Online Survival Analysis Software to Assess the Prognostic Value of Biomarkers Using Transcriptomic Data in Non-Small-Cell Lung Cancer

In the last decade, optimized treatment for non-small cell lung cancer had lead to improved prognosis, but the overall survival is still very short. To further understand the molecular basis of the disease we have to identify biomarkers related to survival. Here we present the development of an online tool suitable for the real-time meta-analysis of published lung cancer microarray datasets to identify biomarkers related to survival. We searched the caBIG, GEO and TCGA repositories to identify samples with published gene expression data and survival information. Univariate and multivariate Cox regression analysis, Kaplan-Meier survival plot with hazard ratio and logrank P value are calculated and plotted in R. The complete analysis tool can be accessed online at: www.kmplot.com/lung. All together 1,715 samples of ten independent datasets were integrated into the system. As a demonstration, we used the tool to validate 21 previously published survival associated biomarkers. Of these, survival was best predicted by CDK1 (p<1E-16), CD24 (p<1E-16) and CADM1 (p = 7E-12) in adenocarcinomas and by CCNE1 (p = 2.3E-09) and VEGF (p = 3.3E-10) in all NSCLC patients. Additional genes significantly correlated to survival include RAD51, CDKN2A, OPN, EZH2, ANXA3, ADAM28 and ERCC1. In summary, we established an integrated database and an online tool capable of uni- and multivariate analysis for in silico validation of new biomarker candidates in non-small cell lung cancer.     

Neural Mechanisms Underlying Breathing Complexity

Breathing is maintained and controlled by a network of automatic neurons in the brainstem that generate respiratory rhythm and receive regulatory inputs. Breathing complexity therefore arises from respiratory central pattern generators modulated by peripheral and supra-spinal inputs. Very little is known on the brainstem neural substrates underlying breathing complexity in humans. We used both experimental and theoretical approaches to decipher these mechanisms in healthy humans and patients with chronic obstructive pulmonary disease (COPD). COPD is the most frequent chronic lung disease in the general population mainly due to tobacco smoke. In patients, airflow obstruction associated with hyperinflation and respiratory muscles weakness are key factors contributing to load-capacity imbalance and hence increased respiratory drive. Unexpectedly, we found that the patients breathed with a higher level of complexity during inspiration and expiration than controls. Using functional magnetic resonance imaging (fMRI), we scanned the brain of the participants to analyze the activity of two small regions involved in respiratory rhythmogenesis, the rostral ventro-lateral (VL) medulla (pre-Bötzinger complex) and the caudal VL pons (parafacial group). fMRI revealed in controls higher activity of the VL medulla suggesting active inspiration, while in patients higher activity of the VL pons suggesting active expiration. COPD patients reactivate the parafacial to sustain ventilation. These findings may be involved in the onset of respiratory failure when the neural network becomes overwhelmed by respiratory overload We show that central neural activity correlates with airflow complexity in healthy subjects and COPD patients, at rest and during inspiratory loading. We finally used a theoretical approach of respiratory rhythmogenesis that reproduces the kernel activity of neurons involved in the automatic breathing. The model reveals how a chaotic activity in neurons can contribute to chaos in airflow and reproduces key experimental fMRI findings.     

Confronting the Paradox of Enrichment to the Metacommunity Perspective

Resource enrichment can potentially destabilize predator-prey dynamics. This phenomenon historically referred as the "paradox of enrichment" has mostly been explored in spatially homogenous environments. However, many predator-prey communities exchange organisms within spatially heterogeneous networks called metacommunities. This heterogeneity can result from uneven distribution of resources among communities and thus can lead to the spreading of local enrichment within metacommunities. Here, we adapted the original Rosenzweig-MacArthur predator-prey model, built to study the paradox of enrichment, to investigate the effect of regional enrichment and of its spatial distribution on predator-prey dynamics in metacommunities. We found that the potential for destabilization was depending on the connectivity among communities and the spatial distribution of enrichment. In one hand, we found that at low dispersal regional enrichment led to the destabilization of predator-prey dynamics. This destabilizing effect was more pronounced when the enrichment was uneven among communities. In the other hand, we found that high dispersal could stabilize the predator-prey dynamics when the enrichment was spatially heterogeneous. Our results illustrate that the destabilizing effect of enrichment can be dampened when the spatial scale of resource enrichment is lower than that of organismss movements (heterogeneous enrichment). From a conservation perspective, our results illustrate that spatial heterogeneity could decrease the regional extinction risk of species involved in specialized trophic interactions. From the perspective of biological control, our results show that the heterogeneous distribution of pest resource could favor or dampen outbreaks of pests and of their natural enemies, depending on the spatial scale of heterogeneity.     

