Axonal junction defects and an inhibitory environment after spinal cord injury seriously hinder the regeneration of damaged tissues and neuronal functions. At the site of spinal cord injury, ...regenerative biomaterials can fill cavities, deliver curative drugs, and provide adsorption sites for transplanted or host cells. Some regenerative biomaterials can also inhibit apoptosis, inflammation and glial scar formation, or further promote neurogenesis, axonal growth and angiogenesis. This review summarized a variety of biomaterial scaffolds made of natural, synthetic, and combined materials applied to spinal cord injury repair. Although these biomaterial scaffolds have shown a certain therapeutic effect in spinal cord injury repair, there are still many problems to be resolved, such as product standards and material safety and effectiveness.
Colorectal cancer (CRC) is among the most lethal and prevalent malignancies in the world and was responsible for nearly 881,000 cancer-related deaths in 2018. Surgery and chemotherapy have long been ...the first choices for cancer patients. However, the prognosis of CRC has never been satisfying, especially for patients with metastatic lesions. Targeted therapy is a new optional approach that has successfully prolonged overall survival for CRC patients. Following successes with the anti-EGFR (epidermal growth factor receptor) agent cetuximab and the anti-angiogenesis agent bevacizumab, new agents blocking different critical pathways as well as immune checkpoints are emerging at an unprecedented rate. Guidelines worldwide are currently updating the recommended targeted drugs on the basis of the increasing number of high-quality clinical trials. This review provides an overview of existing CRC-targeted agents and their underlying mechanisms, as well as a discussion of their limitations and future trends.
Domain-specific hardware is becoming a promising topic in the backdrop of improvement slow down for general-purpose processors due to the foreseeable end of Moore's Law. Machine learning, especially ...deep neural networks (DNNs), has become the most dazzling domain witnessing successful applications in a wide spectrum of artificial intelligence (AI) tasks. The incomparable accuracy of DNNs is achieved by paying the cost of hungry memory consumption and high computational complexity, which greatly impedes their deployment in embedded systems. Therefore, the DNN compression concept was naturally proposed and widely used for memory saving and compute acceleration. In the past few years, a tremendous number of compression techniques have sprung up to pursue a satisfactory tradeoff between processing efficiency and application accuracy. Recently, this wave has spread to the design of neural network accelerators for gaining extremely high performance. However, the amount of related works is incredibly huge and the reported approaches are quite divergent. This research chaos motivates us to provide a comprehensive survey on the recent advances toward the goal of efficient compression and execution of DNNs without significantly compromising accuracy, involving both the high-level algorithms and their applications in hardware design. In this article, we review the mainstream compression approaches such as compact model, tensor decomposition, data quantization, and network sparsification. We explain their compression principles, evaluation metrics, sensitivity analysis, and joint-way use. Then, we answer the question of how to leverage these methods in the design of neural network accelerators and present the state-of-the-art hardware architectures. In the end, we discuss several existing issues such as fair comparison, testing workloads, automatic compression, influence on security, and framework/hardware-level support, and give promising topics in this field and the possible challenges as well. This article attempts to enable readers to quickly build up a big picture of neural network compression and acceleration, clearly evaluate various methods, and confidently get started in the right way.
•Hyperandrogenism, insulin resistance and obesity forming a vicious cycle to promote PCOS development.
Polycystic ovary syndrome (PCOS) is a complex and heterogeneous endocrine disease characterized ...by clinical or laboratorial hyperandrogenism, oligo-anovulation and metabolic abnormalities, including insulin resistance, excessive weight or obesity, type II diabetes, dyslipidemia and an increased risk of cardiovascular disease. The most significant clinical manifestation of PCOS is hyperandrogenism. Excess androgen profoundly affects granulosa cell function and follicular development via complex mechanisms that lead to obesity and insulin resistance. Most PCOS patients with hyperandrogenism have steroid secretion defects that result in abnormal folliculogenesis and failed dominant follicle selection. Hyperandrogenism induces obesity, hairy, acne, and androgenetic alopecia. These symptoms can bring great psychological stress to women. Drugs such as combined oral contraceptive pills, metformin, pioglitazone and low-dose spironolactone help improve pregnancy rates by decreasing androgen levels in vivo. Notably, PCOS is heterogeneous, and hyperandrogenism is not the only pathogenic factor. Obesity and insulin resistance aggravate the symptoms of hyperandrogenism, forming a vicious cycle that promotes PCOS development. Although numerous studies have been conducted, the definitive pathogenic mechanisms of PCOS remain uncertain. This review summarizes and discusses previous and recent findings regarding the relationship between hyperandrogenism, insulin resistance, obesity and PCOS.
Phytophthora root rot caused by the oomycete Phytophthora capsici is the most devastating disease in pepper production worldwide, and current management strategies have not been effective in ...preventing this disease. Therefore, the use of resistant varieties was regarded as an important part of disease management of P. capsici. However, our knowledge of the molecular mechanisms underlying the defense response of pepper roots to P. capsici infection is limited. A comprehensive transcriptome and metabolome approaches were used to dissect the molecular response of pepper to P. capsici infection in the resistant genotype A204 and the susceptible genotype A198 at 0, 24 and 48 hours post-inoculation (hpi). More genes and metabolites were induced at 24 hpi in A204 than A198, suggesting the prompt activation of defense responses in the resistant genotype, which can attribute two proteases, subtilisin-like protease and xylem cysteine proteinase 1, involved in pathogen recognition and signal transduction in A204. Further analysis indicated that the resistant genotype responded to P. capsici with fine regulation by the Ca.sup.2+- and salicylic acid-mediated signaling pathways, and then activation of downstream defense responses, including cell wall reinforcement and defense-related genes expression and metabolites accumulation. Among them, differentially expressed genes and differentially accumulated metabolites involved in the flavonoid biosynthesis pathways were uniquely activated in the resistant genotype A204 at 24 hpi, indicating a significant role of the flavonoid biosynthesis pathways in pepper resistance to P. capsici. The candidate transcripts may provide genetic resources that may be useful in the improvement of Phytophthora root rot-resistant characters of pepper. In addition, the model proposed in this study provides new insight into the defense response against P. capsici in pepper, and enhance our current understanding of the interaction of pepper-P. capsici.
