Faculty Bibliography

BACKGROUND:Psychological resilience predicts better outcomes in persons with multiple sclerosis (pwMS), yet factors which sustain it over time remain poorly understood, particularly in diverse populations. Personality traits may represent stable determinants of resilience. OBJECTIVES/OBJECTIVE:To examine the influence of personality on resilience in Black and Non-Hispanic White pwMS (BpwMS/WpwMS) and their healthy counterparts (BHCs/WHCs). METHODS:Psychological resilience and personality were assessed in a matched cohort of 120 pwMS and 80 HCs using the Connor-Davidson Resilience Scale and NEO-Five Factor Inventory-3. Personality and resilience were compared across groups. In pwMS, cross-sectional regression and longitudinal mixed-effects models evaluated personality-resilience associations; sensitivity analyses adjusted separately for depressive symptoms, psychiatric history, and subjective social status to evaluate the robustness of these associations. RESULTS:PwMS and HCs reported similar levels of Neuroticism, Agreeableness, and Conscientiousness; Extraversion and Openness were lower in pwMS. PwMS had worse resilience compared to HCs at follow-up. Higher Neuroticism predicted lower resilience, with a stronger association observed in BpwMS; higher Extraversion and Conscientiousness predicted better resilience. Higher Conscientiousness was associated with less longitudinal decline in resilience. Adjustment for depression attenuated the Conscientiousness and Neuroticism × Race associations, whereas Neuroticism and Extraversion associations remained significant. In prospective models, Conscientiousness continued to predict follow-up resilience independent of baseline depression. CONCLUSIONS:Personality traits may identify pwMS susceptible to reduced psychological resilience; Conscientiousness in particular may help sustain it over time. Although depression contributes to personality-resilience relationships, Neuroticism and Extraversion remain independently associated with resilience. Our findings support personality-informed approaches to strengthen psychological resilience in pwMS and identify depression as a clinically actionable target for future intervention.

Long COVID has been an important health concern in children and adolescents, yet factors associated with its development remain incompletely understood. Selective serotonin reuptake inhibitors (SSRIs) and serotonin-norepinephrine reuptake inhibitors (SNRIs) are widely prescribed for pediatric neuropsychiatric conditions and may influence immune and autonomic pathways involved in postinfectious symptoms. Here we show associations between SSRI/SNRI use and long coronavirus disease (COVID)-related outcomes in a retrospective cohort of 110,955 children and adolescents with pre-existing neuropsychiatric conditions across 37 US health systems participating in the National Institutes of Health Researching COVID to Enhance Recovery consortium. SSRI/SNRI use was not associated with clinician-recorded long COVID diagnosis but showed heterogeneous associations with individual symptoms. Lower risks were observed for some symptoms, including fever, chills and hair loss, whereas higher risks were observed for neurological and systemic outcomes, including postural orthostatic tachycardia syndrome, cognitive dysfunction and fatigue. These findings suggest that antidepressant exposure may be associated with differing post-COVID symptom patterns in youth and warrant further investigation.

Consciousness science is fragmented, and empirical investigations are largely confined within the framework of each theory of consciousness (ToC). Proliferating ToCs accumulate anomalies without progress, operating orthogonally. The principle of recurrency, functional and architectural, specifies a unifying, mechanistic scaffold for consciousness to arise. We show that all theories tacitly invoke feedback loops and can be re-expressed along a single axis of recursion. Four nested levels, viz., cellular, local inter-areal, global, and lateral, map onto state consciousness, phenomenal (P) content, conscious access (A), and phenomenal character, respectively, thus tying evolved anatomy to phenomenality. The classical P-A distinction dissolves into a graded cascade wherein deeper recursion expands the set of reportable, behaviour-driving variables. Recurrency, defined as structural, causal, and/or functional feedforward and feedback connections between elements within a system, is favoured in biological architectures, and supports the closed-loop interactions between brain, body, and environment that underlie adaptive behaviour and self-related processing. Disparities in the explanatory mechanisms across theories of consciousness can thus be resolved by converging onto this shared principle on the implementation axis, rather than deal with phenomenal-first or functional-first ontologies. The field urgently requires this implementation-first distillation that is biologically plausible, mechanistic, and empirically testable.

In mesial temporal lobe epilepsy, resection or ablation-typically of anterior temporal structures-is highly successful in achieving seizure freedom. However, in a substantial proportion of patients, seizures recur for unclear reasons. Invasive hippocampal recordings suggest that, in some patients, hippocampal seizures are highly focal, often restricted to the anterior or posterior hippocampus. This led us to hypothesize that resection or ablation limited to the hippocampal subregion(s) involved at seizure onset is more likely to control seizures than surgery that does not address the specific onset locations. We present a case in which seizures were successfully controlled after posterior hippocampal ablation, as well as a retrospective case series of 18 patients in which 10 cases demonstrated focal onsets within the anterior or posterior hippocampus. Better outcomes occurred when surgery was concordant with the onset region(s) versus discordant (n = 7 concordant vs. 11 discordant patients, P = 0.046, Barnard Exact test). These data suggest that mesial temporal lobe epilepsy can be subdivided according to whether the hippocampal onset pattern is focal or nonfocal, and that targeting localized seizure onset zones within the hippocampus can be effective for seizure control, while limiting surgical morbidity and potentially the risk of adverse cognitive outcomes.

[This corrects the article DOI: 10.7759/cureus.113024.].

Mechanical thrombectomy (MT) is superior to medical therapy for anterior circulation proximal large-vessel occlusion (LVO) stroke, including in imaging-selected patients treated 6 to 24 h after their last known well (LKW) time. Beyond 4.5 h, the role of intravenous thrombolysis (IVT) has become more relevant because many health systems lack the ability to provide timely thrombectomy access for eligible late-window patients. Recent late-window IVT trials, including TRACE-III and HOPE, have demonstrated benefit in imaging-selected patients in whom thrombectomy was not planned or not effectively deliverable, addressing a critical systems-of-care gap. We review these trials alongside emerging evidence and situate each within a systems-of-care framework, distinguishing bridging scenarios from settings where MT is unavailable or substantially delayed. However, we argue that their results should not be taken to imply therapeutic equivalence with MT, a comparison that is misleading on methodological grounds. No randomized, head-to-head late-window trial of IVT versus MT exists. Comparing treated-arm outcomes across these separate trials as a proxy for therapeutic equivalence is vulnerable to differences in baseline prognosis, occlusion site, imaging selection, access to rescue therapy, and control-group outcomes. In this Perspective, we argue that these trials should be read one at a time. Each treated arm should be judged against its own control group and against the clinical and angiographic profile of the patients enrolled, not against treated arms from trials that enrolled very different strokes.

New onset refractory status epilepticus and febrile infection-related epilepsy syndrome are rare and devastating entities in the pediatric population. While no known therapies have formally been established as the "gold standard" for management of the acute phase, consensus guidelines do establish interleukin therapies such as anakinra and tocilizumab as safe and effective second-line immunotherapeutic options. Despite the use of interleukin therapies, many patients continue to have super refractory status epilepticus. A number of publications (mainly case reports and case series) have described various adjunctive therapies in the management of new onset refractory status epilepticus/febrile infection-related epilepsy syndrome, including neuromodulatory therapies (such as vagal nerve stimulation, deep brain stimulation, and electroconvulsive therapy), surgical resection, noninterleukin immunotherapies (such as intrathecal dexamethasone, intravenous rituximab, and cyclophosphamide), infusions (such as lidocaine and magnesium), and anesthetic agents (such as sevoflurane). Utilizing a modified Preferred Reporting Items for Systematic reviews and Meta-Analyses approach, this narrative review summarizes the effectiveness and safety of second-line immunotherapies such as tocilizumab and anakinra, as well as the various adjunctive third-line therapies that aim to abort seizures and mitigate comorbidities within an intensive care setting, such as prolonged sedation and secondary systemic complications.

