Royal Society Open Science最新文献

An accumulating body of evidence shows that offspring exposure to maternal obesity in the peri-natal period causes an increased risk to develop obesity later in life. Animal models have demonstrated that increased weight gain in offspring exposed to maternal obesity is preceded by increased food intake, implicating altered brain control of food intake as a likely cause. The hypothalamus is crucial for regulating feeding behaviour and energy homeostasis. This article reviews findings from human and animal studies to provide an updated perspective on how maternal obesity alters fetal hypothalamic development, predisposing offspring to long-term metabolic dysfunction. We discuss how maternal obesity impacts on hypothalamic development and the key molecular mechanisms, including epigenetic modifications, hormonal disruption, neuroinflammation and gut-brain axis interactions, which may mediate these changes. We highlight the critical gaps that remain in understanding the specific molecular pathways driving neurodevelopmental alterations in offspring, as well as emerging areas of research, including the role of extracellular vesicles in maternal-fetal communication. An in depth understanding of the molecular mechanisms that mediate the link between maternal metabolic state and offspring hypothalamic control of feeding is crucial in informing public health policies and clinical interventions aimed at reducing the intergenerational transmission of obesity.

Amplexus by male cane toads (Rhinella marina) impairs a female's mobility and may impose a risk of drowning. Near the arid-zone edge of the toads' Australian invasion, artificial ponds provide the only permanent open water. Cane toads must access water to hydrate every few nights, creating a potential for sexual conflict. Our field-based experiments show that a female toad that approaches one of these steep-sided dams encounters numerous reproductively active males, most of which are facing the shore. When amplexed by these males, she may find herself in deep water even close to the shore and is vulnerable to drowning. In trials with tethered females, toads amplexed in deep water could not hold their heads above the water's surface. Demographic effects of this sexual conflict are evident from population surveys: toad populations around dams are strongly male-biased whereas females are concentrated at mesic refuges around buildings that provide less dangerous conditions. Even around the same dam, female toads are often found on land whereas most males are found in the water. If sexual conflict around scarce waterbodies is lethal for female toads, we might reduce recruitment by allowing dense populations of male toads to persist.

Climate change is slowly influencing boreal forest ecosystems, with rising temperatures and altered snow conditions driving phenological shifts in many plant and animal species. Using 7 years (2016-2022) of camera trap data from the Kluane Lake region, Yukon, we quantified seasonal moulting phenology and coat-colour mismatch in snowshoe hares. Autumn moult started between 28 September and 3 October and completed between 5 and 11 November, with the mean moult duration ranging from 36 to 43 days. Spring moult initiated between 12 April and 27 April and completed between 16 May and 27 May, with moult duration ranging from 24 to 38 days. Contrary to our expectations, there was no evidence of delayed or advanced moulting phenology over this 7-year period. The mismatch between snowshoe hare coat colour and background showed an increasing trend and average whiteness of the snowshoe hare coat in autumn declined. Temperature and snow variables influenced various aspects of seasonal moulting phenology, in some cases in the opposite direction. Long-term studies utilizing intrinsic and high-resolution microclimatic data and behavioural observations are needed to understand how moulting phenology and mismatch affect predator-prey dynamics and snowshoe hare demography and population dynamics as climate change continues.

Digital representation of materials is crucial in fields such as virtual reality, industrial design and quality control. However, predicting human perception of materials from image data is challenging due to the complexity of material appearances and the intricacies of human vision. This study introduces a perceptual representation termed the 'visual fingerprint', linking image-based measurements of materials to intuitive, human-understandable attributes. We conducted psychophysical studies using standardized video sequences of 347 diverse real-world materials, including fabrics and wood, selected to encompass a broad spectrum of textures, colours and reflective properties. Sixteen key appearance attributes were identified, and over 110 000 human ratings were collected to map perceptual attributes across material categories. By integrating CLIP-derived image features with a multi-layer perceptron model, we developed a predictive framework for material perception. Our results demonstrate that human judgements of appearance and similarity can be accurately predicted using only two images of a material. This work offers a practical and interpretable approach to material representation, enabling intuitive comparisons and retrievals in applications where material appearance is crucial. The proposed material fingerprint and its prediction directly from image data represent a significant step towards simplifying the understanding and interoperability of material properties in diverse digital environments.

The traditional dissections of the specialized mimetic muscles that produce facial expressions have revealed important insights into the evolution of muscles and their function in human and other mammals' social interactions. However, in small species, the task of manually visualizing and analysing musculature is challenging; even in larger species and muscles, digital anatomy methods, such as DiceCT and MRI-DTI, have been growing in popularity recently, providing detailed new insights into the structure and morphology of muscles. The current work presents for the first time a 9.4T MRI-DTI visualization and analysis of the complete facial musculature used for facial expression in a primate species, in this case a very small species hard to analyse with traditional dissection, the common marmoset. In addition, a quantification and comparison of overall, individual and bilateral muscles was performed in the light of functional anatomy, followed by a critical analysis of this novel method for the study of facial anatomy. Twenty-two muscles were tracked, described, quantified and compared in three individuals. This work demonstrates the feasibility of MRI-DTI as a relatively novel method to digitally visualize the structure of facial muscles in a small species. In addition, this method is able to quantify varied muscle parameters for comparisons between individuals, muscles and hemifaces.

