Gastric cancer remains a highly prevalent malignancy worldwide, with surgical resection currently constituting the cornerstone of treatment aimed at improving long-term patient survival. Owing to their notable advantages, including reduced surgical trauma and accelerated postoperative recovery, minimally invasive procedures are progressively supplanting conventional open surgery and have become the mainstream approach in gastric cancer management. Concurrently, the rapid advancement of artificial intelligence (AI) technologies has enabled real-time intraoperative monitoring of surgical scenes, thereby furnishing novel technical support for adjunctive decision-making, surgical navigation, and skill assessment during gastrectomy. This article provides a systematic review of the current status of AI applications in minimally invasive gastric cancer surgery, with a particular focus on research progress pertaining to instrument recognition, surgical phase identification, delineation of normal anatomical structures, detection of metastatic foci, and early warning of intraoperative adverse events. Furthermore, we discuss the potential value of AI in enhancing surgical efficiency, ensuring patient safety, and optimizing surgical education. On this basis, we further analyze the principal challenges and inherent risks confronting current AI systems, with the aim of informing future technological innovation and facilitating clinical translation.

This work was aimed at analyzing the protein characteristics of Coiled-Coil Domain-Containing Protein 115(CCDC115)and using Ccdc115-deficient mouse monocyte-macrophage leukemia cells(RAW264.7)to explore the influence of CCDC115 on the intracellular survival of Salmonella Typhimurium.Bioinformatics analysis was conducted to examine the fundamental attributes of CCDC115,which was determined to be an unstable protein consisting of two α-helices and an intervening disordered re-gion,devoid of any transmembrane structural domains.A RAW264.7-Ccdc115-KO cell line was successfully established with CRISPR/Cas9 gene-editing technology.To elucidate the effects of CCDC115 on the intracellular survival of Salmonella Typhimurium,we infected RAW264.7 cells with Salmonella Typhimurium.The expression of CCDC115 was found to be upregulated at both the mRNA and protein levels post-infection,according to RT-qPCR and western blot analysis.Via counting of colony-forming units(CFU),the proliferation rate of Salmonella Typhimurium within RAW264.7-Ccdc115-KO cells was found to be 1.5-fold higher than that in RAW264.7 cells.Acidification imaging studies indicated that,whereas Salmonella Typhimurium phagosomes underwent acidifi-cation in RAW264.7 cells,this process was absent in RAW264.7-Ccdc115-KO cells.In conclusion,the study successfully estab-lished a RAW264.7-Ccdc115-KO cell line and demonstrated that the expression of CCDC115 is elevated during Salmonella Ty-phimurium infection,thus potentially inhibiting the intracellular survival of Salmonella Typhimurium by facilitating phagosome acidifi-cation.This study lay a theoretical foundation for functional studies of CCDC115 and the investigation of mechanisms regulating the survival of intracellular Salmonella Typhimurium.

Objective To develop a nomogram-based predictive model for assessing the risk of respiratory distress syndrome(RDS)in premature infants in the high-altitude region of Dali.The predictive performance and clinical applicability of the model will be systematically evaluated to provide evidence-based guidance for the early diagnosis and clinical management of respiratory distress in premature infants.Methods A total of 680 preterm infants admitted to the Dali Maternal and Child Health Hospital between January 2020 and December 2024 were enrolled in the study and randomly divided into a training set(n=476)and a validation set(n=204)at a ratio of 7∶3.Independent predictors were identified through univariate logistic regression and multivariate stepwise regression analyses,and a nomogram model was subsequently developed using R software.The performance of the model,including its discrimination,calibration,stability,and clinical applicability,was evaluated using the receiver operating characteristic curve(ROC),Hosmer-Lemeshow goodness-of-fit test,bootstrap resampling method,and decision curve analysis(DCA).Results The final model incorporated seven independent variables:gestational age,birth weight,Apgar score,blood oxygen saturation,gestational hyperglycemia,prenatal glucocor-ticoid therapy,and maternal history of infection.The areas under the curve(AUCs)for the training and validation sets were 0.88(95%CI:0.84～0.92)and 0.83(95%CI:0.76～0.89),respectively,with all Hosmer-Lemeshow test p-values exceeding 0.05.The bootstrap-corrected AUC was 0.85(95%CI:0.81～0.89).DCA indicated that the model achieved the highest net benefit at a risk threshold range of 10%to 35%.Conclusions This model integrates multiple risk factors associated with the occurrence of RDS in plateau environments,demonstrating robust predictive performance for RDS in preterm infants residing in high-altitude areas such as Dali.It can serve as a valuable tool for risk stratification and clinical decision-making,and may also provide a reference for future multicenter prospective studies.

