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.

Diffuse large B-cell lymphoma （DLBCL） is a highly heterogeneous disease. Although standard first-line regimens can cure ＞50% of patients， approximately one-third of them develop relapsed/refractory DLBCL （r/r DLBCL）. Consequently， immunotherapy targeting molecular abnormalities has become pivotal for managing r/r DLBCL. The results of this review show that with advances in understanding DLBCL pathogenesis and the tumor immune microenvironment， antibody-based therapies have evolved rapidly， progressing from monoclonal antibodies （e.g.， rituximab， tafasitamab） to bispecific antibodies（e.g.， odronextamab，glofitamab， epcoritamab） and antibody-drug conjugate （e.g.， polatuzumab vedotin， loncastuximab tesirine）. These engineered agents enhance immune cytotoxicity and tumor-specific targeting， providing novel therapeutic options for r/r DLBCL patients.

Therapeutic resistance in cancer is responsible for numerous cancer deaths in clinical practice. While target mutations are well recognized as the basis of genetic resistance to targeted therapy, nontarget mutation resistance (or nongenetic resistance) remains poorly characterized. Despite its complex and unintegrated mechanisms in the literature, nongenetic resistance is considered from our perspective to be a collective response of innate or acquired resistant subpopulations in heterogeneous tumors to therapy. These subpopulations, e.g., cancer stem-like cells, cancer cells with epithelial-to-mesenchymal transition, and drug-tolerant persisters, are protected by their resistance traits at cellular and molecular levels. This review summarizes recent advances in the research on resistant populations and their resistance traits. NOTCH signaling, as a central regulator of nongenetic resistance, is discussed with a special focus on its canonical maintenance of resistant cancer cells and noncanonical regulation of their resistance traits. This novel view of canonical and noncanonical NOTCH signaling pathways is translated into our proposal of reshaping therapeutic strategies targeting NOTCH signaling in resistant cancer cells. We hope that this review will lead researchers to study the canonical and noncanonical arms of NOTCH signaling as an integrated resistant mechanism, thus promoting the development of innovative therapeutic strategies.
Neoplasms/metabolism* ; Receptors, Notch/metabolism* ; Disease Resistance/physiology* ; Signal Transduction/physiology* ; Humans ; Drug Resistance, Neoplasm/physiology* ; Molecular Targeted Therapy/methods*

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AIM: To investigate the role of pyroptosis in the development of diabetic retinopathy(DR)and to explore the regulatory mechanism by which circular RNA(circRNA)and its targeted microRNA(miRNA)mediate pyroptosis in DR, providing new therapeutic targets and strategies for the prevention and treatment of DR.METHODS: A streptozotocin(STZ)-induced model of type 1 diabetes in SD rats was established. The expression of circRNA_0076631, miR-214, and pyroptosis-related factors were measured in retinal tissues. CCK-8 and tube formation assays were used to detect the effect of different concentration of glucose on cell proliferation and angiogenic abilities of human retinal microvascular endothelial cells(HRMECs). The expression levels of circRNA_0076631, miR-214, and pyroptosis-related markers were evaluated through qRT-PCR and Western blot analysis, with additional experiments conducted following circRNA_0076631 knockdown to assess its effect on pyroptosis markers. Previous bioinformatics analysis and luciferase reporter assays identified a shared binding site among circRNA_0076631, miR-214, and caspase-1. To clarify the interaction between these molecules, co-transfection experiments using circRNA_0076631 inhibitors(ASO-circRNA_0076631), miR-214 overexpression transfection reagent, and miR-214 inhibitors(AMO-miR-214)were conducted to elucidate the regulatory pathway involved in DR.RESULTS: Both the diabetic rat model and D-glucose-treated HRMECs showed significantly elevated expression of circRNA_0076631 and pyroptosis-related factors(NLRP3, caspase-1, and IL-1β), while miR-214 expression was reduced(all P<0.05). The mRNA expression of pyroptosis-related factors caspase-1 was reduced after the overexpression of miR-214, and it was upregulated after the inhibition of miR-214(all P<0.05). Knockdown of circRNA_0076631 reduced the mRNA expression of pyroptosis markers caspase-1(P<0.05). Co-transfection experiments revealed that the inhibition circRNA_0076631 suppressed pyroptosis(all P<0.05), but this suppression was reversed upon co-transfection with miR-214 inhibitors, leading to increased mRNA expression of the pyroptosis marker caspase-1(all P<0.05).CONCLUSION: The circRNA_0076631 and pyroptosis play critical roles in the pathogenesis of DR, and circRNA_0076631 may regulate pyroptosis by modulating miR-214, which in turn influences the expression of caspase-1 in the pyroptosis signaling pathway, thereby contributing to DR progression. The circRNA_0076631 may serve as a novel therapeutic target, providing new insights for the prevention and treatment of DR.

