Measurement of T1 of the ultrashort T2* components in white matter of the brain at 3T.

Recent research demonstrates that white matter of the brain contains not only long T2 components, but a minority of ultrashort T2* components. Adiabatic inversion recovery prepared dual echo ultrashort echo time (IR-dUTE) sequences can be used to selectively image the ultrashort T2* components in white matter of the brain using a clinical whole body scanner. The T2*s of the ultrashort T2* components can be quantified using mono-exponential decay fitting of the IR-dUTE signal at a series of different TEs. However, accurate T1 measurement of the ultrashort T2* components is technically challenging. Efficient suppression of the signal from the majority of long T2 components is essential for robust T1 measurement. In this paper we describe a novel approach to this problem based on the use of IR-dUTE data acquisitions with different TR and TI combinations to selectively detect the signal recovery of the ultrashort T2* components. Exponential recovery curve fitting provides efficient T1 estimation, with minimized contamination from the majority of long T2 components. A rubber phantom and a piece of bovine cortical bone were used for validation of this approach. Six healthy volunteers were studied. An averaged T2* of 0.32 ± 0.09 ms, and a short mean T1 of 226 ± 46 ms were demonstrated for the healthy volunteers at 3T

A search engine to identify pathway genes from expression data on multiple organisms

<p>Abstract</p> <p>Background</p> <p>The completion of several genome projects showed that most genes have not yet been characterized, especially in multicellular organisms. Although most genes have unknown functions, a large collection of data is available describing their transcriptional activities under many different experimental conditions. In many cases, the coregulatation of a set of genes across a set of conditions can be used to infer roles for genes of unknown function.</p> <p>Results</p> <p>We developed a search engine, the Multiple-Species Gene Recommender (MSGR), which scans gene expression datasets from multiple organisms to identify genes that participate in a genetic pathway. The MSGR takes a query consisting of a list of genes that function together in a genetic pathway from one of six organisms: <it>Homo sapiens</it>, <it>Drosophila melanogaster</it>, <it>Caenorhabditis elegans</it>, <it>Saccharomyces cerevisiae</it>, <it>Arabidopsis thaliana</it>, and <it>Helicobacter pylori</it>. Using a probabilistic method to merge searches, the MSGR identifies genes that are significantly coregulated with the query genes in one or more of those organisms. The MSGR achieves its highest accuracy for many human pathways when searches are combined across species. We describe specific examples in which new genes were identified to be involved in a neuromuscular signaling pathway and a cell-adhesion pathway.</p> <p>Conclusion</p> <p>The search engine can scan large collections of gene expression data for new genes that are significantly coregulated with a pathway of interest. By integrating searches across organisms, the MSGR can identify pathway members whose coregulation is either ancient or newly evolved.</p

Aligned electrospun nanofibers specify the direction of dorsal root ganglia neurite growth

Nerve injury, a significant cause of disability, may be treated more effectively using nerve guidance channels containing longitudinally aligned fibers. Aligned, electrospun nanofibers direct the neurite growth of immortalized neural stem cells, demonstrating potential for directing regenerating neurites. However, no study of neurite guidance on these fibers has yet been performed with primary neurons. Here, we examined neurites from dorsal root ganglia explants on electrospun poly- L -lactate nanofibers of high, intermediate, and random alignment. On aligned fibers, neurites grew radially outward from the ganglia and turned to follow the fibers upon contact. Neurite guidance was robust, with neurites never leaving the fibers to grow on the surrounding cover slip. To compare the alignment of neurites to that of the nanofiber substrates, Fourier methods were used to quantify the alignment. Neurite alignment, however striking, was inferior to fiber alignment on all but the randomly aligned fibers. Neurites on highly aligned substrates were 20 and 16% longer than neurites on random and intermediate fibers, respectively. Schwann cells on fibers assumed a very narrow morphology compared to those on the surrounding coverslip. The robust neurite guidance demonstrated here is a significant step toward the use of aligned, electrospun nanofibers for nerve regeneration. © 2007 Wiley Periodicals, Inc. J Biomed Mater Res, 2007Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/57401/1/31285_ftp.pd

Preparation of anti-vicinal amino alcohols: asymmetric synthesis of D-erythro-Sphinganine, (+)-spisulosine and D-ribo-phytosphingosine

Two variations of the Overman rearrangement have been developed for the highly selective synthesis of anti-vicinal amino alcohol natural products. A MOM-ether directed palladium(II)-catalyzed rearrangement of an allylic trichloroacetimidate was used as the key step for the preparation of the protein kinase C inhibitor D-erythro-sphinganine and the antitumor agent (+)-spisulosine, while the Overman rearrangement of chiral allylic trichloroacetimidates generated by asymmetric reduction of an alpha,beta-unsaturated methyl ketone allowed rapid access to both D-ribo-phytosphingosine and L-arabino-phytosphingosine

LINCS Canvas Browser: interactive web app to query, browse and interrogate LINCS L1000 gene expression signatures

For the Library of Integrated Network-based Cellular Signatures (LINCS) project many gene expression signatures using the L1000 technology have been produced. The L1000 technology is a cost-effective method to profile gene expression in large scale. LINCS Canvas Browser (LCB) is an interactive HTML5 web-based software application that facilitates querying, browsing and interrogating many of the currently available LINCS L1000 data. LCB implements two compacted layered canvases, one to visualize clustered L1000 expression data, and the other to display enrichment analysis results using 30 different gene set libraries. Clicking on an experimental condition highlights gene-sets enriched for the differentially expressed genes from the selected experiment. A search interface allows users to input gene lists and query them against over 100 000 conditions to find the top matching experiments. The tool integrates many resources for an unprecedented potential for new discoveries in systems biology and systems pharmacology. The LCB application is available at http://www.maayanlab.net/LINCS/LCB. Customized versions will be made part of the http://lincscloud.org and http://lincs.hms.harvard.edu websites

