Stem cells present unique regenerative abilities, offering great potential for treatment of prevalent pathologies such as diabetes, neurodegenerative and heart diseases. Various research groups ...dedicated significant effort to identify sets of genes-so-called stemness signatures-considered essential to define stem cells. However, their usage has been hindered by the lack of comprehensive resources and easy-to-use tools. For this we developed StemChecker, a novel stemness analysis tool, based on the curation of nearly fifty published stemness signatures defined by gene expression, RNAi screens, Transcription Factor (TF) binding sites, literature reviews and computational approaches. StemChecker allows researchers to explore the presence of stemness signatures in user-defined gene sets, without carrying-out lengthy literature curation or data processing. To assist in exploring underlying regulatory mechanisms, we collected over 80 target gene sets of TFs associated with pluri- or multipotency. StemChecker presents an intuitive graphical display, as well as detailed statistical results in table format, which helps revealing transcriptionally regulatory programs, indicating the putative involvement of stemness-associated processes in diseases like cancer. Overall, StemChecker substantially expands the available repertoire of online tools, designed to assist the stem cell biology, developmental biology, regenerative medicine and human disease research community. StemChecker is freely accessible at http://stemchecker.sysbiolab.eu.
Restoring the ecosystems of the Cerrado biome is challenging considering the diversity of phytophysiognomies present in the biome, some of which are composed of species from different strata ...(herbaceous, shrubby, and arboreal), which increases the complexity of restructuring the floristic composition. Other factors was involved, such as soil quality, which directly influences the success of restoration, water storage, and nutrients, the financial costs, and a slow ecological process, due to the adverse circumstances found in the area. be restored. The strong anthropogenic interventions by mining processes reduce dramatically the physical and nutritional composition of the soil. We studied two restoration areas in Paracatu, Brazil, to examine their edaphic conditions six years after mining activities ceased and relate them to the status of the restoration process. In 2009, a Cerrado restoration were established in an area previously explored for gravel extraction. Plants were sampled and identified in 11 transects along the planting lines. The diameter base (DB) and total height (HT) were measured. The physical/chemical quality of the soil substrate was determined using a collection of samples in open trenches at four types of points: Cerrado (TC); dead plant pits (TM); seedling pits having living individuals of the most abundant species (TT); and those of the second-most abundant species (TE). Cecropia pachystachya Trécul and Tapirira guianensis Aubl. were most abundant and demonstrated the potential to thrive in areas degraded by mining having low mortality rates and growth at relatively DB and HT. The physical quality indicators in the gravel pits were not limiting, indicating that substrate preparation was efficient in this regard. The organic matter content in TM, TT, and TE was low in comparison to that of TC, and the chemical conditions in the TE pit substrates were similar to those in TM pits, suggesting C. pachystachya is a species with good plasticity, whereas T. guianensis is present in pits with higher levels of phosphorus.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
•Hybrid semiparametric models have been widely used for bioprocess modeling.•Shallow structures and “nondeep” training are well covered in the literature.•Here, deep structures/training are ...investigated in a hybrid modeling context.•ADAM with stochastic regularization significantly reduces the training CPU.•Deep hybrid models show higher predictive power than the shallow counterpart.
Numerous studies have reported the use of hybrid semiparametric systems that combine shallow neural networks with First Principles for bioprocess modeling. Here we revisit the general bioreactor hybrid model and introduce some deep learning techniques. Multi-layer networks with varying depths were combined with First Principles equations in the form of deep hybrid models. Deep learning techniques, namely the adaptive moment estimation method (ADAM), stochastic regularization and depth-dependent weights initialization were evaluated in a hybrid modeling context. Modified sensitivity equations are proposed for the computation of gradients in order to reduce CPU time for the training of deep hybrid models. The methods are illustrated with applications to a synthetic dataset and a pilot 50 L MUT+ Pichia pastoris process expressing a single chain antibody fragment. All in all, the results point to a systematic generalization improvement of deep hybrid models over its shallow counterpart. Moreover, the CPU cost to train the deep hybrid models is shown to be lower than for the shallow counterpart. In the pilot 50L MUT+ Pichia pastoris data set, the prediction accuracy was increased by 18.4% and the CPU decreased by 43.4%.
