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Summary Flavonoid accumulation in most fruits is enhanced by ethylene and jasmonate. However, little is known about the hormone functions related to red pear fruit coloration or their combined effects and potential underlying mechanisms. Various treatments were used to investigate the flavonoid metabolite profile and pear transcriptome to verify the effects of ethylene and jasmonate on flavonoid biosynthesis in red pear fruits as well as the mechanism behind this. Ethylene inhibits anthocyanin biosynthesis in red Chinese pear fruits, whereas jasmonate increases anthocyanin and flavone/isoflavone biosyntheses. The branching of the jasmonate‐induced flavonoid biosynthesis pathway is determined by ethylene. Co‐expression network and Mfuzz analyses revealed 4,368 candidate transcripts. Additionally, ethylene suppresses PpMYB10 and PpMYB114 expression via TF repressors, ultimately decreasing anthocyanin biosynthesis. Jasmonate induces anthocyanin accumulation through transcriptional or post‐translational regulation of TFs‐like MYB and bHLH in the absence of ethylene. However, jasmonate induces ethylene biosynthesis and the associated signalling pathway in pear, thereby decreasing anthocyanin production, increasing the availability of the precursors for flavone/isoflavone biosynthesis and enhancing deep yellow fruit coloration. We herein present new phenotypes and fruit coloration regulatory patterns controlled by jasmonate and ethylene, and confirm that the regulation of fruit coloration is complex.

Plant leaf disease control is crucial given the prevalence of plant leaf diseases around the world. The most crucial aspect of controlling plant leaf diseases is appropriately identifying them. Deep learning-based plant leaf disease recognition is a viable alternative to artificial methods that are useless and inaccurate. The proposed work aims to combine plant leaf disease datasets from various countries, review current research and progress in deep learning algorithms for plant disease recognition, and explain how different types of data are developed and used in this area using different deep learning networks. The feasibility of several network models for deep learning-based plant leaf disease detection is discussed. Solving shortcomings such as sunlight irradiation in plant planting conditions, similar disease incidence of different plant leaf diseases, and varied symptoms of the same disease in different damage periods or infection degrees are all essential study topics in the growth of this discipline. To address the concerns raised above and establish the field’s future development potential, we must research high-performance neural networks based on the benefits and downsides of diverse networks. The proposed work can serve as a foundation for future research and breakthroughs in the identification of plant leaf diseases.

Image recording is now ubiquitous in the fields of endangered-animal conservation and GIS. However, endangered animals are rarely seen, and, thus, only a few samples of images of them are available. In particular, the study of endangered-animal detection has a vital spatial component. We propose an adaptive, few-shot learning approach to endangered-animal detection through data augmentation by applying constraints on the mixture of foreground and background images based on species distributions. First, the pre-trained, salient network U2-Net segments the foregrounds and backgrounds of images of endangered animals. Then, the pre-trained image completion network CR-Fill is used to repair the incomplete environment. Furthermore, our approach identifies a foreground–background mixture of different images to produce multiple new image examples, using the relation network to permit a more realistic mixture of foreground and background images. It does not require further supervision, and it is easy to embed into existing networks, which learn to compensate for the uncertainties and nonstationarities of few-shot learning. Our experimental results are in excellent agreement with theoretical predictions by different evaluation metrics, and they unveil the future potential of video surveillance to address endangered-animal detection in studies of their behavior and conservation.

Cancer-associated fibroblasts (CAFs) influence many aspects of pancreatic adenocarcinoma (PAAD) carcinogenesis, including tumor cell proliferation, angiogenesis, invasion, and metastasis. A six-gene prognostic signature was constructed for PAAD based on the 189 CAF marker genes identified in single-cell RNA-sequencing data. Multivariate analyses showed that the risk score was independently prognostic for survival in the TCGA (P < 0.001) and ICGC (P = 0.004) cohorts. Tumor infiltration of CD8 T (P = 0.005) cells and naïve B cells (P = 0.001) was greater in the low-risk than in the high-risk group, with infiltration of these cells negatively correlated with risk score. Moreover, the TMB score was lower in the low-risk than in the high-risk group (P = 0.0051). Importantly, patients in low-risk group had better immunotherapy responses than in the high-risk group in an independent immunotherapy cohort (IMvigor210) (P = 0.039). The CAV1 and SOD3 were highly expressed in CAFs of PAAD tissues, which revealed by immunohistochemical staining. In summary, this comprehensive analysis resulted in the development of a novel prognostic signature, which was associated with immune cell infiltration, drug sensitivity, and TMB, and could predict the prognosis and immunotherapy response of patients with PAAD.

