Showing papers in "Royal Society Open Science in 2022"

Integrated phylogenomics and fossil data illuminate the evolution of beetles

Abstract: Beetles constitute the most biodiverse animal order with over 380 000 described species and possibly several million more yet unnamed. Recent phylogenomic studies have arrived at considerably incongruent topologies and widely varying estimates of divergence dates for major beetle clades. Here, we use a dataset of 68 single-copy nuclear protein-coding (NPC) genes sampling 129 out of the 193 recognized extant families as well as the first comprehensive set of fully justified fossil calibrations to recover a refined timescale of beetle evolution. Using phylogenetic methods that counter the effects of compositional and rate heterogeneity, we recover a topology congruent with morphological studies, which we use, combined with other recent phylogenomic studies, to propose several formal changes in the classification of Coleoptera: Scirtiformia and Scirtoidea sensu nov., Clambiformia ser. nov. and Clamboidea sensu nov., Rhinorhipiformia ser. nov., Byrrhoidea sensu nov., Dryopoidea stat. res., Nosodendriformia ser. nov. and Staphyliniformia sensu nov., and Erotyloidea stat. nov., Nitiduloidea stat. nov. and Cucujoidea sensu nov., alongside changes below the superfamily level. Our divergence time analyses recovered a late Carboniferous origin of Coleoptera, a late Palaeozoic origin of all modern beetle suborders and a Triassic-Jurassic origin of most extant families, while fundamental divergences within beetle phylogeny did not coincide with the hypothesis of a Cretaceous Terrestrial Revolution.

Causal machine learning for healthcare and precision medicine

Abstract: Causal machine learning (CML) has experienced increasing popularity in healthcare. Beyond the inherent capabilities of adding domain knowledge into learning systems, CML provides a complete toolset for investigating how a system would react to an intervention (e.g. outcome given a treatment). Quantifying effects of interventions allows actionable decisions to be made while maintaining robustness in the presence of confounders. Here, we explore how causal inference can be incorporated into different aspects of clinical decision support systems by using recent advances in machine learning. Throughout this paper, we use Alzheimer’s disease to create examples for illustrating how CML can be advantageous in clinical scenarios. Furthermore, we discuss important challenges present in healthcare applications such as processing high-dimensional and unstructured data, generalization to out-of-distribution samples and temporal relationships, that despite the great effort from the research community remain to be solved. Finally, we review lines of research within causal representation learning, causal discovery and causal reasoning which offer the potential towards addressing the aforementioned challenges.

Dynamics of cumulative advantage and threats to equity in open science: a scoping review

Abstract: Open Science holds the promise to make scientific endeavours more inclusive, participatory, understandable, accessible and re-usable for large audiences. However, making processes open will not per se drive wide reuse or participation unless also accompanied by the capacity (in terms of knowledge, skills, financial resources, technological readiness and motivation) to do so. These capacities vary considerably across regions, institutions and demographics. Those advantaged by such factors will remain potentially privileged, putting Open Science's agenda of inclusivity at risk of propagating conditions of ‘cumulative advantage’. With this paper, we systematically scope existing research addressing the question: ‘What evidence and discourse exists in the literature about the ways in which dynamics and structures of inequality could persist or be exacerbated in the transition to Open Science, across disciplines, regions and demographics?’ Aiming to synthesize findings, identify gaps in the literature and inform future research and policy, our results identify threats to equity associated with all aspects of Open Science, including Open Access, Open and FAIR Data, Open Methods, Open Evaluation, Citizen Science, as well as its interfaces with society, industry and policy. Key threats include: stratifications of publishing due to the exclusionary nature of the author-pays model of Open Access; potential widening of the digital divide due to the infrastructure-dependent, highly situated nature of open data practices; risks of diminishing qualitative methodologies as ‘reproducibility’ becomes synonymous with quality; new risks of bias and exclusion in means of transparent evaluation; and crucial asymmetries in the Open Science relationships with industry and the public, which privileges the former and fails to fully include the latter.

