Pharmacological levels of withaferin A (Withania somnifera) trigger clinically relevant anticancer effects specific to triple negative breast cancer cells

Withaferin A (WA) isolated from Withania somnifera (Ashwagandha) has recently become an attractive phytochemical under investigation in various preclinical studies for treatment of different cancer types. In the present study, a comparative pathway-based transcriptome analysis was applied in epithelial-like MCF-7 and triple negative mesenchymal MDA-MB-231 breast cancer cells exposed to different concentrations of WA which can be detected systemically in in vivo experiments. Whereas WA treatment demonstrated attenuation of multiple cancer hallmarks, the withanolide analogue Withanone (WN) did not exert any of the described effects at comparable concentrations. Pathway enrichment analysis revealed that WA targets specific cancer processes related to cell death, cell cycle and proliferation, which could be functionally validated by flow cytometry and real-time cell proliferation assays. WA also strongly decreased MDA-MB-231 invasion as determined by single-cell collagen invasion assay. This was further supported by decreased gene expression of extracellular matrix-degrading proteases (uPA, PLAT, ADAM8), cell adhesion molecules (integrins, laminins), pro-inflammatory mediators of the metastasis-promoting tumor microenvironment (TNFSF12, IL6, ANGPTL2, CSF1R) and concomitant increased expression of the validated breast cancer metastasis suppressor gene (BRMS1). In line with the transcriptional changes, nanomolar concentrations of WA significantly decreased protein levels and corresponding activity of uPA in MDA-MB-231 cell supernatant, further supporting its anti-metastatic properties. Finally, hierarchical clustering analysis of 84 chromatin writer-reader-eraser enzymes revealed that WA treatment of invasive mesenchymal MDA-MB-231 cells reprogrammed their transcription levels more similarly towards the pattern observed in non-invasive MCF-7 cells. In conclusion, taking into account that sub-cytotoxic concentrations of WA target multiple metastatic effectors in therapy-resistant triple negative breast cancer, WA-based therapeutic strategies targeting the uPA pathway hold promise for further (pre)clinical development to defeat aggressive metastatic breast cancer

Ion implantation in nanodiamonds: Size effect and energy dependence

Nanoparticles are ubiquitous in nature and are increasingly important for technology. They are subject to bombardment by ionizing radiation in a diverse range of environments. In particular, nanodiamonds represent a variety of nanoparticles of significant fundamental and applied interest. Here we present a combined experimental and computational study of the behaviour of nanodiamonds under irradiation by xenon ions. Unexpectedly, we observed a pronounced size effect on the radiation resistance of the nanodiamonds: particles larger than 8 nm behave similarly to macroscopic diamond (i.e. characterized by high radiation resistance) whereas smaller particles can be completely destroyed by a single impact from an ion in a defined energy range. This latter observation is explained by extreme heating of the nanodiamonds by the penetrating ion. The obtained results are not limited to nanodiamonds, making them of interest for several fields, putting constraints on processes for the controlled modification of nanodiamonds, on the survival of dust in astrophysical environments, and on the behaviour of actinides released from nuclear waste into the environment

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Disease- and age-related changes in histone acetylation at gene promoters in psychiatric disorders

Increasing evidence suggests that epigenetic factors have critical roles in gene regulation in neuropsychiatric disorders and in aging, both of which are typically associated with a wide range of gene expression abnormalities. Here, we have used chromatin immunoprecipitation-qPCR to measure levels of acetylated histone H3 at lysines 9/14 (ac-H3K9K14), two epigenetic marks associated with transcriptionally active chromatin, at the promoter regions of eight schizophrenia-related genes in n=82 postmortem prefrontal cortical samples from normal subjects and those with schizophrenia and bipolar disorder. We find that promoter-associated ac-H3K9K14 levels are correlated with gene expression levels, as measured by real-time qPCR for several genes, including, glutamic acid decarboxylase 1 (GAD1), 5-hydroxytryptamine receptor 2C (HTR2C), translocase of outer mitochondrial membrane 70 homolog A (TOMM70A) and protein phosphatase 1E (PPM1E). Ac-H3K9K14 levels of several of the genes tested were significantly negatively associated with age in normal subjects and those with bipolar disorder, but not in subjects with schizophrenia, whereby low levels of histone acetylation were observed in early age and throughout aging. Consistent with this observation, significant hypoacetylation of H3K9K14 was detected in young subjects with schizophrenia when compared with age-matched controls. Our results demonstrate that gene expression changes associated with psychiatric disease and aging result from epigenetic mechanisms involving histone acetylation. We further find that treatment with a histone deacetylase (HDAC) inhibitor alters the expression of several candidate genes for schizophrenia in mouse brain. These findings may have therapeutic implications for the clinical use of HDAC inhibitors in psychiatric disorders

The Timing of the Cognitive Cycle

We propose that human cognition consists of cascading cycles of recurring brain events. Each cognitive cycle senses the current situation, interprets it with reference to ongoing goals, and then selects an internal or external action in response. While most aspects of the cognitive cycle are unconscious, each cycle also yields a momentary “ignition” of conscious broadcasting. Neuroscientists have independently proposed ideas similar to the cognitive cycle, the fundamental hypothesis of the LIDA model of cognition. High-level cognition, such as deliberation, planning, etc., is typically enabled by multiple cognitive cycles. In this paper we describe a timing model LIDA's cognitive cycle. Based on empirical and simulation data we propose that an initial phase of perception (stimulus recognition) occurs 80–100 ms from stimulus onset under optimal conditions. It is followed by a conscious episode (broadcast) 200–280 ms after stimulus onset, and an action selection phase 60–110 ms from the start of the conscious phase. One cognitive cycle would therefore take 260–390 ms. The LIDA timing model is consistent with brain evidence indicating a fundamental role for a theta-gamma wave, spreading forward from sensory cortices to rostral corticothalamic regions. This posteriofrontal theta-gamma wave may be experienced as a conscious perceptual event starting at 200–280 ms post stimulus. The action selection component of the cycle is proposed to involve frontal, striatal and cerebellar regions. Thus the cycle is inherently recurrent, as the anatomy of the thalamocortical system suggests. The LIDA model fits a large body of cognitive and neuroscientific evidence. Finally, we describe two LIDA-based software agents: the LIDA Reaction Time agent that simulates human performance in a simple reaction time task, and the LIDA Allport agent which models phenomenal simultaneity within timeframes comparable to human subjects. While there are many models of reaction time performance, these results fall naturally out of a biologically and computationally plausible cognitive architecture

TRY plant trait database - enhanced coverage and open access

Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

First measurement of the |t|-dependence of coherent J/ψ photonuclear production

The first measurement of the cross section for coherent J/ψ photoproduction as a function of |t|, the square of the momentum transferred between the incoming and outgoing target nucleus, is presented. The data were measured with the ALICE detector in ultra-peripheral Pb–Pb collisions at a centre-of-mass energy per nucleon pair sNN=5.02TeV with the J/ψ produced in the central rapidity region |y|<0.8, which corresponds to the small Bjorken-x range (0.3−1.4)×10−3. The measured |t|-dependence is not described by computations based only on the Pb nuclear form factor, while the photonuclear cross section is better reproduced by models including shadowing according to the leading-twist approximation, or gluon-saturation effects from the impact-parameter dependent Balitsky–Kovchegov equation. These new results are therefore a valid tool to constrain the relevant model parameters and to investigate the transverse gluonic structure at very low Bjorken-x.publishedVersio

Particle identification in ALICE : a Bayesian approach

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