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BACKGROUND: Potatoes, a major economic crop, are significantly impacted by Fusarium dry rot, a prevalent postharvest disease. Despite the broad‐spectrum antimicrobial properties of cinnamaldehyde, a naturally‐derived plant substance, its efficacy against the causal pathogen of potato dry rot (Fusarium oxysporum) and the underlying mechanisms have not been extensively studied. RESULTS: Our study demonstrates that cinnamaldehyde effectively inhibits the growth of Fusarium oxysporum, the pathogen responsible for potato dry rot, and increases its sensitivity to environmental stress factors such as extreme temperatures and high salt stress. Treatment with cinnamaldehyde results in altered fungal mycelium morphology, compromised cell wall stability, and disrupted cell membrane integrity, thereby reducing spore viability. Specifically, it interferes with the cell membrane and cell wall structures of the fungus, potentially disrupting fungal growth by modulating signaling pathways involved in cell wall maintenance, chitin metabolism, and GPI‐anchored protein function. Notably, we show that cinnamaldehyde induces a form of regulated cell death in F. oxysporum, which is characterized not as typical apoptosis, as evidenced by Annexin V negative staining. However, the specific cell death type and underlying mechanism still needed to be further explored. CONCLUSION: Cinnamaldehyde, an environmentally friendly plant‐based active compound, exhibits strong inhibitory effects on F. oxysporum, indicating its potential use in the prevention and control strategies for potato dry rot. This research contributes to the understanding of novel antifungal mechanisms and offers promising insights into eco‐friendly alternatives for managing this economically significant postharvest disease. © 2024 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

BackgroundSolid oxide cell (SOC) is the core converter for hydrogen production by high temperature electrolysis of water vapor and hydrogen fuel utilization.PurposeThis study aims to develope two kinds of aqueous casting pastes of NiO-YSZ with different components for the batch preparation of SOC without the usage of a large number of organic solvents.MethodsA 10 cm×10 cm large-scale full-scale cell was prepared by screen printing the hydrogen electrode functional layer, electrolyte layer, barrier layer and oxygen electrode layer with NiO-YSZ support film at one time casting of about 450 μm. The effect of dispersant on the microstructure of hydrogen electrode support and the stability of the pastes were analyzed by scanning electron microscope (SEM). The performance of the SOCs were tested by I-V curve and electrochemical impedance.ResultsBased on the optimized NiO-YSZ supports, the prepared planar SOCs delivers a peak power density of 0.36 W·cm-2 at 750 ℃. The electrolysis current density of SOC can reach -0.68 A·cm-2 at 1.30 V in solid oxide electrolysis cell (SOEC) model.ConclusionsThe performances of the aqueous-based SOCs can be considered highly remarkable, thus supporting the success in scaling the fabrication of SOCs using more environ-mentally friendly processes than conventional ones.

Species within the genus Chenopodium hold significant research interest due to their nutritional richness and salt tolerance. However, the morphological similarities among closely related species and a dearth of genomic resources have impeded their comprehensive study and utilization. In the present research, we conduct the sequencing and assembly of chloroplast (cp) genomes from six Chenopodium and related species, five of which were sequenced for the first time. These genomes ranged in length from 151,850 to 152,215 base pairs, showcased typical quadripartite structures, and encoded 85 protein-coding genes (PCGs), 1 pseudogene, 37 tRNA genes, and 8 rRNA genes. Compared with the previously published sequences of related species, these cp genomes are relatively conservative, but there are also some interspecific differences, such as inversion and IR region contraction. We discerned 929 simple sequence repeats (SSRs) and a series of highly variable regions across 16 related species, predominantly situated in the intergenic spacer (IGS) region and introns. The phylogenetic evaluations revealed that Chenopodium is more closely related to genera such as Atriplex, Beta, Dysphania, and Oxybase than to other members of the Amaranthaceae family. These lineages shared a common ancestor approximately 60.80 million years ago, after which they diverged into distinct genera. Based on InDels and SNPs between species, we designed 12 pairs of primers for species identification, and experiments confirmed that they could completely distinguish 10 related species. [ABSTRACT FROM AUTHOR]

