Introduction: The functional role of the ipsilateral primary motor cortex (iM1) activation in motor skill acquisition is widely researched; however, its interaction with task complexity remains unclear. This study aimed to address a critical gap in motor neuroscience: how the electroencephalogram (EEG) activation dynamics (specifically in the gamma frequency band) recorded by electrodes over the contralateral primary motor cortex (cM1) and iM1 evolve during the acquisition of simple vs. complex motor skills, and whether these dynamics are modulated by hand dominance. Methods: In a randomized controlled trial, 48 right-handed participants were randomly assigned to train on either simple or complex visuomotor tasks using their right (SR, CR, respectively) or left hand (SL, CL, respectively), with 12 participants per group. One participant in the SL group was excluded due to poor EEG quality, resulting in 11 participants in the SL group. Participants completed 10 training blocks followed by skill retention tests. Brain activity was recorded continuously via 64-channel EEG. Results: Data from 47 participants revealed that, prior to training, the high-gamma band (50-80Hz) activation recorded by electrodes over iM1 exhibited significantly higher activation during simple tasks compared to complex tasks, irrespective of the hand used. However, after 10 training sessions, the electrodes over iM1 activation increased during complex tasks but decreased during simple task for both hands, eliminating significant differences in activation levels between simple and complex tasks. Furthermore, no significant changes were observed in the EEG activation recorded by electrodes over cM1 before and after training. Conclusions: Our data indicated that task complexity affects the EEG activation identified from electrodes over iM1. Specifically, complex task training for both right and left hands enhanced the high-gamma frequency band power recorded from the electrodes over iM1. These findings highlight differential neural responses within specific frequency bands, potentially reflecting distinct impacts of the interventions applied to each group. This supports the idea that iM1 plays a dynamic, task-dependent role in skill acquisition, consistent with prior proposals that iM1 activation scales with task demands.

Background Triple-negative breast cancer (TNBC) is an aggressive breast cancer subtype with limited targeted therapeutic options and marked heterogeneity in response to immune checkpoint blockade. Shikonin, a natural naphthoquinone compound, has shown antitumor and immunomodulatory activities, but its potential molecular targets and immune-related transcriptional programs in TNBC remain incompletely characterized. Methods We integrated systems pharmacology, TCGA-BRCA bulk transcriptomic data, molecular docking, immune infiltration analysis, prognostic modeling, and single-cell RNA sequencing data from GSE176078. Putative shikonin-associated TNBC targets were identified by intersecting predicted shikonin targets, TNBC-related genes, and differentially expressed genes. Functional enrichment analysis was performed to characterize biological pathways. Candidate immune-related genes were prioritized according to their correlation with CD274 expression. The resulting signature was evaluated for associations with immune checkpoint genes, immune cell infiltration, immune activation, computationally inferred immunotherapy-related phenotypes, and overall survival. Single-cell analysis was used to define the cellular distribution of signature genes within the TNBC tumor microenvironment. Results Seventy candidate shikonin-associated TNBC targets were identified and were enriched in immune-related and oncogenic pathways, including PD-1/PD-L1 checkpoint signaling, chemokine signaling, PI3K-Akt signaling, and MAPK signaling. A CD274-prioritized 10-gene immune signature comprising ITK, CCR4, TAP1, JAK3, PIM2, LYZ, SYK, HCK, SOAT1, and PLA2G7 was identified by integrating positive CD274 correlations, false-discovery-rate control, and established immune relevance. High signature scores were associated with elevated immune checkpoint expression, increased immune infiltration, a stronger immune activation index, and lower predicted immune evasion. Molecular docking provided computational support for potential binding compatibility between shikonin and the encoded proteins. At single-cell resolution, the signature genes were distributed across lymphoid, myeloid, epithelial, and stromal compartments, indicating a multicellular immune-related niche. Conclusion This study identifies a shikonin-associated immune signature that reflects an inflamed and checkpoint-enriched tumor microenvironment in TNBC. These findings provide candidate molecular features and a hypothesis-generating framework for further experimental evaluation of the potential immunomodulatory relevance of shikonin in TNBC.