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.

Sensors have been widely recognized in matrix metalloproteinases(MMP)detection for their high sensitivity,simplicity,speed and easy in vivo and vitro detection.The design thought of existing sensors is based on the structure of MMP-9 molecule or the enzyme activity to output different signals in response to sensing.In this paper,we summarize the current research status and difficulties of MMP-9 sensing detection technology,and further discuss the development prospects of MMP sensor,which will provide a reference for the detection of MMP-9 and other good biological target molecules.

AIM:To investigate the therapeutic effects and potential mechanism of pachymic acid(PA)on li-popolysaccharide(LPS)-induced acute kidney injury(AKI)in mice.METHODS:(1)Genes related to AKI were screened using the DAVID database.Core genes were identified by intersecting related genes and analyzed using Cyto-scape software.Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)analyses were performed through the DAVID database for the cross-targets.Molecular docking and activity assays were conducted on the primary core targets.(2)A total of 100 C57BL/6J mice were randomly divided into five groups:normal control(NC),model(LPS),solvent control(LPS+DMSO),and treatment groups(LPS+PA-10 and LPS+PA-20),with 20 mice in each group.The LPS-AKI model was established by intraperitoneal injection of 18 mg/kg LPS.The treatment groups received 10 mg/kg and 20 mg/kg PA,respectively,and the solvent control group was administered an equivalent dose of DMSO.Mice were euthanized 24 h after injection.Serum was collected for biochemical analysis,and Western blot was used to detect neutro-phil gelatinase-associated lipocalin(NGAL),kidney injury molecule-1(KIM-1),caspase-3,cleaved caspase-3,interleu-kin-1β(IL-1β),and monocyte chemoattractant protein-1(MCP-1)protein expression.RT-qPCR was employed to detect inflammatory factor mRNA levels.Molecular docking was used to simulate the optimal binding site of PA to caspase-3.En-zyme activity assays were performed to assess caspase protein activity,and renal lesions were observed via hematoxylin and eosin(HE)staining.Apoptosis was detected by TUNEL staining.RESULTS:(1)Thirty-one potential targets of PA against AKI were identified through network pharmacology.GO and KEGG enrichment analyses indicated that these tar-gets were primarily involved in immune response,inflammatory processes,apoptosis and survival,angiogenesis and hemo-dynamics,oxidative stress,and endoplasmic reticulum stress.Key targets included CASP3(caspase-3),PTGS2,BCL2,CCL2,and CYP219.(2)PA treatment improved renal function and reduced tubular epithelial injury.It significantly de-creased NGAL,KIM-1,and cleaved caspase-3 protein levels,as well as inflammatory factors TNF-α,IL-1β,and MCP-1 mRNA and protein expression.PA also reduced apoptosis of renal tubular epithelial cells.Enzyme activity assays and mo-lecular docking revealed that PA exerted its anti-apoptotic effect by directly binding to caspase-3,thereby inhibiting its ac-tivation by caspase-8.CONCLUSION:PA demonstrated a therapeutic effect in LPS-AKI,potentially through the inhibi-tion of inflammatory factor synthesis and release,as well as the inhibition of caspase-3 activation by caspase-8,reducing apoptosis in renal tubular epithelial cells.

