Background:Twitter has emerged as a critical source of free and openly available information during emergency response operations, providing an unmatched level of on-the-ground situational awareness in real-time. Responders and survivors turn to Twitter to share information and resources within communities, conduct rumor control, and provide a “boots on the ground” understanding of the disaster. However, the ability to tune out background “noise” is essential to effectively utilizing Twitter to identify important and useful information during an emergency response.Methods:This article highlights a two-prong strategy in which the use of a Twitter list paired with subject specific Boolean searches provided increased situational awareness and early event detection during the United States Department of Health and Human Services (HHS), Office of the Assistant Secretary for Preparedness and Response (ASPR) response to Superstorm Sandy in 2012. To maximize the amount of relevant information that was retrieved, the Twitter list and Boolean searches were dynamic and responsive to real-time developments, evolving health threats, and the informational needs of decision-makers.Conclusion:The use of a Twitter list combined with Boolean searches led to enhanced situational awareness throughout the HHS response. The incorporation of a dynamic search strategy over the course of the HHS Sandy response, allowed for the ability to account for over-tweeted information, changes in event related conversation, and decreases in the return of relevant information.  The Use of Twitter in Emergency Response OperationsTwitter has emerged as a critical source of information in emergency response operations. Following and reviewing publicly available information posted on Twitter in real-time provides an unmatched source of on-the-ground situational awareness. Situational awareness is defined as “all knowledge that is accessible and can be integrated into a coherent picture, when required, to assess and cope with a situation.”*The micro-blogging site Twitter, created in 2006, allows users to share information, ideas, and opinions in 140 characters or less. Over the past 8 years, Twitter has grown to more than 241 million active monthly users who send 500 million tweets each day.was their everyday life and became what they tweeted about most, whether about sandbagging efforts, shelter locations, or the needs of displaced families. As the situation subsided and water levels fell, residents returned to tweeting about other aspects of their lives and did not focus exclusively on the flood.The effectiveness of Twitter as a tool to provide situational awareness to emergency responders was demonstrated in multiple large scale disasters including typhoons,To complement official data sources and reporting, the US Department of Health and Human Services (HHS) Office of the Assistant Secretary for Preparedness and Response (ASPR) started monitoring Twitter for situational awareness in 2009 during the H1N1 influenza pandemic. Since then, ASPR has continued to refine its monitoring techniques and has increased the number of analytic tools used to bring further depth and detail to maintaining situational awareness.Presently, Twitter is used for supplementing situational awareness in two distinct ways. The first way is by following long-term trends to identify spikes in Twitter conversation that might indicate an emerging public health concern. This form of monitoring is primarily used for long term epidemiological surveillance of diseases such as Middle East Respiratory Syndrome Coronavirus (MERS-CoV) or H7N9 influenza, and requires the use of a Twitter analytics tool that can access historical Twitter data. The second way ASPR monitors Twitter, which is the focus of this article, is event-specific real-time monitoring. In contrast to the long term trend analysis which focuses on identifying deviations from the historical baseline, event-specific real-time monitoring focuses on finding reports on Twitter that provide situational awareness during an emergency response. The search techniques employed by ASPR for monitoring Twitter are meant to filter down to the most relevant information shared in the midst of a disaster. This article will outline the strategy ASPR employed for event-specific real-time Twitter monitoring during the HHS response to Superstorm Sandy in 2012.The Sandy BasicsSandy made landfall in the US on the coast of Brigantine, New Jersey as a post-tropical cyclone on October 29, 2012.Under the National Disaster Response Framework,Sandy, hurricane, #Sandy, and #hurricane.th, in the immediate hours post-landfall, 20% of all searches conducted on Twitter were Sandy-related searches.As the storm ended and survivors began to assess the damage from the storm, Twitter was inundated with information. Between October 27, 2012 and November 1, 2012 Twitter users sent more than 20 million tweets using the termsASPR began monitoring Twitter for indications and warnings of potential public health emergencies as Sandy made landfall in New Jersey on October 29, 2012. For the initial two weeks of the HHS response, Twitter was monitored 16 hours a day every day. The monitoring team consisted of one full-time social media lead analyst (SHS) and ad-hoc ASPR and HHS employees and interns. When possible, monitoring was split into eight hour shifts to make the work load more manageable. Throughout a shift a single analyst would be entirely dedicated to monitoring Twitter searches and listsDuring the first two weeks of the HHS response, in addition to monitoring for early reports of public health emergencies, an overview of the trends observed on Twitter was provided for overall situational awareness during twice daily HHS briefings. On November 17, 2012, monitoring was scaled back to regular working hours and daily situational awareness reports were reduced to once a day. ASPR stopped daily monitoring of Twitter for public health situational awareness related to Superstorm Sandy on December 13, 2012.AND, OR, NOT (Boolean operators) to limit or broaden a search.Advance notice events  provide responders with crucial time to better prepare for the implementation of a Twitter monitoring strategy. As it became clear that Sandy would be making landfall somewhere along the eastern seaboard of the US, ASPR analysts began implementing a two-prong monitoring strategy. The strategy included the use of: 1) Twitter lists; a curated list of Twitter users usually tweeting about a single topicThese two methods were employed in tandem to retrieve information that addressed an HHS pre-determined list of hurricane Essential Elements of Information (EEIs). The HHS EEIs guide in determining: what information is critical, who is responsible for the data collection, and the frequency of reporting for HHS emergency response operations.Table 1 includes only the EEI categories that ASPR monitored on Twitter for potential relevant information that would improve HHS situational awareness. The full list of EEI categories is more extensive. Throughout the emergency response, the informational needs and HHS response concerns changed on an almost daily basis as the situation on the ground shifted. Flexibility and adaptability were critical to effectively monitor Twitter for evolving information needs, trends, and situational awareness. Therefore, the monitoring strategy used was driven by two primary factors: changes in key word terminology associated with the event on social media and the informational needs of leadership and field teams. The EEI categories listed in Table 1 were selected for monitoring on Twitter as they were top priorities that had been reported on social media channels during previous incidents.HHS and ASPR do not use or rely solely on Twitter for information on any of the EEI categories, as social media (including Twitter) is not always an appropriate source for certain types of information such as the status of deployed personnel or supply needs within medical facilities.The Twitter list and Boolean searches functioned differently  to filter incoming data from Twitter in order to make it more usable and relevant to the concerns of the ongoing HHS response. The use of the two together provided a more complete and robust picture from Twitter. For example, the Twitter list acted as a wide net with specific sized holes to monitor and capture all EEIs of concern that were openly reported by local news, public officials, and local emergency management who were already reporting on Superstorm Sandy. An added benefit of the Twitter list is that it also captured unknown or unconsidered hazards. In contrast, the Boolean searches used a variety of keywords and limiting or broadening Boolean operators to focus on and extract tweets that included more specific EEIs of concern  from the entire sea of Twitter. On its own, the sole use of a Twitter list would result in a search that was too broad, while using only Boolean searches would lead to results that are too narrowly focused.As Bennett and colleagues When the Twitter list was built for an advance notice event , each account was reviewed and verified based on the user’s Twitter profile and Twitter use. Specifically, analysts looked at when the user’s profile was created, how often the user tweets, who is following the user, and historically what kind of information the user tweets. This information was used to verify that real and reliable accounts were added and used. By taking time beforehand to review and verify potential Twitter accounts for a Twitter list, a more trustworthy source of potential information is identified ahead of time thereby allowing analysts to have greater confidence in the information provided via that source during the response.Generally, a pre-made Twitter list for an emergency response would focus on one to two major geographic areas impacted by the emergency. However, with Superstorm Sandy, it remained unclear what areas would be hardest hit until just hours before landfall; models varied, with some citing Washington, D.C. and the Eastern Seashore as the area of greatest concern while others were reporting a direct hit to New York City. Due to this uncertainty leading up to landfall, the Twitter list initially developed covered a large area of the East Coast ranging from Virginia to Rhode Island.However, within the first 24 hours of landfall, major updates were made to the Twitter list as the storm path became clearer. Twitter accounts from states north of Connecticut were culled from the list, and the number of accounts from states south of New Jersey was thinned, but not eliminated entirely. For example, the National Capital Region  remained a focal point because the HHS headquarters are located within this area.The focus of the revised and ever evolving Twitter list became New York, New Jersey, and Connecticut. In the first 24 to 48 hours post-landfall, the number of accounts included on the Twitter list from each of these states grew rapidly. Very few of these additions were the result of actively searching for new accounts. Instead, new accounts were added to the Twitter list during active monitoring, usually through indirect recommendations  of existing list members. For example, if a local news station already included on the list retweeted one of its reporters, who was not on the list and who was live-tweeting an unfolding situation, that reporter would then be added to the Twitter list. Throughout the course of Superstorm Sandy, the locale-specific Twitter list not only provided increased situational awareness, but also resulted in a deluge of new sources of information.As the HHS response grew longer, the number of accounts reporting Sandy-related information decreased to those reporting on, and often from, the most impacted areas. This reinforced what Palen and colleagues learned from the Red River floods, in that interest and attention to a disaster is sustained by those who are local and most impacted by the event.