Diversity and development of domatia: Symbiotic plant structures to host mutualistic ants or mites.

Across the tree of life, specialized structures that offer nesting sites to ants or mites - known as domatia - have evolved independently hundreds of times, facilitating ecologically important defence and/or nutritional mutualisms. Domatia show remarkable diversity in morphology and developmental origin. Here we review the morpho-anatomical diversity of domatia, aiming to unveil the primary mechanisms governing their development. We propose hypotheses to explain the formation of these structures, based on anatomical studies of domatia and developmental genetic analyses in model species. While genes involved in domatium formation are so far unknown, domatia appear to originate via spatiotemporal shifts in the expression of common developmental genetic pathways. Our review paves the way to the genetic dissection of domatium development.

ECG arrhythmia classification based on the fast ant colony clustering algorithm with improved spatiotemporal feature perception ability.

Electrocardiograph (ECG) is one of the most critical physiological signals used for arrhythmia diagnosis. In recent years, ECG arrhythmia classification devices consisting of multi-module sensors, clustering algorithms and neural networks play an important role in monitoring and diagnosing cardiovascular diseases. However, the commonly used ECG arrhythmia classification methods are still facing some problems such as the complex model structure and long running time. To address the above problems, this paper proposes an ECG arrhythmia classification method based on the fast ant colony clustering algorithm with improved spatiotemporal feature perception ability (SFP-FACC), which uses LSTM to fit the cluster centers and avoids the time consumption of updating the cluster centers during the classification process. The spatiotemporal feature perception ability of this model with the dynamic time warping (DTW) algorithm is improved. The classification is achieved by applying the combination of Euclidean distance and DTW. The convergence speed of the model is improved by using dynamic pheromone volatility coefficient; and finally the optimal solution of the model is determined by using radix sort. Based on the MIT-BIH arrhythmia dataset, the overall accuracy of the proposed classification method in this paper achieves 99.04 %, and even the accuracy of certain types of classification achieves 100 %, and the running time is about 3.5 times faster than that of the basic models. The experiments show that the method proposed in this paper has certain advantages.

Intelligent cardiovascular disease diagnosis using deep learning enhanced neural network with ant colony optimization.

To identify patterns in big medical datasets and use Deep Learning and Machine Learning (ML) to reliably diagnose Cardio Vascular Disease (CVD), researchers are currently delving deeply into these fields. Training on large datasets and producing highly accurate validation results is exceedingly difficult. Furthermore, early and precise diagnosis is necessary due to the increased global prevalence of cardiovascular disease (CVD). However, the increasing complexity of healthcare datasets makes it challenging to detect feature connections and produce precise predictions. To address these issues, the Intelligent Cardiovascular Disease Diagnosis based on Ant Colony Optimisation with Enhanced Deep Learning (ICVD-ACOEDL) model was developed. This model employs feature selection (FS) and hyperparameter optimization to diagnose CVD. Applying a min-max scaler, medical data is first consistently prepared. The key feature that sets ICVD-ACOEDL apart is the use of Ant Colony Optimisation (ACO) to select an optimal feature subset, which in turn helps to upgrade the performance of the ensuring deep learning enhanced neural network (DLENN) classifier. The model reforms the hyperparameters of DLENN for CVD classification using Bayesian optimization. Comprehensive evaluations on benchmark medical datasets show that ICVD-ACOEDL exceeds existing techniques, indicating that it could have a significant impact on CVD diagnosis. The model furnishes a workable way to increase CVD classification efficiency and accuracy in real-world medical situations by incorporating ACO for feature selection, min-max scaling for data pre-processing, and Bayesian optimization for hyperparameter tweaking.

Eco-Morphological Responses of Camponotus japonicus (Hymenoptera: Formicidae) to Varied Climates and Habitats.

