Severe Threat Research Articles

Source attribution of human Campylobacter infection: a multi-country model in the European Union

IntroductionInfections caused by Campylobacter spp. represent a severe threat to public health worldwide. National action plans have included source attribution studies as a way to quantify the contribution of specific sources and understand the dynamic of transmission of foodborne pathogens like Salmonella and Campylobacter. Such information is crucial for implementing targeted intervention. The aim of this study was to predict the sources of human campylobacteriosis cases across multiple countries using available whole-genome sequencing (WGS) data and explore the impact of data availability and sample size distribution in a multi-country source attribution model.MethodsWe constructed a machine-learning model using k-mer frequency patterns as input data to predict human campylobacteriosis cases per source. We then constructed a multi-country model based on data from all countries. Results using different sampling strategies were compared to assess the impact of unbalanced datasets on the prediction of the cases.ResultsThe results showed that the variety of sources sampled and the quantity of samples from each source impacted the performance of the model. Most cases were attributed to broilers or cattle for the individual and multi-country models. The proportion of cases that could be attributed with 70% probability to a source decreased when using the down-sampled data set (535 vs. 273 of 2627 cases). The baseline model showed a higher sensitivity compared to the down-sampled model, where samples per source were more evenly distributed. The proportion of cases attributed to non-domestic source was higher but varied depending on the sampling strategy. Both models showed that most cases could be attributed to domestic sources in each country (baseline: 248/273 cases, 91%; down-sampled: 361/535 cases, 67%;).DiscussionThe sample sizes per source and the variety of sources included in the model influence the accuracy of the model and consequently the uncertainty of the predicted estimates. The attribution estimates for sources with a high number of samples available tend to be overestimated, whereas the estimates for source with only a few samples tend to be underestimated. Reccomendations for future sampling strategies include to aim for a more balanced sample distribution to improve the overall accuracy and utility of source attribution efforts.

Natural history, population changes, and conservation needs of the Guacharaquita frog Tachiramantis lentiginosus (Anura, Strabomantidae) in the Colombian Andes

Tachiramantis is a recently proposed genus that includes seven species, four considered threatened with a declining trend, while three lack sufficient data for conservation assessment. The Guacharaquita frog Tachiramantis lentiginosus is one of these species, with substantial information gaps regarding its natural history, threats, and population density changes, particularly in isolated populations such as that studied here. In San Antonio, the only location in Colombia where T. lentiginosus is found, we evaluated changes in population density and vegetation cover over 10 years (2014–2024). Additionally, we mapped current threats and describe key aspects of microhabitat use and activity patterns. Analyses were conducted using the Kruskal-Wallis test, and Global Forest Change Analysis. Our findings reveal a significant decline in population density and vegetation cover, with agriculture, cattle ranching, and mining identified as major threats. We also observed variable microhabitat use and a distinct activity period, suggesting the species lacks specific microhabitat preferences and is primarily nocturnal. We conclude that this only known population in Colombia is in decline, facing severe threats that fragment its forest habitat and contribute to cover loss.

Multi-Target Firefighting Task Planning Strategy for Multiple UAVs Under Dynamic Forest Fire Environment

