Rapid integration of screen-printed electrodes into thermoplastic organ-on-a-chip devices for real-time monitoring of trans-endothelial electrical resistance.

Trans-endothelial electrical resistance (TEER) is one of the most widely used indicators to quantify the barrier integrity of endothelial layers. Over the last decade, the integration of TEER sensors into organ-on-a-chip (OOC) platforms has gained increasing interest for its efficient and effective measurement of TEER in OOCs. To date, microfabricated electrodes or direct insertion of wires has been used to integrate TEER sensors into OOCs, with each method having advantages and disadvantages. In this study, we developed a TEER-SPE chip consisting of carbon-based screen-printed electrodes (SPEs) embedded in a poly(methyl methacrylate) (PMMA)-based multi-layered microfluidic device with a porous poly(ethylene terephthalate) membrane in-between. As proof of concept, we demonstrated the successful cultures of hCMEC/D3 cells and the formation of confluent monolayers in the TEER-SPE chip and obtained TEER measurements for 4 days. Additionally, the TEER-SPE chip could detect changes in the barrier integrity due to shear stress or an inflammatory cytokine (i.e., tumor necrosis factor-α). The novel approach enables a low-cost and facile fabrication of carbon-based SPEs on PMMA substrates and the subsequent assembly of PMMA layers for rapid prototyping. Being cost-effective and cleanroom-free, our method lowers the existing logistical and technical barriers presenting itself as another step forward to the broader adoption of OOCs with TEER measurement capability.

Organ-On-A-Chip Models of the Blood-Brain Barrier: Recent Advances and Future Prospects.

The human brain and central nervous system (CNS) present unique challenges in drug development for neurological diseases. One major obstacle is the blood-brain barrier (BBB), which hampers the effective delivery of therapeutic molecules into the brain while protecting it from blood-born neurotoxic substances and maintaining CNS homeostasis. For BBB research, traditional in vitro models rely upon Petri dishes or Transwell systems. However, these static models lack essential microenvironmental factors such as shear stress and proper cell-cell interactions. To this end, organ-on-a-chip (OoC) technology has emerged as a new in vitro modeling approach to better recapitulate the highly dynamic in vivo human brain microenvironment so-called the neural vascular unit (NVU). Such BBB-on-a-chip models have made substantial progress over the last decade, and concurrently there has been increasing interest in modeling various neurological diseases such as Alzheimer's disease and Parkinson's disease using OoC technology. In addition, with recent advances in other scientific technologies, several new opportunities to improve the BBB-on-a-chip platform via multidisciplinary approaches are available. In this review, an overview of the NVU and OoC technology is provided, recent progress and applications of BBB-on-a-chip for personalized medicine and drug discovery are discussed, and current challenges and future directions are delineated.

Therapeutic preparations of IVIg contain naturally occurring anti-HLA-E antibodies that react with HLA-Ia (HLA-A/-B/-Cw) alleles.

The US Food and Drug Administration approved intravenous immunoglobulin (IVIg), extracted from the plasma of thousands of blood donors, for removing HLA antibodies (Abs) in highly sensitized patients awaiting organ transplants. Since the blood of healthy individuals has HLA Abs, we tested different IVIg preparations for reactivity to HLA single antigen Luminex beads. All preparations showed high levels of HLA-Ia and -Ib reactivity. Since normal nonalloimmunized males have natural antibodies to the heavy chains (HCs) of HLA antigens, the preparations were then tested against iBeads coated only with intact HLA antigens. All IVIg preparations varied in level of antibody reactivity to intact HLA antigens. We raised monoclonal Abs against HLA-E that mimicked IVIg's HLA-Ia and HLA-Ib reactivity but reacted only to HLA-I HCs. Inhibition experiments with synthetic peptides showed that HLA-E shares epitopes with HLA-Ia alleles. Importantly, depleting anti-HLA-E Abs from IVIg totally eliminated the HLA-Ia reactivity of IVIg. Since anti-HLA-E mAbs react with HLA-Ia, they might be useful in suppressing HLA antibody production, similar to the way anti-RhD Abs suppress production. At the same time, anti-HLA-E mAb, which reacts only to HLA-I HCs, is unlikely to produce transfusion-related acute lung injury, in contrast to antibodies reacting to intact-HLA.

Gastric cancer progression may involve a shift in HLA-E profile from an intact heterodimer to ß2-microglobulin-free monomer.

Phenotypic expression of human leukocyte antigen (HLA)-E on the surface of tumor lesions includes intact heterodimer [HLA-E heavy chain and ß2-microglobulin (ß2m)] and ß2m-free monomer. Anti-HLA-E monoclonal antibodies (mAbs), MEM-E/02 or 3D12 bind to the peptide sequences in ß2m-free HLA-E, which is common and shared with HLA-Ia monomers. A newly developed monospecific anti-HLA-E mAb (TFL-033) recognizes HLA-E-restricted peptide sequences on α1 and α2 helices away from ß2-m-site. Tumor progression may involve shedding of ß2-m from HLA-E or overexpression of ß2m-free monomers. There is a need to identify and distinguish the different phenotypic expression of HLA-E, particularly the intact heterodimer from the ß2m-free monomer on the surface of tumor lesions. Because of the unique peptide-binding affinities of the mAbs, it is hypothesized that TFL-033 and MEM-E/02 may distinguish the phenotypic expressions of cell surface HLA-E during stages of tumor progression. Only TFL-033 stained diffusely the cytoplasm of normal mucosa. The incidence and intensity of TFL-033 staining of the cell surface in early stages, poorly or undifferentiated and non-nodal lesions and in diffuse carcinoma is greater than that of MEM-E/02. Whereas MEM-E/02 stained terminal stages, adenocarcinoma and lymph node metastatic lesions intensely, either owing to increased expression of ß2m-free HLA-E with tumor progression or owing to expression of HLA-Ia molecules. Our study evaluates the relative diagnostic potential of HLA-E-monospecific TFL-033 and the HLA-Ia-reactive MEM-E/02 for determining the specific distribution and immunodiagnosis of different phenotypic expression HLA-E in tumor lesions, and the structural and functional alterations undergone by HLA-E during tumor progression.

An integrated database of experimentally validated major histocompatibility complex epitopes for antigen-specific cancer therapy.

Cancer immunotherapy represents a paradigm shift in oncology, offering a superior anti-tumor efficacy and the potential for durable remission. The success of personalized vaccines and cell therapies hinges on the identification of immunogenic epitopes capable of eliciting an effective immune response. Current limitations in the availability of immunogenic epitopes restrict the broader application of such therapies. A critical criterion for serving as potential cancer antigens is their ability to stably bind to the major histocompatibility complex (MHC) for presentation on the surface of tumor cells. To address this, we have developed a comprehensive database of MHC epitopes, experimentally validated for their MHC binding and cell surface presentation. Our database catalogs 451 065 MHC peptide epitopes, each with experimental evidence for MHC binding, along with detailed information on human leukocyte antigen allele specificity, source peptides, and references to original studies. We also provide the grand average of hydropathy scores and predicted immunogenicity for the epitopes. The database (MHCepitopes) has been made available on the web and can be accessed at https://github.com/jcm1201/MHCepitopes.git. By consolidating empirical data from various sources coupled with calculated immunogenicity and hydropathy values, our database offers a robust resource for selecting actionable tumor antigens and advancing the design of antigen-specific cancer immunotherapies. It streamlines the process of identifying promising immunotherapeutic targets, potentially expediting the development of effective antigen-based cancer immunotherapies.

Correction: Integrated biosensors for monitoring microphysiological systems.

Correction for 'Integrated biosensors for monitoring microphysiological systems' by Lei Mou et al., Lab Chip, 2022, 22, 3801-3816, https://doi.org/10.1039/D2LC00262K.

Amphotericin B-loaded natural latex dressing for treating Candida albicans wound infections using Galleria mellonella model.

