Highly accurate classification and discovery of microbial protein-coding gene functions using FunGeneTyper: an extensible deep learning framework.

High-throughput DNA sequencing technologies decode tremendous amounts of microbial protein-coding gene sequences. However, accurately assigning protein functions to novel gene sequences remain a challenge. To this end, we developed FunGeneTyper, an extensible framework with two new deep learning models (i.e., FunTrans and FunRep), structured databases, and supporting resources for achieving highly accurate (Accuracy > 0.99, F1-score > 0.97) and fine-grained classification of antibiotic resistance genes (ARGs) and virulence factor genes. Using an experimentally confirmed dataset of ARGs comprising remote homologous sequences as the test set, our framework achieves by-far-the-best performance in the discovery of new ARGs from human gut (F1-score: 0.6948), wastewater (0.6072), and soil (0.5445) microbiomes, beating the state-of-the-art bioinformatics tools and sequence alignment-based (F1-score: 0.0556-0.5065) and domain-based (F1-score: 0.2630-0.5224) annotation approaches. Furthermore, our framework is implemented as a lightweight, privacy-preserving, and plug-and-play neural network module, facilitating its versatility and accessibility to developers and users worldwide. We anticipate widespread utilization of FunGeneTyper (https://github.com/emblab-westlake/FunGeneTyper) for precise classification of protein-coding gene functions and the discovery of numerous valuable enzymes. This advancement will have a significant impact on various fields, including microbiome research, biotechnology, metagenomics, and bioinformatics.

CyclicPepedia: a knowledge base of natural and synthetic cyclic peptides.

Cyclic peptides offer a range of notable advantages, including potent antibacterial properties, high binding affinity and specificity to target molecules, and minimal toxicity, making them highly promising candidates for drug development. However, a comprehensive database that consolidates both synthetically derived and naturally occurring cyclic peptides is conspicuously absent. To address this void, we introduce CyclicPepedia (https://www.biosino.org/iMAC/cyclicpepedia/), a pioneering database that encompasses 8744 known cyclic peptides. This repository, structured as a composite knowledge network, offers a wealth of information encompassing various aspects of cyclic peptides, such as cyclic peptides' sources, categorizations, structural characteristics, pharmacokinetic profiles, physicochemical properties, patented drug applications, and a collection of crucial publications. Supported by a user-friendly knowledge retrieval system and calculation tools specifically designed for cyclic peptides, CyclicPepedia will be able to facilitate advancements in cyclic peptide drug development.

A deep learning-based method enables the automatic and accurate assembly of chromosome-level genomes.

The application of high-throughput chromosome conformation capture (Hi-C) technology enables the construction of chromosome-level assemblies. However, the correction of errors and the anchoring of sequences to chromosomes in the assembly remain significant challenges. In this study, we developed a deep learning-based method, AutoHiC, to address the challenges in chromosome-level genome assembly by enhancing contiguity and accuracy. Conventional Hi-C-aided scaffolding often requires manual refinement, but AutoHiC instead utilizes Hi-C data for automated workflows and iterative error correction. When trained on data from 300+ species, AutoHiC demonstrated a robust average error detection accuracy exceeding 90%. The benchmarking results confirmed its significant impact on genome contiguity and error correction. The innovative approach and comprehensive results of AutoHiC constitute a breakthrough in automated error detection, promising more accurate genome assemblies for advancing genomics research.

RefMetaPlant: a reference metabolome database for plants across five major phyla.

