Recent advances in large models demonstrate significant prospects for transforming the field of medical imaging. These models, including large language models, large visual models, and multimodal large models, offer unprecedented capabilities in processing and interpreting complex medical data across various imaging modalities. By leveraging self-supervised pretraining on vast unlabeled datasets, cross-modal representation learning, and domain-specific medical knowledge adaptation through fine-tuning, large models can achieve higher diagnostic accuracy and more efficient workflows for key clinical tasks. This review summarizes the concepts, methods, and progress of large models in medical imaging, highlighting their potential in precision medicine. The article first outlines the integration of multimodal data under large model technologies, approaches for training large models with medical datasets, and the need for robust evaluation metrics. It then explores how large models can revolutionize applications in critical tasks such as image segmentation, disease diagnosis, personalized treatment strategies, and real-time interactive systems, thus pushing the boundaries of traditional imaging analysis. Despite their potential, the practical implementation of large models in medical imaging faces notable challenges, including the scarcity of high-quality medical data, the need for optimized perception of imaging phenotypes, safety considerations, and seamless integration with existing clinical workflows and equipment. As research progresses, the development of more efficient, interpretable, and generalizable models will be critical to ensuring their reliable deployment across diverse clinical environments. This review aims to provide insights into the current state of the field and provide directions for future research to facilitate the broader adoption of large models in clinical practice.
Humans ; Diagnostic Imaging/methods* ; Precision Medicine/methods* ; Image Processing, Computer-Assisted/methods*

Objective:To summarized the clinical characteristics and surgical management of anterior cervical enterogenic in pediatric patients. Methods:Clinical data were retrospectively analyzed for 9 children with pathologically confirmed anterior cervical enterogenic cysts（including bronchogenic and esophagogenic subtypes） treated at the Children's Hospital of Shandong University（Jinan Children's Hospital） between January 1, 2020, and November 30, 2023. Results:Nine patients（6 males and 3 females） were involved in this study, aged 14 days to 10 years old. There were 4 cases on the left side, 4 on the right side, and 1 in the middle of the neck. All patients presented with neck masses. The patients were followed up from 3 months to 35 months after surgery and recovered well, with no recurrence or complications observed. Conclusion:①Anterior intestinal cysts in children are rare and easy to be misdiagnosed. ②Concurrent branchial cleft fistulas or associated anomalies may coexist, necessitating comprehensive evaluation. ③Preoperative diagnosis is not easy and mainly depends on pathological diagnosis. ④The treatment of anterior cervical enterogenic cysts in children is surgical resection of the lesion.
Humans ; Male ; Female ; Child ; Retrospective Studies ; Child, Preschool ; Infant ; Neck ; Cysts/surgery*

Objective: To establish a progressive research strategy for “colonic components analysis - efficacy verification and mechanism exploration - gut microbiota”, screen pharmacodynamic substances, and investigate their mechanism via gut microbiota. Methods: The pharmacodynamics of Gegen Qinlian decoction (GQD) were assessed using a mouse model of dextran sulfate sodium-induced ulcerative colitis (UC). Ultra-performance liquid chromatography-quadrupole-orbitrap mass spectrometer was used to identify the prototype and metabolic components of GQD in the colon during UC. To analyze the structure and function of characteristic genera of GQD and its active components, 16S rRNA sequencing was performed. Results: We identified 67 prototypic and 14 metabolic components of GQD in the UC colon. The primary prototype components are flavonoids and alkaloids, including puerarin (PUE), baicalin (BAI), and berberine (BER). The metabolism was predominantly sulfonation. Efficacy verification showed that the main active components, puerarin, baicalin, and berberine, had good therapeutic effects on UC. The results of 16S rRNA gene sequencing showed that GQD improved UC by regulating the structure and function of the gut microbiota. The abundance of gut microbiota involved in the metabolism of the prototype components was influenced by the corresponding components. The function prediction results showed that PUE was the most comparable to GQD, with 24 consistent pathways. BAI and BER showed comparable gut microbiota regulation pathways. Characteristic pathways of BER include glucometabolic processes. Conclusion This study focused on the key issues in the gut microbiota pathway and developed a progressive research strategy to understand the transformation mechanisms of colonic components. This research systematically analyzed the active components and metabolic transformation of GQD in the colon during the pathological state of UC, as well as changes in the structure and function of the gut microbiota, clarified the mechanism of GQD and its active components in improving UC via the gut microbiota pathway.

