Six Easy Pieces: Teaching Experientially

Steven Hartwell explores the growth and value of teaching experientially in this article. Experiential teaching emerged when clinical legal education grew in response to student demands for a more relevant education. The educational advantages of the field clinic model are substantial: students are more motivated to lean, the learning is direct and based on real experience, it entails both cognitive and affective domains, and raises ethical issues by working with real clients. The author examines David Kolb\u27s theory of experiential learning; the basic premise of that theory is that effective learning takes place experientially in a continuous, circular four-stage sequence. The four-stage sequence consists of experience, reflection, theory, and application. The author suggests that simulation, a hybrid form of clinical teaching that historically grew out of the field clinic model, provides a complete experiential sequence

Two CdZnTe Detector-Equipped Gamma-ray Spectrometers for Attribute Measurements on Irradiated Nuclear Fuel

Some United States Department of Energy-owned spent fuel elements from foreign research reactors (FRRs) are presently being shipped from the reactor location to the US for storage at the Idaho National Engineering and Environmental Laboratory (INEEL). Two cadmium zinc telluride detector-based gamma-ray spectrometers have been developed to confirm the irradiation status of these fuels. One spectrometer is configured to operate underwater in the spent fuel pool of the shipping location, while the other is configured to interrogate elements on receipt in the dry transfer cell at the INEEL’s Interim Fuel Storage Facility (IFSF). Both units have been operationally tested at the INEEL

Damage segregation at fissioning may increase growth rates: A superprocess model

A fissioning organism may purge unrepairable damage by bequeathing it preferentially to one of its daughters. Using the mathematical formalism of superprocesses, we propose a flexible class of analytically tractable models that allow quite general effects of damage on death rates and splitting rates and similarly general damage segregation mechanisms. We show that, in a suitable regime, the effects of randomness in damage segregation at fissioning are indistinguishable from those of randomness in the mechanism of damage accumulation during the organism's lifetime. Moreover, the optimal population growth is achieved for a particular finite, non-zero level of combined randomness from these two sources. In particular, when damage accumulates deterministically, optimal population growth is achieved by a moderately unequal division of damage between the daughters. Too little or too much division is sub-optimal. Connections are drawn both to recent experimental results on inheritance of damage in protozoans, to theories of the evolution of aging, and to models of resource division between siblings.Comment: Version 2 had significant conceptual and organizational changes, though only minor changes to the mathematics. Version 3 has minor proofreading corrections, and a few new references. The paper will appear in Theoretical Population Biolog

Feasibility and acceptability of integrated psychological therapy versus treatment as usual for people with bipolar disorder and co-morbid alcohol use:A single blind randomised controlled trial

Background Alcohol use is a common problem in bipolar disorder (BD) and evidence indicates more promising outcomes for alcohol use than other substances. No trials have evaluated individual integrated motivational interviewing and cognitive behaviour therapy (MI-CBT) for problematic alcohol use in BD. We therefore assessed the feasibility and acceptability of a novel MI-CBT intervention for alcohol use in BD. Methods A single blind RCT was conducted to compare MI-CBT plus treatment as usual (TAU) with TAU only. MI-CBT was delivered over 20 sessions with participants followed up at 3, 6, 9 and 12 months post-randomisation. Primary outcomes were the feasibility and acceptability of MI-CBT (recruitment to target, retention to follow-up and therapy, acceptability of therapy and absence of adverse events). We also conducted preliminary analyses of alcohol and mood outcomes (frequency and severity of alcohol use and time to mood relapse). Results 44 participants were recruited with 75% retention to 6 and 12 months follow-up. Therapy participants attended a mean of 17.6 (SD 4.5) sessions. Therapy alliance and treatment fidelity were acceptable. Qualitative interviews indicated the intervention was experienced as collaborative, and helpful, in addressing mood and alcohol issues, although risk of overconfidence following therapy was also identified. Clinical outcomes did not differ between arms at 12 months follow-up. Limitations As a feasibility and acceptability trial any secondary results should be treated with caution. Conclusions Integrated MI-CBT is feasible and acceptable, but lack of clinical impact, albeit in a feasibility study, suggests need for further development. Potential adaptations are discussed

Validating module network learning algorithms using simulated data

In recent years, several authors have used probabilistic graphical models to learn expression modules and their regulatory programs from gene expression data. Here, we demonstrate the use of the synthetic data generator SynTReN for the purpose of testing and comparing module network learning algorithms. We introduce a software package for learning module networks, called LeMoNe, which incorporates a novel strategy for learning regulatory programs. Novelties include the use of a bottom-up Bayesian hierarchical clustering to construct the regulatory programs, and the use of a conditional entropy measure to assign regulators to the regulation program nodes. Using SynTReN data, we test the performance of LeMoNe in a completely controlled situation and assess the effect of the methodological changes we made with respect to an existing software package, namely Genomica. Additionally, we assess the effect of various parameters, such as the size of the data set and the amount of noise, on the inference performance. Overall, application of Genomica and LeMoNe to simulated data sets gave comparable results. However, LeMoNe offers some advantages, one of them being that the learning process is considerably faster for larger data sets. Additionally, we show that the location of the regulators in the LeMoNe regulation programs and their conditional entropy may be used to prioritize regulators for functional validation, and that the combination of the bottom-up clustering strategy with the conditional entropy-based assignment of regulators improves the handling of missing or hidden regulators.Comment: 13 pages, 6 figures + 2 pages, 2 figures supplementary informatio

