Operational evaluation of unmanned aerial vehicle-applied granular larvicides in an integrated mosquito management program.

Itgb1b+ and Itgb2+ leukocytes regulate immune responses to bacterial infection in grass carp.

Savannas are globally important ecosystems and unique in supporting abundant and diverse populations of wild large mammals. Mound building fungus-farming Macrotermitinae are key determinants of savanna structure and function. Termite colonies are sensitive to shade, and their lifetime reproductive success is substantially reduced in forests compared to open savanna areas. Here we experimentally show how ungulates, predominantly impala modify mound soil and vegetation cover and consequently internal temperature in Macrotermes subhyalinus epigeal nests. There are large differences in soil nutrient concentrations between the eastern and western termite mound sector. Ungulates selectively feed on the eastern side of the mounds, reducing vegetation cover and exposing that sector to the warming morning sun. Soil sodium concentration, an essential nutrient for heterotrophs is high on the eastern open mound sector on termite mounds. Important plant nutrients are accumulated on the western side of mounds, facilitating growth of vegetation that shade mounds from the hot afternoon sun. When excluding large herbivores from mounds by fencing, differences in sodium soil concentrations between the eastern and western side of the mound are no longer evident while other soil concentration differences are less pronounced. Following fencing, trees gradually established on the eastern side and eventually mounds were completely covered by trees. Shading arising from ungulate exclusion reduce internal mound temperature by 1.6 degrees, resulting in sub-optimal conditions for termite colonies. This study reveals unknown relationships between key functional groups in tropical savannas. The abundance of large iconic wild herbivores is declining over large African savanna areas. Reduced ungulate populations could in turn lead to sub-optimal conditions for Macrotermes termites with subsequent adverse consequences for litter decomposition and plant and animal diversity across African savannas.

Sepsis-associated acute lung injury (sepsis-ALI) is a complex pathological condition; its underlying mechanisms remain mostly obscure. Thus, in this study, we aimed to explore potential candidate molecular markers, infer the regulatory signaling pathways, and describe the immunological profiles of sepsis-ALI. We developed a comprehensive bioinformatics analytical workflow by combining human transcriptome datasets with single-cell RNA sequencing databases and applied the ComBat algorithm to remove batch effects. A hierarchical gene screening process, incorporating the support vector machine, least absolute shrinkage and selection operator, and random forest machine learning algorithms, was applied. Five epithelial-mesenchymal transition (EMT)-related candidate genes (AURKA, MYB, CCNA2, CD24, and TYMS) were suggested across these algorithms. These candidate genes, which are involved in histone phosphorylation signaling, were subjected to Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses. Single-sample gene set enrichment analysis was used to profile immune cell infiltration patterns, which led to the identification of seven differentially abundant immune cell populations. CellChat analysis suggested the MIF-(CD74 + CXCR4) axis serves as a putative mediator of intercellular communication based on ligand‑receptor expression patterns in sepsis-ALI. Pseudo-time trajectory analysis revealed that CD24 expression and MYB expression are associated with EMT progression and display stage‑specific functional relevance along the inferred cellular trajectory. Together, these integrative multi-resolution transcriptomic analysis findings describe EMT-related molecular characteristics, stage-specific regulatory pathways, and immune processes in sepsis-ALI. It is noteworthy that all these results are hypothesis-generating and derived solely from bioinformatics analyses without experimental validation. Identification of candidate genes and the putative role of the MIF-(CD74 + CXCR4) axis provides preliminary insights into sepsis-ALI pathophysiology; these findings will serve as a basis for further experimental research to develop potential precision-based and stage-specific experimental treatment strategies for sepsis-ALI in the future.

The gut microbiota has been established as a cornerstone of host physiological homeostasis. Among its diverse members, Akkermansia muciniphila has gained significant prominence as a premier next-generation probiotic candidate, demonstrating broad efficacy in alleviating metabolic disorders, inflammatory bowel disease, and neurodegenerative conditions. While early research primarily focused on clinical correlations and population abundance, recent scientific paradigms have shifted toward elucidating the underlying molecular mechanisms and specific host-microbe interactions. This review provides a comprehensive synthesis of recent breakthroughs in identifying A. muciniphila-derived bioactive effectors, including structural components, secreted enzymes, and signaling peptides. We examine how these molecular postbiotics orchestrate host health by reinforcing intestinal barrier integrity, modulating systemic immune responses, and reprogramming the tumor microenvironment. By integrating these multifaceted modes of action into a unified framework, we evaluate the therapeutic potential of both live bacteria and cell-free derivatives. Furthermore, we address the critical challenges regarding strain-specific efficacy and ecological impacts, providing a strategic roadmap for the clinical translation of A. muciniphila into the next frontier of precision microbiome medicine.

