Aging accelerates central nervous system remyelination failure and neurodegeneration. Microglia promote remyelination by phagocytosing myelin debris, but this function is impaired by aging-related CD22 upregulation. However, the molecular mechanisms counteracting premature aging-related microglial dysfunction and remyelination impairment remain unclear. Here, we report that Aurka-Bhlhe41 axis prevents premature aging-like microglial dysfunction and promotes remyelination by restraining progressive CD22 upregulation. We identified that microglia-enriched Bhlhe41 was negatively autoregulated and inhibited by Aurka loss. Bhlhe41- or Aurka-deficient young mice exhibited aging-like microglial morphology, phagocytic deficits, progressive CD22 upregulation, and remyelination impairment in cuprizone-induced demyelination model. Conversely, ectopic Bhlhe41 expression induced hypertrophic microglia, and counteracted phagocytic deficits and CD22 upregulation in Aurka-deficient microglia. CD22 blockade restored phagocytic function and remyelination in Bhlhe41-deficient mice. Notably, a conserved pattern of CD22 upregulation was observed in human PCDH9high microglia subsets with BHLHE41 downregulation. These findings offer insights into potential therapeutic strategies to combat aging-related neurodegeneration and central nervous system functional decline.

Objective To investigate whether bone marrow mesenchymal stem cell（BMSC）-derived exosomes（Exo）can inhibit pulmonary fibrosis by regulating epithelial-mesenchymal transition（EMT）via the transglutaminase（TG）2/nuclear factor κB（NF-κB）pathway. Methods SPF-grade male SD rats were selected, and BMSCs and their derived Exo were isolated, cultured and identified；human alveolar epithelial A549 cells were stimulated with transforming growth factor（TGF）-β1 to establish a pulmonary fibrosis（PF）model. A549 cells with TGM2 knockdown（TG2-）, TGM2 overexpression（TG2+）and empty vector（TG2--con or TG2+-con）were constructed, and were subjected to no treatment（NC group）, TGF-β1 treatment（PF group）, and Exo treatment（Exo group）, respectively. Western blot was used to detect the protein expression of E-cadherin, Vimentin, TG2 and NF-κB. Results Compared with the NC group, the PF group showed significantly decreased E-cadherin expression, while the expression levels of Vimentin and TG2 protein were significantly increased（P＜0.05）. Compared with the PF group, the Exo group showed increased E-cadherin expression and decreased expression levels of Vimentin and TG2 protein（P＜0.05）. TGM2 over expression upregulated NF-κB, and TGM2 knockdown downregulated NF-κB（P＜0.05）.After Exo intervention, E-cadherin increased in the TG2- group, TG2+ group, TG2--con group and TG2+-con group, while Vimentin, TG2 and NF-κB were all significantly decreased（P＜0.05）.Conclusion TGM2 is a key target of BMSC-Exo in regulating EMT. BMSC-Exo can regulate the EMT process by inhibiting the TG2/NF-κB pathway, thereby exerting an inhibitory effect on pulmonary fibrosis.

Microglia are crucial for phagocytic clearance of myelin debris, which hinders remyelination and leads to neurological decline during aging and in multiple sclerosis (MS). However, the molecular mechanism enabling microglia to expand and function effectively in remyelination remains elusive. Here, we identified that mitotic kinase Aurkb was upregulated in microglia during early development and in MS. Neonatal deletion of Aurkb disrupted cell density, morphology, and proliferation, which is attributed to stalled mitosis. Inducible Aurkb ablation in adulthood led to microglial dystrophy and disrupted homeostasis. Aurkb deficiency compromised microglial activation in response to LPS-induced inflammation. Critically, Aurkb-deficient mice exhibited accumulated myelin debris and impaired oligodendrocyte regeneration and remyelination in the CPZ-induced demyelination model. Additionally, Aurkb deletion inhibited microglial clearance of myelin debris, independent of reduced microglia numbers. This defect was associated with diminished autophagy. Together, these findings establish Aurkb as a key regulator of microglial development, homeostasis, and responses to remyelination.

