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Background and Aims Lumen-apposing metal stents (LAMSs) provide an endoscopic method for management of walled-off necrosis (WON) and a gateway for the performance of endoscopic necrosectomy (EN). However, bleeding may occur in up to 20% of EN procedures. Predictive factors for bleeding in this patient population are unknown, and there is no agreed-upon algorithm for management of bleeding. The aim of this study was to evaluate preprocedural risk factors for bleeding in patients undergoing endoscopic drainage or EN for WON. Methods A retrospective cohort of patients undergoing EN for WON was reviewed. Demographics, comorbidities, concurrent medications, and etiology of pancreatitis were recorded. Pre-, peri-, and postprocedural clinical variables were compared using Chi-squared test and independent t-test. Results Between June 2014 and October 2020, 536 EN were performed in 151 patients. Intraprocedural bleeding occurred during 28 procedures (5.2%) in 18 patients (11.9%.) Endoscopic hemostasis was attempted in 8 patients (10 procedures). Eight patients (10 procedures) in total were treated by IR. Thrombocytopenia (p = 0.006) and cirrhosis (p = 0.049) were associated with intraprocedural bleeding, although thrombocytopenia was present in only one patient. Identification of a vessel within the cavity endoscopically was also associated with bleeding (p Conclusions EN for WON was associated with a 5.2% per procedure risk of bleeding and an 11.9% per-patient bleeding risk. Identification of a vessel within the cavity during endoscopy is predictive of bleeding during EN. Patients who require more transfusions before endoscopy may require earlier intervention by IR.

MotivationIllustrative renderings of proteins are useful aids for scientific communication and education. Nevertheless, few software packages exist to automate the generation of these visualizations.ResultsWe introduce CellScape, a tool designed to generate 2D molecular cartoons from atomic coordinates and combine them into larger cellular scenes. These illustrations can outline protein regions in different levels of detail. Unlike most molecular visualization tools which use raster image formats, these illustrations are represented as vector graphics, making them easily editable and composable with other graphics.Availability and ImplementationCellScape is implemented in Python 3 and freely available at https://github.com/jordisr/cellscape. It can be run as a command-line tool or interactively in a Jupyter notebook.Contactjordisr@berkeley.edu

How do instantaneous rate models of insertion-deletion processes relate to distributions over pairwise sequence alignments? The only exactly-solved model is the 1991 Thorne....., We introduce a systematic method of approximating finite-time transition probabilities for continuous-time insertion-deletion models on sequences. The method uses automata theory to describe the action of an infinitesimal evolutionary generator on a probability distribution over alignments, where both the generator and the alignment distribution can be represented by pair hidden Markov models (HMMs). In general, combining HMMs in this way induces a multiplication of their state spaces; to control this, we introduce a coarse-graining operation to keep the state space at a constant size. This leads naturally to ordinary differential equations for the evolution of the transition probabilities of the approximating pair HMM. The TKF91 model emerges as an exact solution to these equations for the special case of single-residue indels. For the more general case of multiple-residue indels, the equations can be solved by numerical integration. Using simulated data, we show that the resulting distribution over alignments, when compared to previous approximations, is a better fit over a broader range of parameters. We also propose a related approach to develop differential equations for sufficient statistics to estimate the underlying instantaneous indel rates by expectation maximization. Our code and data are available at https://github.com/ihh/trajectory-likelihood.

