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 delineate imaging findings using an imaging platform and investigate the correlation between MRI characteristics of spinal cord atrophy and clinical diagnosis in children with spinal cord injury (SCI). MethodsImaging data of 150 children with SCI admitted to Beijing Bo'ai Hospital, China Rehabilitation Research Center, from January, 2002 to March, 2024 were collected and imported into the imaging platform. The anteroposterior and transverse diameters of the middle part of the spinal cord at the cross-section with the most severe atrophy were measured, and the relevant indicators of the previous normal spinal cord segment were measured as controls; the radiomic features were extracted. Clinical data of the children including gender, age, cause of injury, sensory level, motor level, spinal cord injury level, injury severity and disease course were collected. ResultsSpinal cord atrophy was identified in 81 cases (54%), among which 78 cases (96%) were American Spinal Injury Association Impairment Scale (AIS) grade A and 3 cases (4%) were AIS grade C. The upper boundary of the spinal cord atrophy site strongly correlated with the injury level, motor level and sensory level (r > 0.8, P < 0.001). ConclusionMore than half of children with SCI may develop secondary spinal cord atrophy, the vast majority of whom suffer from complete spinal cord injury; the upper boundary of spinal cord atrophy is correlated with the injury level.

ObjectiveTo investigate the mechanisms by which Renshentang treats atherosclerosis （AS） in mice， focusing on the regulation of endothelial inflammatory responses mediated by transient receptor potential vanilloid subtype 1 （TRPV1）. MethodsAn AS model was established in apolipoprotein E knockout （ApoE^-/-） mice fed a high-fat diet. The mice were randomly divided into a simvastatin group （0.02 g·kg^-1·d^-1） and low-， medium-， and high-dose Renshentang groups （1.77， 3.54， 7.08 g·kg^-1·d^-1）， with 12 mice in each group. ApoE^-/- mice were fed a high-fat diet and treated simultaneously. C57BL/6J mice fed a normal diet served as the normal group （n=9）. After continuous administration for 12 weeks， mice were anesthetized and the aortas were collected. Oil Red O staining was used to observe lipid plaque formation in the aorta. Hematoxylin-eosin （HE） staining was performed to examine pathological changes in the aortic root. Immunohistochemistry was used to analyze the levels of pro-inflammatory factors tumor necrosis factor-α （TNF-α） and interleukin-1β （IL-1β）， as well as the expression of TRPV1， phosphorylated phosphoinositide 3-kinase （p-PI3K）， and phosphorylated protein kinase B （p-Akt） in the aortic root. Real-time quantitative polymerase chain reaction （Real-time PCR） was used to detect endothelial nitric oxide synthase （eNOS） mRNA expression in the aorta， and Western blot was used to detect TRPV1 protein expression. ResultsCompared with the normal group， the model group showed a significant increase in aortic plaque formation （P<0.01） and significantly elevated levels of TNF-α and IL-1β in the aortic root （P<0.01）. The expression levels of TRPV1， p-PI3K， and p-Akt were decreased （P<0.05， P<0.01）， and eNOS mRNA expression was reduced （P<0.05， P<0.01）. Compared with the model group， all Renshentang groups significantly reduced aortic plaque formation （P<0.01）， significantly decreased TNF-α and IL-1β levels （P<0.01）， and markedly increased the expression levels of TRPV1， p-PI3K， p-Akt， and eNOS mRNA （P<0.05， P<0.01）. ConclusionRenshentang may inhibit endothelial inflammation and suppress the formation of AS by increasing TRPV1 protein expression and up-regulating the PI3K/Akt/eNOS signaling pathway， which may be one of the molecular mechanisms underlying its therapeutic effect against AS.

Oral potentially malignant disorders (OPMDs) are a group of oral mucosal diseases with different morphological characteristics that have an increased risk of progressing to oral squamous cell carcinoma (OSCC). Epidemiological studies indicate that approximately 4.67% of the global population may have an OPMD, and meta-analysis results show that the risk of progression to OSCC in patients with OPMD is 2.5 times that of the general population. The progression of an OPMD to OSCC is a complex process driven by risk factors including smoking, alcohol consumption, betel quid chewing, and oral microbiota. It is characterized by intricate interactions among genetic alterations, epigenetic modifications, and dysregulation of the tumor microenvironment. At the molecular level, the intrinsic basis of epithelial carcinogenesis is established by genomic loss of heterozygosity and cascading dysregulation of critical signaling pathways, while crucial external support for malignant transformation is provided by the immunosuppressive microenvironment, including M2 macrophage polarization, immune evasion mediated by programmed death-ligand 1, and the pro-tumorigenic effects of oral microbiota. Although a variety of therapeutic modalities (e.g., pharmacotherapy, surgical treatment, and photodynamic therapy) have been employed for the prevention of OPMD malignant transformation, no universally accepted treatment has been proven to completely eradicate the risk of cancer development at present. In recent years, artificial intelligence technologies have demonstrated promising performance in predicting the malignant transformation risk of OPMD by integrating multi-dimensional clinical, pathological, and molecular data, thereby providing new decision-support tools for advancing individualized risk stratification and precise follow-up management. This review summarizes recent advances in the prevention of OPMD malignant transformation, with the aim of offering a reference for the clinical management of OPMDs.

