35 research outputs found

    Gene expression signatures affected by alcohol-induced DNA methylomic deregulation in human embryonic stem cells

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    AbstractStem cells, especially human embryonic stem cells (hESCs), are useful models to study molecular mechanisms of human disorders that originate during gestation. Alcohol (ethanol, EtOH) consumption during pregnancy causes a variety of prenatal and postnatal disorders collectively referred to as fetal alcohol spectrum disorders (FASDs). To better understand the molecular events leading to FASDs, we performed a genome-wide analysis of EtOH's effects on the maintenance and differentiation of hESCs in culture. Gene Co-expression Network Analysis showed significant alterations in gene profiles of EtOH-treated differentiated or undifferentiated hESCs, particularly those associated with molecular pathways for metabolic processes, oxidative stress, and neuronal properties of stem cells. A genome-wide DNA methylome analysis revealed widespread EtOH-induced alterations with significant hypermethylation of many regions of chromosomes. Undifferentiated hESCs were more vulnerable to EtOH's effect than their differentiated counterparts, with methylation on the promoter regions of chromosomes 2, 16 and 18 in undifferentiated hESCs most affected by EtOH exposure. Combined transcriptomic and DNA methylomic analysis produced a list of differentiation-related genes dysregulated by EtOH-induced DNA methylation changes, which likely play a role in EtOH-induced decreases in hESC pluripotency. DNA sequence motif analysis of genes epigenetically altered by EtOH identified major motifs representing potential binding sites for transcription factors. These findings should help in deciphering the precise mechanisms of alcohol-induced teratogenesis

    Novel App knock-in mouse model shows key features of amyloid pathology and reveals profound metabolic dysregulation of microglia.

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    BACKGROUND: Genetic mutations underlying familial Alzheimer\u27s disease (AD) were identified decades ago, but the field is still in search of transformative therapies for patients. While mouse models based on overexpression of mutated transgenes have yielded key insights in mechanisms of disease, those models are subject to artifacts, including random genetic integration of the transgene, ectopic expression and non-physiological protein levels. The genetic engineering of novel mouse models using knock-in approaches addresses some of those limitations. With mounting evidence of the role played by microglia in AD, high-dimensional approaches to phenotype microglia in those models are critical to refine our understanding of the immune response in the brain. METHODS: We engineered a novel App knock-in mouse model (App RESULTS: Leveraging multi-omics approaches, we discovered profound alteration of diverse lipids and metabolites as well as an exacerbated disease-associated transcriptomic response in microglia with high intracellular AÎČ content. The App DISCUSSION: Our findings demonstrate that fibrillar AÎČ in microglia is associated with lipid dyshomeostasis consistent with lysosomal dysfunction and foam cell phenotypes as well as profound immuno-metabolic perturbations, opening new avenues to further investigate metabolic pathways at play in microglia responding to AD-relevant pathogenesis. The in-depth characterization of pathological hallmarks of AD in this novel and open-access mouse model should serve as a resource for the scientific community to investigate disease-relevant biology

    The global abundance of tree palms

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    Aim Palms are an iconic, diverse and often abundant component of tropical ecosystems that provide many ecosystem services. Being monocots, tree palms are evolutionarily, morphologically and physiologically distinct from other trees, and these differences have important consequences for ecosystem services (e.g., carbon sequestration and storage) and in terms of responses to climate change. We quantified global patterns of tree palm relative abundance to help improve understanding of tropical forests and reduce uncertainty about these ecosystems under climate change. Location Tropical and subtropical moist forests. Time period Current. Major taxa studied Palms (Arecaceae). Methods We assembled a pantropical dataset of 2,548 forest plots (covering 1,191 ha) and quantified tree palm (i.e., ≄10 cm diameter at breast height) abundance relative to co‐occurring non‐palm trees. We compared the relative abundance of tree palms across biogeographical realms and tested for associations with palaeoclimate stability, current climate, edaphic conditions and metrics of forest structure. Results On average, the relative abundance of tree palms was more than five times larger between Neotropical locations and other biogeographical realms. Tree palms were absent in most locations outside the Neotropics but present in >80% of Neotropical locations. The relative abundance of tree palms was more strongly associated with local conditions (e.g., higher mean annual precipitation, lower soil fertility, shallower water table and lower plot mean wood density) than metrics of long‐term climate stability. Life‐form diversity also influenced the patterns; palm assemblages outside the Neotropics comprise many non‐tree (e.g., climbing) palms. Finally, we show that tree palms can influence estimates of above‐ground biomass, but the magnitude and direction of the effect require additional work. Conclusions Tree palms are not only quintessentially tropical, but they are also overwhelmingly Neotropical. Future work to understand the contributions of tree palms to biomass estimates and carbon cycling will be particularly crucial in Neotropical forests

    Analysis of productivity performance of real estate and construction firms in Indonesia

