Epigenetic heterogeneity within a tumour can play an important role in tumour evolution and the emergence of resistance to treatment. It is increasingly recognised that the study of DNA methylation (DNAm) patterns along the genome – so-called ‘epialleles’ – offers greater insight into epigenetic dynamics than conventional analyses which examine DNAm marks individually.We have developed a Bayesian model to infer which epialleles are present in multiple regions of the same tumour. We apply our method to reduced representation bisulfite sequencing (RRBS) data from multiple regions of one lung cancer tumour and a matched normal sample. The model borrows information from all tumour regions to leverage greater statistical power. The total number of epialleles, the epiallele DNAm patterns, and a noise hyperparameter are all automatically inferred from the data. Uncertainty as to which epiallele an observed sequencing read originated from is explicitly incorporated by marginalising over the appropriate posterior densities. The degree to which tumour samples are contaminated with normal tissue can be estimated and corrected for. By tracing the distribution of epialleles throughout the tumour we can infer the phylogenetic history of the tumour, identify epialleles that differ between normal and cancer tissue, and define a measure of global epigenetic disorder.Detection and comparison of epialleles within multiple tumour regions enables phylogenetic analyses, identification of differentially expressed epialleles, and provides a measure of epigenetic heterogeneity. R code is available at github.com/james-e-barrett.The online version of this article (doi:10.1186/s12859-017-1753-2) contains supplementary material, which is available to authorized users. Epigenetic variability allows greater phenotypic diversity and plasticity within a population of genetically similar cells. Epigenetic diversity within a tumour provides a mechanism for clonal evolution and the emergence of resistance to therapy . PersistEpigenetic modifications play an important role in the regulation of gene expression. One of the most common types is DNA methylation (DNAm) — where a methyl group is added to the fifth carbon of cytosine. We will focus on DNAm in the canonical CpG context where cytosine (C) is followed by guanine (G). High levels of DNAm in promoter regions are associated with suppressed gene expression whereas increased methylation in gene body regions tends to have the opposite effect .Reduced representation bisulfite sequencing (RRBS) is a sequencing technique that measures DNAm . The expd CpG sites on one read then there are 2d possible methylation patterns, which are called epialleles . Supposing wi=q we can therefore write Let X= and w= as well as the hyperparameter ε and the number of epialleles Q from the observed data Y=. Using Bayes’ theorem the posterior over the unknown quantities is The epialleles are analogous to latent variables in a latent variable model. Our goal is to infer the quantities where the likelihood is δxy=1 if x=y and δxy=0 otherwise. The marginal density X and w. We will use maximum entropy priors which are uniform densities over the 2Qd possible epiallele configurations X and QN possible values of w.The delta function is defined by X,ε, and Q, the maximum a posteriori (MAP) estimate for w is given by attributing each read yi to the epiallele that is most similar to it. That is, For fixed xqμ for fixed w,ε and Q. Let N1 denote the total number of methylated CpGs at site μ in observed reads that have been attributed to epiallele q. That is, wi=q. Similarly, N0 is the total number of unmethylated CpGs at site μ in reads stemming from epiallele q. It is straightforward to show that the MAP estimate is Next we wish to obtain the MAP estimate for matches at a given locus as mismatches as ε is An example is given in Fig. mentclass2pt{minimyiμ may be missing and these are handled by simply omitting them from sums and products over i and μ.which is simply the proportion of observed CpGs at that locus that differ from the underlying epialleles. Some values of w∗ and X∗ are independent of ε. Given a set of observed data Y the first task is to determine optimal values for w and X. This is done according to the following algorithm: w by using hierarchical clustering to group the observed reads Y into Q groups. The hamming distance (the proportion of CpGs that differ between two sequencing reads) is used as a distance measure.Initialise X according to .Repeat steps 2 and 3 until Note that the MAP estimates Denote the final parameter values as p(Y|Q) could be used to compare models with different values of Q. In practice, however, p(Y|Q) is analytically intractable. Instead we use the Akaike information criterion (AIC)  is the proportion of observed tissue that comes from the tumour (the sample ‘purity’), and t and n are the epiallele distributions in the tumour and normal tissues respectively (at the particular locus in question). For example, if we infer n= and t= then for a purity of ρ=0.8 we would expect to observe ϕ=. We can estimate ϕ and n from the observed data at a particular locus. Estimation of both ρ and t requires solving the where tions in  for \docq sums over all of the epialleles inferred at this locus and ξ will take different values at different loci. We can loosely interpret ξ as the proportion of reads unattributable to normal tissue, and in the example above ξ=0.4. If we substitute . For every value of the parameters results were averaged over 100 simulations.Simulations of a single locus were performed to study what effect the number of CpGs, N=100 and d=6 gave a success rate of approximately 95% at a 5% noise level. These values were used to guide the selection of viable loci in subsequent analyses of experimental data. Dropping to N=50 gave a performance of just over 90% . The mean noise level was inferred as 1.1%. This suggests that the majority of methylation is correctly identified as corresponding to a methylated profile and therefore our method is capable of resolving a distinct low frequency cellular subpopulation.The Bayesian model was used to detect the presence of epialleles at each loci. We found that 5.2% of methylated CpGs were attributed to methylated epialleles  along with one matched normal tissue sample. These tissue samples were acquired as part of the larger TRACERx study . The rawIn order to compare the distribution of epialleles within different tumour samples it was necessary to identify all of the loci which occurred in two or more samples. That is, the loci themselves must ‘match up’ between tumour samples in order for a comparison to be made . Only loci with a median read depth ≥100 across normal and tumour tissue samples and six or more CpGs were considered. A total of 39,940 loci were analysed out of which 73% were found to contain a single epiallele, 13% contained two, 7% contained three, 4% contained four, and 3% had five our more (up to a maximum of thirteen).At each locus the Bayesian model is used to infer the epialleles present, the total number of epialleles, and which epialleles each observed sequence came from. An example locus with seven CpGs from chromosome one is presented in Fig. In order to understand shifts in epiallele frequency at a global level we plotted a heatmap of the top 200 most variable epialleles in Fig. ξ within tumour region 2 is plotted in Fig. ρ=0.535. Plots for all tumour regions are given in Additional file The sample purities were estimated as described in the methods section. An example of the empirical density of Phylogenetic trees were generated as described in the methods section. The trees for both contaminated and decontaminated samples are plotted in Fig. ϕs quantifies how disordered or heterogeneous each locus is in sample s. The epiallele entropy at a given locus is defined as The Shannon entropy provides a measure of how disordered a random variable is. In particular, the entropy of the epiallele distribution d is the number of CpGs at that locus and ϕ is the inferred probability distribution of epialleles . In Fig. where Analysis of epialleles allows for a deeper interrogation of the underlying biology than a pointwise examination of CpG methylation states. Tracing the patterns of DNA methylation along epialleles allows one to tease apart different cellular subpopulations and acquire