Brain connectivity during the processing of nouns and verbs: a dynamic Bayesian network analysis

Dynamic Bayesian network was used to study the connections among the brain regions activated during processing of nouns and verbs. Under simplifying assumptions, we arrived at a dynamic Bayesian network learning algorithm with reduced time complexity, which allowed us to test all possible connectivity models exhaustively and choose the best model based on the Bayesian information criterion (BIC) score. We found a posterior to anterior flow of processing of both nouns and verbs. The left medial frontal gyrus was found to play an important role in the network. For verb processing, strong involvements of motor cortex and cerebellum were found.published_or_final_versio

Fed batch production of hydrogen from palm oil mill effluent using anaerobic microflora

Anaerobic production of hydrogen from palm oil mill effluent (POME) by microflora was investigated in 5-l bioreactor at 60 °C and pH 5.5. POME sludge was collected from the anaerobic pond of a POME treatment plant at a palm oil mill and used as a source of inocula. A batch reactor was found to yield a total of 4708 ml H2H2/(l POME) and the maximum evolution rate was 454 ml-H2H2/(l POME h). A fed batch process was conducted after 50 h. Two liters of reaction medium was removed and 2 l of fresh POME was added to the reactor every 24 h (15 times). The reproducibility of the fed batch process checked by changing the feeding time every 8 h (10 times). A yield of 2382 ml H2H2/(l POME) and 2419 ml H2H2/(l POME) at maximum evolution rate of 313 ml H2H2/(l POME h) and 436 ml H2H2/(l POME h) were obtained, respectively. Throughout the study, methane gas was not observed in the evolved gas mixture

Matrix-assisted laser desorption ionization time-of-flight mass spectrometry for rapid identification of mold and yeast cultures of Penicillium marneffei

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Biological production of hydrogen from glucose by natural anaerobic microflora

Palm oil mill effluent (POME) sludge, sludge compost from Malaysia and CREST compost from Philippines were collected for the study. The capability of these microflora to produce hydrogen was examined with 500 ml artificial wastewater containing 1% glucose, 0.2% yeast extract and 0.018% magnesium chloride hexahydrate under anaerobic fermentation in a batch culture. The microflora in POME sludge, sludge compost and CREST compost were found to produce significant amounts of hydrogen. The maximum production yield of hydrogen per decomposed glucose was 2.1 mol/mol-glucose at a conversion rate of 0.137 L/(L-medh) at 50°C obtained by sludge compost. All fermentations were carried out without pH control. It was also found that the addition of nitrogen source in the medium caused a change in hydrogen produced. There was no methane gas in the evolved gas

Prioritization of sustainability indicators for promoting the circular economy: The case of developing countries

The concept of the circular economy has gained well-recognition across the world for the past decades. With the heightening risk of the impact of climate change, resource scarcity to meet the increasing world population, the need to transition to a more sustainable development model is urgent. The circular economy is often cited as one of the best solutions to support sustainable development. However, the diffusion of this concept in the industrial arena is still relatively slow, particularly in the developing country, which collectively exerts high potential to be the world’s largest economies and workforce. It is crucial to make sure that the development of these nations is sustainable and not bearing on the cost of future generation. Thus, this work aims to provide a comprehensive review of the circular economy concept in developing country context. Furthermore, a novel model is proposed by adopting Fuzzy Analytics Network Process (FANP) to quantify the priority weights of the sustainability indicators to provide guidelines for the industry stakeholders at different stages of industry cycle to transition toward the circular economy. The results revealed that improvement in economic performance and public acceptance are they key triggers to encourage stakeholders for sustainable development. The outcomes serve as a reference to enhance the overall decision-making process of industry stakeholders. Local authorities can adopt the recommendations to design policy and incentive that encourage the adoption of circular economy in real industry operation to spur up economic development, without neglecting environmental well-being and jeopardizing social benefits

Prioritization of sustainability indicators for promoting the circular economy: The case of developing countries

The concept of the circular economy has gained well-recognition across the world for the past decades. With the heightening risk of the impact of climate change, resource scarcity to meet the increasing world population, the need to transition to a more sustainable development model is urgent. The circular economy is often cited as one of the best solutions to support sustainable development. However, the diffusion of this concept in the industrial arena is still relatively slow, particularly in the developing country, which collectively exerts high potential to be the world’s largest economies and workforce. It is crucial to make sure that the development of these nations is sustainable and not bearing on the cost of future generation. Thus, this work aims to provide a comprehensive review of the circular economy concept in developing country context. Furthermore, a novel model is proposed by adopting Fuzzy Analytics Network Process (FANP) to quantify the priority weights of the sustainability indicators to provide guidelines for the industry stakeholders at different stages of industry cycle to transition toward the circular economy. The results revealed that improvement in economic performance and public acceptance are they key triggers to encourage stakeholders for sustainable development. The outcomes serve as a reference to enhance the overall decision-making process of industry stakeholders. Local authorities can adopt the recommendations to design policy and incentive that encourage the adoption of circular economy in real industry operation to spur up economic development, without neglecting environmental well-being and jeopardizing social benefits

