Learning Graph-Convolutional Representations for Point Cloud Denoising

Point clouds are an increasingly relevant data type but they are often corrupted by noise. We propose a deep neural network based on graph-convolutional layers that can elegantly deal with the permutation-invariance problem encountered by learning-based point cloud processing methods. The network is fully-convolutional and can build complex hierarchies of features by dynamically constructing neighborhood graphs from similarity among the high-dimensional feature representations of the points. When coupled with a loss promoting proximity to the ideal surface, the proposed approach significantly outperforms state-of-the-art methods on a variety of metrics. In particular, it is able to improve in terms of Chamfer measure and of quality of the surface normals that can be estimated from the denoised data. We also show that it is especially robust both at high noise levels and in presence of structured noise such as the one encountered in real LiDAR scans.Comment: European Conference on Computer Vision (ECCV) 202

Does training with amplitude modulated tones affect tone-vocoded speech perception?

Temporal-envelope cues are essential for successful speech perception. We asked here whether training on stimuli containing temporal-envelope cues without speech content can improve the perception of spectrally-degraded (vocoded) speech in which the temporal-envelope (but not the temporal fine structure) is mainly preserved. Two groups of listeners were trained on different amplitude-modulation (AM) based tasks, either AM detection or AM-rate discrimination (21 blocks of 60 trials during two days, 1260 trials; frequency range: 4Hz, 8Hz, and 16Hz), while an additional control group did not undertake any training. Consonant identification in vocoded vowel-consonant-vowel stimuli was tested before and after training on the AM tasks (or at an equivalent time interval for the control group). Following training, only the trained groups showed a significant improvement in the perception of vocoded speech, but the improvement did not significantly differ from that observed for controls. Thus, we do not find convincing evidence that this amount of training with temporal-envelope cues without speech content provide significant benefit for vocoded speech intelligibility. Alternative training regimens using vocoded speech along the linguistic hierarchy should be explored

Survey of the analysis of continuous conformational variability of biological macromolecules by electron microscopy

Single-particle analysis by electron microscopy is a well established technique for analyzing the three-dimensional structures of biological macromolecules. Besides its ability to produce high-resolution structures, it also provides insights into the dynamic behavior of the structures by elucidating their conformational variability. Here, the different image-processing methods currently available to study continuous conformational changes are reviewedThe authors would like to acknowledge support from the Spanish Ministry of Economy and Competitiveness through grants BIO2013-44647-R and BIO2016-76400-R (AEI/ FEDER, UE), Comunidad Autonoma de Madrid through grant S2017/BMD-3817, Instituto de Salud Carlos III through grants PT13 /0001/0009 and PT17/0009/0010,the European Union (EU) and Horizon 2020 through West-Life (EINFRA- 2015-1, Proposal 675858), CORBEL (INFRADEV-1-2014-1, Proposal 654248), ELIXIR–EXCELERATE (INFRADEV-3- 2015, Proposal 676559), iNEXT (INFRAIA-1-2014-2015, Proposal 653706), EOSCpilot (INFRADEV-04-2016, Proposal 739563) and the National Institutes of Health (P41 GM 103712) (IB

A new method for 2D gel spot alignment: application to the analysis of large sample sets in clinical proteomics

<p>Abstract</p> <p>Background</p> <p>In current comparative proteomics studies, the large number of images generated by 2D gels is currently compared using spot matching algorithms. Unfortunately, differences in gel migration and sample variability make efficient spot alignment very difficult to obtain, and, as consequence most of the software alignments return noisy gel matching which needs to be manually adjusted by the user.</p> <p>Results</p> <p>We present Sili2DGel an algorithm for automatic spot alignment that uses data from recursive gel matching and returns meaningful Spot Alignment Positions (SAP) for a given set of gels. In the algorithm, the data are represented by a graph and SAP by specific subgraphs. The results are returned under various forms (clickable synthetic gel, text file, etc.). We have applied Sili2DGel to study the variability of the urinary proteome from 20 healthy subjects.</p> <p>Conclusion</p> <p>Sili2DGel performs noiseless automatic spot alignment for variability studies (as well as classical differential expression studies) of biological samples. It is very useful for typical clinical proteomic studies with large number of experiments.</p

