Insulating and Conducting Phases of RbC60

Optical measurements were performed on thin films of Rb$_{x}$C$_{60}$, identified by X-ray diffraction as mostly $x=1$ material. The samples were subjected to various heat treatments, including quenching and slow cooling from 400K. The dramatic increase in the transmission of the quenched samples, and the relaxation towards the transmission observed in slow cooled samples provides direct evidence for the existence of a metastable insulating phase. Slow cooling results in a phase transition between two electrically conducting phases.Comment: Minor revisions. Submitted to PRB, RevTeX 3.0 file, 2 postscript figures included, ir_dop

Significant impact of different oxygen breathing conditions on noninvasive in vivo tumor-hypoxia imaging using [18F]-fluoro-azomycinarabino-furanoside ([18F]FAZA)

<p>Abstract</p> <p>Background</p> <p>[¹⁸F]FAZA is a PET biomarker with great potential for imaging tumor hypoxia. Aim of our study was to compare [¹⁸F]FAZA uptake in mice with subcutaneous exogenous CT26 colon carcinomas and endogenous polyoma middle-T (PyV-mT) mammary carcinomas and to analyze the influence of different breathing protocols in CT26 colon carcinomas as well as the reversibility or irreversibility of [¹⁸F]FAZA uptake.</p> <p>Methods</p> <p>We injected subcutaneous CT26 colon carcinoma or polyomavirus middle-T (PyV-mT) mammary carcinoma-bearing mice intravenously with¹⁸F-FAZA and performed PET scans 1-3 h post injection (<it>p.i.</it>). To analyze the impact of oxygen supply in CT26 carcinomas we used three different breathing protocols: (P0) air; (P1) 100% oxygen 1 h prior injection until 3 h <it>p.i.</it>; (P2) 100% oxygen breathing starting 2 min prior tracer injection until 1 h <it>p.i. </it>and during the PET scans; mice were breathing air between the 2 h and 3 h 10 min static scans. Normalized PET images were analyzed by using defined regions of interest. Finally, some mice were dissected for pimonidazole immunohistochemistry.</p> <p>Results</p> <p>There was no difference in¹⁸F-FAZA uptake 1-3 h <it>p.i. </it>between the two carcinoma types (CT26: 1.58 ± 0.45%ID/cc; PyV-mT: 1.47 ± 0.89%ID/cc, 1 h <it>p.i.</it>, tumor size < 0.5 cm³). We measured a significant tracer clearance, which was more pronounced in muscle tissue (P0). The [¹⁸F]FAZA tumor-to-muscle-ratios in CT26 colon carcinoma-bearing mice 2 h and 3 h, but not 1 h <it>p.i. </it>were significantly higher when the mice breathed air (P0: 3.56 ± 0.55, 3 h) compared to the oxygen breathing protocols (P1: 2.45 ± 0.58; P2: 2.77 ± 0.42, 3 h). Surprisingly, the breathing protocols P1 and P2 showed no significant differences in T/M ratios, thus indicating that the crucial [¹⁸F]FAZA uptake phase is during the first hour after [¹⁸F]FAZA injection. Importantly, the muscle clearance was not affected by the different oxygen breathing conditions while the tumor clearance was lower when mice were breathing air.</p> <p>Conclusion</p> <p>Exogenous CT26 colon carcinomas and endogenous polyoma middle-T (PyV-mT) mammary carcinomas showed no differences in [¹⁸F]FAZA uptake 1-3 h <it>p.i. </it>Our analysis using various breathing protocols with air (P0) and with pure oxygen (P1, P2) clearly indicate that [¹⁸F]FAZA is an appropriate PET biomarker for <it>in vivo </it>analysis of hypoxia revealing an enhanced tracer uptake in tumors with reduced oxygen supply. [¹⁸F]FAZA uptake was independent of tumor-type.</p

High-Resolution Motor State Detection in Parkinson's Disease Using Convolutional Neural Networks

Patients with advanced Parkinson's disease regularly experience unstable motor states. Objective and reliable monitoring of these fluctuations is an unmet need. We used deep learning to classify motion data from a single wrist-worn IMU sensor recording in unscripted environments. For validation purposes, patients were accompanied by a movement disorder expert, and their motor state was passively evaluated every minute. We acquired a dataset of 8,661 minutes of IMU data from 30 patients, with annotations about the motor state (OFF,ON, DYSKINETIC) based on MDS-UPDRS global bradykinesia item and the AIMS upper limb dyskinesia item. Using a 1-minute window size as an input for a convolutional neural network trained on data from a subset of patients, we achieved a three-class balanced accuracy of 0.654 on data from previously unseen subjects. This corresponds to detecting the OFF, ON, or DYSKINETIC motor state at a sensitivity/specificity of 0.64/0.89, 0.67/0.67 and 0.64/0.89, respectively. On average, the model outputs were highly correlated with the annotation on a per subject scale (r = 0.83/0.84;p < 0.0001), and sustained so for the highly resolved time windows of 1 minute (r = 0.64/0.70;p < 0.0001). Thus, we demonstrate the feasibility of long-term motor-state detection in a free-living setting with deep learning using motion data from a single IMU

