Trial of spesolimab for generalized pustular psoriasis.

BACKGROUND: Generalized pustular psoriasis (GPP) is a rare, life-threatening, inflammatory skin disease characterized by widespread eruption of sterile pustules. Interleukin-36 signaling is involved in the pathogenesis of this disorder. Spesolimab, a humanized anti–interleukin-36 receptor monoclonal antibody, is being studied for the treatment of GPP flares. METHODS: In a phase 2 trial, we randomly assigned patients with a GPP flare in a 2:1 ratio to receive a single 900-mg intravenous dose of spesolimab or placebo. Patients in both groups could receive an open-label dose of spesolimab on day 8, an open-label dose of spesolimab as a rescue medication after day 8, or both and were followed to week 12. The primary end point was a Generalized Pustular Psoriasis Physician Global Assessment (GPPGA) pustulation subscore of 0 (range, 0 [no visible pustules] to 4 [severe pustulation]) at the end of week 1. The key secondary end point was a GPPGA total score of 0 or 1 (clear or almost clear skin) at the end of week 1; scores range from 0 to 4, with higher scores indicating greater disease severity. RESULTS: A total of 53 patients were enrolled: 35 were assigned to receive spesolimab and 18 to receive placebo. At baseline, 46% of the patients in the spesolimab group and 39% of those in the placebo group had a GPPGA pustulation subscore of 3, and 37% and 33%, respectively, had a pustulation subscore of 4. At the end of week 1, a total of 19 of 35 patients (54%) in the spesolimab group had a pustulation subscore of 0, as compared with 1 of 18 patients (6%) in the placebo group (difference, 49 percentage points; 95% confidence interval [CI], 21 to 67; P<0.001). A total of 15 of 35 patients (43%) had a GPPGA total score of 0 or 1, as compared with 2 of 18 patients (11%) in the placebo group (difference, 32 percentage points; 95% CI, 2 to 53; P=0.02). Drug reactions were reported in 2 patients who received spesolimab, in 1 of them concurrently with a drug-induced hepatic injury. Among patients assigned to the spesolimab group, infections occurred in 6 of 35 (17%) through the first week; among patients who received spesolimab at any time in the trial, infections had occurred in 24 of 51 (47%) at week 12. Antidrug antibodies were detected in 23 of 50 patients (46%) who received at least one dose of spesolimab. CONCLUSIONS: In a phase 2 randomized trial involving patients with GPP, the interleukin-36 receptor inhibitor spesolimab resulted in a higher incidence of lesion clearance at 1 week than placebo but was associated with infections and systemic drug reactions. Longer and larger trials are warranted to determine the effect and risks of spesolimab in patients with pustular psoriasis. (Funded by Boehringer Ingelheim; Effisayil 1 ClinicalTrials.gov number, NCT03782792.

Impact of regular magnetic resonance imaging follow-up after stereotactic radiotherapy to the surgical cavity in patients with one to three brain metastases

Abstract Background Administering stereotactic radiotherapy to the surgical cavity and thus omitting postoperative whole brain radiotherapy (WBRT) is a favored strategy in limited metastatic brain disease. Little is known about the impact of regular magnetic resonance imaging follow-up (MRI FU) in such patient cohorts. The aim of this study is to examine the impact of regular MRI FU and to report the oncological outcomes of patients with one to three brain metastases (BMs) treated with stereotactic radiosurgery (SRS) or hypo-fractionated stereotactic radiotherapy (HFSRT) to the surgical cavity. Methods We retrospectively analyzed patients who received SRS or HFSRT to the surgical cavity after resection of one to two BMs. Additional, non-resected BMs were managed with SRS alone. Survival was estimated by the Kaplan-Meier method. Prognostic factors were examined with the log-rank test and Cox proportional hazards model. Regular MRI FU was defined as performing a brain MRI 3 months after radiotherapy (RT) and/or performing ≥1 brain MRI per 180 days. Primary endpoint was local control (LC). Secondary endpoints were distant brain control (DBC), overall survival (OS) and the correlation between regular MRI FU and overall survival (OS), symptom-free survival (SFS), deferment of WBRT and WBRT-free survival (WFS). Results Overall, 75 patients were enrolled. One, 2 and 3 BMs were seen in 63 (84%), 11 (15%) and 1 (1%) patients, respectively. Forty (53%) patients underwent MRI FU 3 months after RT and 38 (51%) patients received ≥1 brain MRI per 180 days. Median OS was 19.4 months (95% CI: 13.2–25.6 months). Actuarial LC, DBC and OS at 1 year were 72% (95% CI: 60–83%), 60% (95% CI: 48–72%) and 66% (95% CI: 53–76%), respectively. A planning target volume > 15 cm3 (p = 0.01), Graded Prognostic Assessment (GPA) score (p = 0.001) and residual tumor after surgery (p = 0.008) were prognostic for decreased OS in multivariate analysis. No significant correlation between MRI FU at 3 months and OS (p = 0.462), SFS (p = 0.536), WFS (p = 0.407) or deferment of WBRT (p = 0.955) was seen. Likewise, performing ≥1 MRI per 180 days had no significant impact on OS (p = 0.954), SFS (p = 0.196), WFS (p = 0.308) or deferment of WBRT (p = 0.268). Conclusion Our results regarding oncological outcomes consist with the current data from the literature. Surprisingly, regular MRI FU did not result in increased OS, SFS, WFS or deferment of WBRT in our cohort consisting mainly of patients with a single and resected BM. Therefore, the impact of regular MRI FU needs prospective evaluation. Trial registration Project ID: 2017–00033, retrospectively registered

Eco-Friendly Nitrogen-Doped Graphene Preparation and Design for the Oxygen Reduction Reaction

Four N-doped graphene materials with a nitrogen content ranging from 8.34 to 13.1 wt.% are prepared by the ball milling method. This method represents an eco-friendly mechanochemical process that can be easily adapted for industrial-scale productivity and allows both the exfoliation of graphite and the synthesis of large quantities of functionalized graphene. These materials are characterized by transmission and scanning electron microscopy, thermogravimetry measurements, X-ray powder diffraction, X-ray photoelectron and Raman spectroscopy, and then, are tested towards the oxygen reduction reaction by cyclic voltammetry and rotating disk electrode methods. Their responses towards ORR are analysed in correlation with their properties and use for the best ORR catalyst identification. However, even though the mechanochemical procedure and the characterization techniques are clean and green methods (i.e., water is the only solvent used for these syntheses and investigations), they are time consuming and, generally, a low number of materials can be prepared, characterized and tested. In order to eliminate some of these limitations, the use of regression learner and reverse engineering methods are proposed for facilitating the optimization of the synthesis conditions and the materials’ design. Thus, the machine learning algorithms are applied to data containing the synthesis parameters, the results obtained from different characterization techniques and the materials response towards ORR to quickly provide predictions that allow the best synthesis conditions or the best electrocatalysts’ identification

Generating linked-data based domain-specific sentiment lexicons from legacy language and semantic resources

We present a methodology for legacy language resource adaptation that generates domain-specific sentiment lexicons organized around domain entities described with lexical information and sentiment words described in the context of these entities. We explain the steps of the methodology and we give a working example of our initial results. The resulting lexicons are modelled as Linked Data resources by use of established formats for Linguistic Linked Data (lemon, NIF) and for linked sentiment expressions (Marl), thereby contributing and linking to existing Language Resources in the Linguistic Linked Open Data cloud. Keywords: domain specific lexicon, entity extraction and linking, sentiment analysisThis work has been funded by the European project EUROSENTIMENT under grant no. 296277