BACKGROUND: Sudden unexpected death in epilepsy (SUDEP) is a major cause of death in those with drug-resistant epilepsy (DRE). There is a need for inventories and biomarkers associated with the risk for SUDEP. OBJECTIVE: To explore the revised SUDEP Risk Inventory (SUDEP-7) in a cohort with DRE and determine the association with Heart Rate and other covariates. METHODS: Twenty-five subjects with severe DRE were enrolled in a clinical trial for epilepsy. Baseline demographics, duration of epilepsy, seizure types, seizure frequency, seizure severity, AEDs, and vital signs were collected. Heart rate variability (HRV) was calculated from 1-h recordings of ECG. A SUDEP Risk Inventory (SUDEP-7) was administered, which included seven validated and weighted risk factors initially identified by Walczak et al. as factors associated with SUDEP risk. RESULTS: The total score on the revised SUDEP-7 ranged from 1 to 7, mean = 3.4 (SD 1.8). The SUDEP Risk Inventory score was inversely correlated with RMSSD (Pearson r = -0.45, p = 0.027). The following variables were significantly associated with RMSSD: epilepsy duration (p = 0.02), age (p = 0.03), and developmental intellectual disability (p < 0.001). The correlation between RMSSD and SUDEP-7 tended to persist also after the adjustment for patient age (r = -0.40, p = 0.05). Two subjects died of SUDEP: their SUDEP-7 scores were above average and in the upper twenty-fifth and fiftieth percentiles, respectively (6 and 4, mean = 3.4). CONCLUSION: RMSSD, a measure of low frequency HRV, was significantly associated with SUDEP Risk Inventory (SUDEP-7) scores. Using a multivariate model, the covariates of developmental intellectual disability, age, and duration of epilepsy were also significantly associated with decreased HRV. The correlation between decreased HRV and a higher SUDEP-7 score remained unchanged even after the adjustment for patient age. The results suggest that older age, greater duration of epilepsy, and the presence of developmental intellectual disability may increase the risk of SUDEP through their direct influence on decreasing the vagus nerve-mediated HRV. Further validation of the SUDEP-7 inventory is indicated. TRIAL REGISTRATION: ClinicalTrials.gov, NCT00871377.

Mass and body composition are indices of overall animal health and energetic balance and are often used as indicators of resource availability in the environment. This study used morphometric models and isotopic dilution techniques, two commonly used methods in the marine mammal field, to assess body composition of Weddell seals (Leptonychotes weddellii, N = 111). Findings indicated that traditional morphometric models that use a series of circular, truncated cones to calculate marine mammal blubber volume and mass overestimated the animal's measured body mass by 26.9±1.5% SE. However, we developed a new morphometric model that uses elliptical truncated cones, and estimates mass with only -2.8±1.7% error (N = 10). Because this elliptical truncated cone model can estimate body mass without the need for additional correction factors, it has the potential to be a broadly applicable method in marine mammal species. While using elliptical truncated cones yielded significantly smaller blubber mass estimates than circular cones (10.2±0.8% difference; or 3.5±0.3% total body mass), both truncated cone models significantly underestimated total body lipid content as compared to isotopic dilution results, suggesting that animals have substantial internal lipid stores (N = 76). Multiple linear regressions were used to determine the minimum number of morphometric measurements needed to reliably estimate animal mass and body composition so that future animal handling times could be reduced. Reduced models estimated body mass and lipid mass with reasonable accuracy using fewer than five morphometric measurements (root-mean-square-error: 4.91% for body mass, 10.90% for lipid mass, and 10.43% for % lipid). This indicates that when test datasets are available to create calibration coefficients, regression models also offer a way to improve body mass and condition estimates in situations where animal handling times must be short and efficient.

Background

n-3 fatty acids inhibit neuronal excitability and reduce seizures in animal models. High-dose fish oil has been explored in two randomised trials in drug resistant epilepsy with negative results. We performed a phase II randomised controlled crossover trial of low-dose and high-dose fish oil in participants with drug resistant epilepsy to explore whether low-dose or high-dose fish oil reduces seizures or improves cardiovascular health.

