Development of tools for in situ hybridization in human embryonic stem cells

Abstract only availableOur laboratory uses human embryonic stem cells (hESC) to understand how embryonic cells differentiate into the cells of the placenta. The long term goal of my research is to develop in situ hybridization methods and use them to determine where genes are being expressed within differentiating hESC colonies. I focused my research on two genes that code for transcription factors, OCT 4 and GATA 2. OCT 4 is required to maintain stem cells in an undifferentiated state. GATA 2 is thought to be one of the key transcription factors that promote stem cell differentiation into syncytiotrophoblast, a placental cell type. The first step in in situ hybridization is the development of a labeled RNA probe. I designed primers to amplify a 214bp portion of the GATA2 gene sequence by PCR, and then cloned the PCR product into E. coli bacteria. I confirmed the presence and orientation of the insert by using restriction digestion and DNA sequencing. I used bacteria already transformed with a 182bp OCT4 probe sequence to create a riboprobe. I grew up the bacteria overnight, lysed them, and purified the plasmid DNA. I linearized the plasmid with a restriction enzyme, purified it, and transcribed the DNA to RNA, incorporating digoxygenin (DIG) labeled nucleotides. In the near future, I will utilize the same method to transcribe the GATA2 probe, and use both RNA probes to perform in situ hybridizations on hESC.Life Sciences Undergraduate Research Opportunity Progra

The Coagulation and Immune Systems are Directly Linked through the Activation of Interleukin-1α by Thrombin

Ancient organisms have a combined coagulation and immune system, and although links between inflammation and haemostasis exist in mammals, they are indirect and slower to act. Here we investigated direct links between mammalian immune and coagulation systems by examining cytokine proproteins for potential thrombin protease consensus sites. We found that interleukin (IL)-1α is directly activated by thrombin. Thrombin cleaved pro-IL-1α at a site perfectly conserved across disparate species, indicating functional importance. Surface pro-IL-1α on macrophages and activated platelets was cleaved and activated by thrombin, while tissue factor, a potent thrombin activator, colocalised with pro-IL-1α in the epidermis. Mice bearing a mutation in the IL-1α thrombin cleavage site (R114Q) exhibited defects in efficient wound healing and rapid thrombopoiesis after acute platelet loss. Thrombin-cleaved IL-1α was detected in humans during sepsis, pointing to the relevance of this pathway for normal physiology and the pathogenesis of inflammatory and thrombotic diseases.This work was funded by British Heart Foundation Grants FS/09/005/26845, FS/13/3/30038, FS/18/19/33371 and RG/16/8/32388 to MC, RG/13/14/30314 to MB, the BHF Cambridge Centre for Research Excellence RE/13/6/30180, the Oxbridge BHF Regenerative Medicine Centre RM/13/3/30159, and the Cambridge NIHR Biomedical Research Centre

Homogeneous Subgroups of Young Children with Autism Improve Phenotypic Characterization in the Study to Explore Early Development

The objective of this study was to identify homogenous classes of young children with autism spectrum disorder (ASD) to improve phenotypic characterization. Children were enrolled in the Study to Explore Early Development between 2 and 5 years of age. 707 children were classified with ASD after a comprehensive evaluation with strict diagnostic algorithms. Four classes of children with ASD were identified from latent class analysis: mild language delay with cognitive rigidity, mild language and motor delay with dysregulation, general developmental delay, and significant developmental delay with repetitive motor behaviors. We conclude that a four-class phenotypic model of children with ASD best describes our data and improves phenotypic characterization of young children with ASD. Implications for screening, diagnosis, and research are discussed

The CellPhe toolkit for cell phenotyping using time-lapse imaging and pattern recognition

Approaches for temporal analysis and quantitative characterisation of single cell morphology and dynamics remain in high demand. Here authors present CellPhe, a pattern recognition toolkit for the unbiased characterisation of cellular phenotypes within time-lapse videos

Words, concepts, and the geometry of analogy

In Proceedings SLPCS 2016, arXiv:1608.01018In Proceedings SLPCS 2016, arXiv:1608.01018In Proceedings SLPCS 2016, arXiv:1608.01018© S. McGregor, M. Purver & G. Wiggins. This paper presents a geometric approach to the problem of modelling the relationship between words and concepts, focusing in particular on analogical phenomena in language and cognition. Grounded in recent theories regarding geometric conceptual spaces, we begin with an analysis of existing static distributional semantic models and move on to an exploration of a dynamic approach to using high dimensional spaces of word meaning to project subspaces where analogies can potentially be solved in an online, contextualised way. The crucial element of this analysis is the positioning of statistics in a geometric environment replete with opportunities for interpretation

