Students' perceptions of higher education courses and instructors before and during Covid-19:

The recognition of Covid-19 as a global pandemic in March 2020 forced the closure of schools and universities around the world, raising the need to adopt emergency teaching methods. A year and a half later, the situation is still not resolved, but there is more data that allow us to understand the real impact. This study presents a comprehensive analysis of higher education students perceptions about courses and faculty during the last 5 years (2016-2021), with a special focus on the differences in perception between the pre-Covid-19 and the during Covid-19 phases. To this end, the pedagogical surveys that are answered by students from an engineering degree at a Portuguese university at the end of the first and second semester of the academic year are analyzed. The results allow us to identify two distinct moments in the Covid-19 phase: a first in which feelings of positivism and appreciation of students for the instructors and the courses they teach stand out, and a second moment in which students become more demanding and dissatisfied with the courses and with the instructors, leading to a lack of motivation and involvement of students

Pineapple quality in a traditional cultivation system in different soil classes

Pineapple (Ananas comosus (L.) Merril) is considered one of the most important fruits of the tropical and subtropical regions, and the third most-produced in the world due to its high commercial expansion in the world market, in recent years. Therefore, this work aimed to evaluate the influence of landscape position on pineapple quality. The work was developed at the Providência Farm, located in the municipality of Miracema do Tocantins. The following soil parameters were evaluated: hydraulic conductivity - KS, soil bulk density – DS, and total porosity – TP, as well as the following quality attributes: titratable acidity - TA, length and diameter of infructescences, total fresh mass - TM, fresh mass of infructescences – IM, and soluble solids – SS. The analyses were performed at the Agri-Environmental Laboratory of the Agricultural Sciences Complex of the Federal University of Tocantins. Less massive infructescences developed on more porous soils. The variation in the mass of infructescences is not associated with soil types, but rather with soil porosity. Soils with higher KS tend to increase the chances of producing infructescences with high acidity and high levels of soluble solids. The DS did not result in a significant association with the pineapple quality attributes. The infructescences were not affected by the landscape position. No position in the landscape influenced fruit quality. In general, the infructescences showed low acidity and low levels of soluble solids, with length and diameter of infructescences below the standard of the cultivar ‘Pérola’.Pineapple (Ananas comosus (L.) Merril) is considered one of the most important fruits of the tropical and subtropical regions, and the third most-produced in the world due to its high commercial expansion in the world market, in recent years. Therefore, this work aimed to evaluate the influence of landscape position on pineapple quality. The work was developed at the Providência Farm, located in the municipality of Miracema do Tocantins. The following soil parameters were evaluated: hydraulic conductivity - KS, soil bulk density – DS, and total porosity – TP, as well as the following quality attributes: titratable acidity - TA, length and diameter of infructescences, total fresh mass - TM, fresh mass of infructescences – IM, and soluble solids – SS. The analyses were performed at the Agri-Environmental Laboratory of the Agricultural Sciences Complex of the Federal University of Tocantins. Less massive infructescences developed on more porous soils. The variation in the mass of infructescences is not associated with soil types, but rather with soil porosity. Soils with higher KS tend to increase the chances of producing infructescences with high acidity and high levels of soluble solids. The DS did not result in a significant association with the pineapple quality attributes. The infructescences were not affected by the landscape position. No position in the landscape influenced fruit quality. In general, the infructescences showed low acidity and low levels of soluble solids, with length and diameter of infructescences below the standard of the cultivar ‘Pérola’

Evaluating face2gene as a tool to identify cornelia de lange syndrome by facial phenotypes

Characteristic or classic phenotype of Cornelia de Lange syndrome (CdLS) is associated with a recognisable facial pattern. However, the heterogeneity in causal genes and the presence of overlapping syndromes have made it increasingly difficult to diagnose only by clinical features. DeepGestalt technology, and its app Face2Gene, is having a growing impact on the diagnosis and management of genetic diseases by analysing the features of affected individuals. Here, we performed a phenotypic study on a cohort of 49 individuals harbouring causative variants in known CdLS genes in order to evaluate Face2Gene utility and sensitivity in the clinical diagnosis of CdLS. Based on the profile images of patients, a diagnosis of CdLS was within the top five predicted syndromes for 97.9% of our cases and even listed as first prediction for 83.7%. The age of patients did not seem to affect the prediction accuracy, whereas our results indicate a correlation between the clinical score and affected genes. Furthermore, each gene presents a different pattern recognition that may be used to develop new neural networks with the goal of separating different genetic subtypes in CdLS. Overall, we conclude that computer-assisted image analysis based on deep learning could support the clinical diagnosis of CdLS.Spanish Ministry of Science, Innovation and Universities/State Research Agency RTC-2017-6494-1; RTI2018-094434-B-I00 (MCIU/AEI/FEDER, UE) to P.G.-P.; Diputación General de Aragón - FEDER: European Social Fund [Grupo de Referencia B32_17R, to J.P.] as well as funds from the European JPIAMR-VRI network “CONNECT” to P.G.-P.; Medical Faculty of the University of Lübeck J09-2017 to I. P.; German Federal Ministry of Education and Research (BMBF

