Expression of transforming growth factor-beta isoforms and their receptors in chronic tendinosis

Chronic tendon lesions are degenerative conditions and may represent a failure to repair or remodel the extracellular matrix after repeated micro-injury. Since TGF-ß is strongly associated with tissue repair, we investigated the expression of TGF-ß isoforms (ß1, ß2 and ß3) and their 2 signalling receptors (TGF-ßRI and TGF-ßRII) in normal and pathological Achilles tendons. In all tissues, all 3 TGF-ß isoforms and the 2 receptors were present at sites of blood vessels. Cells in the matrix showed no staining for TGF-ß1 or ß3, while TGF-ß2 was associated with cells throughout the normal cadaver tendon. Tissue from tendons with pathological lesions showed an increase in cell numbers and percentage TGF-ß2 expression. TGF-ßRII showed a wide distribution in cells throughout the tissue sections. As with TGF-ß2, there was an increase in the number of cells expressing TGF-ßRII in pathological tissue. TGF-ßRI was restricted to blood vessels and was absent from the fibrillar matrix. We conclude that despite the presence and upregulation of TGF-ß2, TGF-ß signalling is not propagated due to the lack of TGF-ßRI. This might explain why chronic tendon lesions fail to resolve and suggests that the addition of exogenous TGF-ß will have little effect on chronic tendinopathy

User and provider perspectives on emergency obstetric care in a Tanzanian rural setting: A qualitative analysis of the three delays model in a field study

The aim of this field study was to analyze the main dynamics and conflicts in attending and providing good quality delivery care in a local Tanzanian rural setting. The women and their relatives did not see the problems of pregnancy and birth in isolation but in relation to multiple other problems they were facing in the context of poverty. Local health professionals were aware of the poor quality of care at health facilities but were still blaming the community. The study describes the difficulties within the conceptual framework of thewidely used “three delays model”to disentangle different perspectives and to identify a feasible strategy of action to improve access to timely and effective emergency obstetric care. There seems to be a need for a supplementary analytic model that more clearly has the health system as the central agent responsible for improving maternal health. A modified “actantial model is suggested for that purpose

The physiological effects of transcranial electrical stimulation do not apply to parameters commonly used in studies of cognitive neuromodulation

Transcranial direct current stimulation (tDCS) and transcranial random noise stimulation (tRNS) have been claimed to produce many remarkable enhancements in perception, cognition, learning and numerous clinical conditions. The physiological basis of the claims for tDCS rests on the finding that 1 mA of unilateral anodal stimulation increases cortical excitation and 1 mA of cathodal produces inhibition. Here we show that these classic excitatory and inhibitory effects do not hold for the bilateral stimulation or 2 mA intensity conditions favoured in cognitive enhancement experiments. This is important because many, including some of the most salient claims are based on experiments using 2 mA bilateral stimulation. The claims for tRNS are also based on unilateral stimulation. Here we show that, again the classic excitatory effects of unilateral tRNS do not extend to the bilateral stimulation preferred in enhancement experiments. Further, we show that the effects of unilateral tRNS do not hold when one merely doubles the stimulation duration. We are forced to two conclusions: (i) that even if all the data on TES enhancements are true, the physiological explanations on which the claims are based are at best not established but at worst false, and (ii) that we cannot explain, scientifically at least, how so many experiments can have obtained data consistent with physiological effects that may not exist

Biomolecular simulations at the exascale: From drug design to organelles and beyond.

The rapid advancement in computational power available for research offers to bring not only quantitative improvements, but also qualitative changes in the field of biomolecular simulation. Here, we review the state of biomolecular dynamics simulations at the threshold to exascale resources becoming available. Both developments in parallel and distributed computing will be discussed, providing a perspective on the state of the art of both. A main focus will be on obtaining binding and conformational free energies, with an outlook to macromolecular complexes and (sub)cellular assemblies

Random Matrix Theory and Chiral Symmetry in QCD

Random matrix theory is a powerful way to describe universal correlations of eigenvalues of complex systems. It also may serve as a schematic model for disorder in quantum systems. In this review, we discuss both types of applications of chiral random matrix theory to the QCD partition function. We show that constraints imposed by chiral symmetry and its spontaneous breaking determine the structure of low-energy effective partition functions for the Dirac spectrum. We thus derive exact results for the low-lying eigenvalues of the QCD Dirac operator. We argue that the statistical properties of these eigenvalues are universal and can be described by a random matrix theory with the global symmetries of the QCD partition function. The total number of such eigenvalues increases with the square root of the Euclidean four-volume. The spectral density for larger eigenvalues (but still well below a typical hadronic mass scale) also follows from the same low-energy effective partition function. The validity of the random matrix approach has been confirmed by many lattice QCD simulations in a wide parameter range. Stimulated by the success of the chiral random matrix theory in the description of universal properties of the Dirac eigenvalues, the random matrix model is extended to nonzero temperature and chemical potential. In this way we obtain qualitative results for the QCD phase diagram and the spectrum of the QCD Dirac operator. We discuss the nature of the quenched approximation and analyze quenched Dirac spectra at nonzero baryon density in terms of an effective partition function. Relations with other fields are also discussed.Comment: invited review article for Ann. Rev. Nucl. Part. Sci., 61 pages, 11 figures, uses ar.sty (included); references added and typos correcte

Adaptive Optics for Astronomy

Adaptive Optics is a prime example of how progress in observational astronomy can be driven by technological developments. At many observatories it is now considered to be part of a standard instrumentation suite, enabling ground-based telescopes to reach the diffraction limit and thus providing spatial resolution superior to that achievable from space with current or planned satellites. In this review we consider adaptive optics from the astrophysical perspective. We show that adaptive optics has led to important advances in our understanding of a multitude of astrophysical processes, and describe how the requirements from science applications are now driving the development of the next generation of novel adaptive optics techniques.Comment: to appear in ARA&A vol 50, 201

Mapping UV properties throughout the cosmic horseshoe: Lessons from VLT-MUSE

We present the first spatially-resolved rest-frame UV study of the gravitationally lensed galaxy, the 'Cosmic Horseshoe' (J1148+1930) at z=2.38. Our gravitational lens model shows that the system is made up of four star-forming regions, each ~4-8 kpc^2 in size, from which we extract four spatially exclusive regional spectra. We study the interstellar and wind absorption lines, along with CIII] doublet emission lines, in each region to investigate any variation in emission/absorption line properties. The mapped CIII] emission shows distinct kinematical structure, with velocity offsets of ~+/-50 km/s between regions suggestive of a merging system, and a variation in equivalent width that indicates a change in ionisation parameter and/or metallicity between the regions. Absorption line velocities reveal a range of outflow strengths, with gas outflowing between -200<v(km/s)<-50 relative to the systemic velocity of that region. Interestingly, the strongest gas outflow appears to emanate from the most diffuse star-forming region. The star-formation rates remain relatively constant (~8-16 M_sol/yr), mostly due to large uncertainties in reddening estimates. As such, the outflows appear to be 'global' rather than 'locally' sourced. We measure electron densities with a range of log(Ne)=3.92-4.36 cm^-3, and point out that such high densities may be common when measured using the CIII] doublet due to its large critical density. Overall, our observations demonstrate that while it is possible to trace variations in large scale gas kinematics, detecting inhomogeneities in physical gas properties and their effects on the outflowing gas may be more difficult. This study provides important lessons for the spatially-resolved rest-frame UV studies expected with future observatories, such as JWST.BLJ thanks support from the European Space Agency (ESA) and SC acknowledges nancial support from the Science & Technology Facilities Council (STFC). The research leading to these results has received funding from the European Research Council under the European Union's Seventh Framework Programme (FP/2007-2013)/ERC Grant Agreement no. 308024

Sequence learning in Associative Neuronal-Astrocytic Network

The neuronal paradigm of studying the brain has left us with limitations in both our understanding of how neurons process information to achieve biological intelligence and how such knowledge may be translated into artificial intelligence and its most brain-derived branch, neuromorphic computing. Overturning our fundamental assumptions of how the brain works, the recent exploration of astrocytes is revealing that these long-neglected brain cells dynamically regulate learning by interacting with neuronal activity at the synaptic level. Following recent experimental evidence, we designed an associative, Hopfield-type, neuronal-astrocytic network and analyzed the dynamics of the interaction between neurons and astrocytes. We show that astrocytes were sufficient to trigger transitions between learned memories in the neuronal component of the network. Further, we mathematically derived the timing of the transitions that was governed by the dynamics of the calcium-dependent slow-currents in the astrocytic processes. Overall, we provide a brain-morphic mechanism for sequence learning that is inspired by, and aligns with, recent experimental findings. To evaluate our model, we emulated astrocytic atrophy and showed that memory recall becomes significantly impaired after a critical point of affected astrocytes was reached. This brain-inspired and brain-validated approach supports our ongoing efforts to incorporate non-neuronal computing elements in neuromorphic information processing.Comment: 8 pages, 5 figure

Three "universal" mesoscopic Josephson effects

1. Introduction 2. Supercurrent from Excitation Spectrum 3. Excitation Spectrum from Scattering Matrix 4. Short-Junction Limit 5. Universal Josephson Effects 5.1 Quantum Point Contact 5.2 Quantum Dot 5.3 Disordered Point Contact (Average supercurrent, Supercurrent fluctuations)Comment: 21 pages, 2 figures; legacy revie