Teaching hypospadias repair by utilising a novel 3D-printed silicon model: An initial assessment using structured trainee and trainer feedback.

INTRODUCTION: Simulated paediatric surgical training is inherently advantageous and flourishing. Moreover, several working conditions resulted in reduced training hours, index and subspecialty cases encountered, and the COVID-19 pandemic affected elective surgery backlogs, hence training opportunities. Hypospadias repair is technically-demanding and requires a spectrum of dissective and reconstructive skills. We therefore aimed to test a 3D-printed silicon model for hypospadias repair, in the context of hands-on surgical training. MATERIAL AND METHODS: Twenty-Seven trainees, under the supervision of 15 instructors, completed the activity. They were given a seminar to show the relevant anatomy, and 8 key steps of the exercise: (1)-degloving; (2)-urethral plate marking; (3)-incision; (4)-tubularisation; (5)-glansplasty/glanuloplasty; (6)-dartos layer preparation; (7)-preputioplasty and (8)-skin closure. Each trainee completed a structured feedback assessment. An on-site trainer supervised and evaluated each exercise. Trainees and trainers rated the model through the above steps from unsatisfactory-(1/5) to excellent-(5/5), presented herein via cross-sectional analysis. RESULTS: Eleven-(40.7 %) trainees were in years:1-3 of specialist training, 10-(37 %) were in years:4-6, and 6-(22.2 %) were beyond year-6. Two-(7.4 %) trainees had nil-hypospadias experience, 16-(59.2 %) previously assisted in procedures or performed steps, 5-(18.5 %) performed whole procedures supervised and 4-(14.8 %) independently. Twenty-(74 %) trainees and 15-(100 %) instructors judged the model to resemble the anomaly. Seventeen-(63 %) trainees and 13-(86.6 %) instructors rated the material needle-penetrability ≥3/5, compared to human tissue. Sixteen-(59 %) trainees and 13-(86.6 %) instructors rated the material suture holding ≥3/5. Eleven-(73.3 %) trainees and 13-(86.6 %) instructors rated sutures' evenness and edge coaptability ≥3/5. DISCUSSION: Hypospadias is an index operation, which requires precision skills. Simulated training in Paediatric Surgery and Urology is gaining importance. 3D-printed models are gaining a key role in simulated training. The study presents a novel 3D-printed high-fidelity silicon-based hypospadias model designed for hands-on training. A structured pathway to divide a standard hypospadias repair into key steps is displayed to ensure skill acquisition and stabilisation. CONCLUSION: This 3D-printed silicon-based hypospadias model is proven useful for hands-on training. The fidelity can still improve, especially regarding suture holding of the material. LEVEL OF EVIDENCE: LEVEL III.

Simulating Healthy Participant Pharmacokinetics for Renal and Hepatic Impairment Studies: Retrospective Assessment of the Approach.

The recruitment of a parallel, healthy participants (HPs) arm in renal and hepatic impairment (RI and HI) studies is a common strategy to assess differences in pharmacokinetics. Limitations in this approach include the underpowered estimate of exposure differences and the use of the drug in a population for which there is no benefit. Recently, a method was published by Purohit et. al. (2023) that leveraged prior population pharmacokinetic (PopPK) modeling-based simulation to infer the distribution of exposure ratios between the RI/HI arms and HPs. The approach was successful, but it was a single example with a robust model having several iterations of development and fitting to extensive HP data. To test in more studies and models at different stages of development, our catalogue of RI/HI studies was searched, and those with suitable properties and from programs with available models were analyzed with the simulation approach. There were 9 studies included in the analysis. Most studies were associated with models that would have been available at the time (ATT) of the study, and all had a current, final model. For 3 studies, the HP PK was not predicted well by the ATT (2) or final (1) models. In comparison to conventional analysis of variance (ANOVA), the simulation approach provided similar point estimates and confidence intervals of exposure ratios. This PopPK based approach can be considered as a method of choice in situations where the simulation of HP data would not be an extrapolation, and when no other complicating factors are present.

