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Background: Eating disorders are serious mental illnesses requiring a whole of health approach. Routinely collected health administrative data has clinical utility in describing associations and predicting health outcome measures. This study aims to develop models to assess the clinical utility of health administrative data in adult eating disorder emergency presentations and length of stay., Methods: Retrospective cohort study on health administrative data in adults with eating disorders from 2014 to 2020 in Sydney Local Health District. Emergency and admitted patient data were collected with all clinically important variables available. Multivariable regression models were analysed to explore associations and to predict admissions and length of stay., Results: Emergency department modelling describes some clinically important associations such as decreased odds of admission for patients with Bulimia Nervosa compared to Anorexia Nervosa (Odds Ratio [OR] 0.31, 95% Confidence Interval [95%CI] 0.10 to 0.95; p = 0.04). Admitted data included more predictors and therefore further significant associations including an average of 0.96 days increase in length of stay for each additional count of diagnosis/comorbidities (95% Confidence Interval [95% CI] 0.37 to 1.55; p = 0.001) with a valid prediction model (R 2  = 0.56)., Conclusions: Health administrative data has clinical utility in adult eating disorders with valid exploratory and predictive models describing associations and predicting admissions and length of stay. Utilising health administrative data this way is an efficient process for assessing impacts of multiple factors on patient care and predicting health care outcomes., (© 2023. Crown.)

Background: Animal-borne sensors ('bio-loggers') can record a suite of kinematic and environmental data, which are used to elucidate animal ecophysiology and improve conservation efforts. Machine learning techniques are used for interpreting the large amounts of data recorded by bio-loggers, but there exists no common framework for comparing the different machine learning techniques in this domain. This makes it difficult to, for example, identify patterns in what works well for machine learning-based analysis of bio-logger data. It also makes it difficult to evaluate the effectiveness of novel methods developed by the machine learning community. Methods: To address this, we present the Bio-logger Ethogram Benchmark (BEBE), a collection of datasets with behavioral annotations, as well as a modeling task and evaluation metrics. BEBE is to date the largest, most taxonomically diverse, publicly available benchmark of this type, and includes 1654 h of data collected from 149 individuals across nine taxa. Using BEBE, we compare the performance of deep and classical machine learning methods for identifying animal behaviors based on bio-logger data. As an example usage of BEBE, we test an approach based on self-supervised learning. To apply this approach to animal behavior classification, we adapt a deep neural network pre-trained with 700,000 h of data collected from human wrist-worn accelerometers. Results: We find that deep neural networks out-perform the classical machine learning methods we tested across all nine datasets in BEBE. We additionally find that the approach based on self-supervised learning out-performs the alternatives we tested, especially in settings when there is a low amount of training data available. Conclusions: In light of these results, we are able to make concrete suggestions for designing studies that rely on machine learning to infer behavior from bio-logger data. Therefore, we expect that BEBE will be useful for making similar suggestions in the future, as additional hypotheses about machine learning techniques are tested. Datasets, models, and evaluation code are made publicly available at https://github.com/earthspecies/BEBE, to enable community use of BEBE. [ABSTRACT FROM AUTHOR]

Background: Lung cancer brain metastases (LC-BrMs) are frequently associated with dismal mortality rates in patients with lung cancer; however, standard of care therapies for LC-BrMs are still limited in their efficacy. A deep understanding of molecular mechanisms and tumor microenvironment of LC-BrMs will provide us with new insights into developing novel therapeutics for treating patients with LC-BrMs. Methods: Here, we performed integrated analyses of genomic, transcriptomic, proteomic, metabolomic, and single-cell RNA sequencing data which were derived from a total number of 154 patients with paired and unpaired primary lung cancer and LC-BrM, spanning four published and two newly generated patient cohorts on both bulk and single cell levels. Results: We uncovered that LC-BrMs exhibited a significantly greater intra-tumor heterogeneity. We also observed that mutations in a subset of genes were almost always shared by both primary lung cancers and LC-BrM lesions, including TTN, TP53, MUC16, LRP1B, RYR2, and EGFR. In addition, the genome-wide landscape of somatic copy number alterations was similar between primary lung cancers and LC-BrM lesions. Nevertheless, several regions of focal amplification were significantly enriched in LC-BrMs, including 5p15.33 and 20q13.33. Intriguingly, integrated analyses of transcriptomic, proteomic, and metabolomic data revealed mitochondrial-specific metabolism was activated but tumor immune microenvironment was suppressed in LC-BrMs. Subsequently, we validated our results by conducting real-time quantitative reverse transcription PCR experiments, immunohistochemistry, and multiplexed immunofluorescence staining of patients' paired tumor specimens. Therapeutically, targeting oxidative phosphorylation with gamitrinib in patient-derived organoids of LC-BrMs induced apoptosis and inhibited cell proliferation. The combination of gamitrinib plus anti-PD-1 immunotherapy significantly improved survival of mice bearing LC-BrMs. Patients with a higher expression of mitochondrial metabolism genes but a lower expression of immune genes in their LC-BrM lesions tended to have a worse survival outcome. Conclusions: In conclusion, our findings not only provide comprehensive and integrated perspectives of molecular underpinnings of LC-BrMs but also contribute to the development of a potential, rationale-based combinatorial therapeutic strategy with the goal of translating it into clinical trials for patients with LC-BrMs. [ABSTRACT FROM AUTHOR]

