In Silico Synchronization of Cellular Populations Through Expression Data Deconvolution

Cellular populations are typically heterogenous collections of cells at different points in their respective cell cycles, each with a cell cycle time that varies from individual to individual. As a result, true single-cell behavior, particularly that which is cell-cycle--dependent, is often obscured in population-level (averaged) measurements. We have developed a simple deconvolution method that can be used to remove the effects of asynchronous variability from population-level time-series data. In this paper, we summarize some recent progress in the development and application of our approach, and provide technical updates that result in increased biological fidelity. We also explore several preliminary validation results and discuss several ongoing applications that highlight the method's usefulness for estimating parameters in differential equation models of single-cell gene regulation.Comment: accepted for the 48th ACM/IEEE Design Automation Conferenc

Model-Based Deconvolution of Cell Cycle Time-Series Data Reveals Gene Expression Details at High Resolution

In both prokaryotic and eukaryotic cells, gene expression is regulated across the cell cycle to ensure “just-in-time” assembly of select cellular structures and molecular machines. However, present in all time-series gene expression measurements is variability that arises from both systematic error in the cell synchrony process and variance in the timing of cell division at the level of the single cell. Thus, gene or protein expression data collected from a population of synchronized cells is an inaccurate measure of what occurs in the average single-cell across a cell cycle. Here, we present a general computational method to extract “single-cell”-like information from population-level time-series expression data. This method removes the effects of 1) variance in growth rate and 2) variance in the physiological and developmental state of the cell. Moreover, this method represents an advance in the deconvolution of molecular expression data in its flexibility, minimal assumptions, and the use of a cross-validation analysis to determine the appropriate level of regularization. Applying our deconvolution algorithm to cell cycle gene expression data from the dimorphic bacterium Caulobacter crescentus, we recovered critical features of cell cycle regulation in essential genes, including ctrA and ftsZ, that were obscured in population-based measurements. In doing so, we highlight the problem with using population data alone to decipher cellular regulatory mechanisms and demonstrate how our deconvolution algorithm can be applied to produce a more realistic picture of temporal regulation in a cell.</p

Correlation Between Plaque and Gingivitis

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/141522/1/jper0424.pd

Anti-Racism in Higher Education: A Model for Change

Racism continues to persist in higher education and traditional diversity initiatives that focus only on support resources and tolerance training continue to fall short in making lasting change on college and university campuses. The purpose of this scholarly paper is to present a model for change within higher education that distributes leadership and institutional power across racial lines and enlightens the White community about systemic inequities

Effect of Compliant Wall Motion on Turbulent Boundary Layers

A critical analysis of available compliant wall data which indicated drag reduction under turbulent boundary layers is presented. Detailed structural dynamic calculations suggest that the surfaces responded in a resonant, rather than a compliant, manner. Alternate explanations are given for drag reductions observed in two classes of experiments: (1) flexible pipe flows and (2) water-backed membranes in air. Analysis indicates that the wall motion for the remaining data is typified by short wavelengths in agreement with the requirements of a possible compliant wall drag reduction mechanism recently suggested by Langley. Copyright © 1977 American Institute of Physics

Committed to the Cause? Examining Social Work Education\u27s Role in Supporting Ally Behavior for Transgender and Nonbinary People and Communities

Transgender and nonbinary (TNB) youth and adults are under attack in the United States, with at least 300 state-level anti-transgender bills introduced thus far in 2022 (HRC, 2022). Social workers, guided by professional values and ethics, play a critical role in supporting and advocating for TNB youth and adults, clinically and through mezzo and macro approaches. Given the current political context and the goals of the social work profession, understanding correlates of ally behavior on behalf of TNB people among social work students can help guide improvements in social work education. Specifically, in this study, we examine how demographic differences, social work program variables, and psychosocial predictors are related to increased levels of ally behavior among social work students. Correlates of increased ally behavior in the final multivariate model include having TNB friends, having LGBQ friends, lower levels of social dominance orientation, and lower levels of transphobia. Post-hoc analyses suggest that differences emerge based on levels of social dominance orientation. From the findings, we offer suggestions for school-level interventions that have the potential to increase ally behaviors among social work students as it relates to the TNB community

Bounds and Inequalities Relating h-Index, g-Index, e-Index and Generalized Impact Factor

Finding relationships among different indices such as h-index, g-index, e-index, and generalized impact factor is a challenging task. In this paper, we describe some bounds and inequalities relating h-index, g-index, e-index, and generalized impact factor. We derive the bounds and inequalities relating these indexing parameters from their basic definitions and without assuming any continuous model to be followed by any of them.Comment: 17 pages, 6 figures, 5 table

Association of Botryosphaeriaceae grapevine trunk disease fungi with the reproductive structures of Vitis vinifera

Several species belonging to the Botryosphaeriaceae were isolated from grapevine (Vitis vinifera) tissue other than wood during a survey of two vineyards planted to cultivars ‘Chardonnay’ and ‘Shiraz’ in the Hunter Valley, New South Wales, Australia over the 2007/08 and 2008/09 growing seasons. A total of 188 isolates corresponding to nine different species of Diplodia, Dothiorella and Neofusicoccum anamorphs were isolated from dormant buds, flowers, pea-sized berries and mature berries prior to harvest in addition to 142 isolates from the trunks of the same vines. Furthermore, the occurrence of Dothiorella viticola, Diplodia mutila and Neofusicoccum australe is reported here for the first time from grapevines in the Hunter Valley. These findings may provide important information for the management and spread of Botryosphaeriaceae in vineyards where they are considered serious wood-invading pathogens. Botryosphaeriaceae are occasionally found on bunches, however, until now they have not directly been related  to bunch rots. Control strategies for trunk diseases caused by Botryosphaeriaceae are currently limited to remedial surgery and wound protection. These strategies do not consider other grapevine tissue as potential inoculum sources for infection of Botryosphaeriaceae in the vineyard.