Gene expression in cortex and hippocampus during acute pneumococcal meningitis

Background  

Pneumococcal meningitis is associated with high mortality (~30%) and morbidity. Up to 50% of survivors are affected by neurological sequelae due to a wide spectrum of brain injury mainly affecting the cortex and hippocampus. Despite this significant disease burden, the genetic program that regulates the host response leading to brain damage as a consequence of bacterial meningitis is largely unknown.     

Zerumbone induced apoptosis in liver cancer cells via modulation of Bax/Bcl-2 ratio

Background  

Zerumbone is a cytotoxic component isolated from Zingiber zerumbet Smith, a herbal plant which is also known as lempoyang. This new anticancer bioactive compound from Z. zerumbet was investigated for its activity and mechanism in human liver cancer cell lines.     

Cutting edge: B and T lymphocyte attenuator and programmed death receptor-1 inhibitory receptors are required for termination of acute allergic airway inflammation

T cell activation is regulated by coordinate interaction of the T cell Ag receptor and costimulatory signals. Although there is considerable insight into processes that regulate the initiation of inflammation, less is known about the signals that terminate immune responses. We have examined the role of the inhibitory receptors programmed death receptor-1 and B and T lymphocyte attenuator in the regulation of allergic airway inflammation. Our results demonstrate that there is a temporally regulated expression of both the receptors and their ligands during the course of allergic airway inflammation. Following a single inhaled challenge, sensitized wild-type mice exhibit peak inflammation on day 3, which resolves by day 10. In contrast, mice deficient in the expression of programmed death receptor-1 or B and T lymphocyte attenuator have persistent inflammation out to 15 days following challenge. Thus, these receptors are critical determinants of the duration of allergic airway inflammation.     

Predicting host tropism of influenza A virus proteins using random forest

Background

Majority of influenza A viruses reside and circulate among animal populations, seldom infecting humans due to host range restriction. Yet when some avian strains do acquire the ability to overcome species barrier, they might become adapted to humans, replicating efficiently and causing diseases, leading to potential pandemic. With the huge influenza A virus reservoir in wild birds, it is a cause for concern when a new influenza strain emerges with the ability to cross host species barrier, as shown in light of the recent H7N9 outbreak in China. Several influenza proteins have been shown to be major determinants in host tropism. Further understanding and determining host tropism would be important in identifying zoonotic influenza virus strains capable of crossing species barrier and infecting humans.

Results

In this study, computational models for 11 influenza proteins have been constructed using the machine learning algorithm random forest for prediction of host tropism. The prediction models were trained on influenza protein sequences isolated from both avian and human samples, which were transformed into amino acid physicochemical properties feature vectors. The results were highly accurate prediction models (ACC>96.57; AUC>0.980; MCC>0.916) capable of determining host tropism of individual influenza proteins. In addition, features from all 11 proteins were used to construct a combined model to predict host tropism of influenza virus strains. This would help assess a novel influenza strain's host range capability.

Conclusions

From the prediction models constructed, all achieved high prediction performance, indicating clear distinctions in both avian and human proteins. When used together as a host tropism prediction system, zoonotic strains could potentially be identified based on different protein prediction results. Understanding and predicting host tropism of influenza proteins lay an important foundation for future work in constructing computation models capable of directly predicting interspecies transmission of influenza viruses. The models are available for prediction at http://fluleap.bic.nus.edu.sg.

     

Molecular phylogenetics reveal multiple tertiary vicariance origins of the African rain forest trees

Background  

Tropical rain forests are the most diverse terrestrial ecosystems on the planet. How this diversity evolved remains largely unexplained. In Africa, rain forests are situated in two geographically isolated regions: the West-Central Guineo-Congolian region and the coastal and montane regions of East Africa. These regions have strong floristic affinities with each other, suggesting a former connection via an Eocene pan-African rain forest. High levels of endemism observed in both regions have been hypothesized to be the result of either 1) a single break-up followed by a long isolation or 2) multiple fragmentation and reconnection since the Oligocene. To test these hypotheses the evolutionary history of endemic taxa within a rain forest restricted African lineage of the plant family Annonaceae was studied. Molecular phylogenies and divergence dates were estimated using a Bayesian relaxed uncorrelated molecular clock assumption accounting for both calibration and phylogenetic uncertainties.     

Eicosapentaenoic and docosahexaenoic acids production by and okara-utilizing potential of thraustochytrids

Nine thraustochytrid strains isolated from subtropical mangroves were screened for their eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) production potential in a glucose yeast extract medium. Their ability to utilize okara (soymilk residue) for growth and EPA and DHA production was also evaluated. EPA yield was low in most strains, while DHA level was high on glucose yeast extract medium, producing 28.1–41.1% of total fatty acids, for all strains, with the exception of Ulkenia sp. KF13. The DHA yield of Schizochytrium mangrovei strains ranged from 747.7 to 2778.9 mg/l after 52 h of fermentation at 25°C. All strains utilized okara as a substrate for growth, but DHA yield was lower when compared with fermentation in a glucose yeast extract medium. Journal of Industrial Microbiology & Biotechnology (2001) 27, 199–202. Received 11 December 2000/ Accepted in revised form 29 June 2001     

The gene <Emphasis Type="Italic">transformer-2</Emphasis> of <Emphasis Type="Italic">Anastrepha</Emphasis>fruit flies (Diptera,Tephritidae) and its evolution in insects

Background  

In the tephritids Ceratitis, Bactrocera and Anastrepha, the gene transformer provides the memory device for sex determination via its auto-regulation; only in females is functional Tra protein produced. To date, the isolation and characterisation of the gene transformer-2 in the tephritids has only been undertaken in Ceratitis, and it has been shown that its function is required for the female-specific splicing of doublesex and transformer pre-mRNA. It therefore participates in transformer auto-regulatory function. In this work, the characterisation of this gene in eleven tephritid species belonging to the less extensively analysed genus Anastrepha was undertaken in order to throw light on the evolution of transformer-2.     

The four hexamerin genes in the honey bee: structure,molecular evolution and function deduced from expression patterns in queens,workers and drones

Background  

Hexamerins are hemocyanin-derived proteins that have lost the ability to bind copper ions and transport oxygen; instead, they became storage proteins. The current study aimed to broaden our knowledge on the hexamerin genes found in the honey bee genome by exploring their structural characteristics, expression profiles, evolution, and functions in the life cycle of workers, drones and queens.