The frequent occurrence of forest fires in mountainous regions has posed severe threats to both the ecological environment and human activities. This study proposed a multi-target firefighting task planning method of forest fires by multiple UAVs (Unmanned Aerial Vehicles) integrating task allocation and path planning. The forest fire environment factors such high temperatures, dense smoke, and signal shielding zones were considered as the threats. The multi-UAVs task allocation and path planning model was established with the minimum of flight time, flight angle, altitude variance, and environmental threats. In this process, the study considers only the use of fire-extinguishing balls as the fire suppressant for the UAVs. The improved multi-population grey wolf optimization (MP–GWO) algorithm and non-Dominated sorting genetic algorithm II (NSGA-II) were designed to solve the path planning and task allocation models, respectively. Both algorithms were validated compared with traditional algorithms through simulation experiments, and the sensitivity analysis of different scenarios were conducted. Results from benchmark tests and case studies indicate that the improved MP–GWO algorithm outperforms the grey wolf optimizer (GWO), pelican optimizer (POA), Harris hawks optimizer (HHO), coyote optimizer (CPO), and particle swarm optimizer (PSO) in solving more complex optimization problems, providing better average results, greater stability, and effectively reducing flight time and path cost. At the same scenario and benchmark tests, the improved NSGA-II demonstrates advantages in both solution quality and coverage compared to the original algorithm. Sensitivity analysis revealed that with the increase in UAV speed, the flight time in the completion of firefighting mission decreases, but the average number of remaining fire-extinguishing balls per UAV initially decreases and then rises with a minimum of 1.9 at 35 km/h. The increase in UAV load capacity results in a higher average of remaining fire-extinguishing balls per UAV. For example, a 20% increase in UAV load capacity can reduce the number of UAVs from 11 to 9 to complete firefighting tasks. Additionally, as the number of fire points increases, both the required number of UAVs and the total remaining fire-extinguishing balls increase. Therefore, the results in the current study can offer an effective solution for multiple UAVs firefighting task planning in forest fire scenarios.

Preparation of Am-MSN/PVDF Mixed Matrix Membranes for Enhanced Removal of Reactive Black 5

The discharge of large volumes of textile dyeing wastewater, characterized by poor biodegradability and high toxicity, poses severe threats to the environment. In this study, polyvinylidene difluoride (PVDF) membranes were prepared using the nonsolvent-induced phase separation (NIPS) method, with porous amino-functionalized mesoporous silica nanoparticles (Am-MSNs) mixed into the casting solution to fabricate the Am-MSN/PVDF mixed matrix membranes. By varying the amount of Am-MSNs added, the microstructure and overall performance of the membranes were comprehensively analyzed. The results demonstrated that the addition of Am-MSNs significantly enhanced the hydrophilicity of the membranes. The high specific surface area and amino groups of Am-MSNs facilitated interactions with dye molecules, such as Reactive Black 5 (RB5), through hydrogen bonding, electrostatic attraction, and physical adsorption, resulting in a marked improvement in RB5 rejection rates. Static adsorption tests further validated the superior adsorption capacity of the Am-MSN/PVDF mixed matrix membranes for RB5. Additionally, the nanoscale mesoporous structure of Am-MSNs enhanced the mechanical strength of the membranes. The synergistic effects of the mesoporous structure and amino groups significantly increased the efficiency and stability of the Am-MSN/PVDF mixed matrix membranes in dye removal applications, providing an effective and sustainable solution for the treatment of dye-contaminated wastewater.

Microplastics-exposure experience aggravates the accumulation of diarrhetic shellfish toxins (DSTs) in thick-shell mussel Mytilus coruscus through impairing detoxification processes

Possessing sessile filter-feeding lifestyle, bivalves are more susceptible to contamination by benthic phycotoxins such as the diarrhetic shellfish toxins (DSTs). Due to the prevalence of microplastics (MPs) in aquatic environments, bivalve that experienced MP-exposure are potentially at higher risk from exposure to DSTs-producing microalgae, however, little is known about the impacts of past MP-exposure experience on the accumulation of DSTs. In this study, taking polystyrene (PS) MPs and DSTs-producing Prorocentrum lima as representatives, the impacts of MP-exposure on DSTs accumulation were evaluated in the thick-shell mussel Mytilus coruscus. Our results demonstrated that mussels with MP-exposure experience accumulated markedly higher levels of DSTs in their digestive glands, which may result from a significant impairment of detoxification. In addition, although might exert their effects through different mechanisms, both MP- and/or P. lima-exposure aggravated the level of oxidative stress and led to significant histological lesion of the digestive glands, with the highest stress and lesion observed in mussels that exposed to P. lima after a 21-day MP-exposure. Collectively, our results indicate the risk of DSTs-contamination of bivalves could be markedly aggravated by the ubiquitous presence of MPs, which may pose a severe threat to human consumers and warrants upmost attention.

