Electrical model of an NMOS body biased structure in triple-well technology under photoelectric laser stimulation

International audience— This study is driven by the need to optimize failure analysis methodologies based on laser/silicon interactions with an integrated circuit using a triple-well process. It is therefore mandatory to understand the behavior of elementary devices to laser illumination, in order to model and predict the behavior of more complex circuits. This paper presents measurements of the photoelectric currents induced by a pulsed-laser on an NMOS transistor in triple-well Psubstrate/DeepNwell/Pwell structure dedicated to low power body biasing techniques. This evaluation compares the triple-well structure to a classical Psubstrate-only structure of an NMOS transistor. It reveals the possible activation change of the bipolar transistors. Based on these experimental measurements, an electrical model is proposed that makes it possible to simulate the effects induced by photoelectric laser stimulation

Learning 3D Human Pose from Structure and Motion

3D human pose estimation from a single image is a challenging problem, especially for in-the-wild settings due to the lack of 3D annotated data. We propose two anatomically inspired loss functions and use them with a weakly-supervised learning framework to jointly learn from large-scale in-the-wild 2D and indoor/synthetic 3D data. We also present a simple temporal network that exploits temporal and structural cues present in predicted pose sequences to temporally harmonize the pose estimations. We carefully analyze the proposed contributions through loss surface visualizations and sensitivity analysis to facilitate deeper understanding of their working mechanism. Our complete pipeline improves the state-of-the-art by 11.8% and 12% on Human3.6M and MPI-INF-3DHP, respectively, and runs at 30 FPS on a commodity graphics card.Comment: ECCV 2018. Project page: https://www.cse.iitb.ac.in/~rdabral/3DPose

Visualization of positive and negative sense viral RNA for probing the mechanism of direct-acting antivirals against hepatitis C virus

RNA viruses are highly successful pathogens and are the causative agents for many important diseases. To fully understand the replication of these viruses it is necessary to address the roles of both positive-strand RNA ((+)RNA) and negative-strand RNA ((-)RNA), and their interplay with viral and host proteins. Here we used branched DNA (bDNA) fluorescence in situ hybridization (FISH) to stain both the abundant (+)RNA and the far less abundant (-)RNA in both hepatitis C virus (HCV)- and Zika virus-infected cells, and combined these analyses with visualization of viral proteins through confocal imaging. We were able to phenotypically examine HCV-infected cells in the presence of uninfected cells and revealed the effect of direct-acting antivirals on HCV (+)RNA, (-)RNA, and protein, within hours of commencing treatment. Herein, we demonstrate that bDNA FISH is a powerful tool for the study of RNA viruses that can provide insights into drug efficacy and mechanism of action

Novel inhibition mechanism and potent antiviral activity of translocation-deficient reverse transcriptase inhibitors [abstract]

Abstract only availableNucleoside RT inhibitors (NRTIs) are among the most potent anti-HIV agents and act as chain terminators because they lack a 3'OH. However, this feature can reduce affinity for RT compared to the analogous dNTP substrate, as well as reduced intracellular conversion to the active dNTP. To overcome this, it was shown that certain nucleosides that retain the 3'OH and have substitutions at the 4' ribose and 2 position of the base have exceptional antiviral properties. One of these compounds, 4'-ethynyl, 2-fluoro deoxy-adenosine (4'E-2FdA) is the most potent NRTI inhibitor against wild-type and multi-drug resistant HIV viruses described to date. We have recently reported that 4'E-2FdA acts as a chain terminator despite the presence of an accessible 3'OH. We show that after 4'E-2FdA-MP incorporation, RT does not bind the next incoming dNTP. We analyzed RT translocation on different sequences terminated with 4'E-2FdA-MP, and found that even at sequences when RT is naturally found post-translocated, the inhibitor prevents translocation. This decrease in translocation efficiency explains the reduced binding of the next incoming dNTP and the termination of elongation. While the inhibitor stabilizes the pre-translocated 4'E-2FdA-MP-terminated primer, the pyrophosphate-dependent excision rate of 4'E-2FdA-MP was not very high compared to ddAMP. In conclusion, this highly potent chain termination activity arises from difficulty of the primer 3'-terminus to translocate following incorporation of the compound, and not from simple steric hindrance due to the 4' substitution. Therefore, we propose that 4'E-2FdA is a Translocation-Deficient Reverse Transcriptase Inhibitor (TDRTI) that acts by a novel mechanism.NIH grant to S. Sarafiano

K70Q Adds High-Level Tenofovir Resistance to “Q151M Complex” HIV Reverse Transcriptase through the Enhanced Discrimination Mechanism

