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Abstract Background Burkholderia sp. strain SJ98 is known for its chemotaxis towards nitroaromatic compounds (NACs) that are either utilized as sole sources of carbon and energy or co-metabolized in the presence of alternative carbon sources. Here we test for the chemotaxis of this strain towards six chloro-nitroaromatic compounds (CNACs), namely 2-chloro-4-nitrophenol (2C4NP), 2-chloro-3-nitrophenol (2C3NP), 4-chloro-2-nitrophenol (4C2NP), 2-chloro-4-nitrobenzoate (2C4NB), 4-chloro-2-nitrobenzoate (4C2NB) and 5-chloro-2-nitrobenzoate (5C2NB), and examine its relationship to the degradation of such compounds. Results Strain SJ98 could mineralize 2C4NP, 4C2NB and 5C2NB, and co-metabolically transform 2C3NP and 2C4NB in the presence of an alternative carbon source, but was unable to transform 4C2NP under these conditions. Positive chemotaxis was only observed towards the five metabolically transformed CNACs. Moreover, the chemotaxis was induced by growth in the presence of the metabolisable CNAC. It was also competitively inhibited by the presence of nitroaromatic compounds (NACs) that it could metabolise but not by succinate or aspartate. Conclusions Burkholderia sp. strain SJ98 exhibits metabolic transformation of, and inducible chemotaxis towards CNACs. Its chemotactic responses towards these compounds are related to its previously demonstrated chemotaxis towards NACs that it can metabolise, but it is independently inducible from its chemotaxis towards succinate or aspartate.

Mycotoxin contamination of foods is a major concern for food safety and public health worldwide. The contamination of agricultural commodities employed by humankind with mycotoxins (toxic secondary metabolites of fungi) is a major risk to the health of the human population. Common methods for mycotoxin detection include chromatographic separation, often combined with mass spectrometry (accurate but time-consuming to prepare the sample and requiring skilled technicians). Artificial intelligence (AI) has been introduced as a new technique for mycotoxin detection in food, providing high credibility and accuracy. This review article provides an overview of recent studies on the use of AI methods for the discovery of mycotoxins in food. The new approach demonstrated that a variety of AI technologies could be correlated. Deep learning models, machine learning algorithms, and neural networks were implemented to analyze elaborate datasets from different analytical platforms. In addition, this review focuses on the advancement of AI to work concomitantly with smart sensing technologies or other non-conventional techniques such as spectroscopy, biosensors, and imaging techniques for rapid and less damaging mycotoxin detection. We question the requirement for large and diverse datasets to train AI models, discuss the standardization of analytical methodologies, and discuss avenues for regulatory approval of AI-based approaches, among other top-of-mind issues in this domain. In addition, this research provides some interesting use cases and real commercial applications where AI has been able to outperform other traditional methods in terms of sensitivity, specificity, and time required. This review aims to provide insights for future directions in AI-enabled mycotoxin detection by incorporating the latest research results and stressing the necessity of multidisciplinary collaboration among food scientists, engineers, and computer scientists. Ultimately, the use of AI could revolutionize systems monitoring mycotoxins, improving food safety and safeguarding global public health. [ABSTRACT FROM AUTHOR]

To reveal potent ACE inhibitors, researchers screen various bioactive peptides from several sources, and more attention has been given to aquatic sources. This review summarizes the recent research achievements on marine peptides with ACE-inhibitory action and application. Marine peptides are considered excellent bioactives due to their large structural diversity and unusual bioactivities. The mechanisms by which these marine peptides inhibit ACE include competitive binding to ACEs' active site, interfering with ACE conformational changes, and avoiding the identification of substrates. The unique 3D attributes of marine peptides confer inhibition advantages toward ACE activity. Because IC50 values of marine peptides' interaction with ACE are low, structure-based research assumes that the interaction between ACE and peptides increased the therapeutic application. Numerous studies on marine peptides focused on the sustainable extraction of ACE-inhibitory peptides produced from several fish, mollusks, algae, and sponges. Meanwhile, their potential applications and medical benefits are worth investigating and considering. Due to these peptides exhibiting antioxidant, antihypertensive, and even antimicrobial properties simultaneously, their therapeutic potential for cardiovascular disease and other illnesses only increases. In addition, as marine peptides show better pharmacological benefits, they have increased absorption rates and low toxicity and could perhaps be modified for better stability and bioefficacy. Biotechnological advances in peptide synthesis and formulation have greatly facilitated the generation of peptide-based ACE inhibitors from marine sources, which subsequently offer new treatment models. This article gives a complete assessment of the present state of knowledge about marine organism peptides as ACE inhibitors. In addition, it emphasizes the relevance of additional investigation into their mechanisms of action, the optimization of manufacturing processes, and assessment in in vivo, preclinical, and clinical settings, underlining the urgency and value of this study. Using marine peptides for ACE inhibition not only broadens the repertory of bioactive compounds but also shows promise for tackling the global health burden caused by cardiovascular diseases. [ABSTRACT FROM AUTHOR]

Pseudomonas aeruginosa can efficiently adapt to changing environmental conditions due to its ubiquitous nature, intrinsic/acquired/adaptive resistance mechanisms, high metabolic versatility, and the production of numerous virulence factors. As a result, P. aeruginosa becomes an opportunistic pathogen, causing chronic infection in the lungs and several organs of patients suffering from cystic fibrosis. Biofilm established by P. aeruginosa in host tissues and medical device surfaces has been identified as a major obstruction to antimicrobial therapy. P. aeruginosa is very likely to be closely associated with the various microorganisms in the host tissues or organs in a pathogenic or nonpathogenic behavior. Aside from host-derived molecules, other beneficial and pathogenic microorganisms produce a diverse range of secondary metabolites that either directly or indirectly favor the persistence of P. aeruginosa. Thus, it is critical to understand how P. aeruginosa interacts with different molecules and ions in the host and abiotic environment to produce extracellular polymeric substances and virulence factors. Thus, the current review discusses how various natural and synthetic molecules in the environment induce biofilm formation and the production of multiple virulence factors. [ABSTRACT FROM AUTHOR]

Copper magnesium tin sulfide (CMTS) is a multifunctional material that has recently generated a lot of interest as a potential new photocatalyst for organic pollutant degradation. Some of the desirable characteristics of CMTS are its narrow band gap energy, good chemical and photochemical stability, and high relative abundance of its constituent elements. In this work, CMTS (with the empirical formula Cu0.5Mg2.5SnS4) and type-II heterojunction CdS@CMTS composites with varying CdS contents have been synthesized using a cost-effective and energy-efficient microwave-assisted method. X-ray diffraction analysis confirmed the presence of kesterite CMTS and hexagonal CdS in the composites. After the addition of CdS, the effective band gap energy of CMTS increased from 2.07 to 2.40 eV. The composites exhibited a uniform distribution of CdS on the CMTS surface. Photocatalytic studies reveal that CdS@CMTS exhibits higher photocatalytic activity for the degradation of brilliant green (BG) dye under visible light irradiation in comparison to pristine CMTS. Among the synthesized materials, the 30% CdS@CMTS exhibited the highest photocatalytic activity, with up to 95.8 ± 1.45% degradation of BG within 5 h. Thus, CdS@CMTS prepared by microwave-assisted synthesis has shown potential to degrade organic pollutants for wastewater remediation. [ABSTRACT FROM AUTHOR]

The growing threat of antimicrobial-resistant (AMR) pathogens to human health worldwide emphasizes the need for more effective infection control strategies. Bacterial and fungal biofilms pose a major challenge in treating AMR pathogen infections. Biofilms are formed by pathogenic microbes encased in extracellular polymeric substances to confer protection from antimicrobials and the host immune system. Biofilms also promote the growth of antibiotic-resistant mutants and latent persister cells and thus complicate therapeutic approaches. Biofilms are ubiquitous and cause serious health risks due to their ability to colonize various surfaces, including human tissues, medical devices, and food-processing equipment. Detection and characterization of biofilms are crucial for prompt intervention and infection control. To this end, traditional approaches are often effective, yet they fail to identify the microbial species inside biofilms. Recent advances in artificial intelligence (AI) have provided new avenues to improve biofilm identification. Machine-learning algorithms and image-processing techniques have shown promise for the accurate and efficient detection of biofilm-forming microorganisms on biotic and abiotic surfaces. These advancements have the potential to transform biofilm research and clinical practice by allowing faster diagnosis and more tailored therapy. This comprehensive review focuses on the application of AI techniques for the identification of biofilm-forming pathogens in various industries, including healthcare, food safety, and agriculture. The review discusses the existing approaches, challenges, and potential applications of AI in biofilm research, with a particular focus on the role of AI in improving diagnostic capacities and guiding preventative actions. The synthesis of the current knowledge and future directions, as described in this review, will guide future research and development efforts in combating biofilm-associated infections. [ABSTRACT FROM AUTHOR]

Molybdenum sulfide (MoS2) and modified MoS2 with different percentages of CdS (10%, 30%, and 50% CdS@MoS2) were successfully synthesized and characterized. The photocatalytic performance of the MoS2 and CdS@MoS2 was evaluated by degrading brilliant green (BG), methylene blue (MB), and rhodamine B (RhB) dyes under visible light irradiation. Amongst the synthesized photocatalysts, 50% CdS@MoS2 exhibited the highest photocatalytic activity, degrading 97.6%, 90.3%, and 75.5% of BG, MB, and RhB dyes, respectively within 5 h. The active species involved in the degradation processes were investigated. All trapping agents inhibited BG and MB degradation to a similar extent, indicating that all of the probed active species play an important role in the degradation of BG and MB. In contrast, h+ and O2•− were found to be the main reactive species in the photocatalytic RhB degradation. A potential mechanism for the photocatalytic degradation of dyes using CdS@MoS2 has been proposed. This work highlights the potential of CdS@MoS2 as a photocatalyst for more efficient water remediation applications. [ABSTRACT FROM AUTHOR]