Citations

Abstract Objective Resective surgery achieves seizure freedom in approximately 60%–80% of patients with drug‐resistant temporal lobe epilepsy (TLE), yet the extent to which seizure cessation permits recovery of disrupted functional brain networks remains unclear. Increasing evidence suggests that recurrent seizures alter subcortical–cortical communication involved in arousal and cognition, contributing to chronic interictal deficits, such as in executive function. Prior work demonstrates that the nucleus basalis of Meynert (NBM), the primary source of cortical cholinergic input to the cortex, exhibits aberrant functional connectivity in patients with TLE. We examined NBM connectivity in patients with TLE before and after surgery using patient‐specific NBM segmentations. We sought to investigate whether seizure freedom is associated with recovery of NBM functional connectivity, consistent with previous observations of interictal network dysfunction reversal in other subcortical arousal structures. Methods Resting‐state functional magnetic resonance imaging was analyzed in 75 patients with TLE, including 34 patients postoperatively, and 106 controls. Patient‐specific NBM segmentations were used to compute functional connectivity between the NBM and frontoparietal association cortex (FPAC) and across the whole brain. Subcortical arousal network community structure was assessed using community detection. Postoperative network changes were evaluated relative to seizure outcome. Results Prior to surgery, patients exhibited reduced bilateral NBM connectivity to the FPAC and whole brain compared to controls, indicating widespread cholinergic network disruption beyond the ipsilateral hemisphere. Following surgery, NBM connectivity increased and no longer differed from controls. Seizure‐free patients demonstrated greater postoperative increases in ipsilateral NBM‐FPAC connectivity than non‐seizure‐free patients, which was not explained by time to postoperative scan or volumetric change. Subcortical arousal community structure remained altered postoperatively. Significance Successful TLE surgery is associated with partial restoration of cholinergic arousal network connectivity, supporting the idea that seizure cessation enables recovery of brain networks disrupted by recurrent seizures. These findings position the NBM as a potential biomarker of network recovery following epilepsy surgery.

Background/Objectives: Leptin is a pleiotropic adipokine linking energy metabolism with innate and adaptive immunity. Its relationship with clinical severity across distinct airway disease phenotypes remains insufficiently characterized. This study examined serum leptin concentrations in adults with allergic rhinitis, non-allergic asthma, and allergic asthma associated with allergic rhinitis. Methods: This single-center retrospective observational study analyzed fully anonymized clinical and laboratory data from 88 adults: patients with allergic rhinitis (n = 31), non-allergic asthma (n = 15), or allergic asthma with allergic rhinitis (n = 22) and healthy controls (n = 20). Serum leptin was measured using a quantitative sandwich enzyme-linked immunosorbent assay. Disease severity was classified using the Allergic Rhinitis and its Impact on Asthma and Global Initiative for Asthma frameworks applicable during the study period. Statistical analyses were performed using IBM SPSS Statistics, version 26.0 (IBM Corp., Armonk, NY, USA), and available original statistical outputs were summarized using retained t statistics and two-sided p values. Results: Stage-specific mean serum leptin concentrations were heterogeneous and non-monotonic. Statistically significant relationships between leptin concentration and disease stage were reported for allergic rhinitis (t = 2.844; p = 0.008), non-allergic asthma (t = 4.240; p = 0.001), and allergic asthma with allergic rhinitis (t = 2.700; p = 0.013). In the allergic rhinitis subgroup, 64.5% of participants had normal weight, 32.3% were overweight, and 3.2% had grade II obesity; weight category was not significantly related to rhinitis stage. Conclusions: The retained analyses indicate statistically significant relationships between serum leptin concentration and clinical disease stage across the investigated airway phenotypes. However, the stage-specific descriptive means were heterogeneous and non-monotonic and therefore do not support a uniform progressive increase in leptin with increasing disease severity. Because complete model outputs and covariate-adjusted estimates were unavailable, these findings should be regarded as exploratory and require prospective validation with appropriate adjustment for adiposity and other relevant metabolic confounders.

Abstract Striated muscle weakness and motor neuron (MN) death are associated with aging. These alterations affect both brainstem and spinal motor pools, including hypoglossal MNs innervating the tongue and lumbar MNs innervating the lower/hindlimbs. Both MNs and striated muscles exhibit type‐selective motor unit vulnerability, where larger MNs (likely fast fatigable motor units) and type IIx/b muscles are vulnerable to death and atrophy, respectively. These findings have been cemented in humans to some degree and in Fischer 344 and Wistar rats. However, MN survival in old age has not been evaluated in Sprague–Dawley rats. Here, in 6‐ (young) and 24‐month‐old (old) female and male Sprague–Dawley rats, we performed stereological MN counts on hypoglossal and lumbar MNs using 16 μm Nissl‐stained sections. We observed a 35% loss of hypoglossal and lumbar MNs in old age. Although mean MN somal surface areas were moderately reduced in hypoglossal and unchanged in lumbar MNs with age, frequency histogram analyses revealed a disproportionate loss of larger MN in old age hypoglossal and lumbar pools. These findings reveal reliable and robust observations of MN death in rats. This neurogenic aspect of neuromotor impairment with age may be a key driver of sarcopenia and frailty in the elderly.

