Biology subjects

Yoshimura, J.

Publications and source records attributed to Yoshimura, J..

4 recordsLinked to original sources

bioRxiv2025

Excellent agreement between automated deep learning-based and manual DWI infarct volume measurement in hyperacute stroke

BackgroundDiffusion-weighted imaging (DWI) lesion volume and infarct growth are important imaging markers in acute ischemic stroke, but manual volume measurement is time-consuming and resource-intensive. Deep learning (DL)-based automated segmentation may facilitate rapid assessment; however, its performance on hyperacute DWI has not been sufficiently assessed. The aim was to evaluate the agreement between DL-based automated and manual infarct volume measurements and to compare their ability to predict clinical outcomes in patients treated with mechanical thrombectomy (MT). MethodConsecutive MT-treated patients (September 2014-December 2019) who underwent DWI at admission and at approximately 24 hours were retrospectively analyzed. Manual infarct volume was measured by stroke neurologists. Automated measurements were obtained using DL-based software. Agreement was assessed using Pearsons correlation, Bland-Altman analysis, and intraclass correlation coefficients (ICC 2,1). Inter- and intra-rater reliabilities were evaluated in a randomly selected subgroup of 150 patients. Predictive ability for a good outcome at 3 months (modified Rankin Scale score 0-2 or stable/improved from premorbid status) was compared using C-statistics and DeLongs test. ResultsA total of 371 patients (677 DWI scans) were included. Manual and automated measurements showed very strong correlation (r = 0.96) with minimal bias (-1.77 mL). The ICC for manual-automated agreement was 0.959 (95% CI, 0.952-0.965), comparable to inter- and intra-rater ICCs. Agreement remained high across onset-to-imaging times and lesion sizes. Predictive abilities for a good outcome were similar for manual and automated admission DWI volume (C-statistics 0.867 vs. 0.861) and infarct growth (0.859 vs. 0.853). Manual follow-up DWI volume showed slightly better predictive ability than automated measurement (0.880 vs. 0.866). ConclusionDL-based automated infarct volume measurement shows excellent agreement with experienced clinicians, with predictive performance comparable to manual assessment. Automated DWI-based quantification is reliable and feasible for use in hyperacute stroke management.

neuroscience↗

bioRxiv2023

Classification of patients with COVID-19 by blood RNA endotype: A prospective cohort study

BackgroundAlthough the development of vaccines has considerably reduced the severity of COVID-19, its incidence is still high. Hence, a targeted approach based on RNA endotypes of a population should be developed to help design biomarker-based therapies for COVID-19. ObjectivesWe evaluated the major RNAs transcribed in blood cells during COVID-19 using PCR to further elucidate its pathogenesis and determine predictive phenotypes in COVID-19 patients. Study designIn a discovery cohort of 40 patients with COVID-19, 26,354 RNAs were measured on day 1 and day 7. Five RNAs associated with disease severity and prognosis were derived. In a validation cohort of 153 patients with COVID-19 treated in the intensive care unit, we focused on prolactin (PRL), and toll-like receptor 3 (TLR3) among RNAs, which have a strong association with prognosis, and evaluated the accuracy for predicting survival of PRL-to-TL3 ratios (PRL/TLR3) with the areas under the ROC curves (AUC). The validation cohort was divided into two groups based on the cut-off value in the ROC curve with the maximum AUC. The two groups were defined by high PRL/TLR3 (n=47) and low PRL/TLR3 groups (n=106) and the clinical outcomes were compared. ResultsIn the validation cohort, the AUC for PRL/TLR3 was 0.79, showing superior prognostic ability compared to severity scores such as APACHE II and SOFA. The high PRL/TLR3 group had a significantly higher 28-day mortality than the low PRL/TLR3 group (17.0% vs 0.9%, P<0.01). ConclusionsA new RNA endotype classified using high PRL/TLR3 was associated with mortality in COVID-19 patients.

genetics↗

bioRxiv2021

Genomic imprinting drives eusociality

The origin of eusociality, altruistically foregoing personal reproduction to help others, has been a long-standing paradox ever since Darwin. Most eusocial insects and rodents likely evolved from subsocial precursors, in which older offspring "helpers" contribute to the development of younger siblings without a permanent sterile caste. The driving mechanism for the transition from subsociality (with helpers) to eusociality (with lifelong sterile workers) remains an enigma because individuals in subsocial groups are subject to direct natural selection rather than kin selection. Our genomic imprinting theory demonstrates that natural selection generates eusociality in subsocial groups when parental reproductive capacity is linked to a delay in the sexual development of offspring due to sex-antagonistic action of transgenerational epigenetic marks. Focusing on termites, our theory provides the missing evolutionary link to explain the evolution of eusociality from their subsocial wood-feeding cockroach ancestors, and provides a novel framework for understanding the origin of eusociality.

evolutionary biology↗

bioRxiv2020

Hamster PIWI proteins bind to piRNAs with stage-specific size variations during oocyte maturation

In animal gonads, transposable elements (TEs) are actively repressed to preserve genome integrity through the Piwi-interacting RNA (piRNA) pathway. In mice, piRNAs are most abundantly expressed in male germ cells, and form effector complexes with three distinct PIWI proteins. The depletion of individual Piwi genes causes male-specific sterility owing to severe defects in spermatogenesis with no discernible phenotype in female mice. Unlike mice, most other mammals have four PIWI genes, some of which are expressed in the ovary. Here, purification of PIWI complexes from oocytes of the golden hamster revealed that the size of the piRNAs loaded onto PIWIL1 changed during oocyte maturation. In contrast, PIWIL3, an ovary-specific PIWI in most mammals, associates with short piRNAs only in metaphase II oocytes, which coincides with intense phosphorylation of the protein. An improved high-quality genome assembly and annotation revealed that PIWIL1- and PIWIL3-associated piRNAs appear to share the 5'- ends of common piRNA precursors and are mostly derived from unannotated sequences with a diminished contribution from TE-derived sequences, most of which correspond to endogenous retroviruses (ERVs). Although binding sites for the transcription factor A-Myb are identified in the transcription start site regions of the testis piRNA clusters, the piRNA clusters in the ovary show no well-defined binding motifs in their upstream regions. These results show that hamster piRNA clusters are transcribed by different transcriptional factors in the ovary and testis, resulting in the generation of sex-specific piRNAs. Our findings show the complex and dynamic nature of biogenesis of piRNAs in hamster oocytes, and together with the new genome sequence generated, serve as the foundation for developing useful models to study the piRNA pathway in mammalian oocytes. Highlights- The size of PIWIL1-associated piRNAs changes during oocyte maturation - Phosphorylation of PIWIL3 in MII oocytes coincides with its association with small 19-nt piRNAs - Improved high-quality genome assembly and annotation identifies young endogenous retroviruses as major targets of piRNAs in hamster oocytes - PIWIL1- and PIWIL3-associated piRNAs share the 5'-ends of the common piRNA precursors in oocytes

molecular biology↗