This paper summarizes Professor LIU Fengbin's clinical experience in treating autoimmune liver disease （AILD） using the method of nourishing yin and removing stasis based on stage differentiation. He believes that the pathogenesis of AILD generally involves both deficiency in essence and excess in manifestation， with essence deficiency often presenting as liver and kidney yin deficiency， which may progress to spleen deficiency and yang deficiency over time. The excess manifestation commonly includes qi stagnation， blood stasis， damp-heat， and phlegm toxicity. Clinically， he advocates for the treatment principle of nourishing yin and removing stasis. On the foundation of nourishing liver and kidney yin， different pathological factors causing stasis are eliminated according to their nature. Treatment is also tailored to different stages of AILD. In the early and asymptomatic stages， liver qi stagnation and spleen deficiency are prominent， warranting a therapeutic approach of soothing the liver， regulating qi and strengthening the spleen. The modified Chaishao Qizhi Decoction （柴芍气滞汤） is used. During the symptomatic stage， pathogenic factors become more pronounced， often accompanied by a significant deficiency of vital qi， with damp-heat， water retention， and phlegm toxicity as key pathological features. The treatment should focus on strengthening the spleen and dispelling dampness， using modified Sijunzi Decoction （四君子汤） combined with Yinchen Wuling Powder （茵陈五苓散）. In the liver function decompensation stage， vital qi is severely deficient while pathogenic factors persist， with damp-heat， phlegm toxicity， and blood stasis obstructing the liver collaterals. Treatment should focus on nourishing blood， softening the liver， strengthening the spleen， and resolving stasis， using the modified Ruangan Yangxue Decoction （软肝养血汤）. Throughout the treatment process， emphasis is placed on tonifying the liver and kidneys while protecting yin fluids.

Objective:To analyze the screening results of the Urban Cancer Early Diagnosis and Treatment Project in Qinghai Province from 2019 to 2024.Methods:A summary and statistical analysis were conducted on six years of screening data from the Urban Cancer Early Dia-gnosis and Treatment Program in Qinghai Province,with the high-risk rate,screening rate,and detection rate calculated separately for each type of cancer.Results:From 2019 to 2024,56,882 high-risk individuals were identified.The high-risk rates for lung,colorectal,breast,up-per gastrointestinal,and liver cancer were 22.02%,21.57%,14.23%,13.52%,and 6.10%,respectively.Overall,13,592 individuals com-pleted clinical screening,with detection rates of 0.32%for lung cancer,0.41%for liver cancer,0.08%for precancerous gastric lesions,3.63%for precancerous colorectal lesions,0.08%for esophageal cancer,0.16%for gastric cancer,and 0.14%for colorectal cancer.Conclusions:The implementation of the Urban Cancer Early Diagnosis and Treatment Program in Qinghai Province aids in the early detection of cancer,improves early diagnosis and survival rates,and reduces mortality.Nevertheless,due to low public awareness and limited participation,en-hancements in program management and public outreach are required.

Objective:To evaluate the diagnostic performance of artificial intelligence-assisted diagnostic systems in cervical cytopathological examination.Methods:Cervical cytology slide data were retrospectively collected from four hospitals for the external validation of the developed artificial intelligence-assisted diagnostic system. Subsequently, prospective data collection was conducted for human-machine assisted studies.Results:In the retrospective study, a total of 3 162 valid samples were collected as external validation data. The system showed an area under the curve (AUC) of 0.890 (95% CI: 0.878-0.902), accuracy of 0.885 (95% CI: 0.873-0.896), sensitivity of 0.928 (95% CI: 0.914-0.941), and specificity of 0.852 (95% CI: 0.834-0.867). In the prospective study, 212 valid samples were collected, and five junior cytologists participated in the human-machine assisted study. Without artificial intelligence assistance, the average AUC for the five cytologists was 0.686 (95% CI: 0.650-0.722), the accuracy was 0.699 (95% CI: 0.671-0.727), the sensitivity was 0.653 (95% CI: 0.599-0.703), the specificity was 0.719 (95% CI: 0.685-0.750), the Fleiss κ value was 0.510, and the reading time was 223 seconds. With artificial intelligence assistance, the AUC, accuracy, sensitivity, and specificity increased by 0.166, 0.143, 0.225, and 0.107, respectively. Additionally, Fleiss κ was 0.730 and the reading time decreased by 188 seconds. All differences were statistically significant (all P<0.001). Conclusions:Artificial intelligence-assisted diagnosis system shows excellent performance and good generalizability, significantly improving the diagnostic accuracy, consistency, and efficiency of junior cytologists. It can be an effective auxiliary tool for junior cytologists in clinical practice.

Idiopathic pulmonary fibrosis （IPF） is a chronic interstitial lung disease characterized by dyspnea and progressive deterioration of lung function， which significantly impacts patients' quality of life and imposes a major burden on society. Although modern medicine has increasingly enriched the treatment options for pulmonary fibrosis， unfavorable factors such as high costs and significant side effects contribute to the persistently low survival rate of patients. Studies have shown that the occurrence and development of pulmonary fibrosis are closely related to abnormalities in multiple pathways. Among these， Rho/Rho-associated coiled-coil protein kinase （ROCK） plays a key role in the disease progression of IPF by regulating the cytoskeleton. This pathway not only transmits biochemical molecular signals that promote the progress of fibrosis but also responds to the biomechanical environment， such as the increased lung tissue stiffness caused by the deposition of extracellular matrix （ECM） during the process of pulmonary fibrosis. Therefore， research on this pathway is of great significance for the prevention and treatment of IPF. In recent years， traditional Chinese medicine （TCM） has shown remarkable effects in preventing and treating IPF. Many TCM compounds and active components can reduce the production of α-smooth muscle actin （α-SMA）， CollagenⅠ （ColⅠ）， ColⅢ， and inflammatory factors in lung tissue by regulating the Rho/ROCK signaling pathway. These compounds inhibit the transformation of fibroblasts （FBs） into myofibroblasts （MyoFBs）， intervening in the process of pulmonary fibrosis. Based on this， the article briefly reviews relevant research from recent years， discusses the key role of the Rho/ROCK pathway in pulmonary fibrosis from an interdisciplinary perspective， and summarizes the mechanisms through which TCM regulates Rho/ROCK to prevent and treat IPF， based on resources from PubMed， CNKI， and other databases， in order to provide important references for the broader clinical application of TCM in the prevention and treatment of IPF.

