Learning wind fields with multiple kernels

This paper presents multiple kernel learning (MKL) regression as an exploratory spatial data analysis and modelling tool. The MKL approach is introduced as an extension of support vector regression, where MKL uses dedicated kernels to divide a given task into sub-problems and to treat them separately in an effective way. It provides better interpretability to non-linear robust kernel regression at the cost of a more complex numerical optimization. In particular, we investigate the use of MKL as a tool that allows us to avoid using ad-hoc topographic indices as covariables in statistical models in complex terrains. Instead, MKL learns these relationships from the data in a non-parametric fashion. A study on data simulated from real terrain features confirms the ability of MKL to enhance the interpretability of data-driven models and to aid feature selection without degrading predictive performances. Here we examine the stability of the MKL algorithm with respect to the number of training data samples and to the presence of noise. The results of a real case study are also presented, where MKL is able to exploit a large set of terrain features computed at multiple spatial scales, when predicting mean wind speed in an Alpine region.

Cytochrome P450 and ABCB1 genetics: association with quetiapine and norquetiapine plasma and cerebrospinal fluid concentrations and with clinical response in patients suffering from schizophrenia. A pilot study.

Variability in response to atypical antipsychotic drugs is due to genetic and environmental factors. Cytochrome P450 (CYP) isoforms are implicated in the metabolism of drugs, while the P-glycoprotein transporter (P-gp), encoded by the ABCB1 gene, may influence both the blood and brain drug concentrations. This study aimed to identify the possible associations of CYP and ABCB1 genetic polymorphisms with quetiapine and norquetiapine plasma and cerebrospinal fluid (CSF) concentrations and with response to treatment. Twenty-two patients with schizophrenia receiving 600 mg of quetiapine daily were genotyped for four CYP isoforms and ABCB1 polymorphisms. Quetiapine and norquetiapine peak plasma and CSF concentrations were measured after 4 weeks of treatment. Stepwise multiple regression analysis revealed that ABCB1 3435C > T (rs1045642), 2677G > T (rs2032582) and 1236C > T (rs1128503) polymorphisms predicted plasma quetiapine concentrations, explaining 41% of the variability (p = 0.001). Furthermore, the ABCB1 polymorphisms predicted 48% (p = 0.024) of the variability of the Δ PANSS total score, with the non-carriers of the 3435TT showing higher changes in the score. These results suggest that ABCB1 genetic polymorphisms may be a predictive marker of quetiapine treatment in schizophrenia.

Prognostic role of KRAS and BRAF in stage II and III resected colon cancer: results of the translational study on the PETACC-3, EORTC 40993, SAKK 60-00 trial.

PURPOSE: Mutations within the KRAS proto-oncogene have predictive value but are of uncertain prognostic value in the treatment of advanced colorectal cancer. We took advantage of PETACC-3, an adjuvant trial with 3,278 patients with stage II to III colon cancer, to evaluate the prognostic value of KRAS and BRAF tumor mutation status in this setting. PATIENTS AND METHODS: Formalin-fixed paraffin-embedded tissue blocks (n = 1,564) were prospectively collected and DNA was extracted from tissue sections from 1,404 cases. Planned analysis of KRAS exon 2 and BRAF exon 15 mutations was performed by allele-specific real-time polymerase chain reaction. Survival analyses were based on univariate and multivariate proportional hazard regression models. RESULTS: KRAS and BRAF tumor mutation rates were 37.0% and 7.9%, respectively, and were not significantly different according to tumor stage. In a multivariate analysis containing stage, tumor site, nodal status, sex, age, grade, and microsatellite instability (MSI) status, KRAS mutation was associated with grade (P = .0016), while BRAF mutation was significantly associated with female sex (P = .017), and highly significantly associated with right-sided tumors, older age, high grade, and MSI-high tumors (all P < 10(-4)). In univariate and multivariate analysis, KRAS mutations did not have a major prognostic value regarding relapse-free survival (RFS) or overall survival (OS). BRAF mutation was not prognostic for RFS, but was for OS, particularly in patients with MSI-low (MSI-L) and stable (MSI-S) tumors (hazard ratio, 2.2; 95% CI, 1.4 to 3.4; P = .0003). CONCLUSION: In stage II-III colon cancer, the KRAS mutation status does not have major prognostic value. BRAF is prognostic for OS in MS-L/S tumors.

