Emerging early diagnostic methods for acute kidney injury

Research on the global trends of COVID-19 associated acute kidney injury: a bibliometric analysis

Critically ill COVID-19 patients may exhibit various clinical symptoms of renal dysfunction including severe Acute Kidney Injury (AKI). Currently, there is a lack of bibliometric analyses on COVID-19-related AKI. The aim of this study is to provide an overview of the current research status and hot topics regarding COVID-19 AKI. The literature was retrieved from the Web of Science Core Collection (WoSCC) database. Subsequently, we utilized Microsoft Excel, VOSviewer, Citespace, and Pajek software to revealed the current research status, emerging topics, and developmental trends pertaining to COVID-19 AKI. This study encompassed a total of 1507 studies on COVID-19 AKI. The United States, China, and Italy emerged as the leading three countries in terms of publication numbers, contributing 498 (33.05%), 229 (15.20%), and 140 (9.29%) studies, respectively. The three most active and influential institutions include Huazhong University of Science and Technology, Wuhan University and Harvard Medical School. Ronco C from Italy, holds the record for the highest number of publications, with a total of 15 papers authored. Cheng YC's work from China has garnered the highest number of citations, totaling 470 citations. The co-occurrence analysis of author keywords reveals that 'mortality', 'intensive care units', 'chronic kidney disease', 'nephrology', 'renal transplantation', 'acute respiratory distress syndrome', and 'risk factors' emerge as the primary areas of focus within the realm of COVID-19 AKI. In summary, this study analyzes the research trends in the field of COVID-19 AKI, providing a reference for further exploration and research on COVID-19 AKI mechanisms and treatment.

Predictive models of sepsis-associated acute kidney injury based on machine learning: a scoping review

BACKGROUND

With the development of artificial intelligence, the application of machine learning to develop predictive models for sepsis-associated acute kidney injury has made potential breakthroughs in early identification, grading, diagnosis, and prognosis determination.

METHODS

Here, we conducted a systematic search of the PubMed, Cochrane Library, Embase (Ovid), Web of Science, and Scopus databases on April 28, 2023, and screened relevant literature. Then, we comprehensively extracted relevant data related to machine learning algorithms, predictors, and predicted objectives. We subsequently performed a critical evaluation of research quality, data aggregation, and analyses.

RESULTS

We screened 25 studies on predictive models for sepsis-associated acute kidney injury from a total of originally identified 2898 studies. The most commonly used machine learning algorithm is traditional logistic regression, followed by eXtreme gradient boosting. We categorized these predictive models into early identification models (60%), prognostic prediction models (32%), and subtype identification models (8%) according to their predictive purpose. The five most commonly used predictors were serum creatinine levels, lactate levels, age, blood urea nitrogen concentration, and diabetes mellitus. In addition, a single data source, insufficient assessment of clinical utility, lack of model bias assessment, and hyperparameter adjustment may be the main reasons for the low quality of the current research.

CONCLUSIONS

However, studies on the nondeath prognostic outcomes, the long-term clinical outcomes, and the subtype identification models are insufficient. Additionally, the poor quality of the research and the insufficient practicality of the model are problems that need to be addressed urgently.

Dyna-vivo-seq unveils cellular RNA dynamics during acute kidney injury via in vivo metabolic RNA labeling-based scRNA-seq

A fundamental objective of genomics is to track variations in gene expression program. While metabolic RNA labeling-based single-cell RNA sequencing offers insights into temporal biological processes, its limited applicability only to in vitro models challenges the study of in vivo gene expression dynamics. Herein, we introduce Dyna-vivo-seq, a strategy that enables time-resolved dynamic transcription profiling in vivo at the single-cell level by examining new and old RNAs. The new RNAs can offer an additional dimension to reveal cellular heterogeneity. Leveraging new RNAs, we discern two distinct high and low metabolic labeling populations among proximal tubular (PT) cells. Furthermore, we identify 90 rapidly responding transcription factors during the acute kidney injury in female mice, highlighting that high metabolic labeling PT cells exhibit heightened susceptibility to injury. Dyna-vivo-seq provides a powerful tool for the characterization of dynamic transcriptome at the single-cell level in living organism and holds great promise for biomedical applications.

Development of gold nanoparticle-based lateral-flow strips for NGAL protein detection in urine samples

This study focuses on enhancing the sensitivity of lateral-flow strips (LFSs) based on gold nanoparticles (AuNPs) for the detection of Neutrophil Gelatinase-Associated Lipocalin (NGAL) protein in urine samples. Several sizes of AuNP-based LFS biosensors were tested to optimize colorimetric signals for NGAL detection based on improved conjugation conditions. AuNPs of 39.8 nm diameter at pH 8 were the most sensitive for the detection of NGAL. Through systematic enhancements to the AuNP-based LFS, the study significantly improves the sensitivity, enabling the reliable detection of NGAL protein in urine samples at a level as low as 12.5 ng mL-1. These advances contribute to the refinement of diagnostic tools for the early detection of kidney injury, specifically in cases associated with the presence of NGAL protein, offering a more precise and effective screening approach.

A Review of Electronic Early Warning Systems for Acute Kidney Injury

Acute kidney injury (AKI) is characterized by impaired renal function that can result in irreversible severe renal impairment or lifelong dependence on renal replacement therapy in some cases. Early intervention can significantly slow down the progression of AKI and reduce mortality. In recent years, electronic early warning systems for patients with AKI have been gaining attention as a potential clinical decision-support option. This paper presents a review of the application of electronic early warning systems for AKI from four aspects: development process, types of output, influencing factors, and system evaluation.

