Flower Bat Research Articles

The study of Thai herbal plant extract as a potential therapeutic food ingredient for preventing the effects of airborne pollutants via in vitro model

Thai herbal plant is known as medicinal plant material for several treatments of diseases particularly non-communicable diseases (NCDs). This work aimed to investigate the potentiality of three plant extracts, including Bat flower (TCE), Vietnamese Coriander (POE), and Indian Pennywort (Centell), which can be a therapeutic food ingredient, in the protection of blood vessels caused by the effect of airborne through the in vitro model. The vascular smooth muscle cell (VSMC), A7r5 rat aortic cell, was used for cell culture and determined their activity after being treated with dust and plant extracts at different concentrations. The dust was prepared at 0-400 μg/mL, and the plant extracts were prepared as powder by freeze dryer before further use. The toxicity test, antioxidant activity, and cell apoptosis as well as wound healing properties were examined. The results showed the POE was highest the antioxidant activity (TPC: 1156.02±35.78 mg gallic acid/g sample and DPPH: 949.45±31.97 μmol Trolox/g sample) when compared to TCE and Centell (p<0.05). The maximum concentration of plant extracts treated cells was not over 500 μg/mL for cell toxicity. The VSMC cell apoptosis depended on increasing the dust concentration manner. There was a positive effect of plant extracts on wound repair in the blood vessels after being treated with TCE at a concentration of 100 μg/mL. According to the results, it could be suggested that plant extracts, especially TCE can be a food ingredient that plays a vital role in preventing the blood vessel from the airborne effects caused by PM10 receiving. Also, these data help and be useful for healthy food or therapeutic food development for reducing the risk factor of arteriosclerotic effects.

Bat–flower trait matching: Extreme phenotypic specialization affects diet preferences but not diet breadth

AbstractNectarivorous bats have evolved various adaptations to feeding from flowers, such as long, extensible tongues and the ability to hover. The champion of tongue length, Anoura fistulata, can extend its tongue to 150% of its body length, yet little is known about its interactions with flowers in the wild. Here we analyzed the diet of A. fistulata and co‐occurring nectar bats in eight sites across Ecuador. Results demonstrate that, despite its phenotypic specialization, A. fistulata is no more ecologically specialized in its dietary breadth than co‐occurring nectar bats. However, it prefers deeper flowers, and is the sole visitor to two species (Centropogon nigricans and Marcgravia williamsii) whose extremely deep flowers make their nectar inaccessible to other bats. Furthermore, A. fistulata only occurred in sites with at least one flower deeper than the tongue length of other nectar bats, suggesting it needs such a guaranteed nectar source to maintain a population. Finally, we found strong covariation across sites between the local tongue length of A. fistulata and the depth of the deepest flowers it visits. This suggests that the coevolutionary race that selected for the exceptional tongue length of this bat over time is also playing out in a geographic mosaic across space.

Comparative and comprehensive study of linear antenna arrays’ synthesis

<span>In this paper, a comparative and comprehensive study of synthesizing linear antenna array (LAA) designs, is presented. Different desired objectives are considered in this paper; reducing the maximum sidelobe radiation pattern (i.e., pencil-beam pattern), controlling the first null beamwidth (FNBW), and imposing nulls at specific angles in some designs, which are accomplished by optimizing different array parameters (feed current amplitudes, feed current phase, and array elements positions). Three different optimization algorithms are proposed in order to achieve the wanted goals; grasshopper optimization algorithms (GOA), antlion optimization (ALO), and a new hybrid optimization algorithm based on GOA and ALO. The obtained results show the effectiveness and robustness of the proposed algorithms to achieve the wanted targets. In most experiments, the proposed algorithms outperform other well-known optimization methods, such as; Biogeography based optimization (BBO), particle swarm optimization (PSO), firefly algorithm (FA), cuckoo search (CS) algorithm, genetic algorithm (GA), Taguchi method, self-adaptive differential evolution (SADE), modified spider monkey optimization (MSMO), symbiotic organisms search (SOS), enhanced firefly algorithm (EFA), bat flower pollination (BFP) and tabu search (TS) algorithm.</span>

Agrochemical bioaccumulation in pitaya cacti (Stenocereus queretaroensis) and its effect on bat interaction and yield

