Ochratoxin a removal from red wine by several oenological fining agents: Bentonite, egg albumin, allergen-free adsorbents, chitin and chitosan

The ability of several oenological fining agents to remove ochratoxin A (OTA) from red wine was studied. The adsorbents tested were activated sodium bentonite, egg albumin, allergen-free adsorbents (complex PVPP, plant protein and amorphous silica (complex) and high molecular weight gelatine), and the non-toxic biodegradable polymers (chitin and chitosan). Several dosages within the oenological use range were tested and the wine pH, colour parameters and polyphenol concentration impact associated with each fining agent were studied. Generally, OTA removal achieved in all treatments was higher when the adsorbent dosage increased, but the impact on wine quality also was higher. Chitin at 50ghl_1 removed 18% the OTA without affecting significantly the wine-quality parameters. At the highest dosage tested the gelatine and complex treatments achieved greater OTA removal (up to 39-40%) compared with bentonite, egg albumin and chitin. Moreover, the gelatine and the complex had a lower impact on colour parameters and polyphenol concentration compared with chitosan, whilst OTA was reduced to around 40%. Chitosan achieved the greatest OTA removal (67%), but it strongly affected the wine-quality parameters. Otherwise, bentonite showed a relative efficiency to remove OTA, but the CI value decreased considerably. The egg albumin treatment only removed OTA up to 16% and moreover affected strongly the CI value and CIELab parameters. The results of this survey showed that the non-toxic chitin adsorbent and the allergen-free adsorbents tested could be considered as alternative fining agents to reduce OTA in red wine.Peer reviewe

Staphylococcus aureus Alpha-Toxin Induces the Formation of Dynamic Tubules Labeled with LC3 within Host Cells in a Rab7 and Rab1b-Dependent Manner

Staphylococcus aureus is a pathogen that causes severe infectious diseases that eventually lead to septic and toxic shock. S. aureus infection is characterized by the production of virulence factors, including enzymes and toxins. After internalization S. aureus resides in a phagosome labeled with Rab7 protein. Here, we show that S. aureus generates tubular structures marked with the small GTPases Rab1b and Rab7 and by the autophagic protein LC3 at early times post-infection. As shown by live cell imaging these tubular structures are highly dynamic, extend, branch and grow in length. We have named them S. aureus induced filaments (Saf). Furthermore, we demonstrate that the formation of these filaments depends on the integrity of microtubules and the activity of the motor protein Kinesin-1 (Kif5B) and the Rab-interacting lysosomal protein (RILP). Our group has previously reported that α-hemolysin, a secreted toxin of S. aureus, is responsible of the activation of the autophagic pathway induced by the bacteria. In the present report, we demonstrate that the autophagic protein LC3 is recruited to the membrane of S. aureus induced filaments and that α-hemolysin is the toxin that induces Saf formation. Interestingly, increasing the levels of intracellular cAMP significantly inhibited Saf biogenesis. Remarkably in this report we show the formation of tubular structures that emerge from the S. aureus-containing phagosome and that these tubules generation seems to be required for efficient bacteria replication

Large Language Model Operations (LLMOps): Definition, Challenges, and Lifecycle Management

Publisher Copyright: © 2024 University of Split, FESB.Numerous studies explore the prospects presented by the recent upsurge of large language models. The usage of LLMs in production environments poses challenges that highlight the limitations of methodologies such as MLOps, and further investigation in this field is required. To this end, a new methodology, coined large language model operations (LLMOps), has arisen to address the particularities of LLMs. This term is so recent that the scientific literature has not yet agreed on a common definition for it, and the use of non-peer reviewed studies becomes a must. In this research, we review the current literature in the field to shed light on the adoption of LLMOps to drive innovation and efficiency in deploying large language models in real-world applications. To this end, three research questions are used to guide the contribution to the scientific literature with a unified definition of LLMOps, the challenges posed by LLMs that require the need for this new methodology, and to outline the key stages of LLMOps and their particularities that must be considered.Peer reviewe

Edge intelligence secure frameworks: Current state and future challenges

Publisher Copyright: © 2023At the confluence of two great paradigms such as Edge Computing and Artificial Intelligence, Edge Intelligence arises. This new concept is about the smart exploitation of Edge Computing by bringing together reasoning and learning by Artificial Intelligence algorithms and the sensors/actuators computing capabilities. Security is the third paradigm that must join the team in order to have resilient and reliable systems to be used in real-world applications and use cases. Hence, smartness is, in this context, a puzzle of several independent pieces which, once fitted, can derived unprecedented benefits: a) security, b) low communication latency and network load, c) cost and energy saving and d) scalability by means of resource virtualization close to the IoT data generators (IoT devices). In fact, by paying exclusive attention to some of those main pillars and, therefore, disregarding others, edge computation once in operation often suffers from bad performance, unforeseen events or does not exploit the enormous potential that should be unlocked if a proper and complete specification had been laid down. With all this in mind, this work provides a technical review of the available and up-to-date frameworks to implement secure Edge Intelligence, pinpoints the most relevant unfilled gaps (strengths and weaknesses) and, last but nos least, includes challenges and future research lines as a result of our exploration.This work has received funding, in the context of TERMINET project, from the European Unions Horizon 2020 research and innovation program under Grant agreement ID: 957406.Peer reviewe

