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Therapeutic targeting of angiogenesis in glioblastoma has yielded mixed outcomes. Investigation of tumor-associated angiogenesis has focused on the factors that stimulate the sprouting, migration, and hyperproliferation of the endothelial cells. However, little is known regarding the processes underlying the formation of the tumor-associated vessels. To address this issue, we investigated vessel formation in CD31 + cells isolated from human glioblastoma tumors. The results indicate that overexpression of integrin α3β1 plays a central role in the promotion of tube formation in the tumor-associated endothelial cells in glioblastoma. Blocking α3β1 function reduced sprout and tube formation in the tumor-associated endothelial cells and vessel density in organotypic cultures of glioblastoma. The data further suggest a mechanistic model in which integrin α3β1-promoted calcium influx stimulates macropinocytosis and directed maturation of the macropinosomes in a manner that promotes lysosomal exocytosis during nascent lumen formation. Altogether, our data indicate that integrin α3β1 may be a therapeutic target on the glioblastoma vasculature. Tumour-associated angiogenesis facilitates the growth of tumours. Here the authors show that integrin α3β1 promotes blood vessel formation in glioblastoma through calcium-mediated macropinocytosis and lysosomal exocytosis.

Diabetic peripheral neuropathic pain (DPNP) is common and often distressing. Most guidelines recommend amitriptyline, duloxetine, pregabalin, or gabapentin as initial analgesic treatment for DPNP, but there is little comparative evidence on which one is best or whether they should be combined. We aimed to assess the efficacy and tolerability of different combinations of first-line drugs for treatment of DPNP. OPTION-DM was a multicentre, randomised, double-blind, crossover trial in patients with DPNP with mean daily pain numerical rating scale (NRS) of 4 or higher (scale is 0–10) from 13 UK centres. Participants were randomly assigned (1:1:1:1:1:1), with a predetermined randomisation schedule stratified by site using permuted blocks of size six or 12, to receive one of six ordered sequences of the three treatment pathways: amitriptyline supplemented with pregabalin (A-P), pregabalin supplemented with amitriptyline (P-A), and duloxetine supplemented with pregabalin (D-P), each pathway lasting 16 weeks. Monotherapy was given for 6 weeks and was supplemented with the combination medication if there was suboptimal pain relief (NRS >3), reflecting current clinical practice. Both treatments were titrated towards maximum tolerated dose (75 mg per day for amitriptyline, 120 mg per day for duloxetine, and 600 mg per day for pregabalin). The primary outcome was the difference in 7-day average daily pain during the final week of each pathway. This trial is registered with ISRCTN, ISRCTN17545443. Between Nov 14, 2017, and July 29, 2019, 252 patients were screened, 140 patients were randomly assigned, and 130 started a treatment pathway (with 84 completing at least two pathways) and were analysed for the primary outcome. The 7-day average NRS scores at week 16 decreased from a mean 6·6 (SD 1·5) at baseline to 3·3 (1·8) at week 16 in all three pathways. The mean difference was –0·1 (98·3% CI –0·5 to 0·3) for D-P versus A-P, –0·1 (–0·5 to 0·3) for P-A versus A-P, and 0·0 (–0·4 to 0·4) for P-A versus D-P, and thus not significant. Mean NRS reduction in patients on combination therapy was greater than in those who remained on monotherapy (1·0 [SD 1·3] vs 0·2 [1·5]). Adverse events were predictable for the monotherapies: we observed a significant increase in dizziness in the P-A pathway, nausea in the D-P pathway, and dry mouth in the A-P pathway. To our knowledge, this was the largest and longest ever, head-to-head, crossover neuropathic pain trial. We showed that all three treatment pathways and monotherapies had similar analgesic efficacy. Combination treatment was well tolerated and led to improved pain relief in patients with suboptimal pain control with a monotherapy. National Institute for Health Research (NIHR) Health Technology Assessment programme.

The Deepwater Horizon disaster released more than 636 million L of crude oil into the northern Gulf of Mexico. The spill oiled upper surface water spawning habitats for many commercially and ecologically important pelagic fish species. Consequently, the developing spawn (embryos and larvae) of tunas, swordfish, and other large predators were potentially exposed to crude oil-derived polycyclic aromatic hydrocarbons (PAHs). Fish embryos are generally very sensitive to PAH-induced cardiotoxicity, and adverse changes in heart physiology and morphology can cause both acute and delayed mortality. Cardiac function is particularly important for fast-swimming pelagic predators with high aerobic demand. Offspring for these species develop rapidly at relatively high temperatures, and their vulnerability to crude oil toxicity is unknown. We assessed the impacts of field-collected Deepwater Horizon (MC252) oil samples on embryos of three pelagic fish: bluefin tuna, yellowfin tuna, and an amberjack. We show that environmentally realistic exposures (1–15 µg/L total PAH) cause specific dose-dependent defects in cardiac function in all three species, with circulatory disruption culminating in pericardial edema and other secondary malformations. Each species displayed an irregular atrial arrhythmia following oil exposure, indicating a highly conserved response to oil toxicity. A considerable portion of Gulf water samples collected during the spill had PAH concentrations exceeding toxicity thresholds observed here, indicating the potential for losses of pelagic fish larvae. Vulnerability assessments in other ocean habitats, including the Arctic, should focus on the developing heart of resident fish species as an exceptionally sensitive and consistent indicator of crude oil impacts.