As one of the US Department of Agriculture—Agricultural Research Service flagship databases, GrainGenes (https://wheat.pw.usda.gov) serves the data and community needs of globally distributed small grains researchers for the genetic improvement of the Triticeae family and Avena species that include wheat, barley, rye and oat. GrainGenes accomplishes its mission by continually enriching its cross-linked data content following the findable, accessible, interoperable and reusable principles, enhancing and maintaining an intuitive web interface, creating tools to enable easy data access and establishing data connections within and between GrainGenes and other biological databases to facilitate knowledge discovery. GrainGenes operates within the biological database community, collaborates with curators and genome sequencing groups and contributes to the AgBioData Consortium and the International Wheat Initiative through the Wheat Information System (WheatIS). Interactive and linked content is paramount for successful biological databases and GrainGenes now has 2917 manually curated gene records, including 289 genes and 254 alleles from the Wheat Gene Catalogue (WGC). There are >4.8 million gene models in 51 genome browser assemblies, 6273 quantitative trait loci and >1.4 million genetic loci on 4756 genetic and physical maps contained within 443 mapping sets, complete with standardized metadata. Most notably, 50 new genome browsers that include outputs from the Wheat and Barley PanGenome projects have been created. We provide an example of an expression quantitative trait loci track on the International Wheat Genome Sequencing Consortium Chinese Spring wheat browser to demonstrate how genome browser tracks can be adapted for different data types. To help users benefit more from its data, GrainGenes created four tutorials available on YouTube. GrainGenes is executing its vision of service by continuously responding to the needs of the global small grains community by creating a centralized, long-term, interconnected data repository. Database URL:https://wheat.pw.usda.gov

Background and Aims Stent misdeployment (SM) has hindered the dissemination of EUS-guided gastroenterostomy (EUS-GE) for gastric outlet obstruction (GOO) management. We aimed to provide a classification system for SM during EUS-GE and study clinical outcomes and management accordingly. Methods This is a retrospective study involving 16 tertiary care centers (8 in the United States, 8 in Europe) from March 2015 to December 2020. Patients who developed SM during EUS-GE for GOO were included. We propose classifying SM into 4 types. The primary outcome was rate and severity of SM (per American Society for Gastrointestinal Endoscopy lexicon), whereas secondary outcomes were clinical outcomes and management of dislodgement according to the SM classification type, in addition to salvage management of GOO after SM. Results From 467 EUS-GEs performed for GOO during the study period, SM occurred in 46 patients (9.85%). Most SMs (73.2%) occurred during the first 13 EUS-GE cases by the performing operators. SM was graded as mild (n = 28, 60.9%), moderate (n = 11, 23.9%), severe (n = 6, 13.0%), or fatal (n = 1, 2.2%), with 5 patients (10.9%) requiring surgical intervention. Type I SM was the most common (n = 29, 63.1%), followed by type II (n = 14, 30.4%), type IV (n = 2, 4.3%), and type III (n = 1, 2.2%). Type I SM was more frequently rated as mild compared with type II SM (75.9% vs 42.9%, P = .04) despite an equivalent rate of surgical repair (10.3% vs 7.1%, P = .7). Overall, 4 patients (8.7%) required an intensive care unit stay (median, 2.5 days). The median length of stay was 4 days after SM. Conclusions Although SM is not infrequent during EUS-GE, most are type I, mild/moderate in severity, and can be managed endoscopically with a surgical intervention rate of approximately 11%.

International audience; Following the emerging bluetongue virus transmission in European temperate regions, we question the vector competence of the abundant Culicoides austropalpalis Lee and Reye in South-East temperate Australia. Field collected Culicoides midges were membrane fed with a bluetongue virus serotype 1 (BTV-1). The average feeding rate was 50%. After 13 days, survival rate was 25% and virus RNA presence was checked by quantitative PCR targeting viral genome segment 10. Virus RNA was found in 7.4% of individually tested females with relative viral RNA load values lower than freshly fed females, indicating that viral replication was low or null. A second qPCR targeting viral genome segment 1 confirmed the presence of virus RNA in only four out of 29 previously positive specimens. After 10 days culture on Culicoides cells, none of these four confimed positive samples did show subsequent cytopathogenic effect on Vero cells or BTV antigen detection by ELISA. As control for this virus activity detection, 12 days after microinjection of BTV-1, Culex annulirostris mosquitoes showed, after culture on Kc cells, cytopathogenic effect on Vero cells, with ELISA-confirmed infection. Despite its abundance in farm environment of the temperate Australian regions, the results of this study make C. austropalpalis of unlikely epidemiological importance in the transmission of BTV in Australia.

