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Pollination is an ecosystem process that is crucial to maintain biodiversity and ecosystem function. Bats are important pollinators in the tropics and are an integral part of complex plant-pollinator interaction networks. However, network analysis-based approaches are still scarce at the plant species and bat community levels. We used metabarcoding to identify plant taxa present in pollen from fur and faecal samples collected across 1 year from three nectar-feeding bat roosts in central Mexico. We calculated the frequency of occurrence of plant taxa and assembled a zoocentric network of bat-plant interactions. We constructed a year-long network, encompassing the entire period of sampling, two seasonal networks comprising the wet and dry seasons, and six individual networks from sampling at two-month intervals across the year. Four species of nectar-feeding bats interacted with 36 plant species from 16 families. We found highly generalised interaction patterns across networks corresponding with opportunistic feeding behaviour by bats, with little seasonal variation in network structure. There was high resource overlap between bat species, and bats visited a diverse range of plant species even during periods with a high abundance of particular resources in the landscape. The diverse diet of nectar-feeding bats emphasises the importance of floristically rich natural habitats in the landscape to provide reliable foraging resources year-round in a seasonally variable system. While a generalised network structure is thought to increase robustness, further research is necessary to understand how fluctuations in pollinator abundance and diversity in the face of land use and climate change may impact bat-flower networks and the consequences to plant communities., Competing Interests: The authors declare no conflicts of interest., (© 2024 The Author(s). Ecology and Evolution published by John Wiley & Sons Ltd.)

Tropical forest recovery is fundamental to addressing the intertwined climate and biodiversity loss crises. While regenerating trees sequester carbon relatively quickly, the pace of biodiversity recovery remains contentious. Here, we use bioacoustics and metabarcoding to measure forest recovery post-agriculture in a global biodiversity hotspot in Ecuador. We show that the community composition, and not species richness, of vocalizing vertebrates identified by experts reflects the restoration gradient. Two automated measures - an acoustic index model and a bird community composition derived from an independently developed Convolutional Neural Network - correlated well with restoration (adj-R² = 0.62 and 0.69, respectively). Importantly, both measures reflected composition of non-vocalizing nocturnal insects identified via metabarcoding. We show that such automated monitoring tools, based on new technologies, can effectively monitor the success of forest recovery, using robust and reproducible data., (© 2023. Springer Nature Limited.)

Biofilms are highly tolerant to antimicrobials and host immune defense, enabling pathogens to thrive in hostile environments. The diversity of microbial biofilm infections requires alternative and complex treatment strategies. In a previous work we demonstrated that the human Atrial Natriuretic Peptide (hANP) displays a strong anti-biofilm activity toward Pseudomonas aeruginosa and that the binding of hANP by the AmiC protein supports this effect. This AmiC sensor has been identified as an analog of the human natriuretic peptide receptor subtype C (h-NPRC). In the present study, we evaluated the anti-biofilm activity of the h-NPRC agonist, osteocrin (OSTN), a hormone that displays a strong affinity for the AmiC sensor at least in vitro . Using molecular docking, we identified a pocket in the AmiC sensor that OSTN reproducibly docks into, suggesting that OSTN might possess an anti-biofilm activity as well as hANP. This hypothesis was validated since we observed that OSTN dispersed established biofilm of P. aeruginosa PA14 strain at the same concentrations as hANP. However, the OSTN dispersal effect is less marked than that observed for the hANP (-61% versus -73%). We demonstrated that the co-exposure of P. aeruginosa preformed biofilm to hANP and OSTN induced a biofilm dispersion with a similar effect to that observed with hANP alone suggesting a similar mechanism of action of these two peptides. This was confirmed by the observation that OSTN anti-biofilm activity requires the activation of the complex composed by the sensor AmiC and the regulator AmiR of the ami pathway. Using a panel of both P. aeruginosa laboratory reference strains and clinical isolates, we observed that the OSTN capacity to disperse established biofilms is highly variable from one strain to another. Taken together, these results show that similarly to the hANP hormone, OSTN has a strong potential to be used as a tool to disperse P. aeruginosa biofilms., Competing Interests: The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Lesouhaitier Olivier reports financial support was provided by 10.13039/501100007527University of Rouen Normandy. Lesouhaitier Olivier reports a relationship with 10.13039/501100007527University of Rouen Normandy that includes: employment and funding grants. Lesouhaitier Olivier has patent issued to Licensee. No conflict of interest., (© 2023 The Authors.)

Detection of radiological materials in the solution phase is restricted by conventional radiation-counting techniques owing to extreme attenuation. Chemical sensing of the resultant radiological species such as uranyl UO(2)(2+) is possible on the surface of a plastic or glass fibre optic. A dihydroxy isoamethryin complex is tethered to the fibre surface which has a large extinction coefficient (119 000 M(-1) cm(-1) at lambda = 439 nm) and changes colour upon binding UO(2)(2+). The spectral changes are greater on the surface than in solution and binding is specific to UO(2)(2+) with small interferences from Gd(3+). Monitoring the spectral response in three detector bands in the red, green and blue enable the optical power change to be measured with sensitivities of 1 mdB, allowing UO(2)(2+) to be detected confidently at 50-100 ppb levels. Real-time kinetic analysis enables discrimination between the target species and possible interferents.