The cost economics of early-stage lung cancer treatments is a key focus in the field of lung cancer. The primary treatment modalities for early-stage lung cancer include radiotherapy and thoracic surgery, each offering distinct advantages in therapeutic outcomes and costs. To better understand the cost-effectiveness of radiotherapy versus thoracic surgery for early-stage lung cancer, this paper reviews the progress of recent research on economic evaluations of these two treatment approaches.

Objective To investigate the effectiveness of the curriculum design and teaching mode reform in Health Statistics through the assessment by postgraduate students so as to enhance the teaching performance of the course.Methods A questionnaire survey was conducted among the postgraduate students of grade 2023 at a certain medical university.The survey covered such aspects as students'mastery and application of the course learning content,their evaluation and satisfaction with the course,etc.Descriptive approaches were employed to analyze and summarize the data.Results Students achieved a good command of theoretical knowledge and its application.They highly evaluated the teacher,the course content and its practicality,demonstrated a strong interest in learning,expressed a high level of satisfaction with the course,and manifested a strong willingness to continue studying the course.The learning of the course met the expectations of the students.The final exam scores in the later stage of curriculum reform(78.60±10.58)was higher than that before the reform(75.78±7.97,P<0.05);the excellent rate after the reform was 53.6%,which was higher than the 33.5%before the reform(P<0.05).Conclusion The construction of a course system that integrates knowledge,skills the mixed teaching mode of case-based teaching and the combination of theory and statistical software package operation are beneficial for enhancing postgraduate students'learning and application of the course in health statistics.It also strengthens the design and training of course application aspects for students in clinical medicine and dental medicine disciplines.

Perinatal depression (PND) is a critical public health issue affecting maternal and offspring health. Digital health intervention platforms, leveraging advantages in accessibility, privacy, and cost-effectiveness, demonstrate good application in PND prevention and treatment. This review systematically searched literature and policy documents published between January 2018 and March 2025 in CNKI, PubMed, Web of Science and World Health Organization. It summarized the development trajectory of digital health intervention platforms and their current applications and effectiveness in PND prevention and treatment. Existing evidence was evaluated across dimensions of efficacy, systematicity, and practicality, identifying major challenges faced by these platforms. Studies indicate that while PND digital health intervention platforms have achieved preliminary success in alleviating PND symptoms, widespread issues persist, including incomplete service closed-loop systems, low user adherence, and insufficient sustainability. Future efforts should focus on optimizing intervention content and interactive design, advancing intelligent assessment and tiered intervention strategies, strengthening continuous monitoring and crisis response mechanisms, and constructing a multidisciplinary collaborative support system. These steps are essential for achieving efficient, intelligent, and sustainable development of digital health intervention platforms for PND.

Objective:To investigate the awareness levels of doctors from various departments regarding fertility preservation to provide reference and suggestions for further improving awareness and promoting multidisciplinary development in fertility preservation.Methods:From November to December 2023, the China Alliance of Fertility Preservation initiated this survey covering 88 hospitals in 23 cities across 20 provinces in China. The survey focused on the degree of understanding of basic concepts, technological perceptions, treatment concepts, and related challenges regarding fertility preservation. Descriptive statistics and Fisher's exact test were used to analyze the difference in awareness levels across various departments.Results:There was a significant difference in the awareness of fertility preservation guidelines among physicians from different departments ( P<0.001). Reproductive center physicians had the highest level of understanding [68.3% (41/60)]. Doctors in the reproductive centers had a higher awareness rate of the five fertility preservation techniques (ovarian tissue cryopreservation, oocyte cryopreservation, sperm cryopreservation, testicular tissue cryopreservation, and embryo cryopreservation) than that in other departments (all P<0.05). Regarding treatment concepts, more reproductive center physicians believed that psychological counselling about fertility preservation before oncological treatment was necessary ( P=0.016). Hematologists had more worries and concerns about fertility preservation treatment. Additionally, 96.7% (58/60) of reproductive center physicians expressed the need to establish effective referral mechanisms within the same city, province, or across provinces. However, 55.6% (35/63) of oncologists, 64.6% (31/48) of hematologists, and 77.8% (7/9) of pediatricians considered treating primary tumors far more important than fertility preservation. Conclusion:Doctors from different departments have varying levels of understanding regarding fertility preservation. It is necessary to strengthen the dissemination and training of fertility preservation knowledge among physicians from various departments, as well as to promote a multidisciplinary treatment model to improve efficiency, to establish a comprehensive referral mechanism to improve patients' opportunities for fertility preservation.

