Functional sphere profiling reveals the complexity of neuroblastoma tumor-initiating cell model.

Neuroblastoma (NB) is a neural crest-derived childhood tumor characterized by a remarkable phenotypic diversity, ranging from spontaneous regression to fatal metastatic disease. Although the cancer stem cell (CSC) model provides a trail to characterize the cells responsible for tumor onset, the NB tumor-initiating cell (TIC) has not been identified. In this study, the relevance of the CSC model in NB was investigated by taking advantage of typical functional stem cell characteristics. A predictive association was established between self-renewal, as assessed by serial sphere formation, and clinical aggressiveness in primary tumors. Moreover, cell subsets gradually selected during serial sphere culture harbored increased in vivo tumorigenicity, only highlighted in an orthotopic microenvironment. A microarray time course analysis of serial spheres passages from metastatic cells allowed us to specifically "profile" the NB stem cell-like phenotype and to identify CD133, ABC transporter, and WNT and NOTCH genes as spheres markers. On the basis of combined sphere markers expression, at least two distinct tumorigenic cell subpopulations were identified, also shown to preexist in primary NB. However, sphere markers-mediated cell sorting of parental tumor failed to recapitulate the TIC phenotype in the orthotopic model, highlighting the complexity of the CSC model. Our data support the NB stem-like cells as a dynamic and heterogeneous cell population strongly dependent on microenvironmental signals and add novel candidate genes as potential therapeutic targets in the control of high-risk NB.

Efficient knowledge retrieval to calibrate input variables in forest fire prediction

Forest fires are a serious threat to humans and nature from an ecological, social and economic point of view. Predicting their behaviour by simulation still delivers unreliable results and remains a challenging task. Latest approaches try to calibrate input variables, often tainted with imprecision, using optimisation techniques like Genetic Algorithms. To converge faster towards fitter solutions, the GA is guided with knowledge obtained from historical or synthetical fires. We developed a robust and efficient knowledge storage and retrieval method. Nearest neighbour search is applied to find the fire configuration from knowledge base most similar to the current configuration. Therefore, a distance measure was elaborated and implemented in several ways. Experiments show the performance of the different implementations regarding occupied storage and retrieval time with overly satisfactory results.

Combined clonotyping and gene signatures of individual tumor-reactive CD8 T-cells define their functional relevance following peptide vaccination in melanoma patients

Novel cancer vaccines are capableto efficiently induce and boost humantumor antigen specific T-cells. However,the properties of these CD8T-cells are only partially characterized.For in depth investigation ofT-cells following Melan-A/MART-1peptide vaccination in melanoma patients,we conducted a detailed prospectivestudy at the single cell level.We first sorted individual human naiveand effector CD8 T-cells from peripheralblood by flow cytometry, andtested a modified RT-PCR protocolincluding a global amplification ofexpressed mRNAs to obtain sufficientcDNAfromsingle cells.We successfullydetected the expression ofseveral specific genes of interest evendown to 106-fold dilution (equivalentto 10-5 cell). We then analyzed tumor-specific effector memory (EM)CD8T-cell subpopulations ex vivo, assingle cells from vaccinated melanomapatients. To elucidate the hallmarksof effective immunity the genesignatures were defined by a panel ofgenes related to effector functions(e.g. IFN-, granzyme B, perforin),and individual clonotypes were identifiedaccording to the expression ofdistinct T-cell receptors (TCR). Usingthis novel single cell analysis approach,we observed that T-cell differentiationis clonotype dependent,with a progressive restriction in TCRBV clonotype diversity from EMCD28pos to EMCD28neg subsets. However,the effector function gene imprintingis clonotype-independent,but dependent on differentiation,since it correlates with the subset oforigin (EMCD28pos or EMCD28neg). We also conducted a detailedcomparative analysis after vaccinationwith natural vs. analog Melan-Apeptide. We found that the peptideused for vaccination determines thefunctional outcome of individualT-cell clonotypes, with native peptideinducing more potent effector functions.Yet, selective clonotypic expansionwith differentiation was preservedregardless of the peptide usedfor vaccination. In summary, the exvivo single cell RT-PCR approach ishighly sensitive and efficient, andrepresents a reliable and powerfultool to refine our current view of molecularprocesses taking place duringT-cell differentiation.

Targeting of secretory IgA to Peyer's patch dendritic and T cells after transport by intestinal M cells.

