Betanodavirus meningoencephalitis in an Atlantic blue marlin.

Viral nervous necrosis (viral encephalopathy and retinopathy) is caused by piscine nodavirus (Nodaviridae, Betanodavirus). Since 1986, this highly infectious virus has caused mass mortalities of up to 100% in farmed saltwater and freshwater fish around the world (with the exception of South America and Antarctica), affecting >60 species across 10 orders. The Atlantic blue marlin (Makaira nigricans Lacépède, 1802) is a top-level predator found throughout the tropical waters of the Atlantic and Indo-Pacific oceans. Despite their popularity as a sportfish, relatively little is known about the Atlantic blue marlin and other billfish. We describe here chronic betanodavirus infection in a juvenile Atlantic blue marlin, which is, to our knowledge, the first report of disease in M. nigricans.

Histologic lesions of giant African millipedes (Archispirostreptus gigas) from a zoological institution.

Histopathologic data of millipedes are scarce. Little is known about health and disease of these invertebrates despite their exhibition at zoological institutions and use in ecotoxicological studies. In a retrospective study of 69 zoo-housed giant African millipedes (Archispirostreptus gigas) submitted between 2018 and 2021, most deaths occurred during midwinter and in 2021. The most common lesion was inflammation (n = 55; 80%). Necrosis was seen concurrently in 31 (45%) millipedes and of these, bacteria (20; 29%) and fungi (7; 10%) were detected in lesions. Inflammation was seen in the head/collum (20; 29%), hemocoel (16; 23%), and appendages (9; 13%), specifically in perivisceral fat body (42; 61%), gut (16; 23%), tracheae (26; 38%), skeletal muscle (24; 35%), and ventral nerve (17; 25%). Inflammatory cell types and patterns included agranular hemocytes (61; 88%), granular hemocytes (39; 57%), and nodulation/encapsulation (47; 68%) often accompanied by melanization. The oral cavity or gut (ingestion), spiracles (inhalation), or cuticular defects were considered plausible routes of bacterial entry. Metazoan parasites (adult nematodes: 2, 3%; trematode ova: 2, 3%; and arthropods: 1, 1%) were associated with gut necrosis and inflammation in 5 millipedes. In addition, adult nematodes were noted in the gut of 4 millipedes without lesions. Neoplasia was not detected in any millipedes. Speculatively, environmental factors may have predisposed to disease, as most deaths occurred during winter months. Disease surveillance of millipedes is critical to optimize husbandry practices in zoo populations and investigate potential impacts of environmental degradation and climate change on wild millipedes.

Lumbar Spinal Canal Segmentation in Cases with Lumbar Stenosis Using Deep-U-Net Ensembles.

BACKGROUND: Narrowing of the lumbar spinal canal, or lumbar stenosis (LS), may cause debilitating radicular pain or muscle weakness. It is the most frequent indication for spinal surgery in the elderly population. Modern diagnosis relies on magnetic resonance imaging and its inherently subjective interpretation. Diagnostic rigor, accuracy, and speed may be improved by automation. In this work, we aimed to determine whether a deep-U-Net ensemble trained to segment spinal canals on a heterogeneous mix of clinical data is comparable to radiologists' segmentation of these canals in patients with LS. METHODS: The deep U-nets were trained on spinal canals segmented by physicians on 100 axial T2 lumbar magnetic resonance imaging selected randomly from our institutional database. Test data included a total of 279 elderly patients with LS that were separate from the training set. RESULTS: Machine-generated segmentations (MA) were qualitatively similar to expert-generated segmentations (ME1, ME2). Machine- and expert-generated segmentations were quantitatively similar, as evidenced by Dice scores (MA vs. ME1: 0.88 ± 0.04, MA vs. ME2: 0.89 ± 0.04), the Hausdorff distance (MA vs. ME1: 11.7 mm ± 13.8, MA vs. ME2: 13.1 mm ± 16.3), and average surface distance (MAvs. ME1: 0.18 mm ± 0.13, MA vs. ME2 0.18 mm ± 0.16) metrics. These metrics are comparable to inter-rater variation (ME1 vs. ME2 Dice scores: 0.94 ± 0.02, the Hausdorff distances: 9.3 mm ± 15.6, average surface distances: 0.08 mm ± 0.09). CONCLUSION: We conclude that machine learning algorithms can segment lumbar spinal canals in LS patients, and automatic delineations are both qualitatively and quantitatively comparable to expert-generated segmentations.

DETECTION OF ELEPHANT ENDOTHELIOTROPIC HERPESVIRUS 1A IN ARCHIVAL TISSUE USING RNASCOPE® IN SITU HYBRIDIZATION.

