Dramatic increase in the use of nanoparticles (NPs) in a variety of applications greatly increased the likelihood of the release of NPs into the environment. Zinc oxide nanoparticles (ZnO NPs) are among the most commonly used NPs, and it has been shown that ZnO NPs were harmful to several different plants. We report here the effects of ZnO NPs exposure on biomass accumulation and photosynthesis in Arabidopsis. We found that 200 and 300 mg/L ZnO NPs treatments reduced Arabidopsis growth by ∼20 and 80%, respectively, in comparison to the control. Pigments measurement showed that Chlorophyll a and b contents were reduced more than 50%, whereas carotenoid contents remain largely unaffected in 300 mg/L ZnO NPs treated Arabidopsis plants. Consistent with this, net rate of photosynthesis, leaf stomatal conductance, intercellular CO2 concentration and transpiration rate were all reduced more than 50% in 300 mg/L ZnO NPs treated plants. Quantitative RT-PCR results showed that expression levels of chlorophyll synthesis genes including CHLOROPHYLL A OXYGENASE (CAO), CHLOROPHYLL SYNTHASE (CHLG), COPPER RESPONSE DEFECT 1 (CRD1), MAGNESIUM-PROTOPORPHYRIN IX METHYLTRANSFERASE (CHLM) and MG-CHELATASE SUBUNIT D (CHLD), and photosystem structure gene PHOTOSYSTEM I SUBUNIT D-2 (PSAD2), PHOTOSYSTEM I SUBUNIT E-2 (PSAE2), PHOTOSYSTEM I SUBUNIT K (PSAK) and PHOTOSYSTEM I SUBUNIT K (PSAN) were reduced about five folds in 300 mg/L ZnO NPs treated plants. On the other hand, elevated expression, though to different degrees, of several carotenoids synthesis genes including GERANYLGERANYL PYROPHOSPHATE SYNTHASE 6 (GGPS6), PHYTOENE SYNTHASE (PSY) PHYTOENE DESATURASE (PDS), and ZETA-CAROTENE DESATURASE (ZDS) were observed in ZnO NPs treated plants. Taken together, these results suggest that toxicity effects of ZnO NPs observed in Arabidopsis was likely due to the inhibition of the expression of chlorophyll synthesis genes and photosystem structure genes, which results in the inhibition of chlorophylls biosynthesis, leading to the reduce in photosynthesis efficiency in the plants.

Aux/IAA proteins are transcriptional repressors that control auxin signaling by interacting with auxin response factors (ARFs). So far all of the identified Aux/IAA mutants with auxin-related phenotypes in Arabidopsis and rice (Oryza sativa) are dominant gain-of-function mutants, with mutations in Domain II that affected stability of the corresponding Aux/IAA proteins. On the other hand, morphological changes were observed in knock-down mutants of Aux/IAA genes in tomato (Solanum lycopersicum), suggesting that functions of Aux/IAA proteins may be specific for certain plant species. We report here the characterization of PtrIAA14.1, a poplar (Populus trichocarpa) homolog of IAA7. Bioinformatics analysis showed that PtrIAA14.1 is a classic Aux/IAA protein. It contains four conserved domains with the repressor motif in Domain I, the degron in Domain II, and the conserved amino acid signatures for protein–protein interactions in Domain III and Domain IV. Protoplast transfection assays showed that PtrIAA14.1 is localized in nucleus. It is unable in the presence of auxin, and it represses auxin response reporter gene expression. Expression of wild-type PtrIAA14.1 in Arabidopsis resulted in auxin-related phenotypes including down-curling leaves, semi-draft with increased number of branches, and greatly reduced fertility, but expression of the Arabidopsis Aux/IAA genes tested remain largely unchanged in the transgenic plants. Protein–protein interaction assays in yeast and protoplasts showed that PtrIAA14.1 interacted with ARF5, but not other ARFs. Consistent with this observation, vascular patterning was altered in the transgenic plants, and the expression of AtHB8 (Arabidopsis thaliana homeobox gene 8) was reduced in transgenic plants.

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We propose the first multi-frame video object detection framework trained to detect great apes. It is applicable to challenging camera trap footage in complex jungle environments and extends a traditional feature pyramid architecture by adding self-attention driven feature blending in both the spatial as well as the temporal domain. We demonstrate that this extension can detect distinctive species appearance and motion signatures despite significant partial occlusion. We evaluate the framework using 500 camera trap videos of great apes from the Pan African Programme containing 180K frames, which we manually annotated with accurate per-frame animal bounding boxes. These clips contain significant partial occlusions, challenging lighting, dynamic backgrounds, and natural camouflage effects. We show that our approach performs highly robustly and significantly outperforms frame-based detectors. We also perform detailed ablation studies and a validation on the full ILSVRC 2015 VID data corpus to demonstrate wider applicability at adequate performance levels. We conclude that the framework is ready to assist human camera trap inspection efforts. We publish key parts of the code as well as network weights and ground truth annotations with this paper.

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