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.

With the rapid development of sequencing technologies, the detection of alternative polyadenylation (APA) in mammals has become more precise. APA precisely regulates gene expression by altering the length and position of the poly(A) tail, and is involved in various biological processes such as disease occurrence and embryonic development. The research on APA in mammals mainly focuses on the following aspects:(1) identifying APA based on transcriptome data and elucidating their characteristics; (2) investigating the relationship between APA and gene expression regulation to reveal its important role in life regulation;(3) exploring the intrinsic connections between APA and disease occurrence, embryonic development, differentiation, and other life processes to provide new perspectives and methods for disease diagnosis and treatment, as well as uncovering embryonic development regulatory mechanisms. In this review, the classification, mechanisms and functions of APA were elaborated in detail and the methods for APA identifying and APA data resources based on various transcriptome data were systematically summarized. Moreover, we epitomized and provided an outlook on research on APA, emphasizing the role of sequencing technologies in driving studies on APA in mammals. In the future, with the further development of sequencing technology, the regulatory mechanisms of APA in mammals will become clearer.

Purpose To investigate the expression of Versican(VCAN)and thrombospondin 2(THBS2)and their relationship with cancer-associated fibroblast(CAFs)and clinicopathological significance in papillary thyroid car-cinoma(PTC).Methods Bioinformatics analyses were performed using PTC single-cell sequencing data from the GEO and TCGA database.Weighted correlation network analysis identified CAFs-related genes,and enrichment analy-sis highlighted pivotal genes associated with CAFs;the expression of VCAN,THBS2,and α-SMA in 130 PTC tissue samples were detected by immunohistochemistry EnVision method.Masson staining evaluated tumor stromal fibrosis.Relationships between these markers,clinicopathological parameters,and CAF proliferation were analyzed.Results Bioinformatics analysis identified VCAN and THBS2 as core genes significantly associated with CAFs,and extracellular matrix-related pathways.The proliferation rate of CAFs in PTC was 83.1％(108/130),with positivity rate of 96.9％(126/130)for VCAN and 75.4％(98/130)for THBS2.The median mesenchymal fibrosis index was 32.4(inter-quartile range:22.7-50.0).High CAF proliferation correlated positively with lymph node metastasis(P＜0.001),higher TNM stage(P＜0.05),and specific histologic subtypes of PTC.Similarly,VCAN expression,THBS2 expres-sion,and the degree of PTC stromal fibrosis were positively correlated with lymph node metastasis(P＜0.001,P＜0.05,and P＜0.001,respectively).Both THBS2 expression and the degree of PTC stromal fibrosis correlated with the histologic subtype of PTC.The percentage of tumor mesenchymal α-SMA-positive cells strongly correlated with the im-mune response score(IRS)of VCAN and THBS2(rs=0.713,P＜0.001;rs=0.646,P＜0.001).Additionally,the percentage of Masson-stained area was positively correlated with the percentage of tumor mesenchymal α-SMA-posi-tive cells,and the IRS of VCAN and THBS2(rs=0.892,P＜0.001;rs=0.729,P＜0.001;rs=0.616,P＜0.001).Conclusion VCAN and THBS2 serve as potential markers for assessing invasiveness and lymph node metas-tasis of PTC.Their strong association with CAFs provides a basis for further investigation of the malignant biological be-havior of PTC.

Objective To explore the effect and predictive value of ultrasound-guided needling assisted motor evoked potentials(MEP)and electromyography(EMG)monitoring on neurological recovery in spinal surgery.Methods A retrospective analysis was conducted on the clinical data of 80 patients who underwent spinal surgery at Jiangsu Province Hospital of Chinese Medicine from January 2020 to December 2024.A total of 41 patients in the observation group received ultrasound-guided needling assisted MEP and EMG monitoring,and 39 patients in the control group received conventional method for MEP and EMG monitoring.The operative time,intraoperative blood loss,and the proportions of intraoperative MEP and EMG warnings were compared between the two groups,and the sensitivity and specificity of intraoperative MEP monitoring were compared between the two groups.The receiver operating characteristic(ROC)curve was plotted,and the area under the curve(AUC)was calculated to analyze the efficiency of MEP warning in predicting the dysfunction of postoperative spinal cord.Results There were no significant differences in the operative time,intraoperative blood loss,or the proportions of intraoperative MEP and EMG warnings(P>0.05).The sensitivity,specificity and AUC of intraoperative MEP monitoring in the observation group were significantly higher than those in the control group,with statistically significant differences(P<0.05).The sensitivity,specificity,and AUC of postoperative MEP warning in predicting the dysfunction of spinal cord in the observation group were higher than those in the control group,with statistically significant differences(P<0.05).Conclusion Ultrasound-guided needling assisted MEP and EMG monitoring can effectively enhance the intraoperative neural monitoring accuracy,and postoperative MEP warning demonstrates superior predictive value for postoperative neurological dysfunction.