Nowadays, new challenges arise relating to the compensation of power quality problems, where the introduction of innovative solutions based on power electronics is of paramount importance. The ...evolution from conventional electrical power grids to smart grids requires the use of a large number of power electronics converters, indispensable for the integration of key technologies, such as renewable energies, electric mobility and energy storage systems, which adds importance to power quality issues. Addressing these topics, this paper presents an extensive review on power electronics technologies applied to power quality improvement, highlighting, and explaining the main phenomena associated with the occurrence of power quality problems in smart grids, their cause and effects for different activity sectors, and the main power electronics topologies for each technological solution. More specifically, the paper presents a review and classification of the main power quality problems and the respective context with the standards, a review of power quality problems related to the power production from renewables, the contextualization with solid-state transformers, electric mobility and electrical railway systems, a review of power electronics solutions to compensate the main power quality problems, as well as power electronics solutions to guarantee high levels of power quality. Relevant experimental results and exemplificative developed power electronics prototypes are also presented throughout the paper.
With a view to reducing harmonic content in electrical power systems, and, consequently, improving power quality level, filters and other harmonic compensation devices are widely used. In the ...category of filters, they can be distinguished into two classes that are related to the operating mode, active or passive, both widely known and applied in electrical power grids and in the most diverse industry sectors. In this sense, taking into account the use of compensating devices in four-wire electrical systems feeding single-phase, non-linear loads, this paper presents a new hybrid arrangement of harmonic compensation that incorporates both active and passive filtering, which performs all functions concerning the harmonic compensation of a four-leg shunt active power filter. In this hybrid arrangement, the harmonic filtering of positive and negative sequence components is performed by a three-leg shunt active power filter, while the filtering of zero-sequence harmonics is attributed to the electromagnetic zero-sequence suppressor. The results, which confirm the effectiveness of the proposed hybrid arrangement, are proven through simulations and experimental tests in different operating scenarios, revealing a substantial improvement in the system’s power factor, as well as a reduction in harmonic distortions.
The antibacterial activity and efflux pump reversal of thymol and carvacrol were investigated against the
IS-58 strain in this study, as well as their toxicity against
. The minimum inhibitory ...concentration (MIC) was determined using the broth microdilution method, while efflux pump inhibition was assessed by reduction of the antibiotic and ethidium bromide (EtBr) MICs.
toxicity was tested using the fumigation method. Both thymol and carvacrol presented antibacterial activities with MICs of 72 and 256 µg/mL, respectively. The association between thymol and tetracycline demonstrated synergism, while the association between carvacrol and tetracycline presented antagonism. The compound and EtBr combinations did not differ from controls. Thymol and carvacrol toxicity against
were evidenced with EC
values of 17.96 and 16.97 µg/mL, respectively, with 48 h of exposure. In conclusion, the compounds presented promising antibacterial activity against the tested strain, although no efficacy was observed in terms of efflux pump inhibition.
The combination of physical equations with deep learning is becoming a promising methodology for bioprocess digitalization. In this paper, we investigate for the first time the combination of long ...short-term memory (LSTM) networks with first principles equations in a hybrid workflow to describe human embryonic kidney 293 (HEK293) culture dynamics. Experimental data of 27 extracellular state variables in 20 fed-batch HEK293 cultures were collected in a parallel high throughput 250 mL cultivation system in an industrial process development setting. The adaptive moment estimation method with stochastic regularization and cross-validation were employed for deep learning. A total of 784 hybrid models with varying deep neural network architectures, depths, layers sizes and node activation functions were compared. In most scenarios, hybrid LSTM models outperformed classical hybrid Feedforward Neural Network (FFNN) models in terms of training and testing error. Hybrid LSTM models revealed to be less sensitive to data resampling than FFNN hybrid models. As disadvantages, Hybrid LSTM models are in general more complex (higher number of parameters) and have a higher computation cost than FFNN hybrid models. The hybrid model with the highest prediction accuracy consisted in a LSTM network with seven internal states connected in series with dynamic material balance equations. This hybrid model correctly predicted the dynamics of the 27 state variables (R
= 0.93 in the test data set), including biomass, key substrates, amino acids and metabolic by-products for around 10 cultivation days.
