Qualitative Behavioural Assessment as a welfare indicator for farmed Atlantic salmon (Salmo salar) in response to a stressful challenge.

Animal welfare assessments have struggled to investigate the emotional states of animals while focusing solely on available empirical evidence. Qualitative Behavioural Assessment (QBA) may provide insights into an animal's subjective experiences without compromising scientific rigor. Rather than assessing explicit, physical behaviours (i.e., what animals are doing, such as swimming or feeding), QBA describes and quantifies the overall expressive manner in which animals execute those behaviours (i.e., how relaxed or agitated they appear). While QBA has been successfully applied to scientific welfare assessments in a variety of species, its application within aquaculture remains largely unexplored. This study aimed to assess QBA's effectiveness in capturing changes in the emotional behaviour of Atlantic salmon following exposure to a stressful challenge. Nine tanks of juvenile Atlantic salmon were video-recorded every morning for 15 min over a 7-day period, in the middle of which a stressful challenge (intrusive sampling) was conducted on the salmon. The resultant 1-min, 63 video clips were then semi-randomised to avoid predictability and treatment bias for QBA scorers. Twelve salmon-industry professionals generated a list of 16 qualitative descriptors (e.g., relaxed, agitated, stressed) after viewing unrelated video-recordings depicting varying expressive characteristics of salmon in different contexts. A different group of 5 observers, with varied experience of salmon farming, subsequently scored the 16 descriptors for each clip using a Visual Analogue Scale (VAS). Principal Components Analysis (correlation matrix, no rotation) was used to identify perceived patterns of expressive characteristics across the video-clips, which revealed 4 dimensions explaining 74.5% of the variation between clips. PC1, ranging from 'relaxed/content/positive active' to 'unsettled/stressed/spooked/skittish' explained the highest percentage of variation (37%). QBA scores for video-clips on PC1, PC2, and PC4 achieved good inter- and intra-observer reliability. Linear Mixed Effects Models, controlled for observer variation in PC1 scores, showed a significant difference between PC1 scores before and after sampling (p = 0.03), with salmon being perceived as more stressed afterwards. PC1 scores also correlated positively with darting behaviours (r = 0.42, p < 0.001). These results are the first to report QBA's sensitivity to changes in expressive characteristics of salmon following a putatively stressful challenge, demonstrating QBA's potential as a welfare indicator within aquaculture.

Mycena species can be opportunist-generalist plant root invaders.

Traditional strict separation of fungi into ecological niches as mutualist, parasite or saprotroph is increasingly called into question. Sequences of assumed saprotrophs have been amplified from plant root interiors, and several saprotrophic genera can invade and interact with host plants in laboratory growth experiments. However, it is uncertain if root invasion by saprotrophic fungi is a widespread phenomenon and if laboratory interactions mirror field conditions. Here, we focused on the widespread and speciose saprotrophic genus Mycena and performed (1) a systematic survey of their occurrences (in ITS1/ITS2 datasets) in mycorrhizal roots of 10 plant species, and (2) an analysis of natural abundances of 13 C/15 N stable isotope signatures of Mycena basidiocarps from five field locations to examine their trophic status. We found that Mycena was the only saprotrophic genus consistently found in 9 out of 10 plant host roots, with no indication that the host roots were senescent or otherwise vulnerable. Furthermore, Mycena basidiocarps displayed isotopic signatures consistent with published 13 C/15 N profiles of both saprotrophic and mutualistic lifestyles, supporting earlier laboratory-based studies. We argue that Mycena are widespread latent invaders of healthy plant roots and that Mycena species may form a spectrum of interactions besides saprotrophy also in the field.

A new approach to characterising and predicting crop rotations using national-scale annual crop maps.

