Williams (United States)

The National Organization of Nurse Practitioner Faculties (NONPF) Leadership and Mentoring Program (LMP) supports early- and mid-career nurse practitioner (NP) faculty develop effective leadership competencies and skills. The leadership competencies and skills for NP faculty are constantly evolving. NONPF's LMP is grounded in a competency-based education model and uses backward design to align learning outcomes with measurable leadership behaviors. LMP participants engage in structured learning sessions organized around 5 core leadership domains: Lead Self, Engage Others, Achieve Results, Develop Coalitions, and Systems Transformation. One-to-one mentoring runs concurrently with the educational sessions, offering personalized guidance and support throughout the 12-month program. The new NONPF 12-month LMP is redesigned for emerging NP faculty leaders to strengthen their leadership skills and build confidence by applying leadership competencies in real-world academic settings.

Introduction: The etiology of deep-seated intracranial hemorrhages (ICH), in the absence of identifiable vascular lesions on imaging, has traditionally been considered cryptogenic. With increasing recognition of the role of intracranial veins and venous congestion in brain pathology, we aimed to evaluate the venous anatomy—specifically stenosis of the deep venous system—and assess whether venous congestion in the basal ganglia or thalamic regions is associated with deep ICH. Hypothesis: Stenosis of the deep venous system—including the vein of Galen and straight sinus—can lead to increased venous congestion in the basal ganglia and thalamus, predisposing patients to deep-seated hemorrhages. Methods: We conducted a retrospective, single-arm study of adult patients presenting with spontaneous basal ganglia or thalamic hemorrhages without identifiable vascular etiology on magnetic resonance imaging (MRI) and/or digital subtraction angiography (DSA), and without medication or comorbidity history predisposing to increased bleeding risk. Venous stenosis was assessed using CT venography (CTV) sequences acquired as part of the institutional ischemic stroke CT protocol. Both CTA sequences for perfusion processing and 3D-reconstructed venous-phase images were analyzed to evaluate the presence and severity of deep venous system stenosis. Results: We included 104 patients who met the inclusion criteria, of whom 100 (96%) demonstrated stenosis or occlusion of the deep venous system. The median age was 69 years [IQR: 60–80], with 57% male. Hemorrhage location was nearly evenly distributed between the basal ganglia (49%) and thalamus (51%). Hypertension was identified as the underlying etiology in 28%, while the remainder were classified as cryptogenic. Steno-occlusion most commonly involved the vein of Galen (64%), followed by the straight sinus. Two representative cases are shown in Figures 1 and 2. Conclusion: His study provides a novel indication for deep seated ICH. Identification of such stenoses on imaging provides a potential target for endovascular intervention in patients with deep venous stenosis and concurrent risk factors, such as hypertension, to mitigate the risk of hemorrhage and/or their recurrences.

Introduction: Intracranial stenting during endovascular thrombectomy (EVT) is a common practice in the setting of failed reperfusion or severe stenosis. Immediate stent patency requires periprocedural antiplatelet therapy (APT). How APT intensity interacts with prior intravenous thrombolysis (IVT) to influence hemorrhagic risk remains uncertain. We aimed to assess whether the APT regimen modifies the association of IVT with early intracranial hemorrhage after intracranial stenting during EVT. Methods: This was a subanalysis of the RESISTANT registry, a multicenter, international, retrospective cohort (2016 to 2023) of adults with acute ischemic stroke who underwent intracranial stenting during EVT. APT regimens were categorized as conservative (intravenous or oral aspirin alone, or aspirin plus an oral P2Y12 inhibitor) and aggressive (any regimen including intravenous GPIIb/IIIa inhibitor or intravenous cangrelor). Four main groups were compared according to the APT regimen (conservative/aggressive) and the use of IVT (+/-). The primary outcome was a composite of sICH and parenchymal hematoma types 1 and 2 (sICH-PH2-PH1). Multivariable logistic regression models were used to evaluate the interaction between IVT and APT, adjusting for clinically relevant covariates. Results: Among the 823 included patients, 44 (5.3%) received conservative APT with IVT, 130 (15.8%) received conservative APT without IVT, 145 (17.6%) received aggressive APT with IVT, and 504 (61.2%) received aggressive APT without IVT. Among patients who received IVT, sICH-PH2-PH1 rates were 9.3% with conservative APT and 10.7% with aggressive APT; among those without IVT, rates were 3.2% and 9.9%, respectively. Administration of IVT (adjusted odds ratio [aOR] 5.84, 95%CI 1.07 to 43.92; p=0.05) and aggressive APT (aOR 4.81, 95% CI 1.41 to 30.22; p=0.03) were each associated with higher odds of hemorrhagic complications, with a significant IVT by APT interaction (P interaction =0.05; Figures 1 and 2 ). Within the aggressive APT plus IVT subgroup, sICH-PH2-PH1 occurred in 20% of patients treated with cangrelor and 6.1% treated with a glycoprotein IIb/IIIa inhibitor ( Figure 3 ). Conclusion: Among patients requiring intracranial stenting, aggressive periprocedural APT and prior IVT are each associated with higher hemorrhagic risk, with the combination showing the worst observed crude outcome. Prospective evaluation of protocolized APT pathways in the IVT setting is warranted.

