Embryologist agreement when assessing blastocyst implantation probability: is data-driven prediction the solution to embryo assessment subjectivity?

Study Question: What is the accuracy and agreement of embryologists when assessing the implantation probability of blastocysts using time-lapse imaging (TLI), and can it be improved with a data-driven algorithm?

Summary Answer: The overall interobserver agreement of a large panel of embryologists was moderate and prediction accuracy was modest, while the purpose-built artificial intelligence model generally resulted in higher performance metrics.

What Is Known Already: Previous studies have demonstrated significant interobserver variability amongst embryologists when assessing embryo quality. However, data concerning embryologists' ability to predict implantation probability using TLI is still lacking.

Adaptive sequencing using nanopores and deep learning of mitochondrial DNA.

Nanopore sequencing is an emerging technology that reads DNA by utilizing a unique method of detecting nucleic acid sequences and identifies the various chemical modifications they carry. Deep learning has increased in popularity as a useful technique to solve many complex computational tasks. 'Adaptive sequencing' is an implementation of selective sequencing, intended for use on the nanopore sequencing platform.

Assessing the involvement of the placental microbiome and virome in preeclampsia using non coding RNA sequencing.

Objectives: Preeclampsia is a dangerous pregnancy complication. The source of preeclampsia is unknown, though the placenta is believed to have a central role in its pathogenesis. An association between maternal infection and preeclampsia has been demonstrated, yet the involvement of the placental microbiome in the etiology of preeclampsia has not been determined.

Dual inhibition of ABCE1 and LCP1 by microRNA-96 results in an additive effect in breast cancer mouse model.

MicroRNAs (miRNAs) are short non-coding RNAs that regulate the expression of target genes at the post-transcriptional level. Each miRNA can modulate multiple genes and, as a result, a single miRNA may have a profound effect on a specific biological pathway consisting of several of its target genes. Recent studies have indicated that specific miRNA signatures are correlated with tumor aggressiveness and clinical outcome in breast cancer.

Comparison of breast cancer metastasis models reveals a possible mechanism of tumor aggressiveness.

In breast cancer patients, the lungs are among the first sites of cancer metastasis, and in nearly one quarter of metastatic patients, the exclusive first event. Two common mouse models mimic breast cancer lung colonization and distal metastasis: an orthotopic model and intravenous (IV) cell injections. Gene expression analysis of pulmonary lesions from these two methods demonstrated high inter-model resemblance.

The gene regulatory program of reveals conservation of phylum-specific expression.

The evolution of development has been studied through the lens of gene regulation by examining either closely related species or extremely distant animals of different phyla. In nematodes, detailed cell- and stage-specific expression analyses are focused on the model , in part leading to the view that the developmental expression of gene cascades in this species is archetypic for the phylum. Here, we compared two species of an intermediate evolutionary distance: the nematodes (clade V) and (clade IV).