Timing of exposure assessment in studies on Group B streptococcus colonization and preterm birth.

BACKGROUND: Maternal colonization by the bacterium Group B streptococcus (GBS) increases risk of preterm birth, a condition that has an important impact on the health of children. However, research studies that quantify the effect of GBS colonization on preterm birth have reported variable estimates of the effect measure. METHODS: We performed a simulated cohort study of pregnant women to assess how timing of exposure (GBS colonization) assessment might influence results of studies that address this question. We used published data on longitudinal maternal GBS colonization and on the distribution of preterm births by gestational age to inform parameters used in the simulations. RESULTS: Assuming that the probability of preterm birth is higher during weeks when pregnant women are colonized by GBS, our results suggest that studies that assess exposure status early during pregnancy are more likely to estimate an association between GBS colonization and preterm birth that is closer to the null, compared with studies that assess exposure either at birth or during gestational weeks matched to preterm births. In sensitivity analyses assuming different colonization acquisition rates and diagnostic sensitivities, we observed similar results. CONCLUSIONS: Accurate quantification of the effect of maternal GBS colonization on the risk of preterm birth is necessary to understand the full health burden linked to this bacterium. In this study, we investigated one possible explanation, related to the timing of exposure assessment, for the variable findings of previous observational studies. Our findings will inform future research on this question.

Pathways and mechanism of MRTX1133 binding to KRAS G12D elucidated by molecular dynamics simulations and Markov state models.

KRAS G12D is the most common oncogenic mutation identified in several types of cancer. Therefore, design of inhibitors targeting KRAS G12D represents a promising strategy for anticancer therapy. MRTX1133 is a highly potent inhibitor (approximate experiment Kd ≈ 0.0002 nM) of KRAS G12D and is currently in Phase 1/2 study, however, pathways of the compound binding to KRAS G12D has remained unknown, and the mechanism underlying the complicated dynamic process are challenging to capture experimentally, which hinder the structure-based anti-cancer drug design. Here, using MRTX1133 as a probe, unbiased molecular dynamics (MD) was used to simulate the process of MRTX1133 spontaneously binding to KRAS G12D. In six of 42 independent MD simulation (a total of 99 µs), MRTX1133 was observed to successfully associate with KRAS G12D. The kinetically metastable states refer to the potential pathways of MRTX1133 binding to KRAS G12D were revealed by Markov state models (MSM) analysis. Additionally, 8 key residues that are essential for MRTX1133 recognition and tight binding at the preferred low energy states were identified by MM/GBSA analysis. In sum, this study provides a new perspective on understanding the pathways and mechanism of MRTX1133 binding to KRAS G12D.

Concurrent validity of objective assessment by finger tracking for open surgical suturing training.

BACKGROUND: The aim of this study is to evaluate whether the parameters 'time' and 'distance', measured by SurgTrac, correlate with the assessment of the same skills by blinded experts. METHODS: Basic open suturing tasks were executed by medical students. SurgTrac software measured objective parameters by tracking fingers. The executed tasks were recorded by a tablet and additionally assessed by a blinded expert with a Competency Assessment Tool-form (CAT-form). A Pearson's correlation was used to investigate the correlation between the parameters and the outcomes of the expert assessment. RESULTS: A strong correlation between the measured parameters of SurgTrac and the expert-assessment was found for knot tying by hand (r â€‹= â€‹-0.703) and vertical mattress suture (r â€‹= â€‹-0.644) and a moderate correlation for transcutaneous suture (r â€‹= â€‹-0.555) and intracutaneous suture (r â€‹= â€‹-0.451). CONCLUSION: The use of finger tracking by SurgTrac showed a good concurrent validity for the basic open suturing tasks knot tying by hand, transcutaneous suture and vertical mattress suture.

In vitro and in silico assessment of antidiabetic and antioxidant potencies of secondary metabolites from Gymnema sylvestre.