Abstract Bats are among the most valuable pollinators of economically important crops in Mexico including agaves and columnar cacti. High demand for the agricultural products of these crops has resulted in increasing use of agrochemicals, including pesticides and fertilizers, to increase yield and decrease pest damage. However, these compounds can negatively affect crop mutualists such as pollinating bats. In this study, we investigated: (i) how the application of the broad-spectrum pesticide carbamate and/or synthetic fertilizers affect crop yield of the pitaya cacti (Stenocereus queretaroensis); (ii) whether carbamate bioaccumulates in pitaya nectar and fruits; and (iii) whether the application of these agrochemicals affects visitation rates of the pitaya’s most efficient pollinators, nectarivorous bats of the genus Leptonycteris. We designed an experiment consisting of four treatments (pesticide, nutrients, both, or neither) applied to pitaya plants. We estimated the effect of each treatment by quantifying pitaya reproductive structures (flower buds and flowers) and fruit yield and quality, performed trace analysis to detect the pesticide in the nectar and fruits, and estimated bat flower visitation rates using camera traps to determine whether the addition of agrochemicals influenced pitaya–bat interactions. We found that none of the treatments increased yield or fruit sweetness, and they did not affect bat visitation rates. Fruit pulp and floral nectar contained pesticide concentrations above those permitted by international environmental agencies. Thus, our results show that adding these agrochemicals to pitaya crops does not improve yield but could negatively affect their crop pollinators, especially since bats apparently do not avoid visiting flowers containing pesticide residues.

In vitro seed germination and shoot proliferation of bat flower (Tacca chantrieri Andre)

Tacca chantrieri Andre, or bat flower, is a species from Taccaceae family that has unique inflorescences consisting of large, dark-colored bracts with long whiskers, making it suitable as ornamental pot plants. T. chantrieri leaves and rhizomes contain phytochemicals that have been reported to have medicinal properties. T. chantrieri is increasingly hard to find in their native habitat; their seeds have a very slow and low germination rate, whereas propagation in vivo by division takes a long time. A protocol is presented to optimize seed germination and in vitro propagation of T. chantrieri from West Borneo, Indonesia. We have developed a method to improve in vitro germination of freshly harvested T. chantrieri seeds. Pre-sowing treatment with 5 mg L –1 of GA3 for 5 × 24 h and addition of GA3 at 5 mg L–1 to the MS medium significantly promoted earlier and final germination up to >90% within 10 weeks after sowing compared to without GA3, or immersing in GA3 for shorter durations. MS media supplemented with indole acetic acid (IAA) at 0.5 mgL–1 and benzyl adenine (BA) at 1 or 2 mgL–1 was effective to induce shoot proliferation from in vitro germinated seeds; 7–10 shoots were produced after 12 weeks of culture. Shoot proliferation from basal shoot explants were best on MS supplemented with IAA at 0.5 mgL–1. The results of this study have provided a basis for further mass propagation efforts of T. chantrieri.

A review on optimization of antenna array by evolutionary optimization techniques

PurposeOptimization involves changing the input parameters of a process that is experimented with different conditions to obtain the maximum or minimum result. Increasing interest is shown by antenna researchers in finding the optimum solution for designing complex antenna arrays which are possible by optimization techniques.Design/methodology/approachDesign of antenna array is a significant electro-magnetic problem of optimization in the current era. The philosophy of optimization is to find the best solution among several available alternatives. In an antenna array, energy is wasted due to side lobe levels which can be reduced by various optimization techniques. Currently, developing optimization techniques applicable for various types of antenna arrays is focused on by researchers.FindingsIn the paper, different optimization algorithms for reducing the side lobe level of the antenna array are presented. Specifically, genetic algorithm (GA), particle swarm optimization (PSO), ant colony optimization (ACO), cuckoo search algorithm (CSA), invasive weed optimization (IWO), whale optimization algorithm (WOA), fruitfly optimization algorithm (FOA), firefly algorithm (FA), cat swarm optimization (CSO), dragonfly algorithm (DA), enhanced firefly algorithm (EFA) and bat flower pollinator (BFP) are the most popular optimization techniques. Various metrics such as gain enhancement, reduction of side lobe, speed of convergence and the directivity of these algorithms are discussed. Faster convergence is provided by the GA which is used for genetic operator randomization. GA provides improved efficiency of computation with the extreme optimal result as well as outperforming other algorithms of optimization in finding the best solution.Originality/valueThe originality of the paper includes a study that reveals the usage of the different antennas and their importance in various applications.

