A guide to chemokines and their receptors

The chemokines (or chemotactic cytokines) are a large family of small, secreted proteins that signal through cell surface G‐protein coupled heptahelical chemokine receptors. They are best known for their ability to stimulate the migration of cells, most notably white blood cells (leukocytes). Consequently, chemokines play a central role in the development and homeostasis of the immune system, and are involved in all protective or destructive immune and inflammatory responses. Classically viewed as inducers of directed chemotactic migration, it is now clear that chemokines can stimulate a variety of other types of directed and undirected migratory behaviour, such as haptotaxis, chemokinesis, and haptokinesis, in addition to inducing cell arrest or adhesion. However, chemokine receptors on leukocytes can do more than just direct migration, and these molecules can also be expressed on, and regulate the biology of, many non‐leukocytic cell types. Chemokines are profoundly affected by post‐translational modification, by interaction with the extracellular matrix (ECM), and by binding to heptahelical ‘atypical’ chemokine receptors that regulate chemokine localisation and abundance. This guide gives a broad overview of the chemokine and chemokine receptor families; summarises the complex physical interactions that occur in the chemokine network; and, using specific examples, discusses general principles of chemokine function, focussing particularly on their ability to direct leukocyte migration

A new measurement of the intergalactic temperature at z ∼ 2.55–2.95

We present two measurements of the temperature–density relationship (TDR) of the intergalactic medium (IGM) in the redshift range 2.55 < z < 2.95 using a sample of 13 high-quality quasar spectra and high resolution numerical simulations of the IGM. Our approach is based on fitting the neutral hydrogen column density NHI and the Doppler parameter b of the absorption lines in the Lyα forest. The first measurement is obtained using a novel Bayesian scheme that takes into account the statistical correlations between the parameters characterizing the lower cut-off of the b--NHI distribution and the power-law parameters T0 and γ describing the TDR. This approach yields T0/103 K = 15.6 ± 4.4 and γ = 1.45 ± 0.17 independent of the assumed pressure smoothing of the small-scale density field. In order to explore the information contained in the overall b--NHI distribution rather than only the lower cut-off, we obtain a second measurement based on a similar Bayesian analysis of the median Doppler parameter for separate column-density ranges of the absorbers. In this case, we obtain T0/103 K = 14.6 ± 3.7 and γ = 1.37 ± 0.17 in good agreement with the first measurement. Our Bayesian analysis reveals strong anticorrelations between the inferred T0 and γ for both methods as well as an anticorrelation of the inferred T0 and the pressure smoothing length for the second method, suggesting that the measurement accuracy can in the latter case be substantially increased if independent constraints on the smoothing are obtained. Our results are in good agreement with other recent measurements of the thermal state of the IGM probing similar (over-)density ranges.MH acknowledges support by ERC ADVANCED GRANT 320596 ‘The Emergence of Structure during the epoch of Reionization’. GDB was supported by the National Science Foundation through grant AST-1615814. JSB acknowledges the support of a Royal Society University Research Fellowship. MTM thanks the Australian Research Council for Discovery Project grant DP130100568. This work made use of the DiRAC High Performance Computing System (HPCS) and the COSMOS shared memory service at the University of Cambridge. These are operated on behalf of the STFC DiRAC HPC facility. This equipment is funded by BIS National E-infrastructure capital grant ST/J005673/1 and STFC grants ST/H008586/1, ST/K00333X/1

Mechanisms of Psychological Distress following War in the Former Yugoslavia: The Role of Interpersonal Sensitivity

This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.This study was funded by a grant from the European Commission, contract number INCO-CT-2004-509176. AN was supported by a Clinical Early Career Research Fellowship (113295) and a Project Grant (104288

