In vitro effect of lysophosphatidic acid on proliferation, invasion and migration of human ovarian cancer cells

Purpose: To evaluate the effect of lysophosphatidic acid (LPA) on the proliferation, invasion and migration ability of 3AO, SKOV3 and CAOV3 human ovarian cancer cell lines.Methods: SKOV3, 3AO and CAOV3 cell lines were respectively treated with LPA. Changes in the proliferation rate of these cell lines were observed after LPA treatment. The cell lines that were not treated with LPA served as control group. Boyden chamber was used to assess cell invasion and migration capability. The expression levels of relevant cytokines related to cell migration in the supernatant of CAOV3 cell line were determined using ELISA following LPA stimulation.Results: The cell proliferation rate of human ovarian cancer cell lines was significantly accelerated after in vitro LPA treatment in a concentration-dependent fashion. Boyden chamber assay data indicate that invasion indices in 3AO and CAOV3 cell lines were significantly higher than those in untreated control cell lines (p < 0.05). However, no statistical significance was noted between 3AO and CAOV3 cell lines (p < 0.05). The expression levels of relevant cytokines in the CAOV3 cell line were significantly upregulated after LPA treatment (p < 0.05).Conclusion: LPA intervention in vitro accelerates cell proliferation rate and also significantly upregulates the expression levels of multiple cytokines related to cell migration in human ovarian cancer cell lines, suggesting that LPA plays a significant role in the invasion and migration of SKOV3, 3AO and CAOV3 cell lines.Keywords: Ovarian carcinoma, Tumor infiltration, Lysophosphatidic acid, Cell migration, Cytokine

Prognostic Value of MicroRNA-20b in Acute Myeloid Leukemia

Acute myeloid leukemia (AML) is a highly heterogeneous disease that requires fine-grained risk stratification for the best prognosis of patients. As a class of small non-coding RNAs with important biological functions, microRNAs play a crucial role in the pathogenesis of AML. To assess the prognostic impact of miR-20b on AML in the presence of other clinical and molecular factors, we screened 90 AML patients receiving chemotherapy only and 74 also undergoing allogeneic hematopoietic stem cell transplantation (allo-HSCT) from the Cancer Genome Atlas (TCGA) database. In the chemotherapy-only group, high miR-20b expression subgroup had shorter event-free survival (EFS) and overall survival (OS, both P < 0.001); whereas, there were no significant differences in EFS and OS between high and low expression subgroups in the allo-HSCT group. Then we divided all patients into high and low expression groups based on median miR-20b expression level. In the high expression group, patients treated with allo-HSCT had longer EFS and OS than those with chemotherapy alone (both P < 0.01); however, there were no significant differences in EFS and OS between different treatment subgroups in the low expression group. Further analysis showed that miR-20b was negatively correlated with genes in "ribosome," "myeloid leukocyte mediated immunity," and "DNA replication" signaling pathways. ORAI2, the gene with the strongest correlation with miR-20b, also had significant prognostic value in patients undergoing chemotherapy but not in the allo-HSCT group. In conclusion, our findings suggest that high miR-20b expression is a poor prognostic indicator for AML, but allo-HSCT may override its prognostic impact

Prognostic role of Wnt and Fzd gene families in acute myeloid leukaemia

Wnt-Fzd signalling pathway plays a critical role in acute myeloid leukaemia (AML) progression and oncogenicity. There is no study to investigate the prognostic value of Wnt and Fzd gene families in AML. Our study screened 84 AML patients receiving chemotherapy only and 71 also undergoing allogeneic haematopoietic stem cell transplantation (allo-HSCT) from the Cancer Genome Atlas (TCGA) database. We found that some Wnt and Fzd genes had significant positive correlations. The expression levels of Fzd gene family were independent of survival in AML patients. In the chemotherapy group, AML patients with high Wnt2B or Wnt11 expression had significantly shorter event-free survival (EFS) and overall survival (OS); high Wnt10A expressers had significantly longer OS than the low expressers (all P < .05), whereas, in the allo-HSCT group, the expression levels of Wnt gene family were independent of survival. We further found that high expression of Wnt10A and Wnt11 had independent prognostic value, and the patients with high Wnt10A and low Wnt11 expression had the longest EFS and OS in the chemotherapy group. Pathway enrichment analysis showed that genes related to Wnt10A, Wnt11 and Wnt 2B were mainly enriched in 'cell morphogenesis involved in differentiation', 'haematopoietic cell lineage', 'platelet activation, signalling and aggregation' and 'mitochondrial RNA metabolic process' signalling pathways. Our results indicate that high Wnt2B and Wnt11 expression predict poor prognosis, and high Wnt10A expression predicts favourable prognosis in AML, but their prognostic effects could be neutralized by allo-HSCT. Combined Wnt10A and Wnt11 may be a novel prognostic marker in AML

Variations in species diversity patterns and community assembly rules among vegetation types in the karst landscape

