculate sdLDL-C‌. Using data from 4,574 adults aged ≥ 45 from the ‌China Health and Retirement Longitudinal Study (CHARLS)‌, participants were stratified into three groups by sdLDL-C‌/LDL-C‌ percentile divergence (≥ 10%): discordantly low sdLDL-C, concordant, and discordantly high sdLDL-C. Cox regression analyses were performed to examine the relationship between sdLDL-C and HTN, adjusting for potential confounders. Additionally, we compared the LDL-C values derived from the Sampson equation with those measured by the homogeneous assay employed in this study. Over 9 years, 1,826 (39.9%) developed HTN‌. Cox regression adjusted for confounders showed baseline log-transformed sdLDL-C independently predicted HTN risk (hazard ratio [HR]‌ = 1.36, 95% confidence interval [CI]‌:1.17–1.57). The discordantly high sdLDL-C group had 24% higher HTN risk versus the discordantly low group (‌HR‌ = 1.28, 95% ‌CI‌:1.13–1.45). Stratification by three LDL-C clinical thresholds and median values revealed individuals with low LDL-C but high sdLDL-C had the highest HTN risk (vs. low LDL-C/low sdLDL-C reference group in fully adjusted models). Despite strong correlation (Spearman’s r = 0.956), systematic biases between direct LDL-C and Sampson methods may limit clinical interchangeability. sdLDL-C, particularly its discordance with LDL-C, is independently associated with incident HTN risk in Chinese adults. These findings underscore sdLDL-C’s potential to refine cardiovascular risk stratification and enhance precision prevention strategies.

Cardiovascular disease (CVD) is often comorbid with chronic kidney disease (CKD). Small low-density lipoprotein cholesterol (sdLDL-C) has also been found to increase risk for CVD. The goal of the present study was to determine the nature of the relationship between sdLDL-C concentration and CVD in patients with CKD. One-hundred and forty-five subjects (113 men and 32 women) with CKD (Stage 3 and Stage 4) participated this retrospective study. The concentration of sdLDL-C was measured in samples from 145 CKD patients between 2010 and 2012 during a four-year follow-up period. A total of eight fatal cardiovascular events (CVs) and 46 nonfatal CVs were registered in the four-year follow-up period. Multivariate Cox regression analysis showed that sdLDL-C [1.278, 95 % (1.019–1.598)] and sdLDL-C/LDL-C [2.456, 95 % (1.421–15.784)], at final observation, were independent risks of CVs. A Kaplan-Meier survival analysis showed that patients with sdLDL-C >38 mg/dl (logrank: 4.375, P = 0.037), and sdLDL-C/LDL-C ratio >0.3 levels (logrank: 11.94, P = 0.018) were at increased risk for CVs. The results of this study indicated that for patients suffering CKD, a significant relationship exists between an elevated sdLDL-C concentration and the risk of cardiovascular disease.

Background: Trigeminal neuralgia (TN) is the most common neuropathic disorder in the maxillofacial region. The etiology and pathogenesis of TN have not been clearly determined to date, although there are many hypotheses. Objective: The goal of this study was to investigate the interactions between different types of cells in TN, particularly the impact and intrinsic mechanism of demyelination on the trigeminal ganglion, and to identify new important target genes and regulatory pathways in TN. Methods: TN rat models were prepared by trigeminal root compression, and trigeminal nerve tissues were isolated for spatial transcriptome sequencing. The gene expression matrix was reduced dimensionally by PCA and presented by UMAP. Gene function annotation was analyzed by Metascape. The progression of certain clusters and the developmental pseudotime were analyzed using the Monocle package. Modules of the gene coexpression network between different groups were analyzed based on WGCNA and assigned AddModuleScore values. The intercellular communication of genes in these networks via ligand‒receptor interactions was analyzed using CellPhoneDB analysis. Results: The results suggested that the trigeminal ganglion could affect Schwann cell demyelination and remyelination responses through many ligand‒receptor interactions, while the effect of Schwann cells on the trigeminal ganglion was much weaker. Additionally, ferroptosis may be involved in the demyelination of Schwann cells. Conclusions: This study provides spatial transcriptomics sequencing data on TN, reveals new markers, and redefines the relationship between the ganglion and myelin sheath, providing a theoretical basis and supporting data for future mechanistic research and drug development. Export

Post-stroke depression (PSD) is a common but severe mental complication after stroke. However, the cellular and molecular understanding of PSD is still yet to be illustrated. In current study, we prepared PSD rat model (MD) via unilateral middle cerebral artery occlusion (MCAO) and chronic stress stimulation (DEPR), and isolated hippocampal tissues for single cell sequencing of 10x Genomics Chromium. First, we determined the presence of the increased cell population of endothelium and microglia and the compromised oligodendrocytes in MD compared to NC, MCAO and DEPR. The enriched functions of highly variable genes (HVGs) of endothelium and microglia suggested a reinforced blood-brain barrier in MD. Next, cell clusters of endothelium, microglia and oligodendrocytes were individually analyzed, and the subtypes with distinct functions were identified. The presence of expression profiles, intercellular communications and signaling pathways of these three cell populations of PSD displayed a similar but more aggressive appearance with DEPR compared to MCAO and NC. Taken together, this study characterized the specific gene profile of endothelium, microglia and oligodendrocytes of hippocampal PSD by single cell sequencing, emphasizing the crosstalk among them to provide theoretical basis for the in-depth mechanism research and drug therapy of PSD.

Objective: To compare the predictive performance of the novel Cholesterol, High-Density Lipoprotein, and Glucose (CHG) index for the incident type 2 diabetes mellitus (T2DM) versus the established indices—triglyceride-glucose (TyG), atherogenic index of plasma (AIP), and metabolic score for insulin resistance (METS-IR). Methods: A longitudinal cohort study was performed on 15, 453 participants from the NAGALA cohort (2004–2015) without baseline T2DM. The CHG index was calculated from total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), and fasting blood glucose (FBG). Several additional indices were established, including the TyG, AIP, and METS-IR. Cox regression, Kaplan-Meier analysis, restricted cubic spline (RCS) analysis, and time-dependent receiver operating characteristic (ROC) curves were performed to determine the predictive performance, after adjusting for various confounders (e.g., obesity, liver function). Robustness was assessed through sensitivity analyses. Results: During a 6.13-year follow-up, 373 T2DM cases were recorded. In the fully adjusted models, we found that the CHG index had the highest hazard ratio (HR): 6.18 per unit (95% CI: 3.38–11.27), outperforming the TyG index (HR: 1.39), AIP (HR: 1.80), and METS-IR (HR: 1.07). Quartile analysis revealed a dose-response relationship for CHG (Q4 HR: 4.36 vs. Q1, P < 0.001). Further, the RCS analysis revealed a linear association between CHG and T2DM risk ( P for overall trend < 0.001; P for nonlinearity = 0.712). Moreover, the CHG index achieved a satisfactory discriminative accuracy (based on the area under the curve [AUC]: 0.783 vs. TyG: 0.751, AIP: 0.745, METS-IR: 0.780) and its predictive power was consisted over the 12 years (peak AUC: 0.798 at 7 years). Sensitivity analyses for various subgroups (e.g., non-obese, non-fatty liver) confirmed that the obtained results were robust. Conclusions: The CHG index that integrates cholesterol, HDL-C, and glucose metabolism, showed superior predictive performance for the incidence of T2DM. Suggesting that it effectively captures the multifactorial pathophysiology of the disease. It is based on routine biomarkers making it easily applicable in risk stratification, offering a cost-effective tool for early intervention and precise prevention in clinical and public health settings.