Active learning methods for remote sensing image classification

In this paper, we propose two active learning algorithms for semiautomatic definition of training samples in remote sensing image classification. Based on predefined heuristics, the classifier ranks the unlabeled pixels and automatically chooses those that are considered the most valuable for its improvement. Once the pixels have been selected, the analyst labels them manually and the process is iterated. Starting with a small and nonoptimal training set, the model itself builds the optimal set of samples which minimizes the classification error. We have applied the proposed algorithms to a variety of remote sensing data, including very high resolution and hyperspectral images, using support vector machines. Experimental results confirm the consistency of the methods. The required number of training samples can be reduced to 10% using the methods proposed, reaching the same level of accuracy as larger data sets. A comparison with a state-of-the-art active learning method, margin sampling, is provided, highlighting advantages of the methods proposed. The effect of spatial resolution and separability of the classes on the quality of the selection of pixels is also discussed.

Globally aligned photomosaic of the Lucky Strike hydrothermal vent field (Mid-Atlantic Ridge, 37°18.5’N): Release of georeferenced data, mosaic construction, and viewing software

We present a georeferenced photomosaic of the Lucky Strike hydrothermal vent field (Mid-Atlantic Ridge, 37°18’N). The photomosaic was generated from digital photographs acquired using the ARGO II seafloor imaging system during the 1996 LUSTRE cruise, which surveyed a ~1 km2 zone and provided a coverage of ~20% of the seafloor. The photomosaic has a pixel resolution of 15 mm and encloses the areas with known active hydrothermal venting. The final mosaic is generated after an optimization that includes the automatic detection of the same benthic features across different images (feature-matching), followed by a global alignment of images based on the vehicle navigation. We also provide software to construct mosaics from large sets of images for which georeferencing information exists (location, attitude, and altitude per image), to visualize them, and to extract data. Georeferencing information can be provided by the raw navigation data (collected during the survey) or result from the optimization obtained from imatge matching. Mosaics based solely on navigation can be readily generated by any user but the optimization and global alignment of the mosaic requires a case-by-case approach for which no universally software is available. The Lucky Strike photomosaics (optimized and navigated-only) are publicly available through the Marine Geoscience Data System (MGDS, http://www.marine-geo.org). The mosaic-generating and viewing software is available through the Computer Vision and Robotics Group Web page at the University of Girona (http://eia.udg.es/_rafa/mosaicviewer.html)

Localization and characterization of an active fault in an urbanized area in central Guatemala by means of geoelectrical imaging

The Polochic and Motagua faults define the active plate boundary between the North American and Caribbean plates in central Guatemala. A splay of the Polochic Fault traverses the rapidly growing city of San Miguel Uspantan that is periodically affected by destructive earthquakes. This fault splay was located using a 2D electrical resistivity tomography (ERT) survey that also characterized the fault damage zone and evaluated the thickness and nature of recent deposits upon which most of the city is built. ERT images show the fault as a similar to 50 m wide, near-vertical low-resistivity anomaly, bounded within a few meters by high resistivity anomalies. Forward modeling reproduces the key aspects of the observed electrical resistivity data with remarkable fidelity thus defining the overall location, geometry, and internal structure of the fault zone as well as the affected lithologies. Our results indicate that the city is constructed on a similar to 20 m thick surficial layer consisting of poorly consolidated, highly porous, water-logged pumice. This soft layer is likely to amplify seismic waves and to liquefy upon moderate to strong ground shaking. The electrical conductivity as well as the major element chemistry of the groundwater provides evidence to suggest that the local aquifer might, at least in part, be fed by water rising along the fault. Therefore, the potential threat posed by this fault splay may not be limited to its seismic activity per se, but could be compounded its potential propensity to enhance seismic site effects by injecting water into the soft surficial sediments. The results of this study provide the basis for a rigorous analysis of seismic hazard and sustainable development of San Miguel Uspantan and illustrate the potential of ERT surveying for paleoseismic studies.

