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Previous studies have reported that individual variation in N1 amplitude is related to attentional problems and alcoholism. Using data from 651 twins and siblings from 292 families we examined whether variation in N1 amplitude and latency can be explained by genetic factors. In half of the subjects the age centered around 26 (young adult cohort), in the other half the age centered around 49 (middle-aged adult cohort). Two visual N1 components were identified by a spatial PCA -- an early anterior component peaking from 88 to 168 ms after stimulus presentation and a posterior one peaking from 132 to 220 ms. Significant heritability was found for anterior N1 amplitude (22%) and posterior amplitude (50%), and for anterior latency (45%) and posterior latency (43%). We conclude that visual N1 amplitude and latency may serve as endophenotypes to detect genetic variation in susceptibility to psychiatric disorders.
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PMID:Heritability of anterior and posterior visual N1. 1766 32

Alcoholism is a complex disorder that, in man, appears to be genetically influenced, although the underlying genes and molecular pathways are not completely known. Here, the intragastric alcohol feeding model in rodents was used together with high mass accuracy LC-MS(n) analysis to assess the metabonomic changes in nonpolar metabolite profiles for livers from control and alcohol-treated rats and mice. Ion signals with a peak area variance of less than 30% (based on repeat analysis of a pooled quality control sample analyzed throughout the batch) were submitted to multivariate statistical analysis (using principal components analysis, PCA). PCA revealed robust differences between profiles from control and alcohol-treated animals from both species. The major metabolites seen to differ between control and alcohol-treated animals were identified using high accuracy MS(n) data and verified using external search engines ( http://www.lipidmaps.org ; http://www.hmdb.ca; http://www.genome.jp/kegg/ ) and authentic standards. The main metabolite classes to show major changes in the alcoholic liver-derived samples were fatty acyls, fatty acid ethyl esters, glycerolipids, and phosphatidylethanol homologues. Significant metabolites that were up-regulated by alcohol treatment in both rat and mouse livers included fatty acyls, metabolites such as octadecatrienoic acid and eicosapentaenoic acid, a number of fatty acid ethyl esters such as ethyl arachidonate, ethyl docosahexaenoic acid, ethyl linoleate, and ethyl oleate and phosphatidylethanol (PEth) homologues (predominantly PEth 18:0/18:2 and PEth 16:0/18:2; PEth homologues are currently considered as potential biomarkers for harmful and prolonged alcohol consumption in man). A number of glycerophospholipids resulted in both up-regulation (m/z 903.7436 [M + H](+) corresponding to a triglyceride) and down-regulation (m/z 667.5296 [M + H](+) corresponding to a diglyceride). Metabolite profiles were broadly similar in both mouse and rat models. However, there were a number of significant differences in the alcohol-treated group particularly in the marked down-regulation of retinol and free cholesterol in the mouse compared to the rat. Unique markers for alcohol treatment included ethyl docosahexaenoic acid. Metabolites were identified with high confidence using predominantly negative ion MS(n) data for the fatty acyl components to match to www.lipidmaps.org MS and MS/MS databases; interpreting positive ion data needed to take into account possible adduct ions which may confound the identification of other lipid classes. The observed changes in lipid profiles were consistent with alcohol-induced liver injury in humans.
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PMID:Metabonomic investigation of liver profiles of nonpolar metabolites obtained from alcohol-dosed rats and mice using high mass accuracy MSn analysis. 2102 15

Alcohol consumption in man, when seen in its extreme form of alcoholism, is a complex and socially disruptive disorder that can result in significant levels of liver injury. Here the rodent "intragastric feeding model" was used together with UHPLC-TOFMS analysis to determine changes in global metabolite profiles for plasma and urine from alcohol treated rats and mice compared to control animals. Multivariate statistical analysis (using principal components analysis, PCA) revealed robust differences between profiles from control and alcohol-treated animals from both species. A large number of metabolites were seen to differ between control and alcohol-treated animals, for both biofluids.
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PMID:Investigation of chronic alcohol consumption in rodents via ultra-high-performance liquid chromatography-mass spectrometry based metabolite profiling. 2244 76

The aim of the research was to construct the Spiritual Coping Questionnaire (SCQ). Two studies have been carried out: the first on the sample of 1,296 persons facing stressful situations, and the second, on 352 persons undergoing alcohol addiction therapy. The first study provided data for PCA and CFA, calculation of internal consistency, test-retest reliability and descriptive statistics of the questionnaire. The second study allowed the author to verify the construct and criterion validity of the tool. The final version of the SCQ is composed of 32 items constituting two scales: positive and negative spiritual coping. The scale of positive spiritual coping includes four subscales-domains (personal, social, environmental and religious), and the scale of negative spiritual coping, three subscales (personal, social and religious). The validity and reliability of the tool are satisfactory. The questionnaire can be used to measure spiritual coping, both among religious and non-religious people.
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PMID:Multidimensional Approach Toward Spiritual Coping: Construction and Validation of the Spiritual Coping Questionnaire (SCQ). 2489 42

Alcoholism is common among trauma patients and often lacks the appropriate monitoring. Alcohol withdrawal syndrome (AWS), including delirium tremens (DT), can be associated with significant postoperative morbidity and mortality. However, appropriate acute pain management may protect against delirium; the administration of intravenous patient-controlled analgesia (IV - PCA) may not only alleviate pain, but also reduce the incidence of post-operative delirium. IV-PCA is widely used today; however, little attention has been paid to its influence on the development of AWS or DT post-surgery. Here we present a case in which the administration of IV-PCA may have delayed the onset of DT that interfered with postoperative care and the initiation of psychiatric consultation. The literature was reviewed to determine the potential mechanisms behind the effects of IV-PCA on the onset of AWS or DT.IV-PCA may delay the onset of DT. It is imperative to take into consideration trauma patients' psychiatric history including answers to questions on alcoholism, so that when an IV-PCA is administered and then discontinued, adequate interventions to prevent further morbidity associated with AWS and DT can be initiated in sufficient time.
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PMID:Morphine for Intravenous Patient-Controlled Analgesia May Inhibit Delirium Tremens: A Case Report and Literature Review. 2651 87

The alcoholism can be detected by analyzing electroencephalogram (EEG) signals. However, analyzing multi-channel EEG signals is a challenging task, which often requires complicated calculations and long execution time. This paper proposes three data selection methods to extract representative data from the EEG signals of alcoholics. The methods are the principal component analysis based on graph entropy (PCA-GE), the channel selection based on graph entropy (GE) difference, and the mathematic combinations channel selection, respectively. For comparison purposes, the selected data from the three methods are then classified by three classifiers: the J48 decision tree, the K-nearest neighbor and the Kstar, separately. The experimental results show that the proposed methods are successful in selecting data without compromising the classification accuracy in discriminating the EEG signals from alcoholics and non-alcoholics. Among them, the proposed PCA-GE method uses only 29.69% of the whole data and 29.5% of the computation time but achieves a 94.5% classification accuracy. The channel selection method based on the GE difference also gains a 91.67% classification accuracy by using only 29.69% of the full size of the original data. Using as little data as possible without sacrificing the final classification accuracy is useful for online EEG analysis and classification application design.
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PMID:Data selection in EEG signals classification. 2673 50