ObjectiveThis study aimed to investigate the anti-Mycoplasma pneumoniae (MP) activity of luteolin and elucidate its underlying mechanisms. MethodsLuteolin was identified as the primary active compound from the polyphenol extract ofF. diotrys using network pharmacology. Its efficacy was evaluated against two MP strains: the standard strain M129 and the multidrug-resistant strain M19. A modified culture medium with visual characteristics was employed to determine the minimum inhibitory concentration (MIC) of luteolin. The expression of key proteins involved in MP growth and pathogenicity was assessed by qRT-PCR following luteolin treatment. Additionally, the viability of A549 cells infected with MP was compared between luteolin-treated and untreated groups. In vivo anti-MP activity was evaluated using a mouse model, and the expression of inflammatory cytokines in lung tissues was analyzed. ResultsLuteolin effectively inhibited both MP strains, with MIC₉₀ values of 100 mg/L for M19 and M129. Treatment with luteolin significantly downregulated the expression of adhesion proteins P1 and P30 in both strains. However, the expression of P65, HMW3, TrmB, and CARDS TX was reduced only in the M19 strain following luteolin intervention. Luteolin also enhanced the growth and viability of A549 cells infected with MP. In the mouse model, luteolin treatment resulted in steady weight gain and was well tolerated. The bacteriostatic rate of luteolin in lung tissues was 50.7%, significantly higher than the 25.2% observed in the roxithromycin group. Furthermore, luteolin reduced the expression of inflammatory factors, including IL-6, TNF-α, and HMGB1, in MP-infected mice. ConclusionLuteolin effectively and safely inhibits the proliferation and pathogenicity of MP, particularly the drug-resistant M19 strain, by downregulating the expression of toxicity-associated proteins (P1, P30, P65, HMW3, TrmB, CARDS TX) and modulating host inflammatory responses. These findings suggest that luteolin may offer a novel therapeutic strategy for treating MP infections, especially those caused by drug-resistant strains.

ObjectiveThis study aimed to investigate the anti-Mycoplasma pneumoniae (MP) activity of luteolin and elucidate its underlying mechanisms. MethodsLuteolin was identified as the primary active compound from the polyphenol extract ofF. diotrys using network pharmacology. Its efficacy was evaluated against two MP strains: the standard strain M129 and the multidrug-resistant strain M19. A modified culture medium with visual characteristics was employed to determine the minimum inhibitory concentration (MIC) of luteolin. The expression of key proteins involved in MP growth and pathogenicity was assessed by qRT-PCR following luteolin treatment. Additionally, the viability of A549 cells infected with MP was compared between luteolin-treated and untreated groups. In vivo anti-MP activity was evaluated using a mouse model, and the expression of inflammatory cytokines in lung tissues was analyzed. ResultsLuteolin effectively inhibited both MP strains, with MIC₉₀ values of 100 mg/L for M19 and M129. Treatment with luteolin significantly downregulated the expression of adhesion proteins P1 and P30 in both strains. However, the expression of P65, HMW3, TrmB, and CARDS TX was reduced only in the M19 strain following luteolin intervention. Luteolin also enhanced the growth and viability of A549 cells infected with MP. In the mouse model, luteolin treatment resulted in steady weight gain and was well tolerated. The bacteriostatic rate of luteolin in lung tissues was 50.7%, significantly higher than the 25.2% observed in the roxithromycin group. Furthermore, luteolin reduced the expression of inflammatory factors, including IL-6, TNF-α, and HMGB1, in MP-infected mice. ConclusionLuteolin effectively and safely inhibits the proliferation and pathogenicity of MP, particularly the drug-resistant M19 strain, by downregulating the expression of toxicity-associated proteins (P1, P30, P65, HMW3, TrmB, CARDS TX) and modulating host inflammatory responses. These findings suggest that luteolin may offer a novel therapeutic strategy for treating MP infections, especially those caused by drug-resistant strains.

