Efficiency of the Adjusted Binary Classification (ABC) Approach in Osteometric Sex Estimation: A Comparative Study of Different Linear Machine Learning Algorithms and Training Sample Sizes.

The adjusted binary classification (ABC) approach was proposed to assure that the binary classification model reaches a particular accuracy level. The present study evaluated the ABC for osteometric sex classification using multiple machine learning (ML) techniques: linear discriminant analysis (LDA), boosted generalized linear model (GLMB), support vector machine (SVM), and logistic regression (LR). We used 13 femoral measurements of 300 individuals from a modern Turkish population sample and split data into two sets: training (n = 240) and testing (n = 60). Then, the five best-performing measurements were selected for training univariate models, while pools of these variables were used for the multivariable models. ML classifier type did not affect the performance of unadjusted models. The accuracy of univariate models was 82−87%, while that of multivariate models was 89−90%. After applying ABC to the crossvalidation set, the accuracy and the positive and negative predictive values for uni- and multivariate models were ≥95%. Sex could be estimated for 28−75% of individuals using univariate models but with an obvious sexing bias, likely caused by different degrees of sexual dimorphism and between-group overlap. However, using multivariate models, we minimized the bias and properly classified 81−87% of individuals. A similar performance was also noted in the testing sample (except for FEB), with accuracies of 96−100%, and a proportion of classified individuals between 30% and 82% in univariate models, and between 90% and 91% in multivariate models. When considering different training sample sizes, we demonstrated that LR was the most sensitive with limited sample sizes (n < 150), while GLMB was the most stable classifier.

Cardiac stem cells: Current knowledge and future prospects.

Regenerative medicine is the field concerned with the repair and restoration of the integrity of damaged human tissues as well as whole organs. Since the inception of the field several decades ago, regenerative medicine therapies, namely stem cells, have received significant attention in preclinical studies and clinical trials. Apart from their known potential for differentiation into the various body cells, stem cells enhance the organ's intrinsic regenerative capacity by altering its environment, whether by exogenous injection or introducing their products that modulate endogenous stem cell function and fate for the sake of regeneration. Recently, research in cardiology has highlighted the evidence for the existence of cardiac stem and progenitor cells (CSCs/CPCs). The global burden of cardiovascular diseases' morbidity and mortality has demanded an in-depth understanding of the biology of CSCs/CPCs aiming at improving the outcome for an innovative therapeutic strategy. This review will discuss the nature of each of the CSCs/CPCs, their environment, their interplay with other cells, and their metabolism. In addition, important issues are tackled concerning the potency of CSCs/CPCs in relation to their secretome for mediating the ability to influence other cells. Moreover, the review will throw the light on the clinical trials and the preclinical studies using CSCs/CPCs and combined therapy for cardiac regeneration. Finally, the novel role of nanotechnology in cardiac regeneration will be explored.

The potential implications of estrogenic and antioxidant-dependent activities of high doses of methyl paraben on MCF7 breast cancer cells.

Methyl paraben (MP) is an endocrine-disrupting compound that possesses estrogenic properties and contributes to an aberrant burden of estrogen signaling in the human breast and subsequently increasing the risks for the development of breast cancer. The exact exposure, as well as the safe concentrations, are variable among daily products. The present study addresses the effects of exposure to escalated concentrations of MP on the proliferation of MCF-7 breast cancer cells in addition to exploring its other mechanisms of action. The study involved exposure of cultured MCF-7 breast cancer cells to seven MP concentrations, ranging from 40 to 800 µM for 5 days. Cell viability, apoptosis, and proliferation were respectively assessed using crystal violet test, flow cytometric analysis, and quantitative real-time polymerase chain reaction for Ki-67 expression. The estradiol (E2) secretion and oxidative stress were also assessed and analyzed in correlation to MP's proliferation and cytotoxicity potentials. The results showed that the maximum proliferative concentration of MP was 800 µM. At a concentration of 40 µM and higher, MP induced increased expression of Ki-67, denoting enhanced proliferation of the cells in monolayer culture. A positive correlation between the detrimental oxidative stress effect of MP's tested concentrations, cell proliferation, and viability was demonstrated (p < 0.05). Our results indicated that MP at high doses induced sustained cell proliferation due to E2 secretion as well as its antioxidant activity. Accordingly, it was concluded that high and unpredicted exposure to MP might carry a carcinogenic hazard on estrogen receptor-positive breast cancer cells.