Faculty Bibliography

BACKGROUND:Hypercalciuria is a prominent characteristic in Dent disease type 1 (DD1) and is associated with kidney stones and nephrocalcinosis. The objectives of this study were to assess fibroblast growth factor 23 (FGF23) and 24,25-dihydroxyvitamin D (24,25(OH)2D) in DD1 patients and investigate the effects of phosphate supplementation on urinary calcium excretion. METHODS:Serum and 24-hour urine assessments from adult and pediatric DD1 patients (n=10 adults; n=9 pediatrics) were compared to adult control subjects with a history of idiopathic calcium kidney stones and hypercalciuria (n=9). Adult DD1 patients and control participants completed an oral phosphate supplementation intervention (1g/day x 14 days) with reassessment immediately following intervention. RESULTS:FGF23 was significantly lower in DD1 than in the control cohort (adults, p=0.006) and positively correlated with 24,25(OH)2D across all study cohorts. The concentrations of 24,25(OH)2D were low with conversion ratios (25-hydroxyvitamin D:24,25(OH)2D) exceeding the clinical reference limit for five of 10 adults and six of nine pediatric DD1 patients. The DD1 cohorts were then stratified by the 24,25(OH)2D ratio into "normal" and "low" 24,25(OH)2D. Adult DD1 patients with low 24,25(OH)2D (n=5) had lower FGF23, higher 1,25(OH)2D, greater urine calcium, and greater urine protein. Pediatric stratified data mirrored that in adults with the exception of no difference in serum 1,25(OH)2D. Phosphate supplementation was effective in decreasing urine calcium in both adult DD1 and control adult cohorts. CONCLUSIONS:Clinical measurement of 24,25(OH)2D is a novel and useful analysis for evaluating the severity of calcium and protein dysregulation in DD1. In addition, moderate phosphate supplementation effectively mitigates urine calcium excretion in DD1 adult patients.

Neuronal firing patterns have significant spatiotemporal variability with no agreed-upon theoretical framework. Using a combined experimental and modeling approach, we found that spike interval statistics of excitatory neurons in the mammalian forebrain are dominated by a universal low-rate ("ground state"; GS) mode, with irregular spiking at neuron-specific rates. In contrast, when firing rates are increased during intrinsic network patterns or in response to stimuli, spiking across neurons is temporally coordinated with more regular spiking patterns in a region- and brain-state-specific manner. We demonstrate the generality of this distinction in six forebrain areas and show that the majority of spikes in all regions are emitted in the GS mode, emphasizing its physiological importance. We hypothesize that GS spiking maintains persistent neuronal dynamics.

Active avoidance responses (ARs) are instrumental behaviors that prevent harm. Adaptive ARs may contribute to active coping, whereas maladaptive avoidance habits are implicated in anxiety and obsessive-compulsive disorders. The AR learning mechanism has remained elusive, as successful avoidance trials produce no obvious reinforcer. We used a novel outcome-devaluation procedure in rats to show that ARs are positively reinforced by response-produced feedback cues that develop into safety signals during training. Males were sensitive to feedback devaluation after moderate training, but not overtraining, consistent with a transition from goal-directed to habitual avoidance. Using chemogenetics and feedback devaluation, we also show that goal-directed vs. habitual ARs depend on dorsomedial vs. dorsolateral striatum, suggesting a significant overlap between the mechanisms of avoidance and rewarded instrumental behavior. Females were insensitive to feedbackdevaluation due to a remarkable context-dependence of counterconditioning. However, degrading the contingency between avoidance and feedback suggests that both sexes rely on safety signals to perform goal-directed ARs.

Adult neurogenesis in the subgranular zone (SGZ) has been implicated in cognitive and affective functions. The role of neuroinflammation and reactive microglia in SGZ neurogenesis is not well understood. TGF-β signaling is critical to maintaining microglia homeostasis in the adult brain. To investigate the role of microglia in SGZ neurogenesis, using microglia-specific inducible knockout (iKO) mice for TGF-β1 ligand or receptor (Alk5 or Tgfbr2), here we show that TGF-β-deficient microglia increase adult neurogenesis in the SGZ, accompanied by altered anxiety-like behavior in KO mice. Single-cell RNAseq (ScRNAseq) analysis shows decreased PTEN signaling, and immunohistochemistry shows increased mTOR activity in DCX+ newly born neuroblasts at the SGZ in iKO mice. Inhibition of mTOR signaling by rapamycin reverses the heightened SGZ neurogenesis in iKO mice. This study reveals the role of microglia in regulating hippocampal adult neurogenesis via the PTEN-mTOR pathway and its potential implications for behavioral and affective functions.

