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At least 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Clinical practice gaps and challenges in non‐alcoholic steatohepatitis care: An international physician needs assessment

Abstract Background and aims Even as several pharmacological treatments for non‐alcoholic steatohepatitis (NASH) are in development, the incidence of NASH is increasing on an international scale. We aim to assess clinical practice gaps and challenges of hepatologists and endocrinologists when managing patients with NASH in four countries (Germany/Italy/United Kingdom/United States) to inform educational interventions. Methods A sequential mixed‐method design was used: qualitative semi‐structured interviews followed by quantitative online surveys. Participants were hepatologists and endocrinologists practising in one of the targeted countries. Interview data underwent thematic analysis and survey data were analysed with chi‐square and Kruskal‐Wallis tests. Results Most interviewees ( n = 24) and surveyed participants (89% of n = 224) agreed that primary care must be involved in screening for NASH, yet many faced challenges involving and collaborating with them. Endocrinologists reported low knowledge of which blood markers to use when suspecting NASH (56%), when to order an MRI (65%) or ultrasound/FibroScan® (46%), and reported sub‐optimal skills interpreting alanine aminotransferase (ALT, 37%) and aspartate aminotransferase (AST, 38%) blood marker test results, causing difficulty during diagnosis. Participants believed that more evidence is needed for upcoming therapeutic agents; yet, they reported sub‐optimal knowledge of eligibility criteria for clinical trials. Knowledge and skill gaps when managing comorbidities, as well as skill gaps facilitating patient lifestyle changes were reported. Conclusions Educational interventions are needed to address the knowledge and skill gaps identified and to develop strategies to optimize patient care, which include implementing relevant care pathways, encouraging referrals and testing, and multidisciplinary collaboration, as suggested by the recent Global Consensus statement on NAFLD.

Lazure, Patrice↗
DOE OSTI2020

Knocking out barriers to engineered cell activity

Engineered T cell therapies are revolutionizing cancer treatment by achieving long-lasting remission in blood-related cancers, such as leukemia and lymphoma. These therapies involve removal of patient T cells, “reprogramming” them to attack cancer cells, and then transferring them back into the patient. Targeted gene inactivation (knockout) using CRISPR-Cas9 can enhance T cell activity (1, 2) and has the potential to expand cell therapy applications. Until now, it has been unknown whether CRISPR-Cas9–edited T cells would be tolerated and thrive once reinfused into a human. On page 1001 of this issue, Stadtmauer et al. (3) present data from a phase 1 clinical trial (designed to test safety and feasibility) on the first cancer patients treated with CRISPR-Cas9–modified T cells. The findings represent an important advance in the therapeutic application of gene editing and highlight the potential to accelerate development of cell-based therapies.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

SARS-CoV-2 Beta variant infection elicits potent lineage-specific and cross-reactive antibodies

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Beta variant of concern (VOC) resists neutralization by major classes of antibodies from COVID-19 patients and vaccinated individuals. In this study, serum of Beta-infected patients revealed reduced cross-neutralization of wild-type virus. From these patients, we isolated Beta-specific and cross-reactive receptor-binding domain (RBD) antibodies. The Beta-specificity results from recruitment of VOC-specific clonotypes and accommodation of mutations present in Beta and Omicron into a major antibody class that is normally sensitive to these mutations. The Beta-elicited cross-reactive antibodies share genetic and structural features with wild type–elicited antibodies, including a public VH1-58 clonotype that targets the RBD ridge. These findings advance our understanding of the antibody response to SARS-CoV-2 shaped by antigenic drift, with implications for design of next-generation vaccines and therapeutics.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

A Review of Doses for Dental Imaging in 2010–2020 and Development of a Web Dose Calculator

