Dense sampling of bird diversity increases power of comparative genomics.

Whole-genome sequencing projects are increasingly populating the tree of life and characterizing biodiversity1-4. Sparse taxon sampling has previously been proposed to confound phylogenetic inference5, and captures only a fraction of the genomic diversity. Here we report a substantial step towards the dense representation of avian phylogenetic and molecular diversity, by analysing 363 genomes from 92.4% of bird families-including 267 newly sequenced genomes produced for phase II of the Bird 10,000 Genomes (B10K) Project. We use this comparative genome dataset in combination with a pipeline that leverages a reference-free whole-genome alignment to identify orthologous regions in greater numbers than has previously been possible and to recognize genomic novelties in particular bird lineages. The densely sampled alignment provides a single-base-pair map of selection, has more than doubled the fraction of bases that are confidently predicted to be under conservation and reveals extensive patterns of weak selection in predominantly non-coding DNA. Our results demonstrate that increasing the diversity of genomes used in comparative studies can reveal more shared and lineage-specific variation, and improve the investigation of genomic characteristics. We anticipate that this genomic resource will offer new perspectives on evolutionary processes in cross-species comparative analyses and assist in efforts to conserve species.

Thiamine Deficiency Increases Intrinsic Excitability of Mouse Cerebellar Purkinje Cells.

Thiamine deficiency is associated with cerebellar dysfunction; however, the consequences of thiamine deficiency on the electrophysiological properties of cerebellar Purkinje cells are poorly understood. Here, we evaluated these parameters in brain slices containing cerebellar vermis. Adult mice were maintained for 12-13 days on a thiamine-free diet coupled with daily injections of pyrithiamine, an inhibitor of thiamine phosphorylation. Morphological analysis revealed a 20% reduction in Purkinje cell and nuclear volume in thiamine-deficient animals compared to feeding-matched controls, with no reduction in cell count. Under whole-cell current clamp, thiamine-deficient Purkinje cells required significantly less current injection to fire an action potential. This reduction in rheobase was not due to a change in voltage threshold. Rather, thiamine-deficient neurons presented significantly higher input resistance specifically in the voltage range just below threshold, which increases their sensitivity to current at these critical membrane potentials. In addition, thiamine deficiency caused a significant decrease in the amplitude of the action potential afterhyperpolarization, broadened the action potential, and decreased the current threshold for depolarization block. When thiamine-deficient animals were allowed to recover for 1 week on a normal diet, rheobase, threshold, action potential half-width, and depolarization block threshold were no longer different from controls. We conclude that thiamine deficiency causes significant but reversible changes to the electrophysiology properties of Purkinje cells prior to pathological morphological alterations or cell loss. Thus, the data obtained in the present study indicate that increased excitability of Purkinje cells may represent a leading indicator of cerebellar dysfunction caused by lack of thiamine.

Systematic review and meta-analysis on the role of mitochondrial cytochrome c oxidase in Alzheimer's disease.

OBJECTIVE: The present study was designed to test the hypothesis that there is a reduction in the activity of the enzyme cytochrome c oxidase (Cox) in Alzheimer's disease (AD). METHODS: Systematic review of literature and meta-analysis were used with data obtained from the PubMed, Scopus, MEDLINE, Lilacs, Eric and Cochrane. The keywords were Alzheimer's AND Cox AND mitochondria; Alzheimer's AND Cox AND mitochondria; Alzheimer's AND complex IV AND mitochondria. A total of 1372 articles were found, 23 of them fitting the inclusion criteria. The data were assembled in an Excel spreadsheet and analysed using the RevMan software. A random effects model was adopted to the estimative of the effect. RESULTS: The data shows a significant decrease in the activity of the Cox AD patients and animal models. CONCLUSION: Cox enzyme may be an important molecular component involved in the mechanisms underlying AD. Therefore, this enzyme may represent a possible new biomarker for the disease as a complementary diagnosis and a new treatment target for AD.

On-Ground Vineyard Reconstruction Using a LiDAR-Based Automated System.

