How artificial intelligence is transforming nephrology.

Current research in nephrology is increasingly focused on elucidating the complexity inherent in tightly interwoven molecular systems and their correlation with pathology and related therapeutics, including dialysis and renal transplantation. Rapid advances in the omics sciences, medical device sensorization, and networked digital medical devices have made such research increasingly data centered. Data-centric science requires the support of computationally powerful and sophisticated tools able to handle the overflow of novel biomarkers and therapeutic targets. This is a context in which artificial intelligence (AI) and, more specifically, machine learning (ML) can provide a clear analytical advantage, given the rapid advances in their ability to harness multimodal data, from genomic information to signal, image and even heterogeneous electronic health records (EHR). However, paradoxically, only a small fraction of ML-based medical decision support systems undergo validation and demonstrate clinical usefulness. To effectively translate all this new knowledge into clinical practice, the development of clinically compliant support systems based on interpretable and explainable ML-based methods and clear analytical strategies for personalized medicine are imperative. Intelligent nephrology, that is, the design and development of AI-based strategies for a data-centric approach to nephrology, is just taking its first steps and is by no means yet close to its coming of age. These first steps are not even homogeneously taken, as a digital divide in access to technology has become evident between developed and developing countries, also affecting underrepresented minorities. With all this in mind, this editorial aim to provide a selective overview of the current use of AI technologies in nephrology and heralds the "Artificial Intelligence in Nephrology" special issue launched by BMC Nephrology.

Regulation of ClC-K/barttin by endocytosis influences distal convoluted tubule hyperplasia.

ClC-K/barttin channels are involved in the transepithelial transport of chloride in the kidney and inner ear. Their physiological role is crucial in humans because mutations in CLCNKB or BSND, encoding ClC-Kb and barttin, cause Bartter's syndrome types III and IV, respectively. In vitro experiments have shown that an amino acid change in a proline-tyrosine motif in the C-terminus of barttin stimulates ClC-K currents. The molecular mechanism of this enhancement and whether this potentiation has any in vivo relevance remains unknown. We performed electrophysiological and biochemical experiments in Xenopus oocytes and kidney cells co-expressing ClC-K and barttin constructs. We demonstrated that barttin possesses a YxxØ motif and, when mutated, increases ClC-K plasma membrane stability, resulting in larger currents. To address the impact of mutating this motif in kidney physiology, we generated a knock-in mouse. Comparing wild-type (WT) and knock-in mice under a standard diet, we could not observe any difference in ClC-K and barttin protein levels or localization, either in urinary or plasma parameters. However, under a high-sodium low-potassium diet, known to induce hyperplasia of distal convoluted tubules, knock-in mice exhibit reduced hyperplasia compared to WT mice. In summary, our in vitro and in vivo studies demonstrate that the previously identified PY motif is indeed an endocytic YxxØ motif in which mutations cause a gain of function of the channel. KEY POINTS: It is revealed by mutagenesis and functional experiments that a previously identified proline-tyrosine motif regulating ClC-K plasma membrane levels is indeed an endocytic YxxØ motif. Biochemical characterization of mutants in the YxxØ motif in Xenopus oocytes and human embryonic kidney cells indicates that mutants showed increased plasma membrane levels as a result of an increased stability, resulting in higher function of ClC-K channels. Mutation of this motif does not affect barttin protein expression and subcellular localization in vivo. Knock-in mice with a mutation in this motif, under conditions of a high-sodium low-potassium diet, exhibit less hyperplasia in the distal convoluted tubule than wild-type animals, indicating a gain of function of the channel in vivo.

Development of cationic solid lipid nanoparticles incorporating cholesteryl-9-carboxynonanoate (9CCN) for delivery of antagomiRs to macrophages.

Lipid-based nanoparticles are a useful tool for nucleic acids delivery and have been regarded as a promising approach for diverse diseases. However, off-targets effects are a matter of concern and some strategies to improve selectivity of solid lipid nanoparticles (SLNs) were reported. The goal of this study was to test formulations of SLNs incorporating lipid cholesteryl-9-carboxynonanoate (9CCN) as "eat-me" signal to target antagomiR oligonucleotides to macrophages. We formulate four SLNs, and those with a mean diameter of 200 nm and a Z-potential values between 25 and 40 mV, which allowed the antagomiR binding, were selected for in vitro studies. Cell viability, transfection efficiency and cellular uptake assays were performed within in vitro macrophages using flow cytometry and confocal imaging and the SLNs incorporating 25 mg of 9CCN proved to be the best formulation. Subsequently, we used a labeled antagomiR to study tissue distribution in in-vivo ApoE-/- model of atherosclerosis. Using the ApoE-/- model we demonstrated that SLNs with phagocytic signal 9-CCN target macrophages and release the antagomiR cargo in a selective way.

