An integrated metaproteomics workflow for studying host-microbe dynamics in bronchoalveolar lavage samples applied to cystic fibrosis disease.

Airway microbiota are known to contribute to lung diseases, such as cystic fibrosis (CF), but their contributions to pathogenesis are still unclear. To improve our understanding of host-microbe interactions, we have developed an integrated analytical and bioinformatic mass spectrometry (MS)-based metaproteomics workflow to analyze clinical bronchoalveolar lavage (BAL) samples from people with airway disease. Proteins from BAL cellular pellets were processed and pooled together in groups categorized by disease status (CF vs. non-CF) and bacterial diversity, based on previously performed small subunit rRNA sequencing data. Proteins from each pooled sample group were digested and subjected to liquid chromatography tandem mass spectrometry (MS/MS). MS/MS spectra were matched to human and bacterial peptide sequences leveraging a bioinformatic workflow using a metagenomics-guided protein sequence database and rigorous evaluation. Label-free quantification revealed differentially abundant human peptides from proteins with known roles in CF, like neutrophil elastase and collagenase, and proteins with lesser-known roles in CF, including apolipoproteins. Differentially abundant bacterial peptides were identified from known CF pathogens (e.g., Pseudomonas), as well as other taxa with potentially novel roles in CF. We used this host-microbe peptide panel for targeted parallel-reaction monitoring validation, demonstrating for the first time an MS-based assay effective for quantifying host-microbe protein dynamics within BAL cells from individual CF patients. Our integrated bioinformatic and analytical workflow combining discovery, verification, and validation should prove useful for diverse studies to characterize microbial contributors in airway diseases. Furthermore, we describe a promising preliminary panel of differentially abundant microbe and host peptide sequences for further study as potential markers of host-microbe relationships in CF disease pathogenesis.IMPORTANCEIdentifying microbial pathogenic contributors and dysregulated human responses in airway disease, such as CF, is critical to understanding disease progression and developing more effective treatments. To this end, characterizing the proteins expressed from bacterial microbes and human host cells during disease progression can provide valuable new insights. We describe here a new method to confidently detect and monitor abundance changes of both microbe and host proteins from challenging BAL samples commonly collected from CF patients. Our method uses both state-of-the art mass spectrometry-based instrumentation to detect proteins present in these samples and customized bioinformatic software tools to analyze the data and characterize detected proteins and their association with CF. We demonstrate the use of this method to characterize microbe and host proteins from individual BAL samples, paving the way for a new approach to understand molecular contributors to CF and other diseases of the airway.

The impact of incorporating surgical simulation into trichiasis surgery training on operative aspects of initial live-training surgeries.

BACKGROUND: While surgical simulation is regularly used in surgical training in high-income country settings, it is uncommon in low- and middle-income countries, particularly for surgical training that primarily occurs in rural areas. We designed and evaluated a novel surgical simulator for improving trachomatous trichiasis (TT) surgery training, given that trichiasis is mostly found among the poorest individuals in rural areas. METHODOLOGY/PRINCIPAL FINDINGS: TT surgery programs were invited to incorporate surgical simulation with a new, high fidelity, low-cost simulator into their training. Trainees completed standard TT-surgery training following World Health Organization guidelines. A subset of trainees received three hours of supplemental training with the simulator between classroom and live-surgery training. We recorded the time required to complete each surgery and the number of times the trainer intervened to correct surgical steps. Participants completed questionnaires regarding their perceptions. We also assessed trainer and trainee perceptions of surgical simulation training as part of trichiasis surgery training. 22 surgeons completed standard training and 26 completed standard training plus simulation. We observed 1,394 live-training surgeries. Average time to first live-training surgery completion was nearly 20% shorter the simulation versus the standard group (28.3 vs 34.4 minutes; p = 0.02). Trainers intervened significantly fewer times during initial live-training surgeries in the simulation group (2.7 vs. 4.8; p = 0.005). All trainers indicated the simulator significantly improved training by allowing trainees to practice safely and to identify problem areas before performing live-training surgeries. Trainees reported that simulation practice improved their confidence and skills prior to performing live-training surgeries. CONCLUSIONS: A single high-fidelity surgical simulation session can significantly improve critical aspects of initial TT surgeries.

