Biology subjects

Su, Y.

Publications and source records attributed to Su, Y..

At least 37 records · Page 2Linked to original sources

bioRxiv2026

Heterogeneous transmission estimation and strategy optimization for Chikungunya: a vector-borne modeling study differentiating age and sex

Against the backdrop of global climate change and accelerating population mobility in 2025, chikungunya fever (CHIKF) exhibited a trend of worldwide spread, significantly increasing the difficulty of controlling tropical mosquito-borne diseases. To enhance the precision of intervention strategies, this study developed an age- and sex-structured human-mosquito interaction dynamic model based on data from the largest CHIKF outbreak ever recorded in China, and conducted a targeted analysis of prevention and control strategies. By decomposing the basic reproduction number and examining population heterogeneity, asymptomatic males aged 15-59 years were identified as the core transmission group. Optimal control analysis revealed that the synergistic implementation of three measures-- reducing the effective human-to-mosquito transmission rate, reducing the effective mosquito-to-human transmission rate, and suppressing mosquito population density--could reduce the overall infection rate by 95.7586%. Among these, mosquito population suppression should be prioritized as a universal core strategy; however, its protective effect on females aged 60 years and above was relatively weak, warranting particular attention. The study further demonstrated that asymmetric intensity combinations targeting these three intervention pathways--such as intensity profiles of "10%, 90%, 90%" or "60%, 80%, 90%"--could achieve effective outbreak control. This research elucidates population-specific transmission patterns and key pathways for intervention intensity, providing a theoretical and strategic foundation for the precise control of mosquito-borne diseases. It also provides actionable operational insights to support rapid response and strategy optimization for future emerging outbreaks. Author summaryCHIKF is a mosquito-borne viral disease that is gradually spreading from tropical regions to other areas. To achieve more precise control of this disease, we developed an age- and sex-structured analytical model based on the largest CHIKF outbreak in China, aiming to provide a scientific basis for responding to potential future outbreaks with inherent uncertainties. The study found that asymptomatic males aged 15-59 years were the primary drivers of transmission and should be prioritized as a key population for reducing viral spread in prevention efforts. When evaluating the effectiveness of different intervention strategies, females aged 60 years and above were the least affected by the implemented measures, indicating that this group should strengthen personal protection to lower their infection risk. Among all control measures, mosquito suppression was the most effective, suggesting that vector control strategies should be prioritized in future outbreak responses.

pathology↗

bioRxiv2026

Engineering age-adaptive mRNA lipid nanoparticle cancer vaccines via reprogramming systemic gene expression

Lipid nanoparticle (LNP)-based mRNA vaccines have transformed cancer immunotherapy, yet their efficacy in older individuals, who represent the majority of cancer patients, remains poorly understood. Here, we uncover a critical and previously underappreciated barrier to mRNA LNP cancer vaccine performance in aged hosts: impaired systemic transgene expression. Using the SM-102 mRNA LNPs as a benchmark formulation, we show that while local immune activation and antigen presentation at the injection site and draining lymph nodes remain largely intact with age, transgene expression in peripheral organs, including the liver, lungs, and spleen, is markedly reduced. This deficit limits the magnitude and durability of CD8 and CD4 T cell responses and substantially compromises tumour control. Transcriptomic profiling further reveals that attenuated transgene expression parallels broad attenuation of antigen processing, presentation, and activation pathways in immune cells from aged animals, implicating impaired systemic mRNA translation as a central driver of the downstream immune defects and antitumour efficacy loss. Building on these insights, we identify a rationally selected LNP formulation that reestablishes distal antigen expression across age groups as an engineering strategy to revive T cell immunity, achieving full rescue of therapeutic efficacy in aged mice without additional intervention. Together, these findings establish systemic mRNA translation as a tuneable lever of vaccine performance and highlight that optimizing LNP formulations to sustain systemic transgene expression across age groups may enable next-generation, age-adaptive mRNA vaccines for cancer and other diseases of aging.

bioengineering↗

bioRxiv2026

Damage sensing recruitment of a lipid phosphatase couples lysosomal membrane repair to proteostatic adaptation

