69 research outputs found
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Phase I clinical trial of the Src inhibitor dasatinib with dacarbazine in metastatic melanoma.
BackgroundSrc inhibitors sensitise melanoma cells to chemotherapy in preclinical models. The combination of dasatinib and dacarbazine was tested in a phase I trial in melanoma.MethodsPatients had ECOG performance status 0-2 and normal organ function. Dacarbazine was administered on day 1 and dasatinib on day 2 through 19 of each 21-day cycle. Both were escalated from 50 mg b.i.d. of dasatinib and 800 mg m(-2) of dacarbazine. Available pre-treatment biopsies were sequenced for BRAF, NRAS, and C-Kit mutations.ResultsDose-limiting toxicity was reached at dasatinib 70 mg b.i.d./dacarbazine 1000 mg m(-2), and was predominantly haematological. In 29 patients receiving dasatinib 70 mg b.i.d., the objective response rate (ORR) was 13.8%, the clinical benefit rate (ORR+SD) was 72.4%, the 6-month progression-free survival (PFS) was 20.7%, and the 12-month overall survival (OS) was 34.5%. Two out of three patients who were wild type for BRAF, NRAS, and c-KIT mutations had confirmed partial responses, and one had a minor response.ConclusionThe recommended phase II dose is dasatinib 70 mg b.i.d with dacarbazine 800 mg m(-2). PFS and OS data for dasatinib at 70 mg b.i.d. with dacarbazine compared favourably with historical controls. Preliminary data support evaluating tumour mutation status further as a biomarker of response
Gap-filling carbon dioxide, water, energy, and methane fluxes in challenging ecosystems - Comparing between methods, drivers, and gap-lengths
Eddy covariance serves as one the most effective techniques for long-term monitoring of ecosystem fluxes, however long-term data integrations rely on complete timeseries, meaning that any gaps due to missing data must be reliably filled. To date, many gap-filling approaches have been proposed and extensively evaluated for mature and/or less actively managed ecosystems. Random forest regression (RFR) has been shown to be stable and perform better in these systems than alternative approaches, particularly when filling longer gaps. However, the performance of RFR gap filling remains less certain in more challenging ecosystems, e.g., actively managed agri-ecosystems and following recent land-use change due to management disturbances, ecosystems with relatively low fluxes due to low signal to noise ratios, or for trace gases other than carbon dioxide (e.g., methane).
In an extension to earlier work on gap filling global carbon dioxide, water, and energy fluxes, we assess the RFR approach for gap filling methane fluxes globally. We then investigate a range of gap-filling methodologies for carbon dioxide, water, energy, and methane fluxes in challenging ecosystems, including European managed pastures, Southeast Asian converted peatlands, and North American drylands.
Our findings indicate that RFR is a competent alternative to existing research standard gap-filling algorithms. The marginal distribution sampling (MDS) is still suggested for filling short ( 30 days) gaps in carbon dioxide fluxes and also for gap filling other fluxes (e.g. sensible heat, latent energy and methane). In addition, using RFR with globally available reanalysis environmental drivers is effective when measured drivers are unavailable. Crucially, RFR was able to reliably fill cumulative fluxes for gaps > 3 moths and, unlike other common approaches, key environment-flux responses were preserved in the gap-filled data
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Genomic Profiling of Childhood Tumor Patient-Derived Xenograft Models to Enable Rational Clinical Trial Design.
