Localization Recall Precision (LRP): A New Performance Metric for Object Detection

Average precision (AP), the area under the recall-precision (RP) curve, is the standard performance measure for object detection. Despite its wide acceptance, it has a number of shortcomings, the most important of which are (i) the inability to distinguish very different RP curves, and (ii) the lack of directly measuring bounding box localization accuracy. In this paper, we propose 'Localization Recall Precision (LRP) Error', a new metric which we specifically designed for object detection. LRP Error is composed of three components related to localization, false negative (FN) rate and false positive (FP) rate. Based on LRP, we introduce the 'Optimal LRP', the minimum achievable LRP error representing the best achievable configuration of the detector in terms of recall-precision and the tightness of the boxes. In contrast to AP, which considers precisions over the entire recall domain, Optimal LRP determines the 'best' confidence score threshold for a class, which balances the trade-off between localization and recall-precision. In our experiments, we show that, for state-of-the-art object (SOTA) detectors, Optimal LRP provides richer and more discriminative information than AP. We also demonstrate that the best confidence score thresholds vary significantly among classes and detectors. Moreover, we present LRP results of a simple online video object detector which uses a SOTA still image object detector and show that the class-specific optimized thresholds increase the accuracy against the common approach of using a general threshold for all classes. At https://github.com/cancam/LRP we provide the source code that can compute LRP for the PASCAL VOC and MSCOCO datasets. Our source code can easily be adapted to other datasets as well.Comment: to appear in ECCV 201

The toxbox: specific DNA sequence requirements for activation of Vibrio cholerae virulence genes by ToxT

The Gram-negative, curved rod Vibrio cholerae causes the severe diarrhoeal disease cholera. The two major virulence factors produced by V. cholerae during infection are the cholera toxin (CT) and the toxin-coregulated pilus (TCP). Transcription of the genes encoding both CT and the components of the TCP is directly activated by ToxT, a transcription factor in the AraC/XylS family. ToxT binds upstream of the ctxAB genes, encoding CT, and upstream of tcpA , the first gene in a large operon encoding the components of the TCP. The DNA sequences upstream of ctxAB and tcpA that contain ToxT binding sites do not have any significant similarity other than being AT-rich. Extensive site-directed mutagenesis was performed on the region upstream of tcpA previously shown to be protected by ToxT, and we identified specific base pairs important for activation of tcpA transcription by ToxT. This genetic approach was complemented by copper-phenanthroline footprinting experiments that showed protection by ToxT of the base pairs identified as most important for transcription activation in the mutagenesis experiments. Based on this new information and on previous work, we propose the presence of a ToxT-binding motif – the ‘toxbox’– in promoters regulated by ToxT. At tcpA , two toxbox elements are present in a direct repeat configuration and both are required for activation of transcription by ToxT. The identity of only a few of the base pairs within the toxbox is important for activation by ToxT, and we term these the core toxbox elements. Lastly, we examined ToxT binding to a mutant having 5 bp inserted between the two toxboxes at tcpA and found that occupancy of both binding sites is retained regardless of the positions of the binding sites relative to each other on the face of the DNA. This suggests that ToxT binds independently as a monomer to each toxbox in the tcpA direct repeat, in accordance with what we observed previously with the inverted repeat ToxT sites between acfA and acfD .Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/75755/1/j.1365-2958.2006.05053.x.pd

Differential protein expression of hippocampal cells associated with heavy metals (Pb, As, and MeHg) neurotoxicity::Deepening into the molecular mechanism of neurodegenerative diseases

Chronic exposure to heavy metals such as Pb, As, and MeHg can be associated with an increased risk of developing neurodegenerative diseases. Our in vitro bioassays results showed the potency of heavy metals in the order of Pb &lt;As &lt;MeHg on hippocampal cells. The main objective of this study was combining in vitro label free proteomics and systems biology approach for elucidating patterns of biological response, discovering underlying mechanisms of Pb, As, and MeHg toxicity in hippocampal cells. The omics data was refined by using different filters and normalization and multilevel analysis tools were employed to explore the data visualization. The functional and pathway visualization was performed by using Gene ontology and PathVisio tools. Using these all integrated approaches, we identified significant proteins across treatments within the mitochondrial dysfunction, oxidative stress, ubiquitin proteome dysfunction, and mRNA splicing related to neurodegenerative diseases. The systems biology analysis revealed significant alterations in proteins implicated in Parkinson's disease (PD) and Alzheimer's disease (AD). The current proteomics analysis of three metals support the insight into the proteins involved in neurodegeneration and the altered proteins can be useful for metal-specific biomarkers of exposure and its adverse effects.Significance: The proteomics techniques have been claimed to be more sensitive than the conventional toxicological assays, facilitating the measurement of responses to heavy metals (Pb, As, and MeHg) exposure before obvious harm has occurred demonstrating their predictive value. Also, proteomics allows for the comparison of responses between Pb, As, and MeHg metals, permitting the evaluation of potency differences hippocampal cells of the brain. Hereby, the molecular information provided by pathway and gene functional analysis can be used to develop a more thorough understanding of each metal mechanism at the protein level for different neurological adverse outcomes (e.g. Parkinson's disease, Alzheimer's diseases). Efforts are put into developing proteomics based toxicity testing methods using in vitro models for improving human risk assessment. Some of the key proteins identified can also potentially be used as biomarkers in epidemiologic studies. These heavy metal response patterns shed new light on the mechanisms of mRNA splicing, ubiquitin pathway role in neurodegeneration, and can be useful for the development of molecular biomarkers of heavy metals exposure.</p

