OBJECTIVE: EPF3 is a fibrinolysin monomer isolated and purified from Pheretima vulgaris Chen, an earthworm used in traditional Chinese medicine as Dilong for treating blood stasis syndrome. Its composition, anticoagulant and fibrinolytic activities, and relevant mechanisms have been confirmed through in vitro experiments. However, whether it has antithrombotic effects in vivo and can be absorbed by the gastrointestinal tract is unknown. This study evaluates the antithrombotic effect in zebrafish and investigates the gastrointestinal stability and intestinal absorption mechanism of this protein in vitro. METHODS: The antithrombotic effect of EPF3 in vivo was verified using the zebrafish thrombus model induced by arachidonic acid and FeCl₃. Then, the protein bands of EPF3 incubated with simulated gastric fluid (SGF), simulated intestinal fluid (SIF), and homogenate of Caco-2 cells (HC2C) were analyzed by sodium dodecyl sulfate-polyacrylamide gel electrophoresis to evaluate its gastrointestinal stability. Finally, the transport behavior and absorption mechanism of EPF3 were studied using Caco-2 cell monolayer. RESULTS: EPF3 could significantly enhance the returned blood volume and blood flow velocity in zebrafish with platelet aggregation thrombus induced by arachidonic acid. It could also prolong the formation time of tail artery thrombus and increase the blood flow velocity in zebrafish with vessel injury thrombus induced by FeCl₃. EPF3 was stable in SIF and HC2C and unstable in SGF. The permeability of EPF3 in Caco-2 monolayer was time-dependent and concentration-dependent. The efflux ratio was less than 1.2 during transport, and the transport behavior was not affected by inhibitors. EPF3 could reversibly reduce the expression of tight junction-related proteins, including zonula occludens-1, occludin, and claudin-1 in Caco-2 cells. CONCLUSION EPF3 could play a thrombolytic and antithrombotic role in zebrafish. It could be transported and absorbed into the intestine through cellular bypass pathway by opening the intestinal epithelium tight junction. This study provides a scientific explanation for the antithrombotic effect of earthworm and provides a basis for the feasibility of subsequent development of EPF3 as an antithrombotic enteric-soluble preparation. Please cite this article as: Zhong WL, Yang JQ, Liu H, Wu YL, Shen HJ, Li PY, Du SY. Antithrombotic effect in zebrafish of a fibrinolytic protein EPF3 from Dilong (Pheretima vulgaris Chen) and its transport mechanism in Caco-2 monolayer through cell bypass pathway. J Integr Med. 2025; 23(4): 415-428.
Animals ; Zebrafish ; Humans ; Caco-2 Cells ; Fibrinolytic Agents/pharmacology* ; Thrombosis/drug therapy* ; Intestinal Absorption

AIM To evaluate the quality of Rubi Fructus.METHODS UPLC-Q-TOF-MS/MS was adopted in the component identification,after which the HPLC fingerprints were established,cluster analysis,principal component analysis and orthogonal partial least squares discriminant analysis were used for chemical pattern recognition.and the contents of chlorogenic acid,ferulic acid,ellagic acid,isoquercitrin,kaempferol-3-O-rutinoside,astragalin,tiliroside quercetin,kaempferol were determined.RESULTS Total 34 constituents were identified.There were 19 common peaks in the fingerprints for 31 batches of medicinal materials with the similarities of more than 0.8.Wild varieties and cultivated varieties,and medicinal materials from different producing areas could be distinguished;4 principal components demonstrated the accumulative variance contribution rate of 84.142％;8 differential components were screened,2 of which were ellagic acid and astragalin.Ellagic acid and astragalin displayed higher contents in the wild varieties than those in the cultivated varieties(P＜0.05,P＜0.01).CONCLUSION UPLC-Q-TOF-MS/MS,HPLC fingerprints combined with content determination can be used for the quality control of Rubi Fructus.

