CRISPR-Mediated Programmable 3D Genome Positioning and Nuclear Organization.

Programmable control of spatial genome organization is a powerful approach for studying how nuclear structure affects gene regulation and cellular function. Here, we develop a versatile CRISPR-genome organization (CRISPR-GO) system that can efficiently control the spatial positioning of genomic loci relative to specific nuclear compartments, including the nuclear periphery, Cajal bodies, and promyelocytic leukemia (PML) bodies. CRISPR-GO is chemically inducible and reversible, enabling interrogation of real-time dynamics of chromatin interactions with nuclear compartments in living cells. Inducible repositioning of genomic loci to the nuclear periphery allows for dissection of mitosis-dependent and -independent relocalization events and also for interrogation of the relationship between gene position and gene expression. CRISPR-GO mediates rapid de novo formation of Cajal bodies at desired chromatin loci and causes significant repression of endogenous gene expression over long distances (30-600 kb). The CRISPR-GO system offers a programmable platform to investigate large-scale spatial genome organization and function.

Interrogation of the dynamic properties of higher-order heterochromatin using CRISPR-dCas9.

Eukaryotic chromosomes feature large regions of compact, repressed heterochromatin hallmarked by Heterochromatin Protein 1 (HP1). HP1 proteins play multi-faceted roles in shaping heterochromatin, and in cells, HP1 tethering to individual gene promoters leads to epigenetic modifications and silencing. However, emergent properties of HP1 at supranucleosomal scales remain difficult to study in cells because of a lack of appropriate tools. Here, we develop CRISPR-engineered chromatin organization (EChO), combining live-cell CRISPR imaging with inducible large-scale recruitment of chromatin proteins to native genomic targets. We demonstrate that human HP1α tiled across kilobase-scale genomic DNA form novel contacts with natural heterochromatin, integrates two distantly targeted regions, and reversibly changes chromatin from a diffuse to compact state. The compact state exhibits delayed disassembly kinetics and represses transcription across over 600 kb. These findings support a polymer model of HP1α-mediated chromatin regulation and highlight the utility of CRISPR-EChO in studying supranucleosomal chromatin organization in living cells.

Characterization of the bone marrow niche in patients with chronic myeloid leukemia identifies CXCL14 as a new therapeutic option.

Although tyrosine kinase inhibitors (TKIs) are effective in treating chronic myeloid leukemia (CML), they often fail to eradicate the leukemia-initiating stem cells (LSCs), causing disease persistence and relapse. Evidence indicates that LSC persistence may be because of bone marrow (BM) niche protection; however, little is known about the underlying mechanisms. Herein, we molecularly and functionally characterize BM niches in patients with CML at diagnosis and reveal the altered niche composition and function in these patients. Long-term culture initiating cell assay showed that the mesenchymal stem cells from patients with CML displayed an enhanced supporting capacity for normal and CML BM CD34+CD38- cells. Molecularly, RNA sequencing detected dysregulated cytokine and growth factor expression in the BM cellular niches of patients with CML. Among them, CXCL14 was lost in the BM cellular niches in contrast to its expression in healthy BM. Restoring CXCL14 significantly inhibited CML LSC maintenance and enhanced their response to imatinib in vitro, and CML engraftment in vivo in NSG-SGM3 mice. Importantly, CXCL14 treatment dramatically inhibited CML engraftment in patient-derived xenografted NSG-SGM3 mice, even to a greater degree than imatinib, and this inhibition persisted in patients with suboptimal TKI response. Mechanistically, CXCL14 upregulated inflammatory cytokine signaling but downregulated mTOR signaling and oxidative phosphorylation in CML LSCs. Together, we have discovered a suppressive role of CXCL14 in CML LSC growth. CXCL14 might offer a treatment option targeting CML LSCs.

Identification of biomarkers and potential therapeutic targets of kidney stone disease using bioinformatics.

PURPOSE: Kidney stone disease (KSD) is a common urological disease, but its pathogenesis remains unclear. In this study, we screened KSD-related hub genes using bioinformatic methods and predicted the related pathways and potential drug targets. METHODS: The GSE75542 and GSE18160 datasets in the Gene Expression Omnibus (GEO) were selected to identify common differentially expressed genes (DEGs). We conducted Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses to identify enriched pathways. Finally, we constructed a hub gene-miRNA network and drug-DEG interaction network. RESULTS: In total, 44 upregulated DEGs and 1 downregulated DEG were selected from the GEO datasets. Signaling pathways, such as leukocyte migration, chemokine activity, NF-κB, TNF, and IL-17, were identified in GO and KEGG. We identified 10 hub genes using Cytohubba. In addition, 21 miRNAs were predicted to regulate 4 or more hub genes, and 10 drugs targeted 2 or more DEGs. LCN2 expression was significantly different between the GEO datasets. Quantitative real-time polymerase chain reaction (qRT-PCR) analyses showed that seven hub gene expressions in HK-2 cells with CaOx treatment were significantly higher than those in the control group. CONCLUSION: The 10 hub genes identified, especially LCN2, may be involved in kidney stone occurrence and development, and may provide new research targets for KSD diagnosis. Furthermore, KSD-related miRNAs may be targeted for the development of novel drugs for KSD treatment.

Product Selection Toward High-Value Hydrogen and Bamboo-Shaped Carbon Nanotubes from Plastic Waste by Catalytic Microwave Processing.

The escalating levels of plastic waste and energy crises underscore the urgent need for effective waste-to-energy strategies. This study focused on converting polypropylene wastes into high-value products employing various iron-based catalysts and microwave radiative thermal processing. The Al-Fe catalysts exhibited exceptional performance, achieving a hydrogen utilization efficiency of 97.65% and a yield of 44.07 mmol/g PP. The gas yields increased from 19.99 to 94.21 wt % compared to noncatalytic experiments. Furthermore, this catalytic system produced high-value bamboo-shaped carbon nanotubes that were absent in other catalysts. The mechanism analysis on catalytic properties and product yields highlighted the significance of oxygen vacancies in selecting high-value products through two adsorption pathways. Moreover, the investigation examined the variations in product distribution mechanisms between conventional and microwave pyrolysis, in which microwave conditions resulted in 4 times higher hydrogen yields. The technoeconomic assessment and Monte Carlo risk analysis further compared the disparity. The microwave technique had a remarkable internal rate of return (IRR) of 39%, leading to an income of $577/t of plastic with a short payback period of 2.5 years. This research offered sustainable solutions for the plastic crisis, validating the potential applicability of commercializing the research outcomes in real-world scenarios.

A Knowledge-Data Dual-Driven Framework for Predicting the Molecular Properties of Rechargeable Battery Electrolytes.

Developing rechargeable batteries that operate within a wide temperature range and possess high safety has become necessary with increasing demands. Rapid and accurate assessment of the melting points (MPs), boiling points (BPs), and flash points (FPs) of electrolyte molecules is essential for expediting battery development. Herein, we introduce Knowledge-based electrolyte Property prediction Integration (KPI), a knowledge-data dual-driven framework for molecular property prediction of electrolytes. Initially, the KPI collects molecular structures and properties, and then automatically organizes them into structured datasets. Subsequently, interpretable machine learning further explores the structure-property relationships of molecules from a microscopic perspective. Finally, by embedding the discovered knowledge into property prediction models, the KPI achieved very low mean absolute errors of 10.4, 4.6, and 4.8 K for MP, BP, and FP predictions, respectively. The KPI reached state-of-the-art results in 18 out of 20 datasets. Utilizing molecular neighbor search and high-throughput screening, 15 and 14 promising molecules, with and without Chemical Abstracts Service Registry Number, respectively, were predicted for wide-temperature-range and high-safety batteries. The KPI not only accurately predicts molecular properties and deepens the understanding of structure-property relationships but also serves as an efficient framework for integrating artificial intelligence and  domain knowledge.

OTUD4 regulates metastasis and chemoresistance in melanoma by stabilizing Snail1.

Melanoma is the most aggressive form of skin cancer with rapidly increased incidence worldwide especially in the Caucasian population. Surgical excision represents the curative treatment choice in patients with early-stage disease. However, the therapeutic outcomes in patients with metastatic melanoma remains unsatisfactory. Thus, understanding molecular mechanisms contributing to metastasis and chemoresistance is critical for new improved therapies of melanoma. Snail1, an important epithelial-mesenchymal transition transcription factors (EMT-TFs), is critical to induce the EMT process, thereby contributing to cancer metastasis. However, the involvement of Snail1 in melanoma metastasis remains elusive and the underlying mechanism to regulate Snail1 in melanoma needs to be further investigated. Here, we identified OTUD4 as a novel deubiquitinase of Snail1 in melanoma. Moreover, the depletion of OTUD4 in melanoma cells markedly inhibited Snail1 stability and Snail1-driven malignant phenotypes both in vitro and in vivo. Overall, our study establishes OTUD4 as a novel therapeutic target in metastasis and chemoresistance of melanoma by stabilizing Snail1 and provides a rationale for potential therapeutic strategies of melanoma.

Data-Driven Insight into the Reductive Stability of Ion-Solvent Complexes in Lithium Battery Electrolytes.

Lithium (Li) metal batteries (LMBs) are regarded as one of the most promising energy storage systems due to their ultrahigh theoretical energy density. However, the high reactivity of the Li anodes leads to the decomposition of the electrolytes, presenting a huge impediment to the practical application of LMBs. The routine trial-and-error methods are inefficient in designing highly stable solvent molecules for the Li metal anode. Herein, a data-driven approach is proposed to probe the origin of the reductive stability of solvents and accelerate the molecular design for advanced electrolytes. A large database of potential solvent molecules is first constructed using a graph theory-based algorithm and then comprehensively investigated by both first-principles calculations and machine learning (ML) methods. The reductive stability of 99% of the electrolytes decreases under the dominance of ion-solvent complexes, according to the analysis of the lowest unoccupied molecular orbital (LUMO). The LUMO energy level is related to the binding energy, bond length, and orbital ratio factors. An interpretable ML method based on Shapley additive explanations identifies the dipole moment and molecular radius as the most critical descriptors affecting the reductive stability of coordinated solvents. This work not only affords fruitful data-driven insight into the ion-solvent chemistry but also unveils the critical molecular descriptors in regulating the solvent's reductive stability, which accelerates the rational design of advanced electrolyte molecules for next-generation Li batteries.

Molecular analysis of phenotypic heterogeneity in JAK2V617F-positive myeloproliferative neoplasms reveals a potential target for therapy.

JAK2V617F is the most frequent mutation in BCR-ABL-negative myeloproliferative neoplasms (MPNs). It is an important but not the only determinant of MPN phenotype. We performed high-throughput sequencing on JAK2V617F+ essential thrombocythaemia (ET) and polycythaemia vera (PV) patient samples to unveil factors involved in phenotypic heterogeneity and to identify novel therapeutic targets for MPN. Two concurrent mutations that may affect phenotype were identified, including mutations in SH2B3, which is primarily prevalent in PV, and SF3B1, which is more commonly mutated in ET. Next, we conducted transcriptomic analysis at the haematopoietic stem cell (HSC) and megakaryocyte (MK)-erythroid progenitor (MEP) levels. Inflammatory signalling pathways were elevated in both ET HSCs and MEPs, unlike in PV HSCs and MEPs. Notably, Wnt/ß-catenin signalling was uniquely upregulated during ET haematopoietic differentiation from HSC to MEP, and inhibiting Wnt/ß-catenin signalling blocked MK differentiation in vitro. Consistently, Wnt/ß-catenin inhibitor administration decreased platelet counts in JAK2V617F+ MPN mice by blocking MEPs and MK progenitors and by inhibiting maturation of MKs, while in wild-type mice, Wnt/ß-catenin inhibitor did not significantly reduce platelet counts. In conclusion, our findings provide new insights into the mechanisms underlying phenotypic differentiation of JAK2V617F+ PV and ET and indicate Wnt/ß-catenin signalling as a potential therapeutic target for MPN.

Bright and Dark Quadrupolar Excitons in the WSe_{2}/MoSe_{2}/WSe_{2} Heterotrilayer.

Transition metal dichalcogenide heterostructures have been extensively studied as a platform for investigating exciton physics. While heterobilayers such as WSe_{2}/MoSe_{2} have received significant attention, there has been comparatively less research on heterotrilayers, which may offer new excitonic species and phases, as well as unique physical properties. In this Letter, we present theoretical and experimental investigations on the emission properties of quadrupolar excitons (QXs), a newly predicted type of exciton, in a WSe_{2}/MoSe_{2}/WSe_{2} heterotrilayer device. Our findings reveal that the optical brightness or darkness of QXs is determined by horizontal mirror symmetry and valley and spin selection rules. Additionally, the emission intensity and energy of both bright and dark QXs can be adjusted by applying an out-of-plane electric field, due to changes in hole distribution and the Stark effect. These results not only provide experimental evidence for the existence of QXs in heterotrilayers but also uncover their novel properties, which have the potential to drive the development of new exciton-based applications.

A transfusion risk stratification score to facilitate quality management in cardiopulmonary bypass.

BACKGROUND: Our previous showed that a blood management program in the cardiopulmonary bypass (CPB) department, reduced red blood cell (RBC) transfusion and complications, but assessing transfusion practice solely based on transfusion rates was insufficient. This study aimed to design a risk stratification score to predict perioperative RBC transfusion to guide targeted measures for on-pump cardiac surgery patients. STUDY DESIGN AND METHODS: We analyzed data from 42,435 adult cardiac patients. Eight predictors were entered into the final model including age, sex, anemia, New York Heart Association classification, body surface area, cardiac surgery history, emergency surgery, and surgery type. We then simplified the score to an integer-based system. The area under the receiver operating characteristic curve (AUC), Hosmer-Lemeshow goodness-of-fit test, and a calibration curve were used for its performance test. The score was compared to existing scores. RESULTS: The final score included eight predictors. The AUC for the model was 0.77 (95% CI, 0.76-0.77) and 0.77 (95% CI, 0.76-0.78) in the training and test set, respectively. The calibration curves showed a good fit. The risk score was finally grouped into low-risk (score of 0-13 points), medium-risk (14-19 points), and high-risk (more than 19 points). The score had better predictive power compared to the other two existing risk scores. DISCUSSION: We developed an effective risk stratification score with eight variables to predict perioperative RBC transfusion for on-pump cardiac surgery. It assists perfusionists in proactively preparing blood conservation measures for high-risk patients before surgery.

Angiogenic Activity and Mechanism for Bisphenols on Endothelial Cell and Mouse: Evidence of a Structural-Selective Effect.

Increased epidemiological evidence indicates the association of bisphenol exposure with human vascular disorders, while the underlying mechanism has not been clarified. Here, we sought to unveil the potential angiogenic effect and the underlying mechanism of bisphenols with different structural features using endothelial cells treated with an environmentally relevant concentration of bisphenols (range: 1 nM to 10 µM) and a C57BL/6 mouse model fed with doses of 0.002, 0.02, 2, and 20 mg/kg BW/day for 5 weeks. Bisphenol A (BPA) and bisphenol S (BPS) at a 1 nM level significantly increased tube formation by 45.1 and 30.2% and induced the microvessel sprouting, while tube length and microvessel sprouting were significantly inhibited by 37.2 and 55.7% after exposure to tetrabromobisphenol S (TBBPS) at 1 µM, respectively. Mechanistically, TBBPA and TBBPS significantly inhibited the interaction between phosphatidylinositol 3-kinase (PI3K) and thyroid receptor (TR), while BPA and BPS favored the interaction between PI3K and estrogen receptor (ER), resulting in abnormal PI3K signaling with consequent distinct angiogenic activity. BPA- and BPS-induced pro-angiogenic effects and TBBPS showed anti-angiogenic effects due to their distinct disruption on the TR/ER-PI3K pathway. Our work provided new evidence and mechanistic insight on the angiogenic activity of bisphenols and expanded the scope of endocrine disruptors with interference in vascular homeostasis.

Electrically Pumped Polarized Exciton-Polaritons in a Halide Perovskite Microcavity.

Recently, exciton-polaritons in lead halide perovskite microcavities have been extensively investigated to address striking phenomena such as polariton condensation and quantum emulation. However, a critical step in advancing these findings into practical applications, i.e., realizing electrically pumped perovskite polariton light-emitting devices, has not yet been presented. Here, we devise a new method to combine the device with a microcavity and report the first halide perovskite polariton light-emitting device. Specifically, the device is based on a CsPbBr3 capacitive structure, which can inject the electrons and holes from the same electrode, conducive to the formation of excitons and simultaneously maintaining the high quality of the microcavity. In addition, highly polarized polariton emissions have been demonstrated due to the optical birefringence in the CsPbBr3 microplate. This work paves the way for realizing practical polaritonic devices such as high-speed light-emitting devices for information communications and inversionless electrically pumped lasers based on perovskites.

Probing the Origin of Viscosity of Liquid Electrolytes for Lithium Batteries.

Viscosity is an extremely important property for ion transport and wettability of electrolytes. Easy access to viscosity values and a deep understanding of this property remain challenging yet critical to evaluating the electrolyte performance and tailoring electrolyte recipes with targeted properties. We proposed a screened overlapping method to efficiently compute the viscosity of lithium battery electrolytes by molecular dynamics simulations. The origin of electrolyte viscosity was further comprehensively probed. The viscosity of solvents exhibits a positive correlation with the binding energy between molecules, indicating viscosity is directly correlated to intermolecular interactions. Salts in electrolytes enlarge the viscosity significantly with increasing concentrations while diluents serve as the viscosity reducer, which is attributed to the varied binding strength from cation-anion and cation-solvent associations. This work develops an accurate and efficient method for computing the electrolyte viscosity and affords deep insight into viscosity at the molecular level, which exhibits the huge potential to accelerate advanced electrolyte design for next-generation rechargeable batteries.

Promotion of Bladder Cancer Cell Metastasis by 2-Mercaptobenzothiazole via Its Activation of Aryl Hydrocarbon Receptor Transcription: Molecular Dynamics Simulations, Cell-Based Assays, and Machine Learning-Driven Prediction.

2-Mercaptobenzothiazole (MBT) is an industrial chemical widely used for rubber products, corrosion inhibitors, and polymer materials with multiple environmental and exposure pathways. A growing body of evidence suggests its potential bladder cancer (BC) risk as a public health concern; however, the molecular mechanism remains poorly understood. Herein, we demonstrate the activation of the aryl hydrocarbon receptor (AhR) by MBT and reveal key events in carcinogenesis associated with BC. MBT alters conformational changes of AhR ligand binding domain (LBD) as revealed by 500 ns molecular dynamics simulations and activates AhR transcription with upregulation of AhR-target genes CYP1A1 and CYP1B1 to approximately 1.5-fold. MBT upregulates the expression of MMP1, the cancer cell metastasis biomarker, to 3.2-fold and promotes BC cell invasion through an AhR-mediated manner. MBT is further revealed to induce differentially expressed genes (DEGs) most enriched in cancer pathways by transcriptome profiling. The exposure of MBT at environmentally relevant concentrations induces BC risk via AhR signaling disruption, transcriptome aberration, and malignant cell metastasis. A machine learning-based model with an AUC value of 0.881 is constructed to successfully predict 31 MBT analogues. Overall, we provide molecular insight into the BC risk of MBT and develop an effective tool for rapid screening of AhR agonists.

Thyroid Dysfunction of Zebrafish (Danio rerio) after Early-Life Exposure and Discontinued Exposure to Tetrabromobiphenyl (BB-80) and OH-BB-80.

3,3',5,5'-Tetrabromobiphenyl (BB-80) was once used as additive flame retardants. Whether its early exposure and discontinued exposure alter thyroid function remains unknown. We investigate adverse effects after early-life exposure and discontinued exposure to BB-80 and hydroxylated BB-80 (OH-BB-80) on thyroid hormone (TH) levels, thyroid tissue, and transcriptome profiles in zebrafish larvae. BB-80 at 10 µg/L induces pathological changes of thyroid with reduced thyroid follicles in larvae (P < 0.05), whereas OH-BB-80 significantly increases T4 and T3 contents (1.8 and 2.5 times of the control, P < 0.05) at 14 days postfertilization (dpf) without morphological thyroid alterations. BB-80 and OH-BB-80 cause transcriptome aberrations with key differentially expressed genes involved in the disruption of TH synthesis and signal transduction (BB-80 at 14 dpf) or TH pathway activation (OH-BB-80 at 21 dpf). After 7 days of discontinued exposure, thyroglobulin (tg) and thyroid peroxidase (tpo) genes are downregulated (P < 0.05) by 52 and 48% for BB-80 and by 49 and 39% for OH-BB-80, respectively; however, the whole-body TH levels fail to fully recover, and the locomotor activity is impaired more by BB-80. Our results indicate significant adverse impacts of BB-80 and OH-BB-80 on TH homeostasis and thyroid function of zebrafish.

Carcinogenic Risk of 2,6-Di-tert-Butylphenol and Its Quinone Metabolite 2,6-DTBQ Through Their Interruption of RARß: In Vivo, In Vitro, and In Silico Investigations.

Thousands of contaminants are used worldwide and eventually released into the environment, presenting a challenge of health risk assessment. The identification of key toxic pathways and characterization of interactions with target biomacromolecules are essential for health risk assessments. The adverse outcome pathway (AOP) incorporates toxic mechanisms into health risk assessment by emphasizing the relationship among molecular initiating events (MIEs), key events (KEs), and adverse outcome (AO). Herein, we attempted the use of AOP to decipher the toxic effects of 2,6-di-tert-butylphenol (2,6-DTBP) and its para-quinone metabolite 2,6-di-tert-butyl-1,4-benzoquinone (2,6-DTBQ) based on integrated transcriptomics, molecular modeling, and cell-based assays. Through transcriptomics and quantitative real-time PCR validation, we identified retinoic acid receptor ß (RARß) as the key target biomacromolecule. The epigenetic analysis and molecular modeling revealed RARß interference as one MIE, including DNA methylation and conformational changes. In vitro assays extended subsequent KEs, including altered protein expression of p-Erk1/2 and COX-2, and promoted cancer cell H4IIE proliferation and metastasis. These toxic effects altogether led to carcinogenic risk as the AO of 2,6-DTBP and 2,6-DTBQ, in line with chemical carcinogenesis identified from transcriptome profiling. Overall, our simplified AOP network of 2,6-DTBP and 2,6-DTBQ facilitates relevant health risk assessment.

Machine Learning-Based Models with High Accuracy and Broad Applicability Domains for Screening PMT/vPvM Substances.

Persistent, mobile, and toxic (PMT) substances and very persistent and very mobile (vPvM) substances can transport over long distances from various sources, increasing the public health risk. A rapid and high-throughput screening of PMT/vPvM substances is thus warranted to the risk prevention and mitigation measures. Herein, we construct a machine learning-based screening system integrated with five models for high-throughput classification of PMT/vPvM substances. The models are constructed with 44 971 substances by conventional learning, deep learning, and ensemble learning algorithms, among which, LightGBM and XGBoost outperform other algorithms with metrics exceeding 0.900. Good model interpretability is achieved through the number of free halogen atoms (fr_halogen) and the logarithm of partition coefficient (MolLogP) as the two most critical molecular descriptors representing the persistence and mobility of substances, respectively. Our screening system exhibits a great generalization capability with area under the receiver operating characteristic curve (AUROC) above 0.951 and is successfully applied to the persistent organic pollutants (POPs), prioritized PMT/vPvM substances, and pesticides. The screening system constructed in this study can serve as an efficient and reliable tool for high-throughput risk assessment and the prioritization of managing emerging contaminants.

Association Between Preoperative Statin Exposure and Acute Kidney Injury in Adult Patients Undergoing Cardiac Surgery.

