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One question we can ask when investigating the nature of self-representation concerns the types of property that must figure in its content. Here, authors have claimed that self-representations must be about spatial, temporal, bodily, or mental properties. However, we can also ask a second question: how do we need to represent a property to self-represent it? I address this latter question. I argue that a distinction between egocentric and allocentric forms of representation-known from spatial cognition-also applies to representations of other kinds of property. I use examples drawn from animal cognition and developmental psychology to show how creatures allocentrically represent their temporal, bodily, and cognitive properties. These representations are minimal self-representations: they represent one's properties so that an explicit differentiation is made between the system and other objects (or between the system's actual and merely possible properties), they are directly linked to behavior and sensation, and they are immune to error through misidentification. The upshot is a view on which different creatures may self-represent more or fewer kinds of property. More substantive forms of self-representation (for instance, as exemplified by neurotypical adult human beings) then require integrated minimal self-representations of the right kinds of property.

Owing to the extreme toxicity of thiamethoxam, its presence in the aquatic environment can easily cause hazardous risks to people and marine creatures. Accordingly, this study focused on developing high-performance, sustainable, and economical adsorbents, namely biochar derived from corn husk (BC), ferric xanthan gum/okra mucilage beads (XO), BC with xanthan/okra mucilage composite beads (BCXO), for adsorbing thiamethoxam. BCXO's exhibiting a remarkable adsorption performance, demonstrating its mesoporosity (pore diameter of 5.8 nm), pHPZC (6.1), and surface area of 282.8 m2/g. The accurate simulation of thiamethoxam adsorption on the studied adsorbents was performed using a variety of nonlinear kinetic models and isotherm models. The nonlinear Langmuir isotherm model provided a superior fit compared to the Freundlich model, evidenced by higher average R2 (0.9662 vs. 0.869) and lower reduced χ2 values (0.7554 vs. 3.2424).The qm value of BCXO was found to be 158.3 mg/g, the highest among the tested adsorbents, under the fixed experimental circumstances (3 g/L dose, pH 7, 2 h agitation period, and 25 °C). Application to a real wastewater sample resulted in a 41.8% decrease in BCXO adsorption capacity compared with the synthetic solution due to competing ions and coexisting contaminants. The thermodynamic results revealed the adsorption mechanism's exothermicity and spontaneity. BCXO proved its efficacy as a reusable adsorbent, declining by only about 2.3% over eight reuse rounds. The adsorption mechanism is mainly governed by pore diffusion and surface interactions, particularly hydrogen bonding, with possible electrostatic and coordination interactions.

Walker's "Homo informatio" (Walker, 2025) and Deacon's recent work on grounding information in thermodynamics (Deacon, 2025) together mark a significant "informational turn" in the study of anthropogenesis. This paper provides a systematic comparative analysis of these two landmark contributions, examining their theoretical foundations, core mechanisms, and complementary relationships. Deacon offers a naturalistic grounding for information and meaning rooted in thermodynamic work and constraint, explaining what information fundamentally is and how symbolic meaning can be physically anchored. Walker provides an evolutionary mechanistic framework that integrates paleoanthropological evidence with theoretical constructs such as small-world networks, zones of bounded surprisal (ZBS), and active inference, explaining how human information-processing capacities evolved. Despite their different entry points-philosophical grounding versus evolutionary reconstruction-these theories share a common naturalistic paradigm that transcends classical Shannon information theory by insisting that information possesses referentiality and normativity. We argue that their integration yields a complete explanatory chain from physical constraints to human uniqueness: Deacon's "displaced grounding" through cultural practice provides the theoretical foundation for the "survival information" and "constructive information" that circulate through Walker's evolutionary model. Together, these frameworks illuminate how humans became both the "symbolic species" and "Homo informatio"-creatures uniquely defined by their capacity for information and meaning.

In mythology, teratology refers to fantastic creatures and monsters, but the "science of monsters" in biology refers to congenital abnormalities and abnormal formations. These anomalies are well reported in ticks, but only a few of them deal with Ixodes ticks, ticks collected from wildlife, or ticks from Africa. This study investigated a large collection of Afrotropical ticks, Ixodes (Afrixodes), collected from wildlife, which included two nymphs (Ixodes (A.) spp.) and one adult female (I. rasus) that turned out to be teratological specimens, presenting ectromely (missing leg). The present work represents the first report of morphological abnormalities in Ixodes (A.) rasus and Ixodes (A.) spp. collected on Muridae, Soricidae and Tragulidae in the Central African Republic and Gabon.