For the first time, nanofluid boiling was applied as a process for the creation of a semiconductor TiO

Asphalt can be considered a particulate composite with almost no tensile strength, that is, the only physical link between the matrix (bitumen) and the particles (gravel) is the cohesive strength of the bond itself and the aggregate simply breaks away from the binder under any number of tension-based loads such as earth shifts, heavy loads, and even moisture. Over the course of a few months, these breaks lead to larger cracks, potholes, and damaged entire road sections that require significant investment much earlier than the expected 15-year lifecycle. Increasing the strength and modulus of asphalt can improve its durability, extend its lifespan, and reduce its maintenance costs. However, as most asphalt is usually recycled during rehabilitation, improving strength cannot come at the expense of the existing infrastructure support system, i.e., materials and technologies should be compatible with road resurfacing equipment and practices. Short composite fibers have high modulus and strength but are easily broken up by road milling machines, making them ideal candidates to mix into the asphalt during rehabilitation. Additionally, by deliberately limiting the fiber size, this will have a major ancillary benefit for the environment: allowing the use of off-fall composite scraps from the manufacturing sectors that are often chopped and relegated to landfills. This investigation examines the material behavior from both experimental and numerical perspective on the inclusion of short fibers for reinforcing asphalt, creating a dual fiber and particle composite material system. Asphalt by its very nature is a relatively soft material with high strains until failure under some conditions, and brittle under others, making this a complex material system combining both hyperelastic and elastic-brittle response. Validation studies are examined for this unique material under various quasi-static to dynamic loading rates to create a material system for extended finite element analysis in improved infrastructure designs.

Background and study aims The use of lumen apposing metal stents (LAMS) during EUS-guided transmural drainage (EUS-TD) of pancreatic walled-off necrosis (WON) has gained popularity. Data supporting their use in WON over plastic stents (PS), however, remain scarce. The aim of this study was to compare the clinical efficacy of LAMS (Axios, Boston Scientific) with PS in WON. Patients and methods This was a multicenter, retrospective study involving 14 centers. Consecutive patients who underwent EUS-TD of WON (2012 – 2016) were included. The primary end point was clinical success defined as WON size ≤ 3 cm within a 6-month period without need for percutaneous drainage (PCD) or surgery. Results A total of 189 patients (mean age 55.2 ± 15.6 years, 34.9 % female) were included (102 LAMS and 87 PS). Technical success rates were similar: 100 % in LAMS and 98.9 % in PS (P = 0.28). Clinical success was attained in 80.4 % of LAMS and 57.5 % of PS (P = 0.001). Rate of PCD was similar (13.7 % LAMS vs. 16.3 % PS, P = 0.62), while PS was associated with a greater need for surgery (16.1 % PS vs. 5.6 % LAMS, P = 0.02). Adverse events (AEs) were observed in 9.8 % of LAMS and 10.3 % of PS (P = 0.90) and were rated as severe in 2.0 % and 6.9 %, respectively (P = 0.93). After excluding patients with Conclusions When compared to PS, LAMS in WON is associated with higher clinical success, shorter procedure time, lower need for surgery, and lower rate of recurrence.

Background Detecting copy number variations (CNVs) and copy number alterations (CNAs) based on whole-genome sequencing data is important for personalized genomics and treatment. CNVnator is one of the most popular tools for CNV/CNA discovery and analysis based on read depth. Findings Herein, we present an extension of CNVnator developed in Python—CNVpytor. CNVpytor inherits the reimplemented core engine of its predecessor and extends visualization, modularization, performance, and functionality. Additionally, CNVpytor uses B-allele frequency likelihood information from single-nucleotide polymorphisms and small indels data as additional evidence for CNVs/CNAs and as primary information for copy number–neutral losses of heterozygosity. Conclusions CNVpytor is significantly faster than CNVnator—particularly for parsing alignment files (2–20 times faster)—and has (20–50 times) smaller intermediate files. CNV calls can be filtered using several criteria, annotated, and merged over multiple samples. Modular architecture allows it to be used in shared and cloud environments such as Google Colab and Jupyter notebook. Data can be exported into JBrowse, while a lightweight plugin version of CNVpytor for JBrowse enables nearly instant and GUI-assisted analysis of CNVs by any user. CNVpytor release and the source code are available on GitHub at https://github.com/abyzovlab/CNVpytor under the MIT license.

