Psychological factors have become significant contributors to the onset and progression of insomnia. This article explored the treatment of insomnia from the perspective of “liver governs wei qi （defensive qi）”. The concept of “liver governs wei qi （defensive qi）” is summarized in three aspects， firstly， the liver assists the spleen and stomach in transformation and transportation， governing the generation of wei qi； secondly， the liver aids lung qi diffusion and dispersion， governing the distribution of wei qi； thirdly， the liver regulates circadian rhythms， governing the circulation of wei qi. It is proposed that the clinical treatment of insomnia should focus on the following methods： for regulating the liver to harmonize the five viscera， and facilitate the circulation of wei qi， medicinals entering the liver channel include Chaihu （Bupleuri radix）， Baishao （Paeoniae Radix Alba）， Zhizi （Gardeniae Fructus）， and Suanzaoren （Ziziphi Spinosae Semen） could be commonly used； for nourishing the liver， the treatment should align with the day-night rhythm， and herbs such as Baihe （Lilium）， Hehuan （Albizia julibrissin）， and Yejiaoteng （Polygoni multiflori caulis） are commonly used； for soothing the liver and address both mental and physical health to calm wei qi， treatment should advocate verbal counseling， psychological regulation， and health education. Ultimately， this treatment approach can free liver qi to flow， soothe qi movement， restore the motion of wei qi， regulate during day and night， balance yin and yang， and resolve insomnia effectively.

BACKGROUND: Lung cancer is one of the most common malignant tumors in the world. The accuracy of intraoperative frozen section (FS) in the diagnosis of lung adenocarcinoma infiltration cannot fully meet the clinical needs. The aim of this study is to explore the possibility of improving the diagnostic efficiency of FS in lung adenocarcinoma by using the original multi-spectral intelligent analyzer. METHODS: Patients with pulmonary nodules who underwent surgery in the Department of Thoracic Surgery, Beijing Friendship Hospital, Capital Medical University from January 2021 to December 2022 were included in the study. The multispectral information of pulmonary nodule tissues and surrounding normal tissues were collected. A neural network model was established and the accuracy of the neural network diagnostic model was verified clinically. RESULTS: A total of 223 samples were collected in this study, 156 samples of primary lung adenocarcinoma were finally included, and a total of 1,560 sets of multispectral data were collected. The area under the curve (AUC) of spectral diagnosis in the test set (10% of the first 116 cases) of the neural network model was 0.955 (95%CI: 0.909-1.000, P<0.05), and the diagnostic accuracy was 95.69%. In the clinical validation group (the last 40 cases), the accuracy of spectral diagnosis and FS diagnosis were both 67.50% (27/40), and the AUC of the combination of the two was 0.949 (95%CI: 0.878-1.000, P<0.05), and the accuracy was 95.00% (38/40). CONCLUSIONS The accuracy of the original multi-spectral intelligent analyzer in the diagnosis of lung invasive adenocarcinoma and non-invasive adenocarcinoma is equivalent to that of FS. The application of the original multi-spectral intelligent analyzer in the diagnosis of FS can improve the diagnostic accuracy and reduce the complexity of intraoperative lung cancer surgery plan.
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Humans ; Lung Neoplasms/surgery* ; Adenocarcinoma of Lung/surgery* ; Adenocarcinoma/surgery* ; Hospitals ; Multiple Pulmonary Nodules