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Acute kidney injury (AKI) is a common complication of sepsis. Long noncoding RNA nuclear-enriched abundant transcript 1 (NEAT1) plays a vital role in various diseases, including AKI. This study aimed to investigate the function and mechanism of NEAT1 in sepsis-induced AKI.

Postoperative sepsis is one of the main causes of mortality after liver transplantation (LT). Our study aimed to develop and validate a predictive model for postoperative sepsis within 7 d in LT recipients using machine learning (ML) technology. Data of 786 patients received LT from January 2015 to January 2020 was retrospectively extracted from the big data platform of Third Affiliated Hospital of Sun Yat-sen University. Seven ML models were developed to predict postoperative sepsis. The area under the receiver-operating curve (AUC), sensitivity, specificity, accuracy, and f1-score were evaluated as the model performances. The model with the best performance was validated in an independent dataset involving 118 adult LT cases from February 2020 to April 2021. The postoperative sepsis-associated outcomes were also explored in the study. After excluding 109 patients according to the exclusion criteria, 677 patients underwent LT were finally included in the analysis. Among them, 216 (31.9%) were diagnosed with sepsis after LT, which were related to more perioperative complications, increased postoperative hospital stay and mortality after LT (all p <.05). Our results revealed that a larger volume of red blood cell infusion, ascitic removal, blood loss and gastric drainage, less volume of crystalloid infusion and urine, longer anesthesia time, higher level of preoperative TBIL were the top 8 important variables contributing to the prediction of post-LT sepsis. The Random Forest Classifier (RF) model showed the best overall performance to predict sepsis after LT among the seven ML models developed in the study, with an AUC of 0.731, an accuracy of 71.6%, the sensitivity of 62.1%, and specificity of 76.1% in the internal validation set, and a comparable AUC of 0.755 in the external validation set. Our study enrolled eight pre- and intra-operative variables to develop an RF-based predictive model of post-LT sepsis to assist clinical decision-making procedure. Postoperative sepsis is one of the main causes of mortality after liver transplantation (LT). Our results revealed that a larger volume of red blood cell infusion, ascitic removal, blood loss and gastric drainage, less volume of crystalloid infusion and urine, longer anesthesia time, higher level of preoperative TBIL were the top 8 important variables contributing to the prediction of post-LT sepsis. The Random Forest Classifier (RF) model showed the best overall performance to predict sepsis after LT in our study, which could assist in the clinical decision-making procedure. [ABSTRACT FROM AUTHOR]

Luoma Lake is located on the east route of the South-to-North Water Diversion Project, and it is a potential source of drinking water. From March 2011 to May 2013, the spatio-temporal distribution variation of cyanobacteria community associated with environmental factors was comprehensively investigated based on a monthly sampling. A total of 27 cyanobacteria species belonging to 14 genera were identified, and the most predominant cyanobacteria genus wasPseudanabaena, not the usual bloom-forming genera such asMicrocystisandAnabaena. The cyanobacteria abundance at all the sampling sites exhibited similar spatio-temporal distribution variation, and the cyanobacteria abundance ranged over seven orders of magnitude from the undetectable level to 3.9 × 107 cells/L. Redundancy analysis and Pearson correlation analysis were applied to analyze the relationship between species and environment variables. The results suggested there was a positive correlation between cyanobacteria abundance and water temperature and ammonium concentration, while that between cyanobacteria abundance and dissolved oxygen concentration was negative. In addition, other environmental factors like precipitation and water turbulence could affect the cyanobacteria community distribution. Cyanobacterial blooms might not occur in Luoma Lake, with the predominant cyanobacteria genus beingPseudanabaenaand water quality improved owing to the implementation of the water diversion project. [ABSTRACT FROM AUTHOR]

Spatial heterogeneity and plasticity of the mammalian liver are critical for systemic metabolic homeostasis in response to fluctuating nutritional conditions. Here, a spatially resolved transcriptomic landscape of mouse livers across fed, fasted and refed states using spatial transcriptomics is generated. This approach elucidated dynamic temporal-spatial gene cascades and how liver zonation-both expression levels and patterns-adapts to shifts in nutritional status. Importantly, the pericentral nuclear receptor Nr1i3 (CAR) as a pivotal regulator of triglyceride metabolism is pinpointed. It is showed that the activation of CAR in the pericentral region is transcriptionally governed by Pparα. During fasting, CAR activation enhances lipolysis by upregulating carboxylesterase 2a, playing a crucial role in maintaining triglyceride homeostasis. These findings lay the foundation for future mechanistic studies of liver metabolic heterogeneity and plasticity in response to nutritional status changes, offering insights into the zonated pathology that emerge during liver disease progression linked to nutritional imbalances., (© 2024 The Author(s). Advanced Science published by Wiley‐VCH GmbH.)

Construction of Bi 2 FeNbO 7 /bisulfite system for abatement of pharmaceutical residue was achieved. An attempt to synthesize Bi 2 FeNbO 7 through hydrothermal technique was confirmed by X-ray diffraction. The magnetic field experiment revealed that Bi 2 FeNbO 7 possessed a saturation magnetization of 6.99 emu/g, indicating magnetic attributes of Bi 2 FeNbO 7 . Scanning electron microscopy images showed that Bi 2 FeNbO 7 exhibited regular octahedra in the size of 200-300 nm. In a self-made device, the activation of sodium bisulfite using Bi 2 FeNbO 7 for the disposal of amiloride has been carefully explored. The effects of solution pH, sodium bisulfite concentration, Bi 2 FeNbO 7 dosage, amiloride concentration, coexisting ions, and water matrix on the performance of Bi 2 FeNbO 7 /bisulfite system was investigated. The catalytic performance of Bi 2 FeNbO 7 /bisulfite to degrade amiloride was considerably higher than that of traditional iron oxides. The maximum removal efficiency of amiloride was 97.9% in Bi 2 FeNbO 7 /bisulfite process. The involvement of Fe might be crucial for activating bisulfite to create active species. The dominating radical in Bi 2 FeNbO 7 /bisulfite process was identified as SO 3 •‒ . With the help of UHPLC/MS/MS, three new degradation products of amiloride were found. Dehalogenation and deamination of amiloride might account for the formation of these transformation products. This work provides a highly efficient Bi 2 FeNbO 7 /bisulfite process for the disposal of pharmaceutical pollutants in water treatment., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

The design of eco-friendly Bi 1.81 MnNbO 6.72 /sulfite system for efficient degradation of chlortetracycline was achieved. The feasibility of synthesizing Bi 1.81 MnNbO 6.72 by hydrothermal method was determined by X-ray diffraction. The magnetic test suggested that Bi 1.81 MnNbO 6.72 possessed paramagnetic properties, indicating unpaired electrons were present. Scanning electron microscope and transmission electron microscopy images revealed that Bi 1.81 MnNbO 6.72 octahedra exhibited exposed [1,1,1] crystal plane containing high density of Bi, Mn and Nb metal atoms. Large numbers of metal atoms will facilitate heterogeneous catalytic process. In a batch system with aeration, Bi 1.81 MnNbO 6.72 could be used as sulfite activator for the disposal of chlortetracycline. The reaction kinetics of the degradation process conformed to the pseudo-second-order kinetic model. In Bi 1.81 MnNbO 6.72 /sulfite process, initial pH, Bi 1.81 MnNbO 6.72 dosage, sulfite and chlortetracycline concentrations, as well as inorganic salt ions had great effect on chlortetracycline degradation. Under optimal conditions, the efficiency of Bi 1.81 MnNbO 6.72 /sulfite system for degradation of chlortetracycline could reach 76.2%. Moreover, Mn (II) plays a key role in the initiation of the catalytic reaction in Bi 1.81 MnNbO 6.72 /sulfite process. Generated SO 3 ●‒ could act as main reactive species in Bi 1.81 MnNbO 6.72 /sulfite process, while HO ● was also involved. Three new degradation products were detected by UHPLC/MS/MS and the possible degradation pathways in this system were proposed. Based on this, we believe that Bi 1.81 MnNbO 6.72 /sulfite is a type of process for degradation of organic contaminants with research significance and application prospects., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier Ltd. All rights reserved.)