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.

Esophageal cancer （EC） is a highly prevalent malignant tumor in China. The phosphatidylinositol 3-kinase （PI3K）/protein kinase B （Akt） signaling pathway， as one of the key oncogenic pathways， can promote the cell cycle progression， proliferation， migration， and invasion， induce chemoresistance， and inhibit apoptosis and autophagy of EC cells. Traditional Chinese medicine （TCM）， with the advantages of targeting multiple points with multiple components to delay cancer progression， can target the PI3K/Akt signaling pathway for EC treatment. This article preliminarily discusses the molecular mechanism and role of the PI3K/Akt signaling pathway in EC and elaborates on the specific targets and efficacy of TCM in treating EC through intervention in the PI3K/Akt signaling pathway in the past five years. TCM materials and extracts inhibiting the PI3K/Akt signaling pathway in EC include Borneolum， spore powder of Ganoderma lucidum without spore coat， extract of Celastrus orbiculatus， root extract of Taraxacum， and Bruceae Fructus oil emulsion. TCM active ingredients exerting the effect include flavonoids， terpenoids， saponins， phenols， polysaccharides， alkaloids， and other compounds. TCM compound prescriptions with such effect include Qige San， Huqi San， Xuanfu Daizhetang， Tongyoutang and its decomposed prescriptions， Liujunzi Tang， and Xishenzhi Formula. In addition， TCM injections such as Compound Kushen Injection and Kang'ai injection also inhibit the PI3K/Akt signaling pathway in EC. This paper summarizes the role of the PI3K/Akt signaling pathway in EC and the TCM interventions， aiming to provide reference for the research and clinical application of new drugs for EC.

Objective To describe the significance of the pretreatment inflammatory indicators in predicting the prognosis of patients with esophageal squamous cell carcinoma (ESCC) after undergoing radical radiotherapy. Methods The data of 246 ESCC patients who underwent radical radiotherapy were retrospectively collected. Receiver operating characteristic (ROC) curves were drawn to determine the optimal cutoff values for platelet-lymphocyte ratio (PLR), neutrophil-lymphocyte ratio (NLR), and systemic immune-inflammation index (SII). The Kaplan-Meier method was used for survival analysis. We conducted univariate and multivariate analyses by using the Cox proportional risk regression model. Software R (version 4.2.0) was used to create the nomogram of prognostic factors. Results The results of the ROC curve analysis showed that the optimal cutoff values of PLR, NLR, and SII were 146.06, 2.67, and 493.97, respectively. The overall response rates were 77.6% and 64.5% in the low and high NLR groups, respectively (P<0.05). The results of the Kaplan-Meier survival analysis revealed that the prognosis of patients in the low PLR, NLR, and SII group was better than that of patients in the high PLR, NLR, and SII group (all P<0.05). The results of the multivariate Cox regression analysis showed that gender, treatment modalities, T stage, and NLR were independent factors affecting the overall survival (OS). In addition, T stage and NLR were independent factors affecting the progression-free survival (PFS) (all P<0.05). The nomogram models of OS and PFS prediction were established based on multivariate analysis. The C-index values were 0.703 and 0.668. The calibration curves showed excellent consistency between the predicted and observed OS and PFS. Conclusion The pretreatment values of PLR, NLR, and SII are correlated with the prognosis of patients with ESCC who underwent radical radiotherapy. Moreover, NLR is an independent factor affecting the OS and PFS of ESCC patients. The NLR-based nomogram model has a good predictive ability.

Objective To analyze the imaging features of cerebral small vessel disease in patients with type 2 diabetes mellitus by multimodal MRI.Methods The clinical data of 160 patients with cerebral small vessel disease admitted to our hospital from January to December 2020 were retrospectively analyzed.According to whether they were complicated with type 2 diabetes mellitus,they were divided into the diabetic group and the non-diabetic group,with 80 cases in each group.Both groups underwent multimodal MRI scans.And the severity of lacunar infarction,the severity of subcortical and periventricular white matter lesions,white matter integral and cerebral microbleeds of patients in the two groups were compared.Results The severity of lacunar infarction(χ2=34.076,P=0.001),subcortical white matter lesions(χ2=25.000,P=0.001),periventricular white matter lesions(χ2=22.895,P=0.001)and white matter integral(t=12.370,P=0.001)of patients in the diabetic group were significantly higher than those in the non-diabetic group.No cerebral microbleeds were detected in either group of patients.Conclusion Patients with cerebral small vessel disease and type 2 diabetes mellitus show characteristic multimodal MRI changes.The increase in the number of lacunar infarction lesions and the aggravation of white matter lesions can be used as the characteristic imaging basis for the diagnosis of type 2 diabetes mellitus related cerebral small vessel disease.

