1,038 research outputs found
Current concepts on oxidative/carbonyl stress, inflammation and epigenetics in pathogenesis of chronic obstructive pulmonary disease
No full textChronic obstructive pulmonary disease (COPD) is a global health problem. The current therapies for COPD are poorly effective and the mainstays of pharmacotherapy are bronchodilators. A better understanding of the pathobiology of COPD is critical for the development of novel therapies. In the present review, we have discussed the roles of oxidative/aldehyde stress, inflammation/immunity, and chromatin remodeling in the pathogenesis of COPD. An imbalance of oxidants/antioxidants caused by cigarette smoke and other pollutants/biomass fuels plays an important role in the pathogenesis of COPD by regulating redox-sensitive transcription factors (e.g., NF-κB), autophagy and unfolded protein response leading to chronic lung inflammatory response. Cigarette smoke also activates canonical/alternative NF-κB pathways and their upstream kinases leading to sustained inflammatory response in lungs. Recently, epigenetic regulation has been shown to be critical for the development of COPD because the expression/activity of enzymes that regulate these epigenetic modifications have been reported to be abnormal in airways of COPD patients. Hence, the significant advances made in understanding the pathophysiology of COPD as described herein will identify novel therapeutic targets for intervention in COPD
The Rahman Polynomials Are Bispectral
No full textIn a very recent paper, M. Rahman introduced a remarkable family of polynomials in two variables as the eigenfunctions of the transition matrix for a nontrivial Markov chain due to M. Hoare and M. Rahman. I indicate here that these polynomials are bispectral. This should be just one of the many remarkable properties enjoyed by these polynomials. For several challenges, including finding a general proof of some of the facts displayed here the reader should look at the last section of this paper.This paper is a contribution to the Vadim Kuznetsov Memorial Issue ‘Integrable Systems and Related Topics’. I am very thankful to a couple of referees who read the paper with great care and pointed out typos as well as ways to improve the presentation. The author was supported in part by NSF Grant # 0603901
The Rahman Polynomials Are Bispectral
No full textIn a very recent paper, M. Rahman introduced a remarkable family of polynomials in two variables as the eigenfunctions of the transition matrix for a nontrivial Markov chain due to M. Hoare and M. Rahman. I indicate here that these polynomials are bispectral. This should be just one of the many remarkable properties enjoyed by these polynomials. For several challenges, including finding a general proof of some of the facts displayed here the reader should look at the last section of this paper.This paper is a contribution to the Vadim Kuznetsov Memorial Issue ‘Integrable Systems and Related Topics’. I am very thankful to a couple of referees who read the paper with great care and pointed out typos as well as ways to improve the presentation. The author was supported in part by NSF Grant # 0603901
The Rahman Polynomials Are Bispectral
No full textIn a very recent paper, M. Rahman introduced a remarkable family of polynomials in two variables as the eigenfunctions of the transition matrix for a nontrivial Markov chain due to M. Hoare and M. Rahman. I indicate here that these polynomials are bispectral. This should be just one of the many remarkable properties enjoyed by these polynomials. For several challenges, including finding a general proof of some of the facts displayed here the reader should look at the last section of this paper.This paper is a contribution to the Vadim Kuznetsov Memorial Issue ‘Integrable Systems and Related Topics’. I am very thankful to a couple of referees who read the paper with great care and pointed out typos as well as ways to improve the presentation. The author was supported in part by NSF Grant # 0603901
Environmental toxicity, redox signaling and lung inflammation:the role of glutathione
No full textGlutathione (gamma-glutamyl-cysteinyl-glycine, GSH) is the most abundant intracellular antioxidant thiol and is central to redox defense during oxidative stress. GSH metabolism is tightly regulated and has been implicated in redox signaling and also in protection against environmental oxidant-mediated injury. Changes in the ratio of the reduced and disulfide form (GSH/GSSG) can affect signaling pathways that participate in a broad array of physiological responses from cell proliferation, autophagy and apoptosis to gene expression that involve H(2)O(2) as a second messenger. Oxidative stress due to oxidant/antioxidant imbalance and also due to environmental oxidants is an important component during inflammation and respiratory diseases such as chronic obstructive pulmonary disease, idiopathic pulmonary fibrosis, acute respiratory distress syndrome, and asthma. It is known to activate multiple stress kinase pathways and redox-sensitive transcription factors such as Nrf2, NF-kappaB and AP-1, which differentially regulate the genes for pro-inflammatory cytokines as well as the protective antioxidant genes. Understanding the regulatory mechanisms for the induction of antioxidants, such as GSH, versus pro-inflammatory mediators at sites of oxidant-directed injuries may allow for the development of novel therapies which will allow pharmacological manipulation of GSH synthesis during inflammation and oxidative injury. This article features the current knowledge about the role of GSH in redox signaling, GSH biosynthesis and particularly the regulation of transcription factor Nrf2 by GSH and downstream signaling during oxidative stress and inflammation in various pulmonary diseases. We also discussed the current therapeutic clinical trials using GSH and other thiol compounds, such as N-acetyl-l-cysteine, fudosteine, carbocysteine, erdosteine in environment-induced airways disease
