Brain health in diverse settings: How age, demographics and cognition shape brain function.

Diversity in brain health is influenced by individual differences in demographics and cognition. However, most studies on brain health and diseases have typically controlled for these factors rather than explored their potential to predict brain signals. Here, we assessed the role of individual differences in demographics (age, sex, and education; n = 1298) and cognition (n = 725) as predictors of different metrics usually used in case-control studies. These included power spectrum and aperiodic (1/f slope, knee, offset) metrics, as well as complexity (fractal dimension estimation, permutation entropy, Wiener entropy, spectral structure variability) and connectivity (graph-theoretic mutual information, conditional mutual information, organizational information) from the source space resting-state EEG activity in a diverse sample from the global south and north populations. Brain-phenotype models were computed using EEG metrics reflecting local activity (power spectrum and aperiodic components) and brain dynamics and interactions (complexity and graph-theoretic measures). Electrophysiological brain dynamics were modulated by individual differences despite the varied methods of data acquisition and assessments across multiple centers, indicating that results were unlikely to be accounted for by methodological discrepancies. Variations in brain signals were mainly influenced by age and cognition, while education and sex exhibited less importance. Power spectrum activity and graph-theoretic measures were the most sensitive in capturing individual differences. Older age, poorer cognition, and being male were associated with reduced alpha power, whereas older age and less education were associated with reduced network integration and segregation. Findings suggest that basic individual differences impact core metrics of brain function that are used in standard case-control studies. Considering individual variability and diversity in global settings would contribute to a more tailored understanding of brain function.

Educational disparities in brain health and dementia across Latin America and the United States.

BACKGROUND: Education influences brain health and dementia. However, its impact across regions, specifically Latin America (LA) and the United States (US), is unknown. METHODS: A total of 1412 participants comprising controls, patients with Alzheimer's disease (AD), and frontotemporal lobar degeneration (FTLD) from LA and the US were included. We studied the association of education with brain volume and functional connectivity while controlling for imaging quality and variability, age, sex, total intracranial volume (TIV), and recording type. RESULTS: Education influenced brain measures, explaining 24%-98% of the geographical differences. The educational disparities between LA and the US were associated with gray matter volume and connectivity variations, especially in LA and AD patients. Education emerged as a critical factor in classifying aging and dementia across regions. DISCUSSION: The results underscore the impact of education on brain structure and function in LA, highlighting the importance of incorporating educational factors into diagnosing, care, and prevention, and emphasizing the need for global diversity in research. HIGHLIGHTS: Lower education was linked to reduced brain volume and connectivity in healthy controls (HCs), Alzheimer's disease (AD), and frontotemporal lobar degeneration (FTLD). Latin American cohorts have lower educational levels compared to the those in the United States. Educational disparities majorly drive brain health differences between regions. Educational differences were significant in both conditions, but more in AD than FTLD. Education stands as a critical factor in classifying aging and dementia across regions.

Biomarkers of Periodontitis and Its Differential DNA Methylation and Gene Expression in Immune Cells: A Systematic Review.

The characteristic epigenetic profile of periodontitis found in peripheral leukocytes denotes its impact on systemic immunity. In fact, this profile not only stands for periodontitis as a low-grade inflammatory disease with systemic effects but also as an important source of potentially valuable clinical biomarkers of its systemic effects and susceptibility to other inflammatory conditions. Thus, we aimed to identify relevant genes tested as epigenetic systemic biomarkers in patients with periodontitis, based on the DNA methylation patterns and RNA expression profiles in peripheral immune cells. A detailed protocol was designed following the Preferred Reporting Items for Systematic Review and Meta-analysis -PRISMA guideline. Only cross-sectional and case-control studies that reported potential systemic biomarkers of periodontitis in peripheral immune cell types were included. DNA methylation was analyzed in leukocytes, and gene expression was in polymorphonuclear and mononuclear cells. Hypermethylation was found in TLR regulators genes: MAP3K7, MYD88, IL6R, RIPK2, FADD, IRAK1BP1, and PPARA in early stages of periodontitis, while advanced stages presented hypomethylation of these genes. TGFB1I1, VNN1, HLADRB4, and CXCL8 genes were differentially expressed in lymphocytes and monocytes of subjects with poorly controlled diabetes mellitus, dyslipidemia, and periodontitis in comparison with controls. The DAB2 gene was differentially overexpressed in periodontitis and dyslipidemia. Peripheral blood neutrophils in periodontitis showed differential expression in 163 genes. Periodontitis showed an increase in ceruloplasmin gene expression in polymorphonuclears in comparison with controls. Several genes highlight the role of the epigenetics of peripheral inflammatory cells in periodontitis that could be explored in blood as a source of biomarkers for routine testing.