Bat–flower interaction networks in Caatinga reveal generalized associations and temporal stability

AbstractSeasonal variation in precipitation regimes influences species composition and plant–animal interactions. Such temporal variation is especially relevant in the Brazilian Caatinga, the largest Seasonally Dry Tropical Forest in South America, where bat pollination is unusually frequent in comparison with other tropical plant communities. Here, we describe seasonal and annual variations of the interaction networks between nectarivorous bats and flower species in the Caatinga. Five species of nectar‐feeding bats interacted with 30 plant species. Nectarivorous bats showed high levels of interaction overlap, which contributed to ecological generalization (low specialization and modularity) and lack of nestedness in the interaction networks. This pattern was consistent across seasons and years. Chiropterophilous and non‐chiropterophilous plants were equally important components of the interaction network. The generalized interaction patterns found may be a necessary condition for the persistence of nectarivorous bats and their specialized plants in the environmentally harsh and variable Caatinga. The underappreciated generalized interactions of bats with plants calls for studies testing the effectiveness of bats in pollinating the plants they visit, including those not typically categorized as “bat‐flowers”.Abstract in Portuguese is available with online material.

An Energy Efficient Stable Clustering Approach Using Fuzzy Type-2 Bat Flower Pollinator for Wireless Sensor Networks

Wireless sensor network (WSN) is a cost-effective networking solution for information updating in the coverage radius or in the sensing region. To record a real time event, large number of sensor nodes (SNs) need to be arranged systematically, such that information collection is possible for longer span of time. But, the hurdle faced by WSN is the limited resources of SNs. Hence, there is high demand to design and implement an energy efficient scheme to prolong the operational lifetime of WSN. Clustering based routing is the most suitable approach to support for load balancing, fault tolerance, and reliable communication to prolong performance parameters of WSN. These performance parameters are achieved at the cost of reduced lifetime of cluster head (CH). To overcome such limitations in clustering based hierarchical approach, efficient CH selection algorithm, and optimized routing algorithm are essential to design efficient solution for larger scale networks. In this paper, bat flower pollinator (BFP) using fuzzy type-2 based clustering approach is proposed to enhance the network lifespan. Simulation outcomes show that the proposed algorithm outperforms competitive clustering algorithms in the context of energy consumption, stability period and system lifetime.

Salt has contrasting effects on the digestive processing of dilute nectar by two Neotropical nectarivorous bats

Nectarivorous vertebrates might include sugar-dilute nectar in their diet and they are expected to undergo compensatory feeding. However, physiological constraints might limit the intake of sugar-dilute nectar, affecting energy budgets. Among other physiological processes, the limiting role of osmoregulation is supported by enhanced intake rate of dilute sugar solutions by avian nectarivores when salt is added. We tested if the Greater Antillean Long-tongued bat (Monophyllus redmani) and the Brown flower bat (Erophylla sezekorni) compensated energy intake when fed dilute-sugar solutions (2.5 and 5% sucrose), and if salt content (11, 20 and 40 mM NaCl l−1) modulated the intake rate of these solutions. Both species were unable to compensate intake of solutions with varying sugar densities, and energy intake on the 2.5 and 5% diets was lower than on the most concentrated diets (10, 20 and 30% sucrose). Both species responded differently to the addition of salt. Salt addition did not affect the intake of 2.5% sugar solutions by the Greater Antillean Long-tongued bat, and it decreased the intake of 5% sugar solutions. In contrast, the Brown flower bat increased the intake of 2.5 and 5% sugar solutions when salt was added. Intake responses to varying sugar densities of our two focal species and that of other bat species previously studied indicate that they are not uniform and that they might be modulated by digestive and osmoregulatory physiological traits.