This study investigated the chemical constituents, antioxidant potential, and in vitro and in silico antidiabetic activity of Gymnema sylvestre. Column chromatography and spectroscopic techniques identified twelve compounds from the methanol extract, including 4 sterols (1-4), 5 triterpenoids (5-9), and 3 flavonoids (10-12). The chemophenetic significance of all compounds was also investigated. The antioxidant capacity of the extract and compounds (1-4) was evaluated using FRAP and DPPH assays. The extract exhibited strong free radical scavenging activity (IC50 = 48.34 µg/mL), while compounds (1-4) displayed varying degrees of efficacy (IC50 = 98.30-286.13 µg/mL). The FRAP assay indicated significant reducing power for both extract and compounds (58.54, 47.61, 56.61, and 49.11 mg Eq.VitC/g for extract and compounds 1 & 2, 3, and 4, respectively). The antidiabetic potential was assessed through α-amylase and α-glucosidase enzyme inhibition assays. The crude extract demonstrated the most potent inhibition (IC50 = 218.46 and 57.42 µg/mL for α-glucosidase and α-amylase respectively) suggesting its potential for managing postprandial hyperglycaemia. In silico studies employed molecular docking and dynamics simulations to elucidate the interactions between identified compounds and α-amylase/α-glucosidase enzymes. The results revealed promising binding affinities between the compounds and target enzymes, with compound 6 demonstrating the highest predicted inhibitory activity with -10 kcal/mol and -9.1 kcal/mol for α-amylase and α-glucosidase, respectively. This study highlights the presence of diverse bioactive compounds in Gymnema sylvestre. The extract exhibits antioxidant properties and inhibits carbohydrate-digesting enzymes, suggesting its potential as a complementary therapeutic approach for managing hyperglycaemia associated with type 2 diabetes.

Projected Health and Economic Burden of Comorbid Gout and Chronic Kidney Disease in a Virtual US Population: A Microsimulation Study.

INTRODUCTION: Gout, a common comorbidity of chronic kidney disease (CKD), is associated with high morbidity and healthcare utilization. However, a large proportion of gout remains undermanaged or untreated which may lead to worse patient outcomes and greater healthcare costs. This study estimates the present and future health and economic burden of controlled and uncontrolled gout in a virtual United States (US) CKD population. METHODS: A validated microsimulation model was used to project the burden of gout in patients with CKD in the USA through 2035. Databases were utilized to build a virtual CKD population of "individuals" with controlled or uncontrolled gout. Modelling assumptions were made on the basis of the literature, which was sparse in some cases. Health and economic outcomes with the current care (baseline) scenario were evaluated, along with potential benefits of urate-lowering intervention scenarios. RESULTS: The prevalence of comorbid gout and CKD in the USA was projected to increase by 29%, from 7.9 million in 2023 to 9.6 million in 2035 in the baseline scenario. Gout flares, tophi, and comorbidity development were also projected to increase markedly through 2035, with the economic burden of gout in the CKD population subsequently increasing from $38.9 billion in 2023 to $47.3 billion in 2035. An increased use of oral urate-lowering therapies in undermanaged patients, and pegloticase use in patients refractory to oral urate-lowering therapies were also project to result in 744,000 and 353,000 fewer uncontrolled gout cases, respectively, by 2035. Marked reductions in complications and costs ensued. CONCLUSIONS: This study projected a substantial increase in comorbid gout and CKD. However, improved use of urate-lowering interventions could mitigate this growth and reduce the health and economic burdens of gout.

Comparison of two propensity score-based methods for balancing covariates: the overlap weighting and fine stratification methods in real-world claims data.