Hemorrhagic disease due to elephant endotheliotropic herpesvirus infection (EEHV-HD) is an important cause of calf mortality in managed and free-ranging Asian (Elephas maximus) and African elephant (Loxodonta spp.) populations. Consequently, infection has profound implications for elephant population growth and sustainability. The mechanisms of disease caused by EEHV (i.e., infection, dissemination, shedding, latency) are relatively undefined, in part because of a lack of robust validated assays for detecting viral gene products in relevant samples. To address this issue, we used RNAscope® in situ hybridization (ISH) based on EEHV1A DNA polymerase and terminase genes to detect EEHV1A RNA in archival formalin-fixed, paraffin-embedded Asian elephant heart and tongue from PCR-confirmed cases (n = 4) of EEHV-HD and Asian elephants (n = 2) that died from other causes. EEHV1A-positive cases had positive hybridization signal in endothelial cell nuclei of both tissues for both DNA polymerase and terminase. EEHV-negative cases lacked signal. In positive cases, the number of positive nuclei was manually assessed to provide an estimate of the viral load and compare sensitivity of the two probes. In all cases, heart had greater signal than tongue for both probes (Wilcoxon rank test; P ≤ 0.01). Overall, terminase hybridization signal was greater than DNA polymerase signal (Wilcoxon rank test; P ≤ 0.01). Results indicate RNAscope ISH is a valuable tool for detection of EEHV in archival samples and for confirming infection. Additionally, the terminase gene is the optimal target and heart is preferable to tongue for detection in cases of EEHV-HD. Results will inform future investigations of viral tropism in EEHV-HD cases due to EEHV1A.

Structural Changes in the Cervicomedullary Junction in Adult Chiari Patients.

OBJECTIVE: To assess volumetric changes in the spinal cord at the cervicomedullary junction, diameter of the cervicomedullary cord, and width of the brainstem following posterior fossa decompression (PFD). METHODS: A retrospective analysis of adult patients with Chiari malformation who underwent PFD was performed. Segmentations were done on clinical quality T2-weighted cervical magnetic resonance images obtained before and after decompression using ITK-SNAP. Volumes of neural tissue within the cervicomedullary junction were evaluated from 10 mm cranial to the medullary beak to the cervical spinal cord at the level of the caudal endplate of the second cervical vertebra. The diameter of the cervicomedullary cord was calculated perpendicular to the spinal cord. The width of the brainstem was measured perpendicular to the clivus at the level of the basion. RESULTS: Twenty adult patients, a mean age of 49.55 years, were included. The cervical cord increased in volume by 13 mm3 to 338 mm3, with an average increase of 155 mm3 (P-value of 0.00002). The diameter of the cervicomedullary cord increased 10.30% 7 mm superior to the beak (P-value of 0.00074), 11.49% at the apex of the beak (P-value of 0.00082), 8.29% 7 mm inferior to the beak (P-value of 0.00075), and the brainstem increased 14.46% perpendicular to the clivus (P-value of 0.00109). The spinal cord at the inferior aspect of the C3 vertebra changed insignificantly (P-value of 0.10580). CONCLUSION: The volume of the cervical cord at the cervical-medullary junction, width of the cervicomedullary cord, and diameter of the brainstem increase following PFD.

Imaging Biomarker Development for Lower Back Pain Using Machine Learning: How Image Analysis Can Help Back Pain.

State-of-the-art diagnosis of radiculopathy relies on "highly subjective" radiologist interpretation of magnetic resonance imaging of the lower back. Currently, the treatment of lumbar radiculopathy and associated lower back pain lacks coherence due to an absence of reliable, objective diagnostic biomarkers. Using emerging machine learning techniques, the subjectivity of interpretation may be replaced by the objectivity of automated analysis. However, training computer vision methods requires a curated database of imaging data containing anatomical delineations vetted by a team of human experts. In this chapter, we outline our efforts to develop such a database of curated imaging data alongside the required delineations. We detail the processes involved in data acquisition and subsequent annotation. Then we explain how the resulting database can be utilized to develop a machine learning-based objective imaging biomarker. Finally, we present an explanation of how we validate our machine learning-based anatomy delineation algorithms. Ultimately, we hope to allow validated machine learning models to be used to generate objective biomarkers from imaging data-for clinical use to diagnose lumbar radiculopathy and guide associated treatment plans.

Predicting Spinal Surgery Candidacy From Imaging Data Using Machine Learning.

