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Topic Review
Water Footprint in Steel Industries
Steelmaking is a water-intensive process. The mean water intake against each ton of steel manufactured is ascertained as between 2 and 20 m3. Primarily, the stated requirement is in the form of make-up water to compensate for evaporation and mechanical losses and does not contribute to wastewater generation. Conversely, unit operations, such as rolling, continuous casting, pickling, etc., generate highly complex wastewater rich in polycyclic aromatic hydrocarbons (PAH), cyanide, ammonia, non-consumed acids, benzene, toluene, xylene, oil, grease, etc. 
  • 2.7K
  • 15 Jun 2023
Topic Review
Fungal Light Responses
Organisms have developed different features to capture or sense sunlight. Vertebrates have evolved specialized organs (eyes) which contain a variety of photosensor cells that help them to see the light to aid orientation. Opsins are major photoreceptors found in the vertebrate eye. Fungi, with more than five million estimated members, represent an important clade of living organisms which have important functions for the sustainability of life on our planet. Light signalling regulates a range of developmental and metabolic processes including asexual sporulation, sexual fruit body formation, pigment and carotenoid production and even production of secondary metabolites. Fungi have adopted three groups of photoreceptors: (I) blue light receptors, White Collars, vivid, cryptochromes, blue F proteins and DNA photolyases, (II) red light sensors, phytochromes and (III) green light sensors and microbial rhodopsins.
  • 428
  • 15 Jun 2023
Topic Review
Lot-to-Lot Variance in Immunoassays
Immunoassays, which have gained popularity in clinical practice and modern biomedical research, play an increasingly important role in quantifying various analytes in biological samples. Despite their high sensitivity and specificity, as well as their ability to analyze multiple samples in a single run, immunoassays are plagued by the problem of lot-to-lot variance (LTLV). LTLV negatively affects assay accuracy, precision, and specificity, leading to considerable uncertainty in reported results. Therefore, maintaining consistency in technical performance over time presents a challenge in reproducing immunoassays.
  • 255
  • 15 Jun 2023
Topic Review
Big Data on the Farm
The demand for poultry meat and eggs is predicted to considerably increase in pace with human population growth. Although this expansion clearly represents a remarkable opportunity for the sector, it conceals a multitude of challenges. Pollution and land erosion, competition for limited resources between animal and human nutrition, animal welfare concerns, limitations on the use of growth promoters and antimicrobial agents, and increasing risks and effects of animal infectious diseases and zoonoses are several topics that have received attention from authorities and the public. The increase in poultry production must be achieved mainly through optimization and increased efficiency. The increasing ability to generate large amounts of data (“big data”) is pervasive in both modern society and the farming industry. Information accessibility—coupled with the availability of tools and computational power to store, share, integrate, and analyze data with automatic and flexible algorithms—offers an unprecedented opportunity to develop tools to maximize farm profitability, reduce socio-environmental impacts, and increase animal and human health and welfare. A detailed description of all topics and applications of big data analysis in poultry farming would be infeasible. The principles and benefits of advanced statistical techniques, such as machine learning and deep learning, and their use in developing effective and reliable classification and prediction models to benefit the farming system, are also discussed.
  • 369
  • 15 Jun 2023
Topic Review
Regulation of CD36 Expression and Activity in Cancer
Cluster of differentiation 36 (CD36) is a cell surface scavenger receptor that plays critical roles in many different types of cancer, notably breast, brain, and ovarian cancers. While it is arguably most well-known for its fatty acid uptake functions, it is also involved in regulating cellular adhesion, immune response, and apoptosis depending on the cellular and environmental contexts.
  • 653
  • 15 Jun 2023
Topic Review
Continuum of Protein Structures and Dynamics for Function
The range of protein conformational dynamics in nature can be roughly classified into four general categories of increasing complexity and thus difficulty for characterization and prediction. The simplest case is local conformational dynamics within a largely well-defined native fold. Such dynamics include atomic thermal fluctuations around the native structure, which measure the local rigidity.
  • 298
  • 15 Jun 2023
Topic Review
Protein Extraction Methods from Formalin-Fixed Paraffin-Embedded Tissue
The relatively developments in mass spectrometry (MS) have provided novel opportunities for this technology to impact modern medicine. One of those opportunities is in biomarker discovery and diagnostics. Key developments in sample preparation have enabled a greater range of clinical samples to be characterized at a deeper level using MS. While most of these developments have focused on blood, tissues have also been an important resource. Fresh tissues, however, are difficult to obtain for research purposes and require significant resources for long-term storage. There are millions of archived formalin-fixed paraffin-embedded (FFPE) tissues within pathology departments worldwide representing every possible tissue type including tumors that are rare or very small. Owing to the chemical technique used to preserve FFPE tissues, they were considered intractable to many newer proteomics techniques and primarily only useful for immunohistochemistry. In the past couple of decades, however, researchers have been able to develop methods to extract proteins from FFPE tissues in a form making them analyzable using state-of-the-art technologies such as MS and protein arrays. 
  • 255
  • 15 Jun 2023
Topic Review
Seahorse Male Pregnancy
Seahorses, together with sea dragons and pipefishes, belong to the Syngnathidae family of teleost fishes. Seahorses and other Syngnathidae species have a very peculiar feature: male pregnancy. Among different species, there is a gradation of paternal involvement in carrying for the offspring, from a simple attachment of the eggs to the skin surface, through various degrees of egg coverage by skin flaps, to the internal pregnancy within a brood pouch, which resembles mammalian uterus with the placenta. Because of the gradation of parental involvement and similarities to mammalian pregnancy, seahorses are a great model to study the evolution of pregnancy and the immunologic, metabolic, cellular, and molecular processes of pregnancy and embryo development. Seahorses are also very useful for studying the effects of pollutants and environmental changes on pregnancy, embryo development, and offspring fitness. 
  • 364
  • 15 Jun 2023
Topic Review
Bacterial Membrane Vesicles as Smart Drug Delivery Systems
Bacterial membrane vesicles (BMVs) are known to be critical communication tools in several pathophysiological processes between bacteria and host cells. Given this situation, BMVs for transporting and delivering exogenous therapeutic cargoes have been inspiring as promising platforms for developing smart drug delivery systems (SDDSs).
  • 506
  • 15 Jun 2023
Topic Review
Applications of Machine Learning Algorithms in Food Industry
Machine learning assists with food process optimization techniques by developing a model to predict the optimal solution for given input data. Machine learning includes unsupervised and supervised learning, data pre-processing, feature engineering, model selection, assessment, and optimization methods. Various problems with food processing optimization could be resolved using these techniques. Machine learning is increasingly being used in the food industry to improve production efficiency, reduce waste, and create personalized customer experiences. Machine learning may be used to improve ingredient utilization and save costs, automate operations such as packing and labeling, and even forecast consumer preferences to develop personalized products. Machine learning is also being used to identify food safety hazards before they reach the consumer, such as contaminants or spoiled food. The usage of machine learning in the food sector is predicted to rise as more businesses understand the potential of this technology to enhance customer experience and boost productivity.
  • 1.0K
  • 15 Jun 2023
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