BACKGROUND: Two propensity score (PS) based balancing covariate methods, the overlap weighting method (OW) and the fine stratification method (FS), produce superb covariate balance. OW has been compared with various weighting methods while FS has been compared with the traditional stratification method and various matching methods. However, no study has yet compared OW and FS. In addition, OW has not yet been evaluated in large claims data with low prevalence exposure and with low frequency outcomes, a context in which optimal use of balancing methods is critical. In the study, we aimed to compare OW and FS using real-world data and simulations with low prevalence exposure and with low frequency outcomes. METHODS: We used the Texas State Medicaid claims data on adult beneficiaries with diabetes in 2012 as an empirical example (N = 42,628). Based on its real-world research question, we estimated an average treatment effect of health center vs. non-health center attendance in the total population. We also performed simulations to evaluate their relative performance. To preserve associations between covariates, we used the plasmode approach to simulate outcomes and/or exposures with N = 4,000. We simulated both homogeneous and heterogeneous treatment effects with various outcome risks (1-30% or observed: 27.75%) and/or exposure prevalence (2.5-30% or observed:10.55%). We used a weighted generalized linear model to estimate the exposure effect and the cluster-robust standard error (SE) method to estimate its SE. RESULTS: In the empirical example, we found that OW had smaller standardized mean differences in all covariates (range: OW: 0.0-0.02 vs. FS: 0.22-3.26) and Mahalanobis balance distance (MB) (< 0.001 vs. > 0.049) than FS. In simulations, OW also achieved smaller MB (homogeneity: <0.04 vs. > 0.04; heterogeneity: 0.0-0.11 vs. 0.07-0.29), relative bias (homogeneity: 4.04-56.20 vs. 20-61.63; heterogeneity: 7.85-57.6 vs. 15.0-60.4), square root of mean squared error (homogeneity: 0.332-1.308 vs. 0.385-1.365; heterogeneity: 0.263-0.526 vs 0.313-0.620), and coverage probability (homogeneity: 0.0-80.4% vs. 0.0-69.8%; heterogeneity: 0.0-97.6% vs. 0.0-92.8%), than FS, in most cases. CONCLUSIONS: These findings suggest that OW can yield nearly perfect covariate balance and therefore enhance the accuracy of average treatment effect estimation in the total population.

Minimization of metabolic cost of transport predicts changes in gait mechanics over a range of ankle-foot orthosis stiffnesses in individuals with bilateral plantar flexor weakness.

Neuromuscular disorders often lead to ankle plantar flexor muscle weakness, which impairs ankle push-off power and forward propulsion during gait. To improve walking speed and reduce metabolic cost of transport (mCoT), patients with plantar flexor weakness are provided dorsal-leaf spring ankle-foot orthoses (AFOs). It is widely believed that mCoT during gait depends on the AFO stiffness and an optimal AFO stiffness that minimizes mCoT exists. The biomechanics behind why and how an optimal stiffness exists and benefits individuals with plantar flexor weakness are not well understood. We hypothesized that the AFO would reduce the required support moment and, hence, metabolic cost contributions of the ankle plantar flexor and knee extensor muscles during stance, and reduce hip flexor metabolic cost to initiate swing. To test these hypotheses, we generated neuromusculoskeletal simulations to represent gait of an individual with bilateral plantar flexor weakness wearing an AFO with varying stiffness. Predictions were based on the objective of minimizing mCoT, loading rates at impact and head accelerations at each stiffness level, and the motor patterns were determined via dynamic optimization. The predictive gait simulation results were compared to experimental data from subjects with bilateral plantar flexor weakness walking with varying AFO stiffness. Our simulations demonstrated that reductions in mCoT with increasing stiffness were attributed to reductions in quadriceps metabolic cost during midstance. Increases in mCoT above optimum stiffness were attributed to the increasing metabolic cost of both hip flexor and hamstrings muscles. The insights gained from our predictive gait simulations could inform clinicians on the prescription of personalized AFOs. With further model individualization, simulations based on mCoT minimization may sufficiently predict adaptations to an AFO in individuals with plantar flexor weakness.

Cost-Effectiveness of Increasing Access to Colorectal Cancer Diagnosis: Analysis From Thailand.