AIM: To investigate the role of pyroptosis in the development of diabetic retinopathy(DR)and to explore the regulatory mechanism by which circular RNA(circRNA)and its targeted microRNA(miRNA)mediate pyroptosis in DR, providing new therapeutic targets and strategies for the prevention and treatment of DR.METHODS: A streptozotocin(STZ)-induced model of type 1 diabetes in SD rats was established. The expression of circRNA_0076631, miR-214, and pyroptosis-related factors were measured in retinal tissues. CCK-8 and tube formation assays were used to detect the effect of different concentration of glucose on cell proliferation and angiogenic abilities of human retinal microvascular endothelial cells(HRMECs). The expression levels of circRNA_0076631, miR-214, and pyroptosis-related markers were evaluated through qRT-PCR and Western blot analysis, with additional experiments conducted following circRNA_0076631 knockdown to assess its effect on pyroptosis markers. Previous bioinformatics analysis and luciferase reporter assays identified a shared binding site among circRNA_0076631, miR-214, and caspase-1. To clarify the interaction between these molecules, co-transfection experiments using circRNA_0076631 inhibitors(ASO-circRNA_0076631), miR-214 overexpression transfection reagent, and miR-214 inhibitors(AMO-miR-214)were conducted to elucidate the regulatory pathway involved in DR.RESULTS: Both the diabetic rat model and D-glucose-treated HRMECs showed significantly elevated expression of circRNA_0076631 and pyroptosis-related factors(NLRP3, caspase-1, and IL-1β), while miR-214 expression was reduced(all P<0.05). The mRNA expression of pyroptosis-related factors caspase-1 was reduced after the overexpression of miR-214, and it was upregulated after the inhibition of miR-214(all P<0.05). Knockdown of circRNA_0076631 reduced the mRNA expression of pyroptosis markers caspase-1(P<0.05). Co-transfection experiments revealed that the inhibition circRNA_0076631 suppressed pyroptosis(all P<0.05), but this suppression was reversed upon co-transfection with miR-214 inhibitors, leading to increased mRNA expression of the pyroptosis marker caspase-1(all P<0.05).CONCLUSION: The circRNA_0076631 and pyroptosis play critical roles in the pathogenesis of DR, and circRNA_0076631 may regulate pyroptosis by modulating miR-214, which in turn influences the expression of caspase-1 in the pyroptosis signaling pathway, thereby contributing to DR progression. The circRNA_0076631 may serve as a novel therapeutic target, providing new insights for the prevention and treatment of DR.

ObjectiveTo elucidate the critical role of rehabilitation medical records (including electronic records) in rehabilitation medicine's clinical practice and management, comprehensively analyzed the structure, core content and data standards of rehabilitation medical records, to develop a standardized medical record data architecture and core dataset suitable for rehabilitation medicine and to explore the application of rehabilitation data in performance evaluation and payment. MethodsBased on the regulatory documents Basic Specifications for Medical Record Writing and Basic Specifications for Electronic Medical Records (Trial) issued by National Health Commission of China, and referencing the World Health Organization (WHO) Family of International Classifications (WHO-FICs) classifications, International Classification of Diseases (ICD-10/ICD-11), International Classification of Functioning, Disability and Health (ICF), and International Classification of Health Interventions (ICHI Beta-3), this study constructed the data architecture, core content and data standards for rehabilitation medical records. Furthermore, it explored the application of rehabilitation record summary sheets (home page) data in rehabilitation medical statistics and payment methods, including Diagnosis-related Groups (DRG), Diagnosis-Intervention Packet (DIP) and Case Mix Index. ResultsThis study proposed a systematic standard framework for rehabilitation medical records, covering key components such as patient demographics, rehabilitation diagnosis, functional assessment, rehabilitation treatment prescriptions, progress evaluations and discharge summaries. The research analyzed the systematic application methods and data standards of ICD-10/ICD-11, ICF and ICHI Beta-3 in the fields of medical record terminology, coding and assessment. Constructing a standardized data structure and data standards for rehabilitation medical records can significantly improve the quality of data reporting based on the medical record summary sheet, thereby enhancing the quality control of rehabilitation services, effectively supporting the optimization of rehabilitation medical insurance payment mechanisms, and contributing to the establishment of rehabilitation medical performance evaluation and payment based on DRG and DIP. ConclusionStructured rehabilitation records and data standardization are crucial tools for quality control in rehabilitation. Systematically applying the three reference classifications of the WHO-FICs, and aligning with national medical record and electronic health record specifications, facilitate the development of a standardized rehabilitation record architecture and core dataset. Standardizing rehabilitation care pathways based on the ICF methodology, and developing ICF- and ICD-11-based rehabilitation assessment tools, auxiliary diagnostic and therapeutic systems, and supporting terminology and coding systems, can effectively enhance the quality of rehabilitation records and enable interoperability and sharing of rehabilitation data with other medical data, ultimately improving the quality and safety of rehabilitation services.

