Survival, differentiation, and neuroprotective mechanisms of human stem cells complexed with neurotrophin-3-releasing pharmacologically active microcarriers in an ex vivo model of Parkinson's disease

International audience

Survival analysis with internal covariates modelled using a longitudinal dispersion model and flexible links

Poster presented at the From Basic Sciences to Clinical Research: 1st International Congress of CiiEM. Egas Moniz, Caparica, Portugal, 27-28 November 2015

Analysis Of The Contribution Of Immunologically-detectable Her2, Steroid Receptors And Of The Triple-negative" Tumor Status To Disease-free And Overall Survival Of Women With Epithelial Ovarian Cancer."

We assessed associations between steroid receptors including: estrogen-alpha, estrogen-beta, androgen receptor, progesterone receptor, the HER2 status and triple-negative epithelial ovarian cancer (ERα-/PR-/HER2-; TNEOC) status and survival in women with epithelial ovarian cancer. The study included 152 women with primary epithelial ovarian cancer. The status of steroid receptor and HER2 was determined by immunohistochemistry. Disease-free and overall survival were calculated and compared with steroid receptor and HER2 status as well as clinicopathological features using the Cox Proportional Hazards model. A mean follow-up period of 43.6 months (interquartile range=41.4 months) was achieved where 44% of patients had serous tumor, followed by mucinous (23%), endometrioid (9%), mixed (9%), undifferentiated (8.5%) and clear cell tumors (5.3%). ER-alpha staining was associated with grade II-III tumors. Progesterone receptor staining was positively associated with a Body Mass Index≥25. Androgen receptor positivity was higher in serous tumors. In stand-alone analysis of receptor contribution to survival, estrogen-alpha positivity was associated with greater disease-free survival. However, there was no significant association between steroid receptor expression, HER2 status, or TNEOC status, and overall survival. Although estrogen-alpha, androgen receptor, progesterone receptor and the HER2 status were associated with key clinical features of the women and pathological characteristics of the tumors, these associations were not implicated in survival. Interestingly, women with TNEOC seem to fare the same way as their counterparts with non-TNEOC.

Survival Extrapolation In The Presence Of Cause Specific Hazards.

Health economic evaluations require estimates of expected survival from patients receiving different interventions, often over a lifetime. However, data on the patients of interest are typically only available for a much shorter follow-up time, from randomised trials or cohorts. Previous work showed how to use general population mortality to improve extrapolations of the short-term data, assuming a constant additive or multiplicative effect on the hazards for all-cause mortality for study patients relative to the general population. A more plausible assumption may be a constant effect on the hazard for the specific cause of death targeted by the treatments. To address this problem, we use independent parametric survival models for cause-specific mortality among the general population. Because causes of death are unobserved for the patients of interest, a polyhazard model is used to express their all-cause mortality as a sum of latent cause-specific hazards. Assuming proportional cause-specific hazards between the general and study populations then allows us to extrapolate mortality of the patients of interest to the long term. A Bayesian framework is used to jointly model all sources of data. By simulation, we show that ignoring cause-specific hazards leads to biased estimates of mean survival when the proportion of deaths due to the cause of interest changes through time. The methods are applied to an evaluation of implantable cardioverter defibrillators for the prevention of sudden cardiac death among patients with cardiac arrhythmia. After accounting for cause-specific mortality, substantial differences are seen in estimates of life years gained from implantable cardioverter defibrillators.

Exercise Increases Pancreatic β-cell Viability In A Model Of Type 1 Diabetes Through Il-6 Signaling.

Type 1 diabetes (T1D) is provoked by an autoimmune assault against pancreatic β cells. Exercise training enhances β-cell mass in T1D. Here, we investigated how exercise signals β cells in T1D condition. For this, we used several approaches. Wild-type and IL-6 knockout (KO) C57BL/6 mice were exercised. Afterward, islets from control and trained mice were exposed to inflammatory cytokines (IL-1β plus IFN-γ). Islets from control mice and β-cell lines (INS-1E and MIN6) were incubated with serum from control or trained mice or medium obtained from 5-aminoimidazole-4 carboxamide1-β-d-ribofuranoside (AICAR)-treated C2C12 skeletal muscle cells. Subsequently, islets and β cells were exposed to IL-1β plus IFN-γ. Proteins were assessed by immunoblotting, apoptosis was determined by DNA-binding dye propidium iodide fluorescence, and NO(•) was estimated by nitrite. Exercise reduced 25, 75, and 50% of the IL-1β plus IFN-γ-induced iNOS, nitrite, and cleaved caspase-3 content, respectively, in pancreatic islets. Serum from trained mice and medium from AICAR-treated C2C12 cells reduced β-cell death, induced by IL-1β plus IFN-γ treatment, in 15 and 38%, respectively. This effect was lost in samples treated with IL-6 inhibitor or with serum from exercised IL-6 KO mice. In conclusion, muscle contraction signals β-cell survival in T1D through IL-6.-Paula, F. M. M., Leite, N. C., Vanzela, E. C., Kurauti, M. A., Freitas-Dias, R., Carneiro, E. M., Boschero, A. C., and Zoppi, C. C. Exercise increases pancreatic β-cell viability in a model of type 1 diabetes through IL-6 signaling.