Pancreatic cysts, particularly intraductal papillary mucinous neoplasms (IPMNs), pose a potential risk for progressing to pancreatic cancer (PC). This study investigates the genetic architecture of benign pancreatic cysts and its potential connection to PC using genome-wide association studies (GWAS). The discovery GWAS identified significant genetic variants associated with benign cysts, specifically the rs142409042 variant near the OPCML gene. A pairwise GWAS comparing PC to benign cysts revealed the rs7190458 variant near the BCAR1 and CTRB1 genes. Further analysis with identified GWAS genes highlighted the Actin Related Protein (Arp) 2/3 complex as a potentially important molecular mechanism connecting benign cysts and PC. The Arp2/3 complex-associated genes were significantly upregulated in PC, suggesting their role in the malignant transformation of pancreatic cysts. Differential expression of these genes was observed across various cell types in PC, indicating their involvement in the tumor microenvironment. These findings suggest that the Arp2/3 complex-associated genes can serve as potential biomarkers for predicting the malignant transformation of pancreatic cysts, opening new avenues for targeted therapies and early detection strategies.

Early cancer diagnosis is crucial but challenging owing to the lack of reliable biomarkers that can be measured using routine clinical methods. The identification of biomarkers for early detection is complicated by each tumor involving changes in the interactions between thousands of genes. In addition to this staggering complexity, these interactions can vary among patients with the same diagnosis as well as within the same tumor. We hypothesized that reliable biomarkers that can be measured with routine methods could be identified by exploiting three facts: (i) the same tumor can have multiple grades of malignant transformation; (ii) these grades and their molecular changes can be characterized using spatial transcriptomics; and (iii) these changes can be integrated into models of malignant transformation using pseudotime. Pseudotime models were constructed based on spatial transcriptomic data from three independent prostate cancer studies to prioritize the genes that were most correlated with malignant transformation. The identified genes were associated with cancer grade, copy-number aberrations, hallmark pathways, and drug targets, and they encoded candidate biomarkers for prostate cancer in mRNA, IHC, and proteomics data from the sera, prostate tissue, and urine of more than 2,000 patients with prostate cancer and controls. Machine learning-based prediction models revealed that the biomarkers in urine had an AUC of 0.92 for prostate cancer and were associated with cancer grade. Overall, this study demonstrates the diagnostic potential of combining spatial transcriptomics, pseudotime, and machine learning for prostate cancer, which should be further tested in prospective studies. SIGNIFICANCE:Integrating spatial transcriptomics, pseudotime, and machine learning analyses is effective for identifying prostate cancer biomarkers that are reliable in different settings and measurable with routine methods, providing potential early diagnosis strategies. This article is part of a special series: Driving Cancer Discoveries with Computational Research, Data Science, and Machine Learning/AI.

Forkhead box O transcriptional factors, especially FoxO1 and FoxO3a, play critical roles in physiologic and pathologic immune responses. However, the function of FoxO4, another main member of the FoxO family, in lymphoid cells is still poorly understood. Here, we showed that loss of FoxO4 in T cells augmented IFN-γ production of Th1 cells in vitro. Correspondingly, conditional deletion of FoxO4 in CD4+ T cells enhanced T cell–specific responses to Listeria monocytogenes infection in vivo. Genome-wide occupancy and transcriptomic analyses identified Dkk3 (encoding the Dickkopf-3 protein) as a direct transcriptional target of FoxO4. Consistent with the FoxO4-DKK3 relationship, recombinant DKK3 protein restored normal levels of IFN-γ production in FoxO4-deficient Th1 cells through the downregulation of lymphoid enhancer–binding factor 1 (Lef1) expression. Together, our data suggest a potential FoxO4/DKK3 axis in Th1 cell differentiation, providing what we believe to be an important insight and supplement for FoxO family proteins in T lymphocyte biology and revealing a promising target for the treatment of immune-related diseases.

Background Ineffective drug treatment is a major problem for many patients with immune-mediated inflammatory diseases (IMIDs). Important reasons are the lack of systematic solutions for drug prioritisation and repurposing based on characterisation of the complex and heterogeneous cellular and molecular changes in IMIDs. Methods Here, we propose a computational framework, scDrugPrio, which constructs network models of inflammatory disease based on single-cell RNA sequencing (scRNA-seq) data. scDrugPrio constructs detailed network models of inflammatory diseases that integrate information on cell type-specific expression changes, altered cellular crosstalk and pharmacological properties for the selection and ranking of thousands of drugs. Results scDrugPrio was developed using a mouse model of antigen-induced arthritis and validated by improved precision/recall for approved drugs, as well as extensive in vitro, in vivo, and in silico studies of drugs that were predicted, but not approved, for the studied diseases. Next, scDrugPrio was applied to multiple sclerosis, Crohn’s disease, and psoriatic arthritis, further supporting scDrugPrio through prioritisation of relevant and approved drugs. However, in contrast to the mouse model of arthritis, great interindividual cellular and gene expression differences were found in patients with the same diagnosis. Such differences could explain why some patients did or did not respond to treatment. This explanation was supported by the application of scDrugPrio to scRNA-seq data from eleven individual Crohn’s disease patients. The analysis showed great variations in drug predictions between patients, for example, assigning a high rank to anti-TNF treatment in a responder and a low rank in a nonresponder to that treatment. Conclusions We propose a computational framework, scDrugPrio, for drug prioritisation based on scRNA-seq of IMID disease. Application to individual patients indicates scDrugPrio’s potential for personalised network-based drug screening on cellulome-, genome-, and drugome-wide scales. For this purpose, we made scDrugPrio into an easy-to-use R package ( https://github.com/SDTC-CPMed/scDrugPrio ).