β-Catenin is involved in alterations in mitochondrial activity in non-transformed intestinal epithelial and colon cancer cells

BACKGROUND: Alteration in respiratory activity and mitochondrial DNA (mtDNA) transcription seems to be an important feature of cancer cells. Leukotriene D(4) (LTD(4)) is a proinflammatory mediator implicated in the pathology of chronic inflammation and cancer. We have shown earlier that LTD(4) causes translocation of beta-catenin both to the mitochondria, in which it associates with the survival protein Bcl-2 identifying a novel role for beta-catenin in cell survival, and to the nucleus in which it activates the TCF/LEF transcription machinery. METHODS: Here we have used non-transformed intestinal epithelial Int 407 cells and Caco-2 colon cancer cells, transfected or not with wild type and mutated (S33Y) beta-catenin to analyse its effect on mitochondria activity. We have measured the ATP/ADP ratio, and transcription of the mtDNA genes ND2, ND6 and 16 s in these cells stimulated or not with LTD(4). RESULTS: We have shown for the first time that LTD(4) triggers a cellular increase in NADPH dehydrogenase activity and ATP/ADP ratio. In addition, LTD(4) significantly increased the transcription of mtDNA genes. Overexpression of wild-type beta-catenin or a constitutively active beta-catenin mutant mimicked the effect of LTD(4) on ATP/ADP ratio and mtDNA transcription. These elevations in mitochondrial activity resulted in increased reactive oxygen species levels and subsequent activations of the p65 subunit of NF-kappaB. CONCLUSIONS: The present novel data show that LTD(4), presumably through beta-catenin accumulation in the mitochondria, affects mitochondrial activity, lending further credence to the idea that inflammatory signalling pathways are intrinsically linked with potential oncogenic signals

Classifying RNA-Binding Proteins Based on Electrostatic Properties

Protein structure can provide new insight into the biological function of a protein and can enable the design of better experiments to learn its biological roles. Moreover, deciphering the interactions of a protein with other molecules can contribute to the understanding of the protein's function within cellular processes. In this study, we apply a machine learning approach for classifying RNA-binding proteins based on their three-dimensional structures. The method is based on characterizing unique properties of electrostatic patches on the protein surface. Using an ensemble of general protein features and specific properties extracted from the electrostatic patches, we have trained a support vector machine (SVM) to distinguish RNA-binding proteins from other positively charged proteins that do not bind nucleic acids. Specifically, the method was applied on proteins possessing the RNA recognition motif (RRM) and successfully classified RNA-binding proteins from RRM domains involved in protein–protein interactions. Overall the method achieves 88% accuracy in classifying RNA-binding proteins, yet it cannot distinguish RNA from DNA binding proteins. Nevertheless, by applying a multiclass SVM approach we were able to classify the RNA-binding proteins based on their RNA targets, specifically, whether they bind a ribosomal RNA (rRNA), a transfer RNA (tRNA), or messenger RNA (mRNA). Finally, we present here an innovative approach that does not rely on sequence or structural homology and could be applied to identify novel RNA-binding proteins with unique folds and/or binding motifs

Combined NADPH Oxidase 1 and Interleukin 10 Deficiency Induces Chronic Endoplasmic Reticulum Stress and Causes Ulcerative Colitis-Like Disease in Mice