Drug Resistance in Medulloblastoma Is Driven by YB-1, ABCB1 and a Seven-Gene Drug Signature.

Therapy resistance represents an unmet challenge in the treatment of medulloblastoma. Accordingly, the identification of targets that mark drug-resistant cell populations, or drive the proliferation of resistant cells, may improve treatment strategies. To address this, we undertook a targeted approach focused on the multi-functional transcription factor YB-1. Genetic knockdown of YB-1 in Group 3 medulloblastoma cell lines diminished cell invasion in 3D in vitro assays and increased sensitivity to standard-of-care chemotherapeutic vincristine and anti-cancer agents panobinostat and JQ1. For vincristine, this occurred in part by YB-1-mediated transcriptional regulation of multi-drug resistance gene ABCB1, as determined by chromatin immunoprecipitation. Whole transcriptome sequencing of YB-1 knockdown cells identified a role for YB-1 in the regulation of tumourigenic processes, including lipid metabolism, cell death and survival and MYC and mTOR pathways. Stable cisplatin- and vincristine-tolerant Group 3 and SHH cell lines were generated to identify additional mechanisms driving resistance to standard-of-care medulloblastoma therapy. Next-generation sequencing revealed a vastly different transcriptomic landscape following chronic drug exposure, including a drug-tolerant seven-gene expression signature, common to all sequenced drug-tolerant cell lines, representing therapeutically targetable genes implicated in the acquisition of drug tolerance. Our findings provide significant insight into mechanisms and genes underlying therapy resistance in medulloblastoma.

Identifying new biomarkers of aggressive Group 3 and SHH medulloblastoma using 3D hydrogel models, single cell RNA sequencing and 3D OrbiSIMS imaging.

The most common malignant brain tumour in children, medulloblastoma (MB), is subdivided into four clinically relevant molecular subgroups, although targeted therapy options informed by understanding of different cellular features are lacking. Here, by comparing the most aggressive subgroup (Group 3) with the intermediate (SHH) subgroup, we identify crucial differences in tumour heterogeneity, including unique metabolism-driven subpopulations in Group 3 and matrix-producing subpopulations in SHH. To analyse tumour heterogeneity, we profiled individual tumour nodules at the cellular level in 3D MB hydrogel models, which recapitulate subgroup specific phenotypes, by single cell RNA sequencing (scRNAseq) and 3D OrbiTrap Secondary Ion Mass Spectrometry (3D OrbiSIMS) imaging. In addition to identifying known metabolites characteristic of MB, we observed intra- and internodular heterogeneity and identified subgroup-specific tumour subpopulations. We showed that extracellular matrix factors and adhesion pathways defined unique SHH subpopulations, and made up a distinct shell-like structure of sulphur-containing species, comprising a combination of small leucine-rich proteoglycans (SLRPs) including the collagen organiser lumican. In contrast, the Group 3 tumour model was characterized by multiple subpopulations with greatly enhanced oxidative phosphorylation and tricarboxylic acid (TCA) cycle activity. Extensive TCA cycle metabolite measurements revealed very high levels of succinate and fumarate with malate levels almost undetectable particularly in Group 3 tumour models. In patients, high fumarate levels (NMR spectroscopy) alongside activated stress response pathways and high Nuclear Factor Erythroid 2-Related Factor 2 (NRF2; gene expression analyses) were associated with poorer survival. Based on these findings we predicted and confirmed that NRF2 inhibition increased sensitivity to vincristine in a long-term 3D drug treatment assay of Group 3 MB. Thus, by combining scRNAseq and 3D OrbiSIMS in a relevant model system we were able to define MB subgroup heterogeneity at the single cell level and elucidate new druggable biomarkers for aggressive Group 3 and low-risk SHH MB.

Catching the Wave: Detecting Strain-Specific SARS-CoV-2 Peptides in Clinical Samples Collected during Infection Waves from Diverse Geographical Locations.