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    Sustained total factor productivity (TFP) growth of firms is essential to achieve sustained supply growth, which is necessary to solve the housing shortage and affordability problems. Existing productivity literature focuses on large firms whilst smaller firms make a significant contribution to the total supply. This paper investigates the productivity of 363 Indonesian real estate construction firms of medium and large sizes. We estimate FĂ€re-Primont TFP measures under the meta-frontier framework, accounting for differences in the overall technologies under which each group of firms operates. Results deliver several important findings. First, large firms have higher productivity levels than medium firms, but average productivity levels are very low. Second, the productivity growth of large and medium firms is negative, which contributes to the growth of the housing shortage in Indonesia from 2012 to 2016. Third, in case of easier transfer or spill-over of production technologies between two firm groups, firms could enhance further their efficiency and productivity. Fourth, those factors related to branch numbers, legal structure and experience of doing business have positive correlations with the productivity performance of firms in both large and medium groups. Additionally, medium firms could gain higher productivity by diversifying their income. Importantly, our study shows evidence to support that government subsidies have a positive influence on the productivity level of medium firms.</p

    Meta-frontier efficiency analysis of real estate and construction firms in Indonesia

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    Improving the productive efficiency (also called technical efficiency) of real estate and construction firms (RECFs) is essential to tackle the sustained shortage of housing supply and the increasing unaffordability of housing in developing countries. However, there are few studies that focus on this issue in the context of developing countries; and available literature focuses mainly on firms listed on stock markets. Our study employs the meta-frontier framework to measure the efficiency of 832 small, medium, and large RECFs across Indonesia from 2012 to 2016, using a data envelopment analysis technique. The meta-frontier framework allows for different production technologies and different business environments operated by firms of different sizes. Under the specification of group-specific production frontiers, large firms obtain the highest average efficiency scores (0.694), followed by medium firms (0.529), and small firms (0.479). The technology gaps between the meta-frontier and the group-frontiers for small and medium firms are relatively large, suggesting that the overall industry would be able to achieve remarkable efficiency improvement if firms could access technologies used by more efficient firms. Our results also show that determinants of the efficiency vary across firm groups, suggesting that policy and managerial interventions tailored to each group would have more impact on the overall productive efficiency of the entire industry

    Assessing clinical quality performance and staffing capacity differences between urban and rural Health Resources and Services Administration-funded health centers in the United States: A cross sectional study.

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    BackgroundIn the United States, there are nearly 1,400 Health Resources and Services Administration-funded health centers (HCs) serving low-income and underserved populations and more than 600 of these HCs are located in rural areas. Disparities in quality of medical care in urban vs. rural areas exist but data on such differences between urban and rural HCs is limited in the literature. We examined whether urban and rural HCs differed in their performance on clinical quality measures before and after controlling for patient, organizational, and contextual characteristics.Methods and findingsWe used the 2017 Uniform Data System to examine performance on clinical quality measures between urban and rural HCs (n = 1,373). We used generalized linear regression models with the logit link function and binomial distribution, controlling for confounding factors. After adjusting for potential confounders, we found on par performance between urban and rural HCs in all but one clinical quality measure. Rural HCs had lower rates of linking patients newly diagnosed with HIV to care (74% [95% CI: 69%, 80%] vs. 83% [95% CI: 80%, 86%]). We identified control variables that systematically accounted for eliminating urban vs. rural differences in performance on clinical quality measures. We also found that both urban and rural HCs had some clinical quality performance measures that were lower than available national benchmarks. Main limitations included potential discrepancy of urban or rural designation across all HC sites within a HC organization.ConclusionsFindings highlight HCs' contributions in addressing rural disparities in quality of care and identify opportunities for improvement. Performance in both rural and urban HCs may be improved by supporting programs that increase the availability of providers, training, and provision of technical resources

    Assessing clinical quality performance and staffing capacity differences between urban and rural Health Resources and Services Administration-funded health centers in the United States: A cross sectional study.

    No full text
    BackgroundIn the United States, there are nearly 1,400 Health Resources and Services Administration-funded health centers (HCs) serving low-income and underserved populations and more than 600 of these HCs are located in rural areas. Disparities in quality of medical care in urban vs. rural areas exist but data on such differences between urban and rural HCs is limited in the literature. We examined whether urban and rural HCs differed in their performance on clinical quality measures before and after controlling for patient, organizational, and contextual characteristics.Methods and findingsWe used the 2017 Uniform Data System to examine performance on clinical quality measures between urban and rural HCs (n = 1,373). We used generalized linear regression models with the logit link function and binomial distribution, controlling for confounding factors. After adjusting for potential confounders, we found on par performance between urban and rural HCs in all but one clinical quality measure. Rural HCs had lower rates of linking patients newly diagnosed with HIV to care (74% [95% CI: 69%, 80%] vs. 83% [95% CI: 80%, 86%]). We identified control variables that systematically accounted for eliminating urban vs. rural differences in performance on clinical quality measures. We also found that both urban and rural HCs had some clinical quality performance measures that were lower than available national benchmarks. Main limitations included potential discrepancy of urban or rural designation across all HC sites within a HC organization.ConclusionsFindings highlight HCs' contributions in addressing rural disparities in quality of care and identify opportunities for improvement. Performance in both rural and urban HCs may be improved by supporting programs that increase the availability of providers, training, and provision of technical resources
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