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SUMMARYRNA can directly control protein activity in a process called riboregulation; only a few mechanisms of riboregulation have been described in detail, none of these being characterized on structural grounds. Here we present a comprehensive structural, functional, and phylogenetic analysis of riboregulation of cytosolic serine hydroxymethyltransferase (SHMT1), the enzyme interconverting serine and glycine in one-carbon metabolism. We show that the RNA modulator competes with polyglutamylated folates and acts as an allosteric switch, selectively altering the enzyme’s reactivity vs. serine. In addition, we identify the tetrameric assembly and a flap structural motif as key structural elements necessary for binding of RNA to eukaryotic SHMT1. The results presented here suggest that riboregulation may have played a role in the evolution of eukaryotic SHMT1 and the compartmentalization of one-carbon metabolism. The findings also provide insights for RNA-based therapeutic strategies targeting this cancer-linked metabolic pathway.

Vitamins B (thiamine) and B (pyridox (al/ine/amine)) are crucial for central nervous system (CNS) function and neurogenesis due to the coenzyme action of their phosphorylated derivatives in the brain metabolism of glucose and neurotransmitters. Here, the non-coenzyme action of thiamine on the major mammalian producers of pyridoxal-5?-phosphate (PLP), such as pyridoxal kinase (PdxK) and pyridoxine 5?-phosphate oxidase (PNPO), is characterized. Among the natural thiamine compounds, thiamine triphosphate (ThTP) is the best effector of recombinant human PdxK (hPdxK) in vitro, inhibiting hPdxK in the presence of Mg but activating the Zn-dependent reaction. Inhibition of hPdxK by thiamine antagonists decreases from amprolium to pyrithiamine to oxythiamine, highlighting possible dysregulation of both the B- and B-dependent metabolism in the chemical models of thiamine deficiency. Compared with the canonical hPdxK, the D87H and V128I variants show a twofold increase in K of thiamine inhibition, and the V128I and H246Q variants show a fourfold and a twofold decreased K of thiamine diphosphate (ThDP), respectively. Thiamine administration changes diurnal regulation of PdxK activity and phosphorylation at Ser213 and Ser285, expression of the PdxK-related circadian kinases/phosphatases in the rat brain, and electrocardiography (ECG). In contrast to PdxK, PNPO is not affected by thiamine or its derivatives, either in vitro or in vivo. Dephosphorylation of the PdxK Ser285, potentially affecting mobility of the ATP-binding loop, inversely correlates with the enzyme activity. Dephosphorylation of the PdxK Ser213, which is far away from the active site, does not correlate with the activity. The correlations analysis suggests the PdxK Ser213 to be a target of kinase MAP2K1 and phosphatase Ppp1ca. Diurnal effects of thiamine administration on the metabolically linked ThDP- and PLP-dependent enzymes may support the brain homeostatic mechanisms and physiological fitness. (Figure presented.).

The role of aflatoxins (AFs) in the biology of producing strains, Aspergillus sect. Flavi, is still a matter of debate. Over recent years, research has pointed to how environmental factors altering the redox balance in the fungal cell can switch on the synthesis of AF. Notably, it has been known for decades that oxidants promote AF synthesis. More recent evidence has indicated that AF synthesis is controlled at the transcriptional level: reactive species that accumulate in fungal cells in the stationary growth phase modulate the expression of aflR, the main regulator of AF synthesis—through the oxidative stress related transcription factor AP-1. Thus, AFs are largely synthesized and secreted when (i) the fungus has exploited most nutritional resources; (ii) the hyphal density is high; and (iii) reactive species are abundant in the environment. In this study, we show that AFs efficiently scavenge peroxides and extend the lifespan of E. coli grown under oxidative stress conditions. We hypothesize a novel role for AF as an antioxidant and suggest its biological purpose is to extend the lifespan of AFs-producing strains of Aspergillus sect. Flavi under highly oxidizing conditions such as when substrate resources are depleted, or within a host.

Context.The unprecedented amount and the excellent quality of lensing data expected from upcoming ground and space-based surveys present a great opportunity for shedding light on questions that remain unanswered with regard to our universe and the validity of the standard ΛCDM cosmological model. The development of new techniques that are capable of exploiting the vast quantity of data provided by future observations, in the most effective way possible, is of great importance.Aims.This is the reason we chose to investigate the development of a new method for treating weak-lensing higher-order statistics, which are known to break the degeneracy among cosmological parameters thanks to their capacity to probe non-Gaussian properties of the shear field. In particular, the proposed method applies directly to the observed quantity, namely, the noisy galaxy ellipticity.Methods.We produced simulated lensing maps with different sets of cosmological parameters and used them to measure higher-order moments, Minkowski functionals, Betti numbers, and other statistics related to graph theory. This allowed us to construct datasets with a range of sizes, levels of precision, and smoothing. We then applied several machine learning algorithms to determine which method best predicts the actual cosmological parameters associated with each simulation.Results.The most optimal model turned out to be a simple multidimensional linear regression. We use this model to compare the results coming from the different datasets and find that we can measure, with a good level of accuracy, the majority of the parameters considered in this study. We also investigated the relation between each higher-order estimator and the different cosmological parameters for several signal-to-noise thresholds and redshifts bins.Conclusions.Given the promising results we obtained, we consider this approach a valuable resource that is worthy of further development.

