Cystic fibrosis macrophage function and clinical outcomes after elexacaftor/tezacaftor/ivacaftor.

Background: Abnormal macrophage function caused by dysfunctional cystic fibrosis transmembrane conductance regulator (CFTR) is a critical contributor to chronic airway infections and inflammation in people with cystic fibrosis (PWCF). Elexacaftor/tezacaftor/ivacaftor (ETI) is a new CFTR modulator therapy for PWCF. Host-pathogen and clinical responses to CFTR modulators are poorly described.

(R)-Roscovitine and CFTR modulators enhance killing of multi-drug resistant Burkholderia cenocepacia by cystic fibrosis macrophages.

Cystic fibrosis (CF) is characterized by chronic bacterial infections and heightened inflammation. Widespread ineffective antibiotic use has led to increased isolation of drug resistant bacterial strains from respiratory samples. (R)-roscovitine (Seliciclib) is a unique drug that has many benefits in CF studies.

Consequences of CRISPR-Cas9-Mediated CFTR Knockout in Human Macrophages.

Macrophage dysfunction is fundamentally related to altered immunity in cystic fibrosis (CF). How genetic deficits in the cystic fibrosis transmembrane conductance regulator (CFTR) lead to these defects remains unknown. Rapid advances in genomic editing such as the clustered regularly interspaced short palindromic repeats associated protein 9 (CRISPR/Cas9) system provide new tools for scientific study.

Author Correction: Baseline and Disease-Induced Transcriptional Profiles in Children with Sickle Cell Disease.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Baseline and Disease-Induced Transcriptional Profiles in Children with Sickle Cell Disease.

Acute chest syndrome (ACS) is a significant cause of morbidity and mortality in sickle cell disease (SCD), but preventive, diagnostic, and therapeutic options are limited. Further, ACS and acute vasoccclusive pain crises (VOC) have overlapping features, which causes diagnostic dilemmas. We explored changes in gene expression profiles among patients with SCD hospitalized for VOC and ACS episodes to better understand ACS disease pathogenesis.

Metabolomics profiling of tobacco exposure in children with cystic fibrosis.

Background: Inflammation is integral to early disease progression in children with CF. The effect of modifiable environmental factors on infection and inflammation in persons with CF is poorly understood. Our prior studies determined that secondhand smoke exposure (SHSe) is highly prevalent in young children with CF.

The Unfolded Protein Response Mediator PERK Governs Myeloid Cell-Driven Immunosuppression in Tumors through Inhibition of STING Signaling.

The primary mechanisms supporting immunoregulatory polarization of myeloid cells upon infiltration into tumors remain largely unexplored. Elucidation of these signals could enable better strategies to restore protective anti-tumor immunity. Here, we investigated the role of the intrinsic activation of the PKR-like endoplasmic reticulum (ER) kinase (PERK) in the immunoinhibitory actions of tumor-associated myeloid-derived suppressor cells (tumor-MDSCs).

Whole-blood transcriptomic responses to lumacaftor/ivacaftor therapy in cystic fibrosis.

Background: Cystic fibrosis (CF) remains without a definitive cure. Novel therapeutics targeting the causative defect in the cystic fibrosis transmembrane conductance regulator (CFTR) gene are in clinical use. Lumacaftor/ivacaftor is a CFTR modulator approved for patients homozygous for the CFTR variant p.

Cystic fibrosis transmembrane conductance regulator (CFTR) modulators have differential effects on cystic fibrosis macrophage function.

Despite the addition of cystic fibrosis transmembrane conductance regulator (CFTR) modulators to the cystic fibrosis (CF) treatment regimen, patients with CF continue to suffer from chronic bacterial infections that lead to progressive respiratory morbidity. Host immunity, and macrophage dysfunction specifically, has an integral role in the inability of patients with CF to clear bacterial infections. We sought to characterize macrophage responses to CFTR modulator treatment as we hypothesized that there would be differential effects based on patient genotype.

AR-13 reduces antibiotic-resistant bacterial burden in cystic fibrosis phagocytes and improves cystic fibrosis transmembrane conductance regulator function.

Background: There are no effective treatments for Burkholderia cenocepacia in patients with cystic fibrosis (CF) due to bacterial multi-drug resistance and defective host killing. We demonstrated that decreased bacterial killing in CF is caused by reduced macrophage autophagy due to defective cystic fibrosis transmembrane conductance regulator (CFTR) function. AR-12 is a small molecule autophagy inducer that kills intracellular pathogens such as Francisella.

Highly accurate model for prediction of lung nodule malignancy with CT scans.

Computed tomography (CT) examinations are commonly used to predict lung nodule malignancy in patients, which are shown to improve noninvasive early diagnosis of lung cancer. It remains challenging for computational approaches to achieve performance comparable to experienced radiologists. Here we present NoduleX, a systematic approach to predict lung nodule malignancy from CT data, based on deep learning convolutional neural networks (CNN).

