Fetal in vivo continuous cardiovascular function during chronic hypoxia.

Although the fetal cardiovascular defence to acute hypoxia and the physiology underlying it have been established for decades, how the fetal cardiovascular system responds to chronic hypoxia has been comparatively understudied. We designed and created isobaric hypoxic chambers able to maintain pregnant sheep for prolonged periods of gestation under controlled significant (10% O2) hypoxia, yielding fetal mean P(aO2) levels (11.5 ± 0.6 mmHg) similar to those measured in human fetuses of hypoxic pregnancy. We also created a wireless data acquisition system able to record fetal blood flow signals in addition to fetal blood pressure and heart rate from free moving ewes as the hypoxic pregnancy is developing. We determined in vivo longitudinal changes in fetal cardiovascular function including parallel measurement of fetal carotid and femoral blood flow and oxygen and glucose delivery during the last third of gestation. The ratio of oxygen (from 2.7 ± 0.2 to 3.8 ± 0.8; P < 0.05) and of glucose (from 2.3 ± 0.1 to 3.3 ± 0.6; P < 0.05) delivery to the fetal carotid, relative to the fetal femoral circulation, increased during and shortly after the period of chronic hypoxia. In contrast, oxygen and glucose delivery remained unchanged from baseline in normoxic fetuses. Fetal plasma urate concentration increased significantly during chronic hypoxia but not during normoxia (Δ: 4.8 ± 1.6 vs. 0.5 ± 1.4 μmol l(-1), P<0.05). The data support the hypotheses tested and show persisting redistribution of substrate delivery away from peripheral and towards essential circulations in the chronically hypoxic fetus, associated with increases in xanthine oxidase-derived reactive oxygen species.This work was supported by the British Heart Foundation.This is the author accepted manuscript. The final version is available from Wiley via http://dx.doi.org/10.1113/JP27109

Quality of life support in advanced cancer – Web and technological interventions: systematic review and narrative synthesis

Background As treatments continue to progress, patients with advanced cancer are living longer. However, ongoing physical side-effects and psychosocial concerns can compromise quality of life (QoL). Patients and physicians increasingly look to the internet and other technologies to address diverse supportive needs encountered across this evolving cancer trajectory. Objectives 1. To examine the features and delivery of web and technological interventions supporting patients with advanced cancer. 2. To explore their efficacy relating to QoL and psychosocial well-being. Methods Relevant studies were identified through electronic database searches (MEDLINE, PsychINFO, Embase, CINAHL, CENTRAL, Web of Science and ProQuest) and handsearching. Findings were collated and explored through narrative synthesis. Results Of 5274 identified records, 37 articles were included. Interventions were evaluated within studies targeting advanced cancer (13) or encompassing all stages (24). Five subtypes emerged: Interactive Health Communication Applications (n=12), virtual programmes of support (n=11), symptom monitoring tools (n=8), communication conduits (n=3) and information websites (n=3). Modes of delivery ranged from self-management to clinically integrated. Support largely targeted psychosocial well-being, alongside symptom management and healthy living. Most studies (78%) evidenced varying degrees of efficacy through QoL and psychosocial measures. Intervention complexity made it challenging to distinguish the most effective components. Incomplete reporting limited risk of bias assessment. Conclusion While complex and varied in their content, features and delivery, most interventions led to improvements in QoL or psychosocial well-being across the cancer trajectory. Ongoing development and evaluation of such innovations should specifically target patients requiring longer-term support for later-stage cancer

Dark Matter, Muon g-2 and Other SUSY Constraints

Recent developments constraining the SUSY parameter space are reviewed within the framework of SUGRA GUT models. The WMAP data is seen to reduce the error in the density of cold dark matter by about a factor of four, implying that the lightest stau is only 5 -10 GeV heavier than the lightest neutralino when m_0, m_{1/2} < 1 TeV. The CMD-2 re-analysis of their data has reduced the disagreement between the Standard Model prediction and the Brookhaven measurement of the muon magnetic moment to 1.9 sigma, while using the tau decay data plus CVC, the disagreement is 0.7 sigma. (However, the two sets of data remain inconsistent at the 2.9 sigma level.) The recent Belle and BABAR measurements of the B -> phi K CP violating parameters and branching ratios are discussed. They are analyzed theoretically within the BBNS improved factorization method. The CP parameters are in disagreement with the Standard Model at the 2.7 sigma level, and the branching ratios are low by a factor of two or more over most of the parameter space. It is shown that both anomalies can naturally be accounted for by adding a non-universal cubic soft breaking term at M_G mixing the second and third generations.Comment: 16 pages, 7 figures, plenary talk at Beyond The Desert '03, Castle Ringberg, Germany, June 9, 2003. Typos correcte

Multivariate characterization of white matter heterogeneity in autism spectrum disorder

