Search

Obstructive Sleep Apnea (OSA) is one of the most common sleep disorders, and invokes numerous negative health-related outcomes and physiopathological processes. Understanding the mechanisms by which OSA potentiates cardiometabolic risk of patients remains a current challenge. Sleep disruption is highly prevalent among shift workers and shift work (SW) is an important modulator of circadian rhythms, with health consequences intimately related to cardiometabolic health. Since the circadian timing system (CTS) interacts with the normal functioning of the ANS, CTS impact on OSA patients should be closely assessed. This review raises the question of whether SW-induced circadian misalignment potentiates the cardiometabolic risk of OSA patients, providing a novel perspective on the role of autonomic modulation as a key downstream mechanism linking cardiometabolic risk with both OSA and CTS misalignment.

In the last years, Salmonella has been extensively studied not only due to its importance as a pathogen, but also as a host to produce pharmaceutical compounds. However, the full exploitation of Salmonella as a platform for bioproduct delivery has been hampered by the lack of information about its metabolism. Genome-scale metabolic models can be valuable tools to delineate metabolic engineering strategies as long as they closely represent the actual metabolism of the target organism. In the present study, a 13C-MFA approach was applied to map the fluxes at the central carbon pathways of S. typhimurium LT2 growing at glucose-limited chemostat cultures. The experiments were carried out in a 2L bioreactor, using defined medium enriched with 20% 13C-labeled glucose. Metabolic flux distributions in central carbon pathways of S. typhimurium LT2 were estimated using OpenFLUX2 based on the labeling pattern of biomass protein hydrolysates together with biomass composition. The results suggested that pentose phosphate is used to catabolize glucose, with minor fluxes through glycolysis. In silico simulations, using Optflux and pFBA as simulation method, allowed to study the performance of the genome-scale metabolic model. In general, the accuracy of in silico simulations was improved by the superimposition of estimated intracellular fluxes to the existing genome-scale metabolic model, showing a better fitting to the experimental extracellular fluxes, whereas the intracellular fluxes of pentose phosphate and anaplerotic reactions were poorly described.

The lipid nanoparticles, namely Nanostructured Lipid Carriers (NLC), as drug delivery systems have been investigated for several years. One of the delivery routes for which these carriers can be applied is buccal administration. However, the liquid dispersions of lipid nanoparticles can be rapidly removed from oral cavity by saliva. Thus, the development of a system that allows increased retention time on the mucosa is necessary. For this reason, the development of mucoadhesive preparations for buccal administration of lipid nanoparticles becomes important. Hydrogels prepared with mucoadhesive polymers (Carbopol® 980 and polycarbophil) constitute a promising option. The aim of this work was to develop mucoadhesive buccal hydrogels with NLC, using ibuprofen as a model drug. The obtained results showed that the developed NLC dispersions presented particles in the nanometric size range, with low polydispersity index values and efficient ability for the entrapment of the model drug. Moreover, the incorporation of NLC in hydrogels of mucoadhesive polymers resulted in preparations with desirable rheological features as well as texture (firmness and adhesiveness) and mucoadhesive properties, which could benefit the therapeutic efficacy, by increasing the residence time and easiness for topical application in the buccal mucosa. Additionally, the developed preparations exhibited sustained drug release as intended for these systems.

