Angiotensin (1-7) Inhibits Transforming Growth Factor-Β1-Induced Epithelial-Mesenchymal Transition of Human Keratinocyte Hacat Cells in vitro.

Introduction: Angiotensin (1-7) (Ang-(1-7)) is an emerging component of the renin-angiotensin system (RAS) with effective anti-fibrosis properties and has been shown to interfere with epithelial-mesenchymal transition (EMT) by numerous studies. In recent years, EMT has been proposed as a new therapeutic target for skin fibrotic diseases such as keloids. However, the effect of Ang-(1-7) on EMT in skin is still unclear. Hence, the purpose of this study was to explore the effect of Ang-(1-7) on Transforming growth factor-ß1(TGF-ß1)-induced EMT of human immortalized keratinocytes HaCaT in vitro. Methods: The study involved the use of the human immortalized keratinocyte cell line (HaCaT). The cells were cultured in high-glucose DMEM medium with 10% fetal bovine serum and 1% penicillin-streptomycin. Four groups were created for experimentation: control group (Group C), TGF-ß1-treated group (Group T), Ang-(1-7)-treated group (Group A), and a group treated with both TGF-ß1 and Ang-(1-7) (Group A + T). Various assays were conducted, including a cell proliferation assay using CCK-8 solution, a scratch wound healing assay to evaluate cell migration, and Western blotting to detect protein expressions related to cell characteristics. Additionally, quantitative real-time polymerase chain reaction (PCR) was performed to analyze epithelial-mesenchymal transition (EMT) related gene expression levels. The study aimed to investigate the effects of TGF-ß1 and Ang-(1-7) on HaCaT cells. Results: We found that Ang-(1-7) not only reduced the migration of HaCaT cells induced by TGF-ß1 in vitro but also reduced the expression of α-SMA and vimentin, and restored the protein expression of E-cadherin and claudin-1. Mechanistically, Ang-(1-7) inhibits the phosphorylation levels of Smad2 and Smad3 in the TGF-ß1 canonical pathway, and suppresses the expression of EMT-related transcription factors (EMT-TFs) such as SNAI2, TWIST1, and ZEB1. Discussion: Taken together, our findings suggest that Ang-(1-7) inhibits TGF-ß1-induced EMT in HaCaT cells in vitro by disrupting the TGF-ß1-Smad canonical signaling pathway. These results may be helpful in the treatment of EMT in skin fibrotic diseases such as keloids.

Deep-Learning-Guided Evaluation Method for the High-Volume Preparation of Flexible Sensors Based on Inkjet Printing.

Flexible sensors for application in various industries, including biomedicine and wearable electronics, are frequently made using silver nanoparticle (AgNP) inks and inkjet printing (IJP) technology. Inkjet-printed flexible electronic devices are made up of many printed lines that run parallel to each other, and the surface morphology of the printed lines and the interline state directly impact the electrical conductivity of the electronic devices. This paper describes the experimental setup for IJP, the definition of print line characteristics, and common unavoidable defects. Conductivity and physical defects are considered in defining the print line quality assessment. In addition, two prediction models of flexible sensors before batch printing and a model for detecting defects after printing are provided. The predictive models can guide actions, leading to a print success rate of over 80%. We build the defect detection model using a neural architecture search because manually fine-tuning neural networks for reference is challenging. Finally, a target detection model with a mAP@0.5 of 81.2% is built in just 0.77 graphics processing unit (GPU) days. The model takes only 4.6 ms to detect an image, satisfying the real-time monitoring needs. At the same time, an accuracy of 95.5% can be achieved in the test data set. This work provides a new idea for the high-volume preparation of flexible sensors.

Screening androgen receptor agonists of fish species using machine learning and molecular model in NORMAN water-relevant list.

