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Gastrointestinal cancers account for 22.5% of cancer related deaths worldwide and represent circa 20% of all cancers. In the last decades, we have witnessed a shift from histology-based to molecular-based classifications using genomic, epigenomic, and transcriptomic data. The molecular based classification revealed new prognostic markers and may aid the therapy selection. Because of the high-costs to perform a molecular classification, in recent years immunohistochemistry-based surrogate classification were developed which permit the stratification of patients, and in parallel multiple groups developed hematoxylin and eosin whole slide image analysis for sub-classifying these entities. Hence, we are witnessing a return to an image-based classification with the purpose to infer hidden information from routine histology images that would permit to detect the patients that respond to specific therapies and would be able to predict their outcome. In this review paper, we will discuss the current histological, molecular, and immunohistochemical classifications of the most common gastrointestinal cancers, gastric adenocarcinoma, and colorectal adenocarcinoma, and will present key aspects for developing a new artificial intelligence aided image-based classification of these malignancies.

This study aims to present a comparison analysis of two data collection methods that can be used in order to obtain reference ground truth data for forestry – a conventional method that uses specific equipment such as Field Map system, caliper and vertex inclinometer and a modern method based on terrestrial laser scanning (TLS) technology. The research was conducted in six circular Permanent Plots (PPs) with an area of 500 squaremeters each, within thinning and selected cuttings stands of sessile oak (Quercus petraea (Matt.) Liebl.), common beech (Fagus sylvatica L.) and Norway spruce (Picea abies L. Karst.), all situated in the Southern Carpathians (Mihăești, Mușeteși and Vidraru Forest Districts). Using the conventional method, the dendrometric tree characteristics such as height, diameter at breast height (dbh) and tree position were directly recorded in thefield. As a modern method for data collection, a Faro Focus3D X 130 HDR terrestrial laser scanning device was used to scan each plot and to extract the dbh and height of the trees. In this regard, two scanning approaches were used - single scan (SS) and multiple scan (MS). In order to compare the two data acquisitions methods, we applied a Strengths, Weaknesses, Opportunities, Threats (SWOT) analysis on the basis of which we could establish the pros and cons of using the two methods. Therefore, one can choose the most advantageous method for obtaining the reference data for forestry, in terms of equipment acquisition cost, personnel skills and qualifications, data collection working time, accuracy of the data recorded, post processing time, labor costs. Although the use of TLS in forest inventory is a technology with high potential, further investigations need to be done, especially in the case of automatic extraction of the tree height. For accurate reference ground data for forest inventory purposes, we still recommend using the conventional methods although they are time consuming.

Forest ecosystems provide a host of services and societal benefits, including carbon storage, habitat for fauna, recreation, and provision of wood or non-wood products. In a context of complex demands on forest resources, identifying priorities for biodiversity and carbon budgets require accurate tools with sufficient temporal frequency. Moreover, understanding long term forest dynamics is necessary for sustainable planning and management. Remote sensing (RS) is a powerful means for analysis, synthesis and report, providing insights and contributing to inform decisions upon forest ecosystems. In this communication we review current applications of RS techniques in Spanish forests, examining possible trends, needs, and opportunities offered by RS in a forestry context. Currently, wall-to-wall optical and LiDAR data are extensively used for a wide range of applications—many times in combination—whilst radar or hyperspectral data are rarely used in the analysis of Spanish forests. Unmanned Aerial Vehicles (UAVs) carrying visible and infrared sensors are gaining ground in acquisition of data locally and at small scale, particularly for health assessments. Forest fire identification and characterization are prevalent applications at the landscape scale, whereas structural assessments are the most widespread analyses carried out at limited extents. Unparalleled opportunities are offered by the availability of diverse RS data like those provided by the European Copernicus programme and recent satellite LiDAR launches, processing capacity, and synergies with other ancillary sources to produce information of our forests. Overall, we live in times of unprecedented opportunities for monitoring forest ecosystems with a growing support from RS technologies.

