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.

Abelmoschi Corolla is extensively applied in managing diabetic nephropathy (DN) and other renal conditions due to its diuretic and detoxifying properties. The primary bioactive constituents of Abelmoschi Corolla are flavonoids, including notably rutin, hyperoside, isoquercitrin, hibifolin, myricetin, quercetin 3-O-β-D-glucuronide, and quercetin. These flavonoid components can influence the pathological progression of DN via a multi-target synergistic mechanism, effectively reducing proteinuria levels. This review examines the roles of Abelmoschi Corolla and its flavonoid components in modulating the key pathological aspects of DN and their underlying mechanisms, and briefly discusses the metabolic patterns of its bioactive components and the research progress in combined medication, aiming to provide a forward-looking scientific foundation for further investigating the molecular mechanisms and clinical applications of Abelmoschi Corolla in DN treatment.

BACKGROUND:The most common complication of traumatic femoral neck fractures after internal fixation is femoral head necrosis.Currently,many studies have reported on the risk factors that affect the occurrence and development of postoperative femoral head necrosis,but there is still a lack of tools to predict the risk of femoral head necrosis after internal fixation of femoral neck fractures.OBJECTIVE:To develop a predictive model that estimates the risk of femoral head necrosis shortly after patients with femoral neck fractures receive cannulated screw internal fixation.METHODS:A retrospective analysis reviewed clinical records of 172 patients who underwent cannulated screw internal fixation for femoral neck fractures at Department of Orthopedics of Mianyang Central Hospital from January 2013 to June 2023.Patients were categorized into two groups based on the presence or absence of femoral head necrosis within one year post-operation:the necrosis group and the non-necrosis group.Univariate analysis,Lasso regression,and multivariate Logistic regression techniques were employed to identify the determinants of femoral head necrosis.A nomogram prediction model was constructed using R language's"rms"package,version 4.0.The receiver operating characteristic curve was used to evaluate the discriminatory ability of the model.The Hosmer-Lemeshow test was used to evaluate the goodness of fit of the model,and the decision curve analysis was used to determine its clinical application benefits.Internal validation of the study was conducted using the Bootstrap method,involving 1 000 repeated samplings.To delve deeper into the primary factors influencing femoral head necrosis post-internal fixation of the femoral neck,this paper employed the SHAP method for data set analysis.RESULTS AND CONCLUSION:(1)The risk factors leading to femoral head necrosis in the short term after cannulated screw fixation of femoral neck fractures include:smoking,diabetes,Garden classification,fracture line location,reduction quality,age,and operation time.(2)The prediction model demonstrated robust performance,evidenced by an area under the curve of 0.940(95％Confidence Interval:0.903 to 0.977),indicating a high level of prediction accuracy.The model achieved a sensitivity of 90.2％and a specificity of 87.6％,indicating that its diagnostic performance was stable.The Hosmer-Lemeshow goodness-of-fit test yielded a chi-square value of 6.593 with a P-value of 0.581,confirming that the model's predictions closely align with the observed outcomes.(3)The calibration curve of the model also performed well,and its overall trend was very close to the ideal curve,further proving the high accuracy of the model.(4)The internal validation was carried out by the Bootstrap method with 1 000 repeated samplings,and the area under the curve of the model internal validation was still as high as 0.939,proving that the model had good stability.(5)Through the decision curve,it is found that within the probability threshold range of 1％to 92％,the model can obtain the maximum net benefit value.(6)The SHAP analysis results show that among the risk factors analyzed in this study,the location of the fracture line serves as the most significant predictor of femoral head necrosis following internal fixation with cannulated screws in femoral neck fractures,and subcapital fractures are extremely prone to femoral head necrosis after surgery.(7)It is concluded that the validated prediction model demonstrates strong discriminative power and reliability,offering practical clinical utility.It serves as a useful reference tool for short-term risk assessment of femoral head necrosis following internal fixation of femoral neck fractures.