Objective:To explore the association between the use of tetracyclines during pregnancy and congenital malformations, with the aim of providing evidence-based guidance for the rational use of antibiotics during pregnancy.Methods:Data from the U.S. Food and Drug Administration Adverse Event Reporting System (FAERS) and the Canada Vigilance Adverse Reaction (CVAR) database from January 2015 to September 2024 were collected. Five methods including Tree-based scan statistic (TreeScan), proportional reporting ratio (PRR), reporting odds ratio (ROR), the UK Medicines and Healthcare Products Regulatory Agency (MHRA) comprehensive standard, and the Bayesian confidence propagation neural network (BCPNN) were used to detect signals of risk for congenital malformations in offspring following maternal use of tetracyclines during pregnancy. A signal that met the threshold criteria of all above 5 methods was considered as a risk signal. Based on population-based cohort of the drug exposures and adverse pregnancy outcomes (DEEP) data from January 2013 to December 2021 in Xiamen City, propensity score matching (PSM)-based Poisson regression was applied to evaluate the association between the first-trimester tetracyclines exposure and congenital malformations in offspring. Adjusted relative risk (a RR) and its 95% confidence interval ( CI) were calculated. Sensitivity analysis was conducted to validate the reliability of the results. Results:A total of 304 098 reports of adverse events during pregnancy were obtained from the FAERS and CVAR databases. Among them, 5 028 reports were related to tetracyclines, including 1 026 reports of congenital malformations in offspring, involving congenital malformations of musculoskeletal system, other digestive system, and other congenital malformations. Signal detection results suggested that tetracyclines may be a risk signal for above congenital malformations in offspring. The DEEP data included 411 936 pregnant women. After PSM, 240 pregnant women exposed to tetracyclines were included. The results showed no significant association between the first-trimester tetracyclines exposure and congenital malformations in offspring (a RR=0.75, 95% CI: 0.26-2.17), sensitivity analysis also showed no correlation. Conclusions:Data mining from the FAERS and CVAR databases suggests a potential association between tetracyclines use during pregnancy and congenital malformations in offspring. However, the DEEP data study shows no significant correlation.

Objective:To analyze the epidemiological and clinical features of infectious diseases of the central nervous system (CNS).Methods:A cross-sectional study and analysis were conducted to summarize the epidemiological and clinical characteristics of 9 918 patients with CNS infectious diseases, who were diagnosed and treated at 29 hospitals across China from January 1, 2001 to December 31, 2020. Data collected included demographic data, clinical manifestations, health economic indicators, and prognostic outcomes.Results:Among the 9 918 collected cases of CNS infectious diseases, 5 559 were male (56.0%) and 4 359 were female (44.0%), with an onset age of 38 (25, 53) years. Education level: slightly more junior high school education (2 651 cases, 26.7%), and less elementary school education and below (2 181 cases, 22.0%) were found. Occupational distribution: farmers were found predominant (3 215 cases, 32.4%), followed by workers (1 826 cases, 18.4%) and students (1 633 cases, 16.5%). Clinical manifestations: headache (6 074 cases, 61.2%), fever (5 869 cases, 59.2%) and positive meningeal irritation signs (2 273 cases, 22.9%) were the 3 most common clinical manifestations, followed by nausea and (or) vomiting (2 095 cases, 21.1%), impaired consciousness (2 077 cases, 20.9%), psychiatric symptom (1 866 cases, 18.8%) and epilepsy (1 627 cases, 16.4%), etc., and cranial nerve involvement was found in 669 cases (6.7%). Major pathogens included viruses in 6 814 cases (68.7%), Mycobacterium tuberculosis in 1 677 cases (16.9%), common bacteria in 864 cases (8.7%), fungi in 254 cases (2.6%), spirochetes of syphilis in 183 cases (1.8%), parasites in 121 cases (1.2%), and rickettsiae in 5 cases (0.1%). Urban-rural distribution: slightly more cases were found in the countryside (5 418 cases, 54.6%) than in the towns (4 500 cases, 45.4%). Distribution of onset by season: 2 412 cases (24.3%) fell ill in spring, 2 835 cases (28.6%) in summer, 2 187 cases (22.1%) in fall, and 2 484 cases (25.0%) in winter. Health economics: the duration of hospitalization was 15 (8, 27) days, and the cost of hospitalization was 1.53 (0.91, 3.02)×10 000 yuan. Prognosis: 9 531 cases (96.1%) were cured or improved, and 92 cases (0.9%) died. Conclusions:The pathogens responsible for CNS infectious diseases are predominantly viruses. Although the incidence is slightly higher during the summer months, the overall seasonal pattern is not particularly pronounced. These infections are more commonly observed in young and middle-aged males and present with a diverse range of clinical manifestations, contributing to a significant disease burden.

