NovoTTF-100A versus physician's choice chemotherapy in recurrent glioblastoma: A randomised phase III trial of a novel treatment modality.

PURPOSE: NovoTTF-100A is a portable device delivering low-intensity, intermediate frequency electric fields via non-invasive, transducer arrays. Tumour Treatment Fields (TTF), a completely new therapeutic modality in cancer treatment, physically interfere with cell division. METHODS: Phase III trial of chemotherapy-free treatment of NovoTTF (20-24h/day) versus active chemotherapy in the treatment of patients with recurrent glioblastoma. Primary end-point was improvement of overall survival. RESULTS: Patients (median age 54years (range 23-80), Karnofsky performance status 80% (range 50-100) were randomised to TTF alone (n=120) or active chemotherapy control (n=117). Number of prior treatments was two (range 1-6). Median survival was 6.6 versus 6.0months (hazard ratio 0.86 [95% CI 0.66-1.12]; p=0.27), 1-year survival rate was 20% and 20%, progression-free survival rate at 6months was 21.4% and 15.1% (p=0.13), respectively in TTF and active control patients. Responses were more common in the TTF arm (14% versus 9.6%, p=0.19). The TTF-related adverse events were mild (14%) to moderate (2%) skin rash beneath the transducer arrays. Severe adverse events occurred in 6% and 16% (p=0.022) of patients treated with TTF and chemotherapy, respectively. Quality of life analyses favoured TTF therapy in most domains. CONCLUSIONS: This is the first controlled trial evaluating an entirely novel cancer treatment modality delivering electric fields rather than chemotherapy. No improvement in overall survival was demonstrated, however efficacy and activity with this chemotherapy-free treatment device appears comparable to chemotherapy regimens that are commonly used for recurrent glioblastoma. Toxicity and quality of life clearly favoured TTF.

Recurrent idiopathic neuroretinitis: natural history and effect of treatment.

BACKGROUND: Previous reports have emphasized the self-limited nature of idiopathic neuroretinitis. There is less information about a subgroup of patients who suffer recurrent episodes with worse visual outcome. We sought to better characterize the clinical features of recurrent idiopathic neuroretinitis including the effects of immunosuppressive treatment. METHODS: Retrospective chart review of neuroretinitis patients from a single institution from 1983 to 2008. Inclusion criteria included two or more episodes of acute visual loss with disc oedema and macular exudates in a star pattern. Cases due to a specific infectious or inflammatory aetiology were excluded. RESULTS: Forty-one patients were included with an average follow up of 67 months. Median age at the time of the first episode was 28 years (range 10-54 years). Attacks were bilateral sequential in 34 patients (83%). We documented a total of 147 episodes in 75 eyes with an average of 3.6 attacks per patient. The average interval between attacks was 3 years. Visual field loss had a nerve fibre bundle pattern in most cases. Only 36% of eyes retained 6/12 or better visual acuity and greater than two-thirds of their visual field. Long-term immunosuppressive treatment in 13 patients decreased the attack rate by 72%. CONCLUSIONS: Recurrent idiopathic neuroretinitis typically affects young adults, with no gender preference. Recovery is limited and visual loss is cumulative with repeated attacks, often resulting in severe permanent visual loss. Immunosuppressive treatment appears to lessen the attack frequency.

Unconditioned responses and functional fear networks in human classical conditioning.

Human imaging studies examining fear conditioning have mainly focused on the neural responses to conditioned cues. In contrast, the neural basis of the unconditioned response and the mechanisms by which fear modulates inter-regional functional coupling have received limited attention. We examined the neural responses to an unconditioned stimulus using a partial-reinforcement fear conditioning paradigm and functional MRI. The analysis focused on: (1) the effects of an unconditioned stimulus (an electric shock) that was either expected and actually delivered, or expected but not delivered, and (2) on how related brain activity changed across conditioning trials, and (3) how shock expectation influenced inter-regional coupling within the fear network. We found that: (1) the delivery of the shock engaged the red nucleus, amygdale, dorsal striatum, insula, somatosensory and cingulate cortices, (2) when the shock was expected but not delivered, only the red nucleus, the anterior insular and dorsal anterior cingulate cortices showed activity increases that were sustained across trials, and (3) psycho-physiological interaction analysis demonstrated that fear led to increased red nucleus coupling to insula but decreased hippocampus coupling to the red nucleus, thalamus and cerebellum. The hippocampus and the anterior insula may serve as hubs facilitating the switch between engagement of a defensive immediate fear network and a resting network.

