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.

Thrombin-induced ischemic tolerance is prevented by inhibiting c-jun N-terminal kinase.

We have studied ischemic tolerance induced by the serine protease thrombin in two different models of experimental ischemia. In organotypic hippocampal slice cultures, we demonstrate that incubation with low doses of thrombin protects neurons against a subsequent severe oxygen and glucose deprivation. L-JNKI1, a highly specific c-jun N-terminal kinase (JNK) inhibitor, and a second specific JNK inhibitor, SP600125, prevented thrombin preconditioning (TPC). We also show that the exposure to thrombin increases the level of phosphorylated c-jun, the major substrate of JNK. TPC, in vivo, leads to significantly smaller lesion sizes after a 30-min middle cerebral artery occlusion (MCAo), and the preconditioned mice were better off in the three tests used to evaluate functional recovery. In accordance with in vitro results, TPC in vivo was prevented by administration of L-JNKI1, supporting a role for JNK in TPC. These results, from two different TPC models and with two distinct JNK inhibitors, show that JNK is likely to be involved in TPC.

RIP4 (DIK/PKK), a novel member of the RIP kinase family, activates NF-kappa B and is processed during apoptosis.

RIP1 and its homologs, RIP2 and RIP3, form part of a family of Ser/Thr kinases that regulate signal transduction processes leading to NF-kappa B activation. Here, we identify RIP4 (DIK/PKK) as a novel member of the RIP kinase family. RIP4 contains an N-terminal RIP-like kinase domain and a C-terminal region characterized by the presence of 11 ankyrin repeats. Overexpression of RIP4 leads to activation of NF-kappa B and JNK. Kinase inactive RIP4 or a truncated version containing the ankyrin repeats have a dominant negative (DN) effect on NF-kappa B induction by multiple stimuli. RIP4 binds to several members of the TRAF protein family, and DN versions of TRAF1, TRAF3 and TRAF6 inhibit RIP4-induced NF-kappa B activation. Moreover, RIP4 is cleaved after Asp340 and Asp378 during Fas-induced apoptosis. These data suggest that RIP4 is involved in NF-kappa B and JNK signaling and that caspase-dependent processing of RIP4 may negatively regulate NF-kappa B-dependent pro-survival or pro-inflammatory signals.

Multivariate prediction

The problem of prediction is considered in a multidimensional setting. Extending an idea presented by Barndorff-Nielsen and Cox, a predictive density for a multivariate random variable of interest is proposed. This density has the form of an estimative density plus a correction term. It gives simultaneous prediction regions with coverage error of smaller asymptotic order than the estimative density. A simulation study is also presented showing the magnitude of the improvement with respect to the estimative method.

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.

PHYTOCHROME KINASE SUBSTRATE1 regulates root phototropism and gravitropism.

Light promotes the expression of PHYTOCHROME KINASE SUBSTRATE1 (PKS1) in the root of Arabidopsis thaliana, but the function of PKS1 in this organ is unknown. Unilateral blue light induced a negative root phototropic response mediated by phototropin 1 in wild-type seedlings. This response was absent in pks1 mutants. In the wild type, unilateral blue light enhanced PKS1 expression in the subapical region of the root several hours before bending was detectable. The negative phototropism and the enhanced PKS1 expression in response to blue light required phytochrome A (phyA). In addition, the pks1 mutation enhanced the root gravitropic response when vertically oriented seedlings were placed horizontally. The negative regulation of gravitropism by PKS1 occurred even in dark-grown seedlings and did not require phyA. Blue light also failed to induce negative phototropism in pks1 under reduced gravitational stimulation, indicating that the effect of pks1 on phototropism is not simply the consequence of the counteracting effect of enhanced gravitropism. We propose a model where the background level of PKS1 reduces gravitropism. After a phyA-dependent increase in its expression, PKS1 positively affects root phototropism and both effects contribute to negative curvature in response to unilateral blue light.

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.

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.

Insulin and IGF-1 enhance the expression of the neuronal monocarboxylate transporter MCT2 by translational activation via stimulation of the phosphoinositide 3-kinase-Akt-mammalian target of rapamycin pathway.

MCT2 is the main neuronal monocarboxylate transporter essential for facilitating lactate and ketone body utilization as energy substrates. Our study reveals that treatment of cultured cortical neurons with insulin and IGF-1 led to a striking enhancement of MCT2 immunoreactivity in a time- and concentration-dependent manner. Surprisingly, neither insulin nor IGF-1 affected MCT2 mRNA expression, suggesting that regulation of MCT2 protein expression occurs at the translational rather than the transcriptional level. Investigation of the putative signalling pathways leading to translation activation revealed that insulin and IGF-1 induced p44- and p42 MAPK, Akt and mTOR phosphorylation. S6 ribosomal protein, a component of the translational machinery, was also strongly activated by insulin and IGF-1. Phosphorylation of p44- and p42 MAPK was blocked by the MEK inhibitor PD98058, while Akt phosphorylation was abolished by the PI3K inhibitor LY294002. Phosphorylation of mTOR and S6 was blocked by the mTOR inhibitor rapamycin. In parallel, it was observed that LY294002 and rapamycin almost completely blocked the effects of insulin and IGF-1 on MCT2 protein expression, whereas PD98059 and SB202190 (a p38K inhibitor) had no effect on insulin-induced MCT2 expression and only a slight effect on IGF-1-induced MCT2 expression. At the subcellular level, a significant increase in MCT2 protein expression within an intracellular pool was observed while no change at the cell surface was apparent. As insulin and IGF-1 are involved in synaptic plasticity, their effect on MCT2 protein expression via an activation of the PI3K-Akt-mTOR-S6K pathway might contribute to the preparation of neurons for enhanced use of nonglucose energy substrates following altered synaptic efficacy.

Cardiovascular drug interactions with tyrosine kinase inhibitors

Imatinib mesylate, a selective inhibitor of tyrosine kinases, has excellent efficacy in the treatment of chronic myeloid leukaemia (CML) and gastrointestinal stromal tumour (GIST). Inducing durable responses and achieving prolonged survival, it has become the standard of care for the treatment of these diseases. It has opened the way to the development of additional tyrosine kinase inhibitors (TKIs), including sunitinib, nilotinib, dasatinib and sorafenib, all indicated for the treatment of various haematological malignancies and solid tumours. TKIs are prescribed for prolonged periods and are often taken by patients with - notably cardiovascular - comorbidities. Hence TKIs are regularly co-administered with cardiovascular drugs, with a considerable risk of potentially harmful drug-drug interactions due to the large number of agents used in combination. However, this aspect has received limited attention so far, and a comprehensive review of the published data on this important topic has been lacking. We review here the available data and pharmacological mechanisms of interactions between commonly prescribed cardiovascular drugs and the TKIs marketed at present. Regular updating of the literature on this topic will be mandatory, as will the prospective reporting of unexpected clinical observations, given the fact that these drugs have been only recently marketed.