OBJECTIVES: The existing literature has shown conflicting results regarding the association between preoperative statin exposure and the risk of postoperative cardiac surgery-associated acute kidney injury (CSA-AKI). DESIGN: A single-center retrospective observational study. SETTING: A single, large, tertiary care center. PARTICIPANTS: Adult patients undergoing open cardiac surgery between January 1, 2012 and January 1, 2019. INTERVENTIONS: AKI was defined using the Kidney Disease: Improving Global Outcomes criteria. A multivariate logistic regression analysis and propensity score-matched analysis were used to study the association. MEASUREMENTS AND MAIN RESULTS: A total of 58,399 patient charts were retrospectively reviewed. The preoperative statin exposure cohort had a lower prevalence of all stages of CSA-AKI (30.7% v 36.3%, p < 0.001) and stage 3 CSA-AKI (0.9% v 2.1%, p < 0.001). After adjusting for confounding factors, preoperative statin exposure was a protective factor against all stages of postoperative CSA-AKI (odds ratio [OR], 0.885, 95% confidence interval [CI], 0.852-0.920, p < 0.001) and stage 3 CSA-AKI in adults (OR, 0.671, 95% CI, 0.567-0.795, p < 0.001). A propensity score-matched analysis showed that the preoperative statin exposure cohort had a lower risk of all stages of postoperative CSA-AKI (30.7% v 35.3%, p < 0.001) and stage 3 CSA-AKI (0.9% v 2.2%, p < 0.001) than the control cohort. CONCLUSIONS: Preoperative statin exposure was associated with all stages of postoperative CSA-AKI and stage 3 CSA-AKI.

Mild and moderate to severe early acute kidney injury following cardiac surgery among patients with heart failure and preserved vs. mid-range vs. reduced ejection fraction: A retrospective cohort study.

BACKGROUND: Patients with heart failure who undergo cardiac surgery have increased long-term mortality in which acute kidney injury (AKI) plays a role. However, little is known about whether the incidence of AKI differs according to stratified left ventricular ejection fraction (LVEF). OBJECTIVES: To assess the risks of mild AKI and moderate to severe AKI postcardiac surgery among patients with heart failure. DESIGN: Retrospective cohort analysis of patient data. Ejection fractions were categorised as LVEF less than 40%, heart failure with reduced ejection fraction (HFrEF); LVEF 40 to 49%, heart failure with mid-range ejection fraction (HFmrEF); and LVEF at least 50%, heart failure with preserved ejection fraction (HFpEF). PATIENTS AND SETTINGS: Patients who underwent cardiac surgery from 2012 to 2019 in Fuwai Hospital, Beijing, China, were consecutively enrolled. MAIN OUTCOME MEASURES: The primary endpoint was postoperative AKI staged either as mild AKI or moderate to severe AKI. The secondary outcome was the peri-operative composite adverse event of dialysis support, tracheotomy, intrasurgical and postsurgical mechanical cardiac support and in-hospital mortality. This study also assessed chronic renal dysfunction at follow-up. RESULTS: Of the 54 696 included patients, 18.9% presented with heart failure. Among these with HFpEF, HFmrEF and HFrEF, the incidence of postoperative mild AKI was 37.0, 33.4 and 37.6%, respectively. Patients with HFpEF and HFmrEF were characterised by numerically greater prevalence of moderate to severe AKI than HFrEF (8.5 vs. 9.1 vs. 5.8%). HFrEF and HFmrEF patients had comparable risks for mild AKI relative to HFpEF patients, odds ratio (OR) 0.885; 95% confidence interval CI 0.763 to 1.027 for HFmrEF vs. HFpEF; OR 1.083; 95% CI 0.933 to 1.256 for HFrEF vs. HFpEF. Patients with HFmrEF were more at risk for moderate to severe AKI than patients with HFpEF (OR, 1.368; 95% CI 1.066 to 1.742), but HFrEF and HFpEF did not differ significantly (OR 1.012; 95% CI 0.752 to 1.346). An increasing number of noncardiac comorbidities led to a higher risk of mild AKI and moderate to severe AKI in patients with heart failure; and its effect on AKI was almost equal among the three heart failure strata. The incidence of postoperative composite adverse outcome increased in a graded manner from HFpEF to HFmrEF to HFrEF. Information on the creatine concentrations at 3 months postoperatively and longer were retained for 5200 out of 10 347 (50.6%) heart failure patients in our charts.The AKI severity and the presence of HFmrEF contributed substantially to the development of renal dysfunction over a median [IQR] follow-up of 10 months [4.0 to 21.0]. CONCLUSIONS: Initiative programmes aimed at patients with HFrEF to prevent moderate to severe AKI and chronic kidney dysfunction should also include patients with HFmrEF.