Employment is the cornerstone of people's livelihood and a vital component of talent cultivation in higher educa-tion institutions. In the pursuit of the "Healthy China 2030" initiative, medical colleges and universities are com-mitted to ensuring high-quality and comprehensive employment for their students by strengthening Party-building efforts. This approach aims to enhance students' employability, secure favorable employment rates, and align their career development with societal needs. This article explores the significance of Party-building in guiding college students towards proactive employment. It provides a comprehensive analysis of the current employment landscape in medical colleges and universities, identifying key challenges and opportunities. In response to these challenges, the article offers targeted recommendations on how Party-building initiatives within these institutions can foster high-quality and full employment for medical students. By integrating ideological guidance, skill en-hancement, and strategic training reforms, the proposed measures aim to support medical graduates in making informed career choices and securing suitable employment, thereby contributing to the advancement of health-care and societal well-being.

Cardiovascular diseases are still the primary threats to people's health around the world. Automatic heart sound classification technology, as a fast and efficient means for diagnosis and treatment, is of great clinical significance. With the rapid development of artificial intelligence technology, deep learning algorithms are widely used in automatic heart sound classification. This paper reviewed the key technologies related to the automatic classification of heart sounds in recent years, including heart sound denoising, segmentation, feature extraction, and classification recognition. The classification and recognition technologies related to deep learning are presented in detail, with a focus on the application and development of convolutional neural network and recurrent neural network, as well as various combination models for heart sound classification in the past five years.

This paper presents a gait prediction method for lower limb exoskeleton robots using a real-time adaptive Kalman filtering algorithm. The exoskeleton robot targets two user groups: individuals with impaired lower limb motor function requiring rehabilitation training, where the device aids in muscle exercise during walking to facilitate recovery, and healthy individuals using it as a wearable assistive device. To enhance movement intention prediction and improve human-machine coordination, this study focuses on the gait prediction algorithm for walking assistance in healthy users and proposes a gait prediction control strategy based on normal gait orientation. The control system utilizes a microcontroller and Raspberry Pi as its core, enabling functional mode selection through multi-sensor data fusion and effective control of the robot via Bluetooth communication. By comparing the original model algorithm with the proposed real-time updating Kalman filter algorithm, the latter demonstrates feasibility, achieving a prediction error within 1°. This validates the model’s effectiveness in real-time gait prediction.

Obstetric and perinatal anesthesia, while crucial for maternal and neonatal health, carries inherent risks that necessitate careful management and resource optimization to ensure patient safety. Improvements in anesthesia methods, ultrasound-assisted blocks, multimodal analgesia and accelerated rehabilitation protocols have enabled individualized and precise control of postoperative pain to be achieved more readily. Risk analysis, dynamic observation, and personalized intervention can all significantly lower the rates of hypotension, nausea and vomiting, and nerve injury. International practice variations highlight how resource availability—including staffing levels and expertise—and adherence to clinical guidelines profoundly impact maternal and neonatal outcomes, underscoring that scientific resource optimization is essential for ensuring safety and enhancing efficiency. This perspective discusses the current trends in perinatal anesthesia, focusing on risk minimization and resource utilization. By synthesizing recent advancements and practice variations, we aim to offer a conceptual framework and valuable insights for clinicians making management decisions.

Emergency surgery anesthesia is performed in an extremely time-critical and high-risk setting, where delayed or inaccurate assessment may lead to severe perioperative complications. Patients often present with hemodynamic instability, limited preoperative information, and complex comorbidities, creating major challenges for anesthesiologists to rapidly evaluate airway, circulation, and physiological reserve. Although multiple assessment tools exist, conventional approaches remain fragmented and insufficient for dynamic, real-time decision-making in emergency contexts. There is a clear need for an integrated rapid anesthesia assessment framework that combines advanced monitoring, intelligent decision support, and team-based coordination. This perspective article systematically analyzes rapid assessment models that integrate multimodal point-of-care ultrasound, artificial intelligence–assisted regulation, and closed-loop clinical decision support system (CDSS) protocols. Key applications in perioperative airway management, hemodynamic and respiratory assessment, and risk stratification for special populations, including elderly and pediatric patients, are discussed. We further summarize the rapid titration and hemodynamic advantages of novel anesthetic agents in emergency induction, the role of CDSS and closed-loop communication in clinical emergency management, and the optimization of team collaboration using standardized tools such as Situation–Background–Assessment–Recommendation. Ethical and legal considerations, including informed consent, presumed consent, and proxy decision-making in time-sensitive scenarios, are also addressed. Overall, integrated rapid assessment strategies supported by technology, interdisciplinary teamwork, and ethical safeguards may substantially enhance the safety, efficiency, and clinical outcomes of anesthesia management in emergency surgery, providing a practical framework for future perioperative practice and multicenter validation.

Bile duct stenosis is a common condition in gastroenterology and hepatobiliary surgery and can be divided into benign stenosis and malignant stenosis according to different etiologies. The implantation of a gall stent into the site of the stenosis or obstruction is currently an important means of treating the bile duct stenosis. Biliary stents encompass two main types: plastic stents and metal stents. In recent years, biodegradable biliary stents and drug-eluting stents have also emerged. The material and structure of biliary stents have an important influence on their performance. In this paper, the research progress on biliary stent implantation technology in the treatment of biliary stenosis is reviewed. Besides, the advantages and disadvantages of biliary stents made from different materials and structures, along with their respective indications are summarized, and the development trend of degradable biliary stents is prospected.

This review comprehensively examines current intestinal anastomosis techniques. Traditional manual suturing methods, including intermittent and continuous sutures, provide high flexibility but but vary in infection risk and operation time. Continuous suturing is particularly effective in reducing operative time and infection risk. Suture materials include non-absorbable sutures, absorbable sutures, and natural materials, with absorbable sutures the most preferred for intestinal anastomosis. Mechanical anastomosis has gained widespread adoption, featuring both linear and circular metal staplers. Linear staplers are simple to operate, while circular staplers better align with physiological structures. Materials used in staplers include non-degradable metals (e.g., titanium, titanium alloy) and biodegradable anastomosis (e.g., magnesium alloy). Metal nail anastomosis often results in fewer complications than manual suturing in specific surgeries. Magnetic pressure anastomosis, relying on magnet attraction, has been successfully applied in clinical scenarios following extensive research. The adhesive-based approach involves medical adhesives such as cyanoacrylate and fibrin glue, offering auxiliary support for anastomosis. Energy tissue welding encompasses laser and radio frequency energy tissue welding. While laser welding poses a risk of thermal damage, radio frequency welding offers significant advantages, including faster, seamless anastomosis with reduced complications. The support method for intestinal anastomosis is a novel concept, involving the addition of support materials to the original anastomosis. It can be divided into composite and simple support methods. The simple support method, as evidenced by the "degradable internal scaffold method for digestive tract anastomosis" developed by Cai et al. in China, has demonstrated promising results in animal experiments. In conclusion, selecting the appropriate intestinal anastomosis technique depends on clinical scenarios to optimize surgical outcomes and reduce complications. The diverse technological advancements reviewed here present valuable opportunities for enhancing the quality and safety of intestinal surgery.