Genome2D: a visualization tool for the rapid analysis of bacterial transcriptome data

Genome2D is a Windows-based software tool for visualization of bacterial transcriptome and customized datasets on linear chromosome maps constructed from annotated genome sequences. Genome2D facilitates the analysis of transcriptome data by using different color ranges to depict differences in gene-expression levels on a genome map. Such output format enables visual inspection of the transcriptome data, and will quickly reveal transcriptional units, without prior knowledge of expression level cutoff values. The compiled version of Genome2D is freely available for academic or non-profit use from

Adaptation of Hansenula polymorpha to methanol: a transcriptome analysis

Background: Methylotrophic yeast species (e.g. Hansenula polymorpha, Pichia pastoris) can grow on methanol as sole source of carbon and energy. These organisms are important cell factories for the production of recombinant proteins, but are also used in fundamental research as model organisms to study peroxisome biology. During exponential growth on glucose, cells of H. polymorpha typically contain a single, small peroxisome that is redundant for growth while on methanol multiple, enlarged peroxisomes are present. These organelles are crucial to support growth on methanol, as they contain key enzymes of methanol metabolism. In this study, changes in the transcriptional profiles during adaptation of H. polymorpha cells from glucose- to methanol-containing media were investigated using DNA-microarray analyses. Results: Two hours after the shift of cells from glucose to methanol nearly 20% (1184 genes) of the approximately 6000 annotated H. polymorpha genes were significantly upregulated with at least a two-fold differential expression. Highest upregulation (> 300-fold) was observed for the genes encoding the transcription factor Mpp1 and formate dehydrogenase, an enzyme of the methanol dissimilation pathway. Upregulated genes also included genes encoding other enzymes of methanol metabolism as well as of peroxisomal b-oxidation. A moderate increase in transcriptional levels (up to 4-fold) was observed for several PEX genes, which are involved in peroxisome biogenesis. Only PEX11 and PEX32 were higher upregulated. In addition, an increase was observed in expression of the several ATG genes, which encode proteins involved in autophagy and autophagy processes. The strongest upregulation was observed for ATG8 and ATG11. Approximately 20% (1246 genes) of the genes were downregulated. These included glycolytic genes as well as genes involved in transcription and translation. Conclusion: Transcriptional profiling of H. polymorpha cells shifted from glucose to methanol showed the expected downregulation of glycolytic genes together with upregulation of the methanol utilisation pathway. This serves as a confirmation and validation of the array data obtained. Consistent with this, also various PEX genes were upregulated. The strong upregulation of ATG genes is possibly due to induction of autophagy processes related to remodeling of the cell architecture required to support growth on methanol. These processes may also be responsible for the enhanced peroxisomal b oxidation, as autophagy leads to recycling of membrane lipids. The prominent downregulation of transcription and translation may be explained by the reduced growth rate on methanol (td glucose 1 h vs td methanol 4.5 h).Applied Science

Supervised Lowess normalization of comparative genome hybridization data – application to lactococcal strain comparisons

Background: Array-based comparative genome hybridization (aCGH) is commonly used to determine the genomic content of bacterial strains. Since prokaryotes in general have less conserved genome sequences than eukaryotes, sequence divergences between the genes in the genomes used for an aCGH experiment obstruct determination of genome variations (e.g. deletions). Current normalization methods do not take into consideration sequence divergence between target and microarray features and therefore cannot distinguish a difference in signal due to systematic errors in the data or due to sequence divergence. Results: We present supervised Lowess, or S-Lowess, an application of the subset Lowess normalization method. By using a predicted subset of array features with minimal sequence divergence between the analyzed strains for the normalization procedure we remove systematic errors from dual-dye aCGH data in two steps: (1) determination of a subset of conserved genes (i.e. likely conserved genes, LCG); and (2) using the LCG for subset Lowess normalization. Subset Lowess determines the correction factors for systematic errors in the subset of array features and normalizes all array features using these correction factors. The performance of S-Lowess was assessed on aCGH experiments in which differentially labeled genomic DNA fragments of Lactococcus lactis IL1403 and L. lactis MG1363 strains were hybridized to IL1403 DNA microarrays. Since both genomes are sequenced and gene deletions identified, the success rate of different aCGH normalization methods in detecting these deletions in the MG1363 genome were determined. S-Lowess detects 97% of the deletions, whereas other aCGH normalization methods detect up to only 60% of the deletions. Conclusion: S-Lowess is implemented in a user-friendly web-tool. We demonstrate that it outperforms existing normalization methods and maximizes detection of genomic variation (e.g. deletions) from microbial aCGH data.

