AIM:To investigate the effect of fibroblast growth factor 21(FGF21)on high glucose-induced oxidative stress in retinal pigment epithelial(RPE)cells and to clarify the underlying molecular mechanisms.METHODS:Single-cell sequencing data from the GEO database were analyzed to determine the expression profile of the FGF21 receptor FGFR1 in RPE cells. Human ARPE-19 cells were cultured and randomly assigned to control, high glucose(30 mmol/L), and high glucose+FGF21 analog treatment groups, with additional siFGFR1 and PI3K inhibitor groups. Cell viability in different treatment groups was assessed using CCK-8 assay, intracellular reactive oxygen species(ROS)levels were quantified using DCFH-DA fluorescent probing combined with immunofluorescence staining and flow cytometry. Transcriptome sequencing was performed on cells from the high glucose group and high glucose+FGF21 group to analyze the enrichment level of the PI3K/Akt signaling pathway. Western blotting was performed to detect phosphorylation levels of PI3K/Akt pathway components.RESULTS:Single-cell sequencing revealed specific expression of FGFR1 in RPE cells of retinal tissues from diabetic model mice. Under In vitro experiments, high glucose(30 mmol/L)exposure reduced ARPE-19 cell viability by 49.7% and increased ROS levels by approximately 2-fold. Whereas treatment with the FGF21 analog(60 ng/mL)restored cell viability and attenuated high glucose-induced ROS accumulation. Mechanistic studies demonstrated that FGFR1 knockdown inhibited the antioxidative stress of FGF21. Further validation of the molecular mechanism revealed that high glucose significantly suppressed the PI3K/Akt pathway activation(the levels of p-Akt and p-PI3K were decreased by 33.9% and 36.6%, respectively), while FGF21 effectively reversed this inhibitory effect and restored the expression of p-Akt and p-PI3K. Treatment with the PI3K inhibitor LY294002 inhibited the cytoprotective effect of FGF21 and significantly increased the ROS-positive cells, these findings confirm that PI3K/Akt signaling is indispensable downstream mechanism for FGF21 to exert its effects.CONCLUSION:FGF21 alleviates high glucose-induced oxidative stress and cellular injury in RPE cells by activating the PI3K/Akt signaling pathway through its receptor FGFR1.

As the core vehicle for preserving and transmitting traditional Chinese medicine（TCM） academic thought and clinical experience， the establishment of a robust quality evaluation system for TCM clinical case reports is a crucial component in the current standardization and modernization of TCM. Based on the practical experience of constructing the China Clinical Cases Library of Traditional Chinese Medicine by the China Association of Chinese Medicine， this study conducted a comprehensive analysis of critical challenges， including insufficient authenticity and unfocused evaluation criteria. It proposed a three-dimensional evaluation framework grounded in the structure-process-outcome logic， encompassing three dimensions of authenticity and standardization， characteristics and advantages， application and translational impact. This framework integrated 12 key evaluation indicators in a systematic manner. The model preserved the academic characteristics of TCM syndrome differentiation and treatment， while aligning with modern scientific research standards， achieving a balance between individualized TCM experience and standardized evaluation. Concurrently， this study provided theoretical foundations and methodological guidance for evaluating the quality of TCM clinical cases， contributing significantly to the inheritance of TCM knowledge， evidence-based practice， and the reform of talent evaluation mechanisms.

Objective:Exploring the association rules of factors influencing high hospitalization costs for cancer patients, providing references for hospitals to optimize medical cost management measures.Methods:In the inpatient case information system of a tertiary general hospital, the medical record homepages of inpatients in the DRG groups of the oncology department in 2022 were obtained. The upper four scores of hospitalization costs was used as the threshold for patient grouping. Patients with hospitalization costs≥this threshold were the high-cost group, while other patients were control group; 12 factors, including age, gender, and admission condition, etc, were considered as potential influencing factors of high hospitalization costs. FP-Growth and Apriori algorithms were used to excavate the potential association rules between the influencing factors of high hospitalization costs. Logistic regression was used to analyze the independent influencing factors of high hospitalization costs.Results:A total of 5 512 hospitalized patients were included, including 1 378 patients in the high-cost group. Thirteen validated strong association rules for factors influencing high hospitalization costs were obtained, of which the rule antecedents included age (≥70 years), number of days in hospital (≥7 days), other diagnoses (≥5), surgery, planned readmission, use of antibiotics, admission (general/critical), living admission score (61~99), level of care (level 1/level 2), non-day ward, criticality during hospitalisation. Logistic regression results showed that all nine influencing factors except gender, use of antibiotics, and readmission plans were independent influences on high hospitalization costs ( P<0.05). Conclusions:The joint application of FP-Growth and Apriori algorithm could effectively explore the association rules of high hospitalization costs for oncology patients. The early warning information mainly included the number of hospitalization days, the number of other diagnoses, surgeries, and so on. It was suggested that medical institutions can reasonably control the high hospitalization costs through clinical pathway management, diagnosis and treatment process reengineering, admission risk assessment, and multidisciplinary collaborative diagnosis and treatment strategies.

