Upregulation of the Renin-Angiotensin System Pathways and SARS-CoV-2 Infection: The Rationale for the Administration of Zinc-Chelating Agents in COVID-19 Patients

none1noThe article describes the rationale for the administration of zinc-chelating agents in COVID-19 patients. In a previous work I have highlighted that the binding of the SARS-CoV spike proteins to the zinc-metalloprotease ACE2 has been shown to induce ACE2 shedding by activating the zinc-metalloprotease ADAM17, which ultimately leads to systemic upregulation of ACE2 activity. Moreover, based on experimental models, it was also shown the detrimental effect of the excessive systemic activity of ACE2 through its downstream pathways, which leads to "clinical" manifestations resembling COVID-19. In this regard, strong upregulation of circulating ACE2 activity was recently reported in COVID-19 patients, thus supporting the previous hypothesis that COVID-19 may derive from upregulation of ACE2 activity. Based on this, a reasonable hypothesis of using inhibitors that curb the upregulation of both ACE2 and ADAM17 zinc-metalloprotease activities and consequent positive feedback-loops (initially triggered by SARS-CoV-2 and subsequently sustained independently on viral trigger) is proposed as therapy for COVID-19. In particular, zinc-chelating agents such as citrate and ethylenediaminetetraacetic acid (EDTA) alone or in combination are expected to act in protecting from COVID-19 at different levels thanks to their both anticoagulant properties and inhibitory activity on zinc-metalloproteases. Several arguments are presented in support of this hypothesis and based on the current knowledge of both beneficial/harmful effects and cost/effectiveness, the use of chelating agents in the prevention and therapy of COVID-19 is proposed. In this regard, clinical trials (currently absent) employing citrate/EDTA in COVID-19 are urgently needed in order to shed more light on the efficacy of zinc chelators against SARS-CoV-2 infection in vivo.openZamai, LorisZamai, Lori

