Proteomics screening after pediatric allogenic hematopoietic stem cell transplantation reveals an association between increased expression of inhibitory receptor FCRL6 on γδ T cells and cytomegalovirus reactivation.

We studied the associations between inflammation-related proteins in circulation and complications after pediatric allogenic hematopoietic stem cell transplantation (HSCT), to reveal proteomic signatures or individual soluble proteins associated with specific complications after HSCT. We used a proteomics method called Proximity Extension Assay to repeatedly measure 180 different proteins together with clinical variables, cellular immune reconstitution and blood viral copy numbers in 27 children (1-18 years of age) during a 2-year follow-up after allogenic HSCT. Protein profile analysis was performed using unsupervised hierarchical clustering and a regression-based method, while the Bonferroni-corrected Mann-Whitney U-test was used for time point-specific comparison of individual proteins against outcome. At 6 months after allogenic HSCT, we could identify a protein profile pattern associated with occurrence of the complications such as chronic graft-versus-host disease, viral infections, relapse and death. When protein markers were analyzed separately, the plasma concentration of the inhibitory and cytotoxic T-cell surface protein FCRL6 (Fc receptor-like 6) was higher in patients with cytomegalovirus (CMV) viremia [log2-fold change 1.5 (P = 0.00099), 2.5 (P = 0.00035) and 2.2 (P = 0.045) at time points 6, 12 and 24 months]. Flow cytometry confirmed that FCRL6 expression was higher in innate-like γδ T cells, indicating that these cells are involved in controlling CMV reactivation in HSCT recipients. In conclusion, the potentially druggable FCRL6 receptor on cytotoxic T cells appears to have a role in controlling CMV viremia after HSCT. Furthermore, our results suggest that system-level analysis is a useful addition to the studying of single biomarkers in allogenic HSCT.

Deep Learning Enables Automatic Detection of Joint Damage Progression in Rheumatoid Arthritis-Model Development and External Validation.

OBJECTIVES: Although deep learning has demonstrated substantial potential in automatic quantification of joint damage in rheumatoid arthritis (RA), evidence for detecting longitudinal changes at an individual patient level is lacking. Here, we introduce and externally validate our automated RA scoring algorithm (AuRA), and demonstrate its utility for monitoring radiographic progression in a real-world setting. METHODS: The algorithm, originally developed during the Rheumatoid Arthritis 2-Dialogue for Reverse Engineering Assessment and Methods (RA2-DREAM) challenge, was trained to predict expert-curated Sharp-van der Heijde total scores in hand and foot radiographs from two previous clinical studies (n = 367). We externally validated AuRA against data (n = 205) from Turku University Hospital and compared the performance against two top-performing RA2-DREAM solutions. Finally, for 54 patients, we extracted additional radiograph sets from another control visit to the clinic (average time interval of 4.6 years). RESULTS: In the external validation cohort, with a root-mean-square-error (RMSE) of 23.6, AuRA outperformed both top-performing RA2-DREAM algorithms (RMSEs 35.0 and 35.6). The improved performance was explained mostly by lower errors at higher expert-assessed scores. The longitudinal changes predicted by our algorithm were significantly correlated with changes in expert-assessed scores (Pearson's R = 0.74, p< 0.001). CONCLUSION: AuRA had the best external validation performance and demonstrated potential for detecting longitudinal changes in joint damage. Available in https://hub.docker.com/r/elolab/aura, our algorithm can easily be applied for automatic detection of radiographic progression in the future, reducing the need for laborious manual scoring.

scShaper: an ensemble method for fast and accurate linear trajectory inference from single-cell RNA-seq data.

MOTIVATION: Computational models are needed to infer a representation of the cells, i.e. a trajectory, from single-cell RNA-sequencing data that model cell differentiation during a dynamic process. Although many trajectory inference methods exist, their performance varies greatly depending on the dataset and hence there is a need to establish more accurate, better generalizable methods. RESULTS: We introduce scShaper, a new trajectory inference method that enables accurate linear trajectory inference. The ensemble approach of scShaper generates a continuous smooth pseudotime based on a set of discrete pseudotimes. We demonstrate that scShaper is able to infer accurate trajectories for a variety of trigonometric trajectories, including many for which the commonly used principal curves method fails. A comprehensive benchmarking with state-of-the-art methods revealed that scShaper achieved superior accuracy of the cell ordering and, in particular, the differentially expressed genes. Moreover, scShaper is a fast method with few hyperparameters, making it a promising alternative to the principal curves method for linear pseudotemporal ordering. AVAILABILITY AND IMPLEMENTATION: scShaper is available as an R package at https://github.com/elolab/scshaper. The test data are available at https://doi.org/10.5281/zenodo.5734488. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Unifying incidence and prevalence under a time-varying general branching process.