OBJECTIVES: The purpose of this study is to evaluate the cost-effectiveness of increasing access to colorectal cancer (CRC) diagnosis, considering resource limitations in Thailand. METHODS: We analyzed the cost-effectiveness of increasing access to fecal immunochemical test screening (strategy I), symptom evaluation (strategy II), and their combination through healthcare and societal perspectives using Colo-Sim, a simulation model of CRC care. We extended our analysis by adding a risk-stratification score (RS) to the strategies. We analyzed all strategies under the currently limited annual colonoscopy capacity and sufficient capacity. We estimated quality-adjusted life-years (QALYs) and costs over 2023 to 2047 and performed sensitivity analyses. RESULTS: Annual costs for CRC care will increase over 25 years in Thailand, resulting in a cumulative cost of 323B Thai baht (THB). Each strategy results in higher QALYs gained and additional costs. With the current colonoscopy capacity and willingness-to-pay threshold of 160 000 THB, strategy I with and without RS is not cost-effective. Strategy II + RS is the most cost-effective, resulting in 0.68 million QALYs gained with additional costs of 66B THB. Under sufficient colonoscopy capacity, all strategies are deemed cost-effective, with the combined approach (strategy I + II + RS) being the most favorable, achieving the highest QALYs (1.55 million) at an additional cost of 131 billion THB. This strategy also maintains the highest probability of being cost-effective at any willingness-to-pay threshold above 96 000 THB. CONCLUSIONS: In Thailand, fecal immunochemical test screening, symptom evaluation, and RS use can achieve the highest QALYs; however, boosting colonoscopy capacity is essential for cost-effectiveness.

Creating Computational Models of Ion Channel Dynamics.

Markov models are widely used to represent ion channel protein configurations as different states in the model's topology. Such models allow for dynamic simulation of ion channel kinetics through the simulated application of voltage potentials across a cell membrane. In this chapter, we present a general method for creating Markov models of ion channel kinetics using computational optimization alongside a fully featured example model of a cardiac potassium channel. Our methods cover designing training protocols, iteratively testing potential model topologies for structure identification, creation of algorithms for model simulation, as well as methods for assessing the quality of fit for a finalized model.

Virtual Screening, Molecular Dynamics Simulation, and Bioactivity Assessment Validate T13074 as a Dual-Target EGFR/c-Met Inhibitor.

OBJECTIVES: The objective of this study is to identify dual-target inhibitors against EGFR/c-Met through virtual screening, dynamic simulation, and biological activity evaluation. This endeavor is aimed at overcoming the challenge of drug resistance induced by L858R/T790M mutants. METHODS: Active structures were gathered to construct sets of drug molecules. Next, property filtering was applied to the drug structures within the compound library. Active compounds were then identified through virtual screening and cluster analysis. Subsequently, we conducted MTT antitumor activity evaluation and kinase inhibition assays for the active compounds to identify the most promising candidates. Furthermore, AO staining and JC-1 assays were performed on the selected compounds. Ultimately, the preferred compounds underwent molecular docking and molecular dynamics simulation with the EGFR and c-Met proteins, respectively. RESULT: The IC50 of T13074 was determined as 2.446 µM for EGFRL858R/T790M kinase and 7.401 nM for c-Met kinase, underscoring its potential in overcoming EGFRL858R/T790M resistance. Additionally, T13074 exhibited an IC50 of 1.93 µM on the H1975 cell. Results from AO staining and JC-1 assays indicated that T13074 induced tumor cell apoptosis in a concentration-dependent manner. Notably, the binding energy between T13074 and EGFR protein was found to be -90.329 ± 16.680 kJ/mol, while the binding energy with c-Met protein was -139.935 ± 17.414 kJ/mol. CONCLUSION: T13074 exhibited outstanding antitumor activity both in vivo and in vitro, indicating its potential utility as a dual-target EGFR/c-Met inhibitor. This suggests its promising role in overcoming EGFR resistance induced by the L858R/T790M mutation.

Cloud-based serverless computing enables accelerated monte carlo simulations for nuclear medicine imaging.

