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Spatially explicit biogeographic models are among the most used methods in conservation biogeography, with correlative species distribution models (SDMs) being the most popular among them. SDMs can identify the potential for species’ and community range shifts under climate change, and thus can inspire, inform, and guide complex and adaptive conservation management planning efforts such as collaborative transboundary conservation frameworks. However, SDMs are rarely developed collaboratively, which would be ideal for conservation applications of such models. Further, SDMs that are applied to conservation often do not follow best practices of the field, which are particularly important for applications in climate change contexts for which model extrapolation into potentially novel climates is necessary. Thus, while there is substantial promise, particularly among machine-learning based SDM approaches, there are also many pitfalls to consider when applying SDMs to conservation, and especially in the context of transboundary management under climate change. Here, we summarize these pitfalls and the key steps to mitigate them and maximize the promise of applying SDMs to facilitate transboundary conservation planning under climate change. We argue that conservation modeling capacity must be elevated among practitioners such that they can easily implement best practices when using SDMs, especially regarding: 1) avoiding model overcomplexity, 2) addressing input data bias, and 3) accounting for uncertainty in model extrapolations and projections. While our discussion centers mainly on the pitfalls and opportunities of applying the most popular correlative SDM algorithm, Maxent, our suggestions can also be generalized to a range of other SDM tools. Overall, improved training in, tools for, and implementation of best practices in biogeographic models such as SDMs hold great promise to facilitate and help guide complex, transboundary collaborations for long-term planning of conservation under climate change.

Ecological niche models (ENMs) can project changes in species’ distributions under climate change and thus inform conservation efforts and further our understanding of patterns of change. Predictions of species’ distribution shifts under climate change in topographically and geologically complex landscapes, such as karst landforms, should be improved by better integration of non-climate abiotic variables, such as karst geology or habitat structure, into model projections. We built ENMs for one of the limestone langurs, a group of leaf monkeys adapted to forests on the Sino-Vietnamese limestone karst landform. We collected occurrence localities for François’ leaf monkeys (Trachypithecus francoisi) and thinned them to avoid sampling bias. We included as environmental parameters a global dataset for karst geology and 19 bioclimatic variables derived from monthly temperature and precipitation at 30 arc-second resolution. ENMs including karst geology and climatic variables outperformed and differed spatially from climate-only models. Across six future-climate scenario projections, the optimal karst+climate model differed from the best climate-only model and predicted more spatial overlap with karst in the future, a contraction in total area of suitable habitat by the 2070s, and a small loss in the amount of suitable habitat in existing conservation areas. This study shows the importance of considering other abiotic factors beyond climate in projections of suitable habitat under climate change for species in complex landscapes. Because our results show that karst and climate interact to explain the distribution of a karst-adapted species, the results also suggest that, under climate change, these interactions are likely to produce altered networks of species into novel biological communities. Finally, our results support the need for conservation of limestone habitats and cross-border collaboration to maintain refuges and movement connectivity for endangered species in the face of climate change.

Indochina is known as one of the world’s biodiversity hotspots, with populations of many endangered and/or endemic species dramatically declining due to a range of threats, such as illegal hunting, habitat destruction, and global climate change. Climate change is expected to alter the region’s habitat and ecosystem conditions, force contraction of species ranges, and increase the likelihood of local extinctions. Maxent is a widely used modelling approach to predict the species’ current potential distribution, project range shifts in response to climate change, and inform conservation planning. Here, we collated known records and built models for both present and future climatically suitable habitat of the Owston’s Civet (Chrotogale owstoni), an endangered and poorly studied small carnivore occurring in Vietnam, eastern Laos, and a small part of southern China. Projections of climatically suitable habitat for the civet in most climate change scenarios and timeframes suggest significant habitat loss and fragmentation within its current range as a consequence of upward contraction. We recommend that future conservation efforts for C. owstoni focus on key refugia spreading along the Annamite Range in the border area between Vietnam and Laos. To mitigate climate-related extinction risk, close cooperation between Vietnam and Laos’ governmental agencies, research institutions, and non-governmental conservation organizations will play an important role in conserving the remaining habitat of this endangered species.

The commonly mutated human KRAS oncogene encodes two distinct KRAS4A and KRAS4B proteins generated by differential splicing. We demonstrate here that coordinated regulation of both isoforms through control of splicing is essential for development of Kras mutant tumors. The minor KRAS4A isoform is enriched in cancer stem-like cells, where it responds to hypoxia, while the major KRAS4B is induced by ER stress. KRAS4A splicing is controlled by the DCAF15/RBM39 pathway, and deletion of KRAS4A or pharmacological inhibition of RBM39 using Indisulam leads to inhibition of cancer stem cells. Our data identify existing clinical drugs that target KRAS4A splicing, and suggest that levels of the minor KRAS4A isoform in human tumors can be a biomarker of sensitivity to some existing cancer therapeutics.

