Determinants of 14-3-3σ dimerization and function in drug and radiation resistance

Many proteins exist and function as homodimers. Understanding the detailed mechanism driving the homodimerization is important and will impact future studies targeting the “undruggable” oncogenic protein dimers. In this study, we used 14-3-3σ as a model homodimeric protein and performed a systematic investigation of the potential roles of amino acid residues in the interface for homodimerization. Unlike other members of the conserved 14-3-3 protein family, 14-3-3σ prefers to form a homodimer with two subareas in the dimeric interface that has 180° symmetry. We found that both subareas of the dimeric interface are required to maintain full dimerization activity. Although the interfacial hydrophobic core residues Leu12 and Tyr84 play important roles in 14-3-3σ dimerization, the non-core residue Phe25 appears to be more important in controlling 14-3-3σ dimerization activity. Interestingly, a similar non-core residue (Val81) is less important than Phe25 in contributing to 14-3-3σ dimerization. Furthermore, dissociating dimeric 14-3-3σ into monomers by mutating the Leu12, Phe25, or Tyr84 dimerization residue individually diminished the function of 14-3-3σ in resisting drug-induced apoptosis and in arresting cells at G2/M phase in response to DNA-damaging treatment. Thus, dimerization appears to be required for the function of 14-3-3σ

Overview of Mollisols in the world: Distribution, land use and management

Mollisols a.k.a., Black Soils or Prairie Soils make up about 916 million ha, which is 7% of the world’s ice-free land surface. Their distribution strongly correlates with native prairie ecosystems, but is not limited to them. They are most prevalent in the mid-latitudes of North America, Eurasia, and South America. In North America, they cover 200 million ha of the United States, more than 40 million ha of Canada and 50 million ha of Mexico. Across Eurasia they cover around 450 million ha, extending from the western 148 million ha in southern Russia and 34 million ha in Ukraine to the eastern 35 million ha in northeast China. They are common to South America’s Argentina and Uruguay, covering about 89 million and 13 million ha, respectively. Mollisols are often recognized as inherently productive and fertile soils. They are extensively and intensively farmed, and increasingly dedicated to cereals production, which needs significant inputs of fertilizers and tillage. Mollisols are also important soils in pasture, range and forage systems. Thus, it is not surprising that these soils are prone to soil erosion, dehumification (loss of stable aggregates and organic matter) and are suffering from anthropogenic soil acidity. Therefore, soil scientists from all of the world’s Mollisols regions are concerned about the sustainability of some of current trends in land use and agricultural practices. These same scientists recommend increasing the acreage under minimum or restricted tillage, returning plant residues and adding organic amendments such as animal manure to maintain or increase soil organic matter content, and more systematic use of chemical amendments such as agricultural limestone to replenish soil calcium reserves

Recent advances of nanovaccines on cancer theranostics

Cancer is a leading cause of death worldwide, with an estimated 20 million new cancer cases and 9.7 million cancer deaths worldwide in 2022. Immunotherapy provides innovative strategies among the most groundbreaking developments in cancer treatment. Cancer vaccines, as a form of immunotherapy, have a great prospect to help patients resistant to other standard-of-care immunotherapies. On the other hand, the various properties of nanomaterials play an essential role in the collecting, maturation, and activation of the immune system. Cancer vaccines based on nanomaterials (also called nanovaccines) can be specifically delivered to target tissues and cells through nanocarriers and nanoplatforms, thereby improving efficacy, extending the duration of antitumor immunity, and minimizing side effects. This paper reviewed the research progress of some nanovaccines in cancer immunotherapy, including polymer nanoparticle vaccine, liposome nanoparticle vaccine, cell-based nanoparticle vaccine, inorganic nanoparticle vaccine, adjuvant and auxiliary work. We believe that polymer nanoparticle-based nanovaccines have the most widespread applications currently, while liposome nanovaccines using mRNA are expected to see greater development in the future. We also think that nanovaccines can play a great role in cancer prevention and treatment, especially in prolonging the life span of patients

