Combined estimation of presepsin and gelsolin might improve the diagnostic validity of clinical scoring to predict and stratify sepsis in non-sepsis surgical ICU patient DOI Creative Commons

Hany A. Shehab,

Ahmed M. Eid, Yehya Shahin Dabour

et al.

Egyptian Journal of Anaesthesia, Journal Year: 2024, Volume and Issue: 40(1), P. 262 - 272

Published: May 9, 2024

Objectives This study evaluates the ability of serum presepsin (PSEP) and gelsolin (GSN) levels estimated in blood samples obtained at admission sepsis-free patients to surgical ICU (SICU) as early predictors for getting sepsis sepsis-related complications.

Language: Английский

The role of phospholipid transfer protein in sepsis-associated acute kidney injury DOI Creative Commons
Wei Jiang, Song Lin,

Weilei Gong

et al.

Critical Care, Journal Year: 2025, Volume and Issue: 29(1)

Published: Jan. 20, 2025

Language: Английский

Citations

3
Narciclasine attenuates sepsis-associated acute kidney injury through the ESR1/S100A11 axis DOI
Liping Yin, Xiaofei Huang, Beibei Zhang

et al.

Functional & Integrative Genomics, Journal Year: 2025, Volume and Issue: 25(1)

Published: Jan. 14, 2025

Language: Английский

Citations

1
Acute kidney injury following chimeric antigen receptor T-cell therapy: Epidemiology, mechanism and prognosis DOI
Yang Yang,

Kaiping Luo,

Gaosi Xu

et al.

Clinical Immunology, Journal Year: 2024, Volume and Issue: 266, P. 110311 - 110311

Published: July 11, 2024

Language: Английский

Citations

5
Usp9x contributes to the development of sepsis-induced acute kidney injury by promoting inflammation and apoptosis in renal tubular epithelial cells via activation of the TLR4/nf-κb pathway DOI Creative Commons

Shuhao Gong,

Huawei Xiong,

Yingchao Lei

et al.

Renal Failure, Journal Year: 2024, Volume and Issue: 46(2)

Published: June 14, 2024

As a pattern recognition receptor, Toll-like receptor 4 (TLR4) is crucial for the development and progression of acute kidney injury (AKI). This study aims to explore whether deubiquitinase Usp9x influences TLR4/NF-B pathway cause sepsis-induced (S-AKI). The model AKI was established in Sprague-Dawley rats using cecal ligation puncture (CLP) method, while renal tubular epithelial cell NRK-52E stimulated with lipopolysaccharide (LPS) vitro. All plasmids were transfected into cells according indicated group. TLR4 predicted by online prediction software Ubibrowser. Subsequently, Western blot Pearson correlation analysis identified protein as potential candidate. Co-IP verified interaction between Usp9x. Further research revealed that overexpression inhibited degradation downregulating its ubiquitination modification levels. Both vivo vitro experiments observed interference effectively alleviated inflammatory response apoptosis (RTECs) induced CLP or LPS, whereas reversed this situation. Transfection sh-Usp9x suppressed expression proteins associated TLR4/NF-κB LPS. Moreover, effect transfection. Therefore, interacts TLR4, leading upregulation through deubiquitination modification, activation signaling pathway, thereby promoting inflammation contributing injury.

Language: Английский

Citations

4
Advancing Insights into Progression of Acute Kidney Injury with Sepsis: Early Detection and Management DOI Open Access
T. Rama Rao,

Vasavi Sai Saraswati Rayapudi,

Chauhan Laudia Arthika

et al.

Journal of Drug Delivery and Therapeutics, Journal Year: 2025, Volume and Issue: 15(2), P. 129 - 136

Published: Feb. 15, 2025

Acute kidney injury (AKI) associated with sepsis is a major contributor to morbidity and mortality in critically ill patients. The progression of sepsis-induced AKI (S-AKI) complex involves dysregulated immune response, including systemic inflammation, endothelial dysfunction, microvascular injury. These mechanisms compromise renal function, leading significant challenges management. Early detection timely intervention are crucial improving outcomes, yet effective treatment strategies remain elusive. Advances understanding the pathophysiology S-AKI have provided critical insights into underlying damage during sepsis. led identification potential biomarkers that can aid early diagnosis, predict disease progression, guide therapeutic decisions. Current management includes fluid resuscitation, broad-spectrum antibiotics, replacement therapy (RRT), aimed at stabilizing patient supporting function. Emerging therapies, such as novel pharmacological agents approaches modulate under investigation, offering promise for clinical outcomes. However, more research needed validate these treatments ensure their safety efficacy. advancing S-AKI, coupled development innovative diagnostic tools Future should focus on bridging gap between basic science, practice, large-scale trials optimize care outcomes patients suffering from S-AKI. Keywords: Sepsis, injury, Immune Systemic Endothelial Microvascular

