Faculty Bibliography

Pathogens have evolved to be highly adapted to their natural host. Community-associated methicillin-resistant Staphylococcus aureus USA300, for instance, is a lineage responsible for the epidemic of skin and soft tissue infections (SSTIs) in humans. Owing to its human tropism, mechanisms that enabled the rise of USA300 as a major skin pathogen remain incompletely defined. By leveraging a rodent-adapted strain of S. aureus, we developed a natural model of SSTIs. We found that LukMF', a pore-forming leukocidin homolog to the human-specific LukSF-PV toxin, drives skin pathology in mice. LukMF' lyses neutrophils via the chemokine receptor CCR1, which in turn fuels inflammatory pathology and microbial survival within the infectious nidus. Ablation of CCR1, depletion of neutrophils, or vaccination with LukMF' all protected mice from skin pathology. Thus, these data support epidemiological studies linking leukocidins with human SSTIs and highlight the power of natural models to unearth potential targets to curtail infections.

OBJECTIVE:Evaluate real-world effectiveness, patient-reported outcomes (PROs), and safety/tolerability of brivaracetam in patients (≥16 years) with focal-onset seizures currently receiving ≥ 1 antiseizure medication (ASM), and with historical or current use of levetiracetam, lamotrigine, oxcarbazepine, and/or carbamazepine. METHODS:EP0088 was a 12-month, prospective, observational study of brivaracetam in a clinical practice setting in the US. Primary study outcome was brivaracetam retention at 12 months after brivaracetam initiation. Effect of brivaracetam on patients' perceptions of their health was assessed using Patient-Reported Outcomes Measurement Information System (PROMIS) short forms and Seizure-Related Disability Assessment Scale (SERDAS). Safety outcomes included incidence of treatment-emergent adverse events (TEAEs). RESULTS:254 patients (mean age: 44.3 years; median duration of epilepsy: 17.3 years) received ≥ 1 brivaracetam dose (Safety Set; SS). Patients had a median of 3.0 historical and 2.0 concomitant ASMs (SS). For all patients (SS), including those who dropped out with unknown brivaracetam treatment status, 12-month brivaracetam retention was 57.1 % (n = 145/254); in patients with known brivaracetam treatment status (post hoc analysis), 12-month brivaracetam retention was 72.1 % (n = 145/201). Slight improvements in mean PROMIS T-scores, and improvements in mean SERDAS scores, were seen by month 1.5, and generally maintained up to 12 months (Full Analysis Set). 49.6 % of patients reported ≥ 1 TEAE, 38.2 % had drug-related TEAEs, and 16.1 % discontinued due to TEAEs (SS). CONCLUSIONS:Brivaracetam was effective in patients with difficult-to-control focal-onset seizures; as shown by brivaracetam retention at 12 months. Improvements in PROs were seen early. Brivaracetam was well-tolerated and no new safety signals were observed.

Naturalistic electrocorticography (ECoG) data are a rare but essential resource for studying the brain's linguistic capabilities. ECoG offers high temporal resolution suitable for investigating processes at multiple temporal timescales and frequency bands. It also provides broad spatial coverage, often along critical language areas. Here, we share a dataset of nine ECoG participants with 1,330 electrodes listening to a 30-minute audio podcast. The richness of this naturalistic stimulus can be used for various research questions, from auditory perception to narrative integration. In addition to the neural data, we extracted linguistic features of the stimulus ranging from phonetic information to large language model word embeddings. We use these linguistic features in encoding models that relate stimulus properties to neural activity. Finally, we provide detailed tutorials for preprocessing raw data, extracting stimulus features, and running encoding analyses that can serve as a pedagogical resource or a springboard for new research.