Ecological niche models (ENMs) can project changes in species’ distributions under climate change and thus inform conservation efforts and further our understanding of patterns of change. Predictions of species’ distribution shifts under climate change in topographically and geologically complex landscapes, such as karst landforms, should be improved by better integration of non-climate abiotic variables, such as karst geology or habitat structure, into model projections. We built ENMs for one of the limestone langurs, a group of leaf monkeys adapted to forests on the Sino-Vietnamese limestone karst landform. We collected occurrence localities for François’ leaf monkeys (Trachypithecus francoisi) and thinned them to avoid sampling bias. We included as environmental parameters a global dataset for karst geology and 19 bioclimatic variables derived from monthly temperature and precipitation at 30 arc-second resolution. ENMs including karst geology and climatic variables outperformed and differed spatially from climate-only models. Across six future-climate scenario projections, the optimal karst+climate model differed from the best climate-only model and predicted more spatial overlap with karst in the future, a contraction in total area of suitable habitat by the 2070s, and a small loss in the amount of suitable habitat in existing conservation areas. This study shows the importance of considering other abiotic factors beyond climate in projections of suitable habitat under climate change for species in complex landscapes. Because our results show that karst and climate interact to explain the distribution of a karst-adapted species, the results also suggest that, under climate change, these interactions are likely to produce altered networks of species into novel biological communities. Finally, our results support the need for conservation of limestone habitats and cross-border collaboration to maintain refuges and movement connectivity for endangered species in the face of climate change.

Carrier mobility in doped conjugated polymers is limited by Coulomb interactions with dopant counterions. This complicates studying the effect of the dopant's oxidation potential on carrier generation because different dopants have different Coulomb interactions with polarons on the polymer backbone. Here, dodecaborane (DDB)-based dopants are used, which electrostatically shield counterions from carriers and have tunable redox potentials at constant size and shape. DDB dopants produce mobile carriers due to spatial separation of the counterion, and those with greater energetic offsets produce more carriers. Neutron reflectometry indicates that dopant infiltration into conjugated polymer films is redox-potential-driven. Remarkably, X-ray scattering shows that despite their large 2-nm size, DDBs intercalate into the crystalline polymer lamellae like small molecules, indicating that this is the preferred location for dopants of any size. These findings elucidate why doping conjugated polymers usually produces integer, rather than partial charge transfer: dopant counterions effectively intercalate into the lamellae, far from the polarons on the polymer backbone. Finally, it is shown that the IR spectrum provides a simple way to determine polaron mobility. Overall, higher oxidation potentials lead to higher doping efficiencies, with values reaching 100% for driving forces sufficient to dope poorly crystalline regions of the film.

Visible-light-induced generation of dithianyl and dioxolanyl radicals via selective hydrogen atom transfer (HAT) has been achieved. This radical relay tactic enables remote C(sp3)-H functionalization to permit rapid access to polyol and spiroketal segments, and in turn has been exploited as a key synthetic construct in the total synthesis of the danshenspiroketallactones. The conformational stability of the danshenspiroketallactones has also been defined via experiments and DFT calculations.

Next-generation sequencing of human tumours has refined our understanding of the mutational processes operative in cancer initiation and progression, yet major questions remain regarding the factors that induce driver mutations and the processes that shape mutation selection during tumorigenesis. Here we performed whole-exome sequencing on adenomas from three mouse models of non-small-cell lung cancer, which were induced either by exposure to carcinogens (methyl-nitrosourea (MNU) and urethane) or by genetic activation of Kras (Kras(LA2)). Although the MNU-induced tumours carried exactly the same initiating mutation in Kras as seen in the Kras(LA2) model (G12D), MNU tumours had an average of 192 non-synonymous, somatic single-nucleotide variants, compared with only six in tumours from the Kras(LA2) model. By contrast, the Kras(LA2) tumours exhibited a significantly higher level of aneuploidy and copy number alterations compared with the carcinogen-induced tumours, suggesting that carcinogen-induced and genetically engineered models lead to tumour development through different routes. The wild-type allele of Kras has been shown to act as a tumour suppressor in mouse models of non-small-cell lung cancer. We demonstrate that urethane-induced tumours from wild-type mice carry mostly (94%) Kras Q61R mutations, whereas those from Kras heterozygous animals carry mostly (92%) Kras Q61L mutations, indicating a major role for germline Kras status in mutation selection during initiation. The exome-wide mutation spectra in carcinogen-induced tumours overwhelmingly display signatures of the initiating carcinogen, while adenocarcinomas acquire additional C > T mutations at CpG sites. These data provide a basis for understanding results from human tumour genome sequencing, which has identified two broad categories of tumours based on the relative frequency of single-nucleotide variations and copy number alterations, and underline the importance of carcinogen models for understanding the complex mutation spectra seen in human cancers.