Unexpected changes in community size structure in a natural warming experiment

Natural ecosystems typically consist of many small and few large organisms. The scaling of this negative relationship between body mass and abundance has important implications for resource partitioning and energy usage. Global warming over the next century is predicted to favour smaller organisms, producing steeper mass-abundance scaling and a less efficient transfer of biomass through the food web. Here, we show that the opposite effect occurs in a natural warming experiment involving 13 whole-stream ecosystems within the same catchment, which span a temperature gradient of 5-25 °C. We introduce a mechanistic model that shows how the temperature dependence of basal resource carrying capacity can account for these previously unexpected results. If nutrient supply increases with temperature to offset the rising metabolic demand of primary producers, there will be sufficient resources to sustain larger consumers at higher trophic levels. These new data and the model that explains them highlight important exceptions to some commonly assumed 'rules' about responses to warming in natural ecosystems

Cheddar: analysis and visualisation of ecological communities in R

There has been a lack of software available to ecologists for the management, visualisation and analysis of ecological community and food web data. Researchers have been forced to implement their own data formats and software, often from scratch, resulting in duplicated effort and bespoke solutions that are difficult to apply to future analyses and comparative studies. We introduce Cheddar – an R package that provides standard, transparent implementations of a wide range of food web and community-level analyses and plots, focussing on ecological network data that are augmented with estimates of body mass and/or numerical abundance. The package allows analysis of individual communities, as well as collections of communities, allowing examination of changes in structure through time, across environmental gradients, or due to experimental manipulations. Several commonly analysed food web data sets are included and used in worked examples. This is the first time these important features have been combined in a single package that helps improve research efficiency and serves as a unified framework for future development

Biological, clinical and population relevance of 95 loci for blood lipids.

Plasma concentrations of total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol and triglycerides are among the most important risk factors for coronary artery disease (CAD) and are targets for therapeutic intervention. We screened the genome for common variants associated with plasma lipids in &gt;100,000 individuals of European ancestry. Here we report 95 significantly associated loci (P &lt; 5 x 10(-8)), with 59 showing genome-wide significant association with lipid traits for the first time. The newly reported associations include single nucleotide polymorphisms (SNPs) near known lipid regulators (for example, CYP7A1, NPC1L1 and SCARB1) as well as in scores of loci not previously implicated in lipoprotein metabolism. The 95 loci contribute not only to normal variation in lipid traits but also to extreme lipid phenotypes and have an impact on lipid traits in three non-European populations (East Asians, South Asians and African Americans). Our results identify several novel loci associated with plasma lipids that are also associated with CAD. Finally, we validated three of the novel genes-GALNT2, PPP1R3B and TTC39B-with experiments in mouse models. Taken together, our findings provide the foundation to develop a broader biological understanding of lipoprotein metabolism and to identify new therapeutic opportunities for the prevention of CAD

A robust coregistration method for in vivo studies using a first generation simultaneous PET/MR scanner

Purpose: Hybrid positron emission tomography (PET)/magnetic resonance (MR) imaging systems have recently been built that allow functional and anatomical information obtained from PET and MR to be acquired simultaneously. The authors have developed a robust coregistration scheme for a first generation small animal PET/MR imaging system and illustrated the potential of this system to study intratumoral heterogeneity in a mouse model. Methods: An alignment strategy to fuse simultaneously acquired PET and MR data, using the MR imaging gradient coordinate system as the reference basis, was developed. The fidelity of the alignment was evaluated over multiple study sessions. In order to explore its robustness in vivo, the alignment strategy was applied to explore the heterogeneity of glucose metabolism in a xenograft tumor model, using ^(18)F-FDG-PET to guide the acquisition of localized ^1H MR spectra within a single imaging session. Results: The alignment method consistently fused the PET/MR data sets with subvoxel accuracy (registration error mean=0.55 voxels, <0.28 mm); this was independent of location within the field of view. When the system was used to study intratumoral heterogeneity within xenograft tumors, a correlation of high ^(18)F-FDG-PET signal with high choline/creatine ratio was observed. Conclusions: The authors present an implementation of an efficient and robust coregistration scheme for multimodal noninvasive imaging using PET and MR. This setup allows time-sensitive, multimodal studies of physiology to be conducted in an efficient manner

Hundreds of variants clustered in genomic loci and biological pathways affect human height

Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P < 0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways.

New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk.

Levels of circulating glucose are tightly regulated. To identify new loci influencing glycemic traits, we performed meta-analyses of 21 genome-wide association studies informative for fasting glucose, fasting insulin and indices of beta-cell function (HOMA-B) and insulin resistance (HOMA-IR) in up to 46,186 nondiabetic participants. Follow-up of 25 loci in up to 76,558 additional subjects identified 16 loci associated with fasting glucose and HOMA-B and two loci associated with fasting insulin and HOMA-IR. These include nine loci newly associated with fasting glucose (in or near ADCY5, MADD, ADRA2A, CRY2, FADS1, GLIS3, SLC2A2, PROX1 and C2CD4B) and one influencing fasting insulin and HOMA-IR (near IGF1). We also demonstrated association of ADCY5, PROX1, GCK, GCKR and DGKB-TMEM195 with type 2 diabetes. Within these loci, likely biological candidate genes influence signal transduction, cell proliferation, development, glucose-sensing and circadian regulation. Our results demonstrate that genetic studies of glycemic traits can identify type 2 diabetes risk loci, as well as loci containing gene variants that are associated with a modest elevation in glucose levels but are not associated with overt diabetes