Competitive Model Research Articles

Prediction of fixed-bed GAC filter consumption for complex VOC mixtures using a parsimonious competitive adsorption model and a single batch test

Prediction of fixed-bed GAC filter consumption for complex VOC mixtures using a parsimonious competitive adsorption model and a single batch test

Abstract C021: Tumor-associated microbiota suppresses anti-tumor immunity by driving cDC1 dysfunction in lung cancer

Abstract Type 1 conventional dendritic cells (cDC1s) are critical for initiating and sustaining tumor-reactive CD8 T cells; lack of functional cDC1s is a key driver for failed tumor immunosurveillance and immunotherapy. However, what factors cause the cDC1 insufficiency in the tumor microenvironment (TME) remain poorly understood. Commensal microbiota has emerged as a key regulator of TME and the efficacy of cancer immunotherapies. Nonetheless, most studies have focused on the intestinal microbiome; it remains underexplored whether and how the local microbiota within tumors influences the anti-cancer immunity. Using the autochthonous Kras LSL-G12D/+ ; p53 flox/flox (KP) mouse model of lung cancer, we found an increased local bacterial burden and altered bacterial composition associated with lung tumors. Importantly, this local microbiota suppresses the anti-tumor CD8 T cell response both at baseline and in response to ICB therapies. Specifically, single-cell RNA-seq analysis revealed that the microbiota shapes the functional subsets of tumor-reactive CD8 T cells. Bacterial depletion promotes the accumulation of stem-like Tpex cells (precursor of exhausted T cells) in the TME, which serve as a reservoir of effector CD8 T cells and mediate an effective response upon ICB treatment. To distinguish the function of the local microbiota within TME from the distal gut microbiota, we developed a new method of aerosolized antibiotic treatment, which selectively ablates the intra-tumoral lung microbiota while preserving the intact gut microbiota. Using this approach, we demonstrated that removal of the intra-tumoral lung microbiota markedly improves the tumor-reactive T cell response and sensitizing “cold” lung tumors to ICB therapies. Mechanistically, we identified cDC1s as a central player in microbiota-mediated suppression of anti-tumor immunity. Local microbiota diminishes cDC1 quality and quantity in the lung TME, resulting in impaired T cell priming and Tpex maintenance. At the molecular level, our data revealed that bacterial products derived from the local microbiota induce type I interferon expression in tumor-associated myeloid cells and enhance GM-CSF production from cancer cells: chronic type I interferon and GM-CSF signaling acts cooperatively to reduce the functional cDC1 population. Combining in vitro cDC1 assays, competitive bone marrow chimera experiments and cDC1-specific knockout models, we establish the causal relationships between the local microbiota, IFN-I and GM-CSF signaling in cDC1s, and the tumor response to ICB. Altogether, our study uncovered a dominant role of tumor-associated microbiota in inhibiting cDC1s and suppressing anti-tumor immunity through type I IFN and GM-CSF dependent pathways in lung cancer. Our findings not only identify the intra-tumoral microbiota as a critical therapeutic target for lung cancer treatment, but also provide new insights into the tissue-specific, context-dependent regulatory mechanisms of cDC1s in the TME. Citation Format: Qiang Dong, Chengcheng Jin. Tumor-associated microbiota suppresses anti-tumor immunity by driving cDC1 dysfunction in lung cancer [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Tumor-body Interactions: The Roles of Micro- and Macroenvironment in Cancer; 2024 Nov 17-20; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(22_Suppl):Abstract nr C021.

The beach: tourism tax competition along the Italian coasts

AbstractThis paper investigates how tourism taxes are used by municipalities to attract tourists. We analyze how municipalities compete among each other, explicitly accounting for the spatial dimension. This paper provides a novel contribution to the literature on tax competition by explicitly modeling and testing the spatial dimension. First, we present a spatial model of tax competition, which is an adoption of the Hotelling model of imperfect competition in the linear city. We find that tax rates are strategic complements, as a change in taxes of one town will lead to a similar change of tax rates in neighboring towns. Second, we test the model with data from tourism taxes along the Italian coastline. We find that towns on the Tyrrhenian coast loose tourists to municipalities in the (south)east, if those reduce their tourism tax rate, and compete by lowering their own tax rates with respect to towns in the (north)west. We do not find similar behavior along the Adriatic coast.

