ObjectiveThis paper aims to find the identified and validated clinical biomarker data building upon a clinical study of early-phase phase Ⅱ and investigate the correlation analysis of Huanglian Jiedu Wan on syndrome improvement and clinical biomarkers in the treatment of "excess heat-toxicity" based on a machine learning model. Additionally， the effective prediction of clinical biomarker values for the main symptoms of the "excess heat-toxicity" syndrome was assessed. MethodsA total of 229 patients meeting the inclusion criteria for "excess heat-toxicity" syndrome were randomly divided into the Huanglian Jiedu Wan group and the placebo group. Syndrome score transition matrices were constructed for the Huanglian Jiedu Wan group and the placebo group based on three main symptoms of "excess heat-toxicity" syndrome， such as oral ulcers， sore throat， and gum swelling and pain. Data from the patients with these three syndromes were also integrated for an overall analysis. The corresponding syndrome score transition matrices were further constructed to visualize symptom change trends of the patients in the two groups via heatmaps. Based on the identified and validated clinical biomarkers related to inflammation， oxidative stress， and energy metabolism in the early phase， Spearman correlation analysis was employed to analyze and evaluate the associations between clinical biomarkers and syndrome improvement. Key clinical biomarkers reflecting the effect of Huanglian Jiedu Wan were screened through the comparison of differences between groups. An extreme gradient boosting （XGBoost） algorithm was used to develop a prediction model for main symptom classification， with classification performance evaluated through 10-fold cross-validation. Feature importance analysis was applied to identify variables with the greatest contribution to the prediction result. ResultsThe syndrome transition matrix results indicated that the Huanglian Jiedu Wan group showed a superior effect to the placebo group in improving oral ulcers， sore throat， and overall symptoms， with significant effects observed especially in sore throat and overall symptom analyses （P<0.01）. Spearman correlation analysis revealed that several clinical biomarkers positively correlated with "excess heat-toxicity" syndrome and its main symptom improvement， were also called "heat-related biomarkers"， including succinic acid， α-ketoglutaric acid， glycine， lactic acid， adenosine monophosphate （AMP）， tumor necrosis factor-α （TNF-α）， interferon-γ （IFN-γ）， interleukin-1β （IL-1β）， interleukin-4 （IL-4）， interleukin-6 （IL-6）， interleukin-8 （IL-8）， interleukin-10 （IL-10）， and so on. Conversely， clinical biomarkers negatively correlated with symptom severity， were also called "heat-clearing related biomarkers" after administration of Huanglian Jiedu Wan， including malic acid， fumaric acid， cis-aconitic acid， adrenocorticotropic hormone （ACTH）， IL-1β， IL-4， IL-8， succinic acid， and citric acid. The XGBoost classification model using all 52 biomarkers as variables achieved an average test accuracy of 0.754 and an average F1 score of 0.777. Feature importance analysis identified the scores of glutamic acid in saliva and IL-6 were the highest in all the variables， with importance scores of 0.081 and 0.080， respectively. After screening out 14 key variables and optimizing the parameters， model performance improved to an average accuracy of 0.758 and an F1 score of 0.798. Feature importance analysis further determined that the glutamic acid in saliva and IL-6 showed obvious changes after screening the variables， confirming the good syndrome prediction ability of the model constructed by these key clinical biomarkers. ConclusionThis study systematically elucidates the correlation between syndrome improvement and clinical biomarkers of Huanglian Jiedu Wan in the treatment of "excess heat-toxicity" syndrome. An XGBoost classification model based on key clinical biomarkers is successfully established， achieving effective prediction of the symptoms related to the "excess heat-toxicity" syndrome such as oral ulcers and sore throat and providing a new insight for objective identification of traditional Chinese medicine syndromes.

ObjectiveThis paper aims to find the identified and validated clinical biomarker data building upon a clinical study of early-phase phase Ⅱ and investigate the correlation analysis of Huanglian Jiedu Wan on syndrome improvement and clinical biomarkers in the treatment of "excess heat-toxicity" based on a machine learning model. Additionally， the effective prediction of clinical biomarker values for the main symptoms of the "excess heat-toxicity" syndrome was assessed. MethodsA total of 229 patients meeting the inclusion criteria for "excess heat-toxicity" syndrome were randomly divided into the Huanglian Jiedu Wan group and the placebo group. Syndrome score transition matrices were constructed for the Huanglian Jiedu Wan group and the placebo group based on three main symptoms of "excess heat-toxicity" syndrome， such as oral ulcers， sore throat， and gum swelling and pain. Data from the patients with these three syndromes were also integrated for an overall analysis. The corresponding syndrome score transition matrices were further constructed to visualize symptom change trends of the patients in the two groups via heatmaps. Based on the identified and validated clinical biomarkers related to inflammation， oxidative stress， and energy metabolism in the early phase， Spearman correlation analysis was employed to analyze and evaluate the associations between clinical biomarkers and syndrome improvement. Key clinical biomarkers reflecting the effect of Huanglian Jiedu Wan were screened through the comparison of differences between groups. An extreme gradient boosting （XGBoost） algorithm was used to develop a prediction model for main symptom classification， with classification performance evaluated through 10-fold cross-validation. Feature importance analysis was applied to identify variables with the greatest contribution to the prediction result. ResultsThe syndrome transition matrix results indicated that the Huanglian Jiedu Wan group showed a superior effect to the placebo group in improving oral ulcers， sore throat， and overall symptoms， with significant effects observed especially in sore throat and overall symptom analyses （P<0.01）. Spearman correlation analysis revealed that several clinical biomarkers positively correlated with "excess heat-toxicity" syndrome and its main symptom improvement， were also called "heat-related biomarkers"， including succinic acid， α-ketoglutaric acid， glycine， lactic acid， adenosine monophosphate （AMP）， tumor necrosis factor-α （TNF-α）， interferon-γ （IFN-γ）， interleukin-1β （IL-1β）， interleukin-4 （IL-4）， interleukin-6 （IL-6）， interleukin-8 （IL-8）， interleukin-10 （IL-10）， and so on. Conversely， clinical biomarkers negatively correlated with symptom severity， were also called "heat-clearing related biomarkers" after administration of Huanglian Jiedu Wan， including malic acid， fumaric acid， cis-aconitic acid， adrenocorticotropic hormone （ACTH）， IL-1β， IL-4， IL-8， succinic acid， and citric acid. The XGBoost classification model using all 52 biomarkers as variables achieved an average test accuracy of 0.754 and an average F1 score of 0.777. Feature importance analysis identified the scores of glutamic acid in saliva and IL-6 were the highest in all the variables， with importance scores of 0.081 and 0.080， respectively. After screening out 14 key variables and optimizing the parameters， model performance improved to an average accuracy of 0.758 and an F1 score of 0.798. Feature importance analysis further determined that the glutamic acid in saliva and IL-6 showed obvious changes after screening the variables， confirming the good syndrome prediction ability of the model constructed by these key clinical biomarkers. ConclusionThis study systematically elucidates the correlation between syndrome improvement and clinical biomarkers of Huanglian Jiedu Wan in the treatment of "excess heat-toxicity" syndrome. An XGBoost classification model based on key clinical biomarkers is successfully established， achieving effective prediction of the symptoms related to the "excess heat-toxicity" syndrome such as oral ulcers and sore throat and providing a new insight for objective identification of traditional Chinese medicine syndromes.

