Proximity tracking using ultra-wideband technology for equine social behaviour research.

Sociopositive interactions with conspecifics are essential for equine welfare and quality of life. This study aimed to validate the use of wearable ultra-wideband (UWB) technology to quantify the spatial relationships and dynamics of social behaviour in horses by continuous (1/s) measurement of interindividual distances. After testing the UWB devices' spatiotemporal accuracy in a static environment, the UWB measurement validity, feasibility and utility under dynamic field conditions was assessed in a group of 8 horses. Comparison of the proximity measurements with video surveillance data established the measurement accuracy and validity (r = 0.83, p < 0.0001) of the UWB technology. The utility for social behaviour research was demonstrated by the excellent accordance of affiliative relationships (preferred partners) identified using UWB with video observations. The horses remained a median of 5.82 m (95% CI 5.13-6.41 m) apart from each other and spent 20% (median, 95% CI 14-26%) of their time in a distance ≤ 3 m to their preferred partner. The proximity measurements and corresponding speed calculation allowed the identification of affiliative versus agonistic approaches based on differences in the approach speed and the distance and duration of the resulting proximity. Affiliative approaches were statistically significantly slower (median: 1.57 km/h, 95% CI 1.26-1.92 km/h, p = 0.0394) and resulted in greater proximity (median: 36.75 cm, 95% CI 19.5-62 cm, p = 0.0003) to the approached horse than agonistic approaches (median: 3.04 km/h, 95% CI 2.16-3.74 km/h, median proximity: 243 cm, 95% CI 130-319 cm), which caused an immediate retreat of the approached horse at a significantly greater speed (median: 3.77 km/h, 95% CI 3.52-5.85 km/h, p < 0.0001) than the approach.

New Chemistries for Degradable Pressure-Sensitive Adhesive Networks.

With the increasing use of pressure-sensitive adhesives (PSAs) in various industries, there is a need for greater sustainability, particularly in developing polymer materials from renewable resources, as well as the reuse and recycling of materials to reduce environmental impact, reduce waste, or extend their life. Here, we outlined the required properties of PSAs which are governed by the molecular parameters (molecular weights, dispersities, molecular weight between entanglement, molecular weight between cross-links and gel content) of polymer materials which subsequently define the physical properties (storage and loss moduli, glass transition temperature) that are required for good performance in peel, tack and shear tests. The sustainable approach discussed here is the development of degradable polymer materials featuring selectively degradable linkages in the backbone. This provides a viable alternative for the design of PSAs that could overcome the 'stickies' problem and make the recycling of glass and cardboard more efficient.

Automated cross-sectional view selection in CT angiography of aortic dissections with uncertainty awareness and retrospective clinical annotations.

Surveillance imaging of patients with chronic aortic diseases, such as aneurysms and dissections, relies on obtaining and comparing cross-sectional diameter measurements along the aorta at predefined aortic landmarks, over time. The orientation of the cross-sectional measuring planes at each landmark is currently defined manually by highly trained operators. Centerline-based approaches are unreliable in patients with chronic aortic dissection, because of the asymmetric flow channels, differences in contrast opacification, and presence of mural thrombus, making centerline computations or measurements difficult to generate and reproduce. In this work, we present three alternative approaches - INS, MCDS, MCDbS - based on convolutional neural networks and uncertainty quantification methods to predict the orientation (ϕ,θ) of such cross-sectional planes. For the monitoring of chronic aortic dissections, we show how a dataset of 162 CTA volumes with overall 3273 imperfect manual annotations routinely collected in a clinic can be efficiently used to accomplish this task, despite the presence of non-negligible interoperator variabilities in terms of mean absolute error (MAE) and 95% limits of agreement (LOA). We show how, despite the large limits of agreement in the training data, the trained model provides faster and more reproducible results than either an expert user or a centerline method. The remaining disagreement lies within the variability produced by three independent expert annotators and matches the current state of the art, providing a similar error, but in a fraction of the time.

