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.

The recombinant human thyroid-stimulating hormone (rhTSH) can be used for differentiated thyroid cancer (DTC) preparation before ¹³¹I therapy, and follow-up. Since its approval by the American Food and Drug Administration (FDA) in 1998, rhTSH has been clinically used in European countries, the United States, and other countries for nearly 30 years. In April 2024, China’s first independently developed rhTSH agent was approved. Based on clinical experience and evidence from domestic and international studies, an expert consensus on the application of rhTSH has been developed following thorough consultations among experts. The consensus offers evidence-based recommendations to guide the appropriate use of rhTSH in clinical practice.

Objective:To investigate the factors affecting the efficacy of 131I treatment for Graves′ disease (GD) and to construct a predictive model for the treatment outcomes of 131I therapy. Methods:Retrospective analysis of the treatment efficacy was performed on 2 190 patients (547 males, 1 643 females, age (42.9±12.4) years) with GD, who received initial 131I treatment in Tianjin Medical University General Hospital between October 2013 and May 2018. Univariate analysis ( χ2 test, et al) and logistic regression were performed to analyze the possible factors affecting the efficacy of 131I treatment. An efficacy prediction model for 131I treatment of GD was constructed, and decision curve analysis (DCA) was used to evaluate the clinical utility of the prediction model. Results:The overall effectiveness rate of 131I treatment for GD patients was 99.95%(2 189/2 190), with a total cure rate of 83.74%(1 834/2 190), among which 94.11%(1 726/1 834) were cured after a single treatment. Pre-treatment thyroid mass was identified as an independent risk factor affecting the efficacy of initial 131I treatment (odds ratio ( OR)=0.983(95% CI: 0.977-0.989), P<0.001). The clinical cure rate was higher in patients who received an adequate dose of 131I compared with that in patients who didn′t receive an adequate dose (79.97%(1 537/1 922) vs 70.52%(189/268); χ2=12.57, P<0.001), but it did not increase the incidence of hypothyroidism within one year. A predictive model was constructed, and it was found that thyroid mass and disease duration had a relatively high impact on the clinical cure rate. The concordance index (C-index) of the predictive model was 0.623(95% CI: 0.593-0.654). DCA indicated that the predictive model offered substantial net benefits across a wide range of probability thresholds. Conclusions:131I treatment is effective in most patients with GD. The predictive model for efficacy of initial 131I treatment developed in this study can assist in evaluating treatment outcomes and help clinicians select the most suitable 131I treatment dose, enhancing clinical decision-making.

Objective:To investigate the inpact of thyroid cancer-derived cancer-associated fibroblasts(CAF) autophagy on papillary thyroid cancer(PTC).Methods:CAF and normal fibroblasts were isolated from cancerous and adjacent normal thyroid tissues from four PTC patients. Expressions of fibroblast activation protein(FAP) and α-smooth muscle actin in cells were assessed. Conditioned medium of CAF and normal fibroblasts were prepared and used to culture PTC cells. The effects of CAF and normal fibroblasts on survival, proliferation, migration, invasion and iodine uptake of PTC cells were evaluated through cell proliferation assay, cell scratch assay, cell invasion assay, and cell iodine uptake assay. The autophagy level of CAF was also evaluated. Autophagy inhibition and activation were used to regulate the autophagy of CAF, and then their effects on PTC cell proliferation, migration and invasion were further evaluated. The in vivo effect of CAF autophagy on PTC xenograft tumor growth was evaluated.Results:CAF exhibited higher FAP expression and basal autophagy levels. PTC cells co-cultured with CAF-conditioned media showed enhanced proliferation, migration, invasion, and reduced iodine uptake. Autophagy inhibition reduced these effects, while autophagy activation further promoted them. In vivo, inhibiting CAF autophagy suppressed tumor growth.Conclusions:CAF promotes PTC cell malignancy through autophagy activation, enhancing proliferation, migration, and invasion while reducing iodine uptake.

Surgical treatment is one of the key approaches for non-small cell lung cancer (NSCLC). Regular postoperative follow-up is crucial for early detection and timely management of tumor recurrence, metastasis, or second primary tumors. A scientifically sound and reasonable follow-up strategy not only extends patient survival but also significantly improves quality of life, thereby enhancing overall prognosis. This consensus aims to build upon the previous version by incorporating the latest clinical research advancements and refining postoperative follow-up protocols for early-stage NSCLC patients based on different treatment modalities. It provides a scientific and practical reference for clinicians involved in the postoperative follow-up management of NSCLC. By optimizing follow-up strategies, this consensus seeks to promote the standardization and normalization of lung cancer diagnosis and treatment in China, helping more patients receive high-quality care and long-term management. Additionally, the release of this consensus is expected to provide insights for related research and clinical practice both domestically and internationally, driving continuous development and innovation in the field of postoperative management for NSCLC.

