Royal Society Open Science最新文献

The trunks of elephants have prominent wrinkles from their base to the very tip. But neither the obvious differences in wrinkles between elephant species nor their development have been studied before. In this work, we characterize the lifelong development of trunk wrinkles in Asian and African elephants. Asian elephants have more dorsal major, meaning deep and wide, trunk wrinkles (approx. 126 ± 25 s.d.) than African elephants (approx. 83 ± 13 s.d.). Both species have more dorsal than ventral major trunk wrinkles and a closer wrinkle spacing distally than proximally. In Asian elephants, wrinkle density is high in the 'trunk wrapping zone'. Wrinkle numbers on the left and right sides of the distal trunk differed as a function of trunk lateralization, with frequent bending in one direction causing wrinkle formation. Micro-computed tomography (microCT) imaging and microscopy of newborn elephants' trunks revealed a constant thickness of the putative epidermis, whereas the putative dermis shrinks in the wrinkle troughs. During fetal development, wrinkle numbers double every 20 days in an early exponential phase. Later wrinkles are added slowly, but at a faster rate in Asian than African elephants. We discuss the relationship of species differences in trunk wrinkle distribution and number with behavioural, environmental and biomechanical factors.

The simultaneous infection of organisms with two or more co-occurring pathogens, otherwise known as co-infections, concomitant infections or multiple infections, plays a significant role in the dynamics and consequences of infectious diseases in both humans and animals. To understand co-infections, ecologists and epidemiologists rely on models capable of accommodating multiple response variables. However, given the diversity of available approaches, choosing a model that is suitable for drawing meaningful conclusions from observational data is not a straightforward task. To provide clearer guidance for statistical model use in co-infection research, we conducted a systematic review to (i) understand the breadth of study goals and host-pathogen systems being pursued with multi-response models and (ii) determine the degree of crossover of knowledge among disciplines. In total, we identified 69 peer-reviewed primary studies that jointly measured infection patterns with two or more pathogens of humans or animals in natural environments. We found stark divisions in research objectives and methods among different disciplines, suggesting that cross-disciplinary insights into co-infection patterns and processes for different human and animal contexts are currently limited. Citation network analysis also revealed limited knowledge exchange between ecology and epidemiology. These findings collectively highlight the need for greater interdisciplinary collaboration for improving disease management.

Monitoring the flight behaviour of mosquitoes is crucial for assessing their fitness levels and understanding their potential role in disease transmission. Existing methods for tracking mosquito flight behaviour are challenging to implement in laboratory environments, and they also struggle with identity tracking, particularly during occlusions. Here, we introduce FlightTrackAI, a robust convolutional neural network (CNN)-based tool for automatic mosquito flight tracking. FlightTrackAI employs CNN, a multi-object tracking algorithm, and interpolation to track flight behaviour. It automatically processes each video in the input folder without supervision and generates tracked videos with mosquito positions across the frames and trajectory graphs before and after interpolation. FlightTrackAI does not require a sophisticated setup to capture videos; it can perform excellently with videos recorded using standard laboratory cages. FlightTrackAI also offers filtering capabilities to eliminate short-lived objects such as reflections. Validation of FlightTrackAI demonstrated its excellent performance with an average accuracy of 99.9%. The percentage of correctly assigned identities after occlusions exceeded 91%. The data produced by FlightTrackAI can facilitate analysis of various flight-related behaviours, including flight distance and volume coverage during flights. This advancement can help to enhance our understanding of mosquito ecology and behaviour, thereby informing targeted strategies for vector control.

The way biological systems respond to changes in parameter values caused by mutations is a key issue in evolution and quantitative genetics, as it affects fundamental aspects such as adaptation, selective neutrality, robustness, optimality, evolutionary equilibria, etc. We address this question using the enzyme-flux relationship in a metabolic network as a model of the genotype-phenotype relationship. The lack of a suitable mathematical tool from biochemical theory to investigate this relationship led us to use an analogy between electrical circuits and metabolic networks with uni-uni reactions. We show that a behaviour of diminishing returns, which is commonly observed at various phenotypic levels, is inevitable, irrespective of the complexity of the system. We also present a possible generalization to metabolic networks with both uni-uni and bi-bi reactions.

Independent replications are very rare in the behavioural and social sciences. This is problematic because they can help to detect 'false positives' in published research and, in turn, contribute to scientific self-correction. The lack of replication studies is, among other factors, due to a rather passive editorial approach concerning replications by many journals, which does not encourage and may sometimes even actively discourage submission of replications. In this Perspective article, we advocate for a more proactive editorial approach concerning replications and suggest introducing journal-based replication marketplaces as a new publication track. We argue that such replication marketplaces could solve the long-standing problem of lacking independent replications. To establish these marketplaces, a designated part of a journal's editorial board identifies the most relevant new findings reported within the journal's pages and publicly offers them for replication. This public offering could be combined with small grants for authors to support these replications. Authors then compete for the first accepted registered report to conduct the related replications and can thus be sure that their replication will be published independent of the later findings. Replication marketplaces would not only increase the prevalence of independent replications but also help science to become more self-correcting.

