Identifying spatial invasion of pandemics on metapopulation networks via anatomizing arrival history

Spatial spread of infectious diseases among populations via the mobility of humans is highly stochastic and heterogeneous. Accurate forecast/mining of the spread process is often hard to be achieved by using statistical or mechanical models. Here we propose a new reverse problem, which aims to identify the stochastically spatial spread process itself from observable information regarding the arrival history of infectious cases in each subpopulation. We solved the problem by developing an efficient optimization algorithm based on dynamical programming, which comprises three procedures: i, anatomizing the whole spread process among all subpopulations into disjoint componential patches; ii, inferring the most probable invasion pathways underlying each patch via maximum likelihood estimation; iii, recovering the whole process by assembling the invasion pathways in each patch iteratively, without burdens in parameter calibrations and computer simulations. Based on the entropy theory, we introduced an identifiability measure to assess the difficulty level that an invasion pathway can be identified. Results on both artificial and empirical metapopulation networks show the robust performance in identifying actual invasion pathways driving pandemic spread.Comment: 14pages, 8 figures; Accepted by IEEE Transactions on Cybernetic

Tumor-associated EGFR over-expression specifically activates Stat3 and Smad7 resulting in desensitization of TGF-β signaling

Transforming Growth Factor-[beta] (TGF-[beta]) and Epidermal Growth Factor (EGF) signaling pathways are both independently implicated as key regulators in tumor formation and progression. Here, we demonstrate that activation of the tumor-associated and over-expressed EGFR desensitizes TGF-[beta] signaling and its cytostatic regulation through specific Stat3 activation and Smad7 induction. In normal and tumor human cell lines, reduction of TGF-[beta]-mediated Smad2 phosphorylation, nuclear translocation and Smad3 target gene activation were observed where EGFR is over-expressed, but not in cells which expressed EGFR at normal levels. The EGFR downstream signaling molecules phosphatidyinositol-3 Kinase (PI3K) or mitogen-activated protein kinase/ERK kinase (MEK) are not responsible for the down-regulation of TGF-[beta] signaling since blockade of them by specific pharmacological inhibitors LY294002 and U0126 had little effects on the sensitivity of TGF-[beta] signaling. We identified Stat3 as a signaling molecule activated specifically and persistently by over-expressed EGFR, but not by normal levels. Importantly, Stat3 is responsible for the reduced TGF-[beta] sensitivity, since its knockdown by siRNA restored TGF-[beta] signaling sensitivity. Furthermore, over-expressed EGFR, through Stat3 activates Smad7 promoter activity, increasing its protein levels, which is a negative regulator of TGF-[beta] signaling. Consequently, cells were re-sensitized to TGF-[beta] when Smad7 expression was reduced using siRNA. Therefore we establish a novel EGFR-Stat3-Smad7-TGF-[beta] signaling molecular axis where tumor-associated over-expression of EGFR in epithelial cells results in hyperactivation of Stat3, which activates Smad7 expression, compromising the TGF-[beta]'s cytostatic regulation of epithelium and consequent tumor formation

Note on Soft Graviton theorem by KLT Relation

Recently, new soft graviton theorem proposed by Cachazo and Strominger has inspired a lot of works. In this note, we use the KLT-formula to investigate the theorem. We have shown how the soft behavior of color ordered Yang-Mills amplitudes can be combined with KLT relation to give the soft behavior of gravity amplitudes. As a byproduct, we find two nontrivial identities of the KLT momentum kernel must hold.Comment: 25 page