The aim of this study was to understand the internal genetic diversity and population history dynamics of ticks in Inner Mongolia,to provide data for designing effective vector control programs and revealing ticks'transmission mechanisms.From 2022 to 2023,the manual collection method was used to collect samples in Inner Mongolia.The 16S rDNA and COI gene sequences of ticks were used to identify Hyalomma marginatum,Haemaphysalis concinna,and Argas persicus,and analyze the sequence characteristics and genetic diversity within the populations.Base composition analysis indicated that the average A+T content of the 16S rDNA gene and CO I gene in the three ticks was significantly higher than that of C+G.Moreover,22 haplotypes of the COI gene and 12 haplotypes of the 16S rDNA sequence were identified in Hyalomma marginatum.Eleven haplotypes were identified according to the COI gene,and nine haplotypes were identified according to the16S rDNA sequence of Haemaphysalis concinna.Two haplotypes were identified on the basis of the COI gene,and six haplotypes were identified on the basis of the 16S rDNA sequence of Ar gas persicus.The minimum 16S rDNA haplotype diversity was 0.264 for Ar gas persicus and 0.579 for the other two species.The nucleotide diversity of the three tick species was less than 0.05.Tajima's val-ue and Fu's Fs value of the neutrality test were negative.Base saturation substitution analysis indicated that neither of the two genes in the three tick species reached saturation.The phylogenetic tree revealed that Hyalomma marginatum,Haema physalis concinna,and Ar gas persicus in Inner Mongolia independently aggregated into branches.In conclusion,the base content of Hyalomma marginatum,Haemaphysalis concinna,and Argas persicus genes in Inner Mongolia was consist-ent with the characteristics of insect mitochondrial DNA content.Furthermore,the three tick populations showed rapid evolu-tionary population expansion,and the phylogeny of three tick species showed independent aggregation into clades,with no pop-ulation isolation.

Objective To detect the characteristics of whole-brain functional changes in patients with subjective tinnitus(ST)after"frontal-temporal"dual-site repetitive transcranial magnetic stimulation(rTMS)by resting-state functional magnetic resonance imaging(rs-fMRI).Methods A total of 45 ST patients were enrolled,and assessments of tinnitus severity and rs-fMRI scans were performed before and 2 weeks after treatment with"frontal-temporal"dual-site rTMS.Regional homogeneity(ReHo),fractional amplitude of low-frequency fluctuations(fALFF),degree centrality(DC)and seed-based functional connectivity(FC)were analyzed before and after treatment in ST patients.Results Tinnitus handicap inventory(THI)score of ST patients 2 weeks after treatment was significantly decreased compared with that before treatment(P<0.001).ReHo values of the right inferior parietal lobule decreased,fALFF values of the right temporal pole increased,fALFF values of the right superior temporal gyrus decreased,and DC(weighted)and DC(Binarized)values of the right medial temporal gyrus all decreased in ST patients 2 weeks after treatment compared with those before treatment(P<0.05,GRF correction).Using the above differential brain regions as seed points for FC analysis,FC values between right superior temporal gyrus(fALFF)and right middle temporal gyrus reduced,FC values between right middle temporal gyrus[(DC(weighted)]and right superior occipital gyrus reduced,and FC values between right middle temporal gyrus[DC(Binarized)]and right superior occipital gyrus reduced 2 weeks after treatment compared with those before treatment(P<0.05,GRF correction).Conclusion"Frontal-temporal"dual-site rTMS is initially effective for ST patients,and the auditory and non-auditory brain regions of ST patients showed different degrees of regional and interbrain function changes,mainly involving default mode network and visual-auditory network.

