The surface accessibility of α-bungarotoxin monitored by a novel paramagnetic probe

The surface accessibility of {alpha}-bungarotoxin has been investigated by using Gd2L7, a newly designed paramagnetic NMR probe. Signal attenuations induced by Gd2L7 on {alpha}-bungarotoxin C{alpha}H peaks of 1H-13C HSQC spectra have been analyzed and compared with the ones previously obtained in the presence of GdDTPA-BMA. In spite of the different molecular size and shape, for the two probes a common pathway of approach to the {alpha}-bungarotoxin surface can be observed with an equally enhanced access of both GdDTPA-BMA and Gd2L7 towards the protein surface side where the binding site is located. Molecular dynamics simulations suggest that protein backbone flexibility and surface hydration contribute to the observed preferential approach of both gadolinium complexes specifically to the part of the {alpha}-bungarotoxin surface which is involved in the interaction with its physiological target, the nicotinic acetylcholine receptor

A Machine Learning-Based Method for Modelling a Proprietary SO2 Removal System in the Oil and Gas Sector

The aim of this study is to develop a model for a proprietary SO2 removal technology by using machine learning techniques and, more specifically, by exploiting the potentialities of artificial neural networks (ANNs). This technology is employed at the Eni oil and gas treatment plant in southern Italy. The amine circulating in this unit, that allows for a reduction in the SO2 concentration in the flue gases and to be compliant with the required specifications, is a proprietary solvent; thus, its composition is not publicly available. This has led to the idea of developing a machine learning (ML) algorithm for the unit description, with the objective of becoming independent from the licensor and more flexible in unit modelling. The model was developed in MatLab® by implementing ANNs and the aim was to predict three targets, namely the flow rate of SO2 that goes to the Claus unit, the emissions of SO2, and the flow rate of steam sent to the regenerator reboiler. These represent, respectively, the two physical outputs of the unit and a proxy variable of the amine quality. Three different models were developed, one for each target, that employed the Levenberg–Marquardt optimization algorithm. In addition, the ANN topology was optimized case by case. From the analysis of the results, it emerged that with a purely data-driven technique, the targets can be predicted with good accuracy. Therefore, this model can be employed to better manage the SO2 removal system, since it allows for the definition of an optimal control strategy and the maximization of the plant’s productivity by not exceeding the process constraints

A Bioinformatics Approach to Investigate Structural and Non-Structural Proteins in Human Coronaviruses

Recent studies confirmed that people unexposed to SARS-CoV-2 have preexisting reactivity, probably due to previous exposure to widely circulating common cold coronaviruses. Such preexistent reactivity against SARS-CoV-2 comes from memory T cells that can specifically recognize a SARS-CoV-2 epitope of structural and non-structural proteins and the homologous epitopes from common cold coronaviruses. Therefore, it is important to understand the SARS-CoV-2 cross-reactivity by investigating these protein sequence similarities with those of different circulating coronaviruses. In addition, the emerging SARS-CoV-2 variants lead to an intense interest in whether mutations in proteins (especially in the spike) could potentially compromise vaccine effectiveness. Since it is not clear that the differences in clinical outcomes are caused by common cold coronaviruses, a deeper investigation on cross-reactive T-cell immunity to SARS-CoV-2 is crucial to examine the differential COVID-19 symptoms and vaccine performance. Therefore, the present study can be a starting point for further research on cross-reactive T cell recognition between circulating common cold coronaviruses and SARS-CoV-2, including the most recent variants Delta and Omicron. In the end, a deep learning approach, based on Siamese networks, is proposed to accurately and efficiently calculate a BLAST-like similarity score between protein sequences