Objective:To compare the pregnancy outcomes of surviving fetuses in monochorionic diam-niotic(MCDA)twin pregnancies after selective feticide or spontaneous single intrauterine fetal demise(sIUFD),and to explore the influencing factors of prognosis.Methods:A total of 219 cases of intra-uterine death of one fetus in MCDA twin pregnancies admitted to Peking University Third Hospital from September 2010 to August 2021 were collected.According to the mode of fetal death,they were divided into the spontaneous sIUFD group(120 cases)and the selective feticide group(99 cases).Data on the maternal conditions during pregnancy,the situation of the intrauterine-dead fetus,and pregnancy out-comes were collected for retrospective case-analysis.Results:The live-birth rates of surviving fetuses in the spontaneous sIUFD group and the selective feticide group were 85.0％and 81.8％respectively,and the total perinatal survival rates of surviving fetuses were 73.3％and 81.8％respectively,and there were no statistically significant differences.Compared with the spontaneous sIUFD group,the selective feticide group had a greater gestational week at delivery,and lower rate of preterm birth before 37 weeks,neonatal asphyxia,and early neonatal mortality.Using the gestational week at delivery as the outcome variable,Cox regression analysis showed that the mode of fetal death was not a risk factor affecting the gestational week at delivery of the surviving fetus,while gestational hypertension and the gestational week of fetal death were independent risk factors affecting the gestational week at delivery of the surviving fetus.Using preterm birth before 37 weeks,intrauterine death of the surviving fetus,and abnormal neonatal cranial ultrasound as outcome variables respectively,unconditional logistic regression analysis showed that the mode of fetal death,the gestational week of fetal death,the position of the dead fetus,and fetal complications were independent risk factors affecting the outcomes of the above-mentioned survi-ving fetuses.According to the results of the univariate analysis,the above risk factors were included in the multivariate regression analysis,and the results were the same as those of the univariate analysis.Conclusion:For MCDA twin pregnancy patients with severe twin-related complications,the prognosis of surviving fetuses after selective feticide is better.The proactive intrauterine intervention and treatment are of great significance for improving the prognosis of surviving fetuses.

Objective:To observe the relationship between preoperative controlling nutritional status(CONUT)score and cognitive impairment,as well as short-term prognosis after intravenous thrombolysis(IVT)in patients with acute ischemic stroke(AIS).Methods:187 patients with AIS who were admitted to Shandong Provincial Third Hospital from January 2023 to May 2024 were selected,they were divided into non cognitive impairment group(n=106)and cognitive impairment group(n=81)based on whether cognitive impairment occurred,they were divided into poor prognosis group(n=58 cases)and good prognosis group(n=129 cases)according to the prognosis.Preoperative CONUT scores of patients with AIS for different cognitive impairments and prognoses were compared,correlation was analyzed by Spearman rank correlation,influencing factors were analyzed by multivariate logistic regression model.Results:Preoperative CONUT score in the cognitive impairment group was higher than that in the non cognitive impairment group(P＜0.05).Preoperative CONUT score in the poor prognosis group was higher than that in the good prognosis group(P＜0.05).Spearman rank correlation test results showed that,preoperative CONUT score was positively correlated with cognitive impairment and short-term prognosis after IVT(P＜0.05).Cognitive impairment were associated with age,concomitant hypertension,baseline national institutes of health stroke scale(NIHSS)score,and 25 hydroxyvitamin D3[25-(OH)2D3](P＜0.05).Age increase,concomitant hypertension,baseline NIHSS score increase,25-(OH)2D3 decrease,preoperative CONUT score increase were risk factors for cognitive impairment in patients with AIS(P＜0.05).Conclusion:Preoperative CONUT score increase is positively correlated with cognitive impairment and short-term prognosis after IVT.Meanwhile,age increase,concomitant hypertension,baseline NIHSS score increase,25-(OH)2D3 decrease,preoperative CONUT score increase are risk factors for cognitive impairment in patient with AIS.

Objective To investigate the low-dose CT image denoising and generalization performance of the existing mainstream deep learning based denoising networks.Methods The public AAPM Mayo challenge dataset was used to train the denoising network using 3 image-domain methods(REDCNN,WGAN-VGG,CTformer)and 2 projection-image dual-domain methods(VVBP-UNet,CLEAR),separately.The denoising networks were evaluated quantitatively for peak signal-to-noise ratio(PSNR),structural similarity index,root mean square error,number of network parameters and floating point operations,and their generalization performance was analyzed on the AbdomenCT-1K Dataset.Results Image-domain denoising networks effectively suppressed low-dose CT image noise,with REDCNN demonstrating the best denoising performance and achieving a PSNR of 42.0988 dB.The dual-domain denoising networks were better at preserving tiny tissue structures while removing image noise,with VVBP-UNet performing the best and increasing PSNR to 42.150 9 dB.Conclusion The projection-image dual-domain method exhibits superior denoising and generalization performances than the image-domain method,despite requiring a relatively large amount of network parameters and computations.When computing resources are sufficient,the denoising results obtained by dual-domain method better fulfill the requirements for clinical diagnosis.

