Rice University Research Repository
The Rice Research Repository (R-3) provides access to research produced at Rice University, including theses and dissertations, journal articles, research center publications, datasets, and academic journals. Managed by Fondren Library, R-3 is indexed by Google and Google Scholar, follows best practices for preservation, and provides DOIs to facilitate citation. Woodson Research Center collections, including Rice Images and Documents and the Task Force on Slavery, Segregation, and Racial Injustice, have moved here.
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What Instagram Means to Me: Links Between Social Anxiety, Instagram Contingent Self-worth, and Automated Textual Analysis of Linguistic Authenticity
(Springer Nature, 2024) Brandao, Beatriz M.; Denny, Bryan T.
While research has shown mixed effects of social media on mental health and well-being, little is known about the association between social media attitudes and objective measures of social interaction, such as linguistic authenticity. This study examined the relationship between self-reported social anxiety, linguistic authenticity, and Instagram contingent self-worth (ICSW). A total of 149 adults with active Instagram accounts completed online questionnaires and shared their Instagram comment data. Automated linguistic analysis of authenticity was performed on participants’ comment data using validated algorithms. Multiple linear regression showed that ICSW significantly moderated the relationship between social anxiety and linguistic authenticity, whereby higher levels of social anxiety marginally predicted lower linguistic authenticity at high levels of ICSW. As social media use continues to rise, this study emphasizes the need to explore the impact of social media interactions on emotional and social well-being.
Decriptive Enhancements of the Rice Family Papers
(Rice University, 2024) Sanders, Dru
RACER-m leverages structural features for sparse T cell specificity prediction
(AAAS, 2024) Wang, Ailun; Lin, Xingcheng; Chau, Kevin Ng; Onuchic, José N.; Levine, Herbert; George, Jason T.; Center for Theoretical Biological Physics
Reliable prediction of T cell specificity against antigenic signatures is a formidable task, complicated by the immense diversity of T cell receptor and antigen sequence space and the resulting limited availability of training sets for inferential models. Recent modeling efforts have demonstrated the advantage of incorporating structural information to overcome the need for extensive training sequence data, yet disentangling the heterogeneous TCR-antigen interface to accurately predict MHC-allele-restricted TCR-peptide interactions has remained challenging. Here, we present RACER-m, a coarse-grained structural model leveraging key biophysical information from the diversity of publicly available TCR-antigen crystal structures. Explicit inclusion of structural content substantially reduces the required number of training examples and maintains reliable predictions of TCR-recognition specificity and sensitivity across diverse biological contexts. Our model capably identifies biophysically meaningful point-mutant peptides that affect binding affinity, distinguishing its ability in predicting TCR specificity of point-mutants from alternative sequence-based methods. Its application is broadly applicable to studies involving both closely related and structurally diverse TCR-peptide pairs.
Measurement of multijet azimuthal correlations and determination of the strong coupling in proton-proton collisions at $$\sqrt{s}=13\,\text {Te}\hspace{-.08em}\text {V} $$
(Springer Nature, 2024) CMS Collaboration
A measurement is presented of a ratio observable that provides a measure of the azimuthal correlations among jets with large transverse momentum $$p_{\textrm{T}}$$. This observable is measured in multijet events over the range of $$p_{\textrm{T}} = 360$$–$$3170\,\text {Ge}\hspace{-.08em}\text {V} $$based on data collected by the CMS experiment in proton-proton collisions at a centre-of-mass energy of 13$$\,\text {Te}\hspace{-.08em}\text {V}$$, corresponding to an integrated luminosity of 134$$\,\text {fb}^{-1}$$. The results are compared with predictions from Monte Carlo parton-shower event generator simulations, as well as with fixed-order perturbative quantum chromodynamics (pQCD) predictions at next-to-leading-order (NLO) accuracy obtained with different parton distribution functions (PDFs) and corrected for nonperturbative and electroweak effects. Data and theory agree within uncertainties. From the comparison of the measured observable with the pQCD prediction obtained with the NNPDF3.1 NLO PDFs, the strong coupling at the Z boson mass scale is $$\alpha _\textrm{S} (m_{{\textrm{Z}}}) =0.1177 \pm 0.0013\, \text {(exp)} _{-0.0073}^{+0.0116} \,\text {(theo)} = 0.1177_{-0.0074}^{+0.0117}$$, where the total uncertainty is dominated by the scale dependence of the fixed-order predictions. A test of the running of $$\alpha _\textrm{S}$$in the $$\,\text {Te}\hspace{-.08em}\text {V}$$region shows no deviation from the expected NLO pQCD behaviour.
Reassessing the exon–foldon correspondence using frustration analysis
(National Academy of Sciences, 2024) Galpern, Ezequiel A.; Jaafari, Hana; Bueno, Carlos; Wolynes, Peter G.; Ferreiro, Diego U.; Center for Theoretical Biological Physics
Protein folding and evolution are intimately linked phenomena. Here, we revisit the concept of exons as potential protein folding modules across a set of 38 abundant and conserved protein families. Taking advantage of genomic exon–intron organization and extensive protein sequence data, we explore exon boundary conservation and assess the foldon-like behavior of exons using energy landscape theoretic measurements. We found deviations in the exon size distribution from exponential decay indicating selection in evolution. We show that when taken together there is a pronounced tendency to independent foldability for segments corresponding to the more conserved exons, supporting the idea of exon–foldon correspondence. While 45% of the families follow this general trend when analyzed individually, there are some families for which other stronger functional determinants, such as preserving frustrated active sites, may be acting. We further develop a systematic partitioning of protein domains using exon boundary hotspots, showing that minimal common exons correspond with uninterrupted alpha and/or beta elements for the majority of the families but not for all of them.