Recent studies have indicated that the hematopoietic stem/progenitor cell (HSPC) niche, consisting of two major crucial components, namely osteoblasts (OBs) and mesenchymal stromal cells (MSCs), is responsible for the fate of HSPCs. Thus, closely mimicking the HSPC niche ex vivo may be an efficient strategy with which to develop new culture strategies to specifically regulate the balance between HSPC self-renewal and proliferation. The aim of this study was to establish a novel HSPC three-dimensional culture system by co-culturing bone marrow-derived MSCs and OBs differentiated from MSCs without any cytokines as feeder cells and applying bio-derived bone from human femoral metaphyseal portion as the scaffold. Scanning electron microscopy revealed the excellent biocompatibility of bio-derived bone with bone marrow-derived MSCs and OBs differentiated from MSCs. Western blot analysis revealed that many cytokines, which play key roles in HSPC regulation, were comprehensively secreted, while ELISA revealed that extracellular matrix molecules were also highly expressed. Hoechst 33342/propidium iodide fluorescence staining proved that our system could be used to supply a long-term culture of HSPCs. Flow cytometric analysis and qPCR of p21 expression demonstrated that our system significantly promoted the self-renewal and ex vivo expansion of HSPCs. Colony-forming unit (CFU) and long-term culture-initiating cell (LTC-IC) assays confirmed that our system has the ability for both the expansion of CD34+ hematopoietic stem cells (HPCs) and the maintenance of a primitive cell subpopulation of HSCs. The severe-combined immunodeficient mouse repopulating cell assay revealed the promoting effects of our system on the expansion of long-term primitive transplantable HSCs. In conclusion, our system may be a more comprehensive and balanced system which not only promotes the self-renewal and ex vivo expansion of HSPCs, but also maintains primitive HPCs with superior phenotypic and functional attributes.

This letter investigates the effect of imperfect channel state information (CSI) on the performance of radio resource management for a downlink multi-user OFDMA system. It is shown that the imperfect CSI introduces a signal-and-power dependent noise term, which makes the symbol error rate (SER) constellation-point dependent, and yields an error floor on the SER. In addition, a two-step multi-user channel, power and constellation allocation algorithm is proposed to maximize the total network throughput.

We conducted a systematic investigation of the reflectance diffuse optical tomography using continuous wave (CW) measurements and nonlinear reconstruction algorithms. We illustrated and suggested how to fine-tune the nonlinear reconstruction methods in order to optimize target localization with depth-adaptive regularizations, reduce boundary noises in the reconstructed images using a logarithm based objective function, improve reconstruction quantification using transport models, and resolve crosstalk problems between absorption and scattering contrasts with the CW reflectance measurements. The upgraded nonlinear reconstruction algorithms were evaluated with a series of numerical and experimental tests, which show the potentials of the proposed approaches for imaging both absorption and scattering contrasts in the deep targets with enhanced image quality.

Motivation

Genome-wide fitness is an emerging type of high-throughput biological data generated for individual organisms by creating libraries of knockouts, subjecting them to broad ranges of environmental conditions, and measuring the resulting clone-specific fitnesses. Since fitness is an organism-scale measure of gene regulatory network behaviour, it may offer certain advantages when insights into such phenotypical and functional features are of primary interest over individual gene expression. Previous works have shown that genome-wide fitness data can be used to uncover novel gene regulatory interactions, when compared with results of more conventional gene expression analysis. Yet, to date, few algorithms have been proposed for systematically using genome-wide mutant fitness data for gene regulatory network inference.

Results

In this article, we describe a model and propose an inference algorithm for using fitness data from knockout libraries to identify underlying gene regulatory networks. Unlike most prior methods, the presented approach captures not only structural, but also dynamical and non-linear nature of biomolecular systems involved. A state-space model with non-linear basis is used for dynamically describing gene regulatory networks. Network structure is then elucidated by estimating unknown model parameters. Unscented Kalman filter is used to cope with the non-linearities introduced in the model, which also enables the algorithm to run in on-line mode for practical use. Here, we demonstrate that the algorithm provides satisfying results for both synthetic data as well as empirical measurements of GAL network in yeast Saccharomyces cerevisiae and TyrR-LiuR network in bacteria Shewanella oneidensis.

Availability

MATLAB code and datasets are available to download at http://www.duke.edu/∼lw174/Fitness.zip and http://genomics.lbl.gov/supplemental/fitness-bioinf/

We conducted a systematic investigation of the reflectance diffuse optical tomography using continuous wave (CW) measurements and nonlinear reconstruction algorithms. We illustrated and suggested how to fine-tune the nonlinear reconstruction methods in order to optimize target localization with depth-adaptive regularizations, reduce boundary noises in the reconstructed images using a logarithm based objective function, improve reconstruction quantification using transport models, and resolve crosstalk problems between absorption and scattering contrasts with the CW reflectance measurements. The upgraded nonlinear reconstruction algorithms were evaluated with a series of numerical and experimental tests, which show the potentials of the proposed approaches for imaging both absorption and scattering contrasts in the deep targets with enhanced image quality.

Background

Autistic individuals exhibit atypical patterns of sensory processing that are known to be related to quality of life, but which are also highly heterogeneous. Previous investigations of this heterogeneity have ordinarily used questionnaires and have rarely investigated sensory processing in typical development (TD) alongside autism spectrum development (ASD).

