A central question in the evolutionary diversification of large, widespread, mobile mammals is how substantial differentiation can arise, particularly in the absence of topographic or habitat barriers to dispersal. All extant giraffes (Giraffa camelopardalis) are currently considered to represent a single species classified into multiple subspecies. However, geographic variation in traits such as pelage pattern is clearly evident across the range in sub-Saharan Africa and abrupt transition zones between different pelage types are typically not associated with extrinsic barriers to gene flow, suggesting reproductive isolation.

Evidence is accumulating that pesticide self-poisoning is one of the most commonly used methods of suicide worldwide, but the magnitude of the problem and the global distribution of these deaths is unknown.

Developing diagnostic scores for prediction of clinical outcomes uses medical knowledge regarding which variables are most important and empirical/statistical learning to find the functional form of these covariates that provides the most accurate prediction (eg, highest specificity and sensitivity). Given the variables chosen by the clinician as most relevant or available due to limited resources, the job is a purely statistical one: which model, among competitors, provides the most accurate prediction of clinical outcomes, where accuracy is relative to some loss function. An optimal algorithm for choosing a model follows: (1) provides a flexible, sequence of models, which can 'twist and bend' to fit the data and (2) use of a validation procedure that optimally balances bias/variance by choosing models of the right size (complexity). We propose a solution to creating diagnostic scores that, given the available variables, will appropriately trade-off model complexity with variability of estimation; the algorithm uses a combination of machine learning, logistic regression (POLYCLASS) and cross-validation. For example, we apply the procedure to data collected from stroke victims in a rural clinic in India, where the outcome of interest is death within 30 days. A quick and accurate diagnosis of stroke is important for immediate resuscitation. Equally important is giving patients and their families an indication of the prognosis. Accurate predictions of clinical outcomes made soon after the onset of stroke can also help choose appropriate supporting treatment decisions. Severity scores have been created in developed nations (for instance, Guy's Prognostic Score, Canadian Neurological Score, and the National Institute of Health Stroke Scale). However, we propose a method for developing scores appropriate to local settings in possibly very different medical circumstances. Specifically, we used a freely available and easy to use exploratory regression technique (POLYCLASS) to predict 30-day mortality following stroke in a rural Indian population and compared the accuracy of the technique with these existing stroke scales, resulting in more accurate prediction than the existing scores (POLYCLASS sensitivity and specificity of 90% and 76%, respectively). This method can easily be extrapolated to different clinical settings and for different disease outcomes. In addition, the software and algorithms used are open-source (free) and we provide the code in the appendix.

The Cladosporium herbarum complex comprises five species for which Davidiella teleomorphs are known. Cladosporium herbarum s. str. (D. tassiana), C. macrocarpum (D. macrocarpa) and C. bruhnei (D. allicina) are distinguishable by having conidia of different width, and by teleomorph characters. Davidiella variabile is introduced as teleomorph of C. variabile, a homothallic species occurring on Spinacia, and D. macrospora is known to be the teleomorph of C. iridis on Iris spp. The C. herbarum complex combines low molecular distance with a high degree of clonal or inbreeding diversity. Entities differ from each other by multilocus sequence data and by phenetic differences, and thus can be interpreted to represent individual taxa. Isolates of the C. herbarum complex that were formerly associated with opportunistic human infections, cluster with C. bruhnei. Several species are newly described from hypersaline water, namely C. ramotenellum, C. tenellum, C. subinflatum, and C. herbaroides. Cladosporium pseudiridis collected from Iris sp. in New Zealand, is also a member of this species complex and shown to be distinct from C. iridis that occurs on this host elsewhere in the world. A further new species from New Zealand is C. sinuosum on Fuchsia excorticata. Cladosporium antarcticum is newly described from a lichen, Caloplaca regalis, collected in Antarctica, and C. subtilissimum from grape berries in the U.S.A., while the new combination C. ossifragi, the oldest valid name of the Cladosporium known from Narthecium in Europe, is proposed. Standard protocols and media are herewith proposed to facilitate future morphological examination of Cladosporium spp. in culture, and neotypes or epitypes are proposed for all species treated.

How do neurons in a decision circuit integrate time-varying signals, in favor of or against alternative choice options? To address this question, we used a recurrent neural circuit model to simulate an experiment in which monkeys performed a direction-discrimination task on a visual motion stimulus. In a recent study, it was found that brief pulses of motion perturbed neural activity in the lateral intraparietal area (LIP), and exerted corresponding effects on the monkey's choices and response times. Our model reproduces the behavioral observations and replicates LIP activity which, depending on whether the direction of the pulse is the same or opposite to that of a preferred motion stimulus, increases or decreases persistently over a few hundred milliseconds. Furthermore, our model accounts for the observation that the pulse exerts a weaker influence on LIP neuronal responses when the pulse is late relative to motion stimulus onset. We show that this violation of time-shift invariance (TSI) is consistent with a recurrent circuit mechanism of time integration. We further examine time integration using two consecutive pulses of the same or opposite motion directions. The induced changes in the performance are not additive, and the second of the paired pulses is less effective than its standalone impact, a prediction that is experimentally testable. Taken together, these findings lend further support for an attractor network model of time integration in perceptual decision making.