Patients with advanced pregnancy complicated by acute ST-segment elevation myocardial infarction are relatively rare both domestically and internationally,and there are currently no relevant guidelines to guide clinical treatment.In this case,a 39-year-old pregnant woman was admitted to the hospital with sudden chest pain,and the electrocardiogram showed extensive anterior ST-segment elevation myocardial infarction.Coronary angiography showed subtotal subtotal occlusion of the proximal left anterior descending artery.Reperfusion and revascularization were given,and the blood flow grade of the trial of thrombolytic in myocardial infarction was restored.Complete intravascular ultrasonography to determine the cause of occlusion due to spontaneous hematoma of the left anterior descending artery.After the operation,a reasonable antiplatelet and anticoagulant treatment regimen was selected according to the coronary artery lesion,and the pregnancy was terminated at the appropriate time,and 1 live male baby was successfully delivered.Maternal and fetal health was followed up after 1、3 and 6 months.Through the experience and summary of the treatment process,combined with the literature,the pathogenesis of this disease is discussed,and the strategy of revascularization,the selection of antithrombotic drugs and the timing of pregnancy termination are discussed in depth for clinical reference.

Periodontitis is a globally prevalent inflammatory oral disease, affecting approximately 50% of the population worldwide and imposing a substantial burden on patients′ health and quality of life. Early and accurate diagnosis is critical for preventing disease progression; however, conventional diagnostic approaches often rely on subjective clinical assessments, which only primarily evaluate the cumulative state of the disease, thus limiting their ability to achieve precise early detection. In recent years, the rapid advancement of artificial intelligence (AI) in medical diagnostics has demonstrated significant promise, particularly through the integration of multimodal data to enable more comprehensive information capture and analysis. Multimodal data fusion, which combines diverse inputs such as imaging, clinical parameters, and biomarkers, offers transformative potential for AI-powered periodontitis diagnostics. This innovative approach aims to overcome the limitations of traditional methods, significantly enhancing diagnostic accuracy and predictive capabilities. This manuscript reviews the primary diagnostic techniques for periodontitis, explores recent advances in AI applications within this domain, and emphasizes the potential of multimodal data in facilitating precision diagnosis. Furthermore, it provides new insights and supports for personalized treatment strategies.

[This corrects the article DOI: 10.1016/j.apsb.2022.05.019.].

Hypoxic-ischemic (HI) brain damage poses a high risk of death or lifelong disability, yet effective treatments remain elusive. Here, we demonstrated that miR-100-5p levels in the lesioned cortex increased after HI insult in neonatal mice. Knockdown of miR-100-5p expression in the brain attenuated brain injury and promoted functional recovery, through inhibiting the cleaved-caspase-3 level, microglia activation, and the release of proinflammation cytokines following HI injury. Engineered extracellular vesicles (EVs) containing neuron-targeting rabies virus glycoprotein (RVG) and miR-100-5p antagonists (RVG-EVs-Antagomir) selectively targeted brain lesions and reduced miR-100-5p levels after intranasal delivery. Both pre- and post-HI administration showed therapeutic benefits. Mechanistically, we identified protein phosphatase 3 catalytic subunit alpha (Ppp3ca) as a novel candidate target gene of miR-100-5p, inhibiting c-Fos expression and neuronal apoptosis following HI insult. In conclusion, our non-invasive method using engineered EVs to deliver miR-100-5p antagomirs to the brain significantly improves functional recovery after HI injury by targeting Ppp3ca to suppress neuronal apoptosis.
Animals ; MicroRNAs/metabolism* ; Extracellular Vesicles/metabolism* ; Mice ; Recovery of Function/physiology* ; Hypoxia-Ischemia, Brain/therapy* ; Mice, Inbred C57BL ; Antagomirs/administration & dosage* ; Male ; Animals, Newborn ; Apoptosis/drug effects* ; Brain Injuries/metabolism* ; Glycoproteins ; Peptide Fragments ; Viral Proteins

The rapid development of artificial intelligence (AI), especially generative AI (GenAI), has already brought, and will continue to bring, revolutionary changes to our daily production and life, as well as create new opportunities and challenges for diagnostic and therapeutic practices in the medical field. Haihe Hospital of Tianjin University collaborates with the National Supercomputer Center in Tianjin, Tianjin University, and other institutions to carry out research in areas such as smart healthcare, smart services, and smart management. We have conducted research and development of a full-process disease diagnosis and treatment assistance system based on GenAI in the field of smart healthcare. The development of this project is of great significance. The first goal is to upgrade and transform the hospital's information center, organically integrate it with existing information systems, and provide the necessary computing power storage support for intelligent services within the hospital. We have implemented the localized deployment of three models: Tianhe "Tianyuan", WiNGPT, and DeepSeek. The second is to create a digital avatar of the chief physician/chief physician's voice and image by integrating multimodal intelligent interaction technology. With generative intelligence as the core, this solution provides patients with a visual medical interaction solution. The third is to achieve deep adaptation between generative intelligence and the entire process of patient medical treatment. In this project, we have developed assistant tools such as intelligent inquiry, intelligent diagnosis and recognition, intelligent treatment plan generation, and intelligent assisted medical record generation to improve the safety, quality, and efficiency of the diagnosis and treatment process. This study introduces the content of a full-process disease diagnosis and treatment assistance system, aiming to provide references and insights for the digital transformation of the healthcare industry.
Artificial Intelligence ; Humans ; Delivery of Health Care ; Generative Artificial Intelligence