Faculty Bibliography

PURPOSE OF REVIEW/OBJECTIVE:The 2023 CONVINCE trial demonstrated improved survival with high-dose hemodiafiltration (HDF), prompting discussions about widespread adoption. However, this clinical advancement occurs amid growing awareness of healthcare's environmental impact, particularly dialysis treatments that consume extensive water and energy resources. This review examines the environmental implications of HDF adoption, synthesizing recent evidence on resource consumption and emerging sustainability solutions in the context of the climate crisis facing nephrology. RECENT FINDINGS/RESULTS:Life cycle assessments indicate HDF has a carbon footprint 30-40% higher than conventional hemodialysis, consuming an additional 10 300 L of water per patient annually. However, recent technological innovations show promise: expanded hemodialysis (HDx) using medium cut-off membranes reduces water usage by >20% and energy consumption by >30% compared to HDF while potentially achieving similar clinical outcomes. Water conservation technologies, including reverse osmosis, reject water reuse and reduced dialysate flow protocols, can decrease environmental impact by 30-50% without any difference in patient outcomes. SUMMARY/CONCLUSIONS:The adoption of HDF represents a critical test case for sustainable healthcare innovation. While the potential benefits should not be ignored, technology is not static and, if confirmed, additional sustainability work and comprehensive policy frameworks integrating environmental impact assessments into technology evaluation are urgently needed. The nephrology community must balance clinical excellence with planetary stewardship through technological innovation, resource optimization, and evidence-based environmental guidelines that benefit, not compromise, patient care.

OBJECTIVE:We sought to apply a previously developed transimpedance (TIM) heatmap pattern classification scheme in patients with no known risk factors for cochlear anomalies, in addition to patients implanted in the revision setting, to better understand the incidence of pattern variants, and potential clinical implications. STUDY DESIGN/METHODS:Single-center retrospective review. SETTING/METHODS:Tertiary referral centre. PATIENTS/METHODS:Patients older than 6 months of age who underwent cochlear implantation between June 2020 and June 2024 with normal gross cochlear anatomy and no concern for fibrosis that had intraoperative TIM testing completed. Patients undergoing revision implantation were also included as a separate cohort. INTERVENTION/METHODS:None. MAIN OUTCOME MEASURES/METHODS:The number of patients with normal and variant TIM patterns was evaluated for each cohort. TIM patterns were subsequently compared with the electrode position found on intraoperative x-ray. RESULTS:There were 321 ears that underwent implantation and subsequent intraoperative TIM assessment meeting inclusion criteria. Of these, 310 (96.6%) were in the primary surgery setting, and 11 (3.4%) were in the revision surgical setting. In the primary surgical setting, 86.4% (n=268) of the implants demonstrated a normal TIM heatmap. Compared with the primary surgical setting, where only 45.5% (n=5) of revision surgery TIM heatmaps were interpreted as normal. One patient in the revision setting had a newly identified "double X" pattern corresponding to a normal electrode position on x-ray. CONCLUSIONS:There is a decreased incidence of previously developed TIM heatmap pattern variants in CI recipients with normal gross cochlear anatomy.

PURPOSE OF REVIEW/OBJECTIVE:Medullary sponge kidney (MSK) is a congenital disorder of the distal nephron, characterized by cystic dilatation of the papillary and medullary tubules. It commonly presents with recurrent calcium nephrolithiasis and often, severe, life-altering chronic pain syndromes, often independent of urinary obstruction and of uncertain etiology. Management focuses on stone prevention and symptomatic care, but these measures are frequently inadequate. No studies of management of this pain syndrome in these patients have been performed. There are essentially no studies evaluating renal denervation in MSK specifically, although the technique has been utilized with some benefit in other disorders, underscoring a major therapeutic gap. In this review, we describe patients with MSK and chronic pain syndrome and review the role of renal denervation as a potential therapy. RECENT FINDINGS/RESULTS:Renal denervation may represent a promising strategy for chronic kidney pain syndrome. It could provide pain relief and improve quality of life in affected patients. SUMMARY/CONCLUSIONS:The optimal management strategy for chronic pain in MSK has not been elucidated. Renal denervation has recently been utilized and approved for the management of blood pressure. It could be useful for managing chronic kidney pain in this condition as well.

PURPOSE/OBJECTIVE: METHODS:Like many other MRI simulators, ours discretizes magnetic fields in space. However, we extend the MR signal simulation at each grid point from the 0th-order approximation, which assumes piecewise constant fields, to a 1st-order approximation, which assumes piecewise linear fields. We solve the signal equation by analytically integrating over each grid cube, assuming linear field variations, and then summing over all cubes. We provide analytical integrals for several pulse sequences. RESULTS:The 1st-order approximation captures strongly varying fields and associated intravoxel dephasing more accurately, avoiding severe "ringing" artifacts present in the usual 0th-order simulations. This enables simulations on a much coarser grid, facilitating computational feasibility. CONCLUSION/CONCLUSIONS:The first-order simulator enables the evaluation of unconventional scanner designs with strongly varying magnetic fields.

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.

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.

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.