Resveratrol, EGCG and Vitamins Modulate Activated T Lymphocytes.

Vitamins and bioactives, which are constituents of the food chain, modulate T lymphocyte proliferation and differentiation, antibody production, and prevent inflammation and autoimmunity. We investigated the effects of vitamins (vitamin A (VA), D (VD), E (VE)) and bioactives (i.e., resveratrol (Res), epigallocatechin-3-gallate (EGCG)) on the adaptive immune response, as well as their synergistic or antagonistic interactions. Freshly isolated T lymphocytes from healthy individuals were activated with anti-CD3/CD28 antibodies for 4-5 days in the presence of bioactives and were analyzed by cytofluorometry. Interleukins, cytokines, and chemokines were measured by multiple ELISA. Gene expression was measured by quantitative RT-PCR. Res and EGCG increased CD4 surface intensity. EGCG led to an increased proportion of CD8+ lymphocytes. Anti-CD3/CD28 activation induced exuberant secretion of interleukins and cytokines by T lymphocyte subsets. VD strongly enhanced Th2 cytokines (e.g., IL-5, IL-13), whereas Res and EGCG favored secretion of Th1 cytokines (e.g., IL-2, INF-γ). Res and VD mutually influenced cytokine production, but VD dominated the cytokine secretion pattern. The substances changed gene expression of interleukins and cytokines in a similar way as they did secretion. Collectively, VD strongly modulated cytokine and interleukin production and favored Th2 functions. Resveratrol and EGCG promoted the Th1 response. VA and VE had only a marginal effect, but they altered both Th1 and Th2 response. In vivo, bioactives might therefore interact with vitamins and support the outcome and extent of the adaptive immune response.

Ecotoxicity and genotoxicity of a binary combination of triclosan and carbendazim to Daphnia magna.

In the environment, chemical substances appear as complex mixtures and consequently organisms are exposed to a variety of chemicals from different sources (e.g. wastewater treatment plants, agriculture runoffs). When studying chemical mixtures, there are two conceptual models usually used to predict toxicity: the Independent Action (IA) and Concentration Addition (CA) models. However, deviations from these reference models can occur as synergism or antagonism, dose ratio or dose level dependency. The aim of the present study was to investigate the effects of triclosan and carbendazim, and their binary mixture to Daphnia magna. With this purpose, immobilisation, feeding inhibition, and reproduction were assessed as main ecotoxicity endpoints. In addition, in vivo genotoxicity of both chemicals was investigated using the comet assay. In the single exposure, carbendazim was more toxic to D. magna than triclosan. When daphnids were exposed to both single compounds, DNA damage was observed. Concerning mixture exposures, different endpoints followed different patterns of response, from additivity: IA model (feeding inhibition and reproduction data), to deviations that indicate interaction between chemicals inside the organism: dose level dependency (immobilisation data) and dose ratio dependency (DNA damage). This study showed that additivity does not rule the dose-effect relation in chemical mixtures of carbendazim and triclosan and interactions between both chemicals might induce generally higher toxicity than predicted based on single chemical exposures.

Time-dependent nonmonotonic concentration-response and synergism of alkyl glycosides with different alkyl side chain to Vibrio qinghaiensis sp. -Q67.

Alkyl glycosides (AGs), commonly used nonionic surfactants, may have toxic effects on the environmental organisms. However, the complex concentration-response patterns of AGs with varying alkyl side chains and their mixtures have not been thoroughly studied. Therefore, the luminescence inhibition toxicities of six AGs with different alkyl side chains, namely, ethyl (AG02), butyl (AG04), hexyl (AG06), octyl (AG08), decyl (AG10), and dodecyl (AG12) glucosides, were determined in Vibrio qinghaiensis sp. -Q67 (Q67) at 0.25, 3, 6, 9, and 12 h. The six AGs exhibited time- and side-chain-dependent nonmonotonic concentration- responses toward Q67. AG02, with a short side chain, presented a concentration-response curve (CRC) with two peaks after 6 h and stimulated the luminescence of Q67 at both 6 and 9 h. AG04, AG06, and AG08 showed S-shaped CRCs at five exposure time points, and their toxicities increased with the side-chain length. AG10 and AG12, with long side chains, exhibited hormesis at 9 and 12 h. Molecular docking was performed to explore the mechanism governing the possible influence of AGs on the luminescence response. The effects of AGs on Q67 could be attributed to multiple luminescence-regulatory proteins, including LuxA, LuxC, LuxD, LuxG, LuxI, and LuxR. Notably, LuxR was identified as the primary binding protein among the six AGs. Given that they may co-exist, binary mixtures of AG10 and AG12 were designed to explore their concentration-response patterns and interactions. The results revealed that all AG10-AG12 binary mixture rays showed time-dependent hormesis on Q67, similar to that shown by their individual components. The interactions of these binary mixtures were mainly characterized by low-concentration additive action and high-concentration synergism at different times.

Co-culture Wood Block Decay Test with Bacteria and Wood Rotting Fungi to Analyse Synergism/Antagonism during Wood Degradation.

Mixed communities of fungi and bacteria have been shown to be more efficient in degrading wood than fungi alone. Some standardised protocols for quantification of the wood decay ability of fungi have been developed (e.g., DIN V ENV 12038:2002 as the legal standard to test for the resistance of wood against wood-destroying basidiomycetes in Germany). Here, we describe a step-by-step protocol developed from the official standard DIN V ENV12038 to test combinations of bacteria and fungi for their combined wood degradation ability. Equally sized wood blocks are inoculated with wood decay fungi and bacterial strains. Axenic controls allow the analysis of varying degradation rates via comparison of the wood dry weights at the end of the experiments. This protocol provides new opportunities in exploration of inter- and intra-kingdom interactions in the wood-related environment and forms the basis for microcosm experiments. Key features • Quantification of wood decay ability of mixed cultures. • Allows testing if fungi are more efficient in degrading wood when bacteria are present.

