129 research outputs found

    A near-infrared survey of the entire R Corona Australis cloud

    Full text link
    To understand low- to intermediate-mass star-formation in the nearby R CrA molecular cloud, we try to identify the stellar content that is accessible with near-infrared observations. We obtained a JHK band mosaic of 10 x 60 arcmin square covering the entire RCrA molecular cloud with unprecedented sensitivity. We present a catalogue of about 3500 near-infrared sources fainter than the saturation limit K = 10 mag, reaching K = 18mag. We analysed the extended sources by inspecting their morphology and point sources by means of colour-colour and colour-magnitude diagrams. Additionally, we compared the extinction inferred from the NIR data with the line-of-sight dust emission at 1.2 mm. Sources towards high dust emission but relatively low H-K show a projected mm-exces; these sources are either immediately surrounded by cold circumstellar material or, if too red to be a true foreground object, they are embedded in the front layer of the 1.2 mm emitting dust cloud. In both cases they are most likely associated with the cloud.Comment: 11 pages, 12 Figures, accepted by Astronomy and Astrophysic

    Use of 1H and 31P HRMAS to evaluate the relationship between quantitative alterations in metabolite concentrations and tissue features in human brain tumour biopsies

    Full text link
    [EN] Quantitative multinuclear high-resolution magic angle spinning (HRMAS) was performed in order to determine the tissue pH values of and the absolute metabolite concentrations in 33 samples of human brain tumour tissue. Metabolite concentrations were quantified by 1D 1 H and 31P HRMAS using the electronic reference to in vivo concentrations (ERETIC) synthetic signal. 1 H–1 H homonuclear and 1 H–31P heteronuclear correlation experiments enabled the direct assessment of the 1 H–31P spin systems for signals that suffered from overlapping in the 1D 1 H spectra, and linked the information present in the 1D 1 H and 31P spectra. Afterwards, the main histological features were determined, and high heterogeneity in the tumour content, necrotic content and nonaffected tissue content was observed. The metabolite profiles obtained by HRMAS showed characteristics typical of tumour tissues: rather low levels of energetic molecules and increased concentrations of protective metabolites. Nevertheless, these characteristics were more strongly correlated with the total amount of living tissue than with the tumour cell contents of the samples alone, which could indicate that the sampling conditions make a significant contribution aside from the effect of tumour development in vivo. The use of methylene diphosphonic acid as a chemical shift and concentration reference for the 31P HRMAS spectra of tissues presented important drawbacks due to its interaction with the tissue. Moreover, the pH data obtained from 31P HRMAS enabled us to establish a correlation between the pH and the distance between the N(CH3)3 signals of phosphocholine and choline in 1 H spectra of the tissue in these tumour samples.The authors acknowledge the SCSIE-University of Valencia Microscopy Service for the histological preparations. They also acknowledge Martial Piotto (Bruker BioSpin, France) for providing the ERETIC synthetic signal. Furthermore, they acknowledge financial support from the Spanish Government project SAF2007-6547, the Generalitat Valenciana project GVACOMP2009-303, and the E.U.'s VI Framework Programme via the project "Web accessible MR decision support system for brain tumor diagnosis and prognosis, incorporating in vivo and ex vivo genomic and metabolomic data" (FP6-2002-LSH 503094). CIBER-BBN is an initiative funded by the VI National R&D&D&i Plan 2008-2011, Iniciativa Ingenio 2010, Consolider Program, CIBER Actions, and financed by the Instituto de Salud Carlos III with assistance from the European Regional Development Fund.Esteve Moya, V.; Celda, B.; Martínez Bisbal, MC. (2012). Use of 1H and 31P HRMAS to evaluate the relationship between quantitative alterations in metabolite concentrations and tissue features in human brain tumour biopsies. Analytical and Bioanalytical Chemistry. 