Low Linolenic Acid Soybean Variety Trial

Major food providers such as Wendy’s and Applebee’s are switching to zero trans fats in their cooking oil. Trans fats, which do not normally exist in vegetable oils, are formed during the process of partial hydrogenation. New soybean varieties, which produce an oil that is superior to alternative non-hydrogenated oils high in unhealthy saturated fats, have become available. These varieties have a lower percentage of linolenic acid than conventional varieties and command a premium price. This study was conducted to determine if low linolenic (low-lin) varieties yield as well as conventional varieties

A Study and Critique of the Mean Position Concept in Relativistic Wave Mechanics

The basic concept to be used in studying the question of one-particle interpretations of relativistic wave equations is that of observables and operator representations that are different from the more usual classically motivated observables and representations. In particular, the concept of a mean-position observable will be used to determine to what extent the one-particle "problems" can be resolved

syn,syn-15,17-Di-2-naphthyl­hexa­cyclo­[10.2.1.13,10.15,8.02,11.04,9]hepta­decane deuterochloro­form monosolvate

The main molecule of the title compound, C37H36·CDCl3, is a hydro­carbon with two naphthalene segments attached to opposite ends of a rigid norbornylogous spacer with an overall structure that is approximately C-shaped. The dihedral angle between the naphthalene ring planes is 9.27 (7)°. The cleft that exists between the naphthalene rings is large enough that the compound crystallizes with a solvent mol­ecule (CDCl3) in the cleft. The CDCl3 solvent mol­ecule is present in two disordered orientations in a 3:2 ratio, each involving C—D⋯π to C 6 ring centers

Learning Quantum Systems

The future development of quantum technologies relies on creating and manipulating quantum systems of increasing complexity, with key applications in computation, simulation and sensing. This poses severe challenges in the efficient control, calibration and validation of quantum states and their dynamics. Although the full simulation of large-scale quantum systems may only be possible on a quantum computer, classical characterization and optimization methods still play an important role. Here, we review different approaches that use classical post-processing techniques, possibly combined with adaptive optimization, to learn quantum systems, their correlation properties, dynamics and interaction with the environment. We discuss theoretical proposals and successful implementations across different multiple-qubit architectures such as spin qubits, trapped ions, photonic and atomic systems, and superconducting circuits. This Review provides a brief background of key concepts recurring across many of these approaches with special emphasis on the Bayesian formalism and neural networks.Comment: Review. 20 pages, 4 figures and 2 boxes (reformatted

Annual Report: 2011-2012 Storm Season Sampling, Non-Dry Dock Stormwater Monitoring for Puget Sound Naval Shipyard, Bremerton, WA

Annual PSNS non-dry dock storm water monitoring results for 2011-2012 storm season. Included are a brief description of the sampling procedures, storm event information, laboratory methods and data collection, a results and discussion section, and the conclusions and recommendations

Annual Report: 2011-2012 Storm Season Sampling, Non-Dry Dock Stormwater Monitoring for Puget Sound Naval Shipyard, Bremerton, WA

Annual PSNS non-dry dock storm water monitoring results for 2011-2012 storm season. Included are a brief description of the sampling procedures, storm event information, laboratory methods and data collection, a results and discussion section, and the conclusions and recommendations

Applying support-vector machine learning algorithms toward predicting host-guest interactions with cucurbit[7]uril.

