Czechia

Flying insects can achieve remarked and robust flapping aerodynamic performance and flight stability in various environments partially owing to the passive mechanisms of their wings and bodies, but a careful analysis associated with flexible wing hinge for forward flight is missing. Here we develop a fluid-structure interaction (FSI) model that couples one-torsional-spring-based elastic wing-hinge dynamics and flapping aerodynamics to study the aerodynamics and flight stability of hawkmoth Manduca Sexta with flexible wing hinge in various flight velocities. The results show that the leading-edge vortex (LEV), the body vortex (BV) and their interactions are responsible for augmenting the vertical force production interactively in all flight velocities, enabling a 6.5% increase in fast flight; the elastic storage in concern with flexible wing hinge exhibits a J-curve, achieving high power efficiency in intermediate forward flight. It is verified that the realistic wing-hinge stiffness can lead to an optimal aerodynamic performance in terms of vertical force production and power cost; external disturbance-rejection based on flexible wing hinge is of high robustness in multiple directions independent of forward flight velocities. This study thus points to the importance and significance of flexible wing hinge in biomimetic designs for flapping micro aerial vehicles.

SEB Conference 2024

Hawkmoth forward flight with flexible wing hinge: aerodynamics and flight stability

flow-structure interactions

biological fluid dynamics

aerodynamics

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SEB Conference 2025

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Tracking the pose of a swarm of insects in free flight is an important challenge necessary both for behavioural studies at scale, and also for testing interventions for the management of species harmful to human and animal health, including mosquitoes. Multi-camera techniques such as convex hull reconstruction have reconstructed pose of the limbs, head, body, wings and other parts of the animal in a lab setting successfully, but tracking in the field remains an important and difficult open question.
Here we will demonstrate a promising new approach for background subtraction and state estimation of a mosquito in free flight in a variety of conditions. We use both camera recordings and synthetic ray-traced data to train a convolutional neural network to recognise a variety of backgrounds and estimate the state of a mosquito in free flight, showing robust performance with a variety of natural and artificial backgrounds.

Using neural networks to track mosquito pose

Among marine renewable energy (MRE) producers, offshore wind farms are currently booming and are seen as a key energy source for energy transition. Wind farm can induce noise, vibrations, interruptions to ecological continuity and generate electromagnetic fields at the level of submarine electric cables. They can affect behavior of electro- and magneto- sensitive species which use natural electromagnetic fiels to move and feed. The increasing number of offshore windfarms is likely to amplify these effects, while existing information on their impact on ichtyological communities remains patchy. Studies have been limited to a few species of commercial interest and exposure to electromagnetic fields is relatively short-lived. Submarine electric cables can transmit alternating current (AC) or direct current (DC) , depending on the function, power, length of the wind turbine transmission line. Currently, wind farms located less than 50km from the coast use AC current whearas furutre more powerful wind farms will be located more than 50 km away and will use DC current. In this context, our study aims to identify and evaluate the effects of magnetic fields in AC and DC current on the survival, development, growth and behavior of elasmobranchs, an elero-sensitive species at conservation risk. The results will enable us to understand how elasmobranchs react to electromagnetic fields, depending on their intensity and the type of current, and thus the type of offshore wind farm (fixed or floating). They will provide managers and decision-makers information they need to meet the challenges of developing MREs without harming marine biodiversity.

Impact of electromagnetic fields from offshore windfarm submarine electric cables on the development, biology and behavior ofScyliorhinus canicula

In recent years, the COVID-19 virus pandemic has threatened public health globally. In several nations, the pandemic's aftermath is still affecting the human population. Numerous mutant strains of SARS CoV-2 spreading caused several waves of infection. These variants were linked to high infectivity or high mortality. But in the face of such assaults, human immune system developed a defence mechanism of its own against the infection to deal with cytokine storm, antibody neutralization escape and multiple organ failure. In order to boost the defence mechanism and SARS CoV-2 broadly being a respiratory disorder was targeted with multiple remedial strategies procured from traditional knowledge of medicinal plants. A survey was conducted to surmise the usage of such medicinal plants with therapeutic properties during the pandemic in a random population in West Bengal, India. Our data demonstrates the most often utilized raw traditional medicines. To deal with clinical manifestations associated with SARS CoV-2 (such as cough and cold) and boosting immunity, Tulsi (Ocimum tenuiflorum) was the most widely used plant which is easy to manage in kitchen gardens and have a high growth rate on the Indian subcontinent. This survey-based study is done to correlate with the efficacy of Tulsi in combating infectious diseases from common cough and cold to COVID-19. Regulated long-term use of these medicinal plants will also help avoid a number of prevalent illnesses and be advantageous for household healthcare. 