Ants are a highly adaptable group of insects that have globally established themselves in diverse climates and habitats. This study investigates the influence of climate and habitat on the morphological traits of Camponotus japonicus across 22 sites in mainland China. These sites span three climate zones (mid-temperate, warm temperate, and subtropical) and three habitat types (urban parks, farmlands, and sparse woodlands). Principal component analysis (PCA) was used to determine the principal axis of morphological variation, while hypervolume analysis and centroid distance calculation were used to verify the environmental filtering hypothesis and the optimal transfer hypothesis. The results support both hypotheses showing that climate and habitat significantly affect the morphological space of C. japonicus workers. In particular, the morphological space is more constrained in mid-temperate farmlands, while workers in sparse woodlands exhibit greater morphological variation. In contrast, urban parks are characterized by higher stability and reduced morphological differences. Additionally, robust regression analysis reveals that environmental factors such as temperature, precipitation, humidity, and altitude are closely linked to the morphological traits of the workers. Understanding how ant morphology responds to external environmental changes enhances our understanding of their adaptability and their essential ecological roles across various ecosystems.

The urban island: climatic suitability of Linepithema humile (Hymenoptera: Formicidae) and the role of cities in the invasion of the Western Palearctic.

Urban environments often present environmental conditions that facilitate the introduction and establishment of nonnative and invasive species. These can expand their range into areas with unfavorable climates by taking advantage of the ecological and climatic homogenization of cities, bypassing the ecological barriers presented by the surrounding environment. One way to monitor the expansion of these species is using potential distribution models. We used as a model species the Argentine ant, Linepithema humile (Hymenoptera: Formicidae) whose invasion has caused serious consequences for biodiversity and economic losses worldwide. We used the average result of six different algorithms and used climatic variables and population density as a proxy for the urbanization level in the Western Palearctic to build the predictive model. The model indicates this ant prefers to inhabit areas with Mediterranean and Temperate Oceanic climates and that its suitability depends on two main factors: the continentality (temperature annual range) and the degree of urbanization. The species is predicted to be absent in areas with large temperature contrasts throughout the year, particularly in rural and peri-urban areas (i.e. adjacent to urban areas) of inland regions. Conversely, the species has a predilection for coastal and urban areas where environmental conditions are attenuated by the influence of the sea or the "urban heat island" effect in the case of inland cities. In this sense, cities act as "bioclimatic islands" facilitating the establishment of the Argentine ant as a reservoir, enlarging its distribution into climatically nonoptimal areas, and promoting its future expansion in a scenario of global warming and socioeconomic change.

Deciphering the evolution and biogeography of ant-ferns Lecanopteris s.s.

Southeast Asia is a biodiversity hotspot characterized by a complex paleogeography, and its Polypodiopsida flora is particularly diverse. While hybridization is recognized as common in ferns, further research is needed to investigate the relationship between hybridization events and fern diversity. Lecanopteris s.s., an ant-associated fern, has been subject to debate regarding species delimitations primarily due to limited DNA markers and species sampling. Our study integrates 22 newly generated plastomes, 22 transcriptomes, and flow cytometry of all native species along with two cultivated hybrids. Our objective is to elucidate the reticulate evolutionary history within Lecanopteris s.s. through the integration of phylobiogeographic reconstruction, gene flow inference, and genome size estimation. Key findings of our study include: (1) An enlarged plastome size (178-187 Kb) in Lecanopteris s.s., attributed to extreme expansion of the Inverted Repeat (IR) regions; (2) The traditional 'pumila' and 'crustacea' groups are paraphyletic; (3) Significant cytonuclear discordance attributed to gene flow; (4) Natural hybridization and introgression in the 'pumila' and 'darnaedii' groups; (5) L. luzonensis is the maternal parent of L. 'Yellow Tip', with L. pumila suggested as a possible paternal parent; (6) L. 'Tatsuta' is a hybrid between L. luzonensis and L. crustacea; (7) Lecanopteris s.s. first diverged during the Neogene and then during the middle Miocene climatic optimum in the Indochina and Sundaic regions. In conclusion, the biogeographic history and speciation of Lecanopteris have been profoundly shaped by past climate changes and geodynamics of Southeast Asia. Dispersals, hybridization and introgression between species act as pivotal factors in the evolutionary trajectory of Lecanopteris s.s.. This research provides a robust framework for further exploration and understanding of the complex dynamics driving the diversification and distribution patterns within Polypodiaceae subfamily Microsoroideae.

