The effect of COVID-19 on transplant function and development of CLAD in lung transplant patients:A multicenter experience

Background : Concerns have been raised on the impact of coronavirus disease (COVID-19) on lung transplant (LTx) patients. The aim of this study was to evaluate the transplant function pre- and post-COVID-19 in LTx patients. Methods : Data were retrospectively collected from LTx patients with confirmed COVID-19 from all 3 Dutch transplant centers, between February 2020 and September 2021. Spirometry results were collected pre-COVID-19, 3- and 6-months post infection. Results : Seventy-four LTx patients were included. Forty-two (57%) patients were admitted, 19 (26%) to the intensive care unit (ICU). The in-hospital mortality was 20%. Twelve out of 19 ICU patients died (63%), a further 3 died on general wards. Patients with available spirometry (78% at 3 months, 65% at 6 months) showed a significant decline in mean forced expiratory volume in 1 second (FEV1) (ΔFEV1 138 ± 39 ml, p = 0.001), and forced vital capacity (FVC) (ΔFVC 233 ±74 ml, p = 0.000) 3 months post infection. Lung function improved slightly from 3 to 6 months after COVID-19 (ΔFEV1 24 ± 38 ml; ΔFVC 100 ± 46 ml), but remained significantly lower than pre-COVID-19 values (ΔFEV1 86 ml ± 36 ml, p = 0.021; ΔFVC 117 ± 35 ml, p = 0.012). FEV1/FVC was > 0.70. Conclusions: In LTx patients COVID-19 results in high mortality in hospitalized patients. Lung function declined 3 months after infection and gradually improved at 6 months, but remained significantly lower compared to pre-COVID-19 values. The more significant decline in FVC than in FEV1 and FEV1/FVC > 70%, suggested a more restrictive pattern

A chemical survey of exoplanets with ARIEL

Thousands of exoplanets have now been discovered with a huge range of masses, sizes and orbits: from rocky Earth-like planets to large gas giants grazing the surface of their host star. However, the essential nature of these exoplanets remains largely mysterious: there is no known, discernible pattern linking the presence, size, or orbital parameters of a planet to the nature of its parent star. We have little idea whether the chemistry of a planet is linked to its formation environment, or whether the type of host star drives the physics and chemistry of the planet’s birth, and evolution. ARIEL was conceived to observe a large number (~1000) of transiting planets for statistical understanding, including gas giants, Neptunes, super-Earths and Earth-size planets around a range of host star types using transit spectroscopy in the 1.25–7.8 μm spectral range and multiple narrow-band photometry in the optical. ARIEL will focus on warm and hot planets to take advantage of their well-mixed atmospheres which should show minimal condensation and sequestration of high-Z materials compared to their colder Solar System siblings. Said warm and hot atmospheres are expected to be more representative of the planetary bulk composition. Observations of these warm/hot exoplanets, and in particular of their elemental composition (especially C, O, N, S, Si), will allow the understanding of the early stages of planetary and atmospheric formation during the nebular phase and the following few million years. ARIEL will thus provide a representative picture of the chemical nature of the exoplanets and relate this directly to the type and chemical environment of the host star. ARIEL is designed as a dedicated survey mission for combined-light spectroscopy, capable of observing a large and well-defined planet sample within its 4-year mission lifetime. Transit, eclipse and phase-curve spectroscopy methods, whereby the signal from the star and planet are differentiated using knowledge of the planetary ephemerides, allow us to measure atmospheric signals from the planet at levels of 10–100 part per million (ppm) relative to the star and, given the bright nature of targets, also allows more sophisticated techniques, such as eclipse mapping, to give a deeper insight into the nature of the atmosphere. These types of observations require a stable payload and satellite platform with broad, instantaneous wavelength coverage to detect many molecular species, probe the thermal structure, identify clouds and monitor the stellar activity. The wavelength range proposed covers all the expected major atmospheric gases from e.g. H2O, CO2, CH4 NH3, HCN, H2S through to the more exotic metallic compounds, such as TiO, VO, and condensed species. Simulations of ARIEL performance in conducting exoplanet surveys have been performed – using conservative estimates of mission performance and a full model of all significant noise sources in the measurement – using a list of potential ARIEL targets that incorporates the latest available exoplanet statistics. The conclusion at the end of the Phase A study, is that ARIEL – in line with the stated mission objectives – will be able to observe about 1000 exoplanets depending on the details of the adopted survey strategy, thus confirming the feasibility of the main science objectives.Peer reviewedFinal Published versio

Age at first birth in women is genetically associated with increased risk of schizophrenia

