Biology subjects

Deng, K.

Publications and source records attributed to Deng, K..

At least 19 recordsLinked to original sources

bioRxiv2026

Structural streamlining of axonemal doublet microtubules in Plasmodium male gametes

Male gametogenesis in malaria parasites produces up to eight flagellated gametes within approximately 15 min, requiring de novo construction of motile axonemes on an unusually short timescale. Here we combine cellular cryo-electron tomography, high-resolution cryo-EM, proteomics, and parasite genetics to define the molecular architecture and assembly states of the Plasmodium male gamete axoneme. The doublet microtubules retain the principal surface-associated motility modules but contain a markedly reduced luminal microtubule inner protein network. Their inner junction lacks PACRG and is instead organized by CFAP20 and CFAP52, whose combined loss disrupts doublet integrity and exflagellation. We further identify a calmodulin protein at the outer dynein arm docking region and show that outer dynein arms accumulate progressively during gametogenesis. These findings establish distinct form of axonemal remodeling in Plasmodium and reveal the ordered assembly of structural and motor modules during rapid male gamete formation.

cell biology↗

bioRxiv2026

PGM3 inhibition rewires RUVBL2-dependent DNA repair and induces a BRCAness-like state in pancreatic cancer cells

Pancreatic ductal adenocarcinoma (PDAC) exhibits profound metabolic rewiring and strong resistance to DNA-damaging therapies, yet how metabolic pathways regulate genome maintenance remains poorly understood. The hexosamine biosynthetic pathway (HBP) integrates nutrient availability with protein glycosylation through production of UDP-GlcNAc, but its role in DNA damage response (DDR) regulation is unclear. Here we show that inhibition of the HBP enzyme phosphoglucomutase-3 (PGM3) reduces DNA repair capacity in pancreatic cancer cells. Transcriptomic and functional analyses reveal that the selective PGM3 inhibitor FR054 amplifies gemcitabine-induced replication stress, disrupts ATR-CHK1 and ATM-CHK2 checkpoint signaling, and selectively impairs homologous recombination. Glycoproteomic profiling identifies the AAA+ ATPase RUVBL2 as a key metabolic-DDR node. Gemcitabine increases RUVBL2 O-GlcNAcylation, with Thr81 identified as a modified residue within the Walker A nucleotide-binding motif. Structural modelling predicts that Thr81 O-GlcNAcylation stabilizes the RUVBL1-RUVBL2 complex without compromising ATP-Mg engagement. PGM3 inhibition and Thr81 mutation similarly reduced ATR and ATM abundance and promoted persistent DNA damage, supporting a role for RUVBL2 Thr81 O-GlcNAcylation in sustaining checkpoint signalling and genome stability. Consequently, PGM3 inhibition induces a BRCAness-like state that sensitizes pancreatic cancer cells to PARP inhibition, both in vitro and in vivo, as well as to ionizing radiation. These findings reveal a nutrient-sensitive mechanism linking protein glycosylation to genome maintenance and identify HBP-dependent DNA repair as a potentially actionable vulnerability in pancreatic cancer.

cancer biology↗

bioRxiv2026

ATLAS: Population-Level Disease Locus Discovery via Differential Attention in Genomic Language Models

Identifying disease-associated genetic variants remains a key challenge in genomics, especially in small cohorts or for rare and complex mutation types where genome-wide association studies (GWAS) often fall short. We introduce ATLAS, a population-level framework that leverages attention signals from pretrained genomic language models (gLMs) to detect disease-associated genes and loci directly from raw sequences--without requiring explicit variant calls or supervised training. ATLAS first performs gene-level differential attention analysis to prioritize candidate genes, followed by base-level analysis to localize disease-associated regions at single-haplotype resolution. We validate ATLAS on synthetic and {beta}-thalassemia datasets, demonstrating robust performance across diverse allele frequencies (down to 10%), cohort sizes (below 200 individuals per group), and genomic scales. Compared to GWAS, ATLAS achieves higher recall of known loci and captures haplotype-specific signals missed by traditional methods. Cross-model benchmarking further shows that precise localization depends on both model size and pretraining on diverse human genomes. In summary, ATLAS offers a scalable, sequence-native alternative to traditional statistical genetics.

genetics↗

bioRxiv2026

The BELL-type homeobox transcription factor RLC3/OsBLH4 controls leaf rolling and drought tolerance via KNOX-BELL-lignin regulatory network in rice