Parkinson's disease (PD) is a neurodegenerative disease characterized by motor and non-motor symptoms that progressively deteriorate and for which there is no disease-modifying pharmacological treatment. Exercise is widely recommended for individuals with PD due to its potential neuroprotective benefits. However, the mechanisms underlying these exercise-induced effects in PD remain poorly understood. Analyzing fluid biomarkers responsive to exercise could offer valuable insights into the mechanisms by which exercise impacts PD and aid in optimizing exercise prescriptions for individuals with PD. This review explores exercise-responsive biomarkers categorized into three key groups-neurotrophic, inflammatory, and neuroendocrine markers. It highlights both well-validated biomarkers and candidates with promising potential. We also highlight key biomarkers linked to PD pathology, such as α-synuclein, and their potential connection to exercise based on current evidence. Comprehensive characterization of these biomarkers will advance our understanding of the biological effects of exercise in PD, enabling mechanism-based and objective measures to evaluate exercise response in future clinical trials and its impact on PD signs and symptoms.

PURPOSE/UNASSIGNED:To investigate the fairness of existing deep models for diabetic retinopathy (DR) detection and introduce an equitable model to reduce group performance disparities. METHODS/UNASSIGNED:We evaluated the performance and fairness of various deep learning models for DR detection using fundus images and optical coherence tomography (OCT) B-scans. A Fair Adaptive Scaling (FAS) module was developed to reduce group disparities. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC), and equity across various groups was assessed by equity-scaled AUC, which accommodated both overall AUC and AUCs of individual groups. RESULTS/UNASSIGNED:Using color fundus images, the integration of FAS with EfficientNet improved the overall AUC and equity-scaled AUC from 0.88 and 0.83 to 0.90 and 0.84 (P < 0.05) by race. AUCs for Asians and Whites increased by 0.05 and 0.03, respectively (P < 0.01). For gender, both metrics improved by 0.01 (P < 0.05). Using DenseNet121 on OCT B-Scans by race, FAS improved the overall AUC and equity-scaled AUC from 0.875 and 0.81 to 0.884 and 0.82, with gains of 0.03 and 0.02 for Asians and Blacks (P < 0.01). For gender, DenseNet121's metrics rose by 0.04 and 0.03, with gains of 0.05 and 0.04 for females and males (P < 0.01). CONCLUSIONS/UNASSIGNED:Deep learning models demonstrate varying accuracies across different groups in DR detection. FAS improves equity and accuracy of deep learning models. TRANSLATIONAL RELEVANCE/UNASSIGNED:The proposed deep learning model has a potential to improve both model performance and equity of DR detection.

INTRODUCTION/UNASSIGNED:. AREAS COVERED/UNASSIGNED:The authors searched PubMed, GoogleScholar, and clinicaltrials.gov for all types of studies regarding the genetic basis of FD and recent advances in the development of disease-modifying therapies, including publications available through November 2025. EXPERT OPINION/UNASSIGNED:Experimental evidence indicates that boosting ELP1 protein levels could halt disease progression. Several small molecules and genetic therapies have shown the ability to enhance wild-type ELP1 mRNA and protein expression in animal models. An ongoing N-of-1 clinical trial is evaluating the intrathecal administration of an antisense oligonucleotide (ASO) designed to correct the splicing defect in an individual with FD. Combining small molecules, such as optimized potent oral kinetin derivatives, with intrathecal antisense oligonucleotides (ASOs) and intravitreal gene therapy using viral vectors presents a synergistic therapeutic approach to elevate ELP1 levels. Assessing the efficacy and safety of these targeted strategies will require innovative, well-designed clinical trials.

OBJECTIVE:A growing body of evidence indicates a strong genetic overlap between developmental and epileptic encephalopathies (DEEs) and movement disorders. De novo loss-of-function variants in NUS1 have been recently identified in DEE cases. Herein, we report a large cohort of cases with pathogenic NUS1 variants and describe their clinical presentation and the details of the associated epilepsy and movement disorders. METHODS:Cases with NUS1-related disorders were identified through a multicentric international collaboration made possible by the GeneMatcher platform. Clinical data were acquired through retrospective case-note review. RESULTS:We identified 41 subjects carrying 38 different pathogenic or likely pathogenic heterozygous NUS1 variants. The majority of cases displayed developmental delays and intellectual disability of variable severity. Epilepsy was present in 68.3% of cases (28/41) with onset typically in early childhood. Strikingly, 87.8% of cases (36/41) presented with movement disorders and for 13 of these cases the movement disorder was not accompanied by epilepsy. The phenomenology of the movement disorders was complex with myoclonus observed in 68.3% of cases (28/41), either in isolation or in combination with dystonia, ataxia, and/or parkinsonism. Seven cases that otherwise did not have prominent movement disorders had mild incoordination and intention tremor, suggestive of cerebellar dysfunction. There was no observed genotype-phenotype correlation, suggesting that other genetic or acquired factors impact the clinical presentation. INTERPRETATION/CONCLUSIONS:Heterozygous NUS1 pathogenic variants cause a complex neurological disorder, variably featuring developmental and epileptic encephalopathies and a broad spectrum of movement disorders, which represent the major source of neurological disability for most cases. ANN NEUROL 2025.

