As an easily spoiled source of valuable proteins and lipids, fish is preserved by fermentation in many cultures. Over time, diverse types of products have been produced from fish fermentation aside from whole fish, such as fermented fish paste and sauces. The consumption of fermented fish products has been shown to improve both physical and mental health due to the composition of the products. Fermented fish products can be dried prior to the fermentation process and include various additives to enhance the flavours and aid in fermentation. At the same time, the fermentation process and its conditions play a major role in determining the quality and safety of the product as the compositions change biochemically throughout fermentation. Additionally, the necessity of certain microorganisms and challenges in avoiding harmful microbes are reviewed to further optimise fermentation conditions in the future. Although several advanced technologies have emerged to produce better quality products and easier processes, the diversity of processes, ingredients, and products of fermented fish warrants further study, especially for the sake of the consumers’ health and safety. In this review, the nutritional, microbial, and sensory characteristics of fermented fish are explored to better understand the health benefits along with the safety challenges introduced by fermented fish products. An exploratory approach of the published literature was conducted to achieve the purpose of this review using numerous books and online databases, including Google Scholar, Web of Science, Scopus, ScienceDirect, and PubMed Central, with the goal of obtaining, compiling, and reconstructing information on a variety of fundamental aspects of fish fermentation. This review explores significant information from all available library databases from 1950 to 2022. This review can assist food industries involved in fermented fish commercialization to efficiently ferment and produce better quality products by easing the fermentation process without risking the health and safety of consumers.

In higher plants, the complexity of a system and the components within and among species are rapidly dissected by omics technologies. Multi-omics datasets are integrated to infer and enable a comprehensive understanding of the life processes of organisms of interest. Further, growing open-source datasets coupled with the emergence of high-performance computing and development of computational tools for biological sciences have assisted in silico functional prediction of unknown genes, proteins and metabolites, otherwise known as uncharacterized. The systems biology approach includes data collection and filtration, system modelling, experimentation and the establishment of new hypotheses for experimental validation. Informatics technologies add meaningful sense to the output generated by complex bioinformatics algorithms, which are now freely available in a user-friendly graphical user interface. These resources accentuate gene function prediction at a relatively minimal cost and effort. Herein, we present a comprehensive view of relevant approaches available for system-level gene function prediction in the plant kingdom. Together, the most recent applications and sought-after principles for gene mining are discussed to benefit the plant research community. A realistic tabulation of plant genomic resources is included for a less laborious and accurate candidate gene discovery in basic plant research and improvement strategies.

Exploration of the traditional medicinal plants is essential for drug discovery and development for various pharmacological targets. Various phytochemicals derived from medicinal plants were extensively studied for antiviral activity. This review aims to highlight the role of medicinal plants against viral infections that remains to be the leading cause of human death globally. Antiviral properties of phytoconstituents isolated from 45 plants were discussed for five different types of viral infections. The ability of the plants’ active compounds with antiviral effects was highlighted as well as their mechanism of action, pharmacological studies, and toxicological data on a variety of cell lines. The experimental values, such as IC₅₀, EC₅₀, CC₅₀, ED₅₀, TD₅₀, MIC₁₀₀, and SI of the active compounds, were compiled and discussed to determine their potential. Among the plants mentioned, 11 plants showed the most promising medicinal plants against viral infections. Sambucus nigra and Clinacanthus nutans manifested antiviral activity against three different types of viral infections. Echinacea purpurea, Echinacea augustofolia, Echinacea pallida, Plantago major, Glycyrrhiza uralensis, Phyllanthus emblica, Camellia sinensis, and Cistus incanus exhibited antiviral activity against two different types of viral infections. Interestingly, Nicotiana benthamiana showed antiviral effects against mosquito-borne infections. The importance of phenolic acids, alkamides, alkylamides, glycyrrhizin, epicatechin gallate (ECG), epigallocatechin gallate (EGCG), epigallocatechin (EGC), protein-based plant-produced ZIKV Envelope (PzE), and anti-CHIKV monoclonal antibody was also reviewed. An exploratory approach to the published literature was conducted using a variety of books and online databases, including Scopus, Google Scholar, ScienceDirect, Web of Science, and PubMed Central, with the goal of obtaining, compiling, and reconstructing information on a variety of fundamental aspects, especially regarding medicinal plants. This evaluation gathered important information from all available library databases and Internet searches from 1992 to 2022.

Polycystic ovary syndrome (PCOS) is a complex but frequently occurring endocrine abnormality. PCOS has become one of the leading causes of oligo-ovulatory infertility among premenopausal women. The definition of PCOS remains unclear because of the heterogeneity of this abnormality, but it is associated with insulin resistance, hyperandrogenism, obesity and dyslipidaemia. The main purpose of this study was to identify possible candidate genes involved in PCOS. Several genomic approaches, including linkage analysis and microarray analysis, have been used to look for candidate PCOS genes. To obtain a clearer view of the mechanism of PCOS, we have compiled data from microarray analyses. An extensive literature search identified seven published microarray analyses that utilized PCOS samples. These were published between the year of 2003 and 2007 and included analyses of ovary tissues as well as whole ovaries and theca cells. Although somewhat different methods were used, all the studies employed cDNA microarrays to compare the gene expression patterns of PCOS patients with those of healthy controls. These analyses identified more than a thousand genes whose expression was altered in PCOS patients. Most of the genes were found to be involved in gene and protein expression, cell signaling and metabolism. We have classified all of the 1081 identified genes as coding for either known or unknown proteins. Cytoscape 2.6.1 was used to build a network of protein and then to analyze it. This protein network consists of 504 protein nodes and 1408 interactions among those proteins. One hypothetical protein in the PCOS network was postulated to be involved in the cell cycle. BiNGO was used to identify the three main ontologies in the protein network: molecular functions, biological processes and cellular components. This gene ontology analysis identified a number of ontologies and genes likely to be involved in the complex mechanism of PCOS. These include the insulin receptor signaling pathway, steroid biosynthesis, and the regulation of gonadotropin secretion among others.

Transcriptomics has significantly grown as a functional genomics tool for understanding the expression of biological systems. The generated transcriptomics data can be utilised to produce a gene co-expression network that is one of the essential downstream omics data analyses. To date, several gene co-expression network databases that store correlation values, expression profiles, gene names and gene descriptions have been developed. Although these resources remain scattered across the Internet, such databases complement each other and support efficient growth in the functional genomics area. This review presents the features and the most recent gene co-expression network databases in crops and summarises the present status of the tools that are widely used for constructing the gene co-expression network. The highlights of gene co-expression network databases and the tools presented here will pave the way for a robust interpretation of biologically relevant information. With this effort, the researcher would be able to explore and utilise gene co-expression network databases for crops improvement.