Crop 3D modeling allows site-specific management at different crop stages. In recent years, light detection and ranging (LiDAR) sensors have been widely used for gathering information about plant architecture to extract biophysical parameters for decision-making programs. The study reconstructed vineyard crops using light detection and ranging (LiDAR) technology. Its accuracy and performance were assessed for vineyard crop characterization using distance measurements, aiming to obtain a 3D reconstruction. A LiDAR sensor was installed on-board a mobile platform equipped with an RTK-GNSS receiver for crop 2D scanning. The LiDAR system consisted of a 2D time-of-flight sensor, a gimbal connecting the device to the structure, and an RTK-GPS to record the sensor data position. The LiDAR sensor was facing downwards installed on-board an electric platform. It scans in planes perpendicular to the travel direction. Measurements of distance between the LiDAR and the vineyards had a high spatial resolution, providing high-density 3D point clouds. The 3D point cloud was obtained containing all the points where the laser beam impacted. The fusion of LiDAR impacts and the positions of each associated to the RTK-GPS allowed the creation of the 3D structure. Although point clouds were already filtered, discarding points out of the study area, the branch volume cannot be directly calculated, since it turns into a 3D solid cluster that encloses a volume. To obtain the 3D object surface, and therefore to be able to calculate the volume enclosed by this surface, a suitable alpha shape was generated as an outline that envelops the outer points of the point cloud. The 3D scenes were obtained during the winter season when only branches were present and defoliated. The models were used to extract information related to height and branch volume. These models might be used for automatic pruning or relating this parameter to evaluate the future yield at each location. The 3D map was correlated with ground truth, which was manually determined, pruning the remaining weight. The number of scans by LiDAR influenced the relationship with the actual biomass measurements and had a significant effect on the treatments. A positive linear fit was obtained for the comparison between actual dry biomass and LiDAR volume. The influence of individual treatments was of low significance. The results showed strong correlations with actual values of biomass and volume with R2 = 0.75, and when comparing LiDAR scans with weight, the R2 rose up to 0.85. The obtained values show that this LiDAR technique is also valid for branch reconstruction with great advantages over other types of non-contact ranging sensors, regarding a high sampling resolution and high sampling rates. Even narrow branches were properly detected, which demonstrates the accuracy of the system working on difficult scenarios such as defoliated crops.

Evaluation of Vineyard Cropping Systems Using On-Board RGB-Depth Perception.

A non-destructive measuring technique was applied to test major vine geometric traits on measurements collected by a contactless sensor. Three-dimensional optical sensors have evolved over the past decade, and these advancements may be useful in improving phenomics technologies for other crops, such as woody perennials. Red, green and blue-depth (RGB-D) cameras, namely Microsoft Kinect, have a significant influence on recent computer vision and robotics research. In this experiment an adaptable mobile platform was used for the acquisition of depth images for the non-destructive assessment of branch volume (pruning weight) and related to grape yield in vineyard crops. Vineyard yield prediction provides useful insights about the anticipated yield to the winegrower, guiding strategic decisions to accomplish optimal quantity and efficiency, and supporting the winegrower with decision-making. A Kinect v2 system on-board to an on-ground electric vehicle was capable of producing precise 3D point clouds of vine rows under six different management cropping systems. The generated models demonstrated strong consistency between 3D images and vine structures from the actual physical parameters when average values were calculated. Correlations of Kinect branch volume with pruning weight (dry biomass) resulted in high coefficients of determination (R2 = 0.80). In the study of vineyard yield correlations, the measured volume was found to have a good power law relationship (R2 = 0.87). However due to low capability of most depth cameras to properly build 3-D shapes of small details the results for each treatment when calculated separately were not consistent. Nonetheless, Kinect v2 has a tremendous potential as a 3D sensor in agricultural applications for proximal sensing operations, benefiting from its high frame rate, low price in comparison with other depth cameras, and high robustness.

31° South: The physiology of adaptation to arid conditions in a passerine bird.

