Advanced geostatistical and machine-learning models for spatial data analysis of radioactively contaminated regions

Radioactive soil-contamination mapping and risk assessment is a vital issue for decision makers. Traditional approaches for mapping the spatial concentration of radionuclides employ various regression-based models, which usually provide a single-value prediction realization accompanied (in some cases) by estimation error. Such approaches do not provide the capability for rigorous uncertainty quantification or probabilistic mapping. Machine learning is a recent and fast-developing approach based on learning patterns and information from data. Artificial neural networks for prediction mapping have been especially powerful in combination with spatial statistics. A data-driven approach provides the opportunity to integrate additional relevant information about spatial phenomena into a prediction model for more accurate spatial estimates and associated uncertainty. Machine-learning algorithms can also be used for a wider spectrum of problems than before: classification, probability density estimation, and so forth. Stochastic simulations are used to model spatial variability and uncertainty. Unlike regression models, they provide multiple realizations of a particular spatial pattern that allow uncertainty and risk quantification. This paper reviews the most recent methods of spatial data analysis, prediction, and risk mapping, based on machine learning and stochastic simulations in comparison with more traditional regression models. The radioactive fallout from the Chernobyl Nuclear Power Plant accident is used to illustrate the application of the models for prediction and classification problems. This fallout is a unique case study that provides the challenging task of analyzing huge amounts of data ('hard' direct measurements, as well as supplementary information and expert estimates) and solving particular decision-oriented problems.

A benchmark test for a quantitative assessment of simple neuron models

Several methods and algorithms have recently been proposed that allow for the systematic evaluation of simple neuron models from intracellular or extracellular recordings. Models built in this way generate good quantitative predictions of the future activity of neurons under temporally structured current injection. It is, however, difficult to compare the advantages of various models and algorithms since each model is designed for a different set of data. Here, we report about one of the first attempts to establish a benchmark test that permits a systematic comparison of methods and performances in predicting the activity of rat cortical pyramidal neurons. We present early submissions to the benchmark test and discuss implications for the design of future tests and simple neurons models

Dynamic models of viral replication and latency.

PURPOSE OF REVIEW: HIV targets primary CD4(+) T cells. The virus depends on the physiological state of its target cells for efficient replication, and, in turn, viral infection perturbs the cellular state significantly. Identifying the virus-host interactions that drive these dynamic changes is important for a better understanding of viral pathogenesis and persistence. The present review focuses on experimental and computational approaches to study the dynamics of viral replication and latency. RECENT FINDINGS: It was recently shown that only a fraction of the inducible latently infected reservoirs are successfully induced upon stimulation in ex-vivo models while additional rounds of stimulation make allowance for reactivation of more latently infected cells. This highlights the potential role of treatment duration and timing as important factors for successful reactivation of latently infected cells. The dynamics of HIV productive infection and latency have been investigated using transcriptome and proteome data. The cellular activation state has shown to be a major determinant of viral reactivation success. Mathematical models of latency have been used to explore the dynamics of the latent viral reservoir decay. SUMMARY: Timing is an important component of biological interactions. Temporal analyses covering aspects of viral life cycle are essential for gathering a comprehensive picture of HIV interaction with the host cell and untangling the complexity of latency. Understanding the dynamic changes tipping the balance between success and failure of HIV particle production might be key to eradicate the viral reservoir.

Smart suction device for less blood trauma: a comparison with Cell Saver.

OBJECTIVE: The major source of hemolysis during cardiopulmonary bypass remains the cardiotomy suction and is primarily due to the interaction between air and blood. The Smart suction system involves an automatically controlled aspiration designed to avoid the mixture of blood with air. This study was set-up to compare this recently designed suction system to a Cell Saver system in order to investigate their effects on blood elements during prolonged intrathoracic aspiration. METHODS: In a calf model (n=10; mean weight, 69.3+/-4.5 kg), a standardized hole was created in the right atrium allowing a blood loss of 100 ml/min, with a suction cannula placed into the chest cavity into a fixed position during 6 h. The blood was continuously aspirated either with the Smart suction system (five animals) or the Cell Saver system (five animals). Blood samples were taken hourly for blood cell counts and biochemistry. RESULTS: In the Smart suction group, red cell count, plasma protein and free hemoglobin levels remained stable, while platelet count exhibited a significant drop from the fifth hour onwards (prebypass: 683+/-201*10(9)/l, 5 h: 280+/-142*10(9)/l, P=0.046). In the Cell Saver group, there was a significant drop of the red cell count from the third hour onwards (prebypass: 8.6+/-0.9*10(12)/l, 6 h: 6.3+/-0.4*10(12)/l, P=0.02), of the platelet count from the first hour onwards (prebypass: 630+/-97*10(9)/l, 1 h: 224+/-75*10(9)/l, P<0.01), and of the plasma protein level from the first hour onwards (prebypass: 61.7+/-0.6 g/l, 1 h: 29.3+/-9.1 g/l, P<0.01). CONCLUSIONS: In this experimental set-up, the Smart suction system avoids damage to red cells and affects platelet count less than the Cell Saver system which induces important blood cell destruction, as any suction device mixing air and blood, as well as severe hypoproteinemia with its metabolic, clotting and hemodynamic consequences.

