Individual Profiles Research Articles

Response to experimental cold-induced pain discloses a resistant category among endurance athletes, with a distinct profile of pain-related behavior and GABAergic EEG markers: a case-control preliminary study.

Pain is a major public health problem worldwide, with a high rate of treatment failure. Among promising non-pharmacological therapies, physical exercise is an attractive, cheap, accessible and innocuous method; beyond other health benefits. However, its highly variable therapeutic effect and incompletely understood underlying mechanisms (plausibly involving the GABAergic neurotransmission) require further research. This case-control study aimed to investigate the impact of long-lasting intensive endurance sport practice (≥7 h/week for the last 6 months at the time of the experiment) on the response to experimental cold-induced pain (as a suitable chronic pain model), assuming that highly trained individual would better resist to pain, develop advantageous pain-copying strategies and enhance their GABAergic signaling. For this purpose, clinical pain-related data, response to a cold-pressor test and high-density EEG high (Hβ) and low beta (Lβ) oscillations were documented. Among 27 athletes and 27 age-adjusted non-trained controls (right-handed males), a category of highly pain-resistant participants (mostly athletes, 48.1%) was identified, displaying lower fear of pain, compared to non-resistant non-athletes. Furthermore, they tolerated longer cold-water immersion and perceived lower maximal sensory pain. However, while having similar Hβ and Lβ powers at baseline, they exhibited a reduction between cold and pain perceptions and between pain threshold and tolerance (respectively -60% and - 6.6%; -179.5% and - 5.9%; normalized differences), in contrast to the increase noticed in non-resistant non-athletes (+21% and + 14%; +23.3% and + 13.6% respectively). Our results suggest a beneficial effect of long-lasting physical exercise on resistance to pain and pain-related behaviors, and a modification in brain GABAergic signaling. In light of the current knowledge, we propose that the GABAergic neurotransmission could display multifaceted changes to be differently interpreted, depending on the training profile and on the homeostatic setting (e.g., in pain-free versus chronic pain conditions). Despite limitations related to the sample size and to absence of direct observations under acute physical exercise, this precursory study brings into light the unique profile of resistant individuals (probably favored by training) allowing highly informative observation on physical exercise-induced analgesia and paving the way for future clinical translation. Further characterizing pain-resistant individuals would open avenues for a targeted and physiologically informed pain management.

Integrating Banking and Health Insurance for Secure Future

Abstract -In an era marked by technological advancements and interconnected financial services, the integration of banking and health insurance emerges as a strategic approach to foster a secure future for individuals. This conceptual framework envisions a seamless synergy between the banking and health insurance sectors, leveraging data analytics, blockchain technology, and artificial intelligence to enhance customer experiences, mitigate risks, and promote overall financial well- being. The integration process involves the convergence of financial and health data, allowing for a more comprehensive understanding of an individual's financial and health profile. Through secure data sharing mechanisms and advanced analytics, this integrated system enables personalized financial and health planning, ensuring that individuals are better equipped to manage unforeseen medical expenses without compromising their overall financial stability. Blockchain technology plays a pivotal role in establishing a secure and transparent infrastructure for data sharing and transaction processing. Smart contracts, built on blockchain, automate claims processing and facilitate real-time settlement, reducing administrative overhead and enhancing efficiency in the health insurance domain. Additionally, the decentralized nature of blockchain ensures the integrity and confidentiality of sensitive health and financial information. Artificial intelligence further enhances the integrated system by providing predictive analytics and risk assessment tools. By analyzing individual health data, spending patterns, and lifestyle choices, AI algorithms can predict potential health risks and recommend personalized insurance and financial products. This proactive approach not only empowers individuals to make informed decisions but also allows insurers and banks to offer targeted solutions that align with customers' evolving needs. Furthermore, the integration of banking and health insurance creates opportunities for innovative financial products, such as health savings accounts linked to investment portfolios. This dual-purpose approach encourages individuals to save for both their short-term medical needs and long-term International Journal of Scientific Research in Engineering and Management (IJSREM) Volume: 08 Issue: 01 | January - 2024 SJIF Rating: 8.176 ISSN: 2582-3930 © 2024, IJSREM | www.ijsrem.com DOI: 10.55041/IJSREM28065 | Page 2 financial goals, fostering a culture of financial responsibility and resilience. Keywords :- Integrated Financial Services,Data Analytics ,Blockchain Technology,Artificial Intelligence,Predictive Analytics,Risk Assessment ,Smart Contracts,Personalized Financial Planning ,Health Insurance Innovation

Prediction of low-density lipoprotein cholesterol levels using machine learning methods.

