Objective:To compare the aortic remodeling of the Fabulous stent system and standard thoracic aortic endovascular repair (TEVAR) on distal aorta type B aortic dissection (TBAD). Methods:The prospective data collected between Dec 2017 and Oct 2019 from 134 patients with type B aortic dissection (TBAD) who underwent treatment with the "Fabulous" stent system, and retrospective data from 159 TBAD patients receiving standard TEVAR from corresponding multicenter. By using propensity score matching analysis, we compared the prognosis and aortic remodeling outcomes in patients undergoing Fabulous and standard TEVAR treatments during a 1-year postoperative follow-up.Results:In this study, 62 patients in Fabulous group and 62 patients in standard TEVAR were included.There were no significant statistical differences in baseline characteristics between the two groups. In terms of aortic remodeling in bare stent region, Fabulous group had better change trends of diameter of true lumen [10.6 (4.4, 14.5) mm vs. 4.7 (0.9, 10.7) mm, P=0.001] and false lumen [-24.2 (-30.5, -4.9) mm vs. 0.7 (-11.8, 2.3) mm, P<0.001] than those in the standard TEVAR group. The rate of complete false lumen thrombosis was also higher in the Fabulous group (62.9% vs. 37.1%, P=0.042). Conclusion:The Fabulous stent system, when compared to standard TEVAR surgery, demonstrates good aortic remodeling outcomes in the distal aorta.

China prospective multicenter birth cohort (Prospective Omics Health Atlas birth cohort, POHA birth cohort) study was officially launched in 2022. This study, in collaboration with 12 participating units, aims to establish a high-quality, multidimensional cohort comprising 20 000 naturally conceived families and assisted reproductive families. The study involves long-term follow-up of parents and offspring, with corresponding biological samples collected at key time points. Through multi-omics testing and analysis, the study aims to conduct multi-omics big data research across the entire maternal and infant life cycle. The goal is to identify new biomarkers for maternal and infant diseases and provide scientific evidence for risk prediction related to maternal diseases and neonatal health.

Objective To propose a deep learning-based method for removing Gaussian and pepper noises of the surgical instrument visual images so as to recover the detailed features of the images.Methods A lightweight multi-task progressive network was constructed involving in a multi-feature fusion encoder-decoder network,an attention-guided network and a detail-recovery progressive network,which used the multi-feature fusion encoder-decoder network to predict and eliminate the noise information in the visual images,the attention-guided network to remove the residual noise and the detail-recovery progressive network to restore the underlying detail features of the denoised images.Some of the regular convolutions in the detail recovery progressive network were replaced with depth separable convolutions to realize lightweight design of the network constructed.Denoising experiments were conducted on the publicly available CBSD68 and Kodak24 datasets and the self-constructed surgical instrument noise dataset so as to compare the denoising effects of the network constructed and the traditional methods and the classification accuracies of ResNet-18 model and ResNet-34 model for the denosied images by the network and to analyze computing power and memory usage before and after the lightweight design.Results The network constructed gained better denoising effect than the classical methods for publicly available datasets,and ResNet-18 model and ResNet-34 model had higher accuracies when used to classify the images denoised by the network for the self-constructed surgical instrument noise dataset.Lightweight design had the parameter number and floating point operations(FLOPs)decreased by approximately 27.27％and 29.81％,respectively.Conclusion The proposed lightweight multi-task progressive network behaves well in denoising surgical instrument visual images with reduced computating power consump-tion and memory usage.[Chinese Medical Equipment Journal,2024,45(2):1-7]

