Gene/Protein Disease Symptom Drug Enzyme Compound
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Query: UMLS:C0038454 (stroke)
 147,016 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

A novel classifier was constructed in the present paper by combination of an improved canonical variates analysis (ICVA) with Fish linear discriminant analysis (LDA). The resulting discrimination model based on this proposed approach (ICVA-LDA) was divided into two parts: the inner part that estimated the robust weight vector of canonical variates by linear partial least square algorithm and the outer part that built the LDA discrimination model by making use of the extracted canonical variates. The method utilized partial least squares regression as an engine for solving an eigenvector problem involving singular covariance matrices and the canonical variates were more relevant for discriminative purposes. Thus, the weight vectors found in the modified CVA method not only possessed the same properties as weight vectors of the standard CVA method, but also forced the discriminative information into the first fewer of canonical variates. The improved discrimination model was more concise and efficient in dealing with the problem of the effect sensitivity and numerous predictor variables with serious multicollinearity in the spectra data. Furthermore, in ICVA-LDA the interpretation could be performed with respect to the original high-dimensional data space. Finally, application to a four-group problem with near-infrared transmittance spectroscopy data consisting of 310 samples and 404 variables of the proposed ICVA-LDA approach was presented with comparison to the LDA combined with principal component analysis (PCA-LDA) and standard CVA-LDA methods. All the three discrimination models were validated using fivefold segmented cross-validation. The result demonstrates that the limitations of LDA were overcome with PLS algorithm and then the classification performance of LDA was improved by ICVA. This proposed approach can also be widely used in other fields for classification and discrimination of small samples and collinear data.
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PMID:[Classification of pharmaceutical tablet with canonical variates analysis method in spectra analysis]. 1945 87

The first part of this paper gives an overview of a simplified approach to the statistical analysis of PET and fMRI data, including new developments and future directions. The second part outlines a new method, based on multivariate linear models (MLM), for characterising the response in PET and fMRI data, which overcomes some of the drawbacks of current methods such as SSM, SVD, PLS and CVA.
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PMID:An overview and some new developments in the statistical analysis of PET and fMRI data. 2040 25

Cerebral infarction is always of sudden onset, and usually leading to serious consequence. It is of therapeutic significance to develop fast and accurate diagnosis methods for cerebral infarction so that patients can be treated timely and properly. A metabonomic approach was then proposed to investigate the potential biomarkers and metabolic pathways associated with cerebral infarction and also establish a prediction model of cerebral infarction for the fast diagnosis. Serum metabolic profiling of sixty-seven cerebral infarction patients and sixty-two controls was obtained using UPLC-TOF MS. The resulting data were then processed by multivariate statistical analysis to graphically demonstrate metabolic variations. The PLS-DA model was validated with cross validation and permutation tests to assure the model's reliability, and significant difference was obtained between the original and hypothetical models (p<0.0001). A series of endogenous metabolites in the one-carbon cycle, such as folic acid, cysteine, S-adenosyl homocysteine and oxidized glutathione, were determined as potential biomarkers of cerebral infarction. A prediction model developed using PLS-KNN algorithm was established to differentiate cerebral infarction patients from controls, and an average accuracy of 100% was obtained. In conclusion, metabonomic approach is a powerful tool to investigate the pathogenesis of stroke and is expected to be developed as a useful method for the fast diagnosis.
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PMID:A metabonomic approach applied to predict patients with cerebral infarction. 2137 48

Gravity compensation (GC) of the arm is used to facilitate arm movements in conventional therapy as well as in robot-assisted rehabilitation of neurologically impaired persons. Positive effects of GC on Range of Motion (ROM) have been demonstrated in stroke. In Multiple Sclerosis (MS), research regarding this topic is lacking. Since an active participation of the patient is required for effective training, full support of the arm might not be advisable. The present study reports on the development of a procedure to measure actively the individual need for GC and to estimate the influence of GC on ROM during reaching, lifting and transporting in severely affected Persons with MS (PwMS). Ten PwMS were tested with the procedure for determination of GC. Maximal reaching movements were performed in a 3D space in three conditions: No support (NS), with GC by the HapticMaster (GC-HM) and with GC by the HapticMaster combined with a sling suspension system (GC-HMS). For the total sample, significant correlations were found between the amount of GC and clinical tests for upper limb function. In four subjects with severe arm dysfunction it was found that mean ROM is larger in the GC-HMS condition compared to the GC-HM condition, and in the GC-HM condition compared to the NS condition, suggesting positive effects of GC on active ROM in PwMS. Therefore, GC could have a positive effect on arm rehabilitation by enabling the PwMS to actively reach a larger ROM during training.
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PMID:Facilitating robot-assisted training in MS patients with arm paresis: a procedure to individually determine gravity compensation. 2227 3