Detecting copy number variations (CNVs) and copy number alterations (CNAs) based on whole genome sequencing data is important for personalized genomics and treatment. CNVnator is one of the most popular tools for CNV/CNA discovery and analysis based on read depth (RD). Herein, we present an extension of CNVnator developed in Python -- CNVpytor. CNVpytor inherits the reimplemented core engine of its predecessor and extends visualization, modularization, performance, and functionality. Additionally, CNVpytor uses B-allele frequency (BAF) likelihood information from single nucleotide polymorphism and small indels data as additional evidence for CNVs/CNAs and as primary information for copy number neutral losses of heterozygosity. CNVpytor is significantly faster than CNVnator—particularly for parsing alignment files (2 to 20 times faster)—and has (20-50 times) smaller intermediate files. CNV calls can be filtered using several criteria and annotated. Modular architecture allows it to be used in shared and cloud environments such as Google Colab and Jupyter notebook. Data can be exported into JBrowse, while a lightweight plugin version of CNVpytor for JBrowse enables nearly instant and GUI-assisted analysis of CNVs by any user. CNVpytor release and the source code are available on GitHub at https://github.com/abyzovlab/CNVpytor under the MIT license.

Understanding population connectivity within a species as well as potential interactions with its close relatives is crucial to define management units and to derive efficient management actions. However, although genetics can reveal mismatches between biological and management units and other relevant but hidden information such as species misidentification or hybridization, the uptake of genetic methods by the fisheries management process is far from having been consolidated. Here, we have assessed the power of genetics to better understand the population connectivity of white (Lophius piscatorius) and its interaction with its sister species, the black anglerfish (Lophius budegassa). Our analyses, based on thousands of genome-wide single nucleotide polymorphisms, show three findings that are crucial for white anglerfish management. We found (i) that white anglerfish is likely composed of a single panmictic population throughout the Northeast Atlantic, challenging the three-stock based management, (ii) that a fraction of specimens classified as white anglerfish using morphological characteristics are genetically identified as black anglerfish (L. budegassa), and iii) that the two Lophius species naturally hybridize leading to a population of hybrids of up to 20% in certain areas. Our results set the basics for a genetics-informed white anglerfish assessment framework that accounts for stock connectivity, revises and establishes new diagnostic characters for Lophius species identification, and evaluates the effect of hybrids in the current and future assessments of the white anglerfish. Furthermore, our study contributes to provide additional evidence of the potentially negative consequences of ignoring genetic data for assessing fisheries resources., SI

BACKGROUND: The novel human coronavirus SARS-CoV-2 is a major ongoing global threat with huge economic burden. Like all respiratory viruses, SARS-CoV-2 initiates infection in the upper respiratory tract (URT). Infected individuals are often asymptomatic, yet highly infectious and readily transmit virus. A therapy that restricts initial replication in the URT has the potential to prevent progression of severe lower respiratory tract disease as well as limiting person-to-person transmission. METHODS: SARS-CoV-2 Victoria/01/2020 was passaged in Vero/hSLAM cells and virus titre determined by plaque assay. Challenge virus was delivered by intranasal instillation to female ferrets at 5.0 × 106 pfu/ml. Treatment groups received intranasal INNA-051, developed by Ena Respiratory. SARS-CoV-2 RNA was detected using the 2019-nCoV CDC RUO Kit and QuantStudio™ 7 Flex Real-Time PCR System. Histopathological analysis was performed using cut tissues stained with haematoxylin and eosin (H&E). FINDINGS: We show that prophylactic intra-nasal administration of the TLR2/6 agonist INNA-051 in a SARS-CoV-2 ferret infection model effectively reduces levels of viral RNA in the nose and throat. After 5 days post-exposure to SARS-CoV-2, INNA-051 significantly reduced virus in throat swabs (p=

