Graph Distillation for Action Detection with Privileged Modalities

We propose a technique that tackles action detection in multimodal videos under a realistic and challenging condition in which only limited training data and partially observed modalities are available. Common methods in transfer learning do not take advantage of the extra modalities potentially available in the source domain. On the other hand, previous work on multimodal learning only focuses on a single domain or task and does not handle the modality discrepancy between training and testing. In this work, we propose a method termed graph distillation that incorporates rich privileged information from a large-scale multimodal dataset in the source domain, and improves the learning in the target domain where training data and modalities are scarce. We evaluate our approach on action classification and detection tasks in multimodal videos, and show that our model outperforms the state-of-the-art by a large margin on the NTU RGB+D and PKU-MMD benchmarks. The code is released at http://alan.vision/eccv18_graph/.Comment: ECCV 201

MERAV: a tool for comparing gene expression across human tissues and cell types

The oncogenic transformation of normal cells into malignant, rapidly proliferating cells requires major alterations in cell physiology. For example, the transformed cells remodel their metabolic processes to supply the additional demand for cellular building blocks. We have recently demonstrated essential metabolic processes in tumor progression through the development of a methodological analysis of gene expression. Here, we present the Metabolic gEne RApid Visualizer (MERAV, http://merav.wi.mit.edu), a web-based tool that can query a database comprising ∼4300 microarrays, representing human gene expression in normal tissues, cancer cell lines and primary tumors. MERAV has been designed as a powerful tool for whole genome analysis which offers multiple advantages: one can search many genes in parallel; compare gene expression among different tissue types as well as between normal and cancer cells; download raw data; and generate heatmaps; and finally, use its internal statistical tool. Most importantly, MERAV has been designed as a unique tool for analyzing metabolic processes as it includes matrixes specifically focused on metabolic genes and is linked to the Kyoto Encyclopedia of Genes and Genomes pathway search.United States. National Institutes of Health (CA103866)United States. National Institutes of Health (AI47389)Life Sciences Research FoundationMassachusetts Institute of Technology. Ludwig Center for Molecular OncologyHoward Hughes Medical Institut

Zebrafish promoter microarrays identify actively transcribed embryonic genes.

We have designed a zebrafish genomic microarray to identify DNA-protein interactions in the proximal promoter regions of over 11,000 zebrafish genes. Using these microarrays, together with chromatin immunoprecipitation with an antibody directed against tri-methylated lysine 4 of Histone H3, we demonstrate the feasibility of this method in zebrafish. This approach will allow investigators to determine the genomic binding locations of DNA interacting proteins during development and expedite the assembly of the genetic networks that regulate embryogenesis.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

The Contribution of Pre-impact Posture on Restrained Occupant Finite Element Model Response in Frontal Impact.

Objective: The objective of this study was to discuss the influence of the pre-impact posture to the response of a finite element human body model (HBM) in frontal impacts. Methods: This study uses previously published cadaveric tests (PMHS), which measured six realistic pre-impact postures. Seven postured models were created from the THUMS occupant model (v4.0): one matching the standard UMTRI driving posture as it was the target posture in the experiments, and six matching the measured pre-impact postures. The same measurements as those obtained during the cadaveric tests were calculated from the simulations, and biofidelity metrics based on signals correlation (CORA) were established to compare the response of the seven models to the experiments. Results: The HBM responses showed good agreement with the PMHS responses for the reaction forces (CORA = 0.80 ± 0.05) and the kinematics of the lower part of the torso but only fair correlation was found with the head, the upper spine, rib strains (CORA= 0.50 ± 0.05) and chest deflections (CORA = 0.67 ± 0.08). All models sustained rib fractures, sternal fracture and clavicle fracture. The average number of rib fractures for all the models was 5.3 ± 1.0, lower than in the experiments (10.8 ± 9.0). Variation in pre-impact posture greatly altered the time histories of the reaction forces, deflections and the rib strains, mainly in terms of time delay, but no definite improvement in HBM response or injury prediction was observed. By modifying only the posture of the HBM, the variability in the impact response was found to be equivalent to that observed in the experiments. The postured HBM sustained from 4 to 8 rib fractures, confirming that the pre-impact posture influenced the injury outcome predicted by the simulation. Conclusions: This study tries to answer an important question: what is the effect of occupant posture on kinematics and kinetics. Significant differences in kinematics observed between HBM and PMHS suggesting more coupling between the pelvis and the spine for the models which makes the model response very sensitive to any variation in the spine posture. Consequently, the findings observed for the HBM cannot be extended to PMHS. Besides, pre-impact posture should be carefully quantified during experiments and the evaluation of HBM should take into account the variation in the predicted impact response due to the variation in the model posture.This work was supported by funds from Toyota Collaborative SafetyResearch Center (ToyotaCSRC). The experimentswere funded by the NHTSA and the Japan Automobile Research Institute (JARI). The views expressed in this article are those of the authors and do not necessarily represent or reflect the views of the sponsors. The authors acknowledge Masao Muraji and Corinne Uskali (Toyota Motor Engineering & Manufacturing, North America) for their contribution to the design of the study

An inter-laboratory comparison of standard membrane-feeding assays for evaluation of malaria transmission-blocking vaccines.

