This study investigated the regulatory potential of salidroside (SAL), a primary active compound in Rhodiola rosea L., on osteoclast differentiation by modulating the hypoxia-inducible factor 1-alpha (HIF-1a) pathway in osteoblasts. Luciferase reporter assay and chromatin immunoprecipitation (ChIP) assay were employed to validate whether the receptor activator of nuclear factor-?B ligand (RANKL) is the downstream target gene of HIF-1a in osteoblasts. The study also utilized lipopolysaccharide (LPS)-induced mouse osteolysis to examine the impact of SAL on osteolysis in vivo. Furthermore, conditioned medium (CM) from SAL-pretreated osteoblasts was used to investigate the paracrine effects on osteoclastogenesis through the HIF-1a pathway. Hypoxic condition-induced overexpression of HIF-1a upregulated RANKL levels by binding to the RANKL promoter and enhancing transcription in osteoblastic cells. In vivo, SAL significantly alleviated bone tissue hypoxia and decreased the expression of HIF-1a by downregulating the expression of RANKL, vascular endothelial growth factor (VEGF), interleukin 6 (IL-6), and angiopoietin-like 4 (ANGPTL4). In the paracrine experiment, conditioned media from SAL-pretreated osteoblasts inhibited differentiation through the HIF-1a/RANKL, VEGF, IL-6, and ANGPTL4 pathways. RANKL emerges as the downstream target gene regulated by HIF-1a in osteoblasts. SAL significantly alleviates bone tissue hypoxia and bone loss in LPS-induced osteolysis through the HIF-1a/RANKL, VEGF, IL-6, and ANGPTL4 pathways. SAL inhibits osteoclast differentiation by regulating osteoblast paracrine secretion.
Animals ; Osteoblasts/cytology* ; Hypoxia-Inducible Factor 1, alpha Subunit/genetics* ; Glucosides/administration & dosage* ; Cell Differentiation/drug effects* ; Phenols/administration & dosage* ; Mice ; Osteoclasts/metabolism* ; RANK Ligand/genetics* ; Rhodiola/chemistry* ; Osteogenesis/drug effects* ; Signal Transduction/drug effects* ; Interleukin-6/genetics* ; Male ; RAW 264.7 Cells ; Osteolysis/genetics* ; Humans ; Mice, Inbred C57BL

Chemical cleaning and disinfection are crucial steps for eliminating infection in root canal treatment.However,irrigant selection or irrigation procedures are far from clear.The vapor lock effect in the apical region has yet to be solved,impeding irrigation efficacy and resulting in residual infections and compromised treatment outcomes.Additionally,ambiguous clinical indications for root canal medication and non-standardized dressing protocols must be clarified.Inappropriate intracanal medication may present side effects and jeopardize the therapeutic outcomes.Indeed,clinicians have been aware of these concerns for years.Based on the current evidence of studies,this article reviews the properties of various irrigants and intracanal medicaments and elucidates their effectiveness and interactions.The evolution of different kinetic irrigation methods,their effects,limitations,the paradigm shift,current indications,and effective operational procedures regarding intracanal medication are also discussed.This expert consensus aims to establish the clinical operation guidelines for root canal irrigation and a position statement on intracanal medication,thus facilitating a better understanding of infection control,standardizing clinical practice,and ultimately improving the success of endodontic therapy.

The overall health condition of patients significantly affects the diagnosis,treatment,and prognosis of endodontic diseases.A systemic consideration of the patient's overall health along with oral conditions holds the utmost importance in determining the necessity and feasibility of endodontic therapy,as well as selecting appropriate therapeutic approaches.This expert consensus is a collaborative effort by specialists from endodontics and clinical physicians across the nation based on the current clinical evidence,aiming to provide general guidance on clinical procedures,improve patient safety and enhance clinical outcomes of endodontic therapy in patients with compromised overall health.

