Faculty Bibliography

Blood inflammatory marker studies in aging and Alzheimer's disease (AD) research have faced numerous interpretative and methodological challenges that have hindered the field's understanding of the relationship between immune network regulation/dysregulation and aging health factors. We examined how blood inflammation markers directly relate to each other in typical aging, cognitively unimpaired adults using a conditional network analytic modeling approach. We further evaluated how blood inflammation networks relate to key aging risk factors by decomposing the networks into eigenvectors with associated hub proteins and then evaluated the associations of the resulting eigenproteins with demographic information, core biomarkers of AD pathobiology in CSF and blood, and immune health history. Networks of blood inflammation markers showed both divergent and convergent relationships with outcomes, including strong associations between a CXCL5-driven blood inflammation network and age, sex, and CSF Aβ42/Aβ40, and an IL-6- and FGF-21-driven network and sex, CSF Aβ42/Aβ40, and Qalb (CSF-serum albumin ratio). An IFN-gamma- and CXCL9-driven network was associated with both age and CSF Aβ42/Aβ40, whereas blood inflammation networks with hub proteins of CXCL11/CXCL9 and CCL19/CCL4, respectively, were associated solely with sex. Finally, an MCP-3-, MCP-4-, and CXCL6-driven network was associated with cumulative surgical procedure exposures. Despite associations between CSF Aβ42/Aβ40 and multiple networks, plasma Aβ42/Aβ40 was not significantly associated with any blood inflammatory network. Our findings highlight the importance and the challenges of inferring immune pathophysiology from blood-based markers; mirroring the complex pleiotropic biology of inflammation, blood inflammatory markers show associations with multiple demographic and salient health factors in aging adults.

BACKGROUND:Elp1, a subunit of the Elongator complex, is essential for tRNA modification and neuronal development. Mutations in ELP1 underlie familial dysautonomia (FD), a disorder marked by sensory and autonomic neuropathy. While loss of Elp1 disrupts trigeminal ganglion formation and survival, the downstream molecular consequences remain poorly defined. RESULTS:We performed quantitative proteomic profiling of trigeminal ganglia from Elp1 conditional knockout (CKO) and control embryos at E13.5. Across 5650 detected proteins, 25 were significantly up-regulated and 26 down-regulated in Elp1 CKO embryos. EnrichR analysis revealed enrichment of up-regulated proteins in amino acid transport and tRNA aminoacylation pathways, with links to neuromuscular and neuropathic diseases. Down-regulated proteins were associated with RNA modification, cholesterol biosynthesis, and synaptic organization. Validation by immunohistochemistry confirmed decreased expression of the neurotrophic receptor Gfra3 and the neuropeptide Galanin, and increased levels of the chromatin regulator Chd1, in Elp1 CKO embryos relative to controls. CONCLUSIONS:These findings demonstrate that Elp1 loss disrupts metabolic, RNA modification, and neurotrophic signaling pathways in the developing trigeminal ganglion. Proteomic analysis thus provides new insight into the molecular consequences of Elp1 deficiency and highlights candidate mechanisms contributing to sensory neuron vulnerability in FD.

We present a functional magnetic resonance (fMRI) dataset collected as part of an adversarial collaboration aimed at arbitrating between the Global Neuronal Workspace theory (GNWT) and the Integrated Information Theory (IIT) of consciousness. Participants (N = 118) were presented with suprathreshold visual stimuli belonging to four different categories (faces, objects, letters, false fonts) with three orientations (front, left, right view), and three durations (0.5, 1.0, 1.5 seconds). Participants were asked to identify infrequent targets that changed in each block, thereby rendering two categories task-relevant and two task-irrelevant. The simplicity of the experimental design and of the task given to the participants ensures that these data are broadly reusable. Besides testing predictions from other theories of consciousness, these data can be used to examine various aspects of visual processing. The anonymized data were converted to Brain Imaging Data Structure (BIDS), and can be easily accessed through a web platform or an API. The dataset contains quality reports, demographics, behavioral performance, and eye-tracking data. We also provide code for preprocessing and analyzing the data.

OBJECTIVES/OBJECTIVE:To update evidence-based management recommendations for clinicians caring for children (including infants, school-aged children, and adolescents) with sepsis or septic shock. DESIGN/METHODS:A panel of 68 international experts, representing 13 international organizations, as well as six methodologists, was convened. A formal conflict-of-interest policy was developed at the onset of the process and applied throughout. Teleconferences and electronic-based discussion among the chairs, co-chairs, methodologists, and subgroup leads as well as within subgroups, served as an integral part of the guideline development process. METHODS:New priority topics and recommendations from the prior guideline iteration were used to identify Population, Intervention, Control, and Outcomes (PICO) questions likely to have new or updated evidence. We conducted a systematic review to identify the best available evidence, summarized the evidence, and then assessed the quality of evidence using the Grading of Recommendations, Assessment, Development, and Evaluation approach. We used the evidence-to-decision framework to formulate recommendations as strong or conditional, or as a good practice statement. "In our practice," statements were included when evidence was inconclusive to issue a recommendation but the panel felt that some guidance based on practice patterns may be appropriate. RESULTS:The panel provided 61 statements on the management of children with sepsis or septic shock. Overall, five were strong recommendations, 24 were conditional recommendations, and ten were good practice statements. For 22 PICO questions, no recommendations could be made, but, for seven of these, "in our practice" statements were provided. Compared with the 2020 guidelines, 20 recommendations were new, 13 were updated for clarity and/or new evidence, six were reviewed but not changed, and 22 were carried forward based on consensus of the panel that new evidence was not available. Only three recommendations were based on high or moderate certainty of evidence. CONCLUSIONS:Updated management guidelines were issued by a panel of international experts for the best care of children with sepsis or septic shock, acknowledging that most aspects of care continue to have relatively low quality of evidence.

