Sensitive Electrochemical Detection of Bioactive Molecules (Hydrogen Peroxide, Glucose, Dopamine) with Perovskites-Based Sensors

Perovskite-modified electrodes have received increasing attention in the last decade, due to their electrocatalytic properties to undergo the sensitive and selective detection of bioactive molecules, such as hydrogen peroxide, glucose, and dopamine. In this review paper, different types of perovskites involved for their electrocatalytic properties are described, and the proposed mechanism of detection is presented. The analytical performances obtained for different electroactive molecules are listed and compared with those in terms of the type of perovskite used, its nanostructuration, and its association with other conductive nanomaterials. The analytical performance obtained with perovskites is shown to be better than those of Ni and Co oxide-based electrochemical sensors. Main trends and future challenges for enlarging and improving the use of perovskite-based electrochemical sensors are then discussed.

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Electrochemical Biosensors Based on Nanostructured Carbon Black: A Review

Journal of Nanomaterials ◽

10.1155/2017/4571614 ◽

2017 ◽

Vol 2017 ◽

pp. 1-14 ◽

Cited By ~ 37

Author(s):

Tiago Almeida Silva ◽

Fernando Cruz Moraes ◽

Bruno Campos Janegitz ◽

Orlando Fatibello-Filho

Keyword(s):

Carbon Black ◽

Surface Area ◽

Electrochemical Sensors ◽

Low Cost ◽

High Surface ◽

Enzymatic Catalysis ◽

High Surface Area ◽

Modified Electrodes ◽

Nanostructured Material ◽

Future Challenges

Carbon black (CB) is a nanostructured material widely used in several industrial processes. This nanomaterial features a set of remarkable properties including high surface area, high thermal and electrical conductivity, and very low cost. Several studies have explored the applicability of CB in electrochemical fields. Recent data showed that modified electrodes based on CB present fast charge transfer and high electroactive surface area, comparable to carbon nanotubes and graphene. These characteristics make CB a promising candidate for the design of electrochemical sensors and biosensors. In this review, we highlight recent advances in the use of CB as a template for biosensing. As will be seen, we discuss the main biosensing strategies adopted for enzymatic catalysis for several target analytes, such as glucose, hydrogen peroxide, and environmental contaminants. Recent applications of CB on DNA-based biosensors are also described. Finally, future challenges and trends of CB use in bioanalytical chemistry are discussed.

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Electroanalysis of Catecholamine Drugs using Graphene Modified Electrodes

Current Analytical Chemistry ◽

10.2174/1573411014666180917113206 ◽

2019 ◽

Vol 15 (4) ◽

pp. 443-466 ◽

Cited By ~ 1

Author(s):

Mahya Karami Mosammam ◽

Mohammad Reza Ganjali ◽

Mona Habibi-Kool-Gheshlaghi ◽

Farnoush Faridbod

Keyword(s):

Electrochemical Sensors ◽

Modified Electrodes ◽

Electrochemical Methods ◽

High Signal ◽

Signal To Noise ◽

Low Level ◽

Biological Studies

Background: Catecholamine drugs are a family of electroactive pharmaceutics, which are widely analyzed through electrochemical methods. However, for low level online determination and monitoring of these compounds, which is very important for clinical and biological studies, modified electrodes having high signal to noise ratios are needed. Numerous materials including nanomaterials have been widely used as electrode modifies for these families during the years. Among them, graphene and its family, due to their remarkable properties in electrochemistry, were extensively used in modification of electrochemical sensors. Objective: In this review, working electrodes which have been modified with graphene and its derivatives and applied for electroanalyses of some important catecholamine drugs are considered.

