Erratum for PMID 21180585.
Therapeutic advances in gastroenterology
Erratum to 'Possible interactions between dietary fibres and 5-aminosalicyclic acid' by C Henriksen, S Hansen, I Nordgaard-Lassen, J Rikardt Anderson and P Madsen. Therapeutic Advances in Gastroenterology (2010) 3(1) 5-9 [DOI: 10.1177/ 1756283X09347810][This corrects the article on p. 5 in vol. 3.].
Dieckol exerts anticancer activity in human osteosarcoma (MG-63) cells through the inhibition of PI3K/AKT/mTOR signaling pathway.
Saudi journal of biological sciences
BACKGROUND:Osteosarcoma (OS) is the most common malignant bone cancer with more metastasis and increased occurrence in children and teen-agers and being responsible for more number of morbidity and mortality worldwide. OBJECTIVE:The current exploration was planned study the anticancer actions of dieckol against human OS MG-63 cells via PI3K/AKT/mTOR signaling inhibition. METHODOLOGY:The cytotoxicity of dieckol was scrutinized by MTT assay. Effects of dieckol on the ROS accumulation, apoptotic cell death, and MMP level in the MG-63 cells were studied by respective fluorescence staining assays. The levels of proliferative, inflammatory, and apoptotic markers in the dieckol treated MG-63 cells were scrutinized by marker specific kits. The expressions of PI3K, AKT, and mTOR was assayed by RT-PCR. RESULTS:The MTT assay revealed that the dieckol dose dependently prevented MG-63 cells viability and the IC50 was found at 15 µM. Dieckol treatment effectively reduced the MMP level and improved the ROS generation and apoptosis in MG-63 cells. Dieckol also regulated the proliferative (cyclin D1), inflammatory (COX-2, IL-6, TNF-α, and NF-κB), and apoptotic (caspase-3, Bax, Bcl-2) markers in the MG-63 cells. The PI3K/AKT/mTOR signaling in the MG-63 cells were effectively inhibited by the dieckol treatment. CONCLUSION:In conclusion, our findings from this study recommends that the dieckol could be a talented anticancer candidate for the OS management in the future.
Characteristics of systemic lupus erythematosus in a sample of the Egyptian population: a retrospective cohort of 1109 patients from a single center.
El Hadidi K T,Medhat B M,Abdel Baki N M,Abdel Kafy H,Abdelrahaman W,Yousri A Y,Attia D H,Eissa M,El Dessouki D,Elgazzar I,Elgengehy F T,El Ghobashy N,El Hadary H,El Mardenly G,El Naggar H,El Nahas A M,El Refai R M,El Rwiny H Allah,Elsman R M,Galal M,Ghoniem S,Maged L A,Sally S M,Naji H,Saad S,Shaaban M,Sharaf M,Sobhy N,Soliman R M,El Hadidi T S
Introduction Systemic lupus erythematosus (SLE) is a multisystem autoimmune disease that can vary among different ethnic and racial groups. Objective The objective of this paper is to study the prevalence of various manifestations of SLE in a sample of the Egyptian population. Patients and methods Information in this study was derived from the medical records of SLE patients who sought medical advice at a private clinic in Cairo from January 1980 to June 2016. Results This study included 1109 SLE patients, of whom 114 (10.3%) were males and 995 were females (89.7%). Mean age of onset was 25.89 ± 10.81 years, while the median of disease duration from the onset of the disease till the last recorded visit was 26 months. The most common cumulative manifestations were arthritis (76.7%), malar rash (48.5%), leukopenia (45.7%), and photosensitivity (45.6%). A total of 33.1% of the patients had nephritis, and neuropsychiatric lupus was present in 6.4% of the patients. Secondary antiphospholipid syndrome was present in 11.5% of the patients. Antinuclear antibody and anti-double-stranded deoxyribonucleic acid were present in 1060/1094 (96.9%) and 842/1062 (79.3%) of the patients, respectively. Antiphospholipid antibodies were present in 266/636 (41.8%) of the patients, anti-Smith in 54/240 (22.5%), anti-SSA/Ro in 61/229 (20.4%), and anti-SSB/La in 32/277 (11.6%) of the patients. Male patients had a statistically higher prevalence of nephritis ( p = 0.01), whereas arthritis and alopecia were statistically higher in females ( p = 0.012 and p = 0.006, respectively). Patients with juvenile onset had a statistically higher prevalence of nephritis and seizures ( p < 0.001 and p = 0.012, respectively). Conclusions Arthritis and malar rash represented the most common clinical manifestations. Male and juvenile-onset patients had a predilection toward a more severe disease. These results are in agreement with many studies conducted in the Middle East and worldwide. On the other hand, major organ involvement was exceptionally low, which is contradictory to several reports from the Middle East and across the globe.
An Effective Cooperative Co-Evolutionary Algorithm for Distributed Flowshop Group Scheduling Problems.
Pan Quan-Ke,Gao Liang,Wang Ling
IEEE transactions on cybernetics
This article addresses a novel scheduling problem, a distributed flowshop group scheduling problem, which has important applications in modern manufacturing systems. The problem considers how to arrange a variety of jobs subject to group constraints at a number of identical manufacturing cellulars, each one with a flowshop structure, with the objective of minimizing makespan. We explore the problem-specific knowledge and present a mixed-integer linear programming model, a counterintuitive paradox, and two suites of accelerations to save computational efforts. Due to the complexity of the problem, we consider a decomposition strategy and propose a cooperative co-evolutionary algorithm (CCEA) with a novel collaboration model and a reinitialization scheme. A comprehensive and thorough computational and statistical campaign is carried out. The results show that the proposed collaboration model and reinitialization scheme are very effective. The proposed CCEA outperforms a number of metaheuristics adapted from closely related scheduling problems in the literature by a significantly considerable margin.
