Fractional Tensor Recurrent Unit (fTRU): A Stable Forecasting Model With Long Memory.

The tensor recurrent model is a family of nonlinear dynamical systems, of which the recurrence relation consists of a p -fold (called degree- p ) tensor product. Despite such models frequently appearing in advanced recurrent neural networks (RNNs), to this date, there are limited studies on their long memory properties and stability in sequence tasks. In this article, we propose a fractional tensor recurrent model, where the tensor degree p is extended from the discrete domain to the continuous domain, so it is effectively learnable from various datasets. Theoretically, we prove that a large degree p is essential to achieve the long memory effect in a tensor recurrent model, yet it could lead to unstable dynamical behaviors. Hence, our new model, named fractional tensor recurrent unit (fTRU), is expected to seek the saddle point between long memory property and model stability during the training. We experimentally show that the proposed model achieves competitive performance with a long memory and stable manners in several forecasting tasks compared to various advanced RNNs.

A hub gene signature as a therapeutic target and biomarker for sepsis and geriatric sepsis-induced ARDS concomitant with COVID-19 infection.

Background: COVID-19 and sepsis represent formidable public health challenges, characterized by incompletely elucidated molecular mechanisms. Elucidating the interplay between COVID-19 and sepsis, particularly in geriatric patients suffering from sepsis-induced acute respiratory distress syndrome (ARDS), is of paramount importance for identifying potential therapeutic interventions to mitigate hospitalization and mortality risks. Methods: We employed bioinformatics and systems biology approaches to identify hub genes, shared pathways, molecular biomarkers, and candidate therapeutics for managing sepsis and sepsis-induced ARDS in the context of COVID-19 infection, as well as co-existing or sequentially occurring infections. We corroborated these hub genes utilizing murine sepsis-ARDS models and blood samples derived from geriatric patients afflicted by sepsis-induced ARDS. Results: Our investigation revealed 189 differentially expressed genes (DEGs) shared among COVID-19 and sepsis datasets. We constructed a protein-protein interaction network, unearthing pivotal hub genes and modules. Notably, nine hub genes displayed significant alterations and correlations with critical inflammatory mediators of pulmonary injury in murine septic lungs. Simultaneously, 12 displayed significant changes and correlations with a neutrophil-recruiting chemokine in geriatric patients with sepsis-induced ARDS. Of these, six hub genes (CD247, CD2, CD40LG, KLRB1, LCN2, RETN) showed significant alterations across COVID-19, sepsis, and geriatric sepsis-induced ARDS. Our single-cell RNA sequencing analysis of hub genes across diverse immune cell types furnished insights into disease pathogenesis. Functional analysis underscored the interconnection between sepsis/sepsis-ARDS and COVID-19, enabling us to pinpoint potential therapeutic targets, transcription factor-gene interactions, DEG-microRNA co-regulatory networks, and prospective drug and chemical compound interactions involving hub genes. Conclusion: Our investigation offers potential therapeutic targets/biomarkers, sheds light on the immune response in geriatric patients with sepsis-induced ARDS, emphasizes the association between sepsis/sepsis-ARDS and COVID-19, and proposes prospective alternative pathways for targeted therapeutic interventions.

B-cell-derived IL-10 promotes allergic sensitization in asthma regulated by Bcl-3.

Aeroallergen sensitization, mainly mediated by lung epithelium and dendritic cells (DCs), is integral to allergic asthma pathogenesis and progression. IL-10 has a dual role in immune responses, as it inhibits myeloid cell activation but promotes B-cell responses and epithelial cell proliferation. Here, we report a proinflammatory function of B-cell-derived IL-10 modulated by Bcl-3 in allergic asthma. Specifically, Bcl-3-/- mice showed elevated IL-10 levels and were found to be highly vulnerable to allergic asthma induced by house dust mites (HDMs). IL-10 had a positive correlation with the levels of the DC chemoattractant CCL-20 in HDM-sensitized mice and in patients with asthma and induced a selective increase in CCL-20 production by mouse lung epithelial cells. Blockade of IL-10 or IL-10 receptors during sensitization dampened both HDM-induced sensitization and asthma development. IL-10 levels peaked 4 h post sensitization with HDM and IL-10 was primarily produced by B cells under Bcl-3-Blimp-1-Bcl-6 regulation. Mice lacking B-cell-derived IL-10 displayed decreased lung epithelial CCL-20 production and diminished DC recruitment to the lungs upon HDM sensitization, thereby demonstrating resistance to HDM-induced asthma. Moreover, responses to HDM stimulation in Bcl-3-/- mice lacking B-cell-derived IL-10 were comparable to those in Bcl-3+/+ mice. The results revealed an unexpected role of B-cell-derived IL-10 in promoting allergic sensitization and demonstrated that Bcl-3 prevents HDM-induced asthma by inhibiting B-cell-derived IL-10 production. Thus, targeting the Bcl-3/IL-10 axis to inhibit allergic sensitization is a promising approach for treating allergic asthma. IL-10 is released rapidly from lung plasma cells under Bcl-3-Blimp-1-Bcl-6 regulation upon house dust mite exposure and amplifies lung epithelial cell (EC)-derived CCL-20 production and subsequent dendritic cell (DC) recruitment to promote allergic sensitization in asthma.