Androgen receptor (AR) agonists have strong endocrine disrupting effects in fish. Most studies mainly investigate AR binding capacity using human AR in vitro. However, there is still few methods to rapidly predict AR agonists in aquatic organisms. This study aimed to screen AR agonists of fish species using machine learning and molecular models in water-relevant list from NORMAN, a network of reference laboratories for monitoring contaminants of emerging concern in the environment. In this study, machine learning approaches (e.g., Deep Forest (DF)), Random Forests and artificial neural networks) were applied to predict AR agonists. Zebrafish, fathead minnow, mosquitofish, medaka fish and grass carp are all important aquatic model organisms widely used to evaluate the toxicity of new pollutants, and the molecular models of ARs from these five fish species were constructed to further screen AR agonists using AlphaFold2. The DF method showed the best performances with 0.99 accuracy, 0.97 sensitivity and 1 precision. The Asn705, Gln711, Arg752, and Thr877 residues in human AR and the corresponding sites in ARs from the five fish species were responsible for agonist binding. Overall, 245 substances were predicted as suspect AR agonists in the five fish species, including, certain glucocorticoids, cholesterol metabolites, and cardiovascular drugs in the NORMAN list. Using machine learning and molecular modeling hybrid methods rapidly and accurately screened AR agonists in fish species, and helping evaluate their ecological risk in fish populations.

Research progress on the mechanism of angiogenesis in wound repair and regeneration.

Poor wound healing and pathological healing have been pressing issues in recent years, as they impact human quality of life and pose risks of long-term complications. The study of neovascularization has emerged as a prominent research focus to address these problems. During the process of repair and regeneration, the establishment of a new vascular system is an indispensable stage for complete healing. It provides favorable conditions for nutrient delivery, oxygen supply, and creates an inflammatory environment. Moreover, it is a key manifestation of the proliferative phase of wound healing, bridging the inflammatory and remodeling phases. These three stages are closely interconnected and inseparable. This paper comprehensively integrates the regulatory mechanisms of new blood vessel formation in wound healing, focusing on the proliferation and migration of endothelial cells and the release of angiogenesis-related factors under different healing outcomes. Additionally, the hidden link between the inflammatory environment and angiogenesis in wound healing is explored.

BTSC-TNAS: A neural architecture search-based transformer for brain tumor segmentation and classification.

Glioblastoma (GBM), isolated brain metastasis (SBM), and primary central nervous system lymphoma (PCNSL) possess a high level of similarity in histomorphology and clinical manifestations on multimodal MRI. Such similarities have led to challenges in the clinical diagnosis of these three malignant tumors. However, many existing models solely focus on either the task of segmentation or classification, which limits the application of computer-aided diagnosis in clinical diagnosis and treatment. To solve this problem, we propose a multi-task learning transformer with neural architecture search (NAS) for brain tumor segmentation and classification (BTSC-TNAS). In the segmentation stage, we use a nested transformer U-shape network (NTU-NAS) with NAS to directly predict brain tumor masks from multi-modal MRI images. In the tumor classification stage, we use the multiscale features obtained from the encoder of NTU-NAS as the input features of the classification network (MSC-NET), which are integrated and corrected by the classification feature correction enhancement (CFCE) block to improve the accuracy of classification. The proposed BTSC-TNAS achieves an average Dice coefficient of 80.86% and 87.12% for the segmentation of tumor region and the maximum abnormal region in clinical data respectively. The model achieves a classification accuracy of 0.941. The experiments performed on the BraTS 2019 dataset show that the proposed BTSC-TNAS has excellent generalizability and can provide support for some challenging tasks in the diagnosis and treatment of brain tumors.

Adaptive Second-Order Fixed-Time Sliding Mode Controller with a Disturbance Observer for Electronic Throttle Valves.

In order to enhance the precision and speed of control for electronic throttle valves (ETVs) in the face of disturbance and parameter uncertainties, an adaptive second-order fixed-time sliding mode (ASOFxTSM) controller is developed, along with disturbance observer compensation techniques. Initially, a control-oriented model specifically considering lumped disturbances within the ETV is established. Secondly, to address the contradiction between fast response and heavy chattering of conventional fixed-time sliding mode, a hierarchical sliding surface approach is introduced. This approach proficiently alleviates chattering effects while preserving the fixed convergence properties of the controller. Furthermore, to enhance the anti-disturbance performance of the ETV control system, an innovative fixed-time sliding mode observer is incorporated to estimate lumped disturbances and apply them as a feed-forward compensation term to the ASOFxTSM controller output. Building upon this, a parameter adaptive mechanism is introduced to optimize control gains. Subsequently, a rigorous stability proof is conducted, accompanied by the derivation of the expression for system convergence time. Finally, a comparison is drawn between the proposed controller and fixed-time sliding mode and super-twisting controllers through simulations and experiments. The results demonstrate the superiority of the proposed method in terms of chattering suppression, rapid dynamic response, and disturbance rejection capability.

Identification of the natural chalcone glycoside hydroxysafflor yellow A as a suppressor of P53 overactivation-associated hematopoietic defects.

