High-throughput, combinatorial droplet generation by sequential spraying.

One of the central goals of ecology is to explain and predict coexistence of species. In this context, microbial communities provide a model system where community structure can be studied in environmental niches and in laboratory conditions. A community of microbial population is stabilized by interactions between participating species. However, the nature of these stabilizing interactions has remained largely unknown. Theory and experiments have suggested that communities are stabilized by antagonistic interactions between member species, and destabilized by synergistic interactions. However, experiments have also revealed that a large fraction of all the interactions between species in a community are synergistic in nature. To understand the relative significance of the two types of interactions (synergistic vs. antagonistic) between species, we perform simulations of microbial communities with a small number of participating species using two frameworks—a replicator equation and a Lotka-Volterra framework. Our results demonstrate that synergistic interactions between species play a critical role in maintaining diversity in cultures. These interactions are critical for the ability of the communities to survive perturbations and maintain diversity. We follow up the simulations with quantification of the extent to which synergistic and antagonistic interactions are present in a bacterial community present in a soil sample. Overall, our results show that community stability is largely achieved with the help of synergistic interactions between participating species. However, we perform experiments to demonstrate that antagonistic interactions, in specific circumstances, can also contribute toward community stability.

Acute myeloid leukemia (AML) is the most prevalent type of leukemia in adults. Its heterogeneity, both between patients and within the same patient, is often a factor contributing to poor treatment outcomes. Despite advancements in AML biology and medicine in general, the standard AML treatment, the combination of cytarabine and daunorubicin, has remained the same for decades. Combination drug therapies are proven effective in achieving targeted efficacy while minimizing drug dosage and unintended side effects, a common problem for older AML patients. However, a systematic survey of the synergistic potential of drug-drug interactions in the context of AML pathology is lacking. Here, we examine the interactions between 15 commonly used cancer drugs across distinct AML cell lines and demonstrate that synergistic and antagonistic drug-drug interactions are widespread but not conserved across these cell lines. Notably, enasidenib and venetoclax, recently approved anticancer agents, exhibited the highest counts of synergistic interactions and the fewest antagonistic ones. In contrast, 6-Thioguanine, a purine analog, was involved in the highest number of antagonistic interactions. The interactions we report here cannot be attributed solely to the inherent natures of these three drugs, as each drug we examined was involved in several synergistic or antagonistic interactions in the cell lines we tested. Importantly, these drug-drug interactions are not conserved across cell lines, suggesting that the success of combination therapies might vary significantly depending on AML genotypes. For instance, we found that a single mutation in the TF1 cell line could dramatically alter drug-drug interactions, even turning synergistic interactions into antagonistic ones. Our findings provide a preclinical survey of drug-drug interactions, revealing the complexity of the problem.

The study evaluated the fumigant toxicity of cloves (Eugenia aromatica Baill.) and citrus peels (Citrus spp.) powders applied singly and binary combinations (1:1 ratio) to the cowpea storage beetle, Callosobruchus maculatus Fabricius under ambient laboratory conditions (28 ± 4°C and 75 ± 10% rh). The powders (singles and mixtures), placed in empty tea bags, were tested at the dosages of 0.0 (control), 0.5, 1.0 1.5 and 2.0 g/20 g of grain in plastic bottles with airtight lids against freshly emerged adult beetles. Adult mortality was observed 24, 48, and 72 h post fumigation. To determine antagonistic, additive and synergistic interactions, corrected mortality data was used to compute co-toxicity factors. Co-toxicity factor for the binary combinations of powders at different dosages at 24 hours indicated antagonistic interaction, ranging from - 40 to -100. Co-toxicity factor at 48 hours ranged from -30 to -90 indicating mainly antagonistic interaction except for Clove + Tangerine, Clove + Lime and Clove + Grape applied at 2.0 g/20 g of grain with -6.7, 0.0, and 6.6 respectively, indicative of additive interaction. Co-toxicity factor at the 0.5 g/20 g of grain dosage at 72 hours ranged from -53.3 to -56.6 indicating antagonistic interaction; at the 1.0 and 1.5 g/20 g ranged from -20 to 6.7 indicating additive interaction; and at the 2.0 g/20 g was 19.7 for Clove and Sweet orange mixture also indicating additive interaction, but 40, 46.7 and 46.7 for Clove and Grape, Clove and Tangerine, and Clove and Lime mixtures, respectively, indicating synergistic interactions.

