Implicit 3D Orientation Learning for 6D Object Detection from RGB Images

We propose a real-time RGB-based pipeline for object detection and 6D pose estimation. Our novel 3D orientation estimation is based on a variant of the Denoising Autoencoder that is trained on simulated views of a 3D model using Domain Randomization. This so-called Augmented Autoencoder has several advantages over existing methods: It does not require real, pose-annotated training data, generalizes to various test sensors and inherently handles object and view symmetries. Instead of learning an explicit mapping from input images to object poses, it provides an implicit representation of object orientations defined by samples in a latent space. Our pipeline achieves state-of-the-art performance on the T-LESS dataset both in the RGB and RGB-D domain. We also evaluate on the LineMOD dataset where we can compete with other synthetically trained approaches. We further increase performance by correcting 3D orientation estimates to account for perspective errors when the object deviates from the image center and show extended results.Comment: Code available at: https://github.com/DLR-RM/AugmentedAutoencode

A targeted gene panel that covers coding, non-coding and short tandem repeat regions improves the diagnosis of patients with neurodegenerative diseases

Genetic testing for neurodegenerative diseases (NDs) is highly challenging because of genetic heterogeneity and overlapping manifestations. Targeted-gene panels (TGPs), coupled with next-generation sequencing (NGS), can facilitate the profiling of a large repertoire of ND-related genes. Due to the technical limitations inherent in NGS and TGPs, short tandem repeat (STR) variations are often ignored. However, STR expansions are known to cause such NDs as Huntington\u27s disease and spinocerebellar ataxias type 3 (SCA3). Here, we studied the clinical utility of a custom-made TGP that targets 199 NDs and 311 ND-associated genes on 118 undiagnosed patients. At least one known or likely pathogenic variation was found in 54 patients; 27 patients demonstrated clinical profiles that matched the variants; and 16 patients whose original diagnosis were refined. A high concordance of variant calling were observed when comparing the results from TGP and whole-exome sequencing of four patients. Our in-house STR detection algorithm has reached a specificity of 0.88 and a sensitivity of 0.82 in our SCA3 cohort. This study also uncovered a trove of novel and recurrent variants that may enrich the repertoire of ND-related genetic markers. We propose that a combined comprehensive TGPs-bioinformatics pipeline can improve the clinical diagnosis of NDs

Velocity field distributions due to ideal line vortices

We evaluate numerically the velocity field distributions produced by a bounded, two-dimensional fluid model consisting of a collection of parallel ideal line vortices. We sample at many spatial points inside a rigid circular boundary. We focus on ``nearest neighbor'' contributions that result from vortices that fall (randomly) very close to the spatial points where the velocity is being sampled. We confirm that these events lead to a non-Gaussian high-velocity ``tail'' on an otherwise Gaussian distribution function for the Eulerian velocity field. We also investigate the behavior of distributions that do not have equilibrium mean-field probability distributions that are uniform inside the circle, but instead correspond to both higher and lower mean-field energies than those associated with the uniform vorticity distribution. We find substantial differences between these and the uniform case.Comment: 21 pages, 9 figures. To be published in Physical Review E (http://pre.aps.org/) in May 200

Brigatinib Versus Alectinib in ALK-Positive NSCLC After Disease Progression on Crizotinib: Results of Phase 3 ALTA-3 Trial.

