CHIP inhibits odontoblast differentiation through promoting DLX3 polyubiquitylation and degradation.

Dentin is the major hard tissue of teeth formed by differentiated odontoblasts. How odontoblast differentiation is regulated remains enigmatic. Here, we report that the E3 ubiquitin ligase CHIP is highly expressed in undifferentiated dental mesenchymal cells and downregulated after differentiation of odontoblasts. Ectopic expression of CHIP inhibits odontoblastic differentiation of mouse dental papilla cells, whereas knockdown of endogenous CHIP has opposite effects. Chip (Stub1) knockout mice display increased formation of dentin and enhanced expression of odontoblast differentiation markers. Mechanistically, CHIP interacts with and induces K63 polyubiquitylation of the transcription factor DLX3, leading to its proteasomal degradation. Knockdown of DLX3 reverses the enhanced odontoblastic differentiation caused by knockdown of CHIP. These results suggest that CHIP inhibits odontoblast differentiation by targeting its tooth-specific substrate DLX3. Furthermore, our results indicate that CHIP competes with another E3 ubiquitin ligase, MDM2, that promotes odontoblast differentiation by monoubiquitylating DLX3. Our findings suggest that the two E3 ubiquitin ligases CHIP and MDM2 reciprocally regulate DLX3 activity by catalyzing distinct types of ubiquitylation, and reveal an important mechanism by which differentiation of odontoblasts is delicately regulated by divergent post-translational modifications.

DeepKEGG: a multi-omics data integration framework with biological insights for cancer recurrence prediction and biomarker discovery.

Deep learning-based multi-omics data integration methods have the capability to reveal the mechanisms of cancer development, discover cancer biomarkers and identify pathogenic targets. However, current methods ignore the potential correlations between samples in integrating multi-omics data. In addition, providing accurate biological explanations still poses significant challenges due to the complexity of deep learning models. Therefore, there is an urgent need for a deep learning-based multi-omics integration method to explore the potential correlations between samples and provide model interpretability. Herein, we propose a novel interpretable multi-omics data integration method (DeepKEGG) for cancer recurrence prediction and biomarker discovery. In DeepKEGG, a biological hierarchical module is designed for local connections of neuron nodes and model interpretability based on the biological relationship between genes/miRNAs and pathways. In addition, a pathway self-attention module is constructed to explore the correlation between different samples and generate the potential pathway feature representation for enhancing the prediction performance of the model. Lastly, an attribution-based feature importance calculation method is utilized to discover biomarkers related to cancer recurrence and provide a biological interpretation of the model. Experimental results demonstrate that DeepKEGG outperforms other state-of-the-art methods in 5-fold cross validation. Furthermore, case studies also indicate that DeepKEGG serves as an effective tool for biomarker discovery. The code is available at https://github.com/lanbiolab/DeepKEGG.

Single-cell transcriptomic signatures and gene regulatory networks modulated by Wls in mammalian midline facial formation and clefts.

Formation of highly unique and complex facial structures is controlled by genetic programs that are responsible for the precise coordination of three-dimensional tissue morphogenesis. However, the underlying mechanisms governing these processes remain poorly understood. We combined mouse genetic and genomic approaches to define the mechanisms underlying normal and defective midfacial morphogenesis. Conditional inactivation of the Wnt secretion protein Wls in Pax3-expressing lineage cells disrupted frontonasal primordial patterning, cell survival and directional outgrowth, resulting in altered facial structures, including midfacial hypoplasia and midline facial clefts. Single-cell RNA sequencing revealed unique transcriptomic atlases of mesenchymal subpopulations in the midfacial primordia, which are disrupted in the conditional Wls mutants. Differentially expressed genes and cis-regulatory sequence analyses uncovered that Wls modulates and integrates a core gene regulatory network, consisting of key midfacial regulatory transcription factors (including Msx1, Pax3 and Pax7) and their downstream targets (including Wnt, Shh, Tgfß and retinoic acid signaling components), in a mesenchymal subpopulation of the medial nasal prominences that is responsible for midline facial formation and fusion. These results reveal fundamental mechanisms underlying mammalian midfacial morphogenesis and related defects at single-cell resolution.

