Big-Data-Driven Materials Science and its FAIR Data Infrastructure

This chapter addresses the forth paradigm of materials research -- big-data driven materials science. Its concepts and state-of-the-art are described, and its challenges and chances are discussed. For furthering the field, Open Data and an all-embracing sharing, an efficient data infrastructure, and the rich ecosystem of computer codes used in the community are of critical importance. For shaping this forth paradigm and contributing to the development or discovery of improved and novel materials, data must be what is now called FAIR -- Findable, Accessible, Interoperable and Re-purposable/Re-usable. This sets the stage for advances of methods from artificial intelligence that operate on large data sets to find trends and patterns that cannot be obtained from individual calculations and not even directly from high-throughput studies. Recent progress is reviewed and demonstrated, and the chapter is concluded by a forward-looking perspective, addressing important not yet solved challenges.Comment: submitted to the Handbook of Materials Modeling (eds. S. Yip and W. Andreoni), Springer 2018/201

Intrinsic ripples in graphene

The stability of two-dimensional (2D) layers and membranes is subject of a long standing theoretical debate. According to the so called Mermin-Wagner theorem, long wavelength fluctuations destroy the long-range order for 2D crystals. Similarly, 2D membranes embedded in a 3D space have a tendency to be crumpled. These dangerous fluctuations can, however, be suppressed by anharmonic coupling between bending and stretching modes making that a two-dimensional membrane can exist but should present strong height fluctuations. The discovery of graphene, the first truly 2D crystal and the recent experimental observation of ripples in freely hanging graphene makes these issues especially important. Beside the academic interest, understanding the mechanisms of stability of graphene is crucial for understanding electronic transport in this material that is attracting so much interest for its unusual Dirac spectrum and electronic properties. Here we address the nature of these height fluctuations by means of straightforward atomistic Monte Carlo simulations based on a very accurate many-body interatomic potential for carbon. We find that ripples spontaneously appear due to thermal fluctuations with a size distribution peaked around 70 \AA which is compatible with experimental findings (50-100 \AA) but not with the current understanding of stability of flexible membranes. This unexpected result seems to be due to the multiplicity of chemical bonding in carbon.Comment: 14 pages, 6 figure

Building nonparametric nn-body force fields using Gaussian process regression

Constructing a classical potential suited to simulate a given atomic system is a remarkably difficult task. This chapter presents a framework under which this problem can be tackled, based on the Bayesian construction of nonparametric force fields of a given order using Gaussian process (GP) priors. The formalism of GP regression is first reviewed, particularly in relation to its application in learning local atomic energies and forces. For accurate regression it is fundamental to incorporate prior knowledge into the GP kernel function. To this end, this chapter details how properties of smoothness, invariance and interaction order of a force field can be encoded into corresponding kernel properties. A range of kernels is then proposed, possessing all the required properties and an adjustable parameter $n$ governing the interaction order modelled. The order $n$ best suited to describe a given system can be found automatically within the Bayesian framework by maximisation of the marginal likelihood. The procedure is first tested on a toy model of known interaction and later applied to two real materials described at the DFT level of accuracy. The models automatically selected for the two materials were found to be in agreement with physical intuition. More in general, it was found that lower order (simpler) models should be chosen when the data are not sufficient to resolve more complex interactions. Low $n$ GPs can be further sped up by orders of magnitude by constructing the corresponding tabulated force field, here named "MFF".Comment: 31 pages, 11 figures, book chapte

