Biology subjects

Yan, R.

Publications and source records attributed to Yan, R..

At least 19 recordsLinked to original sources

bioRxiv2026

A polysynaptic hypothalamuspelvic-ganglion circuit regulates prostate tumor growth via WNT3A

Brain-tumor communication is increasingly recognized. Peripheral autonomic nerves regulate prostate cancer progression, yet how the brain influences local nerve-tumor interactions remains unclear. We identify a polysynaptic circuit linking the hypothalamic paraventricular nucleus (PVN), dorsal motor nucleus of the vagus (DMV), major pelvic ganglion (MPG) and prostate tumor in mice. Although both nuclei were activated during tumor growth, PVN activity restrained, whereas DMV activity promoted tumor growth. MPG ablation abolished DMV-induced tumor promotion. Combining LMD with Smart-seq2 revealed transcriptional remodeling and increased Wnt3a expression in tumor-innervating, activated MPG neurons under upstream neural control. MPG explants released WNT3A, whose neutralization suppressed explant-induced cancer-cell proliferation. Together, our findings identify a polysynaptic PVN-DMV-MPG circuit that regulates prostate tumor growth and implicate WNT3A as a mediator of the pro-tumor effects of the MPG, highlighting the therapeutic potential of targeting the neural circuit and downstream molecular pathway.

cancer biology↗

bioRxiv2026

Hypothalamic plasticity for alloparenting in male mice

Repeated exposure to young can induce caregiving in virgin female mice, a phenomenon known as pup sensitization, but whether virgin males can similarly acquire parental behavior and the neural mechanisms underlying this transition remain unclear. We show that 7 days of continuous pup exposure reliably converts virgin adult male mice to a parental state. This transition requires calcitonin receptor (CalcR)-expressing neurons in the medial preoptic area (MPOA): silencing MPOACalcR neurons disrupts both the acquisition and expression of paternal behavior, whereas optogenetic activation of GABAergic MPOACalcR neurons promotes caregiving in virgin males. Longitudinal two-photon calcium imaging reveals that MPOACalcR neurons develop enhanced pup-selective responses as males transition to a parental state. Moreover, CalcR signaling in the MPOA promotes synaptic potentiation and facilitates the emergence of parental behavior. These results identify an experience-dependent hypothalamic plasticity mechanism that enables parental behavior in non-father males.

neuroscience↗

bioRxiv2026

From Ligand Binding to Pore Opening in the Mosquito Odorant Receptor AaegOR10

Mosquito olfaction is central to host seeking and other behaviors relevant to vector ecology and disease transmission. Mosquito odorant receptors (ORs) are ligand-gated ion channels, yet how ligand binding is coupled to pore opening remains poorly understood. Here, we combine more than 400 $\mu$s of aggregate molecular dynamics simulations and adaptive sampling with Markov state models (MSMs) and electrophysiological measurements to characterize the gating dynamics of \textit{Aedes aegypti} odorant receptor 10 (AaegOR10). Interaction analysis identifies M288 as a persistent contact between $o$-cresol and S6, connecting the orthosteric pocket to a conformation-dependent hydrophobic network involving I293, F294, and F356 at the S6-S7b interface. The MSMs place the experimentally determined open and closed structures within a multistate conformational landscape and identify a principal intermediate along the dominant gating pathway. A localized S6 kink in this state is associated with weakened S6-S7b coupling and increased flexibility of the pore-lining S7b helix. Ligand binding shifts the conformational equilibrium toward open states and shortens the transition times from the closed state to both the intermediate and open states. We also identify an off-path closed state characterized by a pronounced inward displacement of S6, with phospholipid headgroup insertion observed in some sampled conformations. Mutational analysis and voltage-clamp recordings support the functional relevance of M288, the S6-S7b interface, and the kink-prone S6 region. Together, these results describe a multistate pathway linking ligand recognition to AaegOR10 pore gating.

biophysics↗

bioRxiv2026

Human foregut morphogenesis exhibits murine-like molecular patterning but avian-like epithelial architecture

