1,456 research outputs found
Slow-light enhancement of Beer-Lambert-Bouguer absorption
We theoretically show how slow light in an optofluidic environment
facilitates enhanced light-matter interactions, by orders of magnitude. The
proposed concept provides strong opportunities for improving existing
miniaturized chemical absorbance cells for Beer-Lambert-Bouguer absorption
measurements widely employed in analytical chemistry.Comment: 4 pages including 4 figures. Accepted for AP
Coordinated analysis of age, sex, and education effects on change in MMSE scores
Objectives. We describe and compare the expected performance trajectories of older adults on the Mini-Mental Status Examination (MMSE) across six independent studies from four countries in the context of a collaborative network of longitudinal studies of aging. A coordinated analysis approach is used to compare patterns of change conditional on sample composition differences related to age, sex, and education. Such coordination accelerates evaluation of particular hypotheses. In particular, we focus on the effect of educational attainment on cognitive decline.Method. Regular and Tobit mixed models were fit to MMSE scores from each study separately. The effects of age, sex, and education were examined based on more than one centering point.Results. Findings were relatively consistent across studies. On average, MMSE scores were lower for older individuals and declined over time. Education predicted MMSE score, but, with two exceptions, was not associated with decline in MMSE over time.Conclusion. A straightforward association between educational attainment and rate of cognitive decline was not supported. Thoughtful consideration is needed when synthesizing evidence across studies, as methodologies adopted and sample characteristics, such as educational attainment, invariably differ. © 2012 The Author
Collaborative learning exercises for Teaching Protein Mass Spectrometry [post-print]
A collaborative learning module for teaching protein mass spectrometry has been developed to overcome common obstacles to incorporating the modern topic of biological mass spectrometry into the undergraduate chemistry curriculum. Protein mass spectrometry data is provided to eliminate the need for expensive instrumentation, and an instructor’s manual gives necessary details for those unfamiliar with the topic. The first section provides background information on proteins and the field of proteomics. The second section describes the use of electrospray ionization to determine the molecular weight of a protein. The third section shows how to identify a protein using peptide mass mapping, and the fourth section describes tandem MS experiments for de novo peptide sequencing. Each section also includes lessons on the analytical instrumentation used to make mass measurements including electrospray ionization, matrix assisted laser desorption ionization, and time-of-flight mass spectrometry. The module includes preclass reading assignments and small group problem solving exercises to be used during class sessions. The module was implemented over several semesters at both a small liberal arts college and a large research university. Assessment data from both institutions suggest that the module is effective in helping students to learn about mass-spectrometry-based proteomics. This freely available resource will assist instructors in introducing these topics to the undergraduate curriculum
Review of Student-Built Spectroscopy Instrumentation Projects
Copyright © 2020 American Chemical Society and Division of Chemical Education, Inc. One challenge of teaching chemical analysis is the proliferation of sophisticated, but often impenetrable, instrumentation in the modern laboratory. Complex instruments, and the software that runs them, distance students from the physical and chemical processes that generate the analytical signal. A solution to this challenge is the introduction of a student-driven instrument-building project. Visible absorbance spectroscopy is well-suited to such a project due to its relative simplicity and the ubiquity of absorbance measurements. This Article reviews simple instructor- A nd student-built instruments for spectroscopy, providing an overview of common designs, components, and applications. This comprehensive summary includes options that are suitable for in-person or remote learning with K-12 students and undergraduates in general chemistry, analytical chemistry, instrumental analysis, and electronics courses
Response to commentary “Zinc is decreased in prostate cancer: an established relationship of prostate cancer!”
10.1007/s00775-010-0737-8Journal of Biological Inorganic Chemistry1619-13JJBC
Nonlinear response of dense colloidal suspensions under oscillatory shear: Mode-coupling theory and FT-rheology experiments
Using a combination of theory, experiment and simulation we investigate the
nonlinear response of dense colloidal suspensions to large amplitude
oscillatory shear flow. The time-dependent stress response is calculated using
a recently developed schematic mode-coupling-type theory describing colloidal
suspensions under externally applied flow. For finite strain amplitudes the
theory generates a nonlinear response, characterized by significant higher
harmonic contributions. An important feature of the theory is the prediction of
an ideal glass transition at sufficiently strong coupling, which is accompanied
by the discontinuous appearance of a dynamic yield stress. For the oscillatory
shear flow under consideration we find that the yield stress plays an important
role in determining the non linearity of the time-dependent stress response.
