Xiamen Traditional Chinese Medicine Co., Ltd.

Yuping Tongqiao Tablets is a classic traditional Chinese medicine (TCM) formula commonly employed in China for managing various ailments, especially allergic conditions. Clinical reports indicate its potential as an effective treatment for persistent allergic rhinitis. Nevertheless, there remains a dearth of placebo-controlled studies to definitively establish its safety and efficacy.

Allergic rhinitis (AR) is a global health problem with an annually increasing prevalence and no radical cure to date. This study aimed to evaluate the efficacy and safety of Yuping Tongqiao tablets for the treatment of persistent allergic rhinitis and to provide a basis for using Chinese herbal medicine to treat AR.

This was a multicenter, randomized, double-blind, placebo-controlled study of patients with PAR. A total of 540 patients with PAR were randomly assigned to the test group (n = 360) or the placebo group (n = 180) at a 2:1 ratio. The clinical trial lasted for 4 weeks, evaluating various outcomes including total nasal symptom scores, rhinoconjunctivitis quality of life questionnaire (RQLQ) scores, traditional Chinese medicine (TCM) symptom scores and The incidence of adverse events.

A total of 768 participants were enrolled, with 540 randomized and 516 successfully completed the research. The experimental group using Yuping Tongqiao tablets showed a significant reduction in TNSS, with the least squares mean of the average decrease being -2.56 points, compared to -1.74 points in the placebo group (p < 0.01). The experimental group exhibited a higher nasal symptom response rate at 4 weeks, substantial clinical improvements, and notable enhancements in TCM symptoms and RQLQ scores. Treatment efficacy increased with duration, and adverse events were mild-to-moderate and occurred at similar rates in both groups.

Yuping Tongqiao tablets have been proven to be an effective and safe medication for the treatment of PAR.

ChiCTR, ChiCTR2200061367. Registered June 22, 2022.

Cytokine synergy induced by the activation of multiple Toll-like receptors (TLRs) may result in uncontrollable life-threatening inflammation, the so-called cytokine storm. Owing to the complexity of the crosstalk for individual TLR signaling pathways, analyses of transcriptional changes in addition to differentially expression genes (DEGs) are needed. In the present study, we aimed to create algorithms to obtain a profile of synergistic cytokine production and to evaluate the anti-cytokine synergistic activity of ginsenoside Rg3. RAW264.7 macrophages were activated by TLR2/3 dual ligands; Rg3 was used as an intervention. After interleukin (IL)-6 secretion was detected as a preliminary readout for cytokine synergy, RNA sequencing-based bioinformatic analysis was performed, followed by qPCR and western blotting verification. Specifically, nonadditive transcriptional responses (DIFs) were applied as a measure of synergistic genes, and an anti-synergy score was created as a measure of the antagonistic effect of Rg3. A mouse model of TLR2/3 costimulation was subsequently established to evaluate the anti-cytokine synergistic effect of Rg3 in vivo. The results show that Rg3 alleviates synergistic cytokine production both in vitro and in vivo. Nuclear factor kappa B (NF-κB) and interferon regulatory factor 3 (IRF3) are novel targets of Rg3 related to its anti-cytokine synergistic effects. Our strategy of nonadditive transcriptional change analysis will be helpful for performing high-throughput screening for drugs with anti-cytokine synergy activities.

Biopsy is the gold standard method for diagnosing liver fibrosis. FibroScan is a non-invasive method of diagnosing liver fibrosis, but it still faces some limitations. This study aimed to establish a nomogram model and identify patients at high risk of advanced liver fibrosis associated with hepatitis B infection.

Data were collected from 375 patients with hepatitis B who underwent liver biopsy. Patients were divided randomly into the training (n = 263) and validation sets (n = 112). Their demographic and clinical characteristics were analyzed using the least absolute shrinkage and selection operator regression (LASSO). A nomogram model was established to predict the fibrosis stage, and its performance was assessed using the area under the receiver operating characteristic curve (AUC), calibration curve, and decision curve analysis (DCA) and was compared with other recognized models.

In total, 209 patients with non-advanced fibrosis (S0-1) and 166 patients with advanced fibrosis (S ≥ 2) were included. Hyaluronic acid (HA), laminin, total cholesterol (TC), platelet, and age were entered into the nomogram model based on the LASSO analysis. The nomogram model for predicting advanced fibrosis exhibited a relatively high AUC in the training set. Compared with FIB4 and APRI, the nomogram model showed a better agreement between the actual status and predicted status based on the calibration curve. The nomogram model showed an AUC similar to FibroScan in the validation cohort, and showed high clinical net benefits in the training and validation sets.

Our nomogram model can help identify patients with hepatitis B and advanced liver fibrosis.