ObjectiveTo compare the performance of different automatic evaluation methods for detecting pattern hallucinations generated by large language models （LLMs） in traditional Chinese medicine （TCM） syndrome differentiation and to identify a strategy with higher overall discriminative performance against expert manual judgment. MethodsA standardized TCM syndrome-differentiation dataset containing 598 cases was constructed from case reports published in Chinese core journals indexed by Peking University Core Journals or Chinese Science Citation Database. Each of the 598 cases was submitted to five Chinese LLMs， with each model generating one syndrome-pattern output per case， yielding 2990 outputs in total. The 598 outputs generated by Qwen3-Next-80B-A3B-Thinking were independently annotated for syndrome-pattern hallucinations by two licensed TCM physicians with intermediate or higher professional titles. Disagreements were adjudicated by a third licensed TCM physician with a senior associate professional title and more than 10 years of clinical experience. The resulting consensus annotations served as the reference labels for training and validating the automated evaluation method. Based on these reference labels， three categories of automated evaluation methods were developed and compared following a progressive strategy from text-level semantic similarity， to syndrome-element structural consistency， and finally multi-feature fusion. Method A employed sentence-embedding models based on semantic similarity between pattern texts. Method B adopted a rule-based threshold method using weighted Jaccard coefficients of disease-location and disease-nature syndrome elements. Method C utilized a machine-learning classifier integrating syndrome-element matching scores， missing and redundant syndrome-element counts， and multiple semantic-similarity features. Five-fold cross-validation was used to evaluate the discriminative performance of each method against manual judgment. The optimal method was then applied to uniformly assess the pattern hallucination rates of five LLMs. ResultsIn method A， text2vec-large-chinese showed best overall performance， with an area under the receiver operating characteristic curve （AUROC）， area under the precision-recall curve （PR-AUC）， F1-score， sensitivity， and specificity of 0.849， 0.884， 0.794， 0.801， and 0.691， respectively. In method B， the corresponding metrics of the rule-based syndrome-element Jaccard threshold method were 0.848， 0.851， 0.817， 0.845， and 0.684， respectively； those of the LLM-based syndrome-element Jaccard method were 0.872， 0.906， 0.795， 0.764， and 0.780， respectively. In method C， the multilayer perceptron （MLP） classifier showed the best overall performance， with AUROC， PR-AUC， F1-score， sensitivity， and specificity of 0.933， 0.951， 0.871， 0.857， and 0.846， respectively. Under the unified evaluation framework combining DeepSeek-R1 syndrome-element extraction and MLP classifier， the estimated pattern hallucination rates of the five LLMs ranged from 56.0% to 77.4%. ConclusionAmong the three automatic evaluation methods， Method C integrating syndrome-element discrepancy features and text semantic features using an MLP classifier showed the highest overall discriminative performance against manual judgment， and is more suitable for evaluating syndrome hallucinations in LLM-based TCM syndrome differentiation tasks.

Objective To identify the taste critical quality attribute and design and optimize the flavor-correcting formulation of the traditional Chinese medicine oral preparation Qingre Jiedu Oral Liquid,in order to improve its taste and enhance patient medication adherence.Methods The taste assignment method was employed to identify the taste critical quality attribute of Qingre Jiedu Oral Liquid.Based on human sensory evaluation and the standardized Euclidean distance in electronic tongue analysis,suitable types of corrigent were determined.Subsequently,under constraints such as maximum allowable dosage,solubility,and sweetness,the optimal taste formulation for the sugar-free intermediate of Qingre Jiedu Oral Liquid was determined using Box-Behnken experimental design combined with electronic tongue and human sensory evaluation results.The study was reviewed and approved by the Ethics Committee of Beijing University of Chinese Medicine(Ethics Approval Number 2020BZYLL0609).Results The quantitative score for bitter taste of Qingre Jiedu Oral Liquid accounted for 30.36%,confirming bitterness as the taste critical quality attribute requiring attention.The optimal taste formulation for the sugar-free intermediate of Qingre Jiedu Oral Liquid was determined to be 120 mg·mL?1 erythritol,12 mg·mL?1 acesulfame potassium,and 2.4 mg·mL?1 stevioside.This formulation achieved an 11.75-point improvement in sensory evaluation scores compared to the original commercially available oral liquid.Conclusion This study successfully improved the taste of Qingre Jiedu Oral Liquid and established a comprehensive strategy for flavor-correcting formulation optimization,including a method for identifying taste critical quality attribute.This strategy provides a referential paradigm for palatability enhancement of similar traditional Chinese medicine oral preparations,laying a crucial technical foundation for elevating the clinical value of Chinese herbal medicines and promoting the high-quality development of traditional Chinese medicine(TCM).