An Illustrative Approach to Removing Conjunctival Bitten Ant Foreign Body.

An animate ocular foreign body poses a challenging situation for the ophthalmologist for its complete removal. Incomplete removal may lead to infection and inflammation. A woman in her 50s presented with a history of an ocular foreign body in her left eye while working in the agricultural land. On examination, there was conjunctival congestion and a copious amount of thick secretion in the inferonasal region of the conjunctiva. There was a dark black dot in the red body embedded in the secretion, which aroused my suspicion of an animate object (the red ant). In an animate ocular foreign body, complete removal is warranted to prevent infection and inflammation. Hence, the thick secretion that hid the animate object's body was gently removed using cotton tip applicators, and a part of the dead red ant bitten to the conjunctiva was visible. Initially, we tried to remove it using a cotton tip applicator but failed. In order to remove it completely, we tried to remove it using plain forceps, which were successfully removed by grabbing its head under a slit-lamp examination. The ant was sent to the parasitology department, which ensured the complete removal of the ant in the presence of its mandible. The patient was completely relieved of the symptoms and signs at the one-week follow-up. In this case report, we illustrate our stepwise approach to the management of a conjunctival bitten dead ant foreign body for its complete removal with a photo and video demonstration.

Skin lesion segmentation using deep learning algorithm with ant colony optimization.

BACKGROUND: Segmentation of skin lesions remains essential in histological diagnosis and skin cancer surveillance. Recent advances in deep learning have paved the way for greater improvements in medical imaging. The Hybrid Residual Networks (ResUNet) model, supplemented with Ant Colony Optimization (ACO), represents the synergy of these improvements aimed at improving the efficiency and effectiveness of skin lesion diagnosis. OBJECTIVE: This paper seeks to evaluate the effectiveness of the Hybrid ResUNet model for skin lesion classification and assess its impact on optimizing ACO performance to bridge the gap between computational efficiency and clinical utility. METHODS: The study used a deep learning design on a complex dataset that included a variety of skin lesions. The method includes training a Hybrid ResUNet model with standard parameters and fine-tuning using ACO for hyperparameter optimization. Performance was evaluated using traditional metrics such as accuracy, dice coefficient, and Jaccard index compared with existing models such as residual network (ResNet) and U-Net. RESULTS: The proposed hybrid ResUNet model exhibited excellent classification accuracy, reflected in the noticeable improvement in all evaluated metrics. His ability to describe complex lesions was particularly outstanding, improving diagnostic accuracy. Our experimental results demonstrate that the proposed Hybrid ResUNet model outperforms existing state-of-the-art methods, achieving an accuracy of 95.8%, a Dice coefficient of 93.1%, and a Jaccard index of 87.5. CONCLUSION: The addition of ResUNet to ACO in the proposed Hybrid ResUNet model significantly improves the classification of skin lesions. This integration goes beyond traditional paradigms and demonstrates a viable strategy for deploying AI-powered tools in clinical settings. FUTURE WORK: Future investigations will focus on increasing the version's abilities by using multi-modal imaging information, experimenting with alternative optimization algorithms, and comparing real-world medical applicability. There is also a promising scope for enhancing computational performance and exploring the model's interpretability for more clinical adoption.

Ant colony optimization: A bibliometric review.

This paper is a follow-up of one of the most-cited articles published in the first 20 years of the existence of Physics of Life Reviews. The specific topic is "ant colony optimization", which is a metaheuristic for solving challenging optimization problems. Due to its inspiration from natural ant colonies' shortest path-finding behavior, this optimization technique forms part of a larger field known as swarm intelligence. After a short introduction to ant colony optimization, we first provide a chronology focusing on algorithmic developments rather than applications. The main part of the paper deals with a bibliometric study of the ant colony optimization literature. Interesting trends concerning, for example, the geographic origin of publications and the change in research focus over time, can be learned from the presented graphs and numbers.

[Effects of ant nesting on seasonal dynamics of soil CH4 emissions in a tropical rubber-plantation forest]. / 蚂蚁筑巢对热带橡胶人工林土壤甲烷排放季节动态的影响.

