Objective To study the correlation between Periostin, interleukin-33 (IL-33), and chronic cough after thoracoscopic lobectomy in patients with coronary artery bypass grafting (CABG) combined with lung cancer. Methods A total of 102 lung cancer and coronary heart disease patients at Tianjin Chest Hospital from January 2022 to January 2024 were prospectively enrolled, and they were divided into a chronic cough group (n=42) and a non-chronic cough group (n=60) based on whether chronic cough occurred after surgery. Serum levels of Periostin and IL-33 were measured on the 1st, 7th, and 14th days post-lobectomy. The Pearson method was employed to analyze the correlation between Periostin and IL-33 levels and the severity of cough. Univariate and multivariate logistic regression analyses were conducted to identify factors influencing the occurrence of chronic cough. Additionally, receiver operating characteristic (ROC) curve analysis was utilized to assess the potential value of serum Periostin and IL-33 levels in predicting postoperative chronic cough. Results In patients with chronic cough, the peripheral blood Periostin and IL-33 levels measured on days 7 and 14 were significantly higher than those in patients with non-chronic cough, and the interactions between the two groups and at different time points were significant (P<0.001). The degree of cough was positively correlated with the levels of Periostin and IL-33 on days 7 and 14 (P<0.05), but had no significant correlation with the levels on day 1 (P>0.05). In patients with lung cancer, after thoracoscopic lobectomy, Periostin [OR=1.619, 95%CI (1.295, 2.025)] and IL-33 [OR=1.831, 95%CI (1.216, 2.758)] on day 7 and Periostin [OR=1.952, 95%CI (1.306, 2.918)] and IL-33 [OR=1.742, 95%CI (1.166, 2.603)] on day 14 were identified as risk factors for chronic cough. ROC curve analysis showed that the sensitivity of Periostin on day 7 was 69.05%, the specificity was 71.67%, and the area under the curve (AUC) was 0.756 [95%CI (0.616, 0.893)]. The sensitivity of Periostin on day 14 increased to 71.43% and the specificity was 76.67%, AUC was 0.762 [95%CI (0.633, 0.898)]. At the same time, the critical value of IL-33 on day 7 was 45.03 pg/mL, the sensitivity and specificity were both 83.33%, the AUC was 0.884 [95%CI (0.789, 0.980)], and the critical value of IL-33 on day 14 was 56.01 pg/mL, the sensitivity was 85.71%, the specificity was 80.00%, and the AUC was 0.899 [95%CI (0.799, 0.999)]. Joint logistic regression analysis of Periostin and IL-33 levels on days 7 and 14 showed showed that the sensitivity was 95.24%, the specificity was 95.00%, and the AUC reached 0.993 [95%CI (0.979, 1.000)]. Conclusion Periostin and IL-33 levels, measured at various time points, are abnormally elevated following thoracoscopic lobectomy in patients with combined CABG and lung cancer. These levels significantly correlate with cough severity. Given their predictive potential for chronic cough, these markers are deemed valuable biomarkers.

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.

Brain MRI data is characterized by large volumes and susceptibility to noise and artifacts,which pose significant challenges of improving the speed and accuracy of brain tumor detection and analysis due to the tumors'diverse types,shapes,and boundaries that are both similar and highly variable.Therefore,a series of improvements based on YOLOv7 algorithm are proposed for enhancing detection precision and speed:(1)employing partial convolution during feature extraction to reduce the model's parameters and improve overall detection speed;(2)in light of the complex variability of brain tumors,introducing a three-dimensional spatial attention mechanism during feature extraction to enhance the model's focus on critical image features;(3)replacing the original IoU loss function with WIoU to increase the attention to medium-quality anchor boxes during bounding box regression for further improving detection accuracy.Experiments conducted on two public brain tumor datasets,Brain_Tumor and Glioma_of_test,show that the improved model achieves mAP of 96.9%and 92.8%,which are 1.4%and 2.4%higher than the original YOLOv7 model,and the frames per second reach 162.7 and 158.1,showing improvements of 6.4 and 18.2,respectively.These enhancements enable more effective detection of brain tumors in MRI images.

Iron is an essential trace element in the human body, crucial in maintaining normal physiological functions. Recent studies have identified iron ions as a significant factor in initiating the ferroptosis process, a novel mode of programmed cell death characterized by iron overload and lipid peroxide accumulation. The iron metabolism pathway is one of the primary mechanisms regulating ferroptosis, as it maintains iron homeostasis within the cell. Numerous studies have demonstrated that abnormalities in iron metabolism can trigger the Fenton reaction, exacerbating oxidative stress, and leading to cell membrane rupture, cellular dysfunction, and damage to tissue structures. Therefore, regulation of iron metabolism represents a key strategy for ameliorating ferroptosis and offers new insights for treating diseases associated with iron metabolism imbalances. This review first summarizes the mechanisms that regulate iron metabolic pathways in ferroptosis and discusses the connections between the pathogenesis of various diseases and iron metabolism. Next, we introduce natural and synthetic small molecule compounds, hormones, proteins, and new nanomaterials that can affect iron metabolism. Finally, we provide an overview of the challenges faced by iron regulators in clinical translation and a summary and outlook on iron metabolism in ferroptosis, aiming to pave the way for future exploration and optimization of iron metabolism regulation strategies.

