Rapamycin‐mediated lifespan increase in mice is dose and sex dependent and metabolically distinct from dietary restriction

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/107367/1/acel12194.pd

Development and Evaluation of Sensor Concepts for Ageless Aerospace Vehicles: Report 5 - Phase 2 Implementation of the Concept Demonstrator

This report describes the second phase of the implementation of the Concept Demonstrator experimental test-bed system containing sensors and processing hardware distributed throughout the structure, which uses multi-agent algorithms to characterize impacts and determine a suitable response to these impacts. This report expands and adds to the report of the first phase implementation. The current status of the system hardware is that all 192 physical cells (32 on each of the 6 hexagonal prism faces) have been constructed, although only four of these presently contain data-acquisition sub-modules to allow them to acquire sensor data. Impact detection.. location and severity have been successfully demonstrated. The software modules for simulating cells and controlling the test-bed are fully operational. although additional functionality will be added over time. The visualization workstation displays additional diagnostic information about the array of cells (both real and simulated) and additional damage information. Local agent algorithms have been developed that demonstrate emergent behavior of the complex multi-agent system, through the formation of impact damage boundaries and impact networks. The system has been shown to operate well for multiple impacts. and to demonstrate robust reconfiguration in the presence of damage to numbers of cells

Evidence of a Causal Association Between Insulinemia and Endometrial Cancer: A Mendelian Randomization Analysis.

BACKGROUND: Insulinemia and type 2 diabetes (T2D) have been associated with endometrial cancer risk in numerous observational studies. However, the causality of these associations is uncertain. Here we use a Mendelian randomization (MR) approach to assess whether insulinemia and T2D are causally associated with endometrial cancer. METHODS: We used single nucleotide polymorphisms (SNPs) associated with T2D (49 variants), fasting glucose (36 variants), fasting insulin (18 variants), early insulin secretion (17 variants), and body mass index (BMI) (32 variants) as instrumental variables in MR analyses. We calculated MR estimates for each risk factor with endometrial cancer using an inverse-variance weighted method with SNP-endometrial cancer associations from 1287 case patients and 8273 control participants. RESULTS: Genetically predicted higher fasting insulin levels were associated with greater risk of endometrial cancer (odds ratio [OR] per standard deviation = 2.34, 95% confidence internal [CI] = 1.06 to 5.14, P = .03). Consistently, genetically predicted higher 30-minute postchallenge insulin levels were also associated with endometrial cancer risk (OR = 1.40, 95% CI = 1.12 to 1.76, P = .003). We observed no associations between genetic risk of type 2 diabetes (OR = 0.91, 95% CI = 0.79 to 1.04, P = .16) or higher fasting glucose (OR = 1.00, 95% CI = 0.67 to 1.50, P = .99) and endometrial cancer. In contrast, endometrial cancer risk was higher in individuals with genetically predicted higher BMI (OR = 3.86, 95% CI = 2.24 to 6.64, P = 1.2x10(-6)). CONCLUSION: This study provides evidence to support a causal association of higher insulin levels, independently of BMI, with endometrial cancer risk.This study was supported by MRC grant MC_UU_12015/1 and by the Innovative Medicines Initiative Joint Undertaking under EMIF grant agreement n° 115372 (contributions from the European Union's Seventh Framework Programme (FP7/2007-2013) and EFPIA companies). ANECS recruitment was supported by project grants from the National Health and Medical Research Council of Australia (ID#339435), The Cancer Council Queensland (ID#4196615) and Cancer Council Tasmania (ID#403031 and ID#457636). SEARCH recruitment was funded by a programme grant from Cancer Research UK [C490/A10124]. Case genotyping was supported by the National Health and Medical Research Council (ID#552402). Control data was generated by the Wellcome Trust Case Control Consortium (WTCCC), and a full list of the investigators who contributed to the generation of the data is available from the WTCCC website. We acknowledge use of DNA from the British 1958 Birth Cohort collection, funded by the Medical Research Council grant G0000934 and the Wellcome Trust grant 068545/Z/02. Funding for this project was provided by the Wellcome Trust under award 085475. Recruitment of the QIMR controls was supported by the National Health and Medical Research Council of Australia (NHMRC). The University of Newcastle, the Gladys M Brawn Senior Research Fellowship scheme, The Vincent Fairfax Family Foundation, the Hunter Medical Research Institute and the Hunter Area Pathology Service all contributed towards the costs of establishing the Hunter Community Study. K.T.N. was supported by the Gates Cambridge Trust. R.K.S. is supported by the Wellcome Trust (grant number WT098498). A.B.S. is supported by the National Health and Medical Research Council (NHMRC) Fellowship Scheme. D.F.E. is a Principal Research Fellow of Cancer Research UK. A.M.D is supported by the Joseph Mitchell Trust.This is the final version of the article. It first appeared from Oxford University Press via http://dx.doi.org/10.1093/jnci/djv17

