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.

An evaluation of volume-based morphometry for prediction of mild cognitive impairment and Alzheimer's disease.

Voxel-based morphometry from conventional T1-weighted images has proved effective to quantify Alzheimer's disease (AD) related brain atrophy and to enable fairly accurate automated classification of AD patients, mild cognitive impaired patients (MCI) and elderly controls. Little is known, however, about the classification power of volume-based morphometry, where features of interest consist of a few brain structure volumes (e.g. hippocampi, lobes, ventricles) as opposed to hundreds of thousands of voxel-wise gray matter concentrations. In this work, we experimentally evaluate two distinct volume-based morphometry algorithms (FreeSurfer and an in-house algorithm called MorphoBox) for automatic disease classification on a standardized data set from the Alzheimer's Disease Neuroimaging Initiative. Results indicate that both algorithms achieve classification accuracy comparable to the conventional whole-brain voxel-based morphometry pipeline using SPM for AD vs elderly controls and MCI vs controls, and higher accuracy for classification of AD vs MCI and early vs late AD converters, thereby demonstrating the potential of volume-based morphometry to assist diagnosis of mild cognitive impairment and Alzheimer's disease.

Construct validity and internal reliability of a French version of FACES III in adolescents and adults

Family cohesion and adaptability, as operationalised in the Family Adaptability and Cohesion Scales III (FACES III), are two hypothesised dimensions of family functioning. We tested the properties of a French version of FACES III in school-children (mean age: 13 years; S.D:0.85) recruited from the general population and their parents. Separate confirmatory factor analyses were performed for adolescents and adults. The results of both analyses were compatible with a two-factor structure similar to that proposed by the authors of the original instrument. However, orthogonality between the two factors was only supported in the adult data. Internal reliability estimates were 0.78 and 0.68 in adolescents and 0.82 and 0.65 in adults, for cohesion and adaptability respectively.

Identification of human IKK-2 inhibitors of natural origin (Part II): in Silico prediction of IKK-2 inhibitors in natural extracts with known anti-inflammatory activity.

Human inhibitor NF-κB kinase 2 (hIKK-2) is the primary component responsible for activating NF-κB in response to various inflammatory stimuli. Thus, synthetic ATP-competitive inhibitors for hIKK-2 have been developed as anti-inflammatory compounds. We recently reported a virtual screening protocol (doi:10.1371/journal.pone.0016903) that is able to identify hIKK-2 inhibitors that are not structurally related to any known molecule that inhibits hIKK-2 and that have never been reported to have anti-inflammatory activity. In this study, a stricter version of this protocol was applied to an in-house database of 29,779 natural products annotated with their natural source. The search identified 274 molecules (isolated from 453 different natural extracts) predicted to inhibit hIKK-2. An exhaustive bibliographic search revealed that anti-inflammatory activity has been previously described for: (a) 36 out of these 453 extracts; and (b) 17 out of 30 virtual screening hits present in these 36 extracts. Only one of the remaining 13 hit molecules in these extracts shows chemical similarity with known synthetic hIKK-2 inhibitors. Therefore, it is plausible that a significant portion of the remaining 12 hit molecules are lead-hopping candidates for the development of new hIKK-2 inhibitors.

Treatment of ruptured abdominal aortic aneurysm, a permanent challenge or a waste of resources? Prediction of outcome using a multi-organ-dysfunction score.

OBJECTIVES: in a retrospective study, attempts have been made to identify individual organ-dysfunction risk profiles influencing the outcome after surgery for ruptured abdominal aortic aneurysms. METHODS: out of 235 patients undergoing graft replacement for abdominal aortic aneurysms, 57 (53 men, four women, mean age 72 years [s.d. 8.8]) were treated for ruptured aneurysms in a 3-year period. Forty-eight preoperative, 13 intraoperative and 34 postoperative variables were evaluated statistically. A simple multi-organ dysfunction (MOD) score was adopted. RESULTS: the perioperative mortality was 32%. Three patients died intraoperatively, four within 48 h and 11 died later. A significant influence for pre-existing risk factors was identified only for cardiovascular diseases. Multiple linear-regression analysis indicated that a haemoglobin <90 g/l, systolic blood pressure <80 mmHg and ECG signs of ischaemia at admission were highly significant risk factors. The cause of death for patients, who died more than 48 h postoperatively, was mainly MOD. All patients with a MOD score >/=4 died (n=7). These patients required 27% of the intensive-care unit (ICU) days of all patients and 72% of the ICU days of the non-survivors. CONCLUSION: patients with ruptured aortic aneurysms from treatment should not be excluded. However, a physiological scoring system after 48 h appears justifiable in order to decide on the appropriateness of continual ICU support.