Dental imaging is one of the most common types of diagnostic radiological procedures in modern medicine. We introduce a comprehensive table of organ doses received by patients in dental imaging procedures extracted from literature and a new web application to visualize the summarized dose information. We analyzed articles, published after 2010, from PubMed on organ and effective doses delivered by dental imaging procedures, including intraoral radiography, panoramic radiography, and cone-beam computed tomography (CBCT), and summarized doses by dosimetry method, machine model, patient age, and technical parameters. Mean effective doses delivered by intraoral, 1.32 (0.60–2.56) μSv, and panoramic, 17.93 (3.47–75.00) μSv, procedures were found to be about1% and 15% of that delivered by CBCT, 121.09 (17.10–392.20) μSv, respectively. In CBCT imaging, child phantoms received about 29% more effective dose than the adult phantoms received. The effective dose of a large field of view (FOV) (>150 cm2) was about 1.6 times greater than that of a small FOV (<50 cm2). The maximum CBCT effective dose with a large FOV for children, 392.2 μSv, was about 13% of theeffective dose that a person receives on average every year from natural radiation, 3110 μSv. Monte Carlo simulations of representative cases of the three dental imaging procedures were then conducted to estimate and visualize the dose distribution within the head. The user-friendly interactive web application (available at http://dentaldose.org) receives user input, such as the number of intraoral radiographs taken, and displays total organ and effective doses, dose distribution maps, and a comparison with other medical and natural sources of radiation. The web dose calculator provides a practical resource for patients interested in understanding the radiation doses delivered by dental imaging procedures.

Lee, Hawon↗
DOE OSTI2022

SARS-CoV-2 Infection-Associated Aortic Thrombosis Treated with Oral Factor Xa Inhibition

Coronavirus disease 2019 (COVID-19) is an acute complex systemic disorder caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).While SARS-CoV-2 is known to cause significant pulmonary disease, various extrapulmonary manifestations of COVID-19 have also been reported. Growing evidence suggests that COVID-19 is associated with coagulopathy leading to micro and macrovascular complications. Although in patients with COVID-19, venous thromboembolic events are more frequent, arterial thrombosis also occurs at an increased rate. These often lead to acute life-threatening ischemia, which requires urgent diagnosis and treatment. We present case reports of two patients with an abnormal thrombus formation in the thoracic aorta who recently overcame COVID-19, which led to systemic embolism and splenic infarction. Ambulatory oral factor Xa inhibitor therapy led to aortic thrombosis resolution in both patients.

Strýčková, Alena↗
DOE OSTI2020

Development and validation of a next-generation sequencing-based multigene assay to predict the prognosis of estrogen receptor-positive, HER2-negative breast cancer

Purpose: Multigene assays provide useful prognostic information regarding hormone receptor (HR)-positive breast cancer. Next-generation sequencing (NGS)-based platforms have numerous advantages including reproducibility and adaptability in local laboratories. Here we aimed to develop and validate an NGS-based multigene assay to predict the distant recurrence risk. Experimental Design: In total, 179 genes including 30 reference genes highly correlated with the 21-gene recurrence score (RS) algorithm were selected from public databases. Targeted RNA-sequencing was performed using 250 and 93 archived breast cancer samples with a known RS in the training and verification sets, respectively, to develop the algorithm and NGS–Prognostic Score (NGS-PS). The assay was validated in 413 independent samples with long-term follow-up data on distant metastasis. Results: In the verification set, the NGS-PS and 21-gene RS displayed 91.4% concurrence (85/93 samples). In the validation cohort of 413 samples, area under the receiver operating characteristic curve plotted using NGS-PS values classified for distant recurrence was 0.76. The best NGS-PS cut-off value predicting distant metastasis was 20. Furthermore, 269 and 144 patients were classified as low- and high-risk patients in accordance with the cut-off. Five- and 10-year estimates of distant metastasis–free survival (DMFS) for low- versus high-risk groups were 97.0% versus 77.8% and 93.2% versus 64.4%, respectively. The age-related HR for distant recurrence without chemotherapy was 9.73 (95% CI, 3.59–26.40) and 3.19 (95% CI, 1.40–7.29) for patients aged ≤50 and >50 years, respectively. Conclusions: The newly developed and validated NGS-based multigene assay can predict the distant recurrence risk in ER-positive, HER2-negative breast cancer.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Treatment of Prostate Cancer with CD46-targeted 225 Ac Alpha Particle Radioimmunotherapy

