Identification of sparse neural functional connectivity using penalized likelihood estimation and basis functions

One key problem in computational neuroscience and neural engineering is the identification and modeling of functional connectivity in the brain using spike train data. To reduce model complexity, alleviate overfitting, and thus facilitate model interpretation, sparse representation and estimation of functional connectivity is needed. Sparsities include global sparsity, which captures the sparse connectivities between neurons, and local sparsity, which reflects the active temporal ranges of the input-output dynamical interactions. In this paper, we formulate a generalized functional additive model (GFAM) and develop the associated penalized likelihood estimation methods for such a modeling problem. A GFAM consists of a set of basis functions convolving the input signals, and a link function generating the firing probability of the output neuron from the summation of the convolutions weighted by the sought model coefficients. Model sparsities are achieved by using various penalized likelihood estimations and basis functions. Specifically, we introduce two variations of the GFAM using a global basis (e.g., Laguerre basis) and group LASSO estimation, and a local basis (e.g., B-spline basis) and group bridge estimation, respectively. We further develop an optimization method based on quadratic approximation of the likelihood function for the estimation of these models. Simulation and experimental results show that both group-LASSO-Laguerre and group-bridge-B-spline can capture faithfully the global sparsities, while the latter can replicate accurately and simultaneously both global and local sparsities. The sparse models outperform the full models estimated with the standard maximum likelihood method in out-of-sample predictions.     

Neural Response Phase Tracks How Listeners Learn New Acoustic Representations

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Perturbation of the mutated EGFR interactome identifies vulnerabilities and resistance mechanisms

We hypothesized that elucidating the interactome of epidermal growth factor receptor (EGFR) forms that are mutated in lung cancer, via global analysis of protein–protein interactions, phosphorylation, and systematically perturbing the ensuing network nodes, should offer a new, more systems‐level perspective of the molecular etiology. Here, we describe an EGFR interactome of 263 proteins and offer a 14‐protein core network critical to the viability of multiple EGFR‐mutated lung cancer cells. Cells with acquired resistance to EGFR tyrosine kinase inhibitors (TKIs) had differential dependence of the core network proteins based on the underlying molecular mechanisms of resistance. Of the 14 proteins, 9 are shown to be specifically associated with survival of EGFR‐mutated lung cancer cell lines. This included EGFR, GRB2, MK12, SHC1, ARAF, CD11B, ARHG5, GLU2B, and CD11A. With the use of a drug network associated with the core network proteins, we identified two compounds, midostaurin and lestaurtinib, that could overcome drug resistance through direct EGFR inhibition when combined with erlotinib. Our results, enabled by interactome mapping, suggest new targets and combination therapies that could circumvent EGFR TKI resistance.     

Electron microscopy: essentials for viral structure, morphogenesis and rapid diagnosis

Electron microscopy(EM) should be used in the front line for detection of agents in emergencies and bioterrorism,on accounts of its speed and accuracy.However,the number of EM diagnostic laboratories has decreased considerably and an increasing number of people encounter difficulties with EM results.Therefore,the research on viral structure and morphology has become important in EM diagnostic practice.EM has several technological advantages,and should be a fundamental tool in clinical diagnosis of viruses,particularly when agents are unknown or unsuspected.In this article,we review the historical contribution of EM to virology,and its use in virus differentiation,localization of specific virus antigens,virus-cell interaction,and viral morphogenesis.It is essential that EM investigations are based on clinical and comprehensive pathogenesis data from light or confocal microscopy.Furthermore,avoidance of artifacts or false results is necessary to exploit fully the advantages while minimizing its limitations.     

Knockdown of OsHox33, a member of the class III homeodomain-leucine zipper gene family, accelerates leaf senescence in rice

The class III homeodomain-leucine zipper (HD-Zip III) gene family plays important roles in plant growth and development, including regulation of apical embryo patterning, embryonic shoot meristem formation, leaf polarity, vascular development, and meristem function, with a particularly crucial function in leaf development. Although HD-Zip III members are highly conserved in land plants, previous studies, such as genetic analyses based on multiple mutants in Arabidopsis and other plants, suggest that various HD-Zip III family genes have evolved with distinct functions and pleiotropic effects on plant growth and development. In this study, we analyzed a HD-Zip III member, OsHox33, and demonstrated that it plays an important role in age-dependent leaf senescence in rice. We constructed two specific RNAi vectors derived from the 5′-end region and 3′-UTR of OsHox33 to knockdown its expression. Transgenic plants harboring either RNAi construct displayed similar phenotypes of precocious leaf senescence symptoms, suggesting that knockdown of OsHox33 accelerates leaf senescence in rice. pOsHox33::GUS fusion expression and RT-PCR revealed that OsHox33 is highly expressed in young organs, especially in young meristems such as shoot apical meristems, intercalary meristems, and young callus. In addition, real-time PCR indicated that OsHox33 was more highly expressed in young leaves than in old leaves. To further investigate OsHox33 function, we analyzed chloroplast ultrastructure in different-aged leaves of RNAi plants, and found that OsHox33 knockdown accelerated chloroplast degradation, which is consistent with RNAi phenotypes. Finally, real-time PCR studies showed that OsHox33 can regulate the expression of GS1 and GS2, two senescence-associated genes. Taken together, the work presented here provides new insights into the function of HD-Zip III members in plants.