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Abstract The main objective of the present work was to highlight differences and similarities in gene expression patterns between different pluripotent stem cell cardiac differentiation protocols, using a workflow based on unsupervised machine learning algorithms to analyse the transcriptome of cells cultured as a 2D monolayer or as 3D aggregates. This unsupervised approach effectively allowed to portray the transcriptomic changes that occurred throughout the differentiation processes, with a visual representation of the entire transcriptome. The results allowed to corroborate previously reported data and also to unveil new gene expression patterns. In particular, it was possible to identify a correlation between low cardiomyocyte differentiation efficiencies and the early expression of a set of non-mesodermal genes, which can be further explored as predictive markers of differentiation efficiency. The workflow here developed can also be applied to analyse other stem cell differentiation transcriptomic datasets, envisaging future clinical implementation of cellular therapies.

Stryphnodendron pulcherrimum is a plant found in the Brazilian Amazon and contains high content of catechin/(epi)catechin (flavan-3-ol) derivatives. The polymerization of this kind of flavan-3-ol generates condensed tannins, often associated to plant-based diets and gut microbiota. Thus, the discovery of condensed tannins from plants is a valuable approach once it enhances their availability from natural sources. Herein, we described a tetrameric condensed tannin (Molecular Mass 1,170 a.m.u.) tentatively identified for the first time in the barks from S. pulcherrimum. Condensed tannins-derived (flavan-3-ols units) are likely degraded in the gut, and their degradation products such as 3-hydroxyphenylacetic acid (OPAC), 3,4-dihydroxyphenylacetic acid (DHAA), 3-(3,4-dihydroxyphenyl)-propionic acid (DHPA), and 5-(3′,4′-dihydroxyphenyl)-γ-valerolactone (DHPV) could present benefits to gut microbiome metabolism. Therefore, this observational study represents a new insight into S. pulcherrimum, its molecules, and their potential benefits to avoid different diseases and gut well-functional.

Direct Write Laser (DWL) Grayscale (GS) lithography has gathered attention as a versatile technological solution to fabricate arbitrary and complex 2.5D structures in photoresist (PR). In combination with Reactive Ion Etching (RIE), DWL GS can enable the fabrication of 2.5D micro-structured silicon substrates to be used as molds in high-precision replication processes. To this end, typically, a multilevel pattern is first defined in a low contrast PR and then transferred to the Si substrate via anisotropic RIE. The uniformity and selectivity of the etching process to the PR and substrate materials will define the dimensions of the 2.5D structures in the substrate. However, while there have been numerous examples of etched shapes in Si using this strategy, the wafer scale dimensional variations for etched Si molds fabricated via DWL GS and RIE have not been reported so far. In this work, we present a wafer-scale and wafer-to-wafer analysis of the dimensional variations in the fabrication process of Si molds with 2.5D 100-μm deep cavities using DWL GS lithography and RIE. The dimensional variations and deviations were characterized along each process step over several wafers. The final Si etched shapes consisting of microlens array cavities showed a maximum relative deviation of 10.35% with respect to the intended shape design with a curvature radius variation up to ∼5%, demonstrating this process potential for arbitrary 2.5D Si mold fabrication.

Water-based drilling fluids (WBDF) are often used over oil-based drilling fluids due to economic reasons and environmental regulations. Bentonite-free WBDF is preferred to aid in the reduction of formation damage. In many cases, this WBDF is formulated with xanthan gum. The performance of drilling operations is mainly affected by the drilling fluid formulation. The complex interactions among polymer concentration, thermal, and shear histories influence the rheological behavior of drilling fluids. The present study aims to analyze the effects of xanthan gum concentration on the rheological behavior of water-based drilling fluids. The experimental results performed in rotational rheometers revealed a relationship between concentration, yield stress, and thixotropic phenomena. The increase in xanthan gum concentration not only enhances the stability of the drilling fluid, allowing for more prolonged process interruptions without risking the fluid degradation but also improves the thermal stability of the sample. These findings show that the concentration of xanthan gum improves water-based drilling fluids' rheological and thermal stability. [ABSTRACT FROM AUTHOR]

Swietenia macrophylla King is a plant commonly known as Brazilian mahogany. The wood from its stem is highly prized for its exceptional quality, while its leaves are valued for their high content of phragmalin-type limonoids, a subclass of compounds known for their significant biological activities, including antimalarial, antitumor, antiviral, and anti-inflammatory properties. In this context, twelve isolated limonoids from S. macrophylla leaves were employed as standards in mass spectrometry-based molecular networking to unveil new potential mass spectrometry signatures for phragmalin-type limonoids. Consequently, ultra-performance liquid chromatography coupled with high-resolution mass spectrometry was utilized for data acquisition. Subsequently, the obtained data were analyzed using the Global Natural Products Social Molecular Networking platform based on spectral similarity. In summary, this study identified 24 new putative phragmalin-type limonoids for the first time in S. macrophylla. These compounds may prove valuable in guiding future drug development efforts, leveraging the already established biological activities associated with limonoids.

