Birinapant Reshapes the Tumor Immunopeptidome and Enhances Antigen Presentation.

Birinapant, an antagonist of the inhibitor of apoptosis proteins, upregulates MHCs in tumor cells and displays a better tumoricidal effect when used in combination with immune checkpoint inhibitors, indicating that Birinapant may affect the antigen presentation pathway; however, the mechanism remains elusive. Based on high-resolution mass spectrometry and in vitro and in vivo models, we adopted integrated genomics, proteomics, and immunopeptidomics strategies to study the mechanism underlying the regulation of tumor immunity by Birinapant from the perspective of antigen presentation. Firstly, in HT29 and MCF7 cells, Birinapant increased the number and abundance of immunopeptides and source proteins. Secondly, a greater number of cancer/testis antigen peptides with increased abundance and more neoantigens were identified following Birinapant treatment. Moreover, we demonstrate the existence and immunogenicity of a neoantigen derived from insertion/deletion mutation. Thirdly, in HT29 cell-derived xenograft models, Birinapant administration also reshaped the immunopeptidome, and the tumor exhibited better immunogenicity. These data suggest that Birinapant can reshape the tumor immunopeptidome with respect to quality and quantity, which improves the presentation of CTA peptides and neoantigens, thus enhancing the immunogenicity of tumor cells. Such changes may be vital to the effectiveness of combination therapy, which can be further transferred to the clinic or aid in the development of new immunotherapeutic strategies to improve the anti-tumor immune response.

Supramolecular Nanofibers with Superior Bioactivity to Insulin-Like Growth Factor-I.

Bioactive peptides derived from proteins generally need to be folded into secondary structures to activate downstream signaling pathways. However, synthetic peptides typically form random-coils, thus losing their bioactivities. Here, we show that by introducing a self-assembling peptide motif and using different preparation pathways, a peptide from insulin-like growth factor-I (IGF-1) can be folded into an α-helix and ß-sheet. The ß-sheet one exhibits a low dissociation constant to the IGF-1 receptor (IGF-1R, 11.5 nM), which is only about 3 times higher than that of IGF-1 (4.3 nM). However, the α-helical one and the peptide without self-assembling motif show weak affinities to IGF-1R ( KD = 179.1 and 321.6 nM, respectively). At 10 nM, the ß-sheet one efficiently activates the IGF-1 downstream pathway, significantly enhancing HUVEC proliferation and preventing cell apoptosis. The ß-sheet peptide shows superior performance to IGF-1 in vivo, and it improves ischemic hind-limb salvage by significantly reducing muscle degradation and enhancing limb vascularization. Our study provides a useful strategy to constrain peptides into different conformations, which may lead to the development of supramolecular nanomaterials mimicking biofunctional proteins.

Diglycine Enables Rapid Intrabacterial Hydrolysis for Activating Anbiotics against Gram-negative Bacteria.

Antimicrobial drug resistance demands novel approaches for improving the efficacy of antibiotics, especially against Gram-negative bacteria. Herein, we report that conjugating a diglycine (GG) to an antibiotic prodrug drastically accelerates intrabacterial ester-bond hydrolysis required for activating the antibiotic. Specifically, the attachment of GG to chloramphenicol succinate (CLsu) generates CLsuGG, which exhibits about an order of magnitude higher inhibitory efficacy than CLsu against Escherichia coli. Further studies reveal that CLsuGG undergoes rapid hydrolysis, catalyzed by intrabacterial esterases (e.g., BioH and YjfP), to generate chloramphenicol (CL) in E. coli. Importantly, the conjugate exhibits lower cytotoxicity to bone marrow stromal cells than CL. Structural analogues of CLsuGG indicate that the conjugation of GG to an antibiotic prodrug is an effective strategy for accelerating enzymatic prodrug hydrolysis and enhancing the antibacterial efficacy of antibiotics.

Topic modeling on clinical social work notes for exploring social determinants of health factors.