The objective of the present study was to assess the comparable applicability of orthogonal projections to latent structures (OPLS) statistical model vs traditional linear regression in order to investigate the role of trans cranial doppler (TCD) sonography in predicting ischemic stroke prognosis. The study was conducted on 116 ischemic stroke patients admitted to a specialty neurology ward. The Unified Neurological Stroke Scale was used once for clinical evaluation on the first week of admission and again six months later. All data was primarily analyzed using simple linear regression and later considered for multivariate analysis using PLS/OPLS models through the SIMCA P+12 statistical software package. The linear regression analysis results used for the identification of TCD predictors of stroke prognosis were confirmed through the OPLS modeling technique. Moreover, in comparison to linear regression, the OPLS model appeared to have higher sensitivity in detecting the predictors of ischemic stroke prognosis and detected several more predictors. Applying the OPLS model made it possible to use both single TCD measures/indicators and arbitrarily dichotomized measures of TCD single vessel involvement as well as the overall TCD result. In conclusion, the authors recommend PLS/OPLS methods as complementary rather than alternative to the available classical regression models such as linear regression.
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PMID:OPLS statistical model versus linear regression to assess sonographic predictors of stroke prognosis. 2297 4

Recently, the pharmaceutical industry has shifted to pursuing combination therapies that comprise more than one active ingredient. Interestingly, combination therapies have been used for more than 2500 years in traditional Chinese medicine (TCM). Understanding optimal proportions and synergistic mechanisms of multi-component drugs are critical for developing novel strategies to combat complex diseases. A new multi-objective optimization algorithm based on least angle regression-partial least squares was proposed to construct the predictive model to evaluate the synergistic effect of the three components of a novel combination drug Yi-qi-jie-du formula (YJ), which came from clinical TCM prescription for the treatment of encephalopathy. Optimal proportion of the three components, ginsenosides (G), berberine (B) and jasminoidin (J) was determined via particle swarm optimum. Furthermore, the combination mechanisms were interpreted using PLS VIP and principal components analysis. The results showed that YJ had optimal proportion 3(G): 2(B): 0.5(J), and it yielded synergy in the treatment of rats impaired by middle cerebral artery occlusion induced focal cerebral ischemia. YJ with optimal proportion had good pharmacological effects on acute ischemic stroke. The mechanisms study demonstrated that the combination of G, B and J could exhibit the strongest synergistic effect. J might play an indispensable role in the formula, especially when combined with B for the acute stage of stroke. All these data in this study suggested that in the treatment of acute ischemic stroke, besides restoring blood supply and protecting easily damaged cells in the area of the ischemic penumbra as early as possible, we should pay more attention to the removal of the toxic metabolites at the same time. Mathematical system modeling may be an essential tool for the analysis of the complex pharmacological effects of multi-component drug. The powerful mathematical analysis method could greatly improve the efficiency in finding new combination drug from TCM.
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PMID:An effective solution to discover synergistic drugs for anti-cerebral ischemia from traditional Chinese medicinal formulae. 2423 65

The use of combination drugs is considered to be a promising strategy to control complex diseases such as ischemic stroke. The detection of metabolites has been used as a versatile tool to reveal the potential mechanism of diverse diseases. In this study, the levels of 12 endogenous AAs were simultaneously determined quantitatively in the MCAO rat brain using RRLC-QQQ method. Seven AAs were chosen as the potential biomarkers, and using PLS-DA analysis, the effects of the new combination drug YQJD, which is composed of ginsenosides, berberine, and jasminoidin, on those 7 AAs were evaluated. Four AAs, glutamic acid, homocysteine, methionine, and tryptophan, which changed significantly in the YQJD-treated groups compared to the vehicle groups (P < 0.05), were identified and designated as the AAs to use to further explore the synergism of YQJD. The result of a PCA showed that the combination of these three drugs exhibits the strongest synergistic effect compared to other combination groups and that ginsenosides might play a pivotal role, especially when combined with jasminoidin. We successfully explored the synergetic mechanism of multi-component and provided a new method for evaluating the integrated effects of combination drugs in the treatment of complex diseases.
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PMID:Synergism and rules of the new combination drug Yiqijiedu formulae (YQJD) on ischemic stroke based on amino acids (AAs) metabolism. 2488 25

