Oxygen Limitation and Tissue Metabolic Potential of the African Fish Barbus neumayeri: Roles of Native Habitat and Acclimatization

Background: Oxygen availability in aquatic habitats is a major environmental factor influencing the ecology, behaviour, and physiology of fishes. This study evaluates the contribution of source population and hypoxic acclimatization of the African fish, Barbus neumayeri, in determining growth and tissue metabolic enzyme activities. Individuals were collected from two sites differing dramatically in concentration of dissolved oxygen (DO), Rwembaita Swamp (annual average DO 1.35 mgO2 L-1) and Inlet Stream West (annual average DO 5.58 mgO2 L-1) in Kibale National Park, Uganda, and reciprocally transplanted using a cage experiment in the field, allowing us to maintain individuals under natural conditions of oxygen, food availability, and flow. Fish were maintained under these conditions for four weeks and sampled for growth rate and the activities of phosphofructokinase (PFK), lactate dehydrogenase (LDH), citrate synthase (CS), and cytochrome c oxidase (CCO) in four tissues, liver, heart, brain, and skeletal muscle. Results: Acclimatization to the low DO site resulted in lower growth rates, lower activities of the aerobic enzyme CCO in heart, and higher activities of the glycolytic enzyme PFK in heart and skeletal muscle. The activity of LDH in liver tissue was correlated with site of origin, being higher in fish collected from a hypoxic habitat, regardless of acclimatization treatment. Conclusions: Our results suggest that the influence of site of origin and hypoxic acclimatization in determining enzyme activity differs among enzymes and tissues, but both factors contribute to higher glycolytic capacity and lower aerobic capacity in B. neumayeri under naturally-occurring conditions of oxygen limitation

Rmi1 stimulates decatenation of double Holliday junctions during dissolution by Sgs1-Top3

double Holliday junction (dHJ) is a central intermediate of homologous recombination that can be processed to yield crossover or non-crossover recombination products. To preserve genomic integrity, cells possess mechanisms to avoid crossing over. We show that Saccharomyces cerevisiae Sgs1 and Top3 proteins are sufficient to migrate and disentangle a dHJ to produce exclusively non-crossover recombination products, in a reaction termed "dissolution." We show that Rmi1 stimulates dHJ dissolution at low Sgs1-Top3 protein concentrations, although it has no effect on the initial rate of Holliday junction (HJ) migration. Rmi1 serves to stimulate DNA decatenation, removing the last linkages between the repaired and template DNA molecules. Dissolution of a dHJ is a highly efficient and concerted alternative to nucleolytic resolution that prevents crossing over of chromosomes during recombinational DNA repair in mitotic cells and thereby contributes to genomic integrity

Google Flu Trends Spatial Variability Validated Against Emergency Department Influenza-Related Visits.

BACKGROUND: Influenza is a deadly and costly public health problem. Variations in its seasonal patterns cause dangerous surges in emergency department (ED) patient volume. Google Flu Trends (GFT) can provide faster influenza surveillance information than traditional CDC methods, potentially leading to improved public health preparedness. GFT has been found to correlate well with reported influenza and to improve influenza prediction models. However, previous validation studies have focused on isolated clinical locations. OBJECTIVE: The purpose of the study was to measure GFT surveillance effectiveness by correlating GFT with influenza-related ED visits in 19 US cities across seven influenza seasons, and to explore which city characteristics lead to better or worse GFT effectiveness. METHODS: Using Healthcare Cost and Utilization Project data, we collected weekly counts of ED visits for all patients with diagnosis (International Statistical Classification of Diseases 9) codes for influenza-related visits from 2005-2011 in 19 different US cities. We measured the correlation between weekly volume of GFT searches and influenza-related ED visits (ie, GFT ED surveillance effectiveness) per city. We evaluated the relationship between 15 publically available city indicators (11 sociodemographic, two health care utilization, and two climate) and GFT surveillance effectiveness using univariate linear regression. RESULTS: Correlation between city-level GFT and influenza-related ED visits had a median of .84, ranging from .67 to .93 across 19 cities. Temporal variability was observed, with median correlation ranging from .78 in 2009 to .94 in 2005. City indicators significantly associated (P CONCLUSIONS: GFT is strongly correlated with ED influenza-related visits at the city level, but unexplained variation over geographic location and time limits its utility as standalone surveillance. GFT is likely most useful as an early signal used in conjunction with other more comprehensive surveillance techniques. City indicators associated with improved GFT surveillance provide some insight into the variability of GFT effectiveness. For example, populations with lower socioeconomic status may have a greater tendency to initially turn to the Internet for health questions, thus leading to increased GFT effectiveness. GFT has the potential to provide valuable information to ED providers for patient care and to administrators for ED surge preparedness

Google Flu Trends Spatial Variability Validated Against Emergency Department Influenza-Related Visits