The huge amount and diversity of data generated by Internet of Things (IoT) devices and the need to store and process this data led to the development of fog computing alongside cloud computing. Fog computing is a new paradigm for providing service at the edge of the network and close to end users, so that it can support real-time IoT applications. Because fog involves heterogeneous and distributed infrastructure with limited resources, so efficient resource allocation to satisfy Quality of Service (QoS) is challenging. IoT application placement mechanisms have been developed to address these issues, in which the subordinate services of these applications are mapped to fog nodes. Despite extensive research to solve the Service Placement Problem (SPP) in fog computing, efforts are still ongoing due to the importance of the issue. Hence, this paper proposes an efficient and autonomous mechanism for solving SPP using Teaching Learning-Based Optimization (TLBO) called SPP-TLBO. SPP-TLBO is a multi-objective QoS-aware algorithm that manages resources on distributed and localized fog domains. In addition to the above, we improve the performance of TLBO by configuring the evolution process with a shared parallel architecture. Besides, SPP-TLBO can save more resources to handle future requests by considering application deadlines and extracting the dynamic distribution of resources required over time. The proposed algorithm is evaluated by simulation on a synthetic fog environment. The simulation results show that SPP-TLBO improves system performance and is between 8 and 19% better efficiency compared to some advanced methods such as CSA-FSPP, FSP-ODMA and, WOA-FSP.

Precise quantification of human cells in preclinical animal models by a sensitive and specific approach is warranted. The probe-based quantitative PCR (qPCR) assay as a sensitive and swift approach is suitable for the quantification of human cells by targeting human-specific DNA sequences. In this study, we developed an efficient qPCR assay targeting human-specific DNA in ST6GALNAC3 (termed ST6GAL-qPCR) for the quantification of human cells in preclinical animal models. ST6GAL-qPCR probe was synthesized with FAM and non-fluorescent quencher-minor groove binder conjugated to the 5′ and 3′ end of the probe, respectively. Genomic DNA from human, rhesus monkeys, cynomolgus monkeys, New Zealand White rabbits, SD rats, C57BL/6, and BALB/c mice were utilized for analyzing the specificity and sensitivity of the ST6GAL-qPCR assay. The ST6GAL-qPCR assay targeted human-specific DNA was cloned to pUCM-T vector and released by EcoR I/Hind III digestion for generating a calibration curve. Cell mixing experiment was performed to validate the ST6GAL-qPCR assay by analysis of 0.1

T and B lymphocytes are crucial players in cellular and humoral immune responses. The development, activation and differentiation of T and B lymphocytes are regulated by the best characterized PI3K‐PI (3,4,5) P3‐AKT phosphoinositide signalling pathway. As a branch of the phosphoinositide signalling pathway, the lipid phosphatase INPP4B inhibits AKT activation through degrading the phosphoinositide signalling messenger PI (3,4) P2. However, the role of Inpp4b in T and B lymphocytes remains elusive. Here, we reported that Inpp4b was highly expressed in human and murine T‐ and B‐1 lymphocytes. Despite its higher expression in T lymphocytes, neither T cell development and homeostasis nor in vitro T cell activation and CD4+ T cell differentiation were altered upon loss of Inpp4b. Interestingly, combined direct phenotype analysis of Inpp4b conventional knockout mice and adoptive transfer studies revealed that ablation of Inpp4b intrinsically reduced peritoneal B‐1 cells rather B‐2 cells. Moreover, Inpp4b deficiency led to impaired thymus independent (TI) and thymus dependent (TD) antigens‐induced antibody production. Further in vitro analysis revealed that CD40‐mediated B cell proliferation was impaired upon ablation of Inpp4b. Our findings reveal that Inpp4b is required in regulating B‐1 cell numbers and B cell‐mediated antibody production.

