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Low-cost, instrument-free colorimetric tests were developed to detect SARS-CoV-2 using plasmonic biosensors with Au nanoparticles functionalized with polyclonal antibodies (f-AuNPs). Intense color changes were noted with the naked eye owing to plasmon coupling when f-AuNPs form clusters on the virus, with high sensitivity and a detection limit of 0.28 PFU mL

Herein, we introduce wearable potentiometric biosensors on screen-printed carbon electrodes (SPCEs) for on-body and on-site monitoring of urea in sweat. The biosensor architecture was judiciously designed to detect urea at different pHs and incorporate a pH sensor, thus containing polyaniline ink, urease bioink and a polyvinylchloride membrane. Urea detection could be performed in the wide range from 5 to 200 mM at pH 7.0, encompassing urea levels in human sweat. The biosensor response was fast (incubation time 5 min), with no interference from other substances in sweat. Reliable urea detection could be done in undiluted human sweat with a skin-worn flexible device using the pH correction strategy afforded by the pH sensor. The performance of the epidermal biosensor was not affected by severe bending strains. The feasibility of mass production was demonstrated by fabricating epidermal flexible biosensors using slot-die coating with a roll-to-roll technique.

Low temperature, microcube-shaped zinc stannate (ZnSnO3) nanostructures using a low-power microheater sensor platform to detect NO2 gas with high sensitivity and selectivity.

We report on the preparation of SiO2-based nanoparticles readily available for superhydrophobic applications. In contrast to usual approaches, our process is substrate-free and based on electrostatic adsorption of small SiO2 particles onto large SiO2 cores with the aid of poly(diallyldimethylammonium chloride) followed by calcination and chemical modification with trichlorododecylsilane. The as-prepared nanoparticles are in powder form and exhibit stable superhydrophobic behavior at room temperature because of the unique combination between the hierarchical raspberry-like structure and low surface energy. If properly stored, the nanoparticles retain their functional properties for several months.

Cancer is the second leading cause of death globally and early diagnosis is the best strategy to reduce mortality risk. Biosensors to detect cancer biomarkers are based on various principles of detection, including electrochemical, optical, electrical, and mechanical measurements. Despite the advances in the identification of biomarkers and the conventional 2D manufacturing processes, detection methods for cancers still require improvements in terms of selectivity and sensitivity, especially for point-of-care diagnosis. Three-dimensional printing may offer the features to produce complex geometries in the design of high-precision, low-cost sensors. Three-dimensional printing, also known as additive manufacturing, allows for the production of sensitive, user-friendly, and semi-automated sensors, whose composition, geometry, and functionality can be controlled. This paper reviews the recent use of 3D printing in biosensors for cancer diagnosis, highlighting the main advantages and advances achieved with this technology. Additionally, the challenges in 3D printing technology for the mass production of high-performance biosensors for cancer diagnosis are addressed., This research was funded by CNPq (National Council for Scientific and Technological Development, grant #114307/2020-2), CAPES, and Sao Paulo Research Foundation (Grants #2020/12980-3, #2020/05612-8, #2018/22214-6 and #2018/18953-8).

Calibration curves are essential constructs in analytical chemistry to determine parameters of sensing performance. In the classification of sensing data of complex samples without a clear dependen...

Made available in DSpace on 2021-06-25T10:53:54Z (GMT). No. of bitstreams: 0 Previous issue date: 2021-05-01 Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) EMC Dengue virus infection depends on its fusion with the host membrane, where the binding occurs through interaction between proteins on the virus cell surface and specific viral receptors on target membranes. This process is mediated by the fusion peptide located between residues 98 and 112 (DRGWGNGCGLFGKGG) that forms a loop in domain II of dengue E glycoprotein. In this study, we evaluated the role of fusion peptide surrounding regions (88–97 and 113–123) of the Dengue 2 subtype on its interaction with the membrane and fusion activity. These sequences are important to stabilize the fusion peptide loop and increase fusion activity. Three peptides, besides the fusion peptide, were synthesized by SPPS using the Fmoc chemical approach. The first contains the fusion peptide and the C-terminal region of the loop (sequence 98–123); another contains the N-terminal region (88–112) and the larger peptide contains both regions (88–123). The peptides were able to interact with a model membrane. Differences in morphology of the monolayer promoted by the peptides were assessed by Brewster Angle Microscopy (BAM). Our data indicated that the C-terminal region of fusion peptide loop is more efficient in promoting fusion and interacting with the membrane than the N-terminal sequence, which is responsible for the electrostatic initial interaction. We propose a 2-step mechanism for the interaction of the dengue virus fusion peptide with the host membrane, where the N-terminal sequence docks electrostatically on the headgroups and then the C-terminal interacts via hydrophobic forces in the acyl chains. Departamento de Bioquímica e Química Orgânica Instituto de Química UNESP -Univ Estadual Paulista Instituto de Física de São Carlos Universidade de São Paulo USP, São Carlos Department of Chemistry The Ohio State University Departamento de Bioquímica e Química Orgânica Instituto de Química UNESP -Univ Estadual Paulista

