A mathematical resolution to log transformations and the binning effect in applied processing of data in flow cytometry

This dissertation develops a new mathematical approach that overcomes the effect of a data processing phenomenon known as “histogram binning” inherent to flow cytometry data. A real-time procedure is introduced to prove the effectiveness and fast implementation of such an approach on real-world data. The histogram binning effect is a dilemma posed by two seemingly antagonistic developments: (1) flow cytometry data in its histogram form is extended in its dynamic range to improve its analysis and interpretation, and (2) the inevitable dynamic range extension introduces an unwelcome side effect, the binning effect, which skews the statistics of the data, undermining as a consequence the accuracy of the analysis and the eventual interpretation of the data. ^ Researchers in the field contended with such a dilemma for many years, resorting either to hardware approaches that are rather costly with inherent calibration and noise effects; or have developed software techniques based on filtering the binning effect but without successfully preserving the statistical content of the original data. ^ The mathematical approach introduced in this dissertation is so appealing that a patent application has been filed. The contribution of this dissertation is an incremental scientific innovation based on a mathematical framework that will allow researchers in the field of flow cytometry to improve the interpretation of data knowing that its statistical meaning has been faithfully preserved for its optimized analysis. Furthermore, with the same mathematical foundation, proof of the origin of such an inherent artifact is provided. ^ These results are unique in that new mathematical derivations are established to define and solve the critical problem of the binning effect faced at the experimental assessment level, providing a data platform that preserves its statistical content. ^ In addition, a novel method for accumulating the log-transformed data was developed. This new method uses the properties of the transformation of statistical distributions to accumulate the output histogram in a non-integer and multi-channel fashion. Although the mathematics of this new mapping technique seem intricate, the concise nature of the derivations allow for an implementation procedure that lends itself to a real-time implementation using lookup tables, a task that is also introduced in this dissertation. ^

Characterization of the amp genes involved in the regulation of beta-lactamase expression in Pseudomonas aeruginosa

Antibiotic resistance, production of alginate and virulence factors, and altered host immune responses are the hallmarks of chronic Pseudomonas aeruginosa infection. Failure of antibiotic therapy has been attributed to the emergence of P. aeruginosa strains that produce β-lactamase constitutively. In Enterobacteriaceae, β-lactamase induction involves four genes with known functions: ampC, ampR, ampD, and ampG, encoding the enzyme, transcriptional regulator, amidase and permease, respectively. In addition to all these amp genes, P. aeruginosa possesses two ampG paralogs, designated ampG and ampP. In this study, P. aeruginosa ampC, ampR, ampG and ampP were analyzed. Inactivation of ampC in the prototypic PAO1 failed to abolish the β-lactamase activity leading to the discovery of P. aeruginosa oxacillinase PoxB. Cloning and expression of poxB in Escherichia coli confers β-lactam resistance. Both AmpC and PoxB contribute to P. aeruginosa resistance against a wide spectrum of β-lactam antibiotics. The expression of PoxB and AmpC is regulated by a LysR-type transcriptional regulator AmpR that up-regulates AmpC but down-regulates PoxB activities. Analyses of P. aeruginosa ampR mutant demonstrate that AmpR is a global regulator that modulates the expressions of Las and Rhl quorum sensing (QS) systems, and the production of pyocyanin, LasA protease and LasB elastase. Introduction of the ampR mutation into an alginate-producing strain reveals the presence of a complex co-regulatory network between antibiotic resistance, QS alginate and other virulence factor production. Using phoA and lacZ protein fusion analyses, AmpR, AmpG and AmpP were localized to the inner membrane with one, 16 and 10 transmembrane helices, respectively. AmpR has a cytoplasmic DNA-binding and a periplasmic substrate binding domains. AmpG and AmpP are essential for the maximal expression of β-lactamase. Analysis of the murein breakdown products suggests that AmpG exports UDP-N-acetylmuramyl-L-alanine-γ-D-glutamate-meso-diaminopimelic acid-D-alanine-D-alanine (UDP-MurNAc-pentapeptide), the corepressor of AmpR, whereas AmpP imports N-acetylglucosaminyl-beta-1,4-anhydro-N-acetylmuramic acid-Ala-γ-D-Glu-meso-diaminopimelic acid (GlcNAc-anhMurNAc-tripeptide) and GlcNAc-anhMurNAc-pentapeptide, the co-inducers of AmpR. This study reveals a complex interaction between the Amp proteins and murein breakdown products involved in P. aeruginosa β-lactamase induction. In summary, this dissertation takes us a little closer to understanding the P. aeruginosa complex co-regulatory mechanism in the development of β-lactam resistance and establishment of chronic infection. ^

Signal processing of physiological signals for automated assessment of stress in computer users

The need to provide computers with the ability to distinguish the affective state of their users is a major requirement for the practical implementation of affective computing concepts. This dissertation proposes the application of signal processing methods on physiological signals to extract from them features that can be processed by learning pattern recognition systems to provide cues about a person's affective state. In particular, combining physiological information sensed from a user's left hand in a non-invasive way with the pupil diameter information from an eye-tracking system may provide a computer with an awareness of its user's affective responses in the course of human-computer interactions. In this study an integrated hardware-software setup was developed to achieve automatic assessment of the affective status of a computer user. A computer-based "Paced Stroop Test" was designed as a stimulus to elicit emotional stress in the subject during the experiment. Four signals: the Galvanic Skin Response (GSR), the Blood Volume Pulse (BVP), the Skin Temperature (ST) and the Pupil Diameter (PD), were monitored and analyzed to differentiate affective states in the user. Several signal processing techniques were applied on the collected signals to extract their most relevant features. These features were analyzed with learning classification systems, to accomplish the affective state identification. Three learning algorithms: Naïve Bayes, Decision Tree and Support Vector Machine were applied to this identification process and their levels of classification accuracy were compared. The results achieved indicate that the physiological signals monitored do, in fact, have a strong correlation with the changes in the emotional states of the experimental subjects. These results also revealed that the inclusion of pupil diameter information significantly improved the performance of the emotion recognition system. ^

Theoretical study of chloroperoxidase catalyzed chlorination of beta-cyclopentanedione and role of water in the chlorination mechanism

Chloroperoxidase (CPO) is a potential biocatalyst for use in asymmetric synthesis. The mechanisms of CPO catalysis are therefore of interest. The halogenation reaction, one of several chemical reactions that CPO catalyzes, is not fully understood and is the subject of this dissertation. The mechanism by which CPO catalyzes halogenation is disputed. It has been postulated that halogenation of substrates occurs at the active site. Alternatively, it has been proposed that hypochlorous acid, produced at the active site via oxidation of chloride, is released prior to reaction, so that halogenation occurs in solution. The free-solution mechanism is supported by the observation that halogenation of most substrates often occurs non-stereospecifically. On the other hand, the enzyme-bound mechanism is supported by the observation that some large substrates undergo halogenation stereospecifically. The major purpose of this research is to compare chlorination of the substrate β-cyclopentanedione in the two environments. One study was of the reaction with limited hydration because such a level of hydration is typical of the active site. For this work, a purely quantum mechanical approach was used. To model the aqueous environment, the limited hydration environment approach is not appropriate. Instead, reaction precursor conformations were obtained from a solvated molecular dynamics simulation, and reaction of potentially reactive molecular encounters was modeled with a hybrid quantum mechanical/molecular mechanical approach. Extensive work developing parameters for small molecules was pre-requisite for the molecular dynamics simulation. It is observed that a limited and optimized (active-site-like) hydration environment leads to a lower energetic barrier than the fully solvated model representative of the aqueous environment at room temperature, suggesting that the stable water network near the active site is likely to facilitate the chlorination mechanism. The influence of the solvent environment on the reaction barrier is critical. It is observed that stabilization of the catalytic water by other solvent molecules lowers the barrier for keto-enol tautomerization. Placement of water molecules is more important than the number of water molecules in such studies. The fully-solvated model demonstrates that reaction proceeds when the instantaneous dynamical water environment is close to optimal for stabilizing the transition state.

