ObjectiveHistorically documented Zhejiang Atractylodis Macrocephalae Rhizoma（Baizhu） possesses premium characteristics such as phoenix-like head and crane-like neck， pronounced sweetness， and fragrant aroma. However， its current market circulation is low， and the processed products with Zhejiang-style characteristics are at the risk of being lost. This study aims to preserve the ancient Zhejiang-style processing techniques and evaluate them using modern scientific methods. MethodsMultidimensional intelligent sensory evaluation was used to digitally characterize the "quality-structure" of the external appearance of nine-steamed and nine-processed Baizhu medicinal materials（intermediate processed products） and the "odor-taste" of the internal quality of its decoction pieces（slices）， and the appearance parameters were digitally characterized by colorimeter， texture analyzer， electronic nose and electronic tongue， the chemical composition was analyzed via ultra-performance liquid chromatography-quadrupole-time-of-flight mass spectrometry（UPLC-Q-TOF-MS/MS）. Then， cluster analysis on the differences in odor between the medicinal materials（intermediate processed products） and decoction pieces（slices） of nine-steamed and nine-processed Baizhu was conducted， as well as the differences in taste between water-soluble and alcohol-soluble extracts of the decoction pieces（slices）， and the correlation analysis of chroma value-alcohol-soluble extract content-component response value. ResultsThe nine-steamed and nine-processed Baizhu had a dark brown to black epidermis， a brownish-yellow to brownish-gray cross-section， a slightly tough texture， a faint odor， and a slightly sweet， bitter and pungent taste. Texture analyzer measurements revealed minimal adhesion and maximum recovery in the middle section of the characteristic processed Baizhu， consistent with the processing endpoint of thorough steaming and cooking. The head section showed the highest internal hardness， elasticity and chewiness， indicating a denser texture in this area. The electronic nose sensor could clearly distinguish the difference between the medicinal materials and its decoction pieces， with a more significant clustering effect at 60 ℃ for 30 minutes compared to ambient temperature headspace for 2 hours， highlighting the significant impact of the baking degree before slicing on the quality. The electronic tongue taste signal map clearly distinguished the differences between water-soluble and alcohol-soluble extracts of nine-steamed and nine-processed Baizhu decoction pieces， and the addition of auxiliary materials during processing could enhance its alcohol-soluble extract content. A total of 82 chemical components were identified in the characteristic processed Baizhu. After processing， the contents of 58 components increased， while 24 components decreased. Correlation analysis revealed significant negative correlations（P<0.01） between ethanol-soluble extract content and colorimetric values of brightness（L^*）， yellow-bule value（b^*）， and total color difference（E^*_ab）. E^*_ab showed marked negative correlations（P<0.05） with the response values of isochlorogenic acid A and C. ConclusionThis study establishes a modern intelligent sensory evaluation model for multidimensional holographic characterization of nine-steamed and nine-processed Baizhu， clarifying the correlation between increased isochlorogenic acid content and the visual color appearance after different steaming cycles， as well as its intrinsic alcohol-soluble extracts. This provides a reference for quality evaluation and processing standards of the Zhejiang-style characteristic processed products.

Background/Aims: Lenvatinib resistance remains a critical barrier in advanced hepatocellular carcinoma (HCC) therapy. However, the underlying mechanisms and strategies for reversing resistance remain incompletely understood. Methods: Integrated transcriptomics of lenvatinib-resistant patient tumors and an acquired-resistance murine model identified a novel macrophage subpopulation. Functional validation employed CRISPR-SAM screening, conditioned medium (CM) assays, subcutaneous/orthotopic xenografts, patient-derived organoids (PDOs), and patient-derived xenografts (PDXs). Mechanistic studies included ChIP-qPCR, co-immunoprecipitation, and pharmacologic targeting. Clinical relevance was assessed in a retrospective cohort. Results: Resistant HCC exhibited significant enrichment of a COLEC12high TAM subset , which correlated with poor survival and treatment response. These TAMs secreted neuregulin-1 (NRG1) , activating HER2/HER3-AKT signaling in tumor cells to drive cancer stemness and lenvatinib resistance. Mechanistically, in TAMs COLEC12 sequestered STAT1 in the cytoplasm, preventing its phosphorylation, and thereby derepressing STAT3-mediated NRG1 transcription. Depletion of NRG1 reversed the stemness phenotypes and resensitized tumors to lenvatinib both in vitro and in vivo. Clinically, high NRG1 expression predicted an inferior lenvatinib response and shorter survival. Crucially, the bispecific anti-HER2/HER3 antibody zenocutuzumab restored lenvatinib efficacy in PDOs, PDXs, and murine models. Conclusions Our work establishes the COLEC12high TAM/NRG1 axis as a master regulator of therapeutic resistance and identifies NRG1 as a predictive biomarker, providing a clinically actionable strategy to overcome lenvatinib resistance in HCC.

