Faculty Bibliography

The value of preclinical diffusion MRI (dMRI) is substantial. While dMRI enables in vivo non-invasive characterization of tissue, ex vivo dMRI is increasingly being used to probe tissue microstructure and brain connectivity. Ex vivo dMRI has several experimental advantages including higher SNR and spatial resolution compared to in vivo studies, and enabling more advanced diffusion contrasts for improved microstructure and connectivity characterization. Another major advantage of ex vivo dMRI is the direct comparison with histological data, as a crucial methodological validation. However, there are a number of considerations that must be made when performing ex vivo experiments. The steps from tissue preparation, image acquisition and processing, and interpretation of results are complex, with many decisions that not only differ dramatically from in vivo imaging of small animals, but ultimately affect what questions can be answered using the data. This work represents "Part 2" of a three-part series of recommendations and considerations for preclinical dMRI. We describe best practices for dMRI of ex vivo tissue, with a focus on the value that ex vivo imaging adds to the field of dMRI and considerations in ex vivo image acquisition. We first give general considerations and foundational knowledge that must be considered when designing experiments. We briefly describe differences in specimens and models and discuss why some may be more or less appropriate for different studies. We then give guidelines for ex vivo protocols, including tissue fixation, sample preparation, and MR scanning. In each section, we attempt to provide guidelines and recommendations, but also highlight areas for which no guidelines exist (and why), and where future work should lie. An overarching goal herein is to enhance the rigor and reproducibility of ex vivo dMRI acquisitions and analyses, and thereby advance biomedical knowledge.

BACKGROUND:Despite evidence supporting the efficacy of culturally tailored interventions in reducing stigma, such approaches are lacking for women living with HIV/AIDS (WLWHAs) in China. We conducted this study to determine the efficacy of the culturally tailored Helping Overcome Perceived Stigma (HOPES) intervention in reducing perceived stigma among WLWHAs in China. METHODS:A single-blinded, two-arm parallel-group randomized clinical trial was conducted from 2023 to 2024 in South and Southwest China. WLWHAs from four hospitals were assigned using a WeChat-embedded randomization application to the control group (usual care) or the HOPES intervention. Data analysts remained blinded. Interventions were conducted virtually using Leave No One Behind (LNOB) platform for 3 months. The primary outcome, perceived stigma score, was assessed at baseline, immediately after the intervention and at 3 months post-intervention using 7 items from the HIV/AIDS Stigma Experience Questionnaire (HASEQ), with data analyzed through repeated measures analysis. RESULTS:Of 136 WLWHAs screened, we randomized 101 WLWHAs (50 HOPES; 51 controls). The HOPES group demonstrated a statistically significant reduction in perceived stigma scores immediately after the intervention (-3.86 points, 95 % CI: 5.34 to -2.38, P < .001) and at three months post-intervention (-5.83 points, 95 % CI: 7.20 to -4.47, P < .001) compared to the control group. CONCLUSION/CONCLUSIONS:The findings demonstrate HOPES' efficacy in reducing perceived stigma in WLWHA. However, the clinical significance of these changes needs further investigation. Future research should focus on defining meaningful patient-reported thresholds, assessing long-term impact, and optimizing delivery methods.

UNLABELLED:Research supports an association between diet and health, and emerging evidence suggests that diet is associated with neuropsychiatric symptoms. However, no human study has examined an anti-inflammatory diet across rigorously defined psychiatric diagnoses and its associations with symptom severity and cognition. As inflammation is implicated in mental illness, we investigated adherence to the Mediterranean diet (MD), an anti-inflammatory diet, and the standard American diet (SAD), and examined cross-sectional relationships with psychiatric symptoms and cognition. METHOD/METHODS:Participants included 54 individuals with psychotic disorders, 30 with non-psychosis affective disorders and 40 healthy controls. Participants underwent diagnostic interviews, PANSS symptom ratings, and MATRICS cognitive assessments. The self-report GBAQ was used to assess adherence to the MD versus SAD. RESULTS:The psychosis group was significantly more likely to consume the SAD than healthy controls (p = 0.007), with MD adherence predicting better working memory (r = 0.461, p < 0.001). In the non-psychosis affective disorders group, MD adherence predicted slower processing speed (r = -0.376, p = 0.049). In the non-psychosis affective disorders group, MD predicted reduced PANSS General Psychopathology scale (r = -0.449, p = 0.013), as well as the Activation (r = -0.362, p = 0.049), and Dysphoric Mood factors (r = -0.403, p = 0.027). DISCUSSION/CONCLUSIONS:This first-of-its kind study identified poor dietary choices in persons with psychosis, showing significantly lower symptoms and better cognition in association with the MD in transdiagnostic analyses. It supports the study of dietary interventions for prevention and treatment of psychiatric conditions.