Ant nests can affect the process and seasonal dynamics of forest soil methane emissions through mediating methane oxidation/reduction microorganisms and physicochemical environments. To explore the process and mechanism by which ant nests affect soil methane emissions from Hevea brasiliensis plantation in Xishuangbanna, we measured the seasonal dynamics of methane emissions from ant nest and non-nest soils by using static chamber-gas chromatography method, and analyzed the effect of ant nesting on the changes in functional microbial diversity, microhabitats, and soil nutrients in the plantations. The results showed that: 1) Ant nests significantly affected the mean annual soil methane emissions in tropical plantation. Methane emissions in ant nest were decreased by 59.9% than the non-nest soil. In the dry season, ant nest soil was a methane sink (-1.770 µg·m-2·h-1), which decreased by 87.2% compared with the non-nest soil, while it was a methane source (0.703 µg·m-2·h-1) that increased by 152.7% in the wet season. 2) Ant nesting affected methane emissions via changing soil temperature, humidity, carbon and nitrogen concentrations. In contrast to the control, the mean annual temperature, humidity, and carbon and nitrogen content increased by 4.9%-138.5% in ant nest soils, which explained 90.1%, 97.3%, 27.3%-90.0% of the variation in methane emissions, respectively. 3) Ant nesting affected the emission dynamics through changing the diversity and community structure of methane functional microbe. Compared with the control, the average annual methanogen diversity (Ace, Chao1, Shannon, and Simpson indices) in the ant nest ranged from -9.9% to 61.2%, which were higher than those (-8.7%-31.2%) of the methane-oxidising bacterial communities. The relative abundance fluctuations of methanogens and methanotrophic bacteria were 46.76% and -6.33%, respectively. The explaining rate of methanogen diversity to methane emissions (78.4%) was higher than that of oxidizing bacterial diversity (54.5%), the relative abundance explained by the dominant genus of methanogens was 68.9%. 4) The structural equation model showed that methanogen diversity, methanotroph diversity, and soil moisture were the main factors controlling methane emissions, contributing 95.6%, 95.0%, and 91.2% to the variations of emissions, respectively. The contribution (73.1%-87.7%) of soil temperature and carbon and nitrogen components to the emission dynamics was ranked the second. Our results suggest that ant nesting mediates the seasonal dynamics of soil methane emissions, primarily through changing the diversity of methane-function microorganisms and soil water conditions. The research results deepen the understanding of the mechanism of biological regulation of methane emission in tropical forest soil.

Using Entropy as the Convergence Criteria of Ant Colony Optimization and the Application at Gene Chip Data Analysis.

INTRODUCTION: When Ant Colony Optimization algorithm (ACO) is adept at identifying the shortest path, the temporary solution is uncertain during the iterative process. All temporary solutions form a solution set. METHOD: Where each solution is random. That is, the solution set has entropy. When the solution tends to be stable, the entropy also converges to a fixed value. Therefore, it was proposed in this paper that apply entropy as a convergence criterion of ACO. The advantage of the proposed criterion is that it approximates the optimal convergence time of the algorithm. RESULTS: In order to prove the superiority of the entropy convergence criterion, it was used to cluster gene chip data, which were sampled from patients of Alzheimer's Disease (AD). The clustering algorithm is compared with six typical clustering algorithms. The comparison shows that the ACO using entropy as a convergence criterion is of good quality. CONCLUSION: At the same time, applying the presented algorithm, we analyzed the clustering characteristics of genes related to energy metabolism and found that as AD occurs, the entropy of the energy metabolism system decreases; that is, the system disorder decreases significantly.

A surgical site abscess caused by an ant bite on foot 7 years after mastectomy: A case report.

