The SYMBIOME Project: An Exploratory Investigation of the Biological, Psychological, and Social Mechanisms that Contribute to the Transition from Acute to Chronic Musculoskeletal Pain

This dissertation presents the initial findings of the SYMBIOME project; which attempts to combine the objective and subjective aspects of musculoskeletal pain to develop a prognostic clinical phenotype. Chapter 2 presents a moderator analysis of functional outcomes (pain interference and pain severity). Psychosocial moderators can affect the relationship between biomarkers and pain. For pain severity, TNF-α, TGF-β1, and CRP were moderated by employment status, pre-existing psychopathology, and sex. For pain interference, IL-1β, cortisol, TGF-β1, CRP, and IL-6 were moderated by pre-existing pain, peri-traumatic fear, region of injury, and peri-traumatic stress. Chapter 3 presents a latent growth curve analysis in determining the recovery trajectories of acute non-catastrophic musculoskeletal pain in the context of pain interference and severity over the course of 12 months. For pain interference, 3 distinct trajectories emerged: rapid recovery, delayed recovery, or minimal/no recovery. Pain severity favored a 2-trajectory model with rapid recovery or minimal/no recovery. Classification of recovery group depended on both baseline symptoms and relative rate of symptom decline. Recovery outcomes appeared to stabilize after a period of 3 months. Chapter 4 presents latent class analysis and growth mixture modeling as applied to a panel of 8 biomarkers (TNF-α, IL-1β, IL-6, CRP, IL-10, cortisol, BDNF, and TGF-β1). These markers may have the potential to discriminate between functional recovery outcomes. Using these markers, 3 meaningful groups or classes were identified. These groups could be adequately defined by using only 3 of the 8 markers (IL-1β, BDNF, and TGF-β1) where classes were organized by low concentration of markers in serum, average concentration, or high concentration of BDNF and TGF-β1. Those with high concentration of BDNF/TGF-β1 were more likely to score higher on self-report measures of pain and disability in their 6-month outcomes. These results support the claim that physiological factors are tied to pain through more than simple bivariate relationships. The context of the musculoskeletal trauma, both personal and social, can affect the behavior of biological systems

Design of Phononic Crystal Tethers for Frequency-selective Quality Factor Enhancement in AlN Piezoelectric-on-silicon Resonators

AbstractIn this work, we experimentally demonstrate frequency-selective improvement of unloaded quality factor (Qu) using one-dimensional (1D) phononic crystal (PnC) ring tethers in Aluminium Nitride (AlN) thin-film piezoelectric-on-silicon (TPoS) micromechanical resonators. We show that the 1D-PnC tethers help boost Qu by 3 times specifically at the desired resonant modes that lie in the PnC stopband but not for resonant modes lying outside the PnC stopband. These results show that the 1D-PnCs serve as frequency-selective acoustic reflectors

Examining the Influence of Time-Use Preferences on Technology Acceptance: The Role of Computer Polychronicity

Past research recognizes the important influence of individual beliefs on technology acceptance and use. This line of research has also identified a variety of factors that drive the formation of these beliefs. One category of variables that has not received much attention in this research stream consists of individual preferences, in particular time-use preferences. In the current study we add to the literature on technology acceptance, and belief formation in particular, by introducing and empirically testing a new construct labeled computer polychronicity, which captures individuals’ time-use preferences regarding IT. Computer polychronicity is positioned in this study as a key driver of perceived usefulness, mediating the effects of computer anxiety and computer playfulness. Overall, the results support the notion that preferences play important roles in the formation of technology-related beliefs

Heme Dissociation from Myoglobin in the Presence of the Zwitterionic Detergent N,N-Dimethyl-N-Dodecylglycine Betaine: Effects of Ionic Liquids

We have investigated myoglobin protein denaturation using the zwitterionic detergent Empigen BB (EBB, N,N-Dimethyl-N-dodecylglycine betaine). A combination of absorbance, fluorescence, and circular dichroism spectroscopic measurements elucidated the protein denaturation and heme dissociation from myoglobin. The results indicated that Empigen BB was not able to fully denature the myoglobin structure, but apparently can induce the dissociation of the heme group from the protein. This provides a way to estimate the heme binding free energy, ΔGdissociation. As ionic liquids (ILs) have been shown to perturb the myoglobin protein, we have investigated the effects of the ILs 1-butyl-3-methylimidazolium chloride (BMICl), 1-ethyl-3-methylimidazolium acetate (EMIAc), and 1-butyl-3-methylimidazolium tetrafluoroborate (BMIBF4) in aqueous solution on the ΔGdissociation values. Absorbance experiments show the ILs had minimal effect on ΔGdissociation values when compared to controls. Fluorescence and circular dichroism data confirm the ILs have no effect on heme dissociation, demonstrating that low concentrations ILs do not impact the heme dissociation from the protein and do not significantly denature myoglobin on their own or in combination with EBB. These results provide important data for future studies of the mechanism of IL-mediated protein stabilization/destabilization and biocompatibility studies