Objective To establish a stable,reliable,and clinically relevant porcine model of endotoxin-induced acute respiratory distress syndrome(ARDS).Methods Ten 8-month-old male Bama minipigs were deeply sedated,followed by invasive mechanical ventilation and electrocardiographic monitoring.Lipopolysaccharide(LPS)was intravenously pumped at 600 μg/(kg·h)for 3 hours,then maintained at 15 μg/(kg·h)thereafter.Dynamic monitoring was performed at five time points after LPS injection(LPS 0,1,3,5,and 8 h),including arterial blood gas analysis and chest computed tomography(CT)scans.Pathological examination of lung tissues obtained via bronchoscopic biopsy(HE staining and transmission electron microscopy)was conducted.These indicators were comprehensively used to evaluate the success of the animal model.Results At 5 hours after LPS administration,8 minipigs developed symptoms such as skin cyanosis,elevated body temperature,and respiratory distress.The oxygenation index decreased to<300 mmHg.Chest CT scans showed diffuse pulmonary infiltrates.Histopathology revealed alveolar edema and hyaline membrane formation.Transmission electron microscopy demonstrated disruption of pulmonary blood-air barrier,depletion of lamellar bodies in type Ⅱ pneumocytes,inflammatory cell infiltration,and exudation of plasma proteins and fibrin.Compared with LPS 0 h,at LPS 8 h,the oxygenation index and arterial blood pH were significantly decreased(P<0.001),while blood lactic acid and serum potassium were significantly increased(P<0.05);serum calcium and base excess were significantly decreased(P<0.05),and the lung injury score based on HE-stained lung sections was significantly increased(P<0.01).Conclusion The porcine ARDS model established by continuous LPS injection can dynamically simulate the pathophysiological characteristics and typical pathological manifestations of clinical septic ARDS,making it an effective tool to study the pathogenesis,prevention,and treatment strategies of septic ARDS.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

This work was aimed at analyzing the protein characteristics of Coiled-Coil Domain-Containing Protein 115(CCDC115)and using Ccdc115-deficient mouse monocyte-macrophage leukemia cells(RAW264.7)to explore the influence of CCDC115 on the intracellular survival of Salmonella Typhimurium.Bioinformatics analysis was conducted to examine the fundamental attributes of CCDC115,which was determined to be an unstable protein consisting of two α-helices and an intervening disordered re-gion,devoid of any transmembrane structural domains.A RAW264.7-Ccdc115-KO cell line was successfully established with CRISPR/Cas9 gene-editing technology.To elucidate the effects of CCDC115 on the intracellular survival of Salmonella Typhimurium,we infected RAW264.7 cells with Salmonella Typhimurium.The expression of CCDC115 was found to be upregulated at both the mRNA and protein levels post-infection,according to RT-qPCR and western blot analysis.Via counting of colony-forming units(CFU),the proliferation rate of Salmonella Typhimurium within RAW264.7-Ccdc115-KO cells was found to be 1.5-fold higher than that in RAW264.7 cells.Acidification imaging studies indicated that,whereas Salmonella Typhimurium phagosomes underwent acidifi-cation in RAW264.7 cells,this process was absent in RAW264.7-Ccdc115-KO cells.In conclusion,the study successfully estab-lished a RAW264.7-Ccdc115-KO cell line and demonstrated that the expression of CCDC115 is elevated during Salmonella Ty-phimurium infection,thus potentially inhibiting the intracellular survival of Salmonella Typhimurium by facilitating phagosome acidifi-cation.This study lay a theoretical foundation for functional studies of CCDC115 and the investigation of mechanisms regulating the survival of intracellular Salmonella Typhimurium.

