Objective To evaluate the predictive ability and clinical application value of artificial intelligence (AI) systems in the benign and malignant differentiation and pathological type of pulmonary nodules, and to summarize clinical application experience. Methods A retrospective analysis was conducted on the clinical data of patients with pulmonary nodules admitted to the Department of Thoracic Surgery, Second Hospital of Lanzhou University, from February 2016 to February 2025. Firstly, pulmonary nodules were divided into benign and non-benign groups, and the discriminative abilities of AI systems and clinicians were compared. Subsequently, lung nodules reported as precursor glandular lesions (PGL), microinvasive adenocarcinoma (MIA), and invasive adenocarcinoma (IAC) in postoperative pathological results were analyzed, comparing the efficacy of AI systems and clinicians in predicting the pathological type of pulmonary nodules. Results In the analysis of benign/non-benign pulmonary nodules, clinical data from a total of 638 patients with pulmonary nodules were included, of which there were 257 males (10 patients and 1 patient of double and triple primary lesions, respectively) and 381 females (18 patients and 1 patient of double and triple primary lesions, respectively), with a median age of 55.0 (47.0, 61.0) years. Different lesions in the same patient were analyzed as independent samples. Univariate analysis of the two groups of variables showed that, except for nodule location, the differences in the remaining variables were statistically significant (P<0.05). Multivariate logistic regression analysis showed that age, nodule type (subsolid pulmonary nodule), average density, spicule sign, and vascular convergence sign were independent influencing factors for non-benign pulmonary nodules, among which age, nodule type (subsolid pulmonary nodule), spicule sign, and vascular convergence sign were positively correlated with non-benign pulmonary nodules, while average density was negatively correlated with the occurrence of non-benign pulmonary nodules. The area under the receiver operating characteristic curve (AUC) of the malignancy risk value given by the AI system in predicting non-benign pulmonary nodules was 0.811, slightly lower than the 0.898 predicted by clinicians. In the PGL/MIA/IAC analysis, clinical data from a total of 411 patients with pulmonary nodules were included, of which there were 149 males (8 patients of double primary lesions) and 262 females (17 patients of double primary lesions), with a median age of 56.0 (50.0, 61.0) years. Different lesions in the same patient were analyzed as independent samples. Univariate analysis results showed that, except for gender, nodule location, and vascular convergence sign, the differences in the remaining variables among the three groups of PGL, MIA, and IAC patients were statistically significant (P<0.05). Multinomial multivariate logistic regression analysis showed that the differences between the parameters in the PGL group and the MIA group were not statistically significant (P>0.05), and the maximum diameter and average density of the nodules were statistically different between the PGL and IAC groups (P<0.05), and were positively correlated with the occurrence of IAC as independent risk factors. The average AUC value, accuracy, recall rate, and F1 score of the AI system in predicting lung nodule pathological type were 0.807, 74.3%, 73.2%, and 68.5%, respectively, all better than the clinical physicians’ prediction of lung nodule pathological type indicators (0.782, 70.9%, 66.2%, and 63.7% respectively). The AUC value of the AI system in predicting IAC was 0.853, and the sensitivity, specificity, and optimal cutoff value were 0.643, 0.943, and 50.0%, respectively. Conclusion This AI system has demonstrated high clinical value in predicting the benign and malignant nature and pathological type of lung nodules, especially in predicting lung nodule pathological type, its ability has surpassed that of clinical physicians. With the optimization of algorithms and the adequate integration of multimodal data, it can better assist clinical physicians in formulating individualized diagnostic and treatment plans for patients with lung nodules.