Cropping decisions affect the nature, timing and intensity of agricultural management strategies. Specific crop rotations are associated with different environmental impacts, which can be beneficial or detrimental. The ability to map, characterise and accurately predict rotations enables targeting of mitigation measures where most needed and forecasting of potential environmental risks. Using six years of the national UKCEH Land Cover® plus: Crops maps (2015-2020), we extracted crop sequences for every agricultural field parcel in Great Britain (GB). Our aims were to first characterise spatial patterns in rotation properties over a national scale based on their length, type and structural diversity values, second, to test an approach to predicting the next crop in a rotation, using transition probability matrices, and third, to test these predictions at a range of spatial scales. Strict cyclical rotations only occupy 16 % of all agricultural land, whereas long-term grassland and complex-rotational agriculture each occupy over 40 %. Our rotation classifications display a variety of distinctive spatial patterns among rotation lengths, types and diversity values. Rotations are mostly 5 years in length, short mixed crops are the most abundant rotation type, and high structural diversity is concentrated in east Scotland. Predictions were most accurate when using the most local spatial approach (spatial scaling), 5-year rotations, and including long-term grassland. The prediction framework we built demonstrates that our crop predictions have an accuracy of 36-89 %, equivalent to classification accuracy of national crop and land cover mapping using earth observation, and we suggest this could be improved with additional contextual data. Our results emphasise that rotation complexity is multi-faceted, yet it can be mapped in different ways and forms the basis for further exploration in and beyond agronomy, ecology, and other disciplines.

ROBITT: A tool for assessing the risk-of-bias in studies of temporal trends in ecology.

Aggregated species occurrence and abundance data from disparate sources are increasingly accessible to ecologists for the analysis of temporal trends in biodiversity. However, sampling biases relevant to any given research question are often poorly explored and infrequently reported; this can undermine statistical inference. In other disciplines, it is common for researchers to complete 'risk-of-bias' assessments to expose and document the potential for biases to undermine conclusions. The huge growth in available data, and recent controversies surrounding their use to infer temporal trends, indicate that similar assessments are urgently needed in ecology.We introduce ROBITT, a structured tool for assessing the 'Risk-Of-Bias In studies of Temporal Trends in ecology'. ROBITT has a similar format to its counterparts in other disciplines: it comprises signalling questions designed to elicit information on the potential for bias in key study domains. In answering these, users will define study inferential goal(s) and relevant statistical target populations. This information is used to assess potential sampling biases across domains relevant to the research question (e.g. geography, taxonomy, environment), and how these vary through time. If assessments indicate biases, then users must clearly describe them and/or explain what mitigating action will be taken.Everything that users need to complete a ROBITT assessment is provided: the tool, a guidance document and a worked example. Following other disciplines, the tool and guidance document were developed through a consensus-forming process across experts working in relevant areas of ecology and evidence synthesis.We propose that researchers should be strongly encouraged to include a ROBITT assessment when publishing studies of biodiversity trends, especially when using aggregated data. This will help researchers to structure their thinking, clearly acknowledge potential sampling issues, highlight where expert consultation is required and provide an opportunity to describe data checks that might go unreported. ROBITT will also enable reviewers, editors and readers to establish how well research conclusions are supported given a dataset combined with some analytical approach. In turn, it should strengthen evidence-based policy and practice, reduce differing interpretations of data and provide a clearer picture of the uncertainties associated with our understanding of reality.

The utility of flow cytometric platelet forward scatter as an alternative to mean platelet volume.

The use of mean platelet diameter (MPD) to classify inherited thrombocytopenia (IT) has been demonstrated in several studies. Alternatively, the mean platelet volume (MPV) may be used, but in macrothrombocytopenia this may not be available. We hypothesized that platelet forward scatter (FSC) measurements using flow cytometry may be used for the size-based classification of IT. The study aimed to assess the ability of platelet FSC to measure platelet size and whether it could be used as an alternative to the MPD or MPV.Blood samples were obtained from individuals undergoing investigation for inherited platelet function disorders (IPFD, n = 40) or platelet number disorders (IPND, n = 46). A hematology analyzer was used to obtain MPV and platelet counts, flow cytometry to measure platelet FSC and ImageJ software to measure MPD from stained blood smears. The International Society of Thrombosis and Hemostasis (ISTH) Bleeding Assessment Tool (BAT) was used to calculate bleeding scores.Twenty-nine(63%) of IPND patients had an MPV that could not be reported. A significant correlation to platelet FSC was found to the MPD (p < .0001) and MPV (p < .0001) and an inverse correlation with platelet count (p < .0001). No significant correlation was found between FSC and bleeding history. In conclusion, platelet FSC is an alternative to MPV and may be used in macrothrombocytopenia where the MPV is not recorded.

