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1.
Article in Chinese | WPRIM | ID: wpr-923540

ABSTRACT

@#Objective To explore the effect of Naikan cognitive-music reminiscence therapy on coping style in female patients with chronic schizophrenia.Methods In May, 2020, 72 female patients with chronic schizophrenia from Beijing Huilongguan Hospital were assigned into control group (n = 48) and music group (n = 24) after trait matching. Both groups accepted routine medicine, while the control group accepted Naikan cognitive therapy, and the music group accepted Naikan cognitive therapy combined music reminiscence, for twelve weeks. They were blind assessed with Simplified Coping Style Questionnaire, Self-rating Depression Scale and Self-rating Anxiety Scale before and after intervention.Results There were five cases in the control group removed for erroneous response. The main effects of group were not significant for all the assessments (F < 0.567, P > 0.05). The main effect of time was significant for negative coping style score (F = 6.968, P = 0.01), and the interaction effects were significant for positive coping style score and Self-rating Depression Scale score (F > 4.227, P < 0.05).Conclusion Combining with music reminiscence, Naikan cognitive therapy may be advantageous for the coping style of female patients with chronic schizophrenia.

2.
Protein & Cell ; (12): 140-147, 2012.
Article in English | WPRIM | ID: wpr-757316

ABSTRACT

Biologically important proteins related to membrane receptors, signal transduction, regulation, transcription, and translation are usually low in abundance and identified with low probability in mass spectroscopy (MS)-based analyses. Most valuable proteomics information on them were hitherto discarded due to the application of excessively strict data filtering for accurate identification. In this study, we present a staged-probability strategy for assessing proteomic data for potential functionally important protein clues. MS-based protein identifications from the second (L2) and third (L3) layers of the cascade affinity fractionation using the Trans-Proteomic Pipeline software were classified into three probability stages as 1.00-0.95, 0.95-0.50, and 0.50-0.20 according to their distinctive identification correctness rates (i.e. 100%-95%, 95%-50%, and 50%-20%, respectively). We found large data volumes and more functionally important proteins located at the previously unacceptable lower probability stages of 0.95-0.50 and 0.50-0.20 with acceptable correctness rate. More importantly, low probability proteins in L2 were verified to exist in L3. Together with some MS spectrogram examples, comparisons of protein identifications of L2 and L3 demonstrated that the staged-probability strategy could more adequately present both quantity and quality of proteomic information, especially for researches involving biomarker discovery and novel therapeutic target screening.


Subject(s)
Databases, Protein , Mass Spectrometry , Probability , Proteins , Chemistry , Metabolism , Proteomics , Software
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