Magnetic N-doped carbon derived from mixed ligands MOF as effective electrochemiluminescence coreactor for performance enhancement of SARS-CoV-2 immunosensor.

COVID-19 as an infectious disease with rapid transmission speed is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), so, early and accurate diagnostics of COVID-19 is quite challenging. In this work, the selective and sensitive self-enhanced ECL method to detect of SARS-CoV-2 protein was designed with magnetic N-doped carbon derived from dual-ligand metal-organic frameworks (MOF) (CoO@N-C) with the primary and tertiary amino groups as a novel coreactant that covalently combined with Ru(bpy)2(phen-NH2)2+ as electrochemiluminescence (ECL) emitter. Mixed-ligand strategy and selected nitrogen-containing ligands, 4,4',4''-((1,3,5-triazine-2,4,6-triyl) tris-(azanediyl)) tribenzoic acid (H3TATAB) with 2-aminoterephthalic acid (BDC-NH2) were used for synthesis of the proposed MOF. Also, magnetic CoO@N-C with high synergistically charge transfer kinetics and good stability can be used as an effective platform/coreactor on the ITO electrode which load more Ru-complex as signal producing compound and SARS-CoV-2 N protein antibody to increase the sensitivity of the immunosensor. Furthermore, (CoO@N-C) as coreactor improved the ECL signal of the Ru (II)-complex more than 2.1 folds compared to tripropylamine. In view of these competences, the novel "on-off" ECL biosensor performed with great stability and repeatability for detection of SARS-CoV-2 protein, which exhibited a broad linearity from 8 fg. mL-1 to 4 ng. mL-1 (6 order of magnitude) and an ultra-low limit of detection 1.6 fg. mL-1. Finally, this proposed method was successfully applied to detect of SARS-CoV-2 N protein in serum sample with satisfactory results, indicating the proposed immunosensor has the potential for quick analysis of SARS-CoV-2.

Nano and microparticle drug delivery systems for the treatment of Brucella infections.

Nano-based drug delivery systems are increasingly used for diagnosis, prevention and treatment of several diseases, thanks to several beneficial properties, including the ability to target specific cells or organs, allowing to reduce treatment costs and side effects frequently associated with chemotherapeutic medications, thereby improving treatment compliance of patients. In the field of communicable diseases, especially those caused by intracellular bacteria, the delivery of antibiotics targeting specific cells is of critical importance to maximize their treatment efficacy. Brucella melitensis, an intracellular obligate bacterium surviving and replicating inside macrophages is hard to be eradicated, mainly because of the low ability of antibiotics to enter these phagocityc cells . Although different antibiotics regimens including gentamicin, doxycycline and rifampicin are in fact used against the Brucellosis, no efficient treatment has been attained yet, due to the intracellular life of the respective pathogen. Nano-medicines responding to environmental stimuli allow to maximize drug delivery targeting macropages, thereby boosting treatment efficacy. Several drug delivery nano-technologies, including solid lipid nanoparticles, liposomes, chitosan, niosomes, and their combinations with chitosan sodium alginate can be employed in combination of antibiotics to successfully eradicate Brucellosis infection from patients.

Hierarchical machine learning model predicts antimicrobial peptide activity against Staphylococcus aureus.

Introduction: Staphylococcus aureus is a dangerous pathogen which causes a vast selection of infections. Antimicrobial peptides have been demonstrated as a new hope for developing antibiotic agents against multi-drug-resistant bacteria such as S. aureus. Yet, most studies on developing classification tools for antimicrobial peptide activities do not focus on any specific species, and therefore, their applications are limited. Methods: Here, by using an up-to-date dataset, we have developed a hierarchical machine learning model for classifying peptides with antimicrobial activity against S. aureus. The first-level model classifies peptides into AMPs and non-AMPs. The second-level model classifies AMPs into those active against S. aureus and those not active against this species. Results: Results from both classifiers demonstrate the effectiveness of the hierarchical approach. A comprehensive set of physicochemical and linguistic-based features has been used, and after feature selection steps, only some physicochemical properties were selected. The final model showed the F1-score of 0.80, recall of 0.86, balanced accuracy of 0.80, and specificity of 0.73 on the test set. Discussion: The susceptibility to a single AMP is highly varied among different target species. Therefore, it cannot be concluded that AMP candidates suggested by AMP/non-AMP classifiers are able to show suitable activity against a specific species. Here, we addressed this issue by creating a hierarchical machine learning model which can be used in practical applications for extracting potential antimicrobial peptides against S. aureus from peptide libraries.

