1,725 research outputs found

    The Role of the PGC1α Gly482Ser Polymorphism in Weight Gain due to Intensive Diabetes Therapy

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    The Diabetes Control and Complications Trial (DCCT) involved intensive diabetes therapy of subjects with type 1 diabetes mellitus (T1DM) for an average period of 6.5 years. A subset of these subjects gained excessive weight. We tested for association of polymorphisms in 8 candidate genes with the above trait. We found the Gly482Ser polymorphism in the peroxisome proliferator-activated receptor γ coactivator-1α (PGC1α) to be significantly associated with weight gain in males (P = .0045) but not in females. The Ser allele was associated with greater weight gain than the Gly allele (P = .005). Subjects with a family history of type 2 diabetes mellitus (T2DM) were more common among those who gained excessive weight. We conclude that T2DM and the Gly482Ser polymorphism in PGC1α contribute to the effect of intensive diabetes therapy on weight gain in males with T1DM

    Hankel determinant for a class of analytic functions of complex order defined by convolution

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    In this paper, we obtain the Fekete-Szego inequalities for the functions of complex order defined by convolution. Also, we find upper bounds for the second Hankel determinant a2a4a32|a_2a_4-a_3^2| for functions belonging to the class Sγb(g(z);A,B)S_{\gamma}^b(g(z);A,B)

    Academic Collaborative Efforts to Promote STEM Equity in High Needs Schools

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    America is at risk of facing a shortage of workers in STEM fields in the near future because lack of interest by its youth. It is well known that providing early exposure for P-12 students to engaging science, technology, engineering, and math (STEM) experiences can lead to lifelong learning and positively impact future career decisions. This manuscript describes one university’s collective efforts to bring equity to STEM education for an urban high needs school district in the northeastern part of the United States through various STEM initiatives over a five-year period. Through multiple projects and initiatives targeting both P-12 students and their teachers, descriptive results revealed a positive impact while pinpointing areas that still require attention. P-12 students indicated an increase in STEM knowledge and an increased interest in STEM careers following exposure to various STEM lessons and interactive experiences. P-12 teachers specified that Professional Development (PD) they received from university faculty as well as engaging in STEM experiences with their students enhanced their confidence in their ability to incorporate STEM lessons within their classrooms. An urban partner administrator viewed these various STEM initiatives as vital in their quest to bring equity for STEM education to their diverse student population

    Machine Learning-based Classification of Diffuse Large B-cell Lymphoma Patients by Their Protein Expression Profiles

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    Characterization of tumors at the molecular level has improved our knowledge of cancer causation and progression. Proteomic analysis of their signaling pathways promises to enhance our understanding of cancer aberrations at the functional level, but this requires accurate and robust tools. Here, we develop a state of the art quantitative mass spectrometric pipeline to characterize formalin-fixed paraffin-embedded tissues of patients with closely related subtypes of diffuse large B-cell lymphoma. We combined a super-SILAC approach with label-free quantification (hybrid LFQ) to address situations where the protein is absent in the super-SILAC standard but present in the patient samples. Shotgun proteomic analysis on a quadrupole Orbitrap quantified almost 9,000 tumor proteins in 20 patients. The quantitative accuracy of our approach allowed the segregation of diffuse large B-cell lymphoma patients according to their cell of origin using both their global protein expression patterns and the 55-protein signature obtained previously from patient-derived cell lines (Deeb, S. J., D'Souza, R. C., Cox, J., Schmidt-Supprian, M., and Mann, M. (2012) Mol. Cell. Proteomics 11, 77-89). Expression levels of individual segregation-driving proteins as well as categories such as extracellular matrix proteins behaved consistently with known trends between the subtypes. We used machine learning (support vector machines) to extract candidate proteins with the highest segregating power. A panel of four proteins (PALD1, MME, TNFAIP8, and TBC1D4) is predicted to classify patients with low error rates. Highly ranked proteins from the support vector analysis revealed differential expression of core signaling molecules between the subtypes, elucidating aspects of their pathobiology

    Understanding the Molecular and Structural Selectivity of Oxidant-induced Nitration and its Reversal in Sarcoplasmic Reticulum Ca2+ -ATPase SERCA2a vs. SERCA1a

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    The present study uses existing sequence (SERCA1a & SERCA2a) and structure (SERCA1a) information to extrapolate a tertiary structure construct for SERCA2a using computational modeling software. A comparison of SERCA1a and SERCA2a models could reveal structural anomalies that explain the basis for selective and specific Tyr nitration in SERCA2a but not SERCA1a

