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Background: Cuproptosis may represent a potential biomarker for predicting prognosis and immunotherapy response, but the available evidence is insufficient. Methods: The multiple single-cell RNA sequencing (scRNA-seq) datasets were analyzed to investigate the specific occurrence of cuproptosis in distinct cell populations. Utilizing 28 scRNA-seq datasets, TCGA pan-cancer cohort, and 10 immunotherapy cohorts, we developed a cuproptosis signature (Cup.Sig). This signature was used to construct prediction models for immunotherapy response and identify potential prognostic biomarkers for pan-cancer using 11 different machine learning algorithms. Results: Malignant cells demonstrate the higher cuproptosis scores in comparison to other cell types across diverse cancer types. The Cup.Sig exhibits significant associations with cancer hallmarks and immune cell response in multiple cancer types. Leveraging the Cup.Sig, the robust pan-cancer immunotherapy prediction model and prognostic biomarker have been established and validated using diverse datasets from various platforms. Conclusions: We developed a pan-cancer cuproptosis signature for predicting survival and immunotherapy response.

The annual changes of the scallop’s adductor muscle in Ca2+-ATPase activity, chymotryptic digestion, endogenous fluorescence spectra, sulfhydryl content, and surface hydrophobicity were studied. Ca2+-ATPase activity peaked in February and reached its minimum in August for males and in July for females. However, no significant differences were observed between males and females throughout the year. The inactivation rate of Ca2+-ATPase activity increased by 17- to 36-fold when the temperature rose from 38°C to 45°C. The ratio of free myosin to bound myosin was approximately 5:4 at 0.5 M KCl and changed to 5:1 at 1.0 M, as determined by modeling. Chymotryptic digestion demonstrated that scallop myosin could be cleaved into S-1/rod portions at 0.1 M and HMM/LMM at 0.5 M KCl. Furthermore, no significant seasonal variations were observed in chymotryptic digestion patterns, endogenous fluorescence, surface hydrophobicity, or sulfhydryl content. In conclusion, the structure and thermal stability of both male and female scallops remained stable throughout the year, making them suitable for processing and preservation.

Abstract Chordoma is a relatively rare and locally aggressive malignant tumor. Sirtuin (SIRT)5 plays pivotal roles in various tumors, but the role of SIRT5 in chordoma has not been found. This study was performed to investigate the regulatory effects of SIRT5 on cell proliferation, migration, and invasion and the underlying mechanism in chordoma. A xenograft tumor mouse model was established to assess tumor growth. Reverse transcription-quantitative polymerase chain reaction was used to analyze the mRNA levels of SIRT5 and c-myc. The effects of SIRT5 and c-myc on cell proliferation, migration, and invasion of chordoma cells were detected by cell counting kit-8, colony formation, and Transwell assays. The interaction between SIRT5 and c-myc was evaluated by co-immunoprecipitation (IP) assay. The succinylation of c-myc was analyzed by IP and Western blot. The results showed that SIRT5 expression was upregulated in chordoma tissues and cells. SIRT5 interacted with c-myc to inhibit the succinylation of c-myc at K369 site in human embryonic kidney (HEK)-293T cells. Silencing of SIRT5 suppressed the cell proliferation, migration, and invasion of chordoma cells, while the results were reversed after c-myc overexpression. Moreover, silencing SIRT5 suppressed tumor growth in mice. These findings suggested that SIRT5 promoted the malignant advancement of chordoma by regulating the desuccinylation of c-myc.

Abstract Background The two-way communications along the gut-lung axis influence the immune function in both gut and lung. However, the shared genetic characteristics of lung function with gastrointestinal tract (GIT) diseases remain to be investigated. Methods We first investigated the genetic correlations between three lung function traits and four GIT diseases. Second, we illustrated the genetic overlap by genome-wide pleiotropic analysis (PLACO) and further pinpointed the relevant tissue and cell types by partitioning heritability. Furthermore, we proposed pleiotropic genes as potential drug targets by drug database mining. Finally, we evaluated the causal relationships by epidemiologic observational study and Mendelian randomization (MR) analysis. Results We found lung function and GIT diseases were genetically correlated. We identified 258 pleiotropic loci, which were enriched in gut- and lung-specific regions marked by H3K4me1. Among these, 16 pleiotropic genes were targets of drugs, such as tofacitinib and baricitinib targeting TYK2 for the treatment of ulcer colitis and COVID-19, respectively. We identified a missense variant in TYK2, exhibiting a shared causal effect on FEV1/FVC and inflammatory bowel disease (rs12720356, P PLACO =1.38 × 10− 8). These findings suggested TYK2 as a promising drug target. Although the epidemiologic observational study suggested the protective role of lung function in the development of GIT diseases, no causalities were found by MR analysis. Conclusions Our study suggested the shared genetic characteristics between lung function and GIT diseases. The pleiotropic variants could exert their effects by modulating gene expression marked by histone modifications. Finally, we highlighted the potential of pleiotropic analyses in drug repurposing.

