¿Qué puede decir el sociólogo del conocimiento de 2+2=4?

Sin resume

Remember the « Strong Programme » ?

L’article propose une défense de la sociologie du savoir scientifique appelé le « Programme fort ». (Le « Programme faible » offre seulement une explication sociologique de l’erreur ou de la déviation). Le « Programme fort » considère que tous les énoncés de savoir ont besoin d’une explication de leur crédibilité. L’article propose de mettre en relation la position sociologique avec une position analogue développée par les psychologues de Cambridge à la suite de Sir F. C. Bartlett. Les comparaisons s’appuient sur les propositions de la monographie classique de Bartlett, Remembering.This paper offers a defence of the approach to the sociology of scientific knowledge called « the strong programme ». (The « weak » programme only offers sociological explanations of error or deviation ; the « strong » programme sees all knowledge claims as needing an explanation of their credibility.) The approach of the paper is to relate this sociological standpoint to an analogous position developed by Cambridge psychologists following the lead of Sir F. C. Bartlett. Comparisons are drawn with the doctrines of Bartlett’s classic monograph, Remembering

Inflammation and end-organ damage with obesity and gender

Latest epidemiological data suggests that 1.5 billion adults worldwide are obese or overweight. Excess weight and adipocyte hypertrophy have long been associated with contributing to low-grade systemic inflammation through elevated adipokine secretion. These increased endocrine signals further augment the metabolic dysfunction related to the presence of obesity. A chronic exposure to obesity mediated inflammation is also suggested to be responsible for progression of renal pathology and eventual end-stage organ failure. In human clinical statistics, these factors indicate a gender disparity, as males demonstrate much faster progression rates of obesity-linked renal disease than females. Therefore, the aim of this thesis was to investigate the role of gender in obesity mediated inflammation in the development of renal disease using a large animal model i.e. sheep. Post-natal female and male sheep were exposed to a lean or obesogenic environment by restricting physical activity from ≈3 months to ≈17 months of age. Analysis of body composition and adipose tissue physiology, morphology and deposition identified the development of moderate obesity following chronic exposure to a low physical environment, although no differences were observed with gender. With obesity, both genders demonstrated metabolic irregularities; males showed hyperinsulinaemia and females displayed hypercortisolism. Gene expression analysis identified an up-regulation of inflammatory related genes in perirenal adipose tissue (PAT) and kidney in obese males, a finding not seen in females, although obese females exhibited an up-regulation in glucocorticoid receptor abundance in PAT. Furthermore, the males demonstrated adaptations in renal structure and function with obesity, modifications not observed in females. The main conclusion of my thesis is that after the development of obesity, males appear much more sensitive to the metabolic, inflammatory and renal adaptations associated with an obese condition. Females displayed a down-regulation of inflammatory genes with obesity which I propose acts as a protective mechanism against the progression of renal disease, perhaps mediated by an immunosuppressive glucocorticoid action in adipose tissue. It is also possible that sex hormones play a role in obesity inflammatory renal disease development, postulated to occur through HPA activation and epigenetic alterations

Inflammation and end-organ damage with obesity and gender

Latest epidemiological data suggests that 1.5 billion adults worldwide are obese or overweight. Excess weight and adipocyte hypertrophy have long been associated with contributing to low-grade systemic inflammation through elevated adipokine secretion. These increased endocrine signals further augment the metabolic dysfunction related to the presence of obesity. A chronic exposure to obesity mediated inflammation is also suggested to be responsible for progression of renal pathology and eventual end-stage organ failure. In human clinical statistics, these factors indicate a gender disparity, as males demonstrate much faster progression rates of obesity-linked renal disease than females. Therefore, the aim of this thesis was to investigate the role of gender in obesity mediated inflammation in the development of renal disease using a large animal model i.e. sheep. Post-natal female and male sheep were exposed to a lean or obesogenic environment by restricting physical activity from ≈3 months to ≈17 months of age. Analysis of body composition and adipose tissue physiology, morphology and deposition identified the development of moderate obesity following chronic exposure to a low physical environment, although no differences were observed with gender. With obesity, both genders demonstrated metabolic irregularities; males showed hyperinsulinaemia and females displayed hypercortisolism. Gene expression analysis identified an up-regulation of inflammatory related genes in perirenal adipose tissue (PAT) and kidney in obese males, a finding not seen in females, although obese females exhibited an up-regulation in glucocorticoid receptor abundance in PAT. Furthermore, the males demonstrated adaptations in renal structure and function with obesity, modifications not observed in females. The main conclusion of my thesis is that after the development of obesity, males appear much more sensitive to the metabolic, inflammatory and renal adaptations associated with an obese condition. Females displayed a down-regulation of inflammatory genes with obesity which I propose acts as a protective mechanism against the progression of renal disease, perhaps mediated by an immunosuppressive glucocorticoid action in adipose tissue. It is also possible that sex hormones play a role in obesity inflammatory renal disease development, postulated to occur through HPA activation and epigenetic alterations

Towards a Personal Health Knowledge Graph Framework for Patient Monitoring

Healthcare providers face significant challenges with monitoring and managing patient data outside of clinics, particularly with insufficient resources and limited feedback on their patients' conditions. Effective management of these symptoms and exploration of larger bodies of data are vital for maintaining long-term quality of life and preventing late interventions. In this paper, we propose a framework for constructing personal health knowledge graphs from heterogeneous data sources. Our approach integrates clinical databases, relevant ontologies and standard healthcare guidelines to support alert generation, clinician interpretation and querying of patient data. Through a use case of monitoring Chronic Obstructive Pulmonary Disease (COPD) patients, we demonstrate that inference and reasoning on personal health knowledge graphs built with our framework can aid in patient monitoring and enhance the efficacy and accuracy of patient data queries.Comment: 6 pages, 3 figures, conference proceeding

Towards a Personal Health Knowledge Graph Framework for Patient Monitoring

Healthcare providers face significant challenges with managing and monitoring patient data outside of clinics, particularly with limited resources and insufficient feedback on their patients' conditions. Effective management of these symptoms and exploration of larger bodies of data are vital for maintaining long-term quality of life and preventing late interventions. In this paper, we propose a framework for constructing personal health knowledge graphs from heterogeneous data sources. Our approach integrates clinical databases, relevant ontologies, and standard healthcare guidelines to support alert generation, clinicians' interpretation and querying of patient data. Through a use case focusing on monitoring Chronic Obstructive Lung Disease (COPD) patients, we demonstrate that inference and reasoning on personal health knowledge graphs built with our framework can aid in patient monitoring and enhance the efficacy and accuracy of patient data queries