The Coronavirus disease 2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) resulted in a major health crisis worldwide with its continuously emerging new strains, resulting in new viral variants that drive "waves" of infection. PCR or antigen detection assays have been routinely used to detect clinical infections; however, the emergence of these newer strains has presented challenges in detection. One of the alternatives has been to detect and characterize variant-specific peptide sequences from viral proteins using mass spectrometry (MS)-based methods. MS methods can potentially help in both diagnostics and vaccine development by understanding the dynamic changes in the viral proteome associated with specific strains and infection waves. In this study, we developed an accessible, flexible, and shareable bioinformatics workflow that was implemented in the Galaxy Platform to detect variant-specific peptide sequences from MS data derived from the clinical samples. We demonstrated the utility of the workflow by characterizing published clinical data from across the world during various pandemic waves. Our analysis identified six SARS-CoV-2 variant-specific peptides suitable for confident detection by MS in commonly collected clinical samples.

Inappropriate Implantable Cardioverter-Defibrillator Therapy With the Use of an Underbody Electrosurgery Dispersive Electrode.

Perioperative management of implantable cardioverter-defibrillators is an important part of anesthetic care. Society recommendations and expert consensus statements exist to aid clinicians, and they have identified the umbilicus as an important landmark in decision-making. Implantable cardioverter-defibrillator antitachycardia therapy may not need to be deactivated for infraumbilical surgery because electromagnetic interference is unlikely to occur. The authors present two cases in which inappropriate antitachycardia therapy occurred intraoperatively with use of an underbody dispersive electrode, even though both surgeries were infraumbilical. The authors also present two cadaver models to demonstrate how monopolar electrosurgery below the umbilicus is sensed using both traditional and underbody dispersive electrosurgical return electrodes.

Sizing of airborne particles in an operating room.

Medical procedures that produce aerosolized particles are under great scrutiny due to the recent concerns surrounding the COVID-19 virus and increased risk for nosocomial infections. For example, thoracostomies, tracheotomies and intubations/extubations produce aerosols that can linger in the air. The lingering time is dependent on particle size where, e.g., 500 µm (0.5 mm) particles may quickly fall to the floor, while 1 µm particles may float for extended lengths of time. Here, a method is presented to characterize the size of <40 µm to >600 µm particles resulting from surgery in an operating room (OR). The particles are measured in-situ (next to a patient on an operating table) through a 75mm aperture in a ∼400 mm rectangular enclosure with minimal flow restriction. The particles and gasses exiting a patient are vented through an enclosed laser sheet while a camera captures images of the side-scattered light from the entrained particles. A similar optical configuration was described by Anfinrud et al.; however, we present here an extended method which provides a calibration method for determining particle size. The use of a laser sheet with side-scattered light provides a large FOV and bright image of the particles; however, the particle image dilation caused by scattering does not allow direct measurement of particle size. The calibration routine presented here is accomplished by measuring fixed particle distribution ranges with a calibrated shadow imaging system and mapping these measurements to the in-situ imaging system. The technique used for generating and measuring these particles is described. The result is a three-part process where 1) particles of varying sizes are produced and measured using a calibrated, high-resolution shadow imaging method, 2) the same particle generators are measured with the in-situ imaging system, and 3) a correlation mapping is made between the (dilated) laser image size and the measured particle size. Additionally, experimental and operational details of the imaging system are described such as requirements for the enclosure volume, light management, air filtration and control of various laser reflections. Details related to the OR environment and requirements for achieving close proximity to a patient are discussed as well.

A Sectioning and Database Enrichment Approach for Improved Peptide Spectrum Matching in Large, Genome-Guided Protein Sequence Databases.