Climate change and pesticide resistance: a synthesis on emerging mechanisms and evolutionary dynamics.

Organic sulfur metabolism drives volatile sulfur compound generation during wastewater treatment plant sludge thickening.

Biomass and abundance data are critical for ecosystem monitoring and management of fish populations, yet their acquisition represents a growing challenge as anthropogenic pressures intensify the need for monitoring. Environmental DNA (eDNA) has the potential to provide cost-effective biomass and abundance estimations, but its high molecular stability makes it prone to false positives. By contrast, environmental RNA (eRNA) has a faster turnover rate, potentially increasing spatio-temporal resolution and reducing false positives. Yet no study to date has explored the potential for eRNA to predict organismal biomass and abundance in nature. We compared eDNA and eRNA markers with different turnover rates to: (1) test if eRNA could be used to predict fish biomass from mark-recapture in lakes, (2) determine the relative capacity of different markers to predict fish biomass (and abundance when considering fish mass distribution) and (3) evaluate if integrating allometrically scaled mass strengthens fish biomass predictions using eRNA. We tested mitochondrial cyt b and nuclear ribosomal 18S markers on eRNA and eDNA samples. Concentrations of all markers were positively correlated with fish biomass. However, the eRNA markers (mRNA cyt b and rRNA 18S) generally had stronger relationships with fish biomass than eDNA (mtDNA cyt b and nuDNA 18S). This was especially the case for the potentially faster degrading mRNA cyt b marker that resolved differences amongst lakes in biomass and abundance that the other markers did not. Unlike for eDNA, relationships between eRNA concentration and fish biomass were not strengthened by allometric scaling. Our results show the strong potential of eRNA as a molecular tool for population biomass and abundance estimation in aquatic ecosystems.

Roads are vital for human societies, yet they can also have negative impacts on the ecological communities that live in close proximity to them. Insect pollinators, which nest and forage in road verges running alongside roads, are a group of particular importance. These verges may act as an "ecological trap," drawing insect pollinators into contact with traffic, increasing the risk of pollinator-traffic collisions. Spanning six European regions, we evaluated the complex relationships between traffic, road verge floral composition, and surrounding land use to understand how these factors influence abundance and richness of bees, butterflies, and hoverflies sampled within road verges. Across the study, we observed 10,960 pollinators belonging to 293 species of bees, butterflies, and hoverflies. We observed greater pollinator abundance in verges with higher flower cover, and greater pollinator richness in verges with more species of flowering plants. Lower abundances of bees and butterflies and lower species richness of bees were observed when traffic speed in the adjacent road was higher. This study indicates that road verges with abundant and diverse floral resources support more abundant and diverse pollinator populations, especially on verges alongside lower speed roads. We recommend that lower speed roads should be prioritized for floral enhancements.

Initial colonization and succession of macrofaunal communities in an oyster shell reef in a tropical mangrove wetland.

In this study, we adapted a physiologically structured model based on ordinary differential equations, derived from Rossini’s general framework, to describe the population dynamics of Eotetranychus kankitus in four peach varieties (Oro Azteca, Diamante Mejorado, Arkansas, and F70) under real field conditions in Tepeyahualco, Puebla, México. During the 2024 growing season, 19 samples were collected, yielding the mean mites-per-leaf abundance. The thermal functions for development, fecundity, and mortality were fitted using published laboratory data for E. kankitus , whereas five key reproductive parameters that define the thermal fecundity curve ( a β , b β , k β ), the relative fecundity of mated females ( c 2 ), and the transition from mated to unmated females ( G 1 ← 2 ) were estimated using Bayesian inference. The estimate was obtained using an affine-invariant ensemble sampler Markov Chain Monte Carlo implemented in the emcee library. The overall results provided a satisfactory representation of population abundance; however, variety-specific calibrations revealed biologically and statistically significant differences in reproductive parameters. In particular, cultivar-specific estimates revealed clear differences in parameters governing reproductive state: Arkansas exhibited higher values of the relative fecundity of mated females ( c 2 ) and the transition rate from mated to unmated females ( G 1 ← 2 ), whereas consistently lower values were inferred for F70, indicating reduced reproductive output across the season. These findings demonstrate that peach variety is a key determinant of E. kankitus population dynamics and that accounting for varietal differences through cultivar-specific parameter calibration substantially enhances the model’s predictive performance. This study constitutes one of the first cultivar-scale calibrations for E. kankitus and establishes a methodological framework that integrates physiological data, field observations and Bayesian inference to support pest forecasting and management in fruit tree systems. • Field monitoring and physiological modeling of Eotetranychus kankitus in peach orchards. • Temperature-dependent ODE model (Rossini framework) for development, fecundity and mortality. • Bayesian MCMC estimation of five key reproductive parameters from field data. • First use of affine-invariant MCMC in a tetranychid field population model. • Peach variety identified as a key factor shaping population dynamics.

