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Internet of Things (IoT) devices are becoming a part of our daily life; from health monitors to critical infrastructure, they are used everywhere. This makes them ideal targets for malicious actors to exploit for nefarious purposes. Recent attacks like the Mirai botnet are just examples in which default credentials were used to exploit thousands of devices. This raises major concerns about IoT device security. In this work, we aimed to investigate security of IoT devices through performing automatic penetration test on IoT devices. A penetration test is a way of detecting security problems, but manually testing billions of IoT devices is infeasible. This work has therefore examined autonomous penetration testing on IoT devices. In recent studies, automated attack execution models were developed for modeling automated attacks in cyber ranges. We have (1) investigated how such models can be applied for performing autonomous IoT penetration testing. Furthermore, we have (2) investigated if some well known and severe Wi-Fi related vulnerabilities still exist in IoT devices. Through a case study, we have shown that the such models can be used to model and design autonomous penetration testing agents for IoT devices. In addition, we have demonstrated that well-known vulnerabilities are present in deployed and currently sold products used in IoT devices, and that they can be both autonomously revealed through our developed system.

The purpose of the paper is to investigate whether women directors impact the risk and return of Indian banks. This study employs panel data models for a sample of 29 Indian banks that form part of the National Stock Exchange 500 index for the period 2009–2016. This paper concludes that women directors influence the accounting returns (measured through Return on Assets) of Indian banks. However, it was found that women directors did not affect the risks (measured through Equity Beta and gross NPA to Total Assets) of the sample banks. This paper contributes to the literature and practitioners in several ways. To the best of the knowledge of the authors, no study has examined the impact of women directors on the risk and return of banks operating in India. Hence, the findings of this article have substantial implications both to academia and practitioners.

PurposeThe purpose of this paper is to empirically explore the influence of independent directors (non-executive directors) on the market risks of the Indian banks.Design/methodology/approachThis paper is based on the data collected over a period of seven years (2009-2016) for a set of 29 Indian banks that are the constituents of the National Stock Exchange 500 Index. The data for independent directors of the sample banks are extracted from the annual reports of the banks, whereas the data relating to the dependent and control variables are compiled from the Ace equity and the Reserve Bank of India databases. The study uses the panel data method for analysis of the collected data for the sample banks.FindingsThis study concludes that independent directors increase the market risks for Indian banks (measured through equity beta).Originality/valueThis is, perhaps, the first paper to look into the impact of independent directors on the market risks of Indian banks. The policymakers and banks may need to be aware of the risk implications of the findings of the study in the Indian context, such that the independent directors enable their banks in reducing the market risks.

PurposeThe purpose of the paper is to explore the impact of board size on the accounting returns and asset quality of Indian banks.Design/methodology/approachThis paper uses ordinary least squares regression, robust regression and panel data methods for estimation, based on data collected for a sample of 29 Indian banks that are listed on the National Stock Exchange (NSE) and form part of the NSE-500 index over a period of eight financial years 2009-2016. The data pertaining to the board size of the sample banks is collected from the annual reports of banks, whereas the data relating to return on assets (ROA) and ratio of the gross non-performing assets to total assets and control variables (bank age and bank size) is extracted from ACE Equity database.FindingsThis paper concludes that the size of the governing board has a positive impact on the accounting returns (measured through ROA) of the Indian banks. Further, board size is observed to be insignificant in determining the asset quality of Indian banks.Originality/valueThis paper contributes to the literature and practitioners in a number of ways. First, to the best of the authors’ knowledge, this is the first study on the impact of board size on the accounting returns and asset quality of Indian banks. The findings of the study contribute new theoretical insights to the body of knowledge on the influence of the size of the board, which may be useful for future researchers. Second, banks may enhance their financial performance by taking cognizance of the findings of this study. Finally, equity investors may make use of the findings of this article in deciding on whether to invest in a bank’s stock/lend to the bank based on board size of the bank.

Purpose The purpose of this paper is to assess the impact of deviation from the target investment in working capital (WC) (measured by net trade cycle (NTC)) on the profitability (measured by gross operating income (GOI) and net operating income (NOI)) of the listed non-financial Indian firms. Design/methodology/approach The study is based on the data collected on NTC, GOI, NOI and other variables pertaining to 242 listed non-financial Indian firms that form part of the Bombay Stock exchange 500 Index for the period 2012–2017 (1,452 firm-year observations). Following Banos-Caballero et al. (2010), the authors use a firm fixed effect regression as the benchmark regression for finding out the determinants of NTC of the sample firms. Furthermore, this study explores the impact of deviation (above and below target) from the target investments in WC on the firm profitability (GOI and NOI) employing fixed effect regression. Findings The result of this study reveals that Indian firms maintain a target NTC and try to converge in case of any deviations to it. Furthermore, the profitability of the sample firms was observed to be influenced by the deviation from the target NTC irrespective of whether the deviation was above or below the target investment level in WC. Practical implications This study highlights the importance of good WC management for firms due to the negative impact of the over- and under-investments in WC and contributes to the existing body of knowledge by suggesting that managers should keep close to the target WC and not deviate from this in order to maximize the firms’ profitability. Originality/value To the best of the knowledge of the researchers, this is perhaps the first study to examine the impact of firms’ deviation from their target investment in WC on the profitability for non-financial firms listed and operating in India.

System security assurance provides the confidence that security features, practices, procedures, and architecture of software systems mediate and enforce the security policy and are resilient against security failure and attacks. Alongside the significant benefits of security assurance, the evolution of new information and communication technology (ICT) introduces new challenges regarding information protection. Security assurance methods based on the traditional tools, techniques, and procedures may fail to account new challenges due to poor requirement specifications, static nature, and poor development processes. The common criteria (CC) commonly used for security evaluation and certification process also comes with many limitations and challenges. In this paper, extensive efforts have been made to study the state-of-the-art, limitations and future research directions for security assurance of the ICT and cyber–physical systems (CPS) in a wide range of domains. We conducted a systematic review of requirements, processes, and activities involved in system security assurance including security requirements, security metrics, system and environments and assurance methods. We highlighted the challenges and gaps that have been identified by the existing literature related to system security assurance and corresponding solutions. Finally, we discussed the limitations of the present methods and future research directions.

Attempts have been made to propose a software reliability growth model (SRGM) based on non-homogeneous Poisson process for NVP system. The proposed model concerns the combined effect of increasing fault detection rate and fault removal efficiency under imperfect debugging. Moreover, a cost model has been developed. Also, an optimal release policy based on the proposed cost model and the number of remaining faults has been discussed. The performance of the proposed model has been compared with existing SRGMs for NVP system. Toward the end, the proposed model has been validated using some real data.

Web browsers are primary targets of attacks because of their extensive uses and the fact that they interact with sensitive data. Vulnerabilities present in a web browser can pose serious risk to millions of users. Thus, it is pertinent to address these vulnerabilities to provide adequate protection for personally identifiable information. Research done in the past has showed that few vulnerability discovery models (VDMs) highlight the characterization of vulnerability discovery process. In these models, severity which is one of the most crucial properties has not been considered. Vulnerabilities can be categorized into different levels based on their severity. The discovery process of each kind of vulnerabilities is different from the other. Hence, it is essential to incorporate the severity of the vulnerabilities during the modelling of the vulnerability discovery process. This paper proposes a model to assess the vulnerabilities present in the software quantitatively with consideration for the severity of the vulnerabilities. It is possible to apply the proposed model to approximate the number of vulnerabilities along with vulnerability discovery rate, future occurrence of vulnerabilities, risk analysis, etc. Vulnerability data obtained from one of the major web browsers (Google Chrome) is deployed to examine goodness-of-fit and predictive capability of the proposed model. Experimental results justify the fact that the model proposed herein can estimate the required information better than the existing VDMs.

Software reliability growth models have been proposed to assess and predict the reliability growth of software, remaining number of faults, and failure rate. In previous studies, software faults have been mainly categorized into two categories based on its severity in removal process: simple faults and hard faults. In reality, fault detectability is one of the crucial factors which can influence the reliability growth of software. The detectability of a software fault depends on how frequently the instructions containing faults are executed. However, fault removability of a software fault depends on fault removal efficiency of debugging team. The main motive of this article is to incorporate the fault detectability in software reliability assessment. Fault exposure ratio is an essential factor for software reliability modeling that controls the per-fault hazard rate. It is strongly dependent on fault detectability. In this article, the effect of fault detectability, fault removability, fault exposure ratio, and fault removal efficiency has been considered simultaneously in software reliability growth modeling. Moreover, a logistic fault exposure ratio has been introduced. The effect of change point is incorporated in the proposed software reliability growth model. Two illustrative examples with software testing data have been presented.

This paper explores the role of board characteristics of Indian banks on their market performance. We conducted panel data analysis on a sample of 29 Indian banks that form part of the National Stock Exchange (NSE) 500 index (covering a period of 8 years from 2009-2016). While ten board characteristics were considered as independent variables, Tobin’s Q was considered as the dependent variable (Tobin’s Q was assumed to be a proxy for market performance of banks). Findings suggest that only three out of ten board characteristics (average number of boards served, CEO duality and number of meetings conducted) positively affect market performance of Indian banks. Our sample included 29 Indian banks covering a period of 8 years. Also, other corporate governance mechanisms, such as characteristics of audit committee, stakeholder relations committee, nomination and remuneration committee and risk management committee were not considered for the study. Hence caution must be taken in generalizing the results of the study.

In the past, numerous vulnerability discovery models (VDMs) have been proposed to estimate and forecast the security vulnerabilities present in software systems. These models can be used to assess and mitigate the security risk posed by vulnerabilities and to estimate the resources required to handle the potential security breaches. However, these models have some shortcomings that make it difficult to forecast the vulnerabilities present in a software system precisely. Consideration of the change point problem in modeling the vulnerability discovery process can be one of the possible ways to enhance the forecasting capability of the VDMs. In real situations, the vulnerability discovery rate can be influenced by different factors, such as software age, code size, operational effort, popularity, OS and platform type, known vulnerabilities and their types, and so on. Due to the change in these factors, changes are possible in the vulnerability discovery rate. The time point where such changes occur is known as change point. In this paper, the change point problem is considered in exponential VDM to express the factual vulnerability behavior and to accelerate the forecasting capability. The proposed model is validated using real vulnerability data set reported by the National Vulnerability Database (NVD). Experimental results show that goodness of fit and forecasting ability of the exponential VDM with change point is better in comparison to exponential VDM without change point.

A society’s awareness about its fitness, determines betterment of that society’s life style. Diabetes is a disease which is born because of unhealthy life style. This motivates our work in area of Diabetes detection. In the recent time period the use of Convolutional Neural Network (CNN) to design the diabetes detection framework is getting attention since it is outperforming most of the application areas involving prediction. Here is an attempt to apply Deep Convolutional Neural Network on Ayurvedic data set of Indian population. Samples were collected from a private hospital without privacy violating attributes. The objective of this research is to find the applicability of CNN in diabetes detection. Additionally, it uses fuzzification of data so that data could be used with Convolutional Neural Network. Results show that proposed hybrid approach of integrating fuzzification with CNN has outperformed classical Neural Networks and other state of the art algorithms.

Carbon monoxide (CO) is anti-inflammatory and protective in models of disease. Its actions in vitro are short-lived but are sustained in vivo. We hypothesize that systemic CO can mediate prolonged phenotype changes in vivo, with a focus on macrophages (Mφs). Mφs isolated from CO treated rats responded to lipopolysaccharide (LPS) with increased IL6, IL10 and iNOS expression but decreased TNF. Conditioned media (CM) collected from peritoneal Mφs isolated from CO treated rats stimulated endothelial cell (EC) proliferation versus CM from Mφs from air treated rats. This effect was mediated by Mφ released VEGF and HMGB1. Inhaled CO reduced LPS induced Mφ M1 inflammatory phenotype for up to 5 days. Mitochondrial oxygen consumption in LPS treated Mφs from CO treated mice was preserved compared to LPS treated Mφs from control mice. Finally, transient reduction of inflammatory cells at the time of inhaled CO treatment eliminated the vasoprotective effect of CO in a rodent carotid injury model. Thus, inhaled CO induces a prolonged mixed phenotype change in Mφs, and potentially other inflammatory cells, that contribute to vasoprotection. These findings demonstrate the ability of inhaled CO to modify Mφs in a sustained manner to mediate its therapeutic actions, supporting the translational potential of inhaled CO.

Fault reduction factor (FRF) is one of the most important factors which plays a vital role in software reliability growth. In the past, few studies on the influence of different environmental factors into FRF have been carried out. In these studies, FRF has been defined using some particular functions such as constant, increasing, decreasing and inflection S-shaped. These functions may not be realistic and reasonable to represent the actual behavior of FRF. Therefore, in this study, it has been tried to represent the realistic behavior of FRF using Weibull curve. Moreover, a new approach of software reliability modeling has been proposed in which FRF has been incorporated in fault detection and correction process. Thus, in this paper, a general frame work of software reliability growth model (SRGM) has been proposed considering the fault detection and correction process. The concepts of imperfect debugging and change point have also been incorporated in the present study. Different parameters of the proposed SRGM are estimated using the SPSS and ‘R’ software. Different comparison criteria have been used for comparison of the proposed SRGM with other existing SRGMs. Chi-square goodness-of-fit test has been used for validation of the proposed SRGM.

Arteriogenesis represents the maturation of preformed vascular connections in response to flow changes and shear stress. These collateral vessels can restore up to 60% of the native blood flow. Shear stress and vascular injury can induce the release of nucleotides from vascular smooth muscle cells and platelets that can serve as signaling ligands, suggesting they may be involved in mediating arteriogenesis. The P2Y2 nucleotide receptor (P2Y2R) has also been shown to mediate smooth muscle migration and arterial remodeling. Thus, we hypothesize that P2Y2R mediates arteriogenesis in response to ischemia.Hind limb ischemia was induced by femoral artery ligation (FAL) in C57Bl/6NJ or P2Y2R negative mice (P2Y2(-/-)). Hind limb perfusion was measured with laser Doppler perfusion imaging and compared with the sham-operated contralateral limb immediately and at 3, 7, 14, 21, and 28 days after ligation. Collateral vessel size was measured by Microfil casting. Muscle specimens were harvested and analyzed with immunohistochemistry for Ki67, vascular cell adhesion molecule, macrophages, and muscle viability by hematoxylin and essoin stain.Hind limb ischemia induced by FAL in C57Bl/6NJ mice resulted in significant ischemia as measured by laser Doppler perfusion imaging. There was rapid recovery to nearly normal levels of perfusion by 2 weeks. FAL in P2Y2(-/-) mice resulted in severe ischemia with greater tissue loss. Recovery of perfusion was impaired, achieving only 40% compared with wild-type mice by 28 days. Collateral vessels in the P2Y2(-/-) mice were underdeveloped, with reduced vascular cell proliferation and smaller vessel size. The collaterals were ∼65% the size of wild-type collateral vessels (P = .011). Angiogenesis at 28 days in the ischemic muscle, however, was greater in the P2Y2(-/-) mice (P.001), possibly related to persistent ischemia leading and angiogenic drive. Early macrophage recruitment was reduced by nearly 70% in P2Y2(-/-) despite significantly more myocyte necrosis. However, inflammation was greater at 28 days in the P2Y2(-/-) mice.P2Y2R deficiency does not alter baseline collateral vessel formation but does significantly impair collateral maturation, with resultant persistent limb ischemia despite enhanced angiogenesis. These findings reinforce the importance of arteriogenesis in the recovery of perfusion in ischemic tissues compared with angiogenesis. They also support the role of P2Y2R in mediating this process. The mechanism by which P2Y2R mediates arteriogenesis may involve the recruitment of inflammatory cells to the ischemic tissues, which is essential to arteriogenesis. Approaches to target P2Y2R may yield new therapeutic strategies for the treatment of arterial occlusive disease.

In past four decades, many software reliability growth models (SRGMs) have been proposed to enhance the reliability of the software system. During the testing process potential fault sites are sensitized to detect the faults. Fault detection probability increases as learning and maturity of the testing personnel increases. Therefore, in this paper a time variant fault detection probability has been introduced and integrated into s-shaped coverage SRGM. Experimental results shows that the proposed model is better and will be helpful to improve the accuracy of the software reliability estimation.

Much of the work done in regard to reliability estimation of software relates itself to the testing or development phase of the commodity while less attempt has been made to estimate the reliability in the early phase of software development i.e., in the requirement analysis or design phase. Different reliability allocation methods have been used for assigning component reliability goals, which further were used to determine the reliability of the software. The present paper deals in a software reliability allocation model which has been developed based on user's view in regard to various functions constituting the software. Estimating the achievable reliability of the system at the planning or design phase itself makes reliability a singular measure to evaluate system performance. In order to accomplish the aforementioned task, a hierarchical approach has been established for the system in which the user's view has been combined with programmer and manager's view point to allocate reliability of each component followed by reliability allocation of the entire system. Interval Type-2 fuzzy analytical hierarchical process has been used to compute the software's component reliability in each case and a comparison has been put forth with the reliability measures obtained via Type-1 fuzzy analytical hierarchical process. A numerical example has been presented to validate the model based on both the aforementioned processes. Furthermore, considering the idea of efficiency of performance of each component an optimization problem has been formulated which evaluates the optimal cost for developing the software as also determines the optimal reliability the software is capable of achieving.

Chronic, nonhealing wounds result in patient morbidity and disability. Reactive oxygen species (ROS) and nitric oxide (NO) are both required for normal wound repair, and derangements of these result in impaired healing. Xanthine oxidoreductase (XOR) has the unique capacity to produce both ROS and NO. We hypothesize that XOR contributes to normal wound healing. Cutaneous wounds were created in C57Bl6 mice. XOR was inhibited with dietary tungsten or allopurinol. Topical hydrogen peroxide (H2O2, 0.15%) or allopurinol (30 μg) was applied to wounds every other day. Wounds were monitored until closure or collected at d 5 to assess XOR expression and activity, cell proliferation and histology. The effects of XOR, nitrite, H2O2 and allopurinol on keratinocyte cell (KC) and endothelial cell (EC) behavior were assessed. We identified XOR expression and activity in the skin and wound edges as well as granulation tissue. Cultured human KCs also expressed XOR. Tungsten significantly inhibited XOR activity and impaired healing with reduced ROS production with reduced angiogenesis and KC proliferation. The expression and activity of other tungsten-sensitive enzymes were minimal in the wound tissues. Oral allopurinol did not reduce XOR activity or alter wound healing but topical allopurinol significantly reduced XOR activity and delayed healing. Topical H2O2 restored wound healing in tungsten-fed mice. In vitro, nitrite and H2O2 both stimulated KC and EC proliferation and EC migration. These studies demonstrate for the first time that XOR is abundant in wounds and participates in normal wound healing through effects on ROS production.

There are 1.4 billion Android devices around the globe. With so many users and apps comes the question of privacy and security. Some permissions are critical to the operation of any app. A system is required which can tell whether an app X should be given a permission Y. Our basic idea is that an app belonging to a particular category should request permissions most common in that category. Around 130 users contributed to our dataset which had over 3964 records and 830 unique apps in 39 categories. A voting measure based on statistical mean value was used to decide the permissions to be given to particular app.

This paper presents a software reliability growth model (SRGM) based on a fuzzy stochastic differential equation (FSDE) approach. The software shall comprise of dependent and independent main and sub-components owing to a wide range of functionalities in the system. In order to obtain the optimal date of product release, a two-phase fuzzy goal programing (FGP) method has been applied for solving a fuzzy multi-objective chance-constrained programming (FMOCCP) model. While framing the cost function, the costs associated with changes in software specifications have been considered along with other cost factors. In most cases, the changes in software specifications during the software development process are dynamic in nature necessitating the cost budget to be considered as a random variable while formulating the fuzzy chance-constrained model. The SRGM proposed has been validated on real-time data sets and numerical illustrations have been provided to instantiate the optimal time of product release.

In order to verify whether the functions have been rightly implemented into the software, the developer is involved with the task of developing a set of test cases thereby influencing the set of functions and modules present in the software so that the developer can judge upon the defects laid into the implemented functions. The set of functions which these test cases influence comprises what in common terms is known as testing domain and that the rate of increase of the testing domain is vulnerable to the progress in testing process. The growth rate of the testing domain goes hand in hand with the fault content of the software, that is to say, as the testing domain spreads more number of existing faults are detected and subjected to removal, thereby causing the software fault content to decrease. Further the software developer is endowed with the task of determining the appropriate releasing time of the software into the market such that the cost is minimized and the reliability is maximized in the bargain. In order to counter effect the growing software fault content, this paper includes a testing domain dependent software reliability growth model (SRGM) incorporating the ideas of testing domain coverage efficiency as also the fault removal efficiency. The model so framed is based on Non-Homogenous Poisson Process (NHPP) and its validity has been verified by testing on fault data observed in earlier actual software development process. Along with illustration to the optimal time of software release the model has been subjected to goodness of fit comparison justifying that the developed model outperforms some of the existing ones in its capability of measuring the reliability.

In this paper, application of the secure watermarking scheme based on DWT-SVD domain is examined for piracy. This technique cryptography based on invisible and compressed (using DWT-SVD) watermark image embedded into host image without make an impression the imperceptibility and increase the security of watermark, this technique provides a robust solution for watermarked image. A comparative study of various watermarks attacks is also examined. Space complexity has also been taken into consideration, which makes this technique lesser space complex in comparison to other techniques. The performances of the secure watermarking technique are compared on the basis of entropy and PSNR values.

In past four decades, many nonhomogeneous Poisson process (NHPP) based software reliability growth models (SRGMs) have been proposed to measure and assess the reliability growth of software. During the testing process, the faults which causes failure are detected and removed. One common assumption of many traditional SRGMs is that the fault removal rate is constant. In practical, the fault removal rate increases with time as learning and maturity of software engineer increases. Hence, time variant fault removal rate has been considered in this study. A complex software system may contain different category of faults. Some of faults can be easily detected and removed and some of faults required more effort to be detected and removed. Therefore, in this article, a NHPP based SRGM has been proposed which incorporates mainly two type of faults, major and minor. The concepts of imperfect debugging and change point have also been incorporated in the proposed SRGM. The parameters of the proposed SRGM is estimated using Statistical Package for Social Sciences (SPSS) software and validation of the proposed SRGM has been done using real life data set.

This paper presents a general software reliability growth model (SRGM) based on non-homogeneous Poisson process (NHPP) and optimal software release policy with cost and reliability criteria. The main motive of this study is to develop a software release time decision model considering maintenance cost and warranty cost under fuzzy environment. In previous studies, maintenance cost has been defined either in terms of warranty cost or fault debugging cost. In reality, maintenance cost includes the cost of free patches, updates, technical support and future enhancement. Also, it is possible that maintenance process causes the removal of software faults in the operational phase including the faults which occur outside the warranty period or warranty definition. In other words, warranty action may be included the maintenance action, but not the converse. Considering this fact, maintenance cost and warranty cost are defined separately in the proposed study. Initially, an SRGM has been proposed with the revised concept of imperfect debugging phenomenon considering fault removal efficiency (FRE). Furthermore, the effect of changes in various environmental factors on models parameters has been taken into account. Numerical examples based on real software failure data sets have been given to analyze the performance of the proposed models.

