With the widespread application of low-dose computed tomography (CT), the detection rate of multiple lung cancers (MLCs) is gradually increasing. The diagnosis and treatment of MLCs have become a major challenge in clinical practice in thoracic surgery and oncology. In April 2025, the Lung Cancer Professional Committee of the China Anti-Cancer Association (CACA) organized multidisciplinary experts from both domestic and international fields to release the first edition of the CACA Expert Consensus on the Diagnosis and Treatment of Multiple Lung Cancers, providing systematic recommendations for the diagnostic system, molecularassessment strategies, and surgical and non-surgical management of MLCs. This article provides a detailed interpretation of the core content of this consensus and, by incorporating the latest research progress in the field, delves into the pathogenesis, precise diagnostic strategies, and individualized treatment pathways for multiple lung cancers, aiming to offer a more comprehensive reference for clinical practice.

The construction of a training system for visiting physicians in the department of rare diseases in China is an important measure to improve the overall diagnosis and treatment capacity for rare diseases and address the critical challenge of insufficient knowledge and skills among clinicians in practice. This article systematically describes the visiting physician training system established by the Department of Rare Diseases at Peking Union Medical College Hospital. It summarizes the training objectives and positioning, design logic, and learning modules of the system, aiming to provide a reference for the construction of the specialized talent team for rare diseases in China.

ObjectiveTo explore the structural characteristics， biocompatibility， anti-inflammatory and antioxidant properties of hyaluronic acid （HA）/silk fibroin （SF） composite hydrogel scaffolds loaded with epigallocatechin gallate （EGCG）， and to provide a new material basis for the treatment of periodontitis. MethodsThe composite hydrogel scaffolds were constructed by cross-linking HA and SF and loaded with EGCG. The water absorption rate， degradation property and material characteristics were detected by scanning electron microscopy. The cytocompatibility and anti-inflammatory and antioxidant properties were evaluated by in vitro experiments. ResultsThe EGCG-loaded scaffolds exhibited a porous network structure and desirable swelling properties. In vitro experiments demonstrated that the scaffolds possessed good biocompatibility， along with the ability to inhibit the expression of inflammatory factors and scavenge reactive oxygen species. ConclusionThe HA/SF-EGCG composite scaffolds have excellent biocompatibility and dual functional activities of anti-inflammatory and antioxidant， providing a new strategy for improving the clinical treatment effect of periodontitis.

OBJECTIVE To develop and validate interpretable machine learning models for predicting the risk of medication-related osteonecrosis of the jaw （MRONJ） and surgical outcomes， thereby providing quantitative support for MRONJ risk assessment and treatment decision-making.METHODS Two study cohorts were established. Cohort A adopted a nested case-control study design to develop a predictive model for the risk of MRONJ onset. Cohort B comprised patients with MRONJ from Cohort A who underwent surgical treatment and met the follow-up eligibility criteria， and employed a prospective follow-up cohort study design to develop a predictive model for the efficacy of MRONJ surgery. After missing-data processing， variable standardization， and encoding， predictive features were selected using the least absolute shrinkage and selection operator （LASSO） regression， and collinearity was assessed using the variance inflation factor （VIF）. Random Forest （RF）， eXtreme Gradient Boosting （XGB）， Multi-layer Perceptron （MLP）， Support Vector Machine （SVM）， and Gaussian Naive Bayes （NB） models were subsequently developed using the selected features. Hyperparameter optimization and internal performance evaluation were performed using two-level nested cross-validation repeated 20 times. In Cohort B， the synthetic minority over-sampling technique （SMOTE） was applied within the inner training folds to address class imbalance. Model performance was comprehensively evaluated using the receiver operating characteristic （ROC） curve， the precision-recall （PR） curve， calibration curve， and decision curve analysis （DCA）. Shapley additive explanations （SHAP） were used to quantify the relative contributions of individual clinical features to model predictions.RESULTS Seven clinical features， including alkaline phosphatase and tooth extraction， were retained for Cohort A； whereas eight clinical features， including age and duration of medication use， were retained for Cohort B. In Cohort A， the area under the ROC curve， the area under the PR curve， Brier score， sensitivity， and specificity of the RF model were 0.94， 0.92， 0.09， 0.92， and 0.85， respectively； the corresponding values in Cohort B were 0.93， 0.93， 0.12， 0.83， and 0.93， respectively. The results of calibration curves and DCA indicated that the RF models achieved favorable calibration and clinical net benefit， with VIF values for all variables below 5. SHAP visualization results showed that alkaline phosphatase， tooth extraction， and cumulative drug dose made substantial contributions to MRONJ risk prediction in Cohort A， whereas age， duration of medication use， and MRONJ stage contributed substantially to surgical outcome prediction in Cohort B.CONCLUSIONS The RF-based models for predicting MRONJ risk and surgical outcomes demonstrated good discrimination， accuracy of probabilistic predictions， and potential clinical utility during internal validation. These models may provide decision support for comprehensive MRONJ risk management and individualized clinical decision-making. However， external validation in independent， multicenter， and geographically diverse cohorts is still required.