Objective To investigate the role and mechanism of exosomes derived from mesenchymal stem cells in hyperbaric oxygen caused pulmonary oxygen toxicity.Methods Mice were divided into the control group that was exposed to normal air,and hyperbaric oxygen exposure groups treated with phosphate buffer saline(PBS)or exosomes,respectively.PBS and exosome treatment were given one day prior to exposure.Mice were subjected to 0.23 MPa pure oxygen for 8 hours.The lung wet-dry ratio,inflammation,exudation and pathological injury were analyzed,while cell death and antioxidant related molecules were detected.Results Pretreatment with exosome significantly attenuated lung injury caused by hyperbaric oxygen exposure by decreasing the lung wet-dry ratio,inflammation,and cell apoptosis.Conclusion Prophylactic administration of exosomes derived from mesenchymal stem cells can alleviate hyperbaric oxygen induced pulmonary oxygen poisoning by attenuating cell death and inflammation.

Objective To systematically evaluate the efficacy and safety of ciprofol for sedation and anesthesia outside the operating room.Methods Databases such as PubMed,Embase,Cochrane Library,Web of Science,CNKI,Wanfang Data,CBM,and VIP were searched for randomized controlled trials(RCTs)related to the efficacy and safety of ciprofol for sedation and anesthesia outside the operating room.The search covered all publications up to June 2023.Statistical analysis was performed using RevMan 5.4 software and Stata 15.0.Results Twelve RCTs were included,involving 2 192 patients,of which 1 154 were in the ciprofol group and 1 038 in the propofol group.Compared with the propofol group,the anesthesia induction time(MD=0.28 min,95％CI 0.08-0.47 min,P=0.006)and recovery time(MD=1.16 min,95％CI 0.44-1.87 min,P=0.001)were significantly longer in the ciprofol group,and the inci-dences of injection pain(OR=0.04,95％CI 0.02-0.06,P＜0.001),hypotension(OR=0.64,95％CI 0.49-0.83,P=0.0008),hypoxemia(OR=0.44,95％CI 0.21-0.91,P=0.03),and respirato-ry depression(OR=0.19,95％CI 0.11-0.32,P＜0.001)were significantly lower.There were no sta-tistically significant differences between the two groups in terms of sedation success rate,physician satisfac-tion,the difference in heart rate before and after anesthesia induction,incidence of body movement,brady-cardia,nausea and vomiting,and dizziness.Conclusion The anesthetic effect of cyclopofol and propofol is similar when used for anesthesia outside the operating room.Compared to propofol,ciprofol offers comparable anesthetic effects for sedation and anesthesia outside the operating room,with a lesser impact on respiratory function and more stable hemodynamics.Ciprofol also significantly lowers the incidence of adverse reactions such as injection pain,hypotension,hypoxemia,and respiratory depression.

Helicobacter pylori (Hp) is a unipolar, microaerobic, multiflagellar, spiral-shaped Gram-negative bacterium that survives and colonizes human gastric mucosa. As a classⅠcarcinogen associated with gastric cancer, long-term stimulation of gastric mucosa by Hp can cause atrophic gastritis, peptic ulcer, gastric cancer and gastric mucosa-associated lymphoid tissue lymphoma. It has been reported that Hp can cause epithelial-mesenchymal transition (EMT) in gastric epithelial cells, thereby inducing gastric cancer. We review the mechanism of Hp-induced EMT in gastric epithelial cells, in order to provide new insights for early diagnosis and targeted therapy of gastric cancer.

Objective To explore the feasibility of automatic segmentation of clinical target volume(CTV)and organs at risk(OARs)for cervical cancer using AccuLearning(AL)based on geometric and dosimetric indices.Methods Seventy-five CT localization images with manual contouring data of postoperative cervical cancer were enrolled in this study.Sixty cases were randomly selected to trained to generate automatic segmentation model by AL,and the CTV and OARs of the remaining 15 cases were automatically contoured.Radiotherapy plans on the automatic segmentation contours were imported on the CT images of manual contours.The efficiency,Dice similarity coefficient(DSC),Hausdorff distance(HD)and dosimetric parameters were compared between the two methods.Results The time of automatic segmentation was significantly shorter than that of the manual contour(P<0.05).The DSC of all structures were≥0.87.The HD of bowel bag and rectum were about 10 mm,and that of the rest of OARs were less than 5 mm.CTV(D98,V90% ,V95% ,Dmean,HI),bowel bag(V50)and bladder(V50)had significant differences in dosimetric comparison(P<0.05).Conclusion The automatic segmentation model based on AL can improve the efficiency of radiotherapy.Automatic segmentation of OARs has the potential of clinical application,while that of CTV still needs to be further modified.