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 widespread adoption of low-dose CT screening and the extensive application of high-resolution CT, the detection rate of sub-centimeter lung nodules has significantly increased. How to scientifically manage these nodules while avoiding overtreatment and diagnostic delays has become an important clinical issue. Among them, lung nodules with a consolidation tumor ratio less than 0.25, dominated by ground-glass shadows, are particularly worthy of attention. The therapeutic challenge for this group is how to achieve precise and complete resection of nodules during surgery while maximizing the preservation of the patient's lung function. The "watershed topography map" is a new technology based on big data and artificial intelligence algorithms. This method uses Dicom data from conventional dose CT scans, combined with microscopic (22-24 levels) capillary network anatomical watershed features, to generate high-precision simulated natural segmentation planes of lung sub-segments through specific textures and forms. This technology forms fluorescent watershed boundaries on the lung surface, which highly fit the actual lung anatomical structure. By analyzing the adjacent relationship between the nodule and the watershed boundary, real-time, visually accurate positioning of the nodule can be achieved. This innovative technology provides a new solution for the intraoperative positioning and resection of lung nodules. This consensus was led by four major domestic societies, jointly with expert teams in related fields, oriented to clinical practical needs, referring to domestic and foreign guidelines and consensus, and finally formed after multiple rounds of consultation, discussion, and voting. The main content covers the theoretical basis of the "watershed topography map" technology, indications, operation procedures, surgical planning details, and postoperative evaluation standards, aiming to provide scientific guidance and exploration directions for clinical peers who are currently or plan to carry out lung nodule resection using the fluorescent microscope watershed analysis method.

Objectives:To explore the predictive value of residual Murray's law-based quantitative flow ratio(μQFR)on long-term vessel-oriented composite endpoints(VoCE).Methods:This retrospective study included 3 510 patients from the FAVOR Ⅲ China trial.Offline residual μQFR analysis was performed on all vessels(diameter≥2.5 mm)with 50%-90%stenotic lesions.Patients were stratified into high-,intermediate-,and low-risk groups based on residual μQFR tertiles.The primary endpoint was 3-year VoCE,defined as a composite of cardiac death related to the target vessel,target vessel-related spontaneous myocardial infarction,and ischemia-driven target vessel revascularization.Results:Offline analysis was performed on 5 256 vessels from 3 510 patients.The mean residual μQFR was 0.92±0.75.The high-risk group(residual μQFR≤0.91)with 1 554 patients(1 958 vessels);the intermediate-risk group(residual μQFR 0.92-0.96)with 1 211 patients(1 906 vessels);and the low-risk group(residual μQFR>0.96)with 745 patients(1 392 vessels).Over 3-year follow-up,VoCE occurred in 227 vessels(4.3%).The 3-year VoCE incidence was significantly higher in the high-risk group compared to the intermediate-and low-risk groups(6.2%vs.4.1%vs.2.5%,log-rank P<0.001),primarily driven by ischemia-driven target vessel revascularization(5.0%vs.3.0%vs.1.6%,log-rank P<0.001).Hypertension(OR=0.83,95%CI:0.72-0.96),hypercholesterolemia(OR=0.84,95%CI:0.73-0.97),bifurcation lesions(OR=0.72,95%CI:0.63-0.83),moderate/severe calcification(OR=0.70,95%CI:0.57-0.84),and tandem lesions(OR=0.59,95%CI:0.47-0.75)were independent predictors of lower residual μQFR values.Conclusions:Lower residual μQFR is significantly associated with increased VoCE risk during the 3-year follow up period.

