Serological evidence for non-lethal exposures of Mongolian wild birds to highly pathogenic avian influenza H5N1 virus.

Surveillance for highly pathogenic avian influenza viruses (HPAIV) in wild birds is logistically demanding due to the very low rates of virus detection. Serological approaches may be more cost effective as they require smaller sample sizes to identify exposed populations. We hypothesized that antigenic differences between classical Eurasian H5 subtype viruses (which have low pathogenicity in chickens) and H5N1 viruses of the Goose/Guangdong/96 H5 lineage (which are HPAIV) may be used to differentiate populations where HPAIVs have been circulating, from those where they have not. To test this we performed hemagglutination inhibition assays to compare the reactivity of serum samples from wild birds in Mongolia (where HPAIV has been circulating, n = 1,832) and Europe (where HPAIV has been rare or absent, n = 497) to a panel of reference viruses including classical Eurasian H5 (of low pathogenicity), and five HPAIV H5N1 antigens of the Asian lineage A/Goose/Guangdong/1/96. Antibody titres were detected against at least one of the test antigens for 182 Mongolian serum samples (total seroprevalence of 0.10, n = 1,832, 95% adjusted Wald confidence limits of 0.09-0.11) and 25 of the European sera tested (total seroprevalence of 0.05, n = 497, 95% adjusted Wald confidence limits of 0.03-0.07). A bias in antibody titres to HPAIV antigens was found in the Mongolian sample set (22/182) that was absent in the European sera (0/25). Although the interpretation of serological data from wild birds is complicated by the possibility of exposure to multiple strains, and variability in the timing of exposure, these findings suggest that a proportion of the Mongolian population had survived exposure to HPAIV, and that serological assays may enhance the targeting of traditional HPAIV surveillance toward populations where isolation of HPAIV is more likely.Funding for this work was provided by the National Institute of Allergy and Infectious Diseases, National Institutes of Health (NIH), and the Department of Health and Human Services under contracts HHSN266200700007C and HHSN266200700010C. Further support was provided through a doctoral training grant to MG by the Biotechnology and Biological Sciences Research Council (BB/F016786/1).This is the final version of the article. It first appeared from PLOS via http://dx.doi.org/ 10.1371/journal.pone.011356

Index selection in terminal sires improves lamb performance at finishing

Lamb meat is often perceived by consumers as fatty, and consumption has decreased in recent decades. A lean growth index was developed in the UK for terminal sire breeds to increase carcass lean content and constrain fat content at a constant age end point. The purposes of this study were 1) to evaluate the effects of index selection of terminal sires on their crossbred offspring at finishing and 2) to evaluate its effectiveness within terminal sire breeds. Approximately 70% of lambs marketed in the UK have been sired by rams of breeds typically thought of as specialized terminal sires. The most widely used are Charollais, Suffolk, and Texel. These breeds participated in sire referencing schemes from the early 1990s by sharing rams among flocks selected on the lean growth index. From 1999 to 2002 approximately 15 “high” and 15 “low” lean growth index score rams were selected from within their sire referencing schemes and mated to Welsh and Scottish Mule ewes. Their crossbred offspring were commercially reared on 3 farms in the UK. Lambs were finished to an estimated 11% subcutaneous fat by visual evaluation. At finishing, lambs were weighed, ultrasonically scanned, and assessed for condition score and conformation. Records were obtained for 6,356 lambs on finishing BW (FWT), ultrasonic muscle depth (UMD), ultrasonic fat depth, overall condition score (OCS), and conformation of gigot, loin, and shoulder. Ultrasonic fat depth was log transformed (logUFD) to approach normality. High-index-sired lambs were heavier at finishing (1.2 ± 0.2 kg) with thicker UMD (0.7 ± 0.2 mm) and less logUFD (0.08 ± 0.01 mm; P \u3c 0.05). There were no differences in OCS or conformation based on the sire index or breed (P \u3e 0.08). Suffolk-sired lambs were heavier than Charollais (1.0 ± 0.3 kg), which were heavier than Texel (0.9 ± 0.3 kg; P \u3c 0.001). Texel-sired lambs had thicker UMD than Charollais (0.7 ± 0.2 mm; P \u3c 0.001) but were not different than Suffolk. Charollais-sired lambs had greater logUFD than both Texel (0.098 ± 0.016 mm) and Suffolk (0.061 ± 0.017 mm) sired lambs (P \u3c 0.001). Within a breed, high- and low-index-sired lambs differed in performance with the exceptions of FWT and UMD in Suffolks. Index selection produced heavier and leaner lambs at finishing. Producers have flexibility in choosing the terminal sire that best fits their production system