Cilengitide combined with standard treatment for patients with newly diagnosed glioblastoma with methylated MGMT promoter (CENTRIC EORTC 26071-22072 study): a multicentre, randomised, open-label, phase 3 trial.

BACKGROUND: Cilengitide is a selective αvβ3 and αvβ5 integrin inhibitor. Data from phase 2 trials suggest that it has antitumour activity as a single agent in recurrent glioblastoma and in combination with standard temozolomide chemoradiotherapy in newly diagnosed glioblastoma (particularly in tumours with methylated MGMT promoter). We aimed to assess cilengitide combined with temozolomide chemoradiotherapy in patients with newly diagnosed glioblastoma with methylated MGMT promoter. METHODS: In this multicentre, open-label, phase 3 study, we investigated the efficacy of cilengitide in patients from 146 study sites in 25 countries. Eligible patients (newly diagnosed, histologically proven supratentorial glioblastoma, methylated MGMT promoter, and age ≥18 years) were stratified for prognostic Radiation Therapy Oncology Group recursive partitioning analysis class and geographic region and centrally randomised in a 1:1 ratio with interactive voice response system to receive temozolomide chemoradiotherapy with cilengitide 2000 mg intravenously twice weekly (cilengitide group) or temozolomide chemoradiotherapy alone (control group). Patients and investigators were unmasked to treatment allocation. Maintenance temozolomide was given for up to six cycles, and cilengitide was given for up to 18 months or until disease progression or unacceptable toxic effects. The primary endpoint was overall survival. We analysed survival outcomes by intention to treat. This study is registered with ClinicalTrials.gov, number NCT00689221. FINDINGS: Overall, 3471 patients were screened. Of these patients, 3060 had tumour MGMT status tested; 926 patients had a methylated MGMT promoter, and 545 were randomly assigned to the cilengitide (n=272) or control groups (n=273) between Oct 31, 2008, and May 12, 2011. Median overall survival was 26·3 months (95% CI 23·8-28·8) in the cilengitide group and 26·3 months (23·9-34·7) in the control group (hazard ratio 1·02, 95% CI 0·81-1·29, p=0·86). None of the predefined clinical subgroups showed a benefit from cilengitide. We noted no overall additional toxic effects with cilengitide treatment. The most commonly reported adverse events of grade 3 or worse in the safety population were lymphopenia (31 [12%] in the cilengitide group vs 26 [10%] in the control group), thrombocytopenia (28 [11%] vs 46 [18%]), neutropenia (19 [7%] vs 24 [9%]), leucopenia (18 [7%] vs 20 [8%]), and convulsion (14 [5%] vs 15 [6%]). INTERPRETATION: The addition of cilengitide to temozolomide chemoradiotherapy did not improve outcomes; cilengitide will not be further developed as an anticancer drug. Nevertheless, integrins remain a potential treatment target for glioblastoma. FUNDING: Merck KGaA, Darmstadt, Germany.

Estimating dormant and active hematopoietic stem cell kinetics through extensive modeling of bromodeoxyuridine label-retaining cell dynamics.

Bone marrow hematopoietic stem cells (HSCs) are responsible for both lifelong daily maintenance of all blood cells and for repair after cell loss. Until recently the cellular mechanisms by which HSCs accomplish these two very different tasks remained an open question. Biological evidence has now been found for the existence of two related mouse HSC populations. First, a dormant HSC (d-HSC) population which harbors the highest self-renewal potential of all blood cells but is only induced into active self-renewal in response to hematopoietic stress. And second, an active HSC (a-HSC) subset that by and large produces the progenitors and mature cells required for maintenance of day-to-day hematopoiesis. Here we present computational analyses further supporting the d-HSC concept through extensive modeling of experimental DNA label-retaining cell (LRC) data. Our conclusion that the presence of a slowly dividing subpopulation of HSCs is the most likely explanation (amongst the various possible causes including stochastic cellular variation) of the observed long term Bromodeoxyuridine (BrdU) retention, is confirmed by the deterministic and stochastic models presented here. Moreover, modeling both HSC BrdU uptake and dilution in three stages and careful treatment of the BrdU detection sensitivity permitted improved estimates of HSC turnover rates. This analysis predicts that d-HSCs cycle about once every 149-193 days and a-HSCs about once every 28-36 days. We further predict that, using LRC assays, a 75%-92.5% purification of d-HSCs can be achieved after 59-130 days of chase. Interestingly, the d-HSC proportion is now estimated to be around 30-45% of total HSCs - more than twice that of our previous estimate.

