Validation of purdue engineering shape benchmark clusters by crowdsourcing

The effective organization of CAD data archives is central to PLM and consequently content based retrieval of 2D drawings and 3D models is often seen as a "holy grail" for the industry. Given this context, it is not surprising that the vision of a "Google for shape", which enables engineers to search databases of 3D models for components similar in shape to a query part, has motivated numerous researchers to investigate algorithms for computing geometric similarity. Measuring the effectiveness of the many approaches proposed has in turn lead to the creation of benchmark datasets against which researchers can compare the performance of their search engines. However to be useful the datasets used to measure the effectiveness of 3D retrieval algorithms must not only define a collection of models, but also provide a canonical specification of their relative similarity. Because the objective of shape retrieval algorithms is (typically) to retrieve groups of objects that humans perceive as "similar" these benchmark similarity relationships have (by definition) to be manually determined through inspection

Geometric reasoning via internet crowdsourcing

The ability to interpret and reason about shapes is a peculiarly human capability that has proven difficult to reproduce algorithmically. So despite the fact that geometric modeling technology has made significant advances in the representation, display and modification of shapes, there have only been incremental advances in geometric reasoning. For example, although today's CAD systems can confidently identify isolated cylindrical holes, they struggle with more ambiguous tasks such as the identification of partial symmetries or similarities in arbitrary geometries. Even well defined problems such as 2D shape nesting or 3D packing generally resist elegant solution and rely instead on brute force explorations of a subset of the many possible solutions. Identifying economic ways to solving such problems would result in significant productivity gains across a wide range of industrial applications. The authors hypothesize that Internet Crowdsourcing might provide a pragmatic way of removing many geometric reasoning bottlenecks.This paper reports the results of experiments conducted with Amazon's mTurk site and designed to determine the feasibility of using Internet Crowdsourcing to carry out geometric reasoning tasks as well as establish some benchmark data for the quality, speed and costs of using this approach.After describing the general architecture and terminology of the mTurk Crowdsourcing system, the paper details the implementation and results of the following three investigations; 1) the identification of "Canonical" viewpoints for individual shapes, 2) the quantification of "similarity" relationships with-in collections of 3D models and 3) the efficient packing of 2D Strips into rectangular areas. The paper concludes with a discussion of the possibilities and limitations of the approach

Geometric Reasoning With a Virtual Workforce (Crowdsourcing for CAD/CAM)

This paper reports the initial results of employing a commercial Crowdsourcing (aka Micro-outsourcing) service to provide geometric analysis of complex 3D models of mechanical components. Although Crowdsourcing sites (which distribute browser based tasks to potentially large numbers of anonymous workers on the Internet) are well established for image analysis and text manipulation there is little academic work on the effectiveness or limitations of the approach. The work reported here describes the initial results of using Crowdsourcing to determine the 'best' canonical, or characteristic, views of complex 3D models of engineering components. The results suggest that the approach is a cheap, fast and effective method of solving what is a computationally difficult problem

Blood oxygenation-level dependent cerebrovascular reactivity imaging as strategy to monitor CSF-hemoglobin toxicity

