Aug
12
Mon
2013
Invited Talk: Can we compute what we think? @ Amriteshwari Hall
Aug 12 @ 10:20 am – 10:51 am

gauteGaute Einevoll, Ph.D.
Professor of Physics, Department of Mathematical Sciences & Technology, Norwegian University of Life Sciences (UMB)


Multiscale modeling of cortical network activity: Key challenges

Gaute T. Einevoll Computational Neuroscience Group, Norwegian University of Life Sciences, 1432 Ås, Norway; Norwegian National Node of the International Neuroinformatics Coordinating Facility (INCF)

Several challenges must be met in the development of multiscale models of cortical network activity. In the presentation I will, based on ongoing work in our group (http://compneuro.umb.no/ ) on multiscale modeling of cortical columns, outline some of them. In particular,

  1. Combined modeling schemes for neuronal, glial and vascular dynamics [1,2],
  2. Development of sets of interconnected models describing system at different levels of biophysical detail [3-5],
  3. Multimodal modeling, i.e., how to model what you can measure [6-12],
  4. How to model when you don’t know all the parameters, and
  5. Development of neuroinformatics tools and routines to do simulations efficiently and accurately [13,14].

References:

  1. L. Øyehaug, I. Østby, C. Lloyd, S.W. Omholt, and G.T. Einevoll: Dependence of spontaneous neuronal firing and depolarisation block on astroglial membrane transport mechanisms, J Comput Neurosci 32, 147-165 (2012)
  2. I. Østby, L. Øyehaug, G.T. Einevoll, E. Nagelhus, E. Plahte, T. Zeuthen, C. Lloyd, O.P. Ottersen, and S.W. Omholt: Astrocytic mechanisms explaining neural-activity-induced shrinkage of extraneuronal space, PLoS Comp Biol 5, e1000272 (2009)
  3. T. Heiberg, B. Kriener, T. Tetzlaff, A. Casti, G.T. Einevoll, and H.E. Plesser: Firing-rate models can describe the dynamics of the retina-LGN connection, J Comput Neurosci (2013)
  4. T. Tetzlaff, M. Helias, G.T. Einevoll, and M. Diesmann: Decorrelation of neural-network activity by inhibitory feedback, PLoS Comp Biol 8, e10002596 (2012).
  5. E. Nordlie, T. Tetzlaff, and G.T. Einevoll: Rate dynamics of leaky integrate-and-fire neurons with strong synapses, Frontiers in Comput Neurosci 4, 149 (2010)
  6. G.T. Einevoll, F. Franke, E. Hagen, C. Pouzat, K.D. Harris: Towards reliable spike-train recording from thousands of neurons with multielectrodes, Current Opinion in Neurobiology 22, 11-17 (2012)
  7. H. Linden, T Tetzlaff, TC Potjans, KH Pettersen, S Grun, M Diesmann, GT Einevoll: Modeling the spatial reach of LFP, Neuron 72, 859-872 (2011).
  8. H. Linden, K.H. Pettersen, and G.T. Einevoll: Intrinsic dendritic filtering gives low-pass power spectra of local field potentials, J Computational Neurosci 29, 423-444 (2010)
  9. K.H. Pettersen and G.T. Einevoll: Amplitude variability and extracellular low-pass filtering of neuronal spikes, Biophysical Journal 94, 784-802 (2008).
  10. K.H. Pettersen, E. Hagen, and G.T. Einevoll: Estimation of population firing rates and current source densities from laminar electrode recordings, J Comput Neurosci 24, 291-313 (2008).
  11. K. Pettersen, A. Devor, I. Ulbert, A.M. Dale and G.T. Einevoll. Current-source density estimation based on inversion of electrostatic forward solution: Effects of finite extent of neuronal activity and conductivity discontinuities, Journal of Neuroscience Methods 154, 116-133 (2006).
  12. G.T. Einevoll, K. Pettersen, A. Devor, I. Ulbert, E. Halgren and A.M. Dale: Laminar Population Analysis: Estimating firing rates and evoked synaptic activity from multielectrode recordings in rat barrel cortex, Journal of Neurophysiology 97, 2174-2190 (2007).
  13. LFPy: A tool for simulation of extracellular potentials (http://compneuro.umb.no)
  14. E. Nordlie, M.-O. Gewaltig, H. E. Plesser: Towards reproducible descriptions of neuronal network models, PLoS Comp Biol 5, e1000456 (2009).