Benchmarking of computational methods for predicting circRNA-disease associations.

Accumulating evidences demonstrate that circular RNA (circRNA) plays an important role in human diseases. Identification of circRNA-disease associations can help for the diagnosis of human diseases, while the traditional method based on biological experiments is time-consuming. In order to address the limitation, a series of computational methods have been proposed in recent years. However, few works have summarized these methods or compared the performance of them. In this paper, we divided the existing methods into three categories: information propagation, traditional machine learning and deep learning. Then, the baseline methods in each category are introduced in detail. Further, 5 different datasets are collected, and 14 representative methods of each category are selected and compared in the 5-fold, 10-fold cross-validation and the de novo experiment. In order to further evaluate the effectiveness of these methods, six common cancers are selected to compare the number of correctly identified circRNA-disease associations in the top-10, top-20, top-50, top-100 and top-200. In addition, according to the results, the observation about the robustness and the character of these methods are concluded. Finally, the future directions and challenges are discussed.

Downregulated BMP-Smad1/5/8 signaling causes emphysema via dysfunction of alveolar type II epithelial cells.

Bone morphogenetic protein (BMP)-Smad1/5/8 signaling plays a crucial regulatory role in lung development and adult lung homeostasis. However, it remains elusive whether BMP-Smad1/5/8 signaling is involved in the pathogenesis of emphysema. In this study, we downregulated BMP-Smad1/5/8 signaling by overexpressing its antagonist Noggin in adult mouse alveolar type II epithelial cells (AT2s), resulting in an emphysematous phenotype mimicking the typical pathological features of human emphysema, including distal airspace enlargement, pulmonary inflammation, extracellular matrix remodeling, and impaired lung function. Dysregulation of BMP-Smad1/5/8 signaling in AT2s leads to inflammatory destruction dominated by macrophage infiltration, associated with reduced secretion of surfactant proteins and inhibition of AT2 proliferation and differentiation. Reactivation of BMP-Smad1/5/8 signaling by genetics or chemotherapy significantly attenuated the morphology and pathophysiology of emphysema and improved the lung function in Noggin-overexpressing lungs. We also found that BMP-Smad1/5/8 signaling was downregulated in cigarette smoke-induced emphysema, and that enhancing its activity in AT2s prevented or even reversed emphysema in the mouse model. Our data suggest that BMP-Smad1/5/8 signaling, located at the top of the signaling cascade that regulates lung homeostasis, represents a key molecular regulator of alveolar stem cell secretory and regenerative function, and could serve as a potential target for future prevention and treatment of pulmonary emphysema. © 2023 The Pathological Society of Great Britain and Ireland.

MRUNet-3D: A multi-stride residual 3D UNet for lung nodule segmentation.

Obtaining an accurate segmentation of the pulmonary nodules in computed tomography (CT) images is challenging. This is due to: (1) the heterogeneous nature of the lung nodules; (2) comparable visual characteristics between the nodules and their surroundings. A robust multi-scale feature extraction mechanism that can effectively obtain multi-scale representations at a granular level can improve segmentation accuracy. As the most commonly used network in lung nodule segmentation, UNet, its variants, and other image segmentation methods lack this robust feature extraction mechanism. In this study, we propose a multi-stride residual 3D UNet (MRUNet-3D) to improve the segmentation accuracy of lung nodules in CT images. It incorporates a multi-slide Res2Net block (MSR), which replaces the simple sequence of convolution layers in each encoder stage to effectively extract multi-scale features at a granular level from different receptive fields and resolutions while conserving the strengths of 3D UNet. The proposed method has been extensively evaluated on the publicly available LUNA16 dataset. Experimental results show that it achieves competitive segmentation performance with an average dice similarity coefficient of 83.47 % and an average surface distance of 0.35 mm on the dataset. More notably, our method has proven to be robust to the heterogeneity of lung nodules. It has also proven to perform better at segmenting small lung nodules. Ablation studies have shown that the proposed MSR and RFIA modules are fundamental to improving the performance of the proposed model.