Is Generative Artificial Intelligence the Next Step Toward a Personalized Hemodialysis?

ABSTRACT Artificial intelligence (AI) generative models driven by the integration of AI and natural language processing technologies, such as OpenAI's chatbot generative pre-trained transformer large language model (LLM), are receiving much public attention and have the potential to transform personalized medicine. Dialysis patients are highly dependent on technology and their treatment generates a challenging large volume of data that has to be analyzed for knowledge extraction. We argue that, by integrating the data acquired from hemodialysis treatments with the powerful conversational capabilities of LLMs, nephrologists could personalize treatments adapted to patients' lifestyles and preferences. We also argue that this new conversational AI integrated with a personalized patient-computer interface will enhance patients' engagement and self-care by providing them with a more personalized experience. However, generative AI models require continuous and accurate updates of data, and expert supervision and must address potential biases and limitations. Dialysis patients can also benefit from other new emerging technologies such as Digital Twins with which patients' care can also be addressed from a personalized medicine perspective. In this paper, we will revise LLMs potential strengths in terms of their contribution to personalized medicine, and, in particular, their potential impact, and limitations in nephrology. Nephrologists' collaboration with AI academia and companies, to develop algorithms and models that are more transparent, understandable, and trustworthy, will be crucial for the next generation of dialysis patients. The combination of technology, patient-specific data, and AI should contribute to create a more personalized and interactive dialysis process, improving patients' quality of life.

Sex Differences in Glomerular Lesions, in Atherosclerosis Progression, and in the Response to Angiotensin-Converting Enzyme Inhibitors in the ApoE-/- Mice Model.

This study analyzes sex-based differences in renal structure and the response to the Angiotensin-Converting Enzyme (ACE) inhibitor enalapril in a mouse model of atherosclerosis. Eight weeks old ApoE-/- mice received enalapril (5 mg/kg/day, subcutaneous) or PBS (control) for an additional 14 weeks. Each group consisted of six males and six females. Females exhibited elevated LDL-cholesterol levels, while males presented higher creatinine levels and proteinuria. Enalapril effectively reduced blood pressure in both groups, but proteinuria decreased significantly only in females. Plaque size analysis and assessment of kidney inflammation revealed no significant sex-based differences. However, males displayed more severe glomerular injury, with increased mesangial expansion, mesangiolysis, glomerular foam cells, and activated parietal epithelial cells (PECs). Enalapril mitigated mesangial expansion, glomerular inflammation (particularly in the female group), and hypertrophy of the PECs in males. This study demonstrates sex-based differences in the response to enalapril in a mouse model of atherosclerosis. Males exhibited more severe glomerular injury, while enalapril provided renal protection, particularly in females. These findings suggest potential sex-specific considerations for ACE inhibitor therapy in chronic kidney disease and atherosclerosis cardiovascular disease. Further research is needed to elucidate the underlying mechanism behind these observations.

Measurement of apixaban concentrations in different human biological fluids by UHPLC-MS/MS. Clinical pharmacokinetic application in a subject with chronic kidney disease and nonvalvular atrial fibrillation on haemodialysis.

BACKGROUND: Apixaban's technical sheet does not recommend its use in clinical practice for patients with chronic kidney disease undergoing haemodialysis. However, recent studies indicate that apixaban could be a safe oral anticoagulant in these kinds of patients who do not present valvular atrial fibrillation. We developed and validated ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) procedures for measuring apixaban concentrations in plasma, dialysate liquid, and urine. MATERIAL AND METHODS: Simple protein precipitation was implemented to prepare samples. Chromatographic separations were achieved on an Acquity®-UPLC®-BEHTM (2.1x100 mm id, 1.7 µm) reverse-phase C18 column using a water/acetonitrile non-linear gradient containing 0.1 % formic acid at a 0.4 mL/min flow rate. Apixaban and its internal standard (apixaban-d3) were detected by electrospray ionisation mass spectrometry in positive and multiple reaction monitoring modes, using transitions of 460.3 â†’ 199.0/443.2 and 463.3 â†’ 202.0, respectively. RESULTS: No significant interferences and carry-overs were observed. Precisions, absolute relative biases, normalised-matrix factors, and normalised recoveries were ≤ 12.2%, ≤8.0%, 94.3-105.1%, and 93.9-105.4%, respectively. Linearity was observed between 5 and 500 µg/L for plasma/dialysate liquid and 5-1000 µg/L for urine. CONCLUSIONS: The validated UHPLC-MS/MS procedures could help support a pharmacokinetic study in non-valvular atrial fibrillation subjects with chronic kidney disease undergoing haemodialysis and apixaban-based anticoagulant therapy.

Is generative artificial intelligence the next step toward a personalized hemodialysis?

Artificial intelligence (AI) generative models driven by the integration of AI and natural language processing technologies, such as OpenAI's chatbot generative pre-trained transformer large language model (LLM), are receiving much public attention and have the potential to transform personalized medicine. Dialysis patients are highly dependent on technology and their treatment generates a challenging large volume of data that has to be analyzed for knowledge extraction. We argue that, by integrating the data acquired from hemodialysis treatments with the powerful conversational capabilities of LLMs, nephrologists could personalize treatments adapted to patients' lifestyles and preferences. We also argue that this new conversational AI integrated with a personalized patient-computer interface will enhance patients' engagement and self-care by providing them with a more personalized experience. However, generative AI models require continuous and accurate updates of data, and expert supervision and must address potential biases and limitations. Dialysis patients can also benefit from other new emerging technologies such as Digital Twins with which patients' care can also be addressed from a personalized medicine perspective. In this paper, we will revise LLMs potential strengths in terms of their contribution to personalized medicine, and, in particular, their potential impact, and limitations in nephrology. Nephrologists' collaboration with AI academia and companies, to develop algorithms and models that are more transparent, understandable, and trustworthy, will be crucial for the next generation of dialysis patients. The combination of technology, patient-specific data, and AI should contribute to create a more personalized and interactive dialysis process, improving patients' quality of life.

Editorial to the IJMS Special Issue on "ncRNAS in Therapeutics".

For many years, the RNA world of eukaryotic cells remained stable and predictable, organized by a few families of functionally different molecules [...].

MiR-125b downregulates macrophage scavenger receptor type B1 and reverse cholesterol transport.

OBJECTIVE: To determine whether miR-125b regulates cholesterol efflux in vivo and in vitro through the regulation of scavenger receptor type B1 (SR-B1). APPROACH AND RESULTS: We demonstrated that miR-125b is up-regulated in the human aortas of patients with CAD and is located in macrophages and vascular smooth muscle cells (VSMCs). We identified SCARB1 as a direct target of miR-125b by repressing the activity of the SCARB1 3'-untranslated region reporter construct. Moreover, the overexpression of miR-125b in both human and mouse macrophages as well as VSMCs was found to downregulated the expression of the SCARB1 and the SR-B1 protein levels, thereby impairing α-HDL-mediated macrophage cholesterol efflux in vitro. The in vivo reverse cholesterol transport (RCT) rate from non-cholesterol-loaded macrophages transfected with miR-125b to feces was also found to be decreased when compared with that of control mimic-transfected macrophages. CONCLUSIONS: Together, these results provide evidence that miR-125b downregulates SCARB1 and SR-B1 in both human and mouse macrophages as well as VSMCs, thereby impairing macrophage cholesterol efflux in vitro and the whole macrophage-specific RCT pathway in vivo.

Dynamic Variations of 3'UTR Length Reprogram the mRNA Regulatory Landscape.

This paper concerns 3'-untranslated regions (3'UTRs) of mRNAs, which are non-coding regulatory platforms that control stability, fate and the correct spatiotemporal translation of mRNAs. Many mRNAs have polymorphic 3'UTR regions. Controlling 3'UTR length and sequence facilitates the regulation of the accessibility of functional effectors (RNA binding proteins, miRNAs or other ncRNAs) to 3'UTR functional boxes and motifs and the establishment of different regulatory landscapes for mRNA function. In this context, shortening of 3'UTRs would loosen miRNA or protein-based mechanisms of mRNA degradation, while 3'UTR lengthening would strengthen accessibility to these effectors. Alterations in the mechanisms regulating 3'UTR length would result in widespread deregulation of gene expression that could eventually lead to diseases likely linked to the loss (or acquisition) of specific miRNA binding sites. Here, we will review the mechanisms that control 3'UTR length dynamics and their alterations in human disorders. We will discuss, from a mechanistic point of view centered on the molecular machineries involved, the generation of 3'UTR variability by the use of alternative polyadenylation and cleavage sites, of mutually exclusive terminal alternative exons (exon skipping) as well as by the process of exonization of Alu cassettes to generate new 3'UTRs with differential functional features.

ncRNAs in Therapeutics: Challenges and Limitations in Nucleic Acid-Based Drug Delivery.

Non-coding RNAs (ncRNAs) are emerging therapeutic tools but there are barriers to their translation to clinical practice. Key issues concern the specificity of the targets, the delivery of the molecules, and their stability, while avoiding "on-target" and "off-target" side effects. In this "ncRNA in therapeutics" issue, we collect several studies of the differential expression of ncRNAs in cardiovascular diseases, bone metabolism-related disorders, neurology, and oncology, and their potential to be used as biomarkers or therapeutic targets. Moreover, we review recent advances in the use of antisense ncRNAs in targeted therapies with a particular emphasis on their basic biological mechanisms, their translational potential, and future trends.

In vivo CD40 Silencing by siRNA Infusion in Rodents and Evaluation by Kidney Immunostaining.

The co-stimulatory molecule CD40 and its ligand CD40L play a key role in the regulation of immunological processes and are involved in the pathophysiology of autoimmune and inflammatory diseases. Inhibition of the CD40-CD40L axis is a promising therapy, and a number of strategies and techniques have been designed to hinder its functionality. Our group has broad experience in silencing CD40 using RNAi technology, and here we summarize protocols for the systemic administration of a specific anti-CD40 siRNA in different rodents models, in addition to the subsequent quantification of CD40 expression in murine kidneys by immunostaining. The use of RNAi technology with specific siRNAs to silence genes is becoming an essential method to investigate gene functions and is rapidly emerging as a therapeutic tool. Graphic abstract: CD40 siRNA mechanism.

Treatment for severe COVID-19 with a biomimetic sorbent haemoperfusion device in patients on haemodialysis.

Haemodialysis (HD) patients present more morbidity and mortality risk in coronavirus disease 2019 (COVID-19). In patients who may develop severe symptoms, the process called 'viral sepsis' seems to be a crucial mechanism. In those cases, the HD procedure provides an excellent tool to explore the benefit of some extracorporeal therapies. We reported the outcome of four HD patients with severe COVID-19 treated with Seraph®100 haemoperfusion (HP) device. Three of the four cases presented a good clinical response after HP. In conclusion, the treatment with Seraph®100 device may be a simultaneous treatment to improve HD patients with severe acute respiratory syndrome coronavirus 2.

Impact of obesity on the evolution of outcomes in peritoneal dialysis patients.

BACKGROUND: Some studies reveal that obesity is associated with a decrease in mortality in haemodialysis (HD) patients. However, few studies have addressed the association between body mass index (BMI) and peritoneal dialysis (PD) patients. METHODS: We performed this longitudinal, retrospective study to evaluate the impact of obesity on PD patients, using data from the Catalan Registry of Renal Patients from 2002 to 2015 (n = 1573). Obesity was defined as BMI ≥30; low weight: BMI <18.5; normal range: BMI = 18.5-24.99; and pre-obesity: BMI = 25-29.99 kg/m2. Variations in BMI were calculated during follow-up. The main outcomes evaluated were the technique and patient survival. RESULTS: Obesity was observed in 20% of patients starting PD. We did not find differences in sex or PD modality, with the obesity group being older (65.9% are ≥55 years versus 59% non-obese, P = 0.003) and presenting more diabetes mellitus and cardiovascular disease (CVD) (47.9% obese versus 25.1% non-obese and 41.7% versus 31.5%, respectively). We did not observe differences in haemoglobin, albumin and Kt/V in obese patients. Regarding peritonitis rate, we did not find any difference between groups, presenting more peritonitis patients on continuous ambulatory peritoneal dialysis and aged ≥65 years [sub-hazard ratio (SHR) = 1.75, P = 0.000 and SHR = 1.56, P = 0.009]. In relation to technique survival, we found higher transfer to HD in the obese group of patients in the univariate analysis, which was not confirmed in the multivariate analysis (SHR = 1.12, P = 0.4), and we did not find differences in mortality rate. In relation to being transplanted, the underweight group, elderly and patients with CVD or diabetic nephropathy presented less probability to undergo kidney transplantation (SHR = 0.65, 0.24, 0.5 and 0.54, P < 0.05). Obese patients did not present differences in survival with weight changes but in normal-weight patients, a gain of 7% of the basal weight during the first year had a protective effect on death risk (hazard ratio 0.6, P = 0.034). CONCLUSIONS: Obese and non-obese patients starting on PD had similar outcomes.