HIV-1 carrying the “Q151M complex” reverse transcriptase (RT) mutations (A62V/V75I/F77L/F116Y/Q151M, or Q151Mc) is resistant to many FDA-approved nucleoside RT inhibitors (NRTIs), but has been considered susceptible to tenofovir disoproxil fumarate (TFV-DF or TDF). We have isolated from a TFV-DF-treated HIV patient a Q151Mc-containing clinical isolate with high phenotypic resistance to TFV-DF. Analysis of the genotypic and phenotypic testing over the course of this patient's therapy lead us to hypothesize that TFV-DF resistance emerged upon appearance of the previously unreported K70Q mutation in the Q151Mc background. Virological analysis showed that HIV with only K70Q was not significantly resistant to TFV-DF. However, addition of K70Q to the Q151Mc background significantly enhanced resistance to several approved NRTIs, and also resulted in high-level (10-fold) resistance to TFV-DF. Biochemical experiments established that the increased resistance to tenofovir is not the result of enhanced excision, as K70Q/Q151Mc RT exhibited diminished, rather than enhanced ATP-based primer unblocking activity. Pre-steady state kinetic analysis of the recombinant enzymes demonstrated that addition of the K70Q mutation selectively decreases the binding of tenofovir-diphosphate (TFV-DP), resulting in reduced incorporation of TFV into the nascent DNA chain. Molecular dynamics simulations suggest that changes in the hydrogen bonding pattern in the polymerase active site of K70Q/Q151Mc RT may contribute to the observed changes in binding and incorporation of TFV-DP. The novel pattern of TFV-resistance may help adjust therapeutic strategies for NRTI-experienced patients with multi-drug resistant (MDR) mutations

Evaluation of CNN-Based Human Pose Estimation for Body Segment Lengths Assessment

Human pose estimation (HPE) methods based on convolutional neural networks (CNN) have demonstrated significant progress and achieved state-of-the-art results on human pose datasets. In this study, we aimed to assess the perfor-mance of CNN-based HPE methods for measuring anthropometric data. A Vicon motion analysis system as the reference system and a stereo vision system recorded ten asymptomatic subjects standing in front of the stereo vision system in a static posture. Eight HPE methods estimated the 2D poses which were transformed to the 3D poses by using the stereo vision system. Percentage of correct keypoints, 3D error, and absolute error of the body segment lengths are the evaluation measures which were used to assess the results. Percentage of correct keypoints – the stand-ard metric for 2D pose estimation – showed that the HPE methods could estimate the 2D body joints with a minimum accuracy of 99%. Meanwhile, the average 3D error and absolute error for the body segment lengths are 5 cm

Kinetic Pathway of Pyrophosphorolysis by a Retrotransposon Reverse Transcriptase

DNA and RNA polymerases use a common phosphoryl transfer mechanism for base addition that requires two or three acidic amino acid residues at their active sites. We previously showed, for the reverse transcriptase (RT) encoded by the yeast retrotransposon Ty1, that one of the three conserved active site aspartates (D211) can be substituted by asparagine and still retain in vitro polymerase activity, although in vivo transposition is lost. Transposition is partially restored by second site suppressor mutations in the RNAse H domain. The novel properties of this amino acid substitution led us to express the WT and D211N mutant enzymes, and study their pre-steady state kinetic parameters. We found that the kpol was reduced by a factor of 223 in the mutant, although the Kd for nucleotide binding was unaltered. Further, the mutant enzyme had a marked preference for Mn2+ over Mg2+. To better understand the functions of this residue within the Ty1 RT active site, we have now examined the in vitro properties of WT and D211N mutant Ty1 RTs in carrying out pyrophosphorolysis, the reverse reaction to polymerization, where pyrophosphate is the substrate and dNTPs are the product. We find that pyrophosphorolysis is efficient only when the base-paired primer template region is >14 bases, and that activity increases when the primer end is blunt-ended or recessed by only a few bases. Using pre-steady state kinetic analysis, we find that the rate of pyrophosphorolysis (kpyro) in the D211N mutant is nearly 320 fold lower than the WT enzyme, and that the mutant enzyme has an ∼170 fold lower apparent Kd for pyrophosphate. These findings indicate that subtle substrate differences can strongly affect the enzyme's ability to properly position the primer-end to carry out pyrophosphorolysis. Further the kinetic data suggests that the D211 residue has a role in pyrophosphate binding and release, which could affect polymerase translocation, and help explain the D211N mutant's transposition defect

Monocular Expressive Body Regression through Body-Driven Attention

To understand how people look, interact, or perform tasks, we need to quickly and accurately capture their 3D body, face, and hands together from an RGB image. Most existing methods focus only on parts of the body. A few recent approaches reconstruct full expressive 3D humans from images using 3D body models that include the face and hands. These methods are optimization-based and thus slow, prone to local optima, and require 2D keypoints as input. We address these limitations by introducing ExPose (EXpressive POse and Shape rEgression), which directly regresses the body, face, and hands, in SMPL-X format, from an RGB image. This is a hard problem due to the high dimensionality of the body and the lack of expressive training data. Additionally, hands and faces are much smaller than the body, occupying very few image pixels. This makes hand and face estimation hard when body images are downscaled for neural networks. We make three main contributions. First, we account for the lack of training data by curating a dataset of SMPL-X fits on in-the-wild images. Second, we observe that body estimation localizes the face and hands reasonably well. We introduce body-driven attention for face and hand regions in the original image to extract higher-resolution crops that are fed to dedicated refinement modules. Third, these modules exploit part-specific knowledge from existing face- and hand-only datasets. ExPose estimates expressive 3D humans more accurately than existing optimization methods at a small fraction of the computational cost. Our data, model and code are available for research at https://expose.is.tue.mpg.de .Comment: Accepted in ECCV'20. Project page: http://expose.is.tue.mpg.d