Objective To understand the current situation of healthcare-associated infection(HAI)in China,pro-vide data support and decision-making basis for formulating scientific and effective strategies for HAI prevention and control.Methods A nationwide cross-sectional survey on HAI was conducted among various types and levels of medical institutions in China according to a unified protocol of bedside surveys and case investigations.Results In 2024,a total of 5 736 medical institutions and 2 751 765 patients were surveyed.Among them,34 889 HAI cases were identified,with a prevalence rate of 1.27％.The number of HAI episodes was 38 032,and case prevalence rate was 1.38％.The prevalence rate of HAI in medical institutions in different regions of China ranged from 0.66％to 2.35％.Among medical institutions of different scales,those with a bed capacity of ≥900 had the high-est incidence of HAI,reaching 1.65％.The most common infection site was the lower respiratory tract(44.66％),followed by the urinary tract(12.94％),surgical site(9.32％),upper respiratory tract(7.02％),and bloodstream infection(5.78％).The top 3 departments with the highest HAI rates were the general intensive care unit(10.02％),department of neurosurgery(5.51％),and department(group)of hematology(5.34％).A total of 23 238 strains of HAI pathogens were detected,with 10 714 strains(46.10％)from lower respiratory tract speci-mens.The top 5 detected strains were Klebsiella pneumoniae(14.76％),Pseudomonas aeruginosa(13.33％),Escherichia coli(12.79％),Acinetobacter baumannii(9.23％),and Staphylococcus aureus(7.88％).231 944 pa-tients underwent class Ⅰ incision surgery were monitored,with 1 647 cases experienced surgical site infection,and the prevalence rate of surgical site infection was 0.71％.The number of patients who should undergo pathogen de-tection(patients receiving therapeutic and therapeutic combined prophylactic antimicrobial agents)was 715 179,while the actual number was 480 492,with a pathogen detection rate of 67.18％.425 225 patients received patho-genic detection before treatment,with a detection rate of 59.46％.Conclusion The overall HAI prevalence in Chi-na is lower,showing disparities among medical institutions of different regions and scales.Therefore,precise imple-mentation of measures is necessary for HAI prevention and control,with a focus on high-risk institutions and high-risk departments,key areas,and critical procedures.All levels of medical institutions should continuously reduce the incidence of HAI by strengthening monitoring,standardizing the use of antimicrobial agents,and reinforcing basic HAI prevention and control measures.