The Four types of Tregs in malignant lymphomas

Regulatory T cells (Tregs) are a specialized subpopulation of CD4+ T cells, which act to suppress the activation of other immune cells. Tregs represent important modulators for the interaction between lymphomas and host microenvironment. Lymphomas are a group of serious and frequently fatal malignant diseases of lymphocytes. Recent studies revealed that some lymphoma T cells might adopt a Treg profile. Assessment of Treg phenotypes and genotypes in patients may offer prediction of outcome in many types of lymphomas including diffuse large B-cell lymphoma, follicular lymphoma, cutaneous T cell lymphoma, and Hodgkin's lymphoma. Based on characterized roles of Tregs in lymphomas, we can categorize the various roles into four groups: (a) suppressor Tregs; (b) malignant Tregs; (c) direct tumor-killing Tregs; and (d) incompetent Tregs. The classification into four groups is significant in predicting prognosis and designing Tregs-based immunotherapies for treating lymphomas. In patients with lymphomas where Tregs serve either as suppressor Tregs or malignant Tregs, anti-tumor cytotoxicity is suppressed thus decreased numbers of Tregs are associated with a good prognosis. In contrast, in patients with lymphomas where Tregs serve as tumor-killing Tregs and incompetent Tregs, anti-tumor cytotoxicity is enhanced or anti-autoimmune Tregs activities are weakened thus increased numbers of Tregs are associated with a good prognosis and reduced numbers of Tregs are associated with a poor prognosis. However, the mechanisms underlying the various roles of Tregs in patients with lymphomas remain unknown. Therefore, further research is needed in this regard as well as the utility of Tregs as prognostic factors and therapy strategies in different lymphomas

Nanoscale Dynamics of Phase Flipping in Water near its Hypothesized Liquid-Liquid Critical Point

Achieving a coherent understanding of the many thermodynamic and dynamic anomalies of water is among the most important unsolved puzzles in physics, chemistry, and biology. One hypothesized explanation imagines the existence of a line of first order phase transitions separating two liquid phases and terminating at a novel "liquid-liquid" critical point in a region of low temperature ($T \approx 250 \rm{K}$) and high pressure ($P \approx 200 \rm{MPa}$). Here we analyze a common model of water, the ST2 model, and find that the entire system flips between liquid states of high and low density. Further, we find that in the critical region crystallites melt on a time scale of nanoseconds. We perform a finite-size scaling analysis that accurately locates both the liquid-liquid coexistence line and its associated liquid-liquid critical point.Comment: 22 pages, 5 figure

Liquid-liquid critical point in supercooled silicon

A novel liquid-liquid phase transition has been proposed and investigated in a wide variety of pure substances recently, including water, silica and silicon. From computer simulations using the Stillinger-Weber classical empirical potential, Sastry and Angell [1] demonstrated a first order liquid-liquid transition in supercooled silicon, subsequently supported by experimental and simulation studies. Here, we report evidence for a liquid-liquid critical end point at negative pressures, from computer simulations using the SW potential. Compressibilities exhibit a growing maximum upon lowering temperature below 1500 K and isotherms exhibit density discontinuities below 1120 K, at negative pressure. Below 1120 K, isotherms obtained from constant volume-temperature simulations exhibit non-monotonic, van der Waals-like behavior signaling a first order transition. We identify Tc ~ 1120 +/- 12 K, Pc -0.60 +/- 0.15 GPa as the critical temperature and pressure for the liquid-liquid critical point. The structure of the liquid changes dramatically upon decreasing the temperature and pressure. Diffusivities vary over 4 orders of magnitude, and exhibit anomalous pressure dependence near the critical point. A strong relationship between local geometry quantified by the coordination number, and diffusivity, is seen, suggesting that atomic mobility in both low and high density liquids can usefully be analyzed in terms of defects in the tetrahedral network structure. We have constructed the phase diagram of supercooled silicon. We identify the lines of compressibility, density extrema (maxima and minima) and the spinodal which reveal the interconnection between thermodynamic anomalies and the phase behaviour of the system as suggested in previous works [2-9]Comment: (to be published in revised form); small corrections to previous version; Nature Physics 201

Mechanisms of local immunosuppression in cutaneous melanoma

Cutaneous melanoma is highly immunogenic, yet primary melanomas and metastases develop successfully in otherwise immunocompetent patients. To investigate the local immunosuppressive microenvironment, we examined the presence of suppressor T lymphocytes and tolerising dendritic cells (DCs), the expression of immunosuppressive cytokines (IL-10, TGFβ1 and TGFβ2) and the enzyme indoleamine 2,3-dioxygenase (IDO) using qRT–PCR and immunohistochemistry in primary skin melanomas, negative and positive sentinel lymph nodes (SLN), and lymph nodes with advanced metastases. Our results indicate that tolerogenic DCs and suppressor T lymphocytes are present in melanoma at all stages of disease progression. They express transforming growth factor β receptor 1 (TGFβR1), and are therefore susceptible to TGFβ1 and TGFβ2 specifically expressed by primary melanoma. We found that expression of IDO and interleukin 10 (IL-10) increased with melanoma progression, with the highest concentration in positive SLN. We suggest that negative SLN contain immunosuppressive cells and cytokines, due to preconditioning by tolerogenic DCs migrating from the primary melanoma site to the SLN. In primary melanoma, TGFβ2 is likely to render peripheral DCs tolerogenic, while in lymph nodes IDO and TGFβ1 may have a major effect. This mechanism of tumour-associated immunosuppression may inhibit the immune response to the tumour and may explain the discrepancy between the induction of systemic immunity by anti-melanoma vaccines and their poor performance in the clinic

