Mass spectrometry is commonly used in the identification of species present in microbial samples, but the high similarity in the peptide composition between strains of a single species has made ...analysis at the subspecies level challenging. Prior research in this area has employed methods such as Principal Component Analysis (PCA), the k-Nearest Neighbors’ (kNN) algorithm, and Pearson correlation. Previously, 1D cross-correlation of mass spectra has been shown to be useful in the classification of small molecule compounds as well as in the identification of peptide sequences via the SEQUEST algorithm and its variants. While direct application of cross-correlation to mass spectral data has been shown to aid in the identification of many other types of compounds, this type of analysis has not been demonstrated in the literature for the purpose of LC-MS based identification of microbial strains. A method of identifying microbial strains is presented here that applies the principle of 2D cross-correlation to LC-MS data. For a set of N = 30 yeast isolate samples representing 5 yeast strains (K-97, S-33, T-58, US-05, WB-06), high-resolution LC-MS-Orbitrap data were collected. Reference spectra were then generated for each strain from the combined data of each sample of that strain. Sample strains were then predicted by computing the 2D cross-correlation of each sample against the reference spectra, followed by application of correction factors measuring the asymmetry of the 2D correlation functions.
Phagocytosis is required for a broad range of physiological functions, from pathogen defense to tissue homeostasis, but the mechanisms required for phagocytosis of diverse substrates remain ...incompletely understood. Here, we developed a rapid magnet-based phenotypic screening strategy, and performed eight genome-wide CRISPR screens in human cells to identify genes regulating phagocytosis of distinct substrates. After validating select hits in focused miniscreens, orthogonal assays and primary human macrophages, we show that (1) the previously uncharacterized gene NHLRC2 is a central player in phagocytosis, regulating RhoA-Rac1 signaling cascades that control actin polymerization and filopodia formation, (2) very-long-chain fatty acids are essential for efficient phagocytosis of certain substrates and (3) the previously uncharacterized Alzheimer's disease-associated gene TM2D3 can preferentially influence uptake of amyloid-β aggregates. These findings illuminate new regulators and core principles of phagocytosis, and more generally establish an efficient method for unbiased identification of cellular uptake mechanisms across diverse physiological and pathological contexts.
Microarray-based expression profiling experiments typically use either a one-color or a two-color design to measure mRNA abundance. The validity of each approach has been amply demonstrated. Here we ...provide a simultaneous comparison of results from one- and two-color labeling designs, using two independent RNA samples from the Microarray Quality Control (MAQC) project, tested on each of three different microarray platforms. The data were evaluated in terms of reproducibility, specificity, sensitivity and accuracy to determine if the two approaches provide comparable results. For each of the three microarray platforms tested, the results show good agreement with high correlation coefficients and high concordance of differentially expressed gene lists within each platform. Cumulatively, these comparisons indicate that data quality is essentially equivalent between the one- and two-color approaches and strongly suggest that this variable need not be a primary factor in decisions regarding experimental microarray design.
Recent clusters of outbreaks of mosquito-borne diseases (Rift Valley fever and chikungunya) in Africa and parts of the Indian Ocean islands illustrate how interannual climate variability influences ...the changing risk patterns of disease outbreaks. Although Rift Valley fever outbreaks have been known to follow periods of above-normal rainfall, the timing of the outbreak events has largely been unknown. Similarly, there is inadequate knowledge on climate drivers of chikungunya outbreaks. We analyze a variety of climate and satellite-derived vegetation measurements to explain the coupling between patterns of climate variability and disease outbreaks of Rift Valley fever and chikungunya.
We derived a teleconnections map by correlating long-term monthly global precipitation data with the NINO3.4 sea surface temperature (SST) anomaly index. This map identifies regional hot-spots where rainfall variability may have an influence on the ecology of vector borne disease. Among the regions are Eastern and Southern Africa where outbreaks of chikungunya and Rift Valley fever occurred 2004-2009. Chikungunya and Rift Valley fever case locations were mapped to corresponding climate data anomalies to understand associations between specific anomaly patterns in ecological and climate variables and disease outbreak patterns through space and time. From these maps we explored associations among Rift Valley fever disease occurrence locations and cumulative rainfall and vegetation index anomalies. We illustrated the time lag between the driving climate conditions and the timing of the first case of Rift Valley fever. Results showed that reported outbreaks of Rift Valley fever occurred after ∼3-4 months of sustained above-normal rainfall and associated green-up in vegetation, conditions ideal for Rift Valley fever mosquito vectors. For chikungunya we explored associations among surface air temperature, precipitation anomalies, and chikungunya outbreak locations. We found that chikungunya outbreaks occurred under conditions of anomalously high temperatures and drought over Eastern Africa. However, in Southeast Asia, chikungunya outbreaks were negatively correlated (p<0.05) with drought conditions, but positively correlated with warmer-than-normal temperatures and rainfall.