Restoration of organellar membrane integrity is critical for maintaining cellular homeostasis. Lysosomal membrane damage activates local repair machineries and global stress responses, but how signaling lipid metabolism is engaged by damage sensors to support and mechanistically link these processes remains poorly understood. Here we show that the phosphoinositide 3-phosphatase MTMR14 is recruited to damaged lysosomes through calcium-dependent binding to sphingomyelin. At these sites, MTMR14 promotes local PI(3)P hydrolysis and supports PI(4)P accumulation, thereby facilitating formation of ER-lysosome contact sites associated with membrane repair, without affecting ESCRT recruitment. MTMR14-dependent lipid remodelling causes reduced mTORC1 signalling and a decrease in global protein synthesis, consistent with an acute proteostatic adaptation to lysosomal injury. Cells lacking MTMR14 display impaired damage-induced lipid remodelling, altered repair-associated structures, sustained protein synthesis, and increased sensitivity to lysosomal injury, all of which can be mitigated by mTORC1/S6K inhibition. Our findings identify damage-sensing recruitment of MTMR14 and local PI(3)P turnover on damaged lysosomes as a phosphoinositide module that promotes lysosomal membrane integrity and homeostasis while functionally linking nutrient signalling to proteostasis under membrane stress.

cell biology↗

bioRxiv2026

ZMAP: A single-cell meta-atlas of zebrafish embryonic development reveals a consensus hierarchy of cell identities

Single-cell RNA sequencing (scRNA-seq) efforts have generated large collections of high-resolution cellular atlases of embryonic development, providing unprecedented views of the dynamic gene expression programs that accompany cell fate specification. Alongside parallel efforts in other models, zebrafish has emerged as one of the most extensively profiled vertebrate embryonic systems, with numerous scRNA-seq atlases spanning both embryonic and early larval stages. Despite this progress, cross-study comparisons between datasets remain challenging due to differences in sample processing, mapping, and annotation conventions. Here we present ZMAP (Zebrafish Meta Atlas Project), a harmonized reference integrating 8 published whole-embryo zebrafish scRNA-seq datasets comprising 798,790 cells across 15 developmental time windows. ZMAP unifies component studies through a shared embedding, a standardized marker-gene discovery pipeline, and a hierarchical annotation ontology. Using ZMAP, we inferred "consensus identity programs" - marker gene signatures for each ontology group that were reproducibly detected across studies. To promote broad usage, we provide a Python-based API for automated annotation and retrieval of marker gene sets and reference objects, as well as a web portal that supports interactive 2D and 3D exploration of the UMAP embedding, gene and annotation-level queries, and access to consensus marker resources.

developmental biology↗

bioRxiv2026

pertTF: context-aware AI modeling for genome-scale and cross-system perturbation prediction

Predicting genetic perturbation responses at a single-cell level is central to building models for cell state and disease. However, existing approaches are limited on predicting phenotypic outcomes beyond expression changes and generalizing predictions across genome-scale perturbations in biologically relevant contexts. Here we introduce pertTF, a transformer-based single-cell genetic perturbation model. pertTF was trained from a unique dataset capturing single cell expressions profiles of 30 full gene knockouts across 14 relevant cell types during human pancreatic development and beta-cell differentiation. pertTF outperforms current methods in predicting expression changes of perturbing unseen genes in unseen cellular contexts. In addition, pertTF infers perturbation-induced shifts in cell identity and population composition, an important phenotypic outcome of perturbation in many physiology and disease settings. Through transfer learning, pertTF operates in physiologically relevant systems, including primary human islets, where large-scale perturbation experiments are challenging. The generalizability of pertTF is further demonstrated by in silico pooled and single-cell CRISPR screens, capturing critical regulators of stem cells and early pancreatic cell development. These results establish pertTF as a framework for integrating large-scale single-cell perturbation data with AI models to predict genetic perturbation effects across cellular systems and disease contexts.

bioinformatics↗

bioRxiv2026

Spatial mapping of RNA turnover kinetics and regulatory landscapes of mRNA stability in the mammalian brain

Spatial and activity-dependent gene regulation in the mammalian brain requires coordinated control of RNA synthesis and degradation 1,2, yet spatially resolved measurement of RNA turnover kinetics in complex tissues remains technically challenging 3. Here, we present spatial NT-seq, an approach that integrates transgenesis-free metabolic RNA labeling with in situ chemical recoding to spatially co-map RNA abundance and turnover kinetics in the mouse brain. By distinguishing newly synthesized from pre-existing RNAs, this method reveals spatially resolved transcriptional and post-transcriptional responses to electroconvulsive stimulation (ECS), a treatment for refractory depression. We uncover pronounced spatial heterogeneity in RNA turnover, with the dentate gyrus (DG) exhibiting elevated basal RNA turnover and robust ECS-induced responses. These findings reveal a "kinetics scaling" mechanism of coordinated regulation of RNA synthesis and decay, by which DG cells can rapidly remodel their transcript pools in responses to external stimuli or differentiation signals 4,5. Machine learning applied to in vivo RNA kinetics landscapes further identifies sequence features and post-transcriptional regulators underlying region-and cell-type-specific control of mRNA stability. Together, this integrated experimental and computational framework, in vivo Timescope, enables transcriptome-wide mapping of RNA turnover kinetics and the regulatory architecture of RNA stability across spatial and cellular contexts, providing new insights into the spatiotemporal regulation of RNA dynamics in brain function and disease.

genomics↗

bioRxiv2026

Bright calcium-modulated bioluminescent indicators for activity imaging and red photon-assisted synaptic transmission

Bioluminescent calcium sensors have unique uses in neuroscience and neuroengineering, enabling noninvasive imaging of neuronal activity and contactless activation of opsin-expressing neurons. However, the speed, range, and robustness of non-invasive imaging and rewiring or neuronal activity are limited by the radiance and dynamic range of existing bioluminescent calcium sensors. Here, we report the stepwise engineering of improved cyan-excitable red fluorescent proteins (mCyRFP4 and dCyRFP4), an improved red bioluminescent protein based on NanoLuc and CyRFP4 (Antares3), and an improved bioluminescent calcium sensor based on Antares3 (CaMBI3). Antares3 is 3-fold brighter than its predecessor, while CaMBI3 responds with an overall dynamic range of 24-fold, enabling high-sensitivity detection of calcium dynamics in muscle and neuronal tissues in vivo. Finally, a CaMBI3 variant and a red-shifted opsin ChRmine enabled red photon-assisted synaptic transmission in C. elegans. CaMBI3 thus facilitates genetically targeted non-invasive imaging and rewiring of neural activity in living animals.

neuroscience↗

bioRxiv2026

CellFluxV2: An Image Generative Foundation Model for Virtual Cell Modeling

Building a virtual cell that simulates cellular behavior in silico is a central goal of computational biology. We introduce CellFluxV2, an image-generative model that predicts how cell morphologies change in response to chemical and genetic perturbations. A core innovation of CellFluxV2 is to learn distribution-level transformations from unperturbed to perturbed cells within the same experimental batch using flow matching, enabling it to disentangle true perturbation effects from confounding batch effects. Incorporating three methodological advances, CellFluxV2 achieves up to a 77% improvement in image fidelity over diffusion- and GAN-based baselines, while maintaining biological fidelity comparable to ground-truth images. Scaling up CellFluxV2, we establish the first scaling laws in image-based virtual cell modeling, demonstrating that performance improves consistently with both dataset size and model capacity. Furthermore, the scaled-up model generalizes well to out-of-distribution perturbations and exhibits two novel capabilities: batch-effect correction and cell-state interpolation. Together, these results position CellFluxV2 as a powerful foundation model advancing the vision of a virtual cell, unlocking novel opportunities for in silico drug screening.

bioinformatics↗

bioRxiv2026

Single-cell Tree-based Model for Genomic-Disease Association

The rapid maturation of single-cell multi-omics technologies has enabled unprecedented resolution for mapping disease states and identifying disease-associated biomarkers. In practice, biomarkers are often discovered through differential detection that treat genomic features as independent contributors to phenotypes, while the combinatorial interactions that drive clinical outcomes remain a practical challenge. We present scanCT (single-cell analysis of Clinical Tree), a tree-based framework that identifies groups of genomic features associated with distinct disease phenotypes in a highly interpretable manner. scanCT uses an unbiased, model-based variable-selection procedure for data-driven split selection, which is important for handling the diverse distributional properties of single-cell data across modalities. The tree architecture captures feature interaction effects, and the association modeling enables adjustment for confounding factors. We apply scanCT to longitudinal single-cell multi-omics COVID-19 datasets spanning diverse clinical outcomes and multiple time points per patient. scanCT identifies phenotype-specific gene and protein markers while accounting for age and sex, and it reveals interpretable synergistic marker combinations that help explain differences in patient clinical phenotypes.

bioinformatics↗

bioRxiv2025

To Predict is to Design: Unlocking Generative Capabilities in All-Atom Structure Predictors via Geometric Score Distillation

Current protein binder design largely relies on a decoupled paradigm: generating backbones via unconditioned diffusion followed by sequence filling or refilling with inverse folding models. This separation prevents the design process from accessing the holistic validation metrics of structure predictors during generation, wasting rich physical priors. While recent works like BindCraft have successfully inverted AlphaFold2 for protein design1, extending this inversion to state-of-the-art all-atom diffusion predictors (e.g., AlphaFold3, Boltz-2) remains a formidable challenge, particularly for modalities requiring non-standard residues such as cyclic peptides. In this work, we present DREAM (Differentiable Refinement via Energy-Anchored Manifolds), a model-agnostic framework that turns the passive predictive trajectory of diffusion models into an active, lucid design process. DREAM repurposes Boltz-22--a leading open-source all-atom predictor--via Geometric Score Distillation (GSD), a technique enabling explicit gradient-based optimization directly through the frozen diffusion network. Unlike previous methods constrained by standard amino acids, DREAM directly unlocks the models latent chemical vocabulary, allowing gradients to autonomously select the optimal building blocks up to 55 residue types (including D-amino acids and post-translational modifications) to minimize energy. We demonstrate this capability by designing cyclic peptide binders for diverse targets, including PD-L1, B7-H3, and the human -Opioid Receptor (hMOR). Our results suggest that the programmable design of chemically complex modalities is not a distant goal, but a latent capability of current all-atom predictors, waiting to be inverted. Ultimately, to predict is to design.

biophysics↗

bioRxiv2025

Decoding Neoantigen-encoding Tumor-Specific Transcripts Unveils a Shared Target Reservoir for Immunotherapy in Hepatocellular Carcinoma

Background and AimsPrimary liver cancer, predominantly hepatocellular carcinoma (HCC), has limited therapeutic options. While mutation-derived neoantigen vaccine holds promise, its success is hindered by low antigen availability. This study explores transcriptome-derived neoantigens (neoantigen-encoding tumor-specific transcripts, neoTSTs) in HCC, characterizing their features, generation mechanisms, and therapeutic potential. Approach and ResultsWe analyzed RNA-seq data from 1,013 liver cancer patients and constructed a multi-layered reference dataset. Using a customized pipeline, we identified an average of 60 neoTSTs per patient, significantly surpassing mutation-derived neoantigens (neoMuts). NeoTSTs exhibited higher population frequencies, with 73.1% providing multiple epitopes, and were validated through mass spectrometry and HLA transgenic mouse models. Mechanistically, neoTSTs were generated via retained introns, transposable element activation, HNF4A-regulated alternative promoters, and de novo transmembrane domain (TMD) generation. Single-cell analysis revealed neoTSTs cover >75% of tumor cells and identified antigen-presenting cancer-associated fibroblasts (apCAFs) that enriched in immunotherapy responders and amplified CD4 T-cell responses via MHC-II presentation. In murine HCC models, neoTST vaccination outperformed neoMuts, inducing dual MHC-I/II activation and significant tumor growth inhibition. ConclusionsNeoTSTs represent a superior neoantigen source in HCC, compensating for the limitations of mutation-derived targets. Their abundance, sharedness, and dual MHC pathway activation highlight their potential for personalized immunotherapy, particularly in low-TMB tumors. Graphic Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=178 SRC="FIGDIR/small/692877v1_ufig1.gif" ALT="Figure 1"> View larger version (44K): org.highwire.dtl.DTLVardef@1bedfedorg.highwire.dtl.DTLVardef@5f6c95org.highwire.dtl.DTLVardef@d1deb5org.highwire.dtl.DTLVardef@743e85_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2025

Visualization of photoreceptor outer segment renewal using AAV-delivered Dendra2-tagged rhodopsin