(Sandy OR Hurricane) and EEI qualifiers with simple Boolean commands to retrieve storm-related tweets (Table 3). An important note is that while Sandy was not meteorologically a hurricane at landfall, much of the general public still referred to it as a hurricane and for that reason “hurricane” was still used in the search terminology. In addition, because the social media dashboard used by ASPR analysts searched for keywords within hashtags the use of #Sandy or other hashtags was not needed within any of the subject specific Boolean searches. These EEI searches were intentionally broad at the beginning of the monitoring process. Analysts would look for key issues within the results of each EEI search. Narrower and more complex searches were not used to prevent the exclusion of issues that were not identified prior to the response yet are still of importance and interest due to the unique nature of each emergency response.The initial Boolean Twitter searches created for the HHS Superstorm Sandy response focused on six general areas of concern from the EEIs: hospitals, nursing homes, shelters, injuries/fatalities, cold-related illnesses, and carbon monoxide poisoning. At the beginning, these early subject specific searches were kept simple by using broad hurricane terminology Abbreviation: CO = Carbon MonoxideDuring the course of the response, the Boolean searches were edited to account for over-tweeted information or news. As an example, following multiple hospital evacuations, there was an abundance of stories about nurses evacuating babies in the midst of power outages. As a result, these stories overwhelmed the pre-established hospital search stream. Therefore, to better control the information retrieved, the hospital search was adjusted to exclude the terms most commonly used in the tweets referring to this incident . By excluding these terms, the level of “noise” and volume of tweets retrieved via this search was decreased to a more manageable volume. Figure 2 outlines the steps made to adjust the hospital search. These adjustments were made to account for trends within the Twitter conversation.As the storm weakened and moved north into Canada, further edits and additions were made to the Boolean searches to account for changes in the overall Twitter conversation. Analysts found that as more time passed from the date of landfall, Twitter users referred to the storm less by name. People who had regularly been providing updates via Twitter became less likely to use #Sandy and more likely to simply state a problem or concern with the understanding that they were already talking about Sandy.“Sandy” and “Hurricane” on Twitter between October 17, 2012 and November 17, 2012 within the U.S., excluding retweets. As shown, the use of “Sandy” and “Hurricane” spiked very quickly on October 29th, the day of landfall, but almost as quickly began to decrease in use. This did not mean people were no longer tweeting and providing information, but rather that people were tweeting in a different way. Therefore, changes needed to be made to searches to account for the evolving Twitter discussion and to reflect how people now referred to the event.Figure 3 depicts the results of a retrospective analysis using the Topsy Pro Public Sector Analytics™ (Topsy) of the use of the words “Sandy” and “Hurricane” with basic geographic place names in Boolean searches. For example adding (NYC OR “New York” OR Brooklyn), lead to the retrieval of more specific and potentially relevant information, and thereby a better perspective of the situation within the impacted communities. From the previous example of adjusting a Boolean search based upon trending terms , the additional geographic terms further helped narrow the scope and volume of potentially relevant tweets . Also in addition to adding geographic terminology, analysts chose to further filter the incoming results by adding in the qualifying term of “patients.” This addition helped better focus search results to more relevant tweets referencing the healthcare system.As Twitter is not easily searchable based upon geography and only an estimated 2% of all tweets on a typical day include geographic metadata,Throughout the HHS response the Twitter list and all Boolean searches were monitored via a social media dashboard to allow for ease of viewing and streaming of information. This dashboard allowed for real-time streaming of filtered data and was essential to organizing searches and incoming information into manageable streams. Each analyst utilized his/her own individual dashboard with identical searches and a subscription to the Twitter list. Edits and changes to the list and searches were managed by the lead analyst (SHS) and communicated and tracked on a single document.The monitoring of Twitter using the two-prong strategy outlined above involved significant flexibility and adaptation. When Twitter monitoring was ended for the Sandy response there were a total of 20 Boolean searches followed regularly with additional ad-hoc searches created as needed for further information. The use of this prong of the strategy resulted in the retrieval and flagging of multiple EEI events during the course of the Sandy response. Throughout the HHS response, more than 30 Twitter reports or responses to information requests in addition to daily summaries were sent.One example that demonstrated the value of developing and using a dynamic Twitter monitoring strategy to enhance situational awareness during Superstorm Sandy was the evacuation of Bellevue Hospital in New York City.Boolean Searches and Bellevue HospitalThe use of Boolean searches to track the status of healthcare infrastructure was valuable during the HHS response. The evacuation of a major hospital places additional stress on state and local health systems; therefore, early knowledge or awareness of an evacuation  could potentially help HHS better prepare beforehand should states request federal assistance. Boolean searches worked well for this EEI category as it was a narrow subject matter with defined concerns. Around 8:45 p.m. EST on October 29, 2012, the standard hospital Boolean search retrieved tweets that the Bellevue Hospital was operating on emergency generators . Using the information provided in the initial tweets, new and more specific Boolean searches were created using “Bellevue” as a keyword to attempt to retrieve further details and enhance situational awareness.After the creation of more targeted Boolean searches it was determined that Bellevue Hospital’s emergency generators were not working properly and the basement was flooding with water. Bellevue Hospital hovered in a critical situation before fully evacuating its final 500 patients nearly two days later. This example demonstrated that while it was not plausible to monitor every facility or potential incident of concern ahead of time (particularly in high population density locations), the use of broad searches to identify defined topics of concerns with further investigation as necessary has the potential to be a more efficient use of time and energy during a response.Twitter List and NorovirusSome EEIs were more easily tracked via the Twitter list due to the broad nature of the subject matter. Disease surveillance and outbreaks is a broad subject that could encompass a variety of different illnesses and concerns. It would have been too difficult to attempt to predict and create Boolean searches for every possible illness that could emerge as a consequence of the storm and subsequent recovery efforts. Instead, the Twitter list was used as a wide net to monitor overall community health in the days, weeks, and months following the storm.For example, on November 6, 2012, a local New York newspaper tweeted a report of an outbreak of norovirus at an evacuee shelter. This was the first report ASPR retrieved from Twitter regarding gastrointestinal illness outbreaks at evacuee shelters. By capturing this first mention of a disease outbreak via pre-identified source on Twitter and disseminating this information to HHS personnel, HHS field staff increased precautions and was better prepared to mitigate similar outbreaks in facilities where NDMS representatives and USPHS officers were located.There were several limitations associated with this method of using Twitter for situational awareness. The ability to verify and fully trust information obtained from Twitter and other forms of social media was a concern. Fake Twitter accounts and rumors can quickly inundate Twitter following a disaster. For example, following the Boston bombings in 2013, 29% of the most tweeted content was the result of rumors and fake accounts.It was critical to have a verification system in place prior to the activation of monitoring in order to avoid perpetuating the spread of rumors and inaccurate information.However, during the early hours of the HHS response, the verification process used to add accounts to the Twitter list was modified due to significant constraints on time and resources. The modified process focused on the Twitter account profile information such as the profile biography, creation date, number of followers, and number of tweets sent. Unlike during the preparation phase, a review of past tweets sent by the user was not performed.The level of situational awareness gained from the EEI Boolean searches was only as good as the keywords or phrases they contained. Building good searches required an understanding of the vocabulary associated with the ongoing response and EEIs of concern. It also required a familiarity with the vernacular of the impacted population and geographic area. Analysts had to be willing to immerse themselves in the conversation to gain a better understanding of the needs of the impacted population.(sandy OR hurricane) AND hospital, is made unique enough by the term hospital to filter out a majority of Sandy related tweets while still limiting the return to tweets within the public health sector. The simplicity of this search also limits the need to account for spelling errors, abbreviations or differences in vernacular within tweets. For example, a known concern was generator failure at hospitals. If the following search had been constructed: (sandy OR hurricane) AND hospital AND (generator OR “lost power”), any tweet containing a misspelling or alternate phrasing such as “without power.NYU Hospital is gen. is workingDon’t think their backup ” would not be retrieved. Until a more specific concern was established  it was more beneficial to maintain broad searches with minimal keywords.Nonetheless, overdependence on Boolean searches could lead to the exclusion of certain tweets that may contain important information not included in the search terminology. It is important to acknowledge that every event is unique, and that there inevitably will be a certain number of unknown factors that do not fall into the predetermined EEI categories. Broad searches allow room for anomalies or outliers. The search,#Sandy OR #Snoreastercane OR #Frankenstorm). But, the lack of limiting terminology  resulted in a flood of tweets retrieved via this Boolean search. Additionally, as these hashtags began to trend or increase in popularity and usage, they were used as tweet spam whereby they contained no information relevant to Sandy. Therefore, the absence of EEI terms and the addition of Twitter spam made this stream virtually useless.As stated earlier, hashtags were not used in the initial set of Boolean searches as the social media dashboard used included hashtags in the search results. However, a short and simple search was created to track the traffic of a few major hashtags  and unknown informational needs . Yet, it is not enough to create a Twitter list and some Boolean searches at the beginning of an event and expect a consistent return of useful information. Twitter monitoring during an event involves constantly reacting to trends in the conversation and changing informational needs, and must remain fluid and flexible to prevent the retrieval of irrelevant information resulting from stagnating searches and lists. Investing in the technology, personnel, and training needed to effectively and efficiently monitor Twitter during a response has the potential to result in a high return on investment and inform on the needs of impacted communities.*At time of writing. The number of active monthly users and tweets sent each day is a fluid number.The authors have declared that no competing interests exist.


