Exploiting temporal context in CNN based multisource DOA estimation

Supervised learning methods are a powerful tool for direction of arrival (DOA) estimation because they can cope with adverse conditions where simplified models fail. In this work, we consider a previously proposed convolutional neural network (CNN) approach that estimates the DOAs for multiple sources from the phase spectra of the microphones. For speech, specifically, the approach was shown to work well even when trained entirely on synthetically generated data. However, as each frame is processed separately, temporal context cannot be taken into account. This prevents the exploitation of interframe signal correlations, and the fact that DOAs do not change arbitrarily over time. We therefore consider two different extensions of the CNN: the integration of a long short-term memory (LSTM) layer, or of a temporal convolutional network (TCN). In order to accommodate the incorporation of temporal context, the training data generation framework needs to be adjusted. To obtain an easily parameterizable model, we propose to employ Markov chains to realize a gradual evolution of the source activity at different times, frequencies, and directions, throughout a training sequence. A thorough evaluation demonstrates that the proposed configuration for generating training data is suitable for the tasks of single-, and multi-talker localization. In particular, we note that with temporal context, it is important to use speech, or realistic signals in general, for the sources. Experiments with recorded impulse responses and noise reveal that the CNN with the LSTM extension outperforms all other considered approaches, including the plain CNN, and the TCN extension

The Pah-R261Q mouse reveals oxidative stress associated with amyloid-like hepatic aggregation of mutant phenylalanine hydroxylase

Phenylketonuria (PKU) is caused by autosomal recessive variants in phenylalanine hydroxylase (PAH), leading to systemic accumulation of L-phenylalanine (L-Phe) that may reach neurotoxic levels. A homozygous Pah-R261Q mouse, with a highly prevalent misfolding variant in humans, reveals the expected hepatic PAH activity decrease, systemic L-Phe increase, L-tyrosine and L-tryptophan decrease, and tetrahydrobiopterin-responsive hyperphenylalaninemia. Pah-R261Q mice also present unexpected traits, including altered lipid metabolism, reduction of liver tetrahydrobiopterin content, and a metabolic profile indicative of oxidative stress. Pah-R261Q hepatic tissue exhibits large ubiquitin-positive, amyloid-like oligomeric aggregates of mutant PAH that colocalize with selective autophagy markers. Together, these findings reveal that PKU, customarily considered a loss-of-function disorder, can also have toxic gain-of-function contribution from protein misfolding and aggregation. The proteostasis defect and concomitant oxidative stress may explain the prevalence of comorbid conditions in adult PKU patients, placing this mouse model in an advantageous position for the discovery of mutation-specific biomarkers and therapies.publishedVersio

Methodologies for in vitro and in vivo evaluation of efficacy of antifungal and antibiofilm agents and surface coatings against fungal biofilms

KT acknowledges receipt of a mandate of Industrial Research Fund (IOFm/05/022). JB acknowledges funding from the European Research Council Advanced Award 3400867/RAPLODAPT and the Israel Science Foundation grant # 314/13 (www.isf.il). NG acknowledges the Wellcome Trust and MRC for funding. CD acknowledges funding from the Agence Nationale de Recherche (ANR-10-LABX-62-IBEID). CJN acknowledges funding from the National Institutes of Health R35GM124594 and R21AI125801. AW is supported by the Wellcome Trust Strategic Award (grant 097377), the MRC Centre for Medical Mycology (grant MR/N006364/1) at the University of Aberdeen MaCA: outside this study MaCA has received personal speaker’s honoraria the past five years from Astellas, Basilea, Gilead, MSD, Pfizer, T2Candida, and Novartis. She has received research grants and contract work paid to the Statens Serum Institute from Astellas, Basilea, Gilead, MSD, NovaBiotics, Pfizer, T2Biosystems, F2G, Cidara, and Amplyx. CAM acknowledges the Wellcome Trust and the MRC MR/N006364/1. PVD, TC and KT acknowledge the FWO research community: Biology and ecology of bacterial and fungal biofilms in humans (FWO WO.009.16N). AAB acknowledges the Deutsche Forschungsgemeinschaft – CRC FungiNet.Peer reviewedPublisher PD