Digging deeper into colonial palaeontological practices in modern day Mexico and Brazil

Abstract: Scientific practices stemming from colonialism, whereby middle- and low-income countries supply data for high-income countries and the contributions of local expertise are devalued, are still prevalent today in the field of palaeontology. In response to these unjust practices, countries such as Mexico and Brazil adopted protective laws and regulations during the twentieth century to preserve their palaeontological heritage. However, scientific colonialism is still reflected in many publications describing fossil specimens recovered from these countries. Here, we present examples of ‘palaeontological colonialism’ from publications on Jurassic–Cretaceous fossils from NE Mexico and NE Brazil spanning the last three decades. Common issues that we identified in these publications are the absence of both fieldwork and export permit declarations and the lack of local experts among authorships. In Mexico, access to many fossil specimens is restricted on account of these specimens being housed in private collections, whereas a high number of studies on Brazilian fossils are based on specimens illegally reposited in foreign collections, particularly in Germany and Japan. Finally, we outline and discuss the wider academic and social impacts of these research practices, and propose exhaustive recommendations to scientists, journals, museums, research institutions and government and funding agencies in order to overcome these practices.

Analysis of flow loss characteristics of slanted axial-flow pump device based on entropy production theory

Abstract: Slanted axial-flow pump devices are widely applied in urban water supply, irrigation and drainage engineering fields. The second law of thermodynamics is applied to investigate the flow loss characteristics of the 30° slanted axial-flow pump model according to the flow loss analysis method of entropy production theory, so that the hydraulic loss characteristics can be revealed in internal flow process of the slanted axial-flow pump. The three-dimensional numerical simulation of the whole flow conduit in slanted axial-flow pump was conducted and the entropy production increased in the flow process was calculated. The location and distribution characteristics of the flow loss of the pump were qualitatively analysed. The results show that the entropy production in impeller is the highest among the pump components. With the increase of flow rate, the proportion of the entropy production in impeller in total value of the pump device increases continuously. The wall entropy production of impeller, guide vane and outlet conduit are lower than the mainstream entropy production, and the mainstream entropy production occupies the dominant position. As the flow rate grows, the proportion of turbulent dissipation entropy production decreases, and the proportion of wall dissipation entropy production increases. At 0.8Qbep, the proportion of turbulent dissipation entropy production is close to 74%, which is about 2.8 times that of wall entropy production. Under 1.2Qbep condition, the proportion of turbulent dissipation entropy production is just 5.5% higher than that of wall dissipation entropy production.

Oxidase enzymes as sustainable oxidation catalysts

Abstract: Oxidation is one of the most important processes used by the chemical industry. However, many of the methods that are used pose significant sustainability and environmental issues. Biocatalytic oxidation offers an alternative to these methods, with a now significant enzymatic oxidation toolbox on offer to chemists. Oxidases are one of these options, and as they only depend on molecular oxygen as a terminal oxidant offer perfect atom economy alongside the selectivity benefits afforded by enzymes. This review will focus on examples of oxidase biocatalysts that have been used for the sustainable production of important molecules and highlight some important processes that have been significantly improved through the use of oxidases. It will also consider emerging classes of oxidases, and how they might fit in a future biorefinery approach for the sustainable production of important chemicals.

A survey on how preregistration affects the research workflow: better science but more work

Abstract: The preregistration of research protocols and analysis plans is a main reform innovation to counteract confirmation bias in the social and behavioural sciences. While theoretical reasons to preregister are frequently discussed in the literature, the individually experienced advantages and disadvantages of this method remain largely unexplored. The goal of this exploratory study was to identify the perceived benefits and challenges of preregistration from the researcher’s perspective. To this end, we surveyed 355 researchers, 299 of whom had used preregistration in their own work. The researchers indicated the experienced or expected effects of preregistration on their workflow. The results show that experiences and expectations are mostly positive. Researchers in our sample believe that implementing preregistration improves or is likely to improve the quality of their projects. Criticism of preregistration is primarily related to the increase in work-related stress and the overall duration of the project. While the benefits outweighed the challenges for the majority of researchers with preregistration experience, this was not the case for the majority of researchers without preregistration experience. The experienced advantages and disadvantages identified in our survey could inform future efforts to improve preregistration and thus help the methodology gain greater acceptance in the scientific community.

