Modeling Initial Participation of Diverse Communities in Competitive Swimming

This research note introduces the Initial Participation Model, which theorizes continued participation in a activity or group before individuals make commitment is a function of: enjoyment, feeling of inclusion, and/or involvement opportunities. The specific focus of this research is investigating how deficiency in enjoyment, feeling of inclusion, and involvement opportunities may discourage continuing participation in competitive swimming by underrepresented populations such as African American, Black, Hispanic, Latino, Native American, Pacific Islander and low-socioeconomic communities. Details explain how initial participation differs from other sport stages by emphasizing participation; relating to program instead of sport; and resetting each time an individual joins a new activity or group. Two examples are offered illustrating how the model may be used for identifying points of intervention that stimulate continued initial participation. Also included are specific factors constructing the model and future testing plans for validation

Biotechnology Processes for Scalable, Selective Rare Earth Element Recovery

Biorecovery of rare earth elements (REE) from wastes and ores is achieved by bacteria using biogenic phosphates. One approach uses an enzyme that biomineralises REE phosphate crystals into the extracellular polymeric matrix (EPM). The enzyme, co-localised in the EPM, provides a continuous phosphate feed into biomineralisation. The bacteria can be immobilised in a column, allowing continuous metal removal. Metals biocrystallise at different rates. By choosing suitable conditions and column flow rates selective recovery of REE against uranium and thorium can potentially overcome a bottleneck in recovery of REE from mine tailings and ore leachates co-contaminated with these radionuclides. Another approach to REE recovery first lays down calcium phosphate as hydroxyapatite (Bio-HA) using the enzymatic process. Bio-HA then captures REE, loading REE of up to 84% of the HA-mass. REE3+ first localises at the grain boundaries of the small bio-crystallites and then substitutes for Ca2+ stoichiometrically within the HA. After REE capture the bio-HA/REE hybrid can be separated magnetically. A wider concept: using a ‘priming’ deposit of one mineral to facilitate the capture of REEs, has been shown, potentially providing a basis for selective REE recovery which would provide advantages over the > 100 steps currently used in commercial REE refining

Academic drug discovery:Challenges and opportunities

There are many different approaches to drug discovery in academia, some of which are based broadly on the industrial model of discovering novel targets and then conducting screening within academic drug discovery centres to identify hit molecules. Here we describe our approach to drug discovery, which makes more efficient use of the capabilities and resources of the different stakeholders. Specifically, we have created a large portfolio of drug projects and conducted small amounts of derisking work to ensure projects are investment ready. In this feature we will describe this model, including its limitations and advantages, since we believe the ideas and concepts will be of interest to other academic institutions and consortia.</p

Four-month moxifloxacin-based regimens for drug-sensitive tuberculosis

Supported by the Global Alliance for TB Drug Development with support from the Bill and Melinda Gates Foundation, the European and Developing Countries Clinical Trials Partnership, U.S. Agency for International Development, U.K. Department for International Development, Directorate General for International Cooperation of the Netherlands, Irish Aid, Australia Department of Foreign Affairs and Trade, and National Institutes of Health, AIDS Clinical Trials Group and by grants from the National Institute of Allergy and Infectious Diseases (NIAID) (UM1AI068634, UM1 AI068636, and UM1AI106701) and by NIAID grants to the University of KwaZulu Natal, South Africa, AIDS Clinical Trials Group (ACTG) site 31422 (1U01AI069469); to the Perinatal HIV Research Unit, Chris Hani Baragwanath Hospital, South Africa, ACTG site 12301 (1U01AI069453); and to the Durban International Clinical Trials Unit, South Africa, ACTG site 11201 (1U01AI069426); Bayer Healthcare for the donation of moxifloxacin; and Sanofi for the donation of rifampin.Background: Early-phase and preclinical studies suggest that moxifloxacin-containing regimens could allow for effective 4-month treatment of uncomplicated, smear-positive pulmonary tuberculosis. Methods: We conducted a randomized, double-blind, placebo-controlled, phase 3 trial to test the noninferiority of two moxifloxacin-containing regimens as compared with a control regimen. One group of patients received isoniazid, rifampin, pyrazinamide, and ethambutol for 8 weeks, followed by 18 weeks of isoniazid and rifampin (control group). In the second group, we replaced ethambutol with moxifloxacin for 17 weeks, followed by 9 weeks of placebo (isoniazid group), and in the third group, we replaced isoniazid with moxifloxacin for 17 weeks, followed by 9 weeks of placebo (ethambutol group). The primary end point was treatment failure or relapse within 18 months after randomization. Results: Of the 1931 patients who underwent randomization, in the per-protocol analysis, a favorable outcome was reported in fewer patients in the isoniazid group (85%) and the ethambutol group (80%) than in the control group (92%), for a difference favoring the control group of 6.1 percentage points (97.5% confidence interval [CI], 1.7 to 10.5) versus the isoniazid group and 11.4 percentage points (97.5% CI, 6.7 to 16.1) versus the ethambutol group. Results were consistent in the modified intention-to-treat analysis and all sensitivity analyses. The hazard ratios for the time to culture negativity in both solid and liquid mediums for the isoniazid and ethambutol groups, as compared with the control group, ranged from 1.17 to 1.25, indicating a shorter duration, with the lower bounds of the 95% confidence intervals exceeding 1.00 in all cases. There was no significant difference in the incidence of grade 3 or 4 adverse events, with events reported in 127 patients (19%) in the isoniazid group, 111 (17%) in the ethambutol group, and 123 (19%) in the control group. Conclusions: The two moxifloxacin-containing regimens produced a more rapid initial decline in bacterial load, as compared with the control group. However, noninferiority for these regimens was not shown, which indicates that shortening treatment to 4 months was not effective in this setting. (Funded by the Global Alliance for TB Drug Development and others; REMoxTB ClinicalTrials.gov number, NCT00864383.)Publisher PDFPeer reviewe