Precise quantification of grafted human cells in preclinical animal models such as non-human primates, rodents and rabbits is needed for the evaluations of the safety and efficacy of cell therapy. Quantitative PCR (qPCR) as a swift, sensitive and powerful assay is suitable for human cell quantification. However, it is a formidable challenge due to that the genome of non-human primates share more than 95

Basophils are crucial in regulating allergic reactions via immediate secretion of multiple mediators upon IgE‐induced degranulation. IL‐3 regulates the development and activation of human basophils while epithelial cytokine thymic stromal lymphopoietin (TSLP) is another key regulator for murine basophils. Despite association of increased TSLP with exaggerated basophil responses in oesophageal biopsies, the effects of TSLP in regulating human basophil degranulation and activation are under debate. In this study, we aimed to examine whether human basophils responded to TSLP by co‐expression of TSLP receptors, TSLPR and IL‐7Rα (CD127), upon in vitro activation and in sputum of allergic asthmatic patients. Flow cytometric analysis of fresh basophils from healthy controls revealed no detectable TSLPR and CD127. Further flow cytometric analysis of basophils from healthy controls in vitro stimulated by multiple established basophil modulators for 24 hours showed induction of TSLPR but not CD127 by IL‐3 (10 ng/ml), anti‐IgE (10 μg/ml) and C5a (50 ng/ml). One‐hour stimulation of basophils from allergic asthmatic patients and healthy controls by TSLP (50 ng/ml) with or without IL‐3 (10 ng/ml) and anti‐IgE (10 μg/ml) had no effect on induction of CD63+ degranulated basophils. Similarly, TSLP (50 ng/ml) with or without IL‐3 (10 ng/ml) and anti‐IgE (10 μg/ml) did not induce IL‐4 and IL‐13 production by basophils from healthy controls. Further ex vivo analysis revealed that sputum basophils from allergic asthmatic patients did not express CD127. We conclude that human basophils from healthy controls and allergic asthmatic patients do not respond to TSLP as lacking CD127.

Therapeutic protocols of tumor models and all other methods were described in Supplementary materials and methodsã€,

Supplementary Fig. 1. The expression of TLR3 in OSCC patients; Supplementary Fig. 2. The impacts of poly (I:C) on the vitality of OSCC cells; Supplementary Fig. 3. Poly (I:C) could inhibit the expression of drug transporters; Supplementary Fig. 4. The characteristics of combined chemotherapy in vitro; Supplementary Fig. 5. lnc-IL7R is up-regulated by the combined chemotherapy; Supplementary Fig. 6. Lnc-IL7R knockdown shows weak effects on cell apoptosis and cell cycle; Supplementary Fig. 7. Lnc-IL7R knockdown improves the efficiency of combined chemotherapy; Table 1. information of antibodies and reagents; Table 2. Relationships between TLR3 expression on different cell type and clinicalpathologic Characteristics in OSCC patients.

B-1 lymphocytes exhibit specialized roles in host defense against multiple pathogens. Despite the fact that CD19 + CD93 + B220 lo/- B cells have been identified as B-1 progenitors, the definition for B-1 progenitors remains to be elucidated as CD19 + CD93 + B220 + B cells are capable to give rise to B-1 cells. Given that transcription factor Bhlhe41 is highly and preferentially expressed in B-1 cells and regulates B-1a cell development, we generated a transgenic mouse model, Bhlhe41 dTomato-Cre , for fate mapping and functional analysis of B-1 cells. Bhlhe41 dTomato-Cre mice efficiently traced Bhlhe41 expression, which was mainly restricted to B-1 cells in B-cell lineage. We showed an efficient and specific Cre-mediated DNA recombination in adult B-1 cells and neonatal B-1 progenitors rather than B-2 cells by flow cytometric analysis of Bhlhe41 dTomato-Cre/+ Rosa26 EYFP mice. Treatment of Bhlhe41 dTomato-Cre/+ Rosa26 iDTR mice with diphtheria toxin revealed a robust efficacy of B-1 cell depletion. Interestingly, using Bhlhe41 dTomato-Cre mice, we demonstrated that neonatal B-1 progenitors (CD19 + CD93 + B220 lo/- ) expressed Bhlhe41 and were identical to well-defined transitional B-1a progenitors (CD19 + CD93 + B220 lo/- CD5 + ), which only gave rise to peritoneal B-1a cells. Moreover, we identified a novel population of neonatal splenic CD19 hi dTomato + B220 hi CD43 lo CD5 lo B cells, which differentiated to peritoneal B-1a and B-1b cells. Bhlhe41 deficiency impaired the balance between CD19 hi dTomato + B220 lo/- CD5 hi and CD19 hi dTomato + B220 hi CD5 lo cells. Hence, we identified neonatal CD19 hi dTomato + B220 hi CD43 lo CD5 lo B cells as novel transitional B-1 progenitors. Bhlhe41 dTomato-Cre/+ mouse can be used for fate mapping and functional studies of B-1 cells in host-immune responses.

