Sharmamcgraw1953

Helical curling and spiral structure are very common in nature, which inspire researchers to create various forms of helical configurations and actuators. The helically deformable actuators perform asymmetric deformations and show different chirality, which means that they can be left handed or right handed. However, the mechanism of helical curling and especially how the key factors influence the chirality of the actuator have not been systematically explained and well understood. In this study, we focus on the typical double-layer soft actuator composed of an active (expansion) layer and a passive (supporting) layer and investigate the effect of key factors (expansion coefficient, Young's modulus, relative thickness) on the chirality of the helical actuation or morphing by comprehensive finite element analyses. SB505124 It was found that (i) the anisotropic expansion of the active layer or (ii) the anisotropic Young's modulus of the active or the passive layer is indispensable for helical curling. In Case (i), the actuator curls along the direction of greater expansion of the active layer. In Case (ii), the actuator curls along the direction of closer moduli match of the active and passive layers, and their relative thickness also affects the helical morphing of the actuator. In practice, the above two factors may cooperate or compete with each other, and the dominant one determines the chirality. This work gives the general rules for helical morphing forms and can provide guidance for the design and preparation of spiral actuators and soft robots in the future.Genome regulation, temporal and spatial variations in cell function, continues to puzzle and interest life scientists who aim to unravel the molecular basis of human health and disease, not to mention plant biology and ecosystem diversity. Despite important advances in epigenomics and protein post-translational modifications over the past decade, there is a need for new conceptual lenses to understand biological mechanisms that can help unravel the fundamental regulatory questions in genomes and the cell. To these ends, lys crotonylation (Kcr) is a reversible protein modification catalyzed by protein crotonyl transferases and decrotonylases. First identified on histones, Kcr regulates cellular processes at the chromatin level. Research thus far has revealed that Kcr marks promoter sites of active genes and potential enhancers. Eventually, Kcr on a number of nonhistone proteins was reported. The abundance of Kcr on ribosomal and myofilament proteins indicates its functional roles in protein synthesis and muscle contraction. Kcr has also been associated with pluripotency, spermiogenesis, and DNA repair. In plants, large-scale mass spectrometry-based experiments validated the roles of Kcr in photosynthesis. In this expert review, we present the latest thinking and findings on lys crotonylation with an eye to regulation of cell biology. We discuss the enrichment techniques, putative biological functions, and challenges associated with studying this protein modification with vast biological implications. Finally, we reflect on the future outlook about the broader relevance of Kcr in animals, microbes, and plant species.This study applied two mathematical algorithms, lattice up-stream targeting (LUST) and D-basis, to the identification of prognostic signatures from cancer gene expression data. The LUST algorithm looks for metagenes, which are sets of genes that are either overexpressed or underexpressed in the same patients. Whereas LUST runs unsupervised by clinical data, the D-basis algorithm uses implications and association rules to relate gene expression to clinical outcomes. The D-basis selects a small subset of the metagene (a signature) to predict survival. The two algorithms, LUST and D-basis, were combined and applied to mRNA expression and clinical data from The Cancer Genome Atlas (TCGA) for 203 stage 1 and 2 stomach cancer patients. Two small (four-gene) signatures effectively predict survival in early-stage stomach cancer patients. These signatures could be used as a guide for treatment. The first signature (DU4) consists of genes that are underexpressed on the long-survival/low-risk group FLRT2, KCNB1, MYOC, and TNXB. The second signature consists of genes that are overexpressed on the short-survival/high-risk group ASB5, SFRP1, SMYD1, and TACR2. Another nine-gene signature (REC9) predicts recurrence BNC2, CCDC8, DPYSL3, MOXD1, MXRA8, PRELP, SCARF2, TAGLN, and ZNF423. Each patient is assigned a score that is a linear combination of the expression levels for the genes in the signature. Scores below a selected threshold predict low-risk/long survival, whereas high scores indicate a high risk of short survival. The metagenes associate with TCGA cluster C1. Both our signatures and cluster C1 identify tumors that are genomically silent, and have a low mutation load or mutation count. Furthermore, our signatures identify tumors that are predominantly in the WHO classification of poorly cohesive and the Lauren class of diffuse samples, which have a poor prognosis.Objective To investigate the effects of 12 weeks practice of a structured yoga module on heart rate variability (HRV) and cardiometabolic risks in patients with type 2 diabetes (T2D) receiving similar kind of oral antidiabetic drugs (OAD) with yoga therapy and without yoga therapy, matched for all the known confounders. Design Parallel design interventional (randomized control trial) study. Subjects Eighty treatment-naive males with T2D were randomized into control group (n = 40) and study group (n = 40). Intervention Study group participants received a structured yoga therapy that included asana and pranayama practice for 12 weeks in addition to OAD, whereas control group participants received OAD alone. Outcome measures Before