Model System Research Articles

Direct observation of photoinduced sequential spin transition in a halogen-bonded hybrid system by complementary ultrafast optical and electron probes

A detailed understanding of the ultrafast dynamics of halogen-bonded materials is desired for designing supramolecular materials and tuning various electronic properties by external stimuli. Here, a prototypical halogen-bonded multifunctional material containing spin crossover (SCO) cations and paramagnetic radical anions is studied as a model system of photo-switchable SCO hybrid systems using ultrafast electron diffraction and two complementary optical spectroscopic techniques. Our results reveal a sequential dynamics from SCO to radical dimer softening, uncovering a key transient intermediate state. In combination with quantum chemistry calculations, we demonstrate the presence of halogen bonds in the low- and high-temperature phases and propose their role during the photoinduced sequential dynamics, underscoring the significance of exploring ultrafast dynamics. Our research highlights the promising utility of halogen bonds in finely tuning functional properties across diverse photoactive multifunctional materials.

Small electron polarons bound to interstitial tantalum defects in lithium tantalate

The absorption features of optically generated, short-lived small bound electron polarons are inspected in congruent lithium tantalate, LiTaO3 (LT), in order to address the question whether it is possible to localize electrons at interstitial Ta V :V Li defect pairs by strong, short-range electron–phonon coupling. Solid-state photoabsorption spectroscopy under light exposure and density functional theory are used for an experimental and theoretical access to the spectral features of small bound polaron states and to calculate the binding energies of the small bound Ta Li4+ (antisite) and Ta V4+ :V Li (interstitial site) electron polarons. As a result, two energetically well separated ( ΔE≈0.5 eV) absorption features with a distinct dependence on the probe light polarization and peaking at 1.6 eV and 2.1 eV are discovered. We contrast our results to the interpretation of a single small bound Ta Li4+ electron state with strong anisotropy of the lattice distortion and discuss the optical generation of interstitial Ta V4+ :V Li small polarons in the framework of optical gating of Ta V4+ :Ta Ta4+ bipolarons. We can conclude that the appearance of carrier localization at Ta V :V Li must be considered as additional intermediate state for the 3D hopping transport mechanisms at room temperature in addition to Ta Li , as well, and, thus, impacts a variety of optical, photoelectrical and electrical applications of LT in nonlinear photonics. Furthermore, it is envisaged that LT represents a promising model system for the further examination of the small-polaron based photogalvanic effect in polar oxides with the unique feature of two, energetically well separated small polaron states.

Mitophagy and cancer: role of BNIP3/BNIP3L as energetic drivers of stemness features, ATP production, proliferation, and cell migration.

Mitophagy is a selective form of autophagy which permits the removal of dysfunctional or excess mitochondria. This occurs as an adaptative response to physiological stressors, such as hypoxia, nutrient deprivation, or DNA damage. Mitophagy is promoted by specific mitochondrial outer membrane receptors, among which are BNIP3 and BNIP3L. The role of mitophagy in cancer is being widely studied, and more specifically in the maintenance of cancer stem cell (CSC) properties, such as self-renewal. Given that CSCs are responsible for treatment failure and metastatic capacity, targeting mitophagy could be an interesting approach for CSC elimination. Herein, we describe a new model system to enrich sub-populations of cancer cells with high basal levels of mitophagy, based on the functional transcriptional activity of BNIP3 and BNIP3L. Briefly, we employed a BNIP3(L)-promoter-eGFP-reporter system to isolate cancer cells with high BNIP3/BNIP3L transcriptional activity by flow cytometry (FACS). The model was validated by using complementary lysosomal and mitophagy-specific probes, as well as the mitochondrially-targeted red fluorescent protein (RFP), namely mt-Keima. High BNIP3/BNIP3L transcriptional activity was accompanied by increases in i) BNIP3/BNIP3L protein levels, ii) lysosomal mass, and iii) basal mitophagy activity. Furthermore, cancer cells with increased BNIP3/BNIP3L transcriptional activity exhibited CSC features, such as greater mammosphere-forming ability and high CD44 levels. To further explore the model, we also analysed other stemness characteristics in MCF7 and MDA-MB-231 breast cancer cell lines, directly demonstrating that BNIP3(L)-high cells were more metabolically active, proliferative, migratory, and drug-resistant, with elevated anti-oxidant capacity. Therefore, high levels of basal mitophagy appear to enhance CSC features.

