Preparation of Fresh-Keeping Paper Using Clove Essential Oil through Pickering Emulsion and Maintaining the Quality of Postharvest Cherry Tomatoes.

This study focused on developing a Pickering emulsion fresh-keeping paper that contained clove essential oil (CEO). Cherry tomatoes served as the test material for assessing the preservative efficacy of fresh-keeping paper. The results showed that Pickering emulsion had strong stability. Additionally, the fresh-keeping paper had a good antioxidant activity and sustained-release effect on CEO. In terms of the preservation effect, 0.75 wt% CEO Pickering emulsion paper reduced the decay incidence and weight loss of cherry tomatoes during 12-day storage. Fresh-keeping paper could also play a positive role in protecting the sensory index and color difference of tomatoes. It slowed the decline rate of soluble solid concentration (SSC) and titrable acid (TA). The vitamin C (Vc) and hardness of preserved tomatoes using fresh-keeping paper were maintained at a high level. The paper also inhibited the growth of microorganisms significantly. Therefore, 0.75 wt% CEO Pickering emulsion fresh-keeping paper displayed considerable potential for application in the preservation of postharvest fruits and vegetables. It is a novel fruit and vegetable preservation material worthy of development.

High-throughput fluorescence quantification method based on inner filter effect and fluorescence imaging analysis.

The application of the inner filter effect (IFE) in fluorescent substance determination is gaining popularity. In this paper, a theory of the fluorescence distribution along with the excitation light path is derived from our previous research about the spatial micro-element method. According to the relationship between the summation of fluorescence intensities along the vertical direction at a certain position on the excitation light path and the position, a high-concentration and wide-range fluorescent substance quantification method based on the IFE and fluorescence imaging analysis is proposed. Correspondingly, a high-throughput fluorescent substance quantification detection system is constructed. In order to validate the method, solutions of rhodamine B in different concentrations are used for principle validation, concentration prediction, and experimental investigation on the influence of integration time and lens distortion. The high-throughput system enables the simultaneous measurement of six samples, realizing the high-concentration and wide-range quantification of rhodamine B (100-600 mg/L) with high precision (R2 = 0.9992, MRE = 2.34 %). By setting the filter wheel, the system can measure the concentration of fluorescent substances with different emission wavelengths. The improvement of experimental device is expected to reduce the single sample capacity to tens of microliters and increase the overall sample quantity to tens or even hundreds. The proposed method and system are beneficial to fluorescence measurement in fields such as biomedicine and dye research and to the improvement of high-throughput fluorescence quantitative PCR instruments.

The Phylogeography of Deciduous Tree Ulmus macrocarpa (Ulmaceae) in Northern China.

Disentangling how climate oscillations and geographical events significantly influence plants' genetic architecture and demographic history is a central topic in phytogeography. The deciduous ancient tree species Ulmus macrocarpa is primarily distributed throughout Northern China and has timber and horticultural value. In the current study, we studied the phylogenic architecture and demographical history of U. macrocarpa using chloroplast DNA with ecological niche modeling. The results indicated that the populations' genetic differentiation coefficient (NST) value was significantly greater than the haplotype frequency (GST) (p < 0.05), suggesting that U. macrocarpa had a clear phylogeographical structure. Phylogenetic inference showed that the putative chloroplast haplotypes could be divided into three groups, in which the group Ⅰ was considered to be ancestral. Despite significant genetic differentiation among these groups, gene flow was detected. The common ancestor of all haplotypes was inferred to originate in the middle-late Miocene, followed by the haplotype overwhelming diversification that occurred in the Quaternary. Combined with demography pattern and ecological niche modeling, we speculated that the surrounding areas of Shanxi and Inner Mongolia were potential refugia for U. macrocarpa during the glacial period in Northern China. Our results illuminated the demography pattern of U. macrocarpa and provided clues and references for further population genetics investigations of precious tree species distributed in Northern China.

Clonal expansion of shared T cell receptors reveals the existence of immune commonality among different lesions of synchronous multiple primary lung cancer.

