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.

ObjectiveTo construct an evaluation index system for public health emergency response capacity within the healthcare-associated infection prevention and control systems using the Delphi method, and to provide a basis for infection control management in municipal hospitals. MethodsBased on literature analyses and theoretical researches, a preliminary evaluation index system for response capacity was constructed. The Delphi method was employed to conduct two rounds of consultation with 17 experts. The Analytic Hierarchy Process (AHP) was used to calculate the weights of the indicators. ResultsThe effective questionnaire return rates for both rounds of expert consultation were 100%. The expert authority coefficients for the first and second rounds were 0.97 and 0.95, respectively. Kendall’s W coefficients ranged from 0.31 to 0.58 in the first round and from 0.45 to 0.58 in the second round, with all differences being statistically significant (P<0.01). After two rounds of expert consultation, the municipal-level hospital infection prevention and control system emergency response capacity evaluation index system was finalized, comprising 5 first-level indicators, 18 second-level indicators and 59 third-level indicators. ConclusionThe constructed public health emergency response capacity evaluation index system for municipal-level hospital infection prevention and control systems demonstrates strong scientific rigor, reliability, and practicality, providing a theoretical foundation and valuable reference for enhancing the infection prevention and control capacity of municipal-level hospitals.

OBJECTIVE: To investigate the common mechanisms among collagen-induced arthritis (CIA), bleomycin (BLM)-induced pulmonary fibrosis, and CIA+BLM to evaluate the therapeutic effect of triptolide (TP) on CIA+BLM. METHODS: Thirty-six male Sprague-Dawley rats were randomly assigned to 6 groups according to a random number table (n=6 per group): normal control (NC), CIA, BLM, combined CIA+BLM model, TP low-dose (TP-L, 0.0931 mg/kg), and TP high-dose (TP-H, 0.1862 mg/kg) groups. The CIA model was induced by intradermal injection at the base of the tail with emulsion of bovine type II collagen and incomplete Freund's adjuvant (1:1), with 200 µL administered on day 0 and a booster of 100 µL on day 7. Pulmonary fibrosis was induced via a single intratracheal injection of BLM (5 mg/kg). The CIA+BLM model combined both protocols, and TP was administered orally from day 14 to 35. After successful modeling, arthritis scores were recorded every 3 days, and pulmonary function was assessed once at the end of the treatment period. Lung tissues were collected for histological analysis (hematoxylin eosin and Masson staining), immunohistochemistry, measurement of hydroxyproline (HYP) content, and calculation of lung coefficient. In addition, HE staining was performed on the ankle joint. Total RNA was extracted from lung tissues for transcriptomic analysis. Differentially expressed genes (DEGs) were compared with those from the RA-associated interstitial lung diseases patient dataset GSE199152 to identify overlapping genes, which were then used to construct a protein-protein interaction network. Hub genes were identified using multiple topological algorithms. RESULTS: The successfully established CIA+BLM rat model exhibited significantly increased arthritis scores and severe pulmonary fibrosis (P<0.01). By intersecting the DEGs obtained from transcriptomic analysis of lung tissues in CIA, BLM, and CIA+BLM rats with DEGs from rheumatoid arthritis-interstitial lung disease patients (GSE199152 dataset), 50 upregulated and 44 downregulated genes were identified. Through integrated PPI network analysis using multiple topological algorithms, IGF1 was identified as a central hub gene. TP intervention significantly improved pulmonary function by increasing peak inspiratory flow (P<0.01), and reduced lung index and HYP content (P<0.01). Histopathological analysis showed that TP alleviated alveolar collapse, interstitial thickening, and collagen deposition in the lung tissues (P<0.01). Moreover, TP treatment reduced the expression of collagen type I and α-SMA and increased E-cadherin levels (P<0.01). TP also significantly reduced arthritis scores and ameliorated synovial inflammation (P<0.05). Both transcriptomic and immunohistochemical analyses confirmed that IGF1 expression was elevated in the CIA+BLM group and downregulated following TP treatment (P<0.05). CONCLUSION TP exerts protective effects in the CIA+BLM model by alleviating arthritis and pulmonary fibrosis through the inhibition of IGF1-mediated EMT.
Animals ; Pulmonary Fibrosis/complications* ; Bleomycin/adverse effects* ; Phenanthrenes/pharmacology* ; Male ; Rats, Sprague-Dawley ; Diterpenes/pharmacology* ; Epoxy Compounds/therapeutic use* ; Arthritis, Experimental/complications* ; Insulin-Like Growth Factor I/metabolism* ; Rats ; Lung/physiopathology*