Reconfigurable Chiral Spintronic THz Emitters

AbstractCollective spin arrangements manifest diverse spin textures, encompassing ferromagnetism, antiferromagnetism, and chiral vortices. However, mapping these spin textures in ultrathin magnetic multilayers has remained elusive. A reconfigurable chiral spintronic terahertz emission method is introduced through investigations on a model system of synthetic antiferromagnet and the spin information of individual ferromagnet (FM) layers is extracted. Upon femtosecond photoexcitation of the synthetic antiferromagnet (FM1/Ru/FM2), the ferromagnets generate a pair of linearly polarized ultrafast spin currents, which, after relaxation at the FM/Ru interface, emit corresponding THz pulses. The Ruderman–Kittel–Kasuya–Yosida interactions between the two FMs give rise to magnetic‐field‐controlled spin textures causing a spin relaxation imbalance at the interfaces and induce a phase shift between the orthogonal components of the emitted terahertz fields, consequently reconfiguring the polarization of the emitted terahertz field from linear to circular. This approach offers a novel means of investigating electronic and magnetic states in ultrathin spintronic heterostructures, low‐dimensional quantum materials, topological insulators, and Weyl semimetals. Furthermore, it enables the exploration of spin textures, including skyrmions, merons, and solitons.

Computational study of equilibria formed by diiodine (I2) and the pincer complex [2,6‐bis{(Me2NCH2)2}C6H3]PtIII: intramolecular mobility of I2 using 'Pt‐I2', 'Pt‐I···I2' and 'C para ···I2' species

DFT computation indicates the presence of equilibria with very low barriers when diiodine interacts with the square‐planar platinum(II) pincer complex Pt(NCN)I (NCN = [2,6‐bis{(dimethylamino)methyl}phenyl‐N,C,N]‐) in dichloromethane. Species present include square‐planar Pt(NCN)(η1‐I3) and square‐pyramidal Pt(NCN)I(η1‐I2) interconverted via a triangular transition state with I2 bridging a Pt‐I bond, and interaction of diiodine at the para‐position of the arene ring interconverted with Pt(NCN)I(η1‐I2) via a transition state with diiodine bridging the Cortho and Cmeta positions. Similar facile intramolecular rearrangements occur for a model system with a molar ratio of 1:2 for Pt:I2, exhibiting species such as Pt(NCN)(η1‐I3)(η1‐I2) and mobility of diiodine over the (pincer)PtI plane.

Impact of long-term temperature shifts on activated sludge microbiome dynamics and micropollutant removal

Micropollutants removal efficiency strongly vary across different aerobic wastewater treatment plants, resulting in their frequent detection in surface and ground waters. Seasonal temperature variation is a major factor influencing plant performance, but it is still unclear how prolonged periods of temperature change impact microbiome and micropollutant biotransformation. This work investigates the effect of long-term temperature variation on the microbial dynamics in an activated sludge system, and the impact on micropollutant biotransformation. Sequencing batch reactors were used as model system and 4–40 °C temperature range was studied. 16S rRNA amplicon sequencing showed that temperature drives microbial structure (gDNA) and activity (RNA), rather than time, and this was stronger below 15 °C and above 25 °C. The microbial community was richest and more diverse at 20 °C, while rarer and more specific taxa became predominant over time, at more extreme temperatures. This suggested that less abundant taxa might be responsible for maintaining the biotransformation capability in the activated sludge at extreme temperatures. Micropollutant biotransformation rates mostly deviated from the classic Arrhenius model below 15 °C and above 25 °C, indicating that prolonged exposure to temperature changes leads to temperature-induced taxonomic shifts, resulting in the emerging of different sets of biotransformation pathways over different temperature ranges.

Optimal photoelectron circular dichroism of a model chiral system.

We optimize the internuclear geometry and electronic structure of a model chiral system to achieve a maximal photoelectron circular dichroism (PECD) in its one-photon ionization by circularly polarized light. The electronic structure calculations are performed by the single center method, while the optimization is done using quantum alchemy employing a Taylor series expansion. Thereby, the effect of bond lengths and uncompensated charge distributions on the chiral response of the model is investigated theoretically in some detail. It is demonstrated that manipulating a chiral asymmetry of the ionic potential may enhance the dichroic parameter (i.e., the PECD) of the randomly oriented model system well beyond β1 = 25%. Furthermore, we demonstrate that quantum alchemy is applicable to PECD despite the unusually strong coupling of spatial and electronic degrees of freedom and discuss the relative impact of the individual degrees of freedom in this model system. We define the necessary conditions for the computational design of PECD for real (non-model) chiral molecules using our approach.

