Oral squamous cell carcinoma (OSCC) is a common head and neck malignancy. Approximately 50% to 60% of patients with OSCC are diagnosed at a locally advanced stage (clinical staging III-IVa). Even with comprehensive and sequential treatment primarily based on surgery, the 5-year overall survival rate remains below 50%, and patients often suffer from postoperative functional impairments such as difficulties with speaking and swallowing. Programmed death receptor-1 (PD-1) inhibitors are increasingly used in the neoadjuvant treatment of locally advanced OSCC and have shown encouraging efficacy. However, clinical practice still faces key challenges, including the definition of indications, optimization of combination regimens, and standards for efficacy evaluation. Based on the latest research advances worldwide and the clinical experience of the expert group, this expert consensus systematically evaluates the application of PD-1 inhibitors in the neoadjuvant treatment of locally advanced OSCC, covering combination strategies, treatment cycles and surgical timing, efficacy assessment, use of biomarkers, management of special populations and immune related adverse events, principles for immunotherapy rechallenge, and function preservation strategies. After multiple rounds of panel discussion and through anonymous voting using the Delphi method, the following consensus statements have been formulated: 1) Neoadjuvant therapy with PD-1 inhibitors can be used preoperatively in patients with locally advanced OSCC. The preferred regimen is a PD-1 inhibitor combined with platinum based chemotherapy, administered for 2-3 cycles. 2) During the efficacy evaluation of neoadjuvant therapy, radiographic assessment should follow the dual criteria of Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1 and immune RECIST (iRECIST). After surgery, systematic pathological evaluation of both the primary lesion and regional lymph nodes is required. For combination chemotherapy regimens, PD-L1 expression and combined positive score need not be used as mandatory inclusion or exclusion criteria. 3) For special populations such as the elderly (≥ 70 years), individuals with stable HIV viral load, and carriers of chronic HBV/HCV, PD-1 inhibitors may be used cautiously under the guidance of a multidisciplinary team (MDT), with close monitoring for adverse events. 4) For patients with a poor response to neoadjuvant therapy, continuation of the original treatment regimen is not recommended; the subsequent treatment plan should be adjusted promptly after MDT assessment. Organ transplant recipients and patients with active autoimmune diseases are not recommended to receive neoadjuvant PD-1 inhibitor therapy due to the high risk of immune related activation. Rechallenge is generally not advised for patients who have experienced high risk immune related adverse events such as immune mediated myocarditis, neurotoxicity, or pneumonitis. 5) For patients with a good pathological response, individualized de escalation surgery and function preservation strategies can be explored. This consensus aims to promote the standardized, safe, and precise application of neoadjuvant PD-1 inhibitor strategies in the management of locally advanced OSCC patients.

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.

Patients with periodontal disease often require combined periodontal-orthodontic interventions to restore periodontal health, function, and aesthetics, ensuring both patient satisfaction and long-term stability. Managing these patients involving orthodontic tooth movement can be particularly challenging due to compromised periodontal soft and hard tissues, especially in severe cases. Therefore, close collaboration between orthodontists and periodontists for comprehensive diagnosis and sequential treatment, along with diligent patient compliance throughout the entire process, is crucial for achieving favorable treatment outcomes. Moreover, long-term orthodontic retention and periodontal follow-up are essential to sustain treatment success. This expert consensus, informed by the latest clinical research and practical experience, addresses clinical considerations for orthodontic treatment of periodontal patients, delineating indications, objectives, procedures, and principles with the aim of providing clear and practical guidance for clinical practitioners.
Humans ; Consensus ; Orthodontics, Corrective/standards* ; Periodontal Diseases/complications* ; Tooth Movement Techniques/methods* ; Practice Guidelines as Topic

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*

The focus of green analytical chemistry (GAC) is to minimize the negative impacts of analytical procedures on human safety, human health, and the environment. Several factors, such as the reagents used, sample collection, sample processing, instruments, energy consumed, and the quantities of hazardous materials and waste generated during analytical procedures, need to be considered in the evaluation of the greenness of analytical assays. In this study, we propose a greenness evaluation metric for analytical methods (GEMAM). The new greenness metric is simple, flexible, and comprehensive. The evaluation criteria are based on both the 12 principles of GAC (SIGNIFICANCE) and the 10 factors of sample preparation, and the results are presented on a 0-10 scale. The GEMAM calculation process is easy to perform, and its results are easy to interpret. The output of GEMAM is a pictogram that can provide both qualitative and quantitative information based on color and number.

