Calcium homeostasis and endometriosis: A Mendelian randomization study.

Background: Previous observational studies have investigated the correlation between calcium homeostasis modulator levels and endometriosis risk. Yet, the genetic association between body calcium homeostasis and endometriosis risk remains to be elucidated. Methods: Four tiers of Mendelian randomization (MR) analysis were conducted, as follows: (1) single univariate MR and (2) multivariate MR to evaluate the correlation between calcium homeostasis regulators and endometriosis; (3) inverse MR to probe the influence of endometriosis on body calcium homeostasis; (4) two-sample MR to scrutinize the connection between calcium levels and endometriosis categories. Results: The two-sample MR analysis unveiled a robust positive correlation between genetically inferred calcium levels and endometriosis risk (IVW: OR = 1.15, 95 % CI: 1.02-1.29, p = 0.018). The MVMR analysis corroborated that the positive correlation of calcium levels with endometriosis persisted after adjusting for 25(OH)D and PTH. The inverse MR analysis disclosed a significant association between endometriosis and 25(OH)D (ß = 0.01, 95 % CI: 0.00-0.02, p = 0.007) and calcium (ß = 0.02, 95 % CI: 0.00-0.04, p = 0.035). The two-sample MR analysis further demonstrated that calcium levels were positively linked solely to endometriosis of uterus (i.e. adenomyosis, IVW: OR = 1.23, 95 % CI: 1.01-1.49, p = 0.038), with no evidence of a influence on other endometriosis categories. Conclusions: This study, employing various types of MR, offers some genetic evidence for the relationship between calcium homeostasis and endometriosis, augmenting the current comprehension of the complex association between the two and suggesting that calcium levels are a risk factor for endometriosis. These findings provide a unique genetic perspective that may spur further investigation and may inform future strategies for managing patients with endometriosis.

Thyroid Cancer Central Lymph Node Metastasis Risk Stratification Based on Homogeneous Positioning Deep Learning.

Due to the absence of definitive diagnostic criteria, there remains a lack of consensus regarding the risk assessment of central lymph node metastasis (CLNM) and the necessity for prophylactic lymph node surgery in ultrasound-diagnosed thyroid cancer. The localization of thyroid nodules is a recognized predictor of CLNM; however, quantifying this relationship is challenging due to variable measurements. In this study, we developed a differential isomorphism-based alignment method combined with a graph transformer to accurately extract localization and morphological information of thyroid nodules, thereby predicting CLNM. We collected 88,796 ultrasound images from 48,969 patients who underwent central lymph node (CLN) surgery and utilized these images to train our predictive model, ACE-Net. Furthermore, we employed an interpretable methodology to explore the factors influencing CLNM and generated a risk heatmap to visually represent the distribution of CLNM risk across different thyroid regions. ACE-Net demonstrated superior performance in 6 external multicenter tests (AUC = 0.826), surpassing the predictive accuracy of human experts (accuracy = 0.561). The risk heatmap enabled the identification of high-risk areas for CLNM, likely correlating with lymphatic metastatic pathways. Additionally, it was observed that the likelihood of metastasis exceeded 80% when the nodal margin's minimum distance from the thyroid capsule was less than 1.25 mm. ACE-Net's capacity to effectively predict CLNM and provide interpretable disease-related insights can importantly reduce unnecessary lymph node dissections by 37.9%, without missing positive cases, thus offering a valuable tool for clinical decision-making.

Inhibition of DNA Topoisomerase Ι by Flavonoids and Polyacetylenes Isolated from Bidens pilosa L.

Human DNA topoisomerase I (Topo I) is an essential enzyme in regulating DNA supercoiling during transcription and replication, and it is an important therapeutic target for anti-tumor agents. Bidens pilosa L. is a medicinal herb that is used as a folk medicine for cancers in China. A new flavonoid (1) and a new polyacetylene (20), along with eighteen flavonoids (2-19) and nine polyacetylenes (21-29), were isolated and identified from the methanol extract of the whole plant of B. pilosa, and some of the compounds (4, 5, 6 and 7) exhibited potent cytotoxicity against a panel of five human cancer cell lines. The DNA relaxation assay revealed that some flavonoids and polyacetylenes exerted inhibitory activities on human DNA Topo I, among them compounds 1, 2, 5, 6, 7, 8, 15, 19, 20, 22, and 24 were the most active ones, with IC50 values of 393.5, 328.98, 145.57, 239.27, 224.38, 189.84, 89.91, 47.5, 301.32, 178.03, and 218.27 µM, respectively. The structure-activity analysis of flavonoids was performed according to the results from the Topo I inhibition assay. The DNA content analysis revealed that 5, 6, and 7 potently arrested cell cycle at the G1/S and G2/M phases in human colon cancer cell DLD-1 depending on the concentration of the inhibitors. The levels of protein expression related to the G1/S and G2/M cell cycle checkpoints were in accordance with the results from the DNA content analysis. These findings suggest that flavonoids are one of the key active ingredients accounting for the anti-tumor effect of B. pilosa.

