Treatment of highly virulent mammarenavirus infections-status quo and future directions.

INTRODUCTION: Mammarenaviruses are negative-sense bisegmented enveloped RNA viruses that are endemic in Africa, the Americas, and Europe. Several are highly virulent, causing acute human diseases associated with high case fatality rates, and are considered to be significant with respect to public health impact or bioterrorism threat. AREAS COVERED: This review summarizes the status quo of treatment development, starting with drugs that are in advanced stages of evaluation in early clinical trials, followed by promising candidate medical countermeasures emerging from bench analyses and investigational animal research. EXPERT OPINION: Specific therapeutic treatments for diseases caused by mammarenaviruses remain limited to the off-label use of ribavirin and transfusion of convalescent sera. Progress in identifying novel candidate medical countermeasures against mammarenavirus infection has been slow in part because of the biosafety and biosecurity requirements. However, novel methodologies and tools have enabled increasingly efficient high-throughput molecular screens of regulatory-agency-approved small-molecule drugs and led to the identification of several compounds that could be repurposed for the treatment of infection with several mammarenaviruses. Unfortunately, most of them have not yet been evaluated in vivo. The most promising treatment under development is a monoclonal antibody cocktail that is protective against multiple lineages of the Lassa virus in nonhuman primate disease models.

Patient-reported quality of life and acceptance of the extravascular implantable cardioverter-defibrillator: Results from pivotal study.

INTRODUCTION: The pivotal study of the extravascular implantable cardioverter-defibrillator (EV ICD) recently demonstrated primary efficacy and safety endpoints comparable to previous ICD systems. Patient experience with this novel device has not been reported. The current study examined the standardized patient-reported outcome (PRO) metrics of quality of life (QOL) and patient acceptance of the device. METHODS: The EV ICD Pivotal Study was a prospective, single-arm, nonrandomized, global, premarket approval trial. Patients completed the 12-Item Short Form Survey (SF-12) QOL surveys at baseline and at 6 months following implant. Additionally, patients completed the Florida Patient Acceptance Survey (FPAS) QOL survey at 6 months. RESULTS: From baseline to 6 months, patients within the EV ICD Pivotal Study (n = 247) reported statistically significant SF-12 improvements in physical QOL (45.4 ± 9.4 vs. 46.8 ± 9.1 respectively, p = .020) and no changes in mental QOL (49.3 ± 10.4 vs. 50.5 ± 9.7, p = .061). No differences were noted by sex, atrial fibrillation, or the experience of ICD shock. EV ICD patients reported better total FPAS patient acceptance of their ICD than TV-ICD or S-ICD patients using historical norms comparisons (80.4 ± 15.7 vs. 70.2 ± 17.8, p < .0001 for S-ICD and 73.0 ± 17.4, p = .004 for TV-ICD). CONCLUSION: The initial PROs for EV ICD patients indicated that patients had improvements in physical QOL from baseline to 6-month follow-up and markedly better overall acceptance of their ICD compared to a previous study with S-ICD and TV-ICD data. These initial results suggest that the EV ICD is evaluated positively by patients.

Repeatability of computed tomography liver radiomic features in a nonhuman primate model of diet-induced steatosis.

Purpose: We describe a method to identify repeatable liver computed tomography (CT) radiomic features, suitable for detection of steatosis, in nonhuman primates. Criteria used for feature selection exclude nonrepeatable features and may be useful to improve the performance and robustness of radiomics-based predictive models. Approach: Six crab-eating macaques were equally assigned to two experimental groups, fed regular chow or an atherogenic diet. High-resolution CT images were acquired over several days for each macaque. First-order and second-order radiomic features were extracted from six regions in the liver parenchyma, either with or without liver-to-spleen intensity normalization from images reconstructed using either a standard (B-filter) or a bone-enhanced (D-filter) kernel. Intrasubject repeatability of each feature was assessed using a paired t-test for all scans and the minimum p-value was identified for each macaque. Repeatable features were defined as having a minimum p-value among all macaques above the significance level after Bonferroni's correction. Features showing a significant difference with respect to diet group were identified using a two-sample t-test. Results: A list of repeatable features was generated for each type of image. The largest number of repeatable features was achieved from spleen-normalized D-filtered images, which also produced the largest number of second-order radiomic features that were repeatable and different between diet groups. Conclusions: Repeatability depends on reconstruction kernel and normalization. Features were quantified and ranked based on their repeatability. Features to be excluded for more robust models were identified. Features that were repeatable but different between diet groups were also identified.