Ulcerative colitis (UC) is a chronic inflammatory bowel disease affecting the rectum which progressively extents. Its etiology remains unknown and the number of treatments available is limited. Studies of UC patients have identified an unbalanced endoplasmic reticulum (ER) stress in the non-inflamed colonic mucosa. Animal models with impaired ER stress are sensitive to intestinal inflammation, suggesting that an unbalanced ER stress could cause inflammation. However, there are no ER stress-regulating strategies proposed in the management of UC partly because of the lack of relevant preclinical model mimicking the disease. Here we generated the IL10/Nox1(dKO) mouse model which combines immune dysfunction (IL-10 deficiency) and abnormal epithelium (NADPH oxidase 1 (Nox1) deficiency) and spontaneously develops a UC-like phenotype with similar complications (colorectal cancer) than UC. Our data identified an unanticipated combined role of IL10 and Nox1 in the fine-tuning of ER stress responses in goblet cells. As in humans, the ER stress was unbalanced in mice with decreased eIF2 alpha phosphorylation preceding inflammation. In IL10/Nox1(dKO) mice, salubrinal preserved eIF2 alpha phosphorylation through inhibition of the regulatory subunit of the protein phosphatase 1 PP1R15A/GADD34 and prevented colitis. Thus, this new experimental model highlighted the central role of epithelial ER stress abnormalities in the development of colitis and defined the defective eIF2 alpha pathway as a key pathophysiological target for UC. Therefore, specific regulators able to restore the defective eIF2 alpha pathway could lead to the molecular remission needed to treat UC

Beta-Strand Interfaces of Non-Dimeric Protein Oligomers Are Characterized by Scattered Charged Residue Patterns

Protein oligomers are formed either permanently, transiently or even by default. The protein chains are associated through intermolecular interactions constituting the protein interface. The protein interfaces of 40 soluble protein oligomers of stœchiometries above two are investigated using a quantitative and qualitative methodology, which analyzes the x-ray structures of the protein oligomers and considers their interfaces as interaction networks. The protein oligomers of the dataset share the same geometry of interface, made by the association of two individual β-strands (β-interfaces), but are otherwise unrelated. The results show that the β-interfaces are made of two interdigitated interaction networks. One of them involves interactions between main chain atoms (backbone network) while the other involves interactions between side chain and backbone atoms or between only side chain atoms (side chain network). Each one has its own characteristics which can be associated to a distinct role. The secondary structure of the β-interfaces is implemented through the backbone networks which are enriched with the hydrophobic amino acids favored in intramolecular β-sheets (MCWIV). The intermolecular specificity is provided by the side chain networks via positioning different types of charged residues at the extremities (arginine) and in the middle (glutamic acid and histidine) of the interface. Such charge distribution helps discriminating between sequences of intermolecular β-strands, of intramolecular β-strands and of β-strands forming β-amyloid fibers. This might open new venues for drug designs and predictive tool developments. Moreover, the β-strands of the cholera toxin B subunit interface, when produced individually as synthetic peptides, are capable of inhibiting the assembly of the toxin into pentamers. Thus, their sequences contain the features necessary for a β-interface formation. Such β-strands could be considered as ‘assemblons’, independent associating units, by homology to the foldons (independent folding unit). Such property would be extremely valuable in term of assembly inhibitory drug development

Age-Related Impairment of Ultrasonic Vocalization in Tau.P301L Mice: Possible Implication for Progressive Language Disorders

Tauopathies, including Alzheimer's Disease, are the most frequent neurodegenerative diseases in elderly people and cause various cognitive, behavioural and motor defects, but also progressive language disorders. For communication and social interactions, mice produce ultrasonic vocalization (USV) via expiratory airflow through the larynx. We examined USV of Tau.P301L mice, a mouse model for tauopathy expressing human mutant tau protein and developing cognitive, motor and upper airway defects.At age 4-5 months, Tau.P301L mice had normal USV, normal expiratory airflow and no brainstem tauopathy. At age 8-10 months, Tau.P301L mice presented impaired USV, reduced expiratory airflow and severe tauopathy in the periaqueductal gray, Kolliker-Fuse and retroambiguus nuclei. Tauopathy in these nuclei that control upper airway function and vocalization correlates well with the USV impairment of old Tau.P301L mice.In a mouse model for tauopathy, we report for the first time an age-related impairment of USV that correlates with tauopathy in midbrain and brainstem areas controlling vocalization. The vocalization disorder of old Tau.P301L mice could be, at least in part, reminiscent of language disorders of elderly suffering tauopathy