Objective:To analyze the association between healthcare workers mental health,institu-tional supplies and facilities,inter-organizational coordination during infectious disease outbreaks,and the healthcare institution resilience.Methods:An online questionnaire survey was conducted among the healthcare workforce from 146 institutions in Beijing from January 13,2023 to February 9,2023,and a total of 1 434 eligible respondents were included.The sample comprised 408 responses from tertiary hos-pitals,117 from secondary hospitals,and 909 from primary care institutions.The resilience indicator for healthcare institutions was defined as the degree to which medical services met patient demands,with in-fluencing factors including physical factors,such as material shortages and facility space adaptation or ex-pansion,organizational factors such as information sharing and patient referral,and psychological factors were evaluated using job satisfaction(extrinsic satisfaction,intrinsic satisfaction),burnout(emotional exhaustion,depersonalization,reduced personal accomplishment),and depression status.Ordered mul-ticlassification Logistic regression was used to examine the impact of various factors on the degree to which healthcare services met patient needs;additionally,demographic factors that might influence institutional resilience were controlled.Results:During the emergency response phase,93％of hospitals maintained the capacity to meet patient needs,though tertiary hospitals demonstrated significantly higher rates of service inadequacy(21.05％).Material shortages were reported across all institutions,with tertiary hos-pitals experiencing more frequent multi-item shortages.Inter-institutional collaboration patterns revealed substantial variation:87.50％of primary care facilities,42.86％of secondary hospitals,and 31.58％of tertiary hospitals.Healthcare workers across all levels reported mild depressive symptoms and moderate-to-severe burnout levels.Regression analysis showed high satisfaction(overall satisfaction β=0.04,ex-trinsic satisfaction β=0.06,and intrinsic satisfaction β=0.08),low degree of job burnout(emotional exhaustion β=-0.04,depersonalization β=-0.07 and reduced personal accomplishment β=0.01),low degree of depression(β=-0.06)were significantly associated with higher healthcare institution re-silience.In addition,material shortages were significantly associated with lower resilience,and renova-tion and expansion of treatment spaces,and information sharing,were all associated with higher resilience.Demographic factors(age,gender,marital status,educational background,etc.)had no sig-nificant impact on resilience.Conclusion:Mental health status significantly influences healthcare institu-tion resilience.As human resources constitute the core asset of healthcare institutions,strategic optimiza-tion of workforce allocation and psychological support interventions can effectively strengthen resilience.Moreover,healthcare institution resilience is positively impacted by orderly material supply chains,timely resource distribution,and adaptive reconfiguration of clinical spaces.Finally,facilitating information sharing also enhances institutional resilience.

AIM:To investigate the therapeutic effects and potential mechanism of pachymic acid(PA)on li-popolysaccharide(LPS)-induced acute kidney injury(AKI)in mice.METHODS:(1)Genes related to AKI were screened using the DAVID database.Core genes were identified by intersecting related genes and analyzed using Cyto-scape software.Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)analyses were performed through the DAVID database for the cross-targets.Molecular docking and activity assays were conducted on the primary core targets.(2)A total of 100 C57BL/6J mice were randomly divided into five groups:normal control(NC),model(LPS),solvent control(LPS+DMSO),and treatment groups(LPS+PA-10 and LPS+PA-20),with 20 mice in each group.The LPS-AKI model was established by intraperitoneal injection of 18 mg/kg LPS.The treatment groups received 10 mg/kg and 20 mg/kg PA,respectively,and the solvent control group was administered an equivalent dose of DMSO.Mice were euthanized 24 h after injection.Serum was collected for biochemical analysis,and Western blot was used to detect neutro-phil gelatinase-associated lipocalin(NGAL),kidney injury molecule-1(KIM-1),caspase-3,cleaved caspase-3,interleu-kin-1β(IL-1β),and monocyte chemoattractant protein-1(MCP-1)protein expression.RT-qPCR was employed to detect inflammatory factor mRNA levels.Molecular docking was used to simulate the optimal binding site of PA to caspase-3.En-zyme activity assays were performed to assess caspase protein activity,and renal lesions were observed via hematoxylin and eosin(HE)staining.Apoptosis was detected by TUNEL staining.RESULTS:(1)Thirty-one potential targets of PA against AKI were identified through network pharmacology.GO and KEGG enrichment analyses indicated that these tar-gets were primarily involved in immune response,inflammatory processes,apoptosis and survival,angiogenesis and hemo-dynamics,oxidative stress,and endoplasmic reticulum stress.Key targets included CASP3(caspase-3),PTGS2,BCL2,CCL2,and CYP219.(2)PA treatment improved renal function and reduced tubular epithelial injury.It significantly de-creased NGAL,KIM-1,and cleaved caspase-3 protein levels,as well as inflammatory factors TNF-α,IL-1β,and MCP-1 mRNA and protein expression.PA also reduced apoptosis of renal tubular epithelial cells.Enzyme activity assays and mo-lecular docking revealed that PA exerted its anti-apoptotic effect by directly binding to caspase-3,thereby inhibiting its ac-tivation by caspase-8.CONCLUSION:PA demonstrated a therapeutic effect in LPS-AKI,potentially through the inhibi-tion of inflammatory factor synthesis and release,as well as the inhibition of caspase-3 activation by caspase-8,reducing apoptosis in renal tubular epithelial cells.

