Protein secondary structure prediction can provide important information for protein 3D structure prediction and protein functions. Deep learning offers a new opportunity to significantly improve ...prediction accuracy. In this article, a new deep neural network architecture, named the Deep inception‐inside‐inception (Deep3I) network, is proposed for protein secondary structure prediction and implemented as a software tool MUFOLD‐SS. The input to MUFOLD‐SS is a carefully designed feature matrix corresponding to the primary amino acid sequence of a protein, which consists of a rich set of information derived from individual amino acid, as well as the context of the protein sequence. Specifically, the feature matrix is a composition of physio‐chemical properties of amino acids, PSI‐BLAST profile, and HHBlits profile. MUFOLD‐SS is composed of a sequence of nested inception modules and maps the input matrix to either eight states or three states of secondary structures. The architecture of MUFOLD‐SS enables effective processing of local and global interactions between amino acids in making accurate prediction. In extensive experiments on multiple datasets, MUFOLD‐SS outperformed the best existing methods and other deep neural networks significantly. MUFold‐SS can be downloaded from http://dslsrv8.cs.missouri.edu/~cf797/MUFoldSS/download.html.
Chemodynamic therapy (CDT), enabling selective therapeutic effects and low side effect, attracts increasing attention in recent years. However, limited intracellular content of H2O2 and acid at the ...tumor site restrains the lasting Fenton reaction and thus the anticancer efficacy of CDT. Herein, a nanoscale Co–ferrocene metal–organic framework (Co‐Fc NMOF) with high Fenton activity is synthesized and combined with glucose oxidase (GOx) to construct a cascade enzymatic/Fenton catalytic platform (Co‐Fc@GOx) for enhanced tumor treatment. In this system, Co‐Fc NMOF not only acts as a versatile and effective delivery cargo of GOx molecules to modulate the reaction conditions, but also possesses excellent Fenton effect for the generation of highly toxic •OH. In the tumor microenvironment, GOx delivered by Co‐Fc NMOF catalyzes endogenous glucose to gluconic acid and H2O2. The intracellular acidity and the on‐site content of H2O2 are consequently promoted, which in turn favors the Fenton reaction of Co‐Fc NMOF and enhances the generation of reactive oxygen species (ROS). Both in vitro and in vivo results demonstrate that this cascade enzymatic/Fenton catalytic reaction triggered by Co‐Fc@GOx nanozyme enables remarkable anticancer properties.
A cascade nanozyme, named Co–ferrocene, combined with glucose oxidase (Co‐Fc@GOx) is successfully constructed, presenting a unique cascade enzymatic/Fenton effect for promoted chemodynamic therapy. In this platform, the Co–ferrocene metal–organic framework (Co‐Fc NMOF) shows unique Fenton activity, and GOx molecules are delivered significantly and amplify the Fenton reaction. This study offers another potential therapeutic platform for synergetic cancer treatment.
Recently, a series of innovative information-centric networking (ICN) architectures have been designed to better address the shift from host-centric end-to-end communication to requester-driven ...content retrieval. With the explosive increase of mobile data traffic, the mobility issue in ICN is a growing concern and a number of approaches have been proposed to deal with the mobility problem in ICN. Despite the potential advantages of ICN in mobile wireless environments, several significant research challenges remain to be addressed before its widespread deployment, including consistent routing, local cached content discovery, energy efficiency, privacy, security and trust, and practical deployment. In this paper, we present a brief survey on some of the works that have already been done to achieve mobile ICN, and discuss some research issues and challenges. We identify several important aspects of mobile ICN: overview, mobility enabling technologies, information-centric wireless mobile networks, and research challenges.
Protein disulfide isomerase (PDI) is the prototypic member of the thiol isomerase family that catalyses disulfide bond rearrangement. Initially identified in the endoplasmic reticulum as folding ...catalysts, PDI and other members in its family have also been widely reported to reside on the cell surface and in the extracellular matrix. Although how PDI is exported and retained on the cell surface remains a subject of debate, this unique pool of PDI is developing into an important mechanism underlying the redox regulation of protein sulfhydryls that are critical for the cellular activities under various disease conditions. This review aims to provide an overview of the pathophysiological roles of surface and extracellular PDI and their underlying molecular mechanisms. Understanding the involvement of extracellular PDI in these diseases will advance our knowledge in the molecular aetiology to facilitate the development of novel pharmacological strategies by specifically targeting PDI in extracellular compartments.
Background and Aim
Remimazolam tosilate (RT) is under evaluation as a sedative for endoscopic procedures. Herein, we aimed to evaluate safety including cognition recovery of RT administered in ...elderly patients undergoing upper gastrointestinal endoscopy and assess its safety dosage.
Methods
Ninety‐nine patients presenting for upper gastrointestinal endoscopy were randomized to receive 0.1 mg/kg RT (R1) or 0.2 mg/kg RT (R2), or propofol (P). Cognitive functions (memory, attention, and executive function) were measured via neuropsychological tests conducted before sedation and 5 min after recovery to full alertness. Adverse events were also assessed.
Results
There were no statistical differences between postoperative and baseline results for R1 group and P group, whereas those for R2 group revealed worsened postoperative cognitive functions (immediate recall and short delay recall) than baseline (P < 0.05). Compared with P group, Scores demonstrated worse restoration of immediate recall in R1 group, immediate recall, short‐delayed recall, and attention function in R2 group (P < 0.05). Patients in R2 group had a longer sedation time (12.09 vs 8.27 vs 8.21 min; P < 0.001) and recovery time (6.85 vs 3.82 vs 4.33 min; P < 0.001) than that in R1 group and P group. Moreover, the incidence of hypotension was 3.0% in R1 group, whereas it was 21.2% in R2 group and 48.5% in P group (P < 0.05).
