Biology subjects

Yu, L.

Publications and source records attributed to Yu, L..

At least 37 records · Page 2Linked to original sources

bioRxiv2026

Antibody evasion and receptor binding of SARS-CoV-2 variants PQ.16.1.1 and RK.1

The recent global expansion of the SARS-CoV-2 variant NB.1.8.1 has driven the emergence of sublineages PQ.16.1.1 and RK.1, which independently acquired the D420N mutation in their receptor-binding domains and and now dominate the Asia-Pacific region. Evaluations utilizing surface plasmon resonance and pseudovirus assays demonstrate that these sublineages exhibit significantly reduced human ACE2 receptor engagement compared to their parental strain. However, this functional cost is offset by a marked ability to evade humoral immunity, specifically demonstrating profound resistance to Class 1 neutralizing monoclonal antibodies and convalescent plasma from Wuhan-Hu-1-primed individuals. This convergent evolution exemplifies a classical viral trade-off, sacrificing receptor binding efficiency to escape population-level immune pressure. Consequently, these findings suggest these variants will soon spread globally and emphasize the critical need for ongoing surveillance to monitor D420N-carrying lineages.

immunology↗

bioRxiv2026

Elevated CO2 enhances tomato tolerance to Botrytis cinerea through transcriptional and metabolic defence reprogramming

Atmospheric CO2 concentration is projected to rise substantially over the coming decades, yet its impact on the molecular mechanisms governing plant immunity remains poorly understood. Here, we investigated how elevated CO2 (eCO2; 650 ppm) combined with increased temperature (+5 {degrees}C) influences tomato responses to Botrytis cinerea through integrated phenotypic, metabolomic, transcriptomic, and gene regulatory network (GRN) analyses across eight cultivars. Although cultivars displayed contrasting susceptibility under ambient conditions, eCO2 consistently enhanced tolerance across all genetic backgrounds. Multi-omics analyses revealed a partial uncoupling between transcriptional and metabolic responses during infection, with repression of photosynthesis- and carbon metabolism- related genes contrasting with the accumulation of carbon- and amino acid-derived metabolites. Under eCO2, this metabolic disruption was attenuated, preserving metabolic homeostasis during infection. GRN reconstruction identified a conserved WRKY-ERF regulatory module underlying the growth-defence trade-off, while functional perturbation demonstrated that its contribution to resistance depends on both genotype and environmental context, highlighting the importance of basal defence mechanisms. Targeted metabolomics further revealed that eCO2 promotes a metabolically primed state characterized by reinforcement of structural and chemical defence barriers rather than stronger activation of inducible immune responses. Together, our findings show that enhanced tolerance under eCO2 emerges from coordinated reorganization across regulatory and metabolic networks, providing a systems- level framework for understanding plant immunity and improving crop resilience under future climate scenarios.

plant biology↗

bioRxiv2026

Phasing of the 'Wonderful' Pomegranate Genome Using Haploid DNA Extracted from Pollen Grains

The scientific and commercial interest in pomegranate (Punica granatum L.) cultivation has increased noticeably during the last two decades. Because of the high concentration of bioactive compounds and its promising nutraceutical properties, pomegranate has been defined as a functional food. In order to develop advanced genomic tools to improve pomegranate breeding program efficiency, we present the chromosome-scale and haplotype-resolved genome assembly of Wonderful, a pomegranate cultivar widely grown around the world. DNA isolated from diploid leaf tissues was sequenced using long read sequencing technology (PacBio and Nanopore), while DNA extracted from haploid pollen grains was sequenced using a short-reads platform (Illumina). Genomic data from 11 single haploid gamete cells were analyzed using the R package called Hapi to phase the genome. The final genome assembly size was of 372.51 Mbp anchored to eight pairs of homologous chromosomes. The present study provides an insight on the adoption of an innovative and efficient approach for the assembly of haplotype-resolved genomes, which enables a higher resolution of DNA variant detection and offers the opportunity to investigate crossover events in single gamete cells during meiosis.

genomics↗

bioRxiv2026

Lineage recording reveals hijacked hepatic progenitor states as a common origin of HCC and ICC

