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IntroductionThe ‘social brain hypothesis’ proposes that brain development (particularly primates) is driven by social complexity, more than group size. Yet, small insects with minute brains are capable of the most complex social organization in animals - which warrants further attention. Research has focused on highly eusocial hymenopterans with extreme caste specialization and very large colony sizes that have passed social evolutionary points of no return. However, facultatively social insects that form small colonies (< 20 individuals) are likely to provide greater insight on brain selection at the origin-point of social group living. MethodsWe undertake the first neurobiological investigation of the facultatively social allodapine bees (Apidae: Xylocopinae: Allodapini), an exploratory study comparing single- and multi-female colonies ofExoneura angophorae. Using volume as a proxy for neural investment, we measured mushroom body calyces, optic lobes, antennal lobes and whole brains of queens, workers, and single-females to test three theories associating brain development with behavior: social brain hypothesis; distributed cognition hypothesis; sensory environment hypothesis. ResultsMushroom bodies were reduced in subordinate workers, but did not differ between queens and single-females. Workers had larger optic lobes than queens, but did not differ from single-females. There were no differences in antennal lobes or whole brain volume. DiscussionSocial caste, rather than multi-female versus single-female nesting, influenced mushroom body volume in this allodapine bee – counter to both social brain and distributed cognition theories and in alignment with halictine and ceratinine bees that also form small facultatively social colonies. Optic lobe enhancement is likely a response to dietary niche requirements for extra-nidal foraging behavior – which may be a highly plastic trait capable of rapid transition among allodapine and ceratinine bees that conforms with ecological intelligence hypotheses. These broad volumetric trends require further investigations on the functional neural circuitry involved in the aforementioned environmental contexts. 

Comparing the diversity of gut microbiota between and within social insect colonies can illustrate interactions between bacterial community composition and host behaviour. In many eusocial insect species, different workers exhibit different task behaviours. Evidence of compositional differences between core microbiota in different worker types could suggest a microbial association with the division of labour among workers. Here, we present the core microbiota ofAphaenogaster piceaant workers with different task behaviours. The genusAphaenogasteris abundant worldwide, yet the associated microbiota of this group is unstudied. Bacterial communities fromAphaenogaster piceagut samples in this study consist of 19 phyla, dominated by Proteobacteria, Cyanobacteria and Firmicutes. Analysis of 16S rRNA gene sequences reveals distinct similarity clustering ofAphaenogaster piceagut bacterial communities in workers that have more interactions with the refuse piles. Though gut bacterial communities of nurse and foraging ants are similar in overall composition and structure, the worker groups differ in relative abundances of dominant taxa. Gut bacterial communities from ants that have more interactions with refuse piles are dominated by amplicon sequence variants associated with Entomoplasmataceae. Interaction with faecal matter via refuse piles seems to have the greatest impact on microbial taxa distribution, and this effect appears to be independent of worker type. This is the first report surveying the gut microbiome community composition ofAphaenogasterants. 

Many organisms leave evidence of their former occurrence, such as scat, abandoned burrows, middens, ancient eDNA or fossils, which indicate areas from which a species has since disappeared. However, combining this evidence with contemporary occurrences within a single modeling framework remains challenging. Traditional binary species‐distribution modeling reduces occurrence to two temporally coarse states (present/absent), so thus cannot leverage the information inherent in temporal sequences of evidence of past occurrence. In contrast, ordinal modeling can use the natural time‐varying order of states (e.g. never occupied versus previously occupied versus currently occupied) to provide greater insights into range shifts. We demonstrate the power of ordinal modeling for identifying the major influences of biogeographic and climatic variables on current and past occupancy of the American pikaOchotona princeps, a climate‐sensitive mammal. Sampling over five years across the species' southernmost, warm‐edge range limit, we tested the effects of these variables at 570 habitat patches where occurrence was classified either as binary or ordinal. The two analyses produced different top models and predictors – ordinal modeling highlighted chronic cold as the most‐important predictor of occurrence, whereas binary modeling indicated primacy of average summer‐long temperatures. Colder wintertime temperatures were associated in ordinal models with higher likelihood of occurrence, which we hypothesize reflect longer retention of insulative and meltwater‐provisioning snowpacks. Our binary results mirrored those of other past pika investigations employing binary analysis, wherein warmer temperatures decrease likelihood of occurrence. Because both ordinal‐ and binary‐analysis top models included climatic and biogeographic factors, results constitute important considerations for climate‐adaptation planning. Cross‐time evidences of species occurrences remain underutilized for assessing responses to climate change. Compared to multi‐state occupancy modeling, which presumes all states occur in the same time period, ordinal models enable use of historical evidence of species' occurrence to identify factors driving species' distributions more finely across time. 