BACKGROUND:The most common complication of traumatic femoral neck fractures after internal fixation is femoral head necrosis.Currently,many studies have reported on the risk factors that affect the occurrence and development of postoperative femoral head necrosis,but there is still a lack of tools to predict the risk of femoral head necrosis after internal fixation of femoral neck fractures.OBJECTIVE:To develop a predictive model that estimates the risk of femoral head necrosis shortly after patients with femoral neck fractures receive cannulated screw internal fixation.METHODS:A retrospective analysis reviewed clinical records of 172 patients who underwent cannulated screw internal fixation for femoral neck fractures at Department of Orthopedics of Mianyang Central Hospital from January 2013 to June 2023.Patients were categorized into two groups based on the presence or absence of femoral head necrosis within one year post-operation:the necrosis group and the non-necrosis group.Univariate analysis,Lasso regression,and multivariate Logistic regression techniques were employed to identify the determinants of femoral head necrosis.A nomogram prediction model was constructed using R language's"rms"package,version 4.0.The receiver operating characteristic curve was used to evaluate the discriminatory ability of the model.The Hosmer-Lemeshow test was used to evaluate the goodness of fit of the model,and the decision curve analysis was used to determine its clinical application benefits.Internal validation of the study was conducted using the Bootstrap method,involving 1 000 repeated samplings.To delve deeper into the primary factors influencing femoral head necrosis post-internal fixation of the femoral neck,this paper employed the SHAP method for data set analysis.RESULTS AND CONCLUSION:(1)The risk factors leading to femoral head necrosis in the short term after cannulated screw fixation of femoral neck fractures include:smoking,diabetes,Garden classification,fracture line location,reduction quality,age,and operation time.(2)The prediction model demonstrated robust performance,evidenced by an area under the curve of 0.940(95％Confidence Interval:0.903 to 0.977),indicating a high level of prediction accuracy.The model achieved a sensitivity of 90.2％and a specificity of 87.6％,indicating that its diagnostic performance was stable.The Hosmer-Lemeshow goodness-of-fit test yielded a chi-square value of 6.593 with a P-value of 0.581,confirming that the model's predictions closely align with the observed outcomes.(3)The calibration curve of the model also performed well,and its overall trend was very close to the ideal curve,further proving the high accuracy of the model.(4)The internal validation was carried out by the Bootstrap method with 1 000 repeated samplings,and the area under the curve of the model internal validation was still as high as 0.939,proving that the model had good stability.(5)Through the decision curve,it is found that within the probability threshold range of 1％to 92％,the model can obtain the maximum net benefit value.(6)The SHAP analysis results show that among the risk factors analyzed in this study,the location of the fracture line serves as the most significant predictor of femoral head necrosis following internal fixation with cannulated screws in femoral neck fractures,and subcapital fractures are extremely prone to femoral head necrosis after surgery.(7)It is concluded that the validated prediction model demonstrates strong discriminative power and reliability,offering practical clinical utility.It serves as a useful reference tool for short-term risk assessment of femoral head necrosis following internal fixation of femoral neck fractures.

