Advances in Dynamic Modeling and Computation for Count Data

A class of multi-process models is developed for collections of time indexed count data. Autocorrelation in counts is achieved with dynamic models for the natural parameter of the binomial distribution. In addition to modeling binomial time series, the framework includes dynamic models for multinomial and Poisson time series. Markov chain Monte Carlo (MCMC) and Po ́lya-Gamma data augmentation (Polson et al., 2013) are critical for fitting multi-process models of counts. To facilitate computation when the counts are high, a Gaussian approximation to the P ́olya- Gamma random variable is developed.

Three applied analyses are presented to explore the utility and versatility of the framework. The first analysis develops a model for complex dynamic behavior of themes in collections of text documents. Documents are modeled as a “bag of words”, and the multinomial distribution is used to characterize uncertainty in the vocabulary terms appearing in each document. State-space models for the natural parameters of the multinomial distribution induce autocorrelation in themes and their proportional representation in the corpus over time.

The second analysis develops a dynamic mixed membership model for Poisson counts. The model is applied to a collection of time series which record neuron level firing patterns in rhesus monkeys. The monkey is exposed to two sounds simultaneously, and Gaussian processes are used to smoothly model the time-varying rate at which the neuron’s firing pattern fluctuates between features associated with each sound in isolation.

The third analysis presents a switching dynamic generalized linear model for the time-varying home run totals of professional baseball players. The model endows each player with an age specific latent natural ability class and a performance enhancing drug (PED) use indicator. As players age, they randomly transition through a sequence of ability classes in a manner consistent with traditional aging patterns. When the performance of the player significantly deviates from the expected aging pattern, he is identified as a player whose performance is consistent with PED use.

All three models provide a mechanism for sharing information across related series locally in time. The models are fit with variations on the P ́olya-Gamma Gibbs sampler, MCMC convergence diagnostics are developed, and reproducible inference is emphasized throughout the dissertation.

Investigating the Tradespace between Increased Automation and Optimal Manning on Aircraft Carrier Decks

With increasing prevalence and capabilities of autonomous systems as part of complex heterogeneous manned-unmanned environments (HMUEs), an important consideration is the impact of the introduction of automation on the optimal assignment of human personnel. The US Navy has implemented optimal staffing techniques before in the 1990's and 2000's with a "minimal staffing" approach. The results were poor, leading to the degradation of Naval preparedness. Clearly, another approach to determining optimal staffing is necessary. To this end, the goal of this research is to develop human performance models for use in determining optimal manning of HMUEs. The human performance models are developed using an agent-based simulation of the aircraft carrier flight deck, a representative safety-critical HMUE. The Personnel Multi-Agent Safety and Control Simulation (PMASCS) simulates and analyzes the effects of introducing generalized maintenance crew skill sets and accelerated failure repair times on the overall performance and safety of the carrier flight deck. A behavioral model of four operator types (ordnance officers, chocks and chains, fueling officers, plane captains, and maintenance operators) is presented here along with an aircraft failure model. The main focus of this work is on the maintenance operators and aircraft failure modeling, since they have a direct impact on total launch time, a primary metric for carrier deck performance. With PMASCS I explore the effects of two variables on total launch time of 22 aircraft: 1) skill level of maintenance operators and 2) aircraft failure repair times while on the catapult (referred to as Phase 4 repair times). It is found that neither introducing a generic skill set to maintenance crews nor introducing a technology to accelerate Phase 4 aircraft repair times improves the average total launch time of 22 aircraft. An optimal manning level of 3 maintenance crews is found under all conditions, the point at which any additional maintenance crews does not reduce the total launch time. An additional discussion is included about how these results change if the operations are relieved of the bottleneck of installing the holdback bar at launch time.