Applicability of a Green Nanocomposite Consisted of Spongin Decorated Cu2WO4(OH)2 and AgNPs as a High-Performance Aptasensing Platform in Staphylococcus aureus Detection.

This study reports the synthesis of a nanocomposite consisting of spongin and its applicability in the development of an aptasensing platform with high performance. The spongin was carefully extracted from a marine sponge and decorated with copper tungsten oxide hydroxide. The resulting spongin-copper tungsten oxide hydroxide was functionalized by silver nanoparticles and utilized in electrochemical aptasensor fabrication. The nanocomposite covered on a glassy carbon electrode surface amplified the electron transfer and increased active electrochemical sites. The aptasensor was fabricated by loading of thiolated aptamer on the embedded surface via thiol-AgNPs linkage. The applicability of the aptasensor was tested in detecting the Staphylococcus aureus bacterium as one of the five most common causes of nosocomial infectious diseases. The aptasensor measured S. aureus under a linear concentration range of 10-108 colony-forming units per milliliter and a limit of quantification and detection of 12 and 1 colony-forming unit per milliliter, respectively. The highly selective diagnosis of S. aureus in the presence of some common bacterial strains was satisfactorily evaluated. The acceptable results of the human serum analysis as the real sample may be promising in the bacteria tracking in clinical samples underlying the green chemistry principle.

The Trend of IgG and IgM Antibodies During 6-Month Period After the Disease Episode in COVID-19 Patients.

SARS-CoV-2 is a newly emerged coronavirus that has been widely transmitted since late 2019. It has caused a pandemic and infected roughly 450 million people globally.Hitherto, there is no approved anti-COVID-19 treatment, and vaccination is the only experienced preventive strategy. It mainly promotes the immune system, which is vital as a barrier against COVID-19. Humoral immunity (antibody-mediated immunity), among the various functions of the immune system against the coronavirus, plays an outstanding role in preventing infection. Consequently, we intended to assess IgG and IgM antibodies, 3 and 6 months after infection, to trend their titer and see how long COVID-19 antibodies remained in the human body. According to the research-designed criteria, only 98 patients out of 4500 suspected cases of SARS-CoV-2 infection remained for analysis. Blood samples were taken in three time periods (Day Zero (T 0), 3 and 6 months post-infection) and examined for COVID-19's IgG and IgM antibodies titration using the ELISA platform. Though both IgG and IgM were still detectable for some subjects at the end of the period, the decline in their levels (from 14.45 ± 5.88 to 2.52 ± 2.33 for IgG [85% decline of antibody titer] and 8.3 ± 0.99 to 0.37 ± 0.14 for IgM [95.5% decline of antibody titer]) was statistically significant (P value 0.0001). There was no correlation between gender and IgG and IgM levels. Although the levels of both antibodies were overall higher in the senior group (≥ 60 years old), statistical analysis showed a significantly higher level just for IgM in this group (P value: 0.005). Following the results, although anti-SARS-CoV-2 IgM and IgG antibodies can persist in the blood for 6 months post-infection, their levels steeply declined over time. Therefore, relying on humoral immunity as a trustworthy barrier against SARS-CoV-2 infection calls for more extensive research. Supplementary Information: The online version contains supplementary material available at 10.1007/s40995-022-01382-7.

The structural, dynamic, and thermodynamic basis of darunavir resistance of a heavily mutated HIV-1 protease using molecular dynamics simulation.

