627 research outputs found
Virtual Screening as a Technique for PPAR Modulator Discovery
Virtual screening (VS) is a discovery technique to identify novel compounds with therapeutic and preventive efficacy against disease. Our current focus is on the in silico screening and discovery of novel peroxisome proliferator-activated receptor-gamma (PPARγ) agonists. It is well recognized that PPARγ
agonists have therapeutic applications as insulin sensitizers in type 2 diabetes or as anti-inflammatories. VS is a cost- and time-effective means for identifying small molecules that have therapeutic potential. Our long-term goal is to devise computational approaches for testing the PPARγ-binding activity of extensive naturally occurring compound libraries prior to testing agonist activity using ligand-binding and reporter assays. This review summarizes the high potential for obtaining further fundamental understanding of PPARγ
biology and development of novel therapies for treating chronic inflammatory diseases through evolution and implementation of computational screening processes for immunotherapeutics in conjunction with experimental methods for calibration and validation of results
Prediction of Disease and Phenotype Associations from Genome-Wide Association Studies
Genome wide association studies (GWAS) have proven useful as a method for identifying genetic variations associated with diseases. In this study, we analyzed GWAS data for 61 diseases and phenotypes to elucidate common associations based on single nucleotide polymorphisms (SNP). The study was an expansion on a previous study on identifying disease associations via data from a single GWAS on seven diseases.Adjustments to the originally reported study included expansion of the SNP dataset using Linkage Disequilibrium (LD) and refinement of the four levels of analysis to encompass SNP, SNP block, gene, and pathway level comparisons. A pair-wise comparison between diseases and phenotypes was performed at each level and the Jaccard similarity index was used to measure the degree of association between two diseases/phenotypes. Disease relatedness networks (DRNs) were used to visualize our results. We saw predominant relatedness between Multiple Sclerosis, type 1 diabetes, and rheumatoid arthritis for the first three levels of analysis. Expected relatedness was also seen between lipid- and blood-related traits.The predominant associations between Multiple Sclerosis, type 1 diabetes, and rheumatoid arthritis can be validated by clinical studies. The diseases have been proposed to share a systemic inflammation phenotype that can result in progression of additional diseases in patients with one of these three diseases. We also noticed unexpected relationships between metabolic and neurological diseases at the pathway comparison level. The less significant relationships found between diseases require a more detailed literature review to determine validity of the predictions. The results from this study serve as a first step towards a better understanding of seemingly unrelated diseases and phenotypes with similar symptoms or modes of treatment
Assessing alternate sparger configurations to mitigate supply chain risks in single-use bioreactors
Consumable shortages throughout the pandemic introduced unanticipated challenges for continued manufacture of commercial biologics. With single-use systems, the bioreactors themselves are consumables that were impacted by these supply chain shortages. To ensure patient supply of necessary biologics, risk mitigation planning and determining suitable alternatives was required. In this presentation, we detail work performed to allow for continued manufacturing, while facing stock-out risks for single-use bioreactor bags used at both the seed and production stages. Specifically, this work focused on alternate sparger configurations, as the standard configuration used in the production bioreactor stage was unavailable. Additional options for added flexibility at the seed bioreactor stages were evaluated to address stock-out risks, and are discussed.
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An Integrated Framework to Assess Greenwashing
In this paper we examine definitions of ‘greenwashing’ and its different forms, developing a tool for assessing diverse ‘green’ claims made by various actors. Research shows that significant deception and misleading claims exist both in the regulated commercial sphere, as well as in the unregulated non-commercial sphere (e.g., governments, NGO partnerships, international pledges, etc.). Recently, serious concerns have been raised over rampant greenwashing, in particular with regard to rapidly emerging net zero commitments. The proposed framework we developed is the first actionable tool for analysing the quality and truthfulness of such claims. The framework has widespread and unique potential for highlighting efforts that seek to delay or distract real solutions that are urgently needed today to tackle multiple climate and environmental crises. In addition, we note how the framework may also assist in the development of practices and communication strategies that ultimately avoid greenwashing
An Integrated Framework to Assess Greenwashing
Funding: This research was funded by the Department of Political Science at University of Vienna, Austria and the Institute at Brown for Environment and Society, USA, in association with Climate Social Science Network.Peer reviewedPublisher PD
Biogeochemistry of upland to wetland soils, sediments, and surface waters across Mid-Atlantic and Great Lakes coastal interfaces
Transferable and mechanistic understanding of cross-scale interactions is necessary to predict how coastal systems respond to global change. Cohesive datasets across geographically distributed sites can be used to examine how transferable a mechanistic understanding of coastal ecosystem control points is. To address the above research objectives, data were collected by the EXploration of Coastal Hydrobiogeochemistry Across a Network of Gradients and Experiments (EXCHANGE) Consortium – a regionally distributed network of researchers that collaborated on experimental design, methodology, collection, analysis, and publication. The EXCHANGE Consortium collected samples from 52 coastal terrestrial-aquatic interfaces (TAIs) during Fall of 2021. At each TAI, samples collected include soils from across a transverse elevation gradient (i.e., coastal upland forest, transitional forest, and wetland soils), surface waters, and nearshore sediments across research sites in the Great Lakes and Mid-Atlantic regions (Chesapeake and Delaware Bays) of the continental USA. The first campaign measures surface water quality parameters, bulk geochemical parameters on water, soil, and sediment samples, and physicochemical parameters of sediment and soil
Loss-of-function mutations in Lysyl-tRNA synthetase cause various leukoencephalopathy phenotypes
Objective: To expand the clinical spectrum of lysyl-tRNA synthetase (KARS) gene–related diseases, which so far includes Charcot-Marie-Tooth disease, congenital visual impairment and microcephaly, and nonsyndromic hearing impairment.