Key Clinical Message: Abscess at a previous surgical site induced by an insect bite has rarely been reported. Here we report a case of abscess at the breast surgical site, which occurred 7 years after mastectomy following an ant bite. Abstract: Surgical site abscess generally occurs following operation within 30 days. However, surgical site abscess induced by an insect bite, which occurs several years after surgery, has rarely been reported. Here, we report a 65-year-old female patient with a history of breast cancer presenting with an abscess at the site of her mastectomy and ipsilateral arm lymphedema. Her left foot was bitten by an ant 25 days earlier and itchy red bumps with whiteheads were raised. After antibiotic treatment and abscess incision and drainage, the abscess healed, but the ipsilateral arm lymphedema persisted. This unique case demonstrates that surgical procedures can alter the susceptibility of tissues to allergic or infectious cues long after the operation.

Two +ssRNA mycoviruses cohabiting the fungal cultivar of leafcutter ants.

Leafcutter ants are dominant herbivores in the Neotropics and rely on a fungus (Leucoagaricus gongylophorus) to transform freshly gathered leaves into a source of nourishment rather than consuming the vegetation directly. Here we report two virus-like particles that were isolated from L. gongylophorus and observed using transmission electron microscopy. RNA sequencing identified two +ssRNA mycovirus strains, Leucoagaricus gongylophorus tymo-like virus 1 (LgTlV1) and Leucoagaricus gongylophorus magoulivirus 1 (LgMV1). Genome annotation of LgTlV1 (7401 nt) showed conserved domains for methyltransferase, endopeptidase, viral RNA helicase, and RNA-dependent RNA polymerase (RdRp). The smaller genome of LgMV1 (2636 nt) contains one open reading frame encoding an RdRp. While we hypothesize these mycoviruses function as symbionts in leafcutter farming systems, further study will be needed to test whether they are mutualists, commensals, or parasites.

Fipronil-infused sodium polyacrylate gels provide effective management of Argentine ants in conservation areas.

BACKGROUND: Various types of hydrogel compounds have recently been developed for controlling invasive and pest ants in a range of environmental settings including agricultural, urban and natural areas. The current study evaluated the potential of sodium polyacrylate (ACR) hydrogels to effectively deliver liquid baits to Argentine ants. RESULTS: Relative to standard polyacrylamide (PAM) hydrogels, individual ACR hydrogel particles were approximately five-fold heavier; this may affect how ants interact with the bait particles, and further influence bait uptake and efficacy. Additionally, ACR hydrogels had significantly higher water absorption capacity and significantly slower rate of water loss, especially during the first 2 h. The efficacy of ACR hydrogel bait containing 0.005% fipronil and various attractants was evaluated on laboratory colonies. Results demonstrated that ACR hydrogel acceptance is significantly increased by the addition of feeding attractants. In addition, a field trial was performed in a nature reserve invaded by Argentine ants to evaluate the efficacy of ACR hydrogel bait. The field trial demonstrated that ACR hydrogel bait containing 0.005% fipronil with various attractants is highly effective and that ant densities throughout the baited plots declined by >99% within 7 days. CONCLUSIONS: The results of this study demonstrate that: (i) fipronil is highly effective for Argentine ant control in natural areas when used in low concentrations (0.005%); (ii) ACR hydrogels are an effective tool for delivering liquid baits to Argentine ants; and (iii) hydrogel baits augmented with various attractants including salt, protein and pheromone are highly attractive to Argentine ants. © 2024 The Author(s). Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Consumers' Behavioral Willingness to Use Green Financial Products: An Empirical Study within a Theoretical Framework.

In an era marked by the expansion of the Internet economy and the intensification of environmental concerns, the convergence of digital finance and green finance has emerged as a significant global trend. China's Alipay Ant Forest, an innovative green financial product, has successfully quantified carbon emission reductions resulting from users' green consumption patterns, establishing the first carbon account-based green financial product and pioneering an innovative "green finance plus gamification" model. However, the academic literature has not fully explained the underlying mechanisms that drive consumer engagement with such green financial products. This study, motivated by the academic question of what factors influence consumers' willingness to use green financial products, employs Ant Forest as a case study and develops a novel structural equation model based on self-determination theory, customer-perceived value, and the technology acceptance model. The model incorporates user type as a control variable and considers autonomy, gamification, and bonuses as key independent variables, with customer-perceived value serving as a mediating variable. Data collection involved 606 participants, enabling a comprehensive analysis of the factors influencing users' willingness to engage with green financial products. The findings support the proposed hypothesis, identifying several significant predictors of users' willingness to use green financial products, with the exception of age. This study advances the theoretical understanding of consumer behavior towards green financial products by integrating self-determination theory, customer-perceived value, and the technology acceptance model, while also offering practical insights for marketing strategies. It explores the interface between digital finance, environmental sustainability, and consumer behavior, highlighting opportunities for financial institutions to leverage Internet applications to promote green financial services and enhance their marketing approaches to influence consumer adoption.

