Despite conventional treatment modalities, gallbladder cancer (GBC) remains a highly lethal malignancy. Prognostic biomarkers and effective adjuvant immunotherapy for GBC are not available. In the recent past, immunotherapeutic approaches targeting tumor associated inflammation have gained importance but the mediators of inflammatory circuit remain unexplored in GBC patients. In the current prospective study, we investigated the role of IL17 producing TCRcdand regulatory T cells (Tregs) in pathogenesis of GBC. Analysis by multi-color flow cytometry revealed that compared to healthy individuals (HI), Tcd17, Th17 and Tc17 cells were increased in peripheral blood mononuclear cells (PBMCs) and tumor infiltrating lymphocytes (TIL) of GBC patients. Tregs were decreased in PBMCs but increased in TILs of GBC patients. The suppressive potential of Tregs from GBC patients and HI were comparable. Serum cytokines profile of GBC patients showed elevated levels of cytokines (IL6, IL23 and IL1b) required for polarization and/or stabilization of IL17 producing cells. We demonstrated that Tcd17 cells migrate toward tumor bed using CXCL9-CXCR3 axis. IL17 secreted by Tcd17 induced productions of vascular endothelial growth factor and other angiogenesis related factors in GBC cells. Tcd17 cells promote vasculogenesis as studied by chick chorioallantoic membrane assay. Survival analysis showed that Tcd17, Th17 and Treg cells in peripheral blood were associated with poor survival of GBC patients. Our findings suggest that Tcd17 is a protumorigenic subtype of cdT cells which induces angiogenesis. Tcd17 may be considered as a predictive biomarker in GBC thus opening avenues for targeted therapies.

The tumor microenvironment is an important aspect of cancer biology that contributes to tumor initiation, tumor progression and responses to therapy. The composition and characteristics of the tumor microenvironment vary widely and are important in determining the anti-tumor immune response. Successful immunization requires activation of both innate and adaptive immunity. Generally, immune system is compromised in patients with cancer due to immune suppression, loss of tumor antigen expression and dysfunction of antigen presenting cells (APC). Thus, therapeutic immunization leading to cancer regression remains a significant challenge. Certain cells of the immune system, including dendritic cells (DCs) and gamma delta (γδ) T cells are capable of driving potent anti-tumor responses. The property of MHC-unrestricted cytotoxicity, high potential of cytokine release, tissue tropism and early activation in infections and malignant disease makes γδ T cells as an emerging candidate for immunotherapy. Various strategies are being developed to enhance anti-tumor immune responses of γδ T cells and DCs one of them is the use of novel adjuvants like toll like receptors (TLR) agonists, which enhance γδ T cell function directly or through DC activation, which has ability to prime γδ T cells. TLR agonists are being used clinically either alone or in combination with tumor antigens and has shown initial success in both enhancing immune responses and eliciting anti-tumor activity. TLR activated γδ T cells and DCs nurture each other’s activation. This provides a potent base for first line of defense and manipulation of the adaptive response against pathogens and cancer. The available data provides a strong rationale for initiating combinatorial therapy for the treatment of diseases and this review will summarize the application of adjuvants (TLRs) for boosting immune response of γδ T cells to treat cancer and infectious diseases and their use in combinatorial therapy.

In comparison to conventional αβT cells, γδT cells are considered as specialized T cells based on their contributions in regulating immune response. γδT cells sense early environmental signals and initiate local immune-surveillance. The development of functional subtypes of γδT cells takes place in the thymus but they also exhibit plasticity in response to the activating signals and cytokines encountered in the extrathymic region. Thymic development of Tγδ1 requires strong TCR, CD27, and Skint-1 signals. However, differentiation of IL17-producing γδT cells (Tγδ17) is independent of Skint-1 or CD27 but requires notch signaling along with IL6 and TGFβ cytokines in the presence of weak TCR signal. In response to cytokines like IL23, IL6, and IL1β, Tγδ17 outshine Th17 cells for early activation and IL17 secretion. Despite expressing similar repertoire of lineage transcriptional factors, cytokines, and chemokine receptors, Tγδ17 cells differ from Th17 in spatial and temporal fashion. There are compelling reasons to consider significant role of Tγδ17 cells in regulating inflammation and thereby disease outcome. Tγδ17 cells regulate mobilization of innate immune cells and induce keratinocytes to secrete anti-microbial peptides thus exhibiting protective functions in anti-microbial immunity. In contrast, dysregulated Tγδ17 cells inhibit Treg cells, exacerbate autoimmunity, and are also known to support carcinogenesis by enhancing angiogenesis. The mechanism associated with this dual behavior of Tγδ17 is not clear. To exploit, Tγδ17 cells for beneficial use requires comprehensive analysis of their biology. Here, we summarize the current understanding on the characteristics, development, and functions of Tγδ17 cells in various pathological scenarios.

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Road traffic injuries and deaths are a growing public health concern worldwide, majorly in developing countries. Brake failure constitutes to be one of the primary reasons for accidents. The majority of brake failures are caused due to overheating of the brakes, while wear of lining is another big share-holder. Early detection of such causes can prevent these accidents. This study puts forth a model that can be used for onboard monitoring of drum/disc temperature & lining/pad thickness by taking velocity & road inclination in real-time as inputs. Many quantities are interdependent and vary with respect to time/temperature. Therefore, an incremental approach is used. The model is implemented in the Simulink software. Many standard profiles are also fed to compare results for different terrains and driving conditions. The drivers can also be classified based on their driving behavior. The thermal model can give us an early warning about the brake overheating. This model can be used to study the energy distribution while braking. Researchers and designers can also use this model to study & optimize the brake system.

The use of Absorb BVS in this real-world experience was associated with very good immediate and medium-term clinical outcomes.

Real-space entanglement spectrum (RSES) of a quantum Hall (QH) wavefunction gives a natural route to infer the nature of its edge excitations. Computation of RSES becomes expensive with an increase in the number of particles and included Landau levels (LL). RSES can be efficiently computed using Monte Carlo (MC) methods for trial states that can be written as products of determinants such as the composite fermion (CF) and parton states. This computational efficiency also applies to the RSES of lowest Landau level (LLL) projected CF and parton states; however, LLL projection to be used here requires approximations that generalize the Jain Kamilla (JK) projection. This work is a careful study of how this approximation should be made. We identify the approximation closest in spirit to JK projection and perform tests of the approximations involved in the projection by comparing the MC results with the RSES obtained from computationally expensive but exact methods. We present the techniques and use them to calculate the exact RSES of the exact LLL projected bosonic Jain 2/3 state in bipartition of systems of sizes up to N = 24 on the sphere. For the lowest few angular momentum sectors of the RSES, we present evidence to show that MC results closely match the exact spectra. We also discuss other plausible projection schemes. We also calculate the exact RSES of the unprojected fermionic Jain 2/5 state obtained from the exact diagonalization of the Trugman-Kivelson Hamiltonian in the two lowest LLs on the sphere. By comparing with the RSES of the unprojected 2/5 state from Monte Carlo methods, we show that the latter is practically exact.

This paper deals with the optimal scheduling of public transport e-buses by considering charging rate, discharging rate of batteries, rest time between consecutive trips, and distance between charging stations & estimation of the minimum required charging time between consecutive trips considering given constraints of the journey, also explains how does it help in the optimized scheduling of electric buses.