Limited effects of Muc1 deficiency on mouse adenovirus type 1 respiratory infection

Muc1 (MUC1 in humans) is a membrane-tethered mucin that exerts anti-inflammatory effects in the lung during bacterial infection. Muc1 and other mucins are also likely to form a protective barrier in the lung. We used mouse adenovirus type 1 (MAV-1, also known as MAdV-1) to determine the role of Muc1 in the pathogenesis of an adenovirus in its natural host. Following intranasal inoculation of wild type mice, we detected increased TNF-α, a cytokine linked to Muc1 production, but no consistent changes in the production of lung Muc1, Muc5ac or overall lung mucus production. Viral loads were modestly higher in the lungs of Muc1−/− mice compared to Muc1+/+ mice at several early time points but decreased to similar levels by 14 days post infection in both groups. However, cellular inflammation and the expression of CXCL1, CCL5, and CCL2 did not significantly differ between Muc1−/− and Muc1+/+ mice. Our data therefore suggest that Muc1 may contribute to a physical barrier that protects against MAV-1 respiratory infection. However, our data do not reveal an anti-inflammatory effect of Muc1 that contributes to MAV-1 pathogenesis.

Examining the effects of perceived pregnancy discrimination on mother and baby health

Over the last decade, more than 50,000 pregnancy discrimination claims were filed in the United States (United States Equal Employment Opportunity Commission [U.S. EEOC], 2018a). While pregnancy discrimination claims remain prevalent, research examining the effects of pregnancy discrimination on the well-being and health of working mothers and their babies is lacking. As such, we aim to examine the role of perceived pregnancy discrimination in the workplace on health outcomes for mothers and their babies via mother's stress. We draw on the occupational stress literature and medical research to propose that perceived pregnancy discrimination indirectly relates to mother and baby health via the mother's perceived stress. In our first study, we examine the effects of perceived pregnancy discrimination on mothers' postpartum depressive symptoms via perceived stress. In our second study, we replicate and extend our first study and examine the effects of perceived pregnancy discrimination on mothers' postpartum depressive symptoms and babies' gestational age, Apgar scores, birth weight, and number of doctors' visits, through the mechanism of perceived stress. We find that perceived pregnancy discrimination indirectly relates to increased levels of postpartum depressive symptoms for the mothers, and lower birth weights, lower gestational ages, and increased number of doctors' visits for the babies, via perceived stress of the mothers during pregnancy. Implications for theory and practice, limitations, and future research are discussed

Six-SOMAmer Index Relating to Immune, Protease and Angiogenic Functions Predicts Progression in IPF

<div><p>Rationale</p><p>Biomarkers in easily accessible compartments like peripheral blood that can predict disease progression in idiopathic pulmonary fibrosis (IPF) would be clinically useful regarding clinical trial participation or treatment decisions for patients. In this study, we used unbiased proteomics to identify relevant disease progression biomarkers in IPF.</p><p>Methods</p><p>Plasma from IPF patients was measured using an 1129 analyte slow off-rate modified aptamer (SOMAmer) array, and patient outcomes were followed over the next 80 weeks. Receiver operating characteristic (ROC) curves evaluated sensitivity and specificity for levels of each biomarker and estimated area under the curve (AUC) when prognostic biomarker thresholds were used to predict disease progression. Both logistic and Cox regression models advised biomarker selection for a composite disease progression index; index biomarkers were weighted via expected progression-free days lost during follow-up with a biomarker on the unfavorable side of the threshold.</p><p>Results</p><p>A six-analyte index, scaled 0 to 11, composed of markers of immune function, proteolysis and angiogenesis [high levels of ficolin-2 (FCN2), cathepsin-S (Cath-S), legumain (LGMN) and soluble vascular endothelial growth factor receptor 2 (VEGFsR2), but low levels of inducible T cell costimulator (ICOS) or trypsin 3 (TRY3)] predicted better progression-free survival in IPF with a ROC AUC of 0.91. An index score ≥ 3 (group ≥ 2) was strongly associated with IPF progression after adjustment for age, gender, smoking status, immunomodulation, forced vital capacity % predicted and diffusing capacity for carbon monoxide % predicted (HR 16.8, 95% CI 2.2–126.7, P = 0.006).</p><p>Conclusion</p><p>This index, derived from the largest proteomic analysis of IPF plasma samples to date, could be useful for clinical decision making in IPF, and the identified analytes suggest biological processes that may promote disease progression.</p></div

Biomarker Threshold Values in RFU, Corresponding Sensitivity and Specificity for Predicting 80-week Progression Status and Univariate Odds Ratios (Unadjusted and Adjusted) for Progression When above Versus below the Threshold.

<p>Biomarker Threshold Values in RFU, Corresponding Sensitivity and Specificity for Predicting 80-week Progression Status and Univariate Odds Ratios (Unadjusted and Adjusted) for Progression When above Versus below the Threshold.</p

Distribution of scores for patients meeting the definition for progressor or non-progressor.

<p>Distribution of scores for patients meeting the definition for progressor or non-progressor.</p

Best logistic regression model based on 4 binary biomarkers.

<p>Best logistic regression model based on 4 binary biomarkers.</p

Kaplan-Meier curve showing progression free survival for patients according to the different severity groups in our weighted index score.

<p>In unadjusted analyses, A group level <b>increasing by 1</b> using this index has a hazard ratio = 4.02, (95%CI 2.28–7.10), P<0.0001 for predicting IPF progression by univariate Cox regression model. In adjusted analyses, a group level <b>increasing by 1</b> using this index has a hazard ratio = 4.06, (95%CI 2.17–7.60), P<0.0001 for predicting IPF progression by Cox regression model after being adjusted for age, gender, smoking status, baseline FVC percent predicted, baseline DLCO percent predicted and immunomodulation therapy.</p

Distribution of group scores among progressors and non-progressors.

<p>Distribution of group scores among progressors and non-progressors.</p