Comparison of histomorphology and DNA preservation produced by fixatives in the veterinary diagnostic laboratory setting

Histopathology is the most useful tool for diagnosis of a number of diseases, especially cancer. To be effective, histopathology requires that tissues be fixed prior to processing. Formalin is currently the most common histologic fixative, offering many advantages: it is cheap, readily available, and pathologists are routinely trained to examine tissues fixed in formalin. However, formalin fixation substantially degrades tissue DNA, hindering subsequent use in diagnostics and research. We therefore evaluated three alternative fixatives, TissueTek® Xpress® Molecular Fixative, modified methacarn, and PAXgene®, all of which have been proposed as formalin alternatives, to determine their suitability for routine use in a veterinary diagnostic laboratory. This was accomplished by examining the histomorphology of sections produced from fixed tissues as well as the ability to amplify fragments from extracted DNA. Tissues were sampled from two dogs and four cats, fixed for 24–48 h, and processed routinely. While all fixatives produced acceptable histomorphology, formalin had significantly better morphologic characteristics than the other three fixatives. Alternative fixatives generally had better DNA amplification than formalin, although results varied somewhat depending on the tissue examined. While no fixative is yet ready to replace formalin, the alternative fixatives examined may be useful as adjuncts to formalin in diagnostic practices

Deep learning for necrosis detection using canine perivascular wall tumour whole slide images

Necrosis seen in histopathology Whole Slide Images is a major criterion that contributes towards scoring tumour grade which then determines treatment options. However conventional manual assessment suffers from inter-operator reproducibility impacting grading precision. To address this, automatic necrosis detection using AI may be used to assess necrosis for final scoring that contributes towards the final clinical grade. Using deep learning AI, we describe a novel approach for automating necrosis detection in Whole Slide Images, tested on a canine Soft Tissue Sarcoma (cSTS) data set consisting of canine Perivascular Wall Tumours (cPWTs). A patch-based deep learning approach was developed where different variations of training a DenseNet-161 Convolutional Neural Network architecture were investigated as well as a stacking ensemble. An optimised DenseNet-161 with post-processing produced a hold-out test F1-score of 0.708 demonstrating state-of-the-art performance. This represents a novel first-time automated necrosis detection method in the cSTS domain as well specifically in detecting necrosis in cPWTs demonstrating a significant step forward in reproducible and reliable necrosis assessment for improving the precision of tumour grading

Determining the Repertoire of Immunodominant Proteins via Whole-Genome Amplification of Intracellular Pathogens

Culturing many obligate intracellular bacteria is difficult or impossible. However, these organisms have numerous adaptations allowing for infection persistence and immune system evasion, making them some of the most interesting to study. Recent advancements in genome sequencing, pyrosequencing and Phi29 amplification, have allowed for examination of whole-genome sequences of intracellular bacteria without culture. We have applied both techniques to the model obligate intracellular pathogen Anaplasma marginale and the human pathogen Anaplasma phagocytophilum, in order to examine the ability of phi29 amplification to determine the sequence of genes allowing for immune system evasion and long-term persistence in the host. When compared to traditional pyrosequencing, phi29-mediated genome amplification had similar genome coverage, with no additional gaps in coverage. Additionally, all msp2 functional pseudogenes from two strains of A. marginale were detected and extracted from the phi29-amplified genomes, highlighting its utility in determining the full complement of genes involved in immune evasion

Flavin Mononucleotide as a Biomarker of Organ Quality-A Pilot Study.

BACKGROUND: Flavin mononucleotide (FMN), released from damaged mitochondrial complex I during hypothermic liver perfusion, has been shown to be predictive of 90-day graft loss. Normothermic machine perfusion (NMP) and normothermic regional perfusion (NRP) are used for organ reconditioning and quality assessment before transplantation. This pilot study aimed to investigate the changes of FMN levels during normothermic reperfusion of kidneys, livers, and lungs and examine whether FMN could serve as a biomarker to predict posttransplant allograft quality. METHODS: FMN concentrations, in perfusates collected during NMP of kidneys, abdominal NRP, and ex vivo lung perfusion, were measured using fluorescence spectrometry and correlated to the available perfusion parameters and clinical outcomes. RESULTS: Among 7 transplanted kidneys out of the 11 kidneys that underwent NMP, FMN levels at 60 minutes of NMP were significantly higher in the allografts that developed delayed graft function and primary nonfunction (P = 0.02). Fifteen livers from 23 circulatory death donors that underwent NRP were deemed suitable for transplantation. Their FMN levels at 30 minutes of NRP were significantly lower than those not procured for transplantation (P = 0.004). In contrast, little FMN was released during the 8 lung perfusions. CONCLUSIONS: This proof of concept study suggested that FMN in the perfusates of kidney NMP has the potential to predict posttransplant renal function, whereas FMN at 30 minutes of NRP predicts whether a liver would be accepted for transplantation. More work is required to validate the role of FMN as a putative biomarker to facilitate safe and reliable decision-making before embarking on transplantation.NIHR BTR

