Statistics of correlated percolation in a bacterial community

Signal propagation over long distances is a ubiquitous feature of multicellular communities, but cell-to-cell variability can cause propagation to be highly heterogeneous. Simple models of signal propagation in heterogenous media, such as percolation theory, can potentially provide a quantitative understanding of these processes, but it is unclear whether these simple models properly capture the complexities of multicellular systems. We recently discovered that in biofilms of the bacterium Bacillus subtilis, the propagation of an electrical signal is statistically consistent with percolation theory, and yet it is reasonable to suspect that key features of this system go beyond the simple assumptions of basic percolation theory. Indeed, we find here that the probability for a cell to signal is not independent from other cells as assumed in percolation theory, but instead is correlated with its nearby neighbors. We develop a mechanistic model, in which correlated signaling emerges from cell division, phenotypic inheritance, and cell displacement, that reproduces the experimentally observed correlations. We find that the correlations do not significantly affect the spatial statistics, which we rationalize using a renormalization argument. Moreover, the fraction of signaling cells is not constant in space, as assumed in percolation theory, but instead varies within and across biofilms. We find that this feature lowers the fraction of signaling cells at which one observes the characteristic power-law statistics of cluster sizes, consistent with our experimental results. We validate the model using a mutant biofilm whose signaling probability decays along the propagation direction. Our results reveal key statistical features of a correlated signaling process in a multicellular community. More broadly, our results identify extensions to percolation theory that do or do not alter its predictions and may be more appropriate for biological systems.P50 GM085764 - NIGMS NIH HHS; Howard Hughes Medical Institute; R01 GM121888 - NIGMS NIH HHSPublished versio

May Circulating microRNAs be Gastric Cancer Diagnostic Biomarkers?

Gastric cancer (GC) is the third leading cause of cancer-related deaths. More than 80% of the diagnosis was made at the advanced stages of the disease, highlighting the urgent demand for novel biomarkers that can be used for early detection. Recently, a number of studies suggest that circulating microRNAs (miRNAs) could be potential biomarkers for GC diagnosis. Cancer-related circulating miRNAs, as well as tissue miRNAs, provide a hopeful prospect of detecting GC at early stages, and the prospective participation of miRNAs in biomarker development will enhance the sensitivity and specificity of diagnostic tests for GC. As miRNAs in blood are stable, their potential value as diagnostic biomarkers in GC has been explored over the past few years. However, due to the inconsistent or sometimes conflicting reports, large-scale prospective studies are needed to validate their potential applicability in GC diagnosis. This review summarizes the current development about potential miRNA biomarkers for GC diagnosis and the obstacles hindering their clinical usage

Effects of The COVID-19 Pandemic on Gambling Behavior and Revenues: A Multi-state Analysis

This thesis examines the impact of the COVID-19 pandemic on individual gambling behavior by testing whether ticket sales and revenues in the multi-state parimutuel PowerBall and MegaMillions lotteries decreased or increased between the pre-COVID and COVID periods in Florida, Texas, and Colorado. Two competing hypotheses are investigated. First, gambling activity may have decreased during COVID either due to increased risk-aversion induced by the pandemic, negative changes in household income from the loss of employment, or a combination of the two. Second, gambling activity may have increased during COVID either due to increased willingness to take risks, substitution of income previously spent on other recreational activities to consumption of gambling products, or a combination of the two. To test these hypotheses, I use linear regression methods to model sales of tickets and revenues over the period from May 2016 to March 2022. My findings reveal that ticket sales decreased across all three states and PowerBall revenues declined significantly in Florida during the COVID period. Additionally, the mean marginal effects of the lagged amount of the jackpot and the unemployment rate differ significantly between the periods

A Field Test of Popular Chatbots’ Responses To Questions Concerning Negative Body Image

