Objective To develop an automated system for the determination of gross α and gross β activity concentrations in water, and to support the rapid and automated monitoring of environmental water bodies. Methods Based on the thick source method, microwave evaporation-ashing was used to replace conventional electric hotplate heating. A grinder and a sample-spreading device were designed and operated via a robotic arm, achieving fully automated pretreatment, sample preparation, and measurement. Results Spike recovery tests demonstrated that the recovery rates were 95.7%-102.5% for gross α and 97.2%-108.1% for gross β. The relative standard deviations were 4.1%-7.8% for gross α and 5.9%-7.7% for gross β. Compared with manual laboratory methods, the average relative errors were 2.17%-6.25% for gross α and 4.17%-6.90% for gross β. The sample preparation time was reduced from an average of 72 hours to less than 5 hours, representing an efficiency improvement of over 90%. Conclusion The developed system enables rapid, accurate, and fully automated monitoring of gross α/β radioactivity, making it suitable for online monitoring of environmental water bodies. It can provide timely data on the radiological indicators of water bodies for environmental protection and water resource management authorities.

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.

This study aimed to investigate the mechanism of compound Agrimonia pilosula enteritis capsules (CAPEC) on ulcerative colitis (UC) in mice with dampness-heat syndrome. The mice were randomly divided into five groups: the control group, the model group, the positive drug (5-aminosalicylic acid, 5-ASA) group, the low-dose CAPEC (CAPEC-L) group and the high-dose CAPEC (CAPEC-H) group. The mice models were established by using high-fat high-sucrose diet, feeding with distilled spirit and dextran sulfate sodium (DSS). The effects of CAPEC on bile acids (BAs) metabolic profiles in bile and the FXR-SREBP-1 signaling pathway were investigated in the model of UC in mice with dampness-heat syndrome by ELISA, qRT-PCR, UHPLC-QQQ/MS, and histopathological analysis. The results showed that, compared with the model group, the CAPEC-L group and the CAPEC-H group significantly reduced the disease activity index (DAI), and proinflammatory cytokine levels (including IL-6, IL-1β, and TNF-α) in both serum and colon tissues. Additionally, CAPEC markedly ameliorated intestinal inflammation, hepatic lipid accumulation, and pathological alterations in tongue tissue. The CAPEC-H group significantly attenuated the abnormal elevation of BAs profiles in bile, and up-regulated hepatic mRNA levels of Cyp7a1, Cyp7b1, Cyp27a1, Bsep, Fxr, and Shp, while down-regulating Srebp-1 and Cyp8b1 expression. The experimental results suggest that CAPEC alleviates UC with dampness-heat syndrome by ameliorating BAs metabolic disorders, hepatic lipid accumulation, and intestinal inflammation. These findings provide mechanistic insights into CAPEC’s traditional effects of clearing heat and drying dampness, and strengthening the spleen to relieve diarrhea.

