Acute lymphoblastic leukaemia (ALL) things come to those who wait: 60 years of progress in the treatment of adult ALL

The UK has made a well‐recognised contribution to the international effort to understand and treat acute lymphoblastic leukaemia (ALL) in adults. Work done in the UK by numerous personnel over many years has been instrumental in developing novel risk stratifications, evaluating treatment strategies for adult patients with de novo and relapsed disease and in making novel scientific contributions. The UK has championed and achieved very high levels of recruitment to clinical trials and, in particular, is known for success in large, investigator‐initiated randomised controlled trials. This historical review charts the progress of clinical research in adult ALL from its inception to the present day

Electrochemical sensor based on epoxy-functionalized BEA nanozeolite and graphene oxide modified glassy carbon electrode for bisphenol E determination

An epoxy-functionalized beta type nanozeolite (BEA)/graphene oxide nanocomposite modified glassy carbon electrode (GCE/BEA/APTMS/GA/GO/NF) has been created for the differential pulse voltammetric determination of bisphenol E (BPE). The modified electrode presented an enhanced current response in comparison with bare GCE. A linear dependence of anodic peak current (Ip) and scan rate (ν) was observed, which showed that the electrochemical process was adsorption-controlled. Differential pulse voltammetry (DPV) was employed and optimized for the sensitive determination of BPE. Under the optimized conditions, the anodic peak current was linearly proportional to BPE concentration in the range between 0.07 and 4.81 µM, with a correlation coefficient of 0.995 and limit of detection 0.056 μM (S/N = 3). The electrode showed good repeatability and storage stability, and a low response to interfering compounds. Comparison was made to the determination of bisphenol A. To confirm the electrode analytical performance, recovery tests were performed, and deviations lower than 10% were found. The BEA zeolite-GO nanocomposite proved to be a promising sensing platform for bisphenol determination. Graphical abstract: [Figure not available: see fulltext.]

Ceibinin, a new positional isomer of mangiferin from the inflorescence of Ceiba pentandra (Bombacaceae), elicits similar antioxidant effect but no anti-inflammatory potential compared to mangiferin

Ceiba pentandra (L.) Gaertn. (Bombacaceae) is popular for the quality of its wood. However, its leaf, stem bark and root bark have been popular in ethnomedicine and, apart from the inflorescence, have been subject of extensive phytochemical investigations. In this study, two compounds were isolated from the crude methanol extract of the inflorescence. Through data from UV, NMR, MS, electrochemical studies, differential scanning calorimetry, and thermogravimetric analysis, the structures were elucidated as 3-C-β-D-glucopyranosyl-1,3,6,7-tetrahydroxyxanthone (1) and 2-C-β-D-glucopyranosyl-1,3,6,7-tetrahydroxyxanthone (mangiferin, 2). They were assessed for antioxidant efficacy (DCFDA assay) and for anti-inflammatory efficacy using the lipopolysaccharide (LPS)-induced inflammation model in the RAW 264.7 macrophages (nitrite levels quantified, using Griess Assay, as surrogate for nitric oxide (NO)). Compound 1 (named ceibinin) was established as a novel positional isomer of mangiferin (2). While both 1 and 2 were antioxidant against basal and hydrogen peroxide (100 μM)-induced oxidative stress (6.25 μg/ml abrogated peroxide-induced oxidative stress), ceibinin (1) demonstrated no anti-inflammatory potential, unlike mangiferin (2) which, as previously reported, showed anti-inflammatory effect. Our work reports a positional isomer of mangiferin for the first time in C. pentandra and demonstrates how such isomerism could underlie differences in biological activities and thus the potential for development into therapeutics

The identification of informative genes from multiple datasets with increasing complexity

Background In microarray data analysis, factors such as data quality, biological variation, and the increasingly multi-layered nature of more complex biological systems complicates the modelling of regulatory networks that can represent and capture the interactions among genes. We believe that the use of multiple datasets derived from related biological systems leads to more robust models. Therefore, we developed a novel framework for modelling regulatory networks that involves training and evaluation on independent datasets. Our approach includes the following steps: (1) ordering the datasets based on their level of noise and informativeness; (2) selection of a Bayesian classifier with an appropriate level of complexity by evaluation of predictive performance on independent data sets; (3) comparing the different gene selections and the influence of increasing the model complexity; (4) functional analysis of the informative genes. Results In this paper, we identify the most appropriate model complexity using cross-validation and independent test set validation for predicting gene expression in three published datasets related to myogenesis and muscle differentiation. Furthermore, we demonstrate that models trained on simpler datasets can be used to identify interactions among genes and select the most informative. We also show that these models can explain the myogenesis-related genes (genes of interest) significantly better than others (P < 0.004) since the improvement in their rankings is much more pronounced. Finally, after further evaluating our results on synthetic datasets, we show that our approach outperforms a concordance method by Lai et al. in identifying informative genes from multiple datasets with increasing complexity whilst additionally modelling the interaction between genes. Conclusions We show that Bayesian networks derived from simpler controlled systems have better performance than those trained on datasets from more complex biological systems. Further, we present that highly predictive and consistent genes, from the pool of differentially expressed genes, across independent datasets are more likely to be fundamentally involved in the biological process under study. We conclude that networks trained on simpler controlled systems, such as in vitro experiments, can be used to model and capture interactions among genes in more complex datasets, such as in vivo experiments, where these interactions would otherwise be concealed by a multitude of other ongoing events

Both habitat change and local lek structure influence patterns of spatial loss and recovery in a black grouse population