Snapshots of Pseudomonas aeruginosa SOS response reveal structural requisites for LexA autoproteolysis.

Antimicrobial resistance poses a severe threat to human health and Pseudomonas aeruginosa stands out among the pathogens responsible for this emergency. The SOS response to DNA damage is crucial in bacterial evolution, influencing resistance development and adaptability in challenging environments, especially under antibiotic exposure. Recombinase A (RecA) and the transcriptional repressor LexA are the key players that orchestrate this process, determining either the silencing or the active transcription of the genes under their control. By integrating state-of-the-art structural approaches with invitro binding and functional assays, we elucidated the molecular events activating the SOS response in P.aeruginosa, focusing on the RecA-LexA interaction. Our findings identify the conserved determinants and strength of the interactions that allow RecA to trigger LexA autocleavage and inactivation. These results provide the groundwork for designing novel antimicrobial strategies and exploring the potential translation of Escherichia coli-derived approaches, to address the implications of P.aeruginosa infections.

Pentastiridius leporinus as a plant disease vector: The practical state of knowlege and derived research objectives

Pentastiridius leporinus, a polyphagous planthopper, has emerged as a significant vector of the phloem-limited pathogens ARSEPH and PHYPSO, posing a severe threat to agricultural production across Europe. This study explores the complex interactions between P. leporinus, its pathogens, and host plants, focusing on its impact on sugar beet, potato, and recently identified vegetable crops such as carrots and beetroots. The transmission of these pathogens leads to reduced yield and quality, causing substantial economic losses and threatening food security and supply chains. P. leporinus exhibits remarkable adaptability, spreading efficiently over long distances and colonizing diverse crops. Its life cycle, involving nymph development in soil and adult migration to host plants, underpins its reproductive success and rapid geographic expansion. While ARSEPH and PHYPSO reduce crop viability and processing quality, their combined infections exacerbate the damage, introducing secondary pathogens and compounding challenges for farmers. Control measures for P. leporinus remain limited due to the lack of resistant crop varieties, long-term insecticide efficacy, and precise infestation thresholds. Current efforts emphasize a holistic, integrated pest management (IPM) strategy, combining agronomic practices such as early harvesting, crop rotation, and soil cultivation with emerging tools like biocontrol agents, forecasting models, and experimental genetic techniques. Trials with cover nets and tolerant crop varieties show promise in mitigating the pest’s impact, but further research is essential. This work highlights critical knowledge gaps, advocating for interdisciplinary collaboration and increased funding to develop sustainable, environment-friendly solutions. Practical research and immediate action is necessary to mitigate the devastating effects of P. leporinus on agriculture. The authors therefore propose the establishment of an EU task force on plant health emergencies, as foreseen in the amendment of EU plant health legislation. A national initiative is not sufficient to manage the existential threat situation.

Monitoring and evaluation of ecological restoration in open-pit coal mine using remote sensing data based on a OM-RSEI model

ABSTRACT Open-pit coal mining poses a severe threat to regional ecological security. Rapid and accurate monitoring of ecological quality changes is crucial for regional ecological restoration. In this study, taking the Wujiata open-pit coal mine as an example, the Red-Edge Normalized Difference Vegetation Index (RENDVI), Salinity Index (SI-T), WETness index (WET), Normalized Differential Built Soil Index (NDBSI), Land Surface Temperature (LST), and Desertification Index (DI) were used to construct the Open-pit Mine Remote Sensing Ecological Index (OM-RSEI) through Principal Component Analysis (PCA). The ecological quality and restoration conditions of typical mining areas in arid and semi-arid regions were monitored and evaluated. The results shown that: (1) The contribution rates and eigenvalues of OM-RSEI were higher than those of conventional RSEI, OM-RSEI was more applicable in open-pit mining areas. (2) From 2018 to 2023, the OM-RSEI of the Wujiata open-pit coal mine showed a ‘V’ shaped fluctuation that was damaged and then gradually recovered. (3) The degraded area of Wujiata open-pit coal mine and its 5 km buffer zone accounted for 78.02%, and the improved area accounted for 19.16%. (4) The average Moran’s I index of OM-RSEI in the study area was 0.8189, and the high–high clustering corresponded to the ‘good’ and ‘excellent’ distributions, while the low–low clustering corresponded to the ‘poor’ and ‘less-poor’ distributions. The OM-RSEI provided a new indicator for monitoring and evaluation of ecological restoration in open-pit coal mines, which can provide theoretical support for ecological restoration in open-pit coal mining areas.