Disparities of time trends and birth cohort effects on invasive breast cancer incidence in Shanghai and Hong Kong pre- and post-menopausal women

© 2017 The Author(s). Background: Breast cancer is the leading cause of cancer morbidity among Shanghai and Hong Kong women, which contributes to 20-25% of new female cancer incidents. This study aimed to describe the temporal trend of breast cancer and interpret the potential effects on the observed secular trends. Methods: Cancer incident data were obtained from the cancer registries. Age-standardized incidence rate was computed by the direct method using the World population of 2000. Average annual percentage change (AAPC) in incidence rate was estimated by the Joinpoint regression. Age, period and cohort effects were assessed by using a log-linear model with Poisson regression. Results: During 1976-2009, an increasing trend of breast cancer incidence was observed, with an AAPC of 1.73 [95% confidence interval (CI): 1.54-1.92)] for women in Hong Kong and 2.83 (95% CI, 2.26-3.40) in Shanghai. Greater upward trends were revealed in Shanghai women aged 50 years old or above (AAPC = 3.09; 95% CI, 1.48-4.73). Using age at 50 years old as cut-point, strong birth cohort effects were shown in both pre- and post-menopausal women, though a more remarkable effect was suggested in Shanghai post-menopausal women. No evidence for a period effect was indicated. Conclusions: Incidence rate of breast cancer has been more speedy in Shanghai post-menopausal women than that of the Hong Kong women over the past 30 years. Decreased birth rate and increasing environmental exposures (e.g., light-at-night) over successive generations may have constituted major impacts on the birth cohort effects, especially for the post-menopausal breast cancer; further analytic studies are warranted.Link_to_subscribed_fulltex

Clinical significance of stromal apoptosis in colorectal cancer

BackgroundEpithelial and stromal cells play an important role in the development of colorectal cancer (CRC). We aimed to determine the prognostic significance of both epithelial and stromal cell apoptosis in CRC.MethodsTotal apoptosis was determined by caspase-3 activity measurements in protein homogenates of CRC specimens and adjacent normal mucosa of 211 CRC patients. Epithelial apoptosis was determined by an ELISA specific for a caspase-3-degraded cytokeratin 18 product, the M30 antigen. Stromal apoptosis was determined from the ratio between total and epithelial apoptosis.ResultsEpithelial and stromal apoptosis, as well as total apoptosis, were significantly higher in CRC compared with corresponding adjacent normal mucosa. Low total tumour apoptosis (< or = median caspase-3 activity) was associated with a significantly worse disease recurrence (hazard ratio (HR), 95% confidence interval (95% CI): 1.77 (1.05-3.01)), independent of clinocopathological parameters. Epithelial apoptosis was not associated with clinical outcome. In contrast, low stromal apoptosis (< or = median caspase-3/M30) was found to be an independent prognostic factor for overall survival, disease-free survival and disease recurrence, with HRs (95% CI) of 1.66 (1.17-2.35), 1.62 (1.15-2.29) and 1.69 (1.01-2.85), respectively.InterpretationStromal apoptosis, in contrast to epithelial apoptosis, is an important factor with respect to survival and disease-recurrence in CRC

“Topological Significance” Analysis of Gene Expression and Proteomic Profiles from Prostate Cancer Cells Reveals Key Mechanisms of Androgen Response

The problem of prostate cancer progression to androgen independence has been extensively studied. Several studies systematically analyzed gene expression profiles in the context of biological networks and pathways, uncovering novel aspects of prostate cancer. Despite significant research efforts, the mechanisms underlying tumor progression are poorly understood. We applied a novel approach to reconstruct system-wide molecular events following stimulation of LNCaP prostate cancer cells with synthetic androgen and to identify potential mechanisms of androgen-independent progression of prostate cancer.We have performed concurrent measurements of gene expression and protein levels following the treatment using microarrays and iTRAQ proteomics. Sets of up-regulated genes and proteins were analyzed using our novel concept of "topological significance". This method combines high-throughput molecular data with the global network of protein interactions to identify nodes which occupy significant network positions with respect to differentially expressed genes or proteins. Our analysis identified the network of growth factor regulation of cell cycle as the main response module for androgen treatment in LNCap cells. We show that the majority of signaling nodes in this network occupy significant positions with respect to the observed gene expression and proteomic profiles elicited by androgen stimulus. Our results further indicate that growth factor signaling probably represents a "second phase" response, not directly dependent on the initial androgen stimulus.We conclude that in prostate cancer cells the proliferative signals are likely to be transmitted from multiple growth factor receptors by a multitude of signaling pathways converging on several key regulators of cell proliferation such as c-Myc, Cyclin D and CREB1. Moreover, these pathways are not isolated but constitute an interconnected network module containing many alternative routes from inputs to outputs. If the whole network is involved, a precisely formulated combination therapy may be required to fight the tumor growth effectively