Treg Depletion Inhibits Efficacy of Cancer Immunotherapy: Implications for Clinical Trials

Regulatory T lymphocytes (Treg) infiltrate human glioblastoma (GBM); are involved in tumor progression and correlate with tumor grade. Transient elimination of Tregs using CD25 depleting antibodies (PC61) has been found to mediate GBM regression in preclinical models of brain tumors. Clinical trials that combine Treg depletion with tumor vaccination are underway to determine whether transient Treg depletion can enhance anti-tumor immune responses and improve long term survival in cancer patients.Using a syngeneic intracrabial glioblastoma (GBM) mouse model we show that systemic depletion of Tregs 15 days after tumor implantation using PC61 resulted in a decrease in Tregs present in tumors, draining lymph nodes and spleen and improved long-term survival (50% of mice survived >150 days). No improvement in survival was observed when Tregs were depleted 24 days after tumor implantation, suggesting that tumor burden is an important factor for determining efficacy of Treg depletion in clinical trials. In a T cell dependent model of brain tumor regression elicited by intratumoral delivery of adenoviral vectors (Ad) expressing Fms-like Tyrosine Kinase 3 ligand (Flt3L) and Herpes Simplex Type 1-Thymidine Kinase (TK) with ganciclovir (GCV), we demonstrate that administration of PC61 24 days after tumor implantation (7 days after treatment) inhibited T cell dependent tumor regression and long term survival. Further, depletion with PC61 completely inhibited clonal expansion of tumor antigen-specific T lymphocytes in response to the treatment.Our data demonstrate for the first time, that although Treg depletion inhibits the progression/eliminates GBM tumors, its efficacy is dependent on tumor burden. We conclude that this approach will be useful in a setting of minimal residual disease. Further, we also demonstrate that Treg depletion, using PC61 in combination with immunotherapy, inhibits clonal expansion of tumor antigen-specific T cells, suggesting that new, more specific targets to block Tregs will be necessary when used in combination with therapies that activate anti-tumor immunity

The Tumor-Immune Microenvironment and Response to Radiation Therapy

Chemotherapy and radiation therapy (RT) are standard therapeutic modalities for patients with cancer, including breast cancer. Historic studies examining tissue and cellular responses to RT have predominantly focused on damage caused to proliferating malignant cells leading to their death. However, there is increasing evidence that RT also leads to significant alterations in the tumor microenvironment, particularly with respect to effects on immune cells infiltrating tumors. This review focuses on tumor-associated immune cell responses following RT and discusses how immune responses may be modified to enhance durability and efficacy of RT

Histone deacetylase inhibitors: potential targets responsible for their anti-cancer effect

The histone deacetylase inhibitors (HDACi) have demonstrated anticancer efficacy across a range of malignancies, most impressively in the hematological cancers. It is uncertain whether this clinical efficacy is attributable predominantly to their ability to induce apoptosis and differentiation in the cancer cell, or to their ability to prime the cell to other pro-death stimuli such as those from the immune system. HDACi-induced apoptosis occurs through altered expression of genes encoding proteins in both intrinsic and extrinsic apoptotic pathways; through effects on the proteasome/aggresome systems; through the production of reactive oxygen species, possibly by directly inducing DNA damage; and through alterations in the tumor microenvironment. In addition HDACi increase the immunogenicity of tumor cells and modulate cytokine signaling and potentially T-cell polarization in ways that may contribute the anti-cancer effect in vivo. Here, we provide an overview of current thinking on the mechanisms of HDACi activity, with attention given to the hematological malignancies as well as scientific observations arising from the clinical trials. We also focus on the immune effects of these agents