Processing Graded Feedback: Electrophysiological Correlates of Learning from Small and Large Errors

Feedback processing is important for learning and therefore may affect the consolidation of skills. Considerable research demonstrates electrophysiological differences between correct and incorrect feedback, but how we learn from small versus large errors is usually overlooked. This study investigated electrophysiological differences when processing small or large error feedback during a time estimation task. Data from high-learners and low-learners were analyzed separately. In both high- and low-learners, large error feedback was associated with higher feedback-related negativity (FRN) and small error feedback was associated with a larger P300 and increased amplitude over the motor related areas of the left hemisphere. In addition, small error feedback induced larger desynchronization in the alpha and beta bands with distinctly different topographies between the two learning groups: The high-learners showed a more localized decrease in beta power over the left frontocentral areas, and the low-learners showed a widespread reduction in the alpha power following small error feedback. Furthermore, only the high-learners showed an increase in phase synchronization between the midfrontal and left central areas. Importantly, this synchronization was correlated to how well the participants consolidated the estimation of the time interval. Thus, although large errors were associated with higher FRN, small errors were associated with larger oscillatory responses, which was more evident in the high-learners. Altogether, our results suggest an important role of the motor areas in the processing of error feedback for skill consolidation.

Mitochondrial complex I activity and NAD+/NADH balance regulate breast cancer progression

Despite advances in clinical therapy, metastasis remains the leading cause of death in breast cancer patients. Mutations in mitochondrial DNA, including those affecting complex I and oxidative phosphorylation, are found in breast tumors and could facilitate metastasis. This study identifies mitochondrial complex I as critical for defining an aggressive phenotype in breast cancer cells. Specific enhancement of mitochondrial complex I activity inhibited tumor growth and metastasis through regulation of the tumor cell NAD+/NADH redox balance, mTORC1 activity, and autophagy. Conversely, nonlethal reduction of NAD+ levels by interfering with nicotinamide phosphoribosyltransferase expression rendered tumor cells more aggressive and increased metastasis. The results translate into a new therapeutic strategy: enhancement of the NAD+/NADH balance through treatment with NAD+ precursors inhibited metastasis in xenograft models, increased animal survival, and strongly interfered with oncogene-driven breast cancer progression in the MMTV-PyMT mouse model. Thus, aberration in mitochondrial complex I NADH dehydrogenase activity can profoundly enhance the aggressiveness of human breast cancer cells, while therapeutic normalization of the NAD+/NADH balance can inhibit metastasis and prevent disease progression.

The diabetes-susceptible gene SLC30A8/ZnT8 regulates hepatic insulin clearance

Recent genome-wide association studies demonstrated that common variants of solute carrier family 30 member 8 gene (SLC30A8) increase susceptibility to type 2 diabetes. SLC30A8 encodes zinc transporter-8 (ZnT8), which delivers zinc ion from the cytoplasm into insulin granules. Although it is well known that insulin granules contain high amounts of zinc, the physiological role of secreted zinc remains elusive. In this study, we generated mice with β cell-specific Slc30a8 deficiency (ZnT8KO mice) and demonstrated an unexpected functional linkage between Slc30a8 deletion and hepatic insulin clearance. The ZnT8KO mice had low peripheral blood insulin levels, despite insulin hypersecretion from pancreatic β cells. We also demonstrated that a substantial amount of the hypersecreted insulin was degraded during its first passage through the liver. Consistent with these findings, ZnT8KO mice and human individuals carrying rs13266634, a major risk allele of SLC30A8, exhibited increased insulin clearance, as assessed by c-peptide/insulin ratio. Furthermore, we demonstrated that zinc secreted in concert with insulin suppressed hepatic insulin clearance by inhibiting clathrin-dependent insulin endocytosis. Our results indicate that SLC30A8 regulates hepatic insulin clearance and that genetic dysregulation of this system may play a role in the pathogenesis of type 2 diabetes.