403:2611-2625. https://doi.org/10.1007/s00216-012-6001-zS26112625403Cheng LL, Chang IW, Louis DN, Gonzalez RG (1998) Cancer Res 58:1825–1832Opstad KS, Bell BA, Griffiths JR, Howe FA (2008) Magn Reson Med 60:1237–1242Sjobakk TE, Johansen R, Bathen TF, Sonnewald U, Juul R, Torp SH, Lundgren S, Gribbestad IS (2008) NMR Biomed 21:175–185Martinez-Bisbal MC, Marti-Bonmati L, Piquer J, Revert A, Ferrer P, Llacer JL, Piotto M, Assemat O, Celda B (2004) NMR Biomed 17:191–205Erb G, Elbayed K, Piotto M, Raya J, Neuville A, Mohr M, Maitrot D, Kehrli P, Namer IJ (2008) Magn Reson Med 59:959–965Wilson M, Davies NP, Brundler MA, McConville C, Grundy RG, Peet AC (2009) Mol Cancer 8:6Martinez-Bisbal MC, Monleon D, Assemat O, Piotto M, Piquer J, Llacer JL, Celda B (2009) NMR Biomed 22:199–206Martínez-Granados B, Monleón D, Martínez-Bisbal MC, Rodrigo JM, del Olmo J, Lluch P, Ferrández A, Martí-Bonmatí L, Celda B (2006) NMR Biomed 19:90–100Hubesch B, Sappey-Marinier D, Roth K, Meyerhoff DJ, Matson GB, Weiner MW (1990) Radiology 174:401–409Albers MJ, Krieger MD, Gonzalez-Gomez I, Gilles FH, McComb JG, Nelson MD Jr, Bluml S (2005) Magn Reson Med 53:22–29Wijnen JP, Scheenen TW, Klomp DW, Heerschap A (2010) NMR Biomed 23:968–976Podo F (1999) NMR Biomed 12:413–439Griffiths JR, Cady E, Edwards RH, McCready VR, Wilkie DR, Wiltshaw E (1983) Lancet 1:1435–1436Robitaille PL, Robitaille PA, Gordon Brown G, Brown GG (1991) J Magn Reson 92:73–84, 1969Griffiths JR (1991) Br J Cancer 64:425–427Payne GS, Troy H, Vaidya SJ, Griffiths JR, Leach MO, Chung YL (2006) NMR Biomed 19:593–598De Silva SS, Payne GS, Thomas V, Carter PG, Ind TE, deSouza NM (2009) NMR Biomed 22:191–198Wang Y, Cloarec O, Tang H, Lindon JC, Holmes E, Kochhar S, Nicholson JK (2008) Anal Chem 80:1058–1066Lehnhardt FG, Rohn G, Ernestus RI, Grune M, Hoehn M (2001) NMR Biomed 14:307–317Srivastava NK, Pradhan S, Gowda GA, Kumar R (2010) NMR Biomed 23:113–122Akoka S, Barantin L, Trierweiler M (1999) Anal Chem 71:2554–2557Albers MJ, Butler TN, Rahwa I, Bao N, Keshari KR, Swanson MG, Kurhanewicz J (2009) Magn Reson Med 61:525–532Ben Sellem D, Elbayed K, Neuville A, Moussallieh FM, Lang-Averous G, Piotto M, Bellocq JP, Namer IJ (2011) J Oncol 2011:174019Bourne R, Dzendrowskyj T, Mountford C (2003) NMR Biomed 16:96–101Martinez-Bisbal MC, Esteve V, Martinez-Granados B, Celda B (2011) J Biomed Biotechnol 2011:763684, Epub 2010 Sep 5Celda B, Montelione GT (1993) J Magn Reson B 101:189–193Esteve V, Celda B (2008) Magn Reson Mater Phys MAGMA 21:484–484Collins TJ (2007) Biotechniques 43:25–30Govindaraju V, Young K, Maudsley AA (2000) NMR Biomed 13:129–153Fan TW-M (1996) Prog Nucl Magn Reson Spectrosc 28:161–219Ulrich EL, Akutsu H, Doreleijers JF, Harano Y, Ioannidis YE, Lin J, Livny M, Mading S, Maziuk D, Miller Z, Nakatani E, Schulte CF, Tolmie DE, Kent Wenger R, Yao H, Markley JL (2008) Nucleic Acids Res 36:D402–D408Kriat M, Vion-Dury J, Confort-Gouny S, Favre R, Viout P, Sciaky M, Sari H, Cozzone PJ (1993) J Lipid Res 34:1009–1019Subramanian A, Shankar Joshi B, Roy AD, Roy R, Gupta V, Dang RS (2008) NMR Biomed 21:272–288Daykin CA, Corcoran O, Hansen SH, Bjornsdottir I, Cornett C, Connor SC, Lindon JC, Nicholson JK (2001) Anal Chem 73:1084–1090Griffin JL, Lehtimaki KK, Valonen PK, Grohn OH, Kettunen MI, Yla-Herttuala S, Pitkanen A, Nicholson JK, Kauppinen RA (2003) Cancer Res 63:3195–3201Petroff OAC, Prichard JW (1995) In: Kraicer J, Dixon SJ (eds) Methods in neurosciences. Academic, San DiegoBarton S, Howe F, Tomlins A, Cudlip S, Nicholson J, Anthony Bell B, Griffiths J (1999) Magn Reson Mater Phys Biol Med 8:121–128Sitter B, Sonnewald U, Spraul M, Fjosne HE, Gribbestad IS (2002) NMR Biomed 15:327–337Coen M, Hong YS, Cloarec O, Rhode CM, Reily MD, Robertson DG, Holmes E, Lindon JC, Nicholson JK (2007) Anal Chem 79:8956–8966Russell D, Rubinstein LJ (1998) Russel and Rubinstein's pathology of tumors of the nervous system. Arnold, LondonTynkkynen T, Tiainen M, Soininen P, Laatikainen R (2009) Anal Chim Acta 648:105–112Kjaergaard M, Brander S, Poulsen F (2011) J Biomol NMR 49:139–149Robert O, Sabatier J, Desoubzdanne D, Lalande J, Balayssac S, Gilard V, Martino R, Malet-Martino M (2011) Anal Bioanal Chem 399:987–999Chadzynski GL, Bender B, Groeger A, Erb M, Klose U (2011) J Magn Reson 212:55–63Weljie AM, Jirik FR (2011) Int J Biochem Cell Biol 43:981–989Barba I, Cabanas ME, Arus C (1999) Cancer Res 59:1861–1868Liimatainen T, Hakumaki JM, Kauppinen RA, Ala-Korpela M (2009) NMR Biomed 22:272–279Opstad KS, Bell BA, Griffiths JR, Howe FA (2008) NMR Biomed 21:677–685Schmitz JE, Kettunen MI, Hu D, Brindle KM (2005) Magn Reson Med 54:43–50Glunde K, Artemov D, Penet MF, Jacobs MA, Bhujwalla ZM (2010) Chem Rev 110:3043–3059Hertz L (2008) Neuropharmacology 55:289–309Takahashi T, Otsuguro K, Ohta T, Ito S (2010) Br J Pharmacol 161:1806–181