Objective To construct an age prediction model for adolescents using radiomics from oral panoramic radiographs.Methods Panoramic radiographic images of 441 adolescent patients aged 11.00～13.99 years were imported into the open-source software 3D Slicer for segmentation of regions of interest(ROI).Python was used to extract all features from the ROIs of all patients.The patients were randomly divided into a training set and a test set at a ratio of 7∶3.Machine learning methods were applied to analyze the correlation between radiomics features and age characteristics to build the age prediction model.Results Out of 863 two-dimensional radiomics features,10 were selected.Three machine learning methods—support vector machine,random forest,and logistic regression—were used to train the model on the training set,and the best machine learning model was chosen.The performance of the machine learning models was evaluated using the Area Under Curve(AUC).In the test set,the AUCs for females were 0.795,0.830,and 0.795 for the three methods respectively,while for males,they were 0.830,0.864,and 0.846.Conclusion The radiomics model based on oral panoramic radiographs demonstrates good diagnostic efficacy and can be used for age prediction.

Objective To detect the characteristics of whole-brain functional changes in patients with subjective tinnitus(ST)after"frontal-temporal"dual-site repetitive transcranial magnetic stimulation(rTMS)by resting-state functional magnetic resonance imaging(rs-fMRI).Methods A total of 45 ST patients were enrolled,and assessments of tinnitus severity and rs-fMRI scans were performed before and 2 weeks after treatment with"frontal-temporal"dual-site rTMS.Regional homogeneity(ReHo),fractional amplitude of low-frequency fluctuations(fALFF),degree centrality(DC)and seed-based functional connectivity(FC)were analyzed before and after treatment in ST patients.Results Tinnitus handicap inventory(THI)score of ST patients 2 weeks after treatment was significantly decreased compared with that before treatment(P<0.001).ReHo values of the right inferior parietal lobule decreased,fALFF values of the right temporal pole increased,fALFF values of the right superior temporal gyrus decreased,and DC(weighted)and DC(Binarized)values of the right medial temporal gyrus all decreased in ST patients 2 weeks after treatment compared with those before treatment(P<0.05,GRF correction).Using the above differential brain regions as seed points for FC analysis,FC values between right superior temporal gyrus(fALFF)and right middle temporal gyrus reduced,FC values between right middle temporal gyrus[(DC(weighted)]and right superior occipital gyrus reduced,and FC values between right middle temporal gyrus[DC(Binarized)]and right superior occipital gyrus reduced 2 weeks after treatment compared with those before treatment(P<0.05,GRF correction).Conclusion"Frontal-temporal"dual-site rTMS is initially effective for ST patients,and the auditory and non-auditory brain regions of ST patients showed different degrees of regional and interbrain function changes,mainly involving default mode network and visual-auditory network.

Aim To investigate the protective effect of Shengmai Yin on myocardial ischemia/reperfusion in-jury(MI/RI)in vitro and in vivo and to unravel the underlying mechanism.Methods SD rats were divid-ed into the sham group,model group,and Shengmai Yin group(SM).Rat MI/RI model was established.Cardiac function,infarct area,pathological changes,cardiomyocyte apoptosis,macrophage infiltration,and serum cTnT and CK-MB levels were measured.The mRNA and protein expressions of Calpain-1 and Cal-pain-2 were assessed.The hypoxia/reoxygenation(H/R)model was constructed in H9c2 cells.The active ingredients of Shengmai Yin were screened using net-work pharmacology and verified by CCK-8.In the car-diomyocytes H/R model,Fluo-4 AM staining was used to detect the changes of Ca2+levels.Results Com-pared with model group,LVEF and LVFS of Shengmai Yin-treated rats increased,myocardial infarction area was reduced,while myocardial tissue injury was allevi-ated.Myocardial apoptosis rate and the number of macrophages were reduced.Similarly,cTnT and CK-MB levels decreased.In addition,the expression lev-els of Calpain-1 and Calpain-2 mRNA and protein de-creased in the SM treatment group.Under the H/R model,all the active ingredients of Shengmai decoction had protective effects on cardiomyocytes,and the treat-ment could reduce the level of Ca2+in cardiomyocytes.Conclusions Shengmai Yin has protective effects on MI/RI in rats.This effect may be related to the de-crease in Ca2+levels,as well as Calpain-1 and Calap-in-2 mRNA and protein expression.