To evaluate sources of error in the Magnetic Resonance Imaging (MRI) measurement of percent fibroglandular tissue (%FGT) using two-point Dixon sequences for fat-water separation.1 weighting and sequence type were assessed by comparison of this Dixon sequence with low-resolution GRE PD-weighted Dixon data, and against gradient-echo (GRE) or spin-echo (SE) based T1-weighted Dixon datasets, respectively.Ten female volunteers  gave informed consent following Research Ethics Committee approval. Each volunteer was scanned twice following repositioning to enable an estimation of measurement repeatability from high-resolution gradient-echo (GRE) proton-density (PD)-weighted Dixon sequences. Differences in measures of %FGT attributable to resolution, T1-weighted data were strongly correlated with that derived from PD-weighted data . However, both sequences exhibited higher mean %FGT by 2.9% (p < 0.0001) and 12.6% (p < 0.0001), respectively, in comparison with PD-weighted data; the increase in %FGT from the SE T1-weighted sequence was significantly larger at lower breast densities.%FGT measurement from high-resolution PD-weighted Dixon sequences had a coefficient of repeatability of ±4.3%. There was no significant difference in %FGT between high-resolution and low-resolution PD-weighted data. Values of %FGT from GRE and SE T1 weighting and sequence type impact on the accuracy of Dixon-based %FGT measurements; Dixon MRI protocols for %FGT measurement should be carefully considered, particularly for longitudinal or multi-centre studies.Although measurement of %FGT at low resolution is feasible, T In XRM,ly dense . The proly dense . A meta-ly dense . Althougly dense –7, MRI hly dense ,9.1-weighted sequences, with and without fat suppression, FGT and fat have been separated by means of threshold-based segmentation [et al derived their calibration from a test object experiment [However, as yet, there is no consensus on the most appropriate MRI sequence and methodology for breast density measurement. In Tentation –10 or thentation –16. Howeentation  and withentation ,19. Instentation . The abientation . Howeverperiment  whilst operiment ,23. Here1-weighting, sequence type and resolution in a group of volunteers. With this approach we identify causes of error and thereby provide guidance on MRI protocols for Dixon-based %FGT measurements.In this article we consider the accuracy of Dixon-based %FGT measurements. In order to distinguish between various sources of error , we assess %FGT repeatability and acquire, process and compare Dixon-based images with different TResearch Ethics Committee (UK NHS HRA) approval was granted  and written informed consent was obtained from all subjects in this study. Ten healthy female volunteers  were recruited; a broad age band was chosen to confer a wider range of breast density values. Each volunteer underwent two MRI breast examinations without contrast to enable an estimation of measurement repeatability. The two scans were performed on the same day to exclude the influence of hormonal cycle changes.1-weighting (Repetition Time (TR) = 7.34 ms, Echo Time (TE) = 4.77/2.39 ms, Voxel Size = 1.3×1.3×1.0 mm3, Receiver Bandwidth = 390 Hz/Px, Parallel Imaging Factor = 2 (GRAPPA), Acquisition Time = 2 min 40 s, Flip Angle (FA) = 4° and 25°, respectively), denoted as HR GRE PD and HR GRE T1, respectively. A further low-resolution 2D spin-echo (SE) based T1-weighted two-point Dixon sequence with a longer echo train , Echo Train Length = 8, Acquisition Time = 4 min 59 s) was also acquired, denoted LR SE T1. In the second MRI examination for each volunteer, a repeat high-resolution gradient-echo PD-weighted sequence with identical parameters was acquired to enable a repeatability measurement, denoted as HR GRE PD (R).Breast images were acquired at 1.5T  using the Sentinelle breast coil with Variable Coil Geometry . Prior to each scan, a different radiographer reconfigured the lateral, moveable, breast coils from a standard neutral location and the volunteer was positioned with the nipple aligned to the coil centre. During the first examination, volunteers were scanned with forward arm extension, but were encouraged to reposition the arms alongside the body for the repeat scan should they have experienced any discomfort. Three different Dixon sequences were acquired in the first MRI examination of each volunteer. Two high-resolution, two-point 3D gradient-echo (GRE) based Dixon sequences were acquired with PD- and T1-weighted sequence, denoted as LR GRE PD and LR GRE T1, respectively. In total, for each volunteer, this resulted in five datasets covering the same volume for comparison within the first MRI examination: a high-resolution GRE PD-weighted reference sequence (HR GRE PD), a high-resolution GRE T1-weighted sequence (HR GRE T1), a low-resolution GRE PD-weighted dataset (LR GRE PD), a low-resolution GRE T1-weighted dataset (LR GRE T1) and a low-resolution SE T1-weighted sequence (LR SE T1).From the first MRI examination, two further low-resolution GRE Dixon datasets were generated from the high-resolution GRE sequences using Siemens Multi-Planar Reformatting to match the low resolution SE TSemi-automated breast volume segmentation was performed by a researcher (AEWL) on the in-phase GRE PD-weighted datasets (at high and low resolution) using in-house software . The external contour of the breast volume (retaining the skin) was delineated by a combination of manual signal intensity thresholding and erosion of the background noise (standard erosion implementation in the IDL package library). For each breast, a manual straight coronal cut was performed at the most anterior position of the pectoral muscle to define the posterior limit [2 region of interest (ROI) in the centre of each breast (to minimize possible coil sensitivity effects) in a central slice containing fat and water  were then used to calculate a correction factor for the water-only image of each Dixon dataset (as the ratio of Fmax/Wmax). For every voxel within the volumetric segmentation mask, the water fraction, WF, was calculated asWc and F are the corrected water and fat signal intensities at each voxel location . Dixon fat/water separation techniques to measure breast density assume that water-containing tissues represent the fibroglandular content of the breast. The summation of voxel water fractions multiplied by the voxel size therefore yielded the total volume of fibroglandular tissue (FGT) whilst the percentage of FGT volume relative to the volume of the segmentation mask resulted in a measurement of %FGT for each breast in each Dixon dataset.For the fat- and water-only images of each Dixon dataset, the maximum signal intensity was measured from a standardized 30x30 mmnd water . The relIn this study, the high resolution GRE PD-weighted datasets were assumed to provide the most accurate assessment of %FGT since the variation in signal intensity across the fat- and water-only images in this sequence is minimal, with the least influence of tissue characteristics. As such, a correction factor can be easily estimated via the method above to transform the image intensity into a surrogate for the volume occupied by water and fat within the breast. The HR GRE PD datasets therefore provided the reference standard. Individual comparisons between select Dixon datasets were then made to separate the sources of discrepancy between %FGT measurements from different sequence alterations.Comparison of FGT volume, total breast volume and %FGT between the HR GRE PD and HR GRE PD (R) datasets enabled a measure of repeatability which accounted for changes in patient positioning, coil profile and intra-operator variability in the breast volume segmentation.1 weighting/sequence type or resolution), the same breast volume segmentation at either high or low resolution was applied to the datasets following a rigid registration based on a mutual information algorithm [1 versus PD weighting on the %FGT measurement, since these datasets differed in contrast but not in pixel size. A comparison between LR GRE T1 and LR SE T1 datasets and the LR GRE PD dataset provided information on the differences in %FGT conferred by T1 weighting and by sequence type. In datasets with the same T1 weighting, such as between the HR GRE PD and LR GRE PD datasets, comparison provided information on the effect of resolution on the %FGT measurement.Using datasets from the first MRI examination, the %FGT calculated from each Dixon dataset under investigation was compared with that derived from the reference GRE PD weighted data. To isolate each potential source of error  were used to select two volunteers with high and low breast density, respectively. Using the right breast of these volunteers, the corrected Dixon water fraction for the LR GRE T1 and LR SE T1 datasets were plotted against the LR GRE PD data on a voxel by voxel basis. To assess the potential error conferred on measurement of %FGT by the signal intensity correction factor, the applied correction factor for each subject at each Tt-test.Coil positioning, breast volume  segmentation and signal intensity correction were performed separately and independently for left and right breasts in each image dataset. Statistical testing therefore treated right and left breast measures independently despite originating from the same examination, resulting in a sample size of 20 for each measurement parameter. Data were assessed visually using boxplots to inspect for deviations from the normal distribution. Differences in FGT volume, total breast volume, %FGT and signal intensity correction factor between left and right breasts were evaluated using the paired Student’s r, was defined as ±1.96 σd where σd represents the sample standard deviation of the differences between the paired measures. The coefficient of variation, CoV, which quantifies the random errors in a single measurement, was calculated as Measurement repeatability of FGT volume, total breast volume and %FGT between HR GRE PD and HR GRE PD (R) datasets were evaluated using Bland-Altman statistics, where the coefficient of repeatability, 1 weighting and sequence type using analysis of variance (ANOVA) together with selected comparisons between particular sequence groups using the paired Student’s t-test (two-sided α = 0.05). No correction was made for multiple post-hoc comparisons so the family-wise error rate may be higher than 0.05. Differences in FGT volume and total breast volume between HR and LR GRE PD datasets were also assessed using the paired Student’s t-test (two-sided α = 0.05).Values of %FGT for different pairs of sequences were correlated using the Pearson product-moment correlation coefficient. Measured values of %FGT were compared within each breast between datasets at varying spatial resolution, Tt-test (two-sided α = 0.05). Correlations between voxel-by-voxel water fractions for the low resolution data of two subjects were assessed using the Pearson product-moment correlation coefficient.The repeatability of the applied signal intensity correction factor between the repeat HR GRE PD sequences was evaluated using Bland-Altman statistics. The signal intensity correction factors applied to high and low resolution GRE PD-weighted data were compared using the paired Student’s Analysis results by individual volunteer, laterality and sequence type may be found within 3 (p = 0.02) was detected between the HR GRE PD and HR GRE PD (R) datasets, no significant differences were observed in total breast volume and %FGT. Coefficients of repeatability in FGT volume, total breast volume and %FGT between the two HR GRE PD datasets were found to be ±29.4 cm3, ±64.1 cm3 and ±4.3%, respectively (Although a significant difference in mean FGT volume of 8.5 cmectively . Coefficp < 0.0001). %FGT derived from high and low resolution GRE PD data were strongly correlated (r = 0.99) with no significant difference in mean %FGT (p = 0.06)  but exhibited higher mean %FGT in comparison with GRE PD-weighted data . LR SE T1%FGT values were strongly correlated with LR GRE PD values (r = 0.96), but mean %FGT from LR SE T1 data was 12.6% higher (p < 0.0001) than that from GRE PD-weighted data. This increase in %FGT was significantly larger at lower breast densities  . %FGT meensities .p = 0.006), with a coefficient of repeatability of ±0.38 and coefficient of variation calculated at 12.0%. There was no significant difference in mean correction factor applied to the high and low resolution GRE PD-weighted sequences.Between the repeat HR GRE PD sequences, a significant difference in mean correction factor of 0.13 was detected . However, the correlation was lower between the corrected LR SE T1 and LR GRE PD voxel water fractions for either subject   . For Subctively) . Low-resThis study considered the potential sources of error in %FGT measurement induced by sequence alterations in two-point Dixon fat-water separation techniques, and the impact of these errors on the outcome of %FGT measurement for MR-derived breast density studies.%FGT measurement from HR GRE PD sequences was highly repeatable; we report a coefficient of repeatability of ±4.3% and a coefficient of variation of 4.3%, accounting for changes in both subject and coil position as well as intra-operator variability in data-processing. Although repeatability metrics vary widely in the literature, these results compare favourably with studies which assessed repeat %FGT measurement after subject repositioning, including those which utilised a fuzzy C-means clustering segmentation ,20,25, aThis study suggests that low spatial resolution PD-weighted Dixon sequences could reasonably be used to assess breast density; presuming similar repeatability at high and low resolution, low resolution sequences have the added advantages of a reduction in scan time, an increase in signal-to-noise ratio (SNR) and fewer slices for analysis. This result highlights the ability of Dixon methods to account for partial volume effects, although the impact of resolution on %FGT measurement may be influenced by breast volume segmentation technique.1-weighted data exhibited higher mean %FGT than PD-weighted data. Although this difference was lower than the coefficient of repeatability in the GRE datasets, that derived from the spin-echo T1-weighted dataset (12.6%) was particularly substantial and increased considerably at lower breast densities. This also reduced the range of volunteer %FGT values in the LR SE T1 dataset (40.7%) relative to the LR GRE PD or LR GRE T1 datasets .Despite an applied signal correction, both GRE and SE TAlthough an approximately linear relationship was apparent between the corrected LR GRE T1 and LR GRE PD voxel water fractions, the corrected LR SE T1 voxel water fractions strongly deviated from lower LR GRE PD values in subjects with both high and low breast density  can strongly influence the measurement of %FGT. These errors could potentially influence the study of breast cancer risk factors and could mask density changes in longitudinal studies. In addition, our results are highly relevant to the comparison of breast density studies from different centres and to the analysis of multi-centre trials.Dixon fat/water separation techniques have been considered a more objective approach to MR-derived breast density assessment with reduced user interaction . SeveralIn conclusion, our study demonstrates that Dixon-based measurements of %FGT are highly repeatable and can account for partial volume effects: %FGT can be accurately derived from low resolution Dixon images. However, the selection of MRI protocols for Dixon measurement of %FGT should be carefully considered, as it may not be possible to compensate for changes in image contrast within the fat and water images across the full range of %FGT values. In the wider field, further work is needed to standardize Dixon protocols and to ensure the clinical accuracy of breast density measured via this technique.S1 Table(DOCX)Click here for additional data file.