Background: Chatbots are computer programs, often built upon large artificial intelligence models, that employ dialogue systems to enable online, natural language conversations with users via text, speech, or both. Body image, broadly defined as a combination of thoughts and feelings about one’s physical appearance, has been implicated in many risk behaviors and health problems, especially among adolescents and young adults. Little is known about how chatbots respond to questions about body image. Methods: This study assessed the responses of 14 widely-used chatbots (eight companion and six therapeutic chatbots) to ten body image-related questions developed upon validated instruments. Chatbots’ responses were documented, with qualities systematically assessed by nine pre-determined criteria. Results: The overall quality of the chatbots’ responses was modest (an average score of five out of nine), with substantial variations in the content and quality of responses across chatbots (individual scores ranging from one to eight). Companion and therapeutic chatbots systematically differed in their responses (e.g., focusing on comforting users vs. trying to identify the causes of negative body image and recommending potential remedies). Some therapeutic chatbots recognized potential mental health crises (self-harm) in test users’ messages. Conclusion: Substantial heterogeneities in the responses were present across chatbots and assessment criteria. Adolescents and young adults struggling with body image could be vulnerable to misleading or biased remarks made by chatbots. Still, the technical and supervision challenges to prevent those adverse consequences remain paramount and unsolved

A 2-step penalized regression method for family-based next-generation sequencing association studies

Large-scale genetic studies are often composed of related participants, and utilizing familial relationships can be cumbersome and computationally challenging. We present an approach to efficiently handle sequencing data from complex pedigrees that incorporates information from rare variants as well as common variants. Our method employs a 2-step procedure that sequentially regresses out correlation from familial relatedness and then uses the resulting phenotypic residuals in a penalized regression framework to test for associations with variants within genetic units. The operating characteristics of this approach are detailed using simulation data based on a large, multigenerational cohort

Synthetic Antibody Mimic Peptides

The present disclosure relates to compositions and methods comprising peptide molecules that mimic the binding and functional properties of native antibodies relative to their respective targets. Some embodiments comprise peptide-drug conjugates (PDCs) comprising the mimic peptides disclosed herein. The targets of these mimic peptides include epidermal growth factor receptor (EGFR), and human epidermal growth factor receptor 2 (HER2), vascular endothelial growth factor (VEGF), programmed cell death protein 1 (PD-1), and programmed death-ligand 1 (PD-L1). The present disclosure comprises application of the knob-socket computational model to design antibody mimics for proteins

A single-step preparation of carbohydrate functionalized monoliths for separation and trapping of polar compounds

A single-step copolymerization strategy was developed for the preparation of carbohydrate (glucose and maltose) functionalized monoliths using click reaction. Firstly, novel carbohydrate-functionalized methacrylate monomers were synthesized through Cu(I)-catalyzed 1,3-dipolar cycloaddition (alkyne-azide reaction) of terminal alkyne with azide of carbohydrate derivatives. The corresponding carbohydrate functionalized monolithic columns were then prepared through a single-step in-situ copolymerization. The physicochemical properties and performance of the fabricated monolithic columns were evaluated using scanning electron microscopy, Fourier-transform infrared spectroscopy, and nano-liquid chromatography. For the optimized monolithic column, satisfactory column permeability and good separation performance were demonstrated for polar compounds including nucleoside, phenolic compounds and benzoic acid derivatives. The monolithic column is also highly useful for selective and efficient enrichment of glycopeptides from human IgG tryptic digests. This study not only provided a novel hydrophilic column for separation and selective trapping of polar compounds, but also proposed a facile and efficient approach for preparing carbohydrate functionalized monoliths

