Quantum coherent plasmon in silver nanowires: a real-time TDDFT study

A plasmon-like phenomenon, arising from coinciding resonant excitations of different electronic characteristics in 1D silver nanowires, has been proposed based on theoretical linear absorption spectra. Such a molecular plasmon holds the potential for anisotropic nanoplasmonic applications. However, its dynamical nature remains unexplored. In this work, quantum dynamics of longitudinal and transverse excitations in 1D silver nanowires are carried out within the real-time time-dependent density functional theory framework. The anisotropic electron dynamics confirm that the transverse transitions of different electronic characteristics are collective in nature and oscillate in-phase with respect to each other. Analysis of the time evolutions of participating one-electron wave functions suggests that the transverse transitions form a coherent wave packet that gives rise to a strong plasmon resonance at the molecular level

Analysis of a compartmental model of endogenous immunoglobulin G metabolism with application to multiple myeloma

Immunoglobulin G (IgG) metabolism has received much attention in the literature for two reasons: (i) IgG homeostasis is regulated by the neonatal Fc receptor (FcRn), by a pH-dependent and saturable recycling process, which presents an interesting biological system; (ii) the IgG-FcRn interaction may be exploitable as a means for extending the plasma half-life of therapeutic monoclonal antibodies, which are primarily IgG-based. A less-studied problem is the importance of endogenous IgG metabolism in IgG multiple myeloma. In multiple myeloma, quantification of serum monoclonal immunoglobulin plays an important role in diagnosis, monitoring and response assessment. In order to investigate the dynamics of IgG in this setting, a mathematical model characterizing the metabolism of endogenous IgG in humans is required. A number of authors have proposed a two-compartment nonlinear model of IgG metabolism in which saturable recycling is described using Michaelis-Menten kinetics; however it may be difficult to estimate the model parameters from the limited experimental data that are available. The purpose of this study is to analyse the model alongside the available data from experiments in humans and estimate the model parameters. In order to achieve this aim we linearize the model and use several methods of model and parameter validation: stability analysis, structural identifiability analysis, and sensitivity analysis based on traditional sensitivity functions and generalized sensitivity functions. We find that all model parameters are identifiable, structurally and taking into account parameter correlations, when several types of model output are used for parameter estimation. Based on these analyses we estimate parameter values from the limited available data and compare them with previously published parameter values. Finally we show how the model can be applied in future studies of treatment effectiveness in IgG multiple myeloma with simulations of serum monoclonal IgG responses during treatment

GEP analysis validates high risk MDS and acute myeloid leukemia post MDS mice models and highlights novel dysregulated pathways

International audienceBACKGROUND:In spite of the recent discovery of genetic mutations in most myelodysplasic (MDS) patients, the pathophysiology of these disorders still remains poorly understood, and only few in vivo models are available to help unravel the disease.METHODS:We performed global specific gene expression profiling and functional pathway analysis in purified Sca1+ cells of two MDS transgenic mouse models that mimic human high-risk MDS (HR-MDS) and acute myeloid leukemia (AML) post MDS, with NRASD12 and BCL2 transgenes under the control of different promoters MRP8NRASD12/tethBCL-2 or MRP8[NRASD12/hBCL-2], respectively.RESULTS:Analysis of dysregulated genes that were unique to the diseased HR-MDS and AML post MDS mice and not their founder mice pointed first to pathways that had previously been reported in MDS patients, including DNA replication/damage/repair, cell cycle, apoptosis, immune responses, and canonical Wnt pathways, further validating these models at the gene expression level. Interestingly, pathways not previously reported in MDS were discovered. These included dysregulated genes of noncanonical Wnt pathways and energy and lipid metabolisms. These dysregulated genes were not only confirmed in a different independent set of BM and spleen Sca1+ cells from the MDS mice but also in MDS CD34+ BM patient samples.CONCLUSIONS:These two MDS models may thus provide useful preclinical models to target pathways previously identified in MDS patients and to unravel novel pathways highlighted by this study

Dispersion Correction Derived from First Principles for Density Functional Theory and Hartree−Fock Theory

The modeling of dispersion interactions in density functional theory (DFT) is commonly performed using an energy correction that involves empirically fitted parameters for all atom pairs of the system investigated. In this study, the first-principles-derived dispersion energy from the effective fragment potential (EFP) method is implemented for the density functional theory (DFT-D(EFP)) and Hartree–Fock (HF-D(EFP)) energies. Overall, DFT-D(EFP) performs similarly to the semiempirical DFT-D corrections for the test cases investigated in this work. HF-D(EFP) tends to underestimate binding energies and overestimate intermolecular equilibrium distances, relative to coupled cluster theory, most likely due to incomplete accounting for electron correlation. Overall, this first-principles dispersion correction yields results that are in good agreement with coupled-cluster calculations at a low computational cost

