Biodiversity is facing a global extinction crisis that will reduce ecological trait diversity, evolutionary history, and ultimately ecosystem functioning and services.
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A key challenge ...is understanding how species losses will impact morphological and phylogenetic diversity at global scales.
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Here, we test whether the loss of species threatened with extinction according to the International Union for Conservation of Nature (IUCN) leads to morphological and phylogenetic homogenization
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across both the whole avian class and within each biome and ecoregion globally. We use a comprehensive set of continuous morphological traits extracted from museum collections of 8,455 bird species, including geometric morphometric beak shape data,
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and sequentially remove species from those at most to least threat of extinction. We find evidence of morphological, but not phylogenetic, homogenization across the avian class, with species becoming more alike in terms of their morphology. We find that most biome and ecoregions are expected to lose morphological diversity at a greater rate than predicted by species loss alone, with the most imperiled regions found in East Asia and the Himalayan uplands and foothills. Only a small proportion of assemblages are threatened with phylogenetic homogenization, in particular parts of Indochina. Species extinctions will lead to a major loss of avian ecological strategies, but not a comparable loss of phylogenetic diversity. As the decline of species with unique traits and their replacement with more widespread generalist species continues, the protection of assemblages at most risk of morphological and phylogenetic homogenization should be a key conservation priority.
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Predicted loss of birds will drive exceptional declines in morphological diversity
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Species extinctions lead to a major loss of ecological strategies and functions
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Most biomes and ecoregions will experience morphological homogenization
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Phylogenetic diversity tends to decline as expected as species go extinct
The global extinction crisis will lead to widespread losses of morphological diversity. Hughes et al. show that predicted species extinctions drive far greater declines of ecological strategies than predicted, with important ramifications for humans as ecosystem services are lost. In contrast, phylogenetic diversity declines as expected.
The systemic benefits of anti-inflammatory pharmacotherapy vary across cardiovascular diseases in clinical practice. We aimed to evaluate the application of artificial intelligence to acute type A ...aortic dissection (ATAAD) patients to determine the optimal target population who would benefit from urinary trypsin inhibitor use (ulinastatin). Patient characteristics at admission in the Chinese multicenter 5A study database (2016–2022) were used to develop an inflammatory risk model to predict multiple organ dysfunction syndrome (MODS). The population (5,126 patients from 15 hospitals) was divided into a 60% sample for model derivation, with the remaining 40% used for model validation. Next, we trained an extreme gradient-boosting algorithm (XGBoost) to develop a parsimonious patient-level inflammatory risk model for predicting MODS. Finally, a top-six-feature tool consisting of estimated glomerular filtration rate, leukocyte count, platelet count, De Ritis ratio, hemoglobin, and albumin was built and showed adequate predictive performance regarding its discrimination, calibration, and clinical utility in derivation and validation cohorts. By individual risk probability and treatment effect, our analysis identified individuals with differential benefit from ulinastatin use (risk ratio RR for MODS of RR 0.802 95% confidence interval (CI) 0.656, 0.981 for the predicted risk of 23.5%–41.6%; RR 1.196 0.698–2.049 for the predicted risk of <23.5%; RR 0.922 95% CI 0.816–1.042 for the predicted risk of >41.6%). By using artificial intelligence to define an individual’s benefit based on the risk probability and treatment effect prediction, we found that individual differences in risk probability likely have important effects on ulinastatin treatment and outcome, which highlights the need for individualizing the selection of optimal anti-inflammatory treatment goals for ATAAD patients.
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•An inflammatory risk model is developed to predict multiple organ dysfunction syndrome (MODS) after acute type A aortic dissection (ATAAD) surgery•The differences in inflammatory risk probabilities likely modify the association between ulinastatin use and MODS after ATAAD surgery•Inflammatory risk stratification can help individualize anti-inflammatory pharmacotherapy, highlighting the need for precision theranostics in ATAAD surgery
Self-sensing adaptability is a high-level intelligence in living creatures and is highly desired for their biomimetic soft robots for efficient interaction with the surroundings. Self-sensing ...adaptability can be achieved in soft robots by the integration of sensors and actuators. However, current strategies simply assemble discrete sensors and actuators into one robotic system and, thus, dilute their synergistic and complementary connections, causing low-level adaptability and poor decision-making capability. Here, inspired by vertebrate animals supported by highly evolved backbones, we propose a concept of a bionic spine that integrates sensing and actuation into one shared body based on the reversible piezoelectric effect and a decoupling mechanism to extract the environmental feedback. We demonstrate that the soft robots equipped with the bionic spines feature locomotion speed improvements between 39.5% and 80% for various environmental terrains. More importantly, it can also enable the robots to accurately recognize and actively adapt to changing environments with obstacle avoidance capability by learning-based gait adjustments. We envision that the proposed bionic spine could serve as a building block for locomotive soft robots toward more intelligent machine-environment interactions in the future.
