Rare interstitial lung diseases: a narrative review.

Background and Objective: Interstitial lung diseases (ILDs) encompass over 200 entities. Among them, fibrosing lung diseases, have recently generated special interest due to the emerging therapies for their management. However, it is important to deepen our knowledge of other less prevalent ILD, since many of them are associated with a poor prognosis. This narrative review aims to provide a practical and up-to-date description of some poorly recognized ILD. It covers rare idiopathic interstitial pneumonias and their histologic patterns, genetic disorders with interstitial lung involvement (Hermansky-Pudlak syndrome), and ILD associated with benign proliferation of pulmonary lymphoid tissue, namely follicular bronchiolitis and granulomatous-lymphocytic interstitial lung disease. Methods: Electronic searches of PubMed and Google Scholar using specific keywords were conducted. Articles underwent screening for relevance, covering review articles, meta-analyses, systematic reviews, case series, prospective studies, society guidelines, editorials in peer-reviewed journals; scientific books on the subject. The data included was limited to English and Spanish publications. Key Content and Findings: Despite the low prevalence of these diseases, the increased recognition of radiological patterns, pathological features, and diagnostic procedures, have permitted their better characterization. This review highlights epidemiology, clinical presentation, diagnosis, natural history, and treatment. Conclusions: Lesser-studied ILD represent a diagnostic and therapeutic challenge and can be frequently misdiagnosed. Also, due to the lack of randomized controlled trials, there are no well-established therapeutic options. Further studies or registries are needed to improve accurate diagnosis and management.

Acoustic stack for combined intravascular ultrasound and photoacoustic imaging.

Multimodal intravascular ultrasound and photoacoustic (IVUS/PA) imaging is a promising diagnostic tool for cardiovascular diseases like atherosclerosis. IVUS/PA catheters typically require two independent transducers due to different frequency requirements, potentially increasing the catheter size. To facilitate multimodal imaging within conventional catheter dimensions, we designed, fabricated, and characterized a dual-transducer acoustic stack where a low-frequency (LF) PA receiver sits as a matching layer for the high-frequency (HF) US transducer. While the HF transducer operates around 50 MHz, the LF receiver targets frequencies below 15 MHz to capture most of the PA energy from atherosclerotic plaque lipids. Simulation results reveal that this configuration could increase the sensitivity of the HF transducer by 3.54 dB while maintaining bandwidth. Phantom experiments with fabricated stacks showed improved performance for the US transducer, validating the enhanced sensitivity and bandwidth. Following improvements in stack fabrication, the proposed acoustic stack is a viable design that can significantly enhance diagnostic accuracy for atherosclerosis, providing high-resolution, multifrequency imaging within a compact catheter form factor.

Oral Administration of Efavirenz Dysregulates the Tph2 Gene in Brain Serotonergic Areas and Alters Weight and Mood in Mice.

Most HIV-antiretroviral drugs have adverse effects. Efavirenz (EFV) is an example of a drug with neuropsychiatric effects, such as anxiety, depression, and suicidal thoughts, in people living with HIV (PLWH). The mechanisms by which EFV causes neuropsychiatric alterations in PLWH are complex, multifactorial, and not fully understood, although several studies in animals have reported changes in brain energy metabolism, alterations in monoamine turnover, GABA, and glutamate levels, and changes in 5-HT receptors. In this report, we studied the effects of EFV on the serotonergic system in healthy mice, specifically, whether EFV results in alterations in the levels of the tryptophan hydroxylase 2 (Tph2) gene in the brain. EFV (10 mg/kg) and distilled water (1.5 µL/kg) (control group) were orally administered to the mice for 36 days. At the end of the treatment, Tph2 expression levels in mouse brains were measured, and mood was evaluated by three trials: the forced swim test, elevated plus maze, and open field test. Our results revealed dysregulation of Tph2 expression in the brainstem, amygdala, and hypothalamus in the EFV group, and 5-HT levels increased in the amygdala in the EFV group. In the behavioral tests, mice given EFV exhibited a passive avoidance response in the forced swim test and anxiety-like behavior in the elevated plus maze, and they lost weight. Herein, for the first time, we showed that EFV triggered dysregulation of the Tph2 gene in the three serotonergic areas studied; and 5-HT levels increased in the amygdala using the ELISA method. However, further studies will be necessary to clarify the increase of 5-HT in the amygdala as well as understand the paradoxical decrease in body weight with the simultaneous increase in food consumption. It will also be necessary to measure 5-HT by other techniques different from ELISA, such as HPLC.

