Role of APOE in glaucoma.

Glaucoma is a chronic blinding eye disease caused by the progressive loss of retinal ganglion cells (RGCs). Currently, no clinically approved treatment can directly improve the survival rate of RGCs. The Apolipoprotein E (APOE) gene is closely related to the genetic risk of numerous neurodegenerative diseases and has become a hot topic in the field of neurodegenerative disease research in recent years. The optic nerve and retina are extensions of the brain's nervous system. The pathogenesis of retinal degenerative diseases is closely related to the degenerative diseases of the nerves in the brain. APOE consists of three alleles, ε4, ε3, and ε2, in a single locus. They have varying degrees of risk for glaucoma. APOE4 and the APOE gene deletion (APOE-/-) can reduce RGC loss. By contrast, APOE3 and the overall presence of APOE genes (APOE+/+) result in significant loss of RGC bodies and axons, increasing the risk of glaucoma RGCs death. Currently, there is no clear literature indicating that APOE2 is beneficial or harmful to glaucoma. This study summarises the mechanism of different APOE genes in glaucoma and speculates that APOE targeted intervention may be a promising method for protecting against RGCs loss in glaucoma.

The Role of the Dysregulated JNK Signaling Pathway in the Pathogenesis of Human Diseases and Its Potential Therapeutic Strategies: A Comprehensive Review.

JNK is named after c-Jun N-terminal kinase, as it is responsible for phosphorylating c-Jun. As a member of the mitogen-activated protein kinase (MAPK) family, JNK is also known as stress-activated kinase (SAPK) because it can be activated by extracellular stresses including growth factor, UV irradiation, and virus infection. Functionally, JNK regulates various cell behaviors such as cell differentiation, proliferation, survival, and metabolic reprogramming. Dysregulated JNK signaling contributes to several types of human diseases. Although the role of the JNK pathway in a single disease has been summarized in several previous publications, a comprehensive review of its role in multiple kinds of human diseases is missing. In this review, we begin by introducing the landmark discoveries, structures, tissue expression, and activation mechanisms of the JNK pathway. Next, we come to the focus of this work: a comprehensive summary of the role of the deregulated JNK pathway in multiple kinds of diseases. Beyond that, we also discuss the current strategies for targeting the JNK pathway for therapeutic intervention and summarize the application of JNK inhibitors as well as several challenges now faced. We expect that this review can provide a more comprehensive insight into the critical role of the JNK pathway in the pathogenesis of human diseases and hope that it also provides important clues for ameliorating disease conditions.

Clinical application potential of large language model: a study based on thyroid nodules.

BACKGROUND: Limited data indicated the performance of large language model (LLM) taking on the role of doctors. We aimed to investigate the potential for ChatGPT-3.5 and New Bing Chat acting as doctors using thyroid nodules as an example. METHODS: A total of 145 patients with thyroid nodules were included for generating questions. Each question was entered into chatbot of ChatGPT-3.5 and New Bing Chat five times and five responses were acquired respectively. These responses were compared with answers given by five junior doctors. Responses from five senior doctors were regarded as gold standard. Accuracy and reproducibility of responses from ChatGPT-3.5 and New Bing Chat were evaluated. RESULTS: The accuracy of ChatGPT-3.5 and New Bing Chat in answering Q2, Q3, Q5 were lower than that of junior doctors (all P < 0.05), while both LLMs were comparable to junior doctors when answering Q4 and Q6. In terms of "high reproducibility and accuracy", ChatGPT-3.5 outperformed New Bing Chat in Q1 and Q5 (P < 0.001 and P = 0.008, respectively), but showed no significant difference in Q2, Q3, Q4, and Q6 (P > 0.05 for all). New Bing Chat generated higher accuracy than ChatGPT-3.5 (72.41% vs 58.62%) (P = 0.003) in decision making of thyroid nodules, and both were less accurate than junior doctors (89.66%, P < 0.001 for both). CONCLUSIONS: The exploration of ChatGPT-3.5 and New Bing Chat in the diagnosis and management of thyroid nodules illustrates that LLMs currently demonstrate the potential for medical applications, but do not yet reach the clinical decision-making capacity of doctors.