Akats: A System for Resilient Deployments on Edge Computing Environments Using Federated Machine Learning Techniques

Publisher Copyright: © 2023 University of Split, FESB.Edge computing is a game changer for IoT, as it allows IoT devices to independently process and analyze data instead of just sending it to the cloud. But managing this considerable number of devices and deploying workloads on them in a coordinated and intelligent manner remains a challenge nowadays. In this paper, we focus on introducing the resilience dimension into these deployments, and we provide two main contributions: the use of federated machine learning techniques to develop a collaborative tool between the different devices aimed at detecting the possibility of a device failure, and subsequently, the utilization of the inferred information to optimize deployment plans ensuring the resilience in the devices. These two advances are implemented in an intelligent system, Akats, whose architecture is described in detail in this article. Finally, an application scenario is presented, based on Industry 4.0 - Machine predictive maintenance, to exemplify the benefits of the proposed intelligent system.ACKNOWLEDGMENT This work has been partially financed by the Basque Government through the Elkartek program (EGIA project, Grant KK-2022/00119).Peer reviewe

CCIR: An Architecture for Collecting and Storing Connnected Corridor Infrastructure and Mobility Data

Publisher Copyright: © 2023 IEEE.Connected corridors are programs and initiatives that emerge under the umbrella of major paradigms such as SmartCities, Big Data, Artificial Intelligence or Internet of Things (IoT). Their main objective is to provide environments for testing, validating and demonstrating all kinds of technologies related to Cooperative, Connected and Autonomous Mobility, and Intelligent and Digital Infrastructures, within a real scenario. These corridors need to equip themselves with new intelligent and extremely powerful systems, based on technologies such as intelligent traffic systems. They aim to enhance and evolve these systems by leveraging the possibilities and solutions offered by this new wave of disruptive technologies allows. In this article, we describe the needs of a crucial component for connected corridors, such as the information repository, and we propose its possible technological implementation using the Data Lake paradigm, with a focus on data interoperability as a primary requirement. Finally, we validate the significant usefulness of the proposed architecture for the connected corridor information repository, called CCIR, through the concrete implementation of a specific collaborative corridor, such as the Bizkaia Connected Corridor - BCC is. To demonstrate it, we present different use cases that exploit the data generated and collected in the BCC environment relative to the infrastructure and mobility domain.Peer reviewe

Propuesta de planificación ambiental costera del sector Bahía de los Vientos hasta Costa Bonita, provincia de Buenos Aires

El presente estudio se desarrolla a lo largo de 6 km de costa, al Este del Puerto de Quequén, Partido de Necochea, provincia de Buenos Aires. En este sector históricamente se vinculan varios usos del territorio en relación con las actividades económicas dominantes, la portuaria, la navegación, la pesca y las actividades deportivas, recreativas y turísticas.La recuperación económica iniciada en los últimos años ha impulsado el desarrollo y la expansión de actividades en el sector de playa comprendido entre la Escollera Noreste y Costa Bonita. Los sistemas implicados corresponden a las áreas marina-litoral y litoral-urbana, las cuales están sometidas a múltiples jurisdicciones derivadas de las acciones de las instituciones encargadas de su preservación, desarrollo y administración.En este aporte se proponen zonificaciones en función de la vocación del territorio para el establecimiento de diversas actividades favoreciendo la radicación de usos compatibles del área costera desde Bahía de Los Vientos hasta Costa Bonita.Las propuestas de sectorización se basan en el análisis de datos obtenidos de relevamientos sistemáticos efectuados en el lapso 2005-2010 en 10 perfiles. Se consideró el patrón de variación del ancho de playa (desde la línea de bajamar hasta la base del acantilado o espaldón, según correspondiese), del volumen de material sedimentario y de las características granulométricas del sedimento

Experience-dependent modification of a central amygdala fear circuit

The amygdala is essential for fear learning and expression. The central amygdala (CeA), once viewed as a passive relay between the amygdala complex and downstream fear effectors, has emerged as an active participant in fear conditioning. However, the mechanism by which CeA contributes to the learning and expression of fear is unclear. We found that fear conditioning in mice induced robust plasticity of excitatory synapses onto inhibitory neurons in the lateral subdivision of the CeA (CeL). This experience-dependent plasticity was cell specific, bidirectional and expressed presynaptically by inputs from the lateral amygdala. In particular, preventing synaptic potentiation onto somatostatin-positive neurons impaired fear memory formation. Furthermore, activation of these neurons was necessary for fear memory recall and was sufficient to drive fear responses. Our findings support a model in which fear conditioning-induced synaptic modifications in CeL favor the activation of somatostatin-positive neurons, which inhibit CeL output, thereby disinhibiting the medial subdivision of CeA and releasing fear expression