Renewal equations are a popular approach used in modelling the number of new infections, i.e., incidence, in an outbreak. We develop a stochastic model of an outbreak based on a time-varying variant of the Crump-Mode-Jagers branching process. This model accommodates a time-varying reproduction number and a time-varying distribution for the generation interval. We then derive renewal-like integral equations for incidence, cumulative incidence and prevalence under this model. We show that the equations for incidence and prevalence are consistent with the so-called back-calculation relationship. We analyse two particular cases of these integral equations, one that arises from a Bellman-Harris process and one that arises from an inhomogeneous Poisson process model of transmission. We also show that the incidence integral equations that arise from both of these specific models agree with the renewal equation used ubiquitously in infectious disease modelling. We present a numerical discretisation scheme to solve these equations, and use this scheme to estimate rates of transmission from serological prevalence of SARS-CoV-2 in the UK and historical incidence data on Influenza, Measles, SARS and Smallpox.

A novel easy-to-use index to predict institutionalization and death in older population - a 10-year population-based follow-up study.

BACKGROUND: Various indexes have been developed to estimate the risk for mortality, institutionalization, and other adverse outcomes for older people. Most indexes are based on a large number of clinical or laboratory parameters. An index based on only a few parameters would be more practical to use in every-day clinical practice. Our aim was to create an index to predict the risk for mortality and institutionalization with as few parameters as possible without compromising their predictive ability. METHODS: A prospective study with a 10-year follow-up period. Thirty-six clinical and fourteen laboratory parameters were combined to form an index. Cox regression model was used to analyze the association of the index with institutionalization and mortality. A backward statistical method was used to reduce the number of parameters to form an easy-to-use index for predicting institutionalization and mortality. RESULTS: The mean age of the participants (n = 1172) was 73.1 (SD 6.6, range 64‒97) years. Altogether, 149 (14%) subjects were institutionalized, and 413 (35%) subjects deceased during the follow-up. Institutionalization and mortality rates increased as index scores increased both for the large 50-parameter combined index and for the reduced indexes. After a backward variable selection in the Cox regression model, three clinical parameters remained in the index to predict institutionalization and six clinical and three laboratory parameters in the index to predict mortality. The reduced indexes showed a slightly better predictive value for both institutionalization and mortality compared to the full index. CONCLUSIONS: A large index with fifty parameters included many unimportant parameters that did not increase its predictive value, and therefore could be replaced with a reduced index with only a few carefully chosen parameters, that were individually associated with institutionalization or death.

Risk factors for revision due to prosthetic joint infection following total knee arthroplasty based on 62,087 knees in the Finnish Arthroplasty Register from 2014 to 2020.

BACKGROUND AND PURPOSE: Periprosthetic joint infection (PJI) is the commonest reason for revision after total knee arthroplasty (TKA). We assessed the risk factors for revision due to PJI following TKA based on the Finnish Arthroplasty Register (FAR). PATIENTS AND METHODS: We analyzed 62,087 primary condylar TKAs registered between June 2014 and February 2020 with revision for PJI as the endpoint. Cox proportional hazards regression was used to estimate hazard ratios (HR) with 95% confidence intervals (CI) for the first PJI revision using 25 potential patient- and surgical-related risk factors as covariates. RESULTS: 484 knees were revised for the first time during the first postoperative year because of PJI. The HRs for revision due to PJI in unadjusted analysis were 0.5 (0.4-0.6) for female sex, 0.7 (0.6-1.0) for BMI 25-29, and 1.6 (1.1-2.5) for BMI > 40 compared with BMI < 25, 4.0 (1.3-12) for preoperative fracture diagnosis compared with osteoarthritis, and 0.7 (0.5-0.9) for use of an antimicrobial incise drape. In adjusted analysis the HRs were 2.2 (1.4-3.5) for ASA class III-IV compared with class I, 1.7 (1.4-2.1) for intraoperative bleeding ≥ 100 mL, 1.4 (1.2-1.8) for use of a drain, 0.7 (0.5-1.0) for short duration of operation of 45-59 minutes, and 1.7 (1.3-2.3) for long operation duration > 120 min compared with 60-89 minutes, and 1.3 (1.0-1.8) for use of general anesthesia. CONCLUSION: We found increased risk for revision due to PJI when no incise drape was used. The use of drainage also increased the risk. Specializing in performing TKA reduces operative time and thereby also the PJI rate.

Systematic evaluation of differential splicing tools for RNA-seq studies.

Differential splicing (DS) is a post-transcriptional biological process with critical, wide-ranging effects on a plethora of cellular activities and disease processes. To date, a number of computational approaches have been developed to identify and quantify differentially spliced genes from RNA-seq data, but a comprehensive intercomparison and appraisal of these approaches is currently lacking. In this study, we systematically evaluated 10 DS analysis tools for consistency and reproducibility, precision, recall and false discovery rate, agreement upon reported differentially spliced genes and functional enrichment. The tools were selected to represent the three different methodological categories: exon-based (DEXSeq, edgeR, JunctionSeq, limma), isoform-based (cuffdiff2, DiffSplice) and event-based methods (dSpliceType, MAJIQ, rMATS, SUPPA). Overall, all the exon-based methods and two event-based methods (MAJIQ and rMATS) scored well on the selected measures. Of the 10 tools tested, the exon-based methods performed generally better than the isoform-based and event-based methods. However, overall, the different data analysis tools performed strikingly differently across different data sets or numbers of samples.

Stable Iterative Variable Selection.

MOTIVATION: The emergence of datasets with tens of thousands of features, such as high-throughput omics biomedical data, highlights the importance of reducing the feature space into a distilled subset that can truly capture the signal for research and industry by aiding in finding more effective biomarkers for the question in hand. A good feature set also facilitates building robust predictive models with improved interpretability and convergence of the applied method due to the smaller feature space. RESULTS: Here, we present a robust feature selection method named Stable Iterative Variable Selection (SIVS) and assess its performance over both omics and clinical data types. As a performance assessment metric, we compared the number and goodness of the selected feature using SIVS to those selected by Least Absolute Shrinkage and Selection Operator regression. The results suggested that the feature space selected by SIVS was, on average, 41% smaller, without having a negative effect on the model performance. A similar result was observed for comparison with Boruta and caret RFE. AVAILABILITY AND IMPLEMENTATION: The method is implemented as an R package under GNU General Public License v3.0 and is accessible via Comprehensive R Archive Network (CRAN) via https://cran.r-project.org/package=sivs. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

ILoReg: a tool for high-resolution cell population identification from single-cell RNA-seq data.

MOTIVATION: Single-cell RNA-seq allows researchers to identify cell populations based on unsupervised clustering of the transcriptome. However, subpopulations can have only subtle transcriptomic differences and the high dimensionality of the data makes their identification challenging. RESULTS: We introduce ILoReg, an R package implementing a new cell population identification method that improves identification of cell populations with subtle differences through a probabilistic feature extraction step that is applied before clustering and visualization. The feature extraction is performed using a novel machine learning algorithm, called iterative clustering projection (ICP), that uses logistic regression and clustering similarity comparison to iteratively cluster data. Remarkably, ICP also manages to integrate feature selection with the clustering through L1-regularization, enabling the identification of genes that are differentially expressed between cell populations. By combining solutions of multiple ICP runs into a single consensus solution, ILoReg creates a representation that enables investigating cell populations with a high resolution. In particular, we show that the visualization of ILoReg allows segregation of immune and pancreatic cell populations in a more pronounced manner compared with current state-of-the-art methods. AVAILABILITY AND IMPLEMENTATION: ILoReg is available as an R package at https://bioconductor.org/packages/ILoReg. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Median 10-year whole blood metal ion levels and clinical outcome of ReCap-M2a-Magnum metal-on-metal total hip arthroplasty.