Diffractive lenses can replicate the optical functions of their refractive counterparts using an equivalent surface relief phase profile, enabling more compact optical assemblies and microsystem integration. Greyscale lithography enables the direct definition of tridimensional photoresist lenses atop glass substrates, providing a simple nanofabrication process for complex micro-optics, compatible with nanoimprint replication. In this work, we report the greyscale fabrication and optical characterization of 10 × 10 mm2, NA ≈ 0.25, photoresist diffractive lenses for near-infrared LIDAR applications and evaluate their optical performance in the visible range for imaging. We demonstrate a two-lens varifocal system integrating diffractive lenses for λ = 1550 nm operation with a 55–215 mm focal length tuning range and an average spot size of ø188 ± 82 μm. In addition, we characterize the strong longitudinal chromatic aberration, typical of diffractive lenses, and evaluate their optical performance for imaging in the visible range.

Objectives: Past suicide attempt (SA) is one of the most important risk factors for suicide death. An ideation-to-action framework posits that impulsivity, potentially traumatic events, and mental disorders also play a role in increasing suicide risk. This study aimed to assess the association between trait impulsivity, lifetime exposure to trauma, and post-traumatic stress disorder (PTSD) with SA in a sample of Brazilian college students. Methods: A total of 2,137 participants filled self-reported questionnaires consisting of a sociodemographic and clinical questionnaire, Trauma History Questionnaire, Post-Traumatic Stress Disorder Checklist – Civilian version, and Barratt Impulsiveness Scale. Results: Our findings suggest that trait impulsivity may be interpreted as exerting a distal effect on SA, even in the presence of other variables – such as trauma history, psychological neglect, and PTSD – which also increase the odds of SA. High and medium levels of impulsivity, history of trauma, and PTSD increased the likelihood of SA. Conclusions: Intervention strategies to prevent SA may target trait impulsivity and exposure to traumatic experiences.

Over recent years, the field of cell and gene therapy has witnessed rapid growth due to the demonstrated benefits of using living cells as therapeutic agents in a broad range of clinical studies and trials. Bioprocess economic models (BEMs) are fundamental tools for guiding decision-making in bioprocess design, being capable of supporting process optimization and helping to reduce production costs. These tools are particularly important when it comes to guiding manufacturing decisions and increasing the likelihood of market acceptance of cell-based therapies, which are often cost-prohibitive because of high resource and quality control costs. Not only this, but the inherent biological variability of their underlying bioprocesses makes them particularly susceptible to unforeseen costs arising from failed or delayed production batches. The present work reviews important concepts concerning the development of bioprocesses for stem cell therapy products and highlights the valuable role which BEMs can play in this endeavor. Additionally, some theoretical concepts relevant to the building and structuring of BEMs are explored. Finally, a comprehensive review of the existent BEMs so far reported in the scientific literature for stem cell-related bioprocesses is provided to showcase their potential usefulness.

Deguelia nitidula (Benth.) A.M.G.Azevedo & R.A.Camargo (Fabaceae) is an herbaceous plant distributed in the Brazilian Amazon, and it is called “raiz do sol” (sun roots). On Marajó Island, quilombola communities use its prepared roots to treat skin diseases commonly caused by fungi, viruses, and bacteria. Thus, in this study, the extract, and its fractions from D. nitidula roots were used to perform in vitro cytotoxic and antibacterial assays against Staphylococcus aureus strains. Thereafter, liquid chromatography–mass spectrometry (LC–MS) was used for the metabolite annotation process. The ethanolic extract of D. nitidula roots show significant bactericidal activity against S. aureus with IC50 82 μg.mL−1 and a selectivity index (SI) of 21.35. Furthermore, the SREFr2 and SREFr3 fractions show a potent bactericidal activity, i.e., MIC of 46.8 μg.mL−1 for both, and MBC of 375 and 93.7 μg.mL−1, respectively. As showcased, SREFr3 shows safe and effective antibacterial activity mainly in respect to the excellent selectivity index (SI = 82.06). On the other hand, SREFr2 shows low selectivity (SI = 6.8), which characterizes it as not safe for therapeutic use. Otherwise, due to a limited amount of reference MS2 spectra in public libraries, up to now, it was not possible to perform a complete metabolite annotation. Despite that, our antibacterial results for SREFr3 and correlated substructures of amino acid derivatives show that the roots of D. nitidula are a natural source of specialized metabolites, which can be isolated in the future, and then used as a support for further bio-guided research, as well as natural drug development.