Atlas radiographique et ostéologique du macaque rhésus : macaca mulatta

Macaca mulatta, également connu sous le nom de macaque rhésus, est un primate répandu en Asie, utilisé comme modèle d’étude pour l’homme en matière de recherche scientifique. Cet atlas présente des clichés normaux du squelette et constitue une base de données de référence en matière d’anatomie radiographique de cet animal. Chaque radiographie est commentée et accompagnée de photographies légendées des structures osseuses concernées, facilitant la compréhension des clichés

Derivation and Implementation of the Gradient of the R–7 Dispersion Interaction in the Effective Fragment Potential Method

The dispersion interaction energy may be expressed as a sum over R–n terms, with n ≥ 6. Most implementations of the dispersion interaction in model potentials are terminated at n = 6. Those implementations that do include higher order contributions commonly only include even power terms, despite the fact that odd power terms can be important. Because the effective fragment potential (EFP) method contains no empirically fitted parameters, the EFP method provides a useful vehicle for examining the importance of the leading R–7 odd power term in the dispersion expansion. To fully evaluate the importance of the R–7 contribution to the dispersion energy, it is important to have analytic energy first derivatives for all terms. In the present work, the gradients of the term E7 ∼ R–7 are derived analytically, implemented in the GAMESS software package, and evaluated relative to other terms in the dispersion expansion and relative to the total EFP interaction energy. Periodic boundary conditions in the minimum image convention are also implemented. A more accurate dispersion energy contribution can now be obtained during molecular dynamics simulations

HDAC4 as a potential therapeutic target in neurodegenerative diseases: a summary of recent achievements.

For the past decade protein acetylation has been shown to be a crucial post-transcriptional modification involved in the regulation of protein functions. Histone acetyltransferases (HATs) mediate acetylation of histones which results in the nucleosomal relaxation associated with gene expression. The reverse reaction, histone deacetylation, is mediated by histone deacetylases (HDACs) leading to chromatin condensation followed by transcriptional repression. HDACs are divided into distinct classes: I, IIa, IIb, III, and IV, on the basis of size and sequence homology, as well as formation of distinct repressor complexes. Implications of HDACs in many diseases, such as cancer, heart failure, and neurodegeneration, have identified these molecules as unique and attractive therapeutic targets. The emergence of HDAC4 among the members of class IIa family as a major player in synaptic plasticity raises important questions about its functions in the brain. The characterization of HDAC4 specific substrates and molecular partners in the brain will not only provide a better understanding of HDAC4 biological functions but also might help to develop new therapeutic strategies to target numerous malignancies. In this review we highlight and summarize recent achievements in understanding the biological role of HDAC4 in neurodegenerative processes

Co-morbidity and polypharmacy in Parkinson's Disease:insights from a large Scottish primary care database

Background: Parkinson’s disease is complicated by comorbidity and polypharmacy, but the extent and patterns of these are unclear. We describe comorbidity and polypharmacy in patients with and without Parkinson’s disease across 31 other physical, and seven mental health conditions. Methods: We analysed primary health-care data on 510,502 adults aged 55 and over. We generated standardised prevalence rates by age-groups, gender, and neighbourhood deprivation, then calculated age, sex and deprivation adjusted odds ratios (OR) and 95% confidence intervals (95% CI) for those with PD compared to those without, for the prevalence, and number of conditions. Results: Two thousand six hundred forty (0.5%) had Parkinson’s disease, of whom only 7.4% had no other conditions compared with 22.9% of controls (adjusted OR [aOR] 0.43, 95% 0.38–0.49). The Parkinson’s group had more conditions, with the biggest difference found for seven or more conditions (PD 12.1% vs. controls 3.9%; aOR 2.08 95% CI 1.84–2.35). 12 of the 31 physical conditions and five of the seven mental health conditions were significantly more prevalent in the PD group. 44.5% with Parkinson’s disease were on five to nine repeat prescriptions compared to 24.5% of controls (aOR 1.40; 95% CI 1.28 to 1.53) and 19.2% on ten or more compared to 6.2% of controls (aOR 1.90; 95% CI 1.68 to 2.15). Conclusions: Parkinson’s disease is associated with substantial physical and mental co-morbidity. Polypharmacy is also a significant issue due to the complex nature of the disease and associated treatments