80 research outputs found

    DosR’s multifaceted role on Mycobacterium bovis BCG revealed through multi-omics

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    Mycobacterium tuberculosis (Mtb) is an intracellular bacterium that causes a highly contagious and potentially lethal tuberculosis (TB) in humans. It can maintain a dormant TB infection within the host. DosR (dormancy survival regulator) (Rv3133c) has been recognized as one of the key transcriptional proteins regulating bacterial dormancy and participating in various metabolic processes. In this study, we extensively investigate the still not well-comprehended role and mechanism of DosR in Mycobacterium bovis (M. bovis) Bacillus Calmette-Guérin (BCG) through a combined omics analysis. Our study finds that deleting DosR significantly affects the transcriptional levels of 104 genes and 179 proteins. Targeted metabolomics data for amino acids indicate that DosR knockout significantly upregulates L-Aspartic acid and serine synthesis, while downregulating seven other amino acids, including L-histidine and lysine. This suggests that DosR regulates amino acid synthesis and metabolism. Taken together, these findings provide molecular and metabolic bases for DosR effects, suggesting that DosR may be a novel regulatory target

    Dysregulations of metabolites and gut microbes and their associations in rats with noise induced hearing loss

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    BackgroundNoise exposure could lead to hearing loss and disorders of various organs. Recent studies have reported the close relations of environmental noise exposure to the metabolomics dysregulations and gut microbiota disturbance in the exposers. However, the associations between gut microbial homeostasis and the body metabolism during noise-induced hearing loss (NIHL) were unclear. To get a full understanding of their synergy in noise-associated diseases, it is essential to uncover their impacts and associations under exposure conditions.MethodsWith ten male rats with background noise exposure (≤ 40 dB) as controls (Ctr group), 20 age- and weight-matched male rats were exposed to 95 dB Sound pressure level (SPL) (LN group, n = 10) or 105 dB SPL noise (HN group, n = 10) for 30 days with 4 h/d. The auditory brainstem response (ABR) of the rats and their serum biochemical parameters were detected to investigate their hearing status and the potential effects of noise exposure on other organs. Metabolomics (UPLC/Q-TOF-MS) and microbiome (16S rDNA gene sequencing) analyses were performed on samples from the rats. Multivariate analyses and functional enrichments were applied to identify the dysregulated metabolites and gut microbes as well as their associated pathways. Pearson correlation analysis was performed to investigate the associations of the dysregulations of microbiota and the metabolites.ResultsNIHL rat models were constructed. Many biochemical parameters were altered by noise exposure. The gut microbiota constitution and serum metabolic profiles of the noise-exposed rats were also dysregulated. Through metabolomics analysis, 34 and 36 differential metabolites as well as their associated pathways were identified in LN and HN groups, respectively. Comparing with the control rats, six and 14 florae were shown to be significantly dysregulated in the LN group and HN group, respectively. Further association analysis showed significant correlations between differential metabolites and differential microbiota.ConclusionThere were cochlea injuries and abnormalities of biochemical parameters in the rats with NIHL. Noise exposure could also disrupt the metabolic profiles and the homeostatic balance of gut microbes of the host as well as their correlations. The dysregulated metabolites and microbiota might provide new clues for prevention of noise-related disorders