HighlightsCERAMIC enables continuous and high-capacity lineage tracing of liver tumor initiation Fatty liver-associated hepatocytes acquire regenerative and premalignant cell states before malignant transformation Lineage reconstruction identifies Hep_Bi-zonal cells as the cellular origin of liver tumor initiation Transcriptional and regulatory programs distinguish tumor-fated hepatocytes from failed-to-transform lineages Peroxisomal metabolism is required for progenitor-state formation and liver tumor initiation Spatial remodeling identifies a macrophage niche associated with tumor-fated hepatocytes Dual ontogenies and functional specialization of lipid-associated macrophages shape the tumor-fated hepatocyte niche Fatty liver disease predisposes to primary liver cancer, yet the lineage routes and niche mechanisms that select rare tumor-fated hepatocytes remain unclear. Here we developed CERAMIC, a high-capacity CRISPR-Cas9 lineage recorder that co-recovers editing scars and transcriptomes from single cells, and applied it to an AKT/NRAS-driven model of MASLD-associated liver tumor initiation. Longitudinal lineage, single-cell and spatial analyses revealed a hierarchical trajectory in which bipotential bi-zonal hepatocytes (Hep_Bi-zonal), rather than pericentral-like hepatocytes (Hep_CVlike), generated regenerative and neoplastic hepatocyte progenitor states that progressed toward both hepatocellular carcinoma and intrahepatic cholangiocarcinoma lineages. Tumor-fated cells preferentially expanded along a remodeled midlobular-periportal axis and depended on ACOX1-mediated peroxisomal beta-oxidation to withstand lipotoxic and oxidative stress. Spatial and lineage analyses further identified a sequential lipid-associated macrophage niche, in which monocyte-derived LAMs engaged tumor-fated hepatocytes through an LGALS9-P4HB axis, and P4HB inhibition suppressed tumor expansion. These findings define liver tumor initiation as a lineage-restricted process licensed by peroxisomal metabolic adaptation and macrophage-derived niche signals.

cancer biology↗

bioRxiv2026

Annual life-history strategy hitchhikes low-light adaptation in a clonal seagrass

While life-history strategies are typically fixed within species, evolutionary transitions between perenniality and annuality can occur. In clonal seagrasses, annual and perennial plants often coexist in the same population, providing a unique model for studying the genetic basis of this transition. Two seagrass Zostera marina populations in South Korea display a striking dichotomy: shallow-water sub-populations follow a typical perennial strategy, whereas their deep-water counterparts are annual. Here we show that this shift from perenniality to annuality, potentially caused by the SAPK7 gene, is genetically coupled with the CAO gene, which is under strong positive selection for low-light adaptation. The up-regulation of the SAPK7 gene triggers early flowering in seedlings, before the formation of any lateral shoots via asexual reproduction. In this special case where the genet contains only one ramet, the post-reproductive death of the ramet is equivalent to the death of the whole genet, which explains the annual phenotype. Our findings reveal a mechanistic example where annuality overcomes perenniality by hitchhiking on a positively selected gene. Given that the ancestral state of plants is perennial, this coupling of annuality with beneficial alleles may represent one of the pathways for the repeated evolution of annual life histories across flowering plants.

evolutionary biology↗

bioRxiv2026

Perturbation Curve models continuous transcriptional response trajectories and improves prediction of genetic modulations

Single-cell CRISPR screens, Perturb-seq, have revolutionized functional genomics by revealing biological causality. However, although perturbation assignments are typically represented as discrete labels, the cell-level effective strength of perturbations is often continuous and diverse. Current analytical frameworks struggle to decouple the variability in perturbation strength from the diversity of downstream responses. Here, we present Perturbation Curve (PertCurve), a nonlinear, curve-based computational framework that models the trajectories of transcriptomic responses by explicitly incorporating diverse perturbation magnitudes and strengths. By ordering cells by perturbation strength, we demonstrate that PertCurve accurately recapitulates the response magnitudes and reveals the distinct modularity and asynchrony patterns of downstream gene behaviors. These patterns are categorized into archetypes, including proportional, sensitive, and threshold responses. By applying this framework across CRISPRi/a modalities, we identify universal response patterns in viral infection, apoptosis, and proliferation genes, and reveal previously overlooked context-specific regulatory features in cell differentiation. Finally, incorporating PertCurve into perturbation prediction models and evaluation metrics enhances predictive performance, delivering actionable insights for refining established models.