Objective.This study investigates the potential of cloud-based serverless computing to accelerate Monte Carlo (MC) simulations for nuclear medicine imaging tasks. MC simulations can pose a high computational burden-even when executed on modern multi-core computing servers. Cloud computing allows simulation tasks to be highly parallelized and considerably accelerated.Approach.We investigate the computational performance of a cloud-based serverless MC simulation of radioactive decays for positron emission tomography imaging using Amazon Web Service (AWS) Lambda serverless computing platform for the first time in scientific literature. We provide a comparison of the computational performance of AWS to a modern on-premises multi-thread reconstruction server by measuring the execution times of the processes using between105and2·1010simulated decays. We deployed two popular MC simulation frameworks-SimSET and GATE-within the AWS computing environment. Containerized application images were used as a basis for an AWS Lambda function, and local (non-cloud) scripts were used to orchestrate the deployment of simulations. The task was broken down into smaller parallel runs, and launched on concurrently running AWS Lambda instances, and the results were postprocessed and downloaded via the Simple Storage Service.Main results.Our implementation of cloud-based MC simulations with SimSET outperforms local server-based computations by more than an order of magnitude. However, the GATE implementation creates more and larger output file sizes and reveals that the internet connection speed can become the primary bottleneck for data transfers. Simulating 109decays using SimSET is possible within 5 min and accrues computation costs of about $10 on AWS, whereas GATE would have to run in batches for more than 100 min at considerably higher costs.Significance.Adopting cloud-based serverless computing architecture in medical imaging research facilities can considerably improve processing times and overall workflow efficiency, with future research exploring additional enhancements through optimized configurations and computational methods.

Stability assessment of surrounding rock in downward mining route supported by slab-wall backfill structure.

Characteristic of ground pressure in surrounding rock is generally considered as the theoretical basis of parameter optimization for stope structure and technology. To explore the feasibility of efficient method for the second-step downward route backfill stopes in Shanjin gold mine, various numerical simulation methods were used to investigate the effect of slab-wall backfill structure on stability of surrounding rock in downward route mining system. The maximum principal stress, artificial false roof stress, and displacement were analyzed to evaluate the level of ground pressure in different mining areas. These results indicate the optimized structural parameters for backfill stopes, which may also provide a low-cost way to achieve a high safety for downward route mining system.

The Production, Assessment, and Utility of 3D-Printed Video Laryngoscopes in Eastern India: A Low-Cost Alternative to Conventional Video Laryngoscopes.

Introduction Recognizing the limitations of traditional direct laryngoscopes, particularly in difficult airway situations, video laryngoscopy has emerged as a potentially safer and more effective alternative. This study evaluated the utility of two 3D-printed video laryngoscopes: a standard geometry video laryngoscope (SGVL), resembling the traditional Macintosh blade, and a hyper-angulated video laryngoscope (HAVL) with a more curved design. Their performance was compared to a standard Macintosh direct laryngoscope across various intubation parameters. By leveraging the cost-effectiveness of 3D printing with polylactic acid, the study aimed to assess the potential of this technology to improve airway management across diverse clinical settings and varying levels of physician expertise. Methods This prospective randomized crossover study compared the effectiveness of 3D-printed video laryngoscopes (VL) and a standard direct laryngoscope in intubation. After obtaining IRB approval, physicians from various specialties across multiple centers participated. Participants received training on SGVL, HAVL, and DL intubation using an instructional video and hands-on practice. The training was standardized for all participants. The primary outcome measures were time to successful intubation, number of attempts, and time to visualize vocal cords. Participants were randomized to use all three laryngoscopes on a manikin, with a maximum of two attempts per scope. A 30-minute break separated each laryngoscope evaluation. Successful intubation was defined as the single insertion of each laryngoscope and bougie, followed by endotracheal tube placement and confirmation of lung inflation. Results Ninety-eight doctors, mostly from the EM team (73.5%) and ICU team (23.4%). Teams consist of consultants, residents, and medical officers of the concerned departments. Forty-eight of the participants (49%) were novice operators (<25 intubations). Successful first-attempt intubation in those with <1 year of experience with intubation (n=33) was highest for SGVL (97%) compared to DL (82%) and HAVL (67%). Participants who learned intubation through self-directed learning exhibited a higher acceptance of VL and achieved 100% success on their first attempt. Among those who followed modules or workshops, 97% had successful first-attempt intubation with VL. The average time taken to visualize the vocal cords was lower in SGVL compared to DL (5.6 vs. 7.5 seconds) (p<0.001). The HAVL also had a lower average time compared to the DL (7.1 vs. 7.5 secs) (p<0.001). However, the time taken to intubate using DL (24.2 ±8.7 sec) was similar to SGVL (28.1 ±13 sec). Lastly, the intubation time using HAVL was the longest (49.6 ±35.5 sec). The time to intubate with DL and SGVL had Spearman's rho of 0.64 (p<0.001), and DL and HAVL had 0.59 (p<0.001). Conclusions The ease of use and its cost-effective nature make 3D-printed VLs beneficial in situations where traditional VLs may not be available, especially in simulation and training.

