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.

OBJECTIVES: To evaluate whether adding Fuzheng Jiedu Xiaoji (FZJDXJ) therapy improves survival in advanced hepatitis B virus-related HCC (HBV-HCC) patients. METHODS: This prospective, randomized controlled study was performed at a major academic medical center in Beijing, China from October 2020 to October 2022. Eligible patients with advanced HBV-HCC were randomly divided equally (1:1) to receive either the combination of FZJDXJ and conventional Western medical therapy (63 cases, FZJDXJ group) or solely Western medicine (66 cases, control group). The study endpoints consisted of overall survival (OS) as the primary outcome, with progression-free survival (PFS), disease control rate (DCR), and adverse events (AEs) as secondary measures. RESULTS: The median OS was significantly prolonged in the FZJDXJ group at 8.9 months (95% CI: 6.0-11.9) vs. 4.4 months (95% CI: 3.2-7.3) in the control group (P<0.05). The hazard ratio for mortality in the FZJDXJ group was 0.59 (95% CI: 0.40-0.89), suggesting a 41% lower risk of death compared to the control group. The results revealed that patients receiving FZJDXJ therapy achieved a PFS of 5.1 months (95% CI: 4.1 to 7.2 months), compared to only 2.9 months (95% CI: 2.0 to 4.6 months) in the control group (P<0.05). Additionally, DCR was significantly elevated in the FZJDXJ group (20.6%) compared to the control group (10.6%, P<0.05). Subgroup analysis demonstrated that FZJDXJ significantly improved OS in patients with alpha-fetoprotein levels <400 ng/mL, age <60 years, Barcelona Clinic Liver Cancer (BCLC) stage C, and compensated liver function (Child-Pugh A and B, P<0.05). Multivariate analysis revealed that FZJDXJ therapy acted as an independent factor protecting against mortality within 1 year. Gastrointestinal symptoms are rare side effects, and no fatalities associated with the treatment were reported. CONCLUSION This randomized controlled trial demonstrated that FZJDXJ combined Western conventional therapy significantly improves OS and PFS in patients with advanced HBV-HCC. (registration No. ChiCTR2000033941).
Humans ; Drugs, Chinese Herbal/adverse effects* ; Male ; Female ; Middle Aged ; Liver Neoplasms/virology* ; Carcinoma, Hepatocellular/virology* ; Treatment Outcome ; Hepatitis B virus ; Adult ; Aged ; Hepatitis B/drug therapy*

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 construct a measurement tool for atrial fibrillation(AF)patients'experience of catheter ablation,in order to provide quantifiable basis for improving the patients'perioperative experience.Methods From Jun 2022 to Apr 2023,literature analysis,qualitative research,Delphi expert consultation,and analytic hierarchy process were used to determine the content and weight of various indicators of the measurement tool.Results The enthusiasm of experts in 3 rounds was 100%.The authority coefficient of experts was 0.946,0.961 and 0.976.The Kendal harmony coefficients of the 2 and 3 rounds of expert consultation was 0.130 and 0.370(P＜0.001).The final measurement tool included 46 items and 5 dimensions,including operational and technical quality experience,comfort management experience,information and communication experience,emotional support experience,service process and response experience.Conclusion The preliminary construction of measurement tool for AF patients'experience of catheter ablation,which were based on the features of specialty,could not only evaluate the patients'experience accurately,but also provide a basis for targeted improvement of medical and nursing service quality.

Hashimoto's thyroiditis(HT)is a common endocrine disease,which can be classified into the category of goiter disease in traditional Chinese medicine.Professor LIU Min believes that the pathogenesis of HT is closely related to the heart and gallbladder,and its pathogenesis is due to the gallbladder constraint failing to descend and the disturbance of pivot,together with insufficient heart-qi and the disharmony between the nutritive qi and the defensive qi.For the treatment of HT,the modified Chaihu Guizhi Decoction is often used,which is mainly composed of Bupleuri Radix,Cinnamomi Ramulus,Scutellariae Radix,Pinelliae Rhizoma Praeparatum,Ginseng Radix et Rhizoma Rubra,Glycyrrhizae Radix et Rhizoma Praeparata cum Melle,Jujubae Fructus,Paeoniae Radix Alba,Os Draconis,Ostreae Concha,and Zingiberis Rhizoma Recens.Chaihu Guizhi Decoction has the actions of soothing gallbladder and relieving depression,restoring the function of shaoyang pivot,regulating nutritive qi and the defensive qi,and benefiting heart spirit,which exactly accords with the HT's pathogenesis of gallbladder constraint failing to descend and insufficient heart-qi.In the clinical treatment of HT,the modification of the drugs should be performed according to the concurrent syndromes of the patients,and the dosage of the drugs should also be adjusted.In addition to drug treatment,the attention should also be addressed to the adjustment of patients'lifestyle and dietary habits and to the emotional counseling,thus to achieve significant effect.