Objective To assess functional abnormalities in frontoparietal attention network of patients with traumatic brain injury(TBI),and to analyze neural mechanism of its attention disorders based on independent component analysis(ICA).Methods Totally 84 TBI patients were prospectively enrolled and divided into mild(n=33),moderate(n=27)and severe TBI groups(n=24)according to symptoms,non-contrast enhanced MRI findings,Glasgow coma scale(GCS)and Mayo craniocerebral trauma grading criteria.ICA was used to extract and analyze the optimal independent components(IC)of the dorsal attention network(DAN)and ventral attention network(VAN).Multiple linear regression analyses were performed to explore the correlations of functional connectivity(FC)of brain regions being significantly different among groups within attention network and the scores of trail making test A/B(TMT-A/B).Results Compared with control group and mild TBI group,spatial distribution of DAN(especially bilateral frontal eye field[FEF])in moderate and severe TBI groups were significantly smaller,the clusters tended to be discrete,and the intensity were significantly weakened.The right temporal parietal junction(TPJ)and right ventral frontal cortex(VFC)of VAN in control group,mild and moderate TBI groups were significantly affected,and VFC connection strength was the highest in severe TBI group.FC intensity in right VFC of TBI patients was positively correlated with TMT-A score(r=0.654,P＜0.001),which in left FEF was negatively correlated with TMT-B score(r=—0.383,P＜0.001).Conclusion FC of frontoparietal attention network was abnormal in TBI patients,which might be neural mechanism for its attention behavior disorders.

To investigate the potential protective effect of thalidomide (THD) on diabetic nephropathy (DN) and its underlying mechanisms. Twenty-four C57BL/6J mice were randomly divided into control, DN and DN+THD200 groups by random number table method. The DN mouse model was established via intraperitoneal injection of streptozotocin. The DN+THD200 group received THD treatment (200 mg·kg -1·d -1) for 8 weeks. Blood and urine biochemical parameters, as well as renal histopathological changes, were compared among the three groups. For in vitro experiments, a high glucose (HG)-induced injury model was established in mouse glomerular podocytes (MPC5). Cells were divided into control (NG), HG, HG+DMSO, HG+THD100 (100 μg/ml), and HG+THD200 (200 μg/ml) groups. THD-treated cells were exposed to THD for 24 h. Western blotting and real-time quantitative PCR were performed to respectively detect protein and mRNA expression levels of ferroptosis-related molecules, including nuclear factor erythroid 2-related factor 2 (NRF2), heme oxygenase 1 (HO-1), and glutathione peroxidase 4 (GPX4). Immunofluorescence was used to evaluate the expression of solute carrier family 7 member 11 (SLC7A11) and 4-hydroxynonenal (4-HNE). The results showed that, compared with control group, DN group exhibited significantly lower blood urea nitrogen, serum creatinine and 24 h urinary albumin levels (all P<0.05). Compared with DN group, DN+THD200 group exhibited significantly lower blood urea nitrogen, serum creatinine and 24 h urinary albumin levels (all P<0.05). Histopathological examination revealed glomerular expansion, mesangial widening, and basement membrane thickening in DN group compared to control group, which were markedly ameliorated by THD treatment. In vitro, HG group showed significantly decreased protein and mRNA expression levels of GPX4, NRF2 and HO-1 compared to NG group. Both HG+THD100 and HG+THD200 groups exhibited upregulated expression levels of these proteins and corresponding mRNA compared to HG group (all P<0.05). Immunofluorescence demonstrated HG group had enhanced 4-HNE fluorescence intensity and reduced SLC7A11 fluorescence intensity, which were reversed by THD treatment. THD alleviates renal injury in DN mice and mitigates HG-induced ferroptosis in MPC5 cells, potentially via activation of NRF2-HO-1-GPX4 signaling pathway.

Purpose To investigate interhemispheric homotopic functional connectivity in patients with neuropsychological systemic lupus erythematosus(NPSLE)during resting state and its relationship with clinical indicators and neuropsychological scales.Materials and Methods This prospective study enrolled 35 patients with NPSLE and 31 healthy controls(control group)from Taizhou People's Hospital Affiliated to Nanjing Medical University(June 2020 to March 2023).All participants underwent resting state functional MRI and completed neuropsychological assessments including mini-mental state examination,Montreal cognitive assessment,hospital anxiety and depression scale,fatigue scale for motor and cognitive functions,along with laboratory tests(C3,C4,IgA,IgM,IgG).Image preprocessing and voxel-mirrored homotopic connectivity(VMHC)calculations were performed using DPABI V7.0 on Matlab R2013b.Between-group differences in VMHC values were compared,and correlations between VMHC values in significant regions and neuropsychological/clinical data were analyzed.Results The NPSLE group demonstrated significantly lower mini-mental state examination and Montreal cognitive assessment scores compared with those in control group(t=-6.297,-7.001,both P=0.001).Patients with NPSLE exhibited significantly decreased VMHC values in bilateral parahippocampal gyri,precentral gyri,middle frontal gyri,and medial/paracingulate gyri compared with those in control group(family-wise error corrected,voxel-level P<0.001,cluster-level P<0.05).In the NPSLE group,VMHC values in precentral gyri showed positive correlation with IgA levels(r=0.351,P=0.039),while VMHC values in medial/paracingulate gyri positively correlated with IgA(r=0.345,P=0.043)and negatively with C4(r=-0.368,P=0.030).Conclusion Patients with NPSLE demonstrate abnormal interhemispheric homotopic functional connectivity,and the correlation between imaging metrics and clinical data in differential brain regions may facilitate early diagnosis of NPSLE while providing novel insights into the neuropathological mechanisms of cerebral injury.

