A major role of coumarin-dependent ferric iron reduction in strategy I-type iron acquisition in Arabidopsis.

Many non-graminaceous species release various coumarins in response to iron (Fe) deficiency. However, the physiological relevance of these coumarins remains poorly understood. Here, we show that the three enzymes leading to sideretin biosynthesis co-exist in Arabidopsis (Arabidopsis thaliana) epidermal and cortical cells and that the shift to fraxetin at alkaline pH depends on MYB72-mediated repression of CYTOCHROME P450, FAMILY 82, SUBFAMILY C, POLYPEPTIDE 4 (CYP82C4). In vitro, only fraxetin and sideretin can reduce part of the Fe(III) that they mobilize. We demonstrate that coumarin-mediated Fe(III) reduction is critical under acidic conditions, as fraxetin and sideretin can complement the Fe(III)-chelate reductase mutant ferric reduction oxidase 2 (fro2), and disruption of coumarin biosynthesis in fro2 plants impairs Fe acquisition similar to in the Fe(II) uptake-deficient mutant iron-regulated transporter 1 (irt1). Disruption of sideretin biosynthesis in a fro2 cyp82C4-1 double mutant revealed that sideretin is the dominant chemical reductant that functions with FRO2 to mediate Fe(II) formation for root uptake. At alkaline pH, Fe(III) reduction by coumarins becomes almost negligible but fraxetin still sustains high Fe(III) mobilization, suggesting that its main function is to provide chelated Fe(III) for FRO2. Our study indicates that strategy-I plants link sideretin and fraxetin biosynthesis and secretion to external pH to recruit distinct coumarin chemical activities to maximize Fe acquisition according to prevailing soil pH conditions.

ExTreeM: Scalable Augmented Merge Tree Computation via Extremum Graphs.

Over the last decade merge trees have been proven to support a plethora of visualization and analysis tasks since they effectively abstract complex datasets. This paper describes the ExTreeM-Algorithm: A scalable algorithm for the computation of merge trees via extremum graphs. The core idea of ExTreeM is to first derive the extremum graph G of an input scalar field f defined on a cell complex K, and subsequently compute the unaugmented merge tree of f on G instead of K; which are equivalent. Any merge tree algorithm can be carried out significantly faster on G, since K in general contains substantially more cells than G. To further speed up computation, ExTreeM includes a tailored procedure to derive merge trees of extremum graphs. The computation of the fully augmented merge tree, i.e., a merge tree domain segmentation of K, can then be performed in an optional post-processing step. All steps of ExTreeM consist of procedures with high parallel efficiency, and we provide a formal proof of its correctness. Our experiments, performed on publicly available datasets, report a speedup of up to one order of magnitude over the state-of-the-art algorithms included in the TTK and VTK-m software libraries, while also requiring significantly less memory and exhibiting excellent scaling behavior.

Potassium and Calcium Channel Complexes as Novel Targets for Cancer Research.

The intracellular Ca2+ concentration is mainly controlled by Ca2+ channels. These channels form complexes with K+ channels, which function to amplify Ca2+ flux. In cancer cells, voltage-gated/voltage-dependent Ca2+ channels and non-voltage-gated/voltage-independent Ca2+ channels have been reported to interact with K+ channels such as Ca2+-activated K+ channels and voltage-gated K+ channels. These channels are activated by an increase in cytosolic Ca2+ concentration or by membrane depolarization, which induces membrane hyperpolarization, increasing the driving force for Ca2+ flux. These complexes, composed of K+ and Ca2+ channels, are regulated by several molecules including lipids (ether lipids and cholesterol), proteins (e.g. STIM), receptors (e.g. S1R/SIGMAR1), and peptides (e.g. LL-37) and can be targeted by monoclonal antibodies, making them novel targets for cancer research.

Optimization and Augmentation for Data Parallel Contour Trees.

Contour trees are used for topological data analysis in scientific visualization. While originally computed with serial algorithms, recent work has introduced a vector-parallel algorithm. However, this algorithm is relatively slow for fully augmented contour trees which are needed for many practical data analysis tasks. We therefore introduce a representation called the hyperstructure that enables efficient searches through the contour tree and use it to construct a fully augmented contour tree in data parallel, with performance on average 6 times faster than the state-of-the-art parallel algorithm in the TTK topological toolkit.

