Biology subjects

Luo, Z.

Publications and source records attributed to Luo, Z..

At least 37 records · Page 2Linked to original sources

bioRxiv2026

IEKB: a comprehensive knowledge base for inner ear genetics integrating curated associations, cochlear interactions, Bayesian candidate prioritisation, explainable dark-gene support relations, and a scientific entity network

Inner-ear genetics has expanded rapidly, yet the supporting evidence remains dispersed across a vast literature and across resources that typically emphasise loci, variants, or expression data rather than integrated biological interpretation. Here we present the Inner Ear Knowledge Base (IEKB; https://earkb.org), an open database that unifies curated associations, cochlear interaction evidence, candidate prioritisation, explainable support relations, and network exploration for inner-ear research. IEKB was built with an automated agent-assisted curation workflow that combines schema-constrained literature extraction, continuous human monitoring, and final expert review by inner-ear genetics researchers. By systematically analysing 250,696 PubMed-indexed records retrieved across 16,563 screened genes, IEKB curates 6,051 gene-phenotype-disease associations from 2,494 genes across 43 phenotype categories and 4,102 cochlear gene-gene interactions with pathway, cell-type, and experimental context. IEKB further includes a Bayesian "dark matter" module that prioritises 243,071 candidate gene-phenotype associations for 13,229 genes across all 43 phenotypes (global AUC-ROC = 0.8603; global AUC-PR = 0.1674), together with a supervised dark-relation layer that ranks phenotype-specific known-gene support for each candidate and a multi-entity scientific network containing nearly 4,000 entities, 28,616 deterministic edges, and 83,712 literature-derived relational links. The web resource supports interactive search, multi-parameter filtering, gene-detail pages, bibliometric exploration, domain-specific enrichment against IEKB phenotype and disease gene sets, network visualisation, bulk download in CSV, JSON, SQLite, and XLSX formats, and natural-language evidence-grounded question answering through a companion conversational interface (IEKB QA). To our knowledge, IEKB is the first openly accessible inner-ear resource that integrates curated associations, cochlear interactions, probabilistic candidate prioritisation, auditable known-gene support relations for novel candidates, and a multi-entity scientific network within a single database. All data are released without registration under the CC BY 4.0 license.

bioinformatics↗

bioRxiv2026

End-to-end bimodal anti-counterfeiting by informational DNA nanoparticles

The superior stealth properties and high information density make DNA a sought-after candidate in the field of molecular steganography. Here, we developed the InfinMark end-to-end DNA steganography framework for anti-counterfeiting applications by combining the characteristics of both the Internet of Things (IoT) and DNA-of-Things (DoT). InfinMark includes five modules: Information Transcoding, Fingerprint Writing, Nano-encapsulation, Invisible Marking, and Multi-level Rapid Authentication. It ensures precise anti-counterfeiting information reading and writing through a dynamic DNA-compatible transcoding algorithm, achieves seamless embedding by developing scalable nanoparticle manufacture methods, and supports cross-scenario on-site verification, ultimately granting it comprehensive anti-counterfeiting capabilities spanning from source labeling to terminal tracing. By addressing the bottlenecks in IoT and DoT integration, lifecycle tracking, as well on-site product authentication, this research constructs a full-chain bimodal anti-counterfeiting system, thereby showcasing the practical application of informational DNA nanoparticles in various aspects of production and daily life.

synthetic biology↗

bioRxiv2026

DeSCENT: Deconvolutional Single-Cell RNA-seq Enhances Transcriptome-based Cancer Survival Analysis

MotivationAccurate cancer survival prediction requires modeling tumor heterogeneity across both population and cell levels. Most cancer survival analyses use tumor transcriptomes only, since cohorts are usually measured with bulk RNA-seq but are rarely recorded with single-cell RNA-seq. This prevents the direct use of cell-level transcriptomes in cancer survival analysis. ResultsTo bridge this gap, we propose using bulk RNA-seq deconvolution algorithms to reconstruct each subjects scRNA-seq profile from their bulk data. Then, by combining both scRNA-seq and bulk RNA-seq together with their survival labels (paired to bulk), we perform multimodal transcriptome-based survival analysis. We built this framework as DeSCENT and evaluated it with common survival models on eight TCGA cancer cohorts. Results showed notable and consistent improvements in C-index over bulk-only models or models using cellular information alone. AvailabilityOur code is available at GitHub: https://github.com/YonghaoZhao722/DeSCENT. Contactzpluo@swjtu.edu.cn; y.he@imperial.ac.uk Supplementary informationSupplementary data are available at Bioinformatics online.

bioinformatics↗

bioRxiv2026

OmicClaw: executable and reproducible natural-language multi-omics analysis over the unified OmicVerse ecosystem.

