Application of Advanced Nanomaterials for Kidney Failure Treatment and Regeneration

Eftekhari, Aziz; Dizaj, Solmaz Maleki; Ahmadian, Elham; Przekora, Agata; Khatibi, Seyed Mahdi Hosseiniyan; Ardalan, Mohammadreza; Vahed, Sepideh Zununi; Valiyeva, Mahbuba; Mehraliyeva, Sevil; Khalilov, Rovshan; Hasanzadeh, Mohammad

doi:10.3390/ma14112939

Cited by 32 publications

(15 citation statements)

References 131 publications

(178 reference statements)

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“…Various nanomaterials, including carbon nanotubes, nanofibrous membranes, and mesoporous silica nanoparticles, have been used in medical field. 29,30 However, these “hard” materials have been limited in clinic because of their poor biocompatibility, low solubility, or slow metabolic rate. Nucleic acid-based materials are flexible, highly biocompatible, and easy to be metabolized, and thus were considered as useful “soft” materials which aroused the attention of many researchers.…”

Section: Resultsmentioning

confidence: 99%

Adenosine triphosphate/pH dual-responsive controlled drug release system with high cancer/normal cell selectivity and low side toxicity

Fu¹,

Lin

Chen³

et al. 2022

J Biomater Appl

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Most drug-delivery systems (DDS) suffer from poor selectivity to cancer/normal cells or the complicated synthetic process. Herein, we employed a novel facile method to develop an oligodeoxy nucleotides based DDS composed with adenosine-5′- triphosphate (ATP) aptamer and a pH responsive cytosine (C) DNA fragment for specific daunomycine (DNM) delivery. The DDS has ATP/pH dual-responsive drug release, can selectively internalize into tumor cell lines and thus has ultrahigh cancer/normal cell selectivity over the individual drug. The non-chemical synthesis, controllable dual-responsive intracellular drug release, and high cancer/normal cell selectivity endowed the DDS high biocompatibility and significant tumor suppression.

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Section: Resultsmentioning

confidence: 99%

Adenosine triphosphate/pH dual-responsive controlled drug release system with high cancer/normal cell selectivity and low side toxicity

Fu¹,

Lin

Chen³

et al. 2022

J Biomater Appl

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“…One of the challenges is the poor target tissue distribution for immunosuppressive drugs [ 56 ]. However, with the emergence of nanotechnology, potential nanomaterials with special physiochemical properties are being developed and applied for treating various diseases including glomerulonephritis [ 57 ]. With better penetration of loaded drugs, clinical outcomes could be more likely associated with their therapeutic effects in the absence of tissue barrier, which may lead to better prediction model performance due to stronger connection between drugs and outcomes.…”

Section: Discussionmentioning

confidence: 99%

Incorporating knowledge of disease-defining hub genes and regulatory network into a machine learning-based model for predicting treatment response in lupus nephritis after the first renal flare

Lee

Tsai²,

Chen³

et al. 2023

J Transl Med

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Background Identifying candidates responsive to treatment is important in lupus nephritis (LN) at the renal flare (RF) because an effective treatment can lower the risk of progression to end-stage kidney disease. However, machine learning (ML)-based models that address this issue are lacking. Methods Transcriptomic profiles based on DNA microarray data were extracted from the GSE32591 and GSE112943 datasets. Comprehensive bioinformatics analyses were performed to identify disease-defining genes (DDGs). Peripheral blood samples (GSE81622, GSE99967, and GSE72326) were used to evaluate the effect of DDGs. Single-sample gene set enrichment analysis (ssGSEA) scores of the DDGs were calculated and correlated with specific immunology genes listed in the nCounter panel. GSE60681 and GSE69438 were used to examine the ability of the DDGs to discriminate LN from other renal diseases. K-means clustering was used to obtain the separate gene sets. The clustering results were extended to data derived using the nCounter technique. The least absolute shrinkage and selection operator (LASSO) algorithm was used to identify genes with high predictive value for treatment response after the first RF in each cluster. LASSO models with tenfold validation were built in GSE200306 and assessed by receiver operating characteristic (ROC) analysis with area under curve (AUC). The models were validated by using an independent dataset (GSE113342). Results Forty-five hub genes specific to LN were identified. Eight optimal disease-defining clusters (DDCs) were identified in this study. Th1 and Th2 cell differentiation pathway was significantly enriched in DDC-6. LCK in DDC-6, whose expression positively correlated with various subsets of T cell infiltrations, was found to be differentially expressed between responders and non-responders and was ranked high in regulatory network analysis. Based on DDC-6, the prediction model had the best performance (AUC: 0.75; 95% confidence interval: 0.44–1 in the testing set) and high precision (0.83), recall (0.71), and F1 score (0.77) in the validation dataset. Conclusions Our study demonstrates that incorporating knowledge of biological phenotypes into the ML model is feasible for evaluating treatment response after the first RF in LN. This knowledge-based incorporation improves the model's transparency and performance. In addition, LCK may serve as a biomarker for T-cell infiltration and a therapeutic target in LN.

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“…New technologies are also being employed to tackle the problem of CKD. Nanotechnology is being used in research settings as a tool to identify and treat diverse kidney diseases [ 22 , 23 ] along with new genetic technology [ 24 , 25 ]. New treatment strategies are also emerging.…”

Section: Discussionmentioning

confidence: 99%

Chronic Kidney Disease in Balkan Countries—A Call to Action for Timely Diagnosis and Monitoring

et al. 2022

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Chronic kidney disease (CKD) is a serious illness with important consequences for patients and health systems. Estimation of prevalence and incidence, especially in early stages, is difficult due to a lack of epidemiological studies and consolidated registries. In general, the disease awareness is low, and thus CKD is not timely diagnosed in most cases. Robust screening programs are not implemented in Eastern European countries. A panel consisting of Primary Care Physicians and Nephrologists from Bulgaria, Croatia, Serbia, and Slovenia virtually met in December 2021 to discuss current CKD awareness and diagnostic approaches in the Balkan area The meeting resulted in specific calls to action in the region to improve the number and quality of epidemiology studies and the level of awareness among patients and medical communities, as well as implementation of screening programs in high-risk populations. Collaboration between specialists was acknowledged as a crucial driver for optimal management of patients with CKD. Joint efforts are required to persuade healthcare authorities to establish specific policies for better care of kidney patients.

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Application of Advanced Nanomaterials for Kidney Failure Treatment and Regeneration

Cited by 32 publications

References 131 publications

Adenosine triphosphate/pH dual-responsive controlled drug release system with high cancer/normal cell selectivity and low side toxicity

Adenosine triphosphate/pH dual-responsive controlled drug release system with high cancer/normal cell selectivity and low side toxicity

Incorporating knowledge of disease-defining hub genes and regulatory network into a machine learning-based model for predicting treatment response in lupus nephritis after the first renal flare

Chronic Kidney Disease in Balkan Countries—A Call to Action for Timely Diagnosis and Monitoring

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