ObjectiveTo explore the mechanism by which Sini San （SNS） inhibits ferroptosis， alleviates inflammation and myocardial injury， and improves myocardial infarction （MI）. MethodsThe active ingredients of SNS were obtained by searching the Traditional Chinese Medicine System Pharmacology Platform （TCMSP） database， its target sites were predicted using the SwissTargetPrediction Database， and the core components were screened out using the CytoNCA plug-in. The targets of MI and ferroptosis were obtained by using GeneCards， Online Mendelian Inheritance in Man （OMIM） database， DrugBank， Therapeutic Target Database （TTD）， FerrDb database and literature review， respectively. The intersection of these targets of SNS-MI-ferroptosis was plotted as a Venn diagram. The protein-protein interaction （PPI） network was constructed using the STRING database， and the visualization graph was prepared using Cytoscape. The core targets were screened out using the CytoNCA plug-in， and the biological functions were clustered by the MCODE plug-in. Gene Ontology （GO） functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes （KEGG） pathway enrichment analysis were performed using the David database. Molecular docking was performed using AutoDock and visualized with PyMOL2.5.2. The Kunming mice were randomly divided into the control group， the model group， the SNS group， and the trimetazidine （TMZ） group. The mice were subcutaneously injected with isoprenaline （ISO， 5 mg·kg^-1·d^-1） to establish an MI model. The drug was continuously intervened for 7 days. The ST-segment changes were recorded by electrocardiogram （ECG）， and the tissue morphology changes were observed by hematoxylin-eosin （HE） staining. Cardiomyocyte ferroptosis was investigated by transmission electron microscopy. Serum creatine kinase （CK）， creatine kinase isoenzyme （CK-MB）， lactate dehydrogenase （LDH）， reduced glutathione （GSH）， and malondialdehyde （MDA） levels were detected by biochemical assay. Enzyme-linked immunosorbent assay （ELISA） was used to detect serum levels of interleukin （IL）-6 and 4-hydroxynonenal （4-HNE）. Immunohistochemical staining was employed to detect IL-6 and phosphorylated signal transducer and transcription activator 3 （p-STAT3） in cardiac tissues. Western blot was used to detect STAT3 and p-STAT3 in cardiac tissues. Real-time PCR was used to detect the levels of IL-6， IL-18， solute carrier family 7 member 11 （SLC7A11）， arachidonic acid 15-lipoxygenase （ALOX15）， and glutathione peroxidase 4 （GPx4） in cardiac tissues. ResultsA total of 121 active ingredients of SNS were obtained， and 58 potential targets of SNS in the treatment of MI by regulating ferroptosis were screened. The three protein modules with a score5 were mainly related to the inflammatory response. The GO function was mainly related to inflammation， and KEGG enrichment analysis showed that SNS mainly regulated ferroptosis- and inflammation- related signaling pathways. Molecular docking indicated that the core component had a higher binding force to the target site. Animal experiments confirmed that SNS reduced the level of p-STAT3 （P0.01）， down-regulated the expression of ALOX15 mRNA （P0.01）， up-regulated the level of serum GSH， and the expressions of SLC7A11 and GPx4 mRNA， reduced MDA and 4-HNE levels （P0.05， P0.01）. Additionally， SNS improved the mitochondrial injury induced by cardiomyocyte ferroptosis， reduced the area of MI， alleviated inflammation and myocardial injury， lowered the levels of serum CK， CK-MB， LDH， IL-6， and the mRNA expression levels of IL-16 and IL-18 （P0.05）， and improved ST segment elevation. ConclusionSNS can reduce ISO-induced STAT3 phosphorylation levels， inhibit ferroptosis in cardiomyocytes， alleviate inflammation and myocardial injury， thereby improving MI.

