Unsupervised Point Cloud Representation Learning by Clustering and Neural Rendering

Data augmentation has contributed to the rapid advancement of unsupervised learning on 3D point clouds. However, we argue that data augmentation is not ideal, as it requires a careful application-dependent selection of the types of augmentations to be performed, thus potentially biasing the information learned by the network during self-training. Moreover, several unsupervised methods only focus on uni-modal information, thus potentially introducing challenges in the case of sparse and textureless point clouds. To address these issues, we propose an augmentation-free unsupervised approach for point clouds, named CluRender, to learn transferable point-level features by leveraging uni-modal information for soft clustering and cross-modal information for neural rendering. Soft clustering enables self-training through a pseudo-label prediction task, where the affiliation of points to their clusters is used as a proxy under the constraint that these pseudo-labels divide the point cloud into approximate equal partitions. This allows us to formulate a clustering loss to minimize the standard cross-entropy between pseudo and predicted labels. Neural rendering generates photorealistic renderings from various viewpoints to transfer photometric cues from 2D images to the features. The consistency between rendered and real images is then measured to form a fitting loss, combined with the cross-entropy loss to self-train networks. Experiments on downstream applications, including 3D object detection, semantic segmentation, classification, part segmentation, and few-shot learning, demonstrate the effectiveness of our framework in outperforming state-of-the-art techniques

New Binding Mode to TNF-Alpha Revealed by Ubiquitin-Based Artificial Binding Protein

A variety of approaches have been employed to generate binding proteins from non-antibody scaffolds. Utilizing a beta-sheet of the human ubiquitin for paratope creation we obtained binding proteins against tumor necrosis factor (TNF)-alpha. The bioactive form of this validated pharmacological target protein is a non-covalently linked homo-trimer. This structural feature leads to the observation of a certain heterogeneity concerning the binding mode of TNF-alpha binding molecules, for instance in terms of monomer/trimer specificity. We analyzed a ubiquitin-based TNF-alpha binder, selected by ribosome display, with a particular focus on its mode of interaction. Using enzyme-linked immunosorbent assays, specific binding to TNF-alpha with nanomolar affinity was observed. In isothermal titration calorimetry we obtained comparable results regarding the affinity and detected an exothermic reaction with one ubiquitin-derived binding molecule binding one TNF-alpha trimer. Using NMR spectroscopy and other analytical methods the 1∶3 stoichiometry could be confirmed. Detailed binding analysis showed that the interaction is affected by the detergent Tween-20. Previously, this phenomenon was reported only for one other type of alternative scaffold-derived binding proteins – designed ankyrin repeat proteins – without further investigation. As demonstrated by size exclusion chromatography and NMR spectroscopy, the presence of the detergent increases the association rate significantly. Since the special architecture of TNF-alpha is known to be modulated by detergents, the access to the recognized epitope is indicated to be restricted by conformational transitions within the target protein. Our results suggest that the ubiquitin-derived binding protein targets a new epitope on TNF-alpha, which differs from the epitopes recognized by TNF-alpha neutralizing antibodies

Detection-aware multi-object tracking evaluation

How would you fairly evaluate two multi-object tracking algorithms (i.e. trackers), each one employing a different object detector? Detectors keep improving, thus trackers can make less effort to estimate object states over time. Is it then fair to compare a new tracker employing a new detector with another tracker using an old detector? In this paper, we propose a novel performance measure, named Tracking Effort Measure (TEM), to evaluate trackers that use different detectors. TEM estimates the improvement that the tracker does with respect to its input data (i.e. detections) at frame level (intra-frame complexity) and sequence level (inter-frame complexity). We evaluate TEM over well-known datasets, four trackers and eight detection sets. Results show that, unlike conventional tracking evaluation measures, TEM can quantify the effort done by the tracker with a reduced correlation on the input detections. Its implementation will be made publicly available online. 1 . 1 https://github.com/vpulab/MOT-evaluatio

Determination of morphine in the hair of heroin addicts by high performance liquid chromatography with fluorimetric detection

A procedure has been presented for the quantitative determination of morphine contained in the hair of heroin addicts, by means of heat-acid hydrolysis, pre-column dansyl derivatization, straight phase liquid chromatography, and fluorescence detection. External standardization was used. Intra-assay and day-to-day variation coefficients were 5.6 and 7.8%, respectively (n = 10), when hair containing 1 ng/mg of morphine was assayed. Hair samples of 22 heroin addicts showed positive results in the range 0.08 to 15.7 ng/mg. No false positive results were found in 20 control subjects. A close correlation was shown between high performance liquid chromatography and radioimmunoassay results (y = 0.97x + 0.26)(r = 0.997, n = 15). Morphine hair content results significantly correlated with the grade of heroin use roughly estimated by means of serial determinations of morphine in urines during the last months before hair sampling

HIV-1 p17 binds heparan sulfate proteoglycans to activated CD4(+) T cells

We have previously shown that HIV-1 p17 binds to activated peripheral blood mononuclear cells and enhances secretion of pro-inflammatory cytokines, but we were unable to define a ligand on activated cells. In this work we evaluate the hypothesis that HIV-1 p17 may be a heparin/heparan sulfate-binding protein. HIV-1 p17 contains C- and N-terminal sequences with positively charged residues and a consensus cluster for heparin binding.We demonstrated by affinity chromatography that HIV-1 p17 binds strongly to heparin-agarose at physiological pH. Soluble heparins and heparan sulfate but not chondroitin 4-sulfate and dextran sulfate inhibit binding of HIV-1 p17 to heparin solid phase and to activated CD4+ T cells. Furthermore the inhibition of cell sulfatation by chlorate treatment completely counteracts HIV-1 p17 binding to activated cells. These results indicate for the first time that HIV-1 p17 can be ascribed to the heparin binding protein family and suggest that this interaction might play a key role in the ability of the protein to induce an inflammatory effect on activated cells

HIV p17 reverses the anti-inflammatory activity of IL-4 on IL-15 stimulated monocytes and modulates their ability to secrete MIP-1 alpha

Monocytes play a central role in the immune system by producing and reacting to different soluble factors. Cytokine dysregulation is an hallmark in HIV-infected individuals and it is one of the most significant factors leading to impaired immunity in HIV/AIDS disease. This study investigates the possibility of modulation in the secretion of some inflammatory cytokines and chemokines induced by HIV p17 in monocytes. The results show that p17, while ineffective on resting monocytes, exerts an inflammatory action on IL-4 mediated inhibition of TNF-alpha and IFN- gamma production induced by IL-15 stimulation. In addition, p17 is able to reduce MIP-1alpha secretion, but unable to influence IL-6 production. The ability of HIV p17 to contribute to an altered pattern of secreted soluble factors might imply a key role for this viral protein in the development of AIDS pathogenesi

Determination of allergenicity to three cow's milk hydrolysates and an acid-derived formula in children with cow's milk allergy.

6nonenoneCAFFARELLI C; A. PLEBANI; POIESI C; PETROCCIONE T; SPATTINI A; CAVAGNI G.Caffarelli, C; Plebani, Alessandro; Poiesi, C; Petroccione, T; Spattini, A; Cavagni, G