Artificial Intelligence Applied to Forced Spirometry in Primary Care.

Introduction: This study aims to create an artificial intelligence (AI) based machine learning (ML) model capable of predicting a spirometric obstructive pattern using variables with the highest predictive power derived from an active case-finding program for COPD in primary care. Material and methods: A total of 1190 smokers, aged 30-80 years old with no prior history of respiratory disease, underwent spirometry with bronchodilation. The sample was analyzed using AI tools. Based on an exploratory data analysis (EDA), independent variables (according to mutual information analysis) were trained using a gradient boosting algorithm (GBT) and validated through cross-validation. Results: With an area under the curve close to unity, the model predicted a spirometric obstructive pattern using variables with the highest predictive power: FEV1_theoretical_pre values. Sensitivity: 93%. Positive predictive value: 94%. Specificity: 97%. Negative predictive value: 96%. Accuracy: 95%. Precision: 94%. Conclusion: An ML model can predict the presence of an obstructive pattern in spirometry in a primary care smoking population with no prior diagnosis of respiratory disease using the FEV1_theoretical_pre values with an accuracy and precision exceeding 90%. Further studies including clinical data and strategies for integrating AI into clinical workflow are needed.

Introducción: Este estudio tiene como objetivo crear un modelo de aprendizaje automático (ML) basado en inteligencia artificial (IA) capaz de predecir un patrón obstructivo espirométrico utilizando variables con el mayor poder predictivo derivado de un programa activo de búsqueda de casos de enfermedad pulmonar obstructiva crónica (EPOC) en Atención Primaria. Materiales y métodos: Un total de 1.190 fumadores, de entre 30 y 80 años, sin antecedentes de enfermedad respiratoria, fueron sometidos a espirometría con IA artificial. Sobre la base de un análisis de datos exploratorio (EDA), las variables independientes (según el análisis de información mutua) se entrenaron utilizando un algoritmo de gradiente de aumento (GBT) y se validaron mediante validación cruzada. Resultados: Con un área bajo la curva cercana a la unidad, el modelo predijo un patrón obstructivo espirométrico utilizando los valores del FEV1 prebroncodilatador. Sensibilidad: 93%. Valor predictivo positivo: 94%. Especificidad: 97%. Valor predictivo negativo: 96%. Precisión: 95%. Precisión: 94%. Conclusión: Un modelo ML puede predecir la presencia de un patrón obstructivo en la espirometría en una población fumadora de atención primaria sin diagnóstico previo de enfermedad respiratoria utilizando los valores FEV1 prebroncodilatadores con una exactitud y precisión superiores al 90%. Se necesitan más estudios que incluyan datos clínicos y estrategias para integrar la IA en el flujo de trabajo clínico.

Eight weeks of high-intensity interval vs. sprint interval training effects on overweight and obese adolescents carried out during the cool-down period of physical education classes: randomized controlled trial.

Objective: The aim of this study was to evaluate the effect of sprint interval training (SIT) and [high intensive interval training (HIIT)] carried out during the cool-down period of the physical education classes on body composition, blood pressure variables (BP) and pulse rate (PR), and cardiorespiratory fitness of adolescents who are overweight and obese, and to compare the differences in enjoyment in response to SIT vs. HIIT. Methods: For this randomized controlled trial, forty-five adolescents were recruited from a high school and were randomly placed into three groups. SIT and HIIT trained for 8 weeks, twice a week, for 12 min/session. Experimental group (EG) 3 was the control, and they maintained their regular physical education class schedule. The SIT group performed 6 sets of 60 s of work (90-95%HRmax) / 60 s of rest (50-55%HRmax), and the HIIT group performed 3 sets of 2 min of work (80-85%HRmax) / 2 min of rest (50-55%HRmax). Results: Both experimental groups showed a significant improvement in fat mass (FM) (%) and trunk FM (kg). In addition, EG2 reported a significance improvement in lean mass (kg), blood pressure BP (mmHG), systolic blood pressure (SBP) (mmHg), diastolic blood pressure (DBP) (mmHg), PR (bpm), and VO2max (ml/kg/min). Conclusion: The present study found that a HIIT protocol performed during the cool-down period of the physical education classes generated adaptations such as improvement in body composition, BP variables and PR, and cardiorespiratory fitness, in overweight and obese adolescents. In contrast, the group of overweight and obese adolescents who performed SIT showed limited benefits, with changes in fat mass only.