ObjectiveTo investigate the mechanism by which Feixin decoction treats hypoxic pulmonary hypertension （HPH） by regulating the peroxisome proliferator-activated receptor gamma （PPARγ）/nuclear factor-kappa B （NF-κB）/NOD-like receptor pyrin domain containing 3 （NLRP3） signaling pathway. MethodsForty-eight male SD rats were randomly allocated into normal， hypoxia， and low-， medium- and high-dose （5.85， 11.7， 23.4 g·kg^-1， respectively） Feixin decoction groups， with 8 rats in each group. Except the normal group， the remaining five groups were placed in a hypoxia chamber with an oxygen concentration of （10.0±0.5）% for 8 h per day， 28 days， and administrated with corresponding drugs during the modeling process. After 4 weeks of treatment， echocardiographic parameters ［pulmonary artery acceleration time （PAT）， pulmonary artery ejection time （PET）， right ventricular anterior wall thickness （RVAWd）， and tricuspid annular plane systolic excursion （TAPSE）］ were measured for each group. The right ventricular systolic pressure （RVSP） was measured by the right heart catheterization method， and the right ventricular hypertrophy index （RVHI） was calculated by weighing the heart. The pathological changes in pulmonary arterioles were observed by hematoxylin-eosin staining. The co-localization of α-smooth muscle actin （α-SMA） with NLRP3， N-terminal gasdermin D （N-GSDMD）， and cysteinyl aspartate-specific proteinase-1 （Caspase-1） in pulmonary arteries was detected by immunofluorescence. The protein levels of PPARγ， NF-κB， NLRP3， apoptosis-associated speck-like protein containing a CARD （ASC）， N-GSDMD， interleukin-1β （IL-1β）， interleukin-18（IL-18）， and cleaved Caspase-1 in the lung tissue was determined by Western blot. The ultrastructural changes in pulmonary artery smooth muscle cells （PASMCs） were observed by transmission electron microscopy. ResultsCompared with the normal group， the hypoxia group showed increased RVSP and RVHI （P<0.01）， decreased right heart function （P<0.01）， increased pulmonary vascular remodeling （P<0.01）， increased co-localization of α-SMA with NLRP3， N-GSDMD， and Caspase-1 in pulmonary arterioles （P<0.01）， up-regulated protein levels of NF-κB， NLRP3， ASC， N-GSDMD， IL-1β， IL-18， and cleaved Caspase-1 in the lung tissue （P<0.05， P<0.01）， a down-regulated protein level of PPARγ （P<0.05， P<0.01）， and pyroptosis in PASMCs. Compared with the hypoxia group， Feixin decoction reduced RVSP and RVHI， improved the right heart function and ameliorated pulmonary vascular remodeling （P<0.05， P<0.01）， decreased the co-localization of α-SMA with NLRP3， N-GSDMD， and Caspase-1 （P<0.05， P<0.01）， down-regulated the protein levels of NF-κB， NLRP3， ASC， N-GSDMD， IL-1β， IL-18， and cleaved Caspase-1 in the lung tissue （P<0.05， P<0.01）， up-regulated the protein level of PPARγ （P<0.05， P<0.01）， and alleviated pyroptosis in PASMCs. ConclusionFeixin decoction can ameliorate pulmonary vascular remodeling and right heart dysfunction in chronically induced HPH rats by regulating pyroptosis in PASMCs through the PPARγ/NF-κB/NLRP3 pathway.

BACKGROUND: Postoperative pulmonary complications (PPCs) are major adverse events in neurosurgical patients. This study aimed to develop and validate machine learning models predicting PPCs after neurosurgery. METHODS: PPCs were defined according to the European Perioperative Clinical Outcome standards as occurring within 7 postoperative days. Data of cases meeting inclusion/exclusion criteria were extracted from the anesthesia information management system to create three datasets: The development (data of Huashan Hospital, Fudan University from 2018 to 2020), temporal validation (data of Huashan Hospital, Fudan University in 2021) and external validation (data of other three hospitals in 2023) datasets. Machine learning models of six algorithms were trained using either 35 retrievable and plausible features or the 11 features selected by Lasso regression. Temporal validation was conducted for all models and the 11-feature models were also externally validated. Independent risk factors were identified and feature importance in top models was analyzed. RESULTS: PPCs occurred in 712 of 7533 (9.5%), 258 of 2824 (9.1%), and 207 of 2300 (9.0%) patients in the development, temporal validation and external validation datasets, respectively. During cross-validation training, all models except Bayes demonstrated good discrimination with an area under the receiver operating characteristic curve (AUC) of 0.840. In temporal validation of full-feature models, deep neural network (DNN) performed the best with an AUC of 0.835 (95% confidence interval [CI]: 0.805-0.858) and a Brier score of 0.069, followed by Logistic regression (LR), random forest and XGBoost. The 11-feature models performed comparable to full-feature models with very close but statistically significantly lower AUCs, with the top models of DNN and LR in temporal and external validations. An 11-feature nomogram was drawn based on the LR algorithm and it outperformed the minimally modified Assess respiratory RIsk in Surgical patients in CATalonia (ARISCAT) and Laparoscopic Surgery Video Educational Guidelines (LAS VEGAS) scores with a higher AUC (LR: 0.824, ARISCAT: 0.672, LAS: 0.663). Independent risk factors based on multivariate LR mostly overlapped with Lasso-selected features, but lacked consistency with the important features using the Shapley additive explanation (SHAP) method of the LR model. CONCLUSIONS: The developed models, especially the DNN model and the nomogram, had good discrimination and calibration, and could be used for predicting PPCs in neurosurgical patients. The establishment of machine learning models and the ascertainment of risk factors might assist clinical decision support for improving surgical outcomes. TRIAL REGISTRATION ChiCTR 2100047474; https://www.chictr.org.cn/showproj.html?proj=128279 .
Adult ; Aged ; Female ; Humans ; Male ; Middle Aged ; Algorithms ; Lung Diseases/etiology* ; Machine Learning ; Neurosurgical Procedures/adverse effects* ; Postoperative Complications/diagnosis* ; Risk Factors ; ROC Curve

