Spine fracture and dislocation are common traumatic spinal conditions that often require surgical intervention due to compromised spinal stability. Surgical approaches include anterior, posterior, and combined anterior-posterior spinal procedures. According to the specific surgical requirements, patients may be placed in the prone position or repositioned between prone and supine positions during surgery. Intraoperative repositioning has become an essential step in patient positioning. However, during repositioning, patients with spinal fracture and dislocation are at increased risk for complications such as hemodynamic instability, nerve injury, and pressure injuries to the skin and soft tissue. Notably, due to the instability of the spinal cord, even minor manipulations can further exacerbate the damage, potentially leading to severe outcomes like paraplegia. Although the current clinical guidelines provide instructive recommendations for standard position, there remains no specific protocols for intraoperative repositioning in patients with spine fracture and dislocation. With a concern for the lack of clinical studies on positioning techniques, risk prevention, and operational norms for special patients, no applicable guidelines or standards are available. A consensus was required to provide clinical reference, meet the requirements of surgical treatment, and minimize the safety risks of patients caused by improper placement of positions. Professional Committee of Operating Room Nursing of Shaanxi Nursing Association organized experts in nursing management and operating room nursing from major hospitals across China to formulate Expert consensus on intraoperative repositioning for patients with spinal fracture and dislocation ( version 2025). The consensus provides 11 recommendations covering pre-repositioning preparation, intraoperative maneuvers, and post-repositioning observation, aiming to provide references for clinical standardization of the intraoperative repositioning process and protection of patients′ safety.

Objective To comparatively evaluate the diagnostic value of metagenomic next-generation sequencing(mNGS)versus conventional microbial culture in spinal infections.Methods A cross-section design was conducted on 82 consecutive patients with suspected spinal infections treated between February 2022 and January 2024 at Jiangbei Branch of First Affiliated Hospital of Army Medical University(Third Military Medical University).Microbiological culture,histopathological examination,and mNGS results from infected specimens were analyzed.Clinical diagnosis,primarily based on clinical manifestations,laboratory tests and radiologic features combined with medical history,was defined as the gold standard,and then the diagnostic performance,including sensitivity and specificity,were compared between mNGS and microbial culture.Results Among the 82 patients,definitive microbiological evidence was identified in 70 cases,and mNGS demonstrated a significantly higher detection rate than microbial culture(64 vs 36 cases,78.05％vs 43.9％,P<0.05).mNGS also obtained obviously higher sensitivity,accuracy,and negative predictive value(NPV),and notably lower positive predictive value(PPV)when compared to conventional microbial culture(all P<0.05).When stratified by infection type,mNGS obtained significantly higher sensitivity and accuracy compared to microbial culture in tuberculous spinal infections(P<0.05).For non-tuberculous spinal infections,mNGS also showed superior sensitivity to microbial culture(P<0.05).Conclusion In patients with spinal infections,mNGS demonstrates a significantly higher pathogen detection rate than conventional microbial culture.This technique can provide early and broad-spectrum pathogenic microbiological evidence for spinal infection.

With the advancements in artificial intelligence (AI), computational power, and surgical robotics, the analysis of surgical performance at the granular level of individual surgical gestures has become feasible. Surgical gestures, defined as the smallest independent units of inter-action between surgical instruments and tissues, offer a quantifiable framework for surgical skill assessment. Evidence suggests that the selection and execution of surgical gestures are strongly correlated with the expertise of the surgeon and patient outcomes, underscoring their significance in both surgical training and clinical practice. Moreover, the establishment of a standardized classifi-cation system for surgical gestures and the adoption of uniform terminology have the potential to improve communication efficiency during surgical education and training. The authors synthesize existing classification systems for surgical gestures, with a focus on their applications in diverse tasks such as suturing, exposure and dissection. By examining the latest advancements in AI models applied to surgical gesture, as well as the current research landscape of surgical gesture recognition in digestive surgery, the authors explore the potential applications of such technologies in assisting surgeons during operations in the future.

With the rapid development of minimally invasive techniques in surgery, arti-ficial intelligence (AI), particularly deep learning, is playing an increasingly important role in mini-mally invasive surgery. By automated analysis of surgical videos, AI can efficiently perform key tasks such as instrument recognition, surgical phase identification, action analysis, anatomical structure recognition, intraoperative diagnosis, adverse event monitoring and smart desmoking. These appli-cations provide essential support for real-time monitoring, surgical navigation and skill assessment during surgery. The authors summarize the current research progress of AI in minimally invasive surgery, including its applications in the fields of hepatobiliary and pancreatic surgery, as well as gastrointestinal surgery. It also explores the potential of AI in enhancing surgical safety, efficiency and skill assessment. By synthesizing the latest research achievements of AI technology in the field of surgery, as well as analyzing its technical challenges and risks, it aims to provide guidance for future innovations and clinical applications, promoting the advancement and implementation of AI in minimally invasive surgery.

The esophagogastric junction serves as a natural anti-reflux barrier and possesses a complex anatomical configuration composed of several key components, including the lower esophageal sphincter, diaphragmatic crura, His angle, and phrenoesophageal ligament. Alterations in these anatomical structures or dysfunction thereof may predispose individuals to gastroesophageal reflux disease (GERD). In response to such structural and functional impairments, various therapeutic strategies have been developed. Surgical intervention is currently regarded as an effective approach for fundamentally addressing GERD, with commonly employed techniques including laparoscopic fundoplication, magnetic sphincter augmentation, and endoscopic radiofrequency ablation. The author classifies the anti-reflux mechanisms at the esophagogastric junction into intramural and extramural components, and based on this classification, systematically reviews and evaluates the indications and clinical applications of major surgical interventions for GERD, aiming to provide clinicians with evidence-based guidance for selecting appropriate therapeutic modalities.

