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Protist grazing pressure plays a major role in controlling aquatic bacterial populations, affecting energy flow through the microbial loop and biogeochemical cycles. Predator-escape mechanisms might play a crucial role in energy flow through the microbial loop, but are yet understudied. For example, some bacteria can use planktonic as well as surface-associated habitats, providing a potential escape mechanism to habitat-specific grazers. We investigated the escape response of the marine bacterium Marinobacter adhaerens in the presence of either planktonic (nanoflagellate: Cafeteria roenbergensis) or surface-associated (amoeba: Vannella anglica) protist predators, following population dynamics over time. In the presence of V. anglica, M. adhaerens cell density increased in the water, but decreased on solid surfaces, indicating an escape response towards the planktonic habitat. In contrast, the planktonic predator C. roenbergensis induced bacterial escape to the surface habitat. While C. roenbergensis cell numbers dropped substantially after a sharp initial increase, V. anglica exhibited a slow, but constant growth throughout the entire experiment. In the presence of C. roenbergensis, M. adhaerens rapidly formed cell clumps in the water habitat, which likely prevented consumption of the planktonic M. adhaerens by the flagellate, resulting in a strong decline in the predator population. Our results indicate an active escape of M. adhaerens via phenotypic plasticity (i.e., behavioral and morphological changes) against predator ingestion. This study highlights the potentially important role of behavioral escape mechanisms for community composition and energy flow in pelagic environments, especially with globally rising particle loads in aquatic systems through human activities and extreme weather events.

Smart contracts have gained a lot of popularity in recent times as they are a very powerful tool for the development of decentralised and automatic applications in many fields without the need for intermediaries or trusted third parties. However, due to the decentralised nature of the blockchain on which they are based, a series of challenges have emerged related to vulnerabilities in their programming that, given their particularities, could have (and have already had) a very high economic impact. This article provides a holistic view of security challenges associated with smart contracts, as well as the state of the art of available public domain tools.

The exponential growth of devices connected to the network has resulted in the development of new IoT applications and on-line services. However, these advances are limited by the rigidity of the current network infrastructure, in which the administrator has to implement high-level network policies adapting and configuring protocols manually and usually through a command line interface (CLI). At this point, Software-Defined Networking (SDN) appears as a viable alternative network architecture that allows for programming the network and opening the possibility of creating new services and more efficient applications to cover the actual requirements. In this paper, we describe this new technology and analyze its opportunities in the development of IoT applications. Similarly, we present the first applications and projects based on this technology. Finally, we discuss the issues and challenges in its implementation.

Chronic kidney disease (CKD) is one of the fastest-growing causes of death and is predicted to become by 2040 the fifth global cause of death. CKD is characterized by increased oxidative stress and chronic inflammation. However, therapies to slow or prevent CKD progression remain an unmet need. Nrf2 (nuclear factor erythroid 2-related factor 2) is a transcription factor that plays a key role in protection against oxidative stress and regulation of the inflammatory response. Consequently, the use of compounds targeting Nrf2 has generated growing interest for nephrologists. Pre-clinical and clinical studies have demonstrated that Nrf2-inducing strategies prevent CKD progression and protect from acute kidney injury (AKI). In this article, we review current knowledge on the protective mechanisms mediated by Nrf2 against kidney injury, novel therapeutic strategies to induce Nrf2 activation, and the status of ongoing clinical trials targeting Nrf2 in renal diseases.

The high morbidity and mortality of hepatocellular carcinoma (HCC) has encouraged the search for new biomarkers to be used alongside alpha-foetoprotein (AFP) and imaging tests. The aim of this study was to evaluate the clinical contribution of protein induced by vitamin K absence or antagonist-II (PIVKA-II) for HCC monitoring after liver transplantation (LT) and compare it with AFP, a routinely used tumour marker. A total of 46 HCC patients (Milan criteria) were enrolled in this study. Serum levels of PIVKA-II and AFP were measured before and after transplantation. Clinical features were determined for all the patients that were included. Significant correlations were found between PIVKA-II expression levels and some clinicopathological features, such as tumour size and number of pre-transplant transarterial chemoembolizations (TACEs). Serum levels of PIVKA-II and AFP decreased significantly after LT and increased in patients with tumour recurrence. Serum PIVKA-II levels may play an important role in predicting disease severity. Furthermore, monitoring PIVKA-II levels in HCC transplant recipients reflects the tumor early recurrence after transplantation and could be used, complementing AFP and imaging tests, as a novel biomarker of this pathology.

This systematic literature review delves into the extensive landscape of emotion recognition, sentiment analysis, and affective computing, analyzing 609 articles. Exploring the intricate relationships among these research domains, and leveraging data from four well-established sources—IEEE, Science Direct, Springer, and MDPI—this systematic review classifies studies in four modalities based on the types of data analyzed. These modalities are unimodal, multi-physical, multi-physiological, and multi-physical–physiological. After the classification, key insights about applications, learning models, and data sources are extracted and analyzed. This review highlights the exponential growth in studies utilizing EEG signals for emotion recognition, and the potential of multimodal approaches combining physical and physiological signals to enhance the accuracy and practicality of emotion recognition systems. This comprehensive overview of research advances, emerging trends, and limitations from 2018 to 2023 underscores the importance of continued exploration and interdisciplinary collaboration in these rapidly evolving fields.