Stroke recovery outcomes vary across individuals, motivating the search for biomarkers that can improve prediction. White matter hyperintensities (WMH) volume is a leading biomarker candidate, with FLAIR MRI typically used for WMH segmentation; however, T1-weighted (T1) MRI is often more available. Therefore, we evaluated the performance of two automated WMH segmentation methods (WMH-SynthSeg, SAMSEG) to determine whether WMH volume can be reliably estimated using T1 alone. We analyzed imaging data from 227 stroke patients across three datasets spanning early subacute to chronic recovery, with gold-standard WMH masks and stroke lesion masks manually traced on available T1 and FLAIR scans. WMH was segmented using T1 only as input to WMH-SynthSeg and SAMSEG, as well as using both T1 and FLAIR as input to SAMSEG, as previously implemented in stroke recovery research. Automated WMH segmentations were compared to the gold-standard WMH mask: spatial accuracy was assessed using Dice similarity index (SI) and cluster-level false negative ratio, while volumetric agreement was assessed using intraclass correlation, Pearson's correlation, and volume ratio. We used linear mixed-effects models to evaluate whether SI was influenced by factors such as WMH volume, stroke lesion volume, WMH contrast, age, sex, and days since stroke, with dataset as a random effect. WMH-SynthSeg using T1-only input produced more accurate and reliable WMH segmentations compared to SAMSEG with T1-only input and performed comparably to SAMSEG using both T1 and FLAIR input. WMH-SynthSeg using T1-only input may be used for WMH volume estimation in stroke recovery research in the absence of multimodal imaging.

BACKGROUND:Transcranial electrical stimulation (TES) has limited spatial focus and depth penetration, constraining its therapeutic efficacy. Intersectional Short-Pulse (ISP) stimulation was developed to overcome these limitations by delivering rapidly switching pulses that can be temporally integrated by neuronal membranes. Here, we aimed to establish the biophysical basis of ISP-induced temporal summation and to test whether this mechanism enables effective brain modulation in vivo. METHODS:We combined finite-element modeling, cadaver measurements (n = 2 human cadavers), and biophysically realistic NEURON simulations to characterize the spatial and temporal properties of ISP-induced electric fields. In vivo whole-cell patch-clamp recordings were performed in the rat somatosensory cortex (female Wistar rat) to test the membrane-level integration of sequential electric field pulses. Functional efficacy was evaluated using closed-loop ISP stimulation in a hippocampal kindling model of temporal lobe epilepsy in male Long-Evans rats (n = 11 animals, >500 induced seizures analyzed across conditions). RESULTS:Here we show that neurons integrate sequential ISP pulses in a non-vectorial, temporally accumulative manner, consistent with membrane-level charge integration rather than extracellular field superposition. ISP and conventional TES simulations produced similar instantaneous field magnitudes, but ISP stimulation resulted in more uniform neuronal excitability across brain depths. Closed-loop ISP stimulation significantly outperformed conventional TES in reducing seizure duration and severity. ISP reduced hippocampal seizure duration by 45% and 35% compared to SHAM stimulation and conventional TES, and significantly reduced motor seizure severity. CONCLUSIONS:ISP stimulation provides a non-invasive neuromodulation approach that enhances deep brain engagement through rapid, temporally structured pulse sequences. These findings demonstrate effective seizure suppression in a rodent model and support the translational potential of ISP for disorders involving pathological neural dynamics.

Head computed tomography (CT) imaging is a widely used imaging modality with multitudes of medical indications, particularly in assessing pathology of the brain, skull and cerebrovascular system. It is commonly used as the first-line imaging in neurologic emergencies given its rapidity of image acquisition, safety, cost and ubiquity. Deep learning models may facilitate detection of a wide range of diseases. However, the scarcity of high-quality labels and annotations, particularly among less common conditions, substantially hinders the development of powerful models. To address this challenge, we introduce FM-HCT, a Foundation Model for Head CT for generalizable disease detection, trained using self-supervised learning. Our approach pretrains a deep learning model on a large, diverse dataset of 361,663 non-contrast 3D head CT scans without the need for manual annotations, enabling the model to learn robust, generalizable features. Our results demonstrate that the self-supervised foundation model substantially improves performance on downstream diagnostic tasks compared to models trained from scratch and previous 3D CT foundation models trained on scarce annotated datasets.