Multiomics approaches focused on mass spectrometry (MS)-based data, such as metaproteomics, utilize genomic and/or transcriptomic sequencing data to generate a comprehensive protein sequence database. These databases can be very large, containing millions of sequences, which reduces the sensitivity of matching tandem mass spectrometry (MS/MS) data to sequences to generate peptide spectrum matches (PSMs). Here, we describe and evaluate a sectioning method for generating an enriched database for those protein sequences that are most likely present in the sample. Our evaluation demonstrates how this method helps to increase the sensitivity of PSMs while maintaining acceptable false discovery rate statistics-offering a flexible alternative to traditional large database searching, as well as previously described two-step database searching methods for large sequence database applications. Furthermore, implementation in the Galaxy platform provides access to an automated and customizable workflow for carrying out the method. Additionally, the results of this study provide valuable insights into the advantages and limitations offered by available methods aimed at addressing challenges of genome-guided, large database applications in proteomics. Relevant raw data has been made available at https://zenodo.org/ using data set identifier "3754789" and https://arcticdata.io/catalog using data set identifier "A2VX06340".

Multi-omics Visualization Platform: An extensible Galaxy plug-in for multi-omics data visualization and exploration.

BACKGROUND: Proteogenomics integrates genomics, transcriptomics, and mass spectrometry (MS)-based proteomics data to identify novel protein sequences arising from gene and transcript sequence variants. Proteogenomic data analysis requires integration of disparate 'omic software tools, as well as customized tools to view and interpret results. The flexible Galaxy platform has proven valuable for proteogenomic data analysis. Here, we describe a novel Multi-omics Visualization Platform (MVP) for organizing, visualizing, and exploring proteogenomic results, adding a critically needed tool for data exploration and interpretation. FINDINGS: MVP is built as an HTML Galaxy plug-in, primarily based on JavaScript. Via the Galaxy API, MVP uses SQLite databases as input-a custom data type (mzSQLite) containing MS-based peptide identification information, a variant annotation table, and a coding sequence table. Users can interactively filter identified peptides based on sequence and data quality metrics, view annotated peptide MS data, and visualize protein-level information, along with genomic coordinates. Peptides that pass the user-defined thresholds can be sent back to Galaxy via the API for further analysis; processed data and visualizations can also be saved and shared. MVP leverages the Integrated Genomics Viewer JavaScript framework, enabling interactive visualization of peptides and corresponding transcript and genomic coding information within the MVP interface. CONCLUSIONS: MVP provides a powerful, extensible platform for automated, interactive visualization of proteogenomic results within the Galaxy environment, adding a unique and critically needed tool for empowering exploration and interpretation of results. The platform is extensible, providing a basis for further development of new functionalities for proteogenomic data visualization.

Challenges in Peptide-Spectrum Matching: A Robust and Reproducible Statistical Framework for Removing Low-Accuracy, High-Scoring Hits.

Workflows for large-scale (MS)-based shotgun proteomics can potentially lead to costly errors in the form of incorrect peptide-spectrum matches (PSMs). To improve the robustness of these workflows, we have investigated the use of the precursor mass discrepancy (PMD) to detect and filter potentially false PSMs that have, nonetheless, a high confidence score. We identified and addressed three cases of unexpected bias in PMD results: time of acquisition within a liquid chromatography-mass spectrometry (LC-MS) run, decoy PSMs, and length of the peptide. We created a postanalysis Bayesian confidence measure based on score and PMD, called PMD-false discovery rate (FDR). We tested PMD-FDR on four data sets across three types of MS-based proteomics projects: standard (single organism; reference database), proteogenomics (single organism; customized genomic-based database plus reference), and metaproteomics (microorganism community; customized conglomerate database). On a ground-truth data set and other representative data, PMD-FDR was able to detect 60-80% of likely incorrect PSMs (false-hits) while losing only 5% of correct PSMs (true-hits). PMD-FDR can also be used to evaluate data quality for results generated within different experimental PSM-generating workflows, assisting in method development. Going forward, PMD-FDR should provide detection of high scoring but likely false-hits, aiding applications that rely heavily on accurate PSMs, such as proteogenomics and metaproteomics.

The Golden Opportunity: Multidisciplinary Simulation Training Improves Trauma Team Efficiency.

