An Approach to Constructing Multispecies Biofilm Communities from Rhizosphere Soil.

The multispecies biofilm is a naturally occurring and dominant lifestyle of bacteria in nature, including in rhizosphere soil, although the current understanding of it is limited. Here, we provide an approach to rapidly establish synergistic multispecies biofilm communities. The first step is to extract cells from rhizosphere soil using the differential centrifugation method. Afterward, these soil cells are inoculated into the culture medium to form pellicle biofilm. After 36 h of incubation, the bacterial composition of the biofilm and the solution underneath are determined using the 16S rRNA gene amplicon sequencing method. Meanwhile, high-throughput bacterial isolation from pellicle biofilm is conducted using the limiting dilution method. Then, the top 5 bacterial taxa are selected with the highest abundance in the 16S rRNA gene amplicon sequencing data (pellicle biofilm samples) for further use in constructing multispecies biofilm communities. All combinations of the 5 bacterial taxa were quickly established using a 24-well plate, selected for the strongest biofilm formation ability by the crystal violet staining assay, and quantified by qPCR. Finally, the most robust synthetic bacterial multispecies biofilm communities were obtained through the methods above. This methodology provides informative guidance for conducting research on rhizosphere multispecies biofilm and identifying representative communities for studying the principles governing interactions among these species.

Exploring Novel Fentanyl Analogues Using a Graph-Based Transformer Model.

The structures of fentanyl and its analogues are easy to be modified and few types have been included in database so far, which allow criminals to avoid the supervision of relevant departments. This paper introduces a molecular graph-based transformer model, which is combined with a data augmentation method based on substructure replacement to generate novel fentanyl analogues. 140,000 molecules were generated, and after a set of screening, 36,799 potential fentanyl analogues were finally obtained. We calculated the molecular properties of 36,799 potential fentanyl analogues. The results showed that the model could learn some properties of original fentanyl molecules. We compared the generated molecules from transformer model and data augmentation method based on substructure replacement with those generated by the other two molecular generation models based on deep learning, and found that the model in this paper can generate more novel potential fentanyl analogues. Finally, the findings of the paper indicate that transformer model based on molecular graph helps us explore the structure of potential fentanyl molecules as well as understand distribution of original molecules of fentanyl.

Efficacy and safety of tibial nerve stimulation using a wearable device for overactive bladder.

OBJECTIVE: To evaluate the efficacy and safety of a wearable, smartphone-controlled, rechargeable transcutaneous tibial nerve stimulation (TTNS) device in patients with overactive bladder (OAB). PATIENTS AND METHODS: This multicentre, prospective, single-blind, randomised clinical trial included eligible patients with OAB symptoms who were randomly assigned to the stimulation group or sham group. The primary efficacy outcome was change from baseline in voiding frequency/24 h after 4 weeks of treatment. The secondary efficacy outcomes included changes in bladder diary outcomes (urgency score/void, nocturia episodes/day, micturition volume/void, and incontinence episodes/day), questionnaires on Overactive Bladder Symptom Score (OABSS), Patient Perception of Bladder Condition (PPBC), and American Urological Association Symptom Index Quality of Life Score (AUA-SI-QoL) at baseline and after 4 weeks of treatment. Device-related adverse events (AEs) were also evaluated. RESULTS: In the full analysis set (FAS), the mean (sd) change of voiding frequency/24 h in the stimulation group and sham group at 4 weeks were -3.5 (2.9) and -0.6 (2.4), respectively (P < 0.01). Similar results were obtained in the per-protocol set (PPS): -3.5 (2.9) vs -0.4 (2.3) (P < 0.01). In the FAS and PPS, micturition volume/void significantly improved at 4 weeks (P = 0.01 and P = 0.02). PPBC improvement almost reached significance in the FAS (P = 0.05), while it was significant in the PPS (P = 0.02). In the FAS and PPS, AUA-SI-QoL significantly improved at 4 weeks in the two groups (P < 0.01 and P < 0.01), whereas there were no significant differences in urgency score/void, nocturia episodes/day or OABSS between the groups. Also, no device-related serious AEs were reported. CONCLUSIONS: The non-invasive neuromodulation technique using the novel ambulatory TTNS device is effective and safe for treating OAB. Its convenience and easy maintenance make it a new potential home-based treatment modality. Future studies are warranted to confirm its longer-term efficacy.