a richer quantification of heterogeneity and disorder that would not be possible by looking at individual CpG sites. In particular, the distribution of epialleles throughout a tumour can shed light on the evolutionary history of the tumour.Our analysis protocol specifically pools sequencing reads from multiple tissue samples in order to leverage greater statistical power in epiallele detection. Our Bayesian approach will automatically detect the number of epialleles present, and infer what the methylation pattern of those epialleles are. One strength of the Bayesian approach is that it provides a framework for averaging over uncertainty in model parameters. If there is uncertainty as to which epiallele an observed sequencing read may have originated from, then a natural solution is to average over that uncertainty by marginalising over the appropriate posterior distribution. In addition to the above features our model can easily accommodate missing data and can handle an arbitrary sequencing depth and number of CpG sites per locus. Furthermore, by comparing the distribution of epialleles within normal and tumour tissue samples it is possible to estimate the purity of each sample and to subsequently decontaminate them. Methylation levels at each CpG site can be extracted from the decontaminated samples and subsequently used in standard analysis pipelines.In future work it may be interesting to compare the distribution of loci that are located close to each other. Although it is not possible to phase reads between disjoint loci the number of epialleles and the entropy may be correlated between close loci.Tracking the presence or absence of epialleles throughout the tumour opens up an additional layer of complexity beyond that of conventional methylation analyses. Pointwise methylation analysis protocols typically average over sequencing reads – to ‘call’ the methylation status at single CpGs – that potentially come from a diverse and heterogenous population of cells. Detecting which epialleles are present allows one to distinguish between these cellular subpopulations and identify tumour subclones that are defined by distinct epialleles. One can then probe changes between normal and cancerous tissue at a finer resolution. As we have demonstrated here, studying epiallele frequencies in different parts of the tumour reveals the evolutionary history of the tumour and allows a phylogenetic tree to be constructed. A measure of disorder or heterogeneity inside the tumour can be obtained through measures such as Shannon’s entropy.Understanding tumour heterogeneity is an important step towards understanding why certain therapies fail and why resistance to treatment can emerge. Subclonal populations of treatment-resistant cells can persist after treatment even if they only account for a small fraction of the original tumour. Epigenetic diversity within the tumour may play an important role in tumour evolution alongside genetic variability. It is increasingly recognised that for DNA methylation sequencing data studying the patterns of methylation along the genome – ‘epialleles’ – can provide greater insight into the underlying dynamics of epigenetic regulation than a conventional pointwise analysis.We have exploited this opportunity to study the distribution of epialleles throughout a tumour by performing reduced representation bisulfite sequencing on seven regions of the same tumour and one matched normal tissue sample. Our new Bayesian approach infers which epialleles are present at a given locus. A comparison of the frequency of different epialleles across the tumour and normal tissue highlights changes between normal and cancerous tissue and allows the extraction of a phylogenetic history. The concept of entropy can be used as a measure of global disorder within the tumour. Our method can be applied more generally to any type of DNAm sequencing data.Future work will focus on larger scale studies of multiple patients with multi-region tumour sampling in order to probe for systematic alterations in epiallele expression between normal and cancerous tissue. Previously, measures of epigenetic disorder were found to be associated with clinical outcome and it will be interesting to see if quantification of disorder at the level of epialleles will provide a more refined measure of tumour aggressiveness. Ultimately, it is hoped that a clearer elucidation of epigenetic dynamics will complement our genetic knowledge of cancer and provide a more comprehensive understanding of the disease.


Arterial spin-labelling (ASL) MRI uses intrinsic blood water to quantify the cerebral blood flow (CBF), removing the need for the injection of a gadolinium-based contrast agent used for conventional perfusion imaging such as dynamic susceptibility contrast (DSC). Owing to the non-invasive nature of the technique, ASL is an attractive option for use in paediatric patients. This work compared DSC and multi-timepoint ASL measures of CBF in paediatric brain tumours.n = 23; 20 low-grade tumours and 3 high-grade tumours) had DSC and multi-timepoint ASL with and without vascular crushers (VC). VC removes the contribution from larger vessel blood flow. Mean perfusion metrics were extracted from control and T1-enhanced tumour regions of interest (ROIs): arterial arrival time (AAT) and CBF from the ASL images with and without VC, relative cerebral blood flow (rCBF), relative cerebral blood volume, delay time (DT) and mean transit time (MTT) from the DSC images.Patients  and CBF and rCBF  in control ROIs for ASL-noVC. No significant correlations existed between DSC and ASL measures in the tumour region. Significant differences between control and tumour ROI were found for MTT (p < 0.001) and rCBF (p < 0.005) measures.Significant correlations existed for: AAT and DT (Significant correlations between ASL-noVC and DSC measures in the normal brain suggest that DSC is most sensitive to macrovascular blood flow. The absence of significant correlations within the tumour ROI suggests that ASL is sensitive to different physiological mechanisms compared with DSC measures.ASL provides information which is comparable with that of DSC in healthy tissues, but appears to reflect a different physiology in tumour tissues. Central nervous system tumours are the most common group of solid tumours in childhood and comprise 20–25% of all childhood neoplasms. There are many different types with variable survival rates depending on the histology, biology, age and degree of spread. Although some types of brain tumours may be completely resected, many cannot be completely removed without serious morbidity. In addition to surgery, chemotherapy and radiotherapy are also used as adjuvant treatments. Survivors of central nervous system tumours are frequently susceptible to severe and sometimes devastating neuropsychological, neurological and other pathologies, which may be related to factors such as the tumour location and therapy used. Brain imaging is fundamental to the management of brain tumours, and there is a clear need for the development of improved non-invasive measures of tumour characteristics. The potential benefits of using a non-invasive method to monitor paediatric brain tumour (PBT) progression and response to treatment are reduced distress to patients and increased frequency of monitoring, which may improve treatment plans and possibly lead to better patient outcomes.1 Currently, dynamic susceptibility contrast (DSC) MRI is used clinically, providing quantitative maps of relative cerebral blood flow (rCBF), relative cerebral blood volume (rCBV) and mean transit time (MTT). This method allows for the identification of areas of contrast agent leakage within a tumour and can differentiate between different tissue characteristics such as cystic regions. Whilst it benefits from a high signal-to-noise ratio, DSC does suffer from some limitations such as absolute quantification of blood flow. Accurate quantification of DSC measures depends both on the method of contrast administration and the assumption that the tracer remains intravascular, which may be invalid in tumours with a compromised blood–brain barrier.2MRI has long been established as a useful tool for the assessment of PBT.3 Repeated injections of gadolinium contrast agents are contraindicated in children, and gadolinium agents should not be used at all in very young