An intracellular delivery system for CRISPR/Cas9 is crucial for its application as a therapeutic genome editing technology in a broad range of diseases. Current vehicles carrying CRISPR/Cas9 limit in ...vivo delivery because of low tolerance and immunogenicity; thus, the in vivo delivery of genome editing remains challenging. Here, we report that cancer-derived exosomes function as natural carriers that can efficiently deliver CRISPR/Cas9 plasmids to cancer. Compared to epithelial cell-derived exosomes, cancer-derived exosomes provide potential vehicles for effective in vivo delivery via selective accumulation in ovarian cancer tumors of SKOV3 xenograft mice, most likely because of their cell tropism. CRISPR/Cas9-loaded exosomes can suppress expression of poly (ADP-ribose) polymerase-1 (PARP-1), resulting in the induction of apoptosis in ovarian cancer. Furthermore, the inhibition of PARP-1 by CRISPR/Cas9-mediated genome editing enhances the chemosensitivity to cisplatin, showing synergistic cytotoxicity. Based on these results, tumor-derived exosomes may be very promising for cancer therapeutics in the future.
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Ni‐rich layered oxides and Li‐rich layered oxides are topics of much research interest as cathodes for Li‐ion batteries due to their low cost and higher discharge capacities compared to those of ...LiCoO2 and LiMn2O4. However, Ni‐rich layered oxides have several pitfalls, including difficulty in synthesizing a well‐ordered material with all Ni3+ ions, poor cyclability, moisture sensitivity, a thermal runaway reaction, and formation of a harmful surface layer caused by side reactions with the electrolyte. Recent efforts towards Ni‐rich layered oxides have centered on optimizing the composition and processing conditions to obtain controlled bulk and surface compositions to overcome the capacity fade. Li‐rich layered oxides also have negative aspects, including oxygen loss from the lattice during first charge, a large first cycle irreversible capacity loss, poor rate capability, side reactions with the electrolyte, low tap density, and voltage decay during extended cycling. Recent work on Li‐rich layered oxides has focused on understanding the surface and bulk structures and eliminating the undesirable properties. Followed by a brief introduction, an account of recent developments on the understanding and performance gains of Ni‐rich and Li‐rich layered oxide cathodes is provided, along with future research directions.
Ni‐rich layered oxides and Li‐rich layered oxides are part of a new generation of high‐capacity Li‐ion battery cathodes currently under development. The current state of research on these two families of materials, some of the obstacles to further implementation, and some future areas of exploration are outlined.
Micrometer‐size LiFePO4 spheres with homogeneous double carbon coating layers have been prepared as potential electrode materials for battery applications. The double carbon‐coated LiFePO4 electrodes ...in a lithium‐ion cell exhibited discharge capacities of the order of 160 mAh g−1 and 115 mAh g−1 at 25 °C under 0.1 C‐rate and 10 C‐rate, respectively.
A cathode material of an electrically conducting carbon‐LiMnPO4 nanocomposite is synthesized by ultrasonic spray pyrolysis followed by ball milling. The effect of the carbon content on the ...physicochemical and electrochemical properties of this material is extensively studied. A LiMnPO4 electrode with 30 wt% acetylene black (AB) carbon exhibits an excellent rate capability and good cycle life in cell tests at 55 and 25 °C. This electrode delivers a discharge capacity of 158 mAh g−1 at 1/20 C, 126 mAh g−1 at 1 C, and 107 mAh g−1 at 2 C rate, which are the highest capacities reported so far for this type of electrode. Transmission electron microscopy and Mn dissolution results confirm that the carbon particles surrounding the LiMnPO4 protect the electrode from HF attack, and thus lead to a reduction of the Mn dissolution that usually occurs with this electrode. The improved electrochemical properties of the C‐LiMnPO4 electrode are also verified by electrochemical impedance spectroscopy.
The addition of acetylene black (AB) carbon to a nanostructured C‐LiMnPO4 cathode material results in an extraordinary electrode material for a lithium cell with very high reversible capacity and an excellent cycle life. The composite can easily be made by ultrasonic spray pyrolysis followed by ball milling. Microscopic studies confirm that the carbon particles protect the cathode materials from dissolution.
Delivery of high capacity with good retention is a challenge in developing cathodes for rechargeable sodium-ion batteries. Here we present a radially aligned hierarchical columnar structure in ...spherical particles with varied chemical composition from the inner end (NaNi0.75Co0.02Mn0.23O2) to the outer end (NaNi0.58Co0.06Mn0.36O2) of the structure. With this cathode material, we show that an electrochemical reaction based on Ni(2+/3+/4+) is readily available to deliver a discharge capacity of 157 mAh (g-oxide)(-1) (15 mA g(-1)), a capacity retention of 80% (125 mAh g(-1)) during 300 cycles in combination with a hard carbon anode, and a rate capability of 132.6 mAh g(-1) (1,500 mA g(-1), 10 C-rate). The cathode also exhibits good temperature performance even at -20°C. These results originate from rather unique chemistry of the cathode material, which enables the Ni redox reaction and minimizes the surface area contacting corrosive electrolyte.
In this work we report NaLi0.05(Ni0.25Fe0.25Mn0.5)0.95O2 layered cathode materials that were synthesized via a coprecipitation method. The NaLi0.05(Ni0.25Fe0.25Mn0.5)0.95O2 electrode exhibited an ...exceptionally high capacity (180.1 mA h g–1 at 0.1 C-rate) as well as excellent capacity retentions (0.2 C-rate: 89.6%, 0.5 C-rate: 92.1%) and rate capabilities at various C-rates (0.1 C-rate: 180.1 mA h g–1, 1 C-rate: 130.9 mA h g–1, 5 C-rate: 96.2 mA h g–1), which were achieved due to the Li supporting structural stabilization by introduction into the transition metal layer. By contrast, the electrode performance of the lithium-free NaNi0.25Fe0.25Mn0.5O2 cathode was inferior because of structural disintegration presumably resulting from Fe3+ migration from the transition metal layer to the Na layer during cycling. The long-term cycling using a full cell consisting of a NaLi0.05(Ni0.25Fe0.25Mn0.5)0.95O2 cathode was coupled with a hard carbon anode which exhibited promising cycling data including a 76% capacity retention over 200 cycles.
