Hydroxycinnamic acid antioxidants: an electrochemical overview

Hydroxycinnamic acids (such as ferulic, caffeic, sinapic, and p-coumaric acids) are a group of compounds highly abundant in food that may account for about one-third of the phenolic compounds in our diet. Hydroxycinnamic acids have gained an increasing interest in health because they are known to be potent antioxidants. These compounds have been described as chain-breaking antioxidants acting through radical scavenging activity, that is related to their hydrogen or electron donating capacity and to the ability to delocalize/stabilize the resulting phenoxyl radical within their structure.The free radical scavenger ability of antioxidants can be predicted from standard one-electron potentials. Thus, voltammetric methods have often been applied to characterize a diversity of natural and synthetic antioxidants essentially to get an insight into their mechanism and also as an important tool for the rational design of new and potent antioxidants.The structure-property-activity relationships (SPARs) correlations already established for this type of compounds suggest that redox potentials could be considered a good measure of antioxidant activity and an accurate guideline on the drug discovery and development process. Due to its magnitude in the antioxidant field, the electrochemistry of hydroxycinnamic acid-based antioxidants is reviewed highlighting the structure-property-activity relationships (SPARs) obtained so far.

Multifunctional Biosensor Based on Localized Surface Plasmon Resonance for Monitoring Small Molecule–Protein Interaction

We report an optical sensor based on localized surface plasmon resonance (LSPR) to study small-molecule protein interaction combining high sensitivity refractive index sensing for quantitative binding information and subsequent conformation-sensitive plasmon-activated circular dichroism spectroscopy. The interaction of α-amylase and a small-size molecule (PGG, pentagalloyl glucose) was log concentration-dependent from 0.5 to 154 μM. In situ tests were additionally successfully applied to the analysis of real wine samples. These studies demonstrate that LSPR sensors to monitor small molecule–protein interactions in real time and in situ, which is a great advance within technological platforms for drug discovery.

High-Content Analysis of Breast Cancer Using Single-Cell Deep Transfer Learning

High-content analysis has revolutionized cancer drug discovery by identifying substances that alter the phenotype of a cell, which prevents tumor growth and metastasis. The high-resolution biofluorescence images from assays allow precise quantitative measures enabling the distinction of small molecules of a host cell from a tumor. In this work, we are particularly interested in the application of deep neural networks (DNNs), a cutting-edge machine learning method, to the classification of compounds in chemical mechanisms of action (MOAs). Compound classification has been performed using image-based profiling methods sometimes combined with feature reduction methods such as principal component analysis or factor analysis. In this article, we map the input features of each cell to a particular MOA class without using any treatment-level profiles or feature reduction methods. To the best of our knowledge, this is the first application of DNN in this domain, leveraging single-cell information. Furthermore, we use deep transfer learning (DTL) to alleviate the intensive and computational demanding effort of searching the huge parameter's space of a DNN. Results show that using this approach, we obtain a 30% speedup and a 2% accuracy improvement.

Evolution of Drug Resistance: Insight on TEM β-Lactamases Structure and Activity and β-Lactam Antibiotics

Since the discovery of the first penicillin bacterial resistance to β-lactam antibiotics has spread and evolved promoting new resistances to pathogens. The most common mechanism of resistance is the production of β-lactamases that have spread thorough nature and evolve to complex phenotypes like CMT type enzymes. New antibiotics have been introduced in clinical practice, and therefore it becomes necessary a concise summary about their molecular targets, specific use and other properties. β-lactamases are still a major medical concern and they have been extensively studied and described in the scientific literature. Several authors agree that Glu166 should be the general base and Ser70 should perform the nucleophilic attack to the carbon of the carbonyl group of the β-lactam ring. Nevertheless there still is controversy on their catalytic mechanism. TEMs evolve at incredible pace presenting more complex phenotypes due to their tolerance to mutations. These mutations lead to an increasing need of novel, stronger and more specific and stable antibiotics. The present review summarizes key structural, molecular and functional aspects of ESBL, IRT and CMT TEM β-lactamases properties and up to date diagrams of the TEM variants with defined phenotype. The activity and structural characteristics of several available TEMs in the NCBI-PDB are presented, as well as the relation of the various mutated residues and their specific properties and some previously proposed catalytic mechanisms.

