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.

Polypoidal choroidal vasculopathy(PCV)is one of the important subtypes of neovascular age-related macular degeneration(nARMD), which causes severe vision loss. It is necessary to distinguish PCV from other nARMD subtypes to guide the clinical treatment plans and predict disease outcomes. In recent years, artificial intelligence(AI)has been widely used in the diagnosis and research of ophthalmic diseases. By utilizing machine learning or deep learning combined with examination images in disease classification, lesion segmentation, and quantitative assessment, etc. This article reviews the recent applications of AI in the differential diagnosis of PCV through various examination images, the segmentation and quantification of biomarkers, as well as the prediction of genotype, response to anti-vascular endothelial growth factor(VEGF)therapy, and the short-term risk of vitreous hemorrhage. It summarizes the difficulties and challenges in clinical practice of AI and looks forward to the advantages and development trends of AI in PCV applications in the future. The article aims to provide more information for further research and application, thereby improving the diagnostic rate of PCV, optimizing treatment plans, and improving patients' visual prognosis.

Polypoidal choroidal vasculopathy(PCV)is one of the important subtypes of neovascular age-related macular degeneration(nARMD), which causes severe vision loss. It is necessary to distinguish PCV from other nARMD subtypes to guide the clinical treatment plans and predict disease outcomes. In recent years, artificial intelligence(AI)has been widely used in the diagnosis and research of ophthalmic diseases. By utilizing machine learning or deep learning combined with examination images in disease classification, lesion segmentation, and quantitative assessment, etc. This article reviews the recent applications of AI in the differential diagnosis of PCV through various examination images, the segmentation and quantification of biomarkers, as well as the prediction of genotype, response to anti-vascular endothelial growth factor(VEGF)therapy, and the short-term risk of vitreous hemorrhage. It summarizes the difficulties and challenges in clinical practice of AI and looks forward to the advantages and development trends of AI in PCV applications in the future. The article aims to provide more information for further research and application, thereby improving the diagnostic rate of PCV, optimizing treatment plans, and improving patients' visual prognosis.

AIM: To quantitatively evaluate the clinical characteristics of haze after transepithelial photorefractive keratectomy(TPRK)for astigmatism using corneal densitometry.METHODS:In this retrospective clinical study, a total of 74 patients(106 eyes)with astigmatism ≥1.25 D who underwent TPRK in our hospital from October 2022 to December 2024 were continuously collected. All of the study subjects were divided into transparent group(65 eyes)and haze group(41 eyes)based on whether haze occurred after surgery. Pentacam examination was performed before and after surgery, and corneal densitometry was recorded at the time points of preoperation, 1 mo postoperation in the transparent group and the most severe haze degree in the haze group. The collected corneal densitometry included the average densitometry of the entire corneal layer in the central 2 mm, 2-6 mm, and 6-10 mm areas, as well as the average densitometry of the entire layer of the corneal section in the center 6 mm of the astigmatism axis(astigmatism expressed in negative cylindrical form)and orthogonal axis(the axis perpendicular to the astigmatism axis), and the average densitometry of the entire layer of the corneal section in the nasal and temporal 2-6 mm areas of the astigmatism axis in the haze group of patients with regular astigmatism. The change in corneal densitometry after surgery compared with that before surgery was calculated.RESULTS:There was no statistically significant difference in baseline data such as gender, age, and spherical equivalent between the transparent group and the haze group(all P>0.05). The change in corneal densitometry in the 2-6 mm area of the haze group was greater than that in the transparent group(Z=-2.226, P=0.026), while there was no significant difference in the change of corneal densitometry in the central 2 mm and 6-10 mm areas between the two groups(both P>0.05). There was no significant difference in the change of corneal densitometry between the transparent group and haze group along the orthogonal axis(all P>0.05), while the change of corneal densitometry in the haze group along the astigmatism axis was greater than that in the transparent group(Z=-2.371, P=0.018). The temporal corneal densitometry of patients with regular astigmatism in the haze group after surgery was higher than that of the nasal side, and the change in corneal densitometry was also greater than that of the nasal side(Z=-4.288, P<0.001; Z=-4.043, P<0.001).CONCLUSION:Unlike spherical correction for myopia and hyperopia, haze after TPRK for astigmatism was mainly manifested in the peripheral cutting area of the astigmatism axis, and patients with regular astigmatism had a higher probability or severity of haze on the temporal side of the astigmatism axis than on the nasal side.