Ultrasmall Nanodots with Dual Anti-Ferropototic Effect for Acute Kidney Injury Therapy

Ferroptosis is known to mediate the pathogenesis of chemotherapeutic drug-induced acute kidney injury (AKI); however, leveraging the benefits of ferroptosis-based treatments for nephroprotection remains challenging. Here, ultrasmall nanodots, denoted as FerroD, comprising the amphiphilic conjugate (tetraphenylethylene-L-serine-deferoxamine, TPE-lys-Ser-DFO (TSD)) and entrapped ferrostatin-1 are designed. After being internalized through kidney injury molecule-1-mediated endocytosis, FerroD can simultaneously remove the overloaded iron ions and eliminate the overproduction of lipid peroxides by the coordination-disassembly mechanisms, which collectively confer prominent inhibition efficiency of ferroptosis. In cisplatin (CDDP)-induced AKI mice, FerroD equipped with dual anti-ferroptotic ability can provide long-term nephroprotective effects. This study may shed new light on the design and clinical translation of therapeutics targeting ferroptosis for various ferroptosis-related kidney diseases.

Advancements in Trauma-Induced Acute Kidney Injury: Diagnostic and Therapeutic Innovations

Acute kidney injury following trauma impacts patient recovery critically, necessitating an integrated approach to emergency care and nephrology. This review aims to provide a comprehensive understanding of trauma-induced nephropathy, highlighting recent advancements in pathophysiological insights, diagnostic techniques, and strategic interventions. Our key findings emphasize the role of biomarkers, like Neutrophil Gelatinase-Associated Lipocalin and Liver Fatty Acid-Binding Protein, and imaging techniques, such as contrast-enhanced ultrasound, in early AKI detection. Preventive strategies, including aggressive fluid resuscitation, avoidance of nephrotoxic agents, and hemodynamic optimization, are essential for mitigating AKI progression. Integrating these approaches into trauma care frameworks aims to enhance patient outcomes and set a foundation for future research and clinical improvements.

Targeted treatment of rat AKI induced by rhabdomyolysis using BMSC derived magnetic exosomes and its mechanism

Introduction: rhabdomyolysis (RM) is a serious syndrome. A large area of muscle injury and dissolution induces acute kidney injury (AKI), which results in a high incidence and mortality rate. Exosomes released by mesenchymal stem cells (MSCs) have been used to treat AKI induced by rhabdomyolysis and have shown regenerative effects. However, the most serious drawbacks of these methods are poor targeting and a low enrichment rate after systemic administration. Methods: in this study, we demonstrated that magnetic exosomes derived from bone marrow mesenchymal stem cells (BMSCs) can directly target damaged muscles rather than kidneys using an external magnetic field. Results: magnetic navigation exosomes reduced the dissolution of damaged muscles, greatly reduced the release of cellular contents, slowed the development of AKI. Discussion: in summary, our proposed method can overcome the shortcomings of poor targeting in traditional exosome therapy. Moreover, in the rhabdomyolysis-induced AKI model, we propose for the first time an exosome therapy mode that directly targets damaged muscles through magnetic navigation.

Effect of C60 Fullerene on Muscle Injury-Induced Rhabdomyolysis and Associated Acute Renal Failure

Introduction

Rhabdomyolysis, as an acute stage of myopathy, causes kidney damage. It is known that this pathology is caused by the accumulation of muscle breakdown products and is associated with oxidative stress. Therefore, the present study evaluated the effect of intraperitoneal administration (dose 1 mg/kg) of water-soluble C60 fullerenes, as powerful antioxidants, on the development of rat kidney damage due to rhabdomyolysis caused by mechanical trauma of the muscle soleus of different severity (crush syndrome lasting 1 min under a pressure of 2.5, 3.5, and 4.5 kg/cm2, respectively).

Methods

Using tensometry, biochemical and histopathological analyses, the biomechanical parameters of muscle soleus contraction (contraction force and integrated muscle power), biochemical indicators of rat blood (concentrations of creatinine, creatine phosphokinase, urea and hydrogen peroxide, catalase and superoxide dismutase activity), glomerular filtration rate and fractional sodium excretion value, as well as pathohistological and morphometric features of muscle and kidney damages in rats on days 1, 3, 6 and 9 after the initiation of the injury were studied.

Results

Positive changes in biomechanical and biochemical parameters were found during the experiment by about 27-30 ± 2%, as well as a decrease in pathohistological and morphometric features of muscle and kidney damages in rats treated with water-soluble C60 fullerenes.

Conclusion

These findings indicate the potential application of water-soluble C60 fullerenes in the treatment of pathological conditions of the muscular system caused by rhabdomyolysis and the associated oxidative stress.

A pilot clinical risk model to predict polymyxin-induced nephrotoxicity: a real-world, retrospective cohort study

OBJECTIVES

Polymyxin-induced nephrotoxicity (PIN) is a major safety concern and challenge in clinical practice, which limits the clinical use of polymyxins. This study aims to investigate the risk factors and to develop a scoring tool for the early prediction of PIN.

METHODS

Data on critically ill patients who received intravenous polymyxin B or colistin sulfate for over 24 h were collected. Logistic regression with the least absolute shrinkage and selection operator (LASSO) was used to identify variables that are associated with outcomes. The eXtreme Gradient Boosting (XGB) classifier algorithm was used to further visualize factors with significant differences. A prediction model for PIN was developed through binary logistic regression analysis and the model was assessed by temporal validation and external validation. Finally, a risk-scoring system was developed based on the prediction model.

RESULTS

Of 508 patients, 161 (31.6%) patients developed PIN. Polymyxin type, loading dose, septic shock, concomitant vasopressors and baseline blood urea nitrogen (BUN) level were identified as significant predictors of PIN. All validation exhibited great discrimination, with the AUC of 0.742 (95% CI: 0.696-0.787) for internal validation, of 0.708 (95% CI: 0.605-0.810) for temporal validation and of 0.874 (95% CI: 0.759-0.989) for external validation, respectively. A simple risk-scoring tool was developed with a total risk score ranging from -3 to 4, corresponding to a risk of PIN from 0.79% to 81.24%.

CONCLUSIONS

This study established a prediction model for PIN. Before using polymyxins, the simple risk-scoring tool can effectively identify patients at risk of developing PIN within a range of 7% to 65%.

Empowering an Acute Kidney Injury 3D Graphene-Based Sensor Using Extreme Learning Machine

This study reports on the application of an extreme learning machine (ELM) in near-real-time kidney monitoring via urine neutrophil gelatinase-associated lipocalin (NGAL) detection with a 3D graphene electrode. This integration marks the first instance of combining a graphene-based electrode with machine learning to enhance the NGAL detection accuracy, building on our group's 2020 research. The methodology involves two key components: a graphene electrode functionalized with a lipocalin-2 antibody for NGAL detection and the ELM application for improved prediction accuracy by using urine analysis data. The results show a significant 15% increase in the area under the curve (AUC) for NGAL determination, with error reduction from ±6 to 0.54 ng/mL within a linear range of 2.7-140 ng/mL. The ELM also lowered the detection limit from 14.8 to 0.89 ng/mL and increased accuracy, precision, sensitivity, specificity, and F1 score for AKI prediction by 8.89, 30.69, 6.78, 9.94, and 19.07%, respectively. These findings underscore the efficacy of simple neural networks in enhancing graphene-based electrochemical sensors for AKI biomarkers. ELM was chosen for its optimal performance-resource balance, with a comparative analysis of ELM, support vector machines, multilayer perceptron, and random forest algorithms also included. This research suggests the potential for miniaturizing AI-enhanced sensors for practical applications.

Revitalizing Ancient Mitochondria with Nano-Strategies: Mitochondria-Remedying Nanodrugs Concentrate on Disease Control

Mitochondria, widely known as the energy factories of eukaryotic cells, have a myriad of vital functions across diverse cellular processes. Dysfunctions within mitochondria serve as catalysts for various diseases, prompting widespread cellular demise. Mounting research on remedying damaged mitochondria indicates that mitochondria constitute a valuable target for therapeutic intervention against diseases. But the less clinical practice and lower recovery rate imply the limitation of traditional drugs, which need a further breakthrough. Nanotechnology has approached favorable regiospecific biodistribution and high efficacy by capitalizing on excellent nanomaterials and targeting drug delivery. Mitochondria-remedying nanodrugs have achieved ideal therapeutic effects. This review elucidates the significance of mitochondria in various cells and organs, while also compiling mortality data for related diseases. Correspondingly, nanodrug-mediate therapeutic strategies and applicable mitochondria-remedying nanodrugs in disease are detailed, with a full understanding of the roles of mitochondria dysfunction and the advantages of nanodrugs. In addition, the future challenges and directions are widely discussed. In conclusion, this review provides comprehensive insights into the design and development of mitochondria-remedying nanodrugs, aiming to help scientists who desire to extend their research fields and engage in this interdisciplinary subject.

Exploration of potential biomarkers and therapeutic targets for trauma-related acute kidney injury

PURPOSE

Acute kidney injury (AKI) is one of the most common functional injuries observed in trauma patients. However, certain trauma medications may exacerbate renal injury. Therefore, the early detection of trauma-related AKI holds paramount importance in improving trauma prognosis.

METHODS

Qualified datasets were selected from public databases, and common differentially expressed genes related to trauma-induced AKI and hub genes were identified through enrichment analysis and the establishment of protein-protein interaction (PPI) networks. Additionally, the specificity of these hub genes was investigated using the sepsis dataset and conducted a comprehensive literature review to assess their plausibility. The raw data from both datasets were downloaded using R software (version 4.2.1) and processed with the "affy" package19 for correction and normalization.

RESULTS

Our analysis revealed 585 upregulated and 629 downregulated differentially expressed genes in the AKI dataset, along with 586 upregulated and 948 downregulated differentially expressed genes in the trauma dataset. Concurrently, the establishment of the PPI network and subsequent topological analysis highlighted key hub genes, including CD44, CD163, TIMP metallopeptidase inhibitor 1, cytochrome b-245 beta chain, versican, membrane spanning 4-domains A4A, mitogen-activated protein kinase 14, and early growth response 1. Notably, their receiver operating characteristic curves displayed areas exceeding 75%, indicating good diagnostic performance. Moreover, our findings postulated a unique molecular mechanism underlying trauma-related AKI.

CONCLUSION

This study presents an alternative strategy for the early diagnosis and treatment of trauma-related AKI, based on the identification of potential biomarkers and therapeutic targets. Additionally, this study provides theoretical references for elucidating the mechanisms of trauma-related AKI.

Review of the limitations of current biomarkers in acute kidney injury clinical practices

Acute kidney injury is a prevalent disease in hospitalized patients and is continuously increasing worldwide. Various efforts have been made to define and classify acute kidney injury to understand the progression of this disease. Furthermore, deviations from structure and kidney function and the current diagnostic guidelines are not adequately placed due to baseline serum creatinine values, which are rarely known and estimated based on glomerular function rate, resulting in misclassification of acute kidney injury staging. Hence, the current guidelines are still developing to improve and understand the clinical implications of risk factors and earlier predictive biomarkers of acute kidney injury. Yet, studies have indicated disadvantages and limitations with the current acute kidney injury biomarkers, including lack of sensitivity and specificity. Therefore, the present narrative review brings together the most current evidenced-based practice and literature associated with the limitations of the gold standard for acute kidney injury diagnoses, the need for novel acute kidney injury biomarkers, and the process for biomarkers to be qualified for diagnostic use under the following sections and themes. The introduction section situates the anatomy and normal and abnormal kidney functions related to acute kidney injury disorders. Guidelines in providing acute kidney injury definitions and classification are then considered, followed by a discussion of the disadvantages of standard markers used to diagnose acute kidney injury. Characteristics of an ideal acute kidney injury biomarker are discussed concerning sensitivity, specificity, and anatomic location of injury. A particular focus on the role and function of emerging biomarkers is discussed in relation to their applications and significance to the prognosis and severity of acute kidney injury. Findings show emerging markers are early indicators of acute kidney injury prediction in different clinical settings. Finally, the process required for a biomarker to be applied for diagnostic use is explained.

Chinese experts' consensus on the application of intensive care big data

The development of intensive care medicine is inseparable from the diversified monitoring data. Intensive care medicine has been closely integrated with data since its birth. Critical care research requires an integrative approach that embraces the complexity of critical illness and the computational technology and algorithms that can make it possible. Considering the need of standardization of application of big data in intensive care, Intensive Care Medicine Branch of China Health Information and Health Care Big Data Society, Standard Committee has convened expert group, secretary group and the external audit expert group to formulate Chinese Experts' Consensus on the Application of Intensive Care Big Data (2022). This consensus makes 29 recommendations on the following five parts: Concept of intensive care big data, Important scientific issues, Standards and principles of database, Methodology in solving big data problems, Clinical application and safety consideration of intensive care big data. The consensus group believes this consensus is the starting step of application big data in the field of intensive care. More explorations and big data based retrospective research should be carried out in order to enhance safety and reliability of big data based models of critical care field.

Prevention and management of antibiotic associated acute kidney injury in critically ill patients: new insights

PURPOSE OF REVIEW

Drug associated kidney injury (D-AKI) occurs in 19-26% of hospitalized patients and ranks as the third to fifth leading cause of acute kidney injury (AKI) in the intensive care unit (ICU). Given the high use of antimicrobials in the ICU and the emergence of new resistant organisms, the implementation of preventive measures to reduce the incidence of D-AKI has become increasingly important.

RECENT FINDINGS

Artificial intelligence is showcasing its capabilities in early recognition of at-risk patients for acquiring AKI. Furthermore, novel synthetic medications and formulations have demonstrated reduced nephrotoxicity compared to their traditional counterparts in animal models and/or limited clinical evaluations, offering promise in the prevention of D-AKI. Nephroprotective antioxidant agents have had limited translation from animal studies to clinical practice. The control of modifiable risk factors remains pivotal in avoiding D-AKI.

SUMMARY

The use of both old and new antimicrobials is increasingly important in combating the rise of resistant organisms. Advances in technology, such as artificial intelligence, and alternative formulations of traditional antimicrobials offer promise in reducing the incidence of D-AKI, while antioxidant medications may aid in minimizing nephrotoxicity. However, maintaining haemodynamic stability using isotonic fluids, drug monitoring, and reducing nephrotoxic burden combined with vigilant antimicrobial stewardship remain the core preventive measures for mitigating D-AKI while optimizing effective antimicrobial therapy.

Plasma indole-3-aldehyde as a novel biomarker of acute kidney injury after cardiac surgery: a reanalysis using prospective metabolomic data

BACKGROUND

Acute kidney injury (AKI) is a frequent complication of cardiac surgery that poses significant risks for both the development of chronic kidney diseases and mortality. Our previous study illustrated that heightened expression levels of faecal and plasma indole metabolites before the operation were associated with ischemic AKI. In this study, we aimed to validate the supposition that plasma indole-3-aldehyde (I3A) could serve as a predictive biomarker for AKI in patients undergoing cardiac surgery.

METHODS

This statistical reanalysis utilized AKI metabolomic data from patients scheduled for cardiac surgery between April 2022 and July 2022 in two tertiary hospitals. Faecal and blood samples were prospectively collected before surgery within 24 h, and variables related to the preoperative, intraoperative, and postoperative periods were recorded. AKI diagnosis was based on the Kidney Disease Improving Global Outcomes criteria.

RESULTS

In this study, 55 patients who underwent cardiac surgery were analyzed, and 27 of them (49.1%) developed postoperative AKI. Before surgery, these patients had significantly higher levels of faecal indole metabolites, including skatole, trans-3-indoleacrylic acid, and 5-methoxyindoleacetic acid. The plasma I3A, clinical model that considered perioperative and intraoperative variables, and their combination had area under the receiver operating characteristic curve (ROC) values of 0.79 (95% CI 0.67-0.91), 0.78 (95% CI 0.66-0.90), and 0.84 (95% CI 0.74-0.94) for predicting AKI, respectively. Furthermore, by utilizing net reclassification improvement and integrated discrimination improvement, plasma I3A showed significant improvements in risk reclassification compared to the clinical model alone.

CONCLUSIONS

The dysregulation of gut microbiota metabolism in patients scheduled for cardiac surgery can result in an increase in indoles from tryptophan metabolism, which may be associated with postoperative acute kidney injury (AKI). This suggests that indoles may serve as a predictive biomarker for AKI in patients undergoing cardiac surgery.

Diagnostic value of combined detection of urine NGAL, KIM-1, and TFF3 in acute tubular necrosis associated with cirrhosis

BACKGROUND

Acute kidney injury (AKI) is a common complication of decompensated cirrhosis with high clinical mortality and poor prognosis, of which acute tubular necrosis (ATN) has the worst prognosis. Timely and accurate identification of ATN is a difficult problem to solve clinically. Previous studies have shown that urinary neutrophil gelatinase-associated lipocalin (NGAL), trefoil factor 3 (TFF3), and kidney injury molecule-1 (KIM-1) have potential value in the differential diagnosis of ATN and other types of AKI in patients with liver cirrhosis, but they still cannot be applied in clinical practice due to the low diagnostic efficacy. It is necessary to further explore whether the combined detection of the indicators can improve their diagnostic efficacy for ATN associated with cirrhosis.

AIM

To analyze the value of urinary NGAL, KIM-1, and TFF3, either alone or in combination, in the differential diagnosis of ATN in patients with cirrhosis complicated with AKI, and explore the cut-off values of urinary NGAL and other indicators in the differential diagnosis of ATN.

METHODS

A total of 190 patients with decompensated cirrhosis were selected, including 108 patients with AKI. They were divided into different subgroups according to the cause of AKI, including 33 cases of prerenal azotemia, 27 cases of acute renal injury with hepatorenal syndrome, and 48 cases of ATN. The value of urinary NGAL, TFF3, and KIM-1, either alone or in combination, in the differential diagnosis of ATN in patients with cirrhosis complicated with AKI was then assessed.

RESULTS

Urinary NGAL was of great value in the differential diagnosis of ATN in patients with cirrhosis complicated with AKI. The area under the curve (AUC) was 0.902; when the diagnostic threshold was 271.8 μg/g Cr, the sensitivity was 81.3% and the specificity was 85.0%. The combination of two biomarkers could improve the efficacy of differential diagnosis, with the diagnostic perfomance of urinary NGAL combined with urinary TFF3 being the best (AUC = 0.933, sensitivity 85.4%, specificity 88.3%).

CONCLUSION

Urinary NGAL, KIM-1, and TFF3 are of great value in differentiating ATN from other types of AKI in patients with cirrhosis. The combined detection of any two of these biomarkers can further improve the diagnostic efficiency, which is worthy of further study and clinical promotion.

Association between nutritional status scores and the 30-day mortality in patients with acute kidney injury: an analysis of MIMIC-III database

BACKGROUND

Studies have proven that the risk of acute kidney injury (AKI) increased in patients with malnutrition. Prognostic nutritional index (PNI) and geriatric nutritional risk index (GNRI) were general tools to predict the risk of mortality, but the prognostic value of them for in-hospital mortality among patients with AKI have not been validated yet. Herein, this study aims to explore the association between PNI and GNRI and 30-day mortality in patients with AKI.

METHODS

Demographic and clinical data of 863 adult patients with AKI were extracted from the Medical Information Mart for Intensive Care III (MIMIC-III) database in 2001-2012 in this retrospective cohort study. Univariate and multivariate Cox proportional regression analyses were used to explore the association between PNI and GNRI and 30-day mortality. The evaluation indexes were hazard ratios (HRs) and 95% confidence intervals (CIs). Subgroup analyses of age, Sequential Organ Failure Assessment (SOFA) score and Simplified Acute Physiology (SAPS-II) score were also performed.

RESULTS

Totally, 222 (26.71%) patients died within 30 days. After adjusting for covariates, PNI ≥ 28.5 [HR = 0.71, 95%CI: (0.51-0.98)] and GNRI ≥ 83.25 [HR = 0.63, 95%CI: (0.47-0.86)] were both associated with low risk of 30-day mortality. These relationships were also found in patients who aged ≥ 65 years old. Differently, high PNI level was associated with low risk of 30-day mortality among patients with SOFA score < 6 or SAPS-II score < 43, while high GNRI was associated with low risk of 30-day mortality among those who with SOFA score ≥ 6 or SAPS-II score ≥ 43 (all P < 0.05).

CONCLUSION

PNI and GNRI may be potential predictors of 30-day mortality in patients with AKI. Whether the PNI is more recommended for patients with mild AKI, while GNRI for those with severe AKI is needed further exploration.

Machine learning-based prediction model of acute kidney injury in patients with acute respiratory distress syndrome

BACKGROUND

Acute kidney injury (AKI) can make cases of acute respiratory distress syndrome (ARDS) more complex, and the combination of the two can significantly worsen the prognosis. Our objective is to utilize machine learning (ML) techniques to construct models that can promptly identify the risk of AKI in ARDS patients.

METHOD

We obtained data regarding ARDS patients from the Medical Information Mart for Intensive Care III (MIMIC-III) and MIMIC-IV databases. Within the MIMIC-III dataset, we developed 11 ML prediction models. By evaluating various metrics, we visualized the importance of its features using Shapley additive explanations (SHAP). We then created a more concise model using fewer variables, and optimized it using hyperparameter optimization (HPO). The model was validated using the MIMIC-IV dataset.

RESULT

A total of 928 ARDS patients without AKI were included in the analysis from the MIMIC-III dataset, and among them, 179 (19.3%) developed AKI after admission to the intensive care unit (ICU). In the MIMIC-IV dataset, there were 653 ARDS patients included in the analysis, and among them, 237 (36.3%) developed AKI. A total of 43 features were used to build the model. Among all models, eXtreme gradient boosting (XGBoost) performed the best. We used the top 10 features to build a compact model with an area under the curve (AUC) of 0.850, which improved to an AUC of 0.865 after the HPO. In extra validation set, XGBoost_HPO achieved an AUC of 0.854. The accuracy, sensitivity, specificity, positive prediction value (PPV), negative prediction value (NPV), and F1 score of the XGBoost_HPO model on the test set are 0.865, 0.813, 0.877, 0.578, 0.957 and 0.675, respectively. On extra validation set, they are 0.724, 0.789, 0.688, 0.590, 0.851, and 0.675, respectively.

CONCLUSION

ML algorithms, especially XGBoost, are reliable for predicting AKI in ARDS patients. The compact model maintains excellent predictive ability, and the web-based calculator improves clinical convenience. This provides valuable guidance in identifying AKI in ARDS, leading to improved patient outcomes.

Preoperative urine neutrophil gelatinase-associated lipocalin predicts mortality in colorectal cancer patients after laparoscopic surgery: A single-center study

Purpose

To determine the rate of acute kidney injury (AKI) after laparoscopic colorectal cancer (CRC) surgery and the predictive value of urine neutrophil gelatinase-associated lipocalin (uNGAL) for postoperative AKI and mortality during 3 years of follow-up.

Methods

A total of 216 CRC patients who had undergone laparoscopic surgery were included in our study. We divided all patients into two groups, including group 1 (n = 31) with postoperative AKI and group 2 (n = 185) without postoperative AKI. Urine NGAL was measured using the ELISA technique. Clinical and laboratory data were collected the day before surgery. Postoperative AKI included events occurring within 7 days of the index operation, and mortality was obtained during 3 years of follow-up.

Results

The ratio of postoperative AKI was 14.35% (31/216 patients). The urine NGAL level in group 1 was significantly higher than in group 2, p < 0.001. At cut-off value = 14.94 ng/mL, uNGAL has a predictive value for AKI (area under the curve [AUC] = 0.858, p < 0.001). After 3 years of follow-up, the total mortality rate was 7.9%. The mortality rate in group 1 (45.2%) was significantly higher than in group 2 (1.6%) with p < 0.001). At cut-off value = 19.85 ng/mL, uNGAL has a predictive value for mortality (AUC = 0.941, p < 0.001).

Conclusions

The rate of acute kidney injury after laparoscopic CRC surgery was 14.35%. Preoperative urine NGAL has a good predictive value for postoperative acute kidney injury and mortality during 3 years of follow-up.

Self-assembled hemin-conjugated heparin with dual-enzymatic cascade reaction activities for acute kidney injury

Nanozymes have prominent catalytic activities with high stability as a substitute for unstable and expensive natural enzymes. However, most nanozymes are metal/inorganic nanomaterials, facing difficulty in clinical translation due to their unproven biosafety and limited biodegradability issues. Hemin, an organometallic porphyrin, was newly found to possess superoxide dismutase (SOD) mimetic activity along with previously known catalase (CAT) mimetic activity. However, hemin has poor bioavailability due to its low water solubility. Therefore, a highly biocompatible and biodegradable organic-based nanozyme system with SOD/CAT mimetic cascade reaction activity was developed by conjugating hemin to heparin (HepH) or chitosan (CS-H). Between them, Hep-H formed a smaller (<50 nm) and more stable self-assembled nanostructure and even possessed much higher and more stable SOD and CAT activities as well as the cascade reaction activity compared to CS-H and free hemin. Hep-H also showed a better cell protection effect against reactive oxygen species (ROS) compared to CS-H and hemin in vitro. Furthermore, Hep-H was selectively delivered to the injured kidney upon intravenous administration at the analysis time point (24 h) and exhibited excellent therapeutic effects on an acute kidney injury model by efficiently removing ROS, reducing inflammation, and minimizing structural and functional damage to the kidney.

Antioxidative 0-dimensional nanodrugs overcome obstacles in AKI antioxidant therapy

Acute kidney injury (AKI) is a commonly encountered syndrome associated with various aetiologies and pathophysiological processes leading to enormous health risks and economic losses. In the absence of specific drugs to treat AKI, hemodialysis remains the primary clinical treatment for AKI patients. The revelation of the pathology opens new horizons for antioxidant therapy in the treatment of AKI. However, small molecule antioxidant drugs and common nanozymes have failed to challenge AKI due to their unsatisfactory drug properties and renal physiological barriers. 0-Dimensional (0D) antioxidant nanodrugs stand out at this time thanks to their small size and high performance. Recently, a number of research studies have been carried out around 0D nanodrugs for alleviating AKI, and their multi-antioxidant enzyme mimetic activities, smooth glomerular filtration barrier permeability and excellent biocompatibility have been investigated. Here, we comprehensively summarize recent advances in 0D nanodrugs for AKI antioxidant therapy. We classify these representative studies into three categories according to the characteristics of 0D nanomaterials, namely ultra-small metal nanodots, inorganic non-metallic quantum dots and polymer nanodots. We focus on the antioxidant mechanisms and their distribution in vivo in each inspiring work, and the purpose and ingenuity of each design are rigorously captured and described. Finally, we provide our reflections and prospects for 0D antioxidant nanodrugs in AKI treatment. This mini review provides unique insights and valuable clues in the design of 0D nanodrugs and other kidney absorbable drugs.

Acute Kidney Failure: Current Challenges and New Perspectives

Acute kidney failure, also called acute kidney injury (AKI), is defined by a sudden loss of kidney function that is conventionally determined on the basis of increased serum creatinine levels and reduced urinary output [...].

Nanodrugs alleviate acute kidney injury: Manipulate RONS at kidney

Currently, there are no clinical drugs available to treat acute kidney injury (AKI). Given the high prevalence and high mortality rate of AKI, the development of drugs to effectively treat AKI is a huge unmet medical need and a research hotspot. Although existing evidence fully demonstrates that reactive oxygen and nitrogen species (RONS) burst at the AKI site is a major contributor to AKI progression, the heterogeneity, complexity, and unique physiological structure of the kidney make most antioxidant and anti-inflammatory small molecule drugs ineffective because of the lack of kidney targeting and side effects. Recently, nanodrugs with intrinsic kidney targeting through the control of size, shape, and surface properties have opened exciting prospects for the treatment of AKI. Many antioxidant nanodrugs have emerged to address the limitations of current AKI treatments. In this review, we systematically summarized for the first time about the emerging nanodrugs that exploit the pathological and physiological features of the kidney to overcome the limitations of traditional small-molecule drugs to achieve high AKI efficacy. First, we analyzed the pathological structural characteristics of AKI and the main pathological mechanism of AKI: hypoxia, harmful substance accumulation-induced RONS burst at the renal site despite the multifactorial initiation and heterogeneity of AKI. Subsequently, we introduced the strategies used to improve renal targeting and reviewed advances of nanodrugs for AKI: nano-RONS-sacrificial agents, antioxidant nanozymes, and nanocarriers for antioxidants and anti-inflammatory drugs. These nanodrugs have demonstrated excellent therapeutic effects, such as greatly reducing oxidative stress damage, restoring renal function, and low side effects. Finally, we discussed the challenges and future directions for translating nanodrugs into clinical AKI treatment.

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AKI is a common clinical acute syndrome with high morbidity and mortality but without effective clinical drug available.

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Hypoxia and accumulation of toxic substances are key pathological features of various heterogeneous AKI.

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Excessive RONS is the core of the pathological mechanism of AKI.

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The development of nanodrugs is expected to achieve successful treatment in AKI.

Emerging Sonodynamic Therapy-Based Nanomedicines for Cancer Immunotherapy

Cancer immunotherapy effect can be greatly enhanced by other methods to induce immunogenic cell death (ICD), which has profoundly affected immunotherapy as a highly efficient paradigm. However, these treatments have significant limitations, either by causing damage of the immune system or limited to superficial tumors. Sonodynamic therapy (SDT) can induce ICD to promote immunotherapy without affecting the immune system because of its excellent spatiotemporal selectivity and low side effects. Nevertheless, SDT is still limited by low reactive oxygen species yield and the complex tumor microenvironment. Recently, some emerging SDT-based nanomedicines have made numerous attractive and encouraging achievements in the field of cancer immunotherapy due to high immunotherapeutic efficiency. However, this cross-cutting field of research is still far from being widely explored due to huge professional barriers. Herein, the characteristics of the tumor immune microenvironment and the mechanisms of ICD are firstly systematically summarized. Subsequently, the therapeutic mechanism of SDT is fully summarized, and the advantages and limitations of SDT are discussed. The representative advances of SDT-based nanomedicines for cancer immunotherapy are further highlighted. Finally, the application prospects and challenges of SDT-based immunotherapy in future clinical translation are discussed.

Predicting the risk of acute kidney injury after cardiopulmonary bypass: development and assessment of a new predictive nomogram

BACKGROUND

Acute kidney injury (AKI) is a common and severe complication of cardiac surgery with cardiopulmonary bypass (CPB). This study aimed to establish a model to predict the probability of postoperative AKI in patients undergoing cardiac surgery with CPB.

METHODS

We conducted a retrospective, multicenter study to analyze 1082 patients undergoing cardiac surgery under CPB. The least absolute shrinkage and selection operator regression model was used to optimize feature selection for the AKI model. Multivariable logistic regression analysis was applied to build a prediction model incorporating the feature selected in the previously mentioned model. Finally, we used multiple methods to evaluate the accuracy and clinical applicability of the model.

RESULTS

Age, gender, hypertension, CPB duration, intraoperative 5% bicarbonate solution and red blood cell transfusion, urine volume were identified as important factors. Then, these risk factors were created into nomogram to predict the incidence of AKI after cardiac surgery under CPB.

CONCLUSION

We developed a nomogram to predict the incidence of AKI after cardiac surgery. This model can be used as a reference tool for evaluating early medical intervention to prevent postoperative AKI.

The rate of acute kidney injury (AKI) alert detection by the attending physicians was associated with the prognosis of patients with AKI

Introduction

Early identification of AKI was always considered to improve patients' prognosis. Some studies found that AKI early warning tools didn't affect patients' prognosis. Therefore, additional studies were necessary to explore the reasons.

Methods

This study was a secondary analysis of a multicenter randomized controlled trial that found electronic health record warnings for AKI did not influence patients' prognoses. Univariate, multivariate, subgroup, curve fitting, and threshold effect analysis were used to explore the association between AKI warnings detected by attending physicians and the patient's prognosis.

Results

A total of 6,030 AKI patients were included in the study. The patients were classified into two groups based on the rate of AKI alerts detected by attending physicians: the partial group (n = 5,377), and the complete group (n = 653). In comparison to the partial group, the complete group significantly decreased 14-day AKI progression, 14-day dialysis, and 14-day mortality, with adjusted ORs of 0.48 (0.33, 0.70), 0.26 (0.09, 0.77), and 0.53 (0.33, 0.84) respectively, and the complete group significantly improve the discharge to home, with an OR value of 1.50 (1.21, 1.87). When the rate of AKI alerts detected by the attending physicians as a continuity variable, we found that the rate of alerts seen by attending physicians was associated with 14-day mortality and the discharge to home, with adjusted ORs of 1.76 (1.11, 2.81) and 1.42 (1.13, 1.80). The sensitivity analysis, curve-fitting analysis, and threshold effect analysis also showed that the rate of alert seen by the attending physician was correlated with the patient's prognosis.

