New Hybrid Protected Lands Layer for Vermont Conservation Design Analysis (February 2019)

This shapefile (.shp) is a hybrid of the March 2017 Edition of the Vermont Center for Geographic Information\u27s (VCGI) Vermont Protected Lands Database (VPLD), the Vermont Land Trust\u27s February 2019 Protected Lands database, and The Nature Conservancy\u27s Secured Areas (SA 2018+) database. The VLT and SA 2018+ datasets were used as the scaffolding for the hybrid protected lands layer, with some VCGI VPLD polygons retained if they contained unique contributions. These datasets were combined by C.D. Loeb because each input dataset was missing some protected lands polygons in the state of Vermont. Additionally, the VCGI VPLD dataset contained many overlapping polygons, making it unusable for the area calculations of interest to our study on the overlap between formally protected lands and Vermont Conservation Design landscape-level targets (see publication reference). This hybrid protected lands layer creates a more complete snapshot of Vermont’s protected lands for our study’s purposes than any other known, publicly available dataset as of February 2019, and also corrects for all improperly overlapping polygons. However, we know that this hybrid product still does not capture all of Vermont\u27s protected lands. Specifically, some Upper Valley Land Trust-protected parcels are missing from this hybrid protected lands layer, and there are probably other protected parcels that could not be captured by the input datasets. Thus, our hybrid product will likely underrepresent actual protections. This layer was created to intersect with Vermont Conservation Design targets for input into the software Tableau. Its purpose was to perform cross tabulations to compare Vermont Conservation Design targets with protected lands in Vermont to-date, and to calculate acreages of protected lands that are also design targets by primary protecting agency. All parcel attributes and delineations in the hybrid output are only as good as the parent datasets. In areas where parcels were digitized differently between parent datasets, “slivers” may have been generated by merging them. Our study objectives originally included an analysis of the GAP Status of protected lands in Vermont (reflected in this layer\u27s metadata); however, some serious errors were detected in parent datasets with regards to GAP Status, so GAP Status was discarded as an analysis object. Please note author-identified GAP Status issues if using this dataset. Please see the shapefile\u27s metadata for detailed creation steps. The user implies knowledge of the limitations of this dataset. This dataset should not be used to ascertain boundaries or legal acreages for any parcels. Note: This version of the hybrid protected lands layer does not have county boundaries embedded in it nor waterbodies excluded from it, since it was created to capture all formally protected lands in the state of Vermont to the best of the authors’ abilities. Prior to use in our analysis, this layer was modified to exclude waterbodies and to introduce county boundaries. To obtain the same hybrid protected lands layer with county boundaries embedded in it and waterbodies excluded from it, please contact C. D. Loeb at [email protected]

Nursing Home Residents and Enterobacteriaceae Resistant to Third-Generation Cephalosporins

Limited data identify the risk factors for infection with Enterobacteriaceae resistant to third-generation cephalosporins among residents of long-term-care facilities. Using a nested case-control study design, nursing home residents with clinical isolates of Enterobacteriaceae resistant to third-generation cephalosporins were compared to residents with isolates of Enterobacteriaceae susceptible to third-generation cephalosporins. Data were collected on antimicrobial drug exposure 10 weeks before detection of the isolates, facility-level demographics, hygiene facilities, and staffing levels. Logistic regression models were built to adjust for confounding variables. Twenty-seven case-residents were identified and compared to 85 controls. Exposure to any cephalosporin (adjusted odds ratio [OR] 4.0, 95% confidence interval [CI] 1.2 to13.6) and log percentage of residents using gastrostomy tubes within the nursing home (adjusted OR 3.9, 95% CI 1.3 to 12.0) were associated with having a clinical isolate resistant to third-generation cephalosporins

Epidemiology of Doublet/Multiplet Mutations in Lung Cancers: Evidence that a Subset Arises by Chronocoordinate Events