Self-Esteem and Coping Strategies in Adolescent Cancer Patients during the Period of Illness and Follow-Up.

The importance of self-esteem during the course of oncological illness has been well-documented by some previous studies. However, data assessing its association with various coping strategies, especially considering the period of illness, are still scarce. The objective of this study is to analyze the differences in coping strategies among oncological adolescents, taking into account their self-esteem, illness period, age, and sex. A total of 201 oncological patients between the ages of 12 and 17 from three different Spanish cities were included in this study. All of them were asked to answer a tailored questionnaire, encompassing information about age, sex, and illness period. Additionally, the coping strategies were measured using the ACS scale, while self-esteem was evaluated using the SENA questionnaire. The results demonstrated that male adolescents and older individuals exhibited higher levels of self-esteem. The main coping strategies associated with higher self-esteem were "ignore the problem", "focus on positive", "physical recreation", and "wishful thinking" both during the treatment and the follow-up phases. We conclude that higher self-esteem is associated with some of the coping strategies such as "focus on positive", "ignore the problem", and "wishful thinking". Sociodemographic variables influence the relationship between self-esteem and coping strategies, but no differences were found regarding the period of illness.

Open datasets and code for multi-scale relations on structure, function and neuro-genetics in the human brain.

The human brain is an extremely complex network of structural and functional connections that operate at multiple spatial and temporal scales. Investigating the relationship between these multi-scale connections is critical to advancing our comprehension of brain function and disorders. However, accurately predicting structural connectivity from its functional counterpart remains a challenging pursuit. One of the major impediments is the lack of public repositories that integrate structural and functional networks at diverse resolutions, in conjunction with modular transcriptomic profiles, which are essential for comprehensive biological interpretation. To mitigate this limitation, our contribution encompasses the provision of an open-access dataset consisting of derivative matrices of functional and structural connectivity across multiple scales, accompanied by code that facilitates the investigation of their interrelations. We also provide additional resources focused on neuro-genetic associations of module-level network metrics, which present promising opportunities to further advance research in the field of network neuroscience, particularly concerning brain disorders.

Cognitive and brain connectivity trajectories in critically ill COVID-19 patients.

BACKGROUND: Multiple Organ failure (MOF) is one of the main causes of admission to the Intensive Care Unit (ICU) of patients infected with COVID-19 and can cause short- and long-term neurological deficits. OBJECTIVE: To compare the cognitive functioning and functional brain connectivity at 6-12 months after discharge in two groups of individuals with MOF, one due to COVID-19 and the other due to another cause (MOF-group), with a group of Healthy Controls (HC). METHODS: Thirty-six participants, 12 from each group, underwent a neuropsychological and neuroimaging assessment at both time-points. Functional connectivity of the resting state networks was compared between COVID-19 and HC while controlling for the effect of MOF. The association between functional connectivity and neuropsychological performance was also investigated. RESULTS: Compared to the HC, COVID-19 group demonstrated hypoconnectivity between the Default Mode Network and Salience Network. This pattern was associated with worse performance on tests of attention and information processing speed, at both time-points. CONCLUSION: The study of the association between cognitive function and brain functional connectivity in COVID-19 allows the understanding of the short- and long-term neurological alterations of this disease and promotes the development of intervention programs to improve the quality of life for this understudied population.

Influence of physical fitness components on personality factors and risk perception of children and adolescents: a cross-sectional study.

