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.

Objective:To evaluate the accuracy and feasibility of an automated scanning and uptake system to assist pathologists with hu-man epidermal growth factor receptor 2(HER2)FISH interpretation.Methods:HER2 gene amplification is detected using FISH,and"result interpretation by independent pathologists"is regarded as the"gold standard."The consistency of"human-machine dialogue results"(use of a CytoVision* system combined with manual interpretation)and"CytoVision*-based automated interpretation"with the"gold standard"was assessed.Results:Consistency between"human-machine dialogue results"and the"gold standard"can surpass 91%,with the former method saving up to 50%of the manual operation time.The tendency of each cell nucleus's HER2 copy number to be"underestimated"is the main reason for the low sensitivity observed in cases with low copy number amplification and HER2 heterogeneous expression cases in"human-machine dialogue interpretation."Conclusions:Automatic FISH image analysis and uptake systems simulate the process of manu-ally interpreted cell selection,ensure random cell selection,and improve work efficiency.With its accurate selection of the hybridization re-gion and"human-computer dialogue,"the system is expected to"replace"interpretation by independent pathologists.

Objective:To construct and verify a risk prediction model for pulmonary infection in patients with aneurysmal subarachnoid hemorrhage (aSAH) after craniotomy and clipping, providing theoretical basis and practical guidance for improving the quality of postoperative care.Methods:Using the convenience sampling method, a retrospective selection was made of 397 patients with aSAH after craniotomy and clipping who were hospitalized in the Department of Neurosurgery of Shanxi Bethune Hospital (Shanxi Academy of Medical Sciences) from January 2019 to December 2023 as the modeling group. They were randomly divided into the training set and the test set at a ratio of 7:3, with 278 cases in the training set and 119 cases in the test set. Patients were divided into the infection group and the non-infection group based on whether they developed pulmonary infection. Univariate analysis was used to model the risk factors of pulmonary infection after aSAH craniotomy and clamping in the group, and Lasso regression was used to construct a predictive model. A total of 119 patients with aSAH admitted to the neurosurgery department of the same hospital from January to April 2024 were selected for the external validation of the model. The predictive effect of the model was evaluated through the receiver operating characteristic (ROC) curve.Results:In the modeling group, there were 216 male patients and 181 female patients. The incidence of pulmonary infection was 38.54% (153/397). Finally, five influencing factors, namely stroke, Hunt-Hess classification, mechanical ventilation, indwelling nasogastric tube and the timing of initiating enteral nutrition, were included to construct a predictive model. The areas under the ROC curves of the nomogram prediction models of this model in the training set, test set, and external validation group were 0.859(95% CI 0.791-0.928), 0.843(95% CI 0.796-0.890), and 0.800(95% CI 0.711-0.889), respectively. The calibration curve shows that the model's prediction fits well with the actual situation and has a high degree of calibration. Decision curve analysis indicates that this model has high clinical application value under different risk thresholds. Conclusions:The risk prediction model for pulmonary infection in patients after craniotomy and clipping with aSAH has good discrimination and calibration, which can provide reference for medical staff to identify high-risk patients at an early stage and take preventive intervention measures.

Objective To study the impact of tympanic membrane opening on respiratory-driven middle ear pressure in patients with patulous eustachian tube(PET),using a simplified in vitro model.Methods CT imaging data from a PET patient(with full-length eustachian tube opening observed during a Valsalva maneuver followed by breath-holding)were used to design a simplified eustachian tube model.Two simplified in vitro models of the eusta-chian tube were constructed using silicone-based 3D printing technology and connected to a pressure controller and pressure sensors.The pressure controller was activated to introduce negative-pressure airflow into the nasopharyn-geal model to simulate respiratory-induced middle ear pressure fluctuations.A hemostat was used to alternately open and close the external interface of the middle ear chamber,simulating conditions of an open and intact tympanic membrane,while middle ear pressure was continuously monitored using pressure sensors.Results In the first mod-el,with-800 mbar negative pressure applied at the nasopharynx,the middle ear pressure stabilized between-3.9 mbar and-4.3 mbar with tympanic membrane opening,and between-7.9 mbar and-8.2 mbar with intact tym-panic membrane.In the second model,under the same pressure setting,middle ear pressure stabilized between-2.7 mbar and-3.1 mbar with tympanic membrane opening,and between-5.0 mbar and-7.7 mbar with intact tympanic membrane.Conclusion This study,based on a simplified in vitro model,demonstrates that tympanic membrane opening can effectively reduce respiratory-driven pressure in the middle ear.This phenomenon may partly explain the clinical efficacy of tympanostomy tube insertion in certain PET patients.

