Experiences of male irregular migrants during their migration process and reception in Spain: lessons learned from the COVID-19 pandemic.

Background: The causes behind migration movements are complex. The COVID-19 pandemic highlighted how several countries failed to respond to the virus adequately, while simultaneously infringing on people's rights. Male irregular migrants fled their countries of origin and embarked on a perilous migration journey to Spain. The highly restrictive COVID-19 measures and border closures affected the mobility of male irregular migrants, whose reception in the host country posed a challenge. It led to the establishment of emergency facilities to accommodate male irregular migrants affected by COVID-19, which had repercussions on their mental health. The aim of this study was to describe and understand the experiences of male irregular migrants throughout their migration process and reception in Spain during the COVID-19 pandemic. Methods: Qualitative descriptive study. Sixteen male irregular migrants participated in this study. Data were collected between January and March 2023 through 16 one-on-one in-depth interviews. Thematic analysis was used to analyze the qualitative data using ATLAS.ti computer software. Results: Three main themes emerged: (1) How the COVID-19 pandemic drove male irregular migrants to leave their countries of origin, (2) How COVID-19 lockdown policies affected the migration journey, and (3) Receiving male irregular migrants in a pandemic: a housing labyrinth marked by isolation and loneliness. Conclusion: The COVID-19 pandemic increased the social, employment and health inequalities experienced by male irregular migrants. Border closures exacerbated the migration journey and the social stigmatization of this group, who were seen as carriers of the virus in both transit and host countries. Strict control measures in emergency and reception facilities had a significant psychological impact on the male irregular migrants due to the social isolation they experienced. Health institutions should develop programs to guarantee the care needs of irregular migrants.

Child face detection on front passenger seat through deep learning.

OBJECTIVE: One of the main causes of death worldwide among young people are car crashes, and most of these fatalities occur to children who are seated in the front passenger seat and who, at the time of an accident, receive a direct impact from the airbags, which is lethal for children under 13 years of age. The present study seeks to raise awareness of this risk by interior monitoring with a child face detection system that serves to alert the driver that the child should not be sitting in the front passenger seat. METHODS: The system incorporates processing of data collected, elements of deep learning such as transfer learning, fine-tunning and facial detection to identify the presence of children in a robust way, which was achieved by training with a dataset generated from scratch for this specific purpose. The MobileNetV2 architecture was used based on the good performance shown when compared with the Inception architecture for this task; and its low computational cost, which facilitates implementing the final model on a Raspberry Pi 4B. RESULTS: The resulting image dataset consisted of 102 empty seats, 71 children (0-13 years), and 96 adults (14-75 years). From the data augmentation, there were 2,496 images for adults and 2,310 for children. The classification of faces without sliding window gave a result of 98% accuracy and 100% precision. Finally, using the proposed methodology, it was possible to detect children in the front passenger seat in real time, with a delay of 1 s per decision and sliding window criterion, reaching an accuracy of 100%. CONCLUSIONS: Although our 100% accuracy in an experimental environment is somewhat idealized in that the sensor was not blocked by direct sunlight, nor was it partially or completely covered by dirt or other debris common in vehicles transporting children. The present study showed that is possible the implementation of a robust noninvasive classification system made on Raspberry Pi 4 Model B in any automobile for the detection of a child in the front seat through deep learning methods such as Deep CNN.

Nanostructured Copper Selenide Coatings for Antifouling Applications.