ZNF718, HOXA4, and ZFP57 are differentially methylated in periodontitis in comparison with periodontal health: Epigenome-wide DNA methylation pilot study.

OBJECTIVE: To investigate the differences in the epigenomic patterns of DNA methylation in peripheral leukocytes between patients with periodontitis and gingivally healthy controls evaluating its functional meaning by functional enrichment analysis. BACKGROUND: The DNA methylation profiling of peripheral leukocytes as immune-related tissue potentially relevant as a source of biomarkers between periodontitis patients and gingivally healthy subjects has not been investigated. METHODS: A DNA methylation epigenome-wide study of peripheral leukocytes was conducted using the Illumina MethylationEPIC platform in sixteen subjects, eight diagnosed with periodontitis patients and eight age-matched and sex-matched periodontally healthy controls. A trained periodontist performed the clinical evaluation. Global DNA methylation was estimated using methylation-sensitive high-resolution melting in LINE1. Routine cell count cytometry and metabolic laboratory tests were also performed. The analysis of differentially methylated positions (DMPs) and differentially methylated regions (DMRs) was made using R/Bioconductor environment considering leukocyte populations assessed in both routine cell counts and using the FlowSorted.Blood.EPIC package. Finally, a DMP and DMR intersection analysis was performed. Functional enrichment analysis was carried out with the differentially methylated genes found in DMP. RESULTS: DMP analysis identified 81 differentially hypermethylated genes and 21 differentially hypomethylated genes. Importantly, the intersection analysis showed that zinc finger protein 718 (ZNF718) and homeobox A4 (HOXA4) were differentially hypermethylated and zinc finger protein 57 (ZFP57) was differentially hypomethylated in periodontitis. The functional enrichment analysis found clearly immune-related ontologies such as "detection of bacterium" and "antigen processing and presentation." CONCLUSION: The results of this study propose three new periodontitis-related genes: ZNF718, HOXA4, and ZFP57 but also evidence the suitability and relevance of studying leukocytes' DNA methylome for biological interpretation of systemic immune-related epigenetic patterns in periodontitis.

A low-cost, wireless near-infrared spectroscopy device detects the presence of lower extremity atherosclerosis as measured by computed tomographic angiography and characterizes walking impairment in peripheral artery disease.