In addition to being instrumental to the protection of mucosal epithelia, secretory IgA (SIgA) adheres to and is transported by intestinal Peyer's patch (PP) M cells. The possible functional reason for this transport is unknown. We have thus examined in mice the outcome of SIgA delivered from the intestinal lumen to the cells present in the underlying organized mucosa-associated lymphoreticular tissue. We show selective association of SIgA with dendritic cells and CD4(+) T and B lymphocytes recovered from PP in vitro. In vivo, exogenously delivered SIgA is able to enter into multiple PP lining the intestine. In PP, SIgA associates with and is internalized by dendritic cells in the subepithelial dome region, whereas the interaction with CD4(+) T cells is limited to surface binding. Interaction between cells and SIgA is mediated by the IgA moiety and occurs for polymeric and monomeric molecular forms. Thus, although immune exclusion represents the main function of SIgA, transport of the Ab by M cells might promote Ag sampling under neutralizing conditions essential to the homeostasis of mucosal surfaces.

Modeling resting-state functional networks when the cortex falls asleep: local and global changes.

The transition from wakefulness to sleep represents the most conspicuous change in behavior and the level of consciousness occurring in the healthy brain. It is accompanied by similarly conspicuous changes in neural dynamics, traditionally exemplified by the change from "desynchronized" electroencephalogram activity in wake to globally synchronized slow wave activity of early sleep. However, unit and local field recordings indicate that the transition is more gradual than it might appear: On one hand, local slow waves already appear during wake; on the other hand, slow sleep waves are only rarely global. Studies with functional magnetic resonance imaging also reveal changes in resting-state functional connectivity (FC) between wake and slow wave sleep. However, it remains unclear how resting-state networks may change during this transition period. Here, we employ large-scale modeling of the human cortico-cortical anatomical connectivity to evaluate changes in resting-state FC when the model "falls asleep" due to the progressive decrease in arousal-promoting neuromodulation. When cholinergic neuromodulation is parametrically decreased, local slow waves appear, while the overall organization of resting-state networks does not change. Furthermore, we show that these local slow waves are structured macroscopically in networks that resemble the resting-state networks. In contrast, when the neuromodulator decrease further to very low levels, slow waves become global and resting-state networks merge into a single undifferentiated, broadly synchronized network.

How reliable is the monitoring of permanent vegetation plots? A test with multiple observers

Questions: A multiple plot design was developed for permanent vegetation plots. How reliable are the different methods used in this design and which changes can we measure? Location: Alpine meadows (2430 m a.s.l.) in the Swiss Alps. Methods: Four inventories were obtained from 40 m(2) plots: four subplots (0.4 m(2)) with a list of species, two 10m transects with the point method (50 points on each), one subplot (4 m2) with a list of species and visual cover estimates as a percentage and the complete plot (40 m(2)) with a list of species and visual estimates in classes. This design was tested by five to seven experienced botanists in three plots. Results: Whatever the sampling size, only 45-63% of the species were seen by all the observers. However, the majority of the overlooked species had cover < 0.1%. Pairs of observers overlooked 10-20% less species than single observers. The point method was the best method for cover estimate, but it took much longer than visual cover estimates, and 100 points allowed for the monitoring of only a very limited number of species. The visual estimate as a percentage was more precise than classes. Working in pairs did not improve the estimates, but one botanist repeating the survey is more reliable than a succession of different observers. Conclusion: Lists of species are insufficient for monitoring. It is necessary to add cover estimates to allow for subsequent interpretations in spite of the overlooked species. The choice of the method depends on the available resources: the point method is time consuming but gives precise data for a limited number of species, while visual estimates are quick but allow for recording only large changes in cover. Constant pairs of observers improve the reliability of the records.

Human effector CD8+ T lymphocytes express TLR3 as a functional coreceptor.

TLR are evolutionarily conserved molecules that play a key role in the initiation of innate antimicrobial immune responses. Through their influence on dendritic cell maturation, these receptors are also thought to indirectly shape the adaptive immune response. However, no data are currently available regarding both TLR expression and function in human CD8+ T cell subsets. We report that a subpopulation of CD8+ T cells, i.e., effector, but neither naive nor central memory cells, constitutively expresses TLR3. Moreover, the ligation of the receptor by a specific agonist in TLR3-expressing CD8+ T cells increased IFN-gamma secretion induced by TCR-dependent and -independent stimulation, without affecting proliferation or specific cytolytic activity. These results thereby suggest that TLR3 ligands can not only indirectly influence the adaptive immune response through modulation of dendritic cell activation, but also directly increase IFN-gamma production by Ag-specific CD8+ T cells. Altogether, the present work might open new perspectives for the use of TLR ligands as adjuvants for immunotherapy.

Differential peptide binding to CD40 evokes counteractive responses.