BACKGROUND AND PURPOSE: We have previously reported that the whole blood (WB) chromium (Cr) and cobalt (Co) ion levels decrease in the short term after ReCap-M2a-Magnum large-diameter head (LDH) metal-on-metal (MoM) total hip arthroplasty (THA). This study reports long-term metal ion levels and clinical outcomes after ReCap-Magnum THA. PATIENTS AND METHODS: ReCap-M2a-Magnum LDH THA was used in 1,450 patients in our hospital district from 2005 to 2012. Median follow-up time was 10 years. 991 patients had 2 or more metal ion measurements. The median measurement interval was 4 years. Individual metal ion change was assessed using logarithmic metal ion values in a random coefficient model. Kaplan-Meier survival estimates were calculated for revision surgery for any reason for revision, and separately for metal-related adverse events (metal ions above safe upper limit [SUL], revision due to ARMD, or pseudotumor). RESULTS: Geometric mean of Cr decreased from 1.8 ppb (geometric standard deviation [GSD] 1.8) to 1.0 ppb (GSD 2.8, p < 0.001). The Co levels decreased from 1.7 ppb (GSD 2.4) to 1.4 ppb (GSD 2.8, p < 0.001). The hip-specific survival was 85% for revision due to any reason at 14 years and the hip-specific survival for any metal-related adverse event was 69% at 14 years. INTERPRETATION: WB Cr and Co levels continued to decrease in the long-term follow-up of ReCap-M2a-Magnum THA patients. The amount of metal-related adverse events was rather high, but revision surgery was seldom required. We suggest that after 10 years from the implantation a 5-year measurement interval may be sufficient for asymptomatic ReCap-M2a-Magnum patients.

Repeated metal ion measurements and long-term outcome of Durom/MMC total hip arthroplasty.

Background and purpose - Data regarding long-term behavior of metal ion levels in metal-on-metal total hip arthroplasty (MoM THA) patients is scarce. Therefore, we assessed whether there is any change in whole blood (WB) chromium (Cr), and cobalt (Co) ion measurements in Durom and MMC MoM THA patients over time. The secondary aim was to report the clinical outcomes using these devices in a single district. Patients and methods - Durom and MMC cups were used in 249 MoM THAs from 2005 to 2011 in our district. Median follow-up time was 12 years for Durom THA (interquartile range [IQR] = 3) and 9 years for MMC THA (IQR = 1). A random coefficient model was used to compare individual differences in repeated WB Cr and Co ion measurements. The Kaplan-Meier estimator was used to analyze implant survival with any reason for revision as the endpoint. Results - Geometric means of Cr in Durom THA and MMC THA patients decreased from 2.2 ppb (geometric standard deviation [SD] = 1.9) to 1.5 ppb (geometric SD = 2.5, p< 0.001) and from 1.8 ppb (geometric SD = 1.8) to 1.1 ppb (geometric SD = 2.8, p = 0.01) respectively. The geometric means of Co values remained unchanged. The 10-year survival of Durom THA was 82%, and that of MMC THA 89% for any revision reason as endpoint. Interpretation - WB Cr levels decreased over time, and Co levels remained unchanged at long-term follow-up. Despite this we recommend continuing the follow-up of these devices due to relatively low implant survival.

Inflammatory responses of urban air PM modulated by chemical composition and different air quality situations in Nanjing, China.

The health risks of air pollutants and ambient particulate matter (PM) are widely known. PM composition and toxicity have shown substantial spatiotemporal variability. Yet, the connections between PM composition and toxicological and health effects are vaguely understood. This is a crucial gap in knowledge that needs to be addressed in order to establish air quality guidelines and limit values that consider the chemical composition of PM instead of the current assumption of equal toxicity per inhaled dose. Here, we demonstrate further evidence for varying toxicological effects of urban PM at equal mass concentrations, and estimate how PM composition and emission source characteristics influenced this variation. We exposed a co-culture model mimicking alveolar epithelial cells and macrophages with size-segregated urban ambient PM collected before, during, and after the Nanjing Youth Olympic Games 2014. We measured the release of a set of cytokines, cell cycle alterations, and genotoxicity, and assessed the spatiotemporal variations in these responses by factorial multiple regression analysis. Additionally, we investigated how a previously identified set of emission sources and chemical components affected these variations by mixed model analysis. PM-exposure induced cytokine signaling, most notably by inducing dose-dependent increases of macrophage-regulating GM-CSF and proinflammatory TNFα, IL-6, and IL-1ß concentrations, modest dose-dependent increase for cytoprotective VEGF-A, but very low to no responses for anti-inflammatory IL-10 and immunoregulatory IFNγ, respectively. We observed substantial differences in proinflammatory cytokine production depending on PM sampling period, location, and time of day. The proinflammatory response correlated positively with cell cycle arrest in G1/G0 phase and loss of cellular metabolic activity. Furthermore, PM0.2 caused dose-dependent increases in sub-G1/G0 cells, suggesting increased DNA degradation and apoptosis. Variations in traffic and oil/fuel combustion emissions contributed substantially to the observed spatiotemporal variations of toxicological responses.

