Statistical Modelling Outcome of In Vitro Fertilization and Intracytoplasmic Sperm Injection: A Single Centre Study.

BACKGROUND: Assisted reproductive techniques (ART) have been extensively used to treat infertility. Inaccurate prediction of a couple's fertility often leads to lowered self-esteem for patients seeking ART treatment and causes fertility distress. OBJECTIVE: This prospective study aimed to statistically analyze patient data from a single reproductive medical center over a period of 18 months, and to establish mathematical models that might facilitate accurate prediction of successful pregnancy when ART are used. METHODS: In the present study, we analyzed clinical data prospectively collected from 760 infertile patients visiting the second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University between June 1, 2016 and December 31, 2017. Various advanced statistical methods, including broken-line regression, were employed to analyze the data. RESULTS: Age remained the most important factor affecting the outcome of IVF/ICSI. Using the broken-line regression model, the fastest clinical pregnancy declining age was between 25 and 32. Female infertility type was found to be a key predictor for the number of good-quality embryos and successful pregnancy, along with the antral follicle count (AFC), total number of embryos, recombinant follicle stimulating hormones (rFSH) dosage, estradiol (E2) on the trigger day, and total number of oocytes retrieved. rFSH dosage was also significantly associated with the number of oocytes retrieved and the number of frozen embryos. CONCLUSION: The fastest clinical pregnancy declining age is ranged between 25 and 32, and female infertility type is evidenced as another key predictive factor for the cumulative outcome of ART.

Chromosomally-Encoded Yersinia pestis Type III Secretion Effector Proteins Promote Infection in Cells and in Mice.

Yersinia pestis, the causative agent of plague, possesses a number of virulence mechanisms that allows it to survive and proliferate during its interaction with the host. To discover additional infection-specific Y. pestis factors, a transposon site hybridization (TraSH)-based genome-wide screen was employed to identify genomic regions required for its survival during cellular infection. In addition to several well-characterized infection-specific genes, this screen identified three chromosomal genes (y3397, y3399, and y3400), located in an apparent operon, that promoted successful infection. Each of these genes is predicted to encode a leucine-rich repeat family protein with or without an associated ubiquitin E3 ligase domain. These genes were designated Yersinia leucine-rich repeat gene A (ylrA), B (ylrB), and C (ylrC). Engineered strains with deletions of y3397 (ylrC), y3399 (ylrB), or y3400 (ylrA), exhibited infection defects both in cultured cells and in the mouse. C-terminal FLAG-tagged YlrA, YlrB, and YlrC were secreted by Y. pestis in the absence but not the presence of extracellular calcium and deletions of the DNA sequences encoding the predicted N-terminal type III secretion signals of YlrA, YlrB, and YlrC prevented their secretion, indicating that these proteins are substrates of the type III secretion system (T3SS). Further strengthening the connection with the T3SS, YlrB was readily translocated into HeLa cells and expression of the YlrA and YlrC proteins in yeast inhibited yeast growth, indicating that these proteins may function as anti-host T3S effector proteins.

The outer membrane protein A (OmpA) of Yersinia pestis promotes intracellular survival and virulence in mice.

The plague bacterium Yersinia pestis has a number of well-described strategies to protect itself from both host cells and soluble factors. In an effort to identify additional anti-host factors, we employed a transposon site hybridization (TraSH)-based approach to screen 10(5)Y. pestis mutants in an in vitro infection system. In addition to loci encoding various components of the well-characterized type III secretion system (T3SS), our screen unambiguously identified ompA as a pro-survival gene. We go on to show that an engineered Y. pestis ΔompA strain, as well as a ΔompA strain of the closely related pathogen Yersinia pseudotuberculosis, have fully functioning T3SSs but are specifically defective in surviving within macrophages. Additionally, the Y. pestis ΔompA strain was out competed by the wild-type strain in a mouse co-infection assay. Unlike in other bacterial pathogens in which OmpA can promote adherence, invasion, or serum resistance, the OmpA of Y. pestis is restricted to enhancing intracellular survival. Our data show that OmpA of the pathogenic Yersinia is a virulence factor on par with the T3SS.

Generalized empirical likelihood methods for analyzing longitudinal data.

Efficient estimation of parameters is a major objective in analyzing longitudinal data. We propose two generalized empirical likelihood based methods that take into consideration within-subject correlations. A nonparametric version of the Wilks theorem for the limiting distributions of the empirical likelihood ratios is derived. It is shown that one of the proposed methods is locally efficient among a class of within-subject variance-covariance matrices. A simulation study is conducted to investigate the finite sample properties of the proposed methods and compare them with the block empirical likelihood method by You et al. (2006) and the normal approximation with a correctly estimated variance-covariance. The results suggest that the proposed methods are generally more efficient than existing methods which ignore the correlation structure, and better in coverage compared to the normal approximation with correctly specified within-subject correlation. An application illustrating our methods and supporting the simulation study results is also presented.