Objective:To investigate the pathogenetic characteristics of clinical isolates of Streptococcus suis in Henan Province from 2020 to 2023. Methods:Eight clinical isolates of S. suis in Henan Province from 2020 to 2023 were identified using matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) and real-time fluorescence polymerase chain reaction (PCR). Serotype and virulence genes were detected by the serum agglutination test and PCR, and antibiotic susceptibility was evaluated using the microbroth dilution method. Multilocus sequence typing (MLST), minimum core genome (MCG), identification of antibiotic resistance genes, and core genome single nucleotide polymorphism (cgSNP) analysis were conducted using whole genome sequencing. Results:The results showed that eight S. suis strains isolated from humans were mainly serotype 2 (75.0%), while the rest were serotype 14 (25.0%). ST353 (62.5%) was the predominant genotype, followed by ST1 (25.0%) and ST7 (12.5%). All isolates belonged to the MCG1 group. The virulence genotypes of these isolates were primarily mrp(NA2)/ sly+/ ef+/ gapdh+(75.0%), while the remaining were mrp(EU)/ sly+/ ef+/ gapdh+(25.0%). These isolates carried tetracycline, macrolide, lincosamide and aminoglycoside resistance genes, and their resistance rates to tetracycline, erythromycin and clindamycin were 100.0%, 87.5% and 87.5%, respectively, and 62.5% strains were intermediate-resistant to penicillin. The cgSNP analysis indicated that these isolates were closer to the isolates from Guangdong, Zhejiang and Guangxi Provinces, with five ST353 strains and one ST7 strain belonging to Clade Ⅰ, and two ST1 strains belonging to Clade Ⅱ. Conclusion:The human isolates of S. suis in Henan Province are mainly ST353, harboring multiple virulence and antibiotic resistance genes.

The accurate prediction and evaluation of lymphatic vascular invasion(LVI)are extremely important for the prog-nosis of breast cancer patients.Postoperative histopathology has certain limitations in predicting lymphatic vascular invasion,and mag-netic resonance imaging(MRI)technology,with its high resolution and multi-parameter imaging characteristics,provides a more effec-tive non-invasive means for the prediction and evaluation of lymphatic vascular invasion.With the continuous development of the re-search field of radiomics,researchers have constructed a more accurate prediction model of lymphatic vascular invasion by deeply ana-lyzing a large number of radiological features shown in MRI images and combining with the clinical data of patients.This article re-views the recent research progress of MRI in the field of predicting lymphatic vascular invasion of breast cancer.The purpose of this article is to provide a scientific basis for the clinical treatment of breast cancer patients through accurate identification of lymphatic vascular invasion status before surgery,and to assist clinicians in formulating more personalized treatment plans for patients.

Objective Under the guidance of the Social Ecosystems Theory(SET)framework,this study explores the experience of social isolation among patients with chronic obstructive pulmonary disease(COPD),providing a basis for the development of targeted clinical interventions.Methods This study employed purposeful sampling methods.Semi-structured interviews were conducted from April to July 2024 with patients diagnosed with COPD at a tertiary hospital in Shanxi Province,China,who met the inclusion and exclusion criteria.Data were analyzed using Colaizzi's seven-step analysis method and NVivo 12.0 software.Results This study involved in-depth interviews with 15 patients suffering from COPD,totaling approximately 405 minutes of interview time and yielding over 40,000 words in transcribed text.Totally 3 main themes and 9 sub-themes were distilled,among which the microsystem level reflects the intricate interplay of individual experiences(physical functional limitations,severe negative emotions,heightened emotional imbalance,and weakened social roles);the mesosystem level pertains to the support and challenges from family and social networks(intense need for familial emotional support,widening social gaps in interactions with friends and relatives,and pronounced interpersonal communication barriers);the macrosystem level involves the integrated influence of societal and policy environments(restricted living conditions and urgent demands for policy support and service accessibility).Conclusion The social isolation experienced by patients with COPD manifests in multiple dimensions of experience.It is necessary to develop interdisciplinary and multi-level comprehensive intervention strategies for the future,to create more social opportunities and emotional connections for patients,thereby improving their quality of life.