    "I am pregnant and my husband has diabetes. Is there a risk for my child?" A qualitative study of questions asked by email about the role of genetic susceptibility to diabetes

    Get PDF
    <p>Abstract</p> <p>Background</p> <p>Diabetes Mellitus is a global health problem. Scientific knowledge on the genetics of diabetes is expanding and is more and more utilised in clinical practice and primary prevention strategies. Health consumers have become increasingly interested in genetic information. In the Netherlands, the <it>National Genetic Research and Information Center </it>provides online information about the genetics of diabetes and thereby offers website visitors the opportunity to ask a question per email. The current study aims at exploring people's need of (additional) information about the role of inheritance in diabetes. Results may help to tailor existing clinical and public (online) genetic information to the needs of an increasing population at risk for diabetes.</p> <p>Methods</p> <p>A data base with emailed questions about diabetes and inheritance (n = 172) is used in a secondary content analysis. Questions are posted in 2005-2009 via a website providing information about more than 600 inheritable disorders, including all diabetes subtypes. Queries submitted were classified by contents as well as persons' demographic profiles.</p> <p>Results</p> <p>Questions were received by diabetes patients (49%), relatives (30%), and partners (21%). Questioners were relatively young (54.8% ≤ 30 years) and predominantly female (83%). Most queries related to type 1 diabetes and concerned topics related to (future) pregnancy and family planning. Questioners mainly asked for risk estimation, but also clarifying information (about genetics of diabetes in general) and advice (mostly related to family planning) was requested. Preventive advice to reduce own diabetes risk was hardly sought.</p> <p>Conclusions</p> <p>Genetic information on diabetes provided by professionals or public health initiatives should address patients, as well as relatives and partners. In particular women are receptive to genetic information; they worry about the diabetes related health of (future) offspring. It seems important that information on the contribution of genetics to type 1 diabetes is more readily available. Considering the high prevalence of type 2 diabetes with strong evidence for a genetic predisposition, more effort seems needed to promote awareness around familial clustering and primary prevention.</p