Animals produce diverse motor actions that enable expression of context-appropriate behaviors. Neuromodulators facilitate behavioral flexibility by altering the output of neural circuits. Discrete populations of serotonergic (5-HT) neurons target circuits in the brainstem and spinal cord, but their roles in motor behavior are unclear. Here, we define the pre- and post-synaptic organization of spinal-projecting serotonergic neurons in mice and identify a role in locomotor control. While forebrain-targeting 5-HT neurons decrease their activity during locomotion, spinal-projecting neurons increase their activity in a context-dependent manner. Optogenetic activation of ventrally projecting 5-HT neurons does not initiate movement, but rather enhances the speed and duration of ongoing locomotion. Serotonergic neurons can influence motor output beyond periods of increased activity, indicating that neuromodulators can act over extended timescales. These findings indicate that the descending serotonergic system potentiates locomotor output and demonstrate a role for serotonergic neurons in modulating the temporal dynamics of motor circuits.

The ability to quickly learn and generalize is one of the brain's most impressive feats and recreating it remains a major challenge for modern artificial intelligence research. One of the most mysterious one-shot learning abilities displayed by humans is one-shot perceptual learning, whereby a single viewing experience drastically alters visual perception in a long-lasting manner. Where in the brain one-shot perceptual learning occurs and what mechanisms support it remain enigmatic. Combining psychophysics, 7 T fMRI, and intracranial recordings, we identify the high-level visual cortex as the most likely neural substrate wherein neural plasticity supports one-shot perceptual learning. We further develop a deep neural network model incorporating top-down feedback into a vision transformer, which recapitulates and predicts human behavior. The prior knowledge learnt by this model is highly similar to the neural code in the human high-level visual cortex. These results reveal the neurocomputational mechanisms underlying one-shot perceptual learning in humans.

OBJECTIVES/OBJECTIVE:Despite its high negative predictive value (NPV) for clinically significant prostate cancer (csPCa), MRI suffers from a substantial number of false positives, especially for intermediate-risk cases. In this work, we determine whether a deep learning model trained with PI-RADS-guided representation learning can disambiguate the PI-RADS 3 classification, detect csPCa from bi-parametric prostate MR images, and avoid unnecessary benign biopsies. MATERIALS AND METHODS/METHODS:This study included 28,263 MR examinations and radiology reports from 21,938 men imaged for known or suspected prostate cancer between 2015 and 2023 at our institution (21 imaging locations with 34 readers), with 6352 subsequent biopsies. We trained a deep learning model, a representation learner (RL), to learn how radiologists interpret conventionally acquired T2-weighted and diffusion-weighted MR images, using exams in which the radiologists are confident in their risk assessments (PI-RADS 1 and 2 for the absence of csPCa vs. PI-RADS 4 and 5 for the presence of csPCa, n=21,465). We then trained biopsy-decision models to detect csPCa (Gleason score ≥7) using these learned image representations, and compared them to the performance of radiologists, and of models trained on other clinical variables (age, prostate volume, PSA, and PSA density) for treatment-naïve test cohorts consisting of only PI-RADS 3 (n=253, csPCa=103) and all PI-RADS (n=531, csPCa=300) cases. RESULTS:On the 2 test cohorts (PI-RADS-3-only, all-PI-RADS), RL-based biopsy-decision models consistently yielded higher AUCs in detecting csPCa (AUC=0.73 [0.66, 0.79], 0.88 [0.85, 0.91]) compared with radiologists (equivocal, AUC=0.79 [0.75, 0.83]) and the clinical model (AUCs=0.69 [0.62, 0.75], 0.78 [0.74, 0.82]). In the PIRADS-3-only cohort, all of whom would be biopsied using our institution's standard of care, the RL decision model avoided 41% (62/150) of benign biopsies compared with the clinical model (26%, P<0.001), and improved biopsy yield by 10% compared with the PI-RADS ≥3 decision strategy (0.50 vs. 0.40). Furthermore, on the all-PI-RADS cohort, RL decision model avoided 27% of additional benign biopsies (138/231) compared to radiologists (33%, P<0.001) with comparable sensitivity (93% vs. 92%), higher NPV (0.87 vs. 0.77), and biopsy yield (0.75 vs. 0.64). The combination of clinical and RL decision models further avoided benign biopsies (46% in PI-RADS-3-only and 62% in all-PI-RADS) while improving NPV (0.82, 0.88) and biopsy yields (0.52, 0.76) across the 2 test cohorts. CONCLUSIONS:Our PI-RADS-guided deep learning RL model learns summary representations from bi-parametric prostate MR images that can provide additional information to disambiguate intermediate-risk PI-RADS 3 assessments. The resulting RL-based biopsy decision models also outperformed radiologists in avoiding benign biopsies while maintaining comparable sensitivity to csPCa for the all-PI-RADS cohort. Such AI models can easily be integrated into clinical practice to supplement radiologists' reads in general and improve biopsy yield for any equivocal decisions.