The polysaccharide β-glucan, found in the cell wall of cereals such as wheat, oats, and barley, is believed to lower the concentration of bad cholesterol in humans, but the molecular-level mechanisms responsible for such an action are unknown. In this study, we use Langmuir monolayers of cholesterol and dipalmitoyl phosphatidyl choline (DPPC) as cell membrane models that are made to interact with β-glucan. Neat cholesterol and mixed cholesterol/DPPC monolayers were expanded upon incorporating β-glucan from the aqueous subphase. This incorporation was found to induce ordering in mixed monolayers and dehydration of the carbonyl group at higher cholesterol concentrations. These effects are attributed to hydrophobic interactions as identified with polarization-modulated infrared reflection–absorption spectroscopy. They correlate well with the hypothesis that cholesterol levels can be lowered by the formation of soluble fibers with β-glucan through hydrophobic interactions, blocking cholesterol absorption by the organism.

Although Ag-based materials are efficient against antibiotic-resistant bacteria, their high toxicity to living organisms represents a major challenge for obtaining useful products. In this work, we report the bactericidal activity of Ag

Machine learning and other artificial intelligence methods are gaining increasing prominence in chemistry and materials sciences, especially for materials design and discovery, and in data analysis of results generated by sensors and biosensors. In this paper, we present a perspective on this current use of machine learning, and discuss the prospects of the future impact of extending the use of machine learning to encompass knowledge discovery as an essential step towards a new paradigm of machine-generated knowledge. The reasons why results so far have been limited are given with a discussion of the limitations of machine learning in tasks requiring interpretation. Also discussed is the need to adapt the training of students and scientists in chemistry and materials sciences, to better explore the potential of artificial intelligence capabilities.

In this paper we report on a modular design that allows one to fabricate electrochemical sensors upon combining 3D printing and screen printing. The usefulness of the design is showcased with graphene paste electrodes (GPE) coated with magnetic microspheres used to detect the drug nimesulide (NIM), biomarkers dopamine (DOP) and uric acid (UA). Under optimized conditions, the limit of detection was 0.0023 μmol L−1 in the range from 0.5 to 9 μmol L−1, 0.01 μmol L−1 within the range from 0.8 to 6 μmol L−1, and 0.0034 μmol L−1 from 0.7 to 10 μmol L−1 for dopamine, nimesulide, and uric acid, respectively. The three analytes could also be detected in blood serum and artificial urine samples within approximately 20 s, which is promising for clinical applications. With the modular design, the paste can be prepared with a variety of nanomaterials, functionalized with biomolecules and magnetic particles, and then stored for later use. The working electrode may also be polished to allow for reuse. Furthermore, in contrast to standard sensors made with carbon pastes, the electrochemical sensor proposed here requires small volumes (20–200 μL), which is crucial for drug monitoring and other biomedical applications.

We report on a photoelectrochemical (PEC) device to detect prostatic-specific antigen (PSA) under visible LED light irradiation within the point-of-care (POC) paradigm. The device consists of a 3D printed miniaturized photoelectrochemical system and a disposable PEC immunosensor made with screen-printed carbon electrodes (SPCEs). The SPCEs were coated with nickel single atoms anchored on graphitic carbon nitride (Ni-gC

The Langmuir-Blodgett (LB) technique, through which monolayers are transferred from the air/water interface onto a solid substrate, was the first method to allow for the controlled assembly of organic molecules. With its almost 100 year history, it has been the inspiration for most methods to functionalize surfaces and produce nanocoatings, in addition to serving to explore concepts in molecular electronics and nanoarchitectonics. This paper provides an overview of the history of Langmuir monolayers and LB films, including the potential use in devices and a discussion on why LB films are seldom considered for practical applications today. Emphasis is then given to two areas where these films offer unique opportunities, namely, in mimicking cell membrane models and exploiting nanoarchitectonics concepts to produce sensors, investigate molecular recognitions, and assemble molecular machines. The most promising topics for the short- and long-term prospects of the LB technique are also highlighted.

