Biology subjects

Lu, Y.

Publications and source records attributed to Lu, Y..

At least 19 recordsLinked to original sources

bioRxiv2026

In situ loading of biologics on and tissue redirection of circulating extracellular vesicles with an anchoring nanobody

Extracellular vesicles (EVs) are promising nanocarriers of therapeutic macromolecules, but ex vivo production, cargo loading and quality control constrains clinical translation. Here we demonstrate that NEV3, an EV-anchoring nanobody identified by phage display, binds EVs from multiple sources through interactions involving fibronectin and loads diverse proteins onto EVs, resulting in enhanced intracellular delivery and biological activities in vitro and in vivo. Conjugating NEV3 to target proteins hijacks circulating EVs, prolonging circulation and altering tissue distribution in vivo. When fused with an GFP nanobody or protein A, NEV3 enabled simultaneous capture and loading of circulating GFP or immunoglobulin G (IgG) antibodies on endogenous EVs with enhanced intracellular delivery in vitro and redistribution to liver in vivo. Intravenous protein A-NEV3 significantly reduced circulating IgG and anti-dsDNA antibodies in systemic lupus erythematosus mice with improved survival and reduced pathologies. Intravenous anti-transferrin receptor-protein A-NEV3 redirected circulating EVs to muscle and alleviated muscle pathologies in dystrophin-deficient mdx mice. Our study demonstrates that NEV3 enables in situ loading of protein therapeutics and tissue-specific delivery of circulating EVs, providing a modular strategy for loading cargo onto and redirecting circulating EVs in vivo.

bioengineering↗

bioRxiv2026

Modelling the human IL6RA Asp358Ala variant in mice: effects on atherosclerosis and abdominal aortic aneurysm

The association of IL6RA Asp358Ala variant with reduced risk of atherosclerotic cardiovascular disease (ASCVD) and abdominal aortic aneurysm (AAA) prompted interest in targeting IL6 signalling in these conditions. A recent report that ziltivekimab, a neutralising anti-IL6 antibody, did not reduce major adverse cardiovascular events in patients with ASCVD and chronic kidney disease, has cast doubt on the causal role of IL6 signalling in ASCVD. Here, we show that introducing the orthologous IL6RA Glu357Ala substitution in male mice leads to the same alteration in soluble IL6RA levels seen in humans, and significantly prevents atherosclerosis and AAA. Thus, therapies that more closely reproduce the biological effects of the IL6RA Asp358Ala variant on IL6 signalling are needed to reduce cardiovascular risk in humans.

pathology↗

bioRxiv2026

Metabolite-centric Knowledge Graph Unveils Predictive and Mechanistic Insights through Self-supervised Multimodal Learning

Metabolomics research is advancing toward a comprehensive view of metabolites and their biological functions, yet conventional, dictionary-like databases fall short of presenting these complexities. To overcome this limitation, we developed MetaKG, a metabolite-centric knowledge graph that integrates diverse chemical, biological, and semantic data, coupled with a global self-supervised multimodal learning framework that generates advanced embeddings (MetaKGE) for both predictive and mechanistic analyses. MetaKG outperforms existing models in standard representation learning metrics and across 12 external datasets. Furthermore, MetaKG refines existing database information by detecting misannotated labels and uncovering previously overlooked biochemical relationships. Its predictive capability naturally yields testable biochemical hypotheses, as demonstrated in studies of G6PD deficiency and colorectal cancer. By transforming passive, database-scale information into extractable knowledge and actionable insights, MetaKG paves the way for hypothesis-driven discovery in metabolomics and holds promise for informing future research in clinical biomarker identification and therapeutic development.

