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Cannabis sativa can be classified in two main types, according to psychotropic cannabinoid ∆9-tetrahydrocannabinol (∆9-THC) content: the drug-type and the fiber-type. According to the European Monitoring Center for Drugs and Drug Addiction, most of the European Union countries consider the possession of cannabis, for personal use, a minor offense with possibility of incarceration. Despite of the model of legal supply (i.e., Spanish cannabis clubs, Netherlands coffee shops) or medical use (i.e., Italy), cannabis remains the most used and trafficked illicit plant in the European Union. Differentiating cannabis crops or tracing the biogeographical origin is crucial for law enforcement purposes. Chloroplast DNA (cpDNA) markers may assist to determine biogeographic origin and to differentiate hemp from marijuana. This research aims: to identify and to evaluate nine C. sativa cpDNA polymorphic SNP sites to differentiate crop type and to provide information about its biogeographical origin. Five SNaPshot™ assays for nine chloroplast markers were developed and conducted in marijuana samples seized in Chile, the USA-Mexico border and Spain, and hemp samples grown in Spain and in Italy. The SNapShot™ assays were tested on 122 cannabis samples, which included 16 blind samples, and were able to differentiate marijuana crop type from hemp crop type in all samples. Using phylogenetic analysis, genetic differences were observed between marijuana and hemp samples. Moreover, principal component analysis (PCA) supported the relationship among hemp samples, as well as for USA-Mexico border, Spanish, and Chilean marijuana samples. Genetic differences between groups based on the biogeographical origin and their crop type were observed. Increasing the number of genetic markers, including the most recently studied ones, and expanding the sample database will provide more accurate information about crop differentiation and biogeographical origin.

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Mitragyna speciosa, commonly known as kratom, is a narcotic plant that is used for its unique mood-enhancing and pain-relieving effects. It is marketed throughout the United States as a 'legal high' and has gained popularity as an alternative to opioids. However, kratom's increasing involvement in accidental overdoses, especially among polydrug users, has prompted warnings from the Drug Enforcement Agency (DEA) and the Food and Drug Administration (FDA). Despite these warnings, kratom remains legal federally, although it is banned in six states. This legal disparity complicates monitoring and enforcement efforts in states where kratom is illegal. Common forensic techniques using morphology or chemical analysis are beneficial in some instances but are not useful in source attribution because most seized kratom is powdered and the alkaloid content of samples can vary within products, making sourcing unreliable. This study focused on developing a DNA barcoding method to access sequence variation in commercial kratom products. It evaluated the utility of one nuclear barcode region (ITS) and three chloroplast barcode regions (matK, rbcL, and trnH-psbA) in assessing sequence variation across commercially available kratom products. Novel polymorphisms were discovered, and the ITS region showed the greatest variation between samples. Among the 15 kratom products tested, only two haplotypes were identified across the four barcoding regions. The findings highlight the potential of DNA barcoding as a forensic tool in the traceability and enforcement against illegal kratom distribution. Nonetheless, the limited haplotypic diversity points to a need for further development and expansion of the M. speciosa DNA sequence database.

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Research on plant-nanomaterial interactions has greatly advanced over the past decade. One particularly fascinating discovery encompasses the immunomodulatory effects in plants. Due to the low doses needed and the comparatively low toxicity of many nanomaterials, nanoenabled immunomodulation is environmentally and economically promising for agriculture. It may reduce environmental costs associated with excessive use of chemical pesticides and fertilizers, which can lead to soil and water pollution. Furthermore, nanoenabled strategies can enhance plant resilience against various biotic and abiotic stresses, contributing to the sustainability of agricultural ecosystems and the reduction of crop losses due to environmental factors. While nanoparticle immunomodulatory effects are relatively well-known in animals, they are still to be understood in plants. Here, we provide our perspective on the general components of the plant's immune system, including the signaling pathways, networks, and molecules of relevance for plant nanomodulation. We discuss the recent scientific progress in nanoenabled immunomodulation and nanopriming and lay out key avenues to use plant immunomodulation for agriculture. Reactive oxygen species (ROS), the mitogen-activated protein kinase (MAPK) cascade, and the calcium-dependent protein kinase (CDPK or CPK) pathway are of particular interest due to their interconnected function and significance in the response to biotic and abiotic stress. Additionally, we underscore that understanding the plant hormone salicylic acid is vital for nanoenabled applications to induce systemic acquired resistance. It is suggested that a multidisciplinary approach, incorporating environmental impact assessments and focusing on scalability, can expedite the realization of enhanced crop yields through nanotechnology while fostering a healthier environment.