The antigen-presenting cell-expressed CD40 is implied in the regulation of counteractive immune responses such as induction of pro-inflammatory and anti-inflammatory cytokines interleukin (IL)-12 and IL-10, respectively. The mechanism of this duality in CD40 function remains unknown. Here, we investigated whether such duality depends on ligand binding. Based on CD40 binding, we identifed two dodecameric peptides, peptide-7 and peptide-19, from the phage peptide library. Peptide-7 induces IL-10 and increases Leishmania donovani infection in macrophages, whereas peptide-19 induces IL-12 and reduces L. donovani infection. CD40-peptide interaction analyses by surface plasmon resonance and atomic force microscopy suggest that the functional differences are not associated with the studied interaction parameters. The molecular dynamic simulation of the CD40-peptides interaction suggests that these two peptides bind to two different places on CD40. Thus, we suggest for the first time that differential binding of the ligands imparts functional duality to CD40.

An interregional input-output analysis of the pollution content of trade flows and environmental trade balances between five states in the US Mid-West

In this paper we attempt an empirical application of the multi-region input-output (MRIO) method in order to enumerate the pollution content of interregional trade flows between five Mid-West regions/states in the US –Illinois, Indiana, Iowa, Michigan and Wisconsin – and the rest of the US. This allows us to analyse some very important issues in terms of the nature and significance of interregional environmental spillovers within the US Mid-West and the existence of pollution ‘trade balances’ between states. Our results raise questions in terms of the extent to which authorities at State level can control local emissions where they are limited in the way some emissions can be controlled, particularly with respect to changes in demand elsewhere in the Mid-West and US. This implies a need for policy co-ordination between national and state level authorities in the US to meet emissions reductions targets. The existence of an environmental trade balances between states also raises issues in terms of net losses/gains in terms of pollutants as a result of interregional trade within the US and whether, if certain activities can be carried out using less polluting technology in one region relative to others, it is better for the US as a whole if this type of relationship exists.

Responsibility for regional waste generation: A single region extended input-output analysis with uni-directional trade flows

The paper uses a regional input-output (IO) framework and data derived on waste generation by industry to examine regional accountability for waste generation. In addition to estimating a series of industry output-waste coefficients, the paper considers two methods for waste attribution but focuses first on one (trade endogenised linear attribution system (TELAS)) that permits a greater focus on private and public final consumption as the main exogenous driver of waste generation. Second, the paper uses a domestic technology assumption (DTA) to consider a regional ‘waste footprint’ where local consumption requirements are assumed to be met through domestic production.

An HEI-Disaggregated Input-Output Table for Scotland

This paper describes how the education sector of the Scottish Input-Output tables is disaggregated to identify a separate sector for each of Scotland’s twenty Higher Education Institutions (HEIs). The process draws on accounting and survey data to accurately determine the incomes and expenditures of each institution. In particular we emphasise determining the HEIs incomes source of origin to inform their treatment, as endogenous or exogenous, in subsequent analyses. The HEI-disaggregated Input- Output table provides a useful descriptive snapshot of the Scottish economy and the role of HEIs within it for a particular year, 2006. The table can be used to derive multipliers and conduct various impact studies of each institution or the sector as a whole. The table is furthermore useful to calibrate other multi-sectoral, HEI disaggregated models of regional economies, including Social Accounting Matrix (SAM) and computable general equilibrium (CGE) models.

An HEI-Disaggregated Input-Output Table for Wales

This paper describes how the education sector of the Welsh Input-Output tables is disaggregated to identify a separate sector for each of Wales’s twelve Higher Education Institutions (HEIs). The process draws on accounting and survey data to accurately determine the incomes and expenditures of each institution. In particular we emphasise determining the HEIs incomes source of origin to inform their treatment, as endogenous or exogenous, in subsequent analyses. The HEI-disaggregated Input-Output table provides a useful descriptive snapshot of the Welsh economy and the role of HEIs within it for a particular year, 2006. The table can be used to derive multipliers and conduct various impact studies of each institution or the sector as a whole. The table is furthermore useful to calibrate other multi-sectoral, HEI-disaggregated models of regional economies, including Social Accounting Matrix (SAM) and computable general equilibrium (CGE) models.

An HEI-Disaggregated Input-Output Table for Northern-Ireland

This paper describes how the education sector of an Input-Output table for Northern Ireland is disaggregated to identify a separate sector for each of the four Northern Irish Higher Education Institutions (HEIs). The process draws on accounting and survey data to accurately determine the incomes and expenditures of each institution. In particular we emphasise determining the HEIs incomes source of origin to inform their treatment, as endogenous or exogenous, in subsequent analyses. The HEI-disaggregated Input-Output table provides a useful descriptive snapshot of the Northern Irish economy and the role of HEIs within it for a particular year, 2006. The table can be used to derive multipliers and conduct various impact studies of each institution or the sector as a whole. The table is furthermore useful to calibrate other multisectoral, HEI-disaggregated models of regional economies, including Social Accounting Matrix (SAM) and computable general equilibrium (CGE) models.