Diversity of luciferase sequences and bioluminescence production in Baltic Sea Alexandrium ostenfeldii

The toxic dinoflagellate Alexandrium ostenfeldii is the only bioluminescent bloom-forming phytoplankton in coastal waters of the Baltic Sea. We analysed partial luciferase gene (lcf) sequences and bioluminescence production in Baltic A. ostenfeldii bloom populations to assess the distribution and consistency of the trait in the Baltic Sea, and to evaluate applications for early detection of toxic blooms. Lcf was consistently present in 61 Baltic Sea A. ostenfeldii strains isolated from six separate bloom sites. All Baltic Sea strains except one produced bioluminescence. In contrast, the presence of lcf and the ability to produce bioluminescence did vary among strains from other parts of Europe. In phylogenetic analyses, lcf sequences of Baltic Sea strains clustered separately from North Sea strains, but variation between Baltic Sea strains was not sufficient to distinguish between bloom populations. Clustering of the lcf marker was similar to internal transcribed spacer (ITS) sequences with differences being minor and limited to the lowest hierarchical clusters, indicating a similar rate of evolution of the two genes. In relation to monitoring, the consistent presence of lcf and close coupling of lcf with bioluminescence suggests that bioluminescence can be used to reliably monitor toxic bloom-forming A. ostenfeldii in the Baltic Sea.Peer reviewe

An artificial intelligence approach to remotely assess pale lichen biomass

Although generally given little attention in vegetation studies, ground-dwelling (terricolous) lichens are major contributors to overall carbon and nitrogen cycling, albedo, biodiversity and biomass in many high-latitude ecosystems. Changes in biomass of mat-forming pale lichens have the potential to affect vegetation, fauna, climate and human activities including reindeer husbandry. Lichens have a complex spectral signature and terricolous lichens have limited growth height, often growing in mixtures with taller vegetation. This has, so far, prevented the development of remote sensing techniques to accurately assess lichen biomass, which would be a powerful tool in ecosystem and ecological research and rangeland management. We present a Landsat based remote sensing model developed using deep neural networks, trained with 8914 field records of lichen volume collected for > 20 years. In contrast to earlier proposed machine learning and regression methods for lichens, our model exploited the ability of neural networks to handle mixed spatial resolution input. We trained candidate models using input of 1 x 1 (30 x 30 m) and 3 x 3 Landsat pixels based on 7 reflective bands and 3 indices, combined with a 10 m spatial resolution digital elevation model. We normalised elevation data locally for each plot to remove the region-specific variation, while maintaining informative local variation in topography. The final model predicted lichen volume in an evaluation set (n = 159) reaching an R2 of 0.57. NDVI and elevation were the most important predictors, followed by the green band. Even with moderate tree cover density, the model was efficient, offering a considerable improvement compared to earlier methods based on specific reflectance. The model was in principle trained on data from Scandinavia, but when applied to sites in North America and Russia, the predictions of the model corresponded well with our visual interpretations of lichen abundance. We also accurately quantified a recent historic (35 years) change in lichen abundance in northern Norway. This new method enables further spatial and temporal studies of variation and changes in lichen biomass related to multiple research questions as well as rangeland management and economic and cultural ecosystem services. Combined with information on changes in drivers such as climate, land use and management, and air pollution, our model can be used to provide accurate estimates of ecosystem changes and to improve vegetation-climate models by including pale lichens.Peer reviewe

New national and regional biological records for Finland 11. Contributions to Bryophyta and Marchantiophyta 10

Ten species of mosses (Bryophyta: Entosthodon obtusus, Entosthodon ulvinenii, Eurhynchiastrum diversifolium, Hedwigia emodica, Hedwigia mollis, Hygrohypnum styriacum, Plagiothecium rossicum, Polytrichum perigoniale, Tortella alpicola and Ulota intermedia) are presented as new for Finland. Cephalozia lacinulata, previously considered to be regionally extinct from Finland, is reported to being found again. New records in biogeographical provinces for 67 species of mosses and 34 species of liverworts are listed. Finally, 6 occurrences in provinces are removed due to misidentifications or missing specimens

The entrepreneurial marketing management and commercialization arrangements of born-global bio-enterprises: the case of UK companies

Born global bio-enterprises are a unique “breed” of relatively small biotechnology enterprises operating in multiple countries. The companies are nimble and seemingly well-prepared for challenges that ephemeral markets such as the internationalised biotechnology sector brings. The international marketing management challenges they encounter appear to stimulate their entrepreneurial marketing and commercialisation instincts. Surprisingly, there is a dearth of studies that examine their entrepreneurial predispositions. As such, this study is an attempt to explain their entrepreneurial tendencies by investigating the marketing and commercialisation strategies adopted by born global bio-enterprises in the UK’s biotechnology industry. The study assumes a multi-case approach examining five archetypical born global bio-enterprises currently active in the UK. It contributes to the international entrepreneurship and marketing management literature. Specifically, it provides international business managers with new knowledge about various marketing manoeuvres they can apply in international networks for their marketing mileage. In doing so, the study proposes a theoretical framework mapping out entrepreneurial marketing and commercialisation arrangements in internationalised biotechnology markets. Its findings are useful to various stakeholders including: policy makers, managers of technology-based companies and business management researchers