ObjectiveTo explore the mechanism by which Sini San （SNS） inhibits ferroptosis， alleviates inflammation and myocardial injury， and improves myocardial infarction （MI）. MethodsThe active ingredients of SNS were obtained by searching the Traditional Chinese Medicine System Pharmacology Platform （TCMSP） database， its target sites were predicted using the SwissTargetPrediction Database， and the core components were screened out using the CytoNCA plug-in. The targets of MI and ferroptosis were obtained by using GeneCards， Online Mendelian Inheritance in Man （OMIM） database， DrugBank， Therapeutic Target Database （TTD）， FerrDb database and literature review， respectively. The intersection of these targets of SNS-MI-ferroptosis was plotted as a Venn diagram. The protein-protein interaction （PPI） network was constructed using the STRING database， and the visualization graph was prepared using Cytoscape. The core targets were screened out using the CytoNCA plug-in， and the biological functions were clustered by the MCODE plug-in. Gene Ontology （GO） functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes （KEGG） pathway enrichment analysis were performed using the David database. Molecular docking was performed using AutoDock and visualized with PyMOL2.5.2. The Kunming mice were randomly divided into the control group， the model group， the SNS group， and the trimetazidine （TMZ） group. The mice were subcutaneously injected with isoprenaline （ISO， 5 mg·kg^-1·d^-1） to establish an MI model. The drug was continuously intervened for 7 days. The ST-segment changes were recorded by electrocardiogram （ECG）， and the tissue morphology changes were observed by hematoxylin-eosin （HE） staining. Cardiomyocyte ferroptosis was investigated by transmission electron microscopy. Serum creatine kinase （CK）， creatine kinase isoenzyme （CK-MB）， lactate dehydrogenase （LDH）， reduced glutathione （GSH）， and malondialdehyde （MDA） levels were detected by biochemical assay. Enzyme-linked immunosorbent assay （ELISA） was used to detect serum levels of interleukin （IL）-6 and 4-hydroxynonenal （4-HNE）. Immunohistochemical staining was employed to detect IL-6 and phosphorylated signal transducer and transcription activator 3 （p-STAT3） in cardiac tissues. Western blot was used to detect STAT3 and p-STAT3 in cardiac tissues. Real-time PCR was used to detect the levels of IL-6， IL-18， solute carrier family 7 member 11 （SLC7A11）， arachidonic acid 15-lipoxygenase （ALOX15）， and glutathione peroxidase 4 （GPx4） in cardiac tissues. ResultsA total of 121 active ingredients of SNS were obtained， and 58 potential targets of SNS in the treatment of MI by regulating ferroptosis were screened. The three protein modules with a score5 were mainly related to the inflammatory response. The GO function was mainly related to inflammation， and KEGG enrichment analysis showed that SNS mainly regulated ferroptosis- and inflammation- related signaling pathways. Molecular docking indicated that the core component had a higher binding force to the target site. Animal experiments confirmed that SNS reduced the level of p-STAT3 （P0.01）， down-regulated the expression of ALOX15 mRNA （P0.01）， up-regulated the level of serum GSH， and the expressions of SLC7A11 and GPx4 mRNA， reduced MDA and 4-HNE levels （P0.05， P0.01）. Additionally， SNS improved the mitochondrial injury induced by cardiomyocyte ferroptosis， reduced the area of MI， alleviated inflammation and myocardial injury， lowered the levels of serum CK， CK-MB， LDH， IL-6， and the mRNA expression levels of IL-16 and IL-18 （P0.05）， and improved ST segment elevation. ConclusionSNS can reduce ISO-induced STAT3 phosphorylation levels， inhibit ferroptosis in cardiomyocytes， alleviate inflammation and myocardial injury， thereby improving MI.

With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.

