Faculty Bibliography

Tuberculosis is the leading infectious cause of death globally and extra-pulmonary disease occurs in 15% of incident cases annually. Tuberculous meningitis (TBM) is arguably the most lethal form of tuberculosis and requires prompt diagnosis and initiation of treatment to prevent death and serious neurological disability. The development of rapid diagnostic tests using polymerase chain reaction (PCR) technology for the detection of Mycobacterium tuberculosis (MTB), including the World Health Organization (WHO) - endorsed Xpert MTB/RIF Ultra assay, has allowed earlier definite diagnosis of TBM than conventional culture methods which usually take two weeks or longer for positive identification of MTB. Detection of MTB in cerebrospinal fluid (CSF) using PCR assays requires special attention to the collection, handling, and processing of CSF. Herein we present best practices guidance to maximize the detection rate of MTB in CSF using Xpert MTB/RIF Ultra.

Real-time processing and manipulation of biological signals require bioelectronic devices with integrated components capable of signal amplification, processing, and stimulation. Transistors form the backbone of such circuits, but numerous criteria must be met for efficient and safe operation in biological environments. Here, we introduce an internal ion-gated organic electrochemical transistor (IGT) that uses contained mobile ions within the conducting polymer channel to permit both volumetric capacitance and shortened ionic transit time. The IGT has high transconductance, fast speed, and can be independently gated to create scalable conformable integrated circuits. We demonstrate the ability of the IGT to provide a miniaturized, comfortable interface with human skin using local amplification to record high-quality brain neurophysiological activity. The IGT is an effective transistor architecture for enabling integrated, real-time sensing and stimulation of signals from living organisms.

The T2-FLAIR mismatch sign, in which a low-grade glioma is hyperintense on T2-weighted MR and centrally hypointense on T2-weighted FLAIR MR, has been reported as 100% specific for IDH-mutant astrocytomas in several series. We report several cases of "false positive" T2-FLAIR mismatch sign occurring outside the context of IDH-mutant astrocytomas, predominantly in children or young adults with pediatric-type gliomas. These results suggest caution in the interpretation of the T2-FLAIR mismatch sign in the pediatric glioma population.

A striking observation among veterans returning from the recent conflicts in Iraq and Afghanistan has been the co-occurrence of blast-related mild traumatic brain injury (mTBI) and post-traumatic stress disorder (PTSD). PTSD and mTBI might coexist due to additive effects of independent psychological and physical traumas experienced in a war zone. Alternatively blast injury might induce PTSD-related traits or damage brain structures that mediate responses to psychological stressors, increasing the likelihood that PTSD will develop following a subsequent psychological stressor. Rats exposed to repetitive low-level blasts consisting of three 74.5 kilopascal exposures delivered once daily for three consecutive days develop a variety of anxiety and PTSD-related behavioral traits that are present for at least 9 months after blast exposure. A single predator scent challenge delivered 8 months after the last blast exposure induces additional anxiety-related changes that are still present 45 days later. Because the blast injuries occur under general anesthesia, it appears that blast exposure in the absence of a psychological stressor can induce chronic PTSD-related traits. The reaction to a predator scent challenge delivered many months after blast exposure suggests that blast exposure in addition sensitizes the brain to react abnormally to subsequent psychological stressors. The development of PTSD-behavioral related traits in the absence of a psychological stressor suggests the existence of blast-induced "PTSD". Findings that PTSD-related behavioral traits can be reversed by BCI-838, a group II metabotropic glutamate receptor antagonist offers insight into pathogenesis and possible treatment options for blast-related brain injury.

