Reconstructing the free-energy landscape of Met-enkephalin using dihedral Principal Component Analysis and Well-tempered Metadynamics

Well-Tempered Metadynamics (WTmetaD) is an efficient method to enhance the reconstruction of the free-energy surface of proteins. WTmetaD guarantees a faster convergence in the long time limit in comparison with the standard metadynamics. It still suffers however from the same limitation, i.e. the non trivial choice of pertinent collective variables (CVs). To circumvent this problem, we couple WTmetaD with a set of CVs generated from a dihedral Principal Component Analysis (dPCA) on the Ramachadran dihedral angles describing the backbone structure of the protein. The dPCA provides a generic method to extract relevant CVs built from internal coordinates. We illustrate the robustness of this method in the case of the small and very diffusive Metenkephalin pentapeptide, and highlight a criterion to limit the number of CVs necessary to biased the metadynamics simulation. The free-energy landscape (FEL) of Met-enkephalin built on CVs generated from dPCA is found rugged compared with the FEL built on CVs extracted from PCA of the Cartesian coordinates of the atoms.Comment: 17 pages, 9 figures (4 in color

Interactive Training System for Interventional Electrocardiology Procedures

International audienceRecent progress in cardiac catheterization and devices al-lowed to develop new therapies for severe cardiac diseases like arrhyth-mias and heart failure. The skills required for such interventions are still very challenging to learn, and typically acquired over several years. Vir-tual reality simulators can reduce this burden by allowing to practice such procedures without consequences on patients. In this paper, we propose the first training system dedicated to cardiac electrophysiology, includ-ing pacing and ablation procedures. Our framework involves an efficient GPU-based electrophysiological model. Thanks to an innovative mul-tithreading approach, we reach high computational performances that allow to account for user interactions in real-time. Based on a scenario of cardiac arrhythmia, we demonstrate the ability of the user-guided simulator to navigate inside vessels and cardiac cavities with a catheter and to reproduce an ablation procedure involving: extra-cellular poten-tial measurements, endocardial surface reconstruction, electrophysiology mapping, radio-frequency (RF) ablation, as well as electrical stimulation. This works is a step towards computerized medical learning curriculum

Human Salmonella Typhi exposure generates differential multifunctional cross‐reactive T‐cell memory responses against Salmonella Paratyphi and invasive nontyphoidal Salmonella

Objective There are no vaccines for most of the major invasive Salmonella strains causing severe infection in humans. We evaluated the specificity of adaptive T memory cell responses generated after Salmonella Typhi exposure in humans against other major invasive Salmonella strains sharing capacity for dissemination. Methods T memory cells from eleven volunteers who underwent controlled oral challenge with wt S. Typhi were characterised by flow cytometry for cross‐reactive cellular cytokine/chemokine effector responses or evidence of degranulation upon stimulation with autologous B‐lymphoblastoid cells infected with either S. Typhi, Salmonella Paratyphi A (PA), S. Paratyphi B (PB) or an invasive nontyphoidal Salmonella strain of the S. Typhimurium serovar (iNTSTy). Results Blood T‐cell effector memory (TEM) responses after exposure to S. Typhi in humans evolve late, peaking weeks after infection in most volunteers. Induced multifunctional CD4+ Th1 and CD8+ TEM cells elicited after S. Typhi challenge were cross‐reactive with PA, PB and iNTSTy. The magnitude of multifunctional CD4+ TEM cell responses to S. Typhi correlated with induction of cross‐reactive multifunctional CD8+ TEM cells against PA, PB and iNTSTy. Highly multifunctional subsets and T central memory and T effector memory cells that re‐express CD45 (TEMRA) demonstrated less heterologous T‐cell cross‐reactivity, and multifunctional Th17 elicited after S. Typhi challenge was not cross‐reactive against other invasive Salmonella. Conclusion Gaps in cross‐reactive immune effector functions in human T‐cell memory compartments were highly dependent on invasive Salmonella strain, underscoring the importance of strain‐dependent vaccination in the design of T‐cell‐based vaccines for invasive Salmonella

EP-Net: Learning Cardiac Electrophysiology Models for Physiology-based Constraints in Data-Driven Predictions

International audienceCardiac electrophysiology (EP) models achieved good progress in simulating cardiac electrical activity. However numerical issues and computational times hamper clinical applicability of such models. Moreover , personalisation can still be challenging and model errors can be difficult to overcome. On the other hand, deep learning methods achieved impressive results but suffer from robustness issues in healthcare due to their lack of physiological knowledge. We propose a novel approach which is based on deep learning in order to replace numerical integration of partial differential equations. This has the advantage to directly learn spatio-temporal correlations, which increases stability. Moreover, once trained, solutions are very fast to compute. We present first results in state estimation based on few measurements and evaluate the forecasting power of the trained network. The proposed method performed very well on this preliminary evaluation. It opens up possibilities towards data-driven personalisation, to overcome model error by learning from the data

