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It is essential to use deep learning algorithms for big data to implement a new generation of artificial intelligence. The effective use of deep learning methods depends largely on the number of samples. This work proposes a method combining the Wasserstein generative adversarial network (WGAN) with the specific deep learning model (ResNeXt) network to achieve data enhancement and classification of the Fourier transform infrared (FT-IR) spectra of strawberries. In this method, the data are first preprocessed using convolution, the FT-IR spectral data are augmented by WGAN, and the data are finally classified using the ResNeXt network. For the experimental investigation, 10 types of dimensionalityreduction algorithms combined with nine types of classification algorithms were used for comparing and arranging the 90 groups. The results obtained from these experiments prove that our method of using a combination of WGAN and ResNeXt is highly suitable for the classification of the IR spectra of strawberries and provides a data augmentation idea as a foundation for future research., Fourier transform infrared (FTIR) spectroscopy can be used to obtain biochemical fingerprints quickly and nondestructively, thereby providing a reliable molecular structure as well as composition information (1). These 'spectral fingerprints' [...]

Background: To date, most existing models for predicting neuromyelitis optica spectrum disorder (NMOSD) are based primarily on clinical characteristics. Blood‐based NMOSD severity and prognostic predictive immune‐ and inflammation‐related biomarkers are needed. We aimed to investigate the associations between plasma inflammatory biomarkers and relapse and attack severity in NMOSD. Methods: This two‐step, single‐center prospective cohort study included discovery and validation cohorts. We quantified 92 plasma inflammatory proteins by using Olink's proximity extension assay and identified differentially expressed proteins in the relapse group (relapse within 1 year of follow‐up) and severe attack group. To define a new molecular prognostic model, we calculated the risk score of each patient based on the key protein signatures and validated the results in the validation cohort. Results: The relapse prediction model, including FGF‐23, DNER, GDNF, and SLAMF1, predicted the 1‐year relapse risk. The severe attack prediction model, including PD‐L1 and MCP‐2, predicted the severe clinical attack risk. Both the relapse and severe attack prediction models demonstrated good discriminative ability and high accuracy in the validation cohort. Conclusions: Our discovered biomarker signature and prediction models may complement current clinical risk stratification approaches. These inflammatory biomarkers could contribute to the discovery of therapeutic interventions and prevent NMOSD progression. [ABSTRACT FROM AUTHOR]

Aims: Colony stimulating factor 1 receptor (CSF1R)‐related leukoencephalopathy is a rapidly progressing neurodegenerative disease caused by CSF1R gene mutations. This study aimed to identify and investigate the effect of a novel intronic mutation (c.1754‐3C>G) of CSF1R on splicing. Methods: A novel intronic mutation was identified using whole‐exome sequencing. To investigate the impact of this mutation, we employed various bioinformatics tools to analyze the transcription of the CSF1R gene and the three‐dimensional structure of its encoded protein. Furthermore, reverse transcription polymerase chain reaction (RT‐PCR) was performed to validate the findings. Results: A novel mutation (c.1754‐3C>G) in CSF1R was identified, which results in exon 13 skipping due to the disruption of the 3′ splice site consensus sequence NYAG/G. This exon skipping event was further validated in the peripheral blood of the mutation carrier through RT‐PCR and Sanger sequencing. Protein structure prediction indicated a disruption in the tyrosine kinase domain, with the truncated protein showing significant structural alterations. Conclusions: Our findings underscore the importance of intronic mis‐splicing mutations in the diagnosis and management of CSF1R‐related leukoencephalopathy. [ABSTRACT FROM AUTHOR]