Deep Learning Segmentation of Complex Features in Atomic-Resolution Phase-Contrast Transmission Electron Microscopy Images.

Phase-contrast transmission electron microscopy (TEM) is a powerful tool for imaging the local atomic structure of materials. TEM has been used heavily in studies of defect structures of two-dimensional materials such as monolayer graphene due to its high dose efficiency. However, phase-contrast imaging can produce complex nonlinear contrast, even for weakly scattering samples. It is, therefore, difficult to develop fully automated analysis routines for phase-contrast TEM studies using conventional image processing tools. For automated analysis of large sample regions of graphene, one of the key problems is segmentation between the structure of interest and unwanted structures such as surface contaminant layers. In this study, we compare the performance of a conventional Bragg filtering method with a deep learning routine based on the U-Net architecture. We show that the deep learning method is more general, simpler to apply in practice, and produces more accurate and robust results than the conventional algorithm. We provide easily adaptable source code for all results in this paper and discuss potential applications for deep learning in fully automated TEM image analysis.

Synthetic alkyl-ether-lipid promotes TRPV2 channel trafficking trough PI3K/Akt-girdin axis in cancer cells and increases mammary tumour volume.

The Transient Receptor Potential Vanilloid type 2 (TRPV2) channel is highly selective for Ca2+ and can be activated by lipids, such as LysoPhosphatidylCholine (LPC). LPC analogues, such as the synthetic alkyl-ether-lipid edelfosine or the endogenous alkyl-ether-lipid Platelet Activating Factor (PAF), modulates ion channels in cancer cells. This opens the way to develop alkyl-ether-lipids for the modulation of TRPV2 in cancer. Here, we investigated the role of 2-Acetamido-2-Deoxy-l-O-Hexadecyl-rac-Glycero-3-PhosphatidylCholine (AD-HGPC), a new alkyl-ether-lipid (LPC analogue), on TRPV2 trafficking and its impact on Ca2+ -dependent cell migration. The effect of AD-HGPC on the TRPV2 channel and tumour process was further investigated using calcium imaging and an in vivo mouse model. Using molecular and pharmacological approaches, we dissected the mechanism implicated in alkyl-ether-lipids sensitive TRPV2 trafficking. We found that TRPV2 promotes constitutive Ca2+ entry, leading to migration of highly metastatic breast cancer cell lines through the PI3K/Akt-Girdin axis. AD-HGPC addresses the functional TRPV2 channel in the plasma membrane through Golgi stimulation and PI3K/Akt/Rac-dependent cytoskeletal reorganization, leading to constitutive Ca2+ entry and breast cancer cell migration (without affecting the development of metastasis), in a mouse model. We describe, for the first time, the biological role of a new alkyl-ether-lipid on TRPV2 channel trafficking in breast cancer cells and highlight the potential modulation of TRPV2 by alkyl-ether-lipids as a novel avenue for research in the treatment of metastatic cancer.

Scalable Contour Tree Computation by Data Parallel Peak Pruning.

As data sets grow to exascale, automated data analysis and visualization are increasingly important, to intermediate human understanding and to reduce demands on disk storage via in situ analysis. Trends in architecture of high performance computing systems necessitate analysis algorithms to make effective use of combinations of massively multicore and distributed systems. One of the principal analytic tools is the contour tree, which analyses relationships between contours to identify features of more than local importance. Unfortunately, the predominant algorithms for computing the contour tree are explicitly serial, and founded on serial metaphors, which has limited the scalability of this form of analysis. While there is some work on distributed contour tree computation, and separately on hybrid GPU-CPU computation, there is no efficient algorithm with strong formal guarantees on performance allied with fast practical performance. We report the first shared SMP algorithm for fully parallel contour tree computation, with formal guarantees of O(lg V lg t) parallel steps and O(V lg V) work for data with V samples and t contour tree supernodes, and implementations with more than 30× parallel speed up on both CPU using TBB and GPU using Thrust and up 70× speed up compared to the serial sweep and merge algorithm.

Importance of oxidation products in coumarin-mediated Fe(hydr)oxide mineral dissolution.

