c-MET Protects Breast Cancer Cells from Apoptosis Induced by Sodium Butyrate

Sodium Butyrate (NaBu) is regarded as a potential reagent for cancer therapy. In this study, a specific breast cancer cell population that is resistant NaBu treatment was identified. These cells possess cancer stem cell characters, such as the capability of sphere formation in vitro and high tumor incident rate (85%) in mouse model. Forty percent of the NaBu resistant cells express the cancer stem cells marker, the CD133, whereas only 10% intact cells present the CD133 antigen. Furthermore, the endogenous expressing c-MET contributes to the survival of cancer stem cell population from the treatment of NaBu. The CD133+ group also presents a higher level of c-MET. A combination treatment of MET siRNA and NaBu efficiently prohibited the breast cancer progression, and the incident rate of the tumor decrease to 18%. This study may help to develop a new and alternative strategy for breast cancer therapy

A model for describing and maximising Security Knowledge Sharing to enhance security awareness

Employees play a crucial role in enhancing information security in the workplace, and this requires everyone having the requisite security knowledge and know-how. To maximise knowledge levels, organisations should encourage and facilitate Security Knowledge Sharing (SKS) between employees. To maximise sharing, we need first to understand the mechanisms whereby such sharing takes place and then to encourage and engender such sharing. A study was carried out to test the applicability of Transactive Memory Systems Theory in describing knowledge sharing in this context, which confirmed its applicability in this domain. To encourage security knowledge sharing, the harnessing of Self-Determination Theory was proposed— satisfying employee autonomy, relatedness and competence needs to maximise sharing. Such sharing is required to improve and enhance employee security awareness across organisations. We propose a model to describe the mechanisms for such sharing as well as the means by which it can be encouraged

Can Interactions between Timing of Vaccine-Altered Influenza Pandemic Waves and Seasonality in Influenza Complications Lead to More Severe Outcomes?

Vaccination can delay the peak of a pandemic influenza wave by reducing the number of individuals initially susceptible to influenza infection. Emerging evidence indicates that susceptibility to severe secondary bacterial infections following a primary influenza infection may vary seasonally, with peak susceptibility occurring in winter. Taken together, these two observations suggest that vaccinating to prevent a fall pandemic wave might delay it long enough to inadvertently increase influenza infections in winter, when primary influenza infection is more likely to cause severe outcomes. This could potentially cause a net increase in severe outcomes. Most pandemic models implicitly assume that the probability of severe outcomes does not vary seasonally and hence cannot capture this effect. Here we show that the probability of intensive care unit (ICU) admission per influenza infection in the 2009 H1N1 pandemic followed a seasonal pattern. We combine this with an influenza transmission model to investigate conditions under which a vaccination program could inadvertently shift influenza susceptibility to months where the risk of ICU admission due to influenza is higher. We find that vaccination in advance of a fall pandemic wave can actually increase the number of ICU admissions in situations where antigenic drift is sufficiently rapid or where importation of a cross-reactive strain is possible. Moreover, this effect is stronger for vaccination programs that prevent more primary influenza infections. Sensitivity analysis indicates several mechanisms that may cause this effect. We also find that the predicted number of ICU admissions changes dramatically depending on whether the probability of ICU admission varies seasonally, or whether it is held constant. These results suggest that pandemic planning should explore the potential interactions between seasonally varying susceptibility to severe influenza outcomes and the timing of vaccine-altered pandemic influenza waves

Finding microRNA regulatory modules in human genome using rule induction

Background: MicroRNAs (miRNAs) are a class of small non-coding RNA molecules (20-24 nt), which are believed to participate in repression of gene expression. They play important roles in several biological processes (e.g. cell death and cell growth). Both experimental and computational approaches have been used to determine the function of miRNAs in cellular processes. Most efforts have concentrated on identification of miRNAs and their target genes. However, understanding the regulatory mechanism of miRNAs in the gene regulatory network is also essential to the discovery of functions of miRNAs in complex cellular systems. To understand the regulatory mechanism of miRNAs in complex cellular systems, we need to identify the functional modules involved in complex interactions between miRNAs and their target genes. Results: We propose a rule-based learning method to identify groups of miRNAs and target genes that are believed to participate cooperatively in the post-transcriptional gene regulation, so-called miRNA regulatory modules (MRMs). Applying our method to human genes and miRNAs, we found 79 MRMs. The MRMs are produced from multiple information sources, including miRNA-target binding information, gene expression and miRNA expression profiles. Analysis of two first MRMs shows that these MRMs consist of highly-related miRNAs and their target genes with respect to biological processes. Conclusion: The MRMs found by our method have high correlation in expression patterns of miRNAs as well as mRNAs. The mRNAs included in the same module shared similar biological functions, indicating the ability of our method to detect functionality-related genes. Moreover, review of the literature reveals that miRNAs in a module are involved in several types of human cancer

Gene Expression Profiles of the NCI-60 Human Tumor Cell Lines Define Molecular Interaction Networks Governing Cell Migration Processes