Methods: Whole-exome sequencing was performed on index patients from 4 unrelated families with leukoencephalopathy. Candidate pathogenic variants and their cosegregation were confirmed by Sanger sequencing. Effects of mutations on KARS protein function were examined by aminoacylation assays and yeast complementation assays.
Results: Common clinical features of the patients in this study included impaired cognitive ability, seizure, hypotonia, ataxia, and abnormal brain imaging, suggesting that the CNS involvement is the main clinical presentation. Six previously unreported and 1 known KARS mutations were identified and cosegregated in these families. Two patients are compound heterozygous for missense mutations, 1 patient is homozygous for a missense mutation, and 1 patient harbored an insertion mutation and a missense mutation. Functional and structural analyses revealed that these mutations impair aminoacylation activity of lysyl-tRNA synthetase, indicating that de- fective KARS function is responsible for the phenotypes in these individuals.
Conclusions: Our results demonstrate that patients with loss-of-function KARS mutations can manifest CNS disorders, thus broadening the phenotypic spectrum associated with KARS-related disease
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Molecular testing for the clinical diagnosis of fibrolamellar carcinoma.
Fibrolamellar carcinoma has a distinctive morphology and immunophenotype, including cytokeratin 7 and CD68 co-expression. Despite the distinct findings, accurate diagnosis of fibrolamellar carcinoma continues to be a challenge. Recently, fibrolamellar carcinomas were found to harbor a characteristic somatic gene fusion, DNAJB1-PRKACA. A break-apart fluorescence in situ hybridization (FISH) assay was designed to detect this fusion event and to examine its diagnostic performance in a large, multicenter, multinational study. Cases initially classified as fibrolamellar carcinoma based on histological features were reviewed from 124 patients. Upon central review, 104 of the 124 cases were classified histologically as typical of fibrolamellar carcinoma, 12 cases as 'possible fibrolamellar carcinoma' and 8 cases as 'unlikely to be fibrolamellar carcinoma'. PRKACA FISH was positive for rearrangement in 102 of 103 (99%) typical fibrolamellar carcinomas, 9 of 12 'possible fibrolamellar carcinomas' and 0 of 8 cases 'unlikely to be fibrolamellar carcinomas'. Within the morphologically typical group of fibrolamellar carcinomas, two tumors with unusual FISH patterns were also identified. Both cases had the fusion gene DNAJB1-PRKACA, but one also had amplification of the fusion gene and one had heterozygous deletion of the normal PRKACA locus. In addition, 88 conventional hepatocellular carcinomas were evaluated with PRKACA FISH and all were negative. These findings demonstrate that FISH for the PRKACA rearrangement is a clinically useful tool to confirm the diagnosis of fibrolamellar carcinoma, with high sensitivity and specificity. A diagnosis of fibrolamellar carcinoma is more accurate when based on morphology plus confirmatory testing than when based on morphology alone
Peat swamp forest conservation withstands pervasive land conversion to oil palm plantation in North Selangor, Malaysia
Tropical deforestation remains one of the major global challenges of the twenty-first century driven to a large extent by the conversion of land for agricultural purposes, such as palm oil production. Malaysia is one of the world’s largest palm oil producers and has seen widespread conversion to oil palm from primary forest, including peat swamp forest (PSF). This study investigates the rate and extent of pervasive oil palm expansion in and around North Selangor Peat Swamp Forest (NSPSF) over the last three decades, exploring how land conversion has affected the region’s tropical forests, and assessing the relative success of PSF conservation measures. Time-series Landsat imagery was used to assess thematic land cover change and improvement in vegetation condition since NSPSF was given protected status in 1990. The results show a near tripling in oil palm cover throughout North Selangor, from 24,930 ha in 1989 to 70,070 ha in 2016; while at the same time tropical forest cover shrank from 145,570 ha to 88,400 ha. Despite concerns over the sustainability and environmental impact of such rapid oil palm conversion at a regional level, at the local scale, NSPSF represents a relative conservation success story. Effective land stewardship by government and non-governmental organization (NGO) management actors has limited illegal encroachment of oil palm around the reserve boundary. PSF rehabilitation measures have also markedly improved vegetation condition in NSPFS’s interior. These findings have broad significance for how oil palm agriculture is managed and especially for PSF stewardship and conservation, and the approaches described here may be usefully adopted elsewhere in Southeast Asia and around the world
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