Veterinary drug therapies used for undesirable behaviours in UK dogs under primary veterinary care.

Undesirable behaviours (UBs) in dogs are common and important issues with serious potential welfare consequences for both the dogs and their owners. This study aimed to investigate the usage of drug therapy for UBs in dogs and assess demographic risk factors for drug-prescribed UBs within the dog population under primary-care veterinary care in the UK in 2013. Dogs receiving drug therapy for UB were identified through the retrospective analysis of anonymised electronic patient records in VetCompass™. Risk factor analysis used multivariable logistic regression modelling. The study population comprised 103,597 dogs under veterinary care in the UK during 2013. There were 413 drug-prescribed UBs recorded among 404 dogs. The prevalence of dogs with at least one UB event treated with a drug in 2013 was 0.4%. Multivariable modelling identified 3 breeds with increased odds of drug-prescribed UB compared with crossbred dogs: Toy Poodle (OR 2.75), Tibetan Terrier (OR 2.68) and Shih-tzu (OR 1.95). Increasing age was associated with increased odds of drug-prescribed UB, with dogs ≥ 12 years showing 3.1 times the odds compared with dogs < 3 years. Neutered males (OR 1.82) and entire males (OR 1.50) had increased odds compared with entire females. The relatively low prevalence of dogs with at least one UB event that was treated with a drug in 2013 could suggest that opportunities for useful psychopharmaceutical intervention in UBs may be being missed in first opinion veterinary practice. While bodyweight was not a significant factor, the 3 individual breeds at higher odds of an UB treated with a behaviour modifying drug all have a relatively low average bodyweight. The current results also support previous research of a male predisposition to UBs and it is possible that this higher risk resulted in the increased likelihood of being prescribed a behaviour modifying drug, regardless of neuter status.

Qualitative Behavioral Assessment in Juvenile Farmed Atlantic Salmon (Salmo salar): Potential for On-Farm Welfare Assessment.

There is a growing scientific and legislative consensus that fish are sentient, and therefore have the capacity to experience pain and suffering. The assessment of the welfare of farmed fish is challenging due to the aquatic environment and the number of animals housed together. However, with increasing global production and intensification of aquaculture comes greater impetus for developing effective tools which are suitable for the aquatic environment to assess the emotional experience and welfare of farmed fish. This study therefore aimed to investigate the use of Qualitative Behavioral Assessment (QBA), originally developed for terrestrial farmed animals, in farmed salmon and evaluate its potential for use as a welfare monitoring tool. QBA is a "whole animal" approach based on the description and quantification of the expressive qualities of an animal's dynamic style of behaving, using descriptors such as relaxed, agitated, lethargic, or confident. A list of 20 qualitative descriptors was generated by fish farmers after viewing video-footage showing behavior expressions representative of the full repertoire of salmon in this context. A separate, non-experienced group of 10 observers subsequently watched 25 video clips of farmed salmon, and scored the 20 descriptors for each clip using a Visual Analog Scale (VAS). To assess intra-observer reliability each observer viewed the same 25 video clips twice, in two sessions 10 days apart, with the second clip set presented in a different order. The observers were unaware that the two sets of video clips were identical. Data were analyzed using Principal Component (PC) Analysis (correlation matrix, no rotation), revealing four dimensions that together explained 79% of the variation between video clips, with PC1 (Tense/anxious/skittish-Calm/mellow/relaxed) explaining the greatest percentage of variation (56%). PC1 was the only dimension to show acceptable inter- and intra-observer reliability, and mean PC1 scores correlated significantly to durations of slow and erratic physical movements measured for the same 25 video clips. Further refinements to the methodology may be necessary, but this study is the first to provide evidence for the potential of Qualitative Behavioral Assessment to serve as a time-efficient welfare assessment tool for juvenile salmon under farmed conditions.

Long-term effects of atmospheric deposition on British plant species richness.

