Search

Alzheimer's disease (AD) is the most common type of dementia with millions of affected patients worldwide. Currently, there is still no cure and AD is often diagnosed long time after onset because there is no clear diagnosis. Thus, it is essential to study the physiology and pathogenesis of AD, investigating the risk factors that could be strongly connected to the disease onset. Despite AD, like other complex diseases, is the result of the combination of several factors, there is emerging agreement that environmental pollution should play a pivotal role in the causes of disease. In this work, we implemented an Artificial Intelligence model to predict AD mortality, expressed as Standardized Mortality Ratio, at Italian provincial level over 5 years. We employed a set of publicly available variables concerning pollution, health, society and economy to feed a Random Forest algorithm. Using methods based on eXplainable Artificial Intelligence (XAI) we found that air pollution (mainly O 3 and N O 2 ) contribute the most to AD mortality prediction. These results could help to shed light on the etiology of Alzheimer's disease and to confirm the urgent need to further investigate the relationship between the environment and the disease. [ABSTRACT FROM AUTHOR]

Dementia is on the rise in the world population and has been defined by the World Health Organization as a global public health priority. In Italy, according to demographic projections, in 2051 there will be 280 elderly people for every 100 young people, with an increase in all age-related chronic diseases, including dementia. Currently the total number of patients with dementia is estimated to be over 1 million (mainly with Alzheimer's disease (AD) and Parkinson's disease (PD)). In-depth studies of the etiology and physiology of dementia are complicated due to the complexity of these diseases and their long duration. In this work we present a dataset on mortality rates (in the form of Standardized Mortality Ratios, SMR) for AD e PD in Italy at provincial level over a period of 8 years (2012–2019). Access to long-term, spatially detailed and ready-to-use data could favor both health monitoring and the research of new treatments and new drugs as well as innovative methodologies for early diagnosis of dementia. [ABSTRACT FROM AUTHOR]

Protecting global biodiversity is one of the most urgent tasks for the coming decades. Area-based conservation is a pillar for preserving ecosystems and species. Strictly protected areas specifically preserve biodiversity and ecosystem processes. The "EU Biodiversity Strategy for 2030" targets strict protection for 10% of land area. Here we performed the first analysis of strictly protected areas (as IUCN type Ia, Ib, and II) across Europe, by investigating their area coverage at the level of biogeographical regions, countries and elevation gradients. We show that, with few exceptions, the amount of strictly protected area is very limited and the spatial distribution of such protected areas is biased towards higher elevation sites, as in the case of other protected areas. Then, we suggest that potential areas should be identified to expand strictly protected areas with low economic and social costs including, for instance, areas with high biodiversity value, low population, and low productive land use. Finally, we propose that a coordinated effort and a strategic plan to achieve continental-scale conservation are fundamental, and at least half of this land under strict conservation (i.e. 5%) should be under the protection categories Ia and Ib. [ABSTRACT FROM AUTHOR]

Cumulative area under protection (%) for each country is shown for all strictly protected areas in the upper panel and for the 3 different IUCN categories (Ia, Ib, and II) in the lower panels The original article has been corrected. Cumulative area under protection (%) for each biogeographical region is shown for all strictly protected areas in the upper panel and for the 3 different IUCN categories (Ia, Ib, and II) in the lower panels Graph: Fig. [Extracted from the article]

In Italy, approximately 400.000 new cases of malignant tumors are recorded every year. The average of annual deaths caused by tumors, according to the Italian Cancer Registers, is about 3.5 deaths and about 2.5 per 1,000 men and women respectively, for a total of about 3 deaths every 1,000 people. Long-term (at least a decade) and spatially detailed data (up to the municipality scale) are neither easily accessible nor fully available for public consultation by the citizens, scientists, research groups, and associations. Therefore, here we present a ten-year (2009–2018) database on cancer mortality rates (in the form of Standardized Mortality Ratios, SMR) for 23 cancer macro-types in Italy on municipal, provincial, and regional scales. We aim to make easily accessible a comprehensive, ready-to-use, and openly accessible source of data on the most updated status of cancer mortality in Italy for local and national stakeholders, researchers, and policymakers and to provide researchers with ready-to-use data to perform specific studies. Measurement(s) Standardized Mortality Ratio Technology Type(s) Public database [ABSTRACT FROM AUTHOR]

