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McNamara, R.

Publications and source records attributed to McNamara, R..

7 recordsLinked to original sources

Thermodynamic phase-field modelling predicts non-linear evolution of tumour spheroid dynamics

Patient-derived tumour spheroids provide experimentally tractable models of tumour growth and treatment response, but standard radius-based measurements do not directly identify the tissue-scale mechanisms that shape internal structure. This study develops and calibrates a thermodynamic continuum model of untreated spheroid internal structural growth, in which viable and necrotic cell populations, nutrient transport, mechanical relaxation, and cell-fate transitions are represented as coupled spatial fields. Because the model does not prescribe internal concentric spheroid compartments like traditional spheroid models, the experimentally reported intermediate (inhibited) radius was treated as an exploratory model-to-data mapping and optimised over different candidate field-derived radii. The calibrated model reproduced the experimental trajectories with aggregate uncertainty-weighted root-mean-square error (WRMSE) values ranging from 0.49 to 1.24 on the metric defined in the manuscript, and improved average fit quality by approximately 40% relative to an existing Greenspan-type compartment model. The model recovered the growth-inhibited and necrotic structure observed in spheroids as an emergent consequence of spatial cell-state dynamics rather than prescribing concentric compartments. Biological and nutrient-associated model parameters were locally constrained to the experimental data, although compensatory relationships were observed among nutrient-response and death parameters. The framework was further extended by introducing a drug transport field as a proof-of-concept demonstration of spatial treatment-response modelling. These results show that a continuum cell-growth model can recover classical spheroid structure while preserving flexibility for exploratory field-based analysis of drug response.

bioengineering↗

Distinct antibody-based signatures and functionality distinguish latent and active pediatric tuberculosis

BackgroundTuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb), is among the leading causes of death from an infectious agent among children worldwide. Children represent a particularly vulnerable population due to the greater challenges in diagnosis and the higher risk of progression to severe forms of the disease. However, whether different pediatric outcomes relate to distinct immunologic responses remains incompletely understood. Emerging data suggest that Mtb-specific humoral immune responses represent a correlate of protection against Mtb both following natural infection and vaccination. MethodsTo determine if immune profiles can distinguish children across the spectrum from Mtb infection to TB disease, as well as children with TB from non-TB lower respiratory tract infection, we mapped the humoral immune response across a panel of 4 dozen Mtb antigens across children presenting with symptoms of active TB (ATB), children with evidence of latent TB infection (LTBI) and children exhibiting non-TB lower respiratory tract infection (non-TB LRTI). Using a custom Luminex assay, Mtb-specific antibody subclass/isotype, Fc receptor (FcR) binding profiles, and functions were profiled across the pediatric groups. FindingsA robust humoral immune response was observed in children with active TB compared to non-TB LRTI, marked by a strong IgA response, that exhibited high FcR binding. Conversely, children with LTBI uniquely elicited Mtb-specific antibodies with enhanced opsinophagocytic Fc{gamma}R2A binding, as well as a higher capacity to activate NK cells and neutrophils. InterpretationThere are significant differences in humoral immune profiles across the landscape of pediatric TB, potentially contributing to differential mycobacterial control, and highlighting biomarkers that could guide both diagnostic and therapeutic approaches. FundingUS National Institutes of Health.

immunology↗

Acute infectious mononucleosis generates persistent, functional EBNA-1 antibodies with high cross-reactivity to alpha crystalline beta