Degradable, Ultraviolet-Crosslinked Pressure-Sensitive Adhesives Made from Thioester-Functional Acrylate Copolymers.

Pressure-sensitive adhesives (PSAs) are made from soft, irreversibly lightly crosslinked polymers. Even after removal from surfaces, they retain insoluble networks which pose problems during the recycling of glass and cardboard. Herein, degradable PSAs are presented that provide the required performance in use but have networks that can be degraded after use. A series of copolymers was prepared through radical copolymerization of n-butyl acrylate, 4-acryloyloxy benzophenone (ABP) photo-crosslinker, and dibenzo[c,e]oxepin-5(7H)-thione (DOT) to provide degradable backbone thioesters. The optimum tack and peel strengths were found for molar contents of 0.05 mol% ABP and 0.25 mol% DOT. Degradation of the backbone thioesters through aminolysis or thiolysis led to the full dissolution of the networks, loss of adhesive properties of films (decreases in the measured tack and peel strengths), and the quick detachment of model labels from a substrate. Inclusion of DOT into PSAs offers a viable route toward degradable and recyclable packaging labels.

Enzyme activity profiling for physiological phenotyping within functional phenomics: plant growth and stress responses.

High-throughput profiling of key enzyme activities of carbon, nitrogen, and antioxidant metabolism is emerging as a valuable approach to integrate cell physiological phenotyping into a holistic functional phenomics approach. However, the analyses of the large datasets generated by this method represent a bottleneck, often keeping researchers from exploiting the full potential of their studies. We address these limitations through the exemplary application of a set of data evaluation and visualization tools within a case study. This includes the introduction of multivariate statistical analyses that can easily be implemented in similar studies, allowing researchers to extract more valuable information to identify enzymatic biosignatures. Through a literature meta-analysis, we demonstrate how enzyme activity profiling has already provided functional information on the mechanisms regulating plant development and response mechanisms to abiotic stress and pathogen attack. The high robustness of the distinct enzymatic biosignatures observed during developmental processes and under stress conditions underpins the enormous potential of enzyme activity profiling for future applications in both basic and applied research. Enzyme activity profiling will complement molecular -omics approaches to contribute to the mechanistic understanding required to narrow the genotype-to-phenotype knowledge gap and to identify predictive biomarkers for plant breeding to develop climate-resilient crops.

Azide Photochemistry in Acrylic Copolymers for Ultraviolet Cross-Linkable Pressure-Sensitive Adhesives: Optimization, Debonding-on-Demand, and Chemical Modification.

Pressure-sensitive adhesives (PSAs) are usually made from viscoelastic, high-molecular-weight copolymers, which are fine-tuned by adjusting the comonomer ratios, molecular weights, and cross-link densities to optimize the adhesion properties for the desired end-use. To create a lightly cross-linked network, an ultraviolet (UV) photoinitiator can be incorporated. Here, we present the first use of perfluorophenylazide chemistry to control precisely a polyacrylate network for application as a PSA. Upon UV irradiation, the highly reactive nitrene from the azide moiety reacts with nearby molecules through a C-H insertion reaction, resulting in cross-linking via covalent bonding. This approach offers three benefits: (1) a means to optimize adhesive properties without the addition of an external photoinitiator; (2) the ability to switch off the tack adhesion on demand via a high cross-linking density; and (3) a platform for additional chemical modification. A series of poly(n-butyl acrylate-co-2,3,4,5,6-pentafluorobenzyl acrylate) or poly(PFBA-co-BA) copolymers were synthesized and modified post-polymerization into the photo-reactive poly(n-butyl acrylate-co-4-azido-2,3,5,6-tetrafluorobenzyl acrylate) [azide-modified poly(PFBA-co-BA)] with various molar contents. When cast into films, the azide-modified copolymers with a high azide content achieved a very high shear resistance after UV irradiation, whereas the tack and peel adhesion decreased strongly with the increase in azide content, indicating that excessive cross-linking occurred. These materials are thus photo-switchable. However, in the low range of azide content, an optimum probe tack adhesion energy was obtained in films with a 0.3 mol % azide content, where a long stress plateau (indicating good fibrillation) with a high plateau stress was observed. An optimum peel adhesion strength was achieved with 0.5 mol % azide. Thus, the adhesion was finely controlled by the degree of cross-linking of the PSA, as determined by the azide content of the copolymer chain. Finally, as a demonstration of the versatility and advantages of the material platform, we show an azide-aldehyde-amine multicomponent modification of the azide copolymer to make a dye-functionalized film that retains its adhesive properties. This first demonstration of using azide functionality has enormous potential for functional PSA design.