Genome browsers are essential tools for integrating, exploring, and visualizing data from large cancer genomics datasets. JBrowse 2 is a JavaScript genome browser with novel features for visualizing structural variants, syntenic alignments, and multiple types of genomic data. Although JBrowse 2 is available as a web-based or desktop application, the capabilities and features are not fixed and can be expanded through a comprehensive plugin system. To help address users' needs, we launched the new JBrowse 2 Plugin Store (https://jbrowse.org/jb2/plugin_store/). The overarching goals of the Plugin Store are to showcase the crucial features plugins add to JBrowse 2, to enable researchers to search for plugins they need, and for developers to highlight their plugins. The plugin system spans all aspects of the JBrowse 2 application and enables new track types (e.g. Manhattan plots, Hi-C data, ideograms), data adapters (e.g. API endpoint adapters for NCI Genomic Data Commons and the International Cancer Genome Consortium), and views (e.g. dot plots and multiple sequence alignments). Here, we present the capabilities of JBrowse 2 plugins and describe usage scenarios for cancer biologists and bioinformaticians, and software developers. Citation Format: Robin Andrew Haw, Colin Diesh, Caroline Bridge, Rob Buels, Garrett Stevens, Peter Xie, Teresa Martinez, Elliot Hershberg, Junjun Zhang, Shihab Dider, Scott Cain, Lincoln Stein, Ian Holmes. Using JBrowse 2 plugins to visualize cancer genomic data [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr LB503.

Introduction: Genome browsers are useful tools for research in human genetics, able to display and integrate biological information such as long and short read sequencing data, variant calls, and annotations. While traditional linear genome browsers have demonstrated broad utility for many applications, there is an increasing need for visualizing complex structural variants (SVs) beyond the linear view. To meet these challenges, we created JBrowse 2: an extensible open-source platform for visualizing and integrating genomic data. Results: JBrowse 2 is a flexible platform that provides the foundation for the development of applications and web dashboards that combine novel views and representations extending beyond linear displays in genomic reference coordinates. For example, a flagship JBrowse 2 application is the SV Inspector, which lets users open a list of structural variants in a data table and see the results in a whole-genome circular view. Clicking on a given variant in the table or circular view opens up a linear view that displays the read evidence supporting the SV, even across complex breakpoints like translocations. Dotplot and synteny views are built-in, enabling “long read vs reference” dotplot visualizations, or alignments of de-novo assembled contigs to the genome. These views are integrated with each other, so that (for example) a long read is just a few clicks away from the corresponding dotplot. In addition to including these new views, the JBrowse 2 platform is designed from the ground up to enable third-party plugins to add new views, data adapters, and track types, which has facilitated the creation of new plugins that address some very specific use cases. These include our MSA view plugin for viewing multiple sequence alignments, data adapters that download data from UCSC and CIVIC APIs, and the Quantseq plugin for viewing quantitative motif scores as a genome browser track. JBrowse 2 is available as both a web app or a local desktop app. We also offer re-usable components on NPM, and users of R can programmatically create an instance of JBrowse 2 with the JBrowseR package on CRAN. JBrowse 2 can also generate high quality SVG snapshots from inside the app, and we also created a CLI tool called jb2export to perform automated or bulk exports of JBrowse 2 visualizations. We anticipate that JBrowse 2 will better serve genome scientists with its structural variant visualization capabilities, and will provide the flexibility to adapt to new visualization and analysis challenges as they emerge in the coming years. Citation Format: Scott Cain, Robin Haw, Caroline Bridge, Junjun Zhang, Robert Buels, Colin Diesh, Garrett Stevens, Teresa Martinez, Peter K. Xie, Elliot Hershberg, Shihab Dider, Lincoln Stein, Ian Holmes. JBrowse 2: An extensible open-source platform for modern genome analysis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 6400.

