Hemoglobin determination with paired emitter detector diode

Two ordinary green light-emitting diodes used as light emitter and detector coupled with simple voltmeter form a complete, cost-effective prototype of a photometric hemoglobinometer. The device has been optimized for cuvette assays of total hemoglobin (Hb) in diluted blood using three different chemical methods recommended for the needs of clinical analysis (namely Drabkin, lauryl sulfate, and dithionite methods). The utility of developed device for real analytics has been validated by the assays of total Hb content in human blood. The results of analysis are fully compatible with those obtained using clinically recommended method and clinical analyzer

Systematic quantification of gene interactions by phenotypic array analysis

A phenotypic array method, developed for quantifying cell growth, was applied to the haploid and homozygous diploid yeast deletion strain sets. A growth index was developed to screen for non-additive interacting effects between gene deletion and induced perturbations. From a genome screen for hydroxyurea (HU) chemical-genetic interactions, 298 haploid deletion strains were selected for further analysis. The strength of interactions was quantified using a wide range of HU concentrations affecting reference strain growth. The selectivity of interaction was determined by comparison with drugs targeting other cellular processes. Bio-modules were defined as gene clusters with shared strength and selectivity of interaction profiles. The functions and connectivity of modules involved in processes such as DNA repair, protein secretion and metabolic control were inferred from their respective gene composition. The work provides an example of, and a general experimental framework for, quantitative analysis of gene interaction networks that buffer cell growth

Identification of molecular markers for the early detection of human squamous cell carcinoma of the uterine cervix

To identify novel cellular genes that could potentially act as predictive molecular markers for human cervical cancer, we employed RT–PCR differential display, reverse Northern and Northern blot analysis to compare the gene expression profiles between squamous cell carcinoma biopsies and adjacent histo-pathological normal epithelium tissues. Twenty-eight cDNA clones were isolated that were demonstrated to be consistently over-expressed in squamous cell cervical cancer biopsies of FIGO stages 1B to 3B. Most importantly, it was observed that, in addition to their over-expression in cancer lesions, some of these genes are upregulated in the presumably histo-pathological normal adjacent tissues. Of particular interest is clone G30CC that has been identified to be the gene that encodes S12 ribosomal protein. When employed for RNA–RNA in situ hybridization experiments, expression of G30CC could be detected in the immature basal epithelial cells of histo-pathological normal tissues collected from cervical cancer patients of early FIGO stages. In comparison, the expression of G30CC was not detected in cervical tissues collected from patients admitted for surgery of non-malignant conditions. These results allow the distinct possibility of employing the ribosomal protein S12 gene as an early molecular diagnostic identifier for the screening of human cervical cancer and a potential target employed for cancer gene therapy trials

Comparison of three nudge interventions (priming, default option, and perceived variety) to promote vegetable consumption in a self-service buffet setting.

BACKGROUND: Dietary choices in out-of-home eating are key for individual as well as for public health. These dietary choices are caused by a wide array of determinants, one of which is automatic decision-making. Nudging is attracting considerable interest due to its understanding and application of heuristic biases among consumers. The aim of this study is to test and compare three nudges in promoting vegetable consumption among test persons in a food lab-based experiment. METHODS: The initial sample consisted of 88 participants recruited in Copenhagen, Denmark. Each study participant was randomly assigned to one of the three experiments: priming, default and perceived variety. The priming arm of the experiment consisted of creating a leafy environment with green plants and an odour of herbs. In the default arm of the experiment, the salad was pre-portioned into a bowl containing 200g of vegetables. The third experiment divided the pre-mixed salad into each of its components, to increase the visual variety of vegetables, yet not providing an actual increase in items. Each individual was partaking twice thus serving as her/his own control, randomly assigned to start with control or experimental setting. RESULTS: The default experiment successfully increased the energy intake from vegetables among the study participants (124 kcal vs. 90 kcal in control, p<0.01). Both the priming condition and perceived variety reduced the total energy intake among the study participants (169 kcal, p<0.01 and 124 kcal, p<0.01, respectively), mainly through a decrease in the meat-based meal component. CONCLUSIONS: Considerable progress has been made with regard to understanding the use of nudging in promoting a healthier meal composition, including increasing vegetable intake. This study suggests that the nature of a nudge-based intervention can have different effects, whether it is increasing intake of healthy components, or limiting intake of unhealthy meal components. This work has demonstrated that consumer behaviour can be influenced without restricting or providing incentives for behaviour change. The present findings have promising application to the foodservice sector

Effects of magnolol on UVB-induced skin cancer development in mice and its possible mechanism of action

Background Magnolol, a plant lignan isolated from the bark and seed cones of Magnolia officinalis, has been shown to have chemopreventive effects on chemically-induced skin cancer development. The objectives of this investigation are to study the anticarcinogenic effects of magnolol on UVB-induced skin tumor development in SKH-1 mice, a model relevant to humans, and determine the possible role of apoptosis and cell cycle arrest involved in the skin tumor development. Methods UVB-induced skin carcinogenesis model in SKH-1 mice was used for determining the preventive effects of magnolol on skin cancer development. Western blottings and flow cytometric analysis were used to study the effects of magnolol on apoptosis and cell cycle. Results Magnolol pretreated groups (30, 60 μ g) before UVB treatments (30 mJ/cm2, 5 days/week) resulted in 27-55% reduction in tumor multiplicity as compared to control group in SKH-1 mice. Magnolol pretreatment increased the cleavage of caspase-8 and poly-(-ADP-ribose) polymerase (PARP), increased the expression of p21, a cell cycle inhibitor, and decreased the expression of proteins involved in the G2/M phase of cell cycle in skin samples from SKH-1 mice. Treatment of A431 cells with magnolol decreased cell viability and cell proliferation in a concentration dependent manner. Magnolol induced G2/M phase cell cycle arrest in A431 cells at 12 h with a decreased expression of cell cycle proteins such as cyclin B1, cyclin A, CDK4, Cdc2 and simultaneous increase in the expression of Cip/p21, a cyclin-dependent kinase inhibitor. Magnolol induced apoptosis in vivo and in vitro with an increased cleavage of caspase-8 and PARP. Phospho-signal transducers and activators of transcription 3 (Tyr705), B-Raf, p-MEK, and p-AKT were down-regulated, whereas phosphorylation of ERK was induced by magnolol in A431 cells. Conclusions Magnolol pretreatments prevent UVB-induced skin cancer development by enhancing apoptosis, causing cell cycle arrest at G2/M phase, and affecting various signaling pathways. Magnolol could be a potentially safe and potent anticarcinogenic agent against skin cancer

