Population Differences in Brain Morphology and Microstructure among Chinese,Malay, and Indian Neonates

We studied a sample of 75 Chinese, 73 Malay, and 29 Indian healthy neonates taking part in a cohort study to examine potential differences in neonatal brain morphology and white matter microstructure as a function of ethnicity using both structural T2-weighted magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI). We first examined the differences in global size and morphology of the brain among the three groups. We then constructed the T2-weighted MRI and DTI atlases and employed voxel-based analysis to investigate ethnic differences in morphological shape of the brain from the T2-weighted MRI, and white matter microstructure measured by fractional anisotropy derived from DTI. Compared with Malay neonates, the brains of Indian neonates’ tended to be more elongated in anterior and posterior axis relative to the superior-inferior axis of the brain even though the total brain volume was similar among the three groups. Although most anatomical regions of the brain were similar among Chinese, Malay, and Indian neonates, there were anatomical variations in the spinal-cerebellar and cortical-striatal-thalamic neural circuits among the three populations. The population-related brain regions highlighted in our study are key anatomical substrates associated with sensorimotor functions.     

The community structure of bird assemblages on urban strangler figs

Figs have been regarded as keystone plant resources that support diverse tropical vertebrate frugivore communities. Planting or conserving large fig trees, such as stranglers, have therefore been proposed for enhancing urban biodiversity. We compared the diversity and community structure of bird assemblages on strangler figs with non‐fig urban trees as well as between the fruiting and non‐fruiting fig trees in an urban setting in Singapore. The total bird abundance across all the fig trees when in fruit was 4.5‐fold higher than on non‐fig trees and 3.5‐fold higher than when the same fig trees were not fruiting, but only attracted two more species. On individual trees, after accounting for the presence of mistletoes, tree height, the area covered by buildings, road lane density, and the distance to natural vegetation, mean diversity was not different between non‐fig trees and fig trees when they were not in fruit. On the other hand, when fruiting, each fig tree on average had 1.4 more species, 3 more counts of non‐native birds, and 1.6 more counts of insectivorous birds than when not fruiting. There was significant compositional turnover between non‐fig trees and non‐fruiting fig trees, while community dispersion was significantly lower among fig trees in fruit. Our results demonstrate that fig trees provide fruit and non‐fruit resources for birds in an urban landscape but do not necessarily support more diverse total bird assemblages than non‐fig trees. Instead, bird communities on fruiting urban figs would be highly homogeneous and dominated by a few species. Abstract in Malay is available with online material.     

Towards a global database of weed risk assessments: a test of transferability for the tropics

Worldwide spread and establishment of alien plant species continues to accelerate and damage ecological and agricultural systems. Early warning and prevention of high-risk introductions is the most cost-effective approach to minimise losses while maximising benefits, and the Australian Weed Risk Assessment (A-WRA) system has been the most well-developed and successful predictive scheme. However, any system would be limited if the results or scores were confined to the locality of assessment. We compiled A-WRA scores conducted in four tropical to sub-tropical regions and tested the accuracy of these scores for predicting naturalisations for a separate well-documented, equatorial, exotic flora where weed risk assessments have never been conducted. Receiver Operating Characteristic (ROC) curves reflect high accuracies of predictions, comparable to those in other studies. No significant differences in accuracy were found between each regional subset and the compiled set of scores. Our results show that A-WRA scores assessed at one locality can be used for others of similar climate, increasing the utility of every species’ assessment. A global database of A-WRA scores would enable rapid local decision-making in border controls on imported plant species. A growing record of species assessments would also facilitate monitoring evolutionary and ecological aspects of invasive species.     

Inflammatory aetiology of human myometrial activation tested using directed graphs

There are three main hypotheses for the activation of the human uterus at labour: functional progesterone withdrawal, inflammatory stimulation, and oxytocin receptor activation. To test these alternatives we have taken information and data from the literature to develop causal pathway models for the activation of human myometrium. The data provided quantitative RT-PCR results on key genes from samples taken before and during labour. Principal component analysis showed that pre-labour samples form a homogenous group compared to those during labour. We therefore modelled the alternative causal pathways in non-laboring samples using directed graphs and statistically compared the likelihood of the different models using structural equations and D-separation approaches. Using the computer program LISREL, inflammatory activation as a primary event was highly consistent with the data (p = 0.925), progesterone withdrawal, as a primary event, is plausible (p = 0.499), yet comparatively unlikely, oxytocin receptor mediated initiation is less compatible with the data (p = 0.091). DGraph, a software program that creates directed graphs, produced similar results (p= 0.684, p= 0.280, and p = 0.04, respectively). This outcome supports an inflammatory aetiology for human labour. Our results demonstrate the value of directed graphs in determining the likelihood of causal relationships in biology in situations where experiments are not possible.     

