Cholesterol Oxidation Products: Potential Adverse Effect and Prevention of Their Production in Foods.

Cholesterol oxidation products (COPs) are a group of substances formed during food processing. COPs in diet is a health concern because they may affect human health in association with the risk of various diseases including atherosclerosis, Alzheimer's disease, age-related macular degeneration, diabetes, and chronic gastrointestinal inflammatory colitis. Production of COPs in foods can be affected by many factors such as temperature, pH, light, oxygen, water, carbohydrates, fatty acids, proteins, and metal cations. The key issue is preventing its generation in foods. Some COPs can also be produced in vivo by both nonenzymatic and enzymatic-catalyzed oxidation reactions. Currently, a number of natural antioxidants such as catechins, flavonoids, and other polyphenols have been proven to inhibit the generation of COPs. In addition, measures taken during food processing can also minimize the production of COPs, such as the Maillard reaction and marinating food with plant polyphenol-rich seasonings. In conclusion, a comprehensive approach encompassing the suppression on COPs generation and implementation of processing measures is imperative to safeguard human health against the production of COPs in the food chain.

Non-hypothetical projection pursuit regression for the prediction of hydration heat of Portland-cement-based cementitious system.

In this study, the non-hypothetical projection pursuit regression (NH-PPR) is proposed. The proposed NH-PPR model can predict the hydration heat based on the four cement phases, FA, SL, cement fineness and hydration time. The NH-PPR model is proposed by using the multiple layer iteration method and the non-hypothetical and non-parametric ridge functions to enhance accuracy and solve the problems caused by the parameter selection and the subjective hypothesis. The modeling data set is applied to train model, the testing data set is regressed and fitted into the model, and then the obtained results are compared with the BP model. To further validate the proposed model, another published data set is used to obtain a higher degree of confidence in the prediction. It is shown that the proposed model obtains the better accuracy, stability and versatility, and avoids the parameter selection and subjective hypothesis.

Effect of Gut Microbiota on Blood Cholesterol: A Review on Mechanisms.

The gut microbiota serves as a pivotal mediator between diet and human health. Emerging evidence has shown that the gut microbiota may play an important role in cholesterol metabolism. In this review, we delve into five possible mechanisms by which the gut microbiota may influence cholesterol metabolism: (1) the gut microbiota changes the ratio of free bile acids to conjugated bile acids, with the former being eliminated into feces and the latter being reabsorbed back into the liver; (2) the gut microbiota can ferment dietary fiber to produce short-chain fatty acids (SCFAs) which are absorbed and reach the liver where SCFAs inhibit cholesterol synthesis; (3) the gut microbiota can regulate the expression of some genes related to cholesterol metabolism through their metabolites; (4) the gut microbiota can convert cholesterol to coprostanol, with the latter having a very low absorption rate; and (5) the gut microbiota could reduce blood cholesterol by inhibiting the production of lipopolysaccharides (LPS), which increases cholesterol synthesis and raises blood cholesterol. In addition, this review will explore the natural constituents in foods with potential roles in cholesterol regulation, mainly through their interactions with the gut microbiota. These include polysaccharides, polyphenolic entities, polyunsaturated fatty acids, phytosterols, and dicaffeoylquinic acid. These findings will provide a scientific foundation for targeting hypercholesterolemia and cardiovascular diseases through the modulation of the gut microbiota.