KEY POINTS:Vancomycin exacerbates kidney injury in a mouse model of LPS-induced sepsis. GFR is a more sensitive and earlier indicator of vancomycin-associated kidney injury than serum creatinine or BUN. BACKGROUND:Vancomycin (VAN) is widely used in sepsis but may exacerbate sepsis-associated AKI. The mechanisms by which VAN aggravates renal injury in the septic context remain unclear, and early functional changes are difficult to detect using conventional biomarkers. METHODS:C57BL/6 mice were subjected to LPS-induced sepsis, VAN-induced nephrotoxicity, or combined injury. Renal function was continuously assessed using noninvasive percutaneous real-time GFR monitoring. Conventional renal injury markers, histopathology, and transcriptomic analyses were performed at 2, 24, and 72 hours. RESULTS:In septic mice, VAN administration caused an early and marked decline in GFR, preceding increases in serum creatinine and BUN. Compared with sepsis alone, combined LPS and VAN treatment resulted in more sustained renal dysfunction and more severe tubular injury. Transcriptomic profiling identified early and persistent upregulation of TNF receptor superfamily, member 1a and sustained upregulation of C-C motif chemokine ligand 20 in the combined injury model. Functional enrichment analyses revealed activation of inflammatory and immune-related pathways, including TNF signaling, cytokine-cytokine receptor interaction, and immunoglobulin superfamily cell adhesion molecule signaling. CONCLUSIONS:Real-time GFR monitoring demonstrates that VAN exacerbates sepsis-associated AKI by inducing early functional impairment. Transcriptomic changes suggest that enhanced inflammatory signaling and immune cell recruitment contribute to VAN-aggravated renal injury in sepsis.

Background: Vancomycin (VAN) is widely used in sepsis but may exacerbate sepsis-associated acute kidney injury (SA-AKI). The mechanisms by which VAN aggravates renal injury in the septic context remain unclear, and early functional changes are difficult to detect using conventional biomarkers. Methods: C57BL/6 mice were subjected to lipopolysaccharide (LPS)-induced sepsis, VAN-induced nephrotoxicity, or combined injury. Renal function was continuously assessed using non-invasive percutaneous real-time glomerular filtration rate (GFR) monitoring. Conventional renal injury markers, histopathology, and transcriptomic analyses were performed at 2, 24, and 72 hours. Results: In septic mice, VAN administration caused an early and marked decline in GFR, preceding increases in serum creatinine and blood urea nitrogen. Compared with sepsis alone, combined LPS and VAN treatment resulted in more sustained renal dysfunction and more severe tubular injury. Transcriptomic profiling identified early and persistent upregulation of Tnfrsf1a and sustained upregulation of Ccl20 in the combined injury model. Functional enrichment analyses revealed activation of inflammatory and immune-related pathways, including TNF signaling, cytokine–cytokine receptor interaction, and IgSF cell adhesion molecule signaling. Conclusions: Real-time GFR monitoring demonstrates that vancomycin exacerbates SA-AKI by inducing early functional impairment. Transcriptomic changes suggest that enhanced inflammatory signaling and immune cell recruitment contribute to VAN-aggravated renal injury in sepsis.

Acute respiratory distress syndrome (ARDS) remains a major challenge in critical care, with mortality exceeding 40%. Its diagnosis and management depend on multi-step procedures, invasive arterial blood gas analysis, and subjective CT interpretation, often leading to inconsistency, delayed intervention, and increased procedural burden. To address these limitations, we develop AutoARDS, an all-in-one foundation model that transforms routine chest CT into a quantitative platform, enabling integrated and reproducible assessment of diagnosis, progression, oxygenation, physiology, and prognosis within a single, non-invasive workflow, thereby supporting faster and more standardized critical-care decisions. Technically, AutoARDS proposes to employ a multi-task pretraining strategy with adversarial perturbation, distilling routine but unstructured clinical data into unified representations for fine-grained pathological learning. Trained on over 50,000 CT volumes and validated across six medical centers (6,153 individuals), AutoARDS (1) established a reproducible CT-derived biomarker linking morphological injury with disease severity, enabling standardized tracking of pulmonary progression; (2) accurately diagnosed acute respiratory failure and ARDS (AUCs = 0.97 and 0.87), facilitating early recognition and reducing diagnostic delay; (3) directly estimated the P/F ratio (PCC = 0.83), outperforming SpO2-based monitoring for noninvasive severity stratification and ventilation management; and (4) predicted 28-day outcomes (time-averaged AUC = 0.79), providing complementary risk assessment for clinical planning. Further analyses confirm generalizability to ARDS-associated right ventricular dysfunction (AUC = 0.76) and revealed a positive shift image-derived age residuals, reflecting disease-related imaging patterns that resemble pulmonary aging. By bridging visual information with quantitative physiology, AutoARDS exemplifies a scalable blueprint for transforming chest CT into an integrated, quantitative platform for precise and reproducible critical-care management.