bioinformatics↗

bioRxiv2026

Asymmetric assembly underlies activation mechanism of neuronal GIRK1/2 channels

G protein-gated inwardly rectifying potassium (GIRK; Kir3) channels are principal effectors of inhibitory GPCR signaling. Here we combine cryo-electron microscopy, single-molecule imaging, electrophysiology and molecular dynamics to define the architecture and activation of neuronal GIRK1/2 channels. GIRK1/2 preferentially assembles as an asymmetric heterotetramer containing one GIRK1 and three GIRK2 subunits. Three PIP2; molecules bound to GIRK2 promote partial cytoplasmic-domain docking, whereas engagement of a fourth PIP2 by GIRK1 completes docking and opens the helix bundle crossing gate. GIRK1 also remodels the electrostatic environment beneath the selectivity filter, where its E141 and D173 residues create a permeation module that enhances K+ conduction. The GIRK1-selective activator ML297 binds at the GIRK1-GIRK2 interface and controls both permeation and gating. These findings establish how asymmetric assembly couples sequential lipid-dependent gating to efficient K+ permeation and GIRK1-dependent pharmacological activation.

biophysics↗

bioRxiv2026

Stoichiometry-dependent gating and structural pharmacology of cardiac GIRK1/4 channels

Cardiac G protein-gated inwardly rectifying potassium-K+ (GIRK) channels, formed by GIRK1/4 heterotetramers or GIRK4 homotetramers, are crucial regulators of heart rate, and their dysfunction is associated with atrial fibrillation. Despite their therapeutic potential as anti-arrhythmic targets, development of selective GIRK modulators has been limited by an incomplete understanding of their structures, gating mechanisms, and pharmacology. Here, we report high-resolution structures of the GIRK4 homotetramer and of GIRK1/4 heterotetramers, revealing that they form in unexpected 1:3 and 2:2 assembly stoichiometries that we corroborate using cell-based single molecule microscopy. Electrophysiological assays and molecular dynamics simulations further show that incorporation of one or two GIRK1 subunits into GIRK4-containing channels progressively opens the helix bundle crossing (HBC) gate and increases basal channel activity. Additional structures of GIRK1/4 complexes with ML297, a small-molecule ligand selective for GIRK1-containing channels, reveal distinct GIRK1-centered intersubunit binding environments. Remarkably, ML297 inhibits GIRK1/4 channels with a 1:3 stoichiometry but potentiates channels with a 2:2 stoichiometry, establishing a direct link between subunit composition, ligand-binding environment, and pharmacological efficacy. Together, these findings provide a structural and mechanistic framework for the rational design of ligands with enhanced selectivity among cardiac and neuronal GIRK channel heterotetramers.

molecular biology↗

bioRxiv2026

Lineage tracing reveals asynchronous fate restriction in mouse embryos and stem cell-derived embryo models

How a flexible mammalian embryo gives rise to a reproducible body plan remains unclear, partly because cell lineages cannot be followed continuously in vivo. We combined DNA Typewriter lineage recording with tetraploid complementation to reconstruct high-resolution single-cell genealogies across mouse development and built FateVec, an analysis framework that infers fate-bias dynamics and lineage-associated transcriptional programs from reconstructed phylogenies. Loss of developmental potential proved progressive and asynchronous, with multiple lineages acquiring detectable fate bias before morphological diversification at gastrulation. Within the neural crest, most cells remained multipotent over an extended window, while independent founder clades differed markedly in restriction timing. Extending lineage recording to a stem-cell-derived embryo model revealed that cells with shared transcriptional identities can arise from distinct lineage relationships. We further found embryonic-lineage contributions to extraembryonic-like states, exposing an unexplored lineage plasticity. This lineage-resolved view of embryogenesis reveals that cell identity alone predicts neither developmental ancestry nor the timing of fate restriction.

developmental 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

Factors underlying creativity show distinct genetic architecture and genetic correlations with psychiatric disorders

While creativity is widely recognized as multifaceted, genome-wide association studies have largely focused on individual measures. Here, we used genomic structural equation modeling of six creativity-related GWASs and identified two latent genetic factors: a general factor and an artistic factor, with 22 and 13 genome-wide significant loci, respectively, nine of which are novel. The general factor was almost perfectly genetically correlated with educational attainment (rg = 0.96), suggesting that it primarily captured genetic influences shared with cognitive and educational processes rather than creativity-specific variation. In contrast, the artistic factor showed only a weak genetic correlation with educational attainment (rg = 0.11) and consistent positive genetic correlations with psychiatric disorders, whereas associations for the general factor were largely null or negative. Biological annotation analyses further identified distinct enrichment patterns unique to the artistic factor, providing initial evidence that different dimensions of creativity may be characterized by partially distinct neurobiological pathways.

