Quantifying fungal growth underpins our ability to effectively treat severe fungal infections. Current methods quantify fungal growth rates from time-course morphology-specific data, such as hyphal ...length data. However, automated large-scale collection of such data lies beyond the scope of most clinical microbiology laboratories. In this paper, we propose a mathematical model of fungal growth to estimate morphology-specific growth rates from easy-to-collect, but indirect, optical density (OD600) data of Aspergillus fumigatus growth (filamentous fungus). Our method accounts for OD600 being an indirect measure by explicitly including the relationship between the indirect OD600 measurements and the calibrating true fungal growth in the model. Therefore, the method does not require de novo generation of calibration data. Our model outperformed reference models at fitting to and predicting OD600 growth curves and overcame observed discrepancies between morphology-specific rates inferred from OD600 versus directly measured data in reference models that did not include calibration.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Background
Several biologics for atopic dermatitis (AD) have demonstrated good efficacy in clinical trials, but with a substantial proportion of patients being identified as poor responders. This ...study aims to understand the pathophysiological backgrounds of patient variability in drug response, especially for dupilumab, and to identify promising drug targets in dupilumab poor responders.
Methods
We conducted model‐based meta‐analysis of recent clinical trials of AD biologics and developed a mathematical model that reproduces reported clinical efficacies for nine biological drugs (dupilumab, lebrikizumab, tralokinumab, secukinumab, fezakinumab, nemolizumab, tezepelumab, GBR 830, and recombinant interferon‐gamma) by describing system‐level AD pathogenesis. Using this model, we simulated the clinical efficacy of hypothetical therapies on virtual patients.
Results
Our model reproduced reported time courses of %improved EASI and EASI‐75 of the nine drugs. The global sensitivity analysis and model simulation indicated the baseline level of IL‐13 could stratify dupilumab good responders. Model simulation on the efficacies of hypothetical therapies revealed that simultaneous inhibition of IL‐13 and IL‐22 was effective, whereas application of the nine biologic drugs was ineffective, for dupilumab poor responders (EASI‐75 at 24 weeks: 21.6% vs. max. 1.9%).
Conclusion
Our model identified IL‐13 as a potential predictive biomarker to stratify dupilumab good responders, and simultaneous inhibition of IL‐13 and IL‐22 as a promising drug therapy for dupilumab poor responders. This model will serve as a computational platform for model‐informed drug development for precision medicine, as it allows evaluation of the effects of new potential drug targets and the mechanisms behind patient variability in drug response.
We developed a mathematical model that describes system‐level AD pathogenesis and reproduces reported clinical efficacies of published clinical trials for nine biological drugs. We simulated clinical efficacy of hypothetical therapies on virtual dupilumab poor responders. Simultaneous inhibition of IL‐13 and IL‐22 is the most effective among combinations of two cytokines, whereas inhibition of either IL‐13 or IL‐22 alone is ineffective. Abbreviations: AD, atopic dermatitis; EASI, Eczema Area and Severity Index; IFN‐γ, interferon‐gamma; IL, interleukin.
Atopic dermatitis (AD) is a prevalent disease worldwide and is associated with systemic comorbidities representing a significant burden on patients, their families, and society. Therapeutic options ...for AD remain limited, in part because of a lack of well-characterized animal models. There has been increasing interest in developing experimental approaches to study the pathogenesis of human AD in vivo, in vitro, and in silico to better define pathophysiologic mechanisms and identify novel therapeutic targets and biomarkers that predict therapeutic response. This review critically appraises a range of models, including genetic mutations relevant to AD, experimental challenge of human skin in vivo, tissue culture models, integration of “omics” data sets, and development of predictive computational models. Although no one individual model recapitulates the complex AD pathophysiology, our review highlights insights gained into key elements of cutaneous biology, molecular pathways, and therapeutic target identification through each approach. Recent developments in computational analysis, including application of machine learning and a systems approach to data integration and predictive modeling, highlight the applicability of these methods to AD subclassification (endotyping), therapy development, and precision medicine. Such predictive modeling will highlight knowledge gaps, further inform refinement of biological models, and support new experimental and systems approaches to AD.