Disentangling the link between health and social capital: A comparison of immigrant and native-born populations in Spain

An increasing body of research has pointed to the relevance of social capital in studying a great variety of socio-economic phenomena, ranging from economics growth and development to educational attainment and public health. Conceptually, our paper is framed within the debates about the possible links between health and social capital, on one hand, and within the hypotheses regarding the importance of social and community networks in all stages of the dynamics of international migration, on the other hand. Our primary objective is to explore the ways social relations contribute to health differences between the immigrants and the native-born population of Spain. We also try to reveal differences in the nature of the social networks of foreign-born, as compared to that of the native-born persons. The empirical analysis is based on an individual-level data coming from the 2006 Spanish Health Survey, which contains a representative sample of the immigrant population. To assess the relationship between various health indicators (self-assessed health, chronic conditions and long-term illness) and social capital, controlling for other covariates, we estimate multilevel models separately for the two population groups of interest. In the estimates we distinguish between individual and community-level social capital. While the Health Survey contains information that allows us to define individual social capital measures, the collective indicators come from other official sources. In particular, for the subsample of immigrants, we proxy community-level networks and relationships by variables contained in the Spanish National Survey of Immigrants 2007. The results obtained so far point to the relevance of social capital as a covariate in the health equation, although, the significance varies according to the specific health indicator used. Additionally, and contrary to what is expected, immigrants’ social networks seem to be inferior to those of the native-born population in many aspects; and they also affect immigrant’s health to a lesser extent. Policy implications of the findings are discussed. Keywords: health status, social capital, immigration, Spain

Quantitative comparison between simulations of seismic wave propagation in heterogeneous poro-elastic media and equivalent visco-elastic solids for marine-type environments

There is increasing evidence to suggest that the presence of mesoscopic heterogeneities constitutes an important seismic attenuation mechanism in porous rocks. As a consequence, centimetre-scale perturbations of the rock physical properties should be taken into account for seismic modelling whenever detailed and accurate responses of specific target structures are desired, which is, however, computationally prohibitive. A convenient way to circumvent this problem is to use an upscaling procedure to replace each of the heterogeneous porous media composing the geological model by corresponding equivalent visco-elastic solids and to solve the visco-elastic equations of motion for the inferred equivalent model. While the overall qualitative validity of this procedure is well established, there are as of yet no quantitative analyses regarding the equivalence of the seismograms resulting from the original poro-elastic and the corresponding upscaled visco-elastic models. To address this issue, we compare poro-elastic and visco-elastic solutions for a range of marine-type models of increasing complexity. We found that despite the identical dispersion and attenuation behaviour of the heterogeneous poro-elastic and the equivalent visco-elastic media, the seismograms may differ substantially due to diverging boundary conditions, where there exist additional options for the poro-elastic case. In particular, we observe that at the fluid/porous-solid interface, the poro- and visco-elastic seismograms agree for closed-pore boundary conditions, but differ significantly for open-pore boundary conditions. This is an important result which has potentially far-reaching implications for wave-equation-based algorithms in exploration geophysics involving fluid/porous-solid interfaces, such as, for example, wavefield decomposition.

A critical evaluation of secondary cancer risk models applied to Monte Carlo dose distributions of 2-dimensional, 3-dimensional conformal and hybrid intensity-modulated radiation therapy for breast cancer.