A multiagent genetic algorithm for global numerical optimization.
Zhong Weicai,Liu Jing,Xue Mingzhi,Jiao Licheng
IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics : a publication of the IEEE Systems, Man, and Cybernetics Society
In this paper, multiagent systems and genetic algorithms are integrated to form a new algorithm, multiagent genetic algorithm (MAGA), for solving the global numerical optimization problem. An agent in MAGA represents a candidate solution to the optimization problem in hand. All agents live in a latticelike environment, with each agent fixed on a lattice-point. In order to increase energies, they compete or cooperate with their neighbors, and they can also use knowledge. Making use of these agent-agent interactions, MAGA realizes the purpose of minimizing the objective function value. Theoretical analyzes show that MAGA converges to the global optimum. In the first part of the experiments, ten benchmark functions are used to test the performance of MAGA, and the scalability of MAGA along the problem dimension is studied with great care. The results show that MAGA achieves a good performance when the dimensions are increased from 20-10,000. Moreover, even when the dimensions are increased to as high as 10,000, MAGA still can find high quality solutions at a low computational cost. Therefore, MAGA has good scalability and is a competent algorithm for solving high dimensional optimization problems. To the best of our knowledge, no researchers have ever optimized the functions with 10,000 dimensions by means of evolution. In the second part of the experiments, MAGA is applied to a practical case, the approximation of linear systems, with a satisfactory result.
Artificial neuron-glia networks learning approach based on cooperative coevolution.
Mesejo Pablo,Ibáñez Oscar,Fernández-Blanco Enrique,Cedrón Francisco,Pazos Alejandro,Porto-Pazos Ana B
International journal of neural systems
Artificial Neuron-Glia Networks (ANGNs) are a novel bio-inspired machine learning approach. They extend classical Artificial Neural Networks (ANNs) by incorporating recent findings and suppositions about the way information is processed by neural and astrocytic networks in the most evolved living organisms. Although ANGNs are not a consolidated method, their performance against the traditional approach, i.e. without artificial astrocytes, was already demonstrated on classification problems. However, the corresponding learning algorithms developed so far strongly depends on a set of glial parameters which are manually tuned for each specific problem. As a consequence, previous experimental tests have to be done in order to determine an adequate set of values, making such manual parameter configuration time-consuming, error-prone, biased and problem dependent. Thus, in this paper, we propose a novel learning approach for ANGNs that fully automates the learning process, and gives the possibility of testing any kind of reasonable parameter configuration for each specific problem. This new learning algorithm, based on coevolutionary genetic algorithms, is able to properly learn all the ANGNs parameters. Its performance is tested on five classification problems achieving significantly better results than ANGN and competitive results with ANN approaches.
Coupling of dynamic microtubules to F-actin by Fmn2 regulates chemotaxis of neuronal growth cones.
Kundu Tanushree,Dutta Priyanka,Nagar Dhriti,Maiti Sankar,Ghose Aurnab
Journal of cell science
Dynamic co-regulation of the actin and microtubule subsystems enables the highly precise and adaptive remodelling of the cytoskeleton necessary for critical cellular processes, such as axonal pathfinding. The modes and mediators of this interpolymer crosstalk, however, are inadequately understood. We identify Fmn2, a non-diaphanous-related formin associated with cognitive disabilities, as a novel regulator of cooperative actin-microtubule remodelling in growth cones of both chick and zebrafish neurons. We show that Fmn2 stabilizes microtubules in the growth cones of cultured spinal neurons and in vivo. Super-resolution imaging revealed that Fmn2 facilitates guidance of exploratory microtubules along actin bundles into the chemosensory filopodia. Using live imaging, biochemistry and single-molecule assays, we show that a C-terminal domain in Fmn2 is necessary for the dynamic association between microtubules and actin filaments. In the absence of the cross-bridging function of Fmn2, filopodial capture of microtubules is compromised, resulting in destabilized filopodial protrusions and deficits in growth cone chemotaxis. Our results uncover a critical function for Fmn2 in actin-microtubule crosstalk in neurons and demonstrate that the modulation of microtubule dynamics via associations with F-actin is central to directional motility.
A Novel Method to Detect Functional microRNA Regulatory Modules by Bicliques Merging.
Liang Cheng,Li Yue,Luo Jiawei
IEEE/ACM transactions on computational biology and bioinformatics
UNLABELLED:MicroRNAs (miRNAs) are post-transcriptional regulators that repress the expression of their targets. They are known to work cooperatively with genes and play important roles in numerous cellular processes. Identification of miRNA regulatory modules (MRMs) would aid deciphering the combinatorial effects derived from the many-to-many regulatory relationships in complex cellular systems. Here, we develop an effective method called BiCliques Merging (BCM) to predict MRMs based on bicliques merging. By integrating the miRNA/mRNA expression profiles from The Cancer Genome Atlas (TCGA) with the computational target predictions, we construct a weighted miRNA regulatory network for module discovery. The maximal bicliques detected in the network are statistically evaluated and filtered accordingly. We then employed a greedy-based strategy to iteratively merge the remaining bicliques according to their overlaps together with edge weights and the gene-gene interactions. Comparing with existing methods on two cancer datasets from TCGA, we showed that the modules identified by our method are more densely connected and functionally enriched. Moreover, our predicted modules are more enriched for miRNA families and the miRNA-mRNA pairs within the modules are more negatively correlated. Finally, several potential prognostic modules are revealed by Kaplan-Meier survival analysis and breast cancer subtype analysis. AVAILABILITY:BCM is implemented in Java and available for download in the supplementary materials, which can be found on the Computer Society Digital Library at http://doi.ieeecomputersociety.org/10.1109/ TCBB.2015.2462370.