Objective:To screen differentially expressed circular RNAs(circRNA)associated with lymph node metastasis in cervical cancer and investigate their molecular mechanism and biological function.Methods:Cancer tissue samples were collected from 40 cervical cancer patients(20 with lymph node metastasis and 20 without lymph node metastasis).Three specimens were randomly selected from each group,and the circRNA expression profile was analyzed using high-throughput sequencing technology,and perform KEGG and GO enrichment analy-sis was performed on the differentially expressed circRNA derived mother genes.Real-time fluorescence quantita-tive PCR(qRT-PCR)technology was used to validate four significantly upregulated circRNAs with high differential multiples,and a ceRNA network was constructed for database prediction.The relationship between circRNA with the most significant differential expression and clinical pathological features was analyzed.Transfect circRNA small interfering RNA(siRNA)into cervical cancer cell lines.Cell lines were divided into circRNA knockdown group and negative control(si-NC)group.The proliferation of SiHa cells and HeLa cells in cervical cancer was detected by Cell Counting Kit-8(CCK-8).Results:①A total of 2039 differentially expressed circRNAs were detec-ted.The differentially expressed circRNA derived mother genes are mainly enriched in ubiquitin mediated protein hydrolysis,MAPK signaling pathway,endocytosis,apoptosis and other signaling pathways.②Four significantly up-regulated circRNAs with high differential multiples in the transfer group were selected,which are hsa_circ_0067492,hsa_circ_0004904,hsa_circ_0085465,and hsa_circ_0007718.qRT-PCR showed that hsa_circ_0004904,hsa_circ_0085465,and hsa_circ_0007718 were all highly expressed in cervical cancer tissues with lymph node metas-tasis(P<0.01).Hsa_circ_0004904 could interact with microRNAs(miRNAs)such as hsa-miR-3916.Hsa_circ_0085465 could interact with miRNAs such as hsa-miR-4659b-3p,and hsa_circ_0007718 could interact with miRNAs such as hsa-miR-127-5p.③The high and low expression groups of hsa_circ_0004904 showed statistically signigi-cant differences in lymph node metastasis and lymphovascular invasion status(P<0.05).Compared with the si-NC group,the proliferation ability of SiHa cells and HeLa cells was significantly reduced after transfection with hsa_circ_0004904 at 24,48,and 72 hours(P<0.05).Conclusions:Differentially expressed circRNAs were identi-fied in cervical cancer patients with lymph node metastasis.Silencing these circRNAs significantly inhibited the proliferation of cervical cancer cells,suggesting their potential involvement in the progression of lymph node me-tastasis.These circRNAs may serve as specific biomarkers for predicting lymph node metastasis.

Objective:To screen differentially expressed circular RNAs(circRNA)associated with lymph node metastasis in cervical cancer and investigate their molecular mechanism and biological function.Methods:Cancer tissue samples were collected from 40 cervical cancer patients(20 with lymph node metastasis and 20 without lymph node metastasis).Three specimens were randomly selected from each group,and the circRNA expression profile was analyzed using high-throughput sequencing technology,and perform KEGG and GO enrichment analy-sis was performed on the differentially expressed circRNA derived mother genes.Real-time fluorescence quantita-tive PCR(qRT-PCR)technology was used to validate four significantly upregulated circRNAs with high differential multiples,and a ceRNA network was constructed for database prediction.The relationship between circRNA with the most significant differential expression and clinical pathological features was analyzed.Transfect circRNA small interfering RNA(siRNA)into cervical cancer cell lines.Cell lines were divided into circRNA knockdown group and negative control(si-NC)group.The proliferation of SiHa cells and HeLa cells in cervical cancer was detected by Cell Counting Kit-8(CCK-8).Results:①A total of 2039 differentially expressed circRNAs were detec-ted.The differentially expressed circRNA derived mother genes are mainly enriched in ubiquitin mediated protein hydrolysis,MAPK signaling pathway,endocytosis,apoptosis and other signaling pathways.②Four significantly up-regulated circRNAs with high differential multiples in the transfer group were selected,which are hsa_circ_0067492,hsa_circ_0004904,hsa_circ_0085465,and hsa_circ_0007718.qRT-PCR showed that hsa_circ_0004904,hsa_circ_0085465,and hsa_circ_0007718 were all highly expressed in cervical cancer tissues with lymph node metas-tasis(P<0.01).Hsa_circ_0004904 could interact with microRNAs(miRNAs)such as hsa-miR-3916.Hsa_circ_0085465 could interact with miRNAs such as hsa-miR-4659b-3p,and hsa_circ_0007718 could interact with miRNAs such as hsa-miR-127-5p.③The high and low expression groups of hsa_circ_0004904 showed statistically signigi-cant differences in lymph node metastasis and lymphovascular invasion status(P<0.05).Compared with the si-NC group,the proliferation ability of SiHa cells and HeLa cells was significantly reduced after transfection with hsa_circ_0004904 at 24,48,and 72 hours(P<0.05).Conclusions:Differentially expressed circRNAs were identi-fied in cervical cancer patients with lymph node metastasis.Silencing these circRNAs significantly inhibited the proliferation of cervical cancer cells,suggesting their potential involvement in the progression of lymph node me-tastasis.These circRNAs may serve as specific biomarkers for predicting lymph node metastasis.

