Effects of exogenous lactase administration on hydrogen breath excretion and intestinal symptoms in patients presenting lactose malabsorption and intolerance

To establish whether supplementation with a standard oral dose of Beta-Galactosidase affects hydrogen breath excretion in patients presenting with lactose malabsorption. METHODS: Ninety-six consecutive patients positive to H2 Lactose Breath Test were enrolled. Mean peak H2 levels, the time to reach the peak H2, the time to reach the cut-off value of 20 ppm, the cumulative breath H2 excretion, the areas under the curve, and a Visual Analogical 10-point Scale for symptoms were calculated. Genotyping of the C/T-13910 variant was carried out. RESULTS: Following the oral administration of Beta-Galactosidase, in 21.88% of the cases, H2 Lactose Breath Test became negative (Group A), while mean peak H2 levels (74.95 ppm versus 7.85), P < 0.0000, in 17.71% (Group B) were still positive, with the H2 level 20 ppm above the baseline, but the peak H2 levels were significantly lower than those observed at the baseline test (186.7 ppm versus 66.64), P < 0.0000, while in 60.41% (Group C) they were still positive with the peak H2 levels similar to those observed at the baseline test (94.43 versus 81.60 ppm). All 96 individuals tested presented the C/C-13910 genotype nonpersistence. CONCLUSIONS: The response to oral administration of Beta-Galactosidase in patients with symptoms of lactose malabsorption presents a significant variability

Chronic Intermittent Ethanol Regulates Hippocampal GABA(A) Receptor Delta Subunit Gene Expression.

Chronic ethanol consumption causes structural and functional reorganization in the hippocampus and induces alterations in the gene expression of gamma-aminobutyric acid type A receptors (GABAARs). Distinct forced intermittent exposure models have been used previously to investigate changes in GABAAR expression, with contrasting results. Here, we used repeated cycles of a Chronic Intermittent Ethanol paradigm to examine the relationship between voluntary, dependence-associated ethanol consumption, and GABAAR gene expression in mouse hippocampus. Adult male C57BL/6J mice were exposed to four 16-h ethanol vapor (or air) cycles in inhalation chambers alternated with limited-access two-bottle choice between ethanol (15%) and water consumption. The mice exposed to ethanol vapor showed significant increases in ethanol consumption compared to their air-matched controls. GABAAR alpha4 and delta subunit gene expression were measured by qRT-PCR at different stages. There were significant changes in GABAAR delta subunit transcript levels at different time points in ethanol-vapor exposed mice, while the alpha4 subunit levels remained unchanged. Correlated concurrent blood ethanol concentrations suggested that GABAAR delta subunit mRNA levels fluctuate depending on ethanol intoxication, dependence, and withdrawal state. Using a vapor-based Chronic Intermittent Ethanol procedure with combined two-bottle choice consumption, we corroborated previous evidences showing that discontinuous ethanol exposure affects GABAAR delta subunit expression but we did not observe changes in alpha4 subunit. These findings indicate that hippocampal GABAAR delta subunit expression changes transiently over the course of a Chronic Intermittent Ethanol paradigm associated with voluntary intake, in response to ethanol-mediated disturbance of GABAergic neurotransmission

Editorial: Microbial Regulation of Translation

Since the description of the operon model by Jacob and Monod during the late 1950s and early 1960s (Ullmann, 2010), the concept that the reading of genetic information must be a regulated process has been central to our understanding of biology. This is particularly true for microbes, which can adapt to an incredible variety of environments. Based on the research performed since the description of the operon, we have gained a deep understanding of the diverse strategies used by microbes to modulate the transcription of genetic information from DNA to RNA. In contrast, the mechanisms that regulate the translation of messenger RNAs into proteins has received less attention. The technical developments of the last decade now allow us to obtain detailed information on RNA folding (Rouskin et al., 2014; Aw et al., 2016) and modification (Linder et al., 2015; Lorenz et al., 2020) and the speed of translation (Subramaniam et al., 2013; Ingolia, 2014; Dai et al., 2016). This, in turn, allows us to scrutinize the functionality of translation components in vivo, providing unprecedented opportunities to study translation regulation. In this special issue of Frontiers in Genetics, \u27Microbial Regulation of Translation,\u27 we have assembled a series of articles that use diverse experimental approaches to study the regulation of translation in microbes

Cell-selective metabolic labeling of proteins

Metabolic labeling of proteins with the methionine surrogate azidonorleucine can be targeted exclusively to specified cells through expression of a mutant methionyl-tRNA synthetase (MetRS). In complex cellular mixtures, proteins made in cells that express the mutant synthetase can be tagged with affinity reagents (for detection or enrichment) or fluorescent dyes (for imaging). Proteins made in cells that do not express the mutant synthetase are neither labeled nor detected

Supercritical extraction from Rosa canina L. fruits: fatty acids composition and biological activities

The supercritical fluid extraction from pulp of Rosa canina L. fruits, using CO2 as a solvent, is presented in this study. The extraction experiment was carried out at pressures of 300 bar and a temperature of 40°C, SFE[300:40]. The extract yield was 0.3% for the weight of the charge. The extraction and saponification processes produced a fraction mainly formed by free fatty acids, FA, determined by HPLC-DAD and GC-FID analyses. Pulp extract was characterised by a high level of linolenic acid, 18:3 n-3, (28.37% of total FA); linoleic acid, 18:2 n-6, (26.74%); palmitic acid, 16:0, (18.20%); and oleic acid, 18:1 n-9, (15.74%). Followed by low amounts of stearic acid, 18:0, palmitoleic acid, 16:1 n-7, lauric acid, 12:0, and myristic acid, 14:0. The amounts of the main unsaturated fatty acids, UFA, in SFE[300:40], determined by HPLC analysis, were 121.43 ± 3.21 mg/g, 102.16 ± 2.84 mg/g, and 49.95 ± 2.75 mg/g of extract for 18:3 n-3, 18:2 n-6 and 18:1 n-9, respectively. Interestingly, the sample was characterised by a high proportion of polyunsaturated fatty acids, PUFA, and the ratio value of UFA to SFA, saturated fatty acids, was 2.8. The quality of the SFE[300:40] extract, in terms of its chemical composition, was compared with that obtained using n-hexane in a Soxhlet apparatus, Sx. The sample obtained by solvent extraction showed a chemical profile similar to the one obtained by means of SFE but without the added benefit of not having unwanted traces of solvent. The extracts were evaluated for antioxidant properties, polyphenol content, and inhibitory activity on the xanthine oxidase (XO) enzyme. The antioxidant properties were determined with ABTS assay. The results indicated that the SFE[300:40] extract had low antioxidant activity (EC50 = 0.241 ± 0.022 mg/mL) and the Sx extract had no antioxidant activity. The total phenolics of SFE[300:40] extract was 17.7 mg GAE/g of weight. Both extracts showed a very low inhibition activity towards the XO enzyme

Towards the definition of a European Digital Building Logbook: A survey

Both the operational phase and embodied emissions that are introduced during the construction phase through the manufacture, sourcing, and installation of the building's materials and components are significant contributors to carbon emissions from the built environment. It is essential to change the current design and (re)construction processes in order to achieve the energy-saving targets for the EU building stock and move toward a society that is net carbon neutral. This change must be made from both a technical perspective as well as from a methodological perspective. To accomplish this, the EU has suggested several regulations and legislative steps to phase out inefficient structures. The most recent of these initiatives propose the idea of a Digital Building Logbook, which serves as a central repository for all pertinent building data, including information on energy efficiency. In this work, we present a survey of the elements that have been taken into consideration for the creation of the Digital Building Logbook to give an overview of what research has been done so far

A transformers-based approach for fine and coarse-grained classification and generation of MIDI songs and soundtracks

Music is an extremely subjective art form whose commodification via the recording industry in the 20th century has led to an increasingly subdivided set of genre labels that attempt to organize musical styles into definite categories. Music psychology has been studying the processes through which music is perceived, created, responded to, and incorporated into everyday life, and, modern artificial intelligence technology can be exploited in such a direction. Music classification and generation are emerging fields that gained much attention recently, especially with the latest discoveries within deep learning technologies. Self attention networks have in fact brought huge benefits for several tasks of classification and generation in different domains where data of different types were used (text, images, videos, sounds). In this article, we want to analyze the effectiveness of Transformers for both classification and generation tasks and study the performances of classification at different granularity and of generation using different human and automatic metrics. The input data consist of MIDI sounds that we have considered from different datasets: sounds from 397 Nintendo Entertainment System video games, classical pieces, and rock songs from different composers and bands. We have performed classification tasks within each dataset to identify the types or composers of each sample (fine-grained) and classification at a higher level. In the latter, we combined the three datasets together with the goal of identifying for each sample just NES, rock, or classical (coarse-grained) pieces. The proposed transformers-based approach outperformed competitors based on deep learning and machine learning approaches. Finally, the generation task has been carried out on each dataset and the resulting samples have been evaluated using human and automatic metrics (the local alignment)

Anti-BVDV activity evaluation of naphthoimidazole derivatives compared with parental imidazoquinoline compounds.

Background: Pestivirus genus includes animal pathogens which are involved in economic impact for the livestock industry. Among others, Bovine Viral Diarrhoea Virus (BVDV) establish a persistent infection in cattle causing a long list of symptoms and a high mortality rate. In the last decades, we synthesised and reported a certain number of anti-BVDV compounds. Methods: In them, imidazoquinoline derivatives turned out as the most active. Their mechanism of actions has been deeply investigated, BVDV RNA-dependent RNA polymerase (RpRd) resulted as target and the way of binding was predicted in silico through three main H-bond interaction with the target. The prediction could be confirmed by target or ligand mutation. The first approach has already been performed and published confirming the in silico prediction. Results: Here, we present how the ligand chemical modification affects the anti-BVDV activity. The designed compounds were synthesised and tested against BVDV as in silico assay negative control. Conclusion: The antiviral results confirmed the predicted mechanism of action, as the newly synthesised compounds resulted not active in the in vitro BVDV infection inhibitio