Plants are unique with tremendous chemical diversity and metabolic complexity, which is highlighted by estimates that green plants collectively produce metabolites numbering in the millions. Plant metabolites play crucial roles in all aspects of plant biology, like growth, development, stress responses, etc. However, the lack of a reference metabolome for plants, and paucity of high-quality standard compound spectral libraries and related analytical tools, have hindered the discovery and functional study of phytochemicals in plants. Here, by leveraging an advanced LC-MS platform, we generated untargeted mass spectral data from >150 plant species collected across the five major phyla. Using a self-developed computation protocol, we constructed reference metabolome for 153 plant species. A 'Reference Metabolome Database for Plants' (RefMetaPlant) was built to encompass the reference metabolome, integrated standard compound mass spectral libraries for annotation, and related query and analytical tools like 'LC-MS/MS Query', 'RefMetaBlast' and 'CompoundLibBlast' for searches and profiling of plant metabolome and metabolite identification. Analogous to a reference genome in genomic research, RefMetaPlant provides a powerful platform to support plant genome-scale metabolite analysis to promote knowledge/data sharing and collaboration in the field of metabolomics. RefMetaPlant is freely available at https://www.biosino.org/RefMetaDB/.

Rapid multiple protein sequence search by parallel and heterogeneous computation.

MOTIVATION: Protein sequence database search and multiple sequence alignment generation is a fundamental task in many bioinformatics analyses. As the data volume of sequences continues to grow rapidly, there is an increasing need for efficient and scalable multiple sequence query algorithms for super-large databases without expensive time and computational costs. RESULTS: We introduce Chorus, a novel protein sequence query system that leverages parallel model and heterogeneous computation architecture to enable users to query thousands of protein sequences concurrently against large protein databases on a desktop workstation. Chorus achieves over 100× speedup over BLASTP without sacrificing sensitivity. We demonstrate the utility of Chorus through a case study of analyzing a ∼1.5-TB large-scale metagenomic datasets for novel CRISPR-Cas protein discovery within 30 min. AVAILABILITY AND IMPLEMENTATION: Chorus is open-source and its code repository is available at https://github.com/Bio-Acc/Chorus.

PGG.SV: a whole-genome-sequencing-based structural variant resource and data analysis platform.

Structural variations (SVs) play important roles in human evolution and diseases, but there is a lack of data resources concerning representative samples, especially for East Asians. Taking advantage of both next-generation sequencing and third-generation sequencing data at the whole-genome level, we developed the database PGG.SV to provide a practical platform for both regionally and globally representative structural variants. In its current version, PGG.SV archives 584 277 SVs obtained from whole-genome sequencing data of 6048 samples, including 1030 long-read sequencing genomes representing 177 global populations. PGG.SV provides (i) high-quality SVs with fine-scale and precise genomic locations in both GRCh37 and GRCh38, covering underrepresented SVs in existing sequencing and microarray data; (ii) hierarchical estimation of SV prevalence in geographical populations; (iii) informative annotations of SV-related genes, potential functions and clinical effects; (iv) an analysis platform to facilitate SV-based case-control association studies and (v) various visualization tools for understanding the SV structures in the human genome. Taken together, PGG.SV provides a user-friendly online interface, easy-to-use analysis tools and a detailed presentation of results. PGG.SV is freely accessible via https://www.biosino.org/pggsv.

SMDB: a Spatial Multimodal Data Browser.

Understanding the relationship between fine-scale spatial organization and biological function necessitates a tool that effectively combines spatial positions, morphological information, and spatial transcriptomics (ST) data. We introduce the Spatial Multimodal Data Browser (SMDB, https://www.biosino.org/smdb), a robust visualization web service for interactively exploring ST data. By integrating multimodal data, such as hematoxylin and eosin (H&E) images, gene expression-based molecular clusters, and more, SMDB facilitates the analysis of tissue composition through the dissociation of two-dimensional (2D) sections and the identification of gene expression-profiled boundaries. In a digital three-dimensional (3D) space, SMDB allows researchers to reconstruct morphology visualizations based on manually filtered spots or expand anatomical structures using high-resolution molecular subtypes. To enhance user experience, it offers customizable workspaces for interactive exploration of ST spots in tissues, providing features like smooth zooming, panning, 360-degree rotation in 3D and adjustable spot scaling. SMDB is particularly valuable in neuroscience and spatial histology studies, as it incorporates Allen's mouse brain anatomy atlas for reference in morphological research. This powerful tool provides a comprehensive and efficient solution for examining the intricate relationships between spatial morphology, and biological function in various tissues.