The effects of atmospheric pollution on plant species richness (nsp) are of widespread concern. We carried out a modelling exercise to estimate how nsp in British semi-natural ecosystems responded to atmospheric deposition of nitrogen (Ndep) and sulphur (Sdep) between 1800 and 2010. We derived a simple four-parameter equation relating nsp to measured soil pH, and to net primary productivity (NPP), calculated with the N14CP ecosystem model. Parameters were estimated from a large data set (n = 1156) of species richness in four vegetation classes, unimproved grassland, dwarf shrub heath, peatland, and broadleaved woodland, obtained in 2007. The equation performed reasonably well in comparisons with independent observations of nsp. We used the equation, in combination with modelled estimates of NPP (from N14CP) and soil pH (from the CHUM-AM hydrochemical model), to calculate changes in average nsp over time at seven sites across Britain, assuming that variations in nsp were due only to variations in atmospheric deposition. At two of the sites, two vegetation classes were present, making a total of nine site/vegetation combinations. In four cases, nsp was affected about equally by pH and NPP, while in another four the effect of pH was dominant. The ninth site, a chalk grassland, was affected only by NPP, since soil pH was assumed constant. Our analysis suggests that the combination of increased NPP, due to fertilization by Ndep, and decreased soil pH, primarily due to Sdep, caused an average species loss of 39% (range 23-100%) between 1800 and the late 20th Century. The modelling suggests that in recent years nsp has begun to increase, almost entirely due to reductions in Sdep and consequent increases in soil pH, but there are also indications of recent slight recovery from the eutrophying effects of Ndep.

Data Integration for Large-Scale Models of Species Distributions.

With the expansion in the quantity and types of biodiversity data being collected, there is a need to find ways to combine these different sources to provide cohesive summaries of species' potential and realized distributions in space and time. Recently, model-based data integration has emerged as a means to achieve this by combining datasets in ways that retain the strengths of each. We describe a flexible approach to data integration using point process models, which provide a convenient way to translate across ecological currencies. We highlight recent examples of large-scale ecological models based on data integration and outline the conceptual and technical challenges and opportunities that arise.

Assessment of a large number of empirical plant species niche models by elicitation of knowledge from two national experts.

Quantitative models play an increasing role in exploring the impact of global change on biodiversity. To win credibility and trust, they need validating. We show how expert knowledge can be used to assess a large number of empirical species niche models constructed for the British vascular plant and bryophyte flora. Key outcomes were (a) scored assessments of each modeled species and niche axis combination, (b) guidance on models needing further development, (c) exploration of the trade-off between presenting more complex model summaries, which could lead to more thorough validation, versus the longer time these take to evaluate, (d) quantification of the internal consistency of expert opinion based on comparison of assessment scores made on a random subset of models evaluated by both experts. Overall, the experts assessed 39% of species and niche axis combinations to be "poor" and 61% to show a degree of reliability split between "moderate" (30%), "good" (25%), and "excellent" (6%). The two experts agreed in only 43% of cases, reaching greater consensus about poorer models and disagreeing most about models rated as better by either expert. This low agreement rate suggests that a greater number of experts is required to produce reliable assessments and to more fully understand the reasons underlying lack of consensus. While area under curve (AUC) statistics showed generally very good ability of the models to predict random hold-out samples of the data, there was no correspondence between these and the scores given by the experts and no apparent correlation between AUC and species prevalence. Crowd-sourcing further assessments by allowing web-based access to model fits is an obvious next step. To this end, we developed an online application for inspecting and evaluating the fit of each niche surface to its training data.

Integration of ground survey and remote sensing derived data: Producing robust indicators of habitat extent and condition.

The availability of suitable habitat is a key predictor of the changing status of biodiversity. Quantifying habitat availability over large spatial scales is, however, challenging. Although remote sensing techniques have high spatial coverage, there is uncertainty associated with these estimates due to errors in classification. Alternatively, the extent of habitats can be estimated from ground-based field survey. Financial and logistical constraints mean that on-the-ground surveys have much lower coverage, but they can produce much higher quality estimates of habitat extent in the areas that are surveyed. Here, we demonstrate a new combined model which uses both types of data to produce unified national estimates of the extent of four key habitats across Great Britain based on Countryside Survey and Land Cover Map. This approach considers that the true proportion of habitat per km2 (Zi ) is unobserved, but both ground survey and remote sensing can be used to estimate Zi . The model allows the relationship between remote sensing data and Zi to be spatially biased while ground survey is assumed to be unbiased. Taking a statistical model-based approach to integrating field survey and remote sensing data allows for information on bias and precision to be captured and propagated such that estimates produced and parameters estimated are robust and interpretable. A simulation study shows that the combined model should perform best when error in the ground survey data is low. We use repeat surveys to parameterize the variance of ground survey data and demonstrate that error in this data source is small. The model produced revised national estimates of broadleaved woodland, arable land, bog, and fen, marsh and swamp extent across Britain in 2007.

