Biology subjects

CICEK, M.

Publications and source records attributed to CICEK, M..

2 recordsLinked to original sources

bioRxiv2025

Mathematics Anxiety Selectively Modulates Attentional and Memory-Related Neural Mechanisms During Numerical Cognition

Mathematics achievement can be influenced by negative emotions and expectations related to numerical tasks. Individuals with high mathematics anxiety often show poorer numerical performance. This study investigated the neural mechanisms underlying different levels of numerical processing associated with mathematics anxiety using number line estimation and arithmetic verification tasks during fMRI. Participants were classified into high (n=22, age=23.09{+/-}2.22) and low (n=24, age=22.67{+/-}3.29) mathematics anxiety groups based on detailed screening prior to scanning. Trait and test anxiety were also assessed to capture broader anxiety-related characteristics. Before the fMRI session, participants completed assessments of calculation performance and digit span, and a mock MRI session was used to reduce scanner-related stress. Participants completed task and control conditions for each numerical task during fMRI. Neuroimaging findings were analyzed before and after statistically controlling for trait and test anxiety. Results showed that low mathematics anxiety was associated with greater frontal eye field activity during number-space mapping and stronger supramarginal gyrus activity during arithmetic computation compared with high mathematics anxiety. Controlling for general anxiety revealed a dissociation between mathematics anxiety-specific and general anxiety-related neural effects. Overall, mathematics anxiety selectively influenced attentional and memory mechanisms, whereas broader anxiety processes engaged distinct motor and cognitive systems. Key PointsO_LIMathematics anxiety differentially modulates neural activity across distinct numerical processes. C_LIO_LIMathematics anxiety selectively affects attentional and memory-related mechanisms, independent of general anxiety. C_LIO_LINeural differences in salience and motor-related regions are better explained by general anxiety rather than mathematics anxiety. C_LI

neuroscience↗

bioRxiv2025

E2-Regulated Transcriptome Complexity Revealed by Long-Read Direct RNA Sequencing: From Isoform Discovery to Truncated Proteins

Estrogen receptor alpha (ER)-positive (ER+) breast cancers are driven by 17{beta}-estradiol (E2) binding to ER, which transcriptionally regulates downstream target genes. Although microarrays and conventional RNA sequencing have identified E2 target genes, pre-designed probes and short read lengths are limited in accurately capturing complex transcript structures. Long-read RNA sequencing offers a solution by spanning entire transcripts, providing a more complete view of the transcriptome. Here, we employed nanopore long-read direct RNA sequencing (DRS) complemented with 3-end sequencing, in vitro experiments, and deep learning-based protein modeling to explore the intricate landscape of E2-responsive transcriptome and protein level implications. Our analysis revealed a range of E2-responsive non-coding and coding isoforms, including intronically polyadenylated (IPA) mRNAs. One of these IPA isoforms was detected for TLE1 (Transducin-like enhancer protein 1), which positively assists ER-chromatin interactions for a subset of E2 target genes. The IPA isoform produces a C-terminus truncated protein, lacking the WDR interaction domain, but retains dimerization/tetramerization capacity through its intact N-terminus Q-domain. Structural modeling and protein-based assays confirmed the truncated proteins dimerization potential and nuclear localization. Functional assays showed that overexpression of truncated TLE1 reduces the E2-induced upregulation of GREB1, an E2-responsive gene, thereby disrupting transcriptional regulation. Importantly, a lower IPA isoform ratio is associated with worse survival in ER+ patients, highlighting clinical relevance. Our study uncovers new layers of complexity in the E2-regulated transcriptome, providing insights into truncated proteins. These findings contribute to a deeper understanding of gene regulation and may help the development of new therapeutic strategies.

cancer biology↗