Drug survival is an important measure to help guide treatment selection. However, clinical evidence for newer biologics, including bimekizumab, is limited. To determine the drug survival of biologics used for treating psoriasis in a routine clinical practice setting. This cohort study was based on data from the DERMBIO registry, which includes all patients treated with biologics for psoriasis in Denmark. All adult patients enrolled in DERMBIO from its inception in May 2007 until June 2025 were assessed for eligibility. Data were extracted in June 2025 and analyzed separately among those without previous biologic exposure (bionaive patients) and those with previous biologic exposure (bioexperienced patients). Adalimumab, secukinumab, and ustekinumab among bionaive patients and adalimumab, bimekizumab, brodalumab, guselkumab, ixekizumab, risankizumab, secukinumab, and ustekinumab among bioexperienced patients. The main outcome was standardized absolute risks of treatment discontinuation at 1, 2, and 5 years. Kaplan-Meier estimator was used to determine crude drug survival estimates and the Aalen-Johansen estimator was used to determine crude cause-specific absolute risks. The study included 4438 unique patients with psoriasis (2717 [61.2%] male; mean [SD] age, 45.0 [14.6] years at the time of their first treatment included in the study), 1039 (23.4%) of whom had comorbid psoriatic arthritis. A total of 3790 treatment series from bionaive patients were analyzed: 2646 were with adalimumab, 377 with secukinumab, and 767 with ustekinumab. The 5-year standardized risk of discontinuing ustekinumab was 0.37 (95% CI, 0.33-0.41), which was significantly lower than the standardized risks for adalimumab (0.51; 95% CI, 0.49-0.54) and secukinumab (0.54; 95% CI, 0.48-0.60). A total of 3403 treatment series from bioexperienced patients were analyzed: 790 were with adalimumab, 376 with bimekizumab, 192 with brodalumab, 218 with guselkumab, 556 with ixekizumab, 78 with risankizumab, 466 with secukinumab, and 727 with ustekinumab. The 2-year standardized absolute risk of discontinuing ustekinumab was 0.39 (95% CI, 0.36-0.43). Only bimekizumab (0.27; 95% CI, 0.20-0.34), guselkumab (0.29; 95% CI, 0.22-0.36), and risankizumab (0.25; 95% CI, 0.15-0.36) were associated with a significantly lower standardized absolute risk of discontinuation compared with ustekinumab. In this cohort study in Denmark, among bionaive patients with psoriasis, ustekinumab had superior drug survival compared with adalimumab and secukinumab, and among bioexperienced patients with psoriasis, bimekizumab, guselkumab, and risankizumab had superior drug survival. These results offer insight into the performance of different biologics in the treatment of psoriasis in a routine clinical practice setting.

Pilomatrixoma is a benign adnexal tumour characterised by pathological hair matrix differentiation and is most commonly observed in children. It typically presents as a slow-growing, pink to purplish dermal nodule. Due to its low clinical diagnostic accuracy, pilomatrixoma is often misidentified as other tumours. This case highlights an atypical presentation of pilomatrixoma in a girl in early adolescence and underlines the importance of considering ultrasonography or proceeding directly to surgical excision for definitive diagnosis.

Graphical abstractThe increased detection of adrenal incidentalomas and drug-induced adrenal insufficiency increases the demand for cortisol testing. While liquid chromatography–tandem mass spectrometry (LC-MS/MS) and dynamic testing remain the gold standard, more expedient tools are needed. We compared the Elecsys Cortisol II immunoassay (ElecsysCort II) with LC-MS/MS during dynamic testing and evaluated the diagnostic performance of baseline cortisol cutoffs (0 min cortisol during a short Synacthen test). The study included 547 overnight dexamethasone suppression tests (44% abnormal), mainly performed in adrenal incidentaloma patients (69%), and 519 Synacthen tests (32% abnormal). ElecsysCort II slightly underestimated cortisol compared with LC-MS/MS with a Passing–Bablok regression of −3.20 (95% CI: −3.66 to −2.83) + 0.96X (95% CI: 0.96–0.97) and a mean relative difference of −8.22% (95% CI: −8.99% to −7.45%) by Bland–Altman, which was within the limits of acceptable bias based on biological variation. Agreement was not affected by glucocorticoid or estradiol intake. Compared with LC-MS/MS, ElecsysCort II demonstrated a specificity of 100%, sensitivity of 84%, positive predictive value of 99%, and negative predictive value of 86% for an abnormal overnight dexamethasone suppression test (480 min cortisol ≥50 nmol/L). For an abnormal Synacthen test (30 min cortisol <420 nmol/L), the measures were 95, 99, 89, and 100%, respectively. A baseline cortisol cutoff >300 nmol/L to rule out and <150 nmol/L to rule in adrenal insufficiency demonstrated a high specificity (>92%) and a positive predictive value (>87%). Our study supports the use of ElecsysCort II in general and baseline cortisol as a screening tool for adrenal insufficiency. The high proportion of abnormal overnight dexamethasone suppression tests among incidentaloma patients warrants further research.