Pointing errors in non-metric virtual environments

There have been suggestions that human navigation may depend on representations that have no metric, Euclidean interpretation but that hypothesis remains contentious. An alternative is that observers build a consistent 3D representation of space. Using immersive virtual reality, we measured the ability of observers to point to targets in mazes that had zero, one or three ‘wormholes’ – regions where the maze changed in configuration (invisibly). In one model, we allowed the configuration of the maze to vary to best explain the pointing data; in a second model we also allowed the local reference frame to be rotated through 90, 180 or 270 degrees. The latter model outperformed the former in the wormhole conditions, inconsistent with a Euclidean cognitive map

Psychoeducation and the family burden in schizophrenia: a randomized controlled trial

Abstract Background The majority of patients with schizophrenia live with their relatives in Pakistan, thereby families experience a considerable burden. We aimed to study the impact of psychoeducation on the burden of schizophrenia on the family in a randomised controlled trial. Methods A total of 108 patients with schizophrenia and their family members from the outpatient department of a teaching hospital in Lahore, Pakistan were randomised. Both groups received psychotropic drugs but one group received psychoeducation in addition. Family burden was assessed at the time of recruitment and at 6 months post intervention. Results In all, 99 patients and their relatives completed the treatment. There was significant reduction in burden at post-intervention assessment in the psychoeducation group based on intention to treat analysis. Conclusion Family psychoeducation can be an important intervention for patients with schizophrenia in Pakistan.</p

Wellbeing, mental health knowledge and caregiving experiences of siblings of people with psychosis, compared to their peers and parents: An exploratory study

Purpose The wellbeing and caregiving experiences of family carers supporting people with psychosis has garnered increasing interest. Evidence indicates that the burden of caregiving can adversely impact on parents’ wellbeing, few studies have investigated whether this is also the case for siblings, who often take on caregiving responsibilities. This exploratory study investigated the wellbeing, mental health knowledge, and appraisals of caregiving in siblings of individuals with psychosis. Method Using a cross-sectional design, 90 siblings completed three validated questionnaires: Warwick–Edinburgh Mental Wellbeing Scale (WEMWBS), Mental Health Knowledge Schedule (MAKS), and Experience of Caregiving Inventory (ECI). Data obtained were compared to general population norms and parent-carers’ scores. Multi-variable regression analyses were conducted to examine relationships between questionnaire scores and demographic characteristics including age, sex, birth order, marital status, accommodation and educational level. Results Siblings, especially sisters, had significantly poorer mental wellbeing, compared to normative scores. Conversely, they had better mental health knowledge. Siblings and parent-carers had comparable high levels of negative appraisals of caregiving experiences, but siblings reported more satisfaction with personal experiences and relationships. Education level was a significant predictor for better mental health knowledge; there were no other relationships between siblings’ demographic factors and outcomes. Conclusion Study findings suggest that siblings have overlapping as well as distinct needs, compared to parent-carers. Further research is required to better understand siblings’ experiences so as to inform development of targeted interventions that enhance wellbeing and caregiving capacity

Using a logical model to predict the growth of yeast

<p>Abstract</p> <p>Background</p> <p>A logical model of the known metabolic processes in <it>S. cerevisiae </it>was constructed from iFF708, an existing Flux Balance Analysis (FBA) model, and augmented with information from the KEGG online pathway database. The use of predicate logic as the knowledge representation for modelling enables an explicit representation of the structure of the metabolic network, and enables logical inference techniques to be used for model identification/improvement.</p> <p>Results</p> <p>Compared to the FBA model, the logical model has information on an additional 263 putative genes and 247 additional reactions. The correctness of this model was evaluated by comparison with iND750 (an updated FBA model closely related to iFF708) by evaluating the performance of both models on predicting empirical minimal medium growth data/essential gene listings.</p> <p>Conclusion</p> <p>ROC analysis and other statistical studies revealed that use of the simpler logical form and larger coverage results in no significant degradation of performance compared to iND750.</p

Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990-2015: a systematic analysis for the Global Burden of Disease Study 2015