Objective To achieve automatic segmentation of cell nuclei in gastrointestinal cancer pathological images by using a deep learning algorithm,so as to assist in the quantitative analysis of subsequent pathological images.Methods A total of 59 patients with gastrointestinal cancer treated in Ruijin Hospital,Shanghai Jiao Tong University School of Medicine from Jan 2022 to Feb 2022,were selected as the research objects.Python and LabelMe were used for data anonymization,image segmentation,and region of interest annotation of patients'pathological images.A total of 944 pathological images were included,and 9 703 nuclei were annotated.Then,a new semantic segmentation model based on deep learning was constructed.The model introduced deformable attention transformer(DAT)to realize automatic,accurate and efficient segmentation of pathological image nuclei.Finally,multiple segmentation evaluation criteria are used to evaluate the model's performance.Results The mean absolute error of the segmentation results of the model proposed in this paper was 0.112 6,and the dice coefficient(Dice)was 0.721 5.Its effect was significantly better than the U-net baseline model,and it was ahead of models such as ResU-net++,R2Unet and R2AttUnet.Moreover,the segmentation results were relatively stable with good generalization.Conclusion The segmentation model established in this study can accurately identify and segment the nuclei in the pathological images,with good robustness and generalization,which is helpful to play an auxiliary diagnostic role in practical applications.

Objective:To evaluate the safety and efficiency of robotic visualization system(RVS)-assisted microsurgical re-construction of the reproductive tract in male rats and the satisfaction of the surgeons.Methods:We randomly divided 8 adult male SD rats into an experimental and a control group,the former treated by RVS-assisted microsurgical vasoepididymostomy(VE)or vaso-vasostomy(VV),and the latter by VE or VV under the standard operating microscope(SOM).We compared the operation time,me-chanical patency and anastomosis leakage immediately after surgery,and the surgeons'satisfaction between the two groups.Results:No statistically significant difference was observed the operation time between the experimental and the control groups,and no anasto-mosis leakage occurred after VV in either group.The rate of mechanical patency immediately after surgery was 100％in both groups,and that of anastomosis leakage after VE was 16.7％in the experimental group and 14.3％in the control.Compared with the control group,the experimental group achieved dramatically higher scores on visual comfort(3.00±0.76 vs 4.00±0.53,P＜0.05),neck/back comfort(2.75±1.16 vs 4.38±1.06,P＜0.01)and man-machine interaction(3.88±1.55 va 4.88±0.35,P＜0.05).There were no statistically significant differences in the scores on image definition and operating room suitability between the two groups.Conclusion:RVS can be used in microsurgical reconstruction of the reproductive tract in male rats and,with its advantages over SOM in ergonomic design and image definition,has a potential application value in male reproductive system micosurgery.

Aim To study the therapeutic effect of Balanophora polysaccharide(BPS)on gastric ulcer(GU)induced by acetic acid in rats and to investigateits mechanisms. Methods Sixty male SD rats were randomly divided into sham-operated group, GU model group, omeprazole positive group(3.6 mg·kg-1), and low, medium and high dose of BPS treatment groups(100, 200 and 400 mg·kg-1). The GU model group was prepared by acetic acid cautery method, and the morphology and pathological changes of ulcers were observed by visual observation combined with HE staining, and the ulcer area and inhibition rate were measured and calculated; superoxide dismutase(SOD)activity, malondialdehyde(MDA)content and glutathione peroxidase(GSH-PX)activity were measured by enzymatic assay; tumor necrosis factor-α(TNF-α)and interleukin-6(IL-6)content were detected by ELISA. The expression levels of epidermal growth factor(EGF)and epidermal growth factor receptor(EGFR)were measured by immunohistochemistry staining and Western blot. Results Compared with the sham-operated group, obvious ulcer damage was seen in the model group. Compared with the model group, the BPS-treated group showed a significant reduction in ulcer area, an increase in SOD and GSH-PX activity and EGF and EGFR expression levels, and a significant decrease in MDA, TNF-α and IL-6 content. Conclusions BPS has a therapeutic effect on GU in rats, and its mechanism may be related to the inhibition of oxidative stress, suppression of inflammatory stimuli and promotion of regenerative repair of gastric mucosa.