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•Intelligent spinal robots coupling sensing, recognition, and active adaption.•A bionic spine with integrated sensing and actuation in one shared device.•A design concept highly scalable for various robots for active environmental adaption and obstacle avoidance purposes.
The penetration kinetics of small-molecule compounds like nutrients, drugs, and cryoprotective agents into artificial cell aggregates are of pivotal relevance in many applications, from stem cell ...differentiation and drug screening through to cryopreservation. Depending on compound and tissue properties as well as aggregate size and shape, the penetration behavior can differ vastly. Here, we introduce bioorthogonal Raman microspectroscopy as a contactless technique to investigate the penetration of various compounds into spheroids, organoids, and other tissue models in terms of diffusion coefficients and perfusion times. We showcase the potential of the method by applying it to the radial perfusion of neural stem cell spheroids with the prevalent cryopreservation additive dimethyl sulfoxide. Employing a diffusion model for spherical bodies, the spectroscopic data were quantitatively analyzed. Perfusion times were obtained for spheroids in the sub-mm region, and interesting findings about the spheroid-size dependence of the diffusion coefficient are reported.
Pancreatic adenocarcinoma (PDAC) is one of the most deadly cancers, characterized by extremely limited therapeutic options and a poor prognosis, as it is often diagnosed during late disease stages. ...Innovative and selective treatments are urgently needed, since current therapies have limited efficacy and significant side effects. Through proteomics analysis of extracellular vesicles, we discovered an imbalanced distribution of amino acids secreted by PDAC tumor cells. Our findings revealed that PDAC cells preferentially excrete proteins with certain preferential amino acids, including isoleucine and histidine, via extracellular vesicles. These amino acids are associated with disease progression and can be targeted to elicit selective toxicity to PDAC tumor cells. Both in vitro and in vivo experiments demonstrated that supplementation with these specific amino acids effectively eradicated PDAC cells. Mechanistically, we also identified XRN1 as a potential target for these amino acids. The high selectivity of this treatment method allows for specific targeting of tumor metabolism with very low toxicity to normal tissues. Furthermore, we found this treatment approach is easy-to-administer and with sustained tumor-killing effects. Together, our findings reveal that exocytosed amino acids may serve as therapeutic targets for designing treatments of intractable PDAC and potentially offer alternative treatments for other types of cancers.
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•Tumor cells exocytose amino acids via extracellular vesicles, which act as stressors to tumor cells.•Novel non-starvation approach using amino acids for treating pancreatic cancer.•Amino acid treatment is selective and effective against PDAC cells with no side effects.•The new treatment can be used as an adjuvant with chemotherapy to enhance efficacy.
Penalty kicks are increasingly decisive in major international football competitions. Yet, over 30% of shootout kicks are missed. The outcome of the kick often relies on the ability of the penalty ...taker to exploit anticipatory movements of the goalkeeper to redirect the kick toward the open side of the goal. Unfortunately, this ability is difficult to train using classical methods. We used an augmented reality simulator displaying an holographic goalkeeper to test and train penalty kick performance with 13 young elite players. Machine learning algorithms were used to optimize the learning rate by maintaining an optimal level of training difficulty. Ten training sessions of 20 kicks reduced the redirection threshold by 120 ms, which constituted a 28% reduction with respect to the baseline threshold. Importantly, redirection threshold reduction was observed for all trained players, and all things being equal, it corresponded to an estimated 35% improvement of the success rate.
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•In major football competitions, over 20% of knockout games are decided by penalty shootouts.•Thirty percent of the kicks are missed, notably because players lack specific and adapted training methods.•We developed an augmented reality simulator with a holographic goalkeeper to train sensorimotor kicking skills.•Ten sessions of machine learning-optimized training improved the sensorimotor skills of players by 28%.•This translates into a 35% increase of the success rate, thereby constituting a powerful training tool.
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