Objective: To analyze the epidemiological characteristics and changing trends of non suicidal self injury (NSSI) behaviors among middle school students in Jiading District of Shanghai, from 2015 to 2023, so as to provide a basis for the development of NSSI prevention and control measures among students. Methods: Using a stratified cluster random sampling method, a total of five times for Shanghai Adolescent Health Risk Behavior Surveys were conducted for every two years in Jiading District of Shanghai from 2015 to 2023. A total of 5 231 middle school students from junior high schools and senior high schools were selected for questionnaire surveys. Intergroup comparisons were performed using the x 2 test or the χ 2 trend test, and the JointPoint 5.0 software was used to analyze the changing trends, with the annual percent change (APC) used for evaluation. A binary Logistic regression model was employed to analyze the related factors of NSSI behavior among middle school students. Results: In 2023, the reported NSSI rate among middle school students in Jiading District was 14.2%. The rate was significantly higher among junior high school students (17.1%) than that among senior high school students (11.1%), and higher among females (19.2%) than that among males (10.0%) ( χ 2=10.04, 23.21, both P <0.01). From 2015 to 2023, the overall reported NSSI rate showed an increasing trend, rising from 8.6% in 2015 to 14.2% in 2023 ( χ 2 trend =22.25), with an APC of 6.64% ( t =3.49), and the APC for girls was 9.79 % ( t =3.20) (all P <0.05). Among students reporting NSSI, the proportion experiencing ≥6 episodes increased from 10.8% in 2015 to 19.2% in 2023 ( χ 2 trend =6.57, P <0.05). Multivariate Logistic regression analysis indicated that girls, junior high school students, those with insomnia, depressive emotion and drinkers had higher risks of NSSI, compared to boys, senior high school students, those without insomnia, non depressive emotion students and non drinkers ( OR =1.71, 1.96, 3.44, 4.76, 1.77, all P < 0.05 ). Conclusions The reported rate of NSSI among middle school students in Jiading District of Shanghai, increased annually from 2015 to 2023, and the proportion of repeated NSSI also showed an upward trend. Early intervention measures targeting middle school students, especially junior high school students and females, should be implemented to prevent and control its occurrence and development.

Objective To explore the application value of CT classification of lumbar spinal stenosis(LSS)in selecting endoscopic decompression surgery approach.Methods The clinical data and CT imaging materials of 300 patients with LSS,who received percutaneous endoscopic decompression surgery from March 2018 to December 2024 were selected from Hengshui Municipal People's Hospital in Hebei(Halison International Peace Hospital),were retrospectively analyzed.Preoperative CT scan was performed in all patients.Taking endoscopic classification as the golden standard,the consistency between CT classification results and endoscopic classification results was assessed by Kappa consistency analysis.The effect of surgery of different approaches for percutaneous endoscopic decompression surgery was compared.Results CT diagnostic classification of type Ⅰ LSS was obtained in 87 patients(among them 3 patients with type Ⅲ LSS were misdiagnosed as type Ⅰ LSS),type Ⅱ LSS in 141 patients and type ⅢLSS in 72 patients,the total diagnostic accuracy rate was 97.67％.Using endoscopic classification as the gold standard,the Kappa values for CT diagnosis of type Ⅰ,type Ⅱ and type Ⅲ were 0.975,1.000 and 0.973,respectively.According to the CT classification results,all 300 patients successfully selected different surgical approaches to complete the surgery,and their clinical symptoms were significantly relieved without significant complications.After surgery,the Oswestry disability index(ODI)and visual analogue scale(VAS)scores of leg/lower back in patients with different LSS types showed a decreasing trend(P＜0.05).After treatment,the total frequency of taking non-steroidal drugs was significantly lower than that before surgery(P＜0.05).Conclusion The classification of LSS is highly consistent between CT scan and endoscopic examination,which is of great value for the selection of percutaneous endoscopic decompression surgery approach.

Objective:To analyze the clinical features and genetic etiology of 17 Chinese pedigrees affected with X-linked intellectual disability (XLID).Methods:Seventeen pedigrees affected with unexplained intellectual disability which had presented at Henan Provincial People′s Hospital from May 2021 to May 2023 were selected as the study subjects. Clinical data of the probands and their pedigree members were collected. Trio-whole exome sequencing (Trio-WES), Sanger sequencing and X chromosome inactivation (XCI) analysis were carried out. Pathogenicity of candidate variants was predicted based on the guidelines from the American College of Medical Genetics and Genomics and co-segregation analysis.Results:The 17 probands, including 9 males and 8 females with an age ranging from 0.6 to 8 years old, had all shown mental retardation and developmental delay. Fourteen variants were detected by genetic testing, which included 4 pathogenic variants ( MECP2: c. 502C>T, MECP2: c. 916C>T/c.806delG, IQSEC2: c.1417G>T), 4 likely pathogenic variants ( MECP2: c. 1157_1197del/c.925C>T, KDM5C: c. 2128A>T, SLC6A8: c. 1631C>T) and 6 variants of uncertain significance ( KLHL15: c. 26G>C, PAK3: c. 970A>G/c.1520G>A, GRIA3: c. 2153C>G, TAF1: c. 2233T>G, HUWE1: c. 10301T>A). The PAK3: c.970A>G, GRIA3: c. 2153C>G and TAF1: c. 2233T>G variants were considered as the genetic etiology for pedigrees 12, 14 and 15 by co-segregation analysis, respectively. The proband of pedigree 13 was found to have non-random XCI (81: 19). Therefore, the PAK3: c. 1520G>A variant may underlie its pathogenesis. Conclusion:Trio-WES has attained genetic diagnosis for the 17 XLID pedigrees. Sanger sequencing and XCI assay can provide auxiliary tests for the diagnosis of XLID.

