Diatoms as Indicators of Water-level Change in Freshwater Lakes

Water-level changes result from a variety of geological, biological, and/or climatic processes. Many of these changes occur over long periods; others may be rapid or result from catastrophic events. In aquatic environments, diatoms are highly sensitive indicator organisms and their microfossils, deposited in lake sediments, can be used to infer environmental changes (Smol, 2008). Unambiguous diatom signals can be reconstructed from lakes isolated from marine or brackish waters (e.g. Fritz et al., this volume; Horton & Sawai, this volume). However, in freshwater systems lake-level changes are often recorded as increases in planktonic (free-floating) diatoms – although as discussed below, interpretation of this signal should be supported by additional evidence

Anomaly Inflow for Gauge Defects

Topological defects constructed out of scalar fields and possessing chiral fermion zero modes are known to exhibit an anomaly inflow mechanism which cancels the anomaly in the effective theory of the zero modes through an inflow of current from the space in which the defect is embedded. We investigate the analog of this mechanism for defects constructed out of gauge fields in higher dimensions. In particular we analyze this mechanism for string (one-brane) defects in six dimensions and for fivebranes in ten dimensions.}Comment: 23 pp (harvmac l

A family-based probabilistic method for capturing de novo mutations from high-throughput short-read sequencing data

Recent advances in high-throughput DNA sequencing technologies and associated statistical analyses have enabled in-depth analysis of whole-genome sequences. As this technology is applied to a growing number of individual human genomes, entire families are now being sequenced. Information contained within the pedigree of a sequenced family can be leveraged when inferring the donors' genotypes. The presence of a de novo mutation within the pedigree is indicated by a violation of Mendelian inheritance laws. Here, we present a method for probabilistically inferring genotypes across a pedigree using high-throughput sequencing data and producing the posterior probability of de novo mutation at each genomic site examined. This framework can be used to disentangle the effects of germline and somatic mutational processes and to simultaneously estimate the effect of sequencing error and the initial genetic variation in the population from which the founders of the pedigree arise. This approach is examined in detail through simulations and areas for method improvement are noted. By applying this method to data from members of a well-defined nuclear family with accurate pedigree information, the stage is set to make the most direct estimates of the human mutation rate to date

The Impact of State Mandated Healthcare-Associated Infection Reporting on Infection Prevention and Control Departments in Acute Care Hospitals: Results from a National Survey

Background: In addition to federally mandated reporting, most US states have adopted legislation requiring hospitals to submit healthcare-associated infection (HAI) data. Evidence that state HAI laws have increased patient safety and reduced HAI rates is inconsistent, however, and resources needed to comply are considerable. We evaluated the impact of state HAI laws on infection prevention and control departments (IPCD). Methods: Web-based survey of a national sample of hospital IPCD was conducted in Fall 2011; all non-VA hospitals enrolled in the National Healthcare Safety Network were eligible to participate. States with HAI laws effective prior to Fall 2011 were identified using systematic legal review. Variations in IPCD resources and characteristics in states with and without laws were compared using χ2or Wilcoxon-Mann-Whitney tests. Multinomial logistic regression was used to identify increases or decreases, vs no change, in resources and characteristics. Results: 1,038 IPCD provided complete data (30% response rate); 756 (73%) were located in states with laws. When asked how mandatory reporting affected their IPCD, more respondents in states with laws reported differences in resources (42% vs 33%, p \u3c 0.01), time for routine activities other than for mandatory reporting (79% vs 71%, p \u3c 0.01), influence in hospital decision making (55% vs 48%, p \u3c 0.05), and visibility of their department (75% vs 65%, p \u3c 0.001); they also spent more hours per week fulfilling mandatory reporting requirements (17 vs 13, p \u3c 0.0001). Based on regression analysis, respondents in states with laws were more likely to report increased resources (p = 0.02) and influence (p = 0.04) and decreased time for routine activities (p \u3c 0.01). Perception of visibility in the hospital was mixed with reports of both increased (p \u3c 0.001) and decreased (p = 0.01) visibility vs the same. Conclusion: Respondents in states with laws reported a significantly higher burden to their IPCD, beyond what was required by federally mandated HAI reporting alone. However, they also reported receiving increased resources to offset demands on time for routine activities and fulfilling reporting requirements. Further research is needed to investigate resources necessary to comply with state HAI laws, and to evaluate their unintended consequences

State law mandates for reporting of healthcare-associated Clostridium difficile infections in hospitals.

US state and territorial laws were reviewed to identify Clostridium difficile infection reporting mandates. Twenty states require reporting either under state law or by incorporating federal Centers for Medicare & Medicaid Services\u27 reporting requirements. Although state law mandates are more common, the incorporation of federal reporting requirements has been increasing

An improved zebrafish transcriptome annotation for sensitive and comprehensive detection of cell type-specific genes

The zebrafish is ideal for studying embryogenesis and is increasingly applied to model human disease. In these contexts, RNA-sequencing (RNA-seq) provides mechanistic insights by identifying transcriptome changes between experimental conditions. Application of RNA-seq relies on accurate transcript annotation for a genome of interest. Here, we find discrepancies in analysis from RNA-seq datasets quantified using Ensembl and RefSeq zebrafish annotations. These issues were due, in part, to variably annotated 3\u27 untranslated regions and thousands of gene models missing from each annotation. Since these discrepancies could compromise downstream analyses and biological reproducibility, we built a more comprehensive zebrafish transcriptome annotation that addresses these deficiencies. Our annotation improves detection of cell type-specific genes in both bulk and single cell RNA-seq datasets, where it also improves resolution of cell clustering. Thus, we demonstrate that our new transcriptome annotation can outperform existing annotations, providing an important resource for zebrafish researchers

Impact of Laws Aimed at Healthcare-Associated Infection Reduction: A Qualitative Study

Background: Healthcare-associated infections (HAIs) are preventable. Globally, laws aimed at reducing HAIs have been implemented. In the USA, these laws are at the federal and state levels. It is not known whether the state interventions are more effective than the federal incentives alone. Objective: The aims of this study were to explore the impact federal and state HAI laws have on state departments of health and hospital stakeholders in the USA and to explore similarities and differences in perceptions across states. Methods: A qualitative study was conducted. In 2012, we conducted semistructured interviews with key stakeholders from states with and without state-level laws to gain multiple perspectives. Interviews were transcribed and open coding was conducted. Data were analysed using content analysis and collected until theoretical saturation was achieved. Results: Ninety interviews were conducted with stakeholders from 12 states (6 states with laws and 6 states without laws). We found an increase in state-level collaboration. The publicly reported data helped hospitals benchmark and focus leaders on HAI prevention. There were concerns about the publicly reported data (eg, lack of validation and timeliness). Resource needs were also identified. No major differences were expressed by interviewees from states with and without laws. Conclusions: While we could not tease out the impact of specific interventions, increased collaboration between departments of health and their partners is occurring. Harmonisation of HAI definitions and reporting between state and federal laws would minimise reporting burden. Continued monitoring of the progress of HAI prevention is needed