A LightGBM model was developed to predict sepsis-induced coagulopathy (SIC) within 72 h of ICU admission using routine clinical data. The model achieved an ROC-AUC of 0.937 (95

Abstract Acute kidney injury (AKI) is a common and severe complication of rhabdomyolysis (RM), and early risk stratification remains challenging because of its multifactorial and heterogeneous nature. We developed and externally validated an interpretable machine learning (ML) model for early prediction of AKI in RM across traumatic and non‐traumatic etiologies. Data were obtained from four public critical care databases and a multicenter cohort from tertiary hospitals in China. A total of 1569 patients were included in the derivation cohort and 401 in the external validation cohort. Eighteen variables within 24 h of admission were used to train 12 ML models. Performance was assessed by area under the receiver operating characteristic curve (AUC), and interpretability was evaluated using SHapley Additive exPlanations. The random forest model achieved the best performance (AUC = 0.940) and was simplified into a five‐variable model including lactate dehydrogenase, serum creatinine, Alb, prothrombin time, and activated partial thromboplastin time. The final model achieved AUCs of 0.919 and 0.900 in internal and external validation, respectively, with consistent performance in non‐traumatic (0.911) and traumatic (0.882) subgroups. This interpretable model may support early risk stratification in patients with RM across different etiologies.

Cellular senescence has emerged as an important contributor to acute kidney injury (AKI); however, its role in sepsis-associated acute kidney injury (SA-AKI) remains insufficiently characterized. This study aimed to investigate the involvement of cellular senescence in SA-AKI and to determine the contribution of the Toll-like receptor (TLR)/MyD88 signaling pathway. A cecal ligation and puncture (CLP) mouse model was established to induce SA-AKI. Cellular senescence markers and inflammatory indices were evaluated at 24, 48, and 72 h after injury using senescence-associated β-galactosidase (SA-β-Gal) staining, immunofluorescence, and quantitative real-time PCR (qPCR). Integrated transcriptomic and proteomic analyses were performed to identify candidate hub genes involved in SA-AKI. Human Kidney-2 (HK-2) cells were used to assess the role of MyD88 in tubular epithelial cell senescence, and mice with tubular epithelial cell-specific deletion of Myd88 were subsequently used to investigate the in vivo role of MyD88 in SA-AKI. At 72 h after CLP, SA-AKI was associated with a marked increase in SA-β-Gal activity, p21 expression, DNA damage, and inflammatory cytokine production, together with decreased lamin B1 (LAMNB1) expression and reduced proliferative activity, indicating the induction of cellular senescence. Inflammatory cell infiltration was also evident at this time point. Integrated omics analysis identified MyD88 as a key candidate molecule. In HK-2 cells, pharmacological inhibition of MyD88 attenuated lipopolysaccharide-induced cellular senescence and inflammatory responses. Consistently, tubular epithelial cell-specific deletion of Myd88 significantly reduced cellular senescence, inflammatory infiltration, and renal injury following SA-AKI. These findings indicate that cellular senescence in SA-AKI is mediated, at least in part, by the TLR/MyD88 signaling pathway. Targeting this pathway may represent a potential therapeutic strategy for attenuating SA-AKI progression and improving renal outcomes.

The transition from acute kidney injury (AKI) to chronic kidney disease (CKD) remains a major clinical challenge and contributes to substantial morbidity and mortality. Interleukin-4 (IL-4), a key cytokine in T helper 2 (Th2) immunity, appears to influence this trajectory in a context-dependent manner. In acute injury, IL-4 can limit inflammatory damage, support resolution, and facilitate tubular repair, in part through effects on macrophage phenotype. However, when IL-4 signaling persists during chronic injury, it may contribute to maladaptive remodeling, including activation of profibrotic myeloid and stromal programs and accumulation of extracellular matrix (ECM), thereby promoting renal fibrosis. This review summarizes evidence on IL-4’s biological properties, its canonical (Janus kinase [JAK]–signal transducer and activator of transcription 6 [STAT6]) and non-canonical (insulin receptor substrate [IRS]–phosphoinositide 3-kinase [PI3K]–protein kinase B [AKT]) signaling pathways, and its roles in renal diseases (including AKI, lupus nephritis, diabetic nephropathy, and other chronic glomerulopathies). We also evaluate the therapeutic rationale for targeting IL-4 signaling and highlight candidate molecular targets to mitigate renal fibrosis. Clarifying these determinants may help identify when and how IL-4–related pathways could be modulated to improve repair while limiting fibrosis.

Introduction:Kidney injury is an important manifestation of post-resuscitation syndrome and a significant factor leading to high mortality rates after cardiopulmonary resuscitation (CPR).This study aimed to develop and validate a multivariable nomogram to predict estimated glomerular filtration rate (eGFR) after CPR to assess the degree of kidney injury and provide protective strategies. Methods:The clinical data of patients after CPR admitted to Tianjin Medical University General Hospital from January 2017 to June 2024 and Tianjin Medical University General Hospital Airport Hospital from January 2017 to December 2019 were retrospectively analyzed. The patients those who met the inclusion criteria were randomly divided into training and validation cohorts at a ratio of 7∶3.We obtained clinical data from January 2021 to June 2023 at First Affiliated Hospital of Hebei North University as external validation. Univariate and multivariate linear regression methods were used to identify independent risk factors for 7d-eGFR after CPR, develop and validate (internal and external) a multivariate nomogram model. Calibration curve, Bland-Altman plot, and paired-T validation were used to validate the predictive performance of the model. Results:We included 439 patients after CPR, of whom 307 were in training cohort and 132 were in validation cohort. And 105 patients were included as an external validation cohort. Multivariable linear analysis showed that age (beta coefficient [β], 95% confidence interval: -0.344 [-0.528, -0.160]), hypertension (-3.610 [-5.968, -1.252]), diabetes mellitus (-2.992 [-5.295, -0.689]), no flow time (-0.577 [-0.996, -0.158]), baseline eGFR (0.349 [0.269∼0.429]), ACR (-0.042 [-0.073, -0.011]), lactic acid (-0.650 [-1.214,-0.086]) were the independent risk factors for eGFR after CPR. A composite nomogram predicted eGFR with good accuracy in training (97.07%), internal validation (95.45%), and external validation (91.08%) cohorts. The nomogram model has good predictive ability for AKI and CKD in training (AUC = 0.933 and 0.882), internal validation (AUC = 0.915 and 0.859), and external validation (AUC = 0.823 and 0.784) cohorts. Conclusion:The developed nomogram could be used to predict 7d-eGFR after CPR, which helped to accurately quantify kidney function levels and early predict the probability of AKI and CKD progression, achieving early detection and intervention, thereby improving the prognosis of patients after CPR.

Rhabdomyolysis-induced acute kidney injury (RM-AKI) is a life-threatening complication with incompletely understood pathogenesis. Recent studies have highlighted the roles of endoplasmic reticulum stress (ERS) and cellular senescence in kidney diseases; however, their involvement in RM-AKI remains unclear. A mouse model of glycerol-induced RM-AKI was established, and kidney injury was assessed at 48 h, 7 days, 14 days, and 28 days. Techniques including transcriptomic sequencing, quantitative PCR, Western blotting, immunofluorescence, SA-β-galactosidase staining, and transmission electron microscopy were employed to detect markers of ERS and cellular senescence at different timepoints. In vitro experiments involved treating HK-2 cells with myoglobin to simulate tubular injury, and siRNA was used to knockdown ATF4 to investigate its molecular mechanisms. Early and sustained activation of ERS accompanied by tubular epithelial cell senescence was observed during RM-AKI. Transcriptomic analysis revealed early enrichment of ERS and senescence-related signaling pathways. The ERS markers GRP78, CHOP, and ATF4, as well as the senescence marker p21, were significantly upregulated. Transmission electron microscopy showed endoplasmic reticulum dilation and mitochondrial swelling, while SA-β-gal staining indicated an increased proportion of senescent cells. In vitro, myoglobin induced ERS and cellular senescence in HK-2 cells, both of which were markedly attenuated by ATF4 knockdown. This study provides the first evidence that ATF4-mediated ERS drives the senescence of renal tubular epithelial cells in RM-AKI. This new finding, identifying ATF4 as a key upstream regulator linking ERS to cellular senescence in this pathological state, reveals a previously unrecognized pathogenic mechanism. Targeting ATF4 and its downstream ERS signaling pathways may represent a promising therapeutic strategy for treating RM-AKI.

PurposeAcute kidney injury (AKI) secondary to Rhabdomyolysis syndrome represents a life-threatening complication, characterized by notably high incidence and mortality rates. The role of cellular senescence in the progression of AKI has increasingly garnered attention in recent years. Our previous research has demonstrated that remote ischemic postconditioning (RIPC) can attenuate renal cellular senescence and elevation of serum level of interleukin-6 (IL-6) induced by ischemia-reperfusion injury following crush injury. The objective of this study is to investigate the specific role of IL-6 in Rhabdomyolysis-induced AKI (RM-AKI).MethodsWe established a mouse model of RM-AKI by intramuscular injection of glycerol and simulated RM-AKI at the cellular level by treating Hk-2 cells with myoglobin. Tocilizumab (TCZ), a humanized monoclonal antibody against the interleukin-6 (IL-6) receptor, is a key substance. IL-6, a multifunctional cytokine, plays a crucial role in the occurrence and development of various kidney diseases. It can promote inflammatory responses, cell proliferation, fibrosis, and other processes. TCZ exerts a protective effect on the kidneys by specifically binding to the IL-6 receptor and blocking the signal transduction of IL-6. Additionally, the levels of IL-6 were detected by employing ELISA kits. RNA sequencing analysis was performed on cells treated with myoglobin and tocilizumab. Flow cytometry was utilized to assess cell cycle distribution and the percentage of senescent cells. The expression levels of SERPINE1, GATA2, p53, and p21 were determined by real-time quantitative PCR and Western blot. Additionally, a dual-luciferase reporter gene assay was conducted to validate the binding effect of SERPINE1 and GATA2.ResultsTranscriptome Analysis revealed that genes including GATA2 and SERPINE1 were downregulated in HK-2 cells following tocilizumab treatment. Inhibition of the IL-6 receptor by tocilizumab in these cells led to a reduction in cellular senescence, accompanied by decreased of the cell cycle regulatory proteins P53 and P21 in mRNA and protein levels, while alleviating cell cycle arrest. Additionally, a dual-luciferase reporter assay confirmed that GATA2 binds to the promoter of SERPINE1 (PAI-1), thereby initiating its transcription.ConclusionThe IL-6/GATA2/SERPINE1 pathway mediates cellular senescence after acute kidney injury, and inhibiting IL-6 can alleviate AKI-induced cellular senescence, providing an important basis for exploring new therapeutic strategies.

Background:Rhabdomyolysis (RM) is a complex clinical syndrome with heterogeneous progression patterns among patients of varying severity. Early and accurate prediction of acute kidney injury (AKI), disease severity, renal replacement therapy (RRT) requirements, and mortality risk is essential for timely identification of high-risk individuals, personalized treatment planning, and optimal allocation of healthcare resources. We aimed to develop and externally validate an interpretable multi-task machine learning (ML) model to predict four clinical outcomes in patients with rhabdomyolysis: AKI, disease severity, the need for RRT, and in-hospital mortality. Methods:We conducted a retrospective study using three data sources: the eICU Collaborative Research Database (eICU-CRD), the Medical Information Mart for Intensive Care IV (MIMIC-IV), and electronic medical records from four tertiary hospitals in China. Data from eICU-CRD and MIMIC-IV were combined to form the derivation cohort for model training and internal validation, while data from the Chinese hospitals served as the external validation cohort. We analyzed 1429 patients from 2008 to 2019 in the derivation cohort and 362 patients from 2016 to 2022 in the external validation cohort. AKI was defined according to the Kidney Disease: Improving Global Outcomes (KDIGO) criteria, based on serum creatinine levels and urine output. Twenty-two clinical features available within the first 24 h of admission were selected to develop the prediction models. Ten machine learning (ML) algorithms were applied to construct multi-task prediction models. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC). To improve interpretability, feature importance was assessed using the SHapley Additive exPlanation (SHAP) method. Findings:1429 patients were included in the derivation cohort (69.4% developed AKI, 36.7% were classified as having severe disease, 12.1% required RRT, and 9.8% had in-hospital mortality). 362 patients were included in the external validation cohort (27.9% developed AKI, 25.7% had severe disease, 27.3% required RRT, and 4.1% had in-hospital mortality). Among all evaluated models, the random forest (RF) algorithm exhibited the highest overall discriminative performance across the four prediction tasks. Based on feature importance rankings, interpretable final models were developed for each task using the top five contributing features. These models demonstrated robust predictive accuracy for AKI, disease severity, RRT requirements, and in-hospital mortality, with AUCs and corresponding 95% confidence intervals (CIs) of 0.914 (0.875-0.944), 0.909 (0.869-0.940), 0.888 (0.844-0.921), and 0.823 (0.773-0.865) in the internal validation cohort, and 0.906 (0.871-0.934), 0.856 (0.815-0.890), 0.852 (0.811-0.887), and 0.832 (0.789-0.869) in the external validation cohort, respectively. To support clinical implementation, a web- and Android-based decision support system was developed and is currently undergoing pilot testing in multiple hospitals. Interpretation:We developed and validated an interpretable multi-task ML model capable of accurately predicting key clinical outcomes in patients with RM. To improve clinical applicability, a user-friendly decision support system was implemented, incorporating interactive features to support frontline healthcare providers in real-time risk stratification and individualized management of RM. Funding:National Key Research and Development Program of China (Nos. 2021YFC3002202 and 2023YFF1204104).

OBJECTIVE:To develop and compare risk prediction models for in-hospital post-cardiac arrest brain injury (PCABI) in critically ill patients using nomograms and random forest algorithms, aiming to identify the optimal model for early identification of high-risk PCABI patients and providing evidence for precise treatment. METHODS:A retrospective cohort study was used to collect the first-time in-hospital cardiac arrest (IHCA) patients admitted to the intensive care unit (ICU) from 2008 to 2019 in the Medical Information Mart for Intensive Care-IV (MIMIC-IV) as the study population, and the patients' age, gender, body mass, health insurance utilization, first vital signs and laboratory tests within 24 hours of ICU admission, mechanical ventilation, and critical care scores were extracted. Independent influencing factors of PCABI were identified through univariate and multivariate Logistic regression analyses. The included patients were randomly divided into a training cohort and an internal validation cohort in a 7:3 ratio, and the PCABI risk prediction model was constructed by the nomogram and random forest algorithm, respectively, and the model was evaluated by receiver operator characteristic curve (ROC curve), the calibration curve, and the decision curve analysis (DCA), and after the better model was selected, 179 patients admitted to Tianjin Medical University General Hospital as the external validation cohort for external evaluation were collected by using the same inclusion and exclusion criteria. RESULTS:A total of 1 419 patients with without traumatic brain injury who had their first-time IHCA were enrolled, including 995 in the training cohort (including 176 PCABI and 819 non-PCABI) and 424 in the internal validation cohort (including 74 PCABI and 350 non-PCABI). Univariate and multivariate analysis showed that age, potassium, urea nitrogen, sequential organ failure assessment (SOFA), acute physiology and chronic health evaluation III (APACHE III), and mechanical ventilation were independent influences on the occurrence of PCABI in patients with IHCA (all P < 0.05). Combining the above variables, we constructed a nomogram model and a random forest model for comparison, and the results show that the nomogram model has better predictive efficacy than the random forest model [nomogram model: area under the ROC curve (AUC) of the training cohort = 0.776, with a 95% credible interval (95%CI) of 0.741-0.811; internal validation cohort AUC = 0.776, with a 95%CI of 0.718-0.833; random forest model: AUC = 0.720, with a 95%CI of 0.653-0.787], and they performed similarly in terms of calibration curves, but the nomogram performed better in terms of decision curve analysis (DCA); at the same time, the nomogram model was robust in terms of external validation cohort (external validation cohort AUC = 0.784, 95%CI was 0.692-0.876). CONCLUSIONS:A nomogram risk prediction model for the occurrence of PCABI in critically ill patients was successfully constructed, which performs better than the random forest model, helps clinicians to identify the risk of PCABI in critically ill patients at an early stage and provides a theoretical basis for early intervention.

Sepsis-induced vascular endothelial injury, characterized by ferroptosis and barrier dysfunction, remains a major cause of mortality. This study investigates the role of the stimulator of interferon genes (STING)/ferroptosis suppressor protein 1 (FSP1) pathway in mediating endothelial ferroptosis during sepsis and explores therapeutic interventions. A murine sepsis model was established using cecal ligation and puncture (CLP), along with LPS-stimulated human umbilical vein endothelial cells (HUVECs). STING activation was modulated using inhibitor H-151 and siRNA silencing. Ferroptosis was assessed through lipid peroxidation (MDA, BODIPY C11), Fe2+ accumulation (FerroOrange), and FSP1/GPX4 expression. Vascular permeability was quantified via Evans Blue extravasation and FITC-Dextran assays. STING activation in septic endothelial cells suppressed FSP1 expression, amplifying lipid peroxidation and ferroptosis. CLP mice exhibited elevated vascular leakage, which H-151 reversed. STING inhibition restored FSP1 levels, reduced Fe2+ overload, and preserved VE-cadherin integrity. FSP1 inhibition abolished these protective effects, confirming its necessity in STING-mediated ferroptosis. The STING/FSP1 axis exacerbates septic endothelial injury by driving ferroptosis. Targeting this pathway reduces oxidative stress and vascular dysfunction, highlighting its therapeutic potential for sepsis.

Diabetes insipidus is characterized by polyuria and polydipsia, often resulting from central or nephrogenic causes. In diabetic emergencies, hyperosmolar hyperglycemic state (HHS), severe hypernatremia, and ventricular fibrillation are life-threatening conditions that require prompt intervention. This report describes a 47-year-old male with poorly controlled diabetes mellitus, who developed coma, excessive thirst, polyuria, hyperglycemia (47.29 mmol/L), hypernatremia (195.6 mmol/L), and plasma hyperosmolality (385 mOsm/kg). Despite fluid resuscitation and insulin therapy, refractory hypernatremia persisted, leading to a diagnosis of central diabetes insipidus (CDI). The patient also developed ventricular fibrillation, which was managed with defibrillation. Concurrently, desmopressin and blood purification were administered to address CDI and severe hypernatremia. This case emphasizes the importance of considering CDI when polyuria persists despite glucose control. The occurrence of ventricular fibrillation underscores the necessity of continuous cardiac monitoring in the context of hypovolemia and severe electrolyte imbalance. We propose that diabetes mellitus-related vascular injury impairs blood flow in the hypothalamus-pituitary tract, disrupting arginine vasopressin synthesis and secretion, contributing to CDI in poorly controlled diabetes mellitus.

BACKGROUND AND PURPOSE:Rhabdomyolysis (RM) and rhabdomyolysis-induced acute kidney injury (RM-AKI) are increasingly prevalent, yet specific therapies are lacking.Cellular senescence contributes to the transition of RM-AKI to chronic kidney disease (CKD), in which macrophage-tubular epithelial interactions play a pivotal role. Azathioprine, an immunosuppressant, through its metabolite 6-thio-GTP, inhibits Vav1-mediated Rac2 activation; nevertheless, its potential role in RM-AKI has not been elucidated. This study explores the Vav1/Rac2/NF-κB pathway in macrophage-mediated senescence in RM-AKI and azathioprine's efficacy. EXPERIMENTAL APPROACH:A glycerol-induced RM-AKI mouse model was used. High-throughput RNA sequencing, proteomic profiling, and co-immunoprecipitation were performed to evaluate activation of the Vav1-associated pathway. RAW264.7-TCMK-1 co-cultures verified azathioprine's effects on the pathway and senescence. KEY RESULTS:RM-AKI mice showed renal senescence (elevated p53, p21, p16, SA-β-gal) and activated macrophage Vav1/Rac2/NF-κB. Azathioprine treatment down-regulated Vav1/Rac2 expression, improved renal function, and mitigated histological injury. In vitro, inhibiting the pathway reduced tubular senescence and improved LaminB1 integrity. CONCLUSION AND IMPLICATIONS:Activation of macrophage Vav1/Rac2/NF-κB signaling promotes tubular cell senescence, whereas azathioprine counteracts this process by inhibiting the pathway.

INTRODUCTION:Acute kidney injury (AKI) is a common clinical condition where cellular senescence plays a crucial role in its progression. Previous studies have suggested that DOT1L plays a pivotal role in cellular senescence, yet its specific mechanisms in regulating AKI cellular senescence remain unclear. METHODS:This study utilized a glycerol-induced in vivo AKI model and employed the DOT1L-specific inhibitor EPZ004777 (EPZ) to suppress DOT1L function. Aging staining, periodic acid-Schiff staining, and Masson staining were employed to assess renal aging, injury, and interstitial fibrosis. In vitro experiments utilized doxorubicin-treated human renal tubular epithelial (HK-2) cells to establish an AKI cellular senescence model. EPZ was used to inhibit DOT1L, evaluating its impact on cellular senescence. High-throughput miRNA sequencing was performed to analyze differential expression of miRNAs downstream of DOT1L, and DOT1L overexpression and dual luciferase reporter gene experiments were conducted to explore interactions among DOT1L, miR-222-5p, and Wnt family member 9B (WNT9B). RESULTS:The results demonstrated that in vivo inhibition of DOT1L significantly reduced cellular senescence and improved renal tubular injury and interstitial fibrosis. In the doxorubicin-induced HK-2 cell model, DOT1L inhibition markedly decreased cellular senescence and lowered mRNA and protein levels of senescence markers while alleviating cell cycle arrest. DOT1L inhibition notably upregulated miR-222-5p expression and suppressed WNT9B expression, with opposite effects observed with DOT1L overexpression. CONCLUSION:DOT1L regulates cellular senescence through the miR-222-5p/WNT9B pathway in AKI. These findings suggest that DOT1L may serve as a potential therapeutic target to mitigate the progression of AKI to chronic kidney disease.

Kidney diseases, including both acute and chronic conditions, present significant global health challenges. Macrophages and endothelial cells play critical roles in the onset and progression of these diseases. This review aims to explore the bidirectional interactions between macrophages and endothelial cells and their roles in kidney diseases. By analyzing existing literature, this paper focuses on discussing the interaction mechanisms between macrophages and endothelial cells in acute kidney injury (AKI) and chronic kidney disease (CKD), including cytokine secretion, exosome transport, and adhesion molecule expression. Research demonstrates that macrophages regulate endothelial function and angiogenesis through cytokine release, exosome transfer, and adhesion molecules, while endothelial cells control macrophage recruitment and activation via adhesion molecules. These interactions are essential in balancing kidney injury and repair, as well as modulating inflammation and fibrosis. The current research is mostly based on the animal models and has not fully addressed the issue of species-specific differences. Future research should combine multi-omics technology and patient-derived organoids to validate therapeutic targets and promote clinical translational research.

Acute kidney injury (AKI) is a systemic clinical syndrome increasing morbidity and mortality worldwide in recent years. Renal tubular epithelial cells (TECs) death caused by mitochondrial dysfunction is one of the pathogeneses. The imbalance of mitochondrial quality control is the main cause of mitochondrial dysfunction. Mitochondrial quality control plays a crucial role in AKI. Mitochondrial quality control mechanisms are involved in regulating mitochondrial integrity and function, including antioxidant defense, mitochondrial quality control, mitochondrial DNA (mtDNA) repair, mitochondrial dynamics, mitophagy, and mitochondrial biogenesis. Currently, many studies have used mitochondrial dysfunction as a targeted therapeutic strategy for AKI. Therefore, this review aims to present the latest research advancements on mitochondrial dysfunction in AKI, providing a valuable reference and theoretical foundation for clinical prevention and treatment of this condition, ultimately enhancing patient prognosis.

