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 report the hematological phenotypic characteristics and molecular variant features of a rare abnormal hemoglobin Hb K-Woolwich compound with Southeast Asian α-thalassemia in a Chinese family pedigree, aiming to summarize the laboratory screening patterns and the value for clinical genetic counseling, and to supplement the baseline data of this rare variant in the Chinese population. Methods: A three-generation pedigree involving three carriers was enrolled in this study. The proband's medical history and general clinical data of the family were retrospectively analyzed. Phenotypic analysis and molecular genotypic confirmation were performed using complete blood count parameters, capillary hemoglobin electrophoresis, H100Plus high-performance liquid chromatography (HPLC), and gene sequencing, followed by Sanger sequencing. Results: All three individuals in this pedigree were identified as heterozygous carriers of the HBB:c. 397A>C mutation (Hb K-Woolwich) in the β-globin gene, combined with the αα/--SEA Southeast Asian type α-thalassemia genotype. Hematological findings revealed compensatory elevation of red blood cell count, decreased mean corpuscular volume (MCV) and mean corpuscular hemoglobin (MCH), while hemoglobin (Hb) levels remained within the normal range with no overt anemic phenotype. Both capillary electrophoresis and HPLC detected characteristic abnormal variant peaks, with good concordance between the two screening methods. Conclusion: Hb K-Woolwich compound with αα/--SEA thalassemia presents with distinctive hematological phenotypes, characterized by prominent microcytic and hypochromic changes without anemia, which may be easily overlooked in routine thalassemia screening programs. This is the first report of this compound genotype in China, providing valuable reference for laboratory identification, prenatal screening, and family genetic counseling of rare hemoglobin variants.

Objective To investigate the impact of 15 days of complete fasting on individuals'risk decision-making abilities and the role of physical exercise in this process.Methods Twenty-four healthy participants completed a 28-day experiment divided into baseline,complete fasting,calorie restriction,and full recovery phases.Participants were randomly assigned to a light exercise group(EL),moderate exercise group(EM),or control group(CN).Risk decision-making capacity was assessed using the Balloon Analogue Risk Task(BART),with data analyzed via Kruskal-Wallis and Friedman tests.Results Fifteen days of complete fasting did not significantly affect the participants'risk decision-making abilities.Additionally,after fasting,the moderate exercise group was more likely to make risky decisions compared to the light exercise group.Conclusion Long-term fasting has no significant impact on risk decision-making ability,but engaging in physical exercise makes people more likely to make high-risk decisions.

Cemental tear is a rare and indetectable condition unless obvious clinical signs present with the involvement of surrounding periodontal and periapical tissues. Due to its clinical manifestations similar to common dental issues, such as vertical root fracture, primary endodontic diseases, and periodontal diseases, as well as the low awareness of cemental tear for clinicians, misdiagnosis often occurs. The critical principle for cemental tear treatment is to remove torn fragments, and overlooking fragments leads to futile therapy, which could deteriorate the conditions of the affected teeth. Therefore, accurate diagnosis and subsequent appropriate interventions are vital for managing cemental tear. Novel diagnostic tools, including cone-beam computed tomography (CBCT), microscopes, and enamel matrix derivatives, have improved early detection and management, enhancing tooth retention. The implementation of standardized diagnostic criteria and treatment protocols, combined with improved clinical awareness among dental professionals, serves to mitigate risks of diagnostic errors and suboptimal therapeutic interventions. This expert consensus reviewed the epidemiology, pathogenesis, potential predisposing factors, clinical manifestations, diagnosis, differential diagnosis, treatment, and prognosis of cemental tear, aiming to provide a clinical guideline and facilitate clinicians to have a better understanding of cemental tear.
Humans ; Dental Cementum/injuries* ; Consensus ; Diagnosis, Differential ; Cone-Beam Computed Tomography ; Tooth Fractures/therapy*

