Radioimmunotherapy confers long-term survival to lymphoma patients with acceptable toxicity: registry analysis by the international radioimmunotherapy network.

The Radioimmunotherapy Network (RIT-N) is a Web-based, international registry collecting long-term observational data about radioimmunotherapy-treated patients with malignant lymphoma outside randomized clinical studies. The RIT-N collects unbiased data on treatment indications, disease stages, patients' conditions, lymphoma subtypes, and hematologic side effects of radioimmunotherapy treatment. Methods: RIT-N is located at the University of Gottingen, Germany, and collected data from 14 countries. Data were entered by investigators into a Web-based central database managed by an independent clinical research organization. Results: Patients (1,075) were enrolled from December 2006 until November 2009, and 467 patients with an observation time of at least 12 mo were included in the following analysis. Diagnoses were as follows: 58% follicular lymphoma and 42% other B-cell lymphomas. The mean overall survival was 28 mo for follicular lymphoma and 26 mo for other lymphoma subtypes. Hematotoxicity was mild for hemoglobin (World Health Organization grade II), with a median nadir of 10 g/dL, but severe (World Health Organization grade III) for platelets and leukocytes, with a median nadir of 7,000/mu L and 2.2/mu L, respectively. Conclusion: Clinical usage of radioimmunotherapy differs from the labeled indications and can be assessed by this registry, enabling analyses of outcome and toxicity data beyond clinical trials. This analysis proves that radioimmunotherapy in follicular lymphoma and other lymphoma subtypes is a safe and efficient treatment option.

Analysis, modelling and classification of geospatial data using machine learning

The research considers the problem of spatial data classification using machine learning algorithms: probabilistic neural networks (PNN) and support vector machines (SVM). As a benchmark model simple k-nearest neighbor algorithm is considered. PNN is a neural network reformulation of well known nonparametric principles of probability density modeling using kernel density estimator and Bayesian optimal or maximum a posteriori decision rules. PNN is well suited to problems where not only predictions but also quantification of accuracy and integration of prior information are necessary. An important property of PNN is that they can be easily used in decision support systems dealing with problems of automatic classification. Support vector machine is an implementation of the principles of statistical learning theory for the classification tasks. Recently they were successfully applied for different environmental topics: classification of soil types and hydro-geological units, optimization of monitoring networks, susceptibility mapping of natural hazards. In the present paper both simulated and real data case studies (low and high dimensional) are considered. The main attention is paid to the detection and learning of spatial patterns by the algorithms applied.

SBML qualitative models: a model representation format and infrastructure to foster interactions between qualitative modelling formalisms and tools.

BACKGROUND: Qualitative frameworks, especially those based on the logical discrete formalism, are increasingly used to model regulatory and signalling networks. A major advantage of these frameworks is that they do not require precise quantitative data, and that they are well-suited for studies of large networks. While numerous groups have developed specific computational tools that provide original methods to analyse qualitative models, a standard format to exchange qualitative models has been missing. RESULTS: We present the Systems Biology Markup Language (SBML) Qualitative Models Package ("qual"), an extension of the SBML Level 3 standard designed for computer representation of qualitative models of biological networks. We demonstrate the interoperability of models via SBML qual through the analysis of a specific signalling network by three independent software tools. Furthermore, the collective effort to define the SBML qual format paved the way for the development of LogicalModel, an open-source model library, which will facilitate the adoption of the format as well as the collaborative development of algorithms to analyse qualitative models. CONCLUSIONS: SBML qual allows the exchange of qualitative models among a number of complementary software tools. SBML qual has the potential to promote collaborative work on the development of novel computational approaches, as well as on the specification and the analysis of comprehensive qualitative models of regulatory and signalling networks.

Validation of network communicability metrics for the analysis of brain structural networks.

Computational network analysis provides new methods to analyze the brain's structural organization based on diffusion imaging tractography data. Networks are characterized by global and local metrics that have recently given promising insights into diagnosis and the further understanding of psychiatric and neurologic disorders. Most of these metrics are based on the idea that information in a network flows along the shortest paths. In contrast to this notion, communicability is a broader measure of connectivity which assumes that information could flow along all possible paths between two nodes. In our work, the features of network metrics related to communicability were explored for the first time in the healthy structural brain network. In addition, the sensitivity of such metrics was analysed using simulated lesions to specific nodes and network connections. Results showed advantages of communicability over conventional metrics in detecting densely connected nodes as well as subsets of nodes vulnerable to lesions. In addition, communicability centrality was shown to be widely affected by the lesions and the changes were negatively correlated with the distance from lesion site. In summary, our analysis suggests that communicability metrics that may provide an insight into the integrative properties of the structural brain network and that these metrics may be useful for the analysis of brain networks in the presence of lesions. Nevertheless, the interpretation of communicability is not straightforward; hence these metrics should be used as a supplement to the more standard connectivity network metrics.