Genome-wide association study of recurrent major depressive disorder in two European case-control cohorts.

Major depressive disorder (MDD) is a highly prevalent disorder with substantial heritability. Heritability has been shown to be substantial and higher in the variant of MDD characterized by recurrent episodes of depression. Genetic studies have thus far failed to identify clear and consistent evidence of genetic risk factors for MDD. We conducted a genome-wide association study (GWAS) in two independent datasets. The first GWAS was performed on 1022 recurrent MDD patients and 1000 controls genotyped on the Illumina 550 platform. The second was conducted on 492 recurrent MDD patients and 1052 controls selected from a population-based collection, genotyped on the Affymetrix 5.0 platform. Neither GWAS identified any SNP that achieved GWAS significance. We obtained imputed genotypes at the Illumina loci for the individuals genotyped on the Affymetrix platform, and performed a meta-analysis of the two GWASs for this common set of approximately half a million SNPs. The meta-analysis did not yield genome-wide significant results either. The results from our study suggest that SNPs with substantial odds ratio are unlikely to exist for MDD, at least in our datasets and among the relatively common SNPs genotyped or tagged by the half-million-loci arrays. Meta-analysis of larger datasets is warranted to identify SNPs with smaller effects or with rarer allele frequencies that contribute to the risk of MDD.

Repeat Gamma Knife surgery for recurrent trigeminal neuralgia: long-term outcomes and systematic review.

Object The purpose of this study was to establish the safety and efficacy of repeat Gamma Knife surgery (GKS) for recurrent trigeminal neuralgia (TN). Methods Using the prospective database of TN patients treated with GKS in Timone University Hospital (Marseille, France), data were analyzed for 737 patients undergoing GKS for TN Type 1 from July 1992 to November 2010. Among the 497 patients with initial pain cessation, 34.4% (157/456 with ≥ 1-year follow-up) experienced at least 1 recurrence. Thirteen patients (1.8%) were considered for a second GKS, proposed only if the patients had good and prolonged initial pain cessation after the first GKS, with no other treatment alternative at the moment of recurrence. As for the first GKS, a single 4-mm isocenter was positioned in the cisternal portion of the trigeminal nerve at a median distance of 7.6 mm (range 4-14 mm) anterior to the emergence of the nerve (retrogasserian target). A median maximum dose of 90 Gy (range 70-90 Gy) was delivered. Data for 9 patients with at least 1-year followup were analyzed. A systematic review of literature was also performed, and results are compared with those of the Marseille study. Results The median time to retreatment in the Marseille study was 72 months (range 12-125 months) and in the literature it was 17 months (range 3-146 months). In the Marseille study, the median follow-up period was 33.9 months (range 12-96 months), and 8 of 9 patients (88.9%) had initial pain cessation with a median of 6.5 days (range 1-180 days). The actuarial rate for new hypesthesia was 33.3% at 6 months and 50% at 1 year, which remained stable for 7 years. The actuarial probabilities of maintaining pain relief without medication at 6 months and 1 year were 100% and 75%, respectively, and remained stable for 7 years. The systematic review analyzed 20 peer-reviewed studies reporting outcomes for repeat GKS for recurrent TN, with a total of 626 patients. Both the selection of the cases for retreatment and the way of reporting outcomes vary widely among studies, with a median rate for initial pain cessation of 88% (range 60%-100%) and for new hypesthesia of 33% (range 11%-80%). Conclusions Results from the Marseille study raise the question of surgical alternatives after failed GKS for TN. The rates of initial pain cessation and recurrence seem comparable to, or even better than, those of the first GKS, according to different studies, but toxicity is much higher, both in the Marseille study and in the published data. Neither the Marseille study data nor literature data answer the 3 cardinal questions regarding repeat radiosurgery in recurrent TN: which patients to retreat, which target is optimal, and which dose to use.