Comparative Outcomes of the Two Types of Sacral Extradural Spinal Meningeal Cysts Using Different Operation Methods: A Prospective Clinical Study

This prospective study compares different clinical characteristics and outcomes of patients with two types of sacral extradural spinal meningeal cysts (SESMC) undergoing different means of surgical excision. Using the relationship between the cysts and spinal nerve roots fibers (SNRF) as seen under microscope, SESMCs were divided into two types: cysts with SNRF known as Tarlov cysts and cysts without. The surgical methods were tailored to the different types of SESMCs. The improved Japanese Orthopedic Association (IJOA) scoring system was used to evaluate preoperative and postoperative neurological function of the patients. Preoperative IJOA scores were 18.5±1.73, and postoperative IJOA scores were 19.6±0.78. The difference between preoperative and postoperative IJOA scores was statistically significant (t = -4.52, p = 0.0001), with a significant improvement in neurological function after surgery. Among the improvements in neurological functions, the most significant was sensation (z=-2.74, p=0.006), followed by bowel/bladder function (z=-2.50, p=0.01). There was a statistically significant association between the types of SESMC and the number (F=12.57, p=0.001) and maximum diameter (F=8.08, p=0.006) of the cysts. SESMC with SNRF are often multiple and small, while cysts without SNRF tend to be solitary and large. We advocate early surgical intervention for symptomatic SESMCs in view of significant clinical improvement postoperatively.     

Small Thaw Ponds: An Unaccounted Source of Methane in the Canadian High Arctic

Thawing permafrost in the Canadian Arctic tundra leads to peat erosion and slumping in narrow and shallow runnel ponds that surround more commonly studied polygonal ponds. Here we compared the methane production between runnel and polygonal ponds using stable isotope ratios, ¹⁴C signatures, and investigated potential methanogenic communities through high-throughput sequencing archaeal 16S rRNA genes. We found that runnel ponds had significantly higher methane and carbon dioxide emissions, produced from a slightly larger fraction of old carbon, compared to polygonal ponds. The methane stable isotopic signature indicated production through acetoclastic methanogenesis, but gene signatures from acetoclastic and hydrogenotrophic methanogenic Archaea were detected in both polygonal and runnel ponds. We conclude that runnel ponds represent a source of methane from potentially older C, and that they contain methanogenic communities able to use diverse sources of carbon, increasing the risk of augmented methane release under a warmer climate.     

Are Frontal Cognitive and Atrophy Patterns Different in PSP and bvFTD? A Comparative Neuropsychological and VBM Study

Progressive supranuclear palsy (PSP) and frontotemporal lobar degeneration (FTD) are two clinicohistological entities that share a severe prefrontal syndrome. To what extent do the cognitive syndrome and the location of the underlying brain atrophy unify or segregate these entities? Here, we examined the clinical and radiological patterns of frontal involvement and the neural bases of the cognitive dysfunctions observed in the Richardson form of PSP and the behavioral variant of FTD (bvFTD). The cognitive profile and grey and white matter volume of PSP (n = 19) and bvFTD (n = 16) patients and control participants (n = 18) were compared using a standard battery of neuropsychological tests and voxel-based morphometry (VBM), respectively. Analyses of correlations between neuropsychological and morphometric data were additionally performed. The severity and qualitative pattern of cognitive dysfunction was globally similar between the two patient groups. Grey matter volume was decreased in widespread frontal areas and in the temporal uncus in bvFTD, while it was decreased in the frontal and temporal lobes as well as in the thalamus in PSP. We also found an unexpected involvement of the frontal rectal gyrus in PSP patients compared to controls. Correlation analyses yielded different results in the two groups, with no area showing significant correlations in PSP patients, while several frontal and some temporal areas did so in bvFTD patients. In spite of minor neuropsychological and morphological differences, this study shows that the patterns of cognitive dysfunction and atrophy are very similar in PSP and bvFTD. However, executive dysfunction in these diseases may stem from partially divergent cortical and subcortical neural circuits.