Eleven-month longitudinal study of antibodies in SARS-CoV-2 exposed and naïve primary health care workers upon COVID-19 vaccination

We evaluated the kinetics of antibody responses to Two years into the COVID-19 pandemic and 1 year after the start of vaccination rollout, the world faced a peak of cases associated with the highly contagious Omicron variant of concern (VoC) of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike (S) and nucleocapsid (N) antigens over five cross-sectional visits (January-November 2021), and the determinants of pre-booster immunoglobulin levels, in a prospective cohort of vaccinated primary health care workers in Catalonia, Spain. Antibodies against S antigens after a full primary vaccination course, mostly with BNT162b2, decreased steadily over time and were higher in pre-exposed (n = 247) than naive (n = 200) individuals, but seropositivity was maintained at 100% (100% IgG, 95.5% IgA, 30.6% IgM) up to 319 days after the first dose. Antibody binding to variants of concern was highly maintained for IgG compared to wild type but significantly reduced for IgA and IgM, particularly for Beta and Gamma. Factors significantly associated with longer-term antibodies included age, sex, occupation, smoking, adverse reaction to vaccination, levels of pre-vaccination SARS-CoV-2 antibodies, interval between disease onset and vaccination, hospitalization, oxygen supply, post COVID and symptomatology. Earlier morning vaccination hours were associated with higher IgG responses in pre-exposed participants. Symptomatic breakthroughs occurred in 9/447 (2.01%) individuals, all among naive (9/200, 4.5%) and generally boosted antibody responses. Additionally, an increase in IgA and/or IgM seropositivity to variants, and N seroconversion at later time points (6.54%), indicated asymptomatic breakthrough infections, even among pre-exposed. Seropositivity remained highly stable over almost a year after vaccination. However, gradually waning of anti-S IgGs that correlate with neutralizing activity, coupled to evidence of an increase in breakthrough infections during the Delta and Omicron predominance, provides a rationale for booster immunization

Common Genetic Polymorphisms Influence Blood Biomarker Measurements in COPD

Implementing precision medicine for complex diseases such as chronic obstructive lung disease (COPD) will require extensive use of biomarkers and an in-depth understanding of how genetic, epigenetic, and environmental variations contribute to phenotypic diversity and disease progression. A meta-analysis from two large cohorts of current and former smokers with and without COPD [SPIROMICS (N = 750); COPDGene (N = 590)] was used to identify single nucleotide polymorphisms (SNPs) associated with measurement of 88 blood proteins (protein quantitative trait loci; pQTLs). PQTLs consistently replicated between the two cohorts. Features of pQTLs were compared to previously reported expression QTLs (eQTLs). Inference of causal relations of pQTL genotypes, biomarker measurements, and four clinical COPD phenotypes (airflow obstruction, emphysema, exacerbation history, and chronic bronchitis) were explored using conditional independence tests. We identified 527 highly significant (p 10% of measured variation in 13 protein biomarkers, with a single SNP (rs7041; p = 10−392) explaining 71%-75% of the measured variation in vitamin D binding protein (gene = GC). Some of these pQTLs [e.g., pQTLs for VDBP, sRAGE (gene = AGER), surfactant protein D (gene = SFTPD), and TNFRSF10C] have been previously associated with COPD phenotypes. Most pQTLs were local (cis), but distant (trans) pQTL SNPs in the ABO blood group locus were the top pQTL SNPs for five proteins. The inclusion of pQTL SNPs improved the clinical predictive value for the established association of sRAGE and emphysema, and the explanation of variance (R2) for emphysema improved from 0.3 to 0.4 when the pQTL SNP was included in the model along with clinical covariates. Causal modeling provided insight into specific pQTL-disease relationships for airflow obstruction and emphysema. In conclusion, given the frequency of highly significant local pQTLs, the large amount of variance potentially explained by pQTL, and the differences observed between pQTLs and eQTLs SNPs, we recommend that protein biomarker-disease association studies take into account the potential effect of common local SNPs and that pQTLs be integrated along with eQTLs to uncover disease mechanisms. Large-scale blood biomarker studies would also benefit from close attention to the ABO blood group

From Cleanroom to Desktop: Emerging Micro-Nanofabrication Technology for Biomedical Applications

This review is motivated by the growing demand for low-cost, easy-to-use, compact-size yet powerful micro-nanofabrication technology to address emerging challenges of fundamental biology and translational medicine in regular laboratory settings. Recent advancements in the field benefit considerably from rapidly expanding material selections, ranging from inorganics to organics and from nanoparticles to self-assembled molecules. Meanwhile a great number of novel methodologies, employing off-the-shelf consumer electronics, intriguing interfacial phenomena, bottom-up self-assembly principles, etc., have been implemented to transit micro-nanofabrication from a cleanroom environment to a desktop setup. Furthermore, the latest application of micro-nanofabrication to emerging biomedical research will be presented in detail, which includes point-of-care diagnostics, on-chip cell culture as well as bio-manipulation. While significant progresses have been made in the rapidly growing field, both apparent and unrevealed roadblocks will need to be addressed in the future. We conclude this review by offering our perspectives on the current technical challenges and future research opportunities