Objective:To analyze the epidemiological and clinical features of infectious diseases of the central nervous system (CNS).Methods:A cross-sectional study and analysis were conducted to summarize the epidemiological and clinical characteristics of 9 918 patients with CNS infectious diseases, who were diagnosed and treated at 29 hospitals across China from January 1, 2001 to December 31, 2020. Data collected included demographic data, clinical manifestations, health economic indicators, and prognostic outcomes.Results:Among the 9 918 collected cases of CNS infectious diseases, 5 559 were male (56.0%) and 4 359 were female (44.0%), with an onset age of 38 (25, 53) years. Education level: slightly more junior high school education (2 651 cases, 26.7%), and less elementary school education and below (2 181 cases, 22.0%) were found. Occupational distribution: farmers were found predominant (3 215 cases, 32.4%), followed by workers (1 826 cases, 18.4%) and students (1 633 cases, 16.5%). Clinical manifestations: headache (6 074 cases, 61.2%), fever (5 869 cases, 59.2%) and positive meningeal irritation signs (2 273 cases, 22.9%) were the 3 most common clinical manifestations, followed by nausea and (or) vomiting (2 095 cases, 21.1%), impaired consciousness (2 077 cases, 20.9%), psychiatric symptom (1 866 cases, 18.8%) and epilepsy (1 627 cases, 16.4%), etc., and cranial nerve involvement was found in 669 cases (6.7%). Major pathogens included viruses in 6 814 cases (68.7%), Mycobacterium tuberculosis in 1 677 cases (16.9%), common bacteria in 864 cases (8.7%), fungi in 254 cases (2.6%), spirochetes of syphilis in 183 cases (1.8%), parasites in 121 cases (1.2%), and rickettsiae in 5 cases (0.1%). Urban-rural distribution: slightly more cases were found in the countryside (5 418 cases, 54.6%) than in the towns (4 500 cases, 45.4%). Distribution of onset by season: 2 412 cases (24.3%) fell ill in spring, 2 835 cases (28.6%) in summer, 2 187 cases (22.1%) in fall, and 2 484 cases (25.0%) in winter. Health economics: the duration of hospitalization was 15 (8, 27) days, and the cost of hospitalization was 1.53 (0.91, 3.02)×10 000 yuan. Prognosis: 9 531 cases (96.1%) were cured or improved, and 92 cases (0.9%) died. Conclusions:The pathogens responsible for CNS infectious diseases are predominantly viruses. Although the incidence is slightly higher during the summer months, the overall seasonal pattern is not particularly pronounced. These infections are more commonly observed in young and middle-aged males and present with a diverse range of clinical manifestations, contributing to a significant disease burden.

