iDNA from terrestrial haematophagous leeches as a wildlife surveying and monitoring tool - prospects, pitfalls and avenues to be developed

Invertebrate-derived DNA (iDNA) from terrestrial haematophagous leeches has recently been proposed as a powerful non-invasive tool with which to detect vertebrate species and thus to survey their populations. However, to date little attention has been given to whether and how this, or indeed any other iDNA-derived data, can be combined with state-of-the-art analytical tools to estimate wildlife abundances, population dynamics and distributions. In this review, we discuss the challenges that face the application of existing analytical methods such as site-occupancy and spatial capture-recapture (SCR) models to terrestrial leech iDNA, in particular, possible violations of key assumptions arising from factors intrinsic to invertebrate parasite biology. Specifically, we review the advantages and disadvantages of terrestrial leeches as a source of iDNA and summarize the utility of leeches for presence, occupancy, and spatial capture-recapture models. The main source of uncertainty that attends species detections derived from leech gut contents is attributable to uncertainty about the spatio-temporal sampling frame, since leeches retain host-blood for months and can move after feeding. Subsequently, we briefly address how the analytical challenges associated with leeches may apply to other sources of iDNA. Our review highlights that despite the considerable potential of leech (and indeed any) iDNA as a new survey tool, further pilot studies are needed to assess how analytical methods can overcome or not the potential biases and assumption violations of the new field of iDNA. Specifically we argue that studies to compare iDNA sampling with standard survey methods such as camera trapping, and those to improve our knowledge on leech (and other invertebrate parasite) physiology, taxonomy, and ecology will be of immense future value

Income Elasticities of Food Demand in Africa: A Meta-Analysis

In order to combat malnutrition, economists and policymakers need to understand how food demand will change, as the continent further develops. Especially, a better understanding of, first, the factors underlying the relation between income and food demand, and, second, how this relation is changing according to the income level and/or characteristics of the country under study, may help improve the design and implementation of nutrition policies. There are a number of studies that have estimated the relation between income growth and food demand in Africa, but the resulting estimates are highly heterogeneous. This report provides a systematic review of the existing literature on income elasticities of food demand in Africa. Using a meta-analysis approach, this report identifies the factors determining the relation between food demand and income. Further research could usefully explore in greater detail some of the patterns identified and, in doing so, contribute to the design of policies aimed at addressing malnutrition.JRC.J.4-Agriculture and Life Sciences in the Econom

Feasibility of measuring sedentary time using data from a thigh-worn accelerometer: the 1970 British cohort study

In large-scale cohort studies, sedentary behavior has been routinely measured using self-reports or devices that apply a count-based threshold. We employed a gold standard postural allocation technique using thigh inclination and acceleration to capture free-living sedentary behavior. Participants aged 46.8 (standard deviation (SD), 0.7) years (n = 5,346) from the 1970 British Cohort Study (United Kingdom) were fitted with a waterproofed thigh-mounted accelerometer device (activPAL3 micro; PAL Technologies Ltd., Glasgow, United Kingdom) worn continuously over 7 days; data were collected in 2016-2018. Usable data were retrieved from 83.0% of the devices fitted, with 79.6% of the sample recording at least 6 full days of wear (at least 10 waking hours). Total daily sitting time (average times were 9.5 (SD, 2.0) hours/day for men and 9.0 (SD, 2.0) hours/day for women) accounted for 59.4% and 57.3% of waking hours in men and women, respectively; 73.8% of sample participants recorded >= 8 hours/day of sitting. Sitting in prolonged bouts of 60 continuous minutes or more accounted for 25.3% and 24.4% of total daily sitting in men and women, respectively. In mutually adjusted models, male sex, underweight, obesity, education, poor self-rated health, television-viewing time, and having a sedentary occupation were associated with higher device-measured sitting times. Thigh-worn accelerometry was feasibly deployed and should be considered for larger-scale national surveys

Niraparib Maintenance Therapy in Patients With Recurrent Ovarian Cancer After a Partial Response to the Last Platinum-Based Chemotherapy in the ENGOT-OV16/NOVA Trial

PURPOSEIn the ENGOT-OV16/NOVA trial (ClinicalTrials.gov identifier: NCT01847274), maintenance therapy with niraparib, a poly(ADP-ribose) polymerase inhibitor, prolonged progression-free survival in patients with platinum-sensitive, recurrent ovarian cancer who had a response to their last platinum-based chemotherapy. The objective of the study was to assess the clinical benefit and patient-reported outcomes in patients who had a partial response (PR) and complete response (CR) to their last platinum-based therapy.PATIENTS AND METHODSA total of 553 patients were enrolled in the trial. Of 203 patients with a germline BRCA mutation (gBRCAmut), 99 had a PR and 104 had a CR to their last platinum-based therapy; of 350 patients without a confirmed gBRCAmut (non?gBRCAmut), 173 had a PR and 177 had a CR. Post hoc analyses were carried out to evaluate safety and the risk of progression in these patients according to gBRCAmut status and response to their last platinum-based therapy. Ovarian cancer?specific symptoms and quality of life were assessed using the Functional Assessment of Cancer Therapy?Ovarian Symptom Index.RESULTSProgression-free survival was improved in patients treated with niraparib compared with placebo in both the gBRCAmut cohort (PR: hazard ratio [HR], 0.24; 95% CI, 0.131 to 0.441; P < .0001; CR: HR, 0.30; 95% CI, 0.160 to 0.546; P < .0001) and the non?gBRCAmut cohort (PR: HR, 0.35; 95% CI, 0.230 to 0.532; P < .0001; CR: HR, 0.58; 95% CI, 0.383 to 0.868; P = .0082). The incidence of any-grade and grade 3 or greater adverse events was manageable. No meaningful differences were observed between niraparib and placebo in PR and CR subgroups with respect to patient-reported outcomes.CONCLUSIONPatients achieved clinical benefit from maintenance treatment with niraparib regardless of response to the last platinum-based therapy

Copernicus Sentinel-2 Collection-1: A Consistent Dataset of Multispectral Imagery with enhanced Quality

The Copernicus Sentinel-2 satellite mission, with its Sentinel-2A and Sentinel-2B units, offers since several years now a massive quantitative and qualitative resource for the Earth Observation community. Since the launch of Sentinel-2A in 2015, and Sentinel-2B in 2017, many lessons have been learnt leading to continuous improvements of the radiometric and the geometric performances. However, the current archive is composed of heterogenous processing baselines with inconsistent product formats and uneven data quality, which limits its use for multi-temporal monitoring applications. To overcome this limitation, the Copernicus program has undertaken a complete reprocessing with the latest processing baseline (05.00). It concerns the L1C (Top-OfAtmosphere reflectance) and L2A (Surface Reflectance) products. This paper recalls the features of Collection-1 products and gives an overview of the first validation results

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment