Search

The recycling process of materials from used and wasted printed circuit boards plays an important role in electronic waste management. These waste printed circuit boards (PCBs) hold metals such as copper, aluminium, nickel, and magnesium. The efficient recovery process of such metals from waste PCBs is needed for recycle and possible reuse for manufacturing of products. The metal recovery process is complex and, multidimensional and costly to perform. In addition, the efficient (maximum) recovery of metals exhibit higher dependence on determination of optimum combination of inputs in the recovery process from waste PCBs. Therefore, this work illustrated the ability of four predictive modelling methods (Analysis of Variance, Genetic Programming, Artificial Neural Network and Generalized Neural Network) to model complex suspension electrolysis process (recovery process) and their comparative analysis on recovery of copper metal from waste PCBs. Experiments were designed based on variations of three design/input parameters such as concentration of sulfuric acid, concentration of copper sulphate and current density. The comparative analysis of the four methods mentioned above reveals that Generalized Neural Network performed the best with coefficient of determination value at 0.92. 3-D surface contour analysis showed that a lower concentration of sulfuric acid (0.3–0.6) coupled with higher concentrations of copper sulfate (∼0.8–1) yielded a higher percentage of copper. However, current density brought an increase in copper recovery only when there was a corresponding increase in the concentration of sulfuric acid or copper sulphate. Thus, the optimal conditions to gain the maximum yield of copper obtained through this method were concluded as follows: concentration of copper sulphate value at 31.4 g/L, concentration of sulfuric acid at 112 g/L and current density at 3 A/dm2.

Slope failures are catastrophic in nature, resulting in widespread loss of lives and infrastructure. Consequently, stability analysis of slopes has gathered considerable attention by the research community across the globe. In practice, limit equilibrium approach forms the underlying principle for majority of the conventional slope stability analysis methods. One of the major limitations of the limit equilibrium methods is that they fail to account for inherent variability of in situ soil and its influence on the assessment of slope stability. As a contribution to this important aspect, the current study presents a reliability-based slope stability analysis of a natural slope of an infinite extent. The slope is analyzed in the following four states of the natural slope, namely, dry state, fully submerged state, with steady seepage, and under seismic loading. The reliability analysis is performed using Hasofer–Lind first-order reliability method. The in situ soil properties considered as variables include in situ soil cohesion, angle of internal friction, and unit weight. The analyses results are presented with respect to different levels of in situ soil variability, slope angles, depths of potential failure plane, and magnitude (and its variability) of seismic loading. Evidently, the study provided a better insight and different perspective into the stability analysis of infinite slopes.

The electric operated road vehicles are frequently powered by lithium ion batteries due to its low cost and ease of manufacturing. However, unforeseen impacts in road conditions can lead to fire hazard due to short circuiting of the battery pack. The impact strength of the battery pack can hence provide a key design input for manufacturing next generation batteries with a durable safe limit. In this work, a finite element based neural search approach is proposed for determining the effects of various uncertain phenomena on the strength of the battery. The approach combines the actual impact mechanics of battery as determined by the finite element model along with the high accuracy and robustness provided by neural search algorithm. The derived model is able to satisfactorily predict the variances in the mechanical strength even with slightest uncertainties in the phenomena which can affect the strength of the battery pack. It is anticipated that the proposed model will be of utmost importance in design of next generation safe and durable lithium ion battery packs.

c-Jun N-terminal kinase (JNK), a member of the MAPK family, is associated with a variety of diseases and immune responses. To dissect the mechanistic role of JNKs in such processes, a specific inhibitor for JNKs holds great value. SP600125 is a widely used inhibitor of JNKs despite its non-specific activity. In an effort to obtain better specific inhibitors, three anthrapyrazolone halogenated derivatives have been synthesized and characterized. Among the three derivatives, 5-chloro-2-(2-chloroethyl)dibenzo[cd,g] indazol-6(2H)-one is clearly established as a specific inhibitor of JNK with augmented expression of chemokines in LPS-activated macrophages based on modelling studies followed by in vitro and ex vivo evaluation.

st century forecasting of solar power generation is an important issue due to grid integration. In these days power shading and heavy load is a major problem in front of conventional power generation sources so grid integration is plays an important role to fill the gap in between demand and supply of power generation. So solar power and conventional power are basic sources of grid integration. Solar power is playing a key role in grid integration. In this work, Solar power generation forecasting is carried out based on the data collected from a 5MW Gujarat Power Cooperation limited solar photovoltaic power plant which is installed in Charanka, Gujarat. In this paper we discussed about the single exponential smoothing for solar power forecasting problem and impact of trend and seasonality on modelling of power generation forecasting.

NQO1 and TRXR1 are important host reductases implicated in the regulation of inflammation and apoptosis. Although the transcriptional machinery governing these processes have been extensively investigated, the associated epigenetic regulatory events remain unclear. Here, we report that SET8, a histone H4 lysine 20 monomethylase (H4K20me1), is highly induced during Mycobacterium tuberculosis infection that orchestrates immune evasion strategies through the induction of NQO1 and TRXR1 in vivo. SET8, along with FoxO3a, mediates an active NQO1-PGC1-a complex, which promotes the anti-inflammatory M2 macrophage phenotype, and assists TRXR1-regulated arrest of tumor necrosis factor-related apoptosis-inducing ligand-induced apoptosis. Strikingly, the loss-of-function analysis in an in vivo mouse tuberculosis model further corroborated the pivotal role of SET8-responsive NQO1 and TRXR1 in mycobacterial survival. Thus, augmenting host immune responses against Mycobacterium tuberculosis by harnessing the SET8-NQO1/TRXR1 axis with its specific and potent inhibitors could lead to promising host-directed therapeutic adjuvants for tuberculosis treatment.

Background: Intravenous immunoglobulin (IVIG) is a polyspecific pooled immunoglobulin G preparation and one of the commonly used therapeutics for autoimmune diseases including those of neurological origin. A recent report in murine model proposed that IVIG expands regulatory T (Treg) cells via induction of interleukin 33 (IL-33). However, translational insight on these observations is lacking.Methods: Ten newly diagnosed Guillain-Barré syndrome (GBS) patients were treated with IVIG at the rate of 0.4 g/kg for three to five consecutive days. Clinical evaluation for muscular weakness was performed by Medical Research Council (MRC) and modified Rankin scoring (MRS) system. Heparinized blood samples were collected before and 1, 2, and 4–5 weeks post-IVIG therapy. Peripheral blood mononuclear cells were stained for surface CD4 and intracellular Foxp3, IFN-γ, and tumor necrosis factor alpha (TNF-α) and were analyzed by flow cytometry. IL-33 and prostaglandin E2 in the plasma were measured by ELISA.Results: The fold changes in plasma IL-33 at week 1 showed no correlation with the MRC and MRS scores at weeks 1, 2, and ≥4 post-IVIG therapy. Clinical recovery following IVIG therapy appears to be associated with Treg cell response. Contrary to murine study, there was no association between the fold changes in IL-33 at week 1 and Treg cell frequency at weeks 1, 2, and ≥4 post-IVIG therapy. Treg cell-mediated clinical response to IVIG therapy in GBS patients was associated with reciprocal regulation of effector T cells-expressing TNF-α.Conclusion: Treg cell expansion by IVIG in patients with autoimmune diseases lack correlation with IL-33. Treg cell frequency, but not plasma IL-33 levels, represents potential immunological biomarker to predict clinical response to IVIG therapy.

Mobile Ad-hoc Network (MANET) consists of many wireless mobile nodes that temporally constitute a dynamic infrastructure less network. To enable communication between nodes that do not have direct contact, each node must function as a wireless access point and potentially forward data traffic on behalf of the other nodes present in the network. Due to limitation of resources with these Mobile nodes the property of selfishness is exhibited. A technique system level based Cooperation of Node Fairness in Dynamic Ad hoc Network that promise to detect and nullify the effect of selfish nodes on the basis of monitoring, assigning reputation measure to every node and isolation of the detected misbehaving nodes. Previously, this scheme was implemented in GloMoSim simulator using unicast protocol and the idea is to integrate the CONFIDANT protocol with multicast protocol, so that the network performance can be boosted. In this paper, we suggest a M-CONFIDANT: A Multicast based Cooperation of Node Fairness in Dynamic Ad hoc Network. This scheme integrates a multicast based MAODV protocol with the CONFDIANT protocol previously integrated with DSR protocol.

biometric system provides more efficient and reliable means of identity verification. By this biometric verification it can be decided whether print based identity verification system has been widely used in various applications like access control, two characteristics belongs to the same person or not. Human palm print images contain some unique objects that can easily identify people, which make it a very competitive topic in biometric research. This paper proposes a new method for human identification using palm print based biometrics. In this approach, first of all, the images of the palm are to be captured using digital camera. Then extract some special features for palm print images of human using image processing. Here special region based features are extracted that are more efficient. Dataset is to be created for using such features. Neural network is used here for the similarity matching. Back propagation algorithm is used here.

Existing soil nailing design methodologies are essentially based on limit equilibrium principles that together with a lumped factor of safety or a set of partial factors on the material parameters and loads account for uncertainties in design input parameter values. Recent trends in the development of design procedures for earth retaining structures are towards load and resistance factor design (LRFD). In the present study, a methodology for the use of LRFD in the context of soil-nail walls is proposed and a procedure to determine reliability-based load and resistance factors is illustrated for important strength limit states with reference to a 10 m high soil-nail wall. The need for separate partial factors for each limit state is highlighted, and the proposed factors are compared with those existing in the literature.

The maximum sampling rate of a continuous-time ΔΣ modulator is limited by quantizer delay. Most conventional delay compensation techniques address less than a clock cycle of delay. A technique previously proposed for compensating quantizer delays in excess of a clock cycle in bandpass modulators involves a parallel feedback path that bypasses the quantizer. We analyze this technique for low-pass modulators and show that sampling rates hitherto not possible can be achieved. Design tradeoffs are investigated, and simulation results showing the effectiveness of the technique are given.

Soil nailing technique is being widely used for stabilization of vertical cuts because of its economic, environment friendly and speedy construction. Global stability and lateral displacement are the two important stability criteria for the soil nail walls. The primary objective of the present study is to evaluate soil nail wall stability criteria under the influence of in-situ soil variability. Finite element based numerical experiments are performed in accordance with the methodology of 23 factorial design of experiments. Based on the analysis of the observations from numerical experiments, two regression models are developed, and used for reliability analyses of global stability and lateral displacement of the soil nail wall. A 10 m high prototype soil nail wall is considered for better understanding and to highlight the practical implications of the present study. Based on the study, lateral displacements beyond 0.10% of vertical wall height and variability of in-situ soil parameters are found to be critical from the stability criteria considerations of the soil nail wall.

In practice, field pullout testing of soil nails is a widely accepted method for the construction quality control and the performance assessment of soil nail walls. At the design stage, field pullout tests provide useful information about the design bond strength of the nail–soil interface, which is critical in the determination of minimum soil nail length. To obtain a reliable and representative estimate of the design bond strength, it is necessary to conduct a sufficient number of field pullout tests. This study demonstrates the use of the concepts of simple random sampling and stratified random sampling to assess the adequacy of the ultimate bond strength adopted for design based on the minimum recommended number of field pullout tests.

Field pullout testing of soil nails is identified as the appropriate method for studying the nail-soil interaction and assessing the performance of soil nail walls. The primary objective of this study is to highlight the importance and practical applications of field pullout tests in the design and performance assessment of soil nail walls. Bond strength of soil-nail interface is the essential parameter in the design of soil nail walls. Field pullout tests provide valuable inputs for the selection of appropriate design bond strength. In this paper, a reliability based methodology for the evaluation and selection of appropriate field pullout tests is proposed for the determination of the design bond strength. The proposed methodology is illustrated with reference to the field pullout tests on soil nails conducted at a local site.

In practice, numerical simulations of soil nail walls are often carried out to assess the performance and stability. In the present study, implications of the use of advanced soil models, such as hardening soil model and hardening soil with small-strain stiffness model to simulate the behavior of in situ soil on the overall response of simulated soil nail wall have been studied, and compared with respect to the analysis using conventional and most prevalently used Mohr-Coulomb soil model. Further, influence of the consideration of bending stiffness of soil nails on the simulation results has been examined. Results of the simulations indicated that the use of advanced models is desirable for cases of soil nail walls constructed in soft soils and when lateral wall displacements are critical to the adjoining structures. Incorporation of bending stiffness of nails is found important from the consideration of facing failure modes of soil nail walls.

In India, rural roads are constantly being constructed. To ensure proper design of rural roads, it is desirable to have an appropriate selection of design parameters. The California bearing ratio (CBR) method of pavement design is the most commonly used method employed for the foundation design of rural roads. In the CBR method, the CBR value of the subgrade soil is critical in deciding the overall thickness of the pavement. Additionally, for good drainage, a typical specification for the pavement foundation design requires the value of permeability coefficient of the subgrade material to be specified. Thus, permeability and CBR constitute two important parameters in the design and assessment of long-term performance of the pavement. In this study, laboratory investigation has been carried out on a number of soil samples procured from a roadwork project site. Preliminary tests, such as index tests and particle size distribution tests, useful for soil classification, were followed by light compaction, CBR ...

Lateral displacement and global stability are the two main stability criteria for soil nail walls. Conventional design methods do not adequately address the deformation behaviour of soil nail walls, owing to the complexity involved in handling a large number of influencing factors. Consequently, limited methods of deformation estimates based on empirical relationships and in situ performance monitoring are available in the literature. It is therefore desirable that numerical techniques and statistical methods are used in order to gain a better insight into the deformation behaviour of soil nail walls. In the present study numerical experiments are conducted using a 24 factorial design method. Based on analysis of the maximum lateral deformation and factor-of-safety observations from the numerical experiments, regression models for maximum lateral deformation and factor-of-safety prediction are developed and checked for adequacy. Selection of suitable design factors for the 24 factorial design of numerical experiments enabled the use of the proposed regression models over a practical range of soil nail wall heights and in situ soil variability. It is evident from the model adequacy analyses and illustrative example that the proposed regression models provided a reasonably good estimate of the lateral deformation and global factor of safety of the soil nail walls.

In India, soil nail walls are being extensively used for supporting vertical excavations below ground level to accommodate construction of one-or two-storied basements. Generally, the depth of excavations for basement construction ranges from 10 m to 15 m. For such large depth of excavation, variability of in-situ soil properties has significant influence on the stability of the soil nail walls. In the present study, using reliability analysis, an attempt is made to study the influence of variability of in-situ soil properties on the stability of soil nail walls. For better understanding, a case of 10 m high soil nail wall constructed to support a vertical cut is considered for the study and its stability is evaluated for various failure modes. Additionally, the influence of correlation among soil parameters on soil nail wall stability is assessed. In-situ soil friction angle and correlation between in-situ soil cohesion and angle of friction are found to influence soil nail wall stability significantly. ...

The percentage of renewable energy sources such as solar, wind power and biomass in the energy mix of India is increasing every year. Solar power variability is an important issue for grid integration of solar photovoltaic power plants. The main objective of this paper is to forecast the power generated in a 5 MW solar PV plant owned by Gujarat Power Corporation Limited (GPCL) at Charanka solar park, Gujarat. Charanka is a location with an average of320 sunny days in a year. Average solar insolation available here is 5.7–6.0 kWh/m2 per day. Data obtained from 1st March 2014–31st August 2014 is used for analysis purposes. In this paper a two stage procedure is used referred to as GNN (Generalized Neural Network) model. In the primary stage pre-processing is done on the raw data followed by neural network model for forecasting.

The paper highlights the use of back analyses as a means to analyze the failures that frequently occurs in geotechnical engineering. The importance of in situ conditions, investigations, techniques, inputs complexity of the problem in terms of three-dimensional effects, etc., in the field of forensic studies in geotechnical engineering is highlighted.

In addition to its role in innate immunity, the intracellular pathogen sensor nucleotide-binding oligomerization domain 2 (NOD2) has been implicated in various inflammatory disorders, including the development of acute arthritis. However, the molecular mechanisms involved in the development of NOD2-responsive acute arthritis are not clear. In this study, we demonstrate that NOD2 signals to a cellular protein, Ly6/PLAUR domain–containing protein 6, in a receptor-interacting protein kinase 2–TGF-β–activated kinase 1–independent manner to activate the WNT signaling cascade. Gain- or loss-of-function of the WNT signaling pathway in an in vivo experimental mouse arthritis model or in vitro systems established the role for WNT-responsive X-linked inhibitor of apoptosis during the development of acute arthritis. Importantly, WNT-stimulated X-linked inhibitor of apoptosis mediates the activation of inflammasomes. The subsequent caspase-1 activation and IL-1β secretion together contribute to the phenotypic character of the inflammatory condition of acute arthritis. Thus, identification of a role for WNT-mediated inflammasome activation during NOD2 stimulation serves as a paradigm to understand NOD2-associated inflammatory disorders and develop novel therapeutics.

The primary aim of this paper is to analyze solar power variability. Ground-based measurements of solar photovoltaic power are used for the forecasting of 43-kW A-Si SPV system. In this study, we describe the variability in the power production of solar photovoltaic plant at IIT, Jodhpur. Solar PV generation forecasting is playing a key role in accurate solar power dispatchability as well as scheduling of PV power for hybrid power generation systems. The actual power produced by a PV power system varies according to variation in meteorological parameters and efficiency of PV system components. For the purpose of forecasting as per the schedule in the Indian power sector, a time slot of 15 min is considered for each forecasting. The proposed generalized neural network technique will be appropriated for modeling of solar power variability forecasting. In this paper, we used generalized neural network for forecasting the PV power variability.

The Indian Institute of Technology, Jodhpur (IITJ) has been monitoring and recording all the parameter of 101 kW (43.30 kW A-Si PV system located in Block 1 and 58.08 kW C-Si PV system in Block 2) grid tied solar photovoltaic system over the 4 year. The paper present the operational data 43.30 kW amorphous silicon (A-Si) based PV system located at Block 1 and 58.08 kW crystalline silicon based PV system at Block 2 of IIT Jodhpur. This paper helps in a study of the performance and consistency of this system. This paper will estimate the theoretical and actual Power output, Energy yield of the both PV systems. During the year, the PV systems in Jodhpur, India have generated a 74922 kWh by C-Si PV and 55910 kWh solar energy by A-Si PV system. As a whole, the location of Solar PV system is the primary reason of energy variability and system production.

Macrophages regulate cell fate decisions during microbial challenges by carefully titrating signaling events activated by innate receptors such as dectin-1 or Toll-like receptors (TLRs). Here, we demonstrate that dectin-1 activation robustly dampens TLR-induced proinflammatory signature in macrophages. Dectin-1 induced the stabilization of beta-catenin via spleen tyrosine kinase (Syk)-reactive oxygen species (ROS) signals, contributing to the expression of WNT5A. Subsequently, WNT5A-responsive protein inhibitors of activated STAT (PIAS-1) and suppressor of cytokine signaling 1 (SOCS-1) mediate the downregulation of IRAK-1, IRAK-4, and MyD88, resulting in decreased expression of interleukin 12 (IL-12), IL-1 beta, and tumor necrosis factor alpha (TNF-alpha). In vivo activation of dectin-1 with pathogenic fungi or ligand resulted in an increased bacterial burden of Mycobacteria, Klebsiella, Staphylococcus, or Escherichia, with a concomitant decrease in TLR-triggered proinflammatory cytokines. All together, our study establishes a new role for dectin-1-responsive inhibitory mechanisms employed by virulent fungi to limit the proinflammatory environment of the host.

The main objective of this paper is to perform data analysis of ground based measurement and review the state of the art of IIT Jodhpur Rooftop solar photovoltaic installed 101 kW system. Solar power forecasting is playing a key role in solar PV park installation, operation and accurate solar power dispatchability as well as scheduling. Solar Power varies with time and geographical locations and meteorological conditions such as ambient temperature, wind velocity, solar radiation and module temperature. The location of Solar PV system is the main reason of solar power variability. Solar variability totally depends on system losses (deterministic losses) and weather parameter (stochastic losses). In the case of solar power, deterministic losses can be found out accurately but stochastic losses are very uncertain and unpredicted in nature. The proposed soft computing technique will be suitable for solar power forecasting modeling. In this paper Fuzzy theory, Adaptive Neuro-fuzzy interface system, artificial neural network and generalized neural network are used as powerful tool of solar power Forecasting. This soft computing cum nature inspired techniques are able to accurately and fast forecasting compared to conventional methods of forecasting. This is done analyzing the operational data of 101 kW PV systems (43.30 kW located in Block 1 and 58.08 kW in Block 2), during the year 2011.

