361 research outputs found

    Nested sequences of index filtrations and continuation of the connection matrix

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    AbstractIn this paper, we prove the existence of nested sequences of index filtrations for convergent sequences of (admissible) semiflows on a metric space. This result is new even in the context of flows on a locally compact space. The nested index filtration theorem implies the continuation of homology index braids which, in turn, implies the continuation of connection matrices in the infinite-dimensional Conley index theory

    The random case of Conley's theorem: III. Random semiflow case and Morse decomposition

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    In the first part of this paper, we generalize the results of the author \cite{Liu,Liu2} from the random flow case to the random semiflow case, i.e. we obtain Conley decomposition theorem for infinite dimensional random dynamical systems. In the second part, by introducing the backward orbit for random semiflow, we are able to decompose invariant random compact set (e.g. global random attractor) into random Morse sets and connecting orbits between them, which generalizes the Morse decomposition of invariant sets originated from Conley \cite{Con} to the random semiflow setting and gives the positive answer to an open problem put forward by Caraballo and Langa \cite{CL}.Comment: 21 pages, no figur

    The bipolar disorders: A case for their categorically distinct status based on symptom profiles

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    Background: It is unclear whether the bipolar disorders (i.e. BP-I/BP-II) differ dimensionally or categorically. This study sought to clarify this issue. Methods: We recruited 165 patients, of which 69 and 96 had clinician-assigned diagnoses of BP-I and BP-II respectively. Their psychiatrists completed a data sheet seeking information on clinical variables about each patient, while the patients completed a different data sheet and scored a questionnaire assessing the prevalence and severity of 96 candidate manic/hypomanic symptoms. Results: We conducted a series of analyses examining a set (and two sub-sets) of fifteen symptoms that were significantly more likely to be reported by the clinically diagnosed BP-I patients. Latent class analyses favoured two-class solutions, while mixture analyses demonstrated bimodality, thus arguing for a BP-I/BP-II categorical distinction. Statistically defined BP-I class members were more likely when manic to have experienced psychotic features and over-valued ideas. They were also more likely to have been hospitalised, and to have been younger when they received their bipolar diagnosis and first experienced a depressive or manic episode. Limitations: The lack of agreement between some patients and managing clinicians in judging the presence of psychotic features could have compromised some analyses. It is also unclear whether some symptoms (e.g. grandiosity, noting mystical events) were capturing formal psychotic features or not. Conclusions: Findings replicate our earlier study in providing evidence to support the modelling of BP-I and BP-II as categorically discrete conditions. This should advance research into aetiological factors and determining optimal (presumably differing) treatments for the two conditions

    Differentiating mania/hypomania from happiness using a machine learning analytic approach.

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    Background: This study aimed to improve the accuracy of bipolar disorder diagnoses by identifying symptoms that help to distinguish mania/hypomania in bipolar disorders from general ‘happiness’ in those with unipolar depression. Methods: An international sample of 165 bipolar and 29 unipolar depression patients (as diagnosed by their clinician) were recruited. All participants were required to rate a set of 96 symptoms with regards to whether they typified their experiences of manic/hypomanic states (for bipolar patients) or when they were ‘happy’ (unipolar patients). A machine learning paradigm (prediction rule ensembles; PREs) was used to derive rule ensembles that identified which of the 94 non-psychotic symptoms and their combinations best predicted clinically-allocated diagnoses. Results: The PREs were highly accurate at predicting clinician bipolar and unipolar diagnoses (92% and 91% respectively). A total of 20 items were identified from the analyses, which were all highly discriminating across the two conditions. When compared to a classificatory approach insensitive to the weightings of the items, the ensembles were of comparable accuracy in their discriminatory capacity despite the unbalanced sample. This illustrates the potential for PREs to supersede traditional classificatory approaches. Limitations: There were considerably less unipolar than bipolar patients in the sample, which limited the overall accuracy of the PREs. Conclusions: The consideration of symptoms outlined in this study should assist clinicians in distinguishing between bipolar and unipolar disorders. Future research will seek to further refine and validate these symptoms in a larger and more balanced sample

    Towards the clinical implementation of pharmacogenetics in bipolar disorder.

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    BackgroundBipolar disorder (BD) is a psychiatric illness defined by pathological alterations between the mood states of mania and depression, causing disability, imposing healthcare costs and elevating the risk of suicide. Although effective treatments for BD exist, variability in outcomes leads to a large number of treatment failures, typically followed by a trial and error process of medication switches that can take years. Pharmacogenetic testing (PGT), by tailoring drug choice to an individual, may personalize and expedite treatment so as to identify more rapidly medications well suited to individual BD patients.DiscussionA number of associations have been made in BD between medication response phenotypes and specific genetic markers. However, to date clinical adoption of PGT has been limited, often citing questions that must be answered before it can be widely utilized. These include: What are the requirements of supporting evidence? How large is a clinically relevant effect? What degree of specificity and sensitivity are required? Does a given marker influence decision making and have clinical utility? In many cases, the answers to these questions remain unknown, and ultimately, the question of whether PGT is valid and useful must be determined empirically. Towards this aim, we have reviewed the literature and selected drug-genotype associations with the strongest evidence for utility in BD.SummaryBased upon these findings, we propose a preliminary panel for use in PGT, and a method by which the results of a PGT panel can be integrated for clinical interpretation. Finally, we argue that based on the sufficiency of accumulated evidence, PGT implementation studies are now warranted. We propose and discuss the design for a randomized clinical trial to test the use of PGT in the treatment of BD