Biocompatibility and Physiological Thiolytic Degradability of Radically Made Thioester-Functional Copolymers: Opportunities for Drug Release.

Being nondegradable, vinyl polymers have limited biomedical applicability. Unfortunately, backbone esters incorporated through conventional radical ring-opening methods do not undergo appreciable abiotic hydrolysis under physiologically relevant conditions. Here, PEG acrylate and di(ethylene glycol) acrylamide-based copolymers containing backbone thioesters were prepared through the radical ring-opening copolymerization of the thionolactone dibenzo[c,e]oxepin-5(7H)-thione. The thioesters degraded fully in the presence of 10 mM cysteine at pH 7.4, with the mechanism presumed to involve an irreversible S-N switch. Degradations with N-acetylcysteine and glutathione were reversible through the thiol-thioester exchange polycondensation of R-SC(═O)-polymer-SH fragments with full degradation relying on an increased thiolate/thioester ratio. Treatment with 10 mM glutathione at pH 7.2 (mimicking intracellular conditions) triggered an insoluble-soluble switch of a temperature-responsive copolymer at 37 °C and the release of encapsulated Nile Red (as a drug model) from core-degradable diblock copolymer micelles. Copolymers and their cysteinolytic degradation products were found to be noncytotoxic, making thioester backbone-functional polymers promising for drug delivery applications.

Critical Aspects of Person Counting and Density Estimation.

Many scientific studies deal with person counting and density estimation from single images. Recently, convolutional neural networks (CNNs) have been applied for these tasks. Even though often better results are reported, it is often not clear where the improvements are resulting from, and if the proposed approaches would generalize. Thus, the main goal of this paper was to identify the critical aspects of these tasks and to show how these limit state-of-the-art approaches. Based on these findings, we show how to mitigate these limitations. To this end, we implemented a CNN-based baseline approach, which we extended to deal with identified problems. These include the discovery of bias in the reference data sets, ambiguity in ground truth generation, and mismatching of evaluation metrics w.r.t. the training loss function. The experimental results show that our modifications allow for significantly outperforming the baseline in terms of the accuracy of person counts and density estimation. In this way, we get a deeper understanding of CNN-based person density estimation beyond the network architecture. Furthermore, our insights would allow to advance the field of person density estimation in general by highlighting current limitations in the evaluation protocols.

A Geometric Perspective on Information Plane Analysis.

Information plane analysis, describing the mutual information between the input and a hidden layer and between a hidden layer and the target over time, has recently been proposed to analyze the training of neural networks. Since the activations of a hidden layer are typically continuous-valued, this mutual information cannot be computed analytically and must thus be estimated, resulting in apparently inconsistent or even contradicting results in the literature. The goal of this paper is to demonstrate how information plane analysis can still be a valuable tool for analyzing neural network training. To this end, we complement the prevailing binning estimator for mutual information with a geometric interpretation. With this geometric interpretation in mind, we evaluate the impact of regularization and interpret phenomena such as underfitting and overfitting. In addition, we investigate neural network learning in the presence of noisy data and noisy labels.

The Same is Not the Same: Device Effect during Bipolar Radiofrequency Ablation of Atrial Fibrillation.