Background: The ankle is usually highly effective in modulating the swing foot's trajectory to ensure safe ground clearance but there are few reports of ankle kinetics and mechanical energy exchange during the gait cycle swing phase. Previous work has investigated ankle swing mechanics during normal walking but with developments in devices providing dorsiflexion assistance, it is now essential to understand the minimal kinetic requirements for increasing ankle dorsiflexion, particularly for devices employing energy harvesting or utilizing lighter and lower power energy sources or actuators. Methods: Using a real-time treadmill-walking biofeedback technique, swing phase ankle dorsiflexion was experimentally controlled to increase foot-ground clearance by 4 cm achieved via increased ankle dorsiflexion. Swing phase ankle moments and dorsiflexor muscle forces were estimated using AnyBody modeling system. It was hypothesized that increasing foot-ground clearance by 4 cm, employing only the ankle joint, would require significantly higher dorsiflexion moments and muscle forces than a normal walking control condition. Results: Results did not confirm significantly increased ankle moments with augmented dorsiflexion, with 0.02 N.m/kg at toe-off reducing to zero by the end of swing. Tibialis Anterior muscle force incremented significantly from 2 to 4 N/kg after toe-off, due to coactivation with the Soleus. To ensure an additional 4 cm mid swing foot-ground clearance, an estimated additional 0.003 Joules/kg is required to be released immediately after toe-off. Conclusion: This study highlights the interplay between ankle moments, muscle forces, and energy demands during swing phase ankle dorsiflexion, offering insights for the design of ankle assistive technologies. External devices do not need to deliver significantly greater ankle moments to increase ankle dorsiflexion but, they should offer higher mechanical power to provide rapid bursts of energy to facilitate quick dorsiflexion transitions before reaching Minimum Foot Clearance event. Additionally, for ankle-related bio-inspired devices incorporating artificial muscles or humanoid robots that aim to replicate natural ankle biomechanics, the inclusion of supplementary Tibialis Anterior forces is crucial due to Tibialis Anterior and Soleus co-activation. These design strategies ensures that ankle assistive technologies are both effective and aligned with the biomechanical realities of human movement. [ABSTRACT FROM AUTHOR]

Zoonotic diseases represent a significant societal challenge in terms of their health and economic impacts. One Health approaches to managing zoonotic diseases are becoming more prevalent, but require novel thinking, tools and cross-disciplinary collaboration. Bovine tuberculosis (bTB) is one example of a costly One Health challenge with a complex epidemiology involving humans, domestic animals, wildlife and environmental factors, which require sophisticated collaborative approaches. We undertook a scoping review of multi-host bTB epidemiology to identify trends in species publication focus, methodologies, and One Health approaches. We aimed to identify knowledge gaps where novel research could provide insights to inform control policy, for bTB and other zoonoses. The review included 532 articles. We found different levels of research attention across episystems, with a significant proportion of the literature focusing on the badger-cattle-TB episystem, with far less attention given to tropical multi-host episystems. We found a limited number of studies focusing on management solutions and their efficacy, with very few studies looking at modelling exit strategies. Only a small number of studies looked at the effect of human disturbances on the spread of bTB involving wildlife hosts. Most of the studies we reviewed focused on the effect of badger vaccination and culling on bTB dynamics with few looking at how roads, human perturbations and habitat change may affect wildlife movement and disease spread. Finally, we observed a lack of studies considering the effect of weather variables on bTB spread, which is particularly relevant when studying zoonoses under climate change scenarios. Significant technological and methodological advances have been applied to bTB episystems, providing explicit insights into its spread and maintenance across populations. We identified a prominent bias towards certain species and locations. Generating more high-quality empirical data on wildlife host distribution and abundance, high-resolution individual behaviours and greater use of mathematical models and simulations are key areas for future research. Integrating data sources across disciplines, and a "virtuous cycle" of well-designed empirical data collection linked with mathematical and simulation modelling could provide additional gains for policy-makers and managers, enabling optimised bTB management with broader insights for other zoonoses. [ABSTRACT FROM AUTHOR]

Glioblastoma (GBM), the predominant and primary malignant intracranial tumor, poses a formidable challenge due to its immunosuppressive microenvironment, thereby confounding conventional therapeutic interventions. Despite the established treatment regimen comprising surgical intervention, radiotherapy, temozolomide administration, and the exploration of emerging modalities such as immunotherapy and integration of medicine and engineering technology therapy, the efficacy of these approaches remains constrained, resulting in suboptimal prognostic outcomes. In recent years, intensive scrutiny of the inhibitory and immunosuppressive milieu within GBM has underscored the significance of cellular constituents of the GBM microenvironment and their interactions with malignant cells and neurons. Novel immune and targeted therapy strategies have emerged, offering promising avenues for advancing GBM treatment. One pivotal mechanism orchestrating immunosuppression in GBM involves the aggregation of myeloid-derived suppressor cells (MDSCs), glioma-associated macrophage/microglia (GAM), and regulatory T cells (Tregs). Among these, MDSCs, though constituting a minority (4–8%) of CD45+ cells in GBM, play a central component in fostering immune evasion and propelling tumor progression, angiogenesis, invasion, and metastasis. MDSCs deploy intricate immunosuppressive mechanisms that adapt to the dynamic tumor microenvironment (TME). Understanding the interplay between GBM and MDSCs provides a compelling basis for therapeutic interventions. This review seeks to elucidate the immune regulatory mechanisms inherent in the GBM microenvironment, explore existing therapeutic targets, and consolidate recent insights into MDSC induction and their contribution to GBM immunosuppression. Additionally, the review comprehensively surveys ongoing clinical trials and potential treatment strategies, envisioning a future where targeting MDSCs could reshape the immune landscape of GBM. Through the synergistic integration of immunotherapy with other therapeutic modalities, this approach can establish a multidisciplinary, multi-target paradigm, ultimately improving the prognosis and quality of life in patients with GBM. [ABSTRACT FROM AUTHOR]

