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.

Mucosae are the primary sites of causing infectious diseases in human beings. The high transmissibility and mortality rates of infectious diseases pose a serious threat to human health. Mucosal vaccines, which induce both mucosal and systemic immune responses, have emerged as an effective method for preventing or treating infectious diseases. This paper provides an overview of the structure and response characteristics of the mucosal immune system, as well as adjuvants and delivery vectors in vaccine design. It focuses on the multi-dimensional evaluation system of immunoprotective efficacy,covering key indicators such as antibody response, neutralization ability, antibody affinity and tissue-resident memory cells,providing reference for the future development of more effective mucosal vaccines.

ObjectiveTo study the mechanism of compound Xishu granules （CXG） in inhibiting the proliferation of hepatocellular carcinoma cells by regulating ferroptosis. MethodsThe transplanted tumor model of human Huh7 was established with nude mice and the successfully modeled mice were randomized into model， Fufang Banmao （0.21 g·kg^-1）， low-dose （1.87 g·kg^-1） CXG， medium-dose （3.74 g·kg^-1） CXG， and high-dose （7.49 g·kg^-1） CXG groups. Mice were administrated with drinking water or CXG for 28 days， and the body weight and tumor volume were measured every 4 days. Hematoxylin-eosin staining was employed to observe the histopathological changes of tumors. The cell-counting kit-8 （CCK-8） was used to examine the survival rate of Huh7 cells treated with different concentrations （0， 31.25， 62.5， 125， 250， 500， 1 000 mg·L^-1） of CXG for 24 h and 48 h. CA-AM， DCFH-DA， and C11-BODIPY^581/591 fluorescent probes were used to determine the intracellular levels of ferrous ion （Fe²⁺）， reactive oxygen species （ROS）， and lipid peroxide （LPO）， respectively. The colorimetric method was employed to measure the levels of glutathione （GSH） and superoxide dismutase （SOD）. Western blot was employed to determine the protein levels of glutathione peroxidase 4 （GPX4）， transferrin receptor 1 （TFR1）， and ferritin heavy chain 1 （FTH1）， respectively. ResultsIn the animal experiment， compared with the model group， the drug treatment groups showed reductions in the tumor volume from day 12 （P<0.01）. After treatment， the Fufang Banmao and low-， medium-， and high-dose CXG groups had lower tumor volume， relative tumor volume， and tumor weight than the model group （P<0.05）， with tumor inhibition rates of 48.99%， 79.93%， 91.38%， and 97.36%， respectively. Moreover， the CXG groups had lower tumor volume and relative tumor volume （P<0.05 in all the three dose groups） and lower tumor weight （P<0.05 in medium-dose and high-dose groups） than the Fufang Banmao group. Compared with the model group， the drug treatment groups showed reduced number of tumor cells， necrotic foci with karyopyknosis， nuclear fragmentation， and nucleolysis， and the high-dose CXG group showed an increase in the proportion of interstitial fibroblasts. In the cell experiment， compared with the blank group， CXG reduced the survival rate of Huh7 cells in a dose-dependent manner after incubation for 24 h and 48 h （P<0.05）. Compared with the blank group， the RSL3 group and the low-， medium-， and high-dose CXG groups showed a decrease in the relative fluorescence intensity of CA-AM and increases in the fluorescence intensity of DCFH-DA and fluorescence ratio of C11-BODIPY^581/591， which indicated elevations in the levels of Fe²⁺ （P<0.01）， ROS （P<0.05）， and LPO （P<0.01）， respectively. Compared with the blank group， the RSL3 and low-， medium-， and high-dose CXG groups showed lowered levels of GSH and SOD （P<0.05）. In addition， the RSL3 group and the medium- and high-dose CXG groups showed down-regulated expression of GPX4 and FTH1 （P<0.05）， and the low- and high-dose CXG groups presented up-regulated expression of TFR1 （P<0.05）. ConclusionCXG suppresses the proliferation of hepatocellular carcinoma cells by inducing ferroptosis via downregulating the GSH-GPX4 signaling axis and increasing intracellular Fe²⁺and LPO levels.