Automatic coronary calcium scoring in chest CT using a deep neural network in direct comparison with non-contrast cardiac CT:A validation study

Purpose: To evaluate deep-learning based calcium quantification on Chest CT scans compared with manual evaluation, and to enable interpretation in terms of the traditional Agatston score on dedicated Cardiac CT. Methods: Automated calcium quantification was performed using a combination of deep-learning convolution neural networks with a ResNet-architecture for image features and a fully connected neural network for spatial coordinate features. Calcifications were identified automatically, after which the algorithm automatically excluded all non-coronary calcifications using coronary probability maps and aortic segmentation. The algorithm was first trained on cardiac-CTs and refined on non-triggered chest-CTs. This study used on 95 patients (cohort 1), who underwent both dedicated calcium scoring and chest-CT acquisitions using the Agatston score as reference standard and 168 patients (cohort 2) who underwent chest-CT only using qualitative expert assessment for external validation. Results from the deep-learning model were compared to Agatston-scores(cardiac-CTs) and manually determined calcium volumes(chest-CTs) and risk classifications. Results: In cohort 1, the Agatston score and AI determined calcium volume shows high correlation with a correlation coefficient of 0.921(p < 0.001) and R-2 of 0.91. According to the Agatston categories, a total of 67(70 %) were correctly classified with a sensitivity of 91 % and specificity of 92 % in detecting presence of coronary calcifications. Manual determined calcium volume on chest-CT showed excellent correlation with the AI volumes with a correlation coefficient of 0.923(p < 0.001) and R-2 of 0.96, no significant difference was found (p = 0.247). According to qualitative risk classifications in cohort 2, 138(82 %) cases were correctly classified with a k-coefficient of 0.74, representing good agreement. All wrongly classified scans (30(18 %)) were attributed to an adjacent category. Conclusion: Artificial intelligence based calcium quantification on chest-CTs shows good correlation compared to reference standards. Fully automating this process may reduce evaluation time and potentially optimize clinical calcium scoring without additional acquisitions

Anticancer activity of an extract from needles and twigs of Taxus cuspidata and its synergistic effect as a cocktail with 5-fluorouracil

<p>Abstract</p> <p>Background</p> <p>Botanical medicines are increasingly combined with chemotherapeutics as anticancer drug cocktails. This study aimed to assess the chemotherapeutic potential of an extract of <it>Taxus cuspidata </it>(<it>TC</it>) needles and twigs produced by artificial cuttage and its co-effects as a cocktail with 5-fluorouracil (5-FU).</p> <p>Methods</p> <p>Components of <it>TC </it>extract were identified by HPLC fingerprinting. Cytotoxicity analysis was performed by MTT assay or ATP assay. Apoptosis studies were analyzed by H & E, PI, TUNEL staining, as well as Annexin V/PI assay. Cell cycle analysis was performed by flow cytometry. 5-FU concentrations in rat plasma were determined by HPLC and the pharmacokinetic parameters were estimated using 3p87 software. Synergistic efficacy was subjected to median effect analysis with the mutually nonexclusive model using Calcusyn1 software. The significance of differences between values was estimated by using a one-way ANOVA.</p> <p>Results</p> <p><it>TC </it>extract reached inhibition rates of 70-90% in different human cancer cell lines (HL-60, BGC-823, KB, Bel-7402, and HeLa) but only 5-7% in normal mouse T/B lymphocytes, demonstrating the broad-spectrum anticancer activity and low toxicity to normal cells of <it>TC </it>extract <it>in vitro</it>. <it>TC </it>extract inhibited cancer cell growth by inducing apoptosis and G₂/M cell cycle arrest. Most interestingly, <it>TC </it>extract and 5-FU, combined as a cocktail, synergistically inhibited the growth of cancer cells <it>in vitro</it>, with Combination Index values (CI) ranging from 0.90 to 0.26 at different effect levels from IC50 to IC90 in MCF-7 cells, CI ranging from 0.93 to 0.13 for IC40 to IC90 in PC-3M-1E8 cells, and CI < 1 in A549 cells. In addition, the cocktail had lower cytotoxicity in normal human cell (HEL) than 5-FU used alone. Furthermore, <it>TC </it>extract did not affect the pharmacokinetics of 5-FU in rats.</p> <p>Conclusions</p> <p>The combinational use of the <it>TC </it>extract with 5-FU displays strong cytotoxic synergy in cancer cells and low cytotoxicity in normal cells. These findings suggest that this cocktail may have a potential role in cancer treatment.</p