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Background: Plants have been pivotal in traditional and modern medicine globally, with historical evidence supporting their therapeutic applications. Nigella (Nigella sativa L.) is an annual herbaceous plant of the Ranunculaceae family and is cultivated in the Middle East, Eastern Europe, and Western and Central Asia. The medicinal use of plants dates back thousands of years, documented in ancient writings from various civilizations. Alkaloids, phenolics, saponins, flavonoids, terpenoids, anthraquinones, and tannins found in plants exhibit antioxidant, immunomodulatory, anti-inflammatory, anticancer, antibacterial, and antidiabetic activities. Methodology: This study specifically examines the pharmacological potential of Nigella sativa L., emphasizing thymoquinone-a compound with diverse nutraceutical benefits. The extraction, characterization, and quantification of thymoquinone, alongside other physicochemical parameters, were carried out using ethanol through Soxhlet extraction procedures on five nigella varieties. HPLC analysis was performed to determine the maximum accumulation of thymoquinone in the released variety of the plant and the chemical composition of the seed oil isolated from Nigella sativa L., varieties utilized in the study was determined through GC-MS analysis. Results: The research revealed that the Ajmer nigella-20 variety stands out, exhibiting elevated levels of thymoquinone (0.20 ± 0.07%), antioxidants (76.18 ± 1.78%), and substantial quantities of total phenols (31.85 ± 0.97 mg GAEg-1 seed) and flavonoids (8.150 ± 0.360 mg QE 100 g-1 seed) compared to other varieties. The GC-MS profiling showed the presence of 11 major compounds in the studied varieties, with p-cymene, longifolene, and myristic acid identified as the major chemical compounds present in the oil. Conclusion: The observed variations among Nigella varieties indicate the Ajmer nigella-20 variety as particularly promising for thymoquinone and bioactive compound extraction. This study underscores Nigella's potential as a source of pharmacologically active compounds, highlighting the need for further exploration in therapeutic applications.

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The idea that plants would be efficient, frugal or optimised echoes the recurrent semantics of 'blueprint' and 'program' in molecular genetics. However, when analysing plants with quantitative approaches and systems thinking, we instead find that plants are the results of stochastic processes with many inefficiencies, incoherence or delays fuelling their robustness. If one had to highlight the main value of quantitative biology, this could be it: plants are robust systems because they are not efficient. Such systemic insights extend to the way we conduct plant research and opens plant science publication to a much broader framework.

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The Single-cell Assay for Transposase-Accessible Chromatin with high throughput sequencing (scATAC-seq) has gained increasing popularity in recent years, allowing for chromatin accessibility to be deciphered and gene regulatory networks (GRNs) to be inferred at single-cell resolution. This cutting-edge technology now enables the genome-wide profiling of chromatin accessibility at the cellular level and the capturing of cell-type-specific cis-regulatory elements (CREs) that are masked by cellular heterogeneity in bulk assays. Additionally, it can also facilitate the identification of rare and new cell types based on differences in chromatin accessibility and the charting of cellular developmental trajectories within lineage-related cell clusters. Due to technical challenges and limitations, the data generated from scATAC-seq exhibit unique features, often characterized by high sparsity and noise, even within the same cell type. To address these challenges, various bioinformatic tools have been developed. Furthermore, the application of scATAC-seq in plant science is still in its infancy, with most research focusing on root tissues and model plant species. In this review, we provide an overview of recent progress in scATAC-seq and its application across various fields. We first conduct scATAC-seq in plant science. Next, we highlight the current challenges of scATAC-seq in plant science and major strategies for cell type annotation. Finally, we outline several future directions to exploit scATAC-seq technologies to address critical challenges in plant science, ranging from plant ENCODE(The Encyclopedia of DNA Elements) project construction to GRN inference, to deepen our understanding of the roles of CREs in plant biology.

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Somatic cell reprogramming is a complex feature that allows differentiated cells to undergo fate changes into different cell types. This process, which is conserved between plants and animals, is often achieved via dedifferentiation into pluripotent stem cells, which have the ability to generate all other types of cells and tissues of a given organism. Cellular reprogramming is thus a complex process that requires extensive modification at the epigenetic and transcriptional level, unlocking cellular programs that allow cells to acquire pluripotency. In addition to alterations in the gene expression profile, cellular reprogramming requires rearrangement of the proteome, organelles and metabolism, but these changes are comparatively less studied. In this context, autophagy, a cellular catabolic process that participates in the recycling of intracellular constituents, has the capacity to affect different aspects of cellular reprogramming, including the removal of protein signatures that might hamper reprogramming, mitophagy associated with metabolic reprogramming, and the supply of energy and metabolic building blocks to cells that undergo fate changes. In this Review, we discuss advances in our understanding of the role of autophagy during cellular reprogramming by drawing comparisons between plant and animal studies, as well as highlighting aspects of the topic that warrant further research.

