Ground-State Dynamical Correlation Functions: An Approach from Density Matrix Renormalization Group Method

A numerical approach to ground-state dynamical correlation functions from Density Matrix Renormalization Group (DMRG) is developed. Using sum rules, moments of a dynamic correlation function can be calculated with DMRG, and with the moments the dynamic correlation function can be obtained by the maximum entropy method. We apply this method to one-dimensional spinless fermion system, which can be converted to the spin 1/2 Heisenberg model in a special case. The dynamical density-density correlation function is obtained.Comment: 11 pages, latex, 4 figure

Quantification of Lipoprotein Uptake in Vivo Using Magnetic Particle Imaging and Spectroscopy

Lipids are a major source of energy for most tissues, and lipid uptake and storage is therefore crucial for energy homeostasis. So far, quantification of lipid uptake in vivo has primarily relied on radioactive isotope labeling, exposing human subjects or experimental animals to ionizing radiation. Here, we describe the quantification of in vivo uptake of chylomicrons, the primary carriers of dietary lipids, in metabolically active tissues using magnetic particle imaging (MPI) and magnetic particle spectroscopy (MPS). We show that loading artificial chylomicrons (ACM) with iron oxide nanoparticles (IONPs) enables rapid and highly sensitive post hoc detection of lipid uptake in situ using MPS. Importantly, by utilizing highly magnetic Zn-doped iron oxide nanoparticles (ZnMNPs), we generated ACM with MPI tracer properties superseding the current gold-standard, Resovist, enabling quantification of lipid uptake from whole-animal scans. We focused on brown adipose tissue (BAT), which dissipates heat and can consume a large part of nutrient lipids, as a model for tightly regulated and inducible lipid uptake. High BAT activity in humans correlates with leanness and improved cardiometabolic health. However, the lack of nonradioactive imaging techniques is an important hurdle for the development of BAT-centered therapies for metabolic diseases such as obesity and type 2 diabetes. Comparison of MPI measurements with iron quantification by inductively coupled plasma mass spectrometry revealed that MPI rivals the performance of this highly sensitive technique. Our results represent radioactivity-free quantification of lipid uptake in metabolically active tissues such as BAT

The trans-ancestral genomic architecture of glycemic traits

Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P < 5 x 10(-8)), 80% of which had no significant evidence of between-ancestry heterogeneity. Analyses restricted to individuals of European ancestry with equivalent sample size would have led to 24 fewer new loci. Compared with single-ancestry analyses, equivalent-sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic-feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase our understanding of diabetes pathophysiology by using trans-ancestry studies for improved power and resolution.A trans-ancestry meta-analysis of GWAS of glycemic traits in up to 281,416 individuals identifies 99 novel loci, of which one quarter was found due to the multi-ancestry approach, which also improves fine-mapping of credible variant sets.Diabetes mellitus: pathophysiological changes and therap

Status and perspectives of combined 3D imaging and diffraction experiments at the ESRF

International audienceno abstrac

Altering microtubule dynamics is synergistically toxic with spindle assembly checkpoint inhibition.

Chromosomal instability (CIN) and aneuploidy are hallmarks of cancer. As most cancers are aneuploid, targeting aneuploidy or CIN may be an effective way to target a broad spectrum of cancers. Here, we perform two small molecule compound screens to identify drugs that selectively target cells that are aneuploid or exhibit a CIN phenotype. We find that aneuploid cells are much more sensitive to the energy metabolism regulating drug ZLN005 than their euploid counterparts. Furthermore, cells with an ongoing CIN phenotype, induced by spindle assembly checkpoint (SAC) alleviation, are significantly more sensitive to the Src kinase inhibitor SKI606. We show that inhibiting Src kinase increases microtubule polymerization rates and, more generally, that deregulating microtubule polymerization rates is particularly toxic to cells with a defective SAC. Our findings, therefore, suggest that tumors with a dysfunctional SAC are particularly sensitive to microtubule poisons and, vice versa, that compounds alleviating the SAC provide a powerful means to treat tumors with deregulated microtubule dynamics