A regulatory network for the efficient control of transgene expression.

BACKGROUND: Expression of heterologous genes in mammalian cells or organisms for therapeutic or experimental purposes often requires tight control of transgene expression. Specifically, the following criteria should be met: no background gene activity in the off-state, high gene expression in the on-state, regulated expression over an extended period, and multiple switching between on- and off-states. METHODS: Here, we describe a genetic switch system for controlled transgene transcription using chimeric repressor and activator proteins functioning in a novel regulatory network. In the off-state, the target transgene is actively silenced by a chimeric protein consisting of multimerized eukaryotic transcriptional repression domains fused to the DNA-binding tetracycline repressor. In the on-state, the inducer drug doxycycline affects both the derepression of the target gene promoter and activation by the GAL4-VP16 transactivator, which in turn is under the control of an autoregulatory feedback loop. RESULTS: The hallmark of this new system is the efficient transgene silencing in the off-state, as demonstrated by the tightly controlled expression of the highly cytotoxic diphtheria toxin A gene. Addition of the inducer drug allows robust activation of transgene expression. In stably transfected cells, this control is still observed after months of repeated cycling between the repressed and activated states of the target genes. CONCLUSIONS: This system permits tight long-term regulation when stably introduced into cell lines. The underlying principles of this network system should have general applications in biotechnology and gene therapy.

Candida species distribution and antifungal susceptibility testing according to European Committee on Antimicrobial Susceptibility Testing and new vs. old Clinical and Laboratory Standards Institute clinical breakpoints: a 6-year prospective candidaemia survey from the fungal infection network of Switzerland.

We analyzed the species distribution of Candida blood isolates (CBIs), prospectively collected between 2004 and 2009 within FUNGINOS, and compared their antifungal susceptibility according to clinical breakpoints defined by the European Committee on Antimicrobial Susceptibility Testing (EUCAST) in 2013, and the Clinical and Laboratory Standards Institute (CLSI) in 2008 (old CLSI breakpoints) and 2012 (new CLSI breakpoints). CBIs were tested for susceptiblity to fluconazole, voriconazole and caspofungin by microtitre broth dilution (Sensititre(®) YeastOne? test panel). Of 1090 CBIs, 675 (61.9%) were C. albicans, 191 (17.5%) C. glabrata, 64 (5.9%) C. tropicalis, 59 (5.4%) C. parapsilosis, 33 (3%) C. dubliniensis, 22 (2%) C. krusei and 46 (4.2%) rare Candida species. Independently of the breakpoints applied, C. albicans was almost uniformly (>98%) susceptible to all three antifungal agents. In contrast, the proportions of fluconazole- and voriconazole-susceptible C. tropicalis and F-susceptible C. parapsilosis were lower according to EUCAST/new CLSI breakpoints than to the old CLSI breakpoints. For caspofungin, non-susceptibility occurred mainly in C. krusei (63.3%) and C. glabrata (9.4%). Nine isolates (five C. tropicalis, three C. albicans and one C. parapsilosis) were cross-resistant to azoles according to EUCAST breakpoints, compared with three isolates (two C. albicans and one C. tropicalis) according to new and two (2 C. albicans) according to old CLSI breakpoints. Four species (C. albicans, C. glabrata, C. tropicalis and C. parapsilosis) represented >90% of all CBIs. In vitro resistance to fluconazole, voriconazole and caspofungin was rare among C. albicans, but an increase of non-susceptibile isolates was observed among C. tropicalis/C. parapsilosis for the azoles and C. glabrata/C. krusei for caspofungin according to EUCAST and new CLSI breakpoints compared with old CLSI breakpoints.

Endoleak and in-stent thrombus detection with CT angiography in a thoracic aortic aneurysm phantom at different tube energies using filtered back projection and iterative algorithms.

