ScotCap - A large observational cohort study

ACKNOWLEDGEMENTS We would like to thank all patients and sites that participated in the ScotCap evaluation. Funding Information: This study was funded by the Scottish Government which had no role in the study design, data collection, analysis or interpretation of results, or writing of this report. We would like to thank all patients and sites that participated in the ScotCap evaluation. Publisher Copyright: © 2021 Association of Coloproctology of Great Britain and Ireland.Peer reviewedPublisher PD

Read counts from environmental DNA (eDNA) metabarcoding reflect fish abundance and biomass in drained ponds.

The sampling of environmental DNA (eDNA) coupled with cost-efficient and ever-advancing sequencing technology is propelling changes in biodiversity monitoring within aquatic ecosystems. Despite the increasing number of eDNA metabarcoding approaches, the ability to quantify species biomass and abundance in natural systems is still not fully understood. Previous studies have shown positive but sometimes weak correlations between abundance estimates from eDNA metabarcoding data and from conventional capture methods. As both methods have independent biases a lack of concordance is difficult to interpret. Here we tested whether read counts from eDNA metabarcoding provide accurate quantitative estimates of the absolute abundance of fish in holding ponds with known fish biomass and number of individuals. Environmental DNA samples were collected from two fishery ponds with high fish density and broad species diversity. In one pond, two different DNA capture strategies (on-site filtration with enclosed filters and three different preservation buffers versus lab filtration using open filters) were used to evaluate their performance in relation to fish community composition and biomass/abundance estimates. Fish species read counts were significantly correlated with both biomass and abundance, and this result, together with information on fish diversity, was repeatable when open or enclosed filters with different preservation buffers were used. This research demonstrates that eDNA metabarcoding provides accurate qualitative and quantitative information on fish communities in small ponds, and results are consistent between different methods of DNA capture. This method flexibility will be beneficial for future eDNA-based fish monitoring and their integration into fisheries management

Hematopoietic Cell–Restricted Deletion of CD36 Reduces High-Fat Diet–Induced Macrophage Infiltration and Improves Insulin Signaling in Adipose Tissue

OBJECTIVE: The fatty acid translocase and scavenger receptor CD36 is important in the recognition and uptake of lipids. Accordingly, we hypothesized that it plays a role in saturated fatty acid-induced macrophage lipid accumulation and proinflammatory activation. RESEARCH DESIGN AND METHODS: In vitro, the effect of CD36 inhibition and deletion in lipid-induced macrophage inflammation was assessed using the putative CD36 inhibitor, sulfosuccinimidyl oleate (SSO), and bone marrow-derived macrophages from mice with (CD36KO) or without (wild-type) global deletion of CD36. To investigate whether deletion of macrophage CD36 would improve insulin sensitivity in vivo, wild-type mice were transplanted with bone marrow from CD36KO or wild-type mice and then fed a standard or high-fat diet (HFD) for 20 weeks. RESULTS: SSO treatment markedly reduced saturated fatty acid-induced lipid accumulation and inflammation in RAW264.7 macrophages. Mice harboring CD36-specific deletion in hematopoietic-derived cells (HSC CD36KO) fed an HFD displayed improved insulin signaling and reduced macrophage infiltration in adipose tissue compared with wild-type mice, but this did not translate into protection against HFD-induced whole-body insulin resistance. Contrary to our hypothesis and our results using SSO in RAW264.7 macrophages, neither saturated fatty acid-induced lipid accumulation nor inflammation was reduced when comparing CD36KO with wild-type bone marrow-derived macrophages. CONCLUSIONS: Although CD36 does not appear important in saturated fatty acid-induced macrophage lipid accumulation, our study uncovers a novel role for CD36 in the migration of proinflammatory phagocytes to adipose tissue in obesity, with a concomitant improvement in insulin action

A national-scale dataset for threats impacting Australia's imperiled flora and fauna

Australia is in the midst of an extinction crisis, having already lost 10% of terrestrial mammal fauna since European settlement and with hundreds of other species at high risk of extinction. The decline of the nation's biota is a result of an array of threatening processes; however, a comprehensive taxon-specific understanding of threats and their relative impacts remains undocumented nationally. Using expert consultation, we compile the first complete, validated, and consistent taxon-specific threat and impact dataset for all nationally listed threatened taxa in Australia. We confined our analysis to 1,795 terrestrial and aquatic taxa listed as threatened (Vulnerable, Endangered, or Critically Endangered) under Australian Commonwealth law. We engaged taxonomic experts to generate taxon-specific threat and threat impact information to consistently apply the IUCN Threat Classification Scheme and Threat Impact Scoring System, as well as eight broad-level threats and 51 subcategory threats, for all 1,795 threatened terrestrial and aquatic threatened taxa. This compilation produced 4,877 unique taxon–threat–impact combinations with the most frequently listed threats being Habitat loss, fragmentation, and degradation (n = 1,210 taxa), and Invasive species and disease (n = 966 taxa). Yet when only high-impact threats or medium-impact threats are considered, Invasive species and disease become the most prevalent threats. This dataset provides critical information for conservation action planning, national legislation and policy, and prioritizing investments in threatened species management and recovery

