Effects of the age-composition of spawning sockeye salmon on future returns of sockeye salmon to Bristol, Bay, Alaska

Thesis (M.S.) University of Alaska Fairbanks, 2011The age structure of sockeye salmon on spawning grounds is highly variable, yet little is known about the influence of spawner age composition on subsequent abundance and age composition of recruits. Management of Bristol Bay sockeye salmon relies on estimated spawner abundance to determine escapement goals, without regard to age or size composition. This may not accurately reflect reproductive potential as a basis for setting escapement goals. Parental age structure and environmental conditions were included as independent variables in statistical models to evaluate their effects on the age structure of their progeny. In addition, relationships between spawner age composition and recruit abundance were examined. I found a significant relationship between the age composition of spawners and that of their progeny, as well as environmental effects on age composition. A higher proportion of spawners that spent three years in the ocean were associated with a higher proportion of recruits with this life history pattern, suggesting direct genetic and/or environmental influences. However, redefining spawner-recruit models based on spawner age composition did not significantly improve predictions of the overall number of recruits originating in a given brood year. Nevertheless, the ability to predict the age and hence size composition of returns (with uncertainty), implies that improved predictions of the total biomass of returns in a given year is possible

Minimizing Errors in RT-PCR Detection and Quantification of SARS-CoV-2 RNA for Wastewater Surveillance

Wastewater surveillance for pathogens using the reverse transcription-polymerase chain reaction (RT-PCR) is an effective, resource-efficient tool for gathering additional community-level public health information, including the incidence and/or prevalence and trends of coronavirus disease-19 (COVID-19). Surveillance of SARS-CoV-2 in wastewater may provide an early-warning signal of COVID-19 infections in a community. The capacity of the world’s environmental microbiology and virology laboratories for SARS-CoV-2 RNA characterization in wastewater is rapidly increasing. However, there are no standardized protocols nor harmonized quality assurance and quality control (QA/QC) procedures for SARS-CoV-2 wastewater surveillance. This paper is a technical review of factors that can lead to false-positive and -negative errors in the surveillance of SARS-CoV-2, culminating in recommendations and strategies that can be implemented to identify and mitigate these errors. Recommendations include, stringent QA/QC measures, representative sampling approaches, effective virus concentration and efficient RNA extraction, amplification inhibition assessment, inclusion of sample processing controls, and considerations for RT-PCR assay selection and data interpretation. Clear data interpretation guidelines (e.g., determination of positive and negative samples) are critical, particularly during a low incidence of SARS-CoV-2 in wastewater. Corrective and confirmatory actions must be in place for inconclusive and/or potentially significant results (e.g., initial onset or reemergence of COVID-19 in a community). It will also be prudent to perform inter-laboratory comparisons to ensure results are reliable and interpretable for ongoing and retrospective analyses. The strategies that are recommended in this review aim to improve SARS-CoV-2 characterization for wastewater surveillance applications. A silver lining of the COVID-19 pandemic is that the efficacy of wastewater surveillance was demonstrated during this global crisis. In the future, wastewater will play an important role in the surveillance of a range of other communicable diseases.Highlights: Harmonized QA/QC procedures for SARS-CoV-2 wastewater surveillance are lacking; Wastewater analysis protocols are not optimized for trace analysis of viruses; False-positive and -negative errors have consequences for public health responses; Inter-laboratory studies utilizing standardized reference materials and protocols are needed.info:eu-repo/semantics/publishedVersio

Development and Validation of the NDDI-E-Y: A Screening Tool for Depressive Symptoms in Pediatric Epilepsy

Objectives: To validate the revised 12-item revised Neurological Disorders Depression Inventory-Epilepsy for Youth (NDDI-E-Y), a self-report screening tool for depressive symptoms tailored to youth ages 12–17 with epilepsy. Methods: Youth at two sites completed the NDDI-E-Y during a routine epilepsy visit. Youth at one site also completed the Children\u27s Depression Inventory-2 (CDI-2). Seizure and demographic data were abstracted from the electronic medical record. Exploratory factor analyses were conducted. Internal consistency, area under the curve (AUC), and construct validity were assessed. Results: NDDI-E-Y questionnaires were analyzed for 143 youth. The coefficient for internal consistency for the NDDI-E-Y was 0.92. Factor analyses suggested a one-factor solution with all 12 items loading on the factor. The NDDI-E-Y was positively correlated with the CDI-2 (N = 99). Sensitivity and specificity of the NDDI-E-Y were high. Significance: Reliability and construct validity were established for the revised 12-item NDDI-E-Y. The NDDI-E-Y is a brief, free measure of depressive symptoms that can be administered during a routine epilepsy visit

Prediction of Specific Depressive Symptom Clusters in Youth With Epilepsy: The NDDI-E-Y Versus Neuro-QOL SF

Objective: Proper assessment and early identification of depressive symptoms are essential to initiate treatment and minimize the risk for poor outcomes in youth with epilepsy (YWE). The current study examined the predictive utility of the Neurological Disorders Depression Inventory-Epilepsy for Youth (NDDI-E-Y) and the Neuro-QOL Depression Short Form (Neuro-QOL SF) in explaining variance in overall depressive symptoms and specific symptom clusters on the gold standard Children\u27s Depression Inventory-2 (CDI-2). Methods: Cross-sectional study examining 99 YWE (female 68, mean age 14.7 years) during a routine epilepsy visit, who completed self-report measures of depressive symptoms, including the NDDI-E-Y, CDI-2, and the Neuro-QOL SF. Caregivers completed a measure of seizure severity. All sociodemographic and medical information was evaluated through electronic medical record review. Results: After accounting for seizure and demographic variables, the NDDI-E-Y accounted for 45% of the variance in the CDI-2 Total score and the CDI-2 Ineffectiveness subscale. Furthermore, the NDDI-E-Y predicted CDI-2 Total scores and subscales similarly, with the exception of explaining significantly more variance in the CDI-2 Ineffectiveness subscale compared to the Negative Mood subscale. The NDDI-E-Y explained greater variance compared to Neuro-QOL SF across the Total (48% vs. 37%) and all CDI-2 subscale scores; however, the NDDI-E-Y emerged as a stronger predictor of only CDI-2 Ineffectiveness. Both the NDDI-E-Y and Neuro-QOL SF accounted for the lowest amount of variance in CDI-2 Negative Mood. Sensitivity was poor for the Neuro-QOL SF in predicting high versus low CDI-2 scores. Significance: The NDDI-E-Y has strong psychometrics and can be easily integrated into routine epilepsy care for quick, brief screening of depressive symptoms in YWE