On the improvement in grey wolf optimization

Grey wolf optimization (GWO) is a recently developed nature-inspired global optimization method which mimics the social behaviour and hunting mechanism of grey wolves. Though the algorithm is very competitive and has been applied to various fields of research, it has poor exploration capability and suffers from local optima stagnation. So, in order to improve the explorative abilities of GWO, an extended version of grey wolf optimization (GWO-E) algorithm is presented. This newly proposed algorithm consists of two modifications: Firstly, it is able to explore new areas in the search space because of diverse positions assigned to the leaders. This helps in increasing the exploration and avoids local optima stagnation problem. Secondly, an opposition-based learning method has been used in the initial half of iterations to provide diversity among the search agents. The proposed approach has been tested on standard benchmarking functions for different population and dimension sizes to prove its effectiveness over other state-of-the-art algorithms. Experimental results show that the GWO-E algorithm performs better than GWO, bat algorithm, bat flower pollinator, chicken swarm optimization, differential evolution, firefly algorithm, flower pollination algorithm (FPA) and grasshopper optimization algorithm. Statistical testing of GWO-E has been done to prove its significance over other popular algorithms. Further, as a real-world application, the GWO-E is used to design non-uniform linear antenna array (LAA) for minimum possible sidelobe level and null control. Performance of GWO-E for the synthesis of LAA is evaluated by considering the several different case studies of LAA that exists in the literature, and the results are compared with the results of other popular meta-heuristic algorithms like genetic algorithm, ant lion algorithm, FPA, cat swarm optimization, GWO and many more. Numerical results further show the superior performance of GWO-E over original GWO and other popular algorithms.

On Some Improved Versions of Whale Optimization Algorithm

Whale optimization algorithm (WOA) is a recently developed swarm intelligence-based algorithm which is inspired from the social behavior of humpback whale. This algorithm mimics the bubble-net hunting strategy of whales and has been applied to optimization problems. But the algorithm suffers from the problem of poor exploration and local optima stagnation. In this paper, three different modified algorithms of WOA have been proposed to improve its explorative ability. The modified versions are based on the concepts of opposition-based learning, exponentially decreasing parameters and elimination or re-initialization of worst particles. These properties have been added to improve the explorative properties of WOA by maintaining diversity among the search agents. The proposed algorithms have been tested on CEC2005 benchmark problems for variable population and dimension sizes. Statistical testing and scalability testing of the best algorithm have been carried out to prove its significance over other algorithms such as with well-known algorithms such as bat algorithm, bat flower pollinator, differential evolution, firefly algorithm, flower pollination algorithm. It has been found from the experimental results that the performance of all the proposed versions is better than the original WOA. Here, opposition- and exponential-based WOA is the best among all the proposed variants. Statistical testing and convergence profiles further validate the results.

A Fly on the Cave Wall: Parasite Genetics Reveal Fine-Scale Dispersal Patterns of Bats

Dispersal influences the evolution and adaptation of organisms, but it can be difficult to detect. Host-specific parasites provide information about the dispersal of their hosts and may be valuable for examining host dispersal that does not result in gene flow or that has low signals of gene flow. We examined the population connectivity of the buffy flower bat, Erophylla sezekorni (Chiroptera: Phyllostomidae), and its associated obligate ectoparasite, Trichobius frequens (Diptera: Streblidae), across a narrow oceanic channel in The Bahamas that has previously been implicated as a barrier to dispersal in bats. Due to the horizontal transmission of T. frequens, we were able to test the hypothesis that bats are dispersing across this channel, but this dispersal does not result in gene flow, occurs rarely, or started occurring recently. We developed novel microsatellite markers for the family Streblidae in combination with previously developed markers for bats to genotype individuals from 4 islands in The Bahamas. We provide evidence for a single population of the host, E. sezekorni, but 2 populations of its bat flies, potentially indicating a recent reduction of gene flow in E. sezekorni, rare dispersal, or infrequent transportation of bat flies with their hosts. Despite high population differentiation in bat flies indicated by microsatellites, mitochondrial DNA shows no polymorphism, suggesting that bacterial reproductive parasites may be contributing to mitochondrial DNA sweeps. Parasites, including bat flies, provide independent information about their hosts and can be used to test hypotheses of host dispersal that may be difficult to assess using host genetics alone.

An enhanced moth flame optimization

Moth flame optimization (MFO) is a recent nature-inspired algorithm, motivated from the transverse orientation of moths in nature. The transverse orientation is a special kind of navigation method, which demonstrates the movement of moths toward moon in a straight path. This algorithm has been successfully applied on various optimization problems. But, MFO suffers from the problem of poor exploration. So, in order to enhance the performance of MFO, some modifications are proposed. A Cauchy distribution function is added to enhance the exploration capability, influence of best flame has been added to improve the exploitation and adaptive step size and division of iterations is followed to maintain a balance between the exploration and exploitation. The proposed algorithm has been named as enhanced moth flame optimization (E-MFO) and to validate the applicability of E-MFO, and it has been applied to twenty benchmark functions. Also, comprehensive comparison of E-MFO with other meta-heuristic algorithms like bat algorithm, bat flower pollination, differential evolution, firefly algorithm, genetic algorithm, particle swarm optimization and flower pollination algorithm has been done. Further, the effect of population and dimension size on the performance of MFO and E-MFO has been discussed. The experimental analysis shows the superior performance of E-MFO over other algorithms in terms of convergence rate and solution quality. Also, statistical testing of E-MFO has been done to prove its significance.