Accurately predicting drug-target binding affinity (DTA) is essential for accelerating drug discovery and reducing experimental costs. Existing deep learning-based DTA methods often fail to effectively integrate heterogeneous biological knowledge and structural information, leading to suboptimal generalization across diverse drug-target pairs. In this work, we propose KGPrompt-DTA, a novel framework that injects knowledge graph-driven prompts into a hybrid graph-transformer architecture to enhance molecular and protein representation learning. Specifically, we construct entity-relation-aware prompts from biomedical knowledge graphs and dynamically fuse them with graph-encoded molecular and protein features via a multilevel attention mechanism. This design enables the model to capture both local structural dependencies and high-level semantic associations. Extensive experiments on two benchmark datasets, DAVIS and KIBA, demonstrate that KGPrompt-DTA consistently outperforms state-of-the-art methods, achieving MSE reductions of 15.5 % and 6.5 %, respectively, while also improving CI, <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$r_{m}^{2}$</tex>, and Pearson correlation scores. Ablation studies confirm the contribution of each component, highlighting the effectiveness of integrating knowledge-informed prompts with graph-transformer learning.

We read with great interest the study by Murin et al., “Uncovering Hidden Profiles: From Pain-Centric to Multi-Symptom Small Fiber Neuropathy.” The authors describe a cohort of 203 patients with small fiber neuropathy (SFN) with only 20% of the entire cohort having severe neuropathic pain, which was termed the “algesic” group. The other 80% of patients had significant fatigue, myalgia, and generalized weakness, and either no or mild neuropathic pain [1]. Importantly, most patients also experienced autonomic symptoms, with the most common being dry eyes, dry mouth, and GI dysmotility prior to undergoing a skin biopsy, compared to healthy controls [1]. Noteworthy is that patients in cluster 2 (termed “myalgic”) consisting of 60% of the cohort had especially severe fatigue compared to other symptoms—more intense than neuropathic symptoms. In this cluster, patients also experienced significantly more severe weakness and myalgias than burning pain [1]. Interestingly, autonomic symptoms were present in all three clusters [1]. It's important to note that traditionally, neuropathic pain was required for a diagnosis of SFN, and the absence of neuropathic pain as a feature often excluded neuropathy from the differential diagnoses in patients presenting with fatigue, myalgia, and generalized muscle weakness. The study by Murin et al. illustrates that neuropathic pain may be mild or absent, but SFN may still be present, as confirmed via reduced epidermal nerve fiber density [1]. We emphasize that at least 50% of patients with postural orthostatic tachycardia syndrome (POTS) and Long COVID and nearly a third of patients with myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) were found to have SFN when assessed via skin biopsy, quantitative sudomotor axon reflex test, corneal microscopy or microneurography [2, 3]. However, many patients with these disorders do not experience severe—or any—neuropathic pain and, instead, typically present with fatigue, lightheadedness/dizziness, generalized weakness, and myalgia [1, 3]. Murin et al.'s study compellingly demonstrates that SFN can present predominantly with fatigue and weakness rather than pain, challenging conventional diagnostic assumptions [1]. The fact that patients with fatigue and generalized weakness may have SFN without exhibiting neuropathic pain or significant abnormalities on neurologic exam should be emphasized in neurology training, which we believe is essential to improving diagnostic accuracy and optimizing treatment outcomes. Finally, autoimmune conditions and abnormal autoimmune markers were common in this and other cohorts of patients with SFN [1, 3-5], suggesting an autoimmune and immune-mediated etiology, which is similarly identified as a major pathophysiologic mechanism in patients with POTS, Long COVID and ME/CFS. Additionally, dysautonomia more broadly is a common manifestation of a wide variety of systemic disorders, many of which are autoimmune, immune-mediated, inflammatory and post-acute infectious in nature [3, 4]. Currently, the mechanistic interplay between SFN and dysautonomia, and whether SFN is an underlying mechanism of dysautonomia or an associated comorbidity in the autoimmune and immune-mediated pathways that drive both conditions, is unknown. Regardless, immunotherapies for patients with SFN, POTS, ME/CFS, and Long COVID, especially when accompanied by comorbid autoimmune conditions or abnormal autoimmune or immunologic markers, may be considered, and carefully designed randomized controlled trials are needed to assess their efficacy in each disorder [5]. Svetlana Blitshteyn: conceptualization, writing – original draft, investigation, writing – review and editing. Michael Stingl: writing – review and editing. Jill R. Schofield: writing – review and editing. The authors have nothing to report. The authors have nothing to report. The authors declare no conflicts of interest. Data sharing not applicable to this article as no datasets were generated or analysed during the current study.

Page reclamation is critical for system performance. However, understanding and quantifying inner workings of reclamation policies remains challenging. In this work, we present a comprehensive analysis of Linux’s Two-Queue LRU (2QLRU) and Multi-Generational LRU (MGLRU) policies using a lightweight profiler that measures decision overhead and reclamation effectiveness. Across seven diverse applications under various memory constraints, we quantify how MGLRU achieves better reclamation decisions despite its higher decision making cost, while its performance benefits diminish under severe memory constraint. These insights provide guidance for future memory management optimizations.