We present a mathematical model for optimizing breakaway strategies in competitive cycling, balancing power expenditure, aerodynamic drag and crashing. Our framework incorporates probabilistic crash dynamics, allowing a cyclist's risk tolerance to shape optimal tactics. We define an objective function that accounts for both finish time differences and the probability of crashing, which we optimize subject to an energy expenditure constraint. We demonstrate the methodology for a flat stage with a simple constant-power breakaway. We then extend this analysis to account for fatigue-driven power decay and varying terrain and race conditions. We highlight the importance of strategy by demonstrating that carefully planned decision making can lead to a race win even when the energy expenditure is low. Our results highlight and quantify the fact that, at the elite level, success often depends as much on minimizing risk as on maximizing physical output.

The high capacity of human iconic memory (IM) has been taken as evidence that visual experience is rich and detailed, as introspection suggests. Opponents to this view argue instead that this impression is illusory, with conscious access being mostly limited to what we can attend to. To provide evidence of either view, in this registered report we compared metacognitive sensitivity levels between IM and working memory (WM) representations. The rationale was that, if pre-attentive IM information is as consciously accessible as attention-bounded WM information, metacognitive sensitivity should be comparable across the two memory systems. Replicating classic findings, our results showed that IM capacity exceeded WM capacity. Nevertheless, and despite matched performance, metacognitive sensitivity was higher in WM. We further examined whether reduced metacognition in IM could be explained by inflation-the tendency to overestimate perceptual richness-by comparing confidence levels across the two memory conditions. Pre-registered analyses showed no evidence of inflation, as IM was associated with lower confidence. Our findings suggest that IM supports identification with less consciously accessible information than WM, challenging rich-view interpretations of conscious perception.

Generative adversarial networks (GANs) can create realistic synthetic faces, which have the potential to be used for nefarious purposes. The synthetic faces produced by GANs are difficult to detect and are often judged to be more realistic than real faces. Training programmes have been developed to improve human synthetic face detection accuracy, with mixed results. Here, we investigate synthetic face detection and discrimination in super-recognizers (SRs; who have exceptional face recognition skills), and typical-ability control participants. We also devised a training procedure which sought to highlight rendering artefacts. In two different experimental designs, we found that SRs (total N = 283) were better at detecting and discriminating synthetic faces than controls (total N = 381), where control participants were below chance without training. Trained SRs and controls had significantly better performance than those without training, and the magnitude of the training effect was similar in both groups. Our results suggest that SRs are using cues unrelated to rendering artefacts to detect and discriminate synthetic faces, and that an easily implementable training procedure increases their performance to above chance levels. These results have implications for real-world scenarios, where trained SRs' performance could be harnessed for synthetic face detection.

Akodon montensis is widely distributed throughout the Atlantic Forest (AF) hotspot biodiversity, encompassing Brazil and reaching its southern limit in eastern Paraguay and northeastern Argentina. Here, we combined analysis of molecular data and ecological niche modelling to contribute to elucidating its evolutionary history. At a local scale, we studied the genetic variability in microsatellite loci in populations from the remaining AF in Misiones province, Argentina. The moderate genetic differentiation observed in some populations suggests that limited gene flow may result from habitat fragmentation at the south of the AF. At a wide geographic range, the ecological niche modelling identified areas of high environmental suitability for A. montensis during the last glacial maximum (LGM) on the coast of Brazil, where the forested habitats expanded onto the continental shelf. This could explain the high diversity in the cytochrome b in this region and contiguous areas, agreeing with the Atlantis Forest hypothesis. Additionally, we observed an extended area of high habitat suitability during the LGM and at present in southwestern Brazil, eastern Paraguay and northeastern Argentina. The evolutionary history of A. montensis seems to have been influenced by demographic processes that occurred at different times and regions, shaping its genetic variability and structure.

With growing concerns over water pollution and depletion of freshwater resources, finding sustainable and cost-effective solutions for water treatment is crucial. This study introduces a novel MIL-53(Fe)/Mn-doped SrTiO₃ (MIL-53(Fe)/Mn-STO) direct Z-scheme photocatalyst, designed to efficiently degrade organic contaminants in water. Specifically, the photocatalytic degradation of o-nitrophenol (ONP) was investigated under an Xe lamp. The MIL-53(Fe)/Mn-STO photocatalyst demonstrated a maximum removal efficiency of 97.75% within 90 min, with a rate constant (k) of 0.0374 min^-1, outperforming the individual MIL-53(Fe) and Mn-STO photocatalysts. A comprehensive analysis of the material's properties was conducted using Fourier transform Infrared spectroscopy, energy dispersive X-ray spectroscopy, scanning electron microscopy, diffuse reflectance spectroscopy and photoluminescence techniques, and the photocatalytic activity was evaluated under various conditions, including variations in pH, ONP concentration, catalyst dosage and the presence of inorganic anions. The improved photocatalytic activity of the MIL-53(Fe)/Mn-STO system can be ascribed to the synergistic interaction between its two components, which also contributed to its excellent recyclability over five cycles. These findings demonstrate that MIL-53(Fe)/Mn-STO is a highly effective and sustainable photocatalyst with a strong potential for wastewater treatment applications.