This paper focuses on implementation of MapReduce programming model on Hadoop cluster for parallel processing of huge amount of data efficiently. There is deluge of data everywhere and we need to process these data efficiently to take decisions and to reach at some meaningful conclusion so that the information can be made useful. Processing large data set is a big problem as most of the data in unstructured. So we can't apply any algorithms since efficiency is a issue. In that case we need to process complete data set for almost every query on the data to get the desired result. If we process this huge amount of data on a single machine in linear fashion then we face problems like data storage issues and response time. So we need a mechanism which can process huge data sets in parallel fashion on distributed machines. MapReduce programming model is one such widely accepted model for parallel processing of data. While executing queries on the file containing 10 million records, it is observed that as the number of data nodes in the Hadoop cluster is increased, the minimum performance improvement obtained is over 42%. When implementing Distributed Grep Search vs Normal Implementation of Grep for a input file that has 10 million records containing user name, operation, ip address, with 3 data nodes, an improvement of over 18% is observed. For word count application, a substantial improvement of over 200% is observed with 3 or more data nodes. With our input size secondary sort outperforms insertion sort and bubble sort algorithms.

BackgroundTumor necrosis factor-α (TNF-α) has been implicated in the blood vessel wall response to hemodynamic forces. We hypothesized that TNF-α activity drives neointimal hyperplasia (NIH) during vein graft arterialization and that anti-TNF-α therapy would inhibit NIH.MethodsRabbits underwent bilateral vein grafting using jugular vein. All distal branches except the occipital artery were unilaterally ligated to create distinct flow environments between the bilateral grafts. Vein grafts were harvested sequentially up to 28 days for TNF-α messenger RNA (mRNA) quantitation. In separate experiments, animals received short-term or long-term dosing with pegylated soluble TNF-α type I receptor (PEG sTNF-RI) or vehicle. After 14 to 28 days, grafts were analyzed for morphometry, proliferation, apoptosis, and PEG sTNF-RI distribution.ResultsQuantitative mRNA assay (TaqMan) revealed shear-dependent (P < .001) and time-dependent (P < .001) TNF-α expression. TNF-α induction was maximal at day 1 and gradually decreased over time, but was persistently elevated even 4 weeks later (P < .001). Low shear (associated with increased NIH) resulted in significantly higher TNF-α mRNA expression (P = .03). PEG sTNF-RI was found in high concentrations in the serum and localized to NIH. The high-flow and low-flow vein grafts from treated animals demonstrated similar volumes of NIH compared with controls. PEG-sTNF-RI had only modest impact on vascular wall cell turnover, as reflected by terminal deoxynucleotide transferase-mediated deoxy uridine triphosphate nick-end labeling (P = .064) and anti-Ki-67 (P = .12) assays.ConclusionsPlacement of a vein into the arterial circulation acutely upregulates TNF-α; this expression level correlates with the degree of subsequent NIH. Pharmacologic interruption of this signaling pathway has no significant impact on NIH or wall cellular proliferation/apoptosis, suggesting that early vein graft adaptations can proceed via TNF-α–independent mechanisms.Clinical RelevanceNeointimal hyperplasia stands as a fundamental pathology of vein graft failure. This study reveals that low wall shear significantly upregulates early and acute proinflammatory cytokine tumor necrosis factor-α (TNF-α) in vein grafts (with robust neointimal formation), whereas high wall shear is associated with less TNF-α induction and neointimal hyperplasia. Further studies demonstrate that blockage of inflammatory TNF-α signaling fails to abrogate occlusive vein graft lesions. Thus, further research is required to delineate the biologic significance of the TNF-α expression dynamics observed in the early vein graft.