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 explore current status and potential subtypes of elderly stroke patients' medication literacy among,and to analyze related influencing factors of different subtypes.Methods A total of 285 elderly stroke patients admitted in the First Affiliated Hospital of Zhengzhou University from November 2023 to June 2024 were selected as subjects.General Information questionnaire,medication literacy scale for elderly patients with chronic diseases,and perceived social support scale were conducted.Latent profile analysis(LPA)of elderly stroke patients' medication literacy was conducted,and Logistic regression analysis was used to explore influencing factors of different profiles.Results Score of medication literacy scale for elderly stroke patients was(48.26±12.51)points.Medication literacy among elderly stroke patients can be divided into 3 profiles,namely proactive-high literacy type(51.9％),balanced-medium literacy type(34.0％),and dependent-low literacy type(14.1％).Logistic regression analysis showed that recent medication types,current place of residence,educational level,diabetes,and social support were the influencing factors of elderly stroke patients' medication literacy(P＜0.05).Conclusion The level of medication literacy among elderly stroke patients is medium,which is characterized by 3 categories.Medical staffs targeted intervention should be adopted according to different category characteristics,so as to accurately meet their nursing needs,finally improve the level of elderly stroke patients' medication literacy.

Objective:To investigate the correlation of intracranial arterial calcification (IAC) and its different subtypes with the severity of white matter hyperintensities (WMHs) in patients with cerebral small vessel disease (CSVD).Methods:Consecutive CSVD patients admitted to the Department of Neurology, the First Affiliated Hospital of Zhengzhou University from March 2018 to March 2022 were enrolled. Baseline demographic, laboratory, and imaging data were collected. Based on a developed and validated IAC grading scale using head CT, IAC was classified into intimal and medial types, and further categorized as focal or diffuse based on the extent of involvement. The severity of WMHs on magnetic resonance imaging was assessed using the Fazekas Scale, with patients divided into those with moderate-to-severe (total score>2) and non-moderate-to-severe WMHs (total score≤2). Subgroups were stratified based on baseline characteristics (patients′ sex, age, hypertension history, stroke history, diabetes, coronary heart disease, hyperlipidemia, smoking, and alcohol consumption). Multivariate Logistic regression was used to analyze the correlation between IAC′s subtypes and the severity of WMHs, with forest plots illustrating the interaction between medial IAC and subgroup variables.Results:A total of 490 patients with CSVD who met the inclusion and exclusion criteria were ultimately included, with a age of (60.88±10.99) years, including 162 females (33.1%). Moderate-to-severe WMHs were present in 245 patients (50.0%). Among the 490 CSVD patients, 395 (80.6%) had IAC, including 335 (68.4%) with intimal IAC and 207 (42.2%) with medial IAC. Diffuse IAC was observed in 126 patients (25.7%), all of whom had medial IAC. Intracranial arterial stenosis was present in 271 patients (55.3%). Multivariate Logistic regression showed that IAC ( OR=2.073, 95% CI 1.142-3.761, P=0.016) was significantly associated with moderate-to-severe WMHs and medial IAC ( OR=3.230, 95% CI 1.800-5.797, P<0.001) and advanced age ( OR=1.046, 95% CI 1.019-1.074, P=0.001) were significantly associated with moderate-to-severe WMHs. Subgroup analysis revealed medial IAC had no significant interaction with patients′ gender, age, hypertension, diabetes, coronary heart disease, hyperlipidemia, alcohol or smoking consumption except for stroke history. Conclusion:In the CSVD patients, IAC, especially medial IAC, is significantly associated with the severity of WMHs.

This study was aimed at developing an in vitro fluorescent substrate assay for the activity of leucyl aminopeptid-ase(LAP)from Echinococcus multilocularis and comparing it with the chemical chromogenic substrate enzyme activity assay.Through the establishment of reaction conditions for the fluorescent substrate-based in vitro enzyme activity assay,we com-pared the differences between the fluorescent substrate L-Leucine-7-amido-4-methylocoumarin(Leu-AMC)and the chemical chromogenic substrate L-Leucine-4-nitroanilide(Leu-pNA)through molecular docking,inhibition rates,and precision measures.Molecular docking revealed that the fluorescent substrate Leu-AMC had higher affinity for the protein than the chemical chromogenic substrate Leu-pNA.Through analysis of the effects of varying reaction conditions on fluorescence intensi-ty,we optimized the fluorescent substrate enzyme activity assay to demonstrate favorable performance at a reaction temperature of 37℃,a pH of 9.0,a protein concentration of 800 nmol/L,and a reaction duration of 60 minutes.Leu-AMC exhibited significant and distinct responses at a 5 μmol/L substrate concentration,under varying substrate conditions.The fluo-rescent substrate assay demonstrated more significant intergroup differences than the chemical chromogenic substrate assay when various inhibitors were added.This study established a fluorescence-based enzyme activity assay for leucyl aminopeptidase from Echinococcus multilocularis by using Leu-AMC as the substrate;this method demonstrated a more significant intergroup difference and sensitivity than the chemical chromogenic substrate assay.

