Qingzao Jiufeitang is a famous classical formula for treating lung injury caused by warm and dryness， included in the Catalogue of Ancient Famous Classical Formulas（The First Batch）. By systematically organizing ancient and modern literature on this formula， this study analyzed and verified the origin， medicinal composition， original plants and processing， dosage and decoction method， efficacy and application of this formula. According to the research， Qingzao Jiufeitang was first recorded in Yimen Falyu in the Qing dynasty， and its creation was mainly inspired by the Ming dynasty physician MIAO Xiyong's idea of the moisturizing drugs with sweet flavour and cold nature. Based on the 2020 edition of the Pharmacopoeia of the People's Republic of China（hereinafter referred to as the Chinese Pharmacopoeia） and the textual research results of modern scholars on traditional Chinese herbal medicines， the botanical sources and processing methods of the herbs in this formula are basically clarified. Among them， Mori Folium， Gypsum Fibrosum， Ginseng Radix et Rhizoma， Sesami Semen Nigrum， Asini Corii Colla， Ophiopogonis Radix and Eriobotryae Folium are consistent with the 2020 edition of the Chinese Pharmacopoeia. The primary source of Glycyrrhizae Radix et Rhizoma is the dried roots and rhizomes of Glycyrrhiza uralensis， family Leguminosae， while the primary source of Armeniacae Semen Amarum is the dried mature seeds of Prunus armeniaca， family Rosaceae. It is recommended to use Gypsum Ustum， stir-fried Sesami Semen Nigrum， stir-fried Armeniacae Semen Amarum， Asini Corii Colla bead， and honey-fried Eriobotryae Folium， and the rest of the raw products. According to the conversion of ancient and modern doses， the recommended dosages are 11.19 g for Mori Folium， 9.33 g for Gypsum Fibrosum， 3.73 g for Glycyrrhizae Radix et Rhizoma， 2.61 g for Ginseng Radix et Rhizoma， 3.73 g for Sesami Semen Nigrum， 4.48 g for Ophiopogonis Radix， 2.61 g for Armeniacae Semen Amarum， 3.73 g for Eriobotryae Folium. The decoction method is to add 300 mL of water， decoct it down to 180 mL， remove the residue， and then add 2.98 g of Asini Corii Colla into the decoction. Take it warm after meals， two to three times a day. Qingzao Jiufeitang has the effects of clearing dryness and moistening the lungs， nourishing Yin and invigorating Qi. In ancient times， it was mainly used to treat stagnation and depression of various Qi， as well as paralysis， asthma and vomiting. In modern clinical practice， it is mostly used to treat diseases in respiratory system， otolaryngology， skin system and digestive system caused by warm-dry impairing lung， deficiency of both Qi and Yin. The above research results can provide a reference for the later development of Qingzao Jiufeitang.

BACKGROUND: Chronic kidney disease (CKD) is associated with common pathophysiological processes, such as inflammation and fibrosis, in both the heart and the kidney. However, the underlying molecular mechanisms that drive these processes are not yet fully understood. Therefore, this study focused on the molecular mechanism of heart and kidney injury in CKD. METHODS: We generated an microRNA (miR)-26a knockout (KO) mouse model to investigate the role of miR-26a in angiotensin (Ang)-II-induced cardiac and renal injury. We performed Ang-II modeling in wild type (WT) mice and miR-26a KO mice, with six mice in each group. In addition, Ang-II-treated AC16 cells and HK2 cells were used as in vitro models of cardiac and renal injury in the context of CKD. Histological staining, immunohistochemistry, quantitative real-time polymerase chain reaction (PCR), and Western blotting were applied to study the regulation of miR-26a on Ang-II-induced cardiac and renal injury. Immunofluorescence reporter assays were used to detect downstream genes of miR-26a, and immunoprecipitation was employed to identify the interacting protein of LIM and senescent cell antigen-like domain 1 (LIMS1). We also used an adeno-associated virus (AAV) to supplement LIMS1 and explored the specific regulatory mechanism of miR-26a on Ang-II-induced cardiac and renal injury. Dunnett's multiple comparison and t -test were used to analyze the data. RESULTS: Compared with the control mice, miR-26a expression was significantly downregulated in both the kidney and the heart after Ang-II infusion. Our study identified LIMS1 as a novel target gene of miR-26a in both heart and kidney tissues. Downregulation of miR-26a activated the LIMS1/integrin-linked kinase (ILK) signaling pathway in the heart and kidney, which represents a common molecular mechanism underlying inflammation and fibrosis in heart and kidney tissues during CKD. Furthermore, knockout of miR-26a worsened inflammation and fibrosis in the heart and kidney by inhibiting the LIMS1/ILK signaling pathway; on the contrary, supplementation with exogenous miR-26a reversed all these changes. CONCLUSIONS Our findings suggest that miR-26a could be a promising therapeutic target for the treatment of cardiorenal injury in CKD. This is attributed to its ability to regulate the LIMS1/ILK signaling pathway, which represents a common molecular mechanism in both heart and kidney tissues.
Animals ; MicroRNAs/metabolism* ; Angiotensin II/toxicity* ; Mice ; Renal Insufficiency, Chronic/chemically induced* ; Mice, Knockout ; Disease Models, Animal ; Male ; Signal Transduction/genetics* ; LIM Domain Proteins/genetics* ; Mice, Inbred C57BL ; Cell Line ; Humans

