AI-powered revolution in plant sciences: advancements, applications, and challenges for sustainable agriculture and food security

Published: Aug. 6, 2024

Artificial intelligence (AI) is revolutionizing plant sciences by enabling precise species identification, early disease diagnosis, crop yield prediction, and precision agriculture optimization. AI uses machine learning image recognition to aid ecological research biodiversity conservation. It plays a crucial role in breeding accelerating the development of resilient, high-yielding crops with desirable traits. models using climate soil data contribute sustainable food security. In phenotyping, automates measurement analysis characteristics, enhancing our understanding growth. Ongoing aims improve models’ robustness interpretability while addressing privacy algorithmic biases. Interdisciplinary collaboration essential fully harness AI’s potential for sustainable, food-secure future.

Language: Английский

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Transformative Impact of Nanocarrier‐Mediated Drug Delivery: Overcoming Biological Barriers and Expanding Therapeutic Horizons

Small Science, Journal Year: 2024, Volume and Issue: 4(11)

Published: Sept. 17, 2024

Advancing therapeutic progress is centered on developing drug delivery systems (DDS) that control molecule release, ensuring precise targeting and optimal concentrations. Targeted DDS enhances treatment efficacy minimizes off-target effects, but struggles with degradation. Over the last three decades, nanopharmaceuticals have evolved from laboratory concepts into clinical products, highlighting profound impact of nanotechnology in medicine. Despite advancements, effective therapeutics remains challenging because biological barriers. Nanocarriers offer a solution small size, high surface-to-volume ratios, customizable properties. These address physiological challenges, such as shear stress, protein adsorption, quick clearance. They allow targeted to specific tissues, improve outcomes, reduce adverse effects. exhibit controlled decreased degradation, enhanced efficacy. Their size facilitates cell membrane penetration intracellular delivery. Surface modifications increase affinity for types, allowing This study also elucidates potential integration artificial intelligence nanoscience innovate future nanocarrier systems.

Language: Английский

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Mushroom-Derived Innovations: Sustainable Biomaterials for Biomedical Engineering

Deleted Journal, Journal Year: 2024, Volume and Issue: unknown

Published: Aug. 23, 2024

This study investigates the transformative potential of mushroom-derived biomaterials within biomedical engineering, presenting them as sustainable and eco-friendly alternatives to conventional materials. By examining distinct characteristics chemical compositions various mushroom species, we highlight their suitability for creating innovative biomaterials. The paper focuses on key components, such polysaccharides, fungal mycelium, chitin/chitosan, demonstrating applications in tissue antimicrobial treatments, drug delivery systems. biodegradability cultivation mushrooms underscore environmental advantages, aligning with global sustainability goals. Through detailed case studies, illustrate successful these medical devices, construction, packaging, showcasing versatility effectiveness. also addresses current challenges proposes future research directions, emphasizing need interdisciplinary collaboration ensure safety, biocompatibility, ethical use mushroom-based Our provides a comprehensive roadmap harnessing materials, paving way significant advancements devices contributing more future. We have demonstrated that are promising frontier material science, revolutionize field contribute environment.

Language: Английский

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In Silico Simulation of Daphnia magna Immobilization Exposed to Mixtures of TiO2 Nanoparticles with Inorganic Compounds

Journal of Composites Science, Journal Year: 2025, Volume and Issue: 9(1), P. 16 - 16

Published: Jan. 2, 2025

The development of models the physicochemical and biochemical behavior nanomaterials is useful for improving evaluation management this material. Quasi-SMILES technology makes it possible to quite successfully cope with kind modeling task, accounting various experimental conditions, where use other approaches difficult or even impossible. Here, we describe results using quasi-SMILES model toxicity mixtures titanium nano oxide inorganic substances towards Daphnia magna. approach based on stochastic process optimization correlation weights different codes used in quasi-SMILES. was carried out special statistical criteria predictive potential. It shown that built have best

Language: Английский

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Ensemble Machine Learning-Based Approach to Predict Cervical Cancer with Hyperparameter Tuning and Model Explainability