Primary infection is a chickenpox (95% VZV seropositivive in US adults). Reactivated forms its dormant status is the dorsal root, cranial nerve and other sensory ganglia may lay for years to decades. Reactivation of latens VZV localizated cutaneous rash erupting a single dermatome. It may travel along a sensory axon of the skin from vesicular lesions. Perineuritis causes intensive pain in the nerve distributionLifetime reactivation of VZV as shingles 50% incidence, HZO is rare (10-20%) of all VZV causes. HZO is a trigeminal manifestation of VZV. Reactivated VZV travels down V/1 and V/2 centripetal distribution. Contagious spread of the VZV may lead of the involvement of the other cranial nerves resulting optic neuropathy (II) isolated cranial nerve palsies  neurogene motility disorders. Predisposing factors: immunecompromissed condition (decreased T-cell activity), acute herpes simplex virus infection and other reacting factors. Complications 50% of HZO patient is a postherpetic neuralgia (20% of a cases) involves the orbit (10-25% of a cases).Acute management: antiviral agent immediately-best prognosis started early-within 72 hours and general measures, ophthalmology consultation.Pain management: acute and postherpetic neuralgia.Our patient evaluated for left sided facial pain, unilateral "burning eye" and malaise that began two days ago. The neurological examination has been proven partially n. oculomotorius palsy of the left side and hyperaesthesia in dermatome V/1 unilateral side.Neuroimaging studies  have shown normal status.Two days later on the face in the V/1 and V/2 dermatome we detected special characteristic skin symptom.The diagnosis was clear: herpes zooster ophthalmicus (HZO).We present evolution change in the nature of pain, following and demonstrating the eye movement disorders and skin signs from termination to recorvery process.No conflict of interest.


Over several decades genetic studies have unraveled many molecular mechanisms that underlie the signaling networks guiding morphogenesis, but the mechanical forces at work remain much less well understood. Accumulation of fluid within a luminal space can generate outward hydrostatic pressure capable of shaping morphogenesis at several scales, ranging from individual organs to the entire vertebrate body-plan. Here, we focus on recent work that uncovered mechanical roles for fluid secretion during morphogenesis. Identifying the roles and regulation of fluid secretion will be instrumental for understanding the mechanics of morphogenesis as well as many human diseases of complex genetic and environmental origin including secretory diarrheas and scoliosis. The generation of a complete body-plan from a single cell during embryonic development depends on complex interactions between molecular signals and morphogenetic forces. Genetic analyses have identified key molecular mechanisms controlling morphogenesis, but how molecular functions translate to specific morphogenetic movements is still poorly understood. Research into the mechanics of development has been focused largely on short range forces generated at the cell cortex by actin contractility. However, it has become increasingly clear that more broadly acting forces like fluid flow and hydrostatic pressure play substantial roles during morphogenesis. These “fluid forces” are particularly important during tubulogenesis, a key process underlying the structural organization of most organs. Here, we review the role of hydrostatic pressure during morphogenesis in metazoans; from tubulogenesis to axis elongation and spine formation, and the pathological implications of misregulated fluid secretion.The control of water transport is an essential physiological function for all organisms. Even though water accounts for most of the mass and volume of an organism, cells are unable to directly control its movement. Instead, they rely on ionic and osmotic gradients to power fluid transport. The incompressible nature of liquids allows fluid secreted into luminal spaces to generate considerable hydrostatic pressure that is capable of acting at great distances .+/K+-ATPase, which generates a sodium gradient [+ transport through the V-H+-ATPase  and occludin families . These pTubes are a basic structural element underlying the morphology of most organs. Although the specific morphogenetic strategies may vary between organs and across species, tubulogenesis invariably presents two fundamental elements: 1-All mature tubes contain a single lumen; 2-Lumen opening requires its filling. Typically, one or more lumens initially form through cellular rearrangements to establish a restricted space. Then, lumens expand through fluid accumulation, common in vertebrates, nematodes, and tunicates, or through matrix secretion, as observed in insects. While fluid and matrix secretion occur through different mechanisms, they function in the same way to support and power luminal expansion.+/K+-ATPase drives the opening of several lumens that begin to coalesce as they expand [+/K+-ATPase [The use of fluid secretion during lumen expansion is a key, conserved process in vertebrate organogenesis. In many tubes that undergo cord hollowing, fluid secretion drives expansion of nascent lumens to form a single tube. In zebrafish, the gut tube forms from a solid rod of cells in which TJs are first assembled at multiple actin-rich foci . Then, ty expand . Also esy expand . Lumen e+-ATPase . Similar+-ATPase . The imp+-ATPase .A key driver of vertebrate fluid secretion is the chloride channel CFTR. This channel regulates fluid secretion in several organs from morphogenesis through out life and its loss of function causes cystic fibrosis . Perhaps+/K+-ATPase is essential for ventricle inflation, independent of the circulation required for later stages of expansion [Ciona intestinalis notochord, Slc26-dependent fluid secretion is required for the development of the lumen along the length of the notochord rod [C. elegans excretory canal. In this organ, aquaporins facilitate the movement of water required for unicellular tube extension [Fluid-driven lumen expansion has also been observed in other organs. In the zebrafish brain, Naxpansion ,18. Simihord rod . A similxtension ,21.Lumen expansion driven by hydrostatic pressure is crucial for lumen expansion in vertebrates, but this is not the only mechanism used by metazoans. In the Drosophila tracheal system, a chitinous matrix is secreted into the lumen, which is later cleared to leave a gas-filled tube . Matrix smoothened does not block fluid-driven lumen expansion, but arrests lumen formation at the double lumen stage due to impaired Rab11-dependent contact remodeling [An essential step in tube formation is the resolution of a single lumen, which requires coordinated tissue remodeling and luminal expansion. In the zebrafish gut, opening of multiple lumens is followed by a transient double lumen stage whose resolution requires the remodeling of cellular contacts  Figure . Loss ofmodeling . Similarmodeling . It woulCiona notochord and the zebrafish vasculature. During anastomosis of the zebrafish vasculature TJ remodeling and fluid pressure work together to generate a continuous lumen [Contact and TJ rearrangements are also required for single, continuous lumen formation in the us lumen . In someus lumen . In the us lumen .Fluid pressure can influence epithelial folding, cell proliferation, and can exert global effects on a whole organism as seen during the elongation of the AP axis. Classic studies have established that regulated fluid pressure is essential for the normal development of the brain and lung. In the chick brain, fluid pressure inflates the ventricular lumen after the spinal neurocoele becomes occluded . DraininLung morphogenesis is also dependent upon properly regulated fluid pressure. Modulating fluid pressure in the developing lamb lung leads to changes in the growth rate of the organ and in the development of alveoli, suggesting that fluid is a key driver of lung development . Althoug+-ATPase [Fluid pressure also functions in vertebrate axis elongation, which partly depends on hydrostatic pressure generated within the notochord. The vertebrate notochord is composed of a core of cells that contain large fluid-filled vacuoles enclosed by a sheath of epithelial-like cells surrounded by extracellular matrix  Figure . In a se+-ATPase . In vivo+-ATPase . Loss of+-ATPase . Based o+-ATPase .C. elegans, the body shape and mechanics of the worm depends on internal fluid pressure restricted by a stiff external cuticle [Drosophila oocyte where deposition of an elaborate matrix is required for generating an elliptical structure [Keller also noted that luminal pressure and a restrictive outer wall may be a common theme for directing organogenesis . In C. e cuticle -42  to cystic fibrosis. Pathogens like cholera can activate cyclic AMP signaling, which increases CFTR activity and leads to uncontrolled intestinal fluid secretion. In the human kidney, fluid accumulation within the nephra causes PKD. While PKD is triggered by disruption of ciliary function, CFTR-dependent fluid secretion also contributes to cystic expansion ,47. The Loss of fluid secretion can also lead to human disease. Loss of CFTR activity leads to cystic fibrosis, characterized by mucosal buildup and colonization by opportunistic pathogens in the lung . While lbaobab mutant presents a rapid and dramatic increase in intestinal fluid accumulation and a secretory diarrhea phenotype due to loss of a key negative regulator of Cftr [Regulators of vertebrate fluid secretion have been identified by forward genetic screens in the zebrafish. The  of Cftr . Thus, fThe long range forces generated by fluid pressure are key drivers of many morphogenetic processes. The outward force generated by fluid secretion can drive lumen expansion, influence the shape of developing tissues, and provide proliferative cues. Furthermore, as exemplified by the notochord, these forces can exert effects that span and guide development across an entire embryo. Understanding the functions of hydrostatic fluid pressure during morphogenesis is also likely to provide broad insights into the regulation and responses to diseases characterized by misregulated fluid secretion. Fluid forces represent a key morphogenetic process essential for shaping embryos throughout development.


