Epistemología, ontología y relaciones de poder en el problema de la realidad social y las estructuras del mundo de la vida

En este artículo se expone una reflexión sobre algunos de los principales nudos conceptuales de las obras El problema de la realidad social y Las estructuras del mundo de la vida. En primer lugar, se presenta una breve reseña sobre estos nudos conceptuales. En segundo lugar, se realiza una reflexión crítica de carácter epistemológico sobre las implicaciones que estos conllevan desde el punto de vista ontológico y politológico

Comparison of phenotypic tests for detecting penicillin G resistance with presence of blaZ gene in Staphylococcus aureus isolated from bovine intramammary infections

Few studies have described the relationship between genotypic and phenotypic methods for detecting penicillin resistance in Staphylococcus aureus isolated from bovine intramammary infection (IMI). Six phenotypic methods for penicillinase detection were compared with a genotypic method testing the presence of the β-lactamase gene blaZ in Staph. aureus (n = 150) isolated from bovine IMI. Highest sensitivities and specificities were observed for disk diffusion (DD) (93 and 97·4%), minimum inhibitory concentration (MIC) (90·3 and 97·4%), Cefinase™ (85·9 and 97·4%) and Diatabs™ (85·7 and 98·7%). The estimated cut-off points estimated in the present study can be considered close to the ones indicated by CLSI (2013). The molecular detection of blaZ gene is the only method that may indicate the real or potential capacity of producing β-lactamase in Staph. aureus. Considering that from a clinical standpoint a false negative result from a phenotypic test is the most unfavourable situation, a combination of standard DD with Diatabs™ or Cefinase™ should be performed by routine mastitis laboratories to minimise false negative results.EEA RafaelaFil: Russi, Norma B.. Universidad Nacional del Litoral. Facultad de Ciencias Veterinarias; ArgentinaFil: Maito, Julia. Lactodiagnóstico Sur; ArgentinaFil: Dieser, Silvana Andrea. Universidad Nacional de Río Cuarto. Facultad de Ciencias Exactas, Fisicoquímicas y Naturales; ArgentinaFil: Renna, Maria Sol. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Ciencias Veterinarias del Litoral. Universidad Nacional del Litoral. Facultad de Ciencias Veterinarias. Instituto de Ciencias Veterinarias del Litoral; ArgentinaFil: Signorini, Marcelo. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Rafaela; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Camussone, Cecilia. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Rafaela; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Neder, Veronica Elizabeth. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Rafaela; ArgentinaFil: Pol, Martín. Lactodiagnóstico Sur; ArgentinaFil: Tirante, Liliana. Lactodiagnóstico Sur; ArgentinaFil: Odierno, Liliana Mónica. Universidad Nacional de Río Cuarto. Facultad de Ciencias Exactas, Fisicoquímicas y Naturales. Departamento de Microbiología e Inmunología; ArgentinaFil: Calvinho, Luis Fernando. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Rafaela; Argentina. Universidad Nacional del Litoral. Facultad de Ciencias Veterinarias; Argentin

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 (β > 0.3), mental health (β > 0.6) and cardiometabolic risks (β > 0.22), significantly influenced healthy aging more than age and sex (with null or smaller effects: β < 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.Fil: Santamaria Garcia, Hernando. Pontificia Universidad Javeriana; ColombiaFil: Sainz Ballesteros, Agustín. Universidad Adolfo Ibañez; ChileFil: Hernandez, Hernán. Universidad Adolfo Ibañez; Chile. Universidad de Concepción; ChileFil: Moguilner, Sebastian Gabriel. Universidad Adolfo Ibañez; Chile. University of California; Estados UnidosFil: Maito, Marcelo. Universidad Adolfo Ibañez; ChileFil: OchoaRosales, Carolina. Universidad Adolfo Ibañez; ChileFil: Corley, Michael. No especifíca;Fil: Valcour, Victor. University of California; Estados UnidosFil: Miranda, J. Jaime. No especifíca;Fil: Lawlor, Brian. University of California; Estados UnidosFil: Ibañez, Agustin Mariano. Universidad de San Andrés; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Adolfo Ibañez; Chil

The BrainLat project : a multimodal neuroimaging dataset of neurodegeneration from underrepresented backgrounds

The Latin American Brain Health Institute (BrainLat) has released a unique multimodal neuroimaging dataset of 780 participants from Latin American. The dataset includes 530 patients with neurodegenerative diseases such as Alzheimer's disease (AD), behavioral variant frontotemporal dementia (bvFTD), multiple sclerosis (MS), Parkinson's disease (PD), and 250 healthy controls (HCs). This dataset (62.7 ± 9.5 years, age range 21–89 years) was collected through a multicentric effort across five Latin American countries to address the need for affordable, scalable, and available biomarkers in regions with larger inequities. The BrainLat is the first regional collection of clinical and cognitive assessments, anatomical magnetic resonance imaging (MRI), resting-state functional MRI (fMRI), diffusion-weighted MRI (DWI), and high density resting-state electroencephalography (EEG) in dementia patients. In addition, it includes demographic information about harmonized recruitment and assessment protocols. The dataset is publicly available to encourage further research and development of tools and health applications for neurodegeneration based on multimodal neuroimaging, promoting the assessment of regional variability and inclusion of underrepresented participants in research