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Design, Development and Comparison of Heuristic Driven Algorithms Based on the Crossed Domain Products’ Reviews for User’s Summarization

Recent Advances in Computer Science and Communications ◽

10.2174/2213275912666190626110342 ◽

2020 ◽

Vol 13 (5) ◽

pp. 884-892

Author(s):

Sartaj Ahmad ◽

Ashutosh Gupta ◽

Neeraj Kumar Gupta

Keyword(s):

Decision Making ◽

Online Shopping ◽

Recent Time ◽

Design Development ◽

Different Types ◽

Feature Based ◽

Use Of Internet ◽

Day By Day ◽

Better Than

Background: In recent time, people love online shopping but before any shopping feedbacks or reviews always required. These feedbacks help customers in decision making for buying any product or availing any service. In the country like India this trend of online shopping is increasing very rapidly because awareness and the use of internet which is increasing day by day. As result numbers of customers and their feedbacks are also increasing. It is creating a problem that how to read all reviews manually. So there should be some computerized mechanism that provides customers a summary without spending time in reading feedbacks. Besides big number of reviews another problem is that reviews are not structured. Objective: In this paper, we try to design, implement and compare two algorithms with manual approach for the crossed domain Product’s reviews. Methods: Lexicon based model is used and different types of reviews are tested and analyzed to check the performance of these algorithms. Results: Algorithm based on opinions and feature based opinions are designed, implemented, applied and compared with the manual results and it is found that algorithm # 2 is performing better than algorithm # 1 and near to manual results. Conclusion: Algorithm # 2 is found better on the different product’s reviews and still to be applied on other product’s reviews to enhance its scope. Finally, it will be helpful to automate existing manual process.

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Kinetic resolution of indolines by asymmetric hydroxylamine formation

Nature Communications ◽

10.1038/s41467-021-22658-3 ◽

2021 ◽

Vol 12 (1) ◽

Author(s):

Gang Wang ◽

Ran Lu ◽

Chuangchuang He ◽

Lei Liu

Keyword(s):

Hydrogen Peroxide ◽

Chemical Synthesis ◽

Late Stage ◽

Kinetic Resolution ◽

High Efficiency ◽

Bond Formation ◽

Bioactive Molecules ◽

Environmentally Benign ◽

Secondary Amines

AbstractCatalytic kinetic resolution of amines represents a longstanding challenge in chemical synthesis. Here, we described a kinetic resolution of secondary amines through oxygenation to produce enantiopure hydroxylamines involving N–O bond formation. The economic and practical titanium-catalyzed asymmetric oxygenation with environmentally benign hydrogen peroxide as oxidant is applicable to a range of racemic indolines with multiple stereocenters and diverse substituent patterns in high efficiency with efficient chemoselectivity and enantio-discrimination. Late-stage asymmetric oxygenation of bioactive molecules that are otherwise difficult to synthesize was also explored.

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Fighting Together against the Pandemic: Learning Multiple Models on Tomography Images for COVID-19 Diagnosis

AI ◽

10.3390/ai2020016 ◽

2021 ◽

Vol 2 (2) ◽

pp. 261-273

Author(s):

Mario Manzo ◽

Simone Pellino

Keyword(s):

Network Architecture ◽

State Of The Art ◽

Ensemble Classification ◽

Effective Vaccine ◽

Rt Pcr ◽

Neural Network Architecture ◽

Experimental Phase ◽

Different Types ◽

Polymerase Chain ◽

Better Than

COVID-19 has been a great challenge for humanity since the year 2020. The whole world has made a huge effort to find an effective vaccine in order to save those not yet infected. The alternative solution is early diagnosis, carried out through real-time polymerase chain reaction (RT-PCR) tests or thorax Computer Tomography (CT) scan images. Deep learning algorithms, specifically convolutional neural networks, represent a methodology for image analysis. They optimize the classification design task, which is essential for an automatic approach with different types of images, including medical. In this paper, we adopt a pretrained deep convolutional neural network architecture in order to diagnose COVID-19 disease from CT images. Our idea is inspired by what the whole of humanity is achieving, as the set of multiple contributions is better than any single one for the fight against the pandemic. First, we adapt, and subsequently retrain for our assumption, some neural architectures that have been adopted in other application domains. Secondly, we combine the knowledge extracted from images by the neural architectures in an ensemble classification context. Our experimental phase is performed on a CT image dataset, and the results obtained show the effectiveness of the proposed approach with respect to the state-of-the-art competitors.

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Deep Learning Methods for Classification of Certain Abnormalities in Echocardiography

Electronics ◽

10.3390/electronics10040495 ◽

2021 ◽

Vol 10 (4) ◽

pp. 495

Author(s):

Imayanmosha Wahlang ◽

Arnab Kumar Maji ◽

Goutam Saha ◽

Prasun Chakrabarti ◽

Michal Jasinski ◽

...