Background: Treatment approaches that engage both the innate and adaptive immune response have the potential to transform anti-cancer therapy, especially in settings of checkpoint inhibitor insensitivity or acquired resistance. Toll-like receptors (TLRs) are a class of targets that mediate the initial cellular response to external pathogens or endogenous alarmins, activating downstream pro-inflammatory cascades and leading to the activation and recruitment of key innate subsets. TLR2 is a cell surface receptor, expressed predominantly on macrophages, dendritic cells (DC), neutrophils and subsets of NK and T cells. TLR2 signaling plays important role in NK and T cell cytolytic cell functions, as well as DC and macrophage activation. AXA-042 is a novel synthetic TLR2/6 agonist designed for systemic delivery to re-engage the innate immune response to help overcome tumour immune escape. Methods: In vitro potency and selectivity of AXA-042 was assessed across a panel of human and mouse HEK-blue TLR reporter assays. AXA-042 activity was profiled relative to other TLR agonists in human PBMC cytokine release assays. AXA-042 in vivo efficacy was evaluated in the EMT6 and CT26 syngeneic tumour models. The Nanostring nCounter™ Mouse PanCancer Immune Profiling Panel was used to identify AXA-042 tumour-localized and peripheral response signatures. Results: AXA-042 demonstrated potent and selective activity in murine and human TLR2/6 reporter assays and a differential PBMC cytokine release profile relative to other TLR agonists in vitro. Systemic delivery (QW, IV or IP) of AXA-042 significantly inhibited EMT6 and CT26 tumour growth, which was accompanied by an increase in circulating plasma levels of IL6, IL12 and CXCL10. Combination with anti-PD-1 Ab further potentiated anti-tumour response, resulting in approximately 30-40% tumour regressions. AXA-042 anti-tumour effects were accompanied by increased activation of the tumour-infiltrating myeloid cells, including DCs and macrophages, and a reduction in the M2 TAM subset. Nanostring analysis confirmed TLR and IFNγ pathway engagement and revealed an induction of gene signatures associated with macrophage, DC and NK functions. Longitudinal studies to characterize whole blood biomarkers associated with response are currently in progress. Conclusion: AXA-042 was well tolerated in vivo and demonstrated innate response engagement and anti-tumour efficacy as monotherapy and in combination with anti-PD-1 immunotherapy. AXA-042 has completed GLP toxicology studies and initiation of Phase 1/1b trial is planned for early 2022. Citation Format: Anna V. Galkin, Francesca Mercuri, Nicholas West, Ping Zhang, Weiguang Zeng, Grant McLachlan, Michael Bettess, Ian Holmes, David Jackson, Chris Smith, Christophe Demaison, Tobias Bald, Phil Kearney. AXA-042 - a novel systemic TLR2/6 agonist for anti-tumor therapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3502.

Video Video 1 EGD, which showed obstructed distal flange of the gastrojejunal lumen-apposing metal stent (LAMS) by the contralateral jejunal wall. Two double-pigtail stents were placed across the LAMS to relieve the obstruction.

Motivation Genome browsers are an essential tool in genome analysis. Modern genome browsers enable complex and interactive visualization of a wide variety of genomic data modalities. While such browsers are very powerful, they can be challenging to configure and program for bioinformaticians lacking expertise in web development. Results We have developed an R package that provides an interface to the JBrowse 2 genome browser. The package can be used to configure and customize the browser entirely with R code. The browser can be deployed from the R console, or embedded in Shiny applications or R Markdown documents. Availability and implementation JBrowseR is available for download from CRAN, and the source code is openly available from the Github repository at https://github.com/GMOD/JBrowseR/.

We introduce a systematic method of approximating finite-time transition probabilities for continuous-time insertion-deletion models on sequences. The method uses automata theory to describe the action of an infinitesimal evolutionary generator on a probability distribution over alignments, where both the generator and the alignment distribution can be represented by Pair Hidden Markov Models (Pair HMMs). In general, combining HMMs in this way induces a multiplication of their state spaces; to control this, we introduce a coarse-graining operation to keep the state space at a constant size. This leads naturally to ordinary differential equations for the evolution of the transition probabilities of the approximating Pair HMM. The TKF model emerges as an exact solution to these equations for the special case of single-residue indels. For the general case, the equations can be solved by numerical integration. Using simulated data we show that the resulting distribution over alignments, when compared to previous approximations, is a better fit over a broader range of parameters. We also propose a related approach to develop differential equations for sufficient statistics to estimate the underlying instantaneous indel rates by Expectation-Maximization. Our code and data are available athttps://github.com/ihh/trajectory-likelihood.