Flow cytometry data standards

<p>Abstract</p> <p>Background</p> <p>Flow cytometry is a widely used analytical technique for examining microscopic particles, such as cells. The Flow Cytometry Standard (FCS) was developed in 1984 for storing flow data and it is supported by all instrument and third party software vendors. However, FCS does not capture the full scope of flow cytometry (FCM)-related data and metadata, and data standards have recently been developed to address this shortcoming.</p> <p>Findings</p> <p>The Data Standards Task Force (DSTF) of the International Society for the Advancement of Cytometry (ISAC) has developed several data standards to complement the raw data encoded in FCS files. Efforts started with the Minimum Information about a Flow Cytometry Experiment, a minimal data reporting standard of details necessary to include when publishing FCM experiments to facilitate third party understanding. MIFlowCyt is now being recommended to authors by publishers as part of manuscript submission, and manuscripts are being checked by reviewers and editors for compliance. Gating-ML was then introduced to capture gating descriptions - an essential part of FCM data analysis describing the selection of cell populations of interest. The Classification Results File Format was developed to accommodate results of the gating process, mostly within the context of automated clustering. Additionally, the Archival Cytometry Standard bundles data with all the other components describing experiments. Here, we introduce these recent standards and provide the very first example of how they can be used to report FCM data including analysis and results in a standardized, computationally exchangeable form.</p> <p>Conclusions</p> <p>Reporting standards and open file formats are essential for scientific collaboration and independent validation. The recently developed FCM data standards are now being incorporated into third party software tools and data repositories, which will ultimately facilitate understanding and data reuse.</p

Statistical and visual differentiation of subcellular imaging

<p>Abstract</p> <p>Background</p> <p>Automated microscopy technologies have led to a rapid growth in imaging data on a scale comparable to that of the genomic revolution. High throughput screens are now being performed to determine the localisation of all of proteins in a proteome. Closer to the bench, large image sets of proteins in treated and untreated cells are being captured on a daily basis to determine function and interactions. Hence there is a need for new methodologies and protocols to test for difference in subcellular imaging both to remove bias and enable throughput. Here we introduce a novel method of statistical testing, and supporting software, to give a rigorous test for difference in imaging. We also outline the key questions and steps in establishing an analysis pipeline.</p> <p>Results</p> <p>The methodology is tested on a high throughput set of images of 10 subcellular localisations, and it is shown that the localisations may be distinguished to a statistically significant degree with as few as 12 images of each. Further, subtle changes in a protein's distribution between nocodazole treated and control experiments are shown to be detectable. The effect of outlier images is also examined and it is shown that while the significance of the test may be reduced by outliers this may be compensated for by utilising more images. Finally, the test is compared to previous work and shown to be more sensitive in detecting difference. The methodology has been implemented within the iCluster system for visualising and clustering bio-image sets.</p> <p>Conclusion</p> <p>The aim here is to establish a methodology and protocol for testing for difference in subcellular imaging, and to provide tools to do so. While iCluster is applicable to moderate (<1000) size image sets, the statistical test is simple to implement and will readily be adapted to high throughput pipelines to provide more sensitive discrimination of difference.</p

Survey of the needs of patients with spinal cord injury: impact and priority for improvement in hand function in tetraplegics\ud

Objective: To investigate the impact of upper extremity deficit in subjects with tetraplegia.\ud \ud Setting: The United Kingdom and The Netherlands.\ud \ud Study design: Survey among the members of the Dutch and UK Spinal Cord Injury (SCI) Associations.\ud \ud Main outcome parameter: Indication of expected improvement in quality of life (QOL) on a 5-point scale in relation to improvement in hand function and seven other SCI-related impairments.\ud \ud Results: In all, 565 subjects with tetraplegia returned the questionnaire (overall response of 42%). Results in the Dutch and the UK group were comparable. A total of 77% of the tetraplegics expected an important or very important improvement in QOL if their hand function improved. This is comparable to their expectations with regard to improvement in bladder and bowel function. All other items were scored lower.\ud \ud Conclusion: This is the first study in which the impact of upper extremity impairment has been assessed in a large sample of tetraplegic subjects and compared to other SCI-related impairments that have a major impact on the life of subjects with SCI. The present study indicates a high impact as well as a high priority for improvement in hand function in tetraplegics.\ud \u

Left ventricular non-compaction: clinical features and cardiovascular magnetic resonance imaging