A systematic review of the modelling and economic evaluation studies assessing regulatory options for e-cigarette use.

BACKGROUND: Governments around the world are considering regulating access to nicotine e-cigarettes to prevent uptake among youth however people that smoke tobacco may use them to assist with smoking cessation. The health and cost implications of regulating e-cigarette use among populations are unknown but have been explored in modelling studies. We reviewed health economic evaluation and simulation modelling studies that assessed long-term consequences and interpret their potential usefulness for decision-makers. METHODS: A systematic review with a narrative synthesis was undertaken. Six databases were searched for modelling studies evaluating population-level e-cigarette control policies or interventions restricting e-cigarette use versus more liberalized use. Studies were required to report the outcomes of life years, quality-adjusted life years (QALYs) and/or healthcare costs. The quality of the studies was assessed using two quality assessment tools. RESULTS: In total, 15 studies were included with nine for the United States and one each for the United Kingdom, Italy, Australia, Singapore, Canada, and New Zealand. Three studies included cost-utility analyses. Most studies involved health state transition (or Markov) closed cohort models. Many studies had limitations with their model structures, data input quality and transparency, and insufficient analyses handling model uncertainty. Findings were mixed with 11 studies concluding that policies permitting e-cigarette use lead to net benefits and 4 studies concluding net losses in life-years or QALYs and/or healthcare costs.Five studies had industry conflicts of interest. CONCLUSIONS: While authors did conclude net benefit than net harm in more of the studies so far conducted, the significant limitations that we identified with many of the studies in this review, make it uncertain whether or not countries can expect net population harms or benefits of restrictive versus unrestrictive e-cigarette policies. The generalizability of the findings is limited for decision-makers. In light of the deep uncertainty around the health and economic outcomes of e-cigarettes, simulation modelling methods and uncertainty analyses should be strengthened.

An integrated simulation-optimization approach for combined allocation of water quantity and quality under multiple uncertainties.

Multiple uncertainties such as water quality processes, streamflow randomness affected by climate change, indicators' interrelation, and socio-economic development have brought significant risks in managing water quantity and quality (WQQ) for river basins. This research developed an integrated simulation-optimization modeling approach (ISMA) to tackle multiple uncertainties simultaneously. This approach combined water quality analysis simulation programming, Markov-Chain, generalized likelihood uncertainty estimation, and interval two-stage left-hand-side chance-constrained joint-probabilistic programming into an integration nonlinear modeling framework. A case study of multiple water intake projects in the Downstream and Delta of Dongjiang River Basin was used to demonstrate the proposed model. Results reveal that ISMA helps predict the trend of water quality changes and quantitatively analyze the interaction between WQQ. As the joint probability level increases, under strict water quality scenario system benefits would increase [3.23, 5.90] × 109 Yuan, comprehensive water scarcity based on quantity and quality would decrease [782.24, 945.82] × 106 m3, with an increase in water allocation and a decrease in pollutant generation. Compared to the deterministic and water quantity model, it allocates water efficiently and quantifies more economic losses and water scarcity. Therefore, this research has significant implications for improving water quality in basins, balancing the benefits and risks of water quality violations, and stabilizing socio-economic development.

Time-domain diffuse optical imaging technique for monitoring rheumatoid arthritis disease activity: theoretical development and in silico validation.