Protein subcellular localization prediction using a hybrid of similarity search and error-correcting output code techniques that produces interpretable results

In silico prediction of protein subcellular localization based on amino acid sequence can reveal valuable information about the protein's innate roles in the cell. Unfortunately, such prediction is made difficult because of complex protein sorting signals. Some prediction methods are based on searching for similar proteins with known localization, assuming that known homologs exist. However, it may not perform well on proteins with no known homolog. In contrast, machine learning-based approaches attempt to infer a predictive model that describes the protein sorting signals. Alas, in doing so, it does not take advantage of known homologs (if they exist) by doing a simple "table lookup". Here, we capture the best of both worlds by combining both approaches. On a dataset with 12 locations, similarity-based and machine learning independently achieve an accuracy of 83.8% and 72.6%, respectively. Our hybrid approach yields an improved accuracy of 85.9%. We compared our method with three other methods' published results. For two of the methods, we used their published datasets for comparison. For the third we used the 12 location dataset. The Error Correcting Output Code algorithm was used to construct our predictive model. This algorithm gives attention to all the classes regardless of number of instances and led to high accuracy among each of the classes and a high prediction rate overall. We also illustrated how the machine learning classifier we use, built over a meaningful set of features can produce interpretable rules that may provide valuable insights into complex protein sorting mechanisms.     

Pitcher plant facilitates prey capture in a sympatric congener

Carnivorous plants avoid below-ground competition for nitrogen by utilizing an alternative nitrogen resource—invertebrate prey, but it remains unclear if sympatric carnivorous plants compete for prey resources. The aim of this study was to investigate if exploitative prey-resource competition occurs between the two sympatric pitcher plant species, Nepenthes rafflesiana and N. gracilis in Singapore. We first investigated if prey-resource partitioning occurs between these two species, and then investigated niche shift in N. gracilis by examining its pitcher contents along an in situ gradient of N. rafflesiana interspecific competition. Our results showed clear evidence of resource partitioning between the two species, but contrary to the expectation of competition, proximity to N. rafflesiana pitchers correlated with higher total prey numbers in N. gracilis pitchers. Our multivariate model of prey assemblages further suggested that N. rafflesiana facilitates N. gracilis prey capture, especially in several ant taxa that are trapped by both species. Concurrently, we found strong evidence for intraspecific competition between N. gracilis pitchers, suggesting that prey resources are exhaustible by pitcher-predation. Our results show that resource partitioning can be associated with facilitative interactions, instead of competition as is usually assumed. Facilitation is more typically expected between phylogenetically distant species, but divergences in resource acquisition strategies can permit facilitation between congeners.     

Activation of hypothalamic RIP‐Cre neurons promotes beiging of WAT via sympathetic nervous system

Activation of brown adipose tissue (BAT) and beige fat by cold increases energy expenditure. Although their activation is known to be differentially regulated in part by hypothalamus, the underlying neural pathways and populations remain poorly characterized. Here, we show that activation of rat‐insulin‐promoter‐Cre (RIP‐Cre) neurons in ventromedial hypothalamus (VMH) preferentially promotes recruitment of beige fat via a selective control of sympathetic nervous system (SNS) outflow to subcutaneous white adipose tissue (sWAT), but has no effect on BAT. Genetic ablation of APPL2 in RIP‐Cre neurons diminishes beiging in sWAT without affecting BAT, leading to cold intolerance and obesity in mice. Such defects are reversed by activation of RIP‐Cre neurons, inactivation of VMH AMPK, or treatment with a β3‐adrenergic receptor agonist. Hypothalamic APPL2 enhances neuronal activation in VMH RIP‐Cre neurons and raphe pallidus, thereby eliciting SNS outflow to sWAT and subsequent beiging. These data suggest that beige fat can be selectively activated by VMH RIP‐Cre neurons, in which the APPL2–AMPK signaling axis is crucial for this defending mechanism to cold and obesity.     

IL-1β, IL-6, and RANTES as Biomarkers of Chikungunya Severity

Background

Little is known about the immunopathogenesis of Chikungunya virus. Circulating levels of immune mediators and growth factors were analyzed from patients infected during the first Singaporean Chikungunya fever outbreak in early 2008 to establish biomarkers associated with infection and/or disease severity.

Methods and Findings

Adult patients with laboratory-confirmed Chikungunya fever infection, who were referred to the Communicable Disease Centre/Tan Tock Seng Hospital during the period from January to February 2008, were included in this retrospective study. Plasma fractions were analyzed using a multiplex-microbead immunoassay. Among the patients, the most common clinical features were fever (100%), arthralgia (90%), rash (50%) and conjunctivitis (40%). Profiles of 30 cytokines, chemokines, and growth factors were able to discriminate the clinical forms of Chikungunya from healthy controls, with patients classified as non-severe and severe disease. Levels of 8 plasma cytokines and 4 growth factors were significantly elevated. Statistical analysis showed that an increase in IL-1β, IL-6 and a decrease in RANTES were associated with disease severity.

Conclusions

This is the first comprehensive report on the production of cytokines, chemokines, and growth factors during acute Chikungunya virus infection. Using these biomarkers, we were able to distinguish between mild disease and more severe forms of Chikungunya fever, thus enabling the identification of patients with poor prognosis and monitoring of the disease.