Forum on immune digital twins: a meeting report

Medical digital twins are computational models of human biology relevant to a given medical condition, which can be tailored to an individual patient, thereby predicting the course of disease and individualized treatments, an important goal of personalized medicine. The immune system, which has a central role in many diseases, is highly heterogeneous between individuals, and thus poses a major challenge for this technology. If medical digital twins are to faithfully capture the characteristics of a patient's immune system, we need to answer many questions, such as: What do we need to know about the immune system to build mathematical models that reflect features of an individual? What data do we need to collect across the different scales of immune system action? What are the right modeling paradigms to properly capture immune system complexity? In February 2023, an international group of experts convened in Lake Nona, FL for two days to discuss these and other questions related to digital twins of the immune system. The group consisted of clinicians, immunologists, biologists, and mathematical modelers, representative of the interdisciplinary nature of medical digital twin development. A video recording of the entire event is available. This paper presents a synopsis of the discussions, brief descriptions of ongoing digital twin projects at different stages of progress. It also proposes a 5-year action plan for further developing this technology. The main recommendations are to identify and pursue a small number of promising use cases, to develop stimulation-specific assays of immune function in a clinical setting, and to develop a database of existing computational immune models, as well as advanced modeling technology and infrastructure

Introduction of an agent-based multi-scale modular architecture for dynamic knowledge representation of acute inflammation

<p>Abstract</p> <p>Background</p> <p>One of the greatest challenges facing biomedical research is the integration and sharing of vast amounts of information, not only for individual researchers, but also for the community at large. Agent Based Modeling (ABM) can provide a means of addressing this challenge via a unifying translational architecture for dynamic knowledge representation. This paper presents a series of linked ABMs representing multiple levels of biological organization. They are intended to translate the knowledge derived from in vitro models of acute inflammation to clinically relevant phenomenon such as multiple organ failure.</p> <p>Results and Discussion</p> <p>ABM development followed a sequence starting with relatively direct translation from in-vitro derived rules into a cell-as-agent level ABM, leading on to concatenated ABMs into multi-tissue models, eventually resulting in topologically linked aggregate multi-tissue ABMs modeling organ-organ crosstalk. As an underlying design principle organs were considered to be functionally composed of an epithelial surface, which determined organ integrity, and an endothelial/blood interface, representing the reaction surface for the initiation and propagation of inflammation. The development of the epithelial ABM derived from an in-vitro model of gut epithelial permeability is described. Next, the epithelial ABM was concatenated with the endothelial/inflammatory cell ABM to produce an organ model of the gut. This model was validated against in-vivo models of the inflammatory response of the gut to ischemia. Finally, the gut ABM was linked to a similarly constructed pulmonary ABM to simulate the gut-pulmonary axis in the pathogenesis of multiple organ failure. The behavior of this model was validated against in-vivo and clinical observations on the cross-talk between these two organ systems</p> <p>Conclusion</p> <p>A series of ABMs are presented extending from the level of intracellular mechanism to clinically observed behavior in the intensive care setting. The ABMs all utilize cell-level agents that encapsulate specific mechanistic knowledge extracted from in vitro experiments. The execution of the ABMs results in a dynamic representation of the multi-scale conceptual models derived from those experiments. These models represent a qualitative means of integrating basic scientific information on acute inflammation in a multi-scale, modular architecture as a means of conceptual model verification that can potentially be used to concatenate, communicate and advance community-wide knowledge.</p

Ataluren use in patients with nonsense mutation Duchenne muscular dystrophy: patient demographics and characteristics from the STRIDE Registry

