Unlocking the Potential of Clustering and Classification Approaches: Navigating Supervised and Unsupervised Chemical Similarity.

BACKGROUND: The field of toxicology has witnessed substantial advancements in recent years, particularly with the adoption of new approach methodologies (NAMs) to understand and predict chemical toxicity. Class-based methods such as clustering and classification are key to NAMs development and application, aiding the understanding of hazard and risk concerns associated with groups of chemicals without additional laboratory work. Advances in computational chemistry, data generation and availability, and machine learning algorithms represent important opportunities for continued improvement of these techniques to optimize their utility for specific regulatory and research purposes. However, due to their intricacy, deep understanding and careful selection are imperative to align the adequate methods with their intended applications. OBJECTIVES: This commentary aims to deepen the understanding of class-based approaches by elucidating the pivotal role of chemical similarity (structural and biological) in clustering and classification approaches (CCAs). It addresses the dichotomy between general end point-agnostic similarity, often entailing unsupervised analysis, and end point-specific similarity necessitating supervised learning. The goal is to highlight the nuances of these approaches, their applications, and common misuses. DISCUSSION: Understanding similarity is pivotal in toxicological research involving CCAs. The effectiveness of these approaches depends on the right definition and measure of similarity, which varies based on context and objectives of the study. This choice is influenced by how chemical structures are represented and the respective labels indicating biological activity, if applicable. The distinction between unsupervised clustering and supervised classification methods is vital, requiring the use of end point-agnostic vs. end point-specific similarity definition. Separate use or combination of these methods requires careful consideration to prevent bias and ensure relevance for the goal of the study. Unsupervised methods use end point-agnostic similarity measures to uncover general structural patterns and relationships, aiding hypothesis generation and facilitating exploration of datasets without the need for predefined labels or explicit guidance. Conversely, supervised techniques demand end point-specific similarity to group chemicals into predefined classes or to train classification models, allowing accurate predictions for new chemicals. Misuse can arise when unsupervised methods are applied to end point-specific contexts, like analog selection in read-across, leading to erroneous conclusions. This commentary provides insights into the significance of similarity and its role in supervised classification and unsupervised clustering approaches. https://doi.org/10.1289/EHP14001.

Correction: Pannala et al. High-Throughput Transcriptomics Differentiates Toxic versus Non-Toxic Chemical Exposures Using a Rat Liver Model. Int. J. Mol. Sci. 2023, 24, 17425.

In the original publication [...].

Waitlist Outcomes for Pediatric Heart Transplantation in the Current Era: An Analysis of the Pediatric Heart Transplant Society Database.

BACKGROUND: Waitlist mortality (WM) remains elevated in pediatric heart transplantation. Allocation policy is a potential tool to help improve WM. This study aims to identify patients at highest risk for WM to potentially inform future allocation policy changes. METHODS: The Pediatric Heart Transplant Society database was queried for patients <18 years of age indicated for heart transplantation between January 1, 2010 to December 31, 2021. Waitlist mortality was defined as death while awaiting transplant or removal from the waitlist due to clinical deterioration. Because WM is low after the first year, analysis was limited to the first 12 months on the heart transplant list. Kaplan-Meier analysis and log-rank testing was conducted to compare unadjusted survival between groups. Cox proportional hazard models were created to determine risk factors for WM. Subgroup analysis was performed for status 1A patients based on body surface area (BSA) at time of listing, cardiac diagnosis, and presence of mechanical circulatory support. RESULTS: In total 5974 children met study criteria of which 3928 were status 1A, 1012 were status 1B, 963 were listed status 2, and 65 were listed status 7. Because of the significant burden of WM experienced by 1A patients, further analysis was performed in only patients indicated as 1A. Within that group of patients, those with smaller size and lower eGFR had higher WM, whereas those patients without congenital heart disease or support from a ventricular assist device (VAD) at time of listing had decreased WM. In the smallest size cohort, cardiac diagnoses other than dilated cardiomyopathy were risk factors for WM. Previous cardiac surgery was a risk factor in the 0.3 to 0.7 m2 and >0.7 m2 BSA groups. VAD support was associated with lower WM other than in the single ventricle cohort, where VAD was associated with higher WM. Extracorporeal membrane oxygenation and mechanical ventilation were associated with increased risk of WM in all cohorts. CONCLUSIONS: There is significant variability in WM among status-1A patients. Potential refinements to current allocation system should factor in the increased WM risk we identified in patients supported by extracorporeal membrane oxygenation or mechanical ventilation, single ventricle congenital heart disease on VAD support and small children with congenital heart disease, restrictive cardiomyopathy, or hypertrophic cardiomyopathy.