The effect of thyroid cancer on the survival of patients with digestive system tumors using SEER database.

The number of cancer survivors worldwide is increasing every year, making secondary primary cancers (SPC) is a growing health threat. Studies have been conducted to investigate the risk of occurrence between digestive system tumors (DST) and thyroid cancer (TC). However, existing studies have tended to focus more on the risk of developing SPC and less on the impact of SPC on the survival of cancer survivors. In this study, using the Surveillance, Epidemiology, and End Results database, we aimed to explore the impact of TC on the survival of patients with DST by data between 2000 and 2018. The study employed the standardized incidence ratio to assess the relative risk of SPC, propensity score matching was conducted to mitigate confounding effects, Kaplan-Meier, Cox proportional risk model and competitive risk model were used to analyze the factors affecting the overall survival and cancer-specific survival. We furthermore explored the influence of pathological types and radiotherapy of TC on the survival of DST patients. 518,901 patients with DST only, 801 patients with TC occurring earlier than DST (TC-1st), and 744 patients with DST occurring earlier than TC (DST-1st) were included. The total incidence rate of small intestine cancer after TC was higher than that of the general population, and the incidence of TC after DST was higher than in the general population. DST patients with a history of TC had better overall survival and lower cancer-specific mortality and this difference was particularly significant in patients with DST-1st. In addition, radiotherapy for TC had no effect on cancer-specific mortality in patients with DST.

Why there are more species in several small patches versus few large patches: A multispecies modelling approach

Abstract As global biodiversity is rapidly declining due to habitat loss, it is important to determine how to protect it. The policies of many conservation agencies are still prioritizing the preservation of a single large habitat area (SL) versus several small areas of the same size (SS), despite empirical support favouring SS. However, to date, while many studies have explored this issue using model communities, the results are mixed. In competitive community models, fragmentation has a negative effect at low habitat amounts, whereas neutral community models suggest positive effects. This work aims to explore spatial multispecies models to verify the SS > SL pattern and determine its causes. We used three types of models: a classical neutral, neutral with habitat selection and a competitive hierarchical model. All models have three parameters, namely extinction, reproduction and dispersal distance. In the classical neutral model, species are equivalent and have the same parameters; when there is a reproduction event, they send the propagule to a surrounding patch blindly, and if the patch is already occupied, the propagule dies. In the neutral with habitat selection model, the propagules select an empty patch, so their survival is ensured. In the hierarchical model, species have competitive dominance and more dominant ones can replace the less dominant with a replacement rate parameter. We use 100 species and start simulating the colonization of an empty area; then, we destroy a fixed amount of habitat using different regular patch sizes. The results for all models are almost always that SS retains more species than SL. The extinction of species in patches depends on the quotient between reproduction and extinction rates in relation to patch size. The only case when SL > SS is when dispersal is insufficient to connect patches, and patch size is smaller than the minimum to prevent extinction. If patch size is above the critical size to maintain local populations, the SS > SL pattern is due to the sampling effect of aggregated species distribution combined with the reduction of dispersal ability of species. High‐dispersal rates produce the homogenization of species distribution and a reduction of species richness and this is why habitat fragmentation by habitat loss retains more species when patches are smaller. The model predicts that if a set of species have more dispersal capabilities, the SS effect would be lower than for species with less dispersal. Read the free Plain Language Summary for this article on the Journal blog.

Averaging method for the existence of singular canards in a two-cell inhibitory neural network

Abstract Studies of firing rate neuronal competition models, as observed in binocular rivalry, showed that the variation of the stimulus parameters can lead to rich and interesting dynamics. We use the two-cell inhibitory neural network model to address the canards accompanied by the L^s-typed mixed-mode oscillations (MMOs). Specifically, we prove the existence and asymptotic expression of canards for this two-cell model by the average method. Meanwhile, our simulation indicates that the results are in accordance with the theory. Our solution can provide ideas for determining and selecting weights in model fusion of machine learning.

The strength of interspecies interaction in a microbial community determines its susceptibility to invasion.