The stratum corneum (SC) provides a permeability barrier that limits the inflow and outflow of water. The permeability barrier is continuously and dynamically formed, maintained, and degraded along ...the depth, from the bottom to the top, of the SC. Naturally, its functioning and structure also change dynamically in a depth-dependent manner. While transepidermal water loss is typically used to assess the function of the SC barrier, it fails to provide any information about the dynamic mechanisms that are responsible for the depth-dependent characteristics of the permeability barrier. This paper aims to quantitatively characterize the depth-dependency of the permeability barrier using in vivo non-invasive measurement data for understanding the underlying mechanisms for barrier formation, maintenance, and degradation. As a framework to combine existing experimental data, we propose a mathematical model of the SC, consisting of multiple compartments, to explicitly address and investigate the depth-dependency of the SC permeability barrier. Using this mathematical model, we derive a measure of the water permeability barrier, i.e. resistance to water diffusion in the SC, from the measurement data on transepidermal water loss and water concentration profiles measured non-invasively by Raman spectroscopy. The derived resistance profiles effectively characterize the depth-dependency of the permeability barrier, with three distinct regions corresponding to formation, maintenance, and degradation of the barrier. Quantitative characterization of the obtained resistance profiles allows us to compare and evaluate the permeability barrier of skin with different morphology and physiology (infants vs adults, different skin sites, before and after application of oils) and elucidates differences in underlying mechanisms of processing barriers. The resistance profiles were further used to predict the spatial-temporal effects of skin treatments by in silico experiments, in terms of spatial-temporal dynamics of percutaneous water penetration.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
The stratum corneum is the outermost skin layer with a vital role in skin barrier function. It is comprised of dead keratinocytes (corneocytes) and is known to maintain its thickness by shedding ...cells, although, the precise mechanisms that safeguard stratum corneum maturation and homeostasis remain unclear. Previous ex vivo studies have suggested a neutral-to-acidic pH gradient in the stratum corneum. Here, we use intravital pH imaging at single-corneocyte resolution to demonstrate that corneocytes actually undergo differentiation to develop three distinct zones in the stratum corneum, each with a distinct pH value. We identified a moderately acidic lower, an acidic middle, and a pH-neutral upper layer in the stratum corneum, with tight junctions playing a key role in their development. The upper pH neutral zone can adjust its pH according to the external environment and has a neutral pH under steady-state conditions owing to the influence of skin microbiota. The middle acidic pH zone provides a defensive barrier against pathogens. With mathematical modeling, we demonstrate the controlled protease activation of kallikrein-related peptidases on the stratum corneum surface that results in proper corneocyte shedding in desquamation. This work adds crucial information to our understanding of how stratum corneum homeostasis is maintained.
Background
The Patient‐Oriented Eczema Measure (POEM) is the recommended core outcome instrument for atopic dermatitis (AD) symptoms. POEM is reported by recalling the presence/absence of seven ...symptoms in the last 7 days.
Objective
To evaluate measurement errors in POEM recordings due to imperfect recall.
Methods
Using data from a clinical trial of 247 AD patients aged 12–65 years, we analysed the reported POEM score (r‐POEM) and the POEM derived from the corresponding daily scores for the same seven symptoms without weekly recall (d‐POEM). We quantified recall error by comparing the r‐POEM and d‐POEM for 777 patient‐weeks collected from 207 patients, and estimated two components of recall error: (1) recall bias due to systematic errors in measurements and (2) recall noise due to random errors in measurements, using a bespoke statistical model.
Results
POEM scores have a relatively low recall bias, but a high recall noise. Recall bias was estimated at 1.2 points lower for the r‐POEM on average than the d‐POEM, with a recall noise of 5.7 points. For example, a patient with a recall‐free POEM of 11 (moderate) could report their POEM score anywhere from 5 to 14 (with 95% probability) because of recall error. Model estimates suggested that patients tend to recall itch and dryness more often than experienced (positive bias of less than 1 day), but less often for the other symptoms (bleeding, cracking, flaking, oozing/weeping and sleep disturbance; negative bias ranging 1–4 days).
Conclusions
In this clinical trial data set, we found that patients tended to slightly underestimate their symptoms when reporting POEM, with significant variation in how well they were able to recall the frequency of their symptoms every time they reported POEM. A large recall noise should be taken into consideration when interpreting POEM scores.
The Patient‐Oriented Eczema Measure (POEM) is a recommended score to assess eczema symptoms from a patient's perspective with a weekly recall. Patients tended to slightly underestimate their symptoms when reporting POEM with significant recall noise. Recall errors should be considered when interpreting POEM scores. More research is needed to evaluate methods to reduce poor recall (such as aide‐memoirs).
A growing body of evidence links various biomarkers to atopic dermatitis (AD). Still, little is known about the association of specific biomarkers to disease characteristics and severity in AD.
To ...explore the relationship between various immunological markers in the serum and disease severity in a hospital cohort of AD patients.
Outpatients with AD referred to the Department of Dermatology, Bispebjerg Hospital, Copenhagen, Denmark, were divided into groups based on disease severity (SCORAD). Serum levels of a preselected panel of immunoinflammatory biomarkers were tested for association with disease characteristics. Two machine learning models were developed to predict SCORAD from the measured biomarkers.
A total of 160 patients with AD were included; 53 (33.1%) with mild, 73 (45.6%) with moderate, and 34 (21.3%) with severe disease. Mean age was 29.2 years (range 6-70 years) and 84 (52.5%) were females. Numerous biomarkers showed a statistically significant correlation with SCORAD, with the strongest correlations seen for CCL17/thymus and activation-regulated chemokine (chemokine ligand-17/TARC) and CCL27/cutaneous T cell-attracting-chemokine (CTACK; Spearman R of 0.50 and 0.43, respectively, p < 0.001). Extrinsic AD patients were more likely to have higher mean SCORAD (p < 0.001), CCL17 (p < 0.001), CCL26/eotaxin-3 (p < 0.001), and eosinophil count (p < 0.001) than intrinsic AD patients. Predictive models for SCORAD identified CCL17, CCL27, serum total IgE, IL-33, and IL-5 as the most important predictors for SCORAD, but with weaker associations than single cytokines.
Specific immunoinflammatory biomarkers in the serum, mainly of the Th2 pathway, are correlated with disease severity in patients with AD. Predictive models identified biomarkers associated with disease severity but this finding warrants further investigation.
In multicellular organisms, cells adopt various shapes, from flattened sheets of endothelium to dendritic neurons, that allow the cells to function effectively. Here, we elucidated the unique shape ...of cells in the cornified stratified epithelia of the mammalian epidermis that allows them to achieve homeostasis of the tight junction (TJ) barrier. Using intimate in vivo 3D imaging, we found that the basic shape of TJ-bearing cells is a flattened Kelvin's tetrakaidecahedron (f-TKD), an optimal shape for filling space. In vivo live imaging further elucidated the dynamic replacement of TJs on the edges of f-TKD cells that enables the TJ-bearing cells to translocate across the TJ barrier. We propose a spatiotemporal orchestration model of f-TKD cell turnover, where in the classic context of 'form follows function', cell shape provides a fundamental basis for the barrier homeostasis and physical strength of cornified stratified epithelia.
The skin barrier acts as the first line of defense against constant exposure to biological, microbial, physical, and chemical environmental stressors. Dynamic interplay between defects in the skin ...barrier, dysfunctional immune responses, and environmental stressors are major factors in the development of atopic dermatitis (AD). A systems biology modeling approach can yield significant insights into these complex and dynamic processes through integration of prior biological data.
We sought to develop a multiscale mathematical model of AD pathogenesis that describes the dynamic interplay between the skin barrier, environmental stress, and immune dysregulation and use it to achieve a coherent mechanistic understanding of the onset, progression, and prevention of AD.
We mathematically investigated synergistic effects of known genetic and environmental risk factors on the dynamic onset and progression of the AD phenotype, from a mostly asymptomatic mild phenotype to a severe treatment-resistant form.
Our model analysis identified a “double switch,” with 2 concatenated bistable switches, as a key network motif that dictates AD pathogenesis: the first switch is responsible for the reversible onset of inflammation, and the second switch is triggered by long-lasting or frequent activation of the first switch, causing irreversible onset of systemic TH2 sensitization and worsening of AD symptoms.
Our mathematical analysis of the bistable switch predicts that genetic risk factors decrease the threshold of environmental stressors to trigger systemic TH2 sensitization. This analysis predicts and explains 4 common clinical AD phenotypes from a mild and reversible phenotype through to severe and recalcitrant disease and provides a mechanistic explanation for clinically demonstrated preventive effects of emollient treatments against development of AD.
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•Bifurcations in a mathematical model of atopic dermatitis (AD) are analysed.•Bifurcations leading to qualitative changes in disease severity are identified.•Mechanism-based patient stratification ...for disease severity is proposed.•Synergistic effects of AD treatments with different schedules are investigated.•Patient-specific AD treatment strategies are proposed.
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Atopic dermatitis (AD) is a common inflammatory skin disease, whose incidence is currently increasing worldwide. AD has a complex etiology, involving genetic, environmental, immunological, and epidermal factors, and its pathogenic mechanisms have not yet been fully elucidated. Identification of AD risk factors and systematic understanding of their interactions are required for exploring effective prevention and treatment strategies for AD. We recently developed a mathematical model for AD pathogenesis to clarify mechanisms underlying AD onset and progression. This model describes a dynamic interplay between skin barrier, immune regulation, and environmental stress, and reproduced four types of dynamic behaviour typically observed in AD patients in response to environmental triggers. Here, we analyse bifurcations of the model to identify mathematical conditions for the system to demonstrate transitions between different types of dynamic behaviour that reflect respective severity of AD symptoms. By mathematically modelling effects of topical application of antibiotics, emollients, corticosteroids, and their combinations with different application schedules and doses, bifurcation analysis allows us to mathematically evaluate effects of the treatments on improving AD symptoms in terms of the patients’ dynamic behaviour. The mathematical method developed in this study can be used to explore and improve patient-specific personalised treatment strategies to control AD symptoms.
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