The Outcome of Sac Filling With Fibrin Sealant and Gentamicin After Endovascular Aortic Repair of Brucella-Related Aorto-Iliac Artery Aneurysms: A Retrospective Single-Center Study.

Purpose: This study aimed to analyze the experience of our center and assess the efficacy of sac filling with fibrin sealant (FS) and gentamicin after endovascular aortic repair (EVAR) in patients with Brucella-related aorto-iliac artery aneurysms.

Materials And Methods: All patients who received sac filling with FS and gentamicin after EVAR for Brucella-related aorto-iliac artery aneurysms between March 2019 and September 2022 were reviewed. Before and after sac filling with FS and gentamicin, aneurysm sac thrombosis and endoleak were evaluated using a preloaded catheter to monitor immediate repair outcome.

Outcomes of Castor Single-Branched Stent Graft for Reconstruction of Multiple Supra-Aortic Branches in Aortic Arch Disease.

Purpose: To report the outcomes of a combination of Castor single-branched stent grafts with other techniques for the reconstruction of multiple supra-aortic branches in aortic arch disease.

Materials And Methods: Between December 2019 and December 2021, 20 patients with aortic arch disease underwent thoracic endovascular aortic repair (TEVAR) at our institution using a Castor single-branched stent graft combined with the fenestration, chimney, or bypass techniques. Thoracic endovascular aortic repair is indicated for complicated or acute type B aortic dissection (TBAD), nonruptured aneurysms with a maximum aneurysm diameter >5.

Heterogeneous temporal representation for diabetic blood glucose prediction.

Blood glucose prediction (BGP) has increasingly been adopted for personalized monitoring of blood glucose levels in diabetic patients, providing valuable support for physicians in diagnosis and treatment planning. Despite the remarkable success achieved, applying BGP in multi-patient scenarios remains problematic, largely due to the inherent heterogeneity and uncertain nature of continuous glucose monitoring (CGM) data obtained from diverse patient profiles. This study proposes the first graph-based Heterogeneous Temporal Representation (HETER) network for multi-patient Blood Glucose Prediction (BGP).

Plasma microRNAs as potential biomarkers in diagnosis of acute venous thromboembolism.

Objective: To assess the potential use of plasma microRNAs (miRNAs) in diagnosis of acute venous thromboembolism (VTE).

Methods: Using BGISEQ-500 sequencing technology, we analyzed the miRNA profile of paired plasma samples from the acute and chronic phases of four patients with unprovoked VTE. Using real-time quantitative polymerase chain reaction (RT-qPCR), we verified nine upregulated named miRNAs in the acute phase in the plasma samples of 54 patients with acute VTE and 39 controls.

Multi-Physical Field Simulation of Cracking during Crystal Growth by Bridgman Method.

Crystal materials are prone to cracking during growth, which is a key problem leading to slow growth and difficulty in forming large-size crystals. In this study, based on the commercial finite element software COMSOL Multiphysics, the transient finite element simulation of the multi-physical field, including fluid heat transfer-phase transition-solid equilibrium-damage coupling behaviors, is performed. The phase-transition material properties and maximum tensile strain damage variables are customized.

Incidence and Clinical Features of Venous Thromboembolism in Inpatients with Mental Illness.

Aims: We investigated the incidence and clinical features of venous thromboembolism (VTE) in inpatients with mental illnesses.

Methods: We retrospectively analyzed records of inpatients with mental illnesses and confirmed VTE at The First Hospital of Hebei Medical University between August 2018 and July 2022. We recorded demographic characteristics, psychosis-related conditions, and thrombus distribution.

Uncorrected Preoperative Infection Causing the Death of a Patient with a Thoracic Aortic Aneurysm.

Background: A thoracic aortic aneurysm (TAA) is a known condition seen in cardiovascular practice. A TAA rupture and postoperative infection may result in death. Preoperative infections leading to death are extremely rare.

Midterm Outcomes of Endovascular Therapy for TASC II D Femoropopliteal Lesions with Critical Limb Ischemia: A Retrospective Analysis.

Background: This study evaluated the midterm results of endovascular therapy (EVT) for Trans-Atlantic Inter-Society (TASC) II D femoropopliteal lesions in patients with critical limb ischemia (CLI).

Methods: Fifty seven limbs of 54 patients with CLI due to TASC II D femoropopliteal lesions who underwent EVT at the First Hospital of Hebei Medical University were retrospectively analysed in a single-centre, observational study. The patient characteristics, endovascular procedural details, freedom from target lesion revascularization (TLR), patency rates, ulcer healing rate, and limb salvage rate were accessed.