Low-density lipoprotein cholesterol (LDL-C) has been commonly calculated by equations, but their performance has not been entirely satisfactory. This study aimed to develop a more accurate LDL-C prediction model using machine learning methods. The study involved predicting directly measured LDL-C, using individual characteristics, lipid profiles, and other laboratory results as predictors. The models applied to predict LDL-C values were multiple regression, penalized regression, random forest, and XGBoost. Additionally, a novel 2-step prediction model was developed and introduced. The machine learning methods were evaluated against the Friedewald, Martin, and Sampson equations. The Friedewald, Martin, and Sampson equations had root mean squared error (RMSE) values of 12.112, 8.084, and 8.492, respectively, whereas the 2-step prediction model showed the highest accuracy, with an RMSE of 7.015. The LDL-C levels were also classified as a categorical variable according to the diagnostic criteria of the dyslipidemia treatment guideline, and concordance rates were calculated between the predictive values obtained from each method and the directly measured ones. The 2-step prediction model had the highest concordance rate (85.1%). The machine learning method can calculate LDL-C more accurately than existing equations. The proposed 2-step prediction model, in particular, outperformed the other machine learning methods.

Heart rate prediction with contactless active assisted living technology: a smart home approach for older adults.

As global demographics shift toward an aging population, monitoring their heart rate becomes essential, a key physiological metric for cardiovascular health. Traditional methods of heart rate monitoring are often invasive, while recent advancements in Active Assisted Living provide non-invasive alternatives. This study aims to evaluate a novel heart rate prediction method that utilizes contactless smart home technology coupled with machine learning techniques for older adults. The study was conducted in a residential environment equipped with various contactless smart home sensors. We recruited 40 participants, each of whom was instructed to perform 23 types of predefined daily living activities across five phases. Concurrently, heart rate data were collected through Empatica E4 wristband as the benchmark. Analysis of data involved five prominent machine learning models: Support Vector Regression, K-nearest neighbor, Random Forest, Decision Tree, and Multilayer Perceptron. All machine learning models achieved commendable prediction performance, with an average Mean Absolute Error of 7.329. Particularly, Random Forest model outperformed the other models, achieving a Mean Absolute Error of 6.023 and a Scatter Index value of 9.72%. The Random Forest model also showed robust capabilities in capturing the relationship between individuals' daily living activities and their corresponding heart rate responses, with the highest R2 value of 0.782 observed during morning exercise activities. Environmental factors contribute the most to model prediction performance. The utilization of the proposed non-intrusive approach enabled an innovative method to observe heart rate fluctuations during different activities. The findings of this research have significant implications for public health. By predicting heart rate based on contactless smart home technologies for individuals' daily living activities, healthcare providers and public health agencies can gain a comprehensive understanding of an individual's cardiovascular health profile. This valuable information can inform the implementation of personalized interventions, preventive measures, and lifestyle modifications to mitigate the risk of cardiovascular diseases and improve overall health outcomes.