BACKGROUND: Evidence strongly suggests that spontaneous doublet mutations in normal mouse tissues generally arise from chronocoordinate events. These chronocoordinate mutations sometimes reflect "mutation showers", which are multiple chronocoordinate mutations spanning many kilobases. However, little is known about mutagenesis of doublet and multiplet mutations (domuplets) in human cancer. Lung cancer accounts for about 25% of all cancer deaths. Herein, we analyze the epidemiology of domuplets in the EGFR and TP53 genes in lung cancer. The EGFR gene is an oncogene in which doublets are generally driver plus driver mutations, while the TP53 gene is a tumor suppressor gene with a more typical situation in which doublets derive from a driver and passenger mutation. METHODOLOGY/PRINCIPAL FINDINGS: EGFR mutations identified by sequencing were collected from 66 published papers and our updated EGFR mutation database (www.egfr.org). TP53 mutations were collected from IARC version 12 (www-p53.iarc.fr). For EGFR and TP53 doublets, no clearly significant differences in race, ethnicity, gender and smoking status were observed. Doublets in the EGFR and TP53 genes in human lung cancer are elevated about eight- and three-fold, respectively, relative to spontaneous doublets in mouse (6% and 2.3% versus 0.7%). CONCLUSIONS/SIGNIFICANCE: Although no one characteristic is definitive, the aggregate properties of doublet and multiplet mutations in lung cancer are consistent with a subset derived from chronocoordinate events in the EGFR gene: i) the eight frameshift doublets (present in 0.5% of all patients with EGFR mutations) are clustered and produce a net in-frame change; ii) about 32% of doublets are very closely spaced (< or =30 nt); and iii) multiplets contain two or more closely spaced mutations. TP53 mutations in lung cancer are very closely spaced (< or =30 nt) in 33% of doublets, and multiplets generally contain two or more very closely spaced mutations. Work in model systems is necessary to confirm the significance of chronocoordinate events in lung and other cancers

Comparing estimates of influenza-associated hospitalization and death among adults with congestive heart failure based on how influenza season is defined

<p>Abstract</p> <p>Background</p> <p>There is little consensus about how the influenza season should be defined in studies that assess influenza-attributable risk. The objective of this study was to compare estimates of influenza-associated risk in a defined clinical population using four different methods of defining the influenza season.</p> <p>Methods</p> <p>Using the Studies of Left Ventricular Dysfunction (SOLVD) clinical database and national influenza surveillance data from 1986–87 to 1990–91, four definitions were used to assess influenza-associated risk: (a) three-week moving average of positive influenza isolates is at least 5%, (b) three-week moving average of positive influenza isolates is at least 10%, (c) first and last positive influenza isolate are identified, and (d) 5% of total number of positive isolates for the season are obtained. The clinical data were from adults aged 21 to 80 with physician-diagnosed congestive heart failure. All-cause hospitalization and all-cause mortality during the influenza seasons and non-influenza seasons were compared using four definitions of the influenza season. Incidence analyses and Cox regression were used to assess the effect of exposure to influenza season on all-cause hospitalization and death using all four definitions.</p> <p>Results</p> <p>There was a higher risk of hospitalization associated with the influenza season, regardless of how the start and stop of the influenza season was defined. The adjusted risk of hospitalization was 8 to 10 percent higher during the influenza season compared to the non-influenza season when the different definitions were used. However, exposure to influenza was not consistently associated with higher risk of death when all definitions were used. When the 5% moving average and first/last positive isolate definitions were used, exposure to influenza was associated with a higher risk of death compared to non-exposure in this clinical population (adjusted hazard ratios [HR], 1.16; 95% confidence interval [CI], 1.04 to 1.29 and adjusted HR, 1.19; 95% CI, 1.06 to 1.33, respectively).</p> <p>Conclusion</p> <p>Estimates of influenza-attributable risk may vary depending on how influenza season is defined and the outcome being assessed.</p

Predictive Genes in Adjacent Normal Tissue Are Preferentially Altered by sCNV during Tumorigenesis in Liver Cancer and May Rate Limiting

Background: In hepatocellular carcinoma (HCC) genes predictive of survival have been found in both adjacent normal (AN) and tumor (TU) tissues. The relationships between these two sets of predictive genes and the general process of tumorigenesis and disease progression remains unclear. Methodology/Principal Findings: Here we have investigated HCC tumorigenesis by comparing gene expression, DNA copy number variation and survival using ~250 AN and TU samples representing, respectively, the pre-cancer state, and the result of tumorigenesis. Genes that participate in tumorigenesis were defined using a gene-gene correlation meta-analysis procedure that compared AN versus TU tissues. Genes predictive of survival in AN (AN-survival genes) were found to be enriched in the differential gene-gene correlation gene set indicating that they directly participate in the process of tumorigenesis. Additionally the AN-survival genes were mostly not predictive after tumorigenesis in TU tissue and this transition was associated with and could largely be explained by the effect of somatic DNA copy number variation (sCNV) in cis and in trans. The data was consistent with the variance of AN-survival genes being rate-limiting steps in tumorigenesis and this was confirmed using a treatment that promotes HCC tumorigenesis that selectively altered AN-survival genes and genes differentially correlated between AN and TU. Conclusions/Significance: This suggests that the process of tumor evolution involves rate-limiting steps related to the background from which the tumor evolved where these were frequently predictive of clinical outcome. Additionally treatments that alter the likelihood of tumorigenesis occurring may act by altering AN-survival genes, suggesting that the process can be manipulated. Further sCNV explains a substantial fraction of tumor specific expression and may therefore be a causal driver of tumor evolution in HCC and perhaps many solid tumor types. © 2011 Lamb et al.published_or_final_versio