Future of biomarker evaluation in the realm of artificial intelligence algorithms: application in improved therapeutic stratification of patients with breast and prostate cancer.

Clinical workflows in oncology depend on predictive and prognostic biomarkers. However, the growing number of complex biomarkers contributes to costly and delayed decision-making in routine oncology care and treatment. As cancer is expected to rank as the leading cause of death and the single most important barrier to increasing life expectancy in the 21st century, there is a major emphasis on precision medicine, particularly individualisation of treatment through better prediction of patient outcome.

Evaluation of the Use of Single- and Multi-Magnification Convolutional Neural Networks for the Determination and Quantitation of Lesions in Nonclinical Pathology Studies.

Digital pathology platforms with integrated artificial intelligence have the potential to increase the efficiency of the nonclinical pathologist's workflow through screening and prioritizing slides with lesions and highlighting areas with specific lesions for review. Herein, we describe the comparison of various single- and multi-magnification convolutional neural network (CNN) architectures to accelerate the detection of lesions in tissues. Different models were evaluated for defining performance characteristics and efficiency in accurately identifying lesions in 5 key rat organs (liver, kidney, heart, lung, and brain).

Using Deep Learning Artificial Intelligence Algorithms to Verify N-Nitroso-N-Methylurea and Urethane Positive Control Proliferative Changes in Tg-RasH2 Mouse Carcinogenicity Studies.

In Tg-rasH2 carcinogenicity mouse models, a positive control group is treated with a carcinogen such as urethane or N-nitroso-N-methylurea to test study validity based on the presence of the expected proliferative lesions in the transgenic mice. We hypothesized that artificial intelligence-based deep learning (DL) could provide decision support for the toxicologic pathologist by screening for the proliferative changes, verifying the expected pattern for the positive control groups. Whole slide images (WSIs) of the lungs, thymus, and stomach from positive control groups were used for supervised training of a convolutional neural network (CNN).

Understanding microcystin-LR antibody binding interactions using in silico docking and in vitro mutagenesis.

Microcystins (MCs) are a group of highly potent cyanotoxins that are becoming more widely distributed due to increased global temperatures and climate change. Microcystin-leucine-arginine (MC-LR) is the most potent and most common variant, with a guideline limit of 1 μg/l in drinking water. We previously developed a novel avian single-chain fragment variable (scFv), designated 2G1, for use in an optical-planar waveguide detection system for microcystin determination.

Measurement of the IgM and IgG Autoantibody Immune Responses in Human Serum has High Predictive Value for the Presence of Colorectal Cancer.

Introduction: Colorectal cancer is a major public health issue, with incidences continuing to rise owing to the growing and aging world population. Current screening strategies for colorectal cancer diagnosis suffer from various limitations, including invasiveness and poor uptake. Consequently, there is an unmet clinical need for a minimally invasive, sensitive, and specific method for detecting the presence of colorectal cancer and pre-malignant lesions.

Novel Microfluidic Analytical Sensing Platform for the Simultaneous Detection of Three Algal Toxins in Water.

Globally, the need for "on-site" algal-toxin monitoring has become increasingly urgent due to the amplified demand for fresh-water and for safe, "toxin-free" shellfish and fish stocks. Herein, we describe the first reported, Lab-On-A-Disc (LOAD) based-platform developed to detect microcystin levels in situ, with initial detectability of saxitoxin and domoic acid also reported. Using recombinant antibody technology, the LOAD platform combines immunofluorescence with centrifugally driven microfluidic liquid handling to achieve a next-generation disposable device capable of multianalyte sampling.

Purification of Antibodies Using Affinity Chromatography.

Affinity chromatography permits the isolation of a target analyte from a complex mixture and can be utilized to purify proteins, carbohydrates, drugs, haptens, or any analyte of interest once an affinity pair is available. It involves the exploitation of specific interactions between a binding affinity pair, such as those between an antibody and its associated antigen, or between any ligand and its associated binding receptor/protein. With the discovery of protein A in 1970, and, subsequently protein G and L, immuno-affinity chromatography has grown in popularity and is now the standard methodology for the purification of antibodies which may be implemented for a selection of different applications such as immunodiagnostics.

Immunoaffinity Chromatography: Concepts and Applications.

Antibody-based separation methods, such as immunoaffinity chromatography (IAC), are powerful purification and isolation techniques. Antibodies isolated using these techniques have proven highly efficient in applications ranging from clinical diagnostics to environmental monitoring. Immunoaffinity chromatography is an efficient antibody separation method which exploits the binding efficiency of a ligand to an antibody.

Protein engineering with artificial chemical nucleases.

Herein we report the application of oxidative artificial chemical nucleases as novel agents for protein engineering. The complex ion [Cu(Phen)2(H2O)](2+) (CuPhen; Phen = 1,10-phenanthroline) was applied under Fenton-type conditions against a recombinant antibody fragment specific for prostate-specific antigen (PSA) and compared against traditional DNA shuffling using DNase I for the generation of recombinant mutagenesis libraries. We show that digestion and re-annealment of single chain variable fragment (scFv) coding DNA is possible using CuPhen.

Diagnostic potential of zinc finger protein-specific autoantibodies and associated linear B-cell epitopes in colorectal cancer.

Colorectal cancer is one of the most common cancers worldwide with almost 700,000 deaths every year. Detection of colorectal cancer at an early stage significantly improves patient survival. Cancer-specific autoantibodies found in sera of cancer patients can be used for pre-symptomatic detection of the disease.

Rapid Simultaneous Detection of Anti-protozoan Drugs Using a Lateral-Flow Immunoassay Format.

This research describes the development of a multi-analyte lateral-flow immunoassay intended for the simultaneous detection of three anti-protozoan drugs (coccidiostats). These drugs, namely, halofuginone, toltrazuril and diclazuril, are used in the treatment of Eimeria spp. infections in cattle, pigs, chickens and turkeys.

Light-chain shuffling from an antigen-biased phage pool allows 185-fold improvement of an anti-halofuginone single-chain variable fragment.

Halofuginone is an antiprotozoal drug used in the treatment of coccidiosis in poultry, a contagious enteric disease caused by parasites of the Eimeria spp. To ensure that food is free from any halofuginone residues and safe for human consumption, a rapid method to detect these residues below the maximum residue limits (MRLs) in a variety of matrices is necessary. To address this need, we constructed an immune single-chain variable fragment (scFv) library from the RNA of a halofuginone-immunized chicken and selected halofuginone-specific scFv by phage display.

Purification of antibodies using affinity chromatography.

Affinity chromatography permits the isolation of a target analyte from a complex mixture and can be utilised to purify proteins, carbohydrates, drugs, haptens, or any analyte of interest once an affinity pair is available. It involves the exploitation of specific interactions between a binding affinity pair, such as those between an antibody and its associated antigen, or between any ligand and its associated binding receptor/protein. With the discovery of protein A in 1970, and, subsequently proteins G and L, immuno-affinity chromatography has grown in popularity and is now the standard methodology for the purification of antibodies which may be implemented for a selection of different applications such as immunodiagnostics.

Immunoaffinity chromatography.

Antibody-based separation methods, such as immunoaffinity chromatography (IAC), are powerful purification and isolation techniques. Antibodies isolated using these techniques have proven highly efficient in applications ranging from clinical diagnostics to environmental monitoring. IAC is an efficient antibody separation method which exploits the binding efficiency of a ligand to an antibody.