1.Impact of wearable devices in assisting disease monitoring on heart-focused anxiety in patients with tachyarrhythmias
Yuying LI ; Xinyue DONG ; Zhiyun SHEN ; Xian ZHANG ; Caiying YANG ; Yuxuan HUANG ; Meiqiong YAN
Chinese Journal of Clinical Medicine 2026;33(3):445-451
Objective To explore the impact of wearable devices in assisting disease monitoring on heart-focused anxiety in patients with tachyarrhythmias. Methods A cross-sectional study design was conducted. 305 patients with tachyarrhythmias who attended the department of cardiology of Zhongshan Hospital, Fudan University in Shanghai from July 2025 to December 2025 were enrolled as the research subjects, and clinical data of patients were collected. Univariate analysis and multiple stepwise regression analysis were used to analyze the impact of wearable devices in assisting disease monitoring on patients’ heart-focused anxiety. Results The mean score of heart-focused anxiety in the 305 patients with tachyarrhythmias was 33.16±9.70. Among them, 104(34.10%) patients used wearable devices in assisting disease monitoring. The results of univariate analysis and multiple stepwise regression showed that the use of wearable devices in assisting disease monitoring was an influencing factor for heart-focused anxiety (P<0.05), and the patients who used wearable devices in assisting disease monitoring had a significantly lower level of heart-focused anxiety (P<0.05). Conclusions The use of wearable devices in assisting disease monitoring is associated with a lower level of heart-focused anxiety in patients with tachyarrhythmias. Medical staff can guide patients to rationally use wearable devices in assisting disease monitoring on the basis of evaluating their needs and device operation capabilities.
2.Deep learning model based on fundus images for detection of coronary artery disease with mild cognitive impairment
Yi YE ; Wei FENG ; Yao-dong DING ; Qing CHEN ; Yang ZHANG ; Li LIN ; Tong MA ; Bin WANG ; Xian-gang CHANG ; Zong-yuan GE ; Xiao-yi WANG ; Long-jun CAI ; Yong ZENG
Chinese Journal of Interventional Cardiology 2025;33(6):303-311
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.
3.Research progress on mechanism of intestinal microbiota in tumor immunotherapy resistance
Hui-ling LI ; Xiao-xi LI ; Ying-nan FENG ; Xin HU ; Lan ZHANG ; Xian-zhe DONG
Chinese Pharmacological Bulletin 2025;41(1):1-6
Previous studies have shown that the diversity and composition of intestinal microbiota are related to the effect of tumor immunotherapy,but the mechanism of intestinal microbiota affecting tumor immunotherapy resistance has rarely been sum-marized.This article not only expounds the current clinical sta-tus of tumor immunotherapy resistance,but also summarizes the correlation and regulatory mechanism between the composition and homeostasis of intestinal microbiota and drug resistance to different types of tumor immunotherapy,so as to provide a refer-ence for the study of potential targets for improving tumor immu-notherapy resistance based on intestinal microbiota.
4.Chemical constituents from salt-processed Litchi Semen and their antioxidant activities
Rui YIN ; Xing YANG ; Wei-mao DONG ; Xu-li DENG ; Yi-mou WANG ; Hong-chuan ZHANG ; Kui-lin ZHU ; Zhang-xian CHEN ; Hong-ping HE ; Fa-wu DONG
Chinese Traditional Patent Medicine 2025;47(2):480-486
AIM To study the chemical constituents from salt-processed Litchi Semen and their antioxidant activities.METHODS The 85%ethanol extract from salt-processed Litchi Semen was isolated and purified by silica gel,Sephadex LH-20,MCI,ODS and semi-preparative HPLC,then the structures of obtained compounds were identified by physicochemical properties and spectral data.DPPH and ABTS+free radical scavenging method were used to evaluate their antioxidant activities.RESULTS Fifteen compounds were isolated and identified as dehydrocostuslactone(1),ananosmoside A(2),funingensin A(3),(2S)-pinocembrin-7-O-(6-O-α-L-rhamnopyranosyl-β-D-glucopyranoside)(4),liquiritienin(5),quercetin(6),rutin(7),isorhamnetin-3-O-β-rutinoside(8),procyanidin A2(9),procyanidin A1(10),ethyl protocatechuate(11),5-hydroxymethylfurfural(12),di(2-ethyl-hexyl)phthalate(13),nicotinamide(14),(10E,15Z)-9,12,13-trihydroxyoctadeca-10,15-dienoic acid(15).Compounds 6-7,9-10 exhibited scavenging activities against DPPH radicals with IC50 values of(12.929±1.232),(14.104±0.946),(10.417±1.736),(6.944±0.030)μmol/L,respectively.Compounds 6-10 exhibited scavenging activities against ABTS+radicals with IC50 values of(21.952±0.577),(25.683±0.625),(22.970±1.336),(20.210±1.435),(18.725±0.324)μmol/L,respectively.CONCLUSION Compounds 1,5,14-15 are isolated from Litchi genus for the first time.Compounds 6-7,9-10 have strong in vitro antioxidant activities.
