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In this paper, the flocculation and dye recovery potential of a cationic dye, C.I. Basic Blue 41 (BB41), were explored using a natural, fungus-derived flocculant. The influence of various factors on the flocculation, characterization before and after flocculation, as well as adsorption kinetics were investigated. It was observed that an initial pH of 4, without any pH adjustment, favored flocculation, resulting in over 80% decolorization efficiency, whereas a pH of 2 was found to be unfavorable. Because of this acidic-pH responsive property, dyestuffs can be regenerated at pH 2 with a dye recovery efficiency exceeding 60%. The concentration increased by over 3 times when the regeneration occurred in one-tenth of its original volume. Scanning electron microscope (SEM) morphological analysis observed that the dye particles accumulated on the surface of the flocculant. The adsorption process fitted a pseudo-second-order kinetics model. Fourier transform infrared (FTIR) analysis suggested that amide, amine, and hydroxyl groups played important roles in flocculation. These findings were further confirmed with two other textile cationic dyes, C.I. Basic Red 29 (BR29) and C.I. Basic Blue 54 (BB54), both of which exhibited excellent flocculation performance, achieving nearly 100% decolorization efficiency and approximately 40% recovery efficiency. These results suggest that the flocculant used in this study has the potential not only to remediate dyestuffs from textile wastewater but also to recover dyestuffs in a simple manner.

Digital franchising is increasingly recognized as a technological advancement and a specialized subset of e-commerce, yet its unique entrepreneurial dynamics remain insufficiently explored in the existing literature. Previous studies have primarily focused on platform usability or general e-commerce adoption, often overlooking the motivational, contextual, and capability-based factors that influence individuals’ willingness to engage in digital franchising as either entrepreneurs or consumers. To address this research gap, the present study applies the Motivation-Opportunity-Ability (MOA) framework to examine how personal motivations (e.g., self-expression, financial rewards), perceived platform opportunities (e.g., support, attractiveness), and individual capabilities (e.g., digital literacy, self-efficacy) shape entrepreneurial intention and, in turn, influence consumption adoption intention in digital franchising environments. An online survey was conducted using a non-probability purposive sampling method. The final sample consisted of 491 respondents from Taiwan, all of whom were either entrepreneurs operating digital franchises in the fashion industry or consumers who had purchased fashion products through digital franchising platforms, thereby ensuring contextual relevance to the study’s focus. Data were analyzed using structural equation modeling (SEM). The results indicate that expected external rewards (β = 0.456, p < 0.001) and platform support (β = 0.315, p < 0.001) are the most influential factors in shaping entrepreneurial intention. Furthermore, entrepreneurial intention significantly mediates the relationship between MOA antecedents and consumption adoption intention (β = 0.176, p < 0.001), highlighting its role as a key behavioral mechanism. These findings extend the MOA framework to a new empirical setting and offer practical implications for platform developers, franchisors, and policymakers seeking to promote participation in digital franchising. Future research is encouraged to explore cross-industry comparisons, generational differences, and longitudinal approaches to further enrich the understanding of digital franchising adoption dynamics.

There is a special node, which the large noise of the upstream element may not always lead to a broad distribution of downstream elements. This node is DNA, with upstream element TF and downstream elements mRNA and proteins. By applying the stochastic simulation algorithm (SSA) on gene circuits inspired by the fim operon in Escherichia coli , we found that cells exchanged the distribution of the upstream transcription factor (TF) for the transitional frequency of DNA. Then cells do an inverse transform, which exchanges the transitional frequency of DNA for the distribution of downstream products. Due to this special feature, DNA in the system of frequency modulation is able to reset the noise. By probability generating function, we know the ranges of parameter values that grant such an interesting phenomenon.