AIM: Strategic Targeting of Registries and International Database of Excellence (STRIDE) is an ongoing, multicenter registry providing real-world evidence regarding ataluren use in patients with nonsense mutation Duchenne muscular dystrophy (DMD) in clinical practice (NCT02369731). Here, we describe the initial demographic characteristics of the registry population. PATIENTS & METHODS: Patients will be followed up from enrollment for ≥5 years or until study withdrawal. RESULTS & CONCLUSION: As of 9 July 2018, 213 DMD boys were enrolled from 11 countries. Mean (standard deviation) ages at first symptoms and at study treatment start were 2.7 (1.7) years and 9.8 (3.7) years, respectively. Corticosteroids were used by 190 patients (89.2%) before data cut-off. Mean (standard deviation) ataluren exposure was 639.0 (362.9) days. Six patients withdrew. STRIDE is the first drug registry for patients with DMD and represents the largest real-world registry of patients with nmDMD to date

Structural characteristics and antiviral activity of multiple peptides derived from MDV glycoproteins B and H

<p>Abstract</p> <p>Background</p> <p>Marek's disease virus (MDV), which is widely considered to be a natural model of virus-induced lymphoma, has the potential to cause tremendous losses in the poultry industry. To investigate the structural basis of MDV membrane fusion and to identify new viral targets for inhibition, we examined the domains of the MDV glycoproteins gH and gB.</p> <p>Results</p> <p>Four peptides derived from the MDV glycoprotein gH (gHH1, gHH2, gHH3, and gHH5) and one peptide derived from gB (gBH1) could efficiently inhibit plaque formation in primary chicken embryo fibroblast cells (CEFs) with 50% inhibitory concentrations (IC₅₀) of below 12 μM. These peptides were also significantly able to reduce lesion formation on chorioallantoic membranes (CAMs) of infected chicken embryos at a concentration of 0.5 mM in 60 μl of solution. The HR2 peptide from Newcastle disease virus (NDVHR2) exerted effects on MDV specifically at the stage of virus entry (i.e., in a cell pre-treatment assay and an embryo co-treatment assay), suggesting cross-inhibitory effects of NDV HR2 on MDV infection. None of the peptides exhibited cytotoxic effects at the concentrations tested. Structural characteristics of the five peptides were examined further.</p> <p>Conclusions</p> <p>The five MDV-derived peptides demonstrated potent antiviral activity, not only in plaque formation assays in vitro, but also in lesion formation assays in vivo. The present study examining the antiviral activity of these MDV peptides, which are useful as small-molecule antiviral inhibitors, provides information about the MDV entry mechanism.</p

Can incontinence be cured? A systematic review of cure rates

Background Incontinence constitutes a major health problem affecting millions of people worldwide. The present study aims to assess cure rates from treating urinary (UI) or fecal incontinence (FI) and the number of people who may remain dependent on containment strategies. Methods Medline, Embase, PsycINFO, Cochrane Central Register of Controlled Trials (CENTRAL), CINAHL, and PEDro were searched from January 2005 to June 2015. Supplementary searches included conference abstracts and trials registers (2013–2015). Included studies had patients ≥ 18 years with UI or FI, reported treatment cure or success rates, had ≥ 50 patients treated with any intervention recognized in international guideline algorithms, a follow-up ≥ 3 months, and were published from 2005 onwards. Title and abstract screening, full paper screening, data extraction and risk-of-bias assessment were performed independently by two reviewers. Disagreements were resolved through discussion or referral to a third reviewer where necessary. A narrative summary of included studies is presented. Results Most evidence was found for UI: Surgical interventions for stress UI showed a median cure rate of 82.3% (interquartile range (IQR), 72–89.5%); people with urgency UI were mostly treated using medications (median cure rate for antimuscarinics = 49%; IQR, 35.6–58%). Pelvic floor muscle training and bulking agents showed lower cure rates for UI. Sacral neuromodulation for FI had a median cure rate of 38.6% (IQR, 35.6–40.6%). Conclusions Many individuals were not cured and hence may continue to rely on containment. No studies were found assessing success of containment strategies. There was a lack of data in the disabled and in those with neurological diseases, in the elderly and those with cognitive impairment. Surgical interventions were effective for stress UI. Other interventions for UI and FI showed lower cure rates. Many individuals are likely to be reliant on containment strategies

Tuneable resolution as a systems biology approach for multi-scale, multi-compartment computational models