Enhanced P53 signaling may lead to hematopoietic disorders, yet an effective therapeutic strategy is still lacking. Our study, along with previous research, suggests that P53 overactivation and hematopoietic defects are major consequences of zinc deficiency. However, the relationship between these two pathological processes remains unclear. In this study, we observed a severe reduction in the number of hematopoietic stem cells (HSCs) and multi-lineage progenitor cells in zebrafish treated with the zinc chelator N,N,N',N'-tetrakis(2-pyridylmethyl)ethylenediamine and showed the indispensable role of P53 signaling in the process. Next, we took advantage of HSCs-labeled transgenic zebrafish and conducted a highly efficient phenotypic screening for small molecules against P53-dependent hematopoietic disorders. Hydroxysafflor yellow A (HSYA), a natural chalcone glycoside, exhibited potent protection against hematopoietic failure in zinc-deficient zebrafish and strongly inhibited the P53 pathway. We confirmed the protective effect of HSYA in zinc-deficient mice bone marrow nucleated cells, which showed a significant suppression of P53 signaling and oxidative stress. Furthermore, the hematopoietic-protective activity of HSYA was validated using a mice model of myelotoxicity induced by 5-FU. In summary, our work provides an effective phenotypic screening strategy for identifying hematopoietic-protective agents and reveals the novel role of HSYA as a promising lead compound in rescuing hematopoietic disorders associated with P53 overactivation.

Benchmarking of force fields to characterize the intrinsically disordered R2-FUS-LC region.

Intrinsically Disordered Proteins (IDPs) play crucial roles in numerous diseases like Alzheimer's and ALS by forming irreversible amyloid fibrils. The effectiveness of force fields (FFs) developed for globular proteins and their modified versions for IDPs varies depending on the specific protein. This study assesses 13 FFs, including AMBER and CHARMM, by simulating the R2 region of the FUS-LC domain (R2-FUS-LC region), an IDP implicated in ALS. Due to the flexibility of the region, we show that utilizing multiple measures, which evaluate the local and global conformations, and combining them together into a final score are important for a comprehensive evaluation of force fields. The results suggest c36m2021s3p with mTIP3p water model is the most balanced FF, capable of generating various conformations compatible with known ones. In addition, the mTIP3P water model is computationally more efficient than those of top-ranked AMBER FFs with four-site water models. The evaluation also reveals that AMBER FFs tend to generate more compact conformations compared to CHARMM FFs but also more non-native contacts. The top-ranking AMBER and CHARMM FFs can reproduce intra-peptide contacts but underperform for inter-peptide contacts, indicating there is room for improvement.

Norethindrone suppress the germ cell development via androgen receptor resulting in male bias.

Progestins are widely used and detected in surface waters, and can affect gonad development and sexual differentiation in fish. However, the toxicological mechanisms of sexual differentiation induced by progestins are not well understood. Here, we investigated the effects of norethindrone (NET) and androgen receptor (AR) antagonist flutamide (FLU) on gonadal differentiation in zebrafish from 21 dpf (days post-fertilization) to 49 dpf. The results showed that NET caused male bias, while FLU resulted in female bias at 49 dpf. The NET and FLU mixtures significantly decreased the percentage of males compared to the NET single exposure. Molecular docking analysis showed that FLU and NET had similar docking pocket and docking posture with AR resulting in competitively forming the hydrogen bond with Thr334 of AR. These results suggested that binding to AR was the molecular initiating event of sex differentiation induced by NET. Moreover, NET strongly decreased transcription of biomarker genes (dnd1, ddx4, dazl, piwil1 and nanos1) involved in germ cell development, while FLU significantly increased transcription of these target genes. There was an increase in the number of juvenile oocytes, which was consistent with the female bias in the combined groups. The bliss independence model analysis further showed that NET and FLU had antagonistic effect on transcription and histology during gonadal differentiation. Thus, NET suppressed the germ cell development via AR, resulting in male bias. Understanding the molecular initiation of sex differentiation in progestins is essential to provide a comprehensive biological basis for ecological risk assessment.

Hypoxia activates the PI3K/AKT/HIF-1α pathway to promote the anti-inflammatory effect of adipose mesenchymal stem cells.