Molecular clock is involved in predictive circadian adjustment of renal function.

Renal excretion of water and major electrolytes exhibits a significant circadian rhythm. This functional periodicity is believed to result, at least in part, from circadian changes in secretion/reabsorption capacities of the distal nephron and collecting ducts. Here, we studied the molecular mechanisms underlying circadian rhythms in the distal nephron segments, i.e., distal convoluted tubule (DCT) and connecting tubule (CNT) and the cortical collecting duct (CCD). Temporal expression analysis performed on microdissected mouse DCT/CNT or CCD revealed a marked circadian rhythmicity in the expression of a large number of genes crucially involved in various homeostatic functions of the kidney. This analysis also revealed that both DCT/CNT and CCD possess an intrinsic circadian timing system characterized by robust oscillations in the expression of circadian core clock genes (clock, bma11, npas2, per, cry, nr1d1) and clock-controlled Par bZip transcriptional factors dbp, hlf, and tef. The clock knockout mice or mice devoid of dbp/hlf/tef (triple knockout) exhibit significant changes in renal expression of several key regulators of water or sodium balance (vasopressin V2 receptor, aquaporin-2, aquaporin-4, alphaENaC). Functionally, the loss of clock leads to a complex phenotype characterized by partial diabetes insipidus, dysregulation of sodium excretion rhythms, and a significant decrease in blood pressure. Collectively, this study uncovers a major role of molecular clock in renal function.

Clinical predictors for Legionella in patients presenting with community-acquired pneumonia to the emergency department.

BACKGROUND: Legionella species cause severe forms of pneumonia with high mortality and complication rates. Accurate clinical predictors to assess the likelihood of Legionella community-acquired pneumonia (CAP) in patients presenting to the emergency department are lacking. METHODS: We retrospectively compared clinical and laboratory data of 82 consecutive patients with Legionella CAP with 368 consecutive patients with non-Legionella CAP included in two studies at the same institution. RESULTS: In multivariate logistic regression analysis we identified six parameters, namely high body temperature (OR 1.67, p < 0.0001), absence of sputum production (OR 3.67, p < 0.0001), low serum sodium concentrations (OR 0.89, p = 0.011), high levels of lactate dehydrogenase (OR 1.003, p = 0.007) and C-reactive protein (OR 1.006, p < 0.0001) and low platelet counts (OR 0.991, p < 0.0001), as independent predictors of Legionella CAP. Using optimal cut off values of these six parameters, we calculated a diagnostic score for Legionella CAP. The median score was significantly higher in Legionella CAP as compared to patients without Legionella (4 (IQR 3-4) vs 2 (IQR 1-2), p < 0.0001) with a respective odds ratio of 3.34 (95%CI 2.57-4.33, p < 0.0001). Receiver operating characteristics showed a high diagnostic accuracy of this diagnostic score (AUC 0.86 (95%CI 0.81-0.90), which was better as compared to each parameter alone. Of the 191 patients (42%) with a score of 0 or 1 point, only 3% had Legionella pneumonia. Conversely, of the 73 patients (16%) with > or =4 points, 66% of patients had Legionella CAP. CONCLUSION: Six clinical and laboratory parameters embedded in a simple diagnostic score accurately identified patients with Legionella CAP. If validated in future studies, this score might aid in the management of suspected Legionella CAP.

MGMT methylation analysis of glioblastoma on the Infinium methylation BeadChip identifies two distinct CpG regions associated with gene silencing and outcome, yielding a prediction model for comparisons across datasets, tumor grades, and CIMP-status.