Accelerating cures for children with cancer remains an immediate challenge as a result of extensive oncogenic heterogeneity between and within histologies, distinct molecular mechanisms evolving between diagnosis and relapsed disease, and limited therapeutic options. To systematically prioritize and rationally test novel agents in preclinical murine models, researchers within the Pediatric Preclinical Testing Consortium are continuously developing patient-derived xenografts (PDXs)-many of which are refractory to current standard-of-care treatments-from high-risk childhood cancers. Here, we genomically characterize 261 PDX models from 37 unique pediatric cancers; demonstrate faithful recapitulation of histologies and subtypes; and refine our understanding of relapsed disease. In addition, we use expression signatures to classify tumors for TP53 and NF1 pathway inactivation. We anticipate that these data will serve as a resource for pediatric oncology drug development and will guide rational clinical trial design for children with cancer
CO2 fluxes from three different temperate grazed pastures using Eddy covariance measurements
Grasslands cover around 25% of the global ice-free land surface, they are used predominantly for forage and livestock production and are considered to contribute significantly to soil carbon (C) sequestration. Recent investigations into using ‘nature-based solutions’ to limit warming to <2 °C suggest up to 25% of GHG mitigation might be achieved through changes to grassland management. In this study we evaluate pasture management interventions at the Rothamsted Research North Wyke Farm Platform, under commercial farming conditions, over two years and consider their impacts on net CO2 exchange. We investigate if our permanent pasture system (PP) is, in the short-term, a net sink for CO2 and whether reseeding this with deep-rooting, high-sugar grass (HS) or a mix of high-sugar grass and clover (HSC) might increase the net removal of atmospheric CO2. In general CO2 fluxes were less variable in 2018 than in 2017 while overall we found that net CO2 fluxes for the PP treatment changed from a sink in 2017 (−5.40 t CO2 ha−1 y−1) to a source in 2018 (6.17 t CO2 ha−1 y−1), resulting in an overall small source of 0.76 t CO2 ha−1 over the two years for this treatment. HS showed a similar trend, changing from a net sink in 2017 (−4.82 t CO2 ha−1 y−1) to a net source in 2018 (3.91 t CO2 ha−1 y−1) whilst the HSC field was a net source in both years (3.92 and 4.10 t CO2 ha−1 y−1, respectively). These results suggested that pasture type has an influence in the atmospheric CO2 balance and our regression modelling supported this conclusion, with pasture type and time of the year (and their interaction) being significant factors in predicting fluxes
Carbohydrate Recognition by an Architecturally Complex α-N-Acetylglucosaminidase from Clostridium perfringens
CpGH89 is a large multimodular enzyme produced by the human and animal pathogen Clostridium perfringens. The catalytic activity of this exo-α-d-N-acetylglucosaminidase is directed towards a rare carbohydrate motif, N-acetyl-β-d-glucosamine-α-1,4-d-galactose, which is displayed on the class III mucins deep within the gastric mucosa. In addition to the family 89 glycoside hydrolase catalytic module this enzyme has six modules that share sequence similarity to the family 32 carbohydrate-binding modules (CBM32s), suggesting the enzyme has considerable capacity to adhere to carbohydrates. Here we suggest that two of the modules, CBM32-1 and CBM32-6, are not functional as carbohydrate-binding modules (CBMs) and demonstrate that three of the CBMs, CBM32-3, CBM32-4, and CBM32-5, are indeed capable of binding carbohydrates. CBM32-3 and CBM32-4 have a novel binding specificity for N-acetyl-β-d-glucosamine-α-1,4-d-galactose, which thus complements the specificity of the catalytic module. The X-ray crystal structure of CBM32-4 in complex with this disaccharide reveals a mode of recognition that is based primarily on accommodation of the unique bent shape of this sugar. In contrast, as revealed by a series of X-ray crystal structures and quantitative binding studies, CBM32-5 displays the structural and functional features of galactose binding that is commonly associated with CBM family 32. The functional CBM32s that CpGH89 contains suggest the possibility for multivalent binding events and the partitioning of this enzyme to highly specific regions within the gastrointestinal tract
Perennial biomass cropping and use: Shaping the policy ecosystem in European countries
Demand for sustainably produced biomass is expected to increase with the need to provide renewable commodities, improve resource security and reduce greenhouse gas emissions in line with COP26 commitments. Studies have demonstrated additional environmental benefits of using perennial biomass crops (PBCs), when produced appropriately, as a feedstock for the growing bioeconomy, including utilisation for bioenergy (with or without carbon capture and storage). PBCs can potentially contribute to Common Agricultural Policy (CAP) (2023–27) objectives provided they are carefully integrated into farming systems and landscapes. Despite significant research and development (R&D) investment over decades in herbaceous and coppiced woody PBCs, deployment has largely stagnated due to social, economic and policy uncertainties. This paper identifies the challenges in creating policies that are acceptable to all actors. Development will need to be informed by measurement, reporting and verification (MRV) of greenhouse gas emissions reductions and other environmental, economic and social metrics. It discusses interlinked issues that must be considered in the expansion of PBC production: (i) available land; (ii) yield potential; (iii) integration into farming systems; (iv) R&D requirements; (v) utilisation options; and (vi) market systems and the socio-economic environment. It makes policy recommendations that would enable greater PBC deployment: (1) incentivise farmers and land managers through specific policy measures, including carbon pricing, to allocate their less productive and less profitable land for uses which deliver demonstrable greenhouse gas reductions; (2) enable greenhouse gas mitigation markets to develop and offer secure contracts for commercial developers of verifiable low-carbon bioenergy and bioproducts; (3) support innovation in biomass utilisation value chains; and (4) continue long-term, strategic R&D and education for positive environmental, economic and social sustainability impacts
Kepler K2 Campaign 9: II. First space-based discovery of an exoplanet using microlensing
We report on the discovery of a bound exoplanetary microlensing event from a
blind search of data gathered from Campaign 9 of the Kepler K2 mission (K2C9).