Radiopharmaceutical therapy is changing the standard of care in prostate cancer and other malignancies. We previously reported high CD46 expression in prostate cancer and developed an antibody–drug conjugate and immunoPET agent based on the YS5 antibody, which targets a tumor-selective CD46 epitope. Here, we present the preparation, preclinical efficacy, and toxicity evaluation of [ 225 Ac]DOTA-YS5, a radioimmunotherapy agent based on the YS5 antibody. [ 225 Ac]DOTA-YS5 was developed, and its therapeutic efficiency was tested on cell-derived (22Rv1, DU145), and patient-derived (LTL-545, LTL484) prostate cancer xenograft models. Biodistribution studies were carried out on 22Rv1 tumor xenograft models to confirm the targeting efficacy. Toxicity analysis of the [ 225 Ac]DOTA-YS5 was carried out on nu/nu mice to study short-term (acute) and long-term (chronic) toxicity. Biodistribution study shows that [ 225 Ac]DOTA-YS5 agent delivers high levels of radiation to the tumor tissue (11.64% ± 1.37%ID/g, 28.58% ± 10.88%ID/g, 29.35% ± 7.76%ID/g, and 31.78% ± 5.89%ID/g at 24, 96, 168, and 408 hours, respectively), compared with the healthy organs. [ 225 Ac]DOTA-YS5 suppressed tumor size and prolonged survival in cell line–derived and patient-derived xenograft models. Toxicity analysis revealed that the 0.5 μCi activity levels showed toxicity to the kidneys, likely due to redistribution of daughter isotope 213 Bi. [ 225 Ac]DOTA-YS5 suppressed the growth of cell-derived and patient-derived xenografts, including prostate-specific membrane antigen–positive and prostate-specific membrane antigen–deficient models. Overall, this preclinical study confirms that [ 225 Ac]DOTA-YS5 is a highly effective treatment and suggests feasibility for clinical translation of CD46-targeted radioligand therapy in prostate cancer.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2020

Oxaliplatin–DNA Adducts as Predictive Biomarkers of FOLFOX Response in Colorectal Cancer: A Potential Treatment Optimization Strategy

FOLFOX is one of the most effective treatments for advanced colorectal cancer (CRC). However, cumulative oxaliplatin neurotoxicity often results in halting the therapy. Oxaliplatin functions predominantly via the formation of toxic covalent drug-DNA adducts. We hypothesize that oxaliplatin-DNA adduct levels formed in vivo in peripheral blood mononuclear cells (PBMC) are proportional to tumor shrinkage caused by FOLFOX therapy. We further hypothesize that adducts induced by sub-therapeutic "diagnostic microdoses" are proportional to those induced by therapeutic doses and are also predictive of response to FOLFOX therapy. These hypotheses were tested in CRC cell lines and a pilot clinical study. Four CRC cell lines were cultured with therapeutically relevant (100 µM) or diagnostic microdose (1 µM) concentrations of [ 14 C]oxaliplatin. The C-14 label enabled quantification of oxaliplatin-DNA adduct level with accelerator mass spectrometry (AMS). Oxaliplatin-DNA adduct formation was correlated with oxaliplatin cytotoxicity for each cell line as measured by the MTT viability assay. Six CRC patients received by IV a diagnostic microdose containing [ 14 C]oxaliplatin prior to treatment, as well as a second [ 14 C]oxaliplatin dose during FOLFOX chemotherapy, termed a "therapeutic dose." Oxaliplatin-DNA adduct levels from PBMC correlated significantly to mean tumor volume change of evaluable target lesions (5 of the 6 patients had measurable disease). Finally, oxaliplatin-DNA adduct levels were linearly proportional between microdose and therapeutically relevant concentrations in cell culture experiments and patient samples, as was plasma pharmacokinetics, indicating potential utility of diagnostic microdosing.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Long-term Multimodal Recording Reveals Epigenetic Adaptation Routes in Dormant Breast Cancer Cells

