Objective To develop a deep learning model based on fundus retinal images to improve the detection rate of mild cognitive impairment(MCI)in patients with coronary heart disease,achieve early intervention and improve prognosis.Methods The study was a single-center cross-sectional study that retrospectively included patients diagnosed with coronary heart disease(CHD)by coronary angiography(≥50％ stenosis of at least one coronary vessel)from Beijing Anzhen Hospital between November 2021 and December 2022.The whole data set was randomly divided into the training set and the testing set according to the ratio of 8∶2 for model development.After that,the patient data of the same center from January 2023 to April 2023 were included in the time verification method to verify the model.The diagnostic criteria for MCI were MMSE＜27 or MoCA＜26.Four kinds of convolutional neural network(CNN)architectures were used to train fundus images,and a comprehensive vision model of MCI detection was established through model integration.The area under the curve(AUC),sensitivity and specificity of the receiver operating curve(ROC)were used to evaluate the performance of the AI model.Results We collected 5 880 eligible fundus images from 3 368 CHD patients.Based on the results of the MMSE scale,the algorithm was labeled,including 2 898 males and 527 MCI patients.The AUC of the deep learning model in the test group is 0.733(95％CI 0.688-0.778),and the sensitivity of the algorithm in the test group is 0.577(95％CI 0.528-0.625)by using the operating point with the maximum sum of sensitivity and specificity.With a specificity of 0.758(95％CI 0.714-0.802),corresponding to a validated AUC of 0.710(95％CI 0.601-0.818).Based on the results of the MoCA scale,the algorithm labels 2 437 males and 1 626 MCI patients.The AUC of the deep learning model in the test group was 0.702(95％CI 0.671-0.733).The operating point with the maximum sum of sensitivity and specificity was selected,and the sensitivity of the algorithm was 0.749(95％CI 0.719-0.778)and the specificity was 0.561(95％CI 0.527-0.595),corresponding to the AUC value of the verification group was 0.674(95％CI 0.622-0.726).Conclusions The deep learning algorithm model based on fundus images has good diagnostic performance,and may be used as a new non-invasive,convenient and rapid screening method for MCI in CHD population.

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.

Objective To develop a deep learning model based on fundus retinal images to improve the detection rate of mild cognitive impairment(MCI)in patients with coronary heart disease,achieve early intervention and improve prognosis.Methods The study was a single-center cross-sectional study that retrospectively included patients diagnosed with coronary heart disease(CHD)by coronary angiography(≥50％ stenosis of at least one coronary vessel)from Beijing Anzhen Hospital between November 2021 and December 2022.The whole data set was randomly divided into the training set and the testing set according to the ratio of 8∶2 for model development.After that,the patient data of the same center from January 2023 to April 2023 were included in the time verification method to verify the model.The diagnostic criteria for MCI were MMSE＜27 or MoCA＜26.Four kinds of convolutional neural network(CNN)architectures were used to train fundus images,and a comprehensive vision model of MCI detection was established through model integration.The area under the curve(AUC),sensitivity and specificity of the receiver operating curve(ROC)were used to evaluate the performance of the AI model.Results We collected 5 880 eligible fundus images from 3 368 CHD patients.Based on the results of the MMSE scale,the algorithm was labeled,including 2 898 males and 527 MCI patients.The AUC of the deep learning model in the test group is 0.733(95％CI 0.688-0.778),and the sensitivity of the algorithm in the test group is 0.577(95％CI 0.528-0.625)by using the operating point with the maximum sum of sensitivity and specificity.With a specificity of 0.758(95％CI 0.714-0.802),corresponding to a validated AUC of 0.710(95％CI 0.601-0.818).Based on the results of the MoCA scale,the algorithm labels 2 437 males and 1 626 MCI patients.The AUC of the deep learning model in the test group was 0.702(95％CI 0.671-0.733).The operating point with the maximum sum of sensitivity and specificity was selected,and the sensitivity of the algorithm was 0.749(95％CI 0.719-0.778)and the specificity was 0.561(95％CI 0.527-0.595),corresponding to the AUC value of the verification group was 0.674(95％CI 0.622-0.726).Conclusions The deep learning algorithm model based on fundus images has good diagnostic performance,and may be used as a new non-invasive,convenient and rapid screening method for MCI in CHD population.

