Succinate promotes pulmonary fibrosis through GPR91 and predicts death in idiopathic pulmonary fibrosis.

Idiopathic pulmonary fibrosis (IPF) is believed to be associated with a notable disruption of cellular energy metabolism. By detecting the changes of energy metabolites in the serum of patients with pulmonary fibrosis, we aimed to investigate the diagnostic and prognostic value of energy metabolites in IPF, and further elucidated the mechanism of their involvement in pulmonary fibrosis. Through metabolomics research, it was discovered that the TCA cycle intermediates changed dramatically in IPF patients. In another validation cohort of 55 patients with IPF compared to 19 healthy controls, it was found that succinate, an intermediate product of TCA cycle, has diagnostic and prognostic value in IPF. The cut-off levels of serum succinate were 98.36 µM for distinguishing IPF from healthy controls (sensitivity, 83.64%; specificity, 63.16%; likelihood ratio, 2.27, respectively). Moreover, a high serum succinate level was independently associated with higher rates of disease progression (OR 13.087, 95%CI (2.819-60.761)) and mortality (HR 3.418, 95% CI (1.308-8.927)). In addition, accumulation of succinate and increased expression of the succinate receptor GPR91 were found in both IPF patients and BLM mouse models of pulmonary fibrosis. Reducing succinate accumulation in BLM mice alleviated pulmonary fibrosis and 21d mortality, while exogenous administration of succinate can aggravate pulmonary fibrosis in BLM mice. Furthermore, GPR91 deficiency protected against lung fibrosis caused by BLM. In vitro, succinate promoted the activation of lung fibroblasts by activating ERK pathway through GPR91. In summary, succinate is a promising biomarker for diagnosis and prognosis of IPF. The accumulation of succinate may promote fibroblast activation through GPR91 and pulmonary fibrosis.

Mefunidone ameliorates acute liver failure in mice by inhibiting MKK4-JNK pathway.

Acute liver failure (ALF) is a critical condition that can lead to substantial liver dysfunction. It is characterized by complex clinical manifestations and rapid progression, presenting significant challenges in diagnosis and treatment. We investigated the protective effect of mefunidone (MFD), a novel antifibrosis pyridone agent, on ALF in mice, and explored its potential mechanism of action. MFD pretreatment can alleviate lipopolysaccharide (LPS) and d-galactosamine (D-GalN)-induced ALF, reduce hepatocyte apoptosis, and reduce inflammation and oxidative stress. Additionally, MFD alleviated LPS/D-GalN-stimulated reactive oxygen species (ROS) production and cell death in AML12 cells. RNA sequencing enrichment analysis showed that MFD significantly affected the Mitogen-Activated Protein Kinase (MAPK) pathway. In vivo and in vitro experiments showed that MFD inhibited MKK4 and JNK phosphorylation. JNK activation caused by MKK4 and JNK activators could eliminate the therapeutic effect of MFD on AML12. In addition, MFD pretreatment alleviated ConA-induced ALF, reduced inflammation and oxidative stress in mice, and reduced mouse mortality. These results suggest that MFD can potentially protect against ALF, partially by inhibiting the MKK4-JNK pathway, and is a promising new therapeutic drug for ALF.

Kokusaginine attenuates renal fibrosis by inhibiting the PI3K/AKT signaling pathway.

Kokusaginine is an active ingredient alkaloid that has been isolated and extracted from Ruta graveolens L. Some researches have indicated that alkaloids possess anti-inflammatory and antioxidant effects. Nevertheless, the potential nephroprotective effects of kokusaginine on renal fibrosis remain undetermined. This study was conducted to examine the protective effect of kokusaginine on renal fibrosis and to explore the underlying mechanisms using both in vivo and in vitro models. Renal fibrosis was induced in male C57BL/6 J mice by feeding with 0.2% adenine-containing food and UUO surgery. Kokusaginine was administered orally simultaneously after the establishment of renal fibrosis. Renal function was measured by serum levels of creatinine and urea nitrogen. Renal pathological changes were assessed by HE staining and Masson staining. Western blotting was employed to detect the expression levels of fibrosis-related proteins in mice and cells. Additionally, network pharmacology analysis and RNA-seq were utilized to predict the pathways through which kokusaginine could exert its anti-fibrotic effects. The treatment with kokusaginine enhanced renal function, alleviated renal histoarchitectural lesions, and mitigated renal fibrosis in the renal fibrosis models. The network pharmacology and RNA-seq enrichment analysis of the KEGG pathway demonstrated that kokusaginine could exert anti-renal fibrosis activity via the PI3K/AKT signaling pathway. And the results were verified in both in vitro and in vivo experiments. In conclusion, our data implied that kokusaginine inhibited the activation of the PI3K/AKT signaling pathway both in vitro and in vivo, and suppressed the formation of renal fibrosis. Thus, the kokusaginine-mediated PI3K/AKT signaling pathway may represent a novel approach for the treatment of renal fibrosis.

Characterization of macrophages in ischemia-reperfusion injury-induced acute kidney injury based on single-cell RNA-Seq and bulk RNA-Seq analysis.

Acute kidney injury (AKI) is a complex disease, with macrophages playing a vital role in its progression. However, the mechanism of macrophage function remains unclear and strategies targeting macrophages in AKI are controversial. To address this issue, we used single-cell RNA-seq analysis to identify macrophage sub-types involved in ischemia-reperfusion-induced AKI, and then screened for associated hub genes using intersecting bulk RNA-seq data. The single-cell and bulk RNA-seq datasets were obtained from the Gene Expression Omnibus (GEO) database. Screening of differentially-expressed genes (DEGs) and pseudo-bulk DEG analyses were used to identify common hub genes. Pseudotime and trajectory analyses were performed to investigate the progression of cell differentiation. CellChat analysis was performed to reveal the crosstalk between cell clusters. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses were used to identify enriched pathways in the cell clusters. Immunofluorescence and RT-PCR were preformed to validate the expression of the identified hub genes. Four hub genes, Vim, S100a6, Ier3, and Ccr1, were identified in the infiltrated macrophages between normal samples and those 3 days after ischemia-reperfusion renal injury (IRI); all were associated with the progression of IRI-induced AKI. Increased expression of Vim, S100a6, Ier3, and Ccr1 in infiltrated macrophages may be associated with inflammatory responses and may mediate crosstalk between macrophages and renal tubular epithelial cells under IRI conditions. Our results reveal that Ier3 may be critical in AKI, and that Vim, S100a6, Ier3, and Ccr1 may act as novel biomarkers and potential therapeutic targets for IRI-induced AKI.

The prediction of in-hospital mortality in elderly patients with sepsis-associated acute kidney injury utilizing machine learning models.

Background: Sepsis-associated acute kidney injury (SA-AKI) is a severe complication associated with poorer prognosis and increased mortality, particularly in elderly patients. Currently, there is a lack of accurate mortality risk prediction models for these patients in clinic. Objectives: This study aimed to develop and validate machine learning models for predicting in-hospital mortality risk in elderly patients with SA-AKI. Methods: Machine learning models were developed and validated using the public, high-quality Medical Information Mart for Intensive Care (MIMIC)-IV critically ill database. The recursive feature elimination (RFE) algorithm was employed for key feature selection. Eleven predictive models were compared, with the best one selected for further validation. Shapley Additive Explanations (SHAP) values were used for visualization and interpretation, making the machine learning models clinically interpretable. Results: There were 16,154 patients with SA-AKI in the MIMIC-IV database, and 8426 SA-AKI patients were included in this study (median age: 77.0 years; female: 45%). 7728 patients excluded based on these criteria. They were randomly divided into a training cohort (5,934, 70%) and a validation cohort (2,492, 30%). Nine key features were selected by the RFE algorithm. The CatBoost model achieved the best performance, with an AUC of 0.844 in the training cohort and 0.804 in the validation cohort. SHAP values revealed that AKI stage, PaO2, and lactate were the top three most important features contributing to the CatBoost model. Conclusion: We developed a model capable of predicting the risk of in-hospital mortality in elderly patients with SA-AKI.

Pyroptosis-related signatures predict immune characteristics and prognosis in IPF.

The purpose of this work was to use integrated bioinformatics analysis to screen for pyroptosis-related genes (PRGs) and possible immunological phenotypes linked to the development and course of IPF. Transcriptome sequencing datasets GSE70866, GSE47460 and GSE150910 were obtained from GEO database. From the GSE70866 database, 34 PRGs with differential expression were found in IPF as compared to healthy controls. In addition, a diagnostic model containing 4 genes PRGs (CAMP, MKI67, TCEA3 and USP24) was constructed based on LASSO logistic regression. The diagnostic model showed good predictive ability to differentiate between IPF and healthy, with ROC-AUC ranging from 0.910 to 0.997 in GSE70866 and GSE150910 datasets. Moreover, based on a combined cohort of the Freiburg and the Siena cohorts from GSE70866 dataset, we identified ten PRGs that might predict prognosis for IPF. We constructed a prognostic model that included eight PRGs (CLEC5A, TREM2, MMP1, IRF2, SEZ6L2, ADORA3, NOS2, USP24) by LASSO Cox regression and validated it in the Leuven cohort. The risk model divided IPF patients from the combined cohort into high-risk and low-risk subgroups. There were significant differences between the two subgroups in terms of IPF survival and GAP stage. There is a close correlation between leukocyte migration, plasma membrane junction, and poor prognosis in a high-risk subgroup. Furthermore, a high-risk score was associated with more plasma cells, activated NK cells, monocytes, and activated mast cells. Additionally, we identified HDAC inhibitors in the cMAP database that might be therapeutic for IPF. To summarize, pyroptosis and its underlying immunological features are to blame for the onset and progression of IPF. PRG-based predictive models and drugs may offer new treatment options for IPF.

A novel immune-related gene signature for predicting immunotherapy outcomes and survival in clear cell renal cell carcinoma.

Clear cell renal carcinoma (ccRCC) is one of the most common cancers worldwide. In this study, a new model of immune-related genes was developed to predict the overall survival and immunotherapy efficacy in patients with ccRCC. Immune-related genes were obtained from the ImmPort database. Clinical data and transcriptomics of ccRCC samples were downloaded from GSE29609 and The Cancer Genome Atlas. An immune-related gene-based prognostic model (IRGPM) was developed using the least absolute shrinkage and selection operator regression algorithm and multivariate Cox regression. The reliability of the developed models was evaluated by Kaplan-Meier survival curves and time-dependent receiver operating characteristic curves. Furthermore, we constructed a nomogram based on the IRGPM and multiple clinicopathological factors, along with a calibration curve to examine the predictive power of the nomogram. Overall, this study investigated the association of IRGPM with immunotherapeutic efficacy, immune checkpoints, and immune cell infiltration. Eleven IRGs based on 528 ccRCC samples significantly associated with survival were used to construct the IRGPM. Remarkably, the IRGPM, which consists of 11 hub genes (SAA1, IL4, PLAUR, PLXNB3, ANGPTL3, AMH, KLRC2, NR3C2, KL, CSF2, and SEMA3G), was found to predict the survival of ccRCC patients accurately. The calibration curve revealed that the nomogram developed with the IRGPM showed high predictive performance for the survival probability of ccRCC patients. Moreover, the IRGPM subgroups showed different levels of immune checkpoints and immune cell infiltration in patients with ccRCC. IRGPM might be a promising biomarker of immunotherapeutic responses in patients with ccRCC. Overall, the established IRGPM was valuable for predicting survival, reflecting the immunotherapy response and immune microenvironment in patients with ccRCC.

Peroxiredoxin 1 aggravates acute kidney injury by promoting inflammation through Mincle/Syk/NF-κB signaling.

Damage-associated molecular patterns (DAMPs) are a cause of acute kidney injury (AKI). Our knowledge of these DAMPs remains incomplete. Here, we report serum peroxiredoxin 1 (Prdx1) as a novel DAMP for AKI. Lipopolysaccharide (LPS) and kidney ischemia/reperfusion injury instigated AKI with concurrent increases in serum Prdx1 and reductions of Prdx1 expression in kidney tubular epithelial cells. Genetic knockout of Prdx1 or use of a Prdx1-neutralizing antibody protected mice from AKI and this protection was impaired by introduction of recombinant Prdx1 (rPrdx1). Mechanistically, lipopolysaccharide increased serum and kidney proinflammatory cytokines, macrophage infiltration, and the content of M1 macrophages. All these events were suppressed in Prdx1-/- mice and renewed upon introduction of rPrdx1. In primary peritoneal macrophages, rPrdx1 induced M1 polarization, activated macrophage-inducible C-type lectin (Mincle) signaling, and enhanced proinflammatory cytokine production. Prdx1 interacted with Mincle to initiate acute kidney inflammation. Of note, rPrdx1 upregulated Mincle and the spleen tyrosine kinase Syk system in the primary peritoneal macrophages, while knockdown of Mincle abolished the increase in activated Syk. Additionally, rPrdx1 treatment enhanced the downstream events of Syk, including transcription factor NF-κB signaling pathways. Furthermore, serum Prdx1 was found to be increased in patients with AKI; the increase of which was associated with kidney function decline and inflammatory biomarkers in patient serum. Thus, kidney-derived serum Prdx1 contributes to AKI at least in part by activating Mincle signaling and downstream pathways.

Fluorofenidone protects against acute liver failure in mice by regulating MKK4/JNK pathway.

AIMS: Acute liver failure (ALF) is a life-threatening disease characterized by abrupt and extensive hepatic necrosis and apoptosis, resulting in high mortality. The approved drug, N-acetylcysteine (NAC), is only effective for acetaminophen (APAP)-associated ALF at the early stage. Thus, we investigate whether fluorofenidone (AKF-PD), a novel antifibrosis pyridone agent, protects against ALF in mice and explore its underlying mechanisms. METHODS: ALF mouse models were established using APAP or lipopolysaccharide/D-galactosamine (LPS/D-Gal). Anisomycin and SP600125 were used as JNK activator and inhibitor, respectively, and NAC served as a positive control. Mouse hepatic cell line AML12 and primary mouse hepatocytes were used for in vitro studies. RESULTS: AKF-PD pretreatment alleviated APAP-induced ALF with decreased necrosis, apoptosis, reactive oxygen species (ROS) markers, and mitochondrial permeability transition in liver. Additionally, AKF-PD alleviated mitochondrial ROS stimulated by APAP in AML12 cells. RNA-sequencing in the liver and subsequent gene set enrichment analysis showed that AKF-PD significantly impacted MAPK and IL-17 pathway. In vitro and in vivo studies demonstrated that AKF-PD inhibited APAP-induced phosphorylation of MKK4/JNK, while SP600125 only inhibited JNK phosphorylation. The protective effect of AKF-PD was abolished by anisomycin. Similarly, AKF-PD pretreatment abolished hepatotoxicity caused by LPS/D-Gal, decreased ROS levels, and diminished inflammation. Furthermore, unlike NAC, AKF-PD, inhibited the phosphorylation of MKK4 and JNK upon pretreatment, and improved survival in cases of LPS/D-Gal-induced mortality with delayed dosing. CONCLUSIONS: In summary, AKF-PD can protect against ALF caused by APAP or LPS/D-Gal, in part, via regulating MKK4/JNK pathway. AKF-PD might be a novel candidate drug for ALF.

Corrigendum: Protective effects of Mefunidone on ischemia-reperfusion injury/folic acid-induced acute kidney injury.

[This corrects the article DOI: 10.3389/fphar.2022.1043945.].

Identification of common molecular signatures of SARS-CoV-2 infection and its influence on acute kidney injury and chronic kidney disease.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the main cause of COVID-19, causing hundreds of millions of confirmed cases and more than 18.2 million deaths worldwide. Acute kidney injury (AKI) is a common complication of COVID-19 that leads to an increase in mortality, especially in intensive care unit (ICU) settings, and chronic kidney disease (CKD) is a high risk factor for COVID-19 and its related mortality. However, the underlying molecular mechanisms among AKI, CKD, and COVID-19 are unclear. Therefore, transcriptome analysis was performed to examine common pathways and molecular biomarkers for AKI, CKD, and COVID-19 in an attempt to understand the association of SARS-CoV-2 infection with AKI and CKD. Three RNA-seq datasets (GSE147507, GSE1563, and GSE66494) from the GEO database were used to detect differentially expressed genes (DEGs) for COVID-19 with AKI and CKD to search for shared pathways and candidate targets. A total of 17 common DEGs were confirmed, and their biological functions and signaling pathways were characterized by enrichment analysis. MAPK signaling, the structural pathway of interleukin 1 (IL-1), and the Toll-like receptor pathway appear to be involved in the occurrence of these diseases. Hub genes identified from the protein-protein interaction (PPI) network, including DUSP6, BHLHE40, RASGRP1, and TAB2, are potential therapeutic targets in COVID-19 with AKI and CKD. Common genes and pathways may play pathogenic roles in these three diseases mainly through the activation of immune inflammation. Networks of transcription factor (TF)-gene, miRNA-gene, and gene-disease interactions from the datasets were also constructed, and key gene regulators influencing the progression of these three diseases were further identified among the DEGs. Moreover, new drug targets were predicted based on these common DEGs, and molecular docking and molecular dynamics (MD) simulations were performed. Finally, a diagnostic model of COVID-19 was established based on these common DEGs. Taken together, the molecular and signaling pathways identified in this study may be related to the mechanisms by which SARS-CoV-2 infection affects renal function. These findings are significant for the effective treatment of COVID-19 in patients with kidney diseases.

Machine learning for the prediction of all-cause mortality in patients with sepsis-associated acute kidney injury during hospitalization.

Background: Sepsis-associated acute kidney injury (S-AKI) is considered to be associated with high morbidity and mortality, a commonly accepted model to predict mortality is urged consequently. This study used a machine learning model to identify vital variables associated with mortality in S-AKI patients in the hospital and predict the risk of death in the hospital. We hope that this model can help identify high-risk patients early and reasonably allocate medical resources in the intensive care unit (ICU). Methods: A total of 16,154 S-AKI patients from the Medical Information Mart for Intensive Care IV database were examined as the training set (80%) and the validation set (20%). Variables (129 in total) were collected, including basic patient information, diagnosis, clinical data, and medication records. We developed and validated machine learning models using 11 different algorithms and selected the one that performed the best. Afterward, recursive feature elimination was used to select key variables. Different indicators were used to compare the prediction performance of each model. The SHapley Additive exPlanations package was applied to interpret the best machine learning model in a web tool for clinicians to use. Finally, we collected clinical data of S-AKI patients from two hospitals for external validation. Results: In this study, 15 critical variables were finally selected, namely, urine output, maximum blood urea nitrogen, rate of injection of norepinephrine, maximum anion gap, maximum creatinine, maximum red blood cell volume distribution width, minimum international normalized ratio, maximum heart rate, maximum temperature, maximum respiratory rate, minimum fraction of inspired O2, minimum creatinine, minimum Glasgow Coma Scale, and diagnosis of diabetes and stroke. The categorical boosting algorithm model presented significantly better predictive performance [receiver operating characteristic (ROC): 0.83] than other models [accuracy (ACC): 75%, Youden index: 50%, sensitivity: 75%, specificity: 75%, F1 score: 0.56, positive predictive value (PPV): 44%, and negative predictive value (NPV): 92%]. External validation data from two hospitals in China were also well validated (ROC: 0.75). Conclusions: After selecting 15 crucial variables, a machine learning-based model for predicting the mortality of S-AKI patients was successfully established and the CatBoost model demonstrated best predictive performance.

Sustainable sepiolite-based composites for fast clotting and wound healing.

Uncontrolled bleeding and bacterial coinfection are the major causes of death after an injury. Fast hemostatic capacity, good biocompatibility, and bacterial coinfection inhibition pose great challenges to hemostatic agent development. A prospective sepiolite/Ag nanoparticles (sepiolite@AgNPs) composite has been prepared by using natural clay sepiolite as template. A tail vein hemorrhage mouse model and a rabbit hemorrhage model were used to evaluate the hemostatic properties of the composite. The sepiolite@AgNPs composite can quickly absorb fluid to subsequently stop bleeding due to the natural fibrous crystal structure of sepiolite, and inhibit bacterial growth with the antibacterial ability of AgNPs. Compared with commercially-available zeolite material, the as-prepared composite exhibits competitive hemostatic properties without exothermic reaction in the rabbit model of femoral and carotid artery injury. The rapid hemostatic effect was due to the efficient absorption of erythrocyte and activation of the coagulation cascade factors and platelets. Besides, after heat-treatment, the composites can be recycled without significant reduction of hemostatic performance. Our results also prove that sepiolite@AgNPs nanocomposites can stimulate wound healing. The sustainability, lower-cost, higher bioavailability, and stronger hemostatic efficacy of sepiolite@AgNPs composite render these nanocomposites as more favorable hemostatic agents for hemostasis and wound healing.

A novel lipid metabolism gene signature for clear cell renal cell carcinoma using integrated bioinformatics analysis.

Background: Clear cell renal cell carcinoma (ccRCC), which is the most prevalent type of renal cell carcinoma, has a high mortality rate. Lipid metabolism reprogramming is a hallmark of ccRCC progression, but its specific mechanism remains unclear. Here, the relationship between dysregulated lipid metabolism genes (LMGs) and ccRCC progression was investigated. Methods: The ccRCC transcriptome data and patients' clinical traits were obtained from several databases. A list of LMGs was selected, differentially expressed gene screening performed to detect differential LMGs, survival analysis performed, a prognostic model established, and immune landscape evaluated using the CIBERSORT algorithm. Gene Set Variation Analysis and Gene set enrichment analysis were conducted to explore the mechanism by which LMGs affect ccRCC progression. Single-cell RNA-sequencing data were obtained from relevant datasets. Immunohistochemistry and RT-PCR were used to validate the expression of prognostic LMGs. Results: Seventy-one differential LMGs were identified between ccRCC and control samples, and a novel risk score model established comprising 11 LMGs (ABCB4, DPEP1, IL4I1, ENO2, PLD4, CEL, HSD11B2, ACADSB, ELOVL2, LPA, and PIK3R6); this risk model could predict ccRCC survival. The high-risk group had worse prognoses and higher immune pathway activation and cancer development. Conclusion: Our results showed that this prognostic model can affect ccRCC progression.

Dapagliflozin alleviates renal fibrosis in a mouse model of adenine-induced renal injury by inhibiting TGF-ß1/MAPK mediated mitochondrial damage.

Renal fibrosis is a common pathological outcome of various chronic kidney diseases, and as yet, there is no specific treatment. Dapagliflozin has shown renal protection in some clinical trials as a glucose-lowering drug, but its role and mechanism on renal fibrosis remain unclear. In this study, we used a 0.2% adenine diet-induced renal fibrosis mouse model to investigate whether dapagliflozin could protect renal function and alleviate renal fibrosis in this animal model. In vivo, we found that dapagliflozin's protective effect on renal fibrosis was associated with 1) sustaining mitochondrial integrity and respiratory chain complex expression, maintained the amount of mitochondria; 2) improving fatty acid oxidation level with increased expression of CPT1-α, PPAR-α, ACOX1, and ACOX2; 3) reducing inflammation and oxidative stress, likely via regulation of IL-1ß, IL-6, TNF-α, MCP-1, cxcl-1 expression, and glutathione (GSH) activity, superoxide dismutase (SOD) and malondialdehyde (MDA) levels; and 4) inhibiting the activation of the TGF-ß1/MAPK pathway. In HK2 cells treated with TGF-ß1, dapagliflozin reduced the expression of FN and α-SMA, improved mitochondrial respiratory chain complex expression, and inhibited activation of the TGF-ß1/MAPK pathway.

[Status Quo and Research Progress in Diagnosis and Treatment of Patients With Diabetes Mellitus and Chronic Kidney Disease].

As the incidence of diabetes mellitus is rapidly increasing worldwide,that of related complications,such as diabetic kidney disease(DKD),also increases,conferring a heavy economic burden on the patients,families,society,and government.Diabetes mellitus complicated with chronic kidney disease(CKD)includes DKD and the CKD caused by other reasons.Because of the insufficient knowledge about CKD,the assessment of diabetes mellitus complicated with CKD remains to be improved.The therapies for diabetes mellitus complicated with CKD focus on reducing the risk factors.In clinical practice,DKD may not be the CKD caused by diabetes.According to clinical criteria,some non-diabetic kidney disease may be misdiagnosed as DKD and not be treated accurately.This review summarizes the status quo and research progress in the assessment,diagnosis,and treatment of diabetes mellitus complicated with CKD and predicts the directions of future research in this field.

Protective effects of mefunidone on ischemia-reperfusion injury/Folic acid-induced acute kidney injury.

Renal ischemia-reperfusion injury (IRI) is one of the most common causes of acute kidney injury (AKI). It poses a significant threat to public health, and effective therapeutic drugs are lacking. Mefunidone (MFD) is a new pyridinone drug that exerts a significant protective effect on diabetic nephropathy and the unilateral ureteral obstruction (UUO) model in our previous study. However, the effects of mefunidone on ischemia-reperfusion injury-induced acute kidney injury remain unknown. In this study, we investigated the protective effect of mefunidone against ischemia-reperfusion injury-induced acute kidney injury and explored the underlying mechanism. These results revealed that mefunidone exerted a protective effect against ischemia-reperfusion injury-induced acute kidney injury. In an ischemia-reperfusion injury-induced acute kidney injury model, treatment with mefunidone significantly protected the kidney by relieving kidney tubular injury, suppressing oxidative stress, and inhibiting kidney tubular epithelial cell apoptosis. Furthermore, we found that mefunidone reduced mitochondrial damage, regulated mitochondrial-related Bax/bcl2/cleaved-caspase3 apoptotic protein expression, and protected mitochondrial electron transport chain complexes III and V levels both in vivo and in vitro, along with a protective effect on mitochondrial membrane potential in vitro. Given that folic acid (FA)-induced acute kidney injury is a classic model, we used this model to further validate the efficacy of mefunidone in acute kidney injury and obtained the same conclusion. Based on the above results, we conclude that mefunidone has potential protective and therapeutic effects in both ischemia-reperfusion injury- and folic acid-induced acute kidney injury.