Metabolomic responses to lumacaftor/ivacaftor in cystic fibrosis.

Background: Cystic fibrosis (CF) is a life-limiting disease caused by a defect in the cystic fibrosis transmembrane conductance regulator (CFTR) gene. Lumacaftor/Ivacaftor is a novel CFTR modulator approved for patients that are homozygous for Phe508del CFTR, but its clinical effectiveness varies amongst patients, making it difficult to determine clinical responders. Therefore, identifying biochemical biomarkers associated with drug response are clinically important for follow-up studies.

Cysteamine-mediated clearance of antibiotic-resistant pathogens in human cystic fibrosis macrophages.

Members of the Burkholderia cepacia complex are virulent, multi-drug resistant pathogens that survive and replicate intracellularly in patients with cystic fibrosis (CF). We have discovered that B. cenocepacia cannot be cleared from CF macrophages due to defective autophagy, causing continued systemic inflammation and infection.

SparRec: An effective matrix completion framework of missing data imputation for GWAS.

Genome-wide association studies present computational challenges for missing data imputation, while the advances of genotype technologies are generating datasets of large sample sizes with sample sets genotyped on multiple SNP chips. We present a new framework SparRec (Sparse Recovery) for imputation, with the following properties: (1) The optimization models of SparRec, based on low-rank and low number of co-clusters of matrices, are different from current statistics methods. While our low-rank matrix completion (LRMC) model is similar to Mendel-Impute, our matrix co-clustering factorization (MCCF) model is completely new.

T cells conditioned with MDSC show an increased anti-tumor activity after adoptive T cell based immunotherapy.

The success of adoptive T cell-based immunotherapy (ACT) in cancer is limited in part by the accumulation of myeloid-derived suppressor cells (MDSC), which block several T cell functions, including T cell proliferation and the expression of various cytotoxic mediators. Paradoxically, the inhibition of CD8+ T cell differentiation into cytotoxic populations increased their efficacy after ACT into tumor-bearing hosts. Therefore, we aimed to test the impact of conditioning CD8+ T cells with MDSC on their differentiation potential and ACT efficacy.

SPARCoC: a new framework for molecular pattern discovery and cancer gene identification.

It is challenging to cluster cancer patients of a certain histopathological type into molecular subtypes of clinical importance and identify gene signatures directly relevant to the subtypes. Current clustering approaches have inherent limitations, which prevent them from gauging the subtle heterogeneity of the molecular subtypes. In this paper we present a new framework: SPARCoC (Sparse-CoClust), which is based on a novel Common-background and Sparse-foreground Decomposition (CSD) model and the Maximum Block Improvement (MBI) co-clustering technique.

Big data - a 21st century science Maginot Line? No-boundary thinking: shifting from the big data paradigm.

Whether your interests lie in scientific arenas, the corporate world, or in government, you have certainly heard the praises of big data: Big data will give you new insights, allow you to become more efficient, and/or will solve your problems. While big data has had some outstanding successes, many are now beginning to see that it is not the Silver Bullet that it has been touted to be. Here our main concern is the overall impact of big data; the current manifestation of big data is constructing a Maginot Line in science in the 21st century.

eMBI: Boosting Gene Expression-based Clustering for Cancer Subtypes.

Identifying clinically relevant subtypes of a cancer using gene expression data is a challenging and important problem in medicine, and is a necessary premise to provide specific and efficient treatments for patients of different subtypes. Matrix factorization provides a solution by finding checker-board patterns in the matrices of gene expression data. In the context of gene expression profiles of cancer patients, these checkerboard patterns correspond to genes that are up- or down-regulated in patients with particular cancer subtypes.

Total synthesis and determination of the absolute configuration of rakicidin A.

Rakicidin A is a cyclic depsipeptide that has exhibited unique growth inhibitory activity against chronic myelogenous leukemia stem cells. Furthermore, rakicidin A has five chiral centers with unknown stereochemical assignment, and thus, can be represented by one of 32 possible stereoisomers. To predict the most probable stereochemistry of rakicidin A, calculations and structural comparison with natural cyclic depsipeptides were applied.

No-boundary thinking in bioinformatics research.

Currently there are definitions from many agencies and research societies defining "bioinformatics" as deriving knowledge from computational analysis of large volumes of biological and biomedical data. Should this be the bioinformatics research focus? We will discuss this issue in this review article. We would like to promote the idea of supporting human-infrastructure (HI) with no-boundary thinking (NT) in bioinformatics (HINT).

Trp53 negatively regulates autoimmunity via the STAT3-Th17 axis.

Emerging evidence suggests that the tumor suppressor p53 is also a crucial regulator for many physiological processes. Previous observations indicate that p53 suppresses inflammation by inhibiting inflammatory antigen-presenting cells. To investigate the potential role of p53 in autoimmune effector T cells, we generated p53(null)CD45.