Strongly asymmetric hybridization barriers shape the origin of a new polyploid species and its hybrid ancestor

PREMISE OF THE STUDY:Hybridization between diploids and tetraploids can lead to new allopolyploid species, often via a triploid intermediate. Viable triploids are often produced asymmetrically, with greater success observed for “maternal-excess” crosses where the mother has a higher ploidy than the father. Here we investigated the evolutionary origins ofMimulus peregrinus, an allohexaploid recently derived from the triploidM. ×robertsii, to determine whether reproductive asymmetry has shaped the formation of this new species.  METHODS:We used reciprocal crosses between the diploid (M. guttatus) and tetraploid (M. luteus) progenitors to determine the viability of triploidM. ×robertsiihybrids resulting from paternal- vs. maternal-excess crosses. To investigate whether experimental results predict patterns seen in the field, we performed parentage analyses comparing natural populations ofM. peregrinusto its diploid, tetraploid, and triploid progenitors. Organellar sequences obtained from pre-existing genomic data, supplemented with additional genotyping was used to establish the maternal ancestry of multipleM. peregrinusandM. ×robertsiipopulations.  KEY RESULTS:We found strong evidence for asymmetric origins ofM. peregrinus, but opposite to the common pattern, with paternal-excess crosses significantly more successful than maternal-excess crosses. These results successfully predicted hybrid formation in nature: 111 of 114M. ×robertsiiindividuals, and 27 of 27M. peregrinus, had anM. guttatusmaternal haplotype.  CONCLUSION:This study, which includes the firstMimuluschloroplast genome assembly, demonstrates the utility of parentage analysis through genome skimming. We highlight the benefits of complementing genomic analyses with experimental approaches to understand asymmetry in allopolyploid speciation

The Structure of Analog Representation

This paper develops a theory of analog representation. We first argue that the mark of the analog is to be found in the nature of a representational system’s interpretation function, rather than in its vehicles or contents alone. We then develop the rulebound structure theory of analog representation, according to which analog systems are those that use interpretive rules to map syntactic structural features onto semantic structural features. The theory involves three degree-theoretic measures that capture three independent ways in which a system can be more or less analog. We explain how our theory improves upon prior accounts of analog representation, provides plausible diagnoses for novel challenge cases, extends to hybrid systems that are partially analog and partially symbolic, and accounts for some of the advantages and disadvantages of representing analogically versus symbolically

Iterative graph cuts for image segmentation with a nonlinear statistical shape prior

Shape-based regularization has proven to be a useful method for delineating objects within noisy images where one has prior knowledge of the shape of the targeted object. When a collection of possible shapes is available, the specification of a shape prior using kernel density estimation is a natural technique. Unfortunately, energy functionals arising from kernel density estimation are of a form that makes them impossible to directly minimize using efficient optimization algorithms such as graph cuts. Our main contribution is to show how one may recast the energy functional into a form that is minimizable iteratively and efficiently using graph cuts.Comment: Revision submitted to JMIV (02/24/13

An inhibitory pull-push circuit in frontal cortex.

Push-pull is a canonical computation of excitatory cortical circuits. By contrast, we identify a pull-push inhibitory circuit in frontal cortex that originates in vasoactive intestinal polypeptide (VIP)-expressing interneurons. During arousal, VIP cells rapidly and directly inhibit pyramidal neurons; VIP cells also indirectly excite these pyramidal neurons via parallel disinhibition. Thus, arousal exerts a feedback pull-push influence on excitatory neurons-an inversion of the canonical push-pull of feedforward input

Conditional Adapters: Parameter-efficient Transfer Learning with Fast Inference

We propose Conditional Adapter (CoDA), a parameter-efficient transfer learning method that also improves inference efficiency. CoDA generalizes beyond standard adapter approaches to enable a new way of balancing speed and accuracy using conditional computation. Starting with an existing dense pretrained model, CoDA adds sparse activation together with a small number of new parameters and a light-weight training phase. Our experiments demonstrate that the CoDA approach provides an unexpectedly efficient way to transfer knowledge. Across a variety of language, vision, and speech tasks, CoDA achieves a 2x to 8x inference speed-up compared to the state-of-the-art Adapter approach with moderate to no accuracy loss and the same parameter efficiency