Long non-coding (lnc)RNAs have been recognized as important regulators in gastric cancer. lncRNA GAS8-AS1 is considered a tumor suppressor in multiple types of cancer, such as papillary thyroid carcinoma, ovarian cancer and colorectal cancer. However, the specific role of GAS8-AS1 in gastric cancer remains to be fully elucidated. The aim of the present study was to investigate the role of GAS8-AS1 in gastric cancer and its potential underlying mechanisms of action. The expression levels of GAS8-AS1, microRNA (miR)-21-3p, PTEN and pyruvate dehydrogenase (E1) alpha subunit gene (PDHA1) in gastric cancer and non-cancerous tissues, as well as in gastric cancer cell lines, were detected using reverse transcription-quantitative PCR. Cell proliferation was detected by using a Cell Counting Kit-8 assay. Cell migration and invasion were detected using a Transwell assay. Results of the present study demonstrated that the expression levels of GAS8-AS1 in gastric cancer tissues were significantly decreased, whereas its expression did not differ among cancer tissues at different clinical stages. Low expression levels of GAS8-AS1 predicted poor 5-year survival rates for 70 patients with gastric adenocarcinoma from the Affiliated Hospital of Xuzhou Medical University (Xuzhou, China) during patient follow-up. In addition, the expression levels of miR-21-3p were markedly increased in cancer tissues, and miR-21-3p expression was negatively associated with the expression of GAS8-AS1. The direct interaction between GAS8-AS1 and miR-21-3p was predicted using the starBase database and was confirmed by using an RNA pull-down assay. In gastric cell lines, the overexpression of GAS8-AS1 reduced the expression levels of mature miR-21-3p but did not affect the expression of miR-21-3p precursor, while the overexpression of miR-21-3p did not, in turn, affect the expression of GAS8-AS1. In addition, the overexpression of GAS8-AS1 inhibited cancer cell proliferation, while the overexpression of miR-21-3p promoted cancer cell proliferation and attenuated the effects of GAS8-AS1. Overexpression of miR-21-3p promoted cancer cell migration and invasion, whereas overexpression of GAS8-AS1 did not affect cell migration or invasion. In summary, results of the present study have demonstrated that GAS8-AS1 acts as a tumor suppressor in gastric cancer, and it may inhibit cancer cell proliferation by downregulating miR-21-3p.

Rationale: We found that a subset of signal transducer and activator of transcription 3 (STAT3) translocated into mitochondria in phagocytes, including macrophages isolated from individuals with sepsis. However, the role of mitochondrial STAT3 in macrophages remains unclear. Method: To investigate the function of mitochondrial STAT3 in vivo, we generated inducible mitochondrial STAT3 knock-in mice. A cytokine array analysis, a CBA analysis, flow cytometry, immunofluorescence staining and quantification and metabolic analyses in vivo were subsequently performed in an LPS-induced sepsis model. Single-cell RNA sequencing, a microarray analysis, metabolic assays, mass spectrometry and ChIP assays were utilized to gain insight into the mechanisms of mitochondrial STAT3 in metabolic reprogramming in LPS-induced sepsis. Results: We found that mitochondrial STAT3 induced NF-κB nuclear localization and exacerbated LPS-induced sepsis in parallel with a metabolic switch from mainly using glucose to an increased reliance on fatty acid oxidation (FAO). Moreover, mitochondrial STAT3 abrogated carnitine palmitoyl transferase 1a (CPT1a) ubiquitination and degradation in LPS-treated macrophages. Meanwhile, an interaction between CPT1a and ubiquitin-specific peptidase 50 (USP50) was observed. In contrast, knocking down USP50 decreased CPT1a expression and FAO mediated by mitochondrial STAT3. The ChIP assays revealed that NF-κB bound the USP50 promoter. Curcumin alleviated LPS-mediated sepsis by suppressing the activities of mitochondrial STAT3 and NF-κB. Conclusion: Our findings reveal that mitochondrial STAT3 could trigger FAO by inducing CPT1a stabilization mediated by USP50 in macrophages, at least partially.

