Introduction: Klotho acts as a coreceptor for the phosphaturic hormone fibroblast growth factor-23 (FGF-23) and exists in both a membrane-bound and a soluble form (sKlotho) found in blood and urine. Klotho protein is moderately expressed in kidney proximal tubule and more abundant in the distal convolution (DC), which includes the distal convoluted tubule (DCT) and connecting tubule (CNT). However, the function of Klotho in the DC, particularly its role in sKlotho release and regulation of mineral metabolism, remains unclear. Methods: scRNA-seq was performed on isolated mouse DC cells. Four novel gene-modified mouse models were generated with Klotho deleted in the entire DC, the late DCT/CNT, the DCT only, and pan-tubular. Results: Using scRNA-seq on isolated mouse DC tubules, we showed that Klotho is more abundant in the late-DCT/CNT than in the early DCT. The composite data from three DC specific Klotho knockout mice support DC to be the primary source of urinary sKlotho, with 80% coming from the late-DCT/CNT and only 20% from the DCT. Notably, mice lacking Klotho in the entire DC (Kl-KODC) maintained normal serum sKlotho, FGF-23, and phosphate homeostasis. Bulk RNA-seq of isolated fluorescent DC segments from Kl-KODC_Tomato mice revealed suppressed signaling by mitogen activated protein kinase and downregulation of several genes involved in kidney calcium ion handling (Trpv5, Vdr, Pth1r, Klk1). Consistently, the Kl-KODC mice exhibited profound hypercalciuria and reduced bone density. On the other hand, pan-tubular Klotho deficiency in mice led to severe phosphate imbalance and loss of both serum/urine sKlotho. Conclusions: DC-derived Klotho regulates urinary sKlotho levels and controls calcium ion reabsorption, while Klotho in proximal tubule maintains phosphate homeostasis and likely regulates circulating sKlotho levels.

Background: Artificial intelligence (AI), the overarching field that includes machine learning (ML) and its subfield deep learning (DL), is rapidly transforming clinical research by enabling the analysis of high-dimensional data and automating the output of diagnostic and prognostic tests. As clinical trials become increasingly complex and costly, ML-based approaches (especially DL for image and signal data) offer promising solutions, although they require new approaches in clinical education. Objective: Explore current and emerging AI applications in oncology and cardiology, highlight real-world use cases, and discuss the challenges and future directions for responsible AI adoption. Methods: This narrative review summarizes various aspects of AI technology in clinical research, exploring its promise, use cases, and its limitations. The review was based on a literature search in PubMed covering publications from 2019 to 2025. Search terms included “artificial intelligence”, “machine learning”, “deep learning”, “oncology”, “cardiology”, “digital twin”. and “AI-ECG”. Preference was given to studies presenting validated or clinically applicable AI tools, while non-English articles, conference abstracts, and gray literature were excluded. Results: AI demonstrates significant potential in improving diagnostic accuracy, facilitating biomarker discovery, and detecting disease at an early stage. In clinical trials, AI improves patient stratification, site selection, and virtual simulations via digital twins. However, there are still challenges in harmonizing data, validating models, cross-disciplinary training, ensuring fairness, explainability, as well as the robustness of gold standards to which AI models are built. Conclusions: The integration of AI in clinical research can enhance efficiency, reduce costs, and facilitate clinical research as well as lead the way towards personalized medicine. Realizing this potential requires robust validation frameworks, transparent model interpretability, and collaborative efforts among clinicians, data scientists, and regulators. Interoperable data systems and cross-disciplinary education will be critical to enabling the integration of scalable, ethical, and trustworthy AI into healthcare.

Soluble-Klotho (sKl) is the shed ectodomain of the transmembrane protein-Klotho (mKl) that exhibits pleiotropic actions, including lifespan extension, mineral metabolism, slowing-down kidney diseases and cardioprotection. The sKl is derived from the kidneys, but what type/s of renal cells secrete it is unknown. Secondly the respective roles of mKl versus sKl in regulating mineral metabolism is unclear due to the lack of appropriate in vivo models. Here, using scRNA-seq of renal distal-convolution (DC) cells, we found an unexpected pattern revealing that Klotho transcripts ( Kl) are moderately expressed in overall distal convoluted tubule (DCT), but highly enriched in the end of DCT and in connecting tubule (CNT). Immunohistochemistry further confirmed this pattern for mKl protein as well. Next, Kl was knocked-out only in renal DC to check if it affects sKl production. Interestingly, deleting Kl in the DCT and late-DCT+CNT in mice showed ~20% and ~80% reduction in sKl levels, respectively. Expectedly, knocking-out Kl along the entire DC in mice (Kl-KODC) abolished sKl levels. Furthermore, we found that compared to control mice, Kl-KODC mice exhibited reduced renal TRPV5-Ca2+ channel expression, profound calciuria, and loss of bone mineral density. The RNA-seq of automated-sorted DC cells from Kl-KODC mice revealed enhanced caveolae-mediated endocytosis of TRPV5. On the other hand, Kl-KODC mice had normal phosphate metabolism as confirmed by unchanged serum FGF23, serum phosphate, urinary phosphate excretion, and renal NaPi-IIa expression. Our findings reveal that a small population of renal DC cells accounts for the sKl levels. The lack of sKl may leads to disturbed Ca2+ homeostasis and bone loss without affecting phosphate balance in mice. This is the full abstract presented at the American Physiology Summit 2023 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.