infants and in children with renal impairment, owing to the risk of nephrogenic systemic fibrosis.2 In a research setting, a technique that avoids the distress caused by i.v. injections is much more acceptable to children and parents. Taking these factors into consideration, there is a real need for investigating alternative non-invasive measures of blood flow in PBT.An additional complication in DSC blood flow quantification is the requirement of an arterial input function (AIF), usually chosen from a large vessel. Owing to the differences in blood flow dynamics between adult and paediatric patients, modelling the AIF in a paediatric population can be problematic.4 has seen significant technical developments in the last few years and a push for clinical use.5 The use of ASL in a paediatric population is now starting to gain momentum.6 Sequence modifications, such as a Look–Locker readout allowing multi-timepoint measurements,7 provide an opportunity for more accurate quantification, taking into account different haemodynamics that may be present in children and in tumours in particular.8 Multi-timepoint ASL allows us to quantify arterial arrival time (AAT) in addition to cerebral blood flow (CBF). This may be important in the case of neuropathologies such as stroke9 and PBT,8 where pathology may lead to blood arrival delays. It is also possible to increase the sensitivity of ASL to the microvasculature through the use of magnetic field gradients which cause dephasing of fast-flowing blood [so-called vascular crushers (VC)].10 VC reduce the contribution of signal from the large vessels and so allow a more accurate measurement of true capillary blood flow, which is more closely related to tissue metabolism.Arterial spin labelling (ASL) is an MR technique that allows for the non-invasive absolute quantification of CBF, by using blood water as an endogenous tracer. A key benefit of this technique is that it is not reliant on the acquisition of an appropriate AIF, and quantification is much less sensitive to blood–brain barrier (BBB) leakage. This technique, predominately used in research,This work aimed to compare output measures from DSC to ASL, with and without VC in PBTs. The first aim was to compare the sensitivity of each measure to the presence of tumour tissue. Further, we hypothesized that corresponding DSC and ASL measurements would be correlated; specifically: (i) AAT and Delay time (DT) would be significantly correlated in the tumour tissue and healthy tissue, (ii) CBF and rCBF would be significantly correlated in the tumour tissue and healthy tissue and (iii) the correlations would be stronger for ASL measures without VC (i.e. noVC), which are more akin to DSC measures. It is also expected that ASL with VC would provide qualitatively clearer images of altered tumour blood flow and AAT, without contamination from large vessels. This work was designed to provide the first step towards establishing multi-timepoint ASL as a possible clinical tool in PBTs.All patient data came from the Alder Hey Children's Hospital, Liverpool. Data were collected from a total of 23 paediatric patients  with brain tumours on first presentation and 1 intraoperative case as outlined in ® TX MR scanner . ASL sequences were added to the standard clinical MR protocol. Scans were carried out in the following order: T1 weighted (without gadolinium), ASL without VC, ASL with VC, DSC, T1 weighted acquired post-gadolinium  injection.All imaging was carried out on a 3 T Philips AchievaT1 weighted [three-dimensional fast low angle shot (FLASH)] scans both pre- and post-gadolinium injection were acquired with the following parameters: repetition time (TR): 8.3 ms, echo time (TE): 3.8 ms, 1-mm isotropic voxels, field of view (FOV) of 240 mm and acquisition duration approximately 5 min. Post-gadolinium T1 weighted images were used to identify enhancing tumour regions.T2* weighted echoplanar imaging DSC sequence was used to sample the “first pass” of the contrast agent through the brain vasculature. Sequence parameters were: TR: 1694 ms, TE: 40 ms, voxel size 1.75 × 1.75 × 4 mm, FOV 224 mm, 25 contiguous slices and 40 dynamics. A dynamic pump injection of 1 ml/5 kg with a rate of infusion of 3 ml s−1 was administered on the 10th dynamic of the DSC sequence. A loading dose of 1-ml gadolinium was administered prior to the acquisition.A 11 with a Look–Locker readout7 was used with the following parameters: 3 × 3 × 6-mm voxels; FOV 240 mm; 9 slices with 0.6-mm gap; 8 readout pulses at 300, 670, 1040, 1410, 1780, 2150, 2520 and 2890 ms; TR: 4 s, TE 12 ms; flip angle 40o; 30 pairs of label and control images; total acquisition time 4 min. A second set of images was collected with the addition of vascular crushing gradients with velocity encoding (VENC) level of 5 cm s−1 with the same scanning parameters, except for an increase in the TE to 24 ms. Since full-brain coverage was not possible, slices were positioned to encompass the tumour.A spin tagging with alternating radiofrequency labelling scheme (STAR)www.mathworks.com) routines. Raw ASL images were qualitatively checked for motion and artefacts before being processed. Control and label images were subtracted and averaged to provide difference images at each timepoint. A single blood compartment model,12 adapted for the Look–Locker readout,13 was fit to the averaged images on a voxel-by-voxel basis, producing maps of CBF and AAT (without vascular crushing) and CBF with vascular crushing (CBFVC) and AAT with vascular crushing (AATVC) (with vascular crushing). This model assumes that labelled water remains in the blood and that no labelled water leaves the voxel, an approach that has been shown to be reasonably accurate.12 With these assumptions, the signal in the difference ASL image (control image − label image), ΔM, can be described by:R1 is the apparent longitudinal relaxation rate of blood during the Look–Locker readout and f is the CBF. For STAR labelling, the magnetization of the arterial blood, ma, is given by:ma = 0 at all other times. Here, ta is the arrival time and τ is the bolus width. ma0 is the equilibrium magnetization of arterial blood, α is the inversion efficiency  and R1b is the true R1 of blood. According to Ref. R1 = R1b − ln(cosθ)/TI2, where θ is the flip angle and TI2 is the spacing of the Look–Locker readout. The solution for ΔM is:R1 − R1b. The mean difference signal ΔM was fit on a voxel-wise basis to f (CBF) and ta (AAT), with fixed values for τ = 1000 ms,14T1b = 1600 ms15 (note R1b =1/T1b) and ma0. ma0 was estimated from a whole-brain estimate of m0 (found by fitting the ASL control images to a saturation recovery curve) divided by the blood–brain partition coefficient λ = 0.9.16ASL analysis was carried out using in-house MATLAB . MIStar employs a delay- and dispersion-corrected singular value decomposition deconvolution method19 to create output maps of rCBF, rCBV, MTT and DT. An AIF was chosen manually in a vessel closest to the region of the tumour that would be the most ideal representation of the blood flow dynamics close to the tumour. The chosen AIF is convolved with the tissue contrast-enhancement signal curve, leading to an impulse response function curve. Aspects of the impulse response function curve allow for the calculation of the cerebral blood volume (CBV) (area under the curve), CBF (curve peak) and MTT (CBV/CBF). DT measures were derived from the delay correction as applied by MIStar, with areas of no blood flow deemed to have the largest DT and MTT. As absolute quantification of DSC CBF measures are not possible,21 measures are reported as rCBF and rCBV.DSC analyses were carried out using MIStarT1 weighted images by an experienced paediatric neuroradiologist using MRICRO (www.mricro.com). A separate control ROI with the same size as the enhancing tumour ROI was also created for each patient. These control ROIs were ideally located in the contralateral hemisphere for non-midline tumours. When possible, control regions for midline tumours were chosen within the same structure, but excluding the tumour. Otherwise, ROIs were placed in “healthy” tissue areas close to the tumour area. Registration of the output parameter maps from both the DSC and ASL analyses to the T1 weighted image was carried out using the SPM co-registration toolbox (www.fil.ion.ucl.ac.uk/spm), and mean signals from the ROIs were