K2-2016-BLG-0005Lb is a densely sampled, binary caustic-crossing microlensing
event with caustic entry and exit points that are resolved in the K2C9 data,
enabling the lens-source relative proper motion to be measured. We have fitted
a binary microlens model to the K2 dataset, and to simultaneous observations
from the Optical Gravitational Lensing Experiment (OGLE-IV),
Canada-France-Hawaii Telescope (CFHT), Microlensing Observations in
Astrophysics (MOA-2), the Korean Microlensing Telescope Network (KMTNet), and
the United Kingdom InfraRed Telescope (UKIRT). Whilst the ground-based data
only sparsely sample the binary caustic, they provide a clear detection of
parallax that allows us to break completely the microlensing
mass-position-velocity degeneracy and measure the planet's mass directly. We
find a host mass of and a planetary mass of . The system lies at a distance of kpc from
Earth towards the Galactic bulge. The projected physical separation of the
planet from its host is found to be au which, for circular
orbits, corresponds to au and period yr, making K2-2016-BLG-0005Lb a close Jupiter analogue. Though
previous exoplanet microlensing events have included space-based data, this
event is the first bound microlensing exoplanet to be discovered from
space-based data. Even through a space telescope not designed for microlensing
studies, this result highlights the advantages for exoplanet microlensing
discovery that come from continuous, high-cadence temporal sampling that is
possible from space. (Abridged).Comment: 17 pages. Submitted to MNRA
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<i>Kepler K2</i> Campaign 9: II. First space-based discovery of an exoplanet using microlensing
We present K2-2016-BLG-0005Lb, a densely sampled, planetary binary caustic-crossing microlensing event found from a blind search of data gathered from Campaign 9 of the Kepler K2 mission (K2C9). K2-2016-BLG-0005Lb is the first bound microlensing exoplanet discovered from space-based data. The event has caustic entry and exit points that are resolved in the K2C9 data, enabling the lens–source relative proper motion to be measured. We have fitted a binary microlens model to the Kepler data, and to simultaneous observations from multiple ground-based surveys. Whilst the ground-based data only sparsely sample the binary caustic, they provide a clear detection of parallax that allows us to break completely the microlensing mass–position–velocity degeneracy and measure the planet’s mass directly. We find a host mass of 0.58 ± 0.04M⊙ and a planetary mass of 1.1 ± 0.1MJ. The system lies at a distance of 5.2 ± 0.2 kpc from Earth towards the Galactic bulge, more than twice the distance of the previous most distant planet found by Kepler. The sky-projected separation of the planet from its host is found to be 4.2 ± 0.3 au which, for circular orbits, deprojects to a host separation au and orbital period yr. This makes K2-2016-BLG-0005MLb a close Jupiter analogue orbiting a low-mass host star. According to current planet formation models, this system is very close to the host mass threshold below which Jupiters are not expected to form. Upcoming space-based exoplanet microlensing surveys by NASA’s Nancy Grace Roman Space Telescope and, possibly, ESA’s Euclid mission, will provide demanding tests of current planet formation models
Breeding progress and preparedness for mass-scale deployment of perennial lignocellulosic biomass crops switchgrass, miscanthus, willow and poplar
Genetic improvement through breeding is one of the key approaches to increasing biomass supply. This paper documents the breeding progress to date for four perennial biomass crops (PBCs) that have high output–input energy ratios: namely Panicum virgatum (switchgrass), species of the genera Miscanthus (miscanthus), Salix (willow) and Populus (poplar). For each crop, we report on the size of germplasm collections, the efforts to date to phenotype and genotype, the diversity available for breeding and on the scale of breeding work as indicated by number of attempted crosses. We also report on the development of faster and more precise breeding using molecular breeding techniques. Poplar is the model tree for genetic studies and is furthest ahead in terms of biological knowledge and genetic resources. Linkage maps, transgenesis and genome editing methods are now being used in commercially focused poplar breeding. These are in development in switchgrass, miscanthus and willow generating large genetic and phenotypic data sets requiring concomitant efforts in informatics to create summaries that can be accessed and used by practical breeders. Cultivars of switchgrass and miscanthus can be seed-based synthetic populations, semihybrids or clones. Willow and poplar cultivars are commercially deployed as clones. At local and regional level, the most advanced cultivars in each crop are at technology readiness levels which could be scaled to planting rates of thousands of hectares per year in about 5 years with existing commercial developers. Investment in further development of better cultivars is subject to current market failure and the long breeding cycles. We conclude that sustained public investment in breeding plays a key role in delivering future mass-scale deployment of PBCs
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