OBJECTIVE Carotid artery stenting (CAS) has been considered to prevent ischemic strokes caused by stenosis of the cervical carotid artery. The most common complication of CAS is new cerebral infarction. The authors have previously reported that the jellyfish sign-the rise and fall of the mobile component of the carotid plaque surface detected by carotid ultrasonography-suggests thinning and rupture of the fibrous cap over the unstable plaque content, such as the lipid-rich necrotic core or internal plaque hemorrhage. The authors' aim in the present study was to evaluate the risk of a new ischemic lesion after CAS by using many risk factors including calcification (size and location) and the jellyfish sign. METHODS Eighty-six lesions (77 patients) were treated with CAS. The presence of ischemic stroke was determined using diffusion-weighted imaging (DWI). Risk factors included calcification of the plaque (classified into 5 groups for size and 3 groups for location) and the jellyfish sign, among others. Multiple linear regression analysis (stepwise analysis and partial least squares [PLS] analysis) was conducted, followed by a machine learning analysis using an artificial neural network (ANN) based on the log-linearized gaussian mixture network (LLGMN). The additive effects of the jellyfish sign and calcification on ischemic stroke after CAS were examined using the Kruskal-Wallis test, followed by the Steel-Dwass test. RESULTS The stepwise analysis selected the jellyfish sign, proximal calcification (proximal Ca), low-density lipoprotein (LDL) cholesterol, and patient age for the prediction model to predict new DWI lesions. The PLS analysis revealed the same top 3 variables (jellyfish sign, proximal Ca, and LDL cholesterol) according to the variable importance in projection scores. The ANN was then used, showing that these 3 variables remained. The accuracy of the ANN improved; areas under the receiver operating characteristic curves of the stepwise analysis, the PLS analysis, and the ANN were 0.719, 0.727, and 0.768, respectively. The combination of the jellyfish sign and proximal Ca indicates a significantly increased risk for ischemic stroke after CAS. CONCLUSIONS The jellyfish sign, proximal Ca, and LDL cholesterol were considered to be important predictors for new DWI lesions after CAS. These 3 factors can be easily determined during a standard clinical visit. Thus, these 3 variables-especially the jellyfish sign and proximal Ca-may be useful for reducing the ischemic stroke risk in patients with stenosis of the cervical carotid artery.
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PMID:Predicting ischemic stroke after carotid artery stenting based on proximal calcification and the jellyfish sign. 2868 17

The global epidemic of cardiovascular diseases leads to increased morbidity and mortality caused mainly by myocardial infarction and stroke. Atherosclerosis is the major pathological process behind this epidemic. We designed a novel model of atherosclerosis in swine. Briefly, the first group (11 pigs) received normal pig feed (balanced diet group-BDG) for 12 months, the second group (9 pigs) was fed a Western high-calorie diet (unbalanced diet group-UDG) for 12 months, the third group (8 pigs) received a Western type high-calorie diet for 9 months later replaced by a normal diet for 3 months (regression group-RG). Clinical measurements included zoometric data, arterial blood pressure, heart rate and ultrasonographic evaluation of femoral arteries. Then, the animals were sacrificed and the blood serum, urine and skeletal muscle tissue were collected and 1H NMR based metabolomics studies with the application of fingerprinting PLS-DA and univariate analysis were done. Our results have shown that the molecular disturbances might overlap with other diseases such as onset of diabetes, sleep apnea and other obesity accompanied diseases. Moreover, we revealed that once initiated, molecular changes did not return to homeostatic equilibrium, at least for the duration of this experiment.
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PMID:The influence of different diets on metabolism and atherosclerosis processes-A porcine model: Blood serum, urine and tissues 1H NMR metabolomics targeted analysis. 2899 97

Metabolic syndrome (MetS) represents a group of abnormalities that enhances the risk for cardiovascular disease, diabetes and stroke. The Mediterranean diet seems to be an important dietary pattern, which reduces the incidence of MetS. Hydroxytyrosol (HT) - a simple phenol found in olive oil - has received increased attention for its antioxidant activity. Recently, the European Foods Safety Authority (EFSA) claimed that dietary consumption of HT exhibits a protective role against cardiovascular disease. In this study, an experimental protocol has been setup, including isolated HT administration in a diet induced model of MetS in young Wistar rats, in order to find out whether HT has a protective effect against MetS. Rats were randomly divided into two groups nurtured by high-carbohydrate high-fat (H) (MetS inducing diet) and high-carbohydrate high-fat + HT (HHT). HT (20mg/kg/d oral gavage, water vehicle) was administered for 8 weeks on the basal diet. Previous pharmacological evaluation of HT showed that hepatic steatosis was reduced and the inflammatory cells into the liver were infiltrated. These indicate that HT shows bioactivity against metabolic syndrome. Therefore, the metabolomics evaluation of liver extracts would indicate the putative biochemical mechanisms of HT activity. Thus, the extracts of liver tissues were analyzed using Ultra Performance Liquid Chromatography - High Resolution Mass Spectrometry (UPLC-HRMS, Orbitrap Discovery) and Nuclear Magnetic Resonance (NMR) spectroscopy (Bruker Avance III 600MHz). Multivariate analysis was performed in order to gain insight on the metabolic effects of HT administration on the liver metabolome. Normalization employing multiple internal standards and Quality Control-based Robust LOESS (LOcally Estimated Scatterplot Smoothing) Signal Correction algorithm (QC-RLSC) was added in the processing pipeline to enhance the reliability of metabolomic analysis by reducing unwanted information. Experimentally, HHT rats were clearly distinguished from H in PLS-DA, showing differences in the liver metabolome between the groups and specific biomarkers were determined supporting the pharmacological findings. More specifically, HT has shown to be effective towards the mobilization of lipids as various lipid classes being differentially regulated between the H and HHT groups. Interestingly branched fatty acid esters of hydroxy oleic acids (OAHSA) lipids have been shown to be up regulated to the HHT group, denoting the alleviation of the MetS to the animals administered with HT.
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PMID:Alteration in the liver metabolome of rats with metabolic syndrome after treatment with Hydroxytyrosol. A Mass Spectrometry And Nuclear Magnetic Resonance - based metabolomics study. 2913 19


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