Epstein-Barr Virus (EBV) infects over 95% of the worlds population and is the most common cause of infectious mononucleosis (IM). Epidemiologic studies have linked EBV with certain cancers or autoimmune conditions, including multiple sclerosis (MS). Recent studies suggest that molecular mimicry between EBV proteins, particularly EBV nuclear antigen 1 (EBNA-1), and self-proteins is a plausible mechanism through which EBV infection may contribute to the development of autoimmune disorders. We used a systems immunology approach to investigate the magnitude, specificity, and functional properties of EBNA-1 specific antibodies in a cohort of 97 young adults with IM from presentation through 1-year post-primary infection compared to a control cohort of EBV-seropositive individuals. Levels of EBNA-1 specific IgG1 and IgG3 binding antibodies increased over the course of infection. EBNA-1 antibodies capable of mediating antibody-dependent cellular phagocytosis (ADCP) and antibody-dependent complement deposition (ADCD) were detected at or after 6 months. Binding and ADCP- and ADCD-leveraged antibodies primarily targeted a region of EBNA-1 known to elicit cross-reactive antibodies to several self-peptides in individuals with MS. Significantly higher binding and ADCD-active antibodies targeting EBNA-1 were observed in individuals with at least one HLA-DRB1*15:01 allele, a known genetic risk factor for MS; Importantly, high levels of antibodies capable of binding alpha crystalline beta (CRYAB) and mediating complement deposition were detected at 6 months and 1-year following IM; CRYAB antibodies were resistant to denaturing forces, indicating an affinity matured response. Blocking experiments confirmed that CRYAB antibodies were cross-reactive with EBNA-1. Altogether, these results demonstrate that high levels of functional antibodies targeting EBNA-1 are generated in early EBV infection, some of which are cross-reactive with CRYAB. Further investigation is warranted to determine how these antibody responses may contribute to the subsequent development of MS.

immunology↗

Humoral correlates of protection against Mycobacterium tuberculosis following intravenous Bacille Calmette-Guerin vaccination in rhesus macaques

Altering the route of Bacille Calmette-Guerin (BCG) immunization from low-dose intradermal vaccination to high-dose intravenous (IV) vaccination resulted in a high level of protection against Mycobacterium tuberculosis (Mtb) infection, providing an opportunity to uncover immune correlates and mechanisms of protection. In addition to strong T cell immunity, IV BCG vaccination was associated with a robust expansion of humoral immune responses that tracked with bacterial control. However, given the near complete protection afforded by high-dose IV BCG immunization, a precise correlate of immune protection was difficult to define. Here we leveraged plasma and bronchoalveolar lavage fluid (BAL) from a cohort of rhesus macaques that received decreasing doses of IV BCG and aimed to define the correlates of immunity across macaques that experienced immune protection or breakthrough infection following Mtb challenge. We show an IV BCG dose-dependent induction of mycobacterial-specific humoral immune responses, both in the plasma and in the airways. Moreover, antibody responses at peak immunogenicity significantly predicted bacterial control following challenge. Multivariate analyses revealed antibody-mediated complement and NK cell activating humoral networks as key functional signatures associated with protective immunity. Collectively, this work extends our understanding of humoral biomarkers and potential mechanisms of IV BCG mediated protection against Mtb.

immunology↗

Anamnestic Humoral Correlates of Immunity Across SARS-CoV-2 Variants of Concern

While immune correlates against SARS-CoV-2 are typically defined at peak immunogenicity following vaccination, immunologic responses that expand selectively during the anamnestic response following infection can provide mechanistic and detailed insights into the immune mechanisms of protection. Moreover, whether anamnestic correlates are conserved across VoCs, including the Delta and more distant Omicron variant of concern (VoC), remains unclear. To define the anamnestic correlates of immunity, across VOCs, we deeply profiled the humoral immune response in individuals recently infected with either the Delta or Omicron VoC. While limited acute N-terminal domain and RBD-specific immune expansion was observed following breakthrough, a significant immunodominant expansion of opsinophagocytic Spike-specific antibody responses focused largely on the conserved S2-domain of SARS-CoV-2 was observed 1 week after breakthrough infection. This S2-specific functional humoral response continued to evolve over 2-3 weeks following both Delta and Omicron breakthrough infection, targeting multiple VoCs and common coronaviruses. These responses were focused largely on the fusion peptide 2 and heptad repeat 1, both associated with enhanced rates of viral clearance. Taken together, our results point to a critical role of highly conserved, functional S2-specific responses in the control of SARS-CoV-2 infection, across VOCs, and thus humoral response linked to virus attenuation can guide next-generation generation vaccine boosting approaches to confer broad protection against future SARS-CoV-2 VoCs.

immunology↗

Nonlytic cellular release of hepatitis A virus requires dual capsid recruitment of the ESCRT-associated Bro1 domain proteins HD-PTP and ALIX