Experimental concurrent infection with two or more parasite species in mammalian host models may result in heterologous antagonistic and synergistic interactions ranging in magnitude from reduced/enhanced growth and fecundity to blockage/enhancement of establishment/expulsion. With some exceptions only, there is a reasonable correlation between the levels of interaction monitored by parasitological and by clinico-pathological parameters. Heterologous antagonistic interactions mediated by functional and specific immunological cross-reactivity occur between closely related parasite species exhibiting a marked immunobiological similarity. In contrast, antagonistic interactions between antigenetically more remote species of helminths, protozoan-induced resistance to helminth infection and helminth-induced suppression of concurrent protozoan infection generally appear mediated by immunologically non-specific factors like macrophage activation and inflammatory reactions. Synergistic heterologous interactions between helminths, helminth-induced enhancement of concurrent protozoan infection and interference with the development and maintenance of resistance to helminth infection in response to concurrent protozoan infection are generally thought to be mediated by non-specific parasite-induced immunosuppression. Concurrent experimental infection is very complex. There are problems and limitations in extrapolating from experimental studies on concurrent infection in laboratory animals to natural polyparasitism. This fact, coupled with the complex influence of ecological factors on the pattern and frequency of concurrent natural infection means that major consequences of natural concurrent parasite infection have not been definitively demonstrated. Appropriately planned and controlled field studies and further laboratory experiments on primate and domestic animal models are imperative for elucidation of the importance of heterologous interactions in concurrent parasite infection for the disease pattern in man and domestic stock. Experimental studies hitherto conducted on concurrent parasite infection pointing to natural heterologous interactions may be a valuable starting point for further studies.

There is abundant interest in assessing the joint effects of multiple exposures on human health. This is often referred to as the mixtures problem in environmental epidemiology and toxicology. Classically, studies have examined the adverse health effects of different chemicals one at a time, but there is concern that certain chemicals may act together to amplify each other's effects. Such amplification is referred to as synergistic interaction, while chemicals that inhibit each other's effects have antagonistic interactions. Current approaches for assessing the health effects of chemical mixtures do not explicitly consider synergy or antagonism in the modeling, instead focusing on either parametric or unconstrained nonparametric dose response surface modeling. The parametric case can be too inflexible, while nonparametric methods face a curse of dimensionality that leads to overly wiggly and uninterpretable surface estimates. We propose a Bayesian approach that decomposes the response surface into additive main effects and pairwise interaction effects and then detects synergistic and antagonistic interactions. Variable selection decisions for each interaction component are also provided. This Synergistic Antagonistic Interaction Detection (SAID) framework is evaluated relative to existing approaches using simulation experiments and an application to data from NHANES.

In this paper, a scalable and fast process is developed and employed for the fabrication of the perovskite light harvesting layer in inverted planar heterojunction solar cell (FTO/PEDOT:PSS/CH3NH3PbI3−xClx/PCBM/Al). Perovskite precursor solutions are sprayed onto an ultrasonically vibrating substrate in two sequential steps via a process herein termed as the two-step sequential substrate vibration-assisted spray coating (2S-SVASC). The gentle imposed ultrasonic vibration on the substrate promotes droplet spreading and coalescence, surface wetting, evaporation, mixing of reagents, and uniform growth of perovskite nanocrystals. The role of the substrate temperature, substrate vibration intensity, and the time interval between the two sequential sprays are studied on the roughness, coverage, and crystalline structure of perovskite thin films. We demonstrate that a combination of a long time interval between spraying of precursor solutions (15 min), a high substrate temperature (120 °C), and a mild substrate vibration power (5 W) results in a favorable morphology and surface quality. The characteristics and performance of prepared perovskite thin films made via the 2S-SVASC technique are compared with those of the co-sprayed perovskite thin films. The maximum power conversion efficiency of 5.08 % on a 0.3-cm2 active area is obtained for the device made via the scalable 2S-SVASC technique.

Acute myeloid leukemia (AML) is the most prevalent type of leukemia in adults. Its heterogeneity, both between patients and within the same patient, is often a factor contributing to poor treatment outcomes. Despite advancements in AML biology and medicine in general, the standard AML treatment, the combination of cytarabine and daunorubicin, has remained the same for decades. Combination drug therapies are proven effective in achieving targeted efficacy while minimizing drug dosage and unintended side effects, a common problem for older AML patients. However, a systematic survey of the synergistic potential of drug–drug interactions in the context of AML pathology is lacking. Here, we examine the interactions between 15 commonly used cancer drugs across distinct AML cell lines and demonstrate that synergistic and antagonistic drug–drug interactions are widespread but not conserved across these cell lines. Notably, enasidenib and venetoclax, recently approved anticancer agents, exhibited the highest counts of synergistic interactions and the fewest antagonistic ones. In contrast, 6-Thioguanine, a purine analog, was involved in the highest number of antagonistic interactions. The interactions we report here cannot be attributed solely to the inherent natures of these three drugs, as each drug we examined was involved in several synergistic or antagonistic interactions in the cell lines we tested. Importantly, these drug–drug interactions are not conserved across cell lines, suggesting that the success of combination therapies might vary significantly depending on AML genotypes. For instance, we found that a single mutation in the TF1 cell line could dramatically alter drug–drug interactions, even turning synergistic interactions into antagonistic ones. Our findings provide a preclinical survey of drug–drug interactions, revealing the complexity of the problem.

