On the utility of predictive chromatography to complement mass spectrometry based intact protein identification

The amino acid sequence determines the individual protein three-dimensional structure and its functioning in an organism. Therefore, "reading” a protein sequence and determining its changes due to mutations or post-translational modifications is one of the objectives of proteomic experiments. The commonly utilized approach is gradient high-performance liquid chromatography (HPLC) in combination with tandem mass spectrometry. While serving as a way to simplify the protein mixture, the liquid chromatography may be an additional analytical tool providing complementary information about the protein structure. Previous attempts to develop "predictive” HPLC for large biomacromolecules were limited by empirically derived equations based purely on the adsorption mechanisms of the retention and applicable to relatively small polypeptide molecules. A mechanism of the large biomacromolecule retention in reversed-phase gradient HPLC was described recently in thermodynamics terms by the analytical model of liquid chromatography at critical conditions (BioLCCC). In this work, we applied the BioLCCC model to predict retention of the intact proteins as well as their large proteolytic peptides separated under different HPLC conditions. The specific aim of these proof-of-principle studies was to demonstrate the feasibility of using "predictive” HPLC as a complementary tool to support the analysis of identified intact proteins in top-down, middle-down, and/or targeted selected reaction monitoring (SRM)-based proteomic experiments. Figure Intact protein LC retention time prediction assists protein identification in top- and middle-down proteomic

A Universal Volumetric Haptic Actuation Platform

In this paper, we report a method of implementing a universal volumetric haptic actuation platform which can be adapted to fit a wide variety of visual displays with flat surfaces. This platform aims to enable the simulation of the 3D features of input interfaces. This goal is achieved using four readily available stepper motors in a diagonal cross configuration with which we can quickly change the position of a surface in a manner that can render these volumetric features. In our research, we use a Microsoft Surface Go tablet placed on the haptic enhancement actuation platform to replicate the exploratory features of virtual keyboard keycaps displayed on the touchscreen. We ask seven participants to explore the surface of a virtual keypad comprised of 12 keycaps. As a second task, random key positions are announced one at a time, which the participant is expected to locate. These experiments are used to understand how and with what fidelity the volumetric feedback could improve performance (detection time, track length, and error rate) of detecting the specific keycaps location with haptic feedback and in the absence of visual feedback. Participants complete the tasks with great success (p < 0.05). In addition, their ability to feel convex keycaps is confirmed within the subjective comments.Peer reviewe

Generating Haptic Sensations over Spherical Surface

Haptic imagery, the imagining of haptic sensations in the mind, makes use of and extends human vision. Thus, enabling a better understanding of multi-dimensional sensorimotor information by strengthening space exploration with “seeing by touch." Testing this concept was performed on a spherical surface to optimize the way of generating localized haptic signals and their propagation across the curved surface to generate dynamic movements of perceivable peak vibrations. Through testing of several spherical structure prototypes, it was found that offset actuations can dynamically amplify vibrations at specific locations. A pilot study was followed to understand the impact of haptic stimulation on viewers of video content in a passive VR environment. Results showed a correlation between heart rate and the presented content; complimenting the technical data recorded.Peer reviewe

Fast and flexible selection with a single switch

Selection methods that require only a single-switch input, such as a button click or blink, are potentially useful for individuals with motor impairments, mobile technology users, and individuals wishing to transmit information securely. We present a single-switch selection method, "Nomon," that is general and efficient. Existing single-switch selection methods require selectable options to be arranged in ways that limit potential applications. By contrast, traditional operating systems, web browsers, and free-form applications (such as drawing) place options at arbitrary points on the screen. Nomon, however, has the flexibility to select any point on a screen. Nomon adapts automatically to an individual's clicking ability; it allows a person who clicks precisely to make a selection quickly and allows a person who clicks imprecisely more time to make a selection without error. Nomon reaps gains in information rate by allowing the specification of beliefs (priors) about option selection probabilities and by avoiding tree-based selection schemes in favor of direct (posterior) inference. We have developed both a Nomon-based writing application and a drawing application. To evaluate Nomon's performance, we compared the writing application with a popular existing method for single-switch writing (row-column scanning). Novice users wrote 35% faster with the Nomon interface than with the scanning interface. An experienced user (author TB, with > 10 hours practice) wrote at speeds of 9.3 words per minute with Nomon, using 1.2 clicks per character and making no errors in the final text.Comment: 14 pages, 5 figures, 1 table, presented at NIPS 2009 Mini-symposi

On the utility of predictive chromatography to complement mass spectrometry based intact protein identification

The amino acid sequence determines the individual protein three-dimensional structure and its functioning in an organism. Therefore, "reading" a protein sequence and determining its changes due to mutations or post-translational modifications is one of the objectives of proteomic experiments. The commonly utilized approach is gradient high-performance liquid chromatography (HPLC) in combination with tandem mass spectrometry. While serving as a way to simplify the protein mixture, the liquid chromatography may be an additional analytical tool providing complementary information about the protein structure. Previous attempts to develop "predictive" HPLC for large biomacromolecules were limited by empirically derived equations based purely on the adsorption mechanisms of the retention and applicable to relatively small polypeptide molecules. A mechanism of the large biomacromolecule retention in reversed-phase gradient HPLC was described recently in thermodynamics terms by the analytical model of liquid chromatography at critical conditions (BioLCCC). In this work, we applied the BioLCCC model to predict retention of the intact proteins as well as their large proteolytic peptides separated under different HPLC conditions. The specific aim of these proof-of-principle studies was to demonstrate the feasibility of using "predictive" HPLC as a complementary tool to support the analysis of identified intact proteins in top-down, middle-down, and/or targeted selected reaction monitoring (SRM)-based proteomic experiments

Spotty: Imaging sonification based on spot-mapping and tonal volume

Presented at the 7th International Conference on Auditory Display (ICAD), Espoo, Finland, July 29-August 1, 2001.A basic question at image sonification is the image segmentation. A cognitive model of visual processing in a greater degree could define possible ways of sound mapping. For instance, the scanpath theory suggests that a top-down internal cognitive model, of what we see, drives the sequences of rapid eye movements and fixations or glances that so efficiently travel over scene or picture of interest. The scanpath theory may be applied at sonification of visual image. But it is necessary to solve, what is more important in each stage of the image recognition process: the scan trajectory or the optical characteristics of its extreme positions? That is to say, what is dominant - scanpath or the spot of glance? I hope a solution of these questions will allow to develop new tools for VR applications as well as to continue designing of visualization system for blind people on a basis of blind-eye tracking