Heart disease characterization and myocardial strain analysis in patients with PACS1 Neurodevelopmental Disorder

Background: PACS1 neurodevelopmental disorder (PACS1-NDD) (MIM# 615009) is a rare autosomal dominant disease characterized by neurodevelopmental delay, dysmorphic facial features, and congenital malformations. Heart disease (HD) is frequently present in individuals with PACS1-NDD, but a compressive review of these anomalies and an evaluation of cardiac function in a cohort of patients are lacking. Methods: (i) Cardiac evaluation in 11 PACS1-NDD patients was conducted using conventional echocardiography. (ii) Heart function was assessed by tissue Doppler imaging, and two-dimensional speckle tracking was performed in seven patients and matched controls. (iii) This systematic review focused on determining HD prevalence in individuals with PACS1-NDD. Results: In our cohort, 7 of 11 patients presented HD. (Among them, three cases of ascending aortic dilatation (AAD) were detected and one mitral valve prolapse (MVP).) None of the patients showed echocardiographic pathological values, and the left global longitudinal strain was not significantly different between patients and controls (patients −24.26 ± 5.89% vs. controls −20.19 ± 1.75%, p = 0.3176). In the literature review, almost 42% (42/100) of individuals with PACS1-NDD reportedly experienced HD. Septal defects were the most common malformation, followed by patent ductus arteriosus. Conclusions: Our results show a high prevalence of HD in PACS1-NDD patients; in this way, AAD and MVP are reported for the first time in this syndrome. Furthermore, a detailed cardiac function evaluation in our cohort did not reveal evidence of cardiac dysfunction in individuals with PACS1-NDD. Cardiology evaluation should be included for all individuals with Schuurs-Hoeijmakers syndrome

Things are not always what they seem: From Cornelia de Lange to KBG phenotype in a girl with genetic variants in NIPBL and ANKRD11.

post-print509 K

Detection of Trypanosoma cruzi DTUs TcI and TcIV in two outbreaks of orally-transmitted Chagas disease in the Northern region of Brazi

This study describes the laboratory investigation of two acute Chagas disease outbreaks that occurred in the riverside communities of Marimarituba and Cachoeira do Arua, in the Santarem municipality, Para State, located in the Northern region of Brazil, and occurred in March 2016 and August 2017, respectively. The generation of data regarding the diversity of Trypanosoma cruzi parasites circulating in the Amazon region is key for understanding the emergence and expansion of Chagas disease. This study aimed to identify T. cruzi Discrete Typing Units (DTUs) involved in two outbreaks of acute Chagas disease (ACD) directly from the patient’s biological sample. Nested and multiplex PCR targeting the 24Sα (rRNA) and mini-exon genes, respectively, were used to identify T. cruzi DTU in blood samples from patients diagnosed with ACD. The samples with positive cPCR were submitted for analysis for T. cruzi DTUs, which included 13 samples from the patients with ACD by oral transmission and two samples collected from two newborns of two women with ACD, from Marimarituba and Cachoeira do Arua. The samples were classified as T. cruzi TcIV, from Marimarituba’s outbreak, and T. cruzi TcI, from Cachoeira do Arua’s outbreak. The molecular identification of T. cruzi may increase understanding of the role of this parasite in Chagas disease’s emergence within the Amazon region, contributing to the improvement of the management of this important, but also neglected, diseas

Evaluating Face2Gene as a Tool to Identify Cornelia de Lange Syndrome by Facial Phenotypes

Characteristic or classic phenotype of Cornelia de Lange syndrome (CdLS) is associated with a recognisable facial pattern. However, the heterogeneity in causal genes and the presence of overlapping syndromes have made it increasingly difficult to diagnose only by clinical features. DeepGestalt technology, and its app Face2Gene, is having a growing impact on the diagnosis and management of genetic diseases by analysing the features of affected individuals. Here, we performed a phenotypic study on a cohort of 49 individuals harbouring causative variants in known CdLS genes in order to evaluate Face2Gene utility and sensitivity in the clinical diagnosis of CdLS. Based on the profile images of patients, a diagnosis of CdLS was within the top five predicted syndromes for 97.9% of our cases and even listed as first prediction for 83.7%. The age of patients did not seem to affect the prediction accuracy, whereas our results indicate a correlation between the clinical score and affected genes. Furthermore, each gene presents a different pattern recognition that may be used to develop new neural networks with the goal of separating different genetic subtypes in CdLS. Overall, we conclude that computer-assisted image analysis based on deep learning could support the clinical diagnosis of CdL