Immune Boosting Against SARS CoV-2 Infection: An Approach to Traditional Medicine

This study reports a waterflow sensor for marine biologging and examples of its application to sea turtles. The relative waterflow velocity is one of the most important indicators for evaluating the swimming movements of marine animals. Propeller-type sensors have been used as conventional sensors for marine biologging. However, the sensors' moving parts are easily affected by suspended marine debris and attached organisms. Therefore, long-term and high-temporal resolution measurements of the velocity have been challenging.
Therefore, we have developed a pitot-type waterflow sensor that enables long-term and high-temporal resolution measurement. A rubber film is glued on the inlets, and silicone oil fills inside the flow channel. The film prevents debris from entering, and the oil prevents sensor destruction due to water pressure. In addition, the sensor detects waterflow by measuring the flow-generated pressure without moving parts. These features provide the sensor with high resistance to the harsh marine environment and enable high-temporal resolution measurement.
Finally, we experimentally proved that the developed sensor can be used for biologging. This sensor was connected to a logger and attached to a wild loggerhead turtle. The turtle was equipped with parachutes that generated drag force. The relative waterflow velocity of the turtle was measured for two hours, and the parachute was detached one hour after the start. The sensor measured the waterflow with a high-temporal resolution of 6.25 Hz. Furthermore, we were able to measure the change in the turtle's velocity due to the attachment and detachment of the parachute.


High time-resolution measurement of a sea turtle's relative waterflow velocity using a pitot-type waterflow sensor

Climate change is impacting temperatures globally, altering the frequency, intensity, and extent of extreme events such as heatwaves and droughts. This modification poses a challenge to biodiversity worldwide and presents a particular threat to tropical biota, which already reside close to their thermal maxima. Fish play a crucial role in the diet of the Amazon, particularly for traditional communities that rely on them as their primary protein source. The Amazon boasts the largest diversity of freshwater fish globally, each exhibiting numerous physiological and behavioural adaptations to thrive in the warm and often hypoxic waters of the Amazon. Comprehending how rising temperatures affect Amazonian fish species is essential for policymakers tasked with crafting strategies to safeguard the bio and sociodiversity of the Amazon. Faced with increasing temperatures, fish respond by adjusting their physiology and behaviour until they reach their thermal limit. Traditional thermal tolerance tests conventionally use the loss of equilibrium as the final endpoint for determining thermal limits. However, well before this loss of equilibrium, fish undergo physiological and behavioural adjustments to cope with the changing conditions. Monitoring behavioural changes during critical thermal tolerance tests provides insights into how fish utilise physiological and behavioural adaptations in this progressively warmer environment. We will elucidate behavioural changes observed during thermal tolerance tests of various Amazonian species and explore their connection to physiological adaptations to the Amazonian environment. Additionally, we will consider how these changes can serve as early warning signs of thermal vulnerability for fish species.

Dealing with changes in an extreme world: how is living in tropical waters?

Plant stress phenotyping based on image-analysis techniques can facilitate targeted interventions and optimize management practices. However, considering abiotic stresses – especially under the influence of climate changes – various technical challenges still need to be overcome, and there is a need to identify functional traits that can be used as markers to monitor plants health status accurately and rapidly. This study aimed to develop a machine learning model able to detect salt stress status in Phaseolus vulgaris, by combining image-based approaches and minimal morpho-physiological/biochemical analyses. Therefore, a flexible pipeline was created, starting with the data acquisition and analysis (feature extraction) followed by the feature selection phase, which involved statistical approaches such as principal component analysis and correlation analysis. Finally, two predictive models based on decision trees were developed to detect stress presence (2-class model) and intensity (3-class model). Specific biochemical parameters and image-analysis-derived traits, like malondialdehyde content, chroma difference and chroma ratio indexes, resulted as key features in categorizing both non-stressed and stressed plants (model’s precision: 0.91) as well as stress intensity (model’s precision: 0.84). These results highlighted the potential of machine learning techniques and automated image-based analysis in plant science. In the future, the models’ reliability and accuracy will be improved by adjusting the pipeline to different plant growth stages and specific leaf characteristics, and testing the model across different plant species and abiotic stresses (e.g. drought, temperature).

Enhancing plant stress phenotyping with machine learning: a novel approach for salt stress detection in Phaseolus vulgaris

Maize is one of the most produced cereals worldwide. Many studies have been conducted to decipher the genetic basis of several traits of agronomic relevance. In crops such as maize, where the commercial varieties are F1 hybrids, the optimal populations to screen would theoretically consist of hybrids. However, researchers often use populations composed of inbred lines, which are arguably insufficient for understanding the mechanisms that play a role in hybrid performances. In this study, we have developed a recombinant intercross (RIX) population by crossing pairs of recombinant inbred lines (RILs) belonging to a multi-parental Advanced Generation Inter-Cross (MAGIC) population to perform QTL mapping using a hybrid genetic background. We phenotyped 214 RIX genotypes along with the MAGIC founder inbreds for 10 agronomic traits, including Fusarium Ear Rot (FER) resistance indexes in two consecutive years. The genotypes of RIXs were reconstructed in silico starting from the corresponding RILs’ reconstructed genotype probabilities. For this task, we used a panel of about 74K SNP markers obtained using Single Primer Enrichment Technology (SPET).
Results of the QTL mapping in the hybrid population revealed several genomic regions associated with agronomic traits and FER resistance. Suggestive candidate genes were identified in the mapped intervals. The understanding of their role is currently ongoing. Our findings represent a proof-of-concept that RIX populations are potentially outstanding materials to understand the genetic control of complex quantitative traits in hybrid genetic backgrounds. This kind of resource and the information gathered would provide a future platform to support and accelerate maize improvement.