Amphotericin B (AmB) is the gold standard for antifungal drugs. However, AmB systemic administration is restricted because of its side effects. Here, we report AmB loaded in natural rubber latex (NRL), a sustained delivery system with low toxicity, which stimulates angiogenesis, cell adhesion and accelerates wound healing. Physicochemical characterizations showed that AmB did not bind chemically to the polymeric matrix. Electronic and topographical images showed small crystalline aggregates from AmB crystals on the polymer surface. About 56.6% of AmB was released by the NRL in 120 h. However, 33.6% of this antifungal was delivered in the first 24 h due to the presence of AmB on the polymer surface. The biomaterial's excellent hemo- and cytocompatibility with erythrocytes and human dermal fibroblasts (HDF) confirmed its safety for dermal wound application. Antifungal assay against Candida albicans showed that AmB-NRL presented a dose-dependent behavior with an inhibition halo of 30.0 ± 1.0 mm. Galleria mellonella was employed as an in vivo model for C. albicans infection. Survival rates of 60% were observed following the injection of AmB (0.5 mg.mL-1) in G. mellonella larvae infected by C. albicans. Likewise, AmB-NRL (0.5 mg.mL-1) presented survival rates of 40%, inferring antifungal activity against fungus. Thus, NRL adequately acts as an AmB-sustained release matrix, which is an exciting approach, since this antifungal is toxic at high concentrations. Our findings suggest that AmB-NRL is an efficient, safe, and reasonably priced ($0.15) dressing for the treatment of cutaneous fungal infections.

Oxygen-generating microparticles downregulate HIF-1α expression, increase cardiac contractility, and mitigate ischemic injury.

Myocardial hypoxia is the low oxygen tension in the heart tissue implicated in many diseases, including ischemia, cardiac dysfunction, or after heart procurement for transplantation. Oxygen-generating microparticles have recently emerged as a potential strategy for supplying oxygen to sustain cell survival, growth, and tissue functionality in hypoxia. Here, we prepared oxygen-generating microparticles with poly D,L-lactic-co-glycolic acid, and calcium peroxide (CPO), which yielded a continuous morphology capable of sustained oxygen release for up to 24 h. We demonstrated that CPO microparticles increased primary rat cardiomyocyte metabolic activity while not affecting cell viability during hypoxia. Moreover, hypoxia-inducible factor (HIF)-1α, which is upregulated during hypoxia, can be downregulated by delivering oxygen using CPO microparticles. Single-cell traction force microscopy data demonstrated that the reduced energy generated by hypoxic cells could be restored using CPO microparticles. We engineered cardiac tissues that showed higher contractility in the presence of CPO microparticles compared to hypoxic cells. Finally, we observed reduced myocardial injuries in ex vivo rabbit hearts treated with CPO microparticles. In contrast, an acute early myocardial injury was observed for the hearts treated with control saline solution in hypoxia. In conclusion, CPO microparticles improved cell and tissue contractility and gene expression while reducing hypoxia-induced myocardial injuries in the heart. STATEMENT OF SIGNIFICANCE: Oxygen-releasing microparticles can reduce myocardial ischemia, allograft rejection, or irregular heartbeats after heart transplantation. Here we present biodegradable oxygen-releasing microparticles that are capable of sustained oxygen release for more than 24 hrs. We then studied the impact of sustained oxygen release from microparticles on gene expresseion and cardiac cell and tissue function. Previous studies have not measured cardiac tissue or cell mechanics during hypoxia, which is important for understanding proper cardiac function and beating. Using traction force microscopy and an engineered tissue-on-a-chip, we demonstrated that our oxygen-releasing microparticles improve cell and tissue contractility during hypoxia while downregulating the HIF-1α expression level. Finally, using the microparticles, we showed reduced myocardial injuries in rabbit heart tissue, confirming the potential of the particles to be used for organ transplantation or tissue engineering.

CRISPR/Cas9 Genome Editing for Tissue-Specific In Vivo Targeting: Nanomaterials and Translational Perspective.

Clustered randomly interspaced short palindromic repeats (CRISPRs) and its associated endonuclease protein, i.e., Cas9, have been discovered as an immune system in bacteria and archaea; nevertheless, they are now being adopted as mainstream biotechnological/molecular scissors that can modulate ample genetic and nongenetic diseases via insertion/deletion, epigenome editing, messenger RNA editing, CRISPR interference, etc. Many Food and Drug Administration-approved and ongoing clinical trials on CRISPR adopt ex vivo strategies, wherein the gene editing is performed ex vivo, followed by reimplantation to the patients. However, the in vivo delivery of the CRISPR components is still under preclinical surveillance. This review has summarized the nonviral nanodelivery strategies for gene editing using CRISPR/Cas9 and its recent advancements, strategic points of view, challenges, and future aspects for tissue-specific in vivo delivery of CRISPR/Cas9 components using nanomaterials.

Skin-interfaced electronics: A promising and intelligent paradigm for personalized healthcare.

Skin-interfaced electronics (skintronics) have received considerable attention due to their thinness, skin-like mechanical softness, excellent conformability, and multifunctional integration. Current advancements in skintronics have enabled health monitoring and digital medicine. Particularly, skintronics offer a personalized platform for early-stage disease diagnosis and treatment. In this comprehensive review, we discuss (1) the state-of-the-art skintronic devices, (2) material selections and platform considerations of future skintronics toward intelligent healthcare, (3) device fabrication and system integrations of skintronics, (4) an overview of the skintronic platform for personalized healthcare applications, including biosensing as well as wound healing, sleep monitoring, the assessment of SARS-CoV-2, and the augmented reality-/virtual reality-enhanced human-machine interfaces, and (5) current challenges and future opportunities of skintronics and their potentials in clinical translation and commercialization. The field of skintronics will not only minimize physical and physiological mismatches with the skin but also shift the paradigm in intelligent and personalized healthcare and offer unprecedented promise to revolutionize conventional medical practices.

Engineered Vasculature for Cancer Research and Regenerative Medicine.

Engineered human tissues created by three-dimensional cell culture of human cells in a hydrogel are becoming emerging model systems for cancer drug discovery and regenerative medicine. Complex functional engineered tissues can also assist in the regeneration, repair, or replacement of human tissues. However, one of the main hurdles for tissue engineering, three-dimensional cell culture, and regenerative medicine is the capability of delivering nutrients and oxygen to cells through the vasculatures. Several studies have investigated different strategies to create a functional vascular system in engineered tissues and organ-on-a-chips. Engineered vasculatures have been used for the studies of angiogenesis, vasculogenesis, as well as drug and cell transports across the endothelium. Moreover, vascular engineering allows the creation of large functional vascular conduits for regenerative medicine purposes. However, there are still many challenges in the creation of vascularized tissue constructs and their biological applications. This review will summarize the latest efforts to create vasculatures and vascularized tissues for cancer research and regenerative medicine.

Vascularized adipose tissue engineering: moving towards soft tissue reconstruction.

Soft tissue defects are a common clinical challenge mostly caused by trauma, congenital anomalies and oncological surgery. Current soft tissue reconstruction options include synthetic materials (fillers and implants) and autologous adipose tissue transplantation through flap surgery and/or lipotransfer. Both reconstructive options hold important disadvantages to which vascularized adipose tissue engineering (VATE) strategies could offer solutions. In this review, we first summarized pivotal characteristics of functional adipose tissue such as the structure, function, cell types, development and extracellular matrix (ECM). Next, we discussed relevant cell sources and how they are applied in different state-of-the-art VATE techniques. Herein, biomaterial scaffolds and hydrogels, ECMs, spheroids, organoids, cell sheets, three dimensional printing and microfluidics are overviewed. Also, we included extracellular vesicles and emphasized their potential role in VATE. Lastly, current challenges and future perspectives in VATE are pointed out to help to pave the road towards clinical applications.

Engineered organoids for biomedical applications.

As miniaturized and simplified stem cell-derived 3D organ-like structures, organoids are rapidly emerging as powerful tools for biomedical applications. With their potential for personalized therapeutic interventions and high-throughput drug screening, organoids have gained significant attention recently. In this review, we discuss the latest developments in engineering organoids and using materials engineering, biochemical modifications, and advanced manufacturing technologies to improve organoid culture and replicate vital anatomical structures and functions of human tissues. We then explore the diverse biomedical applications of organoids, including drug development and disease modeling, and highlight the tools and analytical techniques used to investigate organoids and their microenvironments. We also examine the latest clinical trials and patents related to organoids that show promise for future clinical translation. Finally, we discuss the challenges and future perspectives of using organoids to advance biomedical research and potentially transform personalized medicine.

Aloe vera-loaded natural rubber latex dressing as a potential complementary treatment for psoriasis.

Psoriasis is a disease that causes keratinocytes to proliferate ten times faster than normal, resulting in chronic inflammation and immune cell infiltration in the skin. Aloe vera (A. vera) creams have been used topically for treating psoriasis because they contain several antioxidant species; however, they have several limitations. Natural rubber latex (NRL) has been used as occlusive dressings to promote wound healing by stimulating cell proliferation, neoangiogenesis, and extracellular matrix formation. In this work, we developed a new A. vera-releasing NRL dressing by a solvent casting method to load A. vera into NRL. FTIR and rheological analyzes revealed no covalent interactions between A. vera and NRL in the dressing. We observed that 58.8 % of the loaded A. vera, present on the surface and inside the dressing, was released after 4 days. Biocompatibility and hemocompatibility were validated in vitro using human dermal fibroblasts and sheep blood, respectively. We observed that ~70 % of the free antioxidant properties of A. vera were preserved, and the total phenolic content was 2.31-fold higher than NRL alone. In summary, we combined the antipsoriatic properties of A. vera with the healing activity of NRL to generate a novel occlusive dressing that may be indicated for the management and/or treatment of psoriasis symptoms simply and economically.

Integrated biosensors for monitoring microphysiological systems.

Microphysiological systems (MPSs), also known as organ-on-a-chip models, aim to recapitulate the functional components of human tissues or organs in vitro. Over the last decade, with the advances in biomaterials, 3D bioprinting, and microfluidics, numerous MPSs have emerged with applications to study diseased and healthy tissue models. Various organs have been modeled using MPS technology, such as the heart, liver, lung, and blood-brain barrier. An important aspect of in vitro modeling is the accurate phenotypical and functional characterization of the modeled organ. However, most conventional characterization methods are invasive and destructive and do not allow continuous monitoring of the cells in culture. On the other hand, microfluidic biosensors enable in-line, real-time sensing of target molecules with an excellent limit of detection and in a non-invasive manner, thereby effectively overcoming the limitation of the traditional techniques. Consequently, microfluidic biosensors have been increasingly integrated into MPSs and used for in-line target detection. This review discusses the state-of-the-art microfluidic biosensors by providing specific examples, detailing their main advantages in monitoring MPSs, and highlighting current developments in this field. Finally, we describe the remaining challenges and potential future developments to advance the current state-of-the-art in integrated microfluidic biosensors.

Impartially Validated Multiple Deep-Chain Models to Detect COVID-19 in Chest X-ray Using Latent Space Radiomics.

The COVID-19 pandemic continues to spread globally at a rapid pace, and its rapid detection remains a challenge due to its rapid infectivity and limited testing availability. One of the simply available imaging modalities in clinical routine involves chest X-ray (CXR), which is often used for diagnostic purposes. Here, we proposed a computer-aided detection of COVID-19 in CXR imaging using deep and conventional radiomic features. First, we used a 2D U-Net model to segment the lung lobes. Then, we extracted deep latent space radiomics by applying deep convolutional autoencoder (ConvAE) with internal dense layers to extract low-dimensional deep radiomics. We used Johnson-Lindenstrauss (JL) lemma, Laplacian scoring (LS), and principal component analysis (PCA) to reduce dimensionality in conventional radiomics. The generated low-dimensional deep and conventional radiomics were integrated to classify COVID-19 from pneumonia and healthy patients. We used 704 CXR images for training the entire model (i.e., U-Net, ConvAE, and feature selection in conventional radiomics). Afterward, we independently validated the whole system using a study cohort of 1597 cases. We trained and tested a random forest model for detecting COVID-19 cases through multivariate binary-class and multiclass classification. The maximal (full multivariate) model using a combination of the two radiomic groups yields performance in classification cross-validated accuracy of 72.6% (69.4-74.4%) for multiclass and 89.6% (88.4-90.7%) for binary-class classification.

State of the art in integrated biosensors for organ-on-a-chip applications.

Organ-on-a-chip (OoC) models are bioengineered tissue constructs integrated with microfluidics that recapitulate the key features of the physiology of human organs and tissues with applications related to drug development and personalized medicine. The characterization of OoCs relies on conventional labor-intensive approaches despite the many years of research in the field. The physical environment of the tissue constructs, functionality, and metabolic activity of the cells must be monitored to ensure the behavior of the cells, and the cellular environments represent in vivo physiology. Current efforts focus on monitoring these parameters, particularly with in-line biosensors integrated with OoCs. In this review, we describe the recent advances in different biosensing modalities applied to monitor the environment and functionality of OoC models and offer suggestions for future directions in OoC applications.

Personalized prediction of delayed graft function for recipients of deceased donor kidney transplants with machine learning.