extracted.Tumour region of interest (ROI) volume masks were created on the enhancing tissue regions of the post-gadolinium T1 of blood and equilibrium magnetization of blood and for DSC, differences in tracer concentration and its impact on the relaxivity and differences in small- and large-vessel haematocrit levels. Normalized values, i.e. tumour blood flow in relation to global blood flow, should show better agreement. Hence, normalized values were also calculated for the purpose of correlation tests, using a “global” value taken from the entire brain region covered by ASL acquisition, excluding the tumour region  lower within the tumour region than within the control region; however, rCBV did not show a significant difference.No significant differences were noted from the ASL measures (both with and without vascular crushing) in the tumour region when compared with the control region. When considering the measures derived from DSC, MTT and rCBF were both significantly , in addition to the normalized measures of DSC rCBF and ASL CBF  . In general, therefore, measurements are correlated in the control region but not in the tumour region, suggesting that the tumour pathology may be impacting the accuracy of modelling of the different MR measurements.Data from 20 patients were used to assess the significance of correlations between the perfusion metrics. Data from the single intraoperative example and the remaining three patients were not included, as they were found to have tumour blood flow values >±3 standard deviation from the mean and thus were found to be driving the correlations. In the tumour region, there is no significant correlation between any of the DSC and ASL measurements. This is in keeping with the descriptive statistics , which s = 0.02) . Correla22 or blood pooling. The smaller region of elevated blood flow on the vascular-crushed ASL CBF image  tissue, but not for the CBV measures. DSC DT measures were not different between the tumour and healthy tissue, and nor were any of the ASL output measures. It must be concluded therefore that DSC is more sensitive to the tumour tissue than ASL. The sensitivity of course assumes that the perfusion metrics change in the same way across this group of tumours. If, for example, true CBF goes up in some tumours and down in others, then significant changes across the group will be lost. Visually, it was noted that ASL maps showed a difference in the tumour region compared with the surrounding tissue in the majority of cases. There were, however, significant correlations between DSC and ASL output measures within the control region but not in the tumour region. The significant differences observed between tumour and control regions with DSC could be due to a number of reasons such as: (i) DSC measures are contaminated by “leaky” vasculature present in the tumour regions, thus impacting the overall measures and contributing to differences; (ii) AIF choice to model the perfusion profile of the contrast agent was acquired from healthy tissue regions close to the tumour and is not representative of the perfusion profile within the tissue. Therefore, AIF choice may be impacting the overall modelling of the DSC signal change in the tumour region, which is reflected by the significant differences; and finally, (iii) DSC could simply be more sensitive to the true perfusion differences within the tumour tissue.23 and specifically in brain tumours.24 The strong correlations between CBF as measured with ASL and DSC within the control ROI  and Alder Hey Children's Charity.


New York Times about her choice to undergo preventive surgery. In her two op-eds, she explained that − as a carrier of the BRCA1 gene mutation − preventive surgery was the best way to lower her heightened risk of developing breast and ovarian cancer. By applying a digital methods approach to BRCA-related tweets from 2013 and 2015, before, during, and after the exposure of Jolie’s story, this study maps and interprets Twitter discursive dynamics at two time points of the BRCA Twitter stream. Findings show an evolution in curation and framing dynamics occurring between 2013 and 2015, with individual patient advocates replacing advocacy organizations as top curators of BRCA content and coming to prominence as providers of specialist illness narratives. These results suggest that between 2013 and 2015, Twitter went from functioning primarily as an organization-centered news reporting mechanism, to working as a crowdsourced specialist awareness system. This article advances a twofold contribution. First, it points at Twitter’s fluid functionality for an issue public and suggests that by looking at the life story—rather than at a single time point—of an issue-based Twitter stream, we can track the evolution of power roles underlying discursive practices and better interpret the emergence of non-elite actors in the public arena. Second, the study provides evidence of the rise of activist cultures that rely on fluid, non-elite, collective, and individual social media engagement.In May 2013 and March 2015, actress Angelina Jolie wrote in the  New York Times opinion piece to explain her choice to undergo prophylactic double mastectomy. As a carrier of the rare BRCA1 gene mutation—Jolie explained—preventive surgery had lowered her heightened risk of developing breast cancer.1 Following the op-ed, the story was picked up by news and entertainment media in both Western and Asian periodicals, with the celebrity’s picture appearing on the covers of People and Time magazines and the story remaining of news value for months —that is, one that allows users to incorporate information and knowledge deriving from varied sources, challenging traditional protocols of public communication. In other words, the idea of a Twitter-generated “awareness system” backgrounds questions of information reliability while foregrounding issues of knowledge inclusivity. In fact, Twitter does not necessarily enhance intentionally collaborative processes  the curation of content produced and shared in discursive streams and (2) the construction of meaning around the issues at the core of these streams.Twitter discursive work expresses itself in the constant live-streaming of 140-character posts where conversational markers can facilitate networking dynamics among users. Retweeting implies exposing someone else’s tweet to a wider public; via is a way to pay tribute to a source and @ is a conversational marker that allows users to mention or direct posts to other users, sustaining “a high level of interactivity and engagement” , p. 140.Drawing upon work by In an issue-based Twitter stream—or the collection of tweets relevant to a well-defined issue—while broadcasters extend the life-span of successful Twitter content, gatekeepers are Twitter users crowdsourced to prominence via the use of conversational markers. In other words, Twitter users whose messages are most frequently retweeted or shared with the via conversational marker or whose handle is most frequently mentioned via the @ marker become the gatekeepers of an issue-based Twitter stream. As Hence, the investigation of platform-bound curation practices provides insight into the power relations underlying discursive work on Twitter. However, to understand the construction of meaning in issue-based Twitter streams, we need to focus on the actual content produced, shared, and/or dismissed via these curation practices.While users differently participate in Twitter’s awareness system, this system itself develops around the emergence of dominant narratives driven by successful hashtags. In fact, “In scenarios where communities converge on a selected hashtag to represent an issue or topic, such hashtags aid in the creation of an ad hoc issue public, collating tweets along a specific, topical dimension” , p. 143.3Drawing upon Overall, research applying frame theory to the analysis of issue-based Twitter streams focuses on the discursive dimension of meaning construction, overlooking tweeters’ “attachment” to the issues they publicize and to Twitter itself . In otheBy drawing upon findings on curation and framing dynamics, previous research has described Twitter as a platform enhancing the emergence of traditionally marginalized voices or non-elite actors and original representations of reality . HoweverThe BRCA Twitter stream offers a significant