The comparison of radiotherapy techniques regarding secondary cancer risk has yielded contradictory results possibly stemming from the many different approaches used to estimate risk. The purpose of this study was to make a comprehensive evaluation of different available risk models applied to detailed whole-body dose distributions computed by Monte Carlo for various breast radiotherapy techniques including conventional open tangents, 3D conformal wedged tangents and hybrid intensity modulated radiation therapy (IMRT). First, organ-specific linear risk models developed by the International Commission on Radiological Protection (ICRP) and the Biological Effects of Ionizing Radiation (BEIR) VII committee were applied to mean doses for remote organs only and all solid organs. Then, different general non-linear risk models were applied to the whole body dose distribution. Finally, organ-specific non-linear risk models for the lung and breast were used to assess the secondary cancer risk for these two specific organs. A total of 32 different calculated absolute risks resulted in a broad range of values (between 0.1% and 48.5%) underlying the large uncertainties in absolute risk calculation. The ratio of risk between two techniques has often been proposed as a more robust assessment of risk than the absolute risk. We found that the ratio of risk between two techniques could also vary substantially considering the different approaches to risk estimation. Sometimes the ratio of risk between two techniques would range between values smaller and larger than one, which then translates into inconsistent results on the potential higher risk of one technique compared to another. We found however that the hybrid IMRT technique resulted in a systematic reduction of risk compared to the other techniques investigated even though the magnitude of this reduction varied substantially with the different approaches investigated. Based on the epidemiological data available, a reasonable approach to risk estimation would be to use organ-specific non-linear risk models applied to the dose distributions of organs within or near the treatment fields (lungs and contralateral breast in the case of breast radiotherapy) as the majority of radiation-induced secondary cancers are found in the beam-bordering regions.

Ink dating using thermal desorption and gas chromatography / mass spectrometry: comparison of results obtained in two laboratories

Recent ink dating methods focused mainly on changes in solvent amounts occurring over time. A promising method was developed at the Landeskriminalamt of Munich using thermal desorption (TD) followed by gas chromatography / mass spectrometry (GC/MS) analysis. Sequential extractions of the phenoxyethanol present in ballpoint pen ink entries were carried out at two different temperatures. This method is applied in forensic practice and is currently implemented in several laboratories participating to the InCID group (International Collaboration on Ink Dating). However, harmonization of the method between the laboratories proved to be a particularly sensitive and time consuming task. The main aim of this work was therefore to implement the TD-GC/MS method at the Bundeskriminalamt (Wiesbaden, Germany) in order to evaluate if results were comparable to those obtained in Munich. At first validation criteria such as limits of reliable measurements, linearity and repeatability were determined. Samples were prepared in three different laboratories using the same inks and analyzed using two TDS-GC/MS instruments (one in Munich and one in Wiesbaden). The inter- and intra-laboratory variability of the ageing parameter was determined and ageing curves were compared. While inks stored in similar conditions yielded comparable ageing curves, it was observed that significantly different storage conditions had an influence on the resulting ageing curves. Finally, interpretation models, such as thresholds and trend tests, were evaluated and discussed in view of the obtained results. Trend tests were considered more suitable than threshold models. As both approaches showed limitations, an alternative model, based on the slopes of the ageing curves, was also proposed.

Tuberculosis screening in patients with psoriasis before antitumour necrosis factor therapy: comparison of an interferon-gamma release assay vs. tuberculin skin test.

BACKGROUND: Antitumour necrosis factor (anti-TNF) treatments may reactivate latent tuberculosis infection (LTBI). For detecting LTBI, the tuberculin skin test (TST) has low sensitivity and specificity. Interferon-gamma release assays (IGRA) have been shown to be more sensitive and specific than TST. OBJECTIVE: To compare the TST and the T-SPOT.TB IGRA for identifying LTBI in patients with psoriasis before anti-TNF treatment. METHODS: A retrospective study was carried out over a 4-year period on patients with psoriasis requiring anti-TNF treatment. All were subjected to the TST, T-SPOT.TB and chest X-ray. Risk factors for LTBI and history of bacillus Calmette-Guérin (BCG) vaccination were recorded. The association of T-SPOT.TB and TST results with risk factors for LTBI was tested through univariate logistic regression models. Agreement between tests was quantified using kappa statistics. Treatment for LTBI was started 1 month before anti-TNF therapy when indicated. RESULTS: Fifty patients were included; 90% had prior BCG vaccination. A positive T-SPOT.TB was strongly associated with a presumptive diagnosis of LTBI (odds ratio 7.43; 95% confidence interval 1.38-39.9), which was not the case for the TST. Agreement between the T-SPOT.TB and TST was poor, kappa = 0.33 (SD 0.13). LTBI was detected and treated in 20% of the patients. In 20% of the cases, LTBI was not retained in spite of a positive TST but a negative T-SPOT.TB. All patients received an anti-TNF agent for a median of 56 weeks (range 20-188); among patients with a positive TST/negative T-SPOT.TB, no tuberculosis was detected with a median follow-up of 64 weeks (44-188). One case of disseminated tuberculosis occurred after 28 weeks of adalimumab treatment in a patient with LTBI in spite of treatment with rifampicin. CONCLUSION: This study is the first to underline the frequency of LTBI in patients with psoriasis (20%), and to support the use of IGRA instead of the TST for its detection. Nevertheless, there is still a risk of tuberculosis under anti-TNF therapy, even if LTBI is correctly diagnosed and treated.