Immune cells and oxidative stress in the endotoxin tolerance mouse model

Sepsis is a systemic inflammatory response that can lead to tissue damage and death. In order to increase our understanding of sepsis, experimental models are needed that produce relevant immune and inflammatory responses during a septic event. We describe a lipopolysaccharide tolerance mouse model to characterize the cellular and molecular alterations of immune cells during sepsis. The model presents a typical lipopolysaccharide tolerance pattern in which tolerance is related to decreased production and secretion of cytokines after a subsequent exposure to a lethal dose of lipopolysaccharide. The initial lipopolysaccharide exposure also altered the expression patterns of cytokines and was followed by an 8- and a 1.5-fold increase in the T helper 1 and 2 cell subpopulations. Behavioral data indicate a decrease in spontaneous activity and an increase in body temperature following exposure to lipopolysaccharide. In contrast, tolerant animals maintained production of reactive oxygen species and nitric oxide when terminally challenged by cecal ligation and puncture (CLP). Survival study after CLP showed protection in tolerant compared to naive animals. Spleen mass increased in tolerant animals followed by increases of B lymphocytes and subpopulation Th1 cells. An increase in the number of stem cells was found in spleen and bone marrow. We also showed that administration of spleen or bone marrow cells from tolerant to naive animals transfers the acquired resistance status. In conclusion, lipopolysaccharide tolerance is a natural reprogramming of the immune system that increases the number of immune cells, particularly T helper 1 cells, and does not reduce oxidative stress.

Assessing influence in survival data with a cure fraction and covariates

Diagnostic methods have been an important tool in regression analysis to detect anomalies, such as departures from error assumptions and the presence of outliers and influential observations with the fitted models. Assuming censored data, we considered a classical analysis and Bayesian analysis assuming no informative priors for the parameters of the model with a cure fraction. A Bayesian approach was considered by using Markov Chain Monte Carlo Methods with Metropolis-Hasting algorithms steps to obtain the posterior summaries of interest. Some influence methods, such as the local influence, total local influence of an individual, local influence on predictions and generalized leverage were derived, analyzed and discussed in survival data with a cure fraction and covariates. The relevance of the approach was illustrated with a real data set, where it is shown that, by removing the most influential observations, the decision about which model best fits the data is changed.

Survival and Neuronal Differentiation of Mesenchymal Stem Cells Transplanted into the Rodent Brain Are Dependent upon Microenvironment

Introduction: The successful integration of stem cells in adult brain has become a central issue in modern neuroscience. In this study we sought to test the hypothesis that survival and neurodifferentiation of mesenchymal stem cells (MSCs) may be dependent upon microenvironmental conditions according to the site of implant in the brain. Methods: MSCs were isolated from adult rats and labeled with enhanced-green fluorescent protein (eGFP) lentivirus. A cell suspension was implanted stereotactically into the brain of 50 young rats, into one neurogenic area (hippocampus), and into another nonneurogenic area (striatum). Animals were sacrificed 6 or 12 weeks after surgery, and brains were stained for mature neuronal markers. Cells coexpressing NeuN (neuronal specific nuclear protein) and GFP (green fluorescent protein) were counted stereologically at both targets. Results: The isolated cell population was able to generate neurons positive for microtubule-associated protein 2 (MAP2), neuronal-specific nuclear protein (NeuN), and neurofilament 200 (NF200) in vitro. Electrophysiology confirmed expression of voltage-gated ionic channels. Once implanted into the hippocampus, cells survived for up to 12 weeks, migrated away from the graft, and gave rise to mature neurons able to synthesize neurotransmitters. By contrast, massive cell degeneration was seen in the striatum, with no significant migration. Induction of neuronal differentiation with increased cyclic adenosine monophosphate in the culture medium before implantation favored differentiation in vivo. Conclusions: Our data demonstrated that survival and differentiation of MSCs is strongly dependent upon a permissive microenvironment. Identification of the pro-neurogenic factors present in the hippocampus could subsequently allow for the integration of stem cells into nonpermissive areas of the central nervous system.