The increase in the detection rate of synchronous multiple primary lung cancer (MPLC) has posed remarkable clinical challenges due to the limited understanding of its pathogenesis and molecular features. Here, comprehensive comparisons of genomic and immunologic features between MPLC and solitary lung cancer nodule (SN), as well as different lesions of the same patient, were performed. Compared with SN, MPLC displayed a lower rate of EGFR mutation but higher rates of BRAF, MAP2K1, and MTOR mutation, which function exactly in the upstream and downstream of the same signaling pathway. Considerable heterogeneity in T cell receptor (TCR) repertoire exists among not only different patients but also among different lesions of the same patient. Invasive lesions of MPLC exhibited significantly higher TCR diversity and lower TCR expansion than those of SN. Intriguingly, different lesions of the same patient always shared a certain proportion of TCR clonotypes. Significant clonal expansion could be observed in shared TCR clonotypes, particularly in those existing in all lesions of the same patient. In conclusion, this study provided evidences of the distinctive mutational landscape, activation of oncogenic signaling pathways, and TCR repertoire in MPLC as compared with SN. The significant clonal expansion of shared TCR clonotypes demonstrated the existence of immune commonality among different lesions of the same patient and shed new light on the individually tailored precision therapy for MPLC.

Genome-wide identification analysis of the 4-Coumarate: CoA ligase (4CL) gene family expression profiles in Juglans regia and its wild relatives J. Mandshurica resistance and salt stress.

Persian walnut (Juglans regia) and Manchurian walnut (Juglans mandshurica) belong to Juglandaceae, which are vulnerable, temperate deciduous perennial trees with high economical, ecological, and industrial values. 4-Coumarate: CoA ligase (4CL) plays an essential function in plant development, growth, and stress. Walnut production is challenged by diverse stresses, such as salinity, drought, and diseases. However, the characteristics and expression levels of 4CL gene family in Juglans species resistance and under salt stress are unknown. Here, we identified 36 Jr4CL genes and 31 Jm4CL genes, respectively. Based on phylogenetic relationship analysis, all 4CL genes were divided into three branches. WGD was the major duplication mode for 4CLs in two Juglans species. The phylogenic and collinearity analyses showed that the 4CLs were relatively conserved during evolution, but the gene structures varied widely. 4CLs promoter region contained multiply cis-acting elements related to phytohormones and stress responses. We found that Jr4CLs may be participated in the regulation of resistance to anthracnose. The expression level and some physiological of 4CLs were changed significantly after salt treatment. According to qRT-PCR results, positive regulation was found to be the main mode of regulation of 4CL genes after salt stress. Overall, J. mandshurica outperformed J. regia. Therefore, J. mandshurica can be used as a walnut rootstock to improve salt tolerance. Our results provide new understanding the potential functions of 4CL genes in stress tolerance, offer the theoretical genetic basis of walnut varieties adapted to salt stress, and provide an important reference for breeding cultivated walnuts for stress tolerance.

One-step strategy for efficient Cr(VI) removal via phytate modified zero-valent iron: Accelerated electron transfer and enhanced coordination effect.

The toxic Cr(VI) from industrial wastewater pose serious threat to the human beings and eco-systems. To reduce the operation processes and enhance the removal efficiency of Cr(VI), targeted design of functionalized material is critical in practical applications. Herein, we developed a one-step strategy for simultaneous Cr(VI) reduction and total Cr capture by a novel phytate modified zero-valent iron (PA-ZVI). The reaction kinetics of Cr(VI) removal by PA-ZVI (0.2225 min-1) was 53 times higher compared to ZVI (0.0042 min-1). The Fe(0) content on the surface of PA-ZVI increased from 2.2% to 15.6% compared to ZVI. Meanwhile, Cr(VI) was liable to adsorb on the surface of PA-ZVI due to its lower adsorption energy compared with the original ZVI (-2.09 eV vs -0.85 eV). The incorporation of the phytate ligand promoted electron transfer from iron core to Cr(VI), leading to the rapid in-situ reduction of Cr(VI) adsorbed on the surface of PA-ZVI to Cr(III). PA-ZVI exhibited a satisfactory performance for Cr(VI) removal at a broad pH range (3-11) and in the presence of coexisting ions and humic acid. Moreover, the reactor with the addition of PA-ZVI achieved more than 90% Cr(VI) removal within 72 h in continuous flow experiments. The feasibility of PA-ZVI for the removal of Cr(VI) is also validated in authentic wastewater. This work provides novel ZVI materials that can effectively address decontamination challenges from Cr(VI) pollution.

Operator learning for urban water clarification hydrodynamics and particulate matter transport with physics-informed neural networks.

Computational fluid dynamics (CFD) can be a powerful tool for higher-fidelity water infrastructure planning and design. Despite decades of development and demonstration over a wide range of water systems such as clarification basins, activated sludge processes, ozone contactors, etc., CFD remains primarily used in academic research, with limited application in civil and environmental engineering practice. This limitation is contributed by its higher computational cost and demand for specialized user skills. This, however, need not be the case, if a robust and efficient surrogate model can be developed from CFD simulations and independently deployed for engineering purposes. Leveraging the emerging scientific machine learning (ML) techniques of physics-informed ML and operator learning, this study develops a composite neural network (CPNN) for learning the flow hydrodynamics and particulate matter (PM) transport and fate in clarification systems. The CPNN consists of a deep operator network (DeepONet) as an encoder and a physics-informed neural network (PINN) as a decoder. In contrast to common "black box" and lumped ML approaches, the developed CPNN directly incorporates physics principles into its architecture. Furthermore, the CPNN is designed for process-resolved and operator learning, enabling it to predict spatial hydrodynamics and PM concentration distribution (i.e., contours) across different basin geometrics and loading conditions. Compared to CFD simulation, the developed CPNN model has significantly higher computational efficiency (∼ milliseconds) while demonstrating robust predictive capability. For predicting basin hydrodynamics across 10,000 test cases, the trained CPNN model achieves an R2 above 0.8 for 66.4% of cases and an R2 above 0.4 for 89.2% of cases. A similar performance is also demonstrated by the CPNN in predicting basin PM concentration. Further investigation reveals that basin geometrics that trigger bi-modal flow solutions can be particularly challenging for ML. Additionally, this study visualizes the dependency of basin hydrodynamics and PM concentration on basin geometrics and loading conditions, providing valuable insights for optimizing basin configuration. Lastly, the potentials and benefits of web-based applications, e.g., DeepXtorm, as a user-friendly interface for the developed CPNN model is discussed. This study represents the initial step toward achieving real-time higher-fidelity water infrastructure planning, design, optimization, and regulation.

The role of PKP1 in tumor progression in melanoma: Analysis of a cell adhesion-related model.

The incidence rate of melanoma varies across regions, with Europe, the United States, and Australia having 10-25, 20-30, and 50-60 cases per 1 00 000 people. In China, patients with melanoma exhibit different clinical manifestations, pathogenesis, and outcomes. Current treatments include surgery, adjuvant therapy, and immune checkpoint inhibitors. Nonetheless, complications may arise during treatment. Melanoma development is heavily reliant on cell adhesion molecules (CAMs), and studying these molecules could provide new research directions for metastasis and progression. CAMs include the integrin, immunoglobulin, selectin, and cadherin families, and they affect multiple processes, such as maintenance, morphogenesis, and migration of adherens junction. In this study, a cell adhesion-related risk prognostic signature was constructed using bioinformatics methods, and survival analysis was performed. Plakophilin 1 (PKP1) was observed to be crucial to the immune microenvironment and has significant effects on melanoma cell proliferation, migration, invasion, and the cell cycle. This signature demonstrates high reliability and has potential for clinical applications.

Highly efficient adsorption of ciprofloxacin from aqueous solutions by waste cation exchange resin-based activated carbons: Performance, mechanism, and theoretical calculation.

This study focused on the preparation of a highly efficient activated carbon adsorbent from waste cation exchange resins through one-step carbonization to remove ciprofloxacin (CIP) from aqueous solutions. Scanning electron microscopy, X-ray diffraction, Fourier-transform infrared spectrometry, and X-ray photoelectron spectroscopy were used to characterize the physicochemical properties of the carbonized materials. The CIP removal efficiency, influencing factors, and adsorption mechanisms of CIP on the carbonized resins were investigated. Density functional theory (DFT) computations were performed to elucidate the adsorption mechanisms. The CIP removal reached 93 % when the adsorbent dosage was 300 mg/L at 25 °C. The adsorption capacity of the carbonized resins to CIP gradually decreased with an increasing pH from 3.0 to 7.0 and sharply declined with a pH from 7.0 to 11.0. The adsorption process better fitted by the pseudo second-order kinetic and Langmuir models, indicating that the interaction between CIP and the carbonized resins was monolayer adsorption. The maximum adsorption capacity fitted by the Langmuir model was 384.4 mg/g at 25 °C. Microstructural analysis showed that the adsorption of CIP on the carbonized resins was a joint effect of H-bonding, ion exchange, and graphite-N adsorption. Computational results signified the strong H-bonding and ion exchange interactions existed between CIP and carbonized resins. The high adsorption and reusability suggest that waste cation exchange resin-based activated carbons can be used as an effective and reusable adsorbent for removing CIP from aqueous solutions.

Machine Learning-Based Operational State Recognition and Compressive Property Prediction in Fused Filament Fabrication.

3D printing has exhibited significant potential in outer space and medical implants. To use this technology in the specific high-value scenarios, 3D-printed parts need to satisfy quality-related requirements. In this article, the influence of the filament feeder operating states of 3D printer on the compressive properties of 3D-printed parts is studied in the fused filament fabrication process. A machine learning approach, back-propagation neural network with a genetic algorithm (GA-BPNN) optimized by k-fold cross-validation, is proposed to monitor the operating states and predict the compressive properties. Vibration and current sensors are used in situ to monitor the operating states of the filament feeder, and a set of features are extracted and selected from raw sensor data in time and frequency domains. Results show that the operating states of the filament feeder significantly affected the compressive properties of the fabricated samples, the operating states were accurately recognized with 96.3% rate, and compressive properties were successfully predicted by the GA-BPNN. This proposed method has the potential for use in industrial applications after 3D printing without requiring any further quality control.

Decoding functional cell-cell communication events by multi-view graph learning on spatial transcriptomics.

Cell-cell communication events (CEs) are mediated by multiple ligand-receptor (LR) pairs. Usually only a particular subset of CEs directly works for a specific downstream response in a particular microenvironment. We name them as functional communication events (FCEs) of the target responses. Decoding FCE-target gene relations is: important for understanding the mechanisms of many biological processes, but has been intractable due to the mixing of multiple factors and the lack of direct observations. We developed a method HoloNet for decoding FCEs using spatial transcriptomic data by integrating LR pairs, cell-type spatial distribution and downstream gene expression into a deep learning model. We modeled CEs as a multi-view network, developed an attention-based graph learning method to train the model for generating target gene expression with the CE networks, and decoded the FCEs for specific downstream genes by interpreting trained models. We applied HoloNet on three Visium datasets of breast cancer and liver cancer. The results detangled the multiple factors of FCEs by revealing how LR signals and cell types affect specific biological processes, and specified FCE-induced effects in each single cell. We conducted simulation experiments and showed that HoloNet is more reliable on LR prioritization in comparison with existing methods. HoloNet is a powerful tool to illustrate cell-cell communication landscapes and reveal vital FCEs that shape cellular phenotypes. HoloNet is available as a Python package at https://github.com/lhc17/HoloNet.

[Recent Advances and Controversies in Minute Pulmonary Meningothelial-like Nodules].

Minute pulmonary meningothelial-like nodules (MPMNs) are benign small lesions in the lungs, with similar pathological characteristics to the meningeal epithelium. MPMNs have similar imaging manifestations to malignant tumors, which can lead to misdiagnosis in clinical practice. There is no consensus on the pathogenesis of MPMNs, with some suggest that MPMNs derive from reactive proliferation, while others suggest that MPMNs share a common origin and molecular mechanism with meningiomas in the central nervous system. Understanding the characteristics of MPMNs and studying their pathogenesis will help improve the understanding and diagnosis of MPMNs. In this article, we reviewed the clinical, pathological, imaging characteristics, differential diagnosis and pathogenesis of MPMNs. We also analyze the existing research advances regarding the pathogenesis and propose prospects for further research.
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Amphiregulin couples IL1RL1+ regulatory T cells and cancer-associated fibroblasts to impede antitumor immunity.

Regulatory T (Treg) cells and cancer-associated fibroblasts (CAFs) jointly promote tumor immune tolerance and tumorigenesis. The molecular apparatus that drives Treg cell and CAF coordination in the tumor microenvironment (TME) remains elusive. Interleukin 33 (IL-33) has been shown to enhance fibrosis and IL1RL1+ Treg cell accumulation during tumorigenesis and tissue repair. We demonstrated that IL1RL1 signaling in Treg cells greatly dampened the antitumor activity of both IL-33 and PD-1 blockade. Whole tumor single-cell RNA sequencing (scRNA-seq) analysis and blockade experiments revealed that the amphiregulin (AREG)-epidermal growth factor receptor (EGFR) axis mediated cross-talk between IL1RL1+ Treg cells and CAFs. We further demonstrated that the AREG/EGFR axis enables Treg cells to promote a profibrotic and immunosuppressive functional state of CAFs. Moreover, AREG mAbs and IL-33 concertedly inhibited tumor growth. Our study reveals a previously unidentified AREG/EGFR-mediated Treg/CAF coupling that controls the bifurcation of fibroblast functional states and is a critical barrier for cancer immunotherapy.

CRISPR/Cas9­mediated EZH2 knockout suppresses the proliferation and migration of triple­negative breast cancer cells.

Triple-negative breast cancer (TNBC) is an aggressive subtype of BC characterized by extensive intratumoral heterogeneity. Compared with other types of BC, TNBC is more prone to invasion and metastasis. The aim of the present study was to determine whether adenovirus-mediated clustered regulatory interspaced short palindromic repeats (CRISPR)/Cas9 system is capable of effectively targeting enhancer of zeste homolog 2 (EZH2) in TNBC cells and lay an experimental basis for the investigation of the CRISPR/Cas9 system as a gene therapy for BC. In the present study, EZH2 was knocked out in MDA-MB-231 cells using the CRISPR/Cas9 gene editing tool to create EZH2-knockout (KO) group (EZH2-KO group). Moreover, the GFP knockout group (control group), and a blank group (Blank group), were employed. The success of vector construction and EZH2-KO were verified by T7 endonuclease I (T7EI) restriction enzyme digestion, mRNA detection and western blotting. Changes in proliferation and migration ability of MDA-MB-231 cells following gene editing were detected by MTT, wound healing, Transwell and in vivo tumor biology assays. As indicated by the results of mRNA and protein detection, the mRNA and protein expression of EZH2 were significantly downregulated in the EZH2-KO group. The difference in EZH2 mRNA and protein between the EZH2-KO and the two control groups was statistically significant. MTT, wound healing and transwell assay suggested that the proliferation and migration ability of MDA-MB-231 cells in the EZH2-KO group were significantly decreased after EZH2 knockout. In vivo, the tumor growth rate in the EZH2-KO group was significantly lower than that in the control groups. In brief, the present study revealed that the biological functions of tumor cells were inhibited after EZH2 knockout in MDA-MB-231 cells. The aforementioned findings suggested that EZH2 can have a key role in the development of TNBC.

van der Waals Self-Epitaxial Growth of Inch-Sized Superconducting Niobium Diselenide Films.

Ultrathin superconducting films are the basis of superconductor devices. van der Waals (vdW) NbSe2 with noncentrosymmetry exhibits exotic superconductivity and shows promise in superconductor electronic devices. However, the growth of inch-scale NbSe2 films with layer regulation remains a challenge because vdW structural material growth is strongly dependent on the epitaxial guidance of the substrate. Herein, a vdW self-epitaxy strategy is developed to eliminate the substrate driving force in film growth and realize inch-sized NbSe2 film growth with thicknesses from 2.1 to 12.1 nm on arbitrary substrates. The superconducting transition temperature of 5.1 K and superconducting transition width of 0.30 K prove the top homogeneity and quality of superconductivity among all of the synthetic NbSe2 films. Coupled with a large area and substrate compatibility, this work paves the way for developing NbSe2 superconductor electronics.

Topotactic fabrication of transition metal dichalcogenide superconducting nanocircuits.

Superconducting nanocircuits, which are usually fabricated from superconductor films, are the core of superconducting electronic devices. While emerging transition-metal dichalcogenide superconductors (TMDSCs) with exotic properties show promise for exploiting new superconducting mechanisms and applications, their environmental instability leads to a substantial challenge for the nondestructive preparation of TMDSC nanocircuits. Here, we report a universal strategy to fabricate TMDSC nanopatterns via a topotactic conversion method using prepatterned metals as precursors. Typically, robust NbSe2 meandering nanowires can be controllably manufactured on a wafer scale, by which a superconducting nanowire circuit is principally demonstrated toward potential single photon detection. Moreover, versatile superconducting nanocircuits, e.g., periodical circle/triangle hole arrays and spiral nanowires, can be prepared with selected TMD materials (NbS2, TiSe2, or MoTe2). This work provides a generic approach for fabricating nondestructive TMDSC nanocircuits with precise control, which paves the way for the application of TMDSCs in future electronics.

Music with Different Tones Affects the Development of Brain Nerves in Mice in Early Life through BDNF and Its Downstream Pathways.

As a means of environmental enrichment, music environment has positive and beneficial effects on biological neural development. Kunming white mice (61 days old) were randomly divided into the control group (group C), the group of D-tone (group D), the group of A-tone (group A) and the group of G-tone (group G). They were given different tonal music stimulation (group A) for 14 consecutive days (2 h/day) to study the effects of tonal music on the neural development of the hippocampus and prefrontal cortex of mice in early life and its molecular mechanisms. The results showed that the number of neurons in the hippocampus and prefrontal cortex of mice increased, with the cell morphology relatively intact. In addition, the number of dendritic spines and the number of dendritic spines per unit length were significantly higher than those in group C, and the expressions of synaptic plasticity proteins (SYP and PSD95) were also significantly elevated over those in group C. Compared with group C, the expression levels of BDNF, TRKB, CREB, PI3K, AKT, GS3Kß, PLCγ1, PKC, DAG, ERK and MAPK genes and proteins in the hippocampus and prefrontal cortex of mice in the music groups were up-regulated, suggesting that different tones of music could regulate neural development through BDNF and its downstream pathways. The enrichment environment of D-tone music is the most suitable tone for promoting the development of brain nerves in early-life mice. Our study provides a basis for screening the optimal tone of neuroplasticity in early-life mice and for the treatment of neurobiology and neurodegenerative diseases.

One-Click-Based Perception for Interactive Image Segmentation.

Existing deep learning-based interactive image segmentation methods have significantly reduced the user's interaction burden with simple click interactions. However, they still require excessive numbers of clicks to continuously correct the segmentation for satisfactory results. This article explores how to harvest accurate segmentation of interested targets while minimizing the user interaction cost. To achieve the above goal, we propose a one-click-based interactive segmentation approach in this work. For this particularly challenging problem in the interactive segmentation task, we build a top-down framework dividing the original problem into a one-click-based coarse localization followed by a fine segmentation. A two-stage interactive object localization network is first designed, which aims to completely enclose the target of interest based on the supervision of object integrity (OI). Click centrality (CC) is also utilized to overcome the overlapping problem between objects. This coarse localization helps to reduce the search space and increase the focus of the click at a higher resolution. A principled multilayer segmentation network is then designed by a progressive layer-by-layer structure, which aims to accurately perceive the target with extremely limited prior guidance. A diffusion module is also designed to enhance the information flow between layers. Besides, the proposed model can be naturally extended to multiobject segmentation task. Our method achieves the state-of-the-art performance under one-click interaction on several benchmarks.

The Effect of the Microalgae Chlorella vulgaris on the Gut Microbiota of Juvenile Nile Tilapia (Oreochromis niloticus) Is Feeding-Time Dependent.

Chlorella vulgaris is one of the most commonly used microalgae in aquaculture feeds. It contains high concentrations of various kinds of nutritional elements that are involved in the physiological regulation of aquaculture animals. However, few studies have been conducted to illustrate their influence on the gut microbiota in fish. In this work, the gut microbiota of Nile tilapia (Oreochromis niloticus) (average weight is 6.64 g) was analyzed by high-throughput sequencing of the 16S rRNA gene after feeding with 0.5% and 2% C. vulgaris additives in diets for 15 and 30 days (average water temperature was 26 °C). We found that the impact of C. vulgaris on the gut microbiota of Nile tilapia was feeding-time dependent. Only by feeding for 30 days (not 15 days) did the addition of 2% C. vulgaris to diets significantly elevate the alpha diversity (Chao1, Faith pd, Shannon, Simpson, and the number of observed species) of the gut microbiota. Similarly, C. vulgaris exerted a significant effect on the beta diversity (Bray-Curtis similarity) of the gut microbiota after feeding for 30 days (not 15 days). During the 15-day feeding trial, LEfSe analysis showed that Paracoccus, Thiobacillus, Dechloromonas, and Desulfococcus were enriched under 2% C. vulgaris treatment. During the 30-day feeding trial, Afipia, Ochrobactrum, Polymorphum, Albidovulum, Pseudacidovorax, and Thiolamprovum were more abundant in 2% C. vulgaris-treated fish. C. vulgaris promoted the interaction of gut microbiota in juvenile Nile tilapia by increasing the abundance of Reyranella. Moreover, during the feeding time of 15 days, the gut microbes interacted more closely than those during the feeding time of 30 days. This work will be valuable for understanding how C. vulgaris in diets impacts the gut microbiota in fish.