OBJECTIVES: To examine the associations of cardiorespiratory fitness (VO2 max) and muscular strength with indicators related to the risk scale, such as perceived competence, sensation seeking, competitiveness, risk taking and risk perception in sports. DESIGN: Cross-sectional study. SETTING: High schools from the Region of Murcia (Spain). PARTICIPANTS: Three-hundred-and-seventeen adolescents participated (mean age: 13.69±1.2 years old). PRIMARY AND SECONDARY OUTCOME MEASURES: Body mass, body height, Course-Navette test, upper limb strength and psychoeducational factors that determine the propensity towards sports accidents in school children, the Sports Accident Propensity Scale were evaluated. It was performance t-test for independent samples, stepwise multiple linear regression models and a multiple mediation analysis. RESULTS: The analysis showed significant differences with respect to sex in height, VO2 max, handgrip strength and in all factors of the questionnaire (p=0.02-<0.01). Adolescents who presented greater VO2 max, strength in the handgrip test and age showed a higher score in factors 1 and 3. Higher scores in factor 2 were associated with better VO2 max and strength in handgrip test. Youngers and better values of strength in the handgrip showed higher score in factors 4 and 5. The mediation analysis with two mediating variables (handgrip strength and VO2 max) showed a significant indirect effect. When handgrip strength and VO2 max were included in the equations, the association between sex and each factor ceased to be significant. CONCLUSION: This study highlights the potential benefits of muscular strength (handgrip) and VO2 max in the perceived risk scale, and the variable of age on this. TRIAL REGISTRATION NUMBER: Clinical trial: NCT05544370 (pre-results).

Physiological and genomic characterization of Lactiplantibacillus plantarum isolated from Indri indri in Madagascar.

AIMS: Indri indri is a lemur of Madagascar which is critically endangered. The analysis of the microbial ecology of the intestine offers tools to improve conservation efforts. This study aimed to achieve a functional genomic analysis of three Lactiplantibacillus plantarum isolates from indris. METHODS AND RESULTS: Samples were obtained from 18 indri; 3 isolates of Lp. plantarum were obtained from two individuals. The three isolates were closely related to each other, with <10 single nucleotide polymorphisms, suggesting that the two individuals shared diet-associated microbes. The genomes of the three isolates were compared to 96 reference strains of Lp. plantarum. The three isolates of Lp. plantarum were not phenotypically resistant to antibiotics but shared all 17 genes related to antimicrobial resistance that are part of the core genome of Lp. plantarum. The genomes of the three indri isolates of Lp. plantarum also encoded for the 6 core genome genes coding for enzymes related to metabolism of hydroxybenzoic and hydroxycinnamic acids. The phenotype for metabolism of hydroxycinnamic acids by indri isolates of Lp. plantarum matched the genotype. CONCLUSIONS: Multiple antimicrobial resistance genes and gene coding for metabolism of phenolic compounds were identified in the genomes of the indri isolates, suggesting that Lp. plantarum maintains antimicrobial resistance in defense of antimicrobial plant secondary pathogens and that their metabolism by intestinal bacteria aids digestion of plant material by primate hosts.

Overall proportion of orthorexia nervosa symptoms: A systematic review and meta-analysis including 30 476 individuals from 18 countries.

Background: To date, no previous meta-analysis has determined the overall proportion of orthorexia nervosa symptoms on a global scale. The aim of the present study was 2-fold: first, to establish the overall proportion of orthorexia nervosa symptoms on a global scale, assessed with the ORTO-15 questionnaire; and second, to determine the role of sex, type of population, mean age, body mass index, and the temporal trend in relation to orthorexia nervosa symptoms. Methods: Four databases were searched (PubMed, Scopus, Web of Science, and Cochrane Database of Systematic Reviews) with date limits from January 2005 to June 2023. Studies assessing the proportion of orthorexia nervosa assessed using the ORTO-15 questionnaire with a cutoff of <35 or <40 points were included in this review. Results: The overall proportion of orthorexia nervosa symptoms (using the cutoff <35 points) was 27.5% (95% confidence interval (CI) = 23.5-31.6, I2 = 97.0%). In addition, no significant differences were observed between females (34.6%, 95% CI = 29.5-39.8, I2 = 96.1%) and males (32.1%, 95% CI = 26.5-38.1, I2 = 93.1%). According to the type of population, the highest overall proportion was found in people focused on sports performance or body composition (34.5%, 95% CI = 23.1-47.0, I2 = 98.0%). Notwithstanding, caution should be exercised in interpreting this result, as reverse causality could be a potential pitfall in this relationship. Conclusions: We found that approximately three out of 10 study participants showed orthorexia nervosa symptoms according to the ORTO-15 tool. This overall proportion was higher in those participants who were athletes or fitness practitioners. Over the years, the proportion of orthorexia nervosa symptoms seems to be increasing. These high percentages and their increase are worrisome from a public health perspective and highlight the need to develop psychometric instruments to aid in clinical diagnosis and treatment efficacy. Registration: PROSPERO (CRD42022350873).

