Division of Reproductive Science Research

The Reproductive Science Research Division in the Department of Obstetrics and Gynecology was established in 2009 and consists of five full time research faculty members and 11 faculty members with joint appointment with other divisions in the department. Research is conducted in diverse areas of basic reproductive research

In situ correction of liquid meniscus in cell culture imaging system based on parallel Fourier ptychographic microscopy (96 Eyes)

We collaborated with Amgen and spent five years in designing and fabricating next generation multi-well plate imagers based on Fourier ptychographic microscopy (FPM). A 6-well imager (Emsight) and a low-cost parallel microscopic system (96 Eyes) based on parallel FPM were reported in our previous work. However, the effect of liquid meniscus on the image quality is much stronger than anticipated, introducing obvious wavevector misalignment and additional image aberration. To this end, an adaptive wavevector correction (AWC-FPM) algorithm and a pupil recovery improvement strategy are presented to solve these challenges in situ. In addition, dual-channel fluorescence excitation is added to obtain structural information for microbiologists. Experiments are demonstrated to verify their performances. The accuracy of angular resolution with our algorithm is within 0.003 rad. Our algorithms would make the FPM algorithm more robust and practical and can be extended to other FPM-based applications to overcome similar challenges

In situ correction of liquid meniscus in cell culture imaging system based on parallel Fourier ptychographic microscopy (96 Eyes)

We collaborated with Amgen and spent five years in designing and fabricating next generation multi-well plate imagers based on Fourier ptychographic microscopy (FPM). A 6-well imager (Emsight) and a low-cost parallel microscopic system (96 Eyes) based on parallel FPM were reported in our previous work. However, the effect of liquid meniscus on the image quality is much stronger than anticipated, introducing obvious wavevector misalignment and additional image aberration. To this end, an adaptive wavevector correction (AWC-FPM) algorithm and a pupil recovery improvement strategy are presented to solve these challenges in situ. In addition, dual-channel fluorescence excitation is added to obtain structural information for microbiologists. Experiments are demonstrated to verify their performances. The accuracy of angular resolution with our algorithm is within 0.003 rad. Our algorithms would make the FPM algorithm more robust and practical and can be extended to other FPM-based applications to overcome similar challenges

Tumor Necrosis Factor Receptor-Associated Factor 3 Is a Critical Regulator of B Cell Homeostasis in Secondary Lymphoid Organs

SummaryTumor necrosis factor receptor-associated factor 3 (TRAF3) is an adaptor protein that directly binds to a number of receptors of the tumor necrosis factor receptor (TNF-R) superfamily. Despite in vitro evidence that TRAF3 plays diverse roles in different cell types, little is known about the in vivo functions of TRAF3. To address this gap in knowledge and to circumvent the early lethal effect of TRAF3 null mutations, we generated conditional TRAF3-deficient mice. B-cell-specific Traf3−/− mice displayed severe peripheral B cell hyperplasia, which culminated in hyperimmunoglobulinemia and increased T-independent antibody responses, splenomegaly and lymphadenopathy. Resting splenic B cells from these mice exhibited remarkably prolonged survival ex vivo independent of B cell activating factor and showed increased amounts of active nuclear factor-κB2 but decreased amounts of nuclear protein kinase Cδ. Furthermore, these mice developed autoimmune manifestations as they aged. These findings indicate that TRAF3 is a critical regulator of peripheral B cell homeostasis and may be implicated in the regulation of peripheral self-tolerance induction

Image Restoration Based on the Hybrid Total-Variation-Type Model

We propose a hybrid total-variation-type model for the image restoration problem based on combining advantages of the ROF model with the LLT model. Since two L1-norm terms in the proposed model make it difficultly solved by using some classically numerical methods directly, we first employ the alternating direction method of multipliers (ADMM) to solve a general form of the proposed model. Then, based on the ADMM and the Moreau-Yosida decomposition theory, a more efficient method called the proximal point method (PPM) is proposed and the convergence of the proposed method is proved. Some numerical results demonstrate the viability and efficiency of the proposed model and methods