Faculty Bibliography

A transient ischemic attack is an acute neurologic event caused by focal ischemia affecting the brain, eye, or spinal cord, resolving quickly without infarction on magnetic resonance imaging (MRI) diffusion-weighted imaging (DWI). It is a tissue-based diagnosis, highlighting the need for prompt recognition and risk stratification. Evaluation in the emergency department includes detailed history, risk assessment, neurologic examination, and initial noncontrast computed tomography (CT) to rule out other conditions, with MRI DWI as the gold standard for confirming no infarction. Vascular imaging, echocardiography, electrocardiogram (ECG), and laboratories help identify underlying causes. Central retinal artery occlusion (CRAO) requires urgent diagnosis and ophthalmology consultation to prevent permanent vision loss.

We report a case of an 83-year-old female patient who presented with binocular diplopia associated with left periorbital pain. She was diagnosed with a left pupil-involving third nerve palsy initially believed to be either microvascular or aneurysmal. However, negative vascular neuroimaging and further serologic workup suggested the possibility of neurosyphilis. Her clinical course was significant for persistent periorbital pain and a new seventh nerve palsy, despite syphilis treatment, prompting repeat neuroimaging and lumbar puncture. This case highlights the importance of the clinical history, imaging, CSF studies, and repeated workup in distinguishing between infectious and noninfectious causes of cranial neuropathies.

It is well recognized that many pandemic viruses are associated with neurologic complications, most recently with COVID-19. After the outbreak of the COVID-19 pandemic, neurologic surveillance platforms were implemented to characterize the complications of COVID-19. Surveillance platforms are invaluable in providing timely data, informing clinical practice, and directing future research. Lessons learned from recent neurologic surveillance networks include the importance of global and cross-specialty collaboration. It is critical for future surveillance systems to consider these aspects, as it will also serve to improve representation of low and middle-income countries (LMICs) and communities. Trainees played a critical role in the success of neurologic surveillance networks; as frontline health care workers, they were able to provide timely data collection, and their fresh insights are important for future pandemic surveillance system development. In this article, we review the methods of recent neurologic surveillance networks and discuss their strengths and limitations. We explore the outlook for pandemic surveillance platforms and the crucial role global collaboration plays in ensuring that LMICs are represented. We review the role of trainees in pandemic surveillance networks and discuss how it is vital to encourage their continued involvement to ensure that, as future health care leaders, they are prepared to manage future pandemics effectively.

In eukaryotes, each ribosomal subunit includes a ribosomal protein (RP) that is encoded as a fusion protein with ubiquitin (Ub). In yeast, each Ub-RP fusion requires processing by deubiquitylating enzymes (DUBs) to generate ribosome assembly-competent RPs and contribute to the cellular Ub pool. However, how Ub-RP fusions are processed by DUBs in human cells remains unclear. Here, we discovered that Ub-RPs are substrates of the Ub-fusion degradation (UFD) pathway in human cells via lysine 29 and 48 (K29/K48)-specific ubiquitylation and proteasomal degradation. We identified a pool of DUBs that catalytically process Ub-RPs, as well as DUBs that physically occlude Ub-RP interaction with UFD pathway Ub E3 ligases to prevent their degradation in a non-catalytic manner. Our results suggest that DUBs both process and stabilize Ub-RPs, whereas the UFD pathway regulates levels of Ub-RPs that cannot be fully processed by DUBs to fine-tune protein homeostasis.