Direction distributions of neutrons and reference values of the personal dose equivalent in workplace fields

Within the EC project EVIDOS, double-differential (energy and direction) fluence spectra were determined by means of novel direction spectrometers. By folding the spectra with fluence-to-dose equivalent conversion coefficients, contributions to H*(10) for 14 directions, and values of the personal dose equivalent Hp(10) and the effective dose E for 6 directions of a person's orientation in the field were determined. The results of the measurements and calculations obtained within the EVIDOS project in workplace fields in nuclear installations in Europe, i.e., at Krümmel (boiling water reactor and transport cask), at Mol (Venus research reactor and fuel facility Belgonucléaire) and at Ringhals (pressurised reactor and transport cask) are presente

Glioblastoma and glioblastoma stem cells are dependent on functional MTH1

Glioblastoma multiforme (GBM) is an aggressive form of brain cancer with poor prognosis. Cancer cells are characterized by a specific redox environment that adjusts metabolism to its specific needs and allows the tumor to grow and metastasize. As a consequence, cancer cells and especially GBM cells suffer from elevated oxidative pressure which requires antioxidant-defense and other sanitation enzymes to be upregulated. MTH1, which degrades oxidized nucleotides, is one of these defense enzymes and represents a promising cancer target. We found MTH1 expression levels elevated and correlated with GBM aggressiveness and discovered that siRNA knock-down or inhibition of MTH1 with small molecules efficiently reduced viability of patient-derived GBM cultures. The effect of MTH1 loss on GBM viability was likely mediated through incorporation of oxidized nucleotides and subsequent DNA damage. We revealed that MTH1 inhibition targets GBM independent of aggressiveness as well as potently kills putative GBM stem cells in vitro. We used an orthotopic zebrafish model to confirm our results in vivo and light-sheet microscopy to follow the effect of MTH1 inhibition in GBM in real time. In conclusion, MTH1 represents a promising target for GBM therapy and MTH1 inhibitors may also be effective in patients that suffer from recurring disease

Localization recall precision (LRP): A new performance metric for object detection

Average precision (AP), the area under the recall-precision (RP) curve, is the standard performance measure for object detection. Despite its wide acceptance, it has a number of shortcomings, the most important of which are (i) the inability to distinguish very different RP curves, and (ii) the lack of directly measuring bounding box localization accuracy. In this paper, we propose “Localization Recall Precision (LRP) Error”, a new metric specifically designed for object detection. LRP Error is composed of three components related to localization, false negative (FN) rate and false positive (FP) rate. Based on LRP, we introduce the “Optimal LRP” (oLRP), the minimum achievable LRP error representing the best achievable configuration of the detector in terms of recall-precision and the tightness of the boxes. In contrast to AP, which considers precisions over the entire recall domain, oLRP determines the “best” confidence score threshold for a class, which balances the trade-off between localization and recall-precision. In our experiments, we show that oLRP provides richer and more discriminative information than AP. We also demonstrate that the best confidence score thresholds vary significantly among classes and detectors. Moreover, we present LRP results of a simple online video object detector and show that the class-specific optimized thresholds increase the accuracy against the common approach of using a general threshold for all classes. Our experiments demonstrate that LRP is more competent than AP in capturing the performance of detectors. Our source code for PASCAL VOC AND MSCOCO datasets are provided at https://github.com/cancam/LRP

Evaluation of individual monitoring in mixed neutron/photon fields: mid-term results from the EVIDOS project

EVIDOS is an EC sponsored project that aims at an evaluation and improvement of radiation protection dosimetry in mixed neutron/photon fields. This is performed through spectrometric and dosimetric investigations during different measurement campaigns in representative workplaces of the nuclear industry. The performance of routine and, in particular, novel personal dosemeters and survey instruments is tested in selected workplace fields. Reference values for the dose equivalent quantities, H*(10) and Hp(10) and the effective dose E, are determined using different spectrometers that provide the energy distribution of the neutron fluence and using newly developed devices that determine the energy and directional distribution of the neutron fluence. The EVIDOS project has passed the mid-term, and three measurement campaigns have been performed. This paper will give an overview and some new results from the third campaign that was held in Mol (Belgium), around the research reactor VENUS and in the MOX producing plant of Belgonucléair