Machine learning is a valuable tool in the development of chemical technologies but its applications into supramolecular chemistry have been limited. Here, the utility of kernel-based support vector machine learning using density functional theory calculations as training data is evaluated when used to predict equilibrium binding coefficients of small molecules with cucurbit[7]uril (CB[7]). We find that utilising SVMs may confer some predictive ability. This algorithm was then used to predict the binding of drugs TAK-580 and selumetinib. The algorithm did predict strong binding for TAK-580 and poor binding for selumetinib, and these results were experimentally validated. It was discovered that the larger homologue cucurbit[8]uril (CB[8]) is partial to selumetinib, suggesting an opportunity for tunable release by introducing different concentrations of CB[7] or CB[8] into a hydrogel depot. We qualitatively demonstrated that these drugs may have utility in combination against gliomas. Finally, mass transfer simulations show CB[7] can independently tune the release of TAK-580 without affecting selumetinib. This work gives specific evidence that a machine learning approach to recognition of small molecules by macrocycles has merit and reinforces the view that machine learning may prove valuable in the development of drug delivery systems and supramolecular chemistry more broadly.A.T. and M.P.S. thank The Winston Churchill Foundation of the United States. A.T. thanks the National Science Foundation graduate research fellowship, the MIT Chemical Engineering first year fellowship, and the Churchill College post-graduate grant program. G.W. thanks the Leverhulme Trust (project: ‘Natural material innovation for sustainable living’). V.K.R. thanks the Swiss National Science Foundation (P2EZP2_168784). O.A.S. acknowledges EPSRC Programme grant Nano-Optics to controlled Nano- Chemistry (NOtCH, EP/L027151/1) for funding

Expression of vesicular glutamate transporters type 1 and 2 in sensory and autonomic neurons innervating the mouse colorectum

Vesicular glutamate transporters (VGLUTs) have been extensively studied in various neuronal systems, but their expression in visceral sensory and autonomic neurons remains to be analyzed in detail. Here we studied VGLUTs type 1 and 2 (VGLUT(1) and VGLUT(2) , respectively) in neurons innervating the mouse colorectum. Lumbosacral and thoracolumbar dorsal root ganglion (DRG), lumbar sympathetic chain (LSC), and major pelvic ganglion (MPG) neurons innervating the colorectum of BALB/C mice were retrogradely traced with Fast Blue, dissected, and processed for immunohistochemistry. Tissue from additional naïve mice was included. Previously characterized antibodies against VGLUT(1) , VGLUT(2) , and calcitonin gene-related peptide (CGRP) were used. Riboprobe in situ hybridization, using probes against VGLUT(1) and VGLUT(2) , was also performed. Most colorectal DRG neurons expressed VGLUT(2) and often colocalized with CGRP. A smaller percentage of neurons expressed VGLUT(1) . VGLUT(2) -immunoreactive (IR) neurons in the MPG were rare. Abundant VGLUT(2) -IR nerves were detected in all layers of the colorectum; VGLUT(1) -IR nerves were sparse. A subpopulation of myenteric plexus neurons expressed VGLUT2 protein and mRNA, but VGLUT1 mRNA was undetectable. In conclusion, we show 1) that most colorectal DRG neurons express VGLUT(2) , and to a lesser extent, VGLUT(1) ; 2) abundance of VGLUT2-IR fibers innervating colorectum; and 3) a subpopulation of myenteric plexus neurons expressing VGLUT(2). Altogether, our data suggests a role for VGLUT(2) in colorectal glutamatergic neurotransmission, potentially influencing colorectal sensitivity and motility.Fil: Brumovsky, Pablo Rodolfo. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Univeristy of Pittsburgh. School of Medicine; Estados Unidos. Universidad Austral; ArgentinaFil: Robinson, David R.. Univeristy of Pittsburgh. School of Medicine; Estados Unidos. University of Pittsburgh at Johnstown; Estados Unidos. University of Pittsburgh; Estados UnidosFil: La, Jun Ho. Univeristy of Pittsburgh. School of Medicine; Estados UnidosFil: Seroogy, Kim B.. No especifíca;Fil: Lundgren, Kerstin H.. No especifíca;Fil: Albers, Kathryn M.. Univeristy of Pittsburgh. School of Medicine; Estados UnidosFil: Kiyatkin, Michael E.. Univeristy of Pittsburgh. School of Medicine; Estados UnidosFil: Seal, Rebecca P.. No especifíca;Fil: Edwards, Robert H.. No especifíca;Fil: Watanabe, Masahiko. No especifíca;Fil: Hökfelt, Tomas. Karolinska Huddinge Hospital. Karolinska Institutet; SueciaFil: Gebhart, G. F.. Univeristy of Pittsburgh. School of Medicine; Estados Unido

A brain-based pain facilitation mechanism contributes to painful diabetic polyneuropathy.

