Karmeshu, Ph.D.
Dean & Professor, School of Computer & Systems Sciences & School of Computational & Integrative Sciences, Jawaharlal Nehru University, India.
Interspike Interval Distribution of Neuronal Model with distributed delay: Emergence of unimodal, bimodal and Power law
The study of interspike interval distribution of spiking neurons is a key issue in the field of computational neuroscience. A wide range of spiking patterns display unimodal, bimodal ISI patterns including power law behavior. A challenging problem is to understand the biophysical mechanism which can generate the empirically observed patterns. A neuronal model with distributed delay (NMDD) is proposed and is formulated as an integro-stochastic differential equation which corresponds to a non-markovian process. The widely studied IF and LIF models become special cases of this model. The NMDD brings out some interesting features when excitatory rates are close to inhibitory rates rendering the drift close to zero. It is interesting that NMDD model with gamma type memory kernel can also account for bimodal ISI pattern. The mean delay of the memory kernels plays a significant role in bringing out the transition from unimodal to bimodal ISI distribution. It is interesting to note that when a collection of neurons group together and fire together, the ISI distribution exhibits power law.
Sukhithasri V, Nisha N, Vivek V and Raja Biswas
The host innate immune system acts as the first line of defense against invading pathogens. During an infection, the host innate immune cells recognize unique conserved molecules on the pathogen known as Pathogen Associated Molecular Patterns (PAMPs). This recognition of PAMPs helps the host mount an innate immune response leading to the production of cytokines (Akira et al. 2006). Peptidoglycan, one of the most conserved and essential component of the bacterial cell wall is one such PAMP. Peptidoglycan is known to have potent proinflammatory properties (Gust et al. 2007). Host recognize peptidoglycan using Nucleotide oligomerization domain proteins (NODs). This recognition of peptidoglycan activates the NODs and triggers downstream signaling leading to the nuclear translocation of NF-κB and production of cytokines (McDonald et al. 2005). Pathogenic bacteria modify their peptidoglycan as a strategy to evade innate immune recognition, which helps it to establish infection in the host. These peptidoglycan modifications include O-acetylation and N-glycolylation of muramic acid and N-deacetylation of N-acetylglucosamine (Davis et al. 2011). Modification of mycobacterial peptidoglycan by N-glycolylation prevents the catalytic activity of lysozyme (Raymond et al. 2005). Additionally, mycobacterial peptidoglycan is modified by amidation for unknown reasons.
Here, we have investigated the role of amidated peptidoglycan in Mycobacterium sp in modulating the innate immune response. We isolated amidated peptidoglycan from Mycobacterium sp and non-amidated peptidoglycan from Escherichia coli. We made a comparative analysis of the cytokine response produced on stimulation of innate immune cells by peptidoglycan from E. Coli and Mycobacterium sp. Macrophages and whole blood were treated with peptidoglycan and the cytokines secreted into spent medium and plasma respectively were analyzed using ELISA. Our results show that peptidoglycan from Mycobacterium sp is less effective in stimulating innate immune cells to produce cytokines. This intrinsic modulation of the cytokine response suggests that mycobacteria modify their peptidoglycan by amidation to evade innate immune response.