Background: Family violence, which includes intimate partner abuse, child abuse, and elder abuse, is a serious public health concern. Primary healthcare (PHC) offers a vital opportunity to identify and address family violence, yet barriers prevent the effective implementation of family violence interventions in PHC settings. The purpose of this study is to improve family violence identification and response in Alberta's PHC settings by exploring readiness factors. Methods: An integrated knowledge translation approach, combining implementation science and participatory action research, was employed to develop a readiness assessment tool for addressing family violence within PHC settings in Alberta. The research involved three phases: phase 1 involved a rapid evidence assessment, phase 2 engaged a panel of healthcare and family violence experts to explore readiness components in the Alberta context, and phase 3 utilized a 3-round Delphi consensus-building process to refine readiness indicators. Results: Phase 1 findings from a rapid evidence assessment highlighted five main models/tools for assessing readiness to implement family violence interventions in PHC settings. In phase 2, additional concepts were identified through exploration with healthcare and family violence expert panel members, resulting in a total of 16 concepts for assessing family violence readiness within the Alberta PHC context. The 3-round Delphi consensus-building process in Phase 3 involved nine panelists, who collectively agreed on the inclusion of all concepts and indicators, yielding a total of 60 items for the proposed readiness assessment tool for addressing family violence in PHC within Alberta. Conclusion: The current study lays the groundwork for future family violence intervention programs, offering insights into key components that promote readiness for implementing comprehensive programs and supporting PHC organizations in effectively addressing family violence. [ABSTRACT FROM AUTHOR]

Purpose: In the case of Hungarian folk dancers, it is crucial to maintain correct posture and promptly respond to imbalances. However, traditional dances often lack specific training to develop these skills. Methods: In this present study, twelve dancers (8 male, 4 female, age: 21.7 ± 3.6 years) and ten non-dancers subjects forming a control group (6 male, 4 female, age: 21.6 ± 2.87 years) participated. During the measurements a 60-second long bipedal balancing test on the balance board was completed two times, and a spinning intervention was inserted in between the two sessions. The balance capabilities of the two groups were assessed through the characterization of motion on an unstable board, and the analysis of subject's center of mass and head movements. Results: Dancers applied a more sophisticated and resource-intensive strategy to address the balancing task, yielding a better balancing performance in terms of balance board parameters. By preferring a solid stability in the medio-lateral direction, a greater fluctuation in the anterior-posterior direction can be observed (e.g., significantly lower SampEn values). The overall more successful performance is further evidenced by within-subject comparison since significant differences were observed mostly within the control group. Based on the results, the advanced balancing ability of the folk dancer group is more likely to be acquired through years of experience. Conclusion: The results indicate that additional specialized training could further enhance this ability, encouraging the reliance on poorly memorized corrective movements and reducing the risk of injury. [ABSTRACT FROM AUTHOR]

Foraging is a key driver of animal movement patterns, with specific challenges for predators which must search for mobile prey. These patterns are increasingly impacted by global changes, principally in land use and climate. Understanding the degree of flexibility in predator foraging and social strategies is pertinent to wildlife conservation under global change, including potential top-down effects on wider ecosystems. Here we propose key future research directions to better understand foraging strategies and social flexibility in predators. In particular, rapid continued advances in biologging technology are helping to record and understand dynamic behavioural and movement responses of animals to environmental changes, and their energetic consequences. Data collection can be optimised by calibrating behavioural interpretation methods in captive settings and strategic tagging decisions within and between social groups. Importantly, many species' social systems are increasingly being found to be more flexible than originally described in the literature, which may be more readily detectable through biologging approaches than behavioural observation. Integrating the effects of the physical landscape and biotic interactions will be key to explaining and predicting animal movements and energetic balance in a changing world. [ABSTRACT FROM AUTHOR]

Background: Eating disorders (EDs) are severe mental illnesses associated with significant morbidity and mortality. EDs are more prevalent among females and adolescents. Limited research has investigated Canadian trends of ED hospitalizations prior to the COVID-19 pandemic, however during the pandemic, rates of ED hospitalizations have increased. This study examined rates of ED hospitalizations among children and youth in Canada from 2010 to 2022, by sex, age, province/territory, length of stay, discharge disposition and ED diagnosis. Methods: Cases of ED hospitalizations among children and youth, ages 5 to 17 years, were identified using available ICD-10 codes in the Discharge Abstract Database from the 2010/11 to 2022/23 fiscal years. The EDs examined in this study were anorexia nervosa (F50.0), atypical anorexia nervosa (F50.1), bulimia nervosa (F50.2), other EDs (F50.3, F50.8) and unspecified EDs (F50.9). Both cases of total and first-time ED hospitalizations were examined. Descriptive statistics and trend analyses were performed. Results: Between 2010/11 and 2022/23, 18,740 children and youth were hospitalized for an ED, 65.9% of which were first-time hospitalizations. The most frequent diagnosis was anorexia nervosa (51.3%). Females had significantly higher rates of ED hospitalization compared to males (66.7/100,000 vs. 5.9/100,000). Youth had significantly higher rates compared to children. The average age of ED hospitalization was 14.7 years. Rates of ED hospitalizations were relatively stable pre-pandemic, however during the pandemic (2020–2021), rates increased. Interpretation: Rates of pediatric ED hospitalizations in Canada increased significantly during the pandemic, suggesting that there may have been limited access to alternative care for EDs or that ED cases became more severe and required hospitalization. This emphasizes the need for continued surveillance to monitor how rates of ED hospitalizations evolve post-pandemic. Plain English summary: Eating disorders disproportionally affect children and youth, however, literature investigating long-term trends of eating disorder hospitalizations among children and youth in Canada is limited. We conducted a retrospective surveillance study, examining eating disorder hospitalizations among children and youth in Canada, from 2010 to 2022, by sex, age group, geography and eating disorder diagnosis. More than half of eating disorder hospitalizations examined during our study period were first-time hospitalizations. The most common eating disorder diagnoses were anorexia nervosa, followed by unspecified eating disorders. Youth had higher rates of eating disorders compared to younger children and females had higher rates compared to males. In Canada, rates of pediatric eating disorder hospitalizations increased during the pandemic. These results emphasize the need for continued surveillance to monitor how ED hospitalizations evolve post-pandemic, as well as prioritizing early intervention and treatment to help reduce the number of children and youth requiring hospitalization. [ABSTRACT FROM AUTHOR]