The beneficial rhizobacterium Bacillus velezensis SQR9 regulates plant nitrogen uptake via an endogenous signaling pathway.

Nitrogen fertilizer is widely used in agriculture to boost crop yields. Plant growth-promoting rhizobacteria (PGPRs) can increase plant nitrogen use efficiency through nitrogen fixation and organic nitrogen mineralization. However, it is not known whether they can activate plant nitrogen uptake. In this study, we investigated the effects of volatile compounds (VCs) emitted by the PGPR strain Bacillus velezensis SQR9 on plant nitrogen uptake. Strain SQR9 VCs promoted nitrogen accumulation in both rice and Arabidopsis. In addition, isotope labeling experiments showed that strain SQR9 VCs promoted the absorption of nitrate and ammonium. Several key nitrogen-uptake genes were up-regulated by strain SQR9 VCs, such as AtNRT2.1 in Arabidopsis and OsNAR2.1, OsNRT2.3a, and OsAMT1 family members in rice, and the deletion of these genes compromised the promoting effect of strain SQR9 VCs on plant nitrogen absorption. Furthermore, calcium and the transcription factor NIN-LIKE PROTEIN 7 play an important role in nitrate uptake promoted by strain SQR9 VCs. Taken together, our results indicate that PGPRs can promote nitrogen uptake through regulating plant endogenous signaling and nitrogen transport pathways.

Dissection of rhizosphere microbiome and exploiting strategies for sustainable agriculture.

The rhizosphere microbiome plays critical roles in plant growth and provides promising solutions for sustainable agriculture. While the rhizosphere microbiome frequently fluctuates with the soil environment, recent studies have demonstrated that a small proportion of the microbiome is consistently assembled in the rhizosphere of a specific plant genotype regardless of the soil condition, which is determined by host genetics. Based on these breakthroughs, which involved exploiting the plant-beneficial function of the rhizosphere microbiome, we propose to divide the rhizosphere microbiome into environment-dominated and plant genetic-dominated components based on their different assembly mechanisms. Subsequently, two strategies to explore the different rhizosphere microbiome components for agricultural production are suggested, that is, the precise management of the environment-dominated rhizosphere microbiome by agronomic practices, and the elucidation of the plant genetic basis of the plant genetic-dominated rhizosphere microbiome for breeding microbiome-assisted crop varieties. We finally present the major challenges that need to be overcome to implement strategies for modulating these two components of the rhizosphere microbiome.

GSDMD mediated pyroptosis induced inflammation of Graves' orbitopathy via the NF-κB/ AIM2/ Caspase-1 pathway.

Gasdermin D (GSDMD) is a key executor which triggers pyroptosis as well as an attractive checkpoint in various inflammatory and autoimmune diseases but it has yet to prove its function in Graves'orbitopathy (GO). Our aim was to investigate GSDMD levels in orbital connective tissue and serum of GO patients and then assess the association between serum levels and patients' clinical activity score (CAS). Further, GSDMD-mediated pyroptosis and the underlying mechanism in inflammatory pathogenesis in the cultured orbital fibroblasts (OFs) of GO patients were examined. OFs were collected after tumor necrosis factor (TNF)-α or interferon (IFN)-γ treatment or combination treatment at different times, and the expression of GSDMD and related molecular mechanisms were analyzed. Then, we constructed the GSDMD knockout system with siRNA and the system was further exposed to the medium with or without IFN-γ and TNF-α for a specified time. Finally, we evaluated the production of interleukin (IL)-1ß and IL-18. We found that serum GSDMD levels were elevated and positively correlated with the CAS in GO patients. Meanwhile, the expression of GSDMD and N-terminal domain (NT-GSDMD) in orbital connective tissue of GO patients was augmented. Also, increased expression of GSDMD and related pyroptosis factors was observed in vitro model of GO. We further demonstrated that GSDMD-mediated pyroptosis induced inflammation via the nuclear factor kB (NF-κB)/absent in melanoma-2 (AIM-2)/caspase-1 pathway. In addition, blocking GSDMD suppressed proinflammatory cytokine production in GO. We concluded that GSDMD may be a biomarker as well as a potential target for the evaluation and treatment of inflammation related with GO.

Numerical investigation on the influence of nonuniform tip clearance on rotor tip-clearance flow field structure.

A numerical study was conducted on an axial compressor, the NASA Stage 35, with three nonuniform tip clearances to understand the effect of a different shape tip clearances rotor on the compressor's performance. The results demonstrated that by modifying the traditional parallel tip clearance to sine-type tip clearance (STC), hump-type tip clearance (HTC), and concave-type tip clearance (CTC), the compressor's peak efficiency showed remarkable improvement and the SMI was significantly improved. In comparison to the design rotor, the SMI of STC, HTC, and CTC increased by 3.102 %, 2.672 %, and 0.645 %, respectively. The leakage distribution at the tip-clearance region from LE to TE exhibited an inverse pattern to that of the tip curve. The leakage's magnitude could not reflect the TLF's intensity, and the leakage in the middle of the blade tip had a role in the size of the TLV. Leakage at the tip's TE influenced the corner separation's scale in the casing. The STC and HTC schemes' total pressure ratio improved, the low-velocity zone's area, high-entropy area, and high absolute vorticity area at the LE of rotor's PS decreased, the detached shock moved backward, the leading-edge spillage flow decreased, the shock action position of the rotor suction surface moved forward, the BLS increased, the TPL in the stator channel decreased, and the CTC exhibited the opposite trend. A nonuniform tip clearance was achieved by reducing the leakage and TLV intensity, thereby reducing the size of the TLV, induced vortex, or CSV in rotor passage and increasing the compressor's SMI.

Root colonization by beneficial rhizobacteria.

Rhizosphere microbes play critical roles for plant's growth and health. Among them, the beneficial rhizobacteria have the potential to be developed as the biofertilizer or bioinoculants for sustaining the agricultural development. The efficient rhizosphere colonization of these rhizobacteria is a prerequisite for exerting their plant beneficial functions, but the colonizing process and underlying mechanisms have not been thoroughly reviewed, especially for the nonsymbiotic beneficial rhizobacteria. This review systematically analyzed the root colonizing process of the nonsymbiotic rhizobacteria and compared it with that of the symbiotic and pathogenic bacteria. This review also highlighted the approaches to improve the root colonization efficiency and proposed to study the rhizobacterial colonization from a holistic perspective of the rhizosphere microbiome under more natural conditions.

Tuning the number of redox groups in the cathode toward high rate and long lifespan zinc-ion batteries.

We synthesized a small molecule, DBPTO, and used it as a cathode material in aqueous zinc-ion batteries. DBPTO presented a high reversible capacity of 382 mA h g-1 at 0.05 A g-1 and a long lifespan of over 60 000 cycles. In the same π-conjugated skeleton, DBPTO (containing four CO and two CN groups) shows a narrower energy gap than TAPQ (containing CO and four CN groups), which leads to the superior rate and cycling performance of DBPTO. The mechanism of charge storage of DBPTO also revealed that H+ and Zn2+ coordinated with the CO and CN sites by ex situ structural characterization and DFT calculations. Our results provide new insights into the design of organic cathodes with a high rate capability and long lifespan. Further efforts will focus on a deeper understanding of the charge storage mechanism.

Computer-Aided Diagnosis of Laryngeal Cancer Based on Deep Learning with Laryngoscopic Images.

Laryngeal cancer poses a significant global health burden, with late-stage diagnoses contributing to reduced survival rates. This study explores the application of deep convolutional neural networks (DCNNs), specifically the Densenet201 architecture, in the computer-aided diagnosis of laryngeal cancer using laryngoscopic images. Our dataset comprised images from two medical centers, including benign and malignant cases, and was divided into training, internal validation, and external validation groups. We compared the performance of Densenet201 with other commonly used DCNN models and clinical assessments by experienced clinicians. Densenet201 exhibited outstanding performance, with an accuracy of 98.5% in the training cohort, 92.0% in the internal validation cohort, and 86.3% in the external validation cohort. The area under the curve (AUC) values consistently exceeded 92%, signifying robust discriminatory ability. Remarkably, Densenet201 achieved high sensitivity (98.9%) and specificity (98.2%) in the training cohort, ensuring accurate detection of both positive and negative cases. In contrast, other DCNN models displayed varying degrees of performance degradation in the external validation cohort, indicating the superiority of Densenet201. Moreover, Densenet201's performance was comparable to that of an experienced clinician (Clinician A) and outperformed another clinician (Clinician B), particularly in the external validation cohort. Statistical analysis, including the DeLong test, confirmed the significance of these performance differences. Our study demonstrates that Densenet201 is a highly accurate and reliable tool for the computer-aided diagnosis of laryngeal cancer based on laryngoscopic images. The findings underscore the potential of deep learning as a complementary tool for clinicians and the importance of incorporating advanced technology in improving diagnostic accuracy and patient care in laryngeal cancer diagnosis. Future work will involve expanding the dataset and further optimizing the deep learning model.

Metabolic interactions affect the biomass of synthetic bacterial biofilm communities.

IMPORTANCE: Co-occurrence network analysis is an effective tool for predicting complex networks of microbial interactions in the natural environment. Using isolates from a rhizosphere, we constructed multi-species biofilm communities and investigated co-occurrence patterns between microbial species in genome-scale metabolic models and in vitro experiments. According to our results, metabolic exchanges and resource competition may partially explain the co-occurrence network analysis results found in synthetic bacterial biofilm communities.

Biocontrol mechanisms of Bacillus: Improving the efficiency of green agriculture.

Species of the genus Bacillus have been widely used for the biocontrol of plant diseases in the demand for sustainable agricultural development. New mechanisms underlying Bacillus biocontrol activity have been revealed with the development of microbiome and microbe-plant interaction research. In this review, we first briefly introduce the typical Bacillus biocontrol mechanisms, such as the production of antimicrobial compounds, competition for niches/nutrients, and induction of systemic resistance. Then, we discussed in detail the new mechanisms of pathogen quorum sensing interference and reshaping of the soil microbiota. The "cry for help" mechanism was also introduced, in which plants can release specific signals under pathogen attack to recruit biocontrol Bacillus for root colonization against invasion. Finally, two emerging strategies for enhancing the biocontrol efficacy of Bacillus agents, including the construction of synthetic microbial consortia and the application of rhizosphere-derived prebiotics, were proposed.

Engineering multifunctional rhizosphere probiotics using consortia of Bacillus amyloliquefaciens transposon insertion mutants.

While bacterial diversity is beneficial for the functioning of rhizosphere microbiomes, multi-species bioinoculants often fail to promote plant growth. One potential reason for this is that competition between different species of inoculated consortia members creates conflicts for their survival and functioning. To circumvent this, we used transposon insertion mutagenesis to increase the functional diversity within Bacillus amyloliquefaciens bacterial species and tested if we could improve plant growth promotion by assembling consortia of highly clonal but phenotypically dissimilar mutants. While most insertion mutations were harmful, some significantly improved B. amyloliquefaciens plant growth promotion traits relative to the wild-type strain. Eight phenotypically distinct mutants were selected to test if their functioning could be improved by applying them as multifunctional consortia. We found that B. amyloliquefaciens consortium richness correlated positively with plant root colonization and protection from Ralstonia solanacearum phytopathogenic bacterium. Crucially, 8-mutant consortium consisting of phenotypically dissimilar mutants performed better than randomly assembled 8-mutant consortia, suggesting that improvements were likely driven by consortia multifunctionality instead of consortia richness. Together, our results suggest that increasing intra-species phenotypic diversity could be an effective way to improve probiotic consortium functioning and plant growth promotion in agricultural systems.

EAGMN: Coronary artery semantic labeling using edge attention graph matching network.

Coronary artery disease (CAD) is one of the primary causes leading deaths worldwide. The presence of atherosclerotic lesions in coronary arteries is the underlying pathophysiological basis of CAD, and accurate extraction of individual arterial branches using invasive coronary angiography (ICA) is crucial for stenosis detection and CAD diagnosis. However, deep-learning-based models face challenges in generating semantic segmentation for coronary arteries due to the morphological similarity among different types of arteries. To address this challenge, we propose an innovative approach called the Edge Attention Graph Matching Network (EAGMN) for coronary artery semantic labeling. Inspired by the learning process of interventional cardiologists in interpreting ICA images, our model compares arterial branches between two individual graphs generated from different ICAs. We begin with extracting individual graphs based on the vascular tree obtained from the ICA. Each node in the individual graph represents an arterial segment, and the EAGMN aims to learn the similarity between nodes from the two individual graphs. By converting the coronary artery semantic segmentation task into a graph node similarity comparison task, identifying the node-to-node correspondence would assign semantic labels for each arterial branch. More specifically, the EAGMN utilizes the association graph constructed from the two individual graphs as input. A graph attention module is employed for feature embedding and aggregation, while a decoder generates the linear assignment for node-to-node semantic mapping. Based on the learned node-to-node relationships, unlabeled coronary arterial segments are classified using the labeled coronary arterial segments, thereby achieving semantic labeling. A dataset with 263 labeled ICAs is used to train and validate the EAGMN. Experimental results indicate the EAGMN achieved a weighted accuracy of 0.8653, a weighted precision of 0.8656, a weighted recall of 0.8653 and a weighted F1-score of 0.8643. Furthermore, we employ ZORRO to provide interpretability and explainability of the graph matching for artery semantic labeling. These findings highlight the potential of the EAGMN for accurate and efficient coronary artery semantic labeling using ICAs. By leveraging the inherent characteristics of ICAs and incorporating graph matching techniques, our proposed model provides a promising solution for improving CAD diagnosis and treatment.

Plant immunity suppressor SKRP encodes a novel RNA-binding protein that targets exon 3' end of unspliced RNA.

The regulatory roles of RNA splicing in plant immunity are emerging but still largely obscure. We reported previously that Phytophthora pathogen effector Avr3c targets a soybean protein SKRP (serine/lysine/arginine-rich protein) to impair soybean basal immunity by regulating host pre-mRNA alternative splicing, while the biochemical nature of SKRP remains unknown. Here, by using Arabidopsis as a model, we studied the mechanism of SKRP in regulating pre-mRNA splicing and plant immunity. AtSKRP confers impaired plant immunity against Phytophthora capsici and associates with spliceosome component PRP8 and splicing factor SR45, which positively and negatively regulate plant immunity, respectively. Enhanced crosslinking and immunoprecipitation followed by high-throughput sequencing (eCLIP-seq) showed AtSKRP is a novel RNA-binding protein that targets exon 3' end of unspliced RNA. Such position-specific binding of SKRP is associated with its activity in suppressing intron retention, including at positive immune regulatory genes UBP25 and RAR1. In addition, we found AtSKRP self-interact and forms oligomer, and these properties are associated with its function in plant immunity. Overall, our findings reveal that the immune repressor SKRP is a spliceosome-associated protein that targets exon 3' end to regulate pre-mRNA splicing in Arabidopsis.

B lymphocytes transdifferentiate into immunosuppressive erythroblast-like cells.

Recent studies have demonstrated that a particular group of nucleated cells that exhibit erythroid markers (TER119 in mice and CD235a in humans) possess the ability to suppress the immune system and promote tumor growth. These cells are known as CD45+ erythroid progenitor cells (EPCs). According to our study, it appears that a subset of these CD45+ EPCs originate from B lymphocytes. Under conditions of hypoxia, mouse B lymphoma cells are capable of converting to erythroblast-like cells, which display phenotypes of CD45+TER119+ cells, including immunosuppressive effects on CD8 T cells. Furthermore, non-neoplastic B cells have similar differentiation abilities and exert the same immunosuppressive effect under anemia or tumor conditions in mice. Similar B cells exist in neonatal mice, which provides an explanation for the potential origin of immunosuppressive erythroid cells in newborns. Additionally, CD19+CD235a+ double-positive cells can be identified in the peripheral blood of patients with chronic lymphocytic leukemia. These findings indicate that some CD45+ EPCs are transdifferentiated from a selective population of CD19+ B lymphocytes in response to environmental stresses, highlighting the plasticity of B lymphocytes. We anticipate a potential therapeutic implication, in that targeting a specific set of B cells instead of erythroid cells should be expected to restore adaptive immunity and delay cancer progression.

Research on Photoacoustic Synthetic Aperture Focusing Technology Imaging Method of Internal Defects in Cylindrical Components.

Cylindrical components are parts with curved surfaces, and their high-precision defect testing is of great significance to industrial production. This paper proposes a noncontact internal defect imaging method for cylindrical components, and an automatic photoacoustic testing platform is built. A synthetic aperture focusing technology in the polar coordinate system based on laser ultrasonic (LU-pSAFT) is established, and the relationship between the imaging quality and position of discrete points is analyzed. In order to verify the validity of this method, small holes of Φ0.5 mm in the aluminum alloy rod are tested. During the imaging process, since a variety of waveforms can be excited by the pulsed laser synchronously, the masked longitudinal waves reflected by small holes need to be filtered and windowed to achieve high-quality imaging. In addition, the influence of ultrasonic beam angle and signal array spacing on imaging quality is analyzed. The results show that the method can accurately present the outline of the small hole, the circumferential resolution of the small hole is less than 1° and the dimensional accuracy and position error are less than 0.1 mm.

