M89V Sialic Acid Acetyl Esterase (SIAE) and All Other Non-Synonymous Common Variants of This Gene Are Catalytically Normal

Catalytically defective rare variants of Sialic acid Acetyl Esterase (SIAE) have previously been linked to autoimmunity. Studies presented here confirm that the M89V SIAE protein and all other products of common variant alleles of SIAE are catalytically normal. Although overexpressing transfected non-lymphoid cells secrete small amounts of SIAE that can associate with the cell surface, normal human lymphocytes do not exhibit cell surface SIAE, supporting genetic evidence in mice that indicates that this protein functions in a lymphocyte intrinsic manner. Analyses of the plasma proteome also indicate that SIAE is not secreted in vivo. A re-analysis exclusively of catalytically defective rare variant alleles of SIAE in subjects in which this gene was completely sequenced confirmed an association of SIAE with autoimmunity. A subset of catalytically defective rare variant SIAE alleles has previously been typed in a large genotyping study comparing a diverse group of disease subjects and controls; our re-analysis of this data shows that catalytically defective alleles are enriched in disease subjects. These data suggest that SIAE may be associated with autoimmunity and that further study of catalytically defective rare variant SIAE alleles in terms of autoimmune disease susceptibility is strongly warranted

Motion‐Compensated Transform Coding

Interframe Hybrid Transform/dpcm Coders Encode Television Signals by Taking a Spatial Transform of a Block of Picture Elements in a Frame and Predictively Coding the Resulting Coefficients using the Corresponding Coefficients of the Spatial Block at the Same Location in the Previous Frame. These Coders Can Be Made More Efficient for Scenes Containing Objects in Translational Motion by First Estimating the Translational Displacement of Objects and Then using Coefficients of a Spatially Displaced Block in the Previous Frame for Prediction. This Paper Presents Simulation Results for Such Motion‐compensated Transform Coders using Two Algorithms for Estimating Displacements. the First Algorithm, Which is Developed in a Companion Paper, Recursively Estimates the Displacements from the Previously Transmitted Transform Coefficients, Thereby Eliminating the Need to Transmit the Displacement Estimates. the Second Algorithm, Due to Limb and Murphy, Estimates Displacements by Taking Ratios of Accumulated Frame Difference and Spatial Difference Signals in a Block. in This Scheme, the Displacement Estimates Are Transmitted to the Receiver. Computer Simulations on Two Typical Real‐life Sequences of Frames Show that Motion‐compensated Coefficient Prediction Results in Coder Bit Rates that Are 20 to 40 Percent Lower Than Conventional Interframe Transform Coders using Frame Difference of Coefficients. Comparisons of Bit Rates for Approximately the Same Picture Quality Show that the Two Methods of Displacement Estimation Are Quite Similar in Performance with a Slight Preference for the Scheme with Recursive Displacement Estimation. © 1979 the Bell System Technical Journa

Interframe Television Coding using Gain and Displacement Compensation

This Paper Presents Algorithms for Predicting Luminance Changes in Successive Television Frames. the Changes Can Result When Objects in a TV Scene Move or When Illumination Varies. by a Gradient Search Technique, Which Seeks to Minimize a Functional of the Interframe Prediction Error, We Estimate Two Parameters Associated with These Luminance Changes—displacement and Gain. using the Estimates of These Parameters, We Also Develop, for Interframe Coding, Adaptive Predictors and a Segmentor to Determine Which Pels Need to Be Transmitted. We Describe Several Coder Variations and Compare Them by Computer Simulations using Three Substantially Different Scene Sequences. for These Sequences, Gain Compensation with Improved Segmentation Reduced the Bit Rate of a Conditional Replenishment Encoder by 50.7, 11.1, and 39.3 Percent. Displacement Compensation Reduced the Bit Rate by 61.0, 24.8, and 14.5 Percent. Combined Gain and Displacement Compensation Reduced the Bit Rate by 63.4, 32.2, and 44.6 Percent. © 1980 the Bell System Technical Journa

Sustainable polymers

peer reviewedSustainable polymers are materials derived from renewable, recycled and waste carbon resources and their combinations, which at the end of life can be recycled, biodegraded or composted. Sustainable polymers also exhibit reduced environmental impact throughout their life cycle. This Primer presents an overview of the research in and potential of sustainable polymers, with a focus on their life cycle, synthetic routes from renewable carbon feedstocks, production, material characterization, applications, end of life, data reproducibility and limitations faced, and provides a brief outlook. The Primer also briefly covers other carbon feedstocks such as carbon dioxide and wastes, including agricultural and woody residues. Although still in their infancy, new sustainable polymers are already finding applications in packaging, automotive parts and 3D printing. This Primer also discusses the headwinds facing the adoption of sustainable polymers, including complexities of recycling and composting, manufacturing scale-up, data reproducibility, deposition and potential solutions. Development of sustainable polymers will accelerate the age of sustainable polymers and create a truly circular economy for plastics by reducing production and use of virgin plastics from finite resources

Model-Based Deconvolution of Cell Cycle Time-Series Data Reveals Gene Expression Details at High Resolution

In both prokaryotic and eukaryotic cells, gene expression is regulated across the cell cycle to ensure “just-in-time” assembly of select cellular structures and molecular machines. However, present in all time-series gene expression measurements is variability that arises from both systematic error in the cell synchrony process and variance in the timing of cell division at the level of the single cell. Thus, gene or protein expression data collected from a population of synchronized cells is an inaccurate measure of what occurs in the average single-cell across a cell cycle. Here, we present a general computational method to extract “single-cell”-like information from population-level time-series expression data. This method removes the effects of 1) variance in growth rate and 2) variance in the physiological and developmental state of the cell. Moreover, this method represents an advance in the deconvolution of molecular expression data in its flexibility, minimal assumptions, and the use of a cross-validation analysis to determine the appropriate level of regularization. Applying our deconvolution algorithm to cell cycle gene expression data from the dimorphic bacterium Caulobacter crescentus, we recovered critical features of cell cycle regulation in essential genes, including ctrA and ftsZ, that were obscured in population-based measurements. In doing so, we highlight the problem with using population data alone to decipher cellular regulatory mechanisms and demonstrate how our deconvolution algorithm can be applied to produce a more realistic picture of temporal regulation in a cell