Background: Monitoring the behavior of wild animals in situ can improve our understanding of how their behavior is related to their habitat and affected by disturbances and changes in their environment. Moose (Alces alces) are keystone species in their boreal habitats, where they are facing environmental changes and disturbances from human activities. How these potential stressors can impact individuals and populations is unclear, in part due to our limited knowledge of the physiology and behavior of moose and how individuals can compensate for stress and disturbances they experience. We collected data from collar-mounted fine-scale tri-axial accelerometers deployed on captive moose in combination with detailed behavioral observations to train a random forest supervised classification algorithm to classify moose accelerometer data into discrete behaviors. To investigate the generalizability of our model to collared new individuals, we quantified the variation in classification performance among individuals. Results: Our machine learning model successfully classified 3-s accelerometer data intervals from 12 Alaskan moose (A. a. gigas) and two European moose (A. a. alces) into seven behaviors comprising 97.6% of the 395 h of behavioral observations conducted in summer, fall and spring. Classification performance varied among behaviors and individuals and was generally dependent on sample size. Classification performance was highest for the most common behaviors lying with the head elevated, ruminating and foraging (precision and recall across all individuals between 0.74 and 0.90) comprising 79% of our data, and lower and more variable among individuals for the four less common behaviors lying with head down or tucked, standing, walking and running (precision and recall across all individuals between 0.28 and 0.79) comprising 21% of our data. Conclusions: We demonstrate the use of animal-borne accelerometer data to distinguish among seven main behaviors of captive moose and discuss generalizability of the results to individuals in the wild. Our results can support future efforts to investigate the detailed behavior of collared wild moose, for example in the context of disturbance responses, time budgets and behavior-specific habitat selection. [ABSTRACT FROM AUTHOR]

Background: For diving, marine predators, accelerometer and magnetometer data provides critical information on sub-surface foraging behaviours that cannot be identified from location or time-depth data. By measuring head movement and body orientation, accelerometers and magnetometers can help identify broad shifts in foraging movements, fine-scale habitat use and energy expenditure of terrestrial and marine species. Here, we use accelerometer and magnetometer data from tagged Australian sea lions and provide a new method to identify key benthic foraging areas. As Australian sea lions are listed as endangered by the IUCN and Australian legislation, identifying key areas for the species is vital to support targeted management of populations. Methods: Firstly, tri-axial magnetometer and accelerometer data from adult female Australian sea lions is used in conjunction with GPS and dive data to dead-reckon their three-dimensional foraging paths. We then isolate all benthic phases from their foraging trips and calculate a range of dive metrics to characterise their bottom usage. Finally, k-means cluster analysis is used to identify core benthic areas utilised by sea lions. Backwards stepwise regressions are then iteratively performed to identify the most parsimonious model for describing bottom usage and its included predictor variables. Results: Our results show distinct spatial partitioning in benthic habitat-use by Australian sea lions. This method has also identified individual differences in benthic habitat-use. Here, the application of high-resolution magnetometer/accelerometer data has helped reveal the tortuous foraging movements Australian sea lions use to exploit key benthic marine habitats and features. Conclusions: This study has illustrated how magnetometer and accelerometer data can provide a fine-scale description of the underwater movement of diving species, beyond GPS and depth data alone, For endangered species like Australian sea lions, management of populations must be spatially targeted. Here, this method demonstrates a fine-scale analysis of benthic habitat-use which can help identify key areas for both marine and terrestrial species. Future integration of this method with concurrent habitat and prey data would further augment its power as a tool for understanding the foraging behaviours of species. [ABSTRACT FROM AUTHOR]

Background: Epstein–Barr virus (EBV) is an important human pathogenic gammaherpesvirus with carcinogenic potential. The EBV transcriptome has previously been analyzed using both Illumina-based short read-sequencing and Pacific Biosciences RS II-based long-read sequencing technologies. Since the various sequencing methods have distinct strengths and limitations, the use of multiplatform approaches have proven to be valuable. The aim of this study is to provide a more complete picture on the transcriptomic architecture of EBV. Methods: In this work, we apply the Oxford Nanopore Technologies MinION (long-read sequencing) platform for the generation of novel transcriptomic data, and integrate these with other's data generated by another LRS approach, Pacific BioSciences RSII sequencing and Illumina CAGE-Seq and Poly(A)-Seq approaches. Both amplified and non-amplified cDNA sequencings were applied for the generation of sequencing reads, including both oligo-d(T) and random oligonucleotide-primed reverse transcription. EBV transcripts are identified and annotated using the LoRTIA software suite developed in our laboratory. Results: This study detected novel genes embedded into longer host genes containing 5′-truncated in-frame open reading frames, which potentially encode N-terminally truncated proteins. We also detected a number of novel non-coding RNAs and transcript length isoforms encoded by the same genes but differing in their start and/or end sites. This study also reports the discovery of novel splice isoforms, many of which may represent altered coding potential, and of novel replication-origin-associated transcripts. Additionally, novel mono- and multigenic transcripts were identified. An intricate meshwork of transcriptional overlaps was revealed. Conclusions: An integrative approach applying multi-technique sequencing technologies is suitable for reliable identification of complex transcriptomes because each techniques has different advantages and limitations, and the they can be used for the validation of the results obtained by a particular approach. [ABSTRACT FROM AUTHOR]