Endometriosis is a common estrogen-dependent disease in women of childbearing age,often leading to chronic pelvic pain,infertility,ovarian cancer,and other serious complications,and jeopardizing the health of women.The pathogenesis of endometriosis is complex and involves the alteration of multiple signaling pathways mediated by hormones,immunity,genetics,and the environment,and their interactions.Wnt/β-catenin signaling is involved in the regulation of embryonic development and tissue homeostasis,and it has recently been implicated in the pathogenesis of endometriosis via multiple pathways.This review considers the biological characteristics of the Wnt/β-catenin signaling pathway and summarizes the main mechanisms and signaling pathways involved in the pathogenesis of endometriosis,as well as the curr-ent research status of the regulation of this signaling pathway by traditional Chinese medicine for the treatment of endometriosis.We aim to clarify how the Wnt/β-catenin signaling pathway affects the development of endometriosis,and suggest that future studies should focus on exploring its potential role as an indicator for the clinical prediction and early diagnosis of endometriosis,thus providing theoretical support for the early diagnosis of this condition and the development of targeted drugs.

The conventional identification and prediction for failures of medical equipment mainly depend on experience and knowledge of manager for equipment,which are not able to be quantified and have lower efficiency. Therefore,it is obvious that the prediction for the failure of medical equipment is not accurate. With the technical development of computer and machine learning,the conventional identification and prediction that depend on experiences can deal with characteristics of failures through machine learning method to improve efficiency,which are hopeful in filling the gap of discipline about the identification and prediction for failures of medical equipment. This article summarized the application situation of machine learning in identifying and predicting failures of the medical equipment and the similarly electric equipment at home and abroad. Based on the key technique of identification and prediction,this article proposed suggestion about corresponding design architecture. According to the characteristics of the failure of medical equipment,this article summarized a series of information about algorithms of various machine learning in scene and accurate rate of identification and prediction,so as to provide references for relevant research of this field.

Objective To explore the resistance mechanism of tigecycline insensitivity of multidrug-resistant Acine-tobacter baumannii,and provide reference for clinical rational antimicrobial use as well as prevention and control of healthcare-associated infection.Methods 22 strains of tigecycline insensitive multidrug-resistant Acinetobacter bau-mannii(TIS-MDR-AB)and 22 strains of tigecycline sensitive multidrug-resistant Acinetobacter baumannii(TS-MDR-AB)isolated clinically from the First Affiliated Hospital of Guangzhou Medical University from April 2022 to May 2023 were collected.Efflux pump phenotype inhibition assay was performed using efflux pump inhibitor car-bonyl cyanide m-chlorophenylhydrazone(CCCP).The main efflux pump genes(adeB,adeG,adeJ),as well as tigecycline-resistant gene tet(X),were screened by polymerase chain reaction(PCR)technique,and their mRNA expression levels were detected by real-time fluorescence quantitative PCR.Mutations in the efflux pump regulatory gene adeRS were analyzed by Sanger sequencing analysis.Results The detection rates of efflux pump genes adeB,adeG and adeJ were all above 95％in two MDR-AB groups,and tet(X)gene was not detected.Efflux pump inhibi-tor assay showed that the minimum inhibitory concentration(MIC)of TIS-MDR-AB strains decreased after adding CCCP,3 strains showed positive efflux pump phenotype.The mRNA expression level of MDR-AB adeB in the TIS-MDR-AB group was higher than that in the TS-MDR-AB group(P＜0.01),while the expression of adeG and adeJ genes was no statistically different.Multiple mutations were found in the adeR and adeS genes,the adeS of 2 strains was inserted ISAba1,and 3 strains were inserted ISAba13.Conclusion The overexpression of adeABC in the efflux pump system may play an important role in the mechanism of reduced sensitivity of MDR-AB to tigecycline,and its overexpression may be related to the insertion sequence or mutation in the efflux pump regulatory gene adeRS.

