Aug
13
Tue
2013
Plenary Address: Making sense of pathogen sensors of Innate Immunity: Utility of their ligands as antiviral agens and adjuvants for vaccines. @ Acharya Hall
Aug 13 @ 9:17 am – 9:55 am

SuryaprakashSuryaprakash Sambhara, DVM, Ph.D
Chief, Immunology Section, Influenza Division, CDC, Atlanta, USA


Making sense of pathogen sensors of Innate Immunity: Utility of their ligands as antiviral agents and adjuvants for vaccines.

Currently used antiviral agents act by inhibiting viral entry, replication, or release of viral progeny.  However, recent emergence of drug-resistant viruses has become a major public health concern as it is limiting our ability to prevent and treat viral diseases.  Furthermore, very few antiviral agents with novel modes of action are currently in development.  It is well established that the innate immune system is the first line of defense against invading pathogens.  The recognition of diverse pathogen-associated molecular patterns (PAMPs) is accomplished by several classes of pattern recognition receptors (PRRs) and the ligand/receptor interactions trigger an effective innate antiviral response.  In the past several years, remarkable progress has been made towards understanding both the structural and functional nature of PAMPs and PRRs.  As a result of their indispensable role in virus infection, these ligands have become potential pharmacological agents against viral infections.  Since their pathways of action are evolutionarily conserved, the likelihood of viruses developing resistance to PRR activation is diminished.  I will discuss the recent developments investigating the potential utility of the ligands of innate immune receptors as antiviral agents and molecular adjuvants for vaccines.

Suryaprakash (1) Suryaprakash (4) Suryaprakash-Nagaraja

Plenary Talk: Biosensor and Single Cell Manipulation using Nanopipettes @ Amriteshwari Hall
Aug 13 @ 10:06 am – 10:49 am

NaderNader Pourmand, Ph.D.
Director, UCSC Genome Technology Center,University of California, Santa Cruz


Biosensor and Single Cell Manipulation using Nanopipettes

Approaching sub-cellular biological problems from an engineering perspective begs for the incorporation of electronic readouts. With their high sensitivity and low invasiveness, nanotechnology-based tools hold great promise for biochemical sensing and single-cell manipulation. During my talk I will discuss the incorporation of electrical measurements into nanopipette technology and present results showing the rapid and reversible response of these subcellular sensors  to different analytes such as antigens, ions and carbohydrates. In addition, I will present the development of a single-cell manipulation platform that uses a nanopipette in a scanning ion-conductive microscopy technique. We use this newly developed technology to position the nanopipette with nanoscale precision, and to inject and/or aspirate a minute amount of material to and from individual cells or organelle without comprising cell viability. Furthermore, if time permits, I will show our strategy for a new, single-cell DNA/ RNA sequencing technology that will potentially use nanopipette technology to analyze the minute amount of aspirated cellular material.

Plenary Talk: Interspike Interval Distribution of Neuronal Model with distributed delay: Emergence of unimodal, bimodal and Power law @ Sathyam Hall
Aug 13 @ 1:20 pm – 2:00 pm

karmeshuKarmeshu, 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.