O_LIModerate leaf rolling in rice is crucial for plant architecture and stress adaptation, but its molecular regulation remains unclear. We investigated the role of RLC3/OsBLH4, a BELL-type homeobox transcription factor, in controlling leaf rolling and drought tolerance, addressing gaps in lignin biosynthesis and cell wall development mechanisms. C_LIO_LIWe used gene map-based cloning (rlc3-1, rlc3-2), CRISPR/Cas9 knockout lines (rlc3-ko#11, rlc3-ko#12), and allelic complementation to validate RLC3s function. Additionally, we employed biochemical assays, gene expression analysis, and protein interaction studies to explore its regulatory network. C_LIO_LIRLC3 mutations impaired lignin biosynthesis and secondary cell wall formation, reducing bulliform cells area and causing midrib defects. These structural abnormalities accelerated water loss, leading to excessive leaf rolling and compromised drought tolerance. Mechanistically, RLC3 directly activates lignin synthesis genes (OsPAL5, OsCOMT5, OsCCR4, OsCAld5H1) and interacts with KNOX transcription factors (OSH1, OSH45, OSH71) to form a KNOX-BELL complex, further regulating lignin content and cell wall development. C_LIO_LIRLC3 orchestrates lignin deposition and secondary cell wall development to control leaf rolling, water transport, and drought tolerance. This study reveals a novel KNOX-BELL-lignin regulatory module governing leaf morphology and stress adaptation, offering targets for crop improvement under drought conditions. C_LI

plant biology↗

bioRxiv2025

GRASP: Gene-Relation Adaptive Soft Prompt for Universal Gene Network Inference

Gene networks (GNs) encode diverse molecular relationships and are central to interpreting cellular function and disease. The heterogeneity of interaction types has led to computational methods specialized for particular network contexts. Large language models (LLMs) offer a unified, language-based formulation of GN inference by leveraging biological knowledge from large-scale text corpora, yet their effectiveness remains sensitive to prompt design. Here, we introduce Gene-Relation Adaptive Soft Prompt (GRASP), a parameter-efficient and trainable framework that conditions inference on each gene pair through only three virtual tokens. Using factorized gene-specific and relation-aware components, GRASP learns to map each pairs biological context into compact soft prompts that combine pair-specific signals with shared interaction patterns. Across diverse GN inference tasks, GRASP consistently outperforms alternative prompting strategies. It also shows a stronger ability to recover unannotated interactions from synthetic negative sets, suggesting its capacity to identify biologically meaningful relationships beyond existing databases. Together, these results establish GRASP as a scalable and generalizable prompting framework for LLM-based GN inference.

bioinformatics↗

bioRxiv2025

TAFFISH: A lightweight, modular, and containerized workflow framework for reproducible bioinformatics analyses

SummaryBioinformatics analyses often rely on shell commands and small shell scripts whose executable context is difficult to preserve, inspect and reuse. TAFFISH addresses this gap by packaging command-line tool calls and lightweight shell flows as installable, versioned and inspectable executable units. Through a curated public Hub, TAFFISH indexes command interfaces, execution backends, platform constraints, release metadata and smoke-test/validation records. Together, these components provide a command-level reproducibility layer that works directly in ordinary shells and can also be invoked from existing workflow systems. Availability and ImplementationTAFFISH is implemented in Common Lisp and released under Apache-2.0. TAFFISH version 0.10.1, together with the source code, documentation and public Hub resources, is available at https://github.com/taffish/taffish, https://taffish.com, https://taffish.github.io and https://github.com/taffish/. The submitted software release, frozen Hub snapshot, test data, command logs, checksums and reproducibility package are archived at https://doi.org/10.5281/zenodo.21054185. The authors will maintain the software and public resources for at least two years after publication. ContactHao Lyu: hao.lyu@uestc.edu.cn; Hao Lin: hlin@uestc.edu.cn; Kejun Deng: dengkj@uestc.edu.cn Supplementary informationSupplementary data are available online.

bioinformatics↗

bioRxiv2025

Deepening imaging-based spatial proteomics at high spatial resolution through controlled tissue resizing and in-situ bottom-up mass spectrometry