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Artificial intelligence (AI) is advancing rapidly and continually evolving in various fields. Recently, the release of ChatGPT has sparked significant public interest. In this study, we revisit the '100 Important Questions Facing Plant Science' by leveraging ChatGPT as a valuable tool for generating thought-provoking questions relevant to plant science. These questions primarily revolve around the utilization of plants in product development, understanding plant mechanisms, plant-environment interactions, and enhancing plant traits, with an emphasis on sustainable product development. While ChatGPT may not capture certain crucial aspects highlighted by scientists, it offers valuable insights into the questions generated by experts. Our analysis demonstrates that ChatGPT can be cautiously employed as a supportive tool to facilitate, streamline, and expedite specific tasks in plant science.

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Introduction: The challenges associated with data availability, class imbalance, and the need for data augmentation are well-recognized in the field of plant disease detection. The collection of large-scale datasets for plant diseases is particularly demanding due to seasonal and geographical constraints, leading to significant cost and time investments. Traditional data augmentation techniques, such as cropping, resizing, and rotation, have been largely supplanted by more advanced methods. In particular, the utilization of Generative Adversarial Networks (GANs) for the creation of realistic synthetic images has become a focal point of contemporary research, addressing issues related to data scarcity and class imbalance in the training of deep learning models. Recently, the emergence of diffusion models has captivated the scientific community, offering superior and realistic output compared to GANs. Despite these advancements, the application of diffusion models in the domain of plant science remains an unexplored frontier, presenting an opportunity for groundbreaking contributions. Methods: In this study, we delve into the principles of diffusion technology, contrasting its methodology and performance with state-of-the-art GAN solutions, specifically examining the guided inference model of GANs, named InstaGAN, and a diffusion-based model, RePaint. Both models utilize segmentation masks to guide the generation process, albeit with distinct principles. For a fair comparison, a subset of the PlantVillage dataset is used, containing two disease classes of tomato leaves and three disease classes of grape leaf diseases, as results on these classes have been published in other publications. Results: Quantitatively, RePaint demonstrated superior performance over InstaGAN, with average Fréchet Inception Distance (FID) score of 138.28 and Kernel Inception Distance (KID) score of 0.089 ± (0.002), compared to InstaGAN's average FID and KID scores of 206.02 and 0.159 ± (0.004) respectively. Additionally, RePaint's FID scores for grape leaf diseases were 69.05, outperforming other published methods such as DCGAN (309.376), LeafGAN (178.256), and InstaGAN (114.28). For tomato leaf diseases, RePaint achieved an FID score of 161.35, surpassing other methods like WGAN (226.08), SAGAN (229.7233), and InstaGAN (236.61). Discussion: This study offers valuable insights into the potential of diffusion models for data augmentation in plant disease detection, paving the way for future research in this promising field.

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Canada has extensive petroleum hydrocarbon (PHC) contamination in northern areas and the boreal forest region from historical oil and gas activities. Since the 2013 standardization of boreal forest species for plant toxicity testing in Canada, there has been a need to build the primary literature of the toxicity of weathered PHCs to these species. A series of toxicity experiments were carried out using fine-grained (<0.005-0.425 mm) background (100 total mg/kg total PHCs) and weathered contaminated soil (11,900 mg/kg total PHCs) collected from a contaminated site in northern Ontario, Canada. The PHC mixture in the contaminated site soil was characterized through Canadian Council of Ministers of the Environment Fractions, as indicated by the number equivalent normal straight-chain hydrocarbons (nC). The soil was highly contaminated with Fraction 2 (>nC10 to nC16) at 4790 mg/kg and Fraction 3 (>nC16 to nC34) at 4960 mg/kg. Five plant species (Elymus trachycaulus, Achillea millefolium, Picea mariana, Salix bebbiana, and Alnus viridis) were grown from seed in 0%, 25%, 50%, 75%, and 100% relative contamination mixtures of the PHC-contaminated and background soil from the site over 2-6 weeks. All five species showed significant inhibition in shoot length, shoot weight, root length, and/or root weight (Kruskal-Wallis Tests: p < 0.05, df = 4.0). Measurements of 25% inhibitory concentrations (IC25) following PHC toxicity experiments revealed that S. bebbiana was most significantly impaired by the PHC-contaminated soil (410-990 mg/kg total PHCs), where it showed <35% germination. This study indicates that natural weathering of Fraction 2- and Fraction 3-concentrated soil did not eliminate phytotoxicity to boreal plant species. Furthermore, it builds on the limited existing literature for toxicity of PHCs on boreal plants and supports site remediation to existing Canadian provincial PHC guidelines.

