Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

OBJECTIVE: To evaluate the dynamic changes of glucocorticoid (GC) dose and the feasibility of GC discontinuation in rheumatoid arthritis (RA) patients under the background of Chinese medicine (CM). METHODS: This multicenter retrospective cohort study included 1,196 RA patients enrolled in the China Rheumatoid Arthritis Registry of Patients with Chinese Medicine (CERTAIN) from September 1, 2019 to December 4, 2023, who initiated GC therapy. Participants were divided into the Western medicine (WM) and integrative medicine (IM, combination of CM and WM) groups based on medication regimen. Follow-up was performed at least every 3 months to assess dynamic changes in GC dose. Changes in GC dose were analyzed by generalized estimator equation, the probability of GC discontinuation was assessed using Kaplan-Meier curve, and predictors of GC discontinuation were analyzed by Cox regression. Patients with <12 months of follow-up were excluded for the sensitivity analysis. RESULTS: Among 1,196 patients (85.4% female; median age 56.4 years), 880 (73.6%) received IM. Over a median 12-month follow-up, 34.3% (410 cases) discontinued GC, with significantly higher rates in the IM group (40.8% vs. 16.1% in WM; P<0.05). GC dose declined progressively, with IM patients demonstrating faster reductions (median 3.75 mg vs. 5.00 mg in WM at 12 months; P<0.05). Multivariate Cox analysis identified age <60 years [P<0.001, hazard ratios (HR)=2.142, 95% confidence interval (CI): 1.523-3.012], IM therapy (P=0.001, HR=2.175, 95% CI: 1.369-3.456), baseline GC dose ⩽7.5 mg (P=0.003, HR=1.637, 95% CI: 1.177-2.275), and absence of non-steroidal anti-inflammatory drugs use (P=0.001, HR=2.546, 95% CI: 1.432-4.527) as significant predictors of GC discontinuation. Sensitivity analysis (545 cases) confirmed these findings. CONCLUSIONS RA patients receiving CM face difficulties in following guideline-recommended GC discontinuation protocols. IM can promote GC discontinuation and is a promising strategy to reduce GC dependency in RA management. (Trial registration: ClinicalTrials.gov, No. NCT05219214).
Adult ; Aged ; Female ; Humans ; Male ; Middle Aged ; Arthritis, Rheumatoid/drug therapy* ; Glucocorticoids/therapeutic use* ; Medicine, Chinese Traditional ; Retrospective Studies

Objective To analyze the effect of fisetin against venous thrombosis in rats.Methods Seventy SD rats were randomly divided into the following groups:sham-operation group,model group,fisetin 45 mg/kg,15 mg/kg,5 mg/kg groups,and aspirin group(47 mg/kg).The corresponding medication was administered by gavage once a day consecutively(the sham-operation group and the model group were given 0.5％carboxymethyl cellulose sodium solution with 10 mL/kg,respectively)for 7 consecutive days.One hour after the last administration,the rats were anesthetized,the lower part of the intersection of inferior vena cava and left renal vein was ligated with silk thread(no ligation in the sham-operation group),and the abdominal wall was sutured.Two hours later,the abdominal cavity was reopened,the other venous branches 1.5 cm away from the ligation site were closed with the artery clamp,and blood was collected from the abdominal aorta.The anticoagulant ratio of 3.8％sodium citrate∶whole blood was 1∶9.The venous thrombus 1 cm down from the ligation point of the intersection of inferior vena cava and left renal vein was cut and the thrombus was separated.The residual blood was dried with filter paper,weighed and recorded.Plasma was taken after anticoagulant blood centrifugation.The levels of plasma antithrombin-Ⅲ(AT-Ⅲ),protease C(PC),plasminogen(PLG),and plasminogen activator inhibitor(PAI-1)were detected by ELISA kits.Results Compared with the model group,the weight of thrombus in fisetin 45 mg/kg group and aspirin 47 mg/kg group decreased(P＜0.01).The content of AT-Ⅲ in three fisetin groups increased(all P＜0.05).The content of PC in fisetin 45 mg/kg increased(P＜0.05).The content of PLG and PAI-1 in fisetin 45 mg/kg group decreased(both P＜0.05).Conclusion Fisetin has the effect against venous thrombosis in vivo,and the effect is related to the upregulation of AT-Ⅲ and PC and the downregulation of PLG and PAI-1.