This paper presents a deep residual network for improving time-series forecasting models, indispensable to reliable and economical power grid operations, especially with high shares of renewable ...energy sources. Motivated by the potential performance degradation due to the overfitting of the prevailing stacked bidirectional long short-term memory (Bi-LSTM) layers associated with its linear stacking, we propose a concatenated residual learning by connecting the multi-level residual network (MRN) and DenseNet. This method further integrates long and short Bi-LSTM networks, ReLU, and SeLU for its activating function. Rigorous studies present superior prediction accuracy and parameter efficiency for the widely used temperature dataset as well as the actual wind power dataset. The peak value forecasting and generalization capability, along with the credible confidence range, demonstrate that the proposed model offers essential features of a time-series forecasting, enabling a general forecasting framework in grid operations. The source code of this paper can be found in https://github.com/MinseungKo/DRNet.git .
Lactobacillus species are used as probiotics and play an important role in fermented food production. However, use of 16S rRNA gene sequences as standard markers for the differentiation of ...Lactobacillus species offers a very limited scope, as several species of Lactobacillus share similar 16S rRNA gene sequences. In this study, we developed a rapid and accurate method based on comparative genomic analysis for the identification of 37 Lactobacillus species that are commonly used in probiotics and fermented foods.
To select species-specific sequences or genes, a total of 180 Lactobacillus genome sequences were compared using Python scripts. In 14 out of 37 species, species-specific sequences could not be found due to the similarity of the 16S-23S rRNA gene. Selected unique genes were obtained using comparative genomic analysis and all genes were confirmed to be specific for 52,478,804 genomes via in silico analysis; they were found not to be strain-specific, but to exist in all strains of the same species. Species-specific primer pairs were designed from the selected 16S-23S rRNA gene sequences or unique genes of species. The specificity of the species-specific primer pairs was confirmed using reference strains, and the accuracy and efficiency of the polymerase chain reaction (PCR) with the standard curve were confirmed. The PCR method developed in this study is able to accurately differentiate species that were not distinguishable using the 16S rRNA gene alone. This PCR assays were designed to detect and identify 37 Lactobacillus species. The developed method was then applied in the monitoring of 19 probiotics and 12 dairy products. The applied tests confirmed that the species detected in 17 products matched those indicated on their labels, whereas the remaining products contained species other than those appearing on the label.
The method developed in this study is able to rapidly and accurately distinguish different species of Lactobacillus, and can be used to monitor specific Lactobacillus species in foods such as probiotics and dairy products.
The toxicity of endocrine disruptors depends on the synergistic interactions of biological, environmental, and behavioral factors. The specific effects of diet, consumer product use, and behaviors, ...however, are debated in the literature, particularly with regard to endocrine disruptors found in breast milk. This study aimed to measure the levels of phthalate metabolites, bisphenol A, parabens, and triclosan in breast milk and to investigate their associations with various lifestyle factors. The breast milk samples as well as surveys were collected from 221 first-time mothers throughout South Korea and each sample was analyzed for the presence of 15 endocrine disruptors. Phthalate metabolites were detected in 5.4–83.3% of the samples, with median concentrations of 0.08–1.72 μg/L, while bisphenol A, parabens, and triclosan were detected in 25.8–88.2% of the samples, with median concentrations of 0.12–1.47 μg/L. High levels of endocrine disruptors were associated with frequent consumption of fish and cup noodles; the use of plastic and disposable food containers; the use of air fresheners, lotions and make-up; the purchase of new furniture; and socioeconomic status. We also observed the potential role of moderate walking activity on the reduction of these chemicals in breast milk. Our data provide evidence of the potential effects of diet, consumer products, and behavior on the presence of phthalate metabolites, bisphenol A, parabens, and triclosan in breast milk. Future studies should include community or regional impact on a mothers’ exposure to endocrine disruptors, to assess the joint contribution of both individual and neighborhood factors.
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•Phthalate metabolites, bisphenol A, parabens, and triclosan detected in breast milk.•High levels of endocrine disruptors in mothers associated with lifestyle factors.•Diet, consumer products, and behavior affect maternal toxic exposure in Korea.
Although
and
are essential food-fermenting bacteria, they are also opportunistic pathogens. Despite these species being commercially crucial, their taxonomy is still based on inaccurate ...identification methods. In this study, we present a novel approach for identifying two important
species,
.
and
.
, by combining matrix-assisted laser desorption/ionization and time-of-flight mass spectrometer (MALDI-TOF MS) data using machine-learning techniques. After on- and off-plate protein extraction, we observed that the BioTyper database misidentified or could not differentiate
species. Although
species exhibited very similar protein profiles, these species can be differentiated on the basis of the results of a statistical analysis. To classify
.
,
.
, and non-target
species, machine learning was used for 167 spectra, which led to the listing of potential species-specific mass-to-charge (
/
) loci. Machine-learning techniques including artificial neural networks, principal component analysis combined with the K-nearest neighbor, support vector machine (SVM), and random forest were used. The model that applied the Radial Basis Function kernel algorithm in SVM achieved classification accuracy of 1.0 for training and test sets. The combination of MALDI-TOF MS and machine learning can efficiently classify closely-related species, enabling accurate microbial identification.
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