Patients with estrogen receptor–positive breast cancer receive adjuvant endocrine therapies (ET) that delay relapse by targeting clinically undetectable micrometastatic deposits. Yet, up to 50% of patients relapse even decades after surgery through unknown mechanisms likely involving dormancy. To investigate genetic and transcriptional changes underlying tumor awakening, we analyzed late relapse patients and longitudinally profiled a rare cohort treated with long-term neoadjuvant ETs until progression. Next, we developed an in vitro evolutionary study to record the adaptive strategies of individual lineages in unperturbed parallel experiments. Our data demonstrate that ETs induce nongenetic cell state transitions into dormancy in a stochastic subset of cells via epigenetic reprogramming. Single lineages with divergent phenotypes awaken unpredictably in the absence of recurrent genetic alterations. Targeting the dormant epigenome shows promising activity against adapting cancer cells. Overall, this study uncovers the contribution of epigenetic adaptation to the evolution of resistance to ETs.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Association of Serum Triglyceride Levels with Severity in Acute Pancreatitis: Results from an International, Multicenter Cohort Study

Hypertriglyceridemia (HTG) is considered within the top 5 etiologies in acute pancreatitis (AP), but the association of serum triglyceride (TG) levels with the clinical course of AP remains controversial. This study aims to examine the effect of TG levels on severity of AP. Patients were enrolled prospectively through APPRENTICE. High TG levels were defined based on the Endocrine Society Clinical Practice Guidelines. HTG was categorized as mild (serum TG levels 150–199 mg/dL), moderate (200–999 mg/dL), severe (1,000–1,999 mg/dL), and very severe (≥2,000 mg/dL). Severity of AP was based on the revised Atlanta classification criteria. Additionally, early TG levels were measured in 764 subjects and found elevated in 342 (120 with mild; 176, moderate; and 46, severe/very severe HTG). Patients with increased TG levels were younger (age ≥60, 16.7 vs. 30.3%), more likely to be male (66.1 vs. 51.2%), with more frequent alcohol use (62.8 vs. 50.7%), and diabetes mellitus (30.2 vs. 12.3%; all p ≤ 0.005). Severe AP (24.9 vs. 10.0%), ICU admission (32.5 vs. 19.7%), and mortality (5.3 vs. 1.7%; all p ≤ 0.005) were more frequently seen in patients with elevated TG levels. Based on multivariable analysis, elevated TG levels were independently associated with severe AP ( p < 0.05). This large multicenter study confirms that elevated TG levels are associated with severe disease regardless of AP etiology.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Bigpicc: a graph-based approach to identifying carcinogenic gene combinations from mutation data

Abstract Genome data from cancer patients represents relationships between the presence of a gene mutation and cancer occurrence in a patient. Different types of cancer in human are thought to be caused by combinations of two to nine gene mutations. Identifying these combinations through traditional exhaustive search requires the amount of computation that scales exponentially with the combination size and in most cases is intractable even for cutting-edge supercomputers. We propose a parameter-free heuristic approach that leverages the intrinsic topology of gene-patient mutations to identify carcinogenic combinations. The biological relevance of the identified combinations is measured by using them to predict the presence of tumor in previously unseen samples. The resulting classifiers for 16 cancer types perform on par with exhaustive search results, and score the average of 80.1% sensitivity and 91.6% specificity for the best choice of hit range per cancer type. Our approach is able to find higher-hit carcinogenic combinations targeting which would take years of computations using exhaustive search.