OBJECTIVE:To update the 2016 American Headache Society (AHS) guideline on parenteral pharmacologic therapies for the management of migraine attacks in the emergency department (ED). METHODS:We conducted a systematic review and meta-analysis using the same methodology as the 2016 guideline. The original search strategy was repeated and expanded to include studies of nerve blocks and sphenopalatine ganglion (SPG) blocks. We searched Medline, Embase, Cochrane, clinicaltrials.gov, and the World Health Organization (WHO) International Clinical Trials Registry Platform through February 10, 2025. Eligible studies were randomized controlled trials (RCTs) involving adults diagnosed with migraine, treated in the ED with intravenous (IV), intramuscular (IM), subcutaneous (SC), or nerve block (including SPG block) interventions. Two reviewers independently screened titles/abstracts and full texts; a third reviewer resolved disagreements. Data were extracted using a standardized form and verified by a second reviewer. Risk of bias was assessed using the American Academy of Neurology (AAN) criteria. Where applicable, meta-analyses were performed. Efficacy was categorized as highly likely, likely, or possibly effective or ineffective. Clinical recommendations were developed using the AAN guideline development process. RESULTS:The search identified 26 new RCTs evaluating 20 injectable treatments. Of these, 12 were rated class I (low risk of bias), 9 class II, and 4 class III. Prochlorperazine IV, dexketoprofen IV, sumatriptan SC, and greater occipital nerve blocks (GONB) were considered highly likely to be effective based on multiple class I studies. Chlorpromazine IV, metoclopramide IV, eptinezumab IV, ketorolac IV, and supraorbital nerve blocks (SONB) were considered likely effective based on one class I or multiple class II studies. Hydromorphone IV, propofol IV, and paracetamol IV were considered likely ineffective based on class I or multiple class II studies. After review of the evidence and a consensus process, recommendations were made for each intervention. CONCLUSIONS:Prochlorperazine IV and GONB must be offered to eligible adults presenting to the ED with a migraine attack for treatment of headache requiring parenteral therapy (level A - must offer) in those without contraindications, while hydromorphone IV must not be offered (level A - must not offer). Treatments that should be offered when appropriate (level B - should offer) include dexketoprofen IV, ketorolac IV, metoclopramide IV, sumatriptan SC, and SONB. Chlorpromazine IV, dexamethasone IV, and valproate IV may be offered (level C - may offer). Paracetamol IV may not be offered (level C - should not offer). Eptinezumab should be offered (level B) only for patients matching the clinical trial population but is rated level U - no recommendation for an ED-specific population. Additional evidence is needed for caffeine, granisetron, ibuprofen, ketamine, lidocaine, normal saline, propofol, and SPG blocks, all currently rated level U - no recommendation.

BACKGROUND:In many parts of the world including India, the prevalence of autoimmune inflammatory diseases such as neuromyelitis optica spectrum disorders (NMOSD), myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD), and multiple sclerosis (MS) is rising. A diagnosis is often delayed due to insufficient diagnostic tools. Machine learning (ML) models have accurately differentiated eyes of patients with MS from those of healthy controls (HCs) using optical coherence tomography (OCT)-based retinal images. Examining OCT characteristics may allow for early differentiation of these conditions. The objective of this study was to determine feasibility of ML analyses to distinguish between patients with different autoimmune inflammatory diseases, other ocular diseases, and HCs based on OCT measurements of the peripapillary retinal nerve fiber layer (pRNFL), ganglion cell-inner plexiform layer (GCIPL), and inner nuclear layers (INLs). METHODS:Eyes of people with MS (n = 99 patients), NMOSD (n = 40), MOGAD (n = 74), other ocular diseases (OTHER, n = 16), and HCs (n = 54) from the Mangalore Demyelinating Disease Registry were included. Support vector machine (SVM) classification models incorporating age, pRNFL, GCIPL, and INL were performed. Data were split into training (70%) and testing (30%) data and accounted for within-patient correlations. Cross-validation was used in training to choose the best parameters for the SVM model. Accuracy and area under receiver operating characteristic curves (AUROCs) were used to assess model performance. RESULTS:The SVM models distinguished between eyes of patients with each condition (i.e., MOGAD vs NMOSD, NMOSD vs HC, MS vs OTHER, etc) with strong discriminatory power demonstrated from the AUROCs for these comparisons ranging from 0.81 to 1.00. These models also performed with moderate to high accuracy, ranging from 0.66 to 0.81, with the exception of the MS vs NMOSD comparison, which had an accuracy of 0.53. CONCLUSIONS:ML models are useful for distinguishing between autoimmune inflammatory diseases and for distinguishing these from HCs and other ocular diseases based on OCT measures. This study lays the groundwork for future deep learning studies that use analyses of raw OCT images for identifying eyes of patients with such disorders and other etiologies of optic neuropathy.