Seed dormancy and germination play pivotal roles in the agronomic traits of plants, and the degree of dormancy intuitively affects the yield and quality of crops in agricultural production. Seed priming is a pre-sowing seed treatment that enhances and accelerates germination, leading to improved seedling establishment. Seed priming technologies, which are designed to partially activate germination, while preventing full seed germination, have exerted a profound impact on agricultural production. Conventional seed priming relies on external priming agents, which often yield unstable results. What works for one variety might not be effective for another. Therefore, it is necessary to explore the internal factors within the metabolic pathways that influence seed physiology and germination. This review unveils the underlying mechanisms of seed metabolism and germination, the factors affecting seed dormancy and germination, as well as the current seed priming technologies that can result in stable and better germination.

BackgroundSignal transduction mediated by heterotrimeric G proteins, which comprise the α, β, and γ subunits, is one of the most important signaling pathways in rice plants. RGA1, which encodes the Gα subunit of the G protein, plays an important role in the response to various types of abiotic stress, including salt, drought, and cold stress. However, the role of RGA1 in the response to heat stress remains unclear.ResultsThe heat-resistant mutant ett1 (enhanced thermo-tolerance 1) with a new allele of the RGA1 gene was derived from an ethane methyl sulfonate-induced Zhonghua11 mutant. After 45 °C heat stress treatment for 36 h and recovery for 7 d, the survival rate of the ett1 mutants was significantly higher than that of wild-type (WT) plants. The malondialdehyde content was lower, and the maximum fluorescence quantum yield of photosystem II, peroxidase activity, and hsp expression were higher in ett1 mutants than in WT plants after 12 h of exposure to 45 °C. The RNA-sequencing results revealed that the expression of genes involved in the metabolism of carbohydrate, nicotinamide adenine dinucleotide, and energy was up-regulated in ett1 under heat stress. The carbohydrate content and the relative expression of genes involved in sucrose metabolism indicated that carbohydrate metabolism was accelerated in ett1 under heat stress. Energy parameters, including the adenosine triphosphate (ATP) content and the energy charge, were significantly higher in the ett1 mutants than in WT plants under heat stress. Importantly, exogenous glucose can alleviate the damages on rice seedling plants caused by heat stress.ConclusionRGA1 negatively regulates the thermo-tolerance in rice seedling plants through affecting carbohydrate and energy metabolism.

As one of the key vectors for the transmission of Dengue fever, Aedes albopictus is highly ecologically adaptable. The development of environmentally compatible biological defence and control technologies has therefore become an urgent need for vector biological control worldwide. This study constructed and used double-stranded RNA (dsRNA) expression vectors targeting the cyp314a1 and cyp315a1 genes of Ae. albopictus to transform Chlamydomonas reinhardtii and Chlorella vulgaris, achieving RNA interference (RNAi)-mediated gene silencing. The efficacy of the RNAi recombinant algal strain biocide against Ae. albopictus was evaluated by administering it to Ae. albopictus larvae. The results showed that the oral administration of the cyp314a1 and cyp315a1 RNAi recombinant C. reinhardtii/C. vulgaris strains was lethal to Ae. albopictus larvae and severely affected their pupation and emergence. The recombinant algal strains triggered a burst of ROS (Reactive Oxygen Species) in the mosquitoes’ bodies, resulting in significant increases in the activities of the superoxide dismutase (SOD), peroxiredoxin (POD) and catalase (CAT), as well as significant upregulation of the mRNA levels of the CME pathway genes in larvae. In the simulated field experiment, the number of Ae. albopictus was reduced from 1000 to 0 in 16 weeks by the RNAi recombinant Chlorella, which effectively controlled the population of mosquitoes. Meanwhile, the levels of nitrogen (N), phosphorus (P), nitrate, nitrite, ammonia and COD (Chemical Oxygen Demand) in the test water decreased significantly. High-throughput sequencing analyses of 18S rDNA and 16S rDNA showed that, with the release of RNAi recombinant Chlorella into the test water, the biotic community restructuring dominated by resource competition caused by algal bloom, as well as the proliferation of anaerobic bacteria and the decline of aerobic bacteria triggered by anaerobic conditions, are the main trends in the changes in the test water. This study is an important addition to the use of RNAi recombinant microalgae as a biocide.