A high-resolution haplotype-resolved Reference panel constructed from the China Kadoorie Biobank Study.

Precision medicine depends on high-accuracy individual-level genotype data. However, the whole-genome sequencing (WGS) is still not suitable for gigantic studies due to budget constraints. It is particularly important to construct highly accurate haplotype reference panel for genotype imputation. In this study, we used 10 000 samples with medium-depth WGS to construct a reference panel that we named the CKB reference panel. By imputing microarray datasets, it showed that the CKB panel outperformed compared panels in terms of both the number of well-imputed variants and imputation accuracy. In addition, we have completed the imputation of 100 706 microarrays with the CKB panel, and the after-imputed data is the hitherto largest whole genome data of the Chinese population. Furthermore, in the GWAS analysis of real phenotype height, the number of tested SNPs tripled and the number of significant SNPs doubled after imputation. Finally, we developed an online server for offering free genotype imputation service based on the CKB reference panel (https://db.cngb.org/imputation/). We believe that the CKB panel is of great value for imputing microarray or low-coverage genotype data of Chinese population, and potentially mixed populations. The imputation-completed 100 706 microarray data are enormous and precious resources of population genetic studies for complex traits and diseases.

Development and evaluation of a polygenic risk score for lung cancer in never-smoking women: A large-scale prospective Chinese cohort study.

The proportion of lung cancer in never smokers is rising, especially among Asian women, but there is no effective early detection tool. Here, we developed a polygenic risk score (PRS), which may help to identify the population with higher risk of lung cancer in never-smoking women. We first performed a large GWAS meta-analysis (8595 cases and 8275 controls) to systematically identify the susceptibility loci for lung cancer in never-smoking Asian women and then generated a PRS using GWAS datasets. Furthermore, we evaluated the utility and effectiveness of PRS in an independent Chinese prospective cohort comprising 55 266 individuals. The GWAS meta-analysis identified eight known loci and a novel locus (5q11.2) at the genome-wide statistical significance level of P < 5 × 10-8 . Based on the summary statistics of GWAS, we derived a polygenic risk score including 21 variants (PRS-21) for lung cancer in never-smoking women. Furthermore, PRS-21 had a hazard ratio (HR) per SD of 1.29 (95% CI = 1.18-1.41) in the prospective cohort. Compared with participants who had a low genetic risk, those with an intermediate (HR = 1.32, 95% CI: 1.00-1.72) and high (HR = 2.09, 95% CI: 1.56-2.80) genetic risk had a significantly higher risk of incident lung cancer. The addition of PRS-21 to the conventional risk model yielded a modest significant improvement in AUC (0.697 to 0.711) and net reclassification improvement (24.2%). The GWAS-derived PRS-21 significantly improves the risk stratification and prediction accuracy for incident lung cancer in never-smoking Asian women, demonstrating the potential for identification of high-risk individuals and early screening.

Infectious pathogens and risk of esophageal, gastric and duodenal cancers and ulcers in China: A case-cohort study.