Abstract Kidney stone disease (KSD) is a complex disorder with high heritability and prevalence. We performed a large genome-wide association study (GWAS) meta-analysis for KSD to date, including 720,199 individuals with 17,969 cases in European population. We identified 44 susceptibility loci, including 28 novel loci. Cell type-specific analysis pinpointed the proximal tubule as the most relevant cells where susceptibility variants might act through a tissue-specific fashion. By integrating kidney-specific omics data, we prioritized 223 genes which strengthened the importance of ion homeostasis, including calcium and magnesium in stone formation, and suggested potential target drugs for the treatment. The genitourinary and digestive diseases showed stronger genetic correlations with KSD. In this study, we generate an atlas of candidate genes, tissue and cell types involved in the formation of KSD. In addition, we provide potential drug targets for KSD treatment and insights into shared regulation with other diseases.

Abstract The issue of synchronizing delayed and complicated dynamical networks (CDNs) using sampling data is examined in this research. First, modified free-matrix-based integral inequalities (MFMBIIs), respectively, are generated from the current free-matrix-based integral inequalities (FMBIIs) [36] and [37] to optimize CDNs’ sampled-data synchronizing control’s efficiency. Following that, the intended data sampling controller is put forth to asymptotically and exponentially synchronize the CDNs by deploying the time-associated Lyapunov functional technique and convexity-based combining approach, which fully utilize the acceptable information with respect to the actual sampling interval. Finally, computational instances verify the validity of the present outcomes and especially show that a larger upper bound of the sampling interval can be obtained from our results.

Abstract Background Although immune cells are involved in acute coronary syndrome (ACS), few studies have explored the association of incident ACS with the relative immune cell proportions. We aimed to investigate the association of immune cell proportions with the incidence and risk factors of ACS in the Dongfeng–Tongji cohort. Methods We conducted the analyses with 38,295 subjects from the first follow-up of the Dongfeng–Tongji cohort, including DNA methylation profiles for 1570 individuals. The proportions of immune cell types were observed from routine blood tests or estimated from DNA methylation profiles. For both observed and estimated immune cell proportions, we tested their associations with risk factors of ACS by multivariable linear regression models. In addition, the association of each immune cell proportion with incident ACS was assessed by the Cox regression model and conditional logistic regression model, respectively, adjusting for the risk factors of ACS. Findings The proportions of lymphocytes, monocytes, and neutrophils showed strong associations with sex, followed by diabetes. Moreover, sex and current smoking were the two factors with strongest association with the proportions of lymphocyte subtypes. The hazard ratio (HR) and 95% confidence interval (CI) of incident ACS per standard deviation (SD) increase in proportions of lymphocytes and neutrophils were 0.91 (0.85–0.96) and 1.10 (1.03–1.16), respectively. Furthermore, the OR (95% CI) of incident ACS per SD increase in proportions of NK cells, CD4+ T cells, and B cells were 0.88 (0.78–0.99), 1.15 (1.03–1.30), and 1.13 (1.00–1.26), respectively. Interpretation The proportions of immune cells were associated with several risk factors of ACS, including sex, diabetes, and current smoking. In addition, proportion of neutrophils had a risk effect, while proportion of lymphocytes had a protective effect on the incidence of ACS. The protective effect of lymphocytes was probably driven by NK cells.