BACKGROUND: Patients with peripheral artery disease (PAD) who experience intermittent claudication report a range of symptoms. Patients with symptoms other than classically described intermittent claudication may be at the highest risk for functional decline and mobility loss. Therefore, technologies allowing for characterization of PAD severity are desirable. Near-infrared spectroscopy (NIRS) allows for measurements of muscle heme oxygen saturation (StO2) during exercise. We hypothesized lower extremities affected by PAD would exhibit distinct NIRS profiles as measured by a low-cost, wireless NIRS device and that NIRS during exercise predicts walking limitation. METHODS: We recruited 40 patients with PAD and 10 control participants. All patients with PAD completed a computed tomographic angiography, 6-minute walk test, and a standardized treadmill test. Controls completed a 540-second treadmill test for comparison. StO2 measurements were continuously taken from the gastrocnemius during exercise. Variables were analyzed by Fischer's exact, χ2, Wilcoxon rank-sum, and Kruskal-Wallis tests as appropriate. Correlations were assessed by partial Spearman correlation coefficients adjusted for occlusive disease pattern. RESULTS: Patients with PAD experienced claudication onset at a median of 108 seconds with a median peak walking time of 288 seconds. The baseline StO2 was similar between PAD and control. The StO2 of PAD and control participants dropped below baseline at a median of 1 and 104 seconds of exercise, respectively (P < .0001). Patients with PAD reached minimum StO2 earlier than control participants (119 seconds vs 522 seconds, respectively; P < .001) and experienced a greater change in StO2 at 1 minute of exercise (-73.2% vs 8.3%; P < .0001) and a greater decrease at minimum exercise StO2 (-83.4% vs -16.1%; P < .0001). For patients with PAD, peak walking time, and 6-minute walking distance correlated with percent change in StO2 at 1 minute of exercise (r = -0.76 and -0.67, respectively; P < .001) and time to minimum StO2 (r = 0.79 and 0.70, respectively; P < .0001). CONCLUSIONS: In this initial evaluation of a novel, low-cost NIRS device, lower extremities affected by PAD exhibited characteristic changes in calf muscle StO2, which differentiated them from healthy controls and were strongly correlated with walking impairment. These findings confirm and expand on previous work demonstrating the potential clinical value of NIRS devices and the need for further research investigating the ability of low-cost NIRS technology to evaluate, diagnose, and monitor treatment response in PAD.

Quantification of Daily Physical Activity and Sedentary Behavior of Claudicating Patients.

BACKGROUND: Claudication is the most common manifestation of peripheral artery disease (PAD), producing significant ambulatory compromise. Limited information exists on the routine physical activity of claudicating patients. Our objective was to record the intensity/time profiles of physical activity and the timing and duration of sedentary behavior of a sample of community-dwelling claudicating patients. METHODS: Forty-four claudicating patients referred to our vascular clinic were recruited. Physical activity was recorded using the ActiGraph GT1M activity monitor. The Actigraph monitor is a lightweight instrument designed to measure human movement through changes in acceleration, measured as counts over 1-minute time periods. Data from 7 consecutive days were used for the calculations. We processed the data using the ActiLife software program. RESULTS: The average daily activity of the claudicating patients shows a steady increase beginning approximately 05:30 AM until a peak plateau from approximately 10:00 AM to 01:30 PM followed by a steady decrease until approximately 09:30 PM, when a sustained period of inactivity begins. The average claudicating patient takes 3586 steps per day at an average intensity of 1.77 metabolic equivalents of task (METs, a physiological measure expressing the energy cost of physical activities). Average physical activity intensity and peak intensity fluctuate very little during the day, and they rarely exceed the level of light activity (light = <3 METs maximum effort, such as casual walking or light housework). During awake time, approximately 7 hours are spent in sedentary behaviors (<1.5 METs), and sedentary time is spread throughout the day mostly in short intervals between periods of low-energy activity. CONCLUSIONS: Our study objectively demonstrates the reduced physical activity of claudicating patients and documents physical activity/duration profiles throughout the day. The intensity of the physical activity of the average claudicating patient fluctuates very little during the day and rarely exceeds a light intensity level. Claudicating patients spend approximately half of their awake time in sedentary behavior and when they walk they do it in short bursts followed by several minutes of rest. We anticipate that changes in routine physical activity/duration profiles of patients with PAD will provide relevant, sensitive, and direct measures of the effectiveness of therapeutic interventions.

[Temporal trend and spatial distribution of mortality from neglected tropical diseases in Argentina 1991-2016Tendência temporal e distribuição espacial da mortalidade por doenças tropicais negligenciadas na Argentina entre 1991 e 2016]. / Tendencia temporal y distribución espacial de la mortalidad por enfermedades tropicales desatendidas en Argentina entre 1991 y 2016.

