ObjectiveTo explore the listed varieties and prescription characteristics of Chinese patent medicines for stroke in China， explore the medication rules of Chinese medicine for stroke， and provide guidance for further clinical research and development of Chinese patent medicines. MethodsExcel 2021 and the Ancient and Modern Medical Record Cloud Platform （V2.3.5） were used to systematically mine and analyze the varieties and prescriptions of Chinese patent medicines for stroke in China. ResultsA total of 244 Chinese patent medicines （two for different dosage forms of the same prescription）， 1 736 approval documents for Chinese patent medicines， 792 manufacturers， and 83 varieties of protected Chinese patent medicines were finally included in the database. The top three dosage forms were capsules （75）， pills （53）， and tablets （42）. There were 28 Chinese patent medicines for stroke in the National Essential Drug Catalogue （2018）， 129 in the National Essential Medical Insurance， Industrial Injury Insurance and Maternity Insurance Drug Catalogue （2023）， and 4 in the National Non-prescription Drug Catalogue. Among the 138 prescriptions screened out， Chinese patent medicines mainly treated stroke patients with the syndrome of Qi deficiency and blood stasis. The top three most frequent medicinal herbs were Chuanxiong Rhizoma （63）， Pheretima （47）， and Salviae Miltiorrhizae Radix et Rhizoma （47）. The medicinal herbs used were mainly warm， pungent， with the meridian tropism to the liver meridian. The correlation analysis showed that the herb pair with the highest support was Astragali Radix-Chuanxiong Rhizoma， and that with the highest confidence was Carthami Flos-Chuanxiong Rhizoma. Five herb combinations were identified based on the cluster analysis. ConclusionThe Chinese patent medicines for stroke mainly treat patients with the syndrome of Qi deficiency and blood stasis. The medicinal herbs used in the prescriptions mainly have the functions of activating blood and resolving stasis， extinguishing wind and stopping convulsions. Drug compatibility usually focuses on activating blood and resolving stasis， as well as expelling phlegm and opening orifices. This review of the varieties and prescription characteristics of Chinese patent medicines for stroke helps optimize clinical decision-making， guide drug research and development， promote medical research and scientific progress， and provide more effective support and guarantee for the treatment of stroke patients.

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 explore the pharmacokinetic characteristics of 3 blood-absorbed components of Xiangshao sanjie oral liquid in rats with hyperplasia of mammary gland （HMG）. METHODS Female SD rats were divided into control group and HMG group according to body weight， with 6 rats in each group. The HMG group was given estrogen+progesterone to construct HMG model. After modeling， two groups were given 1.485 g/kg of Xiangshao sanjie oral liquid （calculated by crude drug） intragastrically， once a day， for 7 consecutive days. Blood samples were collected before the first administration （0 h）， and at 5， 15， 30 minutes and 1， 2， 4， 8， 12， 24 hours after the last administration， respectively. Using chlorzoxazone as the internal standard， the plasma concentrations of ferulic acid， paeoniflorin and rosmarinic acid in rats were detected by UPLC-Q/TOF-MS. The pharmacokinetic parameters [area under the drug time curve （AUC0－24 h， AUC0－∞）， mean residence time （MRT0－∞）， half-life （t1/2）， peak time （tmax）， peak concentration （cmax）] were calculated by the non-atrioventricular model using Phoenix WinNonlin 8.1 software. RESULTS Compared with the control group， the AUC0－24 h， AUC0－∞ and cmax of ferulic acid in the HMG group were significantly increased （P＜0.05）； the AUC0－24 h， AUC0－∞ ， MRT0－∞ ， t1/2 and cmax of paeoniflorin increased， but there was no significant difference between 2 groups （P＞0.05）； the AUC0－24 h and MRT0-∞ of rosmarinic acid were significantly increased or prolonged （P＜0.05）. C ONCLUSIONS In HMG model rats， the exposure of ferulic acid， paeoniflorin and rosmarinic acid in Xiangshao sanjie oral liquid all increase， and the retention time of rosmarinic acid is significantly prolonged.

