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Rationale: Thymic stromal lymphopoietin (TSLP) and IL-33 are alarmins implicated in EoE pathogenesis by activating multiple cells including mast cells (MCs). Whether TSLP or IL-33 have a role in EoE and whether their activities are distinct requires further investigation.

Methods: Experimental EoE was induced in wild type (WT) Il33 ^-/- and Crlf2 ^-/- mice. TSLP or IL-5 were neutralized using antibodies. Esophageal histopathology was determined by H&E, anti-Ki67, anti-CD31 and anti-MBP staining. Esophageal RNA was subjected to RNA sequencing. Bone marrow-derived MCs were activated with TSLP and IL-13 was determined (ELISA).

Results: TSLP and IL-33 were overexpressed in human and experimental EoE. Human and mouse esophageal MCs displayed the highest level of Crlf2 (TSLPR) compared to other immune cells. Crlf2 ^-/- mice were nearly-completely protected from EoE, and TSLP neutralization resulted in decreased basal cell proliferation, eosinophilia, lamina propria thickening and vascularization. Induction of experimental EoE in Il33 ^-/- mice resulted in reduced eosinophilia but no alterations in tissue remodeling were observed compared to WT mice. RNA sequencing revealed that TSLP regulates the expression of key genes associated with human EoE (e.g. eotaxins, Il19, Klk5, Flg, Il36rn, Il1r2) and suggest a role for TSLP in regulating IL-1 signaling, barrier integrity and epithelial cell differentiation. Experimental EoE was characterized by a MC-associated gene signature and elevated MCs. Activation of MCs with TSLP resulted in secretion of IL-13.

Conclusion: TSLP and IL-33 have non-redundant functions in experimental EoE. This study highlights TSLP as an upstream regulator of IL-13 and a potential therapeutic target for EoE.

Computational epitope prediction remains an unmet need for therapeutic antibody development. We present three complementary approaches for predicting epitope relationships from antibody amino acid sequences. First, we analyze ~18 million antibody pairs targeting ~250 protein families and establish that a threshold of >70% CDRH3 sequence identity among antibodies sharing both heavy and light chain V-genes reliably predicts overlapping-epitope antibody pairs. Next, we develop a supervised contrastive fine-tuning framework for antibody large language models which results in embeddings that better correlate with epitope information than those from pretrained models. Applying this contrastive learning approach to SARS-CoV-2 receptor binding domain antibodies, we achieve 82.7% balanced accuracy in distinguishing same-epitope versus different-epitope antibody pairs and demonstrate the ability to predict relative levels of structural overlap from learning on functional epitope bins (Spearman ρ = 0.25). Finally, we create AbLang-PDB, a generalized model for predicting overlapping-epitope antibodies for a broad range of protein families. AbLang-PDB achieves five-fold improvement in average precision for predicting overlapping-epitope antibody pairs compared to sequence-based methods, and effectively predicts the amount of epitope overlap among overlapping-epitope pairs (ρ = 0.81). In an antibody discovery campaign searching for overlapping-epitope antibodies to the HIV-1 broadly neutralizing antibody 8ANC195, 70% of computationally selected candidates demonstrated HIV-1 specificity, with 50% showing competitive binding with 8ANC195. Together, the computational models presented here provide powerful tools for epitope-targeted antibody discovery, while demonstrating the efficacy of contrastive learning for improving epitope-representation.

DNA-encoded library (DEL) technology has become a powerful tool in modern drug discovery. Fully harnessing its potential requires the use of advanced computational methodologies, which are often available only through proprietary software. This limitation restricts flexibility and accessibility for academic researchers and small biotech companies, hindering the growth of the technology. Here, we present DELi, an open-source DEL informatics platform designed for library design, NGS decoding and calling, and enrichment analysis. To showcase its capabilities, we used DELi to design an in-house custom library (UNC-DEL006), a benzimidazole-based DEL, and performed proof-of-concept selection experiments against Bromodomain-containing Protein 4 (BRD4). The DELi decoding and analysis modules identified top-performing compounds, leading to the off-DNA synthesis of UNC 002-080, which was confirmed as a nanomolar BRD4 binder via isothermal titration calorimetry (ITC). In contrast, a chemically similar compound not prioritized by DELi, UNC 002-083, showed no measurable binding. These results demonstrate DELi as an effective tool for DEL design and analysis. Further, its open-source nature will promote ongoing development and contributions from the DEL community to expand its applications and capabilities.