The use of plant extracts in pre- and post-harvest disease management of agricultural crops to cope with aflatoxin B1 contamination has shown great promise due to their capability in managing toxins and safe-keeping the quality. We investigated the anti-aflatoxigenic effect of multiple doses of eight plant extracts (Heracleum persicum, Peganum harmala, Crocus sativus, Trachyspermum ammi, Rosmarinus officinalis, Anethum graveolens, Berberis vulgaris, Berberis thunbergii) on Aspergillus flavus via LC-MS and the down-regulatory effect of them on aflR, aflM and aflP genes involved in the aflatoxin B1 biosynthesis pathway using RT-qPCR analyses. Our results showed that H. persicum (4 mg/mL), P. harmala (6 mg/mL) and T. ammi (2 mg/mL) completely stopped the production of aflatoxin B1, without inducing significant changes in A. flavus growth. Furthermore, our findings showed a highly significant correlation between the gene expression and the aflatoxin B1 biosynthesis, such that certain doses of the extracts reduced or blocked the expression of the aflR, aflM and aflP and consequently reduced the synthesis of aflatoxin B1. Interestingly, compared to the regulatory gene (aflR), the down-regulation of expression in the structural genes (aflM and aflP) was more consistent and correlated with the inhibition of aflatoxin B1 production. Overall, this study reveals the anti-aflatoxigenic mechanisms of the selected plant extracts at the gene expression level and provides evidence for their use in plant and crop protection.

In recent years, algorithm research in the area of recommender systems has shifted from matrix factorization techniques and their latent factor models to neural approaches. However, given the proven power of latent factor models, some newer neural approaches incorporate them within more complex network architectures. One specific idea, recently put forward by several researchers, is to consider potential correlations between the latent factors, i.e., embeddings, by applying convolutions over the user-item interaction map. However, contrary to what is claimed in these articles, such interaction maps do not share the properties of images where Convolutional Neural Networks (CNNs) are particularly useful. In this work, we show through analytical considerations and empirical evaluations that the claimed gains reported in the literature cannot be attributed to the ability of CNNs to model embedding correlations, as argued in the original papers. Moreover, additional performance evaluations show that all of the examined recent CNN-based models are outperformed by existing non-neural machine learning techniques or traditional nearest-neighbor approaches. On a more general level, our work points to major methodological issues in recommender systems research., Comment: Source code available here: https://github.com/MaurizioFD/RecSys2019_DeepLearning_Evaluation

Aims. Stage IV lensing surveys promise to make an unprecedented amount of excellent data available. This will represent a huge leap in terms of quantity and quality and will open the way for the use of novel tools that surpass the standard second-order statistics for probing the high-order properties of the convergence field. Motivated by these considerations, some of us have started a long-term project aiming at using Minkowski functionals (MFs) as complementary and supplementary probes to increase the lensing figure of merit (FoM). Methods. As a second step on this path, we discuss the use of MFs for a survey consisting of a wide total area Atot that is imaged at a limiting magnitude magW and contains a subset of area Adeep, where observations are pushed to a deeper limiting magnitude magD. We present an updated procedure to match the theoretically predicted MFs to the measured MFs, and take the effect of map reconstruction from noisy shear data into account. We validate this renewed method against simulated datasets with different source redshift distributions and total number density, setting these quantities in accordance with the depth of the survey. We can then rely on a Fisher matrix analysis to forecast the improvement in the FoM that is due to the joint use of shear tomography and MFs under different assumptions on (Atot, Adeep, and magD), and the prior on the MFs nuisance parameters. Results. We find that MFs can provide valuable help in increasing the FoM of the lensing survey when the nuisance parameters are known with non-negligible precision. The possibility of compensating for the loss of FoM through a cut in the multipole range that is probed by shear tomography is even more interesting. This makes the results more robust against uncertainties in the modeling of nonlinearities. This makes MFs a promising tool for increasing the FoM and also protects the constraints on the cosmological parameters mainly from theoretical systematic effects.

Food and feed safety are of paramount relevance in everyday life. The awareness that different chemicals, e.g., those largely used in agriculture, could present both environmental problems and health hazards, has led to a large limitation of their use. Chemicals were also the main tool in a control of fungal pathogens and their secondary metabolites, mycotoxins. There is a drive to develop more environmentally friendly, “green”, approaches to control mycotoxin contamination of foodstuffs. Different mushroom metabolites showed the potential to act as control agents against mycotoxin production. The use of a polysaccharide, Tramesan, extracted from the basidiomycete Trametes versicolor, for controlling biosynthesis of aflatoxin B1 and ochratoxin A, has been previously discussed. In this study, oligosaccharides obtained from Tramesan were evaluated. The purified exopolysaccharide of T. versicolor was partially hydrolyzed and separated by chromatography into fractions from disaccharides to heptasaccharides. Each fraction was individually tested for mycotoxin inhibition in A. flavus and A. carbonarius. Fragments smaller than seven units showed no significant effect on mycotoxin inhibition, heptasaccharides showed inhibitory activity of up to 90% in both fungi. These results indicated that these oligosaccharides could be used as natural alternatives to crop protection chemicals for controlling these two mycotoxins.