Extracorporeal membrane oxygenation (ECMO) stands as a pivotal intervention for patients grappling with cardiopulmonary insufficiency. However, alongside its therapeutic benefits, ECMO carries the risk of complications, with acute kidney injury (AKI) emerging as a significant concern. The precise pathophysiological underpinnings of AKI in the context of ECMO remain incompletely elucidated. A comprehensive literature review was conducted to explore the epidemiology and pathophysiological mechanisms underlying the utilization of ECMO in the management of AKI. ECMO initiates a multifaceted cascade of inflammatory reactions, encompassing complement activation, endothelial dysfunction, white blood cell activation, and cytokine release. Furthermore, factors such as renal hypoperfusion, ischemia–reperfusion injury, hemolysis, and fluid overload exacerbate AKI. Specifically, veno-arterial ECMO (VA-ECMO) may directly induce renal hypoperfusion, whereas veno-venous ECMO (VV-ECMO) predominantly impacts pulmonary function, indirectly influencing renal function. While ECMO offers significant therapeutic advantages, AKI persists as a potentially fatal complication. A thorough comprehension of the pathogenesis underlying ECMO-associated AKI is imperative for effective prevention and management strategies. Moreover, additional research is warranted to delineate the incidence of AKI secondary to ECMO and to refine clinical approaches accordingly.

Background Diabetic kidney disease (DKD), a prevalent complication of diabetes mellitus, is often associated with acute kidney injury (AKI). Thus, the development of preventive and therapeutic strategies is crucial for delaying the progression of AKI and DKD.Methods The GSE183276 dataset, comprising the data of 20 healthy controls and 12 patients with AKI, was downloaded from the Gene Expression Omnibus (GEO) database to analyze the AKI group. For analyzing the DKD group, the GSE131822 dataset, comprising the data of 3 healthy controls and 3 patients with DKD, was downloaded from the GEO database. The common differentially expressed genes (DEGs) in renal tubular epithelial cells (TECs) were subjected to enrichment analyses. Next, a protein-protein interaction (PPI) network was constructed using the Search Tool for the Retrieval of Interacting Genes database to analyze gene-related regulatory networks. Finally, the AKI animal models and the DKD and AKI cell models were established, and the reliability of the identified genes was validated using quantitative real-time polymerase chain reaction analysis.Results Functional analysis was performed with 40 common DEGs in TECs. Eight hub genes were identified using the PPI and gene-related networks. Finally, validation experiments with the in vivo animal model and the in vitro cellular model revealed the four common DEGs. Four DEGs that share molecular mechanisms in the pathogenesis of DKD and AKI were identified. In particular, the expression of Integrin Subunit Beta 6(ITGB6), a hub and commonly upregulated gene, was upregulated in the in vitro models.Conclusion ITGB6 may serve as a biomarker for early AKI diagnosis in patients with DKD and as a target for early intervention therapies.

Abstract–This study explored the role of the non-canonical STING-PERK signaling pathway in sepsis-associated acute kidney injury (SA-AKI). Gene expression data from the GEO database and serum STING protein levels in patients with SA-AKI were analyzed. An LPS-induced mouse model and an in vitro model using HK-2 cells were used to investigate the role of STING in SA-AKI. STING expression was suppressed using shRNA silencing technology and the STING inhibitor C176. Kidney function, inflammatory markers, apoptosis, and senescence were measured. The role of the STING-PERK pathway was investigated by silencing PERK in HK-2 cells and administering the PERK inhibitor GSK2606414. STING mRNA expression and serum STING protein levels were significantly higher in patients with SA-AKI. Suppressing STING expression improved kidney function, reduced inflammation, and inhibited apoptosis and senescence. Silencing PERK or administering GSK2606414 suppressed the inflammatory response, cell apoptosis, and senescence, suggesting that PERK is a downstream effector in the STING signaling pathway. The STING-PERK signaling pathway exacerbates cell senescence and apoptosis in SA-AKI. Inhibiting this pathway could provide potential therapeutic targets for SA-AKI treatment.