Understanding the spatial organization of proteins in tissues is essential for elucidating biological function, but current proteomic imaging methods face limitations in resolution, sensitivity, and multiplexing capability. Here, we present IMPACT (Imaging Mass Spectrometry for Proteome Analysis on Compressed Tissue), a hydrogel-based workflow that integrates controlled vertical tissue compression following expansion to enhance protein detection while improving spatial resolution in mass spectrometry imaging (MSI). Through a 6-fold lateral expansion and 100-fold thickness reduction, analytes were concentrated at the surface to improve detection and enable analysis of thick specimen. Coupled with optimized in-gel digestion using hybrid enzymes, IMPACT increased protein identifications 3-fold compared to conventional MSI while maintaining spatial fidelity. We demonstrate IMPACTs utility in mapping low-abundance proteins and resolving fine anatomical structures. Orthogonal validation with immunofluorescence and integration with spatial transcriptomics further reveal protein-RNA distribution discrepancies, highlighting the need for direct proteomic imaging. IMPACT bridges critical gaps in spatial proteomics by enabling high-resolution, high-sensitivity, and multiplexed untargeted protein imaging, opening new avenues for tissue biology and biomarker discovery.

biophysics↗

bioRxiv2025

A lipid metabolism defect is an underlying contributor to Diamond Blackfan anemia syndrome

Analysis of neither Diamond Blackfan anemia syndrome (DBAS) cohorts nor animal models has revealed a potential mechanism for the variable anemia phenotype, a key feature of this disease. Here, we utilized an established Rpl5Skax23-Jus/+ murine DBAS model in order to study this dynamic erythropoiesis deficiency. These haploinsufficient mice exhibit variably penetrant craniofacial and cardiac defects mimicking the phenotypes of DBAS patients bearing RPL5 mutations. We additionally discovered that this specific heterozygous splicing mutation is pathogenic and leads to partial intron retention. By examining the transcriptome of fetal liver erythroid progenitors at E12.5, we demonstrate that the downregulation of erythroid differentiation pathways is consistent with the DBAS phenotype. We also identified dysregulated transcription of lipid metabolism genes with significant reduction in the abundance of Scd1 in a subset of E12.5 mutant embryos at risk for erythroid failure. SCD1, a key enzyme that converts saturated to monounsaturated fatty acids, has not been previously linked to erythropoiesis or DBAS. When anemia was induced in adult mice, pretreatment with an SCD1 inhibitor resulted in improved erythropoiesis. This analysis suggests a key role of lipid metabolism in the variable anemia penetrance in DBAS and highlights a previously unappreciated pathway that may serve as a potential target for drug development. Key PointsO_LIThe variable anemia in Rpl5Skax23-Jus/+mice is triggered by intrinsic/extrinsic stress C_LIO_LIRpl5 haploinsufficient murine and human erythroid progenitors exhibit a lipid metabolism signature with downregulation of Scd1/SCD. C_LI

developmental biology↗

bioRxiv2025

Obesity Increases Atherosclerosis Susceptibility via Inter-tissue miR-30e-SLC7A11 Axis

BackgroundWith obesity as a risk factor for atherosclerotic disease, recent research suggests that adipose tissue in obese animal models and humans can generate endocrine-like molecules that affect arterial health later on. Previous studies showed that microRNA-30e (miR-30e) level is elevated in atherosclerosis and solute carrier family 7 member 11 (SLC7A11), a cystine/glutamate transporter, is involved in atherogenesis. However, whether an endocrine-like link between the adipose-derived miR-30e-5p and SLC7A11 in the vascular endothelium can lead to obesity-caused atherosclerosis is unknown. MethodsMiRNA data mining and RT-PCR validations were used to demonstrate the positive association among serum level of miR-30e-5p, obesity, and coronary arterial disease in human patients. Transcriptomics (RNA-seq and single-nucleus RNA-seq), metabolomics, and in silico analysis were used to establish a miR-30e-5p-SLC7A11 regulation of central carbon metabolism, mitochondrial and endothelial cell (EC) function. Mouse models with EC-specific Slc7a11 knockout (EC-Slc7a11-/-) and gain or loss of function of miR-30e-5p were used to elucidate the detrimental role of this endocrine-like axis in obesity-related atherosclerosis. ResultsThe level of adipocyte-derived miR-30e-5p was significantly upregulated in obese humans with coronary artery disease and obese and atherosclerotic mice. Via serum exosomes, the adipocyte-generated miR-30e-5p targeted SLC7A11 mRNA in vascular ECs. SLC7A11 deficiency due to miR-30e-5p targeting dysregulated glutamate/cystine metabolism increased glycolysis, reduced oxidative phosphorylation, and impaired mitochondrial function. The EC dysfunction could be rectified by SLC7A11 overexpression or miR-30e-5p antagonism. Exogenously delivered miR-30e-5p phenocopied the increased atherosclerosis in EC-Slc7a11-/- mice. In contrast, miR-30e-5p antagomir treatment reduced atherosclerosis in Apoe-/- and ob/ob mice. ConclusionOur multi-omics approaches demonstrates that the adipose-derived miR-30e-5p downregulated SLC7A11 mRNA in ECs via tissue crosstalk. The resulting EC dysfunction led to obesity-related atherosclerosis in mice. These findings underscore a causality between obesity and atherosclerosis in the context of cardiovascular-kidney-metabolic syndrome.