Epithelial-mesenchymal transition (EMT) is thought to be an important, possibly essential, component of the process of tumor dissemination and metastasis. About 20%-30% of Hras mutant mouse skin carcinomas induced by chemical initiation/promotion protocols have undergone EMT. Reduced exposure to TPA-induced chronic inflammation causes a dramatic reduction in classical papillomas and squamous cell carcinomas (SCCs), but the mice still develop highly invasive carcinomas with EMT properties, reduced levels of Hras and Egfr signaling, and frequent Ink4/Arf deletions. Deletion of Hras from the mouse germline also leads to a strong reduction in squamous tumor development, but tumors now acquire activating Kras mutations and exhibit more aggressive metastatic properties. We propose that invasive carcinomas can arise by different genetic and biological routes dependent on exposure to chronic inflammation and possibly from different target cell populations within the skin. Our data have implications for the use of inhibitors of inflammation or of Ras/Egfr pathway signaling for prevention or treatment of invasive cancers.

Analysis of gene expression patterns in normal tissues and their perturbations in tumours can help to identify the functional roles of oncogenes or tumour suppressors and identify potential new therapeutic targets. Here, gene expression correlation networks were derived from 92 normal human lung samples and patient-matched adenocarcinomas. The networks from normal lung show that NKX2-1 is linked to the alveolar type 2 lineage, and identify PEBP4 as a novel marker expressed in alveolar type 2 cells. Differential correlation analysis shows that the NKX2-1 network in tumours includes pathways associated with glutamate metabolism, and identifies Vaccinia-related kinase (VRK1) as a potential drug target in a tumour-specific mitotic network. We show that VRK1 inhibition cooperates with inhibition of poly (ADP-ribose) polymerase signalling to inhibit growth of lung tumour cells. Targeting of genes that are recruited into tumour mitotic networks may provide a wider therapeutic window than that seen by inhibition of known mitotic genes.

Abstract Background Germline polymorphisms can influence gene expression networks in normal mammalian tissues and can affect disease susceptibility. We and others have shown that analysis of this genetic architecture can identify single genes and whole pathways that influence complex traits, including inflammation and cancer susceptibility. Whether germline variants affect gene expression in tumors that have undergone somatic alterations, and the extent to which these variants influence tumor progression, is unknown. Results Using an integrated linkage and genomic analysis of a mouse model of skin cancer that produces both benign tumors and malignant carcinomas, we document major changes in germline control of gene expression during skin tumor development resulting from cell selection, somatic genetic events, and changes in the tumor microenvironment. The number of significant expression quantitative trait loci (eQTL) is progressively reduced in benign and malignant skin tumors when compared to normal skin. However, novel tumor-specific eQTL are detected for several genes associated with tumor susceptibility, including IL18 (Il18), Granzyme E (Gzme), Sprouty homolog 2 (Spry2), and Mitogen-activated protein kinase kinase 4 (Map2k4). Conclusions We conclude that the genetic architecture is substantially altered in tumors, and that eQTL analysis of tumors can identify host factors that influence the tumor microenvironment, mitogen-activated protein (MAP) kinase signaling, and cancer susceptibility.

Germline polymorphisms in model organisms and humans influence susceptibility to complex trait diseases such as inflammation and cancer. Mice of the Mus spretus species are resistant to tumour development, and crosses between M. spretus and susceptible Mus musculus strains have been used to map locations of genetic variants that contribute to skin cancer susceptibility. We have integrated germline polymorphisms with gene expression in normal skin from a M. musculus x M. spretus backcross to generate a network view of the gene expression architecture of mouse skin. Here we demonstrate how this approach identifies expression motifs that contribute to tissue organization and biological functions related to inflammation, haematopoiesis, cell cycle control and tumour susceptibility. Motifs associated with inflammation, epidermal barrier function and proliferation are differentially regulated in backcross mice susceptible or resistant to tumour development. The intestinal stem cell marker Lgr5 is identified as a candidate master regulator of the hair follicle, and the vitamin D receptor (Vdr) is linked to coordinated control of epidermal barrier function, inflammation and tumour susceptibility.