Infection by certain pathogens is associated with cancer development. We conducted a case-cohort study of ~2500 incident cases of esophageal, gastric and duodenal cancer, and gastric and duodenal ulcer and a randomly selected subcohort of ~2000 individuals within the China Kadoorie Biobank study of >0.5 million adults. We used a bead-based multiplex serology assay to measure antibodies against 19 pathogens (total 43 antigens) in baseline plasma samples. Associations between pathogens and antigen-specific antibodies with risks of site-specific cancers and ulcers were assessed using Cox regression fitted using the Prentice pseudo-partial likelihood. Seroprevalence varied for different pathogens, from 0.7% for Hepatitis C virus (HCV) to 99.8% for Epstein-Barr virus (EBV) in the subcohort. Compared to participants seronegative for the corresponding pathogen, Helicobacter pylori seropositivity was associated with a higher risk of non-cardia (adjusted hazard ratio [HR] 2.73 [95% CI: 2.09-3.58]) and cardia (1.67 [1.18-2.38]) gastric cancer and duodenal ulcer (2.71 [1.79-4.08]). HCV was associated with a higher risk of duodenal cancer (6.23 [1.52-25.62]) and Hepatitis B virus was associated with higher risk of duodenal ulcer (1.46 [1.04-2.05]). There were some associations of antibodies again some herpesviruses and human papillomaviruses with risks of gastrointestinal cancers and ulcers but these should be interpreted with caution. This first study of multiple pathogens with risk of gastrointestinal cancers and ulcers demonstrated that several pathogens are associated with risks of gastrointestinal cancers and ulcers. This will inform future investigations into the role of infection in the etiology of these diseases.

Associations of diabetes, circulating protein biomarkers, and risk of pancreatic cancer.

BACKGROUND: Type 2 diabetes (T2D) is associated with higher risk of pancreatic cancer (PC), but the underlying mechanisms are not fully understood. METHODS: We conducted a case-subcohort study involving 610 PC cases and 623 subcohort participants with 92 protein biomarkers measured in baseline plasma samples. Genetically-instrumented T2D was derived using 86 single-nucleotide polymorphisms (SNPs), including insulin resistance (IR) SNPs. RESULTS: In observational analyses of 623 subcohort participants (mean age, 52 years; 61% women), T2D was positively associated with 13 proteins (SD difference: IL6: 0.52 [0.23-0.81]; IL10: 0.41 [0.12-0.70]), of which 8 were nominally associated with incident PC. The 8 proteins potentially mediated 36.9% (18.7-75.0%) of the association between T2D and PC. In MR, no associations were observed for genetically-determined T2D with proteins, but there were positive associations of genetically-determined IR with IL6 and IL10 (SD difference: 1.23 [0.05-2.41] and 1.28 [0.31-2.24]). In two-sample MR, fasting insulin was associated with both IL6 and PC, but no association was observed between IL6 and PC. CONCLUSIONS: Proteomics were likely to explain the association between T2D and PC, but were not causal mediators. Elevated fasting insulin driven by insulin resistance might explain the associations of T2D, proteomics, and PC.

Long-Term Exposure to Fine Particulate Matter and Incidence of Esophageal Cancer: A Prospective Study of 0.5 Million Chinese Adults.

BACKGROUND & AIMS: Evidence is sparse and inconclusive on the association between long-term fine (≤2.5 µm) particulate matter (PM2.5) exposure and esophageal cancer. We aimed to assess the association of PM2.5 with esophageal cancer risk and compared the esophageal cancer risk attributable to PM2.5 exposure and other established risk factors. METHODS: This study included 510,125 participants without esophageal cancer at baseline from China Kadoorie Biobank. A high-resolution (1 × 1 km) satellite-based model was used to estimate PM2.5 exposure during the study period. Hazard ratios (HR) and 95% CIs of PM2.5 with esophageal cancer incidence were estimated using Cox proportional hazard model. Population attributable fractions for PM2.5 and other established risk factors were estimated. RESULTS: There was a linear concentration-response relationship between long-term PM2.5 exposure and esophageal cancer. For each 10-µg/m3 increase in PM2.5, the HR was 1.16 (95% CI, 1.04-1.30) for esophageal cancer incidence. Compared with the first quarter of PM2.5 exposure, participants in the highest quarter had a 1.32-fold higher risk for esophageal cancer, with an HR of 1.32 (95% CI, 1.01-1.72). The population attributable risk because of annual average PM2.5 concentration ≥35 µg/m3 was 23.3% (95% CI, 6.6%-40.0%), higher than the risks attributable to lifestyle risk factors. CONCLUSIONS: This large prospective cohort study of Chinese adults found that long-term exposure to PM2.5 was associated with an elevated risk of esophageal cancer. With stringent air pollution mitigation measures in China, a large reduction in the esophageal cancer disease burden can be expected.

