Faculty Bibliography

It is increasingly important to study the impact of environmental inhalation exposures on human health in natural or man-made disasters in civilian populations. The members of the World Trade Center Environmental Health Center (WTC EHC; WTC Survivors) had complex exposures to environmental disaster from the destruction of WTC towers and can serve to reveal the effects of WTC exposure on the entire spectrum of lung functions. We aimed to investigate the associations between complex WTC exposures and measures of spirometry and oscillometry in WTC Survivors and included 3605 patients enrolled between Oct 1, 2009 and Mar 31, 2018. We performed latent class analysis and identified five latent exposure groups. We applied linear and quantile regressions to estimate the exposure effects on the means and various quantiles of pre-bronchodilator (BD) % predicted forced expiratory volume in one second (FEV₁), forced vital capacity (FVC) and FEV₁/FVC ratio, as well as the resistance at an oscillating frequency of 5 Hz (R₅), frequency dependence of resistance R_5-20, and reactance area (AX). Compared with Group 5, which had low or unknown exposure and was treated as the reference group, Group 1, the local workers with both acute and chronic exposures, had a lower median of % predicted FVC (-3.6; 95% CI: -5.4, -1.7) and higher (more abnormal) measures of AX at 10th quantile (0.77 cmH₂O L^-1 s; 95% CI: 0.41, 1.13) and 25th quantile (0.80 cmH₂O L^-1 s; 95% CI: 0.41, 1.20). Results suggested heterogeneous exposures to the WTC disaster had differential effects on the distributions of lung functions in the WTC Survivors. These findings could provide insights for future investigation of environmental disaster exposures.

Mutations accumulate in the genome of every cell of the body throughout life, causing cancer and other genetic diseases^1-4. Almost all of these mosaic mutations begin as nucleotide mismatches or damage in only one of the two strands of the DNA prior to becoming double-strand mutations if unrepaired or misrepaired⁵. However, current DNA sequencing technologies cannot resolve these initial single-strand events. Here, we developed a single-molecule, long-read sequencing method that achieves single-molecule fidelity for single-base substitutions when present in either one or both strands of the DNA. It also detects single-strand cytosine deamination events, a common type of DNA damage. We profiled 110 samples from diverse tissues, including from individuals with cancer-predisposition syndromes, and define the first single-strand mismatch and damage signatures. We find correspondences between these single-strand signatures and known double-strand mutational signatures, which resolves the identity of the initiating lesions. Tumors deficient in both mismatch repair and replicative polymerase proofreading show distinct single-strand mismatch patterns compared to samples deficient in only polymerase proofreading. In the mitochondrial genome, our findings support a mutagenic mechanism occurring primarily during replication. Since the double-strand DNA mutations interrogated by prior studies are only the endpoint of the mutation process, our approach to detect the initiating single-strand events at single-molecule resolution will enable new studies of how mutations arise in a variety of contexts, especially in cancer and aging.

In recent years, the field of neuroscience has gone through rapid experimental advances and a significant increase in the use of quantitative and computational methods. This growth has created a need for clearer analyses of the theory and modeling approaches used in the field. This issue is particularly complex in neuroscience because the field studies phenomena that cross a wide range of scales and often require consideration at varying degrees of abstraction, from precise biophysical interactions to the computations they implement. We argue that a pragmatic perspective of science, in which descriptive, mechanistic, and normative models and theories each play a distinct role in defining and bridging levels of abstraction, will facilitate neuroscientific practice. This analysis leads to methodological suggestions, including selecting a level of abstraction that is appropriate for a given problem, identifying transfer functions to connect models and data, and the use of models themselves as a form of experiment.

Animals use information about gravity and other destabilizing forces to balance and navigate through their environment. Measuring how brains respond to these forces requires considerable technical knowledge and/or financial resources. We present a simple alternative: Tilt In Place Microscopy (TIPM). TIPM is a low-cost and non-invasive way to measure neural activity following rapid changes in body orientation. Here we used TIPM to study vestibulospinal neurons in larval zebrafish during and immediately after roll tilts. Vestibulospinal neurons responded with reliable increases in activity that varied as a function of ipsilateral tilt amplitude. TIPM differentiated tonic (i.e. sustained tilt) from phasic responses, revealing coarse topography of stimulus sensitivity in the lateral vestibular nucleus. Neuronal variability across repeated sessions was minor relative to trial-to-trial variability, allowing us to use TIPM for longitudinal studies of the same neurons across two developmental timepoints. There, we observed global increases in response strength, and systematic changes in the neural representation of stimulus direction. Our data extend classical characterization of the body tilt representation by vestibulospinal neurons and establish TIPM's utility to study the neural basis of balance, especially in developing animals.Significance Statement:Vestibular sensation influences everything from navigation to interoception. Here we detail a straightforward, validated and nearly-universal approach to image how the nervous system senses and responds to body tilts. We use our new method to replicate and expand upon past findings of tilt sensing by a conserved population of spinal-projecting vestibular neurons. The simplicity and broad compatibility of our approach will democratize the study of the brain's response to destabilization, particularly across development.