[This corrects the article DOI: 10.1016/j.jointm.2025.08.011.].

Background::Previous studies have highlighted the importance of intensive care units (ICUs) in providing specialized care for critically ill patients. However, little is known about the current distribution of ICU resources, medical personnel, and available technologies across hospitals of different levels in Chinese mainland. In response, this study evaluated the distribution of ICU resources, personnel, major diseases, medical techniques, and the relationship between ICU bed availability and economic development to provide an overview of the current state of ICU services in Chinese mainland.Methods::A comprehensive questionnaire was distributed to intensivists at all levels of hospitals in Chinese mainland via the Questionnaire Starmini-program, a commonly used web-based survey platform in China. The questionnaire covered a wide range of items, including the demographic characteristics of intensivists, ICU type and capacity, composition of medical teams, disease classification, and available medical techniques.Results::Data were analyzed from 3637 intensivists working in 2005 hospitals throughout Chinese mainland, representing approximately half of all hospitals with ICU settings nationwide. The median number of hospital beds was 1000 (interquartile range [IQR], 547-1800), and the median number of ICU beds was 17 (IQR: 11-25). Overall, 600 (IQR: 300-1091) patients were admitted to the ICU annually at each hospital. The mean number of ICU beds per 100,000 people was 5.31 in 2022. The majority of the surveyed medical groups (ranging from 97.7% to 98.8%) led by chief physicians have experience in treating the eight most common conditions managed in the ICU, including severe pneumonia, cardiogenic shock, hypovolemic shock, sepsis, septic shock, cardiopulmonary resuscitation, acute respiratory distress syndrome, and acute renal injury. Regarding essential medical techniques in the ICU, 98.2%, 86.5%, 71.2%, and 24.1% of surveyed hospitals have implemented invasive mechanical ventilation, continuous blood purification, bedside ultrasound, and extracorporeal membrane oxygenation, respectively.Conclusions::This survey indicates that, although ICUs in Chinese mainland have advanced significantly to some extent, there are still challenges to address, such as regional disparities and hospital grade differences.

OBJECTIVE:To investigate superior prognostic accuracy for long-term survival from all-cause mortality in patients with end-stage renal disease (ESRD) undergoing maintenance hemodialysis (MHD). MATERIALS AND METHODS:Reviews of 2,859 ESRD patients on MHD were retrieved. The Geriatric Nutritional Risk Index (GNRI) and systemic immune inflammation index (SII) was utilized to develop a composite score of nutritional-systemic immune inflammation (N-SII). Primary endpoint was prognostic capability for long-term survival from all-cause mortality including cardiovascular events, cerebrovascular events, and infection episodes through an area under curve (AUC) using receiver operating characteristic analysis. Secondary outcomes included optimal cut-off value and hazard ratio. RESULTS:The composite scoring system of N-SII had a better prognostic accuracy for long-term survival from all-cause mortality in hemodialysis patients with a greater AUC of 0.850 (95% CI: 0.825 - 0.874) compared to either the isolated score of GNRI or SII (AUC = 0.761 (95% CI: 0.725 - 0.791) and 0.782 (95% CI: 0.767 - 0.826)) (p < 0.001). Superiority was met if the 95% CI fell within a superiority margin of 0.80. High-risk N-SII score was an independent predictor for all-cause mortality (HR = 2.049 (95% CI: 1.668 - 2.516)) with specificity and sensitivity of 0.784 and 0.899. A significantly shorter survival from all-cause death was observed in high-risk N-SII cohort as opposed to low-risk (44.14 (95% CI: 42.76 - 45.52) vs. 31.19 (95% CI: 28.50 - 33.89), p < 0.001). CONCLUSION:The composite index of N-SII showed a superior prognostic accuracy for long-term survival from all-cause mortality as opposed to isolated GNRI or SII, highlighting the integration of nutritional and inflammatory indexes for effective risk stratification of prognostic assessment among patients on MHD.

Immune checkpoint inhibitors (ICIs) activate the immune system by blocking PD-1, CTLA-4, and PD-L1, thereby inducing autoimmune-mediated adverse reactions known as immune-related adverse events (irAEs). When two or more organs are involved, this condition is defined as multi-organ immune-related adverse events (multi-organ irAEs). Patients with multi-organ irAEs account for approximately 20%-30% of all irAE cases; however, clinical research focusing on this subset remains limited. The purpose of this study is to analyze the clinical characteristics, optimal therapeutic approaches, and mortality-related risk factors of multi-organ irAEs. We searched all case reports of irAEs associated with ICIs in the PubMed, Web of Science, Cochrane Library, and Embase databases from their inception to January 2022. Search terms included "Immune Checkpoint Inhibitors", "Checkpoint Inhibitors, Immune", "Immune Checkpoint Blockers", "PD-L1", "CTLA-4 Inhibitor", "PD-1", and "Case report". After removing duplicate literature and applying strict inclusion/exclusion criteria, a total of 2,740 articles were included, encompassing 2,964 patients (782 with multi-organ irAEs and 2,182 with single-organ irAEs). Patients were stratified by the number of affected organs to compare clinical characteristics between multi-organ and single-organ irAE groups. For patients with multi-organ irAEs, subgroup analyzes were performed based on glucocorticoid dosage to identify optimal treatment strategies, and further stratified by survival status to explore potential mortality risk factors. No statistically significant differences in age or sex were observed between patients with multi-organ irAEs and those with single-organ irAEs (P > 0.05). However, the multi-organ irAE group exhibited significantly higher proportions of cardiovascular toxicity, thyroid toxicity, skin toxicity, and severe adverse reactions (P < 0.05), as well as a significantly elevated mortality rate (P < 0.05). Among patients with severe multi-organ irAEs, there were no significant differences in sex or age between high-dose and low-dose glucocorticoid subgroups (P > 0.05); notably, the high-dose glucocorticoid group had a significantly higher mortality rate (P < 0.05). For patients with non-severe multi-organ irAEs, no statistically significant differences in sex, age, mortality, or prognosis were detected between high-dose and low-dose glucocorticoid groups (P > 0.05). Multivariate logistic regression analysis revealed that cardiovascular toxicity, pulmonary toxicity, hepatotoxicity, and myositis were positively correlated with mortality in patients with multi-organ irAEs (OR > 1, P < 0.05). The most common organ combinations in multi-organ irAEs are "cardiac + neurological, cardiac + pulmonary, thyroid + pituitary, cardiac + hepatic, and gastrointestinal + skin". Multi-organ irAEs are generally more severe and associated with poorer outcomes compared to single-organ irAEs. High-dose glucocorticoids did not demonstrate superior prognostic outcomes and may be associated with an increased mortality risk in severe irAEs.clinical decisions regarding glucocorticoid dosing should be individualized based on the severity of irAEs and the specific organs involved.Cardiovascular toxicity, pulmonary toxicity, hepatotoxicity, and myositis are potential mortality risk factors for multi-organ irAEs induced by ICIs.

BACKGROUND:The objective of this study was to identify key idiopathic pulmonary fibrosis (IPF) related genes, thereby establishing a novel IPF diagnostic/warning panel and proposing drugs against IPF based on the strategy of targeting key genes. METHODS:The GEO datasets GSE245965, GSE279637, and GSE235435 were used to select IPF-related genes, as well as the IPF associated genes from the GeneCards and DisGeNET databases. The DEGs were used for enrichment analysis, PPI network construction, and targeted therapeutic value analysis. RESULTS:An intersection analysis yielded 60 commonly up-regulated genes and 16 commonly down-regulated genes. GO/KEGG/Reactome/Immunologic Signature terms that were novel and interesting were found to be enriched. In the interaction network, WDR90 and ANKRD1 were identified as hub genes. Among the 60 common up-regulated genes, seven (namely SERPINB3, TUBB3, SERPINB4, CHTF18, BAX, WDR90 and ITGAX) were shared by the disease sets. In the Symmap database, we found some herbs with the most targets, such as Lygodii Spora, Smilacis Glabrae Rhizoma, and Aloe. CONCLUSIONS:A panel comprising seven key IPF genes was identified, which may have diagnostic and prognostic value for IPF. A comprehensive analysis of the Dgidb database revealed potential drugs that may be antitumor agents against IPF, such as Lygodii Spora, Smilacis Glabrae Rhizoma, and Aloe.

INTRODUCTION:Type 2 diabetes mellitus (T2DM) increases susceptibility to sepsis-associated acute kidney injury (SA-AKI). While guidelines support chronic sodium-glucose cotransporter 2 (SGLT2) inhibitor use in T2DM, their efficacy and optimal intervention timing in acute sepsis remain unclear. We hypothesized that this efficacy is timing-dependent. To test this, we utilized a T2DM mouse model subjected to graded lipopolysaccharide (LPS) challenges as a clinically relevant surrogate for sepsis. Notably, to precisely capture the longitudinal and dynamic trajectory of renal function, we incorporated continuous real-time transcutaneous glomerular filtration rate (tGFR) monitoring. We evaluated the SGLT2 inhibitor dapagliflozin (DAPA) across three regimens representing distinct clinical scenarios: preventive (pre-LPS only, modeling prior chronic use), therapeutic (initiated post-LPS, modeling de novo intensive care initiation), and whole-course (continuous administration, modeling treatment continuation). RESULTS:Following LPS challenge, T2DM exacerbated renal dysfunction across all doses and impaired endogenous functional recovery. High-resolution real-time tGFR tracking and subsequent biomarker analyses revealed that the renoprotective effect of DAPA was dependent on the timing of intervention. In moderate endotoxemia, both therapeutic and whole-course regimens were superior to the preventive regimen. Compared to preventive administration alone, initiating or continuing treatment during the acute insult (therapeutic and whole-course regimens) more effectively preserved early glomerular filtration rate (GFR) trajectories, attenuated the rise in tubular injury markers, and promoted histological repair. CONCLUSIONS:Supported by dynamic renal function monitoring, this study demonstrates that DAPA provides significant renoprotection in a preclinical T2DM model of endotoxemia-associated acute kidney injury. This efficacy is closely associated with the timing of intervention, with greater protective effects observed when treatment is initiated during or maintained after the acute endotoxemic challenge. These preclinical findings suggest that intervention timing could be a key determinant of SGLT2 inhibitor efficacy, providing a scientific rationale for evaluating the prompt initiation or continuation of this therapy in diabetic patients presenting with acute sepsis.

Background Ischemia-reperfusion injury (IRI) often results in renal impairment. While the presence of neutrophil extracellular traps (NETs) is consistently observed, their specific impact on IRI is not yet defined. Sivelestat sodium, an inhibitor of neutrophil elastase which is crucial for NET formation, may offer a therapeutic approach to renal IRI, warranting further research. Methods A mouse model was established for early-stage renal IRI, confirmed by injury markers and histological assessments. The involvement of NETs in renal I/R was demonstrated using immunofluorescence and Western blot. Renal function and pathology were further evaluated through a comprehensive set of methods, including Periodic Acid-Schiff staining (PAS) and Terminal Deoxynucleotidyl Transferase dUTP Nick End Labeling (TUNEL) staining, enzyme-linked immunosorbent assay (ELISA), Real time Glomerular Filtration Rate (RT-GFR) monitoring, Polymerase Chain Reaction (PCR), biochemical analysis, and additional Western blot and immunofluorescence assays. Results We firstly quantified NET expression in renal IRI mice, noting a peak at 24 h. Subsequently, sivelestat sodium treatment was administered, resulting in decreased MPO, CitH3, and attenuated tubular damage. Moreover, it resulted in a decrease in serum levels of creatinine, blood urea nitrogen (BUN), as well as neutrophil gelatinase-associated lipocalin (NGAL) and kidney injury molecule-1 (KIM-1). Additionally, it lowered the abundance of renal tissue inflammatory markers interleukin-6 (IL-6) and tumor necrosis factor-α (TNF-α), and mitigated the levels of oxidative stress indicators malondialdehyde (MDA) and 4 Hydroxynonenal (4HNE), accompanied by a decline in renal cell apoptosis and an enhancement of GFR in renal I/R mice. Conclusion Sivelestat sodium ameliorates renal IRI by downregulating neutrophil NETs, reducing inflammation, oxidative stress, and apoptosis, thereby enhancing renal function.

Introduction:We aimed to explore the differences of neutrophil elastase (NE) levels between intensive care unit (ICU) and non-ICU patients with COVID-19 infection, as well as its predictive value for COVID-19 progression. Methods:We enrolled the patients admitted with a primary diagnosis of COVID-19. All patients in ICU were diagnosed with the critical type upon admission. Blood was taken within 24 hours, followed by examination of the blood NE level and urine NE level. Other clinical features were recorded. A logistic regression model was used to predict ICU admission. Results:A total of 83 patients were diagnosed, including 52 non-ICU cases and 31 ICU cases. The ICU group showed significantly elevated levels of Neutrophil%, Cr, D-dimer (DD), Procalcitonin (PCT), and C-reactive protein (CRP). Meanwhile, the CD3-cell, T4-cell, and Lymphocyte% levels were lower in the ICU group. Notably, the blood NE levels were similar between groups, whereas the urine NE level was highly significantly higher in the ICU group vs the non-ICU group. After dimension reduction, we constructed a logistic model (UD) using only two factors: the urine NE level and the blood DD level. The overall accuracy of was 86.1%. The urine NE has a strong efficacy in ICU prediction (AUC = 0.893), and the performance of the UD model was even better (AUC = 0.933). Conclusion:Urine NE level is a useful predictor of COVID-19 progression, particularly in patients requiring ICU care. Urine NE has a significantly positive correlation with neutrophil%, DD, and PCT, as well as a negative correlation with lymphocyte levels.

Objective Sepsis-induced myocardial dysfunction is a common complication of sepsis, characterized by high mortality and an unclear underlying mechanism. This study conducted an integrative multiomics analysis of mice with sepsis-induced myocardial dysfunction to provide new insights into potential mechanisms. Method We constructed an animal model of sepsis-induced myocardial dysfunction and analyzed the metabolomics, transcriptomics, and protein profiles of the heart tissues in the control and experimental groups. Results Untargeted metabolomics identified 74 significantly altered metabolites in the positive ion mode, of which 48 were upregulated and 26 downregulated; moreover, 70 significantly altered metabolites were detected in the negative ion mode, with 50 being upregulated and 20 downregulated. Transcriptomics revealed 4831 differentially expressed genes, with 3027 being downregulated and 1804 upregulated. Proteomics identified 107 significant proteins, 94 of which were significantly upregulated and 13 significantly downregulated. Integrated omics analysis revealed three significantly altered metabolites common to both groups: L-glutamate, L-aspartate, and nicotinamide. These metabolites were predominantly involved in nicotinate and nicotinamide metabolism, histidine metabolism, and nitrogen metabolism, potentially related to the pathogenesis of sepsis-induced myocardial dysfunction. Conclusion The pathogenesis of sepsis-induced myocardial dysfunction in mice may be associated with alterations in nicotinate and nicotinamide metabolism, histidine metabolism, and nitrogen metabolism.

Immune checkpoint inhibitors (ICIs) have revolutionized cancer therapy, however, their use is limited by heterogeneous and unpredictable immune-related adverse events (irAEs), which can progress to life-threatening conditions requiring intensive care unit (ICU) admission. Reliable biomarkers for predicting and stratifying ICU-level irAEs are urgently needed to improve immunotherapy safety and critical care management. Here, we performed comprehensive mass spectrometry-based proteomic profiling to identify plasma biomarkers for the prediction and monitoring of irAEs in 65 patients receiving ICI treatment. Our analysis identified 217 differentially abundant proteins and four co-expression modules related to humoral (antibody-mediated) and cellular (T cell-mediated) immunity spanning mild to severe irAEs. Through feature selection and cross-validation with proteomics and ELISA data, we identified two key proteins, IL1RL1 and FABP3, as potential biomarkers for irAE risk. In addition, we developed a plasma proteomic machine learning model (ProIRAE) that demonstrated high and robust predictive performance with area under the receiver-operating characteristic curve (AUROC) values of 0.929 and 0.766 for identifying patients at risk of developing irAEs, and AUROC values of 0.978 and 1.000 for predicting severe irAEs in the discovery and independent validation cohorts, respectively. Collectively, our study provides a valuable plasma proteomic atlas of ICI-related irAEs. The ProIRAE model offers a non-invasive tool for the detection and severity stratification of irAEs, with a great potential to improve precision monitoring and management of immunotherapy complications in critical care settings.

INTRODUCTION:Endotoxemic/septic cardiac dysfunction occurs frequently in elderly patients undergoing major surgery and contributes to postsurgery morbidity and mortality. This study evaluated the effect of aging on cardiac functional recovery following endotoxemia and explored therapeutic approaches for promotion of the recovery. METHODS:A small dose of endotoxin (0.5 mg/kg, iv) was administered to young adult (3-4 mo) and old (18-22 mo) mice with or without subsequent treatment with recombinant interleukin-37 (IL-37, 50 μg/kg, iv) or recombinant Klotho (10 μg/kg, iv). Cardiac function was analyzed using a microcatheter at 24, 48, and 96 h following administration of endotoxin. Myocardial levels of Klotho, intercellular adhesion molecule-1, and IL-6 were determined by immunoblotting and Enzyme-linked immunosorbent assay. RESULTS:Compared to young adult endotoxemic mice, old endotoxemic mice had worse cardiac dysfunction accompanied by greater myocardial levels of intercellular adhesion molecule-1 and IL-6 at each time point and failed to fully recover cardiac function by 96 h. The exacerbated and prolonged myocardial inflammation and cardiac dysfunction in old endotoxemic mice were associated with lower myocardial Klotho level and its further reduction by endotoxemia. Interestingly, recombinant IL-37 up-regulated myocardial Klotho level in old mice with or without endotoxemia and treatment of old endotoxemic mice with IL-37 improved myocardial inflammation resolution and cardiac functional recovery. Similarly, recombinant Klotho suppressed myocardial inflammatory response and promoted inflammation resolution in old endotoxemic mice, leading to complete recovery of cardiac function by 96 h. CONCLUSIONS:Myocardial Klotho insufficiency in old mice exacerbates myocardial inflammatory response, impairs inflammation resolution and hinders cardiac functional recovery. IL-37 is capable of up-regulating myocardial Klotho level to promote myocardial inflammation resolution and cardiac functional recovery in old endotoxemic mice.

Background: This study investigates the clinical features and pulmonary functions of coronavirus disease 2019 (COVID-19) pneumonia survivors at 3 or 6 months after diagnosis in the Heilongjiang Province, China. Methods: Forty-six patients with COVID-19 pneumonia diagnosed starting from February 2020 were enrolled in this study for follow-up in August 2020. These patients were categorized into three groups: Group A ( n = 24) and Group B ( n = 11), who were diagnosed with moderate or severe pneumonia and followed up at three months after diagnosis, and Group C ( n = 11), who were diagnosed with severe pneumonia and were followed up at 6 months after diagnosis. Pulmonary functions, arterial blood gas analysis, and clinical features, including chest high-resolution computed tomography (HRCT), blood tests, and health-related quality of life during hospitalization and at follow-up visits, were collected and analyzed. Results: Abnormal PO2 (A-a) was more prevalent in severe cases (Groups B and C) than in moderate cases (Group A). Respiratory dysfunction was common in our patients. HRCT showed that the abnormal computed tomography (CT) scores of severe cases (Groups B and C) were significantly higher than those of moderate cases (Group A). During the follow-up period, lung abnormalities gradually resolved in the first three months (Groups A and B); however, further resolution was not significant from 3-6 months (Groups B and C). Conclusion: Although pulmonary interstitial changes due to COVID-19 pneumonia gradually reverse over time, respiratory dysfunction is common and appears to persist for at least up to 6 months in patients who have recovered from COVID-19 pneumonia.

Sepsis-associated acute kidney injury (SA-AKI) is strongly associated with increased mortality in critical patients. The early detection of SA-AKI is crucial for clinical intervention. This study aims to integrate multiple metabolomics data related to SA-AKI to identify and validate novel metabolic markers. Real-time glomerular filtration rate (RT-GFR) measurement was adopted to establish SA-AKI mice. Untargeted metabolomics sequencing was performed on SA-AKI mice renal tissue (Control—LPS-8 h—LPS-24 h, N = 4) and urine samples (Control group vs. LPS-24 h group, N = 6). Time series analysis and random forest algorithm were employed to identify key metabolic molecule. Subsequently, renal spatiotemporal metabolomics was used to explore the specific distribution of key molecule. Eventually, a clinical cohort (20 healthy volunteers vs. 30 sepsis patients vs. 45 SA-AKI patients) urine quantitative metabolomic analysis was carried out to validate it as a biomarker and construct a diagnostic model via logistic regression (LR). Forty-two key renal metabolites and top fifty urinary metabolites were determined through multidimensional metabolomics study of SA-AKI mice. Urinary 3-Methylhistidine (3-MH) was charactered as a potential biomarker. The distribution of 3-MH increased in collecting ducts through renal spatiotemporal metabolomics sequencing. Then, we recruited 95 urine samples to validate its diagnostic performance (AUC = 0.86, 95