Objective:To investigate the status of medical care seeking delay and diagnosis delay of pulmonary tuberculosis (PTB) patients in Tongzhou District and Changping District of Beijing, analyze the related factors and put forward suggestions for early detection and scientific management of PTB patients.Methods:A retrospective epidemiological survey was conducted to collect the incidence data of PTB registered in Tongzhou and Changping from January 1 to December 31, 2021 by using the Chinese Tuberculosis Information Management System, and telephone interview were used for information supplement. Multivariate logistic regression model and decision tree model were used to analyze the influencing factors of medical care seeking delay and diagnosis delay of PTB patients.Results:In 2021, the medical care seeking delay time M( Q1, Q3) in the PTB patients in Tongzhou and Changping was 11 (5, 26) days, with a delay rate of 41.71%. Results from multivariate logistic regression model analysis revealed that factors influencing the medical care seeking delay included regular health check-up ( OR=0.033, 95% CI: 0.008-0.147), coughing for less than 2 weeks or showing any symptom of PTB before medical care seeking ( OR=0.378, 95% CI: 0.215-0.665), showing other symptoms before medical care seeking( OR=2.791, 95% CI: 1.710-4.555), no work or school in medical care seeking ( OR=2.990, 95% CI: 1.419-6.298). The diagnosis delay time M( Q1, Q3) in the PTB patients was 8 (0, 18) days, with a delay rate of 35.20%. Multivariate logistic regression model analysis revealed that the factors influencing the diagnosis delay of PTB included being diagnosed at a specialized tuberculosis hospital ( OR=0.426, 95% CI: 0.236-0.767) or a tuberculosis prevention and control institution ( OR=1.843, 95% CI: 1.061-3.202) and being traced as a source of infection ( OR=2.632, 95% CI: 1.062-6.521). The overall performance of the multivariate logistic regression model was comparable to that of the decision tree model, with the decision tree model exhibiting higher sensitivity but lower specificity. Conclusions:The medical care seeking delay rate and diagnosis delay rate of tuberculosis in Tongzhou and Changping were at low levels in 2021. However, it is still necessary to strengthen the health education and active screening, improve the public awareness of PTB prevention and control, and further improve the level of medical services and medical access to reduce the medical care seeking delay and diagnosis delay of PTB patients.

Objective:To evaluate the current status of alpha-fetoprotein (AFP) detection, a comparability analysis was conducted on the results measured by eight automated immunoassay systems, incorporating external quality assessment (EQA) data from the Beijing Center for Clinical Laboratories (BCCL) for the years 2020, 2021, and 2023.Methods:Methodological evaluation. Abbott Architect i2000, Beckman DxI 800, Roche Cobas E601, Diasorin Liaison XL, Maccura IS1200, Autolumo A2000, Leadman CI1000, and Mindray CL-2000i were used to detect 40 individual AFP serum samples that were collected from the laboratory of Beijing Chaoyang Hospital in 2019. The AFP results from eight different systems were compared with the median cohort. Passing-Bablok regression was used to evaluate the correlation between methods, and the concordance correlation coefficient was used to analyse the consistency between methods. Taking the optimal biological variability (±5.90%) as the criterion for bias evaluation, the bias between systems was evaluated using Bland-Altman analysis. The EQA results for AFP from BCCL over the past three years were statistically analysed to calculate the robust mean, robust coefficient of variation ( CV), and standard uncertainty within groups. The acceptance limit is based on the requirement of desirable biological variability (±21.87%) of allowable total error, and the pass rates were calculated for instrument or method groups, respectively. Results:The CVs of the eight detection systems were all≤1/3 allowable total error (±8.3%), passing the precision verification. The average relative biases between two detection systems (Roche Cobas E601 and Maccura IS1200) and the median cohort were>±5.90%, while the other six detection systems were<±5.90%. The eight detection systems showed good correlation and consistency with the median cohort (both R2 and concordance correlation coefficients>0.95). The results of EQA showed that there were no statistically significant differences in the robust means within each instrument or method group ( P>0.05). In the instrument group, except for Siemens and two other groups, the robust CVs of other groups were within 9%. The pass rates of most instruments and methods after being grouped were higher than the total pass rate, but that of the enzyme immunoassay chemiluminescence method was relatively low. Conclusions:The eight automated AFP immunoassay systems show a good correlation with the median cohort, and the consistency of AFP detection results is satisfactory among most detection systems. However, the comparability of AFP detection results for certain systems needs further improvement.