Bayesian Learning with Dependency Structures via Latent Factors, Mixtures, and Copulas

Bayesian methods offer a flexible and convenient probabilistic learning framework to extract interpretable knowledge from complex and structured data. Such methods can characterize dependencies among multiple levels of hidden variables and share statistical strength across heterogeneous sources. In the first part of this dissertation, we develop two dependent variational inference methods for full posterior approximation in non-conjugate Bayesian models through hierarchical mixture- and copula-based variational proposals, respectively. The proposed methods move beyond the widely used factorized approximation to the posterior and provide generic applicability to a broad class of probabilistic models with minimal model-specific derivations. In the second part of this dissertation, we design probabilistic graphical models to accommodate multimodal data, describe dynamical behaviors and account for task heterogeneity. In particular, the sparse latent factor model is able to reveal common low-dimensional structures from high-dimensional data. We demonstrate the effectiveness of the proposed statistical learning methods on both synthetic and real-world data.

Temporomandibular joint pain: a critical role for Trpv4 in the trigeminal ganglion.

Temporomandibular joint disorder (TMJD) is known for its mastication-associated pain. TMJD is medically relevant because of its prevalence, severity, chronicity, the therapy-refractoriness of its pain, and its largely elusive pathogenesis. Against this background, we sought to investigate the pathogenetic contributions of the calcium-permeable TRPV4 ion channel, robustly expressed in the trigeminal ganglion sensory neurons, to TMJ inflammation and pain behavior. We demonstrate here that TRPV4 is critical for TMJ-inflammation-evoked pain behavior in mice and that trigeminal ganglion pronociceptive changes are TRPV4-dependent. As a quantitative metric, bite force was recorded as evidence of masticatory sensitization, in keeping with human translational studies. In Trpv4(-/-) mice with TMJ inflammation, attenuation of bite force was significantly less than in wildtype (WT) mice. Similar effects were seen with systemic application of a specific TRPV4 inhibitor. TMJ inflammation and mandibular bony changes were apparent after injections of complete Freund adjuvant but were remarkably independent of the Trpv4 genotype. It was intriguing that, as a result of TMJ inflammation, WT mice exhibited significant upregulation of TRPV4 and phosphorylated extracellular-signal-regulated kinase (ERK) in TMJ-innervating trigeminal sensory neurons, which were absent in Trpv4(-/-) mice. Mice with genetically-impaired MEK/ERK phosphorylation in neurons showed resistance to reduction of bite force similar to that of Trpv4(-/-) mice. Thus, TRPV4 is necessary for masticatory sensitization in TMJ inflammation and probably functions upstream of MEK/ERK phosphorylation in trigeminal ganglion sensory neurons in vivo. TRPV4 therefore represents a novel pronociceptive target in TMJ inflammation and should be considered a target of interest in human TMJD.

Quality control autophagy: a joint effort of ubiquitin, protein deacetylase and actin cytoskeleton.

Autophagy has been predominantly studied as a nonselective self-digestion process that recycles macromolecules and produces energy in response to starvation. However, autophagy independent of nutrient status has long been known to exist. Recent evidence suggests that this form of autophagy enforces intracellular quality control by selectively disposing of aberrant protein aggregates and damaged organelles--common denominators in various forms of neurodegenerative diseases. By definition, this form of autophagy, termed quality-control (QC) autophagy, must be different from nutrient-regulated autophagy in substrate selectivity, regulation and function. We have recently identified the ubiquitin-binding deacetylase, HDAC6, as a key component that establishes QC. HDAC6 is not required for autophagy activation per se; rather, it is recruited to ubiquitinated autophagic substrates where it stimulates autophagosome-lysosome fusion by promoting F-actin remodeling in a cortactin-dependent manner. Remarkably, HDAC6 and cortactin are dispensable for starvation-induced autophagy. These findings reveal that autophagosomes associated with QC are molecularly and biochemically distinct from those associated with starvation autophagy, thereby providing a new molecular framework to understand the emerging complexity of autophagy and therapeutic potential of this unique machinery.

Myosin VIIA, important for human auditory function, is necessary for Drosophila auditory organ development.