case study to integrate temporality in the investigation of power dynamics in Twitter discursive practices. First, contemporary health communication research has highlighted the development of new active forms of patient engagement where patients—traditionally non-elite actors—often directly engage in the production of health knowledge . A healtRQ1. How do actor power relations  develop through different crucial points in the life story of an issue-based Twitter stream?RQ2. How do prominent frames develop through different crucial points in the life story of an issue-based Twitter stream?RQ3. Do shifts in power relations and meaning construction at different crucial points in the life story of an issue-based Twitter stream suggest changing patterns in Twitter’s platform functionality  for an issue public?4 Hence, this study investigates two Twitter archives—from 2013 and 2015—populated by 25,400 and 18,909 tweets, respectively.To scrape Twitter data relevant to the BRCA gene mutation around the publication of Jolie’s op-eds, I focused on tweets posted over two sample periods: 14 April–13 June 2013 and 24 February–23 April 2015, that is, each starting 1 month before the publication of each Jolie’s op-ed and ending 1 month after it. Using the Discovertext Sifter application—which relies on GNIP service for firehose access to Twitter—I launched two historical searches based on the following queries: “brca since:14-04-2013 until:13/06/2013” and “brca since: 24-02-2015 until:23-04-2015.” Non-BRCA-related tweets and tweets in a language different from English were then excluded from the results.To study broadcasting and gatekeeping dynamics (RQ1), I examined the use of Twitter conversational markers, with social network analysis techniques being employed to identify prominent actors. In particular, measures of outdegree and indegree centrality  were useTo investigate frame articulations (RQ2), I focused on hashtag co-occurrence networks. In hashtag co-occurrence networks, nodes stand for hashtags and undirected edges represent co-occurrences: an undirected edge between two nodes indicates that those nodes’ corresponding hashtags co-occurred in at least one tweet in the sample. I then used degree centrality  measuresFinally, to provide a comprehensive comparison of discursive practices and platform functionality for the BRCA issue public at the two time points being investigated (RQ3), the analytical phases discussed above were replicated over three time periods within each archive: (1) up until the day before the op-ed publication, (2) from the day of the op-ed publication until the last day with daily number of tweets higher than any day before the publication, and (3) in the remaining time in the sample period.Given its socio-technical infrastructure, Twitter hosts “intense curation practices” , p. 245 5Even among broadcasters prominent across two of the three periods (underlined), advocacy organizations  played a primary role. But what was the result of these broadcasting dynamics, that is, which nodes in the conversational network were broadcasted to gatekeeping prominence?Before the public announcement, Breast Cancer Action, Force and Myriad Genetics acted as prominent gatekeepers, together with a few individual Twitter users. Myriad Genetics’ gatekeeping prominence before the public announcement is directly linked to events happening on the ground in relation to the ongoing judicial case “Association for Molecular Pathology versus Myriad Genetics,” where ACLU itself served as counsel for the plaintiffs. The case challenged the legitimacy of Myriad Genetics’ human gene patents and was specifically relevant to the BRCA Twitter stream as human gene patents increased the price of BRCA genetic testing. In fact, Myriad Genetics played a prominent role as a target of tweets campaigning against human gene patenting.In the conversational network developing during the first 8 days after the publication of Jolie’s op-ed  of BRCA-related Twitter content. The BRCA stream was then mainly sourced via “organizationally enabled connective action” , or via 6 and hereditary cancer . Two out of the three broadcasters recurring in two of the three periods (underlined) were also breast cancer individual advocates .Data from the 2015 sample period indicate that in a 2-year span curation practices within the BRCA Twitter stream changed significantly. The three columns of Dynamics in the conversational network also varied compared to 2013 . The graIn fact, Before the exposure of Jolie’s story, several individual patient advocates  played top gatekeeping roles along with only two advocacy organizations . Facebook was among the top mentioned sources, primarily due to a high number of tweets campaigning against the removal of mastectomy photos on BRCA Facebook pages.New York Times and BBC) temporarily reached gatekeeping prominence  played an even stronger gatekeeping role than before the publication of Jolie’s piece, with Facebook re-emerging as the target of campaigning against the removal of mastectomy photos on BRCA Facebook pages.individual actors  to engage in content curation processes that 2 years earlier were controlled by non-elite collective actors . In other words, these findings suggest that not only can Twitter broadcast networks open up space for minorities’ viewpoints —was an event hashtag used during the Human gene patent rally of 15 April 2013. The rally, organized by Breast Cancer Action, took place on the steps of the US Supreme Court while arguments against gene patents were being presented to the Court . Hashtag7 and of prophylactic mastectomy as a preventive measure. Finally, Jolie’s story enhanced the emergence of dedicated Twitter chats .Jolie’s announcement had short-term effects, the most evident of which being a sudden shift toward Jolie’s BRCA-related narrative, with the foregrounding of the BRCA1 gene mutation over the BRCA2 gene mutationIn the remaining period, top hashtag pairs reframed the BRCA issue stream around genes, gene patents, and the trial against Myriad Genetics like in the period prior to the publication of Jolie’s editorial, indicating that the Angelina effect on framing dynamics was extremely short-termed.These results show that across the publication of Jolie’s first op-ed, the BRCA Twitter stream developed around both content-based frames descriptive of real-world events on the ground and more volatile and short-lived content-based frames emerging with Jolie’s story. Hence, Twitter functioned primarily as a “news reporting mechanism” , hostingLooking at both In the short term, Jolie’s announcement—like in 2013—mainly introduced frame articulations directly linked to Jolie’s BRCA narrative. First, it drew attention to the hereditary nature of the BRCA gene mutation via the use of #BRCA with #HCChat—a Twitter chat on hereditary cancer—and #hereditarycancer. Second, it foregrounded inspirational hashtags like #knowledgeispower. Third, it drew attention to ovarian cancer–related narratives via hashtags like #HBOC—tagging hereditary breast and ovarian cancer tweets—and #gyncsm, a Twitter chat for individuals impacted by gynecological cancers.Finally, dynamics similar to those described for the period before the publication of Jolie’s op-ed are evident in the hashtag network developing toward the end of the 2015 sample period. There, #mastectomy, #breastcancer, and #BCSM are frequently associated with #BRCA, and Lynch Syndrome is again linked to the BRCA gene mutation. In this hashtag network, #facebook also gains visibility due to the ongoing campaign against Facebook’s removal of mastectomy photos described in the analysis of curation dynamics.Overall, these framing dynamics suggest that while in April–June 2013 the BRCA Twitter stream primarily functioned as a news reporting mechanism centered around content-based frames, in February–April 2015, it worked more as an “awareness system”  where naEmpirical work interested in the impact of social media usage on discursive practices in general—and public sphere dynamics in particular—has drawn attention to the way social media’s socio-technical infrastructures tend to destabilize traditional power roles in the construction of meaning around issues of public interest. When it comes to Twitter, several studies have investigated one key time point in the life story of a Twitter stream, unveiling the platform’s democratizing potential in allowing non-elite actors to come to prominence in both the selection of information sources and the construction of meaning around specific issues. What is generally missing in previous research is a focus on the temporal dimension of discursive practices, that is, how Twitter functionality for an issue public may differ at different time points in the life story of an issue-based Twitter stream.Drawing upon recent research on Twitter discursive practices, this article investigated curation and framing dynamics at two similar but temporarily distant time points in the life story of the BRCA Twitter stream. The ultimate goal was to potentially unveil changes in platform functionality, that is, changes in the way Twitter usage allowed or supported the coming to prominence of non-elite actors described in previous research .collective actors  to non-elite individual actors , that is, to minorities within minorities.This study’s findings on broadcasting and gatekeeping dynamics (RQ1) showed that curation patterns at any time point in an issue-based Twitter stream reflect transient power structures. In the BRCA Twitter stream, between 2013 and 2015, individual patient advocates supplanted advocacy organizations in top broadcasting and gatekeeping roles, with crowd-enabled replacing organizationally enabled connective action . In otheFindings also show that frame articulation (RQ2) can highly vary at different time points of a Twitter stream. In 2013, the BRCA gene mutation was primarily discussed via content-based frames relevant to Myriad Genetics’ gene patents controversy. By February 2015, the BRCA stream had developed specialist narratives, not only foregrounding breast cancer themes hardly present in mainstream representations of breast cancer  but also drawing links with similar but far less known hereditary cancer conditions . This highlights the need to investigate issue involvement not only in terms of its discursive articulations  but also as situated in socio-technical spaces where meaning is linked to actors , technology , and events  .New York Times opinion pieces. In both occasions, the “Angelina effect” added a “hybrid”  for non-elites within an issue public is highly fluid. For the BRCA public, for instance, in April–June 2013, the platform worked primarily as an organization-centered “news reporting mechanism” , focusinpublic manifestation of these personalized forms of engagement. Hence, in a 2-year span, as a result of the combination of non-platform bound cultural dynamics and platform-specific discursive practices, the public voice of individual patient advocates in the BRCA Twitter stream overcame that of traditional collective advocacy actors.These findings suggest that the effects of new socio-technical infrastructures on the expression of non-elite actors combine with wider cultural dynamics, that is, the coming to prominence on social media of non-elite actors may vary according to—non-platform bound—cultural dynamics. In the case of the BRCA issue public, for instance, rising public awareness around BRCA-related topics—most likely also linked to the “Angelina effect”—led to the development of personalized forms of engagement with these topics. The contemporary emergence of “active patients” described in previous research , p. 1655This article points at Twitter’s fluid functionality and suggests that by looking at the life story—rather than at a single time point—of an issue-based Twitter stream, we can better understand the contribution of new socio-technical infrastructures as embedded in wider cultural dynamics. In particular, we can map the development of power roles in discursive practices and understand the dynamics underlying the emergence of non-elite actors in the public arena. Finally, this article provides evidence of the rise of activist cultures that rely on fluid, non-elite, collective, and individual social media engagement.


The byline and affiliation line of our article should appear as shown above. The following should also be added to the end of Acknowledgments: “M.A.J. was supported by the BBSRC (grant BBI02542).”Volume 8, no. 2, e02311-16, 2017,


A novel method, which was called a slope method, has been proposed to measure fluid density by the micro-cantilever sensing chip. The theoretical formulas of the slope method were discussed and established when the micro-cantilever sensing chip was under flexural and torsional vibrations. The slope was calculated based on the fitted curve between the excitation and output voltages of sensing chip under the nonresonant status. This measuring method need not sweep frequency to find the accurate resonant frequency. Therefore, the fluid density was measured easily based on the calculated slope. In addition, the micro-cantilver was drived by double sided excitation and free end excitation to oscillate under flexural and torsional vibrations, respectively. The corresponding experiments were carried out to measure the fluid density by the slope method. The measurement results were also analyzed when the sensing chip was under flexural and torsional nonresonant vibrations separately. The measurement accuracies under these vibrations were all better than 1.5%, and the density measuring sensitivity under torsional nonresonant vibration was about two times higher than that under flexural nonresonant vibration. An edge-supported vibrating plate was fabricated using MEMS technology [Vibration methods are widely used in online measurements of fluid density ,2,3. Micchnology  to measuchnology  and latechnology  and so ochnology . TherefoAt present, most MEMS vibrating sensors used to measure physical or biochemical quantities, work in resonance mode, such as when measuring fluid density via the resonant frequency shift ,17. TherIn this paper, a sensing chip for the measurement of fluid density with a micro-cantilever structure was designed and fabricated from monocrystalline silicon using MEMS technology. Au was sputtered to fabricate the metallic coil on the micro-cantilever as shown in l, w and d denote the length, width and thickness of the micro-cantilever, respectively, where l = 1500 μm, w = 2500 μm and d = 30 μm. The micro-cantilever has different vibrating modes under different excitations, such as flexural, torsional and lateral vibrations. This research was just concentrated on the flexural and torsional vibrations, which were excited in two different ways.In x axis. The flexural vibration of the micro-cantilever was generated for the sensing chip under this condition. This driving way is called free-end excitation in this research.As shown in z axis. This driving mode is called double sided excitation in this research.The torsional vibration of the micro-cantilever was excited by a torque as shown in Re of an oscillating cantilever is 2πfρw2/(4η), where η and ρ are viscosity and density of the fluid, w is the width and f is the resonant frequency of the cantilever. For high Re (Re >> 1), the viscous effect is negligible and the resonance frequency of the cantilever is primarily a function of fluid density and independent of fluid viscosity [As is known to all, the resonant frequency of a vibrating device immersed in a fluid will be influenced mainly by the fluid density, and the full width at half maximum (FWHM) of the device will be affected by the fluid viscosity , as showiscosity .Re was about 100 and far larger than 1. Therefore, the viscosity effect can be neglected for this sensing chip when the fluid viscosity is not very large (≤10 mPa·s). The experimental results in In this paper, the width of the proposed micro-cantilever was 2500 μm, and the p(l) and applied to the free end of the micro-cantilever. The deflection amplitude in the free end of micro-cantilever is directly proportional to the force p(l) because monocrystalline silicon is a linear elastic material.The cross section of the rectangular micro-cantilever in the fluid is shown in E is the Young modulus, J is moment of inertia, ρe is the equivalent density of the micro-cantilever in the fluid, A is the cross sectional area of the micro-cantilever. Because the cross section of the rectangular micro-cantilever is constant, Equation (1) can be expressed as:Without considering the effect of fluid viscosity, the differential equation of the micro-cantilever under flexural vibration