The generation and organization of the invasion front shape of neoplasms is an intriguing problem. The intimate mechanism is not yet understood, but the prevailing theory is that it represents an example of morphogenesis. Morphogenesis requires the presence of specific molecules, known as morphogens (activators and inhibitors), which can diffuse and elicit dose-dependent responses in their target cells. Due to their ability to modulate most of the coding transcriptome, their well-established role in embryogenesis, and their capacity to rapidly move between neighboring and distant cells, we propose microRNAs as inhibitors that could shape the cancer invasion front. In order to explain the genesis of the tumor border, we use Alan Turing’s reaction diffusion model, refined by Meinhardt and Gierer. This assumes the existence of an activator called a, and an inhibitor called h, which we hypothesize could be a freely moving microRNA. We used the fractal dimension as a measure of tumor border irregularity. We observed that the change in fractal dimension associates with variations in the diffusion coefficient of the activator (Da) or the inhibitor (Dh). We determined that the fractal dimension remains constant (i.e., the irregularity of the tumor border does not change) across a Dh interval, which becomes narrower as Da rises. We therefore conclude that a change in fractal dimension occurs when the balance between Da and Dh is disrupted. Biologically, this could be explained by a faulty distribution of the inhibitor caused by an abnormal density of the intercellular connection network. From a translational perspective, if experimentally confirmed, our observations can be used for a better diagnosis of cancer aggressiveness.

Biomarkers based on the molecular mechanism of sepsis are important for timely diagnosis and treatment. A large panel of small non-coding microRNAs was reported to modulate the immune response in sepsis but have not been tested in clinical practice. Large-scale identification of microRNA networks in sepsis might reveal a new biological mechanism that can be also targeted by gene therapy. Therefore, the main objective of this study is to perform a comparison of the miRNA network between septic patients and healthy controls. We used the previously measured levels of expression of 16 different circulating human and viral microRNAs in plasma from 99 septic patients and 53 healthy controls. We used three different computational methods to find correlations between the expressions of microRNAs and to build microRNA networks for the two categories, septic patients and healthy controls. We found that the microRNA network of the septic patients is significantly less connected when compared to miRNA network of the healthy controls (21 edges vs 52 edges, P < 0.0001). We hypothesize that several microRNAs (miR-16, miR-29a, miR-146, miR-155, and miR-182) are being sponged in sepsis explaining the loss of connection in the septic patient miRNA network. This was specific for sepsis, as it did not occur in other conditions characterized by an increased inflammatory response such as in post-surgery patients. Using several target prediction instruments, we predicted potential common sponges for the miRNA network in sepsis from several signaling pathways. Understanding the dynamics of miRNA network in sepsis is useful to explain the molecular pathophysiology of sepsis and for designing therapeutic strategies that target essential components of the immune response pathways.

In the context of increasing economic interdependence, tax reform has become critical on the international agenda due to widespread tax avoidance by multinational companies and digital giants. The OECD has proposed tax reforms to address these challenges, aiming for a fairer distribution of tax revenues among countries. This paper examines the necessity and impact of implementing the OECD's tax reforms within the EU, considering the diverse tax systems of member states. The analysis reveals an upward trend in profits transferred to tax havens globally. EU tax havens like the Netherlands, Ireland, and Luxembourg are significant recipients of these profits. The OECD reforms, by reallocating profits and establishing a minimum tax, are expected to reduce the attractiveness of these havens. The impact will vary: less developed EU countries may lose foreign investment opportunities, while more developed countries could benefit from increased tax revenues and fairer profit distribution.