Individual prediction of cognitive decline in mild cognitive impairment using support vector machine-based analysis of diffusion tensor imaging data.

Although cross-sectional diffusion tensor imaging (DTI) studies revealed significant white matter changes in mild cognitive impairment (MCI), the utility of this technique in predicting further cognitive decline is debated. Thirty-five healthy controls (HC) and 67 MCI subjects with DTI baseline data were neuropsychologically assessed at one year. Among them, there were 40 stable (sMCI; 9 single domain amnestic, 7 single domain frontal, 24 multiple domain) and 27 were progressive (pMCI; 7 single domain amnestic, 4 single domain frontal, 16 multiple domain). Fractional anisotropy (FA) and longitudinal, radial, and mean diffusivity were measured using Tract-Based Spatial Statistics. Statistics included group comparisons and individual classification of MCI cases using support vector machines (SVM). FA was significantly higher in HC compared to MCI in a distributed network including the ventral part of the corpus callosum, right temporal and frontal pathways. There were no significant group-level differences between sMCI versus pMCI or between MCI subtypes after correction for multiple comparisons. However, SVM analysis allowed for an individual classification with accuracies up to 91.4% (HC versus MCI) and 98.4% (sMCI versus pMCI). When considering the MCI subgroups separately, the minimum SVM classification accuracy for stable versus progressive cognitive decline was 97.5% in the multiple domain MCI group. SVM analysis of DTI data provided highly accurate individual classification of stable versus progressive MCI regardless of MCI subtype, indicating that this method may become an easily applicable tool for early individual detection of MCI subjects evolving to dementia.

Experimental analysis and computer prediction of CTF/NFI transcription factor DNA binding sites.

Accurate prediction of transcription factor binding sites is needed to unravel the function and regulation of genes discovered in genome sequencing projects. To evaluate current computer prediction tools, we have begun a systematic study of the sequence-specific DNA-binding of a transcription factor belonging to the CTF/NFI family. Using a systematic collection of rationally designed oligonucleotides combined with an in vitro DNA binding assay, we found that the sequence specificity of this protein cannot be represented by a simple consensus sequence or weight matrix. For instance, CTF/NFI uses a flexible DNA binding mode that allows for variations of the binding site length. From the experimental data, we derived a novel prediction method using a generalised profile as a binding site predictor. Experimental evaluation of the generalised profile indicated that it accurately predicts the binding affinity of the transcription factor to natural or synthetic DNA sequences. Furthermore, the in vitro measured binding affinities of a subset of oligonucleotides were found to correlate with their transcriptional activities in transfected cells. The combined computational-experimental approach exemplified in this work thus resulted in an accurate prediction method for CTF/NFI binding sites potentially functioning as regulatory regions in vivo.

Improvement of cardiovascular risk prediction: time to review current knowledge, debates, and fundamentals on how to assess test characteristics.

Cardiovascular risk assessment might be improved with the addition of emerging, new tests derived from atherosclerosis imaging, laboratory tests or functional tests. This article reviews relative risk, odds ratios, receiver-operating curves, posttest risk calculations based on likelihood ratios, the net reclassification improvement and integrated discrimination. This serves to determine whether a new test has an added clinical value on top of conventional risk testing and how this can be verified statistically. Two clinically meaningful examples serve to illustrate novel approaches. This work serves as a review and basic work for the development of new guidelines on cardiovascular risk prediction, taking into account emerging tests, to be proposed by members of the 'Taskforce on Vascular Risk Prediction' under the auspices of the Working Group 'Swiss Atherosclerosis' of the Swiss Society of Cardiology in the future.