In January 2014, the Chicago City Council scheduled a vote on local regulation of electronic cigarettes as tobacco products. One week prior to the vote, the Chicago Department of Public Health (CDPH) released a series of messages about electronic cigarettes (e-cigarettes) through its Twitter account. Shortly after the messages, or tweets, were released, the department’s Twitter account became the target of a “Twitter bomb” by Twitter users sending more than 600 tweets in one week against the proposed regulation.The purpose of our study was to examine the messages and tweet patterns in the social media response to the CDPH e-cigarette campaign.We collected all tweets mentioning the CDPH in the week between the e-cigarette campaign and the vote on the new local e-cigarette policy. We conducted a content analysis of the tweets, used descriptive statistics to examine characteristics of involved Twitter users, and used network visualization and descriptive statistics to identify Twitter users prominent in the conversation.Of the 683 tweets mentioning CDPH during the week, 609 (89.2%) were anti-policy. More than half of anti-policy tweets were about use of electronic cigarettes for cessation as a healthier alternative to combustible cigarettes . Just over one-third of anti-policy tweets asserted that the health department was lying or disseminating propaganda . Approximately 14%  of the tweets used an account or included elements consistent with “astroturfing”—a strategy employed to promote a false sense of consensus around an idea. Few Twitter users were from the Chicago area; Twitter users from Chicago were significantly more likely than expected to tweet in support of the policy.Our findings may assist public health organizations to anticipate, recognize, and respond to coordinated social media campaigns. The use of electronic cigarettes (e-cigarettes) is growing rapidly in the United States. In a single year, e-cigarette use in the United States doubled for adults  and middEmerging evidence suggests that e-cigarette use is associated with smoking among adolescents and may encourage smoking initiation . In lighOn April 24, 2014, the Food and Drug Administration (FDA) proposed a new rule to extend existing tobacco authority to e-cigarettes and other tobacco products . As of JInforming and educating constituents about health is one of 10 essential services provided by local health departments (LHDs) in the United States . CommuniOne week prior to the e-cigarette policy vote, the Chicago Department of Public Health (CDPH) used Twitter to disseminate a series of tweets about e-cigarettes. Shortly after releasing the tweets, the CDPH Twitter feed was “Twitter bombed” by Twitter users tweeting against the proposed policy change. Twitter bombing is a social media strategy designed to fill Twitter feeds with a specific message in order to “establish a false sense of group consensus about a particular idea” and to make the message a trending topic on Twitter . In poliAstroturfing through social media has been used with some success in elections for and against candidates and issues ,42,43. TOn January 8, 2014, CDPH conducted a 1-day Twitter campaign about e-cigarettes . CDPH Twth, 12 pro-policy and 11 anti-policy tweets were directed to the CDPH Twitter feed by including the CDPH Twitter handle @ChiPublicHealth in the tweet. Including a Twitter handle in a tweet is called “mentioning”  @chiPublicHealth, spreading nothing but lies #kcavo #vaping…[URL].” The tweet was visible to the followers of @A and Twitter users following #kcavo and/or #vaping. The hashtag #kcavo is short for a saying among e-cigarette users, or vapers, “keep calm and vape on”. The Twitter profile of @A connects to a professional website that links to pro-vaping advocacy groups, conferences, and an e-cigarette-related business. Over the next 6 days more than 600 tweets were sent opposing the e-cigarette policy and including @ChiPublicHealth.At 12:46am January 9Using the twitteR package  for R veIn reviewing the data, we noticed duplicate messages not marked as retweets. We identified these as non-native retweets , coded them as retweets, and attributed each to its original tweeter. To examine how messages spread, retweet network data was visualized and analyzed using Pajek 3.10 ,52.To examine tweet content, four of the authors read the tweets independently and identified themes. The authors then met to discuss and developed a common set of themes: safety, lies/propaganda, science, flavors, regulation, and issue salience . Tweets z≥1.96) to be high. Tweeters with two or more of these three characteristics we considered likely to be involved in astroturfing. Tweet characteristics can also aid in identifying messages consistent with astroturfing. For example, sending multiple copies of the same tweet that include different shortened versions of the same URL is a strategy used to avoid being identified by Twitter as a spammer  @ChiPublicHealth #EcigTruthsRT-1This tweet (RT-1) linked to a newspaper article outlining the debate over e-cigarettes focusing on safety concerns, harm reduction arguments, discussion of laws banning their use, and their increasing popularity .@ChiPublicHealth #Please review all of the science before condemning smokers to #QuitOrDie [URL] #ECigTruthsRT-2This tweet (RT-2) linked to a peer-reviewed journal article about the chemistry of contaminants in e-cigarettes  .Bought this lollipop myself at pharmacy at pediatrician office. #ecigs save lives. Lollipops DO NOT @ChiPublicHealthRT-4RT-4 linked to a photo displaying a nicotine lollipop with a caption comparing the harm reduction effectiveness and reception of nicotine lollipops to e-cigarettes (retweeted 43 times).[URL] @ChiPublicHealth #ecigs save livesRT-5RT-5 linked to a photo showing a cartoon character saying, “Are you saying that you lie to people about ecigs so that they will not use them even though they work and are safer?” (retweeted 20 times).[URL] @ChiPublicHealthRT-6RT-6 linked to a photo of a crumpled combustible cigarette with a caption stating e-cigarettes are the best harm reduction alternative to smoking but big corporations are paying the FDA to over-regulate them (not retweeted).th CASAA call to action; the URL was truncated in all 23 retweets.A total of 11 different tweets from @A were retweeted between one and 12 times. The original Twitter bomb tweet, sent by @A, was retweeted nine times. Another central user, @E, is a Twitter account representing an online community of “e-cigarette users and campaigners”. @E sent a single tweet that was retweeted 23 times by 23 different Twitter users. The URL in the tweet was to the published study …RT-7BMC Public Health journal (see RT-2).The original link pointed to the Finally, @ChiPublicHealth was also central in the retweet network with 29 pro-policy, and three anti-policy, retweets.In the week leading up to a vote on local e-cigarette policy by the Chicago City Council, 683 tweets and retweets about e-cigarettes including a mention of @ChiPublicHealth were sent by 307 Twitter users. The majority of the tweets and retweets were against the policy , and a majority of Twitter users reporting a location in their profile were from states outside Illinois (n=83) or outside the United States (n=48). Twitter users located in Chicago (n=35) were significantly more likely than expected to tweet in favor of the policy.The CDPH and five Twitter users tweeting against the policy were central in the network of retweeting during this week. Retweet patterns were consistent with past research, which has identified argument quality and source as factors associated with retweeting . In thisThe majority of tweets appeared to be from legitimate Twitter users who oppose the regulation of e-cigarettes, and at least one advocacy group (CASAA) aiming to organize policy opposition messaging. However, our results suggested that 96 of the 683 tweets (14.1%) sent by 73 of the 307 Twitter users (23.8%) were using an account or tweet strategy consistent with astroturfing. The structure of the retweeting network was also consistent with findings from a study of astroturfing where a small number of accounts were responsible for a large proportion of retweets contributing to trending topics .th on the Illinois Vapors blog  different shortened URLs pointing to the same place, and (2) Twitter users who have more than one of the characteristics associated with astroturfing . Removing central nodes from a network is a strategy that has been used to disrupt crime and disease transmission networks ,65, howeThe emergence of social media efforts by the tobacco industry  and otheUsing social media to understand and address substance use and addiction (RFA-CA-14-008 and RFA-CA-14-009). As social media use continues to grow, additional research is needed to better understand how to develop and implement effective pro-health social media campaigns that engage the public to improve health.New media marketing strategies present both challenges and opportunities for public health . There i


Since water moves freely among fluid compartments, it was of interest to track whole-body fluid movements during a resting recovery from extended exercise in the heat, but without rehydration. This mechanism was investigated before, during and following an extended heat-acclimation experiment.Eight males were heat acclimated over 17 days  using the controlled hyperthermia technique (deep-body temperature clamped at 38.5 °C). Before (day 1), during (day 8) and after acclimation (day 22), whole-body, inter-compartmental fluid movements were tracked, firstly during progressive dehydration (heat stress test: 30 min seated rest plus 90 min cycling [same posture]: 40 °C) and then during passive recovery (30 min seated rest: 28 °C), all without fluid replacement. Changes in whole-body, intra- and extracellular body-fluid volumes during heat-stress tests and recovery were quantified using combined radionuclide- and dye-dilution techniques. These data illustrate not just compartmental contributions to fluid loss, but fluid movements during the transition from exercise to recovery.P<0.05). This whole-body fluid loss continued during recovery, as sweating continued for some time, with whole-body sweat losses averaging 229 (day 1), 303 (day 8) and 392 mL (day 22). However, recovery of the plasma volume commenced very quickly, even without fluid being consumed. Indeed, during the 30-min recovery, plasma volume increments of 1.9 % (day 1: 65 mL), 3.2 % (day 8: 112 mL) and 5.4 % (day 22: 180 mL), relative to volumes measured immediately following exercise, were observed. This pattern was consistent with an enhancement of the plasma volume restoration as heat acclimation progressed. Prior to commencing heat acclimation, the relative interstitial contribution dominated fluid loss during recovery, with the intracellular share being about half that of the interstitium. Thus, fluid loss occurred only from the intracellular and interstitial reservoirs, with the former sustaining the interstitial volume and thereby permitting a partial intravascular recovery. The mechanism underlying this outcome appeared to be a significant elevation of the plasma and, presumably also, the interstitial osmolality beyond 90 min of dehydration on days 8 and 22. As a consequence, the intracellular fluid contribution to this plasma recovery gradually became more pronounced. This sustained the interstitial fluid compartment, and thereby permitted a partial intravascular recovery, even before fluid was consumed. Whilst the intracellular fluid reduction during exercise represented <30 % of the total water lost, during recovery, the absolute fluid loss from this compartment more than doubled.During exercise in the heat, plasma volume reductions of 9.0 % (SEM 0.9: day 1), 12.4 % (SEM 1.6: day 8) and 13.6 % (SEM 1.2: day 22) were observed, with whole-body fluid losses on days 8 and 22 significantly exceeding day 1 (This snapshot of body-fluid dynamics at the end of recovery illustrates how inter-compartmental fluid movements may help defend against post-exercise hypotension, with the intracellular fluid reserves behaving as a temporary reservoir from which the plasma fraction is restored via the interstitium prior to commencing fluid replacement. Moreover, the recovery of the plasma volume following progressive dehydration was more rapid following heat adaptation.