Background: Influenza is a deadly and costly public health problem. Variations in its seasonal patterns cause dangerous surges in emergency department (ED) patient volume. Google Flu Trends (GFT) can provide faster influenza surveillance information than traditional CDC methods, potentially leading to improved public health preparedness. GFT has been found to correlate well with reported influenza and to improve influenza prediction models. However, previous validation studies have focused on isolated clinical locations. Objective: The purpose of the study was to measure GFT surveillance effectiveness by correlating GFT with influenza-related ED visits in 19 US cities across seven influenza seasons, and to explore which city characteristics lead to better or worse GFT effectiveness. Methods: Using Healthcare Cost and Utilization Project data, we collected weekly counts of ED visits for all patients with diagnosis (International Statistical Classification of Diseases 9) codes for influenza-related visits from 2005-2011 in 19 different US cities. We measured the correlation between weekly volume of GFT searches and influenza-related ED visits (ie, GFT ED surveillance effectiveness) per city. We evaluated the relationship between 15 publically available city indicators (11 sociodemographic, two health care utilization, and two climate) and GFT surveillance effectiveness using univariate linear regression. Results: Correlation between city-level GFT and influenza-related ED visits had a median of .84, ranging from .67 to .93 across 19 cities. Temporal variability was observed, with median correlation ranging from .78 in 2009 to .94 in 2005. City indicators significantly associated (P Conclusions: GFT is strongly correlated with ED influenza-related visits at the city level, but unexplained variation over geographic location and time limits its utility as standalone surveillance. GFT is likely most useful as an early signal used in conjunction with other more comprehensive surveillance techniques. City indicators associated with improved GFT surveillance provide some insight into the variability of GFT effectiveness. For example, populations with lower socioeconomic status may have a greater tendency to initially turn to the Internet for health questions, thus leading to increased GFT effectiveness. GFT has the potential to provide valuable information to ED providers for patient care and to administrators for ED surge preparedness

Advanced Telecommunications and Signal Processing Program

Contains an introduction, and reports on seven research projects.Advanced Telecommunications Research ProgramAT&T FellowshipINTEL FellowshipU.S. Navy - Office of Naval Research NDSEG Graduate FellowshipMaryland Procurement Office Contract MDA904-93-C-418

Advanced Telecommunications and Signal Processing Program

Contains an introduction and reports on seven research projects.Advanced Telecommunications Research ProgramAT&T FellowshipGEM FellowshipU.S. Federal Bureau of InvestigationLucent Technologies FellowshipCharles S. Draper LaboratoryU.S. Navy - Office of Naval Research NDSEG Graduate Fellowshi

The serum proteome of Atlantic salmon, Salmo salar, during pancreas disease (PD) following infection with salmonid alphavirus subtype 3 (SAV3)

Salmonid alphavirus is the aetological agent of pancreas disease (PD) in marine Atlantic salmon, Salmo salar, and rainbow trout, Oncorhynchus mykiss, with most outbreaks in Norway caused by SAV subtype 3 (SAV3). This atypical alphavirus is transmitted horizontally causing a significant economic impact on the aquaculture industry. This histopathological and proteomic study, using an established cohabitational experimental model, investigated the correlation between tissue damage during PD and a number of serum proteins associated with these pathologies in Atlantic salmon. The proteins were identified by two-dimensional electrophoresis, trypsin digest and peptide MS/MS fingerprinting. A number of humoral components of immunity which may act as biomarkers of the disease were also identified. For example, creatine kinase, enolase and malate dehydrogenase serum concentrations were shown to correlate with pathology during PD. In contrast, hemopexin, transferrin, and apolipoprotein, amongst others, altered during later stages of the disease and did not correlate with tissue pathologies. This approach has given new insight into not only PD but also fish disease as a whole, by characterisation of the protein response to infection, through pathological processes to tissue recovery. Biological significance: Salmonid alphavirus causes pancreas disease (PD) in Atlantic salmon, Salmo salar, and has a major economic impact on the aquaculture industry. A proteomic investigation of the change to the serum proteome during PD has been made with an established experimental model of the disease. Serum proteins were identified by two-dimensional electrophoresis, trypsin digest and peptide MS/MS fingerprinting with 72 protein spots being shown to alter significantly over the 12 week period of the infection. The concentrations of certain proteins in serum such as creatine kinase, enolase and malate dehydrogenase were shown to correlate with tissue pathology while other proteins such as hemopexin, transferrin, and apolipoprotein, altered in concentration during later stages of the disease and did not correlate with tissue pathologies. The protein response to infection may be used to monitor disease progression and enhance understanding of the pathology of PD

Impact of Race/Ethnicity and Socioeconomic Status on Risk-Adjusted Readmission Rates: Implications for the Hospital Readmissions Reduction Program

Under the Hospital Readmissions Reduction Program (HRRP) of the Centers for Medicare & Medicaid Services (CMS), hospitals with excess readmissions for select conditions and procedures are penalized. However, readmission rates are not risk adjusted for socioeconomic status (SES) or race/ethnicity. We examined how adding SES and race/ethnicity to the CMS risk-adjustment algorithm would affect hospitals’ excess readmission ratios and potential penalties under the HRRP. For each HRRP measure, we compared excess readmission ratios with and without SES and race/ethnicity included in the CMS standard risk-adjustment algorithm and estimated the resulting effects on overall penalties across a number of hospital characteristics. For the 5 HRRP measures (heart failure, acute myocardial infarction, chronic obstructive pulmonary disease, pneumonia, and total hip or knee arthroplasty), we used data from the Healthcare Cost and Utilization Project’s State Inpatient Databases for 2011-2012 to calculate the excess readmission ratio with and without SES and race/ethnicity included in the model. With these ratios, we estimated the impact on HRRP penalties and found that risk adjusting for SES and race/ethnicity would affect Medicare payments for 83.8% of hospitals. The effect on the size of HRRP penalties ranged from −14.4% to 25.6%, but the impact on overall Medicare base payments was small—ranging from −0.09% to 0.06%. Including SES and race/ethnicity in the calculation had a disproportionately favorable effect on safety-net and rural hospitals. Any financial effects on hospitals and on the Medicare program of adding SES and race/ethnicity to the HRRP risk-adjustment calculation likely would be small