Biochemistry & Molecular Biology↗
DOE OSTI2022

Identifying intragenic functional modules of genomic variations associated with cancer phenotypes by learning representation of association networks

Background Genome-wide Association Studies (GWAS) aims to uncover the link between genomic variation and phenotype. They have been actively applied in cancer biology to investigate associations between variations and cancer phenotypes, such as susceptibility to certain types of cancer and predisposed responsiveness to specific treatments. Since GWAS primarily focuses on finding associations between individual genomic variations and cancer phenotypes, there are limitations in understanding the mechanisms by which cancer phenotypes are cooperatively affected by more than one genomic variation. Results This paper proposes a network representation learning approach to learn associations among genomic variations using a prostate cancer cohort. The learned associations are encoded into representations that can be used to identify functional modules of genomic variations within genes associated with early- and late-onset prostate cancer. The proposed method was applied to a prostate cancer cohort provided by the Veterans Administration’s Million Veteran Program to identify candidates for functional modules associated with early-onset prostate cancer. The cohort included 33,159 prostate cancer patients, 3181 early-onset patients, and 29,978 late-onset patients. The reproducibility of the proposed approach clearly showed that the proposed approach can improve the model performance in terms of robustness. Conclusions To our knowledge, this is the first attempt to use a network representation learning approach to learn associations among genomic variations within genes. Associations learned in this way can lead to an understanding of the underlying mechanisms of how genomic variations cooperatively affect each cancer phenotype. This method can reveal unknown knowledge in the field of cancer biology and can be utilized to design more advanced cancer-targeted therapies.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Dose-finding studies in drug development for rare genetic diseases

The small patient populations inherent to rare genetic diseases present many challenges to the traditional drug development paradigm. One major challenge is generating sufficient data in early phase studies to inform dose selection for later phase studies and dose optimization for clinical use of the drug. However, optimizing the benefit-risk profile of drugs through appropriate dose selection during drug development is critical for all drugs, including those being developed to treat rare diseases. Recognizing the challenges of conducting dose finding studies in rare disease populations and the importance of dose selection and optimization for successful drug development, we assessed the dose-finding studies and analyses conducted for drugs recently approved for rare genetic diseases. Of the 40 marketing applications for new molecular entity (NME) drugs and biologics approved by the United States Food and Drug Administration for rare genetic diseases from 2015 to 2020, 21 (53%) of the development programs conducted at least one dedicated dose-finding study. In addition, the majority of drug development programs conducted clinical studies in healthy subjects and included population pharmacokinetic and exposure–response analyses; some programs also conducted clinical studies in patient populations other than the disease for which the drug was initially approved. The majority of primary endpoints utilized in dedicated dose-finding studies were biomarkers, and the primary endpoint of the safety and efficacy study matched the primary endpoint used in the dose finding study in 9 of 13 (69%) drug development programs where primary study endpoints were assessed. Our study showed that NME drug development programs for rare genetic diseases utilize multiple data sources for dosing information, including studies in healthy subjects, population pharmacokinetic analyses, and exposure–response analyses. In addition, our results indicate that biomarkers play a key role in dose-finding studies for rare genetic disease drug development programs. Our findings highlight the need to develop study designs and methods to allow adequate dose-finding efforts within rare disease drug development programs that help overcome the challenges presented by low patient prevalence and other factors. Furthermore, the frequent reliance on biomarkers as endpoints for dose-finding studies underscores the importance of biomarker development in rare diseases.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

A vision of immuno-oncology: the Siena think tank of the Italian Network for Tumor Biotherapy (NIBIT) foundation