The phenomenon of ionic liquid (IL) nanoconfinement within a copolymer/IL membrane reportedly enhances membrane selectivity, solubility, and transport in gas separations. Also, the copolymer/IL membrane morphology has been found to affect IL stability at high transmembrane pressures. In this work, a combined mesoscopic dynamics simulation and hybrid grand canonical Monte Carlo/molecular dynamics (GCMC-MD) simulations were carried out to investigate the morphologies, as well as CO2/CH4 gas diffusivities, solubilities, and selectivities of polystyrene-b-poly(ethylene oxide) (PS-b-PEO)/1-Ethyl-3-methylimidazolium thiocyanate ([EMIM][SCN]) and PS-b-PEO/1-Ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide ([EMIM][Tf2N]) membranes. The latter simulations focused on nanoconfined ILs in the copolymer/IL phase boundaries at 2.5 and 5 nm confinement lengths. The investigated systems were four nanoconfined ILs, i.e., PS/[EMIM][SCN]/PEO (the IL forming a separate microphase, denoted IL-Micro), PS/[EMIM][Tf2N]/PEO, PS/[EMIM][SCN]-PEO/PS (the IL distributed in the PEO phase, denoted IL-PEO), and PS/[EMIM][Tf2N]-PEO/PS, and five control systems, i.e., PS/PEO/PS, bulk PS, bulk PEO, bulk [EMIM][SCN], and bulk [EMIM][Tf2N]. Based on the mesoscopic dynamics simulation results, the dominant membrane morphologies at IL loadings of <50 vol % were lamellar or cylindrical (favorable for both IL stability at high transmembrane pressures if the bedding planes are horizontal, i.e. at 90° to the nominal direction of the transmembrane pressure gradient) with the IL-PEO or IL-Micro phases. Also, there was an overall 50% match between the observed PS-b-PEO/[EMIM][SCN] and PS-b-PEO/[EMIM][Tf2N] membrane morphologies. Based on the MD simulation results, both CO2 and CH4 diffusivities were the smallest in the bulk PS (control) and highest in the PS/[EMIM][Tf2N]/PEO system (IL-Micro between the PS and PEO phases) at both confinement lengths. The CO2 diffusivities were, on average, larger when the confinement length increased to 5 nm. The GCMC-MD results indicated that the CO2 solubility in the IL-Micro phases was higher than in the corresponding bulk ILs at both confinement lengths, with the PS/[EMIM][Tf2N]/PEO system exhibiting the highest CO2 solubility, followed by the PS/[EMIM][SCN]/PEO system. Additionally, the permselectivities of the nanoconfined IL systems were, on average, 40–50% larger than those of the bulk systems, with the highest permselectivity observed for PS/[EMIM][Tf2N]/PEO at the confinement length of 5 nm. Overall, the IL nanoconfinement between the PS and PEO phases (IL-Micro) leads to significant improvements in the CO2/CH4 permselectivities, suggesting that strategies to create nanoconfined IL morphologies in the copolymer/IL membranes are very promising for optimizing the membrane gas separation performance. 

As a time-domain analogue of fluorescence imaging, FCS offers valuable insights into molecular dynamics, interactions, and concentrations within living cells. The primary insight generated by FCS is molecular mobility and concentration, which makes it useful for investigating molecular-scale details without the need for enrichment or separation. A specific strength of FCS is the ability to probe protein-protein interactions in live cells and several recent applications in this area are summarized. FCS is also used to investigate plasma membrane protein organization, with many applications to cell surface receptors and the mechanisms of drug binding. Finally, FCS is undergoing continual methodological innovations, such as imaging FCS, SPIM-FCS PIE-FCCS, STED-FCS, three-color FCS, and massively parallel FCS, which extend the capabilities to investigate molecular dynamics at different spatial and temporal scales. These innovations enable detailed examinations of cellular processes, including cellular transport and the spatial organization of membrane proteins.