The methylation status of the O(6)-methylguanine-DNA methyltransferase (MGMT) gene is an important predictive biomarker for benefit from alkylating agent therapy in glioblastoma. Recent studies in anaplastic glioma suggest a prognostic value for MGMT methylation. Investigation of pathogenetic and epigenetic features of this intriguingly distinct behavior requires accurate MGMT classification to assess high throughput molecular databases. Promoter methylation-mediated gene silencing is strongly dependent on the location of the methylated CpGs, complicating classification. Using the HumanMethylation450 (HM-450K) BeadChip interrogating 176 CpGs annotated for the MGMT gene, with 14 located in the promoter, two distinct regions in the CpG island of the promoter were identified with high importance for gene silencing and outcome prediction. A logistic regression model (MGMT-STP27) comprising probes cg1243587 and cg12981137 provided good classification properties and prognostic value (kappa = 0.85; log-rank p < 0.001) using a training-set of 63 glioblastomas from homogenously treated patients, for whom MGMT methylation was previously shown to be predictive for outcome based on classification by methylation-specific PCR. MGMT-STP27 was successfully validated in an independent cohort of chemo-radiotherapy-treated glioblastoma patients (n = 50; kappa = 0.88; outcome, log-rank p < 0.001). Lower prevalence of MGMT methylation among CpG island methylator phenotype (CIMP) positive tumors was found in glioblastomas from The Cancer Genome Atlas than in low grade and anaplastic glioma cohorts, while in CIMP-negative gliomas MGMT was classified as methylated in approximately 50 % regardless of tumor grade. The proposed MGMT-STP27 prediction model allows mining of datasets derived on the HM-450K or HM-27K BeadChip to explore effects of distinct epigenetic context of MGMT methylation suspected to modulate treatment resistance in different tumor types.

Robust accelerated failure time regression

Robust estimators for accelerated failure time models with asymmetric (or symmetric) error distribution and censored observations are proposed. It is assumed that the error model belongs to a log-location-scale family of distributions and that the mean response is the parameter of interest. Since scale is a main component of mean, scale is not treated as a nuisance parameter. A three steps procedure is proposed. In the first step, an initial high breakdown point S estimate is computed. In the second step, observations that are unlikely under the estimated model are rejected or down weighted. Finally, a weighted maximum likelihood estimate is computed. To define the estimates, functions of censored residuals are replaced by their estimated conditional expectation given that the response is larger than the observed censored value. The rejection rule in the second step is based on an adaptive cut-off that, asymptotically, does not reject any observation when the data are generat ed according to the model. Therefore, the final estimate attains full efficiency at the model, with respect to the maximum likelihood estimate, while maintaining the breakdown point of the initial estimator. Asymptotic results are provided. The new procedure is evaluated with the help of Monte Carlo simulations. Two examples with real data are discussed.

On the relationship between connections and the asymptotic properties of predictive distributions

In a recent paper, Komaki studied the second-order asymptotic properties of predictive distributions, using the Kullback-Leibler divergence as a loss function. He showed that estimative distributions with asymptotically efficient estimators can be improved by predictive distributions that do not belong to the model. The model is assumed to be a multidimensional curved exponential family. In this paper we generalize the result assuming as a loss function any f divergence. A relationship arises between alpha connections and optimal predictive distributions. In particular, using an alpha divergence to measure the goodness of a predictive distribution, the optimal shift of the estimate distribution is related to alpha-covariant derivatives. The expression that we obtain for the asymptotic risk is also useful to study the higher-order asymptotic properties of an estimator, in the mentioned class of loss functions.

Blocking hypoxia-induced autophagy in tumors restores cytotoxic T-cell activity and promotes regression.