Taxifolin (TAX) is a natural compound known for its liver protection effect, but the mechanism remains unknown. Phosphorylated proteomics analyses discovered that the phosphorylation level of NDRG1 at T328 was a key event of TAX-improved liver fibrosis. We established models with NDRG1 knockout (KO) in vivo and in vitro, demonstrating that NDRG1 KO attenuated the development of hepatocyte injury, and combining NDRG1 KO and TAX administration did not result in a reduction in protection against liver injury. Cellular thermal shift assay and surface plasma resonance analysis showed that TAX directly binds to NDRG1 rather than its upstream kinase, subsequently demonstrating that TAX regulated phosphorylation of NDRG1 at T328 through binding to its C289 site. NDRG1 T328A (phosphorylated mutation) and T328E (mimic phosphorylation) in vivo and in vitro confirmed that pNDRG1_T328 exacerbates hepatocyte injury along with DNA damage, inflammatory response, and apoptosis, thereby contributing to hepatic stellate cells (HSCs) activation. In contrast, TAX can inhibit the above pathological abnormalities and block hepatocyte injury-triggered HSCs activation and fibrosis. Overall, TAX is a potent liver protection drug primarily targeting NDRG1 and inhibiting pNDRG1_T328 in hepatocytes.

The continuous emergence of SARS-CoV-2 variants as well as other potential future coronavirus has challenged the effectiveness of current COVID-19 vaccines. Therefore, there remains a need for alternative antivirals that target processes less susceptible to mutations, such as the formation of six-helix bundle (6-HB) during the viral fusion step of host cell entry. In this study, a novel high-throughput screening (HTS) assay employing a yeast-two-hybrid (Y2H) system was established to identify inhibitors of HR1/HR2 interaction. The compound IMB-9C, which achieved single-digit micromolar inhibition of SARS-CoV-2 and its Omicron variants with low cytotoxicity, was selected. IMB-9C effectively blocks the HR1/HR2 interaction in vitro and inhibits SARS-CoV-2-S-mediated cell-cell fusion. It binds to both HR1 and HR2 through non-covalent interaction and influences the secondary structure of HR1/HR2 complex. In addition, virtual docking and site-mutagenesis results suggest that amino acid residues A930, I931, K933, T941, and L945 are critical for IMB-9C binding to HR1. Collectively, in this study, we have developed a novel screening method for HR1/HR2 interaction inhibitors and identified IMB-9C as a potential antiviral small molecule against COVID-19 and its variants.

OBJECTIVES: To evaluate the impact of HBV infection on pre- and postpartum health-related quality of life (HRQoL) in pregnant women. METHODS: A prospective matched cohort consisting of 70 HBV-infected and 70 healthy pregnant women was recruited from the Fifth Affiliated Hospital of Guangzhou Medical University between April 17 and September 25, 2023. HRQoL of the participants was assessed at 16-24 weeks of gestation, between 32 weeks and delivery, and 5-13 weeks postpartum. Mixed linear models were used for evaluating temporal trends of HRQoL changes, and univariate ANOVA with multiple linear regression was used to identify the predictors of HRQoL. RESULTS: Compared with healthy pregnant women, HBV-infected pregnant women had consistently lower total HRQoL scores across all the 3 intervals, with the lowest scores observed between 32 weeks of gestation and delivery, during which these women had significantly reduced mental component scores (74.27±13.43 vs 80.21±12.9, P=0.009) and postpartum mental (76.52±16.19 vs 85.02±6.51, P<0.001) and physical component scale scores (77.17±14.71 vs 83.09±10.1, P=0.009). HBV infection was identified as an independent risk factor affecting HRQoL during late pregnancy and postpartum periods. Additional independent risk factors for postpartum HRQoL reduction included self-pay medical expenses, spouse's neutral attitude toward the current pregnancy, and preexisting comorbidities (all P<0.05). CONCLUSIONS HRQoL of pregnant women deteriorates progressively in late pregnancy, and HBV infection exacerbates reductions of physical function and role emotion in late pregnancy and after delivery, suggesting the importance of targeted interventions for financial burdens, partner support and comorbid conditions to improve HRQoL of pregnant women with HBV infection.
Humans ; Female ; Pregnancy ; Quality of Life ; Prospective Studies ; Postpartum Period ; Hepatitis B, Chronic/psychology* ; Adult ; Pregnancy Trimester, Third ; Pregnancy Trimester, Second ; Pregnancy Complications, Infectious