Diagnostic MRI evaluation of temporal lobe epilepsy (TLE) depends on the subjective visual interpretation of MRI images. These interpretations could be enhanced by quantitative artificial intelligence (AI) support tools. Humans often make sequential and conditional decisions during their radiological interpretations, such as whether an abnormality is present and, if present, characterizing the abnormality. It is not known whether it is superior to train AI to treat every decision separately in a similar step-wise manner or to train a model holistically on all decisions simultaneously. Here, we analysed three large epilepsy MRI datasets [n = 3676, 2320 people with epilepsy and 1356 healthy controls (HC)] to perform two tasks: (i) establish the presence of a TLE pattern on MRI and (ii) determine TLE pattern lateralization. We compared Step-wise models that independently classify TLE versus HC and lateralize patients as left TLE (L-TLE) or right TLE (R-TLE), against a simultaneous model trained to distinguish all three classes in a single step. To do this, 3D volumetric T1-weighted images were input into an EfficientNetV2 model multiple times to ensure reproducibility of results. Class prediction, model classification confidence and saliency maps were output for interpretability. Step-wise models outperformed the Simultaneous model on both tasks (both Ps < 0.001), with an average ∼2.8% accuracy increase for discriminating HC from TLE and an average 12.7% accuracy increase for distinguishing L-TLE from R-TLE. For both the Step-wise and Simultaneous models, important features discriminating TLE from HC included the known TLE limbic pattern involving the hippocampus, parahippocampal cortical regions, cingulate cortex and lateral temporal regions. However, there was less concordance between the Step-wise and Simultaneous models for the L-TLE versus R-TLE task (all Fisher's Zs > 10.5, Ps < 0.001); the Step-wise model focused less on subcortical regions such as the thalamus and hippocampus and focused more on distributed cortical pathology. Across the two Step-wise models, 95.1% of TLE patients had accurate classifications in either HC versus TLE and/or L-TLE versus R-TLE tasks. These results included 69.6% of patients being both correctly labelled as TLE and lateralized, 13.9% being correctly labelled TLE but lateralized incorrectly and 11.6% being lateralized correctly but not detected as TLE. These findings provide evidence that diagnostic tasks with simpler, Step-wise AI models may enhance diagnostic performance and interpretability in clinical workflows. Future AI clinical support tools can leverage this step-wise approach in the early identification of TLE-related structural patterns, supporting timely diagnosis and treatment decisions.

Alzheimer's disease (AD) is characterised by the intraneuronal aggregation of phosphorylated Tau (pTau) into neurofibrillary tangles and by the extracellular deposition of β-amyloid (Aβ). Tau pathology restricted to the hippocampal formation is frequently observed in the elderly brain in the absence of any Aβ deposition and considered as "primary age-related tauopathy" (PART). Here, we applied an unbiased proteomic approach to determine how concomitant Aβ pathology modifies the neurofibrillary tangle proteome. Neurofibrillary tangles were isolated by dissecting Tau pSer202/pThr205 "AT8" immunopositive neuronal profiles, combining chromogenic immunohistochemistry with laser capture microdissection, from hippocampal sections of 17 post-mortem brains spanning three groups: PART (n = 5; A0, B1-2, C0 scores), intermediate AD (n = 6; A1-2, B2-3, C1-2 scores) and advanced AD (n = 6; A3, B3, C3 scores). A label-free quantitative liquid chromatography-mass spectrometry based proteomic analysis, using data independent acquisition (DIA) on a Bruker timsTOF, was performed. A conserved core of 63 proteins was identified as enriched in tangles across all groups, mostly associated with "RNA binding" and "regulation of mRNA metabolic process", based on the Gene Ontology database. Group-specific signatures were also observed: 33 proteins were significantly enriched only in tangles collected from PART cases and were predominantly linked to "structural molecule activity", whereas Aβ-positive cases showed specific enrichment of "RNA binding" and "cytoplasmic translation" pathways-with intermediate AD cases displaying a transitional profile. Our findings are consistent with PART having distinct tangle proteomic features; however, the majority of its proteomic signature is in common with tangles within the AD continuum. By addressing how Aβ accumulation alters the tangle proteome, this study provides mechanistic insights into the expansion of Tau pathology, paving the way towards the identification of biomarkers and therapeutic strategies that would allow for stabilisation of Tau pathology in the elderly.