Evolution of Drug Resistance: Insight on TEM -Lactamases Structure and Activity and Beta-Lactam Antibiotics

Extended-spectrum β-lactamases (ESBLs) prevalence was studied in the north of Portugal, among 193 clinical isolates belonging to citizens in a district in the boundaries between this country and Spain from a total of 7529 clinical strains. In the present study we recovered some members of Enterobacteriaceae family, producing ESBL enzymes, including Escherichia coli (67.9%), Klebsiella pneumoniae (30.6%), Klebsiella oxytoca (0.5%), Enterobacter aerogenes (0.5%), and Citrobacter freundii (0.5%). β-lactamases genes blaTEM, blaSHV, and blaCTX-M were screened by polymerase chain reaction (PCR) and sequencing approaches. TEM enzymes were among the most prevalent types (40.9%) followed by CTX-M (37.3%) and SHV (23.3%). Among our sample of 193 ESBL-producing strains 99.0% were resistant to the fourth-generation cephalosporin cefepime. Of the 193 isolates 81.3% presented transferable plasmids harboring genes. Clonal studies were performed by PCR for the enterobacterial repetitive intragenic consensus (ERIC) sequences. This study reports a high diversity of genetic patterns. Ten clusters were found for E. coli isolates and five clusters for K. pneumoniae strains by means of ERIC analysis. In conclusion, in this country, the most prevalent type is still the TEM-type, but CTX-M is growing rapidly.

Nonlinear dynamics of the patient’s response to drug effect during general anesthesia

In today’s healthcare paradigm, optimal sedation during anesthesia plays an important role both in patient welfare and in the socio-economic context. For the closed-loop control of general anesthesia, two drugs have proven to have stable, rapid onset times: propofol and remifentanil. These drugs are related to their effect in the bispectral index, a measure of EEG signal. In this paper wavelet time–frequency analysis is used to extract useful information from the clinical signals, since they are time-varying and mark important changes in patient’s response to drug dose. Model based predictive control algorithms are employed to regulate the depth of sedation by manipulating these two drugs. The results of identification from real data and the simulation of the closed loop control performance suggest that the proposed approach can bring an improvement of 9% in overall robustness and may be suitable for clinical practice.

The role of molecular imaging in modern drug development

Drug development represents a highly complex, inefficient and costly process. Over the past decade, the widespread use of nuclear imaging, owing to its functional and molecular nature, has proven to be a determinant in improving the efficiency in selecting the candidate drugs that should either be abandoned or moved forward into clinical trials. This helps not only with the development of safer and effective drugs but also with the shortening of time-to-market. The modern concept and future trends concerning molecular imaging will assumedly be hybrid or multimodality imaging, including combinations between high sensitivity and functional (molecular) modalities with high spatial resolution and morphological techniques.

CANDi: context-aware node discovery for short-range cooperation

Multi-standard mobile devices are allowing users to enjoy higher data rates with ubiquitous connectivity. However, the benefits gained from multiple interfaces come at an expense—that being higher energy consumption in an era where mobile devices need to be energy compliant. One promising solution is the usage of short-range cooperative communication as an overlay for infrastructure-based networks taking advantage of its context information. However, the node discovery mechanism, which is pivotal to the bearer establishment process, still represents a major burden in terms of the total energy budget. In this paper, we propose a technology agnostic approach towards enhancing the MAC energy ratings by presenting a context-aware node discovery (CANDi) algorithm, which provides a priori knowledge towards the node discovery mechanism by allowing it to search nodes in the near vicinity at the ‘right time and at the right place’. We describe the different beacons required for establishing the cooperation, as well as the context information required, including battery level, modes, location and so on. CANDi uses the long-range network (WiMAX and WiFi) to distribute the context information about cooperative clusters (Ultra-wideband-based) in the vicinity. The searching nodes can use this context in locating the cooperative clusters/nodes, which facilitates the establishing of short-range connections. Analytical and simulation results are obtained, and the energy saving gains are further demonstrated in the laboratory using a customised testbed. CANDi saves up to 50% energy during the node discovery process, while the demonstrative testbed shows up to 75% savings in the total energy budget, thus validating the algorithm, as well as providing viable evidence to support the usage of short-range cooperative communications for energy savings.

Development of paper-based color test-strip for drug detection in aquatic environment: Application to oxytetracycline

The wide use of antibiotics in aquaculture has led to the emergence of resistant microbial species. It should be avoided/minimized by controlling the amount of drug employed in fish farming. For this purpose, the present work proposes test-strip papers aiming at the detection/semi-quantitative determination of organic drugs by visual comparison of color changes, in a similar analytical procedure to that of pH monitoring by universal pH paper. This is done by establishing suitable chemical changes upon cellulose, attributing the paper the ability to react with the organic drug and to produce a color change. Quantitative data is also enabled by taking a picture and applying a suitable mathematical treatment to the color coordinates given by the HSL system used by windows. As proof of concept, this approach was applied to oxytetracycline (OXY), one of the antibiotics frequently used in aquaculture. A bottom-up modification of paper was established, starting by the reaction of the glucose moieties on the paper with 3-triethoxysilylpropylamine (APTES). The so-formed amine layer allowed binding to a metal ion by coordination chemistry, while the metal ion reacted after with the drug to produce a colored compound. The most suitable metals to carry out such modification were selected by bulk studies, and the several stages of the paper modification were optimized to produce an intense color change against the concentration of the drug. The paper strips were applied to the analysis of spiked environmental water, allowing a quantitative determination for OXY concentrations as low as 30 ng/mL. In general, this work provided a simple, method to screen and discriminate tetracycline drugs, in aquaculture, being a promising tool for local, quick and cheap monitoring of drugs.