Objective To explore the value of MR modulated flip angle technique in refocused imaging with extended echo train(MATRIX)contrast enhanced(CE)T1-weighted fluid attenuated inversion recovery(T1 FLAIR)for detecting skull metastases.Methods Forty-four patients with malignant tumors who underwent head MR scanning for screening skull metastasis were prospectively enrolled,and skull metastasis were then confirmed by pathology or imaging examinations,including MRI,CT,radionuclide bone imaging(BS),PET/CT and follow-up.Head MATRIX CE-T1 FLAIR(group A),3D gradient recalled echo_fast spin echo with magnetization preparation(GRE_fsp)CE-T1 FLAIR(group B)and fast spin echo(FSE)CE-T1 FLAIR(group C)images of all 44 cases were acquired.The subjective scores(including images quality and diagnostic confidence)and objective evaluation results of images were compared among groups.Taken BS or PET/CT results as standards,the efficacy of 3 kinds of images for detecting skull metastases was calculated.Results The subjective scores of images quality and diagnostic confidence,as well as signal-to-noise ratio(SNR)in group A and C were all higher than those in group B(all P＜0.001),and signal intensity(SI)metastases in group A was higher than those in group B and C(both P＜0.05).No significant difference of subjective score and SNR was found between groups A and C,nor of SImetastases between groups B and C(all P＞0.05).Totally 102 skull metastases were diagnosed with PET/CT or BS,while 129,151 and 115 lesions were detected in group A,B and C,respectively,with accuracy rate of 79.07%(102/129),67.55%(102/151)and 88.70%(102/115),respectively.Conclusion MATRIX CE-T1 FLAIR sequence could be used to detect skull metastases.

Objective To investigate the distribution of A subgroups in the A and AB blood type populations among voluntary blood donors in Zhongshan,study the antigen-antibody characteristics of A subgroups,establish a local A subgroup database,and support the development of precision medicine.Methods ABO subgroup screening was performed using the microplate method.Specimens negative for monoclonal anti-A1 reactivity underwent sequencing of exons 1～7 of the ABO gene to confirm genotypes.Cryopreservation and thawing of glycerolized subgroup red blood cells(RBCs),as well as preservation efficacy of concentrated human-derived antibodies with preservatives,were studied.Results Among 1 212 blood donor specimens,28 subgroup specimens were identified,with a prevalence of 1.54%(15/971)in blood type A and 5.39%(13/241)in blood type AB.Sequencing of 10 specimens revealed 7 ABO genotypes:ABO*A2.01/O.01.02(2 cases),ABO*A1.02/B.01(3 cases),ABO*BA.02/O.01.02,ABO*AW.31.02-05/A2.05,ABO*A2.05/B.01,ABO*A2new/O.01.01,and ABO*A1.02/O.01.01(1 case each).Additionally,one rare allele mutation(c.700C>G)and one novel allele mutation(c.203G>T)(GenBank accession number:PQ152337)were identified.Human anti-A1 antibodies with a titer of 8 were successfully concentrated.Optimal preservation conditions included 0.1%preservative concentration and cryopreserved subgroup RBCs stored at 4℃for 3 days post-thaw.Conclusion The predominant A subgroups in Zhongshan donors are A2 and B(A).A preliminary database for A2 and A2B subgroups is established,along with the discovery of a novel ABO allele mutation.Cryopreservation with glycerol,PEG antibody concentration,and ProClin 300 preservative demonstrate effective applications in preserving ABO blood group antigens and antibodies.

