Antagonistic Interactions Research Articles

Multiple‐stressor effects on leaf litter decomposition in freshwater ecosystems: A meta‐analysis

Abstract Recent years have witnessed a surge in research on the effects of multiple stressors in freshwater ecosystems. While studies have increased, the synthesis of their findings into a broader understanding of ecosystem‐level effects remains an ongoing endeavour. Leaf litter decomposition, a frequently investigated and pivotal ecosystem function in freshwaters, is sensitive to changes in abiotic conditions and biotic communities, and therefore susceptible to multiple‐stressor effects. Here, we synthesize findings from 27 manipulative experimental studies encompassing 61 responses of litter decomposition to paired stressors such as warming, nutrient enrichment and emerging pollutants in freshwater ecosystems. We calculated the individual and overall interaction effect sizes resulting from two stressors occurring simultaneously. Furthermore, we analysed the effect of moderator variables in the size and direction of interaction effect sizes using a meta‐analytical approach. Although the vote‐counting method showed additive interactions to dominate individual observations (91.8%), weighted random‐effects meta‐analysis revealed an overall antagonistic interaction between stressors (i.e. the cumulative effect of paired stressors on litter decomposition was less than the sum of their single effects). Our results emphasized the influence of experimental characteristics such as macroinvertebrate involvement, habitat type (lentic vs. lotic) and litter quality (assumed from plant mycorrhizal association) in shaping the responses of litter decomposition to multiple stressors. Our meta‐analysis highlights the need to incorporate local ecological complexities in manipulative experiments to improve predictions of multiple‐stressor effects on biodiversity and ecosystem functions. The present study underscores the importance of considering biotic interactions and adopting the metacommunity framework in conservation and restoration actions to support the management of freshwater ecosystems in an era of rapid global change. Read the free Plain Language Summary for this article on the Journal blog.

Interactions of Nutrition and Infection: The Role of Micronutrient Deficiencies in the Immune Response to Pathogens and Implications for Child Health.

Approximately five million children die each year from preventable causes, including respiratory infections, diarrhea, and malaria. Roughly half of those deaths are attributable to undernutrition, including micronutrient deficiencies (MNDs). The influence of infection on micronutrient status is well established: The inflammatory response to pathogens triggers anorexia, while pathogens and the immune response can both alter nutrient absorption and cause nutrient losses. We review the roles of vitamin A, vitamin D, iron, zinc, and selenium in the immune system, which act in the regulation of molecular- or cellular-level host defenses, directly affecting pathogens or protecting against oxidative stress or inflammation. We further summarize high-quality evidence regarding the synergistic or antagonistic interactions between MNDs, pathogens, and morbidity or mortality relevant to child health in low- and middle-income countries. We conclude with a discussion of gaps in the literature and future directions for multidisciplinary research on the interactions of MNDs, infection, and inflammation.

Sediment DNA Records the Critical Transition of Bacterial Communities in the Arid Lake

It is necessary to predict the critical transition of lake ecosystems due to their abrupt, non-linear effects on social-economic systems. Given the promising application of paleolimnological archives to tracking the historical changes of lake ecosystems, it is speculated that they can also record the lake’s critical transition. We studied Lake Dali-Nor in the arid region of Inner Mongolia because of the profound shrinking the lake experienced between the 1300 s and the 1600 s. We reconstructed the succession of bacterial communities from a 140-cm-long sediment core at 4-cm intervals and detected the critical transition. Our results showed that the historical trajectory of bacterial communities from the 1200 s to the 2010s was divided into two alternative states: state1 from 1200 to 1300 s and state2 from 1400 to 2010s. Furthermore, in the late 1300 s, the appearance of a tipping point and critical slowing down implied the existence of a critical transition. By using a multi-decadal time series from the sedimentary core, with general Lotka-Volterra model simulations, local stability analysis found that bacterial communities were the most unstable as they approached the critical transition, suggesting that the collapse of stability triggers the community shift from an equilibrium state to another state. Furthermore, the most unstable community harbored the strongest antagonistic and mutualistic interactions, which may imply the detrimental role of interaction strength on community stability. Collectively, our study showed that sediment DNA can be used to detect the critical transition of lake ecosystems.

Viruses contribute to microbial diversification in the rumen ecosystem and are associated with certain animal production traits

BackgroundThe rumen microbiome enables ruminants to digest otherwise indigestible feedstuffs, thereby facilitating the production of high-quality protein, albeit with suboptimal efficiency and producing methane. Despite extensive research delineating associations between the rumen microbiome and ruminant production traits, the functional roles of the pervasive and diverse rumen virome remain to be determined.ResultsLeveraging a recent comprehensive rumen virome database, this study analyzes virus-microbe linkages, at both species and strain levels, across 551 rumen metagenomes, elucidating patterns of microbial and viral diversity, co-occurrence, and virus-microbe interactions. Additionally, this study assesses the potential role of rumen viruses in microbial diversification by analyzing prophages found in rumen metagenome-assembled genomes. Employing CRISPR–Cas spacer-based matching and virus-microbe co-occurrence network analysis, this study suggests that the viruses in the rumen may regulate microbes at strain and community levels through both antagonistic and mutualistic interactions. Moreover, this study establishes that the rumen virome demonstrates responsiveness to dietary shifts and associations with key animal production traits, including feed efficiency, lactation performance, weight gain, and methane emissions.ConclusionsThese findings provide a substantive framework for further investigations to unravel the functional roles of the virome in the rumen in shaping the microbiome and influencing overall animal production performance.3QAbSJqYZPn2njEBJ23VpAVideo

Metabolic perturbations in zebrafish (Danio rerio) larvae exposed to sulfentrazone and imidacloprid

The intensive and widespread application of pesticides in agroecosystems can lead to the simultaneous exposure of non-target aquatic organisms to insecticides and herbicides. However, the underlying mechanisms through which aquatic organisms undergo metabolic reprogramming to withstand the combined effects of the insecticide imidacloprid (IMI) and herbicide sulfentrazone (SUL) remain poorly elucidated. This study employs metabolomics to investigate the effects of individual and combined exposures to IMI and SUL on zebrafish (Danio rerio), aiming to simulate complex environmental conditions. Metabolomics analysis revealed extensive metabolic reprogramming in larvae induced by the selected agrochemicals. Both individual and combined exposures disrupted nucleotide metabolism, inhibited glycolysis, and led to the accumulation of acetylcholine through the shared modulation of differential metabolites. Notably, individual exposure exhibited a unique mode of action. Larvae exposed to IMI alone showed mitochondrial dysfunction, potentially stemming from interference with the electron transport chain, while SUL-induced disruptions were associated with glycerophospholipid accumulation, marking it as a critical target. Additionally, calculations of the metabolic effect level index indicated antagonistic interactions between SUL and IMI mixtures at an overall metabolic level. The results obtained through investigating the lethal and sub-lethal effects also revealed that the simultaneous application of SUL and IMI may have the potential to diminish acute and developmental toxicity in zebrafish. This study underscores the significance of metabolomics as a valuable and effective strategy for deciphering the toxicity and interactions of agrochemical mixtures.

Litter decomposition rate response to multiple global change factors: a meta-analysis

Anthropogenic global change fundamentally impacts ecosystem biogeochemical cycling. Although litter decomposition is a crucial component of carbon (C) cycling, its response to diverse global change factors (GCFs) remains uncertain. In this research, we synthesized 1706 observations from 260 peer-reviewed publications to elucidate the effects of GCFs on litter decomposition rate (k) and the contribution of different variables to them. Overall, nitrogen (N) addition and drought significantly decreased k (-3.3 and -17.7%, respectively), phosphorus (P) addition, warming, and increased precipitation significantly increased k (6.7, 8.2, and 11.6%, respectively), while elevated CO2 had an insignificant effect on k (-0.6%). Combined GCFs had no significant effect on k except for warming*drought, and all combined factors mainly exhibited antagonistic interactions. Further analysis showed that k responses to GCFs were influenced by initial litter quality (C, N, C:N, P, cellulose, lignin, and vegetation types), soil properties (soil organic C, soil total N, soil total P, soil respiration and microbial biomass C), environmental factors (latitude, longitude, annual mean temperature, annual mean precipitation, ecosystem type, and climate type), and experimental methods (experiment type, richness, treatment method, fertilizer form, fertilizer rate, and experimental duration). Initial litter quality predominantly governed the k response to N addition (53.5%), while soil properties were more significant in regulating the P addition response (44.8%). Environmental factors largely determined k responses to warming, drought, and increased precipitation (50.6, 54.7, 46.9%). Moreover, the experimental methodology also played an important role in regulating k responses to GCFs, which explained 8.6, 23.6, 31.1, 23.7, and 29.7% of the variation of the responses of k to N addition, P addition, warming, drought, and increased precipitation. This meta-analysis offers improved global-scale nutrient cycling predictions under climate change and underscores the need for long-term, multi-factor, methodologically standardized experiments to accurately predict the influence of GCFs on litter decomposition.

Cytokinin and MAX2 signaling pathways act antagonistically in drought adaptation of Arabidopsis thaliana

Understanding the mechanisms, especially those associated with phytohormones, of plant drought adaptation is crucial for sustaining agricultural production in the era of climate change. Arabidopsis histidine kinases (AHKs), an integral part of the cytokinin signaling pathway, and more axillary growth 2 (MAX2), a key component of the strigolactone and karrikin signaling pathways are reported to act as negative and postive regulators, respectively, in plant adaption to drought. However, the potential interaction between these singaling pathways in plant drought adaptation is not fully understood. To address this query, we assessed drought tolerance levels and associated phenotypic and physiological traits of the max2 single mutant, ahk2 ahk3 double mutant, ahk2 ahk3 max2 triple mutant, and wild-type (WT) Arabidopsis thaliana plants. Our findings revealed a distinct hierarchy in drought tolerance among these genotypes, as indicated by the differences in plant growth and stress survival rates. Specifically, the max2 mutant displayed the lowest drought tolerance level, followed by WT, ahk2 ahk3 max2, and ahk2 ahk3 plants. Additionally, the observed changes in leaf relative water content, leaf surface temperature, and cuticle formation were coherently aligned with the observed hierarchy of drought tolerance levels. Under drought conditions, the max2 mutant exhibited higher oxidative stress and membrane damage, as evidenced by increased levels of reactive oxygen species (ROS), malondialdehyde, and electrolyte leakage. In contrast, the ahk2 ahk3 and ahk2 ahk3 max2 mutants showed low and intermediate levels, respectively, for these parameters. The max2 mutant displayed reduced sensitivity, whereas ahk2 ahk3 and ahk2 ahk3 max2 mutants demonstrated high and intermediate sensitivities, respectively, to exogenous absicic acid (ABA) treatments. Additionally, the expression analysis of several genes associated with the investigated drought tolerance-related traits showed a positive correlation between the transcript levels and corresponding trait(s) in both mutant and WT plants under drought conditions. Our results collectively indicate the presence of an antagonistic interaction between AHK and MAX2 signaling pathways in plant drought adaptation, impacting ABA responsiveness, leaf water retention, cuticle development, and ROS homestasis. Findings of this study provide a valuable foundation for developing agricultural methods to improve plant drought resilience.

Integrative analyses identify opportunistic pathogens of patients with lower respiratory tract infections based on metagenomic next-generation sequencing

Lower respiratory tract infections (LRTIs) represent some of the most globally prevalent and detrimental diseases. Metagenomic next-generation sequencing (mNGS) technology has effectively addressed the requirement for the diagnosis of clinical infectious diseases. This study aimed at identifying and classifying opportunistic pathogens from the respiratory tract-colonizing microflora in LRTI patients using data acquired from mNGS analyses. A retrospective study was performed employing the mNGS data pertaining to the respiratory samples derived from 394 LRTIs patients. Linear discriminant analysis effect size (LEfSe) analysis was conducted to discern the discriminant bacteria. Receiver operating characteristic curves (ROC) were established to demonstrate discriminant bacterial behavior to distinguish colonization from infection. A total of 443 discriminant bacteria were identified and segregated into three cohorts contingent upon their correlation profiles, detection frequency, and relative abundance in order to distinguish pathogens from colonizing microflora. Among them, 119 emerging opportunistic pathogens (cohort 2) occupied an average area under the curve (AUC) of 0.976 for exhibiting the most prominent predictability in distinguishing colonization from infection, 39 were colonizing bacteria (cohort 1, 0.961), and 285 were rare opportunistic pathogens (cohort 3, 0.887). The LTRIs patients appeared modular in the form of cohorts depicting complex microbial co-occurrence networks, reduced diversity, and a high degree of antagonistic interactions in the respiratory tract microbiome. The study findings indicate that therapeutic interventions should target interaction networks rather than individual microbes, providing an innovative perspective for comprehending and combating respiratory infections. Conclusively, this study reports a profile of LRTIs-associated bacterial colonization and opportunistic pathogens in a relatively large-scale cohort, which might serve as a reference panel for the interpretation of mNGS results in clinical practice.

Telling mutualistic and antagonistic ecological networks apart by learning their multiscale structure

Abstract Characterizing and understanding the processes that shape the structure of ecological networks, which represent who interacts with whom in a community, has many implications in ecology, evolutionary biology and conservation. A highly debated question is whether and how the structure of a bipartite ecological network differs between antagonistic (e.g. herbivory) and mutualistic (e.g. pollination) interaction types. Here, we tackle this question by using a multiscale characterization of network structure, machine learning tools, and a large database of empirical and simulated bipartite networks. Contrary to previous studies focusing on global structural metrics, such as nestedness and modularity, which concluded that antagonistic and mutualistic networks cannot be told apart from only their structure, we find that they can be told apart by combining a meso‐scale characterization of their structure and supervised machine learning. Motif frequencies appear particularly informative, with an over‐representation of densely connected motifs in antagonistic networks and of motifs with asymmetrical specialization in mutualistic networks. These structural properties can be used to predict the type of interaction with relatively good confidence. Beyond this classical mutualism/antagonism dichotomy, we also find significant structural uniqueness linked to specific ecologies (e.g. pollination, parasitism). Our results clarify structural differences between antagonistic and mutualistic networks and suggest the investigation of the structural uniqueness of specific ecologies as a promising approach for characterizing interactions beyond the coarse antagonistic/mutualistic dichotomy.

Number of global change factors alters plant-soil feedbacks via its effect on soil fungal communities

Plants and soil microbes are often challenged by multiple global change factors (GCFs), and their responses to single GCFs may differ from those to multiple GCFs due to synergistic or antagonistic interactions. Therefore, changes in number of GCFs may alter plant-soil feedbacks. We conditioned a soil by growing a plant of Hydrocotyle verticillata in the soil for three months, and then grew a plant of the same species in a sterilized bulk soil inoculated with the live or the sterilized conditioned soil under no, single, two or four GCFs. The strength of plant-soil feedbacks calculated by root biomass was positive in the treatment with four GCFs, but not in any of the other three treatments. The strength of plant-soil feedbacks based on shoot biomass was positive in the treatment with single and four GCFs, but not in the treatments with no or two GCFs. Furthermore, the strength of plant-soil feedbacks was closely related to changes in soil fungal composition mediated by changes in number of GCFs. These results indicate that increasing number of GCFs can alter plant-soil feedbacks via changing fungal legacies that plants leave in the soil. Our results highlight the importance of multiple GCFs in regulating plant-microbial interactions.

Warming and altered precipitation independently and interactively suppress alpine soil microbial growth in a decadal-long experiment

Warming and precipitation anomalies affect terrestrial carbon balance partly through altering microbial eco-physiological processes (e.g., growth and death) in soil. However, little is known about how such processes responds to simultaneous regime shifts in temperature and precipitation. We used the 18O-water quantitative stable isotope probing approach to estimate bacterial growth in alpine meadow soils of the Tibetan Plateau after a decade of warming and altered precipitation manipulation. Our results showed that the growth of major taxa was suppressed by the single and combined effects of temperature and precipitation, eliciting 40–90% of growth reduction of whole community. The antagonistic interactions of warming and altered precipitation on population growth were common (~70% taxa), represented by the weak antagonistic interactions of warming and drought, and the neutralizing effects of warming and wet. The members in Solirubrobacter and Pseudonocardia genera had high growth rates under changed climate regimes. These results are important to understand and predict the soil microbial dynamics in alpine meadow ecosystems suffering from multiple climate change factors.

Bacterial interactome disturbance in chronic obstructive pulmonary disease clinical stability and exacerbations

RationaleOur understanding of airway dysbiosis in chronic obstructive pulmonary disease (COPD) remains incomplete, which may be improved by unraveling the complexity in microbial interactome.ObjectivesTo characterize reproducible features of airway bacterial interactome in COPD at clinical stability and during exacerbation, and evaluate their associations with disease phenotypes.MethodsWe performed weighted ensemble-based co-occurrence network analysis of 1742 sputum microbiomes from published and new microbiome datasets, comprising two case-control studies of stable COPD versus healthy control, two studies of COPD stability versus exacerbation, and one study with exacerbation-recovery time series data.ResultsPatients with COPD had reproducibly lower degree of negative bacterial interactions, i.e. total number of negative interactions as a proportion of total interactions, in their airway microbiome compared with healthy controls. Evaluation of the Haemophilus interactome showed that the antagonistic interaction networks of this established pathogen rather than its abundance consistently changed in COPD. Interactome dynamic analysis revealed reproducibly reduced antagonistic interactions but not diversity loss during COPD exacerbation, which recovered after treatment. In phenotypic analysis, unsupervised network clustering showed that loss of antagonistic interactions was associated with worse clinical symptoms (dyspnea), poorer lung function, exaggerated neutrophilic inflammation, and higher exacerbation risk. Furthermore, the frequent exacerbators (≥ 2 exacerbations per year) had significantly reduced antagonistic bacterial interactions while exhibiting subtle compositional changes in their airway microbiota.ConclusionsBacterial interactome disturbance characterized by reduced antagonistic interactions, rather than change in pathogen abundance or diversity, is a reproducible feature of airway dysbiosis in COPD clinical stability and exacerbations, which suggests that we may target interactome rather than pathogen alone for disease treatment.

WAV E3 ubiquitin ligases mediate degradation of IAA32/34 in the TMK1-mediated auxin signaling pathway during apical hook development

Auxin regulates plant growth and development through downstream signaling pathways, including the best-known SCFTIR1/AFB-Aux/IAA-ARF pathway and several other less characterized "noncanonical" pathways. Recently, one SCFTIR1/AFB-independent noncanonical pathway, mediated by Transmembrane Kinase 1 (TMK1), was discovered through the analyses of its functions in Arabidopsis apical hook development. Asymmetric accumulation of auxin on the concave side of the apical hook triggers DAR1-catalyzed release of the C-terminal of TMK1, which migrates into the nucleus, where it phosphorylates and stabilizes IAA32/34 to inhibit cell elongation, which is essential for full apical hook formation. However, the molecular factors mediating IAA32/34 degradation have not been identified. Here, we show that proteins in the CYTOKININ INDUCED ROOT WAVING 1 (CKRW1)/WAVY GROWTH 3 (WAV3) subfamily act as E3 ubiquitin ligases to target IAA32/34 for ubiquitination and degradation, which is inhibited by TMK1c-mediated phosphorylation. This antagonistic interaction between TMK1c and CKRW1/WAV3 subfamily E3 ubiquitin ligases regulates IAA32/34 levels to control differential cell elongation along opposite sides of the apical hook.

Targeting Colorectal Cancer: Unravelling the Transcriptomic Impact of Cisplatin and High-THC Cannabis Extract.

Cisplatin and other platinum-derived chemotherapy drugs have been used for the treatment of cancer for a long time and are often combined with other medications. Unfortunately, tumours often develop resistance to cisplatin, forcing scientists to look for alternatives or synergistic combinations with other drugs. In this work, we attempted to find a potential synergistic effect between cisplatin and cannabinoid delta-9-THC, as well as the high-THC Cannabis sativa extract, for the treatment of HT-29, HCT-116, and LS-174T colorectal cancer cell lines. However, we found that combinations of the high-THC cannabis extract with cisplatin worked antagonistically on the tested colorectal cancer cell lines. To elucidate the mechanisms of drug interactions and the distinct impacts of individual treatments, we conducted a comprehensive transcriptomic analysis of affected pathways within the colorectal cancer cell line HT-29. Our primary objective was to gain a deeper understanding of the underlying molecular mechanisms associated with each treatment modality and their potential interactions. Our findings revealed an antagonistic interaction between cisplatin and high-THC cannabis extract, which could be linked to alterations in gene transcription associated with cell death (BCL2, BAD, caspase 10), DNA repair pathways (Rad52), and cancer pathways related to drug resistance.

Blessing or curse: how the epigenetic resolution of host-transposable element conflicts shapes their evolutionary dynamics.

Transposable elements (TEs) are selfish genetic elements whose antagonistic interactions with hosts represent a common genetic conflict in eukaryotes. To resolve this conflict, hosts have widely adopted epigenetic silencing that deposits repressive marks at TEs. However, this mechanism is imperfect and fails to fully halt TE replication. Furthermore, TE epigenetic silencing can inadvertently spread repressive marks to adjacent functional sequences, a phenomenon considered a 'curse' of this conflict resolution. Here, we used forward simulations to explore how TE epigenetic silencing and its harmful side effects shape the evolutionary dynamics of TEs and their hosts. Our findings reveal that epigenetic silencing allows TEs and their hosts to stably coexist under a wide range of conditions, because the underlying molecular mechanisms give rise to copy-number dependency of the strength of TE silencing. Interestingly, contrary to intuitive expectations that TE epigenetic silencing should evolve to be as strong as possible, we found a selective benefit for modifier alleles that weaken TE silencing under biologically feasible conditions. These results reveal that the dual nature of TE epigenetic silencing, with both positive and negative effects, complicates its evolutionary trajectory and makes it challenging to determine whether TE epigenetic silencing is a 'blessing' or a 'curse'.

State-of-the-Art Review on Botanical Hybrid Preparations in Phytomedicine and Phytotherapy Research: Background and Perspectives.

Despite some evidence supporting the synergy concept, the commonly known assumption that combinations of several herbs in one formulation can have better efficacy due to additive or synergistic effects has yet to be unambiguously and explicitly studied. The study aimed to reveal the molecular interactions in situ of host cells in response to botanical hybrid preparations (BHP) intervention and justify the benefits of implementing BHP in clinical practice. This prospective literature review provides the results of recent clinical and network pharmacology studies of BHP of Rhodiola rosea L. (Arctic root) with other plants, including Withania somnifera (L.) Dunal (ashwagandha), (Camellia sinensis (L.) Kuntze (green tea), Eleutherococcus senticosus (Rupr. and Maxim.) Maxim. (eleuthero), Schisandra chinensis (Turcz.) Baill. (schisandra), Leuzea carthamoides (Willd.) DC., caffeine, Cordyceps militaris L., Ginkgo biloba L.(ginkgo), Actaea racemosa L. (black cohosh), Crocus sativus L. (saffron), and L-carnosine. The most important finding from network pharmacology studies of BHP was the evidence supporting the synergistic interaction of BHP ingredients, revealing unexpected new pharmacological activities unique and specific to the new BHP. Some studies show the superior efficacy of BHP compared to mono-drugs. At the same time, some a priori-designed combinations can fail, presumably due to antagonistic interactions and crosstalk between molecular targets within the molecular networks involved in the cellular and overall response of organisms to the intervention. Network pharmacology studies help predict the results of studies aimed at discovering new indications and unpredicted adverse events.

Parameter variational based adaptive bipartite formation control of second-order multi-agent systems with antagonistic interactions

This article mainly concentrates on researching the leader-following bipartite formation of second-order nonlinear multi-agent systems (MASs) with antagonistic interactions and time-varying delay. A novel distributed feedback control and impulsive control strategy is proposed for realizing the bipartite formation. By establishing an error system, the bipartite formation issue of the MASs is transformed into the stability issue of the error systems. Sufficient conditions for achieving the bipartite formation of second-order nonlinear MASs are obtained by jointly employing the extended parameters variation formula, the comparison principle and the definition of average impulsive interval. In addition, in order to obtain the optimal control gains and control effects, an adaptive control strategy is taken into account by designing the adaptive updating laws. Ultimately, the effectiveness of the theoretical results is demonstrated by two numerical simulations.

Resilient data‐driven asymmetric bipartite consensus for nonlinear multi‐agent systems against DoS attacks

AbstractIn this article, we study an unified resilient asymmetric bipartite consensus (URABC) problem for nonlinear multi‐agent systems with both cooperative and antagonistic interactions under denial‐of‐service (DoS) attacks. We first prove that the URABC problem is solved by stabilizing the neighborhood asymmetric bipartite consensus error. Then, we develop a distributed compact form dynamic linearization method to linearize the neighborhood asymmetric bipartite consensus error. By using an attack compensation mechanism to eliminate the adverse effects of DoS attacks and an extended discrete state observer to enhance the robustness against unknown dynamics, we finally propose a distributed resilient data‐driven adaptive control (DDAC) algorithm to solve the URABC problem. A numerical example validates the proposed results.

Behaviors of matrix-weighted networks with antagonistic interactions

This essay considers the bipartite consensus of matrix-weighted second-order multi-agent systems with structurally unbalanced antagonistic interactions networks. Owing to the influence of matrix-weights, bipartite consensus and cluster bipartite consensus can also be reached, which is different from the existing works on signed networks. With the assistance of Lyapunov stability and matrix-valued Gauge transformation, a condition to achieve bipartite consensus is established. Moreover, a relatively straightforward algebraic graph condition for reaching cluster bipartite consensus is attained. Finally, simulation examples are supplied to illustrate the obtained results.

Interaction Between Tobacco Smoke Exposure and Zinc Intake and Its Effect on Periodontitis: Evidence From NHANES

Aim: Tobacco smoke exposure, zinc intake with periodontitis were closely related. This study was to assess the relationship of coexistence of tobacco smoke exposure and zinc intake on the periodontitis. Materials and methods: This cross-sectional study included 9,364 participants from National Health and Nutrition Examination Survey. Using weighted multivariate logistic regression model to investigate the independent relationship and interaction effect between tobacco smoke exposure, zinc intake and periodontitis. Odds ratio (OR) with 95% confidence interval (CI) were calculated. The additive interaction was evaluated using relative excess risk due to interaction (RERI), attributable proportion of interaction (AP) and synergy index (SI). Results: 56.57% participants had periodontitis. Compared with participants without tobacco smoke exposure, those with tobacco smoke exposure had an increased odd of periodontitis (OR=1.96, 95%CI: 1.67-2.31). Similarly, the patients with adequate zinc intake were found to have a decreased odds of periodontitis than those inadequate zinc intake (OR=0.86, 95%CI: 0.76-0.98). Importantly, there was antagonistic interaction between zinc intake and tobacco smoke exposure on periodontitis [RERI (95% CI): -0.432 (-0.829, -0.034), AP (95% CI): -0.242 (-0.470, -0.014), SI (95%CI): 0.645 (0.446-0.932)]. Conclusion: This analysis may provide evidence for the antagonistic interaction between tobacco smoke exposure and zinc intake on the periodontitis development.