Objective To study the effects of Hedysarum polysaccharides polysaccharide(HPS)on the farnesoid X receptor(FXR)-fibroblast growth factor-19(FGF19)signaling pathway of diabetes rats.Methods Twelve Wistar male rats were randomly selected as the normal group,and the other rats were fed with a single intraperitoneal injection of streptozotocin(50 mg·kg-1 STZ)and a high sugar and high-fat diet to replicate the diabetes rat model.Model rats were randomly divided into model group,positive control group(given 400 mg·kg-1·d-1 suspension of Bifidobacterium quadruplex live bacterial tablets by gavage),experimental-H,-M,-L groups(given 200,100,and 50 mg·kg-1·d-1 doses of HPS suspension by gavage);normal group,and model group were given equal volume of purified water by gavage once a day for 8 consecutive weeks.Glucose(Glu)was detected by a blood glucose meter;and serum total glyceride(TG)and total cholesterol(TC)were detected by enzyme-linked immunosorbent assay reagent kit;the expressions of FXR、fibroblast growth factor receptors 4(FGFR4)relative mRNA expression level and protein were detected by real-time fluorescence quantitative polymerase chain reaction method and Western blot.Results The Glu concentrations in the normal group,model group,positive control group,and experimental-H groups were(7.66±0.61),(29.25±1.64),(23.31±3.02)and(19.31±5.13)mmol·L-1,respectively;the TG content were(957.00±113.73),(1 345.00±246.44),(958.00±96.53)and(964.00±130.22)μmol·L-1,respectively;the TC content were(161.65±4.53),(302.19±5.35),(236.09±5.14)and(165.58±2.58)μmol·L-1,respectively;the expression of FXR relative mRNA expression level were 1.00±0.06,0.48±0.02,0.67±0.04 and 0.92±0.04,respectively;the expression of FGFR4 relative mRNA expression level were 1.00±0.04,0.17±0.01,0.48±0.04 and 0.41±0.03;respectively.The above indexes of the model group were compared with the control group,and the above indexes of the control group and the experimental-H group were compared with the model group,and the differences were statistically significant(all P＜0.01).Conclusion HPS improves blood sugar,lowers blood lipids,and protects liver and intestinal tissues,possibly by regulating the FXR-FGF19 signaling pathway in intestinal tissue,and regulating bile acid synthesis.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

OBJECTIVES: To explore the measures to improve the follow-up rate of preterm infants after discharge, and to evaluate the effectiveness of these measures using quality improvement methodology. METHODS: The follow-up status of preterm infants discharged from March to May 2017 was used as the baseline before quality improvement, and a specific quality improvement goal for the follow-up rate was proposed. The Pareto chart was used to analyze the causes of follow-up failure, and a key driver diagram was constructed based on the links involved in improving follow-up rate. The causes of failure were analyzed to determine the key links and intervention measures for quality improvement, and the follow-up rate was monitored weekly using a control chart until the quality improvement goal was achieved. RESULTS: The follow-up rate of preterm infants after discharge was 57.92% (117/202) at baseline before quality improvement, and the quality improvement goal was set to increase the follow-up rate of preterm infants from baseline to more than 80% within 12 months. The Pareto chart analysis showed that the main causes of follow-up failure were deficiencies in follow-up file management and irregular follow-up times (33.70%, 31/92), insufficient follow-up education and poor communication (25.00%, 23/92), and the inability to meet the diverse needs of parents (18.48%, 17/92). Based on the key links for quality improvement and the main causes of follow-up failure, the following intervention measures were adopted: (1) strengthen follow-up publicity and education; (2) build a follow-up team; and (3) establish a follow-up platform and system. The control chart indicated that with the implementation of the above intervention measures, the weekly follow-up rate increased to 74.09% (306/413) in July 2017 and 83.09% (511/615) in December 2017, finally achieving the quality improvement goal. During the COVID-19 pandemic, the follow-up rate of preterm infants fluctuated between 23.54% (460/1 954) and 70.97% (1 931/2 721), and subsequently, it returned to pre-pandemic levels starting in February 2023. CONCLUSIONS The application of quality improvement methodology can help to formulate intervention measures based on the main causes of follow-up failure, thereby improving the follow-up rate of preterm infants after discharge. This quality improvement method is feasible and practical and thus holds promise for clinical application.
Humans ; Quality Improvement ; Infant, Premature ; Infant, Newborn ; Patient Discharge ; Follow-Up Studies ; Female ; Male

