Evaluating the predictive value of initial lactate/albumin ratios in determining prognosis of sepsis patients.

Sepsis remains a significant clinical challenge owing to its complex pathophysiology and variable prognosis. The early identification of patients at a higher risk of poor outcomes can be crucial for improving treatment strategies. This study aimed to evaluate the predictive value of early serum lactate and albumin levels and the lactate/albumin (L/A) ratio for 28-day prognosis in patients with sepsis. Patients diagnosed with sepsis between January 2021 and December 2022 were evaluated using a retrospective cohort methodology. Inclusion followed the International Consensus on sepsis and septic shock (Sepsis-3) guidelines and patients were selected based on well-defined criteria. Variables such as lactate, albumin, and the L/A ratio were documented within the first 24 hours of admission. Statistical analyses were performed using various tools, including the nonparametric Mann-Whitney U test and receiver operating characteristic curves. A total of 301 patients were divided into the survival (n = 167) and death (n = 134) groups. Notable differences were detected in the incidence of pulmonary infection, shock, lactate, albumin, and the L/A ratio. The L/A ratio was identified as a key predictor with an area under the curve of 0.868, an optimal cutoff value of >0.17, a sensitivity of 56.21%, and a specificity of 94.18%. Significant disparities in mortality rates and survival times were observed for the lactate, albumin, and L/A levels. This study underscores the predictive value of early serum lactate and albumin levels and the L/A ratio for 28-day prognosis in patients with sepsis, with the L/A ratio showing a superior predictive capability. These findings highlight the importance of L/A ratio as a robust and precise marker for evaluating the future clinical course of patients with sepsis, potentially aiding early detection and management.

Molecular Mechanism of SOX18 in Lipopolysaccharide-Induced Injury of Human Umbilical Vein Endothelial Cells.

Endothelial dysfunction is associated with the progression of sepsis. This study sought to probe the molecular route of sex-determining region on the Y chromosome-box transcription factor 18 (SOX18) in sepsis-associated endothelial injury. Human umbilical vein endothelial cells (HUVECs) were treated with lipopolysaccharide (LPS) to establish the sepsis cell model. Cell viability, lactate dehydrogenase (LDH) release, oxidative stress (reactive oxygen species/malondialdehyde/superoxide dismutase), and inflammation (interleukin-1ß/tumor necrosis factor-α/interleukin-6) were evaluated by cell counting kit-8 assay and relevant assay kits. The expression levels of SOX18, microRNA (miR)-204-5p, and cadherin-2 (CDH2) in cells were determined by real-time quantitative polymerase chain reaction and Western blot assay. The interaction of SOX18, miR-204-5p, and CDH2 was analyzed by chromatin immunoprecipitation and dual-luciferase assay. LPS induced HUVECs injury and downregulation of SOX18. SOX18 overexpression increased cell viability, while decreased LDH activity, oxidative stress, and inflammation. SOX18 bound to the miR-204-5p promoter to promote miR-204-5p expression, and further repressed CDH2 expression. miR-204-5p knockdown and CDH2 overexpression abrogated the protective role of SOX18 in HUVECs injury. Overall, SOX18 alleviated LPS-induced injury of HUVECs by promoting miR-204-5p and repressing CDH2, suggesting it as a potential target for sepsis treatment.

A case report of gadopentetate dimeglumine-induced cardiac arrest: Resuscitation using extracorporeal membrane oxygenation.

Gadopentetate dimeglumine (Gd-DTPA) is commonly used for enhancement in magnetic resonance imaging, but rarely causes serious adverse reactions. The patient presented in this report had a cardiac arrest and multiple organ dysfunction syndrome within a short time after administration of Gd-DTPA. Immediately after receiving an intravenous injection of Gd-DTPA, the patient felt nausea and chest tightness, and developed systemic erythema. He was successfully treated using veno-arterial extracorporeal membrane oxygenation (ECMO) combined with continuous renal replacement therapy without any serious complications or neurological deficits. We report a patient who was successfully treated for Gd-DTPA-induced cardiac arrest with ECMO. Thus, ECMO may be an effective treatment for cardiac arrest secondary to anaphylaxis.

Dynamic Compartmentalization of Peptide-Oligonucleotide Conjugates with Reversible Nanovesicle-Microdroplet Phase Transition Behaviors.

Developing artificial microsystems based on liquid-liquid phase separation (LLPS) to mimic cellular dynamic compartmentalization has gained increasing attention. However, limitations including complicated components and laborious fabrication techniques have hindered their development. Herein, we describe a new single-component dynamic compartmentalization system using peptide-oligonucleotide conjugates (POCs) produced from short elastin-like polypeptides (sELPs) and oligonucleotides (ONs), which can perform thermoreversible phase transition between a nanovesicle and a microdroplet. The phase transition of sELP-ONs is thoroughly investigated, of which the transition temperature can be controlled by concentration, length of sELPs and ONs, base sequences, and salt. Moreover, the sELP-ON microcompartment can enrich a variety of functional molecules including small molecules, polysaccharides, proteins, and nucleic acids. Two sELP-ON compartments are used as nano- and microreactors for enzymatic reactions, separately, in which chemical activities are successfully regulated under different-scaled confinement effects, demonstrating their broad potential application in matter exchange and artificial cells.

Abietic acid attenuates sepsis-induced lung injury by inhibiting nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) pathway to inhibit M1 macrophage polarization.

Lung injury is one of the leading causes of death in sepsis. Abietic acid (AA) has demonstrated anti-inflammatory and bacteriostatic properties. Herein, we established a mouse model of sepsis by cecal ligation and puncture, and intraperitoneally injected AA to treat. Lung injury was assessed by H&E staining and the inflammation in bronchoalveolar lavage fluid (BALF) were assessed by counting the number of inflammatory cells and detecting the content of inflammatory factors. Meanwhile, we also designed to study the effect of AA on lipopolysaccharide (LPS)-induced inflammatory response and macrophage marker gene expression in RAW264.7 cells in vitro. In this study, we found that AA inhibited LPS-induced secretion of inflammatory mediators (IL-1ß, TNF-α, IL-6 and MIP-2), and decreased the expression of M1 macrophage e markers (CD16 and iNOS) and p-p65 protein, while increased the expression of M2 macrophage markers (CD206 and Arg-1) in RAW264.7 cells in vitro. In vivo, the therapy of AA not only rescued septic animals, but also attenuated lung injury in sepsis mice. Moreover, AA decreased the number of total cells, neutrophils and macrophages, the conceration of total protein, and the levels of inflammatory mediators in BALF of sepsis mice. Further, we found that AA inhibited M1 macrophage polarization and blocked nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) pathway in BALF of sepsis mice. In conclusion, Abietic acid attenuates sepsis-induced lung injury, and its mechanism may be related to reducing inflammation by inhibiting NF-κB signaling to inhibit M1 macrophage polarization.

Prediction models for acute kidney injury in critically ill patients: a protocol for systematic review and critical appraisal.

INTRODUCTION: Acute kidney injury (AKI) has high morbidity and mortality in intensive care units, which can lead to chronic kidney disease, more costs and longer hospital stay. Early identification of AKI is crucial for clinical intervention. Although various risk prediction models have been developed to identify AKI, the overall predictive performance varies widely across studies. Owing to the different disease scenarios and the small number of externally validated cohorts in different prediction models, the stability and applicability of these models for AKI in critically ill patients are controversial. Moreover, there are no current risk-classification tools that are standardised for prediction of AKI in critically ill patients. The purpose of this systematic review is to map and assess prediction models for AKI in critically ill patients based on a comprehensive literature review. METHODS AND ANALYSIS: A systematic review with meta-analysis is designed and will be conducted according to the CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies (CHARMS). Three databases including PubMed, Cochrane Library and EMBASE from inception through October 2020 will be searched to identify all studies describing development and/or external validation of original multivariable models for predicting AKI in critically ill patients. Random-effects meta-analyses for external validation studies will be performed to estimate the performance of each model. The restricted maximum likelihood estimation and the Hartung-Knapp-Sidik-Jonkman method under a random-effects model will be applied to estimate the summary C statistic and 95% CI. 95% prediction interval integrating the heterogeneity will also be calculated to pool C-statistics to predict a possible range of C-statistics of future validation studies. Two investigators will extract data independently using the CHARMS checklist. Study quality or risk of bias will be assessed using the Prediction Model Risk of Bias Assessment Tool. ETHICS AND DISSEMINATION: Ethical approval and patient informed consent are not required because all information will be abstracted from published literatures. We plan to share our results with clinicians and publish them in a general or critical care medicine peer-reviewed journal. We also plan to present our results at critical care international conferences. OSF REGISTRATION NUMBER: 10.17605/OSF.IO/X25AT.