With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.

Nicotine addiction is a concern worldwide. Most mechanistic investigations are on nicotine substance dependence properties based on its pharmacological effects. However, no effective therapeutic treatment has been established. Nicotine addiction is reinforced by environments or habits. We demonstrate the neurobiological basis of the behavioural aspect of nicotine addiction. We utilized the conditioned place preference to establish nicotine-associated behavioural preferences (NABP) in rats. Brain-wide neuroimaging analysis revealed that the medial prefrontal cortex (mPFC) was activated and contributed to NABP. Chemogenetic manipulation of µ-opioid receptor positive (MOR⁺) neurons in the mPFC or the excitatory outflow to the nucleus accumbens shell (NAcShell) modulated the NABP. Electrophysiological recording confirmed that the MOR⁺ neurons directly regulate the mPFC-NAcShell circuit via GABA_A receptors. Thus, the MOR⁺ neurons in the mPFC modulate the formation of behavioural aspects of nicotine addiction via direct excitatory innervation to the NAcShell, which may provide new insight for the development of effective therapeutic strategies.
Animals ; Nucleus Accumbens/drug effects* ; Prefrontal Cortex/drug effects* ; Nicotine/pharmacology* ; Receptors, Opioid, mu/metabolism* ; Male ; Rats ; Rats, Sprague-Dawley ; Tobacco Use Disorder/metabolism* ; Neurons/drug effects* ; Neural Pathways/drug effects*

Bone Neoplasms ; Humans ; Ilium ; Paraganglioma ; Sacrum

Objective　To evaluate whether the stimulation on eyes of bendazac lysine eyedrops could be reduced by cold storage.Methods　 Mate design scheme and double-blind clinical trial were performed. 160 healthy eyes was divided into two groups: the test group was given bendazac lysine eyedrops which was stored in refrigerator at 4℃ over night, and the control group was given it which was stored at room temperature.Results　ln the control group and the test group, the occuring rate of stimulation was 19.30% and 6.25%. The cases of B、C stimulation degrees were 31 and 10; the average stimulation degrees of each group were 1.21 and 1.07, the scoring change for eye stimulation were 1.57±1.50,0.79±1.40,all respectively. The statistical difference was significant (P＜0.05 or P＜0.01).Conclusion　The eye stimulation of bendazac lysine eyedrops can be reduced by cold storage.

?-Endorphin cells in the rat gastric antrum and effect of long-term stress on the number of ?-endorphin cells in the pituitary gland and gastric antrum were studied with PAP method and on the basis of stereological principle.The results showed that after long-term stress in rats, the number of ?-endorphin cells in the pituitary gland were significantly increased but decreased in the gastric antrum.