Model-based hypervolumes for complex ecological data.

Developing a holistic understanding of the ecosystem impacts of global change requires methods that can quantify the interactions among multiple response variables. One approach is to generate high dimensional spaces, or hypervolumes, to answer ecological questions in a multivariate context. A range of statistical methods has been applied to construct hypervolumes but have not yet been applied in the context of ecological data sets with spatial or temporal structure, for example, where the data are nested or demonstrate temporal autocorrelation. We outline an approach to account for data structure in quantifying hypervolumes based on the multivariate normal distribution by including random effects. Using simulated data, we show that failing to account for structure in data can lead to biased estimates of hypervolume properties in certain contexts. We then illustrate the utility of these "model-based hypervolumes" in providing new insights into a case study of afforestation effects on ecosystem properties where the data has a nested structure. We demonstrate that the model-based generalization allows hypervolumes to be applied to a wide range of ecological data sets and questions.

Periparturient Behavior and Physiology: Further Insight Into the Farrowing Process for Primiparous and Multiparous Sows.

Giving birth is a critical time for many species and is often the most painful event ever experienced by females. In domestic species, like the pig, pain associated with parturition represents a potential welfare concern, and the consequences of pain can cause economic losses (e.g., by indirectly contributing to piglet mortality as pain could slow post-farrowing recovery, reduce food and water intake, reducing milk let-down). This study investigated pain assessment and its management in primiparous (gilts) and multiparous (sows) breeding pigs, including the provision of a non-steroidal anti-inflammatory drug (NSAID) post-parturition. Individuals were randomly allocated to receive the NSAID ketoprofen (3 mg/kg bodyweight) (n = 11 gilts, 16 sows) or the equivalent volume of saline (n = 13 gilts, 16 sows) by intramuscular injection 1.5 h after the birth of the last piglet. Data collected included putative behavioral indicators of pain (back leg forward, tremble, back arch), salivary cortisol concentrations pre-farrowing and up to 7 days post-injection. In addition, post-partum biomarkers of inflammation, including the acute phase protein C-reactive protein (CRP) and 3 porcine cytokines [interleukin-1 ß (IL1 ß), interleukin-6 (IL6), and tumor necrosis factor α (TNF α)] were measured in plasma collected 6 h following the injection. Behaviors were analyzed using generalized linear mixed models, and physiological variables with linear mixed models. No difference in putative pain behaviors, salivary cortisol, CRP, or cytokines were found between individuals treated with ketoprofen or those administered the saline control. However, there were some differences between gilts and sows, as sows exhibited more putative pain behavior than gilts, had higher salivary cortisol on the day of farrowing and had higher plasma TNF α. Conversely, gilts had higher salivary cortisol than sows on day 3 post-farrowing and had higher CRP. This indicates that, like human females, multiparous sows experience more pain from uterine activity following birth than primiparas. This study provides useful information for developing management practices relating to post-farrowing care for breeding pigs.

The identification of potential behavioural indicators of pain in periparturient sows.

Periparturient pain is a welfare concern and could contribute to piglet losses. This has led to studies investigating post-farrowing analgesia. A clear reduction in pain has not been demonstrated, partly due to a lack of pain indicators. This study quantified behaviours as potential pain indicators (PPIn) in sows: i) before, during and after farrowing, and ii) 2min before and after piglet births. Twenty-five sows were observed during and after, and ten pre-farrowing. Behaviour recorded included: 1) back leg forward (back leg pulled forward and/or in); 2) tremble (movement as if shivering); 3) back arch (leg(s) stretch forming an arched back); 4) paw (leg scraped in pawing motion); and 5) tail flick (tail moved rapidly up and down). Behaviours were analysed using generalized linear models and Spearman's rank correlations. All PPIn were rare or absent pre-farrowing, highest during farrowing, and back leg forward, tremble and back arch were greater in the early post-farrowing period. Several significant positive correlations between PPIn during and post-farrowing were found. Back arch, tail flick and paw were higher before than after a piglet birth, and were more frequent earlier in the birth order. Back leg forward and tremble did not differ before and after births, and tremble increased with birth order. These behaviours, which were absent or rare pre-farrowing, present during farrowing and were lower afterwards, and showed consistent individual variation, may be quantitatively associated with pain. Spontaneous behaviours could be used to test the efficacy of analgesics or identify sows that may benefit.

