Changing measurements or changing movements? Sampling scale and movement model identifiability across generations of biologging technology

Animal movement patterns contribute to our understanding of variation in breeding success and survival of individuals, and the implications for population dynamics. Over time, sensor technology for measuring movement patterns has improved. Although older technologies may be rendered obsolete, the existing data are still valuable, especially if new and old data can be compared to test whether a behavior has changed over time. We used simulated data to assess the ability to quantify and correctly identify patterns of seabird flight lengths under observational regimes used in successive generations of wet/dry logging technology. Care must be taken when comparing data collected at differing timescales, even when using inference procedures that incorporate the observational process, as model selection and parameter estimation may be biased. In practice, comparisons may only be valid when degrading all data to match the lowest resolution in a set. Changes in tracking technology, such as the wet/dry loggers explored here, that lead to aggregation of measurements at different temporal scales make comparisons challenging. We therefore urge ecologists to use synthetic data to assess whether accurate parameter estimation is possible for models comparing disparate data sets before planning experiments and conducting analyses such as responses to environmental changes or the assessment of management actions

Predicting the growth of the amphibian chytrid fungus in varying temperature environments

Environmental temperature is a crucial abiotic factor that influences the success of ectothermic organisms, including hosts and pathogens in disease systems. One example is the amphibian chytrid fungus, Batrachochytrium dendrobatidis (Bd), which has led to widespread amphibian population declines. Understanding its thermal ecology is essential to effectively predict outbreaks. Studies that examine the impact of temperature on hosts and pathogens often do so in controlled constant temperatures. Although varying temperature experiments are becoming increasingly common, it is unrealistic to test every temperature scenario. Thus, reliable methods that use constant temperature data to predict performance in varying temperatures are needed. In this study, we tested whether we could accurately predict Bd growth in three varying temperature regimes, using a Bayesian hierarchical model fit with constant temperature Bd growth data. We fit the Bayesian hierarchical model five times, each time changing the thermal performance curve (TPC) used to constrain the logistic growth rate to determine how TPCs influence the predictions. We then validated the model predictions using Bd growth data collected from the three tested varying temperature regimes. Although all TPCs overpredicted Bd growth in the varying temperature regimes, some functional forms performed better than others. Varying temperature impacts on disease systems are still not well understood and improving our understanding and methodologies to predict these effects could provide insights into disease systems and help conservation efforts

Understanding uncertainty in temperature effects on vector-borne disease: A Bayesian approach

Extrinsic environmental factors influence the distribution and population dynamics of many organisms, including insects that are of concern for human health and agriculture. This is particularly true for vector-borne infectious diseases, like malaria, which is a major source of morbidity and mortality in humans. Understanding the mechanistic links between environment and population processes for these diseases is key to predicting the consequences of climate change on transmission and for developing effective interventions. An important measure of the intensity of disease transmission is the reproductive number $R_0$. However, understanding the mechanisms linking $R_0$ and temperature, an environmental factor driving disease risk, can be challenging because the data available for parameterization are often poor. To address this we show how a Bayesian approach can help identify critical uncertainties in components of $R_0$ and how this uncertainty is propagated into the estimate of $R_0$. Most notably, we find that different parameters dominate the uncertainty at different temperature regimes: bite rate from 15-25$^\circ$ C; fecundity across all temperatures, but especially $\sim$25-32$^\circ$ C; mortality from 20-30$^\circ$ C; parasite development rate at $\sim$15-16$^\circ$C and again at $\sim$33-35$^\circ$C. Focusing empirical studies on these parameters and corresponding temperature ranges would be the most efficient way to improve estimates of $R_0$. While we focus on malaria, our methods apply to improving process-based models more generally, including epidemiological, physiological niche, and species distribution models.Comment: 27 pages, including 1 table and 3 figure

Mapping Physiological Suitability Limits for Malaria in Africa Under Climate Change

We mapped current and future temperature suitability for malaria transmission in Africa using a published model that incorporates nonlinear physiological responses to temperature of the mosquito vector Anopheles gambiae and the malaria parasite Plasmodium falciparum. We found that a larger area of Africa currently experiences the ideal temperature for transmission than previously supposed. Under future climate projections, we predicted a modest increase in the overall area suitable for malaria transmission, but a net decrease in the most suitable area. Combined with human population density projections, our maps suggest that areas with temperatures suitable for year-round, highest-risk transmission will shift from coastal West Africa to the Albertine Rift between the Democratic Republic of Congo and Uganda, whereas areas with seasonal transmission suitability will shift toward sub-Saharan coastal areas. Mapping temperature suitability places important bounds on malaria transmissibility and, along with local level demographic, socioeconomic, and ecological factors, can indicate where resources may be best spent on malaria control

Workplace Traumatic Stress and Mental Health Sequelae among Public Safety Telecommunications Officers in Florida