A Novel Multiarmed Bifunctional PEG Derivative for the Preparation of Mass Spectrometry Ion Sources with Antifouling Property and High Selectivity.

It is challenging to prepare a highly selective mass spectrometry (MS) ion source for the rapid and highly sensitive detection of analytes, especially mycotoxins. In this study, an amino and tetrazine bifunctionalized multiarm PEG derivative (NH2HCl-4armPEG10K-(MTz)3), which can be easily immobilized on the substrate by the addition reaction between amino and polydopamine, was used for the preparation of MS ionization substrate. NH2HCl-4armPEG10K-(MTz)3 can also be used as a linker to immobilize sufficient streptavidin (SA) on the surface of the substrate by a click reaction. The process further promotes the immobilization of broad-spectrum antibodies (3D4), which were used as the recognition element for ZEN and its metabolites. The prepared SSS-Au-PDA-4armPEG10K-SA-3D4 not only can rapidly enrich ZEN and its metabolites with high selectivity but also shows good antifouling properties in the matrix. After simple sample preparation, the prepared SSS-Au-PDA-4armPEG10K-SA-3D4 can be directly coupled with MS to achieve high sensitivity (LODs: 0.18-0.66 ng/mL, LOQs: 0.5-1.0 ng/mL) and selective detection of ZEN and its metabolites in the matrix. At the same time, satisfactory recoveries (83.60-97.80%) and precision (RSD: 2.80-9.10%) can also be obtained. The prepared SSS-Au-PDA-4armPEG10K-SA-3D4 is expected to provide a powerful tool for the rapid and highly sensitive determination of multiple targets by MS.

Mesophilic Argonaute-Mediated Polydisperse Droplet Biosensor for Amplification-Free, One-Pot, and Multiplexed Nucleic Acid Detection Using Deep Learning.

Detection of nucleic acids from a single multiplexed and amplification-free test is critical for ensuring food safety, clinical diagnostics, and environmental monitoring. In this study, we introduced a mesophilic Argonaute protein from Clostridium butyricum (CbAgo), which exhibits nucleic acid endonuclease activity, to achieve a programmable, amplification-free system (PASS) for rapid nucleic acid quantification at ambient temperatures in one pot. By using CbAgo-mediated binding with specific guide DNA (gDNA) and subsequent targeted cleavage of wild-type target DNAs complementary to gDNA, PASS can detect multiple foodborne pathogen DNA (<102 CFU/mL) simultaneously. The fluorescence signals were then transferred to polydisperse emulsions and analyzed by using deep learning. This simplifies the process and increases the suitability of polydisperse emulsions compared to traditional digital PCR, which requires homogeneous droplets for accurate detection. We believe that PASS has the potential to become a next-generation point-of-care digital nucleic acid detection method.

Dual-Track Multifunctional Bimetallic Metal-Organic Frameworks for Antibiotic Enrichment and Detection.

The improper use and overuse of antibiotics have led to significant burdens and detrimental effects on the environment, food supply, and human health. Herein, a magnetic solid-phase extraction program and an optical immunosensor based on bimetallic Ce/Zr-UiO 66 for the detection of antibiotics are developed. A magnetic Fe3O4@SiO2@Ce/Zr-UiO 66 metal-organic framework (MOF) is prepared to extract and enrich chloramphenicol from fish, wastewater, and urine samples, and a horseradish peroxidase (HRP)-Ce/Zr-UiO 66@bovine serum protein-chloramphenicol probe is used for the sensitive detection of chloramphenicol based on the dual-effect catalysis of Ce and HRP. In this manner, the application of Ce/Zr-UiO 66 in integrating sample pretreatment and antibiotic detection is systematically investigated and the associated mechanisms are explored. It is concluded that Ce/Zr-UiO 66 is a versatile dual-track material exhibiting high enrichment efficiency (6.37 mg g-1) and high sensitivity (limit of detection of 51.3 pg mL-1) for chloramphenicol detection and serving as a multifunctional MOF for safeguarding public health and hygiene.