BACKGROUND: Lung cancer is one of the most common malignant tumors worldwide and a major cause of cancer-related deaths. Early-stage lung cancer is often manifested as pulmonary nodules, and accurate assessment of the malignancy risk is crucial for prolonging survival and avoiding overtreatment. This study aims to construct a model based on image feature parameters automatically extracted by artificial intelligence (AI) to evaluate its effectiveness in predicting the malignancy of part-solid nodule (PSN). METHODS: This retrospective study analyzed 229 PSN from 222 patients who underwent pulmonary nodule resection at Lanzhou University Second Hospital between October 2020 and February 2025. According to pathological results, 45 cases of benign lesions and precursor glandular lesion were categorized into the non-malignant group, and 184 cases of pulmonary malignancies were categorized into the malignant group. All patients underwent preoperative chest computed tomography (CT), and AI software was used to extract imaging feature parameters. Univariate analysis was used to screen significant variables; variance inflation factor (VIF) was calculated to exclude highly collinear variables, and LASSO regression was further applied to identify key features. Multivariate Logistic regression was used to determine independent risk factors. Based on the selected variables, five models were constructed: Logistic regression, random forest, XGBoost, LightGBM, and support vector machine (SVM). Receiver operating characteristic (ROC) curves were used to assess the performance of the models. RESULTS: The independent risk factors for the malignancy of PSN include roughness (ngtdm), dependence variance (gldm), and short run low gray-level emphasis (glrlm). Logistic regression achieved area under the curves ( AUCs) of 0.86 and 0.89 in the training and testing sets, respectively, showing good performance. XGBoost had AUCs of 0.78 and 0.77, respectively, demonstrating relatively balanced performance, but with lower accuracy. SVM showed an AUC of 0.93 in the training set, which decreased to 0.80 in the testing set, indicating overfitting. LightGBM performed excellently in the training set with an AUC of 0.94, but its performance declined in the testing set, with an AUC of 0.88. In contrast, random forest demonstrated stable performance in both the training and testing sets, with AUCs of 0.89 and 0.91, respectively, exhibiting high stability and excellent generalizability. CONCLUSIONS The random forest model constructed based on independent risk factors demonstrated the best performance in predicting the malignancy of PSN and could provide effective auxiliary predictions for clinicians, supporting individualized treatment decisions.
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Humans ; Male ; Female ; Lung Neoplasms/pathology* ; Middle Aged ; Retrospective Studies ; Artificial Intelligence ; Aged ; Tomography, X-Ray Computed ; Adult ; Solitary Pulmonary Nodule/diagnostic imaging* ; ROC Curve

Glutamine provides carbon and nitrogen to support the proliferation of cancer cells. However, the precise reason why cancer cells are particularly dependent on glutamine remains unclear. In this study, we report that glutamine modulates the tumor suppressor F-box and WD repeat domain-containing 7 (FBW7) to promote cancer cell proliferation and survival. Specifically, lysine 604 (K604) in the sixth of the 7 substrate-recruiting WD repeats of FBW7 undergoes glutaminylation (Gln-K604) by glutaminyl tRNA synthetase. Gln-K604 inhibits SCFFBW7-mediated degradation of c-Myc and Mcl-1, enhances glutamine utilization, and stimulates nucleotide and DNA biosynthesis through the activation of c-Myc. Additionally, Gln-K604 promotes resistance to apoptosis by activating Mcl-1. In contrast, SIRT1 deglutaminylates Gln-K604, thereby reversing its effects. Cancer cells lacking Gln-K604 exhibit overexpression of c-Myc and Mcl-1 and display resistance to chemotherapy-induced apoptosis. Silencing both c-MYC and MCL-1 in these cells sensitizes them to chemotherapy. These findings indicate that the glutamine-mediated signal via Gln-K604 is a key driver of cancer progression and suggest potential strategies for targeted cancer therapies based on varying Gln-K604 status.
Glutamine/metabolism* ; Myeloid Cell Leukemia Sequence 1 Protein/genetics* ; Humans ; Proto-Oncogene Proteins c-myc/genetics* ; Cell Proliferation ; Signal Transduction ; Neoplasms/pathology* ; F-Box-WD Repeat-Containing Protein 7/genetics* ; Cell Survival ; Cell Line, Tumor ; Apoptosis