bioinformatics↗

bioRxiv2026

Generalisable tissue-wide molecular reconstruction from histology

Spatial transcriptomics technologies measure gene expression within intact tissues but remain difficult to scale across large tissue sections and patient cohorts. Consequently, many studies rely on tissue microarrays (TMAs) or sparse spatial profiling designs, where molecular measurements are available for only limited tissue regions and are often generated using heterogeneous gene panels. Existing H&E to spatial gene expression prediction methods remain challenged by sparse molecular measurements, partially overlapping gene panels and tissue-wide reconstruction across heterogeneous spatial datasets. Here, we present GHIST+, a framework for tissue-wide reconstruction of single-cell molecular states from H&E histology. GHIST+ integrates cellular morphology, local tissue context and shared tissue representations to extend sparse molecular measurements into tissue-wide molecular maps across heterogeneous spatial datasets. Across multiple cancer types and GTEx breast tissues, GHIST+ reconstructs biologically meaningful tissue-wide molecular organisation from sparse TMA-derived measurements while preserving spatial tissue structure, cell-type organisation and age-associated tissue states across cancer and non-cancer settings. GHIST+ establishes a scalable framework for transforming sparse spatial profiling experiments into tissue-wide molecular maps, enabling cohort-scale molecular reconstruction from routine histology under heterogeneous spatial transcriptomic settings.

bioinformatics↗

bioRxiv2026

Lack of ancestral SARS-CoV-2 imprinting promotes BA.3.2.2 infection in children

The ongoing evolution of SARS-CoV-2 is heavily constrained by population-level immune imprinting. Recent genomic surveillance reveals an unexpected demographic shift: the highly mutated BA.3.2.2 sublineage is significantly enriched in paediatric populations globally, unlike concurrent variants XFG and NB.1.8.1. Here, the evidence demonstrates that this paediatric susceptibility arises from the absence of ancestral Wuhan-strain immune imprinting. Serological analyses reveal a profound failure to neutralise BA.3.2.2 in young children with no ancestral strain exposure. Concurrently, single-B-cell sequencing analyses demonstrate that BA.3.2.2 completely evades Omicron-specific Class 1/4 neutralising antibodies, encoded by IGHV2-5 and IGHV5-51, which dominate the repertoires of weakly imprinted individuals such as young children. Conversely, BA.3.2.2 remains uniquely susceptible to broadly cross-reactive Class 1 antibodies, encoded by IGHV3-53/66, typically enriched in adults with strong ancestral imprinting, such as mRNA vaccine recipients. Critically, sustained transmission of BA.3.2.2 in paediatric populations may catalyse the emergence of secondary variants that combine the paediatric-evading features of BA.3.2.2 with adult-evading Class 1 mutations. This could allow the lineage to breach the imprinted immunity of the adult population, potentially driving widespread global transmission. Together, these findings show that legacy immune imprinting paradoxically provides superior protection against a highly divergent saltation variant, directly explaining the age-biased transmission of BA.3.2.2, and informing future paediatric vaccination strategies.

immunology↗

bioRxiv2026

Intra-Abdominal Bowel Dilation in Experimental Gastroschisis is Associated with a Modifiable Transcriptomic Program of Intestinal Dysfunction