The relationship between hypoxic stress, autophagy, and specific cell-mediated cytotoxicity remains unknown. This study shows that hypoxia-induced resistance of lung tumor to cytolytic T lymphocyte (CTL)-mediated lysis is associated with autophagy induction in target cells. In turn, this correlates with STAT3 phosphorylation on tyrosine 705 residue (pSTAT3) and HIF-1α accumulation. Inhibition of autophagy by siRNA targeting of either beclin1 or Atg5 resulted in impairment of pSTAT3 and restoration of hypoxic tumor cell susceptibility to CTL-mediated lysis. Furthermore, inhibition of pSTAT3 in hypoxic Atg5 or beclin1-targeted tumor cells was found to be associated with the inhibition Src kinase (pSrc). Autophagy-induced pSTAT3 and pSrc regulation seemed to involve the ubiquitin proteasome system and p62/SQSTM1. In vivo experiments using B16-F10 melanoma tumor cells indicated that depletion of beclin1 resulted in an inhibition of B16-F10 tumor growth and increased tumor apoptosis. Moreover, in vivo inhibition of autophagy by hydroxychloroquine in B16-F10 tumor-bearing mice and mice vaccinated with tyrosinase-related protein-2 peptide dramatically increased tumor growth inhibition. Collectively, this study establishes a novel functional link between hypoxia-induced autophagy and the regulation of antigen-specific T-cell lysis and points to a major role of autophagy in the control of in vivo tumor growth.

Prevalence, predictors, and consequences of long-term refusal of antipsychotic treatment in first-episode psychosis.

OBJECTIVE: Studies investigating medication adherence in psychosis are limited by the need of a certain degree of medication adherence and the inclusion of mostly multiple-episode patients. By contrast, noninformed consent, epidemiological studies in first-episode psychosis (FEP) allow the assessment of an important subgroup of patients who persistently refuse antipsychotic medication and thereby never receive an adequate antipsychotic trial. The present study aims to assess the prevalence and predictors of such a "medication refusal" subgroup and its association with illness outcome. METHODS: The present file audit study assessed medication adherence in an epidemiological cohort of 605 FEP patients who were treated within the Early Psychosis Prevention and Intervention Centre for up to 18 months. Medication adherence was categorized into full adherence, nonadherence, and persistent medication refusal. Predictors were analyzed using logistic regression models. RESULTS: During the 18-month treatment period, 204 patients (33.7%) were fully adherent, 287 (47.4%) displayed at least 1 phase of nonadherence, and 114 patients (18.8%) were persistent medication refusers. Poor premorbid functioning, comorbid substance use, and poor insight predicted both medication refusal and nonadherence; a forensic history and no previous contact to psychiatric care were specifically predictive of medication refusal. With respect to illness outcome, nonadherent patients were worse off when compared with fully adherent patients, and medication refusers were even worse off compared with nonadherent patients. CONCLUSIONS: Within a nonselected epidemiological FEP cohort, almost 20% of patients are persistent medication refusers. The found predictors may help to identify the individual risk of persistent medication refusal and may enable an early (preventive) treatment adaptation.

Looking for Validity or Testing It? The Perils of Stepwise Regression, Extreme-Scores Analysis, Heteroscedasticity, and Measurement Error

When researchers introduce a new test they have to demonstrate that it is valid, using unbiased designs and suitable statistical procedures. In this article we use Monte Carlo analyses to highlight how incorrect statistical procedures (i.e., stepwise regression, extreme scores analyses) or ignoring regression assumptions (e.g., heteroscedasticity) contribute to wrong validity estimates. Beyond these demonstrations, and as an example, we re-examined the results reported by Warwick, Nettelbeck, and Ward (2010) concerning the validity of the Ability Emotional Intelligence Measure (AEIM). Warwick et al. used the wrong statistical procedures to conclude that the AEIM was incrementally valid beyond intelligence and personality traits in predicting various outcomes. In our re-analysis, we found that the reliability-corrected multiple correlation of their measures with personality and intelligence was up to .69. Using robust statistical procedures and appropriate controls, we also found that the AEIM did not predict incremental variance in GPA, stress, loneliness, or well-being, demonstrating the importance for testing validity instead of looking for it.

Adapting football to the child: an application of the logistic regression model in observational mewthodology.

Logistic regression is included into the analysis techniques which are valid for observationalmethodology. However, its presence at the heart of thismethodology, and more specifically in physical activity and sports studies, is scarce. With a view to highlighting the possibilities this technique offers within the scope of observational methodology applied to physical activity and sports, an application of the logistic regression model is presented. The model is applied in the context of an observational design which aims to determine, from the analysis of use of the playing area, which football discipline (7 a side football, 9 a side football or 11 a side football) is best adapted to the child"s possibilities. A multiple logistic regression model can provide an effective prognosis regarding the probability of a move being successful (reaching the opposing goal area) depending on the sector in which the move commenced and the football discipline which is being played.