Deep learning algorithms can help uncover patterns, make predictions, or generate new content related to folk culture, thus bridging the gap between heritage and advanced technology. The confidence ...model in a cloud context refers to a system or approach used to assess the reliability, security, or performance of cloud seivices. It might involve factors such as seivice uptime, data security, scalability, and compliance with industry standards, hr this paper focused on the dynamic landscape of consumer preferences within folk music through cloud-based technologies integrated with deep learning. Folk music, with its rich cultural diversity and historical significance, presents a unique context for investigating the intricacies of consumer taste. The proposed model uses the "Ranking" based deep learning within cloudbased resources to predict and classify consumer preferences effectively. With the integration of the cloud confidence model ranking is implemented for the estimation of hacks hi folk music. The estimated hacks are evaluated and stored in the cloud environment based on the preferences of the customers. The classification of the hacks and consumer preferences are ranked with the cloud model features. The simulation results demonstrated that the ranking of hacks effectively improves consumer preferences with the cloud confidence model in folk music. The results enhancing personalized experiences and facilitating informed decision-making for busmesses and cultural institutions operating hi the rich and diverse landscape of folk culture.
The intersection of technology and tradition offers unprecedented opportunities for spreading folk culture, mainly through innovative knowledge graph technology. This research delves into the ...transformative potential of knowledge mapping for folk culture dissemination, with the dual goals of boosting dissemination efficiency and safeguarding our rich cultural heritage. We advocate for integrating scientific methods and theoretical insights to enrich cultural communication, exploring the application of knowledge mapping in folk culture through rigorous quantitative analysis and illustrative case studies. The technology’s application has notably increased the reach and engagement of cultural communication, enhancing audience engagement by 20% and interaction rates by 30% over traditional dissemination methods. Our study highlights knowledge mapping technology as a critical driver for innovating folk culture dissemination, providing essential technical support and offering new pathways for the contemporary communication of traditional culture.
The pandemic of coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has become a global crisis. Replication of SARS-CoV-2 requires the viral ...RNA-dependent RNA polymerase (RdRp) enzyme, a target of the antiviral drug remdesivir. Here we report the cryo-electron microscopy structure of the SARS-CoV-2 RdRp, both in the apo form at 2.8-angstrom resolution and in complex with a 50-base template-primer RNA and remdesivir at 2.5-angstrom resolution. The complex structure reveals that the partial double-stranded RNA template is inserted into the central channel of the RdRp, where remdesivir is covalently incorporated into the primer strand at the first replicated base pair, and terminates chain elongation. Our structures provide insights into the mechanism of viral RNA replication and a rational template for drug design to combat the viral infection.
A novel thioether chitosan oligosaccharide (COS-All-Tio) was prepared by the reaction of chitosan oligosaccharide (COS) with 3-bromopropene, followed by the coupling with tiopronin (Tio) using a ...thiol-ene reaction. The degree of substitution of COS-All-Tio reached 1.48. The structure of COS-All-Tio was identified by IR, NMR spectra. It was found that COS-All-Tio possessed more potent antioxidant activities than COS. The IC50 values of COS-All-Tio for scavenging DPPH, ABTS+ and OH were 0.31, 0.39 and 0.73 mg/mL, respectively, while the corresponding values for COS were 0.66, 2.89 and 1.41 mg/mL, respectively. COS-All-Tio was also found to possess much stronger antibacterial effect than COS against five bacteria strains (Staphylococcus aureus, Bacillus subtilis, Listeria monocytogenes, Escherichia coli and Pseudomonas aeruginosa). Further, COS-All-Tio was found to be non-toxic to RAW264.7 macrophages and MRC-5 human lung cells. This work provides a convenient way to improve the antioxidant and antibacterial activities of COS.
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Collagen scaffolds possess a three-dimensional porous structure that provides sufficient space for cell growth and proliferation, the passage of nutrients and oxygen, and the discharge of ...metabolites. In this study, a porous collagen scaffold with axially-aligned luminal conduits was prepared. In vitro biocompatibility analysis of the collagen scaffold revealed that it enhances the activity of neural stem cells and promotes cell extension, without affecting cell differentiation. The collagen scaffold loaded with neural stem cells improved the hindlimb motor function in the rat model of T8 complete transection and promoted nerve regeneration. The collagen scaffold was completely degraded in vivo within 5 weeks of implantation, exhibiting good biodegradability. Rectal temperature, C-reactive protein expression and CD68 staining demonstrated that rats with spinal cord injury that underwent implantation of the collagen scaffold had no notable inflammatory reaction. These findings suggest that this novel collagen scaffold is a good carrier for neural stem cell transplantation, thereby enhancing spinal cord repair following injury. This study was approved by the Animal Ethics Committee of Nanjing Drum Tower Hospital (the Affiliated Hospital of Nanjing University Medical School), China (approval No. 2019AE02005) on June 15, 2019.
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