    Eating disorders: from twin studies to candidate genes and beyond

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    Substantial effort has been put into the exploration of the biological background of eating disorders, through family, twin and molecular genetic studies. Family studies have shown that anorexia (AN) and bulimia nervosa (BN) are strongly familial, and that familial etiologic factors appear to be shared by both disorders. Twin studies often focus on broader phenotypes or subthreshold eating disorders. These studies consistently yielded moderate to substantial heritabilities. In addition, there has been a proliferation of molecular genetic studies that focused on Diagnostic and Statistical Manual of Mental Disorders (4th ed.; DSM-IV; American Psychiatric Association, 1994) AN and BN. Seven linkage regions have been identified in genome-wide screens. Many genetic association studies have been performed, but no consistent association between a candidate gene and AN or BN has been reported. Larger genetic association studies and collaborations are needed to examine the involvement of several candidate genes and biological pathways in eating disorders. In addition, twin studies should be designed to assist the molecular work by further exploring genetic determinants of endophenotypes, evaluating the magnitude of contribution to liability of measured genotypes as well as environmental risk factors related to eating disorders. In this manner twin and molecular studies can move the field forward in a mutually informative way

    Borna disease virus (BDV) circulating immunocomplex positivity in addicted patients in the Czech Republic: a prospective cohort analysis

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    <p>Abstract</p> <p>Background</p> <p>Borna disease virus (BDV) is an RNA virus belonging to the family Bornaviridae. Borna disease virus is a neurotropic virus that causes changes in mood, behaviour and cognition. BDV causes persistent infection of the central nervous system. Immune changes lead to activation of infection. Alcohol and drug dependence are associated with immune impairment.</p> <p>Methods</p> <p>We examined the seropositivity of BDV circulating immunocomplexes (CIC) in patients with alcohol and drug dependence and healthy individuals (blood donors). We examined 41 addicted patients for the presence of BDV CIC in the serum by ELISA at the beginning of detoxification, and after eight weeks of abstinence. This is the first such study performed in patients with alcohol and drug dependence.</p> <p>Results</p> <p>BDV CIC positivity was detected in 36.59% of addicted patients on day 0 and in 42.86% on day 56. The control group was 37.3% positive. However, we did not detect higher BDV CIC positivity in addicted patients in comparison with blood donors (p = 0.179). The significantly higher level of BDV CIC was associated with lower levels of GGT (gamma glutamyl transferase) (p = 0.027) and approached statistical significance with the lower age of addicted patients (p = 0.064). We did not find any association between BDV CIC positivity and other anamnestic and demographic characteristics.</p> <p>Conclusions</p> <p>In our study addicted patients did not have significantly higher levels of BDV CIC than the control group. The highest levels of BDV CIC were detected in patients with lower levels of GGT and a lower age.</p> <p>Trial registration</p> <p>This study was approved by the ethical committee of the University Hospital Medical Faculty of Charles University in Pilsen, Czech Republic (registration number 303/2001).</p

    Exemplar scoring identifies genetically separable phenotypes of lithium responsive bipolar disorder

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    Predicting lithium response (LiR) in bipolar disorder (BD) may inform treatment planning, but phenotypic heterogeneity complicates discovery of genomic markers. We hypothesized that patients with "exemplary phenotypes"-those whose clinical features are reliably associated with LiR and non-response (LiNR)-are more genetically separable than those with less exemplary phenotypes. Using clinical data collected from people with BD (n = 1266 across 7 centers; 34.7% responders), we computed a "clinical exemplar score," which measures the degree to which a subject's clinical phenotype is reliably predictive of LiR/LiNR. For patients whose genotypes were available (n = 321), we evaluated whether a subgroup of responders/non-responders with the top 25% of clinical exemplar scores (the "best clinical exemplars") were more accurately classified based on genetic data, compared to a subgroup with the lowest 25% of clinical exemplar scores (the "poor clinical exemplars"). On average, the best clinical exemplars of LiR had a later illness onset, completely episodic clinical course, absence of rapid cycling and psychosis, and few psychiatric comorbidities. The best clinical exemplars of LiR and LiNR were genetically separable with an area under the receiver operating characteristic curve of 0.88 (IQR [0.83, 0.98]), compared to 0.66 [0.61, 0.80] (p = 0.0032) among poor clinical exemplars. Variants in the Alzheimer's amyloid-secretase pathway, along with G-protein-coupled receptor, muscarinic acetylcholine, and histamine H1R signaling pathways were informative predictors. This study must be replicated on larger samples and extended to predict response to other mood stabilizers
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