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 gain insights into the biological characteristics of different populations of Culex tritaeniorhynchus within and around the Yellow Sea wetland from the perspective of the occurrence of resistance, we investigated the levels of resistance to deltamethrin and kdr gene mutation in the wetland and its peripheral areas. Methods Specimens were collected from Cx. tritaeniorhynchus populations at two monitoring sites in the Rare Bird National Nature Reserve and Tiaozi Ni Wetland Scenic Area, and also from two populations in Yancheng City and the Liuhe District of Nanjing, and the resistance of these mosquitoes to deltamethrin was determined using the CDC biotest bottle method. For each concentration of deltamethrin assessed, a random subset of exposed specimens was selected for amplification of the kdr gene fragment, followed by Sanger sequencing to identify and analyze resistance-associated mutations. Results The LC50 levels of deltamethrin among mosquitoes from the four populations in Luhe, Yancheng, the Rare Bird National Nature Reserve and the Tiaozi Ni Wetland Scenic Area were 2.048 5, 7.798 2, 3.473 3, and 17.695 5 mg/mL, respectively, with corresponding concentrations of deltamethrin ranging from 0.005 to 5.000,0.050 to 50.000,0.050 to 25.000 and 0.050 to 50.000 mg/mL, respectively. Furthermore, the ranges of the KT50 values were 11.76-107.43, 67.05-216.30,29.77-107.43 and 28.40-329.51 min; the 1-h knockdown rates were 34.58%-99.15%, 9.52%-43.80%, 55.09%-73.01%, and 10.09%-68.07%; and the 24-h mortality rates were 12.15%-67.52%,9.52%-79.56%,13.17%-82.21%, and 11.01%-78.99%, respectively. With respect to kdr gene mutation, we assayed a total of 63,70,59, and 57 mosquitoes for the four populations, for which we detected L1014F mutation frequencies of 14.29%, 35.00%, 20.34%, and 31.58%, respectively, with a majority of these mutations being heterozygous for resistance. In addition, five adult mosquitoes were identified has having synonymous mutations at site 1011[i. e. , AAT(asparagine)mutation to AAC(asparagine)]. Conclusions Our findings revealed the clear resistance of Cx. tritaeniorhynchus to deltamethrin in the Yancheng region of the Yellow Sea wetland, and the resistance phenotype and kdr frequency of Cx. tritaeniorhynchus in the wetland environment were comparable to those of Cx. tritaeniorhynchus in the wetland environment, thereby indicating that the resistance of different populations of Cx. tritaeniorhynchus was homogeneous under the pressure of different insecticide selection within and around the wetland. However, the underlying mechanisms need to be further studied.

Background and aims The mechanism of cholestatic liver injury (CLI) is unclear, and effective therapies are lacking. While peroxisome proliferator-activated receptor alpha (PPARα) agonists show potential hepatoprotective effect and pyroptosis is implicated in hepatocellular damage, how PPARα activation mitigates lithocholic acid (LCA)-induced pyroptosis remains unknown. Methods The hepatoprotective effect of PPARα agonists was evaluated in a mouse model of intrahepatic cholestasis induced by LCA. Liver injury was assessed via serum biochemistry, hematoxylin and eosin and TUNEL staining, and electron microscopy. Pyroptosis pathways were analyzed using real-time quantitative polymerase chain reaction, Western blot, and co-immunoprecipitation. Results Combined morphological, histopathological, and biochemical analyses confirmed that PPARα activation protects against CLI. Compared with LCA treatment alone, PPARα activation significantly attenuated the elevation of serum lactate dehydrogenase (LDH), the increased TUNEL-positive cells, and the formation of hepatocyte membrane pores. Mechanistically, PPARα activation suppressed both NOD-like receptor protein 3 (NLRP3) inflammasome-mediated pyroptosis and apoptosis protease-activating factor-1 (APAF-1)/CASPASE-3/GSDME-mediated pyroptosis. Furthermore, PPARα agonist pretreatment inhibited activation of the nuclear factor-kappa B (NF-κB) and forkhead box O1 (FOXO1) signaling pathways. Conclusions PPARα protects against LCA-induced CLI by inhibiting both NLRP3 inflammasome-mediated pyroptosis associated with NF-κB and APAF-1/CASPASE-3/GSDME-mediated pyroptosis associated with the FOXO1 signaling pathway.