Citation counts and journal impact factors do not capture some indicators of research quality in the behavioural and brain sciences

Abstract: Citation data and journal impact factors are important components of faculty dossiers and figure prominently in both promotion decisions and assessments of a researcher’s broader societal impact. Although these metrics play a large role in high-stakes decisions, the evidence is mixed about whether they are strongly correlated with indicators of research quality. We use data from a large-scale dataset comprising 45 144 journal articles with 667 208 statistical tests and data from 190 replication attempts to assess whether citation counts and impact factors predict three indicators of research quality: (i) the accuracy of statistical reporting, (ii) the evidential value of the reported data and (iii) the replicability of a given experimental result. Both citation counts and impact factors were weak and inconsistent predictors of research quality, so defined, and sometimes negatively related to quality. Our findings raise the possibility that citation data and impact factors may be of limited utility in evaluating scientists and their research. We discuss the implications of these findings in light of current incentive structures and discuss alternative approaches to evaluating research.

Language of fungi derived from their electrical spiking activity

Abstract: Fungi exhibit oscillations of extracellular electrical potential recorded via differential electrodes inserted into a substrate colonized by mycelium or directly into sporocarps. We analysed electrical activity of ghost fungi (Omphalotus nidiformis), Enoki fungi (Flammulina velutipes), split gill fungi (Schizophyllum commune) and caterpillar fungi (Cordyceps militaris). The spiking characteristics are species specific: a spike duration varies from 1 to 21 h and an amplitude from 0.03 to 2.1 mV. We found that spikes are often clustered into trains. Assuming that spikes of electrical activity are used by fungi to communicate and process information in mycelium networks, we group spikes into words and provide a linguistic and information complexity analysis of the fungal spiking activity. We demonstrate that distributions of fungal word lengths match that of human languages. We also construct algorithmic and Liz-Zempel complexity hierarchies of fungal sentences and show that species S. commune generate the most complex sentences.

Application of sulfur and nitrogen doped carbon quantum dots as sensitive fluorescent nanosensors for the determination of saxagliptin and gliclazide

Abstract: In this study, highly fluorescent sulfur and nitrogen doped carbon quantum dots (S,N-CQDs) were used as fluorescent nanosensors for direct spectrofluorimetric estimation of each of gliclazide (GLZ) and saxagliptin (SXG) without any pre-derivatization steps for the first time. S,N-CQDs were synthesized employing a simple hydrothermal technique using citric acid and thiosemicarbazide. The produced S,N-CQDs were characterized using different techniques including fluorescence emission spectroscopy, UV spectrophotometry, high-resolution transmission electron microscopy and FT-IR spectroscopy. Following excitation at 360 nm, S,N-CQDs exhibited a strong emission peak at 430 nm. The native fluorescence of S,N-CQDs was quantitatively enhanced by addition of increased concentrations of the studied drugs. The fluorescence enhancement of S,N-CQDs and the concentrations of the studied drugs revealed a wide linear relationship in the range of 30.0–500.0 µM and 75.0–600.0 µM with limits of detection of 5.0 and 10.15 µM for GLZ and SXG, respectively. The proposed method was efficiently used for determination of cited drugs in their commercial tablets with % recoveries ranging from 98.6% to 101.2% and low % relative standard deviation values (less than 2%). The mechanism of interaction between S,N-CQDs and the two drugs was studied. Validation of the proposed method was carried out in accordance with International Conference on Harmonization (ICH) guidelines.

Exposure to the COVID-19 pandemic environment and generosity

Abstract: We report data from an online experiment which allows us to study how generosity changed over a 6-day period during the initial explosive growth of the COVID-19 pandemic in Andalusia, Spain, while the country was under a strict lockdown. Participants (n = 969) could donate a fraction of a €100 prize to an unknown charity. Our data are particularly rich in the age distribution and we complement them with daily public information about COVID-19-related deaths, infections and hospital admissions. We find correlational evidence that donations decreased in the period under study, particularly among older individuals. Our analysis of the mechanisms behind the detected decrease in generosity suggests that expectations about others' behaviour, perceived mortality risk and (alarming) information play a key—but independent—role for behavioural adaptation. These results indicate that social behaviour is quickly adjusted in response to the pandemic environment, possibly reflecting some form of selective prosociality.

Stochastic rounding: implementation, error analysis and applications

Abstract: Stochastic rounding (SR) randomly maps a real number x to one of the two nearest values in a finite precision number system. The probability of choosing either of these two numbers is 1 minus their relative distance to x. This rounding mode was first proposed for use in computer arithmetic in the 1950s and it is currently experiencing a resurgence of interest. If used to compute the inner product of two vectors of length n in floating-point arithmetic, it yields an error bound with constant nu with high probability, where u is the unit round-off. This is not necessarily the case for round to nearest (RN), for which the worst-case error bound has constant nu. A particular attraction of SR is that, unlike RN, it is immune to the phenomenon of stagnation, whereby a sequence of tiny updates to a relatively large quantity is lost. We survey SR by discussing its mathematical properties and probabilistic error analysis, its implementation, and its use in applications, with a focus on machine learning and the numerical solution of differential equations.