Conclusion
The addition of 0.1 mg/kg RT as an adjunct to opiate sedation for upper gastrointestinal endoscopy not only achieves more stable perioperative hemodynamics but also achieves acceptable neuropsychiatric functions in elderly patients.
Worldwide the seafloor has been recognized as a major sink for microplastics. However, currently nothing is known about the sediment microplastic pollution in the North Pacific sector of the Arctic ...Ocean. Here, we present the first record of microplastic contamination in the surface sediment from the northern Bering and Chukchi Seas. The microplastics were extracted by the density separation method from collected samples. Each particle was identified using the microscopic Fourier transform infrared spectroscopy (μFTIR). The abundances of microplastics in sediments from all sites ranged from not detected (ND) to 68.78 items/kg dry weight (DW) of sediment. The highest level of microplastic contamination in the sediment was detected from the Chukchi Sea. A negative correlation between microplastic abundance and water depth was observed. Polypropylene (PP) accounted for the largest proportion (51.5%) of the identified microplastic particles, followed by polyethylene terephthalate (PET) (35.2%) and rayon (13.3%). Fibers constituted the most common shape of plastic particles. The range of polymer types, physical shapes and spatial distribution characteristics of the microplastics suggest that water masses from the Pacific and local coastal inputs are possible sources for the microplastics found in the study area. In overall, our results highlight the global distribution of these anthropogenic pollutants and the importance of management action to reduce marine debris worldwide.
Display omitted
•This is the first report of MPs in sediments from the Bering-Chukchi Sea shelf.•MPs levels were lower than those found in other regions of the world.•The sediments from the Chukchi Sea possessed the highest MPs abundances.•Fibers constituted the most common type in the Arctic sediments.
Aims/Introduction
Some previous studies reported no significant association of consuming fruit or vegetables, or fruit and vegetables combined, with type 2 diabetes. Others reported that only a ...greater intake of green leafy vegetables reduced the risk of type 2 diabetes. To further investigate the relationship between them, we carried out a meta‐analysis to estimate the independent effects of the intake of fruit, vegetables and fiber on the risk of type 2 diabetes.
Materials and Methods
Searches of MEDLINE and EMBASE for reports of prospective cohort studies published from 1 January 1966 to 21 July 2014 were carried out, checking reference lists, hand‐searching journals and contacting experts.
Results
The primary analysis included a total of 23 (11 + 12) articles. The pooled maximum‐adjusted relative risk of type 2 diabetes for the highest intake vs the lowest intake were 0.91 (95% confidence interval CI 0.87–0.96) for total fruits, 0.75 (95% CI 0.66–0.84) for blueberries, 0.87 (95% CI 0.81–0.93) for green leafy vegetables, 0.72 (95% CI 0.57–0.90) for yellow vegetables, 0.82 (95% CI 0.67–0.99) for cruciferous vegetables and 0.93 (95% CI 0.88–0.99) for fruit fiber in these high‐quality studies in which scores were seven or greater, and 0.87 (95% CI 0.80–0.94) for vegetable fiber in studies with a follow‐up period of 10 years or more.
Conclusions
A higher intake of fruit, especially berries, and green leafy vegetables, yellow vegetables, cruciferous vegetables or their fiber is associated with a lower risk of type 2 diabetes.
Our results showed that a higher intake of fruit especially berries and green leafy vegetables, or yellow vegetables, or cruciferous vegetables, or their fiber, is associated with a lower risk of type 2 diabetes.
The Transformer has been an indispensable staple in deep learning. However, for real-life applications, it is very challenging to deploy efficient Transformers due to the immense parameters and ...operations of models. To relieve this burden, exploiting sparsity is an effective approach to accelerate Transformers. Newly emerging Ampere graphics processing units (GPUs) leverage a 2:4 sparsity pattern to achieve model acceleration, while it can hardly meet the diverse algorithm and hardware constraints when deploying models. By contrast, we propose an algorithm-hardware co-optimized framework to flexibly and efficiently accelerate Transformers by utilizing general N:M sparsity patterns. First, from an algorithm perspective, we propose a sparsity inheritance mechanism along with inherited dynamic pruning (IDP) to obtain a series of N:M sparse candidate Transformers rapidly. A model compression scheme is further proposed to significantly reduce the storage requirement for deployment. Second, from a hardware perspective, we present a flexible and efficient hardware architecture, namely, STA, to achieve significant speedup when deploying N:M sparse Transformers. STA features not only a computing engine unifying both sparse-dense and dense-dense matrix multiplications with high computational efficiency but also a scalable softmax module eliminating the latency from intermediate off-chip data communication. Experimental results show that, compared to other methods, N:M sparse Transformers, generated using IDP, achieves an average of 6.7% improvement on accuracy with high training efficiency. Moreover, STA can achieve <inline-formula> <tex-math notation="LaTeX">14.47\times </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">11.33\times </tex-math></inline-formula> speedups compared to Intel i9-9900X and NVIDIA RTX 2080 Ti, respectively, and perform <inline-formula> <tex-math notation="LaTeX">2.00 \,\,\sim 19.47 \times </tex-math></inline-formula> faster inference than the state-of-the-art field-programmable gate array (FPGA)-based accelerators for Transformers.
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