Citrus p-Synephrine Improves Energy Homeostasis by Regulating Amino Acid Metabolism in HFD-Induced Mice.

p-Synephrine is a common alkaloid widely distributed in citrus fruits. However, the effects of p-synephrine on the metabolic profiles of individuals with energy abnormalities are still unclear. In the study, we investigated the effect of p-synephrine on energy homeostasis and metabolic profiles using a high fat diet (HFD)-induced mouse model. We found that p-synephrine inhibited the gain in body weight, liver weight and white adipose tissues weight induced by HFD. p-Synephrine supplementation also reduced levels of serum total cholesterol (TC), triglyceride (TG) and low-density lipoprotein cholesterol (LDL-C) but not to a statistically significant degree. Histological analysis showed that HFD induced excessive lipid accumulation and glycogen loss in the liver and adipocyte enlargement in perirenal fat tissue, while p-synephrine supplementation reversed the changes induced by HFD. Moreover, HFD feeding significantly increased mRNA expression levels of tumor necrosis factor-α (TNF-α) and interleukin-1β (IL-1β) and reduced the mRNA expression level of interleukin-10 (IL-10) compared to the control group, while p-synephrine supplementation significantly reversed these HFD-induced changes. Liver and serum metabolomic analysis showed that p-synephrine supplementation significantly altered small molecule metabolites in liver and serum in HFD mice and that the changes were closely associated with improvement of energy homeostasis. Notably, amino acid metabolism pathways, both in liver and serum samples, were significantly enriched. Our study suggests that p-synephrine improves energy homeostasis probably by regulating amino acid metabolism in HFD mice, which provides a novel insight into the action mechanism of p-synephrine modulating energy homeostasis.

Individual In-Situ GPS-Derived Acceleration-Speed Profiling: Toward Automatization and Refinement in Male Professional Rugby Union Players

BackgroundRecently a proof-of-concept was proposed to derive the soccer players’ individual in-situ acceleration-speed (AS) profile from global positioning system (GPS) data collected over several sessions and games. The present study aimed to propose an automatized method of individual GPS-derived in-situ AS profiling in a professional rugby union setting.MethodAS profiles of forty-nine male professional rugby union players representing 61.5 million positions, from which acceleration was derived from speed during 51 training sessions and 11 official games, were analyzed. A density-based clustering algorithm was applied to identify outlier points. Multiple AS linear relationships were modeled for each player and session, generating numerous theoretical maximal acceleration (A0), theoretical maximal running speed (S0) and AS slope (ASslope, i.e., overall orientation of the AS profile). Each average provides information on the most relevant value while the standard deviation denotes the method accuracy. In order to assess the reliability of the AS profile within the data collection period, data were compared over two 2-week phases by the inter-class correlation coefficient. A0 and S0 between positions and type of sessions (trainings and games) were compared using ANOVA and post hoc tests when the significant threshold had been reached.ResultsAll AS individual profiles show linear trends with high coefficient of determination (r2 > 0.81). Good reliability (Inter-class Correlation Coefficient ranging from 0.92 to 0.72) was observed between AS profiles, when determined 2 weeks apart for each player. AS profiles depend on players’ positions, types of training and games. Training and games data highlight that highest A0 are obtained during games, while greatest S0 are attained during speed sessions.ConclusionsThis study provides individual in-situ GPS-derived AS profiles with automatization capability. The method calculates an error of measurement for A0 and S0, of paramount importance in order to improve their daily use. The AS profile differences between training, games and playing positions open several perspectives for performance testing, training monitoring, injury prevention and return-to-sport sequences in professional rugby union, with possible transferability to other sprint-based sports.Key PointsAS profiles computed from rugby union GPS data provide positional benchmarks during training and competition.This study provides automatic detection of atypical data and the computation of error measurement of theoretical maximal acceleration and speed components.This refinement constitutes a step forward for a daily use of ecological data by considering data collection and method reliabilities.This easy-to-implement approach may facilitate its use to the performance management process (talent identification, training monitoring and individualization, return-to-sport).