Abstract Background Since their inception, human induced pluripotent stem cells (hiPSCs) have held much promise for pharmacological applications and cell-based therapies. However, their potential can only be realised if large numbers of cells can be produced reproducibly on-demand. While bioreactors are ideal systems for this task, due to providing agitation and control of the culture parameters, the common impeller geometries were not designed for the expansion of mammalian cells, potentially leading to sub-optimal results. Results This work reports for the first time the usage of the novel Vertical-Wheel single-use bioreactors for the expansion of hiPSCs as floating aggregates. Cultures were performed in the PBS MINI 0.1 bioreactor with 60 mL of working volume. Two different culture media were tested, mTeSR1 and mTeSR3D, in a repeated batch or fed-batch mode, respectively, as well as dextran sulfate (DS) supplementation. mTeSR3D was shown to sustain hiPSC expansion, although with lower maximum cell density than mTeSR1. Dextran sulfate supplementation led to an increase in 97 and 106% in maximum cell number when using mTeSR1 or mTeSR3D, respectively. For supplemented media, mTeSR1 + DS allowed for a higher cell density to be obtained with one less day of culture. A maximum cell density of (2.3 ± 0.2) × 106 cells∙mL− 1 and a volumetric productivity of (4.6 ± 0.3) × 105 cells∙mL− 1∙d− 1 were obtained after 5 days with mTeSR1 + DS, resulting in aggregates with an average diameter of 346 ± 11 μm. The generated hiPSCs were analysed by flow cytometry and qRT-PCR and their differentiation potential was assayed, revealing the maintenance of their pluripotency after expansion. Conclusions The results here described present the Vertical-Wheel bioreactor as a promising technology for hiPSC bioprocessing. The specific characteristics of this bioreactor, namely in terms of the innovative agitation mechanism, can make it an important system in the development of hiPSC-derived products under current Good Manufacturing Practices.

Momordica charantia L. (Cucurbitaceae) is a plant known in Brazil as “melão de São Caetano”, which has been related to many therapeutic applications in folk medicine. Herein, we describe antibacterial activities and related metabolites for an extract and fractions obtained from the leaves of that species. An ethanolic extract and its three fractions were used to perform in vitro antibacterial assays. In addition, liquid chromatography coupled to mass spectrometry and the molecular networking approach were used for the metabolite annotation process. Overall, 25 compounds were annotated in the ethanolic extract from M. charantia leaves, including flavones, terpenes, organic acids, and inositol pyrophosphate derivatives. The ethanolic extract exhibited low activity against Proteus mirabilis (MIC 312.5 µg·mL−1) and Klebsiella pneumoniae (MIC 625 µg·mL−1). The ethyl acetate phase showed interesting antibacterial activity (MIC 156.2 µg·mL−1) against Klebsiella pneumoniae, and it was well justified by the high content of glycosylated flavones. Therefore, based on the ethyl acetate phase antibacterial result, we suggest that M. charantia leaves could be considered as an alternative antibacterial source against K. pneumoniae and can serve as a pillar for future studies as well as pharmacological application against the bacteria.