Visualization of photoreceptor outer segment (OS) renewal dynamics is essential for vision research but has proved difficult in mice due to the small size and dense packing of their photoreceptors. Lack of effective protein "trackers" and the time-consuming generation of transgenic reporter lines add to these challenges. In this study, we evaluated AAV-mediated delivery of photoconvertible Rhodopsin/Dendra2 and Peripherin2/Dendra2 fusion proteins as a means to track OS renewal in mouse photoreceptors. OS renewal was assessed by two approaches: (1) comparing the lengths of native (green) Dendra2 domains at two post-infection time points, and (2) using photoconversion of Dendra2 to distinguish newly synthesized discs from preexisting ones within the same cell. We validated this method in both wild type mice and a Tmem138-deficient ciliopathy mutant, in which a reduced OS renewal rate was observed. Taken together, this method offers a rapid genetic tool for "real-time" evaluation of OS renewal dynamics in mice, overcoming limitations posed by the compact and densely organized photoreceptor architecture.

cell biology↗

bioRxiv2025

Genome-wide CRISPR screen reveals PEX11B as a host restriction factor against ORFV through membrane fluidity regulation

Host-pathogen interactions are shaped by cellular restriction factors that direct antiviral defenses. We built the first ovine genome-wide CRISPR knockout library in sheep testis (OA3.Ts) cells, targeting all protein-coding genes. Using this platform, we identified PEX11B, a peroxisomal membrane regulatory protein, as a strong restriction factor against orf virus (ORFV) infection. Removing PEX11B increased viral susceptibility and triggered severe cytopathic effects with membrane fusion and syncytia formation. Mechanistic studies showed that PEX11B knockout harmed peroxisomal integrity and disrupted lipid metabolism. This led to greater plasma membrane fluidity, creating a proviral environment that allowed more viral entry and replication. These results reveal a new antiviral function for PEX11B in blocking viral infection and underscore the importance of peroxisomal regulation in host-virus interactions.

microbiology↗

bioRxiv2025

Multi-agent AI enables evidence-based cell annotation in single-cell transcriptomics

Cell type annotation remains a critical bottleneck, with current methods often inaccurate and requiring extensive manual validation, particularly in disease contexts. While large language models (LLMs) show promise, they can be unreliable due to hallucinations. We developed CyteType, a multi-agent framework that generates competing hypotheses grounded in full expression data and study context, validates against external databases, and iteratively self-evaluates. Comprehensive benchmarking demonstrates that CyteType substantially outperforms reference-based and LLM-based methods, with self-generated confidence scores reliably identifying trustworthy annotations. CyteType transforms cell type annotation from label assignment into evidence-grounded biological discovery. Python (AnnData compatible): https://github.com/NygenAnalytics/CyteType R (Seurat compatible): https://github.com/NygenAnalytics/CyteTypeR

bioinformatics↗

bioRxiv2025

Genetically Engineered Cell Membrane-Coated Nanodrug for Targeted Treatment of Thyroid Cancer

Thyroid cancer is the most common endocrine malignancy, particularly in patients with radioactive iodine-refractory differentiated thyroid cancer (RAIR-DTC), who have limited treatment options and poor clinical prognosis. In this study, doxorubicin (DOX) and sorafenib (SOR) were loaded into the photothermal conversion agent mesoporous polydopamine (mPDA), forming mPDS. Tumor cell membrane coating engineering resulted in the formation of mPDS@CAR-M, significantly improving tumor targeting. After internalization by tumor cells, the loaded drugs are rapidly released under near-infrared (NIR) laser irradiation. mPDS@CAR-M effectively inhibits tumor cell proliferation by enhancing oxidative stress, suppressing the PI3K-AKT-mTOR signaling pathway, and inducing cytotoxic autophagy. By activating harmful autophagy, mPDS@CAR-M further inhibits the epithelial-mesenchymal transition (EMT) process, reducing tumor cell migration capacity. In vivo experiments showed that mPDS@CAR-M significantly reduced tumor volume, with its therapeutic efficacy closely related to the expression level of the targeted surface antigen. Therefore, mPDS@CAR-M demonstrates significant potential in the treatment of RAIR-DTC, providing a novel direction for further clinical exploration.

