Background Previous research revealed antibodies targeting Chlamydia trachomatis (CT) elementary bodies was not associated with reduced endometrial or incident infection in CT-exposed women. However, data on the role of CT protein-specific antibodies in protection are limited. Methods A whole-proteome CT array screening serum pools from CT-exposed women identified 121 immunoprevalent proteins. Individual sera were probed using a focused array. IgG antibody frequencies and endometrial or incident infection relationships were examined using Wilcoxon Rank sum test. The impact of breadth and magnitude of protein-specific IgGs on ascension and incident infection were examined using multivariable stepwise logistic regression. Complementary RNA-sequencing quantified CT gene transcripts in cervical swabs from infected women. Results IgG to Pgp3 and CT005 were associated with reduced endometrial infection; anti-CT443, -CT486 and -CT123 were associated with increased incident infection. Increased breadth of protein recognition did not however predict protection from endometrial or incident infection. mRNAs for immunoprevalent CT proteins were highly abundant in the cervix. Conclusions Protein-specific CT antibodies are not sufficient to protect against ascending or incident infection but broad recognition of CT proteins by IgG correlates with cervical CT gene transcript abundance, suggesting CT protein abundance correlates with immunogenicity and signifies their potential as vaccine candidates.
Measuring gene-gene dependence in single cell RNA sequencing (scRNA-seq) count data is often of interest and remains challenging, because an unidentified portion of the zero counts represent non-detected RNA due to technical reasons. Conventional statistical methods that fail to account for technical zeros incorrectly measure the dependence among genes. To address this problem, we propose a bivariate zero-inflated negative binomial (BZINB) model constructed using a bivariate Poisson-gamma mixture with dropout indicators for the technical (excess) zeros. Parameters are estimated based on the EM algorithm and are used to measure the underlying dependence by decomposing the two sources of zeros. Compared to existing models, the proposed BZINB model is specifically designed for estimating dependence and is more flexible, while preserving the marginal zero-inflated negative binomial distributions. Additionally, it has a simple latent variable framework, allowing parameters to have clear and intuitive interpretations, and its computation is feasible with large scale data. Using a recent scRNA-seq dataset, we illustrate model fitting and how the model-based measures can be different from naive measures. The inferential ability of the proposed model is evaluated in a simulation study. An R package 'bzinb' is available on CRAN.
Educational reform in the United States since the 1980s has evolved over the years to develop learner-centered instruction. Research indicated learner-centered instruction has a positive effect on student learning outcomes, such as student engagement, student motivation, and academic performance. However, the evidence is relatively limited in the Chinese higher education context. Therefore, this study aims to explore the relationship between learner-centered instruction and student engagement in Chinese higher education. The researchers collected data of perceived level of learner-centered instruction (i. e., cognitive and metacognitive, motivational, and social domain) and student engagement (i. e., behavioral, emotional, and cognitive domain) from 201 full-time undergraduate students (male=65, female=136) from Wenzhou-Kean University (WKU). The results showed that there was a significant positive correlation between learner-centered instruction and student engagement, r = .798, for example, results indicated the positive relationship between the cognitive and metacognitive domain and behavioral engagement (r = .632), and the social domain and emotional engagement (r = .661). The current study provides extra evidence contributing to the application of learner-centered instruction in Chinese higher education.
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