Promotion of angiogenesis in vitro by Astragalus polysaccharide via activation of TLR4 signaling pathway.

During the implantation of functional tissue-engineered constructs for treating bone defects, a functional vascular network is critical for the survival of the construct. One strategy to achieve rapid angiogenesis for this application is the co-culture of outgrowth endothelial cells (OECs) and primary human osteoblasts (POBs) within a scaffold prior to implantation. In the present study, we aim to investigate whether Astragalus polysaccharide (APS) promotes angiogenesis or vascularization via the TLR4 signaling pathway in a co-culture of OECs and POBs.

Inherited and acquired causes renal vein thrombosis in an 11-year-old boy who was relieved after piperacillin-tazobactam and rivaroxaban treatment: a case report.

Background: Physiological hypercoagulability is a well-known condition in older populations, whereas thrombosis, especially in renal veins, is a rare occurrence in teenagers. This paper presents a pediatric case of renal venous infarction and thrombosis.

Case Description: We report the case of an 11-year-old Chinese boy who presented with low back discomfort and was afraid to walk.

Development and validation of a feature extraction-based logical anthropomorphic diagnostic system for early gastric cancer: A case-control study.

Background: Prompt diagnosis of early gastric cancer (EGC) is crucial for improving patient survival. However, most previous computer-aided-diagnosis (CAD) systems did not concretize or explain diagnostic theories. We aimed to develop a logical anthropomorphic artificial intelligence (AI) diagnostic system named ENDOANGEL-LA (logical anthropomorphic) for EGCs under magnifying image enhanced endoscopy (M-IEE).

A deep learning-based system for real-time image reporting during esophagogastroduodenoscopy: a multicenter study.

Background And Study Aims: Endoscopic reports are essential for the diagnosis and follow-up of gastrointestinal diseases. This study aimed to construct an intelligent system for automatic photo documentation during esophagogastroduodenoscopy (EGD) and test its utility in clinical practice.

Patients And Methods: Seven convolutional neural networks trained and tested using 210,198 images were integrated to construct the endoscopic automatic image reporting system (EAIRS).

Crocin ameliorates atherosclerosis by promoting the reverse cholesterol transport and inhibiting the foam cell formation via regulating PPARγ/LXR-α.

Crocin (CRO) is feasible in alleviating atherosclerosis (AS), the mechanism of which was therefore explored in the study. High-fat diet (HFD)-induced apolipoprotein E-deficient (ApoE) mice and lysophosphatidic acid (LPA)-treated macrophages received CRO treatment. Treated macrophage viability was determined via MTT assay.

Real-time use of artificial intelligence for diagnosing early gastric cancer by magnifying image-enhanced endoscopy: a multicenter diagnostic study (with videos).

Background And Aims: Endoscopy is a pivotal method for detecting early gastric cancer (EGC). However, skill among endoscopists varies greatly. Here, we proposed a deep learning-based system named ENDOANGEL-ME to diagnose EGC in magnifying image-enhanced endoscopy (M-IEE).

Real-time artificial intelligence for detecting focal lesions and diagnosing neoplasms of the stomach by white-light endoscopy (with videos).

Background And Aims: White-light endoscopy (WLE) is the most pivotal tool to detect gastric cancer in an early stage. However, the skill among endoscopists varies greatly. Here, we aim to develop a deep learning-based system named ENDOANGEL-LD (lesion detection) to assist in detecting all focal gastric lesions and predicting neoplasms by WLE.

Effect of a deep learning-based system on the miss rate of gastric neoplasms during upper gastrointestinal endoscopy: a single-centre, tandem, randomised controlled trial.

Background: White light endoscopy is a pivotal first-line tool for the detection of gastric neoplasms. However, gastric neoplasms can be missed during upper gastrointestinal endoscopy due to the subtle nature of these lesions and varying skill among endoscopists. Here, we aimed to evaluate the effect of an artificial intelligence (AI) system designed to detect focal lesions and diagnose gastric neoplasms on reducing the miss rate of gastric neoplasms in clinical practice.

Deep learning system compared with expert endoscopists in predicting early gastric cancer and its invasion depth and differentiation status (with videos).

Background And Aims: We aimed to develop and validate a deep learning-based system that covers various aspects of early gastric cancer (EGC) diagnosis, including detecting gastric neoplasm, identifying EGC, and predicting EGC invasion depth and differentiation status. Herein, we provide a state-of-the-art comparison of the system with endoscopists using real-time videos in a nationwide human-machine competition.

Methods: This multicenter, prospective, real-time, competitive comparative, diagnostic study enrolled consecutive patients who received magnifying narrow-band imaging endoscopy at the Peking University Cancer Hospital from June 9, 2020 to November 17, 2020.

