Validity Of Model Research Articles

Translation, adaptation, and validation of a Chinese version of the Hypertension Self-Care Activity Level effects (H-SCALE) for patients with hypertension.

Lifestyle modification is an essential component of prevention and management of hypertension. Existing instruments in Taiwan focus on assessing lifestyle modifications by evaluating medication adherence or confidence in controlling blood pressure. However, other self-care activities, such as diet, physical activity, weight management, smoking, and alcohol consumption are also important. The Hypertension Self-Care Activity Level Effects (H-SCALE) is one such instrument, but there are no similar tools available in Taiwan. This study aimed to translate the H-SCALE into Chinese and test its validity, and reliability in a sample of adults with hypertension. The English version of the 31-item H-SCALE was translated into Chinese using the forward-backward method. The content validity index (CVI) of the translated scale was determined by five experts in hypertension. Item analysis was conducted with a pilot sample of 20 patients with hypertension. Cronbach's α was used to establish the internal consistency reliability for the Chinese version of the H-SCALE (H-SCALE-C). Exploratory factor analysis (EFA) explored the structure of the H-SCALE-C. Additionally, construct validity was examined with confirmatory factor analysis (CFA). Patients with hypertension were recruited by convenience sampling from a cardiovascular outpatient clinic of a medical center in northern Taiwan. A total of 318 patients met the inclusion criteria and participated in factor analysis in the study. Pilot testing of the scale items indicated most patients could not accurately estimate the number of days of alcohol consumption for the previous week. Therefore, three alcohol-related items were removed. The adaptation resulted in a 28-item H-SCALE-C. EFA revealed a 4-factor solution with 13 items that explained 63.93% of the total variance. CFA indicated a good fit for a 4-factor model and construct validity was acceptable. Internal consistency reliability was acceptable (Cronbach's alpha for the four subscales ranged from 0.65 to 0.94). Convergent validity was acceptable, and discriminant validity was significant. The H-SCALE-C is a valid, reliable tool for promptly assessing life-style activities for patients with hypertension in Taiwan. The instrument is suitable for assisting healthcare providers in evaluating self-care activities, which could be used to facilitate lifestyle modifications for patients with hypertension.

Size-dependent effect on the interaction of surface waves in micropolar thermoelastic medium with dual pore connectivity

This research tackles a critical knowledge gap in Rayleigh surface wave propagation. It offers a comprehensive analysis that surpasses previous limitations. A size-dependent micropolar medium with unique void distributions and thermal effects is considered in this work. The constitutive relations and equations of motion for a nonlocal micropolar thermoelastic medium with double voids (MTMWDV) have been established by using Eringen’s nonlocal elasticity theory. Employing the three-phase-lag thermoelasticity theory (TPLTE), the study utilizes a wave-mode method to derive analytical solutions for Rayleigh waves in a nonlocal MTMWDV. To gain a comprehensive understanding of wave behavior, we solve the characteristic equation and analyze its roots, applying a filter based on the surface wave decay condition. A medium with stress-free and isothermal boundaries is explored through computational simulations to determine the attenuation coefficient and phase velocity. Furthermore, particle motion analysis is conducted to complement the analytical and computational approaches. Moreover, the influence of the nonlocal parameter and various thermoelastic models on these wave phenomena is investigated. The validity of the current mathematical model is confirmed through the derivation of particular scenarios.

A structured process for the validation of a decision-analytic model: application to a cost-effectiveness model for risk-stratified national breast screening.

Decision-makers require knowledge of the strengths and weaknesses of decision-analytic models used to evaluate healthcare interventions to be able to confidently use the results of such models to inform policy. A number of aspects of model validity have previously been described, but no systematic approach to assessing the validity of a model has been proposed. This study aimed to consolidate the different aspects of model validity into a step-by-step approach to assessing the strengths and weaknesses of a decision-analytic model. A pre-defined set of steps were used to conduct the validation process of an exemplar early decision-analytic-model-based cost-effectiveness analysis of a risk-stratified national breast cancer screening programme [UK healthcare perspective; lifetime horizon; costs (£; 2021)]. Internal validation was assessed in terms of descriptive validity, technical validity and face validity. External validation was assessed in terms of operational validation, convergent validity (or corroboration) and predictive validity. The results outline the findings of each step of internal and external validation of the early decision-analytic-model and present the validated model (called 'MANC-RISK-SCREEN'). The positive aspects in terms of meeting internal validation requirements are shown together with the remaining limitations of MANC-RISK-SCREEN. Following a transparent and structured validation process, MANC-RISK-SCREEN has been shown to have satisfactory internal and external validity for use in informing resource allocation decision-making. We suggest that MANC-RISK-SCREEN can be used to assess the cost-effectiveness of exemplars of risk-stratified national breast cancer screening programmes (NBSP) from the UK perspective. A step-by-step process for conducting the validation of a decision-analytic model was developed for future use by health economists. Using this approach may help researchers to fully demonstrate the strengths and limitations of their model to decision-makers.

