Both thyroid hormones and irisin have profound influences on the metabolism of the human body. Based on their similarities, several studies have been conducted to explore changes in irisin levels in patients with hypothyroidism and hyperthyroidism. This study was conducted in accordance with the PRISMA statement and the MOOSE reporting guideline. Based on a preregistered protocol (PROSPERO—CRD42019138430), a comprehensive search of eight databases was performed from inception to April 2020. Studies with original data collected from patients with thyroid dysfunction were included. Subgroup analysis was performed based on the different types of clinical manifestations and patient characteristics. The quality of each study and the presence of publication bias were assessed by the Newcastle‐Ottawa score (NOS) and funnel plot with Egger’s test, respectively. A total of 11 studies with 1210 participants were included. Ten studies were identified as high‐quality studies. Pooled analysis indicated decreased irisin levels in patients with hypothyroidism (MD ‐10.37, 95% CI ‐17.81 to ‐2.93). Subgroup analysis revealed an even lower level of irisin in patients with clinical‐type hypothyroidism (MD ‐17.03, 95% CI ‐30.58 to ‐3.49) and hypothyroidism caused by autoimmune disease (MD ‐19.38, 95% CI ‐36.50 to ‐2.26). No differences were found after achieving euthyroid status from levothyroxine treatment in patients with hypothyroidism compared with controls. No differences were found between patients with hyperthyroidism and controls. Correlation analyses revealed a possible negative correlation between irisin and TSH and positive correlations between irisin and both fT3 and fT4. Irisin was correlated with TSH receptor antibodies.

To determine the risk factors associated with immediate hypersensitivity reactions to contrast media (CM-IHR). A systematic search was conducted in PubMed, Embase, Ovid, Web of Science database and the Cochrane Library up to December 2024 to identify studies in which risk factors associated with CM-IHR were explored. The Newcastle-Ottawa Scale was used to assess the risk of bias. Odds ratios (ORs) with 95% confidence intervals (CIs) for each risk factor were pooled from the selected studies. Heterogeneity was evaluated via the Higgins I² test. From 8,342 citations, seven were ultimately included in the meta-analysis, encompassing a total of 115,043 patients and 736,203 injections. The methodological quality was rated as high in six studies and moderate in one. Four studies investigated iodinated CM (ICM), while 3 investigated gadolinium-based contrast agent. Female sex (OR 1.46; 95 % CI 1.33-1.59) was identified as a significant risk factor for CM-IHR, and age showed an inverse association with risk (OR 0.98; 95 % CI 0.98-0.99). Asthma history was not suggested as a significant risk factor (OR 1.12; 95 % CI, 0.95-1.33; I² = 0 %). For ICM-IHR specifically, outpatient status was associated with higher risk (OR, 3.08; 95 % CI, 1.13-8.44). Notably, pooled analysis of two studies suggested a trend toward increased risk with prior history of hypersensitivity reaction to ICM; however, this association was not statistically significant and was accompanied by high heterogeneity (OR 7.49; 95 % CI, 0.42-135.09, I² = 87 %). Our systematic review and meta-analysis suggest that female sex was a significant risk factor for CM-IHR, whereas increasing age was associated with a lower risk. Outpatient status showed a significant association with ICM-IHR. Prior history of hypersensitivity reaction to ICM was not identified as a significant risk factor. Given the small number of available studies and substantial heterogeneity, these findings should be interpreted with caution.

Introduction Neoadjuvant chemotherapy has been demonstrated to be effective and recommended as the standard treatment option in patients with locally advanced gastric or gastro-oesophageal junction (G/GOJ) cancer. In this study, we will explore the efficacy and safety of chemotherapy combined with cadonilimab, a programmed death-1/cytotoxic T lymphocyte-associated antigen-4 bispecific antibody, in neoadjuvant therapy for locally advanced G/GOJ adenocarcinoma. Methods and analysis This is a single-centre, single-arm, open-label, phase II trial that will enrol 37 patients in total. Eligible patients will be registered and receive three cycles of oxaliplatin and S-1 (SOX) regimen in combination with cadonilimab. Radical D2 (D2 lymphadenectomy) gastrectomy will be performed within 4 weeks after the last administration of chemotherapy plus cadonilimab. The primary endpoint is the pathological complete response rate. Secondary endpoints are R0 resection rate, major pathological response, 2-year disease-free survival rate, 2-year overall survival rate and safety. The first participant was recruited on 1 September 2023 and the enrolment will be completed in July 2025. Ethics and dissemination Written informed consent will be required from and provided by all the patients enrolled. The study protocol (V.3.0, 28 April 2023) has been approved by the independent ethics committee of West China Hospital, Sichuan University (approval number: 2023526) and conducted under the Declaration of Helsinki. The results of the study may provide more evidence for neoadjuvant immunotherapy combined with chemotherapy in locally advanced G/GOJ adenocarcinoma. Trial registration number ClinicalTrials.gov, NCT05948449.

The most common mesenchymal tumors are gastrointestinal stromal tumors (GISTs), which have malignant potential and can occur anywhere along the gastrointestinal system. Imaging methods are important and indispensable of GISTs in diagnosis, risk staging, therapy, and follow-up. The recommended imaging method for staging and follow-up is computed tomography (CT) according to current guidelines. Artificial intelligence (AI) applies and elaborates theses, procedures, modes, and utilization systems for simulating, enlarging, and stretching the intellectual capacity of humans. Recently, researchers have done a few studies to explore AI applications in GIST imaging. This article reviews the present AI studies in GISTs imaging, including preoperative diagnosis, risk stratification and prediction of prognosis, gene mutation, and targeted therapy response.