PURPOSE: To determine the lower limit of dose reduction with hybrid and fully iterative reconstruction algorithms in detection of endoleaks and in-stent thrombus of thoracic aorta with computed tomographic (CT) angiography by applying protocols with different tube energies and automated tube current modulation. MATERIALS AND METHODS: The calcification insert of an anthropomorphic cardiac phantom was replaced with an aortic aneurysm model containing a stent, simulated endoleaks, and an intraluminal thrombus. CT was performed at tube energies of 120, 100, and 80 kVp with incrementally increasing noise indexes (NIs) of 16, 25, 34, 43, 52, 61, and 70 and a 2.5-mm section thickness. NI directly controls radiation exposure; a higher NI allows for greater image noise and decreases radiation. Images were reconstructed with filtered back projection (FBP) and hybrid and fully iterative algorithms. Five radiologists independently analyzed lesion conspicuity to assess sensitivity and specificity. Mean attenuation (in Hounsfield units) and standard deviation were measured in the aorta to calculate signal-to-noise ratio (SNR). Attenuation and SNR of different protocols and algorithms were analyzed with analysis of variance or Welch test depending on data distribution. RESULTS: Both sensitivity and specificity were 100% for simulated lesions on images with 2.5-mm section thickness and an NI of 25 (3.45 mGy), 34 (1.83 mGy), or 43 (1.16 mGy) at 120 kVp; an NI of 34 (1.98 mGy), 43 (1.23 mGy), or 61 (0.61 mGy) at 100 kVp; and an NI of 43 (1.46 mGy) or 70 (0.54 mGy) at 80 kVp. SNR values showed similar results. With the fully iterative algorithm, mean attenuation of the aorta decreased significantly in reduced-dose protocols in comparison with control protocols at 100 kVp (311 HU at 16 NI vs 290 HU at 70 NI, P ≤ .0011) and 80 kVp (400 HU at 16 NI vs 369 HU at 70 NI, P ≤ .0007). CONCLUSION: Endoleaks and in-stent thrombus of thoracic aorta were detectable to 1.46 mGy (80 kVp) with FBP, 1.23 mGy (100 kVp) with the hybrid algorithm, and 0.54 mGy (80 kVp) with the fully iterative algorithm.

System-level Support for Mobile Ad hoc Communications: an Algorithmic & Practical Approach

A mobile ad hoc network (MANET) is a decentralized and infrastructure-less network. This thesis aims to provide support at the system-level for developers of applications or protocols in such networks. To do this, we propose contributions in both the algorithmic realm and in the practical realm. In the algorithmic realm, we contribute to the field by proposing different context-aware broadcast and multicast algorithms in MANETs, namely six-shot broadcast, six-shot multicast, PLAN-B and ageneric algorithmic approach to optimize the power consumption of existing algorithms. For each algorithm we propose, we compare it to existing algorithms that are either probabilistic or context-aware, and then we evaluate their performance based on simulations. We demonstrate that in some cases, context-aware information, such as location or signal-strength, can improve the effciency. In the practical realm, we propose a testbed framework, namely ManetLab, to implement and to deploy MANET-specific protocols, and to evaluate their performance. This testbed framework aims to increase the accuracy of performance evaluation compared to simulations, while keeping the ease of use offered by the simulators to reproduce a performance evaluation. By evaluating the performance of different probabilistic algorithms with ManetLab, we observe that both simulations and testbeds should be used in a complementary way. In addition to the above original contributions, we also provide two surveys about system-level support for ad hoc communications in order to establish a state of the art. The first is about existing broadcast algorithms and the second is about existing middleware solutions and the way they deal with privacy and especially with location privacy. - Un réseau mobile ad hoc (MANET) est un réseau avec une architecture décentralisée et sans infrastructure. Cette thèse vise à fournir un support adéquat, au niveau système, aux développeurs d'applications ou de protocoles dans de tels réseaux. Dans ce but, nous proposons des contributions à la fois dans le domaine de l'algorithmique et dans celui de la pratique. Nous contribuons au domaine algorithmique en proposant différents algorithmes de diffusion dans les MANETs, algorithmes qui sont sensibles au contexte, à savoir six-shot broadcast,six-shot multicast, PLAN-B ainsi qu'une approche générique permettant d'optimiser la consommation d'énergie de ces algorithmes. Pour chaque algorithme que nous proposons, nous le comparons à des algorithmes existants qui sont soit probabilistes, soit sensibles au contexte, puis nous évaluons leurs performances sur la base de simulations. Nous montrons que, dans certains cas, des informations liées au contexte, telles que la localisation ou l'intensité du signal, peuvent améliorer l'efficience de ces algorithmes. Sur le plan pratique, nous proposons une plateforme logicielle pour la création de bancs d'essai, intitulé ManetLab, permettant d'implémenter, et de déployer des protocoles spécifiques aux MANETs, de sorte à évaluer leur performance. Cet outil logiciel vise à accroître la précision desévaluations de performance comparativement à celles fournies par des simulations, tout en conservant la facilité d'utilisation offerte par les simulateurs pour reproduire uneévaluation de performance. En évaluant les performances de différents algorithmes probabilistes avec ManetLab, nous observons que simulateurs et bancs d'essai doivent être utilisés de manière complémentaire. En plus de ces contributions principales, nous fournissons également deux états de l'art au sujet du support nécessaire pour les communications ad hoc. Le premier porte sur les algorithmes de diffusion existants et le second sur les solutions de type middleware existantes et la façon dont elles traitent de la confidentialité, en particulier celle de la localisation.