Tea is a crucial industrial beverage and cash crop that has been facing the dire effects of monoculture cropping (MCC), the accretion of pesticide residues and pest resurgence aggravated by climate change, and the disproportionate use of chemical inputs. Legumes are the most prominent cover crops that can modulate tea quality and attract beneficial arthropods, in tea agroecosystems. This study examined the synergistic impacts of leguminous cover cropping (LCC) with soybean (S) and cowpea (C) on tea quality attributes and the population dynamics of key tea pests. The results vividly demonstrated that, compared to MCC, LCC-S;C significantly enhanced the foliar concentrations of key bioactive compounds such as caffeine and theanine. However, LCC-S;C significantly diminished the foliar concentrations of soluble nutrients, including soluble sugars, proteins, free fatty acids, essential amino acids, and bioactive compounds like total polyphenols, and monomer catechins. Notably, LCC-S;C enriched the foliar concentrations of catechin (epigallocatechin, EGC) and the essential amino acid isoleucine (Ile). Additionally, LCC-S; C significantly reduced the population abundances of three key tea pests (Empoasca onukii, Ricania speculum, and Trialeurodes vaporariorum), thereby aiding in natural pest control. The findings highlight that LCC presents a viable alternative to MCC, improving tea quality, while simultaneously reducing the population abundances of key insect pests, and supporting the development of environmentally benign and economically sustainable cultivation practices in tea plantations. © 2026 Society of Chemical Industry.

Metabolic interactions are fundamental to the assembly and function of microbiomes. Yet, our understanding of how specific interaction mechanisms can drive broader ecological outcomes and population dynamics remains limited. Here, we monitor interactions resulting from plant oligosaccharide degradation by leaf-associated bacteria using a microfluidic device that enables direct cell observation and quantitative metabolite detection. This approach enables the identification of key metabolic mediators, revealing recipient-specific patterns of carbon substrate and cofactor complementation. By linking these patterns to emergent dynamics observed between pairs of bacteria, we identify metabolically driven feedbacks that could lead to a variety of ecological outcomes - from outcompetition to coexistence characterized by oscillating population abundances. Investigating these observations with metabolic modeling allows us to systematically assess the impact of specific molecular mediators on population dynamics, yielding predictions of interaction outcomes that we validate experimentally. Our results provide a detailed mapping of metabolic mechanisms to emergent population trajectories among environmental microbes and help inform strategies for designing microbiomes with desired steady states.

The emergence of single-cell multi-omics technologies has enabled researchers to identify rare cell populations and investigate gene regulation with unmatched resolution, advancing cancer research. However, each technique comes with its own distinct advantages and drawbacks. In this study, we compared two high-throughput droplet-based single-cell RNA sequencing (scRNA-seq) technologies-10X Chromium 3' scRNA-seq and SeekGene scFAST-seq-using two paired samples derived from adrenocortical tumor. scFAST-seq exhibited a higher ratio of long non-coding RNAs, along with an increased number of detected genes and transcripts, while ribosomal RNA was underrepresented. Although the overlap in top cell type markers was relatively low, the relative abundances of cell populations were alike in both datasets. Also gene markers showed to be specific for scFAST-seq and 3' scRNA-seq displayed minimal general variability in gene expression. We noted changes in RNA dynamics across the datasets, identified through RNA velocity analysis and fewer copy number variations (CNV) detected by CNV analysis. Furthermore, we found variations in regulon activity in 3' scRNA-seq and scFAST-seq datasets. In conclusion, our research offers essential insights for selecting the most suitable scRNA-seq approach.