Deleted Journal, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 10, 2025

Cervical cancer remains the top killer of women at a young age in world, 85% cases are detected low-income countries. Preventive measures and therapeutic response enhanced if potential hazards identified early. This research belongs to this field by introducing an end-to-end prediction model based on individual medical records early screening data thus emphasizing discovery meaningful predictors. In order overcome issues with feature selection class imbalances, our study creates ensemble framework that blends Random Forest Logistic Regression techniques. addition achieving astounding accuracy 99.75%, guarantees transparency its decision-making processes utilizing sophisticated machine learning algorithms conjunction interpretability tools like SHAP LIME, which is essential for applications healthcare. The creation extensive method combines several classifiers, advanced techniques locating important predictive factors, help healthcare professionals better understand complex predictions some research's main investments. By offering accurate comprehensible risk assessments, novel has revolutionize clinical enhance cervical cavity identification. promotes development more proactive individualized methods fusing cutting-edge computational technology diagnostics, improving health outcomes everywhere.

Language: Английский

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Nanotechnology in Plant Nanobionics: Mechanisms, Applications, and Future Perspectives

Advanced Biology, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 12, 2025

Abstract Plants are vital to ecosystems and human survival, possessing intricate internal inter‐plant signaling networks that allow them adapt quickly changing environments maintain ecological balance. The integration of engineered nanomaterials (ENMs) with plant systems has led the emergence nanobionics, a field holds potential enhance capabilities significantly. This may result in improved photosynthesis, increased nutrient uptake, accelerated growth development. treated ENMs can be stress mitigators, pollutant detectors, environmental sensors, even light emitters. review explores recent advancements focusing on nanoparticle (NP) synthesis, adhesion, transport, fate, application enhancing physiological functioning, mitigation, health monitoring, energy production, sensing, overall productivity. Potential research directions challenges nanobionics highlighted, how material optimization innovation propelling smart agriculture, pollution remediation, energy/biomass production discussed.

Language: Английский

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Descriptors Divide‐and‐Conquer Enables Multifaceted and Interpretable Materials Structure–Activity Relationship Analysis

Advanced Functional Materials, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 11, 2025

Abstract Machine learning (ML) is increasingly adopted to explore the dependence of properties on descriptors especially for materials with complicated structure–activity relationships. However, most current ML modeling strategies typically depend a single combination descriptors, which leads inaccurate and unilateral inferences. Here, divide‐and‐conquer method proposed machine (descriptors‐DCML) in rough set theory (RST) integrated domain knowledge select multiple optimal sets combinations thus diverse rule extraction are provided dig out mechanisms latent data. Its potential utility applications using sodium ion energy barrier prediction NASICION‐type solid‐state electrolyte compounds multifaceted influencing factors as an example demonstrated. A total 85 samples 45 derived from 72 published literature serve data foundation modeling. Not only does descriptors‐DCML exhibit accuracy 93.8% but also extract 9 relations mapping essential Na 5 ones conform existing understanding rest waiting validation. This work paves way reducing complexity analyzing relationships enhancing interpretability models.

Language: Английский

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The safe and sustainable by design framework applied to graphene-based materials

Environment International, Journal Year: 2025, Volume and Issue: 197, P. 109345 - 109345

Published: Feb. 28, 2025

Language: Английский

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Towards Smart Agriculture through Nano-Fertilizer-A Review

Materials Today Sustainability, Journal Year: 2025, Volume and Issue: unknown, P. 101100 - 101100

Published: March 1, 2025

Language: Английский

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Bioinspired Soft Machines: Engineering Nature’s Grace into Future Innovations

Journal of Functional Biomaterials, Journal Year: 2025, Volume and Issue: 16(5), P. 158 - 158

Published: April 28, 2025

This article explores the transformative advances in soft machines, where biology, materials science, and engineering have converged. We discuss remarkable adaptability versatility of whose designs draw inspiration from nature’s elegant solutions. From intricate movements octopus tentacles to resilience an elephant’s trunk, nature provides a wealth for designing robots capable navigating complex environments with grace efficiency. Central this advancement is ongoing research into bioinspired materials, which serve as building blocks creating machines lifelike behaviors adaptive capabilities. By fostering collaboration innovation, we can unlock new possibilities shaping future seamlessly integrate interact natural world, offering solutions humanity’s most pressing challenges.

Language: Английский

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