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Biology subjects

Cintron, D. L.

Publications and source records attributed to Cintron, D. L..

3 recordsLinked to original sources

Active learnings impact on student course performance in STEM varies by type and intensity

We updated a recent meta-analysis of active learnings impact on student achievement in undergraduate STEM courses by following the same protocol to evaluate studies published from 2010-2017. We screened 1659 papers, coded 1294, and found 210 that met five pre-established inclusion criteria and six pre-established criteria for methodological quality. After further dropping 76 studies with no exam scores data, 134 of these studies contained data on student performance on identical or equivalent exams. We found that on average, active learnings effect size on exam scores was 0.519 {+/-} 0.049, meaning that when students are in active learning classes, they perform roughly half a standard deviation higher on an identical exam. Funnel plots and sensitivity analyses indicated that these results were not due to sampling bias. Active learning had a positive impact on student outcomes regardless of class size, course level, or STEM discipline, though there was heterogeneity in the effects. All of these results are very similar when compared to earlier meta-analyses, however increased resolution in the studies analyzed here revealed two novel results. First, student performance was significantly better in courses that employed high-intensity active learning, defined as students being on task at least two-thirds of class time, versus lower-intensities. Additionally, there was significant heterogeneity in efficacy across different types of active learning employed. These results suggest that most, if not all types of active learning are effective, and that when innovating in their classes, instructors should continually work to increase active learning intensity. We urge caution in interpreting the results on active learning types, however, and propose a preliminary framework for making more-sophisticated and reliable analyses of variation in course design. Finally, the evidence presented here for active learnings impact on student outcomes creates a strong foundation for faculty professional development and administration.

scientific communication and education↗

Massively parallel reporter assays and mouse transgenic assays provide complementary information about neuronal enhancer activity

Genetic studies find hundreds of thousands of noncoding variants associated with psychiatric disorders. Massively parallel reporter assays (MPRAs) and in vivo transgenic mouse assays can be used to assay the impact of these variants. However, the relevance of MPRAs to in vivo function is unknown and transgenic assays suffer from low throughput. Here, we studied the utility of combining the two assays to study the impact of non-coding variants. We carried out an MPRA on over 50,000 sequences derived from enhancers validated in transgenic mouse assays and from multiple fetal neuronal ATAC-seq datasets. We also tested over 20,000 variants, including synthetic mutations in highly active neuronal enhancers and 177 common variants associated with psychiatric disorders. Variants with a high impact on MPRA activity were further tested in mice. We found a strong and specific correlation between MPRA and mouse neuronal enhancer activity including changes in neuronal enhancer activity in mouse embryos for variants with strong MPRA effects. Mouse assays also revealed pleiotropic variant effects that could not be observed in MPRA. Our work provides a large catalog of functional neuronal enhancers and variant effects and highlights the effectiveness of combining MPRAs and mouse transgenic assays.

genomics↗

Integrative single-cell characterization of hypothalamus sex-differential and obesity-associated genes and regulatory elements

Over 500 noncoding genomic loci are associated with obesity. The majority of these loci reside near genes that are expressed in the hypothalamus in specific neuronal subpopulations that regulate food intake, hindering the ability to identify and functionally characterize them. Here, we carried out integrative single-cell analysis (RNA/ATAC-seq) on both mouse and human male and female hypothalamus to characterize genes and regulatory elements in specific cell subpopulations. Utilizing both transcriptome and regulome data, we identify over 30 different neuronal and non-neuronal cell subpopulations and a shared core of transcription factors that regulate cell cluster-specific genes between mice and humans. We characterize several sex-specific differentially expressed genes and the regulatory elements that control them in specific cell subpopulations. Overlapping cell-specific scATAC peaks with obesity-associated GWAS variants, identifies potential obesity-associated regulatory elements. Using reporter assays and CRISPR editing, we show that many of these sequences, including the top obesity-associated loci (FTO and MC4R), are functional enhancers whose activity is altered due to the obesity-associated variant and regulate known obesity genes. Combined, our work provides a catalog of genes and regulatory elements in hypothalamus cell subpopulations and uses obesity to showcase how integrative single-cell sequencing can identify functional variants associated with hypothalamus-related phenotypes.

neuroscience↗