The accumulation of microorganisms, plants, algae, or small animals on wet surfaces that have a mechanical function causes biofouling, which can result in structural or other functional deficiencies. The maritime shipping industry must constantly manage biofouling to optimize operational performance, which is a common and long-lasting problem. It can occur on any metal structure in contact with or submerged in ocean water, which represents additional costs in terms of repairs and maintenance. This study is focused on the production of antifouling coatings, made with nanoparticles of copper selenide (CuSe NPs) modified with gum arabic, within a water-base acrylic polymeric matrix. During the curing of the acrylic resin, the CuSe NPs remain embedded in the resin, but this does not prevent the release of ions. The coatings released copper and selenium ions for up to 80 days, and selenium was the element that was released the most. The adhesion of film coatings to metallic substrates showed good adhesion, scale 5B (ASTM D3359 standard). Antimicrobial activity tests show that the coatings have an inhibitory effect on Escherichia coli and Candida albicans. The effect is more noticeable when the coating is detached from the substrate and placed on a growing medium, compared to the coating on a substrate. Scanning electron microscopy (SEM) observations show that nanostructured CuSe coatings are made up of rod-shaped and spherical particles with an average particle size of 101.6 nm and 50 nm, respectively. The energy dispersive X-ray spectroscopy (EDS) studies showed that the ratio of selenium nanoparticles is greater than that of copper and that their distribution is homogeneous.

Classification and selection of the main features for the identification of toxicity in Agaricus and Lepiota with machine learning algorithms.

The occurrence of fungi is cosmopolitan, and while some mushroom species are beneficial to human health, others can be toxic and cause illness problems. This study aimed to analyze the organoleptic, ecological, and morphological characteristics of a group of fungal specimens and identify the most significant features to develop models for fungal toxicity classification using genetic algorithms and LASSO regression. The results of the study indicated that odor, spore print color, and habitat were the most significant characteristics identified by the genetic algorithm GALGO. Meanwhile, odor, gill size, stalk shape, and twelve other features were the relevant characteristics identified by LASSO regression. The importance score of the odor variable was 99.99%, gill size obtained 73.7%, stalk shape scored 39.9%, and the remaining variables did not score higher than 18%. Logistic regression, k-nearest neighbor (KNN), and XG-Boost classification algorithms were used to develop models using the features selected by both GALGO and LASSO. The models were evaluated using sensitivity, specificity, and accuracy metrics. The models with the highest AUC values were XGBoost, with a maximum value of 0.99 using the features selected by LASSO, followed by KNN with a maximum value of 0.99. The GALGO selection resulted in a maximum AUC of 0.98 in KNN and XGBoost. The models developed in this study have the potential to aid in the accurate identification of toxic fungi, which can prevent health problems caused by their consumption.

Spanish version of the Self-Care of Chronic Illness Inventory: A validation study amongst community-dwelling older adults with chronic multimorbidity.

AIM: To psychometrically assess the Spanish version of the Self-Care of Chronic Illness Inventory (SC-CII-Sp) in community-dwelling older adults with chronic multimorbidity. DESIGN: A methodological study. METHOD: A total of 1260 older adults participated in the study between May 2020 and February 2022. The data were analysed using SPSS Statistics® 26 and AMOS® 24. The items' content validity index and the Fleiss' kappa were calculated to assess the SC-CII-Sp's content validity. Convergent validity was assessed by calculating the Pearson correlation coefficient between the participants' scores on the SC-CII-Sp and their scores on the Spanish Chronic Disease Self-Efficacy scale (SCD-SE). Construct validity was tested by performing a confirmatory factor analysis (CFA). The SC-CII-Sp's reliability was tested by computing the Cronbach's alpha. RESULTS: The SC-CII-Sp showed good content and convergent validity. The CFA showed that the SC-CII-Sp has three sub-scales. The 8-item Self-Care Maintenance sub-scale has good internal consistency and is comprised of two dimensions: illness-related and health-promoting behaviour. The Self-Care Monitoring sub-scale had excellent internal consistency and its five loaded items belonged to a single dimension. The 6-item Self-Care Management sub-scale has adequate internal consistency and two dimensions: autonomous and consulting behaviour. CONCLUSION: The Spanish version of SC-CII is a valid and reliable instrument to be used in the assessment of self-care behaviours amongst Spanish-speaking, community-dwelling older adults with chronic multimorbidity. IMPLICATIONS FOR THE PROFESSION: Nurses need valid and reliable tools to assess self-care behaviours in Spanish-speaking community-dwelling older adults with chronic multimorbidity. This study provides a 19-item tool that allows for the comprehensive evaluation of self-care behaviours in healthy and ill states. IMPACT: Using the SC-CII-Sp in clinical or research settings could help nurses to examine the effects of different interventions on self-care behaviours amongst Spanish-speaking, community-dwelling older adults with chronic multimorbidity. PATIENT OR PUBLIC CONTRIBUTION: None to be reported.