Dynamic Characteristics of Magnetorheological Mounted Metal Rubber Structures Under Multi-physics Coupling Conditions

To accurately predict the dynamic characteristics of MR mounting, the nonlinear electromagnetic coupling law between MR liquid and soft magnetic material and the solid-liquid interaction, the electromagnetic coupling and fluid-structure coupling mathematical models and numerical simulation models of MR mounting are established. Through the magnetorheological mounting test, the simulation results are compared with the experimental results, and the validity of the numerical simulation model is verified. On this basis, the distribution effect of electromagnetic coupling in a magnetic circuit is analyzed. According to the Bingham model, the variation rule of magnetorheological fluid damping force was deduced. The magnetic field simulation results are introduced into the fluid model and the fluid-solid model, and the fluid-solid coupling effect of the numerical model of magnetorheological mounting is calculated. The dynamic and static characteristics of magnetorheological mounting under different current excitation conditions are simulated. It provides the basis for designing and simulating multi-physical field simulation of MR mounting.

Optimization Decomposition of Monthly Contracts for Integrated Energy Service Provider Considering Spot Market Bidding Equilibria

Under the current power trading model, especially in the context of the large-scale penetration of renewable energy and the rapid integration of renewable energy into the power system, reasonable medium- and long-term decomposition can reduce the fluctuation in the energy price when the integrated energy service provider (IESP) participates in the spot market. It helps to avoid the price risk of the spot market. Additionally, it promotes the optimization of the operation of the regional energy day-ahead scheduling. At the present stage, most of the medium- and long-term contract decomposition methods focus on the decomposition of a single power and take less consideration of the bidding space in the spot market. This limitation makes it challenging to achieve efficient interaction and interconnection among multi-energy resources and smooth integration between the medium- and long-term market and the spot market. To address these issues, this paper proposes an optimal monthly contract decomposition method for IESPs that takes into account the equilibrium of spot bidding. First, the linking process and rolling framework of multi-energy transactions between the medium- and long-term market and the spot market are designed. Second, an optimal decomposition model for monthly contracts is constructed, and a daily decomposition method for monthly medium- and long-term contracts that accounts for the spot bidding equilibrium is proposed. Then, the daily preliminary decomposition result of medium- and long-term multi-energy contracts is used as the boundary condition of the day-ahead scheduling model, and the coupling characteristics of the multi-energy networks of electricity, gas, and heat are taken into account, as well as the operational characteristics. Then, considering the coupling characteristics and operating characteristics of electricity, gas, and heat networks, the optimal scheduling model of a multi-energy network is constructed to minimize the sum of cumulative daily operating costs, and the monthly final contract decomposition value and daily spot bidding space are derived. Finally, examples are calculated to verify the validity of the decomposition model, and the examples show that the proposed method can reduce the variance in spot energy purchase by about 4.64%, and, at the same time, reduce the cost of contract decomposition by about USD 0.33 million.

Artificial Intelligence in the Effective Execution Process of Construction Projects in the Future

The construction industry currently constitutes 13% of the global gross domestic product (GDP), with projections indicating an 85% increase in value to $15.5 trillion by 2030. The widespread adoption of information technology (IT) has significantly enhanced the integration of disparate data in construction project environments. Consequently, the construction sector including full construction value chain, is undergoing a transformative phase. The increasing investment in artificial intelligence (AI) makes it impossible to keep pace with its rapid advancements. Hence, this study aims to examine the role of AI in facilitating the effective execution of construction projects in the future. This research employs a document analysis approach and scrutinizes 20 relevant papers from both domestic and international scientific databases. Methodologically, this study adopts an applied research approach, and based on the method of data collection, it is considered a descriptive survey method. Therefore, a questionnaire was designed and distributed among 100 experts and practitioners familiar with AI concepts in Tehran for data collection to conduct a census-style field study. Subsequently, Smart PLS software was employed for data analysis. The findings not only validate the model's reliability, validity and fit but also present solutions and pertinent issues related to challenges concerning AI future role in enhancing project execution efficacy.