The aspiration of this review is to discuss the intricate development of Müller glial cells (MGCs) and their indispensable neuroprotective and regenerative roles, as well as novel avenues of treatment for retinal neurodegenerative diseases. MGCs are the principal radial glial cells of the vertebrate retina, extending from what is composed of a characteristic funnel-shaped morphology spanning throughout the retinal thickness. Their cell bodies are in the inner nuclear layer (INL), and their processes span from the outer limiting membrane to the inner limiting membrane, where they strongly associate with neurons, blood vessels, and the extracellular matrix across all layers of retinal structure. These cells preserve ionic and water homeostasis, control neurotransmitter uptake, and participate in constructing the blood retinal barrier (BRB), as well as deliver crucial metabolic help to neurons by means of the glutamate-glutamine cycle, thus excluding excitotoxic injury. First, we analysed the molecular processes underlying MGCs activation: pro-inflammatory molecules, Reactive oxygen species (ROS), and survival pathways. Special notice was made of changes in gene expression upon activation and the recrudescence of embryonic developmental programs that permit cell-cycle re-entry and retinal regeneration. Systematic searches of Google Scholar and PubMed to find relevant literature. Upon activation, Müller's glia, a type of retinal support cell, commence the expression of protective genes, such as Zfp36, Mt1, and Slc14a1. Some creatures could regenerate; however, in mammals, this capacity is limited, which is particularly evident in the retina, where, despite the activation of Müller's glia, full regeneration of damaged photoreceptors is not achieved. MGCs produces retinal progenitors that assist photoreceptors and interneurons while maintaining retinal integrity. MGCs contain progenitor cells that can differentiate into both neurons and other retinal cell types. Molecular targets for retinal therapeutics that utilize MGCs include pathways that regulate inflammation and oxidative stress. Müller glial cells are essential for maintaining retinal health, safeguarding neurons, and facilitating their regeneration. Targeted molecular therapy is addressed as a promising strategy for retinal neurodegenerative diseases, using their regenerative and protective potential.

Sea urchins are interesting creatures that play important ecological roles in the sea and are popular for their culinary and medicinal uses, which belong to phylum of Echinodermata. However, rapid environmental changes create a significant impact on marine species, including sea urchins, causing them severe stress. To address this issue, scientists are attempting to cultivate sea urchins in aquaculture to aid both conservation and commercial efforts. In this study, we aimed to investigate the physiological effects of stressors on sea urchin Arbacia punctulata, using three different stress conditions: increased temperature as a physical stressor, inoculation of lipopolysaccharides (LPS) as a chemical stressor, and a combination of both (increased temperature and LPS). We collected coelomic fluid (CF) from all the experimental groups at day 1, day 3, day 7, and day 10 and observed significant variations in the numbers of total and differential coelomocytes, namely, phagocytic cells, vibratile cells, red spherule cells, and colorless spherule cells in different stress conditions compared to controlled conditions (p&#x2009;<&#x2009;0.05). The immune cells of sea urchins, especially phagocytic cells and red spherule cells, actively responded with LPS (4 &#xb5;g/ml of CF/day). Our study also found a significant amount of protein in sea urchin's cell free coelomic fluid exposed to increased temperature stress (p&#x2009;<&#x2009;0.05) compared to that of control group. Both physical and chemical stressors impacted the growth and reproduction of sea urchins for long time exposure to stressors. We also observed lower gonadosomatic index (GSI) in the group exposed combined stressors: LPS inoculation (4 &#xb5;g/ml of CF/day) and increased temperature (1&#x2da;C/day) in comparison with the control group (p&#x2009;<&#x2009;0.05) at day 10.

'Artificial intelligence' (AI), as a blanket term, covers many advanced computing techniques that employ divergent methodologies for a wide array of functions. It is too late to affect general usage of the term without qualification-although it is a misnomer-but perhaps not too late to argue for the preferential use of more specific and realistic terminologies when discussing useful applications in science and medicine. Large language models are statistical tools for predicting text; machine learning algorithms are programs that discern patterns from data; and neural networks are mathematical models that predict outputs from inputs. In all cases, the software is unaware of what it is doing or why. The real intelligence is human, exemplified by the expertize of the engineers who designed any particular system, and by the scepticism, realism and vision of those who interpret and apply its outputs. Users may suspend their incredulity if large language models that are not sentient creatures are programmed to answer questions in the first person, since that encourages anthropomorphism. Perhaps we need a new word-which could be 'logimorphism'-to emphasize the dangers of interacting uncritically with inanimate software programs while overtly or subconsciously ascribing them human cognitive powers. Implementing high standards when applying new computing tools in clinical research and practice should start with the avoidance of inappropriate language that degrades our thinking.

