Biology subjects

Yoshihara, H.

Publications and source records attributed to Yoshihara, H..

3 recordsLinked to original sources

bioRxiv2026

Whole slide image analysis of the endometrial decidual reaction reveals multiscale perturbations associated with miscarriage

The inflammatory decidual reaction renders the cycling endometrium transiently permissive for embryo implantation before transforming it into the decidua, the maternal bed accommodating the fetal placenta during pregnancy. Disruptions in decidual tissue remodeling are linked to miscarriage and other pregnancy disorders. However, endometrial assessment is hampered by a lack of affordable technologies capable of mapping the spatiotemporal dysregulation of this dynamic and complex tissue. Employing a graph neural network on whole slide images of 493 CD56-immunostained endometrial samples, Endometronome was developed as a deep learning tool to spatially track the decidual reaction and provide accurate estimates of marker gene expression. When applied to 2,690 additional biopsies, this model consistently identified morphological correlates of prior miscarriage burden, a proxy for future risk. Further, a morphological signature indicative of metabolic glandular impairment discriminated between clinical miscarriage presentations. These findings illustrate how advanced imaging analysis of routine histology can transform miscarriage prevention strategies.

pathology↗

bioRxiv2024

Stalling of the endometrial decidual reaction determines the recurrence risk of miscarriage risk

In each menstrual cycle, progesterone acting on estrogen-primed endometrium elicits an inflammatory decidual reaction, rendering it poised for embryo implantation and transformation into the decidua of pregnancy. Here, we show that the sequential functions of the decidual reaction - implantation and decidualization - pivot on the time-sensitive loss of progesterone-resistant stromal cells that form a transient implantation niche and reciprocal expansion of progesterone-responsive pre-decidual cells. In parallel, proliferation and differentiation increase the abundance of immunotolerant uterine natural killer (uNK) cells. Examination of pre-pregnancy endometrial biopsies from 924 women revealed that the frequency of cycles culminating in a blunted or stalled decidual reaction closely aligns with the age-independent recurrence risk of miscarriage. Further, analysis of 632 biopsies obtained in different cycles from 316 women indicated that prior miscarriages disrupt intercycle endometrial homeostasis, an observation supported by modelling the impacts of prolonged decidual inflammation in three-dimensional endometrial assembloids. Although stalling of the decidual reaction is often accompanied by a poor expansion of immunotolerant uNK cells, miscarriages do not impact intercycle uNK cell dynamics. Our findings indicate that intrinsic uterine mechanisms hardwire the recurrence risk of miscarriage, underscoring the need for pre-pregnancy diagnostics and therapeutics. One Sentence SummaryThe frequency of menstrual cycles culminating in a suboptimal decidual reaction determines the recurrence risk of miscarriage.

physiology↗

bioRxiv2019

RaptRanker: in silico RNA aptamer selection from HT-SELEX experiment based on local sequence and structure information

Aptamers are short single-stranded RNA/DNA molecules that bind to specific target molecules. Aptamers with high binding-affinity and target specificity are identified using an in vitro procedure called high throughput systematic evolution of ligands by exponential enrichment (HT-SELEX). However, the development of aptamer affinity reagents takes a considerable amount of time and is costly because HT-SELEX produces a large dataset of candidate sequences, some of which have insufficient binding-affinity. Here, we present RNA aptamer Ranker (RaptRanker), a novel in silico method for identifying high binding-affinity aptamers from HT-SELEX data by scoring and ranking. RaptRanker analyzes HT-SELEX data by evaluating the nucleotide sequence and secondary structure simultaneously, and by ranking according to scores reflecting local structure and sequence frequencies. To evaluate the performance of RaptRanker, we performed two new HT-SELEX experiments, and evaluated binding affinities of a part of sequences that include aptamers with low binding-affinity. In both datasets, the performance of RaptRanker was superior to Frequency, Enrichment and MPBind. We also confirmed that the consideration of secondary structures is effective in HT-SELEX data analysis, and that RaptRanker successfully predicted the essential subsequence motifs in each identified sequence.

bioinformatics↗