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 investigate the biomechanical differences in plantar pressure,postural stability,and plantar Visual Analogue Scale(VAS)scores between normal feet and unilateral/bilat-eral pes cavus,reveal their unique neuromechanical compensation mechanisms,and construct a sta-bility early warning model based on the minimum center of pressure(COP)trajectory classification.Methods A total of 70 patients with pes cavus from December 2023 to October 2024 were selected as study subjects,including 33 patients in the unilateral pes cavus group and 37 patients in the bilat-eral pes cavus group.During the same period,32 normal feet were included as normal foot group.A flat-panel plantar pressure testing system was used to collect dynamic plantar pressure data and COP trajectories from three groups at a self-selected walking speed.There were no statistically significant differences in baseline data such as age,gender,and body mass index among the three groups(P＞0.05).One-way analysis of variance and the Wilcoxon rank-sum test were used to compare the differences in maximum pressure,contact area,VAS scores,and the 95％confidence ellipse area of the COP among the three groups in 10 plantar regions.Results Patients with pes cavus exhibited lower peak pressure in the MF region compared to normal feet,while higher peak pressure in the M2,M3,and MH regions.Patients with bilateral pes cavus showed lower peak pressure in the T1 region compared to normal feet,and patients with unilateral pes cavus had lower peak pressure in the LH region compared to the normal group(P＜0.05).The plantar contact area in patients with pes cavus was reduced in the T1,M2,M3,M4,MF,and MH regions compared to normal feet(P＜0.05).The 95％confidence ellipse area of the COP was larger in both the bilateral and uni-lateral pes cavus groups compared to the normal foot group(P＜0.001).Unilateral pes cavus pres-ented a specific lateral COP drift(amplitude of 3 to 4 cm),which is a biomechanical manifestation of compensatory eversion of the unaffected foot.Patients with bilateral pes cavus exhibited a"bimod-al oscillation"trajectory(amplitude of 6 to 8 cm),suggesting possible vestibular-spinal regulatory dysfunction and the poorest postural stability.In the pes cavus group,there was a significant in-crease in pressure in the M2,M3,and MH regions,with peak pressures exceeding 190 kPa in pa-tients with bilateral pes cavus,which was highly correlated with plantar pain and could serve as a pain early warning threshold.Conclusion Unilateral and bilateral pes cavus exhibit significantly different neuromechanical compensation patterns.The classification based on the"lateral drift"and"bimodal oscillation"characteristics of the COP trajectory can serve as a stability early warning indi-cator for assessing fall risk.Decompression interventions targeting the key pressure regions of M2,M3,and MH(such as customized orthotic insoles)are the core strategies for alleviating pain and optimizing dynamic gait stability.

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.

BACKGROUND: Quantitative flow ratio (QFR) holds significant value in guiding drug-coated balloon (DCB) treatment and enhancing outcomes. However, the predictive capability of post-angioplasty QFR for long-term clinical events in patients with de novo lesions who receive DCB treatment remains uncertain. The aim of this study was to explore the potential significance of post-angioplasty QFR measurements in predicting clinical outcomes in patients underwent DCB treatment for de novo lesions. METHODS: Patients who underwent DCB-only intervention for de novo lesions were enrolled. QFR was conducted after DCB treatment. The patients were then categorized based on post-angioplasty QFR. The primary endpoint was major adverse cardiac events (MACE), encompassing all-cause death, cardiovascular death, nonfatal myocardial infarction, stroke, and target vessel revascularization. RESULTS: A total of 553 patients with 561 lesions were included. The median follow-up period was 505 days, during which 66 (11.8%) MACEs occurred. Based on post-procedural QFR grouping, there were 259 cases in the high QFR group (QFR > 0.93) and 302 cases in the low QFR group (QFR ≤ 0.93). Kaplan-Meier analysis revealed a significantly higher cumulative incidence of MACE in the low QFR group (log-rank P = 0.004). The multivariate Cox proportional hazards model demonstrated a significant inverse correlation between QFR and the occurrence of MACEs (HR = 0.522, 95%CI: 0.289-0.942, P = 0.031). Landmark analysis indicated that high QFR had a significant reducing effect on the cumulative incidence of MACEs within 1 year (log-rank P = 0.016) and 1-5 years (log-rank P = 0.026). CONCLUSIONS In patients who underwent DCB-only treatment for de novo lesions, higher post-procedural QFR values (> 0.93) were identified as an independent protective factor against adverse prognosis.

Objective: To explore the efficacy of vonoprazan fumarate in the treatment of laryngopharyngeal reflux disease（LPRD） evaluated by the Chinese version of the RSS-12 scale. Methods:A total of 100 LPRD patients treated in the otolaryngology-head and neck surgery outpatient clinic of our hospital were randomly divided into two groups（50 cases each）. The observation group was treated with vonoprazan fumarate（20 mg, once daily）, and the control group was treated with esomeprazole enteric-coated capsules（20 mg, twice daily） for 12 weeks. The selected observation indicators in this study included RSI, the Chinese version of RSS-12, and RFS scores before and after treatment. Results:Prior to treatment, there was no statistically significant difference in the Chinese version of RSS-12, RSI, and RFS between the two groups（P>0.05）. After 8 and 12 weeks of antacid treatment, both the Chinese version of RSS-12 and RSI significantly decreased in both group （P<0.05）. The changes in symptoms were particularly noticeable between 0-8 weeks of treatment according to the Chinese version of RSS-12 and RSI. After 12 weeks of treatment, the RFS scores significantly decreased compared to pretreatment levels （P<0.05）. After 12 weeks of antacid treatment, according to the Chinese version of RSS-12, 80% of patients in the observation group showed a good therapeutic response, compared to 64% in the control group; according to RSI, 90% of patients in the observation group showed a good therapeutic response, compared to 84% in the control group. There was no statistically significant difference in the treatment effect between the two groups after 12 weeks of treatment（P>0.05）. Conclusion:Vonoprazan fumarate can significantly improve the symptoms and signs of laryngopharyngeal reflux, and their treatment effect is not inferior to proton pump inhibitors. Compared with RSI, the Chinese version of RSS-12 can serve as a new screening tool for clinical diagnosis of LPRD in China.
Humans ; Sulfonamides/therapeutic use* ; Male ; Pyrroles/therapeutic use* ; Female ; Laryngopharyngeal Reflux/drug therapy* ; Treatment Outcome ; Middle Aged ; Esomeprazole/therapeutic use* ; Proton Pump Inhibitors/therapeutic use* ; Adult