In early studies, northern vegetation response to global warming recognised both increases in biomass/cover and shrinking of species' distributional ranges. Subsequent field measurements focussed on vegetation cover and biomass increases ("greening"), and more recently decreases ("browning"). However, satellite observations show that more than 50% of arctic vegetation has not changed significantly despite rapid warming. While absence of change in remote sensing data does not necessarily mean no ecological change on the ground, the significant proportion of the Arctic that appears to be stable in the face of considerable climate change points to a greater need to understand Arctic ecosystem stability. In this paper, we performed an extensive review of the available literature to seek balances or imbalances between research focussing on "greening", "browning" and "stability/no change". We find that greening studies dominate the literature though two relatively small areas of the Arctic are disproportionately represented for this main change process. Critically, there are too few studies anywhere investigating stability. We highlight the need to understand the mechanisms driving Arctic ecosystem stability, and the potential longer-term consequences of remaining stable in a rapidly changing climate. [ABSTRACT FROM AUTHOR]

This pandemic situation requests a correct understanding of our impacts on wildlife conservation, which would also provide benefits for our species. In this commentary we revised and discussed some of the repercussions that SARS-CoV-2 pandemic may have to wildlife. We propose four actions that should be taken into account to protect and conserve wildlife in this pandemic era: wildlife "wet" markets must close; human interference with wildlife must be reduced; bats and pangolins must be conserved and not blamed; and Chinese traditional medicine must be more controlled. [ABSTRACT FROM AUTHOR]

The origin of economic niches, conceived as potential markets, has been mostly neglected in economic theory. Ecological niches emerge as new species evolve and fit into a web of interactions, and the more species come into existence, the more (exponentially or power-law distributed) ecological niches emerge. In parallel fashion, economic niches emerge with new goods, and niche formation in economics is also exponentially or power-law distributed. In economics and ecology alike, autocatalytic processes drive the system to greater and greater diversity. Novelty begets novelty in a positive feedback loop. An autocatalytic set of self-enabling transactions feed back upon one another in combinatoric fashion to generate progressive diversity. While these combinatorial dynamics cannot be prestated, the model explains the "hockeystick of economic growth"—a pattern of prolonged stasis followed by a sudden takeoff, such as occurred during the Industrial Revolution or the Cambrian explosion in ecology. Several implications derive from our niche emergence model, including the idea that the evolutionary process of technological change is not something we do; rather, it happens to us. [ABSTRACT FROM AUTHOR]

A relatively small number of broad-scale patterns describe the distribution of biodiversity across the earth. All of them explore biodiversity focusing on a mono or bi-dimensional space. Conversely, the volume of the forests is rarely considered. In the present work, we tested a global correlation between vascular plant species richness (S) and average forest canopy height ( H), the latter regarded as a proxy of volume, using the NASA product of Global Forest Canopy Height map and the global map of plant species diversity. We found a significant correlation between H and S both at global and macro-climate scales, with strongest confidence in the tropics. Hence, two different regression models were compared and discussed to provide a possible pattern of the H-S relation. We suggested that the volume of forest ecosystems should be considered in ecological studies as well as in planning and managing natural sites, although in this first attempt, we cannot definitively prove our hypothesis. Again, high-resolution spatial data could be highly important to confirm the H-S relation, even at different scales. [ABSTRACT FROM AUTHOR]

In the original publication of the article, equation 2 was published incorrectly. [ABSTRACT FROM AUTHOR]

The latitudinal diversity gradient (LDG) is one of the most recognized global patterns of species richness exhibited across a wide range of taxa. Numerous hypotheses have been proposed in the past two centuries to explain LDG, but rigorous tests of the drivers of LDGs have been limited by a lack of high-quality global species richness data. Here we produce a high-resolution (0.025° × 0.025°) map of local tree species richness using a global forest inventory database with individual tree information and local biophysical characteristics from ~1.3 million sample plots. We then quantify drivers of local tree species richness patterns across latitudes. Generally, annual mean temperature was a dominant predictor of tree species richness, which is most consistent with the metabolic theory of biodiversity (MTB). However, MTB underestimated LDG in the tropics, where high species richness was also moderated by topographic, soil and anthropogenic factors operating at local scales. Given that local landscape variables operate synergistically with bioclimatic factors in shaping the global LDG pattern, we suggest that MTB be extended to account for co-limitation by subordinate drivers., (© 2022. The Author(s), under exclusive licence to Springer Nature Limited.)