Extracting expression modules from perturbational gene expression compendia

<p>Abstract</p> <p>Background</p> <p>Compendia of gene expression profiles under chemical and genetic perturbations constitute an invaluable resource from a systems biology perspective. However, the perturbational nature of such data imposes specific challenges on the computational methods used to analyze them. In particular, traditional clustering algorithms have difficulties in handling one of the prominent features of perturbational compendia, namely partial coexpression relationships between genes. Biclustering methods on the other hand are specifically designed to capture such partial coexpression patterns, but they show a variety of other drawbacks. For instance, some biclustering methods are less suited to identify overlapping biclusters, while others generate highly redundant biclusters. Also, none of the existing biclustering tools takes advantage of the staple of perturbational expression data analysis: the identification of differentially expressed genes.</p> <p>Results</p> <p>We introduce a novel method, called ENIGMA, that addresses some of these issues. ENIGMA leverages differential expression analysis results to extract expression modules from perturbational gene expression data. The core parameters of the ENIGMA clustering procedure are automatically optimized to reduce the redundancy between modules. In contrast to the biclusters produced by most other methods, ENIGMA modules may show internal substructure, i.e. subsets of genes with distinct but significantly related expression patterns. The grouping of these (often functionally) related patterns in one module greatly aids in the biological interpretation of the data. We show that ENIGMA outperforms other methods on artificial datasets, using a quality criterion that, unlike other criteria, can be used for algorithms that generate overlapping clusters and that can be modified to take redundancy between clusters into account. Finally, we apply ENIGMA to the Rosetta compendium of expression profiles for <it>Saccharomyces cerevisiae </it>and we analyze one pheromone response-related module in more detail, demonstrating the potential of ENIGMA to generate detailed predictions.</p> <p>Conclusion</p> <p>It is increasingly recognized that perturbational expression compendia are essential to identify the gene networks underlying cellular function, and efforts to build these for different organisms are currently underway. We show that ENIGMA constitutes a valuable addition to the repertoire of methods to analyze such data.</p

Transmission Shifts Underlie Variability in Population Responses to Yersinia pestis Infection

Host populations for the plague bacterium, Yersinia pestis, are highly variable in their response to plague ranging from near deterministic extinction (i.e., epizootic dynamics) to a low probability of extinction despite persistent infection (i.e., enzootic dynamics). Much of the work to understand this variability has focused on specific host characteristics, such as population size and resistance, and their role in determining plague dynamics. Here, however, we advance the idea that the relative importance of alternative transmission routes may vary causing shifts from epizootic to enzootic dynamics. We present a model that incorporates host and flea ecology with multiple transmission hypotheses to study how transmission shifts determine population responses to plague. Our results suggest enzootic persistence relies on infection of an off-host flea reservoir and epizootics rely on transiently maintained flea infection loads through repeated infectious feeds by fleas. In either case, early-phase transmission by fleas (i.e., transmission immediately following an infected blood meal) has been observed in laboratory studies, and we show that it is capable of driving plague dynamics at the population level. Sensitivity analysis of model parameters revealed that host characteristics (e.g., population size and resistance) vary in importance depending on transmission dynamics, suggesting that host ecology may scale differently through different transmission routes enabling prediction of population responses in a more robust way than using either host characteristics or transmission shifts alone

Identification of ORC1/CDC6-Interacting Factors in Trypanosoma brucei Reveals Critical Features of Origin Recognition Complex Architecture

DNA Replication initiates by formation of a pre-replication complex on sequences termed origins. In eukaryotes, the pre-replication complex is composed of the Origin Recognition Complex (ORC), Cdc6 and the MCM replicative helicase in conjunction with Cdt1. Eukaryotic ORC is considered to be composed of six subunits, named Orc1–6, and monomeric Cdc6 is closely related in sequence to Orc1. However, ORC has been little explored in protists, and only a single ORC protein, related to both Orc1 and Cdc6, has been shown to act in DNA replication in Trypanosoma brucei. Here we identify three highly diverged putative T. brucei ORC components that interact with ORC1/CDC6 and contribute to cell division. Two of these factors are so diverged that we cannot determine if they are eukaryotic ORC subunit orthologues, or are parasite-specific replication factors. The other we show to be a highly diverged Orc4 orthologue, demonstrating that this is one of the most widely conserved ORC subunits in protists and revealing it to be a key element of eukaryotic ORC architecture. Additionally, we have examined interactions amongst the T. brucei MCM subunits and show that this has the conventional eukaryotic heterohexameric structure, suggesting that divergence in the T. brucei replication machinery is limited to the earliest steps in origin licensing