An Early Biomarker Algorithm Predicts Lethal Graft-Vs-Host Disease and Survival after Allogeneic Hematopoietic Cell Transplantation

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Biomarkers Predict Graft-Vs-Host Disease Outcomes Better Than Clinical Response after One Week of Treatment

Abstract Graft-versus-host disease (GVHD), the primary cause of non-relapse mortality (NRM) following allogeneic hematopoietic stem cell transplantation, does not always respond to treatment with high dose systemic corticosteroids. We have recently shown that a combination of three biomarkers (TNFR1, ST2, and REG3α) measured at onset of GVHD can predict day 28 response to treatment and 6-month NRM (Levine, Lancet Haem, 2015). Our goal in the current study was to determine if the same biomarker-based Ann Arbor GVHD algorithm can alsopredict treatment response andmortality whenapplied after one week of systemic corticosteroid treatment. The study population consisted of 378 patients (pts) with acute GVHD from 11 centers in the Mount Sinai Acute GVHD International Consortium. All pts were treated with systemic steroids and provided a plasma or serum sample obtained after one week of treatment (±3 days). The median starting dose of systemic steroids for Grade II-IV GVHD was 2.0 mg/kg/day and for Grade I was 1.0 mg/kg/day, after which treatment varied. Patients were divided into test (n=236) and validation (n=142) cohorts. We applied the Ann Arbor GVHD algorithm to concentrations of TNFR1, ST2, and REG3α measured after one week of treatment to generate a predicted probability of 6-month NRM, which we term the treatment score (TS). We employed unsupervised k-medoidclustering to partition TS values from the test cohort into two groups (high and low). This unbiased approach identified a high score group made up of 25% of pts (n=58) in the test cohort. We observed that the day 28 response rate (complete, CR + partial, PR) was significantly lower in pts with high scores compared to low scores in the test cohort (24% vs 65%, p<0.0001) (Fig 1A). Analysis of the validation cohort using the same TS definitions showed similar differences in response rates (22% vs 61%, p<0.0001) (Fig 1B). Further, nearly four times as many pts with high scores in both cohorts died within 6 months from non-relapse causes compared to pts with low scores (test: 57% vs 17%, p<0.0001; validation: 57% vs 14%, p<0.0001) (Fig 1C/D). As expected, the majority of non-relapse deaths in pts treated for GVHD were directly attributable to GVHD (test: 95%; validation: 89%). Relapse rates for high and low score pts were similar (data not shown), and thus pts with a high TS experienced significantly worse overall survival in both cohorts (test: 37% vs 72%, p<0.0001; validation: 38% vs 79%, p<0.0001) (Fig 1E/F). Approximately half of the pts in each cohort (test: 48%; validation: 44%) responded (CR+PR) to the first week of steroids and these ptshad significantly lower 6-month NRM than non-responders (NR) (test: 17% vs 36%, p=0.0002; validation: 13% vs 36%, p=0.0014). Yet the TS continued to stratify mortality risk independently of clinical response. In the test cohort, pts with a high score comprised 16% of all early responders and experienced more than twice the NRM of early responders with a low score (33% vs 13%, p=0.022) (Fig 2A). Conversely, test cohort pts who did not respond by day 7, but had a low score, fared much better than non-responders with a high score (NRM 21% vs 68%, p<0.0001) (Fig 2B). Two thirds of early non-responders comprised this more favorable group. These highly significant results reproduced in the independent validation cohort in similar proportions (CR+PR: 45% vs 6%, p=0.0003; NR: 61% vs 22%, p=0.0001) (Fig 2C/D). Finally, a subset analysis revealed that pts classified as NR after one week of steroids due to isolated, yet persistent, grade I skin GVHD (24/378, 6%) overwhelmingly had low treatment scores (22/24, 92%) and experienced rates of NRM (9%) comparable to responders with low scores, thus forming a distinct, albeit small, subset of pts with non-responsive GVHD that fares particularly well (Fig 3). In conclusion, a treatment score based on three GVHD biomarkers measured after one week of steroids stratifies pts into two groups with distinct risks for treatment failure and 6-month NRM. It is particularly noteworthy that the TS identifies two subsets of pts with steroid refractory (SR) GVHD who have highly different outcomes (Fig 2B/D). The much larger group, approximately two thirds of all SR pts, may not need the same degree of treatment escalation as is traditional for clinical non-response, and thus overtreatment might be avoided. Because the TSis measured at a common decision making time point, it may prove useful to guide risk-adapted therapy. Disclosures Mielke: Novartis: Consultancy; MSD: Consultancy, Other: Travel grants; Celgene: Other: Travel grants, Speakers Bureau; Gilead: Other: Travel grants; JAZZ Pharma: Speakers Bureau. Kroeger:Novartis: Honoraria, Research Funding. Chen:Incyte Corporation: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Research Funding. Jagasia:Therakos: Consultancy. Kitko:Therakos: Honoraria, Speakers Bureau. Ferrara:Viracor: Patents & Royalties: GVHD biomarker patent. Levine:Viracor: Patents & Royalties: GVHD biomarker patent