Objective.Effective early treatment-within 3-5 months of disease onset-significantly improves rheumatoid arthritis (RA) prognosis. Nevertheless, 1 in 3 patients experiences treatment failure which takes 3-6 months to detect with current monitoring techniques. The aim of this work is to develop a method for extracting quantitative features from data obtained with time-domain diffuse optical imaging (TD-DOI), and demonstrate their sensitivity to RA disease activity.Approach.80 virtual phantoms of the proximal interphalangeal joint-obtained from a realistic tissue distribution derived from magnetic resonance imaging-were created to simulate RA-induced alterations in 5 physiological parameters. TD-DOI images were generated using Monte Carlo simulations, and Poisson noise was added to each image. Subsequently, each image was convolved with an instrument response function (IRF) to mimic experimental measurements. Various spatiotemporal features were extracted from the images (i.e. statistical moments, temporal Fourier components), corrected for IRF effects, and correlated with the disease index (DI) of each phantom.Main results.Spatiotemporal Fourier components of TD-DOI images were highly correlated with DI despite the confounding effects of noise and the IRF. Moreover, lower temporal frequency components (⩽0.4 GHz) demonstrated greater sensitivity to small changes in disease activity than previously published spatial features extracted from the same images.Significance.Spatiotemporal components of TD-DOI images may be more sensitive to small changes in RA disease activity than previously reported DOI features. TD-DOI may enable earlier detection of RA treatment failure, which would reduce the time needed to identify treatment failure and improve patient prognosis.

Optimizing health risk assessment for soil trace metals under low-precision sampling conditions: A case study of agricultural soil.

Cost limitations often lead to the adoption of lower precision grids for soil sampling in large-scale areas, potentially causing deviations in the observed trace metal (TM) concentrations from their true values. Therefore, in this study, an enhanced Health Risk Assessment (HRA) model was developed by combining Monte Carlo simulation (MCS) and Empirical Bayesian kriging (EBK), aiming to improve the accuracy of health risk assessment under low-precision sampling conditions. The results showed that the increased sampling scale led to an overestimation of the non-carcinogenic risk for children, resulting in potential risks (the maximum Hazard index value was 1.08 and 1.64 at the 500 and 1000 m sampling scales, respectively). EBK model was suitable for predicting soil TM concentrations at large sampling scale, and the predicted concentrations were closer to the actual value. Furthermore, we found that the improved HRA model by combining EBK and MCS effectively reduced the possibility of over- or under-estimation of risk levels due to the increasing sampling size, and enhanced the accuracy and robustness of risk assessment. This study provides an important methodology support for health risk assessment of soil TMs under data limitation.

Drinking water QMRA and decision-making: Sensitivity of risk to common independence assumptions about model inputs.

When assessing risk posed by waterborne pathogens in drinking water, it is common to use Monte Carlo simulations in Quantitative Microbial Risk Assessment (QMRA). This method accounts for the variables that affect risk and their different values in a given system. A common underlying assumption in such analyses is that all random variables are independent (i.e., one is not associated in any way with another). Although the independence assumption simplifies the analysis, it is not always correct. For example, treatment efficiency can depend on microbial concentrations if changes in microbial concentrations either affect treatment themselves or are associated with water quality changes that affect treatment (e.g., during/after climate shocks like extreme precipitation events or wildfires). Notably, the effects of erroneous assumptions of independence in QMRA have not been widely discussed. Due to the implications of drinking water safety decisions on public health protection, it is critical that risk models accurately reflect the context being studied to meaningfully support decision-making. This work illustrates how dependence between pathogen concentration and either treatment efficiency or water consumption can impact risk estimates using hypothetical scenarios of relevance to drinking water QMRA. It is shown that the mean and variance of risk estimates can change substantially with different degrees of correlation. Data from a water supply system in Calgary, Canada are also used to illustrate the effect of dependence on risk. Recognizing the difficulty of obtaining data to empirically assess dependence, a framework to guide evaluation of the effect of dependence is presented to enhance support for decision making. This work emphasizes the importance of acknowledging and discussing assumptions implicit to models.