The purpose of this study is to use aeolian sand obtained from Inner Mongolia to partially replace quartz sand as fine aggregate to prepare 3D printed mortar to solve the scarcity problems of quartz sand resources in northwestern China. The mechanical properties tests (including flexural strength, compressive strength, tensile bond strength and axial compression tests) and frost resistance tests of cast specimens and printed mortar specimens in the X, Y and Z directions (abbreviated as CS, PS-X, PS-Y and PS-Z) were investigated. Furthermore, their microscopic morphology and pore structure parameters were compared and analyzed using scanning electron microscopy (SEM) and low field nuclear magnetic resonance (NMR), respectively. The results showed that the flexural strength and compressive strength of the samples following the inclined cross-path were superior to those following the Z-shaped path specimens. The tensile bonding strength of the CS, PS-X, PS-Y and PS-Z exhibited that F3 > F3X > F3Z > F3Y, and the peak stress was observed as F4X > F4 > F4Z > F4Y. This was attributed to the cement hydration of CS and PS-X being more sufficient than those of PS-Y and PS-Z. Furthermore, freezing-thawing cycles accelerated the degradation of aeolian sand 3D printed mortar specimens, increased their weight loss rate and porosities, as well as reduced relative dynamic modulus of elasticity. The porosities of specimens were as follows: PS-Y > PS-Z > PS-X > CS, and the porosity of PS-Y was 97.62 %, 36.07 % and 10.67 % higher than those of CS, PS-X and PS-Z, respectively. The significance of this research is to provide technical guidance and basis for the application of aeolian sand in 3D printed mortar in the future.

With the development of Internet technology, online shopping has become increasingly popular. Owing to the improvement of living standards, the quality of e-service has become one of the important criteria for online shopping, with online shopping consultation being one of the key services. At the same time, the emergence of new technologies such as Artificial Intelligent (AI) has allowed online retailers to increase the availability of non-human online shopping consultation services. Therefore, this paper investigates the service decision problem between human and non-human online shopping consultation services for online retailers in the online duopoly market. By constructing a Hotelling improvement model and applying it in a new way, considering consumer preferences for human services, this paper explores the impact of the optimal service level of human online shopping consultation services and consumers’ sensitivity to the service level of human services on online retailers’ pricing, service decisions, etc. Our research results show that consumers’ sensitivity to the service level of human online shopping consultation services has an impact on the demand and profit of online retailers. In addition, human online shopping consultation services are not always beneficial to the profitability. Furthermore, when two online retailers compete, the utility of the non-human online retailer’s service to consumers can influence the service decisions of the other online retailer.

The emergence of short videos has provided a new way for advertisers to place online video advertisements. On short video platforms, the quality of advertisements is the main factor that attracts consumers. This study constructs a model based on advertisers’ advertising behavior and formulates their optimal advertising quality strategies. We then expand on the quality strategy by considering advertisers’ pricing factors. In addition, we compare advertisement placement on short video platforms and on general video platforms and analyze how advertisers should choose their advertisement placement strategies. Our research shows that advertisers should improve the quality of their advertisements to gain more profit when the platform is operating well, so that users become more willing to buy and products become more profitable. In addition, advertisers should present their advertisements in the shortest possible duration and show them after a longer program. Users’ price sensitivity negatively affects advertisers’ optimal advertising quality strategies and profits. Furthermore, advertisers’ choice of platform mainly depends on the advertising nuisance cost to users and the platform’s cost of entry. Finally, we find an optimal budget allocation scheme for small companies joining short video platforms to invest in bidding and designing advertisements.

BackgroundRecently, the incidence rate of renal fibrosis has been increasing worldwide, greatly increasing the burden on society. However, the diagnostic and therapeutic tools available for the disease are insufficient, necessitating the screening of potential biomarkers to predict renal fibrosis.MethodsUsing the Gene Expression Omnibus (GEO) database, we obtained two gene array datasets (GSE76882 and GSE22459) from patients with renal fibrosis and healthy individuals. We identified differentially expressed genes (DEGs) between renal fibrosis and normal tissues and analyzed possible diagnostic biomarkers using machine learning. The diagnostic effect of the candidate markers was evaluated using receiver operating characteristic (ROC) curves and verified their expression using Reverse transcription quantitative polymerase chain reaction (RT-qPCR). The CIBERSORT algorithm was used to determine the proportions of 22 types of immune cells in patients with renal fibrosis, and the correlation between biomarker expression and the proportion of immune cells was studied. Finally, we developed an artificial neural network model of renal fibrosis.ResultsFour candidate genes namely DOCK2, SLC1A3, SOX9 and TARP were identified as biomarkers of renal fibrosis, with the area under the ROC curve (AUC) values higher than 0.75. Next, we verified the expression of these genes by RT-qPCR. Subsequently, we revealed the potential disorder of immune cells in the renal fibrosis group through CIBERSORT analysis and found that immune cells were highly correlated with the expression of candidate markers.ConclusionDOCK2, SLC1A3, SOX9, and TARP were identified as potential diagnostic genes for renal fibrosis, and the most relevant immune cells were identified. Our findings provide potential biomarkers for the diagnosis of renal fibrosis.

