Biomarkers are essential tools for disease detection, risk assessment, therapeutic monitoring, and precision medicine. However, biomarker data are dispersed across heterogeneous resources, inconsistently reported in the literature, and rarely standardized for computational use. This fragmentation limits reproducibility, cross-study integration, and the discovery of novel biomarker and disease relationships. We developed BiomarkerKB, designed to harmonize and integrate biomarker information under a standardized data model. The model captures both core fields (biomarker entity, disease/condition, and exposure agent) and contextual metadata (specimen, biomarker role, evidence, and provenance). Biomarker data and related annotations were either curated from publications or collected from public resources. The initial release of BiomarkerKB contains over 200,000 biomarker-disease associations spanning genes, proteins, metabolites, glycans, and chemical elements. BiomarkerKB data were ingested into a Neo4j-based knowledge graph that comprises more than 300,000 nodes and 1.2 million edges. A publicly accessible web portal provides a unified framework for biomarker knowledge exploration and discovery.

Biomarkers are essential tools for disease detection, risk assessment, therapeutic monitoring, and precision medicine. However, biomarker data are dispersed across heterogeneous resources, inconsistently reported in the literature, and rarely standardized for computational use. This fragmentation limits reproducibility, cross-study integration, and the discovery of novel biomarker and disease relationships. We developed BiomarkerKB, a knowledgebase designed to harmonize and integrate biomarker information under a standardized data model. The model follows the FDA-NIH BEST biomarker definition and captures both core fields (biomarker entity, condition, exposure agent) and contextual metadata (specimen, biomarker role, evidence, provenance). Biomarker data and related annotations were either curated from publications or collected from public resources (e.g., OpenTargets, GWAS Catalog, ClinVar, CIViC, OncoMX) and also contributed by Common Fund Data Coordinating Centers and Early Detection Research Network (EDRN). Standardization was achieved using ontologies and reference resources such as Disease Ontology, UBERON, UniProtKB, and HUGO Gene Nomenclature Committee (HGNC) gene symbols. BiomarkerKB data were ingested into a Neo4j-based knowledge graph and integrated with the Common Fund Data Ecosystem (CFDE) Knowledge Graph. The initial release of BiomarkerKB contains over 200,000 biomarker-disease associations spanning genes, proteins, metabolites, glycans, and chemical elements. The knowledge graph comprises more than 300,000 nodes and 1.2 million edges, enabling structured exploration of biomarker relationships within CFDE data as demonstrated through knowledge graph query-based use cases presented in this study. A publicly accessible web portal (https://biomarkerkb.org) provides keyword search, filtering, data downloads, and access to graph visualization to support both researchers and computational analyses. BiomarkerKB addresses a critical gap in biomarker informatics by providing a unified, FAIR, and computationally enabled framework for biomarker knowledge access. ### Competing Interest Statement The authors have declared no competing interest. NIH Common Fund, https://ror.org/001d55x84, U24OD038423, OT2OD032092

Background: Breast cancer cell heterogeneity and cellular fate are governed by a variety of molecular mechanisms. The LINCS (Library of Integrated Network-based Cellular Signatures) consortium performed multi-omics experiments on normal breast epithelial cells, MCF10a, to deduce temporal mechanisms of regulation and cell state signatures contributing to pro-oncogenic phenotypes. Methods: Normal breast epithelial cells were treated with oncogenic ligands such as EGF, HGF, and OSM, and multi-modal measurements including Reverse phase protein Assay (RPPA), RNA-seq, ATAC-seq, and Cyclic immune-fluorescence (Cyclic-IF) were performed. Result: In our integrated analyses of the data to elucidate mechanisms, contextual functional networks were constructed by integrating protein signaling, transcription factor activity, and gene expression. Phenotypic changes in response to the ligands consisted of cell cycle modifications leading to oncogenic events such as loss of apoptosis and induction of EMT (Epithelial to Mesenchymal Transition). Activation of mTOR was observed with all ligands, which led to the activation of E2F1. Downstream transcriptomic regulation of E2F1 led to an increase in both oncogenic signaling and EMT. Additionally, under OSM treatment, activation of STAT3 facilitated the enhancement of EMT via transcriptomic regulation of JUN and FOS. These findings were further validated using the chromatin changes seen in ATAC-seq and protein localization as seen in Cyclic-IF assay. Conclusion: This analysis provides valuable insights into the mechanisms of transcriptional regulation during oncogenesis in normal breast cells treated with growth factors and can aid in the discovery of novel drug targets and treatments