KGANCDA: predicting circRNA-disease associations based on knowledge graph attention network.

Increasing evidences have proved that circRNA plays a significant role in the development of many diseases. In addition, many researches have shown that circRNA can be considered as the potential biomarker for clinical diagnosis and treatment of disease. Some computational methods have been proposed to predict circRNA-disease associations. However, the performance of these methods is limited as the sparsity of low-order interaction information. In this paper, we propose a new computational method (KGANCDA) to predict circRNA-disease associations based on knowledge graph attention network. The circRNA-disease knowledge graphs are constructed by collecting multiple relationship data among circRNA, disease, miRNA and lncRNA. Then, the knowledge graph attention network is designed to obtain embeddings of each entity by distinguishing the importance of information from neighbors. Besides the low-order neighbor information, it can also capture high-order neighbor information from multisource associations, which alleviates the problem of data sparsity. Finally, the multilayer perceptron is applied to predict the affinity score of circRNA-disease associations based on the embeddings of circRNA and disease. The experiment results show that KGANCDA outperforms than other state-of-the-art methods in 5-fold cross validation. Furthermore, the case study demonstrates that KGANCDA is an effective tool to predict potential circRNA-disease associations.

Reproductive factors and risk of lung cancer among 300,000 Chinese female never-smokers: evidence from the China Kadoorie Biobank study.

BACKGROUND: Lung cancer is the leading cause of cancer mortality among Chinese females despite the low smoking prevalence among this population. This study assessed the roles of reproductive factors in lung cancer development among Chinese female never-smokers. METHODS: The prospective China Kadoorie Biobank (CKB) recruited over 0.5 million Chinese adults (0.3 million females) from 10 geographical areas in China in 2004-2008 when information on socio-demographic/lifestyle/environmental factors, physical measurements, medical history, and reproductive history collected through interviewer-administered questionnaires. Cox proportional hazard regression was used to estimate adjusted hazard ratios (HRs) of lung cancer by reproductive factors. Subgroup analyses by menopausal status, birth year, and geographical region were performed. RESULTS: During a median follow-up of 11 years, 2,284 incident lung cancers occurred among 282,558 female never-smokers. Ever oral contraceptive use was associated with a higher risk of lung cancer (HR = 1.16, 95% CI: 1.02-1.33) with a significant increasing trend associated with longer duration of use (p-trend = 0.03). Longer average breastfeeding duration per child was associated with a decreased risk (0.86, 0.78-0.95) for > 12 months compared with those who breastfed for 7-12 months. No statistically significant association was detected between other reproductive factors and lung cancer risk. CONCLUSION: Oral contraceptive use was associated with an increased risk of lung cancer in Chinese female never-smokers. Further studies are needed to assess lung cancer risk related to different types of oral contraceptives in similar populations.

Regulon active landscape reveals cell development and functional state changes of human primary osteoblasts in vivo.