Machine learning (ML) has shown its potential to improve patient care over the last decade. In organ transplantation, delayed graft function (DGF) remains a major concern in deceased donor kidney transplantation (DDKT). To this end, we harnessed ML to build personalized prognostic models to predict DGF. Registry data were obtained on adult DDKT recipients for model development (n = 55,044) and validation (n = 6176). Incidence rates of DGF were 25.1% and 26.3% for the development and validation sets, respectively. Twenty-six predictors were identified via recursive feature elimination with random forest. Five widely-used ML algorithms-logistic regression (LR), elastic net, random forest, artificial neural network (ANN), and extreme gradient boosting (XGB) were trained and compared with a baseline LR model fitted with previously identified risk factors. The new ML models, particularly ANN with the area under the receiver operating characteristic curve (ROC-AUC) of 0.732 and XGB with ROC-AUC of 0.735, exhibited superior performance to the baseline model (ROC-AUC = 0.705). This study demonstrates the use of ML as a viable strategy to enable personalized risk quantification for medical applications. If successfully implemented, our models may aid in both risk quantification for DGF prevention clinical trials and personalized clinical decision making.

Education Strategies in Dialysis Centers Associated With Increased Transplant Wait-listing Rates.

BACKGROUND: Transplant education in dialysis centers can increase access to kidney transplant; however, dialysis center transplant barriers are common, and limited research identifies the most effective transplant education approaches. METHODS: We surveyed transplant educators in 1694 US dialysis centers about their transplant knowledge, use of 12 education practices, and 8 identified education barriers. Transplant wait-listing rates were calculated using US Renal Data System data. RESULTS: Fifty-two percent of educators orally recommended transplant to patients, 31% had in-center transplant discussions with patients, 17% distributed print educational resources, and 3% used intensive education approaches. Distribution of print education (incident rate ratio: 1.021.151.30) and using >1 intensive education practice (1.001.111.23) within dialysis centers were associated with increased wait-listing rates. Several dialysis center characteristics were associated with reduced odds of using education strategies leading to increased wait-listing. Centers with greater percentages of uninsured patients (odds ratio [OR]: 0.960.970.99), in rural locations (OR: 0.660.790.95), with for-profit ownership (OR: 0.640.770.91), and with more patients older than 65 years (OR: 0.050.110.23) had lower odds of recommending transplant, while centers with a higher patient-to-staff ratio were more likely to do so (OR: 1.011.031.04). Language barriers (OR: 0.480.640.86) and having competing work priorities (OR: 0.400.530.70) reduced the odds of distributing print education. Providers with greater transplant knowledge were more likely to use >1 intensive educational strategy (OR: 1.011.271.60) while providers who reported competing work priorities (OR: 0.510.660.84) and poor communication with transplant centers (OR: 0.580.760.98) were less likely to do so. CONCLUSIONS: Educators should prioritize transplant education strategies shown to be associated with increasing wait-listing rates.

Measurement Characteristics of the Knowledge Assessment of Renal Transplantation.

BACKGROUND: Kidney transplant is the best treatment for most end-stage renal disease (ESRD) patients, but proportionally few ESRD patients receive kidney transplant. To make an informed choice about whether to pursue kidney transplant, patients must be knowledgeable of its risks and benefits. To reliably and validly measure ESRD patients' kidney transplant knowledge, rigorously tested measures are required. This article describes the development and psychometric testing of the Knowledge Assessment of Renal Transplantation (KART). METHODS: We administered 17 transplant knowledge items to a sample of 1294 ESRD patients. Item characteristics and scale scores were estimated using an Item Response Theory graded response model. Construct validity was tested by examining differences in scale scores between patients who had spent less than 1 and 1 hour or longer receiving various types of transplant education. RESULTS: Item Response Theory modeling suggested that 15 items should be retained for the KART. This scale had a marginal reliability of 0.75 and evidenced acceptable reliability (>0.70) across most of its range. Construct validity was supported by the KART's ability to distinguish patients who had spent less than 1 and 1 hour or longer receiving different types of kidney transplant education, including talking to doctors/medical staff (effect size [ES], 0.61; P < 0.001), reading brochures (ES, 0.45; P < 0.001), browsing the internet (ES, 0.56; P < 0.001), and watching videos (ES, 0.56; P < 0.001). CONCLUSIONS: The final 15-item KART can be used to determine the kidney transplant knowledge levels of ESRD patients and plan appropriate interventions to ensure informed transplant decision making occurs.