A Dual-Pipeline Lactate Removal Strategy to Reverse Vascular Hyperpermeability for the Management of Lipopolysaccharide-Induced Sepsis.

Sepsis is an underappreciated yet severe threat to human life, marked by organ dysfunction and high mortality resulting from disordered inflammatory responses to blood infection. Unfortunately, no specific drugs are available for effective sepsis treatment. As a pivotal biomarker for sepsis, lactate levels are closely related to vascular permeability and sepsis-associated mortality. Herein, a dual-pipeline lactate removal strategy is reported from circulating blood to ameliorate vascular permeability and lipopolysaccharide (LPS)-induced sepsis. This is achieved by formulating lactate oxidase (LOX)-encapsulated hollow manganese dioxide (HMnO2) nanohybrids (LOX@HMnO2-P[5]A) bearing pillar[5]arene (P[5]A) macrocycle with excellent host-guest properties. The highly biocompatible nanohybrids enable direct lactate consumption through LOX catalytic degradation and block lactate production by P[5]A-mediated LPS trapping, allowing for dual-pipeline lactate removal to maximize the reversal of lactate-mediated vascular hyperpermeability. Besides, HMnO2 cores decompose hydrogen peroxide produced from lactate oxidation into oxygen, further contributing to lactate consumption and mitigating the hypoxic inflammatory environment. In vivo investigations demonstrate that intravenous administration of LOX@HMnO2-P[5]A nanohybrids with extended blood circulation can effectively ameliorate endothelial barrier dysfunction, inflammatory responses, and multiple organ injury, ultimately improving survival outcomes in LPS-induced sepsis. Taken together, this dual-pipeline lactate removal strategy offers a promising approach for efficient sepsis treatment.

What is left in miombo woodlands? Rarity and commonness of woody species, commercial timber species, and lawful harvestable diameter classes.

Mozambican miombo woodlands (MWs) have been experiencing severe anthropogenic threats, recognized to have an impact on plant species distribution, occurrence, diversity, and rarity patterns. Based on 3725 0.1ha plots distributed across the country's MWs, this study aimed to assess the species rarity and commonness, protection status, and availability of commercial timber in MWs under varied environmental conditions. Results show that, out of the 515 tree and shrub species found, 45% were rare, while just 10% were highly protected. Nine of the 112 commercial miombo species were not observed, and 15 were rare. Commercial-sized trees of the top nine desired species were extremely rare, some species had only 1 tree per 20ha and stem forms unsuitable for sawmilling. Selective overharvesting has also affected trees with no minimum felling diameter. Brachystegia spiciformis, B. boehmii, and Julbernardia globiflora stood out among the few timber species with commercially viable populations. MWs in the semi-arid ecoregion have lower species richness, fewer commercially viable populations, and a higher number of poorly protected species (51%). The rainy ecoregion has the highest percentage of poorly protected species (61%). Based on the results obtained, it was recommended that (1) timber harvesting should be restricted to the humid ecoregion, prohibited for the timber species that were either absent or rare, and halted for the top nine desired species; (2) except B. spiciformis, B. boehmii, and J. globiflora, MWs should preferably undergo a forest closure period corresponding to at least one cutting cycle; (3) to ensure long-term viability, a minimum harvestable density for commercial-sized trees should be determined for each species.