Detail-Enhancing Framework for Reference-Based Image Super-Resolution

Recent years have witnessed the prosperity of reference-based image super-resolution (Ref-SR). By importing the high-resolution (HR) reference images into the single image super-resolution (SISR) approach, the ill-posed nature of this long-standing field has been alleviated with the assistance of texture transferred from reference images. Although the significant improvement in quantitative and qualitative results has verified the superiority of Ref-SR methods, the presence of misalignment before texture transfer indicates room for further performance improvement. Existing methods tend to neglect the significance of details in the context of comparison, therefore not fully leveraging the information contained within low-resolution (LR) images. In this paper, we propose a Detail-Enhancing Framework (DEF) for reference-based super-resolution, which introduces the diffusion model to generate and enhance the underlying detail in LR images. If corresponding parts are present in the reference image, our method can facilitate rigorous alignment. In cases where the reference image lacks corresponding parts, it ensures a fundamental improvement while avoiding the influence of the reference image. Extensive experiments demonstrate that our proposed method achieves superior visual results while maintaining comparable numerical outcomes

Large Eddy Simulation (LES) of Glass Fibre Dispersion in an Internally Spout-Fluidised Bed for Thermoplastic Composite Processing

Large eddy simulation (LES) has been conducted to investigate glass fibre dispersion in an internally spout-fluidised bed with draft tube and disk-baffle, which was used in the manufacture of long glass fibre reinforced thermoplastic composites. The LES results have demonstrated that the internally spout-fluidised bed with draft tube and disk-baffle can remarkably improve its hydrody-namic behaviour, which can effectively disperse fibre bundles and promote pre-impregnation with resin powder in manufacturing fibre reinforced thermoplastics. The hydrodynamics of the spout-fluidised bed has been investigated and reported in a previous paper (Hosseini et al., 2009). This study attempts to reveal important features of fibre dispersion and correlations between the fibre disper-sion and the characteristics of turbulence in the internally spout-fluidised bed using the LES modelling, focusing on the likely hydro-dynamic impact on fibre dispersion. The simulation has clearly indicated that there exists a strong interaction between the turbulent shear flow and transported fibres in the spout-fluidised bed. Fibre entrainment is strongly correlated with the local vorticity distribu-tion. The dispersion of fibres was modelled by a species transport equation in the LES simulation. The turbulent kinetic energy, Rey-nolds stress and strain rate were obtained by statistical analysis of the LES results. The LES results also clearly show that addition of the internals in the spout-fluidised bed can significantly change the turbulent flow features and local vorticity distribution, enhancing the capacity and efficiency of fibre flocs dispersion

Deep Learning on Abnormal Chromosome Segments: An Intelligent Copy Number Variants Detection System Design

Gene testing emerged as a business in the last two decades, and the testing cost has been reduced from 100 million to 1000 dollars for the development of technologies. Preimplantation genetic screening (PGS) is a popular genetic profiling of embryos prior to implantation in gene testing. Copy number variants (CNVs) detection is a key task in PGS which still needs the manual operation and evaluation. At the same time, deep learning technology earns a booming development and wide application in recent years for its strong computing and learning capability. This research redesigns the PGS workflow with the intelligent CNVs detection system, and proposes the corresponding system framework. Deep learning is selected as the proper technology in the system design for CNVs detection, which also fit the task of denoising. The evaluation is conducted on simulation dataset with high accuracy and low time cost, which may achieve the requirements of clinical application and reduce the workload of bioinformatics experts. Moreover, the redesigned process and proposed framework may enlighten the intelligent system design for gene testing in following work, and provide a guidance of deep learning application in AI healthcar