SummaryBackground The Global Burden of Diseases, Injuries, and Risk Factors Study 2015 provides an up-to-date synthesis of the evidence for risk factor exposure and the attributable burden of disease. By providing national and subnational assessments spanning the past 25 years, this study can inform debates on the importance of addressing risks in context. Methods We used the comparative risk assessment framework developed for previous iterations of the Global Burden of Disease Study to estimate attributable deaths, disability-adjusted life-years (DALYs), and trends in exposure by age group, sex, year, and geography for 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks from 1990 to 2015. This study included 388 risk-outcome pairs that met World Cancer Research Fund-defined criteria for convincing or probable evidence. We extracted relative risk and exposure estimates from randomised controlled trials, cohorts, pooled cohorts, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. We developed a metric that allows comparisons of exposure across risk factors—the summary exposure value. Using the counterfactual scenario of theoretical minimum risk level, we estimated the portion of deaths and DALYs that could be attributed to a given risk. We decomposed trends in attributable burden into contributions from population growth, population age structure, risk exposure, and risk-deleted cause-specific DALY rates. We characterised risk exposure in relation to a Socio-demographic Index (SDI). Findings Between 1990 and 2015, global exposure to unsafe sanitation, household air pollution, childhood underweight, childhood stunting, and smoking each decreased by more than 25%. Global exposure for several occupational risks, high body-mass index (BMI), and drug use increased by more than 25% over the same period. All risks jointly evaluated in 2015 accounted for 57·8% (95% CI 56·6–58·8) of global deaths and 41·2% (39·8–42·8) of DALYs. In 2015, the ten largest contributors to global DALYs among Level 3 risks were high systolic blood pressure (211·8 million [192·7 million to 231·1 million] global DALYs), smoking (148·6 million [134·2 million to 163·1 million]), high fasting plasma glucose (143·1 million [125·1 million to 163·5 million]), high BMI (120·1 million [83·8 million to 158·4 million]), childhood undernutrition (113·3 million [103·9 million to 123·4 million]), ambient particulate matter (103·1 million [90·8 million to 115·1 million]), high total cholesterol (88·7 million [74·6 million to 105·7 million]), household air pollution (85·6 million [66·7 million to 106·1 million]), alcohol use (85·0 million [77·2 million to 93·0 million]), and diets high in sodium (83·0 million [49·3 million to 127·5 million]). From 1990 to 2015, attributable DALYs declined for micronutrient deficiencies, childhood undernutrition, unsafe sanitation and water, and household air pollution; reductions in risk-deleted DALY rates rather than reductions in exposure drove these declines. Rising exposure contributed to notable increases in attributable DALYs from high BMI, high fasting plasma glucose, occupational carcinogens, and drug use. Environmental risks and childhood undernutrition declined steadily with SDI; low physical activity, high BMI, and high fasting plasma glucose increased with SDI. In 119 countries, metabolic risks, such as high BMI and fasting plasma glucose, contributed the most attributable DALYs in 2015. Regionally, smoking still ranked among the leading five risk factors for attributable DALYs in 109 countries; childhood underweight and unsafe sex remained primary drivers of early death and disability in much of sub-Saharan Africa. Interpretation Declines in some key environmental risks have contributed to declines in critical infectious diseases. Some risks appear to be invariant to SDI. Increasing risks, including high BMI, high fasting plasma glucose, drug use, and some occupational exposures, contribute to rising burden from some conditions, but also provide opportunities for intervention. Some highly preventable risks, such as smoking, remain major causes of attributable DALYs, even as exposure is declining. Public policy makers need to pay attention to the risks that are increasingly major contributors to global burden. Funding Bill & Melinda Gates Foundation

The dipolar endofullerene HF@C60

The cavity inside fullerenes provides a unique environment for the study of isolated atoms and molecules. We report encapsulation of hydrogen fluoride inside C60 using molecular surgery to give the endohedral fullerene HF@C60. The key synthetic step is the closure of the open fullerene cage while minimizing escape of HF. The encapsulated HF molecule moves freely inside the cage and exhibits quantization of its translational and rotational degrees of freedom, as revealed by inelastic neutron scattering and infrared spectroscopy. The rotational and vibrational constants of the encapsulated HF molecules were found to be redshifted relative to free HF. The NMR spectra display a large 1H-19F J coupling typical of an isolated species. The dipole moment of HF@C60 was estimated from the temperature-dependence of the dielectric constant at cryogenic temperatures and showed that the cage shields around 75% of the HF dipole

The role of socio-economic status in the decision making on diagnosis and treatment of oesophageal cancer in The Netherlands

In the United States (USA), a correlation has been demonstrated between socio-economic status (SES) of patients on the one hand, and tumour histology, stage of the disease and treatment modality of various cancer types on the other hand. It is unknown whether such correlations are also involved in patients with oesophageal cancer in The Netherlands. Between 1994 and 2003, 888 oesophageal cancer patients were included in a prospective database with findings on the diagnostic work-up and treatment of oesophageal cancer. Socio-economic status of patients was defined as the average net yearly income. Linear-by-linear association testing revealed that oesophageal adenocarcinoma was more frequently observed in patients with higher SES and squamous cell carcinoma in patients with lower SES (P=0.02). Multivariable logistic regression analysis showed no correlation between SES and staging procedures and preoperative TNM stage. The adjusted odds ratio (OR) for stent placement was 0.82 (95% CI 0.71–0.95), indicating that with an increase in SES by 1200 €, the likelihood that a stent was placed declined by 18%. Patients with a higher SES more frequently underwent resection or were treated with chemotherapy (OR: 1.15; 95% CI 1.01–1.32 and OR: 1.16; 95% CI 1.02–1.32, respectively). Socio-economic factors are involved in oesophageal cancer in The Netherlands, as patients with a higher SES are more likely to have an adenocarcinoma and patients with a lower SES a squamous cell carcinoma. Moreover, the correlations between SES and different treatment modalities suggest that both patient and doctor determinants contribute to the decision on the most optimal treatment modality in patients with oesophageal cancer