Disconnection between the default mode network and medial temporal lobes in post-traumatic amnesia

Post-traumatic amnesia is very common immediately after traumatic brain injury. It is characterised by a confused, agitated state and a pronounced inability to encode new memories and sustain attention. Clinically, post-traumatic amnesia is an important predictor of functional outcome. However, despite its prevalence and functional importance, the pathophysiology of post-traumatic amnesia is not understood. Memory processing relies on limbic structures such as the hippocampus, parahippocampus and parts of the cingulate cortex. These structures are connected within an intrinsic connectivity network, the Default Mode Network. Interactions within the Default Mode Network can be assessed using resting state functional magnetic resonance imaging, which can be acquired in confused patients unable to perform tasks in the scanner. Here we used this approach to test the hypothesis that the mnemonic symptoms of post-traumatic amnesia are caused by functional disconnection within the Default Mode Network. We assessed whether the hippocampus and parahippocampus showed evidence of transient disconnection from cortical brain regions involved in memory processing. 19 traumatic brain injury patients were classified into post-traumatic amnesia and traumatic brain injury control groups, based on their performance on a paired associates learning task. Cognitive function was also assessed with a detailed neuropsychological test battery. Functional interactions between brain regions were investigated using resting-state functional magnetic resonance imaging. Together with impairments in associative memory patients in post-traumatic amnesia demonstrated impairments in information processing speed and spatial working memory. Patients in post-traumatic amnesia showed abnormal functional connectivity between the parahippocampal gyrus and posterior cingulate cortex. The strength of this functional connection correlated with both associative memory and information processing speed and normalised when these functions improved. We have previously shown abnormally high posterior cingulate cortex connectivity in the chronic phase after traumatic brain injury, and this abnormality was also observed in patients with post-traumatic amnesia. Patients in post-traumatic amnesia showed evidence of widespread traumatic axonal injury measured using diffusion magnetic resonance imaging. This change was more marked within the cingulum bundle, the tract connecting the parahippocampal gyrus to the posterior cingulate cortex. These findings provide novel insights into the pathophysiology of post-traumatic amnesia and evidence that memory impairment acutely after traumatic brain injury results from altered parahippocampal functional connectivity, perhaps secondary to the effects of axonal injury on white matter tracts connecting limbic structures involved in memory processing

LZIFU: an emission-line fitting toolkit for integral field spectroscopy data

We present lzifu (LaZy-IFU), an idl toolkit for fitting multiple emission lines simultaneously in integral field spectroscopy (IFS) data. lzifu is useful for the investigation of the dynamical, physical and chemical properties of gas in galaxies. lzifu has already been applied to many world-class IFS instruments and large IFS surveys, including the Wide Field Spectrograph, the new Multi Unit Spectroscopic Explorer (MUSE), the Calar Alto Legacy Integral Field Area (CALIFA) survey, the Sydney-Australian-astronomical-observatory Multi-object Integral-field spectrograph (SAMI) Galaxy Survey. Here we describe in detail the structure of the toolkit, and how the line fluxes and flux uncertainties are determined, including the possibility of having multiple distinct kinematic components. We quantify the performance of lzifu, demonstrating its accuracy and robustness. We also show examples of applying lzifu to CALIFA and SAMI data to construct emission line and kinematic maps, and investigate complex, skewed line profiles presented in IFS data. The code is made available to the astronomy community through github. lzifu will be further developed over time to other IFS instruments, and to provide even more accurate line and uncertainty estimates

The SAMI Galaxy Survey: revisiting galaxy classification through high-order stellar kinematics

