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.

A variety of plants are used as Gymnadenia conopsea(L.)R.Br medicine in some areas.According to statistics,there are 7 genera and 16 species of Orchidaceae.There is confusion in medicinal varieties,which seriously affects drug safety and rational utilization of resources.Based on the national standards,this article conducted a textual research from the aspects of ancient herbs,modern monographs,the name of the reference,base,property and taste and efficacy and other aspects.The results showed that,the Gymnadenia conopsea(L.)R.Br medicine is named Erheten nai gar,and the Tibetan medicine is named Wangla,and most of the herbs take"Gymnadenia conopsea(L.)R.Br"as the name.The mainstream varieties of Gymnadenia conopsea(L.)R.Br,a plant of the genus Gymnadenia of Orchidaceae,were born in arid grassland or wetland and meadow,with palmlike roots,green stems and leaves and pink and white flowers.Gymnadenia conopsea(L.)R.Br is different in property and taste and efficacy when used as different ethnic medicines,but it has the commonness of tonifying kidney,producing sperm and strengthening yang and nourishing.The conclusion of textual research could provide references for the resource conservation,rational research and utilization,and artificial cultivation of Gymnadenia conopsea(L.)R.Br resources.

Breast cancer remains one of the frequently diagnosed malignant tumors among Chinese women,with hereditary cases accounting for 5%-10%of all diagnoses,where BRCA1/2 gene mutations serve as the primary genetic predisposition factors.Although targeted therapies like poly(ADP-ribose)polymerase(PARP)inhibitors have significantly improved prognoses for patients with BRCA-mutated breast cancer in recent years,critical clinical challenges persist,including the standardization of genetic testing protocols,optimization of precision treatment approaches,and refinement of long-term management strategies.In response to these challenges,our expert panel has conducted a comprehensive update to the 2018 Edition of this consensus by integrating the latest global evidence-based medical research with China's unique clinical practice characteristics.This 2025 Edition provides systematic evaluations and recommendations on five key aspects:indications for BRCA1/2 gene testing,testing methodologies,result interpretation,treatment strategies,and risk management.The main updates include:① Increasing the relationship between BRCA1/2 gene mutations and programmed death ligand-1(PD-L1)expression,as well as related content on BRCAness types;② Standardizing the application of genetic testing,such as increasing the significance,timing,and sample selection of clinical testing,and optimizing the BRCA testing population;③ Updating treatment strategies,such as non-drug treatment of BRCA1/2 gene mutation,treatment of triple negative breast cancer(TNBC)patients with BRCA1/2 gene mutation,treatment decisions of hormone receptor(HR)+/human epidermal growth factor receptor 2(HER2)-breast cancer patients with BRCA1/2 gene mutation,clinical use of PARP inhibitors and adverse reaction management;④ Addion of relevant content on long-term risk management,such as covering follow-up management,indications for preventive surgery,quality control and requirements for new genetic testing,updating genetic testing processes,report content and interpretation.This consensus aimed to establish standardized diagnostic and therapeutic frameworks for clinicians,advance precision medicine in BRCA-mutated breast cancer,and ultimately improve patient survival outcomes.As new evidence emerges,continuous updates will be implemented to incorporate the latest research findings.This consensus has been registered on the Practice guideline REgistration for transPAREncy(PREPARE)platform(registration number:PREPARE-2025CN1085).

Purpose To measure the spatial resolution in MRI quality control testing automatically based on the American College of Radiology(ACR)phantom using the support vector machine(SVM)method,and the feasibility,accuracy and measurement speed of this method are explored.Materials and Methods Quality control tests were performed using eight MRI devices at Beijing Friendship Hospital of Capital Medical University.A retrospective study was conducted on 71 MRI quality control test images collected based on ACR phantoms between 2017 and 2019.The images were preprocessed by binarization,extraction region of interest and so on.An SVM-based classification model was constructed for analyzing the spatial resolution of dot arrays in row and column directions.The dataset was randomly split into a training set and a test set.The generalization performance of the classification model in this study was evaluated through accuracy,precision,recall and F1 score on the test set.Comparing the results of spatial resolution measurements obtained by both manual and automatic method,we demonstrated the feasibility and accuracy of the method.Additionally,the time taken for the automatic spatial resolution measurement was recorded.Results In this study,the proposed method of automatically measuring the spatial resolution of ACR phantom test images using SVM was feasible,high accuracy and short time.In classification performance test,the accuracy of the spatial resolution of the row directional latices was 95%,the precision was 100%.The accuracy of the spatial resolution of the column directional latices was 97%,the precision was 100%.Among the test cases,the results of automatic measurements matched those of manual measurements in 13 out of 14 cases.On average,automatic spatial resolution measurement took 0.158 seconds per case.Conclusion This study achieves automatic measurement of spatial resolution in MRI quality control based on the ACR phantom using SVM method.The method demonstrates high accuracy and fast measurement speeds,holding significant implications for future rapid MRI quality control stability testing.