The Neurogenetics of Functional Connectivity Alterations in Autism: Insights From Subtyping in 657 Individuals.

BACKGROUND: There is little consensus and controversial evidence on anatomical alterations in the brains of people with autism spectrum disorder (ASD), due in part to the large heterogeneity present in ASD, which in turn is a major drawback for developing therapies. One strategy to characterize this heterogeneity in ASD is to cluster large-scale functional brain connectivity profiles. METHODS: A subtyping approach based on consensus clustering of functional brain connectivity patterns was applied to a population of 657 autistic individuals with quality-assured neuroimaging data. We then used high-resolution gene transcriptomic data to characterize the molecular mechanism behind each subtype by performing enrichment analysis of the set of genes showing a high spatial similarity with the profiles of functional connectivity alterations between each subtype and a group of typically developing control participants. RESULTS: Two major stable subtypes were found: subtype 1 exhibited hypoconnectivity (less average connectivity than typically developing control participants) and subtype 2, hyperconnectivity. The 2 subtypes did not differ in structural imaging metrics in any of the analyzed regions (68 cortical and 14 subcortical) or in any of the behavioral scores (including IQ, Autism Diagnostic Interview, and Autism Diagnostic Observation Schedule). Finally, only subtype 2, comprising about 43% of ASD participants, led to significant enrichments after multiple testing corrections. Notably, the dominant enrichment corresponded to excitation/inhibition imbalance, a leading well-known primary mechanism in the pathophysiology of ASD. CONCLUSIONS: Our results support a link between excitation/inhibition imbalance and functional connectivity alterations, but only in one ASD subtype, overall characterized by brain hyperconnectivity and major alterations in somatomotor and default mode networks.

Eating Behavior and Obesity in a Sample of Spanish Schoolchildren.

From the point of view of prevention, it is convenient to explore the association between eating behavior and the obese phenotype during school and adolescent age. The aim of the present study was to identify eating behavior patterns associated with nutritional status in Spanish schoolchildren. A cross-sectional study of 283 boys and girls (aged 6 to 16 years) was carried out. The sample was evaluated anthropometrically by Body Mass Index (BMI), waist-to-height ratio (WHtR) and body fat percentage (%BF). Eating behavior was analyzed using the CEBQ "Children's Eating Behavior Questionnaire". The subscales of the CEBQ were significantly associated with BMI, WHtR and %BF. Pro-intake subscales (enjoyment of food, food responsiveness, emotional overeating, desire for drinks) were positively related to excess weight by BMI (ß = 0.812 to 0.869; p = 0.002 to <0.001), abdominal obesity (ß = 0.543-0.640; p = 0.02 to <0.009) and high adiposity (ß = 0.508 to 0.595; p = 0.037 to 0.01). Anti-intake subscales (satiety responsiveness, slowness in eating, food fussiness) were negatively related to BMI (ß = -0.661 to -0.719; p = 0.009 to 0.006) and % BF (ß = -0.17 to -0.46; p = 0.042 to p = 0.016).

Genetic risk score for common obesity and anthropometry in Spanish schoolchildren.