OBJECTIVES: To explore the status and risk factors of neuropsychological development in small for gestational age (SGA) infants at corrected 12-24 months of age. METHODS: Clinical data were retrospectively collected for 754 SGA infants at corrected ages 12-24 months in Shenzhen Bao'an Women and Children's Hospital between April 2018 and December 2023. Developmental quotient (DQ) levels were analyzed. According to the presence of global developmental delay (GDD), participants were divided into a GDD group (71 cases) and a control group (683 cases), and the incidence and influencing factors of GDD were investigated. RESULTS: In the high-risk preterm SGA group, the total DQ and DQ in all domains were lower than in the full-term SGA group (P<0.017). The overall incidence of GDD was 9.4% (71/754) and increased with decreasing gestational age (P<0.017). Compared with the control group, the GDD group had higher proportions of males; low-risk and high-risk preterm birth; mothers with less than a bachelor's degree; multiple birth; neonatal hypoglycemia; neonatal pneumonia; neonatal respiratory distress syndrome; bronchopulmonary dysplasia; and, at corrected 12-24 months, low body weight, growth retardation, and microcephaly. The length of neonatal hospital stay was longer in the GDD group than in the control group (P<0.05). The weight-for-age Z score, length-for-age Z score, and head circumference-for-age Z score at birth and at corrected 12-24 months were lower in the GDD group than in the control group (P<0.05). Multivariable logistic regression showed that male sex and maternal education below a bachelor's degree were independent risk factors for GDD in SGA infants (P<0.05). CONCLUSIONS Neuropsychological development in preterm SGA infants is comparatively delayed; male SGA infants born to mothers with less than a bachelor's degree should receive priority attention.
Humans ; Female ; Male ; Infant, Small for Gestational Age/psychology* ; Risk Factors ; Infant ; Retrospective Studies ; Child Development ; Developmental Disabilities/epidemiology* ; Infant, Newborn ; Child, Preschool

OBJECTIVE: To explore the efficacy and apoptosis of allogeneic hematopoietic stem cell transplantation (allo-HSCT) in the treatment of acute myeloid leukemia (AML) with ASXL1 mutation. METHODS: The clinical data of 80 AML patients with ASXL1 mutation treated in our hospital from January 2019 to December 2021 were retrospectively analyzed. The clinical characteristics of the patients were summarized, and the therapeutic effect and prognostic factors of allo-HSCT for the patients were analyzed. RESULTS: Among the 80 patients, 38 were males and 42 were females, and the median age was 39(14-65) years. There were 17 patients in low-risk group, 25 patients in medium-risk group and 38 patients in high-risk group. ASXL1 mutation co-occurred with many other gene mutations, and the frequent mutated genes were TET2 (71.25%), NRAS (18.75%), DNMT3A (16.25%), NPM1 (15.00%), CEBPA (13.75%). Among medium and high-risk patients, 29 underwent allo-HSCT, while 34 received chemotherapy. The 2-year overall survival (OS) rate and disease-free survival (DFS) rate of the allo-HSCT group were 72.4% and 70.2%, while those of the chemotherapy group were 44.1% and 34.0%, respectively. The statistical analysis showed significant differences between the two groups (both P < 0.01). Multivariate analysis showed that age at transplantation >50- years and occurrence of acute graft-versus-host disease after transplantation were poor prognostic factors for OS and DFS in transplantation patients. CONCLUSION Allo-HSCT can improve the prognosis of AML patients with ASXL1 mutation.
Humans ; Leukemia, Myeloid, Acute/therapy* ; Hematopoietic Stem Cell Transplantation ; Female ; Male ; Middle Aged ; Mutation ; Adult ; Repressor Proteins/genetics* ; Adolescent ; Retrospective Studies ; Aged ; Nucleophosmin ; Young Adult ; Transplantation, Homologous ; Prognosis ; Survival Rate

Tailored lipid nanoparticles (LNPs)-mediated small interfering RNA (siRNA) nanomedicines show promise in treating liver disease, such as acute liver injury (ALI) and non-alcoholic steatohepatitis (NASH). However, constructing LNPs that address biosafety concerns, ensure efficient delivery, and target specific hepatic subcellular fractions has been challenging. To evade above obstacles, we develop three novel self-degradable "gemini-like" ionizable lipids (SS-MA, SS-DC, SS-MH) by incorporating disulfide bonds and modifying the length of ester bond and tertiary amino head. Our findings reveal that the disulfide-bond-bridged LNPs exhibit reduction-responsive drug release, improving both biosafety and siRNA delivery efficiency. Furthermore, the distance of ester bond and tertiary amino head significantly influences the LNPs' pK _a, thereby affecting endosomal escape, hemolytic efficiency, absorption capacity of ApoE, uptake efficiency of hepatocytes and liver accumulation. We also develop the modified-mannose LNPs (M-LNP) to target liver macrophages specifically. The optimized M-MH_LNP@TNFα exhibits potential in preventing ALI by decreasing tumor necrosis factor α (TNFα) levels in the macrophages, while MH_LNP@DGAT2 could treat NASH by selectively degrading diacylglycerol O-acyltransferase 2 (DGAT2) in the hepatocytes. Our findings provide new insights into developing novel highly effective and low-toxic "gemini-like" ionizable lipids for constructing LNPs, potentially achieving more effective treatment for hepatic diseases.

Objective To explore a deep learning-based automatic bone age estimation model for elbow joint X-ray images of Chinese Han adolescents and children and evaluate its performance.Methods A total of 943(517 males and 426 females)elbow joint frontal view X-ray images of Chinese Han ado-lescents and children aged 6.00 to<16.00 years were collected from East,South,Central and North-west China.Three experimental schemes were adopted for bone age estimation.Scheme 1:Directly in-put preprocessed images into the regression model;Scheme 2:Train a segmentation network using"key elbow joint bone annotations"as labels,then input segmented images into the regression model;Scheme 3:Train a segmentation network using"full elbow joint bone annotations"as labels,then in-put segmented images into the regression model.For segmentation,the optimal model was selected from U-Net,UNet++and TransUNet.For regression,VGG16,VGG19,InceptionV2,InceptionV3,ResNet34,ResNet50,ResNet101 and DenseNet121 models were selected for bone age estimation.The dataset was randomly split into 80%(754 samples)for training and validation for model fitting and hyperparameter tuning,and 20%(189 samples)as an internal test set to test the performance of the trained model.An additional 104 elbow joint X-ray images from the same demographic and age group were col-lected and used as an external test set.Model performance was evaluated by comparing the mean ab-solute error(MAE),root mean square error(RMSE),accuracies within±0.7 years(P±0.7 years)and±1.0 years(P±1.0 years)between the estimated age and the actual age,and by drawing radar charts,scat-ter plots,and heatmaps.Results When segmented with Scheme 3,the UNet++model achieved good segmentation performance with a segmentation loss of 0.000 4 and an accuracy of 93.8%at a learning rate of 0.000 1.In the internal test set,the DenseNet121 model with Scheme 3 yielded the best results with MAE,P±0.7 years and P±1.0 years being 0.83 years,70.03%,and 84.30%,respectively.In the external test set,the DenseNet121 model with Scheme 3 also performed best,with an average MAE of 0.89 years and an average RMSE of 1.00 years.Conclusion When performing automatic bone age estima-tion using elbow joint X-ray images in Chinese Han adolescents and children,it is recommended to use the UNet++model for segmentation.The DenseNet121 model with Scheme 3 achieves optimal per-formance.Using segmentation networks,especially that trained with annotation areas encompassing the full elbow joint including the distal humerus,proximal radius,and proximal ulna,can improve the ac-curacy of bone age estimation based on elbow joint X-ray images.

Objective To explore a deep learning network model suitable for bone age estimation using shoulder joint X-ray images in Chinese Han adolescents.Methods A retrospective collection of 1 286 shoulder joint X-ray images of Chinese Han adolescents aged 12.0 to<18.0 years(708 males and 578 females)was conducted.Using random sampling,approximately 80%of the samples(1 032 cases)were selected as the training and validation sets for model learning,selection and optimization,and the other 20%samples(254 cases)were used as the test set to evaluate the model's generalization ability.The original single-channel shoulder joint X-ray images and dual-channel inputs combining original images with segmentation labels(manually annotated shoulder joint regions multiplied pixel-by-pixel with original images,followed by segmentation via the U-Net++network to retain only key shoulder joint region information)were respectively input into four network models,namely VGG16,ResNet18,ResNet50 and DenseNet121 for bone age estimation.Additionally,manual bone age estimation was con-ducted on the test set data,and the results were compared with the four network models.The mean absolute error(MAE),root mean square error(RMSE),coefficient of determination(R2),and Pear-son correlation coefficient(PCC)were used as main evaluation indicators.Results In the test set,the bone age estimation results of the four models with dual-channel input of shoulder joint X-ray images outperformed those with single-channel input in all four evaluation indicators.Among them,DenseNet121 with dual-channel input achieved best results with MAE of 0.54 years,RMSE of 0.82 years,R2 of 0.76,and PCC(r)of 0.88.Manual estimation yielded an MAE of 0.82 years,ranking second only to dual-channel DenseNet121.Conclusion The DenseNet121 model with dual-channel input combined with original images and segmentation labels is superior to manual evaluation results,and can effectively estimate the bone age of Chinese Han adolescents.