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.
Epidemiology studies and clinical trials have suggested that the use of non-steroidal anti-inflammatory drugs (NSAIDs), including aspirin, can significantly reduce the incidence of and mortality ...associated with many cancers 1–3, and upregulation of the COX2-PGE2 pathway in tumor microenvironments might drive several aspects of cancer progression 4–6. For these reasons, the mechanisms linking COX blockade and cancer prevention have long been an area of active investigation 7. During carcinogenesis, COX-2 is expressed both by malignant epithelial cells 8, 9 and by tumor-associated stromal cells, including macrophages 10–12, but the observation that NSAIDs are most effective in cancer prevention in APCmin/+ mice if the mice are treated from conception 13 suggests that the COX-2/PGE2 pathway might also be critical at the earliest stages of tumor development. In this study we take advantage of the translucency and genetic tractability of zebrafish larvae to investigate the involvement of inflammatory cells at cancer initiation, when transformed cells first arise in tissues. We previously showed that innate immune cells supply early transformed cells with proliferative cues 14 and, by using complementary pharmacological and genetic experiments, we now show that prostaglandin E2 (PGE2) is the trophic signal required for this expansion of transformed cells. Our in vivo observations at these early stages of cancer initiation provide a potential mechanistic explanation for why long-term use of low doses of NSAIDs, including aspirin, might reduce cancer onset.
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►COX-2 inhibition halts early growth of Ras-transformed cells in zebrafish larvae ► Both neutrophils and macrophages contribute to trophic support of transformed cells ► dmPGE2 treatment rescues growth of transformed cells after leukocyte depletion ► Inflammation-derived PGE2 could be a target for cancer prevention by NSAIDs/aspirin
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
Abstract Autosomal recessive spastic ataxia of Charlevoix–Saguenay is a rare neurodegenerative disease caused by biallelic variants in the SACS gene encoding for sacsin. More than 200 pathogenic ...variants have been identified to date, most of which are missense. It is likely that the prevalence of autosomal recessive spastic ataxia of Charlevoix–Saguenay is underestimated due to the lack of an efficient diagnostic tool able to validate variants of uncertain significance. We have previously shown that sacsin is almost absent in fibroblasts of patients with autosomal recessive spastic ataxia of Charlevoix–Saguenay regardless of the type of SACS variant, because sacsin carrying missense variants is cotranslationally degraded. In this work, we aimed to establish the pathogenicity of SACS variants by quantifying sacsin protein in blood samples, with relevant implications for autosomal recessive spastic ataxia of Charlevoix–Saguenay diagnosis. We developed a protocol to assess sacsin protein levels by western blot using small amounts of peripheral blood mononuclear cells, which can be propagated in culture and cryopreserved. The study involves eight patients with autosomal recessive spastic ataxia of Charlevoix–Saguenay (including a novel case) carrying variants of different types and positions along the SACS gene and two parents who are carriers of heterozygous missense variants. We show that patients with autosomal recessive spastic ataxia of Charlevoix–Saguenay (carrying either missense or truncating variants) almost completely lacked sacsin in peripheral blood mononuclear cells. Moreover, both carriers of a SACS missense variant showed 50% reduction in sacsin protein levels compared to controls. We also describe a patient with uniparental isodisomy carrying a homozygous nonsense variant near the 3′ end of the SACS gene. This resulted in a stable sacsin protein lacking the last 202 amino acids, probably due to escape of nonsense-mediated decay of mRNA. In conclusion, we have optimized a minimally invasive diagnostic tool for autosomal recessive spastic ataxia of Charlevoix–Saguenay in blood samples based on sacsin protein level assessment. Indeed, our results provide definite evidence that sacsin carrying missense pathogenic variants undergoes cotranslational degradation. The quantitative reduction in sacsin levels in the case of missense variants of uncertain significance allows defining them as pathogenic variants, something which cannot be predicted bioinformatically with high certainty.
X-ray detection is crucial across various sectors, but traditional techniques face challenges such as inefficient data transmission, redundant sensing, high power consumption, and complexity. The ...innovative idea of a retinomorphic X-ray detector shows great potential. However, its implementation has been hindered by the absence of active layers capable of both detecting X-rays and serving as memory storage. In response to this critical gap, our study integrates hybrid perovskite with hydrion-conductive organic cations to develop a groundbreaking retinomorphic X-ray detector. This novel device stands at the nexus of technological innovation, utilizing X-ray detection, memory, and preprocessing capabilities within a single hardware platform. The core mechanism underlying this innovation lies in the transport of electrons and holes within the metal halide octahedral frameworks, enabling precise X-ray detection. Concurrently, the hydrion movement through organic cations endows the device with short-term resistive memory, facilitating rapid data processing and retrieval. Notably, our retinomorphic X-ray detector boasts an array of formidable features, including reconfigurable short-term memory, a linear response curve, and an extended retention time. In practical terms, this translates into the efficient capture of motion projections with minimal redundant data, achieving a compression ratio of 18.06% and an impressive recognition accuracy of up to 98.6%. In essence, our prototype represents a paradigm shift in X-ray detection technology. With its transformative capabilities, this retinomorphic hardware is poised to revolutionize the existing X-ray detection landscape.
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•Conceptual advance: groundbreaking retinomorphic X-ray detector architecture, in stark contrast to the conventional X-ray detection system with separate detector, memory, and processing modules.•A remarkable compression ratio of 18.06%, an outstanding recognition accuracy of 98.6%, and a retention time of up to 205 s.•Opening up new avenues for exploring additional memristor mechanisms and materials within the realm of organic-inorganic hybrid systems.
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.