Objectives: Cell-free hemoglobin in the cerebrospinal fluid (CSF-Hb) may be one of the main drivers of secondary brain injury after aneurysmal subarachnoid hemorrhage (aSAH). Haptoglobin scavenging of CSF-Hb has been shown to mitigate cerebrovascular disruption. Using digital subtraction angiography (DSA) and blood oxygenation-level dependent cerebrovascular reactivity imaging (BOLD-CVR) the aim was to assess the acute toxic effect of CSF-Hb on cerebral blood flow and autoregulation, as well as to test the protective effects of haptoglobin. Methods: DSA imaging was performed in eight anesthetized and ventilated sheep (mean weight: 80.4 kg) at baseline, 15, 30, 45 and 60 minutes after infusion of hemoglobin (Hb) or co-infusion with haptoglobin (Hb:Haptoglobin) into the left lateral ventricle. Additionally, 10 ventilated sheep (mean weight: 79.8 kg) underwent BOLD-CVR imaging to assess the cerebrovascular reserve capacity. Results: DSA imaging did not show a difference in mean transit time or cerebral blood flow. Whole-brain BOLD-CVR compared to baseline decreased more in the Hb group after 15 minutes (Hb vs Hb:Haptoglobin: -0.03 ± 0.01 vs -0.01 ± 0.02) and remained diminished compared to Hb:Haptoglobin group after 30 minutes (Hb vs Hb:Haptoglobin: -0.03 ± 0.01 vs 0.0 ± 0.01), 45 minutes (Hb vs Hb:Haptoglobin: -0.03 ± 0.01 vs 0.01 ± 0.02) and 60 minutes (Hb vs Hb:Haptoglobin: -0.03 ± 0.02 vs 0.01 ± 0.01). Conclusion: It is demonstrated that CSF-Hb toxicity leads to rapid cerebrovascular reactivity impairment, which is blunted by haptoglobin co-infusion. BOLD-CVR may therefore be further evaluated as a monitoring strategy for CSF-Hb toxicity after aSAH

HLA Ligand Atlas: a benign reference of HLA-presented peptides to improve T-cell-based cancer immunotherapy

BACKGROUND The human leucocyte antigen (HLA) complex controls adaptive immunity by presenting defined fractions of the intracellular and extracellular protein content to immune cells. Understanding the benign HLA ligand repertoire is a prerequisite to define safe T-cell-based immunotherapies against cancer. Due to the poor availability of benign tissues, if available, normal tissue adjacent to the tumor has been used as a benign surrogate when defining tumor-associated antigens. However, this comparison has proven to be insufficient and even resulted in lethal outcomes. In order to match the tumor immunopeptidome with an equivalent counterpart, we created the HLA Ligand Atlas, the first extensive collection of paired HLA-I and HLA-II immunopeptidomes from 227 benign human tissue samples. This dataset facilitates a balanced comparison between tumor and benign tissues on HLA ligand level. METHODS Human tissue samples were obtained from 16 subjects at autopsy, five thymus samples and two ovary samples originating from living donors. HLA ligands were isolated via immunoaffinity purification and analyzed in over 1200 liquid chromatography mass spectrometry runs. Experimentally and computationally reproducible protocols were employed for data acquisition and processing. RESULTS The initial release covers 51 HLA-I and 86 HLA-II allotypes presenting 90,428 HLA-I- and 142,625 HLA-II ligands. The HLA allotypes are representative for the world population. We observe that immunopeptidomes differ considerably between tissues and individuals on source protein and HLA-ligand level. Moreover, we discover 1407 HLA-I ligands from non-canonical genomic regions. Such peptides were previously described in tumors, peripheral blood mononuclear cells (PBMCs), healthy lung tissues and cell lines. In a case study in glioblastoma, we show that potential on-target off-tumor adverse events in immunotherapy can be avoided by comparing tumor immunopeptidomes to the provided multi-tissue reference. CONCLUSION Given that T-cell-based immunotherapies, such as CAR-T cells, affinity-enhanced T cell transfer, cancer vaccines and immune checkpoint inhibition, have significant side effects, the HLA Ligand Atlas is the first step toward defining tumor-associated targets with an improved safety profile. The resource provides insights into basic and applied immune-associated questions in the context of cancer immunotherapy, infection, transplantation, allergy and autoimmunity. It is publicly available and can be browsed in an easy-to-use web interface at https://hla-ligand-atlas.org

EMA-amplicon-based sequencing informs risk assessment analysis of water treatment systems