Objective: Existing research on social determinants of health (SDoH) predominantly focuses on physician notes and structured data within electronic medical records. This study posits that social work notes are an untapped, potentially rich source for SDoH information. We hypothesize that clinical notes recorded by social workers, whose role is to ameliorate social and economic factors, might provide a complementary information source of data on SDoH compared to physician notes, which primarily concentrate on medical diagnoses and treatments. We aimed to use word frequency analysis and topic modeling to identify prevalent terms and robust topics of discussion within a large cohort of social work notes including both outpatient and in-patient consultations. Materials and methods: We retrieved a diverse, deidentified corpus of 0.95 million clinical social work notes from 181 644 patients at the University of California, San Francisco. We conducted word frequency analysis related to ICD-10 chapters to identify prevalent terms within the notes. We then applied Latent Dirichlet Allocation (LDA) topic modeling analysis to characterize this corpus and identify potential topics of discussion, which was further stratified by note types and disease groups. Results: Word frequency analysis primarily identified medical-related terms associated with specific ICD10 chapters, though it also detected some subtle SDoH terms. In contrast, the LDA topic modeling analysis extracted 11 topics explicitly related to social determinants of health risk factors, such as financial status, abuse history, social support, risk of death, and mental health. The topic modeling approach effectively demonstrated variations between different types of social work notes and across patients with different types of diseases or conditions. Discussion: Our findings highlight LDA topic modeling's effectiveness in extracting SDoH-related themes and capturing variations in social work notes, demonstrating its potential for informing targeted interventions for at-risk populations. Conclusion: Social work notes offer a wealth of unique and valuable information on an individual's SDoH. These notes present consistent and meaningful topics of discussion that can be effectively analyzed and utilized to improve patient care and inform targeted interventions for at-risk populations.

Spatial cell-type enrichment predicts mouse brain connectivity.

A fundamental neuroscience topic is the link between the brain's molecular, cellular, and cytoarchitectonic properties and structural connectivity. Recent studies relate inter-regional connectivity to gene expression, but the relationship to regional cell-type distributions remains understudied. Here, we utilize whole-brain mapping of neuronal and non-neuronal subtypes via the matrix inversion and subset selection algorithm to model inter-regional connectivity as a function of regional cell-type composition with machine learning. We deployed random forest algorithms for predicting connectivity from cell-type densities, demonstrating surprisingly strong prediction accuracy of cell types in general, and particular non-neuronal cells such as oligodendrocytes. We found evidence of a strong distance dependency in the cell connectivity relationship, with layer-specific excitatory neurons contributing the most for long-range connectivity, while vascular and astroglia were salient for short-range connections. Our results demonstrate a link between cell types and connectivity, providing a roadmap for examining this relationship in other species, including humans.

DeepHeme: A generalizable, bone marrow classifier with hematopathologist-level performance.

Morphology-based classification of cells in the bone marrow aspirate (BMA) is a key step in the diagnosis and management of hematologic malignancies. However, it is time-intensive and must be performed by expert hematopathologists and laboratory professionals. We curated a large, high-quality dataset of 41,595 hematopathologist consensus-annotated single-cell images extracted from BMA whole slide images (WSIs) containing 23 morphologic classes from the clinical archives of the University of California, San Francisco. We trained a convolutional neural network, DeepHeme, to classify images in this dataset, achieving a mean area under the curve (AUC) of 0.99. DeepHeme was then externally validated on WSIs from Memorial Sloan Kettering Cancer Center, with a similar AUC of 0.98, demonstrating robust generalization. When compared to individual hematopathologists from three different top academic medical centers, the algorithm outperformed all three. Finally, DeepHeme reliably identified cell states such as mitosis, paving the way for image-based quantification of mitotic index in a cell-specific manner, which may have important clinical applications.

Malaria-driven expansion of adaptive-like functional CD56-negative NK cells correlates with clinical immunity to malaria.

Natural killer (NK) cells likely play an important role in immunity to malaria, but the effect of repeated malaria on NK cell responses remains unclear. Here, we comprehensively profiled the NK cell response in a cohort of 264 Ugandan children. Repeated malaria exposure was associated with expansion of an atypical, CD56neg population of NK cells that differed transcriptionally, epigenetically, and phenotypically from CD56dim NK cells, including decreased expression of PLZF and the Fc receptor γ-chain, increased histone methylation, and increased protein expression of LAG-3, KIR, and LILRB1. CD56neg NK cells were highly functional and displayed greater antibody-dependent cellular cytotoxicity than CD56dim NK cells. Higher frequencies of CD56neg NK cells were associated with protection against symptomatic malaria and high parasite densities. After marked reductions in malaria transmission, frequencies of these cells rapidly declined, suggesting that continuous exposure to Plasmodium falciparum is required to maintain this modified, adaptive-like NK cell subset.

Pericyte-to-endothelial cell signaling via vitronectin-integrin regulates blood-CNS barrier.

Endothelial cells of blood vessels of the central nervous system (CNS) constitute blood-CNS barriers. Barrier properties are not intrinsic to these cells; rather they are induced and maintained by CNS microenvironment. Notably, the abluminal surfaces of CNS capillaries are ensheathed by pericytes and astrocytes. However, extrinsic factors from these perivascular cells that regulate barrier integrity are largely unknown. Here, we establish vitronectin, an extracellular matrix protein secreted by CNS pericytes, as a regulator of blood-CNS barrier function via interactions with its integrin receptor, α5, in endothelial cells. Genetic ablation of vitronectin or mutating vitronectin to prevent integrin binding, as well as endothelial-specific deletion of integrin α5, causes barrier leakage in mice. Furthermore, vitronectin-integrin α5 signaling maintains barrier integrity by actively inhibiting transcytosis in endothelial cells. These results demonstrate that signaling from perivascular cells to endothelial cells via ligand-receptor interactions is a key mechanism to regulate barrier permeability.