ObjectiveTo explore the current status and issues regarding the application of ancient books in clinical practice guidelines and expert consensus of traditional Chinese medicine （TCM） published in China， and to provide methodological recommendations for the incorporation of ancient books in the development of TCM guidelines. MethodsWe searched China National Knowledge Infrastructure （CNKI）， WanFang Data， VIP， SinoMed， PubMed， Embase， as well as six industry websites including China Association of Chinese Medicine， National Group Standards Information Platform， and Chinese Association of the Integration of Traditional and Western Medicine，etc. TCM clinical practice guidelines or expert consensus issued during January 1st， 2017， to November 26th， 2022 were searched. Clinical practice guidelines or expert consensus that explicitly referred to ancient books were included， and the content regarding the searching for ancient books， sources of access to ancient books， methods of evaluating the level of evidence， methods of evaluating the level of recommendation， and methods of evaluating the evidence for the ancient books were analysed. ResultsA total of 1,215 TCM clinical practice guidelines or expert consensus were retrieved， with 442 articles explicitly mentioning the application of ancient books， including 300 （67.87%） clinical practice guidelines and 142 （32.13%） expert consensus. Sixty of the 442 publications explicitly reported that ancient books searching had been conducted （13.57%）； among these 60 publications 27 （45.00%） explicitly reported ancient books searching strategies， and the most frequent method was manual searching with a total of 24 articles （40.00%）. The most popular search source was Chinese Medical Dictionary， a TCM classics database， with a total of 18 articles. 197 articles （44.57%） explicitly reported the evaluation criteria for the level of evidence， of which 141 articles （71.57%） involved the evaluation criteria for the ancient books； 413 articles （93.44%） mentioned ancient books in the recommendations， and only the source of formula name was mentioned in 409 （99.03%） of the publications. ConclusionThe current application of ancient books in TCM clinical practice guidelines and expert consensus is limited， with issues of non-standard searching and evaluation methods. Standar-dization and uniformity are needed in evidence grading and recommendation standards. Future research should clarify the scope and methods of applying ancient book， emphasize their integration with modern research evidence， and enhance their value and quality in the development of TCM clinical practice guidelines.

Objective:To investigate the effects of different concentrations of Qilan Prescription(QLP)on the proliferation and apoptosis of human PCa DU145 cells and its underlying mechanism.Methods:We treated human PCa DU145 cells with QLP at 400,200,100,50,25,12.5,6.25,3.125 or 1.56 μg/ml for 24,48 and 72 hours respectively.Then we observed the morphologi-cal changes of the cells,examined their viability by CCK-8 assay,detected their cell cycle and apoptosis by flow cytometry,and deter-mined the protein expressions of cyclin D1,Bax,Bcl-2 and cleaved-caspase 3 in the DU145 cells by Western blot,followed by com-parison of the parameters with those obtained from the blank control group.Results:QLP significantly inhibited the growth,reduced the contour clarity and adhesion ability of the DU145 cells at the concentrations of 100,200 and 400 μg/ml,and markedly decreased the activity of the cells at 200 and 400 μg/ml,most significantly at 400 μg/ml.The number of the G2-phase DU145 cells was dramat-ically increased in all the concentration groups(P＜0.01),so was the total number of apoptotic DU145 cells(P＜0.01),while that of the S-phase cells remarkably decreased in the 400 μg/ml QLP(P＜0.01)and 200 μg/ml QLP(P＜0.05)groups.The ex-pression of the cyclin D1 protein was significantly down-regulated in the 400 μg/ml QLP group(P＜0.01).That of Bcl-2 was also down-regulated(P＜0.01)while those of Bax and cleaved-caspase 3 up-regulated in the 400 and 200 μg/ml QLP groups(P＜0.01).Conclusion:QLP can inhibit the proliferation and promote the apoptosis of human PCa DU145 cells,which may be associat-ed with its effects of down-regulating the expression of the cell cycle-related protein cyclin D1,disrupting the Bax-Bcl-2 balance,and up-regulating the expression of cleaved-caspase 3.

Objective:To clarify the clinical efficacy of first-line oral antiviral drugs tenofovir alafenamide (TAF), tenofovir disoproxil fumarate (TDF), and entecavir (ETV) in the treatment of chronic hepatitis B (CHB) and their safety profiles with lipid, bone, and kidney metabolism.Methods:458 CHB cases diagnosed and treated at the Department of Hepatology of Integrated Traditional Chinese and Western Medicine of the Third Hospital of Hebei Medical University from February 2010 to November 2022 were selected. TAF (175 cases), TDF (124 cases), and ETV (159 cases) were used as therapies. At 24 and 48 weeks, the virology, biochemical response, changes in liver stiffness measurement (LSM), and bone, kidney, and blood lipid metabolism safety profiles were compared and analyzed.Results:After 24 and 48 weeks of TAF, TDF, and ETV therapy, HBV DNA load decreased by 3.28, 2.69, and 3.14 log10 IU/ml and 3.28, 2.83, and 3.65 log10 IU/ml, respectively, compared with the baseline, and the differences between the three groups were statistically significant, P < 0.001. The complete virological response rates were 73.95%, 66.09%, 67.19%, and 82.22%, 72.48%, and 70.49%, respectively. The incidence rates of low-level viremia were 16.67%, 21.70%, and 23.08%, while poor response rates were 1.11%, 3.67%, and 4.10%. ALT normalization rates were 64.00%, 63.89%, 67.96%, and 85.33%, 80.56%, 78.64%, respectively, and there was no statistically significant difference among the groups. LSM was significantly improved in patients treated with TAF for 48 weeks, P = 0.022. Serum phosphorus level gradually decreased with the prolongation of TDF treatment. The TAF treatment group had a good safety profile for kidney, bone, and phosphorus metabolism, with no dyslipidemia or related occurrences of risk. Conclusion:There are some differences in the therapeutic effects of first-line anti-HBV drugs. TAF has the lowest incidence of low-level viremia after 48 weeks of treatment and has a good safety profile in kidney, bone, and blood lipid metabolism.