and after intervention, BP parameters, rate pressure product (RPP) as the marker of myocardial stress, total power (TP) of HRV, low-frequency to high-frequency (LF-HF) ratio of HRV, homeostatic model of insulin resistance (HOMA-IR), lipid profile and lipid risk factors, malondialdehyd module improves TP of HRV, sympathovagal balance, and metabolic functions, and reduce cardiovascular (CV) risks in patients with diabetes who received routine antidiabetic medicines along with yoga therapy, compared with the patients with diabetes who received antidiabetic medicines alone. The reduction in cardiometabolic risks in these patients is linked to the improvement in TP of HRV. Future studies should also include a control group with rapid walking or a similar exercise program of equal time to the yoga intervention group to discern whether it is in fact yoga that is leading to these results and not simply increased CV activity. Clinical Trial Registry of India (No. CTRI/2021/06/034074).With the development of modern information and communication technologies, such as the internet of things and big data analytics, businesses and users have become more adaptable to rapid changes. Both consumers and merchants have obtained great convenience. Meanwhile, a huge amount of data is generated. However, many businesses lack the ability to process these data, which contain critical business values. Therefore, this article uses data from the Dianping website to show how to use big data analytics techniques to exploit the valuable information from these raw data. First, descriptive analysis is conducted by using kernel density estimation. Then, multilinear regression analysis, Naive Bayes, and J48 are used to predict the level of restaurants. We found that flavor, environment, and service score are essential factors to the restaurant level. Moreover, J48 performs best among the three models with an accuracy of 88.89%.Psoriasis is a chronic inflammatory skin disease characterized by massive keratinocyte proliferation and immune cell infiltration into the epidermis. However, the specific mechanisms underlying the development of psoriasis remain unclear. Untargeted metabolomics and transcriptomics have been used separately to profile biomarkers and risk genes in the serum of psoriasis patients. However, the integration of metabolomics and transcriptomics to identify dysregulated metabolites and genes in the psoriatic skin is lacking. In this study, we performed an untargeted metabolomics analysis of imiquimod (IMQ)-induced psoriasis-like mice and healthy controls, and found that levels of a total of 4,188 metabolites differed in IMQ-induced psoriasis-like mice compared with those in control mice. Metabolomic data analysis using MetaboAnalyst showed that the metabolic pathways of primary metabolites, such as folate biosynthesis and galactose metabolism, were significantly altered in the skin of mice after treatment with IMQ. Furthermore, IMQ treatment also significantly altered metabolic pathways of secondary metabolites, including histidine metabolism, in mouse skin tissues. The metabolomic results were verified by transcriptomics analysis. RNA-seq results showed that histamine decarboxylase (HDC) mRNA levels were significantly upregulated after IMQ treatment. Targeted inhibition of histamine biosynthesis process using HDC-specific inhibitor, pinocembrin (PINO), significantly alleviated epidermal thickness, downregulated the expression of interleukin (IL)-17A and IL-23, and inhibited the infiltration of immune cells during IMQ-induced psoriasis-like skin inflammation. In conclusion, our study offers a validated and comprehensive understanding of metabolism during the development of psoriasis and demonstrated that PINO could protect against IMQ-induced psoriasis-like skin inflammation.We introduce the collection of papers from the first workshop on the habitability of the venusian cloud layer organized by the Roscosmos/IKI-NASA Joint Science Definition Team (JSDT) for Russia's Venera-D mission and hosted by the Space Research Institute in Moscow, Russia, during October 2-5, 2019. The collection also includes three papers that were developed independently of the workshop but are relevant to venusian cloud habitability.Background The treatment and survival rate of patients with metastatic prostate cancer (MPCa) remain unsatisfactory. Herein, the authors investigated the clinical value and potential mechanisms of cadherin EGF LAG seven-pass G-type receptor 3 (CELSR3) in MPCa to identify novel targets for clinical diagnosis and treatment. Materials and Methods mRNA microarray and RNA-Seq (n = 1246 samples) data were utilized to estimate CELSR3 expression and to assess its differentiation ability in MPCa. Similar analyses were performed with miRNA-221-3p. Immunohistochemistry performed on clinical samples were used to evaluate the protein expression level of CELSR3 in MPCa. Based on CELSR3 differentially coexpressed genes (DCEGs), enrichment analysis was performed to investigate potential mechanisms of CELSR3 in MPCa. Results The pooled standard mean difference (SMD) for CELSR3 was 0.80, demonstrating that CELSR3 expression was higher in MPCa than in localized prostate cancer (LPCa). CELSR3 showed moderate potential to distinguish MPCa from LPCa. CELSR3 protein expression was found to be markedly upregulated in MPCa than in LPCa tissues. The authors screened 894 CELSR3 DCEGs, which were notably enriched in the focal adhesion pathway. miRNA-221-3p showed a significantly negative correlation with CELSR3 in MPCa. Besides, miRNA-221-3p expression was downregulated in MPCa than in LPCa (SMD = -1.04), and miRNA-221-3p was moderately capable of distinguishing MPCa from LPCa. Conclusions CELSR3 seems to play a pivotal role in MPCa by affecting the focal adhesion pathway and/or being targeted by miRNA-221-3p.