STRUCTURED ABSTRACTO_ST_ABSObjectiveC_ST_ABSTo characterize intestinal transcriptional profiles in gastroschisis, their temporal evolution, and response to fetal intervention. Summary Background DataGastroschisis causes significant intestinal dysfunction, with intra-abdominal bowel dilation clinically shown to correlate with worse outcomes. While inflammation and neurovascular impairment have been implicated, genome-wide transcriptional characterization of disease severity remains lacking. MethodsUsing a fetal ovine model of complex gastroschisis, in which all gastroschisis animals demonstrated significant intra-abdominal bowel dilation at term, bulk RNA sequencing was performed on proximal small intestinal tissue from mid-gestation and term fetuses across three groups: normal, gastroschisis, and prenatally repaired gastroschisis. Differential gene expression (FDR [≤] .05, |log2 fold change| [≥] 1.5) and pathway enrichment analyses were performed, with targeted interrogation of extracellular matrix (ECM), enteric nervous system (ENS), angiogenic, and inflammatory pathways. ResultsAt mid-gestation, gastroschisis intestine showed minimal transcriptional differences (150 differentially expressed genes [DEGs]) and some bowel dilation. By term, dysregulation was substantial (2,423 DEGs) alongside significant dilation. Normal ontogenetic intestinal maturation patterns were altered, with fewer expected developmental gene changes and discordant pathway regulation. ECM pathway aberrations emerged early and persisted, while ENS, angiogenic, and inflammatory pathways were only dysregulated at term. Fetal repair was associated with normalization of gene expression at term (29 DEGs vs controls). ConclusionIntestinal transcriptional changes in experimental gastroschisis parallel progressive bowel dilation, consistent with a mechanical stress contribution to intestinal injury. Prenatal repair normalizes both dilation and gene expression, indicating a dynamic and potentially modifiable transcriptional program that supports the rationale for early fetal intervention. Mini AbstractIn a fetal ovine model, progressive bowel dilation in gastroschisis parallels transcriptomic dysregulation of ECM remodeling, neurovascular impairment, and inflammation which is normalized by prenatal repair.

developmental biology↗

bioRxiv2026

Soft Sensing of Intracellular States for CHO Cell Bioprocessing with Ensemble Kalman Filters

In biotherapeutic manufacturing, product quality such as glycosylation profile is typically assessed only after harvest, limiting opportunities for corrective action during cell culture operation. Intracellular nucleotide sugar donors (NSD) directly determine glycosylation outcomes but are rarely measured, even offline, due to analytical complexity and process disruption. As a result, quality-related decisions remain constrained to fixed operating strategies. This work introduces a model-based soft sensing framework to infer NSD concentrations from readily available extracellular measurements. A Bayesian state estimation approach based on the Ensemble Kalman Filter (EnKF) is developed to reconstruct unmeasured intracellular states during CHO cell culture. An imperfect kinetic process model is combined with noisy extracellular measurements, explicitly accounting for process variability and measurement uncertainty through ensemble-based propagation and updates. The framework is validated using four independent experiments with distinct feeding perturbations that are not used for model calibration. Although the open-loop model exhibited substantial mismatch for both extracellular metabolites and intracellular NSDs, EnKF assimilation of extracellular measurements corrected key metabolic profiles. Building on these corrected extracellular dynamics, the EnKF demonstrated robust estimation of a growth-determining amino acid, asparagine, from correlated extracellular states. Based on the improved extracellular and amino acid estimates, the framework further enabled reliable inference of intracellular NSDs across all experiments.

bioengineering↗

bioRxiv2026

miR-128 Regulates Hypertensive Vascular Remodeling via PPAR-γ

OBJECTIVEThis study aimed to explore the role and underlying mechanism of microRNA-128 (miR-128) in regulating vascular remodeling in spontaneously hypertensive rats (SHRs), focusing on its targeting of peroxisome proliferator-activated receptor {gamma} (PPAR-{gamma}) and modulation of the Toll-like receptor 4/nuclear factor-{kappa}B (TLR4/NF-{kappa}B) inflammatory pathway. METHODSAll experimental procedures were approved by the Animal Care and Use Committee of Fujian Medical University. In vivo, ten-week-old male SHRs were randomly assigned to three groups: renal denervation (RDN, n=6), sacubitril/valsartan (Sac/Val, n=6), and Sham (n=6). Age-matched Wistar-Kyoto (WKY) rats served as normotensive controls (n=6).Eight weeks after intervention, mesenteric arteries were harvested for histological, functional, and molecular analyses. Serum miR-128 levels were measured by quantitative real-time polymerase chain reaction (qRT-PCR). The expression levels of key proteins in the vascular wall were assessed via immunofluorescence (IF), immunohistochemistry (IHC), and Western blotting (WB). Bioinformatics analysis and RNA sequencing (RNA-seq) were employed to identify core genes and signaling pathways associated with hypertension-induced pathological inflammation. RESULTSIn vivo, in the SHR sham-operated group, elevated blood pressure, severe vascular remodeling, and impaired vasodilatory function were observed, accompanied by downregulated miR-128 expression and upregulated TLR4/NF-{kappa}B signaling activity (all p < 0.0001).RDN postoperative, miR-128 expression was significantly restored, which in turn inhibited the TLR4/NF-{kappa}B pathway, reduced the production of pro-inflammatory cytokines (including IL-1{beta}, IL-6, and TNF-), and ameliorated vascular dilation dysfunction in SHRs (all p < 0.0001). Mechanistically, miR-128 negatively regulated the TLR4/NF-{kappa}B signaling pathway while upregulating the expression of PPAR-{gamma} (p < 0.05). CONCLUSIONRDN not only exerts a hypotensive effect but also improves hypertensive vascular remodeling. miR-128 inhibits excessive inflammation in vascular smooth muscle cells and alleviates vascular remodeling in SHRs via the PPAR-{gamma}/TLR4/NF-{kappa}B axis. These findings identify miR-128 as a potential therapeutic target for RDN in the treatment of hypertension, providing a novel regulatory strategy for the precision management of cardiovascular diseases.