ObjectiveTo explore the mechanism of Jiebiao Qingli decoction （JQD） in treating pneumonia caused by influenza A virus （IAV） infection. MethodsA total of 132 Balb/c mice were randomly assigned into normal control （NC）， model control （IAV）， oseltamivir （OSV， 37.5 mg·kg^-1）， and high-， medium-， low-dose JQD （H-， M-， and L-JQD： 6.05， 3.02， and 1.51 g·kg^-1， respectively） groups. The NC group was treated with normal saline nasal drops， and the other groups were intranasally inoculated with A/Brisbane/02/2018 （H1N1） ［pdm09-like virus （H1N1）］ for the modeling of IAV infection. Two hours post-modeling， the NC and IAV groups were administrated with normal saline by gavage， while other groups received corresponding drugs for 7 d. The body mass， survival status， and deaths of mice were recorded daily during the administration of the drugs. On days 3 and 7， the lung index was measured for mice in each group. Pathological changes in the lung tissue were observed via hematoxylin-eosin staining. Real-time fluorescence quantitative polymerase chain reaction （Real-time PCR） was conducted to measure the viral load （IAV-M） and the mRNA levels of Toll-like receptor 7 （TLR7）， p38 mitogen-activated protein kinase （p38 MAPK）， and nuclear factor-kappa B （NF-κB） in the lung tissue. Western blot was employed to measure the protein levels of p38 MAPK and NF-κB. Enzyme-linked immunosorbent assay was used to quantify serum levels of interleukin-2 （IL-2）， interleukin-6 （IL-6）， and tumor necrosis factor-alpha （TNF-α）. ResultsCompared with the NC group， the IAV group showed reduced survival quality and survival days （P<0.01）， lung congestion， inflammatory cell infiltration， elevated lung index （P<0.01）， increased viral load （P<0.01）， upregulated TLR7， p38 MAPK， and NF-κB levels （P<0.05， P<0.01）， decreased IL-2 level （P<0.01）， and elevated IL-6 and TNF-α levels （P<0.01）. Compared with the IAV group， H-JQD prolonged survival days （P<0.05）. All JQD groups alleviated pathological changes in the lung tissue and reduced the lung index （P<0.01）. M-JQD and H-JQD decreased the viral load （P<0.01）. H-JQD downregulated the mRNA levels of TLR7， p38 MAPK， and NF-κB （P<0.05， P<0.01） and the protein levels of p38 MAPK and NF-κB （P<0.01）， increased the serum IL-2 level （P<0.01）， and lowered the IL-6 and TNF-α levels （P<0.05， P<0.01）. M-JQD downregulated the mRNA level of NF-κB （P<0.01） and the protein level of p38 MAPK （P<0.05）， elevated the IL-2 level （P<0.01）， and lowered the TNF-α level （P<0.01）. ConclusionM- and H-JQD can prevent and control IAV infection-induced pneumonia dose-dependently by inhibiting the TLR7/MAPK/NF-κB signaling pathway， increasing IL-2， and reducing excessive secretion of IL-6 and TNF-α.

ObjectiveTo explore the mechanism of Jiebiao Qingli decoction （JQD） in treating pneumonia caused by influenza A virus （IAV） infection. MethodsA total of 132 Balb/c mice were randomly assigned into normal control （NC）， model control （IAV）， oseltamivir （OSV， 37.5 mg·kg^-1）， and high-， medium-， low-dose JQD （H-， M-， and L-JQD： 6.05， 3.02， and 1.51 g·kg^-1， respectively） groups. The NC group was treated with normal saline nasal drops， and the other groups were intranasally inoculated with A/Brisbane/02/2018 （H1N1） ［pdm09-like virus （H1N1）］ for the modeling of IAV infection. Two hours post-modeling， the NC and IAV groups were administrated with normal saline by gavage， while other groups received corresponding drugs for 7 d. The body mass， survival status， and deaths of mice were recorded daily during the administration of the drugs. On days 3 and 7， the lung index was measured for mice in each group. Pathological changes in the lung tissue were observed via hematoxylin-eosin staining. Real-time fluorescence quantitative polymerase chain reaction （Real-time PCR） was conducted to measure the viral load （IAV-M） and the mRNA levels of Toll-like receptor 7 （TLR7）， p38 mitogen-activated protein kinase （p38 MAPK）， and nuclear factor-kappa B （NF-κB） in the lung tissue. Western blot was employed to measure the protein levels of p38 MAPK and NF-κB. Enzyme-linked immunosorbent assay was used to quantify serum levels of interleukin-2 （IL-2）， interleukin-6 （IL-6）， and tumor necrosis factor-alpha （TNF-α）. ResultsCompared with the NC group， the IAV group showed reduced survival quality and survival days （P<0.01）， lung congestion， inflammatory cell infiltration， elevated lung index （P<0.01）， increased viral load （P<0.01）， upregulated TLR7， p38 MAPK， and NF-κB levels （P<0.05， P<0.01）， decreased IL-2 level （P<0.01）， and elevated IL-6 and TNF-α levels （P<0.01）. Compared with the IAV group， H-JQD prolonged survival days （P<0.05）. All JQD groups alleviated pathological changes in the lung tissue and reduced the lung index （P<0.01）. M-JQD and H-JQD decreased the viral load （P<0.01）. H-JQD downregulated the mRNA levels of TLR7， p38 MAPK， and NF-κB （P<0.05， P<0.01） and the protein levels of p38 MAPK and NF-κB （P<0.01）， increased the serum IL-2 level （P<0.01）， and lowered the IL-6 and TNF-α levels （P<0.05， P<0.01）. M-JQD downregulated the mRNA level of NF-κB （P<0.01） and the protein level of p38 MAPK （P<0.05）， elevated the IL-2 level （P<0.01）， and lowered the TNF-α level （P<0.01）. ConclusionM- and H-JQD can prevent and control IAV infection-induced pneumonia dose-dependently by inhibiting the TLR7/MAPK/NF-κB signaling pathway， increasing IL-2， and reducing excessive secretion of IL-6 and TNF-α.