BACKGROUND: While transcription factor (TF) regulation is known to play an important role in osteoblast development, differentiation, and bone metabolism, the molecular features of TFs in human osteoblasts at the single-cell resolution level have not yet been characterized. Here, we identified modules (regulons) of co-regulated genes by applying single-cell regulatory network inference and clustering to the single-cell RNA sequencing profiles of human osteoblasts. We also performed cell-specific network (CSN) analysis, reconstructed regulon activity-based osteoblast development trajectories, and validated the functions of important regulons both in vivo and in vitro. RESULTS: We identified four cell clusters: preosteoblast-S1, preosteoblast-S2, intermediate osteoblasts, and mature osteoblasts. CSN analysis results and regulon activity-based osteoblast development trajectories revealed cell development and functional state changes of osteoblasts. CREM and FOSL2 regulons were mainly active in preosteoblast-S1, FOXC2 regulons were mainly active in intermediate osteoblast, and RUNX2 and CREB3L1 regulons were most active in mature osteoblasts. CONCLUSIONS: This is the first study to describe the unique features of human osteoblasts in vivo based on cellular regulon active landscapes. Functional state changes of CREM, FOSL2, FOXC2, RUNX2, and CREB3L1 regulons regarding immunity, cell proliferation, and differentiation identified the important cell stages or subtypes that may be predominantly affected by bone metabolism disorders. These findings may lead to a deeper understanding of the mechanisms underlying bone metabolism and associated diseases.

Proper Determination of Phase Diagrams while Nanoprecipitating Oils.

The Ouzo effect is a generic process to generate colloidal dispersions from a variety of solutes. Whereas phase diagrams have been quite easily established when nanoprecipitating polymers, the case of oils is less straightforward. Indeed, the short-term stability of generated nanodroplets in water/solvent mixtures complexifies the identification of the diagram boundaries. This article proposes two complementary methods, namely, fluorescence microscopy and dynamic light scattering, to determine with fair accuracy Ouzo limits in ternary systems oil/solvent/nonsolvent, without and with a surfactant, respectively. This accuracy in PD determination opens the way to a better understanding and control of the aggregation events during the nanoprecipitation process.

Poly(vinyl alcohol)s and Their Glycoderivatives as Efficient Shell-Builders of Nanocapsules by Nanoprecipitation.

Poly(vinyl alcohol)s (PVAs) are very popular dispersants for the construction of colloids and common shell-constituents of microcapsules but remain mostly unexplored as building blocks for the design of nanocapsules through nanoprecipitation or other processes. Herein, we first show that model commercial PVAs and oils can be concomitantly engaged in solvent-shifting procedures to give rise to oil-filled nanocapsules in one step. Next, we report the synthesis of precisely defined water-soluble glyco-PVAs by reversible addition-fragmentation chain transfer (RAFT) copolymerization of 6-O-vinyladipoyl-d-glucopyranose and vinyl chloroacetate and selective alcoholysis reactions. We finally demonstrate that these glycopolymers are excellent candidates for the straightforward conception of oil- and drug-filled, surface- and/or core-tagged, stealth, and degradable nanocapsules by nanoprecipitation.

Carbon Dots with Antioxidant Capacity for Detecting Glucose by Fluorescence and Repairing High-Glucose Damaged Glial Cells.

Diabetic mellitus management extends beyond blood glucose monitoring to the essential task of mitigating the overexpression of reactive oxygen species (ROS), particularly vital for cellular repair, especially within the nervous system. Herein, antioxidant carbon dots (Arg-CDs) were designed and prepared using anhydrous citric acid, L-arginine, and ethylenediamine as sources through a hydrothermal method. Arg-CDs exhibited excellent scavenging ability to 2,2-Diphenyl-1-picrylhydrazyl (DPPH∙), and fluorescence response to hydroxyl radicals (∙OH), a characteristic representative of reactive oxygen species (ROS). Assisted by glucose oxidase and Fe2+, Arg-CDs showed a sensitive and selective response to glucose. The quenching mechanism of Arg-CDs by formed ∙OH was based on the static quenching effect (SQE). The analytical performance of this method for glucose detection encompassed a wide linear range (0.3-15 µM), a low practical limit of detection (0.1 µM) and practical applicability for blood glucose monitoring. In an in vitro model employing glial cells (BV2 cells), it was observed that high glucose medium led to notable cellular damage ascribed to the excessive ROS production from hyperglycemia. The diminished and apoptotic glial cells were gradually recovered by adding increased contents of Arg-CDs. This work illustrates a promising area that designs effective carbon dots with antioxidant capacity for the dual applications of detection and cell repairing based on the utilization of antioxidant activity.