Conclusion

The rate of AKI alert detection by attending physician were related to the patient's prognosis. The higher the rate of AKI alert detection by attending physicians, the better the prognosis of patients with AKI.

Ultra-small molybdenum-based nanodots as an antioxidant platform for effective treatment of periodontal disease

Periodontal disease (PD) is a local inflammatory disease with high morbidity, manifesting tissue destruction results from inflammation of the host immune response to bacterial antigens and irritants. The supportive function of connective tissue and skeletal tissue can be jeopardized without prompt and effective intervention, representing the major cause of tooth loss. However, traditional treatments exhibited great limitations, such as low efficacies, causing serious side effects and recurrent inflammatory episodes. As a major defense mechanism, reactive oxygen species (ROS) play important roles in the pathological progression of PD. Antioxidant therapy is widely believed to be an effective strategy for ROS-triggered diseases, including oxidative stress-induced PD. Most antioxidants can only scavenge one or a few limited kinds of ROS and cannot handle all kinds. In addition, current antioxidant nanomaterials present limitations associated with toxicity, low stability, and poor biocompatibility. To this end, we develop ultra-small molybdenum-based nanodots (MoNDs) with strong ROS in oxidative stress-induced PD. To the best of our knowledge, this is the first time that MoNDs have been used for PD. In the present study, MoNDs have shown extremely good therapeutic effects as ROS scavengers. Spectroscopic and in vitro experiments provided strong evidence for the roles of MoNDs in eliminating multiple ROS and inhibiting ROS-induced inflammatory responses. In addition, the mouse model of PD was established and demonstrated the feasibility of MoNDs as powerful antioxidants. It can alleviate periodontal inflammation by scavenging multiple ROS without obvious side effects and exhibit good biocompatibility. Thus, this newly developed nanomedicine is effective in scavenging ROS and inhibiting M1 phenotypic polarization, which provides promising candidates for the treatment of PD.

Immune repertoire analysis of normal Chinese donors at different ages

OBJECTIVES

This study investigated the characteristics of the immune repertoire in normal Chinese individuals of different ages.

MATERIALS AND METHODS

In this study, all seven receptor chains from both B and T cells in peripheral blood of 16 normal Chinese individuals from two age groups were analyzed using high-throughput sequencing and dimer-avoided multiplex PCR amplification. Normal in this study is defined as no chronic, infectious or autoimmune disease within 6 months prior to blood draw.

RESULTS

We found that compared with the younger group, the clonal expression of T-cell receptor repertoire increased in the older group, while diversity decreased. In addition, we found that the T-cell receptor repertoire was more significantly affected by age than the B-cell receptor repertoire, including significant differences in the use of the unique TCR-alpha and TCR-beta V-J gene combinations, in the two groups of normal participants. We further analyzed the degree of complementarity determining region 3 sequence sharing between the two groups, and found shared TCR-alpha, TCR-gamma, immunoglobulin-kappa and immunoglobulin-lambda chain complementarity determining region 3 sequences in all subjects.

CONCLUSION

Taken together, our study gives us a better understanding of the immune repertoire of different normal Chinese people, and these results can be applied to the treatment of age-related diseases. Immune repertoire analysis also allows us to observe participant's wellness, aiding in early-stage diagnosis.

Nanodrugs Manipulating Endoplasmic Reticulum Stress for Highly Effective Antitumor Therapy

Cancer is one of the leading causes of death worldwide due to high morbidity and mortality. Many attempts and efforts have been devoted to fighting cancer. Owing to the significant role of the endoplasmic reticulum (ER) in cell function, inducing ER stress can be promising for cancer treatment. However, the sustained activation of cytoprotective unfolded protein response (UPR) presents a tremendous obstacle for drugs in inducing unsolved ER stress in tumor cells, especially small-molecule drugs with poor bioavailability. Therefore, many emerging nanodrugs inducing and amplifying ER stress have been developed for efficient cancer treatment. More importantly, the novel discovery of ER stress in immunogenic cell death (ICD) makes it possible to repurpose antitumor drugs for immunotherapy through nanodrug-based strategies amplifying ER stress. Therefore, this mini-review aims to provide a comprehensive summary of the latest developments of the strategies underlying nanodrugs in the treatment of cancer via manipulating ER stress. Meanwhile, the prospects of ER stress–inducing nanodrugs for cancer treatment are systematically discussed, which provide a sound platform for novel therapeutic insights and inspiration for the design of nanodrugs in treating cancer.

Nanotech Probes: A Revolution in Cancer Diagnosis

Recent advances in nanotechnologies for cancer diagnosis and treatment have received considerable attention worldwide. Nanoparticles are being used to create nanodrugs and probes to diagnose and treat a variety of diseases, including cancer. Nanomedicines have unique advantages, such as increased surface-to-volume ratios, which enable them to interact with, absorb, and deliver small biomolecules to a very specific target, thereby improving the effectiveness of both probes and drugs. Nanoprobe biotechnology also plays an important role in the discovery of novel cancer biomarkers, and nanoprobes have become an important part of early clinical diagnosis of cancer. Various organic and inorganic nanomaterials have been developed as biomolecular carriers for the detection of disease biomarkers. Thus, we designed this review to evaluate the advances in nanoprobe technology in tumor diagnosis.