Crawling-induced floor dust resuspension affects the microbiota of the infant breathing zone

Background: Floor dust is commonly used for microbial determinations in epidemiological studies to estimate early-life indoor microbial exposures. Resuspension of floor dust and its impact on infant microbial exposure is, however, little explored. The aim of our study was to investigate how floor dust resuspension induced by an infant's crawling motion and an adult walking affects infant inhalation exposure to microbes. Results: We conducted controlled chamber experiments with a simplified mechanical crawling infant robot and an adult volunteer walking over carpeted flooring. We applied bacterial 16S rRNA gene sequencing and quantitative PCR to monitor the infant breathing zone microbial content and compared that to the adult breathing zone and the carpet dust as the source. During crawling, fungal and bacterial levels were, on average, 8- to 21-fold higher in the infant breathing zone compared to measurements from the adult breathing zone. During walking experiments, the increase in microbial levels in the infant breathing zone was far less pronounced. The correlation in rank orders of microbial levels in the carpet dust and the corresponding infant breathing zone sample varied between different microbial groups but was mostly moderate. The relative abundance of bacterial taxa was characteristically distinct in carpet dust and infant and adult breathing zones during the infant crawling experiments. Bacterial diversity in carpet dust and the infant breathing zone did not correlate significantly. Conclusions: The microbiota in the infant breathing zone differ in absolute quantitative and compositional terms from that of the adult breathing zone and of floor dust. Crawling induces resuspension of floor dust from carpeted flooring, creating a concentrated and localized cloud of microbial content around the infant. Thus, the microbial exposure of infants following dust resuspension is difficult to predict based on common house dust or bulk air measurements. Improved approaches for the assessment of infant microbial exposure, such as sampling at the infant breathing zone level, are needed.Peer reviewe

Autoantibodies Against the Complement Regulator Factor H in the Serum of Patients With Neuromyelitis Optica Spectrum Disorder

Neuromyelitis optica spectrum disorder (NMOSD) is an autoimmune inflammatory disease of the central nervous system (CNS), characterized by pathogenic, complement-activating autoantibodies against the main water channel in the CNS, aquaporin 4 (AQP4). NMOSD is frequently associated with additional autoantibodies and antibody-mediated diseases. Because the alternative pathway amplifies complement activation, our aim was to evaluate the presence of autoantibodies against the alternative pathway C3 convertase, its components C3b and factor B, and the complement regulator factor H (FH) in NMOSD. Four out of 45 AQP4-seropositive NMOSD patients (similar to 9%) had FH autoantibodies in serum and none had antibodies to C3b, factor B and C3bBb. The FH autoantibody titers were low in three and high in one of the patients, and the avidity indexes were low. FH-IgG complexes were detected in the purified IgG fractions by Western blot. The autoantibodies bound to FH domains 19-20, and also recognized the homologous FH-related protein 1 (FHR-1), similar to FH autoantibodies associated with atypical hemolytic uremic syndrome (aHUS). However, in contrast to the majority of autoantibody-positive aHUS patients, these four NMOSD patients did not lack FHR-1. Analysis of autoantibody binding to FH19-20 mutants and linear synthetic peptides of the C-terminal FH and FHR-1 domains, as well as reduced FH, revealed differences in the exact binding sites of the autoantibodies. Importantly, all four autoantibodies inhibited C3b binding to FH. In conclusion, our results demonstrate that FH autoantibodies are not uncommon in NMOSD and suggest that generation of antibodies against complement regulating factors among other autoantibodies may contribute to the complement-mediated damage in NMOSD.Peer reviewe

Donor genetic determinant of thymopoiesis, rs2204985, and stem cell transplantation outcome in a multipopulation cohort

\ua9 2024 The Author(s)Background: A genetic polymorphism, rs2204985, has been reported to be associated with the diversity of T-cell antigen receptor repertoire and TREC levels, reflecting the function of the thymus. As the thymus function can be assumed to be an important factor regulating the outcome of stem cell transplantation (SCT), it was of great interest that rs2204985 showed a genetic association to disease-free and overall survival in a German SCT donor cohort. Tools to predict the outcome of SCT more accurately would help in risk assessment and patient safety. Objective: To evaluate the general validity of the original genetic association found in the German cohort, we determined genetic associations between rs2204985 and the outcome of SCT in 1,473 SCT donors from four different populations. Study design: Genetic associations between rs2204985 genotype AA versus AG/GG and overall survival (OS) and disease-free survival (DFS) in 1,473 adult, allogeneic SCT from Finland, the United Kingdom, Spain, and Poland were performed using the Kaplan-Meier analysis and log-rank tests. We adjusted the survival models with covariates using Cox regression. Results: In unrelated SCT donors (N = 425), the OS of genotype AA versus AG/GG had a trend for a similar association (p = 0.049, log-rank test) as previously reported in the German cohort. The trend did not remain significant in the Cox regression analysis with covariates. No other associations were found. Conclusion: Weak support for the genetic association between rs2204985, previously also associated with thymus function, and the outcome of SCT could be found in a cohort from four populations