Chemistry-informed molecular graph as reaction descriptor for machine-learned retrosynthesis planning.

Infusing "chemical wisdom" should improve the data-driven approaches that rely exclusively on historical synthetic data for automatic retrosynthesis planning. For this purpose, we designed a chemistry-informed molecular graph (CIMG) to describe chemical reactions. A collection of key information that is most relevant to chemical reactions is integrated in CIMG:NMR chemical shifts as vertex features, bond dissociation energies as edge features, and solvent/catalyst information as global features. For any given compound as a target, a product CIMG is generated and exploited by a graph neural network (GNN) model to choose reaction template(s) leading to this product. A reactant CIMG is then inferred and used in two GNN models to select appropriate catalyst and solvent, respectively. Finally, a fourth GNN model compares the two CIMG descriptors to check the plausibility of the proposed reaction. A reaction vector is obtained for every molecule in training these models. The chemical wisdom of reaction propensity contained in the pretrained reaction vectors is exploited to autocategorize molecules/reactions and to accelerate Monte Carlo tree search (MCTS) for multistep retrosynthesis planning. Full synthetic routes with recommended catalysts/solvents are predicted efficiently using this CIMG-based approach.

Iron-Catalyzed Primary Amination of C(sp3)-H Bonds.

Primary amines are privileged molecules in drug development. Yet, there is a noticeable scarcity of methods for directly introducing a primary amine group into the ubiquitous C(sp3)-H bonds within organic compounds. Here, we report an iron-based catalytic system that enables direct primary amination of C(sp3)-H bonds under aqueous conditions and air. Various types of C(sp3)-H bonds, including benzylic, allylic, and aliphatic ones, can be readily functionalized with high selectivity and efficiency. The broad utility of this method has been further verified by late-stage amination of 11 complex bioactive molecules. Mechanistic studies unveil a protonated iron-nitrene complex as the key intermediate for the C-H bond activation. This work extends the toolbox for direct C(sp3)-H functionalizations, opening up new opportunities for late-stage modifications of organic molecules.

A Noncoding A-to-U Kozak Site Change Related to the High Transmissibility of Alpha, Delta, and Omicron VOCs.

Three prevalent SARS-CoV-2 variants of concern (VOCs) emerged and caused epidemic waves. It is essential to uncover advantageous mutations that cause the high transmissibility of VOCs. However, viral mutations are tightly linked, so traditional population genetic methods, including machine learning-based methods, cannot reliably detect mutations conferring a fitness advantage. In this study, we developed an approach based on the sequential occurrence order of mutations and the accelerated furcation rate in the pandemic-scale phylogenomic tree. We analyzed 3,777,753 high-quality SARS-CoV-2 genomic sequences and the epidemiology metadata using the Coronavirus GenBrowser. We found that two noncoding mutations at the same position (g.a28271-/u) may be crucial to the high transmissibility of Alpha, Delta, and Omicron VOCs although the noncoding mutations alone cannot increase viral transmissibility. Both mutations cause an A-to-U change at the core position -3 of the Kozak sequence of the N gene and significantly reduce the protein expression ratio of ORF9b to N. Using a convergent evolutionary analysis, we found that g.a28271-/u, S:p.P681H/R, and N:p.R203K/M occur independently on three VOC lineages, suggesting that coordinated changes of S, N, and ORF9b proteins are crucial to high viral transmissibility. Our results provide new insights into high viral transmissibility co-modulated by advantageous noncoding and nonsynonymous changes.

Isolation and Identification of Salinity-Tolerant Rhizobia and Nodulation Phenotype Analysis in Different Soybean Germplasms.