Objective To explore the types of symptom clusters in patients with bladder instillation and identify the core symptoms through symptom network analysis,and to provide evidence for symptom management of the patients.Methods Convenience sampling was used to select 226 patients with bladder instillation for bladder cancer at a Tier-IIIA hospital in Guiyang from March 2023 to July 2024.Data were collected through review of medical record,general information questionnaires and symptom assessment questionnaires specific to the patients with bladder instillation.Exploratory factor analysis was used to extract symptom clusters,and symptom relationships were analysed using R language for network layout and centrality calculations.Results A total of 223 patients with bladder cancer completed the survey.Four symptom clusters were identified,namely the urinary system symptom cluster,digestive system symptom cluster,somatic symptom cluster and psychological symptom cluster,with a cumulative variance contribution rate of 66.038%.The symptom network analysis showed strong associations between dysuria and urethral pain during catheterisation,incomplete emptying and dysuria,as well as distress and poor sleep quality.In terms of centrality indicators,the top three symptoms by strength were dysuria(rS=2.26),incomplete emptying(rS=0.99)and poor sleep quality(rS=0.90).Of the expected impacts,the top three were dysuria(rE=2.09),poor sleep quality(rE=1.34)and frequency of urinary(rE=0.55).Regarding the closeness centrality,the top three were dysuria(rC=2.23),incomplete emptying(rC=0.64)and poor sleep quality(rC=0.54).Dysuria had the highest strength,expected impact and closeness centrality,indicating the dysuria was the core symptom in the patients with bladder cancer.Conclusion For the patients with bladder instillation experience,multiple and interconnected symptoms appear at the same time and together they form a symptom clusters,of which the pain in urination is the core symptom.Medical staff should consider symptom prevalence and core symptoms and to develop the targeted and precise management strategies for targeted nursing.

Objective:To investigate the current situation and influencing factors of work ability in gynecological cancer patients, so as to provide a reference for occupational rehabilitation management of cancer patients.Methods:A total of 183 gynecological cancer patients who visited the gynecological oncology outpatient department of Women′s Hospital of Nanjing Medical University from November 2022 to March 2023 were selected by the convenience sampling. The General Information Questionnaire, Return-to-Work Self-efficacy Questionnaire, Social Support Rating Scale, the European Organization for Research and Treatment of Cancer Quality of Life Quesionnaire Core 30, Work Ability Index were selected for cross-sectional investigaton. The multiple linear regression analysis was used to explore the influencing factors of work ability in gynecological cancer patients.Results:A total of 189 questionnaires were sent out in this study, and 183 were effectively collected, with an effective recovery rate of 96.83% (183/189). The patients were (44.64 ± 7.06) years old. The scores of the patients were (27.77 ± 7.58) points on Work Ability Index, (4.72 ± 1.14) points on Return-to-Work Self-efficacy Questionnaire, (86.93 ± 23.44) points on Social Support Rating Scale, (79.46 ± 19.53) points on overall health status area and (41.23 ± 27.80) points on the field of fatigue symptoms area of the European Organization for Research and Treatment of Cancer Quality of Life Quesionnaire Core 30. Multiple linear regression analysis showed that fatigue, comorbidities, clinical stage of disease, primary treatment, per capita monthly income of families, return-to-work self efficacy and job nature were independent influencing factors of work ability in gynecological cancer patients ( t values were -10.47-2.86, all P<0.05), which explained 67.9% of the total variance. Conclusions:Clinical medical staff should pay attention to the influencing factors that affect work ability in gynecological cancer patients, in order to take targeted occupational rehabilitation measures to improve their work ability.

Since the birth of the first "test-tube baby" in Chinese mainland in 1988, assisted reproductive technology (ART) in China has matured significantly. The number of ART cycles has surpassed one million, and the number of assisted reproductive institutions and practitioners has attained a significant scale, contributing to the establishment of a fertility-friendly society. However, due to the complexity of the ART process, the diversity of personnel backgrounds, and the profound impact of any error that may occur, there is an urgent need to establish an efficient and effective safety management model for error prevention. This paper aims to outline the key processes and steps involved in the implementation of ART, explore control measures for these critical processes, and delve into error prevention strategies for gamete and embryo laboratories through the creation and utilization of a "gamete safety checklist".