PNAS Nexus

Dense, well-ordered material states of proteins form the amyloid fibers that are a hallmark of neurodegenerative disease in the brain. Beyond forming amyloid fibers, some of these proteins can also adopt other material states termed condensates which are initially liquid-like but evolve to a soft, glassy phase. Fiber growth requires a large supply of monomers and, thus, it is often speculated that fibers emerge from within a dense condensate as it ages and its microscopic dynamics slow into a glassy state. Here, we use the well-established model system Fused in Sarcoma (FUS) to directly observe, quantify and theoretically describe fiber growth and its interplay with condensates. We report the discovery that fibers grow overwhelmingly in the dilute phase surrounding the condensates while the condensates concurrently evolve to a glassy arrested solid. The resulting protein fibers and glassy condensates are both distinct solid-like phases that coexist but do not directly interconvert. Taken together, these findings reveal that there are two competitive aging pathways in FUS condensation that are linked through phase separation kinetics.

Accumulation of proteins such as amyloid beta (Abeta), hyperphosphorylated tau and alpha-synuclein within the brain alters neural information processing and causes neurodegeneration(1-3), but how toxic solutes are cleared from the brain remains highly controversial(4,5). Proposed exit routes include efflux across endothelial cells into the blood(6,7), and movement to the pial surface via vasomotion-induced pumping along spaces within arteriolar smooth muscle(8) or via outflow along the perivascular space of ascending venules promoted by water flux through astrocytes (the glymphatic system(9)). From the pial surface of the brain, drainage may continue to dural lymphatics, along the outer sheaths of exiting cranial nerves and across the cribriform plate(10-14). We now report the presence, in mice and humans, of 2 micron diameter conduits that remove fluorescently labelled tau and Abeta from the brain. These conduits form a spatially-organised mesh within the walls of penetrating arterioles and pial arteries, and around the surface of ascending venules and deep cerebral and pial veins. They course through the pial and arachnoid layers to span the CSF space, wrapping the brain and cranial nerves. They are formed of reticular fibroblasts, which label for VE-cadherin(15) and PDGFRalpha(16), the lymphatic markers(17) podoplanin, VEGFR3 and Prox1, and reticular fibroblast extracellular matrix components collagen I and VI(16,18-20). Parenchymal tau drains from the brain at a similar rate via arteriolar conduits and via conduits around venules, arguing against preferential removal by a glymphatic mechanism. In Alzheimer's disease model mice, Abeta is seen traversing these lymph node-like conduits. Modulation of molecular transfer via this route may accelerate or delay cognitive decline, and slowed transfer from arteriolar to pial-arachnoid conduits may initiate cerebral amyloid angiopathy.

The mechanisms by which coarse woody debris (CWD) affects soil microbial diversity across different spatial scales and forest disturbance regimes remain poorly understood. This study investigated the impact of CWD from multiple tree species on forest floor bacterial and fungal communities under varying landscape-scale conditions, specifically comparing old-growth forests situated on Phaozems and Retisols with mass-windthrow areas located on loamy Retisols and sandy Podzols. We analyzed both chemical compound and metagenomic profiles of 63 CWD-associated soil samples collected from the Kaluzhskie Zaseki Nature Reserve (European part of Russia). High-throughput Illumina sequencing of the 16S rRNA gene and the ITS region was used to profile both bacterial and fungal communities, respectively. Scale-dependent diversity patterns and taxonomic accumulation were assessed using GLM, NMDS, dbRDA, and iNEXT frameworks. Our findings revealed a profound spatial decoupling in forest floor microbial communities, where a localized reduction in alpha-diversity under CWD drove a sharp increase in landscape-scale gamma-diversity. While standard soil physicochemical properties rigidly dictated baseline matrix richness, CWD operated as a powerful micro-environmental hotspot overriding these constraints. Deadwood inputs filtered out dominant matrix-associated taxa, creating highly specialized micro-refugia characterized by high compositional dispersion. This niche selection was particularly pronounced beneath Quercus logs on Phaozems and Retisols. Furthermore, post-windthrow microbial responses were heavily filtered by wood traits and baseline soil textures. On loamy Retisols within the windthrow mosaic, this breakaway dynamic was highly taxon-specific: while Acer and Fraxinus CWD triggered partitioned, site-specific hotspot dynamics yielding an exceptionally large pool of unique ASVs for bacteria, the distinct enrichment for fungal communities was primarily driven by Ulmus CWD and log-free windthrow areas. Ultimately, iNEXT accumulation profiles confirmed that deadwood does not merely multiply common soil taxa, but enriches the forest landscape by injecting critical beta-level heterogeneity into the soil matrix. These insights emphasize the role of diverse CWD retention in buffering forest microbiomes against large-scale environmental disturbances across heterogeneous soil landscapes.