This study aimed to investigate the effect of hypoxia on the anti-inflammatory effect of adipose-derived mesenchymal stem cells (AMSCs) in vitro and its possible mechanism. AMSCs were cultured in vitro in a hypoxic environment with 3% O2, and a normoxic (21% O2) environment was used as the control. The cells were identified by in vitro adipogenic and osteogenic differentiation and cell surface antigen detection, and the cell viability were detected. The effect of hypoxic AMSCs on macrophage inflammation was analyzed by co-culture. The results showed that under hypoxia, AMSCs had better viability, significantly downregulated the expression of inflammatory factors, alleviated macrophage inflammation, and activated the PI3K/AKT/HIF-1α pathway.

Response of sediment transport capacity to soil properties and hydraulic parameters in the typical agricultural regions of the Loess Plateau.

The sediment transport capacity by overland flow (Tc) is a key parameter in process-based soil erosion models and Tc variation is sensitive to changes in soil properties. This study was undertaken to investigate Tc variations with respect to soil properties and establish a universal relationship to predict Tc. The test soils were collected from typical agricultural regions (Guanzhong basin-Yangling (YL), Weibei Dry plateau-Chunhua (CH), Hilly and gully region-Ansai (AS), Ago-pastoral transition zone along the Great Wall-Yuyang (YY), and Weiriver floodplain-Weicheng (WC)) of the Loess Plateau, and subjected to 36 different combinations of slope gradients (S, 5.24-44.52 %) and flow discharge (q, 0.00033-0.00125 m2 s-1) in a hydraulic flume. The results showed that the mean Tc values for WC were 2.15, 1.38, 1.32, and 1.16 times greater than those for YL, CH, AS, and YY, respectively. Tc significantly decreased with clay content (C), mean weight diameter (MWD), and soil organic matter content (SOM). Tc for different soil types increased with S and q as a binary power function, and Tc variation was more sensitive to S than to q. Stream power (w) was the most appropriate hydraulic variable to express Tc for different soils. Tc for different soil types could be satisfactorily simulated using a quaternary power function of S, q, C, and MWD (R2 = 0.94; NSE = 0.94) or a ternary power function of w, C, and MWD (R2 = 0.94; NSE = 0.94). The new Tc equation can reflect the effect of soil properties on it and facilitate the development of a process-based soil erosion model.

BTMF-GAN: A multi-modal MRI fusion generative adversarial network for brain tumors.

Image fusion techniques have been widely used for multi-modal medical image fusion tasks. Most existing methods aim to improve the overall quality of the fused image and do not focus on the more important textural details and contrast between the tissues of the lesion in the regions of interest (ROIs). This can lead to the distortion of important tumor ROIs information and thus limits the applicability of the fused images in clinical practice. To improve the fusion quality of ROIs relevant to medical implications, we propose a multi-modal MRI fusion generative adversarial network (BTMF-GAN) for the task of multi-modal MRI fusion of brain tumors. Unlike existing deep learning approaches which focus on improving the global quality of the fused image, the proposed BTMF-GAN aims to achieve a balance between tissue details and structural contrasts in brain tumor, which is the region of interest crucial to many medical applications. Specifically, we employ a generator with a U-shaped nested structure and residual U-blocks (RSU) to enhance multi-scale feature extraction. To enhance and recalibrate features of the encoder, the multi-perceptual field adaptive transformer feature enhancement module (MRF-ATFE) is used between the encoder and the decoder instead of a skip connection. To increase contrast between tumor tissues of the fused image, a mask-part block is introduced to fragment the source image and the fused image, based on which, we propose a novel salient loss function. Qualitative and quantitative analysis of the results on the public and clinical datasets demonstrate the superiority of the proposed approach to many other commonly used fusion methods.

Did Wheat Breeding Simultaneously Alter Grain Concentrations of Macro- and Micro-Nutrient Over the Past 80 Years of Cultivar Releasing in China?