Hypoxia regulates the local expression of angiotensin-generating system in the rat carotid body and the me-tabolite angiotensin IV (Ang IV) may be involved in the modulation of carotid body function. We tested the hypothesis that Ang IV-binding angiotensin AT(4) receptors play a role in the adaptive change of the carotid body in hypoxia. The expression and localization of Ang IV-binding sites and AT(4) receptors in the rat carotid bodies were studied with histochemistry. Specific fluorescein-labeled Ang IV binding sites and positive staining of AT(4) immunoreactivity were mainly found in lobules in the carotid body. Double-labeling study showed the AT(4) receptor was localized in glomus cells containing tyrosine hydroxylase, suggesting the expression in the chemosensitive cells. Intriguingly, the Ang IV-binding and AT(4) immunoreactivity were more intense in the carotid body of chronically hypoxic (CH) rats (breathing 10% oxygen for 4 weeks) than the normoxic (Nx) control. Also, the protein level of AT(4) receptor was doubled in the CH comparing with the Nx group, supporting an upregulation of the expression in hypoxia. To examine if Ang IV induces intracellular Ca(2+) response in the carotid body, cytosolic calcium ([Ca(2+)](i)) was measured by spectrofluorimetry in fura-2-loaded glomus cells dissociated from CH and Nx carotid bodies. Exogenous Ang IV elevated [Ca(2+)](i) in the glomus cells and the Ang IV response was significantly greater in the CH than the Nx group. Hence, hypoxia induces an upregulation of the expression of AT(4) receptors in the glomus cells of the carotid body with an increase in the Ang IV-induced [Ca(2+)]i elevation. This may be an additional pathway enhancing the Ang II action for the activation of chemoreflex in the hypoxic response during chronic hypoxia.

In the central nervous system, fibroblast growth factor (FGF)-20 has been reported to act preferentially on midbrain dopaminergic neurons. It also promotes the dopaminergic differentiation of stem cells. We have analyzed the effects of FGF-20 on human embryonic stem cells (hESCs) differentiation into dopaminergic neurons. We induced neuronal differentiation of hESCs by co-culturing those with PA6 mouse stromal cells for 3 weeks. When we supplemented the culture medium with FGF-20, the number of tyrosine hydroxylase (TH)-expressing neurons increased fivefold, from 3% to 15% of the hESC-derived cells. The cultured cells also expressed other midbrain dopaminergic markers (PITX3, En1, Msx1, and Aldh1), suggesting that some had differentiated into midbrain dopaminergic neurons. We observed no effect of FGF-20 on the size of the soma area or neurite length of the TH-immunopositive neurons. Regardless of whether FGF-20 had been added or not, 17% of the hESC-derived cells expressed the pan-neuronal marker b-III-Tubulin. The proportion of proliferating cells positive for Ki-67 was also not affected by FGF-20 (7% of the hESC-derived cells). By contrast, after 3 weeks in culture FGF-20 significantly reduced the proportion of cells undergoing cell death, as revealed by immunoreactivity for cleaved caspase-8, Bcl-2 associated X protein (BAX) and cleaved caspase-3 (2.5% to 1.2% of cleaved caspase-3-positive cells out of the hESC-derived cells). Taken together, our results indicate that FGF-20 specifically increases the yield of dopaminergic neurons from hESCs grown on PA6 feeder cells and at least part of this effect is due to a reduction in cell death.

Sensory discrimination requires distributed arrays of processing units. In the olfactory bulb, the processing units for odor discrimination are believed to involve dendrodendritic synaptic interactions between mitral and granule cells. There is increasing anatomical evidence that these cells are organized in columns, and that the columns processing a given odor are arranged in widely distributed arrays. Experimental evidence is lacking on the underlying learning mechanisms for how these columns and arrays are formed. To gain insight into these mechanisms, we have used a simplified realistic circuit model to test the hypothesis that distributed connectivity can self-organize through an activity-dependent dendrodendritic synaptic mechanism. The results point to action potentials propagating in the mitral cell lateral dendrites as playing a critical role in this mechanism. The model predicts that columns emerge from the interaction between the local temporal dynamics of the action potentials and the synapses that they activate during dendritic propagation. The results suggest a novel and robust learning mechanism for the development of distributed processing units in a cortical structure.