Objective:To observe the relationship between preoperative controlling nutritional status(CONUT)score and cognitive impairment,as well as short-term prognosis after intravenous thrombolysis(IVT)in patients with acute ischemic stroke(AIS).Methods:187 patients with AIS who were admitted to Shandong Provincial Third Hospital from January 2023 to May 2024 were selected,they were divided into non cognitive impairment group(n=106)and cognitive impairment group(n=81)based on whether cognitive impairment occurred,they were divided into poor prognosis group(n=58 cases)and good prognosis group(n=129 cases)according to the prognosis.Preoperative CONUT scores of patients with AIS for different cognitive impairments and prognoses were compared,correlation was analyzed by Spearman rank correlation,influencing factors were analyzed by multivariate logistic regression model.Results:Preoperative CONUT score in the cognitive impairment group was higher than that in the non cognitive impairment group(P＜0.05).Preoperative CONUT score in the poor prognosis group was higher than that in the good prognosis group(P＜0.05).Spearman rank correlation test results showed that,preoperative CONUT score was positively correlated with cognitive impairment and short-term prognosis after IVT(P＜0.05).Cognitive impairment were associated with age,concomitant hypertension,baseline national institutes of health stroke scale(NIHSS)score,and 25 hydroxyvitamin D3[25-(OH)2D3](P＜0.05).Age increase,concomitant hypertension,baseline NIHSS score increase,25-(OH)2D3 decrease,preoperative CONUT score increase were risk factors for cognitive impairment in patients with AIS(P＜0.05).Conclusion:Preoperative CONUT score increase is positively correlated with cognitive impairment and short-term prognosis after IVT.Meanwhile,age increase,concomitant hypertension,baseline NIHSS score increase,25-(OH)2D3 decrease,preoperative CONUT score increase are risk factors for cognitive impairment in patient with AIS.

Objective To investigate the low-dose CT image denoising and generalization performance of the existing mainstream deep learning based denoising networks.Methods The public AAPM Mayo challenge dataset was used to train the denoising network using 3 image-domain methods(REDCNN,WGAN-VGG,CTformer)and 2 projection-image dual-domain methods(VVBP-UNet,CLEAR),separately.The denoising networks were evaluated quantitatively for peak signal-to-noise ratio(PSNR),structural similarity index,root mean square error,number of network parameters and floating point operations,and their generalization performance was analyzed on the AbdomenCT-1K Dataset.Results Image-domain denoising networks effectively suppressed low-dose CT image noise,with REDCNN demonstrating the best denoising performance and achieving a PSNR of 42.0988 dB.The dual-domain denoising networks were better at preserving tiny tissue structures while removing image noise,with VVBP-UNet performing the best and increasing PSNR to 42.150 9 dB.Conclusion The projection-image dual-domain method exhibits superior denoising and generalization performances than the image-domain method,despite requiring a relatively large amount of network parameters and computations.When computing resources are sufficient,the denoising results obtained by dual-domain method better fulfill the requirements for clinical diagnosis.