Performance Analysis of Hybridization of Heuristic Techniques for Residential Load Scheduling

With the emergence of the smart grid, both consumers and electricity providing companies can benefit from real-time interaction and pricing methods. In this work, a smart power system is considered, where consumers share a common energy source. Each consumer is equipped with a home energy management controller (HEMC) as scheduler and a smart meter. The HEMC keeps updating the utility with the load profile of the home. The smart meter is connected to a power grid having an advanced metering infrastructure which is responsible for two-way communication. Genetic teaching-learning based optimization, flower pollination teaching learning based optimization, flower pollination BAT and flower pollination genetic algorithm based energy consumption scheduling algorithms are proposed. These algorithms schedule the loads in order to shave the peak formation without compromising user comfort. The proposed algorithms achieve optimal energy consumption profile for the home appliances equipped with sensors to maximize the consumer benefits in a fair and efficient manner by exchanging control messages. Control messages contain energy consumption of consumer and real-time pricing information. Simulation results show that proposed algorithms reduce the peak-to-average ratio by 34.56% and help the users to reduce their energy expenses by 42.41% without compromising the comfort. The daily discomfort is reduced by 28.18%.

An Extended Version of Flower Pollination Algorithm

Flower pollination algorithm (FPA) is a novel meta-heuristic algorithm inspired from the pollination of flowers. It has been applied to various fields of research and has proved its worth. But the algorithm suffers from certain limitations which confines its scope to different field of applications. In the present work, four modified versions of FPA have been proposed to improve exploration, searching accuracy, convergence speed and to maintain good balance between intensification and diversification. Sine Cosine operator has been added instead of Levy flight for improving the exploration and searching accuracy. Secondly, an improved probability switching has been used to balance the exploration and exploitation. The last modification uses improved distribution parameter for enhancing the local search phase. The results of proposed versions are tested on nineteen benchmark functions for different population sizes. The best modified version of algorithm has been named as linear–exponential flower pollination algorithm (LEFPA). The results of LEFPA are then compared with firefly algorithm, differential evolution, bat algorithm, bat flower pollination algorithm, Sine Cosine algorithm, particle swarm optimization, genetic algorithm, cuckoo search and FPA. Experimental results show that LEFPA algorithm is better when compared to other algorithms and can be considered as the potential candidate to become state of the art. Further, statistical testing has been done to prove the significance of the proposed approach.

An investigation on metaheuristic techniques for solving cell to switch assignment problem

The assignment of cells to switches in a Personal Communication Services Network (PCSN) is a Non-Deterministic Polynomial Time (NP) hard problem with exponential complexity and is among the hardest combinatorial optimisation problems of great practical importance in wireless communication systems. The objective is to assign cells to switches in an optimal manner, such that the cost comprising the sum of hand-off, cabling and switching cost is minimised with reasonable accuracy in an acceptable time scale, while obeying the constraints that each cell must be assigned to exactly one switch and total load of all the cells which are assigned to a switch is below the capacity of the switch. The aim of this article is to experimentally investigate the performance of three recent metaheuristic algorithms namely Bat Algorithm (BA), Firefly Algorithm (FA) and Flower Pollination Algorithm (FPA) for solving the Cell to Switch Assignment (CSA) problem.

Evaluation of horticultural traits and seed germination of Tacca chantrieri ‘André

Tacca chantrieri André is a perennial plant belonging to the Taccaceae family. T. chantrieri is known as the ‘bat flower’ or ‘bat plant’ due to its unique black bracts that resemble bats. It has the potential to be commercialized as an indoor, flowering, ornamental plant due to its unique flower morphology and shade tolerance. The distribution of T. chantrieri in its natural habitat has contracted due to land clearing and habitat destruction to the extent that it is now very hard to find in its traditional natural environment. The objectives of this study were to evaluate the morphological characteristics of T. chantrieri, to evaluate seed germination in vivo and in vitro, and in vitro culture of the plant using standard Murashige and Skoog (MS) media. Only 10% of the seeds germinated in 22 wk. An evaluation of the non-germinated seed showed that 42% of the seeds did not have embryos. In vitro culture using the standard MS media resulted in 3–7 new shoots growing from the basal parts of the seedlings after 22 wk, and each shoot further developed 4–7 shoots following transfer to MS media supplemented with indole acetic acid (IAA) at 0.25–0.75 mg/L and N6-benzyladenine (BA) at 1–2 mg/L. These results indicate that even though propagation protocols should be further developed, in vitro propagation using standard MS media supplemented with combinations of IAA and BA provides a more effective way to propagate T. chantrieri when compared to the conventional propagation techniques. This information will be useful for introducing T. chantrieri to the new ornamental plant market and to conservation efforts for this species.

A novel bat flower pollination algorithm for synthesis of linear antenna arrays

In this paper, a novel algorithm, namely bat flower pollination (BFP) is proposed for synthesis of unequally spaced linear antenna array (LAA). The new method is a combination of bat algorithm (BA) and flower pollination algorithm (FPA). In BFP, both BA and FPA interact with each other to escape from local minima. The results of BFP for solving a set of 13 benchmark functions demonstrate its superior performance as compared to variety of well-known algorithms available in the literature. The novel proposed method is also used for the synthesis of unequally spaced LAA for single and multi-objective design. Simulation results show that BFP is able to provide better synthesis results than wide range of popular techniques like genetic algorithm, differential evolution, cuckoo search, particle swarm optimization, back scattering algorithm and others.

Food resource partitioning in syntopic nectarivorous bats on Puerto Rico

Abstract:Understanding the dietary needs of syntopic species is essential for examining species coexistence and resource partitioning. We analysed stable isotopes of carbon (δ13C) and nitrogen (δ15N) to estimate the diet of two putative nectarivorous bats on Puerto Rico, the brown flower bat (Erophylla bombifrons) and the Greater Antillean long-tongued bat (Monophyllus redmani). Isotopic ratios of δ13C and δ15N were obtained from whole blood of both species of bat and tissues of available plant foods and insect prey over 15 wk at the same locality. We used a concentration-dependent Bayesian mixing model to determine probability distributions of feasible dietary contributions for major potential foods used by each species of bat. Additionally, separate dietary estimates were conducted for males and non-reproductive, pregnant and lactating females to determine differences due to reproductive condition. Insects were an important source of protein for M. redmani, whereas E. bombifrons obtained most of its protein from plants. In both species of bat, lactating females had lower assimilated nitrogen than males, suggesting more reliance on plants for protein. We observed no intraspecific differences in assimilated carbon among reproductive conditions. Flight and lactation are energetically expensive and may explain the increased consumption of high-energy foods, such as fruit or nectar, in lactating female bats. Comparison of isotopes between E. bombifrons and M. redmani illustrate the differential use of food resources by these insular syntopic species of bat.

The bat flower: a source of microtubule-destabilizing and -stabilizing compounds with synergistic antiproliferative actions.

The biosynthesis of secondary metabolites provides higher plants with mechanisms of defense against microbes, insects, and herbivores. One common cellular target of these molecules is the highly conserved microtubule cytoskeleton, and microtubule-targeting compounds with insecticidal, antifungal, nematicidal, and anticancer activities have been identified from plants. A new retro-dihydrochalcone, taccabulin A, with microtubule-destabilizing activity has been identified from the roots and rhizomes of Tacca species. This finding is notable because the microtubule-stabilizing taccalonolides are also isolated from these sources. This is the first report of an organism producing compounds with both microtubule-stabilizing and -destabilizing activities. A two-step chemical synthesis of taccabulin A was performed. Mechanistic studies showed that taccabulin A binds within the colchicine site on tubulin and has synergistic antiproliferative effects against cancer cells when combined with a taccalonolide, which binds to a different site on tubulin. Taccabulin A is effective in cells that are resistant to many other plant-derived compounds. The discovery of a natural source that contains both microtubule-stabilizing and -destabilizing small molecules is unprecedented and suggests that the synergistic action of these compounds was exploited by nature long before it was discovered in the laboratory.