How wine polyphenols can fight Alzheimer disease progression: towards a molecular explanation

(-)-Epigallocatechin-3-gallate, a Polyphenol from Green Tea, Regulates the Liquid-Liquid Phase Separation of Alzheimer's-Related Protein Tau

The microtubule-associated protein tau is involved in Alzheimer's disease and other tauopathies. Recently, tau has been shown to undergo liquid-liquid phase separation (LLPS), which is implicated in the physiological function and pathological aggregation of tau. In this report, we demonstrate that the green tea polyphenol (-)-epigallocatechin-3-gallate (EGCG) promotes the formation of liquid tau droplets at neutral pH by creating a network of hydrophobic interactions and hydrogen bonds, mainly with the proline-rich domain of tau. We further show that EGCG oxidation, tau phosphorylation, and the chemical structure of the polyphenol influence the efficacy of EGCG in facilitating tau LLPS. Complementary to the inhibitory activity of EGCG in tau fibrillization, our findings provide novel insights into the biological activity of EGCG and offer new clues for future studies on the molecular mechanism by which EGCG alleviates neurodegenerative diseases.

Application of artificial neural network model in diagnosis of Alzheimer's disease

Background

Alzheimer’s disease has become a public health crisis globally due to its increasing incidence. The purpose of this study was to establish an early warning model using artificial neural network (ANN) for early diagnosis of AD and to explore early sensitive markers for AD.

Methods

A population based nested case-control study design was used. 89 new AD cases with good compliance who were willing to provide urine and blood specimen were selected from the cohort of 2482 community-dwelling elderly aged 60 years and over from 2013 to 2016. For each case, two controls living nearby were identified. Biomarkers for AD in urine and blood, neuropsychological functions and epidemiological parameters were included to analyze potential risk factors of AD. Compared with logistic regression, k-Nearest Neighbor (kNN) and support vector machine (SVM) model, back-propagation neural network of three-layer topology structures was applied to develop the early warning model. The performance of all models were measured by sensitivity, specificity, accuracy, positive prognostic value (PPV), negative prognostic value (NPV), the area under curve (AUC), and were validated using bootstrap resampling.

Results

The average age of AD group was about 5 years older than the non-AD controls (P < 0.001). Patients with AD included a significantly larger proportion of subjects with family history of dementia, compared with non-AD group. After adjusting for age and gender, the concentrations of urinary AD7c-NTP and aluminum in blood were significantly higher in AD group than non-AD group (2.01 ± 1.06 vs 1.03 ± 0.43, 1.74 ± 0.62 vs 1.24 ± 0.41 respectively), but the concentration of Selenium in AD group (2.26 ± 0.59) was significantly lower than that in non-AD group (2.61 ± 1.07). All the models were established using 18 variables that were significantly different between AD patients and controls as independent variables. The ANN model outperformed the other classifiers. The AUC for this ANN was 0.897 and the model obtained the accuracy of 92.13%, the sensitivity of 87.28% and the specificity of 94.74% on the average.

Conclusions

Increased risk of AD may be associated with higher age among senior citizens in urban communities. Urinary AD7c-NTP is clinically valuable for the early diagnosis. The established ANN model obtained a high accuracy and diagnostic efficiency, which could be a low-cost practicable tool for the screening and diagnosis of AD for citizens.

Inhibition of the Exoglucanase Cel7A by a Douglas-Fir-Condensed Tannin

Douglas-fir forestry residues are a potential feedstock for saccharification-based biofuels, and condensed tannins are expected to make up ∼3% of the dry mass of this feedstock. Condensed tannins are well-known for their ability to interact with proteins and can bind and inhibit cellulase enzymes used in saccharification. In this study, we use molecular docking and classical molecular dynamics simulations to investigate how a characterized condensed tannin from Douglas-fir bark binds to the exoglucanase Cel7A from Trichoderma reesei. Through looking at the "occupancy" and "residency" of specific amino acid residue-tannin interactions, we find that the binding sites are characterized by many simultaneous tannin-enzyme interactions with the strongest occurring on the catalytic module as opposed to the carbohydrate-binding module. The simulations indicate that tannin inhibition can result from binding at or near the catalytic tunnel's entrance and exit. The analyzed tannin further prefers to bind to loops around the catalytic region and has affinity for aromatic and charged amino acid residues. These insights provide direction for the rational design of tannin-resistant cellulases.

Wine Flavonoids in Health and Disease Prevention

Wine, and particularly red wine, is a beverage with a great chemical complexity that is in continuous evolution. Chemically, wine is a hydroalcoholic solution (~78% water) that comprises a wide variety of chemical components, including aldehydes, esters, ketones, lipids, minerals, organic acids, phenolics, soluble proteins, sugars and vitamins. Flavonoids constitute a major group of polyphenolic compounds which are directly associated with the organoleptic and health-promoting properties of red wine. However, due to the insufficient epidemiological and in vivo evidences on this subject, the presence of a high number of variables such as human age, metabolism, the presence of alcohol, the complex wine chemistry, and the wide array of in vivo biological effects of these compounds suggest that only cautious conclusions may be drawn from studies focusing on the direct effect of wine and any specific health issue. Nevertheless, there are several reports on the health protective properties of wine phenolics for several diseases such as cardiovascular diseases, some cancers, obesity, neurodegenerative diseases, diabetes, allergies and osteoporosis. The different interactions that wine flavonoids may have with key biological targets are crucial for some of these health-promoting effects. The interaction between some wine flavonoids and some specific enzymes are one example. The way wine flavonoids may be absorbed and metabolized could interfere with their bioavailability and therefore in their health-promoting effect. Hence, some reports have focused on flavonoids absorption, metabolism, microbiota effect and overall on flavonoids bioavailability. This review summarizes some of these major issues which are directly related to the potential health-promoting effects of wine flavonoids. Reports related to flavonoids and health highlight some relevant scientific information. However, there is still a gap between the knowledge of wine flavonoids bioavailability and their health-promoting effects. More in vivo results as well as studies focused on flavonoid metabolites are still required. Moreover, it is also necessary to better understand how biological interactions (with microbiota and cells, enzymes or general biological systems) could interfere with flavonoid bioavailability.