This study was aimed at developing an in vitro fluorescent substrate assay for the activity of leucyl aminopeptid-ase(LAP)from Echinococcus multilocularis and comparing it with the chemical chromogenic substrate enzyme activity assay.Through the establishment of reaction conditions for the fluorescent substrate-based in vitro enzyme activity assay,we com-pared the differences between the fluorescent substrate L-Leucine-7-amido-4-methylocoumarin(Leu-AMC)and the chemical chromogenic substrate L-Leucine-4-nitroanilide(Leu-pNA)through molecular docking,inhibition rates,and precision measures.Molecular docking revealed that the fluorescent substrate Leu-AMC had higher affinity for the protein than the chemical chromogenic substrate Leu-pNA.Through analysis of the effects of varying reaction conditions on fluorescence intensi-ty,we optimized the fluorescent substrate enzyme activity assay to demonstrate favorable performance at a reaction temperature of 37℃,a pH of 9.0,a protein concentration of 800 nmol/L,and a reaction duration of 60 minutes.Leu-AMC exhibited significant and distinct responses at a 5 μmol/L substrate concentration,under varying substrate conditions.The fluo-rescent substrate assay demonstrated more significant intergroup differences than the chemical chromogenic substrate assay when various inhibitors were added.This study established a fluorescence-based enzyme activity assay for leucyl aminopeptidase from Echinococcus multilocularis by using Leu-AMC as the substrate;this method demonstrated a more significant intergroup difference and sensitivity than the chemical chromogenic substrate assay.

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 explore current status and potential subtypes of elderly stroke patients' medication literacy among,and to analyze related influencing factors of different subtypes.Methods A total of 285 elderly stroke patients admitted in the First Affiliated Hospital of Zhengzhou University from November 2023 to June 2024 were selected as subjects.General Information questionnaire,medication literacy scale for elderly patients with chronic diseases,and perceived social support scale were conducted.Latent profile analysis(LPA)of elderly stroke patients' medication literacy was conducted,and Logistic regression analysis was used to explore influencing factors of different profiles.Results Score of medication literacy scale for elderly stroke patients was(48.26±12.51)points.Medication literacy among elderly stroke patients can be divided into 3 profiles,namely proactive-high literacy type(51.9％),balanced-medium literacy type(34.0％),and dependent-low literacy type(14.1％).Logistic regression analysis showed that recent medication types,current place of residence,educational level,diabetes,and social support were the influencing factors of elderly stroke patients' medication literacy(P＜0.05).Conclusion The level of medication literacy among elderly stroke patients is medium,which is characterized by 3 categories.Medical staffs targeted intervention should be adopted according to different category characteristics,so as to accurately meet their nursing needs,finally improve the level of elderly stroke patients' medication literacy.

Objective:To investigate the correlation of intracranial arterial calcification (IAC) and its different subtypes with the severity of white matter hyperintensities (WMHs) in patients with cerebral small vessel disease (CSVD).Methods:Consecutive CSVD patients admitted to the Department of Neurology, the First Affiliated Hospital of Zhengzhou University from March 2018 to March 2022 were enrolled. Baseline demographic, laboratory, and imaging data were collected. Based on a developed and validated IAC grading scale using head CT, IAC was classified into intimal and medial types, and further categorized as focal or diffuse based on the extent of involvement. The severity of WMHs on magnetic resonance imaging was assessed using the Fazekas Scale, with patients divided into those with moderate-to-severe (total score>2) and non-moderate-to-severe WMHs (total score≤2). Subgroups were stratified based on baseline characteristics (patients′ sex, age, hypertension history, stroke history, diabetes, coronary heart disease, hyperlipidemia, smoking, and alcohol consumption). Multivariate Logistic regression was used to analyze the correlation between IAC′s subtypes and the severity of WMHs, with forest plots illustrating the interaction between medial IAC and subgroup variables.Results:A total of 490 patients with CSVD who met the inclusion and exclusion criteria were ultimately included, with a age of (60.88±10.99) years, including 162 females (33.1%). Moderate-to-severe WMHs were present in 245 patients (50.0%). Among the 490 CSVD patients, 395 (80.6%) had IAC, including 335 (68.4%) with intimal IAC and 207 (42.2%) with medial IAC. Diffuse IAC was observed in 126 patients (25.7%), all of whom had medial IAC. Intracranial arterial stenosis was present in 271 patients (55.3%). Multivariate Logistic regression showed that IAC ( OR=2.073, 95% CI 1.142-3.761, P=0.016) was significantly associated with moderate-to-severe WMHs and medial IAC ( OR=3.230, 95% CI 1.800-5.797, P<0.001) and advanced age ( OR=1.046, 95% CI 1.019-1.074, P=0.001) were significantly associated with moderate-to-severe WMHs. Subgroup analysis revealed medial IAC had no significant interaction with patients′ gender, age, hypertension, diabetes, coronary heart disease, hyperlipidemia, alcohol or smoking consumption except for stroke history. Conclusion:In the CSVD patients, IAC, especially medial IAC, is significantly associated with the severity of WMHs.

