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Abstract While Cystic Fibrosis is characterized by a high phenotypic variability, a correlation is reported between the pancreatic status and the CFTR genotype. Here we report an unusual case of a child with Cystic Fibrosis (F508del-duplication of exons 1–3 genotype) diagnosed at 8 years old for pancreatic insufficiency and non-pathological sweat test, in absence of respiratory symptoms and acute episodes of pancreatitis. Nasal potential differences and intestinal current measurements were normal, while the short-circuit current measured on patient-derived colonoids grown on Transwell® indicated the presence of a reduced CFTR-dependent current relative to non-CF colonoids with, a modest improvement of CFTR activity record following treatment with elexacaftor/tezacaftor/ivacaftor. This case opens the discussion on the importance of performing CFTR sequencing and the search for large gene rearrangements in cases of pancreatic insufficiency of unclear etiology, also in the presence of non-pathological sweat test. Children with CF and non-pathological sweat chloride are likely to develop higher concentrations if they truly have CF.

Short-form development is an important topic in psychometric research, which requires researchers to face methodological choices at different steps. The statistical techniques traditionally used for shortening tests, which belong to the so-called exploratory model, make assumptions not always verified in psychological data. This article proposes a machine learning-based autonomous procedure for short-form development that combines explanatory and predictive techniques in an integrative approach. The study investigates the item-selection performance of two autoencoders: a particular type of artificial neural network that is comparable to principal component analysis. The procedure is tested on artificial data simulated from a factor-based population and is compared with existent computational approaches to develop short forms. Autoencoders require mild assumptions on data characteristics and provide a method to predict long-form items' responses from the short form. Indeed, results show that they can help the researcher to develop a short form by automatically selecting a subset of items that better reconstruct the original item's responses and that preserve the internal structure of the long-form.

During the COVID-19 pandemic, many workers have been forced to work from home. In this situation, the boundaries between work and private life have become particularly blurred, and recovering from work was even more difficult than in traditional times, with negative consequences for workers' health. Among the psychological experiences that might underlie the recovery process, mastery played a crucial role as people sought new stimuli and challenging situations. However, there are few articles that have explored the role of this specific recovery experience, its antecedents, and the health consequences under conditions of work from home. Therefore, in this multiwave study, we aimed to investigate the role of mastery as a mediator between supervisor support and insomnia problems. The study was conducted during the COVID-19 pandemic in Italy and had a three-wave design. A convenience sample of 130 employees (67% women) completed an online questionnaire. Hypotheses were tested using a three-wave autoregressive cross-lagged panel model. According to the results, supervisor support at Time 1 was positively related to mastery at Time 2, which in turn showed a negative association with insomnia at Time 3. The results demonstrated that mastery experiences have played a crucial role during COVID-19 mandatory work from home, which points to some potential implications for workers' health in the adoption of teleworking beyond the emergency situation.

Deep-seated gravitational slope deformations (DSGSDs) consist of gravity-induced, large-scale, gradual rock mass movements. In the Aosta Valley region (Valle d’Aosta NW Italy), DSGDs affect wide valley slopes and produce several interconnected morpho-structures that involve bedrock and Quaternary cover. Some DSGSD effects are not visible at the surface because of subglacial abrasion or burial by sediments and, therefore, are difficult to map with standard geomorphological surveys. This is the case for the Pointe Leysser DSGSD in the Aosta Valley, which is heavily influenced by the historical movements of the Verrogne-Clusellaz Glacier and its tributaries. We conducted a new geological investigation, integrated with deep electrical resistivity tomography geophysical surveys (ERTs). The ERT results were initially compared with geological/geomorphological evidence at the surface to define the correlation between the values and spatial distributions of electrical resistivity and the sediments, rocks, or morpho-structures. The resistivity values at various depths were subsequently analysed, interpreted, and discussed in conjunction with geological hypotheses. The geological and geophysical survey revealed three wide buried glacial valleys filled with glacial sediments and mapped the locations of gravitational morpho-structures at depth. These new data allowed us to draw a relationship between glacialism and gravitational evolution, distinguishing between pre-singlacial movements and postglacial movements.

