engineering-artificial-factors-to-specifically-manipulate-alternative

Engineering Artificial Factors to Specifically Manipulate Alternative Splicing in Human Cells

The processing of most eukaryotic RNAs is mediated by RNA Binding Proteins (RBPs) with modular configurations, including an RNA recognition module, which ...

Shanghai Institutes for Biological Sciences (SIBS)

The Osteoporosis Assessment Questionnaire Short Version (OPAQ-SV) was cross-culturally adapted to measure health-related quality of life in Chinese osteoporotic fracture females and then validated in China for its psychometric properties. Cross-cultural adaptation, including translation of the original OPAQ-SV into Mandarin Chinese language, was performed according to published guidelines. Validation of the newly cross-culturally adapted OPAQ-SV was conducted by sampling 234 Chinese osteoporotic fracture females and also a control group of 235 Chinese osteoporotic females without fractures, producing robust content, construct, and discriminant validation results. Major categories of reliability were also met: the Cronbach alpha coefficient was 0.975, indicating good internal consistency; the test-retest reliability was 0.80; and principal component analysis resulted in a 6-factor structure explaining 75.847 % of the total variance. Further, the Comparative Fit Index result was 0.922 following the modified model confirmatory factor analysis, and the chi-squared test was 1.98. The root mean squared error of approximation was 0.078. Moreover, significant differences were revealed between females with fractures and those without fractures across all domains (p < 0.001). Overall, the newly cross-culturally adapted OPAQ-SV appears to possess adequate validity and reliability and may be utilized in clinical trials to assess the health-related quality of life in Chinese osteoporotic fracture females.

Cross-cultural adaptation and validation of the osteoporosis assessment questionnaire short version (OPAQ-SV) for Chinese osteoporotic fracture females.

Adenomatoid tumor (AT) is an extremely rare benign tumor in the testis of infants. A case of 14-month-old boy with testicular adenomatoid tumor was reported in this study. On physical examination, a smooth solid nodule sized 8 mm could be palpated with little tenderness on the head of the right testis. It could be clearly revealed by B ultrasonic scanning and computerized tomography. The patient underwent right radical orchiectomy. In postoperative histopathological study, the tumor was characterized by diffuse sheets of epithelioid cell and desmo-stroma structures. There was positive immunohistochemical staining of mesothelioma-associated antigens. The tumor should be differentiated from the tumor of the male genital tract including benign and malignant tumors of both epithelial and stromal origin. And we followed the case and no nodule was found in his scrotum by physical examination and scrotal ultrasonography after 3, 6, 12, 18, 24, 30, 36, 42, 48, 54, 60 months. These findings have important implications that the histogenesis of adenomatoid tumor of the testis is unclear yet. The diagnosis depends on pathologic studies, and should be differentiated from paratesticular malignant mesothelioma and sclerosed lipogranuloma. Radical surgery is the common choice, and as a result of getting a good prognosis.

Primary adenomatoid tumor of the testis: report of a case and review of literature.

there is growing evidence that fathers also experience post partum depression (PPD). However, paternal PPD has been less studied than maternal PPD. Very few studies have investigated PPD in first-time fathers from northwestern China.

Post partum depression and the psychosocial predictors in first-time fathers from northwestern China.

Cell-penetrating peptides are a group of peptides which can transport different types of cargo molecules such as drugs across plasma membrane and have been applied in the treatment of various diseases. Thus, the accurate prediction of cell-penetrating peptides with bioinformatics methods will accelerate the development of drug delivery systems. The study aims to develop a powerful model to accurately identify cell-penetrating peptides. At first, the peptides were translated into a set of vectors with the same dimension by using dipeptide compositions. Secondly, the Analysis of Variance-based technique was used to reduce the dimension of the vector and explore the optimized features. Finally, the support vector machine was utilized to discriminate cell-penetrating peptides from non-cell-penetrating peptides. The five-fold cross-validated results showed that our proposed method could achieve an overall prediction accuracy of 83.6%. Based on the proposed model, we constructed a free webserver called C2Pred (http://lin.uestc.edu.cn/server/C2Pred).

Prediction of cell-penetrating peptides with feature selection techniques.

In prokaryotes, the σ(54) promoters are unique regulatory elements and have attracted much attention because they are in charge of the transcription of carbon and nitrogen-related genes and participate in numerous ancillary processes and environmental responses. All findings on σ(54) promoters are favorable for a better understanding of their regulatory mechanisms in gene transcription and an accurate discovery of genes missed by the wet experimental evidences. In order to provide an up-to-date, interactive and extensible database for σ(54) promoter, a free and easy accessed database called Pro54DB (σ(54) promoter database) was built to collect information of σ(54) promoter. In the current version, it has stored 210 experimental-confirmed σ(54) promoters with 297 regulated genes in 43 species manually extracted from 133 publications, which is helpful for researchers in fields of bioinformatics and molecular biology.

Huan-Huan Wei

Key Laboratory of Computational Biology,
CAS-MPG Partner Institute for Computational Biology,
Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology

Shanghai Institutes for Biological Sciences (SIBS)

Engineering Artificial Factors to Specifically Manipulate Alternative Splicing in Human Cells

Huan-Huan Wei

.css-o250i3{font-size:18px;font-family:Open Sans,sans-serif;line-height:21.6px;}Key Laboratory of Computational Biology,CAS-MPG Partner Institute for Computational Biology,Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology

Shanghai Institutes for Biological Sciences (SIBS)

Engineering Artificial Factors to Specifically Manipulate Alternative Splicing in Human Cells

Key Laboratory of Computational Biology,
CAS-MPG Partner Institute for Computational Biology,
Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology