An open-label multi-center phase 1 safety study of BXQ-350 in children and young adults with relapsed solid tumors, including recurrent malignant brain tumors

BACKGROUND: BXQ-350 is a novel anti-neoplastic agent composed of saposin C (SapC) and phospholipid dioleoylphosphatidyl-serine sodium (DOPS) that selectively binds tumor cell phosphatidylserine (PS), inducing apoptosis. BXQ-350 has demonstrated preclinical antitumor effects in high-grade gliomas (HGG) and clinical activity in adult patients with recurrent HGG. METHODS: A phase 1 study was conducted in pediatric patients with relapsed/refractory solid tumors, including recurrent brain tumors. Primary objectives were to characterize safety and determine maximum tolerated dose (MTD) and preliminary antitumor activity. Sequential dose cohorts were assessed up to 3.2 mg/kg using an accelerated titration design. Each cycle was 28 days; dosing occurred on days 1-5, 8, 10, 12, 15, and 22 of cycle 1, and day 1 of subsequent cycles, until disease progression or toxicity. RESULTS: Nine patients, median age 10 years (range: 4-23), were enrolled. Seven patients (78%) had central nervous system (CNS) and two (22%) had non-CNS tumors. Eight patients completed cycle 1. No dose limiting toxicity (DLT) or BXQ-350-related serious adverse events (SAEs) were observed. Six patients experienced at least one adverse event (AE) considered possibly BXQ-350-related, most were grade ≤2. One patient with diffuse intrinsic pontine glioma experienced stable disease for 5 cycles. The study was terminated after part 1 to focus development on the frontline setting. CONCLUSION: No DLTs or BXQ-350-related SAEs were reported, and the maximal planned dose of 3.2 mg/kg IV was tolerable. Limited safety and efficacy data support continued BXQ-350 development in pediatric HGG; however, early discontinuations for progression suggest novel therapies be assessed at earlier disease stages

Stochastic and epistemic uncertainty propagation in LCA

Purpose: When performing uncertainty propagation, most LCA practitioners choose to represent uncertainties by single probability distributions and to propagate them using stochastic methods. However the selection of single probability distributions appears often arbitrary when faced with scarce information or expert judgement (epistemic uncertainty). Possibility theory has been developed over the last decades to address this problem. The objective of this study is to present a methodology that combines probability and possibility theories to represent stochastic and epistemic uncertainties in a consistent manner and apply it to LCA. A case study is used to show the uncertainty propagation performed with the proposed method and compare it to propagation performed using probability and possibility theories alone. Methods: Basic knowledge on the probability theory is first recalled, followed by a detailed description of hal-00811827, version 1- 11 Apr 2013 epistemic uncertainty representation using fuzzy intervals. The propagation methods used are the Monte Carlo analysis for probability distribution and an optimisation on alpha-cuts for fuzzy intervals. The proposed method (noted IRS) generalizes the process of random sampling to probability distributions as well as fuzzy intervals, thus making the simultaneous use of both representations possible

Search for supersymmetry in events with a photon, jets, b-jets, and missing transverse momentum in proton–proton collisions at 13 TeV

A search for supersymmetry is presented based on events with at least one photon, jets, and large missing transverse momentum produced in proton–proton collisions at a center-of-mass energy of 13TeV. The data correspond to an integrated luminosity of 35.9fb −1 and were recorded at the LHC with the CMS detector in 2016. The analysis characterizes signal-like events by categorizing the data into various signal regions based on the number of jets, the number of b-tagged jets, and the missing transverse momentum. No significant excess of events is observed with respect to the expectations from standard model processes. Limits are placed on the gluino and top squark pair production cross sections using several simplified models of supersymmetric particle production with gauge-mediated supersymmetry breaking. Depending on the model and the mass of the next-to-lightest supersymmetric particle, the production of gluinos with masses as large as 2120GeV and the production of top squarks with masses as large as 1230GeV are excluded at 95% confidence level

Search for supersymmetry in events with a photon, jets, b-jets, and missing transverse momentum in proton-proton collisions at 13TeV

A search for supersymmetry is presented based on events with at least one photon, jets, and large missing transverse momentum produced in proton-proton collisions at a center-of-mass energy of 13 TeV. The data correspond to an integrated luminosity of 35.9 fb -1 and were recorded at the LHC with the CMS detector in 2016. The analysis characterizes signal-like events by categorizing the data into various signal regions based on the number of jets, the number of b-tagged jets, and the missing transverse momentum. No significant excess of events is observed with respect to the expectations from standard model processes. Limits are placed on the gluino and top squark pair production cross sections using several simplified models of supersymmetric particle production with gauge-mediated supersymmetry breaking. Depending on the model and the mass of the nextto-lightest supersymmetric particle, the production of gluinos with masses as large as 2120 GeV and the production of top squarks with masses as large as 1230 GeV are excluded at 95% confidence level.Peer reviewe