The fate of arsenic in rice plants (Oryza sativa L.): Influence of different forms of selenium.

As contamination of rice plants has aroused worldwide concern because of the threats posed to human health through its accumulation in the food chain. However, no data are currently available on the effect of Se nanoparticles (SeNPs) on the fate of As in higher plants, and previously reported relationships between As and Se are inconsistent. Therefore, in this study, the possible mediating roles of SeNPs or selenite on the uptake, translocation, subcellular distribution, and transformation of arsenite and arsenate in rice seedlings (Oryza sativa L.) were investigated through hydroponic experiments. The results showed that, when supplied as arsenite and arsenate, selenite significantly increased root As uptake by 71.7% and 45.9% but decreased shoot As content by 48.9% and 52.4%, respectively. In comparison, the reducing effect of SeNPs on shoot As content (37.1%) was only significant in arsenite-treated rice plants. Furthermore, selenite significantly reduced and increased the As content of different shoot and root subcellular fractions, respectively; and SeNPs also led to a dramatic decrease in the As content of the different shoot subcellular fractions of arsenite-treated rice plants. Moreover, As(III) and As(V) content was reduced in rice shoots while enhanced in rice roots by selenite. Generally, neither As(III) nor As(V) content in rice tissues was dramatically changed by SeNPs. Our results indicate that both SeNPs and selenite are effective in mitigating As toxicity in rice plants, although selenite showed a stronger inhibiting effect on As translocation.

Lethal effects of Cr(III) alone and in combination with propiconazole and clothianidin in honey bees.

Several anthropogenic contaminants, including pesticides and heavy metals, can affect honey bee health. The effects of mixtures of heavy metals and pesticides are rarely studied in bees, even though bees are likely to be exposed to these contaminants in both agricultural and urban environments. In this study, the lethal toxicity of Cr alone and in combination with the neonicotinoid insecticide clothianidin and the ergosterol-biosynthesis-inhibiting fungicide propiconazole was assessed in Apis mellifera adults. The LD50 and lowest benchmark dose of Cr as Cr(NO3)3, revealed a low acute oral toxicity on honey bee foragers (2049 and 379 mg L-1, respectively) and the Cr retention (i.e. bee ability to retain the heavy metal in the body) was generally low compared to other metals. A modified method based on the binomial proportion test was developed to analyse synergistic and antagonistic interactions between the three tested contaminants. The combination of an ecologically-relevant field concentration of chromium with clothianidin and propiconazole did not increase bee mortality. On the contrary, the presence of Cr in mixture with propiconazole elicited a slight antagonistic effect.

Expression Profile of Defense Genes in Rice Lines Pyramided with Resistance Genes Against Bacterial Blight, Fungal Blast and Insect Gall Midge.

BACKGROUND: Rice, a major food crop of the world, endures many major biotic stresses like bacterial blight (BB), fungal blast (BL) and the insect Asian rice gall midge (GM) that cause significant yield losses. Progress in tagging, mapping and cloning of several resistance (R) genes against aforesaid stresses has led to marker assisted multigene introgression into elite cultivars for multiple and durable resistance. However, no detailed study has been made on possible interactions among these genes when expressed simultaneously under combined stresses. RESULTS: Our studies monitored expression profiles of 14 defense related genes in 11 rice breeding lines derived from an elite cultivar with different combination of R genes against BB, BL and GM under single and multiple challenge. Four of the genes found implicated earlier under combined GM and BB stress were confirmed to be induced (≥ 2 fold) in stem tissue following GM infestation; while one of these, cytochrome P450 family protein, was also induced in leaf in plants challenged by either BB or BL but not together. Three of the genes highlighted earlier in plants challenged by both BB and BL were also found induced in stem under GM challenge. Pi54 the target R gene against BL was also found induced when challenged by GM. Though expression of some genes was noted to be inhibited under combined pest challenge, such effects did not result in compromise in resistance against any of the target pests. CONCLUSION: While R genes generally tended to respond to specific pest challenge, several of the downstream defense genes responded to multiple pest challenge either single, sequential or simultaneous, without any distinct antagonism in expression of resistance to the target pests in two of the pyramided lines RPNF05 and RPNF08.

Synergies and antagonisms in virus interactions.

Metagenomic surveys and data from next generation sequencing revealed that mixed infections among plant viruses are probably a rule rather than an exception in natural pathosystems. The documented cases may range from synergism to antagonism, which may depend from the spatiotemporal order of arrival of the viruses on the host and upon the host itself. In synergistic interactions, the measurable differences in replication, phenotypic and cytopathological changes, cellular tropism, within host movement, and transmission rate of one of the two viruses or both are increased. Conversely, a decrease in replication, or inhibition of one or more of the above functions by one virus against the other, leads to an antagonistic interaction. Viruses may interact directly and by transcomplementation of defective functions or indirectly, through responses mediated by the host like the defense mechanism based on RNA silencing. Outcomes of these interactions can be applied to the risk assessment of transgenic crops expressing viral proteins, or cross-protected crops for the identification of potential hazards. Prior to experimental evidence, mathematical models may help in forecasting challenges deriving from the great variety of pathways of synergistic and antagonistic interactions. Actually, it seems that such predictions do not receive sufficient credit in the framework of agriculture.