Comparative performance of supertree algorithms in large data sets using the soapberry family (Sapindaceae) as a case study.

For the last 2 decades, supertree reconstruction has been an active field of research and has seen the development of a large number of major algorithms. Because of the growing popularity of the supertree methods, it has become necessary to evaluate the performance of these algorithms to determine which are the best options (especially with regard to the supermatrix approach that is widely used). In this study, seven of the most commonly used supertree methods are investigated by using a large empirical data set (in terms of number of taxa and molecular markers) from the worldwide flowering plant family Sapindaceae. Supertree methods were evaluated using several criteria: similarity of the supertrees with the input trees, similarity between the supertrees and the total evidence tree, level of resolution of the supertree and computational time required by the algorithm. Additional analyses were also conducted on a reduced data set to test if the performance levels were affected by the heuristic searches rather than the algorithms themselves. Based on our results, two main groups of supertree methods were identified: on one hand, the matrix representation with parsimony (MRP), MinFlip, and MinCut methods performed well according to our criteria, whereas the average consensus, split fit, and most similar supertree methods showed a poorer performance or at least did not behave the same way as the total evidence tree. Results for the super distance matrix, that is, the most recent approach tested here, were promising with at least one derived method performing as well as MRP, MinFlip, and MinCut. The output of each method was only slightly improved when applied to the reduced data set, suggesting a correct behavior of the heuristic searches and a relatively low sensitivity of the algorithms to data set sizes and missing data. Results also showed that the MRP analyses could reach a high level of quality even when using a simple heuristic search strategy, with the exception of MRP with Purvis coding scheme and reversible parsimony. The future of supertrees lies in the implementation of a standardized heuristic search for all methods and the increase in computing power to handle large data sets. The latter would prove to be particularly useful for promising approaches such as the maximum quartet fit method that yet requires substantial computing power.

Monitoring network optimisation for spatial data classification using support vector machines

The paper presents a novel method for monitoring network optimisation, based on a recent machine learning technique known as support vector machine. It is problem-oriented in the sense that it directly answers the question of whether the advised spatial location is important for the classification model. The method can be used to increase the accuracy of classification models by taking a small number of additional measurements. Traditionally, network optimisation is performed by means of the analysis of the kriging variances. The comparison of the method with the traditional approach is presented on a real case study with climate data.

Lipodystrophy and weight changes: data from the Swiss HIV Cohort Study, 2000-2006.

BACKGROUND AND OBJECTIVES: Combination antiretroviral therapy (cART) is changing, and this may affect the type and occurrence of side effects. We examined the frequency of lipodystrophy (LD) and weight changes in relation to the use of specific drugs in the Swiss HIV Cohort Study (SHCS). METHODS: In the SHCS, patients are followed twice a year and scored by the treating physician as having 'fat accumulation', 'fat loss', or neither. Treatments, and reasons for change thereof, are recorded. Our study sample included all patients treated with cART between 2003 and 2006 and, in addition, all patients who started cART between 2000 and 2003. RESULTS: From 2003 to 2006, the percentage of patients taking stavudine, didanosine and nelfinavir decreased, the percentage taking lopinavir, nevirapine and efavirenz remained stable, and the percentage taking atazanavir and tenofovir increased by 18.7 and 22.2%, respectively. In life-table Kaplan-Meier analysis, patients starting cART in 2003-2006 were less likely to develop LD than those starting cART from 2000 to 2002 (P<0.02). LD was quoted as the reason for treatment change or discontinuation for 4% of patients on cART in 2003, and for 1% of patients treated in 2006 (P for trend <0.001). In univariate and multivariate regression analysis, patients with a weight gain of >or=5 kg were more likely to take lopinavir or atazanavir than patients without such a weight gain [odds ratio (OR) 2, 95% confidence interval (CI) 1.3-2.9, and OR 1.7, 95% CI 1.3-2.1, respectively]. CONCLUSIONS: LD has become less frequent in the SHCS from 2000 to 2006. A weight gain of more than 5 kg was associated with the use of atazanavir and lopinavir.

