Diffusion Tensor MRI to Assess Damage in Healthy and Dystrophic Skeletal Muscle after Lengthening Contractions

The purpose of this study was to determine if variables calculated from diffusion tensor imaging (DTI) would serve as a reliable marker of damage after a muscle strain injury in dystrophic (mdx) and wild type (WT) mice. Unilateral injury to the tibialis anterior muscle (TA) was induced in vivo by 10 maximal lengthening contractions. High resolution T1- and T2-weighted structural MRI, including T2 mapping and spin echo DTI was acquired on a 7T small animal MRI system. Injury was confirmed by a significant loss of isometric torque (85% in mdx versus 42% in WT). Greater increases in apparent diffusion coefficient (ADC), axial, and radial diffusivity (AD and RD) of the injured muscle were present in the mdx mice versus controls. These changes were paralleled by decreases in fractional anisotropy (FA). Additionally, T2 was increased in the mdx mice, but the spatial extent of the changes was less than those in the DTI parameters. The data suggest that DTI is an accurate indicator of muscle injury, even at early time points where the MR signal changes are dominated by local edema

Control via electron count of the competition between magnetism and superconductivity in cobalt and nickel doped NaFeAs

Using a combination of neutron, muon and synchrotron techniques we show how the magnetic state in NaFeAs can be tuned into superconductivity by replacing Fe by either Co or Ni. Electron count is the dominant factor, since Ni-doping has double the effect of Co-doping for the same doping level. We follow the structural, magnetic and superconducting properties as a function of doping to show how the superconducting state evolves, concluding that the addition of 0.1 electrons per Fe atom is sufficient to traverse the superconducting domain, and that magnetic order coexists with superconductivity at doping levels less than 0.025 electrons per Fe atom.Comment: 4 pages, 6 figure

Use of BODIPY (493/503) to Visualize Intramuscular Lipid Droplets in Skeletal Muscle

Triglyceride storage is altered across various chronic health conditions necessitating various techniques to visualize and quantify lipid droplets (LDs). Here, we describe the utilization of the BODIPY (493/503) dye in skeletal muscle as a means to analyze LDs. We found that the dye was a convenient and simple approach to visualize LDs in both sectioned skeletal muscle and cultured adult single fibers. Furthermore, the dye was effective in both fixed and nonfixed cells, and the staining seemed unaffected by permeabilization. We believe that the use of the BODIPY (493/503) dye is an acceptable alternative and, under certain conditions, a simpler method for visualizing LDs stored within skeletal muscle

A Fisher-Rao metric for paracatadioptric images of lines

In a central paracatadioptric imaging system a perspective camera takes an image of a scene reflected in a paraboloidal mirror. A 360° field of view is obtained, but the image is severely distorted. In particular, straight lines in the scene project to circles in the image. These distortions make it diffcult to detect projected lines using standard image processing algorithms. The distortions are removed using a Fisher-Rao metric which is defined on the space of projected lines in the paracatadioptric image. The space of projected lines is divided into subsets such that on each subset the Fisher-Rao metric is closely approximated by the Euclidean metric. Each subset is sampled at the vertices of a square grid and values are assigned to the sampled points using an adaptation of the trace transform. The result is a set of digital images to which standard image processing algorithms can be applied. The effectiveness of this approach to line detection is illustrated using two algorithms, both of which are based on the Sobel edge operator. The task of line detection is reduced to the task of finding isolated peaks in a Sobel image. An experimental comparison is made between these two algorithms and third algorithm taken from the literature and based on the Hough transform

The effect of finite-range interactions in classical transport theory

The effect of scattering with non-zero impact parameters between consituents in relativistic heavy ion collisions is investigated. In solving the relativistic Boltzmann equation, the characteristic range of the collision kernel is varied from approximately one fm to zero while leaving the mean-free path unchanged. Modifying this range is shown to significantly affect spectra and flow observables. The finite range is shown to provide effective viscosities, shear, bulk viscosity and heat conductivity, with the viscous coefficients being proportional to the square of the interaction range

Development of a decision support tool to facilitate primary care management of patients with abnormal liver function tests without clinically apparent liver disease [HTA03/38/02]. Abnormal Liver Function Investigations Evaluation (ALFIE)

Liver function tests (LFTs) are routinely performed in primary care, and are often the gateway to further invasive and/or expensive investigations. Little is known of the consequences in people with an initial abnormal liver function (ALF) test in primary care and with no obvious liver disease. Further investigations may be dangerous for the patient and expensive for Health Services. The aims of this study are to determine the natural history of abnormalities in LFTs before overt liver disease presents in the population and identify those who require minimal further investigations with the potential for reduction in NHS costs

Honeybee Colony Vibrational Measurements to Highlight the Brood Cycle

Insect pollination is of great importance to crop production worldwide and honey bees are amongst its chief facilitators. Because of the decline of managed colonies, the use of sensor technology is growing in popularity and it is of interest to develop new methods which can more accurately and less invasively assess honey bee colony status. Our approach is to use accelerometers to measure vibrations in order to provide information on colony activity and development. The accelerometers provide amplitude and frequency information which is recorded every three minutes and analysed for night time only. Vibrational data were validated by comparison to visual inspection data, particularly the brood development. We show a strong correlation between vibrational amplitude data and the brood cycle in the vicinity of the sensor. We have further explored the minimum data that is required, when frequency information is also included, to accurately predict the current point in the brood cycle. Such a technique should enable beekeepers to reduce the frequency with which visual inspections are required, reducing the stress this places on the colony and saving the beekeeper time

Drone-based Water Sampling and Characterization of Three Freshwater Harmful Algal Blooms in the United States

Freshwater harmful algal blooms (HABs), caused mostly by toxic cyanobacteria, produce a range of cyanotoxins that threaten the health of humans and domestic animals. Climate conditions and anthropogenic influences such as agricultural run-off can alter the onset and intensity of HABs. Little is known about the distribution and spread of freshwater HABs. Current sampling protocols in some lakes involve teams of researchers that collect samples by hand from a boat and/or from the shoreline. Water samples can be collected from the surface, from discrete-depth collections, and/or from depth-integrated intervals. These collections are often restricted to certain months of the year, and generally are only performed at a limited number of collection sites. In lakes with active HABs, surface samples are generally sufficient for HAB water quality assessments. We used a unique DrOne Water Sampling SystEm (DOWSE) to collect water samples from the surface of three different HABs in Ohio (Grand Lake St Marys, GLSM and Lake Erie) and Virginia (Lake Anna), United States in 2019. The DOWSE consisted of a 3D-printed sampling device tethered to a drone (uncrewed aerial system, or UAS), and was used to collect surface water samples at different distances (10–100 m) from the shore or from an anchored boat. One hundred and eighty water samples (40 at GLSM, 20 at Lake Erie, and 120 at Lake Anna) were collected and analyzed from 18 drone flights. Our methods included testing for cyanotoxins, phycocyanin, and nutrients from surface water samples. Mean concentrations of microcystins (MCs) in drone water samples were 15.00, 1.92, and 0.02 ppb for GLSM, Lake Erie, and Lake Anna, respectively. Lake Anna had low levels of anatoxin in nearly all (111/120) of the drone water samples. Mean concentrations of phycocyanin in drone water samples were 687, 38, and 62 ppb for GLSM, Lake Erie, and Lake Anna, respectively. High levels of total phosphorus were observed in the drone water samples from GLSM (mean of 0.34 mg/L) and Lake Erie (mean of 0.12 mg/L). Lake Anna had the highest variability of total phosphorus with concentrations that ranged from 0.01 mg/L to 0.21 mg/L, with a mean of 0.06 mg/L. Nitrate levels varied greatly across sites, inverse with bloom biomass, ranging from below detection to 3.64 mg/L, with highest mean values in Lake Erie followed by GLSM and Lake Anna, respectively. Drones offer a rapid, targeted collection of water samples from virtually anywhere on a lake with an active HAB without the need for a boat which can disturb the surrounding water. Drones are, however, limited in their ability to operate during inclement weather such as rain and heavy winds. Collectively, our results highlight numerous opportunities for drone-based water sampling technologies to track, predict, and respond to HABs in the future