Background Hemorrhagic transformation and cerebral edema are feared complications of acute ischemic stroke but mechanisms are poorly understood and reliable early markers are lacking. Early assessment of cerebrovascular hemodynamics may advance our knowledge in both areas. We examined the relationship between dynamic cerebral autoregulation (CA) in the early hours post ischemia, and the risk of developing hemorrhagic transformation and cerebral edema at 24 h post stroke Methods We prospectively enrolled 46 patients from our center with acute ischemic stroke in the middle cerebral artery territory. Cerebrovascular resistance index was calculated. Dynamic CA was assessed by transfer function analysis (coherence, phase and gain) of the spontaneous blood flow velocity and blood pressure oscillations. Infarct volume, hemorrhagic transformation, cerebral edema, and white matter changes were collected from computed tomography performed at presentation and 24 h. Results At admission, phase was lower (worse CA) in patients with hemorrhagic transformation [6.6 ± 30 versus 45 ± 38°; adjusted odds ratio 0.95 (95% confidence internal 0.94–0.98), p = 0.023] and with cerebral edema [6.6 ± 30 versus 45 ± 38°, adjusted odds ratio 0.96 (0.92–0.999), p = 0.044]. Progression to edema was associated with lower cerebrovascular resistance (1.4 ± 0.2 versus 2.3 ± 1.5 mm Hg/cm/s, p = 0.033) and increased cerebral blood flow velocity (51 ± 25 versus 42 ± 17 cm/s, p = 0.033) at presentation. All hemodynamic differences resolved at 3 months Conclusions Less effective CA in the early hour post ischemic stroke is associated with increased risk of hemorrhagic transformation and cerebral edema, possibly reflecting breakthrough hyperperfusion and microvascular injury. Early assessment of dynamic CA could be useful in identifying individuals at risk for these complications.

The composition of a cell in terms of macromolecular building blocks and other organic molecules underlies the metabolic needs and capabilities of a species. Although some core biomass components such as nucleic acids and proteins are evident for most species, the essentiality of the pool of other organic molecules, especially cofactors and prosthetic groups, is yet unclear. Here we integrate biomass compositions from 71 manually curated genome-scale models, 33 large-scale gene essentiality datasets, enzyme-cofactor association data and a vast array of publications, revealing universally essential cofactors for prokaryotic metabolism and also others that are specific for phylogenetic branches or metabolic modes. Our results revise predictions of essential genes in Klebsiella pneumoniae and identify missing biosynthetic pathways in models of Mycobacterium tuberculosis. This work provides fundamental insights into the essentiality of organic cofactors and has implications for minimal cell studies as well as for modeling genotype-phenotype relations in prokaryotic metabolic networks., J.C.X. was sponsored by Fundação para a Ciência e Tecnologia, Portugal [Grant SFRH/BD/81626/2011]. This study was supported by the European Molecular Biology Laboratory, the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UID/BIO/04469/2013 unit, COMPETE 2020 (POCI-01–0145-FEDER-006684) and BioTecNorte operation (NORTE-01–0145-FEDER-000004) funded by European Regional Development Fund under the scope of Norte2020 - Programa Operacional Regional do Norte. This project has received funding from the European Union's Horizon 2020 research and innovation programme under Grant agreement no 686070.

Metabolic Engineering (ME) aims to design microbial cell factories towards the production of valuable compounds. In this endeavor, one important task relates to the search for the most suitable heterologous pathway(s) to add to the selected host. Different algorithms have been developed in the past towards this goal, following distinct approaches spanning constraint-based modelling, graph-based methods and knowledge-based systems based on chemical rules. While some of these methods search for pathways optimizing specific objective functions, here the focus will be on methods that address the enumeration of pathways that are able to convert a set of source compounds into desired targets and their posterior evaluation according to different criteria. Two pathway enumeration algorithms based on (hyper)graph-based representations are selected as the most promising ones and are analyzed in more detail: the Solution Structure Generation and the Find Path algorithms. Their capabilities and limitations are evaluated when designing novel heterologous pathways, by applying these methods on three case studies of synthetic ME related to the production of non-native compounds in E. coli and S. cerevisiae: 1-butanol, curcumin and vanillin. Some targeted improvements are implemented, extending both methods to address limitations identified that impair their scalability, improving their ability to extract potential pathways over large-scale databases. In all case-studies, the algorithms were able to find already described pathways for the production of the target compounds, but also alternative pathways that can represent novel ME solutions after further evaluation., The work is partially funded by ERDF - European Regional Development Fund through the COMPETE Programme (operational programme for competitiveness) and by National Funds through the FCT (Portuguese Foundation for Science and Technology) within projects ref. COMPETE FCOMP-01-0124-FEDER-015079 and Strategic Project PEst-OE/EQB/LA0023/2013, and also by Project 23060, PEM - Technological Support Platform for Metabolic Engineering, co-funded by FEDER through Portuguese QREN under the scope of the Technological Research and Development Incentive system, North Operational.

