Quantitative evaluation of the infrapatellar fat pad in knee osteoarthritis: MRI-based radiomic signature.

BACKGROUND: The infrapatellar fat pad (IFP) may have bilateral influence on knee osteoarthritis (KOA). IFP evaluation may be a key contributor to the diagnostic and clinical management of KOA. Few studies have evaluated KOA-related IFP alteration with radiomics. We investigated radiomic signature for the assessment of IFP for KOA progression in older adults. METHODS: A total of 164 knees were enrolled and grouped based on Kellgren-Lawrence (KL) scoring. MRI-based radiomic features were calculated from IFP segmentation. The radiomic signature was developed using the most predictive subset of features and the machine-learning algorithm with minimum relative standard deviation. KOA severity and structure abnormality were assessed using a modified whole-organ magnetic resonance imaging score (WORMS). The performance of the radiomic signature was evaluated and the correlation with WORMS assessments was analyzed. RESULTS: The area under the curve of the radiomic signature for diagnosing KOA was 0.83 and 0.78 in the training and test datasets, respectively. Rad-scores were 0.41 and 2.01 for the training dataset in the groups with and without KOA (P < 0.001) and 0.63 and 2.31 for the test dataset (P = 0.005), respectively. WORMS significantly and positively correlated with rad-scores. CONCLUSIONS: The radiomic signature may be a reliable biomarker to detect IFP abnormality of KOA. Radiomic alterations in IFP were associated with severity and knee structural abnormalities of KOA in older adults.

Identification of a Non-Invasive Urinary Exosomal Biomarker for Diabetic Nephropathy Using Data-Independent Acquisition Proteomics.

Diabetic nephropathy (DN), as the one of most common complications of diabetes, is generally diagnosed based on a longstanding duration, albuminuria, and decreased kidney function. Some patients with the comorbidities of diabetes and other primary renal diseases have similar clinical features to DN, which is defined as non-diabetic renal disease (NDRD). It is necessary to distinguish between DN and NDRD, considering they differ in their pathological characteristics, treatment regimes, and prognosis. Renal biopsy provides a gold standard; however, it is difficult for this to be conducted in all patients. Therefore, it is necessary to discover non-invasive biomarkers that can distinguish between DN and NDRD. In this research, the urinary exosomes were isolated from the midstream morning urine based on ultracentrifugation combined with 0.22 µm membrane filtration. Data-independent acquisition-based quantitative proteomics were used to define the proteome profile of urinary exosomes from DN (n = 12) and NDRD (n = 15) patients diagnosed with renal biopsy and Type 2 diabetes mellitus (T2DM) patients without renal damage (n = 9), as well as healthy people (n = 12). In each sample, 3372 ± 722.1 proteins were identified on average. We isolated 371 urinary exosome proteins that were significantly and differentially expressed between DN and NDRD patients, and bioinformatic analysis revealed them to be mainly enriched in the immune and metabolic pathways. The use of least absolute shrinkage and selection operator (LASSO) logistic regression further identified phytanoyl-CoA dioxygenase domain containing 1 (PHYHD1) as the differential diagnostic biomarker, the efficacy of which was verified with another cohort including eight DN patients, five NDRD patients, seven T2DM patients, and nine healthy people. Additionally, a concentration above 1.203 µg/L was established for DN based on the ELISA method. Furthermore, of the 19 significantly different expressed urinary exosome proteins selected by using the protein-protein interaction network and LASSO logistic regression, 13 of them were significantly related to clinical indicators that could reflect the level of renal function and hyperglycemic management.

Patellar instability: the reliability of magnetic resonance imaging measurement parameters.

BACKGROUND: Radiological assessments are considered an important part of the management of patellar instability (PI). However, PI measurements are influenced by the knee position, which cannot be guaranteed to be the same for each examination. Therefore, we aimed to determine the reliability of common PI measurements on magnetic resonance imaging (MRI). METHODS: Two MRI examinations within a 6-month period were obtained from 51 knees. The common PI measurements were quantitatively determined and re-evaluated. The intraclass correlation coefficients (ICC), Bland-Altman plot, standard error of measurement (SEM), and minimal detectable change (MDC) were used to determine the intra-observer, inter-observer, and inter-scan reliability. RESULTS: Adequate intra- and inter-observer reliability was obtained for all PI measurements (all ICCs > 0.8). For patellar positional parameters, the inter-scan reliability was adequate for the angle of Fulkerson, angle of Laurin, patellar tilt angle (PTA), lateral patellar displacement (LPD), and bisect offset ratio (BSO; ICCs = 0.723-0.897), although it was inadequate for the angle of Grelsamer and the congruence angle (CA; ICCs = 0.325-0.380). All parameters of trochlear dysplasia showed adequate inter-scan reliability (ICCs = 0.793-0.915). Nearly all patellar height parameters showed adequate inter-scan reliability (ICCs = 0.700-0.903), except the patellar trochlear index (PTI; ICC = 0.655). CONCLUSION: All PI measurements showed adequate intra- and inter-observer reliability on MRI. Most measurements showed adequate inter-scan reliability, with the exception of the angle of Grelsamer, CA, and PTI.

The Role of the Gut Microbiota in Complications among Hemodialysis Patients.

The composition of the gut microbiota varies among end-stage renal disease (ESRD) patients on the basis of their mode of renal replacement therapy (RRT), with notably more pronounced dysbiosis occurring in those undergoing hemodialysis (HD). Interventions such as dialysis catheters, unstable hemodynamics, strict dietary restrictions, and pharmacotherapy significantly alter the intestinal microenvironment, thus disrupting the gut microbiota composition in HD patients. The gut microbiota may influence HD-related complications, including cardiovascular disease (CVD), infections, anemia, and malnutrition, through mechanisms such as bacterial translocation, immune regulation, and the production of gut microbial metabolites, thereby affecting both the quality of life and the prognosis of patients. This review focuses on alterations in the gut microbiota and its metabolites in HD patients. Additionally, understanding the impact of the gut microbiota on the complications of HD could provide insights into the development of novel treatment strategies to prevent or alleviate complications in HD patients.

The clinical significance of HRCT in evaluation of patients with rheumatoid arthritis-associated interstitial lung disease: a report from China.

The objective of this study is to describe the interstitial lung disease (ILD) in rheumatoid arthritis (RA) patients of China, and to study clinical significance of high-resolution computed tomography (HRCT) in evaluation and treatment. One hundred and ten Chinese patients (79 women and 31 man) diagnosed with RA between December 2008 to November 2009 were analyzed. According to the HRCT, 47 (42.73%) RA patients were diagnosed as ILD. Old age, smoking and pulmonary rales were closely related to ILD (P < 0.05). The main appearances of ILD were ground-glass (39.09%), honeycombing (4.55%), reticular patterns and consolidation (1.82%). Patients with reticular patterns and honeycombing were more likely to show the respiratory symptoms. It was also common to find other abnormal changes, such as fiber cord shadow (22.73%), lung markings fuzzy disorder (30%), pulmonary nodules (11.82%), emphysema (9.09%), bronchiectasis (3.64%), subpleural nodules (11.82%) and pleural thickening (24.55%). In treatment, honeycombing and subpleural nodules were more common in patients with methotrexate (MTX) and/or leflunomide treatment than without (P < 0.05). Other abnormal changes were no statistical significance (P > 0.05). Pulmonary involvement is common in RA patients, and it is suggested that HRCT could be a sensitive and useful way in evaluating the lung of RA patients.

A systematic review and Meta-analysis of urinary extracellular vesicles proteome in diabetic nephropathy.

Diabetic nephropathy (DN) is a major microvascular complication of both type 1 and type 2 diabetes mellitus and is the most frequent cause of end-stage renal disease with an increasing prevalence. Presently there is no non-invasive method for differential diagnosis, and an efficient target therapy is lacking. Extracellular vesicles (EV), including exosomes, microvesicles, and apoptotic bodies, are present in various body fluids such as blood, cerebrospinal fluid, and urine. Proteins in EV are speculated to be involved in various processes of disease and reflect the original cells' physiological states and pathological conditions. This systematic review is based on urinary extracellular vesicles studies, which enrolled patients with DN and investigated the proteins in urinary EV. We systematically reviewed articles from the PubMed, Embase, Web of Science databases, and China National Knowledge Infrastructure (CNKI) database until January 4, 2022. The article quality was appraised according to the Newcastle-Ottawa Quality Assessment Scale (NOS). The methodology of samples, isolation and purification techniques of urinary EV, and characterization methods are summarized. Molecular functions, biological processes, and pathways were enriched in all retrievable urinary EV proteins. Protein-protein interaction analysis (PPI) revealed pathways of potential biomarkers. A total of 539 articles were retrieved, and 13 eligible records were enrolled in this systematic review and meta-analysis. And two studies performed mass spectrometry to obtain the proteome profile. Two of them enrolled only T1DM patients, two studies enrolled both patients with T1DM and T2DM, and other the nine studies focused on T2DM patients. In total 988 participants were enrolled, and DN was diagnosed according to UACR, UAER, or decreased GFR. Totally 579 urinary EV proteins were detected and 28 of them showed a potential value to be biomarkers. The results of bioinformatics analysis revealed that urinary EV may participate in DN through various pathways such as angiogenesis, biogenesis of EV, renin-angiotensin system, fluid shear stress and atherosclerosis, collagen degradation, and immune system. Besides that, it is necessary to report results compliant with the guideline of ISEV, in orderto assure repeatability and help for further studies. This systematic review concordance with previous studies and the results of meta-analysis may help to value the methodology details when urinary EV proteins were reported, and also help to deepen the understanding of urinary EV proteins in DN.

Salivary Glycopatterns as Potential Non-Invasive Biomarkers for Diagnosing and Reflecting Severity and Prognosis of Diabetic Nephropathy.

Discriminating between diabetic nephropathy (DN) and non-diabetic renal disease (NDRD) can help provide more specific treatments. However, there are no ideal biomarkers for their differentiation. Thus, the aim of this study was to identify biomarkers for diagnosing and predicting the progression of DN by investigating different salivary glycopatterns. Lectin microarrays were used to screen different glycopatterns in patients with DN or NDRD. The results were validated by lectin blotting. Logistic regression and artificial neural network analyses were used to construct diagnostic models and were validated in in another cohort. Pearson's correlation analysis, Cox regression, and Kaplan-Meier survival curves were used to analyse the correlation between lectins, and disease severity and progression. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) and bioinformatics analyses were used to identify corresponding glycoproteins and predict their function. Both the logistic regression model and the artificial neural network model achieved high diagnostic accuracy. The levels of Aleuria aurantia lectin (AAL), Lycopersicon esculentum lectin (LEL), Lens culinaris lectin (LCA), Vicia villosa lectin (VVA), and Narcissus pseudonarcissus lectin (NPA) were significantly correlated with the clinical and pathological parameters related to DN severity. A high level of LCA and a low level of LEL were associated with a higher risk of progression to end-stage renal disease. Glycopatterns in the saliva could be a non-invasive tool for distinguishing between DN and NDRD. The AAL, LEL, LCA, VVA, and NPA levels could reflect the severity of DN, and the LEL and LCA levels could indicate the prognosis of DN.

Association of Immune and Inflammatory Gene Polymorphism With the Risk of IgA Nephropathy: A Systematic Review and Meta-Analysis of 45 Studies.

IgA nephropathy is the most prevalent primary glomerulonephritis worldwide, with identical immunopathological characteristics caused by multiple etiologies as well as influenced by geographical and ethnical factors. To elucidate the role of immunologic and inflammatory mechanisms in the susceptibility to IgA nephropathy, we explored single nucleotide polymorphisms of related molecules in the immune pathways. We searched the PubMed database for studies that involved all gene variants of molecules in the 20 immunologic and inflammatory pathways selected from the Kyoto Encyclopedia of Genes and Genomes database. The odds ratios with their corresponding 95% confidence intervals in six genetic models (allele model, dominant model, homozygote model, heterozygote model, overdominant model, and recessive model) were summarized using fixed or random effect models. Subgroup analysis was conducted based on different ethnicities with generalized odds ratios. Heterogeneity was evaluated using the Q and I2 tests. Begg's funnel plot and Egger's linear regression test were used to evaluating possible publication bias among the included studies, and sensitivity analysis was used to test the stability of the overall results. A total of 45 studies met our selection criteria and eight related genetic association studies were retrieved, including 320 single-nucleotide polymorphisms from 20 candidate pathways, ranging from 2000 to 2021. A total of 28,994 healthy people versus 20,600 IgA nephropathy patients were enrolled. Upon meta-analyzed results that TGFB1 (rs1800469, rs1982073, rs1800471), IL-1B (rs1143627), IL-18 (rs1946518), and TLR1 (rs5743557) showed effect with or without ethnicity difference. And 10 variants presented stable and robust related to IgA nephropathy. This research showed that genetic variants are related to the immunologic and inflammatory effects of IgA nephropathy pathogenesis. The meta-analysis results supported the previous researches, and may help deepen the understanding of pathogenesis and explore new targets for IgA nephropathy-specific immunotherapy.

Immunomodulatory Effects of Mesenchymal Stem Cells on Drug-Induced Acute Kidney Injury.

Drug-induced nephrotoxicity is an important and increasing cause of acute kidney injury (AKI), which accounts for approximately 20% of hospitalized patients. Previous reviews studies on immunity and AKI focused mainly on ischemia-reperfusion (IR), whereas no systematic review addressing drug-induced AKI and its related immune mechanisms is available. Recent studies have provided a deeper understanding on the mechanisms of drug-induced AKI, among which acute tubular interstitial injury induced by the breakdown of innate immunity was reported to play an important role. Emerging research on mesenchymal stem cell (MSC) therapy has revealed its potential as treatment for drug-induced AKI. MSCs can inhibit kidney damage by regulating the innate immune balance, promoting kidney repair, and preventing kidney fibrosis. However, it is important to note that there are various sources of MSCs, which impacts on the immunomodulatory ability of the cells. This review aims to address the immune pathogenesis of drug-induced AKI versus that of IR-induced AKI, and to explore the immunomodulatory effects and therapeutic potential of MSCs for drug-induced AKI.

Urinary sediment microRNAs can be used as potential noninvasive biomarkers for diagnosis, reflecting the severity and prognosis of diabetic nephropathy.

BACKGROUND: Patients with both diabetes mellitus (DM) and kidney disease could have diabetic nephropathy (DN) or non-diabetic renal disease (NDRD). IgA nephropathy (IgAN) and membranous nephropathy (MN) are the major types of NDRD. No ideal noninvasive diagnostic model exists for differentiating them. Our study sought to construct diagnostic models for these diseases and to identify noninvasive biomarkers that can reflect the severity and prognosis of DN. METHODS: The diagnostic models were constructed using logistic regression analysis and were validated in an external cohort by receiver operating characteristic curve analysis method. The associations between these microRNAs and disease severity and prognosis were explored using Pearson correlation analysis, Cox regression, Kaplan-Meier survival curves, and log-rank tests. RESULTS: Our diagnostic models showed that miR-95-3p, miR-185-5p, miR-1246, and miR-631 could serve as simple and noninvasive tools to distinguish patients with DM, DN, DM with IgAN, and DM with MN. The areas under the curve of the diagnostic models for the four diseases were 0.995, 0.863, 0.859, and 0.792, respectively. The miR-95-3p level was positively correlated with the estimated glomerular filtration rate (p < 0.001) but was negatively correlated with serum creatinine (p < 0.01), classes of glomerular lesions (p < 0.05), and scores of interstitial and vascular lesions (p < 0.05). However, the miR-631 level was positively correlated with proteinuria (p < 0.001). A low miR-95-3p level and a high miR-631 level increased the risk of progression to end-stage renal disease (p = 0.002, p = 0.011). CONCLUSIONS: These four microRNAs could be noninvasive tools for distinguishing patients with DN and NDRD. The levels of miR-95-3p and miR-631 could reflect the severity and prognosis of DN.

Ketamine inhibits LPS-mediated BV2 microglial inflammation via NMDA receptor blockage.

Microglial inflammation leads to the upregulation of proinflammatory cytokine and proinflammatory enzyme expression, resulting in inflammation-induced neuronal cell apoptosis. Ketamine, an anesthetic mostly used in critical patients, has been reported to possess neuroprotective effects. However, the potential mechanism is still not well understood. In the present study, we investigated how ketamine attenuates lipopolysaccharide (LPS)-mediated BV2 cell inflammation. LPS upregulated proinflammatory cytokine and proinflammatory enzyme expression, increased NF-κB phosphorylation and nuclear translocation, and augmented calcium (Ca2+ )/calmodulin-dependent protein kinase II (CaMK II) phosphorylation and Ca2+ levels in BV2 cells. Ketamine could reverse these LPS-induced effects. Furthermore, AP5, an inhibitor of NMDA receptors, inhibited LPS-induced inflammatory effects in BV2 cells, which was similar to the effects of ketamine. Moreover, these effects of ketamine against LPS-mediated inflammation in BV2 cells could be reversed by D-serine, an activator of NMDA receptors. The present study suggests that ketamine, by inhibiting NMDA receptors, attenuating Ca2+ levels, and inhibiting CaMK II phosphorylation, NF-κB phosphorylation and nuclear translocation, may ameliorate LPS-mediated inflammation in BV2 cells.

Critical hubs of renal ischemia-reperfusion injury: endoplasmic reticulum-mitochondria tethering complexes.

Mitochondrial injury and endoplasmic reticulum (ER) stress are considered to be the key mechanisms of renal ischemia-reperfusion (I/R) injury. Mitochondria are membrane-bound organelles that form close physical contact with a specific domain of the ER, known as mitochondrial-associated membranes. The close physical contact between them is mainly restrained by ER-mitochondria tethering complexes, which can play an important role in mitochondrial damage, ER stress, lipid homeostasis, and cell death. Several ER-mitochondria tethering complex components are involved in the process of renal I/R injury. A better understanding of the physical and functional interaction between ER and mitochondria is helpful to further clarify the mechanism of renal I/R injury and provide potential therapeutic targets. In this review, we aim to describe the structure of the tethering complex and elucidate its pivotal role in renal I/R injury by summarizing its role in many important mechanisms, such as mitophagy, mitochondrial fission, mitochondrial fusion, apoptosis and necrosis, ER stress, mitochondrial substance transport, and lipid metabolism.

Machine learning in nephrology: scratching the surface.

Machine learning shows enormous potential in facilitating decision-making regarding kidney diseases. With the development of data preservation and processing, as well as the advancement of machine learning algorithms, machine learning is expected to make remarkable breakthroughs in nephrology. Machine learning models have yielded many preliminaries to moderate and several excellent achievements in the fields, including analysis of renal pathological images, diagnosis and prognosis of chronic kidney diseases and acute kidney injury, as well as management of dialysis treatments. However, it is just scratching the surface of the field; at the same time, machine learning and its applications in renal diseases are facing a number of challenges. In this review, we discuss the application status, challenges and future prospects of machine learning in nephrology to help people further understand and improve the capacity for prediction, detection, and care quality in kidney diseases.