TRPM8 is required for survival and radioresistance of glioblastoma cells

TRPM8 is a Ca$^{2+}$-permeable nonselective cation channel belonging to the melastatin sub-group of the transient receptor potential (TRP) family. TRPM8 is aberrantly overexpressed in a variety of tumor entities including glioblastoma multiforme where it reportedly contributes to tumor invasion. The present study aimed to disclose further functions of TRPM8 in glioma biology in particular upon cell injury by ionizing radiation. To this end, TCGA data base was queried to expose the TRPM8 mRNA abundance in human glioblastoma specimens and immunoblotting was performed to analyze the TRPM8 protein abundance in primary cultures of human glioblastoma. Moreover, human glioblastoma cell lines were irradiated with 6 MV photons and TRPM8 channels were targeted pharmacologically or by RNA interference. TRPM8 abundance, Ca$^{2+}$ signaling and resulting K$^{+}$ channel activity, chemotaxis, cell migration, clonogenic survival, DNA repair, apoptotic cell death, and cell cycle control were determined by qRT-PCR, fura-2 Ca$^{2+}$ imaging, patch-clamp recording, transfilter migration assay, wound healing assay, colony formation assay, immunohistology, flow cytometry, and immunoblotting. As a result, human glioblastoma upregulates TRPM8 channels to variable extent. TRPM8 inhibition or knockdown slowed down cell migration and chemotaxis, attenuated DNA repair and clonogenic survival, triggered apoptotic cell death, impaired cell cycle and radiosensitized glioblastoma cells. Mechanistically, ionizing radiation activated and upregulated TRPM8-mediated Ca$^{2+}$ signaling that interfered with cell cycle control probably via CaMKII, cdc25C and cdc2. Combined, our data suggest that TRPM8 channels contribute to spreading, survival and radioresistance of human glioblastoma and, therefore, might represent a promising target in future anti-glioblastoma therapy

Probabilistic Bisimulation: Naturally on Distributions

In contrast to the usual understanding of probabilistic systems as stochastic processes, recently these systems have also been regarded as transformers of probabilities. In this paper, we give a natural definition of strong bisimulation for probabilistic systems corresponding to this view that treats probability distributions as first-class citizens. Our definition applies in the same way to discrete systems as well as to systems with uncountable state and action spaces. Several examples demonstrate that our definition refines the understanding of behavioural equivalences of probabilistic systems. In particular, it solves a long-standing open problem concerning the representation of memoryless continuous time by memory-full continuous time. Finally, we give algorithms for computing this bisimulation not only for finite but also for classes of uncountably infinite systems

Role of synovial fibroblast subsets across synovial pathotypes in rheumatoid arthritis: a deconvolution analysis

OBJECTIVES: To integrate published single-cell RNA sequencing (scRNA-seq) data and assess the contribution of synovial fibroblast (SF) subsets to synovial pathotypes and respective clinical characteristics in treatment-naïve early arthritis. METHODS: In this in silico study, we integrated scRNA-seq data from published studies with additional unpublished in-house data. Standard Seurat, Harmony and Liger workflow was performed for integration and differential gene expression analysis. We estimated single cell type proportions in bulk RNA-seq data (deconvolution) from synovial tissue from 87 treatment-naïve early arthritis patients in the Pathobiology of Early Arthritis Cohort using MuSiC. SF proportions across synovial pathotypes (fibroid, lymphoid and myeloid) and relationship of disease activity measurements across different synovial pathotypes were assessed. RESULTS: We identified four SF clusters with respective marker genes: PRG4(+) SF (CD55, MMP3, PRG4, THY1(neg)); CXCL12(+) SF (CXCL12, CCL2, ADAMTS1, THY1(low)); POSTN(+) SF (POSTN, collagen genes, THY1); CXCL14(+) SF (CXCL14, C3, CD34, ASPN, THY1) that correspond to lining (PRG4(+) SF) and sublining (CXCL12(+) SF, POSTN(+) + and CXCL14(+) SF) SF subsets. CXCL12(+) SF and POSTN(+) + were most prominent in the fibroid while PRG4(+) SF appeared highest in the myeloid pathotype. Corresponding, lining assessed by histology (assessed by Krenn-Score) was thicker in the myeloid, but also in the lymphoid pathotype + the fibroid pathotype. PRG4(+) SF correlated positively with disease severity parameters in the fibroid, POSTN(+) SF in the lymphoid pathotype whereas CXCL14(+) SF showed negative association with disease severity in all pathotypes. CONCLUSION: This study shows a so far unexplored association between distinct synovial pathologies and SF subtypes defined by scRNA-seq. The knowledge of the diverse interplay of SF with immune cells will advance opportunities for tailored targeted treatments

