Inspiratory effort and lung mechanics in spontaneously breathing patients with acute respiratory failure due to COVID-19. A matched control study.

Several physical and biological mechanisms can drive progression between the different phases of lung injury due to SARS-CoV-2 infection, thus modifying the mechanical properties and behavior of COVID-19 over time. In this research letter we have presented the findings of a registered clinical trial aimed at describing and comparing the inspiratory effort (primary outcome) and the breathing pattern of spontaneously breathing patients with ARF in COVID-19 and historically matched non-COVID-19 patients, either candidate to NIV. Moreover, we reported the response to a 2 hours NIV trial in the two groups. Spontaneously breathing COVID-19 at their early onset of acute respiratory failure with indication for NIV showed different mechanical characteristics and breathing pattern when compared with non-COVID-19

Fibrotic idiopathic interstitial lung disease: the molecular and cellular key players.

Interstitial lung disease (ILDs) that are known as diffuse parenchymal lung diseases (DPLDs) lead to the damage of alveolar epithelium and lung parenchyma culminating into inflammation and widespread fibrosis. ILDs that account for more than 200 different pathologies, can be di-vided into two groups: ILDs that have a known cause and those where the cause is unknown clas-sified as Idiopathic Interstitial Pneumonia (IIPs). IIPs include idiopathic pulmonary fibrosis (IPF), non-specific interstitial pneumonia (NSIP), cryptogenic organizing pneumonia (COP) known also as bronchiolitis obliterans organizing pneumonia (BOOP), Acute interstitial pneumonia (AIP), Desquamative Interstitial Pneumonia (DIP), Respiratory bronchiolitis-associated interstitial lung disease (RB-ILD), and lymphocytic interstitial pneumonia (LIP). In this review our aim is to de-scribe the pathogenic mechanisms that lead to the onset and progression of the different IIPs, starting from IPF as the most studied, in order to find both common and standalone molecular and cellular key players among them. Finally, a deeper molecular and cellular characterization of different interstitial lung disease without known cause, would contribute to give a more accurate diagnosis to the patients, that would translate in a more effective treatment decision

Exome Sequencing Identifies Genetic Variants Associated with Circulating Lipid Levels in Mexican Americans: The Insulin Resistance Atherosclerosis Family Study (IRASFS)

Genome-wide association studies have identified numerous variants associated with lipid levels; yet, the majority are located in non-coding regions with unclear mechanisms. In the Insulin Resistance Atherosclerosis Family Study (IRASFS), heritability estimates suggest a strong genetic basis: low-density lipoprotein (LDL, h2 = 0.50), high-density lipoprotein (HDL, h2 = 0.57), total cholesterol (TC, h2 = 0.53), and triglyceride (TG, h2 = 0.42) levels. Exome sequencing of 1,205 Mexican Americans (90 pedigrees) from the IRASFS identified 548,889 variants and association and linkage analyses with lipid levels were performed. One genome-wide significant signal was detected in APOA5 with TG (rs651821, PTG = 3.67 × 10−10, LODTG = 2.36, MAF = 14.2%). In addition, two correlated SNPs (r2 = 1.0) rs189547099 (PTG = 6.31 × 10−08, LODTG = 3.13, MAF = 0.50%) and chr4:157997598 (PTG = 6.31 × 10−08, LODTG = 3.13, MAF = 0.50%) reached exome-wide significance (P \u3c 9.11 × 10−08). rs189547099 is an intronic SNP in FNIP2 and SNP chr4:157997598 is intronic in GLRB. Linkage analysis revealed 46 SNPs with a LOD \u3e 3 with the strongest signal at rs1141070 (LODLDL = 4.30, PLDL = 0.33, MAF = 21.6%) in DFFB. A total of 53 nominally associated variants (P \u3c 5.00 × 10−05, MAF ≥ 1.0%) were selected for replication in six Mexican-American cohorts (N = 3,280). The strongest signal observed was a synonymous variant (rs1160983, PLDL = 4.44 × 10−17, MAF = 2.7%) in TOMM40. Beyond primary findings, previously reported lipid loci were fine-mapped using exome sequencing in IRASFS. These results support that exome sequencing complements and extends insights into the genetics of lipid levels

Activation of the steroid and xenobiotic receptor, SXR, induces apoptosis in breast cancer cells