We performed a systems vaccinology analysis to investigate immune responses in humans to an H5N1 influenza vaccine, with and without the AS03 adjuvant, to identify factors influencing antibody response magnitude and durability. Our findings revealed a platelet and adhesion-related blood transcriptional signature on day 7 that predicted the longevity of the antibody response, suggesting a potential role for platelets in modulating antibody response durability. As platelets originate from megakaryocytes, we explored the effect of thrombopoietin (TPO)-mediated megakaryocyte activation on antibody response longevity. We found that TPO administration enhanced the durability of vaccine-induced antibody responses. TPO-activated megakaryocytes also promoted survival of human bone-marrow plasma cells through integrin β1/β2-mediated cell–cell interactions, along with survival factors APRIL and the MIF–CD74 axis. Using machine learning, we developed a classifier based on this platelet-associated signature, which predicted antibody response longevity across six vaccines from seven independent trials, highlighting a conserved mechanism for vaccine durability. Pulendran and colleagues define a molecular signature that can be used to predict the durability of antibody responses to vaccination and reveal important insights into the mechanisms by which vaccines induce durable immunity.

Acute T-cell-mediated transplant rejection, the earliest contributor to immunological graft failure responds variably to T-cell suppression. Early rejection can co-exist with donor-specific antibodies which also shorten graft survival, without affecting graft histology visibly. Here, during early liver transplant rejection, blood leukocytes manifest primed T-cells with heat shock protein (HSP) signaling and transcriptional programs for memory cell expansion. Corresponding biopsies demonstrate upregulated immune synapse and proteasomal genes in T-cell-infiltrated portal and central regions of the liver lobule. With donor-specific antibodies, the intervening intralobular region demonstrates a germinal-center-like allograft response with upregulated CD40, chemokine, T-follicular and complement signaling, which intensifies along the direction of sinusoidal blood flow from portal to central regions. Proteasomal and HSP90 inhibitors suppress donor-specific alloresponses of T- and B-cells in blood samples from patients with early rejection. The molecular injury spectrum of early rejection is complex, spatially differentiated and reveals novel early immunosuppressive strategies to extend graft survival. ### Competing Interest Statement The authors have declared no competing interest.

Cellular metabolism is a complex process involving the consumption and production of metabolites, as well as the regulation of enzyme synthesis and activity. Modeling of metabolic processes is important to understand the underlying mechanisms, with a wide range of applications in metabolic engineering and health sciences. Cybernetic modeling is a powerful technique that accounts for unknown intricate regulatory mechanisms in complex cellular processes. It models regulation as goal-oriented, where the levels and activities of enzymes are modulated by the cybernetic control variables to achieve the cybernetic objective. This study used cybernetic model to study the enzyme competition between arachidonic acid (AA) and eicosapentaenoic acid (EPA) metabolism in murine macrophages. AA and EPA compete for the shared enzyme cyclooxygenase. Upon external stimuli, AA produces proinflammatory 2-series prostaglandins and EPA metabolizes to antiinflammatory 3-series prostaglandins, where proinflammatory and antiinflammatory responses are necessary for homeostasis. The cybernetic model adequately captured the experimental data for control and EPA-supplemented conditions. The model is validated by performing an F-test, conducting leave-one-out-metabolite cross-validation, and predicting an unseen experimental condition. The cybernetic variables provide insights into the competition between AA and EPA for the cyclooxygenase enzyme. Predictions from our model suggest that the system undergoes a switch from a predominantly proinflammatory state in the control to an antiinflammatory state with EPA- supplementation. The model can also be used to analytically determine the AA and EPA concentrations required for the switch to occur. The quantitative outcomes enhance understanding of proinflammatory and antiinflammatory metabolism in RAW 264.7 macrophages.

