Medical imaging technology plays a crucial role in clinical diagnosis and treatment. Image compression technology provides robust technical support for the storage and transmission of massive medical imaging data, serving as an effective safeguard for hospital data backup and telemedicine. The technology holds broad application prospects in the medical field, enabling the processing of various imaging modalities, multidimensional imaging, and medical video imaging. This study elaborates on general image and video compression algorithms, the application of compression algorithms in the medical field, and the performance metrics of medical image compression, thereby providing critical technical support for enhancing clinical diagnostic efficiency and data management security.

The biological clock(also known as the circadian rhythm)is the fundamental reliance for all organisms on Earth to adapt and survive in the Earth's rotation environment.Circadian rhythm is the most basic regulatory mechanism of life activities,and plays a key role in maintaining normal physiological and biochemical homeostasis,disease occurrence and treatment.Recent studies have shown that the biologi-cal clock plays an important role in the development of oral tissues and in the occurrence and treatment of oral diseases.Since there is cur-rently no guiding literature on the research methods of biological clock in stomatology,researchers mainly conduct research based on pub-lished references,which has led to controversy about the research methods of biological clock in stomatology,and there are many confusions about how to rationally apply the research methods of circadia rhythms.In view of this,this expert consensus summarizes the characteristics of the biological clock and analyzes the shortcomings of the current biological clock research in stomatology,and organizes relevant experts to summarize and recommend 10 principles as a reference for the rational implementation of the biological clock in stomatology research.

Objective The objective of this study was to explore the differences of serum metabolomics between small cell lung cancer(SCLC)patients and healthy volunteers,and to discover serum potential biomarkers for identification and small cell lung cancer staging. Methods Ultra-performance liquid chromatography time of flight mass spectrometry(UPLS-TOF/MS)was used to establish the serum metabolic profile of SCLC. Principal Component Analysis(PCA)and orthogonal hidden variables were analyzed by the EZinfo2. 0 software. Orthogonal Partial Least Squares Discriminant Analysis(OPLS-DA)was used to analyze the metabolic differ-ences between the case and normal control groups. Through cluster analysis using HMDB and METLIN database to search for the exact mass-to-charge ratio of the difference,preliminary identification of some substances with significant differences was carried out. Results Ten differential metabolites such as lysophosphatidylcholine between patients and control groups were screened and identi-fied by mass spectrometry and database search. There were 10 different metabolites such as glycocholic acid in the contour analysis of SCLC patients with different stages. Conclusion There is a significant difference in serum metabolism between SCLC patients and healthy controls. The discovery of differential metabolites provides experimental evidence for the identification of small cell lung cancer and potential markers of staging.