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Posts on Jan 1970

U27-E02. Open source software

Open source software:

  • HTCondor 9.0 (HTC) job scheduler
  • Python 3.*
  • Python 2.7.18 (python2)
  • GCC/G++ 7/8/9
  • CMake 3.16.3
  • R version 4.2.0
  • OpenFoam
  • LAMMPS
  • LIGGGHTS
  • spparks
  • tetgen(1.6)
  • ovito-2.9 (/home/software/bin/ovito-2.9)
  • paraview
  • sox y libsox-fmt-all
  • ffmpeg
  • mpich
  • git

* possibility of adding any other software compatible with Linux-type systems

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U27-E01. Hermes cluster

Hermes Cluster: The cluster is unit 27 of NANBIOSIS, HERMES has more than 3260 cores and 5920 parallel processing threads, 26TB of RAM, 264TB nvme and 400TB HDD of shared storage, all connected by a 100Gbps backbone network. In addition, we currently have 251,392 cuda cores, 720GB graphics memory, 1,179.42 peak FP16 TFLOPS, and 828.6 peak FP32 TFLOPS. HERMES is capable of processing a year’s worth of work on a personal computer in just 3 hours, greatly accelerating the work of researchers. Technical staff maintain the system and offer technical support, advice on parallel and high-performance supercomputing.

Highlighted figures:

  • +3,260 Cores
  • +5920 Threads
  • 26TB RAM
  • 264TB NVMe
  • 400TB HDD
  • 100 Gbps backbone
  • 251,392 CUDA cores
  • 720 GB Graphics memory
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U25-E10. Animal housing

Animal housing room and animal preparation area equipped with a vital constants monitoring system, 2 full sets of anesthesia equipment, water bath, infrared lamp, injection pump, etc.

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U25-E11. Software packages

Software packages for data acquisition and processing:

  • Paravision, Topspin and Amix.
  • Users will have access to the database of spectra of diffe¬rent substances for metabolomics through this ac¬cess http://sermn. uab.cat/wiki/doku.php?id=bbiorefcode. This database is installed in a SeRMN computer, fully accessible to facility users.
  • The AMIX software page (http://www.bruker-biospin.com/amix. html) contains more information about its different applications: analysis of mixtures, metabolomic stu-dies, etc.
  • Other packages include the INTERPRET decision-support system for human brain tumour diagnosis based on MRS and SpectraClassifier, for pattern recognition of in vivo MRS data single and multivoxel are developed and distributed through the platform (http://gabrmn.uab.es).
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U25-S03. NMR spectrometer 400 MHz with HRMAS/CPMAS probes (Onsite&Remote) OUTSTANDING

NMR spectrometer 400 MHz with HRMAS/CPMAS probes (Onsite&Remote) OUTSTANDING

400 MHz: AVANCE III console, probes 4mm HRMAS BBI 1H/13C/31P/D, with Z-gradients, 4mm MAS VTN 1H/BB for solid-state, and BCU Xtreme unit for sample temperature control

Customer benefits

HRMAS allows for high-resolution NMR spectra of semi-solid and solid samples by spinning the sample at the magic angle, which minimizes broadening due to sample heterogeneity and anisotropic interactions. Also, potential for characterization of polymers, catalysts, porous materials, and nanomaterials, providing insights into molecular structure, dynamics, and interactions. CPMAS NMR is particularly useful for studying crystalline materials, including organic and inorganic compounds, minerals, and pharmaceuticals. It provides information about chemical composition, crystal structure, and molecular dynamics.

Target customer

Researchers or companies with needs to study solid or semisolid samples regarding structure, characterization, interactions or composition.

