Characterizing the decay of ancient Chinese silk fabrics by microbeam synchrotron radiation diffraction

Scanning synchrotron radiation microdiffraction with an approximately 1 x 1 microm(2) beam has been used as a novel method for characterizing the decay of several T'ang dynasty (618-907 AD) silk fabrics. The crystalline fraction could be visualized based on beta-sheet 210 reflection intensities, extracted by recursive peak fits from several thousand diffraction patterns recorded during mesh scans. The azimuthal width of the 210 reflection, which is related to the orientation distribution of the crystalline domains within nanofibrils and the macroscopic orientation of the fibers traversed by the beam, was found to be sensitive to the overall state of decay of the fabric. The fine structure of the histogram of azimuthal width was related to the fiber hierarchical microstructure and the fabric morphology. SAXS/WAXS analysis supports the assumption of an initial loss of the random chain network with decay. At a subsequent state of aging, decay proceeds into the nanofibrils and the silk fibers break up into even smaller fractions.     

The unbiased estimation of the fraction of variance explained by a model

The correlation coefficient squared, r², is commonly used to validate quantitative models on neural data, yet it is biased by trial-to-trial variability: as trial-to-trial variability increases, measured correlation to a model’s predictions decreases. As a result, models that perfectly explain neural tuning can appear to perform poorly. Many solutions to this problem have been proposed, but no consensus has been reached on which is the least biased estimator. Some currently used methods substantially overestimate model fit, and the utility of even the best performing methods is limited by the lack of confidence intervals and asymptotic analysis. We provide a new estimator, r^ER2, that outperforms all prior estimators in our testing, and we provide confidence intervals and asymptotic guarantees. We apply our estimator to a variety of neural data to validate its utility. We find that neural noise is often so great that confidence intervals of the estimator cover the entire possible range of values ([0, 1]), preventing meaningful evaluation of the quality of a model’s predictions. This leads us to propose the use of the signal-to-noise ratio (SNR) as a quality metric for making quantitative comparisons across neural recordings. Analyzing a variety of neural data sets, we find that up to ∼ 40% of some state-of-the-art neural recordings do not pass even a liberal SNR criterion. Moving toward more reliable estimates of correlation, and quantitatively comparing quality across recording modalities and data sets, will be critical to accelerating progress in modeling biological phenomena.     

Gene characterization index: assessing the depth of gene annotation

Background

We introduce the Gene Characterization Index, a bioinformatics method for scoring the extent to which a protein-encoding gene is functionally described. Inherently a reflection of human perception, the Gene Characterization Index is applied for assessing the characterization status of individual genes, thus serving the advancement of both genome annotation and applied genomics research by rapid and unbiased identification of groups of uncharacterized genes for diverse applications such as directed functional studies and delineation of novel drug targets.

Methodology/Principal Findings

The scoring procedure is based on a global survey of researchers, who assigned characterization scores from 1 (poor) to 10 (extensive) for a sample of genes based on major online resources. By evaluating the survey as training data, we developed a bioinformatics procedure to assign gene characterization scores to all genes in the human genome. We analyzed snapshots of functional genome annotation over a period of 6 years to assess temporal changes reflected by the increase of the average Gene Characterization Index. Applying the Gene Characterization Index to genes within pharmaceutically relevant classes, we confirmed known drug targets as high-scoring genes and revealed potentially interesting novel targets with low characterization indexes. Removing known drug targets and genes linked to sequence-related patent filings from the entirety of indexed genes, we identified sets of low-scoring genes particularly suited for further experimental investigation.

Conclusions/Significance

The Gene Characterization Index is intended to serve as a tool to the scientific community and granting agencies for focusing resources and efforts on unexplored areas of the genome. The Gene Characterization Index is available from http://cisreg.ca/gci/.     

A novel cellular protein, VPEF, facilitates vaccinia virus penetration into HeLa cells through fluid phase endocytosis

Vaccinia virus is a large DNA virus that infects many cell cultures in vitro and animal species in vivo. Although it has been used widely as a vaccine, its cell entry pathway remains unclear. In this study, we showed that vaccinia virus intracellular mature virions bound to the filopodia of HeLa cells and moved toward the cell body and entered the cell through an endocytic route that required a dynamin-mediated pathway but not a clathrin- or caveola-mediated pathway. Moreover, virus penetration required a novel cellular protein, vaccinia virus penetration factor (VPEF). VPEF was detected on cell surface lipid rafts and on vesicle-like structures in the cytoplasm. Both vaccinia virus and dextran transiently colocalized with VPEF, and, importantly, knockdown of VPEF expression blocked vaccinia virus penetration as well as intracellular transport of dextran, suggesting that VPEF mediates vaccinia virus entry through a fluid uptake endocytosis process in HeLa cells. Intracellular VPEF-containing vesicles did not colocalize with Rab5a or caveolin but partially colocalized with Rab11, supporting the idea that VPEF plays a role in vesicle trafficking and recycling in HeLa cells. In summary, this study characterized the mechanism by which vaccinia virus enters HeLa cells and identified a cellular factor, VPEF, that is exploited by vaccinia virus for cell entry through fluid phase endocytosis.     

Structures of coenzyme F(420) in Mycobacterium species

The structure of coenzyme F(420) in Mycobacterium smegmatis was examined using proton NMR, amino acid analysis, and HPLC. The two major F(420) structures were shown to be composed of a chromophore identical to that of F(420) from Methanobacterium thermoautotrophicum, with a side chain of a ribityl residue, a lactyl residue and five or six glutamate groups (F(420)-5 and F(420)-6). Peptidase treatment studies suggested that L-glutamate groups are linked by gamma-glutamyl bonds in the side chain. HPLC analysis indicated that Mycobacterium tuberculosis, Mycobacterium bovis BCG, and Mycobacterium fortuitum have F(420)-5 and F(420)-6 as the predominant structures, whereas Mycobacterium avium contains F(420)-5, F(420)-6 and F(420)-7 in significant amounts. 7,8-Didemethyl 8-hydroxy 5-deazariboflavin (FO), an intermediate in F(420) biosynthesis, accounted for about 1-7% of the total deazaflavin in cells. Peptidase treatment of F(420) created F(420) derivatives that may be useful for the assay of enzymes involved in F(420) biosynthesis.