ObjectiveTo assess the efficacy and safety of the Qi-regulating and phlegm-removing method（Liu Junzitang Combined with Linggang Wuwei Jiangxintang） for treating acute exacerbations of chronic obstructive pulmonary disease （AECOPD） with increased eosinophils （EOS）. MethodsSixty-eight AECOPD patients with increased EOS who were hospitalized in the Department of Pulmonary Diseases of Jinhua Traditional Chinese Medicine Hospital from April 2023 to April 2024 were recruited and randomly assigned to an experimental group （EG） or a control group （CG）. Both groups received conventional Western medicine， with the EG additionally receiving Liujunzitang and Linggan Wuwei Jiangxintang. The therapeutic efficacy indicators were measured after the treatment. The main therapeutic efficacy indicators included partial pressure of oxygen （PaO₂） and partial pressure of carbon dioxide （PaCO₂）. The secondary efficacy indicators included the TCM symptom scores， the COPD Assessment Test （CAT） score， the Modified Medical Research Council （mMRC） Dyspnea Scale score， and the length of hospital stay. The indicators were measured at baseline and on days 3 and 7 of intervention. The safety was evaluated based on the adverse events. ResultsBaseline characteristics were not statistically different between the two groups. Compared with CG， EG showed no significant difference in PaO₂ （P=0.773）， PaCO₂ （P=0.632） and or CAT score （P=0.336） at on day 3 but better PaO₂ （P=0.004）， PaCO₂ （P=0.008）， and CAT score （P=0.013） were significantly better at on day 7. Compared with CGAfter treatment， EG had lower TCM syndrome scores of than CG EG on day 3 （P=0.005） and day 7 were significantly decreased （P0.001）. There was no significant difference in mMRC score between the two groups on day 3 （P=0.514） and day 7 （P=0.176） as wasor the length of hospital stay （P=0.915）. The generalized linear mixed model （GLMM） showed that compared with CG， EG had significant improvements over time in PaO₂， PaCO₂， TCM syndrome symptom scores， CAT score， and mMRC score. ConclusionRegulating qi Qi and removing phlegm combined with conventional Western medicine can significantly alleviateimprove the clinical symptoms and improve the lung function of AECOPD patients with increased EOS increased AECOPDwhich has and demonstrates good safety.

ObjectiveTo assess the efficacy and safety of the Qi-regulating and phlegm-removing method（Liu Junzitang Combined with Linggang Wuwei Jiangxintang） for treating acute exacerbations of chronic obstructive pulmonary disease （AECOPD） with increased eosinophils （EOS）. MethodsSixty-eight AECOPD patients with increased EOS who were hospitalized in the Department of Pulmonary Diseases of Jinhua Traditional Chinese Medicine Hospital from April 2023 to April 2024 were recruited and randomly assigned to an experimental group （EG） or a control group （CG）. Both groups received conventional Western medicine， with the EG additionally receiving Liujunzitang and Linggan Wuwei Jiangxintang. The therapeutic efficacy indicators were measured after the treatment. The main therapeutic efficacy indicators included partial pressure of oxygen （PaO₂） and partial pressure of carbon dioxide （PaCO₂）. The secondary efficacy indicators included the TCM symptom scores， the COPD Assessment Test （CAT） score， the Modified Medical Research Council （mMRC） Dyspnea Scale score， and the length of hospital stay. The indicators were measured at baseline and on days 3 and 7 of intervention. The safety was evaluated based on the adverse events. ResultsBaseline characteristics were not statistically different between the two groups. Compared with CG， EG showed no significant difference in PaO₂ （P=0.773）， PaCO₂ （P=0.632） and or CAT score （P=0.336） at on day 3 but better PaO₂ （P=0.004）， PaCO₂ （P=0.008）， and CAT score （P=0.013） were significantly better at on day 7. Compared with CGAfter treatment， EG had lower TCM syndrome scores of than CG EG on day 3 （P=0.005） and day 7 were significantly decreased （P0.001）. There was no significant difference in mMRC score between the two groups on day 3 （P=0.514） and day 7 （P=0.176） as wasor the length of hospital stay （P=0.915）. The generalized linear mixed model （GLMM） showed that compared with CG， EG had significant improvements over time in PaO₂， PaCO₂， TCM syndrome symptom scores， CAT score， and mMRC score. ConclusionRegulating qi Qi and removing phlegm combined with conventional Western medicine can significantly alleviateimprove the clinical symptoms and improve the lung function of AECOPD patients with increased EOS increased AECOPDwhich has and demonstrates good safety.