The final publication is available at Springer via http://dx.doi.org/10.1007/s10144-015-0484-3Land use change is a major driver of declines in wildlife populations. Where human economic or recreational interests and wildlife share landscapes this problem is exacerbated. Changes in UK black grouse Tetrao tetrix populations are thought to have been strongly influenced by upland land use change. In a long-studied population within Perthshire, lek persistence is positively correlated with lek size, and remaining leks clustered most strongly within the landscape when the population is lowest, suggesting that there may be a demographic and/or spatial context to the reaction of the population to habitat changes. Hierarchical cluster analysis of lek locations revealed that patterns of lek occupancy when the population was declining were different to those during the later recovery period. Response curves from lek-habitat models developed using MaxEnt for periods with a declining population, low population, and recovering population were consistent across years for most habitat measures. We found evidence linking lek persistence with habitat quality changes and more leks which appeared between 1994 and 2008 were in improving habitat than those which disappeared during the same period. Generalised additive models (GAMs) identified changes in woodland and starting lek size as being important indicators of lek survival between declining and low/recovery periods. There may also have been a role for local densities in explaining recovery since the population low point. Persistence of black grouse leks was influenced by habitat, but changes in this alone did not fully account for black grouse declines. Even when surrounded by good quality habitat, leks can be susceptible to extirpation due to isolation

Predicting the Impact of Climate Change on Threatened Species in UK Waters

Global climate change is affecting the distribution of marine species and is thought to represent a threat to biodiversity. Previous studies project expansion of species range for some species and local extinction elsewhere under climate change. Such range shifts raise concern for species whose long-term persistence is already threatened by other human disturbances such as fishing. However, few studies have attempted to assess the effects of future climate change on threatened vertebrate marine species using a multi-model approach. There has also been a recent surge of interest in climate change impacts on protected areas. This study applies three species distribution models and two sets of climate model projections to explore the potential impacts of climate change on marine species by 2050. A set of species in the North Sea, including seven threatened and ten major commercial species were used as a case study. Changes in habitat suitability in selected candidate protected areas around the UK under future climatic scenarios were assessed for these species. Moreover, change in the degree of overlap between commercial and threatened species ranges was calculated as a proxy of the potential threat posed by overfishing through bycatch. The ensemble projections suggest northward shifts in species at an average rate of 27 km per decade, resulting in small average changes in range overlap between threatened and commercially exploited species. Furthermore, the adverse consequences of climate change on the habitat suitability of protected areas were projected to be small. Although the models show large variation in the predicted consequences of climate change, the multi-model approach helps identify the potential risk of increased exposure to human stressors of critically endangered species such as common skate (Dipturus batis) and angelshark (Squatina squatina)

Current and potential geographical distribution of Platymeris biguttatus (Linnaeus, 1767) with description of nymphs

Background: The description of Platymeris biguttatus (Linnaeus 1767) nymphal instars as well as the prediction of the potentially suitable ecological niche was the main goal of this study. Our research was based on 258 specimens of P. biguttatus species of museum collections. A set of 23 environmental predictor variables covering Africa was used at ecological niche modeling - a method performed using the Maxent software to prepare potential distribution maps for this species. Results: The results suggested the most suitable areas seen as potentially suitable ecological niche for P. biguttatus in Africa. A jackknife test showed that temperature seasonality and percentage of tree cover were among the most important environmental variables affecting the distribution of the species. The analysis of climate preferences shows that most of the potentially suitable niches for this species were located in the area of tropical savanna climate, with a small participation of tree vegetation. Conclusions: P. biguttatus was only known to be widely distributed in the tropical part of continental Africa. Thanks to the ecological niche modeling methods and the museum data on the occurrence of the species, we introduced new information about potentially suitable ecological niches and the possible range of distribution

Molecular classification improves risk assessment in adult BCR-ABL1–negative B-ALL

Genomic classification has improved risk assignment of pediatric but not adult B-lineage acute lymphoblastic leukemia (B-ALL). The international UKALLXII/ECOG-ACRIN E2993 (NCT00002514) trial accrued 1229 BCR-ABL1-negative adolescent/adult B-ALL patients (aged 14-65 years). While 93% of patients achieved remission, 41% relapsed at a median of 13 months (range 28 days to 12 years). Five-year overall survival (5yr-OS) was 42% (95% CI, 39, 44). Transcriptome sequencing (n=238), gene expression profiling (n=210), cytogenetics (n=197) and fusion PCR (n=274) enabled genomic subtyping of 282 patient samples, of which 264 were eligible for trial, accounting for 64.5% of E2993 patients. Among patients in the outcome analysis, 29.5% of cases had favorable outcomes with 5yr-OS of 65-80% and were deemed standard-risk (DUX4-rearranged [9.2%], ETV6-RUNX1/-like [2.3%], TCF3-PBX1 [6.9%], PAX5 P80R [4.1%], high-hyperdiploid [6.9%]); 50.2% had high-risk genotypes with 5yr-OS of 0-27% (Ph-like [21.2%], KMT2A-AFF1 [12%], low-hypodiploid/near-haploid [14.3%], BCL2/MYC-rearranged [2.8%]); and 20.3% had intermediate-risk genotypes with 5yr-OS of 33-45% (PAX5alt [12.4%], ZNF384/-like [5.1%], MEF2D-rearranged [2.8%]). IKZF1 alterations occurred in 86% of Ph-like and TP53 mutations occurred in low-hypodiploid (54%) and BCL2/MYC-rearranged patients (33%), but were not independently associated with outcome. Of patients considered high-risk for relapse based on presenting age and WBC count, 40% harbored subtype-defining genetic alterations associated with standard- or intermediate-risk outcomes. We identified distinct immunophenotypic features for DUX4-rearranged, PAX5 P80R, ZNF384-R/-like and Ph-like genotypes. These data in a large adult B-ALL cohort treated with a non-risk-adapted approach on a single trial show the prognostic importance of genomic analyses which may translate into future therapeutic benefits