Effects of Argatroban on Hcy, hs-CRP and FIB levels in patients with acute cerebral infarction.

OBJECTIVE: To evaluate the effects of argatroban on the levels of Hcy, hs-CRP and FIB in patients with acute cerebral infarction (ACI). METHODS: A retrospective analysis was performed on 382 patients with ACI who were hospitalized in the Department of Neurology of our hospital from January 2017 to December 2019. Among them, 158 patients received conventional treatment as the control group and 224 patients received combined treatment with argatroban as the study group. NHISS score, mRS score, Hcy, hs-CRP, FIB level, quality of life, adverse reactions were compared between the two groups after treatment. The levels of Hcy and hs-CRP in patients with different mRS scores were compared. RESULTS: A superior clinical efficacy of the study group was observed than the control group (p < 0.05). The study group witnessed a remarkably lower NHISS score, Hcy, hs-CRP and FIB level as compare to the control group (p < 0.05). The ADL and FMA scores in the study group were higher than those in the control group (p < 0.05). The levels of Hcy and hs-CRP in mRS 0-2 patients were lower than those in mRS 3-6 patients (p < 0.05). CONCLUSION: Argatroban in ACI patients can significantly enhance the clinical efficacy and improve the quality of life. It is closely related to the reduction of Hcy and hs-CRP levels, but the mechanism needs to be further studied.

Uncertainty-based Active Learning by Bayesian U-Net for Multi-label Cone-beam CT Segmentation.

INTRODUCTION: Training of Artificial Intelligence (AI) for biomedical image analysis depends on large annotated datasets. This study assessed the efficacy of Active Learning (AL) strategies training AI models for accurate multilabel segmentation and detection of periapical lesions in cone-beam CTs (CBCTs) using a limited dataset. METHODS: Limited field-of-view CBCT volumes (n = 20) were segmented by clinicians (clinician segmentation [CS]) and Bayesian U-Net-based AL strategies. Two AL functions, Bayesian Active Learning by Disagreement [BALD] and Max_Entropy [ME], were used for multilabel segmentation ("Lesion"-"Tooth Structure"-"Bone"-"Restorative Materials"-"Background"), and compared to a non-AL benchmark Bayesian U-Net function. The training-to-testing set ratio was 4:1. Comparisons between the AL and Bayesian U-Net functions versus CS were made by evaluating the segmentation accuracy with the Dice indices and lesion detection accuracy. The Kruskal-Wallis test was used to assess statistically significant differences. RESULTS: The final training set contained 26 images. After 8 AL iterations, lesion detection sensitivity was 84.0% for BALD, 76.0% for ME, and 32.0% for Bayesian U-Net, which was significantly different (P < .0001; H = 16.989). The mean Dice index for all labels was 0.680 ± 0.155 for Bayesian U-Net and 0.703 ± 0.166 for ME after eight AL iterations, compared to 0.601 ± 0.267 for Bayesian U-Net over the mean of all iterations. The Dice index for "Lesion" was 0.504 for BALD and 0.501 for ME after 8 AL iterations, and at a maximum 0.288 for Bayesian U-Net. CONCLUSIONS: Both AL strategies based on uncertainty quantification from Bayesian U-Net BALD, and ME, provided improved segmentation and lesion detection accuracy for CBCTs. AL may contribute to reducing extensive labeling needs for training AI algorithms for biomedical image analysis in dentistry.

[The interactions of stromal-epithelial in a model of co-culture in the rabbit cornea].

OBJECTIVE: The purpose of the study is to produce a reconstructed cornea including epithelia and stroma by tissue engineering. The reconstructed tissue may provide a physiologic model for the investigations of interaction between corneal epithelial cells and keratocytes. METHODS: Epithelial cells and keratocytes were isolated from rabbit corneas and cultured on plastic substrates in vitro. The co-culture model was established using a special transwell in which two different cells were separated but were able to interact each other. Histological and immunohistological studies were performed to identify the cell types. Intercellular communication of both the cultured epithelial cells in pure and in co-culture with the keratocytes was studied by laser confocal scanning microscopy. RESULTS: Population doubling time (PDT) was 3.45, 3.30, 2.11 and 2.32 d in pure corneal epithelial cells, co-culture epithelial cells, pure keratocytes and co-culture keratocytes respectively. The epithelial cells in co-culture grew quicker than those in pure (P < 0.01) and the stromal cells in co-culture grew slower than those in pure (P < 0.01). Intercellular communication of the cultured epithelial cells in co-culture were more than that in pure (U = 2.691, P < 0.05). CONCLUSIONS: The co-culture model of epithelial cell and keratocyte is feasible. Under the co-culture system the responses of cell proliferation and intercellular communication are different between epithelial cells and keratocytes.

Macular thickness as a predictor of loss of visual sensitivity in ethambutol-induced optic neuropathy.

Ethambutol is a common cause of drug-related optic neuropathy. Prediction of the onset of ethambutol-induced optic neuropathy and consequent drug withdrawal may be an effective method to stop visual loss. Previous studies have shown that structural injury to the optic nerve occurred earlier than the damage to visual function. Therefore, we decided to detect structural biomarkers marking visual field loss in early stage ethambutol-induced optic neuropathy. The thickness of peripapillary retinal nerve fiber layer, macular thickness and visual sensitivity loss would be observed in 11 ethambutol-induced optic neuropathy patients (22 eyes) using optical coherence tomography. Twenty-four healthy age- and sex-matched participants (48 eyes) were used as controls. Results demonstrated that the temporal peripapillary retinal nerve fiber layer thickness and average macular thickness were thinner in patients with ethambutol-induced optic neuropathy compared with healthy controls. The average macular thickness was strongly positively correlated with central visual sensitivity loss (r (2) =0.878, P=0.000). These findings suggest that optical coherence tomography can be used to efficiently screen patients. Macular thickness loss could be a potential factor for predicting the onset of ethambutol-induced optic neuropathy.

[Experimental retinal vein occlusion induced by photodynamic approach].

OBJECTIVE: To develop a new photochemical method of experimental retinal vein occlusion and investigate the morphologic and histologic changes in the retina. METHODS: After intravenous injection of rose Bengal, the vessels next to the disc of miniature pigs in the experiment group (n = 15) were exposed to an endo-illuminator for 15 minutes. As a control group, the vessels next to the disc of each pig were exposed to the endo-illuminator without rose Bengal injection. After complete vascular occlusion, the eyes were observed at following times: one hour, and 1, 3, 7, 14, 21, and 28 days. After the 28th day, the eyes were enucleated and prepared for light and electron microscope examination. RESULTS: Histopathologic features were consistent with changes of retinal vein occlusion and formation of retinal vein thrombi was reliable. CONCLUSIONS: Photodynamic method combined with endo-illuminator was a simple, reliable and definitive experimental technique to produce retinal vein occlusion.