Ophthalmic imaging examination is the main basis for early screening, evaluation and diagnosis of eye diseases. In recent years, with the improvement of computer data analysis ability, the deepening of new algorithm research and the popularization of big data platform, artificial intelligence (AI) technology has developed rapidly and become a hot topic in the field of medical assistant diagnosis. The advantage of AI is accurate and efficient, which has great application value in processing image-related data. The application of AI not only helps to promote the development of AI research in ophthalmology, but also helps to establish a new medical service model for ophthalmic diagnosis and promote the process of prevention and treatment of blindness. Future research of ophthalmic AI should use multi-modal imaging data comprehensively to diagnose complex eye diseases, integrate standardized and high-quality data resources, and improve the performance of algorithms.
Parkinson’s disease is a neurodegenerative disease that mostly occurs in middle-aged and elderly people. It is characterized by progressive loss of dopaminergic neurons in the substantia nigra and aggregation of Lewy bodies, resulting in a series of motor symptoms and non-motor symptoms. Depression is the most important manifestation of non-motor symptoms, which seriously affects the quality of life of patients. Clinicians often use antidepressant drugs to improve the depressive symptoms of patients with Parkinson 's disease, but it is still urgent to solve the problems of drug side effects and drug resistance caused by such methods. Repetitive transcranial magnetic stimulation is a safe and non-invasive neuromodulation technique that can change the excitability of the corticospinal tract, induce the release of dopamine and other neurotransmitters, and further improve the depressive symptoms of patients with Parkinson 's disease. Based on this, this paper discusses and summarizes the research progress on the efficacy and potential mechanism of repetitive transcranial magnetic stimulation for improving depression in Parkinson 's disease at home and abroad, in order to provide reference for related clinical application research.
ObjectiveTo investigate the predictive value of pretracheal lymph node (Ⅵc) subdivision for contralateral central lymph node (CLN) metastasis in clinical lymph node negative (cN0) unilateral papillary thyroid carcinoma (PTC). MethodsThe data of patients with cN0 unilateral PTC who initially underwent total thyroidectomy and bilateral CLN dissection in the Department of Thyroid Surgery of West China Hospital, Sichuan University from July 2017 to June 2021 were collected retrospectively. The Ⅵc subdivision was divided into right anterior trachea (Ⅵc1) and left anterior trachea (Ⅵc2); If the lymph nodes crossed the middle line of trachea, which would be included in the side of cancer focus. ResultsA total of 175 patients were included in this study, and the incidences of lymph nodes metastasis in the prelaryngeal (Ⅵd), Ⅵc, ipsilateral Ⅵc, contralateral Ⅵc, ipsilateral central, and contralateral central regions were 54 cases (30.9%), 118 cases (67.4%), 85 cases (48.6%), 72 cases (41.1%), 108 cases (61.7%), and 43 cases (24.6%), respectively. The results of the univariate analysis found that the contralateral CLN metastasis was associated with the lymph node metastases of Ⅵd, Ⅵc, contralateral Ⅵc, and ipsilateral central regions; The results of the multivariate analysis found that the lymph node metastases of Ⅵd and contralateral Ⅵc regions increased the probability of contralateral CLN metastasis (OR=4.444, P<0.001; OR=6.655, P=0.001). ConclusionsFrom the results of the study,Ⅵc subdivision is reasonable and effective, and has a certain predictive value for the metastasis of contralateral CLN in cN0 unilateral papillary thyroid carcinoma. And bilateral CLN dissection should be recommended in patients with a positive intraoperative frozen section result of contralateral pretracheal lymph node metastasis.