Novel machine-learning analysis of SARS-CoV-2 infection in a subclinical nonhuman primate model using radiomics and blood biomarkers.

Detection of the physiological response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is challenging in the absence of overt clinical signs but remains necessary to understand a full subclinical disease spectrum. In this study, our objective was to use radiomics (from computed tomography images) and blood biomarkers to predict SARS-CoV-2 infection in a nonhuman primate model (NHP) with inapparent clinical disease. To accomplish this aim, we built machine-learning models to predict SARS-CoV-2 infection in a NHP model of subclinical disease using baseline-normalized radiomic and blood sample analyses data from SARS-CoV-2-exposed and control (mock-exposed) crab-eating macaques. We applied a novel adaptation of the minimum redundancy maximum relevance (mRMR) feature-selection technique, called mRMR-permute, for statistically-thresholded and unbiased feature selection. Through performance comparison of eight machine-learning models trained on 14 feature sets, we demonstrated that a logistic regression model trained on the mRMR-permute feature set can predict SARS-CoV-2 infection with very high accuracy. Eighty-nine percent of mRMR-permute selected features had strong and significant class effects. Through this work, we identified a key set of radiomic and blood biomarkers that can be used to predict infection status even in the absence of clinical signs. Furthermore, we proposed and demonstrated the utility of a novel feature-selection technique called mRMR-permute. This work lays the foundation for the prediction and classification of SARS-CoV-2 disease severity.

Artificial Intelligence and Infectious Disease Imaging.

The mass production of the graphics processing unit and the coronavirus disease 2019 (COVID-19) pandemic have provided the means and the motivation, respectively, for rapid developments in artificial intelligence (AI) and medical imaging techniques. This has led to new opportunities to improve patient care but also new challenges that must be overcome before these techniques are put into practice. In particular, early AI models reported high performances but failed to perform as well on new data. However, these mistakes motivated further innovation focused on developing models that were not only accurate but also stable and generalizable to new data. The recent developments in AI in response to the COVID-19 pandemic will reap future dividends by facilitating, expediting, and informing other medical AI applications and educating the broad academic audience on the topic. Furthermore, AI research on imaging animal models of infectious diseases offers a unique problem space that can fill in evidence gaps that exist in clinical infectious disease research. Here, we aim to provide a focused assessment of the AI techniques leveraged in the infectious disease imaging research space, highlight the unique challenges, and discuss burgeoning solutions.

Depletion of Bone Marrow Hematopoietic Cells in Ebolavirus-Infected Rhesus Macaques: A Possible Cause of Hematologic Abnormalities in Ebolavirus Disease.

The pathophysiology of long-recognized hematologic abnormalities in Ebolavirus (EBOV) disease (EVD) is unknown. From limited human sampling (of peripheral blood), it has been postulated that emergency hematopoiesis plays a role in severe EVD, but the systematic characterization of the bone marrow (BM) has not occurred in human disease or in nonhuman primate models. In a lethal rhesus macaque model of EVD, 18 sternal BM samples exposed to the Kikwit strain of EBOV were compared to those from uninfected controls (n = 3). Immunohistochemistry, RNAscope in situ hybridization, transmission electron microscopy, and confocal microscopy showed that EBOV infects BM monocytes/macrophages and megakaryocytes. EBOV exposure was associated with severe BM hypocellularity, including depletion of myeloid, erythroid, and megakaryocyte hematopoietic cells. These depletions were negatively correlated with cell proliferation (Ki67 expression) and were not associated with BM apoptosis during disease progression. In EBOV-infected rhesus macaques with terminal disease, BM showed marked hemophagocytosis, megakaryocyte emperipolesis, and the release of immature hematopoietic cells into the sinusoids. Collectively, these data demonstrate not only direct EBOV infection of BM monocytes/macrophages and megakaryocytes but also that disease progression is associated with hematopoietic failure, notably in peripheral cytopenia. These findings inform current pathophysiologic unknowns and suggest a crucial role for BM dysfunction and/or failure, including emergency hematopoiesis, as part of the natural history of severe human disease.