As people’s attention to health continues to increase, the market demand for traditional Chinese medicine (TCM) is growing steadily. The quality and safety of Chinese medicinal materials have attracted unprecedented social attention. In particular, the issue of exogenous harmful residue pollution in TCM has become a hot topic of concern for both regulatory authorities and society. The Chinese Pharmacopoeia 2025 Edition further refines the detection methods and limit standards for exogenous harmful residues in TCM. This not only reflects China’s high-level emphasis on the quality and safety of TCM but also demonstrates the continuous progress made by China in the field of TCM safety supervision. Basis on this study, by systematically reviewing the development history of the detection standards for exogenous harmful residues in TCM and analyzing the revisions and updates of these detection standards in the Chinese Pharmacopoeia 2025 Edition, deeply explores the key points of the changes in the monitoring standards for exogenous harmful residues in TCM in the Chinese Pharmacopoeia 2025 Edition. Moreover, it interprets the future development directions of the detection of exogenous residues in TCM, aiming to provide a reference for the formulation of TCM safety supervision policies.

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*

Microbial communities such as those residing in the human gut are highly diverse and complex, and many with important implications for health and diseases. The effects and functions of these microbial communities are determined not only by their species compositions and diversities but also by the dynamic intra- and inter-cellular states at the transcriptional level. Powerful and scalable technologies capable of acquiring single-microbe-resolution RNA sequencing information in order to achieve a comprehensive understanding of complex microbial communities together with their hosts are therefore utterly needed. Here we report the development and utilization of a droplet-based smRNA-seq (single-microbe RNA sequencing) method capable of identifying large species varieties in human samples, which we name smRandom-seq2. Together with a triple-module computational pipeline designed for the bacteria and bacteriophage sequencing data by smRandom-seq2 in four human gut samples, we established a single-cell level bacterial transcriptional landscape of human gut microbiome, which included 29,742 single microbes and 329 unique species. Distinct adaptive response states among species in Prevotella and Roseburia genera and intrinsic adaptive strategy heterogeneity in Phascolarctobacterium succinatutens were uncovered. Additionally, we identified hundreds of novel host-phage transcriptional activity associations in the human gut microbiome. Our results indicated that smRandom-seq2 is a high-throughput and high-resolution smRNA-seq technique that is highly adaptable to complex microbial communities in real-world situations and promises new perspectives in the understanding of human microbiomes.
Humans ; Gastrointestinal Microbiome/genetics* ; Bacteriophages/physiology* ; High-Throughput Nucleotide Sequencing ; Sequence Analysis, RNA/methods* ; Bacteria/virology*

The focus of green analytical chemistry (GAC) is to minimize the negative impacts of analytical procedures on human safety, human health, and the environment. Several factors, such as the reagents used, sample collection, sample processing, instruments, energy consumed, and the quantities of hazardous materials and waste generated during analytical procedures, need to be considered in the evaluation of the greenness of analytical assays. In this study, we propose a greenness evaluation metric for analytical methods (GEMAM). The new greenness metric is simple, flexible, and comprehensive. The evaluation criteria are based on both the 12 principles of GAC (SIGNIFICANCE) and the 10 factors of sample preparation, and the results are presented on a 0-10 scale. The GEMAM calculation process is easy to perform, and its results are easy to interpret. The output of GEMAM is a pictogram that can provide both qualitative and quantitative information based on color and number.

Background: and Purpose Limited evidence exists on the effectiveness of endovascular treatment (EVT) for acute posterior circulation tandem lesion (PCTL). This study aimed to explore the role of extracranial vertebral artery (VA) stenting in patients with PCTL stroke undergoing EVT. Methods: Individual patient data were pooled from the BASILAR (EVT for Acute Basilar Artery Occlusion Study) and PERSIST (Posterior Circulation Ischemic Stroke) registries. Patients with PCTLs who underwent EVT were included in the present cohort and divided into the stenting and nonstenting groups based on the placement of extracranial VA stents. The primary efficacy outcome was the modified Rankin Scale (mRS) scores at 90 days and 1 year. Safety outcomes included 24-hour symptomatic intracranial hemorrhage (sICH) and all-cause mortality at 90 days and 1 year post-surgery. Results: A combined dataset of 1,320 patients with posterior circulation artery occlusion, including 263 (19.9%) with tandem lesions, of whom 217 (median age, 65 years; 82.9% male) met the inclusion criteria for the analysis. The stenting group had 84 (38.7%) patients, while the non-stenting group had 133 (61.3%). After adjustment for the potential confounders, extracranial VA stenting was associated with favorable shifts in mRS scores at both 90 days (adjusted common odds ratio [OR], 2.30; 95% confidence interval [CI], 1.23–4.28; P<0.01) and 1 year (adjusted OR [aOR], 2.04; 95% CI [1.05–3.97]; P=0.04), along with lower rate of mortality at both 90 days (aOR, 0.45; 95% CI [0.21–0.93]; P=0.01) and 1 year (aOR, 0.36; 95% CI [0.16–0.79]; P=0.01), with no significant difference in sICH incidence (aOR, 0.35; 95% CI [0.06–1.98]; P=0.24). Conclusion Extracranial VA stenting during EVT may improve functional outcomes and reduce mortality in patients with PCTL strokes.