Previous work shows that a host's resident microbial community can provide resistance against an invading pathogen. However, this community is continuously changing over time due to adaptive mutations, and how these changes affect the invasion resistance of these communities remains poorly understood. To address this knowledge gap, we used an experimental evolution approach in synthetic communities of Escherichia coli and Salmonella Typhimurium to investigate how the invasion resistance of this community against a bacterium expressing a virulent phenotype, i.e., colicin secretion, changes over time. We show that evolved communities accumulate mutations in genes involved in carbon metabolism and motility, while simultaneously becoming less resistant to invasion. By investigating two-species competitions and generating a three-species competition model, we show that this outcome is dependent on the strength of interspecies interactions. Our study demonstrates how adaptive changes in microbial communities can make them more prone to the detrimental effects of an invading species.

Market transparency and consumer search—Evidence from the German retail gasoline market

AbstractWe estimate a model of incomplete information price competition where consumers endogenously choose whether to use a price search website. We examine how consumer search and prices would change under different transparency regimes. We find that aggregate consumer welfare is maximized when the price search website lists the lowest 20% of prices (i.e., one station in markets with less than five stations, and two stations in markets with more than five stations), with consumer expenditures falling by 1.5% relative to a regime where all are listed.

Development and validation of a risk predictive nomogram for colon cancer-specific mortality: a competing risk model based on the SEER database

BackgroundUtilizing the SEER database, we developed a competing risk model along with a nomogram designed for the early identification of colon cancer-specific mortality (CSM) risk.MethodsClinical and pathological information, along with other significant data, were obtained from the SEER database. Patients were randomly divided into a training set and a validation set. We investigated the independent factors affecting CSM among colon cancer patients using univariate and multivariate analyses within a competing risk framework, ultimately developing a predictive tool for CSM in colon cancer.ResultsInvolving 40,261 individuals diagnosed with colon cancer, our study included 10,397 deaths directly due to the disease and an additional 5,828 from other causes. We used a competing risk model to predict cancer-specific mortality (CSM) in these patients. For the training dataset, the model’s area under the curve (AUC) for predicting 1-, 3-, and 5-year cancer-specific survival (CSS) was 0.835 (95% confidence interval [CI] 0.826 to 0.844), 0.849 (95% CI 0.843 to 0.855), and 0.843 (95% CI 0.836 to 0.850), respectively. In the validation group, the AUC values for the same time periods were 0.846 (95% CI 0.833 to 0.860), 0.853 (95% CI 0.843 to 0.862), and 0.846 (95% CI 0.835 to 0.856), respectively. In comparison, traditional survival analysis yielded higher cumulative CSM rates over time than those provided by our competing risk approach.ConclusionWe created a competitive risk assessment model along with a predictive tool designed to estimate CSM in patients with colon cancer. This nomogram demonstrates high accuracy and reliability, aiding medical professionals in making clinical decisions and developing patient follow-up plans.

MANAGING COMPETITIVENESS AND RISK: THE EFFECT OF SHARIAH COMPLIANCE AND THE CENTRAL ROLE OF REPUTATION AND INVESTMENT EFFICIENCY

Business practices, especially in Muslim-majority countries, are more influenced by religious values. Therefore, CSR is less relevant or relatively limited to be implemented as an accountability mechanism, so it is advisable to consider religious values as an alternative approach to business ethics. In this context, adopting Sharia Compliance (SC) is seen as one of the dimensions of accountability, a form of business ethics implementation, and a manifestation or proxy of business ethics other than CSR. Therefore, based on the theory of business ethics, this study develops and tests a trivariate relationship model to explain how reputation and investment efficiency play a role in the relationship between SC and competitiveness and risk as proxied by the cost of equity capital. Using 825 observations, the estimation results indicate a partial mediation effect of reputation in the relationship between SC and risk (cost of equity capital). However, there is no mediation effect in the relationship between SC and competitiveness. Other estimation results indicate a partial mediation effect of investment efficiency in the relationship between SC and the cost of equity capital and competitiveness. This indicates that investment efficiency can provide additional totals in the relationship between SC and the cost of equity capital and competitiveness. However, the mediation effect of investment efficiency in the relationship between SC and SC competitiveness produces a total negative effect. Therefore, it can be said that the mediation of investment efficiency in the relationship between SC and competitiveness is an inconsistent or competitive mediation model. Overall, the partial mediation effect of reputation and investment efficiency indicates (1) there are other mediators (hidden mediators) in the relationship between SC and equity capital costs and competitiveness, (2) SC in reducing equity capital costs and producing competitiveness, among others, by building a good reputation and utilizing positive NPV investment opportunities.

