Feasibility and Informative Value of Environmental Sample Collection in the National Children\u27s Vanguard Study

Background: Birth cohort studies provide the opportunity to advance understanding of the impact of environmental factors on childhood health and development through prospective collection of environmental samples. Methods: We evaluated the feasibility and informative value of the environmental sample collection methodology in the initial pilot phase of the National Children\u27s Study, a planned U.S. environmental birth cohort study. Environmental samples were collected from January 2009–September 2010 at up to three home visits: pre-pregnancy (n¼306), pregnancy (n¼807), and 6-months postnatal (n¼117). Collections included air for particulate matter r2.5 mm (PM2.5), nitrogen dioxide, ozone, volatile organic compounds (VOCs), and carbonyls; vacuum dust for allergens/endotoxin; water for VOCs, trihalomethanes (THMs), and haloacetic acids (HAAs); and wipe samples for pesticides, semi-volatile organics, and metals. We characterized feasibility using sample collection rates and times and informative value using analyte detection frequencies (DF). Results: Among the 1230 home visits, environmental sample collection rates were high across all sample types (mean¼89%); all samples except the air PM2.5 samples had collection times o30 min. Informative value was low for water VOCs (median DF¼0%) and pesticide floor wipes (median DF¼5%). Informative value was moderate for air samples (median DF¼35%) and high for water THMs and HAAs (median DF¼91% and 75%, respectively). Conclusions: Though collection of environmental samples was feasible, some samples (e.g., wipe pesticides and water VOCs) yielded limited information. These results can be used in conjunction with other study design considerations, such as target population size and hypotheses of interest, to inform the method selection of future environmental health birth cohort studies

Efficacy and safety profile of deep responders to carfilzomib-based therapy: a subgroup analysis from ASPIRE and ENDEAVOR

To understand the profile of best responders (complete response or better [≥CR]) to carfilzomib, we described the characteristics, progression-free survival (PFS), overall survival (OS) data, and the safety of patients who achieved ≥CR to carfilzomib-based treatment in ASPIRE and ENDEAVOR. In post hoc analyses from ASPIRE and ENDEAVOR, median PFS and OS were longer for ≥CR patients versus those who achieved a very good partial response or partial response (VGPR/PR). In the carfilzomib arm of ASPIRE, median PFS was 50.4 months for ≥CR versus 22.1 months for VGPR/PR; median OS was 67.0 versus 44.2 months, respectively. In the carfilzomib arm of ENDEAVOR, median PFS was 34.0 for ≥CR versus 20.4 months for VGPR/PR; median OS was non-estimable. Despite the longer treatment duration, fewer patients with ≥CR versus VGPR/PR experienced treatment-emergent adverse events that led to discontinuation of carfilzomib-based treatment in ASPIRE or ENDEAVOR. Low serum lactate dehydrogenase was the only factor associated with achieving ≥CR vs patients not achieving CR in ASPIRE in multivariate regression analyses. No association was found between cytogenetic risk status and reaching ≥CR. Carfilzomib treatment may lead to rapid and deep responses, irrespective of most patient characteristics

An updated analysis of NN elastic scattering data to 1.6 GeV

An energy-dependent and set of single-energy partial-wave analyses of $NN$ elastic scattering data have been completed. The fit to 1.6~GeV has been supplemented with a low-energy analysis to 400 MeV. Using the low-energy fit, we study the sensitivity of our analysis to the choice of $\pi NN$ coupling constant. We also comment on the possibility of fitting $np$ data alone. These results are compared with those found in the recent Nijmegen analyses. (Figures may be obtained from the authors upon request.)Comment: 17 pages of text, VPI-CAPS-7/

Childhood Asthma and Environmental Exposures at Swimming Pools: State of the Science and Research Recommendations

OBJECTIVES: Recent studies have explored the potential for swimming pool disinfection by-products (DBPs), which are respiratory irritants, to cause asthma in young children. Here we describe the state of the science on methods for understanding children's exposure to DBPs and biologics at swimming pools and associations with new-onset childhood asthma and recommend a research agenda to improve our understanding of this issue. DATA SOURCES: A workshop was held in Leuven, Belgium, 21-23 August 2007, to evaluate the literature and to develop a research agenda to better understand children's exposures in the swimming pool environment and their potential associations with new-onset asthma. Participants, including clinicians, epidemiologists, exposure scientists, pool operations experts, and chemists, reviewed the literature, prepared background summaries, and held extensive discussions on the relevant published studies, knowledge of asthma characterization and exposures at swimming pools, and epidemiologic study designs. SYNTHESIS: Childhood swimming and new-onset childhood asthma have clear implications for public health. If attendance at indoor pools increases risk of childhood asthma, then concerns are warranted and action is necessary. If there is no such relationship, these concerns could unnecessarily deter children from indoor swimming and/or compromise water disinfection. CONCLUSIONS: Current evidence of an association between childhood swimming and new-onset asthma is suggestive but not conclusive. Important data gaps need to be filled, particularly in exposure assessment and characterization of asthma in the very young. Participants recommended that additional evaluations using a multidisciplinary approach are needed to determine whether a clear association exists

Evaluating housing quality, health and safety using an Internet-based data collection and response system: a cross-sectional study