Prof. Paunio on PGC:n jäsenPrevious studies have shown an increased risk for mental health problems in children born to both younger and older parents compared to children of average-aged parents. We previously used a novel design to reveal a latent mechanism of genetic association between schizophrenia and age at first birth in women (AFB). Here, we use independent data from the UK Biobank (N = 38,892) to replicate the finding of an association between predicted genetic risk of schizophrenia and AFB in women, and to estimate the genetic correlation between schizophrenia and AFB in women stratified into younger and older groups. We find evidence for an association between predicted genetic risk of schizophrenia and AFB in women (P-value = 1.12E-05), and we show genetic heterogeneity between younger and older AFB groups (P-value = 3.45E-03). The genetic correlation between schizophrenia and AFB in the younger AFB group is -0.16 (SE = 0.04) while that between schizophrenia and AFB in the older AFB group is 0.14 (SE = 0.08). Our results suggest that early, and perhaps also late, age at first birth in women is associated with increased genetic risk for schizophrenia in the UK Biobank sample. These findings contribute new insights into factors contributing to the complex bio-social risk architecture underpinning the association between parental age and offspring mental health.Peer reviewe

The effects of digital learning material on students’ mathematics learning in vocational education.

This study investigates the e ects of Digital Learning Material (DLM) including instructional clips, online guidance, structuring of content, and a col- laboration tool on students’ mathematics learning in Dutch vocational education. A pretest–posttest design was used. Apprenticeship students were asked to com- plete assignments and to discuss them with their peers and the online teacher. The results showed that DLM can enhance students’ mathematics learning in vocational education. The learning enhancement was mostly due to the use of instructional clips and structuring of the content of the mathematics tasks. Elaborations of these results, implications, limitations and recommendations for further research are provided

The effects of computer-based virtual learning environments on nursing students’ mathematical learning in medication processes

Computer-based virtual learning environments (CBVLEs) are potentially useful teaching tools for training nursing students in professional duties such as the mathematical tasks associated with medication processes. In this study, a CBVLE was designed with well-structured instructional activities such as interleaved practice and feedback. Mathematical medication scenarios and basic arithmetic exercises were integrated into the CBVLE. Four training conditions were used in the CBVLE to facilitate extra support for mathematical medication learning: (1) learning without worked examples, (2) learning with worked examples involving domain-specific knowledge, (3) learning with worked examples involving regular thinking strategies, and (4) learning with combined worked examples. This study was conducted with 118 nursing students enrolled in post-secondary nursing education and Bachelor’s nursing programmes. Students were pre-tested and post-tested on their mathematical medication learning. Training in the CBVLE improved mathematical medication learning for all students from pre-test to the post-test stages, but no differences were found among the four different conditions. Nursing students’ prior knowledge, non-verbal intelligence, and number of correct tasks predicted mathematical medication learning outcomes. When controlling for non-verbal intelligence, students in the condition 1 benefited more than students in condition 3 in terms of their mathematical medication learning outcomes. The same accounted for the support of the low-achieving students in the CBVLE. The support conditions for the high-achieving group appeared to be unimportant for mathematical medication learning. It seems that technology is taken over some of the capacity of working memory, which accounts for the benefits to the low-achieving learners

Nursing students’ satisfaction with the instructional design of a computer-based virtual learning environment for mathematical medication learning

Computer-based virtual learning environments (CBVLEs) have attracted attention as a learning innovation that can foster students’ self-efficacy and intrinsic motivation. Research on the instructional design regarding these aspects of learning in a virtual learning environment is rather piecemeal. This study investigates the instructional design of a CBVLE for mathematical medication learning by nursing students in vocational education. The instructional design was based on a task-centered approach, and students’ future learning tasks formed the backbone. We examine the extent to which the CBVLE fostered the nursing students’ mathematical learning, self-efficacy, and intrinsic motivation, and the ways in which the design components of the CBVLE met nursing students’ satisfaction. In total, 118 nursing students were assigned to four groups, with or without extra support from worked examples, and were trained via the CBVLE on mathematical medication learning tasks over four consecutive weeks. Students were pre- and post-tested on their mathematical medication learning, self-efficacy, and intrinsic motivation. Students also rated their satisfaction with the instructional design. Our results showed that the CBVLE fostered nursing students’ mathematical medication learning, self-efficacy, and intrinsic motivation, but no significant differences were found between the four conditions. Overall, student satisfaction was above average. The design components were able to predict nursing students’ mathematical medication learning, self-efficacy, and intrinsic motivation

The effects of computer-based virtual learning environments on nursing students’ mathematical learning in medication processes