[EN] The goal of this work is to develop an original and high performance hybrid lab-on-a-chip, coupling actuators and biosensors for the active control and broad range characterization of biofluids samples. These biofluids will be controlled (moved and mixed) actively by Rayleigh-Surface Acoustic Wave (R-SAW) and analysed in real-time by combining Love-SAW (L-SAW) and Surface Plasmon Resonance (SPR) technologies. A microfluidic chamber and specific transducer were designed for this application to interact efficiently with the liquid sample entrapped in the chamber and to detect modifications of its physical properties such as viscosity. AT-cut quartz and LiNbO3 36Y-X substrates were used to generate both Rayleigh and Shear-Horizontal waves and ZnO material as guiding layer. The whole system has proven is full efficiency to interact with the fluid and to detect the signal perturbations with no significant loss compared with the measurements carried out with a probe station., The authors wish to thank the ANR for its financial support through the AWESOM project (ANR-12-BS09-021); the operators Laurent Bouvot, Jean Georges Mussot and Emmanuel Vatoux, for their support and assistance in the fabrication of the cell and the SAW devices; and the engineering students, Olivier Bettoni and Bastien Lafont, for their contribution to the cell design.

We report a case of a patient with recurrent syncope and paroxysmal atrial fibrillation whose clinical status greatly improved after a period of orthostatic training. The potential efficacy of this non-pharmacological measure in modulating the autonomic tone is discussed below.

Resumo: A influência do sistema nervoso autónomo (SNA) na génese da fibrilhação auricular (FA) envolve múltiplos mecanismos complexos com impacto nas propriedades eletrofisiológicas cardíacas. A importância dos efeitos da estimulação autonómica no substrato elétrico auricular e das veias pulmonares (VP) e na vulnerabilidade para FA requer melhor compreensão. Objetivo: Avaliar os efeitos da estimulação vagal (estim_vag) e simpática (estim_simp) aguda na condução e refratariedade das aurículas e VP e na indutibilidade de FA no coração de coelho in vivo com inervação autonómica preservada. Métodos: Estudámos 17 coelhos New Zealand de ambos os sexos. Para abordagem de «toráx-aberto» procedeu-se a anestesia, entubação e ventilação após bloqueio neuro-muscular. O ECG foi obtido a partir de 3 derivações dos membros. Os eletrogramas foram registados com 4 elétrodos monopolares colocados na superfície epicárdica, distribuídos ao longo das aurículas e com um elétrodo circular adaptado à porção proximal das VP. Estimulou-se o nervo vago cervical direito e o tronco simpático torácico com elétrodos bipolares de platina. Estudámos os períodos refratários efetivos (PRE) e a condução elétrica auricular, entre a aurícula direita lateral-alta (AD) e a aurícula esquerda lateral-alta (AE), e entre AD e VP, em condições basais e durante estim_vag, estim_simp e estimulação autonómica combinada (dual_estim). Para indução de FA, procedeu-se a pacing rápido (50 Hz, 10 s, isolado ou com estim_vag, estim_simp ou dual_estim) com elétrodo bipolar no apêndice auricular direito (AAD), apêndice auricular esquerdo (AAE) e VP. Resultados: Em condições basais: os PRE eram maiores no AAE e registou-se um atraso na ativação da AD para as VP, comparando com a condução interauricular. Durante estim_vag ou dual_estim: os PRE encurtaram significativamente em todos os locais, o intervalo de condução interauricular variou de 20 ± 4 ms para 30 ± 10 ms (p 10 s a arritmia terminou imediatamente após interrupção da estim_vagal. Conclusões: No coração de coelho inervado in vivo, a estimulação autonómica aguda encurta a refratariedade auricular e das VP, e modifica a velocidade de condução auricular, potenciando a indução e duração de FA. Os resultados sugerem que as variações agudas e a interação da atividade autonómica podem desempenhar um papel importante na fisiopatologia da FA. Abstract: Atrial fibrillation (AF) is a complex disease with multiple mechanisms, involving the interaction between the autonomic nervous system (ANS), electrophysiological properties of the atria and pulmonary veins (PVs), and vulnerability for AF. Aim: We assessed the effects of acute vagal (vagus_stim) and sympathetic stimulation (symp_stim) on atrial conduction, atrial and PV refractoriness and inducibility of AF in an in vivo rabbit model with preserved autonomic innervation. Methods: An open-epicardial approach was used in 17 anesthetized and artificially ventilated New Zealand white rabbits. The ECG was recorded with bipolar subcutaneous electrodes placed in the four limbs. Electrograms were obtained with four monopolar electrodes placed epicardially along the atria, and a circular electrode adapted to the proximal PVs. The cervical vagus nerve and thoracic sympathetic trunk were stimulated with bipolar electrodes. Epicardial activation was recorded in sinus rhythm, and effective refractory periods (ERPs) and conduction times from the high-lateral right atrium (RA) to the high-lateral left atrium (LA) and PVs were quantified at baseline and during vagus_stim, symp_stim, or combined vagal and sympathetic stimulation (dual_stim). Burst pacing (50 Hz, 10 s), alone or combined with vagus_stim, symp_stim or dual_stim, was performed in the right (RAA) and left atrial appendage (LAA) and PVs to test for AF inducibility. Results: At baseline, ERPs were higher in the LAA and there was a delay in the conduction time from RA to PV, compared to the mean activation time from RA to LA. During vagus_stim or dual_stim, ERP decreased significantly at all sites, and baseline interatrial activation times changed from 20 ± 4 ms to 30 ± 10 ms and 31 ± 11 ms, respectively (p