References

  • Jiménez-Xarrié E, et al. In vivo and ex vivo magnetic resonance spectroscopy of the infarct and the subventricular zone in experimental stroke. J Cereb Blood Flow Metab. 2015 May;35(5):828-34. doi: 10.1038/jcbfm.2014.257. Epub 2015 Jan 21. PMID: 25605287; PMCID: PMC4420856.
  • Delgado-Goñi T, et al. Assessment of a 1H high-resolution magic angle spinning NMR spectroscopy procedure for free sugars quantification in intact plant tissue. Planta. 2013 Aug;238(2):397-413. doi: 10.1007/s00425-013-1924-y. Epub 2013 Jul 4. PMID: 23824526.
  • Martín-Sitjar J, et al. Influence of the spinning rate in the HR-MAS pattern of mobile lipids in C6 glioma cells and in artificial oil bodies. MAGMA. 2012 Dec;25(6):487-96. doi: 10.1007/s10334-012-0327-6. Epub 2012 Jul 20. PMID: 23011574.
  • Valverde-Saubí D, et al. Short-term temperature effect on the HRMAS spectra of human brain tumor biopsies and their pattern recognition analysis. MAGMA. 2010 Sep;23(4):203-15. doi: 10.1007/s10334-010-0218-7. Epub 2010 Jun 13. PMID: 20549297.
  • Simões RV, et al. 1H-MRSI pattern perturbation in a mouse glioma: the effects of acute hyperglycemia and moderate hypothermia. NMR Biomed. 2010 Jan;23(1):23-33. doi: 10.1002/nbm.1421. PMID: 19670263.
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U25-S05. Preclinical horizontal spectrometer Biospec 7T (Onsite&Remote) OUTSTANDING

Preclinical horizontal spectrometer Biospec 7T (Onsite&Remote) OUTSTANDING

7T Bruker BioSpec 70/30 USR MR system (Bruker BioSpin GmbH, Karlsruhe, Germany) equipped with a BGA12 mini-imaging gradient insert (maximum amplitude: 400 mT/m and slew rate: 5500 T/m/s). Capability for magnetic resonance imaging and spectroscopy of small animals (e.g. mouse, rat) and studies of model solutions (e.g. new contrast agents). Also capabilities for advanced imaging techniques such as diffusion and perfusion weighted images and fractional anisotropy. Coupled with anaesthetic equipment and vital signs monitoring for in vivo experiments.

Customer benefits

Noninvasive studies of anatomy and biochemical environment depending on the organ. Studies of physiological and pathological anatomy changes with a high resolution level. Magnetic resonance is not based on ionizing radiation and can be performed as many times as needed. Assessment of new therapeutic agents efficacy and novel contrast agents potential. T1, T2 and T2* maps measurement.

Target customer

Research groups or companies working with preclinical models, novel therapeutic or contrast agents, characterization of novel preclinical models based in cancer, inflammatory or neurological diseases.

References

  • Zhang S, et al. Metal-Free Radical Dendrimers as MRI Contrast Agents for Glioblastoma Diagnosis: Ex Vivo and In Vivo Approaches. Biomacromolecules. 2022 Jul 11;23(7):2767-2777. doi: 10.1021/acs.biomac.2c00088. Epub 2022 Jun 24. PMID: 35749573; PMCID: PMC9277593.
  • García-Pardo J, et al. Bioinspired Theranostic Coordination Polymer Nanoparticles for Intranasal Dopamine Replacement in Parkinson’s Disease. ACS Nano. 2021 May 25;15(5):8592-8609. doi: 10.1021/acsnano.1c00453. Epub 2021 Apr 22. PMID: 33885286; PMCID: PMC8558863.
  • Wu S, et al. Anti-tumour immune response in GL261 glioblastoma generated by Temozolomide Immune-Enhancing Metronomic Schedule monitored with MRSI-based nosological images. NMR Biomed. 2020 Apr;33(4):e4229. doi: 10.1002/nbm.4229. Epub 2020 Jan 11. PMID: 31926117.
  • Güell-Bosch J, et al. Progression of Alzheimer’s disease and effect of scFv-h3D6 immunotherapy in the 3xTg-AD mouse model: An in vivo longitudinal study using Magnetic Resonance Imaging and Spectroscopy. NMR Biomed. 2020 May;33(5):e4263. doi: 10.1002/nbm.4263. Epub 2020 Feb 17. PMID: 32067292.
  • Suárez-García S, et al. Dual T1/ T2 Nanoscale Coordination Polymers as Novel Contrast Agents for MRI: A Preclinical Study for Brain Tumor. ACS Appl Mater Interfaces. 2018 Nov 14;10(45):38819-38832. doi: 10.1021/acsami.8b15594. Epub 2018 Nov 1. PMID: 30351897.
  • Lope-Piedrafita, S. (2018). Diffusion Tensor Imaging (DTI). In: García Martín, M., López Larrubia, P. (eds) Preclinical MRI. Methods in Molecular Biology, vol 1718. Humana Press, New York, NY. doi: 10.1007/978-1-4939-7531-0_7
  • Arias-Ramos N, et al. Metabolomics of Therapy Response in Preclinical Glioblastoma: A Multi-Slice MRSI-Based Volumetric Analysis for Noninvasive Assessment of Temozolomide Treatment. Metabolites. 2017 May 18;7(2):20. doi: 10.3390/metabo7020020. PMID: 28524099; PMCID: PMC5487991.
  • Jiménez-Xarrié E, et al. Brain metabolic pattern analysis using a magnetic resonance spectra classification software in experimental stroke. BMC Neurosci. 2017 Jan 13;18(1):13. doi: 10.1186/s12868-016-0328-x. PMID: 28086802; PMCID: PMC5237280.
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U25-S06. Dynamic nuclear polarizer HyperSense® (Onsite&Remote) OUTSTANDING