The esophagogastric junction serves as a natural anti-reflux barrier and possesses a complex anatomical configuration composed of several key components, including the lower esophageal sphincter, diaphragmatic crura, His angle, and phrenoesophageal ligament. Alterations in these anatomical structures or dysfunction thereof may predispose individuals to gastroesophageal reflux disease (GERD). In response to such structural and functional impairments, various therapeutic strategies have been developed. Surgical intervention is currently regarded as an effective approach for fundamentally addressing GERD, with commonly employed techniques including laparoscopic fundoplication, magnetic sphincter augmentation, and endoscopic radiofrequency ablation. The author classifies the anti-reflux mechanisms at the esophagogastric junction into intramural and extramural components, and based on this classification, systematically reviews and evaluates the indications and clinical applications of major surgical interventions for GERD, aiming to provide clinicians with evidence-based guidance for selecting appropriate therapeutic modalities.

With the advancements in artificial intelligence (AI), computational power, and surgical robotics, the analysis of surgical performance at the granular level of individual surgical gestures has become feasible. Surgical gestures, defined as the smallest independent units of inter-action between surgical instruments and tissues, offer a quantifiable framework for surgical skill assessment. Evidence suggests that the selection and execution of surgical gestures are strongly correlated with the expertise of the surgeon and patient outcomes, underscoring their significance in both surgical training and clinical practice. Moreover, the establishment of a standardized classifi-cation system for surgical gestures and the adoption of uniform terminology have the potential to improve communication efficiency during surgical education and training. The authors synthesize existing classification systems for surgical gestures, with a focus on their applications in diverse tasks such as suturing, exposure and dissection. By examining the latest advancements in AI models applied to surgical gesture, as well as the current research landscape of surgical gesture recognition in digestive surgery, the authors explore the potential applications of such technologies in assisting surgeons during operations in the future.

With the rapid development of minimally invasive techniques in surgery, arti-ficial intelligence (AI), particularly deep learning, is playing an increasingly important role in mini-mally invasive surgery. By automated analysis of surgical videos, AI can efficiently perform key tasks such as instrument recognition, surgical phase identification, action analysis, anatomical structure recognition, intraoperative diagnosis, adverse event monitoring and smart desmoking. These appli-cations provide essential support for real-time monitoring, surgical navigation and skill assessment during surgery. The authors summarize the current research progress of AI in minimally invasive surgery, including its applications in the fields of hepatobiliary and pancreatic surgery, as well as gastrointestinal surgery. It also explores the potential of AI in enhancing surgical safety, efficiency and skill assessment. By synthesizing the latest research achievements of AI technology in the field of surgery, as well as analyzing its technical challenges and risks, it aims to provide guidance for future innovations and clinical applications, promoting the advancement and implementation of AI in minimally invasive surgery.

Spine fracture and dislocation are common traumatic spinal conditions that often require surgical intervention due to compromised spinal stability. Surgical approaches include anterior, posterior, and combined anterior-posterior spinal procedures. According to the specific surgical requirements, patients may be placed in the prone position or repositioned between prone and supine positions during surgery. Intraoperative repositioning has become an essential step in patient positioning. However, during repositioning, patients with spinal fracture and dislocation are at increased risk for complications such as hemodynamic instability, nerve injury, and pressure injuries to the skin and soft tissue. Notably, due to the instability of the spinal cord, even minor manipulations can further exacerbate the damage, potentially leading to severe outcomes like paraplegia. Although the current clinical guidelines provide instructive recommendations for standard position, there remains no specific protocols for intraoperative repositioning in patients with spine fracture and dislocation. With a concern for the lack of clinical studies on positioning techniques, risk prevention, and operational norms for special patients, no applicable guidelines or standards are available. A consensus was required to provide clinical reference, meet the requirements of surgical treatment, and minimize the safety risks of patients caused by improper placement of positions. Professional Committee of Operating Room Nursing of Shaanxi Nursing Association organized experts in nursing management and operating room nursing from major hospitals across China to formulate Expert consensus on intraoperative repositioning for patients with spinal fracture and dislocation ( version 2025). The consensus provides 11 recommendations covering pre-repositioning preparation, intraoperative maneuvers, and post-repositioning observation, aiming to provide references for clinical standardization of the intraoperative repositioning process and protection of patients′ safety.

From September 26 to 28,2024,the 11th Korean International Gastric Cancer Week(KINGCA WEEK 2024),a prestigious academic conference in the field of gastric cancer,was held in Seoul.Organized by the Korean Gastric Cancer Association,the conference featured one main venue,18 sub-venues,and 16 thematic symposiums,including 100 invited presentations and four keynote speeches,attracting 788 experts and scholars from around the world.Additionally,the conference set 16 themes and received 425 submissions from 24 countries,including Republic of Korea,China,Japan,and the United States.After a review process,365 submissions were accepted,which included eight plenary oral presentations,78 oral reports,and 279 poster presentations.The conference covered many hot topics in gastric cancer diagnosis and treatment,with a particular focus on surgical-related areas such as treatment strategies for metastatic gastric cancer,an international consensus meeting on the conversion therapy for stage Ⅳgastric cancer,future research directions of the Korean Laparoendoscopic Gastrointestinal Surgery Study Group,the development of new surgical instruments and equipment,and key issues in lymph node dissection,resection,and reconstruction during minimally invasive gastric cancer surgeries.Furthermore,our team was invited to present two oral reports on"the application of artificial intelligence in minimally invasive gastric cancer surgery".This report aims to detail the dynamics and hotspots related to surgical treatment for gastric cancer,providing valuable references and insights for domestic surgical peers.