OBJECTIVES: To investigate the expression of apolipoprotein C1 (APOC1) in papillary thyroid carcinoma (PTC) and its effects on proliferation and apoptosis of PTC cells. METHODS: The expression level of APOC1 in PTC and its impact on prognosis were analyzed using GEPIA 2 and Kaplan-Meier databases. Immunohistochemistry (IHC) and Western blotting were used to detect the expression of APOC1 in PTC and adjacent tissues and in 3 PTC cell lines and normal thyroid Nthyori 3-1 cells. In TPC-1 and BCPAP cells, the effect of Lipofectamine 2000-mediated transfection with APOC1 siRNA or an APOC1-overexpressing plasmid on cell growth and colony formation ability were examined by observing the growth curves and using colony-forming assay. The changes in cell cycle and apoptosis of the transfected cells were analyzed with flow cytometry. RT-qPCR and Western blotting were used to detect the changes in expressions of P21, P27, CDK4, cyclin D1, Bcl-2, Bax, caspase-3 and caspase-9 and the key proteins in the JAK2/STAT3 signaling pathway. RESULTS: APOC1 expression was significantly higher in PTC tissues and the 3 PTC cell lines than in the adjacent tissues and Nthyori 3-1 cells, respectively. In TPC-1 and BCPAP cells, APOC1 knockdown obviously reduced cell proliferative activity, increased the percentage of G0/G1 phase cells, lowered the percentages of S and G2 phase cells, promoted cell apoptosis, and downregulated mRNA and protein expression levels of CDK4, cyclin D1 and Bcl-2 and the protein levels of p-JAK2 and p-STAT3. APOC1 overexpression in the cells produced the opposite effects on cell proliferation, apoptosis, cell cycle and the mRNA and protein expressions. The application of AG490, a JAK2 inhibitor, strongly attenuated APOC1 overexpression-induced activation of the JAK2/STAT3 signaling pathway in BCPAP cells. CONCLUSIONS APOC1 overexpression promotes proliferation and inhibits apoptosis of PTC cells possibly by activating the JAK2/STAT3 signaling pathway and accelerating cell cycle progression.
Humans ; Apoptosis ; Cell Proliferation ; STAT3 Transcription Factor/metabolism* ; Signal Transduction ; Janus Kinase 2/metabolism* ; Thyroid Neoplasms/pathology* ; Thyroid Cancer, Papillary ; Cell Line, Tumor ; Carcinoma, Papillary

Cemental tear is a rare and indetectable condition unless obvious clinical signs present with the involvement of surrounding periodontal and periapical tissues. Due to its clinical manifestations similar to common dental issues, such as vertical root fracture, primary endodontic diseases, and periodontal diseases, as well as the low awareness of cemental tear for clinicians, misdiagnosis often occurs. The critical principle for cemental tear treatment is to remove torn fragments, and overlooking fragments leads to futile therapy, which could deteriorate the conditions of the affected teeth. Therefore, accurate diagnosis and subsequent appropriate interventions are vital for managing cemental tear. Novel diagnostic tools, including cone-beam computed tomography (CBCT), microscopes, and enamel matrix derivatives, have improved early detection and management, enhancing tooth retention. The implementation of standardized diagnostic criteria and treatment protocols, combined with improved clinical awareness among dental professionals, serves to mitigate risks of diagnostic errors and suboptimal therapeutic interventions. This expert consensus reviewed the epidemiology, pathogenesis, potential predisposing factors, clinical manifestations, diagnosis, differential diagnosis, treatment, and prognosis of cemental tear, aiming to provide a clinical guideline and facilitate clinicians to have a better understanding of cemental tear.
Humans ; Dental Cementum/injuries* ; Consensus ; Diagnosis, Differential ; Cone-Beam Computed Tomography ; Tooth Fractures/therapy*

Objective:To investigate the targets and mechanisms of cycloastragenol in ameliorating azithromycin-induced drug-induced liver injury(DILI)based on network pharmacology and in vitro experiment validation.Methods:Potential targets of cycloastragenol and DILI were predicted using databases.The common and key targets were screened and subjected to GO and KEGG enrichment analyses,as well as molecular docking validation.Primary hepatocytes from C57BL/6 mice were isolated.The optimal concentration and time for azithromycin-induced DILI in mouse primary hepatocytes were determined using CCK8 and ROS assays.The expression of genes and proteins such as NF-κB p65,p-NF-κB p65,AMPKα,and p-AMPKα was assessed using RT-qPCR and Western blot to evaluate the intervention effect of cycloastragenol(10-50 μmol/L).Results:Network pharmacology analysis identified 10 key genes related to cycloastragenol's improvement of DILI,including heat shock protein 90AA1(HSP90AA1),matrix metalloproteinase 2(MMP2),etc.GO enrichment analysis suggested that cycloastragenol primarily regulates biological processes such as membrane potential and chemical synaptic transmission,and affects cellular components such as neuronal cell bodies and distal axons,and related kinase activities.KEGG enrichment analysis showed that it mainly exerts intervention effects through neuro-signaling pathways and IL-17 signaling pathways.Molecular docking demonstrated strong binding of cycloastragenol to HSP90AA1,MMP2,NF-κB p65,AMPKα,nuclear factor erythroid 2-related factor 2(Nrf2),heme oxygenase 1(HO-1),and NAD(P)H:quinone oxidoreductase 1(NQO1),with a binding energy≤-5.0 kcal/mol for Nrf2.In vitro experiments showed that azithromycin(50 μmol/L,12 h)significantly reduced hepatocyte viability and increased ROS levels(P＜0.01).Different concentrations of cycloastragenol significantly improved the activity of mouse primary hepatocytes,reduced the generation of intracellular ROS,downregulated the phosphorylation level of NF-κB p65,and upregulated the mRNA and protein levels of AMPKα,Nrf2,HO-1,NQO1(P＜0.05).Conclusions:Cycloastragenol may alleviate azithromycin-induced hepatocyte oxidative stress and inflammation by inhibiting NF-κB phosphorylation and activating the AMPK/Nrf2/HO-1/NQO1 pathway,with its mechanism likely closely linked to targeting Nrf2.However,the complex mechanisms of DILI may involve additional unverified pathways.Therefore,further studies are necessary to validate the efficacy and safety of cycloastragenol in animal models.

Objective To determine the serum level of quantitative hepatitis B core antibody(qAnti-HBc)in decompensated hepatitis B cirrhosis patients with normal international normalized ratio(INR),and to investigate its prognostic value in this target population.Methods A total of 120 decompensated hepatitis B cirrhosis patients with normal INR who were diagnosed and treated in Tianjin Third Central Hospital from October 1,2018 to April 1,2021 were enrolled.Baseline indicators were collected,the serum level of qAnti-HBc was measured,and the prognosis was followed up.According to the prognosis,the patients were divided into survival group and death group.The independent-samples t test or the Mann-Whitney U test was used for comparison of continuous data between two groups,and the chi-square test was used for comparison of categorical data between groups.Univariate and multivariate Cox regression analyses were used to investigate the candidate variables affecting the prognosis and establish a prognostic model for this population,and the receiver operating characteristic(ROC)curve was plotted.Results The patients enrolled were followed up for 32.17±13.09 months,and there were 99 patients(82.5%)in the survival group and 21 patients(17.5%)in the death group.There were significant differences between the survival group and the death group in sex(χ2=2.151,P=0.014),age(t=-3.218,P=0.003),total bilirubin(Z=-0.901,P=0.027),albumin(t=3.353,P=0.001),and Child-Pugh class(χ2=1.144,P=0.010).The univariate and multivariate Cox regression analyses showed that serum qAnti-HBc(hazard ratio[HR]=0.57,95%confidence interval[CI]:0.32-1.00,P=0.043),age(HR=1.06,95%CI:1.00-1.12,P=0.044),sex(HR=3.82,95%CI:1.46-10.00,P=0.006),platelet count(HR=0.98,95%CI:0.97-1.00,P=0.037),and albumin(HR=0.86,95%CI:0.79-0.95,P=0.002)were independent risk predictive factors for the prognosis of decompensated hepatitis B cirrhosis patients with normal INR.Based on these factors,a predictive model was established as h(t,x)/h0(t)=exp(1.34X1+0.06X2-0.14X3-0.02X4-0.57X5),where X1=sex,X2=age,X3=albumin,X4=platelet count,X5=qAnti-HBc.This predictive model had an area under the ROC curve of 0.842,with a sensitivity of 0.79,a specificity of 0.73,and a C-index of 0.85.Conclusion In decompensated hepatitis B cirrhosis patients with normal INR(0.8-1.2),serum qAnti-HBc is one of the independent risk predictive factors for death,and the predictive model established based on the combination of serum qAnti-HBc and other indicators can effectively predict the prognosis of patients.

