Abductive reasoning in modeling biological phenomena as complex systems

Introduction: Abductive reasoning is a type of reasoning that is applied to generate causal explanations. Modeling for inquiry is an important practice in science and science education that involves constructing models as causal explanations for scientific phenomena. Thus, abductive reasoning is applied in modeling for inquiry. Biological phenomena are often best explained as complex systems, which means that their explanations ideally include causes and mechanisms on different organizational levels. In this study, we investigate the role of abductive reasoning in modeling for inquiry and its potential for explaining biological phenomena as complex systems. Methods: Eighteen pre-service science teachers were randomly assigned to model one of two biological phenomena: either a person's reddened face, for which participants knew of explanations from their everyday lives, or a clownfish changing its sex, for which participants did not know about explanations. Using the think-aloud method, we examined the presence of abductive reasoning in participants' modeling processes. We also analyzed modeling processes in terms of participants' ability to model the phenomena as complex systems. Results: All participants reasoned abductively when solving the modeling task. However, modeling processes differed depending on the phenomenon. For the reddened face, participants generated simple models that they were confident with. In contrast, for the clownfish, participants generated more complex models that they were insecure about. Extensive engagement in abductive reasoning alone did not lead to the generation of models that explained the phenomena as complex systems. Discussion: Based on the findings, we conclude that engagement in abductive reasoning will not suffice to explain phenomena as complex systems. We suggest examining in future studies how abductive reasoning is combined with systems thinking skills to explain phenomena as complex systems in biological model construction

Abductive reasoning in modeling biological phenomena as complex systems

IntroductionAbductive reasoning is a type of reasoning that is applied to generate causal explanations. Modeling for inquiry is an important practice in science and science education that involves constructing models as causal explanations for scientific phenomena. Thus, abductive reasoning is applied in modeling for inquiry. Biological phenomena are often best explained as complex systems, which means that their explanations ideally include causes and mechanisms on different organizational levels. In this study, we investigate the role of abductive reasoning in modeling for inquiry and its potential for explaining biological phenomena as complex systems.MethodsEighteen pre-service science teachers were randomly assigned to model one of two biological phenomena: either a person's reddened face, for which participants knew of explanations from their everyday lives, or a clownfish changing its sex, for which participants did not know about explanations. Using the think-aloud method, we examined the presence of abductive reasoning in participants' modeling processes. We also analyzed modeling processes in terms of participants' ability to model the phenomena as complex systems.ResultsAll participants reasoned abductively when solving the modeling task. However, modeling processes differed depending on the phenomenon. For the reddened face, participants generated simple models that they were confident with. In contrast, for the clownfish, participants generated more complex models that they were insecure about. Extensive engagement in abductive reasoning alone did not lead to the generation of models that explained the phenomena as complex systems.DiscussionBased on the findings, we conclude that engagement in abductive reasoning will not suffice to explain phenomena as complex systems. We suggest examining in future studies how abductive reasoning is combined with systems thinking skills to explain phenomena as complex systems in biological model construction

Adaptation of the Oxygen Sensing System during Lung Development

During gestation, the most drastic change in oxygen supply occurs with the onset of ventilation after birth. As the too early exposure of premature infants to high arterial oxygen pressure leads to characteristic diseases, we studied the adaptation of the oxygen sensing system and its targets, the hypoxia-inducible factor- (HIF-) regulated genes (HRGs) in the developing lung. We draw a detailed picture of the oxygen sensing system by integrating information from qPCR, immunoblotting, in situ hybridization, and single-cell RNA sequencing data in ex vivo and in vivo models. HIF1α protein was completely destabilized with the onset of pulmonary ventilation, but did not coincide with expression changes in bona fide HRGs. We observed a modified composition of the HIF-PHD system from intrauterine to neonatal phases: Phd3 was significantly decreased, while Hif2a showed a strong increase and the Hif3a isoform Ipas exclusively peaked at P0. Colocalization studies point to the Hif1a-Phd1 axis as the main regulator of the HIF-PHD system in mouse lung development, complemented by the Hif3a-Phd3 axis during gestation. Hif3a isoform expression showed a stepwise adaptation during the periods of saccular and alveolar differentiation. With a strong hypoxic stimulus, lung ex vivo organ cultures displayed a functioning HIF system at every developmental stage. Approaches with systemic hypoxia or roxadustat treatment revealed only a limited in vivo response of HRGs. Understanding the interplay of the oxygen sensing system components during the transition from saccular to alveolar phases of lung development might help to counteract prematurity-associated diseases like bronchopulmonary dysplasia