molecular biology↗

bioRxiv2024

Novel derivatives of BCV and (S)-HPMPA inhibit orthopoxviruses and human adenoviruses more potently than BCV

BCV and tecovirimat are the only two chemical drugs that have been approved to treat smallpox and can be requested for Mpox treatment through a single-patient Emergency Investigational New Drug (EIND) application. Disappointedly, the efficacy of tecovirimat manifested in a recent clinical trial is far from being satisfactory, while the clinical efficacy of BCV is still inconclusive. Given that MPXV, variola and other emerging orthopoxviruses are posing serious threats to global health, it is urgent to develop better therapeutics. In this study, we tested the antiviral effects of three novel prodrugs, which were designed based on previously reported parent drugs, either (S)-HPMPC (cidofovir) or (S)-HPMPA. We found that one of the (S)-HPMPA-based prodrugs, ODE-(S)-HPMPA formate, exhibited significantly better anti-orthopoxvirus activity than BCV both in vitro and in vivo, which also inhibited human adenovirus type 2 and type 21 more efficiently than BCV. Most strikingly, the EC50 and EC90 of ODE-(S)-HPMPA formate against MPXV were more than 40-fold lower than those of BCV. In contrast, we observed that the anti-HSV-1 activities of the (S)-HPMPA-based prodrugs were less effective than those of the cidofovir-based prodrugs (BCV and BCV formate), especially in vivo. Moreover, we showed for the first time that cytidine and adenine analog combined therapies could provide mice with complete protection against lethal challenges of both vaccinia and HSV-1. Collectively, we propose that both the ODE-(S)-HPMPA formate and the BCV/ODE-(S)-HPMPA formate combination are worth further investigations for their potential clinical applications.

microbiology↗

bioRxiv2024

PRISM: Multiplexed Profiling of RNA In-Situ through Single-round of Imaging in Three-Dimensional Tissue

Spatial RNA imaging has not been widely adopted because conventional fluorescence microscopy is limited to only a few channels, and the cyclic reactions needed to increase multiplexing in techniques such as sequential fluorescence in-situ hybridization (FISH) require sophisticated instrumentation. Here, we introduce Profiling of RNA In-situ through Single-round iMaging (PRISM), a method that expands coding capacity through color intensity grading. Using a radius vector filtering strategy to ensure the distinguishability of codewords in color space, PRISM achieves up to 64-plex color-barcoded RNA imaging in a single imaging round with conventional microscopes. We validate PRISMs versatility across various tissues by generating a 3D atlas of mouse embryonic development from E12.5 to E14.5, a quasi-3D tumor-normal transition landscape of human hepatocellular carcinoma (HCC), and a 3D cell atlas and subcellular RNA localization landscapes of mouse brain. Additionally, we show the critical role of cancer-associated fibroblasts (CAFs) in mediating immune infiltration and immune response heterogeneity within and between tumor microenvironments.

bioengineering↗

bioRxiv2024

An Engineered IGF2 Mutant for Lysosomal Targeting Chimeras Development and Membrane Proteins Degradation

Lysosome-targeting chimeras (LYTACs) have emerged as a promising strategy for targeted degradation of membrane proteins, offering potential applications in drug development. Currently, two main methods for developing LYTACs exist: chemically modified antibodies [1-2] and wild-type insulin-like growth factor 2 (IGF2) fusion proteins (iLYTACs) [3]. However, the fusion of the IGF2 arm within iLYTACs carries the risk of activating IGF1R tyrosine kinase activity and promoting tumor development. To address this concern, we introduce eiLYTACs, a technology that employs engineered IGF2 fusion antibodies to induce degradation of endogenous membrane proteins. Compared to the wild-type IGF2, the engineered IGF2 mutant exhibited minimal binding affinity for IGF1R but demonstrated a significant 100-fold increase in its binding affinity for IGF2R. In contrast to wild-type IGF2, which promotes tumor growth, the cells incubated with the engineered IGF2 showed no stimulation of tumor growth. The eiLYTACs strategy effectively inhibits tumor cell proliferation by degrading specific targets, resulting in a significant reduction in xenograft tumor size in experimental nude mice. More interestingly, our research revealed that eiLYTACs simultaneously degrade both homo- and heterodimers of disease-relevant proteins,which offer a promising strategy to address the activation of compensatory bypass signaling pathways, drug resistance, and tumor heterogeneity.