Physical Activity Associates With Lower Systemic Inflammatory Gene Expression in Rheumatoid Arthritis.

OBJECTIVE: While general population studies have shown inverse associations between physical activity and common inflammatory biomarkers, the effects of physical activity on inflammatory gene expression and signaling pathways in rheumatoid arthritis (RA) remain unknown. We aimed to determine whether physical activity independently associates with expression of inflammatory genes among people with RA. METHODS: This was a prospective observational study of adults with RA. Physical activity was measured by quantitative actigraphy over 7 consecutive days, and peripheral blood collected during the same time period was used for RNA sequencing followed by differential gene expression, pathway, and network analyses. RESULTS: Actigraphy and RNA sequencing data were evaluated in 35 patients. The cohort had a mean age of 56 (SD 12) years, and was 91% female, 31% White, 9% Black, 9% Asian, and 40% Hispanic. We found 767 genes differentially expressed (adjusted P < 0.1) between patients in the greatest vs lowest physical activity tertiles, after adjusting for sex, age, race, and ethnicity. The most active patients exhibited dose-dependent downregulation of several immune signaling pathways implicated in RA pathogenesis. These included CD40, STAT3, TREM-1, interleukin (IL)-17A, IL-8, Toll-like receptor, and interferon (IFN) signaling pathways. Upstream cytokine activation state analysis predicted reduced activation of tumor necrosis factor-α and IFN in the most active group. In sensitivity analyses, we adjusted for RA disease activity and physical function and found consistent results. CONCLUSION: Patients with RA who were more physically active had lower expression of immune signaling pathways implicated in RA pathogenesis, even after adjusting for disease activity, suggesting that physical activity may confer a protective effect in RA.

An Ultrashort Peptide-Based Supramolecular Hydrogel Mimicking IGF-1 to Alleviate Glucocorticoid-Induced Sarcopenia.

Sarcopenia is a common disease in older people due to aging, and it can also occur in midlife because of diseases including cancer. Sarcopenia, characterized by rapid loss of muscle mass and accelerated loss of function, can lead to adverse outcomes such as frailty, falls, and even mortality. The development of pharmacological and therapeutic approaches to treat sarcopenia remains challenging. The growth status and quantity of myoblasts are the key factors directly affecting muscle formation. Therefore, enhancing the function of myoblasts is crucial for the treatment of sarcopenia. In our study, we introduced an insulin-like growth factor-I (IGF-1) mimicking supramolecular nanofibers/hydrogel formed by Nap-FFGSSSR that effectively promoted proliferation and significantly reduced dexamethasone-induced apoptosis of myoblasts, assisted myoblasts to differentiate into myotubes, and prevented the fibrosis of muscle tissue and the deposition of collagen, ultimately achieving outstanding effects in the treatment of sarcopenia. The RNA-sequencing results revealed that our nanofibers possessed similar bioactivity to the growth factor IGF-1, which increased the phosphorylation of Akt by activating the insulin signaling pathway. We prepared novel supramolecular nanomaterials to reverse glucocorticoid-induced myoblast dysfunction, which was promising for the treatment of muscular atrophy. In addition, we envisioned the generation of biofunctional nanomaterials by molecular self-assembly for the treatment of chronic diseases in middle-aged and older people.

Structure-Activity Relationship of Peptide-Conjugated Chloramphenicol for Inhibiting Escherichia coli.

Intravenous administration of a prodrug, chloramphenicol succinate (CLsu), is ineffective. Recently, we have shown that conjugation of diglycine of CLsu (CLsuGG) not only increases the antibiotic efficacy against Escherichia coli but also reduces adverse drug effects against bone marrow stromal cells. Here, we report the synthesis of structural analogues of CLsuGG and their activities against E. coli. These analogues reveal several trends: (i) except the water-insoluble analogues, the attachment of peptides to CLsu enhances the efficacy of the prodrugs; (ii) negative charges, high steric hindrance in the side chains, or a rigid diester decreases the activities of prodrugs in comparison to CLsuGG; (iii) dipeptides apparently increase the efficacy of the prodrugs most effectively; and so forth. This work suggests that conjugating peptides to CLsu effectively modulates the properties of prodrugs. The structure-activity relationship of these new conjugates may provide useful insights for expanding the pool of antibiotics.