Refined movement analysis in the Staircase test reveals differential motor deficits in mouse models of stroke

Accurate assessment of post-stroke deficits is crucial in translational research. Recent advances in machine learning offer precise quantification of rodent motor behavior post-stroke, yet detecting lesion-specific upper extremity deficits remains unclear. Employing proximal middle cerebral artery occlusion (MCAO) and cortical photothrombosis (PT) in mice, we assessed post-stroke impairments via the Staircase test. Lesion locations were identified using 7 T-MRI. Machine learning was applied to reconstruct forepaw kinematic trajectories and feature analysis was achieved with MouseReach, a new data-processing toolbox. Lesion reconstructions pinpointed ischemic centers in the striatum (MCAO) and sensorimotor cortex (PT). Pellet retrieval alterations were observed, but were unrelated to overall stroke volume. Instead, forepaw slips and relative reaching success correlated with increasing cortical lesion size in both models. Striatal lesion size after MCAO was associated with prolonged reach durations that occurred with delayed symptom onset. Further analysis on the impact of selective serotonin reuptake inhibitors in the PT model revealed no clear treatment effects but replicated strong effect sizes of slips for post-stroke deficit detection. In summary, refined movement analysis unveiled specific deficits in two widely-used mouse stroke models, emphasizing the value of deep behavioral profiling in preclinical stroke research to enhance model validity for clinical translation.

Numerical study on mixed lubrication performance of misaligned microgroove water-lubricated bearings considering cavitation and turbulence effects

This study presents a mixed lubrication model for misaligned microgroove water-lubricated bearings (WLBs). The model considers the effects of cavitation and turbulence to assess the mixed lubrication performance of WLBs with various microgroove morphologies. The equations are discretized using the control volume method (CVM) and solved by using the Fischer–Burmeister–Newton–Schur method for dealing with the constrained system. A comparison of the experimental data from the published literature demonstrates the model and methodology's validity. On this basis, the effects of rotational speed, load, and misalignment angle on the mixed lubrication performance of microgroove WLBs are investigated. The numerical results indicate that the left-triangular microgroove exhibits the best-mixed lubrication performance. Under elastohydrodynamic lubrication and mixed lubrication conditions, there are significant discrepancies in microgroove morphology. However, this discrepancy diminishes with increasing misalignment angles. The edge contact problem resulting from journal misalignment can be efficiently mitigated by selecting the proper microgroove morphology. This study provides useful guidance for the optimal design and mixed lubrication performance improvement of WLBs.

Temperature-dependent debonding behavior of adhesively bonded CFRP-UHPC interface

The adhesively bonded structure, comprising carbon fiber-reinforced polymer (CFRP) and ultra-high-performance concrete (UHPC), enhances structural strength while reducing brittleness and strain softening behavior. However, the adhesively bonded structure is inevitably influenced by temperature variations throughout its service life. When the adhesive layer's temperature surpasses the glass transition temperature (Tg), significant damage occurs to the bond layer joint. To investigate the debonding behavior of the CFRP-UHPC interface at various temperatures, a series of three-point-bending tests were conducted at room temperature, 120 %Tg, 150 %Tg, and 160 %Tg. This study introduced a temperature degradation factor, employing a proposed maximum load capacity prediction formula to adjust both the test results and data from other researchers. By adjusting the cohesion parameters with the temperature degradation factor, a temperature-dependent mixed-mode cohesive zone model (CZM) was developed. The model's validity was confirmed through finite element (FE) analysis, considering two distinct experimental scenarios. The paper concludes that the proposed model effectively simulates interface debonding behavior across varying temperatures.

Screening for eating disorders in adolescents with chronic pain: the Eating Attitudes Test–16–Chronic Pain