Language: Английский

Citations

0
Predictive model for mortality in patients with abdominal sepsis DOI Creative Commons
М. В. Осиков, Л. Ф. Телешева, A. G. Konashov

et al.

Bulletin of Russian State Medical University, Journal Year: 2025, Volume and Issue: 2025(1)

Published: Feb. 1, 2025

Mortality among patients with various forms of sepsis is 36.2–47.7%. Predicting the likelihood death associated critically important for clinical decision-making, stratifying patient risk, and improving overall survival. The study aimed to develop a mathematical model predicting outcome in abdominal surgical pathology. involved 64 diagnosed (AS). Based on AS outcomes, group 1 (n = 46) favorable outcomes 2 18) fatal were allocated. Clinical scales laboratory testing methods used evaluate parameters days 1, 3, 7 since diagnosis. On 3 7, SOFA scores adverse significantly higher, than that outcomes. Complete blood counts showed decrease absolute lymphocyte day compared 1. As biochemistry parameters, elevated serum levels C-reactive protein, urea, creatinine, lactate, procalcitonin, direct bilirubin, as well aspartate aminotransferase, alanine alkaline phosphatase activity observed. Furthermore, respiratory index venous oxygen saturation was A logistic regression constructed, software tool "Calculator AS" developed. predict probability created. High CRP creatinine levels, serve significant prognostic markers AS.

Language: Английский

Citations

0
Carboxymethyl Poria cocos polysaccharides protect against septic kidney injury by regulating the Nrf2-NF-κB signaling pathway DOI
Zongmeng Zhang, Chen Cai, Juan Zhou

et al.

International Journal of Biological Macromolecules, Journal Year: 2025, Volume and Issue: unknown, P. 143030 - 143030

Published: April 1, 2025

Language: Английский

Citations

0
The Regulatory Role of NcRNAs in Pyroptosis and Disease Pathogenesis DOI

Shaocong Wang,

Xinzhe Chen, Kun Wang

et al.

Cell Biochemistry and Biophysics, Journal Year: 2025, Volume and Issue: unknown

Published: April 18, 2025

Language: Английский

Citations

0
Host Biomarkers and Antibiotic Tissue Penetration in Sepsis: Insights from Moxifloxacin DOI Creative Commons
Maria Sanz-Codina, Hartmuth Nowak, Markus Zeitlinger

et al.

European Journal of Drug Metabolism and Pharmacokinetics, Journal Year: 2025, Volume and Issue: unknown

Published: April 23, 2025

Language: Английский

Citations

0
Interpretable Machine Learning for Predicting Anterior Uveitis in Axial Spondyloarthritis DOI
Hui Li, Qin Guo, Tiantian Zhang

et al.

JCR Journal of Clinical Rheumatology, Journal Year: 2025, Volume and Issue: unknown

Published: April 25, 2025

Background Axial spondyloarthritis (axSpA) is a chronic inflammatory disease primarily affecting the spine and sacroiliac joints, with anterior uveitis (AU) as common extra-articular manifestation. Predicting AU onset in axSpA patients challenging, traditional statistical methods often fail to capture disease's complexity. Methods This study aimed develop an interpretable machine learning (ML) model predict through historical cohort analysis of 1508 from tertiary medical center. Clinical data involving 54 variables were preprocessed imputation, factorization, oversampling, outlier capping, standardization. Recursive feature elimination identified 12 key predictors. Subsequently, 10 ML algorithms assessed using performance metrics visualization techniques. Results The gradient boosting incorporating factors showed high accuracy predicting risk. Shapley additive explanations revealed that hip involvement, nonsteroidal anti-inflammatory drug use, smoking most influential model's interpretability provided clear insights into contribution each risk, supporting early diagnosis personalized treatment. Conclusion predicts risk patients, helping identify high-risk cases for intervention treatment prevent complications such vision loss.

Language: Английский

Citations

0