Effects of classroom‐based social problem‐solving training on elementary school children: Investigating the moderating role of executive function

AbstractSocial problem‐solving (SPS) skills represent an individual's ability to effectively solve daily problems. Although previous studies have demonstrated the positive effects of SPS interventions, there is still a lack of evidence on the relevant moderating factors. Therefore, this study investigated the impact of an SPS intervention on a sample of elementary school children, by focusing on the potential moderating effects of executive function. The participants included a total of 101 fifth graders (mean age of 10.6 years), who were divided into two groups for an immediate intervention (treatment) and delayed intervention (control). The following three aspects were measured pre‐ and postintervention: SPS skills, emotional regulation, and school adjustment. Preintervention, we measured two aspects of executive function using the Cambridge Neuropsychological Test Automated Battery, including working memory and inhibition. Following the intervention, the participants increasingly generated alternative solutions, which may have contributed to better adaptive functioning and solutions. However, we also observed some negative impacts on participants with lower executive functioning, including deteriorating effects on emotional regulation (problem solving) and life satisfaction. These findings emphasize the need to pay close attention to the individual profiles of the recipients to design more effective interventions.

MTHFR (C677T) polymorphism and its association with cytogenetic and clinical profile in individuals with primary amenorrhea

BackgroundAbnormal folate metabolism is a risk factor for DNA hypomethylation and chromosomal nondisjunction. MTHFR is a candidate gene for folliculogenesis and ovarian development. In the present study, we aimed to investigate the distribution of the MTHFR C677T polymorphism in individuals with primary amenorrhea and it’s association with the cytogenetic and clinical profile. The MTHFR polymorphism (C677T) was checked in 45 females with PA and 45 control females (age-matched) with regular menstrual cycles using polymerase chain reaction-restriction fragment length polymorphism.ResultsWe observed the CC genotype in 84.4% (n = 38) of the control group females and 48.9% (n = 22) of the case group females, CT genotype in 13.3% (n = 6) in the control group females and 24.4% (n = 11) in the case group females (p = 0.039; χ2 value 4.253; odd ratio 0.316, 95%CI 0.103–0.973) and TT genotype in 2.2% (n = 1) in the control group females and 26.7% (n = 12) in the case group females (p = 0.000266; χ2 value 13.294; odd ratio 0.048, 95%CI 0.006–0.397). Out of 45 case group females, 26 females showed 46,XX karyotype, 4 females showed male karyotype, 3 females showed pure Turner karyotype, 2 females were mosaic Turner and the rest of the females showed structural abnormalities like deletion, isochromosome and normal variants. The serum values revealed significantly lower levels (p = 0.032) of progesterone in the individuals with the TT genotype as compared to the CC genotype and the radiology profile showed a significant role of the MTHFR gene in ovarian development (p = 0.024).ConclusionWe suggest that the MTHFR polymorphism (C677T) might be responsible for the chromosomal nondisjunction in monosomy X females. It also influences the progesterone level and ovarian development, thus affecting folliculogenesis and the ovarian reserve responsible for primary amenorrhea.

Psychological profiles and prescription opioid misuse, craving, and withdrawal in people with chronic pain.

The negative consequences of prescription opioid misuse and opioid use disorder make it relevant to identify factors associated with this problem in individuals with chronic pain. This cross-sectional study aimed at identifying subgroups of people with chronic pain based on their psychological profiles, prescription opioid misuse, craving, and withdrawal. The sample comprised 185 individuals with chronic pain. We performed hierarchical cluster analysis on impulsivity, anxiety sensitivity, pain acceptance, pain intensity, opioid misuse, craving, and withdrawal. The four-cluster solution was the optimal one. Misuse, craving, and anxiety sensitivity were higher among people in the Severe-problems cluster than among people in the other three clusters. Withdrawal was the highest in the High-withdrawal cluster. Impulsivity was higher among people in the Severe-problems and High-withdrawal clusters than those in the Moderate-problems and Mild-problems clusters. Pain acceptance was higher among people in the Mild-problems cluster than among people in the other three clusters. Anxiety sensitivity and misuse were higher among people in the Moderate-problems cluster than among people in the Mild-problems cluster. These results support that impulsivity, anxiety sensitivity, and pain acceptance are useful constructs to identify subgroups of people with chronic pain according to their level of prescription opioid misuse, craving, and withdrawal. The results of this study may help in selecting the early intervention most suitable for each of the identified profiles. The psychological profile of individuals with chronic pain, prescription opioid misuse, craving, and withdrawal is characterized by fearing anxiety-related symptoms due to the catastrophic interpretation of such symptoms and reacting impulsively to negative moods. In contrast, participants with high pain acceptance had less prescription opioid misuse, craving, and withdrawal. The profiles identified in this study could help clinicians select targets for intervention among profiles with similar needs and facilitate early interventions to prevent opioid misuse onset or aggravation.

Sleep and the Social Profiles of Individuals With Rett Syndrome

BackgroundThis study investigates the distinctive social behaviors observed in individuals with Rett syndrome (RTT), characterized by the loss of spoken language, impaired eye gaze communication, gait abnormalities, and sleep issues. The research aims to identify social profiles in RTT and explore their correlation with sleep, sleep-disordered breathing (SDB), and daytime sleepiness. MethodsStandard overnight sleep macrostructure and respiratory parameters were assessed. Extracting 25 social-related items and one for daytime sleepiness from the Rett Syndrome Behavioral Questionnaire, factor analysis was applied to establish latent social profiles. These profiles were then correlated with sleep parameters. The nonparametric Mann-Whitney U test compared social profiles based on the presence of SDB (defined by an apnea-hypopnea index greater than one per hour) and daytime sleepiness. ResultsThe study involved 12 female subjects with confirmed RTT diagnoses and MECP2 mutations, aged 8.54 ± 5.30 years. The Rett Syndrome Behavioral Questionnaire revealed a total average score of 25.83 ± 12.34, indicating varying degrees of social impairments. Comprising 25 social-related items, factor analysis yielded four social profiles: “interactive motricity,” “mood change,” “anxiety/agitation,” and “gazing.” Longer sleep onset latency correlated with increased socio-behavioral impairments, particularly in interactive motricity reduction. Conversely, higher rapid eye movement sleep was associated with fewer interactive socio-motor behaviors. No significant differences in social profiles were found concerning the presence of SDB or daytime sleepiness. ConclusionsThe findings suggest four distinct social profiles in RTT individuals, hinting at shared disrupted circuits between sensorimotor functioning and sleep-related neuronal pathways. Despite the absence of differences in SDB or daytime sleepiness, the study highlights the relationship between sleep parameters, such as sleep onset latency and rapid eye movement sleep, and socio-behavioral outcomes in RTT with MECP2 mutations.

Pre-treatment predictors of cognitive side-effects after treatment with electroconvulsive therapy in patients with depression: A multicenter study

BackgroundElectroconvulsive therapy (ECT) is a highly effective treatment for major depressive episodes (MDE). However, ECT-induced cognitive side-effects remain a concern. Identification of pre-treatment predictors that contribute to these side-effects remain unclear. We examined cognitive performance and individual cognitive profiles over time (up to six months) following ECT and investigated possible pre-treatment clinical and demographic predictors of cognitive decline shortly after ECT. Methods634 patients with MDE from five sites were included with recruitment periods between 2001 and 2020. Linear mixed models were used to examine how cognitive performance, assessed with an extensive neuropsychological test battery, evolved over time following ECT. Next, possible pre-treatment predictors of cognitive side-effects directly after ECT were examined using linear regression. ResultsDirectly after ECT, only verbal fluency (animal and letter; p < 0.0001; Cohen's d: −0.25 and −0.29 respectively) and verbal recall (p < 0.0001; Cohen's d: −0.26) significantly declined. However, during three and six months of follow-up, cognitive performance across all domains significantly improved, even outperforming baseline levels. No other pre-treatment factor than a younger age predicted a larger deterioration in cognitive performance shortly after ECT. LimitationsThere was a substantial amount of missing data especially at 6 months follow-up. ConclusionsOur findings show that verbal fluency and memory retention are temporarily affected immediately after ECT. Younger patients may be more susceptible to experiencing these acute cognitive side-effects, which seems to be mostly due to a more intact cognitive functioning prior to ECT. These findings could contribute to decision-making regarding treatment selection, psychoeducation, and guidance during an ECT course.