ABSTRACTGeographic variation in the diving behaviour of oceanic mammals is a major component of their biodiversity with far‐reaching relevance for ecology and conservation. Here we compared high‐resolution multi‐sensor tag data from northern bottlenose whales in Jan Mayen, Norway (n = 15, 127.2 h) and the Gully, Scotian Shelf, Canada (n = 6, 45.8 h) to compare diving and foraging behaviours. K‐means clustering identified short‐shallow and long‐deep dive types in both locations but showed a propensity for mid‐depth dives in Jan Mayen. Foraging dives (defined by high roll variance corroborated by active clicking) included long‐deep dives (Jan Mayen = 967 ± 394 m SD, n = 26; Gully = 1247 ± 411 m, n = 14) but also these mid‐depth dives (537 ± 135 m, n = 105). Time budgets varied substantially between locations with whales in the Gully spending 15% less time foraging (Z = 2.1, p = 0.03) and twice as much time near‐surface resting (Z = −3.8, p < 0.001). Movement parameters further showed enigmatic gyrations during dives, more common in Jan Mayen. Skin biopsy stable isotopes revealed small regional differences, likely reflecting both diet and ecoregion (Jan Mayen n = 18: δ15N 15.03‰ ± 0.35‰, Gully n = 41: δ15N 15.41‰ ± 0.44‰). These population differences suggest unequal susceptibility to stressors and unequal likelihood of detection, with consequences for population management and abundance estimation.

Frequent use of resting boxes by Culiseta melanura (Coquillett) during the day-time may offer the opportunity for use of these artificial resting sites as delivery substrates for insecticides to manage populations of this eastern equine encephalitis virus (EEEV) vector. In field studies at EEEV-endemic foci in southwestern Michigan, abundance in black-painted resting boxes of adult male and female Cs. melanura varied within the 24-h diel cycle, by whether the interiors of the boxes were treated with a microencapsulated formulation of lambda cyhalothrin (Demand CSTM), and from before to after treatment of boxes at field sites. Abundance was highest at noon, diminished to nil at midnight, and increased by noon the following day. Abundance of Cs. melanura was lower in insecticide-treated boxes compared to untreated boxes, and declined at field sites sampled after treatment of boxes with microencapsulated lambda cyhalothrin, compared to before treatment and to control sites. This population suppression effect lasted at least 30 days and exceeded 90% reduction. Field-caught Cs. melanura males and females experienced high mortality when exposed to lambda cyhalothrin-treated bottles in bottle bioassays and in overnight exposures to treated boxes set in the laboratory. Prolonged daily visits to resting boxes, resulting in exposure to residual insecticide, may explain the sustained, diminishing effect on abundance of field populations of Cs. melanura. Results support use of insecticide-treated boxes distributed into wooded upland edges of natural larval habitats as an intervention against EEEV transmission.

Influenza A virus (IAV) circulates widely in European pig populations and continues to diversify through frequent introductions from humans, followed by reassortment within swine. Spain represents a particularly dynamic ecological setting due to the coexistence of intensive white pig production, extensive Iberian pig systems, and abundant wild boar populations. This study provides an integrated analysis of IAV evolution and genomic diversity in swine in Spain between 2019 and 2022, expanding on previous surveillance from 2016 to 2019. Sampling across 24 provinces yielded 66 new whole genome sequences from Iberian and white pigs.We identified 18 genotypes, including 11 novel reassortants not detected in our previous survey. Several genotypes, such as H1huN2 G21 and G22, H3N2 G23, and the unusual H3N1 G12, were exclusive to the country. Some genotypes were detected across white pigs, Iberian pigs, and wild boar in Toledo and Badajoz, suggesting viral flow among swine populations.Phylogenetic analyses revealed ongoing introductions of H1N1pdm09 from humans into pigs, generating at least five reassortant genotypes (G10, G16–G19). These lineages incorporated pandemic internal cassettes and, in some cases, human seasonal N2 segments, highlighting the continued role of humans as a source of viral incursions. Conversely, four zoonotic infections (H1N1v) detected in Spain between 2022 and 2026 were linked to genotypes circulating in white pigs, underscoring the bidirectional nature of IAV transmission at the human swine interface.Overall, this study demonstrates that Spain provides ecological conditions conducive to IAV diversification, reassortment, and zoonotic risk. The findings reinforce the need for sustained One Health surveillance.