Dynamic nuclear polarizer HyperSense® (Onsite&Remote) OUTSTANDING

Sheltered magnet of 3.35T. Integrated microwave source Elva-1™ VCOM-10, frequency ≈ 94 GHz. BOC Edwards™ E2M80 Series Vacuum Pump. Sample dissolution and automatic transfer system from polarizer to Bruker 600 MHz spectrometer

Customer benefits

DNP significantly boosts the sensitivity of NMR experiments, enabling the detection of nuclei present at low concentrations or in low abundance compared to conventional NMR techniques. It can be used in metabolomics studies to analyze metabolic pathways, identify metabolites, and investigate metabolic fluxes in biological samples such as tissues, cells, and biofluids. Provides real-time monitoring of chemical reactions and kinetics, providing valuable information about reaction mechanisms, intermediate species, and reaction rates.

Target customer

Researchers or companies with needs to enhance sensitivity and elucidate metabolic pathways or changes occurred during therapy, for example, changes in the glycolytic metabolism within tumor cells. Polarized samples can be used for further in vitro or in vivo experiments depending on the information needed.

References

  • Monteagudo E, Virgili A, Parella T, Pérez-Trujillo M. Chiral Recognition by Dissolution DNP NMR Spectroscopy of 13C-Labeled dl-Methionine. Anal Chem. 2017 May 2;89(9):4939-4944. doi: 10.1021/acs.analchem.7b00156. Epub 2017 Apr 21. PMID: 28394124.
  • Chavarria L, Romero-Giménez J, Monteagudo E, Lope-Piedrafita S, Cordoba J. Real-time assessment of ¹³C metabolism reveals an early lactate increase in the brain of rats with acute liver failure. NMR Biomed. 2015 Jan;28(1):17-23. doi: 10.1002/nbm.3226. Epub 2014 Oct 10. PMID: 25303736.
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U25-S07. Focused Microwave Fixation System (Onsite&Remote) OUTSTANDING

Focused Microwave Fixation System (Onsite&Remote) OUTSTANDING

Muromachi Focused Microwave Fixation System 5KW-6402C. The system is configured to mouse (TAW-174A Applicator Head for WJM-28 Mouse Holder). Capable of fast euthanization (miliseconds range) of mice, and also to halt postmortem metabolism in cell suspensions and biopsy samples, allowing further examination without the need of low temperatures to avoid postmortem changes.

Customer benefits

Halting postmortem metabolism may allow for different long-term studies such as 13C NMR (natural abundance), 2D NMR acquisitions, and also to use physiological temperatures without any postmortem deterioration. Still, the halted sample is still valid for histopathological examination if needed.

Target customer

Customers that work with systems subjected to fast postmortem changes which could make detailed studies challenging without the use of extreme, non-physiological conditions.

References

  • Delgado-Goñi T, Campo S, Martín-Sitjar J, Cabañas ME, San Segundo B, Arús C. Assessment of a 1H high-resolution magic angle spinning NMR spectroscopy procedure for free sugars quantification in intact plant tissue. Planta. 2013 Aug;238(2):397-413. doi: 10.1007/s00425-013-1924-y. Epub 2013 Jul 4. PMID: 23824526.
  • Davila M, Candiota AP, Pumarola M, Arus C. Minimization of spectral pattern changes during HRMAS experiments at 37 degrees celsius by prior focused microwave irradiation. MAGMA. 2012 Oct;25(5):401-10. doi: 10.1007/s10334-012-0303-1. PMID: 22286777.
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U25-S08. NMR consultancy for processing and interpreting data (Onsite&Remote)

NMR consultancy for processing and interpreting data (Onsite&Remote)

Possibility of requesting expert advice and guidance while processing and interpreting MR data, especially at the preclinical and clinical levels.

Customer benefits

Customers not willing to install and proceed with a learning curve for using specific software can get expert advice and guidance on metabolite significance, interpretation and meaning.

