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.

Objective: To conduct a scoping review on the types, construction methods and predictive performance of health literacy prediction models based on machine learning methods, so as to provide the reference for the improvement and application of such models. Methods: Publications on health literacy prediction models conducted using machine learning methods were retrieved from CNKI, Wanfang Data, VIP, PubMed and Web of Science from inception to May 1, 2024. The quality of literature was assessed using the Prediction Model Risk of Bias ASsessment Tool. Basic characteristics, modeling methods, data sources, missing value handling, predictors and predictive performance were reviewed. Results: A total of 524 publications were retrieved, and 22 publications between 2007 and 2024 were finally enrolled. Totally 48 health literacy prediction models were involved, and 25 had a high risk of bias (52.08%), with major issues focusing on missing value handling, predictor selection and model evaluation methods. Modeling methods included regression models, tree-based machine learning methods, support vector machines and neural network models. Predictors primarily encompassed factors at four aspects: individual, interpersonal, organizational and society/policy aspects, with age, educational level, economic status, health status and internet use appearing frequently. Internal validation was conducted in 14 publications, and external validation was conducted in 4 publications. Forty-two models reported the areas under the receiver operating characteristic curve, which ranged from 0.52 to 0.983, indicating good discrimination. Conclusion Health literacy prediction models based on machine learning methods perform well, but have deficiencies in risk of bias, data processing and validation.

Functional cure is currently recommended by guidelines as the ideal treatment goal for the prevention and treatment of chronic hepatitis B （CHB） in China and globally， and it is defined as sustained and undetectable serum HBsAg and HBV DNA， HBeAg clearance， and presence or absence of HBsAg seroconversion， accompanied by resolution of liver inflammation， histopathological improvements， and a significant reduction in the incidence rate of end-stage liver disease. HBV can integrate into the host genome and contribute to the continuous production of HBsAg， which can occur in the early stage of chronic HBV infection. In addition to the covalently closed circular DNA that is hard to be eliminated in liver tissue， HBsAg derived from HBV integration independent of viral replication may be the most important factor for the difficulty in achieving functional cure after antiviral therapy in patients with hepatitis B. This article reviews the research advances in HBV integration in recent years and discusses its impact on functional cure.

This paper summarizes Professor HAN Mingxiang's clinical experience in the use of Zeqi （Euphorbia HelioscopiaL.）. It is believed that Zeqi （Euphorbia HelioscopiaL.） has the effects of promoting qi， relieving water retention and swelling， resolving phlegm， stopping cough， dissipating masses， activating blood， removing stasis， and detoxifying. In clinical practice， Zeqi （Euphorbia HelioscopiaL.） is flexibly applied in the treatment of skin diseases， respiratory diseases， tumors， etc. For instance， in treating psoriasis with the pathogenesis of damp-heat toxin， a compound prescription of Zeqi Decoction （泽漆汤） is formulated. For bronchial asthma with kidney deficiency and water retention， Zeqi Decoction is commonly combined with Wuling Powder （五苓散） in adjusted doses. For lung nodules with a combination of deficiency， phlegm， stasis， and toxin， a Lung Nodule Prescription is proposed. For advanced lung cancer with both qi and yin deficiency and toxin accumulation， Qiyu Sanlong Decoction （芪玉三龙汤） is suggested， and for cancer-related ascites with qi deficiency and water retention， Wuling Powder combined with Zeqi （Euphorbia HelioscopiaL.）is chosen.

ObjectiveTo explore the typical syndromes and their characteristic of symptoms and signs with high diagnostic value in patients with metabolic syndrome （MS）. MethodsTraditional Chinese medicine （TCM） diagnostic information was collected from 135 MS patients. Syndrome element differentiation and latent class analysis （LCA） were applied to identify the major TCM syndromes in MS patients. Symptoms were analyzed based on the differentiated syndromes， and a binary logistic regression model was constructed to determine symptoms and signs with high diagnostic value. ResultsA total of 135 MS patients were included， involving 163 symptoms and signs with a total frequency of 1749； twenty-three syndrome elements were extracted， 367 times frequency in total， among which 8 syndrome elements occurred ≥10 times with 323 frequencies （88.01% of the total）. These included location-related elements such as kidney （48 times）， spleen （14 times）， and stomach （14 times）， and nature-related elements such as phlegm （71 times）， yin deficiency （64 times）， dampness （57 times）， heat （42 times）， and qi deficiency （13 times）. Based on LCA， the 135 patients were categorized into two groups distinguished by the syndrome elements of dampness and phlegm， forming the "phlegm-dampness syndrome" as the major syndrome type. Nine high-frequency symptoms and signs associated with the phlegm-dampness syndrome were identified，i.e. obesity （39 times）， greasy coating （38 times）， slippery pulse （33 times）， white coating （31 times）， preference for fatty and heavy foods （30 times）， excessive urination （30 times）， fatigue and lack of strength （29 times）， wiry pulse （25 times）， and dark red tongue （25 times）. A binary logistic regression model was constructed combining these nine symptoms and signs with the LCA classification results， ultimately identifying obesity， greasy coating， fatigue and lack of strength， and white coating as independent factors associated with the phlegm-dampness syndrome in MS patients （P＜0.05）. ConclusionThe major TCM syndrome in MS patients is phlegm-dampness syndrome， and obesity， greasy coating， fatigue and lack of strength， and white coating are the typical symptoms and signs for diagnosing phlegm-dampness syndrome in MS patients.

