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 evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Guided by the concept of quality by design(QbD), this study optimizes the calcination and quenching process of calcined Magnetitum and establishes the XRD characteristic spectra of calcined Magnetitum, providing a scientific basis for the formulation of quality standards. Based on the processing methods and quality requirements of Magnetitum in the Chinese Pharmacopoeia, the critical process parameters(CPPs) identified were calcination temperature, calcination time, particle size, laying thickness, and the number of vinegar quenching cycles. The critical quality attributes(CQAs) included Fe mass fraction, Fe~(2+) dissolution, and surface color. The weight coefficients were determined by combining Analytic Hierarchy Process(AHP) and the criteria importance though intercrieria correlation(CRITIC) method, and the calcination process was optimized using orthogonal experimentation. Surface color was selected as a CQA, and based on the principle of color value, the surface color of calcined Magnetitum was objectively quantified. The vinegar quenching process was then optimized to determine the best processing conditions. X-ray diffraction(XRD) was used to establish the characteristic spectra of calcined Magnetitum, and methods such as similarity evaluation, cluster analysis, and orthogonal partial least squares-discriminant analysis(OPLS-DA) were used to evaluate the quality of the spectra. The optimized calcined Magnetitum preparation process was found to be calcination at 750 ℃ for 1 h, with a laying thickness of 4 cm, a particle size of 0.4-0.8 cm, and one vinegar quenching cycle(Magnetitum-vinegar ratio 10∶3), which was stable and feasible. The XRD characteristic spectra analysis method, featuring 9 common peaks as fingerprint information, was established. The average correlation coefficient ranged from 0.839 5-0.988 1, and the average angle cosine ranged from 0.914 4 to 0.995 6, indicating good similarity. Cluster analysis results showed that Magnetitum and calcined Magnetitum could be grouped together, with similar compositions. OPLS-DA discriminant analysis identified three key characteristic peaks, with Fe_2O_3 being the distinguishing component between the two. The final optimized processing method is stable and feasible, and the XRD characteristic spectra of calcined Magnetitum was initially established, providing a reference for subsequent quality control and the formulation of quality standards for calcined Magnetitum.
X-Ray Diffraction/methods* ; Drugs, Chinese Herbal/chemistry* ; Quality Control ; Particle Size

In this study, the pharmacodynamic components and potential pharmacological functions of Danzhi Xiaoyao Formula in treating nervous system diseases were investigated by hippocampal component characterization and network pharmacology. After rats were administrated with Danzhi Xiaoyao Formula by gavage, high performance liquid chromatography coupled with quadrupole time-of-flight tandem mass spectrometry(HPLC-Q-TOF-MS/MS) was employed to explore the components in the hippocampus of rats. Fifty-seven components were identified in the hippocampus of rats by comparing the extract of Danzhi Xiaoyao Formula, herbal components in the hippocampus after administration, and blank samples. KEGG and GO analyses predicted 74 core targets including GSK3B, MAPK1, AKT, IL6. These targets were involved in PI3K/Akt, NF-κB, MAPK, JAK/STAT, Wnt, and other signaling pathways. The results indicated that Danzhi Xiaoyao Formula may ameliorate other nervous system diseases enriched in DO, such as neurodegenerative diseases, cerebrovascular diseases, and mental and emotional disorders by mediating target pathways, inhibiting inflammation, reducing neuronal damage, and alleviating hippocampal atrophy. The relevant activities exhibited by this formula in nervous system diseases such as Alzheimer's disease, Parkinson's disease, and diabetic neuropathy have extremely high development value and are worthy of further in-depth research. This study provides a theoretical basis and practical guidance for expanding the application of Danzhi Xiaoyao Formula in the treatment of nervous system diseases.
Drugs, Chinese Herbal/administration & dosage* ; Animals ; Rats ; Hippocampus/metabolism* ; Network Pharmacology ; Chromatography, High Pressure Liquid ; Tandem Mass Spectrometry ; Rats, Sprague-Dawley ; Male ; Nervous System Diseases/genetics* ; Humans ; Signal Transduction/drug effects*