The various vegetation types in the karst landscape have been considered the results of heterogeneous habitats. However, the lack of a comprehensive understanding of regional biodiversity patterns and the underlying ecological processes limits further research on ecological management. This study established forest dynamic plots (FDPs) of the dominant vegetation types (shrubland, SL; mixed tree and shrub forest, MTSF; coniferous forest, CF; coniferous broadleaf mixed forest, CBMF; and broadleaf forest, BF) in the karst landscape and quantified the species diversity patterns and potential ecological processes. The results showed that in terms of diversity patterns, the evenness and species richness of the CF community were significantly lower than other vegetation types, while the BF community had the highest species richness. The other three vegetation types showed no significant variation in species richness and evenness. However, when controlling the number of individuals of FDPs, the rarefied species richness showed significant differences and ranked as BF &gt; SL &gt; MTSF &gt; CBMF &gt; CF, highlighting the importance of considering the impacts of abundance. Additionally, the community assembly of climax communities (CF or BF) was dominated by stochastic processes such as species dispersal or species formation, whereas deterministic processes (habitat filtering) dominated the secondary forests (SL, MTSF, and CBMF). These findings proved that community assembly differs mainly between the climax community and other communities. Hence, it is crucial to consider the biodiversity and of the potential underlying ecological processes together when studying regional ecology and management, particularly in heterogeneous ecosystems

Distributed evolutionary algorithms and their models: A survey of the state-of-the-art

The increasing complexity of real-world optimization problems raises new challenges to evolutionary computation. Responding to these challenges, distributed evolutionary computation has received considerable attention over the past decade. This article provides a comprehensive survey of the state-of-the-art distributed evolutionary algorithms and models, which have been classified into two groups according to their task division mechanism. Population-distributed models are presented with master-slave, island, cellular, hierarchical, and pool architectures, which parallelize an evolution task at population, individual, or operation levels. Dimension-distributed models include coevolution and multi-agent models, which focus on dimension reduction. Insights into the models, such as synchronization, homogeneity, communication, topology, speedup, advantages and disadvantages are also presented and discussed. The study of these models helps guide future development of different and/or improved algorithms. Also highlighted are recent hotspots in this area, including the cloud and MapReduce-based implementations, GPU and CUDA-based implementations, distributed evolutionary multiobjective optimization, and real-world applications. Further, a number of future research directions have been discussed, with a conclusion that the development of distributed evolutionary computation will continue to flourish

Ruthenium(III)-Catalyzed beta-Alkylation of Secondary Alcohols with Primary Alcohols

A Ru(III)-NNN complex bearing a pyridyl-supported pyrazolyl-imidazolyl ligand was synthesized and utilized as the catalyst for the direct beta-alkylation of secondary alcohols with primary alcohols. beta-Alkylated secondary alcohols were obtained in moderate to high yields with water formed as the byproduct through a hydrogen borrowing pathway. The present protocol provides a concise atom-economical and environmentally benign method for C-C bond formation

Adaptive patch-based sparsity estimation for image via MOEA/D

Due to the extensive and various information that natural images contain, it is very challenging to estimate the sparsity for an image. In this paper, we propose an adaptive sparsity estimation model for image patches, which consists of an offline training phase and online estimation phase. In offline training, for the training patch, MOEA/D is applied to obtain a group of Pareto solutions and determine a sparsity range. By processing a reduced number of representative training patches, all the sparsity ranges are stored in a look-up table (LUT) for reuse. In the online estimation phase, for a query patch, its sparsity range is set to that of the most similar training patch. And the corresponding sparse representation vector can be obtained by a sparsity-restricted greedy algorithm (SRGA) constrained by this range. Thus, the sparsity is adaptively determined by this sparse representation vector within this range. By comparing with the state-of-the-art greedy algorithms with fixed sparsity and one adaptive method, experimental studies on benchmark dataset demonstrate that our proposed approach is able to achieve better sparse representation quality in terms of PSNR and coding efficiency

Biosolids inhibit bioavailability and plant uptake of triclosan and triclocarban.

Biosolids from wastewater treatment are primarily disposed of via land applications, where numerous pharmaceuticals and personal care products (PPCPs) may contaminate food crops and pose a human exposure risk. Biosolids are rich in organic carbon and addition of biosolids can increase the sorption of certain PPCPs in soil, decreasing their bioavailability. This study tested the hypothesis that the relative plant uptake of PPCPs decreases with increasing biosolids amendment. Accumulation of triclosan and triclocarban was measured in roots of radish and carrot grown in soils with or without biosolids. Addition of biosolids significantly prolonged the persistence of triclosan in soil. When expressed in bioaccumulation factor (BCF), accumulation of triclosan drastically decreased in biosolids-amended soils, while the effect was limited for triclocarban. Compared to the unamended soil, amending biosolids at 2% (w/w) decreased BCF of triclosan in the edible tissues of radish and carrot by 85.4 and 89.3%, respectively. Measurement using a thin-film passive sampler provided direct evidence showing that the availability of triclosan greatly decreased in biosolids-amended soils. Partial correlation analysis using data from this and published studies validated that biosolids decreased plant uptake primarily by increasing soil organic carbon content and subsequently sorption. Therefore, contamination of food crops by biosolids-borne contaminants does not linearly depend on biosolids use rates. This finding bears significant implications in the overall risk evaluation of biosolids-borne contaminants