Perspectives on Advancing Countermeasures for Filovirus Disease: Report From a Multisector Meeting.

Although there are now approved treatments and vaccines for Ebola virus disease, the case fatality rate remains unacceptably high even when patients are treated with the newly approved therapeutics. Furthermore, these countermeasures are not expected to be effective against disease caused by other filoviruses. A meeting of subject-matter experts was held during the 10th International Filovirus Symposium to discuss strategies to address these gaps. Several investigational therapeutics, vaccine candidates, and combination strategies were presented. The greatest challenge was identified to be the implementation of well-designed clinical trials of safety and efficacy during filovirus disease outbreaks. Preparing for this will require agreed-upon common protocols for trials intended to bridge multiple outbreaks across all at-risk countries. A multinational research consortium including at-risk countries would be an ideal mechanism to negotiate agreement on protocol design and coordinate preparation. Discussion participants recommended a follow-up meeting be held in Africa to establish such a consortium.

Ebola Virus Disease Features Hemophagocytic Lymphohistiocytosis/Macrophage Activation Syndrome in the Rhesus Macaque Model.

BACKGROUND: Ebola virus (EBOV) disease (EVD) is one of the most severe and fatal viral hemorrhagic fevers and appears to mimic many clinical and laboratory manifestations of hemophagocytic lymphohistiocytosis syndrome (HLS), also known as macrophage activation syndrome. However, a clear association is yet to be firmly established for effective host-targeted, immunomodulatory therapeutic approaches to improve outcomes in patients with severe EVD. METHODS: Twenty-four rhesus monkeys were exposed intramuscularly to the EBOV Kikwit isolate and euthanized at prescheduled time points or when they reached the end-stage disease criteria. Three additional monkeys were mock-exposed and used as uninfected controls. RESULTS: EBOV-exposed monkeys presented with clinicopathologic features of HLS, including fever, multiple organomegaly, pancytopenia, hemophagocytosis, hyperfibrinogenemia with disseminated intravascular coagulation, hypertriglyceridemia, hypercytokinemia, increased concentrations of soluble CD163 and CD25 in serum, and the loss of activated natural killer cells. CONCLUSIONS: Our data suggest that EVD in the rhesus macaque model mimics pathophysiologic features of HLS/macrophage activation syndrome. Hence, regulating inflammation and immune function might provide an effective treatment for controlling the pathogenesis of acute EVD.

Computed Tomography Imaging for Monitoring of Marburg Virus Disease: a Nonhuman Primate Proof-Of-Concept Study.