Animal models are indispensable for understanding human development, yet evolutionary relatedness does not ensure developmental similarity at all biological scales. In tracheal-esophageal separation (TES), which splits the embryonic foregut into respiratory and digestive tubes in all tetrapods, genetic mouse models rarely reproduce the predominant human malformation, esophageal atresia with tracheoesophageal fistula (EA/TEF). By comparing human, mouse, and chick foreguts, we uncover a mosaic pattern of developmental conservation. The human foregut resembles the mouse in its molecular patterning, but more closely resembles the chick in its densely pseudostratified epithelial architecture and the greater number of cells comprising the epithelial septum. Live imaging shows that epithelial pseudostratification, which depends on actomyosin contractility, is associated with slower septum resolution. Cross-species single-cell transcriptomics analysis reveals lower expression of a myosin regulatory light chain and N-cadherin, and higher expression of a myosin phosphatase subunit in the mouse foregut epithelium than in the human and chick, suggesting candidate molecular mechanisms of these morphological differences. Induction of ectopic BMP signaling through in vivo electroporation in chick embryos recapitulated an EA/TEF-like malformation. These findings suggest that human foregut morphogenesis combines murine-like patterning and avian-like epithelial organization. The chick embryo thus represents an important complementary model for investigating epithelial mechanisms underlying human foregut malformations.

cell biology↗

bioRxiv2026

Prototype-based AI triage for 3D pathology

Non-destructive 3D pathology enables high-resolution slide-free imaging of intact clinical specimens, providing comprehensive visualization of tissue structures beyond what conventional slide-based 2D histopathology can provide. However, the scale and complexity of volumetric datasets make exhaustive manual review impractical, motivating AI-assisted triage methods to select a small number of high-risk 2D slices for pathologist review. While prior triage models have shown promise, interpretability is poor and performance can be suboptimal, especially in the nascent field of 3D pathology in which labeled data is limited. We present SCOPE, a Segmentation-guided CrOss-slice PrototypE learning framework for comprehensive risk assessment of 2D levels within 3D pathology datasets. SCOPE combines (i) clustering-based pretraining on large-scale unlabeled volumetric data to initialize morphology-aware prototypes, (ii) segmentation-derived structural priors from publicly available models to guide proto-type learning, and (iii) cross-slice (2.5D) prototype aggregation across neighboring slices to generate slice-level risk predictions. In prostate and esophageal data cohorts, SCOPE consistently outperforms attention-based and prototype-based multiple instance learning baselines for both binary and multiclass prediction tasks, enabling depth-resolved risk profiling for 3D triage based on morphological prototypes that are interpretable to pathologists.

pathology↗

bioRxiv2026

Scalable 3D cell-interaction analysis via supercell graphs for prostate cancer risk stratification

Cellular interactions underlie fundamental biological processes but are not fully represented in conventional 2D histology images. While 3D pathology allows for more-accurate construction of cell-level graphs, machine-learning models are computationally unwieldy and prone to overfitting, especially when dealing with small cohorts. Here, we introduce SCALE3D, a SuperCell graph Analysis framework for LargE 3D pathology datasets. In SCALE3D, spatially adjacent and morphologically similar cells are grouped into functional "supercells." Supercell subtypes are defined via morphology-based clustering and 3D graphs connecting these supercells are used to model their interactions. Validation was performed with 76 radical prostatectomy specimens from patients with known 5-year biochemical recurrence (BCR) outcomes. SCALE3D-derived features achieve higher performance for BCR prediction than established 3D nuclear and glandular morphological features. Combining these complementary features further improves prediction performance. Compared to individual cell-level 3D graphs, SCALE3D maintains comparable prognostic performance with improved noise tolerance while reducing computational times by up to 1,000-fold.

pathology↗

bioRxiv2026

Pitx2 modulates Fgf10 dosage to initiate asymmetric lung morphogenesis

Most of the visceral organs are anatomically asymmetric across the left-right axis. These asymmetries can be traced to a well-studied molecular cascade leading to left-sided gene expression, including Pitx2, in the mesoderm. Yet how these early differences in gene expression are converted into differential shaping of organs at later stages remains incompletely understood, and for many organs, such as the lung, the question has not even been explored. Meanwhile, the signaling pathways responsible for the morphogenesis of the lung have been intensively studied, but no insight has been reported regarding whether they should differ on the left and right sides. Here we identify Fgf10 as a Pitx2-sensitive signal in the mesenchyme of the developing mouse lung. Fgf10 expression increases as Pitx2 decreases, making the right lung, which lacks Pitx2 expression, grow faster than the left during the budding stage. Modulating Fgf10 dosage in the left mesenchyme is sufficient to alter lung budding asymmetry. At the cellular level, the faster growth of the right lung is established by increased levels of epithelial proliferation, without significant differences in directional migration into the mesenchyme. Conditional genetics further show that Pitx2 acts during the budding stage to establish later branching asymmetry. Thus, Pitx2 converts left-right mesenchymal identity into organ asymmetry by quantitatively tuning Fgf10-dependent epithelial growth during early organogenesis.