Advances in bulk, single-cell and spatial omics have transformed biological discovery, yet analysis remains fragmented across packages with incompatible interfaces, heterogeneous dependencies and limited workflow reproducibility. Here, we present OmicClaw, an executable natural-language framework for multi-omics analysis built on the unified OmicVerse ecosystem and the J.A.R.V.I.S. runtime. OmicVerse organizes upstream processing, preprocessing, single-cell, spatial, bulk-transcriptomic and foundation-model workflows into a shared AnnData-centered interface spanning more than 100 methods. J.A.R.V.I.S. converts this ecosystem into a bounded analytical action space through a registry-grounded, state-aware and recoverable execution layer that validates prerequisites, preserves provenance and supports iterative repair, while enabling conversational, notebook and visual interfaces to operate over the same live analytical state. Rather than relying on unconstrained code generation, OmicClaw translates user requests into traceable workflows over live omics objects. Across a benchmark of 15 tasks spanning scRNA-seq, spatial transcriptomics, RNA velocity, scATAC-seq, CITE-seq and multiome analysis, ov.Agent improved rubric-based performance over bare one-shot large language model baselines, particularly for long-horizon multi-step workflows. OmicClaw further supports external agent access through an MCP-compatible server and a beginner-friendly web platform for interactive analysis, code execution and million-scale visualization. Together, OmicClaw provides a practical foundation for reproducible human-AI collaboration in modern multi-omics research

bioinformatics↗

bioRxiv2026

Exploration of the screening and regulatory mechanisms of biomarkers related to ac4C modification in laryngeal squamous cell carcinoma patients based on single-cell analysis and machine learning

BackgroundN4-acetylcytidine (ac4C) modification plays a critical role in cancer development. Exploring ac4C modification in laryngeal squamous cell carcinoma (LSCC) may help elucidate its pathogenesis. MethodsLSCC-related datasets were obtained from GEO. After preprocessing and annotating single-cell data, malignant cells were identified by CNV scoring and further divided into subpopulations. Malignant epithelial cells (MECs) were identified and subclustered based on ac4C-related gene activity. Prognostic genes were screened using Cox regression and machine-learning approaches, followed by validation in clinical samples using qPCR. The biological and immunological relevance of these genes was further explored through immune infiltration, immunotherapy response, and mutation analyses. ResultsThe 14,465 identified MECs were classified into five subgroups (MEC1-5), among which MEC3 showed the strongest association with the ac4C gene set. Machine-learning analysis of MEC3-derived genes yielded seven prognostic markers, including BARX1, FHL2, NXPH4, PKMYT1, TNFAIP8L1, CRLF1, and CENPP. qPCR confirmed their differential expression between tumor and adjacent normal tissues. These genes were significantly associated with alterations in the tumor immune microenvironment, with high-risk patients showing increased immune infiltration and immune activity. ConclusionSeven ac4C-related prognostic genes were identified that may contribute to LSCC progression by modulating the tumor immune microenvironment, providing potential therapeutic insights.

developmental biology↗

bioRxiv2026

Syndecan is critical for Drosophila CNS and PNS glia function

Glia are irreplaceable components for the nervous system development and function. However, the cellular mechanisms each glial layer utilizes to communicate with each other and the extracellular environment is not well characterized. Here, we investigated the role of a heparan-sulfate proteoglycan, Syndecan (Sdc), in regulating glial cell function and development in the Drosophila nervous system. Sdc is expressed throughout multiple glial layers and loss of Sdc in all glia resulted in disruption of both central and peripheral glia. Within the CNS loss of Sdc in all glia lead to reduced brain lobes and disruption of neuroblast proliferation. In the PNS, loss of Sdc in different glial layers resulted in impaired ensheathment in wrapping glia and abnormal septate junction morphology in subperineurial glia. We focused on the outer layer of perineurial glia and found ensheathment defects and a reduction in glial numbers with Sdc loss. These phenotypes mirror those previously observed with the loss of integrins and a mutation in the integrin {beta}-subunit enhanced the phenotypes observed with loss of Sdc within the perineurial. Thus, our results indicate Sdc has multiple roles in Drosophila nervous system development including as an integral component in regulating glial cell morphology, maintaining neuroblast populations within the optic lobe and in mediating glial-ECM interactions.