Increasing the soybean-planting area and increasing the soybean yield per unit area are two effective solutions to improve the overall soybean yield. Northeast China has a large saline soil area, and if soybeans could be grown there with the help of isolated saline-tolerant rhizobia, the soybean cultivation area in China could be effectively expanded. In this study, soybeans were planted in soils at different latitudes in China, and four strains of rhizobia were isolated and identified from the soybean nodules. According to the latitudes of the soil-sampling sites from high to low, the four isolated strains were identified as HLNEAU1, HLNEAU2, HLNEAU3, and HLNEAU4. In this study, the isolated strains were identified for their resistances, and their acid and saline tolerances and nitrogen fixation capacities were preliminarily identified. Ten representative soybean germplasm resources in Northeast China were inoculated with these four strains, and the compatibilities of these four rhizobium strains with the soybean germplasm resources were analyzed. All four isolates were able to establish different extents of compatibility with 10 soybean resources. Hefeng 50 had good compatibility with the four isolated strains, while Suinong 14 showed the best compatibility with HLNEAU2. The isolated rhizobacteria could successfully establish symbiosis with the soybeans, but host specificity was also present. This study was a preliminary exploration of the use of salinity-tolerant rhizobacteria to help the soybean nitrogen fixation in saline soils in order to increase the soybean acreage, and it provides a valuable theoretical basis for the application of saline-tolerant rhizobia.

Coronavirus GenBrowser for monitoring the transmission and evolution of SARS-CoV-2.

Genomic epidemiology is important to study the COVID-19 pandemic, and more than two million severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomic sequences were deposited into public databases. However, the exponential increase of sequences invokes unprecedented bioinformatic challenges. Here, we present the Coronavirus GenBrowser (CGB) based on a highly efficient analysis framework and a node-picking rendering strategy. In total, 1,002,739 high-quality genomic sequences with the transmission-related metadata were analyzed and visualized. The size of the core data file is only 12.20 MB, highly efficient for clean data sharing. Quick visualization modules and rich interactive operations are provided to explore the annotated SARS-CoV-2 evolutionary tree. CGB binary nomenclature is proposed to name each internal lineage. The pre-analyzed data can be filtered out according to the user-defined criteria to explore the transmission of SARS-CoV-2. Different evolutionary analyses can also be easily performed, such as the detection of accelerated evolution and ongoing positive selection. Moreover, the 75 genomic spots conserved in SARS-CoV-2 but non-conserved in other coronaviruses were identified, which may indicate the functional elements specifically important for SARS-CoV-2. The CGB was written in Java and JavaScript. It not only enables users who have no programming skills to analyze millions of genomic sequences, but also offers a panoramic vision of the transmission and evolution of SARS-CoV-2.

Real-world effectiveness and safety of recombinant human endostatin plus PD-1 inhibitors and chemotherapy as first-line treatment for EGFR/ALK-negative, advanced or metastatic non-small cell lung cancer.

BACKGROUND: This study aimed to evaluate the effectiveness and safety of recombinant human endostatin (Rh-endostatin) plus programmed cell death 1 (PD-1) inhibitors and chemotherapy as first-line treatment for advanced or metastatic non-small cell lung cancer (NSCLC) in a real-world setting. METHODS: This was a retrospective study on patients with EGFR/ALK-negative, advanced or metastatic NSCLC. Patients received Rh-endostatin plus PD-1 inhibitors and chemotherapy every three weeks for 4 to 6 cycles. The primary endpoint was progression-free survival (PFS), and the secondary endpoints were objective response rate (ORR), disease control rate (DCR), overall survival (OS), and safety. RESULTS: A total of 68 patients were included in this retrospective analysis. As of data cutoff (December 13, 2022), the median follow-up of 21.4 months (interquartile range [IQR], 8.3-44.4 months). The median PFS and OS was 22.0 (95% confidence interval [CI]: 16.6-27.4) and 31.0 months (95% CI: 23.4-not evaluable [NE]), respectively. The ORR was 72.06% (95% CI: 59.85-82.27%), and DCR was 95.59% (95% CI: 87.64-99.08%). Patients with stage IIIB/IIIC NSCLC had significantly longer median PFS (23.4 vs. 13.2 months), longer median OS (not reached vs. 18.0 months), and higher ORR (89.2% vs. 51.6%) than those with stage IV NSCLC (all p ≤ 0.001). The ORR was higher in patients with high PD-L1 expression (tumor proportion score [TPS] ≥ 50%) than in those with low PD-L1 expression or positive PD-L1 expression (75% vs. 50%, p = 0.025). All patients experienced treatment-related adverse events (TRAEs), and ≥ grade 3 TRAEs occurred in 16 (23.53%) patients. CONCLUSIONS: Rh-endostatin combined with PD-1 inhibitors plus chemotherapy as first-line treatment yielded favorable effectiveness with a manageable profile in patients with advanced or metastatic NSCLC, representing a promising treatment modality.

Impact of the COVID-19 infection on children with allergic diseases in China.

BACKGROUND: The COVID-19 pandemic has prompted investigations into the association between this novel virus and allergic diseases, particularly asthma in children. However, the nature of this relationship remains poorly established. OBJECTIVE: This study aims to determine the clinical characteristics of children with allergic diseases who have contracted COVID-19. METHODS: A retrospective study was conducted at the Children's Hospital Affiliated to the Capital Institute of Pediatrics from January to March 2023. A total of 568 children aged 0-17 years diagnosed with asthma and COVID-19 infection were included. A comparative analysis of clinical characteristics was conducted between asthma and non-asthma groups. RESULTS: Asthmatic children with COVID-19 infection showed significantly higher frequencies of cough, wheezing, expectoration, and long-term symptoms compared to those without asthma (P < 0.05). Subgroups with poor therapy compliance exhibited elevated proportions of cough, chest tightness, and wheezing compared to good therapy compliance (P < 0.05). Multivariate logistic regression identified poor therapy compliance as a risk factor for long COVID in asthmatic children. CONCLUSION: Children with asthma secondary to COVID-19 infection were more prone to developing coughs, expectoration, and wheezing. Poor therapy compliance emerged as a significant risk factor for long COVID-19 in these individuals. IMPACT: Asthmatic children with COVID-19 infection showed significantly higher frequencies of cough, wheezing, expectoration. Poor therapy compliance was the risk factor for long COVID in asthmatic children. This article supplements the effects of different therapeutic drugs on the condition of children with asthma after infection with COVID-19 as well as the possible risk factors for the long COVID. The results of our study have important implications for public health policy makers and healthcare professionals. To understand the impact of COVID-19 on children with asthma will help guide appropriate management strategies and ensure access to necessary healthcare resources.

NAFLDkb: A Knowledge Base and Platform for Drug Development against Nonalcoholic Fatty Liver Disease.

Nonalcoholic fatty liver disease (NAFLD) is the most common chronic liver disease with a broad spectrum of histologic manifestations. The rapidly growing prevalence and the complex pathologic mechanisms of NAFLD pose great challenges for treatment development. Despite tremendous efforts devoted to drug development, there are no FDA-approved medicines yet. Here, we present NAFLDkb, a specialized knowledge base and platform for computer-aided drug design against NAFLD. With multiperspective information curated from diverse source materials and public databases, NAFLDkb presents the associations of drug-related entities as individual knowledge graphs. Practical drug discovery tools that facilitate the utilization and expansion of NAFLDkb have also been implemented in the web interface, including chemical structure search, drug-likeness screening, knowledge-based repositioning, and research article annotation. Moreover, case studies of a knowledge graph repositioning model and a generative neural network model are presented herein, where three repositioning drug candidates and 137 novel lead-like compounds were newly established as NAFLD pharmacotherapy options reusing data records and machine learning tools in NAFLDkb, suggesting its clinical reliability and great potential in identifying novel drug-disease associations of NAFLD and generating new insights to accelerate NAFLD drug development. NAFLDkb is freely accessible at https://www.biosino.org/nafldkb and will be updated periodically with the latest findings.