Purpose To explore an automatic detection method for quality control performance indicators of radio frequency coils based on American College of Radiology(ACR)phantom,and verify its accuracy stability and computational efficiency.Materials and Methods A retrospective study was conducted on 50 quality control images collected based on ACR phantom in Beijing Friendship Hospital,Capital Medical University from May 2017 to July 2019.The measurement and calculation methods of signal noise ratio(SNR),percent image uniformity(PIU)and percent signal ghosting(PSG)were used to automatically calculate the above indicators using a self-designed program in Python.A simple linear regression analysis on the automatically calculated SNR,PSG and PIU values compared to the manually measured results was performed,and Bland-Altman analysis was used to calculate the percentage difference to evaluate the consistency and bias between the performance indicators calculated by the two methods.The time consumption of two detection methods was compared to verify their computational complexity and efficiency.Results There was a strong correlation between the performance indicators SNR,PSG and PIU of radio frequency coils measured and calculated automatically and manually(r=0.991 4,0.992 8 and 0.909 8,all P<0.0001).The Bland-Altman results showed that most of the data fall within the 95%confidence interval and were evenly distributed.In terms of computational complexity and efficiency,compared to the complex manual delineation and calculation of 2-3 minutes per case,automatic detection could simultaneously obtain SNR,PSG and PIU values in less than 1 second.Conclusion The automatic and manual measurement methods have good consistency,and the automatic detection method is easy to operate,which is helpful for the daily quality control work and performance monitoring of radio frequency coils.

Breast cancer remains one of the frequently diagnosed malignant tumors among Chinese women,with hereditary cases accounting for 5%-10%of all diagnoses,where BRCA1/2 gene mutations serve as the primary genetic predisposition factors.Although targeted therapies like poly(ADP-ribose)polymerase(PARP)inhibitors have significantly improved prognoses for patients with BRCA-mutated breast cancer in recent years,critical clinical challenges persist,including the standardization of genetic testing protocols,optimization of precision treatment approaches,and refinement of long-term management strategies.In response to these challenges,our expert panel has conducted a comprehensive update to the 2018 Edition of this consensus by integrating the latest global evidence-based medical research with China's unique clinical practice characteristics.This 2025 Edition provides systematic evaluations and recommendations on five key aspects:indications for BRCA1/2 gene testing,testing methodologies,result interpretation,treatment strategies,and risk management.The main updates include:① Increasing the relationship between BRCA1/2 gene mutations and programmed death ligand-1(PD-L1)expression,as well as related content on BRCAness types;② Standardizing the application of genetic testing,such as increasing the significance,timing,and sample selection of clinical testing,and optimizing the BRCA testing population;③ Updating treatment strategies,such as non-drug treatment of BRCA1/2 gene mutation,treatment of triple negative breast cancer(TNBC)patients with BRCA1/2 gene mutation,treatment decisions of hormone receptor(HR)+/human epidermal growth factor receptor 2(HER2)-breast cancer patients with BRCA1/2 gene mutation,clinical use of PARP inhibitors and adverse reaction management;④ Addion of relevant content on long-term risk management,such as covering follow-up management,indications for preventive surgery,quality control and requirements for new genetic testing,updating genetic testing processes,report content and interpretation.This consensus aimed to establish standardized diagnostic and therapeutic frameworks for clinicians,advance precision medicine in BRCA-mutated breast cancer,and ultimately improve patient survival outcomes.As new evidence emerges,continuous updates will be implemented to incorporate the latest research findings.This consensus has been registered on the Practice guideline REgistration for transPAREncy(PREPARE)platform(registration number:PREPARE-2025CN1085).

Objective To comprehensively evaluate the quality difference of Huaihua powder obtained by the hospital's electromagnetic furnace decoction method and automatic decoction machine decoction method.Methods Five methods(induction cooker decoction(once decoction,twice decoction),normal pressure decoction(once decoction,twice decoction),and pressure decoction)were used to prepare the decoction.The HPLC method used a Shiseido CAPCELL PAK-C18(250 mm×4.6 mm,5 μm)column,with a UV detection wavelength of 254 nm,mobile phase of acetonitrile 0.1%phosphoric acid water,column temperature of 30℃,flow rate of 1.0 mL/min,and detection of index components including rutin,naringin,quercitrin,neohesperidin,quercetin,and menthone.The extraction rate of the index components was calculated and the cream yield of each decoction was detected.The evaluation of quality differences is based on the comprehensive score of cream yield(40%)and indicator components(60%).Results The HPLC fingerprint similarity of Huaihua powder prepared by 5 decoction methods was greater than 99%.There was no significant difference(P>0.05)in the yield of ointment and the content of indicator components between the induction cooker one decoction and the induction cooker twice decoction methods.The yield of ointment and the extraction rate of indicator components were significantly higher in twice normal pressure decoction using a decoction machine than once normal pressure decoction using a decoction machine(P<0.05).The index component score of machine under pressure decoction once was the highest,but the comprehensive score of twice normal pressure decoction was the highest,with a combined score of 92.13 and 89.58,respectively,far higher than the 36.01,18.79,and 15.60 of the other three decoction methods.Classify the decoction into three categories through cluster analysis.Orthogonal partial least squares-discriminant analysis was used to screen for rutin,naringin and neohesperidin as differential biomarkers.Conclusion The quality of Huaihua powder decocted by a decoction machine is significantly better than that by an induction cooker,and the twice decocted at normal pressure by the decoction machine are significantly better than those decocted at normal pressure once.Decoction under pressure once may be a better choice.