Objective To analyze the clinical and epidemiological characteristics of influenza A(H3N2) in Tangshan City, Hebei Province, from 2023 to 2025, and to provide a scientific basis for precise prevention and control of local influenza. Methods The influenza-like cases and influenza outbreak cases in the influenza surveillance sentinel hospitals in Tangshan City from January 2023 to December 2025 were included in this study. The clinical characteristics and epidemic characteristics of H3N2 influenza patients were analyzed by descriptive epidemiological methods and chi-square test. Results A total of 11 567 influenza case samples were tested in the study, with a positive rate of 9.34% (1 080/11 567). Influenza A (H3N2) remained the predominant circulating subtype throughout the study period. January 2023 to February 2023 marked the tailing end of the previous season’s H3N2. Then, a minor peak dominated by H1N1 occurred from March to June, and H3N2 circulated again from October to December, peaking in December. From September 2024 to December 2024, H1N1 and H3N2 circulated concurrently, with H3N2 as the dominant strain, peaking in January of the following year. From March 2025 to September 2025, influenza activity remained at low level, and activity began to rise in October, with H1N1 peaking in November before declining, and H3N2 becoming the dominant strain in December. H3N2 mainly occurred in the 5-14 years old group. Cases in the 0–4-year-old group were primarily characterized by gastrointestinal symptoms, with high fever being common. Cases in the 5–59-year-old group were primarily characterized by systemic and respiratory symptoms, with better clinical outcomes. Cases aged 60 and older exhibited the highest rates of hospitalization, severe illness, and incidence of complications. Conclusion From 2023 to 2025, the influenza virus in Tangshan City, Hebei Province is dominated by influenza A (H3N2). The epidemic is characterized by a peak incidence during autumn and winter, co-circulation with H1N1, and fluctuations during the peak period. It is necessary to pay attention to the clinical management and prevention and control of influenza A (H3N2) in infants and the elderly.

Objective: To investigate the status and influencing factors of latent tuberculosis infection (LTBI) among enterprise employees in Wenzhou City, Zhejiang Province, so as to provide evidence for optimizing tuberculosis prevention and control strategies in enterprises. Methods: From August 2024 to September 2025, a convenience sampling method was used to select employees from 26 enterprises in Wenzhou City as the study participants. Demographic information, enterprise scale, and industry type were collected by reviewing enterprise employee management files. Interferon-gamma release assays were used to detect Mycobacterium tuberculosis infection and screen for LTBI. Factors affecting LTBI among enterprise employees were identified using a multivariable logistic regression model. Results: A total of 6 476 participants were surveyed, including 3 674 males (56.73%) and 2 802 females (43.27%). The median age was 37.00 (interquartile range, 20.00) years. A total of 994 cases of LTBI were detected, with a detection rate of 15.35%. Multivariable logistic regression analysis showed that male (OR=1.397, 95%CI: 1.211-1.612), age ≥45 years (45-<60 years, OR=1.919, 95%CI: 1.649-2.234; ≥60 years, OR=4.425, 95%CI: 3.170-6.177), household registration outside Zhejiang Province (OR=1.928, 95%CI: 1.577-2.357), employment in small or medium-sized enterprises (medium-sized, OR=1.663, 95%CI: 1.392-1.988; small-sized, OR=1.665, 95%CI: 1.358-2.040), and working in the manufacturing industry (OR=1.799, 95%CI: 1.147-2.822) were associated with a higher risk of LTBI among enterprise employees. Conclusions The detection rate of LTBI among enterprise employees in Wenzhou City was relatively low. Male employees, those aged ≥45 years, those with household registration outside Zhejiang Province, those working in small or medium-sized enterprises, and those in the manufacturing industry were identified as high-risk populations for LTBI.