Herpes simplex virus infections among rural residents in eastern China

<p>Abstract</p> <p>Background</p> <p>Herpes simplex virus (HSV) has two types: HSV-1 and HSV-2. Both infect epithelial cells and establish latent infections in neurons causing an infection that persists for life. Information on age- and gender-specific seroprevalence of HSV-1 and HSV-2 is valuable for understanding HSV transmission dynamics and designing population-based prevention and intervention programs for HSV. However, such information is not available for China.</p> <p>Methods</p> <p>Cryopreserved serum samples of all subjects aged 5 to 60 years from two randomly selected rural villages in Zhejiang province in Eastern China who had participated in the China national seroepidemiological survey of hepatitis B virus (HBV) infection conducted in 2006 were tested. Seroprevalence of HSV-1 and HSV-2 infections were determined by type-specific IgG antibody tests using an ELISA technique. Their 95% confidence intervals adjusted for the sampling fraction were calculated according to the Clopper-Pearson method.</p> <p>Results</p> <p>A total of 2,141 residents participated in the survey, with a response rate of 82.3%. HSV-1 seroprevalence was 92.0% overall, 89.1% for males and 94.2% for females. HSV-1 seroprevalence was 61.6% among children aged 5-9 years, 90.3% among 25-29 years, and nearly 100% among those aged > = 40 years. HSV-2 seroprevalence was 13.2% overall, 10.5% for males and 15.3% for females. No children aged 5-14 years were HSV-2 positive, and HSV-2 seroprevalence was 7.1% among 15-19 years and peaked at 24.3% among those aged 45-49 years. Neither HSV-1 nor HSV-2 infections were significantly different by gender. About 11.8% of study subjects were co-infected with both types of HSV. Among 549 participating couples, 8.6% were HSV-1 serodiscordant and 11.8% were HSV-2 serodiscordant. No one tested positive for HIV. The overall prevalence of HBsAg was 16.2%, 16.9% for males and 15.4% for females.</p> <p>Conclusions</p> <p>HSV-1 was highly prevalent among all rural residents aged between 5-60 years in Eastern China, whereas HSV-2 was prevalent among sexually active people. HSV-1 and HSV-2 have different transmission modes and dynamics. Future HSV prevention and control programs in China should be type specific.</p

Video and Synthetic MRI Pre-training of 3D Vision Architectures for Neuroimage Analysis

Transfer learning represents a recent paradigm shift in the way we build artificial intelligence (AI) systems. In contrast to training task-specific models, transfer learning involves pre-training deep learning models on a large corpus of data and minimally fine-tuning them for adaptation to specific tasks. Even so, for 3D medical imaging tasks, we do not know if it is best to pre-train models on natural images, medical images, or even synthetically generated MRI scans or video data. To evaluate these alternatives, here we benchmarked vision transformers (ViTs) and convolutional neural networks (CNNs), initialized with varied upstream pre-training approaches. These methods were then adapted to three unique downstream neuroimaging tasks with a range of difficulty: Alzheimer's disease (AD) and Parkinson's disease (PD) classification, "brain age" prediction. Experimental tests led to the following key observations: 1. Pre-training improved performance across all tasks including a boost of 7.4% for AD classification and 4.6% for PD classification for the ViT and 19.1% for PD classification and reduction in brain age prediction error by 1.26 years for CNNs, 2. Pre-training on large-scale video or synthetic MRI data boosted performance of ViTs, 3. CNNs were robust in limited-data settings, and in-domain pretraining enhanced their performances, 4. Pre-training improved generalization to out-of-distribution datasets and sites. Overall, we benchmarked different vision architectures, revealing the value of pre-training them with emerging datasets for model initialization. The resulting pre-trained models can be adapted to a range of downstream neuroimaging tasks, even when training data for the target task is limited

Sustainable polyethylene fabrics with engineered moisture transport for passive cooling

Polyethylene (PE) has emerged recently as a promising polymer for incorporation in wearable textiles owing to its high infrared transparency and tuneable visible opacity, which allows the human body to cool via thermal radiation, potentially saving energy on building refrigeration. Here, we show that single-material PE fabrics may offer a sustainable, high-performance alternative to conventional textiles, extending beyond radiative cooling. PE fabrics exhibit ultra-light weight, low material cost and recyclability. Industrial materials sustainability (Higg) index calculations predict a low environmental footprint for PE fabrics in the production phase. We engineered PE fibres, yarns and fabrics to achieve efficient water wicking and fast-drying performance which, combined with their excellent stain resistance, offer promise in reducing energy and water consumption as well as the environmental footprint of PE textiles in their use phase. Unlike previously explored nanoporous PE materials, the high-performance PE fabrics in this study are made from fibres melt spun and woven on standard equipment used by the textile industry worldwide and do not require any chemical coatings. We further demonstrate that these PE fibres can be dry coloured during fabrication, resulting in dramatic water savings without masking the PE molecular fingerprints scanned during the automated recycling process.The textile industry is one of the largest polluters. Here the authors show that polyethylene is a sustainable alternative textile with water wicking and fast-drying performance. The fabrication of polyethylene fabrics is compatible with standard equipment and could be dry-coloured, further reducing water consumption

World squid fisheries

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