Divergent Regulation of CBF Regulon on Cold Tolerance and Plant Phenotype in Cassava Overexpressing Arabidopsis CBF3 Gene

Cassava is a tropical origin plant that is sensitive to chilling stress. In order to understand the CBF cold response pathway, a well-recognized regulatory mechanism in temperate plants, in cassava, overexpression of an Arabidopsis CBF3 gene is studied. This gene renders cassava increasingly tolerant to cold and drought stresses but is associated with retarded plant growth, leaf curling, reduced storage root yield, and reduced anthocyanin accumulation in a transcript abundance-dependent manner. Physiological analysis revealed that the transgenic cassava increased proline accumulation, reduced malondialdehyde production, and electrolyte leakage under cold stress. These transgenic lines also showed high relative water content when faced with drought. The expression of partial CBF-targeted genes in response to cold displayed temporal and spatial variations in the wild-type and transgenic plants: highly inducible in leaves and less altered in apical buds. In addition, anthocyanin accumulation was inhibited by downregulating the expression of genes involved in its biosynthesis and by interplaying between the CBF3 and the endogenous transcription factors. Thus, the heterologous CBF3 modulates the expression of stress-related genes and carries out a series of physiological adjustments under stressful conditions, showing a varied regulation pattern of CBF regulon from that of cassava CBFs

Study on Multi-step Forming Paths for Double Curved Parts of 1561 Aluminium Alloy

Recently, corrosion-resistant 1561 aluminium alloy has been widely applied to the production of curved parts. However, the sheets of this material will generate a high amount of springback during multi-point forming, which means that a large amount of springback compensation is required. In this paper, four multi-step forming paths are designed to study the effect of forming paths on the multi-point forming results of double curved parts for 1561 aluminium alloy. Numerical simulation of the multi-step forming of curved sheets is carried out by ABAQUS finite element simulation software. The simulation results indicate that the 1561 aluminium alloy double curved parts produce poor situations such as wrinkling and low forming accuracy in single-step forming, while the accuracy improves significantly and the forming quality increases after four-step forming. Therefore, a four-step forming path was adopted for stamping tests on double curved parts. The results of the accuracy inspection of the formed parts by Gom-inspect demonstrate that the quality of the curved parts can be effectively improved by four-step forming, which has a certain significance in guiding the forming preparation of parts for engineering applications

Engineering Properties of Sweet Potato Starch for Industrial Applications by Biotechnological Techniques Including Genome Editing

Sweet potato (Ipomoea batatas) is one of the largest food crops in the world. Due to its abundance of starch, sweet potato is a valuable ingredient in food derivatives, dietary supplements, and industrial raw materials. In addition, due to its ability to adapt to a wide range of harsh climate and soil conditions, sweet potato is a crop that copes well with the environmental stresses caused by climate change. However, due to the complexity of the sweet potato genome and the long breeding cycle, our ability to modify sweet potato starch is limited. In this review, we cover the recent development in sweet potato breeding, understanding of starch properties, and the progress in sweet potato genomics. We describe the applicational values of sweet potato starch in food, industrial products, and biofuel, in addition to the effects of starch properties in different industrial applications. We also explore the possibility of manipulating starch properties through biotechnological means, such as the CRISPR/Cas-based genome editing. The ability to target the genome with precision provides new opportunities for reducing breeding time, increasing yield, and optimizing the starch properties of sweet potatoes

Infrared Imaging of Magnetic Octupole Domains in Non-collinear Antiferromagnets

Magnetic structure plays a pivotal role in the functionality of antiferromagnets (AFMs), which not only can be employed to encode digital data but also yields novel phenomena. Despite its growing significance, visualizing the antiferromagnetic domain structure remains a challenge, particularly for non-collinear AFMs. Currently, the observation of magnetic domains in non-collinear antiferromagnetic materials is feasible only in Mn$_{3}$Sn, underscoring the limitations of existing techniques that necessitate distinct methods for in-plane and out-of-plane magnetic domain imaging. In this study, we present a versatile method for imaging the antiferromagnetic domain structure in a series of non-collinear antiferromagnetic materials by utilizing the anomalous Ettingshausen effect (AEE), which resolves both the magnetic octupole moments parallel and perpendicular to the sample surface. Temperature modulation due to the AEE originating from different magnetic domains is measured by the lock-in thermography, revealing distinct behaviors of octupole domains in different antiferromagnets. This work delivers an efficient technique for the visualization of magnetic domains in non-collinear AFMs, which enables comprehensive study of the magnetization process at the microscopic level and paves the way for potential advancements in applications.Comment: National Science Review in pres

PFKFB4 Promotes Breast Cancer Metastasis via Induction of Hyaluronan Production in a p38-Dependent Manner

Background/Aims: The bi-functional enzyme 6-phosphofructo-2-kinase/fructose-2, 6-biphosphatase-4 (PFKFB4) is highly expressed in many types of cancer and its requirement for tumor survival has been demonstrated in glioma, lung, and prostate cancers. However, whether PFKFB4 plays a role in the tumor metastasis remains uncertain. This study explores the role of PFKFB4 in tumor metastasis and its underlying mechanisms in breast cancer cells. Methods: The expression of PFKFB4 was first analyzed using the Cancer Genome Atlas (TCGA) dataset, and confirmed by immunohistochemical staining of tissue microarray and breast cancer tissues from patient samples. Gain- and loss-of- function approaches were used to investigate the effects of PFKFB4 on breast cancer cell migration in vitro. Orthotopic xenograft model and experimental metastasis model were used to assess the effects of PFKFB4 on breast cancer cell metastasis in vivo. ELISA and immunofluorescence staining were used to examine HA production. Quantitative RT-PCR and western blotting were used to explore the mRNA and protein levels of HAS2, respectively. Results: We found that PFKFB4 enhances the migration/invasiveness of breast cancer cells in vitro as well as in vivo. Notably, the effects of PFKFB4 on migration are mediated by induction of HAS2 expression and HA production. Moreover, PFKFB4-induced HAS2 up-regulation depends upon the activation of p38 signaling. Conclusion: PFKFB4 promotes the metastasis of breast cancer cells via induction of HAS2 expression and HA production in a p38-dependent manner. Therefore, the PFKFB4/p38/HAS2 signaling pathway may serve as a potential therapeutic target for metastatic breast cancer

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

MF‐RF: A detection approach based on multi‐features and random forest algorithm for improved collusive interest flooding attack

Abstract A new type of Collusive Interest Flooding Attack (CIFA), Improved Collusive Interest Flooding Attack (I‐CIFA), which originates from CIFA with a stronger concealment, higher attack effect, lower attack cost, and wider attack range in Named Data Networking (NDN). In order to detect this attack, the present study explores new detection features and establishes a sample set of attack features with different granularities, and accordingly, the Pearson coefficient is used to validate the correlation between the proposed features and the network states. Finally, the Random Forest model is designed to detect the I‐CIFA attack. To evaluate the performance of the approach, extensive experiments are conducted in ndnSIM platform. Test results show that the proposed detection approach outperforms other existing approaches with a detection rate of 98.1%, error rate of 1.9%, and false positive rate of 1.5%