    PPARα L162V underlies variation in serum triglycerides and subcutaneous fat volume in young males

    Get PDF
    <p>Abstract</p> <p>Background</p> <p>Of the five sub-phenotypes defining metabolic syndrome, all are known to have strong genetic components (typically 50–80% of population variation). Studies defining genetic predispositions have typically focused on older populations with metabolic syndrome and/or type 2 diabetes. We hypothesized that the study of younger populations would mitigate many confounding variables, and allow us to better define genetic predisposition loci for metabolic syndrome.</p> <p>Methods</p> <p>We studied 610 young adult volunteers (average age 24 yrs) for metabolic syndrome markers, and volumetric MRI of upper arm muscle, bone, and fat pre- and post-unilateral resistance training.</p> <p>Results</p> <p>We found the PPARα L162V polymorphism to be a strong determinant of serum triglyceride levels in young White males, where carriers of the V allele showed 78% increase in triglycerides relative to L homozygotes (LL = 116 ± 11 mg/dL, LV = 208 ± 30 mg/dL; p = 0.004). Men with the V allele showed lower HDL (LL = 42 ± 1 mg/dL, LV = 34 ± 2 mg/dL; p = 0.001), but women did not. Subcutaneous fat volume was higher in males carrying the V allele, however, exercise training increased fat volume of the untrained arm in V carriers, while LL genotypes significantly decreased in fat volume (LL = -1,707 ± 21 mm<sup>3</sup>, LV = 17,617 ± 58 mm<sup>3 </sup>; p = 0.002), indicating a systemic effect of the V allele on adiposity after unilateral training. Our study suggests that the primary effect of PPARα L162V is on serum triglycerides, with downstream effects on adiposity and response to training.</p> <p>Conclusion</p> <p>Our results on association of PPARα and triglycerides in males showed a much larger effect of the V allele than previously reported in older and less healthy populations. Specifically, we showed the V allele to increase triglycerides by 78% (p = 0.004), and this single polymorphism accounted for 3.8% of all variation in serum triglycerides in males (p = 0.0037).</p

    An astrocyte-dependent mechanism for neuronal rhythmogenesis

    Full text link
    Communication between neurons rests on their capacity to change their firing pattern to encode different messages. For several vital functions, such as respiration and mastication, neurons need to generate a rhythmic firing pattern. Here we show in the rat trigeminal sensori-motor circuit for mastication that this ability depends on regulation of the extracellular Ca2+ concentration ([Ca2+]e) by astrocytes. In this circuit, astrocytes respond to sensory stimuli that induce neuronal rhythmic activity, and their blockade with a Ca2+ chelator prevents neurons from generating a rhythmic bursting pattern. This ability is restored by adding S100b, an astrocytic Ca2+-binding protein, to the extracellular space, while application of an anti-S100b antibody prevents generation of rhythmic activity. These results indicate that astrocytes regulate a fundamental neuronal property: the capacity to change firing pattern. These findings may have broad implications for many other neural networks whose functions depend on the generation of rhythmic activity

    Express Attentional Re-Engagement but Delayed Entry into Consciousness Following Invalid Spatial Cues in Visual Search