In the past two decades, major breakthroughs that improve our understanding of the pathophysiology and therapy of kidney stones (KS) have been lacking. The disease continues to be challenging for patients, physicians, and healthcare systems alike. In this context, epidemiological studies are striving to elucidate the worldwide changes in the patterns and the burden of the disease and identify modifiable risk factors that contribute to the development of kidney stones. Our expanding knowledge of the epidemiology of kidney stones is of paramount importance and largely upgrades the modern management of the disease. In this paper, we review the variables affecting prevalence and incidence, including age, gender, race, ethnicity, occupation, climate, geography, systemic diseases, diabetes, vascular disease, chronic kidney disease, and dietary risk factors relevant to kidney stones.

Brain accumulation of soluble oligomers of the amyloid-β peptide (AβOs) has been implicated in synapse failure and memory impairment in Alzheimer's disease. Here, we initially show that treatment with NUsc1, a single-chain variable fragment antibody (scFv) that selectively targets a subpopulation of AβOs and shows minimal reactivity to Aβ monomers and fibrils, prevents the inhibition of long-term potentiation in hippocampal slices and memory impairment induced by AβOs in mice. As a therapeutic approach for intracerebral antibody delivery, we developed an adeno-associated virus vector to drive neuronal expression of NUsc1 (AAV-NUsc1) within the brain. Transduction by AAV-NUsc1 induced NUsc1 expression and secretion in adult human brain slices, and inhibited AβO binding to neurons and AβO-induced loss of dendritic spine loss in primary rat hippocampal cultures. Treatment of mice with AAV-NUsc1 prevented memory impairment induced by AβOs and, remarkably, reversed memory deficits in aged APPswe/PS1ΔE9 Alzheimer's disease model mice. These results support the feasibility of immunotherapy using viral vector-mediated gene delivery of NUsc1 or other AβO-specific single-chain antibodies as a potential therapeutic approach in Alzheimer's disease.

Recent experiments have revealed that neural population codes in many brain areas continuously change even when animals have fully learned and stably perform their tasks. This representational 'drift' naturally leads to questions about its causes, dynamics and functions. Here we explore the hypothesis that neural representations optimize a representational objective with a degenerate solution space, and noisy synaptic updates drive the network to explore this (near-)optimal space causing representational drift. We illustrate this idea and explore its consequences in simple, biologically plausible Hebbian/anti-Hebbian network models of representation learning. We find that the drifting receptive fields of individual neurons can be characterized by a coordinated random walk, with effective diffusion constants depending on various parameters such as learning rate, noise amplitude and input statistics. Despite such drift, the representational similarity of population codes is stable over time. Our model recapitulates experimental observations in the hippocampus and posterior parietal cortex and makes testable predictions that can be probed in future experiments.

To adapt to their environments, animals learn associations between sensory stimuli and unconditioned stimuli. In invertebrates, olfactory associative learning primarily occurs in the mushroom body, which is segregated into separate compartments. Within each compartment, Kenyon cells (KCs) encoding sparse odor representations project onto mushroom body output neurons (MBONs) whose outputs guide behavior. Associated with each compartment is a dopamine neuron (DAN) that modulates plasticity of the KC-MBON synapses within the compartment. Interestingly, DAN-induced plasticity of the KC-MBON synapse is imbalanced in the sense that it only weakens the synapse and is temporally sparse. We propose a normative mechanistic model of the MBON as a linear discriminant analysis (LDA) classifier that predicts the presence of an unconditioned stimulus (class identity) given a KC odor representation (feature vector). Starting from a principled LDA objective function and under the assumption of temporally sparse DAN activity, we derive an online algorithm which maps onto the mushroom body compartment. Our model accounts for the imbalanced learning at the KC-MBON synapse and makes testable predictions that provide clear contrasts with existing models.

The lateral entorhinal cortex (LEC) provides multisensory information to the hippocampus, directly to the distal dendrites of CA1 pyramidal neurons. LEC neurons perform important functions for episodic memory processing, coding for contextually salient elements of an environment or experience. However, we know little about the functional circuit interactions between the LEC and the hippocampus. We combine functional circuit mapping and computational modeling to examine how long-range glutamatergic LEC projections modulate compartment-specific excitation-inhibition dynamics in hippocampal area CA1. We demonstrate that glutamatergic LEC inputs can drive local dendritic spikes in CA1 pyramidal neurons, aided by the recruitment of a disinhibitory VIP interneuron microcircuit. Our circuit mapping and modeling further reveal that LEC inputs also recruit CCK interneurons that may act as strong suppressors of dendritic spikes. These results highlight a cortically driven GABAergic microcircuit mechanism that gates nonlinear dendritic computations, which may support compartment-specific coding of multisensory contextual features within the hippocampus.

The amygdala has long held the center seat in the neural basis of threat conditioning. However, a rapidly growing literature has elucidated extra-amygdala circuits in this process, highlighting the sensory cortex for its critical role in the mnemonic aspect of the process. While this literature is largely focused on the auditory system, substantial human and rodent findings on the olfactory system have emerged. The unique nature of the olfactory neuroanatomy and its intimate association with emotion compels a review of this recent literature to illuminate its special contribution to threat memory. Here, integrating recent evidence in humans and animal models, we posit that the olfactory (piriform) cortex is a primary and necessary component of the distributed threat memory network, supporting mnemonic ensemble coding of acquired threat. We further highlight the basic circuit architecture of the piriform cortex characterized by distributed, auto-associative connections, which is prime for highly efficient content-addressable memory computing to support threat memory. Given the primordial role of the piriform cortex in cortical evolution and its simple, well-defined circuits, we propose that olfaction can be a model system for understanding (transmodal) sensory cortical mechanisms underlying threat memory.