Joint Bayesian separation and restoration of CMB from convolutional mixtures

We propose a Bayesian approach to joint source separation and restoration for astrophysical diffuse sources. We constitute a prior statistical model for the source images by using their gradient maps. We assume a t-distribution for the gradient maps in different directions, because it is able to fit both smooth and sparse data. A Monte Carlo technique, called Langevin sampler, is used to estimate the source images and all the model parameters are estimated by using deterministic techniques.Comment: 11 pages, 6 figures. Submitted to MNRA

Early age exposure to moisture damage and systemic inflammation at the age of 6 years

Cross-sectional studies have shown that exposure to indoor moisture damage and mold may be associated with subclinical inflammation. Our aim was to determine whether early age exposure to moisture damage or mold is prospectively associated with subclinical systemic inflammation or with immune responsiveness in later childhood. Home inspections were performed in children's homes in the first year of life. At age 6 years, subclinical systemic inflammation was measured by serum C-reactive protein(CRP) and blood leucocytes and immune responsiveness by ex vivo production of interleukin 1-beta(IL-1beta), IL-6 and tumor necrosis factor-alpha(TNF-alpha) in whole blood cultures without stimulation or after 24h stimulation with phorbol 12-myristate 13-acetate and ionomycin(PI), lipopolysaccharide(LPS) or peptidoglycan(PPG) in 251 to 270 children. Moisture damage in child's main living areas in infancy was not significantly associated with elevated levels of CRP or leucocytes at 6 years. In contrast, there was some suggestion for an effect on immune responsiveness, as moisture damage with visible mold was positively associated with LPS-stimulated production of TNF-alpha and minor moisture damage was inversely associated with PI-stimulated IL-1beta. While early life exposure to mold damage may have some influence on later immune responsiveness, it does not seem to increase subclinical systemic inflammation in later life. This article is protected by copyright. All rights reserved

Independent Component Analysis-motivated Approach to Classificatory Decomposition of Cortical Evoked Potentials

BACKGROUND: Independent Component Analysis (ICA) proves to be useful in the analysis of neural activity, as it allows for identification of distinct sources of activity. Applied to measurements registered in a controlled setting and under exposure to an external stimulus, it can facilitate analysis of the impact of the stimulus on those sources. The link between the stimulus and a given source can be verified by a classifier that is able to "predict" the condition a given signal was registered under, solely based on the components. However, the ICA's assumption about statistical independence of sources is often unrealistic and turns out to be insufficient to build an accurate classifier. Therefore, we propose to utilize a novel method, based on hybridization of ICA, multi-objective evolutionary algorithms (MOEA), and rough sets (RS), that attempts to improve the effectiveness of signal decomposition techniques by providing them with "classification-awareness." RESULTS: The preliminary results described here are very promising and further investigation of other MOEAs and/or RS-based classification accuracy measures should be pursued. Even a quick visual analysis of those results can provide an interesting insight into the problem of neural activity analysis. CONCLUSION: We present a methodology of classificatory decomposition of signals. One of the main advantages of our approach is the fact that rather than solely relying on often unrealistic assumptions about statistical independence of sources, components are generated in the light of a underlying classification problem itself

Airborne cultivable microflora and microbial transfer in farm buildings and rural dwellings

Exposure to environments rich in microorganisms such as farms has been shown to protect against the development of childhood asthma and allergies. However, it remains unclear where, and how, farm and other rural children are exposed to microbes. Furthermore, the composition of the microbial flora is poorly characterised. We tested the hypothesis that farm children are exposed indoors to substantial levels of viable microbes originating from animal sheds and barns. We also expected that environmental microbial flora on farms and in farm homes would be more complex than in the homes of rural control children

Using Red List Indices to monitor extinction risk at national scales

The Red List Index (RLI) measures change in the aggregate extinction risk of species. It is a key indicator for tracking progress toward nine of the Aichi and many proposed post-2020 Global Biodiversity Framework Targets. Here, we consider two formulations of the RLI used for reporting biodiversity trends at national scales. Disaggregated global RLIs measure changing national contributions to global extinction risk and are currently based on five taxonomic groups, while national RLIs measure changing national extinction risk and are based on taxonomic groups assessed multiple times in country. For 74% of nations, the disaggregated global RLI is currently based on three or fewer taxonomic groups. Meanwhile, national RLIs from selected pilot countries Finland, South Africa, and Brazil are computed from twelve, eight, and nine taxonomic groups, respectively. The national RLI and the disaggregated global RLI measure different aspects of biodiversity, in that the former detects national trends in populations of species for which each country is responsible while the latter provides standardized comparisons of nations' contributions to the global extinction risk of the same species groups. As governments commit to the post-2020 Global Biodiversity Framework, we encourage them to monitor a standard set of taxonomic groups representing different biomes using both RLI formulations to ensure effective target tracking and accurate feedback on their conservation investments.Peer reviewe