Foamy macrophages (FM)s harbor lipid bodies that not only assist mycobacterial persistence within the granulomas but also are sites for intracellular signaling and inflammatory mediators which are essential for mycobacterial pathogenesis. However, molecular mechanisms that regulate intracellular lipid accumulation in FMs during mycobacterial infection are not clear. Here, we report for the first time that jumonji domain containing protein (JMJD)3, a demethylase of the repressive H3K27me3 mark, orchestrates the expression of M. tuberculosis H37Rv-, MDR-JAL2287-, H37Ra- and M. bovis BCG-induced genes essential for FM generation in a TLR2-dependent manner. Further, NOTCH1-responsive RNA-binding protein MUSASHI (MSI), targets a transcriptional repressor of JMJD3, Msx2-interacting nuclear target protein, to positively regulate infection-induced JMJD3 expression, FM generation and M2 phenotype. Investigations in in vivo murine models further substantiated these observations. Together, our study has attributed novel roles for JMJD3 and its regulators during mycobacterial infection that assist FM generation and fine-tune associated host immunity., Author Summary Foamy macrophages (FMs) not only provide a suitable survival niche for the mycobacteria in the granuloma but also are reservoirs for several inflammatory mediators that regulate mycobacterial pathogenesis. Hence, understanding the mechanisms that regulate infection-induced FM generation assumes importance. In this investigation, we present empirical evidence to support the role of host epigenetic mechanisms in generating FMs and thus facilitating mycobacterial persistence in vivo. We show that the signaling pathways that mediate mycobacteria-induced expression of JMJD3, a demethylase of the facultative repression mark, regulate the genes assisting in FM generation. Importantly, the identified pathway could largely contribute to the evasive responses during mycobacterial infection and suppression of such pathways during infection could confer stronger immunity. Together, these regulators could be potential candidates for host-directed therapies against mycobacterial infection.

In last few years, Renewable Energy is introduced as a alternative source of energy. Especially in Indian context solar Energy is an important issue and unlimited source of energy. However, solar radiation is varies with time and geographical locations and meteorological conditions. In this paper, artificial neural network and generalized neural network are used as a powerful tool for Renewable Energy Forecasting. With the help of metrological data such as wind velocity, solar irradiation, and temperature as input to the model we can predict the changes in generated solar power, which is very useful for integration of solar power into grid. In this paper these soft computing techniques are able to prediction the solar power generation accurately and fast compare to conventional methods of forecasting.

An 800MS/s CT ΔΣ ADC with 16MHz/32MHz bandwidths consumes 47.6mW from 1.8V and occupies 1mm2 in a 0.18µm CMOS process. The DR/SNR/SNDR for the two bandwidths are 75/67/65 dB and 64/57/57 dB respectively. Excess loop delay (ELD) of more than one cycle is compensated using a fast path outside the flash ADC. This and a low latency flash ADC and delay free DAC calibration result in the highest reported sampling rate in this process.

Background Increased incidence of lung cancer among pulmonary tuberculosis patients suggests mycobacteria-induced tumorigenic response in the host. The alveolar epithelial cells, candidate cells that form lung adenocarcinoma, constitute a niche for mycobacterial replication and infection. We thus explored the possible mechanism of M. bovis Bacillus Calmette-Guérin (BCG)-assisted tumorigenicity in type II epithelial cells, human lung adenocarcinoma A549 and other cancer cells. Methods Cancer cell lines originating from lung, colon, bladder, liver, breast, skin and cervix were treated with tumor necrosis factor (TNF)-α in presence or absence of BCG infection. p53, COP1 and sonic hedgehog (SHH) signaling markers were determined by immunoblotting and luciferase assays, and quantitative real time PCR was done for p53-responsive pro-apoptotic genes and SHH signaling markers. MTT assays and Annexin V staining were utilized to study apoptosis. Gain- and loss-of-function approaches were used to investigate the role for SHH and COP1 signaling during apoptosis. A549 xenografted mice were used to validate the contribution of BCG during TNF-α treatment. Results Here, we show that BCG inhibits TNF-α-mediated apoptosis in A549 cells via downregulation of p53 expression. Substantiating this observation, BCG rescued A549 xenografts from TNF-α-mediated tumor clearance in nude mice. Furthermore, activation of SHH signaling by BCG induced the expression of an E3 ubiquitin ligase, COP1. SHH-driven COP1 targeted p53, thereby facilitating downregulation of p53-responsive pro-apoptotic genes and inhibition of apoptosis. Similar effects of BCG could be shown for HCT116, T24, MNT-1, HepG2 and HELA cells but not for HCT116 p53-/- and MDA-MB-231 cells. Conclusion Our results not only highlight possible explanations for the coexistence of pulmonary tuberculosis and lung cancer but also address probable reasons for failure of BCG immunotherapy of cancers. Electronic supplementary material The online version of this article (doi:10.1186/1476-4598-13-210) contains supplementary material, which is available to authorized users.