OBJECTIVE: Determine the mortality from neglected tropical diseases (NTD) in Argentina from 1991 to 2016, their overall temporal trend and the trend for the most frequent causes by age and sex. METHODS: Argentina's crude age-specific and age-adjusted mortality from NTDs were calculated for the period 1991-2016. The temporal trend was analyzed using joinpoint regression models. RESULTS: Mortality from NTDs is a phenomenon observed primarily in people over 50 and men. The trend in the age-adjusted NTD death rates shows a statistically significant decline between 1991 and 2016, with an average annual percentage change (AAPC) for both sexes of -3.98 (CI 95%: -4.69; -3.25). In terms of the selected diseases, a steady decline in the rates for echinococcus is observed in the period 1991-2016, while two periods can be identified for Chagas, one in which the decline is significant (1991-2008) and another in which it is not (2008-2016). With regard to leprosy, a period with a sharp and significant increase is observed (1991-1998), followed by another period (1998-2016) of significant moderate decline. With the exception of echinococcus, the selected diseases are found basically in northwestern and northeastern Argentina. CONCLUSIONS: The downward trend in mortality from NTDs is significant for both sexes. It is clear that despite the decline in recent years, mortality from NTDs is an important public health problem.

OBJETIVO: Descrever a mortalidade por doenças tropicais negligenciadas na Argentina entre 1991 e 2016 assim como a tendência temporal geral e as causas mais comuns de mortalidade desagregadas por idade e sexo. MÉTODOS: Foi realizado o cálculo das taxas de mortalidade brutas por doenças tropicais negligenciadas, específicas por faixa etária e padronizadas por idade, na Argentina para o período de 1991 a 2016. A tendência temporal foi analisada com o uso de modelos de regressão joinpoint. RESULTADOS: A mortalidade por doenças tropicais negligenciadas ocorre sobretudo em indivíduos do sexo masculino acima dos 50 anos. A análise da tendência das taxas de mortalidade por doenças tropicais negligenciadas padronizadas por idade demonstra uma redução estatisticamente significativa entre 1991 e 2016, com variação percentual média anual (AAPC) em ambos os sexos de ­3,98 (IC 95% ­4,69; ­3,25). Com relação a doenças específicas, houve uma redução contínua das taxas de mortalidade por equinococose entre 1991 e 2016; para a doença de Chagas, podem ser identificados dois períodos, um de redução significativa (1991­2008) e outro sem redução (2008­2016) e, para hanseníase, houve um período de aumento súbito significativo (1991­1998) seguido por uma redução moderada significativa entre 1998 e 2016. Estas doenças, à exceção da equinococose, estão principalmente distribuídas nas regiões noroeste e nordeste do país. CONCLUSÕES: Verifica-se uma tendência de declínio significativo da mortalidade por doenças tropicais negligenciadas em ambos os sexos. Deve-se salientar que, apesar da redução ocorrida nos últimos anos, a mortalidade por doenças tropicais negligenciadas continua sendo um importante problema de saúde pública na Argentina.

[Time-trend analysis of diabetes mellitus mortality in Argentina, 1990-2013]. / Análisis de la tendencia temporal de la mortalidad por diabetes mellitus en Argentina, 1990-2013.

OBJECTIVES: To describe the time trend of mortality attributable to diabetes mellitus (DM) in Argentina in the years 1990-2013, by age and sex. METHODS: Crude, age-specific, and age-adjusted rates of DM mortality in Argentina were calculated for the period 1990-2013. Mortality data were obtained from the Statistical Report on Deaths issued by the Department of Statistics and Health Information. An analysis of this trend was carried out through joinpoint regression models. RESULTS: Analysis of the trend of crude and age-adjusted DM mortality rates yielded a statistically significant model in which mortality increased between 1990 and 2001 and declined thereafter. Furthermore, for age-adjusted rates, there was a significant downward trend of mortality in women (AAPC -1.10, 95%CI -1.70 to -0.50). Age-specific mortality rates multiplied with every 10-year increment in age. All age groups older than 50 years showed a growing mortality trend between 1990 and 2001. CONCLUSIONS: DM mortality mainly affects people over the age of 50 and men. A significant downward trend in age-adjusted DM mortality rates was observed for women. These findings highlight the importance of developing policies for prevention and early detection, as well as of proper coding of multiple causes of death.