    Get PDF
    Background: In predictive spatial cueing studies, reaction times (RT) are shorter for targets appearing at cued locations (valid trials) than at other locations (invalid trials). An increase in the amplitude of early P1 and/or N1 event-related potential (ERP) components is also present for items appearing at cued locations, reflecting early attentional sensory gain control mechanisms. However, it is still unknown at which stage in the processing stream these early amplitude effects are translated into latency effects. Methodology/Principal Findings: Here, we measured the latency of two ERP components, the N2pc and the sustained posterior contralateral negativity (SPCN), to evaluate whether visual selection (as indexed by the N2pc) and visual-short term memory processes (as indexed by the SPCN) are delayed in invalid trials compared to valid trials. The P1 was larger contralateral to the cued side, indicating that attention was deployed to the cued location prior to the target onset. Despite these early amplitude effects, the N2pc onset latency was unaffected by cue validity, indicating an express, quasiinstantaneous re-engagement of attention in invalid trials. In contrast, latency effects were observed for the SPCN, and these were correlated to the RT effect. Conclusions/Significance: Results show that latency differences that could explain the RT cueing effects must occur after visual selection processes giving rise to the N2pc, but at or before transfer in visual short-term memory, as reflected by th

    The JCMT BISTRO Survey: The Magnetic Field of the Barnard 1 Star-Forming Region

    Get PDF
    This is the final version. Available from American Astronomical Society / IOP Publishing via the DOI in this record.We present the POL-2 850 um linear polarization map of the Barnard 1 clump in the Perseus molecular cloud complex from the B-fields In STar-forming Region Observations (BISTRO) survey at the James Clerk Maxwell Telescope. We find a trend of decreasing polarization fraction as a function of total intensity, which we link to depolarization effects towards higher density regions of the cloud. We then use the polarization data at 850 um to infer the plane-of-sky orientation of the large-scale magnetic field in Barnard 1. This magnetic field runs North-South across most of the cloud, with the exception of B1-c where it turns more East-West. From the dispersion of polarization angles, we calculate a turbulence correlation length of 5.0 +/- 2.5 arcsec (1500 au), and a turbulent-to-total magnetic energy ratio of 0.5 +/- 0.3 inside the cloud. We combine this turbulent-to-total magnetic energy ratio with observations of NH3 molecular lines from the Green Bank Ammonia Survey (GAS) to estimate the strength of the plane-of-sky component of the magnetic field through the Davis-Chandrasekhar-Fermi method. With a plane-of-sky amplitude of 120 +/- 60 uG and a criticality criterion lambda_c = 3.0 +/- 1.5, we find that Barnard 1 is a supercritical molecular cloud with a magnetic field nearly dominated by its turbulent component.National Research Foundation of Korea (NRF)National Key R&D Program of ChinaNational Natural Science Foundation of China (NSFC

    The JCMT BISTRO Survey: Magnetic Fields Associated with a Network of Filaments in NGC 1333

    Get PDF
    We present new observations of the active star formation region NGC 1333 in the Perseus molecular cloud complex from the James Clerk Maxwell Telescope B-Fields In Star-forming Region Observations (BISTRO) survey with the POL-2 instrument. The BISTRO data cover the entire NGC 1333 complex (~1.5 pc × 2 pc) at 0.02 pc resolution and spatially resolve the polarized emission from individual filamentary structures for the first time. The inferred magnetic field structure is complex as a whole, with each individual filament aligned at different position angles relative to the local field orientation. We combine the BISTRO data with low- and high- resolution data derived from Planck and interferometers to study the multiscale magnetic field structure in this region. The magnetic field morphology drastically changes below a scale of ~1 pc and remains continuous from the scales of filaments (~0.1 pc) to that of protostellar envelopes (~0.005 pc or ~1000 au). Finally, we construct simple models in which we assume that the magnetic field is always perpendicular to the long axis of the filaments. We demonstrate that the observed variation of the relative orientation between the filament axes and the magnetic field angles are well reproduced by this model, taking into account the projection effects of the magnetic field and filaments relative to the plane of the sky. These projection effects may explain the apparent complexity of the magnetic field structure observed at the resolution of BISTRO data toward the filament network
    corecore