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The mitochondrion is the cellular "powerhouse" and the integrity of its bioenergetic function is essential in survival. This role is fulfilled by mainly oxidizing NADH + H+ and pyruvate produced essentially in cytosolic glycolysis, inevitably forming toxic methylglyoxal (MGO). The production of cellular energy currency is linked to the function of respiratory chain using molecular oxygen as final electron acceptor and being the source of reactive oxygen species (ROS) formation, too. Although, the cells are well-equipped with protective mechanisms against MGO, the insufficiency of defense system results in the attack to cellular compartments. Mitochondrion is a target of such an insult and the thus emerging mitochondrial dysfunction involves respiratory chain inhibition parallel to ROS formation, protein glycation, lipid peroxidation, and mitochondrial membrane destruction concomitant with dissipation of mitochondrial membrane potential. These pathophysiological changes lead to mitochondrion-dependent cell apoptosis. However, to unmask the molecular mechanisms underlying MGO-induced apoptosis, further studies are needed.
We propose an infinite hidden Markov model for cylindrical time series with von Mises-Gamma emissions. Posterior inference is performed using a beam sampler combining conjugate updates and approximate sampling schemes. Simulation studies and two real data applications demonstrate the effectiveness of the proposed methodology.
Nowadays the use of forest reproductive material (FRM) is carefully regulated, but from the 18th century until few decades ago undocumented large-scale transfers of FRM has been commonly practiced in Europe. Past translocations could have had a profound impact on the genetic layout of European forests, and current plantations could either represent risks (e.g., genetic pollution for local lineages) or opportunities (e.g., unintentional assisted migration experiments in areas not covered by provenance trial networks) for extant forest genetic resources. Aiming at clarifying the role that silver fir plantations could play for the conservation of the genetic diversity of fragmented, rear-edge silver fir populations, we assembled a large genetic dataset of 3342 trees: 1553 from 48 plantations in Northern and Central Apennines, and 1789 from 38 natural populations representing possible sources of FRM. All trees were characterized with 16 microsatellite markers to reconstruct the main past translocations occurred in an area > 500 km wide in peninsular Italy. The integration of > 1000 newly genotyped individuals with previously published datasets enabled a broad review of the genetic structure of silver fir plantations across Italy. Overall, we found that ⁓30% of the planted individuals were translocated from a distant genetic cluster and 92% of nation-wide genetic diversity is conserved in plantations. The consequences of assessing the presence of local vs. non-local genotypes in plantations, as well as all downstream considerations about their spatial genetic structure and levels of genetic diversity, are discussed with a special focus on informing the management of forest tree plantations that could have high conservation value.
This paper investigates Andosols landscapes in Central-Southern Italy to evaluate the potential of high-resolution multispectral satellite imagery for archaeological prospection. The physical and chemical properties of Andosols play a crucial role in determining the visibility and readability of potential subsurface archaeological features within the landscape. In order to make the most of these soil characteristics, the research provides a rigorous comparative analysis of three complementary software platforms - QGIS, ENVI, and eCognition - evaluating traditional, semi-automated, and automated workflows, for the processing, analysis, and interpretation of multispectral satellite imagery. The research focuses on comparing the implementation and performance of Object-Based Image Analysis (OBIA) and Machine Learning (ML) techniques with conventional Pixel-Based Image Analysis (PBIA).Preliminary results demonstrate the capability of the proposed integrated methodology in successfully validating known archaeological features while revealing previously unidentified subsurface anomalies, including ancient road networks, settlements, land divisions, and funerary areas.In summary, the integration of Remote Sensing analysis (RS) and ML has been demonstrated to facilitate the identification of archaeological features in Andosols landscapes.However, the results indicate that automated, machine-driven interpretations must be integrated with traditional photo-interpretation, archaeological expertise, and rigorous ground-truthing to ensure reliable historical landscape reconstructions and effective cultural heritage management.
