Proteomic analysis of human body fluids is highly challenging, therefore many researchers are redirecting efforts towards secretome profiling. The goal is to define potential biomarkers and therapeutic targets in the secretome that can be traced back in accessible human body fluids. However, currently there is a lack of secretome profiles of normal human primary cells making it difficult to assess the biological meaning of current findings. In this study we sought to establish secretome profiles of human primary cells obtained from healthy donors with the goal of building a human secretome atlas. Such an atlas can be used as a reference for discovery of potential disease associated biomarkers and eventually novel therapeutic targets. As a preliminary study, secretome profiles were established for six different types of human primary cell cultures and checked for overlaps with the three major human body fluids including plasma, cerebrospinal fluid and urine. About 67% of the 1054 identified proteins in the secretome of these primary cells occurred in at least one body fluid. Furthermore, comparison of the secretome profiles of two human glioblastoma cell lines to this new human secretome atlas enabled unambiguous identification of potential brain tumor biomarkers. These biomarkers can be easily monitored in different body fluids using stable isotope labeled standard proteins. The long term goal of this study is to establish a comprehensive online human secretome atlas for future use as a reference for any disease related secretome study.

The polarity of the conducting airway epithelium is responsible for its directional secretion. This is an essential characteristic of lung integrity and function that dictates interactions between the external environment (apical) and subepithelial structures (basolateral). Defining the directional secretomes in the in vitro human bronchial epithelial (HBE) differentiated model could bring valuable insights into lung biology and pulmonary diseases. Normal primary HBE cells (n = 3) were differentiated into respiratory tract epithelium. Apical and basolateral secretions (24 h) were processed for proteome profiling and pathway analysis. A total of 243 proteins were identified in secretions from all HBE cultures combined. Of these, 51% were classified as secreted proteins, including true secreted proteins (36%) and exosomal proteins (15%). Close examination revealed consistent secretion of 69 apical proteins and 13 basolateral proteins and differential secretion of 25 proteins across all donors. Expression of Annexin A4 in apical secretions and Desmoglein-2 in basolateral secretions was validated using Western blot or ELISA in triplicate independent experiments. To the best of our knowledge, this is the first study defining apical and basolateral secretomes in the in vitro differentiated HBE model. The data demonstrate that epithelial polarity directs protein secretion with different patterns of biological processes to the apical and basolateral surfaces that are consistent with normal bronchial epithelium homeostatic functions. Applying this in vitro directional secretome model to lung diseases may elucidate their molecular pathophysiology and help define potential therapeutic targets.

Our study indicates that NH is associated with PH in C-SCD, and that screening for NH may help to identify C-SCD with higher morbidity risk.

Background Spirometry is conventionally used to diagnose airway diseases in children with sickle cell disease (C‐SCD). However, spirometry is difficult for younger children to perform, is effort dependent, and it provides limited information on respiratory mechanics. Impulse oscillometry (IOS) is an effort‐independent pulmonary function test (PFT), which measures total airway resistance (R5Hz) and reactance (AX). IOS could be advantageous without certain limitations of spirometry. Aim To compare the accuracy of IOS vs spirometry in making the diagnosis of asthma and assessing age‐related pulmonary changes in C‐SCD. Study design Retrospective chart review. Subject selection Fifty‐six C‐SCD and thirty‐six controls (asthmatics without SCD) followed at Penn State with PFTs obtained during the initial pulmonary evaluation. Methodology We grouped C‐SCD into asthmatics and non‐asthmatics based on pre‐referral diagnosis and compared PFTs between two groups. Receiver operating characteristic (ROC) curve analyses and machine learning tools (XGBoost and artificial neural network) were used to rank the spirometry and IOS measures based on their ability to predict a diagnosis of asthma. Robust linear regression was used to analyze association among height/age with various PFT measures. Results Both ROC and XGBoost indicated that FEF25‐75%, forced expiratory volume in 1 second (FEV1)/forced vital capacity, and R5Hz(%) were the top three predictors for asthma diagnosis. R5Hz(%) and AX had superior bronchodilator response (BDR) than FEV1. IOS parameters had significant association with height/age in C‐SCD (possibly due to the stiff lungs) but not in controls. Conclusion IOS had advantages over spirometry in C‐SCD because it is feasible in early childhood, provides insights into the pulmonary mechanics, and is more sensitive to detect BDR.

Background: Sociodemographic factors such as age, race, education, family income, and sex have been reported to influence COVID-related perceptions, reflected by knowledge, stress, and preventive behavior. We conducted a US-based survey to estimate the difference in COVID-related perceptions among diverse sociodemographic groups and the influence of sociodemographic heterogeneity on COVID-related perceptions. Methods: The survey enquired about sociodemographic parameters and relevant information to measure knowledge, stress, and preventive behavior. COVID-perception scores among sociodemographic subgroups were compared with ANOVA (Bonferroni). The general linear model (GLM) was used to estimate the association among sociodemographic factors and COVID-related perceptions. Results: Females (75%) and White participants (78%) were the predominant (N = 3734). Females, White participants, wealthy, and educated participants demonstrated better knowledge, while participants of minority races, younger ages, low incomes, and females experienced high stress. Females, African-Americans, and educated participants better adopted preventive behaviors. Race, family income, and sex were the highest contributors to the predictive model. Sociodemographic determinants had statistically significant associations with knowledge (F-score = 7.72, p < 0.001; foremost predictor: race), stress (F-score = 16.46, p < 0.001; foremost predictor: income), and preventive behavior (GLM: F-score = 7.72, p < 0.001, foremost predictor: sex). Conclusion: Sociodemographic heterogeneity significantly influenced COVID-related perceptions, while race, family income, and sex were the strongest determinants of COVID-related perceptions.