The complexity and heterogeneity of neuroimaging findings in individuals with autism spectrum disorder has suggested that many of the underlying alterations are subtle and involve many brain regions and networks. The ability to account for multivariate brain features and identify neuroimaging measures that can be used to characterize individual variation have thus become increasingly important for interpreting and understanding the neurobiological mechanisms of autism. In the present study, we utilize the Mahalanobis distance, a multidimensional counterpart of the Euclidean distance, as an informative index to characterize individual brain variation and deviation in autism. Longitudinal diffusion tensor imaging data from 149 participants (92 diagnosed with autism spectrum disorder and 57 typically developing controls) between 3.1 and 36.83 years of age were acquired over a roughly 10-year period and used to construct the Mahalanobis distance from regional measures of white matter microstructure. Mahalanobis distances were significantly greater and more variable in the autistic individuals as compared to control participants, demonstrating increased atypicalities and variation in the group of individuals diagnosed with autism spectrum disorder. Distributions of multivariate measures were also found to provide greater discrimination and more sensitive delineation between autistic and typically developing individuals than conventional univariate measures, while also being significantly associated with observed traits of the autism group. These results help substantiate autism as a truly heterogeneous neurodevelopmental disorder, while also suggesting that collectively considering neuroimaging measures from multiple brain regions provides improved insight into the diversity of brain measures in autism that is not observed when considering the same regions separately. Distinguishing multidimensional brain relationships may thus be informative for identifying neuroimaging-based phenotypes, as well as help elucidate underlying neural mechanisms of brain variation in autism spectrum disorders

Naturalness and Fine Tuning in the NMSSM: Implications of Early LHC Results

We study the fine tuning in the parameter space of the semi-constrained NMSSM, where most soft Susy breaking parameters are universal at the GUT scale. We discuss the dependence of the fine tuning on the soft Susy breaking parameters M_1/2 and m0, and on the Higgs masses in NMSSM specific scenarios involving large singlet-doublet Higgs mixing or dominant Higgs-to-Higgs decays. Whereas these latter scenarios allow a priori for considerably less fine tuning than the constrained MSSM, the early LHC results rule out a large part of the parameter space of the semi-constrained NMSSM corresponding to low values of the fine tuning.Comment: 19 pages, 10 figures, bounds from Susy searches with ~1/fb include

Neutralino dark matter in mSUGRA/CMSSM with a 125 GeV light Higgs scalar

The minimal supergravity (mSUGRA or CMSSM) model is an oft-used framework for exhibiting the properties of neutralino (WIMP) cold dark matter (CDM). However, the recent evidence from Atlas and CMS on a light Higgs scalar with mass m_h\simeq 125 GeV highly constrains the superparticle mass spectrum, which in turn constrains the neutralino annihilation mechanisms in the early universe. We find that stau and stop co-annihilation mechanisms -- already highly stressed by the latest Atlas/CMS results on SUSY searches -- are nearly eliminated if indeed the light Higgs scalar has mass m_h\simeq 125 GeV. Furthermore, neutralino annihilation via the A-resonance is essentially ruled out in mSUGRA so that it is exceedingly difficult to generate thermally-produced neutralino-only dark matter at the measured abundance. The remaining possibility lies in the focus-point region which now moves out to m_0\sim 10-20 TeV range due to the required large trilinear soft SUSY breaking term A_0. The remaining HB/FP region is more fine-tuned than before owing to the typically large top squark masses. We present updated direct and indirect detection rates for neutralino dark matter, and show that ton scale noble liquid detectors will either discover mixed higgsino CDM or essentially rule out thermally-produced neutralino-only CDM in the mSUGRA model.Comment: 17 pages including 9 .eps figure

A Profile Likelihood Analysis of the Constrained MSSM with Genetic Algorithms

The Constrained Minimal Supersymmetric Standard Model (CMSSM) is one of the simplest and most widely-studied supersymmetric extensions to the standard model of particle physics. Nevertheless, current data do not sufficiently constrain the model parameters in a way completely independent of priors, statistical measures and scanning techniques. We present a new technique for scanning supersymmetric parameter spaces, optimised for frequentist profile likelihood analyses and based on Genetic Algorithms. We apply this technique to the CMSSM, taking into account existing collider and cosmological data in our global fit. We compare our method to the MultiNest algorithm, an efficient Bayesian technique, paying particular attention to the best-fit points and implications for particle masses at the LHC and dark matter searches. Our global best-fit point lies in the focus point region. We find many high-likelihood points in both the stau co-annihilation and focus point regions, including a previously neglected section of the co-annihilation region at large m_0. We show that there are many high-likelihood points in the CMSSM parameter space commonly missed by existing scanning techniques, especially at high masses. This has a significant influence on the derived confidence regions for parameters and observables, and can dramatically change the entire statistical inference of such scans.Comment: 47 pages, 8 figures; Fig. 8, Table 7 and more discussions added to Sec. 3.4.2 in response to referee's comments; accepted for publication in JHE

Determining solar effects in Neptune’s atmosphere

Long-duration observations of Neptune’s brightness in two visible wavelengths provide a disk-averaged estimate of its atmospheric aerosol. Brightness variations were previously associated with the 11-year solar cycle, through solar-modulated mechanisms linked with either ultra-violet (UV) or galactic cosmic ray (GCR) effects on atmospheric particles. Here we use a recently extended brightness dataset (1972-2014), with physically realistic modelling to show that rather than alternatives, UV and GCR are likely to be modulating Neptune’s atmosphere in combination. The importance of GCR is further supported by the response of Neptune's atmosphere to an intermittent 1.5 to 1.9 year periodicity, which occurred preferentially in GCR (not UV) during the mid-1980s. This periodicity was detected both at Earth, and in GCR measured by Voyager 2, then near Neptune. A similar coincident variability in Neptune’s brightness suggests nucleation onto GCR ions. Both GCR and UV mechanisms may occur more rapidly than the subsequent atmospheric particle transport