Background: Public safety telecommunications officers (PSTCOs), aka emergency “dispatchers,” are exposed to workplace traumatic stress and can experience situations characterized by uncertainty, communication difficulties, and a lack of resources. Traumatic stress experienced by emergency dispatchers has led to mental health symptoms. Purpose: This paper aims to describe the results of a study examining the patterns of workplace traumatic stress and the relationship between workplace traumatic stress and mental health concerns among a sample of PSTCOs. Methods: PSTCOs (n=54) participated in a cross-sectional, anonymous survey including screeners for depression, anxiety, post-traumatic stress disorder (PTSD), suicidal thoughts, and harmful alcohol use. Respondents also completed the Life Events Checklist (LEC) to screen for exposure to emergency calls identified as having the potential to induce traumatic stress. Results: 18.4% of respondents reported experiencing moderate to severe levels of depression, and 12% reported moderate to severe anxiety. Of the sample, 14% met the criteria for a provisional diagnosis of PTSD, 40% reported hazardous drinking levels, and 10% met the criteria of being at risk for suicide. Overall, 72.2% of PSTCOs experienced at least one form of job-related trauma and varied significantly by marital status. Poisson regression revealed statistically significant relationships between exposure to job-related traumatic events and screener scale scores. For example, those exposed to assault with a weapon had depression scores 2.29 points higher compared to those who were not exposed (p≤0.05). Discussion: Employing organizations of PSTCOs should strive to incorporate comprehensive wellness programs emphasizing education, prevention, early intervention, and recognition of traumatic stress among dispatchers. These programs should emphasize peer support and non-punitive policies to encourage help-seeking. In addition, given that findings in this study indicate exposure to traumatic emergency calls predicts PTSD symptomology, legislation could consider including PSTCOs in Florida Statute 118.1215

Application of multiplexed ion mobility spectrometry towards the identification of host protein signatures of treatment effect in pulmonary tuberculosis.

RationaleThe monitoring of TB treatments in clinical practice and clinical trials relies on traditional sputum-based culture status indicators at specific time points. Accurate, predictive, blood-based protein markers would provide a simpler and more informative view of patient health and response to treatment.ObjectiveWe utilized sensitive, high throughput multiplexed ion mobility-mass spectrometry (IM-MS) to characterize the serum proteome of TB patients at the start of and at 8 weeks of rifamycin-based treatment. We sought to identify treatment specific signatures within patients as well as correlate the proteome signatures to various clinical markers of treatment efficacy.MethodsSerum samples were collected from 289 subjects enrolled in CDC TB Trials Consortium Study 29 at time of enrollment and at the end of the intensive phase (after 40 doses of TB treatment). Serum proteins were immunoaffinity-depleted of high abundant components, digested to peptides and analyzed for data acquisition utilizing a unique liquid chromatography IM-MS platform (LC-IM-MS). Linear mixed models were utilized to identify serum protein changes in the host response to antibiotic treatment as well as correlations with culture status end points.ResultsA total of 10,137 peptides corresponding to 872 proteins were identified, quantified, and used for statistical analysis across the longitudinal patient cohort. In response to TB treatment, 244 proteins were significantly altered. Pathway/network comparisons helped visualize the interconnected proteins, identifying up regulated (lipid transport, coagulation cascade, endopeptidase activity) and down regulated (acute phase) processes and pathways in addition to other cross regulated networks (inflammation, cell adhesion, extracellular matrix). Detection of possible lung injury serum proteins such as HPSE, significantly downregulated upon treatment. Analyses of microbiologic data over time identified a core set of serum proteins (TTHY, AFAM, CRP, RET4, SAA1, PGRP2) which change in response to treatment and also strongly correlate with culture status. A similar set of proteins at baseline were found to be predictive of week 6 and 8 culture status.ConclusionA comprehensive host serum protein dataset reflective of TB treatment effect is defined. A repeating set of serum proteins (TTHY, AFAM, CRP, RET4, SAA1, PGRP2, among others) were found to change significantly in response to treatment, to strongly correlate with culture status, and at baseline to be predictive of future culture conversion. If validated in cohorts with long term follow-up to capture failure and relapse of TB, these protein markers could be developed for monitoring of treatment in clinical trials and in patient care

Quit4baby: Results from a pilot test of a mobile smoking cessation program for pregnant women

Background: Text messaging (short message service, SMS) programs have been shown to be effective in helping adult smokers quit smoking. This study describes the results of a pilot test of Quit4baby, a smoking cessation text messaging program for pregnant smokers that was adapted from Text2quit. Objective: The study aimed to demonstrate the feasibility and acceptability of Quit4baby for women currently enrolled in Text4baby, a perinatal health text messaging program. Methods: Pregnant women enrolled in Text4baby and who were current smokers or had quit within the last 4 weeks (n=20) were enrolled in Quit4baby. Those under the age of 18, not pregnant, not current smokers, those using nicotine replacement therapy, and those not interested in participating were ineligible. Participants were surveyed at baseline and at 2 and 4 weeks postenrollment. Results: Most participants responded to the program favorably. Highly rated aspects included the content of the program, skills taught within the program, and encouragement and social support provided by the program. Participants reported that the program was helpful in quitting, that the program gave good ideas on quitting, and that they would recommend the program to a friend. Suggestions for improvement included increasing the message dose and making the quitpal more interactive. Conclusions: This pilot test provides support for the feasibility and acceptability of Quit4baby. Future studies are needed to assess whether Quit4baby is effective for smoking cessation during pregnancy

Genome-wide association studies of the self-rating of effects of ethanol (SRE).