Understanding the rift, the (still) uneasy bedfellows of History and Organization Studies

Although the use of History has become increasingly discussed and more widely applied within Organization Studies (OS), its relevance for OS still remains far from centrally accepted. This article historicizes the relationship between Sociology and History as a means of better understanding the tensions, perceived and real, that exist between History and Organization Studies. In particular we analyse three differences of epistemological standpoint (method, objectivity and usefulness) that are commonly seen as the foundation stones to incompatibility. Perhaps surprisingly for an analysis of apparent disciplinary differences, we find that these distinctions in terms of approach, once closely examined, are rarely clear-cut and historians and OS scholars are frequently closer in intention and method than they are distant. However, despite their large intersection of interests, we argue that important distinctions between the two fields should be acknowledged. Our contribution to the debates over the need for more historical approaches within OS therefore centrally rests on abandoning aspirations for fully integrative models of working together, in favour of cooperative modes that concede the fields’ differences. This subtle shift of emphasis will, we believe, greatly benefit OS scholars who hope to include historical perspectives in their work

27° Congresso Nazionale AINR Coppito (AQ), 18–21 settembre 2013

CD44v6-targeted T cells mediate potent antitumor effects against acute myeloid leukemia and multiple myeloma

Genetically targeted T cells promise to solve the feasibility and efficacy hurdles of adoptive T-cell therapy for cancer. Selecting a target expressed in multiple-tumor types and that is required for tumor growth would widen disease indications and prevent immune escape caused by the emergence of antigen-loss variants. The adhesive receptor CD44 is broadly expressed in hematologic and epithelial tumors, where it contributes to the cancer stem/initiating phenotype. In this study, silencing of its isoform variant 6 (CD44v6) prevented engraftment of human acute myeloid leukemia (AML) and multiple myeloma (MM) cells in immunocompromised mice. Accordingly, T cells targeted to CD44v6 by means of a chimeric antigen receptor containing a CD28 signaling domain mediated potent antitumor effects against primary AML and MM while sparing normal hematopoietic stem cells and CD44v6-expressing keratinocytes. Importantly, in vitro activation with CD3/CD28 beads and interleukin (IL)-7/IL-15 was required for antitumor efficacy in vivo. Finally, coexpressing a suicide gene enabled fast and efficient pharmacologic ablation of CD44v6-targeted T cells and complete rescue from hyperacute xenogeneic graft-versus-host disease modeling early and generalized toxicity. These results warrant the clinical investigation of suicidal CD44v6-targeted T cells in AML and MM.

Phylogenomics of strongylocentrotid sea urchins

Background Strongylocentrotid sea urchins have a long tradition as model organisms for studying many fundamental processes in biology including fertilization, embryology, development and genome regulation but the phylogenetic relationships of the group remain largely unresolved. Although the differing isolating mechanisms of vicariance and rapidly evolving gamete recognition proteins have been proposed, a stable and robust phylogeny is unavailable. Results We used a phylogenomic approach with mitochondrial and nuclear genes taking advantage of the whole-genome sequencing of nine species in the group to establish a stable (i.e. concordance in tree topology among multiple lies of evidence) and robust (i.e. high nodal support) phylogenetic hypothesis for the family Strongylocentrotidae. We generated eight draft mitochondrial genome assemblies and obtained 13 complete mitochondrial genes for each species. Consistent with previous studies, mitochondrial sequences failed to provide a reliable phylogeny. In contrast, we obtained a very well-supported phylogeny from 2301 nuclear genes without evidence of positive Darwinian selection both from the majority of most-likely gene trees and the concatenated fourfold degenerate sites: (( P. depressus, (M. nudus, M. franciscanus ), ( H. pulcherrimus, ( S. purpuratus, ( S. fragilis, ( S. pallidus, ( S. droebachiensis, S. intermedius )). This phylogeny was consistent with a single invasion of deep-water environments followed by a holarctic expansion by Strongylocentrotus . Divergence times for each species estimated with reference to the divergence times between the two major clades of the group suggest a correspondence in the timing with the opening of the Bering Strait and the invasion of the holarctic regions. Conclusions Nuclear genome data contains phylogenetic signal informative for understanding the evolutionary history of this group. However, mitochondrial genome data does not. Vicariance can explain major patterns observed in the phylogeny. Other isolating mechanisms are appropriate to explore in this system to help explain divergence patterns not well supported by vicariance, such as the effects of rapidly evolving gamete recognition proteins on isolating populations. Our findings of a stable and robust phylogeny, with the increase in mitochondrial and nuclear comparative genomic data, provide a system in which we can enhance our understanding of molecular evolution and adaptation in this group of sea urchins.