Objective:To construct a nomogram based on preoperative MRI imaging features for the prediction of muscle-invasive upper urinary tract urothelial carcinoma（UTUC）and evaluate its performance.Methods:This retrospective cohort study analyzed the clinical data of 99 UTUC patients treated at the First Affiliated Hospital of Nanjing Medical University from April 2018 to May 2024. Among them，69（69.7%）were male and 30（30.3%）were female，with a median age of 67.0 years. All patients underwent preoperative MRI and radical nephroureterectomy. According to postoperative pathology，tumors staged ≥ T 2 were assigned to the muscle-invasive group，and those staged ≤ T 1 were assigned to the non-muscle-invasive group. Baseline data，pathological information，and imaging characteristics were collected and compared between the two groups. Logistic regression analysis was performed to identify risk factors for muscle-invasive UTUC，and a nomogram was constructed. The diagnostic performance of the model was assessed using receiver operating characteristic（ROC）curves，calibration curves，and decision curve analysis（DCA）. Results:Among the 99 patients，70（70.7%）were diagnosed with muscle-invasive UTUC，and 29（29.3%）with non-muscle-invasive UTUC. The muscle-invasive group had significantly larger tumor size［4.5（2.8，7.0）cm vs. 3.0（2.3，4.5）cm， P = 0.029］，a higher incidence of multifocal tumors［37.1%（26/70）vs. 3.5%（1/29）， P < 0.001］，patchy tumors［30.0%（21/70）vs. 6.9%（2/29）， P = 0.019］，spiculated tumor margins［52.9%（37/70）vs. 17.2%（5/29）， P = 0.001］，tumor compression on renal parenchyma or periureteral/peripelvic fat［68.6%（48/70）vs. 10.3%（3/29）， P < 0.001］，high-grade pathology［92.9%（65/70）vs. 75.9%（22/29）， P = 0.043］，lymph node metastasis［28.6%（20/70）vs. 0， P = 0.001］，and lymphovascular invasion［42.9%（30/70）vs. 10.3%（3/29）， P=0.002］. The apparent diffusion coefficient（ADC）values［0.9（0.8，1.1）× 10 -3 mm2/s vs. 1.1（1.0，1.4）× 10 -3 mm2/s， P < 0.001］and normalized ADC（NADC）values［0.8（0.7，1.0）vs. 0.9（0.8，1.1）， P = 0.002］were significantly lower in the muscle-invasive group. Univariate logistic regression identified multifocality，patchy tumor patterns，spiculated tumor margins，tumor compression on renal parenchyma or periureteral/peripelvic fat，and low NADC values as risk factors for muscle-invasive UTUC（all P < 0.05）. Multivariate analysis revealed multifocality（ OR = 17.903，95% CI 1.650 - 194.253， P = 0.018），tumor compression on renal parenchyma or perirenal / ureteral fat（ OR = 14.690，95% CI 3.069 - 70.323， P < 0.001），and low NADC value（ OR = 0.016，95% CI 0.001 - 0.471， P = 0.017）as independent risk factors. A nomogram was constructed based on these factors. The area under the ROC curve（AUC）of the model was 0.898（95% CI 0.838 - 0.957），with an optimal cutoff value of 0.639. The model showed an accuracy of 83.8%，sensitivity of 81.4%，and specificity of 89.7%. Calibration curves indicated good calibration，and DCA showed that the model provided substantial clinical net benefit. Conclusions:This study constructed a nomogram based on preoperative MRI features，including tumor multifocality，compression on renal parenchyma or periureteral/peripelvic fat and NADC value，which demonstrates good predictive performances for muscle-invasive UTUC.

Aim To study whether intravenous injec-tion of miR-129-3p mimetic(agomir)can resist bone loss caused by hind limb disuse,and to provide new i-deas for preventing bone loss in microgravity environ-ment.Methods Forty-eight C57BL/6J male mice were randomly divided into the control group(CON),tail suspension model group(TS),tail suspension+miR-129-3p agomir administration group(miRNA)and tail suspension+miR-129-3p negative sequence agomir control group(NC).The miRNA group was given 4 mg·kg-1 miR-129-3p agomir by intravenous injection into the medial canthus twice a week.The NC agomir group were consistent with those in the miR-129-3p agomir group,and the CON and TS groups were given only equal volumes of normal saline.After four weeks,all mice were sacrificed and samples were collected.Micro-CT scan of femur,three-point femur bending test,serum bone metabolism index detection,oxidative stress index detection and osteogenesis-related protein expression analysis in bone tissue were per-formed.Results After four weeks,the number of tra-becular bone in the TS group was significantly re-duced,and Tb.BMD,Tb.Th,Tb.N,Tb.BS/TV and Tb.BV/TV were significantly lower than those in the CON group(P＜0.01).While Tb.Sp TS group was significantly higher than the CON group(P＜0.05),the maximum load and flexural strength of the femur significantly decreased(P＜0.01),the content of ser-um bone formation index PINP was significantly lower than that of the CON group(P＜0.01),and the con-tent of bone resorption index CTX-I was significantly higher than that of the CON group(P＜0.01),the content of serum oxidative damage indexes 8-iso-PGF2α and 8-OHdG significantly increased(P＜0.01),and the expression of osteogenesis-related pro-teins in bone tissue markedly decreased(P＜0.01).However,the increase or decrease of all indexes in miRNA group was significantly lower than that in TS group.Conclusions miR-129-3p mimetic can signifi-cantly reduce bone loss caused by hind limb disuse.This experiment provides a new idea and method for preventing bone loss in microgravity environment.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.