Controversies and discrepancies in the effect of dietary fat and cholesterol on cardiovascular risk

Rapid classification of whole milk powder and skimmed milk powder by laser-induced breakdown spectroscopy combined with feature processing method and logistic regression

Whole milk powder and skimmed milk powder are suitable for different groups of people due to their differences in composition. Therefore, a rapid classification method for whole milk powder and skimmed milk powder is urgently needed. In this paper, a novel strategy based on laser-induced breakdown spectroscopy (LIBS) and feature processing methods combined with logistic regression (LR) was constructed for the classification of milk powder. A LR classification model based on mini-batch gradient descent (MGD) was employed first. As indicated by the research results, the accuracy of the MGD-LR model for the milk powder samples in the test set is 96.33% and the modeling time is 33.07 s. The modeling efficiency is low and needs to be improved. Principal components analysis (PCA) and mutual information (MI) were used as feature processing methods to reduce the high dimensional LIBS data into fewer features for improving the modeling efficiency of the classification model. The research results indicate that the accuracy of the PCA-MGD-LR model and the MI-MGD-LR model for the test set of milk powder samples was 99.33% and 99.67%, respectively. Compared with MGD-LR model, the modeling efficiency of PCA-MGD-LR and MI-MGD-LR models has increased by 89.7% and 74.8%, respectively. The results fully demonstrate the feasibility of rapid milk powder classification based on LIBS and feature processing methods combined with LR, and it will provide a new technology for the identification and classification of milk powder.

The Potential Role of Nutrition in Overtraining Syndrome: A Narrative Review

Competition between athletes and an increase in sporting knowledge have greatly influenced training methods while increasing the number of them more and more. As a result, the number of athletes who have increased the number and intensity of their workouts while decreasing recovery times is rising. Positive overtraining could be considered a natural and fundamental process when the result is adaptation and improved performance; however, in the absence of adequate recovery, negative overtraining could occur, causing fatigue, maladaptation, and inertia. One of the earliest forms of fatigue is overreaching. It is considered to be an accumulation of training that leads to reduced sports performance, requiring days or weeks to recover. Overreaching, if followed by adequate recovery, can lead to an increase in athletic performance. Nonetheless, if overreaching becomes extreme, combined with additional stressors, it could lead to overtraining syndrome (OTS). OTS, caused by systemic inflammation, leads to central nervous system (CNS) effects, including depressed mood, further inflammation, central fatigue, and ultimately neurohormonal changes. There are therefore not only physiological, biochemical, and immunological but also psychological symptoms or markers that must be considered, independently or together, being intrinsically linked with overtraining, to fully understand OTS. However, to date, there are very few published studies that have analyzed how nutrition in its specific food aspects, if compromised during OTS, can be both etiology and consequence of the syndrome. To date, OTS has not yet been fully studied, and the topic needs further research. The purpose of this narrative review is therefore to study how a correct diet and nutrition can influence OTS in all its aspects, from prevention to treatment.