Sprouting Roots at Sarah Lawrence College

As a campus that has great concern for environmental issues, it is important to find ways in which to engage both students and faculty in working towards a greener campus. The addition of a green roof or biowall to Sarah Lawrence College would be an amazing opportunity to begin building a more eco-friendly community. Green roofs alleviate environmental stressors while a biowall will increase indoor air quality and productivity. Not only do green roofs and biowalls help curb effects of pollution both indoors and out, but either would be an opportunity for continued research into the effects of green technology. With ample flat roof space across campus as well as having the LEED certified Heimbold Visual Arts Center, building a green roof and/or biowall would both guide Sarah Lawrence into a green movement while providing an opportunity for the community to work together towards a greener goal.https://digitalcommons.slc.edu/undergrad_sustainproject/1006/thumbnail.jp

Prediction of Alzheimer's disease pathophysiology based on cortical thickness patterns

AbstractIntroductionRecent studies have shown that pathologically defined subtypes of Alzheimer's disease (AD) represent distinctive atrophy patterns and clinical characteristics. We investigated whether a cortical thickness–based clustering method can reflect such findings.MethodsA total of 77 AD subjects from the Alzheimer's Disease Neuroimaging Initiative 2 data set who underwent 3-T magnetic resonance imaging, [18F]-fluorodeoxyglucose-positron emission tomography (PET), [18F]-Florbetapir PET, and cerebrospinal fluid (CSF) tests were enrolled. After clustering based on cortical thickness, diverse imaging and biofluid biomarkers were compared between these groups.ResultsThree cortical thinning patterns were noted: medial temporal (MT; 19.5%), diffuse (55.8%), and parietal dominant (P; 24.7%) atrophy subtypes. The P subtype was the youngest and represented more glucose hypometabolism in the parietal and occipital cortices and marked amyloid-beta accumulation in most brain regions. The MT subtype revealed more glucose hypometabolism in the left hippocampus and bilateral frontal cortices and less performance in memory tests. CSF test results did not differ between the groups.DiscussionCortical thickness patterns can reflect pathophysiological and clinical changes in AD

Anti-inflammatory Role of Mesenchymal Stem Cells in an Acute Lung Injury Mouse Model

Background Mesenchymal stem cells (MSCs) attenuate injury in various lung injury models through paracrine effects. We hypothesized that intratracheal transplantation of allogenic MSCs could attenuate lipopolysaccharide (LPS)-induced acute lung injury (ALI) in mice, mediated by anti-inflammatory responses. Methods Six-week-old male mice were randomized to either the control or the ALI group. ALI was induced by intratracheal LPS instillation. Four hours after LPS instillation, MSCs or phosphate-buffered saline was randomly intratracheally administered. Neutrophil count and protein concentration in bronchoalveolar lavage fluid (BALF); lung histology; levels of interleukin (IL)-1β, IL-6, tumor necrosis factor (TNF)-α, and macrophage inflammatory protein-2; and the expression of proliferation cell nuclear antigen (PCNA), caspase-3, and caspase-9 were evaluated at 48 hours after injury. Results Treatment with MSCs attenuated lung injury in ALI mice by decreasing protein level and neutrophil recruitment into the BALF and improving the histologic change. MSCs also decreased the protein levels of proinflammatory cytokines including IL-1β, IL-6, and TNF-α, but had little effect on the protein expression of PCNA, caspase-3, and caspase-9. Conclusions Intratracheal injection of bone marrow-derived allogenic MSCs attenuates LPS-induced ALI via immunomodulatory effects

A Sustainable Campus for the Future: Proposals for Sarah Lawrence College

The combined version of A Sustainable Campus for the Future: Proposals for Sarah Lawrence College comes from a joint project between the students in Economics of the Ecological Crisis and Global Change Biology in Spring 2016, taught by Nicholas Reksten and Michelle Hersh, respectively.https://digitalcommons.slc.edu/undergrad_sustainproject/1009/thumbnail.jp

Diagnosis and Treatment of Latent Tuberculosis Infection in Arthritis Patients Treated with Tumor Necrosis Factor Antagonists in Korea