In this work, the oxygen transport and hydrodynamic flow of the PBS Vertical-Wheel MINI™ 0.1 bioreactor were characterized using experimental data and computational fluid dynamics simulations. Data acquired from spectroscopy-based oxygenation measurements was compared with data obtained from 3D simulations with a rigid-lid approximation and LES-WALE turbulence modeling, using the open-source software OpenFOAM-8. The mass transfer coefficients were determined for a range of stirring speeds between 10 and 100 rpm and for working volumes between 60 and 100 mL. Additionally, boundary condition, mesh refinement, and temperature variation studies were performed. Lastly, cell size, energy dissipation rate, and shear stress fields were calculated to determine optimal hydrodynamic conditions for culture. The experimental results demonstrate that the kL can be predicted using Sh=1.68Re0.551Sc13G1.18, with a mean absolute error of 2.08%. Using the simulations and a correction factor of 0.473, the expression can be correlated to provide equally valid results. To directly obtain them from simulations, a partial slip boundary condition can be tuned, ensuring better near-surface velocity profiles or, alternatively, by deeply refining the mesh. Temperature variation studies support the use of this correlation for temperatures up to 37 °C by using a Schmidt exponent of 1/3. Finally, the flow was characterized as transitional with diverse mixing mechanisms that ensure homogeneity and suspension quality, and the results obtained are in agreement with previous studies that employed RANS models. Overall, this work provides new data regarding oxygen mass transfer and hydrodynamics in the Vertical-Wheel bioreactor, as well as new insights for air-water mass transfer modeling in systems with low interface deformation, and a computational model that can be used for further studies.

In vivo and in vitro cells rely on the support of an underlying biocompatible substrate, such as the extracellular matrix or a culture substrate, to spread and proliferate. The mechanical and chemical properties of such structures play a central role in the dynamical and statistical properties of the tissue. At the cell scale, these substrates are highly disordered. Here, we investigate how spatial heterogeneities of the cell-substrate interaction influence the motility of the cells in a model confluent tissue. We use the self-propelled Voronoi model and describe the disorder as a spatially dependent preferred geometry of the individual cells. We found that when the characteristic length scale of the preferred geometry is smaller than the cell size, the tissue is less rigid than its homogeneous counterpart, with a consequent increase in cell motility. This result is in sharp contrast to what has been reported for tissues with heterogeneity in the mechanical properties of the individual cells, where the disorder favors rigidity. Using the fraction of rigid cells, we observe a collapse of the motility data for different model parameters and provide evidence that the rigidity transition in the model tissue is accompanied by the emergence of a spanning cluster of rigid cells.

The Voronoi model is a popular tool for studying confluent living tissues. It exhibits an anomalous glassy behavior even at very low temperatures or weak active self-propulsion, and at zero temperature, the model exhibits a disordered solid structure with no evidence of a rigidity transition. Here, we investigate the properties of the energy landscape in this limit. We find that the structure of the energy landscape changes as a function of the preferred shape parameter of the cells p_{0}. We find two disordered solid phases that have similar structural features but differ in the ultrametricity of their energy landscapes; the crossover between these two states shares phenomenological properties with a Gardner transition. We further highlight how the metric used to calculate distances between configurations influences the ability to detect hierarchical arrangements of basins in the energy landscape.

Peperomia pellucida is a species known in the Amazon as “erva-de-jabuti” that has been used in several therapeutic applications based on folk medicine. Herein, we describe the classes, subclasses, and the main compounds of the leaves, stems, and roots from P. pellucida by ultra-high performance liquid chromatography coupled to high-resolution mass spectrometry associated with molecular networks, mirror plot on the GNPS library, and machine learning. These data show compounds that were annotated for the first time in the Peperomia genus, such as 2′,4′,5′-trihydroxybutyrophenonevelutin, dehydroretrofractamide C, and retrofractamide B.

In Portugal, the dropout rate of university courses is around 29%. Understanding the reasons behind such a high desertion rate can drastically improve the success of students and universities. This work applies existing data mining techniques to predict the academic dropout mainly using the academic grades. Four different machine learning techniques are presented and analyzed. The dataset consists of 331 students who were previously enrolled in the Computer Engineering degree at the Universidade de Trás-os-Montes e Alto Douro (UTAD). The study aims to detect students who may prematurely drop out using existing methods. The most relevant data features were identified using the Permutation Feature Importance technique. In the second phase, several methods to predict the dropouts were applied. Then, each machine learning technique’s results were displayed and compared to select the best approach to predict academic dropout. The methods used achieved good results, reaching an F1-Score of 81% in the final test set, concluding that students’ marks somehow incorporate their living conditions.

Smart, sustainable and inclusive growth is the basis for European 2020 strategy, in which small and medium enterprises (SMEs) are considered the backbone of European countries economies. The present study aims to investigate the relationship between the main variables that characterises small knowledge intensive firms (SKIFs) and the importance of their business expenditure on research and development (BERD). To achieve this, European member states were analysed during the period between 2008 and 2012 using a clusters analysis. Through this study it is possible to conclude that countries that have high growth values on SKIFs also achieve growth in GDP and BERD.