OBJECTIVE:Behavior is encoded across multiple spatiotemporal scales of brain activity. Modern technology can simultaneously record various scales, from spiking of individual neurons to large neural populations measured with field activity. This capability necessitates developing multiscale modeling and decoding algorithms for spike-field activity, which is challenging because of the fundamental differences in statistical characteristics and time-scales of these signals. Spikes are binary-valued with a millisecond time-scale while fields are continuous-valued with slower time-scales. APPROACH/METHODS:We develop a multiscale encoding model, adaptive learning algorithm, and decoder that explicitly incorporate the different statistical profiles and time-scales of spikes and fields. The multiscale model consists of combined point process and Gaussian process likelihood functions. The multiscale filter (MSF) for decoding runs at the millisecond time-scale of spikes while adding information from fields at their slower time-scales. The adaptive algorithm learns all spike-field multiscale model parameters simultaneously, in real time, and at their different time-scales. MAIN RESULTS/RESULTS:We validated the multiscale framework within motor tasks using both closed-loop brain-machine interface (BMI) simulations and non-human primate (NHP) spike and local field potential (LFP) motor cortical activity during a naturalistic 3D reach task. Our closed-loop simulations show that the MSF can add information across scales and that the adaptive MSF can accurately learn all parameters in real time. We also decoded the seven joint angular trajectories of the NHP arm using spike-LFP activity. These data showed that the MSF outperformed single-scale decoding, this improvement was due to the addition of information across scales rather than the dominance of one scale and was largest in the low-information regime, and the improvement was similar regardless of the degree of overlap between spike and LFP channels. SIGNIFICANCE/CONCLUSIONS:This multiscale framework provides a tool to study encoding across scales and may help enhance future neurotechnologies such as motor BMIs.

Neuropsychiatric symptoms (NPS) are common in Alzheimer's disease (AD)-associated neurodegeneration. However, NPS lack a consistent relationship with AD pathology. It is unknown whether any common neural circuits can link these clinically disparate while mechanistically similar features with AD pathology. Here, we explored the neural circuits of NPS in AD-associated neurodegeneration using multivariate pattern analysis (MVPA) of resting-state functional MRI data. Data from 98 subjects (70 amnestic mild cognitive impairment and 28 AD subjects) were obtained. The top 10 regions differentiating symptom presence across NPS were identified, which were mostly the fronto-limbic regions (medial prefrontal cortex, caudate, etc.). These 10 regions' functional connectivity classified symptomatic subjects across individual NPS at 69.46-81.27%, and predicted multiple NPS (indexed by Neuropsychiatric Symptom Questionnaire-Inventory) and AD pathology (indexed by baseline and change of beta-amyloid/pTau ratio) all above 70%. Our findings suggest a fronto-limbic dominated neural circuit that links multiple NPS and AD pathology. With further examination of the structural and pathological changes within the circuit, the circuit may shed light on linking behavioral disturbances with AD-associated neurodegeneration.

BACKGROUND:The phenotypic presentation of multiple sclerosis (MS) may predict long-term outcomes and little is known about factors contributing to heterogeneity at MS onset. Given temporality, it is likely MS risk factors also influence presentation of the disease near onset. METHODS:Using a retrospective cross-sectional study of MS cases, we investigated: age of onset (AOO), number of impaired functional domains (NIFDs), time to second relapse (TT2R), and early relapse activity (ERA). Machine learning variable selection was applied to epidemiologic data for each outcome, followed by multivariable regression models. The models were further adjusted for HLA-DRB1*15:01 carrier status and a MS genetic risk score (GRS). The TT2R and ERA analyses were restricted to relapsing remitting MS cases. RESULTS:HLA-DRB1*15:01, GRS, and smoking were associated with earlier AOO. Cases who were male, obese, had lower education, or had primary progressive MS were older at onset. For NIFDs, those with relapsing remitting MS and of lower SES had increased NIFDs. Among relapsing remitting cases, those who were older at onset, obese, and had polyfocal presentation had shorter TT2R, while ERA was greater among those younger at onset and who were obese. CONCLUSION/CONCLUSIONS:Individual characteristics including age, genetic profiles, obesity, and smoking status contribute to heterogeneity in disease presentation and modulate early disease course evolution.