B cell-derived IL-10 promotes the resolution of lipopolysaccharide-induced acute lung injury.

Inflammation resolution is critical for acute lung injury (ALI) recovery. Interleukin (IL)-10 is a potent anti-inflammatory factor. However, its role in ALI resolution remains unclear. We investigated the effects of IL-10 during the ALI resolution process in a murine lipopolysaccharide (LPS)-induced ALI model. Blockade of IL-10 signaling aggravates LPS-induced lung injury, as manifested by elevated pro-inflammatory factors production and increased neutrophils recruitment to the lung. Thereafter, we used IL-10 GFP reporter mice to discern the source cell of IL-10 during ALI. We found that IL-10 is predominantly generated by B cells during the ALI recovery process. Furthermore, we used IL-10-specific loss in B-cell mice to elucidate the effect of B-cell-derived IL-10 on the ALI resolution process. IL-10-specific loss in B cells leads to increased pro-inflammatory cytokine expression, persistent leukocyte infiltration, and prolonged alveolar barrier damage. Mechanistically, B cell-derived IL-10 inhibits the activation and recruitment of macrophages and downregulates the production of chemokine KC that recruits neutrophils to the lung. Moreover, we found that IL-10 deletion in B cells leads to alterations in the cGMP-PKG signaling pathway. In addition, an exogenous supply of IL-10 promotes recovery from LPS-induced ALI, and IL-10-secreting B cells are present in sepsis-related ARDS. This study highlights that B cell-derived IL-10 is critical for the resolution of LPS-induced ALI and may serve as a potential therapeutic target.

Integrative bioinformatics and validation studies reveal KDM6B and its associated molecules as crucial modulators in Idiopathic Pulmonary Fibrosis.

Background: Idiopathic Pulmonary Fibrosis (IPF) can be described as a debilitating lung disease that is characterized by the complex interactions between various immune cell types and signaling pathways. Chromatin-modifying enzymes are significantly involved in regulating gene expression during immune cell development, yet their role in IPF is not well understood. Methods: In this study, differential gene expression analysis and chromatin-modifying enzyme-related gene data were conducted to identify hub genes, common pathways, immune cell infiltration, and potential drug targets for IPF. Additionally, a murine model was employed for investigating the expression levels of candidate hub genes and determining the infiltration of different immune cells in IPF. Results: We identified 33 differentially expressed genes associated with chromatin-modifying enzymes. Enrichment analyses of these genes demonstrated a strong association with histone lysine demethylation, Sin3-type complexes, and protein demethylase activity. Protein-protein interaction network analysis further highlighted six hub genes, specifically KDM6B, KDM5A, SETD7, SUZ12, HDAC2, and CHD4. Notably, KDM6B expression was significantly increased in the lungs of bleomycin-induced pulmonary fibrosis mice, showing a positive correlation with fibronectin and α-SMA, two essential indicators of pulmonary fibrosis. Moreover, we established a diagnostic model for IPF focusing on KDM6B and we also identified 10 potential therapeutic drugs targeting KDM6B for IPF treatment. Conclusion: Our findings suggest that molecules related to chromatin-modifying enzymes, primarily KDM6B, play a critical role in the pathogenesis and progression of IPF.

Nomograms predict survival benefits of radical prostatectomy and chemotherapy for prostate cancer with bone metastases: A SEER-based study.

Purpose: This study aimed to identify independent prognosis-associated factors of bone-metastatic prostate cancer. The nomograms were further developed to obtain indicators for the prognostic evaluation. Methods: A total of 7315 bone-metastatic prostate cancer (PCa) patients from 2010 to 2016 were retrospectively collected from the Surveillance, Epidemiology, and End Results (SEER) database. Patients were randomly divided into the training cohort (n=5,120) and test cohort (n=2,195) in a ratio of 7:3. Univariate and multivariate Cox regression models were applied to evaluate potential risk factors. A 1:1 propensity score matching (PSM) was further performed to decrease the confounding effect and re-evaluate the influence of radical prostatectomy and chemotherapy on prognosis. Combining these potential prognosis factors, the nomograms of cancer-specific survival (CSS) and overall survival (OS) at different times were established. C-indexes, calibration curves, and decision curves were developed to evaluate the discrimination, calibration, and clinical benefit of the nomograms. Results: Eleven independent prognosis factors for CSS and twelve for OS were utilized to conduct the nomograms respectively. The C-indexes of nomograms for CSS and OS were 0.712 and 0.702, respectively. A favorable consistency between the predicted and actual survival probabilities was demonstrated by adopting calibration curves. Decision curves also exhibited a positive clinical benefit of the nomograms. Conclusions: Nomograms were formulated successfully to predict 3-year and 5-year CSS and OS for bone-metastatic PCa patients. Radical prostatectomy and chemotherapy were strongly associated with the bone-metastatic PCa prognosis.

