LabGenius (United Kingdom)

Abdominal aortic aneurysm (AAA) is a pathologic enlargement of the infrarenal aorta with an associated risk of rupture. However, the responsible mechanisms are only partially understood. Based on murine and human samples, a heterogeneous distribution of characteristic pathologic features across the aneurysm circumference is expected. Yet, complete histologic workup of the aneurysm sac is scarcely reported. Here, samples from five AAAs covering the complete circumference partially as aortic rings are investigated by histologic means (HE, EvG, immunohistochemistry) and a new method embedding the complete ring. Additionally, two different methods of serial histologic section alignment are applied to create a 3D view. The typical histopathologic features of AAA, elastic fiber degradation, matrix remodeling with collagen deposition, calcification, inflammatory cell infiltration and thrombus coverage were distributed without recognizable pattern across the aneurysm sac in all five patients. Analysis of digitally scanned entire aortic rings facilitates the visualization of these observations. Immunohistochemistry is feasible in such specimen, however, tricky due to tissue disintegration. 3D image stacks were created using open-source and non-generic software correcting for non-rigid warping between consecutive sections. Secondly, 3D image viewers allowed visualization of in-depth changes of the investigated pathologic hallmarks. In conclusion, this exploratory descriptive study demonstrates a heterogeneous histomorphology around the AAA circumference. Warranting an increased sample size, these results might need to be considered in future mechanistic research, especially in reference to intraluminal thrombus coverage. 3D histology of such circular specimen could be a valuable visualization tool for further analysis.

Studies of protein fitness landscapes reveal biophysical constraints guiding protein evolution and empower prediction of functional proteins. However, generalisation of these findings is limited due to scarceness of systematic data on fitness landscapes of proteins with a defined evolutionary relationship. We characterized the fitness peaks of four orthologous fluorescent proteins with a broad range of sequence divergence. While two of the four studied fitness peaks were sharp, the other two were considerably flatter, being almost entirely free of epistatic interactions. Mutationally robust proteins, characterized by a flat fitness peak, were not optimal templates for machine-learning-driven protein design – instead, predictions were more accurate for fragile proteins with epistatic landscapes. Our work paves insights for practical application of fitness landscape heterogeneity in protein engineering.

Abstract BackgroundCognitive health is a major concern for many people, and with potential benefits to academic and professional life, maximising cognitive performance is of interest far beyond the older demographics. Several natural products have been suggested as nootropics, including the herb sage. Previous assessments of various Salvia species have reported a range of effects on cognitive performance and mood in both older adult and younger adult populations. This study was conducted with Sibelius™: Sage, an aqueous-ethanol extract of S. officinalis, to assess for the beneficial effects on cognitive performance in adolescents (12-14 year olds) and young adults (18-25 year olds).Methods and FindingsAn acute, double-blind, placebo-controlled study was conducted with two single doses of Sibelius™: Sage (150 mg and 300 mg). Cognitive performance was evaluated using CogTrack™, which probes aspects of cognitive performance covering attention, working memory and episodic/declarative memory through a series of computer-based tasks. Consistent with previous study of Sibelius™: Sage a significant effect was seen on the Immediate Word Recall task in young adults; suggesting acute treatment benefits to verbal episodic/declarative memory performance. Physiological effects of the treatment on salivary cortisol and oxytocin levels, as well as blood pressure and heart rate were also assessed, with limited evidence of an effect on these factors. No adverse events or side-effects linked to the study product intake was observed. The study was registered at the German Clinical Trials Register (DRKS-ID: DRKS00015716).ConclusionsA significant improvement due to the Sage extract was shown for a task assessing short-term episodic memory (Immediate Word Recall), supporting beneficial effects on cognitive performance in young adults that are consistent with previous reports in healthy older adults. These findings suggest that further investigation of the effects observed in this study in larger, long-term human volunteer studies could be beneficial to pursue.

We propose a novel supervised approach for multi-label text classification, which is based on a neural network architecture consisting of a single encoder and multiple classifier heads. Our method predicts which subset of possible tags best matches an input text. It efficiently spends computational resources, exploiting dependencies between tags by encoding an input text into a compact representation which is then passed to multiple classifier heads. We test our architecture on a Twitter hashtag prediction task, comparing it to a baseline model with multiple feedforward networks and a baseline model with multiple recurrent neural networks with GRU cells. We show that our approach achieves a significantly better performance than baselines with an equivalent number of parameters.

We examine the surveying problem, where we attempt to predict how a target user is likely to respond to questions by iteratively querying that user, collaboratively based on the responses of a sample set of users. We focus on an active learning approach, where the next question we select to ask the user depends on their responses to the previous questions. We propose a method for solving the problem based on a Bayesian dimensionality reduction technique. We empirically evaluate our method, contrasting it to benchmark approaches based on augmented linear regression, and show that it achieves much better predictive performance, and is much more robust when there is missing data.

All-pay auctions, a common mechanism for various human and agent interactions, suffers (like many other mechanisms) from the possibility of players' failure to participate in the auction. The authors model such failures and fully characterize equilibrium for this class of games, presenting a symmetric equilibrium and showing that under some conditions the equilibrium is unique. They also reveal various properties of the equilibrium, such as the lack of influence of the most-likely-to-participate player on the behavior of the other players. The authors perform this analysis with two scenarios: the sum-profit model, in which the auctioneer obtains the sum of all submitted bids, and the max-profit model of crowdsourcing contests, in which the auctioneer can only use the best submissions and thus obtains only the winning bid. Finally, the authors examine various methods of influencing the probability of participation such as the effects of misreporting one's own probability of participating and how influencing another player's participation chances changes a player's strategy.

Using heart-type fatty acid-binding protein (H-FABP) as an early cardiac marker for diagnosis of acute myocardial infarction (AMI) soon after the onset of symptoms requires a rapid assay. A one-step test called, CardioDetect®, is used for detection of H-FABP in whole blood sample. Thirty patients suspected of AMI presenting to the emergency department within 12 hours after onset were enrolled in this study. The diagnostic performance of CardioDetect® was compared with different cardiac markers. There were 59.1% of patients with positive H-FABP within 6 hours after onset, while there were only 18.2% with positive cardiac troponin I (cTnI). Results indicated the diagnostic power of H-FABP for AMI was significantly higher than that of cTnI. The sensitivity of H-FABP was 81.8%, which was higher than those of the other cardiac markers, while the specificity was comparable. The area under the receiver operating characteristic curve for H-FABP was 0.909, which was significantly larger than the others. With this rapid and sensitive immunotest, H-FABP could be soon introduced in clinical practice in combination with well-established markers like troponins.