The prognostic value of Foxp3+ tumor-infiltrating lymphocytes in patients with glioblastoma

Forkhead box protein 3 (Foxp3) is known as a specific marker for regulatory T cells which contribute to immunosuppression in tumor microenvironment. However, existing studies regarding clinical significance of Foxp3+ tumor-infiltrating lymphocytes (TILs) in glioblastoma (GBM) remained discrepant. In this study, we aimed to explore whether this subtype of TILs correlated with prognosis in patients with GBM. Foxp3+ TILs as well as CD8+ ones were detected by immunohistochemistry on paraffin-embedded tumor samples from 62 patients. Staining for p53, MGMT and Ki-67 were also performed. The correlation of TIL subtypes with clinicopathologic features were analyzed. Progression-free survival (PFS) and overall survival (OS) were estimated by Kaplan–Meier method and compared using log-rank test. Independent prognostic factors for PFS and OS were determined through univariate and multivariate analysis. Significant correlation was found between Foxp3 and CD8 expression (P = 0.003), but not between TIL subtypes and clinicopathologic characteristics. Patients with higher density of Foxp3+ TILs showed relatively shorter PFS (P < 0.001) and OS (P = 0.003) whereas patients with higher density of CD8+ TILs obtained no significant differences in survival. Survival analysis based on molecular classifications further clarified these predictive values. Univariate and multivariate analysis revealed that frequency of Foxp3+ TILs was probably associated with both PFS (P = 0.002) and OS (P = 0.003). In conclusion, the results suggest that Foxp3 positive infiltrates could provide an independent predictive factor in GBM. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11060-013-1314-0) contains supplementary material, which is available to authorized users

Vegetation–climate interactions in arid and semi–arid regions

Vegetation–climate interactions play an important role in earth system dynamics. It includes the effects of climate on vegetation and feedbacks from vegetation to climate. Such complex and nonlinear processes can enhance climate variation and lead to alternative stable states under given climate regimes. In this thesis, both model and statistical approaches are applied to demonstrate specific mechanisms of vegetation–climate interactions and related consequences. Research area includes arid and semi–arid regions in West Africa, where vegetation and climate are found to be strongly coupled. The thesis starts from a Balanced Optimality Structure Vegetation Model (BOSVM) considering water, energy and carbon balances. The BOSVM is used to demonstrate: 1) How vegetation adjusts to local climate by optimizing its spatial structure to maximize equilibrium biomass? 2) How the optimal structure shifts with climate regimes? Results show that vegetation with a low shoot–total biomass ratio and a vertical canopy can reach the maximal biomass under water–limited conditions. However the optimal structure shifts to high shoot–total biomass ratio and horizontal canopy with an increase of mean annual precipitation. A positive and a negative feedback are found in the water competition between vegetation and bare soil, which makes vegetation grow into patches to maximize water use efficiency, or to extend vegetation cover to stop water loss from bare soil. One important consequence of vegetation–climate interactions is the formation of alternative stable states under a given climate regime. It implies that vegetation can abruptly shift from one stable state to another with a change of climate. The point where the critical transition occurs, is called the tipping point. A complex network approach is applied to monitor the stability of vegetation state and provide early warning signals of upcoming tipping point in a coupled land–atmosphere model. Comparing with two classical indicators, network indicators show higher sensitivity to potential critical transitions and yielded early warning signals can be easier distinguished from local variability. One evidence of alternative stable states is the observed bimodal distribution of woody cover under the same rainfall band in tropical regions. Simulated biomass dynamics affected by fire is compared with observations to understand the observed bimodality. Results suggest that growth rate of woody cover varies with the age of woody plants, which also can lead to the observed bimodality of woody cover. The shift of vegetation structure is the necessary component for the formation of bimodality. Finally, the spatial distribution of land cover types in West Africa is illustrated. Six climatic indicators are analyzed to demonstrate their ability to distinguish land cover types. The mean annual precipitation has large uncertainty to predict specific land cover type. Simultaneously, prediction accuracies of other climatic indicators vary significantly with the change of land cover types. Several indicators are chosen and combined to improve land cover prediction. Patterns of potential land cover change in West Africa are illustrated, where forest is under stress while savanna and grassland show a tendency to extend to the north

Intelligent agent based automatic operating model

In this thesis, the first discussion is about a general automatic model for intelligent agent based operations. Since applications under test and applications released as products are operated for different purposes, two elaborated model are derived from the general model: intelligent agent based operating Model for Product Applications (MPA) and intelligent agent based operating Models for Regression Testing (MRT).MASTER OF ENGINEERING (EEE

De los encuentros feministas a las campañas transnacionales: surgimiento y desarrollo de los movimientos trasnacionales de mujeres en Ámerica Latina

Con el debate sobre la globalización cobran cada vez mayor importancia los movimientos sociales. Dentro de las discusiones sobre la gobernabilidad global se consideran a los movimientos sociales como actores importantes de la sociedad civil. En los medios masivos de comunicación pasan noticias sobre acciones de los movimientos sociales en contra de las políticas económicas internacionales. En este nuevo contexto internacional los movimientos sociales han creado redes que reúnen a los grupos y protagonistas para ha- cer frente a los procesos globales.

