METHODS: This study leverages genetic variation data from genome-wide association study (GWAS) datasets and employs a bidirectional two-sample MR analysis. The analysis incorporates MR Egger, weighted median, weighted mode, and inverse variance weighted (IVW) methods to assess the bidirectional causal relationship between cognitive abilities and WMH volume, FA, and MD.
RESULTS: This study employed MR to explore the causal relationships between WMH volume, FA, MD, and cognitive outcomes. Most MR methods yielded nonsignificant p values (>0.05) and wide confidence intervals. Heterogeneity tests indicated no significant heterogeneity or pleiotropy between WMH volume and cognitive performance or intelligence. However, significant heterogeneity was found between WMH volume and cognitive function, FA with cognitive performance and intelligence, and MD with cognitive performance and intelligence. Reverse analysis also revealed no significant causal relationships.
CONCLUSIONS: This study suggests that the bidirectional causal effects between cognitive abilities and WMH volume, FA, and MD are minimal or nonsignificant and highlights data heterogeneity as a concern.
METHODS: A total of 479 patients with primary pterygium who were admitted to our hospital from March 2019 to March 2023 were randomly divided into three groups: the normal group (Group A: 89 patients), the control group (Group B: 195 patients), and the modified group (Group C: 195 patients). Each group received different intervention measures. Group A did not undergo surgical treatment and were required to follow up as outpatients. Group B received LSC transplantation combined with interrupted suturing plus BCL, whereas Group C received modified LSC transplantation combined with BCL. The degree of corneal irritation symptoms, wound healing and graft status under slit lamp, incidence and recurrence rate of complications, tear film rupture time, tear secretion test, intraocular pressure, ocular surface inflammation response(IL-1β, PGE2, TNF-α, VEGF), and visual quality were compared and analyzed at various time points after surgery.
RESULTS: Compared with those in the Group B, patients in the Group C experienced faster normalization of corneal epithelium recovery, fewer corneal irritation symptoms, and better wound healing. The break-up time (BUT) of the tear film at 1 week to 1 year postoperatively was significantly greater in the Group C than Group B, with values approaching those of Group A by 3 months (P 0.05). The ELISA results indicated that the expression levels of the ocular surface inflammatory factors IL-1β, TNF-α, PEG2, and VEGF in the Group C were lower than those in Group B from 1 week to 1 year post surgery. Under both natural light and low-light conditions (spatial frequency/6 cd), Group C had better best-corrected visual acuity and contrast sensitivity than Group B at 1 week to 1 year postoperatively. Additionally, Group C had lower corneal higher-order aberrations (including astigmatism, spherical aberrations, and total higher-order aberrations) and superior vision-related quality of life scores at 1 year postoperatively than Group B, with statistically significant differences (P
INTRODUCTION: The major goal of this study was to determine the effects of short-term group-based step aerobics (GBSA) exercise on the bone metabolism, bone mineral density (BMD), and functional fitness of postmenopausal women (PMW) with low bone mass.
METHODS: Forty-eight PMW (aged 58.2 ± 3.5 years) with low bone mass (lumbar spine BMD T-score of -2.00 ± 0.67) were recruited and randomly assigned to an exercise group (EG) or to a control group (CG). Participants from the EG attended a progressive 10-week GBSA exercise at an intensity of 75-85 % of heart rate reserve, 90 min per session, and three sessions per week. Serum bone metabolic markers (C-terminal telopeptide of type 1 collagen [CTX] and osteocalcin), BMD, and functional fitness components were measured before and after the training program. Mixed-models repeated measures method was used to compare differences between the groups (α = 0.05).
RESULTS: After the 10-week intervention period, there was no significant exercise program by time interaction for CTX; however, the percent change for CTX was significantly different between the groups (EG = -13.1 ± 24.4 % vs. CG = 11.0 ± 51.5 %, P
METHODS: This study aims to develop a highly accurate and lightweight model for automatically predicting and classifying KOA through knee X-ray imaging. We propose a deep learning model named OA-MEN, which integrates a hybrid model combining ResNet and MobileNet feature extraction with multi-scale feature fusion. This approach ensures enhanced extraction of semantic information without losing the advantages of large feature maps provided by high image resolution in lower layers of the network. This effectively expands the model's receptive field and strengthens its understanding capability. Additionally, we conducted unseen-data tests and compared our model with widely used baseline models to highlight its superiority over conventional approaches.
RESULTS: The OA-MEN model demonstrated exceptional performance in tests. In the unseen-data test, our model achieved an average accuracy (ACC) of 84.88% and an Area Under the Curve (AUC) of 89.11%, marking improvements over the best-performing baseline models. These results showcase its improved capability in predicting KOA from X-ray images, making it a promising tool for assisting radiologists in diagnosis and treatment selection in clinical settings.
CONCLUSION: Leveraging deep learning for osteoarthritis classification guarantees heightened efficiency and accuracy. The future goal is to seamlessly integrate deep learning and advanced computational techniques with the expertise of medical professionals.