The descending pain modulatory system represents one of the oldest and most fundamentally important neurophysiological mechanisms relevant to pain. Extensive work in animals and humans has shown how a functional imbalance between the facilitatory and inhibitory components is linked to exacerbation and maintenance of persistent pain states. Forward translation of these findings into clinical populations is needed to verify the relevance of this imbalance. Diabetic polyneuropathy is one of the most common causes of chronic neuropathic pain; however, the reason why ∼25–30% of patients with diabetes develop pain is not known. The current study used a multimodal clinical neuroimaging approach to interrogate whether the sensory phenotype of painful diabetic polyneuropathy involves altered function of the ventrolateral periaqueductal grey—a key node of the descending pain modulatory system. We found that ventrolateral periaqueductal grey functional connectivity is altered in patients suffering from painful diabetic polyneuropathy; the magnitude of which is correlated to their spontaneous and allodynic pain as well as the magnitude of the cortical response elicited by an experimental tonic heat paradigm. We posit that ventrolateral periaqueductal grey-mediated descending pain modulatory system dysfunction may reflect a brain-based pain facilitation mechanism contributing to painful diabetic polyneuropathy.Funding for this work was generously provided from the following sources: National Institute for Health Research Oxford Biomedical Research Centre, Medical Research Council of Great Britain and Northern Ireland, the Wellcome Trust (London, UK) and the Innovative Medicines Initiative Joint Undertaking (Brussels, Belgium), under grant agreement no 115007 resources of which are composed of financial contribution from the European Union’s Seventh Framework Programme (FP7/2007–2013) and EFPIA companies’ in kind contribution. D.L.B. and A.C.T. are members of the DOLORisk consortium funded by the European Commission Horizon 2020 (ID633491). D.L.B. and A.C.T. are members of the International Diabetic Neuropathy Consortium, the Novo Nordisk Foundation (Ref. NNF14SA0006). D.L.B. is a senior Wellcome clinical scientist (Ref. 202747/Z/16/Z). The project was supported by a strategic award from the Wellcome (Ref. 102645). A.R.S., D.L.B., and I.T. are members of the Wellcome Pain Consortium (Ref. 102645). A.C.T. is an Honorary Research Fellow of the Brain Function Research Group, School of Physiology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa

Assessment of Epidermal Growth Factor Receptor (EGFR) expression in human meningioma

<p>Abstract</p> <p>Purpose</p> <p>This study explores whether meningioma expresses epidermal growth factor receptor (EGFR) and determines if there is a correlation between the WHO grade of this tumor and the degree of EGFR expression.</p> <p>Methods</p> <p>Following institutional review board approval, 113 meningioma specimens from 89 patients were chosen. Of these, 85 were used for final analysis. After a blinded review, immunohistochemical stains for EGFR were performed. Staining intensity (SI) was scored on a scale 0-3 (from no staining to strong staining). Staining percentage of immunoreactive cells (SP) was scored 1-5 (from the least to the maximum percent of the specimen staining). Immunohistochemical score (IHS) was calculated as the product of SI and SP.</p> <p>Results</p> <p>Eighty-five samples of meningioma were classified in accordance with World Health Organization (WHO) criteria: benign 57/85 (67%), atypical 23/85 (27%), and malignant 5/85 (6%). The majority of samples demonstrated a moderate SI for EGFR. IHS for EGFR demonstrated a significant association between SI and histopathologic subtype. Also, there was a correlation between the SP and histopathologic subtype (p = 0.029). A significant association was determined when the benign and the atypical samples were compared to the malignant with respect to the SP (p = 0.009). While there was a range of the IHS for the benign and the atypical histologic subtypes, malignant tumors exhibited the lowest score and were statistically different from the benign and the atypical specimens (p < 0.001).</p> <p>Conclusions</p> <p>To our knowledge, this represents the largest series of meningioma samples analyzed for EGFR expression reported in the literature. EGFR expression is greatest in benign meningiomas and may serve a potential target for therapeutic intervention with selective EGFR inhibitors.</p