genomics↗

bioRxiv2026

MOD-scTWAS: Leveraging gene co-expression for single-cell transcriptome-wide association studies

Transcriptome-wide association studies (TWAS) provide an effective framework for identifying genes associated with complex traits. Population-scale single-cell transcriptomic data enable genetically regulated expression (GReX) prediction and TWAS analyses at cell-type resolution, but the predictive performance of existing single-cell TWAS methods remains limited. Here, we develop MOD-scTWAS, a module-based method that jointly models GReX for genes within co-expression modules to borrow information across genes. Starting from a generative model for single-cell gene expression, MOD-scTWAS accounts for the heteroscedasticity and cross-gene correlation of individual-level pseudobulk expression in joint GReX prediction. In cross-validation analyses of the OneK1K dataset, MOD-scTWAS achieved higher mean GReX prediction accuracy than scTWAS across all 14 cell types and increased the number of imputable genes. When applied to TWAS analyses of UK Biobank quantitative hematological traits, MOD-scTWAS identified more significant cell type-gene-trait associations than scTWAS. These results demonstrate the potential of leveraging gene co-expression through joint modeling to improve cell-type-specific GReX prediction and TWAS discovery.

genetics↗

bioRxiv2026

Connectome-based biophysical modeling of a figure-ground discrimination circuit

Figure-ground discrimination (FGD) via relative motion represents a highly conserved visual computation essential for breaking camouflage. Over forty years ago, the Reichardt-Poggio-Hausen (RPH) model proposed a circuit architecture to explain this phenomenon, relying on an inhibitory wide-field pool cell to aggregate global motion and subsequently inhibit elementary motion detectors. However, a biological implementation of the RPH model has remained elusive. Using Drosophila connectomics data and biophysically accurate modeling, we reveal a biological circuit implementing this canonical architecture. Strikingly, we find that while the dendrites of the elemental motion detectors, T4a, are tuned to motion, their axon terminals compute relative motion. This secondary computation is achieved via presynaptic shunting inhibition from the ventral Centrifugal Horizontal (vCH) cell, which acts as a global motion integrator that normalizes the signal carried by the T4 axon terminals during whole-field optic flow. We extend our model to include the motion-opponency and the binocular communication pathways and show that FGD depends on the T4a-vCH interactions. We further show that specific circuit adjustments are sufficient for our model to make predictions consistent with several physiological and behavioral experiments across different fly species. Ultimately, by uniting connectomic connectivity with morphologically accurate biophysics, our approach demonstrates how detailed, synapse-resolution models of the brain can yield fine-grained biological predictions.

neuroscience↗

bioRxiv2026

Sleep spindle state-dependent motor cortical plasticity induction by EEG-triggered ripple burst TMS

Background: Sleep spindles are fundamental for plasticity and memory consolidation. Here we sought to target different spindle states in sleeping healthy participants with real-time EEG-burst repetitive transcranial magnetic stimulation (rTMS) at hippocampal ripple frequency, and test the spindle state-dependent induction of corticospinal and sensorimotor cortical plasticity. We hypothesized that the spindle-trough is a particularly critical state for plasticity induction because hippocampal ripples are naturally nested in the spindle-trough, reflecting replay of memory traces and facilitating memory consolidation. Methods: Fourteen participants underwent four experimental nights, in which rTMS was applied either at the spindle-trough, spindle-peak, spindle random phase or during spindle-free epochs. Readouts of plasticity were changes in resting-state EEG (rsEEG) power, motor evoked potential (MEP) amplitude, local mean field amplitude (LMFA, for the N45 and P60 potential components), immediate response slope (IRS) and TMS-related time frequency response (TFR), tested 10 and 30 min after the end of the rTMS interventions upon awakening, and compared to pre-sleep baseline. Results: Spindle-trough rTMS resulted in pre- to post-sleep decreases of rsEEG beta-band power, MEP amplitude, P60-LMFA, IRS and TFR in the alpha-band, and an increase in the N45-LMFA. None of the other spindle state-dependent rTMS interventions resulted in consistent plastic changes. Conclusions: Targeting the spindle-trough with ripple-burst rTMS stands out in consistently leading to long-term depression-like changes across a broad array of corticospinal and sensorimotor cortical excitability readouts. This opens the intriguing opportunity of targeted manipulation of human sleep physiology for improving specific behavioral processes, such as memory consolidation.