Objective To propose a multi-cascade deep learning processor-based surgical instrument detection and pose estimation algorithm to facilitate the robotic scurb nurse to recognize and delivery surgical instruments.Methods The proposed multi-cascade deep leaning processor-based CYSP algorithm was hibernated with several functional modules such as YOLOX with coordinate attention block(CA-YOLOX),segment anything model(SAM)and principal component analysis(PCA).Firstly,CA-YOLOX was applied to identifying the types of the surgical instruments and completing the coarse positioning of x and y coordinates;secondly,the SAM segmenter was used to clarify the positions of the instruments in the RGB image,and the depth information and internal parameters of the camera were introduced to obtain the point cloud of the surgical instruments;finally,the center of mass,principal direction and normal direction of the surgical instrument point cloud were determined through the PCA algorithm,with which the rotation and translation(RT)matrix between the target coordinate system(surgical instrument center of mass coordinate system)and the base coordinate system of the robotic arm was solved,and the matrix was converted into a quaternion and then transmitted to the robotic arm control unit so as to drive the robotic arm to arrive at the corresponding position and pick up the instrument to complete the instrument delivery task.Migration training was accomplished on a self-constructed surgical instrument image dataset and the effectiveness of the proposed algorithm was evaluated,and instrument delivery experiments were performed on a seven-degree-of-freedom robotic arm and the success rate of the algorithm was assessed.Results The multi-cascade deep leaning processor-based CYSP algorithm had a recognition accuracy of 98.52％on the surgical instrument dataset,a success rate of 94％for the in-strument delivery experiment and average time for recognition of 0.28 s.Conclusion The multi-cascade deep leaning proces-sor-based CYSP algorithm with high reliability and practicability behaves well in facilitating the robotic scurb nurse to recog-nize and deliver surgical instruments.[Chinese Medical Equipment Journal,2024,45(6):1-8]

Six compounds were isolated from the roots of Ephedra sinica Stapf using various chromatographic techniques such as silica gel column chromatography, thin layer chromatography and semi-preparative HPLC. Their chemical structures were identified by analysis of physicochemical properties and spectral data, and determined as (Z)-docosanylferulate (1), (E)-docosanylferulate (2), bis (2-ethylheptyl) phythalate (3), 2,2′-oxybis (1,4-di-tert-butylbenzene) (4), diisobutyl phthalate (5), bis (2-ethylhexyl) phthalate (6). Among them, compound 1 is a new compound, compounds 2-4 were first isolated from Ephedra. A corticosterone-induced PC-12 cell injury model was used for compound activity screening. The results showed that compounds 1 and 5 significantly improved corticosterone-induced PC-12 cell injury and significantly increased 5-HT₇ receptor protein expression in the cells, indicating potential antidepressant activity.

Four furan α-butenolactones were isolated from 50% acetone extract of tuber of Alisma orientale by silica gel column, chromatography gel column and high performance liquid chromatography techniques. Their structures were identified by modern wave spectroscopy techniques and electronic circular dichroism (ECD) and assigned as (5R)-5-hydroxy-3,4-dimethylfuran-2(5H)-one (1), 5-hydroxy-3,5-dimethylfuran-2(5H)-one (2), 5-hydroxy-4-(1-methylethyl)-2(5H)-furanone (3) and alismanoid A (4). Compound 1 was new compound and compounds 2–4 were first isolated from Alisma orientale. Compound 1-4 had potential antifibrotic activities.

Eleven compounds were isolated from Eucommia ulmoides by silica gel, Sephadex LH-20, HW-40C column chromatography and semi-preparative HPLC. Their structures were identified by modern spectroscopic methods as neoeucommiate A (1), (7S,8R)-dihydrodehydrodiconiferyl alcohol (2), urolignoside (3), ficusal (4), tiruneesiin (5), glochidioboside (6), forsythialansides B (7), ecdysanol B (8), (+)-syringaresinol-4-O-β-D-glucopyranoside (9), (+)-pinoresinol 4-O-[6ʹʹ-O-vanilloyl]-β-D-glucopyranoside (10), samsesquinoside (11). Compound 1 is a new compound, compounds 3-7, 10 and 11 were isolated from Eucommia ulmoides for the first time.