This study investigated the choroplast genome sequence of wild Atractylodes lancea from Yuexi in Anhui province by high-throughput sequencing, followed by characterization of the genome structure, which laid a foundation for the species identification, analysis of genetic diversity, and resource conservation of A. lancea. To be specific, the total genomic DNA was extracted from the leaves of A. lancea with the improved CTAB method. The chloroplast genome of A. lancea was sequenced by the high-throughput sequencing technology, followed by assembling by metaSPAdes and annotation by CPGAVAS2. Bioiformatics methods were employed for the analysis of simple sequence repeats(SSRs), inverted repeat(IR) border, codon bias, and phylogeny. The results showed that the whole chloroplast genome of A. lancea was 153 178 bp, with an 84 226 bp large single copy(LSC) and a 18 658 bp small single copy(SSC) separated by a pair of IRs(25 147 bp). The genome had the GC content of 37.7% and 124 genes: 87 protein-coding genes, 8 rRNA genes, and 29 tRNA genes. It had 26 287 codons and encoded 20 amino acids. Phylogenetic analysis showed that Atractylodes species clustered into one clade and that A. lancea had close genetic relationship with A. koreana. This study established a method for sequencing the chloroplast genome of A. lancea and enriched the genetic resources of Compositae. The findings are expected to lay a foundation for species identification, analysis of genetic diversity, and resource conservation of A. lancea.
Phylogeny ; Atractylodes/genetics* ; Genome, Chloroplast ; Whole Genome Sequencing ; Microsatellite Repeats ; Lamiales

Objectives: To investigated the safety and efficacy of treating patients with acute non-ST-segment elevation myocardial infarction (NSTEMI) and elevated levels of N-terminal pro-hormone B-type natriuretic peptide (NT-proBNP) with levosimendan within 24 hours of first medical contact (FMC). Methods: This multicenter, open-label, block-randomized controlled trial (NCT03189901) investigated the safety and efficacy of levosimendan as an early management strategy of acute heart failure (EMS-AHF) for patients with NSTEMI and high NT-proBNP levels. This study included 255 patients with NSTEMI and elevated NT-proBNP levels, including 142 males and 113 females with a median age of 65 (58-70) years, and were admitted in the emergency or outpatient departments at 14 medical centers in China between October 2017 and October 2021. The patients were randomly divided into a levosimendan group (n=129) and a control group (n=126). The primary outcome measure was NT-proBNP levels on day 3 of treatment and changes in the NT-proBNP levels from baseline on day 5 after randomization. The secondary outcome measures included the proportion of patients with more than 30% reduction in NT-proBNP levels from baseline, major adverse cardiovascular events (MACE) during hospitalization and at 6 months after hospitalization, safety during the treatment, and health economics indices. The measurement data parameters between groups were compared using the t-test or the non-parametric test. The count data parameters were compared between groups using the χ² test. Results: On day 3, the NT-proBNP levels in the levosimendan group were lower than the control group but were statistically insignificant [866 (455, 1 960) vs. 1 118 (459, 2 417) ng/L, Z=-1.25,P=0.21]. However, on day 5, changes in the NT-proBNP levels from baseline in the levosimendan group were significantly higher than the control group [67.6% (33.8%,82.5%)vs.54.8% (7.3%,77.9%), Z=-2.14, P=0.03]. There were no significant differences in the proportion of patients with more than 30% reduction in the NT-proBNP levels on day 5 between the levosimendan and the control groups [77.5% (100/129) vs. 69.0% (87/126), χ²=2.34, P=0.13]. Furthermore, incidences of MACE did not show any significant differences between the two groups during hospitalization [4.7% (6/129) vs. 7.1% (9/126), χ²=0.72, P=0.40] and at 6 months [14.7% (19/129) vs. 12.7% (16/126), χ²=0.22, P=0.64]. Four cardiac deaths were reported in the control group during hospitalization [0 (0/129) vs. 3.2% (4/126), P=0.06]. However, 6-month survival rates were comparable between the two groups (log-rank test, P=0.18). Moreover, adverse events or serious adverse events such as shock, ventricular fibrillation, and ventricular tachycardia were not reported in both the groups during levosimendan treatment (days 0-1). The total cost of hospitalization [34 591.00(15 527.46,59 324.80) vs. 37 144.65(16 066.90,63 919.00)yuan, Z=-0.26, P=0.80] and the total length of hospitalization [9 (8, 12) vs. 10 (7, 13) days, Z=0.72, P=0.72] were lower for patients in the levosimendan group compared to those in the control group, but did not show statistically significant differences. Conclusions: Early administration of levosimendan reduced NT-proBNP levels in NSTEMI patients with elevated NT-proBNP and did not increase the total cost and length of hospitalization, but did not significantly improve MACE during hospitalization or at 6 months.
Male ; Female ; Humans ; Aged ; Natriuretic Peptide, Brain ; Simendan/therapeutic use* ; Non-ST Elevated Myocardial Infarction ; Heart Failure/drug therapy* ; Peptide Fragments ; Arrhythmias, Cardiac ; Biomarkers ; Prognosis