Calls for early exposure of all undergraduates to research have led to the increased use and study of course-based research experiences (CREs). CREs have been shown to increase measures of ...persistence in the sciences, such as science identity, scientific self-efficacy, project ownership, scientific community values, and networking. However, implementing CREs can be challenging and resource-intensive. These barriers may be partly mitigated by the use of short-term CRE modules rather than semester- or year-long projects. One study has shown that a CRE module captures some of the known benefits of CREs as measured by the Persistence in the Sciences (PITS) survey. Here, we used this same survey to assess outcomes for introductory biology students who completed a semester of modular CREs based on faculty research at an R1 university. The results indicated levels of self-efficacy, science community values, and science identity similar to those previously reported for students in the Science Education Alliance-Phage Hunters Advancing Genomics and Evolutionary Science (SEA-PHAGES) full-semester CRE. Scores for project ownership (content) were between previously reported traditional lab and CRE scores, while project ownership (emotion) and networking were similar to those of traditional labs. Our results suggest that modular CREs can lead to significant gains in student affect measures that have been linked to persistence in the sciences in other studies. Although gains were not as great in all measures as with a semester-long CRE, implementation of modular CREs may be more feasible and offers the added benefits of exposing students to diverse research fields and lab techniques.
We address an optimization problem that requires deciding the location of a set of facilities, the allocation of customers to those facilities under capacity constraints, and the allocation of ...customers to trucks at those facilities under truck travel-distance constraints. We present a hybrid approach that combines integer and constraint programming using logic-based Benders decomposition. Computational experiments demonstrate that the Benders model is able to find and prove optimal solutions up to three orders-of-magnitude faster than an existing integer programming approach; it also finds better feasible solutions in less time when compared with an existing tabu search algorithm.
Abstract Huntington disease is an autosomal-dominant neurodegenerative disorder characterized by behavioral abnormalities, cognitive decline, and involuntary movements that lead to a progressive ...decline in functional capacity, independence, and ultimately death. The pathophysiology of Huntington disease is linked to an expanded trinucleotide repeat of cytosine-adenine-guanine (CAG) in the IT-15 gene on chromosome 4. There is no disease-modifying treatment for Huntington disease, and novel pathophysiological insights and therapeutic strategies are needed. Lipids are vital to the health of the central nervous system, and research in animals and humans has revealed that cholesterol metabolism is disrupted in Huntington disease. This lipid dysregulation has been linked to specific actions of the mutant huntingtin on sterol regulatory element binding proteins that result in lower cholesterol levels in affected areas of the brain with evidence that this depletion is pathologic. Huntington disease is also associated with a pattern of insulin resistance characterized by a catabolic state, resulting in weight loss and a lower body mass index than individuals without Huntington disease. Insulin resistance appears to act as a metabolic stressor attending disease progression. The fish-derived omega-3 fatty acids, eicosapentaenoic acid and docosahexaenoic acid, have been examined in clinical trials of Huntington disease patients. Drugs that combat the dysregulated lipid milieu in Huntington disease may help treat this perplexing and catastrophic genetic disease.
Histomorphometric analysis of histologic sections of normal and diseased bone samples,such as healing allografts and fractures,is widely used in bone research.However,the utility of traditional ...semi-automated methods is limited because they are labor-intensive and can have high interobserver variability depending upon the parameters being assessed,and primary data cannot be re-analyzed automatically.Automated histomorphometry has long been recognized as a solution for these issues,and recently has become more feasible with the development of digital whole slide imaging and computerized image analysis systems that can interact with digital slides.Here,we describe the development and validation of an automated application（algorithm）using Visiopharm＇s image analysis system to quantify newly formed bone,cartilage,and fibrous tissue in healing murine femoral allografts in high-quality digital images of H＆E/alcian blue-stained decalcified histologic sections.To validate this algorithm,we compared the results obtained independently using OsteoMeasureTM and Visiopharm image analysis systems.The intraclass correlation coefficient between Visiopharm and OsteoMeasure was very close to one for all tissue elements tested,indicating nearly perfect reproducibility across methods.This new algorithm represents an accurate and labor-efficient method to quantify bone,cartilage,and fibrous tissue in healing mouse allografts.