ObjectiveColorectal cancer (CRC) is a highly heterogeneous malignancy, and traditional Chinese medicine (TCM) syndrome differentiation is widely used in its clinical management. However, the biological basis underlying different TCM syndromes remains insufficiently understood. This study aimed to investigate the proteomic differences between qi-blood deficiency syndrome (QBDS) and damp-heat syndrome (DHS) in CRC patients and to establish a “syndrome-differential protein-herbal component” network for exploring potential molecular mechanisms and therapeutic targets associated with syndrome-specific treatment strategies. MethodsTumor tissue samples were collected from 10 patients with pathologically confirmed CRC, including 5 patients diagnosed with QBDS and 5 with DHS according to standardized TCM syndrome differentiation criteria. Tandem mass tag (TMT)-based quantitative proteomics was employed to identify differentially expressed proteins (DEPs) between the two syndrome groups. Functional enrichment analyses, including Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses, were performed to characterize the biological functions and signaling pathways associated with the identified DEPs. Least absolute shrinkage and selection operator (LASSO) regression analysis was further applied to screen key syndrome-related proteins and construct a core protein prediction model. Subsequently, molecular docking was conducted to evaluate the binding affinities between representative herbal compounds, astragaloside IV and berberine, and the identified core proteins. Finally, cell counting kit-8 (CCK-8) assays were performed in HCT 116 and HT-29 colorectal cancer cell lines to validate the anti-proliferative activities of these compounds in vitro. ResultsA total of 44 DEPs were identified between QBDS and DHS tissues, including 21 upregulated and 23 downregulated proteins in the QBDS group relative to the DHS group. Functional enrichment analyses revealed that these proteins were primarily associated with antiviral immune responses, regulation of inflammatory signaling, NF‑κB signaling pathways, cholesterol metabolism, and other biological processes relevant to tumor progression and host immune regulation. LASSO regression analysis identified eight core proteins with potential syndrome-specific significance. Among them, ST7, GPCPD1, and PODXL were closely associated with QBDS, whereas FAT1, GRB7, KRT7, MAFF, and MMP8 were associated with DHS. Molecular docking demonstrated favorable interactions between astragaloside IV and QBDS-related proteins, with binding energies lower than -5 kcal/mol, indicating stable binding activity. Berberine exhibited even lower binding energies and stronger binding specificity toward DHS-related core proteins. In vitro experiments further confirmed that both compounds inhibited CRC cell proliferation, while berberine displayed significantly greater anti-proliferative efficacy. The lowest 48 h IC₅₀ value of berberine reached 15.21 mg/L in CRC cells, indicating a stronger growth-inhibitory effect than astragaloside IV. ConclusionCRC patients with QBDS and DHS exhibit distinct proteomic characteristics, suggesting that different TCM syndromes possess unique molecular signatures. The identified core proteins may serve as potential biomarkers for syndrome differentiation, while astragaloside IV and berberine may exert therapeutic effects through targeting syndrome-specific molecular networks. These findings provide preliminary proteomic evidence supporting syndrome-guided precision integrative medicine in CRC and offer new insights into the biological basis of TCM syndrome differentiation and individualized therapeutic strategies.

Nitrofurazone(NFZ)is an antibiotic that is used as a veterinary drug in aquaculture.NFZ abuse can lead to a series of environmental and health issues,making it crucial to establish a rapid and highly sensitive method for NFZ detection.In this study,platinum nanoparticle(PtNPs)-loaded zeolitic imidazolate framework(ZIF-8)was used as a precursor,and PtNPs functionalized nitrogen doped porous carbon(NC)was obtained through pyrolysis.Pt@NC was combined with multi-walled carbon nanotubes(MWCNTs)and cast onto a glassy carbon electrode(GCE)surface to construct an electroch-emical sensor.Electrochemical tests revealed that Pt@NC/WCNT/GCE exhibited an electrochemical active area of 0.066 cm2 and a heterogeneous electron transfer rate constant(k0)of 2.03×10-3 cm/s,which were higher than other materials.Compared with the electrodes modified by other materials,the NFZ generated the highest peak current of irreversible reduction peak on the Pt@NC/WCNT/GCE electrode.In comparison with Pt@ZIF-8/WCNT/GCE,after pyrolysis and carbonization treatment,the reduction current of NFZ increased by 2.19 times,and the reduction peak potential shifted positively by 19 mV simultaneously.When compared with NC/WCNT/GCE,the PtNPs in the composite material enhanced the NFZ current by 4.25 times.Additionally,the experimental conditions for detecting NFZ using the sensor were optimized,including the carbonization temperature of Pt@ZIF-8,ratio of Pt@NC to CNT,loading amount of the modified material,and electrolyte pH.Under the optimized conditions,the sensor demonstrated a linear detection range for NFZ of 0.20-240 μmol/L,a sensitivity of 9.995 μA/((μmol/L)?cm2)and a limit of detection(LOD)of 0.06 μmol/L.The sensor exhibited excellent anti-interference capability,good reproducibility,and stability,with spiked recoveries for NFZ in water samples ranging from 94.6%to 105.6%.This study provided a novel electrochemical sensing approach for NFZ detection.