Metabolomics Simultaneously Derives Benchmark Dose Estimates and Discovers Metabolic Biotransformations in a Rat Bioassay.

Benchmark dose (BMD) modeling estimates the dose of a chemical that causes a perturbation from baseline. Transcriptional BMDs have been shown to be relatively consistent with apical end point BMDs, opening the door to using molecular BMDs to derive human health-based guidance values for chemical exposure. Metabolomics measures the responses of small-molecule endogenous metabolites to chemical exposure, complementing transcriptomics by characterizing downstream molecular phenotypes that are more closely associated with apical end points. The aim of this study was to apply BMD modeling to in vivo metabolomics data, to compare metabolic BMDs to both transcriptional and apical end point BMDs. This builds upon our previous application of transcriptomics and BMD modeling to a 5-day rat study of triphenyl phosphate (TPhP), applying metabolomics to the same archived tissues. Specifically, liver from rats exposed to five doses of TPhP was investigated using liquid chromatography-mass spectrometry and 1H nuclear magnetic resonance spectroscopy-based metabolomics. Following the application of BMDExpress2 software, 2903 endogenous metabolic features yielded viable dose-response models, confirming a perturbation to the liver metabolome. Metabolic BMD estimates were similarly sensitive to transcriptional BMDs, and more sensitive than both clinical chemistry and apical end point BMDs. Pathway analysis of the multiomics data sets revealed a major effect of TPhP exposure on cholesterol (and downstream) pathways, consistent with clinical chemistry measurements. Additionally, the transcriptomics data indicated that TPhP activated xenobiotic metabolism pathways, which was confirmed by using the underexploited capability of metabolomics to detect xenobiotic-related compounds. Eleven biotransformation products of TPhP were discovered, and their levels were highly correlated with multiple xenobiotic metabolism genes. This work provides a case study showing how metabolomics and transcriptomics can estimate mechanistically anchored points-of-departure. Furthermore, the study demonstrates how metabolomics can also discover biotransformation products, which could be of value within a regulatory setting, for example, as an enhancement of OECD Test Guideline 417 (toxicokinetics).

Exposure to PFAS chemicals induces sex-dependent alterations in key rate-limiting steps of lipid metabolism in liver steatosis.

Toxicants with the potential to bioaccumulate in humans and animals have long been a cause for concern, particularly due to their association with multiple diseases and organ injuries. Per- and polyfluoro alkyl substances (PFAS) and polycyclic aromatic hydrocarbons (PAH) are two such classes of chemicals that bioaccumulate and have been associated with steatosis in the liver. Although PFAS and PAH are classified as chemicals of concern, their molecular mechanisms of toxicity remain to be explored in detail. In this study, we aimed to identify potential mechanisms by which an acute exposure to PFAS and PAH chemicals can induce lipid accumulation and whether the responses depend on chemical class, dose, and sex. To this end, we analyzed mechanisms beginning with the binding of the chemical to a molecular initiating event (MIE) and the consequent transcriptomic alterations. We collated potential MIEs using predictions from our previously developed ToxProfiler tool and from published steatosis adverse outcome pathways. Most of the MIEs are transcription factors, and we collected their target genes by mining the TRRUST database. To analyze the effects of PFAS and PAH on the steatosis mechanisms, we performed a computational MIE-target gene analysis on high-throughput transcriptomic measurements of liver tissue from male and female rats exposed to either a PFAS or PAH. The results showed peroxisome proliferator-activated receptor (PPAR)-α targets to be the most dysregulated, with most of the genes being upregulated. Furthermore, PFAS exposure disrupted several lipid metabolism genes, including upregulation of fatty acid oxidation genes (Acadm, Acox1, Cpt2, Cyp4a1-3) and downregulation of lipid transport genes (Apoa1, Apoa5, Pltp). We also identified multiple genes with sex-specific behavior. Notably, the rate-limiting genes of gluconeogenesis (Pck1) and bile acid synthesis (Cyp7a1) were specifically downregulated in male rats compared to female rats, while the rate-limiting gene of lipid synthesis (Scd) showed a PFAS-specific upregulation. The results suggest that the PPAR signaling pathway plays a major role in PFAS-induced lipid accumulation in rats. Together, these results show that PFAS exposure induces a sex-specific multi-factorial mechanism involving rate-limiting genes of gluconeogenesis and bile acid synthesis that could lead to activation of an adverse outcome pathway for steatosis.