Measurement invariance of the driving inattention scale (ARDES) across 7 countries.

The Attention-Related Driving Errors Scale (ARDES) is a self-report measure of individual differences in driving inattention. ARDES was originally developed in Spanish (Argentina), and later adapted to other countries and languages. Evidence supporting the reliability and validity of ARDES scores has been obtained in various different countries. However, no study has been conducted to specifically examine the measurement invariance of ARDES measures across countries, thus limiting their comparability. Can different language versions of ARDES provide comparable measures across countries with different traffic regulations and cultural norms? To what extent might cultural differences prevent researchers from making valid inferences based on ARDES measures? Using Alignment Analysis, the present study assessed the approximate invariance of ARDES measures in seven countries: Argentina (n = 603), Australia (n = 378), Brazil (n = 220), China (n = 308). Spain (n = 310), UK (n = 298), and USA (n = 278). The three-factor structure of ARDES scores (differentiating driving errors occurring at Navigation, Manoeuvring and Control levels) was used as the target theoretical model. A fixed alignment analysis was conducted to examine approximate measurement invariance. 12.3 % of the intercepts and 0.8 % of the item-factor loadings were identified as non-invariant, averaging 8.6 % of non-invariance. Despite substantial differences among the countries, sample recruitment or representativeness, study results support resorting to ARDES measures to make comparisons across the country samples. Thus, the range of cultures, laws and collision risk across these 7 countries provides a demanding assessment for a cultural-free inattention while-driving. The alignment analysis results suggest that ARDES measures reach near equivalence among the countries in the study. We hope this study will serve as a basis for future cross-cultural research on driving inattention using ARDES.

Targeted long-read sequencing identifies and characterizes structural variants in cases of inherited platelet disorders.

BACKGROUND: Genetic diagnosis of inherited platelet disorders (IPDs) is mainly performed by high-throughput sequencing (HTS). These short-read-based sequencing methods sometimes fail to characterize the genetics of the disease. OBJECTIVES: To evaluate nanopore long-read DNA sequencing for characterization of structural variants (SVs) in patients with IPDs. METHODS: Four patients with a clinical and laboratory diagnosis of Glanzmann thrombasthenia (GT) (P1 and P2) and Hermansky-Pudlak syndrome (HPS) (P3 and P4) in whom HTS missed the underlying molecular cause were included. DNA was analyzed by both standard HTS and nanopore sequencing on a MinION device (Oxford Nanopore Technologies) after enrichment of DNA spanning regions covering GT and HPS genes. RESULTS: In patients with GT, HTS identified only 1 heterozygous ITGB3 splice variant c.2301+1G>C in P2. In patients with HPS, a homozygous deletion in HPS5 was suspected in P3, and 2 heterozygous HPS3 variants, c.2464C>T (p.Arg822∗) and a deletion affecting 2 exons, were reported in P4. Nanopore sequencing revealed a complex SV affecting exons 2 to 6 in ITGB3 (deletion-inversion-duplication) in homozygosity in P1 and compound heterozygosity with the splice variant in P2. In the 2 patients with HPS, nanopore defined the length of the SVs, which were characterized at nucleotide resolution. This allowed the identification of repetitive Alu elements at the breakpoints and the design of specific polymerase chain reactions for family screening. CONCLUSION: The nanopore technology overcomes the limitations of standard short-read sequencing techniques in SV characterization. Using nanopore, we characterized novel defects in ITGB3, HPS5, and HPS3, highlighting the utility of long-read sequencing as an additional diagnostic tool in IPDs.

Dataset on the mechanical and physical characterization of the Ecuadorian Guadua angustifolia kunth bamboo culms belonging to "Caña Mansa" biotype.