OBJECTIVE: Every trauma patient has a golden hour, and resuscitation efficiency within that hour has large implications for patients. We instituted simulation based trauma resuscitation training with the hypothesis that it would improve trauma team efficiency. METHODS: Five simulation training sessions were conducted with immediate debriefing. Metrics collected in actual trauma resuscitations before and after simulation training included time of primary and secondary surveys and time to computed tomography (CT) scan. Study participants were from multidisciplinary specialties involved in trauma resuscitations as well as former trauma patients from the Trauma Survivors Network. RESULTS: Seventy-three patients undergoing trauma resuscitations were screened and 67 patients were included. Time to CT scan and secondary survey completion were significantly reduced in actual trauma patient activations following implementation of the curriculum (reduction of 23 to 16 minutes for CT scan p < 0.05, and reduction from 14 to 6 minutes for secondary survey, p < 0.05). Time to primary survey completion did not change (5 minutes). CONCLUSIONS: Multidisciplinary simulation training was associated with improved trauma team efficiency in the form of reduced assessment time. As emergency department length of stay is an independent predictor of hospital mortality following trauma activation, team-based simulation training has the potential to improve patient outcomes. Multidisciplinary involvement was a key factor, and Trauma Survivors Network involvement brought credibility from the patient perspective.

Identification of candidate neoantigens produced by fusion transcripts in human osteosarcomas.

Osteosarcomas are characterized by highly disrupted genomes. Although osteosarcomas lack common fusions, we find evidence of many tumour specific gene-gene fusion transcripts, likely due to chromosomal rearrangements and expression of transcription-induced chimeras. Most of the fusions result in out-of-frame transcripts, potentially capable of producing long novel protein sequences and a plethora of neoantigens. To identify fusions, we explored RNA-sequencing data to obtain detailed knowledge of transcribed fusions, by creating a novel program to compare fusions identified by deFuse to de novo transcripts generated by Trinity. This allowed us to confirm the deFuse results and identify unusual splicing patterns associated with fusion events. Using various existing tools combined with this custom program, we developed a pipeline for the identification of fusion transcripts applicable as targets for immunotherapy. In addition to identifying candidate neoantigens associated with fusions, we were able to use the pipeline to establish a method for measuring the frequency of fusion events, which correlated to patient outcome, as well as highlight some similarities between canine and human osteosarcomas. The results of this study of osteosarcomas underscores the numerous benefits associated with conducting a thorough analysis of fusion events within cancer samples.

Bridging the Chromosome-centric and Biology/Disease-driven Human Proteome Projects: Accessible and Automated Tools for Interpreting the Biological and Pathological Impact of Protein Sequence Variants Detected via Proteogenomics.

The Chromosome-centric Human Proteome Project (C-HPP) seeks to comprehensively characterize all protein products coded by the genome, including those expressed sequence variants confirmed via proteogenomics methods. The closely related Biology/Disease-driven Human Proteome Project (B/D-HPP) seeks to understand the biological and pathological associations of expressed protein products, especially those carrying sequence variants that may be drivers of disease. To achieve these objectives, informatics tools are required that interpret potential functional or disease implications of variant protein sequence detected via proteogenomics. Toward this end, we have developed an automated workflow within the Galaxy for Proteomics (Galaxy-P) platform, which leverages the Cancer-Related Analysis of Variants Toolkit (CRAVAT) and makes it interoperable with proteogenomic results. Protein sequence variants confirmed by proteogenomics are assessed for potential structure-function effects as well as associations with cancer using CRAVAT's rich suite of functionalities, including visualization of results directly within the Galaxy user interface. We demonstrate the effectiveness of this workflow on proteogenomic results generated from an MCF7 breast cancer cell line. Our free and open software should enable improved interpretation of the functional and pathological effects of protein sequence variants detected via proteogenomics, acting as a bridge between the C-HPP and B/D-HPP.

An Accessible Proteogenomics Informatics Resource for Cancer Researchers.