Arid environments provide ideal ground for investigating the mechanisms of adaptive evolution. High temperatures and low water availability are relentless stressors for many endotherms, including birds; yet birds persist in deserts. While physiological adaptation probably involves metabolic phenotypes, the underlying mechanisms (plasticity, genetics) are largely uncharacterized. To explore this, we took an intraspecific approach that focused on a species that is resident over a mesic to arid gradient, the Karoo scrub-robin (Cercotrichas coryphaeus). Specifically, we integrated environmental (climatic and primary productivity), physiological (metabolic rates: a measure of energy expenditure), genotypic (genetic variation underlying the machinery of energy production) and microbiome (involved in processing food from where energy is retrieved) data, to infer the mechanism of physiological adaptation. We that found the variation in energetic physiology phenotypes and gut microbiome composition are associated with environmental features as well as with variation in genes underlying energy metabolic pathways. Specifically, we identified a small list of candidate adaptive genes, some of them with known ties to relevant physiology phenotypes. Together our results suggest that selective pressures on energetic physiology mediated by genes related to energy homeostasis and possibly microbiota composition may facilitate adaptation to local conditions and provide an explanation to the high avian intraspecific divergence observed in harsh environments.

Low-Cost Three-Dimensional Modeling of Crop Plants.

Plant modeling can provide a more detailed overview regarding the basis of plant development throughout the life cycle. Three-dimensional processing algorithms are rapidly expanding in plant phenotyping programmes and in decision-making for agronomic management. Several methods have already been tested, but for practical implementations the trade-off between equipment cost, computational resources needed and the fidelity and accuracy in the reconstruction of the end-details needs to be assessed and quantified. This study examined the suitability of two low-cost systems for plant reconstruction. A low-cost Structure from Motion (SfM) technique was used to create 3D models for plant crop reconstruction. In the second method, an acquisition and reconstruction algorithm using an RGB-Depth Kinect v2 sensor was tested following a similar image acquisition procedure. The information was processed to create a dense point cloud, which allowed the creation of a 3D-polygon mesh representing every scanned plant. The selected crop plants corresponded to three different crops (maize, sugar beet and sunflower) that have structural and biological differences. The parameters measured from the model were validated with ground truth data of plant height, leaf area index and plant dry biomass using regression methods. The results showed strong consistency with good correlations between the calculated values in the models and the ground truth information. Although, the values obtained were always accurately estimated, differences between the methods and among the crops were found. The SfM method showed a slightly better result with regard to the reconstruction the end-details and the accuracy of the height estimation. Although the use of the processing algorithm is relatively fast, the use of RGB-D information is faster during the creation of the 3D models. Thus, both methods demonstrated robust results and provided great potential for use in both for indoor and outdoor scenarios. Consequently, these low-cost systems for 3D modeling are suitable for several situations where there is a need for model generation and also provide a favourable time-cost relationship.

Three-Dimensional Modeling of Weed Plants Using Low-Cost Photogrammetry.

Sensing advances in plant phenotyping are of vital importance in basic and applied plant research. Plant phenotyping enables the modeling of complex shapes, which is useful, for example, in decision-making for agronomic management. In this sense, 3D processing algorithms for plant modeling is expanding rapidly with the emergence of new sensors and techniques designed to morphologically characterize. However, there are still some technical aspects to be improved, such as an accurate reconstruction of end-details. This study adapted low-cost techniques, Structure from Motion (SfM) and MultiView Stereo (MVS), to create 3D models for reconstructing plants of three weed species with contrasting shape and plant structures. Plant reconstruction was developed by applying SfM algorithms to an input set of digital images acquired sequentially following a track that was concentric and equidistant with respect to the plant axis and using three different angles, from a perpendicular to top view, which guaranteed the necessary overlap between images to obtain high precision 3D models. With this information, a dense point cloud was created using MVS, from which a 3D polygon mesh representing every plants' shape and geometry was generated. These 3D models were validated with ground truth values (e.g., plant height, leaf area (LA) and plant dry biomass) using regression methods. The results showed, in general, a good consistency in the correlation equations between the estimated values in the models and the actual values measured in the weed plants. Indeed, 3D modeling using SfM algorithms proved to be a valuable methodology for weed phenotyping, since it accurately estimated the actual values of plant height and LA. Additionally, image processing using the SfM method was relatively fast. Consequently, our results indicate the potential of this budget system for plant reconstruction at high detail, which may be usable in several scenarios, including outdoor conditions. Future research should address other issues, such as the time-cost relationship and the need for detail in the different approaches.