Effects of antiplatelet therapy on platelet extracellular vesicle release and procoagulant activity in health and in cardiovascular disease.

Dual antiplatelet therapy with aspirin and clopidogrel is commonly used to prevent recurrent ischemic events in patients with cardiovascular disease. Whilst their effects on platelet reactivity are well documented, it is unclear, however, whether antiplatelet therapy inhibits platelet extracellular vesicle (EV) release. The aim of this study was to investigate the effects of antiplatelet therapy on platelet EV formation and procoagulant activity. Blood samples from 10 healthy controls not receiving antiplatelet therapy were incubated in vitro with aspirin or a P2Y12 inhibitor (MeSAMP). Blood samples from 50 patients receiving long-term dual antiplatelet therapy and undergoing coronary angiography were also studied. Platelet reactivity was assessed by Multiplate™ impedance aggregometry. Platelet EV formation and procoagulant activity of pretreated and untreated blood samples in response to arachidonic acid (AA), adenosine diphosphate (ADP), ADP+PGE1, and thrombin receptor-activating peptide (TRAP) stimulation were assessed by flow cytometry and Procoag-PL assays, respectively. Incubation of normal platelets with aspirin significantly inhibited AA-induced platelet reactivity, EV formation, and procoagulant activity, whilst MeSAMP significantly inhibited platelet reactivity and EV formation in response to AA, ADP, and TRAP, but had minimal effect on procoagulant activity. Most patients receiving dual antiplatelet therapy showed an appropriate reduction in platelet reactivity in response to their treatment; however there was not complete inhibition of increased platelet and EV procoagulant activity in response to ADP, AA, or TRAP. In addition, we could not find any correlation between platelet reactivity and procoagulant activity in patients receiving dual antiplatelet therapy.

Spatial patterns and environmental constraints on ecosystem services at a catchment scale.

Improved understanding and prediction of the fundamental environmental controls on ecosystem service supply across the landscape will help to inform decisions made by policy makers and land-water managers. To evaluate this issue for a local catchment case study, we explored metrics and spatial patterns of service supply for water quality regulation, agriculture production, carbon storage, and biodiversity for the Macronutrient Conwy catchment. Methods included using ecosystem models such as LUCI and JULES, integration of national scale field survey datasets, earth observation products and plant trait databases, to produce finely resolved maps of species richness and primary production. Analyses were done with both 1×1km gridded and subcatchment data. A common single gradient characterised catchment scale ecosystem services supply with agricultural production and carbon storage at opposing ends of the gradient as reported for a national-scale assessment. Species diversity was positively related to production due to the below national average productivity levels in the Conwy combined with the unimodal relationship between biodiversity and productivity at the national scale. In contrast to the national scale assessment, a strong reduction in water quality as production increased was observed in these low productive systems. Various soil variables were tested for their predictive power of ecosystem service supply. Soil carbon, nitrogen, their ratio and soil pH all had double the power of rainfall and altitude, each explaining around 45% of variation but soil pH is proposed as a potential metric for ecosystem service supply potential as it is a simple and practical metric which can be carried out in the field with crowd-sourcing technologies now available. The study emphasises the importance of considering multiple ecosystem services together due to the complexity of covariation at local and national scales, and the benefits of exploiting a wide range of metrics for each service to enhance data robustness.

Longitudinal changes in hemostatic parameters and reduced pulsatility contribute to non-surgical bleeding in patients with centrifugal continuous-flow left ventricular assist devices.