Objective:To investigate the association of skeletal muscle function(including muscle strength and physical performance) and insulin resistance as well as type 2 diabetes mellitus(T2DM).Methods:The retrospective study included 942 patients who visited the Department of Geriatrics at Renji Hospital, Shanghai Jiao Tong University School of Medicine, between October 2020 and July 2024. Low skeletal muscle function was defined as either reduced muscle strength or impaired physical performance. Muscle strength was assessed by grip strength, while physical performance was evaluated using the 5-time chair stand test. The associations between muscle function, insulin resistance, and T2DM were analyzed.Results:A significant association was observed between decreased skeletal muscle function and a higher prevalence of T2DM( P=0.001). Further analysis revealed that decreased physical performance was significantly associated with increased T2DM prevalence( P<0.001), whereas reduced muscle strength showed no significant association with T2DM prevalence( P=0.331). Linear regression analysis indicated that both the homeostasis model assessment of insulin resistance(HOMA2-IR) and fasting blood glucose levels increased significantly with longer chair stand times( P<0.05). Restrictive cubic spline(RCS) analysis demonstrated a nonlinear relationship between chair-rising time and HOMA2-IR. Notably, when the cumulative chair-rising time exceed 8.1 s, HOMA2-IR increased significantly with prolonged chair stand time. Logistic regression analysis showed that compared with patients with normal physical performance, those with decreased physical performance had significantly higher odds of T2DM( OR=2.64, P<0.001) and insulin resistance( OR=2.34, P=0.002). Conclusion:Decline in physical performance is significantly positively associated with insulin resistance and the risk of T2DM. Morever, when the cumulative chair stand time exceed 8.1 s, HOMA2-IR increases progressively with further prolongation of chair stand time.

AIM:To optimize the clinical dosage and administration regimen of a novel long-acting injectable aripiprazole microsphere(LZMT05)using plasma concentration data from two clinical trials.METHODS:Plasma concentrations were collected from 196 schizophrenia patients administered LZMT05,and a population pharmacokinetic(Pop-PK)model was developed.The therapeutic window was defined as the steady-state trough-to-peak concentration range(94.0-534 ng/mL)of oral ar-ipiprazole.Multiple clinical scenarios were simulat-ed to identify the optimal regimen.RESULTS:A one-compartment model with dual first-order ab-sorption and first-order elimination characterized LZMT05 pharmacokinetics.Covariates like sex and CYP2D6 genotype were integrated into the final model.Simulations demonstrated that switching from 10 mg oral aripiprazole to 350 mg LZMT05 ev-ery 4 weeks sustained concentrations within the therapeutic window with minimal peak-to-trough fluctuations.CONCLUSION:The PopPK-guided opti-mized LZMT05 regimen maintained drug exposure within the therapeutic window,suggesting favor-able efficacy and safety.

AIM:To optimize the clinical dosage and administration regimen of a novel long-acting injectable aripiprazole microsphere(LZMT05)using plasma concentration data from two clinical trials.METHODS:Plasma concentrations were collected from 196 schizophrenia patients administered LZMT05,and a population pharmacokinetic(Pop-PK)model was developed.The therapeutic window was defined as the steady-state trough-to-peak concentration range(94.0-534 ng/mL)of oral ar-ipiprazole.Multiple clinical scenarios were simulat-ed to identify the optimal regimen.RESULTS:A one-compartment model with dual first-order ab-sorption and first-order elimination characterized LZMT05 pharmacokinetics.Covariates like sex and CYP2D6 genotype were integrated into the final model.Simulations demonstrated that switching from 10 mg oral aripiprazole to 350 mg LZMT05 ev-ery 4 weeks sustained concentrations within the therapeutic window with minimal peak-to-trough fluctuations.CONCLUSION:The PopPK-guided opti-mized LZMT05 regimen maintained drug exposure within the therapeutic window,suggesting favor-able efficacy and safety.