Background: Understanding what animals do in time and space is important for a range of ecological questions, however accurate estimates of how animals use space is challenging. Within the use of animal-attached tags, radio telemetry (including the Global Positioning System, 'GPS') is typically used to verify an animal's location periodically. Straight lines are typically drawn between these 'Verified Positions' ('VPs') so the interpolation of space-use is limited by the temporal and spatial resolution of the system's measurement. As such, parameters such as route-taken and distance travelled can be poorly represented when using VP systems alone. Dead-reckoning has been suggested as a technique to improve the accuracy and resolution of reconstructed movement paths, whilst maximising battery life of VP systems. This typically involves deriving travel vectors from motion sensor systems and periodically correcting path dimensions for drift with simultaneously deployed VP systems. How often paths should be corrected for drift, however, has remained unclear. Methods and results: Here, we review the utility of dead-reckoning across four contrasting model species using different forms of locomotion (the African lion Panthera leo, the red-tailed tropicbird Phaethon rubricauda, the Magellanic penguin Spheniscus magellanicus, and the imperial cormorant Leucocarbo atriceps). Simulations were performed to examine the extent of dead-reckoning error, relative to VPs, as a function of Verified Position correction (VP correction) rate and the effect of this on estimates of distance moved. Dead-reckoning error was greatest for animals travelling within air and water. We demonstrate how sources of measurement error can arise within VP-corrected dead-reckoned tracks and propose advancements to this procedure to maximise dead-reckoning accuracy. Conclusions: We review the utility of VP-corrected dead-reckoning according to movement type and consider a range of ecological questions that would benefit from dead-reckoning, primarily concerning animal–barrier interactions and foraging strategies. [ABSTRACT FROM AUTHOR]

Background: Fine-scale data on animal position are increasingly enabling us to understand the details of animal movement ecology and dead-reckoning, a technique integrating motion sensor-derived information on heading and speed, can be used to reconstruct fine-scale movement paths at sub-second resolution, irrespective of the environment. On its own however, the dead-reckoning process is prone to cumulative errors, so that position estimates quickly become uncoupled from true location. Periodic ground-truthing with aligned location data (e.g., from global positioning technology) can correct for this drift between Verified Positions (VPs). We present step-by-step instructions for implementing Verified Position Correction (VPC) dead-reckoning in R using the tilt-compensated compass method, accompanied by the mathematical protocols underlying the code and improvements and extensions of this technique to reduce the trade-off between VPC rate and dead-reckoning accuracy. These protocols are all built into a user-friendly, fully annotated VPC dead-reckoning R function; Gundog.Tracks, with multi-functionality to reconstruct animal movement paths across terrestrial, aquatic, and aerial systems, provided within the Additional file 4 as well as online (GitHub). Results: The Gundog.Tracks function is demonstrated on three contrasting model species (the African lion Panthera leo, the Magellanic penguin Spheniscus magellanicus, and the Imperial cormorant Leucocarbo atriceps) moving on land, in water and in air. We show the effect of uncorrected errors in speed estimations, heading inaccuracies and infrequent VPC rate and demonstrate how these issues can be addressed. Conclusions: The function provided will allow anyone familiar with R to dead-reckon animal tracks readily and accurately, as the key complex issues are dealt with by Gundog.Tracks. This will help the community to consider and implement a valuable, but often overlooked method of reconstructing high-resolution animal movement paths across diverse species and systems without requiring a bespoke application. [ABSTRACT FROM AUTHOR]

Background: Training in psychiatry requires specific knowledge, attitudes, and skills that are obtainable by simulation, of which the use is only recent and still needs further development. Evidence is accumulating on its effectiveness but requires further validation for medical students. We aimed to evaluate the effectiveness of a single-day optional teaching program in psychiatry by simulation for medical students and validate a scale measuring Confidence in Psychiatric Clinical Skills (CPCQ), as part of the assessment. Methods: This was a controlled study in a French University that compared (using paired-sample Student t-tests) knowledge and attitudes (university grades and CPCQ scores) before, just after teaching with simulated patients, and 2 months later. Satisfaction with the program (including the quality of the debriefing) was also investigated. The CPCQ scale was validated by assessing the factor structure, internal consistency, and test-retest reliability. Finally, a comparison was run with a control group who received the usual psychiatric instruction using covariance analyses. Results: Twenty-four medical students were included in the simulation group and 76 in the control group. Just after the simulation, knowledge and attitudes increased significantly in the simulation group. Satisfaction with the training and debriefing was very high. The CPCQ scale showed good psychometric properties: a single-factor structure, acceptable internal consistency (α = 0.73 [0.65–0.85]), and good test-retest reliability (ICC = 0.71 [0.35–0.88]). Two months after the simulation, knowledge and attitudes were significantly higher in the simulation group than the control group, despite a lack of difference in knowledge before the simulation. Conclusions: Adding a simulation program in psychiatry to the usual teaching improved the knowledge and confidence of medical students. The CPCQ scale could be used for the evaluation of educational programs. [ABSTRACT FROM AUTHOR]

Background: Congenital cytomegalovirus disease (cCMV) is common and can be fatal or cause severe sequelae. Circulating strains of cytomegalovirus carry a high number of variable or disrupted genes. One of these is UL146, a highly diverse gene with 14 distinct genotypes encoding a CXC-chemokine involved in viral dissemination. UL146 genotypes 5 and 6 lack the conserved ELR motif, potentially affecting strain virulence. Here, we investigate whether UL146 genotypes 5 and 6 were associated with congenital CMV infection.Methods: Viral DNA was extracted and UL146 sequenced from 116 neonatal dried blood spots (DBS) stored in the Danish National Biobank since 1982 and linked to registered cCMV cases through a personal identifier. These sequences were compared to UL146 control sequences obtained from CMV DNA extracted from 83 urine samples from children with suspected bacterial urinary tract infections.Results: Three non-ELR UL146 genotypes (5 and 6) were observed among the cases (2.6%) and two were observed among the controls (2.4%; P > 0.99). Additionally, no significant association with cCMV was found for the other 12 genotypes in a post-hoc analysis, although genotype 8 showed a tendency to be more frequent among cases with 12 observations against three (P = 0.10). All fourteen genotypes were found to have little intra-genotype variation. Viral load, gender, and sample age were not found to be associated with any particular UL146 genotype.Conclusions: No particular UL146 genotype was associated with cCMV in this nationwide retrospective case-control study. Associations between CMV disease and disrupted or polymorph CMV genes among immunosuppressed people living with HIV/AIDS and transplant recipients should be investigated in future studies. [ABSTRACT FROM AUTHOR]