The Ventral Rectopexy International Expert Panel recently published a consensus update on ventral rectopexy. The ability of large language models to synthesize the literature on ventral rectopexy without an explicit knowledge base was studied prior to publication of the consensus. To compare different large language models' responses and citations on ventral rectopexy using the expert panel consensus as a reference standard. ChatGPT-4o, Gemini 1.5 Pro, and OpenEvidence were compared on content appropriateness (1-inappropriate to 5-appropriate), readability (Flesch reading ease), response length, citation fabrication, and citation quality per Oxford Levels of Evidence. The most content-appropriate chatbot response selected by the expert panel was de-identified and presented alongside the consensus text to 15 colorectal surgeons who attempted to identify the chatbot-generated text. Questions were submitted on September 18-19, 2024. Analysis was performed prior to the consensus's publication online on January 30, 2025. Content appropriateness, fabricated citation rate, citation quality, accuracy of identifying human vs. chatbot text by colorectal surgeons. OpenEvidence ranked highest for content appropriateness (mean 3.5/5), above Gemini (3.0/5) and ChatGPT (2.8/5) (p<0.001). ChatGPT was most verbose with the highest readability scores (p=0.021). ChatGPT fabricated 53% of citations; Gemini fabricated 12%; OpenEvidence fabricated 0% (p<0.001). All OpenEvidence citations were peer-reviewed with 40/117 (34%) citing Level I-III studies vs. 46/94 (49%) of the references cited in the consensus (p=0.043). Chatbot-generated responses were identified with 28/51 (55%) accuracy. Reproducibility due to nature of large language models and availability of consensus post-publication. OpenEvidence outperformed Gemini 1.5 Pro and ChatGPT-4o on content appropriateness and peer-reviewed citation quantity and quality. Chatbot-generated text was indistinguishable from expert-authored consensus to subject matter experts. Large language models as an early-stage research tool may be viable for future consensus working groups, provided transparent disclosure and rigorous oversight. See Video Abstract.

While there has been a considerable increase in the understanding of glioblastoma and investigations into the therapeutic utility of several novel putative active compounds, the prognosis of glioblastoma patients remains dismal. This paradox makes glioblastoma a unique disease in which the availability of key molecular and biological insight does not translate into therapeutic discovery or improved outcomes. Much of the challenge in glioblastoma treatment is due to a dearth of tools capable of accurately selecting patients who may benefit from current standard-of-care or targeted therapies. Moreover, the lack of reliable circulating biomarkers also delays treatment initiation and hampers therapeutic response evaluation. However, the emergence of a personalized medicine paradigm employing extracellular vesicles has the potential to revolutionize cancer treatment, bringing renewed hope for patients with glioblastoma. In this review, we provide a brief overview of the clinical outlook of current standard-of-care, immunotherapy, and their drawbacks, introduce the need for a personalized model, and finally discuss the conceptual underpinnings of how extracellular vesicle cargo as superior liquid biopsy tools can be utilized for a new personalized therapeutic approach in glioblastoma.

Inborn errors of immunity (IEI) impairing brain-intrinsic immune defenses can underlie herpes simplex virus encephalitis. By whole-exome sequencing of cohorts of herpesvirus-associated recurrent lymphocytic meningitis and acute retinal necrosis, we identified two patients heterozygous for variants in interferon (IFN) regulatory factor 7 (IRF7). The expression of the Q185X (patient 1, P1) and A86Rfs23X (P2) IRF7 variants in HEK293T cells resulted in truncated IRF7 proteins that lacked IFN-transactivating ability. Peripheral blood mononuclear cells from P1 exhibited reduced type I IFN responses to HSV-2 infection. Genetic knock-in of the IRF7 Q185X variant in THP-1 cells and stem cell-derived plasmacytoid dendritic cells (pDC) confirmed the disrupted IFN expression, resulting in impaired paracrine antiviral protection of meningeal fibroblasts. Strikingly, genetically heterozygous index patient pDC, but not those of healthy carrier family members, showed expression of only the pathogenic IRF7 Q185X allele, resulting in a homozygous transcriptotype. Collectively, this study identifies genetically heterozygous but transcriptionally homozygous IRF7 deficiency as an IEI underlying herpesvirus central nervous system infection.

