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Developing an accurate first-principle model is an important step in employing systems biology approaches to analyze an intracellular signaling pathway. However, an accurate first-principle model is difficult to be developed since it requires in-depth mechanistic understandings of the signaling pathway. Since underlying mechanisms such as the reaction network structure are not fully understood, significant discrepancy exists between predicted and actual signaling dynamics. Motivated by these considerations, this work proposes a hybrid modeling approach that combines a first-principle model and an artificial neural network (ANN) model so that predictions of the hybrid model surpass those of the original model. First, the proposed approach determines an optimal subset of model states whose dynamics should be corrected by the ANN by examining the correlation between each state and outputs through relative order. Second, an L2-regularized least-squares problem is solved to infer values of the correction terms that are necessary to minimize the discrepancy between the model predictions and available measurements. Third, an ANN is developed to generalize relationships between the values of the correction terms and the system dynamics. Lastly, the original first-principle model is coupled with the developed ANN to finalize the hybrid model development so that the model will possess generalized prediction capabilities while retaining the model interpretability. We have successfully validated the proposed methodology with two case studies, simplified apoptosis and lipopolysaccharide-induced NF κ B signaling pathways, to develop hybrid models with in silico and in vitro measurements, respectively.

In this study, we developed a facile gold nanozyme-based paper chip (AuNZ-PAD) for Hg 2+ detection. This device has the advantages of being simple, rapid, cost effective, sensitive, selective, high throughput, and applicable to onsite detection. The colorimetric mercury assay on the AuNZ-PAD is established based on the enzyme-like catalytic activity of gold nanoparticles promoted by the formation of Au–Hg amalgam, which is correlated to the intensity of the colorimetric response resulting from the catalytic reaction of 3,3′,5,5′-tetramethylbenzidine (TMB) and H 2 O 2 . Highly sensitive and selective detection of Hg 2+ ions is achieved in both distilled and tap water samples, indicating the feasibility and applicability of our device for the determination of mercury pollution in real samples. Moreover, AuNZ-PAD analysis using a smartphone camera eliminates the need for expensive analytical equipment, thereby increasing the practicality of field monitoring of trace Hg 2+ compared with other sensing methods.

In this study, we developed a new type of paper-based analytical device (PAD), the three-dimensional (3D) slip-PAD, to detect infectious human norovirus for global healthcare. The 3D configuration of the papers combined with a slip design provides unique features and versatility that overcome the limitations of fluidic manipulation and sensitivity in point-of-care (POC) tests. The assay can be carried out in a single step based on a moveable slip design, making it suitable for unskilled users. The 3D fluidic network developed by layered construction of wax-patterned papers provides different fluidic paths for the sequential delivery of multiple fluids without the need for peripheral equipment. The release and mixing of enhancement reagents on the device improved the sensitivity and detection limit. The assay results could be visualized by naked eye within 10 min, with subsequent amplification of the signal over time (<60 min). The device showed a broad dynamic range of detection and high sensitivity, with a detection limit of 9.5 × 10 4 copies ml −1 for human norovirus. These results demonstrate that the 3D slip-PAD is a sensitive diagnostic assay for detecting human norovirus infection that is particularly suitable for POC testing in regions where resources are scarce.

The growing demand for various types of paper highlights the importance of optimizing the kraft pulping process to achieve desired paper properties. This work proposes a novel multiscale model to optimize the kraft pulping process and obtain desired paper properties. The model combines mass and energy balance equations with a layered kinetic Monte Carlo (kMC) algorithm to predict the degradation of wood chips, the depolymerization of cellulose, and the spatio-temporal evolution of the Kappa number and cellulose degree of polymerization (DP). A surrogate LSTM-ANN model is trained on data generated from the multiscale model under different operating conditions, dealing with both time-varying and time-invariant inputs, and an LSTM-ANN-based model predictive controller is designed to achieve desired set-point values of the Kappa number and cellulose DP while considering process constraints. The results show that the LSTM-ANN-based controller is able to drive the process to desired set-point values with the use of a computationally faster surrogate model with high accuracy and low offset.

