Capillary liquid chromatography fraction collection and postcolumn reaction using segmented flow microfluidics

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/101795/1/jssc3478.pd

Transient Heat Partition Factor for a Sliding Railcar Wheel

During a wheel slide the frictional heat generated at the contact interface causes intense heating of the adjacent wheel material. If this material exceeds the austenitising temperature and then cools quickly enough, it can transform into martensite, which may ultimately crack and cause wheel failure. A knowledge of the distribution of the heat partitioned into the wheel and the rail and the resulting temperature fields is critical to developing designs to minimize these deleterious effects. A number of theoretical solutions have appeared in the literature to model the thermal aspects of this phenomenon. The objective of this investigation was to examine the limitations of these solutions by comparing them to the results of a finite element analysis that does not incorporate many of the simplifying assumptions on which these solutions are based. It was found that these simplified solutions can produce unrealistic results under some circumstances

CE‐MS with electrokinetic supercharging and application to determination of neurotransmitters

Electrokinetic supercharging (EKS) is known as one of the most effective online electrophoretic preconcentration techniques, though pairing with it with mass spectrometry has presented challenges. Here, EKS is successfully paired with ESI‐MS/MS to provide a sensitive and robust method for analysis of biogenic amines in biological samples. Injection parameters including electric field strength and the buffer compositions used for the separation and focusing were investigated to achieve suitable resolution, high sensitivity, and compatibility with ESI‐MS. Using EKS, the sensitivity of the method was improved 5000‐fold compared to a conventional hydrodynamic injection with CZE. The separation allowed for baseline resolution of several neurotransmitters within 16 min with LODs down to 10 pM. This method was applied to targeted analysis of seven biogenic amines from rat brain stem and whole Drosophila tissue. This is the first method to use EKS with CE‐ESI‐MS/MS to analyze biological samples.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/153096/1/elps7049.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/153096/2/elps7049_am.pd

Structural characterization of three hydride-bridged sodium aluminate compounds

Funding information MTW thanks the University of Strathclyde for funding his PhD via a Research Excellence Award.Peer reviewedPublisher PD

Clinical Features and Management of Chronic Chikungunya Arthritis

Chikungunya virus is a single-stranded RNA alphavirus transmitted to humans by Aedes species mosquitos, causing an acute illness known as chikungunya fever with maculopapular rash, headache, polyarthritis/arthralgias, and gastrointestinal symptoms. Up to half of affected patients develop a chronic disabling arthritis following resolution of the acute infection, which can last for months or even years. The pathophysiology of chronic chikungunya arthritis remains controversial; it may result from a dysregulated immune response or be caused by persistent viral infection. Treatment for patients with chronic chikungunya arthritis remains investigational. Limited data suggests that immunosuppressive therapies such as methotrexate and TNF alpha inhibitors may be beneficial, though randomized clinical trials are needed

Burn wound classification model using spatial frequency-domain imaging and machine learning.

Accurate assessment of burn severity is critical for wound care and the course of treatment. Delays in classification translate to delays in burn management, increasing the risk of scarring and infection. To this end, numerous imaging techniques have been used to examine tissue properties to infer burn severity. Spatial frequency-domain imaging (SFDI) has also been used to characterize burns based on the relationships between histologic observations and changes in tissue properties. Recently, machine learning has been used to classify burns by combining optical features from multispectral or hyperspectral imaging. Rather than employ models of light propagation to deduce tissue optical properties, we investigated the feasibility of using SFDI reflectance data at multiple spatial frequencies, with a support vector machine (SVM) classifier, to predict severity in a porcine model of graded burns. Calibrated reflectance images were collected using SFDI at eight wavelengths (471 to 851 nm) and five spatial frequencies (0 to 0.2  mm  -  1). Three models were built from subsets of this initial dataset. The first subset included data taken at all wavelengths with the planar (0  mm  -  1) spatial frequency, the second comprised data at all wavelengths and spatial frequencies, and the third used all collected data at values relative to unburned tissue. These data subsets were used to train and test cubic SVM models, and compared against burn status 28 days after injury. Model accuracy was established through leave-one-out cross-validation testing. The model based on images obtained at all wavelengths and spatial frequencies predicted burn severity at 24 h with 92.5% accuracy. The model composed of all values relative to unburned skin was 94.4% accurate. By comparison, the model that employed only planar illumination was 88.8% accurate. This investigation suggests that the combination of SFDI with machine learning has potential for accurately predicting burn severity

Defect filtering for thermal expansion induced dislocations in III-V lasers on silicon

Epitaxially integrated III-V semiconductor lasers for silicon photonics have the potential to dramatically transform information networks, but currently, dislocations limit performance and reliability even in defect tolerant InAs quantum dot (QD) based lasers. Despite being below critical thickness, QD layers in these devices contain previously unexplained misfit dislocations, which facilitate non-radiative recombination. We demonstrate here that these misfit dislocations form during post-growth cooldown due to the combined effects of (1) thermal-expansion mismatch between the III-V layers and silicon and (2) precipitate and alloy hardening in the active region. By incorporating an additional sub-critical thickness, indium-alloyed misfit dislocation trapping layer, we leverage these mechanical hardening effects to our advantage, successfully displacing 95% of misfit dislocations from the QD layer in model structures. Unlike conventional dislocation mitigation strategies, the trapping layer reduces neither the number of threading dislocations nor the number of misfit dislocations. It simply shifts the position of misfit dislocations away from the QD layer, reducing the defects' impact on luminescence. In full lasers, adding a misfit dislocation trapping layer both above and below the QD active region displaces misfit dislocations and substantially improves performance: we measure a twofold reduction in lasing threshold currents and a greater than threefold increase in output power. Our results suggest that devices employing both traditional threading dislocation reduction techniques and optimized misfit dislocation trapping layers may finally lead to fully integrated, commercially viable silicon-based photonic integrated circuits.Comment: 9 pages, 6 figure

Data representing two separate LC-MS methods for detection and quantification of water-soluble and fat-soluble vitamins in tears and blood serum

Tears serve as a viable diagnostic fluid with advantages including less invasive sample to collect and less complex to prepare for analysis. Several water-soluble and fat-soluble vitamins were detected and quantified in human tears and compared with blood serum levels. Samples from 15 family pairs, each pair consisting of a four-month-old infant and one parent were analyzed; vitamin concentrations were compared between tears and blood serum for individual subjects, between infants and parents, and against self-reported dietary intakes. Water-soluble vitamins B1, B2, B3 (nicotinamide), B5, B9 and fat-soluble vitamin E (α-tocopherol) were routinely detected in tears and blood serum while fat-soluble vitamin A (retinol) was detected only in blood serum. Water-soluble vitamin concentrations measured in tears and blood serum of single subjects were comparable, while higher concentrations were measured in infants compared to their parents. Fat-soluble vitamin E concentrations were lower in tears than blood serum with no significant difference between infants and parents. Serum vitamin A concentrations were higher in parents than infants. Population trends were compiled and quantified using a cross correlation factor. Strong positive correlations were found between tear and blood serum concentrations of vitamin E from infants and parents and vitamin B3 concentrations from parents, while slight positive correlations were detected for infants B3 and parents B1 and B2 concentrations. Correlations between infants and parents were found for the concentrations of B1, B2, B3, and E in tears, and the concentrations of B2, A, and E in blood serum. Stronger vitamin concentration correlations were found between infants and parents for the breast-fed infants, while no significant difference was observed between breast-fed and bottle-fed infants. This work is the first to demonstrate simultaneous vitamin A, B, and E detection and to quantify correlations between vitamin concentrations in tears and blood serum. Our results suggest that tears are a viable biofluid to monitor nutritional health because they sufficiently mirror blood serum data and may enhance the speed of deficiency diagnoses

Structural elaboration of the surprising ortho-zincation of benzyl methyl ether

Breaking with convention, the reaction of the sodium zincate, [(TMEDA)Na(μ-TMP)(μ-tBu)Zn(tBu)] with benzyl methyl ether (PhCH2OMe) produces exclusively an ortho-zincated intermediate [(TMEDA)Na(μ-TMP)(μ-C6H4CH2OMe)Zn(tBu)] instead of the expected 'thermodynamic' α-metallated product