Mapping Fusarium Ear Rot resistance using recombinant hybrids developed from the MAGIC maize population

Enhancing fertilizer use efficiency is a key aspect in attaining sustainable agriculture objectives, aiming to curtail costs, mitigate greenhouse gas emissions, and alleviate pollution stemming from nutrient runoff. While extensive research has delved into fertilizer utilization in cereal crops, understanding the broader monocot plant community could unveil novel insights. In this study, we investigated nitrogen uptake efficiency across three species—Anthurium andreanum, Epipremnum aureum, and Philodendron scandens—belonging to the Araceae family. Like maize, these species are characterized by root development from both subterranean and aerial tissues. Employing 15N-labeled sources of nitrate, ammonium, and glycine, we assessed nitrogen uptake capacity in both aerial and soil-originating roots, juxtaposed with similar investigations conducted on maize brace roots from field-grown plants. Intriguingly, our findings revealed a positive correlation between nitrogen uptake capacity and root thickness across all species. Notably, nitrate exhibited the strongest correlation with root thickness, succeeded by ammonium, while glycine uptake displayed variable patterns among species. Further examination of species-specific traits encompassing growth form, anatomy, and physiological attributes elucidates finer nuances in nitrogen uptake dynamics. Unravelling these parallels and distinctions among diverse species not only informs translational advancements in crop breeding but also underscores opportunities for enhancing urban greenspaces.

Inside out or outside in? Using aroid indoor plants and field grown maize to gain translational insights about nitrogen uptake patterns.

The General Control Non–derepressible 5 (GCN5) protein is a histone acetyltransferase that acetylates Lys residues in the N-terminal tail of the core histone H3. GCN5 interacts with the Alteration / Deficiency in Activation 2b (ADA2b), which enhances its ability to acetylate histones. These two proteins regulate multiple developmental processes, including reproductive fitness, in Arabidopsis thaliana. This study demonstrates that GCN5 and ADA2b affect anther dehiscence and pollen tube growth. Anthers of ada2b-1 do not release their pollen, leading to seed absence, while gcn5-1 partially releases its pollen and carries an overall reduced seed set inside a smaller silique. Anther indehiscence is supported by RNA-sequencing data, which revealed that both mutants exhibit down-regulation of genes implicated in their anther development. When gcn5-1 pollen was used to fertilise emasculated Ws-2 flowers, the resulting siliques had a wild-type phenotype with a complete seed set, indicative of proper pollen tube growth. The transcriptomic analysis also showed that ada2b-1 inflorescences, contrary to gcn5-1, exhibit down-regulation of pollen tube growth-related genes, including transcription factors. Therefore, GCN5 and ADA2b are positive regulators of anther and pollen development and are essential contributors to the reproductive success of Arabidopsis thaliana.

This work is supported by the Hellenic Foundation for Research and Innovation (HFRI) Grant Number 73333. PI Konstantinos Vlachonasios

GCN5 and ADA2b regulate pollen development and function in Arabidopsis thaliana.

After recovery from stress by pests and diseases, plants maintain an elevated state of defence. This induced resistance (IR) is often based on defence priming, which enables a faster and stronger immune response upon recurrent exposure to the same type of attacker. We study the epigenetic basis of this form of immune memory. We have recently shown that exposure of seedlings to herbivory induces long-lasting DNA de-methylation at transposable elements (TEs), which prime genomically distant defence genes. Although more variable in intensity, immune memory can partially be transmitted to the offspring of stressed plants. This heritable IR is proportional to the stress encountered in previous generations and involves the DNA demethylase ROS1. To advance our understanding of how DNA demethylation controls immune memory, we are following artificial strategies to manipulate the plant methylome. Using epigenetic recombinant inbred lines (epiRILs), which share the same genetic (wild-type) background but vary in heritable DNA methylation of TE-rich regions, we have previously identified epialleles that prime defence gene expression and provide high levels of disease resistance without negative effects on plant growth. To translate this form of epigenetic disease resistance to crops, we are currently developing a new method to introduce dosed amounts of ROS1-dependent DNA hypo-methylation into plant genomes. This tool will not only allow us to induce long-lasting resistance against pests and diseases, but also explore the epigenetic mechanisms by which plants establish, maintain and reset immune memory.



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