Hematologic malignancies,such as lymphoma,myeloma,and myeloid neoplasms,can occur in extramedullary tissues.Traditional histopathological morphology and immunohistochemical staining have lim-itations,including time-consuming specimen processing,prolonged reporting cycles,and relatively low sensi-tivity in cases of limited cell numbers.Flow cytometry offers significant advantages in detecting tissue sam-ples,such as rapid processing,shorter reporting cycles,and high accuracy and sensitivity,making it an effective complement to histopathological and immunohistochemical methods.However,the application of flow cytome-try in tissue sample detection currently lacks standardized protocols for sample collection and preservation,single-cell suspension preparation,antibody panel design for limited samples,data analysis,and result repor-ting.To promote the standardized application of flow cytometry in detecting hematologic tumor cells in tissue samples,the Cell Analysis Professional Committee of the Chinese Society of Biotechnology organized experts to develop the Chinese Expert Consensus on Flow Cytometry for Detecting Hematologic Tumor Cells in Tis-sue Samples(hereinafter referred to as the Consensus).This Consensus elaborates on the technical aspects of flow cytometry for tissue sample detection,covering sample processing,antibody panel design,data analysis,reporting content,and quality management.It particularly emphasizes recommended antibody panels and data analysis methods for flow cytometry when tissue sample cell counts are low.This article aims to interpret the key points of the Consensus to facilitate its better application in clinical practice.

Objective: The CT/MRI Liver Imaging Reporting and Data System (LI-RADS) demonstrates high specificity with relatively limited sensitivity for diagnosing hepatocellular carcinoma (HCC) in high-risk patients. This study aimed to explore the possibility of improving sensitivity by combining CT/MRI LI-RADS v2018 with second-line contrast-enhanced ultrasound (CEUS) LI-RADS v2017 using sulfur hexafluoride (SHF) or perfluorobutane (PFB). Materials and Methods: This retrospective analysis of prospectively collected multicenter data included high-risk patients with treatment-naive hepatic observations. The reference standard was pathological confirmation or a composite reference standard (only for benign lesions). Each participant underwent concurrent CT/MRI, SHF-enhanced US, and PFB-enhanced US examinations. The diagnostic performances for HCC of CT/MRI LI-RADS alone and three combination strategies (combining CT/ MRI LI-RADS with either LI-RADS SHF, LI-RADS PFB, or a modified algorithm incorporating the Kupffer-phase findings for PFB [modified PFB]) were evaluated. For the three combination strategies, apart from the CT/MRI LR-5 criteria, HCC was diagnosed if CT/MRI LR-3 or LR-4 observations met the LR-5 criteria using LI-RADS SHF, LI-RADS PFB, or modified PFB. Results: In total, 281 participants (237 males; mean age, 55 ± 11 years) with 306 observations (227 HCCs, 40 non-HCC malignancies, and 39 benign lesions) were included. Using LI-RADS SHF, LI-RADS PFB, and modified PFB, 20, 23, and 31 CT/MRI LR-3/4 observations, respectively, were reclassified as LR-5, and all were pathologically confirmed as HCCs. Compared to CT/MRI LI-RADS alone (74%, 95% confidence interval [CI]: 68%–79%), the three combination strategies combining CT/MRI LI-RADS with either LI-RADS SHF, LI-RADS PFB, or modified PFB increased sensitivity (83% [95% CI: 77%–87%], 84% [95% CI: 79%–89%], 88% [95% CI: 83%–92%], respectively; all P < 0.001), while maintaining the specificity at 92% (95% CI: 84%–97%). Conclusion The combination of CT/MRI LI-RADS with second-line CEUS using SHF or PFB improved the sensitivity of HCC diagnosis without compromising specificity.