IntroductionCommon or non-syndromic obesity is a complex polygenic trait conditioned by biallelic or single-base polymorphisms called SNPs (Single-Nucleotide Polymorphisms) that present an additive effect and act synergistically. Most genotype-obese phenotype association studies include body mass index (BMI) or waist-to-height ratio (WtHR), and very few introduce a broad anthropometric profile. ObjectiveTo verify whether a genetic risk score (GRS) developed from 10 SNPs is associated with the obesity phenotype assessed from anthropometric measures indicative of excess weight, adiposity and fat distribution. Material and methodsA series of 438 Spanish schoolchildren (6-16 years old) were evaluated anthropometrically (weight, height, waist circumference, skinfold thickness, BMI, WtHR, body fat percentage [%BF]). Ten SNPs were genotyped from saliva samples, generating a GRS for obesity, establishing genotype-phenotype association. ResultsSchoolchildren categorised as obese by BMI, ICT and %BF had higher GRS than their non-obese peers. The prevalence of overweight and adiposity was higher in subjects with a GRS above the median. Similarly, between 11 and 16 years of age, all anthropometric variables presented higher averages. ConclusionsGRS estimated from the 10 SNPs can be a diagnostic tool for the potential risk of obesity in Spanish schoolchildren and could be useful from the preventive perspective.

Multimodal and multidomain lesion network mapping enhances prediction of sensorimotor behavior in stroke patients.

Beyond the characteristics of a brain lesion, such as its etiology, size or location, lesion network mapping (LNM) has shown that similar symptoms after a lesion reflects similar dis-connectivity patterns, thereby linking symptoms to brain networks. Here, we extend LNM by using a multimodal strategy, combining functional and structural networks from 1000 healthy participants in the Human Connectome Project. We apply multimodal LNM to a cohort of 54 stroke patients with the aim of predicting sensorimotor behavior, as assessed through a combination of motor and sensory tests. Results are two-fold. First, multimodal LNM reveals that the functional modality contributes more than the structural one in the prediction of sensorimotor behavior. Second, when looking at each modality individually, the performance of the structural networks strongly depended on whether sensorimotor performance was corrected for lesion size, thereby eliminating the effect that larger lesions generally produce more severe sensorimotor impairment. In contrast, functional networks provided similar performance regardless of whether or not the effect of lesion size was removed. Overall, these results support the extension of LNM to its multimodal form, highlighting the synergistic and additive nature of different types of network modalities, and their corresponding influence on behavioral performance after brain injury.

Brain Mapping of Behavioral Domains Using Multi-Scale Networks and Canonical Correlation Analysis.

Simultaneous mapping of multiple behavioral domains into brain networks remains a major challenge. Here, we shed some light on this problem by employing a combination of machine learning, structural and functional brain networks at different spatial resolutions (also known as scales), together with performance scores across multiple neurobehavioral domains, including sensation, motor skills, and cognition. Provided by the Human Connectome Project, we make use of three cohorts: 640 participants for model training, 160 subjects for validation, and 200 subjects for model performance testing thus enhancing prediction generalization. Our modeling consists of two main stages, namely dimensionality reduction in brain network features at multiple scales, followed by canonical correlation analysis, which determines an optimal linear combination of connectivity features to predict multiple behavioral performance scores. To assess the differences in the predictive power of each modality, we separately applied three different strategies: structural unimodal, functional unimodal, and multimodal, that is, structural in combination with functional features of the brain network. Our results show that the multimodal association outperforms any of the unimodal analyses. Then, to answer which human brain structures were most involved in predicting multiple behavioral scores, we simulated different synthetic scenarios in which in each case we completely deleted a brain structure or a complete resting state network, and recalculated performance in its absence. In deletions, we found critical structures to affect performance when predicting single behavioral domains, but this occurred in a lesser manner for prediction of multi-domain behavior. Overall, our results confirm that although there are synergistic contributions between brain structure and function that enhance behavioral prediction, brain networks may also be mutually redundant in predicting multidomain behavior, such that even after deletion of a structure, the connectivity of the others can compensate for its lack in predicting behavior.

Mindfulness-based psychotherapy in patients with obsessive-compulsive disorder: A meta-analytical Study.

Background/Objective: Obsessive compulsive disorder is a disorder of special relevance in mental health, however, not all patients respond adequately to traditional intervention systems. The present work aims to study the usefulness of mindfulness-based interventions in patients with obsessive compulsive disorder. Method: An exhaustive search of the literature between 1996 and 2021 allowed us to locate 11 published articles. The effect size was the pretest-posttest standardized mean change calculated for obsession-compulsion, as well as depression symptoms and conscious coping. Results: he results showed mean effect sizes for mindfulness in the reduction of obsessive-compulsive symptoms (d + = 0.648) and, to a lesser extent, depression (d + = 0.417) and the improvement in Mindfull coping (d + = 0.509). There was no significant decrease in effect size when mindfulness was applied in patients with residual symptoms from previous treatments. Conclusions: These results are promising regarding the usefulness of the application of intervention programs based on mindfulness in people with obsessive compulsive disorder, both as an alternative option and as a complementary treatment to more traditional intervention formats.

Typological differences influence the bilingual advantage in metacognitive processing.

Previous studies showed a bilingual advantage in metacognitive processing (tracking one's own cognitive performance) in linguistic tasks. However, bilinguals do not constitute a homogeneous population, and it was unclear which aspects of bilingualism affect metacognition. In this project, we tested the hypothesis that simultaneous acquisition and use of typologically different languages leads to development of diverse processing strategies and enhances metacognition. The hypothesis was tested in the visual and auditory modalities in language and nonlanguage domains, in an artificial language learning task. In the auditory modality, the hypothesis was confirmed for linguistic stimuli, with no between-domain transfer of metacognitive abilities was observed at the individual level. In the visual modality, no differences in metacognitive efficiency were observed. Moreover, we found that bilingualism per se and the use of typologically different languages modulated separate metacognitive processes engaged in monitoring cognitive performance in statistical learning task. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Family care prior to the admission of the elderly in a nursing home and continuity in family care: A comparative study of Colombia and Spain.

This study examined the background before admission to a nursing home and the conditions for the continuity of care, of the relatives of older adults of Colombia and Spain. The study sample comprised 546 participants: 278 and 268 from Colombia and Spain, respectively. Structured interviews were conducted with the older adults' relatives. Sociodemographic similarities predominated, although in the Colombian sample there were significantly more unrelated people. Similarities in previous and current care conditions also predominated too. Cluster 1 included all the cases of Colombian low-resource nursing homes, and Cluster 2 included all the relatives of Colombian high-resource nursing homes and all the Spanish centers. The type of nursing home was the variable more important to identify the abovementioned clusters. Conclusions: Family members from Colombia and Spain continue to care for the elderly admitted to geriatric homes. The type of geriatric center is what establishes the differences in the users.

Heart-brain synchronization breakdown in Parkinson's disease.

Heart rate variability (HRV) abnormalities are potential early biomarkers in Parkinson's disease (PD) but their relationship with central autonomic network (CAN) activity is not fully understood. We analyzed the synchronization between HRV and brain activity in 31 PD patients and 21 age-matched healthy controls using blood-oxygen-level-dependent (BOLD) signals from resting-state functional brain MRI and HRV metrics from finger plethysmography recorded for 7.40 min. We additionally quantified autonomic symptoms (SCOPA-AUT) and objective autonomic cardiovascular parameters (blood pressure and heart rate) during deep breathing, Valsalva, and head-up tilt, which were used to classify the clinical severity of dysautonomia. We evaluated HRV and BOLD signals synchronization (HRV-BOLD-sync) with Pearson lagged cross-correlations and Fisher's statistics for combining window-length-dependent HRV-BOLD-Sync Maps and assessed their association with clinical dysautonomia. HRV-BOLD-sync was lower significantly in PD than in controls in various brain regions within CAN or in networks involved in autonomic modulation. Moreover, heart-brain synchronization index (HBSI), which quantifies heart-brain synchronization at a single-subject level, showed an inverse exposure-response relationship with dysautonomia severity, finding the lowest HBSI in patients with severe dysautonomia, followed by moderate, mild, and, lastly, controls. Importantly, HBSI was associated in PD, but not in controls, with Valsalva pressure recovery time (sympathetic), deep breathing E/I ratio (cardiovagal), and SCOPA-AUT. Our findings support the existence of heart-brain de-synchronization in PD with an impact on clinically relevant autonomic outcomes.