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*

Traumatic supraorbital fissure syndrome (TSOFS) is a symptom complex caused by nerve entrapment in the supraorbital fissure after skull base trauma. If the compressed cranial nerve in the supraorbital fissure is not decompressed surgically, ptosis, diplopia and eye movement disorder may exist for a long time and seriously affect the patients′ quality of life. Since its overall incidence is not high, it is not familiarized with the majority of neurosurgeons and some TSOFS may be complicated with skull base vascular injury. If the supraorbital fissure surgery is performed without treatment of vascular injury, it may cause massive hemorrhage, and disability and even life-threatening in severe cases. At present, there is no consensus or guideline on the diagnosis and treatment of TSOFS that can be referred to both domestically and internationally. To improve the understanding of TSOFS among clinical physicians and establish standardized diagnosis and treatment plans, the Skull Base Trauma Group of the Neurorepair Professional Committee of the Chinese Medical Doctor Association, Neurotrauma Group of the Neurosurgery Branch of the Chinese Medical Association, Neurotrauma Group of the Traumatology Branch of the Chinese Medical Association, and Editorial Committee of Chinese Journal of Trauma organized relevant experts to formulate Chinese expert consensus on the diagnosis and treatment of traumatic supraorbital fissure syndrome ( version 2024) based on evidence of evidence-based medicine and clinical experience of diagnosis and treatment. This consensus puts forward 12 recommendations on the diagnosis, classification, treatment, efficacy evaluation and follow-up of TSOFS, aiming to provide references for neurosurgeons from hospitals of all levels to standardize the diagnosis and treatment of TSOFS.

Mice ; Animals ; Humans ; Disease Models, Animal

Objective:To study the distribution and antibiotics resistance of the main pathogens of neonatal purulent meningitis in different regions of China.Methods:A retrospective descriptive clinical epidemiological study was conducted in children with neonatal purulent meningitis which admitted to 18 tertiary hospitals in different regions of China between January 2015 to December 2019. The test results of blood and cerebrospinal fluid, and drug sensitivity test results of the main pathogens were collected. The distributions of pathogenic bacteria in children with neonatal purulent meningitis in preterm and term infants, early and late onset infants, in Zhejiang Province and other regions outside Zhejiang Province, and in Wenzhou region and other regions of Zhejiang Province were analyzed. The chi-square test was used for statistical analysis.Results:A total of 210 neonatal purulent meningitis cases were collected. The common pathogens were Escherichia coli ( E. coli)(41.4%(87/210)) and Streptococcus agalactiae ( S. agalactiae)(27.1%(57/210)). The proportion of Gram-negative bacteria in preterm infants (77.6%(45/58)) with neonatal purulent meningitis was higher than that in term infants (47.4%(72/152)), and the difference was statistically significant ( χ2=15.54, P=0.001). There were no significant differences in the constituent ratios of E. coli (36.5%(31/85) vs 44.8%(56/125)) and S. agalactiae (24.7%(21/85) vs 28.8%(36/125)) between early onset and late onset cases (both P>0.05). The most common pathogen was E. coli in different regions, with 46.7%(64/137) in Zhejiang Province and 31.5%(23/73) in other regions outside Zhejiang Province. In Zhejiang Province, S. agalactiae was detected in 49 out of 137 cases (35.8%), which was significantly higher than other regions outside Zhejiang Province (11.0%(8/73)). The proportions of Klebsiella pneumoniae, and coagulase-negative Staphylococcus in other regions outside Zhejiang Province (17.8%(13/73) and 16.4%(12/73)) were both higher than those in Zhejiang Province (2.9%(4/137) and 5.1%(7/137)). The differences were all statistically significant ( χ2=14.82, 12.26 and 7.43, respectively, all P<0.05). The proportion of Gram-positive bacteria in Wenzhou City (60.8%(31/51)) was higher than that in other regions in Zhejiang Province (38.4%(33/86)), and the difference was statistically significant ( χ2=6.46, P=0.011). E. coli was sensitive to meropenem (0/45), and 74.4%(32/43) of them were resistant to ampicillin. E. coli had different degrees of resistance to other common cephalosporins, among which, cefotaxime had the highest resistance rate of 41.8%(23/55), followed by ceftriaxone (32.4%(23/71)). S. agalactiae was sensitive to penicillin, vancomycin and linezolid. Conclusions:The composition ratios of pathogenic bacteria of neonatal purulent meningitis are different in different regions of China. The most common pathogen is E. coli, which is sensitive to meropenem, while it has different degrees of resistance to other common cephalosporins, especially to cefotaxime.