Structural investigation of Rett-inducing MeCP2 mutations

X-ray structure of methyl-CpG binding domain (MBD) of MeCP2, an intrinsically disordered protein (IDP) involved in Rett syndrome, offers a rational basis for defining the spatial distribution for most of the sites where mutations responsible of Rett syndrome, RTT, occur. We have ascribed pathogenicity for mutations of amino acids bearing positively charged side chains, all located at the protein-DNA interface, as positive charge removal cause reduction of the MeCP2-DNA adduct lifetime. Pathogenicity of the frequent proline replacements, outside the DNA contact moiety of MBD, can be attributed to the role of this amino acid for maintaining both unfolded states for unbound MeCP2 and, at the same time, to favor some higher conformational order for stabilizing structural determinants required by protein activity. These hypotheses can be extended to transcription repressor domain, TRD, the other MeCP2-DNA interaction site and, in general, to all the IDP that interact with nucleic acids

A Project to Promote English Learning in Primary School: “An English Island®” E-learning Platform

The present study was aimed to investigate English learning as second language, in school, in first, second and third graders of twelve classes randomly assigned to a control or an experimental group. Children in the latter are exposed during English school teaching to the method “An English Island®” and to its platform activities. The method “An English Island®” offers a variety of strategies for teaching English in primary school, an innovative digital tool that promotes teaching/learning English language’s communicative approach, lead students to become familiar with the language in a sort of continuous, inclusive workout, in which everyone participates and talks. English skills as well as cognitive abilities are tested in both groups at the beginning and at the end of the school year with the aim to compare control and experimental classes in both a longitudinal and a cross-sectional design

Chemical composition and apparent digestibility of a panel of dried microalgae and cyanobacteria biomasses in rainbow trout (Oncorhynchus mykiss)

Despite a growing interest in microalgae and cyanobacteria as potential sources of nutrients in aquafeeds, little information is presently available on their nutritive value for carnivorous fish species. The aim of this study was to evaluate chemical composition and nutrient digestibility of a panel of microalgae and cyanobacteria dried biomasses (MACB), using rainbow trout (Oncorhynchus mykiss W.) as a fish model. Nine test diets were obtained by mixing 80 parts of a reference diet, added with 20 g/kg of acid insoluble ash as an indigestible marker, to 20 parts of each of the following dried whole-cell biomass: Arthrospira platensis, Nostoc sphaeroides, two strains of Chlorella sorokiniana, Nannochloropsis oceanica, Tisochrysis lutea, Phaeodactylum tricornutum, Porphyridium purpureum and Tetraselmis suecica. The digestibility measurements were conducted with rainbow trout (52.4 \ub1 1.5 g) kept in six tank units each including three 60-L vessels singularly stocked with 12 fish and fitted with a settling column for faecal recovery. Per each diet, faeces were collected over three independent 10-day periods. Apparent digestibility coefficients (ADCs) of dry matter, crude protein (CP), organic matter and gross energy (GE) of single MACB were calculated by difference relative to those of the reference diet. The MACBs had heterogeneous chemical composition (CP, from 20 to 69%; Lipid, 5\u201327%; GE, 12.5-\u201322.6 MJ/kg dry matter basis) reflecting their overall biodiversity. Most of them can be considered as virtually good sources of minerals and trace elements and exhibit an essential amino acid profile comparable or even better than that of soybean meal commonly used in fish feeds with P. purpureum showing the best protein profile. The digestibility results obtained with rainbow trout allowed ranking the MACBs into two major groups. A first one, including C. sorokiniana, N. oceanica and T. suecica, resulted in markedly lower (P < 0.05) crude protein and energy ADC (64\u201373%; 51\u201359%, respectively) compared to a second group including P. purpureum, T. lutea and cyanobacteria (CP-ADC, 83\u201388%; GE-ADC, 74\u201390%) while P. tricornutum resulted in intermediate values. Overall, the present study confirms the consistently reported role of cell-wall structure/composition in affecting accessibility of nutrients to digestive enzyme. Based on the overall outcomes, only T. lutea and cyanobacteria actually meet the requirements for being used as protein sources in aquafeeds provided their mass production becomes more feasible and costeffective, hence attractive for the feed-mill industry in the near future