Keyword(s):

Deep Learning ◽

Short Term Memory ◽

Support Vector ◽

Variational Autoencoder ◽

Different Types ◽

Static Images ◽

Long Short Term Memory ◽

2D And 3D ◽

Better Than

This article experiments with deep learning methodologies in echocardiogram (echo), a promising and vigorously researched technique in the preponderance field. This paper involves two different kinds of classification in the echo. Firstly, classification into normal (absence of abnormalities) or abnormal (presence of abnormalities) has been done, using 2D echo images, 3D Doppler images, and videographic images. Secondly, based on different types of regurgitation, namely, Mitral Regurgitation (MR), Aortic Regurgitation (AR), Tricuspid Regurgitation (TR), and a combination of the three types of regurgitation are classified using videographic echo images. Two deep-learning methodologies are used for these purposes, a Recurrent Neural Network (RNN) based methodology (Long Short Term Memory (LSTM)) and an Autoencoder based methodology (Variational AutoEncoder (VAE)). The use of videographic images distinguished this work from the existing work using SVM (Support Vector Machine) and also application of deep-learning methodologies is the first of many in this particular field. It was found that deep-learning methodologies perform better than SVM methodology in normal or abnormal classification. Overall, VAE performs better in 2D and 3D Doppler images (static images) while LSTM performs better in the case of videographic images.

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A metabolic modeling approach reveals promising therapeutic targets and antiviral drugs to combat COVID-19

Scientific Reports ◽

10.1038/s41598-021-91526-3 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Fernando Santos-Beneit ◽

Vytautas Raškevičius ◽

Vytenis A. Skeberdis ◽

Sergio Bordel

Keyword(s):

Literature Search ◽

Metabolic Modeling ◽

Bioactive Molecules ◽

Flux Balance ◽

Triacsin C ◽

Protein Palmitoylation ◽

Positive Sense ◽

Different Types ◽

Balance Analysis ◽

Docking Calculations

AbstractIn this study we have developed a method based on Flux Balance Analysis to identify human metabolic enzymes which can be targeted for therapeutic intervention against COVID-19. A literature search was carried out in order to identify suitable inhibitors of these enzymes, which were confirmed by docking calculations. In total, 10 targets and 12 bioactive molecules have been predicted. Among the most promising molecules we identified Triacsin C, which inhibits ACSL3, and which has been shown to be very effective against different viruses, including positive-sense single-stranded RNA viruses. Similarly, we also identified the drug Celgosivir, which has been successfully tested in cells infected with different types of viruses such as Dengue, Zika, Hepatitis C and Influenza. Finally, other drugs targeting enzymes of lipid metabolism, carbohydrate metabolism or protein palmitoylation (such as Propylthiouracil, 2-Bromopalmitate, Lipofermata, Tunicamycin, Benzyl Isothiocyanate, Tipifarnib and Lonafarnib) are also proposed.

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Etude par spectrométrie infrarouge de l'action de solvants aprotiques sur l'association ester–eau et ester–Ba2+. Discussion du rôle catalytique du solvant et de l'ion Ba2+ dans l'hydrolyse alcaline du propionate de methyle

Canadian Journal of Chemistry ◽

10.1139/v79-067 ◽

1979 ◽

Vol 57 (4) ◽

pp. 400-403 ◽

Cited By ~ 1

Author(s):

Anne Le Narvor ◽

Pierre Saumagne

Keyword(s):

Ir Spectra ◽

Charge Density ◽

Carbonyl Group ◽

Alkaline Hydrolysis ◽

Experimental Results ◽

Methyl Propionate ◽

Orbital Control ◽

Different Types ◽

Kinetics Of ◽

Better Than

The ir spectra of mixtures of methyl propionate/water and methyl propionate/Ba2+ in dimethylsulfoxide and in acetonitrile have been recorded in the region of the νCO mode of the ester. Evidence is presented to indicate the presence of different types of complexes; their concentration was determined as a function of the composition of the medium. The spectroscopic results are compared to those from the kinetics of the alkaline hydrolysis in the same conditions. It is demonstrated that the orbital control explains the experimental results better than does the charge density on the carbon of the carbonyl group. [Journal translation]

