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Glucose transporter 1 deficiency syndrome (GLUT1DS) is a neurometabolic disorder caused by haploinsufficiency of the GLUT1 glucose transporter (encoded by SLC2A1) leading to defective glucose transport across the blood–brain barrier. This work describes the genetic analysis of 56 patients with clinical or biochemical GLUT1DS hallmarks. 55.4% of these patients had a pathogenic variant of SLC2A1, and 23.2% had a variant in one of 13 different genes. No pathogenic variant was identified for the remaining patients. Expression analysis of SLC2A1 indicated a reduction in SLC2A1 mRNA in patients with pathogenic variants of this gene, as well as in one patient with a pathogenic variant in SLC9A6, and in three for whom no candidate variant was identified. Thus, the clinical and biochemical hallmarks generally associated with GLUT1DS may be caused by defects in genes other than SLC2A1, Carlos III Institute (ISCIII), European Regional Development Funds (PI19/01155); CIBERER (ERTRLE0I1); Consejería de Educacion, Juventud y Deporte, Comunidad de Madrid (B2017/BMD3721); Fundacion Isabel Gemio, the Fundacion La Caixa (LCF/PR/ PR16/11110018)

Resumo Este estudo pretende identificar as estratégias de estudo e de aprendizagem utilizadas por estudantes de Ensino Superior. Participaram 48 jovens adultos voluntários, homens e mulheres, estudantes do primeiro e do terceiro anos de cursos de licenciatura em Psicologia e em Biologia, de uma instituição de Ensino Superior portuguesa. As idades variaram entre 18 e 25 anos. Este estudo, de cariz qualitativo e exploratório, realizado a partir de entrevistas semiestruturadas e com recurso de análise de conteúdo, revelou que os estudantes utilizam estratégias de organização (organização da atividade de estudo e organização do material), cognitivas (leitura, identificação da informação mais relevante, apontamentos/anotações e escrita) e metacognitivas (monitorização da aprendizagem, planeamento e gestão do tempo e avaliação/ajuste das estratégias). Não foram encontradas diferenças entre os grupos, tendo em conta o curso, o ano de frequência e o sexo. Os resultados trazem evidências que enriquecem o conhecimento nesta área de investigação e implicações para a prática. Abstract This study intends to identify the study and learning strategies used by Higher Education students. Group of participants was composed of 48 voluntary young male and female adults, students from 1st and 3rd academic years of Psychology and Biology degrees, from a Portuguese university. Ages varied from 18 to 25 years old. This exploratory research used a qualitative approach. Interviews and content analysis were used. Results revealed that students use organization strategies (organization of the study activity and organization of the material), cognitive (reading, identification of the most relevant information, notes, and writing) and metacognitive (monitoring of learning, planning and time management and evaluation/adjustment of strategies), being the cognitive predominant. The analysis carried out showed no differences when considering the degree, year, and gender. Results provide evidence that enriches the knowledge in this area of research and its implications for practice. Resumen Este estudio tiene como objetivo identificar las estrategias de estudio y aprendizaje utilizadas por los estudiantes de Educación Superior. Participaron 48 jóvenes adultos voluntarios, hombres y mujeres, estudiantes de primero y tercer año de las carreras de Licenciatura en Psicología y Biología, de una institución de Educación Superior portuguesa. Las edades oscilaron entre 18 y 25 años. Este estudio cualitativo y exploratorio, realizado a partir de entrevistas semiestructuradas y utilizando análisis de contenido, reveló que los estudiantes utilizan estrategias organizativas (organización de la actividad de estudio y organización del material), estrategias cognitivas (lectura, identificación de la información más relevante, apuntes/apuntes y redacción) y metacognitivas (seguimiento del aprendizaje, planificación y gestión del tiempo y evaluación/ajuste de estrategias). No se encontraron diferencias entre los grupos, teniendo en cuenta el curso, el año de asistencia y el sexo. Los resultados traen evidencias que enriquecen el conocimiento en esta área de investigación e implicaciones para la práctica.

The indicators of student success at higher education institutions are continuously analysed to increase the students’ enrolment in multiple scientific areas. Every semester, the students respond to a pedagogical survey that aims to collect the student opinion of curricular units in terms of content and teaching methodologies. Using this information, we intend to anticipate the success in higher-level courses and prevent dropouts. Specifically, this paper contributes with an interpretable student classification method. The proposed solution relies on (i) a pedagogical survey to collect student’s opinions; (ii) a statistical data analysis to validate the reliability of the survey; and (iii) machine learning algorithms to classify the success of a student. In addition, the proposed method includes an explainable mechanism to interpret the classifications and their main factors. This transparent pipeline was designed to have implications in both digital and sustainable education, impacting the three pillars of sustainability, i.e.,economic, social, and environmental, where transparency is a cornerstone. The work was assessed with a dataset from a Portuguese higher-level institution, contemplating multiple courses from different departments. The most promising results were achieved with Random Forest presenting 98% in accuracy and F-measure.