Objective:To analyze the influencing factors of China′s DRG payment system reform(DRG reform) and its hierarchical relationship, for references for the in-depth promotion of China′s medical insurance payment reform.Methods:Relevant literature on DRG reform in China from databases such as CNKI, Wanfang Database, Pubmed, etc, were obtained. Content analysis method was used to extract the influencing factors of DRG reform. The correlation between each influencing factor was determined through expert discussion. An interpretive structural model(ISM) was constructed to analyze the hierarchical relationship of factors influencing DRG reform.Results:After analysis, the influencing factors(12) of DRG reform in China were included such as medical level, hospital management, and medical staff′s cognition and behavior. Among them, the local situation was the deep-level factor affecting DRG reform, 9 factors such as data quality assurance and policy design/implementation were the middle-level factors, and patients′ interests/needs and disease grouping were the surface-level factors.Conclusions:There were many influencing factors on the reform of China′s DRG payment system. It was suggested that relevant management departments in various regions should focus on the actual situation of the locality, take data quality and policy design and implementation as the key points of reform, formulate a scientific and reasonable DRG grouping scheme, safeguard the interests of patients, so as to promote the deepening of DRG reform.

Objective To analyze the medication rules of traditional Chinese medicine in treating breast cancer based on real-world data mining.Methods Inpatients with breast cancer who received traditional Chinese medicine treatment at the Affiliated Hospital of Chengdu University of Traditional Chinese Medicine from January 2017 to December 2021 were selected.Python 3.10 software was used to mine traditional Chinese medicine prescription data;SPSS 23.0 software was applied for descriptive analysis,and systematic cluster analysis was performed on high-frequency drugs.Results A total of 3026 consultation records of inpatients with breast cancer were collected.The main traditional Chinese medicine syndrome diagnosis of"predominantly liver depression and Qi stagnation"accounted for 60.94％of the total consultations.A total of 240 kinds of traditional Chinese medicine were used,with a cumulative frequency of 35 462 times.Among them,29 kinds of traditional Chinese medicine such as Danggui,Fuling,Baizhu,Chaihu had a cumulative usage frequency exceeding 300 times.Regarding the four natures of drugs,cold-natured(43.55％),warm-natured(30.05％),and neutral-natured(23.34％)drugs were predominant;In terms of five flavors,sweet(46.12％),bitter(30.91％),and pungent(20.02％)were the main ones.The most frequently used drugs were tonifying herbs(32.77％),followed by heat-clearing herbs(15.96％)and phlegm-resolving herbs(14.71％).Systematic cluster analysis yielded 7 groups of drug combinations.Conclusion In real-world clinical practice,traditional Chinese medicine for breast cancer mainly uses tonifying herbs,reflecting the traditional Chinese medicine principle of"strengthening healthy Qi and cultivating the root"in treating tumors.The four natures and five flavors of drugs follow syndrome differentiation and the combination of cold and heat.The clustered drug combinations have extensive therapeutic effects,covering various syndromes of breast cancer at different stages,which can provide a reference for clinical medication.

An effective method for simultaneously detecting four semivolatile earthy-musty odors in freshwater fish by gas chromatography-mass spectrometry(GC-MS)was developed.The concurrent extraction of geosmin(GSM),2-methylisoborneol(MIB),2-isopropyl-3-methoxypyrazine(IPMP),and 2-isobutyl-3-methoxypyrazine(IBMP)in fish tissue was conducted with n-hexane.The optimized QuEChERS material was implemented,and it was found that C18,primary secondary amine(PSA)and MgSO4 could adsorb the target analytes in n-hexane.So only the graphitized carbon black(GCB)could be used to purify the extraction.The adsorption rates of different materials for the four kinds of odors materials were explored in n-hexane and ethyl acetate.The experimental results revealed that the adsorption rates of silica for the four targets were 99.5%-100%in n-hexane and 0.7%-5.0%in ethyl acetate respectively.Then the silica solid phase extraction(SPE)method was utilized to eluent the compounds using 1.0 mL n-hexane/ethyl acetate in different proportions.The results of the comparative analysis demonstrated that n-hexane/ethyl acetate(4∶1,V/V)was the optimized eluent.Based on the obtained results,n-hexane extraction and GCB purification combined with silica SPE were used to isolate GSM,MIB,IPMP and IBMP from fish and the method was validated.It was found that the method showed good linearity in the range of 0.5-200 ng/mL,and with detection limits of 0.6 μg/kg for GSM and MIB,0.2 μg/kg for IPMP and IBMP.The limits of quantitation(LOQ)were 1.0 μg/kg for GSM and MIB,0.6 μg/kg for IPMP and IBMP.Good recoveries(77.5%-112.0%)and relative standard deviations(1.56%-9.42%)were also obtained.The use of silica SPE greatly mitigated the issue that the off-flavor compounds were easily lost in the gas blowing concentration process.There was no cross contamination in this method because the sample pretreatments were conducted separately,which was different with the most commonly used HS-SPME method for detecting semi-volatile substances.The sensitivity of this method was high enough to produce good quantitative results below the odor thresholds of the examined off-flavor compounds.