Objective To establish an efficient and stable model of pelvic inflammatory disease in rats via a non-surgical method,and to evaluate its application in pharmacodynamic testing.Methods Female Sprague-Dawley rats were divided randomly into the following groups:control group;model group with phenol for 7 d;model group with phenol for 10 d;treatment group modeled with phenol;model group with low concentration of bacteria;model group with high concentration of bacteria;and treatment group modeled with bacteria.Rats in the model and treatment groups were injected with 25%phenol gel and 2×107 or 2×108 Escherichia coli and Staphylococcus aureus mixture via a non-surgical method,to construct a rat model of pelvic inflammatory disease.Rats in the treatment groups received the Chinese patent medicine Jingangteng capsules by gavage,and rats in the control group received the same volume of solvent solution.The health status,weight changes,and uterine appearance were monitored and the uterine coefficient was calculated.Pathological changes in the uterus and fallopian tubes,endometrial thickness,and number of glands were detected by hematoxylin and eosin staining.Serum levels of interleukin(IL)-1β,IL-6,and tumor necrosis factor(TNF)-α were detected by enzyme-linked immunosorbent assay.Protein expression of the macrophage marker CD68 was detected by immunofluorescence.Expression of Toll-like receptor 4(TLR4)/nuclear factor(NF)-κB pathway-related proteins in the uterus was detected by Western blot.Results The mortality rate in the model group was only 5%.Compared with the control group,model rats showed decreased body weight,increased uterine coefficient,pathological changes in the uterus and Fallopian tubes,thinner endometrium,fewer glands,significantly higher serum levels of IL-1β,IL-6,and TNF-α and more macrophages in the uterine tissue,and activation of the TLR4/NF-κB signaling pathway.The 7 d phenol and low-concentration bacterial solution models were judged to be mild pelvic inflammatory disease models,and the 10 d phenol and high-concentration bacterial solution models were considered severe pelvic inflammatory disease models.Treatment with Jingangteng capsules relieved the pathological symptoms in the uterus and fallopian tubes,in line with the efficacy evaluation of clinical pelvic inflammatory disease.Conclusions We established rat models of pelvic inflammatory disease using phenol and a mixed bacterial solution via a non-surgical method,to simulate the different pathological states of pelvic inflammatory disease caused by different factors.These models will be suitable for evaluating drug efficacy and elucidating the pathological mechanism of pelvic inflammatory disease.

OBJECTIVE: To explore the effects of different endotracheal tube cuff pressure management modes on cuff sealing and the pressure exerted on the tracheal wall. METHODS: A prospective self-controlled study was conducted. Eleven patients undergoing endotracheal intubation and mechanical ventilation with an automatic airway management system (AGs) admitted to the Second Medical Centre of the Chinese People's Liberation Army General Hospital from October 1, 2020, to April 1, 2022, were enrolled as the study subjects. Within 24 hours after the establishment of artificial airway and mechanical ventilation, four cuff pressure management modes were randomly applied to each patient for 24 hours in sequence: automatic cuff pressure management mode [modeI: the safe range of cuff pressure was set at 20-35 cmH₂O (1 cmH₂O≈0.098 kPa), and the CO₂ pressure above the endotracheal tube cuff was automatically detected by AGs every 5 minutes to determine the cuff sealing status, and the cuff pressure was automatically adjusted], constant cuff pressure (25 cmH₂O) management mode (mode II: the cuff pressure was monitored by AGs through a pressure sensor, and the cuff pressure was maintained at 25 cmH₂O via a pressure pump), constant cuff pressure (30 cmH₂O) management mode (mode III: the cuff pressure was monitored by AGs through a pressure sensor, and the cuff pressure was maintained at 30 cmH₂O via a pressure pump), and manual cuff pressure management mode (mode IV: the cuff pressure was manually measured by nurses every 6-8 hours using a cuff pressure gauge to keep the cuff pressure at 25-30 cmH₂O after inflation). The CO₂ pressure above the endotracheal tube cuff (at 60-minute intervals) and the cuff pressure changes (at 50-ms intervals) were recorded to compare the differences in number of cuff leaks [no leak was defined as CO₂ pressure = 0, small leak as 0 < CO₂ pressure < 2 mmHg (1 mmHg≈0.133 kPa), and large leak as CO₂ pressure ≥ 2 mmHg] and cuff pressure among modesI-IV. RESULTS: A total of 24 CO₂ pressure measurements were taken per patient across the four modes, resulting in a total of 264 detections for each mode. Regarding the cuff leak, the total number of leak and large leak in modeIwas significantly lower than that in modes II-IV [total leak: 30 cases (11.36%) vs. 81 cases (30.68%), 70 cases (26.52%), 103 cases (39.02%); large leak: 15 cases (5.68%) vs. 50 cases (18.94%), 48 cases (18.18%), 66 cases (25.00%), all P < 0.05]. There was no significant difference in the number of cuff leak between modes II and III, and mode IV had the most severe cuff leak. In terms of cuff pressure, since mode IV required blocking the cuff tube from the AGs tube and the AGs cuff pressure management module did not actually work, real-time monitoring of cuff pressure was not possible. Therefore, cuff pressure changes were only analyzed in modes I-III. Each of the 11 patients underwent 24-hour cuff pressure monitoring under modes I-III, with 19 008 000 monitoring times for each mode. The cuff pressure in mode I was between that in modes II and III [cmH₂O: 27.09 (26.10, 28.14) vs. 26.60 (25.92, 27.47), 31.01 (30.33, 31.88), both P < 0.01]. Moreover, the number of extreme values of cuff pressure > 50 cmH₂O in mode I was significantly lower than that in modes II and III [19 900 cases (0.105%) vs. 22 297 cases (0.117%), 27 618 cases (0.145%), both P < 0.05]. CONCLUSION Dynamically monitoring the CO₂ pressure above the cuff to guide the adjustment of endotracheal tube cuff pressure can achieve better cuff sealing with a relatively lower cuff pressure load.