Glycogen synthase 1 (GYS1) is the rate-limiting enzyme responsible for glycogen synthesis in skeletal muscle, heart, brain, and other extrahepatic tissues, playing a central role in systemic energy homeostasis. The human GYS1 gene maps to chromosome 19q13.33, comprises 16 exons, and encodes a 737-amino-acid polypeptide that is highly conserved across mammals. GYS1 activity is subject to multilayered and precisely coordinated regulation. At the transcriptional level, the GYS1 promoter contains a hypoxia response element (HRE) that mediates HIF-1α-dependent induction under low-oxygen conditions, as well as a muscle-specific enhancer harboring MEF2 and MyoD binding sites that confers tissue-restricted expression. At the post-translational level, a hierarchical phosphorylation cascade serves as the primary activity switch: glycogen synthase kinase 3β (GSK3β) sequentially phosphorylates four C-terminal serine residues following casein kinase II priming, while protein kinase A (PKA) and AMP-activated protein kinase (AMPK) provide parallel inhibitory inputs at both N- and C-terminal sites. Dephosphorylation and reactivation are mediated by protein phosphatase 1 (PP1) through tissue-specific glycogen-targeting regulatory subunits such as PPP1R3A and PPP1R3B, which anchor PP1 to glycogen particles and direct its activity toward GYS1. The allosteric activator glucose-6-phosphate (G6P) binds at the dimer interface, simultaneously enhancing catalytic efficiency and promoting dephosphorylation susceptibility, thereby establishing a feed-forward activation loop that couples substrate availability to glycogen synthesis. Beyond phosphorylation, GYS1 is regulated by ubiquitination (mediated by the E3 ligase PJA1), acetylation, O-linked β-N-acetylglucosamine (O-GlcNAc) modification, and SUMOylation, which collectively modulate protein stability, subcellular localization, and protein-protein interactions. Epigenetic mechanisms, including CpG island methylation and histone acetylation dynamics, govern chromatin accessibility at the GYS1 locus, while muscle-specific microRNAs such as miR-1 and miR-206 fine-tune GYS1 expression at the post-transcriptional level. Dysregulation of GYS1 has been identified as a central pathogenic driver in a spectrum of human diseases. In inherited glycogen storage disorders—including Lafora disease, adult polyglucosan body disease (APBD), and Pompe disease—loss of upstream regulatory control leads to GYS1 hyperactivation and the accumulation of structurally abnormal or excessive glycogen, resulting in progressive neurodegeneration, myopathy, and multiorgan dysfunction. In type 2 diabetes mellitus (T2DM), impaired insulin signaling through the PI3K-AKT-GSK3β axis maintains GYS1 in a hyperphosphorylated inactive state in skeletal muscle, compromising postprandial glucose disposal and exacerbating hyperglycemia. In oncology, GYS1 exhibits context-dependent roles across multiple cancer types. In hepatocellular carcinoma, FMO2⁺ cancer-associated fibroblasts stabilize GYS1 by competitively inhibiting PJA1-mediated ubiquitination, and stabilized GYS1 subsequently activates NF‑κB/CCL19 signaling to promote tertiary lymphoid structure formation and enhance anti-PD-1 immunotherapy responsiveness. In clear cell renal cell carcinoma, GYS1 promotes tumor progression through non-canonical NF‑κB pathway activation via the scaffold protein RPS27A. In triple-negative breast cancer, GYS1 has been identified as a trigger of disulfidptosis and an activator of NF-κB signaling through non-enzymatic facilitation of IκBα degradation. In colorectal cancer, mitochondrial fission deficiency drives AMPK-dependent GYS1 upregulation and glycogen accumulation as a compensatory survival mechanism, while in cervical cancer, GYS1-maintained glycogen reserves fuel the pentose phosphate pathway to generate NADPH for ROS clearance, thereby conferring cisplatin resistance in cancer stem cells. Therapeutic strategies targeting GYS1 have gained substantial momentum across these disease contexts. For glycogen storage disorders, antisense oligonucleotides, small interfering RNAs (e.g., ABX1100), and small-molecule inhibitors (e.g., MZ-101) have demonstrated preclinical and early clinical efficacy in reducing pathological glycogen accumulation. For T2DM, pharmacological activation of GYS1 through GSK3β inhibition or enhancement of PP1-mediated dephosphorylation is being explored to restore insulin-stimulated glycogen synthesis. In cancer, GYS1-directed interventions—including targeted silencing to sensitize tumors to chemotherapy and immune microenvironment modulation to enhance immunotherapy—represent emerging precision oncology approaches. This review provides a comprehensive and integrated account of GYS1 gene structure, tissue-specific distribution, regulatory networks, and pathogenic roles in metabolic disorders and malignancies, with the aim of establishing a theoretical framework for the development of GYS1-targeted precision therapies.

Inflammatory diseases (IDs) are a general term of diseases characterized by chronic inflammation as the primary pathogenetic mechanism, which seriously affect the quality of patient′s life and cause significant social and medical burden. Current drugs for IDs include nonsteroidal anti-inflammatory drugs, corticosteroids, immunomodulators, biologics, and antioxidants, but these drugs may cause gastrointestinal side effects, induce or worsen infections, and cause non-response or intolerance. Given the outstanding performance of metal polyphenol network (MPN) in the fields of drug delivery, biomedical imaging, and catalytic therapy, its application in the diagnosis and treatment of IDs has attracted much attention and significant progress has been made. In this paper, we first provide an overview of the types of IDs and their generating mechanisms, then sort out and summarize the different forms of MPN in recent years, and finally discuss in detail the characteristics of MPN and their latest research progress in the diagnosis and treatment of IDs. This research may provide useful references for scientific research and clinical practice in the related fields.

