Effects of secukinumab combined with tretinoin on metabolism, liver enzymes, and inflammatory factors in patients with moderate to severe psoriasis vulgaris.

Introduction: Psoriasis is a T cell-mediated polygenic chronic inflammatory disease. Interleukin (IL)-17A plays a major role in psoriasis pathogenesis. Secukinumab is a high-affinity human monoclonal antibody against IL-17A. Aim: This article explored efficacy and safety of secukinumab plus tretinoin in moderate to severe psoriasis (MSP) vulgaris, and assessed metabolism, liver function, and inflammation. Material and methods: A total of 135 patients diagnosed with moderate or severe psoriasis vulgaris were enrolled and randomized into three groups at a 1 : 1 : 1 ratio, receiving treatment with rretinoin, secukinumab, or combination therapy for a duration of 16 weeks. Psoriasis area and severity index (PASI) scores, serum T lymphocyte subsets, glucose, lipid, and uric acid (UA) metabolism, liver enzymes, and inflammatory factors (IFs) were measured. Results: Following the therapy, subjects had decreased PASI scores, increased serum CD3+, CD4+, and CD4+/CD8+, decreased serum CD8+, and decreased serum UA and IL-2, IL-6, IL-23, interferon-γ (IFN-γ), and tumor necrosis factor (TNF)-α (p < 0.05). Total cholesterol, triglycerides, low-density lipoprotein, high-density lipoprotein, apolipoproteins A1, B, fasting blood glucose, alanine transaminase, aspartate transaminase, and alkaline phosphatase had no obvious differences among the subjects (p > 0.05). As against the Tretinoin and the Secukinumab groups, the PASI score was visiblysmaller, the changes in serum T lymphocyte subsets were more obvious, and serum UA and IFs were lower in the Combination group following the therapy (p < 0.05). Conclusions: Secukinumab combined with tretinoin is more effective in MSP vulgaris, which can visibly reduce inflammatory response without affecting glucose and lipid metabolism and liver function.

Enhanced biomass and thermotolerance of Arabidopsis by SiERECTA isolated from Setaria italica L.

Foxtail millet is commonly used as a food and forage grass. ERECTA (ER) is a receptor-like kinase that can improve plant biomass and stress resistance. The sorghum SbER10_X1 gene was used as a probe to identify ER family genes on the Setaria italica genomes (SiERs), and determine the characteristics of the SiERs family. Herein, the structural features, expression patterns, and thermotolerance of SiERs function were identified by bioinformatics analysis, real-time PCR and transgenesis estimation. Results showed that SiERs had four members: two members were located on chromosome 1 with a total of six copies (SiER1_X1, SiER1_X2, SiER1_X3, SiER1_X4, SiER1_X5, and SiER1_X6), and two were on chromosome 4, namely, SiER4 (SiER4_X1 and SiER4_X2) and SiERL1. Among them, SiER1_X4 and SiER4_X1 were expressed highest in above-ground organs of foxtail millet, and actively responded to treatments with abscisic acid, brassinolide, gibberellin, and indole acetic acid. After overexpression of SiER1_X4 and SiER4_X1 in Arabidopsis, the plant height and biomass of the transgenic Arabidopsis significantly increased. Following high-temperature treatment, transgenic seedlings survived better compared to wild type. Transgenic lines showed higher SOD and POD activities, and expression level of AtHSF1 and AtBl1 genes significantly increased. These results indicated that SiER1_X4 and SiER4_X1 played important regulatory roles in plant growth and thermotolerance. The two genes provide potential targets for conventional breeding or biotechnological intervention to improve the biomass of forage grass and thermotolerance of field crops.

Spring Back Behavior of Large Multi-Feature Thin-Walled Part in Rigid-Flexible Sequential Loading Forming Process.

The spring back behavior of large complex multi-feature parts in the rigid-flexible sequential forming process has certain special characteristics. The hydraulic pressure loading locus has a significant influence on the spring back of small features of the part, and the applicability of the spring back prediction model to the process needs further research. Therefore, this paper takes the large aluminum alloy inner panel of an automobile as the research object, and the spring back model and the influence laws of the hydraulic pressure loading locus are revealed by combining the theoretical analysis and numerical simulation with the process tests. Meanwhile, based on the theoretical prediction and experimental results, the spring back compensation of the complex inner panel is carried out. Results show that the hardening model has a greater impact on the accuracy of spring back prediction than the yield criterion does, and the prediction accuracy of Barlat'89 + Yoshida-Uemori mixed hardening model is the highest. Finally, the optimized loading locus of hydraulic pressure is obtained, and the accuracy results of the compensated parts verify the accuracy of the analysis model.

LSTM networks based on attention ordered neurons for gear remaining life prediction.

Gear is a commonly-used rotating part in industry, it is of great significance to predict its failure in advance, which is helpful to maintain the health of the whole machine. Firstly, the isometric mapping algorithm is applied to construct the health indicator (HI) based on the statistical characteristics of gear. Then a novel variant of long-short-term memory neural network with attention-guided ordered neurons (LSTM-AON) is constructed to achieve the accurate prediction of gear remaining useful life (RUL). LSTM-AON divides the hierarchy of health characteristic information via attention ordered neurons, so that it can use the sequence information of neurons to improve the predictive performance, which improves the long-term prediction ability and robustness. The experiments show the superiority of the new gear RUL prediction methodology based on LSTM-AON compared to the current prediction methods.

Transcriptome profiling and digital gene expression analysis of sweet potato for the identification of putative genes involved in the defense response against Fusarium oxysporum f. sp. batatas.

Sweet potato production is constrained by Fusarium wilt, which is caused by Fusarium oxysporum f. sp. batatas (Fob). The identification of genes related to disease resistance and the underlying mechanisms will contribute to improving disease resistance via sweet potato breeding programs. In the present study, we performed de novo transcriptome assembly and digital gene expression (DGE) profiling of sweet potato challenged with Fob using Illumina HiSeq technology. In total, 89,944,188 clean reads were generated from 12 samples and assembled into 101,988 unigenes with an average length of 666 bp; of these unigenes, 62,605 (61.38%) were functionally annotated in the NCBI non-redundant protein database by BLASTX with a cutoff E-value of 10-5. Clusters of Orthologous Groups (COG), Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) annotations were examined to explore the unigenes' functions. We constructed four DGE libraries for the sweet potato cultivars JinShan57 (JS57, highly resistant) and XinZhongHua (XZH, highly susceptible), which were challenged with pathogenic Fob. Genes that were differentially expressed in the four libraries were identified by comparing the transcriptomes. Various genes that were differentially expressed during defense, including chitin elicitor receptor kinase 1 (CERK), mitogen-activated protein kinase (MAPK), WRKY, NAC, MYB, and ethylene-responsive transcription factor (ERF), as well as resistance genes, pathogenesis-related genes, and genes involved in salicylic acid (SA) and jasmonic acid (JA) signaling pathways, were identified. These data represent a sequence resource for genetic and genomic studies of sweet potato that will enhance the understanding of the mechanism of disease resistance.