This article presents a set of experimental data on the mechanical and physical properties of the Ecuadorian endemic bamboo species Guadua angustifolia kunth (Guadua a.k.), specifically the "Caña Mansa" biotype. The data on compressive, shear, tensile and bending strength, as well as the moisture content and density, were obtained by carrying out the corresponding tests following the ISO 22157:2019 standard. For this purpose, each bamboo culm examined was divided along its height into three sections that were thoroughly characterized. The equations used for the calculations of the mechanical and physical properties are described in detail for each test. Besides, the main mechanical properties of the characterized bamboo were compared to those of similar species reported in the literature. Property charts (compressive/tensile strength and modulus of rupture vs. density) were built to compare the Ecuadorian biotype evaluated with other classical and green materials by using appropriate software. These data give an insight into the valorization of natural structural materials harvested in the Americas for potential applications in different engineering fields, particularly for sustainable building.

Spanish version of the Maastricht Personal Autonomy Questionnaire: A validation study among community-dwelling older adults with chronic multimorbidity.

BACKGROUND: Loss of personal autonomy in older adults with chronic multimorbidity is associated with worsened biopsychosocial health. In order to facilitate the standardised assessment of personal autonomy in older adults with chronic conditions, nurses could use the Maastricht Personal Autonomy Questionnaire (MPAQ). OBJECTIVE: To translate, culturally adapt and psychometrically assess the Spanish version of the MPAQ in community-dwelling older adults with chronic multimorbidity (MPAQ-Sp). METHODS: Observational cross-sectional study. A convenience sample of 884 community-dwelling older adults was recruited from 10 community centres in five health districts in southeastern Spain. Data were collected between January 2021 and September 2022. The study was completed in four phases. Phase 1: The MPAQ was translated into Spanish. Phase 2: A pilot test of reliability and content validity was conducted. Phase 3: To test the dimensionality of the tool, an exploratory factor analysis (EFA) was conducted. Phase 4: a final validation study was conducted which included a confirmatory factor analysis (CFA) and assessed the validity (content, criterion and construct), reliability and readability of the MPAQ-Sp. RESULTS: The average age of the sample was 75.89 years (SD = ±8.04). Their mean number of chronic conditions was 4.84 (SD = ±2.19) and 67% were women. The MPAQ-Sp is comprised of 16 items distributed in four subscales: [1] the 'Degree of autonomy' scale, [2] the 'Working on autonomy' scale, [3] the 'Dilemmas: health over preferences' scale and [4] the 'Dilemmas: preferences over health' scale. CONCLUSIONS: The Spanish version of the MPAQ-Sp is a valid and reliable instrument to assess personal autonomy in Spanish-speaking, community-dwelling older adults with chronic multimorbidity. IMPLICATIONS FOR PRACTICE: The use of the MPAQ-Sp would allow researchers and healthcare professionals to identify a loss of personal autonomy among Spanish-speaking community-dwelling older adults with chronic multimorbidity.

Contralateral Arm Pain as a Sign of Distress Regarding Symptoms.

BACKGROUND: Pain intensity and magnitude of incapability are associated with common unhelpful thoughts about symptoms such as catastrophic thinking and kinesiophobia. To determine whether reports of pain in the upper limb contralateral to a non-trauma condition were associated with unhelpful thoughts, we measured the relationship between pain intensity in the opposite limb and levels of unhelpful thinking. METHODS: In a cross-sectional study, 152 new and return patients seeking care of an upper-limb musculoskeletal condition completed measures of upper-extremity-specific magnitude of capability, pain intensity of the involved and contralateral arms, unhelpful thoughts regarding symptoms, symptoms of distress regarding symptoms, and general symptoms of depression. Factors associated with contralateral and ipsilateral pain intensity and upper-extremity-specific magnitude of capability were assessed using multivariable statistics. RESULTS: In bivariate analysis, contralateral arm pain was associated with symptoms of distress regarding pain, but not in multivariable analysis. Accounting for potential confounding in negative binominal regression analysis, greater pain intensity of the affected side was independently associated with greater feelings of distress regarding symptoms and no prior surgery. Greater upper-extremity-specific capability was independently associated with less distress regarding symptoms, married/partnered, men, and no prior surgery. CONCLUSIONS: The observation that greater pain intensity in the opposite arm was associated with greater distress regarding symptoms suggests that, in combination with other verbal and non-verbal signs of distress, patient concerns about pain in the contralateral limb can help direct patients and surgeons to evidence-based care strategies for alleviating stress regarding symptoms.