First-principles studies on the electronic and contact properties of monolayer Ga2STe-metal contacts.

Monolayer (ML) Janus III-VI compounds have attracted the use of multiple competitive platforms for future-generation functional electronics, including non-volatile memories, field effect transistors, and sensors. In this work, the electronic and interfacial properties of ML Ga2STe-metal (Au, Ag, Cu, and Al) contacts are systematically investigated using first-principles calculations combined with the non-equilibrium Green's function method. The ML Ga2STe-Au/Ag/Al contacts exhibit weak electronic orbital hybridization at the interface, while the ML Ga2STe-Cu contact exhibits strong electronic orbital hybridization. The Te surface is more conducive to electron injection than the S surface in ML Ga2STe-metal contact. Quantum transport calculations revealed that when the Te side of the ML Ga2STe is in contact with Au, Ag and Cu electrodes, p-type Schottky contacts are formed. When in contact with the Al electrode, an n-type Schottky contact is formed with an electron SBH of 0.079 eV. When the S side of ML Ga2STe is in contact with Au and Al electrodes, p-type Schottky contacts are formed, and when it is in contact with Ag and Cu electrodes, n-type Schottky contacts are formed. Our study will guide the selection of appropriate metal electrodes for constructing ML Ga2STe devices.

The diversity and biogeography of bacterial communities in lake sediments across different climate zones.

Bacteria are diverse and play important roles in biogeochemical cycling of aquatic ecosystems, but the global distribution patterns of bacterial communities in lake sediments across different climate zones are still obscure. Here we integrated the high-throughput sequencing data of 750 sediment samples from published literature to investigate the distribution of bacterial communities in different climate zones and the potential driving mechanisms. The obtained results indicated that the diversity and richness of bacterial community were notably higher in temperate and cold zones than those in other climate zones. In addition, the bacterial community composition varied significantly in different climate zones, which further led to changes in bacterial functional groups. Specifically, the relative abundance of nitrogen cycling functional groups in polar zones was notably higher compared to other climate zones. Regression analysis revealed that climate (mean annual precipitation, MAP; and mean annual temperature, MAT), vegetation, and geography together determined the diversity pattern of sediment bacterial community on a global scale. The results of partial least squares path modeling further demonstrated that climate was the most significant factor affecting the composition and diversity of bacterial communities, and MAP was the most important climate factor affecting the composition of bacteria community (R2 = 0.443, P < 0.001). It is worth noting that a strong positive correlation was observed between the abundance of the dominant bacterial group uncultured_f_Anaerolineaceae and the normalized difference vegetation index (NDVI; P < 0.001), suggesting that vegetation could affect bacterial community diversity by influencing dominant bacterial taxa. This study enhances our understanding of the global diversity patterns and biogeography of sediment bacteria.

Management of esophageal cancer in patients with a right aortic arch or double aortic arch: a case series of 34 cases.