Single-cell spatial transcriptomics enables precise mapping of cellular states and functional domains within their native tissue environment. These functional domains often exist at multiple spatial scales, with larger domains encompassing smaller ones, reflecting the hierarchical organization of biological systems. However, the identification of these functional domain hierarchies has been largely unexplored due to the lack of suitable computational methods. In this work, we present SCALE, an unsupervised algorithm for multiscale domain identification in spatial transcriptomics data. SCALE combines deep learning-based graph representation learning with an entropy-based search algorithm to detect functional domains at different scales. We demonstrate its effectiveness in identifyingmultiscale domains using both simulated data and spatial transcriptomics data from murine brain (Xenium and MERFISH) and patient-derived kidney tissue, highlighting its robustness and scalability across diverse tissue types and platforms. SCALE outperforms state-of-the-art multidomain identification by up to 191.1 percentage points. SCALE's ease of use makes it a powerful aid for advancing our understanding of tissue organization and function in health and disease.

To define and articulate research priorities in epilepsy identified by the European Reference Network for Rare and Complex Epilepsies (ERN EpiCARE), addressing key unmet needs across the spectrum of rare and complex epilepsies. This position paper was developed through a structured collaborative process involving patient associations and experts from EpiCARE Working Groups, the EpiCARE Executive Committee, and its Research Council. Contributions were integrated and harmonized to establish a shared set of research priorities reflecting clinical, translational, and methodological perspectives. Six priority areas were identified and examined: prevention of epileptogenesis and disease-modifying challenges; genetics and targeted therapies; improved surgical decision-making; innovative trial designs and outcome measures; artificial intelligence for diagnosis and prediction; understanding and preventing comorbidities and mortality. For each priority, the paper discusses the current state of research, identifies challenges, and proposes strategic directions for future investigations. This position paper provides a strategic framework to guide future research efforts, inform prioritization by funders and policymakers, and foster coordinated collaboration across stakeholders. By advancing these priorities, the epilepsy research community aims to improve patient care, reduce health disparities, and develop innovative solutions to address the complexities of epilepsy. This position paper, developed by the European Reference Network for Rare and Complex Epilepsies (EpiCARE) in collaboration with its Patient Advocacy Group, defines six areas of research priorities in epilepsy. Each section describes key challenges, current knowledge, and areas for improvement. They focus on preventing epilepsy, developing targeted therapies, improving surgery and clinical trials, using artificial intelligence to support diagnosis, and addressing comorbidities such as cognition, sleep, and overall health. Each provides a roadmap for clinicians and researchers to guide their research projects within their areas of expertise. Collectively, these priorities converge on actions for improving diagnosis, treatment, and patient outcomes through European collaboration and sustainable research efforts.

Background and Clinical Significance: Patients with Hodgkin lymphoma (HL) often present with lymphadenopathy, biochemical inflammation, and constitutional symptoms, but may experience symptoms from extra-nodal organs. Symptoms are caused by either lymphoma or a paraneoplastic phenomenon but overt central nervous system (CNS) involvement in HL is very uncommon. However, in rare cases, paraneoplastic neuro-ophthalmologic manifestations occur. Case Presentation: This case report describes a young female diagnosed with HL initially presenting with visual loss, reduced visual field, impaired balance, and sensory disturbances but no evidence of CNS-lymphoma. After treatment with bleomycin, etoposide, adriamycin, cyclophosphamide, vincristine, procarbazine, and prednisolone (escalated BEACOPP), she experienced full recovery of all neurological and ophthalmological symptoms. She experienced complete remission without any signs of relapse at follow-up after 2.5 years. Paraneoplastic cerebellar degeneration (PCD) related to HL have been described as a rare neurological syndrome, with varying neurological symptoms preceding the diagnosis of HL. PCD is typically associated with anti-Tr antibodies. Despite being negative for anti-Tr antibodies in both serum and cerebrospinal fluid (CSF), the neuro-ophthalmologic symptoms were interpreted as a paraneoplastic phenomenon in HL resembling PCD. The exact pathophysiology in this case is unknown but might be associated with undetected antigens and T-cell-mediated autoimmunity because of the presence of non-malignant T-cells in the CSF. Conclusions: This manuscript describes a case of an atypical presentation of HL with neuro-ophthalmologic symptoms which fully recovered upon anti-lymphoma treatment. Because of the good prognosis, we aim to emphasize the awareness of rare cases of HL initially presenting such manifestations to avoid diagnostic delays.