BackgroundFew measures have been validated to screen for eating disorders (ED) in youth with chronic pain. We conducted confirmatory (CFA) of two established factor structures of the Eating Attitudes Test-26 (EAT-26) in a sample of youth with chronic pain attending an intensive interdisciplinary pain treatment (IIPT) program and examined the validity of the best-fitting model in predicting ED diagnoses in this sample.MethodsParticipants were 880 adolescents (M age = 16.1, SD = 2.1) consecutively admitted into an IIPT program who completed the EAT-26 upon admission. CFA was conducted and in the case of inadequate fit, EFA was planned to identify alternative models. Factors of the best-fitting model were included in a logistic regression analysis to predict ED diagnoses.ResultsThe TLIs (0.70; 0.90), RMSEAs (0.09; 0.07) and CFIs (0.73; 0.92) suggested poor fit of one model and adequate of the second model. Goodness of fit indices from EFA (TLI:0.85, RMSEA:0.06) did not outperform the fit of the second CFA. As such, the second model was retained with the exception of one factor. The items loaded onto a 16-item, five factor model: Fear of Getting Fat, Social Pressure to Gain Weight, Eating-Related Control, Eating-Related Guilt and Food Preoccupation. Based on chart review, 19.1% of the participants were diagnosed with an eating disorder. Logistic regression analyses indicated the new 16-item measure and Fear of Getting Fat, significantly predicted an ED diagnosis that did not include avoidant restrictive food intake disorder (ARFID) and Social Pressure to Gain Weight significantly predicted a diagnosis of ARFID.ConclusionsAn alternative 16-item, 5-factor structure of the EAT-26 should be considered in screening for EDs with youth with chronic pain.

Importance of the innovation term for GARCH modelling of direct real estate returns

ABSTRACT The autoregressive heteroscedastic effects of the conditional volatility processes of direct real estate (capital value) returns are subject to a broad range of econometrics. However, while many specifications have been utilised in the empirical design, the literature has commonly modelled the innovation term within the GARCH volatility processes of real estate capital values through a Gaussian normal distribution. This a priori assumption falls short of the data characteristics exhibited by capital value returns, implying that capital value returns cannot be adequately modelled without adapting to the innovation term distribution. Misspecification can underestimate risk and lead to the over-allocation of riskier assets. This study investigates the impact of the a priori assumption about the innovation terms applied to capital value returns, as well as their robustness, through a time-varying framework. The main findings are that misspecification and parameterisation occur when assuming the normality of the innovation term, and that the application of a priori assumptions of the innovation term beyond those of a normal, Student’s t, or generalised error distribution currently employed in the literature can increase the validity of volatility models when applied to capital value returns. The application of the Johnson – SU distribution yields the best overall performance.

Stabilizing tumor resident mast cells restores T cell infiltration and sensitizes sarcomas to PD-L1 inhibition.

To explore the cellular crosstalk of tumor resident mast cells (MCs) in controlling the activity of cancer-associated fibroblasts (CAFs) to overcome TME abnormalities, enhancing the efficacy of immune checkpoint inhibitors (ICIs) in sarcoma. We used a coculture system followed by further validation in mouse models of fibrosarcoma and osteosarcoma with or without administration of the MC stabilizer and antihistamine ketotifen. To evaluate the contribution of ketotifen in sensitizing tumors to therapy, we performed combination studies with doxorubicin chemotherapy and anti-PD-L1 (B7-H1, clone 10F.9G2) treatment. We investigated the ability of ketotifen to modulate the TME in human sarcomas in the context of a repurpose phase II clinical trial. Inhibition of MC activation with ketotifen successfully suppressed CAF proliferation and stiffness of the extracellular matrix accompanied by an increase in vessel perfusion in fibrosarcoma and osteosarcoma as indicated by ultrasound shear wave elastography imaging. The improved tissue oxygenation increased the efficacy of chemo-immunotherapy, supported by enhanced T cell infiltration and acquisition of tumor antigen-specific memory. Importantly, the effect of ketotifen in reducing tumor stiffness was further validated in sarcoma patients highlighting its translational potential. Our study suggests the targeting of MCs with clinically administered drugs, such as antihistamines, as a promising approach to overcome resistance to immunotherapy in sarcomas.

Global Uncertainty: The Influence of Monetary Policies Order and Inflation Volatility on Bank Profitability African Bank and Middle East Bank

The objective of this paper is to examine the factors that influence the resilience and adaptability of banks to economic disruption. The aim is to encourage a collaborative and cooperative approach to these challenges. This study analyses the impact of monetary policies, inflation trends, and bank-specific determinants on bank profitability in the African and Middle Eastern regions. A quantitative research approach was used to assess macro and micro factors affecting bank profitability, using secondary data. The macro variables were obtained from the International Monetary Fund (IMF), and the micro variables were extracted from the banks' annual accounts. The research findings indicate that monetary policy and inflation have significant impacts on banks' profitability. Additionally, the System Generalized Method of Moments (GMM) model revealed that the annual interest rate (IR), inflation (INF), capital adequacy ratio (CAR), and previous financial performance (Lagged ROA/ROE) have positive and significant effects on both ROA and ROE. In addition, the loan-to-deposit ratio (LDR) had a significant positive effect on ROE, while the non-performing loan ratio (NPLr) had a significant negative effect. The validity and suitability of the GMM regression model used in this study were confirmed by the AR(2) and Sargan Test results. These findings provide valuable insights for decision-makers in the banking sector to respond to changes in monetary policy and manage risks associated with inflation fluctuations. The study emphasizes the importance of capital management and credit risk management in sustaining bank profitability amidst economic uncertainty.

