Projected land-use change impacts on ecosystem services in the United States

Providing food, timber, energy, housing, and other goods and services, while maintaining ecosystem functions and biodiversity that underpin their sustainable supply, is one of the great challenges of our time. Understanding the drivers of land-use change and how policies can alter land-use change will be critical to meeting this challenge. Here we project land-use change in the contiguous United States to 2051 under two plausible baseline trajectories of economic conditions to illustrate how differences in underlying market forces can have large impacts on land-use with cascading effects on ecosystem services and wildlife habitat. We project a large increase in croplands (28.2 million ha) under a scenario with high crop demand mirroring conditions starting in 2007, compared with a loss of cropland (11.2 million ha) mirroring conditions in the 1990s. Projected land-use changes result in increases in carbon storage, timber production, food production from increased yields, and \u3e10% decreases in habitat for 25% of modeled species. We also analyze policy alternatives designed to encourage forest cover and natural landscapes and reduce urban expansion. Although these policy scenarios modify baseline land-use patterns, they do not reverse powerful underlying trends. Policy interventions need to be aggressive to significantly alter underlying land-use change trends and shift the trajectory of ecosystem service provision

Economic-based Projections Of Future Land Use In The Conterminous United States Under Alternative Policy Scenarios

The article presents a study which constructs and parameterizes an econometric model of land-use change to project future land use to the year 2051 at a fine spatial scale across the conterminous U.S. under several alternative land-use policy scenarios. It parameterizes the econometric model of land-use change with the National Resource Inventory (NRI) 1992 and 1997 land-use data for 844 000 sample points

Immune-Instructive Polymers Control Macrophage Phenotype and Modulate the Foreign Body Response In Vivo

© 2020 The Author(s) Implantation of medical devices can result in inflammation. A large library of polymers is screened, and a selection found to promote macrophage differentiation towards pro- or anti-inflammatory phenotypes. The bioinstructive properties of these materials are validated within a rodent model. By identifying novel materials with immune-instructive properties, the relationship between material-immune cell interactions could be investigated, and this offers exciting possibilities to design novel bioinstructive materials that can be used for numerous clinical applications including medical implants

Projected land-use change impacts on ecosystem services in the U.S.

Providing food, timber, energy, housing, and other goods and services, while maintaining ecosystem functions and biodiversity that underpin their sustainable supply, is one of the great challenges of our time. Understanding the drivers of land-use change and how policies can alter land-use change will be critical to meeting this challenge. Here we project land-use change in the contiguous U.S. to 2051 under two plausible baseline trajectories of economic conditions to illustrate how differences in underlying market forces can have large impacts on land-use with cascading effects on ecosystem services and wildlife habitat. We project a large increase in croplands (28.2 million ha) under a scenario with high crop demand mirroring conditions starting in 2007, compared to a loss of cropland (11.2 million ha) mirroring conditions in the 1990s. Projected land-use changes result in increases in carbon storage, timber production, food production from increased yields, and >10% decreases in habitat for 25% of modeled species. We also analyze policy alternatives designed to encourage forest cover, natural landscapes, and reduce urban expansion. Although these policy scenarios modify baseline land-use patterns, they do not reverse powerful underlying trends. Policy interventions need to be aggressive to significantly alter underlying land-use change trends and shift the trajectory of ecosystem service provision.Keywords: econometric model, land-use change, ecosystem services, food production, biodiversity, timber, carbonThis is an author's peer-reviewed final manuscript, as accepted by the publisher. The published article is copyrighted by [publisher] and can be found at: http://www.pnas.org/

Identification of Rigosertib for the Treatment of Recessive Dystrophic Epidermolysis Bullosa–Associated Squamous Cell Carcinoma

PURPOSE: Squamous cell carcinoma (SCC) of the skin is the leading cause of death in patients with the severe generalized form of the genetic disease recessive dystrophic epidermolysis bullosa (RDEB). Although emerging data are identifying why patients suffer this fatal complication, therapies for treatment of RDEB SCC are in urgent need. EXPERIMENTAL DESIGN: We previously identified polo-like kinase 1 (PLK1) as a therapeutic target in skin SCC, including RDEB SCC. Here, we undertake a screen of 6 compounds originally designated as PLK1 inhibitors, and detail the efficacy of the lead compound, the multipathway allosteric inhibitor ON-01910, for targeting RDEB SCC in vitro and in vivo. RESULTS: ON-01910 (or rigosertib) exhibited significant specificity for RDEB SCC: in culture rigosertib induced apoptosis in 10 of 10 RDEB SCC keratinocyte populations while only slowing the growth of normal primary skin cells at doses 2 orders of magnitude higher. Furthermore, rigosertib significantly inhibited the growth of two RDEB SCC in murine xenograft studies with no apparent toxicity. Mechanistically, rigosertib has been shown to inhibit multiple signaling pathways. Comparison of PLK1 siRNA with MEK inhibition, AKT inhibition, and the microtubule-disrupting agent vinblastine in RDEB SCC shows that only PLK1 reduction exhibits a similar sensitivity profile to rigosertib. CONCLUSIONS: These data support a “first in RDEB” phase II clinical trial of rigosertib to assess tumor targeting in patients with late stage, metastatic, and/or unresectable SCC

Biological Misinterpretation of Transcriptional Signatures in Tumor Samples Can Unknowingly Undermine Mechanistic Understanding and Faithful Alignment with Preclinical Data

PURPOSE Precise mechanism-based gene expression signatures (GES) have been developed in appropriate in vitro and in vivo model systems, to identify important cancer-related signaling processes. However, some GESs originally developed to represent specific disease processes, primarily with an epithelial cell focus, are being applied to heterogeneous tumor samples where the expression of the genes in the signature may no longer be epithelial-specific. Therefore, unknowingly, even small changes in tumor stroma percentage can directly influence GESs, undermining the intended mechanistic signaling. EXPERIMENTAL DESIGN Using colorectal cancer as an exemplar, we deployed numerous orthogonal profiling methodologies, including laser capture microdissection, flow cytometry, bulk and multiregional biopsy clinical samples, single-cell RNA sequencing and finally spatial transcriptomics, to perform a comprehensive assessment of the potential for the most widely used GESs to be influenced, or confounded, by stromal content in tumor tissue. To complement this work, we generated a freely-available resource, ConfoundR; https://confoundr.qub.ac.uk/, that enables users to test the extent of stromal influence on an unlimited number of the genes/signatures simultaneously across colorectal, breast, pancreatic, ovarian and prostate cancer datasets. RESULTS Findings presented here demonstrate the clear potential for misinterpretation of the meaning of GESs, due to widespread stromal influences, which in-turn can undermine faithful alignment between clinical samples and preclinical data/models, particularly cell lines and organoids, or tumor models not fully recapitulating the stromal and immune microenvironment. CONCLUSIONS Efforts to faithfully align preclinical models of disease using phenotypically-designed GESs must ensure that the signatures themselves remain representative of the same biology when applied to clinical samples