Profiles of Peer-Rejected Individuals: Their Attitudes toward the Intellectual Disability Population and the Mediating Role of Resilience

Literature shows that public perceptions toward people with intellectual disability (ID) tend to be negative, perhaps more so than toward any other population with disabilities, causing severe consequences on the quality of life of these people. Understanding factors associated with these attitudes may contribute to better integration of the ID population into society. This study focuses on the predictive role of school-age peer rejection and contemporaneous familial support on attitudes toward people with ID. Specifically, it aims to identify distinct profiles of people who experienced peer rejection during their school years and who experienced various levels of familial support during the rejection period, and to examine the disparities between these profiles regarding attitudes toward people with ID. An additional goal is to examine whether resilience can mediate the association between profiles of peer-rejected individuals and their attitudes toward individuals with ID. The research sample comprised 1063 Israeli adults reporting various levels of peer rejection during school years. Cluster analysis revealed two profiles of peer-rejected individuals that significantly differ in the level of familial support provided in the face of peer rejection. In accordance with the hypotheses, attitudes of peer-rejected individuals with poor familial support were more negative than those with high familial support and the mediating effect of resilience was significant. Findings emphasize the protective role of familial support in the face of peer rejection, contributing to the emerging literature that deals with the long-term effects of peer rejection and poor resiliency resources on negative attitudes toward out-groups.

Dietary Epigenetic Modulators: Unravelling the Still-Controversial Benefits of miRNAs in Nutrition and Disease.

In the context of nutrient-driven epigenetic alterations, food-derived miRNAs can be absorbed into the circulatory system and organs of recipients, especially humans, and potentially contribute to modulating health and diseases. Evidence suggests that food uptake, by carrying exogenous miRNAs (xenomiRNAs), regulates the individual miRNA profile, modifying the redox homeostasis and inflammatory conditions underlying pathological processes, such as type 2 diabetes mellitus, insulin resistance, metabolic syndrome, and cancer. The capacity of diet to control miRNA levels and the comprehension of the unique characteristics of dietary miRNAs in terms of gene expression regulation show important perspectives as a strategy to control disease susceptibility via epigenetic modifications and refine the clinical outcomes. However, the absorption, stability, availability, and epigenetic roles of dietary miRNAs are intriguing and currently the subject of intense debate; additionally, there is restricted knowledge of their physiological and potential side effects. Within this framework, we provided up-to-date and comprehensive knowledge on dietary miRNAs' potential, discussing the latest advances and controversial issues related to the role of miRNAs in human health and disease as modulators of chronic syndromes.

Legal Perspectives on the Rehabilitation of Sex Offenders: Efficacy, Ethical Considerations, and the Pursuit of Recidivism Reduction

This dissertation critically examines the efficacy of group-based therapeutic interventions for sex offenders within correctional facilities, aiming to enhance rehabilitation and reduce recidivism. Despite contemporary treatment paradigms demonstrating some effectiveness, as indicated by lower recidivism rates among treated offenders, the success of these programs is not uniform, prompting a need for reevaluation. Treatment challenges include infrastructural limitations, the need for individualized approaches due to offenders' diverse psychosocial profiles, and the complexity of achieving group cohesion. Furthermore, high dropout rates and short assessment periods undermine the establishment of evidence-based practices. The dissertation advocates for a stratified approach to therapy, recognizing individual psychological profiles and tailoring treatment accordingly. It calls for advancements in cognitive-behavioral therapy (CBT) methodologies within Sex Offender Treatment Programs (SOTPs), considering ethical dimensions of interventions such as chemical castration, and employing Multisystemic Therapy (MST) with biometric monitoring to better assess and manage recidivism risks. This synthesis of academic literature and analysis of programmatic limitations highlights the necessity of refining sex offender rehabilitation to ensure public safety effectively.