a b s t r a c t In metabolic systems, the cellular network of metabolic reactions together with constraints of (ir)reversibility of enzymes determines the space of all possible steady-state phenotypes. Analysis of large metabolic models, however, is not feasible in real-time and identification of a smaller model without loss of accuracy is desirable for model-based bioprocess optimization and control. To this end, we propose two search algorithms for systematic identification of a subset of pathways that match the observed cellular phenotype relevant for a particular process condition. Central carbon metabolism of Escherichia coli was used as a case-study together with three phenotypic datasets obtained from the literature. The first search method is based on ranking pathways and the second is a controlled random search (CRS) algorithm. Since we wish to obtain a biologically realistic subset of pathways, the objective function to be minimized is a trade-off between the error and investment costs. We found that the CRS outperforms the ranking algorithm, as it is less likely to fall into local minima. In addition, we compared two pathway analysis methods (elementary modes versus generating vectors) in terms of modelling accuracy and computational intensity. We conclude that generating vectors have preference over elementary modes to describe a particular phenotype. Overall, the original model containing 433 generating vectors or 2706 elementary modes could be reduced to a system of one to three pathways giving a good correlation with the measured datasets. We consider this work as a first step towards the use of detailed metabolic models to improve real-time optimization, monitoring, and control of biological processes.

An ultrasonic assisted solid–liquid extraction method was developed to determine the level of lead in the brain and urine of rats. Lead was determined by electrothermal atomic absorption spectrometry with longitudinal-Zeeman background correction. Several analytical drawbacks were addressed and overcome, namely small brain sample mass and the formation of precipitate in the urine samples. Utrasonication provided by an ultrasonic probe succeeded in extracting lead from brain samples. Furthermore, it was demonstrated that the formation of a precipitate lowered the lead content in the liquid phase of the urine. Lead was back extracted from the precipitate to the liquid phase with the aid of ultrasonic energy and acidifying the urine with 10% v/v nitric acid. A microwave-assisted acid digestion protocol was used to check the completeness of the lead extraction. The within bath and between bath precision was 5% ( n = 9) and 7% ( n = 3) respectively. The limit of quantification was 1.05 μg g −1 for brain samples and 2.1 μg L −1 for urine samples. A total of 6 samples of urine and 12 samples of brain from control rats and another 6 samples of urine and 12 samples of brain from rats fed with tap water rich in lead acetate were used in this research. Lead levels in brain and urine from exposed rats ranged from1.9 ± 0.2 μg g −1 to 3.5 ± 0.2 μg g −1 and from 752 ± 56 μg L −1 to 60.9 ± 1.2 mg L −1 respectively. Statistically significant differences of levels of lead in brain and urine were found between exposed and non exposed rats.

