Biology subjects

Zhu, Y.

Publications and source records attributed to Zhu, Y..

At least 19 recordsLinked to original sources

bioRxiv2026

Endosperm secretion remodels the maternal seed coat

In flowering plants and mammals, maternal tissues must accommodate the growth of the offspring they enclose. The maternal seed coat expands around the developing embryo and endosperm. Endosperm pressure and hormonal signals coordinate seed-coat development1,2, but whether the endosperm directly promotes maternal cell elongation remains unclear. Here we show that the coenocytic Arabidopsis endosperm directly supplies cell-wall-loosening proteins to maternal seed-coat walls. The seed-size-regulating HAIKU-WRKY10 pathway activates an endosperm secretory programme enriched in cell-wall-associated proteins. These proteins spread through a shared extracellular domain across multiple inner seed-coat layers, revealing an extensive functional maternal-filial interface through which the endosperm reaches maternal cells it does not directly contact. Among these proteins, three expansins are necessary and sufficient for maternal cell elongation and seed growth. The endosperm therefore promotes its own growth by enabling expansion of the maternal tissues that enclose it. Paternal DNA methylation and maternal Polycomb activity jointly regulate this programme, with Polycomb also required for timely shutdown of expansin expression. These findings link parental epigenetic states to maternal tissue expansion through proteins supplied by the offspring. This cross-generational control of growth parallels epigenetically regulated signaling from mammalian extraembryonic tissues3, suggesting a shared strategy for adapting the maternal environment to offspring development.

plant biology↗

bioRxiv2026

ATR is a master regulator of the oocyte meiotic prophase checkpoint

During meiotic prophase, programmed double-strand breaks (DSBs) initiate meiotic recombination, and defects in this process result in persistent DSBs and chromosome asynapsis, triggering checkpoint-mediated oocyte elimination before primordial follicle formation. However, how the oocyte meiotic prophase checkpoint is regulated remains unclear. ATR is a DNA damage response kinase essential for male meiosis, but its role in female meiosis is poorly characterized. Here, we identify ATR as a master regulator of the oocyte meiotic prophase checkpoint. ATR loss fully rescues the survival of Dmc1-/- oocytes, which exhibit persistent DSBs and extensive chromosome asynapsis. ATR loss also fully rescues the survival of asynaptic Spo11-/- oocytes and Trip13-/- oocytes with aberrant checkpoint activation, demonstrating an essential role for ATR in the chromosome asynapsis checkpoint. Mechanistically, BRCA1 is required for ATR localization to unsynapsed chromosome axes, whereas ATR is dispensable for BRCA1 localization, establishing a BRCA1-ATR regulatory hierarchy at unsynapsed chromosome axes that is conserved between oocytes and spermatocytes. Together, these findings place ATR at the center of the oocyte meiotic prophase checkpoint and define a BRCA1-ATR signaling axis that links chromosome asynapsis to oocyte elimination.

developmental biology↗

bioRxiv2026

Enzymatic extracellular matrix remodeling in ex vivo slices of aged myocardium

Cardiac aging is accompanied by extracellular matrix (ECM) remodeling and increased myocardial stiffness, which may contribute to age-associated functional decline. However, whether direct remodeling of the aged cardiac ECM can modify myocardial mechanics and function remains poorly understood. Here, we established an ex vivo living myocardial slice platform to investigate whether enzymatic remodeling of the aged ECM can alter myocardial structure, mechanics, and function. Left ventricular myocardial slices (LMS) from young and aged mice were maintained under static stretch for 48 hours using a custom 3D-printed culture setup. Aged slices were treated with collagenase and subsequently characterized using quantitative imaging, tensile testing, contractility measurements, and transcriptomic analysis. Aged myocardium exhibited increased collagen and fibronectin abundance, altered collagen network architecture, and increased stiffness compared with young tissue. Collagenase treatment reduced collagen and network complexity and reduced myocardial stiffness toward young tissue values without compromising ultimate tensile stress. Despite these structural and biomechanical changes, age-associated differences in myocardial contractility remained comparable across groups. Transcriptomic analysis indicated that treated aged tissue largely retained its age-associated molecular phenotype, despite pathway-level shifts involving metabolism, cardiac function, and inflammatory responses. These findings demonstrate that enzymatic ECM remodeling can modify the aged myocardial mechanical environment while selected functional and transcriptional features of aging persist over 48 hours. The LMS platform provides a controllable ex vivo tissue-level approach for investigating ECM contributions during cardiac aging and evaluating strategies for ECM engineering.

bioengineering↗

bioRxiv2026

TiSAM: fusing spatial and histopathology foundation models for whole-slide image segmentation

Semantic segmentation of whole-slide images (WSIs) quantifies tissue composition and architecture, but existing models require extensive annotation and lose accuracy as the number of tissue classes increases or on heterogeneous, cross-scanner datasets. Here, we present the Tissue Segment Anything Model (TiSAM), which fuses SAM3 spatial features with UNI2-h pathology features within a multi-scale decoder. Because public benchmarks contain few tissue classes, we release MegaMouse, comprising 36,833 annotations of 52 tissue classes from 12 mouse organs, and an 11-class human pancreas dataset. TiSAM achieved the highest overall performance across four public datasets compared to existing convolutional neural network and vision transformer models, maintained high accuracy on MegaMouse, and maintained high accuracy in the human pancreas dataset when trained on as few as 5 annotated WSIs where previous integrations of SAM with pathology foundation models did not. TiSAM segmentations were also more consistent across eight slide scanners compared to other models. These results establish TiSAM as a general and highly adaptable framework for tissue segmentation, enabling studies containing many tissue classes, limited annotations, or images from multiple scanners.

bioinformatics↗

bioRxiv2026

Decomposing scanner batch effects and their impact on pathology foundation models

Pathology foundation models (PFMs) are expected to represent the same tissue in the same way on any scanner, but their embeddings still carry scanner signals. Scanner-related image differences and the scanner sensitivity of PFMs have each been described. How tissue-dependent changes in color and spatial frequency relate to shifts in PFM representations, and what this means for correction, is less understood. We imaged 103 slides from 37 normal tissue types on six scanners (PanNormal; 95,780 matched locations) and used the real paired images as targets. We used the public PLISM dataset for external validation. First, we decomposed scanner differences into image properties. Color and spatial frequency changed together, by amounts that depended on tissue type. Second, corrections that matched these measured properties brought images closer to the target more reliably than representations. Pix2Pix reduced the image residual by 69% but increased UNI distance to the target by 27%. The same frequency matching helped one scanner and hurt another. Probes still distinguished corrected from real target embeddings after every correction. Third, changing one frequency band at a time showed that PFMs differ in how strongly each band moves them and whether it moves them toward the target. Across eight PFMs pretrained on whole-slide image tiles, the models that moved least under these small changes were the most robust to real scanner differences (Spearman {rho}=-0.90). Aligning images and aligning representations are therefore different goals. The gap between them depends on scanner, tissue, and model.

bioinformatics↗

bioRxiv2026

Stimulus overlap confounds generalization in EEG foundation-model benchmarks

Neural decoding benchmarks commonly evaluate generalization across participants while reusing the same experimental stimuli in training and test sets. This design cannot distinguish transfer to new stimuli from recognition of familiar material, a distinction that is increasingly important for electroencephalography (EEG) foundation models, pretrained models designed to learn reusable neural representations. Here we introduce a training-matched audit that varies stimulus overlap while holding test trials, training participants and stimulus counts fixed. Across ten tasks from seven EEG emotion datasets, stimulus overlap increased differential-entropy decoding accuracy in every task and accounted for 77% of above-chance seen-stimulus performance on FACED-9. Across representations, overlap-dependent gains tracked stimulus identifiability; for CBraMod and LaBraM, advantages over input-matched handcrafted features were concentrated on familiar stimuli. Architecture-matched random controls nevertheless showed transferable benefits of pretraining on unseen stimuli. These results separate participant generalization from stimulus generalization and provide a framework for evaluating both in neural decoding benchmarks.

neuroscience↗

bioRxiv2026

Identifying neural correlates of auditory perceptual awareness and deviance using a no-report inattentional deafness paradigm

