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.

Owing to its inherent advantages—such as being non-destructive, rapid, highly molecule-specific, and minimally interfered with by moisture—Raman spectroscopy has been widely adopted in the fields of skin barrier function assessment, monitoring the transdermal penetration of active cosmetic ingredients, and the identification and quality control of cosmetic products. Despite these strengths, the practical application of this technique faces a significant bottleneck: the strong fluorescence background generated by endogenous skin components and exogenous cosmetic additives. Endogenous skin substances, such as structural proteins (e.g., collagen and elastin), metabolic coenzymes (e.g., nicotinamide adenine dinucleotide), and pigments (e.g., melanin), together with exogenous cosmetic constituents like organic colorants, chemical sunscreens, and fragrances, often possess strong absorption and emission characteristics. When excited by lasers, these components produce a fluorescence background that can be 10⁶ to 10⁸ times stronger than the Raman scattering signals, effectively masking the inherently weak vibrational fingerprint information. In recent years, driven by the rapid development of optoelectronic hardware and artificial intelligence algorithms, fluorescence suppression strategies have evolved from isolated, single-method approaches into comprehensive, multi-level synergistic systems. These systems are categorized into three distinct tiers: sample preparation, signal acquisition, and data processing. At the sample preparation level, techniques such as photobleaching and surface-enhanced Raman spectroscopy (SERS) are employed to eliminate or bypass the generation of fluorescence at the source. At the signal acquisition level, instrumental improvements—including the use of long-wavelength near-infrared excitation (typically 785 nm or 1 064 nm), confocal spatial filtering, and shifted excitation Raman difference spectroscopy (SERDS)— are utilized to physically isolate Raman signals from the fluorescence background. Furthermore, at the data processing level, numerical baseline correction methods such as polynomial fitting, penalized least squares (e.g., airPLS, arPLS), wavelet transform, and derivative algorithms are increasingly integrated into the analytical pipeline to extract Raman spectral features from mixed signals without increasing hardware costs or acquisition time. This review provides a systematic categorization and critical evaluation of these fluorescence suppression methods, detailing their underlying principles, technical advantages, and inherent limitations in diverse experimental setups. By focusing on critical application scenarios—including skin barrier assessment, percutaneous absorption monitoring, the routine quality control of cosmetics, and the emerging field of portable on-site detection—this paper explores the current state of technique selection and optimization. Finally, the article discusses future development trends, emphasizing the necessity of constructing adaptive, tiered suppression strategies, developing intelligent and automated data processing algorithms, and promoting the integration of portable, multi-modal diagnostic devices. The objective of this review is to provide a comprehensive technical reference to facilitate the transition of Raman spectroscopy from a specialized laboratory tool into a routine, robust analytical platform for advancements in skin science and cosmetic research.

Metabolic dysfunction-associated fatty liver disease （MAFLD） progresses to metabolic dysfunction-associated steatohepatitis （MASH） due to mitochondrial homeostasis imbalance and dysfunction in hepatocytes caused by various factors such as lipotoxicity and inflammatory infiltration. Recent studies have confirmed that mitochondrial injury is closely associated with chronic inflammation， with extracellular vesicle （EV） acting as a key mediator linking the two processes. This article systematically reviews the molecular mechanisms of hepatocyte mitochondrial dysfunction in MAFLD/MASH， highlights the regulatory role of hepatocyte-derived EV in intrahepatic inflammation， and discusses the potential application prospects of mitochondria-targeted therapies and intercellular communication interventions in MAFLD/MASH， in order to provide a theoretical basis for developing novel therapeutic strategies for these diseases.

Aim To explore the role and mechanism of epimedokoreanin B(EKB)in HepaRG cell pyroptosis through endoplasmic reticulum stress and NLRP1-me-diated pyroptosis pathway.Methods The effect of EKB on the viability of HepaRG cells at different con-centrations was determined by MTT assay,and the cell growth status was recorded by Incucyte.Four groups of HepaRG cells were set up.The control group was cul-tured with complete medium for 24 h;the drug admin-istration group was cultured with three concentration gradients of 6.25,12.5 and 25 μmol·L-1 of EKB for 24 h.Western blot was used to detect the expression levels of endoplasmic reticulum stress-related proteins and pyroptosis-related proteins in the cells of each group.Results HepaRG cells showed cytotoxicity at a concentration of 6.25 μmol·L-1 for 24 h,and the half maximal inhibitory concentration(IC50)was 12.41 μmol·L-1.Incucyte recordings of the cell growth status showed that the cells in the control group were in good growth status,and the vesicular pyropto-sis cells appeared in the different concentrations of EKB and the cells swelled and ruptured after 24 h.Western blot showed that the protein expression levels of endoplasmic reticulum stress-related proteins pERK,eIF-2α,ATF-4,GRP78,and CHOP significantly in-creased in HepaRG cells at 25 μmol·L-1 of EKB compared with the control group.The proteins of the classical pathway of cellular pyroptosis mediated by NLRP1,caspase-1,cleaved caspase-1,GSDMD,GS-DMD-N significantly increased in HepaRG cells.Con-clusion EKB administration induces HepaRG cell py-roptosis,and EKB activates HepaRG cells to undergo endoplasmic reticulum stress and activates the NLRP1/caspase-1/GSDMD-mediated pyroptosis pathway.