The yearly Think Tank Meeting of the Italian Network for Tumor Biotherapy (NIBIT) Foundation, brings together in Siena, Tuscany (Italy), experts in immuno-oncology to review the learnings from current immunotherapy treatments, and to propose new pre-clinical and clinical investigations in selected research areas. While immunotherapies in non-small cell lung cancer and melanoma led to practice changing therapies, the same therapies had only modest benefit for patients with other malignancies, such as mesothelioma and glioblastoma. One way to improve on current immunotherapies is to alter the sequence of each combination agent. Matching the immunotherapy to the host’s immune response may thus improve the activity of the current treatments. A second approach is to combine current immunotherapies with novel agents targeting complementary mechanisms. Identifying the appropriate novel agents may require different approaches than the traditional laboratory-based discovery work. For example, artificial intelligence-based research may help focusing the search for innovative and most promising combination partners. Novel immunotherapies are needed in cancer patients with resistance to or relapse after current immunotherapeutic drugs. Such new treatments may include targeted agents or monoclonal antibodies to overcome the immune-suppressive tumor microenvironment. The mode of combining the novel treatments, including vaccines, needs to be matched to the patient’s immune status for achieving the maximum benefit. In this scenario, specific attention should be also paid nowadays to the immune intersection between COVID-19 and cancer.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Spatially distributed infection increases viral load in a computational model of SARS-CoV-2 lung infection

A key question in SARS-CoV-2 infection is why viral loads and patient outcomes vary dramatically across individuals. Because spatial-temporal dynamics of viral spread and immune response are challenging to study in vivo, we developed Spatial Immune Model of Coronavirus (SIMCoV), a scalable computational model that simulates hundreds of millions of lung cells, including respiratory epithelial cells and T cells. SIMCoV replicates viral growth dynamics observed in patients and shows how spatially dispersed infections can lead to increased viral loads. The model also shows how the timing and strength of the T cell response can affect viral persistence, oscillations, and control. By incorporating spatial interactions, SIMCoV provides a parsimonious explanation for the dramatically different viral load trajectories among patients by varying only the number of initial sites of infection and the magnitude and timing of the T cell immune response. When the branching airway structure of the lung is explicitly represented, we find that virus spreads faster than in a 2D layer of epithelial cells, but much more slowly than in an undifferentiated 3D grid or in a well-mixed differential equation model. These results illustrate how realistic, spatially explicit computational models can improve understanding of within-host dynamics of SARS-CoV-2 infection.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Combining biomarker and virus phylogenetic models improves HIV-1 epidemiological source identification

To identify and stop active HIV transmission chains new epidemiological techniques are needed. Here, we describe the development of a multi-biomarker augmentation to phylogenetic inference of the underlying transmission history in a local population. HIV biomarkers are measurable biological quantities that have some relationship to the amount of time someone has been infected with HIV. To train our model, we used five biomarkers based on real data from serological assays, HIV sequence data, and target cell counts in longitudinally followed, untreated patients with known infection times. The biomarkers were modeled with a mixed effects framework to allow for patient specific variation and general trends, and fit to patient data using Markov Chain Monte Carlo (MCMC) methods. Subsequently, the density of the unobserved infection time conditional on observed biomarkers were obtained by integrating out the random effects from the model fit. This probabilistic information about infection times was incorporated into the likelihood function for the transmission history and phylogenetic tree reconstruction, informed by the HIV sequence data. To critically test our methodology, we developed a coalescent-based simulation framework that generates phylogenies and biomarkers given a specific or general transmission history. Testing on many epidemiological scenarios showed that biomarker augmented phylogenetics can reach 90% accuracy under idealized situations. Under realistic within-host HIV-1 evolution, involving substantial within-host diversification and frequent transmission of multiple lineages, the average accuracy was at about 50% in transmission clusters involving 5–50 hosts. Realistic biomarker data added on average 16 percentage points over using the phylogeny alone. Using more biomarkers improved the performance. Shorter temporal spacing between transmission events and increased transmission heterogeneity reduced reconstruction accuracy, but larger clusters were not harder to get right. More sequence data per infected host also improved accuracy. We show that the method is robust to incomplete sampling and that adding biomarkers improves reconstructions of real HIV-1 transmission histories. The technology presented here could allow for better prevention programs by providing data for locally informed and tailored strategies.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Detection of significant antiviral drug effects on COVID-19 with reasonable sample sizes in randomized controlled trials: A modeling study