Deep Learning Approach in Seismology: Enhancing Earthquake Forecasting using K-Means Clustering and LSTM Networks

Located in the subduction zone of four tectonic plates, the high occurrence of seismic events is a severe threat in Indonesia. Mitigating the adverse effects of such disasters is essential to forecast the likelihood of future earthquakes. Consequently, developing a robust method of forecasting future earthquakes is critical to facilitate prevention and mitigation efforts. A reliable earthquake prediction method is necessary to reduce the after-effects to the greatest extent possible. This study utilises historical seismic and proposes innovative data pre-processing methods using K-means clustering to build a Long Short-Term Memory (LSTM) model for earthquake forecasting to overcome high-disparity locations. Four LSTM layers are embedded with adjusted fine-tuned network hyperparameters to enhance forecasting accuracy. The results attain 0.379816, 0.616292, and 0.414586 for Mean Square Error (MSE), Root MSE, and Mean Absolute Error, respectively, providing significant insights into earthquake prediction. In addition, predicted seismic occurrences are plotted on a map to display their geographic location within the specified research region. This research provides significant value in facilitating the efficient distribution of resources, such as evacuating residents impacted by earthquakes or reinforcing buildings and infrastructure, for emergency responders and policymakers.

Intuitions over arguments or arguments over intuitions? – An empirical study on Chinese participants

ABSTRACT According to experimental philosophers, the diversity and sensitivity of intuitions have posed a severe threat to the traditional philosophical methodology, which relies extensively on intuitions triggered by thought experiments. However, defenders of traditional armchair philosophical methodology argue that experimental philosophers misunderstand the importance of intuitions for philosophy. What philosophers genuinely rely on are arguments, which provide a reliable foundation for their judgments on thought experiments. However, a recent cross-cultural experiment conducted by Wysocki (2017) indicates that arguments do not affect the judgments about Gettier cases as philosophers once expected. That poses a challenge to those philosophers who contend that judgments are based on arguments. In this paper, we expand the experimental investigation of the effect of arguments on judgments about thought experiments. We report the result of three experiments in which eleven thought experiments drawn from multiple philosophical subdisciplines were used. It turns out that arguments have significant impacts on Chinese participants’ judgments in response to most of these thought experiments. These results present new resources for defending the traditional methodology but also bring new challenges.

Media consolidation and news content quality

Abstract News organizations have been under financial pressure to streamline their activities for decades. Critics argue that this pressure undermines the quality of news, posing a severe threat to democracy. However, the effects of media consolidation on news quality are theoretically ambiguous and empirical evidence is scarce. To address this gap, we study the case of the Swedish newspaper industry between 2014 and 2022, a period where more than half of the country’s newspapers changed their owners. We collect over 2 million articles from 108 newspapers and apply state-of-the-art computational methods to create theoretically grounded, fine-grained measures of news content quality. Our results indicate that mergers are associated with slight increases in content quality. However, we also find evidence of content homogenization, as merging newspapers tend to slightly decrease their provision of local news, while relying more on content shared with co-owned newspapers.

Development of a novel fluorescent probe for the detection of glyphosate in food and water samples and the construction of a smartphone-assisted platform.

The extensive use of glyphosate has been a severe threat to the environment and human health, which highlights the importance of the detection of glyphosate in various environmental and food samples. Herein, a novel fluorescent probe (DT-Gly) was constructed for the detection of glyphosate. DT-Gly and glyphosate binding to copper ions (Cu2+) is competitive. Therefore, the increased glyphosate will decrease DT-Gly binds to Cu2+. Accordingly, the absorbance (at 507nm) and fluorescence (at 580nm) intensity of DT-Gly showed excellent linear relationships with glyphosate concentrations (0-20μM). Moreover, the detection limits of DT-Gly for Cu2+ and glyphosate were 94nM and 71nM, respectively. DT-Gly was successfully applied to detect glyphosate in food samples and water samples. We further constructed a convenient platform for the detection of glyphosate by analyzing the changes in RGB values of the probe solution and test strips using a smartphone.