Oxidative damage in the gastrocnemius predicts long-term survival in patients with peripheral artery disease.

Patients with peripheral artery disease (PAD) have increased mortality rates and a myopathy in their affected legs which is characterized by increased oxidative damage, reduced antioxidant enzymatic activity and defective mitochondrial bioenergetics. This study evaluated the hypothesis that increased levels of oxidative damage in gastrocnemius biopsies from patients with PAD predict long-term mortality rates. Oxidative damage was quantified as carbonyl adducts in myofibers of the gastrocnemius of PAD patients. The oxidative stress data were grouped into tertiles and the 5-year, all-cause mortality for each tertile was determined by Kaplan-Meier curves and compared by the Modified Peto test. A Cox-regression model was used to control the effects of clinical characteristics. Results were adjusted for age, sex, race, body mass index, ankle-brachial index, smoking, physical activity, and comorbidities. Of the 240 study participants, 99 died during a mean follow up of 37.8 months. Patients in the highest tertile of oxidative damage demonstrated the highest 5-year mortality rate. The mortality hazard ratios (HR) from the Cox analysis were statistically significant for oxidative damage (lowest vs middle tertile; HR = 6.33; p = 0.0001 and lowest vs highest; HR = 8.37; p < 0.0001). Survival analysis of a contemporaneous population of PAD patients identifies abundance of carbonyl adducts in myofibers of their gastrocnemius as a predictor of mortality rate independently of ankle-brachial index, disease stage and other clinical and myopathy-related covariates.

Structural inequality and temporal brain dynamics across diverse samples.

BACKGROUND: Structural income inequality - the uneven income distribution across regions or countries - could affect brain structure and function, beyond individual differences. However, the impact of structural income inequality on the brain dynamics and the roles of demographics and cognition in these associations remains unexplored. METHODS: Here, we assessed the impact of structural income inequality, as measured by the Gini coefficient on multiple EEG metrics, while considering the subject-level effects of demographic (age, sex, education) and cognitive factors. Resting-state EEG signals were collected from a diverse sample (countries = 10; healthy individuals = 1394 from Argentina, Brazil, Colombia, Chile, Cuba, Greece, Ireland, Italy, Turkey and United Kingdom). Complexity (fractal dimension, permutation entropy, Wiener entropy, spectral structure variability), power spectral and aperiodic components (1/f slope, knee, offset), as well as graph-theoretic measures were analysed. FINDINGS: Despite variability in samples, data collection methods, and EEG acquisition parameters, structural inequality systematically predicted electrophysiological brain dynamics, proving to be a more crucial determinant of brain dynamics than individual-level factors. Complexity and aperiodic activity metrics captured better the effects of structural inequality on brain function. Following inequality, age and cognition emerged as the most influential predictors. The overall results provided convergent multimodal metrics of biologic embedding of structural income inequality characterised by less complex signals, increased random asynchronous neural activity, and reduced alpha and beta power, particularly over temporoposterior regions. CONCLUSION: These findings might challenge conventional neuroscience approaches that tend to overemphasise the influence of individual-level factors, while neglecting structural factors. Results pave the way for neuroscience-informed public policies aimed at tackling structural inequalities in diverse populations.

Brain clocks capture diversity and disparities in aging and dementia across geographically diverse populations.