BACKGROUND: The referral process for consultation with a spine surgeon remains inefficient, given a substantial proportion of referrals to spine surgeons are nonoperative. OBJECTIVE: To develop a machine-learning-based algorithm which accurately identifies patients as candidates for consultation with a spine surgeon, using only magnetic resonance imaging (MRI). METHODS: We trained a deep U-Net machine learning model to delineate spinal canals on axial slices of 100 normal lumbar MRI scans which were previously delineated by expert radiologists and neurosurgeons. We then tested the model against lumbar MRI scans for 140 patients who had undergone lumbar spine MRI at our institution (60 of whom ultimately underwent surgery, and 80 of whom did not). The model generated automated segmentations of the lumbar spinal canals and calculated a maximum degree of spinal stenosis for each patient, which served as our biomarker for surgical pathology warranting expert consultation. RESULTS: The machine learning model correctly predicted surgical candidacy (ie, whether patients ultimately underwent lumbar spinal decompression) with high accuracy (area under the curve = 0.88), using only imaging data from lumbar MRI scans. CONCLUSION: Automated interpretation of lumbar MRI scans was sufficient to correctly determine surgical candidacy in nearly 90% of cases. Given that a significant proportion of referrals placed for spine surgery evaluation fail to meet criteria for surgical intervention, our model could serve as a valuable tool for patient triage and thereby address some of the inefficiencies within the outpatient surgical referral process.

Adverse cardiovascular events in patients treated with mogamulizumab.

Study objectives: Mogamulizumab is an important treatment for T-cell leukemia and lymphoma. Adverse cardiovascular events (ACE) after mogamulizumab therapy have not been investigated. The aim of the study is to investigate ACE occurrence after mogamulizumab therapy. Methods: The International World Health Organization database, VigiBase, was analyzed from January 2013 to August 2019 for all adverse events, including ACE, that occurred after mogamulizumab treatment. ACE was defined as: cardiac death, myocardial infarction, heart failure, myocarditis, arrhythmia, vasculitis, thrombosis, palpitations and new hypertension. Results: ACE after mogamulizumab therapy affected 28 out of 650 unique patients (4.3%). Heart failure (42.8%) and ventricular arrhythmias (17.85%) were most common. ACE accounted for 10% of all fatal adverse outcomes, and 25% of all ACE were fatal. Time to fatal outcome was significantly shorter for patients with ACE compared to non-cardiovascular events, with a mean of 7.7 days (SD 6.91) vs 73 days (SD 90.7), p = 0.017, respectively. There was an increased total number of adverse cardiovascular events in patients greater than 65 and in Asian countries. Conclusions: Cardiovascular toxicity with mogamulizumab is a possible early occurring adverse outcome associated with high mortality.

Development and validation of a probe hybridization reverse-transcription quantitative PCR for detection of mamastrovirus 2 in domestic cats.

Astroviruses are viral pathogens that have been associated with enteric and neurologic disease in a variety of species. The domestic cat is a prominent host, with reports of astroviral infection being both highly prevalent and widely distributed in the feline population. Despite the potential for inducing significant disease, especially within shelter environments, there is currently only one reliable method of detection: standard reverse-transcription PCR using pan-astrovirus degenerate primers (consensus RT-PCR) with product sequencing. Unfortunately, this process is relatively slow and costly. Quantitative real-time PCR (qPCR) represents an efficient, economical alternative, with the added benefit of viral load quantification. We developed a RT-qPCR assay using probe hybridization technique to detect conserved regions of mamastrovirus 2 extracted from fecal samples of domestic cats. Known positive and negative samples were tested, and results were compared with gold standard consensus RT-PCR and sequencing. A standard curve was employed to determine limits of detection. In order to assess analytic specificity, we tested several additional samples that had been collected from non-felid species and were known to contain non-target astroviruses. Discrepant results between consensus RT-PCR and RT-qPCR testing were further analyzed with a validation RT-PCR assay, using mamastrovirus 2-specific primers. Our probe hybridization RT-qPCR assay is reliable and effective for the detection of mamastrovirus 2. This assay will allow rapid, affordable detection and facilitate further research on astroviral infection within domestic cats.

Determination of the diversity of astroviruses in feces from cats in Florida.

Astroviruses are small, nonenveloped RNA viruses that have been linked to numerous diseases in a variety of species, including enteric disease in humans and cheetahs. Species Mamastrovirus 2, previously known as feline astrovirus, has been isolated from the feces of domestic cats and cheetahs. A total of 122 cat fecal samples from Alachua County, FL Animal Services and the Veterinary Community Outreach Program at the University of Florida were analyzed, and 35 contained astroviral RNA that was amplified and identified using consensus RT-PCR and sequence analysis. Using phylogenetic analysis, 19 of the astroviral sequences were identified as Mamastrovirus 2, making it the most prevalent astrovirus in this population. Three samples were identified as an astrovirus similar to viruses previously identified in foxes in The Netherlands and a cat in California, and one was similar to a bat astrovirus. One astroviral sequence was identified as an Avastrovirus. Although a causative relationship between mamastroviruses and enteric disease in cats has yet to be established, it is clear that mamastroviruses are prevalent, and an understanding of prevalence of astroviral types may help direct future test development.