INTRODUCTION: This open-label, phase 3 trial (ALTA-3; NCT03596866) compared efficacy and safety of brigatinib versus alectinib for ALK+ NSCLC after disease progression on crizotinib. METHODS: Patients with advanced ALK+ NSCLC that progressed on crizotinib were randomized 1:1 to brigatinib 180 mg once daily (7-d lead-in, 90 mg) or alectinib 600 mg twice daily, aiming to test superiority. The primary end point was blinded independent review committee-assessed progression-free survival (PFS). Interim analysis for efficacy and futility was planned at approximately 70% of 164 expected PFS events. RESULTS: The population (N = 248; brigatinib, n = 125; alectinib, n = 123) was notable for long median duration of prior crizotinib (16.0-16.8 mo) and low rate of ALK fusion in baseline circulating tumor DNA (ctDNA; 78 of 232 [34%]). Median blinded independent review committee-assessed PFS was 19.3 months with brigatinib and 19.2 months with alectinib (hazard ratio = 0.97 [95% confidence interval: 0.66-1.42], p = 0.8672]). The study met futility criterion. Overall survival was immature (41 events [17%]). Exploratory analyses pooled across the treatment groups revealed median PFS of 11.1 versus 22.5 months in patients with versus without ctDNA-detectable ALK fusion at baseline (hazard ratio: 0.48 [95% confidence interval: 0.32-0.71]). Treatment-related adverse events in more than 30% of patients (brigatinib, alectinib) were elevated levels of blood creatine phosphokinase (70%, 29%), aspartate aminotransferase (53%, 38%), and alanine aminotransferase (40%, 36%). CONCLUSIONS: Brigatinib was not superior to alectinib for PFS in crizotinib-pretreated ALK+ NSCLC. Safety was consistent with the well-established and unique profiles of each drug. The low proportion of patients with ctDNA-detectable ALK fusion may account for prolonged PFS with both drugs in ALTA-3

The control parameterization method for nonlinear optimal control: A survey

The control parameterization method is a popular numerical technique for solving optimal control problems. The main idea of control parameterization is to discretize the control space by approximating the control function by a linear combination of basis functions. Under this approximation scheme, the optimal control problem is reduced to an approximate nonlinear optimization problem with a finite number of decision variables. This approximate problem can then be solved using nonlinear programming techniques. The aim of this paper is to introduce the fundamentals of the control parameterization method and survey its various applications to non-standard optimal control problems. Topics discussed include gradient computation, numerical convergence, variable switching times, and methods for handling state constraints. We conclude the paper with some suggestions for future research

Prediction of protein binding sites in protein structures using hidden Markov support vector machine

<p>Abstract</p> <p>Background</p> <p>Predicting the binding sites between two interacting proteins provides important clues to the function of a protein. Recent research on protein binding site prediction has been mainly based on widely known machine learning techniques, such as artificial neural networks, support vector machines, conditional random field, etc. However, the prediction performance is still too low to be used in practice. It is necessary to explore new algorithms, theories and features to further improve the performance.</p> <p>Results</p> <p>In this study, we introduce a novel machine learning model hidden Markov support vector machine for protein binding site prediction. The model treats the protein binding site prediction as a sequential labelling task based on the maximum margin criterion. Common features derived from protein sequences and structures, including protein sequence profile and residue accessible surface area, are used to train hidden Markov support vector machine. When tested on six data sets, the method based on hidden Markov support vector machine shows better performance than some state-of-the-art methods, including artificial neural networks, support vector machines and conditional random field. Furthermore, its running time is several orders of magnitude shorter than that of the compared methods.</p> <p>Conclusion</p> <p>The improved prediction performance and computational efficiency of the method based on hidden Markov support vector machine can be attributed to the following three factors. Firstly, the relation between labels of neighbouring residues is useful for protein binding site prediction. Secondly, the kernel trick is very advantageous to this field. Thirdly, the complexity of the training step for hidden Markov support vector machine is linear with the number of training samples by using the cutting-plane algorithm.</p

Differential Specificity of Endocrine FGF19 and FGF21 to FGFR1 and FGFR4 in Complex with KLB

Background: Recent studies suggest that betaKlotho (KLB) and endocrine FGF19 and FGF21 redirect FGFR signaling to regulation of metabolic homeostasis and suppression of obesity and diabetes. However, the identity of the predominant metabolic tissue in which a major FGFR-KLB resides that critically mediates the differential actions and metabolism effects of FGF19 and FGF21 remain unclear. Methodology/Principal Findings: We determined the receptor and tissue specificity of FGF21 in comparison to FGF19 by using direct, sensitive and quantitative binding kinetics, and downstream signal transduction and expression of early response gene upon administration of FGF19 and FGF21 in mice. We found that FGF21 binds FGFR1 with much higher affinity than FGFR4 in presence of KLB; while FGF19 binds both FGFR1 and FGFR4 in presence of KLB with comparable affinity. The interaction of FGF21 with FGFR4-KLB is very weak even at high concentration and could be negligible at physiological concentration. Both FGF19 and FGF21 but not FGF1 exhibit binding affinity to KLB. The binding of FGF1 is dependent on where FGFRs are present. Both FGF19 and FGF21 are unable to displace the FGF1 binding, and conversely FGF1 cannot displace FGF19 and FGF21 binding. These results indicate that KLB is an indispensable mediator for the binding of FGF19 and FGF21 to FGFRs that is not required for FGF1. Although FGF19 can predominantly activate the responses of the liver and to a less extent the adipose tissue, FGF21 can do so significantly only in the adipose tissue an