Objective:To investigate the clinical characteristics and survival outcomes of patients with nasopharyngeal carcinoma (NPC) complicated by multiple primary malignancies (MPCs) in a real-world setting.Methods:A retrospective study was performed on 238 NPC patients with MPCs who received radical radiotherapy at Fujian Cancer Hospital between January 1st, 2004 and December 31st, 2023. The primary endpoints were overall survival (OS) and cumulative survival rate. Survival analysis was conducted using the Kaplan-Meier method with log-rank / Breslow tests, and univariate analysis of prognostic factors was performed using the Cox proportional hazards model.Results:A total of 246 primary malignant tumors were identified in 238 patients, involving 12 organ systems and 39 tumor types. The most common coexisting malignancies occurred in the respiratory and intrathoracic organs [25.2% (62/246)], followed by digestive organ malignancies [22.8% (56/246)], malignancies of the lip, oral cavity, and pharynx [22.8% (56/246)], and thyroid and other endocrine gland malignancies [15.4% (38/246)]. The median OS was 186 months, and the 3-, 5-, and 10-year cumulative survival rates were 90.84%, 85.25%, and 69.45%, respectively. Poorer survival was associated with male sex, age>48 years at onset, locally advanced disease (stage IVA), synchronous MPCs and/or digestive system malignancies, fewer total cycles of chemotherapy, and lack of concurrent or adjuvant chemotherapy.Conclusions:In patients with NPC, MPCs most frequently involve the respiratory system, digestive system, and head and neck organs (including the thyroid). Male sex, older age, locally advanced primary NPC, synchronous and/or digestive system MPCs, fewer chemotherapy cycles, and lach of concurrent or adjuvant chemotherapy were significantly associated with poorer prognosis.

Objective By analyzing the gene expression data in TCGA-THCA dataset,the differentially expressed genes related to thyroid carcinoma(THCA)were identified,a risk model was construct,and the role of CCL chemokine family in the development of THCA and its effect on the tumor immune microenvironment were investigated.Methods TCGA-THCA dataset was downloaded and analyzed,including 512 cancer samples and 59 adjacent tissue samples.The differentially expressed genes were obtained by taking the intersection of R packages of differential analysis,and the principal component analysis(PCA),Gene Ontology(GO),and Kyoto Encyclopedia of Genes and Genomes(KEGG)enrichment analysis were performed.CellMarker,monocle,and CellChat were used to explore the Cell atlas,pseudotemporal trajectory,and cellular communication.Results A total of 698 up-regulated genes and 285 down-regulated genes were identified.PCA showed that there were significant differences in gene expression patterns between the THCA group and the normal group.GO and KEGG enrichment analysis revealed that differentially expressed genes were mainly involved in biological processes such as extracellular matrix tissue,cell junction assembly,and complement system.The results of risk model showed that the CCL genes was significantly correlated with poor prognosis(P=0.005).Single cell analysis revealed that fibroblasts played a key role in the development of THCA,and the expression of CCL gene was significantly up-regulated in fibroblasts(P<0.05).The results of pseudotemporal trajectory analysis showed that CCL gene was differentially expressed during cellular differentiation;the results of cellular communication analysis showed that the interaction between fibroblasts and endothelial cells is crucial in the tumor microenvironment.Conclusion The expression of CCL chemokine family in THCA is closely related to poor prognosis,especially CCL4,which activates the downstream signaling pathways by interacts with CCR receptors of cancer-associated fibroblasts,thereby promoting the development of cancer.These findings provide novel insights for understanding the role of CCL chemokine family in THCA and its regulation of the tumor immune microenvironment.