Although picornaviruses are conventionally considered nonenveloped, members of multiple picornaviral genera are released nonlytically from infected cells in extracellular vesicles. The mechanisms underlying this process are poorly understood. Here, we describe interactions of the hepatitis A virus (HAV) capsid with components of host endosomal sorting complexes required for transport (ESCRT) that play an essential role in release. We show release of quasi-enveloped virus (eHAV) in exosome-like vesicles requires a conserved export signal located within the 8 kDa C-terminal VP1 pX extension that functions in a manner analogous to late domains of canonical enveloped viruses. Fusing pX to a self-assembling engineered protein nanocage (EPN-pX) resulted in its ESCRT-dependent release in extracellular vesicles. Mutational analysis identified a 24 amino acid peptide sequence located within the center of pX that was both necessary and sufficient for nanocage release. Deleting a YxxL motif within this sequence ablated eHAV release, resulting in virus accumulating intracellularly. The pX export signal is conserved in non-human hepatoviruses from a wide range of mammalian species, and functional in pX sequences from bat hepatoviruses when fused to the nanocage protein, suggesting these viruses are released as quasi-enveloped virions. Quantitative proteomics identified multiple ESCRT-related proteins associating with EPN-pX, including ALG2-interacting protein X (ALIX), and its paralog, tyrosine-protein phosphatase non-receptor type 23 (HD-PTP), a second Bro1 domain protein linked to sorting of ubiquitylated cargo into multivesicular endosomes. RNAi-mediated depletion of either Bro1 domain protein impeded eHAV release. Super-resolution fluorescence microscopy demonstrated colocalization of viral capsids with endogenous ALIX and HD-PTP. Co-immunoprecipitation assays using biotin-tagged peptides and recombinant proteins revealed pX interacts directly through the export signal with N-terminal Bro1 domains of both HD-PTP and ALIX. Our study identifies an exceptionally potent viral export signal mediating extracellular release of virus-sized protein assemblies and shows release requires non-redundant activities of both HD-PTP and ALIX. Authors SummaryMechanisms underlying nonlytic release of canonical nonenveloped viruses from infected cells are poorly understood. We show here that release of hepatitis A virus from cells in exosome-like vesicles requires nonredundant activities of two distinct Bro1-domain proteins associated with host cell machinery (ESCRT) for endosomal sorting, HD-PTP and ALIX. We demonstrate both Bro1 domain proteins are recruited to the viral capsid by the pX segment of the 1D capsid protein, and that they act in a non-redundant manner to mediate virus release. Fusing pX to a self-assembling nanocage protein resulted in ESCRT-dependent release mediated by a short pX peptide sequence conserved in hepatoviruses from bats to humans. Mutations within the pX sequence ablate release and result in noncytolytic virus accumulating intracellularly. Our study identifies an exceptionally potent viral export signal mediating extracellular release of virus-sized protein assemblies and shows nonlytic release of quasi-enveloped virus is an ancient evolutionary trait of hepatoviruses.

microbiology↗

Machine-learning to Improve Prediction of Mortality following Acute Myocardial Infarction: An Assessment in the NCDR-Chest Pain-Myocardial Infarction Registry

IntroductionAccurate prediction of risk of death following acute myocardial infarction (AMI) can guide the triage of care services and shared decision-making. Contemporary machine-learning may improve risk-prediction by identifying complex relationships between predictors and outcomes. Methods and ResultsWe studied 993,905 patients in the American College of Cardiology Chest Pain-MI Registry hospitalized with AMI (mean age 64 {+/-} 13 years, 34% women) between January 2011 and December 2016. We developed and validated three machine learning models to predict in-hospital mortality and compared the performance characteristics with a logistic regression model. In an independent validation cohort, we compared logistic regression with lasso regularization (c-statistic, 0.891 [95% CI, 0.890-0.892]), gradient descent boosting (c-statistic, 0.902 [0.901-0.903]), and meta-classification that combined gradient descent boosting with a neural network (c-statistic, 0.904 [0.903-0.905]) with traditional logistic regression (c-statistic, 0.882 [0.881-0.883]). There were improvements in classification of individuals across the spectrum of patient risk with each of the three methods; the meta-classifier model - our best performing model - reclassified 20.9% of individuals deemed high-risk for mortality in logistic regression appropriately as low-to-moderate risk, and 8.2% of deemed low-risk to moderate-to-high risk based consistent with the actual event rates. ConclusionsMachine-learning methods improved the prediction of in-hospital mortality for AMI compared with logistic regression. Machine learning methods enhance the utility of risk models developed using traditional statistical approaches through additional exploration of the relationship between variables and outcomes.

bioinformatics↗