neuroscience↗

bioRxiv2026

Five novel ubiquitous totiviruses function as virulence-promoting symbionts in the obligate biotrophic fungus Puccinia triticina

Mycoviruses modulate fungal fitness and pathogenicity, yet their biological roles in obligate biotrophic phytopathogens remain poorly understood. Here, we report the first functional characterization of totiviruses in rust fungi, identifying five novel totiviruses, designated Puccinia triticina totivirus 1 to 5 (PtTV1?PtTV5), from the wheat leaf rust fungus Puccinia triticina (Pt). All five PtTVs possess the canonical genomic architecture of Totiviridae, including two overlapping ORFs and a conserved ?1 ribosomal frameshifting motif. Transcriptional profiling revealed that PtTVs are highly expressed during early Pt infection. PtTV-encoded proteins suppressed BAX-triggered programmed cell death in Nicotiana benthamiana, indicating immune-suppressive activity. Using BSMV-mediated host-induced gene silencing (HIGS), we showed that knockdown of PtTV transcripts significantly impaired fungal hyphal expansion and uredinial formation, concomitant with enhanced host H?O? accumulation. A survey of 90 Pt field isolates from four major wheat-growing regions of China revealed that PtTVs are ubiquitously distributed in natural rust populations. Collectively, these findings demonstrate that totiviruses function as virulence-promoting symbionts in Pt, establishing for the first time a functional link between totiviral infection and enhanced pathogenicity in cereal rust fungi and identifying candidate targets for RNAi-based disease control.

plant biology↗

bioRxiv2026

Compressed representations underpin knowledge awareness in sequence learning

Humans can acquire sequence structure before its presence enters awareness, and in some learners this implicit knowledge later becomes accessible and reportable. Yet the neural reformatting that enables this transition remains unclear. Here we used electro/magnetoencephalography (EEG/MEG) to resolve how category-based triplet rules were organized before and after awareness emerged. We found that implicit sequence knowledge was already represented in an abstract, compressed format. Within this format, rule information generalized across triplet elements, and regular-sequence elements became more similar while perceptual-category structure remained separable. Compression rate quantified how efficiently local rule information entered this shared format, and its pre-awareness level predicted later awareness specifically in the event-related potential P3 window. MEG source imaging localised pre-transition compression to left middle temporal cortex and showed post-awareness expansion into prefrontal cortex. Pre-awareness directional connectivity further showed that temporal-to-prefrontal theta-band transfer was rule-specific and predicted later awareness. Overall, these findings identify a mechanism supporting conscious access to abstract sequence-rule knowledge, involving cross-element representational compression and theta-band routing from the compression source to prefrontal cortex.

neuroscience↗

bioRxiv2026

A Generative Virtual Tissue Model Enables Computational Design of Therapeutic Perturbation Strategies