developmental biology↗

bioRxiv2026

In situ molecular architecture of the mammalian sperm nuclear vacuole

Direct identification of macromolecular complexes in their native context remains a major barrier to unbiased biological discovery. This challenge is particularly acute in mammalian sperm nuclei, in which condensed chromatin is interspersed with poorly understood phase-separated compartments termed nuclear vacuoles. Vacuoles are associated with reduced fertilization efficiency, yet their composition remains unclear. Here we combine high-resolution in situ cryo-electron tomography (cryo-ET) with AlphaFold docking to identify vacuole components as proteasomes, the proteasome activator PA200, and ferritin. In situ structures at resolutions up to 3.8 [A] reveal distinct proteasome-PA200 associations and gating states, consistent with a stepwise activation mechanism. Ferritin assemblies exhibit heterogeneous mineralization states and directly contact chromatin. Together, these findings establish the molecular organization of sperm nuclear vacuoles and implicate protein turnover and metal homeostasis in shaping the nuclear landscape, while demonstrating the power of in situ cryo-ET to resolve protein identity and conformational dynamics in native cellular environments.

biochemistry↗

bioRxiv2026

Reconstructing True 3D Spatial Omics at Single-Cell Resolution

Capturing the three-dimensional (3D) organization of cells is essential for deciphering complex biological processes, yet comprehensive 3D spatial omics is severely hindered by the destructive nature of physical sectioning and the depth limitations of intact tissue imaging. Current computational methods rely on 2.5D stacking of discrete slices, which inherently disrupts tissue topology and fails to resolve continuous depth-dependent molecular gradients. To bridge this gap, we introduce DO_SCPLOWEEPC_SCPLOWSO_SCPLOWPATIALC_SCPLOW, an Optimal Transport flow matching framework that models tissue evolution as a continuous dynamic vector field. By solving the underlying probability flow ODEs, DO_SCPLOWEEPC_SCPLOWSO_SCPLOWPATIALC_SCPLOW enables the direct extraction of uninterrupted, infinitely resolvable tissue states at arbitrary spatial depths. Using Deep STAR/RIBOmap 3D technologies, we demonstrate that DO_SCPLOWEEPC_SCPLOWSO_SCPLOWPATIALC_SCPLOW achieves improved 3D reconstruction fidelity relative to 2.5D approaches, yielding structures that more closely recapitulate native tissue microenvironments in real-world datasets. Across diverse spatial omics modalities, including spatial proteomics using imaging mass cytometry in human breast cancer and spatial transcriptomics using openST in head and neck squamous cell carcinoma metastatic lymph nodes, DO_SCPLOWEEPC_SCPLOWSO_SCPLOWPATIALC_SCPLOW produces biologically interpretable and high-fidelity reconstructions across datasets. We evaluated the scalability and robustness of DO_SCPLOWEEPC_SCPLOWSO_SCPLOWPATIALC_SCPLOW on a large-scale mouse brain dataset, reconstructing a continuous 3D cellular atlas comprising 39 million cells within 41.6 hours. Systematic downstream characterization validated its ability to recapitulate consistent spatial architectures, cell-type distributions, transcriptomic patterns, and microenvironmental structures across brain regions. Collectively, these results demonstrate DO_SCPLOWEEPC_SCPLOWSO_SCPLOWPATIALC_SCPLOW as a generalizable and efficient solution for true 3D spatial reconstruction across scales and modalities. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=117 SRC="FIGDIR/small/721395v2_ufig1.gif" ALT="Figure 1"> View larger version (49K): org.highwire.dtl.DTLVardef@1a19624org.highwire.dtl.DTLVardef@188361forg.highwire.dtl.DTLVardef@199321corg.highwire.dtl.DTLVardef@a8f411_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2026

H2O: A Foundation Model Bridging Histopathology to Spatial Multi-Omics Profiling

Spatial omics technologies have revolutionized the molecular profiling of tissues but remain constrained by high costs and limited scalability. While hematoxylin and eosin (H&E) staining is ubiquitous, it lacks molecular specificity. Here, we present H2O (Histopathology to Omics), a generalist AI framework that bridges the modality gap between histopathology and spatial multi-omics, enabling the direct inference of spatial transcriptomics (ST) and proteomics (SP) landscapes from routine H&E images. H2O integrates Vision Transformers (ViT) with Large Language Models (LLM) via contrastive learning to align histological morphology with semantic molecular knowledge. This cross-modal approach allows the model to incorporate spatial expression profiles into histological pattern recognition, effectively decoding the molecular heterogeneity underlying tissue morphology. Trained on a pan-tissue dataset of 1.3 million paired H&E-spatial patches across 25 organs and cancer types, H2O predicts spatial omics expression from histology with high concordance to sequenced measurements and consistently outperforms state-of-the-art models across three cancer benchmarks. Notably, H2O recovers the MIF-CD74/CD44 signaling axis directly from H&E images, highlighting its capacity to infer biologically meaningful cell-cell communication without molecular profiling. Applying on three additional public cohorts covering fetal and paediatric thymus tissues, human metastatic lymph node, and breast cancer, encompassing human development, 3D spatial frameworks, and integrative multi-omics, H2O yields biologically concordant insights, demonstrating superior accuracy, robustness, and generalizability across real-world applications in diverse scenarios. H2O converts routine histopathology into a portal for spatially resolved multi-omics profiling by computationally generating transcriptomic and proteomic landscapes, thereby enhancing tissue phenotyping and enabling scalable, integrative tissue-atlas construction.

bioinformatics↗

bioRxiv2026

IRE1 drives a homeostatic response to reduced protein influx into the endoplasmic reticulum

IRE1, alongside ATF6 and PERK, orchestrates the Unfolded Protein Response, a network of signaling pathways that maintains endoplasmic reticulum (ER) homeostasis. Two modes of IRE1 activation are known: i) in response to an accumulation of unfolded proteins in the ER lumen and ii) in response to compositional changes to the ER membrane that alter its physical properties. Here we identify a third, independent mode of IRE1 activation: ER co-translational translocation deficits activate IRE1 through a mechanism that relies on the release of IRE1 molecules from unoccupied translocons. We define this mechanism as TRES for "TRanslocon Engagement Surveillance". TRES leads to spontaneous activation of IRE1 and bypasses its unfolded protein- and ER membrane composition-sensing functions. Inhibiting translation initiation similarly activates IRE1 by TRES, as it leads to a decline in ER protein import, thus linking the Integrated Stress Response to IRE1 signaling. TRES drives IRE1 activation without activating ATF6 or PERK, resulting in a distinct gene expression program that feeds back by boosting the co-translational translocation machinery to rebalance the ER protein load. Our findings thus demonstrate that monitoring and adjusting the rates of protein translocation are critical for maintaining ER homeostasis.

cell biology↗

bioRxiv2025

CGAS (Chloroplast Genome Analysis Suite): An Automated Python Pipeline for Comprehensive Comparative Chloroplast Genomics

BackgroundChloroplast genome analysis underpins plant phylogenetics, comparative genomics, and molecular marker development. Although high-quality chloroplast genomes are now routinely generated, downstream comparative analyses still rely on fragmented toolchains requiring separate tools for annotation, codon analysis, and SNP detection, extensive manual curation, and ad hoc scripting, which limit reproducibility and scalability. ResultsWe present the Chloroplast Genome Analysis Suite (CGAS), an automated Python-based pipeline designed as a comprehensive solution for comparative chloroplast genomics. CGAS integrates nine core analytical modules into a single, reproducible workflow operating directly on annotated GenBank files and pre-aligned FASTA datasets. The pipeline performs automated gene content analysis, publication-ready gene table generation, chloroplast structural characterization (LSC/SSC/IR boundaries and GC content), codon usage and amino acid composition analyses enabling batch processing of 10-50+ genomes, SNP detection with transition/transversion statistics, intron feature characterization, simple sequence repeat identification, and nucleotide diversity profiling. Unlike existing tools, CGAS emphasizes biologically informed handling of edge cases, including trans-spliced genes (e.g., rps12), IR-mediated gene duplication, and annotation artifacts. All outputs are generated in standardized, publication-ready Excel and Word formats with timestamped provenance. ConclusionsCGAS provides a unified, automated, and biologically robust framework for comparative chloroplast genome analysis. By minimizing manual intervention and emphasizing batch processing, the suite substantially accelerates methodologically consistent analyses. The pipeline is openly available at https://github.com/abdullah30/Chloroplast-Genome-Analysis-Suite-CGAS and readily extensible, supporting its adoption as a standardized analytical backend for chloroplast comparative genomics.