Multi-Span Extractive Question Answering for Named Entity Recognition

openNamed Entity Recognition (NER) is a Natural Language Processing (NLP) task that involves detecting and categorizing named entities in a text. Named entities can be names of people, organizations, locations and dates or can be specifically defined for the domain in which the NER task is adopted. NER proves helpful in a variety of applications, the most notable of which is Information Extraction, where NER allows the extraction of structured information from unstructured text. Plenty of approaches have been exploited, ranging from rule-based methods to machine-learning algorithms such as Conditional Random Fields and Hidden Markov Models, to deep-learning systems based on Recurrent Neural Networks and Transformer-based architectures. Lately, with the advent of Large Language Models (LLMs) such as GPT and in-context learning techniques, a new approach to NER has emerged: extracting named entities by posing questions and having the LLM fill in the answer with the named entities (one or more) to extract. These LLMs, employed as Generative Question Answering (GQA) models, still require careful prompt-engineering, both for dealing with inputs not fitting into the context-window, and for producing well-formatted output. If a traditional NER system detects several text spans associated with a named entity, the generative QA model should be prompted to extract the same number of text spans. Furthermore, if a named entity does not appear, the generative LLM used as QA should not produce non-existent content. Based on the above considerations, NER approached as a QA task might be a viable option, although an Extractive QA method may be more appropriate over a generative one. This thesis delves into the Extractive QA approach to NER, providing a comprehensive exploration of its core concepts and methodologies. In particular, this work will first present the operating principle of single-span EQA models, which can only extract a single span of text for each question, before moving on to the design and development of a new transformer-based model that enables Multi-Span Extractive QA, implemented according to specific guidelines so that it is a natural extension of the single-span operating principle. The proposed model is then evaluated on a NER dataset named BUSTER, where specific named entities from business transaction documents have to be extracted. Experiments and comparisons with other transformer-based NER systems, which constitute the baselines for the classical NER approach, allow to show the equal power of this Multi-span EQA approach to NER. Further investigative experiments reveal that the QA approach to NER through the proposed model implementation achieves better results in reduced training set scenarios. Future work will focus on trying to develop a technique to make the model perform Continual Learning on a sequence of NER datasets while retaining its capability to correctly respond to questions from all previously encountered datasets.Named Entity Recognition (NER) is a Natural Language Processing (NLP) task that involves detecting and categorizing named entities in a text. Named entities can be names of people, organizations, locations and dates or can be specifically defined for the domain in which the NER task is adopted. NER proves helpful in a variety of applications, the most notable of which is Information Extraction, where NER allows the extraction of structured information from unstructured text. Plenty of approaches have been exploited, ranging from rule-based methods to machine-learning algorithms such as Conditional Random Fields and Hidden Markov Models, to deep-learning systems based on Recurrent Neural Networks and Transformer-based architectures. Lately, with the advent of Large Language Models (LLMs) such as GPT and in-context learning techniques, a new approach to NER has emerged: extracting named entities by posing questions and having the LLM fill in the answer with the named entities (one or more) to extract. These LLMs, employed as Generative Question Answering (GQA) models, still require careful prompt-engineering, both for dealing with inputs not fitting into the context-window, and for producing well-formatted output. If a traditional NER system detects several text spans associated with a named entity, the generative QA model should be prompted to extract the same number of text spans. Furthermore, if a named entity does not appear, the generative LLM used as QA should not produce non-existent content. Based on the above considerations, NER approached as a QA task might be a viable option, although an Extractive QA method may be more appropriate over a generative one. This thesis delves into the Extractive QA approach to NER, providing a comprehensive exploration of its core concepts and methodologies. In particular, this work will first present the operating principle of single-span EQA models, which can only extract a single span of text for each question, before moving on to the design and development of a new transformer-based model that enables Multi-Span Extractive QA, implemented according to specific guidelines so that it is a natural extension of the single-span operating principle. The proposed model is then evaluated on a NER dataset named BUSTER, where specific named entities from business transaction documents have to be extracted. Experiments and comparisons with other transformer-based NER systems, which constitute the baselines for the classical NER approach, allow to show the equal power of this Multi-span EQA approach to NER. Further investigative experiments reveal that the QA approach to NER through the proposed model implementation achieves better results in reduced training set scenarios. Future work will focus on trying to develop a technique to make the model perform Continual Learning on a sequence of NER datasets while retaining its capability to correctly respond to questions from all previously encountered datasets

Unveiling Human Non-Random Genome Editing Mechanisms Activated in Response to Chronic Environmental Changes: I. Where Might These Mechanisms Come from and What Might They Have Led To?

none1noThis article challenges the notion of the randomness of mutations in eukaryotic cells by unveiling stress-induced human non-random genome editing mechanisms. To account for the existence of such mechanisms, I have developed molecular concepts of the cell environment and cell environmental stressors and, making use of a large quantity of published data, hypothesised the origin of some crucial biological leaps along the evolutionary path of life on Earth under the pressure of natural selection, in particular, (1) virus-cell mating as a primordial form of sexual recombination and symbiosis; (2) Lamarckian CRISPR-Cas systems; (3) eukaryotic gene development; (4) antiviral activity of retrotransposon-guided mutagenic enzymes; and finally, (5) the exaptation of antiviral mutagenic mechanisms to stress-induced genome editing mechanisms directed at "hyper-transcribed" endogenous genes. Genes transcribed at their maximum rate (hyper-transcribed), yet still unable to meet new chronic environmental demands generated by "pollution", are inadequate and generate more and more intronic retrotransposon transcripts. In this scenario, RNA-guided mutagenic enzymes (e.g., Apolipoprotein B mRNA editing catalytic polypeptide-like enzymes, APOBECs), which have been shown to bind to retrotransposon RNA-repetitive sequences, would be surgically targeted by intronic retrotransposons on opened chromatin regions of the same "hyper-transcribed" genes. RNA-guided mutagenic enzymes may therefore "Lamarkianly" generate single nucleotide polymorphisms (SNP) and gene copy number variations (CNV), as well as transposon transposition and chromosomal translocations in the restricted areas of hyper-functional and inadequate genes, leaving intact the rest of the genome. CNV and SNP of hyper-transcribed genes may allow cells to surgically explore a new fitness scenario, which increases their adaptability to stressful environmental conditions. Like the mechanisms of immunoglobulin somatic hypermutation, non-random genome editing mechanisms may generate several cell mutants, and those codifying for the most environmentally adequate proteins would have a survival advantage and would therefore be Darwinianly selected. Non-random genome editing mechanisms represent tools of evolvability leading to organismal adaptation including transgenerational non-Mendelian gene transmission or to death of environmentally inadequate genomes. They are a link between environmental changes and biological novelty and plasticity, finally providing a molecular basis to reconcile gene-centred and "ecological" views of evolution.openZamai, LorisZamai, Lori