The level of response (LR) to alcohol as measured with the Self-Report of the Effects of Alcohol Retrospective Questionnaire (SRE) evaluates the number of standard drinks usually required for up to four effects. The need for a higher number of drinks for effects is genetically influenced and predicts higher risks for heavy drinking and alcohol problems. We conducted genome-wide association study (GWAS) in the African-American (COGA-AA, N = 1527 from 309 families) and European-American (COGA-EA, N = 4723 from 956 families) subsamples of the Collaborative Studies on the Genetics of Alcoholism (COGA) for two SRE scores: SRE-T (average of first five times of drinking, the period of heaviest drinking, and the most recent 3 months of consumption) and SRE-5 (the first five times of drinking). We then meta-analyzed the two COGA subsamples (COGA-AA + EA). Both SRE-T and SRE-5 were modestly heritable (h2 : 21%-31%) and genetically correlated with alcohol dependence (AD) and DSM-IV AD criterion count (rg : 0.35-0.76). Genome-wide significant associations were observed (SRE-T: chromosomes 6, rs140154945, COGA-EA P = 3.30E-08 and 11, rs10647170, COGA-AA+EA P = 3.53E-09; SRE-5: chromosome13, rs4770359, COGA-AA P = 2.92E-08). Chromosome 11 was replicated in an EA dataset from the National Institute on Alcohol Abuse and Alcoholism intramural program. In silico functional analyses and RNA expression analyses suggest that the chromosome 6 locus is an eQTL for KIF25. Polygenic risk scores derived using the COGA SRE-T and SRE-5 GWAS predicted 0.47% to 2.48% of variances in AD and DSM-IV AD criterion count in independent datasets. This study highlights the genetic contribution of alcohol response phenotypes to the etiology of alcohol use disorders

EXPORTS North Atlantic eddy tracking

The EXPORTS North Atlantic field campaign (EXPORTS-NA) of May 2021 used a diverse array of ship-based and autonomous platforms to measure and quantify processes leading to carbon export in the open ocean. The success of this field program relied heavily on the ability to make measurements following a Lagrangian trajectory within a coherent, retentive eddy (Sections 1, 2). Identifying an eddy that would remain coherent and retentive over the course of a monthlong deployment was a significant challenge that the EXPORTS team faced. This report details the processes and procedures used by the primarily shore-based eddy tracking team to locate, track, and sample with autonomous assets such an eddy before and during EXPORTS-NA.This field deployment was funded by the NASA Ocean Biology and Biogeochemistry program and the National Science Foundation Biological and Chemical Oceanography programs. Initial gliders deployments were performed by the RRS Discovery and the authors thank the Porcupine Abyssal Plain – Sustained Observatory of the Natural Environment Research Council (NERC, UK), which is principally funded through the Climate Linked Atlantic Sector Science (CLASS) project supported by NERC National Capability funding (NE/R015953/1) and by IFADO (Innovation in the Framework of the Atlantic Deep Ocean) EAPA_165/2016. Technical assistance with glider deployment was provided by Marine Autonomous Robotic Systems (NOC). The authors thank Inia Soto Ramos for assistance in publishing this manuscript through the NASA Technical Memorandum series. This is PMEL contribution number 5372

Genome-wide association study of phenotypes measuring progression from first cocaine or opioid use to dependence reveals novel risk genes

AIM: Substance use disorders (SUD) result in substantial morbidity and mortality worldwide. Opioids, and to a lesser extent cocaine, contribute to a large percentage of this health burden. Despite their high heritability, few genetic risk loci have been identified for either opioid or cocaine dependence (OD or CD, respectively). A genome-wide association study of OD and CD related phenotypes reflecting the time between first self-reported use of these substances and a first DSM-IV dependence diagnosis was conducted. METHODS: Cox proportional hazards regression in a discovery sample of 6,188 African-Americans (AAs) and 6,835 European-Americans (EAs) participants in a genetic study of multiple substance dependence phenotypes were used to test for association between genetic variants and these outcomes. The top findings were tested for replication in two independent cohorts. RESULTS: In the discovery sample, three independent regions containing variants associated with time to dependence at CONCLUSIONS: Although the two GWS variants are not in genes with obvious links to SUD biology and have modest effect sizes, they are statistically robust and show evidence for association in independent samples. These results may point to novel pathways contributing to disease progression and highlight the utility of related phenotypes to better understand the genetics of SUDs