Incorporation of social sciences and humanities in the training of health professionals and practitioners in other ways of knowing

It would appear that education in health sciences is currently focused primarily on instilling effective scientific, cognitive and technical competencies in health professionals and practitioners; it is not according the same level of importance to personal, relational, ethical and moral competencies. This review supports the quest for greater balance in biomedical and healthcare education by incorporating social sciences and humanities. It also argues that this is an urgent teaching and training task, especially in the developing world (Africa, Latin America and Asia). It is of critical importance to understand that matters of health and disease/illness are not only about the ‘disease in the body’ but also about the ‘disease in the body of the person suffering’, and that these two ways of knowing (epistemologies) or world-views have different implications in the health sciences education process. Lastly, as an ethics of care, the understandings afforded by these more inclusive approaches of the social sciences and humanities should not be a privilege confined to medical schools

Identifiability of Control-Oriented Glucose-Insulin Linear Models: Review and Analysis

One of the main challenges of glucose control in patients with type 1 diabetes is identifying a control-oriented model that reliably predicts the behavior of glycemia. Here, a review is provided emphasizing the structural identifiability and observability properties, which surprisingly reveals that few of them are globally identifiable and observable at the same time. Thus, a general proposal was developed to encompass four linear models according to suitable assumptions and transformations. After the corresponding structural properties analysis, two minimal model structures are generated, which are globally identifiable and observable. Then, the practical identifiability is analyzed for this application showing that the standard collected data in many cases do not have the necessary quality to ensure a unique solution in the identification process even when a considerable amount of data is collected. The two minimal control-oriented models were identified using a standard identification procedure using data from 30 virtual patients of the UVA/Padova simulator and 77 diabetes care data from adult patients of a diabetes center. The identification was performed in two stages: calibration and validation. In the first stage, the average length was taken as two days (dictated by the practical identifiability). For both structures, the mean absolute error was 16.8 mg/dl and 9.9 mg/dl for virtual patients and 21.6 mg/dl and 21.5 mg/dl for real patients. For the second stage, a one-day validation window was considered long enough for future artificial pancreas applications. The mean absolute error was 23.9 mg/dl and 12.3 mg/dl for virtual patients and 39.2 mg/dl and 36.6 mg/dl for virtual and real patients. These results confirm that linear models can be used as prediction models in model-based control strategies as predictive control.Fil: Hoyos, J. D.. Universidad Nacional de Colombia. Sede Medellín; ColombiaFil: Villa Tamayo, M. F.. Universidad Nacional de Colombia. Sede Medellín; ColombiaFil: Builes Montano, C. E.. Universidad de Antioquia; ColombiaFil: Ramirez Rincon, A.. Universidad Pontificia Bolivariana; ColombiaFil: Godoy, José Luis. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; ArgentinaFil: Garcia Tirado, J.. University of Virginia; Estados UnidosFil: Rivadeneira Paz, Pablo Santiago. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; Argentin

Gender specific effects of the calcium channel TRPV4 on osteoporotic fracture risk and osteoblast-osteoclast coupling

TRPV4 is a member of the transient receptor potential (TRP) superfamily and responds to an array of stimuli, including osmolarity, pH and pressure. Recent findings showing that TRPV4 deficiency leads to reduced sensing of mechanical stimuli led us to explore the role of TRPV4 in bone. TRPV4 mRNA was abundantly expressed in both osteoblasts and osteoclasts as assessed by qPCR. Femoral cortical and trabecular bone mass as assessed by microcomputed tomography was higher in male TRPV4 knockout mice compared to wild type mice. Despite thicker bone structures, cortical porosity was increased in the male TRPV4 knockout mice leading to reduced bone strength as assessed by 3-point bending. Osteoclast and osteoblast differentiation and function was studied, using bone marrow cultures from wildtype and TRPV4 knockout mice. Osteoclast numbers as well as the formation of resorption pits were significantly reduced in cultures of TRPV4 knockout mice compared to wildtype littermates. In contrast, osteoblast differentiation and matrix mineralization was significantly increased in TRPV4 knockout bone marrow cultures. None of these parameters were significantly different in bones and bone marrow cultures of female knock out mice. These data implicate a gender-specific osteoblast–osteoclast uncoupling and support the observed increase in bone mass in male TRPV4 deficient mice. To assess the possible impact of TRPV4 on osteoporotic outcome in humans, we extracted data from the genome-wide association study within the Rotterdam Study. Two single nucleotide polymorphisms (SNPs) in the TRPV4 gene showed strong associations with osteoporotic fracture risk fragility fracture risk and hip fracture risk in men, but not in women. This was not affected after adjusting for height, weight, age and bone mineral density (BMD). In conclusion, TRPV4 plays an important role in male but not female bone biology. Apparently, the increased periosteal bone apposition fails to overcome the increased cortical porosity, leading to reduced bone strength in TRPV4 deficient male mice. In line with the gender-specific findings in mice, variations in the TRPV4 gene are predicting fracture risk in men but not in women