The importance of context: an exploration of factors influencing the adoption of student-centered teaching among chemistry, biology, and physics faculty

Background: Research at the secondary and postsecondary levels has clearly demonstrated the critical role that individual and contextual characteristics play in instructors’ decision to adopt educational innovations. Although recent research has shed light on factors influencing the teaching practices of science, technology, engineering, and mathematics (STEM) faculty, it is still not well understood how unique departmental environments impact faculty adoption of evidence-based instructional practices (EBIPs) within the context of a single institution. In this study, we sought to characterize the communication channels utilized by STEM faculty, as well as the contextual and individual factors that influence the teaching practices of STEM faculty at the departmental level. Accordingly, we collected survey and observational data from the chemistry, biology, and physics faculty at a single large research-intensive university in the USA. We then compared the influencing factors experienced by faculty in these different departments to their instructional practices. Results: Analyses of the survey data reveal disciplinary differences in the factors influencing adoption of EBIPs. In particular, the physics faculty (n = 15) had primarily student-centered views about teaching and experienced the most positive contextual factors toward adoption of EBIPs. At the other end of the spectrum, the chemistry faculty (n = 20) had primarily teacher-centered views and experienced contextual factors that hindered the adoption of student-centered practices. Biology faculty (n = 25) fell between these two groups. Classroom observational data reflected these differences: The physics classrooms were significantly more student-centered than the chemistry classrooms. Conclusions: This study demonstrates that disciplinary differences exist in the contextual factors teaching conceptions that STEM faculty experience and hold, even among faculty within the same institution. Moreover, it shows that these differences are associated to the level of adoption of student-centered teaching practices. This work has thus identified the critical need to carefully characterize STEM faculty’s departmental environment and conceptions about teaching before engaging in instructional reform efforts, and to adapt reform activities to account for these factors. The results of this study also caution the over generalization of findings from a study focused on one type of STEM faculty in one environment to all STEM faculty in any environment

Prediction of Human Disease Genes by Human-Mouse Conserved Coexpression Analysis

One of the most limiting aspects of biological research in the post-genomic era is the capability to integrate massive datasets on gene structure and function for producing useful biological knowledge. In this report we have applied an integrative approach to address the problem of identifying likely candidate genes within loci associated with human genetic diseases. Despite the recent progress in sequencing technologies, approaching this problem from an experimental perspective still represents a very demanding task, because the critical region may typically contain hundreds of positional candidates. We found that by concentrating only on genes sharing similar expression profiles in both human and mouse, massive microarray datasets can be used to reliably identify disease-relevant relationships among genes. Moreover, we found that integrating the coexpression criterion with systematic phenome analysis allows efficient identification of disease genes in large genomic regions. Using this approach on 850 OMIM loci characterized by unknown molecular basis, we propose high-probability candidates for 81 genetic diseases

Atomistic characterization of the active-site solvation dynamics of a model photocatalyst

The interactions between the reactive excited state of molecular photocatalysts and surrounding solvent dictate reaction mechanisms and pathways, but are not readily accessible to conventional optical spectroscopic techniques. Here we report an investigation of the structural and solvation dynamics following excitation of a model photocatalytic molecular system [Ir-2(dimen)(4)](2+), where dimen is para-diisocyanomenthane. The time-dependent structural changes in this model photocatalyst, as well as the changes in the solvation shell structure, have been measured with ultrafast diffuse X-ray scattering and simulated with Born-Oppenheimer Molecular Dynamics. Both methods provide direct access to the solute-solvent pair distribution function, enabling the solvation dynamics around the catalytically active iridium sites to be robustly characterized. Our results provide evidence for the coordination of the iridium atoms by the acetonitrile solvent and demonstrate the viability of using diffuse X-ray scattering at free-electron laser sources for studying the dynamics of photocatalysis.1

Impact Factor: outdated artefact or stepping-stone to journal certification?

A review of Garfield's journal impact factor and its specific implementation as the Thomson Reuters Impact Factor reveals several weaknesses in this commonly-used indicator of journal standing. Key limitations include the mismatch between citing and cited documents, the deceptive display of three decimals that belies the real precision, and the absence of confidence intervals. These are minor issues that are easily amended and should be corrected, but more substantive improvements are needed. There are indications that the scientific community seeks and needs better certification of journal procedures to improve the quality of published science. Comprehensive certification of editorial and review procedures could help ensure adequate procedures to detect duplicate and fraudulent submissions.Comment: 25 pages, 12 figures, 6 table

Pitfalls of vaccinations with WT1-, Proteinase3- and MUC1-derived peptides in combination with MontanideISA51 and CpG7909