Emergence of splits and collective turns in pigeon flocks under predation

Abstract: Complex patterns of collective behaviour may emerge through self-organization, from local interactions among individuals in a group. To understand what behavioural rules underlie these patterns, computational models are often necessary. These rules have not yet been systematically studied for bird flocks under predation. Here, we study airborne flocks of homing pigeons attacked by a robotic falcon, combining empirical data with a species-specific computational model of collective escape. By analysing GPS trajectories of flocking individuals, we identify two new patterns of collective escape: early splits and collective turns, occurring even at large distances from the predator. To examine their formation, we extend an agent-based model of pigeons with a ‘discrete’ escape manoeuvre by a single initiator, namely a sudden turn interrupting the continuous coordinated motion of the group. Both splits and collective turns emerge from this rule. Their relative frequency depends on the angular velocity and position of the initiator in the flock: sharp turns by individuals at the periphery lead to more splits than collective turns. We confirm this association in the empirical data. Our study highlights the importance of discrete and uncoordinated manoeuvres in the collective escape of bird flocks and advocates the systematic study of their patterns across species.

Food security and emerging infectious disease: risk assessment and risk management

Abstract: Climate change, emerging infectious diseases (EIDs) and food security create a dangerous nexus. Habitat interfaces, assumed to be efficient buffers, are being disrupted by human activities which in turn accelerate the movement of pathogens. EIDs threaten directly and indirectly availability and access to nutritious food, affecting global security and human health. In the next 70 years, food-secure and food-insecure countries will face EIDs driving increasingly unsustainable costs of production, predicted to exceed national and global gross domestic products. Our modern challenge is to transform this business as usual and embrace an alternative vision of the biosphere formalized in the Stockholm paradigm (SP). First, a pathogen-centric focus shifts our vision of risk space, determining how pathogens circulate in realized and potential fitness space. Risk space and pathogen exchange are always heightened at habitat interfaces. Second, apply the document-assess-monitor-act (DAMA) protocol developing strategic data for EID risk, to be translated, synthesized and broadcast as actionable information. Risk management is realized through targeted interventions focused around information exchanged among a community of scientists, policy practitioners of food and public health security and local populations. Ultimately, SP and DAMA protect human rights, supporting food security, access to nutritious food, health interventions and environmental integrity.

Resveratrol-loaded chitosan–pectin core–shell nanoparticles as novel drug delivery vehicle for sustained release and improved antioxidant activities

Abstract: Resveratrol, chemically known as 3,5,4'-trihydroxy-trans-stilbene, is a natural polyphenol with promising multi-targeted health benefits. The optimal therapeutic uses of resveratrol are limited due to its poor solubility, rapid metabolism and low bioavailability. To address the issues, we have encapsulated resveratrol inside the nanosized core made of chitosan and coated this core with pectin-shell in order to fabricate a drug delivery vehicle which can entrap resveratrol for a longer period of time. The core-shell nanoparticles fabricated in this way were characterized with the help of Fourier transform infrared spectrometer, field-emission scanning electron microscope, field-emission transmission electron microscopy/selected area electron diffraction, high-resolution transmission electron microscope, dynamic light scattering and zeta potential measurements. In vitro drug release study showed the ability of the core-shell nanoparticles to provide sustained release of resveratrol for almost 30 h. The release efficiency of the drug was found to be pH dependent, and a sequential control over drug release can be obtained by varying the shell thickness. The resveratrol encapsulated in a nanocarrier was found to have a better in vitro antioxidant activity than free resveratrol as determined by 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging method. This work finally offers a novel nano-based drug delivery system.

School and community reopening during the COVID-19 pandemic: a mathematical modelling study

Abstract: Operating schools safely during the COVID-19 pandemic requires a balance between health risks and the need for in-person learning. Using demographic and epidemiological data between 31 July and 23 November 2020 from Toronto, Canada, we developed a compartmental transmission model with age, household and setting structure to study the impact of schools reopening in September 2020. The model simulates transmission in the home, community and schools, accounting for differences in infectiousness between adults and children, and accounting for work-from-home and virtual learning. While we found a slight increase in infections among adults (2.2%) and children (4.5%) within the first eight weeks of school reopening, transmission in schools was not the key driver of the virus resurgence in autumn 2020. Rather, it was community spread that determined the outbreak trajectory, primarily due to increases in contact rates among adults in the community after school reopening. Analyses of cross-infection among households, communities and schools revealed that home transmission is crucial for epidemic progression and safely operating schools, while the degree of in-person attendance has a larger impact than other control measures in schools. This study suggests that safe school reopening requires the strict maintenance of public health measures in the community.

The puzzling relationship between multi-laboratory replications and meta-analyses of the published literature

Abstract: What is the best way to estimate the size of important effects? Should we aggregate across disparate findings using statistical meta-analysis, or instead run large, multi-laboratory replications (MLR)? A recent paper by Kvarven, Strømland and Johannesson (Kvarven et al. 2020 Nat. Hum. Behav. 4, 423–434. (doi:10.1038/s41562-019-0787-z)) compared effect size estimates derived from these two different methods for 15 different psychological phenomena. The authors reported that, for the same phenomenon, the meta-analytic estimate tended to be about three times larger than the MLR estimate. These results are a specific example of a broader question: What is the relationship between meta-analysis and MLR estimates? Kvarven et al. suggested that their results undermine the value of meta-analysis. By contrast, we argue that both meta-analysis and MLR are informative, and that the discrepancy between the two estimates that they observed is in fact still largely unexplained. Informed by re-analyses of Kvarven et al.’s data and by other empirical evidence, we discuss possible sources of this discrepancy and argue that understanding the relationship between estimates obtained from these two methods is an important puzzle for future meta-scientific research.

Trajectories of adolescent life satisfaction

Abstract: Increasing global policy interest in measuring and improving population wellbeing has prompted academic investigations into the dynamics of lifespan life satisfaction. Yet little research has assessed the complete adolescent age range, although it harbours developmental changes that could affect wellbeing far into adulthood. This study investigates how life satisfaction develops throughout the whole of adolescence, and compares this development to that in adulthood, by applying exploratory and confirmatory latent growth curve modelling to UK and German data, respectively (37 076 participants, 10-24 years). We find a near universal decrease in life satisfaction during adolescence. This decrease is steeper than at any other point across adulthood. Further, our findings suggest that adolescent girls' life satisfaction is lower than boys', but that this difference does not extend into adulthood. The study highlights the importance of studying adolescent subjective wellbeing trajectories to inform research, policy and practice.

Sparsifying priors for Bayesian uncertainty quantification in model discovery

Abstract: We propose a probabilistic model discovery method for identifying ordinary differential equations governing the dynamics of observed multivariate data. Our method is based on the sparse identification of nonlinear dynamics (SINDy) framework, where models are expressed as sparse linear combinations of pre-specified candidate functions. Promoting parsimony through sparsity leads to interpretable models that generalize to unknown data. Instead of targeting point estimates of the SINDy coefficients, we estimate these coefficients via sparse Bayesian inference. The resulting method, uncertainty quantification SINDy (UQ-SINDy), quantifies not only the uncertainty in the values of the SINDy coefficients due to observation errors and limited data, but also the probability of inclusion of each candidate function in the linear combination. UQ-SINDy promotes robustness against observation noise and limited data, interpretability (in terms of model selection and inclusion probabilities) and generalization capacity for out-of-sample forecast. Sparse inference for UQ-SINDy employs Markov chain Monte Carlo, and we explore two sparsifying priors: the spike and slab prior, and the regularized horseshoe prior. UQ-SINDy is shown to discover accurate models in the presence of noise and with orders-of-magnitude less data than current model discovery methods, thus providing a transformative method for real-world applications which have limited data.

An overview of chemo- and site-selectivity aspects in the chemical conjugation of proteins

Abstract: The bioconjugation of proteins—that is, the creation of a covalent link between a protein and any other molecule—has been studied for decades, partly because of the numerous applications of protein conjugates, but also due to the technical challenge it represents. Indeed, proteins possess inner physico-chemical properties—they are sensitive and polynucleophilic macromolecules—that make them complex substrates in conjugation reactions. This complexity arises from the mild conditions imposed by their sensitivity but also from selectivity issues, viz the precise control of the conjugation site on the protein. After decades of research, strategies and reagents have been developed to address two aspects of this selectivity: chemoselectivity—harnessing the reacting chemical functionality—and site-selectivity—controlling the reacting amino acid residue—most notably thanks to the participation of synthetic chemistry in this effort. This review offers an overview of these chemical bioconjugation strategies, insisting on those employing native proteins as substrates, and shows that the field is active and exciting, especially for synthetic chemists seeking new challenges.