Humans ; Intubation, Intratracheal/instrumentation* ; Pressure ; Prospective Studies ; Respiration, Artificial ; Male ; Airway Management/methods* ; Female ; Middle Aged

Purpose To investigate the clinicopathological characteristics of the gastric oxyntic gland adenoma(GOGA).Methods We collected 18 samples of GOGA,histopathological features and immunohistochemical staining were assessed.Main features of pathological diagnosis,treatment methods and follow-up were retrospectively analyzed.Results There were 18 patients,including 9 females and 9 males,aged from 36 to 86 years old.The endoscopic im-age showed a flat lesion with whitish in color or a polypoid protrusions.The size ranged from 0.3 cm to 0.8 cm.Hema-toxylin and eosin staining showed irregular glandular structures in the mucosal lamina propria,with branched and anas-tomosed patterns.The tumour demonstrating composed of chief cells hyperplasia with mild nuclear atypia.All lesions were confined to the mucous lamina propria.There was no atrophic within the peripheral gastic mucosa.Immunohisto-chemical examination showed positive for Pepsinogen-Ⅰ and MUC6.Gene mutation were analyzed in 2 cases using next generation sequence technology,and no KRAS and GNAS mutation had been detected.Endoscopic surgical treatment was performed in 11 cases,and biopsy forceps removal was carried out in 7 cases.No recurrence or metastasis was ob-served during the follow-up period of 1 to 58 months.Conclusion GOGA is a rare lesion,and appears to behave bio-logically benign.A full understanding of its histological morphology and biological behavior can improve the diagnostic ability of clinincans,and facilitate further research in the future.

Objective To comprehensively evaluate the quality difference of Huaihua powder obtained by the hospital's electromagnetic furnace decoction method and automatic decoction machine decoction method.Methods Five methods(induction cooker decoction(once decoction,twice decoction),normal pressure decoction(once decoction,twice decoction),and pressure decoction)were used to prepare the decoction.The HPLC method used a Shiseido CAPCELL PAK-C18(250 mm×4.6 mm,5 μm)column,with a UV detection wavelength of 254 nm,mobile phase of acetonitrile 0.1%phosphoric acid water,column temperature of 30℃,flow rate of 1.0 mL/min,and detection of index components including rutin,naringin,quercitrin,neohesperidin,quercetin,and menthone.The extraction rate of the index components was calculated and the cream yield of each decoction was detected.The evaluation of quality differences is based on the comprehensive score of cream yield(40%)and indicator components(60%).Results The HPLC fingerprint similarity of Huaihua powder prepared by 5 decoction methods was greater than 99%.There was no significant difference(P>0.05)in the yield of ointment and the content of indicator components between the induction cooker one decoction and the induction cooker twice decoction methods.The yield of ointment and the extraction rate of indicator components were significantly higher in twice normal pressure decoction using a decoction machine than once normal pressure decoction using a decoction machine(P<0.05).The index component score of machine under pressure decoction once was the highest,but the comprehensive score of twice normal pressure decoction was the highest,with a combined score of 92.13 and 89.58,respectively,far higher than the 36.01,18.79,and 15.60 of the other three decoction methods.Classify the decoction into three categories through cluster analysis.Orthogonal partial least squares-discriminant analysis was used to screen for rutin,naringin and neohesperidin as differential biomarkers.Conclusion The quality of Huaihua powder decocted by a decoction machine is significantly better than that by an induction cooker,and the twice decocted at normal pressure by the decoction machine are significantly better than those decocted at normal pressure once.Decoction under pressure once may be a better choice.

