Circulating microRNA-33b levels are associated with the presence and severity of coronary heart disease.

MicroRNA-33b (miR-33b) affected various biological pathways in regulating cholesterol homeostasis which may link to the pathogenesis of atherosclerotic lesions. However, whether this marker is associated with the presence and severity of coronary heart disease (CHD) is undetermined. We aim to explore the diagnostic value of circulating miR-33b level in the presence and severity of CHD. Altogether 320 patients were enrolled, including 240 patients diagnosed with CHD while 80 were classified as controls after CAG examination. Circulating miR-33b level was analyzed in all subjects, the Gensini score was calculated to assess the severity of stenotic lesions. The association between miR-33b and the presence and severity of CHD was analyzed, and the diagnostic potential of miR-33b of CHD was performed by the receiver operating characteristic (ROC) analysis. The CHD group had higher miR-33b levels (p < 0.001), and the miR-33b content significantly elevated following an increasing Gensini score (p for trend < 0.001). After adjustments for potential risk factors, such as several blood lipid markers, miR-33b remained a significant determinant for CHD (p < 0.001). ROC analysis disclosed that the AUC was 0.931. The optimal cutoff value of miR-33b was with a sensitivity of 81.3% and a specificity of 98.7% in differentiating CHD. It can prognosticate that the higher level of miR-33b was linked to increased severity of disease in CHD patients. Thus, the application of this marker might assist in the diagnosis and classification of CHD patients. Nevertheless, additional studies with larger sample sizes will be required to verify these results.

Impact of Immune Cells on Stroke Limited to Specific Subtypes: Evidence from Mendelian Randomization Study.

INTRODUCTION: Stroke is one of the common diseases that pose a severe threat to human health, with immune cells playing a crucial role in its onset and recovery. However, the specific mechanisms and causal relationships of different immune cell groups in various clinical stroke subtypes are unclear. This study explored the causal relationship between immune cells and stroke and its subtypes using Mendelian randomization (MR) analysis. METHODS: Data from genome-wide association studies were analyzed using inverse-variance weighted (IVW), MR-Egger, and weighted median methods for MR analysis, along with heterogeneity tests, sensitivity analysis, and pleiotropy analysis. RESULTS: CD45RA+CD28-CD8+ T cell %T cell (OR 1.002, 95% CI 1.001-1.003; PFDR = 0.02), CD27 on CD24+CD27+ B cell (OR 1.127, 95% CI 1.061-1.198; PFDR = 0.04), CD27 on IgD-CD38dim B cell (OR 1.138, 95% CI 1.076-1.203; PFDR = 0.005), and CD27 on switched memory B cell (OR 1.144, 95% CI 1.076-1.216; PFDR = 0.01) were found to increase the risk of large artery stroke. Switched memory B cell %lymphocyte (OR 1.206, 95% CI 1.103-1.318; PFDR = 0.02) increased the risk of small vessel stroke. Reverse MR analysis did not reveal any reverse causal associations. Furthermore, by substituting the outcome data, a secondary MR analysis was conducted to validate the primary findings. CONCLUSION: Our study reveals several causal links between immune phenotypes and stroke and its different subtypes, highlighting the complex interactions between the immune system and stroke. These findings provide new directions for further uncovering the biological basis of stroke and assist in advancing research on early interventions and treatment strategies.

Improved Multi-Stream Convolutional Block Attention Module for sEMG-Based Gesture Recognition.

As a key technology for the non-invasive human-machine interface that has received much attention in the industry and academia, surface EMG (sEMG) signals display great potential and advantages in the field of human-machine collaboration. Currently, gesture recognition based on sEMG signals suffers from inadequate feature extraction, difficulty in distinguishing similar gestures, and low accuracy of multi-gesture recognition. To solve these problems a new sEMG gesture recognition network called Multi-stream Convolutional Block Attention Module-Gate Recurrent Unit (MCBAM-GRU) is proposed, which is based on sEMG signals. The network is a multi-stream attention network formed by embedding a GRU module based on CBAM. Fusing sEMG and ACC signals further improves the accuracy of gesture action recognition. The experimental results show that the proposed method obtains excellent performance on dataset collected in this paper with the recognition accuracies of 94.1%, achieving advanced performance with accuracy of 89.7% on the Ninapro DB1 dataset. The system has high accuracy in classifying 52 kinds of different gestures, and the delay is less than 300 ms, showing excellent performance in terms of real-time human-computer interaction and flexibility of manipulator control.

Aberrant activation of the Hedgehog signaling pathway in granulosa cells from patients with polycystic ovary syndrome.

The molecular mechanism that triggers polycystic ovary syndrome (PCOS) is mysterious. Abnormal development of ovarian granulosa cells (GCs) is one of the causes of PCOS. Herein, our study was carried out using RNA-seq to detect the different gene expression levels in ovarian GCs between three patients with PCOS and four normal controls. To verify the RNA-seq data, GCs from 22 patients with PCOS and 21 controls with normal ovulation were collected to perform the RT-PCR analysis. Hedgehog signaling pathway (Hh) members, Ihh and Ptch2 were abnormally highly expressed in the PCOS tissue (PT). The qPCR also indicated that the expression levels of Hh signaling pathway downstream members, Ptch1, Gli1, and Gli2 in the PT were significantly higher than those in the normal tissue (NT). Besides, the expression of TNF-α mRNA in PCOS patients was higher than that in the control group. Through the chromatin immunoprecipitation assay (ChIP), we found that the Gli1-IP-DNA enriched from the granular cells of PCOS patients was higher than that of the control group. Finally, the Hh signaling pathway inhibitor, cyclopamine, can decrease the apoptosis of PCOS ovarian granulosa cells. These results suggest that abnormal activation of Hh signaling pathway, especially Ihh signal, may have a profound influence on PCOS.