Unlocking the potential of synthetic patients for accelerating clinical trials: Results of the first GIMEMA experience on acute myeloid leukemia patients.

Artificial Intelligence has the potential to reshape the landscape of clinical trials through innovative applications, with a notable advancement being the emergence of synthetic patient generation. This process involves simulating cohorts of virtual patients that can either replace or supplement real individuals within trial settings. By leveraging synthetic patients, it becomes possible to eliminate the need for obtaining patient consent and creating control groups that mimic patients in active treatment arms. This method not only streamlines trial processes, reducing time and costs but also fortifies the protection of sensitive participant data. Furthermore, integrating synthetic patients amplifies trial efficiency by expanding the sample size. These straightforward and cost-effective methods also enable the development of personalized subject-specific models, enabling predictions of patient responses to interventions. Synthetic data holds great promise for generating real-world evidence in clinical trials while upholding rigorous confidentiality standards throughout the process. Therefore, this study aims to demonstrate the applicability and performance of these methods in the context of onco-hematological research, breaking through the theoretical and practical barriers associated with the implementation of artificial intelligence in medical trials.

Invertebrate and vertebrate predation rates in a hyperarid ecosystem following an oil spill.

Extreme temperatures and scarce precipitation in deserts have led to abiotic factors often being regarded as more important than biotic ones in shaping desert communities. The presumed low biological activity of deserts is also one reason why deserts are often overlooked by conservation programs. We provide the first quantification of predation intensity from a desert ecosystem using artificial sentinel prey emulating caterpillars, a standardized monitoring tool to quantify relative predation pressure by many invertebrate and vertebrate predators. The study was conducted in a protected natural area affected by oil spills in 1975 and 2014; hence, we assessed the potential effects of oil pollution on predation rates. We found that predation was mostly due to invertebrate rather than vertebrate predators, fluctuated throughout the year, was higher at the ground level than in the tree canopy, and was not negatively affected by the oil spills. The mean predation rate per day (12.9%) was within the range found in other ecosystems, suggesting that biotic interactions in deserts ought not to be neglected and that ecologists should adopt standardized tools to track ecological functions and allow for comparisons among ecosystems.

The Impact of Terrestrial Oil Pollution on Parasitoid Wasps Associated With Vachellia (Fabales: Fabaceae) Trees in a Desert Ecosystem, Israel.

Oil is a major pollutant of the environment, and terrestrial oil spills frequently occur in desert areas. Although arthropods account for a large share of animal diversity, the effect of oil pollution on this group is rarely documented. We evaluated the effects of oil pollution on parasitoid wasps associated with Vachellia (formerly Acacia) tortilis (Forssk.) and Vachellia raddiana (Savi) trees in a hyper-arid desert that was affected by two major oil spills (in 1975 and 2014). We sampled the parasitoid populations between 2016 and 2018 in three sampling sites and compared their abundance, diversity, and community composition between oil-polluted and unpolluted trees. Parasitoid abundance in oil-polluted trees was lower in one of the sites affected by the recent oil spill, but not in the site affected by the 1975 oil spill. Oil-polluted trees supported lower parasitoid diversity than unpolluted trees in some sampling site/year combinations; however, such negative effects were inconsistent and pollution explained a small proportion of the variation in parasitoid community composition. Our results indicate that oil pollution may negatively affect parasitoid abundances and diversity, although the magnitude of the effect depends on the tree species, sampling site, and the time since the oil spill.

Seed Predation on Oil-Polluted and Unpolluted Vachellia (Acacia) Trees in a Hyper-Arid Desert Ecosystem.

Acacia trees are keystone species in many arid environments, supporting high levels of plant and animal diversity. In Israel, the populations of Vachellia (formerly Acacia) tortilis (Forssk.) and V. raddiana (Savi) are declining at an alarming rate. Severe infestations by bruchid beetles (Coleoptera, Chrysomelidae) are among the major causes of seed mortality, but additional environmental stressors can reduce the defence level of the seeds, exacerbating their susceptibility to predators. In a hyper-arid desert ecosystem affected by two major oil spills (in 1975 and 2014), we quantified seed predation rates caused by insect granivores before and after the pods dropped to the ground. We recorded predation rates of up to 84% for both tree species, and higher predation rates at the ground level than in the canopy, suggesting that repeated infestations occur. These results reinforce the call to protect the populations of large ungulates such as gazelles, which kill the bruchids by feeding upon the pods, and promote seed germination and dispersion. We found no clear evidence of a negative effect of the oil spill on seed predation, indicating that oil pollution did not increase the vulnerability of the seeds to granivores even in trees affected by the recent oil spill.

The potential of trap and barrier cropping to decrease densities of the whitefly Bemisia tabaci MED on cotton in China.

BACKGROUND: The whitefly, Bemisia tabaci (Gennadius) MED, is a destructive insect pest in many countries of the world. Although the use of insecticides for controlling B. tabaci has been effective to a certain extent, pesticides are not an acceptable long-term control method, and alternatives should be sought. This paper focuses on the possibility of controlling B. tabaci on cotton using trap and barrier crops. We performed field experiments using cantaloupe (Cucumis melo) and sunflower (Helianthus annuus) as trap crops, and maize (Zea mays) as a barrier crop in various configurations in Hebei Province, North China. RESULTS: The main activity periods were shortest on cantaloupe and ranged between 16-32 days for immatures and 14-33 days for adults. Adult whitefly densities were not significantly reduced by any treatment. During the main activity period, maize intercropping reduced densities of immature whiteflies from 24.2 individuals (ind.) 100 cm-2 to 4.0 ind.100 cm-2 , but all treatments were successful in significantly reducing immature B. tabaci densities. This resulted in a significant yield premium. CONCLUSIONS: Intercropping reduced B. tabaci densities on cotton more than perimeter planting. Maize was more effective to reduce densities of immature whiteflies on cotton than cantaloupe. The results will contribute to the development of more effective and practical approaches for protecting cotton from B. tabaci and lowering chemical pressure on this crop. © 2019 Society of Chemical Industry.

Concise Whole-Cell Modeling of BKCa-CaV Activity Controlled by Local Coupling and Stoichiometry.

Large-conductance Ca2+-dependent K+ (BKCa) channels are important regulators of electrical activity. These channels colocalize and form ion channel complexes with voltage-dependent Ca2+ (CaV) channels. Recent stochastic simulations of the BKCa-CaV complex with 1:1 stoichiometry have given important insight into the local control of BKCa channels by fluctuating nanodomains of Ca2+. However, such Monte Carlo simulations are computationally expensive, and are therefore not suitable for large-scale simulations of cellular electrical activity. In this work we extend the stochastic model to more realistic BKCa-CaV complexes with 1:n stoichiometry, and analyze the single-complex model with Markov chain theory. From the description of a single BKCa-CaV complex, using arguments based on timescale analysis, we derive a concise model of whole-cell BKCa currents, which can readily be analyzed and inserted into models of cellular electrical activity. We illustrate the usefulness of our results by inserting our BKCa description into previously published whole-cell models, and perform simulations of electrical activity in various cell types, which show that BKCa-CaV stoichiometry can affect whole-cell behavior substantially. Our work provides a simple formulation for the whole-cell BKCa current that respects local interactions in BKCa-CaV complexes, and indicates how local-global coupling of ion channels may affect cell behavior.