Developing Instruments to Measure Montessori Instructional Practices

Researchers who study any intervention must rule out potential alternative explanations for their results by establishing that the program being investigated is implemented with fidelity. Various instructional practices are attributed to the Montessori Method because the term is not legally protected, meaning any school can say it is Montessori regardless of the degree to which it adheres to practices generally understood to represent Montessori education. Researchers have used a variety of tools to measure the fidelity of Montessori environments they study, but most of these tools lack an extensive psychometric foundation or are labor intensive, requiring in-person observation. The purpose of this study was to examine the psychometric properties of instruments that were developed to measure Montessori implementation through Early Childhood (EC) and Elementary (EL) teachers’ reported instructional practices. Findings supported three hypothesized dimensions of Montessori implementation (structure, curriculum, and freedom), which worked fairly well in describing practices. While the properties of these instruments are promising and provide preliminary supporting evidence, results of this analysis suggest further refinement of the items in these instruments is necessary with larger and more diverse samples. While we do not suggest that these are finalized tools, we believe they provide a valuable starting point that is a vast improvement over the requirement of investigators to develop their own instruments as part of each Montessori study they design. The authors hope other researchers will incorporate these instruments into their studies to help build a robust body of evidence supporting their use

Biosynthesis of zinc sulfide quantum dots using waste off-gas from a metal bioremediation process

Waste H2S biogas from a mine-water remediation bioprocess is used to make zinc sulfide quantum dots which are identical to ZnS QDs made by chemical methods.</p

Development of childhood asthma prediction models using machine learning approaches

Background: Respiratory symptoms are common in early life and often transient. It is difficult to identify in which children these will persist and result in asthma. Machine learning (ML) approaches have the potential for better predictive performance and generalisability over existing childhood asthma prediction models. This study applied ML approaches to predict school-age asthma (age 10) in early life (Childhood Asthma Prediction in Early life, CAPE model) and at preschool age (Childhood Asthma Prediction at Preschool age, CAPP model). Methods: Clinical and environmental exposure data was collected from children enrolled in the Isle of Wight Birth Cohort (N = 1368, ∼15% asthma prevalence). Recursive Feature Elimination (RFE) identified an optimal subset of features predictive of school-age asthma for each model. Seven state-of-the-art ML classification algorithms were used to develop prognostic models. Training was performed by applying fivefold cross-validation, imputation, and resampling. Predictive performance was evaluated on the test set. Models were further externally validated in the Manchester Asthma and Allergy Study (MAAS) cohort. Results: RFE identified eight and twelve predictors for the CAPE and CAPP models, respectively. Support Vector Machine (SVM) algorithms provided the best performance for both the CAPE (area under the receiver operating characteristic curve, AUC = 0.71) and CAPP (AUC = 0.82) models. Both models demonstrated good generalisability in MAAS (CAPE 8-year = 0.71, 11-year = 0.71, CAPP 8-year = 0.83, 11-year = 0.79) and excellent sensitivity to predict a subgroup of persistent wheezers. Conclusion: Using ML approaches improved upon the predictive performance of existing regression-based models, with good generalisability and ability to rule in asthma and predict persistent wheeze.</p