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Background: Peripheral facial paralysis (PFP) is a common peripheral neural disease. Acupuncture treatment combined with PFP rehabilitation exercises is a routine method of PFP treatment. This article is to provide a new visual and objective evaluation method for exploring the mechanism and efficacy of acupuncture treatment on PFP, and develop an interactive augmented facial nerve function rehabilitation training system with multiple training models. Methods: This prospective and observational trial will recruit 200 eligible participants for the following study. In the trial, the laser speckle contrast analysis (LASCA) technology will be applied to monitor the microcirculation of facial blood flow during acupuncture, and real-time monitoring algorithms, data sampling, and digital imaging methods will be conducted by machine learning and image segmentation. Then, a database of patient facial expressions will be built, the correlation between surface blood flow perfusion volume and facial structure symmetry will be analyzed, combined with scale assessment and electrophysiological detection. In addition, we will also explore the objectivity and effectiveness of LASCA in the evaluation of facial paralysis (FP), and the changes in blood flow microcirculation before and after acupuncture treatment will be analyzed. Results: The standard image of the facial target area with facial nerve injury will be manually segmented by the convolutional neural network method. The blood flow images of the eyelid, cheek, and mandible of the patients’ affected and healthy side will be compared and evaluated. Laser speckle blood flow symmetry Pr and its changes in FP condition evolution and prognosis outcome will be measured, and relevant characteristic signals values will be extracted. Finally, COX regression analysis method is conducted to establish a higher accuracy prediction model of FP with cross-validation based on laser speckle blood flow imaging technology. Conclusions: We use modern interdisciplinary high-tech technologies to explore the mechanism of acupuncture rehabilitation training in PFP. And we will provide evidence for the feasibility of using the LASCA technique as a typing diagnosis of FP in the acupuncture rehabilitation treatment of PFP. Registration number: ChiCTR1800019463

Drug-induced liver injury (DILI) is often undiagnosed or misdiagnosed clinically because of diagnostic difficulties caused by lack of laboratory-specific serological markers. In this study, we comprehensively assessed the clinical characteristics, laboratory indices, hepatotoxic drugs, risk factors and outcomes concerning DILI, and explored the similarities in mechanisms between Chinese and Western drug-induced DILI. Patients with a first diagnosis of DILI and a Roussel Uclaf Causality Assessment Method (RUCAM) score >3 points were enrolled for systematic retrospective study. Their clinical characteristics, clinical classification, risk factors, laboratory indices, hepatotoxic drugs and outcomes were analyzed. Cholestatic patients had the highest alkaline phosphatase (ALP) and prothrombin time activity (PTA) levels (P

Color gamut mapping has been recognized as one of the key elements for accurate image reproduction. A variety of gamut mapping algorithms (GMAs) has been proposed to minimize the image differences between originals and their reproductions across different media. However, the use of a single-GMA is normally unable to fulfill all types of image reproductions. Therefore, we doubt if itis a right way to further improve the performance of a single algorithm while increasing its complexity. In this study, we propose an optimal multi-GMAs approach based on image analysis to select an appropriate GMA from a range of LUT-type GMAs to give the image the best treatment at low-computational cost. Because there are too many image statistics can be extracted from an image, the present study introduces methods to select the principal statistics for the GMA selection. To save the cost for real-time image analysis, the importance of scanning patterns and image compression was investigated as well. The results suggested that the performance of the above applications would be enhanced to a certain level if we choose appropriate image statistics for calculation.