Recent Advances towards the Understanding of Secondary Acute Myeloid Leukemia Progression.

Secondary acute myeloid leukemia (sAML) is a heterogeneous malignant hematopoietic disease that arises either from an antecedent hematologic disorder (AHD) including myelodysplastic syndromes (MDS), myeloproliferative neoplasms (MPN), aplastic anemia (AA), or as a result of exposure to genotoxic chemotherapeutic agents or radiotherapy (therapy related AML, tAML). sAML is diagnosed when the number of blasts is ≥20% in the bone marrow or peripheral blood, and it is characterized by poor prognosis, resistance to therapy and low overall survival rate. With the recent advances in next generation sequencing technologies, our understanding of the molecular events associated with sAML evolution has significantly increased and opened new perspectives for the development of novel therapies. The genetic aberrations that are associated with sAML affect genes involved in processes such as splicing, chromatin modification and genome integrity. Moreover, non-coding RNAs' emerged as an important contributing factor to leukemogenesis. For decades, the standard treatment for secondary AML has been the 7 + 3 regimen of cytarabine and daunorubicin which prolongs survival for several months, but modifications in either dosage or delivery has significantly extended that time. Apart from traditional chemotherapy, hematopoietic stem cell transplantation, CAR-T cell therapy and small molecule inhibitors have also emerged to treat sAML.

Impact of prolonged ischemic time on pediatric heart transplantation outcomes: Improved outcomes in the most recent era.

BACKGROUND: Impacts of ischemic time (IT) on pediatric heart transplant outcomes are multifactorial. We aimed to analyze the effect of prolonged IT on graft loss after pediatric heart transplantation. We hypothesized that graft survival with prolonged IT has improved across eras. METHODS: Patients <18 years old in the Pediatric Heart Transplant Society database were included (N=6,765) and stratified by diagnosis and era (1993-2004, 2005-2009, and 2010-2019). Severe graft failure (SGF) was defined as death, retransplant, or need for mechanical circulatory support in the first 7 days post-transplant. Descriptive statistical methods were used to compare differences between patient characteristics and IT. Kaplan-Meier survival analysis compared freedom from graft loss, rejection, and infection. Multivariable analysis was performed for graft loss and SGF (hazard and logistic regression modeling, respectively). RESULTS: Diagnoses were cardiomyopathy (N = 3,246) and congenital heart disease (CHD; N = 3,305). CHD were younger, more likely to have an IT ≥4.5 hours, and more likely to require extracorporeal membrane oxygenation or mechanical ventilation at transplant (all p < 0.001). Median IT was 3.6 hours (interquartile range 2.98-4.31; range 0-10.5). IT was associated with early graft loss (HR 1.012, 95% CI 1.005-1.019), but not when analyzed only in the most recent era. IT was associated with SGF (OR 1.016 95%CI 1.003-1.030). CONCLUSIONS: Donor IT was independently associated with an increased risk of graft loss, albeit with a small effect relative to other risk factors. Graft survival with prolonged IT has improved in the most recent era but the risk of SGF persists.

Anti-spike antibody durability after SARS-CoV-2 vaccination in adolescent solid organ transplant recipients.

BACKGROUND: Adolescent solid organ transplant recipients (aSOTRs) who received three doses of the COVID-19 mRNA vaccine experience high seroconversion rates and antibody persistence for up to 3 months. Long-term antibody durability beyond this timeframe following three doses of the SARS-CoV-2 mRNA vaccine remains unknown. We describe antibody responses 6 months following the third vaccine dose (D3) of the BNT162b2 mRNA vaccination among aSOTRs. METHODS: Participants in a multi-center, observational cohort who received the third dose of the vaccine were analyzed for antibodies to the SARS-CoV-2 spike protein receptor-binding domain (Roche Elecsys anti-SARS-CoV-2-S positive: ≥0.8, maximum: >2500 U/mL). Samples were collected at 1-, 3-, and 6-months post-D3. Participants were surveyed at each timepoint and at 12-months post-D3. RESULTS: All 34 participants had positive anti-RBD antibody titers 6 months post-D3. Variations in titers occurred between 3 and 6 months post-D3, with 8/28 (29%) having decreased antibody levels at 6 months compared to 3 months and 2/28 (7%) reporting increased titers at 6 months. The remaining 18/28 (64%) had unchanged antibody titers compared to 3-month post-D3 levels. A total of 4/34 (12%) reported breakthrough infection within 6 months and 3/32 (9%) reported infection after 6-12 months following the third dose of the SARS-CoV-2 mRNA vaccine. CONCLUSIONS: The results suggest that antibody durability persists up to 6 months following three doses of the SARS-CoV-2 mRNA in aSOTRs. Demography and transplant characteristics did not differ for those who experienced antibody weaning. Breakthrough infections did occur, reflecting immune-evasive nature of novel variants such as Omicron.