BACKGROUND:With aging,the regenerative capacity and differentiation function of bone marrow mesenchymal stem cells progressively decline,reducing bone tissue repair efficacy.Thus,identifying bone marrow mesenchymal stem cell subpopulations with enhanced osteogenic potential is of significant importance for advancing bone tissue engineering.OBJECTIVE:To evaluate the osteogenic differentiation potential differences between STRO-1 positive and negative bone marrow mesenchymal stem cells under osteogenic induction conditions.METHODS:SD rat bone marrow mesenchymal stem cells were isolated and cultured.The expression of CD29,CD45,CD90,and STRO-1 was identified via flow cytometry and immunofluorescence.Immunomagnetic cell sorting was used to separate STRO-1 positive and negative bone marrow mesenchymal stem cells.The cells of two groups were subjected to osteogenic induction for 7 and 14 days.qRT-PCR and western blotting were performed to analyze differences in osteogenesis-related gene expression(Collagen I,Runt-related transcription factor 2,osteoprotegerin,and osteocalcin)and protein levels.Alizarin red staining and alkaline phosphatase staining were used to observe calcium nodule formation.RESULTS AND CONCLUSION:Flow cytometry showed high expression levels of CD29 and CD90 and low expression of CD45,with a positive STRO-1 expression rate of 12.8％.Immunofluorescence results were consistent with those of flow cytometry.After magnetic cell sorting,STRO-1 positive cells demonstrated a higher colony formation rate than STRO-1 negative cells.On day 14,STRO-1 positive cells showed significantly higher osteogenic differentiation potential than on day 7,with significantly elevated osteogenesis-related marker levels compared to STRO-1 negative cells(P＜0.01).The findings indicate that STRO-1 positive bone marrow mesenchymal stem cells exhibit significant advantages in osteogenic potential,providing a theoretical basis for their selection as ideal seed cells in bone tissue engineering.In future applications,they may represent a promising therapeutic approach for bone defect repair.

BACKGROUND:With aging,the regenerative capacity and differentiation function of bone marrow mesenchymal stem cells progressively decline,reducing bone tissue repair efficacy.Thus,identifying bone marrow mesenchymal stem cell subpopulations with enhanced osteogenic potential is of significant importance for advancing bone tissue engineering.OBJECTIVE:To evaluate the osteogenic differentiation potential differences between STRO-1 positive and negative bone marrow mesenchymal stem cells under osteogenic induction conditions.METHODS:SD rat bone marrow mesenchymal stem cells were isolated and cultured.The expression of CD29,CD45,CD90,and STRO-1 was identified via flow cytometry and immunofluorescence.Immunomagnetic cell sorting was used to separate STRO-1 positive and negative bone marrow mesenchymal stem cells.The cells of two groups were subjected to osteogenic induction for 7 and 14 days.qRT-PCR and western blotting were performed to analyze differences in osteogenesis-related gene expression(Collagen I,Runt-related transcription factor 2,osteoprotegerin,and osteocalcin)and protein levels.Alizarin red staining and alkaline phosphatase staining were used to observe calcium nodule formation.RESULTS AND CONCLUSION:Flow cytometry showed high expression levels of CD29 and CD90 and low expression of CD45,with a positive STRO-1 expression rate of 12.8％.Immunofluorescence results were consistent with those of flow cytometry.After magnetic cell sorting,STRO-1 positive cells demonstrated a higher colony formation rate than STRO-1 negative cells.On day 14,STRO-1 positive cells showed significantly higher osteogenic differentiation potential than on day 7,with significantly elevated osteogenesis-related marker levels compared to STRO-1 negative cells(P＜0.01).The findings indicate that STRO-1 positive bone marrow mesenchymal stem cells exhibit significant advantages in osteogenic potential,providing a theoretical basis for their selection as ideal seed cells in bone tissue engineering.In future applications,they may represent a promising therapeutic approach for bone defect repair.

