Experimental and theoretical investigation of sensing parameters in carbon nanotube-based DNA sensor

Nowadays, sensitive biosensors with high selectivity, lower costs and short response time are required for detection of DNA. The most preferred materials in DNA sensor designing are nanomaterials such as carbon and Au nanoparticles, because of their very high surface area and biocompatibility which lead to performance and sensitivity improvements in DNA sensors. Carbon nanomaterials such as carbon nanotubes (CNTs) can be considered as a suitable DNA sensor platform due to their high surface-to-volume ratio, favourable electronic properties and fast electron transfer rate. Therefore, in this study, the CNTs which are synthesised by pulsed AC arc discharge method on a high-density polyethylene substrate are used as conducting channels in a chemiresistor for the electrochemical detection of double stranded DNA. Moreover, the response of the proposed sensor is investigated experimentally and analytically in different temperatures, which confirm good agreement between the presented model and experimental data

Computational Clues of Immunogenic Hotspots in Plasmodium falciparum Erythrocytic Stage Vaccine Candidate Antigens: In Silico Approach

Malaria is the most pernicious parasitic infection, and Plasmodium falciparum is the most virulent species with substantial morbidity and mortality worldwide. The present in silico investigation was performed to reveal the biophysical characteristics and immunogenic epitopes of the 14 blood-stage proteins of the P. falciparum using comprehensive immunoinformatics approaches. For this aim, various web servers were employed to predict subcellular localization, antigenicity, allergenicity, solubility, physicochemical properties, posttranslational modification sites (PTMs), the presence of signal peptide, and transmembrane domains. Moreover, structural analysis for secondary and 3D model predictions were performed for all and stable proteins, respectively. Finally, human helper T lymphocyte (HTL) epitopes were predicted using HLA reference set of IEDB server and screened in terms of antigenicity, allergenicity, and IFN-gamma induction as well as population coverage. Also, a multiserver B-cell epitope prediction was done with subsequent screening for antigenicity, allergenicity, and solubility. Altogether, these proteins showed appropriate antigenicity, abundant PTMs, and many B-cell and HTL epitopes, which could be directed for future vaccination studies in the context of multiepitope vaccine design

The Anopheles-midgut APN1 structure reveals a new malaria transmission-blocking vaccine epitope

Mosquito-based malaria transmission-blocking vaccines (mTBVs) target midgut-surface antigens of the Plasmodium parasite's obligate vector, the Anopheles mosquito. The alanyl aminopeptidase N (AnAPN1) is the leading mTBV immunogen; however, AnAPN1's role in Plasmodium infection of the mosquito and how anti-AnAPN1 antibodies functionally block parasite transmission have remained elusive. Here we present the 2.65-angstrom crystal structure of AnAPN1 and the immunoreactivity and transmission-blocking profiles of three monoclonal antibodies (mAbs) to AnAPN1, including mAb 4H5B7, which effectively blocks transmission of natural strains of Plasmodium falciparum. Using the AnAPN1 structure, we map the conformation-dependent 4H5B7 neoepitope to a previously uncharacterized region on domain 1 and further demonstrate that nonhuman-primate neoepitope-specific IgG also blocks parasite transmission. We discuss the prospect of a new biological function of AnAPN1 as a receptor for Plasmodium in the mosquito midgut and the implications for redesigning the AnAPN1 mTBV

The Anopheles-midgut APN1 structure reveals a new malaria transmission-blocking vaccine epitope

Mosquito-based malaria transmission-blocking vaccines (mTBVs) target midgut-surface antigens of the Plasmodium parasite's obligate vector, the Anopheles mosquito. The alanyl aminopeptidase N (AnAPN1) is the leading mTBV immunogen; however, AnAPN1's role in Plasmodium infection of the mosquito and how anti-AnAPN1 antibodies functionally block parasite transmission have remained elusive. Here we present the 2.65-Å crystal structure of AnAPN1 and the immunoreactivity and transmission-blocking profiles of three monoclonal antibodies (mAbs) to AnAPN1, including mAb 4H5B7, which effectively blocks transmission of natural strains of Plasmodium falciparum. Using the AnAPN1 structure, we map the conformation-dependent 4H5B7 neoepitope to a previously uncharacterized region on domain 1 and further demonstrate that nonhuman-primate neoepitope-specific IgG also blocks parasite transmission. We discuss the prospect of a new biological function of AnAPN1 as a receptor for Plasmodium in the mosquito midgut and the implications for redesigning the AnAPN1 mTBV

Identification of a Biomarker Panel for Early Detection of Lung Cancer Patients

Lung cancer is the most common cause of cancer-related mortality worldwide, characterized by late clinical presentation (49-53% of patients are diagnosed at stage IV) and consequently poor outcomes. One challenge in identifying biomarkers of early disease is the collection of samples from patients prior to symptomatic presentation. We used blood collected during surgical resection of lung tumors in an iTRAQ isobaric tagging experiment to identify proteins effluxing from tumors into pulmonary veins. Forty proteins were identified as having an increased abundance in the vein draining from the tumor compared to "healthy" pulmonary veins. These protein markers were then assessed in a second cohort that utilized the mass spectrometry (MS) technique: Sequential window acquisition of all theoretical fragment ion spectra (SWATH) MS. SWATH-MS was used to measure proteins in serum samples taken from 25 patients <50 months prior to and at lung cancer diagnosis and 25 matched controls. The SWATH-MS analysis alone produced an 11 protein marker panel. A machine learning classification model was generated that could discriminate patient samples from patients within 12 months of lung cancer diagnosis and control samples. The model was evaluated as having a mean AUC of 0.89, with an accuracy of 0.89. This panel was combined with the SWATH-MS data from one of the markers from the first cohort to create a 12 protein panel. The proteome signature developed for lung cancer risk can now be developed on further cohorts