Biofortification of wheat with mineral through crop breeding is a sustainable and cost-effective approach to address human mineral malnutrition. A better understanding of the trends of grain concentrations of mineral nutrients in wheat over the breeding period may help to assess the breeding progress to date. A 2-year field experiment using 138 Chinese wheat landraces and 154 cultivars was conducted. Grain concentrations of micronutrients (Cu and Mn) and macronutrients (N, P, and K) were measured and corrected for a yield level to elucidate the trends of these mineral nutrients over the 80 years of cultivar releasing and identify genetic variation for these mineral nutrients in cultivars and landraces. Large genetic variation exists for grain mineral nutrients concentrations among tested genotypes, indicating that selection for enhancing mineral nutrient concentrations in wheat is possible. Landraces showed a slightly wide genetic variation of grain Cu concentration and a much narrow variation of Mn concentration when compared to modern cultivars. Grain concentrations of Cu and Mn decreased slightly with increasing grain yield with a weak correlation, while N, P, and K concentrations declined obviously with increasing yield with a strong correlation, revealing that increased grain yield had a strong negative effect on grain concentration of macronutrients, but a relative weak negative effect on micronutrients concentrations. When considering the impact of the variation in yield on mineral concentrations, grain concentrations of Cu, Mn, N, P, and K in wheat cultivars released from 1933 to 2017 exhibited different trends with a year of variety release. Grain Cu, N, and P concentrations showed significant decreasing trends over a breeding period, while grain Mn and K concentrations showed no clear trend, suggesting wheat breeding in China over the past 80 years has decreased grain concentrations of Cu, N, and P, and did not alter Mn and K concentrations. Finally, a total of 14 outstanding accessions with high grain mineral nutrients concentrations/contents were identified, and these genotypes can be considered as promising donors for developing mineral-dense wheat cultivars.

Pharmacokinetics and Bioequivalence of 2 Oral Formulations of Domperidone After Single-Dose Administration in Healthy Chinese Subjects.

To evaluate the pharmacokinetic properties and bioequivalence of 2 oral formulations of domperidone in healthy Chinese subjects, a randomized, open-label, 2-way crossover study was conducted under fasting and fed states. All 96 healthy subjects were randomized to receive a single oral dose of a 10-mg generic domperidone tablet (test) or branded domperidone tablet (reference). Blood samples were collected at specified time intervals and analyzed for domperidone using liquid chromatography-tandem mass spectrometry. In the fasting test, 90% CIs of geometric mean ratios were 86.7% to 105.8% for maximum concentration, 96.7% to 106.1% for area under the concentration-time curve (AUC) from time 0 to the time of the last measurable plasma concentration, and 97.1% to 106.1% for AUC from time 0 extrapolated to infinity. In the fed test, the 90% CIs were 90.8% to 121.1%, 99.7% to 109.4%, and 99.4% to 109.1%, respectively. All 90% CIs were within the bioequivalence range of 80% to 125%, indicating that the 2 formulations were bioequivalent. In addition, the values of time to maximum concentration, terminal-phase elimination half-life, and AUC were significantly higher in the fed group than in the fasting group, suggesting that a high-fat meal slowed down the absorption and elimination of domperidone and significantly increased domperidone exposure.

Upward social comparison sensitivity on teachers' emotional exhaustion: A moderated moderation model of self-esteem and gender.

Drawing on conservation of resources theory, this study aims to extend the work on individual differences in the relationship between upward social comparison sensitivity and emotional exhaustion in a sample of teachers by examining the interaction effects of self-esteem and gender differences. A total of 681 teachers completed a self-reported questionnaire including the Upward Social Comparison Sensitivity Scale, the Self-Esteem Scale, and the Maslach Burnout Inventory-Educators Survey (MBI-ES) subscale. The results based on a moderated moderation model indicated that: (1) Upward social comparison sensitivity was positively correlated with emotional exhaustion; (2) self-esteem moderated the relationship between upward social comparative sensitivity and emotional exhaustion; and (3) there was a significant gender difference in self-esteem that moderated the relationship between upward social comparison sensitivity and emotional exhaustion. These findings contribute to the understanding of how upward social comparison sensitivity predicts teachers' emotional exhaustion and provide practical insights for prevention and intervention programs to protect teachers' mental health in school settings.

Pneumoconiosis computer aided diagnosis system based on X-rays and deep learning.

PURPOSE: The objective of this study is to construct a computer aided diagnosis system for normal people and pneumoconiosis using X-raysand deep learning algorithms. MATERIALS AND METHODS: 1760 anonymous digital X-ray images of real patients between January 2017 and June 2020 were collected for this experiment. In order to concentrate the feature extraction ability of the model more on the lung region and restrain the influence of external background factors, a two-stage pipeline from coarse to fine was established. First, the U-Net model was used to extract the lung regions on each sides of the collection images. Second, the ResNet-34 model with transfer learning strategy was implemented to learn the image features extracted in the lung region to achieve accurate classification of pneumoconiosis patients and normal people. RESULTS: Among the 1760 cases collected, the accuracy and the area under curve of the classification model were 92.46% and 89% respectively. CONCLUSION: The successful application of deep learning in the diagnosis of pneumoconiosis further demonstrates the potential of medical artificial intelligence and proves the effectiveness of our proposed algorithm. However, when we further classified pneumoconiosis patients and normal subjects into four categories, we found that the overall accuracy decreased to 70.1%. We will use the CT modality in future studies to provide more details of lung regions.