Recent cosmological hydrodynamical simulations suggest that integral field spectroscopy can connect the high-order stellar kinematic moments h3 (~skewness) and h4 (~kurtosis) in galaxies to their cosmological assembly history. Here, we assess these results by measuring the stellar kinematics on a sample of 315 galaxies, without a morphological selection, using two-dimensional integral field data from the SAMI Galaxy Survey. Proxies for the spin parameter (${\lambda }_{{R}_{{\rm{e}}}}$) and ellipticity (${\epsilon }_{{\rm{e}}}$) are used to separate fast and slow rotators; there exists a good correspondence to regular and non-regular rotators, respectively, as also seen in earlier studies. We confirm that regular rotators show a strong h3 versus $V/\sigma$ anti-correlation, whereas quasi-regular and non-regular rotators show a more vertical relation in h3 and $V/\sigma$. Motivated by recent cosmological simulations, we develop an alternative approach to kinematically classify galaxies from their individual h3 versus $V/\sigma$ signatures. Within the SAMI Galaxy Survey, we identify five classes of high-order stellar kinematic signatures using Gaussian mixture models. Class 1 corresponds to slow rotators, whereas Classes 2–5 correspond to fast rotators. We find that galaxies with similar {\lambda }_{{R}_{{\rm{e}}}}\mbox{--}{\epsilon }_{{\rm{e}}} values can show distinctly different {h}_{3}\mbox{--}V/\sigma signatures. Class 5 objects are previously unidentified fast rotators that show a weak h3 versus $V/\sigma$ anti-correlation. From simulations, these objects are predicted to be disk-less galaxies formed by gas-poor mergers. From morphological examination, however, there is evidence for large stellar disks. Instead, Class 5 objects are more likely disturbed galaxies, have counter-rotating bulges, or bars in edge-on galaxies. Finally, we interpret the strong anti-correlation in h3 versus $V/\sigma$ as evidence for disks in most fast rotators, suggesting a dearth of gas-poor mergers among fast rotators

The SAMI Galaxy Survey : spatially resolving the main sequence of star formation

We present the ∼800 star formation rate maps for the Sydney-AAO Multi-object Integral field spectrograph (SAMI) Galaxy Survey based on H α emission maps, corrected for dust attenuation via the Balmer decrement, that are included in the SAMI Public Data Release 1. We mask out spaxels contaminated by non-stellar emission using the [O iii]/H β, [N ii]/H α, [S ii]/H α, and [O i]/H α line ratios. Using these maps, we examine the global and resolved star-forming main sequences of SAMI galaxies as a function of morphology, environmental density, and stellar mass. Galaxies further below the star-forming main sequence are more likely to have flatter star formation profiles. Early-type galaxies split into two populations with similar stellar masses and central stellar mass surface densities. The main-sequence population has centrally concentrated star formation similar to late-type galaxies, while galaxies >3σ below the main sequence show significantly reduced star formation most strikingly in the nuclear regions. The split populations support a two-step quenching mechanism, wherein halo mass first cuts off the gas supply and remaining gas continues to form stars until the local stellar mass surface density can stabilize the reduced remaining fuel against further star formation. Across all morphologies, galaxies in denser environments show a decreased specific star formation rate from the outside in, supporting an environmental cause for quenching, such as ram-pressure stripping or galaxy interactions.Publisher PDFPeer reviewe

The SAMI Galaxy Survey: Data Release One with emission-line physics value-added products

We present the first major release of data from the SAMI Galaxy Survey. This data release focuses on the emission-line physics of galaxies. Data Release One includes data for 772 galaxies, about 20 per cent of the full survey. Galaxies included have the redshift range 0.004 < z < 0.092, a large mass range (7.6 < logM*/M⊙ < 11.6), and star formation rates of ~10-4 to ~101M⊙ yr-1. For each galaxy, we include two spectral cubes and a set of spatially resolved 2D maps: single- and multi-component emission-line fits (with dust-extinction corrections for strong lines), local dust extinction, and star formation rate. Calibration of the fibre throughputs, fluxes, and differential atmospheric refraction has been improved over the Early Data Release. The data have average spatial resolution of 2.16 arcsec (full width at half-maximum) over the 15 arcsec diameter field of view and spectral (kinematic) resolution of R = 4263 (σ = 30 km s-1) around Ha. The relative flux calibration is better than 5 per cent, and absolute flux calibration has an rms of 10 per cent. The data are presented online through the Australian Astronomical Observatory's Data Central.The SAMI Galaxy Survey is funded by the Australian Research Council Centre of Excellence for All-sky Astrophysics (CAASTRO), through project number CE110001020, and other participating institutions. JTA acknowledges the award of a SIEF John Stocker Fellowship. MSO acknowledges the funding support from the Australian Research Council through a Future Fellowship (FT140100255). BG is the recipient of an Australian Research Council Future Fellowship (FT140101202). NS acknowledges support of a University of Sydney Postdoctoral Research Fellowship. SB acknowledges the funding support from the Australian Research Council through a Future Fellowship (FT140101166). JvdS is funded under Bland-Hawthorn’s ARC Laureate Fellowship (FL140100278). SMC acknowledges the support of an Australian Research Council Future Fellowship (FT100100457). Support for AMM is provided by NASA through Hubble Fellowship grant #HST-HF2-51377 awarded by the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Inc., for NASA, under contract NAS5-26555. CF gratefully acknowledges funding provided by the Australian Research Council’s Discovery Projects (grants DP150104329 and DP170100603). BC is the recipient of an Australian Research Council Future Fellowship (FT120100660)