The incidence and mortality rates of lung cancer have been continuously rising. Smoking is a crucial modifiable factor contributing to the high incidence of lung cancer, and quitting smoking is of great significance for the treatment and prognosis of lung cancer patients. This article systematically reviews the harms of smoking to lung cancer patients, such as carcinogenic substances triggering lung cancer, affecting the course of the disease, and the improvement of prognosis after quitting smoking. It also analyzes the current situation of smoking cessation among lung cancer patients, who face numerous difficulties and have a relatively small number of successful quitters. Meanwhile, this article provides a detailed introduction to the clinical diagnosis and treatment methods for smoking cessation interventions. This includes the explanation of the pathophysiology of smoking cessation, psychological supportive therapies [brief psychological intervention and 5A’s model (Ask, Advise, Assess, Assist, Arrange) psychological counseling], and pharmacotherapies (nicotine-based and non-nicotine-based smoking cessation medications). In addition, it covers the behavioral intervention therapies for smoking cessation, including the PRECEDE-PROCEED model, cognitive behavior theory model, capacity opportunity motivation-behavior (COM-B) theoretical model, information-motivation-behavioral skills (IMB) model, timing is right (TIR) theoretical model, and the economic incentive intervention model. Although some of the current intervention methods lack the support of clinical randomized controlled studies, existing research and practice have confirmed their positive effects on smoking cessation among lung cancer patients. It is hoped that relevant intervention methods can be further improved in the future to help lung cancer patients improve their quality of life.

Objective:To investigate the prediction of the tumor proliferation antigen(Ki-67) expression status in breast cancer patients based on ultrasound radiomics combined with clinicopathologic features.Methods:Breast cancer patients who underwent 2D ultrasound and Ki-67 examination from January 2018 to February 2022 in Changzhou Second People′s Hospital, Nanjing Medical University were retrospectively analyzed. Among them, 427 patients from Chengzhong campus were randomly divided into training and validation sets in the ratio of 8∶2, and 229 patients from Yanghu campus were used as an independent external test set. Radiomics features were extracted from the region of interest of 2D ultrasound images, and the Mann-Whitney U test, recursive feature elimination, and minimum absolute shrinkage and selection operators were used to perform feature dimensionality reduction and to establish a radiomics score(Rad-score). Subsequently, single/multifactor logistic regression regression analyses were used to construct a joint prediction model based on Rad-score and clinicopathological features. Model performance and utility were assessed using the subject operating characteristic area under the curve (AUC), calibration curve, and decision curve analyses. Results:The AUCs of the joint model for predicting Ki-67 expression status in breast cancer in the training, validation, and test sets were 0.858, 0.797, and 0.802, respectively, which were superior to those of the radiomics (0.772, 0.731, and 0.713) and clinical models (0.738, 0.750, and 0.707). Calibration curve and decision curve analyses indicated that the joint model had good calibration and clinical value.Conclusions:A joint model based on ultrasound radiomics and clinicopathological features can effectively predict the Ki-67 expression status of breast cancer, which is expected to become a non-invasive tool for Ki-67 detection and provide clinicians with an important auxiliary diagnostic and therapeutic decision-making basis.

Objective:To evaluate the feasibility of 3D reconstruction techniques based on multi-depth cameras for daily patient positioning in radiotherapy.Methods:Through region of interest (ROI) extraction, filtering, registration, splicing and other processes, multi-depth cameras (Intel RealSense D435i) were used to fuse point clouds in real-time manner to obtain the real optical 3D surface of patients. The reconstructed surface was matched with the external contour of the localization CT to complete the positioning. In this article, the feasibility of the system was validated by using multiple models. Clinical feasibility of 5 patients with head and neck radiotherapy, 10 cases of chest radiotherapy and 5 cases of pelvic radiotherapy was also validated. The data of each group were analyzed by paired t-test. Results:The system running time was 0.475 s, which met the requirement of real-time monitoring. The six-dimensional registration errors in the model experiment were (1.00±0.74) mm, (1.69±0.69) mm, (1.36±0.87) mm, 0.15°±0.14°, 0.25°±0.20°, 0.13°±0.13° in the x, y, z, rotational, pitch and roll directions, respectively. In the actual patient positioning, the mean positioning errors were (0.77±0.51) mm, (1.24±0.67) mm, (0.94±0.76) mm, 0.61°±0.41°, 0.69°±0.55°, and 0.52°±0.35° in the x, y, z, rotational, pitch and roll directions, respectively. The translational error was less than 2.8 mm, and the positioning error was the largest in the pelvic region. Conclusions:Real-time 3D reconstruction techniques based on multi-depth cameras is applicable for patient positioning during radiotherapy. The method is accurate in positioning and can detect the small movement of the patient's position, which meets the requirements of radiotherapy.