The Diffusive Lotka–Volterra Competitive Model with Advection Term: Exclusion, Coexistence and Multiplicity

Earlier, the research was mainly focused on the classic diffusive two-species Lotka–Volterra competitive system (without advection). Averill et al. [2017] regarded a diffusive two-species Lotka–Volterra competitive system with advection term (with one species having a combination of random dispersal and biased movement upward along the resource gradient, while the other species adopts purely random dispersal). In this paper, we consider a more general diffusive two-species Lotka–Volterra competitive system with advection term (involving both species with a combination of random dispersal and biased movement upward along their respective resource gradients). By utilizing the theory of monotone dynamical systems, spectral analysis, methods of super- and sub-solutions and some nontrivial analytic skills, we finally obtain a rather deep understanding on the global dynamics. Moreover, our results reveal that the dynamical behavior of the system is very complex: exclusion, coexistence and bistability all may happen depending closely on the interspecific competition intensities. More interestingly, by bifurcation theory, we find that the system always admits multiple coexistence steady states when the interspecific competition intensities are near the critical point.

Anatomical prior-based vertebral landmark detection for spinal disorder diagnosis

As one of fundamental ways to interpret spine images, detection of vertebral landmarks is an informative prerequisite for further diagnosis and management of spine disorders such as scoliosis and fractures. Most existing machine learning-based methods for automatic vertebral landmark detection suffer from overlapping landmarks or abnormally long distances between nearby landmarks against anatomical priors, and thus lack sufficient reliability and interpretability. To tackle the problem, this paper systematically utilizes anatomical prior knowledge in vertebral landmark detection. We explicitly formulate anatomical priors of the spine, related to distances among vertebrae and spatial order within the spine, and integrate these geometrical constraints within training loss, inference procedure, and evaluation metrics. First, we introduce an anatomy-constraint loss to regularize the training process with the aforementioned contextual priors explicitly. Second, we propose a simple-yet-effective anatomy-aided inference procedure by employing sequential prediction rather than a parallel counterpart. Third, we provide novel anatomy-related metrics to quantitatively evaluate to which extent landmark predictions follow the anatomical priors, as is not reflected within the widely-used landmark localization error metric. We employ the localization framework on 1410 anterior-posterior radiographic images. Compared with competitive baseline models, we achieve superior landmark localization accuracy and comparable Cobb angle estimation for scoliosis assessment. Ablation studies demonstrate the effectiveness of designed components on the decrease of localization error and improvement of anatomical plausibility. Additionally, we exhibit effective generalization performance by transferring our detection method onto sagittal 2-D slices of CT scans and boost the performance of downstream compression fracture classification at vertebra-level.

Equilibrium loadings and adsorption isotherm model parameters estimated from multi-component breakthrough curves

Quantitative knowledge of competitive adsorption isotherms is essential for the design and optimization of adsorption based separation processes. Since the experimental determination of these thermodynamic functions is complicated and time consuming, there is a need for fast and easy to apply methods. In particular attractive are methods that evaluate measured breakthrough curves (BTC). Key features of these curves can be predicted with the equilibrium theory, which ignores kinetic effects that cause band broadening. If the adsorption equilibria can be described by the classical competitive Langmuir isotherm model, outlet concentration profiles can be calculated analytically. The paper summarizes and illustrates well-known classical results for N-component systems. The theory is applied to analyze experimentally determined BTC for a ternary mixture fed into an initially fully regenerated column under constant flowrate and under isothermal conditions. It is demonstrated that the retention times and intermediate plateau concentrations, which are observable for example in a single ternary BTC experiment, allow estimating a defined number of characteristic equilibrium loadings. These loadings can be directly used for easy estimation of the parameters of an assumed isotherm model. Various possibilities to use a reduced number of loadings and to include complementary results of standard pulse experiments are described. The isotherms generated from the ternary BTC are successfully validated by results of single component and ternary BTC experiments carried out subsequently. Options to generalize the method to determine isotherm model parameters from measured BTC to initially preloaded columns and to more complex mixtures are finally outlined.