Almost all individuals with Down Syndrome (DS) develop Alzheimer's disease (AD) by mid to late life. However, the degree to which AD in DS shares pathological changes with sporadic late-onset AD (LOAD) and autosomal dominant AD (ADAD) beyond core AD biomarkers such as amyloid-β (Aβ) and tau is unknown. Here, we used proteomics of cerebrospinal fluid from individuals with DS (n = 229) in the Down Alzheimer Barcelona Neuroimaging Initiative (DABNI) cohort to assess the evolution of AD pathophysiology from asymptomatic to dementia stages and compared the proteomic biomarker changes in DS to those observed in LOAD and ADAD. Although many proteomic alterations were shared across DS, LOAD, and ADAD, DS demonstrated more severe changes in immune-related proteins, extracellular matrix pathways, and plasma proteins likely related to blood-brain barrier dysfunction compared to LOAD. These changes were present in young adults with DS prior to the onset of Aβ or tau pathology, suggesting they are associated with trisomy 21 and may serve as risk factors for DSAD. DSAD showed an earlier increase in markers of axonal and white matter pathology and earlier changes in markers potentially associated with cerebral amyloid angiopathy compared to ADAD. The unique features of DSAD may have important implications for treatment strategies in this population.

BACKGROUND AND OBJECTIVES/OBJECTIVE:The aim of this study was to identify distinct inflammatory response subtypes in patients with c-NORSE by analyzing their cytokine profiles. Insights into underlying mechanisms were sought to understand the pathophysiology and guide personalized therapies to improve patient outcomes. METHODS:Sixty-two patients with c-NORSE were included. A comprehensive panel of 96 cytokines was analyzed in serum samples. Patients were clustered based on their cytokine profiles using the Louvain algorithm, an unsupervised graph-based clustering method. The identified clusters of patients were compared regarding cytokine levels and clinical features. Protein pathway analysis was used to explore the biological relevance of the inflammatory markers within each cluster. Patients with c-NORSE were compared with control patients (n = 18) and patients with other forms of refractory SE (n = 45). RESULTS:Compared with controls, patients with c-NORSE exhibited significant differences in 33 cytokines. Pathway analysis revealed dysregulations in chemotaxis and neutrophil recruitment and migration, highlighting the importance of innate immunity in patients with c-NORSE. Within the c-NORSE cohort, 3 clusters of patients emerged: cluster A, lacking specific inflammatory markers; cluster B, with a much stronger innate-immunity cytokine-driven inflammatory response compared with clusters A and C; and cluster C, defined by dysregulated autoimmune processes. Notably, patients in cluster B showed a statistically significant elevation of innate immune-related proinflammatory cytokines associated with leukocyte recruitment and degranulation. By contrast, those in cluster C showed activation of Janus kinase signal transducer and activator of transcription (JAK-STAT) pathways, suggesting autoimmune mechanisms. Patients in clusters B and C demonstrated varied responses to immunotherapies, with cluster C patients showing favorable outcomes after multiple immunotherapies. DISCUSSION/CONCLUSIONS:The identification of distinct inflammatory subgroups in c-NORSE suggests that variations in the underlying immune mechanisms contribute to differential treatment responses. These findings underscore the importance of personalized therapeutic strategies, potentially targeting specific inflammatory pathways, to optimize clinical outcomes in this challenging condition.