Objective:To investigate the risk factors and construct a nomogram prediction model for neonatal bacterial meningitis (BM).Methods:A retrospective cohort study was conducted on 1 228 neonates who underwent lumbar puncture for cerebrospinal fluid examination in the Department of Neonatology at Gansu Provincial Women and Child Healthcare Hospital from December 2019 to February 2024. The subjects were randomly divided into a training cohort and a validation cohort at a ratio of 7∶3 using a computer program. Rank sum test or Chi-square tests were used to compare differences between the two cohorts. The subjects were divided into BM and non-BM groups based on the presence or absence of BM. Multivariate logistic regression analysis (forward stepwise regression method) was used in the training cohort to identify risk factors for BM. The area under the receiver operating characteristic curve (AUC) and the Hosmer-Lemeshow goodness-of-fit test were used to assess the discrimination and calibration of the model, respectively. Calibration curves were used to evaluate the accuracy of the model and to construct the nomogram. Internal validation was performed using the Bootstrap resampling method. Decision curve analysis was used to assess the clinical utility of the model. Results:Among the 1 228 neonates, 151 (12.3%) had BM. The training cohort included 859 neonates, of whom 106 (12.3%) had BM and 753 (87.7%) did not. The validation cohort included 369 neonates, of whom 45 (12.2%) had BM and 324 (87.8%) did not. The results of the multivariate logistic regression analysis in the training cohort showed that sepsis ( OR=4.446, 95% CI:2.583-7.653), convulsions ( OR=3.749, 95% CI:1.930-7.280), high maximum body temperature ( OR=2.027, 95% CI:1.636-2.513), and elevated C-reactive protein ( OR=1.007, 95% CI:1.003-1.012) were independent risk factors for BM, while greater gestational age at birth ( OR=0.946, 95% CI: 0.898-0.995) and higher hemoglobin levels ( OR=0.990, 95% CI:0.981-0.998) were protective factors for BM (all P<0.05). Based on these findings, a nomogram prediction model for neonatal BM was constructed and validated for accuracy. The AUC values of the nomogram model in the training and validation cohorts were 0.796 (95% CI: 0.750-0.843) and 0.781 (95% CI: 0.700-0.862), respectively. The Hosmer-Lemeshow goodness-of-fit test showed P>0.05 in both cohorts. The clinical decision curve analysis demonstrated good net benefit across most threshold ranges. Conclusions:Sepsis, convulsions, high maximum body temperature, and elevated C-reactive protein increase the risk of neonatal BM. The nomogram model constructed based on these factors, combined with gestational age and hemoglobin levels, provides a reference value for predicting the risk of neonatal BM.

Objective:To analyze the accuracy of nine estimation methods for umbilical venous catheterization (UVC) insertion depth in neonates.Methods:This prospective study enrolled neonates who underwent successful UVC placement in the Department of Neonatology at Gansu Provincial Women and Child Healthcare Hospital between September 2023 and October 2024. The standard catheter tip position was defined as the junction of the inferior vena cava and right atrium, with a deviation of ≤0.5 cm considered accurate. Patients were stratified by birth weight (BW) into three groups: <1 500 g, 1 500- 2 499 g, and ≥2 500 g. The actual UVC depth was compared with depths estimated using nine methods: Shukla formula, modified Shukla formula, JSS formula, BW formula, Tambasco formula, modified Tambasco formula, Dunn's nomogram, body surface measurement, and ultrasonographic measurement. Accuracy was evaluated using nonparametric tests and Bland-Altman agreement analysis.Results:The study included 111 neonates: 41 (36.9%) in the <1 500 g group, 55 (49.6%) in the 1 500-2 499 g group, and 15 (13.5%) in the ≥2 500 g group. In the <1 500 g group, accuracy rates ranged from 24% to 56%, with body surface measurement showing the highest accuracy (56%); the mean difference from actual depth was－0.073 cm, with 95% limits of agreement (LOA) of－1.764 to 1.618 cm. In the 1 500-2 499 g group, accuracy rate ranged from 15% to 51%, with the modified Tambasco formula being most accurate (51%); the mean difference was 0.113 cm (95%LOA:－1.558-1.783 cm). In the ≥2 500 g group, accuracy rate ranged from 0/15 to 10/15, with Dunn's nomogram being most accurate (10/15); the mean difference was－0.120 cm (95%LOA:－1.380-1.140 cm).Conclusions:The accuracy of the nine UVC depth estimation methods varied across different BW groups and among methods within the same group. Selection of an estimation method should be tailored to the neonate's birth weight.