Background: Inertial measurement units (IMUs) with high-resolution sensors such as accelerometers are now used extensively to study fine-scale behavior in a wide range of marine and terrestrial animals. Robust and practical methods are required for the computationally-demanding analysis of the resulting large datasets, particularly for automating classification routines that construct behavioral time series and time-activity budgets. Magnetometers are used increasingly to study behavior, but it is not clear how these sensors contribute to the accuracy of behavioral classification methods. Development of effective classification methodology is key to understanding energetic and life-history implications of foraging and other behaviors. Methods: We deployed accelerometers and magnetometers on four species of free-ranging albatrosses and evaluated the ability of unsupervised hidden Markov models (HMMs) to identify three major modalities in their behavior: 'flapping flight', 'soaring flight', and 'on-water'. The relative contribution of each sensor to classification accuracy was measured by comparing HMM-inferred states with expert classifications identified from stereotypic patterns observed in sensor data. Results: HMMs provided a flexible and easily interpretable means of classifying behavior from sensor data. Model accuracy was high overall (92%), but varied across behavioral states (87.6, 93.1 and 91.7% for 'flapping flight', 'soaring flight' and 'on-water', respectively). Models built on accelerometer data alone were as accurate as those that also included magnetometer data; however, the latter were useful for investigating slow and periodic behaviors such as dynamic soaring at a fine scale. Conclusions: The use of IMUs in behavioral studies produces large data sets, necessitating the development of computationally-efficient methods to automate behavioral classification in order to synthesize and interpret underlying patterns. HMMs provide an accessible and robust framework for analyzing complex IMU datasets and comparing behavioral variation among taxa across habitats, time and space. [ABSTRACT FROM AUTHOR]

Kaposi's sarcoma-associated herpesvirus (KSHV), also designated human herpesvirus 8 (HHV-8), has been linked to Kaposi's sarcoma, as well as to primary effusion lymphoma (PEL), and a subset of multicentric Castleman's disease. KSHV genomes are maintained as episomes within infected cells and the virus exhibits a biphasic life cycle consisting of a life-long latent phase during which only a few viral genes are expressed and no viral progeny are produced and a transient lytic reactivation phase, in which a full repertoire of ~ 80 lytic genes are activated in a temporally regulated manner culminating in the release of new virions. Lytic replication is initiated by a single viral protein, K-Rta (ORF50), which activates more than 80 viral genes from multiple resident viral episomes (i.e., viral chromosomes). One of the major targets of K-Rta is a long non-coding nuclear RNA, PAN RNA (polyadenylated nuclear RNA), a lncRNA that accumulates to exceedingly high levels in the nucleus during viral reactivation. K-Rta directly binds to the PAN RNA promoter and robustly activates PAN RNA expression. Although PAN RNA has been known for over 20 years, its role in viral replication is still incompletely understood. In this perspective, we will briefly review the current understanding of PAN RNA and then describe our current working model of this RNA. The model is based on our observations concerning events that occur during KSHV lytic reactivation including (i) a marked accumulation of RNA Pol II at the PAN promoter, (ii) genomic looping emanating from the PAN locus, (iii) interaction of a second viral lytic protein (ORF57) with K-Rta, PAN RNA and RNA Pol II, (iv) the essential requirement for PAN RNA expression in cis for optimal transcriptional execution needed for the entire lytic program, and (v) ORF57 recruitment of RNA Pol II to the PAN genomic locus. Together our results generate a model in which the PAN locus serves as a hub for sequestration/trapping of the cellular transcriptional machinery proximal to viral episomes. Sequestration at the PAN locus facilitates high levels of viral transcription throughout the viral genome during lytic replication. ORF57 acts as a transcription-dependent transactivator at the PAN locus by binding to both Rta and PAN to locally trap RNA Pol II. The resulting accumulation of high levels of nuclear PAN RNA created by this process is an inducible enhancer-derived (eRNA) by-product that litters the infected cell nucleus. [ABSTRACT FROM AUTHOR]

Background: Congenital cytomegalovirus (cCMV) infection is the most common congenital infection and a leading cause of long-term neurological and sensory sequelae, the most common being sensorineural hearing loss (SNHL). Despite extensive research, clinical or laboratory markers to identify CMV infected children with increased risk for disease have not been identified. This study utilizes viral whole-genome next generation-sequencing (NGS) of specimens from congenitally infected infants to explore viral diversity and specific viral variants that may be associated with symptomatic infection and SNHL.Methods: CMV DNA from urine specimens of 30 infants (17 asymptomatic, 13 symptomatic) was target enriched and next generation sequenced resulting in 93% coverage of the CMV genome allowing analysis of viral diversity.Results: Variant frequency distribution was compared between children with symptomatic and asymptomatic cCMV and those with (n = 13) and without (n = 17) hearing loss. The CMV genes UL48A, UL88, US19 and US22 were found to have an increase in nucleotide diversity in symptomatic children; while UL57, UL20, UL104, US14, UL115, and UL35 had an increase in diversity in children with hearing loss. An analysis of single variant differences between symptomatic and asymptomatic children found UL55 to have the highest number, while the most variants associated with SNHL were in the RL11 gene family. In asymptomatic infants with SNHL, mutations were observed more frequently in UL33 and UL20.Conclusion: CMV genomes from infected newborns can be mapped to 93% of the genome at a depth allowing accurate and reproducible analysis of polymorphisms for variant and gene discovery that may be linked to symptomatic and hearing loss outcomes. [ABSTRACT FROM AUTHOR]