Extremes in climate conditions forced by the El Niño/Southern Oscillation (ENSO) lead to severe droughts or floods, ideal ecological conditions for disease vectors to emerge, and may result in epizootics and epidemics of Rift Valley fever and chikungunya. However, the immune status of livestock (Rift Valley fever) and human (chikungunya) populations is a factor that is largely unknown but very likely plays a role in the spatial-temporal patterns of these disease outbreaks. As the frequency and severity of extremes in climate increase, the potential for globalization of vectors and disease is likely to accelerate. Understanding the underlying patterns of global and regional climate variability and their impacts on ecological drivers of vector-borne diseases is critical in long-range planning of appropriate disease and disease-vector response, control, and mitigation strategies.
Background:
Players in the National Football League (NFL) sustain injuries every season as the result of their participation. One factor associated with the rate of injury is the type of playing ...surface on which the players participate.
Hypothesis:
There is no difference in the rate of knee sprains and ankle sprains during NFL games when comparing rates of those injuries during games played on natural grass surfaces with rates of those injuries during games played on the artificial surface FieldTurf.
Study Design:
Descriptive epidemiology study.
Methods:
The NFL records injury and exposure (ie, game) data as part of its injury surveillance system. During the 2000-2009 NFL seasons, there were 2680 games (5360 team games) played on grass or artificial surfaces. Specifically, 1356 team games were played on FieldTurf and 4004 team games were played on grass. We examined the 2000-2009 game-related injury data from those games as recorded by the injury surveillance system. The data included the injury diagnosis, the date of injury, and the surface at the time of injury. The injury data showed that 1528 knee sprains and 1503 ankle sprains occurred during those games. We calculated injury rates for knee sprains and ankle sprains—specifically, medial collateral ligament (MCL) sprains, anterior cruciate ligament (ACL) sprains, eversion ankle sprains, and inversion ankle sprains—using incidence density ratios (IDRs). We used a Poisson model and logistic regression odds ratios to validate the IDR analysis. A multivariate logistic regression model was used to adjust the odds ratio for weather conditions.
Results:
The observed injury rate of knee sprains on FieldTurf was 22% (IDR = 1.22, 95% confidence interval CI, 1.09-1.36) higher than on grass, and the injury rate of ankle sprains on FieldTurf was 22% (IDR = 1.22, 95% CI, 1.09-1.36) higher than on grass. These differences are statistically significant. Specifically, the observed injury rates of ACL sprains and eversion ankle sprains on FieldTurf surfaces were 67% (P < .001) and 31% (P < .001) higher than on grass surfaces and were statistically significant. The observed injury rates of MCL sprains and inversion ankle sprains were also not significantly higher on FieldTurf surfaces (P = .689 and .390, respectively).
Conclusion:
Injury rates for ACL sprains and eversion ankle sprains for NFL games played on FieldTurf were higher than rates for those injuries in games played on grass, and the differences were statistically significant.
Abstract
We introduce a galaxy cluster mass observable, μ⋆, based on the stellar masses of cluster members, and we present results for the Dark Energy Survey (DES) Year 1 (Y1) observations. Stellar ...masses are computed using a Bayesian model averaging method, and are validated for DES data using simulations and COSMOS data. We show that μ⋆ works as a promising mass proxy by comparing our predictions to X-ray measurements. We measure the X-ray temperature–μ⋆ relation for a total of 129 clusters matched between the wide-field DES Y1 redMaPPer catalogue and Chandra and XMM archival observations, spanning the redshift range 0.1 < $z$ < 0.7. For a scaling relation that is linear in logarithmic space, we find a slope of α = 0.488 ± 0.043 and a scatter in the X-ray temperature at fixed μ⋆ of $\sigma _{{\rm ln} T_\mathrm{ X}|\mu _\star }= 0.266^{+0.019}_{-0.020}$ for the joint sample. By using the halo mass scaling relations of the X-ray temperature from the Weighing the Giants program, we further derive the μ⋆-conditioned scatter in mass, finding $\sigma _{{\rm ln} M|\mu _\star }= 0.26^{+ 0.15}_{- 0.10}$. These results are competitive with well-established cluster mass proxies used for cosmological analyses, showing that μ⋆ can be used as a reliable and physically motivated mass proxy to derive cosmological constraints.