The gustatory cortex (GC) processes chemosensory and somatosensory information and is involved in learning and anticipation. Previously we found that a subpopulation of GC neurons responded to tastants in a single lick (Stapleton et al., 2006). Here we extend this investigation to determine if small ensembles of GC neurons, obtained while rats received blocks of tastants on a fixed ratio schedule (FR5), can discriminate between tastants and their concentrations after a single 50 muL delivery. In the FR5 schedule subjects received tastants every fifth (reinforced) lick and the intervening licks were unreinforced. The ensemble firing patterns were analyzed with a Bayesian generalized linear model whose parameters included the firing rates and temporal patterns of the spike trains. We found that when both the temporal and rate parameters were included, 12 of 13 ensembles correctly identified single tastant deliveries. We also found that the activity during the unreinforced licks contained signals regarding the identity of the upcoming tastant, which suggests that GC neurons contain anticipatory information about the next tastant delivery. To support this finding we performed experiments in which tastant delivery was randomized within each block and found that the neural activity following the unreinforced licks did not predict the upcoming tastant. Collectively, these results suggest that after a single lick ensembles of GC neurons can discriminate between tastants, that they may utilize both temporal and rate information, and when the tastant delivery is repetitive ensembles contain information about the identity of the upcoming tastant delivery.

Individuals differ in their social status and societies in the extent of social status differences among their members. There is great interest in understanding the key factors that contribute to the establishment of social dominance structures. Given that stress can affect behavior and cognition, we hypothesized that, given equal opportunities to become either dominant or submissive, stress experienced by one of the individuals during their first encounter would determine the long-term establishment of a social hierarchy by acting as a two-stage rocket: (1) by influencing the rank achieved after a social encounter and (2) by facilitating and/or promoting a long-term memory for the specific hierarchy. Using a novel model for the assessment of long-term dominance hierarchies in rats, we present here the first evidence supporting such hypothesis. In control conditions, the social rank established through a first interaction and food competition test between two male rats is not maintained when animals are confronted 1 week later. However, if one of the rats is stressed just before their first encounter, the dominance hierarchy developed on day 1 is still clearly observed 1 week later, with the stressed animal becoming submissive (i.e., looser in competition tests) in both social interactions. Our findings also allow us to propose that stress potentiates a hierarchy-linked recognition memory between "specific" individuals through mechanisms that involve de novo protein synthesis. These results implicate stress among the key mechanisms contributing to create social imbalance and highlight memory mechanisms as key mediators of stress-induced long-term establishment of social rank.

We propose a new computational tool to produce models of biological systems by assembling models from biological parts. Our software not only takes advantage of modularity, but it also enforces standardisation in part characterisation by considering a model of each part. We have used model parts in SBML to design transcriptional networks. Our software is open source, it works in linux and windows platforms, and it could be used to automatically produce models in a server. Our tool not only facilitates model design, but it will also help to promote the establishment of a registry of model parts.

One of the most common modes of secretion of toxins in gram-negative bacteria is via the type three secretion system (TTSS), which enables the toxins to be specifically exported into the host cell. The hilA gene product is a key regulator of the expression of the TTSS located on the pathogenicity island (SPI-1) of Salmonella enterica serovar Typhimurium. It has been proposed earlier that the regulation of HilA expression is via a complex feedforward loop involving the transactivators HilD, HilC and RtsA. In this paper, we have constructed a mathematical model of regulation of hilA-promoter by all the three activators using two feedforward loops. We have modified the model to include additional complexities in regulation such as the proposed positive feedback and cross regulations of the three transactivators. Results of the various models indicate that the basic model involving two Type I coherent feedforward loops with an OR gate is sufficient to explain the published experimental observations. We also discuss two scenarios where the regulation can occur via monomers or heterodimers of the transactivators and propose experiments that can be performed to distinguish the two modes of regulator function.

Neuropathological studies have demonstrated that multiple system atrophy (MSA) produces selective atrophy of the putamen with sparing of the caudate nucleus, while both structures are spared in idiopathic Parkinson's disease (PD). In this study we evaluated the clinical efficacy of using putaminal atrophy in brain MRI to differentiate MSA and PD.

Many kinds of microevolutionary studies require data on multiple polymorphisms in multiple populations. Increasingly, and especially for human populations, multiple research groups collect relevant data and those data are dispersed widely in the literature. ALFRED has been designed to hold data from many sources and make them available over the web. Data are assembled from multiple sources, curated, and entered into the database. Multiple links to other resources are also established by the curators. A variety of search options are available and additional geographic based interfaces are being developed. The database can serve the human anthropologic genetic community by identifying what loci are already typed on many populations thereby helping to focus efforts on a common set of markers. The database can also serve as a model for databases handling similar DNA polymorphism data for other species.

