Dan Cao

Jan 16, 2025 | biorxiv.org | Yanghui Xiang |Xu Dong |Lan Ma |Dan Cao

AbstractBackground: The genus Providencia includes species of ecological and clinical significance, with some acting as opportunistic pathogens in hospital-acquired infections such as urinary tract infection (UTI). However, overlapping phenotypic traits and genetic similarities pose challenges for accurate species characterization. This study exemplifies this challenge by identifying a novel Providencia isolate through genomic analysis.

Aug 21, 2024 | cell.com | Jin Billy Li |Dan Cao |Wenlu Li

Highlights Intracranial neural recordings have revealed the distinct roles of various medial temporal lobe (MTL) regions in working memory (WM). MTL regions exhibit specific interactions both internally and with the neocortex, engaging in distinct oscillatory patterns across various phases of WM. Incorporating the MTL into working memory models deepens our understanding of the intricate neural mechanisms that underlie WM.

May 31, 2024 | translational-medicine.biomedcentral.com | Guanrong Wu |Yijun Hu |Anyi Liang |Zijing Du |Yanhua Liang |Yuxiang Zheng | +13 more

Diabetic macular edema (DME) is the leading cause of visual impairment in patients with diabetes mellitus (DM). The goal of early detection has not yet achieved due to a lack of fast and convenient methods. Therefore, we aim to develop and validate a prediction model to identify DME in patients with type 2 diabetes mellitus (T2DM) using easily accessible systemic variables, which can be applied to an ophthalmologist-independent scenario. In this four-center, observational study, a total of 1994 T2DM patients who underwent routine diabetic retinopathy screening were enrolled, and their information on ophthalmic and systemic conditions was collected. Forward stepwise multivariable logistic regression was performed to identify risk factors of DME. Machine learning and MLR (multivariable logistic regression) were both used to establish prediction models. The prediction models were trained with 1300 patients and prospectively validated with 104 patients from Guangdong Provincial People’s Hospital (GDPH). A total of 175 patients from Zhujiang Hospital (ZJH), 115 patients from the First Affiliated Hospital of Kunming Medical University (FAHKMU), and 100 patients from People’s Hospital of JiangMen (PHJM) were used as external validation sets. Area under the receiver operating characteristic curve (AUC), accuracy (ACC), sensitivity, and specificity were used to evaluate the performance in DME prediction. The risk of DME was significantly associated with duration of DM, diastolic blood pressure, hematocrit, glycosylated hemoglobin, and urine albumin-to-creatinine ratio stage. The MLR model using these five risk factors was selected as the final prediction model due to its better performance than the machine learning models using all variables. The AUC, ACC, sensitivity, and specificity were 0.80, 0.69, 0.80, and 0.67 in the internal validation, and 0.82, 0.54, 1.00, and 0.48 in prospective validation, respectively. In external validation, the AUC, ACC, sensitivity and specificity were 0.84, 0.68, 0.90 and 0.60 in ZJH, 0.89, 0.77, 1.00 and 0.72 in FAHKMU, and 0.80, 0.67, 0.75, and 0.65 in PHJM, respectively. The MLR model is a simple, rapid, and reliable tool for early detection of DME in individuals with T2DM without the needs of specialized ophthalmologic examinations.

Dec 9, 2023 | onlinelibrary.wiley.com | Dan Cao |Liang Zhou |Rong Hu

CONFLICT OF INTEREST STATEMENT The authors declare no conflict of interest. REFERENCES 1, , , , , , , , , Exp. Eye Res. 2022, 218, 108984. 2, , , , , , , Redox Rep. 2022, 27(1), 70. 3, , , , , , , Biomed. Pharmacother. 2022, 148, 112254. 4, , , , Horm. Metab. Res. 2022, 54(2), 119. 5, , , , , , , , , PLoS One 2016, 11(6), e0156495. 6, , , , , , J. Endocrinol. Invest. 2021, 44(6), 1193. 7, , , Neural Regen. Res. 2016, 11(9), 1512. 8, , , , , , , , , , , J.

Nov 16, 2023 | jneurosci.org | jin Li |Dan Cao |Shan Yu |Haiyan Wang

Theta-alpha connectivity in the hippocampal-entorhinal circuit predicts working memory load Jin Li (李瑾), Dan Cao (曹丹), Shan Yu (余山), Haiyan Wang (王海艳), Lukas Imbach, Lennart Stieglitz, Johannes Sarnthein, Tianzi Jiang (蒋田仔) Journal of Neuroscience 4 December 2023, JN-RM-0398-23; DOI: 10.1523/JNEUROSCI.0398-23.2023