Development and Validation of a Nomogram for Predicting Drug-Induced Acute Kidney Injury in Hospitalized Patients: A Case-Control Study Based on Propensity-Score Matching.

Background: Drug-induced acute kidney injury (D-AKI) is associated with increased mortality and longer hospital stays. This study aims to establish a nomogram to predict the occurrence of D-AKI in hospitalized patients in a multi-drug environment. Methods: A single center retrospective study among adult hospitalized patients was conducted from July 2019 to September 2019 based on the Adverse Drug Events Active Surveillance and Assessment System-2 developed by our hospital. According to the propensity score matching algorithm, four controls per case were matched to eliminate the confounding bias caused by individual baseline variables. The predictors for D-AKI were obtained by logistic regression equation and used to establish the nomogram. Results: Among 51,772 hospitalized patients, 332 were diagnosed with D-AKI. After matching, 288 pairs and 1,440 patients were included in the study, including 1,005 cases in the development group and 435 cases in the validation group. Six variables were independent predictors for D-AKI: alcohol abuse, the concurrent use of nonsteroidal anti-inflammatory drugs or diuretics, chronic kidney disease, lower baseline red blood cell count and neutrophil count ≥7 × 109/L. The area under the curve (AUC) of the prediction model in the development group and validation group were 0.787 (95%CI, 0.752-0.823) and 0.788 (95%CI, 0.736-0.840), respectively. The GiViTI calibration belts showed that the model had a good prediction accuracy for the occurrence of D-AKI (p > 0.05). Conclusion: This nomogram can help identify patients at high risk of D-AKI, which was useful in preventing the progression of D-AKI and treating it in the early stages.

Anti-Cancer Activity Based on the High Docetaxel Loaded Poly(2-Oxazoline)s Micelles.

PURPOSE: Nanocarriers, with a high drug loading content and good safety, to achieve desirable therapeutic effect are always the goals for industry and research. METHODS AND RESULTS: In the present study, we developed a docetaxel loaded poly-2-oxazoline polymer micellar system which employed poly-2-butyl-2 oxazoline and poly-2-methyl-2 oxazoline as the hydrophobic chain and hydrophilic chain, respectively. This micellar system achieves a high load up to 25% against the docetaxel, and further demonstrates an IC50 as low as 40% of the commercialized docetaxel injection in vitro and a double maximum tolerated dose in MCF-7 cells in vivo. CONCLUSION: The high drug loading content, superior safety, and considerable anti-cancer activity make this newly developed docetaxel loaded poly(2-oxazoline) micelle go further in future clinical research.

[The expression and significance of TET gene and 5hmC in chronic rhinosinusitis].

Objective:To investigate the expression and clinical significance of TET gene and 5hmC in chronic sinusitis. Methods:Acquiring 20 cases of nasal polyps from chronic sinusitis with polyps（CW）, 20 cases of uncinate process tissues from chronic sinusitis without polyps（CS）, 10 cases of middle turbinate tissues from patients with nasal septum deviated as normal group（N）.The expression of TET gene and 5hmC in chronic sinusitis was measured by immunofluorescence, Western-Blot and Quantitative real-time PCR. Results:Both TET1/2/3 gene and 5 hmC were highly expressed in the CS group, but were lower in the CW group and the N group.There were statistically significant differences between the CS group and the CW group（P<0.05）, and between the CS group and the N group（P<0.05）.The expressions of TET1 and TET3 in the N group were higher than those in the CW group, and the difference was statistically significant（P<0.05）. Conclusion:DNA demethylation plays an important role in the formation of nasal polyps.High expression of TET1, TET2, TET3 and 5hmC May reduce the risk of nasal polyps.Increased DNA demethylation in chronic sinusitis may reduce the risk of nasal polyp formation.When the degree of DNA methylation in chronic sinusitis is high and the degree of DNA demethylation is low, the disease may develop to CRSwNP, and when the degree of DNA methylation is low and the degree of DNA demethylation is high, the disease may develop to CRSsNP.