No abstract available

The use of biomarkers derived from radiological images as surrogate end-points in therapeutic cancer clinical trials is well established. DICOM is the ubiquitous standard for the interchange of images for both clinical use as well as research. It also has capabilities for the exchange of image-related information, including categorical and quantitative information derived from images. The use of DICOM Structured Reporting for the encoding and interchange of clinical trial results in a standard manner is reviewed.

The biological interpretation of gene expression microarray results is a daunting challenge. For complex diseases such as cancer, wherein the body of published research is extensive, the incorporation of expert knowledge provides a useful analytical framework. We have previously developed the Exploratory Visual Analysis (EVA) software for exploring data analysis results in the context of annotation information about each gene, as well as biologically relevant groups of genes. We present EVA as a flexible combination of statistics and biological annotation that provides a straightforward visual interface for the interpretation of microarray analyses of gene expression in the most commonly occurring class of brain tumors, glioma. We demonstrate the utility of EVA for the biological interpretation of statistical results by analyzing publicly available gene expression profiles of two important glial tumors. The results of a statistical comparison between 21 malignant, high-grade glioblastoma multiforme (GBM) tumors and 19 indolent, low-grade pilocytic astrocytomas were analyzed using EVA. By using EVA to examine the results of a relatively simple statistical analysis, we were able to identify tumor class-specific gene expression patterns having both statistical and biological significance. Our interactive analysis highlighted the potential importance of genes involved in cell cycle progression, proliferation, signaling, adhesion, migration, motility, and structure, as well as candidate gene loci on a region of Chromosome 7 that has been implicated in glioma. Because EVA does not require statistical or computational expertise and has the flexibility to accommodate any type of statistical analysis, we anticipate EVA will prove a useful addition to the repertoire of computational methods used for microarray data analysis. EVA is available at no charge to academic users and can be found at http://www.epistasis.org.

Alzheimer's disease (AD) is the most common neurodegenerative disease in the developed world. The increasing life expectancy in the last years has led to an increase in the prevalence of this age-related condition and has posed an important medical and social challenge for developed societies. The mainstays of current therapy for AD rely on the cholinergic hypothesis developed more than 20 years ago. These compounds, known as acetylcholinesterase inhibitors (AChEIs), inhibit the cholinesterases and aim at improving the brain synaptic availability of acetylcholine. These drugs have been approved for the treatment of AD based on pivotal clinical trials showing modest symptomatic benefit on cognitive, behavioral, and global measures. Memantine, an NMDA antagonist, has been recently included as a therapeutic option for AD. Memantine can be combined safely with AChEIs for an additional symptomatic benefit. During the last years our understanding of the mechanisms underlying the pathogenesis of AD has markedly expanded. Several putative neuroprotective drugs are thoroughly investigated and many of them have reached the clinical arena. It can be anticipated that some of these drugs will be able to slow/prevent the progression of this condition in the near future.

Critics of the drug safety system have discussed many different potential reforms, ranging from mandatory registration of clinical trials to increasing the power of regulatory agencies, but few have discussed one of the most important ways of enhancing safety: increasing the number of long-term studies of medications. Long-term studies of the risks and benefits of drugs can provide useful information for regulators, healthcare professionals, and patients. Government funding agencies should lead the effort to conduct long-term studies of drugs, but private companies should also be required to lend financial support. Because cost-effectiveness is likely to be an important consideration in conducting this research, funding agencies should focus, at first, on drugs that are used to treat common, chronic conditions.

Mass spectrometry-based analyses are essential tools in the field of biomarker research. However, detection and characterization of plasma low abundance and/or low molecular weight peptides is challenged by the presence of highly abundant proteins, salts and lipids. Numerous strategies have already been tested to reduce the complexity of plasma samples. The aim of this study was to enrich the low molecular weight fraction of rat plasma. To this end, we developed and compared simple protocols based on membrane filtration, solid phase extraction, and a combination of both. As assessed by UV absorbance, an albumin depletion >99% was obtained. The multistep fractionation strategy (including reverse phase HPLC) allowed detection, in a reproducible manner (CV < 30%-35%), of more than 450 peaks below 3000 Da by MALDI-TOF/MS. A MALDI-TOF/MS-determined LOD as low as 1 fmol/muL was obtained, thus allowing nanoLC-Chip/MS/MS identification of spiked peptides representing ~10(-6)% of total proteins, by weight. Signal peptide recovery ranged between 5%-100% according to the spiked peptide considered. Tens of peptide sequence tags from endogenous plasma peptides were also obtained and high confidence identifications of low abundance fibrinopeptide A and B are reported here to show the efficiency of the protocol. It is concluded that the fractionation protocol presented would be of particular interest for future differential (high throughput) analyses of the plasma low molecular weight fraction.