Three decades of collaboration through the Pediatric Heart Transplant Society Registry: A journey through registry data with a highlight on children with single ventricle anatomy.

BACKGROUND: The Pediatric Heart Transplant Society (PHTS) Registry was founded 30 years ago as a collaborative effort among like-minded providers of this novel life-saving technique for children with end-stage heart failure. In the intervening decades, the data from the Registry have provided invaluable knowledge to the field of pediatric heart transplantation. This report of the PHTS Registry provides a comprehensive look at the data, highlighting both the longevity of the registry and one unique aspect of the PHTS registry, allowing for exploration into children with single ventricle anatomy. METHODS: The PHTS database was queried from January 1, 1993 to December 31, 2019 to include pediatric (age < 18 years) patients listed for HT. For our analysis, we primarily analyzed patients by era. The early era was defined as children listed for HT from January 1, 1993 to December 31, 2004; middle era January 1, 2005 to December 31, 2009; and recent era January 1, 2010 to December 31, 2019. Outcomes after listing and transplant, including mortality and morbidities, are presented as unadjusted for risk, but compared across eras. RESULTS: Since 1993, 11 995 children were listed for heart transplant and entered into the PHTS Registry with 9755 listed during the study period. The majority of listings occurred within the most recent era. Waitlist survival improved over the decades as did posttransplant survival. Other notable changes over time include fewer patients experiencing allograft rejection or infection after transplant. Waitlist and posttransplant survival have changed dramatically in patients with single ventricle physiology and significantly differ by stage of single ventricle palliation. SUMMARY: Key points from this PHTS Registry summary and focus on patients with single ventricle congenital heart disease in particular, include the changing landscape of candidates and recipients awaiting heart transplant. There is clear improvement in waitlist and transplant outcomes for children with both cardiomyopathy and congenital heart disease alike.

Omicron Infections in Vaccinated Pediatric Solid Organ Transplant Recipients.

SARS-CoV-2 infection during the Omicron period was frequent amongst a cohort of vaccinated pediatric solid organ transplant recipients (pSOTRs) despite robust anti-receptor-binding domain (anti-RBD) antibody response, suggesting poor neutralizing capacity against Omicron subvariants. Breakthrough infections among pSOTRs were overall limited in severity.

Research Gaps in Pediatric Heart Failure: Defining the Gaps and Then Closing Them Over the Next Decade.

Given the numerous opportunities and the wide knowledge gaps in pediatric heart failure, an international group of pediatric heart failure experts with diverse backgrounds were invited and tasked with identifying research gaps in each pediatric heart failure domain that scientists and funding agencies need to focus on over the next decade.

Changes in estimated glomerular filtration rate over the first year following repeat heart transplant in children and young adults.

BACKGROUND: Renal function is reduced in patients undergoing heart transplant due to hemodynamic compromise, cardiorenal syndrome, and nephrotoxin exposure. No current studies evaluate renal function in retransplants. METHODS: We reviewed all heart transplants at our center from 1995 to 2021 and matched first-time heart transplants with retransplants, based on age at transplant, sex, and race. Estimated glomerular filtration rate (eGFR) was derived from CKiD-U25 calculator using creatinine and measured prior to transplant, 1-week post-transplant, 1-3, 6, and 12 months post-transplant, and recent follow-up. Changes in eGFR were measured within and between patients using a piecewise linear mixed effect model with matching. Exploratory univariate analysis was performed to evaluate pre-transplant risk factors for decreased eGFR. RESULTS: The unmatched cohort included 393 heart transplant recipients, with 47 being retransplants. Thirty-eight patients in both groups with at least 1 year of follow-up underwent matching. Both retransplants and first-time transplants had an initial decline in eGFR. eGFR rebounded to baseline or above baseline at 1-3 months post-transplant, but eGFR in retransplants remained significantly lower. At 1-year post-transplant, the average eGFR was 67.8 ± 4.3 mL/min/1.73 m2 versus 104.7 ± 4.3 mL/min/1.73 m2 (p < .001) in the retransplants and first-time transplants group, respectively. CONCLUSION: This study provides data on anticipated renal trajectory following retransplantation.