Objective To design an 8-channel gene analyzer to take the place of the widely used gene analyzer with problems in inconvenient consumable replacement and short storage time of electrophoresis polymer.Methods The 8-channel gene analyzer had its mechanical components composed of an automatic sample loading table,a polymer injection module,a high-voltage temperature control module,an optical module and an integrated U box,its electrical control system made up of a host computer(an embedded computer)and three slave computers(a sampling control board,a polymer injection control board and a high-voltage temperature control board).The automatic sample loading table involved in four motors and transmission systems for x,y,z directions and optical alignment,the transmission systems adopted mainly belt drive mode and the optical alignment motor had its threads with an anti-backlash structure;the polymer injuection module was manipulated by the polymer injection control board,and the polymer block was made of highly transparent acrylic material;the high-voltage temperature control module realized the regulation of electrophoresis voltage and the detection of electrophoresis current by the low-ripple precision high-voltage power supply,and controlled the temperature of the heating furnace by the proportional-integral-differential(PID)algorithm;the optical module consisted of an excitation module and a light-receiving module,which had the base of the reflector made of low expansion coefficient alloy material;the integrated U box had the electrophoresis polymer,capillary array,polymer block and anode buffer in a plastic housing;the host computer had the data acquisition software programmed with C# and C++,and the slave computers were controlled by STM32 SCM.Results The 8-channel gene analyzer had no significant differences with the widely used ABI3500 gene analyzer in resolution,precision accuracy and clinical results.Conclusion The 8-channel gene analyzer gains advantages in consumable replacement and storage time of electrophoresis polymer,and can meet the requirements for gene sequencing.[Chinese Medical Equipment Journal,2025,46(2):24-30]

Aim To explore the mechanism of the syn-ergistic effect of the ferroptosis inducer erastin com-bined with shikonin in promoting ferroptosis in human hypertrophic scar fibroblasts(HSFBs).Methods Hypertrophic scar tissues provided by the General Hos-pital of Ningxia Medical University were collected,and HSFBs were extracted.HSFBs were identified by HE staining and immunofluorescence.The inhibitory rates of Era and SHK on HSFBs at different concentrations were detected by CCK-8 assay,and the IC50 value was calculated.CompuSyn software was used to calculate the co-use index(CI).Control group,Erastin(Era)group,shikonin(SHK)group and Era+SHK group were set up,and the number and morphological chan-ges of cells were observed after 24 hours of interven-tion.The ability of cell migration and invasion was de-tected by scratch test and Transwell test.The changes of malondialdehyde(MDA),total iron ion and reactive oxygen species(ROS)were detected by corresponding biochemical kits.The expressions of collagen I,α-SMA and GOT1,SLC7A11,GPX4 and FTH1 were detected by Western blot.Results The IC50 value of Era and SHK of primary HSFBs was 2.22 μmol·L-1 and 3.94μmol·L-1 respectively,which was used as the single drug concentration for subsequent experiments.The CompuSyn software was employed to calculate the CI value when the two drugs were used in combination,and the concentrations corresponding to CI=0.39597(Era:1.2 μmol·L-1+SHK:1.5 μmol·L-1)were selected as subsequent combination concentrations(Because when CI was equal to 0.395 97,the concen-tration of each drug was lower than the concentration of single drug,and the inhibition rate of combined drug was greater than 50％).Compared with the monother-apy group,the number of HSFBs in the SHK+Era group was significantly reduced,cell membrane showed breakage and vesiculation,cell wrinkling became smal-ler,and cytoplasm was concentrated.The migration and invasion ability of HSFBs in the SHK+Era group were obviously weakened(P＜0.05),and the expres-sion of fibrosis-related proteins collagen Ⅰ and α-SMA was reduced(P＜0.05);the contents of MDA,total i-ron ions,and ROS in HSFBs of the SHK+Era group increased(P＜0.05),and the protein expression lev-els of SLC7A11,GOT1,GPX4,and FTH1 further de-creased(P＜0.05).Conclusions Erastin in combi-nation with shikonin can synergistically inhibit the pro-liferation,migration and fibrosis levels of HSFBs.The mechanism may be that erastin enhances the inhibition of shikotin on GOT1,increases the levels of cellular i-ron ions,ROS,and lipid peroxides,thereby promoting ferroptosis in HSFBs.

The development of breast cancer is closely related to the information transfer in its microenvironment.As a novel information communication tool,exosomes present non-coding RNAs that are involved in breast cancer cell proliferation,migration,invasion,tumour-associated fibroblasts ogenesis,cell cycle,degradation of oncogenes,etc.This paper reviews the relationship between exosomes and the tumour microenvironment and the role of their presenting non-coding RNAs on breast cancer as well as their clinical applications in order to provide new ideas for biological research and therapeutic strategies.