ObjectiveTo explore the data standard system of electronic medical records in the field of rehabilitation, focusing on the terminology and coding standards, data structure, and key content categories of rehabilitation electronic medical records. MethodsBased on the Administrative Norms for the Application of Electronic Medical Records issued by the National Health Commission of China, the electronic medical record standard architecture issued by the International Organization for Standardization and Health Level Seven (HL7), the framework of the World Health Organization Family of International Classifications (WHO-FICs), Basic Architecture and Data Standards of Electronic Medical Records, Basic Data Set of Electronic Medical Records, and Specifications for Sharing Documents of Electronic Medical Records, the study constructed and organized the data structure, content, and data standards of rehabilitation electronic medical records. ResultsThe data structure of rehabilitation electronic medical records should strictly follow the structure of electronic medical records, including four levels (clinical document, document section, data set and data element) and four major content areas (basic information, diagnostic information, intervention information and cost information). Rehabilitation electronic medical records further integrated information related to rehabilitation needs and characteristics, emphasizing rehabilitation treatment, into clinical information. By fully applying the WHO-FICs reference classifications, rehabilitation electronic medical records could establish a standardized framework, diagnostic criteria, functional description tools, coding tools and terminology index tools for the coding, indexing, functional description, and analysis and interpretation of diseases and health problems. The study elaborated on the data structure and content categories of rehabilitation electronic medical records in four major categories, refined the granularity of reporting rehabilitation content in electronic medical records, and provided detailed data reporting guidance for rehabilitation electronic medical records. ConclusionThe standardization of rehabilitation electronic medical records is significant for improving the quality of rehabilitation medical services and promoting the rehabilitation process of patients. The development of rehabilitation electronic medical records must be based on the national and international standards. Under the general electronic medical records data structure and standards, a rehabilitation electronic medical records data system should be constructed which incorporates core data such as disease diagnosis, functional description and assessment, and rehabilitation interventions. The standardized rehabilitation electronic medical records scheme constructed in this study can support the improvement of standardization of rehabilitation electronic medical records data information.

ObjectiveTo analyze the data structure and standards of rehabilitation outpatient medical records, to provide data support for improving the quality of rehabilitation outpatient care and developing medical insurance payment policies. MethodsBased on the normative documents issued by the National Health Commission, Basic Standards for Medical Record Writing and Standards for Electronic Medical Record Sharing Documents, in accordance with the Quality Management Regulations for Outpatient (Emergency) Diagnosis and Treatment Information Pages (Trial), reference to the framework of the World Health Organization Family of International Classifications (WHO-FICs), the data framework and content of rehabilitation outpatient medical records were determined, and the data standards were discussed. ResultsThis study constructed a data framework for rehabilitation outpatient medical records, including four main components: patient basic information, visit process information, diagnosis and treatment information, and cost information. Three major reference classifications of WHO-FICs, International Classification of Diseases, International Classification of Functioning, Disability and Health, and International Classification of Health Interventions,were used to establish diagnostic standards and standardized terminology, as well as coding disease diagnosis, functional description, functional assessment, and rehabilitation interventions, to improve the quality of data reporting, and level of quality control in rehabilitation. ConclusionThe structuring and standardization of rehabilitation outpatient medical records are the foundation for sharing of rehabilitation data. The using of the three major classifications of WHO-FICs is valuable for the terminology and coding of disease diagnosis, functional description and assessment, and intervention in rehabilitation outpatient medical records, which is significant for sharing and interconnectivity of rehabilitation outpatient data, as well as for optimizing the quality and safety of rehabilitation medical services.