Objective: The aim of the present study was to develop the beverage addiction scale for college students,so as to provide an effective tool for assessing college students beverage addiction. Methods: In November 2022, a cluster sample of 8 792 college students from three colleges in Yunnan and Jiangxi were surveyed by Beverage Addication Scale for College Students. After a through literature review, 12 items were proposed, including withdrawal symptoms, health effects and addiction symptoms, with 4 items each. The ttest and correlation analysis were used to filter the items, and exploratory factor analysis and confirmatory factor analysis were used to evaluate the structural validity of the questionnaire. In May 2023, 5 279 college students from the above three universities were surveyed again to evaluate the reliability and validity of the scale and the positive demarcation value of symptoms. Results: The scale fitted into a tool for measuring symptoms of beverage dependence in a college student population. The scale was composed of 11 items in accordance with withdrawal symptoms, health effects and addiction symptoms, with a cumulative contribution rate of variance was 74.51%. Cronbach α coefficients for the overall scale and three dimensions were 0.94, 0.88, 0.90 and 0.92, respectively. The correlation coefficient between each item and the total score ranged from 0.56 to 0.79, and the correlation coefficient with the dimension ranged from 0.71 to 0.92. The confirmatory factor analysis model was well fitted, and the RMSEA, CFI, TLI and SRMR value were 0.06, 0.95, 0.93 and 0.04, respectively. The application of the scale showed that scores on the scale and each dimension ≥P85 were positive for symptoms. Conclusion The reliability and validity of Beverage Addiction Scale for College Students is good, which can be used to evaluate the beverage addiction symptom of college students.

The research focus of diabetes, a common chronic metabolic disease, has shifted from individual factors to environmental factors at the population level. Epidemiological studies suggest an association between exposure to environmental pollutants and the risk of diabetes. Major environmental pollutants include organochlorine pesticides, polychlorinated biphenyls, phthalates and their metabolites, and arsenics, which primarily enter the human body through the skin, respiratory tract, and digestive system. Long-term exposure to these pollutants can affect the pathology of diabetes through various mechanisms, such as promoting insulin resistance, causing insulin secretion deficiencies, inducing oxidative stress-induced glucose metabolism disorders, and affecting DNA methylation. However, the potential damaging mechanism of the impact of environmental pollutants on diabetes remain unclear. Limitations such as insufficient sample sizes, uncertainties regarding exposure time and dosage, and differences between single and co-exposures. In the future, it is necessary to focus on exploring and analyzing the mechanisms of environmental pollutant exposure on diabetes to develop effective prevention strategies, control and reduce the incidence and development of diabetes, and provide new insights into its diagnosis and treatment.

Objective: To explore the association between processed food consumption and anxiety symptoms among college students in Yunnan Province, so as to provide a reference for the prevention and treatment of anxiety symptoms in this population. Methods: A cluster random sample of 2 515 first year students from two universities in Yunnan Province was selected to carry out a longitudinal investigation which included a baseline survey (November 2021, T1) and three follow up visits (June 2022, T2; November 2022, T3; June 2023, T4). The food frequency questionnaire was administered to assess processed food consumption, and the Depression Anxiety Stress Scale-21 (DASS-21, Chinese version) was used to evaluate anxiety symptoms. A generalized estimation equation model was used to analyze the relationship between processed food consumption and anxiety symptoms. Results: The detection rates of T1-T4 anxiety symptoms among college students in Yunnan Province were 29.70%, 36.70%, 37.69% and 38.73 %, respectively, and the corresponding anxiety symptom scores were 4(0,8), 4(0,10), 4(0,12), 2(0,14). After controlling for demographic variables and confounding factors in the generalized estimation equation model, a statistically significant association was found between consumption of carbonated beverages ( β=0.06, 95%CI =0.03-0.08), and other processed snacks ( β= 0.04 , 95%CI =0.01-0.07) ( P <0.05). The stratified analysis by gender showed that the consumption of carbonated beverages ( β=0.08, 95%CI =0.05-0.12) and fast food ( β=0.03, 95%CI =0.00-0.06) was significantly associated with anxiety symptoms in female college students ( P <0.05). There was no significant association between processed food consumption and anxiety symptoms in male college students ( P >0.05). Conclusions Processed food consumption by college students in Yunnan Province may increase the risk of anxiety symptoms, particularly among female students. There is a need to strengthen guidance in respect to processed food consumption, so as to prevent and treat anxiety symptoms.