[Expressions of zinc homeostasis proteins, GPR39 and ANO1 mRNA in the sperm of asthenozoospermia patients and their clinical significance].

OBJECTIVE: To explore the expressions of zinc homeostasis-related proteins, G protein-coupled receptor 39 (GPR39) and ANO1 mRNA in the sperm of patients with asthenozoospermia (AS), and analyze their correlation with sperm motility. METHODS: We collected semen samples from 82 male subjects with PR+NP < 40%, PR < 32% and sperm concentration > 15×106/ml (the AS group, n = 40) or PR+NP ≥ 40%, PR ≥ 32% and sperm concentration > 15×106/ml (the normal control group, n = 42). We analyzed the routine semen parameters and measured the zinc content in the seminal plasma using the computer-assisted sperm analysis system, detected the expressions of zinc transporters (ZIP13, ZIP8 and ZNT10), metallothioneins (MT1G, MT1 and MTF), GPR39, and calcium-dependent chloride channel protein (ANO1) in the sperm by real-time quantitative PCR (RT qPCR), examined free zinc distribution in the sperm by laser confocal microscopy, and determined the expressions of GPR39 and MT1 proteins in the sperm by immunofluorescence staining, followed by Spearman rank correlation analysis of their correlation with semen parameters. RESULTS: There was no statistically significant difference in the zinc concentration in the seminal plasma between the AS and normal control groups (P>0.05). Compared with the controls, the AS patients showed a significantly reduced free zinc level (P<0.05), relative expressions of MT1G, MTF, ZIP13, GPR39 and ANO1 mRNA (P<0.05), and that of the GPR39 protein in the AS group (P<0.05). No statistically significant differences were observed in the relative expression levels of ZIP8, ZNT10 and MT1 mRNA between the two groups (P>0.05). The relative expression levels of GPR39, ANO1, MT1G and MTF mRNA were positively correlated with sperm motility and the percentage of progressively motile sperm (P<0.05). CONCLUSION: The expressions of zinc homeostasis proteins (MT1G, MTF and ZIP13), GPR39 and ANO1 mRNA are downregulated in the sperm of asthenozoospermia patients, and positively correlated with sperm motility.

CMTM6: A Critical Prognostic Indicator in Non-Small Cell Lung Cancer.

While CKLF-like MARVEL transmembrane domain containing 6 (CMTM6)'s role in stabilizing PD-L1 and immune evasion within tumors is established, its expression in lung cancer tissue and adjacent macrophages remains uncertain. The study aimed to elucidate this ambiguity by investigating CMTM6's role in non-small cell lung cancer (NSCLC) prognosis. Employing immunohistochemical staining on 141 NSCLC and 110 adjacent normal lung tissue samples, CMTM6 expression was evaluated using the HSCORE system. Interestingly, NSCLC exhibited significantly higher CMTM6 levels (161.04±86.60) compared to normal tissues (71.20±45.10) (p < 0.001), detected not only in cancer cells but also in macrophages, lymphocytes, and nearby bronchial epithelial cells. Stratifying patients by CMTM6 levels unveiled a correlation between heightened expression and poorer overall survival (p = 0.003), alongside a link to tumor-infiltrating lymphocytes (TIL) (p = 0.037), especially in cases with increased TIL. Multivariate analysis identified CMTM6 as an independent predictor of overall survival (p = 0.009), implying that elevated CMTM6 expression in NSCLC might signify an adverse prognostic marker for patient outcomes.

Enhancing the fairness of AI prediction models by Quasi-Pareto improvement among heterogeneous thyroid nodule population.