SARS-CoV-2 Vaccine Effectiveness in Hospitalized Patients: A Multicenter Test-Negative Case-Control Study.

BACKGROUND: Phase III clinical trials have documented the efficacy of the SARS-CoV-2 vaccines in preventing symptomatic COVID-19. Nonetheless, it is imperative to continue analyzing the clinical response to different vaccines in real-life studies. Our objective was to evaluate the effectiveness of five different vaccines in hospitalized patients with COVID-19 during the third COVID-19 outbreak in Mexico dominated by the Delta variant. METHODS: A test-negative case-control study was performed in nine tertiary-care hospitals for COVID-19. We estimated odds ratios (OR) adjusted by variables related a priori with the likelihood of SARS-CoV-2 infection and its severity. RESULTS: We studied 761 subjects, 371 cases, and 390 controls with a mean age of 53 years (SD, 17 years). Overall, 51% had a complete vaccination scheme, and an incomplete scheme (one dose from a scheme of two), 14%. After adjustment for age, gender, obesity, and diabetes mellitus, we found that the effectiveness of avoiding a SARS-CoV-2 infection when hospitalized with at least one vaccination dose was 71% (OR 0.29, 95% CI 0.19-0.45), that of an incomplete vaccination scheme, 67% (OR 0.33, 95% CI 0.18-0.62), and that of any complete vaccination scheme, 73% (OR 0.27, 95% CI 0.17-0.43). CONCLUSIONS: The SARS-CoV-2 vaccination program showed effectiveness in preventing SARS-CoV-2 infection in hospitalized patients during a Delta variant outbreak.

Compassion in health professionals: Development and validation of the Capacity for Compassion Scale.

BACKGROUND: Health professionals witness pain and suffering when they care for sick people and their families. Compassion is a necessary quality in their work as it combines the will to help, alleviate suffering and promote the well-being of both the people they are attending and the professionals themselves. The aim of the study was to design and evaluate the psychometric properties of the Capacity for Compassion Scale (CCS). DESIGN: A quantitative, descriptive and cross-sectional study was carried out to evaluate the psychometric properties of the scale (reliability, temporal stability, content validity, criterion validity and construct validity). METHODS: The study was carried out in two phases: pilot study and final validation. The data were collected between April and May 2022. The sample was selected by convenience sampling and was made up of a total of 264 participants, 59 in the pilot phase and 205 in the final validation. RESULTS: The Capacity for Compassion Scale has been shown to have good psychometric properties in relation to reliability, temporal stability, and content, criterion, and construct validity. Factor analysis showed that there were four subdimensions of the scale: motivation/commitment, presence, shared humanity and self-compassion. The results also indicate that compassionate ability is significantly correlated with age and work experience. CONCLUSIONS: The Capacity for Compassion Scale shows adequate psychometric properties. This instrument measures the compassion capacity of health professionals, which is a valuable discovery for new lines of research in this field. IMPACT: Through this scale, low levels of capacity for compassion can be detected that negatively influence the quality of care provided by health professionals. The Capacity for Compassion Scale can therefore contribute to the identification of needs and promote training around compassion for health professionals. PATIENT OR PUBLIC CONTRIBUTION: No patient or public contribution. WHAT PROBLEM DID THE STUDY ADDRESS?: Compassion in health professionals has positive effects on improving the quality of care, the satisfaction of professionals and the work environment. There are compassion cultivation programmes whose validity has been proven for the development of the dimensions of compassion. There is no specific instrument that measures capacity for compassion in healthcare professionals. WHAT WERE THE MAIN FINDINGS?: A scale is designed to measure capacity for compassion in health professionals. This is the only such scale available up until now. The scale measures four dimensions of compassion: motivation/commitment, presence, shared humanity and self-compassion. WHERE AND ON WHOM WILL THE RESEARCH HAVE AN IMPACT?: The development of specific programmes that can increase the compassion of health professionals with all the benefits that this can bring to health care is encouraged. It will be possible to analyse the effects of training programmes on the cultivation of compassion.