in the fluid can be written as :(1)∂2∂xw(l) is the maximum deflection of micro-cantilever along y direction.The deflection of the stationary response on the free end of the micro-cantilever was presumed as:After Equation (4) was substituted into Equation (2):Ci (i = 1~6) is constant.After solving Equation (5), the general solution of the deflection on the free end of the micro-cantilever can be presented as follows:p1(l), the deflection amplitude of the free end of micro-cantilever is denoted by w1(l), and when the excitation force is p2(l), the deflection amplitude of its free end is changed to w2(l), and the following equation is obtained based on Equation (7):When the vibration force on the free end of a micro-cantilever changes, the vibration amplitude is also changed correspondingly. When the excitation force is defined as sρ is the density of micro-cantilever and fρ is the density of fluid, C7 is a constant.In Equation (9), U of the Wheatstone bridge, which is located on the fixed end of the micro-cantilever, has a linear relationship with the deflection amplitude of the free end of the micro-cantilever [V on the coil. An output voltage ntilever . FurtherTherefore:After substituting Equations (9)–(11) into Equation (8), we obtain the following function:m is applied to the micro-cantilever, it vibrates torsionally along the major axis (x) to generate a deflection angle ϕ.The torsional vibration sketch of the micro-cantilever was shown in G is the shear modulus of the micro-cantilever, and I is the polar moment of inertia about the major axis of rotation. The parameter K in Equation (13) is a torsional constant related to the cross-sectional area. For a rectangular cross section with width w and thickness d, K is given by [The vibration differential equation of the micro-cantilever in the fluid under torsional vibration could be written as :(13)GK∂given by :(14)K=1w > d. Equation (13) could be solved like Equation (1) in U of the Wheatstone bridge and the driving voltage V on the coil under torsional vibration can be expressed as:D1 and D2 are also constants.Equation (14) is an approximation based on the assumption that the cross section is a narrow rectangle with k) of the fitted curves that are obtained from the corresponding output voltages of the Wheatstone bridge and different driving voltages on the coil. Equations (12) and (15) have a similar form; their left parts are actually the slopes , which is called the slope method.Therefore, both Equations (12) and (15) can be simplified to demonstrate the relationship between the fluid density and slope An experimental system had been established as shown in U of the Wheatstone bridge when the sinusoidal AC voltage as the driving voltage V excited the metal coil at a constant frequency. The driving voltage V was provided by a 33220 A signal generator  and a constant current of 2 mA was provided by an ITECH IT6233B DC source  to power the Wheatstone bridge.A SR830 lock-in amplifier  detected the output voltage x axis of the micro-cantilever. A metal frame around the micro-cantilever as shown in z axis of the micro-cantilever.The free end excitation method is explained in V on the coil should not be larger than 1000 mV to ensure the vibration amplitude of the micro-cantilever is far smaller than any dimension of the sensing chip. U of the Wheatstone bridge under the driving voltage V with 800 mV in sweeping frequency from 10 Hz to 100 kHz with steps of 200 Hz. The interval time between two adjacent testing points was one second. The measuring process was completed in octane at 30 °C. In The experimental parameters of the two excitation modes are discussed in this section. First, the driving voltage −3 to 0.97 kg·m−3. Based on Equations (12) and (15), the values of slope k were calculated after the micro-cantilever sensing chip was immersed in the selected silicone oils under different excitation modes. The effect of viscosity on the measurement of the fluid density by the slope method was researched in the next experiment. In order to evaluate the effect of viscosity, silicone oil was selected as the sample. The viscosity values of silicone oils range from 0.5 mPa·s to 100 mPa·s, but their density value changes are very small, only from 0.93 kg·mk were all about 2 when the viscosity values of silicone oils were 0.65 mPa·s, 10 mPa·s and 50 mPa·s (the black curve) under double sided excitation, but it became 0.56 when the viscosity value was 100 mPa·s. However, in the red curve corresponding to free end excitation, the values of slope k were all about 3.4 when the viscosity values of silicone oils were 0.65 mPa·s and 10 mPa·s, but they became 2.63 and 0.77 when the viscosity values were 50 mPa·s and 100 mPa·s, respectively. The experimental results illustrate that the slope method for the measurement of fluid density was not significantly affected by the viscosity when the viscosity value of measured fluid was less than 10 mPa·s. Therefore, a low viscosity value can be neglected for the proposed slope method to measure the density of a fluid.As shown in The experiments for the density measurements of five fluids were carried out under different temperatures of 25 °C, 30 °C and 35 °C, the corresponding reference values of their densities are shown in V on the coil was from 250 mV to 1000 mV with steps of 250 mV. There were 15 different density values of five fluids under three different temperatures. The output voltage U of the Wheatstone bridge was tested 10 times at every measuring point, and the final output voltage U of the Wheatstone bridge at every measuring point was the average value of these measurement results. As shown in V and output voltage U when the micro-cantilever sensing chip was immersed in each fluid under each temperature. Also, the corresponding slope values for the fitted curves were calculated and are shown in The sensing chip was packaged as shown in n-hexane and methylbenzene under 30 °C were used to calibrate the working Equation (16). Thus, the constants of m and n were calculated as:The reference density values of Then, the working Equation (16) became:Therefore, the density values of the fluids at different temperatures measured by the slope method under free end excitation were calculated using Equation (17) and are shown in k and fluid density under free end excitation was fitted from the data in fρ = 0.005 (kg·m−3)−1, where the unit of slope k was 1.As shown in V and output voltage U when the micro-cantilever sensing chip was immersed in each fluid at each temperature. In addition, the corresponding slope values were also calculated and are shown in The sensing chip was packaged as shown in n-hexane and methylbenzene under 30 °C were also used to calibrate the working Equation (16). Thus, the constants of m and n were calculated as:The reference density values of Then, the working Equation (16) was changed to:The other density values of fluids by the slope method under double sided excitation were calculated using Equation (18) and are shown in k and fluid density under double sided excitation from the data in k also decreased linearly with increasing fluid density, which is consistent with Equation (18). The absolute average measuring accuracy was about 0.60%. In addition, the DMS under double sided excitation was S = Δk/Δfρ = 0.013 (kg·m−3)−1, which was above two times that under free end excitation.As shown in It can be seen from −3 to 870 kg·m−3 were 0.46% and 0.60% by the slope method under free end excitation and double sided excitation, respectively. The experimental results showed that the measurement accuracy under double sided excitation was not better than under free end excitation, but the DMS of 0.013 (kg·m−3)−1 under double sided excitation was better than that under free end excitation (0.005 (kg·m−3)−1). Therefore, it’s better for micro-cantilever sensing chip to measure fluid density under torsional vibration by the slope method. A novel slope method for the measurement of fluid density was presented. The slope between driving and output voltages of a sensing chip under nonresonant status was inversely proportional to the density of the surrounding fluid. This measurement method did not need to find accurate resonance frequencies via the sweeping frequency in a large frequency range. The relationship between fluid density and slope has been deduced under flexural