Background: It is apparent that despite lack of family history, patients with the morphological characteristics of left ventricular non-compaction develop arrhythmias, thrombo-embolism and left ventricular dysfunction. METHODS: Forty two patients, aged 48.7 +/- 2.3 yrs (mean +/- SEM) underwent cardiovascular magnetic resonance (CMR) for the quantification of left ventricular volumes and extent of non-compacted (NC) myocardium. The latter was quantified using planimetry on the two-chamber long axis LV view (NC area). The patients included those referred specifically for CMR to investigate suspected cardiomyopathy, and as such is represents a selected group of patients. RESULTS: At presentation, 50% had dyspnoea, 19% chest pain, 14% palpitations and 5% stroke. Pulmonary embolism had occurred in 7% and brachial artery embolism in 2%. The ECG was abnormal in 81% and atrial fibrillation occurred in 29%. Transthoracic echocardiograms showed features of NC in only 10%. On CMR, patients who presented with dyspnoea had greater left ventricular volumes (both p < 0.0001) and a lower left ventricular ejection fraction (LVEF) (p < 0.0001) than age-matched, healthy controls. In patients without dyspnoea (n = 21), NC area correlated positively with end-diastolic volume (r = 0.52, p = 0.0184) and end-systolic volume (r = 0.56, p = 0.0095), and negatively with EF (r = -0.72, p = 0.0001). CONCLUSION: Left ventricular non-compaction is associated with dysrrhythmias, thromboembolic events, chest pain and LV dysfunction. The inverse correlation between NC area and EF suggests that NC contributes to left ventricular dysfunction

Unbiased Rare Event Sampling in Spatial Stochastic Systems Biology Models Using a Weighted Ensemble of Trajectories

The long-term goal of connecting scales in biological simulation can be facilitated by scale-agnostic methods. We demonstrate that the weighted ensemble (WE) strategy, initially developed for molecular simulations, applies effectively to spatially resolved cell-scale simulations. The WE approach runs an ensemble of parallel trajectories with assigned weights and uses a statistical resampling strategy of replicating and pruning trajectories to focus computational effort on difficult-to-sample regions. The method can also generate unbiased estimates of non-equilibrium and equilibrium observables, sometimes with significantly less aggregate computing time than would be possible using standard parallelization. Here, we use WE to orchestrate particle-based kinetic Monte Carlo simulations, which include spatial geometry (e.g., of organelles, plasma membrane) and biochemical interactions among mobile molecular species. We study a series of models exhibiting spatial, temporal and biochemical complexity and show that although WE has important limitations, it can achieve performance significantly exceeding standard parallel simulation—by orders of magnitude for some observables

Extreme rainstorms drive exceptional organic carbon export from forested humid-tropical rivers in Puerto Rico

Extreme rainfall events in the humid-tropical Luquillo Mountains, Puerto Rico export the bulk of suspended sediment and particulate organic carbon. Using 25 years of river carbon and suspended sediment data, which targeted hurricanes and other large rainstorms, we estimated biogenic particulate organic carbon yields of 65 ± 16 tC km(−2) yr(−1) for the Icacos and 17.7 ± 5.1 tC km(−2) yr(−1) for the Mameyes rivers. These granitic and volcaniclastic catchments function as substantial atmospheric carbon-dioxide sinks, largely through export of river biogenic particulate organic carbon during extreme rainstorms. Compared to other regions, these high biogenic particulate organic carbon yields are accompanied by lower suspended sediment yields. Accordingly, particulate organic carbon export from these catchments is underpredicted by previous yield relationships, which are derived mainly from catchments with easily erodible sedimentary rocks. Therefore, rivers that drain petrogenic-carbon-poor bedrock require separate accounting to estimate their contributions to the geological carbon cycle

Challenges to the development of antigen-specific breast cancer vaccines

Continued progress in the development of antigen-specific breast cancer vaccines depends on the identification of appropriate target antigens, the establishment of effective immunization strategies, and the ability to circumvent immune escape mechanisms. Methods such as T cell epitope cloning and serological expression cloning (SEREX) have led to the identification of a number target antigens expressed in breast cancer. Improved immunization strategies, such as using dendritic cells to present tumor-associated antigens to T lymphocytes, have been shown to induce antigen-specific T cell responses in vivo and, in some cases, objective clinical responses. An outcome of successful tumor immunity is the evolution of antigen-loss tumor variants. The development of a polyvalent breast cancer vaccine, directed against a panel of tumor-associated antigens, may counteract this form of immune escape