BACKGROUND: Bleeding and thromboembolic events are identified complications in patients supported with newer centrifugal continuous-flow left ventricular assist devices (cfLVADs). Bleeding events have been associated with acquired von Willebrand syndrome (vWS) in these patients, though longitudinal changes and the effect of pulsatility remain unquantified. We evaluated longitudinal effects of third-generation cfLVADs on hemostatic biomarkers, non-surgical bleeding, and thromboembolic events. We investigated the association between pulsatility (as defined by aortic valve opening) on von Willebrand Factor (VWF) profile and bleeding. METHODS: We prospectively studied 28 patients implanted with the HeartWare (HeartWare International, Framingham, MA) cfLVAD for up to 360 days. We performed bleeding and coagulation assays 8 times from pre-implant to Day 360 (D360) post-implant, including platelet aggregometry, VWF collagen binding activity-to-antigen (CBA/Ag) ratio, thromboelastography, soluble P-selectin, platelet-specific marker soluble glycoprotein VI (sGPVI), and platelet microparticles. Aortic valve opening was assessed by echocardiography at each assessment. Bleeding and thromboembolic events were documented. RESULTS: Bleeding events occurred in 14 patients (50%). Maximal platelet inhibition occurred by D30. VWF profile impairment (VWF CBA/Ag < 0.8) was demonstrated in 89% of patients at D30, with subsequent recovery but further deterioration after D180. Bleeding was associated with elevated pre-implant sGPVI (p = 0.008). Pulsatility was associated with higher VWF CBA/Ag (p = 0.02) and a trend to less bleeding. CONCLUSIONS: Third-generation cfLVADs were associated with longitudinal changes in hemostatic markers, and bleeding was associated with elevated pre-implant plasma sGPVI. Further, pulsatility may contribute to recovery of the VWF profile and potentially lower bleeding risk.

Acoustic detection of biosonar activity of deep diving odontocetes at Josephine Seamount High Seas Marine Protected Area.

The temporal occurrence of deep diving cetaceans in the Josephine Seamount High Seas Marine Protected Area (JSHSMPA), south-west Portugal, was monitored using a passive acoustic recorder. The recorder was deployed on 13 May 2010 at a depth of 814 m during the North Atlantic Treaty Organization Centre for Maritime Research and Experimentation cruise "Sirena10" and recovered on 6 June 2010. The recorder was programmed to record 40 s of data every 2 min. Acoustic data analysis, for the detection and classification of echolocation clicks, was performed using automatic detector/classification systems: M3R (Marine Mammal Monitoring on Navy Ranges), a custom matlab program, and an operator-supervised custom matlab program to assess the classification performance of the detector/classification systems. M3R CS-SVM algorithm contains templates to detect beaked whales, sperm whales, blackfish (pilot and false killer whales), and Risso's dolphins. The detections of each group of odontocetes was monitored as a function of time. Blackfish and Risso's dolphins were detected every day, while beaked whales and sperm whales were detected almost every day. The hourly distribution of detections reveals that blackfish and Risso's dolphins were more active at night, while beaked whales and sperm whales were more active during daylight hours.

Strong altitudinal partitioning in the distributions of ectomycorrhizal fungi along a short (300 m) elevation gradient.

Changes in species richness and distributions of ectomycorrhizal (ECM) fungal communities along altitudinal gradients have been attributed to changes in both host distributions and abiotic variables. However, few studies have considered altitudinal relationships of ECM fungi associated with a single host to identify the role of abiotic drivers. To address this, ECM fungal communities associated with one host were assessed along five altitudinal transects in Scotland. Roots of Scots pine (Pinus sylvestris) were collected from sites between 300 and 550-600 m altitude, and ECM fungal communities were identified by 454 pyrosequencing of the fungal internal transcribed spacer (ITS) region. Soil moisture, temperature, pH, carbon : nitrogen (C : N) ratio and organic matter content were measured as potential predictors of fungal species richness and community composition. Altitude did not affect species richness of ECM fungal communities, but strongly influenced fungal community composition. Shifts in community composition along the altitudinal gradient were most clearly related to changes in soil moisture and temperature. Our results show that a 300 m altitudinal gradient produced distinct shifts in ECM fungal communities associated with a single host, and that this pattern was strongly related to climatic variables. This finding suggests significant climatic niche partitioning among ECM fungal species.