Quantitative understanding of cellular processes, such as cell cycle and differentiation, is impeded by various forms of complexity ranging from myriad molecular players and their multilevel regulatory interactions, cellular evolution with multiple intermediate stages, lack of elucidation of cause-effect relationships among the many system players, and the computational complexity associated with the profusion of variables and parameters. In this paper, we present a modeling framework based on the cybernetic concept that biological regulation is inspired by objectives embedding rational strategies for dimension reduction, process stage specification through the system dynamics, and innovative causal association of regulatory events with the ability to predict the evolution of the dynamical system. The elementary step of the modeling strategy involves stage-specific objective functions that are computationally determined from experiments, augmented with dynamical network computations involving endpoint objective functions, mutual information, change-point detection, and maximal clique centrality. We demonstrate the power of the method through application to the mammalian cell cycle, which involves thousands of biomolecules engaged in signaling, transcription, and regulation. Starting with a fine-grained transcriptional description obtained from RNA sequencing measurements, we develop an initial model, which is then dynamically modeled using the cybernetic-inspired method, based on the strategies described above. The cybernetic-inspired method is able to distill the most significant interactions from a multitude of possibilities. In addition to capturing the complexity of regulatory processes in a mechanistically causal and stage-specific manner, we identify the functional network modules, including novel cell cycle stages. Our model is able to predict future cell cycles consistent with experimental measurements. We posit that this innovative framework has the promise to extend to the dynamics of other biological processes, with a potential to provide novel mechanistic insights.

Cellular response to inflammatory stimuli leads to the production of eicosanoids—prostanoids (PRs) and leukotrienes (LTs)—and signaling molecules—cytokines and chemokines—by macrophages. Quantitative modeling of the inflammatory response is challenging owing to a lack of knowledge of the complex regulatory processes involved. Cybernetic models address these challenges by utilizing a well-defined cybernetic goal and optimizing a coarse-grained model toward this goal. We developed a cybernetic model to study arachidonic acid (AA) metabolism, which included two branches, PRs and LTs. We utilized a priori biological knowledge to define the branch-specific cybernetic goals for PR and LT branches as the maximization of TNFα and CCL2, respectively. We estimated the model parameters by fitting data from three experimental conditions. With these parameters, we were able to capture a novel fourth independent experimental condition as part of the model validation. The cybernetic model enhanced our understanding of enzyme dynamics by predicting their profiles. The success of the model implies that the cell regulates the synthesis and activity of the associated enzymes, through cybernetic control variables, to accomplish the chosen biological goal. The results indicated that the dominant metabolites are PGD2 (a PR) and LTB4 (an LT), aligning with their corresponding known prominent biological roles during inflammation. Using heuristic arguments, we also infer that eicosanoid overproduction can lead to increased secretion of cytokines/chemokines. This novel model integrates mechanistic knowledge, known biological understanding of signaling pathways, and data-driven methods to study the dynamics of eicosanoid metabolism.

Under normal homeostatic conditions, self-double-stranded RNA (self-dsRNA) is modified by adenosine deaminase acting on RNA 1 (ADAR1) to prevent the induction of a type I interferon-mediated inflammatory cascade. Antigen-presenting cells (APCs) sense pathogen-associated molecular patterns, such as dsRNA, to activate the immune response. The impact of ADAR1 on the function of APCs and the consequences to immunity are poorly understood. Here, we show that ADAR1 deletion in CD11c+ APCs leads to (1) a skewed myeloid cell compartment enriched in inflammatory cDC2-like cells, (2) enhanced numbers of activated tissue resident memory T cells in the lung, and (3) the imprinting of a broad antiviral transcriptional signature across both immune and non-immune cells. The resulting changes can be partially reversed by blocking IFNAR1 signaling and promote early resistance against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Our study provides insight into the consequences of self-dsRNA sensing in APCs on the immune system.