Objective:To systematically evaluate the recurrence risk prediction model of diabetic foot ulcers (DFU) .Methods:Research on DFU recurrence risk prediction models was electronically searched in PubMed, Embase, Web of Science, Cochrane Library, China National Knowledge Infrastructure, Wanfang Data, and China Biomedical Service System. The search period was from database establishment to July 20, 2023. Two researchers independently screened literature and conducted data extraction and quality evaluation using the prediction model research data extraction table and the Prediction Model Risk of Bias Assessment Tool (PROBAST) .Results:A total of 8 articles were included, including 14 models. The area under the receiver operating characteristic (ROC) curve included in the model ranged from 0.660 to 0.940. The most common five predictors in the model were ulcers location, glycosylated hemoglobin, smoking, combined peripheral neuropathy and diabetes course. All 8 articles had a high risk of bias, mainly due to insufficient sample size, improper handling and reporting of missing data, and a lack of internal validation, which might lead to overfitting of the model. Only one article was subjected to external validation.Conclusions:The research on DFU recurrence risk prediction models is still in the development stage, and the predictive performance of various studies is still acceptable, but there is a high risk of bias. Future research still needs to use rigorous statistical analysis methods to construct new risk prediction models and improve internal and external validation.

ObjectiveTaking the rat model of spleen-stomach damp-heat syndrome（SSDHS） as the research object， this study aimed to investigate the potential biomarkers of SSDHS and the related metabolic pathways based on urine metabolomics， and tried to reveal the essence of SSDHS at the level of endogenous small molecular metabolites. MethodSixteen SD rats were randomly divided into normal and model groups. The normal group was fed normal chow and the model group was fed with 200 g·L^-1 honey water daily， and lard and Chinese Baijiu alternately on alternate days for 17 days. The SSDHS model rats were exposed to external dampness-heat environment with temperature at 30-34 ℃， relative humidity of 95% for 2 h at the same time every day from the 10^th day for 7 d. Then， the model was evaluated by observing the general conditions of the rats， measuring the contents of motilin（MTL） and gastrin（GT） in plasma by enzyme-linked immunosorbent assay（ELISA）， and examining the histopathology of gastronitestinal tissues. In additon， the urine metabolomics analysis was performed by ultra-high performance liquid chromatography-quadrupole-time-of-flight mass spectrometry（UPLC-Q-TOF-MS）， and the detection conditions was as follows：ACQUITY™ UPLC BEH C₁₈ column（2.1 mm×100 mm， 1.7 μm）， mobile phase of 0.1% formic acid aqueous solution（A）-0.1% formic acid acetonitrile solution（B） for gradient elution （0-3 min， 1%-18%B； 3-8 min， 18%-40%B； 8-10 min， 40%-100%B）， the flow rate of 0.4 mL·min^-1， electrospray ionization（ESI） in positive and negative ion modes， scanning range of m/z 50-1 000. The univariate and multivariate statistical analysis were constructed for screening inter-group differential ions， the element composition was calculated according to the precise relative molecular weight， and ion information was matched with databases such as Human Metabolome Database（HMDB） to identify biomarkers. Kyoto Encyclopedia of Genes and Genomes（KEGG） database was used to obtain the biological information of metabolites， and their associated metabolic pathways were analyzed by MetaboAnalyst 5.0. ResultCompared with the normal group， the rectal temperature of the model group increased significantly（P<0.01）， the levels of plasma MTL and GT decreased significantly（P<0.05， P<0.01）， and pathological changes such as bleeding， congestion and inflammatory infiltration in the gastric and colonic tissues. A total of 25 differential metabolites such as L-histidine， citric acid and isocitric acid were found to be the potential biomarker of SSDHS by urine metabolomics， 13 of which were phase Ⅱ metabolites of endogenous substances（glucuronic acid conjugates， sulfuric acid conjugates and acetyl conjugates）， involving the metabolic pathways of histidine metabolism， tricarboxylic acid cycle， glyoxylate and dicarboxylate metabolism. ConclusionSSDHS primarily causes disorders of histidine metabolism， tricarboxylic acid cycle， glyoxylate and dicarboxylate metabolism， as well as the imbalance of the activation/inactivation of endogenous metabolites， which may involve the immune response， material and energy metabolism， inflammatory response and intestinal flora， and may provide a basis for the establishment and application of SSDHS model.