Adherence to and effectiveness of highly active antiretroviral treatment for HIV infection: assessing the bidirectional relationship.

BACKGROUND: It is well established that high adherence to HIV-infected patients on highly active antiretroviral treatment (HAART) is a major determinant of virological and immunologic success. Furthermore, psychosocial research has identified a wide range of adherence factors including patients' subjective beliefs about the effectiveness of HAART. Current statistical approaches, mainly based on the separate identification either of factors associated with treatment effectiveness or of those associated with adherence, fail to properly explore the true relationship between adherence and treatment effectiveness. Adherence behavior may be influenced not only by perceived benefits-which are usually the focus of related studies-but also by objective treatment benefits reflected in biological outcomes. METHODS: Our objective was to assess the bidirectional relationship between adherence and response to treatment among patients enrolled in the ANRS CO8 APROCO-COPILOTE study. We compared a conventional statistical approach based on the separate estimations of an adherence and an effectiveness equation to an econometric approach using a 2-equation simultaneous system based on the same 2 equations. RESULTS: Our results highlight a reciprocal relationship between adherence and treatment effectiveness. After controlling for endogeneity, adherence was positively associated with treatment effectiveness. Furthermore, CD4 count gain after baseline was found to have a positive significant effect on adherence at each observation period. This immunologic parameter was not significant when the adherence equation was estimated separately. In the 2-equation model, the covariances between disturbances of both equations were found to be significant, thus confirming the statistical appropriacy of studying adherence and treatment effectiveness jointly. CONCLUSIONS: Our results, which suggest that positive biological results arising as a result of high adherence levels, in turn reinforce continued adherence and strengthen the argument that patients who do not experience rapid improvement in their immunologic and clinical statuses after HAART initiation should be prioritized when developing adherence support interventions. Furthermore, they invalidate the hypothesis that HAART leads to "false reassurance" among HIV-infected patients.

Fast Geodesic Active Fields for Image Registration Based on Splitting and Augmented Lagrangian Approaches.

In this paper, we present an efficient numerical scheme for the recently introduced geodesic active fields (GAF) framework for geometric image registration. This framework considers the registration task as a weighted minimal surface problem. Hence, the data-term and the regularization-term are combined through multiplication in a single, parametrization invariant and geometric cost functional. The multiplicative coupling provides an intrinsic, spatially varying and data-dependent tuning of the regularization strength, and the parametrization invariance allows working with images of nonflat geometry, generally defined on any smoothly parametrizable manifold. The resulting energy-minimizing flow, however, has poor numerical properties. Here, we provide an efficient numerical scheme that uses a splitting approach; data and regularity terms are optimized over two distinct deformation fields that are constrained to be equal via an augmented Lagrangian approach. Our approach is more flexible than standard Gaussian regularization, since one can interpolate freely between isotropic Gaussian and anisotropic TV-like smoothing. In this paper, we compare the geodesic active fields method with the popular Demons method and three more recent state-of-the-art algorithms: NL-optical flow, MRF image registration, and landmark-enhanced large displacement optical flow. Thus, we can show the advantages of the proposed FastGAF method. It compares favorably against Demons, both in terms of registration speed and quality. Over the range of example applications, it also consistently produces results not far from more dedicated state-of-the-art methods, illustrating the flexibility of the proposed framework.

Antiretroviral therapy during pregnancy and premature birth: analysis of Swiss data.