Quantification of Myocardial Perfusion Using 13N-ammonia PET: a Cross-Comparison Study on Analysis Software Packages - Carimas, PMOD and FlowQuant

Aim. Several software packages (SWP) and models have been released for quantification of myocardial perfusion (MP). Although they all are validated against something, the question remains how well their values agree. The present analysis focused on cross-comparison of three SWP for MP quantification of 13N-ammonia PET studies. Materials & Methods. 48 rest and stress MP 13N-ammonia PET studies of hypertrophic cardiomyopathy (HCM) patients (Sciagrà et al., 2009) were analysed with three SW packages - Carimas, PMOD, and FlowQuant - by three observers blinded to the results of each other. All SWP implement the one-tissue-compartment model (1TCM, DeGrado et al. 1996), and first two - the two-tissue-compartment model (2TCM, Hutchins et al. 1990) as well. Linear mixed model for the repeated measures was fitted to the data. Where appropriate we used Bland-Altman plots as well. The reproducibility was assessed on global, regional and segmental levels. Intraclass correlation coefficients (ICC), differences between the SWPs and between models were obtained. ICC≥0.75 indicated excellent reproducibility, 0.4≤ICC<0.75 indicated fair to good reproducibility, ICC<0.4 - poor reproducibility (Rosner, 2010). Results. When 1TCM MP values were compared, the SW agreement on global and regional levels was excellent, except for Carimas vs. PMOD at RCA: ICC=0.715 and for PMOD vs. FlowQuant at LCX:ICC=0.745 which were good. In segmental analysis in five segments: 7,12,13, 16, and 17 the agreement between all SWP was excellent; in the remaining 12 segments the agreement varied between the compared SWP. Carimas showed excellent agreement with FlowQuant in 13 segments and good in four - 1, 5, 6, 11: 0.687≤ICCs≤0.73; Carimas had excellent agreement with PMOD in 11 segments, good in five_4, 9, 10, 14, 15: 0.682≤ICCs≤0.737, and poor in segment 3: ICC=0.341. PMOD had excellent agreement with FlowQuant in eight segments and substantial-to-good in nine_1, 2, 3, 5, 6,8-11: 0.585≤ICCs≤0.738. Agreement between Carimas and PMOD for 2TCM was good at a global level: ICC=0.745, excellent at LCX (0.780) and RCA (0.774), good at LAD (0.662); agreement was excellent for ten segments, fair-to-substantial for segments 2, 3, 8, 14, 15 (0.431≤ICCs≤0.681), poor for segments 4 (0.384) and 17 (0.278). Conclusions. The three SWP used by different operators to analyse 13N-ammonia PET MP studies provide results that agree well at a global level, regional levels, and mostly well even at a segmental level. Agreement is better for 1TCM. Poor agreement at segments 4 and 17 for 2TCM needs further clarification.

Comparison and validation of tissue modelization and statistical classification methods in T1-weighted MR brain images.

This paper presents a validation study on statistical nonsupervised brain tissue classification techniques in magnetic resonance (MR) images. Several image models assuming different hypotheses regarding the intensity distribution model, the spatial model and the number of classes are assessed. The methods are tested on simulated data for which the classification ground truth is known. Different noise and intensity nonuniformities are added to simulate real imaging conditions. No enhancement of the image quality is considered either before or during the classification process. This way, the accuracy of the methods and their robustness against image artifacts are tested. Classification is also performed on real data where a quantitative validation compares the methods' results with an estimated ground truth from manual segmentations by experts. Validity of the various classification methods in the labeling of the image as well as in the tissue volume is estimated with different local and global measures. Results demonstrate that methods relying on both intensity and spatial information are more robust to noise and field inhomogeneities. We also demonstrate that partial volume is not perfectly modeled, even though methods that account for mixture classes outperform methods that only consider pure Gaussian classes. Finally, we show that simulated data results can also be extended to real data.