The relationship between neural processes supporting perception, deviance processing, and post-perceptual task demands during auditory processing is not well understood. We used multitone masking and a no-report inattentional deafness paradigm to dissociate neural correlates of auditory perceptual awareness, deviance processing, and task demands. Evoked responses to physically identical target-tone pairs were recorded across three phases differing only in task instructions. In Phase A, human participants remained nave to (and thus unaware of) the target tones. In Phase B, participants were informed about (and thus aware of) the target tones. In Phase C, participants remained aware of the target tones and judged the duration of the silent gap between them, rendering them task-relevant. When participants were aware of them, target tones elicited an auditory awareness negativity and an increased positivity in the P3 window), with larger responses when target tones were additionally task-relevant. Furthermore, though largest in Phase C, deviant stimuli elicited a mismatch negativity across all task conditions, while a significant P3 to deviants was only observed in Phase C. Thus, early and late responses can be independently modulated by awareness, deviance, and task-relevance, indicating that they do not necessarily rely on shared neural mechanisms despite overlapping spatiotemporal profiles.

neuroscience↗

bioRxiv2026

Tissue retention of dendritic cells drives age-associated protective tolerogenic lymphoid structures

Ectopic lymphoid structures are typically associated with chronic tissue inflammation in autoimmunity and cancer, where they can amplify local immune responses. Similar structures arise spontaneously with age, yet their origin and function remain unclear. Here we identify tissue retention of mature migratory conventional dendritic cells (cDCs) as a driver of age-associated lymphoid organization. Mature cDCs accumulated within lymphoid structures in aged human and mouse tissues. We demonstrate that impaired cDC egress or pharmacological cDC expansion induced de novo structures in mice across multiple otherwise homeostatic organs without associated pathology. Strikingly, senescence-associated tissue cues, which promoted a distinct cDC maturation state, were required for lymphoid niche initiation. Unlike inflammatory structures described in disease, these cDC-driven structures preferentially accumulated tissue-adapted regulatory T cells and protected against inflammatory injury, revealing a previously unrecognized regulatory dimension of age-associated lymphoid organization.

immunology↗

bioRxiv2026

In situ architecture of the basal body reveals regionalized assembly and central pair microtubules nucleation

The basal body (BB) is essential for axoneme assembly and ciliary function, and its defects are associated with ciliogenesis disorders and ciliopathies (1,2). However, the molecular basis of the BB's region-specific transitions along the proximal-distal axis, and the mechanism by which ciliary central pair (CP) microtubules are nucleated during ciliogenesis, have remained largely unknown. Here, we resolve the subnanometer architecture of native BBs in mammalian multiciliated cells using cryo-electron tomography and subtomogram averaging, and identify 11 ciliary-base microtubule-associated proteins (CMAPs), including 5 previously uncharacterized core components. These CMAPs localize specifically along ciliary base that facilitate the triplet-to-doublet microtubule transition. We further identify luminal gamma-tubulin ring complexes (gamma-TuRCs) anchored to the microtubule wall via the augmin complex, and propose that they may serve as candidate nucleation sites for CP microtubules biogenesis. Together, these findings define a molecular blueprint of the BB and provide a structural framework for understanding how regional architectural specialization and luminal nucleation collectively drive ciliary assembly and how their dysfunction causes ciliopathies.

cell biology↗

bioRxiv2026

Exacerbation of neurodegeneration by a metabolically engineered bacterium in a mouse model of tauopathy

BackgroundTherapeutics that modulate peripheral and central immune responses are emerging as promising approaches for neurodegenerative disease. However, the biological context in which these interventions are deployed may critically influence therapeutic outcomes. An attenuated Brucella melitensis 16M strain and a similar strain engineered to express the metabolite indole have previously demonstrated therapeutic efficacy in preclinical models of cancer and autoimmunity through immune system modulation. Here, we tested whether repeated administration of these bacterial strains could modify pathological outcomes in a mouse model of tauopathy. MethodsAttenuated Brucella strains were administered to transgenic mice overexpressing mutant tau protein on a human APOE4 knock-in background via intraperitoneal injection every 5 weeks starting at 6 months of age. Mice were analyzed at 9.5 months of age for tau pathology, neurodegeneration, and changes in innate and adaptive immune responses. ResultsBrucella strains distributed predominantly in the periphery following repeated intraperitoneal treatment in transgenic mice, with minimal detection in the brain and no detection in the dural meninges. Repeated administration of either bacterial strain was well tolerated, with no evidence of adverse safety events. Surprisingly, repeated treatment with the engineered Brucella strain exacerbated neurodegenerative pathology, resulting in reduced hippocampal volume and increased phosphorylated tau pathology compared with control- and non-engineered Brucella strain -treated animals. Immunohistochemical analyses revealed increased numbers of hippocampal CD4+ T cells following treatment with either Brucella strain relative to PBS controls. However, only treatment with the engineered Brucella increased microglial reactivity within the hippocampus. ConclusionThese findings demonstrate that peripheral administration of an engineered bacterial therapeutic can differentially influence neuroimmune responses and disease progression. These results underscore the importance of disease context when developing bacteria-based immunomodulatory therapies for neurodegenerative disorders.