Background The multidimensional and dynamically complex process of ageing presents key challenges to economic evaluation of geriatric interventions, including: (1) accounting for indirect, long-term effects of a geriatric shock such as a fall; (2) incorporating a wide range of societal, non-health outcomes such as informal caregiver burden; and (3) accounting for heterogeneity within the demographic group. Measures of frailty aim to capture the multidimensional and syndromic nature of geriatric health. Using a case study of community-based falls prevention, this article explores how incorporating a multivariate frailty index in a decision model can help address the above key challenges. Methods A conceptual structure of the relationship between geriatric shocks and frailty was developed. This included three key associations involving frailty: (A) the shock-frailty feedback loop; (B) the secondary effects of shock via frailty; and (C) association between frailty and intervention access. A case study of economic modelling of community-based falls prevention for older persons aged 60 + was used to show how parameterising these associations contributed to addressing the above three challenges. The English Longitudinal Study of Ageing (ELSA) was the main data source for parameterisation. A new 52-item multivariate frailty index was generated from ELSA. The main statistical methods were multivariate logistic and linear regressions. Estimated regression coefficients were inputted into a discrete individual simulation with annual cycles to calculate the continuous variable value or probability of binary event given individuals’ characteristics. Results All three conceptual associations, in their parameterised forms, contributed to addressing challenge (1). Specifically, by worsening the frailty progression, falls incidence in the model increased the risk of falling in subsequent cycles and indirectly impacted the trajectories and levels of EQ-5D-3 L, mortality risk, and comorbidity care costs. Intervention access was positively associated with frailty such that the greater access to falls prevention by frailer individuals dampened the falls-frailty feedback loop. Association (B) concerning the secondary effects of falls via frailty was central to addressing challenge (2). Using this association, the model was able to estimate how falls prevention generated via its impact on frailty paid and unpaid productivity gains, out-of-pocket care expenditure reduction, and informal caregiving cost reduction. For challenge (3), frailty captured the variations within demographic groups of key model outcomes including EQ-5D-3 L, QALY, and all-cause care costs. Frailty itself was shown to have a social gradient such that it mediated socially inequitable distributions of frailty-associated outcomes. Conclusion The frailty-based conceptual structure and parameterisation methods significantly improved upon the methods previously employed by falls prevention models to address the key challenges for geriatric economic evaluation. The conceptual structure is applicable to other geriatric and non-geriatric intervention areas and should inform the data selection and statistical methods to parameterise structurally valid economic models of geriatric interventions.

A single glycan-lectin interaction is often weak and semi-specific. Multiple binding domains in a single lectin can bind with multiple glycan molecules simultaneously, making it difficult for the classic “lock-and-key” model to explain these interactions. We demonstrated that hetero-multivalency, a homo-oligomeric protein simultaneously binding to at least two types of ligands, influences LecA (a Pseudomonas aeruginosa adhesin)-glycolipid recognition. We also observed enhanced binding between P. aeruginosa and mixed glycolipid liposomes. Interestingly, strong ligands could activate weaker binding ligands leading to higher LecA binding capacity. This hetero-multivalency is probably mediated via a simple mechanism, Reduction of Dimensionality (RD). To understand the influence of RD, we also modeled LecA’s two-step binding process with membranes using a kinetic Monte Carlo simulation. The simulation identified the frequency of low-affinity ligand encounters with bound LecA and the bound LecA’s retention of the low-affinity ligand as essential parameters for triggering hetero-multivalent binding, agreeing with experimental observations. The hetero-multivalency can alter lectin binding properties, including avidities, capacities, and kinetics, and therefore, it likely occurs in various multivalent binding systems. Using hetero-multivalency concept, we also offered a new strategy to design high-affinity drug carriers for targeted drug delivery.

Slickwater hydraulic fracturing is becoming a prevalent approach to economically recovering shale hydrocarbon. It is very important to understand the proppant’s transport behavior during slickwater hydraulic fracturing treatment for effective creation of a desired propped fracture geometry. The currently available models are either oversimplified or have been performed at limited length scales to avoid high computational requirements. Another limitation is that the currently available hydraulic fracturing simulators are developed using only single-sized proppant particles. Motivated by this, in this work, a computationally efficient, three-dimensional, multiphase particle-in-cell (MP-PIC) model was employed to simulate the multi-size proppant transport in a field-scale geometry using the Eulerian–Lagrangian framework. Instead of tracking each particle, groups of particles (called parcels) are tracked, which allows one to simulate the proppant transport in field-scale geometries at an affordable computational cost. Then, we found from our sensitivity study that pumping schedules significantly affect propped fracture surface area and average fracture conductivity, thereby influencing shale gas production. Motivated by these results, we propose an optimization framework using the MP-PIC model to design the multi-size proppant pumping schedule that maximizes shale gas production from unconventional reservoirs for given fracturing resources.

