OBJECTIVE: To evaluate the safety and effectiveness of robot-assisted percutaneous coronary intervention (R-PCI) compared to traditional manual percutaneous coronary intervention (M-PCI). METHODS: This prospective, multicenter, randomized controlled, non-inferior clinical trial enrolled patients with coronary heart disease who met the inclusion criteria and had indications for elective percutaneous coronary intervention. Participants were randomly assigned to either the R-PCI group or the M-PCI group. Primary endpoints were clinical and technical success rates. Clinical success was defined as visually estimated residual post-percutaneous coronary intervention stenosis < 30% with no 30-day major adverse cardiac events. Technical success in the R-PCI group was defined as successful completion of percutaneous coronary intervention using the ETcath200 robot-assisted system, without conversion to M-PCI in the event of a guidewire or balloon/stent catheter that was unable to cross the vessel or was poorly supported by the catheter. Secondary endpoints included total procedure time, percutaneous coronary intervention procedure time, fluoroscopy time, contrast volume, operator radiation exposure, air kerma, and dose-area product. RESULTS: The trial enrolled 152 patients (R-PCI: 73 patients, M-PCI: 79 patients). Lesions were predominantly B2/C type (73.6%). Both groups achieved 100% clinical success rate. No major adverse cardiac events occurred during the 30-day follow-up. The R-PCI group had a technical success rate of 100%. The R-PCI group had longer total procedure and fluoroscopy times, but lower operator radiation exposure. The percutaneous coronary intervention procedure time, contrast volume, air kerma, and dose-area product were similar between the two groups. CONCLUSIONS For certain complex lesions, performing percutaneous coronary intervention using the ETcath200 robot-assisted system is safe and effective and does not result in conversion to M-PCI.

AIM To establish a UPLC-ESI-MS/MS method for analyzing the toxic material basis of 95％ethanol cold soaked ultrasonic extract(EC),95％ethanol heated reflux extract(EH)and water decoction extract(WD)from Dryopteris crassirhizoma Nakai.METHODS The analysis was performed on a 25 ℃ thermostatic agilent ZORBAX RRHD StableBond C18 column(2.1 mm×150 mm,1.8 μm),with the mobile phase comprising of methanol-0.2％formic acid flowing at 0.30 mL/min,and heated electrospray ion source was adopted in positive and negative ion scanning.Compounds were identified by Compound Discover 3.3 software combined with the database and related literature,and the main differential components were screened by Heatmap cluster analysis and partial least squares discriminant analysis.RESULTS 72 compounds were identified(22 phloroglucinols,19 flavonoids,8 phenylpropanoids,6 terpenoids and 17 other components).The main toxic differential components were phloroglucinols such as flavaspidic acid AB,didemethylpseudoaspidin AA and filixic acid PBP,flavonoids such as(-)-epicatechin,(-)-epigallocatechin,cianidanol,and other compounds such as indole-3-carboxaldehyde.CONCLUSION This method can rapidly,effectively and comprehensively characterize the main chemical composition of D.crassirhizoma,and provide a reference for the study of its pharmacological mechanism.

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.

AIM To establish a UPLC-ESI-MS/MS method for analyzing the toxic material basis of 95％ethanol cold soaked ultrasonic extract(EC),95％ethanol heated reflux extract(EH)and water decoction extract(WD)from Dryopteris crassirhizoma Nakai.METHODS The analysis was performed on a 25 ℃ thermostatic agilent ZORBAX RRHD StableBond C18 column(2.1 mm×150 mm,1.8 μm),with the mobile phase comprising of methanol-0.2％formic acid flowing at 0.30 mL/min,and heated electrospray ion source was adopted in positive and negative ion scanning.Compounds were identified by Compound Discover 3.3 software combined with the database and related literature,and the main differential components were screened by Heatmap cluster analysis and partial least squares discriminant analysis.RESULTS 72 compounds were identified(22 phloroglucinols,19 flavonoids,8 phenylpropanoids,6 terpenoids and 17 other components).The main toxic differential components were phloroglucinols such as flavaspidic acid AB,didemethylpseudoaspidin AA and filixic acid PBP,flavonoids such as(-)-epicatechin,(-)-epigallocatechin,cianidanol,and other compounds such as indole-3-carboxaldehyde.CONCLUSION This method can rapidly,effectively and comprehensively characterize the main chemical composition of D.crassirhizoma,and provide a reference for the study of its pharmacological mechanism.

As artificial intelligence technology rapidly advances, its deployment within the medical sector presents substantial ethical challenges. Consequently, it becomes crucial to create a standardized, transparent, and secure framework for processing medical data. This includes setting the ethical boundaries for medical artificial intelligence and safeguarding both patient rights and data integrity. This consensus governs every facet of medical data handling through artificial intelligence, encompassing data gathering, processing, storage, transmission, utilization, and sharing. Its purpose is to ensure the management of medical data adheres to ethical standards and legal requirements, while safeguarding patient privacy and data security. Concurrently, the principles of compliance with the law, patient privacy respect, patient interest protection, and safety and reliability are underscored. Key issues such as informed consent, data usage, intellectual property protection, conflict of interest, and benefit sharing are examined in depth. The enactment of this expert consensus is intended to foster the profound integration and sustainable advancement of artificial intelligence within the medical domain, while simultaneously ensuring that artificial intelligence adheres strictly to the relevant ethical norms and legal frameworks during the processing of medical data.
Artificial Intelligence/legislation & jurisprudence* ; Humans ; Consensus ; Computer Security/standards* ; Confidentiality/ethics* ; Informed Consent/ethics*