Seasonality of coronavirus shedding in tropical bats

Abstract: Anticipating cross-species transmission of zoonotic diseases requires an understanding of pathogen infection dynamics within natural reservoir hosts. Although bats might be a source of coronaviruses (CoVs) for humans, the drivers of infection dynamics in bat populations have received limited attention. We conducted a fine-scale 2-year longitudinal study of CoV infection dynamics in the largest colony of Reunion free-tailed bats (Mormopterus francoismoutoui), a tropical insectivorous species. Real-time PCR screening of 1080 fresh individual faeces samples collected during the two consecutive years revealed an extreme variation of the detection rate of bats shedding viruses over the birthing season (from 0% to 80%). Shedding pulses were repeatedly observed and occurred both during late pregnancy and within two months after parturition. An additional shedding pulse at the end of the second year suggests some inter-annual variations. We also detected viral RNA in bat guano up to three months after bats had left the cave. Our results highlight the importance of fine-scale longitudinal studies to capture the rapid change of bat CoV infection over months, and that CoV shedding pulses in bats may increase spillover risk.

The impact of the COVID-19 pandemic on adolescent mental health: a natural experiment

Abstract: Despite widespread concern about the impact of COVID-19 on adolescent mental health, there remains limited empirical evidence that can causally attribute changes to the pandemic. The current study aimed to overcome existing methodological limitations by exploiting a serendipitously occurring natural experiment within two ongoing, multi-phase cluster randomized controlled trials. Depressive symptoms (primary outcome), externalizing difficulties and life satisfaction (secondary outcomes) were assessed at baseline (phase 1 [pre-COVID-19 group]: September - October 2018, phase 2 [COVID-19 group]: September - October 2019) and 1-year follow-up (pre-COVID-19 group: January - March 2020, COVID-19 group: February - April 2021). Participants in phase 1 (N = 6419) acted as controls. In phase 2, participants (N = 5031) were exposed to the COVID-19 pandemic between the baseline and follow-up assessments providing a natural experimental design. The primary analysis used a random intercept linear multivariable regression model with phase (exposure to the COVID-19 pandemic) included as the key predictor while controlling for baseline scores and individual and school-level covariates. Depressive symptoms were higher and life satisfaction scores lower in the group exposed to the COVID-19 pandemic. Had the COVID-19 pandemic not occurred, we estimate that there would be 6% fewer adolescents with high depressive symptoms. No effect of exposure to the pandemic on externalizing difficulties was found. Exploratory analyses to examine subgroup differences in impacts suggest that the negative impact of the COVID-19 pandemic on adolescent mental health may have been greater for females than males. Given the widespread concern over rising adolescent mental health difficulties prior to the pandemic, this paper quantifies the additional impacts of the pandemic. A properly resourced, multi-level, multi-sector public health approach for improving adolescent mental health is necessary. Following in-principle acceptance, the approved Stage 1 version of this manuscript was preregistered on the OSF at https://doi.org/10.17605/OSF.IO/B25DH. This preregistration was performed prior to data analysis.

DFT investigation on the application of pure and doped X12N12 (X = B and Al) fullerene-like nano-cages toward the adsorption of temozolomide

Abstract: The sensitivity of pure and doped X12N12 (X = B and Al) fullerene-like nano-cages (FLNs) toward the anti-cancer drug temozolomide (TMZ) is probed herein at DFT/M06-2X-D3/6-311G(d,p) theoretical level in both gas phase and water. A noticeable affinity of the FLNs toward TMZ was observed along with the negative gas-phase adsorption energies −1.37 and −2.09 eV for the most stable configurations of pure B12N12 and Al12N12 pristines, respectively. Considerable charge transfer from TMZ to the FLNs was also revealed via NBO analysis and the Hirshfeld atomic charges, making the dipole moment vector of the molecular complexes to be oriented from the nano-cages to the TMZ moiety. Furthermore, a percentage decrease in the HOMO-LUMO energy gap (ΔEg) of 38.09 and 17.72% was obtained for the B12N12 and Al12N12 nano-cages, respectively. The percentage change in ΔEg was found to be reduced upon doping and solvation of the FLNs. Finally, a recovery time in vacuum ultraviolet light of 1.06 s is found for the complex with pure B12N12, which in addition to the above-mentioned parameters make this boron nitride cage the best sensor for TMZ, among the FLNs considered in the present work.