Synchronous versus asynchronous modeling of gene regulatory networks.

MOTIVATION: In silico modeling of gene regulatory networks has gained some momentum recently due to increased interest in analyzing the dynamics of biological systems. This has been further facilitated by the increasing availability of experimental data on gene-gene, protein-protein and gene-protein interactions. The two dynamical properties that are often experimentally testable are perturbations and stable steady states. Although a lot of work has been done on the identification of steady states, not much work has been reported on in silico modeling of cellular differentiation processes. RESULTS: In this manuscript, we provide algorithms based on reduced ordered binary decision diagrams (ROBDDs) for Boolean modeling of gene regulatory networks. Algorithms for synchronous and asynchronous transition models have been proposed and their corresponding computational properties have been analyzed. These algorithms allow users to compute cyclic attractors of large networks that are currently not feasible using existing software. Hereby we provide a framework to analyze the effect of multiple gene perturbation protocols, and their effect on cell differentiation processes. These algorithms were validated on the T-helper model showing the correct steady state identification and Th1-Th2 cellular differentiation process. AVAILABILITY: The software binaries for Windows and Linux platforms can be downloaded from http://si2.epfl.ch/~garg/genysis.html.

Future trypanosomatid phylogenies: refined homologies, supertrees and networks

There has been good progress in inferring the evolutionary relationships within trypanosomes from DNA data as until relatively recently, many relationships have remained rather speculative. Ongoing molecular studies have provided data that have adequately shown Trypanosoma to be monophyletic and, rather surprisingly, that there are sharply contrasting levels of genetic variation within and between the major trypanosomatid groups. There are still, however, areas of research that could benefit from further development and resolution that broadly fall upon three questions. Are the current statements of evolutionary homology within ribosomal small sub-unit genes in need of refinement? Can the published phylograms be expanded upon to form `supertrees' depicting further relationships? Does a bifurcating tree structure impose an untenable dogma upon trypanosomatid phylogeny where hybridisation or reticulate evolutionary steps have played a part? This article briefly addresses these three questions and, in so doing, hopes to stimulate further interest in the molecular evolution of the group.

Structural Analysis of Networks

Network analysis naturally relies on graph theory and, more particularly, on the use of node and edge metrics to identify the salient properties in graphs. When building visual maps of networks, these metrics are turned into useful visual cues or are used interactively to filter out parts of a graph while querying it, for instance. Over the years, analysts from different application domains have designed metrics to serve specific needs. Network science is an inherently cross-disciplinary field, which leads to the publication of metrics with similar goals; different names and descriptions of their analytics often mask the similarity between two metrics that originated in different fields. Here, we study a set of graph metrics and compare their relative values and behaviors in an effort to survey their potential contributions to the spatial analysis of networks.

Dynamic simulation of regulatory networks using SQUAD.

BACKGROUND: The ambition of most molecular biologists is the understanding of the intricate network of molecular interactions that control biological systems. As scientists uncover the components and the connectivity of these networks, it becomes possible to study their dynamical behavior as a whole and discover what is the specific role of each of their components. Since the behavior of a network is by no means intuitive, it becomes necessary to use computational models to understand its behavior and to be able to make predictions about it. Unfortunately, most current computational models describe small networks due to the scarcity of kinetic data available. To overcome this problem, we previously published a methodology to convert a signaling network into a dynamical system, even in the total absence of kinetic information. In this paper we present a software implementation of such methodology. RESULTS: We developed SQUAD, a software for the dynamic simulation of signaling networks using the standardized qualitative dynamical systems approach. SQUAD converts the network into a discrete dynamical system, and it uses a binary decision diagram algorithm to identify all the steady states of the system. Then, the software creates a continuous dynamical system and localizes its steady states which are located near the steady states of the discrete system. The software permits to make simulations on the continuous system, allowing for the modification of several parameters. Importantly, SQUAD includes a framework for perturbing networks in a manner similar to what is performed in experimental laboratory protocols, for example by activating receptors or knocking out molecular components. Using this software we have been able to successfully reproduce the behavior of the regulatory network implicated in T-helper cell differentiation. CONCLUSION: The simulation of regulatory networks aims at predicting the behavior of a whole system when subject to stimuli, such as drugs, or determine the role of specific components within the network. The predictions can then be used to interpret and/or drive laboratory experiments. SQUAD provides a user-friendly graphical interface, accessible to both computational and experimental biologists for the fast qualitative simulation of large regulatory networks for which kinetic data is not necessarily available.