Effect of eplerenone on extracellular cardiac matrix biomarkers in patients with acute ST-elevation myocardial infarction without heart failure: insights from the randomized double-blind REMINDER Study

Objective: Aldosterone stimulates cardiac collagen synthesis. Circulating biomarkers of collagen turnover provide a useful tool for the assessment of cardiac remodeling in patients with an acute myocardial infarction (MI).  Methods: The REMINDER trial assessed the effect of eplerenone in patients with an acute ST-elevation Myocardial Infarction (STEMI) without known heart failure (HF), when initiated within 24 h of symptom onset. The primary outcome was almost totally (>90%) driven by natriuretic peptide (NP) thresholds after 1-month post-MI (it also included a composite of cardiovascular death or re-hospitalization or new onset HF or sustained ventricular tachycardia or fibrillation or LVEF ≤40% after 1-month post-MI). This secondary analysis aims to assess the extracellular matrix marker (ECMM) levels with regards to: (1) patients` characteristics; (2) determinants; (3) and eplerenone effect.  Results: Serum levels of ECMM were measured in 526 (52%) of the 1012 patients enrolled in the REMINDER trial. Patients with procollagen type III N-terminal propeptide (PIIINP) above the median were older and had worse renal function (p < 0.05). Worse renal function was associated with increased levels of PIIINP (standardized β ≈ 0.20, p < 0.05). Eplerenone reduced PIIINP when the levels of this biomarker were above the median of 3.9 ng/mL (0.13 ± 1.48 vs. -0.37 ± 1.56 ng/mL, p = 0.008). Higher levels of PIIINP were independently associated with higher proportion of NP above the prespecified thresholds (HR = 1.95, 95% CI 1.16-3.29, p = 0.012).  Conclusions: Eplerenone effectively reduces PIIINP levels when baseline values were above the median. Eplerenone may limit ECMM formation in post-MI without HF

International Recommendations on Reirradiation by Intensity Modulated Radiation Therapy for Locally Recurrent Nasopharyngeal Carcinoma

Purpose: Reirradiation for locally recurrent nasopharyngeal carcinoma (NPC) is challenging because prior radiation dose delivered in the first course is often close to the tolerance limit of surrounding normal structures. A delicate balance between achieving local salvage and minimizing treatment toxicities is needed. However, high-level evidence is lacking because available reports are mostly retrospective studies on small series of patients. Pragmatic consensus guidelines, based on an extensive literature search and the pooling of opinions by leading specialists, will provide a useful reference to assist decision-making for these difficult decisions. Methods and Materials: A thorough review of available literature on recurrent NPC was conducted. A set of questions and preliminary draft guideline was circulated to a panel of international specialists with extensive experience in this field for voting on controversial areas and comments. A refined second proposal, based on a summary of the initial voting and different opinions expressed, was recirculated to the whole panel for review and reconsideration. The current guideline was based on majority voting after repeated iteration for final agreement. Results: The initial round of questions showed variations in clinical practice even among the specialists, reflecting the lack of high-quality supporting data and the difficulties in formulating clinical decisions. Through exchange of comments and iterative revisions, recommendations with high-to-moderate agreement were formulated on general treatment strategies and details of reirradiation (including patient selection, targets contouring, dose prescription, and constraints). Conclusion: This paper provides useful reference on radical salvage treatment strategies for recurrent NPC and optimization of reirradiation through review of published evidence and consensus building. However, the final decision by the attending clinician must include full consideration of an individual patient's condition, understanding of the delicate balance between risk and benefits, and acceptance of risk of complications. (C) 2021 Elsevier Inc. All rights reserved