An Engineering Learning Community To Promote Retention And Graduation Of At-Risk Engineering Students

Retention and graduation rates for engineering disciplines are significantly lower than desired, and research literature offers many possible causes. Engineering learning communities provide the opportunity to study relationships among specific causes and to develop and evaluate activities designed to lessen their impact. This paper details an engineering learning community created to combat three common threats to academic success of engineering students: financial difficulties, math deficiencies, and the lack of a supportive engineering culture. The project tracks participants in the learning community from first year through graduation to assess the effectiveness of its activities in improving retention and graduation rates. Scholarships were made available to address the financial difficulties; tutors, mentors, study groups, and a “freshman-to-sophomore bridge” summer program were provided to address math deficiencies; cohort engineering courses, active learning techniques, required group meetings, required group study sessions, dedicated study space, and dedicated faculty advisors were used to promote a sense of community. Quantitative retention and graduation rates for the cohort are compared to other engineering groups at the same institution. Qualitative results collected via student surveys and interviews, and lessons learned by project administrators are also presented. Retention and graduation rates of the cohort are better than those of comparable groups at the same institution. Graduation rates based upon freshman math placement are also higher than comparable groups.

MT-HESS: an efficient Bayesian approach for simultaneous association detection in OMICS datasets, with application to eQTL mapping in multiple tissues.

MOTIVATION: Analysing the joint association between a large set of responses and predictors is a fundamental statistical task in integrative genomics, exemplified by numerous expression Quantitative Trait Loci (eQTL) studies. Of particular interest are the so-called ': hotspots ': , important genetic variants that regulate the expression of many genes. Recently, attention has focussed on whether eQTLs are common to several tissues, cell-types or, more generally, conditions or whether they are specific to a particular condition. RESULTS: We have implemented MT-HESS, a Bayesian hierarchical model that analyses the association between a large set of predictors, e.g. SNPs, and many responses, e.g. gene expression, in multiple tissues, cells or conditions. Our Bayesian sparse regression algorithm goes beyond ': one-at-a-time ': association tests between SNPs and responses and uses a fully multivariate model search across all linear combinations of SNPs, coupled with a model of the correlation between condition/tissue-specific responses. In addition, we use a hierarchical structure to leverage shared information across different genes, thus improving the detection of hotspots. We show the increase of power resulting from our new approach in an extensive simulation study. Our analysis of two case studies highlights new hotspots that would remain undetected by standard approaches and shows how greater prediction power can be achieved when several tissues are jointly considered. AVAILABILITY AND IMPLEMENTATION: C[Formula: see text] source code and documentation including compilation instructions are available under GNU licence at http://www.mrc-bsu.cam.ac.uk/software/

Insight into Genotype-Phenotype Associations through eQTL Mapping in Multiple Cell Types in Health and Immune-Mediated Disease

Genome-wide association studies (GWAS) have transformed our understanding of the genetics of complex traits such as autoimmune diseases, but how risk variants contribute to pathogenesis remains largely unknown. Identifying genetic variants that affect gene expression (expression quantitative trait loci, or eQTLs) is crucial to addressing this. eQTLs vary between tissues and following in vitro cellular activation, but have not been examined in the context of human inflammatory diseases. We performed eQTL mapping in five primary immune cell types from patients with active inflammatory bowel disease (n = 91), anti-neutrophil cytoplasmic antibody-associated vasculitis (n = 46) and healthy controls (n = 43), revealing eQTLs present only in the context of active inflammatory disease. Moreover, we show that following treatment a proportion of these eQTLs disappear. Through joint analysis of expression data from multiple cell types, we reveal that previous estimates of eQTL immune cell-type specificity are likely to have been exaggerated. Finally, by analysing gene expression data from multiple cell types, we find eQTLs not previously identified by database mining at 34 inflammatory bowel disease-associated loci. In summary, this parallel eQTL analysis in multiple leucocyte subsets from patients with active disease provides new insights into the genetic basis of immune-mediated diseases.This research was funded by a Wellcome Trust Clinical PhD Programme Fellowship (JEP), the NIH-Oxford-Cambridge Scholars Program (ACR), Wellcome Trust Grant 083650/Z/07/Z and MRC Grant MR/L19027/1 (KGCS), and the National Institute for Health Research Cambridge Biomedical Research Centre. KGCS is a National Institute for Health Research Senior Investigator. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Oligonucleotide ligation assay detects HIV drug resistance associated with virologic failure among antiretroviral-naive adults in Kenya