A novel parabolic model driven by double phase flux operator with variable exponents: Application to image decomposition and denoising

This work tackles a novel parabolic equation driven by a nonlinear operator with double variable exponents, aiming to decompose and denoise images. Our primary approach involves enhancing classical models based on variable exponent operators by considering a novel nonlinear operator having a double-phase flux with unbalanced growth. We begin initially by analyzing the theoretical solvability of our model. Employing the Musielak-Orlicz space, we establish a suitable functional framework for investigating the proposed model. Subsequently, we use the Faedo-Galerkin approach to establish the existence and uniqueness of a weak solution for our problem. Furthermore, we provide a demonstration showcasing how our model preserves solution positivity, emphasizing this as a consistent feature of the proposed model. To evaluate our theoretical results, we present various numerical simulations on some grayscale and medical images (Magnetic Resonance Images (MRI)). These simulations covered aspects like decomposition, robustness and behavior sensitivity of model parameters with visual and quantitative comparisons. The obtained numerical results strongly support the efficiency of the proposed model in preserving features, reducing artifacts and deleting noise in comparison to some well-known existing state-of-the-art models. Furthermore, the proposed model quantitatively surpasses the competitive models in terms of several well-known criteria, namely the Peak Signal-to-Noise Ratio (PSNR), the Structural Similarity Index (SSIM) and the Mean-Square Error (MSE).

Effect of microbial interactions on performance of community metabolic modeling algorithms: flux balance analysis (FBA), community FBA (cFBA) and SteadyCom.

To explore the impact of microbial interactions on outcomes from three prevalent algorithms (Flux Balance Analysis (FBA), community FBA (cFBA), and SteadyCom) analyzing microbial community metabolic networks, five toy community models representing common microbial interactions were designed. These include commensalism, mutualism, competition, mutualism-competition, and commensalism-competition. Various scenarios, considering different biomass yields and substrate constraints, were examined for each type. In commensal communities, all algorithms consistently produced similar results. However, changes in biomass yields and substrate constraints led to variable abundances (0.33-0.8) and community growth rates (2-5 1/h) within a broad range. For competitive communities, all algorithms predicted growth of fastest-growing member. To comply with the natural coexistence of members, suboptimal solutions over optimal point are recommended. FBA faced challenges in modeling mutualism, consistently predicting growth of only one member. Although cFBA and SteadyCom resulted in a lower community growth rate, coexistence of both members were satisfied. In toy models with dual interactions, more realistic outcomes were achieved contrary to purely competitive model as the dependency fosters the coexistence which was missing in the competitive only scenarios. These findings emphasize the importance of algorithm choice based on specific microbial interaction types for reliable community behavior predictions.​.

A competing-risk nomogram for predicting gastric cancer-specific survival in patients over 70 years: A SEER-based study

BackgroundCancer-specific survival in older patients with gastric cancer is competitively affected by death from other causes. This study aimed to investigate cancer-specific survival and associated risk factors by competing-risk analysis in older patients with gastric cancer. MethodsThe data of this study are from the SEER database, using univariable and multivariable analysis of competitive risk model to weaken the impact of competitive events, explore the risk factors of cancer-specific survival, and developed a nomogram model. Then, the performance of the model is verified by C-index, ROC curve, calibration curve and DCA, and the new model is compared with the traditional TNM stage by NRI and IDI. ResultsOur study encompassed a total of 8183 patients, with 5731 in the training cohort and 2452 in the validation cohort. Univariable and multivariable analysis showed that age, years of diagnosis, race, site, SEER stage, TNM stage, surgery, radiation or chemotherapy, LNE, tumor grade and size are independent risk factors for cancer-specific survival in older patients with gastric cancer. Based on the risk factors, we developed a diagram model to predict cancer-specific survival. C-index, ROC curve, calibration curve and DCA also show good results. We compared the new model with the traditional TNM stage model, and the NRI and IDI showed the new model has been significantly improved. ConclusionThis study developed a nomogram to predict the cancer-specific survival of older patients with gastric cancer, which can accurately predict the prognosis and contribute to clinical treatment decision-making.