Although there is extensive information on gene expression and molecular interactions in various cell types, integrating those data in a functionally coherent manner remains challenging. This study explores the premise that genes whose expression at the mRNA level is correlated over diverse cell lines are likely to function together in a network of molecular interactions. We previously derived expression-correlated gene clusters from the database of the NCI-60 human tumor cell lines and associated each cluster with function categories of the Gene Ontology (GO) database. From a cluster rich in genes associated with GO categories related to cell migration, we extracted 15 genes that were highly cross-correlated; prominent among them were RRAS, AXL, ADAM9, FN14, and integrin-beta1. We then used those 15 genes as bait to identify other correlated genes in the NCI-60 database. A survey of current literature disclosed, not only that many of the expression-correlated genes engaged in molecular interactions related to migration, invasion, and metastasis, but that highly cross-correlated subsets of those genes engaged in specific cell migration processes. We assembled this information in molecular interaction maps (MIMs) that depict networks governing 3 cell migration processes: degradation of extracellular matrix, production of transient focal complexes at the leading edge of the cell, and retraction of the rear part of the cell. Also depicted are interactions controlling the release and effects of calcium ions, which may regulate migration in a spaciotemporal manner in the cell. The MIMs and associated text comprise a detailed and integrated summary of what is currently known or surmised about the role of the expression cross-correlated genes in molecular networks governing those processes

Spectral hole burning: examples from photosynthesis

The optical spectra of photosynthetic pigment–protein complexes usually show broad absorption bands, often consisting of a number of overlapping, ‘hidden’ bands belonging to different species. Spectral hole burning is an ideal technique to unravel the optical and dynamic properties of such hidden species. Here, the principles of spectral hole burning (HB) and the experimental set-up used in its continuous wave (CW) and time-resolved versions are described. Examples from photosynthesis studied with hole burning, obtained in our laboratory, are then presented. These examples have been classified into three groups according to the parameters that were measured: (1) hole widths as a function of temperature, (2) hole widths as a function of delay time and (3) hole depths as a function of wavelength. Two examples from light-harvesting (LH) 2 complexes of purple bacteria are given within the first group: (a) the determination of energy-transfer times from the chromophores in the B800 ring to the B850 ring, and (b) optical dephasing in the B850 absorption band. One example from photosystem II (PSII) sub-core complexes of higher plants is given within the second group: it shows that the size of the complex determines the amount of spectral diffusion measured. Within the third group, two examples from (green) plants and purple bacteria have been chosen for: (a) the identification of ‘traps’ for energy transfer in PSII sub-core complexes of green plants, and (b) the uncovering of the lowest k = 0 exciton-state distribution within the B850 band of LH2 complexes of purple bacteria. The results prove the potential of spectral hole burning measurements for getting quantitative insight into dynamic processes in photosynthetic systems at low temperature, in particular, when individual bands are hidden within broad absorption bands. Because of its high-resolution wavelength selectivity, HB is a technique that is complementary to ultrafast pump–probe methods. In this review, we have provided an extensive bibliography for the benefit of scientists who plan to make use of this valuable technique in their future research

Mapping geographical inequalities in access to drinking water and sanitation facilities in low-income and middle-income countries, 2000-17

Background Universal access to safe drinking water and sanitation facilities is an essential human right, recognised in the Sustainable Development Goals as crucial for preventing disease and improving human wellbeing. Comprehensive, high-resolution estimates are important to inform progress towards achieving this goal. We aimed to produce high-resolution geospatial estimates of access to drinking water and sanitation facilities. Methods We used a Bayesian geostatistical model and data from 600 sources across more than 88 low-income and middle-income countries (LMICs) to estimate access to drinking water and sanitation facilities on continuous continent-wide surfaces from 2000 to 2017, and aggregated results to policy-relevant administrative units. We estimated mutually exclusive and collectively exhaustive subcategories of facilities for drinking water (piped water on or off premises, other improved facilities, unimproved, and surface water) and sanitation facilities (septic or sewer sanitation, other improved, unimproved, and open defecation) with use of ordinal regression. We also estimated the number of diarrhoeal deaths in children younger than 5 years attributed to unsafe facilities and estimated deaths that were averted by increased access to safe facilities in 2017, and analysed geographical inequality in access within LMICs. Findings Across LMICs, access to both piped water and improved water overall increased between 2000 and 2017, with progress varying spatially. For piped water, the safest water facility type, access increased from 40.0% (95% uncertainty interval [UI] 39.4-40.7) to 50.3% (50.0-50.5), but was lowest in sub-Saharan Africa, where access to piped water was mostly concentrated in urban centres. Access to both sewer or septic sanitation and improved sanitation overall also increased across all LMICs during the study period. For sewer or septic sanitation, access was 46.3% (95% UI 46.1-46.5) in 2017, compared with 28.7% (28.5-29.0) in 2000. Although some units improved access to the safest drinking water or sanitation facilities since 2000, a large absolute number of people continued to not have access in several units with high access to such facilities (>80%) in 2017. More than 253 000 people did not have access to sewer or septic sanitation facilities in the city of Harare, Zimbabwe, despite 88.6% (95% UI 87.2-89.7) access overall. Many units were able to transition from the least safe facilities in 2000 to safe facilities by 2017; for units in which populations primarily practised open defecation in 2000, 686 (95% UI 664-711) of the 1830 (1797-1863) units transitioned to the use of improved sanitation. Geographical disparities in access to improved water across units decreased in 76.1% (95% UI 71.6-80.7) of countries from 2000 to 2017, and in 53.9% (50.6-59.6) of countries for access to improved sanitation, but remained evident subnationally in most countries in 2017. Interpretation Our estimates, combined with geospatial trends in diarrhoeal burden, identify where efforts to increase access to safe drinking water and sanitation facilities are most needed. By highlighting areas with successful approaches or in need of targeted interventions, our estimates can enable precision public health to effectively progress towards universal access to safe water and sanitation. Copyright (C) 2020 The Author(s). Published by Elsevier Ltd.Peer reviewe