neuroscience↗

bioRxiv2026

Tractable and Thermodynamically Consistent pKa Prediction via First-Dissociation Aggregation

Ionization governs molecular behavior, yet predicting aqueous pKa accurately and tractably remains a fundamental challenge. Rigorous ensemble methods require enumerating a protonation-state space that grows exponentially with the number of ionizable sites, while fast graph predictors return numbers without thermodynamic consistency. Here we derive an exact thermodynamic identity showing that the macroscopic first-dissociation constant is fully determined by protonated-microstate populations and unique first-deprotonation events, eliminating the deprotonated ensemble algebraically and reducing aggregation to O(n+E) operations. We implement this identity in DTi-pKa, a dual-head graph neural network whose free-energy and dissociation heads are coupled by thermodynamic constraints. On four external benchmarks (355 molecules), DTi-pKa achieves a pooled MAE of 0.5665 pKa units, with 0.6285 on the 169 records lacking training-cache matches, while providing site-resolved micro-pKa values and protonation-state populations. Controlled ablations show that constraint placement at the level of the reported macroscopic equilibrium matters more than microscopic label precision--a design principle transferable to physics-informed machine learning beyond chemistry. Closure diagnostics expose numerical self-consistency as an open frontier, which we report transparently. By replacing an intractable computation with a physical identity, DTi-pKa unifies macroscopic accuracy and microscopic interpretability in a single framework.

bioinformatics↗

bioRxiv2026

Pathological tau leads to network hyperexcitability through neuronal-subtype-specific functional impairment

Pathological tau disrupts neuronal activity and brain function in Alzheimer s disease and other tauopathies. However, the underlying mechanisms for neuronal network dysfunction remain largely unknown. Using human inducible pluripotent stem cell (iPSC) - derived neurons, we show that the familial MAPT P301L mutation leads to neuronal network hyperexcitability. Imbalanced excitation and inhibition were attributable to neuronal subtype-specific tau pathology that was associated with different alterations of tau interactomes in excitatory versus inhibitory neurons. Suppressing enhanced excitatory synaptic transmission or blocking Ca2+ influx resulting from enhanced P301L tau/AHNAK interaction in inhibitory neurons rescued the neuronal network hyperexcitability. This study expands our understanding on how disease-causing tau mutations alter the excitatory/inhibitory balance, leading to network dysfunction in human neurons.

neuroscience↗

bioRxiv2026

Bayesian inference of global land plant diversification dynamics across the Phanerozoic

Underlying diversification patterns and potential drivers of land plants remain puzzling, particularly at deep-time and global scales. Here, we reconstruct the diversification dynamics of land plants using an updated time-calibrated phylogeny comprising approximately 30,000 extant species, and nearly 40,000 fossil occurrences within the Bayesian birth-death frameworks. Our analyses indicate that angiosperms exhibit the highest diversification rates, whereas ferns underwent a marked diversification increase during the Cretaceous, coincident with the rapid radiation of angiosperms. Among the major Phanerozoic mass extinctions, the Cretaceous-Paleogene event has the most significant impact on land plant diversity, with estimated genus-level losses of 13%, 14%, and 4% in bryophytes, pteridophytes, and gymnosperms. We identify a pattern consistent with competitive displacement scenario, in which pteridophytes origination rates declined as gymnosperm diversity increased, accompanying the transition from pteridophyte- to gymnosperm-dominated floras. We find that plant-insect interactions have originated as early as the emergence of pteridophytes, potentially promoting the diversification of pteridophytes and gymnosperms. During the Cretaceous, these associations shifted toward angiosperms, as indicated by a positive relationship between insect diversity and angiosperm origination rates. Finally, continental fragmentation, fluctuations in aridity, atmospheric carbon and sedimentary dynamics, showed stronger associations with the successive rise and decline of major land plant groups.

evolutionary biology↗

bioRxiv2026

TRIM21 licenses pancreatic acinar fate by modulating BiP phase state through VCP-dependent retrotranslocation

The endoplasmic reticulum (ER) chaperone BiP/GRP78 sits at the center of the proteostasis network, coordinating unfolded protein response (UPR) signaling and supporting oncogenic programs of plasticity, metastasis, immune evasion, and chemoresistance. While BiP undergoes liquid-liquid phase separation in vitro, whether mammalian cells dynamically tune this physicochemical behavior to prevent functional exhaustion or pathological condensation under sustained ER stress has remained unclear. Here, we identify the E3 ubiquitin ligase TRIM21 as a phase-state regulator that suppresses BiP's liquid-to-solid phase separation, clearing, and preventing insoluble aggregates-thereby controlling BiP's localization and availability to sustain the adaptive UPR under ER stress. We found that during ER stress, BiP is prone to liquid-to-solid phase separation, a transition that renders the chaperone dysfunctional. TRIM21 is recruited to BiP, where it directly polyubiquitinates BiP at specific K547/553/554/556 sites with K6-, K27-, K33-, and K63-linked chains; VCP recognizes these marks and extracts BiP from the ER lumen via ER-associated degradation (ERAD), coupling ubiquitin tagging to retrotranslocation. This preserves chaperone availability and sustains adaptive UPR-a homeostatic mechanism broadly relevant to UPR-driven diseases. In vivo, genetic ablation of Trim21 in KrasG12D/+; Pdx1Cre/+ mice triggers aberrant BiP solidification while curtailing acinar-to-ductal transdifferentiation and tumorigenesis; notably, TRIM21 co-localizes with BiP condensates in pre-malignant human pancreatic lesions, underscoring the clinical relevance of this regulatory axis. Our findings define the TRIM21-BiP axis as a phase-control system at the interface of proteostasis and stress adaptation, offering a new framework with translational potential.

cell biology↗

bioRxiv2026

Programmable sequence-resolved in situ profiling of glycoRNA-protein interactomes by GlycoRNA-Map

Cell-surface glycoRNAs participate in diverse biological processes, but they were investigated as pooled populations and the protein interactome of individual glycoRNA species remain unresolved. Here we develop GlycoRNA-Map, a programmable photocatalytic proximity-labeling method that maps proteins surrounding sequence-defined endogenous glycoRNAs on living cells. A sialic-acid-binding aptamer and an RNA-hybridization probe jointly recruit a fluorophore-modified oligonucleotide through dual recognition of the glycan and RNA moieties of glycoRNAs. Light-activated biotinylation followed by quantitative mass spectrometry identified 200-418 enriched proteins for each of five glycoRNAs in A549 cells. Comparison of these proteomes revealed limited overlap among different glycoRNA sequences and across cell types, demonstrating that glycoRNA-associated protein environments depend on both RNA identity and cellular context. Transforming growth factor-{beta} receptors 1 and 2 (TGFBR1 and TGFBR2) were identified in the proximal proteomes of multiple glycoRNAs. Removal of cell-surface RNAs enhanced TGF-{beta} receptor signaling and promoted cell migration, demonstrating that glycoRNAs can functionally regulate extracellular signaling by interacting with their protein neighborhoods. GlycoRNA-Map thus provides an accessible strategy for resolving sequence-specific glycoRNA-protein interactome and discovering their roles in membrane signaling.

biochemistry↗

bioRxiv2026

DECIPHER integrates disentangled representation learning and prototype-based cell-type deconvolution across molecular modalities

The growing availability of single-cell resources creates new opportunities to extract cell-type-resolved information from the vast body of existing bulk omics data through cell-type deconvolution. Conventional deconvolution methods often rely on linear mixture models or specific probabilistic assumptions and can be sensitive to batch effects, whereas many deep-learning approaches are modality-specific or lack a unified end-to-end learning framework. Here, we developed DECIPHER, an end-to-end representation-learning framework for cell-type deconvolution that can be applied across multiple molecular modalities. DECIPHER learns a domain-constant representation (Zc) for deconvolution and a domain-specific representation (Zs) to model domain-associated variation. By integrating nonlinear representation learning with differentiable non-negative least-squares optimization, DECIPHER estimates cell-type proportions from Zc. Across simulated datasets, experimentally generated bulk-cell mixtures, real-world datasets, and multiple molecular modalities, DECIPHER showed robust and competitive cell-type deconvolution performance. Beyond cell-type proportion estimation, the learned Zc supported chronological age prediction across independent cohorts and prognostic stratification in lung adenocarcinoma, demonstrating that DECIPHER can transform high-dimensional bulk omics data into low-dimensional, biologically informative representations. DECIPHER thus broadens the utility of existing bulk omics resources for biological discovery and clinical research.