Effects of sample size on the performance of species distribution models

A wide range of modelling algorithms is used by ecologists, conservation practitioners, and others to predict species ranges from point locality data. Unfortunately, the amount of data available is limited for many taxa and regions, making it essential to quantify the sensitivity of these algorithms to sample size. This is the first study to address this need by rigorously evaluating a broad suite of algorithms with independent presence-absence data from multiple species and regions. We evaluated predictions from 12 algorithms for 46 species (from six different regions of the world) at three sample sizes (100, 30, and 10 records). We used data from natural history collections to run the models, and evaluated the quality of model predictions with area under the receiver operating characteristic curve (AUC). With decreasing sample size, model accuracy decreased and variability increased across species and between models. Novel modelling methods that incorporate both interactions between predictor variables and complex response shapes (i.e. GBM, MARS-INT, BRUTO) performed better than most methods at large sample sizes but not at the smallest sample sizes. Other algorithms were much less sensitive to sample size, including an algorithm based on maximum entropy (MAXENT) that had among the best predictive power across all sample sizes. Relative to other algorithms, a distance metric algorithm (DOMAIN) and a genetic algorithm (OM-GARP) had intermediate performance at the largest sample size and among the best performance at the lowest sample size. No algorithm predicted consistently well with small sample size (n < 30) and this should encourage highly conservative use of predictions based on small sample size and restrict their use to exploratory modelling.

Comparison of quality of life after stereotactic body radiotherapy and surgery for early-stage prostate cancer

Background: As the long-term efficacy of stereotactic body radiation therapy (SBRT) becomes established and other prostate cancer treatment approaches are refined and improved, examination of quality of life (QOL) following prostate cancer treatment is critical in driving both patient and clinical treatment decisions. We present the first study to compare QOL after SBRT and radical prostatectomy, with QOL assessed at approximately the same times pre- and post-treatment and using the same validated QOL instrument. Methods: Patients with clinically localized prostate cancer were treated with either radical prostatectomy (n = 123 Spanish patients) or SBRT (n = 216 American patients). QOL was assessed using the Expanded Prostate Cancer Index Composite (EPIC) grouped into urinary, sexual, and bowel domains. For comparison purposes, SBRT EPIC data at baseline, 3 weeks, 5, 11, 24, and 36 months were compared to surgery data at baseline, 1, 6, 12, 24,and 36 months. Differences in patient characteristics between the two groups were assessed using Chi-squared tests for categorical variables and t-tests for continuous variables. Generalized estimating equation (GEE) models were constructed for each EPIC scale to account for correlation among repeated measures and used to assess the effect of treatment on QOL. Results: The largest differences in QOL occurred in the first 16 months after treatment, with larger declines following surgery in urinary and sexual QOL as compared to SBRT, and a larger decline in bowel QOL following SBRT as compared to surgery. Long-term urinary and sexual QOL declines remained clinically significantly lower for surgery patients but not for SBRT patients. Conclusions: Overall, these results may have implications for patient and physician clinical decision making which are often influenced by QOL. These differences in sexual, urinary and bowel QOL should be closely considered in selecting the right treatment, especially in evaluating the value of non-invasive treatments, such as SBRT.

Comparison of an EMG-based and a stress-based method to predict shoulder muscle forces.

The estimation of muscle forces in musculoskeletal shoulder models is still controversial. Two different methods are widely used to solve the indeterminacy of the system: electromyography (EMG)-based methods and stress-based methods. The goal of this work was to evaluate the influence of these two methods on the prediction of muscle forces, glenohumeral load and joint stability after total shoulder arthroplasty. An EMG-based and a stress-based method were implemented into the same musculoskeletal shoulder model. The model replicated the glenohumeral joint after total shoulder arthroplasty. It contained the scapula, the humerus, the joint prosthesis, the rotator cuff muscles supraspinatus, subscapularis and infraspinatus and the middle, anterior and posterior deltoid muscles. A movement of abduction was simulated in the plane of the scapula. The EMG-based method replicated muscular activity of experimentally measured EMG. The stress-based method minimised a cost function based on muscle stresses. We compared muscle forces, joint reaction force, articular contact pressure and translation of the humeral head. The stress-based method predicted a lower force of the rotator cuff muscles. This was partly counter-balanced by a higher force of the middle part of the deltoid muscle. As a consequence, the stress-based method predicted a lower joint load (16% reduced) and a higher superior-inferior translation of the humeral head (increased by 1.2 mm). The EMG-based method has the advantage of replicating the observed cocontraction of stabilising muscles of the rotator cuff. This method is, however, limited to available EMG measurements. The stress-based method has thus an advantage of flexibility, but may overestimate glenohumeral subluxation.

Developing models for online academic advising

Peer-reviewed