Homozygous mutation in DNAAF4 causes primary ciliary dyskinesia in a Chinese family.

Primary ciliary dyskinesia (PCD) is a rare autosomal recessive disorder that affects the structure and function of motile cilia, leading to classic clinical phenotypes, such as situs inversus, chronic sinusitis, bronchiectasis, repeated pneumonia and infertility. In this study, we diagnosed a female patient with PCD who was born in a consanguineous family through classic clinical manifestations, transmission electron microscopy and immunofluorescence staining. A novel DNAAF4 variant NM_130810: c.1118G>A (p. G373E) was filtered through Whole-exome sequencing. Subsequently, we explored the effect of the mutation on DNAAF4 protein from three aspects: protein expression, stability and interaction with downstream DNAAF2 protein through a series of experiments, such as transfection of plasmids and Co-immunoprecipitation. Finally, we confirmed that the mutation of DNAAF4 lead to PCD by reducing the stability of DNAAF4 protein, but the expression and function of DNAAF4 protein were not affected.

Prognosis of clear cell renal cell carcinoma patients stratified by age: A research relied on SEER database.

Objective: Clear cell renal cell carcinoma may affect patients of any age. To date, there are only a limited number of large data studies on renal clear cell carcinoma in different age groups. This study assessed CCRCC risk factors in different age groups using the Surveillance Epidemiology and End Results (SEER) database. Methods: We selected 58372 cases from the SEER database. These patients were divided into seven different age groups. Cox regression models were used to find independent risk factors for the survival of CCRCC patients. Based on independent risk factors, a nomogram was drawn with R software. Kaplan-Meier method for survival analysis and X-tile software were used to find the optimal age group for diagnosis. Results: Univariate analysis revealed that patients' age, sex, race, marital status, grade, TNM (tumor, node, metastasis) stage, surgery, WHO/ISUP grade were correlated with survival (P<0.01). Age was an independent risk factor for survival in patients with CCRCC according to multivariate Cox regression analysis (p<0.01). All-cause mortality and tumor-specific mortality increased according to the increasing age of the patients. The optimal cut-off values for age were defined as 58 and 76 years and 51 and 76 years, respectively, according to overall survival (OS) and cause-specific survival (CSS). Conclusion: There is a negative correlation between age and survival of CCRCC patients. The difference in prognosis of patients in different age groups has important implications for clinical treatment. Therefore, the diagnosis and treatment plan should be based on more detailed age grouping, which is more beneficial to improving the prognosis and survival of patients.

Identification of selective homeodomain interacting protein kinase 2 inhibitors, a potential treatment for renal fibrosis.

Homeodomain interacting protein kinase 2 (HIPK2) has emerged as a promising target for the discovery of anti-renal fibrosis drugs. Herein, to develop specific pharmacologic inhibitors of HIPK2, we designed and synthesized a series of compounds containing benzimidazole and pyrimidine scaffolds via fragment-based drug design strategy. Kinase assay was applied to evaluate the inhibitory activity of target compounds against HIPKs enzyme. The molecular docking study suggest the contribution of tyrosine residues beside the active sites of HIPK1-3 to the selectivity of active compounds. Compound 15q displayed good selectivity and potent inhibitory activity against HIPK2 compared to other two subtype enzymes. 15q could downregulate phosphorylated p53, the direct substrate of HIPK2, and decrease the fibrosis-related downstream of HIPK2, such as p-Smad3 and α-SMA in NRK-49F cells. 15q showed no effect on the cell apoptosis in fibrotic or cancer cell lines, suggesting little cancer risk of 15q. Notably, 15q displayed encouraging in vivo anti-fibrotic effects in the unilateral ureteral obstruction mouse model, which could be used as a potential lead for structural optimization and candidate for the development of selective HIPK2 inhibitors.