ObjectiveTo investigate the accuracy of multiple discriminant analysis （MDA） versus fibrosis-4 （FIB-4） in assessing liver fibrosis degree in patients with HBV infection， as well as the possibility of MDA as an indicator for disease progression. MethodsA total of 263 patients with HBV infection who underwent liver biopsy in The First Affiliated Hospital of Guangxi Medical University from April 2010 to April 2024 were included， and their clinical data were collected. According to the results of pathological examination， they were divided into non-significant fibrosis group （F<2） with 126 patients and significant fibrosis group （F≥2） with 137 patients. The correlation of MDA and FIB-4 with liver fibrosis degree was analyzed， and MDA and FIB-4 were compared in terms of their accuracy in assessing significant liver fibrosis. A total of 62 patients completed follow-up， and according to the presence or absence of progression to liver cirrhosis at the last follow-up visit， they were divided into progressive group with 21 patients and non-progressive group with 41 patients； the efficacy of MDA and FIB-4 in diagnosing disease progression was analyzed and compared. The independent-samples t test was used for comparison of normally distributed continuous data between groups， and the Mann-Whitney U test was used for comparison of non-normally distributed continuous data between groups； the Kruskal-Wallis H test was used for comparison between multiple groups， and the Bonferroni method was used for further comparison between two groups. The chi-square test was used for comparison of categorical data. The Spearman’s correlation coefficient was used for correlation analysis. The Wilcoxon signed rank sum test was used for the analysis of baseline data and data at the end of follow-up， and the binary Logistic regression analysis was used to investigate the influencing factors for progression to liver cirrhosis. The receiver operating characteristic （ROC） curve was used to investigate the diagnostic efficacy of indicators， the Z-test was used for comparison of the area under the ROC curve （AUC）， and the paired chi-square test was used for comparison of the sensitivity， specificity， and accuracy of the two indicators. ResultsThe correlation coefficient between FIB-4 and liver fibrosis degree was 0.378， while the correlation coefficient between MDA and liver fibrosis degree was -0.325 （both P<0.001）. FIB-4 had an AUC of 0.688， a sensitivity of 64.96%， a specificity of 68.87%， a positive predictive value of 67.42%， a negative predictive value of 63.36%， an accuracy of 65.40%， and a cut-off value of 1.01， while MDA had an AUC of 0.653， a sensitivity of 52.55%， a specificity of 78.57%， a positive predictive value of 72.73%， a negative predictive value of 60.37%， an accuracy of 65.02%， and a cut-off value of 0.29， suggesting that compared with FIB-4， MDA had a lower sensitivity （P=0.004） and a higher specificity （P=0.001）. The progressive group had a significantly higher age than the non-progressive group at baseline （t=2.611， P=0.011）. For the progressive group， there was an increase in FIB-4 and a reduction in MDA from baseline to the end of follow-up （both P<0.001）， while the non-progressive group showed no significant changes （both P>0.05）. The multivariate Logistic regression analysis showed that aspartate aminotransferase （odds ratio ［OR］=0.940， 95% confidence interval ［CI］： 0.885‍ ‍—‍ ‍0.998， P<0.05） and MDA （OR=0.445， 95%CI： 0.279‍ ‍—‍ ‍0.710， P<0.001） were independent influencing factors for disease progression. MDA had an AUC of 0.893 and an optimal cut-off value of -0.01 in diagnosing the disease progression of liver cirrhosis. ConclusionMDA has a comparable accuracy to FIB-4 in the diagnosis of significant liver fibrosis， and MDA<-0.01 has a high accuracy in diagnosing the progression of liver fibrosis to liver cirrhosis， which can help to reduce the need for liver biopsy in clinical practice.