Nanomaterials are becoming important materials in several fields and industries thanks to their very reduced size and shape-related features. Scientists think that nanoparticles and nanostructured materials originated during the Big Bang process from meteorites leading to the formation of the universe and Earth. Since 1990, the term nanotechnology became very popular due to advances in imaging technologies that paved the way to specific industrial applications. Currently, nanoparticles and nanostructured materials are synthesized on a large scale and are indispensable for many industries. This fact fosters and supports research in biochemistry, biophysics, and biochemical engineering applications. Recently, nanotechnology has been combined with other sciences to fabricate new forms of nanomaterials that could be used, for instance, for diagnostic tools, drug delivery systems, energy generation/storage, environmental remediation as well as agriculture and food processing. In contrast with traditional materials, specific features can be integrated into nanoparticles, nanostructures, and nanosystems by simply modifying their scale, shape, and composition. This article first summarizes the history of nanomaterials and nanotechnology. Followed by the progress that led to improved synthesis processes to produce different nanoparticles and nanostructures characterized by specific features. The content finally presents various origins and sources of nanomaterials, synthesis strategies, their toxicity, risks, regulations, and self-aggregation.

In an attempt to identify biochemical analytes that could enhance the discrimination between the patients with severe liver fibrosis (F3‐F4) and mild fibrosis (F1‐F2) based on absolute values of biochemical markers, we measured 12 analytes, including procollagen III aminoterminal propeptide (PIIINP), laminin, proline, hydroxylproline, glycine, AST, ALT, alkaline phosphatase, albumin, total bilirubin, total protein, and prothrombin time in 252 individuals with chronic hepatitis C infection (CHC). PIIINP and laminin were determined by radio‐immunoassay; the degraded amino acids were determined using high performance liquid chromatography. Statistical analyses were performed by logistic regression, and receiver operating characteristic (ROC) curves. The best linear combination of blood markers was selected by multivariate discriminant analysis (MDA) for construction of the fibrosis discriminant score (FDS). FDS, an index of five markers (PIIINP, laminin, hydroxyproline, prothrombin activity, and AST/ALT) correctly classified 82% of the patients with severe liver fibrosis at a discriminant cut‐off score=−0.5 (i.e., less than −0.5 indicated severe liver fibrosis and greater than −0.5 indicated mild liver fibrosis with sensitivity (76%) and specificity (89%). This result was reproduced in a validation study with no significant difference. In conclusion, FDS is useful for identifying severe liver fibrosis in patients with CHC.

The incidence of hepatocellular carcinoma (HCC) and HCC-related deaths has increased over the last few decades. There are several risk factors of HCC such as viral hepatitis (B, C), cirrhosis, tobacco and alcohol use, aflatoxin-contaminated food, pesticides, diabetes, obesity, nonalcoholic fatty liver disease (NAFLD), and metabolic and genetic diseases. Diagnosis of HCC is based on different methods such as imaging ultrasonography (US), multiphasic enhanced computed tomography (CT), magnetic resonance imaging (MRI), and several diagnostic biomarkers. In this review, we examine the epidemiology of HCC worldwide and in Egypt as well as risk factors associated with the development of HCC and, finally, provide the updated diagnostic biomarkers for the diagnosis of HCC, particularly in the early stages of HCC. Several biomarkers are considered to diagnose HCC, including downregulated or upregulated protein markers secreted during HCC development, circulating nucleic acids or cells, metabolites, and the promising, recently identified biomarkers based on quantitative proteomics through the isobaric tags for relative and absolute quantitation (iTRAQ). In addition, a diagnostic model used to improve the sensitivity of combined biomarkers for the diagnosis of early HCC is discussed.

A simple scoring system is needed to discriminate HCC from patients with chronic liver diseases (CLD). The simplest score would be one that requires only variables that can be documented simply from routine laboratory tests without the need for sophisticated tests. Data from the estimation group (1351 patients) and the validation group (2208 patients) were retrospectively analysed. Liver fibrosis-negative control and liver cirrhosis were compared with HCC. Area under ROC curve (AUC) were used to develop HCC-α-fetoprotein-routine test (HCC-ART). Hepatocellular carcinoma-AFP-routine test showed diagnostic accuracy for liver cirrhosis vs HCC with ROC curves of 0.99%, sensitivity of 97%, and specificity of 96% in the estimation, and 0.95%, 90%, and 83%, respectively, in the validation. Sensitivity (97%) and specificity (100%) were obtained to discriminate HCC from liver fibrosis. Area under curve for AFP at 400 U l⁻¹ was 0.70, sensitivity was 41%, and specificity was 99% in the estimation, and 0.77%, 54%, and 99%, respectively, in the validation. The AUC for HCC-ART in HCC with single tumour, absent vascular invasion, size <2 cm and CLIP score (0–1) were 0.95, 0.93, 0.86, 0.87, respectively, compared with 0.72, 0.71, 0.71, 0.50, respectively, for AFP. Hepatocellular carcinoma-AFP-routine test could increase the accuracy of HCC screening and surveillances and could be used worldwide without extra efforts.