Objective To explore the toxicity of Polygonum multiflorum alcohol extract on 3D hepatospheres.Methods Variations in culture conditions and cell ratios were implemented,followed by the assessment of cell sphere diameter,density,and roundness,aiming to explore the optimal culture conditions.The 3D hepatocyte spheres were divided into control group and experimental-L,-M,-H groups.The experimental-L,-M,-H groups were treated with 0.25,1.00 and 2.50 mg·mL-1 Polygounm multiforum alcohol extract,and the control group was given the same amount of culture medium.The cell viability of the cell spheroids was tested by CellTiter-Glo reagent,the expression level of liver function related genes was detected by fluorescent quantitative polymerase chain reaction(RT-qRCR).The toxicity of cell spheres was detected by double fluorescent staining of living and dead cells.Results The ideal culture condition of cell sphere was 500 cells per micropore,and the cell ratio was HepG2-Huvec-LX-2=8∶1∶1.It displayed the values of 0.91±0.07 for circularity,0.91±0.02 for firmness,1.12±0.14 for aspect ratio,and(170.97±14.79)μm for diameter.On the 3rd,7th,10th and 14th days,the expression levels of albumin(ALB)mRNA were 1.00±0.02,0.96±0.02,0.54±0.07,0.52±0.07,and the expression levels of cytochrome P450 1A2(CYP1A2)mRNA were 1.00±0.10,2.15±0.16,2.45±0.33,1.30±0.03,respectively.The expression levels of multidrug resistance protein 2(MPR2)in the control group and the experimental-L,-M,-H groups were 1.00±0.31,1.38±0.24,1.48±0.06 and 1.90±0.08,respectively;spheroid viability were(98.19±0.49)％,(88.53±0.90)％,(71.60±2.91)％and(56.65±5.41)％.There were statistically significant differences in the above indexes between the experimental-L,-M,-H groups and the control group(all P＜0.05).Conclusion The established hepatocyte sphere co-culture model showed varying degrees of expression of phase Ⅰ/Ⅱ drug metabolism enzymes,transporters,and liver cell specific marker molecule albumin and can be used to evaluate the toxicity of multiflorum multiflorum,which provides further reference for the clinical application of multiflorum multiflorum.

OBJECTIVE: This study was aimed at investigating the carrier rate of, and molecular variation in, α- and β-globin gene mutations in Hunan Province. METHODS: We recruited 25,946 individuals attending premarital screening from 42 districts and counties in all 14 cities of Hunan Province. Hematological screening was performed, and molecular parameters were assessed. RESULTS: The overall carrier rate of thalassemia was 7.1%, including 4.83% for α-thalassemia, 2.15% for β-thalassemia, and 0.12% for both α- and β-thalassemia. The highest carrier rate of thalassemia was in Yongzhou (14.57%). The most abundant genotype of α-thalassemia and β-thalassemia was -α ^3.7/αα (50.23%) and β ^IVS-II-654/β ^N (28.23%), respectively. Four α-globin mutations [CD108 (ACC>AAC), CAP +29 (G>C), Hb Agrinio and Hb Cervantes] and six β-globin mutations [CAP +8 (C>T), IVS-II-848 (C>T), -56 (G>C), beta nt-77 (G>C), codon 20/21 (-TGGA) and Hb Knossos] had not previously been identified in China. Furthermore, this study provides the first report of the carrier rates of abnormal hemoglobin variants and α-globin triplication in Hunan Province, which were 0.49% and 1.99%, respectively. CONCLUSION Our study demonstrates the high complexity and diversity of thalassemia gene mutations in the Hunan population. The results should facilitate genetic counselling and the prevention of severe thalassemia in this region.
Humans ; beta-Thalassemia/genetics* ; alpha-Thalassemia/genetics* ; Hemoglobinopathies/genetics* ; China/epidemiology* ; High-Throughput Nucleotide Sequencing