Development of an effective antiviral drug for Coronavirus Disease 2019 (COVID-19) is a global health priority. Although several candidate drugs have been identified through in vitro and in vivo models, consistent and compelling evidence from clinical studies is limited. The lack of evidence from clinical trials may stem in part from the imperfect design of the trials. We investigated how clinical trials for antivirals need to be designed, especially focusing on the sample size in randomized controlled trials. A modeling study was conducted to help understand the reasons behind inconsistent clinical trial findings and to design better clinical trials. We first analyzed longitudinal viral load data for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) without antiviral treatment by use of a within-host virus dynamics model. The fitted viral load was categorized into 3 different groups by a clustering approach. Comparison of the estimated parameters showed that the 3 distinct groups were characterized by different virus decay rates (p-value < 0.001). The mean decay rates were 1.17 d -1 (95% CI: 1.06 to 1.27 d -1 ), 0.777 d -1 (0.716 to 0.838 d -1 ), and 0.450 d -1 (0.378 to 0.522 d -1 ) for the 3 groups, respectively. Such heterogeneity in virus dynamics could be a confounding variable if it is associated with treatment allocation in compassionate use programs (i.e., observational studies). Subsequently, we mimicked randomized controlled trials of antivirals by simulation. An antiviral effect causing a 95% to 99% reduction in viral replication was added to the model. To be realistic, we assumed that randomization and treatment are initiated with some time lag after symptom onset. Using the duration of virus shedding as an outcome, the sample size to detect a statistically significant mean difference between the treatment and placebo groups (1:1 allocation) was 13,603 and 11,670 (when the antiviral effect was 95% and 99%, respectively) per group if all patients are enrolled regardless of timing of randomization. The sample size was reduced to 584 and 458 (when the antiviral effect was 95% and 99%, respectively) if only patients who are treated within 1 day of symptom onset are enrolled. We confirmed the sample size was similarly reduced when using cumulative viral load in log scale as an outcome. We used a conventional virus dynamics model, which may not fully reflect the detailed mechanisms of viral dynamics of SARS-CoV-2. The model needs to be calibrated in terms of both parameter settings and model structure, which would yield more reliable sample size calculation. In this study, we found that estimated association in observational studies can be biased due to large heterogeneity in viral dynamics among infected individuals, and statistically significant effect in randomized controlled trials may be difficult to be detected due to small sample size. The sample size can be dramatically reduced by recruiting patients immediately after developing symptoms. We believe this is the first study investigated the study design of clinical trials for antiviral treatment using the viral dynamics model.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Structure and antigenicity of the divergent human astrovirus VA1 capsid spike

Human astrovirus (HAstV) is a known cause of viral gastroenteritis in children worldwide, but HAstV can cause also severe and systemic infections in immunocompromised patients. There are three clades of HAstV: classical, MLB, and VA/HMO. While all three clades are found in gastrointestinal samples, HAstV-VA/HMO is the main clade associated with meningitis and encephalitis in immunocompromised patients. To understand how the HAstV-VA/HMO can infect the central nervous system, we investigated its sequence-divergent capsid spike, which functions in cell attachment and may influence viral tropism. Here we report the high-resolution crystal structures of the HAstV-VA1 capsid spike from strains isolated from patients with gastrointestinal and neuronal disease. The HAstV-VA1 spike forms a dimer and shares a core beta-barrel structure with other astrovirus capsid spikes but is otherwise strikingly different, suggesting that HAstV-VA1 may utilize a different cell receptor, and an infection competition assay supports this hypothesis. Furthermore, by mapping the capsid protease cleavage site onto the structure, the maturation and assembly of the HAstV-VA1 capsid is revealed. Finally, comparison of gastrointestinal and neuronal HAstV-VA1 sequences, structures, and antigenicity suggests that neuronal HAstV-VA1 strains may have acquired immune escape mutations. Overall, our studies on the HAstV-VA1 capsid spike lay a foundation to further investigate the biology of HAstV-VA/HMO and to develop vaccines and therapeutics targeting it.

60 APPLIED LIFE SCIENCES↗