Objective To investigate the dietary patterns of rural residents in the high-incidence areas of esophageal cancer (EC), and to explore the clustering and influencing factors of risk factors associated with high-incidence characteristics. Methods A special structured questionnaire was applied to conduct a face-to-face survey on the dietary patterns of rural residents in Yanting county of Sichuan Province from July to August 2021. Univariate and multivariate logistic regression models were used to analyze the influencing factors of risk factor clustering for EC. Results There were 838 valid questionnaires in this study. A total of 90.8% of rural residents used clean water such as tap water. In the past one year, the people who ate fruits and vegetables, soybean products, onions and garlic in high frequency accounted for 69.5%, 32.8% and 74.5%, respectively; the people who ate kimchi, pickled vegetables, sauerkraut, barbecue, hot food and mildew food in low frequency accounted for 59.2%, 79.6%, 68.2%, 90.3%, 80.9% and 90.3%, respectively. The clustering of risk factors for EC was found in 73.3% of residents, and the aggregation of two risk factors was the most common mode (28.2%), among which tumor history and preserved food was the main clustering pattern (4.6%). The logistic regression model revealed that the gender, age, marital status and occupation were independent influencing factors for the risk factors clustering of EC (P<0.05). Conclusion A majority of rural residents in high-incidence areas of EC in Yanting county have good eating habits, but the clustering of some risk factors is still at a high level. Gender, age, marital status, and occupation are influencing factors of the risk factors clustering of EC.

Objective To observe the effect of different concentrations of glutamine(Gln)on the radiosensitivity of colorectal cancer HT-29 cells and explore the possible mechanism.Methods According to different Gln concentrations,HT-29 cells at logarithmical growth were divided into control group(2 mmol/L,as the basal medium concentration group)and experimental groups Ⅰ,Ⅱ and Ⅲ(4,6 and 8 mmol/L).After a 2-hour pre-treatment,all groups were exposed to 8 Gy irradiation of a Co-60 radiation source.CCK-8 assay and clonal formation assay were used respectively to explore the effects of different Gln concentrations on cell viability and cell radiosensitivity after irradiation.The level of reactive oxygen species(ROS)in each group was measured in 24 h after irradiation,and the apoptotic rate was detected with flow cytometry in 48 h after irradiation.The protein expression levels of Nrf2,HO-1,and cleaved-Caspase3 were determined by Western blotting.Results In 24 h after Gln intervention,the cell viability of experimental groups Ⅱ and Ⅲof non-irradiated HT-29 cells was significantly higher than that of the control group and of experimental group Ⅰ(P＜0.05).In 24 h after radiation,the cell viability of each experimental group was significantly higher than that of the control group(P＜0.05).In 14 d after radiation,there were more clone formation in each experimental group than the control group(P＜0.05).The ROS level was significantly lower in each experimental group than the control group in 24 h after radiation(P＜0.05).After 48 h of radiation,the apoptotic rate was notably lower in each experimental group than the control group(P＜0.05).The expression level of Nrf2 in the experimental group Ⅰ was higher than that of the control group(P＜0.05),those of Nrf2 and HO-1 in the experimental groups Ⅱ and Ⅲ were higher than those of the control group and experimental group Ⅰ(P＜0.05).While the expression of cleaved-Caspase3 in the experimental groups Ⅱ and Ⅲ was lower than the control group and experimental group Ⅰ(P＜0.05),and it in the experimental group Ⅲ was lower than that of experimental group Ⅱ(P＜0.05).Conclusion Gln can significantly reduce the radiosensitivity of HT-29 cells,which is associated with its reducing oxidative stress damage and reducing cell apoptosis.Our results suggest that Gln might be detrimental to radiation therapy in patients with colorectal cancer.