Objective:To analyze the association between healthcare workers mental health,institu-tional supplies and facilities,inter-organizational coordination during infectious disease outbreaks,and the healthcare institution resilience.Methods:An online questionnaire survey was conducted among the healthcare workforce from 146 institutions in Beijing from January 13,2023 to February 9,2023,and a total of 1 434 eligible respondents were included.The sample comprised 408 responses from tertiary hos-pitals,117 from secondary hospitals,and 909 from primary care institutions.The resilience indicator for healthcare institutions was defined as the degree to which medical services met patient demands,with in-fluencing factors including physical factors,such as material shortages and facility space adaptation or ex-pansion,organizational factors such as information sharing and patient referral,and psychological factors were evaluated using job satisfaction(extrinsic satisfaction,intrinsic satisfaction),burnout(emotional exhaustion,depersonalization,reduced personal accomplishment),and depression status.Ordered mul-ticlassification Logistic regression was used to examine the impact of various factors on the degree to which healthcare services met patient needs;additionally,demographic factors that might influence institutional resilience were controlled.Results:During the emergency response phase,93％of hospitals maintained the capacity to meet patient needs,though tertiary hospitals demonstrated significantly higher rates of service inadequacy(21.05％).Material shortages were reported across all institutions,with tertiary hos-pitals experiencing more frequent multi-item shortages.Inter-institutional collaboration patterns revealed substantial variation:87.50％of primary care facilities,42.86％of secondary hospitals,and 31.58％of tertiary hospitals.Healthcare workers across all levels reported mild depressive symptoms and moderate-to-severe burnout levels.Regression analysis showed high satisfaction(overall satisfaction β=0.04,ex-trinsic satisfaction β=0.06,and intrinsic satisfaction β=0.08),low degree of job burnout(emotional exhaustion β=-0.04,depersonalization β=-0.07 and reduced personal accomplishment β=0.01),low degree of depression(β=-0.06)were significantly associated with higher healthcare institution re-silience.In addition,material shortages were significantly associated with lower resilience,and renova-tion and expansion of treatment spaces,and information sharing,were all associated with higher resilience.Demographic factors(age,gender,marital status,educational background,etc.)had no sig-nificant impact on resilience.Conclusion:Mental health status significantly influences healthcare institu-tion resilience.As human resources constitute the core asset of healthcare institutions,strategic optimiza-tion of workforce allocation and psychological support interventions can effectively strengthen resilience.Moreover,healthcare institution resilience is positively impacted by orderly material supply chains,timely resource distribution,and adaptive reconfiguration of clinical spaces.Finally,facilitating information sharing also enhances institutional resilience.

Objective:To explore the association between the use of tetracyclines during pregnancy and congenital malformations, with the aim of providing evidence-based guidance for the rational use of antibiotics during pregnancy.Methods:Data from the U.S. Food and Drug Administration Adverse Event Reporting System (FAERS) and the Canada Vigilance Adverse Reaction (CVAR) database from January 2015 to September 2024 were collected. Five methods including Tree-based scan statistic (TreeScan), proportional reporting ratio (PRR), reporting odds ratio (ROR), the UK Medicines and Healthcare Products Regulatory Agency (MHRA) comprehensive standard, and the Bayesian confidence propagation neural network (BCPNN) were used to detect signals of risk for congenital malformations in offspring following maternal use of tetracyclines during pregnancy. A signal that met the threshold criteria of all above 5 methods was considered as a risk signal. Based on population-based cohort of the drug exposures and adverse pregnancy outcomes (DEEP) data from January 2013 to December 2021 in Xiamen City, propensity score matching (PSM)-based Poisson regression was applied to evaluate the association between the first-trimester tetracyclines exposure and congenital malformations in offspring. Adjusted relative risk (a RR) and its 95% confidence interval ( CI) were calculated. Sensitivity analysis was conducted to validate the reliability of the results. Results:A total of 304 098 reports of adverse events during pregnancy were obtained from the FAERS and CVAR databases. Among them, 5 028 reports were related to tetracyclines, including 1 026 reports of congenital malformations in offspring, involving congenital malformations of musculoskeletal system, other digestive system, and other congenital malformations. Signal detection results suggested that tetracyclines may be a risk signal for above congenital malformations in offspring. The DEEP data included 411 936 pregnant women. After PSM, 240 pregnant women exposed to tetracyclines were included. The results showed no significant association between the first-trimester tetracyclines exposure and congenital malformations in offspring (a RR=0.75, 95% CI: 0.26-2.17), sensitivity analysis also showed no correlation. Conclusions:Data mining from the FAERS and CVAR databases suggests a potential association between tetracyclines use during pregnancy and congenital malformations in offspring. However, the DEEP data study shows no significant correlation.