Objective To observe the value of enhanced MRI"strawberry sign"for differentiating solitary predominantly cystic brain metastasis and glioma.Methods Thirty-four patients with solitary predominantly cystic(cystic proportion greater than 50％)brain metastasis(metastasis group)and 43 with solitary predominantly cystic glioma(glioma group)were retrospectively enrolled,and the value of"strawberry sign"showed on contrast enhanced T1WI(CE-T1WI)for differentiation was analyzed.Results The detection rate of"strawberry sign"in metastasis group was 44.12％(15/34),and the primary cancer was lung adenocarcinoma in 6 cases(6/15,40.00％),small cell lung cancer in 3 cases(3/15,20.00％),as well as lung squamous cell carcinoma,breast cancer,colon adenocarcinoma,endometrioid carcinoma,fallopian tube adenocarcinoma and rectal melanoma each in 1 case(1/15,6.67％).Meanwhile,the detection rate of"strawberry sign"in glioma group was 18.60％(8/43),and all were observed in WHO grade 4 gliomas.The detection rate of"strawberry sign"in metastasis group was higher than that in glioma group,which was not related to patients' gender(P=0.442).The sensitivity,specificity,accuracy,positive predictive value and negative predictive value of"strawberry sign"for differentiating solitary predominantly cystic brain metastasis and glioma was 44.12％,81.40％,64.94％,65.22％and 64.81％,respectively.Conclusion"Strawberry sign"showed on CE-T1WI was helpful for differentiating solitary predominantly cystic brain metastasis and glioma.

To investigate the role of the DPP4-nestin axis in liver fibrosis induced by alveolar cyst infection,a murine model was established using C57BL/6 mice via hepatic portal vein injection.Liver histopathological changes were assessed using HE staining,while immunohistochemistry and immunofluorescence were employed to evaluate the expression levels of nestin and DPP4 in infected mouse livers.In vitro,J S1 cell line was stimulated with recombinant DPP4 protein to es-tablish a cellular model,and qPCR,Western blot,and shRNA lentivirus interference techniques were utilized to examine the involvement of the DPP4-nestin axis in hepatic stellate cell activation.The findings demonstrated that compared to the Sham group,liver tissue structure disruption and collagen deposition were evident along with significantly increased expressions of nestin and DPP4(P＜0.050 0),which colocalized with nesin and α-SMA.Furthermore,stimulation with recombi-nant DPP4 protein significantly enhanced JS1 cell activation(P＜0.050 0)as well as upregulated nestin expression(P＜0.050 0)when compared to control group cells.Notably,shRNA lentivirus-mediated inhibition of nestin expression effectively suppressed the activating effects exerted by re-combinant DPP4 protein on JS1 cells(P＜0.050 0).Collectively,these results highlight the crucial regulatory role played by the DPP4-nestin axis in hepatic stellate cell activation triggered by alveo-lar infection;thus,targeting this axis may represent a novel therapeutic strategy for treating alveo-lar infection-induced liver fibrosis.

Objective:To evaluate the accuracy and feasibility of an automated scanning and uptake system to assist pathologists with hu-man epidermal growth factor receptor 2(HER2)FISH interpretation.Methods:HER2 gene amplification is detected using FISH,and"result interpretation by independent pathologists"is regarded as the"gold standard."The consistency of"human-machine dialogue results"(use of a CytoVision* system combined with manual interpretation)and"CytoVision*-based automated interpretation"with the"gold standard"was assessed.Results:Consistency between"human-machine dialogue results"and the"gold standard"can surpass 91%,with the former method saving up to 50%of the manual operation time.The tendency of each cell nucleus's HER2 copy number to be"underestimated"is the main reason for the low sensitivity observed in cases with low copy number amplification and HER2 heterogeneous expression cases in"human-machine dialogue interpretation."Conclusions:Automatic FISH image analysis and uptake systems simulate the process of manu-ally interpreted cell selection,ensure random cell selection,and improve work efficiency.With its accurate selection of the hybridization re-gion and"human-computer dialogue,"the system is expected to"replace"interpretation by independent pathologists.