"State-target medicine" is a traditional Chinese medicine （TCM） diagnosis and treatment theoretical system proposed by Academician Tong Xiaolin based on the current development of modern medicine. The active stage of gastric ulcer， as a precancerous state of gastric cancer， has a great impact on people's health. Prof. ZHOU Xuewen， a master of TCM， innovatively put forward the theory of "toxicity-heat" etiology for the active stage of gastric ulcer， which plays an important guiding role in clinical diagnosis and treatment. The article took the theoretical system of "state-target medicine" as the framework to explain the rationale， method， formula， and medicine of Prof. ZHOU Xuewen， who applied the Xiaoyong Kuidekang based on the "toxicity-heat" theory to treat the gastric ulcer in the active stage. The Chinese medical name of gastric ulcer， "gastric carbuncle"， was established， and it was believed that gastric ulcer is born due to "toxicity" and is based on "toxicity and heat". In the course of the disease， "toxicity"， "heat"， "deficiency"， and "stasis" coexisted， and its pathogenesis was divided into three phases， namely， toxicity-heat accumulation phase， toxicity-heat affecting the health phase， and weakened body resistance and strengthened toxicity phase. According to the positioning of gastric ulcer as an "internal carbuncle"， Prof. ZHOU Xuewen proposed the treatment of gastric ulcer in the active stage with "carbuncle theory" and introduced the surgical methods of "elimination"， "support"， and "tonifying" into the treatment of gastric ulcer in the active stage. Prof. ZHOU Xuewen took "clearing heat and removing toxins， eliminating carbuncle and generating muscle" as the basic treatment of the disease. For different stages of the disease， Prof. ZHOU Xuewen emphasized the use of the methods of clearing heat and removing toxins， supporting rot and muscle growth， and strengthening the spleen and harmonizing the stomach and created the representative formula for the treatment of gastric ulcer in the active stage with "carbuncle theory"， namely "Xiaoyong Kuidekang"， which could regulate state and targets.

Objective:To evaluate the impact of preemptive analgesia with ibuprofen on postoperative pain following the extraction of impacted mandibular third molars in a Chinese population, aiming to provide a clinical reference for its application.Methods:This multicenter, randomized, double-blind, placebo-controlled parallel-group trial was conducted from April 2022 to October 2023 at the Capital Medical University School of Stomatology (40 cases), Beijing TianTan Hospital, Capital Medical University (22 cases), and Beijing Chao-Yang Hospital, Capital Medical University (20 cases). It included 82 patients with impacted mandibular third molars, with 41 in the ibuprofen group and 41 in the control group. Participants in the ibuprofen group received 300 mg of sustained-release ibuprofen capsules orally 15 min before surgery, while the control group received a placebo. Both groups were instructed to take sustained-release ibuprofen capsules as planned for 3 days post-surgery. Pain intensity was measured using the numerical rating scale at 30 min, 4 h, 6 h, 8 h, 24 h, 48 h, and 72 h after surgery, and the use of additional analgesic medication was recorded during days 4 to 6 postoperatively.Results:All 82 patients completed the study according to the protocol. No adverse events such as nausea, vomiting, or allergies were reported in either group during the trial. The ibuprofen group exhibited significantly lower pain scores at 4 h [2.0 (1.0, 4.0) vs. 4.0 (3.0, 5.0)] ( Z=-3.73, P<0.001), 6 h [2.0 (1.0, 4.0) vs. 5.0(2.5, 6.0)] ( Z=-3.38, P<0.001), and 8 h [2.0 (1.0, 4.0) vs. 5.0 (2.0, 6.0)] ( Z=-2.11, P=0.035) postoperatively compared to the control group. There were no statistically significant differences in pain scores between the groups at 30 min, 24 h, 48 h, and 72 h postoperatively ( P>0.05). Additionally, 11 out of 41 patients (26.8%) in the ibuprofen group and 23 out of 41 patients (56.1%) in the control group required extra analgesic medication between days 4 and 6 post-surgery, with the ibuprofen group taking significantly fewer additional pills [0.0 (0.0, 1.0) vs. 1.0 (0.0, 3.0)] ( Z=-2.81, P=0.005). Conclusions:A pain management regimen involving 300 mg of oral sustained-release ibuprofen capsules administered 15 minutes before surgery and continued for 3 d postoperatively effectively reduces pain levels and the total amount of analgesic medication used after the extraction of impacted mandibular third molars. Considering its efficacy, safety, and cost-effectiveness, ibuprofen is recommended as a first-line drug for perioperative pain management, enhancing patient comfort during diagnosis and treatment in a feasible manner.