BIOFRAG: A new database for analysing BIOdiversity responses to forest FRAGmentation

Habitat fragmentation studies are producing inconsistent and complex results across which it is nearly impossible to synthesise. Consistent analytical techniques can be applied to primary datasets, if stored in a flexible database that allows simple data retrieval for subsequent analyses. Method: We developed a relational database linking data collected in the field to taxonomic nomenclature, spatial and temporal plot attributes and further environmental variables (e.g. information on biogeographic region. Typical field assessments include measures of biological variables (e.g. presence, abundance, ground cover) of one species or a set of species linked to a set of plots in fragments of a forested landscape. Conclusion: The database currently holds records of 5792 unique species sampled in 52 landscapes in six of eight biogeographic regions: mammals 173, birds 1101, herpetofauna 284, insects 2317, other arthropods: 48, plants 1804, snails 65. Most species are found in one or two landscapes, but some are found in four. Using the huge amount of primary data on biodiversity response to fragmentation becomes increasingly important as anthropogenic pressures from high population growth and land demands are increasing. This database can be queried to extract data for subsequent analyses of the biological response to forest fragmentation with new metrics that can integrate across the components of fragmented landscapes. Meta-analyses of findings based on consistent methods and metrics will be able to generalise over studies allowing inter-comparisons for unified answers. The database can thus help researchers in providing findings for analyses of trade-offs between land use benefits and impacts on biodiversity and to track performance of management for biodiversity conservation in human-modified landscapes.Fil: Pfeifer, Marion. Imperial College London; Reino UnidoFil: Lefebvre, Veronique. Imperial College London; Reino UnidoFil: Gardner, Toby A.. Stockholm Environment Institute; SueciaFil: Arroyo Rodríguez, Víctor. Universidad Nacional Autónoma de México; MéxicoFil: Baeten, Lander. University of Ghent; BélgicaFil: Banks Leite, Cristina. Imperial College London; Reino UnidoFil: Barlow, Jos. Lancaster University; Reino UnidoFil: Betts, Matthew G.. State University of Oregon; Estados UnidosFil: Brunet, Joerg. Swedish University of Agricultural Sciences; SueciaFil: Cerezo Blandón, Alexis Mauricio. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Métodos Cuantitativos y Sistemas de Información; ArgentinaFil: Cisneros, Laura M.. University of Connecticut; Estados UnidosFil: Collard, Stuart. Nature Conservation Society of South Australia; AustraliaFil: D´Cruze, Neil. The World Society for the Protection of Animals; Reino UnidoFil: Da Silva Motta, Catarina. Ministério da Ciência, Tecnologia, Inovações. Instituto Nacional de Pesquisas da Amazônia; BrasilFil: Duguay, Stephanie. Carleton University; CanadáFil: Eggermont, Hilde. University of Ghent; BélgicaFil: Eigenbrod, Félix. University of Southampton; Reino UnidoFil: Hadley, Adam S.. State University of Oregon; Estados UnidosFil: Hanson, Thor R.. No especifíca;Fil: Hawes, Joseph E.. University of East Anglia; Reino UnidoFil: Heartsill Scalley, Tamara. United State Department of Agriculture. Forestry Service; Puerto RicoFil: Klingbeil, Brian T.. University of Connecticut; Estados UnidosFil: Kolb, Annette. Universitat Bremen; AlemaniaFil: Kormann, Urs. Universität Göttingen; AlemaniaFil: Kumar, Sunil. State University of Colorado - Fort Collins; Estados UnidosFil: Lachat, Thibault. Swiss Federal Institute for Forest; SuizaFil: Lakeman Fraser, Poppy. Imperial College London; Reino UnidoFil: Lantschner, María Victoria. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca; Argentina. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Patagonia Norte. Estación Experimental Agropecuaria San Carlos de Bariloche; ArgentinaFil: Laurance, William F.. James Cook University; AustraliaFil: Leal, Inara R.. Universidade Federal de Pernambuco; BrasilFil: Lens, Luc. University of Ghent; BélgicaFil: Marsh, Charles J.. University of Leeds; Reino UnidoFil: Medina Rangel, Guido F.. Universidad Nacional de Colombia; ColombiaFil: Melles, Stephanie. University of Toronto; CanadáFil: Mezger, Dirk. Field Museum of Natural History; Estados UnidosFil: Oldekop, Johan A.. University of Sheffield; Reino UnidoFil: Overal , Williams L.. Museu Paraense Emílio Goeldi. Departamento de Entomologia; BrasilFil: Owen, Charlotte. Imperial College London; Reino UnidoFil: Peres, Carlos A.. University of East Anglia; Reino UnidoFil: Phalan, Ben. University of Southampton; Reino UnidoFil: Pidgeon, Anna Michle. University of Wisconsin; Estados UnidosFil: Pilia, Oriana. Imperial College London; Reino UnidoFil: Possingham, Hugh P.. Imperial College London; Reino Unido. The University Of Queensland; AustraliaFil: Possingham, Max L.. No especifíca;Fil: Raheem, Dinarzarde C.. Royal Belgian Institute of Natural Sciences; Bélgica. Natural History Museum; Reino UnidoFil: Ribeiro, Danilo B.. Universidade Federal do Mato Grosso do Sul; BrasilFil: Ribeiro Neto, Jose D.. Universidade Federal de Pernambuco; BrasilFil: Robinson, Douglas W.. State University of Oregon; Estados UnidosFil: Robinson, Richard. Manjimup Research Centre; AustraliaFil: Rytwinski, Trina. Carleton University; CanadáFil: Scherber, Christoph. Universität Göttingen; AlemaniaFil: Slade, Eleanor M.. University of Oxford; Reino UnidoFil: Somarriba, Eduardo. Centro Agronómico Tropical de Investigación y Enseñanza; Costa RicaFil: Stouffer, Philip C.. State University of Louisiana; Estados UnidosFil: Struebig, Matthew J.. University of Kent; Reino UnidoFil: Tylianakis, Jason M.. University College London; Estados Unidos. Imperial College London; Reino UnidoFil: Teja, Tscharntke. Universität Göttingen; AlemaniaFil: Tyre, Andrew J.. Universidad de Nebraska - Lincoln; Estados UnidosFil: Urbina Cardona, Jose N.. Pontificia Universidad Javeriana; ColombiaFil: Vasconcelos, Heraldo L.. Universidade Federal de Uberlandia; BrasilFil: Wearn, Oliver. Imperial College London; Reino Unido. The Zoological Society of London; Reino UnidoFil: Wells, Konstans. University of Adelaide; AustraliaFil: Willig, Michael R.. University of Connecticut; Estados UnidosFil: Wood, Eric. University of Wisconsin; Estados UnidosFil: Young, Richard P.. Durrell Wildlife Conservation Trust; Reino UnidoFil: Bradley, Andrew V.. Imperial College London; Reino UnidoFil: Ewers, Robert M.. Imperial College London; Reino Unid