The FGFR1 gene encoding fibroblast growth factor receptor 1 has emerged as a frequently altered oncogene in the pathogenesis of multiple low-grade neuroepithelial tumor (LGNET) subtypes including pilocytic astrocytoma, dysembryoplastic neuroepithelial tumor (DNT), rosette-forming glioneuronal tumor (RGNT), and extraventricular neurocytoma (EVN). These activating FGFR1 alterations in LGNET can include tandem duplication of the exons encoding the intracellular tyrosine kinase domain, in-frame gene fusions most often with TACC1 as the partner, or hotspot missense mutations within the tyrosine kinase domain (either at p.N546 or p.K656). However, the specificity of these different FGFR1 events for the various LGNET subtypes and accompanying genetic alterations are not well defined. Here we performed comprehensive genomic and epigenomic characterization on a diverse cohort of 30 LGNET with FGFR1 alterations. We identified that RGNT harbors a distinct epigenetic signature compared to other LGNET with FGFR1 alterations, and is uniquely characterized by FGFR1 kinase domain hotspot missense mutations in combination with either PIK3CA or PIK3R1 mutation, often with accompanying NF1 or PTPN11 mutation. In contrast, EVN harbors its own distinct epigenetic signature and is characterized by FGFR1 - TACC1 fusion as the solitary pathogenic alteration. Additionally, DNT and pilocytic astrocytoma are characterized by either kinase domain tandem duplication or hotspot missense mutations, occasionally with accompanying NF1 or PTPN11 mutation, but lacking the accompanying PIK3CA or PIK3R1 mutation that characterizes RGNT. The glial component of LGNET with FGFR1 alterations typically has a predominantly oligodendroglial morphology, and many of the pilocytic astrocytomas with FGFR1 alterations lack the biphasic pattern, piloid processes, and Rosenthal fibers that characterize pilocytic astrocytomas with BRAF mutation or fusion. Together, this analysis improves the classification and histopathologic stratification of LGNET with FGFR1 alterations.

Land surface models (LSMs) are essential tools for simulating the coupled climate system, representing the dynamics of water, energy, and carbon fluxes on land and their interaction with the atmosphere. However, parameterizing sub‐grid processes at the scales relevant to climate models (∼${\\sim} $ 10–100 km) remains a considerable challenge. The parameterizations typically have a large number of unknown and often correlated parameters, making calibration and uncertainty quantification difficult. Moreover, many existing LSMs are not readily adaptable to the incorporation of modern machine learning (ML) parameterizations trained with in situ and satellite data. This article presents the first version of ClimaLand, a new LSM designed for overcoming these limitations, including a description of the core equations underlying the model, the results of an extensive set of validation exercises, and an assessment of the computational performance of the model. We show that ClimaLand can leverage graphics processing units for computational efficiency, and that its modular architecture and high‐level programming language, Julia, allows for integration with ML libraries. In the future, this will enable efficient simulation, calibration, and uncertainty quantification with ClimaLand. Plain Language Summary Simulating the Earth's atmosphere, ocean, and land surface is an important method that scientists use for understanding the Earth's climate, including its response to climate change. Due the complexity of the processes involved, approximations are made when representing certain aspects of the land surface, such as vegetation heterogeneity or topographical variation. These approximations can be improved by using data (“calibration”), but doing so has a large computational cost. They can also be improved using machine learning (ML), but this requires models to be easily integrated with ML packages. ClimaLand is a new land surface model which has been designed from the start to incorporate ML parameterizations and to more efficiently calibrate parameterizations with data. This article presents the ClimaLand model, benchmarks its computational performance, and compares model output against data in a variety of regimes. Follow‐on studies will improve the core model using ML parameterizations and by calibrating the model. Key Points ClimaLand, a land surface model, simulates energy, water, and carbon fluxes within and across soil, canopy and snow components The soil model simulates flow and phase changes of water in both saturated and unsaturated zones The model runs natively on graphics processing units and is designed to enable the inclusion of data‐driven parameterizations

