Higher Adherence to Plant-Based Diet Lowers Type 2 Diabetes Risk among High and Non-High Cardiovascular Risk Populations: A Cross-Sectional Study in Shanxi, China.

This study aimed to investigate the association between the plant-based diet index (PDI) score and T2D risk among residents of Shanxi Province, China, and explore whether the association was influenced by different levels of cardiovascular risk. A total of 50,694 participants aged 35-75 years were recruited between 2017 and 2019, and they were further divided into the high cardiovascular risk population (HCRP; n = 17,255) and the non-high cardiovascular risk population (non-HCRP; n = 33,439). The PDI was calculated based on food frequency from a food frequency questionnaire (FFQ). Incident T2D was defined based on elevated plasma glucose (≥7 mmol/L) or hypoglycemic medicine use. We investigated the association of the PDI andT2D risk using a two-level generalized estimating equation and restricted cubic splines model. The results showed that quartile 4 of the PDI indicated significantly reduced T2D risk in the total population (OR: 0.83; 95% CI: 0.75-0.92), HCRP (OR: 0.80; 95% CI: 0.71-0.91), and non-HCRP (OR: 0.80; 95% CI: 0.74-0.87) compared with corresponding quartile 1 (OR = 1). In stratified analysis, the negative associations between PDI and T2D risk were stronger in the total population with the elderly (age > 60 years), BMI < 24, and men, and in the non-HCRP with men and BMI 24-28, and in the HCRP with the elderly and BMI < 24 than those with corresponding subgroups (pinteraction < 0.05). Linear curves were observed for the total population and non-HCRP, but an L-shaped association was observed for the HCRP. Therefore, our results suggest that higher PDI scores may effectively attenuate the T2D risk in the Chinese population and non-HCRP, and a beneficial association of PDI with T2D risk was observed in the HCRP at a certain threshold level. Longitudinal studies and intervention trials are required to validate our study findings.

Application and prospects of AI-based radiomics in ultrasound diagnosis.

Artificial intelligence (AI)-based radiomics has attracted considerable research attention in the field of medical imaging, including ultrasound diagnosis. Ultrasound imaging has unique advantages such as high temporal resolution, low cost, and no radiation exposure. This renders it a preferred imaging modality for several clinical scenarios. This review includes a detailed introduction to imaging modalities, including Brightness-mode ultrasound, color Doppler flow imaging, ultrasound elastography, contrast-enhanced ultrasound, and multi-modal fusion analysis. It provides an overview of the current status and prospects of AI-based radiomics in ultrasound diagnosis, highlighting the application of AI-based radiomics to static ultrasound images, dynamic ultrasound videos, and multi-modal ultrasound fusion analysis.

Recurrent Implantation Failure May Be Identified by a Combination of Diagnostic Biomarkers: An Analysis of Peripheral Blood Lymphocyte Subsets.

Background: Recurrent implantation failure (RIF) is a challenge during assisted reproductive technology (ART). In the present study, potential diagnostic biomarkers for the immune status of peripheral blood lymphocyte subsets in patients with RIF were analyzed, with the aim of identifying novel biomarkers that may predict RIF. Methods: A total of 41 participants, including 21 women with RIF and 20 fertile controls, were included in the present study. Functional analysis was performed and the cytokine status of natural killer (NK), T, CD8+ T, T helper (Th), and γδ T cells which are lymphocyte subsets in peripheral blood was measured using flow cytometry. Binary logistic regression analysis adjusted for T follicular helper 1 (Tfh1), Tfh2, Tfh17, and early NK cells was performed to determine the relationship between the peripheral blood lymphocyte subsets and RIF. Potential diagnostic biomarkers were assessed by logistic regression analysis and receiver operating characteristic curves. Results: There were significantly more Tfh1, Tfh17, and NK cells in the RIF group compared with the control group (all P < 0.05). However, the percentage of T, regulatory T (Tregs), and Tfh2 cells, as well as early inhibitory NK cells, was significantly lower in the RIF group compared with the control group (all P < 0.05). Following logistics regression analysis, Treg, Tfh17, and early inhibitory NK cells exhibited significant differences between the two groups. Combination diagnosis using these 3 biomarkers had a higher area under the curve of 0.900 (95% confidence interval: 0.808-0.992, P < 0.001) in the RIF group compared with that in the control group. Conclusion: T, Tregs, Tfh1, Tfh2, Tfh17, NK cells, and early inhibitory NK cells may play important regulatory roles in embryo implantation. The combination of 3 molecular markers (Treg, Tfh17, and early inhibitory NK cells) could provide a high diagnostic value for women with RIF, thus providing novel potential biomarkers for RIF in ART. The present findings could provide a reference either for the clinical treatment of patients with RIF or for future large, well-designed studies.

An exploratory analysis of γ-synuclein expression in endometrioid endometrial cancer.

OBJECTIVE: This study aims to investigate the expression of γ-synuclein in endometrioid endometrial carcinoma and assess if the γ-synuclein expression correlates with the aggression of the tumour and its prognostic value in endometrioid endometrial carcinoma. DESIGN: This retrospective study evaluated (60) specimens of the primary untreated endometrioid endometrial carcinoma and (12) normal endometrium tissues, and the expression of γ-synuclein was checked by immunohistochemistry. The correlation between γ-synuclein expression and the clinicopathological features of patients with endometrioid endometrial carcinoma was analysed, and SPSS V.13.0 software was used for statistical analysis. RESULTS: The expression of γ-synuclein was positive in 48.3% (29/60) endometrioid endometrial carcinomas compared with the control group, and the difference was significant (p=0.001). The expression level of γ-synuclein in endometrioid endometrial carcinoma was closely associated with FIGO (International Federation of Gynecology and Obstetrics) stages, the depth of myometrial invasion and lymph nodes metastases (p<0.05), but not correlated with the histopathological grades, the patient's age and the expression of ER (estrogen receptor) and PR (progesterone receptor) (p>0.05). In univariate and multivariate analyses, the γ-synuclein expression was significantly associated with a shorter overall survival (95% CI 1.429 to 101.892, p=0.020). CONCLUSIONS: This study suggests that the expression of γ-synuclein is expected to be a useful marker for endometrioid endometrial carcinoma invasion, metastasis and prognosis in endometrioid endometrial carcinoma.