Classification of Alzheimer's disease and frontotemporal dementia using routine clinical and cognitive measures across multicentric underrepresented samples: a cross sectional observational studyResearch in context

Summary: Background: Global brain health initiatives call for improving methods for the diagnosis of Alzheimer's disease (AD) and frontotemporal dementia (FTD) in underrepresented populations. However, diagnostic procedures in upper-middle-income countries (UMICs) and lower-middle income countries (LMICs), such as Latin American countries (LAC), face multiple challenges. These include the heterogeneity in diagnostic methods, lack of clinical harmonisation, and limited access to biomarkers. Methods: This cross-sectional observational study aimed to identify the best combination of predictors to discriminate between AD and FTD using demographic, clinical and cognitive data among 1794 participants [904 diagnosed with AD, 282 diagnosed with FTD, and 606 healthy controls (HCs)] collected in 11 clinical centres across five LAC (ReDLat cohort). Findings: A fully automated computational approach included classical statistical methods, support vector machine procedures, and machine learning techniques (random forest and sequential feature selection procedures). Results demonstrated an accurate classification of patients with AD and FTD and HCs. A machine learning model produced the best values to differentiate AD from FTD patients with an accuracy = 0.91. The top features included social cognition, neuropsychiatric symptoms, executive functioning performance, and cognitive screening; with secondary contributions from age, educational attainment, and sex. Interpretation: Results demonstrate that data-driven techniques applied in archival clinical datasets could enhance diagnostic procedures in regions with limited resources. These results also suggest specific fine-grained cognitive and behavioural measures may aid in the diagnosis of AD and FTD in LAC. Moreover, our results highlight an opportunity for harmonisation of clinical tools for dementia diagnosis in the region. Funding: This work was supported by the Multi-Partner Consortium to Expand Dementia Research in Latin America (ReDLat), funded by NIA/NIH (R01AG057234), Alzheimer's Association (SG-20-725707-ReDLat), Rainwater Foundation, Takeda (CW2680521), Global Brain Health Institute; as well as CONICET; FONCYT-PICT (2017-1818, 2017-1820); PIIECC, Facultad de Humanidades, Usach; Sistema General de Regalías de Colombia (BPIN2018000100059), Universidad del Valle (CI 5316); ANID/FONDECYT Regular (1210195, 1210176, 1210176); ANID/FONDAP (15150012); ANID/PIA/ANILLOS ACT210096; and Alzheimer's Association GBHI ALZ UK-22-865742

The Multi-Partner Consortium to Expand Dementia Research in Latin America (ReDLat): Driving Multicentric Research and Implementation Science.

Dementia is becoming increasingly prevalent in Latin America, contrasting with stable or declining rates in North America and Europe. This scenario places unprecedented clinical, social, and economic burden upon patients, families, and health systems. The challenges prove particularly pressing for conditions with highly specific diagnostic and management demands, such as frontotemporal dementia. Here we introduce a research and networking initiative designed to tackle these ensuing hurdles, the Multi-partner consortium to expand dementia research in Latin America (ReDLat). First, we present ReDLat's regional research framework, aimed at identifying the unique genetic, social, and economic factors driving the presentation of frontotemporal dementia and Alzheimer's disease in Latin America relative to the US. We describe ongoing ReDLat studies in various fields and ongoing research extensions. Then, we introduce actions coordinated by ReDLat and the Latin America and Caribbean Consortium on Dementia (LAC-CD) to develop culturally appropriate diagnostic tools, regional visibility and capacity building, diplomatic coordination in local priority areas, and a knowledge-to-action framework toward a regional action plan. Together, these research and networking initiatives will help to establish strong cross-national bonds, support the implementation of regional dementia plans, enhance health systems' infrastructure, and increase translational research collaborations across the continent

The Multi-Partner Consortium to Expand Dementia Research in Latin America (ReDLat): Driving Multicentric Research and Implementation Science

Dementia is becoming increasingly prevalent in Latin America, contrasting with stable or declining rates in North America and Europe. This scenario places unprecedented clinical, social, and economic burden upon patients, families, and health systems. The challenges prove particularly pressing for conditions with highly specific diagnostic and management demands, such as frontotemporal dementia. Here we introduce a research and networking initiative designed to tackle these ensuing hurdles, the Multi-partner consortium to expand dementia research in Latin America (ReDLat). First, we present ReDLat's regional research framework, aimed at identifying the unique genetic, social, and economic factors driving the presentation of frontotemporal dementia and Alzheimer's disease in Latin America relative to the US. We describe ongoing ReDLat studies in various fields and ongoing research extensions. Then, we introduce actions coordinated by ReDLat and the Latin America and Caribbean Consortium on Dementia (LAC-CD) to develop culturally appropriate diagnostic tools, regional visibility and capacity building, diplomatic coordination in local priority areas, and a knowledge-to-action framework toward a regional action plan. Together, these research and networking initiatives will help to establish strong cross-national bonds, support the implementation of regional dementia plans, enhance health systems' infrastructure, and increase translational research collaborations across the continent