The use of multi-scale mathematical and computational models to study complex biological processes is becoming increasingly productive. Multi-scale models span a range of spatial and/or temporal scales and can encompass multi-compartment (e.g., multi-organ) models. Modeling advances are enabling virtual experiments to explore and answer questions that are problematic to address in the wet-lab. Wet-lab experimental technologies now allow scientists to observe, measure, record, and analyze experiments focusing on different system aspects at a variety of biological scales. We need the technical ability to mirror that same flexibility in virtual experiments using multi-scale models. Here we present a new approach, tuneable resolution, which can begin providing that flexibility. Tuneable resolution involves fine- or coarse-graining existing multi-scale models at the user's discretion, allowing adjustment of the level of resolution specific to a question, an experiment, or a scale of interest. Tuneable resolution expands options for revising and validating mechanistic multi-scale models, can extend the longevity of multi-scale models, and may increase computational efficiency. The tuneable resolution approach can be applied to many model types, including differential equation, agent-based, and hybrid models. We demonstrate our tuneable resolution ideas with examples relevant to infectious disease modeling, illustrating key principles at work. WIREs Syst Biol Med 2014, 6:225–245. doi:10.1002/wsbm.1270 How to cite this article: WIREs Syst Biol Med 2014, 6:289–309. doi:10.1002/wsbm.127

Insulin Degrading Enzyme Induces a Conformational Change in Varicella-Zoster Virus gE, and Enhances Virus Infectivity and Stability

Varicella-zoster virus (VZV) glycoprotein E (gE) is essential for virus infectivity and binds to a cellular receptor, insulin-degrading enzyme (IDE), through its unique amino terminal extracellular domain. Previous work has shown IDE plays an important role in VZV infection and virus cell-to-cell spread, which is the sole route for VZV spread in vitro. Here we report that a recombinant soluble IDE (rIDE) enhances VZV infectivity at an early step of infection associated with an increase in virus internalization, and increases cell-to-cell spread. VZV mutants lacking the IDE binding domain of gE were impaired for syncytia formation and membrane fusion. Pre-treatment of cell-free VZV with rIDE markedly enhanced the stability of the virus over a range of conditions. rIDE interacted with gE to elicit a conformational change in gE and rendered it more susceptible to proteolysis. Co-incubation of rIDE with gE modified the size of gE. We propose that the conformational change in gE elicited by IDE enhances infectivity and stability of the virus and leads to increased fusogenicity during VZV infection. The ability of rIDE to enhance infectivity of cell-free VZV over a wide range of incubation times and temperatures suggests that rIDE may be useful for increasing the stability of varicella or zoster vaccines

SNi from SN2: a front-face mechanism ‘synthase’ engineered from a retaining hydrolase

SNi or SNi-like mechanisms, in which leaving group departure and nucleophile approach occur on the same ‘front’ face, have been observed previously experimentally and computationally in both the chemical and enzymatic (glycosyltransferase) substitution reactions of α-glycosyl electrophiles. Given the availability of often energetically comparable competing pathways for substitution (SNi vs SN1 vs SN2) the precise modulation of this archetypal reaction type should be feasible. Here, we show that the drastic engineering of a protein that catalyzes substitution, a retaining β-glycosidase (from Sulfolobus solfataricus SSβG), apparently changes the mode of reaction from “SN2” to “SNi”. Destruction of the nucleophilic Glu387 of SSβG-WT through Glu387Tyr mutation (E387Y) created a catalyst (SSβG-E387Y) with lowered but clear transglycosylation substitution activity with activated substrates, altered substrate and reaction preferences and hence useful synthetic (‘synthase’) utility by virtue of its low hydrolytic activity with unactivated substrates. Strikingly, the catalyst still displayed retaining β stereoselectivity, despite lacking a suitable nucleophile; pH-activity profile, mechanism-based inactivators and mutational analyses suggest that SSβG-E387Y operates without either the use of nucleophile or general acid/base residues, consistent with a SNi or SNi-like mechanism. An x-ray structure of SSβG-E387Y and subsequent metadynamics simulation suggest recruitment of substrates aided by a π-sugar interaction with the introduced Tyr387 and reveal a QM/MM free energy landscape for the substitution reaction catalyzed by this unnatural enzyme similar to those of known natural, SNi-like glycosyltransferase (GT) enzymes. Proton flight from the putative hydroxyl nucleophile to the developing p-nitrophenoxide leaving group of the substituted molecule in the reactant complex creates a hydrogen bond that appears to crucially facilitate the mechanism, mimicking the natural mechanism of SNi-GTs. An oxocarbenium ion-pair minimum along the reaction pathway suggests a step-wise SNi-like DN*ANss rather than a concerted SNi DNAN mechanism. This first observation of a front face mechanism in a β-retaining glycosyl transfer enzyme highlights, not only that unusual SNi reaction pathways may be accessed through direct engineering of catalysts with suitable environments, but also suggests that ‘β-SNi’ reactions are also feasible for glycosyl transfer enzymes and the more widespread existence of SNi or SNi-like mechanism in nature