IntroductionNeural induction of human induced pluripotent stem cells represents a critical switch in cell state during which pluripotency is lost and commitment to a neural lineage is initiated. Although many of the key transcription factors involved in neural induction are known, we know little of the temporal and causal relationships that are required for this state transition. MethodsHere, we have carried out a longitudinal analysis of the transcriptome of human iPSCs undergoing neural induction. Using the temporal relationships between the changing profile of key transcription factors and subsequent changes in their target gene expression profiles, we have identified distinct functional modules operative throughout neural induction. ResultsIn addition to modules that govern loss of pluripotency and gain of neural ectoderm identity, we discover other modules governing cell cycle and metabolism. Strikingly, some of these functional modules are retained throughout neural induction, even though the gene membership of the module changes. Systems analysis identifies other modules associated with cell fate commitment, genome integrity, stress response and lineage specification. We then focussed on OTX2, one of the most precociously activated transcription factors during neural induction. Our temporal analysis of OTX2 target gene expression identified several OTX2 regulated gene modules representing protein remodelling, RNA splicing and RNA processing. Further CRISPRi inhibition of OTX2 prior to neural induction promotes an accelerated loss of pluripotency and a precocious and aberrant neural induction disrupting some of the previously identified modules. DiscussionWe infer that OTX2 has a diverse role during neural induction and regulates many of the biological processes that are required for loss of pluripotency and gain of neural identity. This dynamical analysis of transcriptional changes provides a unique perspective of the widespread remodelling of the cell machinery that occurs during neural induction of human iPSCs.

Our previous study using systems vaccinology identified an association between the sterol regulatory binding protein (SREBP) pathway and humoral immune response to vaccination in humans. To investigate the role of SREBP signaling in modulating immune responses, we generated mice with B cell- or CD11c+ antigen-presenting cell (APC)-specific deletion of SCAP, an essential regulator of SREBP signaling. Ablation of SCAP in CD11c+ APCs had no effect on immune responses. In contrast, SREBP signaling in B cells was critical for antibody responses, as well as the generation of germinal centers,memory B cells and bone marrow plasma cells. SREBP signaling was required for metabolic reprogramming in activated B cells. Upon mitogen stimulation, SCAP-deficient B cells could not proliferate and had decreased lipid rafts. Deletion of SCAP in germinal center B cells using AID-Cre decreased lipid raft content and cell cycle progression. These studies provide mechanistic insights coupling sterol metabolism with the quality and longevity of humoral immunity.

The development of a portfolio of SARS-CoV-2 vaccines to vaccinate the global population remains an urgent public health imperative. Here, we demonstrate the capacity of a subunit vaccine under clinical development, comprising the SARS-CoV-2 Spike protein receptor-binding domain displayed on a two-component protein nanoparticle (RBD-NP), to stimulate robust and durable neutralizing antibody (nAb) responses and protection against SARS-CoV-2 in non-human primates. We evaluated five different adjuvants combined with RBD-NP including Essai O/W 1849101, a squalene-in-water emulsion; AS03, an alpha-tocopherol-containing squalene-based oil-in-water emulsion used in pandemic influenza vaccines; AS37, a TLR-7 agonist adsorbed to Alum; CpG 1018-Alum (CpG-Alum), a TLR-9 agonist formulated in Alum; or Alum, the most widely used adjuvant. All five adjuvants induced substantial nAb and CD4 T cell responses after two consecutive immunizations. Durable nAb responses were evaluated for RBD-NP/AS03 immunization and the live-virus nAb response was durably maintained up to 154 days post-vaccination. AS03, CpG-Alum, AS37 and Alum groups conferred significant protection against SARS-CoV-2 infection in the pharynges, nares and in the bronchoalveolar lavage. The nAb titers were highly correlated with protection against infection. Furthermore, RBD-NP when used in conjunction with AS03 was as potent as the prefusion stabilized Spike immunogen, HexaPro. Taken together, these data highlight the efficacy of the RBD-NP formulated with clinically relevant adjuvants in promoting robust immunity against SARS-CoV-2 in non-human primates.

Regulation of metabolism in mammalian cells is achieved through a complex interplay between cellular signaling, metabolic reactions, and transcriptional changes. The modeling of metabolic fluxes in a cell requires the knowledge of all these mechanisms, some of which may be unknown. A cybernetic approach provides a framework to model these complex interactions through implicit accounting of such regulatory mechanisms, assuming a biological 'goal'. The premise underlying the cybernetic framework is that the regulatory processes affecting metabolism can be mathematically formulated as a cybernetic objective through variables that constrain the metabolic reaction network to achieve a specified biological 'goal'. Here, we highlight the utility of the cybernetic framework in modeling of prostaglandin metabolism in murine macrophage cells during inflammation. We present a perspective for future use of the cybernetic framework for modeling complex cellular processes using multiple objectives, which can represent distinct subprocesses within the metabolic reaction network.