Small molecule kinase inhibitors are critical in the modern treatment of cancers, evidenced by the existence of over 80 FDA-approved small-molecule kinase inhibitors. Unfortunately, intrinsic or acquired resistance, often causing therapy discontinuation, is frequently caused by mutations in the kinase therapeutic target. The advent of clinical tumor sequencing has opened additional opportunities for precision oncology to improve patient outcomes by pairing optimal therapies with tumor mutation profiles. However, modern precision oncology efforts are hindered by lack of sufficient biochemical or clinical evidence to classify each mutation as resistant or sensitive to existing inhibitors. Structure-based methods show promising accuracy in retrospective benchmarks at predicting whether a kinase mutation will perturb inhibitor binding, but comparisons are made by pooling disparate experimental measurements across different conditions. We present the first prospective benchmark of structure-based approaches on a blinded dataset of in-cell kinase inhibitor affinities to Abl kinase mutants using a NanoBRET reporter assay. We compare NanoBRET results to structure-based methods and their ability to estimate the impact of mutations on inhibitor binding (measured as ΔΔG). Comparing physics-based simulations, Rosetta, and previous machine learning models, we find that structure-based methods accurately classify kinase mutations as inhibitor-resistant or inhibitor-sensitizing, and each approach has a similar degree of accuracy. We show that physics-based simulations are best suited to estimate ΔΔG of mutations that are distal to the kinase active site. To probe modes of failure, we retrospectively investigate two clinically significant mutations poorly predicted by our methods, T315A and L298F, and find that starting configurations and protonation states significantly alter the accuracy of our predictions. Our experimental and computational measurements provide a benchmark for estimating the impact of mutations on inhibitor binding affinity for future methods and structure-based models. These structure-based methods have potential utility in identifying optimal therapies for tumor-specific mutations, predicting resistance mutations in the absence of clinical data, and identifying potential sensitizing mutations to established inhibitors.

While cerebrovascular dysfunction and reactive astrocytosis are extensively characterized hallmarks of Alzheimer's disease (AD) and related dementias, the dynamic relationship between reactive astrocytes and cerebral vessels remains poorly understood. Here, we used jGCaMP8f and two photon microscopy to investigate Ca2+ signaling in multiple astrocyte subcompartments, concurrent with changes in cerebral arteriole activity, in fully awake eight-month-old male and female 5xFAD mice, a model for AD-like pathology, and wild-type (WT) littermates. In the absence of movement, spontaneous Ca2+ transients in barrel cortex occurred more frequently in astrocyte somata, processes, and perivascular regions of 5xFAD mice. However, evoked arteriole dilations (in response to air puff stimulation of contralateral whiskers) and concurrent Ca2+ transients across astrocyte compartments were reduced in 5xFAD mice relative to WTs. Synchronous activity within multi-cell astrocyte networks was also impaired in the 5xFAD group. Using a custom application to assess functional coupling between astrocyte endfeet and immediately adjacent arteriole segments, we detected deficits in Ca2+ response probability in 5xFAD mice. Moreover, endfeet Ca2+ transients following arteriole dilations exhibited a slower onset, reduced amplitude, and lacked relative proportionality to vasomotive activity compared to WTs. The results reveal nuanced alterations in 5xFAD reactive astrocytes highlighted by impaired signaling fidelity between astrocyte endfeet and cerebral arterioles. The results have important implications for the mechanistic underpinnings of brain hypometabolism and the disruption of neurophysiological communication found in AD and other neurodegenerative conditions.

Decades of macaque research established the importance of prefrontal cortex for working memory. Surprisingly, recent human neuroimaging studies demonstrated that the contents of working memory can be decoded from primary visual cortex (V1). However the necessity of this mnemonic information remains unknown and contentious. Here we provide causal evidence that transcranial magnetic stimulation targeting human V1 disrupted the fidelity of visual working memory. Errors increased only for targets remembered in the portion of the visual field disrupted by stimulation. Moreover, concurrently measured electroencephalography confirmed that stimulation disrupted not only memory behavior, but neurophysiological signatures of working memory. These results change the question from whether visual cortex is necessary for working memory to what mechanisms it uses to support memory. Moreover, they point to models in which the mechanisms supporting working memory are distributed across brain regions, including sensory areas that here we show are critical for memory storage.