Transcription profile of soybean-root-knot nematode interaction reveals a key role of phythormones in the resistance reaction

Background Root-knot nematodes (RKN– Meloidogyne genus) present extensive challenges to soybean crop. The soybean line (PI 595099) is known to be resistant against specific strains and races of nematode species, thus its differential gene expression analysis can lead to a comprehensive gene expression profiling in the incompatible soybean-RKN interaction. Even though many disease resistance genes have been studied, little has been reported about phytohormone crosstalk on modulation of ROS signaling during soybean-RKN interaction. Results Using 454 technology to explore the common aspects of resistance reaction during both parasitism and resistance phases it was verified that hormone, carbohydrate metabolism and stress related genes were consistently expressed at high levels in infected roots as compared to mock control. Most noteworthy genes include those encoding glycosyltransferases, peroxidases, auxin-responsive proteins and gibberellin-regulated genes. Our data analysis suggests the key role of glycosyltransferases, auxins and components of gibberellin signal transduction, biosynthesis and deactivation pathways in the resistance reaction and their participation in jasmonate signaling and redox homeostasis in mediating aspects of plant growth and responses to biotic stress. Conclusions Based on this study we suggest a reasonable model regarding to the complex mechanisms of crosstalk between plant hormones, mainly gibberellins and auxins, which can be crucial to modulate the levels of ROS in the resistance reaction to nematode invasion. The model also includes recent findings concerning to the participation of DELLA-like proteins and ROS signaling controlling plant immune or stress responses. Furthermore, this study provides a dataset of potential candidate genes involved in both nematode parasitism and resistance, which can be tested further for their role in this biological process using functional genomics approaches.

Compositional patterns in the genomes of unicellular eukaryotes

Background The genomes of multicellular eukaryotes are compartmentalized in mosaics of isochores, large and fairly homogeneous stretches of DNA that belong to a small number of families characterized by different average GC levels, by different gene concentration (that increase with GC), different chromatin structures, different replication timing in the cell cycle, and other different properties. A question raised by these basic results concerns how far back in evolution the compartmentalized organization of the eukaryotic genomes arose. Results In the present work we approached this problem by studying the compositional organization of the genomes from the unicellular eukaryotes for which full sequences are available, the sample used being representative. The average GC levels of the genomes from unicellular eukaryotes cover an extremely wide range (19%-60% GC) and the compositional patterns of individual genomes are extremely different but all genomes tested show a compositional compartmentalization. Conclusions The average GC range of the genomes of unicellular eukaryotes is very broad (as broad as that of prokaryotes) and individual compositional patterns cover a very broad range from very narrow to very complex. Both features are not surprising for organisms that are very far from each other both in terms of phylogenetic distances and of environmental life conditions. Most importantly, all genomes tested, a representative sample of all supergroups of unicellular eukaryotes, are compositionally compartmentalized, a major difference with prokaryotes.

Semantic integration of gene expression analysis tools and data sources using software connectors

Background The study and analysis of gene expression measurements is the primary focus of functional genomics. Once expression data is available, biologists are faced with the task of extracting (new) knowledge associated to the underlying biological phenomenon. Most often, in order to perform this task, biologists execute a number of analysis activities on the available gene expression dataset rather than a single analysis activity. The integration of heteregeneous tools and data sources to create an integrated analysis environment represents a challenging and error-prone task. Semantic integration enables the assignment of unambiguous meanings to data shared among different applications in an integrated environment, allowing the exchange of data in a semantically consistent and meaningful way. This work aims at developing an ontology-based methodology for the semantic integration of gene expression analysis tools and data sources. The proposed methodology relies on software connectors to support not only the access to heterogeneous data sources but also the definition of transformation rules on exchanged data. Results We have studied the different challenges involved in the integration of computer systems and the role software connectors play in this task. We have also studied a number of gene expression technologies, analysis tools and related ontologies in order to devise basic integration scenarios and propose a reference ontology for the gene expression domain. Then, we have defined a number of activities and associated guidelines to prescribe how the development of connectors should be carried out. Finally, we have applied the proposed methodology in the construction of three different integration scenarios involving the use of different tools for the analysis of different types of gene expression data. Conclusions The proposed methodology facilitates the development of connectors capable of semantically integrating different gene expression analysis tools and data sources. The methodology can be used in the development of connectors supporting both simple and nontrivial processing requirements, thus assuring accurate data exchange and information interpretation from exchanged data.