Due to the advancement of technology, cybercrime has increased considerably, making digital forensics essential for any organisation. One of the most critical challenges is to analyse and classify the information on devices, identifying the relevant and valuable data for a specific purpose. This phase of the forensic process is one of the most complex and time-consuming, and requires expert analysts to avoid overlooking data relevant to the investigation. Although tools exist today that can automate this process, they will depend on how tightly their parameters are tuned to the case study, and many lack support for complex scenarios where language barriers play an important role. Recent advances in machine learning allow the creation of new architectures to significantly increase the performance of information analysis and perform the intelligent search process automatically, reducing analysis time and identifying relationships between files based on initial parameters. In this paper, we present a bibliographic review of artificial intelligence algorithms that allow an exhaustive analysis of multimedia information contained in removable devices in a forensic process, using natural language processing and natural language understanding techniques for the automatic classification of documents in seized devices. Finally, some of the open challenges technology developers face when generating tools that use artificial intelligence techniques to analyse the information contained in documents on seized devices are reviewed.

Since its discovery, the BTK inhibitor ibrutinib has redefined the standard treatments for hematological cancers, such as chronic lymphocytic leukemia (CLL). However, concerns exist regarding its secondary effects in humans and its occasional lack of efficacy in certain malignancies. Therefore, combined therapies with ibrutinib have emerged as promising new approaches. In this study, we aimed to explore its therapeutic potential through different approaches. For this purpose, we combined this drug with the BH3 mimetics ABT-199 and ABT-737, which inhibit anti-apoptotic members of the Bcl-2 family, and with the PDK1 inhibitor dichloroacetate (DCA), respectively. As cell models, we used ex vivo samples from patients and also selected the in vitro CLL cell line Mec-1, generating two sub-lines overexpressing Bcl-XL and Mcl-1, a common feature in this cancer. Results demonstrated a synergistic effect for both approaches, in all tumor cells tested, for both cytostatic and cytotoxic effects. Mechanistically, the expression of Bcl-2-family proteins was explored, exhibiting increases in pro-apoptotic, but also in anti-apoptotic, proteins upon ibrutinib treatment and a relative increase in the amount of the pro-apoptotic protein PUMA after treatment with DCA. Our data provides new insights into combined therapies with ibrutinib for CLL, which further expands our knowledge and the potential of this drug for cancer treatment.

Adoptive transfer of allogeneic natural killer (NK) cells is becoming a credible immunotherapy for hematological malignancies. In the present work, using an optimized expansion/activation protocol of human NK cells, we generate expanded NK cells (eNK) with increased expression of CD56 and NKp44, while maintaining that of CD16. These eNK cells exerted significant cytotoxicity against cells from 34 B-CLL patients, with only 1 sample exhibiting resistance. This sporadic resistance did not correlate with match between KIR ligands expressed by the eNK cells and the leukemic cells, while cells with match resulted sensitive to eNK cells. This suggests that KIR mismatch is not relevant when expanded NK cells are used as effectors. In addition, we found two examples of de novo resistance to eNK cell cytotoxicity during the clinical course of the disease. Resistance correlated with KIR-ligand match in one of the patients, but not in the other, and was associated with a significant increase in PD-L1 expression in the cells from both patients. Treatment of one of these patients with idelalisib correlated with the loss of PD-L1 expression and with re-sensitization to eNK cytotoxicity. We confirmed the idelalisib-induced decrease in PD-L1 expression in the B-CLL cell line Mec1 and in cultured cells from B-CLL patients. As a main conclusion, our results reinforce the feasibility of using expanded and activated allogeneic NK cells in the treatment of B-CLL.

The concealment of assets is a critical challenge in financial fraud and asset recovery investigations, posing significant obstacles for creditors and regulatory authorities. National governments commonly possess the necessary data for detecting and combating this type of fraud, typically related to personal data and asset ownership. However, this information is often dispersed across different departments within the same government and sometimes in databases shared by other countries. This leads to difficulty semantically integrating this large amount of data in various formats and correlating entities through identifying hidden relationships, which are essential in this type of analysis. In this regard, this work proposes an ontology to support the data integration process in the domain of asset concealment and recovery and fill the gap in the existence of a public ontology for this domain. The applicability of this ontology in the context of integration between data from different departments and countries was validated. The use of the ontology in a pilot project in the context of a tool for investigating this type of fraud was conducted with a Brazilian government agency, and the users validated its applicability. Finally, a new method for constructing ontologies is proposed. The proposed process was evaluated during the asset concealment ontology building and proved to be more suitable than the similar processes analyzed concerning the partial reuse of existing ontologies and the construction of ontologies for data with a transnational scope.