Risk factors for prosthetic joint infections following total hip arthroplasty based on 33,337 hips in the Finnish Arthroplasty Register from 2014 to 2018.

Background and purpose - Periprosthetic joint infection (PJI) is a devastating complication and more information on risk factors for PJI is required to find measures to prevent infections. Therefore, we assessed risk factors for PJI after primary total hip arthroplasty (THA) in a large patient cohort.Patients and methods - We analyzed 33,337 primary THAs performed between May 2014 and January 2018 based on the Finnish Arthroplasty Register (FAR). Cox proportional hazards regression was used to estimate hazard ratios with 95% confidence intervals (CI) for first PJI revision operation using 25 potential patient- and surgical-related risk factors as covariates.Results - 350 primary THAs were revised for the first time due to PJI during the study period. The hazard ratios for PJI revision in multivariable analysis were 2.0 (CI 1.3-3.2) for ASA class II and 3.2 (2.0-5.1) for ASA class III-IV compared with ASA class I, 1.4 (1.1-1.7) for bleeding > 500 mL compared with < 500 mL, 0.4 (0.2-0.7) for ceramic-on-ceramic bearing couple compared with metal-on-polyethylene and for the first 3 postoperative weeks, 3.0 (1.6-5.6) for operation time of > 120 minutes compared with 45-59 minutes, and 2.6 (1.4-4.9) for simultaneous bilateral operation. In the univariable analysis, hazard ratios for PJI revision were 2.3 (1.7-3.3) for BMI of 31-35 and 5.0 (3.5-7.1) for BMI of > 35 compared with patients with BMI of 21-25.Interpretation - We found several modifiable risk factors associated with increased PJI revision risk after THA to which special attention should be paid preoperatively. In particular, high BMI may be an even more prominent risk factor for PJI than previously assessed.

Air quality intervention during the Nanjing youth olympic games altered PM sources, chemical composition, and toxicological responses.

Ambient particulate matter (PM) is a leading global environmental health risk. Current air quality regulations are based on airborne mass concentration. However, PM from different sources have distinct chemical compositions and varied toxicity. Connections between emission control measures, air quality, PM composition, and toxicity remain insufficiently elucidated. The current study assessed the composition and toxicity of PM collected in Nanjing, China before, during, and after an air quality intervention for the 2014 Youth Olympic Games. A co-culture model that mimics the alveolar epithelium with the associated macrophages was created using A549 and THP-1 cells. These cells were exposed to size-segregated inhalable PM samples. The composition and toxicity of the PM samples were influenced by several factors including seasonal variation, emission sources, and the air quality intervention. For example, we observed a size-dependent shift in particle mass concentrations during the air quality intervention with an emphasized proportion of smaller particles (PM2.5) present in the air. The roles of industrial and fuel combustion and traffic emissions were magnified during the emission control period. Our analyses revealed that the PM samples demonstrated differential cytotoxic potencies at equal mass concentrations between sampling periods, locations, and time of day, influenced by variations in the predominant emission sources. Coal combustion and industrial emissions were the most important sources affecting the toxicological responses and displayed the least variation in emission contributions between the sampling periods. In conclusion, emission control mitigated cytotoxicity and oxidative stress for particles larger than 0.2 µm, but there was inadequate evidence to determine if it was the key factor reducing the harmful effects of PM0.2.

Mutations in ASIP and MC1R: dominant black and recessive black alleles segregate in native Swedish sheep populations.

By studying genes associated with coat colour, we can understand the role of these genes in pigmentation but also gain insight into selection history. North European short-tailed sheep, including Swedish breeds, have variation in their coat colour, making them good models to expand current knowledge of mutations associated with coat colour in sheep. We studied ASIP and MC1R, two genes with known roles in pigmentation, and their association with black coat colour. We did this by sequencing the coding regions of ASIP in 149 animals and MC1R in 129 animals from seven native Swedish sheep breeds in individuals with black, white or grey fleece. Previously known mutations in ASIP [recessive black allele: g.100_105del (D5 ) and/or g.5172T>A] were associated with black coat colour in Klövsjö and Roslag sheep breeds and mutations in both ASIP and MC1R (dominant black allele: c.218T>A and/or c.361G>A) were associated with black coat colour in Swedish Finewool. In Gotland, Gute, Värmland and Helsinge sheep breeds, coat colour inheritance was more complex: only 11 of 16 individuals with black fleece had genotypes that could explain their black colour. These breeds have grey individuals in their populations, and grey is believed to be a result of mutations and allelic copy number variation within the ASIP duplication, which could be a possible explanation for the lack of a clear inheritance pattern in these breeds. Finally, we found a novel missense mutation in MC1R (c.452G>A) in Gotland, Gute and Värmland sheep and evidence of a duplication of MC1R in Gotland sheep.

The evolutionary history of the DMRT3 'Gait keeper' haplotype.

A previous study revealed a strong association between the DMRT3:Ser301STOP mutation in horses and alternate gaits as well as performance in harness racing. Several follow-up studies have confirmed a high frequency of the mutation in gaited horse breeds and an effect on gait quality. The aim of this study was to determine when and where the mutation arose, to identify additional potential causal mutations and to determine the coalescence time for contemporary haplotypes carrying the stop mutation. We utilized sequences from 89 horses representing 26 breeds to identify 102 SNPs encompassing the DMRT3 gene that are in strong linkage disequilibrium with the stop mutation. These 102 SNPs were genotyped in an additional 382 horses representing 72 breeds, and we identified 14 unique haplotypes. The results provided conclusive evidence that DMRT3:Ser301STOP is causal, as no other sequence polymorphisms showed an equally strong association to locomotion traits. The low sequence diversity among mutant chromosomes demonstrated that they must have diverged from a common ancestral sequence within the last 10 000 years. Thus, the mutation occurred either just before domestication or more likely some time after domestication and then spread across the world as a result of selection on locomotion traits.

Particulate emissions from the combustion of birch, beech, and spruce logs cause different cytotoxic responses in A549 cells.

According to the World Health Organization particulate emissions from the combustion of solid fuels caused more than 110,000 premature deaths worldwide in 2010. Log wood combustion is the most prevalent form of residential biomass heating in developed countries, but it is unknown how the type of wood logs used in furnaces influences the chemical composition of the particulate emissions and their toxicological potential. We burned logs of birch, beech and spruce, which are used commonly as firewood in Central and Northern Europe in a modern masonry heater, and compared them to the particulate emissions from an automated pellet boiler fired with softwood pellets. We determined the chemical composition (elements, ions, and carbonaceous compounds) of the particulate emissions with a diameter of less than 1 µm and tested their cytotoxicity, genotoxicity, inflammatory potential, and ability to induce oxidative stress in a human lung epithelial cell line. The chemical composition of the samples differed significantly, especially with regard to the carbonaceous and metal contents. Also the toxic effects in our tested endpoints varied considerably between each of the three log wood combustion samples, as well as between the log wood combustion samples and the pellet combustion sample. The difference in the toxicological potential of the samples in the various endpoints indicates the involvement of different pathways of toxicity depending on the chemical composition. All three emission samples from the log wood combustions were considerably more toxic in all endpoints than the emissions from the pellet combustion. © 2016 Wiley Periodicals, Inc. Environ Toxicol 32: 1487-1499, 2017.

Acute exposure to wood smoke from incomplete combustion--indications of cytotoxicity.

BACKGROUND: Smoke from combustion of biomass fuels is a major risk factor for respiratory disease, but the underlying mechanisms are poorly understood. The aim of this study was to determine whether exposure to wood smoke from incomplete combustion would elicit airway inflammation in humans. METHODS: Fourteen healthy subjects underwent controlled exposures on two separate occasions to filtered air and wood smoke from incomplete combustion with PM1 concentration at 314 µg/m(3) for 3 h in a chamber. Bronchoscopy with bronchial wash (BW), bronchoalveolar lavage (BAL) and endobronchial mucosal biopsies was performed after 24 h. Differential cell counts and soluble components were analyzed, with biopsies stained for inflammatory markers using immunohistochemistry. In parallel experiments, the toxicity of the particulate matter (PM) generated during the chamber exposures was investigated in vitro using the RAW264.7 macrophage cell line. RESULTS: Significant reductions in macrophage, neutrophil and lymphocyte numbers were observed in BW (p < 0.01, <0.05, <0.05, respectively) following the wood smoke exposure, with a reduction in lymphocytes numbers in BAL fluid (<0.01. This unexpected cellular response was accompanied by decreased levels of sICAM-1, MPO and MMP-9 (p < 0.05, <0.05 and <0.01). In contrast, significant increases in submucosal and epithelial CD3+ cells, epithelial CD8+ cells and submucosal mast cells (p < 0.01, <0.05, <0.05 and <0.05, respectively), were observed after wood smoke exposure. The in vitro data demonstrated that wood smoke particles generated under these incomplete combustion conditions induced cell death and DNA damage, with only minor inflammatory responses. CONCLUSIONS: Short-term exposure to sooty PAH rich wood smoke did not induce an acute neutrophilic inflammation, a classic hallmark of air pollution exposure in humans. While minor proinflammatory lymphocytic and mast cells effects were observed in the bronchial biopsies, significant reductions in BW and BAL cells and soluble components were noted. This unexpected observation, combined with the in vitro data, suggests that wood smoke particles from incomplete combustion could be potentially cytotoxic. Additional research is required to establish the mechanism of this dramatic reduction in airway leukocytes and to clarify how this acute response contributes to the adverse health effects attributed to wood smoke exposure. TRIAL REGISTRATION: NCT01488500.