    Autofluorescence of routinely hematoxylin and eosinstained sections without exogenous markers

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    Hematoxylin and eosin stained paraffin section was examined by fluorescence microscopy to study the pattern and distribution of fluorescence. Autofluorescence was sensitive and specific for detection ofelastic and collagen fibers. It was concluded that analytical morphological techniques based on autofluorescence can obtain information about morphological and pathological state of tissue and cells

    Molecular Symmetry Properties of Conical Intersections and Nonadiabatic Coupling Terms: Theory and Quantum Chemical Demonstration for Cyclopenta-2,4-dienimine (C5H4NH)

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    This paper discovers molecular symmetry (MS) properties of conical intersections (CIs) and the related nonadiabatic coupling terms (NACTs) in molecules which allow large amplitude motions such as torsion, in the frame of the relevant molecular symmetry group, focusing on groups with one-dimensional (1-d) irreducible representations (IREPs). If one employs corresponding MS-adapted nuclear coordinates, the NACTs can be classified according to those IREPs. The assignment is supported by theorems which relate the IREPs of different NACTs to each other, and by properties of the NACTs related to the CIs. For example, planar contour integrals of the NACTs evaluated along loops around the individual CIs are equal to +π or -π, depending on the IREP-adapted signs of the NACTs. The + or - signs for the contour integrals may also be used to define the “charges” and IREPs of the CIs. We derive various general molecular symmetry properties of the related NACTs and CIs. These provide useful applications; e.g., the discovery of an individual CI allows one to generate, by means of all molecular symmetry operations, the complete set of CIs at different symmetry-related locations. Also, we show that the seams of CIs with different IREPs may have different topologies in a specific plane of MS-adapted coordinates. Moreover, the IREPs impose symmetrical nodes of the NACTs, and this may support their calculations by quantum chemical ab initio methods, even far away from the CIs. The general approach is demonstrated by application to an example. Specifically, we investigate the CIs and NACTs of cyclopenta-2,4-dienimine (C5H4NH) which has C2V(M) molecular symmetry with 1-d IREPs. The results are confirmed by quantum chemical calculations, starting from the location of a CI based on the Longuet-Higgins phase change theorem, until a proof of self-consistency, i.e., the related symmetryadapted NACTs fulfill quantization rules which have been derived in [Baer, M. Beyond Born-Oppenheimer: Electronic non-Adiabatic Coupling Terms and Conical Intersections; Wiley & Sons Inc.: Hoboken, NJ, 2006].We thank Prof. Lluis Blancafort, Prof. Dietrich Haase, Prof. Yehuda Haas, PD Dr. Dirk Andrae, Mr. Thomas Grohmann, and Ms. Shireen Alfalah for advice and stimulating discussions, and Mr. Dominik Sattler for preparing Figures 1 and 2. This study was supported by the Deutsche Forschungsgemeinschaft in the framework of Project No. MA 515/22-2, and by Fonds der Chemischen Industrie

    Tissue microarrays and their use for preparation of reference slides for educational purposes in histology and histopathology

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    Use of Tissue array was first applied in 1998, and has received a significant amount of attention from the research community ever since. In this technique, a large number (up to 1000) of cylindrical tissue core extracted from \"donor\" paraffin block are deposited into \"recipient\" block. The aim was modification of the technique of tissue array for manual preparation of the recipient block and production of slides of educational interest in histology and histopathology. The area of interest was localized with the help of stained section, the area was punctured, and the cylindrical core of tissue removed was then introduced into another (recipient) paraffin block. Puncture method was suitable only for parenchymatous organs (liver, kidney, heart, spleen, etc.) but longitudinal sections were required for tubular (gastrointestinal tract, urinary tract, genital tract) and hollow organs (gallbladder, urinary bladder) and brain. The method described is of importance in procurement of materials for preparation of slides for educational purposes and in overcoming the shortage of these materials especially in the field of pathology African Journal of Health Sciences Vol. 13 (3-4) 2006: pp. 66-6

    Analysis of Potential Protein Biomarkers in Epithelial Ovarian Cancer Using the Gene Expression Omnibus Database

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    Michelle Davis and Ruba Deeb's poster examining the use of the Gene Expression Omnibus database to identify genetic protein biomarkers of epithelial ovarian cancer
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