Plasmonic and magnetic silicon hybrids are suitable hyperthermia nanoagents owing to their ability to generate heat under an external stimulus in addition to their biocompatibility, limited aggregation, dielectric properties, and surface functionalization. In this chapter, a discussion will be provided the applications of plasmonic and magnetic silicon hybrid nanoparticles in hyperthermia treatments. We shall first introduce the fundamentals of nanoparticle heating with the mechanisms triggered by localized surface plasmon polaritons and alternating magnetic fields. The synthesis and characterization of plasmonic and magnetic silicon hybrid nanoparticles will then be described, including examples of promising hyperthermia nanoagents designed to possess a heating efficient conversion. The last topic deals with hyperthermia in vivo and in vitro applications for pathological diseases, especially those related to malignant tumor cells and bacterial infections.

Flexible, fully printed immunosensors can meet the requirements of precision nutrition, but this demands optimized molecular architectures to reach the necessary sensitivity. Herein, we report on flexible and label-free immunosensor chips made with tree-like gold dendrites (AuDdrites) electrochemically formed by selective desorption of l-cysteine (

Drug resistance is known to depend on the interactions with cell membranes and other molecules such as human cytochromes P450 (CYPs) which are anchored on the endoplasmic reticulum (ER) membrane and involved in the metabolism of anticancer drugs. In this study, we determined the influence from cytochrome P450 3A4 (CYP3A4) on the interaction between the drug doxorubicin (DOX) and Langmuir monolayers mimicking cell membranes. The lipid composition was varied by changing the relative concentrations of cholesterol (Chol), 1,2-dipalmitoyl-sn-glycero-3-phosphocholine (DPPC), 1,2-dipalmitoyl-sn-glycero-3-phosphoethanolamine (DPPE), and L-α-phosphatidylinositol (PI). Three compositions were studied in detail which represented a healthy cell membrane and cancerous cell membranes. DOX induced an expansion in the surface pressure isotherms for all monolayers, with stronger effect for the composition of cancerous cell with a high Chol content, thus confirming the relevance of lipid composition. This effect decreased considerably when CYP3A4 was incorporated with the formation of CYP3A4-DOX complexes, according to results from polarization-modulated infrared reflection absorption spectroscopy (PM-IRRAS) measurements. Taken together, these results support the hypothesis of CYP3A4 being involved in drug resistance, which may be exploited to design strategies to enhance chemotherapy efficacy.

Low-cost sensors to detect cancer biomarkers with high sensitivity and selectivity are essential for early diagnosis. Herein, an immunosensor was developed to detect the cancer biomarker p53 antigen in MCF7 lysates using electrical impedance spectroscopy. Interdigitated electrodes were screen printed on bacterial nanocellulose substrates, then coated with a matrix of layer-by-layer films of chitosan and chondroitin sulfate onto which a layer of anti-p53 antibodies was adsorbed. The immunosensing performance was optimized with a 3-bilayer matrix, with detection of p53 in MCF7 cell lysates at concentrations between 0.01 and 1000 Ucell. mL−1, and detection limit of 0.16 Ucell mL−1. The effective buildup of the immunosensor on bacterial nanocellulose was confirmed with polarization-modulated infrared reflection absorption spectroscopy (PM-IRRAS) and surface energy analysis. In spite of the high sensitivity, full selectivity with distinction of the p53-containing cell lysates and possible interferents required treating the data with a supervised machine learning approach based on decision trees. This allowed the creation of a multidimensional calibration space with 11 dimensions (frequencies used to generate decision tree rules), with which the classification of the p53-containing samples can be explained., This work was supported by CAPES, CNPq (160290/2019-8, 164569/2020-0, 311757/2019-7 and 423952/2018-8), INEO, FAPESP (2018/18953-8, 2020/09587-8, 2016/01919-6, 2019/01777-5 and 2018/22214-6) (Brazil).