biochemistry↗

bioRxiv2023

HCCDB v2.0: Decompose the Expression Variations by Single-cell RNA-seq and Spatial Transcriptomics in HCC

Large-scale transcriptomic data are crucial for understanding the molecular features of hepatocellular carcinoma (HCC). By integrating 15 transcriptomic datasets of HCC clinical samples, the first version of HCCDB was released in 2018. The meta-analysis of differentially expressed genes and prognosis-related genes across multiple datasets provides a systematic view of the altered biological processes and the inter-patient heterogeneities of HCC with high reproducibility and robustness. After four years, the database needs to integrate recently published datasets. Furthermore, the latest single-cell and spatial transcriptomics provided a great opportunity to decipher the complex gene expression variations at the cellular level with spatial architecture. Here, we present HCCDB v2.0, an updated version that combines bulk, single-cell, and spatial transcriptomic data of HCC clinical samples. It dramatically expands the bulk sample size, adding 1656 new samples of 11 datasets to the existing 3917 samples, thereby enhancing the reliability of transcriptomic meta-analysis. A total of 182,832 cells and 69,352 spatial spots are added to the single-cell and spatial transcriptomics sections, respectively. A novel single-cell level and 2-dimension (sc-2D) metric was proposed to summarize the cell type-specific and dysregulated gene expression patterns. Results are all graphically visualized in our online portal, allowing users to easily retrieve data through a user-friendly interface and navigate between different views. With extensive clinical phenotypes and transcriptomic data in the database, we show two applications for identifying prognosis-associated cells and tumor microenvironment. HCCDB v2.0 is available at http://lifeome.net/database/hccdb2.

cancer biology↗

bioRxiv2022

motifNet: Functional motif interactions discovered in mRNA sequences with implicit neural representation learning

We present a new approach for predicting functional sequence patterns in mRNA, known as motifs. These motifs play an important role in understanding the mechanisms of the cell life cycle in clinical research and drug discovery. However, many existing neural network models for mRNA event prediction only take the sequence as input, and do not consider the positional information of the sequence. In contrast, motifNet is a lightweight neural network that uses both the sequence and its positional information as input. This allows for the implicit neural representation of the various motif interaction patterns in human mRNA sequences. The model can then be used to interactively generate motif patterns and the positional effect score in mRNA activities. Additionally, motifNet can identify violations of motif patterns in real human mRNA variants that are associated with disease-related cell dysfunction.

bioinformatics↗

bioRxiv2022

Dynamic changes in the transcriptome of oocytes during adolescent-onset PCOS in mice

(1) Background: This study aimed to explore temporal changes in the transcriptome of oocytes in an adolescent-onset polycystic ovarian syndrome (PCOS) mouse model. (2) Methods: An adolescent-onset PCOS mouse model was established using DHEA. Genes with a similar expression trend over time were identified using trend analysis. KEGG pathway enrichment analysis and gene regulatory network diagrams were examined for signaling pathways to identify potential hub genes related to the pathogenesis of PCOS. (3) Results: Four main trends of gene expression were extracted, of which six combinations of Venn diagrams were generated. Differentially expressed genes were mainly enriched in oxidative phosphorylation, cell cycle, P53 signaling pathway. Cell cycle-related genes (Skp1, Ccnb1, Orc1 and 5, Wee2, Mapk3, Cdc20) were abnormally down-regulated in the DHEA group. Ptges3 was the top1 DEGs at the initial stage of PCOS modeling. (4) Conclusion: This study provides a novel insight into the altered transcriptome of oocytes from PCOS mice. mtDNA-related genes and Cell cycle-related genes play the most important role in the development of PCOS. Ptges3 was the one of the top DEGs which was up-regulated in DHEA group at the initial stage of modeling, which suggested it may play an important role in the early stage of PCOS.

genetics↗

bioRxiv2022

Metabolic traits and the niche of bulk soil bacteria in a Mediterranean grassland