Background: Transmitted drug resistance (TDR) is increasing in some areas of Africa. Detection of TDR may predict virologic failure of first-line non-nucleoside reverse-transcriptase inhibitor (NNRTI)-based antiretroviral therapy (ART). We evaluated the utility of a relatively inexpensive oligonucleotide ligation assay (OLA) to detect clinically relevant TDR at time of ART initiation. Methods: Pre-ART plasmas from ART-naive Kenyans initiating an NNRTI-based fixed-dose combination ART in a randomized adherence trial conducted in 2006 were retrospectively analyzed by OLA for mutations conferring resistance to NNRTI (K103N, Y181C, and G190A) and lamivudine (M184V). Post-ART plasmas were analyzed for virologic failure (≥1,000 copies/mL) at 6 month intervals over 18-month follow-up. Pre-ART plasmas of those with virologic failure were evaluated for drug resistance by consensus and 454-pyrosequencing. Results: Among 386 participants, TDR was detected by OLA in 3.89% [95% Confidence Interval (CI), 2.19-6.33], and was associated with a 10-fold higher rate of virologic failure [Hazard Ratio (HR), 10.39; 95% CI, 3.23-32.41; p Conclusions: Detection of TDR by a point mutation assay may prevent use of sub-optimal ART

An approach for verifying biogenic greenhouse gas emissions inventories with atmospheric CO₂ concentration data

Verifying national greenhouse gas (GHG) emissions inventories is a critical step to ensure that reported emissions data to the United Nations Framework Convention on Climate Change (UNFCCC) are accurate and representative of a country\u27s contribution to GHG concentrations in the atmosphere. Furthermore, verifying biogenic fluxes provides a check on estimated emissions associated with managing lands for carbon sequestration and other activities, which often have large uncertainties. We report here on the challenges and results associated with a case study using atmospheric measurements of CO₂ concentrations and inverse modeling to verify nationally-reported biogenic CO₂ emissions. The biogenic CO₂ emissions inventory was compiled for the Mid-Continent region of United States based on methods and data used by the US government for reporting to the UNFCCC, along with additional sources and sinks to produce a full carbon balance. The biogenic emissions inventory produced an estimated flux of −408 ± 136 Tg CO₂ for the entire study region, which was not statistically different from the biogenic flux of −478 ± 146 Tg CO₂ that was estimated using the atmospheric CO₂concentration data. At sub-regional scales, the spatial density of atmospheric observations did not appear sufficient to verify emissions in general. However, a difference between the inventory and inversion results was found in one isolated area of West-central Wisconsin. This part of the region is dominated by forestlands, suggesting that further investigation may be warranted into the forest C stock or harvested wood product data from this portion of the study area. The results suggest that observations of atmospheric CO₂ concentration data and inverse modeling could be used to verify biogenic emissions, and provide more confidence in biogenic GHG emissions reporting to the UNFCCC

A Phase 2 Study of Bortezomib in Relapsed, Refractory Myeloma

BACKGROUND Bortezomib, a boronic acid dipeptide, is a novel proteasome inhibitor that has been shown in preclinical and phase 1 studies to have antimyeloma activity. METHODS In this multicenter, open-label, nonrandomized, phase 2 trial, we enrolled 202 patients with relapsed myeloma that was refractory to the therapy they had received most recently. Patients received 1.3 mg of bortezomib per square meter of body-surface area twice weekly for 2 weeks, followed by 1 week without treatment, for up to eight cycles (24 weeks). In patients with a suboptimal response, oral dexamethasone (20 mg daily, on the day of and the day after bortezomib administration) was added to the regimen. The response was evaluated according to the criteria ofthe European Group for Blood and Marrow Transplantation and confirmed by an independent review committee. RESULTS Of 193 patients who could be evaluated, 92 percent had been treated with three or more ofthe major classes of agents for myeloma, and in 91 percent, the myeloma was refractory to the therapy received most recently. The rate of response to bortezomib was 35 percent, and those with a response included 7 patients in whom myeloma protein became undetectable and 12 in whom myeloma protein was detectable only by immuno-fixation. The median overall survival was 16 months, with a median duration of response of 12 months. Grade 3 adverse events included thrombocytopenia (in 28 percent of patients), fatigue (in 12 percent), peripheral neuropathy (in 12 percent), and neutropenia (in 11 percent). Grade 4 events occurred in 14 percent of patients. CONCLUSIONS Bortezomib, a member of a new class of anticancer drugs, is active in patients with relapsed multiple myeloma that is refractory to conventional chemotherapy

The Indianapolis Flux Experiment (INFLUX): A test-bed for developing urban greenhouse gas emission measurements