13 páginas, 4 figuras 2 tablas, Different strategies are being investigated for treating PMM2-CDG, the most common congenital disorder of glycosylation. The use of pharmacochaperones (PCs) is one of the most promising. The present work characterizes the expression, stability, and enzymatic properties of 15 previously described clinical variants of the PMM2 protein, four novel variants, the Pmm2 mouse variant p.Phe115Leu, and its p.Phe119Leu human counterpart, with the aim of extending the potential use of pharmacochaperoning treatment. PMM2 variants were purified as stable homodimers, except for p.Asp65Gly, p.Ile120Thr, and p.Thr237Lys (no expression detected), p.Thr226Ser and p.Val231Met (aggregates), and p.Glu93Ala, p.Phe119Leu, and p.Phe115Leu (partial dissociated). Enzyme activity analyses identified severe variants and milder ones. Pure dimeric mutant proteins showed a reduction in thermal stability except for p.Asn216Asp. The thermal stability of all the unstable mutants was recovered in the presence of the PC compound VIII. This study adds to the list of destabilizing human variants amenable to rescue by small chemical compounds that increase the stability/activity of PMM2. The proposed platform can be reliably used for assessing the disease-causing effects of PMM2 missense variants, for assessing the correlation between genotype and phenotype, for confirming new clinical defects, and for identifying destabilizing mutations amenable to rescue by PCs., Instituto de Salud Carlos III; Consejería de Educación, Juventud y Deporte, Comunidad de Madrid; Fundación Isabel Gemio‐La Caixa; Fundación Ramón Areces; Australian Government's Medical Research Future Fund

The pharmaceutical industry is a data-intensive environment and a heavily-regulated sector, where exhaustive audits and inspections are performed to ensure the safety of drugs. In this context, processing and evaluating the data generated in the manufacturing lines is a relevant challenge since it requires compliance with pharma regulations. This work combines data integrity metrics and blockchain technology to evaluate the compliance-degree of ALCOA+ principles among different levels of drug manufacturing data. We propose the DIALCOA tool, a software to assess the compliance-degree for each ALCOA+ principle, based on the assessment of data from manufacturing batch reports and its different levels of information.

Human interaction with intelligent systems, services, and devices generates large volumes of user-related data. This multi-source information can be used to build richer user profiles and improve personalization. Our goal is to combine multi-source data to create user profiles by assigning dynamic individual weights. This paper describes a multi-source user profiling methodology and illustrates its application with a film recommendation system. The contemplated data sources include (i) personal history, (ii) explicit preferences (ratings), and (iii) social activities (likes, comments, or shares). The MovieLens dataset was selected and adapted to assess our approach by comparing the standard and the proposed methodologies. In the standard approach, we calculate the best global weights to apply to the different profile sources and generate all user profiles accordingly. In the proposed approach, we determine, for each user, individual weights for the different profile sources. The approach proved to be an efficient solution to a complex problem by continuously updating the individual data source weights and improving the accuracy of the generated personalised multimedia recommendations.

Digital transformation could change our daily routines, from currency to the purchases. Specifically, financial sector aims to efficiently supply distinct services using an infrastructure by relying on a centralised authority to manage and coordinate transactions at specific prices. In turn, final customers constantly seek to lower costs, quality, and reliability. Moreover, costumers desire less documentation and bureaucracy which hinder the access to financial services and credits. Financial system needs to create a digital strategy at the organisational level to address technology challenges and satisfy user’s needs. In this scenario, financial and technology domains have been integrated originating FinTech business models with significant impact. Therefore, this paper contributes not only with a technology background which allow to explore new FinTech-based business models but also describing existing business models employed in the market. Moreover, we present a comparison among traditional and FinTech-based models allowing to analyse the financial progress. The paper identifies, still, future research opportunities including regulation of decentralised financial business models.

Due to COVID19 disease contingencies, in several countries, universities were forced to replace the face-to-face classes for a non-face-to-face system, also called as Emergency Remote Teaching - ERT. In this scenario, both teachers and students experienced several challenges and had to adapt to new ways of teaching and learning. The goal of this study was to understand how students experienced this situation. Through a qualitative methodology, we interviewed eight higher education students from social sciences scientific areas. Thematic analysis was used to identify and interpret patterns and themes in students’ responses. Results show that students experimented several difficulties at different levels: cognitive level (e.g., attention, concentration, and information storage), motivational (e.g., demotivation to study), tiredness; organizational (e.g., time and tasks management), and social level (e.g., interpersonal relationship and lack of contact with people). These results bring new knowledge to this problematic area and can be useful for students, teachers, and higher education institutions.

We report two new 6-pyruvoyl-tetrahydropterin synthase splicing variants identified through genomic sequencing and transcript analysis in a patient with tetrahydrobiopterin deficiency, presenting with hyperphenylalaninemia and monoamine neurotransmitter deficiency. Variant c.243 + 3A>G causes exon 4 skipping. The deep-intronic c.164-672C>T variant creates a potential 5' splice site that leads to the inclusion of four overlapping pseudoexons, corresponding to exonizations of an antisense short interspersed nuclear element AluSq repeat sequence. Two of the identified pseudoexons have been reported previously, activated by different deep-intronic variants, and were also detected at residual levels in control cells. Interestingly, the predominant pseudoexon is nearly identical to a disease causing activated pseudoexon in the F8 gene, with the same 3' and 5' splice sites. Splice switching antisense oligonucleotides (SSOs) were designed to hybridize with splice sites and/or predicted binding sites for regulatory splice factors. Different SSOs corrected the aberrant pseudoexon inclusion, both in minigenes and in fibroblasts from patients carrying the new variant c.164-672C>T or the previously described c.164-716A>T. With SSO treatment PTPS protein was recovered, illustrating the therapeutic potential of the approach, for patients with different pseudoexon activating variants in the region. In addition, the natural presence of pseudoexons in the wild type context suggests the possibility of applying the antisense strategy in patients with hypomorphic PTS variants with the purpose of upregulating their expression to increase overall protein and activity.