bioinformatics↗

bioRxiv2026

G-SPRI: A Structure-Centric Graph Model for Comprehensive Prediction of Cancer Driver Events from Missense Mutations

In silico approaches for predicting the functional impact of missense mutations are critical for interpreting personal genomes and identifying disease-related biomarkers. Existing methods largely rely on sequence-based information or intuitive structural features, but often overlook the complex biophysical patterns encoded in protein 3D structures. Here, we present G-SPRI, a multilevel framework built on a novel alpha-shape protein graph that accurately captures residue connectivity from atomic-resolution geometry and enables precise message passing around mutation sites. Using this graph representation, G-SPRI integrates wild-type structural properties and mutation-specific perturbation signals derived from the Protein Data Bank (PDB) universe to support graph-based learning for distinguishing pathogenic from benign missense variants. G-SPRI performs strongly across multiple key tasks. On the binary prediction benchmark, G-SPRI delivers improved pathogenicity prediction for individual mutations. By integrating mutation recurrence across the pan-cancer cohort, G-SPRI recovers more known cancer driver genes than state-of-the-art methods from more than 2.3 million mutations. Furthermore, by jointly quantifying site-specific pathogenicity and co-clustering influence within higher-order structural organization units, G-SPRI provides comprehensive evidence for pinpointing likely driver mutations and structurally susceptible regions within disease genes.

bioinformatics↗

bioRxiv2026

BRIDGE: A Multi-organ Histo-ST Foundation Model Enables Virtual Spatial Transcriptomics for Enhanced Few-shot Cancer Diagnosis

Recent studies have explored generating virtual spatial transcriptomics (ST) profiles from histological images, offering a promising alternative to laboratory-measured molecular profiling. However, existing approaches predominantly rely on single-organ models and require sub-stantial organ-specific training data, restricting their accuracy under challenging few-shot conditions in clincical practice, where less than 10 slides are available for specific organs or techniques. Here, we present BRIDGE, a multi-organ foundation model pre-trained on over 600,000 paired histology-ST profiles across 13 human organs and three sequencing techniques. By robustly aligning morphological features and genomic information within a shared multi-organ latent space, BRIDGE can leverage common biological knowledge across distinct tissues to enable accurate and generalizable pan-cancer molecular profiling. Without additional organ-specific fine-tuning, BRIDGE accurately predicts the spatial expression of 80 biomarker genes, achieving an average Pearson correlation coefficient (PCC) of 0.474--a 30% improvement over existing state-of-the-art models under three clinically challenging few-shot scenarios. With generated virtual ST, BRIDGE outperforms current state-of-the-art pathology foundation models in predicting cancer survival, achieving an average concordance index (C-index) of 0.724 across six TCGA cohorts. Notably, BRIDGE maintains exceptional performance even in zero-shot scenarios involving three cancer types not seen during its training, achieving an average C-index of 0.717, thereby demonstrating its strong generalization capability that transcends organ- and subtype-specific boundaries. Moreover, BRIDGE-generated virtual spatial transcriptomes match the prognostic accuracy of bulk RNA-seq, highlighting their potential as a spatially informative alternative to laboratory sequencing. In general, BRIDGE represents a data-efficient tool in virtual ST that facilitates biomedical discoveries in clinical few-shot contexts and advances diagnosis of understudied cancers without sufficient samples.