The two main blood flow patterns, namely, pulsatile shear (PS) prevalent in straight segments of arteries and oscillatory shear (OS) observed at branch points, are associated with atheroprotective (healthy) and atheroprone (unhealthy) vascular phenotypes, respectively. The effects of blood flow-induced shear stress on endothelial cells (ECs) and vascular health have generally been studied using human umbilical vein endothelial cells (HUVECs). While there are a few studies comparing the differential roles of PS and OS across different types of ECs at a single time point, there is a paucity of studies comparing the temporal responses between different EC types. In the current study, we measured OS and PS transcriptomic responses in human aortic endothelial cells (HAECs) over 24 h and compared these temporal responses of HAECs with our previous findings on HUVECs. The measurements were made at 1, 4, and 24 h in order to capture the responses at early, mid, and late time points after shearing. The results indicate that the responses of HAECs and HUVECs are qualitatively similar for endothelial function-relevant genes and several important pathways with a few exceptions, thus demonstrating that HUVECs can be used as a model to investigate the effects of shear on arterial ECs, with consideration of the differences. Our findings show that HAECs exhibit an earlier response or faster kinetics as compared to HUVECs. The comparative analysis of HAECs and HUVECs presented here offers insights into the mechanisms of common and disparate shear stress responses across these two major endothelial cell types.

Emerging evidence indicates a fundamental role for the epigenome in immunity. Here, we mapped the epigenomic and transcriptional landscape of immunity to influenza vaccination in humans at the single-cell level. Vaccination against seasonal influenza induced persistently diminished H3K27ac in monocytes and myeloid dendritic cells (mDCs), which was associated with impaired cytokine responses to Toll-like receptor stimulation. Single-cell ATAC-seq analysis revealed an epigenomically distinct subcluster of monocytes with reduced chromatin accessibility at AP-1-targeted loci after vaccination. Similar effects were observed in response to vaccination with the AS03-adjuvanted H5N1 pandemic influenza vaccine. However, this vaccine also stimulated persistently increased chromatin accessibility at interferon response factor (IRF) loci in monocytes and mDCs. This was associated with elevated expression of antiviral genes and heightened resistance to the unrelated Zika and Dengue viruses. These results demonstrate that vaccination stimulates persistent epigenomic remodeling of the innate immune system and reveal AS03's potential as an epigenetic adjuvant.

The development of a portfolio of COVID-19 vaccines to vaccinate the global population remains an urgent public health imperative1. Here we demonstrate the capacity of a subunit vaccine, comprising the SARS-CoV-2 spike protein receptor-binding domain displayed on an I53-50 protein nanoparticle scaffold (hereafter designated RBD-NP), to stimulate robust and durable neutralizing-antibody responses and protection against SARS-CoV-2 in rhesus macaques. We evaluated five adjuvants including Essai O/W 1849101, a squalene-in-water emulsion; AS03, an α-tocopherol-containing oil-in-water emulsion; AS37, a Toll-like receptor 7 (TLR7) agonist adsorbed to alum; CpG1018-alum, a TLR9 agonist formulated in alum; and alum. RBD-NP immunization with AS03, CpG1018-alum, AS37 or alum induced substantial neutralizing-antibody and CD4 T cell responses, and conferred protection against SARS-CoV-2 infection in the pharynges, nares and bronchoalveolar lavage. The neutralizing-antibody response to live virus was maintained up to 180 days after vaccination with RBD-NP in AS03 (RBD-NP-AS03), and correlated with protection from infection. RBD-NP immunization cross-neutralized the B.1.1.7 SARS-CoV-2 variant efficiently but showed a reduced response against the B.1.351 variant. RBD-NP-AS03 produced a 4.5-fold reduction in neutralization of B.1.351 whereas the group immunized with RBD-NP-AS37 produced a 16-fold reduction in neutralization of B.1.351, suggesting differences in the breadth of the neutralizing-antibody response induced by these adjuvants. Furthermore, RBD-NP-AS03 was as immunogenic as a prefusion-stabilized spike immunogen (HexaPro) with AS03 adjuvant. These data highlight the efficacy of the adjuvanted RBD-NP vaccine in promoting protective immunity against SARS-CoV-2 and have led to phase I/II clinical trials of this vaccine (NCT04742738 and NCT04750343).

