RESUMEN
Facilitated learning approaches are increasingly being used as a means to enhance climate and sustainability collaborations working across disciplines, regions, and scales. With investments into promoting and supporting inter- and transdisciplinary learning in major programs on complex global challenges like climate change on the rise, scholars and practitioners are calling for a more grounded and empirical understanding of learning processes and their outcomes. Yet, methodologies for studying the interplay between learning and change in these initiatives remain scarce, owing to both the "hard to measure" nature of learning and the complexity of large-scale program implementation and evaluation. This paper proposes a new method for studying social learning in the context of large research programs. It aims to analyze the social learning of researchers and practitioners engaged in these programs and assess the contributions of this learning to the resilience of the natural and social systems that these programs seek to influence. We detail the theoretical basis for this new approach and set out six steps for developing multi-layered contribution pathways and contribution stories with stakeholders to document both the process and outcomes of social learning. The proposed method, we argue, can strengthen our analytical capacity to uncover the structural drivers and barriers to social learning that are often masked by the complexity of large-scale programs. An illustrative example, drawn from a large-scale climate adaptation research program, provides evidence on how this method might advance our methodological strategies for studying learning in these programs. We conclude by highlighting two key methodological contributions brought about through this approach, and by reflecting on opportunities for further methodological development. Enriching our understanding of learning and change processes, we argue, is an important avenue for understanding how we can pursue transformations for sustainability.
RESUMEN
P-glycoprotein (P-gp) is a drug efflux pump in many organs, including the intestine and liver. Two single nucleotide polymorphisms (SNPs) of P-gp gene, 2677G>T and 3435C>T, were reported to influence function and expression of P-gp and have the controversial effects on drug disposition. Phenytoin is one substrate of P-gp. Persistent low phenytoin levels in plasma and P-gp overexpression in brain in several refractory epilepsy patients were reported. P-gp polymorphisms may also affect phenytoin efficacy by altering its bioavailability (F). Because two P-gp SNPs, 2677G>T and 3435C>T, may affect P-gp expression in tissue, we examined phenytoin disposition in patients of different P-gp haplotypes, G/G2677C/C3435 and T/T2677T/T3435. We found that the mean absolute F of phenytoin in T/T2677T/T3435 subjects (91%) is slightly higher than in G/G2677C/C3435 subjects (82%). There was no difference in the maximum concentration (Cmax ) and the area under the serum concentration-time curve of phenytoin administered orally between two genotypic groups. However, the time of maximum concentration was higher in T/T2677T/T3435 subjects (10 h) than in G/G2677C/C3435 subjects (6 h). The study ruled out the possibility that genetic polymorphisms of P-gp may affect phenytoin efficacy through the decreased absorption or the increased elimination. P-gp SNPs could affect phenytoin efficacy in refractory epilepsy patients probably because of central nervous system.
