Fundació Privada Centre CIM

ABSTRACT Background Fingerprint patterns are developed during pregnancy and share a common embryogenic origin with the central nervous system. Considering the observed relationship between prenatal abnormalities and higher risk for schizophrenia, we previously built fingerprint‐based algorithms achieving validation accuracies up to 70% in a large sample of patients with schizophrenia. In this new study, we apply them to a sample of patients with bipolar disorder. Methods Besides validating the developed algorithms with an independent sample of fingerprints from N = 127 patients with schizophrenia and N = 116 healthy controls, here we applied them to a sample of N = 118 bipolar disorder patients. Scores from a premorbid IQ scale were also obtained from all participants, and the link between these scores and the algorithm outcomes was analyzed. Results The initial validation provided balanced accuracies similar to those of the original study (57%–68%). When applied to subjects with bipolar disorder (against healthy individuals), algorithms also showed significant predictive power (accuracies: 55%–68%). Consequently, the capacity to discriminate between schizophrenia and bipolar disorder was poor (accuracies: 47%–57%). Regression analyses between averaged probabilities and premorbid IQ scores were significant in schizophrenia (r = −0.184; p = 0.041) and in the whole sample (r = −0.159; p = 0.002). Conclusions Algorithms were predictive of bipolarity, highlighting the existence of fingerprint abnormalities also in bipolar disorder. In addition, the observed associations with premorbid IQ underline the neurodevelopmental origin of fingerprint patterns and suggest the potential use of fingerprints for prediction in other neurodevelopmental disorders. The lack of specificity with the diagnosis of schizophrenia, though, points to the need for new algorithms for differential diagnosis in psychosis.

ABSTRACTIntroductionA strong nurse–patient therapeutic relationship is crucial in acute mental health care yet remains challenging, potentially affecting outcomes and perceived quality of care. Interventions that foster structured, person‐centred encounters may address these challenges effectively.AimTo evaluate the effects of the ‘Reserved Therapeutic Space’ intervention in terms of its impact on the improvement of the nurse–patient therapeutic relationship, the quality of care, perceived coercion and humiliation and length of stay.MethodsA multicentre quasi‐experimental trial design in twelve acute mental health units compared the Reserved Therapeutic Space to standard care. Participants completed validated instruments assessing the therapeutic relationship, perceived quality of care and coercion. Mixed‐effects models and survival analyses evaluated intervention effects.ResultsParticipants receiving the Reserved Therapeutic Space reported stronger nurse–patient relationships, higher quality of care ratings and lower coercion scores compared to those receiving standard care. Survival analysis indicated significantly shorter hospitalizations in the intervention group.ImplicationsFindings suggest that dedicating structured time for nurse–patient engagement enhances therapeutic relationships, reduces negative experiences and potentially improves both satisfaction and resource use. Providing structured therapeutic encounters can advance person‐centred, collaborative mental health nursing practices in acute settings. Future research should explore long‐term outcomes of this intervention.

Nature-based Solutions are strategies inspired by nature that address major societal challenges, such as climate change and food security, by providing several socio-economic and environmental contributions. Despite widespread adoption, evaluating their impacts poses challenges within the field of environmental economics. In this study, we develop a framework for the comprehensive assessment of ponds as Nature-based Solutions. These water systems contribute to carbon storage, provide habitats for biodiversity, as well as leisure, business, and cultural opportunities. We assess them in terms of both effectiveness, which refers to their capacity to deliver benefits according to stakeholder expectations, and eco-efficiency, measuring input-output performance in environmental economic terms. First, we successfully reduce the heterogeneity of pond-specific contributions into comparable composite indicators with a novel application of the Benefit-of-the-Doubt method. Next, we combine Multi-Criteria Decision Analysis with stakeholder preferences to calculate ponds' effectiveness. The results show that these can be viable strategies for the delivery of locally relevant Ecosystem Services. Then, we investigate ponds' technical as well as ecological efficiencies by Data Envelopment Analysis, demonstrating that they can provide both socio-economic and environmental contributions in an efficient manner. Finally, we compare these complementary metrics and confirm the hypothesis that effective ponds can also provide eco-efficient Nature-based Solutions. Furthermore, we elaborate on the potential extensions of our analytical method to other strategies, highlighting how it could support decision makers taking context-specific, informed decisions on the best measures to implement.