Gaute

Aug
14
Wed
2013
Invited Talk: Electrospray ionization ion trap mass spectrometry for cyclic peptide characterization @ Amriteshwari Hall
Aug 14 @ 12:14 pm – 12:43 pm

SudarslalSudarslal S, Ph.D.
Associate Professor, School of Biotechnology, Amrita University


Electrospray ionization ion trap mass spectrometry for cyclic peptide characterization

There has been considerable interest in the isolation and structural characterization of bioactive peptides produced by bacteria and fungi. Most of the peptides are cyclic depsipeptides characterized by the presence of lactone linkages and β-hydroxy fatty acids. Occurrence of microheterogeneity is another remarkable property of these peptides. Even if tandem mass spectrometers are good analytical tools to structurally characterize peptides and proteins, sequence analysis of cyclic peptides is often ambiguous due to the random ring opening of the peptides and subsequent generation of a set of linear precursor ions with the same m/z. Here we report combined use of chemical derivatization and multistage fragmentation capability of ion trap mass spectrometers to determine primary sequences of a series of closely related cyclic peptides.

Sudars (1) Sudars (2)

 

Delegate Talk: Bioanalytical Characterization of Therapeutic Proteins @ Amriteshwari Hall
Aug 14 @ 12:44 pm – 12:54 pm
Delegate Talk: Bioanalytical Characterization of Therapeutic Proteins @ Amriteshwari Hall | Vallikavu | Kerala | India

Ravindra Gudihal, Suresh Babu C V


Bioanalytical Characterization of Therapeutic Proteins

The characterization of therapeutic proteins such as monoclonal antibody (mAb) during different stages of manufacturing is crucial for timely and successful product release. Regulatory agencies require a variety of analytical technologies for comprehensive and efficient protein analysis. Electrophoresis-based techniques and liquid chromatography (LC) either standalone or coupled to mass spectrometry (MS) are at the forefront for the in-depth analysis of protein purity, isoforms, stability, aggregation, posttranslational modifications, PEGylation, etc. In this presentation, a combination of various chromatographic and electrophoretic techniques such as liquid-phase isoelectric focusing, microfluidic and capillary-based electrophoresis (CE), liquid chromatography (LC) and combinations of those with mass spectrometry techniques will be discussed. We present a workflow based approach to the analysis of therapeutic proteins. In successive steps critical parameters like purity, accurate mass, aggregation, peptide sequence, glycopeptide and glycan analysis are analyzed. In brief, the workflow involved proteolytic digestion of therapeutic protein for peptide mapping, N-Glycanase and chemical labeling reaction for glycan analysis, liquid-phase isoelectric focusing for enrichment of charge variants followed by a very detailed analysis using state of the art methods such as CE-MS and LC-MS. For the analysis of glycans, we use combinations of CE-MS and LC-MS to highlight the sweet spots of these techniques. CE-MS is found to be more useful in analysis of highly sialylated glycans (charged glycans) while nano LC-MS seems to be better adapted for analysis of neutral glycans. These two techniques can be used to get complementary data to profile all the glycans present in a given protein. In addition, microfluidic electrophoresis was used as a QC tool in initial screening for product purity, analysis of papain digestion fragments of mAb, protein PEGylation products, etc. The described workflow involves multiple platforms, provides an end to end solution for comprehensive protein characterization and aims at reducing the total product development time.