5.Deep learning model based on fundus images for detection of coronary artery disease with mild cognitive impairment
Yi YE ; Wei FENG ; Yao-dong DING ; Qing CHEN ; Yang ZHANG ; Li LIN ; Tong MA ; Bin WANG ; Xian-gang CHANG ; Zong-yuan GE ; Xiao-yi WANG ; Long-jun CAI ; Yong ZENG
Chinese Journal of Interventional Cardiology 2025;33(6):303-311
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.
6.Mechanism of Polygonum capitatum on atherosclerosis based on data mining
Zi YE ; Yun-pei WANG ; Yu-hui WANG ; Xun-de XIAN ; Xiao-jie LI ; Chun-hua HUANG ; Yuan-zhu LIAO ; Di-dong LOU ; Yi-xia ZHOU
Chinese Pharmacological Bulletin 2025;41(12):2369-2378
Aim To systematically investigate the ac-tive components,targets,and regulatory pathways of Po-lygonum capitatum in intervening atherosclerosis(AS)through network pharmacology,molecular docking and animal experiments.Methods Active components of Polygonum capitatum and AS-related targets were screened and identified through database searches.Protein-protein interaction(PPI)network analysis was performed using the STRING database,followed by GO and KEGG enrichment analyses via the David plat-form.Molecular docking validation was conducted with AutoDock.An AS model was established in Syrian golden hamsters fed a high-fat diet.Predicted pathways and targets were validated using qPCR,ELISA,and histopathological assessment of aortic and hepatic tis-sues via HE staining.Results Network pharmacology identified 27 potential active components of Polygonum capitatum(primarily flavonoids such as quercetin and luteolin)and 110 drug-disease intersection targets,in-cluding core targets MMP-9,ALB,and AKT1.GO and KEGG analyses enriched 593 and 125 pathways,re-spectively,with the NF-κB inflammatory pathway,TNF signaling pathway and lipid metabolism/atherosclerosis pathways highlighted as key mechanisms.Animal ex-periments demonstrated that Polygonum capitatum im-proved serum lipid profiles(reduced TC,TG,LDL-C)in AS hamsters,suppressed the MMP-9/NF-κB signa-ling pathway(downregulated MMP-9,p65 phosphoryla-tion,TNF-α,and IL-6),and inhibited VSMC synthetic phenotypic transformation(upregulated α-SMA and myocardin)by downregulating MCPIP1.Additionally,Polygonum capitatum ameliorated aortic lesions and he-patic lipid deposition in AS hamsters.Conclusions Polygonum capitatum alleviates AS by synergistically regulating the MMP-9/NF-κB/MCPIP1 axis through flavonoid components,suppressing vascular inflammato-ry cascades and maintaining VSMC contractile pheno-types.This reflects Polygonum capitatum's multi-com-ponent,multi-pathway,and multi-target characteristics in combating AS.