Objective To develop a nomogram-based predictive model for assessing the risk of respiratory distress syndrome(RDS)in premature infants in the high-altitude region of Dali.The predictive performance and clinical applicability of the model will be systematically evaluated to provide evidence-based guidance for the early diagnosis and clinical management of respiratory distress in premature infants.Methods A total of 680 preterm infants admitted to the Dali Maternal and Child Health Hospital between January 2020 and December 2024 were enrolled in the study and randomly divided into a training set(n=476)and a validation set(n=204)at a ratio of 7∶3.Independent predictors were identified through univariate logistic regression and multivariate stepwise regression analyses,and a nomogram model was subsequently developed using R software.The performance of the model,including its discrimination,calibration,stability,and clinical applicability,was evaluated using the receiver operating characteristic curve(ROC),Hosmer-Lemeshow goodness-of-fit test,bootstrap resampling method,and decision curve analysis(DCA).Results The final model incorporated seven independent variables:gestational age,birth weight,Apgar score,blood oxygen saturation,gestational hyperglycemia,prenatal glucocor-ticoid therapy,and maternal history of infection.The areas under the curve(AUCs)for the training and validation sets were 0.88(95%CI:0.84～0.92)and 0.83(95%CI:0.76～0.89),respectively,with all Hosmer-Lemeshow test p-values exceeding 0.05.The bootstrap-corrected AUC was 0.85(95%CI:0.81～0.89).DCA indicated that the model achieved the highest net benefit at a risk threshold range of 10%to 35%.Conclusions This model integrates multiple risk factors associated with the occurrence of RDS in plateau environments,demonstrating robust predictive performance for RDS in preterm infants residing in high-altitude areas such as Dali.It can serve as a valuable tool for risk stratification and clinical decision-making,and may also provide a reference for future multicenter prospective studies.

Objective To explore the publication trends and future directions in the field of value of MRI for diagnosing uterine fibroids using bibliometrics.Methods Literature related to diagnostic value of MRI for uterine fibroids in CNKI,Wanfang Med Online,SinoMed and WOSCC databases from 2006 to 2024 were retrieved,and 460 Chinese and 166 English articles were included.A bibliometric analysis was conducted to examine annual publication volume,country/region collaborations,journal distribution,core authors,highly cited literatures and keywords related to MRI for diagnosing uterine fibroids.Results From 2006 to 2024,the number of publications showed a fluctuating upward trend,with Chinese literature dominating.Authors from United States led research in this field and had the closest collaboration with those from France.Chinese and English articles were published in 221 and 81 journals,respectively,with several journals demonstrating significant influence.Highly cited articles mainly focused on differential diagnosis in early publications.Keywords analysis indicated that Chinese studies emphasized diagnosis and pathological typing,while English studies were more concerned with technical comparisons and accuracy assessment.Since 2020,research focus shifted toward image analysis technology and MRI-guided therapy.Conclusion The research on value of MRI for diagnosing uterine fibroids has been continuously developing.In the future,application of new technologies could be further explored,and multi-center cooperation and clinical transformation should be strengthened to promote the development and innovation in this field.

INTRODUCTION: Obstructive sleep apnoea (OSA) is common in Singapore, with moderate to severe OSA affecting around 30% of residents. These consensus statements aim to provide scientifically grounded recommendations for the management of OSA, standar-dise the management of OSA in Singapore and promote multidisciplinary collaboration. METHOD: An expert panel, which was convened in 2024, identified several areas of OSA management that require guidance. The expert panel reviewed the current literature and developed consensus statements, which were later independently voted on using a 3-point Likert scale (agree, neutral or disagree). Consensus (total ratings of agree and neutral) was set a priori at ≥80% agreement. Any statement not reaching consensus was excluded. RESULTS: The final consensus included 49 statements that provide guidance on the screening, diagnosis and management of adults with OSA. Additionally, 23 statements on the screening, diagnosis and management of paediatric OSA achieved consensus. These 72 consensus statements considered not only the latest clinical evidence but also the benefits and harms, resource implications, feasibility, acceptability and equity impact of the recommendations. CONCLUSION The statements presented in this paper aim to guide clinicians based on the most updated evidence and collective expert opinion from sleep specialists in Singapore. These recommendations should augment clinical judgement rather than replace it. Management decisions should be individualised, taking into account the patient's clinical characteristics, as well as patient and caregiver concerns and preferences.
Humans ; Sleep Apnea, Obstructive/diagnosis* ; Singapore ; Consensus ; Adult