IgM Promotes the Clearance of Small Particles and Apoptotic Microparticles by Macrophages

Background: Antibodies are often involved in enhancing particle clearance by macrophages. Although the mechanisms of antibody-dependent phagocytosis have been studied for IgG in greater detail, very little is known about IgM-mediated clearance. It has been generally considered that IgM does not support phagocytosis. Recent studies indicate that natural IgM is important to clear microbes and other bioparticles, and that shape is critical to particle uptake by macrophages; however, the relevance of IgM and particle size in their clearance remains unclear. Here we show that IgM has a sizedependent effect on clearance. Methodology/Principal Findings: We used antibody-opsonized sheep red blood cells, different size beads and apoptotic cells to determine the effect of human and mouse IgM on phagocytosis by mouse alveolar macrophages. Our microscopy (light, epifluorescence, confocal) and flow cytometry data show that IgM greatly enhances the clearance of small particles (about 1–2 micron) by these macrophages. There is an inverse relationship between IgM-mediated clearance by macrophages and the particle size; however, macrophages bind and internalize many different size particles coated with IgG. We also show that IgM avidly binds to small size late apoptotic cells or bodies (2–5 micron) and apoptotic microparticles (,2 mm) released from dying cells. IgM also promotes the binding and uptake of microparticle-coated beads. Conclusions/Significance: Therefore, while the shape of the particles is important for non-opsonized particle uptake, th

NRXN3 Is a Novel Locus for Waist Circumference: A Genome-Wide Association Study from the CHARGE Consortium

Central abdominal fat is a strong risk factor for diabetes and cardiovascular disease. To identify common variants influencing central abdominal fat, we conducted a two-stage genome-wide association analysis for waist circumference (WC). In total, three loci reached genome-wide significance. In stage 1, 31,373 individuals of Caucasian descent from eight cohort studies confirmed the role of FTO and MC4R and identified one novel locus associated with WC in the neurexin 3 gene [NRXN3 (rs10146997, p = 6.4×10−7)]. The association with NRXN3 was confirmed in stage 2 by combining stage 1 results with those from 38,641 participants in the GIANT consortium (p = 0.009 in GIANT only, p = 5.3×10−8 for combined analysis, n = 70,014). Mean WC increase per copy of the G allele was 0.0498 z-score units (0.65 cm). This SNP was also associated with body mass index (BMI) [p = 7.4×10−6, 0.024 z-score units (0.10 kg/m2) per copy of the G allele] and the risk of obesity (odds ratio 1.13, 95% CI 1.07–1.19; p = 3.2×10−5 per copy of the G allele). The NRXN3 gene has been previously implicated in addiction and reward behavior, lending further evidence that common forms of obesity may be a central nervous system-mediated disorder. Our findings establish that common variants in NRXN3 are associated with WC, BMI, and obesity

Circulating IgM Requires Plasma Membrane Disruption to Bind Apoptotic and Non-Apoptotic Nucleated Cells and Erythrocytes

<div><p>Autoimmunity is associated with defective phagocytic clearance of apoptotic cells. IgM deficient mice exhibit an autoimmune phenotype consistent with a role for circulating IgM antibodies in apoptotic cell clearance. We have extensively characterised IgM binding to non-apoptotic and apoptotic mouse thymocytes and human Jurkat cells using flow cytometry, confocal imaging and electron microscopy. We demonstrate strong specific IgM binding to a subset of Annexin-V (AnnV)⁺PI (Propidium Iodide)⁺ apoptotic cells with disrupted cell membranes. Electron microscopy studies indicated that IgM⁺AnnV⁺PI⁺ apoptotic cells exhibited morphologically advanced apoptosis with marked plasma membrane disruption compared to IgM^-AnnV⁺PI⁺ apoptotic cells, suggesting that access to intracellular epitopes is required for IgM to bind. Strong and comparable binding of IgM to permeabilised non-apoptotic and apoptotic cells suggests that IgM bound epitopes are 'apoptosis independent' such that IgM may bind any cell with profound disruption of cell plasma membrane integrity. In addition, permeabilised erythrocytes exhibited significant IgM binding thus supporting the importance of cell membrane epitopes. These data suggest that IgM may recognize and tag damaged nucleated cells or erythrocytes that exhibit significant cell membrane disruption. The role of IgM <i>in vivo</i> in conditions characterized by severe cell damage such as ischemic injury, sepsis and thrombotic microangiopathies merits further exploration.</p></div