Jing Luo

Jul 2, 2024 | nature.com | Jing Luo |Song Lin

Our study aimed to investigate the relationship between sleep–wake changes and depressive symptoms events among midlife women. We enrolled 1579 women aged 44–56 years who had no clinically relevant depressive symptoms at baseline. Depressive symptoms were assessed at each visit using the Center for Epidemiologic Studies Depression scale. At the third and fourth follow-up visits, women reported their sleep habits. The sleep midpoint was defined as the time to fall asleep plus one-half of the sleep duration. Sleep–wake changes were determined by the difference in the midpoint of sleep between the third and fourth visits, which were 1 year apart. The median follow-up time was 7 years (range 1–7 years). Cox proportional hazard models were fitted to calculate hazard ratios and 95% confidence intervals for the incidence of depressive symptoms associated with sleep–wake changes. After adjusting for potential confounding factors, the hazard ratio (95% confidence interval) of depressive symptoms for severe sleep midpoint changes was 1.51 (1.12, 2.05) compared with mild sleep midpoint changes. This relationship remained statistically significant and changed little when additionally controlling for sleep duration, sleep quality, insomnia symptoms, use of sleep medications, use of nervous medications, glucose, insulin, lipids, dietary energy intake, and C-reactive protein. Our findings indicate that exposure to long-term severe sleep–wake changes increases the risk of depressive symptoms in midlife women.

Apr 19, 2024 | ift.onlinelibrary.wiley.com | Jiayi Chen |Hongwu Ji |Jing Luo |Di Zhang

CONFLICT OF INTEREST STATEMENT The authors declare that they have no known conflicts of financial interest or personal relationships that could have appeared to influence the work reported in this paper. REFERENCES , , , , , , , , & (2023). Medicinal chemistry of non-peptidomimetic dipeptidyl peptidase IV (DPP IV) inhibitors for treatment of type-2 diabetes mellitus: Insights on recent development. Journal of Molecular Structure, 1284, 135249.

Apr 16, 2024 | translational-medicine.biomedcentral.com | Yanzhu Chen |Haoyu Li |Xiaoxi Yao |Yongan Meng |Yuqian Hu |Dan Liu | +7 more

Diabetic macular edema (DME) is a leading cause of vision loss in patients with diabetes. This study aimed to develop and evaluate an OCT-omics prediction model for assessing anti-vascular endothelial growth factor (VEGF) treatment response in patients with DME. A retrospective analysis of 113 eyes from 82 patients with DME was conducted. Comprehensive feature engineering was applied to clinical and optical coherence tomography (OCT) data. Logistic regression, support vector machine (SVM), and backpropagation neural network (BPNN) classifiers were trained using a training set of 79 eyes, and evaluated on a test set of 34 eyes. Clinical implications of the OCT-omics prediction model were assessed by decision curve analysis. Performance metrics (sensitivity, specificity, F1 score, and AUC) were calculated. The logistic, SVM, and BPNN classifiers demonstrated robust discriminative abilities in both the training and test sets. In the training set, the logistic classifier achieved a sensitivity of 0.904, specificity of 0.741, F1 score of 0.887, and AUC of 0.910. The SVM classifier showed a sensitivity of 0.923, specificity of 0.667, F1 score of 0.881, and AUC of 0.897. The BPNN classifier exhibited a sensitivity of 0.962, specificity of 0.926, F1 score of 0.962, and AUC of 0.982. Similar discriminative capabilities were maintained in the test set. The OCT-omics scores were significantly higher in the non-persistent DME group than in the persistent DME group (p < 0.001). OCT-omics scores were also positively correlated with the rate of decline in central subfield thickness after treatment (Pearson’s R = 0.44, p < 0.001). The developed OCT-omics model accurately assesses anti-VEGF treatment response in DME patients. The model’s robust performance and clinical implications highlight its utility as a non-invasive tool for personalized treatment prediction and retinal pathology assessment.

Jun 9, 2023 | pubs.rsc.org | Jing Luo |Xiang Ren |Huan Wang |Dan Wu

Photoelectrochemical aptamer sensor based on AgInS2 and ZnS co-sensitized TiO2 for detection of Hg2+ Jing Luo,   Xiang Ren,   Huan Wang,   Dan Wu,   Dawei Fan,   Ying-Ju Fan  and  Qin Wei   Abstract In this work, a photoelectrochemical (PEC) aptamer sensor using TiO2/AgInS2/ZnS composite material as photoelectric active anode substrate and NiCo-MOF@Au as quenching element is constructed to detect Hg2+.