Vital function of PRELI and essential requirement of its LEA motif

Proteins containing the late embryogenesis abundant (LEA) motif comprise a conserved family, postulated to act as cell protectors. However, their function and mechanisms of action remain unclear. Here we show that PRELI, a mammalian LEA-containing homolog of yeast Ups1p, can associate with dynamin-like GTPase Optic Atrophy-1 (OPA1) and contribute to the maintenance of mitochondrial morphology. Accordingly, PRELI can uphold mitochondrial membrane potential (ΔΨm) and enhance respiratory chain (RC) function, shown by its capacity to induce complex-I/NADH dehydrogenase and ATP synthase expression, increase oxygen consumption and reduce reactive oxygen species (ROS) production. PRELI can also inhibit cell death induced by STS, TNF-α or UV irradiation. Moreover, in vitro and in vivo dominant-negative overexpression of mutant PRELI/LEA− (lacking the LEA motif) and transient in vitro PRELI-specific knockdown can render lymphocytes vulnerable to apoptosis, cause mouse embryo lethality and revert the resistance of lymphoma cells to induced death. Collectively, these data support the long-presumed notion of LEA protein-dependent mechanisms of cytoprotection and suggest that PRELI interacts with OPA1 to maintain mitochondria structures intact, sustain balanced ion−/proton+ gradients, promote oxidative phosphorylation reactions, regulate pro- and antiapoptotic protein traffic and enable cell responses to induced death. These findings may help to understand how bioenergetics is mechanistically connected with cell survival cues

Gene Set Enrichment Analysis Identifies LIF as a Negative Regulator of Human Th2 Cell Differentiation

In this study we show that IL-4 is crucial during reinforcement window of human Th2 differentiation for optimal Th2 development. We have also shown here that during this stage, IL-4 helps in cellular decision-making process of differentiation versus proliferation. We have combined computational and experimental methods to analyze Th2 transcription network to name novel players of the process of Th2 differentiation. Here we report that LIF through STAT3 negatively regulates Th2 differentiation. This approach can be generalized to analyze “omics” data to identify key regulatory modules

Indirect interaction between two native thistles mediated by an invasive exotic floral herbivore

Spatial and temporal variation in insect floral herbivory is common and often important. Yet, the determinants of such variation remain incompletely understood. Using 12 years of flowering data and 4 years of biweekly insect counts, we evaluated four hypotheses to explain variation in damage by the Eurasian flower head weevil, Rhinocyllus conicus, to the native North American wavyleaf thistle, Cirsium undulatum. The four factors hypothesized to influence weevil impact were variations in climate, weevil abundance, phenological synchrony, and number of flower heads available, either on wavyleaf thistle or on the other co-occurring, acquired native host plant (Platte thistle, Cirsium canescens), or on both. Climate did not contribute significantly to an explanation of variation in R. conicus damage to wavyleaf thistle. However, climate did influence weevil synchrony with wavyleaf flower head initiation, and phenological synchrony was important in determining R. conicus oviposition levels on wavyleaf thistle. The earlier R. conicus was active, the less it oviposited on wavyleaf thistle, even when weevils were abundant. Neither weevil abundance nor availability of wavyleaf flower heads predicted R. conicus egg load. Instead, the strongest predictor of R. conicus egg load on wavyleaf thistle was the availability of flower heads on Platte thistle, the more common, earlier flowering native thistle in the sand prairie. Egg load on wavyleaf thistle decreased as the number of Platte thistle flower heads at a site increased. Thus, wavyleaf thistle experienced associational defense in the presence of flowering by its now declining native congener, Platte thistle. These results demonstrate that prediction of damage to a native plant by an exotic insect may require knowledge of both likely phenological synchrony and total resource availability to the herbivore, including resources provided by other nontarget native species

A Macroecological Analysis of SERA Derived Forest Heights and Implications for Forest Volume Remote Sensing

Individual trees have been shown to exhibit strong relationships between DBH, height and volume. Often such studies are cited as justification for forest volume or standing biomass estimation through remote sensing. With resolution of common satellite remote sensing systems generally too low to resolve individuals, and a need for larger coverage, these systems rely on descriptive heights, which account for tree collections in forests. For remote sensing and allometric applications, this height is not entirely understood in terms of its location. Here, a forest growth model (SERA) analyzes forest canopy height relationships with forest wood volume. Maximum height, mean, H100, and Lorey's height are examined for variability under plant number density, resource and species. Our findings, shown to be allometrically consistent with empirical measurements for forested communities world-wide, are analyzed for implications to forest remote sensing techniques such as LiDAR and RADAR. Traditional forestry measures of maximum height, and to a lesser extent H100 and Lorey's, exhibit little consistent correlation with forest volume across modeled conditions. The implication is that using forest height to infer volume or biomass from remote sensing requires species and community behavioral information to infer accurate estimates using height alone. SERA predicts mean height to provide the most consistent relationship with volume of the height classifications studied and overall across forest variations. This prediction agrees with empirical data collected from conifer and angiosperm forests with plant densities ranging between 102–106 plants/hectare and heights 6–49 m. Height classifications investigated are potentially linked to radar scattering centers with implications for allometry. These findings may be used to advance forest biomass estimation accuracy through remote sensing. Furthermore, Lorey's height with its specific relationship to remote sensing physics is recommended as a more universal indicator of volume when using remote sensing than achieved using either maximum height or H100