Due to the low iron solubility in alkaline soils, plants have evolved different iron acquisition strategies, which are either based on ferric iron reduction (strategy I) or complexation by phytosiderophores (strategy II). Recently, a prominent role of coumarins for iron acquisition has been discovered, but details of the respective mechanism remain unclear. Since coumarins may act as iron-binding ligands but also as reductants, various reaction sequences are possible, resulting in different iron species and oxidized coumarins. In this context, it is often overlooked that oxidized coumarins are not just byproducts of iron(III) reduction, but may be actively involved in further steps of iron mobilization. In order to verify this active role of oxidized coumarins in Fe(hydr)oxide dissolution, we complemented iron dissolution data with data of single coumarins (esculetin, scopoletin, fraxetin) and their oxidation products, as a function of time, pH, and mineral (goethite, lepidocrocite). Our results demonstrate that there are four different routes for coumarin oxidation, leading to quinones, dimers, hydroxylated coumarins, demethylated coumarins, and combinations of these. The time-dependent species pattern differs with respect to mineral, pH, and coumarin molecule. Oxidized coumarins are often more reactive than the original coumarins, explaining unexpected iron mobilization by scopoletin, which is demethylated to esculetin. Also oxidative hydroxylation and dimerization increase the number of phenolic groups and yield new chelating properties. Several iron-species are identified for the three coumarins. Since oxidation reactions are initiated directly at mineral surfaces, they are often very effective-but this does not always result in more iron mobilization.

Dynamic Nested Tracking Graphs.

This work describes an approach for the interactive visual analysis of large-scale simulations, where numerous superlevel set components and their evolution are of primary interest. The approach first derives, at simulation runtime, a specialized Cinema database that consists of images of component groups, and topological abstractions. This database is processed by a novel graph operation-based nested tracking graph algorithm (GO-NTG) that dynamically computes NTGs for component groups based on size, overlap, persistence, and level thresholds. The resulting NTGs are in turn used in a feature-centered visual analytics framework to query specific database elements and update feature parameters, facilitating flexible post hoc analysis.

Sulfated Glycoaminoglycans and Proteoglycan Syndecan-4 Are Involved in Membrane Fixation of LL-37 and Its Pro-Migratory Effect in Breast Cancer Cells.

Initially characterized by its antimicrobial activities, LL-37 has also been shown to significantly contribute to tumor development. On breast cancer cell lines, LL-37 increases intracellular calcium via the TRPV2 channel and their migration via the activation of PI3K/AKT signaling. Its all-d enantiomer d-LL-37 induces similar effects, which excludes a protein-protein interaction of LL-37 in a classic ligand-receptor manner. Its net charge of +6 gave rise to the hypothesis that the peptide uses the negative charges of sulfoglycans or sialic acids to facilitate its attachment to the cell membrane and to induce its activities. Whereas several vegetal lectins, specifically attaching to sialylated or sulfated structures, blocked the activities of LL-37 on both calcium increase and cell migration, several sialidases had no effect. However, the competitive use of free sulfated glycoaminoglycans (GAGs) as chrondroitin and heparin, or treatment of the cell surface with chondroitinase and heparinase resulted in an activity loss of 50-100% for LL-37. Concordant results were obtained by blocking the synthesis of GAGs with 4-Methylumbelliferyl-ß-d-xyloside, and by suppression of glycan sulfatation by sodium chlorate. Using a candidate approach by suppressing proteoglycan synthesis using RNA interference, syndecan-4 was shown to be required for the activities of LL-37 and its binding to the cell surface. This leads to the conclusion that syndecan-4, by means of sulfated GAGs, could act as a receptor for LL-37.

Multi-scale visual analysis of time-varying electrocorticography data via clustering of brain regions.