Sensitisation profile to pollen allergens of selected grass and tree species in Filipino communities

Pollen allergy remains insufficiently studied in the Philippines despite its global significance. This community-based, cross-sectional study thus determined the sensitisation profile of Filipino individuals to pollen allergens from selected grass species (Zea mays, Saccharum spontaneum, and Dichanthium spp.) and tree species (Mangifera indica, Delonix regia, and Peltophorum pterocarpum). Study subjects (n = 523), 2–70 years old, and residents of Bustos, Bulacan, Mayorga, Leyte, and Laoag, Ilocos Norte, were recruited from November 2018 to July 2019. Clinical history was evaluated through a self-directed questionnaire, while pollen sensitisation was assessed through skin prick test (SPT) and pollen-specific immunoglobulin E enzyme-linked immunosorbent assay (sIgE ELISA). Correlation and multiple logistic regression analyses were performed to identify significant relationships between pollen sensitisation and demographic characteristics. Of the 523 study subjects, 38.24% reported symptoms of allergic rhinitis, 32.70% reported atopic dermatitis, and 30.02% reported allergic asthma. Participants were mainly sensitised to M. indica (32.70%). More males were sensitised at earlier age groups than females. Alternatively, females had increased odds of reporting allergic rhinitis and more than one type of allergic disease. Sensitisation to tree pollen, age, smoking, and secondhand smoking status were also significant predictors (p ≥ 0.05). Smoking status, sex, age, family history, and sensitisation to tree pollen were significant risk factors associated with allergic diseases.

Exploring the cognitive profiles related to unimodal auditory versus multisensory hallucinations in schizophrenia-spectrum disorders

ABSTRACT Introduction Hallucinations can be experienced across multiple sensory modalities, but psychiatric studies investigating the cognitive mechanisms of hallucinations have been somewhat restricted to the auditory domain. This study explored the cognitive profiles of individuals experiencing multisensory hallucinations (MH) in schizophrenia-spectrum disorders (SSD) and compared these to those experiencing unimodal auditory hallucinations (AH) or no hallucinations (NH). Methods Participants included SSD patients (n = 119) stratified by current hallucination status (NH, AH, MH) and nonclinical controls (NCs; n = 113). Group performance was compared across several cognitive domains: speed of processing, attention, working memory, verbal learning, visual learning, reasoning and problem-solving, social cognition, and inhibition. Results The clinical groups performed worse than NCs but differences between the clinical groups were not evident across most cognitive domains. Exploratory analyses revealed that the MH group was more impaired on the visual learning task compared to the NH (but not AH) group. Conclusions Preliminary results suggest that impaired visual learning may be related to MH. This could be attributed to the presence of visual hallucinations (VH), or greater psychopathology, in this group. However, replication is needed, as well as the investigation of other potential cognitive mechanisms of MH.

Emotion regulation, hope, and optimism during the third wave of the COVID-19 pandemic: The role of age and personality.

This study examined age-related differences between young and older adults' emotion regulation, hope, and optimism 1 year after the COVID-19 outbreak. Whether personality explained such outcomes was also examined. A sample of 228 young adults and 161 older adults was interviewed in April-May 2021 to complete questionnaires assessing cognitive reappraisal (CR) and expressive suppression (ES) emotion regulation strategies use, optimism, hope (agency and pathways components), and personality traits. Older adults reported greater CR and ES use, optimism, and hope-agency levels than young adults, whereas no age differences emerged for hope-pathway scores. Personality traits (more consistently emotional stability) contributed to explaining CR and ES use, and greater hopeful and optimistic dispositions. These findings confirm older adults' advantage in facing the emotional and psychological fallout of the COVID-19 pandemic in its third wave. They also underscore the importance of considering personality to depict individual profiles prone to experiencing long-term negative emotional/psychological consequences of emergencies as COVID-19.

VigiNUTRI Brasil: methods of request, data extraction, treatment and consistency analysis of individual data from adolescents monitored by the Food and Nutrition Surveillance System (Sisvan Web).