Acute ischemic stroke (AIS) is a cerebrovascular disease characterized by high morbidity, disability, and mortality, posing a significant threat to human health. Endovascular treatment has now been established as a key method for AIS management, in which stent retrievers that can mechanically remove blood clots play a key role in this technique. In recent years, stent retrievers have evolved in complexity and functionality to improve the ability of clot removing and surgical safety. However, the present instruments still have limitations on treatment efficiency, vascular adaptability, and operational precision, posing an urgent need for innovation in the design of stent retrievers. This paper systematically reviewed the structural features and working principles of AIS stent retrievers from the perspective of efficacy evaluation metrics, historical development, recent advancements in stent retrieval technology, and future prospects.
Humans ; Ischemic Stroke/surgery* ; Stents ; Endovascular Procedures/methods* ; Thrombectomy/methods* ; Device Removal/methods*

Hyperuricemia (HUA) and gout became typical metabolic disorders characterized by multiple pathogenic factors. Their incidence increased annually, affecting younger populations. Given that uric acid (UA) and inflammation were the primary disease mechanisms, the search for effective and low-side-effect UA-lowering and anti-inflammatory drugs became a pressing scientific priority. Traditional Chinese medicine (TCM) encompassed a rich array of theoretical and practical experience, along with a diverse range of chemical substances, making herbs or their components potential sources for therapeutic drugs. Despite the significant role that modern herbal medicines played in treating HUA and gout, the existing research literature remained fragmented, lacking comprehensive and systematic reviews. In this review, we focused on the regulation of UA and summarized the discovery of UA-lowering pharmacodynamic components or ingredients derived from herbs and formulas, as well as their multi-targeted mechanisms of action. Emphasizing this focus, we proposed that, compared to acute inflammation, low-grade inflammation may play a relatively "unnoticed" role in the disease process. In contrast to Western medicine, we discussed the risks and benefits of herbal medicines and their ingredients for treatment, drawing from theoretical insights and clinical practice. This review offered comprehensive perspectives on the research into anti-HUA and gout treatments using herbal medicines and their natural products. Additionally, it provided a forward-looking view on natural product discovery, the exploration of therapeutic strategies, and new drug research in this field.

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OBJECTIVE To establish refined medication rules for parenteral nutrition （PN） and evaluate its effectiveness. METHODS Refined medication rules for PN were constructed based on drug instructions， relevant guidelines， and expert consensus. Through the pre-approval review system of prescription automatic screening system （PASS）， PN prescription information for inpatients from January to December 2024 （referred to as “post-intervention”） was collected to analyze the post- intervention prescription review status. PN prescription information for inpatients at our hospital from January to December 2023 and January to December 2024 was collected through the medical order review system to evaluate the rationality rates of PN prescriptions. RESULTS The established refined medication rules for PN included system module rules （including nutrients， drug compatibility， PN concentration and osmotic pressure） and custom review rules （covering off-label drug use， drug compatibility， and other drug use conditions）. As of December 2024， the PASS pre-approval review system had established a total of 102 rules， comprising 55 system module rules and 47 custom review rules for PN. After intervention， when comparing with the first quarter of 2024， the number of PN reviewed and intervened by pharmacists decreased， the pharmacist intervention rate dropped， while the rate of physician modifications following pharmacist intervention increased in the fourth quarter. The primary types of irrational prescriptions identified by the system module rules were irrational PN concentration and osmotic pressure. The primary types of irrational prescriptions identified by the custom review rules were off-label drug use （specifically indications for amino acids） and irrational drug incompatibility. In 2024， the number of false-positive tasks and the false-positive rate initially increased and then decreased， while both the number of irrational prescriptions identified through manual review and the false-negative rate showed a declining trend. In 2024， the overall rationality rate after manual review PN refined medication rules for PN medical order review system significantly increased compared to that in 2023 （P＜0.01）. CONCLUSIONS The refined medication rules for PN in our hospital were established successfully， which can reduce the PN-induced risks and significantly improve the rationality of PN prescriptions.