Objective:To screen differentially expressed long non-coding RNA (lncRNA) in exosomes of the brain extracellular space in mice with traumatic brain injury (TBI) and explore their biological roles in brain injury repair.Methods:Twenty-four C57BL/6J male mice were randomly divided into TBI group and control group with 12 in each group. The TBI group was treated with drill craniostomy followed by hydraulic impact while the control group was treated with drill craniostomy only. The brain tissue samples were collected at 3 hours after TBI. The exosomes from the brain extracellular space were isolated with papain digestion combined with an exosome isolation kit, the appearance of the exosomes was observed by phosphotungstic acid negative staining under a transmission electron microscope, and western blot was used to identify the exosomal marker proteins cluster of differentiation 63 (CD63), tumor susceptibility gene 101 (TSG101) and heat shock protein 70 (HSP70). After exosome identification, RNA libraries were constructed and subjected to library quality control, whole transcriptome sequencing was performed to detect, characterize and annotate lncRNA. Subsequently, the RNA high-throughput sequencing results were verified by randomly selecting five differentially expressed lncRNA. Moreover, the accuracy of the RNA high-throughput sequencing results was verified by qRT-PCR. The differentially expressed lncRNA were screened afterwards. Finally, bioinformatics analysis of differentially expressed lncRNA was performed, i.e., gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathway analysis were performed based on differentially expressed lncRNA-related genes.Results:(1) Identification of exosomes: the exosomes were cup-shaped with clear and intact membranes and diameters of 30-100 nm. Western blot confirmed the presence of typical exosome markers of the exosomes, such as CD63, TSG101, and HSP70, as well as astrocyte marker glial fibrillary acidic protein (GFAP), all of which were found in the brain tissue. (2) Validation of lncRNA high-throughput sequencing data accuracy: the 4/5 sequencing accuracy indicated that the sequencing results of lncRNAs were largely reliable. (3) Screening of differentially expressed exosomal lncRNAs after TBI: compared with the control group, a total of 442 lncRNA were significantly differentially expressed in the TBI group, including 255 up-regulated and 187 down-regulated lncRNA. (4) Bioinformatics analysis of differentially expressed lncRNAs after TBI: GO analysis showed that the differentially expressed lncRNA mainly involved in cell localization, cognition, learning or memory, were closely related to the composition of the nucleus and organelles and the binding processes of proteins, oxygen, and kinases. KEGG pathway analysis showed that upregulated lncRNA were mainly enriched in the mitogen activated protein kinase (MAPK) signaling pathway, while downregulated lncRNA were mainly enriched in the endocytosis pathway. The pathway relation network showed that MAPK signaling pathway played a key role in downstream regulation.Conclusions:There are significant differences in lncRNA expression profiles of the exosomes in the extracellular spaces of the brain cells in mice with TBI, and the differentially expressed lncRNA may mediate the process of neuronal repair, body prognosis and learning ability recovery after TBI by participating in MAPK and endocytosis signaling pathways.

Objective:Exploring the association rules of factors influencing high hospitalization costs for cancer patients, providing references for hospitals to optimize medical cost management measures.Methods:In the inpatient case information system of a tertiary general hospital, the medical record homepages of inpatients in the DRG groups of the oncology department in 2022 were obtained. The upper four scores of hospitalization costs was used as the threshold for patient grouping. Patients with hospitalization costs≥this threshold were the high-cost group, while other patients were control group; 12 factors, including age, gender, and admission condition, etc, were considered as potential influencing factors of high hospitalization costs. FP-Growth and Apriori algorithms were used to excavate the potential association rules between the influencing factors of high hospitalization costs. Logistic regression was used to analyze the independent influencing factors of high hospitalization costs.Results:A total of 5 512 hospitalized patients were included, including 1 378 patients in the high-cost group. Thirteen validated strong association rules for factors influencing high hospitalization costs were obtained, of which the rule antecedents included age (≥70 years), number of days in hospital (≥7 days), other diagnoses (≥5), surgery, planned readmission, use of antibiotics, admission (general/critical), living admission score (61~99), level of care (level 1/level 2), non-day ward, criticality during hospitalisation. Logistic regression results showed that all nine influencing factors except gender, use of antibiotics, and readmission plans were independent influences on high hospitalization costs ( P<0.05). Conclusions:The joint application of FP-Growth and Apriori algorithm could effectively explore the association rules of high hospitalization costs for oncology patients. The early warning information mainly included the number of hospitalization days, the number of other diagnoses, surgeries, and so on. It was suggested that medical institutions can reasonably control the high hospitalization costs through clinical pathway management, diagnosis and treatment process reengineering, admission risk assessment, and multidisciplinary collaborative diagnosis and treatment strategies.