Berkeley College

ABSTRACT TESOL educators have access to diverse didactic resources, including popular music and songwriting, which can be especially effective tools for writing instruction. This conceptual article explores the use of sones—the song verses of son jarocho, a folkloric regional music genre from southeastern Mexico—as a medium for poetic (re)writing, reflection, and social critique in the TESOL classroom. The improvisational tradition of son jarocho allows language‐minoritized students to creatively reinterpret the genre by emphasizing individual experience and dynamic expression. We focus on the Chicane/x band, Las Cafeteras, and their (re)interpretation of the centuries‐old son (son jarocho song), “Señor Presidente/Mr. President” as a catalyst for son jarocho‐based writing practices. We highlight this Mexican musical tradition as a resource for teachers to foster creativity and criticality in TESOL classrooms. Co‐authored with Las Cafeteras lead singer‐songwriter, Denise Carlos, this article theorizes son jarocho as a powerful tool for cultivating creativity and critical literacy while envisioning more equitable futures for immigrants and racialized multilingual communities.

Although machine learning has transformed protein structure prediction of folded protein ground states with remarkable accuracy, intrinsically disordered proteins and regions (IDPs/IDRs) are defined by diverse and dynamical structural ensembles that are predicted with low confidence by algorithms such as AlphaFold and RoseTTAFold. We present a new machine learning method, IDPForge (IntrinsicallyDisorderedProtein,FOlded and disorderedRegionGEnerator), that exploits a transformer protein language diffusion model to create all-atom IDP ensembles and IDR disordered ensembles that maintains the folded domains. IDPForge does not require sequence-specific training, back transformations from coarse-grained representations, nor ensemble reweighting, as in general the created IDP/IDR conformational ensembles show good agreement with solution experimental data, and options for biasing with experimental restraints are provided if desired. We envision that IDPForge with these diverse capabilities will facilitate integrative and structural studies for proteins that contain intrinsic disorder, and is available as an open source resource for general use.

Scholars seek to understand campaign donor behavior and its effects on candidates. Researchers generally agree that individual donors are more ideologically extreme than most organizational donors but disagree as to whether small individual donors (those giving less than $200 per cycle) are especially correlated to extremist candidates. We study the relationship between small individual donors and legislators’ NPAT and CFscores for the California, Washington, and Oregon legislatures between 2016 and 2022. We find both that individual donors correlate to more partisan legislators in general and that the correlation between donors and politically polarized legislators is even greater for small individual donors than for large individual donors in most cases.

With digital learning environments becoming more prevalent, the ease with which generative AI enables the scalable production of real-time, automated feedback holds the potential to reshape learning and teaching experiences. This meeting report synthesizes the interdisciplinary perspectives of 50 scholars from educational psychology, computer science, science education, and the learning sciences on the use of generative AI for feedback and its promises and risks in educational practice. We highlight points of convergence in the scholarship, identify areas of debate and unresolved challenges, and outline open questions and future directions for research and educational practice that emerged from structured small-group activities designed to bridge disciplinary barriers.

Abstract A design-based research project evaluating novel resources for culturally situated embodied geometry learning occasioned an opportunity for the researchers to consider conceptual relations between two prominent neo-Vygotskian theories, the semiotic–cultural theory of objectification by Luis Radford and instrumental genesis by Pierre Vérillon and Pierre Rabardel. We examine the case of Nath, an 11-year-old student who spontaneously created sign–tool hybridity in the form of a single artifact functioning fluidly as either a semiotic means of objectification or a cognitive instrument supporting his inquiry and argumentation. From an ecological standpoint, the hybridity arose through a perception–action coupling in which the artifact’s meaning and utility co-evolved with the unfolding cultural activity. Analyzing the artifact exclusively as either semiotic or instrumental may compromise the synthetic coherence of an enactivist theoretical modeling. Interfacing epistemologically affiliated theoretical perspectives on the ontology and cognitive function of educational resources may enable researchers to better understand the resources’ rich pedagogical affordances and, thereby, render these affordances accessible to students. Moreover, practicing epistemologically pluralist learning environments, where students are left to tinker with available resources into new semiotic–cum–instrumental objects of their own device, in turn may afford researchers likewise to tinker with available theories toward greater explanatory power.

I formally characterize three objectives of causally-oriented empirical research: identification, explanation, and generalization. I then analyze some logical relationships between them. Loosely, causal identification is measurability of treatment effects from data; causal explanation occurs when a unique theoretical model is consistent with observed data; and causal generalization is application of a causal model from one setting to another. I show that explanation implies identification but not vice versa; that explanation is possible even if no pairwise causal effects are identified for any variables; and that improvement in identification also improves explanation. Causal generalization requires a known mapping of causal models across cases based on the background or contextual characteristics of each case. Necessary conditions to recover this mapping empirically are stringent and require theoretical commitments. Overall the results show a strong connection between theoretical models and causal inference.

Abstract Copy number variations (CNVs) are a hallmark of cancer genomes, yet the relationship between CNV and gene expression is not strictly deterministic. Some genes maintain stable expression despite copy number changes through regulatory compensation. Identifying these dosage-insensitive genes is challenging, requiring methods that distinguish true regulatory escape from technical noise in heterogeneous single-cell data. Here, we present a contrastive learning framework that learns a shared latent space aligning single-cell RNA-seq expression profiles with inferred CNV patterns. Our key innovation is hard negative mining: explicitly training on cell pairs with similar CNV but divergent expression patterns, which represent potential dosage insensitivity. By combining InfoNCE loss with hard negative triplet loss, we learn embeddings where expression-CNV distance quantifies regulatory concordance. We apply this framework to 10 lung adenocarcinoma patients (80k cells) from the GSE131907 atlas, classifying cancer cells as “concordant” (expression follows CNV) or “discordant” (expression escapes CNV). Differential expression analysis between these groups reveals two gene categories: escape genes upregulated in discordant cells despite CNV status, and compensation genes downregulated in discordant cells. Pooled analysis across 40,775 cancer cells identifies significant escape genes including VSIG4, FCGR1A, TREM2 , and MARCO , as well as compensation genes such as MALAT1, CCL5 , and CD8A . These genes represent candidate therapeutic targets and biomarker hypotheses for CNV-independent tumor behavior. Our approach provides a generalizable frame-work for discovering regulatory escape mechanisms in cancer using standard single-cell RNA-seq data.

Neonatal life is marked by rapid antigen exposure, necessitating establishment of peripheral immune tolerance via conversion of naive CD4+ T cells into Tregs. We demonstrated heightened capacity for FOXP3 expression and tolerogenic function among cord blood versus adult blood naive CD4+ T cells. Further, this was linked to a distinct cord blood metabolic profile and elevated neonatal expression of the NADase, CD38. Early-life naive CD4+ T cells demonstrated a metabolic preference for glycolysis, which directly facilitated their differentiation trajectory. We revealed an age-dependent gradient in CD38 levels on naive CD4+ T cells and showed that high CD38 expression contributes to the glycolytic state and tolerogenic potential of neonatal CD4+ T cells, effects mediated at least partly via the NAD-dependent deacetylase SIRT1. Thus, the early-life window for peripheral tolerance in humans is critically enabled by the immunometabolic state of the naive CD4+ compartment.