Brain clocks, which quantify discrepancies between brain age and chronological age, hold promise for understanding brain health and disease. However, the impact of diversity (including geographical, socioeconomic, sociodemographic, sex and neurodegeneration) on the brain-age gap is unknown. We analyzed datasets from 5,306 participants across 15 countries (7 Latin American and Caribbean countries (LAC) and 8 non-LAC countries). Based on higher-order interactions, we developed a brain-age gap deep learning architecture for functional magnetic resonance imaging (2,953) and electroencephalography (2,353). The datasets comprised healthy controls and individuals with mild cognitive impairment, Alzheimer disease and behavioral variant frontotemporal dementia. LAC models evidenced older brain ages (functional magnetic resonance imaging: mean directional error = 5.60, root mean square error (r.m.s.e.) = 11.91; electroencephalography: mean directional error = 5.34, r.m.s.e. = 9.82) associated with frontoposterior networks compared with non-LAC models. Structural socioeconomic inequality, pollution and health disparities were influential predictors of increased brain-age gaps, especially in LAC (R² = 0.37, F² = 0.59, r.m.s.e. = 6.9). An ascending brain-age gap from healthy controls to mild cognitive impairment to Alzheimer disease was found. In LAC, we observed larger brain-age gaps in females in control and Alzheimer disease groups compared with the respective males. The results were not explained by variations in signal quality, demographics or acquisition methods. These findings provide a quantitative framework capturing the diversity of accelerated brain aging.

Brain clocks capture diversity and disparity in aging and dementia.

Brain clocks, which quantify discrepancies between brain age and chronological age, hold promise for understanding brain health and disease. However, the impact of multimodal diversity (geographical, socioeconomic, sociodemographic, sex, neurodegeneration) on the brain age gap (BAG) is unknown. Here, we analyzed datasets from 5,306 participants across 15 countries (7 Latin American countries -LAC, 8 non-LAC). Based on higher-order interactions in brain signals, we developed a BAG deep learning architecture for functional magnetic resonance imaging (fMRI=2,953) and electroencephalography (EEG=2,353). The datasets comprised healthy controls, and individuals with mild cognitive impairment, Alzheimer's disease, and behavioral variant frontotemporal dementia. LAC models evidenced older brain ages (fMRI: MDE=5.60, RMSE=11.91; EEG: MDE=5.34, RMSE=9.82) compared to non-LAC, associated with frontoposterior networks. Structural socioeconomic inequality and other disparity-related factors (pollution, health disparities) were influential predictors of increased brain age gaps, especially in LAC (R2=0.37, F2=0.59, RMSE=6.9). A gradient of increasing BAG from controls to mild cognitive impairment to Alzheimer's disease was found. In LAC, we observed larger BAGs in females in control and Alzheimer's disease groups compared to respective males. Results were not explained by variations in signal quality, demographics, or acquisition methods. Findings provide a quantitative framework capturing the multimodal diversity of accelerated brain aging.

Aberrant AHRR, ADAMTS2 and FAM184 DNA Methylation: Candidate Biomarkers in the Oral Rinse of Heavy Smokers.

OBJECTIVE: To identify DNA methylation patterns of heavy smokers in oral rinse samples. METHODS: Genome-wide DNA methylation data was imported from Gene Expression Omnibus GSE70977 using the GEOquery package. Two independent sets were analyzed: (a) 71 epigenomes of cancer-free subjects (heavy smokers n = 37 vs. non-smokers n = 31); for concordance assessment (b) 139 oral-cancer patients' epigenomes (heavy smokers n = 92 vs. non-smokers n = 47). Differential DNA methylation for CpG positions and at the regional level was determined using Limma and DMRcate Bioconductor packages. The linear model included sex, age, and alcohol consumption. The statistical threshold was set to p < 0.05. Functional gene prioritization analysis was performed for gene-targeted analysis. RESULTS: In individuals without cancer and heavy smokers, the FAM184B gene was found with two CpG positions differentially hypermethylated (p = 0.012 after FDR adjustment), in a region of 48 bp with an absolute methylation difference >10% between groups (p = 1.76 × 10-8). In the analysis corresponding to oral-cancer patients, we found AHRR differentially hypomethylated cancer patients, but also in subjects without oral cancer in the targeted analyses. Remarkably, ADAMTS2 was found differentially hypermethylated in heavy smokers without a diagnosis of cancer in two consecutive probes cg05575921 (p = 3.13 × 10-7) and cg10208897 (p = 1.36 × 10-5). CONCLUSIONS: Differentially methylated AHRR, ADAMTS2, and FAM184B genes are biomarker candidates in oral rinse samples.