Prospective individual patient data meta-analysis of two randomized trials on convalescent plasma for COVID-19 outpatients

Data on convalescent plasma (CP) treatment in COVID-19 outpatients are scarce. We aimed to assess whether CP administered during the first week of symptoms reduced the disease progression or risk of hospitalization of outpatients. Two multicenter, double-blind randomized trials (NCT04621123, NCT04589949) were merged with data pooling starting when = 50 years and symptomatic for <= 7days were included. The intervention consisted of 200-300mL of CP with a predefined minimum level of antibodies. Primary endpoints were a 5-point disease severity scale and a composite of hospitalization or death by 28 days. Amongst the 797 patients included, 390 received CP and 392 placebo; they had a median age of 58 years, 1 comorbidity, 5 days symptoms and 93% had negative IgG antibody-test. Seventy-four patients were hospitalized, 6 required mechanical ventilation and 3 died. The odds ratio (OR) of CP for improved disease severity scale was 0.936 (credible interval (CI) 0.667-1.311); OR for hospitalization or death was 0.919 (CI 0.592-1.416). CP effect on hospital admission or death was largest in patients with <= 5 days of symptoms (OR 0.658, 95%CI 0.394-1.085). CP did not decrease the time to full symptom resolution

SSMS: A Split Step MultiBand Simulation Software

We introduce SSMS, a multiband optical fiber simulator entirely developed in MATLAB. SSMS solves the generalized nonlinear Schrödinger equation relying on the 4th order Runge-Kutta method in Interaction Picture (RK4IP) with adaptive step size approach and compare it with the widely used split-step Fourier method (SSFM). The simulator is validated considering S+C+L multiband transmission. Results show that the RK4IP method is approximately 10× faster than the traditional SSFM model for a similar level of accuracy

Soft failure localization during commissioning testing and lightpath operation

In elastic optical networks (EONs), effective soft failure localization is of paramount importance to early detection of service level agreement violations while anticipating possible hard failure events. So far, failure localization techniques have been proposed and deployed mainly for hard failures, while significant work is still required to provide effective and automated solutions for soft failures, both during commissioning testing and in-operation phases. In this paper, we focus on soft failure localization in EONs by proposing two techniques for active monitoring during commissioning testing and for passive in-operation monitoring. The techniques rely on specifically designed low-cost optical testing channel (OTC) modules and on the widespread deployment of cost-effective optical spectrum analyzers (OSAs). The retrieved optical parameters are elaborated by machine learning-based algorithms running in the agent's node and in the network controller. In particular, the Testing optIcal Switching at connection SetUp timE (TISSUE) algorithm is proposed to localize soft failures by elaborating the estimated bit-error rate (BER) values provided by the OTC module. In addition, the FailurE causE Localization for optIcal NetworkinG (FEELING) algorithm is proposed to localize failures affecting a lightpath using OSAs. Extensive simulation results are presented, showing the effectiveness of the TISSUE algorithm in properly exploiting OTC information to assess BER performance of quadrature-phase-shift-keying-modulated signals, and the high accuracy of the FEELING algorithm to correctly detect soft failures as laser drift, filter shift, and tight filtering

Airway surface liquid from smokers promotes bacterial growth and biofilm formation via iron-lactoferrin imbalance

Abstract Background Smoking is a leading cause of respiratory infections worldwide. Tobacco particulate matter disrupts iron homeostasis in the lungs and increases the iron content in the airways of smokers. The airway epithelia secrete lactoferrin to quench iron required for bacteria to proliferate and cause lung infections. We hypothesized that smokers would have increased bacterial growth and biofilm formation via iron lactoferrin imbalance. Methods We collected bronchoalveolar lavage (BAL) samples from non-smokers and smokers. We challenged these samples using a standard inoculum of Staphylococcus aureus and Pseudomonas aeruginosa and quantified bacterial growth and biofilm formation. We measured both iron and lactoferrin in the samples. We investigated the effect of supplementing non-smoker BAL with cigarette smoke extract (CSE) or ferric chloride and the effect of supplementing smoker BAL with lactoferrin on bacterial growth and biofilm formation. Results BAL from smokers had increased bacterial growth and biofilm formation compared to non-smokers after both S. aureus and P. aeruginosa challenge. In addition, we found that samples from smokers had a higher iron to lactoferrin ratio. Supplementing the BAL of non-smokers with cigarette smoke extract and ferric chloride increased bacterial growth. Conversely, supplementing the BAL of smokers with lactoferrin had a concentration-dependent decrease in bacterial growth and biofilm formation. Conclusion Cigarette smoking produces factors which increase bacterial growth and biofilm formation in the BAL. We propose that smoking disrupts the iron-to-lactoferrin in the airways. This finding offers a new avenue for potential therapeutic interventions to prevent respiratory infections in smokers