BACKGROUND: While emotional distress, encompassing anxiety and depression, has been associated with negative clinical outcomes, its impact across various clinical departments and general hospitals has been less explored. Previous studies with limited sample sizes have examined the effectiveness of specific treatments (e.g., antidepressants) rather than a systemic management strategy for outcome improvement in non-psychiatric inpatients. To enhance the understanding of the importance of addressing mental health care needs among non-psychiatric patients in general hospitals, this study retrospectively investigated the impacts of emotional distress and the effects of early detection and management of depression and anxiety on hospital length of stay (LOS) and rate of long LOS (LLOS, i.e., LOS >30 days) in a large sample of non-psychiatric inpatients. METHODS: This retrospective cohort study included 487,871 inpatients from 20 non-psychiatric departments of a general hospital. They were divided, according to whether they underwent a novel strategy to manage emotional distress which deployed the Huaxi Emotional Distress Index (HEI) for brief screening with grading psychological services (BS-GPS), into BS-GPS ( n = 178,883) and non-BS-GPS ( n = 308,988) cohorts. The LOS and rate of LLOS between the BS-GPS and non-BS-GPS cohorts and between subcohorts with and without clinically significant anxiety and/or depression (CSAD, i.e., HEI score ≥11 on admission to the hospital) in the BS-GPS cohort were compared using univariable analyses, multilevel analyses, and/or propensity score-matched analyses, respectively. RESULTS: The detection rate of CSAD in the BS-GPS cohort varied from 2.64% (95% confidence interval [CI]: 2.49%-2.81%) to 20.50% (95% CI: 19.43%-21.62%) across the 20 departments, with a average rate of 5.36%. Significant differences were observed in both the LOS and LLOS rates between the subcohorts with CSAD (12.7 days, 535/9590) and without CSAD (9.5 days, 3800/169,293) and between the BS-GPS (9.6 days, 4335/178,883) and non-BS-GPS (10.8 days, 11,483/308,988) cohorts. These differences remained significant after controlling for confounders using propensity score-matched comparisons. A multilevel analysis indicated that BS-GPS was negatively associated with both LOS and LLOS after controlling for sociodemographics and the departments of patient discharge and remained negatively associated with LLOS after controlling additionally for the year of patient discharge. CONCLUSION Emotional distress significantly prolonged the LOS and increased the LLOS of non-psychiatric inpatients across most departments and general hospitals. These impacts were moderated by the implementation of BS-GPS. Thus, BS-GPS has the potential as an effective, resource-saving strategy for enhancing mental health care and optimizing medical resources in general hospitals.
Humans ; Retrospective Studies ; Male ; Length of Stay/statistics & numerical data* ; Female ; Middle Aged ; Adult ; Psychological Distress ; Inpatients/psychology* ; Aged ; Anxiety/diagnosis* ; Depression/diagnosis*