Maternal histone methyltransferase is critical for epigenetic regulation and development of mammalian embryos by regulating histone and DNA modifications. Here, we reported a novel mechanism by revealing the critical effects of maternal Ezh1/2 deletion on mitochondria in MII oocytes and early embryos in mice. We found that Ezh1/2 knockout in mouse MII oocytes impaired the structure of mitochondria and decreased its number, but membrane potential and respiratory function of mitochondrion were increased. The similar effects of Ezh1/2 deletion have been observed in 2‐cell and morula embryos, indicating that the effects of maternal Ezh1/2 deficiency on mitochondrion extend to early embryos. However, the loss of maternal Ezh1/2 resulted in a severe defect of morula: the number, membrane potential, respiratory function, and ATP production of mitochondrion dropped significantly. Content of reactive oxygen species was raised in both MII oocytes and early embryos, suggesting maternal Ezh1/2 knockout induced oxidative stress. In addition, maternal Ezh1/2 ablation interfered the autophagy in morula and blastocyst embryos. Finally, maternal Ezh1/2 deletion led to cell apoptosis in blastocyst embryos in mice. By analyzing the gene expression profile, we revealed that maternal Ezh1/2 knockout affected the expression of mitochondrial related genes in MII oocytes and early embryos. The chromatin immunoprecipitation‐polymerase chain reaction assay demonstrated that Ezh1/2 directly regulated the expression of genes Fxyd6, Adpgk, Aurkb, Zfp521, Ehd3, Sgms2, Pygl, Slc1a1, and Chst12 by H3K27me3 modification. In conclusion, our study revealed the critical effect of maternal Ezh1/2 on the structure and function of mitochondria in oocytes and early embryos, and suggested a novel mechanism underlying maternal epigenetic regulation on early embryonic development through the modulation of mitochondrial status. [ABSTRACT FROM AUTHOR]

The males ability to reproduce is completely dependent on Sertoli cells. However, the mechanisms governing the functional integrity of Sertoli cells have remained largely unexplored. Here, we demonstrate that deletion of Shp2 in Sertoli cells results in infertility in mice. In Shp2 knockout mice (SCSKO), a normal population of Sertoli cells was observed, but the blood-testis barrier (BTB) was not formed. Shp2 ablation initiated the untimely and excessive differentiation of spermatogonial stem cells (SSCs) by disturbing the expression of paracrine factors. As a consequence, the process of spermatogenesis was disrupted, and the germ cells were depleted. Furthermore, Shp2 deletion impaired the cell junctions of the primary Sertoli cells and failed to support the clonal formation of SSCs co-cultured with SCSKO Sertoli cells. As expected, Shp2 restoration largely restores the cell junctions of the primary Sertoli cells and the clonal formation of SSCs. To identify the underlying mechanism, we further demonstrated that the absence of Shp2 suppressed Erk phosphorylation, and thus, the expression of follicle-stimulating hormone (FSH)- and testosterone-induced target genes. These results collectively suggest that Shp2 is a critical signaling protein that is required to maintain Sertoli cell function and could serve as a novel target for male infertility therapies.

Zn‐ion capacitors (ZICs) take advantage of batteries and supercapacitors in delivering high energy and power densities for energy storage by using porous carbons due to their low cost, lightweight, high conductivity, and good stability. However, it remains a grand challenge to regulate the mesoporous structures of carbons, including pore sizes and surface functional groups, which are essential for ion transport and electrochemical reactions of ZICs. Herein, a bi‐directional electrolysis strategy is developed to directly reduce CO2 to oxygen‐rich mesoporous carbons (OMCs) with adjustable pore sizes and oxygen‐bearing functional groups, which are preferred for ZICs as theoretically proved by density functional theory (DFT). The designed OMCs exhibit a remarkable energy density of 216.6 Wh kg−1 and performance retention of 90% after 15000 cycles. When assembled in the flexible ZICs, the OMCs demonstrate a high capacitance of 329.5 mAh g−1. This work presents a novel strategy for synthesizing OMCs through a decarbonization process and reveals the crucial role of microstructure and surface functional groups in promoting the performance of ZICs. [ABSTRACT FROM AUTHOR]

The use of an argon–water medium rather than air–water medium is proposed to increase the material removal rate (MRR) and decrease surface oxide production for short electric arc machining. To provide a more stable discharge state during high-temperature processing, this approach uses argon to reduce the production of highly resistant refractory materials (e.g. titanium oxide). For short-arc machining of Ti6Al4V titanium alloy, the effects of the voltage, milling depth, electrode speed and gas flow rate on the MRR, relative electrode loss rate and surface roughness were compared for air–water and argon–water mixtures. It was discovered that the milling depth and voltage had the greatest impact on the MRR, voltage and electrode rotational speed had the greatest impact on the relative tool electrode wear rate (REWR), and voltage had the greatest impact on the surface roughness. In contrast to the air–water mixture, the MRR with the argon–water working medium was as high as 9391 mm3/min, with a 13% improvement in MRR, as well as a smooth and flat surface of the machined workpiece. Nevertheless, the REWR increased to 2.46% and the surface roughness was at least 432 μm with the argon–water medium, increasing by 59 μm compared with the air–water medium. Moreover, the addition of argon reduced the types of surface compound on the workpiece and decreased the residual stress defects, including the recast layer, microcracks and holes. [ABSTRACT FROM AUTHOR]