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The electrocatalytic response of metallophthalocyanines when clicked to electrodes and to nanomaterials

10.21504/10962/172191 ◽

2021 ◽

Author(s):

◽

Lekhetho Simon Mpeta

Keyword(s):

Hydrogen Peroxide ◽

Silver Nanoparticles ◽

Zinc Oxide ◽

Photoelectron Spectroscopy ◽

Electrocatalytic Activity ◽

Electrochemical Impedance ◽

Modified Electrodes ◽

Transmission Electron ◽

Reduced Graphene ◽

Electrochemical Microscopy

Conjugates of nanomaterials and metallophthalocyanines (MPcs) have been prepared and their electrocatalytic activity studied. The prepared nanomaterials are zinc oxide and silver nanoparticles, reduced graphene oxide nanosheets and semiconductor quantum dots. The MPcs used in this work are cobalt (II) (1a), manganese(III) (1b) and iron (II) (1c) 2,9(10),16(17),23(24)- tetrakis 4-((4-ethynylbenzyl) oxy) phthalocyaninato, 2,9(10),16(17),23(24)- tetrakis(5-pentyn-oxy) cobalt (II) phthalocyaninato (2), 9(10),16(17),23(24)- tris-[4-tert-butylphenoxy)-2- (4-ethylbezyl-oxy) cobalt (II) phthalocyaninato (3), 9(10),16(17),23(24)- tris-[4-tertbutylphenoxy)-2-(pent-4yn-yloxy)] cobalt (II) phthalocyaninato (4), cobalt (II) (5a) and manganese (III) (5b) 2,9(10),16(17),23(24)- tetrakis [4-(4-(5-chloro-1H-benzo [d]imidazol-2-yl)phenoxy] phthalocyaninato and 9(10),16(17),23(24)- tris tert butyl phenoxy- 2- [4-(4-(5-chloro-1H-benzo[d]imidazole-2-yl)phenoxy] cobalt (II) phthalocyaninato (6). Some of these MPcs (1a, 3 and 4) were directly clicked on azide grafted electrode, while some (1b, 1c, 2, 5a and 5b) were clicked to azide functionalised nanomaterials and then drop-dried on the electrodes. One phthalocyanine (5b) was drop-dried on the electrode then silver nanoparticles were electrodeposited on it taking advantage of metal-N bond. Scanning electrochemical microscopy, voltammetry, chronoamperometry, electrochemical impedance spectroscopy are among electrochemical methods used to characterise modified electrodes. Transmission electron microscopy, X-ray photoelectron spectroscopy, Xray diffractometry, Raman spectroscopy and infrared spectroscopy were employed to study surface functionalities, morphology and topography of the nanomaterials and complexes. Electrocatalytic activity of the developed materials were studied towards oxidation of 2-mercaptoethanol, hydrazine and hydrogen peroxide while the reduction study was based on oxygen and hydrogen peroxide. In general, the conjugates displayed superior catalytic activity when compared to individual materials. Complex 2 alone and when conjugated to zinc oxide nanoparticles were studied for their nonlinear optical behaviour. And the same materials were explored for their hydrazine detection capability. The aim of this study was to develop sensitive, selective and affordable sensors for selected organic waste pollutants. Conjugates were found to achieve the aim of the study compared to when individual materials were employed.

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Development of Au-Pd@UiO-66-on-ZIF-L/CC as a self-supported electrochemical sensor for in situ monitoring of cellular hydrogen peroxide

Journal of Materials Chemistry B ◽

10.1039/d1tb01120k ◽

2021 ◽

Author(s):

Jilin Zheng ◽

Peng Zhao ◽

Shiying Zhou ◽

Sha Chen ◽

Yi Liang ◽

...

Keyword(s):

Hydrogen Peroxide ◽

Electrochemical Sensor ◽

Noble Metals ◽

Electrochemical Sensors ◽

Metal Organic Frameworks ◽

Electrochemical Sensing ◽

In Situ Monitoring ◽

Metal Organic

Integrating metal-organic frameworks (MOFs) of different components or structures together and exploiting them as electrochemical sensors for electrochemical sensing have aroused great interest. And the incorporation of noble metals with...

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