Conventional microbial cell cultivation techniques are typically labor intensive, low throughput, and poorlyparallelized, rendering them inefficient. The development of automated, modular microbial ...cell micro‐cultivation systems, particularly those employing droplet microfluidics, have gained attention for their high‐throughput, highly paralellized and efficient cultivation capabilities. Here, we report the development of a microbial microdroplet culture system (MMC), which is an integrated platform for automated, high‐throughput cultivation and adaptive evolution of microorganisms. We demonstrated that the MMC yielded both accurate and reproducible results for the manipulation and detection of droplets. The superior performance of MMC for microbial cell cultivation was validated by comparing the growth curves of six microbial strains grown in MMC, conventional shake flasks or well plates. The highest incipient growth rate for all six microbial strains was achieved by using MMC. We also conducted an 18‐day process of adaptive evolution of methanol‐essential Escherichia coli strain in MMC and obtained two strains exhibiting higher growth rates compared with the parent strain. Our study demonstrates the power of MMC to provide an efficient and reliable approach for automated, high‐throughput microbial cultivation and adaptive evolution.
An integrated platform called microbial microdroplet culture system (MMC), which can perform various accurate and reproducible operations on microliter droplets, is developed for automated, high‐throughput cultivation and adaptive evolution of multiple microorganisms. Here, Jian and Guo validate the superior performance of MMC for microbial cultivation by comparing the growth rates of six microbial strains grown in MMC, conventional shake flasks or well plates. The authors also demonstrate its efficient power for adaptive evolution using a methanol–essential Escherichia coli strain.
Objective
Oral lichen planus (OLP) is a chronic inflammatory disease that occurs in the oral mucosa with characteristic white striations lesions, recurrent erosions, and pains. The etiology and ...pathogenesis of OLP are still unclear.
Materials and Methods
We analyzed the bacterial community structure of buccal mucosa in patients with OLP and normal controls by high‐throughput sequencing. Fluorescence in situ hybridization (FISH) was used to detect Prevotella melaninogenica (P. melaninogenica) in 13 OLP samples and 10 controls. The amounts of P. melaninogenica in OLP buccal mucosa and the expression of inflammatory cytokines in co‐culture of mouse‐derived macrophages with P. melaninogenica were detected by RT‐qPCR.
Results
The P. melaninogenica was more abundant in OLP than in healthy controls, and the differences were significant at the level of the phylum, family, genus, and species (p < .05). FISH showed that P. melaninogenica can invade the epithelium and even the lamina propria of OLP, while no invasion was found in the normal mucosa. Prevotella melaninogenica can adhere to and invade macrophages and then activate the transcription of IL‐1β, IL‐6, and TNF‐α in NF‐κB signaling pathway.
Conclusion
Prevotella melaninogenica may be involved in the pathogenic process of OLP, and its specific mechanism deserves further study.
G-quadruplex (G4) structures formed by guanine-rich nucleic acids are implicated in essential physiological and pathological processes and serve as important drug targets. The genome-wide detection ...of G4s in living cells is important for exploring the functional role of G4s but has not yet been achieved due to the lack of a suitable G4 probe. Here we report an artificial 6.7 kDa G4 probe (G4P) protein that binds G4s with high affinity and specificity. We used it to capture G4s in living human, mouse, and chicken cells with the ChIP-Seq technique, yielding genome-wide landscape as well as details on the positions, frequencies, and sequence identities of G4 formation in these cells. Our results indicate that transcription is accompanied by a robust formation of G4s in genes. In human cells, we detected up to >123 000 G4P peaks, of which >1/3 had a fold increase of ≥5 and were present in >60% promoters and ∼70% genes. Being much smaller than a scFv antibody (27 kDa) or even a nanobody (12-15 kDa), we expect that the G4P may find diverse applications in biology, medicine, and molecular devices as a G4 affinity agent.