Sample Exploring the ocean environment holds profound significance in areas such as resource exploration and ecological protection. Underwater robots struggle with extreme water pressure and often cause noise and damage to the underwater ecosystem, while bio-inspired soft robots draw inspiration from aquatic creatures to address these challenges. These bio-inspired approaches enable robots to withstand high water pressure, minimize drag, operate with efficient manipulation and sensing systems, and interact with the environment in an eco-friendly manner. Consequently, bio-inspired soft robots have emerged as a promising field for ocean exploration. This paper reviews recent advancements in underwater bio-inspired soft robots, analyses their design considerations when facing different desired functions, bio-inspirations, ambient pressure, temperature, light, and biodiversity, and finally explores the progression from bio-inspired principles to practical applications in the field and suggests potential directions for developing the next generation of underwater soft robots.

Urban trees are attracting increasing interest due to their contribution to mitigating some negative urbanization effects. Indeed, trees provide numerous ecosystem services such as carbon sequestration, heat island mitigation, habitats for myriad living creatures, and aesthetic values. However, a lack of tree diversity at the street and neighborhood levels threatens their resilience and service delivery. This article presents SylvCiT, a machine learning and optimization-based system that recommends a diversity of suitable tree species based on functional traits, planting location, and neighboring trees, and therefore maximizes functional diversity at different spatial scales. Special emphasis is placed on human-machine interfaces, including factors that affect user experience, recommendation acceptance and transparency. We show two use cases within SylvCiT. First, we analyze the urban forest of a Montreal neighborhood (Quebec, Canada) in terms of tree diversity, structure, and carbon storage. Second, we assessed species and functional group richness and diversity in 10 parks of Montreal and simulated the effects of planting the recommended species, which resulted in higher species and functional group diversity.

Even before the advent of multicellular life, unicellular creatures would communicate with their neighbours to coordinate their behaviours. Multicellular organisms have the particular challenge of orchestrating the differentiation of stem and progenitor cells to generate and maintain coherent functional tissues. However, stem and progenitor cells face a problem: their differentiation response can be buffeted by oscillations or stochastic fluctuations in intrinsic regulators. This generates cell-to-cell variability, which can be further compounded when extrinsic cues don't provide clear unambiguous instructions. So, left to their own devices, cells may differentiate at different rates or different directions even in response to the same cues. Fortunately, cells in multicellular organisms are not left to their own devices: they continually sense and respond to the behaviours of their neighbours. Here I discuss when, where, and how stem and progenitor cells communicate to synchronise their response to differentiation cues. I highlight technical challenges in identifying such synchronisation mechanisms, and survey emerging technologies that may help overcome these challenges.

Underwater soft robots offer many potential applications, including exploration, search, and rescue missions. Notably, these recently developed underwater soft robots present a safer and more adaptable alternative to rigid robots currently in use. Their flexible and deformable bodies enable them to easily adapt to challenging underwater environments and interact with diverse aquatic creatures and structures. In this paper, we present a soft buoyancy gripper that can manage buoyancy and adjust its position in the water without relying on external mechanisms. Modulating the volume of internal fluid can function both as a gripper and adjust buoyancy as needed. When buoyancy is reduced and fluid volume is minimized, the gripper can securely grasp objects, while increased fluid volume and buoyancy allow for delicate object placement. During experiments, the gripper successfully grasped and released multiple objects. When an extra channel was added, the crawling motion was achieved. The buoyancy control system demonstrates versatility and adaptability, offering the possibility of safe underwater exploration and research. Its ability to operate without harming marine environments or organisms makes it suitable for underwater research.

The third biggest concentration of metallic ions is traces of the element copper (Cu2+), which is crucial to all living creatures and plays a key role in several operations. However, deficiency or excessive copper ions may trigger a wide range of disorders, as determined by cellular requirements. To identify these factors, optical SPR-based refractive index sensors have emerged that&#xa0;concentrate&#xa0;on the swift identification of Cu2&#x2009;+&#x2009;ions in the present moment,&#xa0;that has excellent selectivity and sensitivity. Here, this paper intends to design and discuss a Four-Quadrant Circular Grid Refractive Index Biosensor (FQCGRIB) with a machine learning approach for detecting heavy metals like Cu2+. The four-quadrant circular grid refractive index biosensor enhances conventional biosensor performance via improved accuracy, sensitivity, specificity, and detection efficiency. significant sensitivity values of 719.85&#xa0;nm/RIU, 763.35&#xa0;nm/RIU, 761.90&#xa0;nm/RIU, and 734.52&#xa0;nm/RIU are achieved for n2cu2+, n3cu2+, n4cu2+, and n5cu2+, respectively. Simultaneously, a greater detection range of 1175.46, 1175.14, 1176.47, 1189.56, and 1180.59, along with a greater quality factor of 835.35&#xa0;nm/RIU, 828.85&#xa0;nm/RIU, 827.72&#xa0;nm/RIU, 843.21&#xa0;nm/RIU, and 828.57&#xa0;nm/RIU, for the n1cu2+, n2cu2+, n3cu2+, n4cu2+, and n5cu2+, respectively, is obtained. In addition, the minimal achieved detection limit is 0.000932 for n4cu2+, and a greater figure of merit is 382.86 for n4cu2+. The high predicted value of 0.981494 has been achieved by the machine learning approach for Cu2+ ions, and the mean square error value of 0.001987 for Cu2+ ions. Along with the results, this sensor has a greater capability with compactness in detecting heavy metal ions.