Objective To construct a nomogram prediction model for predicting hemoglobin A1c(HbA1c)failure in type 2 diabetes mellitus(T2DM)patients.Methods A total of 936 inpatients with T2DM admitted to the Department of Endocrinology of the Affiliated Hospital of Shandong Second Medical University from January 2021 to January 2022 were selected as the research objects and divided into the non-standard group(HbA1c≥7%,n=801)and the standard group(HbA1c<7%,n=135).Univariate analysis was used to screen the related factors of HbA1c failure.Logistic regression multivariate model was used to analyze the influencing factors of HbA1c failure in T2DM patients.The R language was used to construct a nomogram,and the area under the receiver operating characteristic(ROC)curve(AUC)was used to evaluate the predictive ability of the model.The C-index and Hosmer-Lemeshow test were used to evaluate the discrimination and calibration of the model.Results There were statistically significant differences in triglyceride(TG),low-density lipoprotein cholesterol,direct bilirubin,urinary albumin/creatinine ratio(UACR),self-monitoring of blood glucose(SMBG),meat and vegetable pairing,hot pot,whole grain and animal viscera consumption between the two groups(P<0.05).Logistic regression analysis showed that TG(OR 1.699,95%CI 1.298～2.222),UACR(OR 1.003,95%CI 1.001～1.005),SMGB(OR 0.480,95%CI 0.313～0.735),more meat and less vegetables(OR 1.432,95%CI 1.062～1.931)were the influencing factors of HbA1c failure.The AUC of the nomogram prediction model based on the influencing factors was 0.711,with C-index 0.710(95%CI 0.663～0.758)and good calibration(χ2=11.185,P=0.191).Conclusions The nomogram prediction model for HbA1c failure in T2DM patients established based on TG,UACR,SMGB,meat and vegetarian mix has good discrimination and calibration,which can provide certain reference value for warning of poor blood glucose control.

Objective:To evaluate the training efficacy of the autonomic nervous system stability assessing and enhancing capsule (hereinafter referred to as the EC), and to study the difference in physiological indicators for autonomic nervous system stability training between the EC and a non-capsule environment.Methods:A total of 1 478 male military pilots under autonomic nervous system stability training between February 2022 and February 2024 were selected before they completed training sessions in both the EC and a non-capsule environment. The pre-training time-domain and frequency-domain indices of heart rate variability (HRV) and the 0.1 Hz index were compared with the post-training ones, and across difficulty levels (low, moderate, and high). The difference that the EC made in relaxation training was analyzed.Results:①Time-domain indices of HRV were of statistical significance in the main effects of training difficulty, those of training environments, and their interactions ( F=4.40-160.80, all P<0.05 or 0.01). Simple effect analysis revealed that in the same phase of training the standard deviation of all NN intervals (SDNN) at the low level of difficulty in the EC was lower than in the non-capsule environment. However, all time-domain indices after training were higher in the EC than in the non-capsule environment. The differences were statistically significant (all P<0.05 or 0.01).②For frequency-domain HRV indices, significant differences were observed in both the main effect of training difficulty and the interactions ( F=4.40-1 524.33, all P<0.01). Very low frequency power (VLF), high frequency (HF), the ratio of low frequency to high frequency (LF/HF), normalized low frequency (LFnorm), and normalized high frequency (HFnorm) were significantly different in the main effect of training environments ( F=4.24, 12.00, 6.91, 23.39, 23.39, P=0.040, <0.001, =0.009, <0.001, <0.001). Simple effect analysis revealed that at the same level of training difficulty, the EC delivered significantly lower values of LF and LFnorm but higher values of HF and HFnorm than the non-capsule environment before training (all P<0.05). VLF across levels of training difficulty and LF/HF at the high level of difficulty level were significantly lower in the EC than in the non-capsule environment. After training, total power, VLF, LF, HF, and HFnorm were significantly higher in the EC than in the non-capsule environment, but LF/HF and LFnorm were significantly lower (all P<0.05). ③For the 0.1 Hz index, significant differences were observed in both the main effect of training difficulty and the interactions ( F=2 147.75, 6.63, both P<0.001). Subsequent simple effect analysis revealed that at the same level of training difficulty, 0.1 Hz indices of pilots in the EC were lower than in the non-capsule environment before and after training (all P<0.01). Conclusions:During the autonomic nervous system stability training, the EC can effectively and quickly regulate and alleviate pilots′ fatigue and stress. Furthermore, it provides sustained autonomic nervous system training, thereby stabilizing pilots′ autonomic nervous system.

In recent decades,the incidence of human papillomavirus(HPV)-associated oropharyngeal squamous cell carcinoma(OPSCC)has shown a marked increase.Significant changes have also occurred in the OPSCC diagnosis and treatment paradigm.Deter-mining HPV status prior to treatment is now essential,and radiotherapy/chemotherapy,immunotherapy,and minimally invasive surgical techniques have progressively emerged as key modalities for managing OPSCC.However,alongside these paradigm shifts,a comprehen-sive technical consensus guiding the entire diagnostic and therapeutic process for OPSCC patients is currently lacking.Given China's large population base and the rising incidence of OPSCC,an expert panel convened to develop a clinical technical consensus on OPSCC diagno-sis and management tailored to China's specific context.This consensus aims to further enhance and standardize understanding of OPSCC management techniques among relevant healthcare professionals.