The human immunodeficiency virus type 1 protease (HIV-1 PR) is an important enzyme in the life cycle of the HIV virus. It cleaves inactive pre-proteins of the virus and changes them into active proteins. Darunavir (DRV) suppresses the wild-type HIV-1 PR (WT-Pr) activity but cannot inhibit some mutant resistant forms (MUT-Pr). Increasing knowledge about the resistance mechanism can be helpful for designing more effective inhibitors. In this study, the mechanism of resistance of a highly MUT-Pr strain against DRV was investigated. For this purpose, complexes of DRV with WT-Pr (WT-Pr-D) and MUT-Pr (MUT-Pr-D) were studied by all-atom molecular dynamics simulation in order to extract the dynamic and energetic properties. Our data revealed that mutations increased the flap-tip flexibility due to the reduction of the flap-flap hydrophobic interactions. So, the protease's conformation changed from a closed state to a semi-open state that can facilitate the disjunction of DRV from the active site. On the other hand, energy analysis limited to the final basins of the energy landscape indicated that the entropy of binding of DRV to MUT-Pr was more favorable than that of WT-Pr. However, the enthalpy penalty overcomes it and makes binding more unfavorable relative to the WT-Pr. The unfavorable interaction of DRV with R8, I50, I84, D25', and A28' residues in MUT-Pr-D relative to WT-Pr-D is the reason for this enthalpy penalty. Thus, mutations drive resistance to DRV. The hydrogen bond analysis showed that compared with WT-Pr, the hydrogen bonds between DRV and the active-site residues of MUT-Pr were disrupted.

A novel label-free electrochemical immunesensor for ultrasensitive detection of LT toxin using prussian blue@gold nanoparticles composite as a signal amplification.

In the current study, a novel electrochemical label-free immunosensor is proposed for sensitive detection of heat-labile enterotoxin (LT) from Escherichia coli. Firstly, a glassy carbon electrode (GCE) was modified by a mixture containing reduced graphene oxide/room temperature ionic liquid (rGO/RTIL) composite. Then, simultaneous electrodeposition of prussian blue and gold nanoparticles led to formation of prussian blue@gold nanoparticles (PB@GNPs) composite on the electrode surface. The modified electrode was characterized by field emission scanning electron microscopy (FE-SEM), energy dispersive spectroscopy (EDS), cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) techniques. After immobilization of anti-LT and blocking the unreacted sites with BSA (bovine serum albumin), the analytical performance of the proposed immunosensor was evaluated under optimal conditions (i.e. optimal pH, incubation time and temperature of incubation). Square wave voltammetry (SWV) was used to determine different concentrations of the LT antigen. The linear dynamic range of the proposed immunosensor was from 0.01 to 50 µg/mL and the detection limit of the immunosensor was found to be 0.0023 µg/mL. An acceptable selectivity in the real sample, long-term stability and goodreproducibility made the fabricated immunosensor a good candidate for detecting LT.

Candidate Molecular Biomarkers for the Non- Invasive Detection of Colorectal Cancer using Gene Expression Profiling.

BACKGROUND & OBJECTIVE: olorectal Cancer (CRC) is the third most common cancer after prostate (breast in women) and lung cancer; it is also the third cause of cancer deaths reported in both men and women in 2020. Currently, the most commonly used diagnostic tools for CRC are colonoscopy, serological methods, and other imaging techniques. Despite the benefits and abilities of these methods, each of them has disadvantages that reduce its functionality and acceptance. The aim of this study was identifying specific and non-invasive genetic biomarkers to diagnose colorectal cancer. METHODS: In this study, changes in the expression of HLTF and SEPT9 genes were evaluated by Real Time PCR in blood and tissue samples of CRC patients. A total of 100 samples (50 Blood and 50 Tissue samples) were evaluated with a definite diagnosis of CRC in Firoozgar Hspital, Tehran, Iran, in 2018. The QPCR method was used to compare the expression of candidate genes between the patients group and control group in both samples. Sensitivity and specificity of the test were examined using ROC curve analysis. RESULTS: The results showed a significant down-regulation in the expression of both selected genes in tissue and peripheral blood in the various stages of the CRC. The sensitivity and specifity of both genes was about 80%. CONCLUSION: The findings showed that the two candidate genes can be suggested as specific biomarkers for diagnosis of CRC using the peripheral blood as a non-invasive method. For a definite conclusion, more research is needed.