cancer biology↗

bioRxiv2025

The Critical and Unexpected Role of a Methyl Group in Interleukin-17A Inhibitors

Interleukin-17 (IL-17) is a pro-inflammatory cytokine primarily secreted by Th17 cells. It plays a crucial role in the bodys immune defense against fungal and bacterial pathogens. However, an imbalance in IL-17 production can contribute to the development of autoimmune and inflammatory disorders. Therapeutic strategies targeting IL-17, such as blocking antibodies like secukinumab (Cosentyx), have been successfully developed. These antibodies are currently employed in the treatment of various conditions, including psoriasis, psoriatic arthritis, and ankylosing spondylitis. More recently, a small molecule inhibitor of IL-17, LY3509754, progressed to clinical trials but was halted during Phase 1 due to unfavorable hepatotoxicity. Two derivatives, compounds 7 and 8, did not advance to clinical trials due to safety concerns. These three compounds (7, 8, and the original lead compound, presumably implied) share a common difluoro substituent, which was hypothesized to be the cause of the observed safety issues. In subsequent structure-activity relationship (SAR) studies, replacing the difluoro substituent with a single methyl group (resulting in compound 9) unexpectedly led to a significant improvement in cellular activity. Furthermore, compound 9 exhibited a very low unbound fraction and reduced liver distribution, ultimately translating to high in vivo efficacy with a sufficient safety margin. This seemingly minor methyl substitution transformed the compound into a highly promising preclinical candidate (compound 9), now slated for further development. Co-development inquiries are welcome. Please contact us at enan1@dcpc.com. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=76 SRC="FIGDIR/small/680113v2_ufig1.gif" ALT="Figure 1"> View larger version (13K): org.highwire.dtl.DTLVardef@3f31adorg.highwire.dtl.DTLVardef@d6873forg.highwire.dtl.DTLVardef@494af7org.highwire.dtl.DTLVardef@1d8b7eb_HPS_FORMAT_FIGEXP M_FIG C_FIG

pharmacology and toxicology↗

bioRxiv2025

Observing biological spatio-angular structures and dynamics with statistical image reconstruction and polarized fluorescence microscopy

Understanding molecular orientation and density distributions is essential for exploring biological structure and function. Polarized fluorescence microscopy (PFM) provides insights into molecular architecture but struggles to resolve three-dimensional (3D) molecular orientation distributions, particularly in densely labeled or structurally complex specimens. To address this, we introduce the efficient generalized Richardson-Lucy (eGRL) algorithm, a robust framework for reconstructing 3D molecular density and orientation (spatio-angular) distributions from PFM data. By modeling the imaging process in spatio-angular hyperspace, we propose a maximum-likelihood solution enhanced by dimensionality reduction and angular domain transformation to overcome computational challenges. eGRL improves accuracy and efficiency across different PFM implementations, enabling use on standard platforms. We utilize our methods to resolve biological spatio-angular structures and dynamics otherwise impossible to resolve, including the tangential alignment of actin filaments in U2OS cells, nanowire-guided cytoskeletal organization in NIH3T3 cells, rotational actin patterns in live HeLa protrusions, and membrane tension-induced anisotropy in live macrophages.

bioengineering↗

bioRxiv2025

NEST-Scoring, a Novel miRNA Target Gene Profile Network Analysis of Placenta-Derived Extracellular Vesicles in a Transgenic Rat Model of Preeclampsia

Preeclampsia is a multisystem hypertensive disorder of pregnancy and a leading cause of maternal morbidity and mortality. Despite its increasing incidence and the debilitating nature of its cerebrovascular complications, the underlying mechanisms remain incompletely understood. The goals of this study were to 1) determine whether middle cerebral artery (MCA) hemodynamics are altered in late gestation (LG) or two months postpartum in transgenic rats with preeclampsia compared to normal pregnant Sprague-Dawley (SD) rats, and 2) evaluate the microRNA (miRNA) profiles of circulating placental-derived extracellular vesicles (EVPD) using the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway framework using NEST-Scoring [Node, Edge, System, Topology], a novel target gene profile network analysis. Our data showed elevated blood pressure in transgenic preeclampsia rats at both LG and two months post-partum (PP-2M) compared to normal pregnant SD rats in the setting of hypertension. The heart rate was also significantly higher in preeclampsia rats at LG. No differences were observed in left MCA (LMCA) velocities between strains or time points. However, LMCA resistance and pulsatility indexes were lower at PP-2M in transgenic preeclampsia rats compared to SD rats. Exposure to preeclampsia differentially altered the miRNA profiles of circulating EVPD in transgenic preeclampsia rats at both LG and PP-2M. The identified miRNA targets were associated with key vascular and cellular regulatory pathways, suggesting a mechanistic link between placental dysfunction and postpartum vascular alterations in this preeclampsia model. Overall, this study suggests that the TGA-PE rat model could be a valuable platform to study the mechanistic link between preeclampsia and cerebrovascular disease.

bioinformatics↗