Resting-brain functional connectivity predicted by analytic measures of network communication.

The complex relationship between structural and functional connectivity, as measured by noninvasive imaging of the human brain, poses many unresolved challenges and open questions. Here, we apply analytic measures of network communication to the structural connectivity of the human brain and explore the capacity of these measures to predict resting-state functional connectivity across three independently acquired datasets. We focus on the layout of shortest paths across the network and on two communication measures-search information and path transitivity-which account for how these paths are embedded in the rest of the network. Search information is an existing measure of information needed to access or trace shortest paths; we introduce path transitivity to measure the density of local detours along the shortest path. We find that both search information and path transitivity predict the strength of functional connectivity among both connected and unconnected node pairs. They do so at levels that match or significantly exceed path length measures, Euclidean distance, as well as computational models of neural dynamics. This capacity suggests that dynamic couplings due to interactions among neural elements in brain networks are substantially influenced by the broader network context adjacent to the shortest communication pathways.

Citrus fruit and cancer risk in a network of case-control studies.

BACKGROUND: Citrus fruit has shown a favorable effect against various cancers. To better understand their role in cancer risk, we analyzed data from a series of case-control studies conducted in Italy and Switzerland. PATIENTS AND METHODS: The studies included 955 patients with oral and pharyngeal cancer, 395 with esophageal, 999 with stomach, 3,634 with large bowel, 527 with laryngeal, 2,900 with breast, 454 with endometrial, 1,031 with ovarian, 1,294 with prostate, and 767 with renal cell cancer. All cancers were incident and histologically confirmed. Controls were admitted to the same network of hospitals for acute, nonneoplastic conditions. Odds ratios (OR) were estimated by multiple logistic regression models, including terms for major identified confounding factors for each cancer site, and energy intake. RESULTS: The ORs for the highest versus lowest category of citrus fruit consumption were 0.47 (95% confidence interval, CI, 0.36-0.61) for oral and pharyngeal, 0.42 (95% CI, 0.25-0.70) for esophageal, 0.69 (95% CI, 0.52-0.92) for stomach, 0.82 (95% CI, 0.72-0.93) for colorectal, and 0.55 (95% CI, 0.37-0.83) for laryngeal cancer. No consistent association was found with breast, endometrial, ovarian, prostate, and renal cell cancer. CONCLUSIONS: Our findings indicate that citrus fruit has a protective role against cancers of the digestive and upper respiratory tract.

Endocytic and secretory traffic in Arabidopsis merge in the trans-Golgi network/early endosome, an independent and highly dynamic organelle.

Plants constantly adjust their repertoire of plasma membrane proteins that mediates transduction of environmental and developmental signals as well as transport of ions, nutrients, and hormones. The importance of regulated secretory and endocytic trafficking is becoming increasingly clear; however, our knowledge of the compartments and molecular machinery involved is still fragmentary. We used immunogold electron microscopy and confocal laser scanning microscopy to trace the route of cargo molecules, including the BRASSINOSTEROID INSENSITIVE1 receptor and the REQUIRES HIGH BORON1 boron exporter, throughout the plant endomembrane system. Our results provide evidence that both endocytic and secretory cargo pass through the trans-Golgi network/early endosome (TGN/EE) and demonstrate that cargo in late endosomes/multivesicular bodies is destined for vacuolar degradation. Moreover, using spinning disc microscopy, we show that TGN/EEs move independently and are only transiently associated with an individual Golgi stack.