A glassy carbon electrode modified with carbon nanoonions for electrochemical determination of fentanyl.

Fentanyl is a pain reliever stronger and deadlier than heroin. This lethal drug has killed many people in different countries recently. Due to the importance of the diagnosis of this drug, a fentanyl electrochemical sensor is developed based on a glassy carbon electrode (GCE) modified with the carbon nanoonions (CNOs) in this study. Accordingly, the electrochemical studies indicated the sensor is capable of the voltammetric determination of traces of fentanyl at a working potential of 0.85 (vs. Ag/AgCl). To obtain the great efficiency of the sensor some experimental factors such as time, the potential of accumulation and pH value of the electrolyte were optimized. The results illustrated a reduction and two oxidation peaks for fentanyl in phosphate buffer (PB) with pH = 7.0 under a probable mechanism of electrochemical-chemical-electrochemical (ECE). The differential pulse voltammetry (DPV) currents related to the fentanyl detection were linear with an increase of fentanyl concentrations in a linear range between 1 µM to 60 µM with a detection limit (LOD) of 300 nM. Furthermore, the values of the diffusion coefficient (D), transfer coefficient (α) and catalytic constant rate (kcat) were calculated to be 2.76 × 10-6 cm2 s-1, 0.54 and 1.76 × 104 M-1 s-1, respectively. These satisfactory results may be attributed to utilizing the CNOs in the electrode modification process due to some of its admirable characterizations of this nanostructure including high surface area, excellent electrical conductivity and good electrocatalytic activity. Consequently, these finding points the achieving a simple sensing system to measure of the fentanyl as an important drug from the judicial perspective might be a dream coming true soon.

Sono-coprecipitation synthesis of ZnO/CuO nanophotocatalyst for removal of parathion from wastewater.

Semiconductor photocatalysis is an effective method used to degrade organophosphorus compounds. Here, the potential of a commonly mixed oxide semiconductor, ZnO/CuO, has been examined to degrade methyl parathion. Sono-coprecipitation method was used to provide ZnO/CuO nanocomposites, and it was applied to photocatalytic and sono-photocatalytic degradation of methyl parathion under solar light irradiation. Powder x-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), the Brunauer-Emmett-Teller (BET) surface area, field emission scanning electron microscopy (FE-SEM), and transmission electron microscopy (TEM) were used to characterize the synthesized samples. The optimal experimental conditions such as ZnO/CuO photocatalyst 90:10 M ratios, the initial concentration of 20 mg/L parathion, 1 g/L photocatalyst loading, no compressed air sparging, pH of 8, and ultrasonic power (60 W and 80 kHz) were used to degrade the parathion effectively. The parathion was fully (100% removal) degraded after 60 min sono-photoirradiation in the optimal experimental conditions. A real water sample was used to examine the ability of the ZnO/CuO photocatalyst 90:10 to remove the parathion in the water-soluble ions. Graphical abstract.

CdS nanocrystals/graphene oxide-AuNPs based electrochemiluminescence immunosensor in sensitive quantification of a cancer biomarker: p53.

An ultrahigh sensitive, simple and reliable Electrochemiluminescence (ECL) immunosensor for selective quantification of p53 protein was designed according to the enhancement effects of AuNPs on ECL emission of CdS nanocrystals (CdS NCs). CdS NCs were immobilized on the glassy carbon electrode and AuNPs introduced to the process through formation of a sandwich-type immunocomplex between first anti-p53/p53/ secondary anti-p53. ECL of CdS NCs firstly evoked the SPR of AuNPs which in return amplified the CdS NCs ECL intensity. By using graphene oxide in immunosensor fabrication procedure, and attaching more AuNPs on the surface of the electrode, the ECL intensity was further increased resulting in much higher sensitivity. After applying the optimum conditions, the linear range of the developed immunosensor was found between 20 and 1000 fg/ml with a calculated limit of detection of 4 fg/ml. Moreover, the interference, reproducibility and storage stability studies of the immunosensor were investigated. Finally, immunosensor's authenticity was evaluated by detecting the p53 protein in human spikes which offers it as a potential in early detection of cancer, monitoring the cancer progress and clinical prognosis.