MiLMo:Minority Multilingual Pre-trained Language Model

Pre-trained language models are trained on large-scale unsupervised data, and they can fine-turn the model only on small-scale labeled datasets, and achieve good results. Multilingual pre-trained language models can be trained on multiple languages, and the model can understand multiple languages at the same time. At present, the search on pre-trained models mainly focuses on rich resources, while there is relatively little research on low-resource languages such as minority languages, and the public multilingual pre-trained language model can not work well for minority languages. Therefore, this paper constructs a multilingual pre-trained model named MiLMo that performs better on minority language tasks, including Mongolian, Tibetan, Uyghur, Kazakh and Korean. To solve the problem of scarcity of datasets on minority languages and verify the effectiveness of the MiLMo model, this paper constructs a minority multilingual text classification dataset named MiTC, and trains a word2vec model for each language. By comparing the word2vec model and the pre-trained model in the text classification task, this paper provides an optimal scheme for the downstream task research of minority languages. The final experimental results show that the performance of the pre-trained model is better than that of the word2vec model, and it has achieved the best results in minority multilingual text classification. The multilingual pre-trained model MiLMo, multilingual word2vec model and multilingual text classification dataset MiTC are published on http://milmo.cmli-nlp.com/

“Left on read” examining social media users’ lurking behavior: an integration of anxiety and social media fatigue

IntroductionWith the widespread use of social media, the behavior and mindset of users have been transformed, leading to a gradual increase in lurking users, which can impede the sustainable development of social media platforms. In this study, we aim to investigate the impact of intrinsic and extrinsic motivational factors on social media users’ anxiety, social media fatigue, and lurking behavior.MethodologyFor the confirmation of these phenomena and to validate the theories, a structural equation model was constructed based on the SSO (Stressor-Strain-Outcome) theoretical framework. The model was then tested and validated with data from 836 valid online surveys. These data were analyzed using SPSS 27.0 and AMOS 24.0 software.ResultsThe results indicate that intrinsic motivations (such as social comparison and privacy concerns) and extrinsic motivations (including information overload, functional overload, and social overload) are positively associated with users’ lurking behavior through the mediating effects of social media fatigue and anxiety. Additionally, for the mediator variables, social media fatigue was found to be positively associated with anxiety.DiscussionThese findings underscore the importance of social media platforms considering both intrinsic and extrinsic motivational factors to mitigate user anxiety and social media fatigue. By addressing these factors, platforms can foster user satisfaction and increase engagement, ultimately contributing to the sustainable development of social media platforms

The combination of bioactive herbal compounds with biomaterials for regenerative medicine

Regenerative medicine aims to restore the function of diseased or damaged tissues and organs by cell therapy, gene therapy, and tissue engineering, along with the adjunctive application of bioactive molecules. Traditional bioactive molecules, such as growth factors and cytokines, have shown great potential in the regulation of cellular and tissue behavior, but have the disadvantages of limited source, high cost, short half-life, and side effects. In recent years, herbal compounds extracted from natural plants/herbs have gained increasing attention. This is not only because herbal compounds are easily obtained, inexpensive, mostly safe, and reliable, but also owing to their excellent effects, including anti-inflammatory, antibacterial, antioxidative, proangiogenic behavior and ability to promote stem cell differentiation. Such effects also play important roles in the processes related to tissue regeneration. Furthermore, the moieties of the herbal compounds can form physical or chemical bonds with the scaffolds, which contributes to improved mechanical strength and stability of the scaffolds. Thus, the incorporation of herbal compounds as bioactive molecules in biomaterials is a promising direction for future regenerative medicine applications. Herein, an overview on the use of bioactive herbal compounds combined with different biomaterial scaffolds for regenerative medicine application is presented. We first introduce the classification, structures, and properties of different herbal bioactive components and then provide a comprehensive survey on the use of bioactive herbal compounds to engineer scaffolds for tissue repair/regeneration of skin, cartilage, bone, neural, and heart tissues. Finally, we highlight the challenges and prospects for the future development of herbal scaffolds toward clinical translation. Overall, it is believed that the combination of bioactive herbal compounds with biomaterials could be a promising perspective for the next generation of regenerative medicine