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Metabolic scaling theory (MST) provides an understanding of scaling in organismal morphology. Empirical data on the apparently universal pattern of tip-to-base conduit widening across vascular plants motivate a set of generalized MST (gMST) relationships allowing for variable rates of conduit coalescence and taper and a transition between transport and diffusive domains. Our model, with coalescence limited to the distalmost part of the conductive system, reconciles previous MST-based models and extends their applicability to the entire plant. We derive an inverse relationship between stem volume taper and conduit widening, which implies that plant morphology is dictated by vascular optimality and not the assumption of constant sapwood area across all branching levels, contradicting Leonardo's rule. Thus, energy efficiency controls conduit coalescence rate, lowering the carbon cost needed to sustain the vascular network. Our model shows that as a plant grows taller, it must increase conduit widening and coalescence, which may make it more vulnerable to drought. We calculated how our gMST model implies a lower carbon cost to sustain a similar network compared to previous MST-based models. We also show that gMST predicts the cross-sectional area of vessels and their frequency along the relative length better than previous MST models for a range of plant types. We encourage further research obtaining data that would allow testing other gMST predictions that remain unconfirmed empirically, such as conduit coalescence rate in stems. The premise of energy efficiency can potentially become instrumental to our understanding of plant carbon allocation.

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Codon usage bias of coding sequences has been usually used for exploring the evolutionary factors that affect the variation of genes. We took 20 chloroplast genomes of Malus species into account to explore the codon usage patterns, including the composition, relationship between GC3s and effective number of codons, the parity rule two analyses, the relative synonymous codon usage, the codon adaptation index, the frequency of optimal codons, the codon bias index, etc., of their coding genes. The relationship between GC3 and the ENC values showed that when the separate genes are concerned, the distribution of their GC3 contents is relatively concentrated and the distribution of the ENC values are from 35 to 61 or so. The neutrality plot showed that the correlation coefficient between GC12 and GC3 is 0.095, revealing the mutation factor played a weak role in codon pattern formation. Correspondence analysis results revealed that the codon usage patterns in the chloroplast genomes of Malus species are similar. All these results showed that all Malus chloroplast genomes are AT rich ones, the third bases of the codons are affected by the natural selection pressure, the first two nucleotide base of the codon are affected by mutation pressure. Some genes, such as the rsp7, psbA and ycf2 are of lower codon usage divergences, while the rps12, rps16 and ndhD are of higher codon usage divergences. Codon usage bias exists in the Malus genomes could be used for exploring the evolutionary characteristics in chloroplast genomes and for further study on evolutionary phenomenon in other species.

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Successful human space exploration requires more products than can be taken as payload. There is a need, therefore, for in-space circular manufacturing. Requirements for this include limited resource inflow, from either Earth or other planets and the generation of minimal waste. The provision of nutritious food is a clear need for human survival on the Moon or Mars and is one of the most complex to solve. Demand in large quantities, constant and reliable provision of food requires the development of specialist agricultural technologies. Here, we first review the history of space farming over the past five decades. This survey assesses the technologies which have been tested under the harsh conditions of space, identifying which modern horticultural components are applicable for in-space plant growth. We then outline which plants have been grown and under what conditions, and speculate upon the types of plants that could be selected to best nourish astronauts. Current systems are focussed on experimentation and exploration, but do not yet provide turn-key solutions for efficient food production within a long-term space exploration scenario. With that take, this review aims to provide a perspective on how an engineered closed circular environmental life-support system (ECCLES) might be constructed. To exemplify the latter, nutrient auto accumulation by biofortification is proposed through the integration of space farming and space mining, which is uncharted on Earth.

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This study investigated the in vitro simulated gastrointestinal digestion (GID) effects on wild and micropropagated Apennines Genepì infusions. Wild and micropropagated infusions were compared for their antioxidant activity, phenolic contents, and polyphenolic profiles before and after GID. Before digestion, the wild infusions had higher amounts of phenolic compounds and antioxidant activity than the micropropagated ones. Instead, after digestion, the differences in the total phenolic content (TPC) and antioxidant activity between wild and micropropagated infusions were less pronounced. The changes in the TPC and phenolic profiles revealed the presence of several chemical transformations and rearrangements that resulted in compounds with different reactivity and antioxidant potential. Without enzyme actions, the wild infusion digest undergoes higher modifications than those obtained from the micropropagated ones. The current study offers the first concrete proof of the impact of GID on the polyphenolic chemicals present in infusions of wild and micropropagated Apennines Genepì and their antioxidant properties. Our findings are essential for future in-depth analyses of Apennine Genepì infusions and their potential impacts on human health.