Detection of hydrogen peroxide and glucose by using Tb2(MoO4)3 nanoplates as peroxidase mimics.

Tb2(MoO4)3 nanostructures are demonstrated for the first time to have an intrinsic peroxidase-like activity. Tb2(MoO4)3 nanoplates could efficiently catalyse the oxidation of 3,3',5,5'-tetramethylbenzidine (TMB) to generate a blue dye (with an absorbance maximum at 652nm) in the presence of H2O2. Based on the highly efficient catalytic of Tb2(MoO4)3 nanoplates, a novel system for optical determination of H2O2 and glucose was successfully established under optimized conditions. The assay had 0.0.08µM and 0.1µM detection limit for H2O2 and glucose, respectively. In our opinion, this enzyme mimetic has a potential to use in other oxidase based assays.

Interaction of insulin with colloidal ZnS quantum dots functionalized by various surface capping agents.

Interaction of quantum dots (QDs) and proteins strongly influenced by the surface characteristics of the QDs at the protein-QD interface. For a precise control of these surface-related interactions, it is necessary to improve our understanding in this field. In this regard, in the present work, the interaction between the insulin and differently functionalized ZnS quantum dots (QDs) were studied. The ZnS QDs were functionalized with various functional groups of hydroxyl (OH), carboxyl (COOH), amine (NH2), and amino acid (COOH and NH2). The effect of surface hydrophobicity was also studied by changing the alkyl-chain lengths of mercaptocarboxylic acid capping agents. The interaction between insulin and the ZnS QDs were investigated by fluorescence quenching, synchronous fluorescence, circular dichroism (CD), and thermal aggregation techniques. The results reveal that among the studied QDs, mercaptosuccinic acid functionalized QDs has the strongest interaction (∆G°=-51.50kJ/mol at 310K) with insulin, mercaptoethanol functionalized QDs destabilize insulin by increasing the beta-sheet contents, and only cysteine functionalized QDs improves the insulin stability by increasing the alpha-helix contents of the protein, and. Our results also indicate that by increasing the alkyl-chain length of capping agents, due to an increase in hydrophobicity of the QDs surface, the beta-sheet contents of insulin increase which results in the enhancement of insulin instability.

Affinity enhancement of nanobody binding to EGFR: in silico site-directed mutagenesis and molecular dynamics simulation approaches.

Epidermal growth factor receptor (EGFR), a transmembrane glycoprotein, is overexpressed in many cancers such as head-neck, breast, prostate, and skin cancers for this reason it is a good target in cancer therapy and diagnosis. In nanobody-based cancer diagnosis and treatment, nanobodies with high affinity toward receptor (e.g. EGFR) results in effective treatment or diagnosis of cancer. In this regard, the main aim of this study is to develop a method based on molecular dynamic (MD) simulations for designing of 7D12 based nanobody with high affinity compared with wild-type nanobody. By surveying electrostatic and desolvation interactions between different residues of 7D12 and EGFR, the critical residues of 7D12 that play the main role in the binding of 7D12 to EGFR were elucidated and based on these residues, five logical variants were designed. Following the 50 ns MD simulations, pull and umbrella sampling simulation were performed for 7D12 and all its variants in complex with EGFR. Binding free energy of 7D12 (and all its variants) with EGFR was obtained by weighted histogram analysis method. According to binding free energy results, GLY101 to GLU mutation showed the highest binding affinity but this variant is unstable after 50 ns MD simulations. ALA100 to GLU mutation shows suitable binding enhancement with acceptable structural stability. Suitable position and orientation of GLU in residue 100 of 7D12 against related amino acids of EGFR formed some extra hydrogen and electrostatic interactions which resulted in binding enhancement.