Objective:To observe the genetic variation of SH2B3 in patients with myeloid neoplasms.Methods:The results of targeted DNA sequencing associated with myeloid neoplasms in the Department of Hematology,Xuanwu Hospital,Capital Medical University from November 2017 to November 2022 were retrospectively analyzed,and the patients with SH2B3 gene mutations were identified.The demographic and clinical data of these patients were collected,and characteristics of SH2B3 gene mutation,co-mutated genes and their correlations with diseases were analyzed.Results:The sequencing results were obtained from 1 005 patients,in which 19 patients were detected with SH2B3 gene mutation,including 18 missense mutations(94.74％),1 nonsense mutation(5.26％),and 10 patients with co-mutated genes(52.63％).Variant allele frequency(VAF)ranged from 0.03 to 0.66.The highest frequency mutation was p.Ile568Thr(5/19,26.32％),with an average VAF of 0.49,involving 1 case of MDS/MPN-RS(with SF3B1 mutation),1 case of MDS-U(with SF3B1 mutation),1 case of aplastic anemia with PNH clone(with PIGA and KMT2A mutations),2 cases of MDS-MLD(1 case with SETBP1 mutation).The other mutations included p.Ala567Thr in 2 cases(10.53％),p.Arg566Trp,p.Glu533Lys,p.Met437Arg,p.Arg425Cys,p.Glu314Lys,p.Arg308*,p.Gln294Glu,p.Arg282Gln,p.Arg175Gln,p.Gly86Cys,p.His55Asn and p.Gln54Pro in 1 case each.Conclusion:A wide distribution of genetic mutation sites and low recurrence of SH2B3 is observed in myeloid neoplasms,among of them,p.Ile568Thr mutation is detected with a higher incidence and often coexists with characteristic mutations of other diseases.

The first patient,a 10-year-old girl,presented with pancytopenia and recurrent epistaxis,along with a history of repeated upper respiratory infections,café-au-lait spots,and microcephaly.Genetic testing revealed compound heterozygous mutations in the DNA ligase Ⅳ(LIG4)gene,leading to a diagnosis of LIG4 syndrome.The second patient,a 6-year-old girl,was seen for persistent thrombocytopenia lasting over two years and was noted to have short stature,hyperpigmented skin,and hand malformations.She had a positive result from chromosome breakage test.She was diagnosed with Fanconi anemia complementation group A.Despite similar clinical presentations,the two children were diagnosed with different disorders,suggesting that children with hemocytopenia and malformations should not only be evaluated for hematological diseases but also be screened for other potential underlying conditions such as immune system disorders.[Chinese Journal of Contemporary Pediatrics,2024,26(4):410-4131

Objective To investigate the risk factors for bronchopulmonary dysplasia(BPD)in twin preterm infants with a gestational age of<34 weeks,and to provide a basis for early identification of BPD in twin preterm infants in clinical practice.Methods A retrospective analysis was performed for the twin preterm infants with a gestational age of<34 weeks who were admitted to 22 hospitals nationwide from January 2018 to December 2020.According to their conditions,they were divided into group A(both twins had BPD),group B(only one twin had BPD),and group C(neither twin had BPD).The risk factors for BPD in twin preterm infants were analyzed.Further analysis was conducted on group B to investigate the postnatal risk factors for BPD within twins.Results A total of 904 pairs of twins with a gestational age of<34 weeks were included in this study.The multivariate logistic regression analysis showed that compared with group C,birth weight discordance of>25%between the twins was an independent risk factor for BPD in one of the twins(OR=3.370,95%CI:1.500-7.568,P<0.05),and high gestational age at birth was a protective factor against BPD(P<0.05).The conditional logistic regression analysis of group B showed that small-for-gestational-age(SGA)birth was an independent risk factor for BPD in individual twins(OR=5.017,95%CI:1.040-24.190,P<0.05).Conclusions The development of BPD in twin preterm infants is associated with gestational age,birth weight discordance between the twins,and SGA birth.