Illumina amplicon-based sequencing was coupled with ethidium monoazide bromide (EMA) pre-treatment to monitor the total viable bacterial community and subsequently identify and prioritise the target organisms for the health risk assessment of the untreated rainwater and rainwater treated using large-volume batch solar reactor prototypes installed in an informal settlement and rural farming community. Taxonomic assignments indicated that Legionella and Pseudomonas were the most frequently detected genera containing opportunistic bacterial pathogens in the untreated and treated rainwater at both sites. Additionally, Mycobacterium, Clostridium sensu stricto and Escherichia/Shigella displayed high (≥80%) detection frequencies in the untreated and/or treated rainwater samples at one or both sites. Numerous exposure scenarios (e.g. drinking, cleaning) were subsequently investigated and the health risk of using untreated and solar reactor treated rainwater in developing countries was quantified based on the presence of L. pneumophila, P. aeruginosa and E. coli. The solar reactor prototypes were able to reduce the health risk associated with E. coli and P. aeruginosa to below the 1 × 10−4 annual benchmark limit for all the non-potable uses of rainwater within the target communities (exception of showering for E. coli). However, the risk associated with intentional drinking of untreated or treated rainwater exceeded the benchmark limit (E. coli and P. aeruginosa). Additionally, while the solar reactor treatment reduced the risk associated with garden hosing and showering based on the presence of L. pneumophila, the risk estimates for both activities still exceeded the annual benchmark limit. The large-volume batch solar reactor prototypes were thus able to reduce the risk posed by the target bacteria for non-potable activities rainwater is commonly used for in water scarce regions of sub-Saharan Africa. This study highlights the need to assess water treatment systems in field trials using QMRA

Involvement of the Efflux Pumps in Chloramphenicol Selected Strains of Burkholderia thailandensis: Proteomic and Mechanistic Evidence

Burkholderia is a bacterial genus comprising several pathogenic species, including two species highly pathogenic for humans, B. pseudomallei and B. mallei. B. thailandensis is a weakly pathogenic species closely related to both B. pseudomallei and B. mallei. It is used as a study model. These bacteria are able to exhibit multiple resistance mechanisms towards various families of antibiotics. By sequentially plating B. thailandensis wild type strains on chloramphenicol we obtained several resistant variants. This chloramphenicol-induced resistance was associated with resistance against structurally unrelated antibiotics including quinolones and tetracyclines. We functionally and proteomically demonstrate that this multidrug resistance phenotype, identified in chloramphenicol-resistant variants, is associated with the overexpression of two different efflux pumps. These efflux pumps are able to expel antibiotics from several families, including chloramphenicol, quinolones, tetracyclines, trimethoprim and some β-lactams, and present a partial susceptibility to efflux pump inhibitors. It is thus possible that Burkholderia species can develop such adaptive resistance mechanisms in response to antibiotic pressure resulting in emergence of multidrug resistant strains. Antibiotics known to easily induce overexpression of these efflux pumps should be used with discernment in the treatment of Burkholderia infections

Anti-infectives in Drug Delivery-Overcoming the Gram-Negative Bacterial Cell Envelope.

Infectious diseases are becoming a major menace to the state of health worldwide, with difficulties in effective treatment especially of nosocomial infections caused by Gram-negative bacteria being increasingly reported. Inadequate permeation of anti-infectives into or across the Gram-negative bacterial cell envelope, due to its intrinsic barrier function as well as barrier enhancement mediated by resistance mechanisms, can be identified as one of the major reasons for insufficient therapeutic effects. Several in vitro, in silico, and in cellulo models are currently employed to increase the knowledge of anti-infective transport processes into or across the bacterial cell envelope; however, all such models exhibit drawbacks or have limitations with respect to the information they are able to provide. Thus, new approaches which allow for more comprehensive characterization of anti-infective permeation processes (and as such, would be usable as screening methods in early drug discovery and development) are desperately needed. Furthermore, delivery methods or technologies capable of enhancing anti-infective permeation into or across the bacterial cell envelope are required. In this respect, particle-based carrier systems have already been shown to provide the opportunity to overcome compound-related difficulties and allow for targeted delivery. In addition, formulations combining efflux pump inhibitors or antimicrobial peptides with anti-infectives show promise in the restoration of antibiotic activity in resistant bacterial strains. Despite considerable progress in this field however, the design of carriers to specifically enhance transport across the bacterial envelope or to target difficult-to-treat (e.g., intracellular) infections remains an urgently needed area of improvement. What follows is a summary and evaluation of the state of the art of both bacterial permeation models and advanced anti-infective formulation strategies, together with an outlook for future directions in these fields