Intuition and its component parts in the heuristic processing of deception detection: Hunch, *evidence, and reliance on intuitive efficacy

Rated trust in intuitive efficacy (measured as trust, belief, use, accuracy and weighting of intuition) was investigated as a predictor of self-designated use of intuitive (hunch and hunch plus evidential belief) vs. deliberative (evidential belief and evidential belief plus hunch) deception detection judgments and actual accuracy. Twenty-nine student participants were filmed as they made true and deceptive statements about their everyday activities on a given evening (last Friday night), and college students (N=238) judged 20 (10=true, 10=deceptive) of these filmed statements as truthful or deceptive. Participants provided ratings of reliance on hunches vs. evidential belief, confidence in film judgments, intuitive efficacy, accuracy in deception detection, reliance on cues to deception, and experiences with intuition. Generalized estimated equation modeling using binary logistics demonstrated accuracy in identifying true vs. deceptive statements was predicted by film number, hunch-evidence ratings, weighting of intuition, and total cues cited. Weighting of intuition was predictive of accuracy across participants, with higher weighting predictive of higher accuracy in general. Participants who cited evidential belief plus hunch and moderate to high weighting incorrectly reversed their true vs. deceptive judgments. Accuracy for true statements was higher for hunches and hunch plus evidential belief, whereas accuracy for deceptive statements was higher for evidential belief Accuracy for participants who relied on evidential belief plus hunch was at chance. Subjective experiences underlying judgments differed by participant and type of film viewed (true vs. deceptive) and were predicted by hunch-evidence ratings, trust, use, intuitive accuracy, and total cues cited. Trust predicted increases in judging films to be true, whereas use and accuracy predicted increases in judging films as deceptive; none were predictive of accuracy. Increased number of cues cited predicted judgments of deception, whereas decreased number of cues cited predicted truth. The study concluded that participants have the capacity to self-define their judgments as subjectively vs. deliberately based, provide subjective assessments of the influence of intuitive vs. objective information on their judgments, and can apply this self-knowledge, through effective weighting of intuition vs. other types of information, in making accurate judgments of true and deceptive everyday statements.

A mathematical resolution to log transformations and the binning effect in applied processing of data in flow cytometry

This dissertation develops a new mathematical approach that overcomes the effect of a data processing phenomenon known as "histogram binning" inherent to flow cytometry data. A real-time procedure is introduced to prove the effectiveness and fast implementation of such an approach on real-world data. The histogram binning effect is a dilemma posed by two seemingly antagonistic developments: (1) flow cytometry data in its histogram form is extended in its dynamic range to improve its analysis and interpretation, and (2) the inevitable dynamic range extension introduces an unwelcome side effect, the binning effect, which skews the statistics of the data, undermining as a consequence the accuracy of the analysis and the eventual interpretation of the data. Researchers in the field contended with such a dilemma for many years, resorting either to hardware approaches that are rather costly with inherent calibration and noise effects; or have developed software techniques based on filtering the binning effect but without successfully preserving the statistical content of the original data. The mathematical approach introduced in this dissertation is so appealing that a patent application has been filed. The contribution of this dissertation is an incremental scientific innovation based on a mathematical framework that will allow researchers in the field of flow cytometry to improve the interpretation of data knowing that its statistical meaning has been faithfully preserved for its optimized analysis. Furthermore, with the same mathematical foundation, proof of the origin of such an inherent artifact is provided. These results are unique in that new mathematical derivations are established to define and solve the critical problem of the binning effect faced at the experimental assessment level, providing a data platform that preserves its statistical content. In addition, a novel method for accumulating the log-transformed data was developed. This new method uses the properties of the transformation of statistical distributions to accumulate the output histogram in a non-integer and multi-channel fashion. Although the mathematics of this new mapping technique seem intricate, the concise nature of the derivations allow for an implementation procedure that lends itself to a real-time implementation using lookup tables, a task that is also introduced in this dissertation.

The Processing of Preposition-Stranding Constructions in English

One of the prominent questions in modern psycholinguistics is the relationship between the grammar and the parser. Within the approach of Generative Grammar, this issue has been investigated in terms of the role that Principles of Universal Grammar may play in language processing. The aim of this research experiment is to investigate this topic. Specifically, this experiment aims to test whether the Minimal Structure Principle (MSP) plays a role in the processing of Preposition-Stranding versus Pied-Piped Constructions. This investigation is made with a self-paced reading task, an on-line processing test that measures participants’ unconscious reaction to language stimuli. Monolingual English speakers’ reading times of sentences with Preposition-Stranding and Pied-Piped Constructions are compared. Results indicate that neither construction has greater processing costs, suggesting that factors other than the MSP are active during language processing.