A New Mouse Model for Marfan Syndrome Presents Phenotypic Variability Associated with the Genetic Background and Overall Levels of Fbn1 Expression

Marfan syndrome is an autosomal dominant disease of connective tissue caused by mutations in the fibrillin-1 encoding gene FBN1. Patients present cardiovascular, ocular and skeletal manifestations, and although being fully penetrant, MFS is characterized by a wide clinical variability both within and between families. Here we describe a new mouse model of MFS that recapitulates the clinical heterogeneity of the syndrome in humans. Heterozygotes for the mutant Fbn1 allele mg Delta(loxPneo), carrying the same internal deletion of exons 19-24 as the mg Delta mouse model, present defective microfibrillar deposition, emphysema, deterioration of aortic wall and kyphosis. However, the onset of a clinical phenotypes is earlier in the 129/Sv than in C57BL/6 background, indicating the existence of genetic modifiers of MFS between these two mouse strains. In addition, we characterized a wide clinical variability within the 129/Sv congenic heterozygotes, suggesting involvement of epigenetic factors in disease severity. Finally, we show a strong negative correlation between overall levels of Fbn1 expression and the severity of the phenotypes, corroborating the suggested protective role of normal fibrillin-1 in MFS pathogenesis, and supporting the development of therapies based on increasing Fbn1 expression.

Syzygium jambolanum treatment improves survival in lethal sepsis induced in mice

Background: The leaves and the fruits from Syzygium jambolanum DC.(Myrtaceae), a plant known in Brazil as sweet olive or 'jambolao', have been used by native people to treat infectious diseases, diabetes, and stomachache. Since the bactericidal activity of S. jambolanum has been confirmed in vitro, the aim of this work was to evaluate the effect of the prophylactic treatment with S. jambolanum on the in vivo polymicrobial infection induced by cecal ligation and puncture (CLP) in mice. Methods: C57BI/6 mice were treated by the subcutaneous route with a hydroalcoholic extract from fresh leaves of S. jambolanum (HCE). After 6 h, a bacterial infection was induced in the peritoneum using the lethal CLP model. The mice were killed 12 h after the CLP induction to evaluate the cellular influx and local and systemic inflammatory mediators' production. Some animals were maintained alive to evaluate the survival rate. Results: The prophylactic HCE treatment increased the mice survival, the neutrophil migration to infectious site, the spreading ability and the hydrogen peroxide release, but decreased the serum TNF and nitrite. Despite the increased migration and activation of peritoneal cells the HCE treatment did not decrease the number of CFU. The HCE treatment induced a significant decrease on the bone marrow cells number but did not alter the cell number of the spleen and lymph node. Conclusion: We conclude that the treatment with S. jambolanum has a potent prophylactic antiseptic effect that is not associated to a direct microbicidal effect but it is associated to a recruitment of activated neutrophils to the infectious site and to a diminished systemic inflammatory response.

Survival time of random walk in random environment among soft obstacles

We consider a Random Walk in Random Environment (RWRE) moving in an i.i.d. random field of obstacles. When the particle hits an obstacle, it disappears with a positive probability. We obtain quenched and annealed bounds on the tails of the survival time in the general d-dimensional case. We then consider a simplified one-dimensional model (where transition probabilities and obstacles are independent and the RWRE only moves to neighbour sites), and obtain finer results for the tail of the survival time. In addition, we study also the ""mixed"" probability measures (quenched with respect to the obstacles and annealed with respect to the transition probabilities and vice-versa) and give results for tails of the survival time with respect to these probability measures. Further, we apply the same methods to obtain bounds for the tails of hitting times of Branching Random Walks in Random Environment (BRWRE).

Residuals for log-Burr XII regression models in survival analysis

In this paper, we compare three residuals to assess departures from the error assumptions as well as to detect outlying observations in log-Burr XII regression models with censored observations. These residuals can also be used for the log-logistic regression model, which is a special case of the log-Burr XII regression model. For different parameter settings, sample sizes and censoring percentages, various simulation studies are performed and the empirical distribution of each residual is displayed and compared with the standard normal distribution. These studies suggest that the residual analysis usually performed in normal linear regression models can be straightforwardly extended to the modified martingale-type residual in log-Burr XII regression models with censored data.

A log-extended Weibull regression model

A bathtub-shaped failure rate function is very useful in survival analysis and reliability studies. The well-known lifetime distributions do not have this property. For the first time, we propose a location-scale regression model based on the logarithm of an extended Weibull distribution which has the ability to deal with bathtub-shaped failure rate functions. We use the method of maximum likelihood to estimate the model parameters and some inferential procedures are presented. We reanalyze a real data set under the new model and the log-modified Weibull regression model. We perform a model check based on martingale-type residuals and generated envelopes and the statistics AIC and BIC to select appropriate models. (C) 2009 Elsevier B.V. All rights reserved.