ObjectiveTo investigate the epidemiological feature of Mpox infection and genetic characteristics of Mpox viruses (MPXVs), so as to understand the etiological evolution of the pathogen. MethodsThe cases infected with MPXVs were originated from Changning District, Shanghai from July 20 to August 24 in 2023. Epidemiological investigations were conducted, and throat swabs, anal swabs, or vesicle fluid were collected for MPXVs nucleic acid testing. High-throughput sequencing was performed using Miniseq of the Illumina sequencing platform, and thereafter the sequences were concatenated and analyzed using the online analysis tool Nextclade. An evolutionary tree was constructed using the MEGA 11 software. ResultsAll 8 cases were male, with an average age of (35.76±7.00) years. Among them, 6 cases were identified through active hospital visits, and 2 cases were discovered during contact tracing for Mpox cases. Within the 21 days preceding the disease onset, all cases had male-male sexual behaviors, and the incubation period ranged from 6 to 10 days. 3 cases had a history of sexually transmitted diseases (STDs). MPXVs nucleic acid testing indicated that the detection rate of MPXVs was found to be 25.00% for throat swabs, 87.50% for anal swabs, and 100.00% for vesicle fluid, with statistically significant differences (χ²=11.052, P=0.004). Sequencing analyses using the online tool Nextclade indicated that all 8 MPXVs belonged to the West African clade Ⅱb, 4 MPXVs were classified as C.1 sub-lineages, and 4 MPXVs were identified as C.1.1 sub-lineages. Phylogenetic analysis using MEGA 11 indicated that 5 MPXVs were classified as Lineage C.1.1, closely related to the prevalent strains in Portugal and other European regions. ConclusionThe MPXVs sequences from Changning District are clssified into clade Ⅱb, lineage C.1.1. The detection rates of vesicle fluid and anal swabs for MPXVs are significantly higher than that of throat swabs.