BACKGROUND: There is an ongoing debate as to whether combined antiretroviral treatment (cART) during pregnancy is an independent risk factor for prematurity in HIV-1-infected women. OBJECTIVE: The aim of the study was to examine (1) crude effects of different ART regimens on prematurity, (2) the association between duration of cART and duration of pregnancy, and (3) the role of possibly confounding risk factors for prematurity. METHOD: We analysed data from 1180 pregnancies prospectively collected by the Swiss Mother and Child HIV Cohort Study (MoCHiV) and the Swiss HIV Cohort Study (SHCS). RESULTS: Odds ratios for prematurity in women receiving mono/dual therapy and cART were 1.8 [95% confidence interval (CI) 0.85-3.6] and 2.5 (95% CI 1.4-4.3) compared with women not receiving ART during pregnancy (P=0.004). In a subgroup of 365 pregnancies with comprehensive information on maternal clinical, demographic and lifestyle characteristics, there was no indication that maternal viral load, age, ethnicity or history of injecting drug use affected prematurity rates associated with the use of cART. Duration of cART before delivery was also not associated with duration of pregnancy. CONCLUSION: Our study indicates that confounding by maternal risk factors or duration of cART exposure is not a likely explanation for the effects of ART on prematurity in HIV-1-infected women.

GSVA: gene set variation analysis for microarray and RNA-seq data

Gene set enrichment (GSE) analysis is a popular framework for condensing information from gene expression profiles into a pathway or signature summary. The strengths of this approach over single gene analysis include noise and dimension reduction, as well as greater biological interpretability. As molecular profiling experiments move beyond simple case-control studies, robust and flexible GSE methodologies are needed that can model pathway activity within highly heterogeneous data sets. To address this challenge, we introduce Gene Set Variation Analysis (GSVA), a GSE method that estimates variation of pathway activity over a sample population in an unsupervised manner. We demonstrate the robustness of GSVA in a comparison with current state of the art sample-wise enrichment methods. Further, we provide examples of its utility in differential pathway activity and survival analysis. Lastly, we show how GSVA works analogously with data from both microarray and RNA-seq experiments. GSVA provides increased power to detect subtle pathway activity changes over a sample population in comparison to corresponding methods. While GSE methods are generally regarded as end points of a bioinformatic analysis, GSVA constitutes a starting point to build pathway-centric models of biology. Moreover, GSVA contributes to the current need of GSE methods for RNA-seq data. GSVA is an open source software package for R which forms part of the Bioconductor project and can be downloaded at http://www.bioconductor.org.

Mycobacterium tuberculosis-specific CD8 T cells are functionally and phenotypically different between latent infection and active disease

Purpose/Objective: Tuberculosis (TB) is the second worldwide leading cause of death from an infectious disease after HIV infection. Protective immunity to Mycobacterium tuberculosis (Mtb) remains poorly understood and the role of Mtb-specific CD8 T-cells is controversial. We performed comprehensive functional and phenotypic characterizations of Mtb-specific CD8 T-cell responses in 273 subjects with either latent Mtb infection (LTBI) or active TB disease (TB) to assess their profile and relevance in TB. Materials and methods: Using multi-parametric flow cytometry, we assessed Mtb-specific CD8 T-cell functional (production of IFNgamma, IL-2 and TNF-alpha; proliferation capacity and cytotoxicity) and phenotypic (T-cell differentiation and exhaustion) profiles in cells isolated from peripheral blood and correlated these profiles with distinct clinical presentations. Results: Mtb-specific CD8 T-cells were detected in most TB patients and few LTBI subjects (65% and 15%, respectively; P < 0.00001) and were of similar magnitude with a comparable cytokines profile (IFNg+TNFa+IL2-) in both groups. Mtb-specific CD8 T-cells were mostly TEMRA (CD45RA+ CCR7-) co-expressing 2B4 and CD160 in LTBI subjects and mostly TEM (CD45RA-CCR7-) lacking PD-1/ CD160/2B4 in TB patients. Furthermore, Mtb-specific CD8 T-cells mostly expressed very little perforin and granulysin but contained granzymes A and B or lacked all these cytotoxic markers in TB and LTBI subjects, respectively. However, in vitro expanded Mtb-specific CD8 T-cells acquired perforin, granulysin and granzymes. Finally, Mtb-specific CD8 T-cell responses were more robust and prone to proliferate in patients with extrapulmonary compared to pulmonary TB. Conclusions: The clinical status and TB presentation are associated to specific profiles of Mtb-specific CD8 T-cell responses, thus indicating distinct dynamics between the mycobacteria, the CD8 T-cell response and the clinical outcome. Our data shed light on the controversial reached by studies performed in human and animal models, thus advancing the current knowledge on the complex dynamic of TB immunity.