Abstract Background Recurrent respiratory infections are a leading cause of morbidity and mortality in persons with Cystic Fibrosis (pwCF). Recently, the emergence of Nocardia species as a potential pathogen in CF has raised questions about its role and management, as its clinical significance and the optimal patient management remain unclear in current clinical practice. This review explores the clinical implications of Nocardia species in patients with Cystic Fibrosis (pwCF) through a comprehensive literature review. Key objectives include assessing its impact on lung function, identifying colonization risk factors, and evaluating an appropriate treatment. Methods The literature review, conducted until June 30, 2023, from databases like MEDLINE, PubMed, Embase, and Cochrane, included 16 articles involving 89 pwCF with Nocardia species isolation according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guideline recommendations. Articles reporting Nocardia prevalence and symptoms based on original data in adult and paediatric pwCF were included. All the retrieved studies were observational ones, thus, they were categorized by study type as case report and case series. Results Overall 89 pwCF and Nocardia species isolation were included: 42 children and 47 adults. Where reported, we found these main following bacterial species: Nocardia asteroides (35%, 23/64), Nocardia farcinica (21%, 14/64), Nocardia tranvalensis (13%, 8/64) and Nocardia cyriacigeorgica (11%, 7/64). A co-infection was reported in 85% of patients (61/72). Of patients whose lung function was reported before and after Nocardia isolation, 23% (16/68) showed a decline in FEV1. Above all, 82 patients were treated at least once after isolation of Nocardia strain. In 93% (77/82) of cases, treatment was started immediately upon isolation. Antibiotic treatment was performed per os or intravenously depending on the clinical condition of the individual patient. Nocardia eradication was attempted in only 32 cases out of 82, and 78% (25/32) of these patients were successfully eradicated after one or more courses of antibiotics. Death was reported in 3 patients, 2 of which were children. Conclusion In general the isolation of the bacteria does not necessarily imply therapy, but patients need to be monitored closely to assess the possible occurrence of active infection. The treatment seems to be indicated in patients showing lung involvement with the possible appearance of pneumonia, pleural effusion, fever, cough, or a decrease in FEV1, as in the case that we described, or in patients undergoing pulmonary transplantation.

In this paper, we consider the long-term behavior of some special solutions to the Wave Kinetic Equation. This equation provides a mesoscopic description of wave systems interacting nonlinearly via the cubic NLS equation. Escobedo and Velázquez showed that, starting with initial data given by countably many Dirac masses, solutions remain a linear combination of countably many Dirac masses at all times. Moreover, there is convergence to a single Dirac mass at long times. The first goal of this paper is to give quantitative rates for the speed of said convergence. In order to study the optimality of the bounds we obtain, we introduce and analyze a toy model accounting only for the leading order quadratic interactions.

Emotional dysregulation involving anger can have severe consequences on the individual’s psychosocial and emotional functioning. This study aimed to investigate the role that the companion animal bond and the personality dimension of trait anger play in explaining affective dysregulation. A cross-sectional online survey was administered to 365 participants. Using the PROCESS macro for SPSS, a moderated model was tested to analyze the hypothesis that affective dysregulation depends on trait anger and that the companion animal bond moderates the relationship between trait anger and affective dysregulation. The results showed that the effect of trait anger on affective dysregulation increases especially when the degree of bonding to an animal companion is low, suggesting that a strong bond to a companion animal may protect individuals with trait anger from the likelihood of experiencing affective regulation problems. The psychological, health-related, and educational implications of the current anthrozoological study include the potential of the human–animal bond in acting as a facilitator of adaptive affective regulation processes, which can reduce the levels of uncontrolled anger-related emotions and the subsequent risk of out-of-control behaviors.