Objective:To evaluate the clinical equivalence between a domestic calcipotriol/betamethasone dipropionate ointment and the originator product in the treatment of stable plaque psoriasis.Methods:A multicenter, randomized, double-blind, three-arm, parallel-group, active- and placebo-controlled study was conducted, and 449 patients aged 18 - 65 years with stable plaque psoriasis were enrolled from 25 hospitals (such as the First Affiliated Hospital of China Medical University). Eligible patients had a baseline physician's global assessment (PGA) score of ≥ 3 points, baseline body surface area (BSA) involvement of 5% - 30%, and a target lesion psoriasis area and severity index (TL-PASI) for plaque elevation of ≥ 3 points. Participants were randomly assigned in a 2:2:1 ratio to the test group ( n = 179), reference group ( n = 180), and placebo group ( n = 90), and applied the domestic calcipotriol/betamethasone dipropionate ointment, originator product, and ointment base respectively, once daily in the evening for 4 weeks. Efficacy and safety were assessed at weeks 1, 2, and 4. The primary efficacy endpoints were the treatment success rates and clinical success rates in each group at week 4. The per-protocol set (PPS) was used for the primary efficacy analysis, and the intention-to-treat (ITT) set for supplementary efficacy analysis. Equivalence between the test and reference preparations was tested using the Cochran-Mantel-Haenszel method adjusted for randomization strata. Superiority of the test and reference preparations over the placebo was also tested. Measurement data were compared among the 3 groups using analysis of variance or non-parametric tests, while treatment success rates, clinical success rates, and incidence rates of adverse reactions were compared using the chi-square test. Results:The ITT, PPS, and safety sets included 447, 420, and 448 patients, respectively. In the ITT set, patients were aged 43.6 ± 12.8 years, including 320 (71.6%) males and 127 (28.4%) females, and the disease duration was 11.21 ± 9.05 years; 316 (70.7%) had a PGA score of 3 points and 131 (29.3%) had a PGA score of 4 - 5 points. No significant differences in the baseline characteristics (including age, sex, disease duration and disease severity) were observed among the 3 groups (all P > 0.05). Based on the PPS analysis, the treatment success rates were 57.9% (99/171) in the test group, 50.3% (86/171) in the reference group, and 7.7% (6/78) in the placebo group, and the clinical success rates were 57.9% (99/171), 50.3% (86/171), and 10.3% (8/78), respectively; both the test and reference groups were superior to the placebo group in both treatment and clinical success rates (all P < 0.001) ; the rate differences for treatment success (90% confidence interval [ CI]: -1.3% - 16.4%) and clinical success (90% CI: -1.3% - 16.3%) between the test and reference groups were entirely within the pre-defined equivalence margin (-20% - 20%). Subgroup analyses by baseline PGA scores: for patients with a baseline PGA score of 3 points, the treatment success rates in the test, reference, and placebo groups were 60.8% (73/120), 52.1% (62/119), and 11.1% (6/54), respectively, and the corresponding clinical success rates were 61.7% (74/120), 53.8% (64/119), and 13% (7/54), respectively; the test and reference groups did not differ significantly in treatment or clinical success rates (both P > 0.05), but both showed higher success rates than the placebo group (all P < 0.001) ; the results of statistical comparisons among the 3 groups in patients with a baseline PGA score of 4 - 5 points were consistent with those observed in patients with a baseline PGA score of 3 points. The percentage reductions in PGA and TL-PASI scores from baseline to weeks 1, 2, and 4 showed significant differences among the 3 groups, which were significantly higher in the test and reference groups than in the placebo group (all P < 0.001), but did not differ between the test and reference groups (all P > 0.05). The primary adverse reactions were local skin reactions, such as pruritus, pain, and erythema. The incidence rates of adverse reactions were 8.9% (16/179) in the test group, 7.3% (13/179) in the reference group, and 7.8% (7/90) in the placebo group, with no significant difference among the 3 groups ( P > 0.05) . Conclusions:The domestic calcipotriol/betamethasone dipropionate ointment demonstrated clinical equivalence to the originator product in the treatment of stable plaque psoriasis, and the two agents exhibited comparable efficacy for patients with varying degrees of disease severity, and were comparable in the speed and degree of clinical improvement, with similar favorable safety profiles.