neuroscience↗

bioRxiv2026

TRU-PE: A Universal, Trackable Prime Editor Toolkit for Robust Single- and Multi-Locus Genome Engineering

Prime editing (PE) holds immense promise for precise genome editing, but its wider adoption is constrained by large payloads and inefficient delivery in recalcitrant cell types. Here, we present TRU-PE (Trackable, Robust, and Universal Prime Editor), a toolkit that overcomes these barriers via a split-vector architecture coupled with fluorescence-guided enrichment. This design ensures stoichiometric component expression, yielding marked improvements in editing efficiency and accelerated workflows compatible with both plasmid and viral delivery. By integrating a polycistronic hCtRNA-sgRNA/pegRNA array, the derivative TRU-MPE system enables simultaneous editing of up to ten genomic loci. Furthermore, it enhances the performance of evolved PE editors, allows flexible vector stoichiometry and inspires novel editing reporters. Leveraging these capabilities, we successfully generated a combinatorial human iPSC-based platform for GATA2 deficiency, which accurately recapitulates genotype-specific hematopoietic defects. TRU-PE thus provides a user-friendly, scalable framework for robust single- and multi-locus genome engineering, accelerating functional genomics and therapeutic development.

genetics↗

bioRxiv2026

Structural evolution of the MTCH family of mitochondrial insertases

We demonstrate that MTCH2 is the defining member of a large family of mitochondrial outer membrane (OM) insertases. MTCH insertases are conserved across holozoa and have diverged from the solute carrier 25 transporters. The cryoelectron microscopy structure of the 33 kDa human MTCH2 revealed that evolution of its insertase activity required loss of a transmembrane helix, which created a lipid-accessible hydrophilic groove stabilized by its unique, structured C-terminus. Mutational analyses showed that MTCH insertase activity is attenuated, while experimental structures and reconstitution of hyperactive mutants demonstrated that the hydrophobicity, charge, and size of the residues that line its groove regulated MTCH function. Leveraging the MTCH2 structure, we identified the plant OM insertase, and proposed a universal mechanism for OM insertion across all kingdoms of life. TeaserStructure of human MTCH2 reveals conserved features necessary to maintain mitochondrial proteome integrity across eukaryotes.

cell biology↗

bioRxiv2026

Deep learning-guided design of cell type-specific AAV promoters

Precise cell type targeting is critical for both clinical and experimental applications of adeno-associated viral (AAV) vectors, yet engineering vectors with cell type-specific activity remains a challenge. Here, we compared three strategies leveraging single-cell chromatin accessibility data to design cell type-specific AAV promoters, including a deep learning-based method to generate de novo regulatory sequences. When applied to target retinal ganglion cells or horizontal cells in mouse retina, deep learning-guided design consistently outperformed rational approaches, yielding synthetic promoters with stronger and more specific expression in vivo. Synthetic AAV promoters supported diverse transgenes, enabling the recording and ablation of targeted cells. Promoter activity was also maintained in human retinal organoids, suggesting that deep learning-designed sequences may be suitable for translation. Our findings highlight the potential of deep learning to synthesize cell type-specific AAV promoters and establish a versatile platform for cell type targeting with broad implications for gene therapy and basic research.

synthetic biology↗

bioRxiv2025

Ensemble-DeepSets: an interpretable deep learning framework for single-cell resolution profiling of immunological aging

Immunosenescence increases susceptibility to infection and reduces vaccine responsiveness, yet bulk transcriptomic clocks obscure the cellular heterogeneity underlying this process. Here, we present IDEAL-Age, an interpretable deep learning framework that operates directly on single-cell PBMC transcriptomes. Benchmarking against 31 methods across independent cohorts demonstrates superior predictive performance. The frameworks interpretability uncovers linear and non-linear transcriptomic dynamics that reveal phase-specific physiological transitions, and identifies pro-youthful or pro-aging cellular contributions. Application to systemic lupus erythematosus (SLE) reveals accelerated immunological aging driven by interferon-associated monocyte shifts. IDEAL-Age establishes a high-resolution computational framework for deciphering systemic immune aging.