Genetic evaluation of days to harvest in crossbred lambs

Days to harvest (DTH) is the number of days a lamb is fed before reaching a target level of fatness. Although economically relevant, this trait has not been thoroughly evaluated in sheep. Most lambs harvested in the United Kingdom are crossbreds sired by purebred terminal sires, with Charollais, Suffolk, and Texel most commonly used. Sires from these breeds were selected on an index designed to increase lean growth while constraining fat. The purpose of this research was to 1) evaluate the effects of index selection in terminal sires on DTH and 2) evaluate the feasibility of incorporating DTH into genetic evaluation programs. Charollais, Suffolk, and Texel sheep had participated in sire referencing schemes where genetic links among flocks were established by sharing rams. Rams with high or low index scores were chosen from these schemes and mated to crossbred ewes at 3 farms in the United Kingdom. Lambs were harvested at a target 11% subcutaneous fat. Records on DTH from 6,350 lambs were analyzed in 2 ways: 1) as time to harvest fitting a survival model and 2) as a normally distributed variable in a bivariate analysis with weight at harvest. The survival analysis was stratified by rearing type (single or twin). In both approaches, sires were fitted using a multivariate normal distribution with a relationship matrix. Regardless of model fitted, sire index did not affect DTH (P \u3e 0.10). However, Texel-sired lambs reached harvest faster (P \u3c 0.01) than either Charollais- or Suffolk-sired lambs although DTH in those 2 breed types did not differ (P \u3e 0.1). Ewe lambs reached harvest faster than wethers (P \u3c 0.01). Lambs from older ewes were harvested faster (P \u3c 0.001). The heritability of DTH was 0.21 from the survival model and 0.20 from the bivariate model. Rank correlation of sire EBV between methods was 0.9, suggesting strong agreement. The use of high or low index sires did not extend DTH in lambs harvested at a target fatness. Importantly, there is no antagonism between improving carcass merit and extending the grazing season. Furthermore, DTH is moderately heritable. If economically justified within a breeding program, it could be reduced through genetic selection

On definitions of "mathematician"

The definition of who is or what makes a ``mathematician" is an important and urgent issue to be addressed in the mathematics community. Too often, a narrower definition of who is considered a mathematician (and what is considered mathematics) is used to exclude people from the discipline -- both explicitly and implicitly. However, using a narrow definition of a mathematician allows us to examine and challenge systemic barriers that exist in certain spaces of the community. This paper explores and illuminates tensions between narrow and broad definitions and how they can be used to promote both inclusion and exclusion simultaneously. In this article, we present a framework of definitions based on identity, function, and qualification and exploring several different meanings of ``mathematician". By interrogating various definitions, we highlight their risks and opportunities, with an emphasis on implications for broadening and/or narrowing participation of underrepresented groups.Comment: 21 pages, 2 figure

The Sydney-AAO Multi-object Integral field spectrograph (SAMI)

We demonstrate a novel technology that combines the power of the multi-object spectrograph with the spatial multiplex advantage of an integral field spectrograph (IFS). The Sydney-AAO Multi-object IFS (SAMI) is a prototype wide-field system at the Anglo-Australian Telescope (AAT) that allows 13 imaging fibre bundles ("hexabundles") to be deployed over a 1-degree diameter field of view. Each hexabundle comprises 61 lightly-fused multimode fibres with reduced cladding and yields a 75 percent filling factor. Each fibre core diameter subtends 1.6 arcseconds on the sky and each hexabundle has a field of view of 15 arcseconds diameter. The fibres are fed to the flexible AAOmega double-beam spectrograph, which can be used at a range of spectral resolutions (R=lambda/delta(lambda) ~ 1700-13000) over the optical spectrum (3700-9500A). We present the first spectroscopic results obtained with SAMI for a sample of galaxies at z~0.05. We discuss the prospects of implementing hexabundles at a much higher multiplex over wider fields of view in order to carry out spatially--resolved spectroscopic surveys of 10^4 to 10^5 galaxies.Comment: 24 pages, 16 figures. Accepted by MNRA

Rapid neurogenesis through transcriptional activation in human stem cells

Advances in cellular reprogramming and stem cell differentiation now enable ex vivo studies of human neuronal differentiation. However, it remains challenging to elucidate the underlying regulatory programs because differentiation protocols are laborious and often result in low neuron yields. Here, we overexpressed two Neurogenin transcription factors in human-induced pluripotent stem cells and obtained neurons with bipolar morphology in 4 days, at greater than 90% purity. The high purity enabled mRNA and microRNA expression profiling during neurogenesis, thus revealing the genetic programs involved in the rapid transition from stem cell to neuron. The resulting cells exhibited transcriptional, morphological and functional signatures of differentiated neurons, with greatest transcriptional similarity to prenatal human brain samples. Our analysis revealed a network of key transcription factors and microRNAs that promoted loss of pluripotency and rapid neurogenesis via progenitor states. Perturbations of key transcription factors affected homogeneity and phenotypic properties of the resulting neurons, suggesting that a systems-level view of the molecular biology of differentiation may guide subsequent manipulation of human stem cells to rapidly obtain diverse neuronal types