Objective To analyze the health effects of long-term occupational exposure to ionizing radiation on radiation workers in a nuclear power plant, and to provide a scientific basis for their occupational health monitoring. Methods In 2023, 183 radiation workers in a nuclear power plant were subjected to the analysis of blood cell parameters such as mean red blood cell count, white blood cell count (WBC), lymphocyte count, and hemoglobin count, thyroid function indicators such as serum triiodothyronine, thyroxine, and thyrotropin, as well as the chromosomal aberration rate and micronucleus rate of the lymphocytes in the peripheral blood. Results The blood cell parameters, thyroid function indicators, chromosomal aberration rate, and micronucleus rate of these radiation workers in the nuclear power plant were within normal reference ranges. Comparison among radiation workers with different ages showed statistically significant differences in triiodothyronine (H = 6.98, P < 0.05) and micronucleus rate (H = 48.44, P < 0.05). Among the three groups of radiation workers with different working years, WBC was significantly different (χ² = 3.87, P < 0.05), with the lowest WBC observed in radiation workers with ≥ 20 years of service. Thyroxine (χ² = 4.01, P < 0.05) and micronucleus rate (H = 40.95, P < 0.05) also varied significantly among these three groups. Conclusion Thyroid triiodothyronine level and micronucleus rate were affected by age, while WBC, thyroid thyroxine level, and micronucleus rate were related to working years. Targeted health management should be carried out for radiation workers in nuclear power plants to improve the awareness of radiation protection and continuously enhance their health status.

Acute burns and chronic wounds frequently fail to heal owing to various reasons. Most drugs currently used for wound therapy in clinical practice have notable drawbacks, making their application a substantial concern. For instance, anti-inflammatory drugs can exert multisystem toxicity, and cellular therapies are costly and difficult to retain. In recent years, natural functional proteins derived from animals and plants have gained increasing attention owing to their unique biological activities, low cost, and broad application prospects in wound therapy. Herein, we isolated a new protein (JH015Y) from amphibians and demonstrated its excellent wound repair and regeneration properties compared with those of epidermal growth factor, both in vitro and in vivo. JH015 protein increased the proliferative ability of human keratinocytes and skin fibroblasts by 47.73 and 41.40%, respectively. In vivo, the medium-dose (0.5 mg/dose) groups of JH015Y protein demonstrated accelerated wound healing from day 4, with wound healing rates 1.26, 1.27, and 1.14 times that of the blank group in acute wounds, burn wounds, and diabetic ulcer, respectively. Histological analysis of Masson-stained sections indicated that the JH015Y protein contributed to collagen deposition on the wound surface, markedly reduced inflammatory cell infiltration, and exhibited low biological toxicity. Accordingly, the JH015Y protein is a promising biotherapeutic agent for accelerated wound repair and regeneration.

Acute burns and chronic wounds frequently fail to heal owing to various reasons. Most drugs currently used for wound therapy in clinical practice have notable drawbacks, making their application a substantial concern. For instance, anti-inflammatory drugs can exert multisystem toxicity, and cellular therapies are costly and difficult to retain. In recent years, natural functional proteins derived from animals and plants have gained increasing attention owing to their unique biological activities, low cost, and broad application prospects in wound therapy. Herein, we isolated a new protein (JH015Y) from amphibians and demonstrated its excellent wound repair and regeneration properties compared with those of epidermal growth factor, both in vitro and in vivo. JH015 protein increased the proliferative ability of human keratinocytes and skin fibroblasts by 47.73 and 41.40%, respectively. In vivo, the medium-dose (0.5 mg/dose) groups of JH015Y protein demonstrated accelerated wound healing from day 4, with wound healing rates 1.26, 1.27, and 1.14 times that of the blank group in acute wounds, burn wounds, and diabetic ulcer, respectively. Histological analysis of Masson-stained sections indicated that the JH015Y protein contributed to collagen deposition on the wound surface, markedly reduced inflammatory cell infiltration, and exhibited low biological toxicity. Accordingly, the JH015Y protein is a promising biotherapeutic agent for accelerated wound repair and regeneration.