Aliskiren monotherapy does not cause paradoxical blood pressure rises: meta-analysis of data from 8 clinical trials.

Angiotensin receptor blockers, angiotensin-converting enzyme inhibitors, and diuretics all cause reactive rises in plasma renin concentration, but particularly high levels have been reported with aliskiren. This prompted speculation that blockade of plasma renin activity with aliskiren could be overwhelmed, leading to paradoxical increases in blood pressure. This meta-analysis of data from 4877 patients from 8 randomized, double-blind, placebo- and/or active-controlled trials examined this hypothesis. The analysis focused on the incidence of paradoxical blood pressure increases above predefined thresholds, after > or =4 weeks of treatment with 300 mg of aliskiren, angiotensin receptor blockers (300 mg of irbesartan, 100 mg of losartan, or 320 mg of valsartan), 10 mg of ramipril, 25 mg of hydrochlorothiazide, or placebo. There were no significant differences in the frequency of increases in systolic (>10 mm Hg; P=0.30) or diastolic (>5 mm Hg; P=0.65) pressure among those treated with aliskiren (3.9% and 3.1%, respectively), angiotensin receptor blockers (4.0% and 3.7%), ramipril (5.7% and 2.6%), or hydrochlorothiazide (4.4% and 2.7%). Increases in blood pressure were considerably more frequent in the placebo group (12.6% and 11.4%; P<0.001). None of the 536 patients with plasma renin activity data who received 300 mg of aliskiren exhibited an increase in systolic pressure >10 mm Hg that was associated with an increase in plasma renin activity >0.1 ng/mL per hour. In conclusion, the incidence of blood pressure increases with aliskiren was similar to that during treatment with other antihypertensive drugs. Blood pressure rises on aliskiren treatment were not associated with increases in plasma renin activity. This meta-analysis found no evidence that aliskiren uniquely causes paradoxical rises in blood pressure.

Lack of Mycobacterium tuberculosis-specific interleukin-17A-producing CD4(+) T cells in active disease.

Protective immunity to Mycobacterium tuberculosis (Mtb) is commonly ascribed to a Th1 profile; however, the involvement of Th17 cells remains to be clarified. Here, we characterized Mtb-specific CD4(+) T cells in blood and bronchoalveolar lavages (BALs) from untreated subjects with either active tuberculosis disease (TB) or latent Mtb infection (LTBI), considered as prototypic models of uncontrolled or controlled infection, respectively. The production of IL-17A, IFN-γ, TNF-α, and IL-2 by Mtb-specific CD4(+) T cells was assessed both directly ex vivo and following in vitro antigen-specific T-cell expansion. Unlike for extracellular bacteria, Mtb-specific CD4(+) T-cell responses lacked immediate ex vivo IL-17A effector function in both LTBI and TB individuals. Furthermore, Mtb-specific Th17 cells were absent in BALs, while extracellular bacteria-specific Th17 cells were identified in gut biopsies of healthy individuals. Interestingly, only Mtb-specific CD4(+) T cells from 50% of LTBI but not from TB subjects acquired the ability to produce IL-17A following Mtb-specific T-cell expansion. Finally, IL-17A acquisition by Mtb-specific CD4(+) T cells correlated with the coexpression of CXCR3 and CCR6, currently associated to Th1 or Th17 profiles, respectively. Our data demonstrate that Mtb-specific Th17 cells are selectively undetectable in peripheral blood and BALs from TB patients.