Fe0.95S1.05 with high reactivity and stability was incorporated into WS2 nanosheets via a one‐step solvothermal method for the first time. The resulted hybrid catalyst has much higher catalytic activity than WS2 and Fe0.95S1.05 alone, and the optimal WS2/Fe0.95S1.05 hybrid catalyst was found by adjusting the feed ratio. The addition of Fe0.95S1.05 was proven to be able to enhance the hydrogen evolution reaction (HER) activity of WS2, and vice versa. At the same time, it was found that the catalytic effect of the hybrid catalyst was the best when the feed ratio was W : Fe=2 : 1. In other words, we confirmed that there is a synergistic effect between W‐ and Fe‐based sulfide hybrid catalysts, and validated that the reason for the improved HER performance is the strong interaction between the two in the middle sulfur. WS2/Fe0.95S1.05‐2 hybrid catalyst leads to enhanced HER activity, which shows a low overpotential of ∼0.172 V at 10 mA cm−2, low Tafel slope of ∼53.47 mV/decade. This study supplies innovative synthesis of a highly active WS2/Fe0.95S1.05 hybrid catalyst for HER. [ABSTRACT FROM AUTHOR]

The synthesis of highly active, stable and cost-effective electrocatalysts for overall water splitting is critical but challenging. Herein, we synthesized nickel-doped pyrrhotite iron sulfide (Fe0.95−xNixS1.05) nanosheets via a one-pot synthetic route. When tested for oxygen evolution reaction (OER) performance in alkaline solutions, the as-prepared Fe0.8Ni0.15S1.05 catalyst exhibited superior electrocatalytic performance to commercial IrO2 with a current density of 10 mA cm−2 at an overpotential of 228 mV, and a Tafel slope of 53 mV dec−1. The hydrogen evolution reaction (HER) activity was achieved on Fe0.8Ni0.15S1.05 with a Tafel slope of 103 mV per decade, and a current density of 10 mA cm−2 at an overpotential of 263 mV. With nickel doping, the as-prepared pyrrhotite iron sulfide nanosheets can expose more active sites, and hence act as a highly efficient catalyst for overall water splitting. [ABSTRACT FROM AUTHOR]

Efficient and accurate semantic segmentation is the key technique for automatic remote sensing image analysis. While there have been many segmentation methods based on traditional hand-craft feature extractors, it is still challenging to process high-resolution and large-scale remote sensing images. In this work, a novel patch-wise semantic segmentation method with a new training strategy based on fully convolutional networks is presented to segment common land resources. First, to handle the high-resolution image, the images are split as local patches and then a patch-wise network is built. Second, training data is preprocessed in several ways to meet the specific characteristics of remote sensing images, i.e., color imbalance, object rotation variations and lens distortion. Third, a multi-scale training strategy is developed to solve the severe scale variation problem. In addition, the impact of conditional random field (CRF) is studied to improve the precision. The proposed method was evaluated on a dataset collected from a capital city in West China with the Gaofen-2 satellite. The dataset contains ten common land resources (Grassland, Road, etc.). The experimental results show that the proposed algorithm achieves 54.96% in terms of mean intersection over union (MIoU) and outperforms other state-of-the-art methods in remote sensing image segmentation. [ABSTRACT FROM AUTHOR]

Introduction: The WD40 gene family, prevalent in eukaryotes, assumes diverse roles in cellular processes. Spartina alterniflora , a halophyte with exceptional salt tolerance, flood tolerance, reproduction, and diffusion ability, offers great potential for industrial applications and crop breeding analysis. The exploration of growth and development-related genes in this species offers immense potential for enhancing crop yield and environmental adaptability, particularly in industrialized plantations. However, the understanding of their role in regulating plant growth and development remains limited., Methods: In this study, we conducted a comprehensive analysis of WD40 genes in S. alterniflora at the whole-genome level, delving into their characteristics such as physicochemical properties, phylogenetic relationships, gene architecture, and expression patterns. Additionally, we cloned the TTG1 gene, a gene in plant growth and development across diverse species., Results: We identified a total of 582 WD40 proteins in the S. alterniflora genome, exhibiting an uneven distribution across chromosomes. Through phylogenetic analysis, we categorized the 582 SaWD40 proteins into 12 distinct clades. Examining the duplication patterns of SaWD40 genes, we observed a predominant role of segmental duplication in their expansion. A substantial proportion of SaWD40 gene duplication pairs underwent purifying selection through evolution. To explore the functional aspects, we selected SaTTG1 , a homolog of Arabidopsis TTG1 , for overexpression in Arabidopsis. Subcellular localization analysis revealed that the SaTTG1 protein localized in the nucleus and plasma membrane, exhibiting transcriptional activation in yeast cells. The overexpression of SaTTG1 in Arabidopsis resulted in early flowering and increased seed size., Discussion: These outcomes significantly contribute to our understanding of WD40 gene functions in halophyte species. The findings not only serve as a valuable foundation for further investigations into WD40 genes in halophyte but also offer insights into the molecular mechanisms governing plant development, offering potential avenues in molecular breeding., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The reviewer ZL declared a shared affiliation with the authors MY, SC, and HL to the handling editor at the time of review. The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision., (Copyright © 2024 Yang, Chen, Geng, Gao, Chen and Li.)