Evidence available on the independent and combined associations of sleep duration, bedtime, and genetic predisposition with hearing loss was lacking. The present study included 15,827 participants from the Dongfeng–Tongji cohort study. Genetic risk was characterized by polygenic risk score (PRS) based on 37 genetic loci related to hearing loss. We conducted multivariate logistic regression models to assess the odds ratio (OR) for hearing loss with sleep duration and bedtime, as well as the joint association and interaction with PRS. Results showed that hearing loss was independently associated with sleeping ≥9 h/night compared to the recommended 7 to 9:00 p.m. to 10:00 p.m. compared to those with bedtime >10:00 p.m. to 11:00 p.m., with estimated ORs of 1.25, 1.27, and 1.16, respectively. Meanwhile, the risk of hearing loss increased by 29% for each 5-risk allele increment of PRS. More importantly, joint analyses showed that the risk of hearing loss was 2-fold in sleep duration ≥9 h/night and high PRS, and 2.18-fold in bedtime ≤9:00 p.m. and high PRS. With significant joint effects of sleep duration and bedtime on hearing loss, we found an interaction of sleep duration with PRS in those with early bedtime and an interaction of bedtime with PRS in those with long sleep duration on hearing loss (Pint

Oxide dispersion strengthening (ODS) is an effective way to optimize mechanical performance, radiation tolerance and wear resistance in alloys. Therefore, in this research, lightweight and oxyphilic element Ti was utilized to induce oxides particles for in-situ fabricating ODS alloys. We investigated systematically the influence of Ti content on the phase evolution and mechanical behaviors of Ni1.5Co1.5CrTix (x = 0, 0.2, 0.4, molar ratio) multi-principal element alloys (MPEAs) fabricated by mechanically alloying and high-pressure sintering (HPS). The Ni1.5Co1.5CrTix powders presented BCC phase, FCC phase and few additional oxides. Following HPS, the BCC phase transformed to FCC phase in these MPEAs. Ni1.5Co1.5Cr MPEA was composed of FCC, Cr7C3 and Cr2O3 phases. As Ti content increased, Cr oxides or carbides gradually transformed into Ti oxides or carbides. The Ni1.5Co1.5CrTix (x = 0.2, 0.4) MPEAs after HPS displayed ultrafine grained FCC matrix and uniformly dispersed ultrafine/nano Cr-C or TiOC complex compounds. With Ti content increasing, the grain sizes of FCC matrix and precipitates had a tendency to decrease. Quantitative increment of precipitation-strengthening and fine-grain-strengthening clarifies the influence of Ti content on MPEAs. The investigations may provide key insights into tuning Ti content into the MPEAs for being available structural materials.

Chaolong Wang and colleagues report a large genome-wide association study for COVID-19 severity in Chinese individuals. By meta-analysis with European data, they identify 3 loci associated with severe disease that suggest key roles for the adaptive immune system and the ABO blood group system in development of severe COVID-19.

When predicting the defaults of a large number of samples in a region, this will be affected by industry default heterogeneity. To build a credit risk model that is more suitable for Chinese-listed firms, which have highly industry-specific default heterogeneity, we extend the forward intensity model to predict the defaults of Chinese-listed firms with information about the default heterogeneity of industries. Compared with the original model, we combine the Bayes approach with the forward intensity model to generate time-varying industry-specific default heterogeneity indicators. Our model can capture co-movements of different industries that cannot be observed based on the original forward intensity model so that the model can flexibly adjust the firm’s PD according to the industry. In addition, we also consider the impact of default heterogeneity in other industries by studying the influence of the level and trends of other industries’ default heterogeneity on a firm’s credit risk. Finally, we compute PDs for 4476 firms from January 2001 to December 2019 for 36 prediction horizons. The extended model improves the prediction accuracy ratios both for the in-sample and out-of-sample firm’s PDs for all 36 horizons. Almost all the accuracy ratios of the prediction horizons’ PDs are increased by more than 6%. In addition, our model also reduces the gap between the aggregated PDs and the realized number of defaults. Our industry-specific default heterogeneity indicator is helpful to improve the model’s performance, especially for predicting defaults in a large portfolio, which is of significance for credit risk management in China and other regions.