Vascular remodeling responds to local wall shear stress, but transport efficiency belongs to the network as a whole. We connect these scales by minimizing dissipation under a fixed maintenance budget, with vessel cost proportional to mass raised to an exponent b. At an optimum, dissipated power is proportional to vessel cost. This yields the shear set point |{tau} | {propto} r^(b-1){ell}^(b-1)/2 for radius r and length {ell}, with uniform shear recovered at b = 1. The associated local adaptation rule decreases the global functional, although the topology it reaches retains a memory of development. Simulations with 400 and 700 sinks show that staged growth improves transport mainly by allowing pruned connections to regrow. Fluctuating demand sustains loops without increasing the maintenance budget. The local condition fixes allocation on a given support, whereas growth and variable demand shape the topology that survives.

The emergence of treatment resistant mutants is one of the primary contributors to therapy failure in cancer. Evolution-based adaptive therapies aim to exploit the competition between sensitive and resistant cells to prolong therapeutic control. However, in the densely packed tissues of solid tumors, competition is not only determined by cell-intrinsic factors but also a result of local physical interactions between neighboring cells. The successful development of physics-informed adaptive therapies therefore hinges upon the bottom-up integration of tissue mechanics and experimentally grounded models of tumor evolution. Here, we show how population-level treatment response emerges from mechanical interactions between individual cells. Combining genetically tailored therapy-mimicry experiments in spatially structured 2D melanoma colonies with mechanistic, particle-based tissue simulations as digital twins in a real-to-sim-to-real framework, we reveal how treatment-induced changes in mechanical crowding shape a cascade of resistance expansion, spatial competitive escape, and consequent therapy failure. We then link these underlying physical mechanisms to population-level observables in an abstracted mathematical model for reinforcement-learning-based therapy optimization and a distilled treatment-decision-heuristic, which we test experimentally. Together, our results identify mechanical crowding and escape as governing principles of resistance-mediated therapy failure in solid tumours and provide a basis for mechanistically informed, evolution-based treatment strategies.

Tumor progression is shaped by a continuous competition between malignant expansion and immune access within the surrounding microenvironment. Although spatial assays can reveal where T cells accumulate, most current approaches remain descriptive, treating immune organization as a static pattern and failing to infer the latent resistance structure that governs progression. Here we show that changes in peri-tumoral T-cell distribution can support noninvasive tomography of tumor progression. Using spatially resolved human breast tumor sections and controlled numerical experiments, we formulate immune-tumor interaction within a mean-field game framework in which T cells act as agents responding to a heterogeneous microenvironment while the tumor shapes an equivalent barrier field that restricts infiltration. This framework converts boundary enrichment, layered blocking and core penetration patterns into a constrained inference problem whose solution yields quantitative maps of immune exclusion, barrier strength and progression-associated internal states. Forward simulations show that barrier geometry reshapes immune-density equilibria, and inference experiments show that closely related barrier fields can be recovered from immune-density observations under controlled and tissue-shaped proxy settings. By linking observable T-cell redistribution to latent microenvironmental resistance, this approach establishes a route toward noninvasive, repeatable assessment of tumor progression without direct biopsy of the underlying barrier structure.

Environmental exposures shape disease risk, but the generalizability of circulating protein-based readouts of exposures across diverse populations remains unknown. Using plasma proteomic profiles of 5,416 proteins in 10,043 participants from the All of Us Research Program, we evaluated associations with and composite scores of 100+ exposures, spanning adiposity, air pollution, ambient temperature, and substance use. We find that proteomic exposure signatures are largely consistent across populations and socioeconomic strata, with <1% of proteins showing significant cross-population heterogeneity, which included BMI as an exception, with leptin being the most heterogeneous association. Population-specific leptin trajectories adiposity, together with residual leptin-type 2 diabetes associations after BMI adjustment, revealed sex-specific metabolic risk not captured by BMI alone. Aggregated protein scores were largely exposure-specific, but substance-use scores showed cross-prediction and SES scores were broadly associated. PM2.5 protein scores captured within-region exposure variation and outperformed geographic and socioeconomic correlates, but spatial confounders remain embedded within protein-environment associations. Scores trained in UK Biobank transferred to All of Us for biologically proximal exposures, supporting cross-biobank portability. These findings establish plasma proteomics as a scalable framework for exposure measurement across diverse populations, while underscoring that responsible applications require careful consideration of biological context, social patterning, and cohort structure.

Body odors inform human kin recognition. However, underlying chemical mechanisms and how they relate to body odor perception are still unclear. The present study therefore simultaneously examined perceptual body odor similarity according to human raters, its chemical basis and the link between the two in human families. The study included 33 raters who assessed body odors collected from 60 odor donors belonging to 15 biological families. Each family comprised a mother, a father and one adolescent same-sex sibling-dyad (8 sister dyads, 7 brother dyads). Body odor sampling was conducted with cotton pads for presentation to human raters and with thermal desorption (TD) tubes for Gas Chromatography-Mass Spectrometry (GC-MS) analysis. Relatedness and sex predicted perceived body odor similarity in parent-offspring versus unrelated control dyads. Analyses of chemical profiles revealed greater body odor similarity within families than between unrelated individuals. Parallel to the perceptual results, relatedness and sex predicted chemical similarity based on whole odor profiles. Finally, a machine-learning prediction model integrating perceptual and chemical data, revealed a small but significant positive association between chemical similarity of body odor and perceived olfactory similarity according to human raters, suggesting that odor perception is partly informed by chemical characteristics. Overall, the present study extends our understanding of human chemosensory communication and supports the notion of a family-specific olfactory signature.

Cancer progression often requires the accumulation of multiple driver mutations, yet the same set of drivers may be acquired in different orders. How these alternative mutation-order pathways jointly shape tumor clonal structure remains unclear. We develop a multitype branching-process model in which malignant transformation requires two driver mutations and distinguish malignant cells both by their mutation order and by the independent transformation event that founded their clone. Under a successive exponential approximation, we establish point-process limits for the pathway-specific clone-size processes and derive a closed-form expression for the limiting expected Simpson's index of the combined malignant population. When the two mutation orders produce malignant cells with the same net growth rate, the limiting index separates into effective pathway weights, determined by mutation rates and birth-death dynamics at preceding stages, and within-pathway concentration terms, determined by intermediate-to-malignant growth-rate ratios. This decomposition shows that a driver's effect on heterogeneity depends critically on when it is acquired. A strong driver acquired early expands the intermediate lineage and increases the supply of independent malignant founders, whereas the same driver acquired at the final transition strengthens the growth and age advantage of early-founded malignant clones. Under additive fitness effects, these counteracting mechanisms can produce a non-monotone relationship between selective advantage and clonal concentration. We further show that threshold-like non-additive fitness effects can generate highly concentrated malignant populations, while order-dependent terminal fitness leads the faster-growing pathway to dominate asymptotically. Together, these results reveal how mutation order, mutational accessibility, selection, and epistasis jointly determine lineage-level intratumor heterogeneity.

Raman spectroscopy (RS) has been shown to differentiate various disease states in tissue samples, yet the impact of sample substrate on spectral quality and downstream machine-learning (ML) performance is under-explored. We collected 960 spectra from 36 formalin-fixed, paraffin-embedded colonic specimens mounted in parallel on calcium fluoride (CaF2) and mirrored stainless-steel (SS) slides. Raw SS spectra were more intense than CaF2, and routine dewaxing left prominent paraffin peaks on CaF2 that were largely absent on SS. Extending CaF2 xylene immersion to 48 h reduced key paraffin peaks by 11 to 23%, aligning its biochemical profile with SS. Nested cross-validated classifiers were built to distinguish true disease (T1) from epithelial misplacement (EM). The highest accuracies were observed on SS (0.65 - 0.66), while CaF2 improved from 0.41 - 0.57 to 0.65 - 0.69 after extended dewaxing, chiefly via gains in recall. Although optimal dewaxing renders CaF2 diagnostically non-inferior, SS still offers superior accuracy, faster preparation, at approximately 4% of the cost, supporting its integration into scalable, AI-enabled RS pathology workflows.

Biofilm formation--the establishment of cellular communities within a self-secreted polymer matrix--is a behavior exhibited by almost all species of bacteria. Bacterial biofilms are well described as viscoelastic materials, with properties that grant physical advantages, such as elastic resilience and viscous adaptability. Additionally, many biofilm-forming species produce a subpopulation of highly resilient spores. In the model biofilm- and spore-forming species Bacillus subtilis, sporulation and matrix production are regulated by a common gene pathway, provoking the question of how sporulation influences biofilm viscoelastic properties. Investigating this point will facilitate the management of both salutary and deleterious biofilms, especially through manipulating their establishment and dispersion. Here, we investigate the interplay of sporulation and viscoelastic properties using rheological measurements of B. subtilis biofilms with varied matrix and spore production. We find that, to a significantly greater extent than matrix production, biofilm physical development is strongly altered by activation of sporulation through the spo0A regulation pathway. Spore-deficient strains initially establish physically robust biofilms with linear viscoelastic properties and recovery behavior distinct from spore-producing biofilms. However, spore-deficient biofilms fail to maintain their physical properties over time. In contrast, spore-producing wild-type and matrix-mutant biofilms exhibit more stable physical properties. Our results demonstrate that cell-level gene regulation is associated with macroscopic mechanical transitions in cellular communities, with sporulation granting not only a cellular-level survival advantage, but also greater community-level physical stability.

We investigate the dynamics of the spread of the infection due to a phage- during the range expansion of an E coli colony. We find a rich panoply of spatio-temporal dynamics at large colony-level length scales, arising due to the interplay of mechanical forces, growth and viral infection dynamics at smaller cellular length scales. Strikingly, the phages "surf" the front of the growing bacterial colony by hitchhiking on E coli that are advected due to the growth of bacteria in the colony, resulting in an anisotropic spread of the phages. We identify microscopic processes - of the phage release during lysis (occurring on short millisecond timescales at length scales close to that of a single bacterium) and local nematic alignment of the rod-like E coli bacteria (occurring on timescales comparable to the bacterial growth rate and the length scales of a few bacterial cells) - that enhance the advective effects driving the hitchhiking behavior. Combining our experiments with a mathematical model, we explain the multiple spatio-temporal dynamical regimes - from the coexistence of uninfected bacteria, resistant (lysogenic) cells and phages, to fixed points where the entire population turns resistant or remains uninfected. Our work broaches a new frontier in the investigation of eco-evolutionary processes arising from the mechanical and ecological forces due to the interactions between viruses and their hosts.