This work is part of a project that aims to carry out industrial research on recovery of metallic Ti6Al4V waste material through the generation of recycled powders for their incorporation into the feedstock (in granular form) of extrusion based additive manufacturing processes. Preliminary printing tests show that commercially available 3D printing extrusion-based systems are ineffective at printing granules with particle sizes below 100 μm. Thus, a novel material extrusion screw-based 3D printing extrusion head is designed and tested with granular feedstock of different particle size distributions (1-100, 1-400, 100-475 and 475-550 μm). By means of this novel system, granular feedstock with sizes between 1 and 475 μm was successfully employed for the printing of green Ti6Al4V highly complex geometries. Critical printing parameters were investigated and optimized, demonstrating the feasibility of the incorporation of recycled Ti6Al4V powders into thermoplastic feedstocks for material extrusion additive manufacturing processes.

ABSTRACT The Validation Method (VM) is a specific communication method for older people with dementia. The aim of this study was to analyze the effect of an introductory training course on the Bases of the Validation Method (BVM) on job satisfaction and motivation in healthcare professionals working in nursing homes (NHs) and its influence on self-efficacy, perceived personal competence, organizational commitment, attitudes toward dementia and burnout. A quasi-experimental pilot study was conducted during the COVID-19 pandemic (September 2020–February 2021). Participants were divided into two groups: experimental group (who did 16 hours of training on BVM), and a control group (no intervention). Assessments were made at baseline, one week and 4 months after starting the intervention through validated questionnaires to assess job satisfaction, work motivation, self-efficacy, perceived competence, organizational commitment, attitudes toward people with dementia and burnout. A paired Student’s t-test was used to check intragroup differences, and unpaired Student’s test and multilevel mixed-effects linear regression model were used to assess the impact of the intervention; Hedges’g was used to determine the effect size. The sample consisted of 31 NH professionals, assigned to an experimental group (n = 11) or a control group (n = 20). The BVM training had a positive moderate effect size on job satisfaction, work motivation, self-efficacy, perceived competence and organizational commitment (Hedges’g > 0.30). In contrast, there was a smaller effect on attitudes toward people with dementia (Hedges’g = –0.21), and a moderate negative effect on burnout (Hedges’g = –0.38). BVM training had a positive moderate effect on all variables 4 months after finishing training, except for attitudes toward dementia, for which the effect size was smaller.

This research presents the microstructural and mechanical evolution throughout the welded seam of an austenitic stainless steel (ASS) tube. It was found that the main hardness decrement occurred in the fusion zone (FZ), followed by the heat-affected zone (HAZ) and the base material (BM). Optical microscopy indicated a dendritic structure in FZ and heterogeneous austenitic grain size from the HAZ towards the BM, ranging from 100 µm to 10 µm. The welding process generated an intense texture around the FZ and the HAZ, while the BM still showed an extrusion-like texture. In terms of mechanical behavior, the largest austenite grain size in the FZ led to the lowest strength and ductility of all zones due to the earliest strain localization manifested by heterogeneous strain distribution. However, the strain localization in all zones appeared after 0.4 true strain, indicating an overall good ductility of the seam. These high values were related to two microstructure characteristics: (1) the 10% δ-ferrite after solidification in the FZ favored by the Creq/Nieq=1.67 relationship that delayed the crack propagation along the austenite grains and (2) the heterogeneous microstructure made up of soft austenite and hard martensite in the HAZ and BM producing multiple strain concentrations. Kernel Average Misorientation (KAM) maps obtained by Electron Back-Scattering Diffraction (EBSD) allowed observing higher internal misorientations in the FZ than in the HAZ due to interconnected walls between the δ-ferrite grains. However, the largest KAM values were observed in the BM between γ-austenite and the deformation-induced α’-martensite phases. X-ray diffraction revealed that the residual stresses in the cross-section of the welded seam were compression-type and then switched to tension-type in the outer surface.