IntroductionMissing data in psychometric research presents a substantial challenge, impacting the reliability and validity of study outcomes. Various factors contribute to this issue, including participant non-response, dropout, or technical errors during data collection. Traditional methods like mean imputation or regression, commonly used to handle missing data, rely upon assumptions that may not hold on psychological data and can lead to distorted results.MethodsThis study aims to evaluate the effectiveness of transformer-based deep learning for missing data imputation, comparing ReMasker, a masking autoencoding transformer model, with conventional imputation techniques (mean and median imputation, Expectation–Maximization algorithm) and machine learning approaches (K-nearest neighbors, MissForest, and an Artificial Neural Network). A psychometric dataset from the COVID distress repository was used, with imputation performance assessed through the Root Mean Squared Error (RMSE) between the original and imputed data matrices.ResultsResults indicate that machine learning techniques, particularly ReMasker, achieve superior performance in terms of reconstruction error compared to conventional imputation techniques across all tested scenarios.DiscussionThis finding underscores the potential of transformer-based models to provide robust imputation in psychometric research, enhancing data integrity and generalizability.

Introduction: We investigated Quality of Life (QOL) in a sample of individuals (n = 341) who experienced different consequences in terms of displacement from their house after earthquake. Methods: Three groups were studied: those who had been displaced but are no longer so, those still displaced, and those who were never displaced. QOL for four time points was assessed: pre-earthquake, during displacement, at the time of the survey, and in ten years. Results: Different trajectories of QOL were observed in the three groups: not displaced individuals showed no significant variation, those who were displaced had a significant decline in QOL after the earthquake but a significant recovery after the displacement experience, and those who were still displaced at the time of the survey reported lowest QOL both after the earthquake and in the future, with no recovery. Predictors of perceived QOL decline were quality and type of temporary accommodation, place attachment, and perceived health impairment. Subsequent QOL perceived improvement was predicted by quality and type of temporary accommodation, risk awareness, and emotional well-being. Discussion: Our findings highlight the importance of minimizing the duration of temporary displacement and providing high-quality temporary accommodations, considering individual needs in the local contexts and communities.

The Safe System Approach is an evidence-based strategy committed to eliminating fatalities and serious injuries among all road users. The Safe System Approach as developed in Sweden, acknowledges that human errors will occur, but the cost of these mistakes should not be death or serious injury. Technology is an integral component of the Safe System Approach and can address equity and reduce human error among other safety benefits. A literature review will be conducted to compare high-income countries leveraging the Safe System Approach and assess opportunities for technology interventions in low- and middle-income contexts. Evidence will be analyzed, as well as implementation considerations of the recent National adoption of the Safe System Approach in the United States. As SSA evolves in a global context, further evaluation is needed on the role of technology and how government policies can restrict or advance its implementation.

Abstract Background Bangladesh has a shortfall of health professionals. The World Health Organization states that improving education will increase recruitment and retention of health workers. Traditional learning approaches, in medical education particularly, focus on didactic teaching, teaching of subjects and knowledge testing. These approaches have been superseded in some programmes, with a greater focus on active learning, integrated teaching and learning of knowledge, application, skills and attitudes or values and associated testing of competencies as educational outcomes. In addition, some regions do not have continuous professional development or clinical placements for health worker students, contributing to difficulties in retention of health workers. This study aims to explore the experiences of health professional education in Bangladesh, focusing on what is through observation of health professional education sessions and experiences of educators. Methods This mixed method study included 22 observations of teaching sessions in clinical and educational settings, detailed analysis of 8 national curricula documents mapped to Global Competency and Outcomes Framework for Universal Health Coverage and 15 interviews of professionals responsible for health education. An observational checklist was created based on previous literature which assessed training of within dimensions of basic clinical skills; diagnosis and management; professionalism; professional development; and effective communication. Interviews explored current practices within health education in Bangladesh, as well as barriers and facilitators to incorporating different approaches to learning. Results Observations revealed a variety of approaches and frameworks followed across institutions. Only one observation included all sub-competencies of the checklist. National curricula documents varied in their coverage of the Global Competency and Outcomes Framework domains. Three key themes were generated from a thematic analysis of interview transcripts: (1) education across the career span; (2) challenges for health professional education; (3) contextual factors and health professional education. Opportunities for progression and development post qualification are limited and certain professions are favoured over others. Conclusion Traditional approaches seem to predominate but there is some enthusiasm for a more clinical focus to education and for more competency based approaches to teaching, learning and assessment.

BackgroundHealth outcomes are significantly influenced by unmet social needs. Although screening for social needs has become common in health care settings, there is often poor linkage to resources after needs are identified. The structural barriers (eg, staffing, time, and space) to helping address social needs could be overcome by a technology-based solution. ObjectiveThis study aims to present the design and evaluation of a chatbot, DAPHNE (Dialog-Based Assistant Platform for Healthcare and Needs Ecosystem), which screens for social needs and links patients and families to resources. MethodsThis research used a three-stage study approach: (1) an end-user survey to understand unmet needs and perception toward chatbots, (2) iterative design with interdisciplinary stakeholder groups, and (3) a feasibility and usability assessment. In study 1, a web-based survey was conducted with low-income US resident households (n=201). Following that, in study 2, web-based sessions were held with an interdisciplinary group of stakeholders (n=10) using thematic and content analysis to inform the chatbot’s design and development. Finally, in study 3, the assessment on feasibility and usability was completed via a mix of a web-based survey and focus group interviews following scenario-based usability testing with community health workers (family advocates; n=4) and social workers (n=9). We reported descriptive statistics and chi-square test results for the household survey. Content analysis and thematic analysis were used to analyze qualitative data. Usability score was descriptively reported. ResultsAmong the survey participants, employed and younger individuals reported a higher likelihood of using a chatbot to address social needs, in contrast to the oldest age group. Regarding designing the chatbot, the stakeholders emphasized the importance of provider-technology collaboration, inclusive conversational design, and user education. The participants found that the chatbot’s capabilities met expectations and that the chatbot was easy to use (System Usability Scale score=72/100). However, there were common concerns about the accuracy of suggested resources, electronic health record integration, and trust with a chatbot. ConclusionsChatbots can provide personalized feedback for families to identify and meet social needs. Our study highlights the importance of user-centered iterative design and development of chatbots for social needs. Future research should examine the efficacy, cost-effectiveness, and scalability of chatbot interventions to address social needs.

The Lac Fallère area in the upper Clusellaz Valley (tributary of the middle Aosta Valley) is shaped in micaschist and gneiss (Mont Fort Unit, Middle Penninic) and in calcschist and marble (Aouilletta Unit, Combin Zone). Lac Fallère exhibits an elongated shape and is hosted in a WSW–ENE-trending depression, according to the slope direction. This lake also shows a semi-submerged WSW–ENE rocky ridge that longitudinally divides the lake. This evidence, in addition to the extremely fractured rocks, indicates a wide, deep-seated gravitational slope deformation (DSGSD), even if this area is not yet included within the regional landslide inventory of the Aosta Valley Region. The Lac Fallère area also shows reliefs involved in glacial erosion (roches moutonnée), an extensive cover of subglacial sediments, and many moraines essentially referred to as Lateglacial. The DSGSD evolution in a glacial environment produced, as observed in other areas, effects on the facies of Quaternary sediments and the formation of a lot of wide moraines. Glacial slope sectors and lateral moraines displaced by minor scarps and counterscarps, and glaciers using trenches forming several arched moraines, suggest an interplay between glacial and gravitational processes, which share part of their evolution history.

This study examined the factors that contributed to ePortfolio persistence in an online program from data collected in 2016 (Thibodeaux, Harapnuik, & Cummings, 2017) and again in 2018. A myriad of research points to learning portfolios as having transformational power; however, many traditional instructional models that use ePortfolios in higher education downplay the significance and transformational learning that effective ePortfolios offer. To research this phenomenon, a convergent, parallel mixed-methods design was used to gather data from an online program in order to explore the learning conditions and context of ePortfolio usage over multiple years. Results indicated that real-world projects and authentic artifacts, the ePortfolio used as a career tool, and management of the ePortfolio were common factors identified in studies that contributed to continued use of the ePortfolio. Findings also revealed that learner autonomy, control, and agency, as well as continued opportunities for choice and voice, led to increased appreciation and ownership of the ePortfolio beyond the program of study.