Importance: The utilization of artificial intelligence for the differentiation of benign and malignant breast lesions in multiparametric MRI (mpMRI) assists radiologists to improve diagnostic performance., Objectives: To develop an automated deep learning model for breast lesion segmentation and characterization and to evaluate the characterization performance of AI models and radiologists., Materials and Methods: For lesion segmentation, 2,823 patients were used for the training, validation, and testing of the VNet-based segmentation models, and the average Dice similarity coefficient (DSC) between the manual segmentation by radiologists and the mask generated by VNet was calculated. For lesion characterization, 3,303 female patients with 3,607 pathologically confirmed lesions (2,213 malignant and 1,394 benign lesions) were used for the three ResNet-based characterization models (two single-input and one multi-input models). Histopathology was used as the diagnostic criterion standard to assess the characterization performance of the AI models and the BI-RADS categorized by the radiologists, in terms of sensitivity, specificity, accuracy, and the area under the receiver operating characteristic curve (AUC). An additional 123 patients with 136 lesions (81 malignant and 55 benign lesions) from another institution were available for external testing., Results: Of the 5,811 patients included in the study, the mean age was 46.14 (range 11-89) years. In the segmentation task, a DSC of 0.860 was obtained between the VNet-generated mask and manual segmentation by radiologists. In the characterization task, the AUCs of the multi-input and the other two single-input models were 0.927, 0.821, and 0.795, respectively. Compared to the single-input DWI or DCE model, the multi-input DCE and DWI model obtained a significant increase in sensitivity, specificity, and accuracy (0.831 vs. 0.772/0.776, 0.874 vs. 0.630/0.709, 0.846 vs. 0.721/0.752). Furthermore, the specificity of the multi-input model was higher than that of the radiologists, whether using BI-RADS category 3 or 4 as a cutoff point (0.874 vs. 0.404/0.841), and the accuracy was intermediate between the two assessment methods (0.846 vs. 0.773/0.882). For the external testing, the performance of the three models remained robust with AUCs of 0.812, 0.831, and 0.885, respectively., Conclusions: Combining DCE with DWI was superior to applying a single sequence for breast lesion characterization. The deep learning computer-aided diagnosis (CADx) model we developed significantly improved specificity and achieved comparable accuracy to the radiologists with promise for clinical application to provide preliminary diagnoses., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Zhu, Geng, Shan, Zhang, Shen, Dong, Liu, Li and Cheng.)

Fe 0.95 S 1.05 with high reactivity and stability was incorporated into WS 2 nanosheets via a one-step solvothermal method for the first time. The resulted hybrid catalyst has much higher catalytic activity than WS 2 and Fe 0.95 S 1.05 alone, and the optimal WS 2 /Fe 0.95 S 1.05 hybrid catalyst was found by adjusting the feed ratio. The addition of Fe 0.95 S 1.05 was proven to be able to enhance the hydrogen evolution reaction (HER) activity of WS 2 , and vice versa. At the same time, it was found that the catalytic effect of the hybrid catalyst was the best when the feed ratio was W : Fe=2 : 1. In other words, we confirmed that there is a synergistic effect between W- and Fe-based sulfide hybrid catalysts, and validated that the reason for the improved HER performance is the strong interaction between the two in the middle sulfur. WS 2 /Fe 0.95 S 1.05 -2 hybrid catalyst leads to enhanced HER activity, which shows a low overpotential of ∼0.172 V at 10 mA cm -2 , low Tafel slope of ∼53.47 mV/decade. This study supplies innovative synthesis of a highly active WS 2 /Fe 0.95 S 1.05 hybrid catalyst for HER., (© 2021 Wiley-VCH GmbH.)