Because of the small particle number of intracellular species participating in genetic circuits, stochastic fluctuations are inevitable. This intracellular noise is detrimental to precise regulation. To maintain the proper function of a cell, some natural motifs attenuate the noise at the protein level. In many biological systems, the protein monomer is used as a regulator, but the protein dimer also exists. In the present study, we demonstrated that the dimerization reaction reduces the noise intensity of the protein monomer. Compared with two common noise-buffering motifs, the incoherent feedforward loop (FFL) and negative feedback control, the coefficient of variation (COV) in the case of dimerization was 25% less. Furthermore, we examined a system with direct interaction between proteins and other ligands. Both the incoherent FFL and negative feedback control failed to buffer the noise, but the dimerization was effective. Remarkably, the formation of only one protein dimer was sufficient to cause a 7.5% reduction in the COV.

Conjugation is one of the most common ways bacteria acquire antibiotic resistance, contributing to the emergence of multidrugresistant \"superbugs.\" Bacteria of the genus Enterococcus faecalis are highly antibiotic-resistant nosocomial pathogens that use the mechanism of conjugation to spread antibiotic resistance between resistance-bearing donor cells and resistance-deficient recipient cells. Here, we report a unique quorum sensing-based communication system that uses two antagonistic signaling molecules to regulate conjugative transfer of tetracycline-resistance plasmid pCF10 in E. faecalis. A \"mate-sensing\" peptide sex pheromone produced by recipient cells is detected by donor cells to induce conjugative genetic transfer. Using mathematical modeling and experimentation, we show that a second antagonistic \"self-sensing\" signaling peptide, previously known to suppress self-induction of donor cells, also serves as a classic quorum-sensing signal for donors that functions to reduce antibiotic-resistance transfer at high donor density. This unique form of quorum sensing may provide a means of limiting the spread of the plasmid and present opportunities to control antibiotic-resistance transfer through manipulation of intercellular signaling, with implications in the clinical setting.

The stochastic nature of gene regulatory networks described by Chemical Master Equation (CME) leads to the distribution of proteins. A deterministic bistability is usually reflected as a bimodal distribution in stochastic simulations. Within a certain range of the parameter space, a bistable system exhibits two stable steady states, one at the low end and the other at the high end. Consequently, it appears to have a bimodal distribution with one sub-population (mode) around the low end and the other around the high end. In most cases, only one mode is favorable, and guiding cells to the desired state is valuable. Traditionally, the population was redistributed simply by adjusting the concentration of the inducer or the stimulator. However, this method has limitations; for example, the addition of stimulator cannot drive cells to the desired state in a common bistable system studied in this work. In fact, it pushes cells only to the undesired state. In addition, it causes a position shift of the modes, and this shift could be as large as the value of the mode itself. Such a side effect might damage coordination, and this problem can be avoided by applying a new method presented in this work. We illustrated how to manipulate the intensity of internal noise by using biologically practicable methods and utilized it to prompt the population to the desired mode. As we kept the deterministic behavior untouched, the aforementioned drawback was overcome. Remarkably, more than 96% of cells has been driven to the desired state. This method is genetically applicable to biological systems exhibiting a bimodal distribution resulting from bistability. Moreover, the reaction network studied in this work can easily be extended and applied to many other systems.

Convergent gene pairs with head-to-head configurations are widespread in both eukaryotic and prokaryotic genomes and are speculated to be involved in gene regulation. Here we present a unique mechanism of gene regulation due to convergent transcription from the antagonistic prgX/prgQ operon in Enterococcus faecalis controlling conjugative transfer of the antibiotic resistance plasmid pCF10 from donor cells to recipient cells. Using mathematical modeling and experimentation, we demonstrate that convergent transcription in the prgX/prgQ operon endows the system with the properties of a robust genetic switch through premature termination of elongating transcripts due to collisions between RNA polymerases (RNAPs) transcribing from opposite directions and antisense regulation between complementary counter-transcripts. Evidence is provided for the presence of truncated RNAs resulting from convergent transcription from both the promoters that are capable of sense-antisense interactions. A mathematical model predicts that both RNAP collision and antisense regulation are essential for a robust bistable switch behavior in the control of conjugation initiation by prgX/prgQ operons. Moreover, given that convergent transcription is conserved across species, the mechanism of coupling RNAP collision and antisense interaction is likely to have a significant regulatory role in gene expression.

There is increasing recognition that stochasticity involved in gene regulatory processes may help cells enhance the signal or synchronize expression for a group of genes. Thus the validity of the traditional deterministic approach to modeling the foregoing processes cannot be without exception. In this study, we identify a frequently encountered situation, i.e., the biofilm, which has in the past been persistently investigated with intracellular deterministic models in the literature. We show in this paper circumstances in which use of the intracellular deterministic model appears distinctly inappropriate. In Enterococcus faecalis, the horizontal gene transfer of plasmid spreads drug resistance. The induction of conjugation in planktonic and biofilm circumstances is examined here with stochastic as well as deterministic models. The stochastic model is formulated with the Chemical Master Equation (CME) for planktonic cells and Reaction-Diffusion Master Equation (RDME) for biofilm. The results show that although the deterministic model works well for the perfectly-mixed planktonic circumstance, it fails to predict the averaged behavior in the biofilm, a behavior that has come to be known as stochastic focusing. A notable finding from this work is that the interception of antagonistic feedback loops to signaling, accentuates stochastic focusing. Moreover, interestingly, increasing particle number of a control variable could lead to an even larger deviation. Intracellular stochasticity plays an important role in biofilm and we surmise by implications from the model, that cell populations may use it to minimize the influence from environmental fluctuation.

The cellular behaviors under the control of genetic circuits are subject to stochastic fluctuations, or noise. The stochasticity in gene regulation, far from a nuisance, has been gradually appreciated for its unusual function in cellular activities. In this work, with Chemical Master Equation (CME), we discovered that the addition of inhibitors altered the stochasticity of regulatory proteins. For a bistable system of a mutually inhibitory network, such a change of noise led to the migration of cells in the bimodal distribution. We proposed that the consumption of regulatory protein caused by the addition of inhibitor is not the only reason for pushing cells to the specific state; the change of the intracellular stochasticity is also the main cause for the redistribution. For the level of the inhibitor capable of driving 99% of cells, if there is no consumption of regulatory protein, 88% of cells were guided to the specific state. It implied that cells were pushed, by the inhibitor, to the specific state due to the change of stochasticity.

Biological control is an effective and environmentally friendly strategy for managing plant diseases. In this study, a broad-spectrum antagonistic bacterium, designated strain AN6, was isolated from rice plants and exhibited potent inhibitory activity against a variety of phytopathogens. In Oxford cup assays, AN6 suppressed the growth of Xanthomonas oryzae pv. oryzae (Xoo) by 73.60%, and its cell-free culture filtrate caused pronounced morphological deformation in the bacterial cells. Further in vitro assays, including dual-culture assays, volatile organic compound (VOC) assays, and cell-free supernatant (CFS) assays, demonstrated that AN6 also exerted strong antifungal effects against several pathogenic fungi. In addition, the strain was found to produce proteases and siderophores, which may contribute to its antagonistic capabilities. Taxonomic identification based on morphological traits, 16S rRNA and gyrA gene sequencing, average nucleotide identity (ANI), in silico DNA–DNA hybridization (isDDH), and phylogenetic analysis classified strain AN6 as Bacillus velezensis. Whole-genome sequencing revealed that AN6 harbors a 3,929,788 bp genome comprising 4025 protein-coding genes with a GC content of 46.50%. Thirteen biosynthetic gene clusters (BGCs) associated with the production of secondary metabolites—such as nonribosomal peptides, polyketides, and dipeptide antibiotics—were identified. The pot experiment further validated the biocontrol potential of AN6, achieving an 80.49% reduction in rice bacterial blight caused by Xanthomonas oryzae pv. oryzae. Collectively, these results indicate that B. velezensis AN6 is a promising candidate for development as a highly effective biocontrol agent for the integrated management of diverse plant diseases.