During the decocting process of traditional Chinese medicine(TCM), molecules spontaneously form self-assembled nanoparticles(SAN) through intermolecular non-covalent interactions. This process effectively addresses the low bioavailability of poorly soluble components, becoming a research hotspot. However, SAN formed in traditional decoctions often exhibit low Zeta potential, poor stability, and easy aggregation, which limit their clinical applications. According to the extensive studies of SAN in TCM decoctions, this paper proposes innovative strategies of utilizing techniques such as micro-precipitation and pH-driven methods to improve SAN. These strategies significantly enhance the uniformity and stability of SAN and effectively increase the transfer rate of poorly soluble components, overcoming the technical bottlenecks of low stability and drug delivery efficiency in TCM decoctions. This article reviews the origins, advantages, and limitations of traditional SAN, discusses the strategies for improving SAN construction and characterization, and delves into the scientific issues that need to be addressed in future research. The aim is to provide new directions for the development of modern TCM preparations.
Nanoparticles/chemistry* ; Drugs, Chinese Herbal/chemistry* ; Humans ; Medicine, Chinese Traditional ; Drug Delivery Systems ; Animals ; Drug Compounding/methods*

This study aims to explore whether Albiziae Cortex-Tribuli Fructus can exert an anti-hepatic fibrosis effect by regulating the nuclear factor E2-related factor 2(Nrf2)/NOD-like receptor protein 3(NLRP3)/cysteine protease-1(caspase-1) pathway and analyze its potential mechanism. In the in vivo experiment, a mouse model of hepatic fibrosis was established by subcutaneous injection of carbon tetrachloride. The levels of alanine aminotransferase(ALT), aspartate aminotransferase(AST), collagen type Ⅳ(ColⅣ), laminin(LN), procollagen type Ⅲ(PCⅢ), and hyaluronic acid(HA) in the serum of mice were measured using a fully automated biochemical analyzer and ELISA. Hematoxylin and eosin(HE) and Masson staining were used to observe inflammation and collagen fiber deposition in the liver tissue. Western blot and RT-qPCR were employed to detect the protein and mRNA expression of collagen type Ⅰ(collagen Ⅰ), α-smooth muscle actin(α-SMA), Nrf2, NLRP3, gasdermin D(GSDMD), and caspase-1 in the hepatic tissue. In the in vitro experiment, human hepatic stellate cells(HSC-LX2) were pretreated with Nrf2 agonist or inhibitor, followed by the addition of blank serum, AngⅡ + blank serum, and AngⅡ + Albiziae Cortex-Tribuli Fructus-containing serum for intervention. Western blot was used to detect the protein expression of Nrf2, NLRP3, GSDMD, caspase-1, α-SMA, GSDMD-N, and apoptosis-associated speck-like protein(ASC) in cells. DCFH-DA fluorescence probe was used to detect the cellular ROS levels. The results from the in vivo experiment showed that, compared with the model group, Albiziae Cortex-Tribuli Fructus significantly reduced the serum levels of AST, ALT, ColⅣ, LN, PCⅢ, and HA, reduced the infiltration of inflammatory cells and collagen fiber deposition in the liver tissue, significantly upregulated the protein and mRNA expression of Nrf2 in the liver tissue, and significantly downregulated the protein and mRNA expression of collagen I, α-SMA, NLRP3, GSDMD, and caspase-1 in the liver tissue. The results from the in vitro experiment showed that Nrf2 activation decreased the protein expression of NLRP3, GSDMD, caspase-1, α-SMA, GSDMD-N, ASC, and ROS levels in HSC-LX2, while Nrf2 inhibition showed the opposite trend. Furthermore, Albiziae Cortex-Tribuli Fructus-containing serum directly decreased the expression of the above proteins and ROS levels. In conclusion, Albiziae Cortex-Tribuli Fructus can effectively improve hepatic fibrosis, and its mechanism of action may involve inhibiting pyroptosis through the regulation of the Nrf2/NLRP3/caspase-1 pathway.
Animals ; NF-E2-Related Factor 2/genetics* ; Liver Cirrhosis/genetics* ; Mice ; Drugs, Chinese Herbal/administration & dosage* ; Caspase 1/genetics* ; Male ; NLR Family, Pyrin Domain-Containing 3 Protein/genetics* ; Signal Transduction/drug effects* ; Humans ; Liver/metabolism* ; Mice, Inbred C57BL ; Plant Extracts ; Tribulus

BACKGROUND AND OBJECTIVE: Patients with glioma experience a high symptom burden and have diverse palliative care needs. However, the assessment scales used in palliative care remain non-standardized and highly heterogeneous. To evaluate the application patterns of the current scales used in palliative care for glioma, we aim to identify gaps and assess the need for disease-specific scales in glioma palliative care. METHODS: We conducted a systematic search of five databases including PubMed, Web of Science, Medline, EMBASE, and CINAHL for quantitative studies that reported scale-based assessments in glioma palliative care. We extracted data on scale characteristics, domains, frequency, and psychometric properties. Quality assessments were performed using the Cochrane ROB 2.0 and ROBINS-I tools. RESULTS: Of the 3,405 records initially identified, 72 studies were included. These studies contained 75 distinct scales that were used 193 times. Mood (21.7%), quality of life (24.4%), and supportive care needs (5.2%) assessments were the most frequently assessed items, exceeding half of all scale applications. Among the various assessment dimensions, the Distress Thermometer (DT) was the most frequently used tool for assessing mood, while the Short Form-36 Health Survey Questionnaire (SF-36) was the most frequently used tool for assessing quality of life. The Mini Mental Status Examination (MMSE) was the most common tool for cognitive assessment. Performance status (5.2%) and social support (6.8%) were underrepresented. Only three brain tumor-specific scales were identified. Caregiver-focused scales were limited and predominantly burden-oriented. CONCLUSIONS: There are significant heterogeneity, domain imbalances, and validation gaps in the current use of assessment scales for patients with glioma receiving palliative care. The scale selected for use should be comprehensive and user-friendly.
Humans ; Glioma/psychology* ; Palliative Care/methods* ; Quality of Life ; Psychometrics ; Brain Neoplasms/psychology*

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

OBJECTIVES: To explore the application of the colloidal gold method and chemiluminescence method in detecting gonadotropin (Gn) in morning urine for assessing pubertal development status in children. METHODS: A total of 132 children diagnosed with central precocious puberty (CPP), early and fast puberty (EFP), and premature thelarche (PT) at Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine from November 2021 to December 2022 were included, along with 685 healthy children who underwent routine health examinations at the hospital's pediatric health care department during the same period. All 132 patients underwent a gonadotropin-releasing hormone (GnRH) stimulation test. Both patients and healthy children had their urinary Gn levels measured using the colloidal gold method and chemiluminescence method, including levels of luteinizing hormone (LH) and follicle-stimulating hormone (FSH). The correlation between serum Gn and urinary Gn detected by the two methods, as well as the correlation between Tanner stages of healthy children and urinary Gn, was analyzed. RESULTS: Urine Gn levels detected by both the colloidal gold method and chemiluminescence method showed a positive correlation with serum LH baseline values, LH peak values, baseline LH/FSH ratios, and peak LH/FSH ratios (P<0.05). In healthy children, urinary LH levels detected by the chemiluminescence method gradually increased from Tanner stage Ⅰ to Ⅳ (P<0.05), while urinary FSH levels were lower in Tanner stage I than in stages Ⅱ, Ⅲ, and IV (P<0.05). Urinary LH levels detected by the colloidal gold method were lower in Tanner stage I compared to stages Ⅱ, Ⅲ, and IV, with the highest levels observed in Tanner stage Ⅳ (P<0.05). Additionally, urinary FSH levels in Tanner stage Ⅲ were higher than in stages Ⅰ and Ⅱ (P<0.05). The area under the receiver operating characteristic curve for evaluating Tanner stages I and II in healthy children using urinary LH and FSH levels by the chemiluminescence method and urinary LH levels by the colloidal gold method were 0.730, 0.699, and 0.783, respectively. CONCLUSIONS The colloidal gold method and chemiluminescence method for detecting Gn in morning urine show good correlation with serum Gn levels. As a non-invasive and convenient detection method, the colloidal gold method can serve as a useful tool for screening the onset of pubertal development in children.
Humans ; Child ; Male ; Female ; Gold Colloid ; Luminescent Measurements/methods* ; Gonadotropins/urine* ; Puberty ; Luteinizing Hormone/urine* ; Child, Preschool ; Adolescent ; Follicle Stimulating Hormone/urine*