705 Is it possible to establish a causal relationship between CFS (chronic fatigue syndrome) and chemical exposures? paracelsus paradigm implications

When exposed to parasites, hosts often mount energetically expensive immune responses, and this may alter resource allocation between competing life history traits including other components of the immune system. Here, we investigated whether a humoral immune challenge towards a vaccine reduces or enhances the cutaneous immune responses towards an injection of lipopolysaccharid (LPS, innate immunity) and phytohaemagglutinin (PHA, T-cell immunity) in nestling tawny owls in interaction with the degree of plumage melanin-based coloration. The humoral immune challenge enhanced the response to LPS similarly in differently coloured nestlings. In contrast, the same humoral immune challenge enhanced immune response to PHA in dark reddish melanic nestlings while reducing it in pale reddish melanic nestlings. Our results highlight that both antagonistic and synergistic interactions can take place among branches of immune system, and that the sign and magnitude of these interactions can vary with immune responses involved and the degree of melanin-based coloration.

Cholinesterase inhibition by organophosphorus and carbamate pesticides in aggregate cultures of neural cells from the foetal rat brain: The effects of metabolic activation and pesticide mixtures

Plants have evolved various defence mechanisms against herbivorous pests, ranging from physical barriers (constitutive defences) to the release of toxins (induced defences) in response to an attack. Plant defences are not always target-specific and can also act against natural enemies of these pests. This could potentially become problematic when considering both plant defences and predators as part of an Integrated Pest Management (IPM) scheme. Here we used a predator-prey model to capture the population dynamics of a biological control system to investigate the conditions where both plant defences and biological control act synergistically, leading to better pest control, and under what condition antagonistic outcomes could be expected. Our results demonstrate that both antagonistic and synergistic interactions are observable under small changes in key parameters, such as predation and growth rates. We then compared the qualitative model predictions against a set of population dynamic experiments using the Orius laevigatus (Hemiptera: Anthocoridae) - Frankliniella occidentalis (Thysanoptera: Thripidae) predator-pest system on tomato plants. In particular, we investigated the effect of plant defence-induced changes in pest growth rates and predation rates. For this we compared wild-type tomato with a mutant unable to synthesise jasmonic acid, an induced defence mechanism against pest attack, whereas changes to predation rates were realised by using O. laevigatus predator strains that are, due to differences in size, differentially affected by the plant's trichome-based constitutive defences. In agreement with model predictions, the qualitative dynamics confirmed the existence of both antagonistic and synergistic outcomes. Our results highlight the importance of considering multi-trophic interactions for the development of effective IPMs.

Currently multimodal therapy is widely used for treatment of chronic diseases including cancer. The joint use of ionizing or onionizing radiation with hyperthermia or chemotherapeutic agents increases the effectiveness of the treatment. A response of living things to combination treatment may be synergistic, additive or antagonistic. The study is aimed to examine the common regularities of synergistic and antagonistic effects development following exposure of biological objects to various factors. The article presents analysis of experimental data received by the authors of the paper and the data published by other teams. It has been found that therapeutic effects of the same factors do not depend on the objects under study, it depends on the agents parameters: a dose rate, intensity, degree of heating (temperature), concentration of chemotherapeutic agents, etc. The common regularities of synergistic interactions are: 1) synergistic effect is maximum, if the agents act simultaneously, it depends on the ratio of injuries induced by each agent; 2) the optimal correlation between influencing factors provides the maximum synergistic effect; 3) in order to maintain maximum synergistic or antagonistic effects interaction, it is necessary to reduce or to increase the intensity of one of the agents and proportionally to increase or to reduce the intensity of the second agent. The combined effects of hyperthermia and glycerol on bacterial cells are considered as an example of the antagonistic effect. Exposure to different concentrations of sodium chloride, NaCl, in combination with ionizing radiation, or ultrasound, or hyperthermia forms a stable antagonistic effect. Both glycerol and NaCl are osmotic substances and their negative effects can be attenuated by means that stabilize the osmotic homeostasis system. Yeast cells shown the synergistic interaction of ultraviolet light and hyperthermia then it began smoothly passed into antagonistic interaction as the temperature load decreased and the parameters of the influencing factors deviated from the optimal. At the same time, the antagonistic effects are also characterized by the optimal ratio of doses of the agents used, at which the observed effect has the maximum value. The conclusion is made about the commonality of the main regularities of the manifestation of the effects of synergy and antagonism at the interaction of factors of different nature regardless of the biological object, which is subjected to combined influence.