genomics↗

bioRxiv2026

linearPOA: A parallel, memory-efficient framework for Partial Order Alignment with linear space complexity

Multiple sequence alignment (MSA) is a fundamental problem in computational bioinformatics, playing a critical role in genome biology, especially in long read sequencing and assembly. One solution for representing and solving MSA is Partial Order Alignment (POA), which employs Directed Acyclic Graphs (DAGs) to represent sequence relationships. However, when facing the ultra-long, error-prone reads (e.g., >100 kbps), existing POA algorithms with quadratic space complexity become impractical due to excessive memory consumption. This paper introduces the linearPOA, which based on divide-and-conquer strategy to solve the POA, aimed at saving memory compared to quadratic space complexity algorithms like SPOA, abPOA and TSTA. Particularly notable is its capability to save up to 102.74 times memory usage when aligning sequences with 100 kbp reads, compared to the abPOA method using non-heuristic methods. The algorithm was implemented within the linearPOA library, providing functionality for POA and foundational support for sequencing analysis, like error correction for reads. The linearPOA algorithm provides memory-efficient algorithms for long-read sequencing, especially in directly assembling long reads like 100 kbp reads. AvailabilityThe linearPOA library is freely available at https://github.com/malabz/linearPOA, and the data underlying this article are available in Zenodo, at https://doi.org/10.5281/zenodo.15637837. Supplementary informationSupplementary information are available at BioRxiv online.

bioinformatics↗

bioRxiv2026

Cerebellar Microcircuits and Cortico-Cerebellar Cooperation Enable Robust Decisions

The cerebellum is increasingly implicated in perceptual decision-making, yet how cerebellar circuits-- without prominent recurrent excitation and slow reverberant loops--could support sparse evidence accumulation over behavioral timescales remains unclear. We present a biologically constrained modeling framework showing that cerebellar microcircuits can implement graded accumulation and competition without cortical-like excitatory recurrence. Type-II Purkinje-neuron excitability generates firing-rate hysteresis that prolongs the impact of brief inputs far beyond intrinsic membrane and synaptic time constants, enabling accumulation across long inter-event intervals. Purkinje neuron collateral inhibition produces competitive divergence and tunes temporal evidence weighting, revealing a trade-off between commitment and primacy bias. In a bidirectionally coupled cortico-cerebello-cortical model, cerebellar processing reduces primacy while cortical processing reduces indecision, improving robustness. Together, these results propose a mechanistic division of labor that positions the cerebellum as an active computational partner in perceptual decisions.

neuroscience↗

bioRxiv2026

Connecting polygenic disease risk to cell states and regulatory programs through single-cell chromatin accessibility

Single-cell ATAC-sequencing enables high-resolution mapping of cell states and their putative regulatory elements. The enrichment of genome-wide association study (GWAS) signals within context-specific regulatory regions can reveal disease-relevant cell populations. We present Single-Cell ATAC-seq Disease Score (SCADS), a computational framework that integrates GWAS summary statistics with scATAC-seq data to prioritize disease-relevant cells. SCADS produces calibrated, cell-level scores that are comparable across datasets and traits by: (i) identifying chromatin co-regulatory regions via topic modeling, (ii) quantifying their polygenic GWAS enrichment, and (iii) calculating cell-specific disease scores from topic weights and enrichment levels. Across extensive simulations, SCADS outperforms existing methods in power while controlling false positives. Applied to multiple autoimmune traits, SCADS reveals marked heterogeneity in disease relevance within canonical immune cell types. We specifically studied the differential disease relevance within CD8+ T and colon epithelial cells for inflammatory bowel disease, and pinpointed underlying gene programs and variants. SCADS is scalable, interpretable, and modular, providing a general framework to connect noncoding regulatory variation to cellular identity and function.