Objective To identify the taste critical quality attribute and design and optimize the flavor-correcting formulation of the traditional Chinese medicine oral preparation Qingre Jiedu Oral Liquid,in order to improve its taste and enhance patient medication adherence.Methods The taste assignment method was employed to identify the taste critical quality attribute of Qingre Jiedu Oral Liquid.Based on human sensory evaluation and the standardized Euclidean distance in electronic tongue analysis,suitable types of corrigent were determined.Subsequently,under constraints such as maximum allowable dosage,solubility,and sweetness,the optimal taste formulation for the sugar-free intermediate of Qingre Jiedu Oral Liquid was determined using Box-Behnken experimental design combined with electronic tongue and human sensory evaluation results.The study was reviewed and approved by the Ethics Committee of Beijing University of Chinese Medicine(Ethics Approval Number 2020BZYLL0609).Results The quantitative score for bitter taste of Qingre Jiedu Oral Liquid accounted for 30.36%,confirming bitterness as the taste critical quality attribute requiring attention.The optimal taste formulation for the sugar-free intermediate of Qingre Jiedu Oral Liquid was determined to be 120 mg·mL?1 erythritol,12 mg·mL?1 acesulfame potassium,and 2.4 mg·mL?1 stevioside.This formulation achieved an 11.75-point improvement in sensory evaluation scores compared to the original commercially available oral liquid.Conclusion This study successfully improved the taste of Qingre Jiedu Oral Liquid and established a comprehensive strategy for flavor-correcting formulation optimization,including a method for identifying taste critical quality attribute.This strategy provides a referential paradigm for palatability enhancement of similar traditional Chinese medicine oral preparations,laying a crucial technical foundation for elevating the clinical value of Chinese herbal medicines and promoting the high-quality development of traditional Chinese medicine(TCM).

Objective:To predict lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer based on preoperative inflammatory and immune nutritional indicators,and to construct a nomo-gram prediction model,providing a basis and tool for preoperative diagnosis of lymph node metastasis in cervical cancer.Methods:A retrospective analysis was conducted on the clinical data of 307 patients preoperatively diag-nosed with early-stage cervical cancer who underwent surgical treatment at the Obstetrics and Gynecology De-partment of the Second Affiliated Hospital of Zhengzhou University from January 2018 to July 2023.R software was used to randomize the groups into a training set(n=231)and a validation set(n=76)in a 3∶1 ratio.Uni-variate and multivariate logistic regression analyses were employed to identify factors influencing lymph node me-tastasis in patients preoperatively diagnosed with early-stage cervical cancer.R software was used to establish a nomogram prediction model and draw receiver operating characteristic(ROC)curves and calibration curves for validation.Results:① The results of univariate logistic regression analysis showed that positive lymphovascular invasion,platelet-to-lymphocyte ratio(PLR)≥151.70,neutrophil-to-white blood cell ratio(NWR)≥0.65,plate-let-to-albumin ratio(PAR)≥ 4.94,preoperative systemic immune-inflammation index(SII)≥604.03,and sys-temic inflammatory response index(SIRI)≥ 1.05 were associated with lymph node metastasis(P＜0.05).②Multivariate logistic regression analysis found that positive lymphovascular invasion,NWR≥0.65,and PAR≥4.94 were independent risk factors for lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer(OR＞1,P＜0.05).③ A nomogram was constructed to predict lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer.The ROC curve shows an area under the train-ing set curve(AUC)of 0.821 and a validation set AUC of 0.858.The calibration curve shows an average abso-lute error of 0.024 for the training set and 0.059 for the validation set.Conclusions:The prediction model for lymph node metastasis in cervical cancer constructed using preoperative inflammatory and immune nutritional indi-cators such as NWR,PAR is helpful for gynecological oncologists to predict lymph node metastasis in cervical cancer patients before surgery.