Genetic bias in repeated evolution of pigment loss in cave populations of the Asellus aquaticus species complex.

Similar phenotypes can evolve repeatedly under the same evolutionary pressures. A compelling example is the evolution of pigment loss and eye loss in cave-dwelling animals. While specific genomic regions or genes associated with these phenotypes have been identified in model species, it remains uncertain whether a bias towards particular genetic mechanisms exists. An isopod crustacean, Asellus aquaticus, is an ideal model organism to investigate this phenomenon. It inhabits surface freshwaters throughout Europe but has colonized groundwater on multiple independent occasions and evolved several cave populations with distinct ecomorphology. Previous studies have demonstrated that three different cave populations utilized common genetic regions, potentially the same genes, in the evolution of pigment and eye loss. Expanding on this, we conducted analysis on two additional cave populations, distinct either phylogenetically or biogeographically from those previously examined. We generated F2 hybrids from cave × surface crosses and tested phenotype-genotype associations, as well as conducted complementation tests by crossing individuals from different cave populations. Our findings revealed that pigment loss and orange eye pigment in additional cave populations were associated with the same genomic regions as observed in the three previously tested cave populations. Moreover, the lack of complementation across all cross combinations suggests that the same gene likely drives pigment loss. These results substantiate a genetic bias in the recurrent evolution of pigment loss in this model system. Future investigations should focus on the cause behind this bias, possibly arising from allele recruitment from ancestral surface populations' genetic variation or advantageous allele effects via pleiotropy.

Spatiotemporally distinct responses to mechanical forces shape the developing seed of Arabidopsis.

Organ morphogenesis depends on mechanical interactions between cells and tissues. These interactions generate forces that can be sensed by cells and affect key cellular processes. However, how mechanical forces, together with biochemical signals, contribute to the shaping of complex organs is still largely unclear. We address this question using the seed of Arabidopsis as a model system. We show that seeds first experience a phase of rapid anisotropic growth that is dependent on the response of cortical microtubule (CMT) to forces, which guide cellulose deposition according to shape-driven stresses in the outermost layer of the seed coat. However, at later stages of development, we show that seed growth is isotropic and depends on the properties of an inner layer of the seed coat that stiffens its walls in response to tension but has isotropic material properties. Finally, we show that the transition from anisotropic to isotropic growth is due to the dampening of cortical microtubule responses to shape-driven stresses. Altogether, our work supports a model in which spatiotemporally distinct mechanical responses control the shape of developing seeds in Arabidopsis.

Industrial Park low-carbon energy system planning framework: Heat pump based energy conjugation between industry and buildings

The accelerating urbanization, rapid industrial development, and excessive consumption of fossil fuels pose survival challenges such as energy depletion and environmental degradation for humanity. In the context of industrial park development, constructing a low-carbon energy system, increasing the proportion of renewable energy, enhancing energy-level matching, and utilizing heat pumps for deep waste heat recovery are effective approaches to reduce fossil energy consumption and alleviate environmental pressures. Addressing issues such as diverse thermal flows in industrial sites, complex electricity-heat-cooling energy demands, and unclear industrial-building energy coupling mechanisms, this paper proposes a two-stage planning framework, comprising the following five steps: (1) constructing a waste heat utilization system centered around heat pumps, (2) establishing a mechanism for matching heat sources, equipment, and thermal sinks, (3) establishing an energy conversion model and energy quality quantification system, (4) optimizing waste heat utilization path allocation, and (5) conducting a system energy flow analysis. Case studies demonstrate that the proposed system achieves optimized matching of multiple heat sources and sinks in industrial and building scenarios through thermal integration, meeting diverse energy demands in the park, including electricity, cooling, and multi-grade heat. After coupling with traditional steam pipeline networks, the annual total cost and annual steam power consumption decrease by 33% and 39% respectively, with a waste heat contribution rate of up to 26% and a renewable energy penetration rate of up to 25%, and a waste heat recovery system payback period of 6 years. By establishing an energy quality quantification system and conducting multi-objective optimization considering losses and economic costs, this paper provides Pareto frontier solutions, offering references for engineering proposals. The proposed networked waste heat recovery system is characterized by low energy consumption and high economic efficiency, effectively integrating the energy characteristics of industrial parks and demonstrating engineering applicability.