BACKGROUND: Few cases describing patients with a right aortic arch (RAA) or double aortic arch (DAA) and esophageal cancer (EC) have been reported. METHODS: We analyzed RAA and DAA cases treated with esophagectomy in our center's database and reported in English-language studies until April 1, 2023. Our study assessed the malformation characteristics and surgical details of EC patients with RAA and DAA. RESULTS: We extracted data of 24 EC patients with RAAs and 10 EC patients with DAAs. In both groups, the patients were more likely to be Japanese and male, to have squamous cell carcinoma and to have tumors located in the upper thoracic esophagus or middle thoracic esophagus. Left thoracotomy was commonly applied for RAA patients. For DAA patients, the proportions of left-sided and right-sided approaches were similar. Esophagectomy under video-assisted thoracoscopic surgery (VATS) in RAA or DAA patients had been performed on a routine basis in recent years. There were two anastomotic leakages in each group. Specifically, Kommerell diverticulum rupture occurred in 1 RAA patient; gastric tube dilation occurred in 1 DAA patient; and recurrent laryngeal nerve (RLN) injury occurred in 2 RAA patients. The postoperative course was uneventful for most patients in both cohorts. CONCLUSIONS: Esophageal carcinoma is rarely seen in patients with an RAA or DAA. To adequately dissect superior mediastinal LNs, an auxiliary incision (such as sternotomy), the left door open method or a preceding cervical procedure should be used appropriately. Esophagectomy, whether via thoracotomy or thoracoscopic surgery, can be performed safely for both RAA and DAA.

Balancing thermodynamic stability, dynamics, and kinetics in phase separation of intrinsically disordered proteins.

Intrinsically disordered proteins (IDPs) are prevalent participants in liquid-liquid phase separation due to their inherent potential for promoting multivalent binding. Understanding the underlying mechanisms of phase separation is challenging, as phase separation is a complex process, involving numerous molecules and various types of interactions. Here, we used a simplified coarse-grained model of IDPs to investigate the thermodynamic stability of the dense phase, conformational properties of IDPs, chain dynamics, and kinetic rates of forming condensates. We focused on the IDP system, in which the oppositely charged IDPs are maximally segregated, inherently possessing a high propensity for phase separation. By varying interaction strengths, salt concentrations, and temperatures, we observed that IDPs in the dense phase exhibited highly conserved conformational characteristics, which are more extended than those in the dilute phase. Although the chain motions and global conformational dynamics of IDPs in the condensates are slow due to the high viscosity, local chain flexibility at the short timescales is largely preserved with respect to that at the free state. Strikingly, we observed a non-monotonic relationship between interaction strengths and kinetic rates for forming condensates. As strong interactions of IDPs result in high stable condensates, our results suggest that the thermodynamics and kinetics of phase separation are decoupled and optimized by the speed-stability balance through underlying molecular interactions. Our findings contribute to the molecular-level understanding of phase separation and offer valuable insights into the developments of engineering strategies for precise regulation of biomolecular condensates.

The relationship between tricuspid annular plane systolic excursion on transesophageal echocardiography and the incidence of postoperative acute kidney injury in patients undergoing coronary artery bypass grafting surgery: a multicenter prospective cohort study.

BACKGROUND: To date, the relationship between the Transesophageal Echocardiography (TEE) monitoring indicator tricuspid annular plane systolic excursion (TAPSE) and the incidence of postoperative acute kidney injury (AKI) in Coronary Artery Bypass Grafting(CABG) patients remains unknown. The main objective of this study was to explore the relationship between the TAPSE and the incidence of AKI in CABG patients. METHODS: This was a multicenter prospective cohort study was conducted between September 2021 and July 2022. Among 266 patients aged at least 18 years who underwent elective CABG, 140 were included. RESULTS: We measured TAPSE via M-mode TEE via the mid-esophageal (ME) right ventricle(RV) inflow-outflow view (60°). All echocardiographic measurements were performed three separate times at each time point: T0 (before the start of CABG), T2 (approximately 5 ∼ 10 min after neutralization of protamine) and T3 (before leaving the operating room), and then averaged. Serum creatinine was measured 1 day before and within 7 days after CABG. There was no statistically significant association between the TEE-monitoring indicator TAPSE and the incidence of postoperative AKI in patients who underwent CABG. CONCLUSIONS: The TAPSE was not significantly correlated with postoperative AKI incidence and could not predict the early occurrence of postoperative AKI in CABG patients. TEE needs more evaluation for clinical efficacy of predicting the early occurrence of postoperative AKI in isolated CABG.