bioinformatics↗

bioRxiv2025

Nano-Sieve Enabled On Chip Concentration and Multiplexed Detection of Raman-Dye Labeled Nanocubes

To address persistent challenges in molecular detection--particularly signal variability, low analyte abundance, and poor spectral reproducibility--a portable bead-stacked nano-sieve platform was engineered to enable robust on-chip Raman signal amplification using silver nanocubes (AgNCs) functionalized with Raman-active thiolated ligands. The microdevice integrates deformable elastomeric channels with magnetic bead stacking to immobilize and concentrate AgNCs within confined nanoscopic junctions, thereby generating densely packed plasmonic hot-spot architectures that markedly enhance Surface-Enhanced Raman Scattering (SERS) efficiency. Time-resolved measurements revealed substantial increases in Raman intensity for both 4-mercaptobenzoic acid (4-MBA) and 4-aminothiophenol (4-ATP), outperforming corresponding off-chip assays and maintaining stable enhancement factors over a four-hour operational window. Furthermore, the platform successfully demonstrated multiplexed sensing capability: mixed-analyte experiments containing 4-MBA, 4-ATP, and cysteamine produced clearly distinguishable spectral fingerprints, even under serial dilution and dynamically pulsed sample delivery. Collectively, these results establish the bead-stacked nano-sieve as a versatile, label-free, and scalable diagnostic architecture capable of achieving high sensitivity and spectral fidelity under continuous-flow conditions. Our technology holds significant promise for real-time, non-invasive molecular surveillance, point-of-care diagnostics, and early disease monitoring in resource-limited or field-deployable settings.

bioengineering↗

bioRxiv2025

3D pathology-guided microdissection

Traditional micro- and macro-dissection techniques enable the extraction of localized regions in thin tissue sections for molecular analysis. Despite the growing use of 3D microscopy, analogous methods for volumetric microdissection are lacking. We have developed a 3D microdissection method based on computer numerical controlled (CNC) milling integrated with open-top light-sheet microscopy. We demonstrate the ability to study tumor evolution along convoluted 3D branching architectures, which is inaccessible to 2D methods.

bioengineering↗

bioRxiv2025

Model of ocular surface ion and water transport predicts efficacy of dry eye therapeutics targeting epithelial transport and tear fluid dynamics

The composition and volume of tear fluid lining the ocular surface are governed by the rates of lacrimal gland secretion, tear film evaporation, nasolacrimal drainage, and epithelial ion and water transport. Tear fluid hyperosmolality and reduced volume are key drivers of dry eye disease (DED) pathogenesis. We constructed a mathematical model to compute the composition and volume of tear fluid and epithelial cell compartments, with transport parameters specified for the mouse eye from published data and in vivo measurements of ocular surface potential differences. The model accounted for transcellular and paracellular transport across the epithelia under open-circuit conditions utilizing flux equations for individual transport mechanisms, with mass balance constraints on solute and water content in cytoplasm and tear fluid. Under DED conditions established by reduced lacrimal secretion and increased evaporation, the model predicted the efficacy of currently available DED therapies including punctal plugs, humidification goggles, lacrimal gland stimulation, and artificial tears eye drops. The model also predicted the limited efficacy of anti-absorptive and pro-secretory drugs targeting epithelial ion transporters, and the high efficacy of targeting epithelial water permeability or paracellular ion permeability. The modeling herein provided quantitative predictions to prioritize novel targets for DED and drive the development of new therapies. Author SummaryDry eye disease (DED) affects billions of adults worldwide, but a full picture is lacking of how the tear film becomes abnormally thin and hyperosmolar. The computer model built here links four processes - tear production by the lacrimal gland, tear fluid evaporation, tear drainage through tear ducts, and transport of solutes and water across eye surface epithelial cells - to predict the thickness and composition of the tear film in various conditions. Model parameters were selected using published data and electrical measurements of voltage changes across the ocular surface produced by ion transport. The model predicted that existing therapies, such as punctal plugs, moisture goggles, or stimulating tear production, can substantially increase tear thickness or lower saltiness. The model also predicted limited efficacy of drug therapies in current development that target ion transport, and identified epithelial cell water transport and paracellular ion permeability as novel targets for DED treatment. By making ocular surface transport mechanisms explicit and testable, our work offers a roadmap for development of new therapies that restore a healthy tear film, a major unmet medical need.

