Shigeki Miyamoto, Ph.D.
Professor, McArdle Laboratory for Cancer Research – UW Carbone Cancer Center
Department of Oncology, School of Medicine and Public Health
University of Wisconsin-Madison
“Inside-out” NF-κB signaling in cancer and other pathologies
The NF-κB/Rel family of transcription factors contributes to critical cellular processes, including immune, inflammatory and cell survival responses. As such, NF-κB is implicated in immunity-related diseases, as well as multiple types of human malignancies. Indeed, genetic alterations in the NF-κB signaling pathway are frequently observed in multiple human malignancies. NF-κB is normally kept inactive in the cytoplasm by inhibitor proteins. Extracellular ligands can induce the release of NF-κB from the inhibitors to allow its migration into the nucleus to regulate a variety of target genes. NF-κB activation is also induced in response to multiple stress conditions, including those induced by DNA-damaging anticancer agents. Although precise mechanisms are still unclear, research from our group has revealed a unique nuclear-to-cytoplasmic signaling pathway. In collaboration with bioengineers, clinicians and pharmaceutical industry, our lab has developed new methods to analyze primary cancer patient samples and identified several compounds with different mechanisms that mitigate this cell survival pathway. Further contributions from other labs have also revealed additional mechanisms and molecular players in this “inside-out” signaling pathway and expanded its role in other physiological and pathological processes, including B cell development, premature aging and therapy resistance of certain cancers. Our own new findings, along with these recent developments in the field, will be highlighted.
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.