Methods

Randomised placebo-controlled trial of low-dose and high-dose fish oil versus placebo (corn oil, linoleic acid) in 24 participants with drug resistant epilepsy. A three-period crossover design was utilised lasting 42 weeks, with three 10-week treatment periods and two 6-week washout periods. All participants were randomised in double-blind fashion to receive placebo, high dose or low dose in different sequences. The primary outcome was per cent change in total seizure frequency.

Findings

Low-dose fish oil (3 capsules/day, 1080 mg eicosapentaenoic acid+docosahexaenoic acid) was associated with a 33.6% reduction in seizure frequency compared with placebo. Low-dose fish oil was also associated with a mild but significant reduction in blood pressure. High-dose fish oil was no different than placebo in reducing seizures or improving cardiac risk factors.

Interpretation

In this phase II randomised crossover trial, low-dose fish oil was effective in reducing seizures compared with placebo. The magnitude of improvement is similar to that of recent antiepileptic drug trials in drug resistant epilepsy (DRE). The results indicate that low-dose fish oil may reduce seizures and improve the health of people with epilepsy. These findings justify a large multicentre randomised trial of low-dose fish oil (n-3 fatty acids <1080 mg/day) in drug resistant epilepsy.

Trial registration number

NCT00871377.

The assessment of behavioural disturbance in cetacean species (e.g. resulting from exposure to anthropogenic sources such as military sonar, seismic surveys, or pile driving) is important for effective conservation and management. Disturbance effects can be informed by Behavioural Response Studies (BRSs), involving either controlled exposure experiments (CEEs) where noise exposure conditions are presented deliberately to meet experimental objectives or in opportunistic contexts where ongoing activities are monitored in a strategic manner. In either context, animal-borne sensors or in situ observations can provide information on individual exposure and disturbance responses. The past 15 years of research have greatly expanded our understanding of behavioural responses to noise, including hundreds of experiments in nearly a dozen cetacean species. Many papers note limited sample sizes, required knowledge of baseline behaviour prior to exposure and the importance of contextual factors modulating behavioural responses, all of which in combination can lead to sampling biases, even for well-designed research programs. It is critical to understand these biases to robustly identify responses. This ensures outcomes of BRSs help inform predictions of how anthropogenic disturbance impacts individuals and populations. Our approach leverages concepts from the animal behaviour literature focused on helping to avoid sampling bias by considering what shapes an animals response. These factors include social, experience, genetic and natural changes in responsiveness. We developed and applied a modified version of this framework to synthesise current knowledge on cetacean response in the context of effects observed across marine and terrestrial taxa. This new Sampling, Exposure, Receptor framework (SERF) identifies 43 modulating factors, highlights potential biases, and assesses how these vary across selected focal species. In contrast to studies that identified variation in Exposure factors as a key concern, our analysis indicated that factors relating to Sampling (e.g. deploying tags on less evasive individuals, which biases selection of subjects), and Receptor (e.g. health status or coping style) have the greatest potential for weakening the desired broad representativeness of BRSs. Our assessment also highlights how potential biases could be addressed with existing datasets or future developments.