Background: The use of accelerometers in bio-logging devices has proved to be a powerful tool for the quantification of animal behaviour. While bio-logging techniques are being used on wide range of species, to date they have only been seldom used with non-human primates. This is likely due to three main factors: the long tradition of direct field observations, a difficulty of attaching bio-logging devices to wild primates and the challenge of deciphering acceleration signals in species' with remarkable locomotor and behavioural diversity. Here, we overcome these aforementioned obstacles and provide methodology for identification of behaviours from accelerometer data of wild chacma baboons (Papio ursinus) in Cape Town, South Africa. Results: We apply machine learning techniques to process complex accelerometer data, collected by bespoke tracking collars to quantify a range of behaviours (focusing on locomotion and foraging behaviour). We successfully identify six broad state behaviours that represent 93.3% of the time budget of the baboons. Resting, walking, running and foraging were all identified with high recall and precision representing the first classification of multiple behavioural states from accelerometer data for a wild primate. Conclusion: Our 'end to end' process--from collar design and build to the collection and quantification of acceleration data--provides advantages over gathering data by traditional observation, not least because it affords data collection without the presence of an observer which may affect an animal's behaviour. Furthermore, our methodology and findings open new possibilities for the fine-scale study of movement and foraging ecology in wild primates, and in particular our baboon study population which is in conflict with people. [ABSTRACT FROM AUTHOR]

Background: GPS and accelerometer tracking presently revolutionises the fields of ecology and animal behaviour. However, the effects of tag characteristics like weight, attachment and data quality on study outcomes and animal welfare are important to consider. In this study, we compare how different tag attachment types influence the behaviour of a group of tagged large waterbirds, GPS accuracy and behaviour classification success from accelerometer data. Results: Both neckband and backpack tags had similar effects on the behaviour of six captive Canada geese (Branta canadensis), increasing the amount of discomfort behaviour in relation to untagged individuals. Both treatment groups also slightly decreased the amount of foraging, but the duration of neither vigilance nor resting was affected. GPS positions that were filtered with classical GPS platform settings (i.e. smoothing) were more accurate than positions improved by satellite-based differential augmentation. Tag attachment, however, did not induce any differences in position accuracy of both data types. Behaviour classification success was generally similar for neckband and backpack tags. But in detail, behaviours mainly performed by the head like foraging and vigilance were better detected from accelerometer data of neckband tags, whereas behaviours like resting and walking were more successfully detected from backpack tag data. Conclusion: Our findings suggest that the use of neckband or backpack tags for tracking large waterbirds and their behaviour largely depends on which behaviours are most important to detect. However, for wildlife tracking studies, factors like tag retention time are also of great importance, especially for animals like some goose species that are known to quickly destroy backpack tags. For future studies, we advise to carefully evaluate not only tag weight, but also attachment methods and data quality, because the right choice depends on the research question. This will improve the scope of wildlife tracking even more for various scientific, conservation and management applications. [ABSTRACT FROM AUTHOR]

Background: Accelerometry has been used to identify behaviours through the quantification of body posture and motion for a range of species moving in different media. This technique has not been applied to light behaviours to the same degree, having only been used to distinguish lapping from soaring light, even though identifying the type of soaring light could provide important insights into the factors underlying movement paths in soaring birds. This may be due to the complexities of interpreting acceleration data, as movement in the aerial environment may be influenced by phenomena such as centripetal acceleration (pulling-g). This study used high-resolution movement data on the light of free-living Andean condors (Vultur gryphus) and a captive Eurasian griffon vulture (Gyps fulvus) to examine the influence of gravitational, dynamic and centripetal acceleration in different light types. Flight behaviour was categorised as thermal soaring, slope soaring, gliding and lapping, using changes in altitude and heading from magnetometry data. We examined the ability of the k-nearest neighbour (KNN) algorithm to distinguish between these behaviours using acceleration data alone. Results: Values of the vectorial static body acceleration (VeSBA) suggest that these birds experience relatively little centripetal acceleration in light, though this varies between light types. Centripetal acceleration appears to be of most influence during thermal soaring; consequently, it is not possible to derive bank angle from smoothed values of lateral acceleration. In contrast, the smoothed acceleration values in the dorso-ventral axis provide insight into body pitch, which varied linearly with airspeed. Classification of passive light types via KNN was limited, with low accuracy and precision for soaring and gliding. Conclusion: The importance of soaring was evident in the high proportion of time each bird spent in this light mode (52.17-84.00 %). Accelerometry alone was limited in its ability to distinguish between passive light types, though smoothed values in the dorso-ventral axis did vary with airspeed. Other sensors, in particular the magnetometer, provided powerful methods of identifying light behaviour and these data may be better suited for automated behavioural identification. This should provide further insight into the type and strength of updraughts available to soaring birds. [ABSTRACT FROM AUTHOR]

Background: Pseudorabies virus is a widely-studied model organism of the Herpesviridae family, with a compact genome arrangement of 72 known coding sequences. In order to obtain an up-to-date genetic map of the virus, a combination of RNA-sequencing approaches were applied, as recent advancements in high-throughput sequencing methods have provided a wealth of information on novel RNA species and transcript isoforms, revealing additional layers of transcriptome complexity in several viral species. Results: The total RNA content and polyadenylation landscape of pseudorabies virus were characterized for the first time at high coverage by Illumina high-throughput sequencing of cDNA samples collected during the lytic infectious cycle. As anticipated, nearly all of the viral genome was transcribed, with the exception of loci in the large internal and terminal repeats, and several small intergenic repetitive sequences. Our findings included a small novel polyadenylated non-coding RNA near an origin of replication, and the single-base resolution mapping of 3' UTRs across the viral genome. Alternative polyadenylation sites were found in a number of genes and a novel alternative splice site was characterized in the ep0 gene, while previously known splicing events were confirmed, yielding no alternative splice isoforms. Additionally, we detected the active polyadenylation of transcripts earlier believed to be transcribed as part of polycistronic RNAs. Conclusion: To the best of our knowledge, the present work has furnished the highest-resolution transcriptome map of an alphaherpesvirus to date, and reveals further complexities of viral gene expression, with the identification of novel transcript boundaries, alternative splicing of the key transactivator EP0, and a highly abundant, novel non-coding RNA near the lytic replication origin. These advances provide a detailed genetic map of PRV for future research. [ABSTRACT FROM AUTHOR]