bioinformatics↗

bioRxiv2026

PTMExplorer: A Multi-Dimensional Integrative Visualization Platform for Protein Post-Translational Modification Function and Structure

Deciphering the functions of post-translational modifications (PTMs) is a critical bridge connecting large-scale modification proteomics data to mechanistic studies. However, most existing tools for visualizing PTM omics data are limited to site catalogs or single-dimensional feature displays. They lack the capability to simultaneously map user-derived differential modification sites onto multi-dimensional contexts, including protein three-dimensional (3D) structure, evolutionary conservation, functional sites, and disease associations. This limitation makes it difficult for researchers to rapidly assess the biological importance of candidate sites from among a vast number of differentially modified sites. Here, we present PTMExplorer, an interactive platform for the multi-dimensional visualization of protein PTMs. PTMExplorer comprises three core modules: PTM Inspector, built upon ProtVista, provides a multi-track, sequence-feature integrated view incorporating intrinsically disordered region (IDR) prediction (via flDPnn), surface accessibility calculation (via FreeSASA), and UniProt functional annotations; PTM 3D Locator, leveraging the Nightingale/Mol* engine, anchors modification sites onto AlphaFold/Protein Data Bank (PDB) 3D structures through residue mapping via PDBe-SIFTS; and PTM Overview, utilizing the R circlize package, presents a panoramic polar circos plot illustrating modification distribution and inter-group differential regulation. Additionally, three major disease-associated modification databases (PTMD, qPTM, and PhosCancer) are integrated as PTM-Disease Nexus, enabling co-localization comparison between user-defined differential sites and reported disease-related sites. PTMExplorer currently supports eight model organisms, accepts user-uploaded differential analysis results, and provides multi-dimensional annotations and various visualization options (https://www.bioladder.cn/PTMExplorer/). Using a multi-omics dataset from hepatocellular carcinoma (18 patients, 9 modification types) as a case study, we demonstrate the practical utility of PTMExplorer in screening potential biomarkers, revealing multi-modification coordination mechanisms, and distinguishing between absolute and relative quantification patterns.

bioinformatics↗

bioRxiv2026

A Chemigenetic Fluorescence Lifetime Biosensor for Dopamine Sensing

Measuring the precise dynamics of specific neuromodulators in neurons is key to understanding how information is transmitted and processed in the brain. Despite the growing use of intensity-based neural activity sensors such as dLight in recent years, it remains challenging to monitor the dynamics of multiple neurochemicals simultaneously in live neurons. Unlike intensiometric sensors that are susceptible to artifacts caused by fluctuations in excitation power and rapid photobleaching, fluorescence lifetime-based sensors are less affected by these factors and can provide more stable measurements. Here we introduce dHaloLife635, a novel genetically encoded fluorescence-lifetime-based dopamine (DA) sensor that exhibits a fluorescence lifetime change up to -0.20 ns upon dopamine binding. dHaloLife635 consists of a G protein-coupled dopamine receptor (DRD1), a circularly permuted HaloTag (cpHaloTag), and a cell-permeable dye JF635 functionalized with a HaloTag ligand, a reactive chloroalkane linker (JF635-HTL). When dopamine binds to the dHaloLife635 sensor, it induces a conformational change in the cpHaloTag that alters the local environment of the conjugated dye, thereby changing its fluorescence lifetime. In live HEK293T cells and primary neurons, dHaloLife635 responds selectively to dopamine but not to serotonin, L-DOPA, or GABA, demonstrating excellent specificity. This dHaloLife635 sensor represents an initial step toward the establishment of a broader family of chemigenetic lifetime sensors that exhibit distinct fluorescence lifetime signatures upon binding their respective targets, thereby enabling highly specific and sensitive, real-time monitoring of multiple neurochemical dynamics in vivo.

bioengineering↗