Saccharomyces cerevisiae is a widely used microorganism for industrial biotechnology that has great potential to replace traditional petrochemical synthesis. Optimization of cell factories for production of different biotechnological products is still a cost and time inefficient process. Availability of pre-optimized yeast chassis cells, with improved precursor supply, will overcome such hurdles. Building upon this premise, we have developed a framework for rational design of chassis strains combining genome-scale metabolic models with a multi-objective metaheuristic approach. Here, we present the non-intuitive gene deletion targets optimized for growth-product coupled production of a family of C4-dicarboxylic acids, namely fumaric, succinic and malic acids. Several multi-gene deletion strains, including the chassis cell and the final producer strains, were implemented and experimentally tested. The strains encompassing the chassis backbone produce higher yields of respective targeted compounds than those containing merely the intuitive gene deletion(s). Taking advantage of the growth-product coupled design, best producing strains have been improved by adaptive laboratory evolution. As a proof-of-concept, we have generated pre-optimized chassis yeast cells for enhanced production of C4-dicarboxylic acids, hence showing that modular design strategies may contribute to accelerate cell factory development., info:eu-repo/semantics/publishedVersion

In Biomedical research, retrieving documents that match an interesting query is a task performed quite frequently. Typically, the set of obtained results is extensive containing many non-interesting documents and consists in a flat list, i.e., not organized or indexed in any way. This work proposes BioDR, a novel approach that allows the semantic indexing of the results of a query, by identifying relevant terms in the documents. These terms emerge from a process of Named Entity Recognition that annotates occurrences of biological terms (e.g. genes or proteins) in abstracts or full-texts. The system is based on a learning process that builds an Enhanced Instance Retrieval Network (EIRN) from a set of manually classified documents, regarding their relevance to a given problem. The resulting EIRN implements the semantic indexing of documents and terms, allowing for enhanced navigation and visualization tools, as well as the assessment of relevance for new documents., Fundação para a Ciência e a Tecnologia (FCT), Maria Barbeito” contract Xunta, HUELLA financed by the Consellería de Sanidade (Xunta de Galicia de Galicia)

The lack of model-based information in bioreactor monitoring and control can have a profound impact on biological systems. We therefore aim to develop a model using elementary modes (EMs) that represents the observed phenotype in given environmental conditions suited for bioprocess control. Challenges in the model development were the high number of possible phenotypes of stoichiometric models and the high computational intensity. Two methods were compared to reduce the number of EMs to match the observed cellular phenotype. The first method is based on ranking modes and the second is a controlled random search (CRS) algorithm. Since we wish to obtain a biologically realistic subset of EMs, the objective function to be minimized is a trade-off between the error, efficiency of the modes, and model size. The case study considered the central carbon metabolism of Escherichia coli. The original model containing 2706 modes for case 1 and 11718 for case 2 was reduced to a system of one for case 1 and three modes for case 2 giving a good correlation with the measured data. Furthermore, considering also intracellular besides extracellular metabolites, results in a better fit of the measured rates. Finally, the CRS outperformed the ranking algorithm., (undefined)