Myeloid Targeted Human MLL-ENL and MLL-AF9 Induces cdk9 and bcl2 Expression in Zebrafish Embryos.

Acute myeloid leukemia (AML) accounts for greater than twenty thousand new cases of leukemia annually in the United States. The average five-year survival rate is approximately 30%, pointing to the need for developing novel model systems for drug discovery. In particular, patients with chromosomal rearrangements in the mixed lineage leukemia (MLL) gene have higher relapse rates with poor outcomes. In this study we investigated the expression of human MLL-ENL and MLL-AF9 in the myeloid lineage of zebrafish embryos. We observed an expansion of MLL positive cells and determined these cells colocalized with the myeloid markers spi1b, mpx, and mpeg. In addition, expression of MLL-ENL and MLL-AF9 induced the expression of endogenous bcl2 and cdk9, genes that are often dysregulated in MLL-r-AML. Co-treatment of lyz: MLL-ENL or lyz:MLL-AF9 expressing embryos with the BCL2 inhibitor, Venetoclax, and the CDK9 inhibitor, Flavopiridol, significantly reduced the number of MLL positive cells compared to embryos treated with vehicle or either drug alone. In addition, cotreatment with Venetoclax and Flavopiridol significantly reduced the expression of endogenous mcl1a compared to vehicle, consistent with AML. This new model of MLL-r-AML provides a novel tool to understand the molecular mechanisms underlying disease progression and a platform for drug discovery.

Universal Dimensionality of Ferroelectric Domain Walls in Ultrathin Films

AbstractThe dimensionality of dynamic interfaces—domain walls (DWs) —is greatly influenced by symmetry and physical dimensions, irrespective of the microscopic details of the system. To address this fundamental question for the ferroelectric model system, the DW scaling criticality and dimensionality is investigated in ultrathin films of varied ferroelectric materials, compositions, and electrode–ferroelectric interfaces, grown on nominally flat and vicinal substrates. In spite of significant variations among ferroelectric systems, the observed prevalence of 1D DWs is consistent with a random bond disorder, elucidated through a scenario of 2D nucleation and growth‐driven DW creep. These findings highlight the thickness size‐dominated universal behavior of ferroelectric DWs, uncovering fascinating prospects for dimensionally engineered DW‐based nanoelectronics.

Eigenvalue spectra of finely structured random matrices

Random matrix theory allows for the deduction of stability criteria for complex systems using only a summary knowledge of the statistics of the interactions between components. As such, results like the well-known elliptical law are applicable in a myriad of different contexts. However, it is often assumed that all components of the complex system in question are statistically equivalent, which is unrealistic in many applications. Here we introduce the concept of a finely structured random matrix. These are random matrices with element-specific statistics, which can be used to model systems in which the individual components are statistically distinct. By supposing that the degree of “fine structure” in the matrix is small, we arrive at a succinct “modified” elliptical law. We demonstrate the direct applicability of our results to the niche and cascade models in theoretical ecology, as well as a model of a neural network, and a directed network with arbitrary degree distribution. The simple closed form of our central results allow us to draw broad qualitative conclusions about the effect of fine structure on stability. Published by the American Physical Society 2024

Conserved molecular recognition by an intrinsically disordered region in the absence of sequence conservation.

Intrinsically disordered regions (IDRs) are critical for cellular function yet often appear to lack sequence conservation when assessed by multiple sequence alignments. This raises the question of if and how function can be encoded and preserved in these regions despite massive sequence variation. To address this question, we have applied coarse-grained molecular dynamics simulations to investigate non-specific RNA binding of coronavirus nucleocapsid proteins. Coronavirus nucleocapsid proteins consist of multiple interspersed disordered and folded domains that bind RNA. Here, we focus on the first two domains of coronavirus nucleocapsid proteins: the disordered N-terminal domain (NTD) and the folded RNA binding domain (RBD). While the NTD is highly variable across evolution, the RBD is structurally conserved. This combination makes the NTD-RBD a convenient model system for exploring the interplay between an IDR adjacent to a folded domain and how changes in IDR sequence can influence molecular recognition of a partner. Our results reveal a surprising degree of sequence-specificity encoded by both the composition and the precise order of the amino acids in the NTD. The presence of an NTD can - depending on the sequence - either suppress or enhance RNA binding. Despite this sensitivity, large-scale variation in NTD sequences is possible while certain sequence features are retained. Consequently, a conformationally-conserved dynamic and disordered RNA:protein complex is found across nucleocapsid protein orthologs despite large-scale changes in both NTD sequence and RBD surface chemistry. Taken together, these insights shed light on the ability of disordered regions to preserve functional characteristics despite their sequence variability.