ObjectiveRecent studies have highlighted the critical role of NUDT19 in the initiation, progression, and prognosis of specific cancer types. However, its involvement in pan-cancer analysis has not been fully characterized. This study aims to systematically explore the expression patterns, clinical significance, and immune-related functions of NUDT19 in various cancer types through multi-omics analysis, further revealing its potential role in cancer, particularly its functional and therapeutic target value in leukemia. MethodsTo achieve this goal, various bioinformatics approaches were employed to evaluate the expression patterns, clinical significance, and immune-related functions of NUDT19 in tumors and normal tissues. Additionally, we analyzed the mutation characteristics of NUDT19 and its relationship with epigenetic modifications. Using the single-cell analysis tool SingleCellBase, we explored the distribution of NUDT19 across different cell subpopulations in tumors. To validate these findings, qRT-PCR was used to measure NUDT19 expression levels in specific tumor cell lines, and we established acute myeloid leukemia (AML) cell lines (HL-60 and THP-1) to conduct NUDT19 knockdown and overexpression experiments, assessing its effects on leukemia cell proliferation, apoptosis, and invasion. ResultsPan-cancer analysis revealed the dysregulated expression of NUDT19 across multiple cancer types, which was closely associated with poor prognosis, clinical staging, and diagnostic markers. Furthermore, NUDT19 was significantly correlated with tumor biomarkers, immune-related genes, and immune cell infiltration in different cancers. Mutation analysis showed that multiple mutations in NUDT19 were significantly associated with epigenetic changes. Single-cell analysis revealed the heterogeneity of NUDT19 expression in cancer cells, suggesting its potentially diverse functional roles in different cell subpopulations. qRT-PCR experiments confirmed the significant upregulation of NUDT19 in various tumor cell lines. In AML cell lines, NUDT19 knockdown led to reduced cell proliferation and invasion, with increased apoptosis, while NUDT19 overexpression significantly enhanced cell proliferation and invasion while reducing apoptosis. ConclusionThis study demonstrates the diverse roles of NUDT19 in various cancer types, with a particularly prominent functional role in leukemia. NUDT19 is not only associated with tumor initiation and progression but may also influence cancer progression through the regulation of immune microenvironment and epigenetic mechanisms. Our research highlights the potential of NUDT19 as a therapeutic target, particularly for targeted therapies in malignancies such as leukemia, with significant clinical application prospects.

The focus of green analytical chemistry(GAC)is to minimize the negative impacts of analytical pro-cedures on human safety,human health,and the environment.Several factors,such as the reagents used,sample collection,sample processing,instruments,energy consumed,and the quantities of hazardous materials and waste generated during analytical procedures,need to be considered in the evaluation of the greenness of analytical assays.In this study,we propose a greenness evaluation metric for analytical methods(GEMAM).The new greenness metric is simple,flexible,and comprehensive.The evaluation criteria are based on both the 12 principles of GAC(SIGNIFICANCE)and the 10 factors of sample prep-aration,and the results are presented on a 0-10 scale.The GEMAM calculation process is easy to perform,and its results are easy to interpret.The output of GEMAM is a pictogram that can provide both qualitative and quantitative information based on color and number.

Intestinal microecological changes are closely related to liver cirrhosis and cirrhosis-related sarcopenia.Studies has demonstrated that interventions targeting the intestinal microbiota could contribute to the treatment of cirrhosis and cirrhosis-related sarcopenia.Here we reviewed the research progress on the alterations in intestinal microbiota during liver cirrhosis and the underlying mechanisms by which these changes impacted the development of the disease.The potential of microbiota-targeted interventions in both preventing and treating liver cirrhosis and related sarcopenia was also discussed,which might provide valuable insights into clinical diagnosis and management of the disease.