To investigate the impact of different strategies adopted by the merged firm on supply chain members, we consider a two-tier supply chain involving two suppliers and multiple manufacturers. Different from most studies, manufacturers, downstream in the supply chain, are asymmetric and produce differentiated products. Due to the differences between products, the postmerger manufacturer can choose focus strategy to generate synergy effect or differentiation strategy to implement price collusion. We give equilibrium results for the supply chain under different strategies. Theoretical analysis shows that for supplier, no matter which strategy is chosen, the price sensitivity for suppliers will increase. Surprisingly, the merger has the opposite effect on the profits of two suppliers under differentiation strategy. Regarding the strategic options after the merger, our research indicates that with the increased substitutability between products, shifting from differentiation strategy to focus strategy should be taken by the postmerger manufacturer. In addition, when focus strategy is chosen and the synergy effect is weak, or when differentiation strategy is chosen and the substitution between products is small, the merger may be beneficial to nonparticipating manufacturers.

By exploiting the electro-absorption characteristic of graphene, we proposed and theoretically demonstrated an electro-absorption optical modulator (EOM) based on the graphene-buried polymer waveguides. By burying the graphene layers inside the polymer waveguide, acquiring a strong graphene-light interaction when the graphene layers buried in the center of core, which bring about an important change of the optical mode and effective mode index in the waveguide. The width of the graphene capacitor was also optimized to enhance the bandwidth of the device. Calculations show that the proposed EOM can realize 29 dB extinction ratio, 7 dB modulation depth and 42 GHz bandwidth with an 800 μm-long active region. The required switching voltage form its minimum to maximum absorption state is 1.6 V and 1.55 pJ/bit energy consumption can be achieved. The proposed modulator can remedy the lack of high-speed optical modulator on the passive polymer waveguide and have a potential application for polymer-based photonic integrated circuits.

In customer-intensive services, advertising can increase customers’ patience and bring more utility to customers. However, customers’ different perceptions of advertising can affect their utility and indirectly affect the decision making of the service provider. Thus, this paper uses the M/M/1 queueing model to study the optimal decision making of customer-intensive service providers in different markets according to the customers’ heterogeneity. We first classify customers into two categories: high sensitivity and low sensitivity, and then we analyze the consumption behavior of these two types of customers in the service system as the potential customer arrival rate increases. Finally, the optimal decisions of the service provider with different demands are determined. We find that the service provider can benefit from making optimal decisions based on market demand as the potential customer arrival rate increases. If the potential arrival rate exceeds a certain threshold, the service provider has more dominance in the market, and relevant decision making is no longer affected by the potential customer arrival rate. Furthermore, it is not always beneficial for the service provider to serve all customers regardless of whether there are low-sensitivity customers in the service system, and advertising can tap more highly sensitive customers and help to further increase the revenue of service providers. The results also show that ignoring the heterogeneity of customers’ sensitivity to advertising very likely leads to losses in revenue.

We employed a forward intensity approach to predict the multi-period defaults of Chinese-listed firms during the period 2001–2019 on a monthly basis. We introduced the firm’s default heterogeneity into the model, and each firm’s actual past default situation was considered for Bayesian estimation. Maximum pseudo-likelihood estimation was conducted on 3513 firms to calculate the parameters of the Bayesian model to adjust the default intensity of all 4216 firms. Finally, we re-calculated the default probabilities and compared them with the original default probabilities of the out-of-sample 703 firms for all prediction horizons. We found that the Bayesian model, considering the firm’s default heterogeneity, improved the prediction accuracy ratio of the out-of-sample firm’s default probabilities both for short and long horizons. As compared with the original model, the prediction accuracy ratio of the out-of-sample’s default probabilities, which were computed by our model, increased by almost 15% for horizons from 1 month to 6 months. When the horizon was extended from 1 year to 3 years, the prediction accuracy ratio increased by more than 10%. We found that the Bayesian model improved the predictive performance of the forward intensity model, which is helpful to improve the credit risk measurement system of Chinese-listed firms.