Bioinformatics and systems-biology analysis to determine the effects of Coronavirus disease 2019 on patients with allergic asthma.

Background: The coronavirus disease (COVID-19) pandemic has posed a significant challenge for global health systems. Increasing evidence shows that asthma phenotypes and comorbidities are major risk factors for COVID-19 symptom severity. However, the molecular mechanisms underlying the association between COVID-19 and asthma are poorly understood. Therefore, we conducted bioinformatics and systems biology analysis to identify common pathways and molecular biomarkers in patients with COVID-19 and asthma, as well as potential molecular mechanisms and candidate drugs for treating patients with both COVID-19 and asthma. Methods: Two sets of differentially expressed genes (DEGs) from the GSE171110 and GSE143192 datasets were intersected to identify common hub genes, shared pathways, and candidate drugs. In addition, murine models were utilized to explore the expression levels and associations of the hub genes in asthma and lung inflammation/injury. Results: We discovered 157 common DEGs between the asthma and COVID-19 datasets. A protein-protein-interaction network was built using various combinatorial statistical approaches and bioinformatics tools, which revealed several hub genes and critical modules. Six of the hub genes were markedly elevated in murine asthmatic lungs and were positively associated with IL-5, IL-13 and MUC5AC, which are the key mediators of allergic asthma. Gene Ontology and pathway analysis revealed common associations between asthma and COVID-19 progression. Finally, we identified transcription factor-gene interactions, DEG-microRNA coregulatory networks, and potential drug and chemical-compound interactions using the hub genes. Conclusion: We identified the top 15 hub genes that can be used as novel biomarkers of COVID-19 and asthma and discovered several promising candidate drugs that might be helpful for treating patients with COVID-19 and asthma.

Single-Cell Analyses Reveal Mechanisms of Cancer Stem Cell Maintenance and Epithelial-Mesenchymal Transition in Recurrent Bladder Cancer.

PURPOSE: Bladder cancer treatment remains a major clinical challenge due to therapy resistance and a high recurrence rate. Profiling intratumor heterogeneity can reveal the molecular mechanism of bladder cancer recurrence. EXPERIMENTAL DESIGN: Here, we performed single-cell RNA sequencing and Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq) on tumors from 13 patients with low recurrence risk, high recurrence risk, and recurrent bladder cancer. RESULTS: Our study generated a comprehensive cancer-cell atlas consisting of 54,971 single cells and identified distinct cell subpopulations. We found that the cancer stem-cell subpopulation is enriched during bladder cancer recurrence with elevated expression of EZH2. We further defined a subpopulation-specific molecular mechanism whereby EZH2 maintains H3K27me3-mediated repression of the NCAM1 gene, thereby inactivating the cell invasive and stemness transcriptional program. Furthermore, taking advantage of this large single-cell dataset, we elucidated the spectrum of epithelial-mesenchymal transition (EMT) in clinical samples and revealed distinct EMT features associated with bladder cancer subtypes. We identified that TCF7 promotes EMT in corroboration with single-cell ATAC with high-throughput sequencing (scATAC-seq) analysis. Additionally, we constructed regulatory networks specific to recurrent bladder cancer. CONCLUSIONS: Our study and analytic approaches herein provide a rich resource for the further study of cancer stem cells and EMT in the bladder cancer research field.

Single-cell analyses reveal suppressive tumor microenvironment of human colorectal cancer.

Profiling heterologous cell types within tumors is essential to decipher tumor microenvironment that shapes tumor progress and determines the outcome of therapeutic response. Here, we comprehensively characterized transcriptomes of 34,037 single cells obtained from 12 treatment-naïve patients with colorectal cancer. Our comprehensive evaluation revealed attenuated B-cell antigen presentation, distinct regulatory T-cell clusters with different origin and novel polyfunctional tumor associated macrophages associated with CRC. Moreover, we identified expanded XCL1+ T-cell clusters associated with tumor mutational burden high status. We further explored the underlying molecular mechanisms by profiling epigenetic landscape and inferring transcription factor motifs using single-cell ATAC-seq. Our dataset and analysis approaches herein provide a rich resource for further study of the impact of immune cells and translational research for human colorectal cancer.