OBJECTIVE: To explore the clinical features of patients with necrotizing soft tissue infection (NSTI) and the related factors for sepsis, so as to provide a basis for early intervention and improvement of patients' prognosis. METHODS: A retrospective case series study was conducted to analyze the clinical data of NSTI patients admitted to the department of burns and wound repair surgery of Guangdong Provincial People's Hospital from October 2021 to December 2024. Demographic information, underlying diseases, infection characteristics, laboratory test results and etiological findings at admission, treatment status, occurrence of complications (including sepsis) and prognosis were collected. Univariate and multivariate Logistic regression analyses were used to identify the associated factors for sepsis in NSTI patients. Receiver operator characteristic curves (ROC curves) were plotted to evaluate the predictive value of individual and combined factors for sepsis. RESULTS: A total of 159 NSTI patients were enrolled, mainly middle-aged and elderly males. Most patients had comorbidities, including diabetes mellitus (110 cases, 69.2%) and hypertension (67 cases, 42.1%). The main infection site was the lower extremities (104 cases, 65.4%). Common symptoms included redness (96 cases, 60.4%), swelling (129 cases, 81.1%), local heat (60 cases, 37.7%), pain (100 cases, 62.9%), and skin ulceration or necrosis (9 cases, 5.7%). Imaging findings included soft tissue swelling (66 cases, 57.9%), gas accumulation (41 cases, 36.0%), and abnormal signal/density shadows (50 cases, 43.9%). Staphylococcus aureus was the main pathogenic bacterium [12.0% (31/259)], and drug-resistant Escherichia coli had the highest detection rate among drug-resistant bacteria [35.1% (13/37)]. Regarding debridement and repair, most patients (80 cases, 50.3%) underwent debridement ≥ 72 hours after admission, while only 10.1% (16 cases) received debridement within 6 hours. Most patients underwent multiple debridements, with 2 times of debridements being the most common (68 cases, 42.8%), and the maximum times of debridements reached 6. The largest number of patients received secondary suture (44 cases, 27.7%). In terms of complications, sepsis was the most common (66 cases, 41.51%), followed by acute kidney injury, respiratory failure requiring mechanical ventilation, and multiple organ dysfunction syndrome (MODS), while disseminated intravascular coagulation (DIC) was the least common. During the follow-up period, 9 patients (5.66%) were readmitted within 90 days, and 11 patients died, with a mortality rate of 6.92%. Univariate analysis showed that diabetes, coronary heart disease, gout, body temperature, heart rate, C-reactive protein, platelet count, total bilirubin, albumin, creatinine, out-of-hospital treatment, and out-of-hospital use of antimicrobial agents were significantly associated with sepsis in NSTI patients (all P < 0.05). Multivariate Logistic regression analysis showed that coronary heart disease [odds ratio (OR) = 30.085, 95% confidence interval (95%CI) was 2.105-956.935], C-reactive protein (OR = 1.026, 95%CI was 1.009-1.054), and total bilirubin (OR = 1.436, 95%CI was 1.188-1.948) were independent associated factors for sepsis in NSTI patients (all P < 0.05). ROC curve analysis revealed that the combination of the three predictors yielded the highest AUC for predicting sepsis in NSTI patients compared to any individual predictor [area under the curve (AUC) = 0.799 (95%CI was 0.721-0.878)]. CONCLUSIONS The clinical features of NSTI patients show certain regularity. Coronary heart disease, C-reactive protein, and total bilirubin are independent associated factors for sepsis in NSTI patients.
Humans ; Retrospective Studies ; Male ; Sepsis ; Soft Tissue Infections/microbiology* ; Female ; Middle Aged ; Aged ; Adult ; Prognosis ; Risk Factors ; Necrosis ; Logistic Models ; Fasciitis, Necrotizing

This article summarizes Professor Huang Guicheng's clinical experience in the syndrome differentiation and treatment of lumbar spinal stenosis using the theory of"diseases of tendons,bones and collaterals".It is believed that lumbar spinal stenosis be-longs to the syndrome of deficiency in the root and excess in the superficiality,and is closely related to the three zang organs of the liv-er,spleen and kidney.Deficiency of the liver and kidney leading to a lack of the source of qi and blood,insufficiency of the spleen and stomach giving rise to phlegm and blood stasis,and the invasion of wind,cold and dampness pathogens cause the disease.The key to the pathogenesis lies in the obstruction of the collaterals.Taking the principles of"nourishing the collaterals and strengthening the healthy qi,dredging the collaterals and expelling the pathogens"as the therapeutic principles,Professor Huang is proficient in using insect drugs.The medicinal power can directly reach the collaterals,so that the collaterals can be unobstructed and the qi and blood can flow smoothly,achieving the therapeutic effect of expelling the pathogens,unblocking the collaterals and restoring the healthy qi.

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.