Objective:This study aims to develop a rapid identification technique for various genotypes of extended-spectrum β-lactamase (ESBL) producing Escherichia coli using matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS) in conjunction with machine learning algorithms. Methods:A total of 158 Escherichia coli strains were isolated from the clinical laboratory of the First Hospital of Jilin University from August 2018 to December 2022. Polymerase chain reaction (PCR) was employed to detect the CTX-M-1, CTX-M-8, CTX-M-9, and SHV genes. Mass spectral data of the bacterial strains were acquired by MALDI-TOF MS with a cooperative matrix of (E)-propyl α-cyano-4-hydroxycinnamate (CHCA-C3). Models based on random forest (RF), logistic regression (LR), and support vector machine (SVM) algorithms were constructed. The performance of the constructed models was evaluated using metrics including accuracy, sensitivity, specificity, and the area under the receiver operating characteristic curve (AUC). Mass spectral peaks exhibiting sensitivity and specificity exceeding 80% in the models were designated as characteristic peaks. To validate the efficacy of the cooperative matrix of CHCA-C3, clinical isolates of ESBL-producing Escherichia coli were analyzed by MALDI-TOF MS using the conventional CHCA matrix for comparative purposes. Results:Among the 158 strains of Escherichia coli, 91 strains produced ESBL, all of which were CTX-M genotype. The AUC values for the respective models were as follows: CTX-M-1 genotype exhibited AUC values of 0.98 for LR, 1.00 for RF, and 0.73 for SVM; CTX-M-9 genotype exhibited AUC values of 0.93 for LR, 0.99 for RF, and 0.76 for SVM; for CTX-M-8, all models achieved an AUC of 1.00, indicating excellent classification performance with respect to accuracy, specificity, and sensitivity. The characteristic mass spectral peaks associated with each genotype included: CTX-M-1 genotype at m/z 6 390; CTX-M-8 genotype at m/z 5 224, m/z 5 393, and m/z 9 021; CTX-M-9 genotype at m/z 5 161 and m/z 5 273. In the MALDI-TOF MS analysis conducted with the conventional CHCA matrix, the characteristic peak at m/z 9 021 for CTX-M-8 was the only one detected, with the characteristic peaks for CTX-M-1 and CTX-M-9 remaining undetected. Conclusion:The application of cooperative matrix of CHCA-C3 in conjunction with MALDI-TOF MS and machine learning algorithms facilitates the rapid and precise identification of extended-spectrum β-lactamase (ESBL)-producing Escherichia coli. This approach offers a feasible solution for evidence-based clinical therapy and the control of healthcare-associated infections.

Objective·To analyze the clinicopathologic characteristics,gene mutation profile,and prognostic factors of patients with adrenal diffuse large B-cell lymphoma(DLBCL).Methods·From March 2002 to December 2022,a total of 105 patients with adrenal DLBCL admitted to Ruijin Hospital,Shanghai Jiao Tong University School of Medicine were retrospectively analyzed for their clinicopathological data,survival outcomes,and prognostic factors.Patients'gene mutation profiles were evaluated by targeted sequencing of 152 lymphoma-related genes.Results·The median age of the patients was 62(15?82)years and the male-to-female ratio was 2.3∶1.Among them,63 patients(60.0%)were over 60 years old,22 patients(21.0%)had an Eastern Cooperative Oncology Group(ECOG)performance status of two or higher,87 patients(82.9%)were staged Ann Arbor Ⅲ?Ⅳ,92 patients(87.6%)had elevated serum lactate dehydrogenase(LDH)levels(above the upper limit of reference),84 patients(80.0%)had extranodal invasion in at least two organs,67 patients(63.8%)were of non-germinal center B-cell(non-GCB)origin,and 95 patients(90.5%)had an international prognosis index(IPI)scored over 2.With a median follow-up of 28.3(0.7?191.9)months,the estimated 2-year overall survival(OS)rate and progression-free survival(PFS)rate were 68.3%and 53.1%,respectively.The estimated 5-year OS rate and PFS rate were 52.6%and 44.0%,respectively.Among 93 patients who could be evaluated for clinical outcomes,62(66.7%)got a complete response(CR).Univariate analysis and multivariate Cox analysis revealed that age over 60 years was an adverse prognostic factor for PFS,and ECOG performance status of two or higher was an adverse prognostic factor for both OS and PFS.Targeted gene sequencing in 46 adrenal diffuse DLBCL patients showed high mutation frequencies in lysine methyltransferase 2D(KMT2D;n=17,37%),Pim-1 proto-oncogene,serine/threonine kinase(PIM1;n=17,37%),MYD88 innate immune signal transduction adaptor(MYD88;n=15,33%),CD79b molecule(CD79B;n=13,28%),and BTG anti-proliferation factor 2(BTG2;n=10,22%).Conclusion·Age over 60 years is an adverse prognostic factor for PFS,and ECOG performance status of two or higher is an adverse prognostic factor for both OS and PFS in patients with adrenal DLBCL.Patients exhibited high frequencies of KMT2D,PIM1,MYD88,CD79B,and BTG2 mutations,as well as an increased proportion of the MCD-like subtype.

Objective:To evaluate the cumulative live birth rate (CLBR) and cost-effectiveness of fixed versus adjusted follicle-stimulation hormone (FSH) dosages in infertile women with different ovarian responses during their first assisted reproductive technology (ART) cycle.Methods:A retrospective real-world cohort study was conducted on 5 419 infertile women who underwent their first ART treatment at the Department of Reproductive Medicine of the First Affiliated Hospital of Nanjing Medical University between January 2013 and December 2017. All patients received an individualized starting dosage of gonadotropin. Based on whether FSH dosages were adjusted during controlled ovarian stimulation (COS), patients were divided into fixed-dosage group ( n=2 061) and adjusted-dosage group ( n=3 358). Clinical outcomes and FSH cost-effectiveness were compared between the two groups across different ovarian response groups, with CLBR as the primary outcome. Propensity score matching (PSM) and multivariable logistic regression were used to adjust for potential confounders. Results:FSH dosage adjustments were found in 62.0% (3 358/5 419) of cycles during COS. After PSM, baseline characteristics were comparable between the two groups (all P>0.05). After adjusting for confounders using multivariable logistic regression, FSH dosage adjustment was not significantly associated with CLBR ( OR=1.06, 95% CI: 0.94-1.20, P=0.332). Compared with the adjusted-dosage group, the fixed-dosage group showed no significant differences in CLBR in poor-, normal-, and high-responder groups (all P>0.05). The incidence of ovarian hyperstimulation syndrome (OHSS) did not differ significantly between the two groups ( P>0.05). In poor-, normal-, and high-responder groups, the total FSH dosages in the fixed-dose group [1 350 (375, 1 825) U, 1 200 (375, 1 500) U and 525 (375, 1 128) U, respectively] were significantly lower than those in the adjusted-dose group [1 875 (1 425, 2 294) U, P=0.001; 1 425 (450, 1 875) U, P<0.001; 600 (375, 1 425) U, P=0.020]. Similarly, average FSH costs in different ovarian response groups in the fixed-dosage group [4 725.0 (1 312.5, 6 387.5) yuan, 4 200.0 (1 312.5, 5 250.0) yuan and 1 837.5 (1 312.5, 3 947.3) yuan, respectively] were significantly lower than those in the adjusted-dosage group [6 562.5 (4 987.5, 8 028.1) yuan, P=0.001; 4 987.5 (1 575.0, 6 562.5) yuan, P<0.001; 2 100.0 (1 312.5, 4 987.5) yuan, P=0.020]. For normal-responders, the FSH cost per high-quality embryo in the fixed-dosage group [1 365.0 (875.0, 2 537.5) yuan] was significantly lower than that in the adjusted-dosage group [2 056.3 (1 268.8, 3 412.5) yuan, P<0.001]. Conclusion:FSH dosage adjustment during COS is not associated with CLBR or the incidence of OHSS. However, the fixed-dose group exhibited lower total FSH dosages and costs across different ovarian response populations. In the context of ART being covered by medical insurance, fixed FSH dosage may represent a more cost-effective ovarian stimulation protocol.