Abstract INTRODUCTION We examined the procedural safety and length of hospital stay for patients who underwent stereotactic laser ablation (SLA). METHODS Patients undergoing stereotactic laser ablation were prospectively enrolled in the Laser Ablation of Abnormal Neurological Tissue using Robotic Neuroblate System (LAANTERN) registry. Data from the first 100 enrolled patients are presented. RESULTS >The demographic of the patient cohort consisted of 58% females and 42% males. The mean age and KPS of the cohort were 51 (±17) years and 83 (±15), respectively. 87% of the SLA-treated patients had undergone prior surgical or radiation treatment. In terms of indications, 84% of the SLAs were performed as treatment for brain tumor and 16% were performed as treatment for epilepsy. In terms of the procedure, 79% of the SLA patients underwent treatment of a single lesion. In 72% of the SLA treated patients, >90% of the target lesion was ablated. The average procedural time was 188.2 minutes (range: 48–368 minutes). The average blood loss per procedure was 17.7 cc (range: 0–300cc). In terms of hospitalization, the average length of Intensive Care stay was 38.1 hours (range 0335). The number of hours post-procedure before patient discharge was 61.1 hours (range 6–612). 85% of the patients were discharged home. There were 15 adverse events at the one-month follow-up (12%), with two events definitively related to the procedure (2%), including one patient with post-operative intraventricular hemorrhage and another with post-procedural gait compromise. CONCLUSION SLA is a minimally invasive procedure with favorable profile in terms of safety and hospital length of stay.

Abstract INTRODUCTION Stereotactic laser ablation (SLA) is a minimally invasive procedure that is increasingly utilized in neurosurgery. We wished to understand how this procedure is changing the landscape of treatment option for neurosurgical patients. METHODS Patients undergoing stereotactic laser ablation were prospectively enrolled in the LAANTERN registry. Data from the first 100 enrolled patients are presented here. RESULTS >Clinical indications for SLA include treatment of high grade gliomas (HGG, 40%), brain metastases (BM, 34%), epilepsy (17%), low grade gliomas (5%), and meningioma/other primary brain tumor (4%). For HGGs, SLA was equally likely used in the up-front (45%) or the recurrent setting (55%, P = 0.54). In contrast, SLA was predominantly used as treatment for BMs that failed radiation therapy/radiosurgery (91%), with only 9% of SLAs performed as up-front treatment for newly diagnosed lesions (P < 0.001). Of all SLAs performed in brain tumor patients, 42.9% of the procedures were performed in lieu of surgical resection, and 21% were performed because the lesion was not accessible through conventional neurosurgery. Time trend analysis comparing the first and the latter cohort of 50 enrolled patient revealed expanding oncologic applications of SLA beyond treatment of HGG and BM (P = 0.02). CONCLUSION HGGs and BMs are the leading indications for SLA in the LAANTERN study. For HGGs, SLA is equally likely used in the up-front or recurrent setting. For BMs, SLA is typically used in the recurrent setting. There is an evolving trend toward expanding oncologic applications of SLA beyond treatment of HGGs and BMs

Following publication of the original article [1], the authors reported an error in the spelling of one of the author names. In this Correction the incorrect and correct author names are indicated and the author name has been updated in the original publication. The authors also reported an error in the Methods section of the original article. In this Correction the incorrect and correct versions of the affected sentence are indicated. The original article has not been updated with regards to the error in the Methods section.

Purpose To determine the rate of progression of eyes with subclinical diabetic macular edema (DME) to clinically apparent DME or DME necessitating treatment during a 2-year period. Methods In all, 43 eyes from 39 study participants with subclinical DME, defined as absence of foveal center edema as determined with slit lamp biomicroscopy but a center point thickness (CPT) between 225 and 299  μ m on time domain (Stratus, Carl Zeiss Meditec) optical coherence tomography (OCT) scan, were enrolled from 891 eyes of 582 subjects screened. Eyes were evaluated annually for up to 2 years for the primary outcome, which was an increase in OCT CPT of at least 50  μ m from baseline and a CPT of at least 300  μ m, or treatment for DME (performed at the discretion of the investigator). Results The cumulative probability of meeting an increase in OCT CPT of at least 50  μ m from baseline and a CPT of at least 300  μ m, or treatment for DME was 27% (95% confidence interval (CI): 14%, 38%) by 1 year and 38% (95% CI: 23%, 50%) by 2 years. Conclusions Although subclinical DME may be uncommon, this study suggests that between approximately one-quarter and one-half of eyes with subclinical DME will progress to more definite thickening or be judged to need treatment for DME within 2 years after its identification.