Objective:To evaluate the diagnostic performance of artificial intelligence-assisted diagnostic systems in cervical cytopathological examination.Methods:Cervical cytology slide data were retrospectively collected from four hospitals for the external validation of the developed artificial intelligence-assisted diagnostic system. Subsequently, prospective data collection was conducted for human-machine assisted studies.Results:In the retrospective study, a total of 3 162 valid samples were collected as external validation data. The system showed an area under the curve (AUC) of 0.890 (95% CI: 0.878-0.902), accuracy of 0.885 (95% CI: 0.873-0.896), sensitivity of 0.928 (95% CI: 0.914-0.941), and specificity of 0.852 (95% CI: 0.834-0.867). In the prospective study, 212 valid samples were collected, and five junior cytologists participated in the human-machine assisted study. Without artificial intelligence assistance, the average AUC for the five cytologists was 0.686 (95% CI: 0.650-0.722), the accuracy was 0.699 (95% CI: 0.671-0.727), the sensitivity was 0.653 (95% CI: 0.599-0.703), the specificity was 0.719 (95% CI: 0.685-0.750), the Fleiss κ value was 0.510, and the reading time was 223 seconds. With artificial intelligence assistance, the AUC, accuracy, sensitivity, and specificity increased by 0.166, 0.143, 0.225, and 0.107, respectively. Additionally, Fleiss κ was 0.730 and the reading time decreased by 188 seconds. All differences were statistically significant (all P<0.001). Conclusions:Artificial intelligence-assisted diagnosis system shows excellent performance and good generalizability, significantly improving the diagnostic accuracy, consistency, and efficiency of junior cytologists. It can be an effective auxiliary tool for junior cytologists in clinical practice.

Objective:To analyze the screening results of the Urban Cancer Early Diagnosis and Treatment Project in Qinghai Province from 2019 to 2024.Methods:A summary and statistical analysis were conducted on six years of screening data from the Urban Cancer Early Dia-gnosis and Treatment Program in Qinghai Province,with the high-risk rate,screening rate,and detection rate calculated separately for each type of cancer.Results:From 2019 to 2024,56,882 high-risk individuals were identified.The high-risk rates for lung,colorectal,breast,up-per gastrointestinal,and liver cancer were 22.02%,21.57%,14.23%,13.52%,and 6.10%,respectively.Overall,13,592 individuals com-pleted clinical screening,with detection rates of 0.32%for lung cancer,0.41%for liver cancer,0.08%for precancerous gastric lesions,3.63%for precancerous colorectal lesions,0.08%for esophageal cancer,0.16%for gastric cancer,and 0.14%for colorectal cancer.Conclusions:The implementation of the Urban Cancer Early Diagnosis and Treatment Program in Qinghai Province aids in the early detection of cancer,improves early diagnosis and survival rates,and reduces mortality.Nevertheless,due to low public awareness and limited participation,en-hancements in program management and public outreach are required.

Two new neolignans and one new lignan (1-3) were obtained from the roots of Paeonia lactiflora. Their structures were unambiguously elucidated based on extensive spectroscopic analysis, single-crystal X-ray crystallography, and the calculated and experimental electronic circular dichroism (ECD) spectra. Compound 1 was a racemic mixture and successfully resolved into the anticipated enantiomers via chiral-phase HPLC. Compound 3 demonstrated moderate inhibitory activity against human carboxylesterase 2A1 (hCES2A1) with an IC₅₀ value of 7.28 ± 0.94 μmol·^-1.
Chromatography, High Pressure Liquid ; Humans ; Lignans/chemistry* ; Paeonia ; Plant Roots/chemistry* ; Stereoisomerism

Objective To investigate the correlation between the quality of life and joint health status of adult hemophilia patients. Methods Forty-nine adult hemophilia patients were selected.The quality of life and joint health status of patients were evaluated by hemophilia-specific health related quality of life questionnaire for adults (Hemo-QOL-A) and hemophilia joint health score (HJHS). Results The Hemo-QOL-A score of adult hemophilia patients was (39.34 ± 18.97) scores, and HJHS score was(33.16 ± 13.17)scores.The Pearson correlation analysis result showed that Hemo-QOL-A score was positively related with HJHS score (r = 0.490, P<0.05), and Hemo-QOL-A score was positively correlated with muscular condition,joint activity and joint friction sound score of HJHS score(r=0.469, 0.396 and 0.290; P<0.05). Hemo-QOL-A score was not correlated with swelling, swelling duration, arthralgia and gait of HJHS score (P>0.05). In 294 joints of 49 patients, the total abnormal rate of the joint was 82.7%(243/294),the abnormal rate of the elbow joint was 72.4%(71/98),the abnormal rate of the knee joint was 90.8%(89/98),and the abnormal rate of ankle joint was 84.7%(83/98).Conclusions Decreased joint health status, mainly including the surrounding muscle condition and joint mobility, results in lower quality of life in patients with hemophilia.