<p>Abstract</p> <p>Background</p> <p>The steroid and xenobiotic receptor, SXR, is an orphan nuclear receptor that regulates metabolism of diverse dietary, endobiotic, and xenobiotic compounds. SXR is expressed at high levels in the liver and intestine, and at lower levels in breast and other tissues where its function was unknown. Since many breast cancer preventive and therapeutic compounds are SXR activators, we hypothesized that some beneficial effects of these compounds are mediated through SXR.</p> <p>Methods</p> <p>To test this hypothesis, we measured proliferation of breast cancer cells in response to SXR activators and evaluated consequent changes in the expression of genes critical for proliferation and cell-cycle control using quantitative RT-PCR and western blotting. Results were confirmed using siRNA-mediated gene knockdown. Statistical analysis was by t-test or ANOVA and a P value ≤ 0.05 was considered to be significant.</p> <p>Results</p> <p>Many structurally and functionally distinct SXR activators inhibited the proliferation of MCF-7 and ZR-75-1 breast cancer cells by inducing cell cycle arrest at the G1/S phase followed by apoptosis. Decreased growth in response to SXR activation was associated with stabilization of p53 and up-regulation of cell cycle regulatory and pro-apoptotic genes such as p21, PUMA and BAX. These gene expression changes were preceded by an increase in inducible nitric oxide synthase and nitric oxide in these cells. Inhibition of iNOS blocked the induction of p53. p53 knockdown inhibited up-regulation of p21 and BAX. We infer that NO is required for p53 induction and that p53 is required for up-regulation of cell cycle regulatory and apoptotic genes in this system. SXR activator-induced increases in iNOS levels were inhibited by siRNA-mediated knockdown of SXR, indicating that SXR activation is necessary for subsequent regulation of iNOS expression.</p> <p>Conclusion</p> <p>We conclude that activation of SXR is anti-proliferative in p53 wild type breast cancer cells and that this effect is mechanistically dependent upon the local production of NO and NO-dependent up-regulation of p53. These findings reveal a novel biological function for SXR and suggest that a subset of SXR activators may function as effective therapeutic and chemo-preventative agents for certain types of breast cancers.</p

PatternLab for proteomics: a tool for differential shotgun proteomics

<p>Abstract</p> <p>Background</p> <p>A goal of proteomics is to distinguish between states of a biological system by identifying protein expression differences. Liu <it>et al</it>. demonstrated a method to perform semi-relative protein quantitation in shotgun proteomics data by correlating the number of tandem mass spectra obtained for each protein, or "spectral count", with its abundance in a mixture; however, two issues have remained open: how to normalize spectral counting data and how to efficiently pinpoint differences between profiles. Moreover, Chen <it>et al</it>. recently showed how to increase the number of identified proteins in shotgun proteomics by analyzing samples with different MS-compatible detergents while performing proteolytic digestion. The latter introduced new challenges as seen from the data analysis perspective, since replicate readings are not acquired.</p> <p>Results</p> <p>To address the open issues above, we present a program termed PatternLab for proteomics. This program implements existing strategies and adds two new methods to pinpoint differences in protein profiles. The first method, ACFold, addresses experiments with less than three replicates from each state or having assays acquired by different protocols as described by Chen <it>et al</it>. ACFold uses a combined criterion based on expression fold changes, the AC test, and the false-discovery rate, and can supply a "bird's-eye view" of differentially expressed proteins. The other method addresses experimental designs having multiple readings from each state and is referred to as nSVM (natural support vector machine) because of its roots in evolutionary computing and in statistical learning theory. Our observations suggest that nSVM's niche comprises projects that select a minimum set of proteins for classification purposes; for example, the development of an early detection kit for a given pathology. We demonstrate the effectiveness of each method on experimental data and confront them with existing strategies.</p> <p>Conclusion</p> <p>PatternLab offers an easy and unified access to a variety of feature selection and normalization strategies, each having its own niche. Additionally, graphing tools are available to aid in the analysis of high throughput experimental data. PatternLab is available at <url>http://pcarvalho.com/patternlab</url>.</p

Current challenges in software solutions for mass spectrometry-based quantitative proteomics

This work was in part supported by the PRIME-XS project, grant agreement number 262067, funded by the European Union seventh Framework Programme; The Netherlands Proteomics Centre, embedded in The Netherlands Genomics Initiative; The Netherlands Bioinformatics Centre; and the Centre for Biomedical Genetics (to S.C., B.B. and A.J.R.H); by NIH grants NCRR RR001614 and RR019934 (to the UCSF Mass Spectrometry Facility, director: A.L. Burlingame, P.B.); and by grants from the MRC, CR-UK, BBSRC and Barts and the London Charity (to P.C.

A novel patient-derived tumorgraft model with TRAF1-ALK anaplastic large-cell lymphoma translocation.

Although anaplastic large-cell lymphomas (ALCL) carrying anaplastic lymphoma kinase (ALK) have a relatively good prognosis, aggressive forms exist. We have identified a novel translocation, causing the fusion of the TRAF1 and ALK genes, in one patient who presented with a leukemic ALK+ ALCL (ALCL-11). To uncover the mechanisms leading to high-grade ALCL, we developed a human patient-derived tumorgraft (hPDT) line. Molecular characterization of primary and PDT cells demonstrated the activation of ALK and nuclear factor kB (NFkB) pathways. Genomic studies of ALCL-11 showed the TP53 loss and the in vivo subclonal expansion of lymphoma cells, lacking PRDM1/Blimp1 and carrying c-MYC gene amplification. The treatment with proteasome inhibitors of TRAF1-ALK cells led to the downregulation of p50/p52 and lymphoma growth inhibition. Moreover, a NFkB gene set classifier stratified ALCL in distinct subsets with different clinical outcome. Although a selective ALK inhibitor (CEP28122) resulted in a significant clinical response of hPDT mice, nevertheless the disease could not be eradicated. These data indicate that the activation of NFkB signaling contributes to the neoplastic phenotype of TRAF1-ALK ALCL. ALCL hPDTs are invaluable tools to validate the role of druggable molecules, predict therapeutic responses and implement patient specific therapies