Abstract
Summary
Here, we present sbml2hyb, an easy-to-use standalone Python tool that facilitates the conversion of existing mechanistic models of biological systems in Systems Biology Markup ...Language (SBML) into hybrid semiparametric models that combine mechanistic functions with machine learning (ML). The so-formed hybrid models can be trained and stored back in databases in SBML format. The tool supports a user-friendly export interface with an internal format validator. Two case studies illustrate the use of the sbml2hyb tool. Additionally, we describe HMOD, a new model format designed to support and facilitate hybrid models building. It aggregates the mechanistic model information with the ML information and follows as close as possible the SBML rules. We expect the sbml2hyb tool and HMOD to greatly facilitate the widespread usage of hybrid modeling techniques for biological systems analysis.
Availability and implementation
The Python interface, source code and the example models used for the case studies are accessible at: https://github.com/r-costa/sbml2hyb.
Supplementary information
Supplementary data are available at Bioinformatics online.
Undue exposure to antimicrobials has led to the acquisition and development of sophisticated bacterial resistance mechanisms, such as efflux pumps, which are able to expel or reduce the intracellular ...concentration of various antibiotics, making them ineffective. Therefore, inhibiting this mechanism is a promising way to minimize the phenomenon of resistance in bacteria. In this sense, the present study sought to evaluate the activity of the Carvacrol (CAR) and Thymol (THY) terpenes as possible Efflux Pump Inhibitors (EPIs), by determining the Minimum Inhibitory Concentration (MIC) and the association of these compounds in subinhibitory concentrations with the antibiotic Norfloxacin and with Ethidium Bromide (EtBr) against strains SA-1199 (wild-type) and SA-1199B (overexpresses NorA) of
Staphylococcus aureus
. In order to verify the interaction of the terpenes with the NorA efflux protein, an in silico molecular modeling study was carried out. The assays used to obtain the MIC of CAR and THY were performed by broth microdilution, while the Efflux Pump inhibitory test was performed by the MIC modification method of the antibiotic Norfloxacin and EtBr. docking was performed using the Molegro Virtual Docker (MVD) program. The results of the study revealed that CAR and THY have moderate bacterial activity and are capable of reducing the MIC of Norfloxacin antibiotic and EtBr in strains of
S. aureus
carrying the NorA efflux pump. The docking results showed that these terpenes act as possible competitive NorA inhibitors and can be investigated as adjuvants in combined therapies aimed at reducing antibiotic resistance.
•Compounds with the most functional groups obtained clinically relevant results.•Against SA 1199B only isoeugenol had direct antibacterial activity.•For the NorA carrier strain ...4-allyl-2-6-dimethoxyphenol, eugenol and isoeugenol potentiated the action of the antibiotic.•The docking demonstrated the hydrogen bonds and hydrophobic interactions are key for NorA inhibition.•The 4-Allyl-2,6-dimetoxyphenol compound as a lead compound as NorA inhibitors.
Staphylococcus aureus is a Gram-positive bacterium responsible for a number of diseases and has demonstrated resistance to conventional antibiotics. This study aimed to evaluate the antibacterial activity of eugenol and its derivatives allylbenzene, 4-allylanisole, isoeugenol and 4-allyl-2,6-dimethoxyphenol against the S. aureus NorA efflux pump (EP) in association with norfloxacin and ethidium bromide. The antibacterial activity of the compounds was assessed using the broth microdilution method to determine the minimum inhibitory concentration (MIC). A reduction in the MIC of ethidium bromide (a substrate for several efflux pumps) or norfloxacin was used as a parameter of EP inhibition. Molecular modeling studies were used to predict the 3D structure and analyze the interaction of selected compounds with the binding pocket of the NorA efflux pump. Except for 4-allylanisole and allylbenzene, the compounds presented clinically effective antibacterial activity. When associated with norfloxacin against the SA 1199B strain, 4-allyl-2,6-dimethoxyphenol eugenol and isoeugenol caused significant reduction in the MIC of the antibiotic, demonstrating synergistic effects. Similar effects were observed when 4-allyl-2,6-dimethoxyphenol, allylbenzene and isoeugenol were associated with ethidium bromide. Together, these findings indicate a potential inhibition of the NorA pump by eugenol and its derivatives. This in vitro evidence was corroborated by docking results demonstrating favorable interactions between 4-allyl-2,6-dimetoxypheno and the NorA pump mediated by hydrogen bonds and hydrophobic interactions. In conclusion, eugenol derivatives have the potential to be used in antibacterial drug development in strains carrying the NorA efflux pump.
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