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 investigate the factors affecting the efficacy of 131I treatment for Graves′ disease (GD) and to construct a predictive model for the treatment outcomes of 131I therapy. Methods:Retrospective analysis of the treatment efficacy was performed on 2 190 patients (547 males, 1 643 females, age (42.9±12.4) years) with GD, who received initial 131I treatment in Tianjin Medical University General Hospital between October 2013 and May 2018. Univariate analysis ( χ2 test, et al) and logistic regression were performed to analyze the possible factors affecting the efficacy of 131I treatment. An efficacy prediction model for 131I treatment of GD was constructed, and decision curve analysis (DCA) was used to evaluate the clinical utility of the prediction model. Results:The overall effectiveness rate of 131I treatment for GD patients was 99.95%(2 189/2 190), with a total cure rate of 83.74%(1 834/2 190), among which 94.11%(1 726/1 834) were cured after a single treatment. Pre-treatment thyroid mass was identified as an independent risk factor affecting the efficacy of initial 131I treatment (odds ratio ( OR)=0.983(95% CI: 0.977-0.989), P<0.001). The clinical cure rate was higher in patients who received an adequate dose of 131I compared with that in patients who didn′t receive an adequate dose (79.97%(1 537/1 922) vs 70.52%(189/268); χ2=12.57, P<0.001), but it did not increase the incidence of hypothyroidism within one year. A predictive model was constructed, and it was found that thyroid mass and disease duration had a relatively high impact on the clinical cure rate. The concordance index (C-index) of the predictive model was 0.623(95% CI: 0.593-0.654). DCA indicated that the predictive model offered substantial net benefits across a wide range of probability thresholds. Conclusions:131I treatment is effective in most patients with GD. The predictive model for efficacy of initial 131I treatment developed in this study can assist in evaluating treatment outcomes and help clinicians select the most suitable 131I treatment dose, enhancing clinical decision-making.

Objective:To investigate the inpact of thyroid cancer-derived cancer-associated fibroblasts(CAF) autophagy on papillary thyroid cancer(PTC).Methods:CAF and normal fibroblasts were isolated from cancerous and adjacent normal thyroid tissues from four PTC patients. Expressions of fibroblast activation protein(FAP) and α-smooth muscle actin in cells were assessed. Conditioned medium of CAF and normal fibroblasts were prepared and used to culture PTC cells. The effects of CAF and normal fibroblasts on survival, proliferation, migration, invasion and iodine uptake of PTC cells were evaluated through cell proliferation assay, cell scratch assay, cell invasion assay, and cell iodine uptake assay. The autophagy level of CAF was also evaluated. Autophagy inhibition and activation were used to regulate the autophagy of CAF, and then their effects on PTC cell proliferation, migration and invasion were further evaluated. The in vivo effect of CAF autophagy on PTC xenograft tumor growth was evaluated.Results:CAF exhibited higher FAP expression and basal autophagy levels. PTC cells co-cultured with CAF-conditioned media showed enhanced proliferation, migration, invasion, and reduced iodine uptake. Autophagy inhibition reduced these effects, while autophagy activation further promoted them. In vivo, inhibiting CAF autophagy suppressed tumor growth.Conclusions:CAF promotes PTC cell malignancy through autophagy activation, enhancing proliferation, migration, and invasion while reducing iodine uptake.

OBJECTIVE: To examine the effectiveness of Chinese medicine (CM) Lianhua Qingwen Granule (LHQW) and Jingyin Gubiao Prescription (JYGB) in asymptomatic or mild patients with Omicron infection in the shelter hospital. METHODS: This single-center retrospective cohort study was conducted in the largest shelter hospital in Shanghai, China, from April 10, 2022 to May 30, 2022. A total of 56,244 asymptomatic and mild Omicron cases were included and divided into 4 groups, i.e., non-administration group (23,702 cases), LHQW group (11,576 cases), JYGB group (12,112 cases), and dual combination of LHQW and JYGB group (8,854 cases). The length of stay (LOS) in the hospital was used to assess the effectiveness of LHQW and JYGB treatment on Omicron infection. RESULTS: Patients aged 41-60 years, with nadir threshold cycle (C_T) value of N gene <25, or those fully vaccinated preferred to receive CM therapy. Before or after propensity score matching (PSM), the multiple linear regression showed that LHQW and JYGB treatment were independent influence factors of LOS (both P<0.001). After PSM, there were significant differences in LOS between the LHQW/JYGB combination and the other groups (P<0.01). The results of factorial design ANOVA proved that the LHQW/JYGB combination therapy synergistically shortened LOS (P=0.032). CONCLUSIONS Patients with a nadir C_T value <25 were more likely to accept CM. The LHQW/JYGB combination therapy could shorten the LOS of Omicron-infected individuals in an isolated environment.
Humans ; Drugs, Chinese Herbal/therapeutic use* ; Male ; Female ; Middle Aged ; Adult ; China/epidemiology* ; Hospitalization ; COVID-19 Drug Treatment ; COVID-19/epidemiology* ; SARS-CoV-2 ; Retrospective Studies ; Treatment Outcome ; Length of Stay ; Young Adult ; Aged

Hyperkalemia is one of the common ion metabolism disorders in clinical practice. Hyperkalemia is defined as serum potassium higher than 5.0 mmol/L according to the guidelines at home and abroad. Acute severe hyperkalemia can cause serious consequences, such as flaccid paralysis, fatal arrhythmia, and even cardiac arrest. The use of renin-angiotensin- aldosterone system inhibitors, β-blockers and diuretics, low-sodium and high-potassium diets, and the presence of related comorbidities increase the occurrence of hyperkalemia. Hyperkalemia risk exist in all clinical departments, but there is a lack of a standardization in the management of multi- department cooperation in hospital. Therefore, a number of domestic nephrology and cardiology department experts have discussed a management model for multi-department cooperation in hyperkalemia, formulating the management standard on hospital evaluation, early warning, diagnosis and treatment, and process. This can promote each department to more effectively participate in nosocomial hyperkalemia diagnosis and treatment, as well as the long-term management of chronic hyperkalemia, improving the quality of hyperkalemia management in hospital.