Beyond the Pharmacopoeia: To what extent is trade for “TCM” limited to official TCM taxa?

The global trade in wildlife affects ~24% of terrestrial vertebrates, and demand for traditional medicinal materials, especially for traditional Chinese medicine, is a high profile driver. At present the relative extent to which demand for wild-animal-origin medicinal materials arises from different markets (OTCM, zhongyi and CMP, see companion paper) within "TCM" is unknown. We wished to populate the above categories, revealing the numbers and types of species involved, to provide the first consolidated description of the diversity of animal species potentially able to be used for different facets of "TCM”, an overview of their conservation status, and an initial estimate of the degree to which existing trade feeds into these different facets of "TCM”. We found that the number and diversity of wild-animal-origin medicinal materials listed as available for use in "TCM" differ markedly between the Pharmacopoeia of the People’s Republic of China (representing OTCM) - which currently lists 70 wild species - and the Medical Fauna of China, representing zhongyi - which lists 2275 animal species. Our findings indicated a substantial trade - both imports to, and exports from China - of "TCM" medicinal materials from wild animal taxa listed in the Medical Fauna of China but not listed in the Pharmacopoeia, and also of species for which there is no prior textual support, including species potentially being traded as substitutes for listed species. We recommend working with TCM practitioners to enact the targeted substitution of sustainably sourced plant-based medicinal materials for the currently-used animal-origin materials. We suggest that this should initially target the 70 OTCM species, as well as inferred OTCM species and selected genera likely to be imported as substitutes, to strike a balance between keeping the focus of the required research narrow, while targeting the taxa most likely to be traded

GELATIN DRYING PROCESS

In one of the stages of the gelatin production process, a highly concentrated solution of gel is cooled and extruded to form gelatin noodles, which are then laid on a drying belt. Gelatin is a molecular colloid that is not porous under these drying conditions, and as a consequence, water migration occurs solely by diffusive processes. To achieve a commercial standard of dryness, the dependence of the diffusion coefficient as a function of temperature is used. This set of circumstances favors the appearance of sharp concentration gradients inside the gel. In a numerical simulation of the drying process these characteristics create difficult conditions for use of the traditional methods for solution of time-dependent partial differential equation models. This paper evaluates an implementation of the boundary element method to determine surface conditions of the gelatin particle