Abstract Objective Interictal epileptiform spikes (IESs) are widely used biomarkers of epileptogenic tissue in presurgical epilepsy evaluation. However, their reliability for seizure onset zone (SOZ) localization in high‐density intracranial electroencephalography (iEEG) remains inconsistent. It is underexplored whether this variability reflects methodological differences across detection algorithms or a limitation of IESs as a biomarker. This study evaluates whether IES detection alone provides sufficient spatial specificity for accurate SOZ localization in iEEG. Methods We systematically benchmarked eight established IES detection algorithms using iEEG recordings from 35 patients with drug‐resistant focal epilepsy. To provide a clinically meaningful reference, algorithm performance was evaluated against the clinically defined SOZ. To refine detection outputs and move beyond only IES detection, we applied masking strategies to isolate informative IES subsets based on rate, amplitude, frequency, and co‐occurrence with high‐frequency oscillations (HFOs). Conceptually, masking acts as a spatial refinement strategy that progressively restricts diffuse IES activity to more focal, pathologically relevant event populations. Results Despite substantial variability in detection characteristics, SOZ localization performance (ratio of events originating from SOZ divided by total number of events) converged within a narrow range (.23–.51), suggesting that IESs exhibit an intrinsic ceiling in SOZ localization performance when used alone. Amplitude‐based masking yielded modest improvements, whereas frequency‐based masking reduced performance. In contrast, IES‐HFO co‐occurrence markedly improved localization, particularly when combined with rate‐based masking, achieving a median SOZ localization ratio of .89, exceeding IESs (.37) and HFOs (.63) evaluated independently. Significance These findings demonstrate that IES‐based SOZ localization may require moving beyond detection‐only approaches. The integration of informed, biomarker‐driven masking strategies provides a more robust framework for identifying the activity most relevant to the epileptogenic network and paves the way for future incorporation into the clinical decision‐making pipeline.

ABSTRACT Diagnosis The diagnosis of multiple myeloma requires ≥ 10% clonal bone marrow plasma cells or a biopsy proven plasmacytoma plus evidence of one or more multiple myeloma defining events (MDE): CRAB (hypercalcemia, renal failure, anemia, or lytic bone lesions) attributable to the plasma cell disorder, bone marrow clonal plasmacytosis ≥ 60%, serum involved/uninvolved free light chain (FLC) ratio ≥ 100 (provided involved FLC is ≥ 100 mg/L and urine monoclonal protein is ≥ 200 mg/24 h), or > 1 focal lesion on magnetic resonance imaging. Risk Stratification High‐risk multiple myeloma is defined by the presence of del(17p), p53 mutation, or bi‐allelic del(1p); t(4;14), t(14;16), t(14;20) in combination with gain(1q) or del(1p); or gain(1q) plus del(1p). Initial Therapy Initial therapy consists of a quadruplet regimen consisting of anti‐CD38 monoclonal antibody (daratumumab or isatuximab) plus bortezomib, lenalidomide, dexamethasone (VRd) followed by autologous stem cell transplantation in eligible patients. Selected standard risk patients can delay transplant until first relapse. Frail patients who are not candidates for transplant are treated with a triplet regimen, either anti‐CD 38 antibody plus lenalidomide and dexamethasone, or VRd. Maintenance Therapy Standard maintenance is lenalidomide in combination with daratumumab or isatuximab. Lenalidomide is discontinued after 2 years in standard‐risk patients. Bortezomib plus lenalidomide is an alternative option for high‐risk myeloma. Management of Relapsed Disease Major options are chimeric antigen receptor T (CAR‐T) cell therapy, bispecific antibodies, various triplet regimens, and belantamab mafadotin. Management of Smoldering Multiple Myeloma Daratumumab for 3 years should be considered in high‐risk smoldering multiple myeloma.

Abstract Background Personalized meal planning by registered dietitian nutritionists (RDNs) is time‐intensive. Large language models (LLMs) may automate drafting meal plans, but their nutritional accuracy in clinical practice is uncertain. Methods In this proof‐of‐concept study, five outpatient RDNs and four LLMs (Gemini, CoPilot, ChatGPT 4.0, and customized ChatGPT 4.0) each generated 3‐day meal plans for five validated clinical scenarios. Effectiveness was defined as accuracy in meeting pre‐specified energy, protein, carbohydrate, fat, and sodium targets. Time to create plans and RDN comfort (self‐rated confidence in nutritional accuracy and clinical appropriateness on 1–5 Likert scale) were recorded. Three independent RDNs, blinded to source, analyzed nutrient content using Nutritionist Pro. Group differences were assessed with t ‐test and ANOVA. Results All LLMs and RDNs produced feasible meal plans. LLMs generated meal plans in under 1 min, whereas RDNs required a mean of 44 min per scenario. RDNs reported comfort levels ranging from 3.8 to 4.8. Across most scenarios, LLM plans delivered a smaller proportion of requested energy than RDN plans, which more consistently approached energy targets. Both groups performed similarly for the Mediterranean diet scenario. Overall, protein accuracy did not differ. However, in chronic kidney disease, LLMs undershot the guideline‐based protein target, while RDNs tended to modestly exceed it. Accuracy for low‐carbohydrate, fat, and sodium diets was comparable. Conclusion LLMs can rapidly generate clinically plausible meal plans but are less reliable than RDNs in achieving prescribed energy and selected macronutrient goals. Prompt precision is essential for nutrient‐specific targets. A hybrid model in which RDNs refine LLM‐generated drafts may leverage efficiency without sacrificing clinical accuracy.