Ultrastructural Features of Apoptosis

Apoptosis is a gene-directed physiological and programmed process of cell deletion aimed at the regulation of tissue and organ development. It affects different cell types and is triggered by a variety of stimuli all inducing closely comparable structural changes. Despite the deeply different morphology and metabolism of the cell models and the various inducers and their initial effects, a convergence seems to take place in a common metabolic pathway that, in most cases, involves the activation of a Ca2+ dependent endonuclease. A growing body of data is now available on the molecular events that lead to DNA damage. DNA cleavage in nucleosomic or oligonucleosomic fragments is related to the appearance of unusual and very characteristic ultrastructural changes. The nucleus is especially affected, and shows chromatin rearrangements consisting of cup-shaped marginations, sharply separated from diffuse chromatin areas. Nuclear fragmentation subsequently appears, finally followed by the formation of numerous micronuclei. Cytoplasmic damage appears at a very late stage and the process takes place despite good preservation of plasma membrane and cytoplasm

Framework para gestão de informações institucionais no Sistema Nacional de Inovação

Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro Tecnológico. Programa de Pós-Graduação em Ciência da Computação.Neste trabalho propõe-se um framework (i.e., uma estrutura que dá suporte à construção de aplicações em um mesmo domínio, de forma genérica, extensível e reutilizável) para a gestão de informações referentes a instituições em sistemas de governo ligados à Ciência, Tecnologia e Inovação. O framework proposto foi aplicado ao domínio da gestão de informações institucionais em C&T, com o desenvolvimento do Diretório de Instituições da Plataforma Lattes do CNPq. Como resultado tornou-se possível gerenciar as informações sobre as organizações do sistema brasileiro de C&T de forma dinâmica, flexível e interoperável

Endothelial cells, endoplasmic reticulum stress and oxysterols

Oxysterols are bioactive lipids that act as regulators of lipid metabolism, inflammation, cell viability and are involved in several diseases, including atherosclerosis. Mounting evidence linked the atherosclerosis to endothelium dysfunction; in fact, the endothelium regulates the vascular system with roles in processes such as hemostasis, cell cholesterol, hormone trafficking, signal transduction and inflammation. Several papers shed light the ability of oxysterols to induce apoptosis in different cell lines including endothelial cells. Apoptotic endothelial cell and endothelial denudation may constitute a critical step in the transition to plaque erosion and vessel thrombosis, so preventing the endothelial damaged has garnered considerable attention as a novel means of treating atherosclerosis. Endoplasmic reticulum (ER) is the site where the proteins are synthetized and folded and is necessary for most cellular activity; perturbations of ER homeostasis leads to a condition known as endoplasmic reticulum stress. This condition evokes the unfolded protein response (UPR) an adaptive pathway that aims to restore ER homeostasis. Mounting evidence suggests that chronic activation of UPR leads to cell dysfunction and death and recently has been implicated in pathogenesis of endothelial dysfunction. Autophagy is an essential catabolic mechanism that delivers misfolded proteins and damaged organelles to the lysosome for degradation, maintaining basal levels of autophagic activity it is critical for cell survival. Several evidence suggests that persistent ER stress often results in stimulation of autophagic activities, likely as a compensatory mechanism to relieve ER stress and consequently cell death. In this review, we summarize evidence for the effect of oxysterols on endothelial cells, especially focusing on oxysterols-mediated induction of endoplasmic reticulum stress