Optimisation and analysis of streamwise-varying wall-normal blowing in a turbulent boundary layer

Skin-friction drag is a major engineering concern, with wide-ranging consequences across many industries. Active flow-control techniques targeted at minimising skin friction have the potential to significantly enhance aerodynamic efficiency, reduce operating costs, and assist in meeting emission targets. However, they are difficult to design and optimise. Furthermore, any performance benefits must be balanced against the input power required to drive the control. Bayesian optimisation is a technique that is ideally suited to problems with a moderate number of input dimensions and where the objective function is expensive to evaluate, such as with high-fidelity computational fluid dynamics simulations. In light of this, this work investigates the potential of low-intensity wall-normal blowing as a skin-friction drag reduction strategy for turbulent boundary layers by combining a high-order flow solver (Incompact3d) with a Bayesian optimisation framework. The optimisation campaign focuses on streamwise-varying wall-normal blowing, parameterised by a cubic spline. The inputs to be optimised are the amplitudes of the spline control points, whereas the objective function is the net-energy saving (NES), which accounts for both the skin-friction drag reduction and the input power required to drive the control (with the input power estimated from real-world data). The results of the optimisation campaign are mixed, with significant drag reduction reported but no improvement over the canonical case in terms of NES. Selected cases are chosen for further analysis and the drag reduction mechanisms and flow physics are highlighted. The results demonstrate that low-intensity wall-normal blowing is an effective strategy for skin-friction drag reduction and that Bayesian optimisation is an effective tool for optimising such strategies. Furthermore, the results show that even a minor improvement in the blowing efficiency of the device used in the present work will lead to meaningful NES

Doubling up on supersymmetry in the Higgs sector

We explore the possibility that physics at the TeV scale possesses approximate N =2 supersymmetry, which is reduced to the N =1 minimal supersymmetric extension of the Standard Model (MSSM) at the electroweak scale. This doubling of supersymmetry modifies the Higgs sector of the theory, with consequences for the masses, mixings and couplings of the MSSM Higgs bosons, whose phenomenological consequences we explore in this paper. The mass of the lightest neutral Higgs boson h is independent of tan β at the tree level, and the decoupling limit is realized whatever the values of the heavy Higgs boson masses. Radiative corrections to the top quark and stop squarks dominate over those due to particles in N = 2 gauge multiplets. We assume that these radiative corrections fix mh ≃ 125 GeV, whatever the masses of the other neutral Higgs bosons H, A, a scenario that we term the h2MSSM. Since the H, A bosons decouple from the W and Z bosons in the h2MSSM at tree level, only the LHC constraints on H, A and H± couplings to fermions are applicable. These and the indirect constraints from LHC measurements of h couplings are consistent with mA ≳ 200 GeV for tan β ∈ (2, 8) in the h2MSSM

Tumor-derived GDF-15 blocks LFA-1 dependent T cell recruitment and suppresses responses to anti-PD-1 treatment

Immune checkpoint blockade therapy is beneficial and even curative for some cancer patients. However, the majority don’t respond to immune therapy. Across different tumor types, pre-existing T cell infiltrates predict response to checkpoint-based immunotherapy. Based on in vitro pharmacological studies, mouse models and analyses of human melanoma patients, we show that the cytokine GDF-15 impairs LFA-1/β2-integrin-mediated adhesion of T cells to activated endothelial cells, which is a pre-requisite of T cell extravasation. In melanoma patients, GDF-15 serum levels strongly correlate with failure of PD-1-based immune checkpoint blockade therapy. Neutralization of GDF-15 improves both T cell trafficking and therapy efficiency in murine tumor models. Thus GDF-15, beside its known role in cancer-related anorexia and cachexia, emerges as a regulator of T cell extravasation into the tumor microenvironment, which provides an even stronger rationale for therapeutic anti-GDF-15 antibody development. Experimental cancer immunology and therap

Targeting of preexisting and induced breast cancer stem cells with trastuzumab and trastuzumab emtansine (T-DM1)

The antibody trastuzumab (Herceptin) has substantially improved overall survival for patients with aggressive HER2-positive breast cancer. However, about 70% of all treated patients will experience relapse or disease progression. This may be related to an insufficient targeting of the CD44(high)CD24(low) breast cancer stem cell subset, which is not only highly resistant to chemotherapy and radiotherapy but also a poor target for trastuzumab due to low HER2 surface expression. Hence, we explored whether the new antibody-drug conjugate T-DM1, which consists of the potent chemotherapeutic DM1 coupled to trastuzumab, could improve the targeting of these tumor-initiating or metastasis-initiating cells. To this aim, primary HER2-overexpressing tumor cells as well as HER2-positive and HER2-negative breast cancer cell lines were treated with T-DM1, and effects on survival, colony formation, gene and protein expression as well as antibody internalization were assessed. This revealed that CD44(high)CD24(low)HER2(low) stem cell-like breast cancer cells show high endocytic activity and are thus particularly sensitive towards the antibody-drug conjugate T-DM1. Consequently, preexisting CD44(high)CD24(low) cancer stem cells were depleted by concentrations of T-DM1 that did not affect the bulk of the tumor cells. Likewise, colony formation was efficiently suppressed. Moreover, when tumor cells were cocultured with natural killer cells, antibody-dependent cell-mediated cytotoxicity was enhanced, and EMT-mediated induction of stem cell-like properties was prevented in differentiated tumor cells. Thus our study reveals an unanticipated targeting of stem cell-like breast cancer cells by T-DM1 that may contribute to the clinical efficacy of this recently approved antibody-drug conjugate

Comparative Modeling and Analysis of Extremophilic D-Ala-D-Ala Carboxypeptidases

Understanding the molecular adaptations of organisms to extreme environments requires a comparative analysis of protein structure, function, and dynamics across species found in different environmental conditions. Computational studies can be particularly useful in this pursuit, allowing exploratory studies of large numbers of proteins under different thermal and chemical conditions that would be infeasible to carry out experimentally. Here, we perform such a study of the MEROPS family S11, S12, and S13 proteases from psychophilic, mesophilic, and thermophilic bacteria. Using a combination of protein structure prediction, atomistic molecular dynamics, and trajectory analysis, we examine both conserved features and trends across thermal groups. Our findings suggest a number of hypotheses for experimental investigation

Comparative Modeling and Analysis of Extremophilic D-Ala-D-Ala Carboxypeptidases

Understanding the molecular adaptations of organisms to extreme environments requires a comparative analysis of protein structure, function, and dynamics across species found in different environmental conditions. Computational studies can be particularly useful in this pursuit, allowing exploratory studies of large numbers of proteins under different thermal and chemical conditions that would be infeasible to carry out experimentally. Here, we perform such a study of the MEROPS family S11, S12, and S13 proteases from psychophilic, mesophilic, and thermophilic bacteria. Using a combination of protein structure prediction, atomistic molecular dynamics, and trajectory analysis, we examine both conserved features and trends across thermal groups. Our findings suggest a number of hypotheses for experimental investigation