Objective:To predict lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer based on preoperative inflammatory and immune nutritional indicators,and to construct a nomo-gram prediction model,providing a basis and tool for preoperative diagnosis of lymph node metastasis in cervical cancer.Methods:A retrospective analysis was conducted on the clinical data of 307 patients preoperatively diag-nosed with early-stage cervical cancer who underwent surgical treatment at the Obstetrics and Gynecology De-partment of the Second Affiliated Hospital of Zhengzhou University from January 2018 to July 2023.R software was used to randomize the groups into a training set(n=231)and a validation set(n=76)in a 3∶1 ratio.Uni-variate and multivariate logistic regression analyses were employed to identify factors influencing lymph node me-tastasis in patients preoperatively diagnosed with early-stage cervical cancer.R software was used to establish a nomogram prediction model and draw receiver operating characteristic(ROC)curves and calibration curves for validation.Results:① The results of univariate logistic regression analysis showed that positive lymphovascular invasion,platelet-to-lymphocyte ratio(PLR)≥151.70,neutrophil-to-white blood cell ratio(NWR)≥0.65,plate-let-to-albumin ratio(PAR)≥ 4.94,preoperative systemic immune-inflammation index(SII)≥604.03,and sys-temic inflammatory response index(SIRI)≥ 1.05 were associated with lymph node metastasis(P＜0.05).②Multivariate logistic regression analysis found that positive lymphovascular invasion,NWR≥0.65,and PAR≥4.94 were independent risk factors for lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer(OR＞1,P＜0.05).③ A nomogram was constructed to predict lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer.The ROC curve shows an area under the train-ing set curve(AUC)of 0.821 and a validation set AUC of 0.858.The calibration curve shows an average abso-lute error of 0.024 for the training set and 0.059 for the validation set.Conclusions:The prediction model for lymph node metastasis in cervical cancer constructed using preoperative inflammatory and immune nutritional indi-cators such as NWR,PAR is helpful for gynecological oncologists to predict lymph node metastasis in cervical cancer patients before surgery.

Objective:To predict lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer based on preoperative inflammatory and immune nutritional indicators,and to construct a nomo-gram prediction model,providing a basis and tool for preoperative diagnosis of lymph node metastasis in cervical cancer.Methods:A retrospective analysis was conducted on the clinical data of 307 patients preoperatively diag-nosed with early-stage cervical cancer who underwent surgical treatment at the Obstetrics and Gynecology De-partment of the Second Affiliated Hospital of Zhengzhou University from January 2018 to July 2023.R software was used to randomize the groups into a training set(n=231)and a validation set(n=76)in a 3∶1 ratio.Uni-variate and multivariate logistic regression analyses were employed to identify factors influencing lymph node me-tastasis in patients preoperatively diagnosed with early-stage cervical cancer.R software was used to establish a nomogram prediction model and draw receiver operating characteristic(ROC)curves and calibration curves for validation.Results:① The results of univariate logistic regression analysis showed that positive lymphovascular invasion,platelet-to-lymphocyte ratio(PLR)≥151.70,neutrophil-to-white blood cell ratio(NWR)≥0.65,plate-let-to-albumin ratio(PAR)≥ 4.94,preoperative systemic immune-inflammation index(SII)≥604.03,and sys-temic inflammatory response index(SIRI)≥ 1.05 were associated with lymph node metastasis(P＜0.05).②Multivariate logistic regression analysis found that positive lymphovascular invasion,NWR≥0.65,and PAR≥4.94 were independent risk factors for lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer(OR＞1,P＜0.05).③ A nomogram was constructed to predict lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer.The ROC curve shows an area under the train-ing set curve(AUC)of 0.821 and a validation set AUC of 0.858.The calibration curve shows an average abso-lute error of 0.024 for the training set and 0.059 for the validation set.Conclusions:The prediction model for lymph node metastasis in cervical cancer constructed using preoperative inflammatory and immune nutritional indi-cators such as NWR,PAR is helpful for gynecological oncologists to predict lymph node metastasis in cervical cancer patients before surgery.