The objective of the Indianapolis Flux Experiment (INFLUX) is to develop, evaluate and improve methods for measuring greenhouse gas (GHG) emissions from cities. INFLUX’s scientific objectives are to quantify CO2 and CH4 emission rates at 1 km2 resolution with a 10% or better accuracy and precision, to determine whole-city emissions with similar skill, and to achieve high (weekly or finer) temporal resolution at both spatial resolutions. The experiment employs atmospheric GHG measurements from both towers and aircraft, atmospheric transport observations and models, and activity-based inventory products to quantify urban GHG emissions. Multiple, independent methods for estimating urban emissions are a central facet of our experimental design. INFLUX was initiated in 2010 and measurements and analyses are ongoing. To date we have quantified urban atmospheric GHG enhancements using aircraft and towers with measurements collected over multiple years, and have estimated whole-city CO2 and CH4 emissions using aircraft and tower GHG measurements, and inventory methods. Significant differences exist across methods; these differences have not yet been resolved; research to reduce uncertainties and reconcile these differences is underway. Sectorally- and spatially-resolved flux estimates, and detection of changes of fluxes over time, are also active research topics. Major challenges include developing methods for distinguishing anthropogenic from biogenic CO2 fluxes, improving our ability to interpret atmospheric GHG measurements close to urban GHG sources and across a broader range of atmospheric stability conditions, and quantifying uncertainties in inventory data products. INFLUX data and tools are intended to serve as an open resource and test bed for future investigations. Well-documented, public archival of data and methods is under development in support of this objective

Winds at the Mars 2020 Landing Site. 2. Wind Variability and Turbulence

Wind speeds measured by the Mars 2020 Perseverance rover in Jezero crater were fitted as a Weibull distribution. InSight wind data acquired in Elysium Planitia were also used to contextualize observations. Jezero winds were found to be much calmer on average than in previous landing sites, despite the intense aeolian activity observed. However, a great influence of turbulence and wave activity was observed in the wind speed variations, thus driving the probability of reaching the highest wind speeds at Jezero, instead of sustained winds driven by local, regional, or large-scale circulation. The power spectral density of wind speed fluctuations follows a power-law, whose slope deviates depending on the time of day from that predicted considering homogeneous and isotropic turbulence. Daytime wave activity is related to convection cells and smaller eddies in the boundary layer, advected over the crater. The signature of convection cells was also found during dust storm conditions, when prevailing winds were consistent with a tidal drive. Nighttime fluctuations were also intense, suggesting strong mechanical turbulence. Convective vortices were usually involved in rapid wind fluctuations and extreme winds, with variations peaking at 9.2 times the background winds. Transient high wind events by vortex-passages, turbulence, and wave activity could be driving aeolian activity at Jezero. We report the detection of a strong dust cloud of 0.75–1.5 km in length passing over the rover. The observed aeolian activity had major implications for instrumentation, with the wind sensor suffering damage throughout the mission, probably due to flying debris advected by winds.The authors acknowledge and thank the Mars 2020 team. The authors would like to thank Editors and two anonymous reviewers for their constructive reviews, which greatly improved this manuscript. This work is supported by the Spanish Ministry of Science and Innovation, under project RTI2018-098728-B-C31. The derived data presented in this work were processed in the DPS24PA system, which is supported by project no. DV2020-ATM-A01. Part of the research was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration (80NM0018D0004). The UPV/EHU team is supported by Grant PID2019-109467GB-I00 funded by 1042 MCIN/AEI/10.13039/501100011033/ and by Grupos Gobierno Vasco IT1742-22

Consistent phenological shifts in the making of a biodiversity hotspot: the Cape flora

Background The best documented survival responses of organisms to past climate change on short (glacial-interglacial) timescales are distributional shifts. Despite ample evidence on such timescales for local adaptations of populations at specific sites, the long-term impacts of such changes on evolutionary significant units in response to past climatic change have been little documented. Here we use phylogenies to reconstruct changes in distribution and flowering ecology of the Cape flora - South Africa's biodiversity hotspot - through a period of past (Neogene and Quaternary) changes in the seasonality of rainfall over a timescale of several million years. Results Forty-three distributional and phenological shifts consistent with past climatic change occur across the flora, and a comparable number of clades underwent adaptive changes in their flowering phenology (9 clades; half of the clades investigated) as underwent distributional shifts (12 clades; two thirds of the clades investigated). Of extant Cape angiosperm species, 14-41% have been contributed by lineages that show distributional shifts consistent with past climate change, yet a similar proportion (14-55%) arose from lineages that shifted flowering phenology. Conclusions Adaptive changes in ecology at the scale we uncover in the Cape and consistent with past climatic change have not been documented for other floras. Shifts in climate tolerance appear to have been more important in this flora than is currently appreciated, and lineages that underwent such shifts went on to contribute a high proportion of the flora's extant species diversity. That shifts in phenology, on an evolutionary timescale and on such a scale, have not yet been detected for other floras is likely a result of the method used; shifts in flowering phenology cannot be detected in the fossil record