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.

OBJECTIVE To investigate the effects and mechanism of Wenpi tongluo kaiqiao formula （WPTL） against neuronal necroptosis in Alzheimer’s disease （AD） mice based on the Z-DNA binding protein 1 （ZBP1）/mixed lineage kinase domain-like protein （MLKL） signaling pathway. METHODS Forty APP/PS1 transgenic AD mice were randomly divided into model group， WPTL low-dose （WPTL-L） group （10.4 g/kg， calculated by the raw medicine）， WPTL high-dose （WPTL-H） group （20.8 g/kg， calculated by the raw medicine） and donepezil hydrochloride group （3 mg/kg）， with 10 mice in each group； another 10 C57BL/6J mice were selected as normal control group. Intragastric administration， once a day， for 30 consecutive days. Twenty-four hours after the last administration， Morris water maze test was performed to evaluate learning and memory abilities； the pathological morphology of hippocampal tissues was observed； the serum levels of tumor necrosis factor-α （TNF-α） and interleukin-4 （IL-4） were determined； the expressions of amyloid precursor protein （APP）， Tau protein， and ZBP1/MLKL signaling pathway-related proteins in hippocampal tissues were detected； the positive expression of phosphorylated receptor-interacting protein kinase 3 （p-RIPK3） in the neurons of hippocampal tissues and mRNA expression of ZBP1 were measured in hippocampal tissues. RESULTS Compared with normal control group， the escape latency of mice in model group was prolonged significantly on day 3 to 5 （P＜0.05）， the times of crossing platform reduced significantly （P＜0.05）， and obvious pathological changes were observed in the hippocampal tissue. The level of TNF- α， the expressions of APP， p-Tau and ZBP1， the phosphorylation levels of RIPK1， RIPK3 and MLKL， the fluorescence intensity of p-RIPK3 as well as the mRNA expression of ZBP1 were significantly increased （P＜0.05）， while the serum level of IL-4 was decreased significantly （P＜0.05）. Compared with model group， above indexes were reversed significantly in administration groups （P＜0.05）， and pathological damage of hippocampal tissue was alleviated. CONCLUSIONS WPTL can inhibit the ZBP1/MLKL signaling pathway， reduce neuronal necroptosis in AD mice， and inhibit inflammatory responses， thereby improving learning and spatial memory abilities in AD mice.

Objective: To identify an optimal back-flush solution for leukocyte-depleted filters that maximizes peripheral blood mononuclear cell (PBMC) recovery with high viability, long-term storage stability, and sterility of the harvested residues, thereby providing a clinically translatable strategy. Methods: Three sterile bag-packaged solutions—Saline, Solvent, and Hanks' balanced salt solution (HBSS)—were used to back-flush randomly assigned leukocyte-depleted filters. Nucleated cell recovery rate and viability of the harvested residues were compared. The optimal solution identified was applied to an expanded sample set. PBMC viability and yield were evaluated after 1h vs 48h storage of the residues. PBMCs isolated from the residues were cryopreserved in liquid nitrogen for 1 month, followed by post-thaw comparisons of viability and T-cell expansion capacity. Results: The Solvent group achieved the highest and most consistent nucleated cell recovery rate. Post-flush recovery rate from filters after 400 mL whole blood processing was (21.3±1.6)% for the Solvent group, significantly higher than Saline group (19.2±6.3)% and HBSS group (11.2±5.0)%, with residues from all groups maintaining viability >90%. No biologically significant difference in residue viability was observed between 48h vs 1h storage groups (93.3±2.3)% vs (95.7±1.8)%). PBMC recovery rates from residues showed no statistical difference between 48h vs 1h storage groups [(48.2%±9.5%)vs (40.41%±8.35%), P>0.05], with (17.7±2.6)×10 cells. After 1-month cryopreservation and 10-day expansion, PBMCs isolated from 48-hour-stored residues retained (91.2±3.2)% viability and achieved a (61.9±15.9)-fold expansion. Conclusion: The bag-packaged Solvent, as a back-flush solution, enables sterile acquisition of leukocyte-depleted filter residues through closed-system tubing connections. These residues maintained PBMC viability and recovery rates after 48h storage at 2℃-8℃, with post-cryopreservation (1-month liquid nitrogen) viability and expansion capacity remaining stable. This protocol complies with blood bank regulatory criteria, addresses the concerns about the infectious window period in cell therapy raw materials, and provides a clinically translatable strategy for PBMC-based applications.

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.