Automated Denudation of Oocytes

Denudation is a technique for removal of the cumulus cell mass from oocytes in clinical intracytoplasmic sperm injection (ICSI). Manual oocyte denudation requires long training hours and stringent skills, but still suffers from low yield rate and denudation efficiency due to human fatigue and skill variations across operators. To address these limitations, this paper reports a robotic system for automated oocyte denudation. In this system, several key techniques are proposed, including a vision-based contact detection method for measuring the relative z position between the micropipette tip and the dish substrate, recognition of oocytes and the surrounding cumulus cells, automated calibration algorithm for eliminating the misalignment angle, and automated control of the flow rate based on the model of oocyte dynamics during micropipette aspiration and deposition. Experiments on mouse oocytes demonstrated that the robotic denudation system achieved a high yield rate of 97.0 ± 2.8% and denudation efficiency of 95.0 ± 0.8%. Additionally, oocytes denuded by the robotic system showed comparable fertilization rate and developmental competence compared with manual denudation. Our robotic denudation system represents one step towards the automation and standardization of ICSI procedures

Polyethylene glycol-coated ultrasmall superparamagnetic iron oxide nanoparticles-coupled sialyl Lewis X nanotheranostic platform for nasopharyngeal carcinoma imaging and photothermal therapy

Abstract Background Nasopharyngeal carcinoma (NPC) is a type of head and neck malignant tumor with a high incidence in specific regional distribution, and its traditional therapies face some challenges. It has become an urgent need to seek new therapeutic strategies without or with low toxicity and side effects. At present, more and more researchers has been attracting attention by nanotheranostic platform. Therefore, our team synthesized the polyethylene glycol-coated ultrasmall superparamagnetic iron oxide nanoparticles-coupled sialyl Lewis X (USPIO-PEG-sLex) nanotheranostic platform with high temperature pyrolysis. Results The USPIO-PEG-sLex nanoparticles had excellent photothermal conversion property, and the temperature of USPIO-PEG-sLex nanoparticles solution increased with its concentration and power density of near-infrared (NIR) on 808 nm wavelengths. Five USPIO-PEG-sLex nanoparticles with different concentrations of 0 mg/ml, 0.025 mg/ml, 0.05 mg/ml, 0.1 mg/ml and 0.2 mg/ml were prepared. The biological toxicity results showed that the viability of NPC 5-8F cells is related to the concentration of USPIO-PEG-sLex nanoparticles and the culture time (P < 0.001). The results of photothermal therapy (PTT) in vitro indicated that the viability of 5-8F cells decreased significantly with the concentration of USPIO-PEG-sLex nanoparticles increases (P < 0.001), and the viability of NPC 5-8F cells were 91.04% ± 5.20%, 77.83% ± 3.01%, 73.48% ± 5.55%, 59.50% ± 10.98%, 17.11% ± 3.14%, respectively. The USPIO-PEG-sLex nanoparticles could target the tumor area, and reduce the T2* value of tumor tissue. The T2* values of tumor pre- and post-injection were 30.870 ± 5.604 and 18.335 ± 4.351, respectively (P < 0.001). In addition, USPIO-PEG-sLex nanoparticles as a photothermal agent for PTT could effectively inhibit tumor progression. The ratio of volume change between tail vein injection group, control group, nanoparticles without laser irradiation group and blank group after 5 treatments were 3.04 ± 0.57, 5.80 ± 1.06, 8.09 ± 1.96, 7.89 ± 2.20, respectively (P < 0.001). Conclusions Our synthesized USPIO-PEG-sLex nanotheranostic platform, and it may be become a new strategy for the treatment of NPC. Graphic Abstrac

Development and evaluation of a live birth prediction model for evaluating human blastocysts from a retrospective study

Background: In infertility treatment, blastocyst morphological grading is commonly used in clinical practice for blastocyst evaluation and selection, but has shown limited predictive power on live birth outcomes of blastocysts. To improve live birth prediction, a number of artificial intelligence (AI) models have been established. Most existing AI models for blastocyst evaluation only used images for live birth prediction, and the area under the receiver operating characteristic (ROC) curve (AUC) achieved by these models has plateaued at ~0.65. Methods: This study proposed a multimodal blastocyst evaluation method using both blastocyst images and patient couple’s clinical features (e.g., maternal age, hormone profiles, endometrium thickness, and semen quality) to predict live birth outcomes of human blastocysts. To utilize the multimodal data, we developed a new AI model consisting of a convolutional neural network (CNN) to process blastocyst images and a multilayer perceptron to process patient couple’s clinical features. The data set used in this study consists of 17,580 blastocysts with known live birth outcomes, blastocyst images, and patient couple’s clinical features. Results: This study achieved an AUC of 0.77 for live birth prediction, which significantly outperforms related works in the literature. Sixteen out of 103 clinical features were identified to be predictors of live birth outcomes and helped improve live birth prediction. Among these features, maternal age, the day of blastocyst transfer, antral follicle count, retrieved oocyte number, and endometrium thickness measured before transfer are the top five features contributing to live birth prediction. Heatmaps showed that the CNN in the AI model mainly focuses on image regions of inner cell mass and trophectoderm (TE) for live birth prediction, and the contribution of TE-related features was greater in the CNN trained with the inclusion of patient couple's clinical features compared with the CNN trained with blastocyst images alone. Conclusions: The results suggest that the inclusion of patient couple’s clinical features along with blastocyst images increases live birth prediction accuracy. Funding: Natural Sciences and Engineering Research Council of Canada and the Canada Research Chairs Program

Transcriptome analysis of Sinorhizobium meliloti nodule bacteria in nifA mutant background

Tian Z, Zou H, Li J, et al. Transcriptome analysis of Sinorhizobium meliloti nodule bacteria in nifA mutant background. CHINESE SCIENCE BULLETIN. 2006;51(17):2079-2086.Gene expression profiles of a Sinorhizobium meliloti 1021 nifA mutant and wild type nodule bacteria were compared using whole genome microarrays. The results revealed a large scale alteration of gene expression (601 genes) in the nifA minus background. The loss of NifA altered the expression of many functional groups of genes (macromolecular metabolism, TCA cycle and respiration, nodulation and nitrogen fixation) and may lead to quite different life stages of the nodule bacteria. Upregulation of fixK and its associated genes was observed in the nifA mutant nodule bacteria. Additional quantitative real-time PCR experiments revealed that the transcript levels of fixLJ were significantly upshifted in the nifA mutant nodule bacteria. Putative NifA binding sites were predicted by a statistical method in the upstream sequences of 13 differentially regulated genes from the nifA transcriptome