David Garcia

Jorge Mpodozis presents natural drift as an organism-centered view of biological evolution. Currently, many other research programs in biology and philosophy of biology pursue organismic perspectives in evolution. We consider some of the features appearing in the article in this light in order to highlight what is special in Mpodozis’s proposal. We contend that collaborations among research programs would be valuable and suggest that the major contribution of natural drift for organismic projects lies in its dynamic organizational features.

This paper aims to propose an inferential and dynamic approach to understanding with models in biology. Understanding plays a central role in the practice of modeling. From its links with the other two central elements of scientific research, experimentation, and explanation, we show its epistemic relevance to the case of explanation in biology. Furthermore, by including the notion of understanding, we propose a non-referentialist perspective on scientific models, which is determined by their use.

Este artículo presenta dos objetivos principales, ambos relacionados con los planteamientos de la corriente transhumanista. El primero consiste en realizar una aproximación al aspecto tecnológico del transhumanismo, en concreto a su estado actual en cuanto a los avances en el ámbito de la ingeniería cibernética. Tras una introducción al concepto de transhumanismo, se expondrán algunos proyectos actuales que buscan desde la reparación de daños hasta el mejoramiento humano. Como ejemplo de la implementación de la tecnología con el objetivo de amplificar los sentidos, se presenta el concepto de cíborg. El segundo objetivo se centrará en presentar las cuestiones de carácter bioético que los avances en ingeniería cibernética plantean y que irán surgiendo a lo largo del artículo con el fin de ver cómo estos avances realmente pueden ponerse al servicio de la naturaleza humana y de su desarrollo integral.

This paper aims to propose an inferential and dynamic approach to understanding with models in biology. Understanding plays a central role in the practice of modeling. From its links with the other two central elements of scientific research, experimentation, and explanation, we show its epistemic relevance to the case of explanation in biology. Furthermore, by including the notion of understanding, we propose a non-referentialist perspective on scientific models, which is determined by their use.

ObjectiveTo investigate the association of pre-existing migraine in patients hospitalised and who recovered from severe acute respiratory syndrome coronavirus 2 infection with the presence of post-coronavirus disease symptoms.BackgroundNo study has investigated the role of migraine as a risk factor for development of post-COVID symptoms.MethodsA case-control study including individuals hospitalised during the first wave of the pandemic was conducted. Patients with confirmed previous diagnosis of migraine were considered cases. Two age- and sex-matched individuals without a history of headache per case were also recruited as controls. Hospitalisation/clinical data were collected from hospital medical records. Patients were scheduled for a telephone interview. A list of post-COVID symptoms was systematically evaluated, but participants were invited to freely report any symptom. The Hospital Anxiety and Depression Scale and the Pittsburgh Sleep Quality Index were used to assess anxiety/depressive symptoms and sleep quality. Multivariable conditional logistic regression models were constructed.ResultsOverall, 57 patients with confirmed diagnosis of migraine and 144 non-migraine controls who had recovered from COVID-19 were assessed at 7.3 months after hospital discharge. The number of post-COVID symptoms in the migraine group was significantly greater than in the non-migraine group. Fatigue was significantly more prevalent in the migraine group. However, no between-groups difference in the prevalence of headache as a post-COVID symptom was detected.ConclusionPatients with a history of migraine who recovered from COVID-19 exhibited more long-term fatigue as post-COVID sequelae than those without migraine. Some of the pathophysiological changes associated with migraine could predispose to the occurrence of post-COVID symptoms.

Clinical practices are considered one of the cornerstones in nurses' education. This study provides a framework to determine how factors in the academic environment, influence nursing student's satisfaction with their practices. A cross-sectional analytical study was conducted in a convenience sample of 574 nursing students at a private university in Valencia, during the 2016/2017 academic year, 79% were women. Two statistical methodologies were used for data analysis: hierarchical regression models and fuzzy sets qualitative comparative analysis. The HRM indicate that the students' mean score influences all dimensions of satisfaction. Furthermore, in the fsQCA, the type of service and center, as well as the type of management, the preference in the choice of the practice center and the number of students per period per clinical educator influence satisfaction with clinical practices. These results could be used to understand how academic factors influence nursing students' satisfaction with their clinical practices and to create intervention programmes that improve it. This will help prepare students to be the future nursing workforce.