bioinformatics↗

bioRxiv2025

Comparative evaluation of reference genomes and cell-type annotation frameworks for single-nucleus transcriptomic analysis in apple

Single-nucleus RNA sequencing (snRNA-seq) provides a powerful tool to profile cell-type-specific transcriptional programs in woody fruit trees. Yet its application in Malus domestica has been limited by heterogeneous reference genomes and the lack of validated marker genes. Here, we first established a comprehensive set of marker genes corresponding to 29 plant cell types and identified their orthologs in apple. Using these resources, we systematically evaluated six publicly available apple genome assemblies as references for snRNA-seq analysis. Our results demonstrate that reference genome selection has a major impact on mapping performance and downstream cell type annotation, with the GDDH13 assembly consistently producing the highest transcript counts per nucleus and the greatest number of identifiable transcriptional clusters (15 clusters representing 11 distinct cell types across 35,557 high-quality nuclei). To achieve robust cell type annotation, we integrated classical marker gene-based annotation with two cross-species computational frameworks -- Orthologous Marker Gene Groups (OMGs) and XSpeciesSpanner. These three approaches enabled confident identification of 11 major cell types in apple seedlings and provided cross-validation for ambiguous or previously unannotated clusters. Pseudotime analysis reconstructed the developmental trajectories of both procambial and stomatal lineages, revealing their progressive transcriptional transitions and enabling the delineation of key molecular programs underlying vascular differentiation and early guard-cell formation. Together, this work provides a reference-quality single-nucleus transcriptomic atlas for apple and underlined the critical impact of genome choice and multi-method cell-type annotation on single-cell studies in non-model crops.

bioinformatics↗

bioRxiv2025

Lineage-specific evolution of regulatory landscapes in polyploid plant and its diploid progenitors

Cis-regulatory elements are specific DNA sequences that control gene expression in a spatiotemporal manner, and variation within these elements represents a major source of phenotypic diversity and evolutionary innovation. Nevertheless, how regulatory elements evolve and shape gene expression remains poorly understood, particularly in plants. The well-resolved phylogeny of allopolyploid peanut (Arachis hypogaea) and its diploid progenitors, A. duranensis and A. ipaensis, provides an ideal system to investigate the regulatory evolution at a lineage-specific level. By integrating comparative analyses of sequence similarity, chromatin accessibility, histone modifications, conserved noncoding sequences (CNSs), and gene expression, we reconstructed the evolutionary trajectories of Accessible Chromatin Regions (ACRs), where regulatory elements typically reside, and revealed their distinct contributions to homeolog expression bias, unequal expressions between homeologs. Most ACRs exhibited high sequence similarity, comparable chromatin accessibility, and conserved states for H3K4me3, H3K56ac, and H3K36me3, indicating regulatory stability after hybridization and polyploidization. However, a subset of novel ACRs emerged de novo from previously non-regulatory regions or through sequence mutations in preexisting ACRs, arising at different rates and evolutionary stages. Notably, even highly sequence-conserved ACRs exhibited substantial variation in chromatin accessibility, consistent with CNS composition differences and minor sequence variation, although causal relationships remain to be demonstrated. Our analyses further revealed a complex spectrum of CNS dynamics across the diploid-polyploid framework. Overall, our study provides empirical insights into the fine-scale evolution of plant regulatory landscapes and complements previous large-scale comparisons across distant lineages.

evolutionary biology↗

bioRxiv2025

Single-cell multi-omic characterization of the soybean root response to cyst nematode infection

Soybean cyst nematodes parasitize soybean roots by inducing the formation of multinucleate syncytia to feed and complete their life cycle. However, the molecular basis of syncytia initiation and development remains limited. Here, we generated an integrated single-nucleus RNA and chromatin accessibility profile of soybean roots from infected and uninfected plants. We profiled 56,448 high-quality nuclei and identified all major root cell types, including distinct subpopulations enriched with syncytial nuclei. Transcriptomic and chromatin accessibility analyses support their procambium cell signature that progresses through distinct stages associated with immune suppression, cell fusion, and endoreduplication. Integrative gene expression and transcription factor motif chromatin accessibility analyses identified CAMTA1, as a potential transcriptional repressor of defense-related genes including receptor-like kinases, whereas MYB, MYB-related, and E2F were identified as potential transcriptional activators that coordinate cell wall remodeling, chromatin modification and DNA replication, respectively, across developmental trajectories. These findings provide mechanistic insights into host reprogramming during nematode parasitism and serve as a foundational resource for engineering nematode-resistant soybean.

