BACKGROUND: Pulmonary complications, including infections, are highly prevalent in patients after hematopoietic cell transplantation with chronic graft-vs-host disease. These comorbid diseases can make the diagnosis of early lung graft-vs-host disease (bronchiolitis obliterans syndrome) challenging. A quantitative method to differentiate among these pulmonary diseases can address diagnostic challenges and facilitate earlier and more targeted therapy. STUDY DESIGN AND METHODS:We conducted a single-center study of 66 patients with CT chest scans analyzed with a quantitative imaging tool known as parametric response mapping. Parametric response mapping results were correlated with pulmonary function tests and clinical characteristics. Five parametric response mapping metrics were applied to K-means clustering and support vector machine models to distinguish among posttransplantation lung complications solely from quantitative output.RESULTS: Compared with parametric response mapping, spirometry showed a moderate correlation with radiographic air trapping, and total lung capacity and residual volume showed a strong correlation with radiographic lung volumes. K-means clustering analysis distinguished four unique clusters. Clusters 2 and 3 represented obstructive physiology (encompassing 81% of patients with bronchiolitis obliterans syndrome) in increasing severity (percentage air trapping 15.6% and 43.0%, respectively). Cluster 1 was dominated by normal lung, and cluster 4 was characterized by patients with parenchymal opacities. A support vector machine algorithm differentiated bronchiolitis obliterans syndrome with a specificity of 88%, sensitivity of 83%, accuracy of 86%, and an area under the receiver operating characteristic curve of 0.85. INTERPRETATION:Our machine learning models offer a quantitative approach for the identification of bronchiolitis obliterans syndrome vs other lung diseases, including late pulmonary complications after hematopoietic cell transplantation.

Despite the ability of combination antiretroviral therapy (cART) to increase the life expectancy of patients infected with human immunodeficiency virus (HIV), viral reservoirs persist during life-long treatment. Notably, two cases of functional cure for HIV have been reported and are known as the “Berlin Patient” and the “London Patient”. Both patients received allogeneic hematopoietic stem cell transplantation from donors with homozygous CCR5 delta32 mutation for an associated hematological malignancy. Therefore, there is growing interest in creating an HIV-resistant immune system through the use of gene-modified autologous hematopoietic stem cells with non-functional CCR5. Moreover, studies in CXCR4-targeted gene therapy for HIV have also shown great promise. Developing a cure for HIV infection remains a high priority. In this review, we discuss the increasing progress of coreceptor-based hematopoietic stem cell gene therapy, cART, milder conditioning regimens, and shock and kill strategies that have important implications for designing potential strategies aiming to achieve a functional cure for the majority of people with HIV.

Background Pancreatic ductal adenocarcinoma (PDAC) is a fatal malignant neoplasm. It is necessary to improve the understanding of the underlying molecular mechanisms and identify the key genes and signaling pathways involved in PDAC. Methods The microarray datasets GSE28735, GSE62165, and GSE91035 were downloaded from the Gene Expression Omnibus. Differentially expressed genes (DEGs) were identified by integrated bioinformatics analysis, including protein–protein interaction (PPI) network, Gene Ontology (GO) enrichment, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. The PPI network was established using the Search Tool for the Retrieval of Interacting Genes (STRING) and Cytoscape software. GO functional annotation and KEGG pathway analyses were performed using the Database for Annotation, Visualization, and Integrated Discovery. Hub genes were validated via the Gene Expression Profiling Interactive Analysis tool (GEPIA) and the Human Protein Atlas (HPA) website. Results A total of 263 DEGs (167 upregulated and 96 downregulated) were common to the three datasets. We used STRING and Cytoscape software to establish the PPI network and then identified key modules. From the PPI network, 225 nodes and 803 edges were selected. The most significant module, which comprised 11 DEGs, was identified using the Molecular Complex Detection plugin. The top 20 hub genes, which were filtered by the CytoHubba plugin, comprised FN1, COL1A1, COL3A1, BGN, POSTN, FBN1, COL5A2, COL12A1, THBS2, COL6A3, VCAN, CDH11, MMP14, LTBP1, IGFBP5, ALB, CXCL12, FAP, MATN3, and COL8A1. These genes were validated using The Cancer Genome Atlas (TCGA) and Genotype–Tissue Expression (GTEx) databases, and the encoded proteins were subsequently validated using the HPA website. The GO analysis results showed that the most significantly enriched biological process, cellular component, and molecular function terms among the 20 hub genes were cell adhesion, proteinaceous extracellular matrix, and calcium ion binding, respectively. The KEGG pathway analysis showed that the 20 hub genes were mainly enriched in ECM–receptor interaction, focal adhesion, PI3K-Akt signaling pathway, and protein digestion and absorption. These findings indicated that FBN1 and COL8A1 appear to be involved in the progression of PDAC. Moreover, patient survival analysis performed via the GEPIA using TCGA and GTEx databases demonstrated that the expression levels of COL12A1 and MMP14 were correlated with a poor prognosis in PDAC patients (p < 0.05). Conclusions The results demonstrated that upregulation of MMP14 and COL12A1 is associated with poor overall survival, and these might be a combination of prognostic biomarkers in PDAC.

Alzheimer’s disease (AD) is an age-associated progressive neurodegenerative disorder which is of clinical concern. The association between the nervous and immune system is defined as an neuroimmunological theory that supports a model of pathology or treatment for AD. Interleukin (IL)-1β has a pro-inflammatory function in AD; however, the mechanism of its dysregulation in AD remains unknown. It is therefore of significance to understand the molecular mechanisms of IL-1β and how it may regulate AD. Proteins, which have been previously reported to be associated with IL-1β in AD, have been used in the present study as nodes to illustrate a net of protein interaction in Cytoscape. The Kyoto Encyclopedia of Genes and Genomes was used to further analyze the association of these proteins with the pathology of AD. The present study identified and subsequently compared two AD and six IL-1β pathways with the network produced in Cytoscape. The present study identified important mechanisms in the pathology of AD and constructed two novel networks using Cytoscape.

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