Although energetics is fundamental to animal ecology, traditional methods of determining metabolic rate are neither direct nor instantaneous. Recently, continuous blood oxygen (O2) measurements were used to assess energy expenditure in diving elephant seals (Mirounga angustirostris), demonstrating that an exceptional hypoxemic tolerance and exquisite management of blood O2 stores underlie the extraordinary diving capability of this consummate diver. As the detailed relationship of energy expenditure and dive behavior remains unknown, we integrated behavior, ecology, and physiology to characterize the costs of different types of dives of elephant seals. Elephant seal dive profiles were analyzed and O2 utilization was classified according to dive type (overall function of dive: transit, foraging, food processing/rest). This is the first account linking behavior at this level with in vivo blood O2 measurements in an animal freely diving at sea, allowing us to assess patterns of O2 utilization and energy expenditure between various behaviors and activities in an animal in the wild. In routine dives of elephant seals, the blood O2 store was significantly depleted to a similar range irrespective of dive function, suggesting that all dive types have equal costs in terms of blood O2 depletion. Here, we present the first physiological evidence that all dive types have similarly high blood O2 demands, supporting an energy balance strategy achieved by devoting one major task to a given dive, thereby separating dive functions into distinct dive types. This strategy may optimize O2 store utilization and recovery, consequently maximizing time underwater and allowing these animals to take full advantage of their underwater resources. This approach may be important to optimizing energy expenditure throughout a dive bout or at-sea foraging trip and is well suited to the lifestyle of an elephant seal, which spends > 90% of its time at sea submerged making diving its most "natural" state.

Many baleen whales undertake annual fasting and feeding cycles, resulting in substantial changes in their body condition, an important factor affecting fitness. As a measure of lipid-store body condition, tissue density of a few deep diving marine mammals has been estimated using a hydrodynamic glide model of drag and buoyancy forces. Here, we applied the method to shallow-diving humpback whales (Megaptera novaeangliae) in North Atlantic and Antarctic feeding aggregations. High-resolution 3-axis acceleration, depth and speed data were collected from 24 whales. Measured values of acceleration during 5 s glides were fitted to a hydrodynamic glide model to estimate unknown parameters (tissue density, drag term and diving gas volume) in a Bayesian framework. Estimated species-average tissue density (1031.6 ± 2.1 kg m-3, ±95% credible interval) indicates that humpback whale tissue is typically negatively buoyant although there was a large inter-individual variation ranging from 1025.2 to 1043.1 kg m-3. The precision of the individual estimates was substantially finer than the variation across different individual whales, demonstrating a progressive decrease in tissue density throughout the feeding season and comparably high lipid-store in pregnant females. The drag term (CDAm-1) was estimated to be relatively high, indicating a large effect of lift-related induced drag for humpback whales. Our results show that tissue density of shallow diving baleen whales can be estimated using the hydrodynamic gliding model, although cross-validation with other techniques is an essential next step. This method for estimating body condition is likely to be broadly applicable across a range of aquatic animals and environments.

Marine mammals may be negatively affected by anthropogenic noise. Behavioural response studies (BRS) aim to establish a relationship between noise exposure conditions (dose) from a potential stressor and associated behavioural responses of animals. A recent series of BRS have focused on the effects of naval sonar sounds on cetaceans. Here, we review the current state of understanding of naval sonar impact on marine mammals and highlight knowledge gaps and future research priorities. Many marine mammal species exhibit responses to naval sonar sounds. However, responses vary between and within individuals and populations, highlighting the importance of exposure context in modulating dose–response relationships. There is increasing support from both terrestrial and marine systems for the risk-disturbance hypothesis as an explanation for underlying response processes. This proposes that sonar sounds may be perceived by animals as a threat, evoking a response shaped by the underlying species-specific risk of predation and anti-predator strategy. An understanding of responses within both the dose–response and risk-disturbance frameworks may enhance our ability to predict responsiveness for unstudied species and populations. Many observed behavioural responses are energetically costly, but the way that these responses may lead to long-term individual and population-level impacts is poorly understood. Synthesis and applications. Behavioural response studies have greatly improved our understanding of the potential effects of naval sonar on marine mammals. Despite data gaps, we believe a dose-response approach within a risk-disturbance framework will enhance our ability to predict responsiveness for unstudied species and populations. We advocate for (1) regulatory frameworks to utilize peer-reviewed research findings when making predictions of impact, (2) regulatory frameworks to account for the inherent uncertainty in predictions of impact and (3) investment in monitoring programmes that are both directed by recent research and offer opportunities for validation of predictions at the individual and population level.