Tumor necrosis factor (TNF) is essential for host defense against Mycobacterium tuberculosis, and the risk of reactivation of latent tuberculosis infection (LTBI) increases with anti-TNF therapy. This study estimated the prevalence of LTBI and evaluated the safety and completion rate of short-course therapy with isoniazid plus rifampin for 3 months to treat LTBI in a cohort of Korean arthritis patients before initiating anti-TNF therapy. We retrospectively studied the files of 112 consecutive patients to evaluate LTBI before starting anti-TNF drugs. Screening tests were performed, including a tuberculin skin test and chest radiography. LTBI treatment was indicated in 41 patients (37%). Of these, three patients refused the LTBI treatment. Of the 38 patients who underwent LTBI treatment, 36 (95%) took isoniazid plus rifampin for 3 months. Six patients (16%) showed transient elevations of liver enzymes during the LTBI treatment. Overall, 35 patients (92%) completed the LTBI treatment as planned. In conclusion, LTBI was diagnosed in one-third of Korean arthritis patients before initiating anti-TNF therapy. A high percentage of these patients completed 3 months of LTBI treatment with isoniazid plus rifampin without serious complications

Measurement of the Bottom-Strange Meson Mixing Phase in the Full CDF Data Set

We report a measurement of the bottom-strange meson mixing phase \beta_s using the time evolution of B0_s -> J/\psi (->\mu+\mu-) \phi (-> K+ K-) decays in which the quark-flavor content of the bottom-strange meson is identified at production. This measurement uses the full data set of proton-antiproton collisions at sqrt(s)= 1.96 TeV collected by the Collider Detector experiment at the Fermilab Tevatron, corresponding to 9.6 fb-1 of integrated luminosity. We report confidence regions in the two-dimensional space of \beta_s and the B0_s decay-width difference \Delta\Gamma_s, and measure \beta_s in [-\pi/2, -1.51] U [-0.06, 0.30] U [1.26, \pi/2] at the 68% confidence level, in agreement with the standard model expectation. Assuming the standard model value of \beta_s, we also determine \Delta\Gamma_s = 0.068 +- 0.026 (stat) +- 0.009 (syst) ps-1 and the mean B0_s lifetime, \tau_s = 1.528 +- 0.019 (stat) +- 0.009 (syst) ps, which are consistent and competitive with determinations by other experiments.Comment: 8 pages, 2 figures, Phys. Rev. Lett 109, 171802 (2012

Association analyses of East Asian individuals and trans-ancestry analyses with European individuals reveal new loci associated with cholesterol and triglyceride levels

Large-scale meta-analyses of genome-wide association studies (GWAS) have identified >175 loci associated with fasting cholesterol levels, including total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglycerides (TG). With differences in linkage disequilibrium (LD) structure and allele frequencies between ancestry groups, studies in additional large samples may detect new associations. We conducted staged GWAS meta-analyses in up to 69,414 East Asian individuals from 24 studies with participants from Japan, the Philippines, Korea, China, Singapore, and Taiwan. These meta-analyses identified (P < 5 × 10-8) three novel loci associated with HDL-C near CD163-APOBEC1 (P = 7.4 × 10-9), NCOA2 (P = 1.6 × 10-8), and NID2-PTGDR (P = 4.2 × 10-8), and one novel locus associated with TG near WDR11-FGFR2 (P = 2.7 × 10-10). Conditional analyses identified a second signal near CD163-APOBEC1. We then combined results from the East Asian meta-analysis with association results from up to 187,365 European individuals from the Global Lipids Genetics Consortium in a trans-ancestry meta-analysis. This analysis identified (log10Bayes Factor ≥6.1) eight additional novel lipid loci. Among the twelve total loci identified, the index variants at eight loci have demonstrated at least nominal significance with other metabolic traits in prior studies, and two loci exhibited coincident eQTLs (P < 1 × 10-5) in subcutaneous adipose tissue for BPTF and PDGFC. Taken together, these analyses identified multiple novel lipid loci, providing new potential therapeutic targets

Genetic Drivers of Heterogeneity in Type 2 Diabetes Pathophysiology

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P \u3c 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care

Genetic drivers of heterogeneity in type 2 diabetes pathophysiology

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P &lt; 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care.</p

Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

Publisher Copyright: © 2022, The Author(s).Background: Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. Results: To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3–5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. Conclusions: Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk.Peer reviewe