7.Research progress on mechanism of intestinal microbiota in tumor immunotherapy resistance
Hui-ling LI ; Xiao-xi LI ; Ying-nan FENG ; Xin HU ; Lan ZHANG ; Xian-zhe DONG
Chinese Pharmacological Bulletin 2025;41(1):1-6
Previous studies have shown that the diversity and composition of intestinal microbiota are related to the effect of tumor immunotherapy,but the mechanism of intestinal microbiota affecting tumor immunotherapy resistance has rarely been sum-marized.This article not only expounds the current clinical sta-tus of tumor immunotherapy resistance,but also summarizes the correlation and regulatory mechanism between the composition and homeostasis of intestinal microbiota and drug resistance to different types of tumor immunotherapy,so as to provide a refer-ence for the study of potential targets for improving tumor immu-notherapy resistance based on intestinal microbiota.
8.Influence of helical tomography radiotherapy planning parameters on threading effect
Ruo-qi CAO ; Xia-yu HANG ; Hua HUANG ; Xian-qiang SONG ; Jin-da ZHOU ; Yun-jie BAI ; Xiang-dong SUN ; Yi-kun LI
Chinese Medical Equipment Journal 2025;46(8):58-66
Objective To investigate the influence of helical tomographic radiotherapy plans with different combinations of lead gate width,pitch and algorithms on threading effects.Methods A target model was established with a Cheese Phantom used as the simulated human body,then three lead gate widths(1.0,2.5,and 5.0 cm),six screw pitches(0.143,0.172,0.215,0.287,0.430,and 0.500)and two computational grids(Fine algorithm and Normal algorithm)were respectively combined for designing the helical tomography radiotherapy plans.The radiotherapy plans with a pitch of 0.143,0.172,0.215,0.287 or 0.430 were enrolled into an experimental group,and the plans with a pitch of 0.500 were divided into a control group.The dosimetric parameters including maximum dose(Dmax),minimum dose(Dmin)and mean dose(Dmean)of the target area PTV1 and PTV2 were evaluated by the dose volume histogram(DVH).The dose homogeneity index(HI)of the target area was calculated,and the single rotation time and total treatment time of each plan were recorded and counted.SPSS 27.0 software was used for statistical analysis.Results No significant threading effect appeared regardless of the pitch value when the lead gate width was 1.0 cm.The threading effects in the experimental group were weaker than those in the control group when the lead gate width was 2.5 or 5.0 cm.The threading effect gradually rose with the pitch increased when the lead gate width was 5.0 cm.The most significant difference was found between the threading effect in case of the screw pitch being 0.500 and that with the screw pitch being 0.143,with the differenes being statistically obvious(P<0.05).The lead gate width had significant effects on the Dmax,Dmin,Dmean and HI of PTV1 and PTV2.When the lead gate width was 5.0 cm,high HI value and uneven dose distribution were detected and lowered screw pitch weakened the threading effect.The single rotation time first remained constant and then increased with the screw pitch was enlarged,with the changing points occurring in case of the screw pitches of 0.287 and 0.430.With a certain lead gate width,the treatment time for plans was shortened with the decrease of the pitches in case of the pritches lower than 0.287,and tended to be constant after the screw pitches reached 0.287.The changes of the computational grid had no significant effects on the results of radiotherapy plans when the lead gate width and screw pitch were kept constant.Conclusion When designing a spiral tomotherapy plan with conventional doses,a lead gate width of 1.0 or 2.5 cm and a screw pitch of 0.287 or 0.430 should be selected in order to minimize the threading effect while ensuring the efficiency of plan implementation.[Chinese Medical Equipment Journal,2025,46(8):58-66]
9.Mechanism of Polygonum capitatum on atherosclerosis based on data mining