Objective:To investigate the distribution of CGG repeat numbers in the FMR1 gene among reproductive-age women in China, providing data reference for carrier screening and genetic counseling of Fragile X syndrome. Methods:This cross-sectional study recruited 16 610 reproductive-age women from 12 medical institutions between July 2022 and October 2023. Peripheral venous blood samples (3 mL) were collected, and genomic DNA was extracted. The number of CGG repeats in the FMR1 gene was determined using the triplet-primed polymerase chain reaction (TP-PCR) combined with capillary electrophoresis technology. Statistical analyses were performed to assess the prevalence and distribution of CGG repeat expansions. Results:Among 16 610 women of childbearing age, 5 684 (34.220%) women had the same number of CGG repeats in the two alleles of FMR1 gene, and 10 926 (65.780%) women had different numbers of repeats in the two alleles. Among the 33 220 FMR1 alleles in 16 610 women of reproductive age, the most common CGG repeat numbers were 29 [48.645% (16 160/33 220)] and 30 [26.276% (8 729/33 220)], while the most frequent CGG genotype was CGG 29/29 [24.726% (4 107/16 610)]. The CGG repeat numbers of FMR1 gene were normal in 16 498 women (99.326%). Among the 112 women (0.674%) with CGG repeat abnormities, 96 (0.578%) women were classified as intermediate carriers, 15 (0.090%) as premutation carriers, and 1 (0.006%) as a full mutation carrier, whose CGG genotype was (36, >200). Conclusion:In the general reproductive-age female population in China, the normal CGG repeat numbers of the FMR1 gene account for 99.326%, while the intermediate carrier rate is 0.578%, and the combined carrier rate of the premutation and full mutation types is 0.096%.

Objective:To analyze the symptoms,diagnosis and treatment of upper urinary tract calculi patients combined with mild and moderate benign prostatic hyperplasia(BPH)after ureteral stent implantation.Methods:One hundred and six BPH pa-tients who were hospitalized for upper urinary tract calculi and had ureteral stents retained from January 2019 to December 2022 were selected and divided into 2 weeks group and 4 weeks group according to the time of removal of ureteral stents after surgery.Their gener-al clinical data were analyzed and compared.International Prostatic Symptom Scale(IPSS),postoperative ureteral Stent Symptom Questionnaire(USSQ),and incidence of adverse events after ureteral stent removal were recorded before and after removal.Results:The scores of IPSS were significantly increased in all patients,and symptoms in urinary tract had improved significantly after discharge(P＜0.05).Compared with the 2 weeks group,the USSQ score of the 4 weeks group was significantly increased(P＜0.05).And no significant adverse event was observed in the 2 weeks group after the removal of ureteral sten.Conclusion:IPSS score and USSQ score increased significantly during stent implantation in BPH patients with lithiasis.And complications increased sig-nificantly over time.Following thorough clinical assessment,early ureteral stent removal demonstrates both safety and efficacy,repre-senting an optimal therapeutic approach in selected cases.

AIM To establish the preparation process and quality standard for Zhenggu Pills.METHODS With decoction time,decoction frequency and water addition as influencing factors,comprehensive score for extract yield and transfer rates of epicatechin and naringin as an evaluation index,the decoction process was optimized by orthogonal test.With sugarless paste relative density,medicinal powder fineness,sugarless paste-corn starch ratio,drying temperature and drying time as influencing factors,soft material traits,pill formability,moisture and disintegration time limit as evaluation indices,the formability process was optimized by single factor test.TLC was adopted in the qualitative identification of Dipsaci Radix,salt-processed Psoraleae Fructus,cooked Rhei Radix et Rhizoma and Notoginseng Radix et Rhizoma.HPLC was used for the content determination of paeoniflorin and naringin.RESULTS The optimal decoction process was determined to be 0.5 h for decoction time,two times for decoction frequency,and 10 times for water addition,the comprehensive score was 0.93.The optimal formability process was determined to be 1.21-1.22 for sugarless paste relative density,80 mesh for medicinal powder fineness,1∶0.17-1∶0.18 for sugarless paste-corn starch ratio,70 ℃ for drying temperature,and 24 h for drying time,good soft material traits and pill formability were observable,and moisture and disintegration time limit accored with 2020 edition of Chinese Pharmacopoeia requirements.The TLC spots were clear without negative interference.Two constituents showed good linear relationships within 61.30-490.41 μg/mL(r=0.999 8)and 3.27-26.18 μg/mL(r=0.999 8),whose average recoveries were 100.15％and 98.15％with the RSDs of 0.55％and 2.30％,respectively.CONCLUSION This stable,reliable and specific method can be used for the production and quality evaluation of Zhenggu Pills.