Objective:To predict lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer based on preoperative inflammatory and immune nutritional indicators,and to construct a nomo-gram prediction model,providing a basis and tool for preoperative diagnosis of lymph node metastasis in cervical cancer.Methods:A retrospective analysis was conducted on the clinical data of 307 patients preoperatively diag-nosed with early-stage cervical cancer who underwent surgical treatment at the Obstetrics and Gynecology De-partment of the Second Affiliated Hospital of Zhengzhou University from January 2018 to July 2023.R software was used to randomize the groups into a training set(n=231)and a validation set(n=76)in a 3∶1 ratio.Uni-variate and multivariate logistic regression analyses were employed to identify factors influencing lymph node me-tastasis in patients preoperatively diagnosed with early-stage cervical cancer.R software was used to establish a nomogram prediction model and draw receiver operating characteristic(ROC)curves and calibration curves for validation.Results:① The results of univariate logistic regression analysis showed that positive lymphovascular invasion,platelet-to-lymphocyte ratio(PLR)≥151.70,neutrophil-to-white blood cell ratio(NWR)≥0.65,plate-let-to-albumin ratio(PAR)≥ 4.94,preoperative systemic immune-inflammation index(SII)≥604.03,and sys-temic inflammatory response index(SIRI)≥ 1.05 were associated with lymph node metastasis(P＜0.05).②Multivariate logistic regression analysis found that positive lymphovascular invasion,NWR≥0.65,and PAR≥4.94 were independent risk factors for lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer(OR＞1,P＜0.05).③ A nomogram was constructed to predict lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer.The ROC curve shows an area under the train-ing set curve(AUC)of 0.821 and a validation set AUC of 0.858.The calibration curve shows an average abso-lute error of 0.024 for the training set and 0.059 for the validation set.Conclusions:The prediction model for lymph node metastasis in cervical cancer constructed using preoperative inflammatory and immune nutritional indi-cators such as NWR,PAR is helpful for gynecological oncologists to predict lymph node metastasis in cervical cancer patients before surgery.

Objective:To predict lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer based on preoperative inflammatory and immune nutritional indicators,and to construct a nomo-gram prediction model,providing a basis and tool for preoperative diagnosis of lymph node metastasis in cervical cancer.Methods:A retrospective analysis was conducted on the clinical data of 307 patients preoperatively diag-nosed with early-stage cervical cancer who underwent surgical treatment at the Obstetrics and Gynecology De-partment of the Second Affiliated Hospital of Zhengzhou University from January 2018 to July 2023.R software was used to randomize the groups into a training set(n=231)and a validation set(n=76)in a 3∶1 ratio.Uni-variate and multivariate logistic regression analyses were employed to identify factors influencing lymph node me-tastasis in patients preoperatively diagnosed with early-stage cervical cancer.R software was used to establish a nomogram prediction model and draw receiver operating characteristic(ROC)curves and calibration curves for validation.Results:① The results of univariate logistic regression analysis showed that positive lymphovascular invasion,platelet-to-lymphocyte ratio(PLR)≥151.70,neutrophil-to-white blood cell ratio(NWR)≥0.65,plate-let-to-albumin ratio(PAR)≥ 4.94,preoperative systemic immune-inflammation index(SII)≥604.03,and sys-temic inflammatory response index(SIRI)≥ 1.05 were associated with lymph node metastasis(P＜0.05).②Multivariate logistic regression analysis found that positive lymphovascular invasion,NWR≥0.65,and PAR≥4.94 were independent risk factors for lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer(OR＞1,P＜0.05).③ A nomogram was constructed to predict lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer.The ROC curve shows an area under the train-ing set curve(AUC)of 0.821 and a validation set AUC of 0.858.The calibration curve shows an average abso-lute error of 0.024 for the training set and 0.059 for the validation set.Conclusions:The prediction model for lymph node metastasis in cervical cancer constructed using preoperative inflammatory and immune nutritional indi-cators such as NWR,PAR is helpful for gynecological oncologists to predict lymph node metastasis in cervical cancer patients before surgery.

