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 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.

Cemental tear is a rare and indetectable condition unless obvious clinical signs present with the involvement of surrounding periodontal and periapical tissues. Due to its clinical manifestations similar to common dental issues, such as vertical root fracture, primary endodontic diseases, and periodontal diseases, as well as the low awareness of cemental tear for clinicians, misdiagnosis often occurs. The critical principle for cemental tear treatment is to remove torn fragments, and overlooking fragments leads to futile therapy, which could deteriorate the conditions of the affected teeth. Therefore, accurate diagnosis and subsequent appropriate interventions are vital for managing cemental tear. Novel diagnostic tools, including cone-beam computed tomography (CBCT), microscopes, and enamel matrix derivatives, have improved early detection and management, enhancing tooth retention. The implementation of standardized diagnostic criteria and treatment protocols, combined with improved clinical awareness among dental professionals, serves to mitigate risks of diagnostic errors and suboptimal therapeutic interventions. This expert consensus reviewed the epidemiology, pathogenesis, potential predisposing factors, clinical manifestations, diagnosis, differential diagnosis, treatment, and prognosis of cemental tear, aiming to provide a clinical guideline and facilitate clinicians to have a better understanding of cemental tear.
Humans ; Dental Cementum/injuries* ; Consensus ; Diagnosis, Differential ; Cone-Beam Computed Tomography ; Tooth Fractures/therapy*

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.

Metabolic-bariatric surgery(MBS)has become an important treatment for pathological obesity and metabolic diseases.However,common postoperative nutritional complications—such as protein-energy malnutrition,iron deficiency anemia,and vitamin B12 deficiency—significantly affect patients' long-term prognosis.Traditional nutritional management models rely on static monitoring and standardized supplementation,which are insufficient to address individual variability and dynamic postoperative changes.Artificial intelligence(AI),through integrating multimodal data(such as biochemical indicators,imaging information,and wearable device monitoring)and intelligent modeling,offers new approaches for dynamic monitoring,risk prediction,and personalized intervention.Based on literature from 2017 to 2025,this article systematically evaluates the application of AI in perioperative nutritional management for MBS,covering key technologies including machine learning,deep learning,and natural language processing.It also analyzes current challenges in clinical translation,such as data fragmentation,lack of model interpretability,and limited long-term validation.In the future,enhanced multi-center collaboration,the development of standardized databases,and explainable models will be essential to advancing nutritional management in MBS from empirical practice to precision medicine.

In view of the characteristics of H5N6 subtype avian influenza virus(AIV)that it has both high pathogenicity and the risk of cross-species transmission,posing a serious threat to the poultry farming industry and public health security,in order to effectively prevent and control the spread of H5N6 avian influenza,a rapid,sensitive and specific detection technolo-gy was established in this study.The specific monoclonal antibodies against the neuraminidase N6 protein of avian influenza A virus subtype H5N6 were obtained through hybridoma and monoclonal antibody technology.These antibodies were coupled and labeled with carboxyl-functionalized fluorescent quantum dots,along with previously prepared specific antibodies against the hemagglutinin H5 protein.A rapid fluorescence immunochromatographic detection method for the H5N6 subtype of avian influ-enza virus was established according to the principle of double-antibody sandwich immunochromatography.This method a-chieved a detection sensitivity of 1 ng/mL for recombinant hemagglutinin H5 subtype protein and 0.1 ng/mL for recombinant neuraminidase N6 subtype protein.Moreover,the method exhibited no cross-reactivity with other influenza subtypes or patho-gens,such as Newcastle disease(ND),infectious bronchitis(IB),and infectious laryngotracheitis(ILT),thus demonstrating good specificity.The method effectively identified the highly pathogenic avian influenza virus H5 subtype and directly distin-guished the H5N6 subtype with good accuracy.The fluorescent quantum dot immunochromatographic typing detection method established herein met the sensitivity,specificity,and accuracy requirements for H5N6 subtype detection,and can be further used for rapid detection of the H5 and H5N6 subtypes of avian influenza virus.