Objective:This multicenter retrospective study aimed to analyze the clinicopathological features of duodenal adenocarcinoma (DA) and identify prognostic factors for postoperative survival.Methods:Demographic characteristics, clinicopathological features, treatment outcomes and survival of DA patients undergoing surgical treatment at 18 Chinese medical centers from January 2012 to December 2023 were retrospectively analyzed.Results:Among the 2 056 DA patients included, 46.8% (963) had extra-ampullary DA (EA-DA), and 53.2% (1 093) had peri-ampullary DA (PA-DA). The 1-, 3-, and 5-year overall survival (OS) rates for patients who underwent radical surgery were 93.2%, 71.0%, and 57.2%, respectively. The median overall survival was 76 months, and the median progression-free survival (PFS) was 65 months. No differences in survival were observed between the laparotomy group and minimally invasive surgery (MIS) group either before or after propensity score matching (OS: 76 vs. 75 months before PSM, P=0.986; OS: 75 vs. 75 months after PSM, P=0.602). Furthermore, there were no significant differences between-group in operation time and postoperative complications ( P＞0.05). The MIS group experienced less intraoperative blood loss and shorter hospital stays. The multivariate Cox regression analysis revealed that advanced age ( HR=1.43,95% CI:1.18-1.73), elevated carbohydrate antigen 19-9 levels ( HR=1.24,95% CI:1.02-1.51), perineural invasion ( HR=1.44,95% CI:1.14-1.81), vascular invasion ( HR=1.35,95% CI:1.07-1.71), advanced T stage (T3-4 vs. T1-2: HR=1.86,95% CI:1.49-2.31), regional lymph node metastasis ( HR=1.93,95% CI:1.58-2.36), preoperative biliary drainage ( HR=1.26,95% CI:1.04-1.53), intraoperative blood loss ( HR=1.34,95% CI:1.11-1.62), clinically significant postoperative pancreatic fistulas ( HR=1.53,95% CI:1.12-2.09), and postoperative hemorrhage ( HR=1.62,95% CI:1.14-2.29) were independent risk factors for poor prognosis after surgery (all P＜0.05). Conclusions:Radical surgery is associated with favorable overall survival among DA patients, and no difference in survival is observed between EA-DA and PA-DA patients. MIS is a reliable alternative for DA treatment.

Given the escalating number of cancer patients and the consequent rise in demand for radiation therapy in China, there is an urgent need to establish and improve a talent cultivation system for radiation dosimetrists. The United States, with an early-established cultivation system for radiation dosimetrists, boasts relatively mature and comprehensive systems of academic education and qualification certification. This study summarized and analyzed the educational and certification patterns for radiation dosimetrists in the United States based on public data from relevant institutions, related literature, and interviews with American radiation dosimetrists. Meanwhile, this study delved into and assessed the shortcomings in China′s radiation dosimetry education, examination, certification, and career advancement pathways. Furthermore, this study offered suggestions and recommendations for constructing a novel pattern tailored to the cultivation of radiation dosimetrists in China, in order to facilitate the high-quality development of the medical dosimetry discipline.

Medical physicists play an important role in radiodiagnosis, radiotherapy, and nuclear medicine practices. The International Atomic Energy Agency (IAEA) suggests that medical physicists should be trained and achieve professional certifications. Many developed countries/regions have established comprehensive examination and certification programs for medical physicists. However, these systems are yet to be improved in China. This leads to a lack of control over the professional competence and practice standards in the workforce, posing a negative impact on the quality and safety of China’s clinical services in radiation medicine. The International Medical Physics Certification Board (IMPCB) is aimed at accrediting national/regional medical physics certification programs and providing certification of individual medical physicists in countries/regions lacking such certification programs. This study introduces the procedures and specific method for China’s medical physicists to achieve professional certifications via IMPCB, aiming to help improve their professionalism.

Objective To investigate the expression of kinesin family member 23(KIF23)in rectal cancer and its association with prognosis.Methods This study included 90 patients with rectal cancer who underwent surgical treatment at the First Central Hospital of Baoding from May 2017 to October 2019.Immunohistochemical staining was used to detect KIF23 expression,and the results were analyzed in combination with clinical and pathological data.Survival analysis was conducted using Kaplan-Meier methods and Cox proportional hazards models to assess the association between KIF23 expression and patient prognosis.Results Compared with adjacent non-tumor tis-sues,the expression level of KIF23 protein was significantly higher in rectal cancer tissues.Positive expression of KIF23 was significantly correlated with TNM stage,lymph node metastasis and distant metastasis in rectal cancer patients(P＜0.05).Kaplan-Meier analysis revealed that individuals expressing high levels of KIF23 experienced notably diminished disease-free survival(DFS)and overall survival(OS)relative to those with low KIF23 expression(P＜0.05).Cox regression analysis revealed that advanced TNM stage,lymph node metastasis,distant metastasis,and elevated KIF23 expression served as an independent predictor of adverse outcomes in pa-tients with rectal cancer(P＜0.05).Conclusions The expression level of KIF23 is closely related to the prognosis of rectal cancer.