BACKGROUND: There exists a need for effective and easy-to-use software tools supporting the analysis of complex Electrocorticography (ECoG) data. Understanding how epileptic seizures develop or identifying diagnostic indicators for neurological diseases require the in-depth analysis of neural activity data from ECoG. Such data is multi-scale and is of high spatio-temporal resolution. Comprehensive analysis of this data should be supported by interactive visual analysis methods that allow a scientist to understand functional patterns at varying levels of granularity and comprehend its time-varying behavior. RESULTS: We introduce a novel multi-scale visual analysis system, ECoG ClusterFlow, for the detailed exploration of ECoG data. Our system detects and visualizes dynamic high-level structures, such as communities, derived from the time-varying connectivity network. The system supports two major views: 1) an overview summarizing the evolution of clusters over time and 2) an electrode view using hierarchical glyph-based design to visualize the propagation of clusters in their spatial, anatomical context. We present case studies that were performed in collaboration with neuroscientists and neurosurgeons using simulated and recorded epileptic seizure data to demonstrate our system's effectiveness. CONCLUSION: ECoG ClusterFlow supports the comparison of spatio-temporal patterns for specific time intervals and allows a user to utilize various clustering algorithms. Neuroscientists can identify the site of seizure genesis and its spatial progression during various the stages of a seizure. Our system serves as a fast and powerful means for the generation of preliminary hypotheses that can be used as a basis for subsequent application of rigorous statistical methods, with the ultimate goal being the clinical treatment of epileptogenic zones.

Apply or Die: On the Role and Assessment of Application Papers in Visualization.

Application-oriented papers provide an important way to invigorate and cross-pollinate the visualization field, but the exact criteria for judging an application paper's merit remain an open question. This article builds on a panel at the 2016 IEEE Visualization Conference entitled "Application Papers: What Are They, and How Should They Be Evaluated?" that sought to gain a better understanding of prevalent views in the visualization community. This article surveys current trends that favor application papers, reviews the benefits and contributions of this paper type, and discusses their assessment in the review process. It concludes with recommendations to ensure that the visualization community is more inclusive to application papers.

Brain Modulyzer: Interactive Visual Analysis of Functional Brain Connectivity.

We present Brain Modulyzer, an interactive visual exploration tool for functional magnetic resonance imaging (fMRI) brain scans, aimed at analyzing the correlation between different brain regions when resting or when performing mental tasks. Brain Modulyzer combines multiple coordinated views-such as heat maps, node link diagrams and anatomical views-using brushing and linking to provide an anatomical context for brain connectivity data. Integrating methods from graph theory and analysis, e.g., community detection and derived graph measures, makes it possible to explore the modular and hierarchical organization of functional brain networks. Providing immediate feedback by displaying analysis results instantaneously while changing parameters gives neuroscientists a powerful means to comprehend complex brain structure more effectively and efficiently and supports forming hypotheses that can then be validated via statistical analysis. To demonstrate the utility of our tool, we present two case studies-exploring progressive supranuclear palsy, as well as memory encoding and retrieval.

SK3/TRPC1/Orai1 complex regulates SOCE-dependent colon cancer cell migration: a novel opportunity to modulate anti-EGFR mAb action by the alkyl-lipid Ohmline.

BACKGROUND: Barely 10-20% of patients with metastatic colorectal cancer (mCRC) receive a clinical benefit from the use of anti-EGFR monoclonal antibodies (mAbs). We hypothesized that this could depends on their efficiency to reduce Store Operated Calcium Entry (SOCE) that are known to enhance cancer cells. RESULTS: In the present study, we demonstrate that SOCE promotes migration of colon cancer cell following the formation of a lipid raft ion channel complex composed of TRPC1/Orai1 and SK3 channels. Formation of this complex is stimulated by the phosphorylation of the reticular protein STIM1 by EGF and activation of the Akt pathway. Our data show that, in a positive feedback loop SOCE activates both Akt pathway and SK3 channel activity which lead to SOCE amplification. This amplification occurs through the activation of Rac1/Calpain mediated by Akt. We also show that Anti-EGFR mAbs can modulate SOCE and cancer cell migration through the Akt pathway. Interestingly, the alkyl-lipid Ohmline, which we previously showed to be an inhibitor of SK3 channel, can dissociated the lipid raft ion channel complex through decreased phosphorylation of Akt and modulation of mAbs action. CONCLUSIONS: This study demonstrates that the inhibition of the SOCE-dependent colon cancer cell migration trough SK3/TRPC1/Orai1 channel complex by the alkyl-lipid Ohmline may be a novel strategy to modulate Anti-EGFR mAb action in mCRC.

Activation of TRPV2 and BKCa channels by the LL-37 enantiomers stimulates calcium entry and migration of cancer cells.

Expression of the antimicrobial peptide hCAP18/LL-37 is associated to malignancy in various cancer forms, stimulating cell migration and metastasis. We report that LL-37 induces migration of three cancer cell lines by activating the TRPV2 calcium-permeable channel and recruiting it to pseudopodia through activation of the PI3K/AKT pathway. Ca2+ entry through TRPV2 cooperated with a K+ efflux through the BKCa channel. In a panel of human breast tumors, the expression of TRPV2 and LL-37 was found to be positively correlated. The D-enantiomer of LL-37 showed identical effects as the L-peptide, suggesting that no binding to a specific receptor was involved. LL-37 attached to caveolae and pseudopodia membranes and decreased membrane fluidity, suggesting that a modification of the physical properties of the lipid membrane bilayer was the underlying mechanism of its effects.

Comparative study of the oxidation behavior of sulfur-containing amino acids and glutathione by electrochemistry-mass spectrometry in the presence and absence of cisplatin.

Small sulfur-containing compounds are involved in several important biochemical processes, including-but not limited to-redox regulation and drug conjugation/detoxification. While methods for stable redox pairs of such compounds (thiols/disulfides) are available, analytical data on more labile and short-lived redox intermediates are scarce, due to highly challenging analytical requirements. In this study, we employ the direct combination of reagentless electrochemical oxidation and mass spectrometric (EC-MS) identification for monitoring oxidation reactions of cysteine, N-acetylcysteine, methionine, and glutathione under simulated physiological conditions (pH 7.4, 37 °C). For the first time, all theoretically expected redox intermediates-with only one exception-are detected simultaneously and in situ, including sulfenic, sulfinic, and sulfonic acids, disulfides, thiosulfinates, thiosulfonates, and sulfoxides. By monitoring the time/potential-dependent interconversion of sulfur species, mechanistic oxidation routes are confirmed and new reactions detected, e.g., sulfenamide formation due to reaction with ammonia from the buffer. Furthermore, our results demonstrate a highly significant impact of cisplatin on the redox reactivity of sulfur species. Namely, the amount of thiol oxidation to sulfonic acid via sulfenic and sulfinic acid intermediates is diminished for glutathione in the presence of cisplatin in favor of the disulfide formation, while for N-acetylcysteine the contrary applies. N-acetylcysteine is the only ligand which displays enhanced oxidation currents upon cisplatin addition, accompanied by increased levels of thiosulfinate and thiosulfonate species. This is traced back to thiol reactivity and highlights the important role of sulfenic acid intermediates, which may function as a switch between different oxidation routes.

In situ and in-transit analysis of cosmological simulations.

Modern cosmological simulations have reached the trillion-element scale, rendering data storage and subsequent analysis formidable tasks. To address this circumstance, we present a new MPI-parallel approach for analysis of simulation data while the simulation runs, as an alternative to the traditional workflow consisting of periodically saving large data sets to disk for subsequent 'offline' analysis. We demonstrate this approach in the compressible gasdynamics/N-body code Nyx, a hybrid MPI + OpenMP code based on the BoxLib framework, used for large-scale cosmological simulations. We have enabled on-the-fly workflows in two different ways: one is a straightforward approach consisting of all MPI processes periodically halting the main simulation and analyzing each component of data that they own ('in situ'). The other consists of partitioning processes into disjoint MPI groups, with one performing the simulation and periodically sending data to the other 'sidecar' group, which post-processes it while the simulation continues ('in-transit'). The two groups execute their tasks asynchronously, stopping only to synchronize when a new set of simulation data needs to be analyzed. For both the in situ and in-transit approaches, we experiment with two different analysis suites with distinct performance behavior: one which finds dark matter halos in the simulation using merge trees to calculate the mass contained within iso-density contours, and another which calculates probability distribution functions and power spectra of various fields in the simulation. Both are common analysis tasks for cosmology, and both result in summary statistics significantly smaller than the original data set. We study the behavior of each type of analysis in each workflow in order to determine the optimal configuration for the different data analysis algorithms.