Marburg virus (MARV) is a highly virulent zoonotic filovirid that causes Marburg virus disease (MVD) in humans. The pathogenesis of MVD remains poorly understood, partially due to the low number of cases that can be studied, the absence of state-of-the-art medical equipment in areas where cases are reported, and limitations on the number of animals that can be safely used in experimental studies under maximum containment animal biosafety level 4 conditions. Medical imaging modalities, such as whole-body computed tomography (CT), may help to describe disease progression in vivo, potentially replacing ethically contentious and logistically challenging serial euthanasia studies. Towards this vision, we performed a pilot study, during which we acquired whole-body CT images of 6 rhesus monkeys before and 7 to 9 days after intramuscular MARV exposure. We identified imaging abnormalities in the liver, spleen, and axillary lymph nodes that corresponded to clinical, virological, and gross pathological hallmarks of MVD in this animal model. Quantitative image analysis indicated hepatomegaly with a significant reduction in organ density (indicating fatty infiltration of the liver), splenomegaly, and edema that corresponded with gross pathological and histopathological findings. Our results indicated that CT imaging could be used to verify and quantify typical MVD pathogenesis versus altered, diminished, or absent disease severity or progression in the presence of candidate medical countermeasures, thus possibly reducing the number of animals needed and eliminating serial euthanasia. IMPORTANCE Marburg virus (MARV) is a highly virulent zoonotic filovirid that causes Marburg virus disease (MVD) in humans. Much is unknown about disease progression and, thus, prevention and treatment options are limited. Medical imaging modalities, such as whole-body computed tomography (CT), have the potential to improve understanding of MVD pathogenesis. Our study used CT to identify abnormalities in the liver, spleen, and axillary lymph nodes that corresponded to known clinical signs of MVD in this animal model. Our results indicated that CT imaging and analyses could be used to elucidate pathogenesis and possibly assess the efficacy of candidate treatments.

Deep-Learning-Based Whole-Lung and Lung-Lesion Quantification Despite Inconsistent Ground Truth: Application to Computerized Tomography in SARS-CoV-2 Nonhuman Primate Models.

RATIONALE AND OBJECTIVES: Animal modeling of infectious diseases such as coronavirus disease 2019 (COVID-19) is important for exploration of natural history, understanding of pathogenesis, and evaluation of countermeasures. Preclinical studies enable rigorous control of experimental conditions as well as pre-exposure baseline and longitudinal measurements, including medical imaging, that are often unavailable in the clinical research setting. Computerized tomography (CT) imaging provides important diagnostic, prognostic, and disease characterization to clinicians and clinical researchers. In that context, automated deep-learning systems for the analysis of CT imaging have been broadly proposed, but their practical utility has been limited. Manual outlining of the ground truth (i.e., lung-lesions) requires accurate distinctions between abnormal and normal tissues that often have vague boundaries and is subject to reader heterogeneity in interpretation. Indeed, this subjectivity is demonstrated as wide inconsistency in manual outlines among experts and from the same expert. The application of deep-learning data-science tools has been less well-evaluated in the preclinical setting, including in nonhuman primate (NHP) models of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection/COVID-19, in which the translation of human-derived deep-learning tools is challenging. The automated segmentation of the whole lung and lung lesions provides a potentially standardized and automated method to detect and quantify disease. MATERIALS AND METHODS: We used deep-learning-based quantification of the whole lung and lung lesions on CT scans of NHPs exposed to SARS-CoV-2. We proposed a novel multi-model ensemble technique to address the inconsistency in the ground truths for deep-learning-based automated segmentation of the whole lung and lung lesions. Multiple models were obtained by training the convolutional neural network (CNN) on different subsets of the training data instead of having a single model using the entire training dataset. Moreover, we employed a feature pyramid network (FPN), a CNN that provides predictions at different resolution levels, enabling the network to predict objects with wide size variations. RESULTS: We achieved an average of 99.4 and 60.2% Dice coefficients for whole-lung and lung-lesion segmentation, respectively. The proposed multi-model FPN outperformed well-accepted methods U-Net (50.5%), V-Net (54.5%), and Inception (53.4%) for the challenging lesion-segmentation task. We show the application of segmentation outputs for longitudinal quantification of lung disease in SARS-CoV-2-exposed and mock-exposed NHPs. CONCLUSION: Deep-learning methods should be optimally characterized for and targeted specifically to preclinical research needs in terms of impact, automation, and dynamic quantification independently from purely clinical applications.

The Australian and New Zealand Cardiac Implantable Electronic Device Survey, Calendar Year 2021: 50-Year Anniversary.