Objective:To investigate the application value of risk prediction model for acute kidney injury (AKI) after donation of cardiac death (DCD) liver transplantation based on machine learning algorithm.Methods:The retrospective cohort study was conducted. The clinicopathological data of 1 001 pairs of DCD liver transplant donors and recipients at five hospitals, including The First Affiliated Hospital of Zhejiang University School of Medicine et al, in the Chinese Liver Transplan-tation Registry from January 2015 to December 2023 were collected. Of the donors, there were 825 males and 176 females. Of the recipients, there were 806 males and 195 females, aged 52 (range, 18-75)years. There were 281 recipients included using oversampling technique, and all 1 282 recipients were divided to the training set of 897 recipients and the validation set of 385 recipients by a ratio of 7∶3 using computer-generated random numbers. Seven prediction models, including Random Forest (RF), Extreme Gradient Boosting (XGBoost), Support Vector Machine (SVM), Logistic Regression (LR), Decision Tree (DT), K-Nearest Neighbors (KNN), and Categorical Boosting (CatBoost), were constructed for AKI after liver transplantation based on machine learning algorithm. Observation indicators: (1) comparison of clinicopathological characteristics between recipients with and without AKI and donors; (2) follow-up and survival of recipients with and without AKI; (3) construction and validation of nomogram prediction model of AKI after liver transplantation; (4) construction and validation of machine learning prediction model of AKI after liver transplantation. Comparison of measurement data with normal distribution between groups was conducted using the independent sample t test. Comparison of measurement data with skewed distribution between groups was conducted using the Mann-Whitney U test, and comparison among groups was conducted using the Kruskal-Wallis H test. Comparison of count data between groups was conducted using the chi-square test or corrected chi-square test. Kaplan-Meier method was used to calculate survival rates and plot survival curves. Logistic regression model was performed for univariate and multivariate analyses. The receiver operating characteristic (ROC) curve was plotted to calculate area under curve (AUC) and 95% confidence interval ( CI). The performance of prediction model was evaluated using DeLong test, accuracy, sensitivity, specificity. The calibration curve was plotted to evaluate the performance of predicted probability and actual probability. The interpretability analysis of machine learning algorithm and SHapley Additive exPlanations was used to explain the model decision separately. Results:(1) Comparison of clinicopathological characteristics between recipients with and without AKI and donors. Of 1 001 recipients, there were 360 cases with AKI and 641 cases without AKI after liver transplantation. There were significant differences in body mass index (BMI), hepatic encepha-lopathy, hepatitis B surfact antigen (HBsAg), hepatorenal syndrome (HRS) and donor diabetes, donor blood urea nitrogen, donor alanine aminotransferase, donor aspartate aminotransferase, mass of graft, volume of blood loss during liver transplantation, warm ischema time of donor liver, and operation time between recipients with and without AKI ( Z=-4.337, χ2=9.751, 9.088, H=11.142, χ2=5.286, Z=-3.360, -2.539, -3.084, -1.730, -3.497, -1.996, -2.644, P<0.05). (2) Follow-up and survival of recipients with and without AKI. All the 1 001 recipients received follow-up. The recipients with AKI after liver transplantation were followed up for 18.6(range, 0-102.3)months, and recipients without AKI after liver transplantation were followed up for 31.9(range, 0.1-105.5)months. The 1-, 3-, and 5-year overall survival rates were 72.1%, 63.5%, and 59.3% of recipients with AKI, versus 86.7%, 76.7%, and 72.5% of recipients without AKI, respectively, showing a significant difference in overall survival between them ( χ2=26.028, P<0.05). (3) Construction and validation of nomogram predic-tion model of AKI after liver transplantation. Results of multivariate analysis showed that recipient BMI, recipient creatinine, recipient HBsAg, recipient HRS, donor blood urea nitrogen, donor crea-tinine, anhepatic phase and volume of blood loss during liver transplantation were independent risk factors for AKI of recipients after liver transplantation ( odds ratio=1.113, 0.998, 0.605, 1.580, 1.047, 0.998, 1.006, 1.157, 95% CI as 1.070-1.157, 0.996-1.000, 0.450-0.812, 1.021-2.070, 1.021-1.074, 0.996-0.999, 1.000-1.012, 1.045-1.281, P<0.05). The nomogram prediction model of AKI after liver transplantation was constructed based on the results of multivariate analysis. Results of ROC curve showed that the AUC of 0.666 (95% CI as 0.637-0.696). (4) Construction and validation of machine learning prediction model of AKI after liver transplantation. Based on the Lasso regression analysis, seven machine learning algorithm prediction models, including RF, XGBoost, SVM, LR, DT, KNN, and CatBoost, were constructed, with ROC curves of the validation set plotted. The AUC of above models were 0.863, 0.841, 0.721, 0.637, 0.620, 0.708, 0.731, accuracies were 0.764, 0.782, 0.701, 0.592, 0.605, 0.605, 0.681, sensitivities were 0.764, 0.789, 0.719, 0.588, 0.694, 0.694, 0.704, specificities were 0.763, 0.774, 0.683, 0.597, 0.511, 0.511, 0.656, respectively. Delong test showed that the RF model with the highest AUC of 0.863(95% CI as 0.828-0.899). Calibration curve analysis showed the predicted probability closest to the actual probability of RF model, indicating the model with a good validation value. Further sorting of SHAP of different clinical factors based on RF model showed that recipient BMI, donor blood urea nitrogen, volume of blood loss during liver transplantation, donor age had large effects on the output outcomes. Conclusion:The nomogram prediction model and seven machine learning algorithm prediction models for AKI after DCD liver transplantation are constructed, and the RF model based on machine learning has a better predictive performance.