Real-time detection and monitoring of public littering behavior using deep learning for a sustainable environment

With the global population surpassing 8 billion, waste production has skyrocketed, leading to increased pollution that adversely affects both terrestrial and marine ecosystems. Public littering, a significant contributor to this pollution, poses severe threats to marine life due to plastic debris, which can inflict substantial ecological harm. Additionally, this pollution jeopardizes human health through contaminated food and water sources. Given the annual global plastic consumption of approximately 475 million tons and the pervasive issue of public littering, addressing this challenge has become critically urgent. The Surveillance and Waste Notification (SAWN) system presents an innovative solution to combat public littering. Leveraging surveillance cameras and advanced computer vision technology, SAWN aims to identify and reduce instances of littering. Our study explores the use of the MoViNet video classification model to detect littering activities by vehicles and pedestrians, alongside the YOLOv8 object detection model to identify individuals responsible through facial recognition and license plate detection. Collecting appropriate data for littering detection presented significant challenges due to its unavailability. Consequently, project members simulated real-life littering scenarios to gather the required data. This dataset was then used to train different models, including LRCN, CNN-RNN, and MoViNets. After extensive testing, MoViNets demonstrated the most promising results. Through a series of experiments, we progressively improved the model’s performance, achieving accuracy rates of 93.42% in the first experiment, 95.53% in the second, and ultimately reaching 99.5% in the third experiment. To detect violators’ identities, we employed YOLOv8, trained on the KSA vehicle plate dataset, achieving 99.5% accuracy. For face detection, we utilized the Haar Cascade from the OpenCV library, known for its real-time performance. Our findings will be used to further enhance littering behavior detection in future developments.

Structure and function of the uracil DNA glycosylases from hyperthermophiles: Elucidating DNA uracil repair mechanisms: A review.

Base deamination can lead to DNA base damage, among which cytosine deamination to uracil occurs frequently. Before repair, replication of uracil in DNA will generate GC → AT transversion mutation. Since base deamination is accelerated by high temperature, genomic DNA stability of hyperthermophiles, which grow optimally above 75 °C, is facing a severe threat by the elevated base deamination created by their living high temperature environments. To counteract its potentially harmful effect, cells have employed several pathways for DNA uracil repair, among which base excision repair (BER) is one of major pathways. Uracil DNA glycosylase (UDG) is the first enzyme that initiates BER by excising uracil from DNA. Based on their sequence similarities, UDGs have been divided into six families, among which families IV and V members are predominantly found in hyperthermophiles. Besides, two novel UDGs have been reported from hyperthermophiles. Generally, UDGs from hyperthermophiles exhibit biochemical and structural characteristics distinct from other family UDG members, thereby enriching functional diversity of UDGs. Herein, we have reviewed structure and function of UDGs from hyperthermophiles to provide insights into DNA uracil repair mechanisms, focusing on difference between UDGs from various hyperthermophiles, and difference between archaeal UDGs and bacterial homologs.

Disruption in Corruption Eradication in Indonesia

Corruption is a severe threat to society and the nation’s future. Consequently, in Indonesia, various regulations have been formulated and implemented as part of the anti-corruption legal framework. However, recent years have shown a weakening in anti-corruption efforts marked by the revision and non-enactment of several key regulations. The weakening trend is due to changes in the legal and political landscape surrounding corruption eradication. Therefore, this study aimed to analyze and understand the disruptions in the Indonesian anti-corruption legal framework. A legal analysis method was used which included examining existing laws, proposed legislative changes, and the impacts on anti-corruption efforts in Indonesia. The findings showed that the Indonesian anti-corruption legal system experienced significant disruptions, leading to diminished efforts in countering corruption. These disruptions originated from the accumulation of several revised regulations including the Corruption Eradication Commission Law, leniency towards corrupt offenders, minimal prison sentences, reduced fines, and delays in enacting asset forfeiture law. To address these challenges, policymakers are motivated to strengthen the substance of anti-corruption laws to enhance the effectiveness of law enforcement and promote stronger corruption eradication efforts.

Establishment of a 3D-Printed Tissue-on-a-Chip Model for Live Imaging of Bacterial Infections.

Despite advances in healthcare, bacterial pathogens remain a severe global health threat, exacerbated by rising antibiotic resistance. Lower respiratory tract infections, with their high death toll, are of particular concern. Accurately replicating host-pathogen interactions in laboratory models is crucial for understanding these diseases and evaluating new therapies. In this communication, we briefly present existing in vivo models for cystic fibrosis and their limitations in replicating human respiratory infections. We then present a novel, 3D-printed, cytocompatible microfluidic lung-on-a-chip device, designed to simulate the human lung environment, and with possible use in recapitulating general infectious diseases.Our device enables the colonisation of fully differentiated lung epithelia at an air-liquid interface with Pseudomonas aeruginosa, a key pathogen in many severe infections. By incorporating dynamic flow, we replicate the clearance of bacterial toxins and planktonic cells, simulating both acute and chronic infections. This platform supports real-time monitoring of therapeutic interventions, mimics repeated drug administrations as in clinical settings, and facilitates the analysis of colony-forming units and cytokine secretion over time. Our findings indicate that this lung-on-a-chip device has significant potential for advancing infectious disease research, in optimizing treatment strategies against infections and in developing novel treatments.

Unraveling the Molecular Architecture of Mosquito D1-Like Dopamine Receptors: Insights Into Ligand Binding and Structural Dynamics for Insecticide Development.

Vector-borne diseases pose a severe threat to human life, contributing significantly to global mortality. Understanding the structure-function relationship of the vector proteins is pivotal for effective insecticide development due to their involvement in drug resistance and disease transmission. This study reports the structural and dynamic features of D1-like dopamine receptors (DARs) in disease-causing mosquito species, such as Aedes aegypti, Culex quinquefasciatus, Anopheles gambiae, and Anopheles stephensi. Through molecular modeling and simulations, we describe the common structural fold of mosquito DARs within the G-protein-coupled receptor family, highlighting the importance of an orthosteric and enlarged binding pocket. The orthosteric binding pocket, resembling a cage-like structure, is situated ~15 Å deep within the protein, with two serine residues forming the roof and an aspartate residue, along with two conserved water molecules (W1 and W2), forming the floor. The side walls are composed of two phenylalanine residues on one side and a valine residue on the other. The antagonist binding site, an enlarged binding pocket (EBP) near the entrance cavity, can accommodate ligands of varying sizes. The binding energy of dopamine is observed to be ~2-3 kcal/mol higher than that of the antagonist molecules amitriptyline, asenapine, and flupenthixol in mosquito DARs. These antagonist molecules bind to EBP, which obstructs dopamine movement toward the active site, thereby inhibiting signal transduction. Our findings elucidate the molecular architecture of the binding pockets and the versatility of DARs in accommodating diverse ligands, providing a foundational framework for future drug and insecticide development.

Cellulose-Based Aerogels for Environmentally Sustainable Applications: A Review of the Production, Modification, and Sorption of Environmental Contaminants.

Environmental pollution, stemming from the disposal of contaminants, poses severe threats to ecosystems and human health. The emergence of a new class of pollutants, termed emerging contaminants (ECs), in soil, water, and air has raised global concerns, aligning with the UN 2030 Agenda's Sustainable Development Goals. Aerogels, three-dimensional structures with high porosity and low density, offer promise in addressing this issue. Cellulose-based aerogels, derived from abundant, renewable, and biodegradable sources, particularly stand out for their potential in adsorption applications. However, challenges arise in water and wastewater treatment due to cellulose aerogel's inherent hydrophilicity. To overcome this limitation, incorporating new components and employing modification processes becomes essential. This article explores the production phases and diverse modifications of cellulose aerogels, aiming to enhance their adsorption capabilities for various environmental contaminants. By addressing hydrophilicity issues and developing stable composites, cellulose aerogels can contribute significantly to efficient and sustainable solutions in the quest for cleaner ecosystems and improved human health.