Gut microbiota-derived metabolites play vital roles in the regulation of host-gut microbiota mutualism, gut homeostasis and the pathogenesis of multiple human diseases. Fermentation of indigestible dietary fibers by gut microbiota produces a variety of short-chain fatty acids (SCFAs) consisting mainly of acetate, propionate and butyrate. Despite high concentrations of SCFAs in the gut, it has been reported in a large number of studies that SCFAs are involved in the onset and development of multiple diseases, including colitis, diabetes mellitus, hepatic steatosis, and obesity. Recent studies including our work found that SCFAs regulates allergic immune reactions and the pathogenesis of allergic diseases via their action on allergic effector immune cells, including T helper 2 (Th2) cells, type 2 innate lymphoid cells (ILC2), eosinophils, mast cells and basophils. Herein, we reviewed the association of SCFAs with human allergic diseases, their role in regulating the animal model of allergic diseases and the effects of different SCFAs in regulating the functions of allergic effectors cells and the underlying mechanisms, aiming to provide research clues for in-depth investigation in the role played by SCFAs in regulating various allergic diseases.

Abstract This study aims to explore the functional mechanism of LINC01638 in ovarian cancer (OC). The OC cell proliferation, viability and colony formation were respectively measured using CCK-8, MTT and colony formation assay. The cell cycle and apoptosis were both assessed using flow cytometry. Online bioinformatics tools were performed to predict the downstream gene of LINC01638. RNA pull down experiment and luciferase reporter assay were processed to verify the predictions. The expression of LINC01638, miR-128-3p and PDK1 in OC tissues and cells were detected using qRT-PCR and ISH analysis. The expressions of cisplatin-related proteins were determined by western blot. OC mice model was constructed to carry out in vivo experiment. LINC01638 was highly expressed in OC tissues and cells, and its high expression was related to poor OC prognosis. LINC01638 knockdown inhibited cell proliferation, colony formation and cisplatin resistance, promoted cell apoptosis and induced cell cycle arrest in OC cells. LINC01638 knockdown suppressed tumor growth, proliferation and cisplatin resistance and enhanced apoptosis in vivo. LINC01638 directly targeted miR-128-3p/PDK1 in OC cells. LINC01638 affected OC cell proliferation, survival and cisplatin resistance via combing miR-128-3p and promoting PDK1 expression.

Background Medical digital twins are computational disease models for drug discovery and treatment. Unresolved problems include how to organize and prioritize between disease-associated changes in digital twins, on cellulome- and genome-wide scales. We present a dynamic framework that can be used to model such changes and thereby prioritize upstream regulators (URs) for biomarker- and drug discovery. Methods We started with seasonal allergic rhinitis (SAR) as a disease model, by analyses of in vitro allergen-stimulated peripheral blood mononuclear cells (PBMC) from SAR patients. Time-series a single-cell RNA-sequencing (scRNA-seq) data of these cells were used to construct multicellular network models (MNMs) at each time point of molecular interactions between cell types. We hypothesized that predicted molecular interactions between cell types in the MNMs could be traced to find an UR gene, at an early time point. We performed bioinformatic and functional studies of the MNMs to develop a scalable framework to prioritize UR genes. This framework was tested on a single-cell and bulk-profiling data from SAR and other inflammatory diseases. Results Our scRNA-seq-based time-series MNMs of SAR showed thousands of differentially expressed genes (DEGs) across multiple cell types, which varied between time points. Instead of a single-UR gene in each MNM, we found multiple URs dispersed across the cell types. Thus, at each time point, the MNMs formed multi-directional networks. The absence of linear hierarchies and time-dependent variations in MNMs complicated the prioritization of URs. For example, the expression and functions of Th2 cytokines, which are approved drug targets in allergies, varied across cell types, and time points. Our analyses of bulk- and single-cell data from other inflammatory diseases also revealed multi-directional networks that showed stage-dependent variations. We therefore developed a quantitative approach to prioritize URs: we ranked the URs based on their predicted effects on downstream target cells. Experimental and bioinformatic analyses supported that this kind of ranking is a tractable approach for prioritizing URs. Conclusions We present a scalable framework for modeling dynamic changes in digital twins, on cellulome- and genome-wide scales, to prioritize UR genes for biomarker and drug discovery.