Artificial Intelligence (AI) models for medical diagnosis often face challenges of generalizability and fairness. We highlighted the algorithmic unfairness in a large thyroid ultrasound dataset with significant diagnostic performance disparities across subgroups linked causally to sample size imbalances. To address this, we introduced the Quasi-Pareto Improvement (QPI) approach and a deep learning implementation (QP-Net) combining multi-task learning and domain adaptation to improve model performance among disadvantaged subgroups without compromising overall population performance. On the thyroid ultrasound dataset, our method significantly mitigated the area under curve (AUC) disparity for three less-prevalent subgroups by 0.213, 0.112, and 0.173 while maintaining the AUC for dominant subgroups; we also further confirmed the generalizability of our approach on two public datasets: the ISIC2019 skin disease dataset and the CheXpert chest radiograph dataset. Here we show the QPI approach to be widely applicable in promoting AI for equitable healthcare outcomes.

Tumor immunity: A brief overview of tumor­infiltrating immune cells and research advances into tumor­infiltrating lymphocytes in gynecological malignancies (Review).

Tumor immunity is a promising topic in the area of cancer therapy. The 'soil' function of the tumor microenvironment (TME) for tumor growth has attracted wide attention from scientists. Tumor-infiltrating immune cells in the TME, especially the tumor-infiltrating lymphocytes (TILs), serve a key role in cancer. Firstly, relevant literature was searched in the PubMed and Web of Science databases with the following key words: 'Tumor microenvironment'; 'TME'; 'tumor-infiltrating immunity cells'; 'gynecologic malignancies'; 'the adoptive cell therapy (ACT) of TILs'; and 'TIL-ACT' (https://pubmed.ncbi.nlm.nih.gov/). According to the title and abstract of the articles, relevant items were screened out in the preliminary screening. The most relevant selected items were of two types: All kinds of tumor-infiltrating immune cells; and advanced research on TILs in gynecological malignancies. The results showed that the subsets of TILs were various and complex, while each subpopulation influenced each other and their effects on tumor prognosis were diverse. Moreover, the related research and clinical trials on TILs were mostly concentrated in melanoma and breast cancer, but relatively few focused on gynecological tumors. In conclusion, the present review summarized the biological classification of TILs and the mechanisms of their involvement in the regulation of the immune microenvironment, and subsequently analyzed the development of tumor immunotherapy for TILs. Collectively, the present review provides ideas for the current treatment dilemma of gynecological tumor immune checkpoints, such as adverse reactions, safety, personal specificity and efficacy.

Convolutional neural networks combined with classification algorithms for the diagnosis of periodontitis.

OBJECTIVES: We aim to develop a deep learning model based on a convolutional neural network (CNN) combined with a classification algorithm (CA) to assist dentists in quickly and accurately diagnosing the stage of periodontitis. MATERIALS AND METHODS: Periapical radiographs (PERs) and clinical data were collected. The CNNs including Alexnet, VGG16, and ResNet18 were trained on PER to establish the PER-CNN models for no periodontal bone loss (PBL) and PBL. The CAs including random forest (RF), support vector machine (SVM), naive Bayes (NB), logistic regression (LR), and k-nearest neighbor (KNN) were added to the PER-CNN model for control, stage I, stage II and stage III/IV periodontitis. Heat map was produced using a gradient-weighted class activation mapping method to visualize the regions of interest of the PER-Alexnet model. Clustering analysis was performed based on the ten PER-CNN scores and the clinical characteristics. RESULTS: The accuracy of the PER-Alexnet and PER-VGG16 models with the higher performance was 0.872 and 0.853, respectively. The accuracy of the PER-Alexnet + RF model with the highest performance for control, stage I, stage II and stage III/IV was 0.968, 0.960, 0.835 and 0.842, respectively. Heat map showed that the regions of interest predicted by the model were periodontitis bone lesions. We found that age and smoking were significantly related to periodontitis based on the PER-Alexnet scores. CONCLUSION: The PER-Alexnet + RF model has reached high performance for whole-case periodontal diagnosis. The CNN models combined with CA can assist dentists in quickly and accurately diagnosing the stage of periodontitis.

Liver indicators affecting the relationship between BMI and hypertension in type 2 diabetes: a mediation analysis.