Factors associated with healthy aging in Latin American populations.

Latin American populations may present patterns of sociodemographic, ethnic and cultural diversity that can defy current universal models of healthy aging. The potential combination of risk factors that influence aging across populations in Latin American and Caribbean (LAC) countries is unknown. Compared to other regions where classical factors such as age and sex drive healthy aging, higher disparity-related factors and between-country variability could influence healthy aging in LAC countries. We investigated the combined impact of social determinants of health (SDH), lifestyle factors, cardiometabolic factors, mental health symptoms and demographics (age, sex) on healthy aging (cognition and functional ability) across LAC countries with different levels of socioeconomic development using cross-sectional and longitudinal machine learning models (n = 44,394 participants). Risk factors associated with social and health disparities, including SDH (ß > 0.3), mental health (ß > 0.6) and cardiometabolic risks (ß > 0.22), significantly influenced healthy aging more than age and sex (with null or smaller effects: ß < 0.2). These heterogeneous patterns were more pronounced in low-income to middle-income LAC countries compared to high-income LAC countries (cross-sectional comparisons), and in an upper-income to middle-income LAC country, Costa Rica, compared to China, a non-upper-income to middle-income LAC country (longitudinal comparisons). These inequity-associated and region-specific patterns inform national risk assessments of healthy aging in LAC countries and regionally tailored public health interventions.

Heterogeneous factors influence social cognition across diverse settings in brain health and age-related diseases.

Aging may diminish social cognition, which is crucial for interaction with others, and significant changes in this capacity can indicate pathological processes like dementia. However, the extent to which non-specific factors explain variability in social cognition performance, especially among older adults and in global settings, remains unknown. A computational approach assessed combined heterogeneous contributors to social cognition in a diverse sample of 1063 older adults from 9 countries. Support vector regressions predicted the performance in emotion recognition, mentalizing, and a total social cognition score from a combination of disparate factors, including clinical diagnosis (healthy controls, subjective cognitive complaints, mild cognitive impairment, Alzheimer's disease, behavioral variant frontotemporal dementia), demographics (sex, age, education, and country income as a proxy of socioeconomic status), cognition (cognitive and executive functions), structural brain reserve, and in-scanner motion artifacts. Cognitive and executive functions and educational level consistently emerged among the top predictors of social cognition across models. Such non-specific factors showed more substantial influence than diagnosis (dementia or cognitive decline) and brain reserve. Notably, age did not make a significant contribution when considering all predictors. While fMRI brain networks did not show predictive value, head movements significantly contributed to emotion recognition. Models explained between 28-44% of the variance in social cognition performance. Results challenge traditional interpretations of age-related decline, patient-control differences, and brain signatures of social cognition, emphasizing the role of heterogeneous factors. Findings advance our understanding of social cognition in brain health and disease, with implications for predictive models, assessments, and interventions.

Near Real-Time Telemetry of Nation-Wide ICU's Capacity Strain in Argentina.

Due to the fast-spreading of COVID-19 during the pandemic, decision-makers turned into innovative digital solutions for data collection in order to make well-informed public health decisions based on reliable data from verified sources. This work describes one of such solutions, implemented in partnership with the Ministry of Health in Argentina.

[Congenital cytomegalovirus infection screening in high risk newborn]. / Cribado de infección por citomegalovirus congénito en recién nacidos de alto riesgo.

