Rodrigues, V. R. | Search bioRxiv

bioRxiv2025

Mitochondria redistribution organizes the immunosuppressive tumor ecosystem

Hostile conditions in the tumor microenvironment restrict cellular respiration, yet mitochondrial metabolism remains indispensable for tumor growth and the activity of immunosuppressive cells. How tumor ecosystems sustain mitochondrial output has been unclear. Here, we show that cancer cells resolve this paradox by acting as hubs of intercellular mitochondrial redistribution. Using mitochondrial reporter systems, we demonstrate that cancer cells import host-derived mitochondria, integrate them into their endogenous network, and subsequently relay these hybrid organelles to neighboring immune cells. Mitochondria redistribution reprograms recipient neutrophils, macrophages, and CD4+ T cells into highly suppressive states but drives CD8+ T cell exhaustion. Within cancer cells, fusion of incoming mitochondria induces filamentous P5CS assembly, enhances biosynthetic output, and enables the refurbishment of damaged organelles into fully functional units. Disrupting mitochondrial redistribution collapses the immunosuppressive ecosystem and impairs tumor growth. Thus, cancer cells do not hoard resources but orchestrate a redistribution program that fortifies their own metabolic resilience, derails anti-tumor immunity, and sustains immunosuppressive partners. HIGHLIGHTSO_LITumor cells regulate their ecosystem by redistributing mitochondria C_LIO_LIRedistributed mitochondria expand immunosuppressive cells but exhausts CD8+ T cells C_LIO_LIMitochondria fusion within cancer cells, which precedes redistribution, optimizes metabolic output by triggering conformational changes in P5CS C_LIO_LIMitochondria fusion allows cancer cells to incorporate and refurbish seemingly incompetent host-derived mitochondria, improving efficiency in the tumor ecosystem C_LI

cancer biology↗

bioRxiv2025

Pumping Up your Predictive Power for Cognitive State Detection with the Proper GAINS

Detecting cognitive states and impairments through EEG signals is crucial for applications in aviation and medicine and has broad applications in the field of human-machine interaction. However, existing methods often fail to capture the fine-grained neural dynamics of critical brain processes due to limited temporal resolution and inadequate signal decomposition techniques. To address this, we introduce the Spectral Intensity Stability (SIS) algorithm, a novel technique that analyzes the stability and competition of dominant brain frequency oscillations across granular timescales (4 ms). Unlike traditional spectral methods, SIS captures rapid neural transitions and hierarchical frequency dynamics, enabling more accurate characterization of task-specific cognitive processes. Our study focuses on EEG data from pilots performing multitasking simulations under hypoxic and non-hypoxic conditions, a high-stakes scenario where cognitive performance is crucial. We divided this multitasking scenario into specific cognitive states, such as task precursor, interruption, execution, and recovery. Our algorithm SIS achieved a 29.8% improvement in cognitive state classification compared to conventional methods, demonstrating superior accuracy in distinguishing both task states and hypoxic impairments. This work is novel because it bridges gaps left by traditional methods by revealing the role of hierarchical spectral dynamics in maintaining cognitive performance. Through the Granular Analysis Informing Neural Stability (GAINS) framework, we reveal how neuronal groups self-organize across fine-grained time scales, providing new understanding of task-switching, neural communication, and criticality. The findings highlight the potential for developing real-time cognitive monitoring systems to enhance safety and performance in environments where cognitive impairments can have serious consequences. Future research should extend these insights by incorporating transient behaviors and spatial dynamics to achieve a more comprehensive framework for characterizing cognitive states.

neuroscience↗