High-altitude hypoxia challenges avian embryonic development, prompting the evolution of phenotypic traits of plateau creatures such as the Snowy White chicken. However, how the possible changes in adaptations when those birds are transferred to lowland remain uncertain. We investigated the phenotypic and molecular changes over three generations (G0: the initial Generation in the plateau; G1 to G2: the first to second generation birds transferred to the lowland at Ya'an, Sichuan province) of Snowy White chickens. We assessed the eggshell characteristics at day 315 of the layers, and the organ index and the expression of hypoxia-responsive metabolic genes of heart, liver, lung, and kidney for the embryos at day 20 from G0 to G2. Our findings indicated that eggshell, as the most important structure affecting embryo respiration, exhibits significant changes. Birds from G1 and G2 exhibited increased eggshell thickness, reduced pore density, and decreased water vapor permeability compared with those in G0 (P < 0.05). The embryonic organ indices (heart, liver, lung and kidney) increased in G1 and G2 compared with those from G0 (P < 0.05). More interesting, G0 demonstrated higher levels of HIF-1&#x3b1;, VEGF, and glycolytic genes (GLUT2, HK2, and LDHA) in heart, lung, and kidney, but lower levels of oxidative phosphorylation genes (IDH2 and MDH1) (P < 0.05) than those by G1 and G2. Our findings of the low-altitude adaptations observed in Snowy White chickens indicate that the phenotypic and genetic expression pattern of important respiratory metabolism organs are reconfigurable to maintain the survival of the birds in the new environment. Our research offers valuable insights into the evolutionary dynamics of attitude adaption for those living being which tranters their living environment.

Highly scattering materials have widespread applications in daily life. Achieving efficient light scattering often requires the use of high-refractive-index inorganic materials, such as titanium dioxide. However, the production of titanium dioxide particles leads to serious environmental pollution, and since 2020, they have been classified by the EU as a Category 2 carcinogen for inhalation. Therefore, it is urgent to develop safer materials for preparing highly scattering products, such as polymers. Recently, scientists have made remarkable progress in the preparations and applications of highly scattering polymeric materials through mimicking the delicate internal structure of white-appearing creatures found in nature. This viewpoint summarizes the current progress and applications in highly scattering polymeric materials and forecasts future trends. Unlike previous reviews, this work systematically evaluates the use of natural polymers&#x2500;specifically cellulose and its derivatives&#x2500;for producing highly scattering materials and their corresponding applications in optoelectronics, wearable devices and passive radiative cooling.

Arthropods, such as jumping spiders, depend on vision over a distance when hunting. Their tactics suggest planning. Experimental evidence indicates that they use representations acquired from one location when acting in another. These tiny creatures should, therefore, depend upon reality-monitoring and be conscious. Is this necessarily the case? Could we know what sort of consciousness they might possess?

A wide diversity of arthropod taxa have demonstrated the capacity for learning, but most of our current understanding comes from only a select subset of this highly diverse clade, with most studies focusing on various insect groups. Amblypygids (Order Amblypygi, Class Arachnida), however, are emerging as a model group for studying sensory integration and the neural substrates associated with learning and memory, especially as it relates to navigation. These nocturnal creatures possess specialized sensory appendages and one of the largest and most complex mushroom bodies - the part of the arthropod brain associated with learning and memory - of any arthropod. Prior field studies on multiple species demonstrate sophisticated homing abilities while laboratory-based behavioral assays in Phrynus marginemaculatus confirm olfactory-based learning associated with a refuge. In this study, we expand these laboratory-based assays to test the olfactory learning ability of two additional amblypygid species - Paraphrynus laevifrons and Phrynus pseudoparvulus - for which field data suggest complex navigation. We trained each species to associate an open refuge with a distinct chemical stimulus, using slightly different species-specific experimental details. We found evidence of olfactory learning in the training trials for both species, with an unexpected pattern of seeming avoidance learning of hexanol. Our test trials did not show significant associations with the trained stimulus, but this may have been in part due to our experimental design. Ultimately, we find some evidence of olfactory learning in additional amblypygid species, but our findings raise additional questions and highlight the need for species-specific study designs.