Aim To screen and study the effects of Tao Hong Si Wu decoction(THSWD)-mediated treat-ment on circular RNA(circRNA)expression profiles in rats with middle cerebral artery occlusion(MCAO),and investigate the possible roles and molecular mecha-nisms of THSWD.Methods Next-generation RNA sequencing was conducted to identify circRNA expres-sion profiles in MCAO rats after treatment with THSWD and compared with the MCAO model group and control group.Bioinformatics analysis was performed to predict the potential target microRNAs and mRNAs.Gene On-tology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway analyses for the potential target mRNAs were applied to explore the potential roles of differentially expressed circRNAs.RT-qPCR was performed to verify circRNAs with significant differences in expression.Results We identified 87 significantly differentially expressed circRNAs between the MCAO group versus the control group,and 86 sig-nificantly differentially expressed circRNAs between the MCAO group versus the THSWD group.respective-ly.Among them,17 circRNAs induced by the MCAO model were reversed via treatment with THSWD.To demonstrate the roles of mRNAs targeted by DECs,the GO and KEGG databases were used.Further analysis revealed that five circRNAs may play important roles in the development of MCAO.Conclusions The com-prehensive expression profile of circRNAs in rats with middle cerebral artery occlusion after THSWD treat-ment is determined for the first time,suggesting that the therapeutic effect of THSWD on MCAO may be a-chieved by regulating the expression of circRNAs.

Objective To understand the current situation of human brain donation in Hebei Province by analyzing the basic information of Human Brain Bank samples of Hebei Medical University in order to provide basic data support for subsequent scientific research.Methods The samples collected from the Human Brain Bank of Hebei Medical University were analyzed(from December 2019 to February 2024),including gender,age,cause of death,as well as quality control data such as postmortem delay time,pH value of cerebrospinal fluid and and RNA integrity number and result of neuropathological diagnosis.Results Until February 2024,30 human brain samples were collected and stored in the Human Brain Bank of Hebei Medical University,with a male to female ratio of 9∶1.Donors over 70 years old accounted for 53％.Cardiovascular and cerebrovascular diseases(36.67％)and nervous system diseases(23.33％)accounted for a high proportion of the death causes.The location of brain tissue donors in Shijiazhuang accounted for 90％donations,and the others were from outside the city.The postmortem delay time was relatively short,90％within 12 hours and 10％more than 12 hours.69.23％of the brain samples had RNA integrity values greater than 6.Cerebrospinal fluid pH values ranged from 5.8 to 7.5,with an average value of 6.60±0.45.Brain weights ranged from 906-1496 g,with an average value of(1210.78±197.84)g.Three apolipoprotein E(APOE)alleles were detected including five genotypes(ε2/ε3,ε2/ε4,ε3/ε3,ε3/ε4,ε4/ε4).Eleven staining methods related to neuropathological diagnosis had been established and used.A total of 12 cases were diagnosed as neurodegenerative diseases(including Alzheimer's disease,Parkinson's disease,multiple system atrophy,corticobasal degeneration and progressive supranuclear palsy,etc.),accounting for 40％donated brains.The comorbidity rate of samples over 80 years old was 100％.Conclusion The summary and analyses of the data of brain donors in the Human Brain Bank of Hebei Medical University can reflect the current situation of the construction and operation of the brain bank in Hebei Province,and it can also be more targeted to understand and identify potential donors.Our information can provide reference for the construction of brain bank and provides more reliable materials and data support for scientific research.

Aim To screen and study the expression of long non-coding RNA (IncRNA) in rats with middle cerebral artery occlusion (MCAO) with MCAO treated with Tao Hong Si Wu decoction (THSWD) and determine the possible molecular mechanism of THSWD in treating MCAO rats. Methods Three cerebral hemisphere tissue were obtained from the control group, MCAO group and MCAO + THSWD group. RNA sequencing technology was used to identify IncRNA gene expression in the three groups. THSWD-regulated IncRNA genes were identified, and then a THSWD-regu-lated IncRNA-mRNA network was constructed. MCODE plug-in units were used to identify the modules of IncRNA-mRNA networks. Gene ontology (GO) and kyoto encyclopedia of genes and genomes (KEGG) were used to analyze the enriched biological functions and signaling pathways. Cis- and trans-regulatory genes for THSWD-regulated IncRNAs were identified. Reverse transcription real-time quantitative pol-ymerase chain reaction (RT-qPCR) was used to verify IncRNAs. Molecular docking was used to identify IncRNA-mRNA network targets and pathway-associated proteins. Results In MCAO rats, THSWD regulated a total of 302 IncRNAs. Bioinformatics analysis suggested that some core IncRNAs might play an important role in the treatment of MCAO rats with THSWD, and we further found that THSWD might also treat MCAO rats through multiple pathways such as IncRNA-mRNA network and network-enriched complement and coagulation cascades. The results of molecular docking showed that the active compounds gallic acid and a-mygdalin of THSWD had a certain binding ability to protein targets. Conclusions THSWD can protect the brain injury of MCAO rats through IncRNA, which may provide new insights for the treatment of ischemic stroke with THSWD.