Objective:To investigate the clinical effects of free posterior interosseous artery perforator flap on reconstruction of the soft tissue defects of multiple fingers in one hand.Methods:Clinical data of 9 patients with soft tissue defect of multiple fingers in one hand admitted to the Department of Hand Surgery, Yongkang Orthopedic Hospital between January 2021 and August 2023 were retrospectively studied. The patients were 7 males and 2 females, aged between 19 and 55 years old. The soft tissue defects of 2 patients with 3 fingers injury and 7 patients with 2 fingers injury were reconstructed with free posterior interosseous artery perforator flaps. The size of defects in single finger was 1.5 cm×2.5 cm-3.0 cm×4.5 cm. The size of flap was 2.5 cm×7.0 cm-3.5 cm×13.0 cm. The posterior cutaneous nerve of the forearm were sutured to the intrinsic nerve of palmar side of the 14 fingers. Donor sites in forearm were directly sutured. After discharge, regular follow-up at outpatient clinic and through WeChat interviews were conducted to observe the appearance and texture of the flaps, finger fullness, donor site function and appearance, as well as patient satisfaction. For the flaps with anastomosis of cutaneous nerve, the recovery of TPD of the flap was tested. Sensory recovery was assessed according to the British Medical Research Council (BMRC) sensory function assessment criteria. Hand functions were evaluated using the Total Active Movement (TAM) of fingers of the Hand Surgery of the Chinese Medical Association.Results:All of the 20 flaps survived and were evaluated through follow-up visits, which ranged from 6 to 25 months with an average of 13 months. The flaps were soft, unbloated and without obvious pigmentation. The protective sensations were recovered with an average static TPD of 14 flaps anastomosed with cutaneous nerve was of 9.7 (7-13) mm. Among them, S 3+ 10 fingers, S 3 4 fingers; 6 fingers of flap without sutured cutaneous nerve, S 2 5 fingers, S 1 1 finger. According to the TAM of Hand Surgery of Chinese Medical Association, the results were excellent for 15 fingers and good for 5 fingers. There was no scar contracture in the forearm donor sites and motor function was not affected. Conclusion:Posterior interosseous artery perforator flap has the advantages of thin flap, similar texture to the hand, good recovery in sensory, and minimal damage to the donor site. Therefore, it is a good option in reconstruction of soft tissue defects of multiple fingers in one hand.

Objective To explore potential genes associated with the pathogenesis of hypospadias using weighted Gene co-expression network analysis(WGCNA).Methods The WGCNA algorithm was used to process the hypospadias-related dataset GSE35034,and then a gene co-expression weight network was constructed to screen the modules with the highest correlation with hypospadias,and the genes in the modules were enriched and detected by gene ontology(GO),Kyoto Encyclopedia of Genes and Genomes(KEGG).Differential analysis was also performed to screen out differential genes.The differential genes were imported into the String database.Using Cytoscape software,the hub genes in the network were identified.The results screened by the above three methods were combined and analyzed,and the core genes in the intersection set were screened.Using the external dataset GSE121712,the core genes were verified by mRNA expression changes and subject work characterization receiver operating characteristic(ROC)curve diagnosis.Results Fifteen co-expression modules were obtained based on the WGCNA method.Ninety-three common differential genes meeting the conditions were obtained by differential analysis.Ten core genes were finally obtained by Cytoscape software analysis.Finally MEbrown module,differential genes and the 10 core genes yielded a total of 2 intersecting genes:FBXL16 and SYNDIG1.ROC curves verified that the intersecting genes were differentially expressed in patients with hypospadias versus normal subjects.Conclusion In this study,two key genes with significant correlation with hypospadias were obtained by WGCNA,which may be used for the early diagnosis and treatment of hypospadias after further study.