BACKGROUND: Myosin VIIA (MyoVIIA) is an unconventional myosin necessary for vertebrate audition [1]-[5]. Human auditory transduction occurs in sensory hair cells with a staircase-like arrangement of apical protrusions called stereocilia. In these hair cells, MyoVIIA maintains stereocilia organization [6]. Severe mutations in the Drosophila MyoVIIA orthologue, crinkled (ck), are semi-lethal [7] and lead to deafness by disrupting antennal auditory organ (Johnston's Organ, JO) organization [8]. ck/MyoVIIA mutations result in apical detachment of auditory transduction units (scolopidia) from the cuticle that transmits antennal vibrations as mechanical stimuli to JO. PRINCIPAL FINDINGS: Using flies expressing GFP-tagged NompA, a protein required for auditory organ organization in Drosophila, we examined the role of ck/MyoVIIA in JO development and maintenance through confocal microscopy and extracellular electrophysiology. Here we show that ck/MyoVIIA is necessary early in the developing antenna for initial apical attachment of the scolopidia to the articulating joint. ck/MyoVIIA is also necessary to maintain scolopidial attachment throughout adulthood. Moreover, in the adult JO, ck/MyoVIIA genetically interacts with the non-muscle myosin II (through its regulatory light chain protein and the myosin binding subunit of myosin II phosphatase). Such genetic interactions have not previously been observed in scolopidia. These factors are therefore candidates for modulating MyoVIIA activity in vertebrates. CONCLUSIONS: Our findings indicate that MyoVIIA plays evolutionarily conserved roles in auditory organ development and maintenance in invertebrates and vertebrates, enhancing our understanding of auditory organ development and function, as well as providing significant clues for future research.

Patient expectation is the most important predictor of discharge destination after primary total joint arthroplasty.

The purpose of this study was to identify preoperative predictors of discharge destination after total joint arthroplasty. A retrospective study of three hundred and seventy-two consecutive patients who underwent primary total hip and knee arthroplasty was performed. The mean length of stay was 2.9 days and 29.0% of patients were discharged to extended care facilities. Age, caregiver support at home, and patient expectation of discharge destination were the only significant multivariable predictors regardless of the type of surgery (total knee versus total hip arthroplasty). Among those variables, patient expectation was the most important predictor (P < 0.001; OR 169.53). The study was adequately powered to analyze the variables in the multivariable logistic regression model, which had a high concordance index of 0.969.

Unipedal balance is affected by lower extremity joint arthroplasty procedure 1 year following surgery.

Lower Extremity Joint Arthroplasty (LEJA) surgery is an effective way to alleviate painful osteoarthritis. Unfortunately, these surgeries do not normalize the loading asymmetry during the single leg stance phase of gait. Therefore, we examined single leg balance in 234 TJA patients (75 hips, 65 knees, 94 ankles) approximately 12 months following surgery. Patients passed if they maintained single leg balance for 10s with their eyes open. Patients one year following total hip arthroplasty (THA-63%) and total knee arthroplasty (TKA-69%) had similar pass rates compared to a total ankle arthroplasty (TAA-9%). Patients following THA and TKA exhibit better unilateral balance in comparison with TAA patients. It may be beneficial to include a rigorous proprioception and balance training program in TAA patients to optimize functional outcomes.

Percent body fat more associated with perioperative risks after total joint arthroplasty than body mass index

Copyright © 2014 Elsevier Inc. All rights reserved.Understanding the impact of obesity on elective total joint arthroplasty (TJA) remains critical. Perioperative outcomes were reviewed in 316 patients undergoing primary TJA. Higher percent body fat (PBF) was associated with postoperative blood transfusion, increased hospital length of stay (LOS) >3 days, and discharge to an extended care facility while no significant differences existed for BMI. Additionally, PBF of 43.5 was associated with a 2.4× greater likelihood of blood transfusion, PBF of 36.5 with a 1.9× greater likelihood for LOS >3 days, and PBF of 36.0 with a 1.4× greater likelihood for discharge to an extended care facility. PBF may be a more effective measure than BMI to use in screening for perioperative risks and acute outcomes associated with obese total joint patients.