Soil microorganisms have adapted to compete and exploit different metabolic niches in their physically and chemically diverse environment via evolution and acquisition of distinct physiological and biochemical traits. As the interface for most carbon and nutrient exchange between plants and microorganisms, the rhizosphere has received substantial attention. By comparison, what is commonly termed bulk-soil (soil free of living roots) represents a far greater volume and surface area throughout the season, and substantially higher taxonomic and phylogenetic diversity; the traits and activity of its inhabitants may also have a significant impact on overall soil function. We used a combination of comparative genomics and exoproteomics to identify metabolic traits of bacteria adapted to life in bulk soil and compared these with traits of bacteria living in the rhizosphere of wild oat, Avena barbata. In bulk soil bacteria, we observed: (i) greater investment in extracellular polymer-degrading enzyme production; (ii) greater potential for secretion (presence of signal peptides) of polymer-degrading enzymes; (iii) production of accessory proteins (carbohydrate binding modules) fused with glycoside hydrolases that enhance substrate affinity, stabilize, and increase reaction rates of polymer degrading enzymes; and (iv) organization of polymer degradation machinery within gene clusters that facilitate co-transcription of enzymes, transcription factors and transporters for polymer depolymerization products. Together, these findings suggest that unlike rhizosphere-adapted bacteria--which specialize on small molecules released primarily as root exudates--bulk soil-adapted bacteria have evolved to exploit plant polymers. This biochemically costly strategy may be mitigated by protein-level adaptations that enhance the efficiency of extracellular enzyme-mediated substrate acquisition. IMPORTANCEPlant-soil-microbe interactions are dynamic and complex, with significant implications for ecosystem functioning. Microbial traits, such as nutrient acquisition and growth yield, combined with soil and climate parameters, impact major biogeochemical processes and can define the future fate of soil carbon. Diverse soil microorganisms occupy different physical habitats within soil and exploit distinct niches by expressing different metabolic traits. Identifying and quantifying traits that underlie their fitness and function is key for understanding and predicting how soil carbon transformation and stabilization will change in the future or can be managed through intervention.

microbiology↗

bioRxiv2022

Multimodal single cell data integration challenge: results and lessons learned

Biology has become a data-intensive science. Recent technological advances in single-cell genomics have enabled the measurement of multiple facets of cellular state, producing datasets with millions of single-cell observations. While these data hold great promise for understanding molecular mechanisms in health and disease, analysis challenges arising from sparsity, technical and biological variability, and high dimensionality of the data hinder the derivation of such mechanistic insights. To promote the innovation of algorithms for analysis of multimodal single-cell data, we organized a competition at NeurIPS 2021 applying the Common Task Framework to multimodal single-cell data integration. For this competition we generated the first multimodal benchmarking dataset for single-cell biology and defined three tasks in this domain: prediction of missing modalities, aligning modalities, and learning a joint representation across modalities. We further specified evaluation metrics and developed a cloud-based algorithm evaluation pipeline. Using this setup, 280 competitors submitted over 2600 proposed solutions within a 3 month period, showcasing substantial innovation especially in the modality alignment task. Here, we present the results, describe trends of well performing approaches, and discuss challenges associated with running the competition.

bioinformatics↗

bioRxiv2022

Ascorbic acid derived carbon dots promote circadian rhythm and contribute to attention deficit hyperactivity disorder

Attention deficit hyperactivity disorder (ADHD) is one of the most prevalent psychiatric disorders in children, and ADHD patients always display circadian abnormalities. While, the ADHD drugs currently used in clinic have strong side effects, such as psychosis, allergic reactions and heart problems. Here, we demonstrated carbon dots derived from the ascorbic acid (VCDs) could strongly rescue the hyperactive and impulsive behaviour of a zebrafish ADHD disease model caused by per1b mutation. VCDs prolonged the circadian period of zebrafish for more than half an hour. In addition, the amplitude and circadian phase were also changed. The dopamine level was specifically increased, which may be caused by stimulation of the dopaminergic neuron development in the midbrain. Notably, it was found that the serotonin level was not altered by VCDs treatments. Also, the gene transcriptome effects of VCDs were discussed in present work. Our results provided the dynamic interactions of carbon dots with circadian system and dopamine signaling pathway, which illustrates a potential application of degradable and bio-safe VCDs for the treatment of the attention deficient and hyperactive disorder through circadian intervention. Brief summary O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=138 SRC="FIGDIR/small/482578v1_ufig1.gif" ALT="Figure 1"> View larger version (32K): org.highwire.dtl.DTLVardef@198eeforg.highwire.dtl.DTLVardef@1f714f7org.highwire.dtl.DTLVardef@819d8eorg.highwire.dtl.DTLVardef@18ef9cb_HPS_FORMAT_FIGEXP M_FIG C_FIG

animal behavior and cognition↗