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.

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.

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.

BACKGROUND: There is a high morbidity, mortality, and poor clinical prognosis of lung squamous cell carcinoma (LUSC). However, there is currently no effective targeted treatment plan for LUSC. As a long non-coding RNA (lncRNA), lncRNA miR143HG has been proven to play an important role in the occurrence and development of various tumors. However, the biological role played by lncRNA miR143HG in LUSC cells is still unclear. Therefore, this study aimed to investigate the mechanism of lncRNA miR143HG on regulating the biological behavior of LUSC H520 cells. METHODS: Pan-cancer analysis and differential expression analysis of lncRNA miR143HG were performed based on The Cancer Genome Atlas (TCGA) database. The predictive effect of lncRNA miR143HG on the diagnosis and prognosis of LUSC was evaluated by adopting the receiver operating characteristic (ROC) curve and timeROC curve. The enrichment degree of each pathway to lncRNA miR143HG was determined. The expression of lncRNA miR143HG and miR-155 in BEAS-2B cells and H520 cells was detected using quantitative real-time polymerase chain reaction (qRT-PCR). H520 cells were randomly divided into blank control group (without any treatment), negative control group (transfected with lncRNA-NC), lncRNA miR143HG group (transfected with lncRNA miR143HG), and lncRNA miR143HG+miR-155 group (co-transfected with lncRNA miR143HG and miR-155). The approaches of CCK-8, wound healing test, Transwell assay, flow cytometry, qRT-PCR, and Western blot were respectively employed to detect the cell proliferation ability, cell migration ability, cell invasion ability, cell apoptosis rate, and expression level of related genes and proteins of the Wnt/β-Catenin pathway. RESULTS: The results of pan-cancer analysis and differential analysis collectively showed that except for renal clear cell carcinoma, the expression of lncRNA miR143HG in other cancer tissues was higher than that in healthy tissues, and the differences were significant in LUSC. The evaluation results of the ROC curve and timeROC curve suggested that lncRNA miR143HG was of great significance in the prediction of diagnosis and prognosis of LUSC. The pathways enriched in high expression of lncRNA miR143HG mainly included focal adhesion, vascular smooth muscle contraction, calcium signaling pathways, and so on; the pathways enriched in the low expression of lncRNA miR143HG embraced oxidative phosphorylation, cell cycle, basic transcription factors, etc. The qRT-PCR results showed that lncRNA miR143HG was low expressed but miR-155 was highly expressed in H520 cells when compared to BEAS-2B cells (P<0.05). Compared with the negative control group, the expression levels of the gene of lncRNA miR143HG, the gene and protein of Wnt, as well as the gene and protein of β-Catenin were significantly increased, while the gene expression of miR-155, the ability of cell proliferation, cell migration, and cell invasion were significantly reduced, but the cell apoptosis rate was dominantly elevated in cells of lncRNA miR143HG group (P<0.05). In addition, compared with the lncRNA miR143HG group, overexpression of miR-155 could reverse the biological behavior mediated by lncRNA miR143HG, and the difference was statistically significant (P<0.05). CONCLUSIONS LncRNA miR143HG was of great significance for the biological behavior of H520 cells. LncRNA miR143HG inhibited the ability of proliferation, migration, and invasion, as well as enhanced the apoptosis of H520 cells by downregulating miR-155 expression, which may be related to the Wnt/β-Catenin pathway.
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Humans ; RNA, Long Noncoding/genetics* ; beta Catenin/metabolism* ; Lung Neoplasms/genetics* ; Carcinoma, Squamous Cell/genetics* ; Carcinoma, Non-Small-Cell Lung/genetics* ; MicroRNAs/genetics* ; Lung/pathology* ; Cell Proliferation/genetics* ; Cell Movement/genetics* ; Gene Expression Regulation, Neoplastic