Objective:To evaluate the cumulative live birth rate (CLBR) and cost-effectiveness of fixed versus adjusted follicle-stimulation hormone (FSH) dosages in infertile women with different ovarian responses during their first assisted reproductive technology (ART) cycle.Methods:A retrospective real-world cohort study was conducted on 5 419 infertile women who underwent their first ART treatment at the Department of Reproductive Medicine of the First Affiliated Hospital of Nanjing Medical University between January 2013 and December 2017. All patients received an individualized starting dosage of gonadotropin. Based on whether FSH dosages were adjusted during controlled ovarian stimulation (COS), patients were divided into fixed-dosage group ( n=2 061) and adjusted-dosage group ( n=3 358). Clinical outcomes and FSH cost-effectiveness were compared between the two groups across different ovarian response groups, with CLBR as the primary outcome. Propensity score matching (PSM) and multivariable logistic regression were used to adjust for potential confounders. Results:FSH dosage adjustments were found in 62.0% (3 358/5 419) of cycles during COS. After PSM, baseline characteristics were comparable between the two groups (all P>0.05). After adjusting for confounders using multivariable logistic regression, FSH dosage adjustment was not significantly associated with CLBR ( OR=1.06, 95% CI: 0.94-1.20, P=0.332). Compared with the adjusted-dosage group, the fixed-dosage group showed no significant differences in CLBR in poor-, normal-, and high-responder groups (all P>0.05). The incidence of ovarian hyperstimulation syndrome (OHSS) did not differ significantly between the two groups ( P>0.05). In poor-, normal-, and high-responder groups, the total FSH dosages in the fixed-dose group [1 350 (375, 1 825) U, 1 200 (375, 1 500) U and 525 (375, 1 128) U, respectively] were significantly lower than those in the adjusted-dose group [1 875 (1 425, 2 294) U, P=0.001; 1 425 (450, 1 875) U, P<0.001; 600 (375, 1 425) U, P=0.020]. Similarly, average FSH costs in different ovarian response groups in the fixed-dosage group [4 725.0 (1 312.5, 6 387.5) yuan, 4 200.0 (1 312.5, 5 250.0) yuan and 1 837.5 (1 312.5, 3 947.3) yuan, respectively] were significantly lower than those in the adjusted-dosage group [6 562.5 (4 987.5, 8 028.1) yuan, P=0.001; 4 987.5 (1 575.0, 6 562.5) yuan, P<0.001; 2 100.0 (1 312.5, 4 987.5) yuan, P=0.020]. For normal-responders, the FSH cost per high-quality embryo in the fixed-dosage group [1 365.0 (875.0, 2 537.5) yuan] was significantly lower than that in the adjusted-dosage group [2 056.3 (1 268.8, 3 412.5) yuan, P<0.001]. Conclusion:FSH dosage adjustment during COS is not associated with CLBR or the incidence of OHSS. However, the fixed-dose group exhibited lower total FSH dosages and costs across different ovarian response populations. In the context of ART being covered by medical insurance, fixed FSH dosage may represent a more cost-effective ovarian stimulation protocol.