BACKGROUND: Different ablation devices deliver the same type of energy but use individual control mechanisms to estimate efficacy. We compared patient outcome after the application of radiofrequency ablation systems, using temperature- or resistance-control in paroxysmal and persistent atrial fibrillation (AF). METHODS: This is an unselected all-comers study. Patients underwent standardized left atrial (paroxysmal atrial fibrillation, [PAF] n = 31) or biatrial ablation (persistent atrial fibrillation [persAF] n = 61) with bipolar RF from October 2010 to June 2013. Patients with left atrial dilatation (up to 57 mm), reduced left ventricular (LV) function, and elderly were included. We used resistance-controlled (RC) or temperature-controlled (TC) devices. We amputated atrial appendices and checked intraoperatively for completeness of pulmonary vein exit block. All patients received implantable loop recorders. Follow-up interval was every 6 months. Antiarrhythmic medical treatment endured up to month 6. RESULTS: We reached 100% freedom from atrial fibrillation (FAF) in PAF. In perAF 19% of the RC but 82% of the TC patients reached FAF (12 months; p < 0.05). TC patients exhibited higher creatine kinase-muscle/brain (CK-MB) peak values. In persAF, CK-MB-levels correlated to FAF. No and no mortality (30 days) was evident. Twelve-month mortality did not correlate to AF type, AF duration, LV dimension, or function and age. Prolonged need of oral anticoagulants was 90.1% (RC) and 4.5% (TC). CONCLUSION: In patients with persAF undergoing RF ablation, TC reached higher FAF than RC. Medical devices are not "the same" regarding effectiveness even if used according to manufacturer's instructions. Thus, putative application of "the same" energy is not always "the same" efficacy.

Colloidal assembly of polydisperse particle blends during drying.

In this work, we synthesize a polydisperse aqueous colloidal system composed of small and large zwitterionic particles, as well as medium sized standard acrylic particles. By assembling these dispersions into films by drying, we show using atomic force microscopy (AFM) how their top surfaces can be mostly covered by zwitterionic groups for a wide range of evaporation rates. We probe underneath the top film surface using Fourier-transform infrared (FTIR) spectroscopy - attenuated total reflection (ATR), observing that the content in zwitterionic particles of the film upper layer increases for faster evaporation rates. We show how polydisperse systems hold great potential to overcome the evaporation rate dependence of size segregation processes in drying colloidal blends, and we provide further insights into the assembly mechanisms involved. Polydisperse blends enhance the robustness of such processes for application in coatings and other soft products where evaporation rate can not be tuned.

Publisher's Note: Welcome to Dermatopathology-A New Society Journal at MDPI Publishers.

The European Society of Dermatopathology (ESDP) decided to publish their official journal with MDPI Publishers, Basel, Switzerland [...].

Risk of perioperative coronary stent stenosis or occlusion in patients with previous percutaneous coronary intervention undergoing coronary artery bypass grafting surgery.

OBJECTIVES: There is an ongoing discussion about how to treat coronary stents during bypass surgery: Should patent stents be left alone and the stented vessels be ungrafted, or should every stented coronary artery receive a bypass graft? This study aims to determine the relevance of perioperative stent stenosis or occlusion on postoperative outcomes up to 3 years postoperatively. METHODS: Patients undergoing coronary artery bypass grafting surgery (CABG) (±concomitant procedures) with previous percutaneous coronary intervention from 4 centres were prospectively included in this observatory study between April 2015 and June 2017. A coronary angiography was conducted between the fifth and seventh postoperative days. The preoperative and postoperative angiograms were assessed in a core laboratory, assessing the patencies of coronary stents and bypass grafts. The core lab investigators were blinded to the patients' characteristics and perioperative course. RESULTS: A total of 107 patients were included in the study. In the postoperative coronary angiography, 265 bypass grafts and 189 coronary stents were examined angiographically. Ninety-seven percent of preoperatively patent stents remained patent. New coronary stent stenoses were observed in 5 patients (4.7%). All 5 patients were asymptomatic and managed conservatively. Bypass stenoses were observed in 12 patients (11%), of whom were managed conservatively, 4 underwent percutaneous coronary intervention and 1 underwent redo-CABG. Two years postoperatively, 97% of patients were alive. Patients with new stent stenosis tended to have a better survival compared with patients with bypass stenosis (100% vs 73%; P = 0.09) up to 3 years postoperatively. CONCLUSIONS: Perioperative coronary stent stenosis occurs rarely. It is safe to leave a patently stented coronary vessel without bypass grafting.