Percutaneous Stenting of a Stenotic Berlin Heart Outflow Cannula Graft in a 2 Year Old Child.

Left ventricular assist device (LVAD) outflow obstruction is a rare complication of long-term LVAD support. We present the first case of successful percutaneous stent implantation in a pediatric patient with LVAD outflow obstruction.

Corrigendum: Tox21Enricher-Shiny: an R Shiny application for toxicity functional annotation analysis.

[This corrects the article DOI: 10.3389/ftox.2023.1147608.].

Widening care gap in VAD therapy.

BACKGROUND: The removal of the HeartWare ventricular assist device (HVAD) due to pump malfunctions and inferior outcomes compared to HeartMate 3 (HM3) in adults has created a care gap for younger patients. It is unclear if the reported HVAD survival differs by age and if the initial experience with HM3 can bridge the gap. METHODS: Using the Society of Thoracic Surgeons (STS) Intermacs and Pedimacs registries, durable ventricular assist device (VAD) implants between September 2012 and December 2021 were identified. Young adults (YA) were defined as <40 years old in Intermacs. Patients were excluded if they had an isolated right VAD (RVAD) or were implanted as destination therapy (DT). Survival analysis by Kaplan-Meier (KM) and competing outcomes curves was performed, and 1-year survival is reported. RESULTS: The Intermacs cohort consisted of YA (n = 1226; HVAD 818; HM3 408) with a median age of YA of 32.07 (26.66-36.27) years and weight (wt) of 83.2 (68-104.2) kg. Most had cardiomyopathy (CM) (92.2%). The Pedimacs cohort was 668 patients (median age 9.47 [1.82-14.23] years, wt 27.2 [10-57.05] kg), and most also had CM (70.5%). Device breakdown included HVAD (n = 326), Berlin EXCOR (n = 277), and HM3 (n = 65). HVAD survival differed by age in adults, with YA fairing better than adults >40 years old (88.8% vs 79.4% at 1 year, p < 0.0001). YA survival was also better compared to Pedimacs patient (88.9% vs 83.7%, p = 0.0002), but when competing events were analyzed, mortality was similar to YA (9.2% vs 9.6%, p = 0.1) with a higher proportion of patient undergoing transplant at 1 year in Pedimacs (74% vs 31.3%, p < 0.0001). Survival by device differed between HVAD and HM3 in YA (88.8% vs 94.4%, p = 0.0025). This difference in device survival was not seen in all children (83.7% vs 87.3%, p = 0.21), including those ≥25 kg. Adverse event profiles also differed across the groups with adults seeing less adverse events with the HM3, but the same was not found (including stroke) in the pediatric cohort. Survival outcomes for patients between 10 and 25 kg were similar with the HVAD compared to the Berlin Heart EXCOR (p = 0.4290), with similarities in stroke risk. CONCLUSION: The removal of the HVAD device may result in a care gap in younger patient whose survival outcomes do not mirror that of older adults. The HM3 can fill a portion of this gap with good survival, but there remains a subset of pediatric patients that, based on initial HM3 use, will no longer have access to intracorporeal support and therefore, despite reasonable outcomes with the Berlin Heart EXCOR, will not be able to be discharged home. Lastly, it is essential that future changes to the availability of devices take into account the various patient populations that utilize the device to avoid unintended consequences of access inequality.

Expanding use of the HeartMate 3 ventricular assist device in pediatric and adult patients within the Advanced Cardiac Therapies Improving Outcomes Network (ACTION).