Deep Learning and Data Balancing Approaches in Mining Hospital Surveillance Data
No full textA number of classifier models on hospital surveillance data to classify admitted patients according to their critical conditions with an emphasis to deep learning paradigms, namely convolutional neural network, were used in this research. Three class labels were used to distinguish the criticality of the admitted 25,261 patients. The authors have set forth two distinct approaches to address the unbalance nature of data. They used multilayer perceptron (MLP), convolutional neural network (CNN), and multinomial logistic regression classifications and finally compared the performance of our models with the models developed by Firoze, Hasan and Rahman (2013). After comparison, the authors show that one of the models, including convolutional neural network based on deep learning, surpasses most models in terms of classification performance in contingent with training times and epochs. The trade-off is computational power for which—to achieve optimal accuracy—multiple CUDA cores are necessary. The authors achieved stable improvement of classification for their model using CNN. </jats:p
Reynolds number effect on 3D turbulent offset jet reattaching to a free surface
No full textExperimental study was carried out to investigate the effect of Reynolds number on 3D offset jet reattaching to above free surface. Sharp edged square nozzle was used to produce the jets, and the measurements were performed at the following six different Reynolds numbers: 2300, 3700, 5100, 7900, 10300 and 11900. Detailed velocity measurements were made in the symmetry plane. From the PIV data, the mean velocity and turbulence statistics were obtained to study the effects of Reynolds number on the salient features of the jet flow. Preliminary results on streamwise mean velocity decay along the nozzle centerline, contours of streamwise mean velocity and Reynolds shear stress are presented herein
Dietary polyphenols mediated regulation of oxidative stress and chromatin remodeling in inflammation
No full textAn algorithmic approach to estimate cognitive aesthetics of images relative to ground truth of human psychology through a large user study
No full textThis research introduces a learning model that estimates the cognitive perception of aesthetics. Taking psychology into account, this bridges the gap between human and machine. The goal is to build a machine-learning model that can estimate beauty in images perceived by human eyes. We have summand our research [Firoze, A., Osman, T., Psyche, S. S., & Rahman, R. M. (2018). Scoring photographic rule of thirds in a large MIRFLICKR dataset: A showdown between machine perception and human perception of image aesthetics. Asian Conference on Intelligent Information and Database Systems (pp. 466–475), Springer; Osman, T., Psyche, S. S., Deb, T., Firoze, A., & Rahman, R. M. (2018). Differential color harmony: A robust approach for extracting Harmonic Color features and perceive aesthetics in a large dataset. International Conference on Big Data and Cloud Computing, Springer] together with the idea of humans’ personal preferences and achieved higher than state of the art performances. An extensive user study (374 participants) has been conducted to support claims. Several photographical compositional metrics have been used. Colour gradient, rule of thirds and human subject’s psychology has been picked as features. The consideration of user’s perspective or psychology is one of the key contributions of this research
RETRACTION: Optimization of conditions for the biological treatment of textile dyes using isolated soil bacteria
No full textThe article titled “Optimization of conditions for the biological treatment of textile dyes using isolated soil bacteria” ([version 1; referees: peer review discontinued]. F1000Research 2018, 7:351 https://doi.org/10.12688/f1000research.13757.1) by Shafkat Shamim Rahman and colleagues, has been retracted by F1000Research on grounds of misconduct by the first author. Following publication of the article, the editorial team at F1000Research were notified by Romana Siddique, from BRAC University, that the data presented in this paper significantly overlaps with the data in her recently published article : Siddique and Alif; ARRB, 22(5): 1-12, 2018; Article no.ARRB.38637; https://doi.org/10.9734/ARRB/2018/38637. In response to our queries to the authors, the second and last author listed on this article, Fahim Ahmed Alif and M. Mahboob Hossain, have stated that they were not aware of the submission of this article to F1000Research, and did not agree to be authors. We have evidence which confirms their statement. After further investigation by the F1000Research team, and a separate investigation by BRAC University, it has become clear that Shafkat Shamim Rahman was not involved with the research presented in this paper, and that the decision to submit and publish the article was taken independently by him, and not his listed co-authors. BRAC University has confirmed that Shafkat Shamim Rahman is not currently based at their institution.</ns4:p
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