How online pro-environmental games affect users' pro-environmental behavioural intentions? - Insights from Ant Forest.

Information technology has created new ways for people to participate in environmental protection. Ant Forest, a pro-environmental game that actively encourages users to take part in offline environmental activities through online gaming content, has gained great popularity. However, research in this area is still limited, and the effect of playing such games on users' pro-environmental intentions in real life and the underlying mechanisms are unknown. Therefore, this research draws from Persuasive Systems Design model and value theory and examines the relationships between design features of Ant Forest, users' values and their pro-environmental behavioural intentions. The research model is empirically tested by survey data from 428 Ant Forest users. Results indicate that users' self-enhancement values, including utilitarian, hedonic and social values, and self-transcendence values, including altruistic and biospheric values, all positively affect their continued gameplay intentions and therefore affect their pro-environmental behavioural intentions. Additionally, the primary task support, social support, dialogue support, and system credibility of Ant Forest have varying positive effects on users' perceived values.

Unlocking synergies of drawdown operation: Multi-objective optimization of reservoir emergency storage capacity.

Optimizing reservoir drawdown operations holds significant implications for hydropower generation, water supply, and drought mitigation strategies. However, achieving multi-objective optimization in reservoir drawdown operations poses fundamental challenges, particularly considering emergency storage capacity and seasonal drought patterns. This study introduces a novel multi-objective optimization framework tailored for a mega reservoir, focusing on drawdown operations to enhance hydropower generation and water supply reliability. A drawdown operation model leveraging a multi-objective ant lion optimizer is developed to simultaneously maximize reservoir hydropower output and minimize water shortage rates. China's Three Gorges Reservoir (TGR), situated over the upper reaches of the Yangtze River, constitutes the case study, with the standard operation policy (SOP) serving as a benchmark. Results showcase the efficacy of the proposed method, with substantial improvements observed: a 10.6% increase in hydropower output, a 6.0% reduction in water shortage days, and a 9.5% decrease in minimal reservoir water release compared to SOP. This study provides robust technical and scientific bolster to optimize reservoir ESC and enhance the synergy between hydropower generation, water supply, and drought resilience. Additionally, it offers decision-makers actionable strategies that account for emergency water supply capacities. These strategies aim to support mega reservoir's resilience against extreme drought events facilitating the collaboration between modelers and policy-makers, by means of intelligent optimization and decision-making technologies.

Exogenous application of selenium on sunflower (Helianthus annuus L.) to enhance drought stress tolerance by morpho-physiological and biochemical adaptations.

Drought stress poses a significant obstacle to agricultural productivity, particularly in the case of oilseed crops such as sunflower (Helianthus annuus L.). Selenium (Se) is a fundamental micronutrient that has been recognized for its ability to enhance plant resilience in the face of various environmental stresses. The FH-770 sunflower variety was cultivated in pots subjected to three stress levels (100% FC, 75% FC, and 50% FC) and four Se application rates (0 ppm, 30 ppm, 60 ppm, and 90 ppm). This research aimed to investigate the effect of exogenously applied Se on morpho-physiological and biochemical attributes of sunflower to improve the drought tolerance. Foliar Se application significantly lowered H2O2 (hydrogen peroxide; ROS) (20.89%) accumulation that markedly improved glycine betaine (GB) (74.46%) and total soluble protein (Pro) (68.63%), improved the accumulation of ascorbic acid (AA) (25.51%), total phenolics (TP) (39.34%), flavonoids (Flv) (73.16%), and anthocyanin (Ant) (83.73%), and improved the activity of antioxidant system superoxide dismutase (SOD) (157.63%), peroxidase (POD) (100.20%), and catalase (CAT) (49.87%), which ultimately improved sunflower growth by 36.65% during drought stress. Supplemental Se significantly increased shoot Se content (93.86%) and improved calcium (Ca2+), potassium (K+), and sodium (Na+) ions in roots by 36.16%, 42.68%, and 63.40%, respectively. Selenium supplements at lower concentrations (60 and 90 ppm) promoted the growth, development, and biochemical attributes of sunflowers in controlled and water-deficient circumstances. However, selenium treatment improved photosynthetic efficiency, plant growth, enzymatic activities, osmoregulation, biochemical characteristics, and nutrient balance. The mechanisms and molecular processes through which Se induces these modifications need further investigation to be properly identified.

