skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

Explore Research Products in the PAR
It may take a few hours for recently added research products to appear in PAR search results.


  • NSF Public Access
  • Search Results
  • pyQCM-BraTaDio: A tool for visualization, data mining, and modelling of Quartz crystal microbalance with dissipation data
Title: pyQCM-BraTaDio: A tool for visualization, data mining, and modelling of Quartz crystal microbalance with dissipation data
Abstract Here, we present a Python based software that allows for the rapid visualization, data mining, and basic model applications of quartz crystal microbalance with dissipation data. Our implementation begins with a Tkinter GUI to prompt the user for all required information, such as file name/location, selection of baseline time, and overtones for visualization (with customization capabilities). These inputs are then fed to a workflow that will use the baseline time to scrub and temporally shift data using the Pandas and Numpy libraries and carry out the plot options for visualization. The last stage consists of an interactive plot, that presents the data and allows the user to select ranges in MatPlotLib-generated panels, followed by application of data models, including Sauerbrey, thin films in liquid, among others, that are carried out with NumPy and SciPy. The implementation of this software allows for simple and expedited data analysis,in lieuof time consuming and labor-intensive spreadsheet analysis. Metadata  more » « less
Award ID(s):
2112675
PAR ID:
10527262
Author(s) / Creator(s):
; ; ; ; ; ;
Publisher / Repository:
bioRxiv
Date Published:
Format(s):
Medium: X
Institution:
bioRxiv
Sponsoring Org:
National Science Foundation
More Like this
  1. ; ; ; (, bioRxiv)
    Abstract Pollen function is critical for successful plant reproduction and crop productivity and it is important to develop accessible methods to quantitatively analyze pollen performance to enhance reproductive resilience. Here we introduce TubeTracker as a method to quantify key parameters of pollen performance such as, time to pollen grain germination, pollen tube tip velocity and pollen tube survival. TubeTracker integrates manual and automatic image processing routines and the graphical user interface allows the user to interact with the software to make manual corrections of automated steps. TubeTracker does not depend on training data sets required to implement machine learning approaches and thus can be immediately implemented using readily available imaging systems. Furthermore, TubeTracker is an excellent tool to produce the pollen performance data sets necessary to take advantage of emerging AI-based methods to fully automate analysis. We tested TubeTracker and found it to be accurate in measuring pollen tube germination and pollen tube tip elongation across multiple cultivars of tomato. Abstract FigureGraphical AbstractGraphical user interface of TubeTracker showing all supported functionalities. 
    more » « less
  2. ; ; ; ; ; ; (, bioRxiv)
    ABSTRACT Microbes can be programmed to record participation in gene transfer by coding biological-recording devices into mobile DNA. Upon DNA uptake, these devices transcribe a catalytic RNA (cat-RNA) that binds to conserved sequences within ribosomal RNA (rRNA) and perform a trans-splicing reaction that adds a barcode to the rRNA. Existing cat-RNA designs were generated to be broad-host range, providing no control over the organisms that were barcoded. To achieve control over the organisms barcoded by cat-RNA, we created a program called Ribodesigner that uses input sets of rRNA sequences to create designs with varying specificities. We show how this algorithm can be used to identify designs that enable kingdom-wide barcoding, or selective barcoding of specific taxonomic groups within a kingdom. We use Ribodesigner to create cat-RNA designs that target Pseudomonadales while avoiding Enterobacterales, and we compare the performance of one design to a cat-RNA that was previously found to be broad host range. When conjugated into a mixture ofEscherichia coliandPseudomonas putida, the new design presents increased selectivity compared to a broad host range cat-RNA. Ribodesigner is expected to aid in developing cat-RNA that store information within user-defined sets of microbes in environmental communities for gene transfer studies. GRAPHICAL ABSTRACT 
    more » « less
  3. ; ; ; ; ; ; (, bioRxiv)
    Abstract Three-dimensional (3D) tissue engineering (TE) is a prospective treatment that can be used to restore or replace damaged musculoskeletal tissues such as articular cartilage. However, current challenges in TE include identifying materials that are biocompatible and have properties that closely match the mechanical properties and cellular environment of the target tissue, while allowing for 3D tomography of porous scaffolds as well as their cell growth and proliferation characterization. This is particularly challenging for opaque scaffolds. Here we use graphene foam (GF) as a 3D porous biocompatible substrate which is scalable, reproduceable, and a suitable environment for ATDC5 cell growth and chondrogenic differentiation. ATDC5 cells are cultured, maintained, and stained with a combination of fluorophores and gold nanoparticle to enable correlative microscopic characterization techniques, which elucidate the effect of GF properties on cell behavior in a three-dimensional environment. Most importantly, our staining protocols allows for direct imaging of cell growth and proliferation on opaque GF scaffolds using X-ray MicroCT, including imaging growth of cells within the hollow GF branches which is not possible with standard fluorescence and electron microscopy techniques. Abstract Figure 
    more » « less
  4. ; ; ; ; (, bioRxiv)
    Abstract RNA molecules adopt complex structures that perform essential biological functions across all forms of life, making them promising candidates for therapeutic applications. However, our ability to design new RNA structures remains limited by an incomplete understanding of their folding principles. While global metrics such as the minimum free energy are widely used, they are at odds with naturally occurring structures and incompatible with established design rules. Here, we introduce local stability compensation (LSC), a principle that RNA folding is governed by the local balance between destabilizing loops and their stabilizing adjacent stems, challenging the focus on global energetic optimization. Analysis of over 100,000 RNA structures revealed that LSC signatures are particularly pronounced in bulges and their adjacent stems, with distinct patterns across different RNA families that align with their biological functions. To validate LSC experimentally, we systematically analyzed thousands of RNA variants using DMS chemical mapping. Our results demonstrate that stem folding, as measured by reactivity, correlates with LSC (R2= 0.458 for hairpin loops) and that instabilities show no significant effect on folding for distal stems. These findings demonstrate that LSC can be a guiding principle for understanding RNA function and for the rational design of custom RNAs. Graphical Abstract 
    more » « less
  5. ; ; ; ; ; (, bioRxiv)
    Abstract Although multiple high-performing epigenetic aging clocks exist, few are based directly on gene expression. Such transcriptomic aging clocks allow us to extract age-associated genes directly. However, most existing transcriptomic clocks model a subset of genes and are limited in their ability to predict novel biomarkers. With the growing popularity of single-cell sequencing, there is a need for robust single-cell transcriptomic aging clocks. Moreover, clocks have yet to be applied to investigate the elusive phenomenon of sex differences in aging. We introduce TimeFlies, a pan-cell-type scRNA-seq aging clock for theDrosophila melanogasterhead. TimeFlies uses deep learning to classify the donor age of cells based on genome-wide gene expression profiles. Using explainability methods, we identified key marker genes contributing to the classification, with lncRNAs showing up as highly enriched among predicted biomarkers. The top biomarker gene across cell types is lncRNA:roX1, a regulator of X chromosome dosage compensation, a pathway previously identified as a top biomarker of aging in the mouse brain. We validated this finding experimentally, showing a decrease in survival probability in the absence of roX1in vivo. Furthermore, we trained sex-specific TimeFlies clocks and noted significant differences in model predictions and explanations between male and female clocks, suggesting that different pathways drive aging in males and females. Graphical Abstract 
    more » « less
  • Citation Formats
  • MLA
  • APA
  • Chicago
  • BibTeX
  • Save / Share this Record
  • Send to Email