Risk factors for invasive aspergillosis in ICU patients with COVID-19: current insights and new key elements

Abstract Invasive pulmonary aspergillosis (IPA) has always been a challenging diagnosis and risk factors an important guide to investigate specific population, especially in Intensive Care Unit. Traditionally recognized risk factors for IPA have been haematological diseases or condition associated with severe immunosuppression, lately completed by chronic conditions (such as obstructive pulmonary disease, liver cirrhosis, chronic kidney disease and diabetes), influenza infection and Intensive Care Unit (ICU) admission. Recently, a new association with SARS-CoV2 infection, named COVID-19-associated pulmonary aspergillosis (CAPA), has been reported worldwide, even if its basic epidemiological characteristics have not been completely established yet. In this narrative review, we aimed to explore the potential risk factors for the development of CAPA and to evaluate whether previous host factors or therapeutic approaches used in the treatment of COVID-19 critically ill patients (such as mechanical ventilation, intensive care management, corticosteroids, broad-spectrum antibiotics, immunomodulatory agents) may impact this new diagnostic category. Reviewing all English-language articles published from December 2019 to December 2020, we identified 21 papers describing risk factors, concerning host comorbidities, ICU management, and COVID-19 therapies. Although limited by the quality of the available literature, data seem to confirm the role of previous host risk factors, especially respiratory diseases. However, the attention is shifting from patients’ related risk factors to factors characterizing the hospital and intensive care course, deeply influenced by specific features of COVID treatment itself. Prolonged invasive or non-invasive respiratory support, as well as the impact of corticosteroids and/or immunobiological therapies seem to play a pivotal role. ICU setting related factors, such as environmental factors, isolation conditions, ventilation systems, building renovation works, and temporal spread with respect to pandemic waves, need to be considered. Large, prospective studies based on new risk factors specific for CAPA are warranted to guide surveillance and decision of when and how to treat this particular population

ESTUDO FITOQUÍMICO E DE ATIVIDADE ANTIMICROBIANA DE Ptychopetalum olacoides Bentham

A espécie Ptychopetalum olacoides Bentham, popularmente conhecida como marapuama ou muirapuama, é uma Olacaceae nativa da região norte do Brasil, há muito conhecida e utilizada por suas propriedades estimulantes e afrodisíacas, sendo inclusive exportada para diversos países. O estudo fitoquímico do lenho desta árvore, neste trabalho representado pelos galhos da planta, revelou a presença majoritária de vários ácidos graxos, esteróides e xantinas, sendo eles: ácido palmítico, ácido esteárico, -sitosterol, estigmasterol, lupeol, glutinol, a-amirina, cafeína, teobromina e adenina, sendo que as três últimas não haviam ainda sido reportadas na espécie. O estudo das atividades antimicrobianas revelou que os extratos da planta não apresentam atividade inibitória sobre o desenvolvimento de cepas de Escherichia coli, Staphylococcus aureus ou Staphylococcus epidermidis. Porém, o resíduo do extrato alcoólico apresenta uma significativa ação inibitória do crescimento micelial de Colletotrichum acutatum, e ação menos pronunciada sobre o crescimento de Fusarium oxysporum. PHYTOCHEMICAL STUDY AND ANTIMICROBIAL ACTIVITY OF Ptychopetalumolacoides Bentham Abstract Ptychopetalum olacoides Bentham, popularly known as marapuama or muirapuama, is an Olacaceae native from north Brazil, known and used for its stimulating and aphrodisiac properties for a long time, being also exported to several countries all over the world. The phytochemical study of the wood of this tree, represented by its stems, revealed the presence of several fatty acids, sterols and xanthines, including palmitic acid, stearic acid, -sitosterol, stigmasterol, lupeol, glutinol, a-amirin, caffeine, theobromine and adenine, and the latest three substances have not been reported in this specie yet. The study of antimicrobial properties revealed that the plant extracts dont have any inhibitory activity against strains of Escherichia coli, Staphylococcus aureus or Staphylococcus epidermidis. However, the alcoholic extract residue does have a remarkable inhibitory action on the mycelial growth of Colletotrichum acutatum and Fusarium oxysporum.2

Neural-powered unit disk graph embedding: qubits connectivity for some QUBO problems

Graph embedding is a recurrent problem in quantum computing, for instance, quantum annealers need to solve a minor graph embedding in order to map a given Quadratic Unconstrained Binary Optimization (QUBO) problem onto their internal connectivity pattern. This work presents a novel approach to constrained unit disk graph embedding, which is encountered when trying to solve combinatorial optimization problems in QUBO form, using quantum hardware based on neutral Rydberg atoms. The qubits, physically represented by the atoms, are excited to the Rydberg state through laser pulses. Whenever qubits pairs are closer together than the blockade radius, entanglement can be reached, thus preventing entangled qubits to be simultaneously in the excited state. Hence, the blockade radius determines the adjacency pattern among qubits, corresponding to a unit disk configuration. Although it is straight-forward to compute the adjacency pattern given the qubits' coordinates, identifying a feasible unit disk arrangement that matches the desired QUBO matrix is, on the other hand, a much harder task. In the context of quantum optimization, this issue translates into the physical placement of the qubits in the 2D/3D register to match the machine's Ising-like Hamiltonian with the QUBO formulation of the optimization problems. The proposed solution exploits the power of neural networks to transform an initial embedding configuration, which does not match the quantum hardware requirements or does not account for the unit disk property, into a feasible embedding properly representing the target optimization problems. Experimental results show that this new approach overcomes in performance Gurobi solver