This study investigated the functions and regulatory mechanism of Portulacae Herba and its chemical components on the Toll-like receptor 4(TLR4)/myeloid differentiation primary response 88(MyD88)/nuclear factor kappa B(NF-κB) inflammatory signaling pathway in the colon tissue of mice with dextran sodium sulfate(DSS)-induced ulcerative colitis(UC). A total of 35 mice were randomly divided into groups, including a blank group, a model group, a mesalazine group(0. 5 g·kg~(-1)), and low, medium,and high dose alkaloids from Portulacae Herba groups(9, 18, 36 mg·kg~(-1)), and a combination treatment group, with 5 mice in each group. The blank group was given purified water, while the other groups were continuously given a 3% DSS solution for 7 days to induce the UC model. From day 8 onwards, the treatment group received oral gavage according to the prescribed doses for 14 days. The overall condition, body weight, stool characteristics, and presence of blood in the stool were recorded daily. After the experiment, the disease activity index(DAI) was assessed for each group, and colon length was measured. Histopathological changes in colon tissue were examined using hematoxylin-eosin(HE) staining. The levels of pro-inflammatory cytokines, tumor necrosis factor-α(TNF-α),and interleukin-1β( IL-1β) in serum were measured by enzyme-linked immunosorbent assay( ELISA). The protein and m RNA expression of TLR4, MyD88, and NF-κB in colon tissue were measured using Western blot and quantitative real-time PCR(qPCR).Compared to the blank group, the model group showed a significant decrease in body weight, a notable increase in DAI scores, a significant shortening of colon length, and evident histopathological damage. The levels of inflammatory cytokines TNF-α and IL-1β in the serum were significantly elevated, and the protein and m RNA expression of TLR4, MyD88, and NF-κB in colon tissue were significantly up-regulated. In contrast, the alkaloids from Portulacae Herba treatment groups significantly improved symptoms and reduced body weight loss in mice, decreased DAI scores, alleviated colon shortening, lowered serum levels of TNF-α and IL-1β,significantly down-regulated the expression levels of TLR4, MyD88, and NF-κB proteins and genes in colon tissue, as well as reduced histopathological damage. Therefore, the study suggests that alkaloids from Portulacae Herba can alleviate intestinal inflammation damage in DSS-induced UC mice, with its mechanism involving the TLR4/MyD88/NF-κB signaling pathway.
Animals ; Colitis, Ulcerative/immunology* ; Toll-Like Receptor 4/immunology* ; Myeloid Differentiation Factor 88/metabolism* ; Mice ; NF-kappa B/metabolism* ; Signal Transduction/drug effects* ; Male ; Alkaloids/administration & dosage* ; Drugs, Chinese Herbal/administration & dosage* ; Humans ; Female ; Colon/metabolism* ; Disease Models, Animal

The therapeutic effects of traditional Chinese medicine(TCM) decoction is closely related to its decocting methods. A correct understanding of the scientific connotations of decocting methods in TCM is of great significance for guiding the application of decoctions and the development of modern TCM preparations based on decoctions. The decocting process is not only a hot water extraction process of chemical components but also accompanied by complex chemical and physical changes, forming a complex multiphase system and significantly affecting the absorption and therapeutic effect of TCM. This article reviews the research progress in scientific connotations of decocting methods in TCM from the perspectives of chemical composition changes, phase state differences,absorption behavior changes, and pharmacological and toxicological changes caused by decocting. This review is expected to provide implications for studying decocting methods and their scientific interpretation, boost the innovation and development of TCM decoctions,and promote the design and development of modern TCM preparations.
Drugs, Chinese Herbal/isolation & purification* ; Humans ; Medicine, Chinese Traditional/methods* ; Animals

Metal ion-promoted chemodynamic therapy(CDT) combined with photodynamic therapy(PDT) offers broad application prospects for enhancing anti-tumor effects. In this study, glycyrrhizic acid(GA), copper ions(Cu~(2+)), and norcantharidin(NCTD) were co-assembled to successfully prepare a natural small-molecule, carrier-free hydrogel(NCTD Gel) with excellent material properties. Under 808 nm laser irradiation, NCTD Gel responded to the tumor microenvironment(TME) and acted as an efficient Fenton reagent and photosensitizer, catalyzing the conversion of endogenous hydrogen peroxide(H_2O_2) within the tumor into oxygen(O_2), and hydroxyl radicals(·OH, type Ⅰ reactive oxygen species) and singlet oxygen(~1O_2, type Ⅱ reactive oxygen species), while depleting glutathione(GSH) to stabilize reactive oxygen species and alleviate tumor hypoxia. In vitro and in vivo experiments demonstrated that NCTD Gel exhibited significant CDT/PDT synergistic therapeutic effects. Further safety evaluation and metabolic testing confirmed its good biocompatibility and safety. This novel hydrogel is not only simple to prepare, safe, and cost-effective but also holds great potential for clinical transformation, providing insights and references for the research and development of metal ion-mediated hydrogel-based anti-tumor therapies.
Hydrogels/chemistry* ; Animals ; Photochemotherapy ; Humans ; Mice ; Antineoplastic Agents/administration & dosage* ; Photosensitizing Agents/chemistry* ; Neoplasms/metabolism* ; Female ; Copper/chemistry* ; Reactive Oxygen Species/metabolism* ; Tumor Microenvironment/drug effects* ; Cell Line, Tumor ; Male