Detecting and measuring deprivation in primary care: development, validity and reliability of a self-reported questionnaire - the DiPCare-Q

Background: General practitioners play a central role in taking deprivation into consideration when caring for patients in primary care. Validated questions to identify deprivation in primary-care practices are still lacking. For both clinical and research purposes, this study therefore aims to develop and validate a standardized instrument measuring both material and social deprivation at an individual level. Methods: The Deprivation in Primary Care Questionnaire (DiPCare-Q) was developed using qualitative and quantitative approaches between 2008 and 2011. A systematic review identified 199 questions related to deprivation. Using judgmental item quality, these were reduced to 38 questions. Two focus groups (primary-care physicians, and primary-care researchers), structured interviews (10 laymen), and think aloud interviews (eight cleaning staff) assured face validity. Item response theory analysis was then used to derive the DiPCare-Q index using data obtained from a random sample of 200 patients who were to complete the questionnaire a second time over the phone. For construct and criterion validity, the final 16 questions were administered to a random sample of 1,898 patients attending one of 47 different private primary-care practices in western Switzerland (validation set) along with questions on subjective social status (subjective SES ladder), education, source of income, welfare status, and subjective poverty. Results: Deprivation was defined in three distinct dimensions (table); material deprivation (eight items), social deprivation (five items) and health deprivation (three items). Item consistency was high in both the derivation (KR20 = 0.827) and the validation set (KR20 = 0.778). The DiPCare-Q index was reliable (ICC = 0.847). For construct validity, we showed the DiPCare-Q index to be correlated to patients' estimation of their position on the subjective SES ladder (rs = 0.539). This position was correlated to both material and social deprivation independently suggesting two separate mechanisms enhancing the feeling of deprivation. Conclusion: The DiPCare-Q is a rapid, reliable and validated instrument useful for measuring both material and social deprivation in primary care. Questions from the DiPCare-Q are easy to use when investigating patients' social history and could improve clinicians' ability to detect underlying social distress related to deprivation.

Prediction of Recanalization Trumps Prediction of Tissue Fate: The Penumbra: A Dual-edged Sword.

BACKGROUND AND PURPOSE: To determine whether infarct core or penumbra is the more significant predictor of outcome in acute ischemic stroke, and whether the results are affected by the statistical method used. METHODS: Clinical and imaging data were collected in 165 patients with acute ischemic stroke. We reviewed the noncontrast head computed tomography (CT) to determine the Alberta Score Program Early CT score and assess for hyperdense middle cerebral artery. We reviewed CT-angiogram for site of occlusion and collateral flow score. From perfusion-CT, we calculated the volumes of infarct core and ischemic penumbra. Recanalization status was assessed on early follow-up imaging. Clinical data included age, several time points, National Institutes of Health Stroke Scale at admission, treatment type, and modified Rankin score at 90 days. Two multivariate regression analyses were conducted to determine which variables predicted outcome best. In the first analysis, we did not include recanalization status among the potential predicting variables. In the second, we included recanalization status and its interaction between perfusion-CT variables. RESULTS: Among the 165 study patients, 76 had a good outcome (modified Rankin score ≤2) and 89 had a poor outcome (modified Rankin score >2). In our first analysis, the most important predictors were age (P<0.001) and National Institutes of Health Stroke Scale at admission (P=0.001). The imaging variables were not important predictors of outcome (P>0.05). In the second analysis, when the recanalization status and its interaction with perfusion-CT variables were included, recanalization status and perfusion-CT penumbra volume became the significant predictors (P<0.001). CONCLUSIONS: Imaging prediction of tissue fate, more specifically imaging of the ischemic penumbra, matters only if recanalization can also be predicted.

Development and validation of a clinical prediction rule for chest wall syndrome in primary care.

