Biology subjects

Kurosawa, T.

Publications and source records attributed to Kurosawa, T..

3 recordsLinked to original sources

bioRxiv2025

FOXM1 Expression in Invasive Ductal Breast Carcinoma of No Special Type: Insights from RNA-seq and Immunohistochemical Analysis

BackgroundInvasive ductal carcinoma of no special type (IDC-NST) is the most common subtype of breast cancer, characterized by significant clinical heterogeneity. Forkhead box M1 (FOXM1) is a key transcription factor involved in cell cycle regulation and tumor progression, but its expression profile and clinical significance in IDC-NST remain incompletely understood. MethodsWe analyzed FOXM1 expression in a cohort of 100 IDC-NST patients using RNA sequencing and immunohistochemistry (IHC). FOXM1 mRNA levels were quantified, and protein expression was scored based on the percentage of positive tumor cells. Differentially expressed genes (DEGs) between high and low FOXM1 expression groups were identified, followed by pathway enrichment and protein-protein interaction (PPI) network analyses. The prognostic value of FOXM1 was evaluated by recurrence-free survival (RFS) analysis. ResultsFOXM1 protein expression correlated significantly with mRNA abundance in 22 representative cases (p < 0.05). Receiver operating characteristic (ROC) curve analysis identified a cut-off value of 4.954 CPM for FOXM1 mRNA to predict recurrence (AUC = 0.642). High FOXM1 expression was associated with larger tumor size, higher histological grade, and negative hormone receptor status. Patients with high FOXM1 expression exhibited significantly poorer 5-year RFS (73.6% vs. 92.3%, p < 0.001). Multivariate analysis confirmed FOXM1 as an independent prognostic factor (HR 15.26; p = 0.026). Transcriptomic profiling revealed 190 upregulated and 197 downregulated genes in the FOXM1-high group, enriched in cell cycle and mitotic pathways. PPI network analysis positioned FOXM1 as a central hub coordinating genes involved in chromosomal stability and mitosis. ConclusionsFOXM1 overexpression is a strong independent predictor of poor prognosis in IDC-NST and plays a critical role in tumor proliferation and genome integrity. These findings support FOXM1 as a potential prognostic biomarker and therapeutic target, warranting further investigation into FOXM1-targeted therapies for breast cancer management.

cancer biology↗

bioRxiv2025

Attention robustly dissociates objective performance and subjective visibility reports

Visual experience can sometimes depart from visual performance, providing a powerful lens into the mechanisms generating conscious perception. In one proposed dissociation--subjective inflation--unattended locations in the periphery appear stronger than attended ones despite equated performance. Subjective inflation has played a central role in motivating theories of consciousness that reject the sufficiency of sensory signals for conscious perception. Yet the empirical basis for subjective inflation is limited. Here, in a large-scale adversarial collaboration, we conducted four simultaneously-replicated experiments testing the strength, character, and extent of subjective inflation under inattention. We used a new analytic approach to quantify inattentional inflation over full psychometric functions, beyond single matched-performance levels. We found robust inattentional inflation for contrast-dependent and texture-based perception, at and above the visual threshold. However at suprathreshold, we found inattentional inflation for the overall stimulus but not the specific feature relevant for performance. Finally, we establish the unifying principle that inattentional inflation occurs if and only if attention reduces performance thresholds more than visibility thresholds. Thus what we think we see may regularly exceed what we can visually discriminate, placing constraints on theories of conscious perception.

neuroscience↗

bioRxiv2023

Assessing the potential for genome-assisted breeding in red perilla using quantitative trait locus analysis and genomic prediction

Red perilla is an important medicinal plant used in Kampo medicine, and the development of elite varieties of this species is urgently necessary. Medicinal compounds are generally considered target traits in medicinal plant breeding; however, selection based on the phenotypes of the compounds (i.e., conventional selection) is expensive and time-consuming. Here, we proposed genomic selection (GS) and marker-assisted selection (MAS) as suitable selection methods for medicinal plants, and evaluated the effectiveness of GS and MAS in red perilla breeding. Three breeding populations generated from crosses between one red and three green perilla genotypes were used to elucidate the genetic mechanisms underlying the production of major medicinal compounds using quantitative trait locus analysis and to evaluate the accuracy of genomic prediction (GP). We found that GP had sufficiently high accuracy for all traits, confirming that GS was an effective method for perilla breeding. Moreover, the three populations showed varying degrees of segregation, suggesting that use of these populations in breeding may yield simultaneous enhancements of different target traits. This study can contribute to research on the genetic mechanisms of the major medicinal compounds of red perilla as well as the breeding efficiency of this medicinal plant.

genomics↗