Validation of a new global irrigation scheme in the land surface model ORCHIDEE v2.2

International audienceAbstract. Irrigation activities are important for sustaining food production and account for 70 % of total global water withdrawals. In addition, due to increased evapotranspiration (ET) and changes in the leaf area index (LAI), these activities have an impact on hydrology and climate. In this paper, we present a new irrigation scheme within the land surface model ORCHIDEE (ORganising Carbon and Hydrology in Dynamic EcosystEms)). It restrains actual irrigation according to available freshwater by including a simple environmental limit and using allocation rules that depend on local infrastructure. We perform a simple sensitivity analysis and parameter tuning to set the parameter values and match the observed irrigation amounts against reported values, assuming uniform parameter values over land. Our scheme matches irrigation withdrawals amounts at global scale, but we identify some areas in India, China, and the USA (some of the most intensively irrigated regions worldwide), where irrigation is underestimated. In all irrigated areas, the scheme reduces the negative bias of ET. It also exacerbates the positive bias of the leaf area index (LAI), except for the very intensively irrigated areas, where irrigation reduces a negative LAI bias. The increase in the ET decreases river discharge values, in some cases significantly, although this does not necessarily lead to a better representation of discharge dynamics. Irrigation, however, does not have a large impact on the simulated total water storage anomalies (TWSAs) and its trends. This may be partly explained by the absence of nonrenewable groundwater use, and its inclusion could increase irrigation estimates in arid and semiarid regions by increasing the supply. Correlation of irrigation biases with landscape descriptors suggests that the inclusion of irrigated rice and dam management could improve the irrigation estimates as well. Regardless of this complexity, our results show that the new irrigation scheme helps simulate acceptable land surface conditions and fluxes in irrigated areas, which is important to explore the joint evolution of climate, water resources, and irrigation activities

Bidirectional two-sample mendelian randomization analysis identifies causal associations of MRI-based cortical thickness and surface area relation to NAFLD

Abstract Background Non-alcoholic fatty liver disease (NAFLD) patients have exhibited extra-hepatic neurological changes, but the causes and mechanisms remain unclear. This study investigates the causal effect of NAFLD on cortical structure through bidirectional two-sample Mendelian randomization analysis. Methods Genetic data from 778,614 European individuals across four NAFLD studies were used to determine genetically predicted NAFLD. Abdominal MRI scans from 32,860 UK Biobank participants were utilized to evaluate genetically predicted liver fat and volume. Data from the ENIGMA Consortium, comprising 51,665 patients, were used to evaluate the associations between genetic susceptibility, NAFLD risk, liver fat, liver volume, and alterations in cortical thickness (TH) and surface area (SA). Inverse-variance weighted (IVW) estimation, Cochran Q, and MR-Egger were employed to assess heterogeneity and pleiotropy. Results Overall, NAFLD did not significantly affect cortical SA or TH. However, potential associations were noted under global weighting, relating heightened NAFLD risk to reduced parahippocampal SA and decreased cortical TH in the caudal middle frontal, cuneus, lingual, and parstriangularis regions. Liver fat and volume also influenced the cortical structure of certain regions, although no Bonferroni-adjusted p-values reached significance. Two-step MR analysis revealed that liver fat, AST, and LDL levels mediated the impact of NAFLD on cortical structure. Multivariable MR analysis suggested that the impact of NAFLD on the cortical TH of lingual and parstriangularis was independent of BMI, obesity, hyperlipidemia, and diabetes. Conclusion This study provides evidence that NAFLD causally influences the cortical structure of the brain, suggesting the existence of a liver-brain axis in the development of NAFLD

Daytime-only mean data enhance understanding of land–atmosphere coupling

Abstract. Land–atmosphere (L–A) interactions encompass the co-evolution of the land surface and overlying planetary boundary layer, primarily during daylight hours. However, many studies have been conducted using monthly or entire-day mean time series due to the lack of subdaily data. It is unclear whether the inclusion of nighttime data alters the assessment of L–A coupling or obscures L–A interactive processes. To address this question, we generate monthly (M), entire-day mean (E), and daytime-only mean (D) data based on the ERA5 (5th European Centre for Medium-Range Weather Forecasts reanalysis) product and evaluate the strength of L–A coupling through two-legged metrics, which partition the impact of the land states on surface fluxes (the land leg) from the impact of surface fluxes on the atmospheric states (the atmospheric leg). Here we show that the spatial patterns of strong L–A coupling regions among the M-, D-, and E-based diagnoses can differ by more than 80 %. The signal loss from E- to M-based diagnoses is determined by the memory of local L–A states. The differences between E- and D-based diagnoses can be driven by physical mechanisms or averaging algorithms. To improve understanding of L–A interactions, we call attention to the urgent need for more high-frequency data from both simulations and observations for relevant diagnoses. Regarding model outputs, two approaches are proposed to resolve the storage dilemma for high-frequency data: (1) integration of L–A metrics within Earth system models, and (2) producing alternative daily datasets based on different averaging algorithms