Metabolic dysfunction-associated steatohepatitis (MASH) represents a progressive form of steatotic liver disease which increases the risk for fibrosis and advanced liver disease. The accumulation of discrete species of bioactive lipids has been postulated to activate signaling pathways that promote inflammation and fibrosis. However, the key pathogenic lipid species is a matter of debate. We explored candidates using various dietary, molecular, and genetic models. Mice fed a choline-deficient L-amino acid-defined high-fat diet (CDAHFD) developed steatohepatitis and manifested early markers of liver fibrosis associated with increased cholesterol content in liver lipid droplets within 5 days without any changes in total liver cholesterol content. Treating mice with antisense oligonucleotides (ASOs) against Coenzyme A synthase (Cosay) or treatment with bempedoic acid or atorvastatin decreased liver lipid droplet cholesterol content and prevented CDAHFD-induced MASH and the fibrotic response. All these salutary effects were abrogated with dietary cholesterol supplementation. Analysis of human liver samples demonstrated that cholesterol in liver lipid droplets was increased in humans with MASH and liver fibrosis and was higher in PNPLA3 I148M (variants rs738409) than in HSD17B13 variants (rs72613567). Together, these data identify cholesterol in liver lipid droplets as a critical mediator of MASH and demonstrate that COASY knockdown and bempedoic acid are novel therapeutic approaches to reduce liver lipid droplet cholesterol content and thereby prevent the development of MASH and liver fibrosis.

Significance statement: Metabolic dysfunction-associated steatohepatitis (MASH) is a progressive liver disease linked to fibrosis. The role of specific lipid species in its pathogenesis remains debated. Using dietary, molecular, and genetic models, we found that mice on a choline-deficient, high-fat diet (CDAHFD) developed steatohepatitis and early fibrosis, marked by increased cholesterol in liver lipid droplets within five days. Targeting COASY with antisense oligonucleotides or treating with bempedoic acid or atorvastatin reduced lipid droplet cholesterol and prevented MASH. However, dietary cholesterol supplementation negated these effects. Human liver samples confirmed elevated lipid droplet cholesterol in MASH and fibrosis, especially in PNPLA3 I148M carriers. These findings highlight cholesterol reduction as a potential MASH therapy.

Despite the importance of liver secreted proteins in health and disease, an understanding of their regulation by biological variables such as sex and circadian time is lacking. Here, we validated a well-maintained, dynamic, and unbiased ex vivo assay of liver protein secretion, revealing novel findings. Proteomic analyses uncovered hundreds of sex-dependent hepatokines involved in lipid metabolism, sulfation, and serine protease inhibition, as well as time-dependent hepatokines. Many apolipoproteins and well-characterized plasma proteins were secreted more during daytime, whereas several carboxylesterases and proteins with unconventional secretion tended to be secreted more during nighttime. Time-dependent secreted proteins were transcriptionally regulated by the molecular clock and dysregulated by chronic jet lag-induced circadian misalignment. Finally, we showed that the clock-dependent liver secreted protein endostatin tunes the expression of metabolic genes in white adipose tissue during daytime in female mice. Together, these findings provide key insights into circadian control and sexual dimorphism of liver secreted proteins, which serve as clinical biomarkers and novel therapeutic targets.

Retinal ganglion cells in the mammalian central nervous system fail to regenerate following injury, with the capacity to survive and regrow varying by cell type. This variability may be linked to differences in developmental programs that overlap with the genetic pathways that mediate regeneration. To explore this correlation, we compared the structural changes in mouse retinal ganglion cells during development with those occurring after axonal injury. The dendritic trees of over 1,000 ganglion cells were reconstructed at different developmental stages, revealing that each cell type follows a distinct timeline. ON-sustained (sONα) cells reach maturity by P14, whereas ON-transient (tONα) cells achieve their maximum dendritic size by P10. Modeling of the dendritic changes indicate that while sONα and tONα follow similar growth programs the onset of growth was later in sONα. After optic nerve crush, the remodeling of dendritic architecture differed between the two cell-types. sONα cells exhibited rapid dendritic shrinkage, while tONα cells shrank more gradually with changes in branching features. Following injury, sONα cells reverted to an earlier developmental state than tONα cells. In addition, after co-deletion of PTEN and SOC3, neurons appeared to regress further back in developmental time. Our results provide evidence that a ganglion cell's resilience to injury and regenerative potential is predicted by its maturation timeline. Understanding these intrinsic differences could inform targeted neuroprotective interventions.