So far, few large scale kinetic models of metabolic networks have been successfully constructed. The main reasons for this are not only the associated mathematical complexity, but also the large number of unknown kinetic parameters required in the rate equations to define the system. In contrast to kinetic models, the constraint-based modelling approach bypasses these difficulties by using basically only stoichiometric information with certain physicochemical constraints to delimit the solution space without large fitted parameter sets. Although these constraintbased models are highly relevant to predict feasible steady-state fluxes under a diverse range of genetic and environmental conditions, the steady-state assumption may oversimplify cellular behaviour and cannot predict time-course profiles. To overcome these problems, combining these two approaches appears as a reasonable alternative to modelling large-scale metabolic networks. On the other hand, several of the experimental data required for model construction are often rare and in this way it is usually assumed that the enzyme concentrations are constant. In this work, we used a central carbon metabolic network of E. coli to investigate whether including high throughput enzyme concentration data into a kinetic model allows improved predictions of metabolic flux distributions in response to single knockouts perturbations. For this purpose, an E. coli model, based on results obtained from flux balance analysis (FBA) and approximate lin-log kinetics was constructed. The intracellular fluxes distributions, obtained using this model, were compared with published in vivo measurements., (undefined)

The heart rate and blood pressure power spectrum, especially the power of the low frequency (LF) and high frequency (HF) components, have been widely used in the last decades for quantification of both autonomic function and respiratory activity. Discrete Wavelet Transform (DWT) is an important tool in this field. The paper presents a LF and HF fast estimator that uses artificial neural networks and Daubechies DWT processing techniques. Radial Basis Function and Multilayer Perceptron neural networks were designed and implemented for fast assessment of cardiovascular autonomic nervous system control. The training values to design the networks were obtained after heart rate and blood pressure wavelets processing. The designed neural structures assure a faster evaluation tool of the sympathetic and parasympathetic autonomic nervous system control of the cardiovascular function.

The specific growth rate is one of the most important process variables characterizing the state of microorganisms during fermentations mainly because the biosynthesis of many products of interest is often related with the values assumed by this parameter. In the particular case of the fed-batch operation of Escherichia coli for the production of recombinant proteins, it is important to maintain the specific growth rate below a certain threshold in order to avoid the accumulation of acetic acid throughout the fermentation and, additionally, it is often argued that both pre- and the post-induction specific growth rates should be closely controlled in order to achieve maximum productivities of the desired recombinant protein. In a previous work the authors have developed and validated by simulations a strategy for the automatic control of the specific growth rate in E. coli fed-batch fermentations based on an asymptotic observer for biomass and on developed estimators for the specific growth rates. The main purpose of the present work was to implement experimentally the developed observer, estimator and controller in a real fed-batch fermentation process. For that purpose a data acquisition and control program was developed in LabVIEW that allows the acquisition of the necessary on line data (off gas and dissolved oxygen concentration and culture weight) and the calculation of the feeding rates using the developed equations. The feedforward-feedback controller developed was able to keep the culture growing in an exponential phase throughout the fermentation without accumulation of glucose and acetate., Fundação para a Ciência e a Tecnologia (FCT) - RecSysBio projecto POCI/BIO/60139/2004

Compared to our knowledge on metabolic pathways and the establishment of tools to manipulate these pathways, we know very little about the mechanisms behind the secretion of metabolic intermediates. Microorganisms secrete a wide range of metabolic intermediates, and many of them are of great industrial interest. Despite the cellular process of metabolite efflux being ubiquitous to all microbial cells, we still do not know clearly how this process works and how it is regulated. It is believed that small metabolites, mainly those end products of fermentation are excreted through the plasma membrane passively, or they are secreted through specialised mechanisms such as vectorial reaction in response to hypo-osmotic stress, or uniport and synport transport systems. However, all of these mechanisms are based on the concept of “metabolic overflow”, which under specific metabolic conditions it is observed a massive excretion of some metabolic intermediates due to their intracellular accumulation. Although this concept seems appropriate to explain the secretion of some intracellular metabolites, it does not apply to many cases studied during continuous culture. Our metabolomics data obtained during different time-series studies of microbial growth under continuous and batch cultures confirm that the concept of “metabolic overflow” cannot be applied to explain the efflux of several intracellular metabolites found in the extracellular medium. Most of our studies indicate that microbial cells very often get rid of some intracellular metabolites in response to an environmental stimulus, even if these metabolites are key intermediates of central carbon metabolism.

s of the European Congress on Biotechnology, 14, Barcelona, Spain, 2009