Epigenetic silencing of SOCS3 expression contributes to fibrosis in Crohn’s disease

Identified risk polymorphisms affecting the Jak-STAT3 pathway in patients with Crohn’s disease could affect TGF-β1 and collagen I expression and in the pathway’s negative regulator, SOCS3. Genetic factors, however, account for only ~25% of disease. Epigenetic events also shape gene expression. Recent experiments showed that autocrine IL-6 production in mesenchymal cells, subepithelial myofibroblasts (SEMF) and muscle cells, of patients with fibrostenotic Crohn’s disease causes sustained Jak-STAT3 activity, excess TGF-β1 and Collagen I production and fibrosis. SOCS3 paradoxically decreased in these cells. We now identify epigenetic mechanisms that silence SOCS3 expression in SEMF of patients with fibrostenotic Crohn’s disease. In a previous experiment, using isolated SEMF of normal ileum and affected ileum from patients with each Crohn’s phenotype, inflammatory (Montreal B1), fibrostenotic (B2) and penetrating (B3), we confirmed decreased SOCS3 protein levels were unique to B2 patients. Expression of miR-19b increased in SEMF of affected ileum. SOCS3 transcriptional activity decreased after transfection of miR-19b mimic and increased when antagomiR-19b was expressed. Epigenetic silencing of SOCS3 in ileal SEMF of patients with fibrostenotic Crohn’s disease occurs by increased miR-19b mediated inhibition of SOCS3

Venture Capital in Japan: A Financial Instrument Supporting the Innovativeness of the Japanese Economy

Two factors: First, the relatively small number of new companies as well as the number of companies subject to liquidation over the year ("firm turnover") in Japan, and second, the insignificant prestige associated with the profession of entrepreneur do not foster growth in the dynamics of this form of financing ventures. The cited indicator for Japan in among the lowest in comparison with other highly developed countries1, while the profession of entrepreneur is not the foremost dream of college graduates. They would much rather prefer realizing their professional careers as members of the government bureaucracy or employees of a major corporation2. However, this mindset is slowly changing, if for no other reason then, in spite of popular conviction, because most small companies are not established during periods of prosperity, but near the end of the downward phase of the economic cycle. That is exactly the phase Japan has been dealing with for several years now. Young, creative people, recruited from the unemployed, are seeking self-employment, using all possible opportunities embedded in the "again starting up" machinery of the economy.Dwa czynniki: pierwszy - stosunkowo mała liczba nowych firm, a także firm likwidowanych w skali roku ("firm turnover") w Japonii oraz drugi - niewielki prestiż, jakim cieszy się zawód przedsiębiorcy, nie sprzyjają dynamizacji omawianej formy finansowania przedsięwzięć. Cytowany wskaźnik, dla Japonii należy do najniższych w porównaniu z innymi krajami wysoko rozwiniętymi (Grabowiecki 2000), zaś profesja przedsiębiorcy nie jest szczytem marzeń ludzi po studiach. Znacznie bardziej chcieliby oni swoją karierę zawodową realizować jako członkowie rządowej biurokracji lub pracownicy dużej korporacji (Corver 2008, s. 2). Ta świadomość ulega jednak stopniowej zmianie, chociażby dlatego, że wbrew popularnym przekonaniom, większość niewielkich przedsiębiorstw, powstaje nie w okresie prosperity, lecz pod koniec spadkowej fazy cyklu koniunkturalnego. Z taką fazą mamy do czynienia w Japonii od paru lat. Młodzi, kreatywni ludzie, rekrutujący się z bezrobotnych, poszukują samozatrudnienia, wykorzystują wszelakie szanse, tkwiące w "ruszającej na powrót" maszynerii gospodark (Yonekura, Lynskey 2003, s. 11)

Representing composition, spatial structure and management intensity of European agricultural landscapes: A new typology

Comprehensive maps that characterize the variation in agricultural landscapes across Europe are lacking. In this paper we present a new Europe-wide, spatially-explicit typology and inventory of the diversity in composition, spatial structure and management intensity of European agricultural landscapes. Agricultural landscape types were characterized at a 1 k

Changing patterns of conflict between humans, carnivores and crop-raiding prey as large carnivores recolonize human-dominated landscapes

Large carnivores are making remarkable comebacks in Europe, but how this affects human-wildlife conflict remains unclear. Rebounding carnivore populations lead to increasing livestock depredation, which in turn leads to greater economic losses for farmers. However, returning carnivores could also influence the behavior of wild ungulates, which are themselves responsible for major crop damage and associated economic losses. Here, we exploit the natural experiment of a rebounding wolf population in the Italian Apennines to study how this affected both types of human-wildlife conflic. We used large datasets of wolf occurrences (n = 351), livestock depredation events (n = 165), and crop damage events by wild boar (n = 3442) to independently model the determinants of livestock depredation and crop damage distribution in relation to wolf habitat suitability over a ten-year period of increasing wolf numbers. These analyses yielded two major insights. First, livestock depredations were mainly related to insufficient prevention measures (e.g. lacking fencing) rather than landscape context, providing a clear pathway to conflict mitigation. Second, crop damage decreased in areas of higher wolf habitat suitability and became more likely in areas of lower wolf habitat suitability, closer to settlements. This suggests increasing predation pressure forces wild boars to avoid the most suitable wolf habitat, leading to a redistribution of crop damage in the landscape. More generally, our study highlights complex human-wildlife interactions as large carnivores recover in human-dominated landscapes, suggesting that multiple, cooccurring conflicts need to be assessed jointly and adaptively in order to foster coexistence between humans and wildlife