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.

Background/Aims: Treatment indications for patients with chronic hepatitis B (CHB) remain contentious, particularly for patients with mild alanine aminotransferase (ALT) elevation. We aimed to evaluate treatment effects in this patient population. Methods: This rollover study extended a placebo-controlled trial that enrolled non-cirrhotic patients with CHB and ALT levels below two times the upper limit of normal. Following 3 years of randomized intervention with either tenofovir disoproxil fumarate (TDF) or placebo, participants were rolled over to open-label TDF for 3 years. Liver biopsies were performed before and after the treatment to evaluate histopathological changes. Virological, biochemical, and serological outcomes were also assessed (NCT02463019). Results: Of 146 enrolled patients (median age 47 years, 80.8% male), 123 completed the study with paired biopsies. Overall, the Ishak fibrosis score decreased in 74 (60.2%), remained unchanged in 32 (26.0%), and increased in 17 (13.8%) patients (p<0.0001). The Knodell necroinflammation score decreased in 58 (47.2%), remained unchanged in 29 (23.6%), and increased in 36 (29.3%) patients (p=0.0038). The proportion of patients with an Ishak score ≥ 3 significantly decreased from 26.8% (n=33) to 9.8% (n=12) (p=0.0002). Histological improvements were more pronounced in patients switching from placebo. Virological and biochemical outcomes also improved in placebo switchers and remained stable in patients who continued TDF. However, serum HBsAg levels did not change and no patient cleared HBsAg. Conclusions In CHB patients with minimally raised ALT, favorable histopathological, biochemical, and virological outcomes were observed following 3-year TDF treatment, for both treatment-naïve patients and those already on therapy.

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.

Background/Aims: Treatment indications for patients with chronic hepatitis B (CHB) remain contentious, particularly for patients with mild alanine aminotransferase (ALT) elevation. We aimed to evaluate treatment effects in this patient population. Methods: This rollover study extended a placebo-controlled trial that enrolled non-cirrhotic patients with CHB and ALT levels below two times the upper limit of normal. Following 3 years of randomized intervention with either tenofovir disoproxil fumarate (TDF) or placebo, participants were rolled over to open-label TDF for 3 years. Liver biopsies were performed before and after the treatment to evaluate histopathological changes. Virological, biochemical, and serological outcomes were also assessed (NCT02463019). Results: Of 146 enrolled patients (median age 47 years, 80.8% male), 123 completed the study with paired biopsies. Overall, the Ishak fibrosis score decreased in 74 (60.2%), remained unchanged in 32 (26.0%), and increased in 17 (13.8%) patients (p<0.0001). The Knodell necroinflammation score decreased in 58 (47.2%), remained unchanged in 29 (23.6%), and increased in 36 (29.3%) patients (p=0.0038). The proportion of patients with an Ishak score ≥ 3 significantly decreased from 26.8% (n=33) to 9.8% (n=12) (p=0.0002). Histological improvements were more pronounced in patients switching from placebo. Virological and biochemical outcomes also improved in placebo switchers and remained stable in patients who continued TDF. However, serum HBsAg levels did not change and no patient cleared HBsAg. Conclusions In CHB patients with minimally raised ALT, favorable histopathological, biochemical, and virological outcomes were observed following 3-year TDF treatment, for both treatment-naïve patients and those already on therapy.