BACKGROUND: A cardiac implantable electronic device (CIED) survey was undertaken in Australia and New Zealand for calendar year 2021. The survey involved pacemakers (PMs) and implantable cardioverter-defibrillators (ICDs). The survey was conducted on the 50th anniversary of the first survey for both Australia and New Zealand in 1972; that initial survey being conducted by two of the current authors. RESULTS AND CONCLUSIONS: For 2021, there were 19,410 PMs (17,971 in 2017) sold in Australia for new implants and 2,282 (1,811 in 2017) sold in New Zealand. The number of new PM implants per million population was 755 for Australia (745 in 2017) and 446 for New Zealand (384 in 2017). Unlike previous recent surveys, the percentage of PM replacements compared to total sales in both Australia and New Zealand rose. Pulse generator types implanted were predominantly dual chamber; Australia 77% (73% in 2017) and New Zealand 70% (68% in 2017). There were 1,509 biventricular PMs implanted in Australia (1,247 in 2017) and 172 in New Zealand (118 in 2017). Transvenous pacing leads were >90% active fixation in the atrium and ventricle. There was an increase in ICD usage with Australia 4,519 new implants (4,212 in 2017) and New Zealand 449 (396 in 2017). New ICD implants per million population were 187 for Australia (175 in 2017) and 88 for New Zealand (90 in 2017). For the first time the survey included implantable event monitors with 6,933 being implanted in Australia. However, for proprietary reasons, survey figures for subcutaneous implantable defibrillators, leadless pacemakers and conduction system pacing have not been included. Both Australia and New Zealand have high PM and ICD implant numbers compared to the rest of the Asia Pacific region.

Natural history of Ebola virus disease in rhesus monkeys shows viral variant emergence dynamics and tissue-specific host responses.

Ebola virus (EBOV) causes Ebola virus disease (EVD), marked by severe hemorrhagic fever; however, the mechanisms underlying the disease remain unclear. To assess the molecular basis of EVD across time, we performed RNA sequencing on 17 tissues from a natural history study of 21 rhesus monkeys, developing new methods to characterize host-pathogen dynamics. We identified alterations in host gene expression with previously unknown tissue-specific changes, including downregulation of genes related to tissue connectivity. EBOV was widely disseminated throughout the body; using a new, broadly applicable deconvolution method, we found that viral load correlated with increased monocyte presence. Patterns of viral variation between tissues differentiated primary infections from compartmentalized infections, and several variants impacted viral fitness in a EBOV/Kikwit minigenome system, suggesting that functionally significant variants can emerge during early infection. This comprehensive portrait of host-pathogen dynamics in EVD illuminates new features of pathogenesis and establishes resources to study other emerging pathogens.

Anti-Ebola virus mAb 3A6 with unprecedented potency protects highly viremic animals from fatal outcome and physically lifts its glycoprotein target from the virion membrane.

Monoclonal antibodies (mAbs) against Ebola virus (EBOV) glycoprotein (GP1,2) are the standard of care for Ebola virus disease (EVD). Anti-GP1,2 mAbs targeting the stalk and membrane proximal external region (MPER) potently neutralize EBOV in vitro. However, their neutralization mechanism is poorly understood because they target a GP1,2 epitope that has evaded structural characterization. Moreover, their in vivo efficacy has only been evaluated in the mouse model of EVD. Using x-ray crystallography and cryo-electron tomography of 3A6 complexed with its stalk- GP1,2 MPER epitope we reveal a novel mechanism in which 3A6 elevates the stalk or stabilizes a conformation of GP1,2 that is lifted from the virion membrane. In domestic guinea pig and rhesus monkey EVD models, 3A6 provides therapeutic benefit at high viremia levels, advanced disease stages, and at the lowest dose yet demonstrated for any anti-EBOV mAb-based monotherapy. These findings can guide design of next-generation, highly potent anti-EBOV mAbs.

Visual acuity and vision-related quality of life outcomes following cataract surgery in Ebola virus disease survivors.