The virtues and vices of protein citrullination

Abstract: The post-translational modification of proteins expands the regulatory scope of the proteome far beyond what is achievable through genome regulation. The field of protein citrullination has seen significant progress in the last two decades. The small family of peptidylarginine deiminase (PADI or PAD) enzymes, which catalyse citrullination, have been implicated in virtually all facets of molecular and cell biology, from gene transcription and epigenetics to cell signalling and metabolism. We have learned about their association with a remarkable array of disease states and we are beginning to understand how they mediate normal physiological functions. However, while the biochemistry of PADI activation has been worked out in exquisite detail in vitro, we still lack a clear mechanistic understanding of the processes that regulate PADIs within cells, under physiological and pathophysiological conditions. This review summarizes and discusses the current knowledge, highlights some of the unanswered questions of immediate importance and gives a perspective on the outlook of the citrullination field.

Tetracycline adsorption on magnetic sludge biochar: size effect of the Fe3O4 nanoparticles

Abstract: Activated sludge, which is difficult and expensive to treat and dispose of, is a key concern in wastewater treatment plants. In this study, magnetic sludge biochar containing activated sludge and different sizes (14.3, 40.2 and 90.5 nm) of Fe3O4 nanoparticles was investigated as an effective adsorbent for tetracycline (TC) adsorption. Magnetic sludge-based biochar was prepared by a facile cross-linking method and characterized by transmission electron microscopy, Fourier transform infrared spectroscopy (FTIR), X-ray diffraction, X-ray photoelectron spectroscopy (XPS) and zeta potential analysis. The adsorption performances of TC on three kinds of adsorbents were investigated. Although 14.3 nm Fe3O4 nanoparticles could be inclined to aggregate and partially filled with pores of biochar, it turned out that magnetic sludge biochar with 14.3 nm Fe3O4 nanoparticles exhibited optimum performance for TC removal with adsorption capacity up to 184.5 mg g−1, due to the larger amounts of functional groups and the change of zeta potential. Furthermore, the adsorption kinetics of TC on three kinds of adsorbents were studied, which implied that the pseudo-second-order kinetic model exhibited the better fit for the entire sorption process.

Climate change and alpine-adapted insects: modelling environmental envelopes of a grasshopper radiation

Abstract: Mountains create steep environmental gradients that are sensitive barometers of climate change. We calibrated 10 statistical models to formulate ensemble ecological niche models for 12 predominantly alpine, flightless grasshopper species in Aotearoa New Zealand, using their current distributions and current conditions. Niche models were then projected for two future global climate scenarios: representative concentration pathway (RCP) 2.6 (1.0°C rise) and RCP8.5 (3.7°C rise). Results were species specific, with two-thirds of our models suggesting a reduction in potential range for nine species by 2070, but surprisingly, for six species, we predict an increase in potential suitable habitat under mild (+1.0°C) or severe global warming (+3.7°C). However, when the limited dispersal ability of these flightless grasshoppers is taken into account, all 12 species studied are predicted to suffer extreme reductions in range, with a quarter likely to go extinct due to a 96–100% reduction in suitable habitat. Habitat loss is associated with habitat fragmentation that is likely to escalate stochastic vulnerability of remaining populations. Here, we present the predicted outcomes for an endemic radiation of alpine taxa as an exemplar of the challenges that alpine species, both in New Zealand and internationally, are subject to by anthropogenic climate change.

Distinctive diets of eutherian predators in Australia

Abstract: Introduction of the domestic cat and red fox has devastated Australian native fauna. We synthesized Australian diet analyses to identify traits of prey species in cat, fox and dingo diets, which prey were more frequent or distinctive to the diet of each predator, and quantified dietary overlap. Nearly half (45%) of all Australian terrestrial mammal, bird and reptile species occurred in the diets of one or more predators. Cat and dingo diets overlapped least (0.64 ± 0.27, n = 24 location/time points) and cat diet changed little over 55 years of study. Cats were more likely to have eaten birds, reptiles and small mammals than foxes or dingoes. Dingo diet remained constant over 53 years and constituted the largest mammal, bird and reptile prey species, including more macropods/potoroids, wombats, monotremes and bandicoots/bilbies than cats or foxes. Fox diet had greater overlap with both cats (0.79 ± 0.20, n = 37) and dingoes (0.73 ± 0.21, n = 42), fewer distinctive items (plant material, possums/gliders) and significant spatial and temporal heterogeneity over 69 years, suggesting the opportunity for prey switching (especially of mammal prey) to mitigate competition. Our study reinforced concerns about mesopredator impacts upon scarce/threatened species and the need to control foxes and cats for fauna conservation. However, extensive dietary overlap and opportunism, as well as low incidence of mesopredators in dingo diets, precluded resolution of the debate about possible dingo suppression of foxes and cats.

Language acquisition and speech rhythm patterns: an auditory neuroscience perspective

Abstract: All human infants acquire language, but their brains do not know which language/s to prepare for. This observation suggests that there are fundamental components of the speech signal that contribute to building a language system, and fundamental neural processing mechanisms that use these components, which are shared across languages. Equally, disorders of language acquisition are found across all languages, with the most prevalent being developmental language disorder (approx. 7% prevalence), where oral language comprehension and production is atypical, and developmental dyslexia (approx. 7% prevalence), where written language acquisition is atypical. Recent advances in auditory neuroscience, along with advances in modelling the speech signal from an amplitude modulation (AM, intensity or energy change) perspective, have increased our understanding of both language acquisition and these developmental disorders. Speech rhythm patterns turn out to be fundamental to both sensory and neural linguistic processing. The rhythmic routines typical of childcare in many cultures, the parental practice of singing lullabies to infants, and the ubiquitous presence of BabyTalk (infant-directed speech) all enhance the fundamental AM components that contribute to building a linguistic brain.

Vulnerability of avian populations to renewable energy production

Abstract: Renewable energy production can kill individual birds, but little is known about how it affects avian populations. We assessed the vulnerability of populations for 23 priority bird species killed at wind and solar facilities in California, USA. Bayesian hierarchical models suggested that 48% of these species were vulnerable to population-level effects from added fatalities caused by renewables and other sources. Effects of renewables extended far beyond the location of energy production to impact bird populations in distant regions across continental migration networks. Populations of species associated with grasslands where turbines were located were most vulnerable to wind. Populations of nocturnal migrant species were most vulnerable to solar, despite not typically being associated with deserts where the solar facilities we evaluated were located. Our findings indicate that addressing declines of North American bird populations requires consideration of the effects of renewables and other anthropogenic threats on both nearby and distant populations of vulnerable species.

Macrophage targeting of nitazoxanide-loaded transethosomal gel in cutaneous leishmaniasis

Abstract: Topical delivery is preferable over systemic delivery for cutaneous leishmaniasis, because of its easy administration, reduced systemic adverse effects and low cost. Nitazoxanide (NTZ) has broad-spectrum activity against various parasites and has the potential to avoid drug resistance developed by enzymatic mutations. NTZ oral formulation is associated with severe dyspepsia and stomach pain. Herein, NTZ-transethosomes (NTZ-TES) were prepared and loaded into chitosan gel (NTZ-TEG) for topical delivery. NTZ-TES were prepared by the thin-film hydration method and optimized statistically via the Box-Behnken method. The optimized formulation indicated excellent particle size (176 nm), polydispersity index (0.093), zeta potential (−26.4 mV) and entrapment efficiency (86%). The transmission electron microscopy analysis showed spherical-sized particles and Fourier-transform infrared spectroscopy analysis indicated no interaction among the excipients. Similarly, NTZ-TEG showed optimal pH, desirable viscosity and good spreadability. NTZ-TES and NTZ-TEG showed prolonged release behaviour and higher skin penetration and deposition in the epidermal/dermal layer of skin in comparison with the NTZ-dispersion. Moreover, NTZ-TES showed higher percentage inhibition, lower half-maximal inhibitory concentration (IC50) against promastigotes and higher macrophage uptake. Additionally, skin irritation and histopathology studies indicated the safe and non-irritant behaviour of the NTZ-TEG. The obtained findings suggested the enhanced skin permeation and improved anti-leishmanial effect of NTZ when administered as NTZ-TEG.