Antimicrobial Peptide LL-37 Is Both a Substrate of Cathepsins S and K and a Selective Inhibitor of Cathepsin L.

Lung cysteine cathepsins B, K, L, and S contribute to physiological and pathological processes including degradation of antimicrobial peptides/proteins (AMPs) such as surfactant protein SP-A, lactoferrin, secretory leukocyte peptidase inhibitor, and beta-defensins-2 and -3. Substantial amounts of uncleaved LL-37, a 37-mer cationic AMP, were observed in the sputum of patients with cystic fibrosis (CF). Nevertheless LL-37 was degraded after prolonged incubation in CF sputum, and the hydrolysis was blocked by E-64, a selective inhibitor of cysteine proteases. Cathepsins K and S, expressed in human alveolar macrophages, thoroughly hydrolyzed LL-37 in vitro, whereas it competitively inhibited cathepsin L (Ki = 150 nM). Cleavage of LL-37 by cathepsins S and K impaired its antimicrobial activity against Pseudomonas aeruginosa and Staphylococcus aureus, in a time- and concentration-dependent manner. The exchange of residues 67 and 205 in the S2 pockets of cathepsins L (Leu67Tyr/Ala205Leu) and K (Tyr67Leu/Leu205Ala) switched the specificity of these mutants toward LL-37. Molecular modeling suggested that LL-37 interacted with the active site of cathepsin L in both forward (i.e., substrate-like) and reverse orientations with similar binding energies. Our data support the hypothesis that cysteine cathepsins modulate the innate immunity response by degrading distinct and representative members of the AMP family.

Lipid rafts, KCa/ClCa/Ca2+ channel complexes and EGFR signaling: Novel targets to reduce tumor development by lipids?

Membrane lipid rafts are distinct plasma membrane nanodomains that are enriched with cholesterol, sphingolipids and gangliosides, with occasional presence of saturated fatty acids and phospholipids containing saturated acyl chains. It is well known that they organize receptors (such as Epithelial Growth Factor Receptor), ion channels and their downstream acting molecules to regulate intracellular signaling pathways. Among them are Ca2+ signaling pathways, which are modified in tumor cells and inhibited upon membrane raft disruption. In addition to protein components, lipids from rafts also contribute to the organization and function of Ca2+ signaling microdomains. This article aims to focus on the lipid raft KCa/ClCa/Ca2+ channel complexes that regulate Ca2+ and EGFR signaling in cancer cells, and discusses the potential modification of these complexes by lipids as a novel therapeutic approach in tumor development. This article is part of a Special Issue entitled: Membrane channels and transporters in cancers.

Suppression of PPARß, and DHA treatment, inhibit NaV1.5 and NHE-1 pro-invasive activities.

Peroxisome proliferator-activated receptor ß (PPARß) and NaV1.5 voltage-gated sodium channels have independently been shown to regulate human breast cancer cell invasiveness. The n-3 polyunsaturated docosahexaenoic acid (DHA, 22:6n-3), a natural ligand of PPAR, is effective in increasing survival and chemotherapy efficacy in breast cancer patient with metastasis. DHA reduces breast cancer cell invasiveness and it also inhibits PPARß expression. We have shown previously that NaV1.5 promotes MDA-MB-231 breast cancer cells invasiveness by potentiating the activity of Na(+)/H(+) exchanger type 1 (NHE-1), the major regulator of H(+) efflux in these cells. We report here that DHA inhibited NaV1.5 current and NHE-1 activity in human breast cancer cells, and in turn reduced NaV1.5-dependent cancer cell invasiveness. For the first time, we show that antagonizing PPARß, or inhibiting its expression, reduced NaV1.5 mRNA and protein expression and NaV1.5 current, as well as NHE-1 activity and cell invasiveness. Consistent with these results, the DHA-induced reduction of both NaV1.5 expression and NHE-1 activity was abolished in cancer cells knocked-down for the expression of PPARß (shPPARß). This demonstrates a direct link between the inhibition of PPARß expression and the inhibition of Nav1.5/NHE-1 activities and breast cancer cell invasiveness. This study provides new mechanistic data advocating for the use of natural fatty acids such as DHA to block the development of breast cancer metastases.