Objective To investigate the incidence rate,clinical characteristics,and prognosis of neonatal stroke in Shenzhen,China.Methods Led by Shenzhen Children's Hospital,the Shenzhen Neonatal Data Collaboration Network organized 21 institutions to collect 36 cases of neonatal stroke from January 2020 to December 2022.The incidence,clinical characteristics,treatment,and prognosis of neonatal stroke in Shenzhen were analyzed.Results The incidence rate of neonatal stroke in 21 hospitals from 2020 to 2022 was 1/15 137,1/6 060,and 1/7 704,respectively.Ischemic stroke accounted for 75％(27/36);boys accounted for 64％(23/36).Among the 36 neonates,31(86％)had disease onset within 3 days after birth,and 19(53％)had convulsion as the initial presentation.Cerebral MRI showed that 22 neonates(61％)had left cerebral infarction and 13(36％)had basal ganglia infarction.Magnetic resonance angiography was performed for 12 neonates,among whom 9(75％)had involvement of the middle cerebral artery.Electroencephalography was performed for 29 neonates,with sharp waves in 21 neonates(72％)and seizures in 10 neonates(34％).Symptomatic/supportive treatment varied across different hospitals.Neonatal Behavioral Neurological Assessment was performed for 12 neonates(33％,12/36),with a mean score of(32±4)points.The prognosis of 27 neonates was followed up to around 12 months of age,with 44％(12/27)of the neonates having a good prognosis.Conclusions Ischemic stroke is the main type of neonatal stroke,often with convulsions as the initial presentation,involvement of the middle cerebral artery,sharp waves on electroencephalography,and a relatively low neurodevelopment score.Symptomatic/supportive treatment is the main treatment method,and some neonates tend to have a poor prognosis.

Objective To explore the feasibility of octreotide injection for"oral administration"in children.Methods The acid resistance stability experiment was divided into experimental group(dissolve octreotide in hydrochloric acid at pH 4.0-4.5)and control group(dissolve octreotide in 0.9％NaCl at pH 7.0-7.5).BN juvenile rats were randomly assigned to the subcutaneous injection group of octreotide(12 μg·kg-1·d-1,subcutaneous injection),the oral administration group of octreotide(12 μg·kg-1·d1-1,oral administration),and the control group(0.9％NaCl)based on gender and body mass grading,with 10 rats in each group.Collect blood samples from 2 children with refractory diarrhea after subcutaneous injection and oral administration of octreotide for 1 hour,and monitor the plasma concentration.Compare the differences in plasma and gastrointestinal concentrations in rats,as well as the differences in plasma concentration in two pediatric patients.Measure the plasma concentration of octreotide using radioimmunoassay.Detection of octreotide concentration in rat intestine by immunohistochemical method.Results The concentrations of octreotide in the experimental group and control group were(810.71±1.91)and(816.55±5.60)ng·mL-1,respectively,without statistically significant difference(P＞0.05).The integrated optical density(IOD)values of octreotide in the subcutaneous injection group and oral administration group were 6.84±0.88 and 9.82±1.07;the concentrations of octreotide in peripheral blood were(26.07±12.19)and(3.53±0.76)ng·mL-1,with statistical significance(all P＜0.001).The plasma concentration of octreotide administered orally and subcutaneously in two pediatric patients were 2.52-3.30 and 22.36-31.68 ng·mL-1.Conclusion"Oral administration"of octreotide exhibits a distribution of"high gastrointestinal concentration/low plasma concentration".High gastrointestinal concentration can treat local gastrointestinal diseases in children and avoid injection pain.Oral administration of low plasma concentration is beneficial for reducing systemic adverse drug reactions in children with growth inhibition.

Objective To provide clinical practitioners with references for rational and safe usage of cyclophosphamide(CTX)by conducting an in-depth analysis of its adverse drug events(ADE)reported in clinical settings.Methods Based on the Food and Drug Administration(FDA)adverse event reporting system,the online pharmacovigilance tool OpenVigil collected ADE data of CTX from January 1,2013 to March 11,2023.The ADE data mining analysis was performed using the reporting odds ratio(ROR)and Bayesian confidence propagation neural network(BCPNN)methods.Results A total of 8 223 ADE reports met the inclusion criteria,and 422 ADE signals were obtained,involving 21 system organ classification(SOC),of which women(44.12％)accounted for a higher proportion than men(31.02％),the age distribution was mainly in the population 46-65 years old.The involved SOC mainly included infections and invasive diseases,hematologic and lymphatic system diseases,systemic diseases and various reactions at the site of administration,etc.;the ADE signals with a higher number of reports were myelosuppression,disease progression,pyrexia,febrile neutropenia,etc.A total of 18 suspected adverse drug reaction(ADR)not documented in the CTX drug insert were unearthed.Conclusion Clinical practitioners should be alert to ADE signals outside the drug insert,such as neonatal diseases and maternal exposure before pregnancy,methemoglobinemia,etc.,when using cyclophosphamide to improve the safety and effectiveness of clinical treatment.