Glulam frame corner joints built of birch plywood and mechanical fasteners: An experimental, analytical, and numerical study

This study investigates frame corner joints built of birch plywood plates and glulam elements connected via self-tapping screws. Analytical calculations based on the fastener group’s torsional moment resistance, the proposed fastener group’s elastic and post-elastic load-bearing criteria, and the design formulas in Eurocode 5 were performed to predict the connection capacity in both elastic and post-elastic stages. A combined action check formula was adopted to predict the capacity of birch plywood plates and glulam elements. Frame corner specimens constructed with three different plywood thicknesses were planned to study the influence on global behavior and rotational stiffness. The specimens were intentionally designed so that failure occurred either in plywood or in glulam, in order to examine the robustness and validity of analytical calculation models. Another supplementary test group with 21 mm plywood and fewer fasteners was also designed and tested, in which the plastic yield of fasteners was expected. The test results of this supplementary group served to calibrate the analytical model that predicts the elastic and post-elastic capacity of the connection group. As a result of the comparison, the analytical calculations gave reasonable predictions on the failure of plywood, glulam, and the capacity of the fastener group. Only when the exposed moment exceeded the post-elastic limit of the fastener group did the plastic yielding of fasteners become observable. Moreover, numerical finite element models adopting the foundation zone-modeling scheme were constructed, which were proven to capture all test configurations' linear loading stiffness satisfactorily.

Investigation of a potential upstream harmonization based on image appearance matching to improve radiomics features robustness: a phantom study

Objective. Radiomics is a promising valuable analysis tool consisting in extracting quantitative information from medical images. However, the extracted radiomics features are too sensitive to variations in used image acquisition and reconstruction parameters. This limited robustness hinders the generalizable validity of radiomics-assisted models. Our aim is to investigate a possible harmonization strategy based on matching image quality to improve feature robustness. Approach. We acquired CT scans of a phantom with two scanners across different dose levels and percentages of Iterative Reconstruction algorithms. The detectability index was used as a comprehensive task-based image quality metric. A statistical analysis based on the Intraclass Correlation Coefficient was performed to determine if matching image quality/appearance could enhance the robustness of radiomics features extracted from the phantom images. Additionally, an Artificial Neural Network was trained on these features to automatically classify the scanner used for image acquisition. Main results. We found that the ICC of the features across protocols providing a similar detectability index improves with respect to the ICC of the features across protocols providing a different detectability index. This improvement was particularly noticeable in features relevant for distinguishing between scanners. Significance. This preliminary study demonstrates that a harmonization based on image quality/appearance matching could improve radiomics features robustness and heterogeneous protocols can be used to obtain a similar image appearance in terms of the detectability index. Thus protocols with a lower dose level could be selected to reduce the amount of radiation dose delivered to the patient and simultaneously obtain a more robust quantitative analysis.

Development of a workplace breastfeeding support practice model in South Africa

BackgroundGlobally, mothers have identified work as one of the main obstacles to exclusive and continued breastfeeding. The support a woman receives in her workplace in terms of workplace arrangements can be critical to enable women to continue breastfeeding. This study aimed to develop and assess the face validity of a practice model to support exclusive and continued breastfeeding in workplaces in the Western Cape, South Africa.MethodsAn explanatory, sequential, mixed-method research design, was conducted (June 2017 to March 2019) in three distinct phases. Phase one employed a quantitative, descriptive, cross-sectional study design. Phase 2 used a qualitative, multiple case study. Phase three involved the development and face validity of a practice model to support exclusive breastfeeding in workplaces. The face validity included two Delphi rounds for experts to provide input on the draft practice model. This paper will only report on phase 3 of the study. The practice model was developed, drawing on the analysis of data from phases one and two and using programme theory approaches and a logic model.ResultsThe practice model was positively perceived. Participants viewed it as informative, well designed and easy to follow, even for those not knowledgeable about the subject. It was viewed as an ideal tool, if accompanied by some training. Participants were positive that the model would be feasible and most commended the tiered approach to implementation. They felt that workplaces would be more open to a step-by-step approach to implementation and if only a few activities are implemented it would be a start to make the work environment more conducive for breastfeeding employees. There were mixed opinions regarding commitment; a few participants mentioned commitment as a challenge they anticipated in the male-dominant environments in which they worked. The provision of space for breastfeeding at the workplace was also highlighted as a potential challenge.ConclusionsAdvocacy around creating an enabling workplace environment for breastfeeding is needed. The practice model has the potential to be internationally relevant, locally applied and may be of particular use to workplaces that want to initiate and/or strengthen breastfeeding support.