Objective:To evaluate the efficacy and feasibility of a domestically developed robotic surgical system based on fiber-optic dedicated line communication in cross-regional urological telesurgery.Methods:This was multicenter，single-arm，retrospective case series study. The data of patients who underwent urological telesurgeries using the telesurgical system between January 2023 and December 2024 were analyzed. The cohort included 59 patients from seven hospitals across China. Among the patients，47 were male（79.7%）and 12 were female（20.3%），with a median age of 63.0（56.0，68.0）years and a body mass index of（24.7 ± 3.0）kg/m 2. Surgical procedures included 32 radical prostatectomies，24 partial nephrectomies，one radical nephrectomy，one adrenalectomy，and one ureteral reconstruction. The perioperative indicators，pathological results and postoperative complications were analyzed. The network monitoring data were collected，and the perioperative data of patients，remote system monitoring data and costs were compared between the two communication modes of optical transport network（OTN）and cloud-connect network（CCN）. Results:All 59 remote surgeries were successfully completed，with a mean operative time of（138.0 ± 54.0）minutes，median intraoperative blood loss of 50.0（30.0，100.0）ml and a postoperative hospital stay of 5.0（4.0，6.0）days. No cases required reoperation，Clavien-Dindo grade ≥3 complications，or readmission. The geographical distance between the primary and remote surgical sites ranged from 450 to 2 800 km. Network monitoring revealed increased bidirectional latency with distance increasing：the shortest latency time（Hefei-Hangzhou，450 km）was（16.59 ± 0.80）ms，while the longest（Harbin-Hangzhou，2 200 km）latency time was（53.31 ± 0.31）ms. Average frame loss per procedure was 0?1.27 frames. The results of subgroup analysis comparing OTN and CCN communication modes showed no significant differences in operative time［（130.7 ± 70.5）minutes vs.（142.1 ± 42.9）minutes， P = 0.442］，postoperative hospitalization［6.0（4.0，8.0）d vs. 5.0（4.0，6.0）d， P = 0.581］，or readmission rates（0 vs. 0）. However，CCN demonstrated significant cost advantages with 500 RMB per operation vs. 3 000 RMB per operation for OTN. Conclusions:Urological telesurgery using fiber-optic communication is feasible. The CCN mode，with its cost-effectiveness，excellent usability，and multi-point interconnection flexibility，is currently the preferred communication model for telesurgical applications.

Objective:To assess the value of artificial intelligence（AI）assisted system in the diagnosis of malignancy in follicular thyroid tumours，and to compare with the diagnostic results of doctors with different levels of experience.Methods:A total of 101 nodules were retrospectively collected from 86 patients with follicular thyroid tumours who underwent surgical treatment at Peking Union Medical College Hospital，Chinese Academy of Medical Sciences，Peking Union Medical College from May 2016 to January 2018.The nodules were classified into risk group（29 patients，34 nodules，including 15 follicular carcinomas and 19 follicular tumours of indeterminable malignant potential）and benign group（59 atients，67 nodules，including 15 follicular adenomas and 52 nodular goitre adenomatoid hyperplasia）. The sensitivities，specificities and accuracies of the AI system，two doctors of different seniorities（one junior A and one senior B），and guidelines of thyroid ultrasound malignancy risk stratification［including the 2015 American Thyroid Guidelines（ATA），the 2017 American College of Radiology Thyroid Imaging Reporting and Data System（ACR TI-RADS），the 2020 Chinese Society of Ultrasound，Thyroid Imaging Reporting and Data System（C-TIRADS）］（classified by a senior doctor C）for diagnosing follicular tumours in the risk group and follicular carcinomas were calculated and compared.Results:The AI system showed a sensitivity of 46.7%，specificity of 89.6% and accuracy of 81.7% for diagnosing follicular carcinoma；and a sensitivity of 32.4%，specificity of 89.6% and accuracy of 70.3% for diagnosing follicular neoplasms（risk group）. Compared with junior doctor A，the specificity of AI system in diagnosing follicular cancer and follicular neoplasms（risk group）was higher（89.6% vs. 83.6%， P=0.020；89.6% vs. 73.1%， P=0.020），and the differences of sensitivity were not significant（46.7% vs. 32.4%， P=0.181；32.4% vs. 11.8%， P=0.073）. The difference of sensitivity and specificity were not statistically significant between the AI system and senior doctor B（all P＞0.05）.The differences in area under the curve for diagnosis of follicular carcinoma and follicular tumour（risk group）were not statistically significant between the AI system compared to junior doctor A，senior doctor B，the C-TIRADS，ATA guideline，and ACR TI-RADS（all P＞0.05）. Conclusions:Ultrasound-based AI-assisted diagnostic system is similarly efficient in diagnosing follicular thyroid tumours as experienced doctors，and the AI system diagnostic specificity is superior to that of junior doctors.