Schizophrenia (SZ) stands as a severe psychiatric disorder. This study applied diffusion tensor imaging (DTI) data in conjunction with graph neural networks to distinguish SZ patients from normal controls (NCs) and showcases the superior performance of a graph neural network integrating combined fractional anisotropy and fiber number brain network features, achieving an accuracy of 73.79% in distinguishing SZ patients from NCs. Beyond mere discrimination, our study delved deeper into the advantages of utilizing white matter brain network features for identifying SZ patients through interpretable model analysis and gene expression analysis. These analyses uncovered intricate interrelationships between brain imaging markers and genetic biomarkers, providing novel insights into the neuropathological basis of SZ. In summary, our findings underscore the potential of graph neural networks applied to multimodal DTI data for enhancing SZ detection through an integrated analysis of neuroimaging and genetic features.
Humans ; Schizophrenia/pathology* ; Diffusion Tensor Imaging/methods* ; Male ; Female ; Adult ; Brain/metabolism* ; Young Adult ; Middle Aged ; White Matter/pathology* ; Gene Expression ; Nerve Net/diagnostic imaging* ; Graph Neural Networks

Hemorrhagic shock is a common clinical emergency that can aggravate cell injury after resuscitation. Astrocytes are crucial for the survival of neurons because they regulate the surrounding ionic microenvironment of neurons. Although hemorrhagic shock and resuscitation (HSR) injury can impair cognition, it remains unclear how this insult directly affects astrocytes. In this study, we established an HSR model by bleeding and re-transfusion in mice. The social interaction test and new object recognition test were applied to evaluate post-operative cognitive changes, and the results suggest that mice experience cognitive impairment following exposure to HSR. In the HSR group, the power spectral density of β and γ oscillations decreased, and the coupling of the θ oscillation phase and γ oscillation amplitude was abnormal, which indicated abnormal neuronal oscillation and cognitive impairment after HSR exposure. In brief, cognitive impairment in mice is strongly correlated with Ca²⁺ signal strength in lateral septum astrocytes following HSR.
Animals ; Astrocytes/metabolism* ; Shock, Hemorrhagic/metabolism* ; Resuscitation/adverse effects* ; Male ; Mice ; Calcium Signaling/physiology* ; Mice, Inbred C57BL ; Septal Nuclei/metabolism* ; Cognitive Dysfunction/etiology* ; Disease Models, Animal ; Cognition Disorders/etiology*

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 To investigate the effects of ROCK-siRNA transfection on endothelial cell senescence and endothelial microparticles (EMPs) induced by angiotensin II (Ang II). Methods Human umbilical vein endothelial cells (HUVECs) were treated with Ang II (1.0 μmo/L) to induce cellular senescence models, followed by transfection with ROCK-siRNA. The cells were divided into four groups: control group, model group, negative transfection control group (Ang II combined with NC-siRNA), and ROCK-siRNA transfection group (Ang II combined with ROCK-siRNA). Cellular senescence was assessed by SA-β-Gal staining. EMP levels in cell supernatants and intracellular reactive oxygen species (ROS) levels were assessed using flow cytometry. The expression levels of silenced information regulator 1(SIRT1) and p53 protein in each group were analyzed by Western blotting. Results Following ROCK-siRNA transfection, the number of senescent cells induced by Ang II was significantly reduced, accompanied by decreased CD31⁺ EMP levels and suppressed intracellular ROS levels. Meanwhile, the expression levels of SIRT1 were up-regulated, while the expression levels of p53 were down-regulated. Conclusion Silencing ROCK expression suppresses EMP release, reduces ROS generation, regulates the expression of SIRT1 and p53, and ultimately attenuates Ang II-induced endothelial cell senescence.
Humans ; Angiotensin II/pharmacology* ; Cellular Senescence/genetics* ; Human Umbilical Vein Endothelial Cells/cytology* ; RNA, Small Interfering/metabolism* ; Reactive Oxygen Species/metabolism* ; Sirtuin 1/genetics* ; Transfection ; Tumor Suppressor Protein p53/genetics* ; Cell-Derived Microparticles/drug effects* ; rho-Associated Kinases/metabolism* ; Endothelial Cells/metabolism* ; Cells, Cultured