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DNA methylation is an important molecular modification that plays a key role in the expression of cancer genes. Evaluation of epigenetic changes, hypomethylation and hypermethylation, in specific genes are applied for cancer diagnosis. Numerous studies have concentrated on describing DNA methylation patterns as biomarkers for cancer diagnosis monitoring and predicting response to cancer therapy. Various techniques for detecting DNA methylation status in cancers are based on sodium bisulfite treatment. According to the application of these methods in research and clinical studies, they have a number of advantages and disadvantages. The current review highlights sodium bisulfite treatment-based techniques, as well as, the advantages, drawbacks, and applications of these methods in the evaluation of human cancers., (© 2024. The Author(s).)

Background: The purpose of this study is to investigate the use of radiomics and deep features obtained from multiparametric magnetic resonance imaging (mpMRI) for grading prostate cancer. We propose a novel approach called multi-flavored feature extraction or tensor, which combines four mpMRI images using eight different fusion techniques to create 52 images or datasets for each patient. We evaluate the effectiveness of this approach in grading prostate cancer and compare it to traditional methods., Methods: We used the PROSTATEx-2 dataset consisting of 111 patients' images from T2W-transverse, T2W-sagittal, DWI, and ADC images. We used eight fusion techniques to merge T2W, DWI, and ADC images, namely Laplacian Pyramid, Ratio of the low-pass pyramid, Discrete Wavelet Transform, Dual-Tree Complex Wavelet Transform, Curvelet Transform, Wavelet Fusion, Weighted Fusion, and Principal Component Analysis. Prostate cancer images were manually segmented, and radiomics features were extracted using the Pyradiomics library in Python. We also used an Autoencoder for deep feature extraction. We used five different feature sets to train the classifiers: all radiomics features, all deep features, radiomics features linked with PCA, deep features linked with PCA, and a combination of radiomics and deep features. We processed the data, including balancing, standardization, PCA, correlation, and Least Absolute Shrinkage and Selection Operator (LASSO) regression. Finally, we used nine classifiers to classify different Gleason grades., Results: Our results show that the SVM classifier with deep features linked with PCA achieved the most promising results, with an AUC of 0.94 and a balanced accuracy of 0.79. Logistic regression performed best when using only the deep features, with an AUC of 0.93 and balanced accuracy of 0.76. Gaussian Naive Bayes had lower performance compared to other classifiers, while KNN achieved high performance using deep features linked with PCA. Random Forest performed well with the combination of deep features and radiomics features, achieving an AUC of 0.94 and balanced accuracy of 0.76. The Voting classifiers showed higher performance when using only the deep features, with Voting 2 achieving the highest performance, with an AUC of 0.95 and balanced accuracy of 0.78., Conclusion: Our study concludes that the proposed multi-flavored feature extraction or tensor approach using radiomics and deep features can be an effective method for grading prostate cancer. Our findings suggest that deep features may be more effective than radiomics features alone in accurately classifying prostate cancer., (© 2023. The Author(s).)

Background: Unhealthy dietary patterns are the most important modifiable risk factors for obesity and overweight. This study aimed to examine the relationship between Dietary Phytochemical Index (DPI) and resting metabolic rate (RMR), mediated by inflammatory factors, in overweight and obese women., Methods: A total of 404 women, aged 18-48 years, were included in the cross-sectional study. DPI was calculated using the 147-item food frequency questionnaire (FFQ). Anthropometric measurements, RMR, and blood biomarkers were assessed using standard protocols., Results: There was marginally significant association between adherence to DPI and RMR status in the crude model (OR = 1.41, 95% CI 0.94-2.11, P = 0.09). After adjusting for potential confounders, a significant association was seen between the DPI and increase RMR.per.kg (OR = 2.77, 95% CI 0.98-7.82, P = 0.05). Our results indicated that plasminogen activator inhibitor-1 (PAI-1), transforming growth factor (TGF-β), and monocyte chemoattractant protein-1 (MCP-1) had a mediatory effect on the association between RMR and DPI (P > 0.05). Indeed, it was shown that, PAI-1, TGF-β, and MCP-1 destroyed the significance of this association and could be considered as mediating markers. However, no mediating effect was observed for high-sensitivity C reactive protein (hs-CRP)., Conclusions: Adherence to DPI can improve the RMR by reducing levels of inflammatory markers, and may be considered as a treatment for obesity. However, more long-term studies are recommended., (© 2022. The Author(s).)