Role of microbial and chemical composition in toxicological properties of indoor and outdoor air particulate matter.

BACKGROUND: Ambient air particulate matter (PM) is increasingly considered to be a causal factor evoking severe adverse health effects. People spend the majority of their time indoors, which should be taken into account especially in future risk assessments, when the role of outdoor air particles transported into indoor air is considered. Therefore, there is an urgent need for characterization of possible sources seasonally for harmful health outcomes both indoors and outdoors. METHODS: In this study, we collected size-segregated (PM(10-2.5), PM(2.5-0.2)) particulate samples with a high volume cascade impactor (HVCI) simultaneously both indoors and outdoors of a new single family detached house at four different seasons. The chemical composition of the samples was analyzed as was the presence of microbes. Mouse macrophages were exposed to PM samples for 24 hours. Thereafter, the levels of the proinflammatory cytokines, NO-production, cytotoxicity and changes in the cell cycle were investigated. The putative sources of the most toxic groups of constituents were resolved by using the principal component analysis (PCA) and pairwise dependencies of the variables were detected with Spearman correlation. RESULTS: Source-related toxicological responses clearly varied according to season. The role of outdoor sources in indoor air quality was significant only in the warm seasons and the significance of outdoor microbes was also larger in the indoor air. During wintertime, the role of indoor sources of the particles was more significant, as was also the case for microbes. With respect to the outdoor sources, soil-derived particles during a road dust episode and local wood combustion in wintertime were the most important factors inducing toxicological responses. CONCLUSIONS: Even though there were clear seasonal differences in the abilities of indoor and outdoor air to induce inflammatory and cytotoxic responses, there were relatively small differences in the chemical composition of the particles responsible of those effects. Outdoor sources have only a limited effect on indoor air quality in a newly built house with a modern ventilation system at least in a low air pollution environment. The most important sources for adverse health related toxicological effects were related to soil-derived constituents, local combustion emissions and microbes.

Worldwide frequency distribution of the 'Gait keeper' mutation in the DMRT3 gene.

For centuries, domestic horses have represented an important means of transport and served as working and companion animals. Although their role in transportation is less important today, many horse breeds are still subject to intense selection based on their pattern of locomotion. A striking example of such a selected trait is the ability of a horse to perform additional gaits other than the common walk, trot and gallop. Those could be four-beat ambling gaits, which are particularly smooth and comfortable for the rider, or pace, used mainly in racing. Gaited horse breeds occur around the globe, suggesting that gaitedness is an old trait, selected for in many breeds. A recent study discovered that a nonsense mutation in DMRT3 has a major impact on gaitedness in horses and is present at a high frequency in gaited breeds and in horses bred for harness racing. Here, we report a study of the worldwide distribution of this mutation. We genotyped 4396 horses representing 141 horse breeds for the DMRT3 stop mutation. More than half (2749) of these horses also were genotyped for a SNP situated 32 kb upstream of the DMRT3 nonsense mutation because these two SNPs are in very strong linkage disequilibrium. We show that the DMRT3 mutation is present in 68 of the 141 genotyped horse breeds at a frequency ranging from 1% to 100%. We also show that the mutation is not limited to a geographical area, but is found worldwide. The breeds with a high frequency of the stop mutation (>50%) are either classified as gaited or bred for harness racing.