Tumour blood vessels are gateways for distant metastasis. Recent studies have revealed that tumour endothelial cells (TECs) demonstrate distinct phenotypes from their normal counterparts. We have demonstrated that features of TECs are different depending on tumour malignancy, suggesting that TECs communicate with surrounding tumour cells. However, the contribution of TECs to metastasis has not been elucidated. Here, we show that TECs actively promote tumour metastasis through a bidirectional interaction between tumour cells and TECs. Co-implantation of TECs isolated from highly metastatic tumours accelerated lung metastases of low metastatic tumours. Biglycan, a small leucine-rich repeat proteoglycan secreted from TECs, activated tumour cell migration via nuclear factor-κB and extracellular signal–regulated kinase 1/2. Biglycan expression was upregulated by DNA demethylation in TECs. Collectively, our results demonstrate that TECs are altered in their microenvironment and, in turn, instigate tumour cells to metastasize, which is a novel mechanism for tumour metastasis. Tumour metastasis causes the high mortality rates that are associated with cancer. During the first stage of the metastatic process, tumour cells migrate through a vascular wall (intravasation) and then travel to target organs14610121315Here, we investigated the roles of TECs in tumour metastasis by utilizing the two aforementioned different tumour models (HM-tumours and LM-tumours) and the corresponding TECs (HM-TECs and LM-TECs) isolated from these tumours. Our results provide clear evidence that TECs actively promote tumour metastasis, particularly during intravasation, through the secretion of the small leucine-rich proteoglycan, biglycan. In addition, we found that biglycan expression was upregulated by DNA demethylation of its promoter region in TECs. Collectively, to the best of our knowledge, these results demonstrate for the first time a novel mechanism for tumour metastasis.LM-tumour and HM-tumour cells were subcutaneously xenografted into nude mice. The two melanoma cell lines were derived from identical human tumours but with significantly different metastatic potentials; A375 cells barely metastasize, whereas A375SM cells (generated from A375 cells by repeatedly re-inoculating metastasized tumour cells) develop lung metastasesin vitro. TECs were isolated from HM- and LM-tumours14in vitro model of intravasation), a transendothelial migration assay20In hematogenous metastasis, tumour cells detach from the primary site and enter the blood vasculature. This process of intravasation can be divided into three steps: 1) tumour cell migration toward endothelial cells (ECs), i.e., “migration”; 2) arrest on ECs, i.e., “adhesion”; and 3) migration through the endothelium, i.e., “transendothelial migration”in vivo primary tumours, the red fluorescence signals originating from co-implanted ECs were detected in lectin-positive blood vessels to some extent Based on the differences between HM-TECs and LM-TECs in the tumour microenvironment, we speculated that HM-TECs acquired their specific characteristics from tumour-derived factors. Thus, we cultured LM-TECs in CM derived from HM-tumour cells, LM-tumour cells, or LM-TECs (Control) for 2 days, after which biglycan mRNA expression was evaluated. Biglycan mRNA in LM-TECs was upregulated after treatment with HM-tumour-CM  and the in vivo. In mice bearing tumours co-implanted with shBiglycan HM-TECs, the numbers of CTCs and the occurrence of lung metastasis were dramatically decreased from those in the control group  2 and TLR425To clarify the potential intracellular signalling cascade by which biglycan stimulates tumour cell migration, we investigated the effects of biglycan on the activation of NF-κB and ERK 1 and 2, known downstream biglycan signalling pathways25The relationship between the gene expression and prognosis of patients with various cancers is available from the PrognoScan databaseIn this study, we demonstrated that TECs isolated from high-metastatic tumours promoted lung metastasis of tumours that rarely metastasize on their own. Tumour cell intravasation was enhanced by TEC-derived biglycan and vice versa. Expression of biglycan was regulated by DNA demethylation, indicating a bidirectional interaction between tumour cells and TECs in the tumour microenvironment. In this regard, TECs are altered by the tumour microenvironment, which, in turn, creates a local milieu more favourable for tumour metastasis, including facilitated tumour intravasation .Much remains to be elucidated regarding the determinants for tumour metastasis. A number of studies conducted during recent decades have challenged this paradigm by addressing tumour cell-autonomous mechanisms. Nevertheless, it remains difficult to predict metastasis. Tumour size and the histological grade, as evaluated by pathological examination, are not always linked with metastatic status. These observations encouraged us to examine the role of tumour stromal cells, as we focused on the properties of TECs in this study. Evidence gathered to date indicates that tumour stromal cells, such as cancer associated fibroblasts, promote tumour progression after co-implantation of these cells with tumour cells3215Although we have previously shown that TECs from tumours with different metastatic potential had distinct properties25353625HM-tumour CM treatment upregulated the expression of biglycan in LM-TECs and made LM-TECs attract more tumour cells, indicating a bidirectional interaction between tumour cells and TECs. It has been reported that TGF-β upregulates biglycan414244Although the detailed molecular mechanisms by which tumour cells acquire their metastatic potential remain to be determined, our results provide the first clear evidence for the importance of the different properties of TECs for determining tumour progression and/or malignancy. Tumour blood vessels act as a “gate” for metastasis (during intravasation of tumour cells), which is guarded by TECs as “gatekeepers.” TECs in highly metastatic tumours are thereby provided with a “key” molecule, biglycan, through DNA hypomethylation to allow tumour cells to break through this gate and proceed into the blood stream, which results in hematogenous metastasis . The prein vivo selection of pulmonary metastatic lesions in nude mice and eventually display significantly high metastatic potentials, relative to those of the parental A375 cells2. The absence of Mycoplasma pulmonis was checked by PCR at the ICLAS Monitoring Center.Human malignant melanoma A375 cells (LM-tumour) were purchased from the American Type Culture Collection (ATCC). A375SM (super-metastatic) cells (HM-tumour) were kindly provided by Dr. Fidler . HM-tumour cells were established by Six-week-old female nude mice  were housed under specific pathogen-free conditions. All procedures for animal care and experimentation adhered to institutional guidelines and were approved by the Ethical Committee for Experimental Animal Care of Hokkaido University.TECs and NECs were isolated as previously described14The following chemicals were purchased: fluorescein isothiocyanate (FITC)-Bandeiraea simplicifolia isolectin B4 (BS1-B4) (Vector Laboratories), Alexa Fluor 647-Griffonia simplicifolia 1 isolectin B4 (GS1-B4) (Invitrogen), Biglycan protein from bovine articular cartilage (Sigma-Aldrich), MEK inhibitor U0126 (CST) and NF-κB inhibitor BAY11-7082 . The antibodies used are listed in Total RNA was isolated using an RNeasy Micro kit (Qiagen). cDNA was synthesized using ReverTra-Plus (Toyobo), as previously describedTECs and NECs were incubated with an antibody against either BS1-B4, CD144, CD45, or CD11b, as previously describedECs were seeded on Matrigel (BD Biosciences), as previously describedTumour cell migration toward ECs was assessed using transwell chambers (Corning), as previously described46Tumour cells were pre-labelled with mouse anti-human HLA-ABC antibody, added to EC monolayers in a Lab-Tek 8-well Chamber Slide  and allowed to adhere for 30 min. After removing non-adherent cells, cells were fixed, stained with DAPI (Dojin) and counted under a fluorescence microscope.Venus-expressing ECs were cultured on 35-mm glass-bottomed dishes (Matsunami Glass). RFP-expressing tumour cells were added to EC monolayers. After 2 h of co-culture, cells were fixed with 4% paraformaldehyde, covered with mounting medium (Vector Laboratories) and then examined using an Olympus FV1000 confocal microscope for a total of 20 fields. X-Z orthogonal reconstructions were made using FV10-ASW Viewer software. Tumour cells were scored according to the positional categories shown in cDNA for Rluc, kindly provided by Y. Ohmiya (AIST), was amplified by PCR and cloned into pCR-Blunt II-TOPO (Invitrogen). The resulting PCR products were subcloned into the XhoI and NotI sites of pCAGGS-Venus6) and ECs (2 × 104) were subcutaneously implanted in the right flanks of nude mice. After 29 days, blood was collected from anesthetized mice by cardiac puncture. Circulating tumour cells were analysed using a FACS Aria II. Data were analysed using FlowJo software. Lungs were subjected to ex vivo bioluminescence imaging using IVIS Spectrum . Tumour vessels were imaged using an Olympus SZX12 fluorescence stereomicroscope equipped with a RFP filter set (Olympus). DP20 (Olympus) and MicroMax 1300YHS (Princeton Instruments) under the control of MetaMorph software  were used to acquire bright-field (exposure time of 20 ms) and fluorescent images (1.0 s), respectively.A375 cells  was introduced into cells using Lipofectamine RNAiMAX Transfection Reagent . A non-targeting control siRNA  was used as a negative control.ECs were grown to subconfluence and culture medium was replaced with fresh EGM-2 MV. After 18–24 h, CM was collected and passed through a 0.22-μm filter (Merck Millipore) and subsequently concentrated approximately 120-fold using Amicon Ultra-15 30 K centrifugal filter units and Amicon Ultra 0.5-mL 30 K centrifugal filters (Merck Millipore). LM-tumour cells were preincubated with anti-TLR2 and/or TLR4 antibodies (Biolegend) for 90 min, or with U0126 or BAY11-7082 for 60 min. Cells were lysed after stimulation of biglycan for 30 min (ERK) or 60 min (NF-κB). Equal amounts of total protein were separated by sodium dodecyl sulphate polyacrylamide gel electrophoresis (SDS-PAGE) and transferred to polyvinylidene difluoride (PDVF) membranes. Equal loading and transfer were confirmed by MemCode Reversible Protein Stain Kit (Thermo Scientific) for detection of biglycan in the CM of ECs. Western blotting was performed using antibodies listed in 10Plasma biglycan concentrations were determined using a sandwich enzyme immunoassay for mouse or human biglycan .The correlation between biglycan expression levels and the prognosis of patients was obtained from the PrognoScan databaseBlood was collected from patients who were clinically diagnosed with colon cancer or hepatocellular carcinoma  and fromGenomic DNA was extracted using NucleoSpin Tissue (Macherey-Nagel). The extracted DNA was bisulfite-treated using an EpiTect Bisulfite kit (Qiagen) and amplified with methylation- or unmethylation-specific primers designed with MethPrimer software. The primers are listed in http://quma.cdb.riken.jp/top/quma_main_j.html).Genomic DNA samples were treated with bisulfite using a MethylEasy Xceed Rapid DNA Bisulphite Modification kit (Takara Bio) and then used as a template for PCR amplification of the region of interest. The primer pairs are listed in The demethylating agent 5-aza-2′-deoxycytidine (5-aza-dC) (Sigma) was added to the culture medium and incubated for 3 days.All data, unless otherwise specified, are expressed as the mean ± standard deviation (SD) of three independent experiments performed in triplicate and subjected to one-way ANOVA, followed by a Tukey–Kramer multiple comparison test. A two-sided Student’s t-test was used for comparison between two groups.How to cite this article: Maishi, N. et al. Tumour endothelial cells in high metastatic tumours promote metastasis via epigenetic dysregulation of biglycan. Sci. Rep.6, 28039; doi: 10.1038/srep28039 (2016).