Objective:To predict lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer based on preoperative inflammatory and immune nutritional indicators,and to construct a nomo-gram prediction model,providing a basis and tool for preoperative diagnosis of lymph node metastasis in cervical cancer.Methods:A retrospective analysis was conducted on the clinical data of 307 patients preoperatively diag-nosed with early-stage cervical cancer who underwent surgical treatment at the Obstetrics and Gynecology De-partment of the Second Affiliated Hospital of Zhengzhou University from January 2018 to July 2023.R software was used to randomize the groups into a training set(n=231)and a validation set(n=76)in a 3∶1 ratio.Uni-variate and multivariate logistic regression analyses were employed to identify factors influencing lymph node me-tastasis in patients preoperatively diagnosed with early-stage cervical cancer.R software was used to establish a nomogram prediction model and draw receiver operating characteristic(ROC)curves and calibration curves for validation.Results:① The results of univariate logistic regression analysis showed that positive lymphovascular invasion,platelet-to-lymphocyte ratio(PLR)≥151.70,neutrophil-to-white blood cell ratio(NWR)≥0.65,plate-let-to-albumin ratio(PAR)≥ 4.94,preoperative systemic immune-inflammation index(SII)≥604.03,and sys-temic inflammatory response index(SIRI)≥ 1.05 were associated with lymph node metastasis(P＜0.05).②Multivariate logistic regression analysis found that positive lymphovascular invasion,NWR≥0.65,and PAR≥4.94 were independent risk factors for lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer(OR＞1,P＜0.05).③ A nomogram was constructed to predict lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer.The ROC curve shows an area under the train-ing set curve(AUC)of 0.821 and a validation set AUC of 0.858.The calibration curve shows an average abso-lute error of 0.024 for the training set and 0.059 for the validation set.Conclusions:The prediction model for lymph node metastasis in cervical cancer constructed using preoperative inflammatory and immune nutritional indi-cators such as NWR,PAR is helpful for gynecological oncologists to predict lymph node metastasis in cervical cancer patients before surgery.

Objective:To predict lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer based on preoperative inflammatory and immune nutritional indicators,and to construct a nomo-gram prediction model,providing a basis and tool for preoperative diagnosis of lymph node metastasis in cervical cancer.Methods:A retrospective analysis was conducted on the clinical data of 307 patients preoperatively diag-nosed with early-stage cervical cancer who underwent surgical treatment at the Obstetrics and Gynecology De-partment of the Second Affiliated Hospital of Zhengzhou University from January 2018 to July 2023.R software was used to randomize the groups into a training set(n=231)and a validation set(n=76)in a 3∶1 ratio.Uni-variate and multivariate logistic regression analyses were employed to identify factors influencing lymph node me-tastasis in patients preoperatively diagnosed with early-stage cervical cancer.R software was used to establish a nomogram prediction model and draw receiver operating characteristic(ROC)curves and calibration curves for validation.Results:① The results of univariate logistic regression analysis showed that positive lymphovascular invasion,platelet-to-lymphocyte ratio(PLR)≥151.70,neutrophil-to-white blood cell ratio(NWR)≥0.65,plate-let-to-albumin ratio(PAR)≥ 4.94,preoperative systemic immune-inflammation index(SII)≥604.03,and sys-temic inflammatory response index(SIRI)≥ 1.05 were associated with lymph node metastasis(P＜0.05).②Multivariate logistic regression analysis found that positive lymphovascular invasion,NWR≥0.65,and PAR≥4.94 were independent risk factors for lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer(OR＞1,P＜0.05).③ A nomogram was constructed to predict lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer.The ROC curve shows an area under the train-ing set curve(AUC)of 0.821 and a validation set AUC of 0.858.The calibration curve shows an average abso-lute error of 0.024 for the training set and 0.059 for the validation set.Conclusions:The prediction model for lymph node metastasis in cervical cancer constructed using preoperative inflammatory and immune nutritional indi-cators such as NWR,PAR is helpful for gynecological oncologists to predict lymph node metastasis in cervical cancer patients before surgery.