H2O2 released to the extracellular space (ECS) regulates diverse physiological processes, yet its concentrations and spatial distribution in tissues remain poorly defined. This uncertainty hampers mechanistic understanding of redox signaling. Here, we used reaction-diffusion modeling to estimate extracellular H2O2 concentrations and transport ranges in various scenarios. Idealized analytical models were combined with numerical models incorporating localized NADPH oxidase (NOX) clusters, ECS microstructure, membrane permeability, and the thioredoxin- and GSH-dependent clearance systems. Using maximal neutrophil and NOX superoxide/H2O2 release rates, we obtained upper bounds for extracellular H2O2. Adjacent to isolated average-sized, fully active NOX2 clusters H2O2 peaked at ~540 nM at adhesion cell-cell separations, and decreased radially over ~50-100 nm. At the receptor cell surface, peak concentration decreased inversely with intercellular separation, to <5 nM at 1 m separation. Radial decrease here, for this wide separation, was over ~2.5 m. Even the former maximal extracellular concentrations induce just a minimal, highly localized oxidation of the intracellular Prdx, Trx and GSH pools. In turn, maximally activated neutrophils carry ~2000 such NOX2 clusters, inducing 10s of M peak ECS H2O2 concentrations. These cause extensive Prdx and Trx oxidation near the exposed membranes. However, the GSH-dependent system still sustains a strong transmembrane gradient if the permeation barrier remains intact, and ECS H2O2 concentrations decay to sub-M within a few m of the source cell. Extracellular H2O2 concentrations scaled linearly with source flux in all the examined conditions. These results establish stringent constraints on autocrine, juxtacrine and next-cell paracrine H2O2 signaling.

Hyaluronan (HA) is a principal component of the tumor glycocalyx in colorectal cancer (CRC). However, how the disease progression is linked to HA abundance and its nanoscale organization remains unclear. Single-molecule measurements of surface glycans on cell membranes and extracellular vesicles (EVs) have not yet been correlated. In this work, using single-molecule force spectroscopy, we mapped HA density and chain length on CRC cells and their EVs across Dukes' stages. HA density increased with stage in both compartments, but their organization diverged. Cell-surface HA became progressively fragmented, whereas EVs remained enriched in short HA chains at every stage. EVs, therefore, appear to select HA during formation rather than inherit it from the parent cell. This divergence had mechanical consequences. Both cells and EVs softened with stage, and removing HA reversed this softening. In addition, coarse-grained membrane simulations revealed that both HA chain length and surface density regulate membrane wrapping, with chain length primarily influencing wrapping kinetics and surface density affecting the final wrapping extent. These findings provide a physical basis for the differences we observed in EV uptake. Reprogramming stage D cells with exogenous high-molecular-weight HA reversed this signature, lowering EV surface HA density, stiffening the vesicles, slowing migration, and suppressing EV uptake by recipient cells. These findings establish HA surface architecture as a stage-encoded and experimentally reversible determinant of CRC progression.

Myelin membranes are tightly connected to the axon, forming an electrical route for rapid saltatory conduction of action potentials from node to node. Beneath the myelin, adjacent to the node, lie voltage-gated potassium (K+) channels, whose fundamental role in conduction remains poorly understood. Constrained by biological data, we developed a finite element model of a node of Ranvier encompassing an adaxonal membrane separating oligodendrocyte cytoplasm from the periaxonal space, and solved the full coupled set of physical equations governing electrodiffusion and voltage profiles at the nanoscale. Remarkably, we find that nodal action potentials invert at the inner adaxonal myelin membrane. The hyperpolarization-driven opening of myelinic Kir4.1 channels produces an instantaneous, powerful K+ prebuffering, clamping the periaxonal K+ concentration and enabling high-frequency action potential generation. Together, these findings indicate that the periaxon maintains an electrical feedback loop with the node, and suggest a key evolutionary advantage of juxtaparanodal K+ channel positioning.

