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.

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.

Multimodal image fusion technique is a key technology that combines a variety of medical imaging methods to obtain compre-hensive diagnostic information,which has been widely used in clinical disease research.Finite element analysis is essentially a numerical method for solving differential equations,which simulates various physiological and pathological scenarios through combining with multimodal image fusion technique.It has been applied to many medical fields such as the whole lumbar spine,and plays an important role in anatomical research,biomechanical research,and the occurrence and development of diseases.This combination of technologies can simulate pathological processes such as vertebral loading,intervertebral disc degeneration and ligament ossification in three-dimensional space,thereby offering precise support for the elucidation of mechanical mechanisms,assessment of risk and design of surgical plan.This paper systematically reviewed the advances of finite element analysis based on multimodal image fusion in different anatomical units of the whole lumbar spine through literature collection and collation,and analyzed its key problems in model construction,material property assignment,validation methods and clinical transformation.The synergy of finite element analysis and multimodal image fusion provides clinicians with more basis for the diagnosis and treatment of lumbar spine diseases,and has broad application prospects.

Objective To explore the application value of MRI diaphragmatic navigation technology combined with three dimensional liver acquisition with volume acceleration-flexible(3D LAVA-FLEX)sequence in abdominal enhanced imaging of infants and young children.Methods A retrospective analysis was conducted on imaging data of 84 infants and young children who underwent abdominal enhanced MRI examination in our hospital between January 2021 and December 2023.All 84 infants and young children initially underwent conventional dynamic contrast-enhanced 3D LAVA-FLEX sequence scanning;the delayed phase images obtained were included in the dynamic enhancement group.Subsequently,diaphragmatic navigation combined with 3D LAVA-FLEX sequence examination was implemented,and the obtained images were included in the diaphragm navigation group.Subjective scoring was performed for images in both groups,while the signal to noise ratio(SNR),contrast to noise ratio(CNR),and artifact quantification(AQ)were measured and compared between the two groups.Results The respiratory motion artifacts,the clarity of liver parenchyma enhancement,the clarity of liver vascular enhancement,the clarity of spleen parenchyma enhancement and the overall image quality score in the diaphragm navigation group were higher than those in the dynamic enhancement group,and the differences were statistically significant(P<0.05).There were statistically significant differences in SNR and AQ between the two groups of images(P<0.000 1),while there was no statistically significant difference in CNR between the two groups of images(P>0.05).Conclusion Diaphragmatic navigation technology combined with 3D LAVA-FLEX sequence imaging can improve the image quality of abdominal MRI enhanced imaging in infants and young children,and provide a reference for clinical diagnosis and treatment.

Multimodal image fusion technique is a key technology that combines a variety of medical imaging methods to obtain compre-hensive diagnostic information,which has been widely used in clinical disease research.Finite element analysis is essentially a numerical method for solving differential equations,which simulates various physiological and pathological scenarios through combining with multimodal image fusion technique.It has been applied to many medical fields such as the whole lumbar spine,and plays an important role in anatomical research,biomechanical research,and the occurrence and development of diseases.This combination of technologies can simulate pathological processes such as vertebral loading,intervertebral disc degeneration and ligament ossification in three-dimensional space,thereby offering precise support for the elucidation of mechanical mechanisms,assessment of risk and design of surgical plan.This paper systematically reviewed the advances of finite element analysis based on multimodal image fusion in different anatomical units of the whole lumbar spine through literature collection and collation,and analyzed its key problems in model construction,material property assignment,validation methods and clinical transformation.The synergy of finite element analysis and multimodal image fusion provides clinicians with more basis for the diagnosis and treatment of lumbar spine diseases,and has broad application prospects.

Objective To explore the application value of MRI diaphragmatic navigation technology combined with three dimensional liver acquisition with volume acceleration-flexible(3D LAVA-FLEX)sequence in abdominal enhanced imaging of infants and young children.Methods A retrospective analysis was conducted on imaging data of 84 infants and young children who underwent abdominal enhanced MRI examination in our hospital between January 2021 and December 2023.All 84 infants and young children initially underwent conventional dynamic contrast-enhanced 3D LAVA-FLEX sequence scanning;the delayed phase images obtained were included in the dynamic enhancement group.Subsequently,diaphragmatic navigation combined with 3D LAVA-FLEX sequence examination was implemented,and the obtained images were included in the diaphragm navigation group.Subjective scoring was performed for images in both groups,while the signal to noise ratio(SNR),contrast to noise ratio(CNR),and artifact quantification(AQ)were measured and compared between the two groups.Results The respiratory motion artifacts,the clarity of liver parenchyma enhancement,the clarity of liver vascular enhancement,the clarity of spleen parenchyma enhancement and the overall image quality score in the diaphragm navigation group were higher than those in the dynamic enhancement group,and the differences were statistically significant(P<0.05).There were statistically significant differences in SNR and AQ between the two groups of images(P<0.000 1),while there was no statistically significant difference in CNR between the two groups of images(P>0.05).Conclusion Diaphragmatic navigation technology combined with 3D LAVA-FLEX sequence imaging can improve the image quality of abdominal MRI enhanced imaging in infants and young children,and provide a reference for clinical diagnosis and treatment.

Objective To investigate the status of population dynamics and distribution changes of Aedes aegypti in Guangdong Province.Methods Continuous monitoring was conducted from May 2018 to July 2024 in Wushi Town and Qishui Town,Leizhou City,Zhanjiang City,Guangdong Province.Additionally,a survey of the distribution of Ae.aegypti along the Leizhou Peninsula coast was carried out.Results The density of Ae.aegypti in Zhanjiang showed a gradual decline from 2018 to 2024.The last detection of adult Ae.aegypti in Wushi Town was in September 2021,and the last larva was found in October 2023.No Ae.aegypti was detected in Qishui Town during surveys from 2021 to 2024.A survey of 18 coastal villages in the Leizhou Peninsula revealed no detections of Ae.aegypti.Conclusions This study provides a basis for understanding the distribution and population density fluctuations of Ae.aegypti,assessing its invasion risk,and scientifically conducting relevant prevention and control efforts.

BACKGROUND: Medical informatics accumulated vast amounts of data for clinical diagnosis and treatment. However, limited access to follow-up data and the difficulty in integrating data across diverse platforms continue to pose significant barriers to clinical research progress. In response, our research team has embarked on the development of a specialized clinical research database for cardiology, thereby establishing a comprehensive digital platform that facilitates both clinical decision-making and research endeavors. METHODS: The database incorporated actual clinical data from patients who received treatment at the Cardiovascular Medicine Department of Chinese PLA General Hospital from 2012 to 2021. It included comprehensive data on patients' basic information, medical history, non-invasive imaging studies, laboratory test results, as well as peri-procedural information related to interventional surgeries, extracted from the Hospital Information System. Additionally, an innovative artificial intelligence (AI)-powered interactive follow-up system had been developed, ensuring that nearly all myocardial infarction patients received at least one post-discharge follow-up, thereby achieving comprehensive data management throughout the entire care continuum for high-risk patients. RESULTS: This database integrates extensive cross-sectional and longitudinal patient data, with a focus on higher-risk acute coronary syndrome patients. It achieves the integration of structured and unstructured clinical data, while innovatively incorporating AI and automatic speech recognition technologies to enhance data integration and workflow efficiency. It creates a comprehensive patient view, thereby improving diagnostic and follow-up quality, and provides high-quality data to support clinical research. Despite limitations in unstructured data standardization and biological sample integrity, the database's development is accompanied by ongoing optimization efforts. CONCLUSION The cardiovascular specialty clinical database is a comprehensive digital archive integrating clinical treatment and research, which facilitates the digital and intelligent transformation of clinical diagnosis and treatment processes. It supports clinical decision-making and offers data support and potential research directions for the specialized management of cardiovascular diseases.

Ischemic stroke (IS) is a globally life-threatening disease. Presently, few therapeutic medicines are available for treating IS, and rt-PA is the only drug approved by the US Food and Drug Administration (FDA) in the US. In fact, many agents showing excellent neuroprotection but no blood flow-improving activity in animals have not achieved ideal clinical efficacy, while thrombolytic drugs only improving blood flow without neuroprotection have limited their wider application. To address these challenges and meet the huge unmet clinical need, we have designed and identified a novel compound AAPB with dual effects of neuroprotection and cerebral blood flow improvement. AAPB significantly reduced cerebral infarction and neural function deficit in tMCAO rats, pMCAO rats, and IS rhesus monkeys, as well as displayed exceptional safety profiles and excellent pharmacokinetic properties in rats and dogs. AAPB has now entered phase I of clinical trials fighting IS in China.

Tailored lipid nanoparticles (LNPs)-mediated small interfering RNA (siRNA) nanomedicines show promise in treating liver disease, such as acute liver injury (ALI) and non-alcoholic steatohepatitis (NASH). However, constructing LNPs that address biosafety concerns, ensure efficient delivery, and target specific hepatic subcellular fractions has been challenging. To evade above obstacles, we develop three novel self-degradable "gemini-like" ionizable lipids (SS-MA, SS-DC, SS-MH) by incorporating disulfide bonds and modifying the length of ester bond and tertiary amino head. Our findings reveal that the disulfide-bond-bridged LNPs exhibit reduction-responsive drug release, improving both biosafety and siRNA delivery efficiency. Furthermore, the distance of ester bond and tertiary amino head significantly influences the LNPs' pK _a, thereby affecting endosomal escape, hemolytic efficiency, absorption capacity of ApoE, uptake efficiency of hepatocytes and liver accumulation. We also develop the modified-mannose LNPs (M-LNP) to target liver macrophages specifically. The optimized M-MH_LNP@TNFα exhibits potential in preventing ALI by decreasing tumor necrosis factor α (TNFα) levels in the macrophages, while MH_LNP@DGAT2 could treat NASH by selectively degrading diacylglycerol O-acyltransferase 2 (DGAT2) in the hepatocytes. Our findings provide new insights into developing novel highly effective and low-toxic "gemini-like" ionizable lipids for constructing LNPs, potentially achieving more effective treatment for hepatic diseases.