BACKGROUND: Congenital cytomegalovirus infection (cCMV) is the most frequent cause of congenital infection, 90% of affected newborn (NB) are asymptomatic at birth and 6-15% will develop long term sequalae. It is the main etiology of non-genetic sensorineural hearing loss. AIM: To determine prevalence of CMV in high risk NB. METHODS: Cohort prospective study, including inpatient NB with one or more of following criteria: birth weight < 1,500 g, < 32 weeks gestational age (GA), severe small for gestational age (SGA), suspected congenital infection or "refer" in newborn hearing test, also NB to HIV-infected mothers. Urine CMV polymerase chain reaction was performed within 21 day of life. RESULTS: 193 NB were enrolled. Global cCMV prevalence 2.6% (n: 5) and by risk group: one third (n: 1) in NB with suspected congenital infection, 8.3% in NB with "refer" result in hearing test, 4.9% in NB to HIV-infected mothers, 3.3% in severe SGA and 1.7% in < 1,500 g, none with significant association. Only one symptomatic cCMV was detected who died in neonatal period and the remaining (asymptomatic) cCMV patients have normal hearing follow-up. DISCUSSION: Reported prevalence was comparable to international reports. We recommend cCMV screening, at least in risk groups, being ideal the universal screening. This would allow timely treatment and active follow-up.

Softepigen: Primers Design Web-Based Tool for MS-HRM Technique.

Polymerase Chain Reaction (PCR) based techniques for DNA methylation techniques includes the MS-HRM technique. Methylation Sensitive High-Resolution Melting (MS-HRM) primer-design requires a set of necessary recommendations for such DNA methylation assessment. However, there were not any available software that allows an automatic design of this kind primers. We present Softepigen, the first complete MS-HRM primer design software. Softepigen allows to search for primers in a genomic region following Wojdacz's recommendations and targets primer binding regions with high linguistic complexity sequences that increase the specificity of the converted sequence of the human genome. We performed in-silico PCR analysis through BiSearch ePCR tool to validate the specificity of the of the primers designed using Softepigen. Softepigen for MS-HRM performance in our genomic regions of interest show satisfactory specificity measurements, and we implemented it for freely available use in the web-based interface at www.soft-epigen.com.

Surveillance Intensity Comparison by Risk for T1NX Locally Excised Rectal Adenocarcinoma: a Cost-Effective Analysis.

BACKGROUND: Controversy exists regarding the optimal surveillance strategy following local excision of T1NX rectal adenocarcinoma. This study aims to determine the cost-effectiveness of surveillance strategies for locally excised T1NX rectal adenocarcinoma based on histopathologic and local staging risk factors. METHODS: A Markov model with 10-year follow-up was developed for cost-effectiveness analysis of high-, medium-, and low-intensity surveillance strategies after local excision of T1NX rectal adenocarcinoma. Literature review and expert consensus were utilized to populate state/transition probabilities and rewards. Based on this data, 87% of T1NX patients undergoing local excision were low risk. Healthcare utilization costs were based on Centers for Medicare and Medicaid Services data. The primary outcomes were costs in 2018 US dollars and effectiveness in life-years presented as net monetary benefit and incremental cost-effectiveness ratios. One-way sensitivity and probabilistic sensitivity analyses were performed. RESULTS: Net monetary benefit for low-, medium-, and high-intensity surveillance strategies ($393,117.00, $397,978.80, and $397,290.00) shows medium-intensity surveillance to be optimal. One-way sensitivity analysis shows medium-intensity surveillance to be optimal when the cohort is 73-94% low risk. High-intensity surveillance is preferred when less than 73% of the cohort is low risk. Low-intensity surveillance is preferred when greater than 94% is low risk. Probabilistic sensitivity analysis of the base-case shows medium-intensity surveillance is the optimal strategy for 51.5% of the iterations performed. CONCLUSIONS: Medium-intensity surveillance is the most cost-effective surveillance strategy for locally excised T1NX rectal adenocarcinoma in a clinically representative population model.