Background Falls significantly harm geriatric health and impose substantial costs on care systems and wider society. Decision modelling can inform the commissioning of falls prevention but face methodological challenges, including: (1) capturing non-health outcomes and societal intervention costs; (2) considering heterogeneity and dynamic complexity; (3) considering theories of human behaviour and implementation; and (4) considering issues of equity. This study seeks methodological solutions in developing a credible economic model of community-based falls prevention for older persons (aged 60 +) to inform local falls prevention commissioning as recommended by UK guidelines. Methods A framework for conceptualising public health economic models was followed. Conceptualisation was conducted in Sheffield as a representative local health economy. Model parameterisation used publicly available data including English Longitudinal Study of Ageing and UK-based falls prevention trials. Key methodological developments in operationalising a discrete individual simulation model included: (1) incorporating societal outcomes including productivity, informal caregiving cost, and private care expenditure; (2) parameterising dynamic falls-frailty feedback loop whereby falls influence long-term outcomes via frailty progression; (3) incorporating three parallel prevention pathways with unique eligibility and implementation conditions; and (4) assessing equity impacts through distributional cost-effectiveness analysis (DCEA) and individual-level lifetime outcomes (e.g., number reaching ‘fair innings’). Guideline-recommended strategy (RC) was compared against usual care (UC). Probabilistic sensitivity, subgroup, and scenario analyses were conducted. Results RC had 93.4% probability of being cost-effective versus UC at cost-effectiveness threshold of £20,000 per QALY gained under 40-year societal cost-utility analysis. It increased productivity and reduced private expenditure and informal caregiving cost, but productivity gain and private expenditure reduction were outstripped by increases in intervention time opportunity costs and co-payments, respectively. RC reduced inequality delineated by socioeconomic status quartile. Gains in individual-level lifetime outcomes were small. Younger geriatric age groups can cross-subsidise their older peers for whom RC is cost-ineffective. Removing the falls-frailty feedback made RC no longer efficient or equitable versus UC. Conclusion Methodological advances addressed several key challenges associated with falls prevention modelling. RC appears cost-effective and equitable versus UC. However, further analyses should confirm whether RC is optimal versus other potential strategies and investigate feasibility issues including capacity implications.

Purpose The Pediatric Quality of Life Inventory™ Version 4.0 Generic Core Scales (PedsQL GCS), comprising 23 items covering four subscales (physical, emotional, social, and school functioning), is a widely applied generic measure of childhood health-related quality of life (HRQoL). This study aimed to assess the psychometric performance of the self-reported Child version in an Australian general population of children using psychometric criteria based on Rasch measurement theory. Methods To minimise type I error, a random sample of n  = 500 was drawn from 1,874 Australian children aged 11–12 years who participated in the Longitudinal Study of Australian Children and completed the PedsQL GCS Child self-report measure. The partial credit model was applied. The following properties were assessed: unidimensionality, model goodness of fit, model reliability, targeting, item fit, threshold ordering, differential item functioning (DIF), and local dependency. Results Areas of poor performance included: weak support for unidimensionality of school functioning subscale; only emotional functioning subscale showing sufficient model goodness of fit; poor targeting, suggesting that item thresholds are limited in discriminating HRQoL differences in this cohort; seven items showing disordered thresholds; and five pairs of items being locally dependent. Only two items showed poor fit, and there was no evidence of non-uniform DIF regarding sex and age. Conclusion Not all Rasch measurement criteria were satisfied by the PedsQL GCS Child self-report measure applied in Australian children. This Rasch-based psychometric evaluation identified potential areas of improvement that can complement the known conceptual, practical, and classical psychometric strengths of the PedsQL GCS.

Background Falls impose significant health and economic burdens on older people. The volume of falls prevention economic evaluations has increased, the findings from which have been synthesised by systematic reviews (SRs). Such SRs can inform commissioning and design of future evaluations; however, their findings can be misleading and incomplete, dependent on their pre-specified criteria. This study aims to conduct a systematic overview (SO) to: (1) systematically identify SRs of community-based falls prevention economic evaluations; (2) describe the methodology and findings of SRs; (3) critically appraise the methodology of SRs; and (4) suggest commissioning recommendations based on SO findings. Methods The SO followed the PRISMA guideline and the Cochrane guideline on SO, covering 12 databases and grey literature for the period 2003–2020. Eligible studies were SRs with 50% or more included studies that were economic evaluations of community-based falls prevention (against any comparator) for older persons (aged 60 +) or high-risk individuals aged 50–59. Identified SRs’ aims, search strategies and results, extracted data fields, quality assessment methods/results, and commissioning and research recommendations were synthesised. The comprehensiveness of previous SRs’ data synthesis was judged against criteria drawn from literature on falls prevention/public health economic evaluation. Outcomes of general population, lifetime decision models were re-analysed to inform commissioning recommendations. The SO protocol is registered in the Prospective Register of Systematic Reviews (CRD42021234379). Results Seven SRs were identified, which extracted 8 to 33 data fields from 44 economic evaluations. Four economic evaluation methodological/reporting quality checklists were used; three SRs narratively synthesised methodological features to varying extent and focus. SRs generally did not appraise decision modelling features, including methods for characterising dynamic complexity of falls risk and intervention need. Their commissioning recommendations were based mainly on cost-per-unit ratios (e.g., incremental cost-effectiveness ratios) and neglected aggregate impact. There is model-based evidence of multifactorial and environmental interventions, home assessment and modification and Tai Chi being cost-effective but also the risk that they exacerbate social inequities of health. Conclusions Current SRs of falls prevention economic evaluations do not holistically inform commissioning and evaluation. Accounting for broader decisional factors and methodological nuances of economic evaluations, particularly decision models, is needed.