RoPod, a customizable toolkit for non-invasive root imaging, reveals cell type-specific dynamics of plant autophagy

Arabidopsis root is a classic model system in plant cell and molecular biology. The sensitivity of plant roots to local environmental perturbation challenges data reproducibility and incentivizes further optimization of imaging and phenotyping tools. Here we present RoPod, an easy-to-use toolkit for low-stress live time-lapse imaging of Arabidopsis roots. RoPod comprises a dedicated protocol for plant cultivation and a customizable 3D-printed vessel with integrated microscopy-grade glass that serves simultaneously as a growth and imaging chamber. RoPod reduces impact of sample handling, preserves live samples for prolonged imaging sessions, and facilitates application of treatments during image acquisition. We describe a protocol for RoPods fabrication and provide illustrative application pipelines for monitoring root hair growth and autophagic activity. Furthermore, we showcase how the use of RoPods advanced our understanding of plant autophagy, a major catabolic pathway and a key player in plant fitness. Specifically, we obtained fine time resolution for autophagy response to commonly used chemical modulators of the pathway and revealed previously overlooked cell type-specific changes in the autophagy response. These results will aid a deeper understanding of the physiological role of autophagy and provide valuable guidelines for choosing sampling time during end-point assays currently employed in plant autophagy research.

RhoMax: Computational Prediction of Rhodopsin Absorption Maxima Using Geometric Deep Learning.

Microbial rhodopsins (MRs) are a diverse and abundant family of photoactive membrane proteins that serve as model systems for biophysical techniques. Optogenetics utilizes genetic engineering to insert specialized proteins into specific neurons or brain regions, allowing for manipulation of their activity through light and enabling the mapping and control of specific brain areas in living organisms. The obstacle of optogenetics lies in the fact that light has a limited ability to penetrate biological tissues, particularly blue light in the visible spectrum. Despite this challenge, most optogenetic systems rely on blue light due to the scarcity of red-shifted opsins. Finding additional red-shifted rhodopsins would represent a major breakthrough in overcoming the challenge of limited light penetration in optogenetics. However, determining the wavelength absorption maxima for rhodopsins based on their protein sequence is a significant hurdle. Current experimental methods are time-consuming, while computational methods lack accuracy. The paper introduces a new computational approach called RhoMax that utilizes structure-based geometric deep learning to predict the absorption wavelength of rhodopsins solely based on their sequences. The method takes advantage of AlphaFold2 for accurate modeling of rhodopsin structures. Once trained on a balanced train set, RhoMax rapidly and precisely predicted the maximum absorption wavelength of more than half of the sequences in our test set with an accuracy of 0.03 eV. By leveraging computational methods for absorption maxima determination, we can drastically reduce the time needed for designing new red-shifted microbial rhodopsins, thereby facilitating advances in the field of optogenetics.

Dose-dependent effects of Dnmt3a in an inducible murine model of KrasG12D-driven leukemia

