NEUROREG adminnb 18 de August de 2022


Regenerative medicine applied to spinal cord injury and damage to the peripheral nervous system: new advanced therapy products and diagnostic tools

INNPACTO 2011 – 2013 Ministry of Science and Innovation

Project Code: IPT-2011-0742-900000

Received grant: 322.062,03€

Project financed by the Ministry of Science and Innovation under the 2011 call of the programme for public-private collaboration, INNPACTO subprogramme.

The main objective of the NeuroReg project was the creation of regenerative medicine products and diagnostic tools for spinal cord injury and damage in the peripheral nervous system. It will be achieved by combining the following three aspects:

  1. Cells, in particular mesenchymal stem cells, because of its potential for the development of cell therapies.
  2. Innovative biomaterials that serve as support for the development of Tissue Engineering technologies.
  3. Technologies based on image analysis systems and software for diagnosis and treatment monitoring of new advanced therapies in the regeneration of nerve damage.

Activity of NorayBio

Development of a software prototype called NEUROMASS in order to analyze nervous tissue samples using image analysis by mass spectrometry (IMS). It allowed to identify differentiating regions of the nervous tissue and to join them to compounds through various statistical techniques in order to obtain, among others, differential regions by its composition, markers and location of compounds.

Developed in collaboration with

Histocell, S.L.
Universidad del País Vasco
Fundación para la Investigación Biosanitaria de Andalucía Oriental Alejandro Otero
Fundación Hospital Nacional de Parapléjicos

Results of the proyect: MSI Analyst

MSI Analyst is a new software application for Mass Spectrometric Imaging that came from the NEUROREG project. This software enables fast data processing, visualization of MSI experiments and integrates a number of data mining tools that provide new analysis perspectives and a more comprehensive data interpretation.

MSI Analyst works with the formats of major manufacturers and other standards as imzML, includes all the classic tools for processing mass spectrometry data, plus some own developments (for example, eight different types of normalization), and includes graphical tools that provide a new visual experience to the researcher. It also integrates functionalities to semi-automatically identify peaks against a customizable database of molecules.


  • Fast and comprehensive processing. Import, filter, align and normalize to get the data ready in just a couple of minutes.
  • Intuitive and powerful visualization, through new visual components and tools thanks to the XNA technology.
  • Automation of the extraction of knowledge. Integrated data mining tools automate the detection of differential regions and the identification of compounds.
  • Easy management of experiments, processes and compounds.
  • Automated reports. Get a comprehensive report on your results with just one click.

Key features

Data pre-treatment

  • Filtering by mass.
  • Filter by intensity (signal to Noise Ratio / Percentage of the Maximum / Polynomic Fit Threshold).
  • Peak discarding.
  • Binning methods: Standard Binning / Centre of Mass Binning.
  • Smoothing: Savitzky-Golay method.
  • Baseline correction: Stretches / Polynomial fitting.
  • Peak selection: Naïve / Simple Peak Finding.
  • Life pre-visualization of the effects of the filters over the spectra data to make easy the decision taking.

Alignment and Calibration

  • Alignment: Block Alignment / Xiong Method.
  • Block calibration.


  • 8 normalization methods: Total Ion Current / P-norm / Mean / Median / Noise Level / Maximum / TIC with range exclusion / Normalization against selected peak.

Data Management

  • Intuitive Experiments management: List / Filtering / Browse / Tree-view of Processes associated to an experiment.
  • Compound Database: Search / Import From File or Add Manually / Edit / Group.
  • Automated and comprehensive reports.

Data Visualization

  • Peak distributions: display and scrutinize two dimensional molecule distribution in tissues.
  • Get average spectrums of the whole experiment or a certain region of interest.
  • Identify compounds.
  • Visualize “mass videos” made of shots of average spectrum peaks’ distributions in the tissue.
  • Select from more than 20 colour gradients.
  • Fix colour-intensity ranges.
  • Zoom images and spectra.

Compound database

  • Exportation to file of images and spectra.
  • Importación, búsqueda y gestión de compuestos.
  • The updateable pre-loaded database includes more than 33.000 lipids, although it accepts any kind of molecule.
  • Peaks identification. Find all the ionized compound candidates for a given peak / Get a list of candidates for all the peaks on the average spectrum.

Statistical Analysis: Principal Component Analysis

  • Three algorithms: Classical PCA / Iterative PCA / Landmark Isomap.
  • Automatically finds differentiated regions of the tissue according to their composition.
  • Visualize the distribution of the individual components.
  • Display the Principal Components coefficients graph.

Statistical Analysis: Clustering

  • Two algorithms: K-MEANS / Partitional Hierarchical Clustering.
  • Finds differentiated regions and assigns each tissue point to one or another.
  • Show each cluster’s average spectrum.
  • Biomarker identification: Get main peaks involved in a cluster.


  • R. Fernández, S. Lage, B. Abad, G. Barceló, S. Terés, D. H. López, F Guardiola, M. L. Martín, P. V. Escribá and J. A. Fernández. Analysis of the lipidome of xenografts using MALDI-IMS and UHPLC-ESI-QTOF, J. Am. Soc. Mass Spectrom. 2014, Accepted for publication

It was also reviewed in the following publication:

  • David Fernández ( 2012) Minería de datos aplicada a Imagen por Espectrometría de Masas. LifeSciencesLab, Num. 24 24 24