To describe the methods for requesting, extracting data, processing and analyzing the consistency of anthropometric and food consumption data of adolescents monitored by Sisvan Web. Methodological study with individualized data from Sisvan web between 2008 and 2018. The modules of anthropometry and consumption, made available by the Ministry of Health, had a unique identifier for linkages. Implausible values and individuals outside the age range were excluded. Consistency analyses, with corrections for imputations and descriptive statistics, were performed using Stata 16.0 software. A database was obtained with 18,812,232 observations of anthropometric data between 2008 and 2018 and 440,534 records of food consumption between 2015 and 2018; after merging the banks, 64,976 observations were obtained. The combination of anthropometry and food consumption databases made it possible to link individual adolescent data and build a database with information for future analyzes relating to the dietary and nutritional profile of the same individual. The proposal for processing individual data from the Food and Nutrition Surveillance System (Sisvan Web) generated 18 million observations for anthropometric data and 65,000 observations after merging the anthropometry and food consumption databases. This work will enable replication of the methodology for processing data available in Sisvan Web, allowing for enhanced analyzes by healthcare teams and researchers in the field of public health. It is expected that these procedures will assist researchers, managers and healthcare professionals in handling and analyzing the information generated by Sisvan Web.

Salivary proteomic profile of response to different resistance training protocols: A case report.

Resistance training (RT) with blood flow restriction (BFR) or high intensity (HI) are effective to increase muscle mass. To understand this effect, techniques known as "omics" are used to identify possible biomarkers. This study analyzed the salivary proteomic profile of healthy individuals trained before and after two RT protocols both designed with eight exercises for upper- and lower-limbs, one performed at low percentage of one-maximum repetition (%1RM) with BFR technique, and other at high %1RM (HI) without BRF technique. Four healthy males between 18 and 28 years participated in the study. Stimulated saliva was collected before (BBFR/BHI) and immediately after (ABFR/AHI) the two RT protocols. All protein-related processing was performed using label-free proteomic. The difference in expression between groups was expressed as p < .05 for downregulated proteins and 1-p > .95 for upregulated proteins. There was difference in salivary flow between ABFR and BBFR (p = .005). For HI, 87 proteins were found after the practice and 119 before. Three hemoglobin isoforms were increased in AHI compared with BHI. In the BFR comparison, 105 proteins were identified after (ABFR) and 70 before (BBFR). Among those increased ABFR, we highlight five hemoglobin isoforms and Deleted in malignant brain tumors 1 protein. Between ABFR and AHI, 17 isoforms of histones, Transaldolase, Transketolase, Glyceraldehyde-3-phosphate dehydrogenase, and Antileukoproteinase were decreased ABFR. For HI, there was an increase in proteins related to oxidative stress and metabolism of the musculoskeletal system, compared with BFR. HI seems to induce higher anabolic signaling to muscle mass increase and antiatherosclerotic effects.

Effects of fat loss and low energy availability on the serum cardiometabolic profile of physique athletes.

Low energy availability (LEA) is a health concern for athletes, although it may paradoxically lead to improved cardiometabolic health in the general population. We investigated the associations between LEA, body composition, and serum cardiometabolic profile in 23 physique athletes (DIET) and 21 controls (CONT) during a 5-month pre-competition diet (MID), followed by 1 week of increased energy availability (COMP) and a 5-month weight regain period (POST). Quantification of 250 serum metabolome variables was conducted by NMR spectroscopy, body composition by dual-energy x-ray absorptiometry, dietary intake by food diaries, and exercise levels by training logs. Body fat percentage decreased from 19.5 ± 7.0% to 8.3 ± 5.3% (p < 0.001) in DIET through increased exercise levels and decreased energy intake, while CONT maintained those constant. In MID, DIET had increased (FDR < 0.01) HDL cholesterol, HDL particle size and number, and decreased (FDR < 0.05) VLDL lipids, serum triglycerides, and low-grade inflammation (glycoprotein acetyls) compared to baseline and CONT. The changes were associated with reduced android fat mass (-78 ± 13%) and energy intake (-28 ± 10%). In COMP, most of the metabolic changes found in MID persisted, except for altered triglycerides in all lipoprotein classes. After weight regain in POST, serum metabolome, body composition, energy intake, and exercise levels had reverted to baseline levels. In conclusion, fat loss and LEA may have beneficial yet transient effects on the serum cardiometabolic profile of lean individuals. Especially the HDL lipidome and lipoprotein triglycerides offer potential novel biomarkers for detecting LEA in athletes.