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.

Atrial functional mitral regurgitation (AFMR) is mitral regurgitation in patients with atrial fibrillation (AF), whose left atrium (LA) is enlarged, the left ventricle is not enlarged or only slightly enlarged, the left ventricular ejection fraction is preserved, and the mitral valve itself has no apparent lesion. At present, the etiology, pathophysiology and mechanism of this disease have not been completely clear yet. Existing studies have found that the causes of AFMR mainly include AF, enlargement of LA and mitral annulus, destruction of mitral annular shape, inability of mitral valve remodeling to compensate for mitral annular expansion, and hamstringing of the posterior mitral leaflet by atriogenic tethering. AFMR is demonstrated to be associated with an increased risk of mortality and readmission due to heart failure. Therefore, it serves as a primary therapeutic target for patients with heart failure and AF. However, the optimal treatment of AFMR still remains controversial. Therefore, this article will mainly expound the current definition, etiology, pathophysiological mechanism, treatment, and prognosis of AFMR.

Objective To investigate the changes of serum lipoxin A4(LXA4), vitamin D and IL-18 levels and their correlation with lung function in patients with bronchial asthma, and to provide theoretical basis for clinical evaluation of bronchial asthma lung function. Methods A total of 284 patients with bronchial asthma admitted to our hospital from March 2018 to March 2020 were selected from the observation group, and 284 healthy normal people who received physical examination in our hospital during the same period were selected from the control group. The FEV1% and serum levels of LXA4, 25 hydroxyvitamin D3[25(OH)D3] and IL-18 in both groups were determined. Pearson correlation analysis was conducted between serum LXA4, vitamin D and IL-18 levels and lung function in patients with bronchial asthma. Results The FEV1% value in observation group was significantly lower than that in control group (t=56.059，P<0.05). The FEV1% value in acute attack stage was significantly lower than that in chronic duration and clinical remission stage (t₁=8.605，t₁=23.464，P<0.05). The serum LXA4 and 25(OH)D3 levels in observation group were significantly lower than those in control group, and the serum IL-18 level was significantly higher than that in control group (P<0.05). The levels of serum LXA4 and 25(OH)D3 in acute attack stage were significantly lower than those in chronic duration and clinical remission stage, and the levels of serum IL-18 were significantly higher than those in chronic duration and clinical remission stage (P<0.05). The levels of serum LXA4 and 25(OH)D3 in chronic asthma were significantly lower than those in clinical remission, and the levels of serum IL-18 were significantly higher than those in clinical remission (P<0.05).Pearson correlation analysis showed that 25(OH)D3 was positively correlated with FEV1% value (r=0.519, P<0.05). LXA4 and IL-18 was positively related with FEV1% values (r₁=-0.492, r₁=-0.615, P<0.05) . Conclusion LXA4, vitamin D and IL-18 can be used as markers to assess lung function in bronchial asthma.

Given the opposing effects of Akt and AMP-activated protein kinase (AMPK) on metabolic homeostasis, this study examined the effects of deletion of Akt2 and AMPKα2 on fat diet-induced hepatic steatosis. Akt2–Ampkα2 double knockout (DKO) mice were placed on high fat diet for 5 months. Glucose metabolism, energy homeostasis, cardiac function, lipid accumulation, and hepatic steatosis were examined. DKO mice were lean without anthropometric defects. High fat intake led to adiposity and decreased respiratory exchange ratio (RER) in wild-type (WT) mice, which were ablated in DKO but not Akt2−/− and Ampkα2−/− mice. High fat intake increased blood and hepatic triglycerides and cholesterol, promoted hepatic steatosis and injury in WT mice. These effects were eliminated in DKO but not Akt2−/− and Ampkα2−/− mice. Fat diet promoted fat accumulation, and enlarged adipocyte size, the effect was negated in DKO mice. Fat intake elevated fatty acid synthase (FAS), carbohydrate-responsive element-binding protein (CHREBP), sterol regulatory element-binding protein 1 (SREBP1), peroxisome proliferator-activated receptor gamma coactivator 1-alpha (PGC-1α), peroxisome proliferator-activated receptor-α (PPARα), PPARγ, stearoyl-CoA desaturase 1 (SCD-1), phosphoenolpyruvate carboxykinase (PEPCK), glucose 6-phosphatase (G6Pase), and diglyceride O-acyltransferase 1 (DGAT1), the effect was absent in DKO but not Akt2−/− and Ampkα2−/− mice. Fat diet dampened mitophagy, promoted inflammation and phosphorylation of forkhead box protein O1 (FoxO1) and AMPKα1 (Ser485), the effects were eradicated by DKO. Deletion of Parkin effectively nullified DKO-induced metabolic benefits against high fat intake. Liver samples from obese humans displayed lowered microtubule-associated proteins 1A/1B light chain 3B (LC3B), Pink1, Parkin, as well as enhanced phosphorylation of Akt, AMPK (Ser485), and FoxO1, which were consolidated by RNA sequencing (RNAseq) and mass spectrometry analyses from rodent and human livers. These data suggest that concurrent deletion of Akt2 and AMPKα2 offers resilience to fat diet-induced obesity and hepatic steatosis, possibly through preservation of Parkin-mediated mitophagy and lipid metabolism.