Spatial variation in determinants of agricultural land abandonment in Europe

© 2018 Elsevier B.V. Agricultural abandonment is widespread and growing in many regions worldwide, often because of agricultural intensification on productive lands, conservation policies, or the spatial decoupling of agricultural production from consumption. Abandonment has major environmental and social impacts, which differ starkly depending on the geographical context, as does its potential to serve as a land reservoir for recultivation. Understanding determinants of abandonment patterns, and especially how their influence varies across broad geographic extents, is therefore important. Using a pan-European map of agricultural abandonment derived from MODIS NDVI time series between 2001 and 2012, we quantified the importance of farm management, climatic, environmental, and socio-economic variables in explaining abandonment patterns. We chose a machine learning modelling framework that accounts for spatial variation in the relationship between abandonment and its determinants. We predicted abandonment probability as well as determinant coefficients for the entire study area and summarised them for regions under selected EU support schemes. Our results highlight that agricultural abandonment was mainly explained by climate conditions suboptimal for agriculture (i.e., low/high growing degrees days). Determinants related to farm management (smaller field size, lower yields) and socio-economic conditions (high unemployment, negative migration balance) also contributed to describing agricultural abandonment patterns in Europe. Several determinants influenced abandonment in strongly non-linear ways and we found substantial spatial non-stationarity effects, although abandonment patterns were equally well-explained by predictors specified with spatially constant and varying effects. Predicted abandonment probability was similar inside and outside EU support or conservation zones, whereas observed MODIS-based abandonment was generally higher outside these zones, suggesting that schemes such as Natura 2000 or High Nature Value Farmland likely influence abandonment patterns. Our work highlights the potential value of spatial boosting for gaining insights into land-use change processes and their outcomes, which should increase the ability of such models to inform context-specific, regionalised decision making

The potential of historical spy-satellite imagery to support research in ecology and conservation

Remote sensing data are important for assessing ecological change, but their value is often restricted by their limited temporal coverage. Major historical events that affected the environment, such as those associated with colonial history, World War II, or the Green Revolution are not captured by modern remote sensing. In the present article, we highlight the potential of globally available black-and-white satellite photographs to expand ecological and conservation assessments back to the 1960s and to illuminate ecological concepts such as shifting baselines, time-lag responses, and legacy effects. This historical satellite photography can be used to monitor ecosystem extent and structure, species’ populations and habitats, and human pressures on the environment. Even though the data were declassified decades ago, their use in ecology and conservation remains limited. But recent advances in image processing and analysis can now unlock this research resource. We encourage the use of this opportunity to address important ecological and conservation questions

Mapping agricultural land abandonment from spatial and temporal segmentation of Landsat time series

© 2018 Elsevier Inc. Agricultural land abandonment is a common land-use change, making the accurate mapping of both location and timing when agricultural land abandonment occurred important to understand its environmental and social outcomes. However, it is challenging to distinguish agricultural abandonment from transitional classes such as fallow land at high spatial resolutions due to the complexity of change process. To date, no robust approach exists to detect when agricultural land abandonment occurred based on 30-m Landsat images. Our goal here was to develop a new approach to detect the extent and the exact timing of agricultural land abandonment using spatial and temporal segments derived from Landsat time series. We tested our approach for one Landsat footprint in the Caucasus, covering parts of Russia and Georgia, where agricultural land abandonment is widespread. First, we generated agricultural land image objects from multi-date Landsat imagery using a multi-resolution segmentation approach. Second, we estimated the probability for each object that agricultural land was used each year based on Landsat temporal-spectral metrics and a random forest model. Third, we applied temporal segmentation of the resulting agricultural land probability time series to identify change classes and detect when abandonment occurred. We found that our approach was able to accurately separate agricultural abandonment from active agricultural lands, fallow land, and re-cultivation. Our spatial and temporal segmentation approach captured the changes at the object level well (overall mapping accuracy = 97 ± 1%), and performed substantially better than pixel-level change detection (overall accuracy = 82 ± 3%). We found strong spatial and temporal variations in agricultural land abandonment rates in our study area, likely a consequence of regional wars after the collapse of the Soviet Union. In summary, the combination of spatial and temporal segmentation approaches of time-series is a robust method to track agricultural land abandonment and may be relevant for other land-use changes as well

Simulating and delineating future land change trajectories across Europe

Explorations of future land use change are important to understand potential conflicts between competing land uses, trade-offs associated with particular land change trajectories, and the effectiveness of policies to steer land systems into desirable states. Most model-based explorations and scenario studies focused on conversions in broad land use classes, but disregarded changes in land management or focused on individual sectors only. Using the European Union (EU) as a case study, we developed an approach to identifying typical combinations of land cover and management changes by combining the results of multimodel simulations in the agriculture and forest sectors for four scenarios from 2000 to 2040. We visualized land change trajectories by mapping regional hotspots of change. Land change trajectories differed in extent and spatial pattern across the EU and among scenarios, indicating trajectory-specific option spaces for alternative land system outcomes. In spite of the large variation in the area of change, similar hotspots of land change were observed among the scenarios. All scenarios indicate a stronger polarization of land use in Europe, with a loss of multifunctional landscapes. We analyzed locations subject to change by comparing location characteristics associated with certain land change trajectories. Results indicate differences in the location conditions of different land change trajectories, with diverging impacts on ecosystem service provisioning. Policy and planning for future land use needs to account for the spatial variation of land change trajectories to achieve both overarching and location-specific targets