Ant colony optimization for the identification of dysregulated gene subnetworks from expression data.

BACKGROUND: High-throughput experimental technologies can provide deeper insights into pathway perturbations in biomedical studies. Accordingly, their usage is central to the identification of molecular targets and the subsequent development of suitable treatments for various diseases. Classical interpretations of generated data, such as differential gene expression and pathway analyses, disregard interconnections between studied genes when looking for gene-disease associations. Given that these interconnections are central to cellular processes, there has been a recent interest in incorporating them in such studies. The latter allows the detection of gene modules that underlie complex phenotypes in gene interaction networks. Existing methods either impose radius-based restrictions or freely grow modules at the expense of a statistical bias towards large modules. We propose a heuristic method, inspired by Ant Colony Optimization, to apply gene-level scoring and module identification with distance-based search constraints and penalties, rather than radius-based constraints. RESULTS: We test and compare our results to other approaches using three datasets of different neurodegenerative diseases, namely Alzheimer's, Parkinson's, and Huntington's, over three independent experiments. We report the outcomes of enrichment analyses and concordance of gene-level scores for each disease. Results indicate that the proposed approach generally shows superior stability in comparison to existing methods. It produces stable and meaningful enrichment results in all three datasets which have different case to control proportions and sample sizes. CONCLUSION: The presented network-based gene expression analysis approach successfully identifies dysregulated gene modules associated with a certain disease. Using a heuristic based on Ant Colony Optimization, we perform a distance-based search with no radius constraints. Experimental results support the effectiveness and stability of our method in prioritizing modules of high relevance. Our tool is publicly available at github.com/GhadiElHasbani/ACOxGS.git.

Discovering Native Ant Species with the Potential to Suppress Red Imported Fire Ants.

Native ants have long been considered for their potential to suppress the red imported fire ant, Solenopsis invicta Buren (Hymenoptera: Formicidae), a highly invasive and destructive species. However, the knowledge in this field is limited to behavioral observations of a few related native ants. In this study, by setting up a series of ant combinations of three native ants, i.e., Monomorium chinense Santschi, the robust crazy ant Nylanderia bourbonica Forel, and Iridomyrmex anceps Roger, with S. invicta, we observed the aggression levels and mortality rates. Using baited vials, we also investigated the abundance of native ants in four types of habitats in Eastern China that are preferred by S. invicta (woodland, green belts on roadsides, grassland, and farmland), as well as their seasonal abundance when co-existing with S. invicta and their spatial distribution before and after control of S. invicta. We found that M. chinense and N. bourbonica show a degree of aggression towards S. invicta and can kill substantial proportions of S. invicta under laboratory conditions, but I. anceps does not. Both M. chinense and N. bourbonica can occur in each type of habitat investigated and are more abundant in green belts (particularly lawns with turf) and grasslands relative to other habitats. In grasslands with S. invicta, M. chinense maintained a low density before early July; however, its abundance increased thereafter and reached a peak in September. N. bourbonica also had a low density early in the season and increased steadily from April. Its abundance began to decrease substantially from November. In grasslands invaded by S. invicta, both M. chinense and N. bourbonica were restricted to sites close to the margins before S. invicta was controlled; however, they spread to a larger range within a few weeks after control of S. invicta. In conclusion, M. chinense and N. bourbonica have the potential to suppress S. invicta invasion in habitats that are abundant with these two native ants.