Two New Methods of Supine Venographically Guided Popliteal Vein Puncture: A Retrospective Study.

Objective: Presently, the prone position is necessary for popliteal vein puncture access, but it makes the patients uncomfortable and does not allow traditional femoral or jugular access. To address these deficiencies, this study introduces two new methods, anterior and medial access carried out in the supine position.

Methods: Venous interventions with punctures in the popliteal vein of 120 limbs in 97 patients were performed during the period from February 2017 to April 2019.

A Novel Model Based on Deep Convolutional Neural Network Improves Diagnostic Accuracy of Intramucosal Gastric Cancer (With Video).

Background And Aims: Prediction of intramucosal gastric cancer (GC) is a big challenge. It is not clear whether artificial intelligence could assist endoscopists in the diagnosis.

Methods: A deep convolutional neural networks (DCNN) model was developed retrospectively collected 3407 endoscopic images from 666 gastric cancer patients from two Endoscopy Centers (training dataset).

Evaluation of the effects of an artificial intelligence system on endoscopy quality and preliminary testing of its performance in detecting early gastric cancer: a randomized controlled trial.

Background: Esophagogastroduodenoscopy (EGD) is a prerequisite for detecting upper gastrointestinal lesions especially early gastric cancer (EGC). An artificial intelligence system has been shown to monitor blind spots during EGD. In this study, we updated the system (ENDOANGEL), verified its effectiveness in improving endoscopy quality, and pretested its performance in detecting EGC in a multicenter randomized controlled trial.

Recurrent arterial thrombosis of the lower extremity with secondary thrombocythemia due to reperfusion injury: a case report.

Thrombocythemia is an important cause for thrombogenesis and can be classified as essential or secondary according to the etiology. Secondary thrombocythemia (ST), also called reactive thrombocytosis, is caused by a disorder that triggers increased production by normal platelet-forming cells and is characterized in terms of abnormal increased number of platelet in blood and megakaryocytes in bone marrow. Previous reports have found that complications from malignant tumors, chronic inflammation, acute inflammation, acute hemorrhage, spleen resection etc.

A deep learning-based system for identifying differentiation status and delineating the margins of early gastric cancer in magnifying narrow-band imaging endoscopy.

BACKGROUND : Accurate identification of the differentiation status and margins for early gastric cancer (EGC) is critical for determining the surgical strategy and achieving curative resection in EGC patients. The aim of this study was to develop a real-time system to accurately identify differentiation status and delineate the margins of EGC on magnifying narrow-band imaging (ME-NBI) endoscopy. METHODS : 2217 images from 145 EGC patients and 1870 images from 139 EGC patients were retrospectively collected to train and test the first convolutional neural network (CNN1) to identify EGC differentiation status.

Detection of colorectal adenomas with a real-time computer-aided system (ENDOANGEL): a randomised controlled study.

Background: Colonoscopy performance varies among endoscopists, impairing the discovery of colorectal cancers and precursor lesions. We aimed to construct a real-time quality improvement system (ENDOANGEL) to monitor real-time withdrawal speed and colonoscopy withdrawal time and to remind endoscopists of blind spots caused by endoscope slipping. We also aimed to evaluate the effectiveness of this system for improving adenoma yield of everyday colonoscopy.

Comparing blind spots of unsedated ultrafine, sedated, and unsedated conventional gastroscopy with and without artificial intelligence: a prospective, single-blind, 3-parallel-group, randomized, single-center trial.

Background And Aims: EGD is the most vital procedure for the diagnosis of upper GI lesions. We aimed to compare the performance of unsedated ultrathin transoral endoscopy (U-TOE), unsedated conventional EGD (C-EGD), and sedated C-EGD with or without the use of an artificial intelligence (AI) system.

Methods: In this prospective, single-blind, 3-parallel-group, randomized, single-center trial, 437 patients scheduled to undergo outpatient EGD were randomized to unsedated U-TOE, unsedated C-EGD, or sedated C-EGD, and each group was then divided into 2 subgroups: with or without the assistance of an AI system to monitor blind spots during EGD.

Randomised controlled trial of WISENSE, a real-time quality improving system for monitoring blind spots during esophagogastroduodenoscopy.

Objective: Esophagogastroduodenoscopy (EGD) is the pivotal procedure in the diagnosis of upper gastrointestinal lesions. However, there are significant variations in EGD performance among endoscopists, impairing the discovery rate of gastric cancers and precursor lesions. The aim of this study was to construct a real-time quality improving system, WISENSE, to monitor blind spots, time the procedure and automatically generate photodocumentation during EGD and thus raise the quality of everyday endoscopy.