Fluid overload is frequently found in acute kidney injury patients in critical care units. Recent studies have shown the relationship of fluid overload with adverse outcomes; hence, manage and optimization of fluid balance becomes a central component of the management of critically ill patients.In critically ill patients, in order to restore cardiac output, systemic blood pressure and renal perfusion an adequate fluid resuscitation is essential. Achieving an appropriate level of volume management requires knowledge of the underlying pathophysiology, evaluation of volume status, and selection of appropriate solution for volume repletion, and maintenance and modulation of the tissue perfusion. Numerous recent studies have established a correlation between fluid overload and mortality in critically ill patients. Fluid overload recognition and assessment requires an accurate documentation of intakes and outputs; yet, there is a wide difference in how it is evaluated, reviewed and utilized. Accurate volume status evaluation is essential for appropriate therapy since errors of volume evaluation can result in either in lack of essential treatment or unnecessary fluid administration, and both scenarios are associated with increased mortality. There are several methods to evaluate fluid status; however, most of the tests currently used are fairly inaccurate. Diuretics, especially loop diuretics, remain a valid therapeutic alternative. Fluid overload refractory to medical therapy requires the application of extracorporeal therapies.In critically ill patients, fluid overload is related to increased mortality and also lead to several complications like pulmonary edema, cardiac failure, delayed wound healing, tissue breakdown, and impaired bowel function. Therefore, the evaluation of volume status is crucial in the early management of critically ill patients. Diuretics are frequently used as an initial therapy; however, due to their limited effectiveness the use of continuous renal replacement techniques are often required for fluid overload treatment. Successful fluid overload treatment depends on precise assessment of individual volume status, understanding the principles of fluid management with ultrafiltration, and clear treatment goals. Fluid overload is frequently found in critically ill patients with acute kidney injury (AKI). Increasing fluid overload should not merely be considered an expected consequence of fluid resuscitation or severe AKI, it should be seen as a probably mediator of adverse outcomes. In critically ill patients, recent studies have highlighted the role of fluid overload on adverse outcomes . ObservaIn critically ill patients, adequate fluid resuscitation is essential to the restoration of cardiac output, systemic blood pressure and renal perfusion in patients with cardiogenic or septic shock , 8. PromThe administration of crystalloids solutions that are recommend for the initial management of patients with or at risk of AKI, and also in patients with sepsis expands the extracellular compartment, but over time since critically ill patients have a increased capillary leak intravenous solutions will leave the circulation and distribute in the extracellular volume leading to edema and to fluid overload. These results in impaired oxygen and metabolite diffusion, distorted tissue architecture, obstruction of capillary blood flow and lymphatic drainage, and disturbed cell to cell interactions that may then contribute to progressive organ dysfunction Table . These eP = 0.03) [Several observational studies have demonstrated a correlation between fluid overload and mortality in critically ill patients with acute respiratory distress syndrome, acute lung injury, sepsis, and AKI. Bouchard et al., have shown that patients with fluid overload defined as an increase in body weight of over 10 % had significantly more respiratory failure, need of mechanical ventilation, and more sepsis. After adjusting for severity of illness, AKI patients with fluid overload had increased 30 day and 60 day mortality. Among survivors, AKI patients who required renal replacement therapy had a significantly lower level of fluid accumulation at initiation of dialysis and at dialysis cessation than non-survivors. Renal recovery was significantly lower in patients with fluid overload [Lungs are one of the organs in which adverse effects of fluid overload are most evident, which can lead to acute pulmonary edema or acute respiratory distress syndrome . SeveralDaily fluid balance: daily difference in all intakes and all outputs, which frequently does not include insensible losses.Cumulative fluid balance: sum of each day fluid balance over a period of time.Fluid overload: usually implies a degree of pulmonary edema or peripheral edema.Fluid accumulation: positive fluid balance, with or without linked fluid overload.Percentage of fluid overload adjusted for body weight: cumulative fluid balance that is expressed as a percent. A cutoff of ≥10 % has been associated with increased mortality. Fluid overload percentage can be calculated using the following formula [ formula :Fluid overload recognition and assessment in critically ill patients requires an accurate documentation of intakes and outputs; however, there is a wide variation in how this information is recorded, reviewed and utilized. Mehta RL and Bouchard J proposed some useful definitions to help us to standardize the approach and facilitated comparisons :Daily flHistory and physical examination:The usefulness of medical history, symptoms, and signs along with routine diagnostic studies ) that differentiate heart failure from other causes of dyspnea in the emergency department were evaluated in a meta-analysis. Many features increased the probability of heart failure, with the best feature for each category being the presence of past history of heart failure ; paroxysmal nocturnal dyspnea ; third heart sound gallop ; chest radiograph showing pulmonary venous congestion ; and electrocardiogram showing atrial fibrillation . A low serum BNP proved to be the most useful test  .Importantly, signs like pulmonary rales, lower extremity edema, and jugular venous distention have significant limits for assessing fluid overload. There are some studies that have correlated these sings during physical examination and invasive measures ). Butman et al.  found thOn the other hand, in a prospective study, physical signs of fluid overload were compared with hemodynamic measurements in 50 patients with known chronic heart failure. Sings like rales, edema, and elevated mean jugular venous pressures were absent in 18 of 43 patients with pulmonary capillary wedge pressures ≥22 mmHg. The combination of these signs had a sensitivity of 58 % and specificity of 100 % .Chest radiographyChest x-ray has been one of the most used tests to evaluate for hypervolemia. Radiographic sings of volume overload include dilated upper lobe vessels, cardiomegaly, interstitial edema, enlarged pulmonary artery, pleural effusion, alveolar edema, prominent superior vena cava, and Kerley lines. However, up to 20 % of patients diagnosed with heart failure had negative chest radiographs at initial emergency department evaluation. Additionally, these radiographic sings can be minimal in patients with late-stage heart failure .In patients with congestive heart failure, radiographic signs had poor predictive value for identifying patients with PCWP values ≥30 mmHg where radiographic pulmonary congestion was absent in 39 % of patients .The X-ray technique and the clinical status of patient impact radiographic performance for detecting volume overload. Portably chest X-ray, reduce the sensitivity of findings of volume overload , and pleNatriuretic peptidesHigh levels of BNP can be found with volume overload; however, some conditions like myocardial infraction and pulmonary embolism can cause elevated levels of BNP. Other conditions that have to be taken into account when evaluating BNP levels are obesity, associated with lower BNP levels and renal failure, associated with high BNP levels. Patients with heart failure who have elevated base-line levels of BNP.The greatest utility of BNP levels is in the absence of elevation, since low BNP levels have a high negative predictive value for excluding heart failure diagnosis. On the other hand, high BNP levels can be non-specific for volume overload .Bioimpedance vector analysisBioelectrical impedance analysis is a commonly used method for estimating body composition, specifically detecting soft tissue hydration with a 2–3 % measurement error. It is a noninvasive, inexpensive and highly versatile test that transforms electrical properties of tissues into clinical information . BioimpeThoracic ultrasoundSonographic artifacts known as B-lines that suggest thickened interstitial or fluid-filled alveoli can be detected using thoracic ultrasound Fig. . PCWP anVena cava diameter ultrasoundThe measurement of the inferior vena cava (IVC) diameter can also be use to assess volume status. Normal diameter of IVC is 1.5 to 2.5 cm (measured 3 cm from the right atrium); volume depletion is considered with an IVC diameter <1.5 cm while an IVC diameter >2.5 cm suggests volume overload.i) and during expiration (IVCde), before and after blood donation of 450 mL. Significant differences were found between the IVCde before and after blood donation and between IVCdi before and after donation  [In an observational study on blood donors, Lyon et al. evaluated the inferior vena cava diameter (IVCd) during inspiration (IVCdctively) . In patictively) . BedsideAccurate volume status evaluation is essential for appropriate therapy as inadequate assessment of volume status can result in not providing necessary treatment or in the administration of unneeded therapy, both associated with increased mortality. There are several methods to evaluate fluid status; however, most of the tests currently used are fairly inaccurate. We will describe some of these methods.Diuretics, especially loop diuretics, remain a valid therapeutic alternative for relieving symptoms and improving pathophysiological states of fluid overload such as congestive heart failure and in patients with AKI. At this time, there is no evidence that favors ultrafiltration over diuretic use in volume overload patients with or without AKI in terms of less progression of AKI, improved clinical outcomes or reduce incidence of AKI . DespiteWhat should be the goal of urine output when using diuretics to manage fluid overload? Some empirical observations have shown that a urine output of 3–4 ml/kg/h rarely causes intravascular volume depletion as capillary refill can meet such rates in almost all patients . DiuretiSince common electrolyte disturbances could be encountered during diuretic therapy, it is important to monitor electrolytes levels