genomics↗

bioRxiv2026

Balancing Inhibition and Sparsity for Stable, Accurate Cerebellar Learning

The cerebellums structured circuitry supports learning across motor and cognitive domains, yet the coding strategies in granule cells that enable this versatility remain unclear. Using a theoretical cerebellar model, we examined how feedforward inhibition (FFI) and feedback inhibition (FBI) shape granule cell activation patterns to optimize learning in two tasks: complex trace learning and pattern identification. For trace learning, performance depends on spatiotemporally ordered granule cell activity shaped by FBI, with temporal sparsity emerging as the key determinant of accuracy. For pattern identification, both pathways support high accuracy, with only slight sensitivity to pathway choice. In both tasks, spatial sparsity becomes critical in incremental learning to prevent memory interference, a role reinforced by advanced synaptic plasticity strategies. These findings identify sparse granule cell activation as a unifying principle for cerebellar learning and reveal task-dependent roles of inhibitory pathways, providing a mechanistic framework for understanding stability-plasticity trade-offs in cerebellar learning.

neuroscience↗

bioRxiv2026

The mechanism of Hsa_circ_0000629 in bronchial asthma through sponge adsorption of miR-212-5p/NLRP3

To explore the mechanism of Hsa_circ_0000629 adsorbing miR-212-5p/ nucleotide-binding oligomerization domain-like receptor protein 3 (NLRP3) through sponge in bronchial asthma. Twenty BALB/C mice were randomly divided into a normal control group and an asthma group. Pathological changes in lung tissue were observed via HE staining. Human bronchial epithelial cells (16HBE) were transfected with Hsa_circ_0000629 overexpression group (Hsa_circ_0000629-over), Hsa_circ_0000629 siRNA (Hsa_circ_0000629-si), mimic NC, miR-212-5p mimic, inhibitor NC, miR-212-5p inhibitor, and LPS+Hsa_circ_0000629 si. LPS-induced asthmatic cell models (LPS group) and untransfected 16HBE cells (NC group) served as controls. qRT-PCR was used to measure Hsa_circ_0000629, miR-212-5p and NLRP3 expression. ELISA assessed interleukin 18 (IL-18), interleukin 1{beta} (IL-1{beta}), interleukin 6 (IL-6) and tumor necrosis factor - (TNF-) levels. Cell proliferation and the apoptosis were evaluated by EDU assay and flow cytometry, respectively. Western blot analyzed Cleaved-caspase 1, 3 and 9 proteins expression. Dual-luciferase assay verified the binding sites of Hsa_circ_0000629 to miR-212-5p and NLRP3 to miR-212-5p. HE staining revealed inflammatory cell infiltration, bronchial wall thickening, smooth muscle hyperplasia, and alveolar destruction in asthmatic mice. Compared with the controls, Hsa_circ_0000629 and NLRP3 expression were significantly increased, while miR-212-5p expression was decreased in asthmatic lung tissues. In 16HBE cells, Hsa_circ_0000629-over and LPS groups showed elevated Hsa_circ_0000629 and NLRP3 expression but reduced miR-212-5p levels. Silencing Hsa_circ_0000629 in LPS-treated cells (LPS+Hsa_circ_0000629-si) reversed these effects. Overexpression of miR-212-5p counteracted Hsa_circ_0000629-induced NLRP3 upregulation, while miR-212-5p inhibition enhanced NLRP3 expression. LPS exposure increased TNF-, IL-18, IL-6, and IL-1{beta} levels, reduced cell proliferation, and promoted apoptosis. These changes were attenuated by Hsa_circ_0000629 silencing or miR-212-5p overexpression. Western blot confirmed that Hsa_circ_0000629 overexpression upregulated Cleaved-Caspase 1, 3, and 9, whereas miR-212-5p mimic or Hsa_circ_0000629-si reversed this trend. Dual-luciferase assays demonstrated targeted interactions among Hsa_circ_0000629, miR-212-5p, and NLRP3. Interference with Hsa_circ_0000629 expression can alleviate LPS induced apoptosis in 16HBE cells and inhibit the expression of inflammatory factors by targeting the miR-212-5p/NLRP pathway, which may be a new target for the treatment of asthma.

immunology↗