BACKGROUND: We report current outcomes in patients supported with the HeartMate 3 (HM3) ventricular assist device in a multicenter learning network. METHODS: The Advanced Cardiac Therapies Improving Outcomes Network database was queried for HM3 implants between 12/2017 and 5/2022. Clinical characteristics, postimplant course, and adverse events were collected. Patients were stratified according to body surface area (BSA) (<1.4 m2, 1.4-1.8 m2, and >1.8 m2) at device implantation. RESULTS: During the study period, 170 patients were implanted with the HM3 at participating network centers, with median age 15.3years; 27.1% were female. Median BSA was 1.68 m2; the smallest patient was 0.73 m2 (17.7 kg). Most (71.8%) had a diagnosis of dilated cardiomyopathy. With a median support time of 102.5days, 61.2% underwent transplantation, 22.9% remained supported on device, 7.6% died, and 2.4% underwent device explantation for recovery; the remainder had transferred to another institution or transitioned to a different device type. The most common adverse events included major bleeding (20.8%) and driveline infection (12.9%); ischemic and hemorrhagic stroke were encountered in 6.5% and 1.2% of patients, respectively. Patients with BSA <1.4 m2 had a higher incidence of infection, renal dysfunction, and ischemic stroke. CONCLUSIONS: In this updated cohort of predominantly pediatric patients supported with the HM3 ventricular assist device, outcomes are excellent with <8% mortality on device. Device-related adverse events including stroke, infection, and renal dysfunction were more commonly seen in smaller patients, highlighting opportunities for improvements in care.

Tox21Enricher-Shiny: an R Shiny application for toxicity functional annotation analysis.

Inference of toxicological and mechanistic properties of untested chemicals through structural or biological similarity is a commonly employed approach for initial chemical characterization and hypothesis generation. We previously developed a web-based application, Tox21Enricher-Grails, on the Grails framework that identifies enriched biological/toxicological properties of chemical sets for the purpose of inferring properties of untested chemicals within the set. It was able to detect significantly overrepresented biological (e.g., receptor binding), toxicological (e.g., carcinogenicity), and chemical (e.g., toxicologically relevant chemical substructures) annotations within sets of chemicals screened in the Tox21 platform. Here, we present an R Shiny application version of Tox21Enricher-Grails, Tox21Enricher-Shiny, with more robust features and updated annotations. Tox21Enricher-Shiny allows users to interact with the web application component (available at http://hurlab.med.und.edu/Tox21Enricher/) through a user-friendly graphical user interface or to directly access the application's functions through an application programming interface. This version now supports InChI strings as input in addition to CASRN and SMILES identifiers. Input chemicals that contain certain reactive functional groups (nitrile, aldehyde, epoxide, and isocyanate groups) may react with proteins in cell-based Tox21 assays: this could cause Tox21Enricher-Shiny to produce spurious enrichment analysis results. Therefore, this version of the application can now automatically detect and ignore such problematic chemicals in a user's input. The application also offers new data visualizations, and the architecture has been greatly simplified to allow for simple deployment, version control, and porting. The application may be deployed onto a Posit Connect or Shiny server, and it uses Postgres for database management. As other Tox21-related tools are being migrated to the R Shiny platform, the development of Tox21Enricher-Shiny is a logical transition to use R's strong data analysis and visualization capacities and to provide aesthetic and developmental consistency with other Tox21 applications developed by the Division of Translational Toxicology (DTT) at the National Institute of Environmental Health Sciences (NIEHS).

Applying genomics in regulatory toxicology: a report of the ECETOC workshop on omics threshold on non-adversity.

In a joint effort involving scientists from academia, industry and regulatory agencies, ECETOC's activities in Omics have led to conceptual proposals for: (1) A framework that assures data quality for reporting and inclusion of Omics data in regulatory assessments; and (2) an approach to robustly quantify these data, prior to interpretation for regulatory use. In continuation of these activities this workshop explored and identified areas of need to facilitate robust interpretation of such data in the context of deriving points of departure (POD) for risk assessment and determining an adverse change from normal variation. ECETOC was amongst the first to systematically explore the application of Omics methods, now incorporated into the group of methods known as New Approach Methodologies (NAMs), to regulatory toxicology. This support has been in the form of both projects (primarily with CEFIC/LRI) and workshops. Outputs have led to projects included in the workplan of the Extended Advisory Group on Molecular Screening and Toxicogenomics (EAGMST) group of the Organisation for Economic Co-operation and Development (OECD) and to the drafting of OECD Guidance Documents for Omics data reporting, with potentially more to follow on data transformation and interpretation. The current workshop was the last in a series of technical methods development workshops, with a sub-focus on the derivation of a POD from Omics data. Workshop presentations demonstrated that Omics data developed within robust frameworks for both scientific data generation and analysis can be used to derive a POD. The issue of noise in the data was discussed as an important consideration for identifying robust Omics changes and deriving a POD. Such variability or "noise" can comprise technical or biological variation within a dataset and should clearly be distinguished from homeostatic responses. Adverse outcome pathways (AOPs) were considered a useful framework on which to assemble Omics methods, and a number of case examples were presented in illustration of this point. What is apparent is that high dimension data will always be subject to varying processing pipelines and hence interpretation, depending on the context they are used in. Yet, they can provide valuable input for regulatory toxicology, with the pre-condition being robust methods for the collection and processing of data together with a comprehensive description how the data were interpreted, and conclusions reached.