Systematic NMR Analysis of Stable Isotope Labeled Metabolite Mixtures in Plant and Animal Systems: Coarse Grained Views of Metabolic Pathways

BACKGROUND: Metabolic phenotyping has become an important 'bird's-eye-view' technology which can be applied to higher organisms, such as model plant and animal systems in the post-genomics and proteomics era. Although genotyping technology has expanded greatly over the past decade, metabolic phenotyping has languished due to the difficulty of 'top-down' chemical analyses. Here, we describe a systematic NMR methodology for stable isotope-labeling and analysis of metabolite mixtures in plant and animal systems. METHODOLOGY/PRINCIPAL FINDINGS: The analysis method includes a stable isotope labeling technique for use in living organisms; a systematic method for simultaneously identifying a large number of metabolites by using a newly developed HSQC-based metabolite chemical shift database combined with heteronuclear multidimensional NMR spectroscopy; Principal Components Analysis; and a visualization method using a coarse-grained overview of the metabolic system. The database contains more than 1000 (1)H and (13)C chemical shifts corresponding to 142 metabolites measured under identical physicochemical conditions. Using the stable isotope labeling technique in Arabidopsis T87 cultured cells and Bombyx mori, we systematically detected >450 HSQC peaks in each (13)C-HSQC spectrum derived from model plant, Arabidopsis T87 cultured cells and the invertebrate animal model Bombyx mori. Furthermore, for the first time, efficient (13)C labeling has allowed reliable signal assignment using analytical separation techniques such as 3D HCCH-COSY spectra in higher organism extracts. CONCLUSIONS/SIGNIFICANCE: Overall physiological changes could be detected and categorized in relation to a critical developmental phase change in B. mori by coarse-grained representations in which the organization of metabolic pathways related to a specific developmental phase was visualized on the basis of constituent changes of 56 identified metabolites. Based on the observed intensities of (13)C atoms of given metabolites on development-dependent changes in the 56 identified (13)C-HSQC signals, we have determined the changes in metabolic networks that are associated with energy and nitrogen metabolism

The role of leadership in salespeople’s price negotiation behavior

Salespeople assume a key role in defending firms’ price levels in price negotiations with customers. The degree to which salespeople defend prices should critically depend upon their leaders’ influence. However, the influence of leadership on salespeople’s price defense behavior is barely understood, conceptually or empirically. Therefore, building on social learning theory, the authors propose that salespeople might adopt their leaders’ price defense behavior given a transformational leadership style. Furthermore, drawing on the contingency leadership perspective, the authors argue that this adoption fundamentally depends on three variables deduced from the motivation–ability–opportunity (MAO) framework, that is, salespeople’s learning motivation, negotiation efficacy, and perceived customer lenience. Results of a multi-level model using data from 92 salespeople and 264 salesperson–customer interactions confirm these predictions. The first to explore contingencies of salespeople’s adoption of their transformational leaders’ price negotiation behaviors, this study extends marketing theory and provides actionable guidance to practitioners