With the continuous evolution of minimally invasive surgical concepts,operative techniques are progressively advancing from"minimal injury"toward"scarless"approaches.Super-minimally laparoscopic surgery(SMLS)is a novel surgical modality developed on the basis of conventional laparoscopic techniques through the innovation and recombination of operative elements,aiming to achieve smaller trauma and improved cosmetic outcomes.Utilizing the umbilical skin fold as a natural scar-concealing site,SMLS establishes no more than two primary operating channels(maximum diameter≤15 mm),supplemented by auxiliary ports≤2 mm in diameter on the abdominal wall.Combined with innovative separable surgical instruments and high-definition visualization systems,this approach provides a systematic solution to key issues such as residual access-site scarring.This review summarizes the development,technical innovations,current clinical applications,and potential aesthetic value of SMLS in the evolution of minimally invasive surgery,aiming to offer theoretical insights and research reference for its future promotion and technical refinement.

Objective:Systematically review the release status and characteristics of policies related to cross-regional medical insurance settlement policies in China,providing reference for promoting the convenience of medical insurance settlement services and improving management efficiency.Methods:Using content analysis,a two-dimensional framework of"policy objectives-policy tools"was constructed.A total of 127 policy documents were coded and analyzed.Results:Demand-based tools were applied most frequently(43.6%),followed by environmental and supply-based tools.Policy objectives mainly focused on improving service convenience,supported by expanding coverage and ensuring regulatory security.Conclusions:China's cross-regional medical insurance settlement policies have improved service accessibility and strengthened institutional supervision while gradually expanding coverage.However,deficiencies remain in assessment refinement and emergency mechanisms.Greater interdepartmental coordination is needed to enhance regulatory linkage and ensure the safe operation of medical insurance funds.

Objective:To construct a key item checklist for the Mini-HTA report specification,providing scientific guidance for drafting each section of Mini-HTA research reports,enhancing their standardization,scientific rigor,and completeness,thereby improving the efficiency and quality of health decision-making.Methods:Based on preliminary literature review and qualitative systematic review,a pool of problem items for the Mini-HTA report specification was formed.Delphi questionnaires were distributed,and the Delphi technique was employed through two rounds of expert consultation to optimize and select key items.Results:Through two rounds of Delphi expert consultation,the initial Mini-HTA report specification item checklist was screened,integrated,and supplemented.A finalized key item checklist was constructed,comprising 8 first-level items(Title,Abstract,Introduction,Methods,Results,Discussion,Conclusion,and Other Relevant Information)and 48 second-level items.Conclusion:The constructed key item checklist for the Mini-HTA report specification provides scientific guidance for drafting Mini-HTA research reports.It helps enhance the standardization and transparency of the assessment process and the reliability of results,thereby optimizing the efficiency and quality of health decision-making.

Objective:To observe the influence of acupuncture for regulating the mind and replenishing qi combined with butylphthalide soft capsules on sleep parameters and neurological function in patients with sleep disorders after stroke.Methods:From May 2022 to September 2024,a total of 85 patients with sleep disorders after stroke who were admitted to our hospital were prospectively included,and they were divided into control group(received treatment with butylphthalein soft capsules,42 cases)and study group(received treatment with acupuncture for regulating the mind and replenishing qi combined with butylphthalide soft capsules,43 cases)by the double chromosphere method.Sleep parameters,sleep quality score[pittsburgh sleep quality index(PSQI),insomnia severity index(ISI)],related functional scale score[modified edinburgh scandinavian stroke scale(MMSSS),hospital anxiety and depression scale(HADS),Fugl-Meyer assessment scale(FMA),montreal cognitive assessment(MoCA)]and related serum indicators[hypersensitive C-reactive protein(hs-CRP),tumor necrosis factor-α(TNF-α),5-hydroxy tryptamine(5-HT),gama-aminobutyric acid(GABA)]were compared between the two groups.Result:The total sleep time,sleep efficiency,FMA score,MoCA score,5-HT and GABA indicators in the study group after treatment were higher than those in the control group,the number of awakenings,sleep latency,PSQI score,ISI score,MESSS score,HADS score,hs-CRP and TNF-α indicators were lower than those in the control group(P＜0.05).Conclusion:Acupuncture for regulating the mind and replenishing qi combined with butylphthalide soft capsules can effectively improve the sleep quality of patients with sleep disorders after stroke,regulate the neurological functions,reduce inflammatory factors levels,and improve the motor and cognitive function.