Computational design has transformed many fields of engineering, where simulators can explore millions of candidate design configurations before experimental development and testing. Therapeutic design in biomedicine has resisted computational design approaches because disease progression and therapeutic response emerge from interactions among many cell types within human tissue, governed by biochemical parameters that are largely unknown and potentially unknowable. Here, we introduce the Cell Interaction Foundation Model (CIFM), a virtual tissue model that forward-simulates the transcriptional dynamics of cells in human tissue under arbitrary therapeutic conditions based upon a spatial transcriptomic seed. CIFM is a geometric graph neural network trained by self-supervised masked-transcriptome prediction on millions of cellular microenvironments spanning human tissue types and disease states; generative, auto-regressive, monte-carlo play-out, then, simulates transcriptional dynamics under combinatorial perturbations from a spatial transcriptomic seed. We validate CIFM by showing accuracy gains in gene expression prediction and imputation, disease classification, recapitulation of perturbation responses in prostate cancer models, and recovery of T cell-tumor signaling measured in cell-cell sequencing experiments. Beyond such conventional tasks, CIFM enables target identification and therapeutic design through generative tissue simulation play-outs. Analyzing over 106 single and combinatorial perturbations, CIFM designs immunotherapy strategies for cancer and autoimmune disease that exploit combinatorial manipulation of signaling pathways to induce or suppress immune activation. Broadly, CIFM shows how generative artificial intelligence methods can be applied to model emergent behavior in highly interacting biological systems, yielding new approaches to fundamental understanding of tissue behavior as well as large-scale therapeutic design.

bioinformatics↗

bioRxiv2026

The HES1-SOD1 Antagonism Shapes Senescence Heterogeneity and Impacts Metastatic Relapse of Circulating Tumor Cells

Circulating tumor cells (CTCs) encounter multiple challenges within the blood microenvironment, including oxidative stress, flow shear forces, and immune surveillance, often leading to anoikis. Recently, a transitional state of CTC senescence has been identified, contributing to metastatic inefficiency. However, the molecular mechanisms linking senescent CTCs to disease relapse remain to be defined. By integrating a genetic model of cortactin knockdown-induced CTC senescence with single-cell multi-omic analyses, we revealed two distinct senescent CTC subpopulations marked by HES1 expression levels. These HES1low and HES1high subpopulations exhibited differential evolutionary trajectory dynamics and unique molecular and metabolic signatures, which were significantly correlated with adverse clinical outcome across several patient cohorts. HES1low senescent CTCs displayed enhanced mitochondrial fitness, oxidative phosphorylation, and ROS-detoxifying capabilities, resulting in more efficient tumor regrowth with a pro-inflammatory and thrombotic phenotype when compared to the HES1high group. Mechanistically, HES1 directly bound to the Sod1 promoter and repressed its expression, leading to redox imbalance and mitochondrial dysfunction that were linked to weakened tumor regrowth capacity. Both senescent CTC subpopulations were broadly resistant to cytotoxic and targeted therapies, yet they showed elevated dependency on anti-apoptosis programs that make them susceptible to dual blockade by SOD1 inhibitor and the anti-senolytic drug ABT737 in vivo. Finally, in a prospective cohort of on-treatment melanoma patients, HES1 senescent CTCs were highly enriched in patients with progressive disease. Thus, the HES1-SOD1 antagonism shapes CTC senescence heterogeneity and contributes to differential tumor relapse, which can be therapeutically explored for eliminating residual metastatic disease.

cancer biology↗

bioRxiv2026

Spatial second-order features predict glioma malignant transformation

Isocitrate dehydrogenase (IDH) mutant gliomas often transform from low to high grade aggressive tumors. The genetic and molecular drivers of this Malignant Transformation (MT) are poorly understood, and predicting whether a patient will undergo MT is an unmet challenge of high clinical relevance. To stratify patients by MT risk, we applied integrated spatial DNA and RNA profiling to biopsies from 18 retrospective glioma patients which will either remain stable, undergo MT or have already transformed. The resulting dataset consisted of >600,000 single cells, measuring 962 DNA loci, 1150 RNAs, and their spatial locations. Using this dataset, we found that genetic copy number alterations (CNAs), cell types compositions, and cellular neighborhoods did not predict MT. Instead, second order effects i.e. pairwise interactions, are highly predictive of future transformation. First, we identified abnormal chromosomal contact patterns that clearly separate future stable versus future MT samples. Second, we identified 24 ligand-receptors (LR) pairs cross-expressed in neighboring cells as the main molecular factors predictive of transformation and recurrences. We then validated a cross-expressing pair of ENPP2-LPAR1 interactions with a separate cohort of patient samples. In addition, using the LR+ cell pairs as an anchor, we identified cell signaling-specific gene expression programs that can predict from bulk or single cell RNAseq data the time to recurrence. We used a cell-interaction-based foundation model (CIFM) optimized on the spatial RNA data in forward simulations and identified potential myeloid signaling factors involved in MT. Lastly, we analyzed the effect of detection sensitivity on the ability to capture pertinent LR+ neighboring cells by down-sampling transcript and showed that the ability to detect cross-expressing signaling LR transcripts (typically <10 copies per cell) decays rapidly with lower sensitivity, but is more robust to down-sampling of the areas of the tissue imaged. The importance of second-order features suggests that increased depth and dimensionality of data on a smaller quantity of samples can provide valuable insight, and that high-sensitivity and multiple-modalities spatial approaches can help identify markers to risk-stratify patients, aid in therapeutic decision making, and uncover potential therapeutic targets.