The longitudinal effects of initial influenza exposure on the magnitude, persistence, and antigen specificity of antibody responses during infancy remain incompletely understood. We investigated humoral antibody responses following primary influenza infection or seasonal vaccination in a prospective US birth cohort with weekly respiratory surveillance for influenza infection. Influenza-specific serum IgG binding to H1 and H3 haemagglutinin (HA) antigens, HA inhibition (HAI), and live-virus neutralizing antibody responses were assessed longitudinally. To minimize influence of maternally derived antibodies, analyses of primary exposure responses were restricted to infants for whom influenza-specific maternal antibodies had declined below the assay detection limit before exposure. Antibody responses were compared following primary infection and vaccination and examined after subsequent annual vaccination. We found that maternal influenza-specific IgG declined rapidly during early infancy. Among infants without detectable pre-exposure influenza-specific antibodies, primary influenza infection was associated with greater post-exposure antibody responses and less measurable decline over follow-up than primary vaccination. These groups differed in age, calendar season, and exposure characteristics, limiting direct attribution of these differences to route of exposure. In infants with previous influenza infection followed by vaccination, responses after subsequent vaccination initially showed greater binding to the previously infecting subtype among the tested HA antigens. With repeated vaccination, responses became more distributed across the tested antigens. Our findings reveal differences in the magnitude, persistence, and antigen specificity of antibody responses according to the nature and sequence of influenza exposure. By prospectively capturing early-life exposures, this study provides longitudinal evidence linking exposure history to subsequent humoral antibody responses.

The emerging neonatal bacterial pathogen Paenibacillus thiaminolyticus causes sepsis and postinfectious hydrocephalus, yet few tools are available to study or specifically detect it. We developed fluorescent probes based on cell wall-binding domains (CBDs) from bacteriophage-derived cell-wall hydrolases. CBDs can target structurally conserved cell-wall glycans, making them attractive affinity reagents for bacterial detection. None of the 11 probes we designed labeled intact cells under standard conditions, and we identified a surface layer (S-layer) that prevented access to their cell-wall targets. Brief acidic treatment (pH 2.0) released abundant high-molecular-mass proteins from the cell surface and enabled labeling by five distinct CBD probes, each containing a single C-terminal S-layer homology domain. Mass spectrometry identified the main released protein as an ortholog of the P. alvei SpaA S-layer protein, which we designate SlsA. Across 26 surveyed P. thiaminolyticus genomes, we identified four distinct SlsA variants with 58-79% pairwise amino acid identity, encoded within a conserved cluster homologous to the P. alvei S-layer-associated locus. After either the acidic treatment or a quick flame fixation, the lead probe mGL-BDPt9 labeled six P. thiaminolyticus strains, including three Ugandan clinical isolates, as well as a P. dendritiformis clinical isolate from a US infant, and three additional Paenibacillus species. mGL-BDPt9 also distinguished P. thiaminolyticus from five gram-positive sepsis pathogens in pairwise mixtures and detected it in a five-species suspension. Together, these findings establish the presence of an S-layer in P. thiaminolyticus and provide a rapid fluorescent labeling strategy for multiple Paenibacillus pathogens associated with neonatal paenibacilliosis.

The maternal brain exhibits impressive plasticity, undergoing many anatomical and functional alterations over the transition to parenting. Such alterations can reflect maternal adaptation to offspring needs, aligning with the onset and maintenance of maternal care behaviors. These brain-wide neural changes occur across stages, starting during pregnancy and continuing through the peripartal transition. We therefore wanted to understand brain changes with pregnancy, parenting, and care behaviors over time. Many brain regions have been implicated in the coordination of maternal adaptation and corresponding care behaviors. We used computational modeling of multi-region neural oscillation data to identify distinct electrical networks during naturally-occurring care behaviors and across multiple maternal stages in outbred, highly maternal mice. This work demonstrates that multi-region oscillatory electrical dynamics at high spatiotemporal resolution reflect these functions. Distinct, discriminative networks predict maternal behavior and stage, showcasing network adaptation with parental transition. Maternal behavior and stage also had substantial effects on other distinct, multi-region oscillatory electrical networks relevant to stress susceptibility, further linking maternal adaptation to the neurophysiology of stress. While these stress networks were perturbed by maternal experience of early life stress, networks trained on maternal behavior and stage remained robust against such perturbation. This suggests a uniquely persistent strength of maternal electrical dynamics. Together, this work supports the role of oscillatory electrical dynamics as networks underlying fundamentally conserved behaviors and transitions, demonstrating wide relevance and significance to brain-behavior discovery.