We report an electronic tongue based on impedance spectroscopy to detect Staphylococcus aureus and diagnose bovine mastitis in milk samples. This was achieved with optimized sensing units made with layer-by-layer films and by treating the capacitance data with machine learning algorithms employing decision trees models. These films were made with chitosan, chondroitin sulfate, sericin and gold nanoparticles /sericin, whose molecular-level interaction with S.aureus depended on the architecture according to PM-IRRAS measurements. The limit of detection in blank milk varied from 3.41 to 2.01 CFU/mL depending on the sensing unit. This sensitivity was complemented with the selectivity provided by combining the electrical responses of the four sensing units. Indeed, with machine learning it was possible to determine multidimensional calibration spaces (MCS) that could generate rules to explain how the milk samples could be discriminated. With a 7-dimension MCS, distinct S.aureus concentrations could be distinguished from possible interferents with a 100 % accuracy. In crude milk samples, 94 % accuracy was obtained with a 6-dimension MCS in multiclass classification for milk from different udders of a mastitis infected cow, including samples diluted 50-fold, in addition to milk from an infected cow treated with Bronopol and from a healthy cow. It is significant that in a ternary classification with these crude milk samples, a 2-dimension MCS could distinguish between milk from an infected cow, treated with Bronopol and from a healthy cow with 100 % accuracy. The combination of electronic tongues and machine learning – as in this proof-of-concept study - is promising for diagnosis of mastitis at a low cost., This work is supported by São Paulo Research Foundation (FAPESP) (Grants # 2018/18953-8 and 2018/22214-6), Brazilian National Council for Scientific and Technological Development (CNPq) (Grant # 402287/2013-4, 304044/2019-9 and # 303796/2014-6), FAPEMIG (CVZ PPM 00691/17 and RED-00282/16), SISNANO-MCTI, the Financier of Studies and Projects (FINEP), INEO and Rede Agronano/Embrapa. Participation of SSdM and MSG were made possible through the Harvard-wide Program on Antibiotic Resistance (NIH Grant AI083214). We thank Prof. Paulo Machado (ESALQ-USP/ Clínica do Leite) and Mr. Augusto Lima (Clínica do Leite) for crude milk samples with Bronopol. 6. References

Langmuir monolayers are used to simulate the biological membrane environment, acting as a mimetic system of the outer or the inner membrane leaflet. Herein, we analyze the interaction of membrane models with a partially N-acetylated chitosan (Ch35%) possessing a quasi-ideal random pattern of acetylation, full water solubility up to pH ≈ 8.5 and unusually high weight average molecular weight. Lipid monolayers containing dipalmitoyl phosphatidyl choline (DPPC), dipalmitoyl phosphatidyl ethalonamine (DPPE), dipalmitoyl phosphatidyl glycerol (DPPG) or E. coli total lipid extract were spread onto subphases buffered at pH 4.5 or 7.4. The incorporation of Ch35% chitosan caused monolayer expansion and a general trend of decreasing monolayer rigidity with Ch35% concentration. Due to its relatively high content of N-acetylglucosamine (GlcNAc) units, Ch35% interactions with negatively charged monolayers and with E. coli extract were weaker than those involving zwitterionic monolayers or lipid rafts. While the smaller interaction with negatively charged lipids was unexpected, this finding can be attributed to the degree of acetylation (35%) which imparts a small number of charged groups for Ch35% to interact. Chitosan properties are therefore determinant for interactions with model cell membranes, which explains the variability in chitosan bactericide activity in the literature. This is the first study on the effects from chitosans on realistic models of bacterial membranes under physiological pH.

In this paper, we report a simple procedure to decouple effects from temperature and volume on the emission properties of thin films of poly[2-methoxy-5-(2'-ethylhexyloxy)-1,4-phenylene-vinylene] (MEH-PPV). This procedure consists of applying a positive pressure close to the β-relaxation temperature, Tβ (∼220 K), of MEH-PPV, which controls the molecular movement to retain a disordered state for the polymer chains even after the sample is cooled from room temperature. Such decoupling could be confirmed by calculating the photoluminescence (PL) spectra line shape using a semi-empirical model based on molecular exciton and Franck-Condon transitions, and with electron-vibrational modes coupling being parameterized with the Huang-Rhys factor. We also show that the decoupling between temperature and volume effects does not occur if the molecular movement is restricted either by thermal annealing or by depositing the MEH-PPV film on a rigid substrate. This latter finding may be exploited in designing thermally stable devices.