Fibrin-Coated Collagen Fleece Seems to Prevent Sternal Instability after Cardiac Surgery: A Matched Pair Data Analysis.

BACKGROUND: To examine if fibrin-coated collagen fleece (Tachosil) interferes with bone and wound healing when it is used on the cut surface of the sternum after median sternotomy. METHODS: A total of 25 patients with osteoporotic sternal disorders were treated with fibrin-coated collagen fleece at the cut surface of the sternum after median sternotomy (therapy group). We compared the occurrence of impaired wound healing and sternal instability, reoperation rate, and 30-day mortality with a control group of 25 case-matched patients. After matching for age, gender, and risk factors for sternal instability (diabetes mellitus, osteoporosis, body mass index, nicotine consumption), both groups were comparable. RESULTS: Sternal instability occurred in one (4%) patient in the study group and in five (20%) patients in the control group. Impaired wound healing occurred in one (4%) patient in the therapy group and two (8%) patients in the control group. Reoperation was necessary in four (16%) patients in the therapy group and 6 (24%) patients in the control group. The 30-day mortality occurred in six (24%) patients in the therapy group and four (16%) patients in the control group. CONCLUSIONS: The use of fibrin-coated collagen fleece on the cut surface of the sternum in patients with osteoporosis does not impair bone and wound healing. Furthermore, it seems to result in less sternal instability. A larger prospective study is necessary to verify the results of this explorative study.

Mitral valve leaflet repair with the new PASCAL system: early real-world data from a German multicentre experience.

AIMS: To examine the clinical experience and practical use of the PASCAL transcatheter valve repair system (Edwards Lifesciences, Irvine, CA, USA) and to report some of the first clinical results. METHODS AND RESULTS: A total of 18 consecutive patients with severe, symptomatic mitral regurgitation (MR) were included in this German multicentre registry. All patients underwent clinical, echocardiographic, and laboratory assessment prior to the PASCAL procedure and before hospital discharge. MR was classified as functional in 6 patients, degenerative in 2, and combined in 10. All except one received a single PASCAL implant. The preprocedural severe MR present in all patients was reduced: grade 0 in 4 (22.2%), grade I in 11 (61.1%), grade II in 3 (16.7%). The v-wave was significantly reduced from 31.7 ± 9.5 to 18 ± 7.7 mmHg (p < 0.001). Independent leaflet capture, performed in 4 (22.2%) of the patients, wide clasps, and the 10-mm central spacer are features of the PASCAL device to optimize mitral leaflet repair. There were no periprocedural complications. CONCLUSION: PASCAL is a safe and effective mitral valve repair device for the treatment of severe MR. Device-specific features allow valve repair tailored to the individual anatomy of the underlying mitral pathology in each patient.

Predicting Cardiac Surgery-Associated Acute Kidney Injury Using a Combination of Clinical Risk Scores and Urinary Biomarkers.

BACKGROUND: Prediction, early diagnosis, and therapy of cardiac surgery-associated acute kidney injury (CSA-AKI) are challenging. We prospectively tested a staged approach to identify patients at high risk for CSA-AKI combining clinical risk stratification and early postoperative quantification of urinary biomarkers for AKI. METHODS: All patients, excluding those on chronic hemodialysis, undergoing scheduled surgery with cardiopulmonary bypass between August 2015 and July 2016 were included. First, patients were stratified by calculating the Cleveland clinic score (CCS) and the Leicester score (LS). In high-risk patients (defined as LS > 25 or CCS > 6), urinary concentrations of biomarkers for AKI ([TIMP-2]*[IGFBP-7]) were evaluated 4 hours postoperatively. CSA-AKI was observed until postoperative day 6 and classified using the Kidney Disease: Improving Global Outcomes criteria. RESULTS: AKI occurred in 352 of613 patients (54%). In high-risk patients, AKI occurred more frequently than in low-risk patients (66 vs. 49%; p = 0.001). In-hospital mortality after AKI stage 2 (15%) or AKI stage 3 (49%) compared with patients without AKI (1.8%; p = 0.001) was increased. LS was predictive for all stages of AKI (area under the curve [AUC] 0.601; p < 0.001) with a poor or fair accuracy, while CCS was only predictive for stage 2 or 3 AKI (AUC 0.669; p < 0.001) with fair accuracy. In 133 high-risk patients, urinary [TIMP-2]*[IGFBP-7] was significantly predictive for all-stage AKI within 24 hours postoperatively (AUC 0.63; p = 0.017). However, for the majority of AKI (55%), which occurred beyond 24 hours postoperatively, urinary [TIMP-2]*[IGFBP-7] was not significantly predictive. Sensitivity for all-stage AKI within 24 hours was 0.38 and specificity was 0.81 using a cutoff value of 0.3. CONCLUSION: CSA-AKI is a relevant and frequent complication after cardiac surgery. Patients at high risk for CSA-AKI can be identified using clinical prediction scores, however, with only poor to fair accuracy. Due to its weak test performance, urinary [TIMP-2]*[IGFBP-7] quantification 4 hours postoperatively does not add to the predictive value of clinical scores.

Biomedical image augmentation using Augmentor.

MOTIVATION: Image augmentation is a frequently used technique in computer vision and has been seeing increased interest since the popularity of deep learning. Its usefulness is becoming more and more recognized due to deep neural networks requiring larger amounts of data to train, and because in certain fields, such as biomedical imaging, large amounts of labelled data are difficult to come by or expensive to produce. In biomedical imaging, features specific to this domain need to be addressed. RESULTS: Here we present the Augmentor software package for image augmentation. It provides a stochastic, pipeline-based approach to image augmentation with a number of features that are relevant to biomedical imaging, such as z-stack augmentation and randomized elastic distortions. The software has been designed to be highly extensible meaning an operation that might be specific to a highly specialized task can easily be added to the library, even at runtime. Although it has been designed as a general software library, it has features that are particularly relevant to biomedical imaging and the techniques required for this domain. AVAILABILITY AND IMPLEMENTATION: Augmentor is a Python package made available under the terms of the MIT licence. Source code can be found on GitHub under https://github.com/mdbloice/Augmentor and installation is via the pip package manager (A Julia version of the package, developed in parallel by Christof Stocker, is also available under https://github.com/Evizero/Augmentor.jl).

Exploit fully automatic low-level segmented PET data for training high-level deep learning algorithms for the corresponding CT data.

We present an approach for fully automatic urinary bladder segmentation in CT images with artificial neural networks in this study. Automatic medical image analysis has become an invaluable tool in the different treatment stages of diseases. Especially medical image segmentation plays a vital role, since segmentation is often the initial step in an image analysis pipeline. Since deep neural networks have made a large impact on the field of image processing in the past years, we use two different deep learning architectures to segment the urinary bladder. Both of these architectures are based on pre-trained classification networks that are adapted to perform semantic segmentation. Since deep neural networks require a large amount of training data, specifically images and corresponding ground truth labels, we furthermore propose a method to generate such a suitable training data set from Positron Emission Tomography/Computed Tomography image data. This is done by applying thresholding to the Positron Emission Tomography data for obtaining a ground truth and by utilizing data augmentation to enlarge the dataset. In this study, we discuss the influence of data augmentation on the segmentation results, and compare and evaluate the proposed architectures in terms of qualitative and quantitative segmentation performance. The results presented in this study allow concluding that deep neural networks can be considered a promising approach to segment the urinary bladder in CT images.