Endometriosis is classically defined as a chronic inflammatory heterogeneous disorder occurring in any part of the body, characterized by estrogen-driven periodic bleeding, proliferation, and fibrosis of ectopic endometrial glands and stroma outside the uterus. Endometriosis can take overwhelmingly serious damage to the structure and function of multi-organ, even impair whole-body systems, resulting in severe dysmenorrhea, chronic pelvic pain, infertility, fatigue and depression in 5–10% women of reproductive age. Precisely because of a huge deficiency of cognition about underlying etiology and complex pathogenesis of the debilitating disease, early diagnosis and treatment modalities with relatively minor side effects become bottlenecks in endometriosis. Thus, endometriosis warrants deeper exploration and expanded investigation in pathogenesis. The gut microbiota plays a significant role in chronic diseases in humans by acting as an important participant and regulator in the metabolism and immunity of the body. Increasingly, studies have shown that the gut microbiota is closely related to inflammation, estrogen metabolism, and immunity resulting in the development and progression of endometriosis. In this review, we discuss the diverse mechanisms of endometriosis closely related to the gut microbiota in order to provide new approaches for deeper exploration and expanded investigation for endometriosis on prevention, early diagnosis and treatment.

Tuberculous meningitis (TBM) is not only one of the most fatal forms of tuberculosis, but also a major public health concern worldwide, presenting grave clinical challenges due to its nonspecific symptoms and the urgent need for timely intervention. The severity and the rapid progression of TBM underscore the necessity of early and accurate diagnosis to prevent irreversible neurological deficits and reduce mortality rates. Traditional diagnostic methods, reliant primarily on clinical findings and cerebrospinal fluid analysis, often falter in delivering timely and conclusive results. Moreover, such methods struggle to distinguish TBM from other forms of neuroinfections, making it critical to seek advanced diagnostic solutions. Against this backdrop, magnetic resonance imaging (MRI) has emerged as an indispensable modality in diagnostics, owing to its unique advantages. This review provides an overview of the advancements in MRI technology, specifically emphasizing its crucial applications in the early detection and identification of complex pathological changes in TBM. The integration of artificial intelligence (AI) has further enhanced the transformative impact of MRI on TBM diagnostic imaging. When these cutting-edge technologies synergize with deep learning algorithms, they substantially improve diagnostic precision and efficiency. Currently, the field of TBM imaging diagnosis is undergoing a phase of technological amalgamation. The melding of MRI and AI technologies unquestionably signals new opportunities in this specialized area.