<p>Abstract</p> <p>Background</p> <p>Typically housing and health surveys are not integrated together and therefore are not representative of population health or national housing stocks. In addition, the existing channels for distributing information about housing and health issues to the general public are limited. The aim of this study was to develop a data collection and response system that would allow us to assess the Finnish housing stock from the points of view of quality, health and safety, and also to provide a tool to distribute information about important housing health and safety issues.</p> <p>Methods</p> <p>The data collection and response system was tested with a sample of 3000 adults (one per household), who were randomly selected from the Finnish Population Register Centre. Spatial information about the exact location of the residences (i.e. coordinates) was included in the database inquiry. People could participate either by completing and returning a paper questionnaire or by completing the same questionnaire via the Internet. The respondents did not receive any compensation for their time in completing the questionnaire.</p> <p>Results</p> <p>This article describes the data collection and response system and presents the main results of the population-based testing of the system. A total of 1312 people (response rate 44%) answered the questionnaire, though only 80 answered via the Internet. A third of the respondents had indicated they wanted feedback. Albeit a majority (>90%) of the respondents reported being satisfied or quite satisfied with their residence, there were a number of prevalent housing issues identified that can be related to health and safety.</p> <p>Conclusions</p> <p>The collected database can be used to evaluate the quality of the housing stock in terms of occupant health and safety, and to model its association with occupant health and well-being. However, it must be noted that all the health outcomes gathered in this study are self-reported. A follow-up study is needed to evaluate whether the occupants acted on the feedback they received. Relying solely on an Internet-based questionnaire for collecting data would not appear to provide an adequate response rate for random population-based surveys at this point in time.</p

Automated Docking Screens: A Feasibility Study

Molecular docking is themost practical approach to leverage protein structure for ligand discovery, but the technique retains important liabilities that make it challenging to deploy on a large scale. We have therefore created an expert system, DOCKBlaster, to investigate the feasibility of full automation. The method requires a PDB code, sometimes with a ligand structure, and from that alone can launch a full screen of large libraries. A critical feature is self-assessment, which estimates the anticipated reliability of the automated screening results using pose fidelity and enrichment. Against common benchmarks, DOCKBlaster recapitulates the crystal ligand pose within 2 A ̊ rmsd 50-60 % of the time; inferior to an expert, but respectrable. Half the time the ligand also ranked among the top 5 % of 100 physically matched decoys chosen on the fly. Further tests were undertaken culminating in a study of 7755 eligible PDB structures. In 1398 cases, the redocked ligand ranked in the top 5 % of 100 property-matched decoys while also posing within 2 A ̊ rmsd, suggesting that unsupervised prospective docking is viable. DOCK Blaster is available a

Automated time activity classification based on global positioning system (GPS) tracking data

<p>Abstract</p> <p>Background</p> <p>Air pollution epidemiological studies are increasingly using global positioning system (GPS) to collect time-location data because they offer continuous tracking, high temporal resolution, and minimum reporting burden for participants. However, substantial uncertainties in the processing and classifying of raw GPS data create challenges for reliably characterizing time activity patterns. We developed and evaluated models to classify people's major time activity patterns from continuous GPS tracking data.</p> <p>Methods</p> <p>We developed and evaluated two automated models to classify major time activity patterns (i.e., indoor, outdoor static, outdoor walking, and in-vehicle travel) based on GPS time activity data collected under free living conditions for 47 participants (N = 131 person-days) from the Harbor Communities Time Location Study (HCTLS) in 2008 and supplemental GPS data collected from three UC-Irvine research staff (N = 21 person-days) in 2010. Time activity patterns used for model development were manually classified by research staff using information from participant GPS recordings, activity logs, and follow-up interviews. We evaluated two models: (a) a rule-based model that developed user-defined rules based on time, speed, and spatial location, and (b) a random forest decision tree model.</p> <p>Results</p> <p>Indoor, outdoor static, outdoor walking and in-vehicle travel activities accounted for 82.7%, 6.1%, 3.2% and 7.2% of manually-classified time activities in the HCTLS dataset, respectively. The rule-based model classified indoor and in-vehicle travel periods reasonably well (Indoor: sensitivity > 91%, specificity > 80%, and precision > 96%; in-vehicle travel: sensitivity > 71%, specificity > 99%, and precision > 88%), but the performance was moderate for outdoor static and outdoor walking predictions. No striking differences in performance were observed between the rule-based and the random forest models. The random forest model was fast and easy to execute, but was likely less robust than the rule-based model under the condition of biased or poor quality training data.</p> <p>Conclusions</p> <p>Our models can successfully identify indoor and in-vehicle travel points from the raw GPS data, but challenges remain in developing models to distinguish outdoor static points and walking. Accurate training data are essential in developing reliable models in classifying time-activity patterns.</p

Swim-Training Changes the Spatio-Temporal Dynamics of Skeletogenesis in Zebrafish Larvae (Danio rerio)

Fish larvae experience many environmental challenges during development such as variation in water velocity, food availability and predation. The rapid development of structures involved in feeding, respiration and swimming increases the chance of survival. It has been hypothesized that mechanical loading induced by muscle forces plays a role in prioritizing the development of these structures. Mechanical loading by muscle forces has been shown to affect larval and embryonic bone development in vertebrates, but these investigations were limited to the appendicular skeleton. To explore the role of mechanical load during chondrogenesis and osteogenesis of the cranial, axial and appendicular skeleton, we subjected zebrafish larvae to swim-training, which increases physical exercise levels and presumably also mechanical loads, from 5 until 14 days post fertilization. Here we show that an increased swimming activity accelerated growth, chondrogenesis and osteogenesis during larval development in zebrafish. Interestingly, swim-training accelerated both perichondral and intramembranous ossification. Furthermore, swim-training prioritized the formation of cartilage and bone structures in the head and tail region as well as the formation of elements in the anal and dorsal fins. This suggests that an increased swimming activity prioritized the development of structures which play an important role in swimming and thereby increasing the chance of survival in an environment where water velocity increases. Our study is the first to show that already during early zebrafish larval development, skeletal tissue in the cranial, axial and appendicular skeleton is competent to respond to swim-training due to increased water velocities. It demonstrates that changes in water flow conditions can result into significant spatio-temporal changes in skeletogenesis