Molecular clocks indicate turnover and diversification of modern coleoid cephalopods during the Mesozoic Marine Revolution.

Coleoid cephalopod molluscs comprise squid, cuttlefish and octopuses, and represent nearly the entire diversity of modern cephalopods. Sophisticated adaptations such as the use of colour for camouflage and communication, jet propulsion and the ink sac highlight the unique nature of the group. Despite these striking adaptations, there are clear parallels in ecology between coleoids and bony fishes. The coleoid fossil record is limited, however, hindering confident analysis of the tempo and pattern of their evolution. Here we use a molecular dataset (180 genes, approx. 36 000 amino acids) of 26 cephalopod species to explore the phylogeny and timing of cephalopod evolution. We show that crown cephalopods diverged in the Silurian-Devonian, while crown coleoids had origins in the latest Palaeozoic. While the deep-sea vampire squid and dumbo octopuses have ancient origins extending to the Early Mesozoic Era, 242 ± 38 Ma, incirrate octopuses and the decabrachian coleoids (10-armed squid) diversified in the Jurassic Period. These divergence estimates highlight the modern diversity of coleoid cephalopods emerging in the Mesozoic Marine Revolution, a period that also witnessed the radiation of most ray-finned fish groups in addition to several other marine vertebrates. This suggests that that the origin of modern cephalopod biodiversity was contingent on ecological competition with marine vertebrates.

Possible involvement of ACSS2 gene in alcoholism.

Alcoholism is a psychiatric disorder that composes one of the principal causes of health disabilities in the world population. Furthermore, the available pharmacotherapy is limited. Therefore, this research was carried out to better understand the basis of the underlying neurobiological processes of this disorder and to discover potential therapeutic targets. Real-time PCR analysis was performed in the amygdala nuclei region of the brain of mice exposed to a chronic three-bottle free-choice model (water, 5 and 10% v/v ethanol). Based on individual ethanol intake, the mice were classified into three groups: "compulsive-like" (i.e., ethanol intake not affected by quinine adulteration), "ethanol-preferring" and "ethanol non-preferring". A fourth group had access only to tap water (control group). The candidate gene ACSS2 was genotyped in human alcoholics by real-time polymerase chain reaction using the markers rs6088638 and rs7266550. Seven genes were picked out (Acss2, Acss3, Acat1, Acsl1, Acaa2, Hadh, and Hadhb) and the mRNA level of the Acss2 gene was increased only in the "compulsive-like" group (p = 0.004). The allele frequency of rs6088638 for the gene ACSS2 was higher in the Alcoholic human group (p = 0.03), although sample size was very small. The gene ACSS2 is associated with alcoholism, suggesting that biochemical pathways where it participates may have a role in the biological mechanisms susceptible to the ethanol effects.

A Low-Cost Approach to Automatically Obtain Accurate 3D Models of Woody Crops.

Crop monitoring is an essential practice within the field of precision agriculture since it is based on observing, measuring and properly responding to inter- and intra-field variability. In particular, "on ground crop inspection" potentially allows early detection of certain crop problems or precision treatment to be carried out simultaneously with pest detection. "On ground monitoring" is also of great interest for woody crops. This paper explores the development of a low-cost crop monitoring system that can automatically create accurate 3D models (clouds of coloured points) of woody crop rows. The system consists of a mobile platform that allows the easy acquisition of information in the field at an average speed of 3 km/h. The platform, among others, integrates an RGB-D sensor that provides RGB information as well as an array with the distances to the objects closest to the sensor. The RGB-D information plus the geographical positions of relevant points, such as the starting and the ending points of the row, allow the generation of a 3D reconstruction of a woody crop row in which all the points of the cloud have a geographical location as well as the RGB colour values. The proposed approach for the automatic 3D reconstruction is not limited by the size of the sampled space and includes a method for the removal of the drift that appears in the reconstruction of large crop rows.