There are many systems and techniques that address stochastic planning and scheduling problems, based on distinct and sometimes opposite approaches, especially in terms of how generation and ...execution of the plan, or the schedule, are combined, and if and when knowledge about the uncertainties is taken into account. In many real-life problems, it appears that many of these approaches are needed and should be combined, which to our knowledge has never been done. In this paper, we propose a typology that distinguishes between proactive, progressive, and revision approaches. Then, focusing on scheduling and schedule execution, a theoretic model integrating those three approaches is defined. This model serves as a general template to implement a system that will fit specific application needs: we introduce and discuss our experimental prototypes which validate our model in part, and suggest how this framework could be extended to more general planning systems.
Faculty development workshops are frequently used to bring about change in faculty teaching. Yet, the characteristics of successful faculty professional development in the context of laboratory ...teaching are unclear. In this Perspective, we describe our approach to intensive hands-on faculty development workshops for fostering change in laboratory teaching and present evidence for the effectiveness of the approach. The outcomes from our workshops and feedback from past participants support the following recommendations: 1) faculty should attend workshops in teams from their institutions, 2) workshops should allow participants to develop curricula that can be implemented with relatively little additional work after the workshop, 3) workshops should allow faculty time to “work” on tangible products and should involve hands-on activities, 4) workshops should be of sufficient duration to allow for faculty to develop expertise and tangible products but short enough that faculty do not “burn out,” and 5) a structure for ongoing and systematic follow-up with participants is essential.
Patients with diabetes mellitus, prior myocardial infarction, older age, and a relatively preserved left ventricular ejection fraction remain at risk for sudden cardiac death that is potentially ...amenable by the subcutaneous implantable cardioverter defibrillator with a good risk-benefit profile. The launched MADIT S-ICD study is designed to test the hypothesis that post–myocardial infarction diabetes patients with relatively preserved ejection fraction of 36%-50% will have a survival benefit from a subcutaneous implantable cardioverter defibrillator.
Objective
To identify design elements of clinical trials leading to US Food and Drug Administration approval of drugs for neurological diseases with and without orphan indications.
Methods
We used ...publicly available information to identify approvals for drugs for neurological diseases with an orphan indication (n = 19) and compared them with recent approvals for drugs for neurological diseases without an orphan indication (n = 20). We identified “pivotal trials” from drug labels and drug approval packages, and assessed them on four elements of clinical trial design: control, blinding, randomization, and size.
Results
All drugs for neurological diseases (100%) approved without an orphan indication included at least two randomized, double‐blind, placebo‐controlled trials. In comparison, 32% of drugs with an orphan indication had at least two such trials (p < 0.001) and 74% had at least one (p = 0.02). Thirty‐three pivotal trials were conducted for the 19 drugs approved with an orphan indication. Of the 33 trials, 11 (33%) did not use a placebo control, 9 (27%) were not double blind, and 4 (12%) were not randomized. Drugs approved without an orphan indication had more pivotal trials per drug (3.8 vs 1.7 trials; p < 0.001) and a larger mean trial size (506 vs 164 trial participants; p < 0.001).
Interpretation
The US Food and Drug Administration has approved orphan drugs for neurological diseases without randomized, doubled‐blind, placebo‐controlled pivotal trials. As orphan drug development grows, demand will likely increase for alternative designs for conducting adequate and well‐controlled studies to demonstrate drug efficacy. Ann Neurol 2009;66:184–190
Since the end of the 1990s, there has been an increasing interest in the application of artificial intelligence (AI) planning techniques to solve real-life problems. In addition to characteristics of ...academic problems, such as the need to reason about actions, real-life problems require detailed knowledge elicitation, engineering, and management. A systematic design process in which Knowledge and Requirements Engineering tools play a fundamental role is necessary in such applications. One of the main challenges in such design process, and consequently in the study of Knowledge Engineering in AI planning, has been the analysis of requirements and their subsequent transformation into an input-ready model for planners. itSIMPLE is a research project dedicated to the study of a project process to support the design phases of real-life planning models. In this paper, we give an overview of itSIMPLE focusing on the main translation processes among a minimal set of representations: from requirements represented in Unified Modeling Language (UML) to Petri Nets and from UML models to planning domain definition language for problem solving.
PDF