Viral Enrichment Methods Affect the Detection but Not Sequence Variation of West Nile Virus in Equine Brain Tissue

West Nile virus (WNV), a small, positive sense, single stranded RNA virus continues to encroach into new locales with emergence of new viral variants. Neurological disease in the equine can be moderate to severe in the face of low to undetectable virus loads. Physical methods of virus enrichment may increase sensitivity of virus detection and enhance analysis of viral diversity, especially for deep sequencing studies. However, the use of these techniques is limited mainly to non-neural tissues. We investigated the hypothesis that elimination of equine brain RNA enhances viral detection without limiting viral variation. Eight different WNV viral RNA enrichment and host RNA separation methods were evaluated to determine if elimination of host RNA enhanced detection of WNV and increase the repertoire of virus variants for sequencing. Archived brain tissue from 21 different horses was inoculated with WNV, homogenized, before enrichment and separation. The protocols utilized combinations of low-speed centrifugation, syringe filtration, and nuclease treatment. Viral and host RNA were analyzed using real-time PCR targeting the WNV Envelope (E) protein and equine G3PDH to determine relative sensitivity for WNV and host depletion, respectively. To determine the effect of these methods on viral variation, deep sequencing of the E protein was performed. Our results demonstrate that additional separation and enrichment methods resulted in loss of virus in the face of host RNA depletion. DNA sequencing showed no significant difference in total sequence variation between the RNA enrichment protocols. For equine brain infected with WNV, direct RNA extraction followed by host RNA depletion was most suitable. This study highlights the importance of evaluating viral enrichment and separation methods according to tissue type before embarking on studies where quantification of virus and viral variants is essential to the outcome of the study

Nuclear Morphometry using a Deep Learning-based Algorithm has Prognostic Relevance for Canine Cutaneous Mast Cell Tumors

Variation in nuclear size and shape is an important criterion of malignancy for many tumor types; however, categorical estimates by pathologists have poor reproducibility. Measurements of nuclear characteristics (morphometry) can improve reproducibility, but manual methods are time consuming. In this study, we evaluated fully automated morphometry using a deep learning-based algorithm in 96 canine cutaneous mast cell tumors with information on patient survival. Algorithmic morphometry was compared with karyomegaly estimates by 11 pathologists, manual nuclear morphometry of 12 cells by 9 pathologists, and the mitotic count as a benchmark. The prognostic value of automated morphometry was high with an area under the ROC curve regarding the tumor-specific survival of 0.943 (95% CI: 0.889 - 0.996) for the standard deviation (SD) of nuclear area, which was higher than manual morphometry of all pathologists combined (0.868, 95% CI: 0.737 - 0.991) and the mitotic count (0.885, 95% CI: 0.765 - 1.00). At the proposed thresholds, the hazard ratio for algorithmic morphometry (SD of nuclear area $\geq 9.0 \mu m^2$) was 18.3 (95% CI: 5.0 - 67.1), for manual morphometry (SD of nuclear area $\geq 10.9 \mu m^2$) 9.0 (95% CI: 6.0 - 13.4), for karyomegaly estimates 7.6 (95% CI: 5.7 - 10.1), and for the mitotic count 30.5 (95% CI: 7.8 - 118.0). Inter-rater reproducibility for karyomegaly estimates was fair ($\kappa$ = 0.226) with highly variable sensitivity/specificity values for the individual pathologists. Reproducibility for manual morphometry (SD of nuclear area) was good (ICC = 0.654). This study supports the use of algorithmic morphometry as a prognostic test to overcome the limitations of estimates and manual measurements

Astrometric Redshifts for Quasars

The wavelength dependence of atmospheric refraction causes differential chromatic refraction (DCR), whereby objects imaged at different optical/UV wavelengths are observed at slightly different positions in the plane of the detector. Strong spectral features induce changes in the effective wavelengths of broad-band filters that are capable of producing significant positional offsets with respect to standard DCR corrections. We examine such offsets for broad-emission-line (type 1) quasars from the Sloan Digital Sky Survey (SDSS) spanning 0<z<5 and an airmass range of 1.0 to 1.8. These offsets are in good agreement with those predicted by convolving a composite quasar spectrum with the SDSS bandpasses as a function of redshift and airmass. This astrometric information can be used to break degeneracies in photometric redshifts of quasars (or other emission-line sources) and, for extreme cases, may be suitable for determining "astrometric redshifts". On the SDSS's southern equatorial stripe, where it is possible to average many multi-epoch measurements, more than 60% of quasars have emission-line-induced astrometric offsets larger than the SDSS's relative astrometric errors of 25-35 mas. Folding these astrometric offsets into photometric redshift estimates yields an improvement of 9% within Delta z+/-0.1. Future multi-epoch synoptic surveys such as LSST and Pan-STARRS could benefit from intentionally making ~10 observations at relatively high airmass (AM~1.4) in order to improve their photometric redshifts for quasars.Comment: 29 pages, 13 figures (3 color); AJ, accepte