Influence of Wind Speed on RGB-D Images in Tree Plantations.

Weather conditions can affect sensors' readings when sampling outdoors. Although sensors are usually set up covering a wide range of conditions, their operational range must be established. In recent years, depth cameras have been shown as a promising tool for plant phenotyping and other related uses. However, the use of these devices is still challenged by prevailing field conditions. Although the influence of lighting conditions on the performance of these cameras has already been established, the effect of wind is still unknown. This study establishes the associated errors when modeling some tree characteristics at different wind speeds. A system using a Kinect v2 sensor and a custom software was tested from null wind speed up to 10 m·s-1. Two tree species with contrasting architecture, poplars and plums, were used as model plants. The results showed different responses depending on tree species and wind speed. Estimations of Leaf Area (LA) and tree volume were generally more consistent at high wind speeds in plum trees. Poplars were particularly affected by wind speeds higher than 5 m·s-1. On the contrary, height measurements were more consistent for poplars than for plum trees. These results show that the use of depth cameras for tree characterization must take into consideration wind conditions in the field. In general, 5 m·s-1 (18 km·h-1) could be established as a conservative limit for good estimations.

An Approach to the Use of Depth Cameras for Weed Volume Estimation.

The use of depth cameras in precision agriculture is increasing day by day. This type of sensor has been used for the plant structure characterization of several crops. However, the discrimination of small plants, such as weeds, is still a challenge within agricultural fields. Improvements in the new Microsoft Kinect v2 sensor can capture the details of plants. The use of a dual methodology using height selection and RGB (Red, Green, Blue) segmentation can separate crops, weeds, and soil. This paper explores the possibilities of this sensor by using Kinect Fusion algorithms to reconstruct 3D point clouds of weed-infested maize crops under real field conditions. The processed models showed good consistency among the 3D depth images and soil measurements obtained from the actual structural parameters. Maize plants were identified in the samples by height selection of the connected faces and showed a correlation of 0.77 with maize biomass. The lower height of the weeds made RGB recognition necessary to separate them from the soil microrelief of the samples, achieving a good correlation of 0.83 with weed biomass. In addition, weed density showed good correlation with volumetric measurements. The canonical discriminant analysis showed promising results for classification into monocots and dictos. These results suggest that estimating volume using the Kinect methodology can be a highly accurate method for crop status determination and weed detection. It offers several possibilities for the automation of agricultural processes by the construction of a new system integrating these sensors and the development of algorithms to properly process the information provided by them.

Merge Fuzzy Visual Servoing and GPS-Based Planning to Obtain a Proper Navigation Behavior for a Small Crop-Inspection Robot.

The concept of precision agriculture, which proposes farming management adapted to crop variability, has emerged in recent years. To effectively implement precision agriculture, data must be gathered from the field in an automated manner at minimal cost. In this study, a small autonomous field inspection vehicle was developed to minimise the impact of the scouting on the crop and soil compaction. The proposed approach integrates a camera with a GPS receiver to obtain a set of basic behaviours required of an autonomous mobile robot to inspect a crop field with full coverage. A path planner considered the field contour and the crop type to determine the best inspection route. An image-processing method capable of extracting the central crop row under uncontrolled lighting conditions in real time from images acquired with a reflex camera positioned on the front of the robot was developed. Two fuzzy controllers were also designed and developed to achieve vision-guided navigation. A method for detecting the end of a crop row using camera-acquired images was developed. In addition, manoeuvres necessary for the robot to change rows were established. These manoeuvres enabled the robot to autonomously cover the entire crop by following a previously established plan and without stepping on the crop row, which is an essential behaviour for covering crops such as maize without damaging them.

A Multi-Robot Sense-Act Approach to Lead to a Proper Acting in Environmental Incidents.