BACKGROUND: Body mass index (BMI) is an important risk factor for hypertension in diabetic patients. However, the underlying mechanisms remain poorly understood. Although liver-derived biological intermediates may play irreplaceable roles in the pathophysiology of diabetes, few studies have explored them in the association between BMI and hypertension in diabetes. OBJECTIVE: To investigate the role of liver enzymes in mediating the relationship between BIM exposure and hypertension in type 2 diabetes mellitus (T2DM). METHODS: We included a total of 1765 participants from the China National Diabetic Chronic Complications Study Cohort. Associations between liver enzymes and hypertension were estimated using multivariable regression models. The function of liver indicators in the relationship between BMI and hypertension was assessed using mediation analysis. Mediation analysis was conducted, taking into account age, diabetes duration, current smoking, fasting plasma glucose level, glycated hemoglobin, anti-diabetic therapy, and family history of diseases, including diabetes, hypertension, obesity, and hyperlipidemia. RESULTS: For men, the association of BMI with hypertension was partially mediated by alanine aminotransferase (ALT), with a proportion of mediation was 68.67%, by aspartate aminotransferase (AST) was 27.02%, and by γ-glutamyltransferase (GGT) was 38.58%, by AST/ALT was 63.35%; for women, the proportion mediated by ALT was 36.93%, and by AST was 37.47%, and GGT was 44.60%, and AST/ALT was 43.73% for BMI (all P < 0.05). CONCLUSION: The effect of BMI on hypertension is partly mediated by liver indicators (ALT, AST, GGT, and AST/ALT) in diabetic patients. Our results may provide opportunities to identify new targets for hypertension interventions.

The Effect of Diabetes Management Shared Care Clinic on Glycated Hemoglobin A1c Compliance and Self-Management Abilities in Patients with Type 2 Diabetes Mellitus.

Objective: We aim to evaluate the impact of diabetes management shared care clinic (DMSCC) on glycated hemoglobin A1c (HbA1c) compliance and self-management abilities in patients with type 2 diabetes mellitus (T2DM). Methods: This study was a prospective cohort study of patients with T2DM participating in the DMSCC. At baseline and after management, the HbA1c levels were measured, the HbA1c compliance rate were calculated, and the Summary of Diabetes Self-Care Activities-6 (SDSCA-6), Diabetes Empowerment Scale-DAWN Short Form (DES-DSF), and Problem Areas in Diabetes Scale-Five-item Short Form (PAID-5) were completed. These pre- and post-management data were compared. Results: A total of 124 eligible patients were enrolled. After the diabetes management of DMSCC, the average HbA1c decreased and the HbA1c compliance rate increased significantly (P < 0.01). SDSCA-6 showed significant improvement in physical activity, glycemic monitoring, smoking (P < 0.01), and taking medication (P < 0.05). DES-DSF suggested a greater willingness to try to effectively treat diabetes (P < 0.05). PAID-5 indicated significant improvement in diabetes-related emotional distress. Conclusion: DMSCC can help patients with T2DM reduce HbA1c, increase HbA1c compliance, improve diabetes self-management behaviors, empowerment, and diabetes-related emotional distress and serve as an effective exploration and practice of diabetes self-management education and support.

Mitochondrial genome nucleotide substitution pattern between domesticated silkmoth, Bombyx mori, and its wild ancestors, Chinese Bombyx mandarina and Japanese Bombyx mandarina

Bombyx mori and Bombyx mandarina are morphologically and physiologically similar. In this study, we compared the nucleotide variations in the complete mitochondrial (mt) genomes between the domesticated silkmoth, B. mori, and its wild ancestors, Chinese B. mandarina (ChBm) and Japanese B. mandarina (JaBm). The sequence divergence and transition mutation ratio between B. mori and ChBm are significantly smaller than those observed between B. mori and JaBm. The preference of transition by DNA strands between B. mori and ChBm is consistent with that between B. mori and JaBm, however, the regional variation in nucleotide substitution rate shows a different feature. These results suggest that the ChBm mt genome is not undergoing the same evolutionary process as JaBm, providing evidence for selection on mtDNA. Moreover, investigation of the nucleotide sequence divergence in the A+T-rich region of Bombyx mt genomes also provides evidence for the assumption that the A+T-rich region might not be the fastest evolving region of the mtDNA of insects.