Objective:To predict lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer based on preoperative inflammatory and immune nutritional indicators,and to construct a nomo-gram prediction model,providing a basis and tool for preoperative diagnosis of lymph node metastasis in cervical cancer.Methods:A retrospective analysis was conducted on the clinical data of 307 patients preoperatively diag-nosed with early-stage cervical cancer who underwent surgical treatment at the Obstetrics and Gynecology De-partment of the Second Affiliated Hospital of Zhengzhou University from January 2018 to July 2023.R software was used to randomize the groups into a training set(n=231)and a validation set(n=76)in a 3∶1 ratio.Uni-variate and multivariate logistic regression analyses were employed to identify factors influencing lymph node me-tastasis in patients preoperatively diagnosed with early-stage cervical cancer.R software was used to establish a nomogram prediction model and draw receiver operating characteristic(ROC)curves and calibration curves for validation.Results:① The results of univariate logistic regression analysis showed that positive lymphovascular invasion,platelet-to-lymphocyte ratio(PLR)≥151.70,neutrophil-to-white blood cell ratio(NWR)≥0.65,plate-let-to-albumin ratio(PAR)≥ 4.94,preoperative systemic immune-inflammation index(SII)≥604.03,and sys-temic inflammatory response index(SIRI)≥ 1.05 were associated with lymph node metastasis(P＜0.05).②Multivariate logistic regression analysis found that positive lymphovascular invasion,NWR≥0.65,and PAR≥4.94 were independent risk factors for lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer(OR＞1,P＜0.05).③ A nomogram was constructed to predict lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer.The ROC curve shows an area under the train-ing set curve(AUC)of 0.821 and a validation set AUC of 0.858.The calibration curve shows an average abso-lute error of 0.024 for the training set and 0.059 for the validation set.Conclusions:The prediction model for lymph node metastasis in cervical cancer constructed using preoperative inflammatory and immune nutritional indi-cators such as NWR,PAR is helpful for gynecological oncologists to predict lymph node metastasis in cervical cancer patients before surgery.

Objective:To predict lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer based on preoperative inflammatory and immune nutritional indicators,and to construct a nomo-gram prediction model,providing a basis and tool for preoperative diagnosis of lymph node metastasis in cervical cancer.Methods:A retrospective analysis was conducted on the clinical data of 307 patients preoperatively diag-nosed with early-stage cervical cancer who underwent surgical treatment at the Obstetrics and Gynecology De-partment of the Second Affiliated Hospital of Zhengzhou University from January 2018 to July 2023.R software was used to randomize the groups into a training set(n=231)and a validation set(n=76)in a 3∶1 ratio.Uni-variate and multivariate logistic regression analyses were employed to identify factors influencing lymph node me-tastasis in patients preoperatively diagnosed with early-stage cervical cancer.R software was used to establish a nomogram prediction model and draw receiver operating characteristic(ROC)curves and calibration curves for validation.Results:① The results of univariate logistic regression analysis showed that positive lymphovascular invasion,platelet-to-lymphocyte ratio(PLR)≥151.70,neutrophil-to-white blood cell ratio(NWR)≥0.65,plate-let-to-albumin ratio(PAR)≥ 4.94,preoperative systemic immune-inflammation index(SII)≥604.03,and sys-temic inflammatory response index(SIRI)≥ 1.05 were associated with lymph node metastasis(P＜0.05).②Multivariate logistic regression analysis found that positive lymphovascular invasion,NWR≥0.65,and PAR≥4.94 were independent risk factors for lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer(OR＞1,P＜0.05).③ A nomogram was constructed to predict lymph node metastasis in patients preoperatively diagnosed with early-stage cervical cancer.The ROC curve shows an area under the train-ing set curve(AUC)of 0.821 and a validation set AUC of 0.858.The calibration curve shows an average abso-lute error of 0.024 for the training set and 0.059 for the validation set.Conclusions:The prediction model for lymph node metastasis in cervical cancer constructed using preoperative inflammatory and immune nutritional indi-cators such as NWR,PAR is helpful for gynecological oncologists to predict lymph node metastasis in cervical cancer patients before surgery.