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This research introduces a fractional high-order sliding mode control (FHOSMC) method that utilises an inverse integral fractional order, 0 < β < 1 , as the high order on the FHOSMC reaching law, exhibiting a novel contribution in the related field of study. The application of the proposed approach into a bioreactor system via diffeomorphism operations demonstrates a notable improvement in the management of the bioreactor dynamics versus classic controllers. The numerical findings highlight an improved precision in tracking reference signals and an enhanced plant stability compared to proportional–integral–derivative (PID) controller implementations within challenging disturbance scenarios. The FHOSMC effectively maintains the biomass concentration at desired levels, reducing the wear of the system as well as implementation expenses. Furthermore, the theoretical analysis of the convergence within time indicates substantial potential for further enhancements. Subsequent studies might focus on extending this control approach to bioreactor systems that integrate sensor technologies and the formulation of adaptive algorithms for real-time adjustments of β -type fractional-orders. [ABSTRACT FROM AUTHOR]

As photosynthetic microorganisms, cyanobacteria play a dominant part in numerous ecological systems owing to their ability to fix carbon and nitrogen and are therefore an essential part of primary production in both aquatic and terrestrial environments. The utility of nitrogen-fixing cyanobacteria in plant biotechnology opens up promising strategies for the conservation and sustainable use of rare, endangered plant species and bioactive cell cultures. Here, we discuss the complicated physiological aspects of biological nitrogen fixation in cyanobacteria and their symbiotic relationship with plants. This review focuses on recent advances in biotechnological tools such as CRISPR-Cas9, nanotechnology and multiomics-based approaches for enhancing plant regeneration systems to cultivate specialized metabolites. We also look at the methods in vitro preservation of plants and how to scale up a culture using bioreactor systems. The review ends by highlighting the promise of cyanobacteria-powered plant biotechnology as a renewable mechanism for rare species conservation and specialized metabolites production, providing an optimistic modal, formative future direction in plant biosynthesis.

The editorial discusses the advancements in cell therapy, focusing on diverse cell types, induction methods, and culture techniques that are driving the potential of cell-based therapies. Key topics include the use of 3D organoid cultures for liver diseases, refining CAR-T cell therapies for cancer treatment, and exploring the potential of CAR-macrophages for solid tumor treatment. The editorial highlights the importance of gene editing, bioprocessing technologies, and optimizing cell delivery methods for the successful translation of cell therapies into clinical practice. Despite challenges, interdisciplinary collaboration is key to developing personalized and effective cell-based treatments for various diseases. [Extracted from the article]

This research introduces a fractional high-order sliding mode control (FHOSMC) method that utilises an inverse integral fractional order, 0<β<1, as the high order on the FHOSMC reaching law, exhibiting a novel contribution in the related field of study. The application of the proposed approach into a bioreactor system via diffeomorphism operations demonstrates a notable improvement in the management of the bioreactor dynamics versus classic controllers. The numerical findings highlight an improved precision in tracking reference signals and an enhanced plant stability compared to proportional–integral–derivative (PID) controller implementations within challenging disturbance scenarios. The FHOSMC effectively maintains the biomass concentration at desired levels, reducing the wear of the system as well as implementation expenses. Furthermore, the theoretical analysis of the convergence within time indicates substantial potential for further enhancements. Subsequent studies might focus on extending this control approach to bioreactor systems that integrate sensor technologies and the formulation of adaptive algorithms for real-time adjustments of β-type fractional-orders.

Hemi-pyocyanin (HPC) is a heterocyclic nitrogenous compound with some reported potential medical effects. The current report aimed to investigate the potential use of organic industrial waste for the production of HPC via microbial fermentation. The novel antidiabetic activity of HPC was also accessed and reported in this work. A peanut oil processing by-product (groundnut cake) was screened as the best substrate for Pseudomonas aeruginosa TUN03 conversion to obtain high-yield HPC. This compound was further produced in a 14 L bioreactor system on a large scale (6 L per pilot) and reached higher productivity (35.1 μg/mL) in a shorter time course of cultivation (8 h) compared to fermentation on a small scale in flasks (19.5 μg/mL; 3 days of fermentation). On assessing its activity, HPC demonstrated potent inhibition against α-glucosidase, an antidiabetic enzyme, with a low IC50 value (0.572 mg/mL) and a maximum inhibition rate of 100%. In an in silico study, HPC was found to inhibit α-glucosidase with a good binding energy score (−9.0 kcal/mol) via interaction with amino acids Lys156, Leu313, and Arg315 at the active site, and three bonds (1 H-acceptor and 2 pi-H) were generated. The data from five Lipkin's rules and ADMET-based pharmacokinetics and pharmacology revealed that HPC possesses drug-like properties and good ADMET properties within the required allotted limitations. The data obtained in the current work highlighted the potential application of groundnut cakes for the eco-friendly and scaled-up production of HPC, a new anti-α-glucosidase agent that should be further investigated for type 2 diabetes management. [ABSTRACT FROM AUTHOR]

This review provides a summary of the most recent advancements in bioreactor systems, which have become more popular over the past few decades due to the outstanding qualities they offer for the creation of plant tissue and organ cultures in the laboratory as well as on a large scale. It provides a comprehensive discussion on the application of bioreactor systems in fruit cultivation as well as current research. This review presents a solution for researchers who are interested in the cultivation of diverse fruit species, as well as describes the methods that are used in the bioreactor system to propagate various fruit species. [ABSTRACT FROM AUTHOR]

Biological nitrogen removal (BNR) technologies are the most effective approaches for the remediation of environmental nitrogen pollutants from wastewater treatment plants (WWTPs). Presently, research is going on to elucidate the structure and function of BNR microbial communities and optimizing BNR treatment systems to enhance nitrogen removal efficiency. The literature on BNR microbial communities and experimental datasets is not unified across various repositories, while a uniform resource for the collection, annotation, and structuring of these BNR datasets is still unavailable. Herein, we present the Biological Nitrogen Removal Database (BNRdb), an integrated resource containing various manually curated BNR-related data. At present, BNRdb contains 23,308 microbial strains, 46 gene families, 24 enzymes, 18 reactions, 301 BNR treatment datasets, 860 BNR-associated next-generation sequencing datasets, and 6 common BNR bioreactor systems. BNRdb provides a user-friendly interface enabling interactive data browsing. To our knowledge, BNRdb is the first BNR data resource that systematically integrates BNR data from archaeal, bacterial, and fungal communities. We believe that BNRdb will contribute to a better understanding of BNR process and nitrogen bioremediation research.

Biological nitrogen removal (BNR) technologies are the most effective approaches for the remediation of environmental nitrogen pollutants from wastewater treatment plants (WWTPs). Presently, research is going on to elucidate the structure and function of BNR microbial communities and optimizing BNR treatment systems to enhance nitrogen removal efficiency. The literature on BNR microbial communities and experimental datasets is not unified across various repositories, while a uniform resource for the collection, annotation, and structuring of these BNR datasets is still unavailable. Herein, we present the Biological Nitrogen Removal Database (BNRdb), an integrated resource containing various manually curated BNR-related data. At present, BNRdb contains 23,308 microbial strains, 46 gene families, 24 enzymes, 18 reactions, 301 BNR treatment datasets, 860 BNR-associated next-generation sequencing datasets, and 6 common BNR bioreactor systems. BNRdb provides a user-friendly interface enabling interactive data browsing. To our knowledge, BNRdb is the first BNR data resource that systematically integrates BNR data from archaeal, bacterial, and fungal communities. We believe that BNRdb will contribute to a better understanding of BNR process and nitrogen bioremediation research. [ABSTRACT FROM AUTHOR]