Objective:To predict lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer based on preoperative inflammatory and immune nutritional indicators,and to construct a nomo-gram prediction model,providing a basis and tool for preoperative diagnosis of lymph node metastasis in cervical cancer.Methods:A retrospective analysis was conducted on the clinical data of 307 patients preoperatively diag-nosed with early-stage cervical cancer who underwent surgical treatment at the Obstetrics and Gynecology De-partment of the Second Affiliated Hospital of Zhengzhou University from January 2018 to July 2023.R software was used to randomize the groups into a training set(n=231)and a validation set(n=76)in a 3∶1 ratio.Uni-variate and multivariate logistic regression analyses were employed to identify factors influencing lymph node me-tastasis in patients preoperatively diagnosed with early-stage cervical cancer.R software was used to establish a nomogram prediction model and draw receiver operating characteristic(ROC)curves and calibration curves for validation.Results:① The results of univariate logistic regression analysis showed that positive lymphovascular invasion,platelet-to-lymphocyte ratio(PLR)≥151.70,neutrophil-to-white blood cell ratio(NWR)≥0.65,plate-let-to-albumin ratio(PAR)≥ 4.94,preoperative systemic immune-inflammation index(SII)≥604.03,and sys-temic inflammatory response index(SIRI)≥ 1.05 were associated with lymph node metastasis(P＜0.05).②Multivariate logistic regression analysis found that positive lymphovascular invasion,NWR≥0.65,and PAR≥4.94 were independent risk factors for lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer(OR＞1,P＜0.05).③ A nomogram was constructed to predict lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer.The ROC curve shows an area under the train-ing set curve(AUC)of 0.821 and a validation set AUC of 0.858.The calibration curve shows an average abso-lute error of 0.024 for the training set and 0.059 for the validation set.Conclusions:The prediction model for lymph node metastasis in cervical cancer constructed using preoperative inflammatory and immune nutritional indi-cators such as NWR,PAR is helpful for gynecological oncologists to predict lymph node metastasis in cervical cancer patients before surgery.

Objective:To predict lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer based on preoperative inflammatory and immune nutritional indicators,and to construct a nomo-gram prediction model,providing a basis and tool for preoperative diagnosis of lymph node metastasis in cervical cancer.Methods:A retrospective analysis was conducted on the clinical data of 307 patients preoperatively diag-nosed with early-stage cervical cancer who underwent surgical treatment at the Obstetrics and Gynecology De-partment of the Second Affiliated Hospital of Zhengzhou University from January 2018 to July 2023.R software was used to randomize the groups into a training set(n=231)and a validation set(n=76)in a 3∶1 ratio.Uni-variate and multivariate logistic regression analyses were employed to identify factors influencing lymph node me-tastasis in patients preoperatively diagnosed with early-stage cervical cancer.R software was used to establish a nomogram prediction model and draw receiver operating characteristic(ROC)curves and calibration curves for validation.Results:① The results of univariate logistic regression analysis showed that positive lymphovascular invasion,platelet-to-lymphocyte ratio(PLR)≥151.70,neutrophil-to-white blood cell ratio(NWR)≥0.65,plate-let-to-albumin ratio(PAR)≥ 4.94,preoperative systemic immune-inflammation index(SII)≥604.03,and sys-temic inflammatory response index(SIRI)≥ 1.05 were associated with lymph node metastasis(P＜0.05).②Multivariate logistic regression analysis found that positive lymphovascular invasion,NWR≥0.65,and PAR≥4.94 were independent risk factors for lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer(OR＞1,P＜0.05).③ A nomogram was constructed to predict lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer.The ROC curve shows an area under the train-ing set curve(AUC)of 0.821 and a validation set AUC of 0.858.The calibration curve shows an average abso-lute error of 0.024 for the training set and 0.059 for the validation set.Conclusions:The prediction model for lymph node metastasis in cervical cancer constructed using preoperative inflammatory and immune nutritional indi-cators such as NWR,PAR is helpful for gynecological oncologists to predict lymph node metastasis in cervical cancer patients before surgery.