Volumetric CT-based segmentation of NSCLC using 3D-Slicer

Accurate volumetric assessment in non-small cell lung cancer (NSCLC) is critical for adequately informing treatments. In this study we assessed the clinical relevance of a semiautomatic computed tomography (CT)-based segmentation method using the competitive region-growing based algorithm, implemented in the free and public available 3D-Slicer software platform. We compared the 3D-Slicer segmented volumes by three independent observers, who segmented the primary tumour of 20 NSCLC patients twice, to manual slice-by-slice delineations of five physicians. Furthermore, we compared all tumour contours to the macroscopic diameter of the tumour in pathology, considered as the “gold standard”. The 3D-Slicer segmented volumes demonstrated high agreement (overlap fractions > 0.90), lower volume variability (p = 0.0003) and smaller uncertainty areas (p = 0.0002), compared to manual slice-by-slice delineations. Furthermore, 3D-Slicer segmentations showed a strong correlation to pathology (r = 0.89, 95%CI, 0.81–0.94). Our results show that semiautomatic 3D-Slicer segmentations can be used for accurate contouring and are more stable than manual delineations. Therefore, 3D-Slicer can be employed as a starting point for treatment decisions or for high-throughput data mining research, such as Radiomics, where manual delineating often represent a time-consuming bottleneck

Predicting neurodegeneration from sleep related biofluid changes

Sleep-wake disturbances are common in neurodegenerative diseases and may occur years before the clinical diagnosis, potentially either representing an early stage of the disease itself or acting as a pathophysiological driver. Therefore, discovering biomarkers that identify individuals with sleep-wake disturbances who are at risk of developing neurodegenerative diseases will allow early diagnosis and intervention. Given the association between sleep and neurodegeneration, the most frequently analyzed fluid biomarkers in people with sleep-wake disturbances to date include those directly associated with neurodegeneration itself, such as neurofilament light chain, phosphorylated tau, amyloid-beta and alpha-synuclein. Abnormalities in these biomarkers in patients with sleep-wake disturbances are considered as evidence of an underlying neurodegenerative process. Levels of hormonal sleep-related biomarkers such as melatonin, cortisol and orexin are often abnormal in patients with clinical neurodegenerative diseases, but their relationships with the more standard neurodegenerative biomarkers remain unclear. Similarly, it is unclear whether other chronobiological/circadian biomarkers, such as disrupted clock gene expression, are causal factors or a consequence of neurodegeneration. Current data would suggest that a combination of fluid biomarkers may identify sleep-wake disturbances that are most predictive for the risk of developing neurodegenerative disease with more optimal sensitivity and specificity

Centerscope

Centerscope, formerly Scope, was published by the Boston University Medical Center "to communicate the concern of the Medical Center for the development and maintenance of improved health care in contemporary society.

Predicting Imminent Cyanobacterial Blooms in Lakes Using Incomplete Timely Data

Toxic cyanobacterial blooms (CBs) are becoming more frequent globally, posing a threat to freshwater ecosystems. While making long-range forecasts is overly challenging, predicting imminent CBs is possible from precise monitoring data of the underlying covariates. It is, however, infeasibly costly to conduct precise monitoring on a large scale, leaving most lakes unmonitored or only partially monitored. The challenge is hence to build a predictive model that can use the incomplete, partially-monitored data to make near-future CB predictions. By using 30 years of monitoring data for 78 water bodies in Alberta, Canada, combined with data of watershed characteristics (including natural land cover and anthropogenic land use) and meteorological conditions, we train a Bayesian network that predicts future 2-week CB with an area under the curve (AUC) of 0.83. The only monitoring data that the model needs to reach this level of accuracy are whether the cell count and Secchi depth are low, medium, or high, which can be estimated by advanced high-resolution imaging technology or trained local citizens. The model is robust against missing values as in the absence of any single covariate, it performs with an AUC of at least 0.78. While taking a major step toward reduced-cost, less data-intensive CB forecasting, our results identify those key covariates that are worth the monitoring investment for highly accurate predictions.This article is published as Heggerud, Christopher M., Jingjing Xu, Hao Wang, Mark A. Lewis, Ron W. Zurawell, Charlie JG Loewen, Rolf D. Vinebrooke, and Pouria Ramazi. "Predicting imminent cyanobacterial blooms in lakes using incomplete timely data." Water Resources Research 60, no. 2 (2024): e2023WR035540. doi:10.1029/2023WR035540. © 2024 The Authors. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited