A new microscope for the kidney: mathematics

Sex differences in renal transporters: assessment and functional consequences

Mammalian kidneys are specialized to maintain fluid and electrolyte homeostasis. The epithelial transport processes along the renal tubule that match output to input have long been the subject of experimental and theoretical study. However, emerging data have identified a new dimension of investigation: sex. Like most tissues, the structure and function of the kidney is regulated by sex hormones and chromosomes. Available data demonstrate sex differences in the abundance of kidney solute and electrolyte transporters, establishing that renal tubular organization and operation are distinctly different in females and males. Newer studies have provided insights into the physiological consequences of these sex differences. Computational simulations predict that sex differences in transporter abundance are likely driven to optimize reproduction, enabling adaptive responses to the nutritional requirements of serial pregnancies and lactation - normal life-cycle changes that challenge the ability of renal transporters to maintain fluid and electrolyte homeostasis. Later in life, females may also undergo menopause, which is associated with changes in disease risk. Although numerous knowledge gaps remain, ongoing studies will provide further insights into the sex-specific mechanisms of sodium, potassium, acid-base and volume physiology throughout the life cycle, which may lead to therapeutic opportunities.

"Hi, how can i help you?": embracing artificial intelligence in kidney research

In recent years, biology and precision medicine have benefited from major advancements in generating large-scale molecular and biomedical datasets and in analyzing those data using advanced machine learning algorithms. Machine learning applications in kidney physiology and pathophysiology include segmenting kidney structures from imaging data and predicting conditions like acute kidney injury or chronic kidney disease using electronic health records. Despite the potential of machine learning to revolutionize nephrology by providing innovative diagnostic and therapeutic tools, its adoption in kidney research has been slower than in other organ systems. Several factors contribute to this underutilization. The complexity of the kidney as an organ, with intricate physiology and specialized cell populations, makes it challenging to extrapolate bulk omics data to specific processes. In addition, kidney diseases often present with overlapping manifestations and morphological changes, making diagnosis and treatment complex. Moreover, kidney diseases receive less funding compared with other pathologies, leading to lower awareness and limited public-private partnerships. To promote the use of machine learning in kidney research, this review provides an introduction to machine learning and reviews its notable applications in renal research, such as morphological analysis, omics data examination, and disease diagnosis and prognosis. Challenges and limitations associated with data-driven predictive techniques are also discussed. The goal of this review is to raise awareness and encourage the kidney research community to embrace machine learning as a powerful tool that can drive advancements in understanding kidney diseases and improving patient care.

Renal tubular solute transport and oxygen consumption: insights from computational models

PURPOSE OF REVIEW

To maintain electrolyte homeostasis, the kidneys reabsorb more than 99% of the filtered Na under physiological conditions, resulting in less than 1% of the filtered Na excreted in urine. In contrast, due to distal tubular secretion, urinary K output may exceed filtered load. This review focuses on a relatively new methodology for investigating renal epithelial transport, computational modelling and highlights recent insights regarding renal Na and K transport and O2 consumption under pathophysiological conditions, with a focus on nephrectomy.

RECENT FINDINGS

Recent modelling studies investigated the extent to which the adaptive response to nephrectomy, which includes elevation in single-nephron glomerular filtration rate and tubular transport capacity, may achieve balance but increases O2 consumption per nephron. Simulation results pointed to potential mechanisms in a hemi-nephrectomized rat that may attenuate the natriuresis response under K load, or that may augment the natriuretic, diuretic and kaliuretic effects of sodium glucose cotransporter 2 inhibition.

SUMMARY

Computational models provide a systemic approach for investigating system perturbations, such as those induced by drug administration or genetic alterations. Thus, computational models can be a great asset in data interpretation concerning (but not limited to) renal tubular transport and metabolism.

3D simulation of solutes concentration in urinary concentration mechanism in rat renal medulla

In this work, a mathematical model was developed to simulate the urinary concentration mechanism. A 3-D geometry was derived based on the detail physiological pictures of rat kidney. The approximate region of each tubule was obtained from the volume distribution of structures based on Walter Pfaller's monograph and Layton's region-based model. Mass and momentum balances were applied to solve for the change in solutes concentration and osmolality. The osmolality of short and long descending nephrons at the end of the outer medulla was obtained to be 530 mOsmol/kgH2O and 802 mOsmol/kgH2O, respectively, which were in acceptable agreement with experimental data. The fluid osmolality of the short and long ascending nephrons was also compatible with experimental data. The osmolality of CD fluid at the end of the inner medulla was determined to be 1198 mOsmol/kgH2O which was close the experimental data (1216 ± 118). Finally, the impact of the position of each tubule on the fluid osmolality and solutes concentration were obvious in the results; for example, short descending limb a1, which is the closest tubule to the collecting duct, had the highest urea concentration in all tubules. This reflects the important effect of the 3D modeling on the precise analysis of urinary concentration mechanism.

Functional implications of sexual dimorphism of transporter patterns along the rat proximal tubule: modeling and analysis

The goal of this study is to investigate the functional implications of the sexual dimorphism in transporter patterns along the proximal tubule. To do so, we have developed sex-specific computational models of solute and water transport in the proximal convoluted tubule of the rat kidney. The models account for the sex differences in expression levels of the apical and basolateral transporters, in single-nephron glomerular filtration rate, and in tubular dimensions. Model simulations predict that 70.6 and 38.7% of the filtered volume is reabsorbed by the proximal tubule of the male and female rat kidneys, respectively. The lower fractional volume reabsorption in females can be attributed to their smaller transport area and lower aquaporin-1 expression level. The latter also results in a larger contribution of the paracellular pathway to water transport. Correspondingly similar fractions (70.9 and 39.2%) of the filtered Na+ are reabsorbed by the male and female proximal tubule models, respectively. The lower fractional Na+ reabsorption in females is due primarily to their smaller transport area and lower Na+/H+ exchanger isoform 3 and claudin-2 expression levels. Notably, unlike most Na+ transporters, whose expression levels are lower in females, Na+-glucose cotransporter 2 (SGLT2) expression levels are 2.5-fold higher in females. Model simulations suggest that the higher SGLT2 expression in females may compensate for their lower tubular transport area to achieve a hyperglycemic tolerance similar to that of males.