plant biology↗

bioRxiv2025

Female-predominant anti-CD4 IgG autoantibody production and its correlations with plasma levels of progesterone, microbial translocation, and blunted immune reconstitution in HIV-infected patients on suppressive ART

Autoimmunity contributes to HIV immunopathogenesis even in the absence of overt autoimmune disease. We previously showed that anti-CD4 autoantibodies from people with HIV (PWH) on suppressive antiretroviral therapy (ART) can mediate cytotoxicity against CD4+ T cells, implicating a role in impaired immune reconstitution. Despite viral suppression, many PWH with poor CD4 recovery exhibit chronic immune activation, microbial translocation, and dysregulated humoral immunity. Here, we identify a female-predominant elevation of plasma anti-CD4 IgG autoantibodies in aviremic PWH receiving ART. Across two independent cohorts, HIV-positive females, but not males, displayed significantly higher anti-CD4 IgG, predominantly IgG1, compared with HIV-negative controls, without parallel increases in anti-CD4 IgA or IgM. This sex-specific pattern was unique to anti-CD4 IgG and was not observed for anti-CD8 IgG, anti-double-stranded DNA IgG, or anti-nuclear antigen IgG; these control autoantibodies correlated with one another but not with anti-CD4 IgG. Elevated anti-CD4 IgG levels were associated with lower plasma progesterone levels and reduced absolute CD4+ T-cell counts. Markers of microbial translocation, soluble CD14 (sCD14), lipopolysaccharide-binding protein (LBP), and lipopolysaccharide (LPS), were also selectively increased in HIV-positive females, with sCD14 and LBP showing significant or borderline associations with anti-CD4 IgG. Together, these findings identify anti-CD4 IgG as a sex-dimorphic autoimmune signature in treated HIV infection, linked to progesterone levels, persistent microbial translocation, and incomplete immune recovery. This work highlights an under-recognized intersection of sex, mucosal barrier dysfunction, and autoimmunity in HIV pathogenesis and suggests potential therapeutic targets to improve immune reconstitution in women.

pathology↗

bioRxiv2025

OPUS-ET: Resolving Compositional and Conformational Heterogeneities of Biomolecules in Cryo-Electron Tomography

Structural heterogeneity in biomolecules, arising from both compositional and conformational variability, limits resolution and interpretability of cryo-electron tomography (cryo-ET). Here, we present OPUS-ET, a deep learning framework that resolves multiscale heterogeneity throughout the cryo-ET workflow. OPUS-ET combines a composition decoder that captures compositional differences with a conformation decoder that models large-scale motions, thereby providing a hierarchical representation of structural heterogeneity. Starting from noisy template-matching candidates with templates of varying similarity or quality, OPUS-ET efficiently enriches target particle populations and delivers sub-nanometer in situ reconstructions in a single round. It leads to improved resolutions by up to 4.5 [A] over expert annotations or existing deep-learning approaches in four benchmark systems, and reveals continuous conformational landscapes capturing F-F flexible coupling in mitochondrial ATP synthase and tRNA-translocation intermediates in eukaryotic and bacterial ribosomes. Together, these results establish OPUS-ET as a powerful computational tool for linking particle purification, high-resolution reconstruction, and analysis of structural heterogeneity in cryo-ET, with demonstrated robustness to template quality, initial pose noise, and clustering parameters.

molecular biology↗

bioRxiv2025

Cannabis-enriched oral Actinomyces induces anxiety-like behavior via impairing mitochondria and GABA signaling