cancer biology↗

bioRxiv2026

12-plex DiLeu enables robust quantification of the feeding neuropeptidome

Understanding the feeding-induced neuropeptidome cascade requires analytical strategies capable of quantifying low-abundance, highly modified peptides across multiple tissues and time points. Herein, we apply 12-plex N,N-dimethyl leucine (DiLeu) isobaric labeling to perform the first multiplexed, tissue-wide, temporal quantitation of the Cancer borealis feeding neuropeptidome. This approach enabled sensitive measurement of neuropeptides across five tissues over six timepoints, revealing distinct regulatory patterns. The pericardial organ (PO) showed rapid early upregulation followed by suppression aligned with foregut emptying, whereas the thoracic ganglion (TG) displayed inverse and strongly condition-dependent responses, indicating previously unrecognized neuromodulatory roles. Single-residue variants and post-translational modifications, including pyro-Glu formation and amidation, produced markedly different temporal profiles, underscoring the functional specificity of closely related isoforms. We further identify differential regulation of proctolin and its amidated form, suggesting modified variants may contribute uniquely to feeding physiology. Collectively, these results establish multiplexed DiLeu labeling as a powerful platform for quantitative neuropeptidomics and reveal new dimensions of peptide-mediated feeding regulation.

neuroscience↗

bioRxiv2026

A cuffed CRISPR guide RNA for microRNA activity-dependent genome editing

Cells in multicellular eukaryotic systems are diverse biological units, with characteristics and functions determined by their molecular profiles. CRISPR-Cas9 genome editing has been widely used across biology to modulate gene expression and study gene function. However, there is currently no versatile and scalable method for editing a cells genome in response to endogenous cellular signals. Here, we report the engineering of a CRISPR guide RNA that efficiently confers genome editing in response to the catalytic activity of a target microRNA (miRNA) within a cell. miRNAs are short non-coding RNAs that are widely conserved across eukaryotes and can cleave their target RNA through almost perfect base pairing. In mammals, miRNAs are largely involved in development and homeostasis as well as disease progression and developmental disorders. To leverage these properties for genome editing, we developed a cuffed guide RNA (cgRNA) which is composed of a permutated order of sequence domains from the commonly used single guide RNA (sgRNA). These permutated domains were then concatenated with a miRNA target sequence, yielding a warped guide RNA that is inactive until cleaved by a complementary miRNA. We demonstrated that cgRNA enabled efficient miRNA activity-dependent genome editing in human and mouse cell lines. Biochemical and structural analyses revealed three stages of inhibition of the CRISPR genome-editing pathway for unprocessed cgRNA. Utilizing a lentiviral library of cgRNAs containing miRNA targets covering mouse genome-wide miRNAs, we identified miRNA cleavage activities and their sequence specificities in mouse embryonic stem cells and during smooth muscle cell differentiation. Furthermore, we showed that endogenous mRNA expression could be irreversibly recorded into a DNA sequence using a cgRNA targeted by a synthetic miRNA repeat. cgRNA is a simple, robust, miRNA activity-gated genome editing system that could facilitate the development of cell state-specific genome editing, the mapping of miRNA activity and gene expression landscapes, and the recording of molecularly determined cell states during the long-term progression of multicellular systems.

bioengineering↗