OBJECTIVE: This study aimed to identify high-risk areas for type 2 diabetes mellitus (T2DM) mortality to provide relevant evidence for interventions in emerging economies. METHODS: Empirical Bayesian Kriging and a discrete Poisson space-time scan statistic were applied to identify the spatiotemporal clusters of T2DM mortality. The relationships between economic factors, air pollutants, and the mortality risk of T2DM were assessed using regression analysis and the Poisson Log-linear Model. RESULTS: A coastal district in East Guangdong, China, had the highest risk (Relative Risk [RR] = 4.58, P < 0.01), followed by the 10 coastal districts/counties in West Guangdong, China (RR = 2.88, P < 0.01). The coastal county in the Pearl River Delta, China (RR = 2.24, P < 0.01), had the third-highest risk. The remaining risk areas were two coastal counties in East Guangdong, 16 districts/counties in the Pearl River Delta, and two counties in North Guangdong, China. Mortality due to T2DM was associated with gross domestic product per capita (GDP per capita). In pilot assessments, T2DM mortality was significantly associated with carbon monoxide. CONCLUSION High mortality from T2DM occurred in the coastal areas of East and West Guangdong, especially where the economy was progressing towards the upper middle-income level.
Diabetes Mellitus, Type 2/epidemiology* ; China/epidemiology* ; Humans ; Risk Factors ; Spatio-Temporal Analysis ; Air Pollutants/analysis* ; Socioeconomic Factors ; Bayes Theorem ; Female ; Male ; Middle Aged

OBJECTIVE To mine the cardiovascular safety signal of relugolix， and provide a reference for the listing of this drug in China and future clinical safety drug evaluation. METHODS The adverse event （AE） report data of relugolix， as the primary or secondary suspected drug， was collected from the FDA Adverse Event Reporting System （FAERS） from the first quarter of 2021 to the third quarter of 2023. The reporting odds ratio （ROR） method was used for data mining. The AEs in the FAERS database were identified and coded using preferred terms （PT） stated in version 24.0 of the Medical Dictionary for Drug Regulatory Activities （MedDRA）. The AEs of the target drug were identified by the narrow standardized MedDRA query （SMQ） terms and high-level term （HLT）. Sensitivity analysis was conducted using AEs suspected to be primarily or secondarily related to relugolix or related to drug interaction and concomitant drug， and broad SMQ terms. RESULTS A total of 4 354 relugolix-related AE reports were extracted. In the primary analysis， nine SMQ terms were analyzed， involving 2 positive signals such as dyslipidemia and hyperglycemia/new onset diabetes mellitus. Eleven HLTs were analyzed， and three positive signals were detected for three terms including cholesterol analyses， triglyceride analyses and hyperglycemia conditions （non-alternative analysis）. Sensitivity analysis results indicated the reliability of the study findings. CONCLUSIONS Relugolix may induce risk signals related to high blood lipids and high blood glucose， but no moderate risk signals such as hypertension， heart disease， and stroke are found. During relugolix treatment in clinical practice， attention must be paid to hyperlipidemia and hyperglycemia-related AE.

Background and objective Lung cancer is the cancer with the highest incidence and mortality rates in China,and non-small cell lung cancer(NSCLC)accounts for 80％-85％of all malignant lung tumors.Currently,surgical treat-ment remains the primary treatment modality for lung cancer.In recent years,the effectiveness of immune checkpoint inhibi-tors for NSCLC has become a consensus,and neoadjuvant immunochemotherapy(nICT)has shown promising efficacy and safety in early to intermediate stage NSCLC.However,there are fewer studies related to nICT for locally advanced NSCLC.This study aims to evaluate the efficacy and safety of nICT therapy in locally advanced resectable NSCLC.Methods 85 con-firmed resectable stage ⅢA and ⅢB patients treated in the Department of Thoracic Surgery,Second Hospital of Lanzhou University,from January 2021 to April 2024,were divided into the nICT group(n=32)and the surgery alone group(n=53).Clinical baseline data,perioperative indicators,postoperative complications,imaging response rate,pathological response rate,incidence of adverse events,and quality of life were compared between the two groups.Results There were no statisti-cally significant differences in clinical baseline data between the two groups(P＞0.05).Incidence of choosing thoracotomy was higher in the nICT group than in the surgery alone group(P=0.002).There were no significant differences in surgical time,intraoperative blood loss,number of dissected lymph nodes,duration of chest tube placement,postoperative hospital stay,and R0 resection rate between the two groups(P＞0.05).The overall incidence of postoperative complications was 31.25％in the nICT group and 22.64％in the surgery alone group,with no statistically significant difference(P=0.380).In the nICT group,the objective response rate(ORR)was 84.38％,with 5 cases of complete response(CR)(15.63％),22 cases of partial response(PR)(68.75％),15 cases of pathological response rate(pCR)(46.88％),and 11 cases of major pathological reaponse(MPR)(34.38％).During nICT treatment,12 cases(37.50％)experienced grade 3 treatment-related adverse events,no death induced by adverse events or immune related adverse events.Moreover,the symptoms of the patients were improved after nICT treat-ment.Conclusion Neoadjuvant immunochemotherapy shows promising efficacy in locally advanced resectable NSCLC,with manageable treatment-related adverse events.It is a safe and feasible neoadjuvant treatment modality for locally advanced resectable NSCLC.