Objectives: The objectives of this study were to assess relationships between vision-related quality of life (QoL) and visual acuity (VA) in Ebola virus disease (EVD) survivors after cataract surgery in the Ebola Viral Persistence in Ocular Tissues and Fluids (EVICT) Study. Materials and Methods: EVD survivors with undetectable Ebola virus (EBOV) ribonucleic acid in their aqueous humour were eligible to receive manual small-incision cataract surgery (MSICS). Among those that received surgery, assessments of VA and vision-related QoL were assessed pre-and post-cataract surgery. VA was converted from units on a tumbling 'E' chart to the logarithm of the minimal angle of resolution VA (logMAR VA). Vision-related QoL was assessed using the 25-item National Eye Institute Visual Function Questionnaire (NEI VFQ-25). Linear regression was used to evaluate the associations between VA and vision-related QoL. P = 0.05 was considered statistically significant for all analyses. Results: Thirty-four EVD survivors underwent cataract surgery in the EVICT study. Before MSICS, the mean logMAR VA was 2.24 (standard deviation [SD]: 0.98), and the mean NEI-VFQ-25 composite score was 54 (SD: 15); however, there was no significant association between the pre-surgery measurements (average difference in VA/10 unit increase in NEI-VFQ-25: -0.04, 95% confidence interval (CI): -0.33-0.26, P = 0.80). There was a significant improvement in logMAR VA after MSICS (mean: 1.6, P < 0.001), but there was no significant change in the NEI-VFQ-25 composite (-0.87, 95% (CI): -10.32-8.59, P = 0.85). None of the subscales showed significant improvements (P > 0.12 for all); however, the magnitude of the mean change for distance activities (6.65), near activities (6.76), general vision (-7.69), social functioning (-9.13) and colour vision (13.33) met the criteria for a clinically meaningful difference (4-6). In the subset with paired measurements (n = 16), there were no significant association changes in logMAR VA and NEI VFQ-25 composite scores (P > 0.12 for all). Conclusion: Following cataract surgery, VA in EVD survivors improved, but these improvements were not reflected in NEI VFQ-25 composite scores or specific subscales; however, the small sample size limits generalizability absent more research. Differences in sociocultural context and activities that affect the QoL in resource-limited areas may contribute to the limitations seen with NEI VFQ-25. In addition, better eye dominance could contribute to any lack of association as NEI VFQ-25 evaluates vision as a whole. Further, assessment of factors contributing to improved QoL may help to define the impact of vision health in varied environments.

Toward the determination of sensitive and reliable whole-lung computed tomography features for robust standard radiomics and delta-radiomics analysis in a nonhuman primate model of coronavirus disease 2019.

Purpose: We propose a method to identify sensitive and reliable whole-lung radiomic features from computed tomography (CT) images in a nonhuman primate model of coronavirus disease 2019 (COVID-19). Criteria used for feature selection in this method may improve the performance and robustness of predictive models. Approach: Fourteen crab-eating macaques were assigned to two experimental groups and exposed to either severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) or a mock inoculum. High-resolution CT scans were acquired before exposure and on several post-exposure days. Lung volumes were segmented using a deep-learning methodology, and radiomic features were extracted from the original image. The reliability of each feature was assessed by the intraclass correlation coefficient (ICC) using the mock-exposed group data. The sensitivity of each feature was assessed using the virus-exposed group data by defining a factor R that estimates the excess of variation above the maximum normal variation computed in the mock-exposed group. R and ICC were used to rank features and identify non-sensitive and unstable features. Results: Out of 111 radiomic features, 43% had excellent reliability ( ICC > 0.90 ), and 55% had either good ( ICC > 0.75 ) or moderate ( ICC > 0.50 ) reliability. Nineteen features were not sensitive to the radiological manifestations of SARS-CoV-2 exposure. The sensitivity of features showed patterns that suggested a correlation with the radiological manifestations. Conclusions: Features were quantified and ranked based on their sensitivity and reliability. Features to be excluded to create more robust models were identified. Applicability to similar viral pneumonia studies is also possible.