Parsonage-Turner syndrome (PTS) is a spontaneous neuropathy characterized by severe upper extremity pain and muscle denervation and is considered to be a rare disease that is under-recognized. Quantitative MRI (qMRI) characterizes muscle denervation but has not been previously assessed in a longitudinal PTS cohort. The aims of this study are to prospectively and longitudinally characterize qMRI changes in PTS patients at baseline (< 6 months' symptom onset) and at follow-up timepoints (3, 6, and 12 months), to measure associations against electromyography (EMG) and muscle strength, and to predict muscle strength at follow-up. A total of 49 subjects (age = 47.2 ± 14.0 years, 31 M/18 F) underwent 3-Tesla qMRI with T2-mapping, diffusion-based muscle fiber diameter, volumetry, and fat fraction (FF) mapping. Image segmentation of involved muscles was performed by two raters. Linear regression between qMRI metrics and days from symptom onset (DSO) was performed. Pearson's correlation quantified correlations between qMRI metrics, and Kendall's tau assessed correlations between qMRI and EMG and muscle strength. For predictive modeling of muscle strength, a generalized linear model was used, and the coefficient of determination (r²) was compared for combinations of baseline inputs. Regression detected a mean T2 increase of 0.66 ms/week and a mean muscle fiber diameter decrease of 0.96 μm/week within DSO of 100. Muscle fiber diameter correlated with muscle volume (r = 0.850). T2 correlated with EMG (|τ| = 0.34-0.78) and muscle strength (|τ| = 0.40-0.83) in most muscles that could be analyzed. Muscle fiber diameter was correlated to EMG (|τ| = 0.43-0.72) and muscle strength in some muscles (|τ| = 0.39-0.56). The addition of baseline T2 values improved the prediction of muscle strength at 3-month (from r² = 0.57 to 0.67, with -0.057 to -0.068 muscle grade per ms T2), at 6-month (r² = 0.40-0.59, -0.057 to -0.071 grade per ms), and at 12-month follow-up (r² = 0.40-0.62, -0.053 to -0.080 grade per ms). Muscle qMRI measurements in PTS depict muscle denervation and provide complementary characterization of muscle quality for diagnosis and follow-up assessment.

INTRODUCTION/AIMS/OBJECTIVE:There is a lack of information about startle reflex (SR) in primary lateral sclerosis (PLS). This study examined the presence and prevalence of SR in PLS and compared findings with amyotrophic lateral sclerosis (ALS). METHODS:46 PLS and 54 ALS participants were assessed through structured interviews in this cross-sectional study. Fisher's exact test was used to compare reported SR prevalence. Multivariable linear regression was utilized to study associations between disease group and SR frequency in response to sudden stimuli. RESULTS:SR differed markedly between the two groups, with a higher prevalence in PLS (93.5%) than ALS (20.4%; p < 0.001). Among ALS patients, SR was present in all upper motor neuron (UMN)-predominant cases, which accounted for 54.5% of the SR-positive ALS group, but only 10.4% of probable/definite ALS cases. In SR-positive patients, response frequency to sudden stimuli exceeded 60% in both ALS and PLS, most often triggered by auditory stimuli. Younger age, shorter disease duration, and PLS diagnosis were associated with more frequent SR. DISCUSSION/CONCLUSIONS:SR is significantly more common in PLS than in ALS. Notably, UMN-predominant ALS, although limited in number, showed a higher prevalence of SR (6 out of 6, 100%), indicating that predominant UMN involvement may be a key determinant of SR across both conditions. These hypothesis-generating findings suggest that SR may serve as a novel clinical marker in PLS and UMN-predominant ALS, warranting further validation through prospective studies.

BACKGROUND:Deep medullary veins (DMVs) play important roles within the cerebrovascular network related to brain drainage and clearance. Although they have been previously correlated with brain volume, it is unknown whether their count is specifically correlated with subcortical or cortical volume changes. PURPOSE/OBJECTIVE:This study aims to better understand the relationship between DMVs, subcortical (lateral ventricle to intracranial volume ratio (ICV)) and cortical atrophy (cortical thickness) to identify whether DMVs can be a predictor of volume changes in these regions. METHODS:We performed a retrospective analysis of 332 cognitively healthy subjects previously followed between 2010 and 2019. Imaging and patient charts were analyzed for baseline demographic and clinical characteristics. Patients underwent a standardized cognitive interview and received a magnetic resonance imaging scan to assess DMVs, cortical thickness, lateral ventricle and global gray matter (GM) volumes, white matter lesions (WMLs) and microbleeds. RESULTS:Among 332 patients (62% female, median age 70), lateral ventricle/ICV was significantly related to DMV count (p<0.001). Similarly, sex stratified analyses confirmed that a larger lateral ventricle/ICV ratio, but not cortical thickness or global GM volumes, was associated with fewer DMVs. In the entire group, subcortical atrophy remained a significant predictor of DMVs even after accounting for baseline characteristics, WMLs, microbleeds and total gray matter volume. CONCLUSIONS:In a large cohort of cognitively unaffected people, subcortical, but not cortical, atrophy was significantly correlated with venous health as measured by DMVs. Reduced DMVs are a strong predictor of ventricular enlargement.