Orbits and phase transitions in the multifractal spectrum

We consider the one dimensional classical Ising model in a symmetric dichotomous random field. The problem is reduced to a random iterated function system for an effective field. The D_q-spectrum of the invariant measure of this effective field exhibits a sharp drop of all D_q with q < 0 at some critical strength of the random field. We introduce the concept of orbits which naturally group the points of the support of the invariant measure. We then show that the pointwise dimension at all points of an orbit has the same value and calculate it for a class of periodic orbits and their so-called offshoots as well as for generic orbits in the non-overlapping case. The sharp drop in the D_q-spectrum is analytically explained by a drastic change of the scaling properties of the measure near the points of a certain periodic orbit at a critical strength of the random field which is explicitly given. A similar drastic change near the points of a special family of periodic orbits explains a second, hitherto unnoticed transition in the D_q-spectrum. As it turns out, a decisive role in this mechanism is played by a specific offshoot. We furthermore give rigorous upper and/or lower bounds on all D_q in a wide parameter range. In most cases the numerically obtained D_q coincide with either the upper or the lower bound. The results in this paper are relevant for the understanding of random iterated function systems in the case of moderate overlap in which periodic orbits with weak singularity can play a decisive role.Comment: The article has been completely rewritten; the title has changed; a section about the typical pointwise dimension as well as several references and remarks about more general systems have been added; to appear in J. Phys. A; 25 pages, 11 figures, LaTeX2

Computational modelling of wound healing insights to develop new treatments

About 1% of the population will suffer a severe wound during their life. Thus, it is really important to develop new techniques in order to properly treat these injuries due to the high socioeconomically impact they suppose. Skin substitutes and pressure based therapies are currently the most promising techniques to heal these injuries. Nevertheless, we are still far from finding a definitive skin substitute for the treatment of all chronic wounds. As a first step in developing new tissue engineering tools and treatment techniques for wound healing, in silico models could help in understanding the mechanisms and factors implicated in wound healing. Here, we review mathematical models of wound healing. These models include different tissue and cell types involved in healing, as well as biochemical and mechanical factors which determine this process. Special attention is paid to the contraction mechanism of cells as an answer to the tissue mechanical state. Other cell processes such as differentiation and proliferation are also included in the models together with extracellular matrix production. The results obtained show the dependency of the success of wound healing on tissue composition and the importance of the different biomechanical and biochemical factors. This could help to individuate the adequate concentration of growth factors to accelerate healing and also the best mechanical properties of the new skin substitute depending on the wound location in the body and its size and shape. Thus, the feedback loop of computational models, experimental works and tissue engineering could help to identify the key features in the design of new treatments to heal severe wounds

CD8+ T Cells as a Source of IFN-γ Production in Human Cutaneous Leishmaniasis

Cutaneous leishmaniasis (CL) is usually a self-healing skin lesion caused by different species of Leishmania parasite. Resistance and susceptibility of mice to Leishmania major infection is associated with two types of CD4+ T lymphocytes development: Th1 type response with production of cytokine IFN-γ is associated with resistance, whereas Th2 type response with production of cytokines IL-4 and IL-5 is associated with susceptibility. A clear Th1/Th2 dichotomy similar to murine model is not defined in human leishmaniasis and we need as much information as possible to define marker(s) of protection. We purified CD4+/CD8+ T cells, stimulated them with Leishmania antigens and analysed gene and protein expression of Th1/Th2 cytokines in volunteers with a history of self-healing CL who are presumed to be protected against further Leishmania infection. We have seen significant upregulation of IFN-γ gene expression and high IFN-γ production in the Leishmania stimulated CD4+ T cells and CD8+ T cells. We concluded that both antigen-specific IFN-γ producing CD4+ Th1 cells and IFN-γ producing CD8+ T cells contribute to the long term protection in individuals with a history of CL. This proves the importance of CD8+ T cells as a source of IFN-γ in Th1-like immune responses

Strategic Business Plan Based on Total Quality Management for Property-Marketing Small Enterprises in UK

NoThe chapter investigates the property marketing enterprises in northern England, UK, through examination of the Macro/Micro environments and using standard evaluation of the Strengths, Weaknesses, Opportunities and Threat (SWOT)factors and the Political, Economic, Social and Technological, Environmental (ecological) and Legal (PESTEL) factors, and five forces analyses in order to explore the enterprise's standing within the market place. The PESTEL analysis provides a ‘Big Picture' of the environments in which the small enterprises operate along with identifying key strategic opportunities and threats. Insights gained here will allow entrepreneurs to take advantage of the opportunities and minimise the threats. The research methodology is examined through a real case study in a small enterprise company called Property-Marketing Company based in the UK. The findings show that the small firm seem to be in a strong sustainable position within the regional property marketing segment, and have the potential to expand. The findings also reveal that the entrepreneur's goals are reasonably well established whereas they currently suffer from the lack of a strategic plan to achieve their goals. The project aims to provide a strategic business plan for the company under study with an effective process flow in order to maximise available time, and a strategic plan of how to grow the business

A price-based adaptive task allocation for wireless sensor network

10.1109/MOBHOC.2009.53370392009 IEEE 6th International Conference on Mobile Adhoc and Sensor Systems, MASS '09888-89