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Background: It has been predicted that the UL31 gene originates from the positive strand of the human cytomegalovirus (HCMV) genome, whereas the UL30 and UL32 genes originate from the complementary strand. Except for the UL32 gene, the transcription of this gene region has not been investigated extensively. Methods: Northern blotting, cDNA library screening, RACE-PCR,and RT-PCR were used. Results: At least eight transcripts of the antisense orientation of UL31 were transcribed from the UL30-UL32 region during the late phase of HCMV infection. The 30 coterminus of these transcripts was located within the predicted UL30 gene. The longest 6.0-kb transcript was initiated upstream of the predicted UL32 gene. Other transcripts were derived from the predicted UL30 and UL31 gene region. Except for the previously predicted UL32 open reading frame (ORF), three novel ORFs, named UL31anti-1, UL31anti-2 and UL31anti-3, were located in the transcripts from the UL31anti-UL32 transcription unit. No transcription was found in UL31. Conclusion: A family of novel 30 coterminal transcripts was transcribed from the UL30-UL32 gene region [ABSTRACT FROM AUTHOR]

Background: Biologging studies have revealed a wealth of information about the spatio-temporal movements of a wide range of vertebrates large enough to carry electronic tracking tags. Advances in autonomous underwater vehicles (AUVs or UAVs) and unmanned aerial vehicles (commonly known as drones), which can carry far larger payloads of sensor technologies, have revealed insights into the environment through which animals travel. Some AUVs have been used to film target animals, but are generally limited to periods as long as a drone operator can actively follow an animal. In the present study, we use an AUV, the REMUS-100 SharkCam, paired with a custom transponder tag attached to the shark, to autonomously follow three basking sharks for a cumulative total of 10.9 h to collect video and environmental data on their sub-surface behaviour. The basking shark is the second largest fish in the world and is endangered globally, but despite being subject to various biologging studies, little is known of this species breeding ecology and their mating grounds remain unknown. Results: We detail the first successful autonomous tracking of basking sharks, comprising three missions that filmed basking sharks in mid-water and close to benthic habitats. Sharks spent very little time feeding, and travelled relatively close to sandy, rocky and algae-covered benthos. One basking shark was observed defecating. Conspecifics were not observed in the three missions, nor were courtship or breeding behaviours. AUV offset distances for videography were determined iteratively through tracking. These offsets varied depending on the trade-off of between water clarity and proximity of the AUV for obtaining useful video data and directly influencing shark behaviour. Conclusions: The present study is the first successful use of an AUV to gain insight into the sub-surface behaviour of basking sharks. [ABSTRACT FROM AUTHOR]

Background: Alcoholic liver disease (ALD) is the leading cause of liver transplantation (LT). The magnitude and risk factors of post-LT alcohol relapse are not well described. We conducted a meta-analysis to evaluate alcohol relapse rate and its predictors after LT.Methods: Searches of MEDLINE and SCOPUS identified eligible published studies of alcohol relapse after LT published up to 31 March 2018. Alcohol relapse was defined as any alcohol consumption post-LT, and heavy alcohol relapse was defined as a relapse of alcohol consumption that was associated with a significant harm. Data for the proportion of alcohol relapse was pooled using a meta-analysis for pooling proportion. An odds ratio (OR) of the predictor of alcohol relapse was extracted and pooled using meta-analysis for the pooling risk factor. Data were analyzed using a random effect model if heterogeneity was presented; otherwise, a fixed effect model was applied. The study was registered at PROSPERO (CRD42017052659).Results: Ninety-two studies with over 8000 cases were recruited for pooling proportion of alcohol relapse. The alcohol relapse rate and heavy alcohol relapse rate after LT during the mean follow-up time of 48.4 ± 24.7 months were 22% (95% confidence interval (CI): 19-25%) and 14% (95%CI: 12-16%). Psychiatric comorbidities (odds ratio (OR) 3.46, 95%CI: 1.87-6.39), pre-transplant abstinence of less than 6 months (OR 2.76, 95%CI: 2.10-3.61), unmarried status (OR 1.84, 95%CI: 1.39-2.43), and smoking (OR 1.72, 95%CI: 1.21-2.46) were associated with alcohol relapse after LT. However, we noticed publication bias of unpublished negative studies and high heterogeneity of results.Conclusions: Post-transplant alcohol relapse occurred in about one-fifth of patients who underwent alcohol-related LT. Psychiatric comorbidities represented the strongest predictor of alcohol relapse. Psychiatric comorbidities monitoring and pre-LT alcohol abstinence for at least 6 months may decrease alcohol relapse after LT. [ABSTRACT FROM AUTHOR]

Background: Classifying behaviour with animal-borne accelerometers is quickly becoming a popular tool for remotely observing behavioural states in a variety of species. Most accelerometry work in pinnipeds has focused on classifying behaviour at sea often quantifying behavioural trade-offs associated with foraging and diving in income breeders. Very little work to date has been done to resolve behaviour during the critical period of lactation in a capital breeder. Capital breeding phocids possess finite reserves that they must allocate appropriately to maintain themselves and their new offspring during their brief nursing period. Within this short time, fine-scale behavioural trade-offs can have significant fitness consequences for mother and offspring and must be carefully managed. Here, we present a case study in extracting and classifying lactation behaviours in a wild, breeding pinniped, the grey seal (Halichoerus grypus). Results: Using random forest models, we were able to resolve 4 behavioural states that constitute the majority of a female grey seals' activity budget during lactation. Resting, alert, nursing, and a form of pup interaction were extracted and classified reliably. For the first time, we quantified the potential confounding variance associated with individual differences in a wild context as well as differences due to sampling location in a largely inactive model species. Conclusions: At this stage, the majority of a female grey seal's activity budget was classified well using accelerometers, but some rare and context-dependent behaviours were not well captured. While we did find significant variation between individuals in behavioural mechanics, individuals did not differ significantly within themselves; inter-individual variability should be an important consideration in future efforts. These methods can be extended to other efforts to study grey seals and other pinnipeds who exhibit a capital breeding system. Using accelerometers to classify behaviour during lactation allows for fine-scale assessments of time and energy trade-offs for species with fixed stores. [ABSTRACT FROM AUTHOR]