systems biology↗

bioRxiv2025

Deep-learning triage of 3D pathology datasets for comprehensive and efficient pathologist assessments

Standard-of-care slide-based 2D histopathology severely undersamples spatially heterogeneous tissue specimens, with each thin 2D section representing <1% of the entire tissue volume (in the case of a biopsy). Recent advances in non-destructive 3D pathology, such as open-top light-sheet microscopy (OTLS), enable comprehensive high-resolution imaging of large clinical specimens. While fully automated computational analyses of such 3D pathology datasets are being explored, a potential low-risk route for accelerated clinical adoption would be to continue to rely upon pathologists to provide final diagnoses. Since manual review of these massive and complex 3D datasets is infeasible for routine clinical practice, we present CARP3D, a deep learning triage framework that identifies high-risk 2D cross sections within large 3D pathology datasets to enable time-efficient pathologist evaluation. CARP3D assigns risk scores to all 2D levels within a tissue volume by leveraging context from a subset of neighboring depth levels, outperforming models in which predictions are based on isolated 2D levels. In two use cases - risk stratification based on prostate cancer biopsies and screening for dysplasia/cancer in endoscopic biopsies of Barretts esophagus - AI-triaged 3D pathology, enabled by CARP3D, demonstrates the potential to improve the detection of high-risk diseases in comparison to slide-based 2D histopathology while optimizing pathologist workloads.

pathology↗

bioRxiv2025

Systematic molecular glue drug discovery with a high-throughput effector protein remodeling platform

Realising the promise of new medicines that operate through a targeted molecular glue-induced degradation mechanism requires systematic tools that can uncover the relevant principles of neomorphic protein-protein interactions. Whilst some monovalent glue degraders have been found through serendipity, the rules for small molecule attributes and the pairs or complexes of proteins that are amenable to drug-induced proximity control remain poorly articulated. Here we introduce a new approach to address this by using programmed libraries of intramolecularly edited proteins to expand protein surface landscapes and trigger new druggable interactions. We show that effector proteins, such as the E3 ligase Cereblon, can be engineered to provoke neomorphic activity by inducing the degradation of new client proteins and that these de novo interactions provide a blueprint from which new small molecule degraders can be built. As a demonstration of the approach, we use the platform to identify new non-IMiD molecular glue degraders of the oncology target GSPT1. SUMMARYO_LIMolecular glues are a highly important and promising new form of therapeutic agent, but rationalising their discovery has so far been impossible C_LIO_LIGlueSEEKER screening enables prospective monovalent drug discovery by using high-throughput deep mutational scanning to re-engineer the function of effector proteins like E3 ligases C_LIO_LIWe used this approach to enable the computational discovery of small molecule glues which degrade the oncology target GSPT1 and show how the technology can be used across new targets C_LI

bioengineering↗

bioRxiv2025

The neural mechanisms supporting the rise and fall of maternal aggression

To protect the helpless young, lactating females dramatically increase aggression towards intruders, known as maternal aggression. However, attack is costly and risky. When pups no longer exist, maternal aggression rapidly declines. Our study reveals the critical role of the pathway from posterior amygdala cells expressing estrogen receptor alpha (PAEsr1) to the ventrolateral part of ventromedial hypothalamus cells expressing neuropeptide Y receptor Y2 (VMHvlNpy2r) in the rise and fall of maternal aggression. Functional manipulations and recordings demonstrate that VMHvl-projecting PAEsr1 (PAEsr1[->]VMHvl) cells are naturally active and required for maternal aggression. During lactation, PA-VMHvlNpy2r connection strengthens, and VMHvlNpy2r excitability increases to facilitate attack. Furthermore, PAEsr1 expresses abundant oxytocin receptors, enabling oxytocin to boost PAEsr1 cell output. After pup separation, the oxytocin level drops, causing decreased maternal aggression, which can be restored by optogenetically increasing the oxytocin level. Thus, diverse forms of plasticity occur at the PAEsr1-VMHvlNpy2r circuit to support need-based maternal aggression.

neuroscience↗