Outcome and prognostic factors in olfactory neuroblastoma: a rare cancer network study.

Purpose: To assess the outcome in patients with olfactory neuroblastoma (ONB). Methods and Materials: Seventy-seven patients treated for nonmetastatic ONB between 1971 and 2004 were included. According to Kadish classification, there were 11 patients with Stage A, 29 with Stage B, and 37 with Stage C. T-classification included 9 patients with T1, 26 with T2, 16 with T3, 15 with T4a, and 11 with T4b tumors. Sixty-eight patients presented with N0 (88%) disease. Results: Most of the patients (n = 56, 73 %) benefited from surgery (S), and total excision was possible in 44 patients (R0 in 32, R1 in 13, R2 in 11). All but five patients benefited from RT, and chemotherapy was given in 21(27%). Median follow-up period was 72 months (range, 6-315). The 5-year overall survival (OS), disease-free survival (DES), locoregional control, and local control were 64%, 57%, 62%, and 70%, respectively. In univariate analyses, favorable factors were Kadish A or B disease, T1 T3 tumors, no nodal involvement, curative surgery, R0/R1 resection, and RT-dose 54 Gy or higher. Multivariate analysis revealed that the best independent factors predicting the outcome were T1 T3, N0, R0/R1 resection, and total RT dose (54 Gy or higher). Conclusion: In this multicenter retrospective study, patients with ONB treated with R0 or R1 surgical resection followed by at least 54-Gy postoperative RT had the best outcome. Novel strategies including concomitant chemotherapy and/or higher dose RT should be prospectively investigated in this rare disease for which local failure remains a problem.

Early stage primary bone lymphoma - a retrospective, multicenter rare cancer network (rcn) study

Purpose: Primary bone lymphoma (PBL) accounts for less than 1% of all malignant lymphomas, and 4-5% of all extra-nodal lymphomas. In this study, the disease profile, outcome, and prognostic factors were assessed in patients with stage I and II PBL.Patients and Methods: Thirteen Rare Cancer Network (RCN) institutions enrolled 116 consecutive patients with PBL treated between 1987 and 2008 in this study. Inclusion criteria were age > 16 years, stage I and II, minimum 6 months follow-up and a biopsy-proven confirmation of non-Hodgkin's lymphoma (NHL). Eighty-seven patients underwent chemoradiotherapy (CXRT), 15 radiotherapy (RT) without (13) or with (2) surgery, 14 chemotherapy (CXT) without (9) or with (5) surgery. Median RT dose was 40 Gy (range: 4-60). The median number of CXT cycles was 6 (range: 2-8). Median follow-up was 41 months (range: 6-242).Results: The overall response rate at the end of treatment was 91% (CR 74%, PR 17%). Local recurrence or progression was observed in 12 (10%) patients, and systemic recurrence in 17 (15%). Causes of death included disease progression in 21, unrelated in 5, CXT-related toxicity in 1, and second primary cancer in 2 patients. The 5-yr overall survival (OS), lymphoma-specific survival (LSS), and local control (LC) were 76%, 78% and 92%, respectively. In univariate analyses (log-rank test), favorable prognostic factors for OS were age <50 years (P=0.008), international prognostic index (IPI) score ≤1 (P=0.009), high grade histology (P=0.04), CXRT (P=0.05), CXT (P=0,0004), complete response (CR) (P<0.0001), number of CXT cycles ( ≥6 ) (P=0.01), and RT dose > 40 Gy (P=0.005). All above-mentioned parameters were also significant for LSS except for age and number of chemotherapy cycles. For LC, only CR and stage I were favorable factors. In multivariate analysis, IPI score, RT dose, complete response, and chemotherapy were independently influencing the outcome (OS and LSS). Complete response at the end of treatment was the only predicting factor for LC. Six patients developed grade 3 or more toxicities, according to Common Terminology Criteria for Adverse Events (CTCAE) V3.0.Conclusion: This large multicenter study confirms the relatively good prognosis of early stage PBL treated with combined CXRT. Local control was excellent, while systemic failures were rare. An adequate dose of RT (40 Gy or more) and complete CXT regime (≥ 6 cycles) were associated with better outcome.