Cariogenic potential of the Streptococcus mutans Cid/Lrg system: an in vivo animal case study.

In our prior study using a dual-species (Streptococcus mutans/Streptococcus gordonii) competitive mouse caries model to investigate the contribution of S. mutans LrgAB to in vivo fitness, S. mutans wild-type and ΔlrgAB mutants consistently outnumbered S. gordonii and had high caries scores, even though the ΔlrgAB mutant is highly sensitive to oxidative stress. To determine whether the highly cariogenic sucrose diet used in the previous study masked the contribution of LrgAB to competitive fitness of S. mutans against S. gordonii, we recapitulated our previous mouse caries experiment with a modification in which 4% sucrose drinking water was replaced with sterile water, hypothesized to decrease the frequency of exposure of mice to sucrose, a determinant in the cariogenicity of S. mutans. Given that both S. mutans ΔlrgAB and ΔcidB mutants are sensitive to oxidative stress and share similar transcriptional profiles, these strains, as well as wild-type UA159, were tested in this modified dual-species mouse caries model. When comparing between groups the colonization within molar dental biofilms of S. mutans strains, ΔlrgAB mutant was at a level similar to the wild type, whereas S. mutans ΔcidB was modestly lower than both wild-type and S. mutans ΔlrgAB. The severity of total sulcal caries in both the ∆cidB and ∆lrgAB mutant infections was significantly lower than that of wild type. These results demonstrate that the Cid/Lrg system aids in S. mutans fitness against S. gordonii and caries potential in vivo, a phenotype likely masked in our previous study by more frequent exposure to sucrose.IMPORTANCEThe development of a mature biofilm on the tooth surface is the central event in the pathogenesis of dental caries, which primarily requires that cariogenic organisms withstand the limited resources or environmental fluctuations experienced in the oral cavity. The sensitive and heterogeneous response of the cid and lrg operons to complex external signals has been hypothesized to trigger differentiation of the Streptococcus mutans biofilm community into distinct functional subpopulations to promote survival and persistence of the S. mutans community when challenged by an unfavorable environment. The study described herein enlightens our understanding of how Cid/Lrg contributes to S. mutans pathogenic potential in vivo (caries development), warranting further research regarding the adaptive role of Cid/Lrg system in human oral biofilms toward the development of anti-caries strategies directed at the Cid/Lrg system.

A Model of Information Security and Competition

We study platforms’ incentives to invest in cybersecurity under ad-funded and subscription-funded business models.

Digital Transformation Strategies for Enterprises - An Case Study of the Traditional Retail Industry

Against the background of rapid changes in science and technology and the rapid development of the digital economy, the market landscape is going through unprecedented and profound changes, consumer preferences becoming more and more personalized and diversified, while the e-commerce sector has shown a vigorous development trend. More and more traditional retail companies realize that digital transformation has become an unavoidable trend under competitive pressure. How traditional retail companies can establish a competitive and adaptable business model through digital technology is an urgent problem that needs to be solved nowadays, but many companies have no clear idea about it and lack systematic digital transformation plans. This paper analyses the current situation of traditional retail enterprises and the dilemma of digital transformation. It puts forward suggestions for digital transformation strategies, hoping to help retail enterprises understand and cope with the challenges of digital transformation, enrich the ideas of digital transformation at the theoretical level, and provide references for traditional retail enterprises that are undergoing digital transformation.

Process Intensification via Structured Catalysts: Production of Sugar Alcohols

AbstractWith the aid of structured catalysts and reactors, such as monoliths, solid foams, and 3D printed structures, the limitations of conventional slurry and packed‐bed reactors can be surmounted. Multiphase mathematical models were presented for solid foam structures and the models were verified for the hydrogenation of arabinose, galactose, and xylose to the corresponding sugar alcohols. High product selectivities were obtained in batch and continuous experiments. Three kinetic models were considered: a competitive adsorption model, a semi‐competitive adsorption model as well as a non‐competitive adsorption model for sugar monomers and hydrogen. The models gave a good reproduction of the data, but the semi‐competitive adsorption model was the most plausible one because of the size difference between adsorbed sugar and hydrogen molecules.