ObjectiveTo construct and validate a clinical prediction model for Qi deficiency and blood stasis syndrome in chronic heart failure （CHF），aiming to assist clinical diagnosis and provide tools and methods for individualized treatment of CHF. MethodsThe clinical data of patients with chronic heart failure treated at Dongzhimen Hospital of Beijing University of Chinese Medicine from January 2022 to January 2024 were retrospectively collected. The patients were randomly divided into a training group and a validation group with a ratio of 7∶3. First， the least absolute shrinkage and selection operator （LASSO） regression analysis was used to preliminarily screen the predictive factors affecting the diagnosis of Qi deficiency and blood stasis syndrome in CHF. Subsequently， the Logistic regression method was applied to conduct a more in-depth and detailed analysis of these factors. Variables with P<0.05 in the results of the multi-factor Logistic regression were carefully selected and included. Based on the regression coefficients obtained from this analysis， a model was constructed， and a nomogram was accurately drawn. Using R software，the receiver operating characteristic （ROC） curve，calibration curve，and decision curve analysis （DCA） were precisely drawn. These analyses were used to comprehensively evaluate the model from three crucial aspects： discrimination，calibration，and clinical applicability. Additionally， the accuracy，specificity，sensitivity，positive predictive value，and negative predictive value of the model were meticulously calculated to conduct a more all-round and comprehensive assessment. ResultsIn total， 168 cases were successfully obtained in the training group， and 71 cases were included in the validation group. After a thorough comparison， it was found that there were no statistically significant differences in the baseline data between the two groups. After being rigorously screened by the LASSO-multivariate logistic regression method， dark red tongue，smoking history，cardiac troponin I，and N-terminal pro-B-type natriuretic peptide （NT-ProBNP） were identified as the influencing factors for diagnosing patients with the Qi deficiency and blood stasis syndrome in CHF. The constructed model demonstrated an area under the curve （AUC） of 0.812 in the training group and 0.719 in the validation group. The calibration curve showed that the predicted curve of the model was close to the actual observed curve. DCA indicated that the model could provide substantial clinical benefits for patients at the decision thresholds ranging from 0.2 to 0.9. ConclusionThe clinical prediction model for Qi deficiency and blood stasis syndrome in chronic heart failure constructed in this study shows good performance. It has certain application value in clinical practice， which may contribute to the improvement of the diagnosis and treatment of CHF patients with this syndrome.

AIM: To compare the clinical outcomes of extended depth-of-focus intraocular lenses(EDOF IOLs)using either micromonovision implantation or mixed implantation of EDOF and diffractive bifocal IOLs.METHODS: This retrospective clinical trial included 130 patients(260 eyes), who were divided into two groups. Group RR comprised 70 patients(140 eyes)bilaterally implanted with ZXR00 IOLs(Tecnis ZXR00, where one target was -0.5 D to -0.75 D and the other was 0 to -0.25 D). Group RM comprised 60 patients(120 eyes)unilaterally implanted with both ZXR00 and ZMB00 IOLs(Tecnis ZMB00, 0 to -0.25 D). Postoperative outcomes were compared after 3 mo, including visual acuity, defocus curves, stereoacuity, modulation transfer functions(MTFs), higher-order aberrations, and Visual Function-14(VF-14)questionnaire responses.RESULTS: Group RR had superior bilateral intermediate vision, while the group RM had superior bilateral near vision(both P<0.05). Group RM also exhibited superior MTFs and reduced higher-order aberrations(both P<0.05). Stereoacuity and VF-14 questionnaire results showed no statistically significant difference between groups(P>0.05).CONCLUSION: The implantation of micromonovision has significantly improved near vision. IOLs and their collocation can be customized according to individual patient needs to achieve precise treatment and provide cataract patients with high-quality vision.

AIM: To compare the clinical outcomes of extended depth-of-focus intraocular lenses(EDOF IOLs)using either micromonovision implantation or mixed implantation of EDOF and diffractive bifocal IOLs.METHODS: This retrospective clinical trial included 130 patients(260 eyes), who were divided into two groups. Group RR comprised 70 patients(140 eyes)bilaterally implanted with ZXR00 IOLs(Tecnis ZXR00, where one target was -0.5 D to -0.75 D and the other was 0 to -0.25 D). Group RM comprised 60 patients(120 eyes)unilaterally implanted with both ZXR00 and ZMB00 IOLs(Tecnis ZMB00, 0 to -0.25 D). Postoperative outcomes were compared after 3 mo, including visual acuity, defocus curves, stereoacuity, modulation transfer functions(MTFs), higher-order aberrations, and Visual Function-14(VF-14)questionnaire responses.RESULTS: Group RR had superior bilateral intermediate vision, while the group RM had superior bilateral near vision(both P<0.05). Group RM also exhibited superior MTFs and reduced higher-order aberrations(both P<0.05). Stereoacuity and VF-14 questionnaire results showed no statistically significant difference between groups(P>0.05).CONCLUSION: The implantation of micromonovision has significantly improved near vision. IOLs and their collocation can be customized according to individual patient needs to achieve precise treatment and provide cataract patients with high-quality vision.

ObjectiveFor prepubertal and urgently treated malignant tumor patients, ovarian tissue cryopreservation and transplantation represent more appropriate fertility preservation methods. Current clinical practices often involve freezing ovarian tissue with high concentrations of cryoprotectants (CPAs) and thawing with water baths. These processes lead to varying degrees of toxicity and devitrification damage to ovarian tissue. Therefore, this paper proposes optimized methods for vitrification of ovarian tissues based on sodium alginate hydrogel encapsulation and magnetic induction nanowarming technology. MethodsFirstly, the study investigated the effects of sodium alginate concentration, the sequence of hydrogel encapsulation and CPAs loading on vitrification efficiency of encapsulated ovarian tissue. Additionally, the capability of sodium alginate hydrogel encapsulation to reduce the required concentration of CPAs was validated. Secondly, a platform combining water bath and magnetic induction nanowarming was established to rewarm ovarian tissue under various concentrations of magnetic nanoparticles and magnetic field strengths. The post-warming follicle survival rate, antioxidant capacity, and ovarian tissue integrity were evaluated to assess the efficacy of the method. ResultsThe study found that ovarian tissue encapsulated with 2% sodium alginate hydrogel exhibited the highest follicle survival rate after vitrification. The method of loading CPAs prior to encapsulation proved more suitable for ovarian tissue cryopreservation, effectively reducing the required concentration of CPAs by 50%. A combination of 8 g/L Fe₃O₄ nanoparticles and an alternating magnetic field of 300 Gs showed optimal warming effectiveness for ovarian tissue. Combining water bath rewarming with magnetic induction nanowarming yielded the highest follicle survival rate, enhanced antioxidant capacity, and preserved tissue morphology. ConclusionSodium alginate hydrogel encapsulation of ovarian tissue reduces the concentration of CPAs required during the freezing process. The combination of magnetic induction nanowarming with water bath provides an efficient method ovarian tissue rewarming. This study offers novel approaches to optimize ovarian tissues vitrification.

In the field of oral medicine, 3D-printed individualized titanium mesh technology is gradually becoming an important means for the treatment of severe alveolar bone defect augmentation. This article provides a comprehensive analysis of the advantages of this technology, the evaluation of osteogenic effects, and the progress of research in clinical applications. In response to the current issue of variability in bone augmentation outcomes, this paper delves into multiple factors affecting bone augmentation effects, including individualized titanium mesh design (involving the thickness, pore size, pore shape, porosity, contour shape, selection of titanium alloy materials, and 3D printing technology), intraoperative procedures (the accuracy of placement during 3D-printed individualized titanium mesh surgery), and postoperative care (including the prevention of complications, formation of pseudoperiosteum, and stability of the titanium mesh). By integrating the clinical experience and research findings of our team, we propose a series of targeted optimization strategies, including designing, manufacturing, and clinically applying self-positioning individualized titanium meshs (positioning wings + individualized titanium meshs) to improve the positioning accuracy of the titanium mesh; propose individualized treatment processes and titanium mesh design schemes based on specific conditions of alveolar bone defects and soft tissue status; and emphasize the importance of long-term stable fixation of the titanium mesh to reduce the risk of postoperative mesh loosening and displacement. In addition, we appropriately summarize the evaluation methods for the bone augmentation effects of 3D-printed individualized titanium meshes, covering the following key indicators: (1) vertical bone augmentation and horizontal bone augmentation; (2) changes in bone contour morphology; (3) bone volume increase; (4) clinical indicators (surgical success rate, titanium mesh exposure, infection rate, and postoperative recovery); (5) aesthetic effect evaluation; (6) long-term stability; (7) radiological assessment; (8) patient satisfaction; and (9) precision of surgical operation, aiming to assist doctors in comprehensively assessing and in-depth analyzing the surgical outcomes to achieve the best therapeutic effects. The purpose of this article is to provide a reference for the optimization and clinical application of 3D-printed individualized titanium mesh technology and to lay a theoretical foundation for achieving the best osteogenic effects.