Patients with schizophrenia often display unusual language impairments. This is a wide ranging critical review of the literature on language in schizophrenia since the 19th century. We survey schizophrenic language level by level, from phonetics through phonology, morphology, syntax, semantics, and pragmatics.There are at least two kinds of impairment (perhaps not fully distinct): thought disorder, or failure to maintain a discourse plan, and schizophasia, comprising various dysphasia-like impairments such as clanging, neologism, and unintelligible utterances.Thought disorder appears to be primarily a disruption of executive function and pragmatics, perhaps with impairment of the syntax-semantics interface; schizophasia involves disruption at other levels. Phonetics is also often abnormal (manifesting as flat intonation or unusual voice quality), but phonological structure, morphology, and syntax are normal or nearly so (some syntactic impairments have been demonstrated). Access to the lexicon is clearly impaired, manifesting as stilted speech, word approximation, and neologism. Clanging (glossomania) is straightforwardly explainable as distraction by self-monitoring.Recent research has begun to relate schizophrenia, which is partly genetic, to the genetic endowment that makes human language possible. D
The database, CryptoDB (), is a community bioinformatics resource for the AIDS-related apicomplexan-parasite, Cryptosporidium. CryptoDB integrates whole genome sequence and annotation with expressed sequence tag and genome survey sequence data and provides supplemental bioinformatics analyses and data-mining tools. A simple, yet comprehensive web interface is available for mining and visualizing the data. CryptoDB is allied with the databases PlasmoDB and ToxoDB via ApiDB, an NIH/NIAID-fundedBioinformatics Resource Center. Recent updates to CryptoDB include the deposition of annotated genome sequences for Cryptosporidium parvum and Cryptosporidium hominis, migration to a relational database (GUS), a new query and visualization interface and the introduction of Web services.
Speech disturbances are well-known symptoms contributing to the diagnosis of schizophrenia. Subanesthetic doses of the N-methyl-D-aspartate (NMDA) antagonist ketamine have been reported to produce positive and negative symptoms and cognitive impairments consistent with those seen in schizophrenia. Insofar as this is true, it constitutes evidence that the NMDA system is involved in schizophrenia. It is therefore of interest to know whether ketamine produces speech disturbances like those of schizophrenia. Quantitative computer-aided analysis of apparently normal speech can detect clinically relevant changes and differences that are not noticeable to the human observer. Accordingly, in this study, speech samples were analysed for repetitiousness, idea density, and verb density using software developed by the authors. The samples came from two experiments, a within-subjects study of healthy volunteers given intravenous ketamine versus placebo, and a between-groups study of patients diagnosed with schizophrenia and comparable healthy controls.Our primary hypothesis was that in both schizophrenia and ketamine, repetitiousness would increase, since perserverative speech is a well-known symptom of schizophrenia. Our secondary hypotheses were that in both schizophrenia and ketamine, idea density and verb density would decrease as indicators of cognitive impairment. The primary hypothesis was confirmed in the schizophrenia experiment (between groups) and the ketamine experiment (within subjects). The secondary hypotheses were disconfirmed except that in the ketamine experiment, verb density was significantly lowered. Reduced use of verbs apparently reflects a cognitive impairment of a different type than repetitiousness, and further investigation is needed to determine whether this impairment occurs in psychosis.
Stochastic Context-Free Grammars (SCFG) has been shown to be effective in modelling RNA secondary structure for searches. Our previous work (Cai et al., 2003) in Stochastic Parallel Communicating Grammar Systems (SPCGS) has extended SCFG to model RNA pseudoknots. However, the alignment algorithm requires O(n4) memory for a sequence of length n. In this paper, we develop a memory efficient algorithm for sequence-structure alignments including pseudoknots. This new algorithm reduces the memory space requirement from O(n4) to O(n2) without increasing the computation time. Our experiments have shown that this novel approach can achieve excellent performance on searching for RNA pseudoknots.
In an earlier article , we reported a subsignificant difference in idea density in the speech of healthy volunteers given subanaesthetic doses of ketamine, compared with placebo, and no such difference in a group of schizophrenia patients compared with matched healthy controls (neither group given ketamine). More accurate measurement of idea density with new software shows a much more definite difference between ketamine-influenced speech and schizophrenic speech.As detailed in the original article, data came from nine volunteers who were given, in random order, placebo or lowdose ketamine (0.40 mg/kg spread over 10 min followed by 0.21 mg/kg/h for 90 min), and from matched populations of 11 schizophrenia patients and 12 controls. Experiments were approved by the ethics committees of the respective universities.Subjects were asked to describe pictures from the Thematic Apperception Test (Murray, 1971). The idea density (proposition density) of their transcribed speech was measured. In the reanalysis, we used CPIDR-3 (Brown, et al., 2007a(Brown, et al., , program version 3.2.2694 see Covington, 2007, andBrown, et al., 2007b). Like the software used in the original article, CPIDR-3 counts parts of speech that express predication (verbs, adjectives, adverbs, prepositions and conjunctions). However, CPIDR-3 skips hesitation forms (umm, uh, etc.) and repetitions of the immediately preceding word so that results are not thrown off by hesitant speech. (Our earlier software counted umm as a word though not an idea, and could count a repeated idea-word as two ideas.) CPIDR-3 also uses an elaborate set of rules to adjust its idea counts to match, as far as possible, the standards proposed by Turner and Greene (1977). Because CPIDR-3 recognizes more of Turner and Greene's idea expressions, and because it omits hesitation forms and repetitions, all idea densities are higher with CPIDR-3 than with our original software. They are also considerably more accurate by Turner and Greene's standards.Comparing the ketamine and placebo groups as a whole, we found a statistically significant difference in idea density. The mean ± SD idea density (in propositions per word) was 0.499 ± 0.046 with ketamine and 0.541 ± 0.018 with placebo, giving t = 2.50, df = 16, P = 0.02. Originally we reported 0.346 ± 0.076 and 0.373 ± 0.020 respectively, giving t = 1.02, df = 16, P = 0.33, which is not a statistically significant difference of means, although we did note significantly unequal variances.The mean ± SD within-subject change in idea density, from placebo to ketamine, was −0.041 ± 0.047, giving t = −2.64, df = 8, P = 0.03, which again is statistically significant. Originally we reported −0.027 ± 0.063, t = −1.28, df = 8, P = 0.24. Thus, we now conclude, rather than merely suspect, that ketamine reduces idea density in speech.There continued to be no significant difference between the schizophrenic and matched control groups. That is, we did not find lower idea density to be the characteristic of schizophrenia. Mean ± SD idea density was ...
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