The surface functionalization of nanoporous silica materials with chemical agents opens up numerous possibilities, including improvement in the materials' ability to carry high payloads of drugs. In this study, KCC-1 nanofibrous silica microparticles are functionalized with methyl groups and then combined with poly(vinyl alcohol) (PVA) and poly(acrylic acid) (PAA) to produce hybrid aerogels that can deliver a poorly water-soluble anticancer drug. The synthetic steps involve freeze-drying a polymer solution of PVA and PAA that contains methyl-modified KCC-1 microparticles and then cross-linking the two polymers via a solid-state reaction. Benefiting from the incorporated methyl-modified KCC-1 microparticles, the hybrid aerogels can load and deliver a payload of camptothecin (CPT), an anticancer drug with antitumor activity but limited clinical application due to its hydrophobicity. The aerogels also show a sustained release of CPT for more than two weeks. The drug release profile can further be tuned by varying the relative amounts of PVA, PAA, and methyl-modified KCC-1. The aerogels are biocompatible to healthy cells, such as immortalized human epithelial (HaCaT), African green monkey kidney (Vero) and murine fibroblast (L929) cells. When loaded with CPT, they show potent antitumor activity against HeLa (HPV18-positive), SiHa (HPV16-positive) and C33A (HPV-negative) cancer cells, significantly inhibiting cell growth.

Detection of human papillomavirus 16 (HPV16) is essential for the diagnosis of cervix and head and neck cancer, which has prompted the development of biosensors to replace the sophisticated molecular techniques. In this paper, we employ a genosensor made with a HPV16 DNA probe (cpHPV16) immobilized on a layer-by-layer (LbL) film of chitosan and carbon nanotubes to detect a complementary sequence HPV16 oligo (ssHPV16). In addition to employing impedance spectroscopy, which has already been used in the literature, we detect ssHPV16 in buffer samples and in cancer cell line samples with UV-vis. spectroscopy. The limit of detection was 18.5 pmol L−1 in impedance spectroscopy measurements and 10.9 pmol L−1 in UV-vis measurements. Distinction of the various ssHPV16 concentrations and of the cancer cell line samples CasKi, SiHa, UMSCC-47, UM-SCC104 and 93-VU147T with both electrical and optical data could be made with the multidimensional projection technique referred to as interactive document mapping (IDMAP), with which we could confirm the absence of false positives by testing cell lines that did not contain ssHPV16 (JHU12, JHU13 and JHU28). The hybridization between cpHPV16 and ssHPV16 responsible for the biosensing was verified with polarization-modulated infrared reflection absorption spectroscopy (PM-IRRAS), while the concentration dependence could be modeled with a double Freundlich function. The use of optical absorbance measurements to detect ssHPV16 is promising toward a simple colorimetric detection.

This paper reports the development of a low-cost ( US$ 0.03 per device) immunosensor based on gold-modified screen-printed carbon electrodes (SPCEs). As a proof of concept, the immunosensor was tested for a fast and sensitive determination of S proteins from both SARS-CoV and SARS-CoV-2, by a single disposable device. Gold nanoparticles were electrochemically deposited via direct reduction of gold ions on the electrode using amperometry. Capture antibodies from spike (S) protein were covalently immobilized on carboxylic groups of self-assembled monolayers (SAM) of mercaptoacetic acid (MAA) attached to the gold nanoparticles. Label-free detection of S proteins from both SARS-CoV and SARS-CoV-2 was performed with electrochemical impedance spectroscopy (EIS). The immunosensor fabricated with 9 s gold deposition had a high performance in terms of selectivity, sensitivity, and low limit of detection (LOD) (3.16 pmol L

Mass testing for the diagnosis of COVID-19 has been hampered in many countries owing to the high cost of genetic material detection. This study reports on a low-cost immunoassay for detecting SARS-CoV-2 within 30 min using dynamic light scattering (DLS). The immunosensor comprises 50-nm gold nanoparticles (AuNPs) functionalized with antibodies against SARS-CoV-2 spike glycoprotein, whose bioconjugation was confirmed using transmission electron microscopy (TEM), UV-Vis spectroscopy, Fourier transform infrared spectroscopy (FTIR), and surface-enhanced Raman scattering spectroscopy (SERS). The specific binding of the bioconjugates to the spike protein led to an increase in bioconjugate size, with a limit of detection (LOD) 5.29 × 10