Objective This study aimed to clarify the intervention effect of salidroside(SAL)on lung injury caused by PM2.5 in mice and illuminate the function of SIRT1-PGC-1ɑ axis. Methods Specific pathogen-free(SPF)grade male C57BL/6 mice were randomly assigned to the following groups:control group,SAL group,PM2.5 group,SAL+PM2.5 group.On the first day,SAL was given by gavage,and on the second day,PM2.5 suspension was given by intratracheal instillation.The whole experiment consist of a total of 10 cycles,lasting 20 days.At the end of treatment,blood samples and lung tissues were collected and analyzed.Observation of pathological changes in lung tissue using inverted microscopy and transmission electron microscopy.The expression of inflammatory,antioxidants,apoptosis,and SIRT1-PGC-1ɑ proteins were detected by Western blotting. Results Exposure to PM2.5 leads to obvious morphological and pathologica changes in the lung of mice.PM2.5 caused a decline in levels of antioxidant-related enzymes and protein expressions of HO-1,Nrf2,SOD2,SIRT1 and PGC-1ɑ,and an increase in the protein expressions of IL-6,IL-1β,Bax,caspase-9 and cleaved caspase-3.However,SAL reversed the aforementioned changes caused by PM2.5 by activating the SIRT1-PGC-1α pathway. Conclusion SAL can activate SIRT1-PGC-1ɑ to ameliorate PM2.5-induced lung injury.

Objective To investigate the formation and mechanism of dipeptidylpeptidase-4 inhibitor anagliptin inhibiting lung metastasis of colorectal cancer.Methods Twenty-four male BALB/c mice were randomly divided into normal group,model group,anagliptin group.The control group did not undergo any treatment.The model group was injected with 0.1 ml CT-26 cells of 109 cells/L.once through the tail vein of the mouse to construct a lung metastasis model,while the anagliptin group was injected intraperitoneally 20 mg/(kg d)0 day after constructing a lung metastasis model.The mice were sacrificed after 14 days.HE staining was used to detect the morphological alteration.Determination of CT-26 cell viability through MTT assay and CT-26 cell apoptosis was detected by flow cytometry and live/dead cell staining.Reactive oxygen species(ROS)production was measured by ROS kit.Western blotting was conducted to measure the expression level of Bcl-2,Bax,cleaved-caspase-3,superoxide dismutase(SOD-1)and SOD-2.Results HE staining showed that the administration of anagliptin could significantly inhibit the abnormal changes in the model group.Anagliptin inhibited the viability of CT-26 cells above 2 mmol/L.Anagliptin promoted the apoptosis of CT-26 cells.Incubation of anagliptin in CT-26 cells significant promoted the production of ROS.Incubation of anagliptin stimulated the expressions of Bax and cleaved-Caspase-3,while down-regulated the expression of Bcl-2 in CT-26 cells.Administration of anagliptin decreased the expression of SOD-1,but not SOD-2.Conclusion Anagliptin promotes apoptosis of colorectal cancer cells and inhibits the formation of lung metastatic tumors through the SOD-1/ROS pathway.

Fourteen flavonoids were isolated and purified from Epimedium sagittatum by various chromatography techniques such as macroporous adsorbent resin, silica gel, ODS, Sephadex LH-20, HW-40C and semi-preparative HPLC. Their structures were identified by analysis of physicochemical properties and spectral data, and determined as 3′-hydroxy-baohuoside-Ⅱ (1), huazhongilexone-7-O-β-D-glucopyranoside (2), kaempferol-3-O-α-L-rhamnoside (3), baohuoside-Ⅱ (4), icariside-Ⅱ (5), kaempferol 3,7-di-O-α-L-rhamnopyranoside (6), (+)-aromadendrin (7), kaempferol 3-O-(2-O-β-D-apiofuranosyl)-α-L-rhamnopyranoside (8), sagittatoside A (9), 2″-O-rhamnosyl icariside-II (10), apigenin-7-O-β-D-glucoside (11), quercetin 3-O-β-D-apiofuranoyl-(1→2)-α-L-rhamnopyranoside (12), kaempferol (13), icariin (14). Among them, compound 1 is a new compound, while compounds 2, 6-8, 11, and 12 were isolated from E.sagittatum for the first time.