T cells with specificity for antigens derived from Wilms Tumor gene (WT1), Proteinase3 (Pr3), and mucin1 (MUC1) have been demonstrated to lyse acute myeloid leukemia (AML) blasts and multiple-myeloma (MM) cells, and strategies to enhance or induce such tumor-specific T cells by vaccination are currently being explored in multiple clinical trials. To test safety and immunogenicity of a vaccine composed of WT1-, Pr3-, and MUC1-derived Class I-restricted peptides and the pan HLA-DR T helper cell epitope (PADRE) or MUC1-helper epitopes in combination with CpG7909 and MontanideISA51, four patients with AML and five with MM were repetitively vaccinated. No clinical responses were observed. Neither pre-existing nor naive WT1-/Pr3-/MUC1-specific CD8+ T cells expanded in vivo by vaccination. In contrast, a significant decline in vaccine-specific CD8+ T cells was observed. An increase in PADRE-specific CD4+ T helper cells was observed after vaccination but these appeared unable to produce IL2, and CD4+ T cells with a regulatory phenotype increased. Taken into considerations that multiple clinical trials with identical antigens but different adjuvants induced vaccine-specific T cell responses, our data caution that a vaccination with leukemia-associated antigens can be detrimental when combined with MontanideISA51 and CpG7909. Reflecting the time-consuming efforts of clinical trials and the fact that 1/3 of ongoing peptide vaccination trails use CpG and/or Montanide, our data need to be taken into consideration

Computational and mathematical approaches to societal transitions

After an introduction of the theoretical framework and concepts of transition studies, this article gives an overview of how structural change in social systems has been studied from various disciplinary perspectives. This overview first leads to the conclusion that computational and mathematical approaches and their practical form, modeling, up till now, have been almost absent in the research and theorizing of structural change or transitions in social systems. Second, this review of the social science literature suggests numerous theoretical constructs relevant for transition modeling. Relevant concepts include the conceptualization of the micro-to-macro link, the importance of explaining both stability and change, quantitative and qualitative definitions of structural change, the use of dichotomies, synchronic and diachronic reasoning in explaining structural change, definitions of basic patterns of social change, the conceptualization of resistance to change and intentional and normative aspects of social change. This article employs these theoretical concepts to describe and discuss the models presented in this special issue in order to develop an understanding of what exactly entails a computational or mathematical approach to societal transitions

Maternal Genome-Wide DNA Methylation Patterns and Congenital Heart Defects

The majority of congenital heart defects (CHDs) are thought to result from the interaction between multiple genetic, epigenetic, environmental, and lifestyle factors. Epigenetic mechanisms are attractive targets in the study of complex diseases because they may be altered by environmental factors and dietary interventions. We conducted a population based, case-control study of genome-wide maternal DNA methylation to determine if alterations in gene-specific methylation were associated with CHDs. Using the Illumina Infinium Human Methylation27 BeadChip, we assessed maternal gene-specific methylation in over 27,000 CpG sites from DNA isolated from peripheral blood lymphocytes. Our study sample included 180 mothers with non-syndromic CHD-affected pregnancies (cases) and 187 mothers with unaffected pregnancies (controls). Using a multi-factorial statistical model, we observed differential methylation between cases and controls at multiple CpG sites, although no CpG site reached the most stringent level of genome-wide statistical significance. The majority of differentially methylated CpG sites were hypermethylated in cases and located within CpG islands. Gene Set Enrichment Analysis (GSEA) revealed that the genes of interest were enriched in multiple biological processes involved in fetal development. Associations with canonical pathways previously shown to be involved in fetal organogenesis were also observed. We present preliminary evidence that alterations in maternal DNA methylation may be associated with CHDs. Our results suggest that further studies involving maternal epigenetic patterns and CHDs are warranted. Multiple candidate processes and pathways for future study have been identified

Molecular mechanistic associations of human diseases

<p>Abstract</p> <p>Background</p> <p>The study of relationships between human diseases provides new possibilities for biomedical research. Recent achievements on human genetic diseases have stimulated interest to derive methods to identify disease associations in order to gain further insight into the network of human diseases and to predict disease genes.</p> <p>Results</p> <p>Using about 10000 manually collected causal disease/gene associations, we developed a statistical approach to infer meaningful associations between human morbidities. The derived method clustered cardiometabolic and endocrine disorders, immune system-related diseases, solid tissue neoplasms and neurodegenerative pathologies into prominent disease groups. Analysis of biological functions confirmed characteristic features of corresponding disease clusters. Inference of disease associations was further employed as a starting point for prediction of disease genes. Efforts were made to underpin the validity of results by relevant literature evidence. Interestingly, many inferred disease relationships correspond to known clinical associations and comorbidities, and several predicted disease genes were subjects of therapeutic target research.</p> <p>Conclusions</p> <p>Causal molecular mechanisms present a unifying principle to derive methods for disease classification, analysis of clinical disorder associations, and prediction of disease genes. According to the definition of causal disease genes applied in this study, these results are not restricted to genetic disease/gene relationships. This may be particularly useful for the study of long-term or chronic illnesses, where pathological derangement due to environmental or as part of sequel conditions is of importance and may not be fully explained by genetic background.</p