Chronic Kidney Disease-Associated Inflammation Increases the Risks of Acute Kidney Injury and Mortality after Cardiac Surgery.

Cardiovascular mortality increases with decreasing renal function although the cause is yet unknown. Here, we have investigated whether low chronic inflammation in chronic kidney diseases (CKD) could contribute to increased risk for coronary artery diseases (CAD). Thus, a prospective case-control study was conducted in patients with CAD and CKD undergoing coronary artery bypass graft surgery with the aim of detecting differences in cardiovascular outcomes, epicardial adipose tissue volume, and inflammatory marker activity associated with renal dysfunction. Expression of membrane CD14 and CD16, inflammatory cytokines and chemokines, mitogen-activated protein (MAP) kinases and hsa-miR-30a-5p were analyzed in peripheral blood mononuclear cells (PBMCs). Epicardial fat volume and tissue inflammation in perivascular adipose tissue and in the aorta were also studied. In the present study, 151 patients were included, 110 with CAD (51 with CKD) and 41 nonCAD controls (15 with CKD). CKD increased the risk of cardiac surgery-associated acute kidney injury (CSA-AKI) as well as the 30-day mortality after cardiac surgery. Higher counts of CD14++CD16+ monocytes were associated with vascular inflammation, with an increased expression of IL1ß, and with CKD in CAD patients. Expression of hsa-miR-30a-5p was correlated with hypertension. We conclude that CKD patients show an increased risk of CSA-AKI and mortality after cardiovascular surgery, associated with the expansion of the CD14++CD16+ subset of proinflammatory monocytes and with IL1ß expression. We propose that inflammation associated with CKD may contribute to atherosclerosis (ATH) pathogenesis.

Leveraging Data Science for a Personalized Haemodialysis.

BACKGROUND: The 2019 Science for Dialysis Meeting at Bellvitge University Hospital was devoted to the challenges and opportunities posed by the use of data science to facilitate precision and personalized medicine in nephrology, and to describe new approaches and technologies. The meeting included separate sections for issues in data collection and data analysis. As part of data collection, we presented the institutional ARGOS e-health project, which provides a common model for the standardization of clinical practice. We also pay specific attention to the way in which randomized controlled trials offer data that may be critical to decision-making in the real world. The opportunities of open source software (OSS) for data science in clinical practice were also discussed. SUMMARY: Precision medicine aims to provide the right treatment for the right patients at the right time and is deeply connected to data science. Dialysis patients are highly dependent on technology to live, and their treatment generates a huge volume of data that has to be analysed. Data science has emerged as a tool to provide an integrated approach to data collection, storage, cleaning, processing, analysis, and interpretation from potentially large volumes of information. This is meant to be a perspective article about data science based on the experience of the experts invited to the Science for Dialysis Meeting and provides an up-to-date perspective of the potential of data science in kidney disease and dialysis. KEY MESSAGES: Healthcare is quickly becoming data-dependent, and data science is a discipline that holds the promise of contributing to the development of personalized medicine, although nephrology still lags behind in this process. The key idea is to ensure that data will guide medical decisions based on individual patient characteristics rather than on averages over a whole population usually based on randomized controlled trials that excluded kidney disease patients. Furthermore, there is increasing interest in obtaining data about the effectiveness of available treatments in current patient care based on pragmatic clinical trials. The use of data science in this context is becoming increasingly feasible in part thanks to the swift developments in OSS.