The human oral microbiome is increasingly recognized as a contributor to brain health, yet its mechanisms remain unclear. Our previous work revealed that oral Actinomyces species was enriched in chronic cannabis smokers. Here, we show oral inoculation of cannabis use-associated Actinomyces species, especially A. meyeri, to wild-type C57BL/6 mice leads to anxiety-like behaviors, non-region-specific microglia activation, mitochondrial dysfunction, and reduced GABAergic neurotransmission, without evidence of bacterial translocation to the brain, neuroinflammation, and memory decline. Notably, Actinomyces species-producing metabolites, i.e., arginine and argininosuccinate, were increased in both oral swabs and brain following inoculation in vivo. These Actinomyces species-producing metabolites induced mitochondrial dysfunction and oxidative stress in neurons in vitro, indicating a neuropathogenic role and aligning with reduced GABAergic neurotransmission in vivo. Together, these results suggest that oral cannabis-associated dysbiosis impacts behavior through mitochondrial stress and impaired inhibitory signaling, indicating the oral-brain metabolic axis is potentially consequential in neuropsychiatric disorders. TeaserChronic heavy cannabis use-enriched oral bacteria can drive anxiety and neuropathogenesis in mice. Highlights{whitebullet} Cannabis-associated oral Actinomyces enrichment induces anxiety-like behavior in mice {whitebullet}Microglial activation occurs without neuroinflammation (IL-1{beta}, TNF-, and IL-6) {whitebullet}Mitochondrial hyperactivation and reduced inhibitory GABAergic signaling Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=160 SRC="FIGDIR/small/689724v1_ufig1.gif" ALT="Figure 1"> View larger version (28K): org.highwire.dtl.DTLVardef@120b0b1org.highwire.dtl.DTLVardef@1304782org.highwire.dtl.DTLVardef@a6aa77org.highwire.dtl.DTLVardef@17d6d_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2025

Mineral guided molecular enrichment: An interfacial driving force for protocell emergence on early Earth

The emergence of protocells from a dilute prebiotic environment is a fundamental challenge in origins-of-life research. which requires the simultaneous overcoming of molecular dilution, the establishment of metabolic cycles and the formation of selectively permeable compartments. But where and how such critical conditions are satisfied is very obscure and debated. We demonstrate, using contemporary model proteins and enzymatic systems, that mineral surfaces can facilitate the co-adsorption and spatial arrangement of nucleotides, proteins, and lipids into locally enriched, protocell-like assemblies under the examined laboratory conditions. We showed that geochemically relevant minerals efficiently co-adsorb and colocalize diverse biomolecules, creating crowded interfacial microenvironments that support enzyme cascades with substrate channeling-like behavior. Subsequently, these mineral-protein complexes template the assembly of lipid membranes, leading to the formation of discrete compartments that maintain metabolic activity while permitting molecular exchange. This mineral-guided surface enrichment (MSE) mechanism integrates key aspects of "metabolism-first" and "membrane-first" scenarios into a unified pathway, reconciling long-standing conceptual divides in prebiotic chemistry. Our findings establish mineral interfaces as active organizers of protocell emergence, offering a geochemically plausible framework for the origin of cellular life.

evolutionary biology↗

bioRxiv2025

CARP Protects Against Doxorubicin-induced Cardiotoxicity through NRF1-driven Mitochondrial Homeostasis

AimsDoxorubicin (DOX), a highly effective anthracycline chemotherapeutic agent, is limited by its dose-dependent cardiotoxicity. This study investigates the cardioprotective mechanisms of cardiac adriamycin responsive protein (CARP) and its underlying mechanisms in DOX-induced cardiotoxicity (DIC). Methods and resultsCardiac-specific CARP transgenic and wild-type mice were subjected to a DIC model. Cardiac function was assessed via echocardiography, histopathology, and transmission electron microscopy (TEM). In vitro, DOX-treated cardiomyocytes overexpressing CARP were analyzed for oxidative stress (ROS levels), mitochondrial function (mtDNA copy number etc.), and mitochondrial-related proteins (Western blot). CARP-NRF1 interaction was validated by co-immunoprecipitation (Co-IP), and NRF1 siRNA knockdown was performed to assess CARPs role in mitochondrial homeostasis. CARP overexpression markedly alleviated DOX-induced cardiac dysfunction and mitochondrial damage, restoring mitochondrial dynamics and mitophagy. Mechanistically, CARP directly interacted with NRF1, and NRF1 knockdown ameliorated CARP-mediated cardioprotection in DIC. ConclusionCARP safeguards against DIC by maintaining mitochondrial homeostasis via NRF1 signaling, positioning it as a promising therapeutic target for DOX-induced cardiomyopathy.

molecular biology↗