Enhanced predictive validity of integrative models for refractory hyperthyroidism considering baseline and early therapy characteristics: a prospective cohort study

Enhanced predictive validity of integrative models for refractory hyperthyroidism considering baseline and early therapy characteristics: a prospective cohort study

Computational fluid dynamics based digital twins of fixed bed bioreactors validate scaling principles for recombinant adeno-associated virus gene therapy manufacturing.

Gene therapy using recombinant adeno-associated virus (rAAV) as delivery vehicles has garnered much interest in recent years. There are still significant gaps in our fundamental understanding of the manufacturing processes to deliver sufficient products. Manufacturing efforts of rAAV using HEK293 cells have commonly relied on fixed bed falling film bioreactors like the iCELLis®. We used computational fluid dynamics (CFD) to validate the operating conditions required for a predictive iCELLis® 500 scale-down model. The small-scale and at-scale systems have different flow paths causing validation of the corresponding agitation rates required to achieve the same linear flow through the fixed bed across scales to be non-trivial. Therefore, we used CFD to predict the theoretical scaling relationship. In addition, CFD could predict kLa differences between the two systems and the operating conditions required to match kLa between scales. We also confirmed that the location of DO control must be the same in both systems to achieve proper scaling. Experimental runs confirming the validity of the novel scale-down model showed that based on the modifications to the iCELLis® Nano system, we achieved similar DO, key metabolite, pH, and GC titer trends in both systems.

Deep Learning-Based Design Method for Acoustic Metasurface Dual-Feature Fusion.

Existing research in metasurface design was based on trial-and-error high-intensity iterations and requires deep acoustic expertise from the researcher, which severely hampered the development of the metasurface field. Using deep learning enabled the fast and accurate design of hypersurfaces. Based on this, in this paper, an integrated learning approach was first utilized to construct a model of the forward mapping relationship between the hypersurface physical structure parameters and the acoustic field, which was intended to be used for data enhancement. Then a dual-feature fusion model (DFCNN) based on a convolutional neural network was proposed, in which the first feature was the high-dimensional nonlinear features extracted using a data-driven approach, and the second feature was the physical feature information of the acoustic field mined using the model. A convolutional neural network was used for feature fusion. A genetic algorithm was used for network parameter optimization. Finally, generalization ability verification was performed to prove the validity of the network model. The results showed that 90% of the integrated learning models had an error of less than 3 dB between the real and predicted sound field data, and 93% of the DFCNN models could achieve an error of less than 5 dB in the local sound field intensity.

Review of the current TB human infection studies for use in accelerating TB vaccine development: A meeting report.

Tools to evaluate and accelerate tuberculosis (TB) vaccine development are needed to advance global TB control strategies. Validated human infection studies for TB have the potential to facilitate breakthroughs in understanding disease pathogenesis, identify correlates of protection, develop diagnostic tools, and accelerate and de-risk vaccine and drug development. However, key challenges remain for realizing the clinical utility of these models, which require further discussion and alignment amongst key stakeholders. In March 2023, the Wellcome Trust and the International AIDS Vaccine Initiative (IAVI) convened international experts involved in developing both TB and Bacillus Calmette-Guerin (BCG) human infection studies (including mucosal and intradermal challenge routes) to discuss the status of each of the models and the key enablers to move the field forward. This report provides a summary of the presentations and discussion from the meeting. Discussions identified key issues, including demonstrating model validity, to provide confidence for vaccine developers, which may be addressed through demonstration of known vaccine effects, e.g. BCG vaccination in specific populations, and by comparing results from field efficacy and human infection studies. The workshop underscored the importance of establishing safe and acceptable studies in high-burden settings, and the need to validate more than one model to allow for different scientific questions to be addressed as well as to provide confidence to vaccine developers and regulators around use of human infection study data in vaccine development and licensure pathways.