Proteogenomics has emerged as a valuable approach in cancer research, which integrates genomic and transcriptomic data with mass spectrometry-based proteomics data to directly identify expressed, variant protein sequences that may have functional roles in cancer. This approach is computationally intensive, requiring integration of disparate software tools into sophisticated workflows, challenging its adoption by nonexpert, bench scientists. To address this need, we have developed an extensible, Galaxy-based resource aimed at providing more researchers access to, and training in, proteogenomic informatics. Our resource brings together software from several leading research groups to address two foundational aspects of proteogenomics: (i) generation of customized, annotated protein sequence databases from RNA-Seq data; and (ii) accurate matching of tandem mass spectrometry data to putative variants, followed by filtering to confirm their novelty. Directions for accessing software tools and workflows, along with instructional documentation, can be found at z.umn.edu/canresgithub. Cancer Res; 77(21); e43-46. ©2017 AACR.

Cobalamin riboswitches exhibit a broad range of ability to discriminate between methylcobalamin and adenosylcobalamin.

Riboswitches are a widely distributed class of regulatory RNAs in bacteria that modulate gene expression via small-molecule-induced conformational changes. Generally, these RNA elements are grouped into classes based upon conserved primary and secondary structure and their cognate effector molecule. Although this approach has been very successful in identifying new riboswitch families and defining their distributions, small sequence differences between structurally related RNAs can alter their ligand selectivity and regulatory behavior. Herein, we use a structure-based mutagenic approach to demonstrate that cobalamin riboswitches have a broad spectrum of preference for the two biological forms of cobalamin in vitro using isothermal titration calorimetry. This selectivity is primarily mediated by the interaction between a peripheral element of the RNA that forms a T-loop module and a subset of nucleotides in the cobalamin-binding pocket. Cell-based fluorescence reporter assays in Escherichia coli revealed that mutations that switch effector preference in vitro lead to differential regulatory responses in a biological context. These data demonstrate that a more comprehensive analysis of representative sequences of both previously and newly discovered classes of riboswitches might reveal subgroups of RNAs that respond to different effectors. Furthermore, this study demonstrates a second distinct means by which tertiary structural interactions in cobalamin riboswitches dictate ligand selectivity.

Association of a Surgical Task During Training With Team Skill Acquisition Among Surgical Residents: The Missing Piece in Multidisciplinary Team Training.

IMPORTANCE: The human patient simulators that are currently used in multidisciplinary operating room team training scenarios cannot simulate surgical tasks because they lack a realistic surgical anatomy. Thus, they eliminate the surgeon's primary task in the operating room. The surgical trainee is presented with a significant barrier when he or she attempts to suspend disbelief and engage in the scenario. OBJECTIVE: To develop and test a simulation-based operating room team training strategy that challenges the communication abilities and teamwork competencies of surgeons while they are engaged in realistic operative maneuvers. DESIGN, SETTING, AND PARTICIPANTS: This pre-post educational intervention pilot study compared the gains in teamwork skills for midlevel surgical residents at Wake Forest Baptist Medical Center after they participated in a standardized multidisciplinary team training scenario with 3 possible levels of surgical realism: (1) SimMan (Laerdal) (control group, no surgical anatomy); (2) "synthetic anatomy for surgical tasks" mannequin (medium-fidelity anatomy), and (3) a patient simulated by a deceased donor (high-fidelity anatomy). INTERVENTIONS: Participation in the simulation scenario and the subsequent debriefing. MAIN OUTCOMES AND MEASURES: Teamwork competency was assessed using several instruments with extensive validity evidence, including the Nontechnical Skills assessment, the Trauma Management Skills scoring system, the Crisis Resource Management checklist, and a self-efficacy survey instrument. Participant satisfaction was assessed with a Likert-scale questionnaire. RESULTS: Scenario participants included midlevel surgical residents, anesthesia providers, scrub nurses, and circulating nurses. Statistical models showed that surgical residents exposed to medium-fidelity simulation (synthetic anatomy for surgical tasks) team training scenarios demonstrated greater gains in teamwork skills compared with control groups (SimMan) (Nontechnical Skills video score: 95% CI, 1.06-16.41; Trauma Management Skills video score: 95% CI, 0.61-2.90) and equivalent gains in teamwork skills compared with high-fidelity simulations (deceased donor) (Nontechnical Skills video score: 95% CI, -8.51 to 6.71; Trauma Management Skills video score: 95% CI, -1.70 to 0.49). CONCLUSIONS AND RELEVANCE: Including a surgical task in operating room team training significantly enhanced the acquisition of teamwork skills among midlevel surgical residents. Incorporating relatively inexpensive, medium-fidelity synthetic anatomy in human patient simulators was as effective as using high-fidelity anatomies from deceased donors for promoting teamwork skills in this learning group.