Zi YE ; Yun-pei WANG ; Yu-hui WANG ; Xun-de XIAN ; Xiao-jie LI ; Chun-hua HUANG ; Yuan-zhu LIAO ; Di-dong LOU ; Yi-xia ZHOU
Chinese Pharmacological Bulletin 2025;41(12):2369-2378
Aim To systematically investigate the ac-tive components,targets,and regulatory pathways of Po-lygonum capitatum in intervening atherosclerosis(AS)through network pharmacology,molecular docking and animal experiments.Methods Active components of Polygonum capitatum and AS-related targets were screened and identified through database searches.Protein-protein interaction(PPI)network analysis was performed using the STRING database,followed by GO and KEGG enrichment analyses via the David plat-form.Molecular docking validation was conducted with AutoDock.An AS model was established in Syrian golden hamsters fed a high-fat diet.Predicted pathways and targets were validated using qPCR,ELISA,and histopathological assessment of aortic and hepatic tis-sues via HE staining.Results Network pharmacology identified 27 potential active components of Polygonum capitatum(primarily flavonoids such as quercetin and luteolin)and 110 drug-disease intersection targets,in-cluding core targets MMP-9,ALB,and AKT1.GO and KEGG analyses enriched 593 and 125 pathways,re-spectively,with the NF-κB inflammatory pathway,TNF signaling pathway and lipid metabolism/atherosclerosis pathways highlighted as key mechanisms.Animal ex-periments demonstrated that Polygonum capitatum im-proved serum lipid profiles(reduced TC,TG,LDL-C)in AS hamsters,suppressed the MMP-9/NF-κB signa-ling pathway(downregulated MMP-9,p65 phosphoryla-tion,TNF-α,and IL-6),and inhibited VSMC synthetic phenotypic transformation(upregulated α-SMA and myocardin)by downregulating MCPIP1.Additionally,Polygonum capitatum ameliorated aortic lesions and he-patic lipid deposition in AS hamsters.Conclusions Polygonum capitatum alleviates AS by synergistically regulating the MMP-9/NF-κB/MCPIP1 axis through flavonoid components,suppressing vascular inflammato-ry cascades and maintaining VSMC contractile pheno-types.This reflects Polygonum capitatum's multi-com-ponent,multi-pathway,and multi-target characteristics in combating AS.
10.Chemical constituents from salt-processed Litchi Semen and their antioxidant activities
Rui YIN ; Xing YANG ; Wei-mao DONG ; Xu-li DENG ; Yi-mou WANG ; Hong-chuan ZHANG ; Kui-lin ZHU ; Zhang-xian CHEN ; Hong-ping HE ; Fa-wu DONG
Chinese Traditional Patent Medicine 2025;47(2):480-486
AIM To study the chemical constituents from salt-processed Litchi Semen and their antioxidant activities.METHODS The 85%ethanol extract from salt-processed Litchi Semen was isolated and purified by silica gel,Sephadex LH-20,MCI,ODS and semi-preparative HPLC,then the structures of obtained compounds were identified by physicochemical properties and spectral data.DPPH and ABTS+free radical scavenging method were used to evaluate their antioxidant activities.RESULTS Fifteen compounds were isolated and identified as dehydrocostuslactone(1),ananosmoside A(2),funingensin A(3),(2S)-pinocembrin-7-O-(6-O-α-L-rhamnopyranosyl-β-D-glucopyranoside)(4),liquiritienin(5),quercetin(6),rutin(7),isorhamnetin-3-O-β-rutinoside(8),procyanidin A2(9),procyanidin A1(10),ethyl protocatechuate(11),5-hydroxymethylfurfural(12),di(2-ethyl-hexyl)phthalate(13),nicotinamide(14),(10E,15Z)-9,12,13-trihydroxyoctadeca-10,15-dienoic acid(15).Compounds 6-7,9-10 exhibited scavenging activities against DPPH radicals with IC50 values of(12.929±1.232),(14.104±0.946),(10.417±1.736),(6.944±0.030)μmol/L,respectively.Compounds 6-10 exhibited scavenging activities against ABTS+radicals with IC50 values of(21.952±0.577),(25.683±0.625),(22.970±1.336),(20.210±1.435),(18.725±0.324)μmol/L,respectively.CONCLUSION Compounds 1,5,14-15 are isolated from Litchi genus for the first time.Compounds 6-7,9-10 have strong in vitro antioxidant activities.

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