Computer-based virtual learning environments (CBVLEs) are potentially useful teaching tools for training nursing students in professional duties such as the mathematical tasks associated with medication processes. In this study, a CBVLE was designed with well-structured instructional activities such as interleaved practice and feedback. Mathematical medication scenarios and basic arithmetic exercises were integrated into the CBVLE. Four training conditions were used in the CBVLE to facilitate extra support for mathematical medication learning: (1) learning without worked examples, (2) learning with worked examples involving domain-specific knowledge, (3) learning with worked examples involving regular thinking strategies, and (4) learning with combined worked examples. This study was conducted with 118 nursing students enrolled in post-secondary nursing education and Bachelor’s nursing programmes. Students were pre-tested and post-tested on their mathematical medication learning. Training in the CBVLE improved mathematical medication learning for all students from pre-test to the post-test stages, but no differences were found among the four different conditions. Nursing students’ prior knowledge, non-verbal intelligence, and number of correct tasks predicted mathematical medication learning outcomes. When controlling for non-verbal intelligence, students in the condition 1 benefited more than students in condition 3 in terms of their mathematical medication learning outcomes. The same accounted for the support of the low-achieving students in the CBVLE. The support conditions for the high-achieving group appeared to be unimportant for mathematical medication learning. It seems that technology is taken over some of the capacity of working memory, which accounts for the benefits to the low-achieving learners

Effects of Digital Learning Materials on nursing students’ mathematics learning, self-efficacy, and task value in vocational education

The use of digital environments in nursing education offers new opportunities for nursing students' medical mathematics learning. The aim of this study was to investigate the effects of Digital Learning Materials (DLMs) on nursing students' mathematics learning, self-efficacy, and task value. A pre-test/post-test control group design was used. Students were assigned to the DLMs group (experimental condition) or the face-to-face group (control condition). Students in both conditions completed the same assignments and discussed these with their peers and the (online) teacher via the discussion board or in the classroom setting. The results showed that the mathematics learning of students undergoing DLMs training and of those undergoing face-to-face training improved from the pretest to the post-test, but no significant differences were found between the two conditions. A significant interaction effect between condition and self-efficacy was reported, producing a large reduction in the self-efficacy of students in the DLMs condition and a small reduction in the self-efficacy of students in the face-to-face condition. No significant differences were found for students' task value. The study offers new insights for the future design of mathematics training with DLMs, focusing on students’ appreciation of DLMs features, considering students with low and high learning abilities separately.</p

Effects of Digital Learning Materials on nursing students’ mathematics learning, self-efficacy, and task value in vocational education

The use of digital environments in nursing education offers new opportunities for nursing students' medical mathematics learning. The aim of this study was to investigate the effects of Digital Learning Materials (DLMs) on nursing students' mathematics learning, self-efficacy, and task value. A pre-test/post-test control group design was used. Students were assigned to the DLMs group (experimental condition) or the face-to-face group (control condition). Students in both conditions completed the same assignments and discussed these with their peers and the (online) teacher via the discussion board or in the classroom setting. The results showed that the mathematics learning of students undergoing DLMs training and of those undergoing face-to-face training improved from the pretest to the post-test, but no significant differences were found between the two conditions. A significant interaction effect between condition and self-efficacy was reported, producing a large reduction in the self-efficacy of students in the DLMs condition and a small reduction in the self-efficacy of students in the face-to-face condition. No significant differences were found for students' task value. The study offers new insights for the future design of mathematics training with DLMs, focusing on students’ appreciation of DLMs features, considering students with low and high learning abilities separately.</p

The effects of computer-based virtual learning environments on nursing students’ mathematical learning in medication processes

Computer-based virtual learning environments (CBVLEs) are potentially useful teaching tools for training nursing students in professional duties such as the mathematical tasks associated with medication processes. In this study, a CBVLE was designed with well-structured instructional activities such as interleaved practice and feedback. Mathematical medication scenarios and basic arithmetic exercises were integrated into the CBVLE. Four training conditions were used in the CBVLE to facilitate extra support for mathematical medication learning: (1) learning without worked examples, (2) learning with worked examples involving domain-specific knowledge, (3) learning with worked examples involving regular thinking strategies, and (4) learning with combined worked examples. This study was conducted with 118 nursing students enrolled in post-secondary nursing education and Bachelor’s nursing programmes. Students were pre-tested and post-tested on their mathematical medication learning. Training in the CBVLE improved mathematical medication learning for all students from pre-test to the post-test stages, but no differences were found among the four different conditions. Nursing students’ prior knowledge, non-verbal intelligence, and number of correct tasks predicted mathematical medication learning outcomes. When controlling for non-verbal intelligence, students in the condition 1 benefited more than students in condition 3 in terms of their mathematical medication learning outcomes. The same accounted for the support of the low-achieving students in the CBVLE. The support conditions for the high-achieving group appeared to be unimportant for mathematical medication learning. It seems that technology is taken over some of the capacity of working memory, which accounts for the benefits to the low-achieving learners