Edelman, B. J. | Search bioRxiv

bioRxiv2026

A single-plane electrical impedance tomography framework for integrated liver and kidney assessment

Chronic liver and kidney diseases frequently coexist, but their assessment typically requires separate clinical workflows involving serum-based estimated glomerular filtration rate (eGFR) testing and liver elastography-based controlled attenuation parameter (CAP). Electrical impedance tomography (EIT) has recently shown promise for providing portable, non-invasive proxies for both reference measurements. However, existing multi-organ EIT assessment still requires different acquisition protocols for each organ. To simplify this procedure, we assessed the feasibility of a single-plane EIT framework for reconstructing organ-specific images and estimating liver and kidney health from one abdominal belt placement. Across diverse abdominal belt locations, opposite-plane deviation was significantly greater for eGFREIT estimates (2.92%; IQR, 0.46-12.53%) than for CAPEIT estimates (0.94%; IQR, 0.66-1.70%) (p < 0.01). For both organs, compared to images acquired at the conventional organ-specific planes, image correlation significantly decreased (both, p < 0.05) and normalized root mean squared error significantly increased (both, p < 0.05) at the furthest imaging plane, with these differences being numerically larger for the kidney. Together, these results supported the kidney plane as the preferred location for multi-organ assessment. Test-retest evaluation after belt removal and reapplication demonstrated that the correlation between two repeated CAPEIT estimates was just as strong at the kidney plane (R2 = 0.98, p < 0.001) as it was at the conventional liver plane (R2 = 0.97, p < 0.001). Finally, in an independent clinical cohort, kidney-plane CAPEIT estimates were significantly higher in participants with a high metabolic liver-risk profile (i.e. diabetes and high blood pressure) (p < 0.005). CAPEIT estimates also distinguished high and low metabolic risk groups with an AUC of 0.756. Together, these findings support the feasibility of a portable multi-organ EIT imaging framework capable of extracting complementary liver and kidney information from a single belt placement.

bioengineering↗

bioRxiv2026

A transition-prone brain state precedes spontaneous behavioral switching

Animals exhibit behavior in the absence of external stimuli or explicit tasks. Is the initiation of such spontaneous behavior shaped by internal brain states in a predictable manner? If so, does it engage specific brain circuits independent of behavioral form? Here, we studied the initiation of uninstructed behaviors of head-fixed mice in two contexts: a virtual burrow and a running wheel. Across both contexts, mice spent most of the time in quiet wakefulness and spontaneously initiated bouts of egress (exiting the burrow), running, or grooming. We employed functional ultrasound imaging (fUS) to record whole-brain activity and to identify whether the initiation of spontaneous behavior could be predicted from hemodynamic signals. We first identified distinct hemodynamic patterns associated with each behavior and subsequently performed time-resolved decoding to predict behavioral transitions from fUS data. We found that whole-brain hemodynamic signals could decode spontaneous egress and running around 10 seconds before their onset, a timescale that cannot be accounted for by preceding behavioral changes alone. Furthermore, we found a network of regions, including the medial septum (MS), that decreased their signal several seconds before the onset of egress and running. Mimicking this decrease by inhibiting neurons in the MS via optogenetics increased the probability of egress, running, and grooming. Through this unbiased approach, our work sheds light on a whole-brain transition-prone state that precedes uninstructed behavior transitions.

neuroscience↗