Abstract Introduction Lack of exposure to the field of Sleep Medicine at the medical student level hinders sleep training. Instead of the traditional didactic style, there is a need for innovative collaborative measures to spark interest in the younger generation of learners. The goal of this educational endeavor was to introduce medical students to the field of Sleep Medicine through the platform of Student Interest Group in Neurology (SIGN). Methods An interactive session was conducted for SIGN at the University of Minnesota. 24 second-year medical students were divided into 6 groups. The session consisted of introduction, videos of common sleep disorders and interactive briefing afterward. 5-point Likert scale pre and post-session surveys were administered to measure the level of knowledge regarding sleep, familiarity with diagnostic tools, available education, pathways to Sleep Medicine, learner’s interest and impact of the session. Wilcoxon matched-pairs signed-rank test was performed to compare pre- and post-surveys. Results There was a significant improvement in measures of students’ knowledge about sleep diagnostic modalities (p =7.8*10-5), education received (p= 3.2*10-5) and pathways to sleep medicine (p=4.1*10-5). Survey also showed improvement in students’ interest in pursuing a Sleep Medicine career (p=0.07). There was no difference in knowledge about the importance of sleep for health (p=0.69). All of the students found the session to be informative. Conclusion Early exposure to sleep disorders in interactive format was well received by the medical students with significant improvement in scores regarding sleep education, awareness of diagnostic modalities, career pathway and interest in sleep medicine (p=0.07). Integration of exposure to Sleep Medicine within the medical curriculum in an innovative format should be done to instigate interest in this field. Further larger studies are warranted to evaluate the changes in the students’ interest in the subspecialty with an introduction in the early stages of their career. Support

Recent efforts toward an HIV vaccine focus on inducing broadly neutralizing antibodies, but eliciting both neutralizing antibodies (nAbs) and cellular responses may be superior. Here, we immunized macaques with an HIV envelope trimer, either alone to induce nAbs, or together with a heterologous viral vector regimen to elicit nAbs and cellular immunity, including CD8+ tissue-resident memory T cells. After ten vaginal challenges with autologous virus, protection was observed in both vaccine groups at 53.3% and 66.7%, respectively. A nAb titer >300 was generally associated with protection but in the heterologous viral vector + nAb group, titers <300 were sufficient. In this group, protection was durable as the animals resisted six more challenges 5 months later. Antigen stimulation of T cells in ex vivo vaginal tissue cultures triggered antiviral responses in myeloid and CD4+ T cells. We propose that cellular immune responses reduce the threshold of nAbs required to confer superior and durable protection. An HIV vaccine that elicits both antibodies and cellular immune responses confers long-lasting protection against viral challenge in nonhuman primates.

Massive rectal bleeding is an uncommon presentation of ileal tuberculosis (TB). We report an uncommon cause of anemia in a post-renal transplant patient due to massive lower gastrointestinal (LGI) bleed. The index case had a normal upper and LGI endoscopy, but the (99)technetium labeled red blood cell scan showed active bleeding from terminal ileum and caecum. Microscopic examination of the resected specimen revealed tubercular granuloma with acid-fast bacilli. Intestinal TB should be a differential diagnosis for massive LGI bleed in immunosuppressed patients in developing country.

The optimal expression of endothelial nitric oxide synthase (eNOS), the hallmark of endothelial homeostasis, is vital to vascular function. Dynamically regulated by various stimuli, eNOS expression is modulated at transcriptional, post-transcriptional, and post-translational levels. However, epigenetic modulations of eNOS, particularly through long non-coding RNAs (lncRNAs) and chromatin remodeling, remain to be explored. Here we identify an enhancer-associated lncRNA that enhances eNOS expression (LEENE). Combining RNA-sequencing and chromatin conformation capture methods, we demonstrate that LEENE is co-regulated with eNOS and that its enhancer resides in proximity to eNOS promoter in endothelial cells (ECs). Gain- and Loss-of-function of LEENE differentially regulate eNOS expression and EC function. Mechanistically, LEENE facilitates the recruitment of RNA Pol II to the eNOS promoter to enhance eNOS nascent RNA transcription. Our findings unravel a new layer in eNOS regulation and provide novel insights into cardiovascular regulation involving endothelial function.