Nonlinear dynamics of the patient’s response to drug effect during general anesthesia

In today’s healthcare paradigm, optimal sedation during anesthesia plays an important role both in patient welfare and in the socio-economic context. For the closed-loop control of general anesthesia, two drugs have proven to have stable, rapid onset times: propofol and remifentanil. These drugs are related to their effect in the bispectral index, a measure of EEG signal. In this paper wavelet time–frequency analysis is used to extract useful information from the clinical signals, since they are time-varying and mark important changes in patient’s response to drug dose. Model based predictive control algorithms are employed to regulate the depth of sedation by manipulating these two drugs. The results of identification from real data and the simulation of the closed loop control performance suggest that the proposed approach can bring an improvement of 9% in overall robustness and may be suitable for clinical practice.

Physical therapy with drug treatment in bell palsy: a focused review

ABSTRACT: The physical therapy (PT) associated with standard drug treatment (SDT) in Bell palsy has never been investigated. Randomized controlled trials or quasirandomized controlled trials have compared facial PT (except treatments such as acupuncture and osteopathic) combined with SDT against a control group with SDT alone. Participants included those older than 15 yrs with a clinical diagnosis of Bell palsy, and the primary outcome measure was motor function recovery by the House-Brackmann scale. The methodologic quality of each study was also independently assessed by two reviewers using the PEDro scale. Four studies met the inclusion criteria. Three trials indicate that PT in association with SDT supports higher motor function recovery than SDT alone between 15 days and 1 yr of follow-up. On the other hand, one trial showed that electrical stimulation added to conventional PT with SDT did not influence treatment outcomes. The present review suggests that the current practice of Bell palsy treatment by PT associated with SDT seems to have a positive effect on grade and time recovery compared with SDT alone. However, there is very little quality evidence from randomized controlled trials, and such evidence is insufficient to decide whether combined treatment is beneficial in the management of Bell palsy.

Modelos Teóricos de Difusão Dérmica: abordagens matemáticas e computacionais para terapias transdérmicas da Obesidade

É de senso comum que os nutrientes são fundamentais à vida e que a subnutrição leva à acumulação de gorduras que pode chegar a casos de obesidade, tendo como consequência inúmeras complicações de saúde. Diferentes estruturas neuroanatómicas do cérebro têm um papel essencial no comportamento digestivo. A ação de várias moléculas de sinalização (hormonas, neurotransmissores e neuropéptidos) resulta na regulação da ingestão de alimentos, sendo que, por exemplo, algumas hormonas podem aumentar a sensação de saciedade podendo diminuir o apetite e a ingestão calórica. A descoberta de hormonas envolvidas no balanço energético proporcionou novas oportunidades para desenvolver meios para o tratamento da obesidade. A transferência de medicação antiobesidade por via tópica ou transdérmica é um desafio pois a pele funciona como uma barreira natural e protetora. Sendo uma barreira com uma grande área de superfície e de fácil acessibilidade, a pele tem potencial interesse na libertação de fármacos específicos a cada terapia. Vários métodos têm sido estudados de modo a permitir um aumento da permeabilidade de moléculas terapêuticas para o interior da pele e através da pele. As biotecnologias transdérmicas são um campo de interesse cada vez maior, devido as aplicações dérmicas e farmacêuticas que lhes estão subjacentes. Existem vários modelos computacionais e matemáticos em uso que permite uma visão mais abrangente de puros dados experimentais e até mesmo permite a extrapolação prática de novas metodologias de difusão dérmica. Contudo, eles compreendem uma complexa variedade de teorias e suposições que atribuem a sua utilização para situações específicas. Este trabalho, primeiramente analisa, de forma extensiva, as várias metodologias teóricas para o estudo da difusão dérmica e sistematiza as suas características, realizando depois a fase prévia duma nova abordagem computacional para o estudo da difusão dérmica, que determina características microscópicas de moléculas capazes de provocar a perda de peso, tais como a Leptina e/ou os seus agonistas.