    Strain mediated phase crossover in Ruddlesden Popper nickelates

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    Recent progress on the signatures of pressure-induced high temperature superconductivity in Ruddlesden Popper (RP) nickelates (Lan+1NinO3n+1) has attracted growing interest in both theoretical calculations and experimental efforts. The fabrication of high-quality single crystalline RP nickelate thin films is critical for possible reducing the superconducting transition pressure and advancing applications in microelectronics in the future. In this study, we report the observations of an active phase transition in RP nickelate films induced by misfit strain. We found that RP nickelate films favor the perovskite structure (n = infinite) under tensile strains, while compressive strains stabilize the La3Ni2O7 (n = 2) phase. The selection of distinct phases is governed by the strain dependent formation energy and electronic configuration. In compressively strained La3Ni2O7, we experimentally determined splitting energy is ~0.2 eV and electrons prefer to occupy in-plane orbitals. First principles calculations unveil a robust coupling between strain effects and the valence state of Ni ions in RP nickelates, suggesting a dual driving force for the inevitable phase co-existence transition in RP nickelates. Our work underscores the sensitivity of RP nickelate formation to epitaxial strain, presenting a significant challenge in fabricating pure-phase RP nickelate films. Therefore, special attention to stacking defects and grain boundaries between different RP phases is essential when discussing the pressure-induced superconductivity in RP nickelates.Comment: 29 pages, 5 figures, one supplementary material

    Tuberous Sclerosis Complex With Multiple Organ Tumors: Case Report and Literature Review

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    Pancreatic neuroendocrine neoplasms (PNEN) are tumors that originate from neuroendocrine cells. Only about 1% patients are related to mutation of tuberous sclerosis complex gene. Here, we reported a rare case with involvement of multiple organs and space-occupying lesions. Initially, the patient was thought to have metastasis of a pancreatic tumor. However, the patient was diagnosed as pancreatic neuroendocrine tumors, liver perivascular epithelioid tumors, splenic hamartoma, and renal angiomyolipoma by pathological examination after surgery. We performed genetic mutation detection to identify that tuberous sclerosis complex 2 gene presented with a heterozygous variant. Tuberous sclerosis often presents with widespread tumors, but it is less common to present with pancreatic neuroendocrine tumors and liver perivascular tumors as highlighted in the case. So we analyzed the relationship between TSC gene mutations and related tumors. And we also reviewed the current molecular mechanisms and treatments for tuberous sclerosis complex

    Flame Image Segmentation Based on the Bee Colony Algorithm with Characteristics of Levy Flights

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    The real-time processing of the image segmentation method with accuracy is very important in the application of the flame image detection system. This paper considers a novel method for flame image segmentation. It is the bee colony algorithm with characteristics enhancement of Levy flights against the problems of the algorithm during segmentation, including long calculation time and poor stability. By introducing the idea of Levy flights, this method designs a new local search strategy. By setting the current optimal value and based on the collaboration between the populations, it reinforces the overall convergence speed. By adopting the new fitness evaluation method and combining it with the two-dimensional entropy multithreshold segmentation principle, this paper develops a threshold segmentation test of the flame image. Test results show that this method has some advantages in terms of accuracy of threshold selection and calculation time. The robustness of the algorithm meets the actual demands in the engineering application

    Do Green Energy and Information Technology Influence Greenhouse Gas Emitting Countries to Attain Sustainable Development?

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    Transitioning from traditional energy sources to green and sustainable energy sources can potentially reduce environmental problems. Many countries are gradually recording increasing greenhouse gas (GHG) emissions as they develop their economies. As a result, this study aims to use top GHG-emitting countries in its analysis to establish the role green energy and information technology play in reducing their pollution levels. Data from 11 GHG-emitting countries from 1990–2020 were utilized. The Fully Modified Ordinary Least squares (FMOLS), Dynamic ordinary least squares (DOLS), and Granger causality are used for the analysis. The empirical results revealed that an increase in non-renewable energy usage of 1% increases GHG gas emissions by 0.6960% (FMOLS) and 0.6119% (DOLS). On the impact of renewable energy, a 1% increase reduces GHG emissions by 0.1145% (FMOLS) and 0.1957% (DOLS). Also, a 1% increase in information technology increases GHG emissions by 0.0459% (FMOLS) and 0.0429% (DOLS) under the specifications of FMOLS and DOLS. The directional causalities are established in the study as well. In light of this, using “abundant” renewable energy sources is the gateway to reducing GHG emissions alongside their tremendous economic growth and I.T. development. Other policy implications are outlined for future research and policymakers
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