BioTIME: A database of biodiversity time series for the Anthropocene.

MotivationThe BioTIME database contains raw data on species identities and abundances in ecological assemblages through time. These data enable users to calculate temporal trends in biodiversity within and amongst assemblages using a broad range of metrics. BioTIME is being developed as a community-led open-source database of biodiversity time series. Our goal is to accelerate and facilitate quantitative analysis of temporal patterns of biodiversity in the Anthropocene.Main types of variables includedThe database contains 8,777,413 species abundance records, from assemblages consistently sampled for a minimum of 2 years, which need not necessarily be consecutive. In addition, the database contains metadata relating to sampling methodology and contextual information about each record.Spatial location and grainBioTIME is a global database of 547,161 unique sampling locations spanning the marine, freshwater and terrestrial realms. Grain size varies across datasets from 0.0000000158 km2 (158 cm2) to 100 km2 (1,000,000,000,000 cm2).Time period and grainBioTIME records span from 1874 to 2016. The minimal temporal grain across all datasets in BioTIME is a year.Major taxa and level of measurementBioTIME includes data from 44,440 species across the plant and animal kingdoms, ranging from plants, plankton and terrestrial invertebrates to small and large vertebrates.Software format.csv and .SQL

Trends in International Cancer Research Investment 2006-2018.

The International Cancer Research Partnership (ICRP) is an active network of cancer research funding organizations, sharing information about funded research projects in a common database. Data are publicly available to enable the cancer research community to find potential collaborators and avoid duplication. This study presents an aggregated analysis of projects funded by 120 partner organizations and institutes in 2006-2018, to highlight trends in cancer research funding. Overall, the partners' funding for cancer research increased from $5.562 billion (bn) US dollars (USD) in 2006 to$8.511bn USD in 2018, an above-inflation increase in funding. Analysis by the main research focus of projects using Common Scientific Outline categories showed that Treatment was the largest investment category in 2018, followed by Early Detection, Diagnosis, and Prognosis; Cancer Biology; Etiology; Control, Survivorship, and Outcomes; and Prevention. Over the 13 years covered by this analysis, research funding into Treatment and Early Detection, Diagnosis, and Prognosis had increased in terms of absolute investment and as a proportion of the portfolio. Research funding in Cancer Biology and Etiology declined as a percentage of the portfolio, and funding for Prevention and Control, Survivorship and Outcomes remained static. In terms of cancer site-specific research, funding for breast cancer and colorectal cancer had increased in absolute terms but declined as a percentage of the portfolio. By contrast, investment for brain cancer, lung cancer, leukemia, melanoma, and pancreatic cancer increased both in absolute terms and as a percentage of the portfolio

First pregnancy events and future breast density: modification by age at first pregnancy and specific VEGF and IGF1R gene variants

PURPOSE: Pregnancy characteristics have been associated with breast cancer risk, but information is limited on their relationship with breast density. Our objective was to examine the relationship between first pregnancy characteristics and later life breast density, and whether the association is modified by genotype. METHODS: The Marin Women’s Study was initiated to examine breast cancer in a high-incidence mammography population (Marin County, CA). Reproductive characteristics and pregnancy information including pregnancy-induced hypertension (PIH) were self-reported at the time of mammography. Forty-seven candidate single nucleotide polymorphisms were obtained from saliva samples; seven were assessed in relation to PIH and percent fibroglandular volume (%FGV). Breast density assessed as %FGV was measured on full-field digital mammograms by the San Francisco Mammography Registry. RESULTS: A multivariable regression model including 2,440 parous women showed that PIH during first pregnancy was associated with a statistically significant decrease in %FGV (b = −0.31, 95 % CI −0.52, −0.11), while each month of breast-feeding after first birth was associated with a statistically significant increase in %FGV (b = 0.01, 95 % CI 0.003, 0.02). PIH and breast-feeding associations with %FGV were modified by age at first birth. In a subsample of 1,240 women, there was evidence of modification in the association between PIH and %FGV by specific vascular endothelial growth factor (VEGF) (rs3025039) and insulin growth factor receptor-1 (IGFR1) (rs2016347) gene variants. CONCLUSION: These findings suggest that first pregnancy characteristics may exert an influence on extent of breast density later in life and that this influence may vary depending on inherited IGFR1 and VEGF genotypes. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s10552-014-0386-2) contains supplementary material, which is available to authorized users

Addressing resistance to PD-1/PD-(L)1 pathway inhibition: considerations for combinatorial clinical trial designs

With multiple PD-(L)1 inhibitors approved across dozens of indications by the US Food and Drug Administration, the number of patients exposed to these agents in adjuvant, first-line metastatic, second-line metastatic, and refractory treatment settings is increasing rapidly. Although some patients will experience durable benefit, many have either no clinical response or see their disease progress following an initial response to therapy. There is a significant need to identify therapeutic approaches to overcome resistance and confer clinical benefits for these patients. PD-1 pathway blockade has the longest history of use in melanoma, non-small cell lung cancer (NSCLC), and renal cell carcinoma (RCC). Therefore, these settings also have the most extensive clinical experience with resistance. In 2021, six non-profit organizations representing patients with these diseases undertook a year-long effort, culminating in a 2-day workshop (including academic, industry, and regulatory participants) to understand the challenges associated with developing effective therapies for patients previously exposed to anti-PD-(L)1 agents and outline recommendations for designing clinical trials in this setting. This manuscript presents key discussion themes and positions reached through this effort, with a specific focus on the topics of eligibility criteria, comparators, and endpoints, as well as tumor-specific trial design options for combination therapies designed to treat patients with melanoma, NSCLC, or RCC after prior PD-(L)1 pathway blockade

Anopheles species associations in Southeast Asia: indicator species and environmental influences

BACKGROUND: Southeast Asia presents a high diversity of Anopheles. Environmental requirements differ for each species and should be clarified because of their influence on malaria transmission potential. Monitoring projects collect vast quantities of entomological data over the whole region and could bring valuable information to malaria control staff but collections are not always standardized and are thus difficult to analyze. In this context studying species associations and their relation to the environment offer some opportunities as they are less subject to sampling error than individual species. METHODS: Using asymmetrical similarity coefficients, indirect clustering and the search of indicator species, this paper identified species associations. Environmental influences were then analysed through canonical and discriminant analysis using climatic and topographic data, land cover in a 3 km buffer around villages and vegetation indices. RESULTS: Six groups of sites characterized the structure of the species assemblage. Temperature, rainfall and vegetation factors all play a role. Four out of the six groups of sites based on species similarities could be discriminated using environmental information only. CONCLUSIONS: Vegetation indices derived from satellite imagery proved very valuable with one variable explaining more variance of the species dataset than any other variable. The analysis could be improved by integrating seasonality in the sampling and collecting at least 4 consecutive days