Objective:To report the results of national surveillance on the distribution and antimicrobial resistance profile of clinical Gram-negative bacteria isolates from bloodstream infections in China in 2022.Methods:The clinical isolates of Gram-negative bacteria from blood cultures in member hospitals of national bloodstream infection Bacterial Resistant Investigation Collaborative System（BRICS）were collected during January 2022 to December 2022. Antibiotic susceptibility tests were conducted by agar dilution or broth dilution methods recommended by Clinical and Laboratory Standards Institute（CLSI）. WHONET 5.6 and SPSS 25.0 software were used to analyze the data.Results:During the study period，9 035 strains of Gram-negative bacteria were collected from 51 hospitals，of which 7 895（87.4%）were Enterobacteriaceae and 1 140（12.6%）were non-fermenting bacteria. The top 5 bacterial species were Escherichia coli（ n=4 510，49.9%）， Klebsiella pneumoniae（ n=2 340，25.9%）， Pseudomonas aeruginosa（ n=534，5.9%）， Acinetobacter baumannii complex（ n=405，4.5%）and Enterobacter cloacae（ n=327，3.6%）. The ESBLs-producing rates in Escherichia coli， Klebsiella pneumoniae and Proteus spp. were 47.1%（2 095/4 452），21.0%（427/2 033）and 41.1%（58/141），respectively. The prevalence of carbapenem-resistant Escherichia coli（CREC）and carbapenem-resistant Klebsiella pneumoniae（CRKP）were 1.3%（58/4 510）and 13.1%（307/2 340）；62.1%（36/58）and 9.8%（30/307）of CREC and CRKP were resistant to ceftazidime/avibactam combination，respectively. The prevalence of carbapenem-resistant Acinetobacter baumannii（CRAB）complex was 59.5%（241/405），while less than 5% of Acinetobacter baumannii complex was resistant to tigecycline and polymyxin B. The prevalence of carbapenem-resistant Pseudomonas aeruginosa（CRPA）was 18.4%（98/534）. There were differences in the composition ratio of Gram-negative bacteria in bloodstream infections and the prevalence of main Gram-negative bacteria resistance among different regions，with statistically significant differences in the prevalence of CRKP and CRPA（ χ2=20.489 and 20.252， P<0.001）. The prevalence of CREC，CRKP，CRPA，CRAB，ESBLs-producing Escherichia coli and Klebsiella pneumoniae were higher in provinicial hospitals than those in municipal hospitals（ χ2=11.953，81.183，10.404，5.915，12.415 and 6.459， P<0.01 or <0.05），while the prevalence of CRPA was higher in economically developed regions（per capita GDP ≥ 92 059 Yuan）than that in economically less-developed regions（per capita GDP <92 059 Yuan）（ χ2=6.240， P=0.012）. Conclusions:The proportion of Gram-negative bacteria in bloodstream infections shows an increasing trend，and Escherichia coli is ranked in the top，while the trend of CRKP decreases continuously with time. Decreasing trends are noted in ESBLs-producing Escherichia coli and Klebsiella pneumoniae. Low prevalence of carbapenem resistance in Escherichia coli and high prevalence in CRAB complex have been observed. The composition ratio and antibacterial spectrum of bloodstream infections in different regions of China are slightly different，and the proportion of main drug resistant bacteria in provincial hospitals is higher than those in municipal hospitals.

The ICR(Institute of Cancer Research)mouse infection model was constructed to study the pathogenicity of Sal-monella Telelkebir serotype,and the pathogenic identification of mouse isolates was carried out.Observe the bacterial excretion cycle,evaluate the pathogenicity of Salmonella serotype to mice,and calculate the LD50 by the changes in clinical characteris-tics,histopathology and tissue bacterial load of infected mice;by flight mass spectrometry,biochemical identification,serotype identification,molecular typing and other experiments,compared with human isolates;virulence gene analysis was carried out by PCR experiment and whole genome sequencing.The LD50 of Salmonella Telelkebir is 2.67 × 108 CFU/mL;curling and fluffing may occur 0.5 h after infection;autopsy of dead mice showed that the small intestine was severely congested,with more bubbles and fluid accumulation,cecal necrosis,liver apical degeneration and necrosis,necrotic foci on the surface of the kidney and spleen atrophy;the bacterial load of spleen,kidney,lung,liver and jejunum in mice reached its peak at 3 days after infection,while that of heart at 6 days;the bacterial excretion time of the high-dose group exceeded 100 days;The level of CD3 in tissues increased with increasing dose,with inflammatory cell infiltration,myocardial capillary dilation and hyperemia,large area of vacuoles,degeneration and necrosis of hepatocytes,obvious enlargement of splenic sinus,blurred zoning,thickening of glomerular basement membrane,partial exfoliation of ciliated epithelium,atrophy and exfoliation of jejunal villi;PCR and whole genome sequencing revealed Salmonella-related virulence genes such as cdtB,plt A and pltB.This study was the first to successfully establish the ICR mouse model of Salmonella Telelkebir,demonstrating that this serotype of Salmonella has some pathogenicity.

Objective To study the effect of high mobility group box B1(HMGB1)gene knockout on alleviating a-cute lung injury and inhibiting toll-like receptor 4(TLR4)/nuclear factor-KB(NF-κB)pathway of sepsis mice.Methods Wild-type(WT)mice were divided into WT-Sham group and WT-model group,and HMGB1 knockout(KO)mice were divided into KO-sham group and KO-model group.Sepsis ALI model was established by cecal ligation and perforation in WT-model group and KO-model group.Sham operation was performed in WT-Sham group and KO-Sham group.24 h after modeling,the partial pressure of arterial oxygen(PaO2)was detected,oxy-genation index(OI)was calculated,pathological changes of lung tissue were detected and lung injury score was calculated,the concentrations of tumor necrosis factor-α(TNF-α),interleukin-1 β(IL-1 β),interleukin-6(IL-6),reactive oxygen species(ROS),malondialdehyde(MDA),superoxide dismutase(SOD),in serum and lung tissues and the expression of HMGB1,TLR4 and nuclear NF-κB in lung tissues were detected.Results The PaO2,OI and the concentration of SOD in serum and lung tissue of WT-model group were lower than those of WT-Sham group,the lung injury scores,the concentrations of TNF-α,IL-1 β,IL-6,ROS and MDA in serum and lung tissue,and the expression levels of HMGB1,TLR4 and nuclear NF-κB in lung tissue were higher than those in WT-Sham group(P＜0.05).HMGB1 was not expressed in lung tissue of KO-model group,and the concentrations of PaO2,OI and the concentration of SOD in serum and lung tissue of KO-model group were higher than those of WT-model group,the lung injury scores,the concentrations of TNF-α,IL-1β,IL-6,ROS and MDA in serum and lung tissue,and the expression levels of TLR4 and nuclear NF-κB in lung tissue were lower than those of the WT-model group(P＜0.05).Conclusion HMGB1 gene knockout alleviates acute lung injury of sepsis mice,the re-lated molecular mechanism may be the inhibition of TLR4/NF-κB pathway mediated inflammation and oxidative stress.

Chemical cleaning and disinfection are crucial steps for eliminating infection in root canal treatment.However,irrigant selection or irrigation procedures are far from clear.The vapor lock effect in the apical region has yet to be solved,impeding irrigation efficacy and resulting in residual infections and compromised treatment outcomes.Additionally,ambiguous clinical indications for root canal medication and non-standardized dressing protocols must be clarified.Inappropriate intracanal medication may present side effects and jeopardize the therapeutic outcomes.Indeed,clinicians have been aware of these concerns for years.Based on the current evidence of studies,this article reviews the properties of various irrigants and intracanal medicaments and elucidates their effectiveness and interactions.The evolution of different kinetic irrigation methods,their effects,limitations,the paradigm shift,current indications,and effective operational procedures regarding intracanal medication are also discussed.This expert consensus aims to establish the clinical operation guidelines for root canal irrigation and a position statement on intracanal medication,thus facilitating a better understanding of infection control,standardizing clinical practice,and ultimately improving the success of endodontic therapy.