Methods

The present study used hierarchical clustering in a large sample to identify subgroups of young autistic and typically developing children based on the normalized global field power (GFP) of their event-related potentials (ERPs) to auditory stimuli of four different loudness intensities (50, 60, 70, 80 dB SPL): that is, based on an index of the relative strengths of their neural responses across these loudness conditions.

Results

Four clusters of participants were defined. Normalized GFP responses to sounds of different intensities differed strongly across clusters. There was considerable overlap in cluster assignments of autistic and typically developing participants, but autistic participants were more likely to display a pattern of relatively linear increases in response strength accompanied by a disproportionately strong response to 70 dB stimuli. Autistic participants displaying this pattern trended towards obtaining higher scores on assessments of cognitive abilities. There was also a trend for typically developing participants to disproportionately fall into a cluster characterized by disproportionately/nonlinearly strong 60 dB responses. Greater auditory distractibility was reported among autistic participants in a cluster characterized by disproportionately strong responses to the loudest (80 dB) sounds, and furthermore, relatively strong responses to loud sounds were correlated with auditory distractibility. This appears to provide evidence of coinciding behavioral and neural sensory atypicalities.

Limitations

Replication may be needed to verify exploratory results. This analysis does not address variability related to classical ERP latencies and topographies. The sensory questionnaire employed was not specifically designed for use in autism. Hearing acuity was not measured. Variability in sensory responses unrelated to loudness is not addressed, leaving room for additional research.

Conclusions

Taken together, these data demonstrate the broader benefits of using electrophysiology to explore individual differences. They illuminate different neural response patterns and suggest relationships between sensory neural responses and sensory behaviors, cognitive abilities, and autism diagnostic status.

Finding conserved motifs in genomic sequences represents one of essential bioinformatic problems. However, achieving high discovery performance without imposing substantial auxiliary constraints on possible motif features remains a key algorithmic challenge. This work describes BAMBI-a sequential Monte Carlo motif-identification algorithm, which is based on a position weight matrix model that does not require additional constraints and is able to estimate such motif properties as length, logo, number of instances and their locations solely on the basis of primary nucleotide sequence data. Furthermore, should biologically meaningful information about motif attributes be available, BAMBI takes advantage of this knowledge to further refine the discovery results. In practical applications, we show that the proposed approach can be used to find sites of such diverse DNA-binding molecules as the cAMP receptor protein (CRP) and Din-family site-specific serine recombinases. Results obtained by BAMBI in these and other settings demonstrate better statistical performance than any of the four widely-used profile-based motif discovery methods: MEME, BioProspector with BioOptimizer, SeSiMCMC and Motif Sampler as measured by the nucleotide-level correlation coefficient. Additionally, in the case of Din-family recombinase target site discovery, the BAMBI-inferred motif is found to be the only one functionally accurate from the underlying biochemical mechanism standpoint. C++ and Matlab code is available at http://www.ee.columbia.edu/~guido/BAMBI or http://genomics.lbl.gov/BAMBI/.

Although prior studies have compared sensory event-related potential (ERP) responses between groups of autistic and typically-developing participants, it is unclear how heterogeneity contributes to the results of these studies. The present study used examined individual differences in these responses. 130 autistic children and 81 typically-developing children, aged between 2 and 5 years, listened to tones at four identity levels while 61-channel electroencephalography was recorded. Hierarchical clustering was used to group participants based on rescaled ERP topographies between 51 and 350 ms. The hierarchical clustering analysis revealed substantial heterogeneity. Some of the seven clusters defined in this analysis were characterized by prolonged fronto-central positivities and/or weak or absent N2 negativities. However, many other participants fell into clusters in which N2 responses were present at varying latencies. Atypical response morphologies such as absent N2 responses and/or prolonged positive-going responses found in some autistic participants may account for prior research findings of attenuated N2 amplitudes in autism. However, there was also considerable overlap between groups, with participants of both groups appearing in all clusters. These results emphasize the utility of using clustering to explore individual differences in brain responses, which can expand on and clarify the results of analyses of group mean differences.

In Arabidopsis, NPR1 is a key transcriptional coregulator of systemic acquired resistance. Upon pathogen challenge, NPR1 translocates from the cytoplasm to the nucleus, in which it interacts with TGA-bZIP transcription factors to activate the expression of several pathogenesis-related (PR) genes. In a screen of a yeast two-hybrid library from wheat leaves infected with Puccinia striiformis f. sp. tritici, we identified a conserved rust protein that interacts with wheat NPR1 and named it PNPi (for Puccinia NPR1 interactor). PNPi interacts with the NPR1/NIM1-like domain of NPR1 via its C-terminal DPBB_1 domain. Using bimolecular fluorescence complementation assays, we detected the interaction between PNPi and wheat NPR1 in the nucleus of Nicotiana benthamiana protoplasts. A yeast three-hybrid assay showed that PNPi interaction with NPR1 competes with the interaction between wheat NPR1 and TGA2.2. In barley transgenic lines overexpressing PNPi, we observed reduced induction of multiple PR genes in the region adjacent to Pseudomonas syringae pv. tomato DC3000 infection. Based on these results, we hypothesize that PNPi has a role in manipulating wheat defense response via its interactions with NPR1.