Association of major and minor ECG abnormalities with coronary heart disease events.

CONTEXT: In populations of older adults, prediction of coronary heart disease (CHD) events through traditional risk factors is less accurate than in middle-aged adults. Electrocardiographic (ECG) abnormalities are common in older adults and might be of value for CHD prediction. OBJECTIVE: To determine whether baseline ECG abnormalities or development of new and persistent ECG abnormalities are associated with increased CHD events. DESIGN, SETTING, AND PARTICIPANTS: A population-based study of 2192 white and black older adults aged 70 to 79 years from the Health, Aging, and Body Composition Study (Health ABC Study) without known cardiovascular disease. Adjudicated CHD events were collected over 8 years between 1997-1998 and 2006-2007. Baseline and 4-year ECG abnormalities were classified according to the Minnesota Code as major and minor. Using Cox proportional hazards regression models, the addition of ECG abnormalities to traditional risk factors were examined to predict CHD events. MAIN OUTCOME MEASURE: Adjudicated CHD events (acute myocardial infarction [MI], CHD death, and hospitalization for angina or coronary revascularization). RESULTS: At baseline, 276 participants (13%) had minor and 506 (23%) had major ECG abnormalities. During follow-up, 351 participants had CHD events (96 CHD deaths, 101 acute MIs, and 154 hospitalizations for angina or coronary revascularizations). Both baseline minor and major ECG abnormalities were associated with an increased risk of CHD after adjustment for traditional risk factors (17.2 per 1000 person-years among those with no abnormalities; 29.3 per 1000 person-years; hazard ratio [HR], 1.35; 95% CI, 1.02-1.81; for minor abnormalities; and 31.6 per 1000 person-years; HR, 1.51; 95% CI, 1.20-1.90; for major abnormalities). When ECG abnormalities were added to a model containing traditional risk factors alone, 13.6% of intermediate-risk participants with both major and minor ECG abnormalities were correctly reclassified (overall net reclassification improvement [NRI], 7.4%; 95% CI, 3.1%-19.0%; integrated discrimination improvement, 0.99%; 95% CI, 0.32%-2.15%). After 4 years, 208 participants had new and 416 had persistent abnormalities. Both new and persistent ECG abnormalities were associated with an increased risk of subsequent CHD events (HR, 2.01; 95% CI, 1.33-3.02; and HR, 1.66; 95% CI, 1.18-2.34; respectively). When added to the Framingham Risk Score, the NRI was not significant (5.7%; 95% CI, -0.4% to 11.8%). CONCLUSIONS: Major and minor ECG abnormalities among older adults were associated with an increased risk of CHD events. Depending on the model, adding ECG abnormalities was associated with improved risk prediction beyond traditional risk factors.

Increased tender point counts before and after total hip arthroplasty are associated with poorer outcomes but are not individually predictive.

In a prospective study, total hip arthroplasty (THA) patients were assessed preoperatively and postoperatively (n = 95) to determine if tender points (TPs) are associated with poor THA outcomes. Patients with high follow-up TP counts had higher visual analog scale (VAS) for pain and sleep, higher follow-up Western Ontario and McMaster Universities Arthritis Index (pain, stiffness, function), lower Health Assessment Questionnaire, Harris Hip, and Short Form 36 (physical functioning, bodily pain, physical component summary) scores. High follow-up TP were associated with increased pain, pain not relieved by surgery, poor function, and poor sleep. Visual analog scale pain and sleep, Short Form 36 (physical functioning, bodily pain), Western Ontario and McMaster Universities Arthritis Index, Health Assessment Questionnaire, and Harris hip scores improved significantly after THA; TP scores did not. Higher preoperative TP were predictive of higher follow-up TP but were poorly predictive of poor outcome measures after surgery in individual patients, suggesting that preoperative TPs are contraindicative for THA.