BACKGROUND: An effective malaria transmission-blocking vaccine may play an important role in malaria elimination efforts, and a robust biological assay is essential for its development. The standard membrane-feeding assay (SMFA) for Plasmodium falciparum infection of mosquitoes is considered a "gold standard" assay to measure transmission-blocking activity of test antibodies, and has been utilized widely in both non-clinical and clinical studies. While several studies have discussed the inherent variability of SMFA within a study group, there has been no assessment of inter-laboratory variation. Therefore, there is currently no assurance that SMFA results are comparable between different studies. METHODS: Mouse anti-Pfs25 monoclonal antibody (mAb, 4B7 mAb), rat anti-Pfs48/45 mAb (85RF45.1 mAb) and a human polyclonal antibody (pAb) collected from a malaria-exposed adult were tested at the same concentrations (6-94 μg/mL for 4B7, 1.2-31.3 μg/mL for 85RF45.1 and 23-630 μg/mL for human pAb) in two laboratories following their own standardized SMFA protocols. The mAbs and pAb, previously shown to have strong inhibition activities in the SMFA, were tested at three or four concentrations in two or three independent assays in each laboratory, and percent inhibition in mean oocyst intensity relative to a control in the same feed was determined in each feeding experiment. RESULTS: Both monoclonal and polyclonal antibodies dose-dependently reduced oocyst intensity in all experiments performed at the two test sites. In both laboratories, the inter-assay variability in percent inhibition in oocyst intensity decreased at higher levels of inhibition, regardless of which antibody was tested. At antibody concentrations that led to a >80 % reduction in oocyst numbers, the inter-laboratory variations were in the same range compared with the inter-assay variation observed within a single laboratory, and the differences in best estimates from multiple feeds between the two laboratories were <5 percentage points. CONCLUSIONS: This study confirms previous reports that the precision of the SMFA increases with increasing percent inhibition. Moreover, the variation between the two laboratories is not greater than the variation observed within a laboratory. The findings of this study provide guidance for comparison of SMFA data from different laboratories

Experimental investigation of the effect of occupant characteristics on contemporary seat belt payout behavior in frontal impacts.

Objective: The goal of this study was to investigate the influence of the occupant characteristics on seat belt force vs. payout behavior based on experiment data from different configurations in frontal impacts. Methods: The data set reviewed consists of 58 frontal sled tests using several anthropomorphic test devices (ATDs) and postmortem human subjects (PMHS), restrained by different belt systems (standard belt, SB; force-limiting belt, FLB) at 2 impact severities (48 and 29 km/h). The seat belt behavior was characterized in terms of the shoulder belt force vs. belt payout behavior. A univariate linear regression was used to assess the factor significance of the occupant body mass or stature on the peak tension force and gross belt payout. Results: With the SB, the seat belt behavior obtained by the ATDs exhibited similar force slopes regardless of the occupant size and impact severities, whereas those obtained by the PMHS were varied. Under the 48 km/h impact, the peak tension force and gross belt payout obtained by ATDs was highly correlated to the occupant stature (P = .03, P = .02) and body mass (P = .05, P = .04), though no statistical difference with the stature or body mass were noticed for the PMHS (peak force: P = .09, P = .42; gross payout: P = .40, P = .48).With the FLB under the 48 km/h impact, highly linear relationshipswere noticed between the occupant body mass and the peak tension force (R2 =0.9782) and between the gross payout and stature (R2 =0.9232) regardless of the occupant types. Conclusions: The analysis indicated that the PMHScharacteristics showed a significant influence on the belt response, whereas the belt response obtained with the ATDs was more reproducible. The potential cause included the occupant anthropometry, body mass distribution, and relative motion among body segments specific to the population variance. This study provided a primary data source to understand the biomechanical interaction of the occupant with the restraint system. Further research is necessary to consider these effects in the computational studies and optimized design of the restraint system in a more realistic manner.The experiments reviewed in this study were funded by the NHTSA and Autoliv Research. The opinions expressed herein are solely those of the authors

