The importance of methylthio-IMP for methylmercaptopurine ribonucleoside (Me-MPR) cytotoxicity in Molt F4 human malignant T-lymphoblasts

The importance of methyl-thioIMP (Me-tIMP) formation for methylmercaptopurine ribonucleoside (Me-MPR) cytotoxicity was studied in Molt F4 cells. Cytotoxicity of Me-MPR is caused by Me-tIMP formation with concomitant inhibition of purine de novo synthesis. Inhibition of purine de novo synthesis resulted in decreased purine nucleotide levels and enhanced 5-phosphoribosyl-1-pyrophosphate (PRPP) levels, with concurrent increased pyrimidine nucleotide levels. The Me-tIMP concentration increased proportionally with the concentration of Me-MPR. High Me-tIMP concentration also caused inhibition of PRPP synthesis. Maximal accumulation of PRPP thus occurred at low Me-MPR concentrations. As little as 0.2 μM Me-MPR resulted already after 2 h in maximal inhibition of formation of adenine and guanine nucleotides, caused by inhibition of purine de novo synthesis by Me-tIMP. Under these circumstances increased intracellular PRPP concentrations could be demonstrated, resulting in increased levels of pyrimidine nucleotides. So, in Molt F4 cells, formation of Me-tIMP form Me-MPR results in cytotoxicity by inhibition of purine de novo synthesis.     

Molecular magnetic materials from polyoxometalates

The significance of polyoxometalates in the field of molecular magnetism is discussed. We show that this kind of inorganic complexes provides remarkable examples for the study of the exchange interactions in clusters. On the other hand, we examine the possibility of using these metal oxide anions as magnetic components of molecular materials containing organic tetrathiafulvalenes as electron donor molecules.     

Enhancing estimation methods for integrating probability and nonprobability survey samples with machine-learning techniques. An application to a Survey on the impact of the COVID-19 pandemic in Spain

Web surveys have replaced Face-to-Face and computer assisted telephone interviewing (CATI) as the main mode of data collection in most countries. This trend was reinforced as a consequence of COVID-19 pandemic-related restrictions. However, this mode still faces significant limitations in obtaining probability-based samples of the general population. For this reason, most web surveys rely on nonprobability survey designs. Whereas probability-based designs continue to be the gold standard in survey sampling, nonprobability web surveys may still prove useful in some situations. For instance, when small subpopulations are the group under study and probability sampling is unlikely to meet sample size requirements, complementing a small probability sample with a larger nonprobability one may improve the efficiency of the estimates. Nonprobability samples may also be designed as a mean for compensating for known biases in probability-based web survey samples by purposely targeting respondent profiles that tend to be underrepresented in these surveys. This is the case in the Survey on the impact of the COVID-19 pandemic in Spain (ESPACOV) that motivates this paper. In this paper, we propose a methodology for combining probability and nonprobability web-based survey samples with the help of machine-learning techniques. We then assess the efficiency of the resulting estimates by comparing them with other strategies that have been used before. Our simulation study and the application of the proposed estimation method to the second wave of the ESPACOV Survey allow us to conclude that this is the best option for reducing the biases observed in our data.     

A mechanistic spatio-temporal modeling of COVID-19 data

Understanding the evolution of an epidemic is essential to implement timely and efficient preventive measures. The availability of epidemiological data at a fine spatio-temporal scale is both novel and highly useful in this regard. Indeed, having geocoded data at the case level opens the door to analyze the spread of the disease on an individual basis, allowing the detection of specific outbreaks or, in general, of some interactions between cases that are not observable if aggregated data are used. Point processes are the natural tool to perform such analyses. We analyze a spatio-temporal point pattern of Coronavirus disease 2019 (COVID-19) cases detected in Valencia (Spain) during the first 11 months (February 2020 to January 2021) of the pandemic. In particular, we propose a mechanistic spatio-temporal model for the first-order intensity function of the point process. This model includes separate estimates of the overall temporal and spatial intensities of the model and a spatio-temporal interaction term. For the latter, while similar studies have considered different forms of this term solely based on the physical distances between the events, we have also incorporated mobility data to better capture the characteristics of human populations. The results suggest that there has only been a mild level of spatio-temporal interaction between cases in the study area, which to a large extent corresponds to people living in the same residential location. Extending our proposed model to larger areas could help us gain knowledge on the propagation of COVID-19 across cities with high mobility levels.     

Growth kinetics of Rhizopus arrhizus in solid state fermentation of treated cassava

Summary Growth kinetics of Rhizopus arrhizus MUCL 28168 were determined for different treatments of cassava during solid state fermentation. The best case gave a specific growth rate () of 0.24 h^-1, a yield calculated on a basis that oxygen consumption (Y_x/o) was 2.9 g biomass. g^-1 O₂ consumed and the maintenance coefficient (m) was 0.004 g O₂ consumed. g^-1 biomass. h^-1.     

Influence of seasonal variation to the population growth and ecophysiology of Typha domingensis (Typhaceae)

Journal of Plant Research - Precipitation is an important climatic element that defines the hydrological regime, and its seasonal variation produces annual dry and wet periods in some areas. This...     

Phytochemical Characterization of Cannabis sativa L. Roots from Northeastern Brazil

This article describes the phytochemical study of Cannabis sativa roots from northeastern Brazil. The dried plant material was pulverized and subjected to exhaustive maceration with ethanol at room temperature, obtaining the crude ethanolic extract (Cs-EEBR). The volatile compounds were analyzed by gas chromatography coupled with mass spectrometry (GC/MS), which allowed to identify 22 compounds by comparing the linear retention index (LRI), the similarity index (SI) and the fragmentation pattern of the constituents with the literature. By this technique the major compounds identified were: friedelan-3-one and β-sitosterol. In addition, two fractions were obtained from Cs-EEBR by classical column chromatography and preparative thin layer chromatography. These fractions were analyzed by NMR and IR and together with the mass spectrometry data allowed to identify the compounds: epifriedelanol, friedelan-3-one, β-sitosterol and stigmasterol. The study contributed to the phytochemical knowledge of Cannabis sativa, specifically the roots, as there are few reports on the chemical constituents of this part of the plant.     

In Silico Design of an Oseltamivir Derivative with Increased Affinity against Wild-Type and Mutant Variants of Neuraminidase and Hemagglutinin of Influenza A H1N1 Virus

Antiviral resistance has turned into a world concern nowadays. Influenza A H1N1 emerged as a problem at the world level due to the neuraminidase (NA) mutations. The NA mutants conferred resistance to oseltamivir and zanamivir. Several efforts were conducted to develop better anti-influenza A H1N1 drugs. Our research group combined in silico methods to create a compound derived from oseltamivir to be tested in vitro against influenza A H1N1. Here we show the results of a new compound derived from oseltamivir but with specific chemical modifications, with significant affinity either on NA (in silico and in vitro assays) or HA (in silico) from influenza A H1N1 strain. We include docking and molecular dynamics (MD) simulations of the oseltamivir derivative at the binding site onto NA and HA of influenza A H1N1. Additionally, the biological experimental results show that oseltamivir derivative decreases the lytic-plaque formation on viral susceptibility assays, and it does not show cytotoxicity. Finally, oseltamivir derivative assayed on viral NA showed a concentration-dependent inhibition behavior at nM, depicting a high affinity of the compound for the enzyme, corroborated with the MD simulations results, placing our designed oseltamivir derivative as a potential antiviral against influenza A H1N1.