and torsional nonresonant vibrations. The influences of frequency and viscosity on the measurement of fluid density by the slope method were studied in experiments. The slope method could be used to measure fluid density with good accuracy when the viscosity value of the measured fluid was less than 10 mPa·s. The fluid density measurement accuracies in the range from 640 kg·mThe slope method significantly shortens the measuring time of fluid density compared with traditional measurement methods via the resonant frequency. It just needs to obtain two groups of voltage points to calculate the slope. Accordingly, the resonant method needs to sweep the frequency to obtain the resonant frequency, and it was hard to calculate the accurate resonant frequency over a large range, thus the slope method greatly improves the fluid density measurement efficiency.3. In addition, the noise investigation in the measurement is another important research topic for future study.Nevertheless some disadvantages still exist in this study. For example, the sensor cannot work in conductive liquids because there was no isolation layer to protect the coil and pads, so a future research direction will be to design a new chip with a protective layer to measure the density of conductive liquidd, and some experiments will be carried out in the fluids with densities larger than 1000 kg/m


Page 1: The following statement should be added to Acknowledgments. “Publication of this study was supported by grant no. 2017/22402-4, São Paulo Research Foundation (FAPESP).”Volume 6, no. 7, e01274-17, 2018,


Dysregulation of fluid and salt transport across epithelium contributes to the pathogenesis of many diseases, such as pulmonary edema and cystic fibrosis. Intracellular and extracellular signals, i.e., hormones and protein kinases, regulate fluid and salt turnover and resolution. Increasing evidence demonstrates that transepithelial fluid transport is regulated by cyclic guanosine monophosphate-dependent protein kinase (cGK) signals. cGK2 was originally identified and cloned from intestinal specimens, the presence of which has also been confirmed in the kidney and the lung. cGK2 regulates fluid and salt through ENaC, CFTR and NHE. Deficient cGK2 regulation of transepithelial ion transport was seen in acute lung injury, and cGK2 could be a novel druggable target to restore edematous disorder in epithelial tissues.Transepithelial fluid and salt re-absorption in epithelial tissues play an important role in fluid and salt homeostasis. In absorptive epithelium, fluid and salt flux is controlled by machinery mainly composed of epithelial sodium channels (ENaC), cystic fibrosis transmembrane conductance regulator (CFTR), Na Cyclic guanosine monophosphates-dependent protein kinases (cGKs) belong to the serine/threonine kinase family and are present in many eukaryotes ranging from unicellular organisms to human beings . As the +/K+-ATPase  [The mechanisms of regulating active fluid and salt transport across the epithelium have become an area of research with vital implications for understanding fluid homeostasis under both normal and pathologic conditions. Epithelial fluid and salt transports are predominately controlled by the epithelial sodium channel (ENaC), cystic fibrosis transmembrane conductance regulator (CFTR), aquaporin, and Na+-ATPase . The ENace (AFC) . In epitFour mammalian subunits, α, β, γ, and δ ENaC, have been cloned so far. These transmembrane proteins are predominately expressed in the apical plasma membrane of epithelial cells in the lung, the kidney, the colon, and the airway, serving as a critical pathway for maintaining fluid/salt homeostasis locally and systematically.+-absorption by cGK2 in the small intestine, the nephron, and the lung [Increasing evidence demonstrates the regulation of Nathe lung . We founthe lung . Furtherthe lung . In addithe lung . AFC in the lung . Our stuthe lung . Moreovethe lung . Given tthe lung . In addithe lung . In thisthe lung .CFTR is a cyclic adenosine-dependent chloride channel protein, the only ion channel in the adenosine triphosphate-binding cassette transporter family. Consisting of two membrane-spanning domains and a regulatory domain that regulates sodium channel, CFTR is expressed in many epithelial tissues, for example, the lung, the intestine, the pancreas and, the kidney . The rolEscherichia coli heat-stable enterotoxin -induced trafficking of CFTR to the cell surface of villus enterocytes activation. In contrast, blocking of cyclic adenosine monophosphate (cAMP)/protein kinases A (PKA) signaling did not alter the cell surface levels of CFTR [In rat intestine epithelium cell line, which stably expresses CFTR, some studies have demonstrated the effects of cGK2 on activating CFTR ,22, whil of CFTR . These r of CFTR ,27. To i of CFTR . A later of CFTR . In addi of CFTR ,30. The  of CFTR . In the  of CFTR . Moreove of CFTR .NHE are integral plasma membrane proteins catalyzing the electroneutral exchange of extracellular sodium for intracellular protons with a stoichiometry of one for one. They exist as homodimers through intermolecular interactions, and their N-terminus contains 12 transmembrane domains that are involved in ion transportation . Nine NH+ absorption in the small intestine epithelium by inhibiting NHE3 [cGK2 is located in the secretory epithelium of the kidney and the small intestine, and regulates the metabolism of sodium and protons, possibly through the mediation of NHE. The inhibition of cGK signaling abolishes the suppression of pH recovery induced by NHE inhibitors in renal tubular epithelial cells . A recening NHE3 .+/K+-ATPase. As one of the characteristics of ALI during the early exudative phase, pulmonary edema results from the imbalance of AFC and turnover. An increasing number of studies have confirmed that cGK2 signals mediate the attenuation of ALI induced by lipopolysaccharide [ALI is a common clinical condition caused by infectious and non-infectious insults, the current therapy for which is supportive, and there is an urgent need for novel and more effective interventions. AFC is the resolution of fluid by alveolar epithelium consisting of ENaC, aquaporin and Naccharide ,43. As accharide ,45. Studccharide ,18. ReguSeveral strategies have been applied in the development of cGK2-specific activators, which interact with the binding sites for cGK2 substrate peptides. The cGK2-specific activation drugs may be useful for the treatment of substantial pulmonary diseases by modulating the transport of fluid and salt. The membrane-permeable analogues can interact with cGK2 at the cGMP binding sites, which can be used as tools for the treatment of pulmonary diseases . The mosAnother activator associated with cGK2 signals is natriuretic peptide (NP). NP binds to the NP receptors that contain the intracellular guanylyl cyclase domain, which catalyzes guanosine triphosphate and produces cGMP . Mainly +, H+ and Cl− by regulating ENaC, CFTR and NHE (+/K+-ATPase, which have roles in the metabolism of potassium ion and fluid. However, our understanding of the cellular and molecular mechanisms by which cGK2 signals regulate other transepithelial fluid and salt-metabolizing pathways are incomplete and limited. Future studies including greater awareness of these metabolism pathways and explaining their modulation by cGK2 signals will provide more evidence of the mechanisms by which cGK2 signals regulate the metabolism of fluid and salt, satisfying the urgent need for novel and more effective interventions in pulmonary diseases.The metabolism of fluid and salt in epithelium is crucial for the occurrence and development of many diseases, such as pulmonary edema and CF. Researchers have been studying cGKs for many years, and evidence regarding the regulations of transepithelial fluid and salt re-absorption by cGK2 signals is accumulating, most of which focuses on the whole cGKs or cGK1. Studies regarding the effects of cGK2 on the metabolism of fluid and salt are limited, and this emerging field has not been synopsized to date. This review mainly summarized the increasing evidence regarding the effects of cGK2 signals on transepithelial fluid and salt transport and the underlying relative mechanisms. We can conclude that cGK2 signals regulate transepithelial fluid and salt re-absorption partly through the mediation of Na and NHE . In addi