Objective: Low resting metabolic rate (RMR), as a risk factor for weight gain and obesity, can be influenced by many factors. Empirical research has confirmed the role of appetite and related hormones in obesity and energy intake. This study aimed to investigate the relationship between appetite and related hormones in overweight or obese Iranian women with normal and hypo RMR., Methods: This case-control study was conducted on 42 Iranian adult women (21 cases, and 21 controls), aged 18-48 years. An impedance body analyzer was used to obtain the body composition and an indirect calorimeter was used to assess the RMR. The Flint questionnaire was used to assess appetite, dietary intake, and physical activity were assessed by FFQ and IPAQ questionnaires respectively, and ELISA kits were used to assess leptin, ghrelin, and insulin hormones., Results: The results of the study demonstrated a negative association between ghrelin hormone level (β = -0.34, 95%CI = -61.70,-3.86, P-value = 0.027) and RMR, and a positive association between insulin hormone level (β = 0.48, 95%CI = 9.38-34.35, P-value = 0.001) and RMR. Also, results of the appetite questionnaire showed that, in general, both appetite (β = 0.32, 95%CI = -0.10-2.99 P-value = 0.044) and hunger variable (β = 0.30, 95%CI = 0.04-5.87, P-value = 0.047) have a positive association with RMR. There was no significant association between leptin levels and RMR., Conclusion: It is evident that appetite and related hormones have a potential role in promoting a normal RMR., (© 2022. The Author(s).)

Objective: Recent studies have shown that increased dietary inflammatory index (DII) score or consumption of pro-inflammatory foods can lead to increased waist circumference (WC) as well as triglyceride (TG) concentrations in obese people. The purpose of this study is to examine the association between DII and hypertriglyceridemic waist circumference phenotype (HTGWCP) in women with overweight and obesity., Results: There was a positive significant correlation between DII and HTGWCPs. In other words, with an increase in DII score or higher consumption of pro-inflammatory foods, the odds of having abnormal phenotypes including; enlarged waist normal TG (EWNT) (OR = 2.85, 95% CI 1.02 to 7.98, P for trend = 0.04), normal waist enlarged TG (NWET) (OR = 5.85, 95% CI 1.1 to 31.11, P for trend = 0.03) and enlarged waist enlarged TG (EWET) (OR = 3.13, 95% CI 0.95 to 10.27, P for trend = 0.05) increase compared to normal waist normal TG (NWNT) phenotype. In conclusion; increasing DII scores can increase abnormal phenotypes and therefore may increase WC and TG levels in overweight and obese women., (© 2021. The Author(s).)

Objective: Equivocal association the contribution of 25-hydroxyvitamin D (25(OH)D) and the well-accepted role of vitamin D-binding protein (VDBP) on bioavailability of 25(OH)D or its independent roles, has led to possible association of the VDBP in glucose metabolism. This study was conducted to evaluate the relationships among 25(OH)D, VDBP, glucose/insulin metabolism and homeostatic model assessment (HOMA-IR). Blood samples were collected from 236 obese and overweight women. VDBP and 25(OH)D levels, and biochemical parameters were measured using an enzyme-linked immunosorbent assay (ELISA). An impedance fat analyzer was utilized to acquire the body composition., Results: Using the multivariate linear regression, a reverse relationship was observed between VDBP and (HOMA-IR), such that women with higher VDBP displayed lower insulin resistance. The relationship was independent of age, body mass index, standardized energy intake and physical activity (p = 0.00). No significant relationship between 25(OH)D levels, FBS, body composition or insulin resistance were observed (p > 0.2). Current study observed that higher level of VDBP may be associated with lower levels of insulin and HOMA-IR, thus the evaluation of VDBP in diverse population groups seems to have significant clinical value in evaluating the prevalence of DM or early stage of glucose intolerance.