Our theoretical findings are strongly supported by both large amplitude
oscillatory (LAOS) experiments (with FT-rheology analysis) on suspensions of
thermosensitive core-shell particles dispersed in water and Brownian dynamics
simulations performed on a two-dimensional binary hard-disc mixture. In
particular, theory predicts nontrivial values of the exponents governing the
final decay of the storage and loss moduli as a function of strain amplitude
which are in excellent agreement with both simulation and experiment. A
consistent set of parameters in the presented schematic model achieves to
jointly describe linear moduli, nonlinear flow curves and large amplitude
oscillatory spectroscopy
Deep learning from MRI-derived labels enables automatic brain tissue classification on human brain CT
Automatic methods for feature extraction, volumetry, and morphometric analysis in clinical neuroscience typically operate on images obtained with magnetic resonance (MR) imaging equipment. Although CT scans are less expensive to acquire and more widely available than MR scans, their application is currently limited to the visual assessment of brain integrity and the exclusion of co-pathologies. CT has rarely been used for tissue classification because the contrast between grey matter and white matter was considered insufficient. In this study, we propose an automatic method for segmenting grey matter (GM), white matter (WM), cerebrospinal fluid (CSF), and intracranial volume (ICV) from head CT images. A U-Net deep learning model was trained and validated on CT images with MRI-derived segmentation labels. We used data from 744 participants of the Gothenburg H70 Birth Cohort Studies for whom CT and T1-weighted MR images had been acquired on the same day. Our proposed model predicted brain tissue classes accurately from unseen CT images (Dice coefficients of 0.79, 0.82, 0.75, 0.93 and 0.98 for GM, WM, CSF, brain volume and ICV, respectively). To contextualize these results, we generated benchmarks based on established MR-based methods and intentional image degradation. Our findings demonstrate that CT-derived segmentations can be used to delineate and quantify brain tissues, opening new possibilities for the use of CT in clinical practice and research
Identification and quantification of microplastics in wastewater using focal plane array-based reflectance micro-FT-IR imaging
Microplastics (<5 mm) have been documented in environmental samples on a global scale. While these pollutants may enter aquatic environments via wastewater treatment facilities, the abundance of microplastics in these matrices has not been investigated. Although efficient methods for the analysis of microplastics in sediment samples and marine organisms have been published, no methods have been developed for detecting these pollutants within organic-rich wastewater samples. In addition, there is no standardized method for analyzing microplastics isolated from environmental samples. In many cases, part of the identification protocol relies on visual selection before analysis, which is open to bias. In order to address this, a new method for the analysis of microplastics in wastewater was developed. A pretreatment step using 30% hydrogen peroxide (H2O2) was employed to remove biogenic material, and focal plane array (FPA)-based reflectance micro-Fourier-transform (FT-IR) imaging was shown to successfully image and identify different microplastic types (polyethylene, polypropylene, nylon-6, polyvinyl chloride, polystyrene). Microplastic-spiked wastewater samples were used to validate the methodology, resulting in a robust protocol which was nonselective and reproducible (the overall success identification rate was 98.33%). The use of FPA-based micro-FT-IR spectroscopy also provides a considerable reduction in analysis time compared with previous methods, since samples that could take several days to be mapped using a single-element detector can now be imaged in less than 9 h (circular filter with a diameter of 47 mm). This method for identifying and quantifying microplastics in wastewater is likely to provide an essential tool for further research into the pathways by which microplastics enter the environment.This work is funded by a NERC (Natural Environment Research Council) CASE studentship (NE/K007521/1) with contribution from industrial partner Fera Science Ltd., United Kingdom. The authors would like to thank Peter Vale, from Severn Trent Water Ltd, for providing access to and additionally Ashley Howkins (Brunel University London) for providing travel and assistance with the sampling of the Severn Trent wastewater treatment plant in Derbyshire, UK. We are grateful to Emma Bradley and Chris Sinclair for providing helpful suggestions for our research
Fruit and vegetable processing and food technology: a summary of research
Evaluation of tomato cultivars for processing / W. A. Gould and R. Stillabower -- Physical and subjective color evaluation of tomato juice / Kenneth L. Beck and W. A. Gould -- Flavor evaluation of tomato juice fortified with sugar and citric acid / J. A. Gould and W. A. Gould -- Effects of citric acid and sugar ratios on thermal resistance of Bacillus coagulans var. thermoacidurans in tomato juice / Dennis L. Gierhart and W. A. Gould -- Protein bodies of the germinating tomato seed cotyledon / L. K. Eggers and J. R. Geisman -- Studies concerning the protein of tomato seeds recovered from tomato cannery waste / L. K. Eggers and J. R. Geisman -- Lipid composition of cucumber / A. C. Peng -- Fatty acids in fresh and recycled brines / A. C. Peng and J. R. Geisman -- Repeated recycling of spent pickle brine affects pickle quality / J. R. Geisman and M. Lazear -- Evaluation of snap bean cultivars for processing / W. Gould, J. Gould, J. Mount, M. Skoog and R. Stillabower -- Evaluating strawberries for freezing / J. F. Gallander and J. F. Stetson -- Grapes for Ohio wines / J. F. Gallander and J. F. Stetso
- …