Objective: We assessed the combined crude plant extract (CPE) effects of Allium cepa, Ananas comosus, Bidens pilosa, Carica papaya, Nicotiana tabacum, Vernonia amygdalina, Zingiber officinale, and Aloe vanbalenii on sheep and goat gastrointestinal nematodes (GINs) in vitro. Materials and Methods: Fecal samples from naturally GIN-infected sheep and goats were incubated with L3 larvae and then treated with CPE combinations. The treated L3 was separated and counted under a light microscope to determine the synergistic or antagonistic interactions between the combined CPEs. Interactions between combined CPEs were calculated using Webb’s fractional product (WFPM) and simple (SM) methods. Results: Animal species showed the same CPE efficacy on GINs (p > 0.05). CPE combinations, however, showed 80%–100% effective action against sheep or goat GINs. Whereas SM alone produced synergistic interactions, WFPM produced antagonistic and synergistic interactions. The most effective combination for goats was V. amygdalina + Z. officinale (100%), whereas the most effective combinations for sheep were A. cepa + C. papaya (100%), V. amygdalina + Z. officinale (100%), and A. comosus + N. tabacum (100%). Goats had a lower CPE combined efficacy (89.16% ± 0.95%) than sheep (95.45% ± 0.95%) (p < 0.001). Conclusion: Combined CPEs that were effective in the current study should be studied in vivo.

BackgroundThe emergence and spread of antibiotic-resistant pathogens have led to the exploration of antibiotic combinations to enhance clinical effectiveness and counter resistance development. Synergistic and antagonistic interactions between antibiotics can intensify or diminish the combined therapy’s impact. Moreover, these interactions can evolve as bacteria transition from wildtype to mutant (resistant) strains. Experimental studies have shown that the antagonistically interacting antibiotics against wildtype bacteria slow down the evolution of resistance. Interestingly, other studies have shown that antibiotics that interact antagonistically against mutants accelerate resistance. However, it is unclear if the beneficial effect of antagonism in the wildtype bacteria is more critical than the detrimental effect of antagonism in the mutants. This study aims to illuminate the importance of antibiotic interactions against wildtype bacteria and mutants on the deacceleration of antimicrobial resistance.MethodsTo address this, we developed and analyzed a mathematical model that explores the population dynamics of wildtype and mutant bacteria under the influence of interacting antibiotics. The model investigates the relationship between synergistic and antagonistic antibiotic interactions with respect to the growth rate of mutant bacteria acquiring resistance. Stability analysis was conducted for equilibrium points representing bacteria-free conditions, all-mutant scenarios, and coexistence of both types. Numerical simulations corroborated the analytical findings, illustrating the temporal dynamics of wildtype and mutant bacteria under different combination therapies.ResultsOur analysis provides analytical clarification and numerical validation that antibiotic interactions against wildtype bacteria exert a more significant effect on reducing the rate of resistance development than interactions against mutants. Specifically, our findings highlight the crucial role of antagonistic antibiotic interactions against wildtype bacteria in slowing the growth rate of resistant mutants. In contrast, antagonistic interactions against mutants only marginally affect resistance evolution and may even accelerate it.ConclusionOur results emphasize the importance of considering the nature of antibiotic interactions against wildtype bacteria rather than mutants when aiming to slow down the acquisition of antibiotic resistance.

Interactions among drugs play a critical role in the killing efficacy of multi-drug treatments. Recent advances in theory and experiment for three-drug interactions enable the search for emergent interactions-ones not predictable from pairwise interactions. Previous work has shown it is easier to detect synergies and antagonisms among pairwise interactions when a rescaling method is applied to the interaction metric. However, no study has carefully examined whether new types of normalization might be needed for emergence. Here, we propose several rescaling methods for enhancing the classification of the higher order drug interactions based on our conceptual framework. To choose the rescaling that best separates synergism, antagonism and additivity, we conducted bacterial growth experiments in the presence of single, pairwise and triple-drug combinations among 14 antibiotics. We found one of our rescaling methods is far better at distinguishing synergistic and antagonistic emergent interactions than any of the other methods. Using our new method, we find around 50% of emergent interactions are additive, much less than previous reports of greater than 90% additivity. We conclude that higher order emergent interactions are much more common than previously believed, and we argue these findings for drugs suggest that appropriate rescaling is crucial to infer higher order interactions.