Suchergebnisse

Automatically detecting mentions of pharmaceutical drugs and chemical substances is key for the subsequent extraction of relations of chemicals with other biomedical entities such as genes, proteins, diseases, adverse reactions or symptoms. The identification of drug mentions is also a prior step for complex event types such as drug dosage recognition, duration of medical treatments or drug repurposing. Formally, this task is known as named entity recognition (NER), meaning automatically identifying mentions of predefined entities of interest in running text. In the domain of medical texts, for chemical entity recognition (CER), techniques based on hand-crafted rules and graph-based models can provide adequate performance. In the recent years, the field of natural language processing has mainly pivoted to deep learning and state-of-the-art results for most tasks involving natural language are usually obtained with artificial neural networks. Competitive resources for drug name recognition in English medical texts are already available and heavily used, while for other languages such as Spanish these tools, although clearly needed were missing. In this work, we adapt an existing neural NER system, NeuroNER, to the particular domain of Spanish clinical case texts, and extend the neural network to be able to take into account additional features apart from the plain text. NeuroNER can be considered a competitive baseline system for Spanish drug and CER promoted by the Spanish national plan for the advancement of language technologies (Plan TL). ; This work was supported by the Encargo de Gestion SEAD-CNIO of the Spanish National Plan for the Advancement of Language Technologies, the ICTUSnet INTERREG Sudoe programme, the European Union Horizon2020 eTransafe project, grant agreement ID 777365. ; Peer Reviewed ; Postprint (published version)

Probiotics microorganisms exert their health-associated activities through some of the following general actions: competitive exclusion, enhancement of intestinal barrier function, production of bacteriocins, improvement of altered microbiota, and modulation of the immune response. Among them, Limosilactobacillus fermentum CECT5716 has become one of the most promising probiotics and it has been described to possess potential beneficial effects on inflammatory processes and immunological alterations. Different studies, preclinical and clinical trials, have evidenced its anti-inflammatory and immunomodulatory properties and elucidated the precise mechanisms of action involved in its beneficial effects. Therefore, the aim of this review is to provide an updated overview of the effect on host health, mechanisms, and future therapeutic approaches. ; This work was supported by the Junta de Andalucía (CTS 164) and Instituto de Salud Carlos III (PI19/01058) with funds from the European Union. ; Yes

Amino acids are of paramount importance as chiral building blocks of life, for drug development in modern medicinal chemistry, and for the manufacture of industrial products. In this work, the stereoselective synthesis of (S)- and (R)-2-amino-4-hydroxybutanoic acid was accomplished using a systems biocatalysis approach comprising a biocatalytic one-pot cyclic cascade by coupling of an aldol reaction with an ensuing stereoselective transamination. A class II pyruvate aldolase from E. coli, expressed as a soluble fusion protein, in tandem with either an S- or R-selective, pyridoxal phosphate dependent transaminase was used as a catalyst to realize the conversion, with formaldehyde and alanine being the sole starting materials. Interestingly, the class II pyruvate aldolase was found to tolerate formaldehyde concentrations of up to 1.4 M. The cascade system was found to reach product concentrations for (S)- or (R)-2-amino-4-hydroxybutanoic acid of at least 0.4 M, rendering yields between 86% and >95%, respectively, productivities of >80 g L–1 d–1, and ee values of >99%. ; This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement no. 635595 (CarbaZymes), the Ministerio de Economía y Competitividad (MINECO), the Fondo Europeo de Desarrollo Regional (FEDER) (grant no. CTQ2015-63563-R to P.C.), and COST action CM1303 Systems Biocatalysis. ; We acknowledge support by the CSIC Open Access Publication Initiative through its Unit of Information Resources for Research (URICI). ; Peer reviewed

The objective of this study was to determine the energy values, standardized ileal digestibility coefficients and digestible amino acid contents of parboiled brown rice bran (PBRB), protein sorghum meal (PSM) and bread waste meal (BWM) in broiler diets. In the first trial, 144 broiler chicks at 14 days of age were evaluated in a completely randomized design involving three feedstuffs + a control diet, with six replicates and six birds per experimental unit. The total excreta collection method was adopted to determine the energy values of the feedstuffs. In the second trial, 144 broilers at 24 days of age were used in a completely randomized design involving three feedstuffs + a protein-free diet, with six replicates and six birds per experimental unit. Ileal digesta was harvested to determine the standardized ileal digestibility coefficients and digestible amino acid contents of the feedstuffs. The nitrogen-corrected apparent metabolizable energy (AMEn) values of PBRB, PSM and BWM were 2638, 2799 and 3399 kcal.kg-1, respectively. The metabolizability coefficients of AMEn (CAMEn) of PBRB, PSM and BWM were 54.13, 57.35 and 86.66%, respectively. Bread waste meal had the highest CAMEn (p < 0.05) and standardized ileal digestibility of amino acids (p < 0.01), followed by PBRB and PSM. The main limiting digestible amino acids in PBRB, PSM and BWM were found at the following respective levels: methionine - 0.19, 0.33 and 0.24%; lysine - 0.40, 0.46 and 0.40%; threonine - 0.25, 0.50 and 0.45%; and valine - 0.44, 0.73 and 0.48%.