Pilot proteomic analysis of cerebrospinal fluid in Alzheimer's disease

Proteomic analysis of cerebrospinal fluid (CSF) holds great promise in understanding the progression of neurodegenerative diseases, including Alzheimer's disease (AD). As one of the primary reservoirs of neuronal biomolecules, CSF provides a window into the biochemical and cellular aspects of the neurological environment. CSF can be drawn from living participants allowing the potential alignment of clinical changes with these biochemical markers. Using cutting-edge mass spectrometry technologies, we perform a streamlined proteomic analysis of CSF. We quantify greater than 700 proteins across 10 pairs of age- and sex-matched participants in approximately one hour of analysis time each. Using the paired participant study structure, we identify a small group of biologically relevant proteins that show substantial changes in abundance between cognitive normal and AD participants, which were then analyzed at the peptide level using parallel reaction monitoring experiments. Our findings suggest the utility of fractionating a single sample and using matching to increase proteomic depth in cerebrospinal fluid, as well as the potential power of an expanded study.     

A channel estimation algorithm for MIMO-SCFDE

This letter proposes a novel method for channel estimation in a single-carrier multiple input-multiple output (MIMO) system with frequency-domain equalization/detection. To this end, we construct novel short MIMO training sequences that have constant envelope in the time domain to preclude the peak-to-average power ratio problem encountered in many systems that utilize the frequency domain for data recovery. Simultaneously, the spectrum in the frequency domain is flat except for a grid of s for predefined frequency tones. Armed with these sequences, we provide an algorithm that is optimal in the least squares (LS) sense at a potentially low computational cost. Results show that the algorithm performs identically to other proposed LS techniques. Furthermore, the algorithm is extremely bandwidth efficient in that the total training overhead required to obtain full CSI is just one block.     

Precoding in OFDM-based multi-antenna ultra-wideband systems

Next-generation ultra-wideband systems will be required to operate in a robust manner over short distances while achieving data rates on the order of gigabits per second. Sophisticated multiantenna techniques can be employed to meet these objectives; in particular, multi-antenna precoding (or beamforming) methods are promising solutions. However, due to the strict power regulations placed on UWB transmissions, conventional precoding techniques are not always suitable for use in UWB networks. In this article we present new theoretical results and practical approaches to performing precoding in OFDM-based multi-antenna UWB systems.     

A Content Analysis of Print News Coverage of Media Violence and Aggression Research

We conducted a content analysis of news articles (N = 540) to examine whether news coverage of media violence accurately reflects scientific knowledge about exposure to media violence and its effects on viewer aggression. The analysis revealed that over the past 30 years, news articles generally suggested that a link between media violence and aggression exists. However, the tone shifted sharply back toward a neutral conclusion since 2000. This shift may be attributable to the type of medium discussed (e.g., television vs. video games), the number of unaffiliated sources that are cited in the news article, and the sex of the journalist. Implications for how this news coverage may influence news readers are discussed.     

Multifactor,Sequentially Releasing Scaffolds for Tissue Engineering:Fabrication Using Solvent/Nonsolvent Sintering Technology

Biodegradable constructs, providing both mechanical support to growing tissues and timed release of biological agents, are highly desired in tissue engineering. This study aimed to develop a platform technology that responds to these challenges. Accordingly, we report herein on model systems in which microspheres of poly(suberic anhydride), containing all-trans retinoic acid (atRA), and poly(d,l -lactic acid-co-glycolic acid), containing bovine serum albumin (BSA), were co-sintered at room temperature, using a solvent/nonsolvent mixture. These scaffolds release about 60% of atRA and negligible amounts of BSA within the first five days, followed by slower and steady release of BSA. They have pores of 150–500 μm and a compressive modulus of 200 kPa. Myoblasts and fibroblasts were seeded on the loaded scaffolds and both showed enhanced proliferation rates. Based on sound thermodynamic principles of polymer science, this technology demonstrates an as yet unachieved degree of versatility. It allows for the tailoring of “intelligent” scaffolds that preserve the integrity of the incorporated agents and of advanced modalities to release various drugs in a scheduled manner.     

Efficient Learning of Relational Object Class Models

We present an efficient method for learning part-based object class models from unsegmented images represented as sets of salient features. A model includes parts’ appearance, as well as location and scale relations between parts. The object class is generatively modeled using a simple Bayesian network with a central hidden node containing location and scale information, and nodes describing object parts. The model’s parameters, however, are optimized to reduce a loss function of the training error, as in discriminative methods. We show how boosting techniques can be extended to optimize the relational model proposed, with complexity linear in the number of parts and the number of features per image. This efficiency allows our method to learn relational models with many parts and features. The method has an advantage over purely generative and purely discriminative approaches for learning from sets of salient features, since generative method often use a small number of parts and features, while discriminative methods tend to ignore geometrical relations between parts. Experimental results are described, using some bench-mark data sets and three sets of newly collected data, showing the relative merits of our method in recognition and localization tasks.     

Minimal Decomposition of Model-Based Invariants

Model-based invariants are relations between model parameters and image measurements, which are independent of the imaging parameters. Such relations are true for all images of the model. Here we describe an algorithm which, given L independent model-based polynomial invariants describing some shape, will provide a linear re-parameterization of the invariants. This re-parameterization has the properties that: (i) it includes the minimal number of terms, and (ii) the shape terms are the same in all the model-based invariants. This final representation has 2 main applications: (1) it gives new representations of shape in terms of hyperplanes, which are convenient for object recognition; (2) it allows the design of new linear shape from motion algorithms. In addition, we use this representation to identify object classes that have universal invariants.     

Ovine arylalkylamine N-acetyltransferase in the pineal and pituitary glands: differences in function and regulation

The enzyme arylalkylamine N-acetyltransferase (AANAT; EC 2.3.1.87) has been conventionally linked with the biosynthesis of melatonin within the pineal gland and retina. This study establishes that AANAT messenger RNA (mRNA) and functional enzyme occurs within the pars tuberalis (PT) and to a lesser degree within the pars distalis (PD) of the sheep pituitary gland; expression in these tissues is approximately 1/15th (PT) and 1/300th (PD) of that in the ovine pineal gland. AANAT mRNA in the PT appears to be expressed in the same cells as the Mel1a receptor. No evidence was obtained to indicate that either PT or PD cells have the ability to synthesize melatonin, suggesting that this enzyme plays a different functional role in the pituitary. We also found that cAMP regulation of the abundance of AANAT mRNA differs between the PT and pineal gland. Forskolin (10 microM) has no effect on pineal AANAT mRNA levels, yet represses expression in the PT. This suppressive influence could be mediated by ICER (inducible cAMP response early repressor), which is induced by forskolin in both tissues. Although it appears that the specific function and regulation of AANAT in the pituitary gland differ from that in the pineal gland, it seems likely that AANAT may play a role in the broader area of signal transduction through the biotransformation of amines.