Single-cell transcriptomic atlases resolve thousands of putative brain cell types, yet common analytical workflows often rely on low-dimensional embeddings that can distort neighborhood relationships and obscure continuous variation between closely related populations. We introduce single-cell Discrete Morse Graph Construction (scDMGC), a deterministic framework based on topological data analysis and discrete Morse theory that extracts a compact graph from neighborhood structure in high-dimensional gene-expression space. Because graph edges are derived from the original k-nearest-neighbor complex, scDMGC provides an interpretable multiscale representation of transcriptomic organization without requiring a low-dimensional embedding. Local maxima represent coherent transcriptional states, saddles quantify their separation, and gradient paths capture intermediate states and continuous transitions. Applied to cortical and hippocampal datasets, scDMGC recovers established inhibitory-neuron classes and elucidates transcriptional gradients. In mouse whole-cortex data, Morse graph structure evaluates cell-type hierarchy and type robustness. Persistence across scales provides a quantitative measure of cell-type identity and discrete versus continuous relationships. Finally, in Alzheimers disease single-nucleus data, scDMGC distinguishes changes in cell-type abundance from disease-associated shifts in transcriptional state. scDMGC therefore provides a multiscale framework for quantifying whether transcriptional populations form persistent cell types, how strongly external annotations are supported by intrinsic data structure, how cell types relate to one another, and where discrete organization transitions into continuous variation.

Environmental microplastics and nanoplastics (MNPs) are emerging contaminants that accumulate in human tissues, including the brain, yet their mechanistic impact on the nervous system remains poorly understood. Converging postmortem evidence indicates increased MNP burden in brains from individuals with dementia, suggesting a potential link between plastic accumulation and disorders of the nervous system. However, whether MNPs directly contribute to brain aging and ensuing neurodegenerative processes, or disrupt neurodevelopment, is unknown. Here, we show that exposure to environmentally relevant MNPs induces cellular senescence and innate immune transcriptional programs in human brain organoids. Using region-specific cortical organoids, we demonstrate that synthetic polystyrene (PS), polyethylene terephthalate (PET), low-density polyethylene (LDPE), and high-density polyethylene (HDPE), as well as environmental ocean-derived MNPs (eMNPs) isolated from the coast of Hawaii, elicit a robust neuroinflammatory response. Transcriptomic analyses revealed activation of senescence-associated secretory phenotype (SASP) pathways. MNP exposure further disrupted neurodevelopmental trajectories, impairing neuroectodermal differentiation and redirecting lineage commitment toward mesoderm-like states, with concomitant enrichment of choroid plexus-like populations and a marked imbalance in neuronal and glial differentiation. These developmental alterations occurred in parallel with a pro-inflammatory and senescent microenvironment, suggesting coordinated disruption of developmental and aging programs. Importantly, high-density multielectrode array recordings revealed that MNP exposure altered electrophysiological activity and neuronal network dynamics, demonstrating that MNP-driven perturbations translate into dysfunctional neurological outcomes. Collectively, our findings identify MNPs as potent disruptors of human neurophysiology, linking plastic exposure to altered developmental trajectories, cellular senescence, neuroinflammation, and impaired neuronal network activity, providing mechanistic insights into how plastic accumulation may contribute to impaired brain dynamics.