Daisyworld: a review

Daisyworld is a simple planetary model designed to show the long-term effects of coupling between life and its environment. Its original form was introduced by James Lovelock as a defense against criticism that his Gaia theory of the Earth as a self-regulating homeostatic system requires teleological control rather than being an emergent property. The central premise, that living organisms can have major effects on the climate system, is no longer controversial. The Daisyworld model has attracted considerable interest from the scientific community and has now established itself as a model independent of, but still related to, the Gaia theory. Used widely as both a teaching tool and as a basis for more complex studies of feedback systems, it has also become an important paradigm for the understanding of the role of biotic components when modeling the Earth system. This paper collects the accumulated knowledge from the study of Daisyworld and provides the reader with a concise account of its important properties. We emphasize the increasing amount of exact analytic work on Daisyworld and are able to bring together and summarize these results from different systems for the first time. We conclude by suggesting what a more general model of life-environment interaction should be based on

Size-dependent activity of carbon dots for photocatalytic H2 generation in combination with a molecular Ni cocatalyst

Carbon dots (CDs) are low-cost light-absorbers in photocatalytic multicomponent systems, but their wide size distribution has hampered rational design and the identification of the factors that lead to their best performance. To address this challenge, we report herein the novel use of gel filtration size exclusion chromatography to separate amorphous, graphitic, and graphitic N-doped CDs depending on their lateral size to study the effect of their size on photocatalytic H2 evolution with a DuBois type Ni cocatalyst. Transmission electron microscopy and dynamic light scattering confirm size-dependent separation, while UV-vis and fluorescence spectroscopy of the more monodisperse fractions show a distinct response which computational modelling attributed to a complex interplay between CD size and optical properties. A size-dependent effect on the photocatalytic H2 evolution performance of the CDs in combination with a molecular Ni cocatalyst is demonstrated with a maximum activity at approximately 2-3 nm CD diameter. Overall, size separation leads to a two-fold increase in the specific photocatalytic activity for H2 evolution using the monodisperse CDs compared to the as synthesized polydisperse samples, highlighting the size-dependent effect on photocatalytic activity towards H2 evolution

Climatic control on Icelandic volcanic activity during the mid-Holocene

Human-induced climate change is causing rapid melting of ice in many volcanically active regions. Over glacial-interglacial time scales changes in surface loading exerted by large variations in glacier size affect the rates of volcanic activity. Numerical models suggest that smaller changes in ice volume over shorter time scales may also influence rates of mantle melt generation. However, this effect has not been verified in the geological record. Furthermore, the time lag between climatic forcing and a resultant change in the frequency of volcanic eruptions is unknown. We present empirical evidence that the frequency of volcanic eruptions in Iceland was affected by glacial extent, modulated by climate, on multicentennial time scales during the Holocene. We examine the frequency of volcanic ash deposition over northern Europe and compare this with Icelandic eruptions. We identify a period of markedly reduced volcanic activity centered on 5.5–4.5 ka that was preceded by a major change in atmospheric circulation patterns, expressed in the North Atlantic as a deepening of the Icelandic Low, favoring glacial advance on Iceland. We calculate an apparent time lag of ∼600 yr between the climate event and change in eruption frequency. Given the time lag identified here, increase in volcanic eruptions due to ongoing deglaciation since the end of the Little Ice Age may not become apparent for hundreds of years

Climatic control on Icelandic volcanic activity during the mid-Holocene

Human-induced climate change is causing rapid melting of ice in many volcanically active regions. Over glacial-interglacial time scales changes in surface loading exerted by large variations in glacier size affect the rates of volcanic activity. Numerical models suggest that smaller changes in ice volume over shorter time scales may also influence rates of mantle melt generation. However, this effect has not been verified in the geological record. Furthermore, the time lag between climatic forcing and a resultant change in the frequency of volcanic eruptions is unknown. We present empirical evidence that the frequency of volcanic eruptions in Iceland was affected by glacial extent, modulated by climate, on multicentennial time scales during the Holocene. We examine the frequency of volcanic ash deposition over northern Europe and compare this with Icelandic eruptions. We identify a period of markedly reduced volcanic activity centered on 5.5–4.5 ka that was preceded by a major change in atmospheric circulation patterns, expressed in the North Atlantic as a deepening of the Icelandic Low, favoring glacial advance on Iceland. We calculate an apparent time lag of ∼600 yr between the climate event and change in eruption frequency. Given the time lag identified here, increase in volcanic eruptions due to ongoing deglaciation since the end of the Little Ice Age may not become apparent for hundreds of years

Addressing global ruminant agricultural challenges through understanding the rumen microbiome::Past, present and future

The rumen is a complex ecosystem composed of anaerobic bacteria, protozoa, fungi, methanogenic archaea and phages. These microbes interact closely to breakdown plant material that cannot be digested by humans, whilst providing metabolic energy to the host and, in the case of archaea, producing methane. Consequently, ruminants produce meat and milk, which are rich in high-quality protein, vitamins and minerals, and therefore contribute to food security. As the world population is predicted to reach approximately 9.7 billion by 2050, an increase in ruminant production to satisfy global protein demand is necessary, despite limited land availability, and whilst ensuring environmental impact is minimized. Although challenging, these goals can be met, but depend on our understanding of the rumen microbiome. Attempts to manipulate the rumen microbiome to benefit global agricultural challenges have been ongoing for decades with limited success, mostly due to the lack of a detailed understanding of this microbiome and our limited ability to culture most of these microbes outside the rumen. The potential to manipulate the rumen microbiome and meet global livestock challenges through animal breeding and introduction of dietary interventions during early life have recently emerged as promising new technologies. Our inability to phenotype ruminants in a high-throughput manner has also hampered progress, although the recent increase in “omic” data may allow further development of mathematical models and rumen microbial gene biomarkers as proxies. Advances in computational tools, high-throughput sequencing technologies and cultivation-independent “omics” approaches continue to revolutionize our understanding of the rumen microbiome. This will ultimately provide the knowledge framework needed to solve current and future ruminant livestock challenges