This study investigates the impact of tax avoidance on Romania's economy, specifically its relationship with GDP, comparing Romania's situation to other EU member states. The research utilizes a quantitative methodology, analyzing data from 2015 to 2020 through statistical methods, including regression analysis. The findings indicate a substantial increase in profits transferred from Romania to tax havens, rising from 4 billion USD in 2015 to 7 billion USD in 2020, with a peak of 8 billion USD in 2019. The share of profits lost as a percentage of GDP ranged from 2.25% to 3.19%, with an average of 2.63%. Transfers to non-EU tax havens increased significantly, while those to EU tax havens remained constant. Regression analysis shows a positive and significant relationship between GDP growth and profits lost, with an increase of 0.039904 units of profits lost for each additional unit of GDP. These results highlight the economic impact of tax avoidance and underline the need for effective policy measures to address this issue.

In the context of contemporary debates on fiscal and economic policy, the impact of tax avoidance in the European Union was a frequently discussed topic at the negotiating table. In this paper, we followed the inflows of foreign direct investments and corporate tax collected to the state budget, trying to find out if a state with a high tax rate from the European Union could have an amortized impact of profit shifting, due to foreign direct investment inflows, also tracking how the corporate tax collected at the state budget changes, as the respective state reduces taxes. Following the research, we found out that paradoxically, as the state decreased the tax rate, corporate tax collected increased and also in certain years, the level of foreign direct investment exceeded corporate tax collected, which would indicate an amortized impact of tax avoidance.

The profound societal effects resulting from the digital revolution in Europe have completely reshaped the fabric of everyday life. This revolution is characterized by the seamless integration of digital technology into all aspects of society, influencing the way people interact, businesses function, and governments operate. Notably, it has greatly improved connectivity and access to information, fostering both innovation and economic growth. The objective of this paper is to explore the complex connection between the Digital Society and Economy Index (DSEI) and the Social Progress Index (SPI), which together provide a holistic representation of societal progress. The main aim is to establish the correlation between these indices, shedding light on how digitalization impacts different dimensions of social advancement in European countries. Through this examination, the study aims to offer valuable insights into the implications of digital transformation on the well-being of society, economic stability, and overall social development throughout Europe.

Otosclerosis is a pathological condition affecting the temporal bone, and is characterized by remodelling of the labyrinthine bone tissue through a dynamic process of osteolysis and osteogenesis. This condition progressively leads to hearing loss, tinnitus, and vertigo. Stapedotomy, a surgical procedure involving the removal of the stapes superstructure and its replacement with a prosthesis, is the treatment of choice to improve hearing in individuals with otosclerosis. However, vestibular dysfunction is a significant complication associated with this procedure, which can occur intraoperatively or postoperatively, ranging from the immediate postoperative period to weeks, months, or even years after surgery. This paper aims to provide a comprehensive review of the most important causes of vertigo associated with otosclerosis and stapes surgery with the goal of minimizing the incidence of this complication. Understanding the underlying factors contributing to vertigo in this context is crucial for the prevention and effective management of vertigo in patients undergoing stapedotomy.

A new European Union own resource based on non-recycled plastic packaging has been introduced. Each Member State must contribute on a national level in proportion to the amount of "plastic packaging waste" that is not recycled. This new policy raises several issues from a political, monetary, and legal perspective. The purpose of the paper is to study the sustainability of this revenue to the budget of the European Union taking into account that it's still unclear if this "EU plastic contribution" is a budgetary tool with an environmental spin or the other way around. While the fiscal and environmental goals might initially seem to be complementary.

The practice of transfer pricing for the purpose of fiscal optimization has become the center of attention in recent years due to the negative impact it has on the tax base, the state budget and competition. In this paper, we analyzed the functioning of transfer prices from two points of view, the value of fiscal optimization and the value of the market. The purpose was to determine the key indicators that address transfer prices in order to optimize the tax to come up with recommendations that could inhibit this practice. The results of the paper showed that the indicators are sales revenue, tax level and profit. So, the proposed recommendations considered the three indicators and the main recommendation regarding the profit involves the taxation of profit at the level of the value that would be realized under the conditions of the sale at the market price.