Targeting acetylcholinesterase is one of the most important strategies for developing therapeutics against Alzheimer's disease. In this work, we have employed a new approach that combines machine learning models, a multi-step similarity search of the PubChem library and molecular dynamics simulations to investigate potential inhibitors for acetylcholinesterase. Our search strategy has been shown to significantly enrich the set of compounds with strong predicted binding affinity to acetylcholinesterase. Both machine learning prediction and binding free energy calculation, based on linear interaction energy, suggest that the compound CID54414454 would bind strongly to acetylcholinesterase and hence is a promising inhibitor.

Facial expressions are critical for non-verbal communication. The Canis genus epitomizes the interplay between behaviour and morphology in the evolution of non-verbal communication. Recent work suggests that the levator anguli oculi medialis (LAOM) muscle is unique to dogs (Canis familiaris) within the Canis genus and evolved due to domestication. The LAOM raises the inner eyebrows, resulting in the 'puppy dog eyes' expression. Here, we test whether the LAOM is a derived trait in dogs by (i) examining the facial expression muscles of a closely related and ancestral wild Canis species, the coyote (C. latrans) and (ii) comparing our results with other Canis and canid taxa. We discover that coyotes have a well-developed LAOM like dogs, which differs from the modified/absent LAOM in grey wolves. Our findings challenge the hypothesis that the LAOM developed due to domestication. We suggest that the LAOM is a basal trait that was lost in grey wolves. Additionally, we find inter- and intraspecific variations in the size of the muscles of the outer ear, forehead, lips and rostrum, indicating potential adaptations related to sensory perception, communication and individual-level functional variations within canids. Together, this research expands our knowledge of facial expressions, their evolution and their role in communication.

Accounting for population age structure and age-specific contact patterns is crucial for accurate modelling of human infectious disease dynamics and impact. A common approach is to use contact matrices, which estimate the number of contacts between individuals of different ages. These contact matrices are frequently based on data collected from populations with very different demographic and socio-economic characteristics from the population of interest. Here we use a comprehensive household composition dataset based on Aotearoa New Zealand census and administrative data to construct a household contact matrix and a synthetic population that can be used for modelling. We investigate the behaviour of a compartment-based and an agent-based epidemic model parametrized using these data, compared with a commonly used contact matrix that was constructed by projecting international data onto New Zealand's population. We find that using the New Zealand household data, either in a compartment-based model or in an agent-based model, leads to lower attack rates in older age groups compared with using the projected contact matrix. This difference becomes larger when household transmission is more dominant relative to non-household transmission. We provide electronic versions of the synthetic population and household contact matrix for other researchers to use in infectious disease models.

Human communities have self-organizing properties in which specific Dunbar Numbers may be invoked to explain group attachments. By analysing Wikipedia editing histories across a wide range of subject pages, we show that there is an emergent coherence in the size of transient groups formed to edit the content of subject texts, with two peaks averaging at around $N=8$ for the size corresponding to maximal contention, and at around $N=4$ as a regular team. These values are consistent with the observed sizes of conversational groups, as well as the hierarchical structuring of Dunbar graphs. We use a model of bipartite trust to derive a scaling law that fits the data and may apply to all group size distributions when these are based on attraction to a seeded group process. In addition to providing further evidence that even spontaneous communities of strangers are self-organizing, the results have important implications for the governance of the Wikipedia commons and for the security of all online social platforms and associations.

As urbanization expands globally, human-wildlife interactions will inevitably increase. Here, we analysed 10 years of wildlife rehabilitation records of squamate (snake and lizard) reptiles (n = 37 075) from the Greater Sydney region, New South Wales, Australia, to explore their value to address management and conservation issues. Rescues were highly non-random regarding taxonomic focus, spatial occurrences and temporal trends due to the combined influence of (i) reptile phenology and behaviour and (ii) human perceptions of reptiles. Seasonal peaks in rescues reflect reptile and, to a lesser extent, human activity. Spatial patterns of rescues were informative about distributions and presence of easily identified taxa but were primarily driven by human presence. Larger squamate species were rescued more frequently, potentially reflecting a perception of greater danger or rescue priority. While uncommon species were often misidentified, accurate reports of these taxa may guide targeted surveys. The value of these data for conservation and management could be enhanced by emphasizing reptile identification training of volunteers and use of applications for informed species identification. Wildlife rehabilitation data offer a cost-effective means of quantifying thousands of human-reptile interactions, identifying foci (in both time and space) of human-wildlife conflict such as snakebite risk and roadkill-related reptile mortality.