Development of a Burn Escharotomy Assessment Tool: A Pilot Study.

Severe burn injuries can require escharotomies which are urgent, infrequent, and relatively high-risk procedures necessary to preserve limb perfusion and sometimes ventilation. The American Burn Association Advanced Burn Life Support© course educates surgeons and emergency providers about escharotomy incisions but lacks a biomimetic trainer to demonstrate, practice, or provide assessment. The goal was to build an affordable biomimetic trainer with discrete points of failure and pilot a validation study. Fellowship-trained burn and plastic surgeons worked with special effect artists and anatomists to develop a biomimetic trainer with three discrete points of failure: median or ulnar nerve injury, fasciotomy, and failure to check distal pulse. Participants were divided between experienced and inexperienced, survey pre- and post-procedure on a biomimetic model while being timed. The trainer total cost per participant was less than $35. Eighteen participants were involved in the study. The inexperienced (0-1 prior escharotomies performed) had significantly more violations at the discrete points of failure relative to more experienced participants (P = .036). Face validity was assessed with 100% of participants agreement that the model appeared similar to real life and was valuable in their training. Given the advancements in biomimetic models and the need to train surgeons in how to perform infrequent, emergent surgical procedures, an escharotomy trainer is needed today. The authors developed an affordable model with a successful pilot study demonstrating discrimination between experienced and inexperienced surgeons. Additional research is needed to increase the reliability and assessment metrics.

Toxoplasmosis-associated abortion in an alpaca (Vicugna pacos) fetus.

A near-full-term alpaca (Vicugna pacos) was stillborn 2 days before the expected date of delivery; necropsy examination was conducted within 6 hr of delivery. Gross lesions were enlarged liver and hydrocephalus. On histologic examination, mild inflammatory lesions were identified in the placenta, liver, and lungs, although no etiology was recognized. Within the brain, there was a mild nonsuppurative meningoencephalitis, hydrocephalus, and hydromyelia. Both kidneys had inflammatory foci in cortex and medulla associated with protozoal tissue cysts. Protozoa in brain and kidneys were identified as Toxoplasma gondii based on immunoreactivity to T. gondii polyclonal antibodies that stain both tachyzoites and tissue cysts and BAG1 T. gondii antibodies that are bradyzoite specific. The tissue cysts exhibited intense positivity to T. gondii and mild immunoreactivity to Neospora caninum antibodies. The dam had a high antibody titer (1 : 12,800) to T. gondii and low titer (1 : 100) to N. caninum using their respective agglutination tests. This is the first report of toxoplasmosis-associated abortion in alpaca.

MMuFLR: missense mutation and frameshift location reporter.

MOTIVATION: Cancer researchers seeking immunotherapy targets in cancer cells need tools to locate highly expressed proteins unique to cancer cells. Missense mutation and frameshift location reporter (MMuFLR), a Galaxy-based workflow, analyzes next-generation sequencing paired read RNA-seq output to reliably identify small frameshift mutations and missense mutations in highly expressed protein-coding genes. MMuFLR ignores known SNPs, low quality reads and poly-A/T sequences. For each frameshift and missense mutation identified, MMuFLR provides the location and sequence of the amino acid substitutions in the novel protein candidates for direct input into epitope evaluation tools. AVAILABILITY: http://toolshed.g2.bx.psu.edu/ CONTACT: rath0096@umn.edu or johns198@umn.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Patient education and self-advocacy. Managing pain in osteoarthritis.

Osteoarthritis (OA) affects the cartilage between joints and is primarily seen in older patients due to the time it takes to manifest. Various factors increase risks for the disease, including genetics, obesity, and joint over use. Although no drugs exist to repair the cartilage, treatments to manage the associated pain vary widely and range from physical therapy and steroid injections to joint fusion surgery.