COVID-19 mortality analysis from soft-data multivariate curve regression and machine learning.

A multiple objective space-time forecasting approach is presented involving cyclical curve log-regression, and multivariate time series spatial residual correlation analysis. Specifically, the mean quadratic loss function is minimized in the framework of trigonometric regression. While, in our subsequent spatial residual correlation analysis, maximization of the likelihood allows us to compute the posterior mode in a Bayesian multivariate time series soft-data framework. The presented approach is applied to the analysis of COVID-19 mortality in the first wave affecting the Spanish Communities, since March 8, 2020 until May 13, 2020. An empirical comparative study with Machine Learning (ML) regression, based on random k-fold cross-validation, and bootstrapping confidence interval and probability density estimation, is carried out. This empirical analysis also investigates the performance of ML regression models in a hard- and soft-data frameworks. The results could be extrapolated to other counts, countries, and posterior COVID-19 waves. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00477-021-02021-0.

Amyloid-ß/Drug Interactions from Computer Simulations and Cell-Based Assays.

Targeting the early oligomers formed by the amyloid-ß (Aß) peptide of 40 and 42 amino acids is considered one promising therapeutic approach for Alzheimer's disease (AD). In vitro experiments and computer simulations are often used in synergy to reveal the modes of interactions of drugs. In this account, we present our contribution to understanding how small molecules bind to Aß40/Aß42 peptides, based either on extensive coarse-grained and all-atom simulations, or a variety of experimental techniques. We conclude by offering several perspectives on the future of this field to design more efficient drugs.

Synthesis and Evaluation of Antimicrobial and Antibiofilm Properties of A-Type Procyanidin Analogues against Resistant Bacteria in Food.

Natural A-type procyanidins have shown very interesting biological activities, such as their proven antiadherence properties against pathogenic bacteria. In order to find the structural features responsible for their activities, we describe herein the design and synthesis of six A-type procyanidin analogues and the evaluation of their antimicrobial and antibiofilm properties against 12 resistant bacteria, both Gram positive and Gram negative, isolated from organic foods. The natural A-type procyanidin A-2, which had known antiadherence activity, was also tested as a reference compound for the comparative studies. Within the series, analogue 4, which had a NO2 group on ring A, showed the highest antimicrobial activity (MIC of 10 µg/mL) and was one of the best molecules at preventing biofilm formation (up to 40% decreases at 100 µg/mL) and disrupting preformed biofilms (up to 40% reductions at 0.1 µg/mL). Structure-activity relationships are also analyzed.

Why Is Research on Amyloid-ß Failing to Give New Drugs for Alzheimer's Disease?

The two hallmarks of Alzheimer's disease (AD) are the presence of neurofibrillary tangles (NFT) made of aggregates of the hyperphosphorylated tau protein and of amyloid plaques composed of amyloid-ß (Aß) peptides, primarily Aß1-40 and Aß1-42. Targeting the production, aggregation, and toxicity of Aß with small molecule drugs or antibodies is an active area of AD research due to the general acceptance of the amyloid cascade hypothesis, but thus far all drugs targeting Aß have failed. From a review of the recent literature and our own experience based on in vitro, in silico, and in vivo studies, we present some reasons to explain this repetitive failure.

Combined experimental and simulation studies suggest a revised mode of action of the anti-Alzheimer disease drug NQ-Trp.

Inhibition of the aggregation of the monomeric peptide ß-amyloid (Aß) into oligomers is a widely studied therapeutic approach in Alzheimer's disease (AD). Many small molecules have been reported to work in this way, including 1,4-naphthoquinon-2-yl-L-tryptophan (NQ-Trp). NQ-Trp has been reported to inhibit aggregation, to rescue cells from Aß toxicity, and showed complete phenotypic recovery in an in vivo AD model. In this work we investigated its molecular mechanism by using a combined approach of experimental and theoretical studies, and obtained converging results. NQ-Trp is a relatively weak inhibitor and the fluorescence data obtained by employing the fluorophore widely used to monitor aggregation into fibrils can be misinterpreted due to the inner filter effect. Simulations and NMR experiments showed that NQ-Trp has no specific "binding site"-type interaction with mono- and dimeric Aß, which could explain its low inhibitory efficiency. This suggests that the reported anti-AD activity of NQ-Trp-type molecules in in vivo models has to involve another mechanism. This study has revealed the potential pitfalls in the development of aggregation inhibitors for amyloidogenic peptides, which are of general interest for all the molecules studied in the context of inhibiting the formation of toxic aggregates.