Background Sepsis-associated acute kidney injury (SA-AKI) is a frequent complication in patients with sepsis and is associated with high mortality. Therefore, early recognition of SA-AKI is essential for administering supportive treatment and preventing further damage. This study aimed to identify and validate metabolite biomarkers of SA-AKI to assist in early clinical diagnosis.MethodsUntargeted renal proteomic and metabolomic analyses were performed on the renal tissues of LPS-induced SA-AKI and sepsis mice. Glomerular filtration rate (GFR) monitoring technology was used to evaluate real-time renal function in mice. To elucidate the distinctive characteristics of SA-AKI, a multi-omics Spearman correlation network was constructed integrating core metabolites, proteins, and renal function. Subsequently, metabolomics analysis was used to explore the dynamic changes of core metabolites in the serum of SA-AKI mice at 0, 8, and 24 h. Finally, a clinical cohort (28 patients with SA-AKI vs. 28 patients with sepsis) serum quantitative metabolomic analysis was carried out to build a diagnostic model for SA-AKI via logistic regression (LR).ResultsThirteen differential renal metabolites and 112 differential renal proteins were identified through a multi-omics study of SA-AKI mice. Subsequently, a multi-omics correlation network was constructed to highlight five core metabolites, i.e., 3-hydroxybutyric acid, 3-hydroxymethylglutaric acid, creatine, myristic acid, and inosine, the early changes of which were then observed via serum time series experiments of SA-AKI mice. The levels of 3-hydroxybutyric acid, 3-hydroxymethylglutaric acid, and creatine increased significantly at 24 h, myristic acid increased at 8 h, while inosine decreased at 8 h. Ultimately, based on the identified core metabolites, we recruited 56 patients and constructed a diagnostic model named IC3, using inosine, creatine, and 3-hydroxybutyric acid, to early identify SA-AKI (AUC = 0.90).ConclusionsWe proposed a blood metabolite model consisting of inosine, creatine, and 3-hydroxybutyric acid for the early screening of SA-AKI. Future studies will observe the performance of these metabolites in other clinical populations to evaluate their diagnostic role.

BACKGROUND:Amphotericin B (AmB) remains a cornerstone in antifungal therapy, but its clinical use is limited by dose-dependent nephrotoxicity. Lipid-based formulations such as amphotericin B cholesterol sulfate complex dispersion (ABCD) were developed to mitigate renal injury, though their comparative renal safety profiles remain incompletely defined. OBJECTIVE:This study aimed to establish a pharmacologically relevant mouse model to characterise the nephrotoxicity of conventional AmB (AmB-D) and ABCD formulations, using continuous non-invasive glomerular filtration rate (GFR) monitoring and renal injury biomarkers. METHODS:Male C57BL/6 mice received a single intravenous dose of AmB-D or ABCD at low or high doses. Renal function was assessed via real-time GFR monitoring, serum creatinine (SCr), blood urea nitrogen (BUN) and mRNA expression of kidney injury molecule-1 (KIM-1) and neutrophil gelatinase-associated lipocalin (NGAL). Histopathological injury was evaluated at defined time points. RESULTS:High-dose AmB-D (2 mg/kg) and ABCD (20 mg/kg) induced rapid GFR decline within 2 h, preceding significant increases in SCr, BUN, and injury biomarkers. ABCD demonstrated 6-10-fold lower nephrotoxic potency compared to AmB-D. Low-dose groups exhibited mild, reversible changes in GFR and minimal tubular injury. CONCLUSION:Continuous GFR monitoring enables sensitive detection of early renal dysfunction and reveals distinct nephrotoxic profiles between AmB-D and ABCD. This pharmacologically relevant model provides a powerful tool for preclinical nephrotoxicity assessment and for quantitatively comparing the renal safety of different drug formulations.