Social philanthropy and innovation systems both require significant resource investment—how can organizations achieve both? This paper combines social exchange theory, signaling theory and imprinting theory to analyze the intrinsic dynamics mechanism from the perspective of government technology resource acquisition and to explore the influential role of generalist CEOs. Based on the hand-collected multidimensional career experience dataset of CEOs and the quantitative analysis of 3651 enterprises in China’s A-share listed manufacturing industry from 2010–2019, the results show that: philanthropic donation has a systematic contribution to corporate innovation investment, in which government science and technology (S&T) resource acquisition plays a partially mediating role; generalist CEOs significantly enhance the effect of philanthropic donations and government S&T resource acquisition on innovation investment. Finally, the statistical results remain stable in the lagged effects experiment and the IV-2SLS model analysis using exogenous variables. The contribution of this study lies in expanding the research on maximizing the combined benefits of economic value creation and social performance from a social exchange perspective, and helping us understand why the share of generalists in the global managerial market big data has been steadily increasing.

Video platforms allow users to interact with others. They enhance the user experience by providing interaction functions, such as “like”, “comment”, and “share”. In order to explore the value of the users’ behavior to the video platforms, we constructed a video platform operation model that considered interaction and then identified the logical relationships implied by the parameters. We adopted the mathematical model method and analyzed the entire video platform system using numerical optimization techniques. From the pricing decision, we obtained the equilibrium result for the video platform profits and analyzed the favorable market demands. We complemented this strategy by proposing a model that enables platforms to consider the promotion behavior of advertisers. Finally, we expanded the basic model by analyzing the competitive strategies of two video platforms in the market. Our research shows that interactivity, advertisement nuisance, and advertiser profitability are important factors that influence video platform pricing strategies. When interactivity is weak, the platforms need to adjust their pricing to obtain a share of the users in the market. However, they need to obtain all the users in the market to achieve optimal profit. In addition, it is profitable for platforms to adopt promotion strategies when the users are highly sensitive to promotions.

Many catering merchants are currently adopting omnichannel sales methods. At a restaurant, customers can place their orders, and while waiting for the food to be completed, they can enjoy the restaurant’s service environment. Online customers, by placing orders on various apps, can skip the queue, increasing their utility by reducing the opportunity cost, but they cannot enjoy the restaurant’s service environment. For merchants, it is important to adequately address how to choose the optimal capacity to provide services to customers in different channels and obtain optimal profits based on the service environment. In this paper, we establish a stylized theoretical model to study the impact of the service environment on customers’ shopping behavior online and offline, and we study how merchants can formulate the optimal capacity. Our main results are as follows: First, improving the service environment was conducive to reducing the merchants’ safety capacity and could help them obtain higher profits. In short-term omnichannel operations, merchants obtained higher profits than in traditional offline single-channel operations. Improving the service environment increased profits, but the profit difference between short-term omnichannel and offline single-channel operations gradually decreased. Finally, in long-term operations, the process of online customers transferring to offline channels based on a high-quality service environment might be detrimental to merchants’ profits.

This paper investigates the price and service rate decisions in a customer-intensive service in an M/M/1 queue system under the influence of social interactions, where a higher value of the service is perceived if more customers purchase the service. The customer-intensive nature of the service requires a low service speed to maintain its quality, which may increase the congestion of the system. Two cases where customers are either homogeneous or heterogeneous in terms of the customer intensity are considered. It is found that social interactions can always benefit the service provider as more expected revenue can be achieved, and potential profits would be lost if the influence of social interactions is ignored. For the case with heterogeneous customers, the optimal price and service rate decisions are solved with or without considering social interaction effect. The study finds the proportions of high and low sensitive customers and the social interaction intensity are critical to the operational decisions and the market coverage strategies. These results offer a better understanding on the interplay between the quality-speed conundrum and the influence of social interactions in customers’ purchase behaviour in managing customer-intensive services.

From the perspective of the interactive cooperation among subjects, this paper portrays the process of cooperative innovation in industrial cluster, in order to capture the correlated equilibrium relationship among them. Through the utilization of two key tools, evolutionary stable strategy and replicator dynamics equations, this paper considers the cost and gains of cooperative innovation and the amount of government support as well as other factors to build and analyze a classic evolutionary game model. On this basis, the subject’s own adaptability is introduced, which is regarded as the system noise in the stochastic evolutionary game model so as to analyze the impact of adaptability on the game strategy selection. The results show that, in the first place, without considering subjects’ adaptability, their cooperation in industrial clusters depends on the cost and gains of innovative cooperation, the amount of government support, and some conditions that can promote cooperation, namely, game steady state. In the second place after the introduction of subjects’ adaptability, it will affect both game theory selection process and time, which means that the process becomes more complex, presents the nonlinear characteristics, and helps them to make faster decisions in their favor, but the final steady state remains unchanged.