DNMT3A mutations are frequently found in clonal hematopoiesis and a variety of hematologic malignancies, including acute myeloid leukemia. An assortment of mouse models have been engineered to explore the tumorigenic potential and malignant lineage bias due to loss of function of DNMT3A in consort with commonly comutated genes in myeloid malignancies, such as Flt3, Nras, Kras, and c-Kit. We employed several tamoxifen-inducible Cre-ERT2 murine model systems to study the effects of constitutively active KrasG12D-driven myeloid leukemia (Kras) development together with heterozygous (3aHet) or homozygous Dnmt3a deletion (3aKO). Due to the rapid generation of diverse nonhematologic tumors appearing after tamoxifen induction, we employed a transplantation model. With pretransplant tamoxifen induction, most Kras mice died quickly of T-cell malignancies regardless of Dnmt3a status. Using posttransplant induction, we observed a dose-dependent effect of DNMT3A depletion that skewed the leukemic phenotype toward a myeloid lineage. Specifically, 64% of 3aKO/Kras mice had exclusively myeloid disease compared with 36% of 3aHet/Kras and only 13% of Kras mice. Here, 3aKO combined with Kras led to increased disease burden, multiorgan infiltration, and faster disease progression. DOT1L inhibition exerted profound antileukemic effects in malignant 3aKO/Kras cells, but not malignant cells with Kras mutation alone, consistent with the known sensitivity of DNMT3A-mutant leukemia to DOT1L inhibition. RNAseq from malignant myeloid cells revealed that biallelic Dnmt3a deletion was associated with loss of cell-cycle regulation, MYC activation, and TNF⍺ signaling. Overall, we developed a robust model system for mechanistic and preclinical investigations of acute myeloid leukemia with DNMT3A and Ras-pathway lesions.

An Efficient Sulfadiazine Selection Scheme for Stable Transformation in the Model Liverwort Marchantia polymorpha.

Plant macroevolutionary studies leverage the phylogenetic position of non-flowering model systems like the liverwort Marchantia polymorpha to investigate the origin and evolution of key plant processes. To date, most molecular genetic studies in Marchantia rely on hygromycin and/or chlorsulfuron herbicide resistance markers for the selection of stable transformants. Here, we use a sulfonamide-resistant dihydropteroate synthase (DHPS) gene to enable sulfadiazine-based transformation selection in M. polymorpha. We demonstrate the reliability of sulfadiazine selection on its own and in combination with existing hygromycin and chlorsulfuron selection schemes through transgene stacking experiments. The utility of this system is further demonstrated through confocal microscopy of a triple transgenic line carrying fluorescent proteins labelling the plasma membrane, cortical microtubules, and the nucleus. Collectively, our findings and resources broaden the capacity to genetically manipulate the increasingly popular model liverwort M. polymorpha.

Animal models to study cognitive impairment of chronic kidney disease.

Mild cognitive impairment (MCI) is common in people with chronic kidney disease (CKD), and its prevalence increases with progressive loss of kidney function. MCI is characterized by a decline in cognitive performance greater than expected for an individual age and education level but with minimal impairment of instrumental activities of daily living. Deterioration can affect one or several cognitive domains (attention, memory, executive functions, language, and perceptual motor or social cognition). Given the increasing prevalence of kidney disease, more and more people with CKD will also develop MCI causing an enormous disease burden for these individuals, their relatives, and society. However, the underlying pathomechanisms are poorly understood, and current therapies mostly aim at supporting patients in their daily lives. This illustrates the urgent need to elucidate the pathogenesis and potential therapeutic targets and test novel therapies in appropriate preclinical models. Here, we will outline the necessary criteria for experimental modeling of cognitive disorders in CKD. We discuss the use of mice, rats, and zebrafish as model systems and present valuable techniques through which kidney function and cognitive impairment can be assessed in this setting. Our objective is to enable researchers to overcome hurdles and accelerate preclinical research aimed at improving the therapy of people with CKD and MCI.

Chimeric states induced by higher-order interactions in coupled prey-predator systems.

Higher-order interactions have been instrumental in characterizing the intricate complex dynamics in a diverse range of large-scale complex systems. Our study investigates the effect of attractive and repulsive higher-order interactions in globally and non-locally coupled prey-predator Rosenzweig-MacArthur systems. Such interactions lead to the emergence of complex spatiotemporal chimeric states, which are otherwise unobserved in the model system with only pairwise interactions. Our model system exhibits a second-order transition from a chimera-like state (mixture of oscillating and steady state nodes) to a chimera-death state through a supercritical Hopf bifurcation. The origin of these states is discussed in detail along with the effect of the higher-order non-local topology which leads to the rise of a distinct and dynamical state termed as "amplitude-mediated chimera-like states." Our study observes that the introduction of higher-order attractive and repulsive interactions exhibit incoherence and promote persistence in consumer-resource population dynamics as opposed to susceptibility shown by synchronized dynamics with only pairwise interactions, and these results may be of interest to conservationists and theoretical ecologists studying the effect of competing interactions in ecological networks.