Scoring rules and competitive behavior in best value construction auctions

This paper examines the extent to which engineers can influence the competitive behavior of bidders in Best Value or multi-attribute construction auctions, where both the (dollar) bid and technical non-price criteria are scored according to a scoring rule. From a sample of Spanish construction auctions with a variety of bid scoring rules, it is found that bidders are influenced by the auction rules in significant and predictable ways. The bid score weighting, bid scoring formula and abnormally low bid criterion are variables likely to influence the competitiveness of bidders in terms of both their aggressive/conservative bidding and concentration/dispersion of bids. Revealing the influence of the bid scoring rules and their magnitude on bidders’ competitive behavior opens the door for the engineer to condition bidder competitive behavior in such a way as to provide the balance needed to achieve the owner’s desired strategic outcomes

All n-3 PUFA are not the same: MD simulations reveal differences in membrane organization for EPA, DHA and DPA

Eicosapentaenoic (EPA, 20:5), docosahexaenoic (DHA, 22:6) and docosapentaenoic (DPA, 22:5) acids are omega-3 polyunsaturated fatty acids (n-3 PUFA) obtained from dietary consumption of fish oils that potentially alleviate the symptoms of a range of chronic diseases. We focus here on the plasma membrane as a site of action and investigate how they affect molecular organization when taken up into a phospholipid. All atom MD simulations were performed to compare 1-stearoyl-2-eicosapentaenoylphosphatylcholine (EPA-PC, 18:0–20:5PC), 1-stearoyl-2-docosahexaenoylphosphatylcholine (DHA-PC, 18:0–22:6PC), 1-stearoyl-2-docosapentaenoylphosphatylcholine (DPA-PC, 18:0–22:5PC) and, as a monounsaturated control, 1-stearoyl-2-oleoylphosphatidylcholine (OA-PC, 18:0–18:1PC) bilayers. They were run in the absence and presence of 20 mol% cholesterol. Multiple double bonds confer high disorder on all three n-3 PUFA. The different number of double bonds and chain length for each n-3 PUFA moderates the reduction in membrane order exerted (compared to OA-PC, ̅ = 0.152). EPA-PC (̅ = 0.131) is most disordered, while DPA-PC ( ̅ = 0.140) is least disordered. DHA-PC (̅ = 0.139) is, within uncertainty, the same as DPA-PC. Following the addition of cholesterol, order in EPA-PC (̅ = 0.169), DHA-PC (̅ = 0.178) and DPA-PC (̅ = 0.182) is increased less than in OA-PC (̅ = 0.214). The high disorder of n-3 PUFA is responsible, preventing the n-3 PUFA-containing phospholipids from packing as close to the rigid sterol as the monounsaturated control. Our findings establish that EPA, DHA and DPA are not equivalent in their interactions within membranes, which possibly contributes to differences in clinical efficacy

miRNAs as potential biomarkers in early breast cancer detection following mammography

Breast cancer is the most common cancer among American women, except for skin cancers. About 12 % women in the United States will develop invasive breast cancer during their lifetime. Currently one of the most accepted model/theories is that ductal breast cancer (most common type of breast cancer) follows a linear progression: from normal breast epithelial cells to ductal hyperplasia to atypical ductal hyperplasia (ADH) to ductal carcinoma in situ (DCIS), and finally to invasive ductal carcinoma (IDC). Distinguishing pure ADH diagnosis from DCIS and/or IDC on mammography, and even combined with follow-up core needle biopsy (CNB) is still a challenge. Therefore subsequent surgical excision cannot be avoided to make a definitive diagnosis. MicroRNAs (miRNAs) are a highly abundant class of endogenous non-coding RNAs, which contribute to cancer initiation and progression, and are differentially expressed between normal and cancer tissues. They can function as either tumor suppressors or oncogenes. With accumulating evidence of the role of miRNAs in breast cancer progression, including our own studies, we sought to summarize the nature of early breast lesions and the potential use of miRNA molecules as biomarkers in early breast cancer detection. In particular, miRNA biomarkers may potentially serve as a companion tool following mammography screening and CNB. In the long-term, a better understanding of the molecular mechanisms underlying the miRNA signatures associated with breast cancer development could potentially result in the development of novel strategies for disease prevention and therapy