Objective To analyze the chemical constituents in the water extract of Bupleuri Radix and investigate the active ingredients of Bupleuri Radix for the treatment of depression.Methods The chemical constituents in the water extract of Bupleuri Radix were identified by Ultra-high-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry(UPLC-Q-TOF/MS).CORT-induced poorly differentiated PC12 depression cell model was launched,and PC12 cells were pretreated with monomeric compounds from Bupleuri Radix for 24 h.The cell viability and LDH release rate were measured by CCK-8 assy kit and LDH assay kit,respectively.Results A total of 53 compounds were identified in the water extract of Bupleuri Radix,mainly including type Ⅰ,type Ⅱ and type Ⅲsaikosaponins.Among them,saikosaponin A,saikosaponin B2,saikosaponin C,saikosaponin E,saikosaponin F and 6″-acetyl saikosaponin A contributed the most to the metabolite profile of Bupleuri Radix,and could improve the viability of CORT-induced PC12 cells(P<0.05,P<0.01).Furthermore,saikosaponin A,saikosaponin B2,saikosaponin C,saikosaponin E and saikosaponin F could decrease the LDH release rate of CORT-induced PC12 cells(P<0.05,P<0.01).Conclusion The major anti-depression active ingredients in Bupleuri Radix may be Saikosaponin A,saikosaponin B2,saikosaponin C,saikosaponin E and saikosaponin F,which lays a foundation for the research of the quality control and pharmacodynamic material basis of Bupleuri Radix.

Humans ; Consensus ; Pancreatic Neoplasms/therapy* ; Neuroendocrine Tumors/therapy*

Objective:To compare results of four glycosylated hemoglobin A1c (HbA1c) detection methods and to evaluate the uncertainty of HbA1C results in clinical laboratory, and to provide method for clinical laboratory on the evaluation of uncertainty.Methods:According to the four uncertainty evaluation methods, which were recommended by "CNAS-TRL-001, the evaluation and expression of measurement uncertainty in medical laboratory", the relative and absolute uncertainty of low, medium and high HbA1c in 33 clinical laboratories measured in 2019 and 35 clinical laboratories measured in 2020 was evaluated by more than 6 months of internal quality control (IQC) data, trueness verification and external quality assessment (EQA) data. The four uncertainty evaluation methods were: IQC data and trueness verification data (method 1), only trueness verification data (method 2), IQC and EQA data (method 3) and only EQA data (method 4). The related statistical methods used in this analysis were Friedman and Wilcoxon signed rank test.Results:For method 1, the median range of relative and absolute uncertainty of low, medium and high HbA1c detection in 2019 and 2020 ranged from 4.21% to 9.24% and from 0.27% to 0.64%, respectively. Compared to method 1, the relative and absolute uncertainties obtained by method 2 were smaller, and the differences were statistically significant ( P<0.016 7, P<0.05). Compared to method 1, the relative uncertainties obtained by method 3 and method 4 were smaller, except for the high concentration of HbA1c level in 2020. Among the 6 pairs of comparisons (low, medium and high HbA1c in 2019 and 2020), there were 3 pairs (high HbA1c in 2019, low and medium HbA1c in 2020) and 2 pairs (low and high HbA1c in 2020) of differences with statistical significance (all P<0.016 7). Conclusion:The uncertainty evaluation of HbA1c detection in clinical laboratory should be evaluated based on IQC and trueness verification data.