Coevolutionary networks: a novel approach to understanding the relationships of humans with the infectious agents

Human organism is interpenetrated by the world of microorganisms, from the conception until the death. This interpenetration involves different levels of interactions between the partners including trophic exchanges, bi-directional cell signaling and gene activation, besides genetic and epigenetic phenomena, and tends towards mutual adaptation and coevolution. Since these processes are critical for the survival of individuals and species, they rely on the existence of a complex organization of adaptive systems aiming at two apparently conflicting purposes: the maintenance of the internal coherence of each partner, and a mutually advantageous coexistence and progressive adaptation between them. Humans possess three adaptive systems: the nervous, the endocrine and the immune system, each internally organized into subsystems functionally connected by intraconnections, to maintain the internal coherence of the system. The three adaptive systems aim at the maintenance of the internal coherence of the organism and are functionally linked by interconnections, in such way that what happens to one is immediately sensed by the others. The different communities of infectious agents that live within the organism are also organized into functional networks. The members of each community are linked by intraconnections, represented by the mutual trophic, metabolic and other influences, while the different infectious communities affect each other through interconnections. Furthermore, by means of its adaptive systems, the organism influences and is influenced by the microbial communities through the existence of transconnections. It is proposed that these highly complex and dynamic networks, involving gene exchange and epigenetic phenomena, represent major coevolutionary forces for humans and microorganisms.

Information Mobility: Information Dissemination in Mobile Networks

En el nostre projecte, considerem un escenari urbà o interurbà on persones amb dispositius mòbils (smartphones) o vehicles equipats amb interfícies de comunicació, estan interessats en compartir fitxers entre ells o descarregar-los al creuar Punts d’Accés (APs) propers a la carretera. Estudiem la possibilitat d’utilizar la cooperació en les trobades casuals entre nodes per augmentar la velocitat de descàrrega global. Amb aquest objectiu, plantejem algoritmes per a la selecció de quins paquets, per a quins destins i quins transportistes s’escullen en cada moment. Mitjançant extenses simulacions, mostrem com les cooperacions carry&forward dels nodes augmenten significativament la velocitat de descàrrega dels usuaris, i com aquest resultat es manté per a diversos patrons de mobilitat, col•locacions d'AP i càrregues de la xarxa. Per altra banda, aparells com els smartphones, on la targeta de WiFi està encesa contínuament, consumeixen l'energia de la bateria en poques hores. En molts escenaris, una targeta WiFi sempre activa és poc útil, perque sovint no hi ha necessitat de transmissió o recepció. Aquest fet es veu agreujat en les Delay Tolerant Networks (DTN), on els nodes intercanvien dades quan es creuen i en tenen l’oportunitat. Les tècniques de gestió de l’estalvi d’energia permeten extendre la duració de les bateries. El nostre projecte analitza els avantatges i inconvenients que apareixen quan els nodes apaguen períodicament la seva targeta wireless per a estalviar energia en escenaris DTN. Els nostres resultats mostren les condicions en que un node pot desconnectar la bateria sense afectar la probabilitat de contacte amb altres nodes, i les condicions en que aquesta disminueix. Per exemple, es demostra que la vida del node pot ser duplicada mantenint la probabilitat de contacte a 1. I que aquesta disminueix ràpidament en intentar augmentar més la vida útil.