The structure of compound eyes in arthropods has been the subject of many studies, revealing important biological principles. Until recently, these studies were constrained by the two-dimensional nature of available ultrastructural data. By taking advantage of the novel three-dimensional ultrastructural dataset obtained using volume electron microscopy, we present the first cellular-level reconstruction of the whole compound eye of an insect, the miniaturized parasitoid wasp Megaphragma viggianii. The compound eye of the female M. viggianii consists of 29 ommatidia and contains 478 cells. Despite the almost anucleate brain, all cells of the compound eye contain nuclei. As in larger insects, the dorsal rim area of the eye in M. viggianii contains ommatidia that are believed to be specialized in polarized light detection as reflected in their corneal and retinal morphology. We report the presence of three 'ectopic' photoreceptors. Our results offer new insights into the miniaturization of compound eyes and scaling of sensory organs in general.

This study investigated the potential of combining multiple MR parameters to enhance the characterization of myelin in the mouse brain. We collected ex vivo multiparametric MR data at 7 T from control and Gli1^-/- mice; the latter exhibit enhanced myelination at Postnatal Day 10 (P10) in the corpus callosum and cortex. The MR data included relaxivity, magnetization transfer, and diffusion measurements, each targeting distinct myelin properties. This analysis was followed by and compared to myelin basic protein (MBP) staining of the same samples. Although a majority of the MR parameters included in this study showed significant differences in the corpus callosum between the control and Gli1^-/- mice, only T₂, T₁/T₂, and radial diffusivity (RD) demonstrated a significant correlation with MBP values. Based on data from the corpus callosum, partial least square regression suggested that combining T₂, T₁/T₂, and inhomogeneous magnetization transfer ratio could explain approximately 80% of the variance in the MBP values. Myelin predictions based on these three parameters yielded stronger correlations with the MBP values in the P10 mouse brain corpus callosum than any single MR parameter. In the motor cortex, combining T₂, T₁/T₂, and radial kurtosis could explain over 90% of the variance in the MBP values at P10. This study demonstrates the utility of multiparametric MRI in improving the detection of myelin changes in the mouse brain.

Cerebellar dysfunction leads to postural instability. Recent work in freely moving rodents has transformed investigations of cerebellar contributions to posture. However, the combined complexity of terrestrial locomotion and the rodent cerebellum motivate new approaches to perturb cerebellar function in simpler vertebrates. Here, we adapted a validated chemogenetic tool (TRPV1/capsaicin) to describe the role of Purkinje cells - the output neurons of the cerebellar cortex - as larval zebrafish swam freely in depth. We achieved both bidirectional control (activation and ablation) of Purkinje cells while performing quantitative high-throughput assessment of posture and locomotion. Activation modified postural control in the pitch (nose-up/nose-down) axis. Similarly, ablations disrupted pitch-axis posture and fin-body coordination responsible for climbs. Postural disruption was more widespread in older larvae, offering a window into emergent roles for the developing cerebellum in the control of posture. Finally, we found that activity in Purkinje cells could individually and collectively encode tilt direction, a key feature of postural control neurons. Our findings delineate an expected role for the cerebellum in postural control and vestibular sensation in larval zebrafish, establishing the validity of TRPV1/capsaicin-mediated perturbations in a simple, genetically tractable vertebrate. Moreover, by comparing the contributions of Purkinje cell ablations to posture in time, we uncover signatures of emerging cerebellar control of posture across early development. This work takes a major step towards understanding an ancestral role of the cerebellum in regulating postural maturation.

Noise is a fundamental problem for information processing in neural systems. In decision-making, noise is thought to cause stochastic errors in choice. However, little is known about how noise arising from different sources may contribute differently to value coding and choice behaviors. Here, we examine how noise arising early versus late in the decision process differentially impacts context-dependent choice behavior. We find in model simulations that under early noise, contextual information enhances choice accuracy, while under late noise, context degrades choice accuracy. Furthermore, we verify these opposing predictions in experimental human choice behavior. Manipulating early and late noise - by inducing uncertainty in option values and controlling time pressure - produces dissociable positive and negative context effects. These findings reconcile controversial experimental findings in the literature, suggesting a unified mechanism for context-dependent choice. More broadly, these findings highlight how different sources of noise can interact with neural computations to differentially modulate behavior.

BACKGROUND:MRI plays a critical role in prostate cancer (PCa) detection and management. Bi-parametric MRI (bpMRI) offers a faster, contrast-free alternative to multi-parametric MRI (mpMRI). Routine use of mpMRI for all patients may not be necessary, and a tailored imaging approach (bpMRI or mpMRI) based on individual risk might optimize resource utilization. PURPOSE/OBJECTIVE:To develop and evaluate a deep learning (DL) model for classifying clinically significant PCa (csPCa) using bpMRI and to assess its potential for optimizing MRI protocol selection by recommending the additional sequences of mpMRI only when beneficial. STUDY TYPE/METHODS:Retrospective and prospective. POPULATION/METHODS:The DL model was trained and validated on 26,129 prostate MRI studies. A retrospective cohort of 151 patients (mean age 65 ± 8) with ground-truth verification from biopsy, prostatectomy, or long-term follow-up, alongside a prospective cohort of 142 treatment-naïve patients (mean age 65 ± 9) undergoing bpMRI, was evaluated. FIELD STRENGTH/SEQUENCE/UNASSIGNED:3 T, Turbo-spin echo T2-weighted imaging (T2WI) and single shot EPI diffusion-weighted imaging (DWI). ASSESSMENT/RESULTS:The DL model, based on a 3D ResNet-50 architecture, classified csPCa using PI-RADS ≥ 3 and Gleason ≥ 7 as outcome measures. The model was evaluated on a prospective cohort labeled by consensus of three radiologists and a retrospective cohort with ground truth verification based on biopsy or long-term follow-up. Real-time inference was tested on an automated MRI workflow, providing classification results directly at the scanner. STATISTICAL TESTS/METHODS:AUROC with 95% confidence intervals (CI) was used to evaluate model performance. RESULTS:In the prospective cohort, the model achieved an AUC of 0.83 (95% CI: 0.77-0.89) for PI-RADS ≥ 3 classification, with 93% sensitivity and 54% specificity. In the retrospective cohort, the model achieved an AUC of 0.86 (95% CI: 0.80-0.91) for Gleason ≥ 7 classification, with 93% sensitivity and 62% specificity. Real-time implementation demonstrated a processing latency of 14-16 s for protocol recommendations. DATA CONCLUSION/CONCLUSIONS:The proposed DL model identifies csPCa using bpMRI and integrates it into clinical workflows. EVIDENCE LEVEL/METHODS:1. TECHNICAL EFFICACY/UNASSIGNED:Stage 2.

In order to forage for food, many animals regulate not only specific limb movements but the statistics of locomotor behavior, switching between long-range dispersal and local search depending on resource availability. How premotor circuits regulate locomotor statistics is not clear. Here, we analyze and model locomotor statistics and their modulation by attractive food odor in walking Drosophila. Food odor evokes three motor regimes in flies: baseline walking, upwind running during odor, and search behavior following odor loss. During search, we find that flies adopt higher angular velocities and slower ground speeds and turn for longer periods in the same direction. We further find that flies adopt periods of different mean ground speed and that these state changes influence the length of odor-evoked runs. We next developed a simple model of neural locomotor control that suggests that contralateral inhibition plays a key role in regulating the statistical features of locomotion. As the fly connectome predicts decussating inhibitory neurons in the premotor lateral accessory lobe (LAL), we gained genetic access to a subset of these neurons and tested their effects on behavior. We identified one population whose activation induces all three signature of local search and that regulates angular velocity at odor offset. We identified a second population, including a single LAL neuron pair, that bidirectionally regulates ground speed. Together, our work develops a biologically plausible computational architecture that captures the statistical features of fly locomotion across behavioral states and identifies neural substrates of these computations.

Fanconi anemia (FA) is a rare genetic disease characterized by loss-of-function variants in any of the 22 previously identified genes (FANCA-FANCW) that encode proteins participating in the repair of DNA interstrand crosslinks (ICLs). Patient phenotypes are variable, but may include developmental abnormalities, early onset pancytopenia, and predisposition to hematologic and solid tumors. Here, we describe two unrelated families with multiple pregnancy losses and offspring presenting with severe developmental and hematologic abnormalities leading to death in utero or in early life. Homozygous loss-of-function variants in FAAP100 were identified in affected children of both families. The FAAP100 protein associates with FANCB and FANCL, the E3 ubiquitin ligase responsible for the monoubiquitination of FANCD2 and FANCI, which is necessary for FA pathway function. Patient-derived cells exhibited phenotypes consistent with FA. Expression of the wild-type FAAP100 cDNA, but not the patient-derived variants, rescued the observed cellular phenotypes. This establishes FAAP100 deficiency as a cause of Fanconi anemia, with FAAP100 gaining an alias as FANCX. The extensive developmental malformations of individuals with FAAP100 loss-of-function variants are among the most severe across previously described FA phenotypes, indicating that the FA pathway is essential for human development.