Many environmental incidents affect large areas, often in rough terrain constrained by natural obstacles, which makes intervention difficult. New technologies, such as unmanned aerial vehicles, may help address this issue due to their suitability to reach and easily cover large areas. Thus, unmanned aerial vehicles may be used to inspect the terrain and make a first assessment of the affected areas; however, nowadays they do not have the capability to act. On the other hand, ground vehicles rely on enough power to perform the intervention but exhibit more mobility constraints. This paper proposes a multi-robot sense-act system, composed of aerial and ground vehicles. This combination allows performing autonomous tasks in large outdoor areas by integrating both types of platforms in a fully automated manner. Aerial units are used to easily obtain relevant data from the environment and ground units use this information to carry out interventions more efficiently. This paper describes the platforms and sensors required by this multi-robot sense-act system as well as proposes a software system to automatically handle the workflow for any generic environmental task. The proposed system has proved to be suitable to reduce the amount of herbicide applied in agricultural treatments. Although herbicides are very polluting, they are massively deployed on complete agricultural fields to remove weeds. Nevertheless, the amount of herbicide required for treatment is radically reduced when it is accurately applied on patches by the proposed multi-robot system. Thus, the aerial units were employed to scout the crop and build an accurate weed distribution map which was subsequently used to plan the task of the ground units. The whole workflow was executed in a fully autonomous way, without human intervention except when required by Spanish law due to safety reasons.

A refined model of the genomic basis for phenotypic variation in vertebrate hemostasis.

BACKGROUND: Hemostasis is a defense mechanism that enhances an organism's survival by minimizing blood loss upon vascular injury. In vertebrates, hemostasis has been evolving with the cardio-vascular and hemodynamic systems over the last 450 million years. Birds and mammals have very similar vascular and hemodynamic systems, thus the mechanism that blocks ruptures in the vasculature is expected to be the same. However, the speed of the process varies across vertebrates, and is particularly slow for birds. Understanding the differences in the hemostasis pathway between birds and mammals, and placing them in perspective to other vertebrates may provide clues to the genetic contribution to variation in blood clotting phenotype in vertebrates. We compiled genomic data corresponding to key elements involved in hemostasis across vertebrates to investigate its genetic basis and understand how it affects fitness. RESULTS: We found that: i) fewer genes are involved in hemostasis in birds compared to mammals; and ii) the largest differences concern platelet membrane receptors and components from the kallikrein-kinin system. We propose that lack of the cytoplasmic domain of the GPIb receptor subunit alpha could be a strong contributor to the prolonged bleeding phenotype in birds. Combined analysis of laboratory assessments of avian hemostasis with the first avian phylogeny based on genomic-scale data revealed that differences in hemostasis within birds are not explained by phylogenetic relationships, but more so by genetic variation underlying components of the hemostatic process, suggestive of natural selection. CONCLUSIONS: This work adds to our understanding of the evolution of hemostasis in vertebrates. The overlap with the inflammation, complement and renin-angiotensin (blood pressure regulation) pathways is a potential driver of rapid molecular evolution in the hemostasis network. Comparisons between avian species and mammals allowed us to hypothesize that the observed mammalian innovations might have contributed to the diversification of mammals that give birth to live young.

Distributed multi-level supervision to effectively monitor the operations of a fleet of autonomous vehicles in agricultural tasks.

This paper describes a supervisor system for monitoring the operation of automated agricultural vehicles. The system analyses all of the information provided by the sensors and subsystems on the vehicles in real time and notifies the user when a failure or potentially dangerous situation is detected. In some situations, it is even able to execute a neutralising protocol to remedy the failure. The system is based on a distributed and multi-level architecture that divides the supervision into different subsystems, allowing for better management of the detection and repair of failures. The proposed supervision system was developed to perform well in several scenarios, such as spraying canopy treatments against insects and diseases and selective weed treatments, by either spraying herbicide or burning pests with a mechanical-thermal actuator. Results are presented for selective weed treatment by the spraying of herbicide. The system successfully supervised the task; it detected failures such as service disruptions, incorrect working speeds, incorrect implement states, and potential collisions. Moreover, the system was able to prevent collisions between vehicles by taking action to avoid intersecting trajectories. The results show that the proposed system is a highly useful tool for managing fleets of autonomous vehicles. In particular, it can be used to manage agricultural vehicles during treatment operations.