Vaccination-Associated Myocarditis and Myocardial Injury.

SARS-CoV-2 vaccine-associated myocarditis/myocardial injury should be evaluated in the contexts of COVID-19 infection, other types of viral myocarditis, and other vaccine-associated cardiac disorders. COVID-19 vaccine-associated myocardial injury can be caused by an inflammatory immune cell infiltrate, but other etiologies such as microvascular thrombosis are also possible. The clinical diagnosis is typically based on symptoms and cardiac magnetic resonance imaging. Endomyocardial biopsy is confirmatory for myocarditis, but may not show an inflammatory infiltrate because of rapid resolution or a non-inflammatory etiology. Myocarditis associated with SARS-COVID-19 vaccines occurs primarily with mRNA platform vaccines, which are also the most effective. In persons aged >16 or >12 years the myocarditis estimated crude incidences after the first 2 doses of BNT162b2 and mRNA-1273 are approximately 1.9 and 3.5 per 100 000 individuals, respectively. These rates equate to excess incidences above control populations of approximately 1.2 (BNT162b2) and 1.9 (mRNA-1273) per 100 000 persons, which are lower than the myocarditis rate for smallpox but higher than that for influenza vaccines. In the studies that have included mRNA vaccine and SARS-COVID-19 myocarditis measured by the same methodology, the incidence rate was increased by 3.5-fold over control in COVID-19 compared with 1.5-fold for BNT162b2 and 6.2-fold for mRNA-1273. However, mortality and major morbidity are less and recovery is faster with mRNA vaccine-associated myocarditis compared to COVID-19 infection. The reasons for this include vaccine-associated myocarditis having a higher incidence in young adults and adolescents, typically no involvement of other organs in vaccine-associated myocarditis, and based on comparisons to non-COVID viral myocarditis an inherently more benign clinical course.

Considerations for application of benchmark dose modeling in radiation research: workshop highlights.

BACKGROUND: Exposure to different forms of ionizing radiation occurs in diverse occupational, medical, and environmental settings. Improving the accuracy of the estimated health risks associated with exposure is therefore, essential for protecting the public, particularly as it relates to chronic low dose exposures. A key aspect to understanding health risks is precise and accurate modeling of the dose-response relationship. Toward this vision, benchmark dose (BMD) modeling may be a suitable approach for consideration in the radiation field. BMD modeling is already extensively used for chemical hazard assessments and is considered statistically preferable to identifying low and no observed adverse effects levels. BMD modeling involves fitting mathematical models to dose-response data for a relevant biological endpoint and identifying a point of departure (the BMD, or its lower bound). Recent examples in chemical toxicology show that when applied to molecular endpoints (e.g. genotoxic and transcriptional endpoints), BMDs correlate to points of departure for more apical endpoints such as phenotypic changes (e.g. adverse effects) of interest to regulatory decisions. This use of BMD modeling may be valuable to explore in the radiation field, specifically in combination with adverse outcome pathways, and may facilitate better interpretation of relevant in vivo and in vitro dose-response data. To advance this application, a workshop was organized on June 3rd, 2022, in Ottawa, Ontario that brought together BMD experts in chemical toxicology and the radiation scientific community of researchers, regulators, and policy-makers. The workshop's objective was to introduce radiation scientists to BMD modeling and its practical application using case examples from the chemical toxicity field and demonstrate the BMDExpress software using a radiation dataset. Discussions focused on the BMD approach, the importance of experimental design, regulatory applications, its use in supporting the development of adverse outcome pathways, and specific radiation-relevant examples. CONCLUSIONS: Although further deliberations are needed to advance the use of BMD modeling in the radiation field, these initial discussions and partnerships highlight some key steps to guide future undertakings related to new experimental work.