Abstract
Species occurrence data are foundational for research, conservation, and science communication, but the limited availability and accessibility of reliable data represents a major obstacle, ...particularly for insects, which face mounting pressures. We present
BeeBDC
, a new
R
package, and a global bee occurrence dataset to address this issue. We combined >18.3 million bee occurrence records from multiple public repositories (GBIF, SCAN, iDigBio, USGS, ALA) and smaller datasets, then standardised, flagged, deduplicated, and cleaned the data using the reproducible
BeeBDC R
-workflow. Specifically, we harmonised species names (following established global taxonomy), country names, and collection dates and, we added record-level flags for a series of potential quality issues. These data are provided in two formats, “cleaned” and “flagged-but-uncleaned”. The
BeeBDC
package with online documentation provides end users the ability to modify filtering parameters to address their research questions. By publishing reproducible
R
workflows and globally cleaned datasets, we can increase the accessibility and reliability of downstream analyses. This workflow can be implemented for other taxa to support research and conservation.
This study aimed to determine if delayed cord clamping (DCC) affected brain myelin water volume fraction (VFm) and neurodevelopment in term infants.
This was a single-blinded randomized controlled ...trial of healthy pregnant women with term singleton fetuses randomized at birth to either immediate cord clamping (ICC) (≤ 20 seconds) or DCC (≥ 5 minutes). Follow-up at 12 months of age consisted of blood work for serum iron indices and lead levels, a nonsedated magnetic resonance imaging (MRI), followed within the week by neurodevelopmental testing.
At birth, 73 women were randomized into one of two groups: ICC (the usual practice) or DCC (the intervention). At 12 months, among 58 active participants, 41 (80%) had usable MRIs. There were no differences between the two groups on maternal or infant demographic variables. At 12 months, infants who had DCC had increased white matter brain growth in regions localized within the right and left internal capsules, the right parietal, occipital, and prefrontal cortex. Gender exerted no difference on any variables. Developmental testing (Mullen Scales of Early Learning, nonverbal, and verbal composite scores) was not significantly different between the two groups.
At 12 months of age, infants who received DCC had greater myelin content in important brain regions involved in motor function, visual/spatial, and sensory processing. A placental transfusion at birth appeared to increase myelin content in the early developing brain.
· DCC resulted in higher hematocrits in newborn period.. · DCC appears to increase myelin at 12 months.. · Gender did not influence study outcomes..
ABSTRACT
Using archival X-ray observations and a lognormal population model, we estimate constraints on the intrinsic scatter in halo mass at fixed optical richness for a galaxy cluster sample ...identified in Dark Energy Survey Year-One (DES-Y1) data with the redMaPPer algorithm. We examine the scaling behaviour of X-ray temperatures, TX, with optical richness, λRM, for clusters in the redshift range 0.2 < z < 0.7. X-ray temperatures are obtained from Chandra and XMM observations for 58 and 110 redMaPPer systems, respectively. Despite non-uniform sky coverage, the TX measurements are $\gt 50{{\ \rm per\ cent}}$ complete for clusters with λRM > 130. Regression analysis on the two samples produces consistent posterior scaling parameters, from which we derive a combined constraint on the residual scatter, $\sigma _{\ln T \, |\, \lambda }= 0.275 \pm 0.019$. Joined with constraints for TX scaling with halo mass from the Weighing the Giants program and richness–temperature covariance estimates from the LoCuSS sample, we derive the richness-conditioned scatter in mass, $\sigma _{\ln M \, |\, \lambda }= 0.30 \pm 0.04\, _{({\rm stat})} \pm 0.09\, _{({\rm sys})}$, at an optical richness of approximately 100. Uncertainties in external parameters, particularly the slope and variance of the TX–mass relation and the covariance of TX and λRM at fixed mass, dominate the systematic error. The $95{{\ \rm per\ cent}}$ confidence region from joint sample analysis is relatively broad, $\sigma _{\ln M \, |\, \lambda }\in 0.14, \, 0.55$, or a factor 10 in variance.