Medical image is a powerful tool to assist doctors in the diagnosis and treatment planning.Nowadays,the segmentation of medical images is no longer limited to manual segmentation methods.Traditional methods and deep learning methods have been used to achieve more accurate results in medical image segmentation.Herein some innovative medical image segmentation methods in recent years are reviewed.By elaborating on the innovations of deep learning methods(SAM,SegNet,Mask R-CNN,and U-NET)and traditional methods(active contour model and threshold segmentation model),the differences and similarities between them are compared.The summary of medical image segmentation methods and the prospect is expected to help researchers better grasp and familiarize themselves with research status and development trend.

Ulcerative colitis (UC) is a chronic inflammation of the gastrointestinal tract and is characterized by alternating periods of inflammation and remission. Although UC incidence is lower in Taiwan than in Western countries, its impact remains considerable, demanding updated guidelines for addressing local healthcare challenges and patient needs. The revised guidelines employ international standards and recent research, emphasizing practical implementation within the Taiwanese healthcare system. Since the inception of the guidelines in 2017, the Taiwan Society of Inflammatory Bowel Disease has acknowledged the need for ongoing revisions to incorporate emerging therapeutic options and evolving disease management practices. This updated guideline aims to align UC management with local contexts, ensuring comprehensive and context-specific recommendations, thereby raising the standard of care for UC patients in Taiwan. By adapting and optimizing international protocols for local relevance, these efforts seek to enhance health outcomes for patients with UC.

Crohn’s disease (CD) is a chronic, fluctuating inflammatory condition that primarily affects the gastrointestinal tract. Although the incidence of CD in Taiwan is lower than that in Western countries, the severity of CD presentation appears to be similar between Asia and the West. This observation indicates the urgency for devising revised guidelines tailored to the unique reimbursement system, and patient requirements in Taiwan. The core objectives of these updated guidelines include the updated treatment choices and the integration of the treat-to-target strategy into CD management, promoting the achievement of deep remission to mitigate complications and enhance the overall quality of life. Given the diversity in disease prevalence, severity, insurance policies, and access to medical treatments in Taiwan, a customized approach is imperative for formulating these guidelines. Such tailored strategies ensure that international standards are not only adapted but also optimized to local contexts. Since the inception of its initial guidelines in 2017, the Taiwan Society of Inflammatory Bowel Disease (TSIBD) has acknowledged the importance of continuous revisions for incorporating new therapeutic options and evolving disease management practices. The latest update leverages international standards and recent research findings focused on practical implementation within the Taiwanese healthcare system.

Gestational diabetes mellitus (GDM) is one of the most common pregnancy complications and has serious implications for the health of mothers and their offspring. In recent years, studies have confirmed that air pollution is one of the main risk factors for diabetes, and there is increasing evidence that air pollution exposure is closely related to the occurrence of gestational diabetes. However, current studies on the association between air pollutant exposure and the incidence of gestational diabetes are inconsistent, and the window period of pollutant exposure is still unclear. Limited mechanistic studies suggest that airborne particulate matter and gaseous pollutants may affect GDM through multiple mechanisms, including inflammation, oxidative stress, disruption of adipokine secretion, and imbalance of intestinal flora. This review summarizes the relationship between air pollutant exposure and the incidence of GDM in recent years, as well as the possible molecular mechanism of the occurrence and development of GDM caused by air pollutants, in order to provide scientific basis for preventing pollutant exposure, reducing the risk of GDM, improving maternal and fetal outcomes and improving the quality of the birth population.
Pregnancy ; Female ; Humans ; Diabetes, Gestational/epidemiology* ; Air Pollution/analysis* ; Air Pollutants/analysis* ; Particulate Matter/analysis* ; Risk Factors ; Maternal Exposure/adverse effects*

Image-guided radiation therapy (IGRT) is a visual image-guided radiotherapy technique that has many advantages such as increasing the dose of tumor target area and reducing the dose of normal organ exposure. Cone beam CT (CBCT) is one of the most commonly used medical images in IGRT, and the rapid and accurate targeting of CBCT and the segmentation of dangerous organs are of great significance for radiotherapy. The current research method mainly includes partitioning method based on registration and segmentation method based on deep learning. This study reviews the CBCT image segmentation method, existing problems and development directions.