and also to assess acid-based status. In order to avoid hypokalemia, administration of oral potassium it is easy. Measuring urinary potassium concentration and calculating the daily losses of potassium, which require replacement is a strategy that can be used to estimate daily potassium requirements. Another strategy is the use of potassium-sparing diuretics like spironolactone. Hypomagnesemia is frequently found during diuretic therapy, magnesium replacement can be achieved either intravenously or orally, typically with 20–30 mmoL per day. Finally in some patients, chloride losses exceed sodium losses and hypochloremic metabolic alkalosis develops; this is usually corrected with the administration of potassium chloride and magnesium chloride.A recent comprehensive review have shown that torsemide and bumetanide have more favorable pharmacokinetic profiles than furosemide, and in the case of torsemide it could be more efficacious than furosemide in patients with heart failure . In AKI patients, as compared with torsemide the use of furosemide was associated with a significant improvement in urine output. Moreover, two trials comparing bumetanide with furosemide showed conflicting results .Finally, in patients with AKI the response to furosemide may be reduced due to multiple mechanisms including a reduced tubular secretion of furosemide and blunted response of Na-K-2Cl co-transporters at the loop of Henle . This reFluid overload refractory to medical therapy requires the use of extracorporeal therapies such as continuous renal replacement therapies since critically ill patients often show hemodynamic instability and/or multiple organ dysfunctions. Accurate management of fluid balance becomes obligatory with the ultimate goal of improving pulmonary gas exchange and organ perfusion while maintaining stable hemodynamic parameters. The optimal renal replacement therapy for patients with AKI and fluid overload has not been defined yet and there is still an ongoing debate. Choice of the initial modality needs to be based on the availability of resources, local expertise; the individual needs of the patients, and finally on patient’s hemodynamic status.In patients with fluid overload, CRRT provides a slower fluid removal over intermittent hemodialysis (IHD) resulting in more hemodynamic stability and better fluid balance control, other advantages of CRRT over IHD include: a slower control of solute concentration avoiding large fluctuations and fluid shifts, which reduce the risk of cerebral edema, the great flexibility in terms of treatment adjustment to patient’s needs at anytime, and finally CRRT allows to perform the treatment with relatively simple and user friendly machines . Some laIn the absence of definite data to support the use of particular type of renal replacement therapy, one should consider CRRT and IHD as complementary therapies. Therefore, during the treatment of critically ill patients with AKI and fluid overload transitions between CRRT and IHD are frequent, and are frequently driven by patients’ hemodynamic status.Slow continuous ultrafiltration (SCUF) is a type of continuous renal replacement therapy that is usually performed with low blood flow rates (50 to 100 ml/min), and ultrafiltration rates between 100 and 300 ml/h according to fluid balance necessities. Relatively small surface-area filters can be employed with reduced heparin doses since low ultrafiltration and blood flow rates are required, .Continuous veno-venous hemofiltration (CVVH) is another CRRT technique that allows meticulous, minute-to-minute control of fluid balance by providing continuous fluid, electrolyte, and toxin clearance.The prescription of CRRT related fluid management and its integration into overall patient fluid management could be improved by using a specific order chart for the machine fluid balance as shown on Table The ultimate goal is to preserve tissue perfusion, optimizing fluid balance by effectively removing fluid without compromising the effective circulating fluid volume; therefore, meticulous monitoring of fluid balance is critical for all patients .p = 0.018) and a serious study product-related adverse events (p = 0.026) [Another option for treating patients with fluid overload are the new smaller and more portable devices like the Aquadex FlexFlow System . In patients with heart failure, Costanzo et al. compare adjustable ultrafiltration using a small ultrafiltration device to the use of intravenous loop diuretics. The authors found a trend to longer time to recurrence of heart failure within 90 days event after hospital discharge in patients treated with the ultrafiltration device, and fewer heart failure and cardiovascular events. Changes in renal function and the 90-day mortality were similar in both groups. However, more patients who were randomized to adjustable ultrafiltration experienced an adverse effect of special interest (= 0.026) .Several complications like congestive heart failure, pulmonary edema, delayed wound healing, tissue breakdown, and impaired bowel function are associated with fluid overload. Fluid overload has also been related to increased mortality. The optimal assessment of volume status in critically ill patients is of vital importance particularly during the early management of these patients. One key aspect of fluid overload management is to maintain hemodynamic stability and optimize organ function. Loop diuretics are frequently used as the initial therapy to treat critically ill patients with fluid overload; nevertheless, diuretics have limited effectiveness due to several factors such as underlying acute kidney injury that contribute to diuretic resistance. Renal replacement therapies are often required for optimal volume management in critically ill patients with fluid overload. In this setting, successful volume management depends on an accurate estimation of patients’ fluid status, an adequate understanding of the principles of fluid overload treatment with ultrafiltration, and clear treatment goals.AKI, acute kidney injury; BIVA, Bio-impedance vector analysis; BNP, B-type natriuretic peptide; CRRT, continuous renal replacement therapy; CVP, central venous pressure; CVVH, continuous veno-venous hemofiltration; EVLW, extra-vascular lung water; ICU, intensive care unit; IHD, intermittent hemodialysis; IVC, inferior vena cava; IVCd, inferior vena cava diameter; IVCde, inferior vena cava diameter during expiration; IVCdi, inferior vena cava diameter during inspiration; PCWP, pulmonary catheter wedge pressure; RVd, right ventricle diameter; SCUF, slow continuous ultrafiltration


The Perivascular Epithelioid Cell tumours (PEComas) are rare mesenchymal neoplasms recognized as entity by the World Health Organization. The tumour cells have an uncertain origin and are characterized by distinctive histological and immunohistochemical features. We report a case of PEComa occurring as intraorbital lesion in a 47-year-old man. We found only two other cases described in the literature and we considered all three cases together in order of histology, immunohistochemistry, and clinical outcome. We found a strict histological overlapping and quite similar immunohistological results. All three cases showed a favourable clinical course probably related to small size of tumours (<5 cm), low mitotic rate (<2 mitoses in 50 HPF), and absence of necrosis. Bonetti et al.  firstly Although the tumour cells have an uncertain origin, they however display histological and immunohistochemical distinctive features. Owing to the variety of condition of origin, the histological pattern is not uniform, the constant features being represented by a nested architecture composed of epithelioid cells with abundant eosinophilic or clear granular cytoplasm typically surrounded by thin capillary vessels. On immunohistochemical ground the cells characteristically express HMB45 but are negative for S100 protein.The site of origin of this tumour is extremely variable and has been reported in kidney, bladder, prostate, uterus, ovary, vulva and vagina, lung, pancreas, liver, GIT, nasal cavity, soft tissues, retroperitoneum, and bone .Orbital location is exceptionally rare. At the best of our knowledge, up to date, only 2 other cases have been described in the literature , 6. We pA 47-year-old male patient complained of progressive diplopia lasting 4 months. Otherwise the patient was in a healthy condition. Ophthalmological examination revealed a marked hypofunction of the left inferior oblique muscle.Magnetic resonance imaging (MRI) showed an intraorbital, extraconal, oval, capsulated mass measuring 2.0 × 1.5 cm, located inferomedially in the anterior part of the left orbit. The medial rectus muscle appeared cranially displaced whereas the inferior rectus one was laterally displaced. After infusion of contrast medium the lesion showed a heterogeneous density reflecting hypervascularity Figures . The proThe patient underwent surgical operation at the Maxillofacial Surgery Unit of the University of Sassari for a benign left intraorbital mass of angiomatous nature. The tumour was completely removed in February 2012 through an inferior transconjunctival approach and a lateral canthotomy . The posAt macroscopy the tumour appeared as a well-circumscribed nodule of 1.5 × 2.0 cm in diameter with a brown coloration .Routinely processed paraffin-embedded tissue sections stained with haematoxylin and eosin (H&E) were evaluated. At histology the neoplasm showed a well-circumscribed, capsulated, expansive growth, formed by a cell proliferation arranged in vascular trabecular features or in solid cords. The cells were plump and large and showed an epithelioid phenotype with vesicular round nuclei,  nucleoli, and a low mitotic activity (2 mitoses in 50 HPF). The cells showed a clear or finely granular cytoplasm, sometimes containing a granular brown pigment. No necrosis was observed Figures .α-SMA, Vimentin, Cytokeratins AE1/AE3, CK8/18, Chromogranin-A (CgA), CD 10, HMB45, Melan A, and S100 protein.The preliminary microscopic diagnosis was “angiomatous proliferation with epithelioid large cells resembling PEComa.” In order to better define the nature of the tumour, a panel of histochemical and immunohistochemical staining was performed, including Perls' Prussian blue and Schmörl techniques, CD 31, CD 34, Desmin, α-SMA was observed  aborted this possibility too.α-SMA, and positivity only for HMB45) the diagnosis of Perivascular Epithelioid Cell tumour was considered the most plausible. Since the location of this tumour is unusual in the orbit, the case was sent for a second opinion to Bonetti and Zamboni group that confirmed the diagnosis.Therefore, considering morphology  and the immunohistochemical results , tumours with size below 5 cm and low mitotic rate without evidence of necrosis could becriteria .