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IntroductionRhizosphere bacterial communities play a crucial role in promoting plant and soil ecosystem health and productivity. They also have great potential as key indicators of soil health in agroecosystems. Various environmental factors affect soil parameters, which have been demonstrated to influence soil microbial growth and activities. Thus, this study investigated how rhizosphere bacterial community structure and functions are affected by agronomic practices such as organic and conventional fertiliser application and plant species types.MethodsRhizosphere soil of vegetable crops cultivated under organic and conventional fertilisers in different farms was analysed using high-throughput sequencing of the 16S rRNA gene and co-occurrence network pattern among bacterial species. The functional structure was analysed with PICRUSt2 pipeline.ResultsOverall, rhizosphere bacterial communities varied in response to fertiliser type, with soil physicochemical parameters, including NH4, PO4, pH and moisture content largely driving the variations across the farms. Organic farms had a higher diversity richness and more unique amplicon sequence variants than conventional farms. Bacterial community structure in multivariate space was highly differentiated across the farms and between organic and conventional farms. Co-occurrence network patterns showed community segmentation for both farms, with keystone taxa more prevalent in organic than conventional farms.DiscussionModule hub composition and identity varied, signifying differences in keystone taxa across the farms and positive correlations between changes in microbial composition and ecosystem functions. The organic farms comprised functionally versatile communities characterised by plant growth-promoting keystone genera, such as Agromyces, Bacillus and Nocardioides. The results revealed that organic fertilisers support high functional diversity and stronger interactions within the rhizosphere bacterial community. This study provided useful information about the overall changes in soil microbial dynamics and how the changes influence ecosystem functioning under different soil nutrient management and agronomic practices.

Abstract Aloe species are often used interchangeably for medicinal and cosmeceutical applications, presenting a challenge to the biological efficacy consistency of some herbal preparations. Sustainable production of high-quality commonly used medicinal plants remains a limitation for commercialisation. Thus, this study investigated the potential for plant substitution by examining bacterial endophytes capable of producing similar host plant secondary metabolites. The metabolite profiles and endophytic bacterial communities of endangered Aloe lettyae were compared with those of Aloe longibracteata using nuclear magnetic resonance spectroscopy and 16 S rRNA gene sequencing. Only 15 metabolites were significantly different between A. lettyae and A. longibracteata based on metabolite concentrations. However, both plants’ functionality and potential application remain comparable. Phytohormones, including indole-3-acetate and 5-hydroxyindole-3-acetate, were more concentrated in A. lettyae than A. longibracteata. Metabolites such as tyrosine, allantoin, and myo-inositol, with human health benefits, were annotated in both species. Aloe lettyae harboured a phylogenetically diverse bacteria community compared to A. longibracteata, with a higher richness of bacterial species, indicating a likelihood of diverse metabolic capabilities among the bacteria. Dominant endophytes, including Bacillus, Comamonas, and Pseudomonas, possess enzymes contributing to various metabolic pathways. The enzymes have the potential to impact the synthesis, or breakdown of plant metabolites, consequently influencing the overall metabolic composition of the host plant. Therefore, this study supports the interchangeability of A. lettyae and A. longibracteata due to their ability to produce similar metabolites, and although the Aloe species exhibit phylogenetically diverse endophytic communities, the feasibility of utilizing their endophytes as producers of secondary metabolites remains viable. Graphical abstract

Cancer poses a significant global health challenge, with 10 million deaths and 19.3 million new cases reported annually. This review aims to investigate the emerging field of synbiotics and their potential to enhance the effectiveness of cancer therapies. By conducting a thorough analysis of preclinical and clinical studies, this review clarifies the various mechanisms through which synbiotics improve the efficacy of conventional cancer treatments, such as chemotherapy, immunotherapy, surgery, and radiotherapy. A search of literature on the anti-cancer efficacy of synbiotics was performed using the PubMed database and Google Scholar search engine to find important original research and review publications. A selection, analysis, and discussion of related English-language papers were conducted. This review unravels the intricate connections between microbiota and cancer therapeutics, harnessing the power of synbiotics as a promising strategy to improve treatment outcomes and elevate the standard of care in oncology. Further research is required to establish the efficacy and long-term safety of synbiotics, the ideal prebiotic-probiotic combinations, and the distinct microbiota signatures of different cancer types for the development of future synbiotics.

Dynamic multi-objective optimization problems (DMOPs) are optimization problems where elements of the problems, such as the objective functions and/or constraints, change with time. These problems are characterized by two or more objective functions, where at least two objective functions are in conflict with one another. When solving real-world problems, the incorporation of human decision-makers (DMs)’ preferences or expert knowledge into the optimization process and thereby restricting the search to a specific region of the Pareto-optimal Front (POF) may result in more preferred or suitable solutions. This study proposes approaches that enable DMs to influence the search process with their preferences by reformulating the optimization problems as constrained problems. The subsequent constrained problems are solved using various constraint handling approaches, such as the penalization of infeasible solutions and the restriction of the search to the feasible region of the search space. The proposed constraint handling approaches are compared by incorporating the approaches into a differential evolution (DE) algorithm and measuring the algorithm’s performance using both standard performance measures for dynamic multi-objective optimization (DMOO), as well as newly proposed measures for constrained DMOPs. The new measures indicate how well an algorithm was able to find solutions in the objective space that best reflect the DM’s preferences and the Pareto-optimality goal of dynamic multi-objective optimization algorithms (DMOAs). The results indicate that the constraint handling approaches are effective in finding Pareto-optimal solutions that satisfy the preference constraints of a DM.

Background: . Up to 20% of people with HIV (PWH) who undergo virologically suppressed antiretroviral therapy (ART) fail to experience complete immune restoration. We recently reported that plasma anti-CD4 IgG (antiCD4IgG) autoantibodies from immune non-responders specifically deplete CD4 + T cells via antibody-dependent cytotoxicity. However, the mechanism of antiCD4IgG production remains unclear., Methods: . Blood samples were collected from 16 healthy individuals and 25 PWH on suppressive ART. IgG subclass, plasma lipopolysaccharide (LPS), and antiCD4IgG levels were measured by ELISA. Gene profiles in B cells were analyzed by microarray and quantitative PCR. Furthermore, a patient-derived antiCD4IgG-producing B cell line was generated and stimulated with LPS in vitro. B cell IgG class switch recombination (CSR) was evaluated in response to LPS in splenic B cells from C57/B6 mice in vitro., Results: . Increased plasma anti-CD4 IgGs in PWH were predominantly IgG1 and associated with increased plasma LPS levels as well as B cell expression of TLR2, TLR4, and MyD88 mRNA in vivo. Furthermore, LPS stimulation induced antiCD4IgG production in the antiCD4IgG B cell line in vitro. Finally, LPS promoted CSR in vitro., Conclusion: . Our findings suggest that persistent LPS translocation may promote anti-CD4 autoreactive B cell activation and antiCD4IgG production in PWH on ART, which may contribute to gradual CD4 + T cell depletion. This study suggests that reversing a compromised mucosal barrier could improve ART outcomes in PWH who fail to experience complete immune restoration., (© 2023. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)

Coronavirus disease 2019 (COVID-19) is associated with autoimmune features and autoantibody production in a small subset of the population. Pre-existing neutralizing antitype I interferons (IFNs) autoantibodies are related to the severity of COVID-19. Plasma levels of IgG and IgM against 12 viral antigens and 103 self-antigens were evaluated using an antibody protein array in patients with severe/critical or mild/moderate COVID-19 disease and uninfected controls. Patients exhibited increased IgGs against Severe acute respiratory syndrome coronavirus-2 proteins compared to controls, but no difference was observed in the two patient groups. 78% autoreactive IgGs and 93% autoreactive IgMs were increased in patients versus controls. There was no difference in the plasma levels of anti-type I IFN autoantibodies or neutralizing anti-type I IFN activity of plasma samples from the two patient groups. Increased anti-type I IFN IgGs were correlated with higher lymphocyte accounts, suggesting a role of nonpathogenic autoantibodies. Notably, among the 115 antibodies tested, only plasma levels of IgGs against human coronavirus (HCOV)-229E and HCOV-NL63 spike proteins were associated with mild disease outcome. COVID-19 was associated with a bystander polyclonal autoreactive B cell activation, but none of the autoantibody levels were linked to disease severity. Long-term humoral immunity against HCOV-22E and HCOV-NL63 spike protein was associated with mild disease outcome. Understanding the mechanism of life-threatening COVID-19 is critical to reducing mortality and morbidity., (© 2022 Wiley Periodicals LLC.)