Factor XI in Carriers of Antiphospholipid Antibodies: Elevated Levels Associated with Symptomatic Thrombotic Cases, While Low Levels Linked to Asymptomatic Cases.

Antiphospholipid syndrome (APS) is a thromboinflammatory disorder caused by circulating antiphospholipid autoantibodies (aPL) and characterized by an increased risk of thrombotic events. The pathogenic mechanisms of these antibodies are complex and not fully understood, but disturbances in coagulation and fibrinolysis have been proposed to contribute to the thrombophilic state. This study aims to evaluate the role of an emerging hemostatic molecule, FXI, in the thrombotic risk of patients with aPL. Cross-sectional and observational study of 194 consecutive and unrelated cases with aPL recruited in a single center: 82 asymptomatic (AaPL) and 112 with primary antiphospholipid syndrome (APS). Clinical and epidemiological variables were collected. The profile of aPL was determined. Plasma FXI was evaluated by Western blotting and two coagulation assays (FXI:C). In cases with low FXI, molecular analysis of the F11 gene was performed. FXI:C levels were significantly higher in patients with APS than in patients with AaPL (122.8 ± 33.4 vs. 104.5 ± 27.5; p < 0.001). Multivariate analysis showed a significant association between symptomatic patients with aPL (APS) and high FXI (>150%) (OR = 11.57; 95% CI: 1.47-90.96; p = 0.020). In contrast, low FXI (<70%), mostly caused by inhibitors, was less frequent in the group of patients with APS compared to AaPL (OR = 0.17; 95%CI: 0.36-0.86; p = 0.032). This study suggests that FXI levels may play a causal role in the prothrombotic state induced by aPLs and holds the promise of complementary treatments in APS patients by targeting FXI.

Optimizing Clinical Diabetes Diagnosis through Generative Adversarial Networks: Evaluation and Validation.

The escalating prevalence of Type 2 Diabetes (T2D) represents a substantial burden on global healthcare systems, especially in regions such as Mexico. Existing diagnostic techniques, although effective, often require invasive procedures and labor-intensive efforts. The promise of artificial intelligence and data science for streamlining and enhancing T2D diagnosis is well-recognized; however, these advancements are frequently constrained by the limited availability of comprehensive patient datasets. To mitigate this challenge, the present study investigated the efficacy of Generative Adversarial Networks (GANs) for augmenting existing T2D patient data, with a focus on a Mexican cohort. The researchers utilized a dataset of 1019 Mexican nationals, divided into 499 non-diabetic controls and 520 diabetic cases. GANs were applied to create synthetic patient profiles, which were subsequently used to train a Random Forest (RF) classification model. The study's findings revealed a notable improvement in the model's diagnostic accuracy, validating the utility of GAN-based data augmentation in a clinical context. The results bear significant implications for enhancing the robustness and reliability of Machine Learning tools in T2D diagnosis and management, offering a pathway toward more timely and effective patient care.

Top of the Basilar Syndrome: A Case Report of a Healthy Young Woman and Literature Review.

Top of the basilar syndrome (TBS) is defined as the presence of multiple ischemic lesions on magnetic resonance image (MRI) including more than two territories supplied by branches of the distal portion of the basilar artery, causing symptoms such as dizziness, diplopia, ataxia, and acute cognitive decline that can lead to quadriplegia and death. Diagnosing TBS is challenging because it can mimic other conditions such as thalamic hemorrhages or vertebrobasilar ischemia, and requires advanced imaging. Although the prognosis for these patients is poor, rehabilitation is essential for their recovery. This case describes a healthy 28-year-old woman who presented with headache, vomiting, and tonic-clonic seizures sent to the hospital with a stroke diagnosis.