Background Aedes albopictus is a primary vector for the transmission of dengue fever. RNA interference (RNAi)-based biocidal technology represents an important alternative and complement to conventional chemically synthesized insecticides. Methods Chlorella vulgaris was used as a carrier organism for RNAi-mediated gene silencing of Ae. albopictus . Short hairpin RNA (shRNA) expression vectors targeting the vgat and vmat genes of Ae. albopictus were constructed and subsequently used to transform C. vulgaris . The shRNA-transformed Chlorella were then administered to Ae. albopictus larvae or incorporated into attractive toxic sugar baits (ATSB) for adult feeding. The effects of silencing the vgat and vmat genes on Ae. albopictus were then investigated. Results Both vgat and vmat shRNA-recombinant Chlorella exhibited high lethality against Ae. albopictus larvae and adults. Conversely, shRNA-recombinant Chlorella ATSBs were found to have no lethal effects on non-target organisms, including Drosophila melanogaster , Megalurothrips usitatus , Messor structor , and Lithobates catesbeiana tadpoles. Together, these results confirm the specificity and safety of using shRNA-recombinant Chlorella as a mosquito-killing agent. The results of a semi-field trial demonstrate that recombinant Chlorella ATSB maintained high lethality against Ae. albopictus and significantly reduced the number of eggs laid by this species. Additional experiments revealed that knockdown of the vgat gene in Ae. albopictus resulted in reduced sleep duration, leg twitching, and impaired flight. Conversely, knockdown of the vmat gene increased sleep duration, impaired walking and flight, and induced insensitivity to light levels. Conclusions Recombinant Chlorella expressing vgat and vmat shRNAs demonstrated strong lethality, high specificity, and good safety against both larval and adult Ae. albopictus . Oral delivery of shRNAs effectively knocked down mosquito target genes, providing a convenient approach for functional studies of mosquito genetics. Notably, this study is an important addition to the use of recombinant microalgae as a mosquito biocide. Graphical Abstract

Dry direct seeding of rice has emerged as an effective method for reducing the excessive water demand associated with conventional rice transplantation, presenting significant potential for enhancing sustainability. However, this cultivation method is hindered by high seed usage and often inconsistent and low seedling emergence. Seed priming, a pre-sowing treatment, has been employed to mitigate these issues, but the inconsistent effects of exogenous priming agents remain a concern. Currently, there is limited molecular-level information on the uneven seedling emergence and effective screening methods for priming agents. In this study, we employed a metabolomics approach using advanced chromatography and mass spectrometry technology to identify differential accumulation of metabolites (DAMs) in seeds with varying germination energies. The seed priming technique was also used to validate the identified DAMs. We investigated the proportion of different specific gravity seeds and the corresponding germination energy across 20 varieties and established a relationship between different specific gravity seeds and germination energy. Our results showed that seeds with high and low germination energy differed in several metabolites, including amino acids, organic acids, and others. We further confirmed the critical role of these DAMs in determining seed germination energy under dry direct seeding. This research provides valuable insights into the metabolic mechanisms associated with germination energy and offers a useful approach for screening effective endogenous seed priming agents.