Adipose tissue is a promising target for treating obesity and metabolic diseases. However, pharmacological agents usually fail to effectively engage adipocytes due to their extraordinarily large size and insufficient vascularization, especially in obese subjects. We have previously shown that during cold exposure, connexin43 (Cx43) gap junctions are induced and activated to connect neighboring adipocytes to share limited sympathetic neuronal input amongst multiple cells. We reason the same mechanism may be leveraged to improve the efficacy of various pharmacological agents that target adipose tissue. Using an adipose tissue-specific Cx43 overexpression mouse model, we demonstrate effectiveness in connecting adipocytes to augment metabolic efficacy of the β ₃-adrenergic receptor agonist Mirabegron and FGF21. Additionally, combing those molecules with the Cx43 gap junction channel activator danegaptide shows a similar enhanced efficacy. In light of these findings, we propose a model in which connecting adipocytes via Cx43 gap junction channels primes adipose tissue to pharmacological agents designed to engage it. Thus, Cx43 gap junction activators hold great potential for combination with additional agents targeting adipose tissue.

Objective::To discover a small molecule active ingredient of traditional Chinese medicine (TCM) with the inhibitory activity of histone deacetylase (HDAC) 3/8. Method::The molecular docking technique was performed by AutoDock 4.2.6 software. Trichostatin A (TSA) was used as a reference to screen 19 small molecular components from TCM, and the default docking conformation number was set to obtain the docking binding energy, active site amino acid residues and hydrogen bonds, and the biological activity was verified. Result::The binding energies of 19 small molecule components from TCM to HDAC3 and HDAC8 were different. Among them, ursolic acid, fangchinoline and tetrandrine have low binding energies to HDAC3 and HDAC8, and their binding activities were strong. The optimal binding energy of fangchinoline and HDAC3 at the site 1 was the lowest (-26.71 kJ·mol^-1), and that of HDAC8 at the site 9 was the lowest (-26.84 kJ·mol^-1). The optimal binding energy of tetrandrine and HDAC3 at the site 13 was the lowest (-26.38 kJ·mol^-1), and that of HDAC8 at the site 12 was the lowest (-25.41 kJ·mol^-1). In addition, the binding energy of ursolic acid and HDAC3 at the site 16 was the lowest (-25.83 kJ·mol^-1), and that of HDAC8 at the site 8 was the lowest (-35.62 kJ·mol^-1). Three kinds of amino acids at the docking site of small molecules were rendered by PyMOL 2.3.1.When ursolic acid was combined with HDAC3/8, the active sites produced two hydrogen bonds, and the interaction was strong, and many amino acids were connected at the active site. The fangchinoline formed two hydrogen bonds with the active site of HDAC3 and one hydrogen bond with the active site of HDAC8, and hydrophobic binding with some active site amino acids. There was no hydrogen bond between tetrandrine and HDAC3/8, and all docking sites were docked by 4 active amino acids. Three small molecules (ursolic acid, fangchinoline and tetrandrine) with the best docking effect had the inhibitory activity against HDAC3/8 at the concentration of 500 μmol·L^-1 and 100 μmol·L^-1, and the inhibitory activity was still optimal among the 10 selected small molecules. Conclusion::Among the screened 19 small molecules, ursolic acid, tetrandrine and fangchinoline may be the new anti-inflammatory drugs of HDAC3/8 inhibitory target, which provides a reference for further exploration and discovery of new anti-inflammatory drugs.