Thromboelastography in Selected Avian Species.

Currently available assay methods and reagents are not optimized for evaluating avian hemostasis; therefore, assessing avian coagulopathies is challenging. Recently, thromboelastography (TEG), which measures the viscoelastic properties of blood, has been used clinically in mammalian species to diagnose and characterize hemostatic disorders. To evaluate TEG in healthy individuals of 6 avian species, we modified existing mammalian TEG protocols to allow analysis of citrated, avian whole-blood samples collected from scarlet ibis (Eudocimus ruber) (n = 13), American flamingos ( Phoenicopterus ruber ) (n = 13), helmeted Guinea fowl ( Numida meleagris ) (n = 12), Amazon parrots (Amazona species) (n = 9), Humboldt penguins ( Spheniscus humboldti ) (n = 6), and domestic chickens (n = 16). Activated partial thromboplastin time, prothrombin time, and fibrinogen were measured as a means of comparison. Regardless of the mode of activation, clot formation in the species studied was markedly delayed compared with mammals. Because of prolonged reaction time (14.7-52.7 minutes) with kaolin and diluted tissue factor, undiluted human tissue factor was used in all avian samples because it provided the shortest reaction time. Species differed significantly in reaction time (P = .007), clotting rate (P < .001), rate of clot formation (α angle; P < .001), and maximum amplitude (P < .001) values, indicating that species-specific reference intervals are necessary. Based on these results, TEG with specific reference intervals could prove useful in evaluating avian hemostatic disorders.

Comparison of clinical outcomes in patients undergoing mitral valve replacement with mechanical or biological substitutes: a 20 years cohort.

BACKGROUND: The choice of prosthesis for mitral valve replacement still remains controversial. This study assessed mortality, bleeding events and reoperation in patients who underwent mitral valve replacement surgery with biological or mechanical substitutes. METHODS: A total of 352 patients who underwent mitral valve replacement surgery between 1990 and 2008 with 5 to 23 years of follow-up were retrospectively evaluated in a cohort study. RESULTS: The 5, 10, 15 and 20 year survival rates after surgery using a mechanical substitute were 87.7%, 74.2%, 69.3% and 69.3%, respectively, while after surgery with a biological substitute, they were 87.6%, 71.0%, 64.2% and 56.6%, respectively. There was no significant difference between the two groups (p = 0.38). In the multivariate analysis, the factors associated with death were age, bleeding events and renal failure. The probabilities of remaining free of reoperation at 5, 10, 15 and 20 years after surgery using a mechanical substitute were 94.4%, 92.7%, 92.7% and 92.7%; after surgery with a bioprosthesis, they were 95.9%, 86.4%, 81.2% and 76.5%, respectively (p = 0.073). There was a significantly higher incidence of reoperation for the bioprosthetic valve replacement group (p = 0.008). The probabilities of remaining free of bleeding events at 5, 10, 15 and 20 years after surgery using a mechanical substitute were 95.0%, 91.0%, 89.6% and 89.6%, respectively, while after surgery with a bioprosthesis, they were 96.9%, 94.0%, 94.0% and 94.0%, (p = 0.267). CONCLUSIONS: The authors concluded that: 1) mortality during follow-up was statistically similar for both groups; 2) there was a greater tendency to reoperation in the bioprosthesis group; 3) the probability of remaining free from reoperation remained unchanged after 10 years' follow-up for patients with mechanical substitute valves; 4) the probability of remaining fee from bleeding events remained unchanged after 10 years' follow-up for patients given bioprostheses; 5) the baseline characteristics of patients were the greatest determinants of later mortality after surgery; 6) the type of prosthesis was not an independent predictive factor of any of the outcomes tested in the multivariate analysis.