Biting midges of the genus Culicoides (Diptera: Ceratopogonidae) are key arbovirus vectors of human and animal health relevance. Understanding the biological and molecular factors influencing arbovirus transmission is essential for informing effective mitigation strategies. Culicoides brevitarsis Kieffer is of particular importance due to its close relationship to cattle, high population abundance in suitable sites, and demonstrated vector capacity for arboviruses. However, limited genomic resources have constrained investigation into its molecular and evolutionary biology, necessitating a chromosome-level genome assembly and comparative genomic analyses. A chromosome-level genome assembly of C. brevitarsis was generated using Oxford Nanopore long reads, polished with Illumina short reads, and scaffolded using Hi-C sequencing, followed by genome annotation, comparative dipteran genomics, immune gene characterisation, and evolutionary analyses of vector competence-associated genes. A 129.5Mb genome was assembled into three chromosomes with high contiguity (N50 = 43Mb, L50 = 2) and high completeness (98% for Arthropoda BUSCO odb10 lineage). Genome annotation identified 11,708 genes, including 661 immunity-related genes, as well as genes associated with key functional categories such as metabolism, sensory perception, and host-pathogen interactions. Comparative gene family analyses across 12 dipteran genomes revealed strong family-level (Ceratopogonidae) and genus-level (Culicoides) evolutionary signatures. In C.brevitarsis, 405 expanded and 262 contracted gene families were enriched for functions associated with metabolism, regulation, locomotion, and stimulus response. Integration of transcriptomic datasets from C.sonorensis Wirth and Jones identified 82 orthologous genes in C.brevitarsis corresponding to genes previously associated with differential responses to bluetongue virus infection, including lineage-specific patterns of conservation and selection. The genome provides a foundational resource to understand the molecular biology and evolutionary features of C.brevitarsis. Integration of immune, sensory, metabolic, and evolutionary analysis provides a framework for future functional and comparative studies aimed at understanding variation in arbovirus transmission among Culicoides species.

Sarcoidosis is a systemic granulomatousinflammatory disease and patients with cardiac involvement are at increased risk of adverse events. Pathophysiologic processes leading to myocardial inflammation and fibrosis are yet to be determined. Therefore, characterization of the immune response leading to enhanced disease activity and portending poor prognosis of patients with cardiac sarcoidosis (CS) is crucial. Twenty-six patients with biopsy-proven sarcoidosis were prospectively enrolled for evaluation of suspected CS and disease activity was determined by hybrid cardiac PET/MR imaging. We then analyzed the peripheral blood of individuals with active CS (aCS), chronic CS (cCS), extracardiac sarcoidosis (noCS), and healthy controls using a 36-color spectral flow cytometry and immunoassay panel. Analysis of the inflammatory fingerprint in patients with CS uncovered 56 characteristic immune cell populations. Immunophenotyping of the inflammatory cells revealed distinctive differences between healthy individuals and patients with sarcoidosis. Further, the abundance of the cell populations was associated with cardiac manifestation and disease activity. A critical shift of lymphocytes, innate immune cells, and monocyte subsets occurred in patients with CS compared to extracardiac sarcoidosis and healthy individuals. In addition, cytokine/chemokine expression was aberrant in patients with CS and may contribute to the cardiac pathophysiology of sarcoidosis. Comprehensive characterization of the inflammatory fingerprint reveals changes in frequency and phenotype of several immune cell populations associated with cardiac sarcoidosis. Our results may add further knowledge to the pathophysiology of cardiac sarcoidosis, allowing a better stratification of patients with high disease activity who seem to benefit most from immunosuppressive therapy.

ABSTRACTWhile proteomics is being increasingly applied to investigate extracellular vesicles (EVs), there remains no consensus on how to address the inevitable missing values within proteomics datasets. Here, we devised a three‐step approach that prioritized retaining biologically‐relevant information in EV samples using a dataset containing two populations of EVs analysed by liquid chromatography electrospray ionization tandem mass spectrometry (LC‐ESI‐MS/MS). Firstly, to avoid overfitting, we excluded proteins in which more than half of the values were missing. Next, we statistically tested for low protein abundance in a single population: when the number of potential “missing not at random” (MNAR) values was significantly enriched, these values were replaced with the lowest possible value of “1”. Finally, all remaining missing values were then imputed using the Random Forest machine learning algorithm. Our final dataset included 49.9 % of proteins that originally contained at least one missing value, from which 84.7 % were listed in the ExoCarta database, significantly more than would be expected by chance, strongly indicating biologically relevant imputation. To enable other EV researchers to analyse proteomics data in a robust, easy‐to‐use and peer‐reviewed manner, we provide BioProEV, a bioinformatics pipeline to impute missing values with biological relevance in EV datasets.