AGMN: Association Graph-based Graph Matching Network for Coronary Artery Semantic Labeling on Invasive Coronary Angiograms.

Semantic labeling of coronary arterial segments in invasive coronary angiography (ICA) is important for automated assessment and report generation of coronary artery stenosis in computer-aided coronary artery disease (CAD) diagnosis. However, separating and identifying individual coronary arterial segments is challenging because morphological similarities of different branches on the coronary arterial tree and human-to-human variabilities exist. Inspired by the training procedure of interventional cardiologists for interpreting the structure of coronary arteries, we propose an association graph-based graph matching network (AGMN) for coronary arterial semantic labeling. We first extract the vascular tree from invasive coronary angiography (ICA) and convert it into multiple individual graphs. Then, an association graph is constructed from two individual graphs where each vertex represents the relationship between two arterial segments. Thus, we convert the arterial segment labeling task into a vertex classification task; ultimately, the semantic artery labeling becomes equivalent to identifying the artery-to-artery correspondence on graphs. More specifically, the AGMN extracts the vertex features by the embedding module using the association graph, aggregates the features from adjacent vertices and edges by graph convolution network, and decodes the features to generate the semantic mappings between arteries. By learning the mapping of arterial branches between two individual graphs, the unlabeled arterial segments are classified by the labeled segments to achieve semantic labeling. A dataset containing 263 ICAs was employed to train and validate the proposed model, and a five-fold cross-validation scheme was performed. Our AGMN model achieved an average accuracy of 0.8264, an average precision of 0.8276, an average recall of 0.8264, and an average F1-score of 0.8262, which significantly outperformed existing coronary artery semantic labeling methods. In conclusion, we have developed and validated a new algorithm with high accuracy, interpretability, and robustness for coronary artery semantic labeling on ICAs.

Diagnostic Performance and Safety of a Novel Ferumoxytol-Enhanced Coronary Magnetic Resonance Angiography.

BACKGROUND: Currently, noninvasive arteriography for the diagnosis of coronary artery disease is clinically limited to the computed tomography scanning, where patients have to be exposed to the radiation and risks associated with iodinated contrast. We aimed to investigate the diagnostic performance and safety of a novel ferumoxytol-enhanced coronary magnetic resonance angiography (CMRA) in patients with suspected coronary artery disease. METHODS: Thirty patients, 19 males, with a median age of 63 years old, and 17 with renal insufficiency, who were scheduled for invasive coronary angiography, were enrolled. Ferumoxytol was administered intravenously with a dose of 3 mg/kg during CMRA. Images were acquired with an ECG-triggered, navigator-gated, inversion recovery-prepared 3D fast low-angle shot sequence, and the image quality was assessed by a 4-point scale. Eighteen-segment coronary artery model was adopted to evaluate the visibility of the coronary arteries, and the image quality and stenosis were evaluated in nine segments. The diagnostic performance of CMRA is described as sensitivity, specificity, positive and negative predictive values, and accuracy with the invasive coronary angiography results as reference. The patients' vital signs were monitored during CMRA, and their hepatic and renal functions were followed up for 3 months to evaluate the safety of ferumoxytol. RESULTS: Two hundred fifty-two of the 270 study segments were identified by CMRA, and their quality score reached 3.6±0.7. Referring to the invasive coronary angiography results, the sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of ferumoxytol-enhanced CMRA reached 100.0%, 66.7%, 92.3%, 100.0%, and 93.3% respectively in patient-based analysis; 91.4%, 90.9%, 86.5%, 94.3%, and 91.1%, respectively in vessel-based analysis; and 92.3%, 96.7%, 83.7%, 98.6%, and 96.0%, respectively in segment-based analysis. No ferumoxytol-related adverse event was observed during the 3-month follow-up. CONCLUSIONS: Ferumoxytol-enhanced CMRA demonstrated good diagnostic performance and excellent safety in the diagnosis of significant coronary stenosis, providing an alternative to coronary computed tomography angiography for the diagnosis of coronary artery disease. REGISTRATION: URL: https://www. CLINICALTRIALS: gov; Unique identifier: NCT05032937.