Gene knockdown in Paracoccidioides brasiliensis using antisense RNA

Paracoccidioides brasiliensis is a thermal dimorphic fungus which at host environment exhibits a multinucleated and multibudding yeast form. The cellular and molecular mechanisms underlying these phenotypes remain to be clarified, mostly due to the absence of efficient classical genetic and molecular techniques. Here we describe a method for gene expression knockdown in P. brasiliensis by antisense RNA (aRNA) technology taking advantage of an Agrobacterium tumefaciens-mediated transformation (ATMT) system. Together, these techniques represent a reliable toolbox that can be employed for functional genetic analysis of putative virulence factors and morphogenic regulators, aiming to the identification of new potential drug targets.Fundação para a Ciência e a Tecnologia, Portugal (FCT) - Ref. PTDC/BIA-MIC/108309/2008, Ref. SFRH/BD/33446/2008)

Polinizadores de bertholletia excelsa (Lecythidales: Lecythidaceae): interações com abelhas sem ferrão (Apidae: Meliponini) e nicho trófico

This paper presents an analysis of the foraging behavior and interactions of Xylocopa frontalis Olivier (Apidae: Xylocopini) and Eulaema mocsaryi (Friese) (Apidae: Euglossini) in the presence of stingless bees (Apidae: Meliponini) in flowers of Bertholletia excelsa, the Brazilian nut. The palynological load carried by both species was also examined. This study was conducted in the farm Aruanã, Itacoatiara/ Amazonas state, Brazil, during the flowering peak of B. excelsa. The visitation by the main pollinators X. frontalis and E. mocsaryi were influenced by the presence and activities of stingless bees in the flowers of B. excelsa. Meliponini bees did not have any effect on the visits and collection of fl oral resources by X. frontalis, while negatively affecting the number of visits by E. mocsaryi. The stingless bees presented a variety of strategies to get access to pollen grains of B. excelsa, grouped into two categories: opportunism - Frieseomelitta trichocerata Moure, Tetragona goettei (Friese), and Tetragona kaieteurensis (Schwarz), and stealing - Trigona branneri Cockerell, Trigona fuscipennis Friese, and Trigona guianae Cockerell. The palynological analysis from X. frontalis showed that the bee collected pollen in a few species of plants, but mainly on B. excelsa. The pollen grains of B. excelsa were poorly represented in the pollen shipments of E. mocsaryi, due to its large trophic niche in the locality

A Multi-level Approach to Evaluate the Impact of GPU Permanent Faults on CNN's Reliability

Graphics processing units (GPUs) are widely used to accelerate Artificial Intelligence applications, such as those based on Convolutional Neural Networks (CNNs). Since in some domains in which CNNs are heavily employed (e.g., automotive and robotics) the expected lifetime of GPUs is over ten years, it is of paramount importance to study the impact of permanent faults (e.g. due to aging). Crucially, while the impact of transient faults on GPUs running CNNs has been widely studied, an accurate evaluation of the impact of permanent faults is still lacking. Performing this evaluation is challenging due to the complexity of GPU devices and the software implementing a CNN. In this work, we propose a methodology that combines the accuracy of gate-level fault simulation with the speed and flexibility of software fault injection to evaluate the effects of permanent hardware faults affecting a GPU. First, we profile the executed low-level GPU instructions during the CNN inference. Then, using extensive gate-level fault injection campaigns, we provide an accurate analysis of the effects of permanent faults on the internal modules executing the targeted instructions. Finally, we propagate these effects using fast software-based fault injection. The method allows, for the first time, to estimate the percentage of permanent faults leading the CNN to produce wrong results (i.e., changing the result of its work). The method's feasibility, which allows for flexibly trade-off accuracy with the required computational effort, is shown using LeNet running on an Ampere Nvidia GPU as a case study. The method reduces the computational effort for the evaluation by several orders of magnitude with respect to plain gate- and RTL-level faults simulation

Paving the way for predictive diagnostics and personalized treatment of invasive aspergillosis

Invasive aspergillosis (IA) is a life-threatening fungal disease commonly diagnosed among individuals with immunological deficits, namely hematological patients undergoing chemotherapy or allogeneic hematopoietic stem cell transplantation. Vaccines are not available, and despite the improved diagnosis and antifungal therapy, the treatment of IA is associated with a poor outcome. Importantly, the risk of infection and its clinical outcome vary significantly even among patients with similar predisposing clinical factors and microbiological exposure. Recent insights into antifungal immunity have further highlighted the complexity of host-fungus interactions and the multiple pathogen-sensing systems activated to control infection. How to decode this information into clinical practice remains however, a challenging issue in medical mycology. Here, we address recent advances in our understanding of the host-fungus interaction and discuss the application of this knowledge in potential strategies with the aim of moving toward personalized diagnostics and treatment (theranostics) in immunocompromised patients. Ultimately, the integration of individual traits into a clinically applicable process to predict the risk and progression of disease, and the efficacy of antifungal prophylaxis and therapy, holds the promise of a pioneering innovation benefiting patients at risk of IA.CC is supported by the Fundação para a Ciência e Tecnologia, Portugal (SFRH/BPD/96176/2013

Are we still chasing molecules that were never there? The role of quantum chemical simulations of NMR parameters in structural reassignment of natural products

Covering: 2019 to 2023. Even with the advent of modern and complementary spectroscopy techniques, comprehensive characterization of natural product continues to represent an onerous and time-consuming task, being far away to become rather “routine”. Mainly due to their highly complex structures and small amount of isolated sample, in milligram or sub-milligram quantities, structural misassignment of natural products are still a recurrence theme in the modern literature. Since the seminal paper from Nicolau and Snider, in 2005, evaluating the various cases of reassignment of natural products, from the present era, in which NMR parameters calculations play such an important role in the structural elucidation of natural products, helping to uncover and ultimately revise the structure of previously reported compounds, a pertinent question arises: are we still chasing molecules that were never there? In this minireview, we intent to discuss the current state of computational NMR parameter calculations, with a particular focus on their application in the structural determination of natural products. Additionally, we have conducted a comprehensive survey of the literature spanning the years 2019–2023, in order to select and discuss recent noteworthy cases of incorrectly assigned structures that were revised through NMR calculations. Therefore, our main goal is to show what can be done through computational simulations of NMR parameters, currently user-friendly and easily implemented by non-expert users with basic skills in computational chemistry, before venturing into complex and time-consuming total synthesis projects. In conclusion, we anticipate a promising future for NMR parameter calculations, fueled by the ongoing development of user-friendly tools and the integration of artificial intelligence. The emergence of these advancements is poised to broaden the applications of NMR simulations, offering a more accessible and reliable means to address the persistent challenge of structural misassignments in natural product chemistry

Application of flow cytometry for the identification of Staphylococcus epidermidis by peptide nucleic acid fluorescence in situ hybridization (PNA FISH) in blood samples

Staphylococcus epidermidis is considered to be one of the most common causes of nosocomial bloodstream infections, particularly in immune-compromised individuals. Here, we report the development and application of a novel peptide nucleic acid probe for the specific detection of S. epidermidis by fluorescence in situ hybridization. The theoretical estimates of probe matching specificity and sensitivity were 89 and 87%, respectively. More importantly, the probe was shown not to hybridize with closely related species such as Staphylococcus aureus. The method was subsequently successfully adapted for the detection of S. epidermidis in mixed-species blood cultures both by microscopy and flow cytometry.This work was supported by the Portuguese Institute Fundacao para a Ciencia e Tecnologia (PhD Fellowship SFRH/BD/29297/2006 and Post-Doc Fellowship SFRH/BPD/42208/2007)