N-acetylcysteine (NAC) in schizophrenia resistant to clozapine: a double blind randomised placebo controlled trial targeting negative symptoms

BACKGROUND: Clozapine is an effective treatment for a proportion of people with schizophrenia (SZ) who are resistant to the beneficial effects of other antipsychotic drugs. However, anything from 40-60&nbsp;% of people on clozapine experience residual symptoms even on adequate doses of the medication, and thus could be considered \u27clozapine resistant\u27. Agents that could work alongside clozapine to improve efficacy whilst not increasing the adverse effect burden are both desired and necessary to improve the lives of individuals with clozapine-resistant SZ. N-Acetylcysteine (NAC) is one such possible agent. Previous research from our research group provided promising pilot data suggesting the efficacy of NAC in this patient population. The aim of the study reported here is to expand this work by conducting a large scale clinical trial of NAC in the treatment of clozapine-resistant SZ. METHODS: This study is an investigator initiated, multi-site, randomised, placebo-controlled trial. It aims to include 168 patients with clozapine-resistant SZ, divided into an intervention group (NAC) and a control group (placebo). Participants in the intervention group will receive 2&nbsp;g daily of NAC. The primary outcome measures will be the negative symptom scores of the Positive and Negative Syndrome Scale (PANSS). Secondary outcome measures will include: changes in quality of life (QoL) as measured by the Lancashire Quality of Life Profile (LQoLP) and cognitive functioning as measured by the total score on the MATRICS. Additionally we will examine peripheral and cortical glutathione (GSH) concentrations as process outcomes. DISCUSSION: This large scale clinical trial will investigate the efficacy of NAC as an adjunctive medication to clozapine. This trial, if successful, will establish a cheap, safe and easy-to-use agent (NAC) as a \u27go to\u27 adjunct in patients that are only partly responsive to clozapine.<br /

Photometric redshifts for the next generation of deep radio continuum surveys - I: template fitting

We present a study of photometric redshift performance for galaxies and active galactic nuclei detected in deep radio continuum surveys. Using two multi-wavelength datasets, over the NOAO Deep Wide Field Survey Boötes and COSMOS fields, we assess photometric redshift (photo-z) performance for a sample of 4; 500 radio continuum sources with spectroscopic redshifts relative to those of 63; 000 non radio-detected sources in the same fields. We investigate the performance of three photometric redshift template sets as a function of redshift, radio luminosity and infrared/X-ray properties. We find that no single template library is able to provide the best performance across all subsets of the radio detected population, with variation in the optimum template set both between subsets and between fields. Through a hierarchical Bayesian combination of the photo-z estimates from all three template sets, we are able to produce a consensus photo-z estimate which equals or improves upon the performance of any individual template set

WISE x SuperCOSMOS photometric redshift catalog: 20 million galaxies over 3pi steradians

We cross-match the two currently largest all-sky photometric catalogs, mid-infrared WISE and SuperCOSMOS scans of UKST/POSS-II photographic plates, to obtain a new galaxy sample that covers 3pi steradians. In order to characterize and purify the extragalactic dataset, we use external GAMA and SDSS spectroscopic information to define quasar and star loci in multicolor space, aiding the removal of contamination from our extended-source catalog. After appropriate data cleaning we obtain a deep wide-angle galaxy sample that is approximately 95% pure and 90% complete at high Galactic latitudes. The catalog contains close to 20 million galaxies over almost 70% of the sky, outside the Zone of Avoidance and other confused regions, with a mean surface density of over 650 sources per square degree. Using multiwavelength information from two optical and two mid-IR photometric bands, we derive photometric redshifts for all the galaxies in the catalog, using the ANNz framework trained on the final GAMA-II spectroscopic data. Our sample has a median redshift of z_{med} = 0.2 but with a broad dN/dz reaching up to z>0.4. The photometric redshifts have a mean bias of |delta_z|~10^{-3}, normalized scatter of sigma_z = 0.033 and less than 3% outliers beyond 3sigma_z. Comparison with external datasets shows no significant variation of photo-z quality with sky position. Together with the overall statistics, we also provide a more detailed analysis of photometric redshift accuracy as a function of magnitudes and colors. The final catalog is appropriate for `all-sky' 3D cosmology to unprecedented depths, in particular through cross-correlations with other large-area surveys. It should also be useful for source pre-selection and identification in forthcoming surveys such as TAIPAN or WALLABY