ABSTRACT: BACKGROUND: Chest wall syndrome (CWS), the main cause of chest pain in primary care practice, is most often an exclusion diagnosis. We developed and evaluated a clinical prediction rule for CWS. METHODS: Data from a multicenter clinical cohort of consecutive primary care patients with chest pain were used (59 general practitioners, 672 patients). A final diagnosis was determined after 12 months of follow-up. We used the literature and bivariate analyses to identify candidate predictors, and multivariate logistic regression was used to develop a clinical prediction rule for CWS. We used data from a German cohort (n = 1212) for external validation. RESULTS: From bivariate analyses, we identified six variables characterizing CWS: thoracic pain (neither retrosternal nor oppressive), stabbing, well localized pain, no history of coronary heart disease, absence of general practitioner's concern, and pain reproducible by palpation. This last variable accounted for 2 points in the clinical prediction rule, the others for 1 point each; the total score ranged from 0 to 7 points. The area under the receiver operating characteristic (ROC) curve was 0.80 (95% confidence interval 0.76-0.83) in the derivation cohort (specificity: 89%; sensitivity: 45%; cut-off set at 6 points). Among all patients presenting CWS (n = 284), 71% (n = 201) had a pain reproducible by palpation and 45% (n = 127) were correctly diagnosed. For a subset (n = 43) of these correctly classified CWS patients, 65 additional investigations (30 electrocardiograms, 16 thoracic radiographies, 10 laboratory tests, eight specialist referrals, one thoracic computed tomography) had been performed to achieve diagnosis. False positives (n = 41) included three patients with stable angina (1.8% of all positives). External validation revealed the ROC curve to be 0.76 (95% confidence interval 0.73-0.79) with a sensitivity of 22% and a specificity of 93%. CONCLUSIONS: This CWS score offers a useful complement to the usual CWS exclusion diagnosing process. Indeed, for the 127 patients presenting CWS and correctly classified by our clinical prediction rule, 65 additional tests and exams could have been avoided. However, the reproduction of chest pain by palpation, the most important characteristic to diagnose CWS, is not pathognomonic.

Détermination de l'antigène HLA-G soluble dans le liquide folliculaire et dans le milieu de culture d'embryons comme indicateur du succès d'un traitement par FIV-ICSI [Soluble human leukocyte antigen-G (sHLA-G) in follicular fluid and embryo culture medium and its impact on pregnancy prediction in IVF-ICSI treatment]

In IVF around 70% of embryos fail to implant. Often more than one embryo is transferred in order to enhance the chances of pregnancy, but this is at the price of an increased multiple pregnancy risk. In the aim to increase the success rate with a single embryo, research projects on prognostic factors of embryo viability have been initiated, but no marker has found a routine clinical application to date. Effects of soluble human leukocyte antigen-G (sHLA-G) on both NK cell activity and on Th1/Th2 cytokine balance suggest a role in the embryo implantation process, but the relevance of sHLA-G measurements in embryo culture medium and in follicular fluid (FF) are inconsistent to date. In this study, we have investigated the potential of sHLA-G in predicting the achievement of a pregnancy after IVF-ICSI in a large number of patients (n = 221). sHLA-G was determined in media and in FF by ELISA. In both FF and embryo medium, no significant differences in sHLA-G concentrations were observed between the groups "pregnancy" and "implantation failure", or between the groups "ongoing" versus "miscarried pregnancies". Our results do not favour routine sHLA-G determinations in the FF nor in embryo conditioned media, with the current assay technology available.

The family alliance assessment scales : steps toward validity and reliability of an observational assessment tool for early family interactions

We present the first steps in the validation of an observational tool for father-mother-infant interactions: the FAAS (Family Alliance Assessment Scales). Family-level variables are acknowledged as unique contributors to the understanding of the socio-affective development of the child, yet producing reliable assessments of family-level interactions poses a methodological challenge. There is, therefore, a clear need for a validated and clinically relevant tool. This validation study has been carried out on three samples: one non-referred sample, of families taking part in a study on the transition to parenthood (normative sample; n = 30), one referred for medically assisted procreation (infertility sample; n = 30) and one referred for a psychiatric condition in one parent (clinical sample; n = 15). Results show that the FAAS scales have (1) good inter-rater reliability and (2) good validity, as assessed through known-group validity by comparing the three samples and through concurrent validity by checking family interactions against parents' self-reported marital satisfaction.