Instructional Improvement Through Individual Consultation

Theoretical Bases: Theory 1: Instructional Interaction Theory 2: Student Differences Theory 3: Change The Approach An Example: Step 1: Identify the Instructor\u27s Major Concerns Step 2: Challenge Instructor\u27s Concepts of Teaching Step 3: Formulate Alternative Teaching Approaches Step 4: Evaluate New Approach Conclusions Reference

Instructional Improvement Through Individual Consultation

Theoretical Bases: Theory 1: Instructional Interaction Theory 2: Student Differences Theory 3: Change The Approach An Example: Step 1: Identify the Instructor\u27s Major Concerns Step 2: Challenge Instructor\u27s Concepts of Teaching Step 3: Formulate Alternative Teaching Approaches Step 4: Evaluate New Approach Conclusions Reference

Replication in Cells of Hematopoietic Origin Is Necessary for Dengue Virus Dissemination

Dengue virus (DENV) is a mosquito-borne pathogen for which no vaccine or specific therapeutic is available. Although it is well established that dendritic cells and macrophages are primary sites of DENV replication, it remains unclear whether non-hematopoietic cellular compartments serve as virus reservoirs. Here, we exploited hematopoietic-specific microRNA-142 (miR-142) to control virus tropism by inserting tandem target sites into the virus to restrict replication exclusively in this cell population. In vivo use of this virus restricted infection of CD11b+, CD11c+, and CD45+ cells, resulting in a loss of virus spread, regardless of the route of administration. Furthermore, sequencing of the targeted virus population that persisted at low levels, demonstrated total excision of the inserted miR-142 target sites. The complete conversion of the virus population under these selective conditions suggests that these immune cells are the predominant sources of virus amplification. Taken together, this work highlights the importance of hematopoietic cells for DENV replication and showcases an invaluable tool for the study of virus pathogenesis

Health effects of ambient air pollution – recent research development and contemporary methodological challenges

Exposure to high levels of air pollution can cause a variety of adverse health outcomes. Air quality in developed countries has been generally improved over the last three decades. However, many recent epidemiological studies have consistently shown positive associations between low-level exposure to air pollution and health outcomes. Thus, adverse health effects of air pollution, even at relatively low levels, remain a public concern. This paper aims to provide an overview of recent research development and contemporary methodological challenges in this field and to identify future research directions for air pollution epidemiological studies

[Comment] Redefine statistical significance

The lack of reproducibility of scientific studies has caused growing concern over the credibility of claims of new discoveries based on “statistically significant” findings. There has been much progress toward documenting and addressing several causes of this lack of reproducibility (e.g., multiple testing, P-hacking, publication bias, and under-powered studies). However, we believe that a leading cause of non-reproducibility has not yet been adequately addressed: Statistical standards of evidence for claiming discoveries in many fields of science are simply too low. Associating “statistically significant” findings with P < 0.05 results in a high rate of false positives even in the absence of other experimental, procedural and reporting problems. For fields where the threshold for defining statistical significance is P<0.05, we propose a change to P<0.005. This simple step would immediately improve the reproducibility of scientific research in many fields. Results that would currently be called “significant” but do not meet the new threshold should instead be called “suggestive.” While statisticians have known the relative weakness of using P≈0.05 as a threshold for discovery and the proposal to lower it to 0.005 is not new (1, 2), a critical mass of researchers now endorse this change. We restrict our recommendation to claims of discovery of new effects. We do not address the appropriate threshold for confirmatory or contradictory replications of existing claims. We also do not advocate changes to discovery thresholds in fields that have already adopted more stringent standards (e.g., genomics and high-energy physics research; see Potential Objections below). We also restrict our recommendation to studies that conduct null hypothesis significance tests. We have diverse views about how best to improve reproducibility, and many of us believe that other ways of summarizing the data, such as Bayes factors or other posterior summaries based on clearly articulated model assumptions, are preferable to P-values. However, changing the P-value threshold is simple and might quickly achieve broad acceptance

Counseling theories and counselor education

xii, 166 p.; 20 cm

Counseling theories and counselor education

v,166 hal;ilu