Pre- and Postnatal Fine Particulate Matter Exposure and Childhood Cognitive and Adaptive Function

Increasing evidence exists for an association between early life fine particulate matter (PM2.5) exposure and several neurodevelopmental outcomes, including autism spectrum disorder (ASD); however, the association between PM2.5 and adaptive and cognitive function remains poorly understood. Participants included 658 children with ASD, 771 with a non-ASD developmental disorder, and 849 population controls from the Study to Explore Early Development. Adaptive functioning was assessed in ASD cases using the Vineland Adaptive Behavior Scales (VABS); cognitive functioning was assessed in all groups using the Mullen Scales of Early Learning (MSEL). A satellite-based model was used to assign PM2.5 exposure averages during pregnancy, each trimester, and the first year of life. Linear regression was used to estimate beta coefficients and 95% confidence intervals, adjusting for maternal age, education, prenatal tobacco use, race-ethnicity, study site, and season of birth. PM2.5 exposure was associated with poorer VABS scores for several domains, including daily living skills and socialization. Associations were present between prenatal PM2.5 and lower MSEL scores for all groups combined; results were most prominent for population controls in stratified analyses. These data suggest that early life PM2.5 exposure is associated with specific aspects of cognitive and adaptive functioning in children with and without ASD

Burned area and carbon emissions across northwestern boreal North America from 2001-2019

Fire is the dominant disturbance agent in Alaskan and Canadian boreal ecosystems and releases large amounts of carbon into the atmosphere. Burned area and carbon emissions have been increasing with climate change, which have the potential to alter the carbon balance and shift the region from a historic sink to a source. It is therefore critically important to track the spatiotemporal changes in burned area and fire carbon emissions over time. Here we developed a new burned-area detection algorithm between 2001-2019 across Alaska and Canada at 500 m (meters) resolution that utilizes finer-scale 30 m Landsat imagery to account for land cover unsuitable for burning. This method strictly balances omission and commission errors at 500 m to derive accurate landscape- and regional-scale burned-area estimates. Using this new burned-area product, we developed statistical models to predict burn depth and carbon combustion for the same period within the NASA Arctic-Boreal Vulnerability Experiment (ABoVE) core and extended domain. Statistical models were constrained using a database of field observations across the domain and were related to a variety of response variables including remotely sensed indicators of fire severity, fire weather indices, local climate, soils, and topographic indicators. The burn depth and aboveground combustion models performed best, with poorer performance for belowground combustion. We estimate 2.37×106 ha (2.37 Mha) burned annually between 2001-2019 over the ABoVE domain (2.87 Mha across all of Alaska and Canada), emitting 79.3 ± 27.96 Tg (±1 standard deviation) of carbon (C) per year, with a mean combustion rate of 3.13 ± 1.17 kg C m-2. Mean combustion and burn depth displayed a general gradient of higher severity in the northwestern portion of the domain to lower severity in the south and east. We also found larger-fire years and later-season burning were generally associated with greater mean combustion. Our estimates are generally consistent with previous efforts to quantify burned area, fire carbon emissions, and their drivers in regions within boreal North America; however, we generally estimate higher burned area and carbon emissions due to our use of Landsat imagery, greater availability of field observations, and improvements in modeling. The burned area and combustion datasets described here (the ABoVE Fire Emissions Database, or ABoVE-FED) can be used for local- to continental-scale applications of boreal fire science

Autism Spectrum Disorder Symptoms Among Children Enrolled in the Study to Explore Early Development (SEED)

This study examined the phenotypic profiles of children aged 30–68 months in the Study to Explore Early Development (SEED). Children classified as autism spectrum disorder (ASD), developmental delay (DD) with ASD symptoms, DD without ASD symptoms, and population comparison (POP) differed significantly from each other on cognitive, adaptive, behavioral, and social functioning and the presence of parent-reported conditions. Children with ASD and DD with ASD symptoms had mild to severe ASD risk on several measures compared to children with other DD and POP who had little ASD risk across measures. We conclude that children in SEED have varying degrees of ASD impairment and associated deficits. SEED thus provides a valuable sample to explore ASD phenotypes and inform risk factor analyses