Target customer

Researchers or companies dealing with MR datasets.

References

El-Abtah ME, Wenke MR, Talati P, Fu M, Kim D, Weerasekera A, He J, Vaynrub A, Vangel M, Rapalino O, Andronesi O, Arrillaga-Romany I, Forst DA, Yen YF, Rosen B, Batchelor TT, Gonzalez RG, Dietrich J, Gerstner ER, Ratai EM. Myo-Inositol Levels Measured with MR Spectroscopy Can Help Predict Failure of Antiangiogenic Treatment in Recurrent Glioblastoma. Radiology. 2022 Feb;302(2):410-418. doi: 10.1148/radiol.2021210826. Epub 2021 Nov 9. PMID: 34751617; PMCID: PMC8805659.

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U25-S09. Access to specific software and database (Remote) OUTSTANDING

Access to specific software and database (Remote) OUTSTANDING

Possibility of access to specific software developed in-house (postprocessing of MR spectroscopy data, conversion of spectroscopic data to canonical format, software for automated classification of MR spectroscopic data, decision support systems), provided disclaimer and agreement are signed. Databases with patient MR imaging and spectroscopic data, as well as epidemiological data from two multicentric european projects.

Customer benefits

Curated databases with a high quality level data for further studies. Software no currently available in public repositories. Interaction with researchers specialized in MR data.

Target customer

Customers willing to apply automated classification to their MR spectroscopic data, or willing to apply their methods to different clinically sound datasets.

References

  • Ungan G, et al. Using Single-Voxel Magnetic Resonance Spectroscopy Data Acquired at 1.5T to Classify Multivoxel Data at 3T: A Proof-of-Concept Study. Cancers (Basel). 2023 Jul 21;15(14):3709. doi: 10.3390/cancers15143709. PMID: 37509372; PMCID: PMC10377805.
  • Hernández-Villegas Y, et al. Extraction of artefactual MRS patterns from a large database using non-negative matrix factorization. NMR Biomed. 2022 Apr;35(4):e4193. doi: 10.1002/nbm.4193. Epub 2019 Dec 2. PMID: 31793715.
  • Hellström J, et al. Evaluation of the INTERPRET decision-support system: can it improve the diagnostic value of magnetic resonance spectroscopy of the brain? Neuroradiology. 2019 Jan;61(1):43-53. doi: 10.1007/s00234-018-2129-7. Epub 2018 Nov 15. PMID: 30443796; PMCID: PMC6336758.
  • Julià-Sapé M, et al. Classification of brain tumours from MR spectra: the INTERPRET collaboration and its outcomes. NMR Biomed. 2016 Mar;29(3):371. doi: 10.1002/nbm.3483. Epub 2015 Dec 22. Erratum for: NMR Biomed. 2015 Dec;28(12):1772-87. Tate, Rosemary A [Corrected to Tate, A Rosemary]. PMID: 26915795.
  • Mocioiu V, et al. From raw data to data-analysis for magnetic resonance spectroscopy–the missing link: jMRUI2XML. BMC Bioinformatics. 2015 Nov 9;16:378. doi: 10.1186/s12859-015-0796-5. PMID: 26552737; PMCID: PMC4640235.
  • Ortega-Martorell S, et al. SpectraClassifier 1.0: a user friendly, automated MRS-based classifier-development system. BMC Bioinformatics. 2010 Feb 24;11:106. doi: 10.1186/1471-2105-11-106. PMID: 20181285; PMCID: PMC2846905.
  • Pérez-Ruiz A, et al. The INTERPRET Decision-Support System version 3.0 for evaluation of Magnetic Resonance Spectroscopy data from human brain tumours and other abnormal brain masses. BMC Bioinformatics. 2010 Nov 29;11:581. doi: 10.1186/1471-2105-11-581. PMID: 21114820; PMCID: PMC3004884.
  • Luts J, et al. A combined MRI and MRSI based multiclass system for brain tumour recognition using LS-SVMs with class probabilities and feature selection. Artif Intell Med. 2007 Jun;40(2):87-102. doi: 10.1016/j.artmed.2007.02.002. Epub 2007 Apr 26. PMID: 17466495.
  • Julià-Sapé M, et al. A multi-centre, web-accessible and quality control-checked database of in vivo MR spectra of brain tumour patients. MAGMA. 2006 Feb;19(1):22-33. doi: 10.1007/s10334-005-0023-x. Epub 2006 Feb 14. PMID: 16477436.

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