Angiogenesis plays an important role in the development of rheumatoid arthritis (RA), which increases the supply of nutrients, cytokines, and inflammatory cells to the synovial membrane. Genistein ...(GEN), a soy-derived isoflavone, has been validated that can effectively inhibit the angiogenesis of several tumours. We thus carried out a study in vitro to investigate the effect of GEN in vascular endothelial growth factor (VEGF) expression and angiogenesis induced by the inflammatory environment of RA.
MH7A cells were used to verify whether GEN can inhibit the expression of VEGF in MH7A cells under inflammatory conditions and demonstrate the mechanism. EA.hy926 cells were used to verify whether GEN can inhibit the migration and tube formation of vascular endothelial cells in inflammatory environment.
GEN dose-dependently inhibited the expression and secretion of interleukin (IL)-6 and VEGF, as well as the nucleus translocation of Signal transducer and activator of transcription 3 (STAT3) in MH7A. Furthermore, GEN inhibited IL-6–induced vascular endothelial cell migration and tube formation in vitro.
GEN inhibits IL-6–induced VEGF expression and angiogenesis partially through the Janus kinase 2 (JAK2)/STAT3 pathway in RA, which has provided a novel insight into the antiangiogenic activity of GEN in RA.
Our study provides scientific guidance for the clinical translational research of GEN in the RA treatment.
In this paper, non-orthogonal multiple access (NOMA) is investigated as a viable solution to address spectrum scarcity in unmanned aerial vehicle (UAV) communications. Specifically, the performance ...analysis of a NOMA-aided UAV communication system (UCS) with dual-diversity receivers on UAVs is conducted over bivariate Rician shadowed fading channels. Using newly obtained closed-form expressions for the joint probability density function (PDF) and joint cumulative distribution function (CDF), the outage probability and finite signal-to-noise ratio (SNR) diversity gain of NOMA-aided UCS are investigated within a stochastic geometry framework. A comprehensive analysis reveals that NOMA-aided UCSs can support more UAVs on the same spectrum than OMA-based systems, with similar outage probability. It is also shown that the cross correlation affects the diversity gain of NOMA-aided and OMA-based UCSs only at low SNR regimes. Therefore, NOMA-aided UCSs can be an attractive alternative over OMA-based UCSs in future wireless systems.
Feature selection is a crucial step in the development of a system for identifying emotions in speech. Recently, the interaction between features generated from the same audio source was rarely ...considered, which may produce redundant features and increase the computational costs. To solve this problem, feature selection method based on correlation analysis and Fisher is proposed, which can remove the redundant features that have close correlations with each other. To improve the recognition performance of the feature subset after proposal feature selection further, an emotion recognition method based on extreme learning machine (ELM) decision tree is proposed according to the confusion degree among different basic emotions. A framework of speech emotion recognition is proposed and the classification experiments based on proposed classification method by using Chinese speech database from institute of automation of Chinese academy of sciences (CASIA) are performed. And the experimental results show that the proposal achieved 89.6% recognition rate on average. By proposal, it would be fast and efficient to discriminate emotional states of different speakers from speech, and it would make it possible to realize the interaction between speaker-independent and computer/robot in the future.
An organic Na‐ion battery is reported with a polyanionic 9,10‐anthraquinone‐2,6‐disulfonate (Na2AQ26DS, 130 mAh g−1) cathode and the Na‐intercalated state (Na4TP) of sodium terephthalate (Na2TP, 255 ...mAh g−1) as the anode. The resulting full cells deliver the maximum discharge capacity of 131 mAh g−1cathode in 0.5–3.2 V, simultaneously maintaining the average value of ≈62 mAh g−1cathode during 1200 cycles (0.5 A g−1, ≈4 C). These results are among the best performing organic sodium‐ion full cells reported to date.
Go Organic! A long‐lifespan small‐molecule organic sodium‐ion battery is described. The battery is constructed using a 9,10‐anthraquinone‐2,6‐disulfonate (Na2AQ26DS) cathode and sodium terephthalate (Na2TP) anode, and delivers a maximum discharge capacity of 131 mAh g−1cathode in 0.5–3.2 V, maintaining an average value of approximately 62 mAh g−1cathode over 1200 cycles (0.5 A g−1, ≈4 C).
Abstract The radio galaxy PKS 1007+142 is classified as a compact steep-spectrum source (CSS) and belongs to the class of young active galactic nuclei (AGNs). In this paper, we investigate the γ -ray ...emission from this CSS by conducting a comprehensive analysis of the 15 yr Fermi Large Area Telescope (Fermi-LAT) observation data. The Fermi-LAT latest Source Catalog, 4FGL-DR4, includes an unassociated γ -ray source, 4FGL J1010.0+1416, located at 0.°24 away from the radio position of PKS 1007+142. Using the 15 yr Fermi-LAT observation data, we reestimate the best-fit position of the γ -ray source and find that PKS 1007+142 is in close proximity to the γ -ray source and falls within its 68% error circle. Therefore, we conclude that PKS 1007+142 is the most plausible counterpart to the unassociated LAT source with detection test statistics ∼ 43.4 (∼6.6 σ ). PKS 1007+142 exhibits a steep power-law spectrum in the 0.1–300 GeV band, with a photon spectral index (Γ γ ) of 2.86 ± 0.17. The average flux in the considered time interval is (2.14 ± 0.34) × 10 −12 erg cm −2 s −1 . Comparing PKS 1007+142 with other γ -ray emitting AGNs in both the L γ –Γ γ and L γ – L 1.4 GHz planes, it shows a softer γ -ray spectrum and lower luminosity compared to other γ -ray emitting CSSs. Furthermore, the possible origins of γ -ray in PKS 1007+142 are also discussed.
A deep neural network of multiple nonlinear layers forms a large function space, which can easily lead to overfitting when it encounters small-sample data. To mitigate overfitting in small-sample ...classification, learning more discriminative features from small-sample data is becoming a new trend. To this end, this paper aims to find a subspace of neural networks that can facilitate a large decision margin. Specifically, we propose the Orthogonal Softmax Layer (OSL), which makes the weight vectors in the classification layer remain orthogonal during both the training and test processes. The Rademacher complexity of a network using the OSL is only <inline-formula> <tex-math notation="LaTeX">\frac {1}{K} </tex-math></inline-formula>, where <inline-formula> <tex-math notation="LaTeX">K </tex-math></inline-formula> is the number of classes, of that of a network using the fully connected classification layer, leading to a tighter generalization error bound. Experimental results demonstrate that the proposed OSL has better performance than the methods used for comparison on four small-sample benchmark datasets, as well as its applicability to large-sample datasets. Codes are available at: https://github.com/dongliangchang/OSLNet .
Due to lack of data, overfitting ubiquitously exists in real-world applications of deep neural networks (DNNs). We propose advanced dropout, a model-free methodology, to mitigate overfitting and ...improve the performance of DNNs. The advanced dropout technique applies a model-free and easily implemented distribution with parametric prior, and adaptively adjusts dropout rate. Specifically, the distribution parameters are optimized by stochastic gradient variational Bayes in order to carry out an end-to-end training. We evaluate the effectiveness of the advanced dropout against nine dropout techniques on seven computer vision datasets (five small-scale datasets and two large-scale datasets) with various base models. The advanced dropout outperforms all the referred techniques on all the datasets. We further compare the effectiveness ratios and find that advanced dropout achieves the highest one on most cases. Next, we conduct a set of analysis of dropout rate characteristics, including convergence of the adaptive dropout rate, the learned distributions of dropout masks, and a comparison with dropout rate generation without an explicit distribution. In addition, the ability of overfitting prevention is evaluated and confirmed. Finally, we extend the application of the advanced dropout to uncertainty inference, network pruning, text classification, and regression. The proposed advanced dropout is also superior to the corresponding referred methods. Codes are available at https://github.com/PRIS-CV/AdvancedDropout .
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