JBrowse and Apollo: Tools for Genome Visualization and Annotation https://github.com/GMOD/jbrowse https://github.com/GMOD/Apollo JBrowse 2: https://github.com/GMOD/jbrowse-components

Impacts between birds and aircraft, referred to as bird strikes, are remarkably common and present a major issue with flight safety as a single incident can cause catastrophic damage. The Federal Aviation Administration requires that aircraft must withstand these impacts through testing using euthanized birds. This process is unethical, inefficient, costly and unreliable. Previous research has validated gelatin as a replacement material and hydrodynamic modeling as a computational approach. A great variation in results remains due to a lack of standardization in the experimental and computational testing methodologies. Authorities agree that a standard approach will better facilitate testing and reduce the threat that bird strikes pose. We hypothesized that further testing of gelatin substitutes and numerical approaches using advanced processing would facilitate impactful results and aid in introducing a new global bird strike testing standard. High-speed impacts on a Hopkinson bar and dynamic impacts using a pendulum serve to identify a valid setup and design that best represents impact behavior. Smoothed particle hydrodynamics (SPH) is used to create a numerical model representing the fluid nature of the collision. By performing various impacts through various techniques, we hypothesize that the numerical SPH model will validate the material behavior by yielding accurate force-time profiles. Implementing this model will allow for reliable prediction of material response and damage evolution following bird strike impacts.

Nanopore technology allows for direct sequencing of individual DNA duplexes. However, its higher error rate compared to other sequencing methods has limited its application in situations where deep coverage is unavailable, such as detection of rare variants or characterization of highly polymorphic samples. In principle, 2X coverage is available even for single duplexes, using Oxford Nanopore Technologies’ 1D2protocol or related methods which sequence both strands of the duplex consecutively. Using both strands should improve accuracy; however, most neural network basecaller architectures are designed to operate on single strands. We have developed a general approach for improving accuracy of 1D2and related protocols by finding the consensus of two neural network basecallers, by combining a constrained profile-profile alignment with a heuristic variant of beam search. When run on a basecalling neural network we trained, our consensus algorithm improves median basecall accuracy from 86.2% (for single-read decoding) to 92.1% (for pair decoding). Our software can readily be adapted to work with the output of other basecallers, such as the recently released Bonito basecaller. Although Bonito operates only on individual strands and was not designed to leverage the 1D2protocol, our method lifts its median accuracy from 93.3% to 97.7%, more than halving the median error rate. This surpasses the maximum accuracy achievable with Guppy, an alternate basecaller which was designed to include pair decoding of 1D2reads. Our software PoreOver, including both our neural network basecaller and our consensus pair decoder (which can be separably applied to improve other basecallers), is implemented in Python 3 and C++11 and is freely available athttps://github.com/jordisr/poreover.

Motivation Many software libraries for using Hidden Markov Models in bioinformatics focus on inference tasks, such as likelihood calculation, parameter-fitting and alignment. However, construction of the state machines can be a laborious task, automation of which would be time-saving and less error-prone. Results We present Machine Boss, a software tool implementing not just inference and parameter-fitting algorithms, but also a set of operations for manipulating and combining automata. The aim is to make prototyping of bioinformatics HMMs as quick and easy as the construction of regular expressions, with one-line ‘recipes’ for many common applications. We report data from several illustrative examples involving protein-to-DNA alignment, DNA data storage and nanopore sequence analysis. Availability and implementation Machine Boss is released under the BSD-3 open source license and is available from http://machineboss.org/. Supplementary information Supplementary data are available at Bioinformatics online.