Proteomic analysis of blastema formation in regenerating axolotl limbs

BACKGROUND: Following amputation, urodele salamander limbs reprogram somatic cells to form a blastema that self-organizes into the missing limb parts to restore the structure and function of the limb. To help understand the molecular basis of blastema formation, we used quantitative label-free liquid chromatography-mass spectrometry/mass spectrometry (LC-MS/MS)-based methods to analyze changes in the proteome that occurred 1, 4 and 7 days post amputation (dpa) through the mid-tibia/fibula of axolotl hind limbs. RESULTS: We identified 309 unique proteins with significant fold change relative to controls (0 dpa), representing 10 biological process categories: (1) signaling, (2) Ca2+ binding and translocation, (3) transcription, (4) translation, (5) cytoskeleton, (6) extracellular matrix (ECM), (7) metabolism, (8) cell protection, (9) degradation, and (10) cell cycle. In all, 43 proteins exhibited exceptionally high fold changes. Of these, the ecotropic viral integrative factor 5 (EVI5), a cell cycle-related oncoprotein that prevents cells from entering the mitotic phase of the cell cycle prematurely, was of special interest because its fold change was exceptionally high throughout blastema formation. CONCLUSION: Our data were consistent with previous studies indicating the importance of inositol triphosphate and Ca2+ signaling in initiating the ECM and cytoskeletal remodeling characteristic of histolysis and cell dedifferentiation. In addition, the data suggested that blastema formation requires several mechanisms to avoid apoptosis, including reduced metabolism, differential regulation of proapoptotic and antiapoptotic proteins, and initiation of an unfolded protein response (UPR). Since there is virtually no mitosis during blastema formation, we propose that high levels of EVI5 function to arrest dedifferentiated cells somewhere in the G1/S/G2 phases of the cell cycle until they have accumulated under the wound epidermis and enter mitosis in response to neural and epidermal factors. Our findings indicate the general value of quantitative proteomic analysis in understanding the regeneration of complex structures

Machine learning and computational chemistry to improve biochar fertilizers : a review

Traditional fertilizers are highly inefficient, with a major loss of nutrients and associated pollution. Alternatively, biochar loaded with phosphorous is a sustainable fertilizer that improves soil structure, stores carbon in soils, and provides plant nutrients in the long run, yet most biochars are not optimal because mechanisms ruling biochar properties are poorly known. This issue can be solved by recent developments in machine learning and computational chemistry. Here we review phosphorus-loaded biochar with emphasis on computational chemistry, machine learning, organic acids, drawbacks of classical fertilizers, biochar production, phosphorus loading, and mechanisms of phosphorous release. Modeling techniques allow for deciphering the influence of individual variables on biochar, employing various supervised learning models tailored to different biochar types. Computational chemistry provides knowledge on factors that control phosphorus binding, e.g., the type of phosphorus compound, soil constituents, mineral surfaces, binding motifs, water, solution pH, and redox potential. Phosphorus release from biochar is controlled by coexisting anions, pH, adsorbent dosage, initial phosphorus concentration, and temperature. Pyrolysis temperatures below 600 °C enhance functional group retention, while temperatures below 450 °C increase plant-available phosphorus. Lower pH values promote phosphorus release, while higher pH values hinder it. Physical modifications, such as increasing surface area and pore volume, can maximize the adsorption capacity of phosphorus-loaded biochar. Furthermore, the type of organic acid affects phosphorus release, with low molecular weight organic acids being advantageous for soil utilization. Lastly, biochar-based fertilizers release nutrients 2–4 times slower than conventional fertilizers

Functional genomics reveals serine synthesis is essential in PHGDH-amplified breast cancer

Cancer cells adapt their metabolic processes to drive macromolecular biosynthesis for rapid cell growth and proliferation[superscript 1, 2]. RNA interference (RNAi)-based loss-of-function screening has proven powerful for the identification of new and interesting cancer targets, and recent studies have used this technology in vivo to identify novel tumour suppressor genes[superscript 3]. Here we developed a method for identifying novel cancer targets via negative-selection RNAi screening using a human breast cancer xenograft model at an orthotopic site in the mouse. Using this method, we screened a set of metabolic genes associated with aggressive breast cancer and stemness to identify those required for in vivo tumorigenesis. Among the genes identified, phosphoglycerate dehydrogenase (PHGDH) is in a genomic region of recurrent copy number gain in breast cancer and PHGDH protein levels are elevated in 70% of oestrogen receptor (ER)-negative breast cancers. PHGDH catalyses the first step in the serine biosynthesis pathway, and breast cancer cells with high PHGDH expression have increased serine synthesis flux. Suppression of PHGDH in cell lines with elevated PHGDH expression, but not in those without, causes a strong decrease in cell proliferation and a reduction in serine synthesis. We find that PHGDH suppression does not affect intracellular serine levels, but causes a drop in the levels of α-ketoglutarate, another output of the pathway and a tricarboxylic acid (TCA) cycle intermediate. In cells with high PHGDH expression, the serine synthesis pathway contributes approximately 50% of the total anaplerotic flux of glutamine into the TCA cycle. These results reveal that certain breast cancers are dependent upon increased serine pathway flux caused by PHGDH overexpression and demonstrate the utility of in vivo negative-selection RNAi screens for finding potential anticancer targets.Susan G. Komen Breast Cancer Foundation (Fellowship)Life Sciences Research Foundation (Fellowship)W. M. Keck FoundationDavid H. Koch Cancer Research FundAlexander and Margaret Stewart TrustNational Institutes of Health (U.S.) (Grant CA103866