Research using orthotopic and transgenic models of cancer requires imaging methods to non-invasively quantify tumour burden. As the choice of appropriate imaging modality is wide-ranging, this study aimed to compare low-field (1T) magnetic resonance imaging (MRI), a novel and relatively low-cost system, against established preclinical techniques: bioluminescence imaging (BLI), ultrasound imaging (US), and high-field (9.4T) MRI.A model of colorectal metastasis to the liver was established in eight mice, which were imaged with each modality over four weeks post-implantation. Tumour burden was assessed from manually segmented regions.All four imaging systems provided sufficient contrast to detect tumours in all of the mice after two weeks. No significant difference was detected between tumour doubling times estimated by low-field MRI, ultrasound imaging or high-field MRI. A strong correlation was measured between high-field MRI estimates of tumour burden and all the other modalities .These results suggest that both low-field MRI and ultrasound imaging are accurate modalities for characterising the growth of preclinical tumour models. Translation of research in oncology, from basic biology to therapeutic drug strategies, requires the use of experimental models of disease. Transgenic and orthotopic models are increasingly used to study a tumour microenvironment that more accurately reflects the growth and clinical presentation of the disease  than in In recent years, small-animal imaging has rapidly evolved and many dedicated platforms exist , includiMeasuring tumour volume is generally straightforward and fast, although the imaging modality that provides the optimal platform, both in terms of scientific and practical considerations, depends on the requirements of a particular study. The accessibility of each small animal imaging platform will vary between institutions and research groups, and deciding which systems to use can be complex, and has led to a few studies comparing the application of different systems ;18. HoweThe aim of this study was to assess the ability of a low-field MRI system (field strength 1T) to longitudinally characterise and quantify the growth of a mouse liver metastatic model whilst directly comparing its performance to three small-animal imaging platforms: high-field MRI (field strength 9.4T); bioluminescence imaging (BLI); and ultrasound imaging (US). Of all the available modalities, these provide the best potential for assessing tumour burden, without the use of ionising radiation. We hope that this study may provide useful information for imaging laboratories planning tumour growth characterisation studies or looking to invest in new imaging equipment.Preclinical MRI is generally performed using high-field systems (4.7T – 11.75T), due to the signal-to-noise gains that can be achieved with larger magnetic fields. Such imaging systems are able to characterise both anatomical and functional information across the whole body. However, high-field systems are expensive, occupy a relatively large area and require routine maintenance due to the cryogenic cooling system of the superconducting magnet. Given the ability of MRI to allow precise and accurate quantification of tumour volume , it was in vivo pre-clinical research with mice and small rats. Such low-field MRI scanners inherently have lower signal-to-noise characteristics than their high-field counterparts, although the lower field can also lead to reduced image artefacts [Recently developed, low-field, permanent-magnet MRI systems have a number of advantages over high field systems such as their relative small footprint , and canrtefacts . Moreovertefacts ;28. Thusin vivo. As such it is particularly suited to cell tracking, either of cancerous cells or cells of the immune system, in a longitudinal, non-invasive manner [BLI is one of the most extensively used technologies for assessing biological function in preclinical models of disease ;30. The e manner ;33. BLI US imaging has been employed in preclinical research for several decades. Recent development of dedicated US systems with ultra-high frequency transducers (25–70 MHz) has revolutionised preclinical US imaging, allowing high temporal (<1 ms) and spatial (<30 um) resolution images of heart , blood fAll animal studies were approved by the University College London Biological Services Ethical Review Committee and licensed under the UK Home Office regulations and the Guidance for the Operation of Animals (Scientific Procedures) Act 1986  and United Kingdom Co-ordinating Committee on Cancer Research Guidelines for the Welfare and Use of Animals in Cancer Research .nu/nu mice ; defined as day 1. 1 x106 SW1222 luc cells were injected intrasplenically in a Dulbecco’s Modified Eagle’s Medium vehicle  via sterile surgical procedure so tumour cells washed through to the liver, where they established solid tumour deposits. Following splenectomy, to remove the possibility of tumours growing at the spleen, the laparotomy rectus sheath incision was sutured  and the skin was closed with wound clips .The human colorectal carcinoma cell line SW1222 was previously engineered in-house to express the luciferase gene . A modelThe mice were then monitored for development of solid tumour deposits via bioluminescence imaging, ultrasound imaging, low-field (1T) MRI and high-field (9.4T) MRI. Mice were allowed to recover for 24 hours between imaging sessions, in accordance with local regulations. US and BLI imaging were performed on the same day where possible; due to the proximity and efficiency of the systems, mice were kept anesthetised between the acquisitions. BLI and US imaging started at day 2. As the tumours were not expected to grow to a size detectable by the resolution of the high- and low-field MRI in the first week, these modalities began from day 7.2, and then maintained at 1.5% isoflurane using nose-cones within the imaging systems. Animals were monitored daily, mice that presented a tumour burden greater than 50% of the total liver volume were sacrificed by cervical dislocation, in accordance with the local regulations.For all imaging, mice were anesthetised with 4% isoflurane in 1 L/min Oin vivo images, animals were administered 150 μL D-luciferin  intraperitoneally at 150 mg/kg. Four mice were imaged simultaneously per acquisition. Peak emission had previously been determined to be at approximately 15 minutes post-injection, so animals were anaesthetised at 12 minutes and placed within the imaging chamber. Images were acquired in a single, supine orientation, with a 10 s exposure time.BLI was performed on days 2, 9, 20 and 23 using a Photon Imager Optima . For whole body High-field imaging was carried out on days 8, 14, 20 and 27 on an Agilent 9.4T horizontal-bore VNMRS scanner  using a 39 mm diameter birdcage coil . Animals were placed supine within a custom-built cradle. Core temperature was monitored with a rectal temperature probe, and maintained using heated water pipes. Respiratory rate was monitored using respiratory bellows, which were also used to gate the image acquisition . Animals were then positioned within the scanner and a gated, manual shim was carried out over the entire liver volume.2; slice thickness, 0.75 mm; effective echo time (TE), 19 ms; repetition time (TR), 1 s; 2 averages; total acquisition time was 9 minutes. These parameter values were chosen on the basis of previous in-house measurements of tumour and liver longitudinal (T1) and transverse (T2) relaxation times at 9.4T , which were used to numerically optimise the contrast between each tissue type [Entire liver volumes were acquired with a respiratory triggered, multi-slice fast spin-echo sequence, typically using 30–35 slices. Sequence parameters included: in-plane resolution 0.156 x 0.156 mmsue type . These rsue type .Low-field MRI was performed on days 7, 15, 18, 23 and 28 on a Bruker 1T ICON  using a 30 mm diameter solenoid coil. As mentioned above, the practical differences between low- and high-field MRI required that they were treated as different imaging modalities. However, the image resolution of low-field MRI was matched to those acquired on the high-field MRI scanner, and scan duration was limited to below 30 minutes. Animals were anesthetised and positioned prone within a holding cradle: physiological monitoring was provided via a rectal thermometer and respiratory bellows , the temperature was maintained via a water-heated cradle. Once the animal was positioned within the scanner, automated power calibration and shimming were performed prior to pilot imaging.T1 = 310 ± 87 ms, T2 = 56 ± 34 ms; tumour T1 = 505 ± 278 ms, T2 = 78 ± 28 ms [Whole liver anatomical data were acquired using a respiratory-triggered, multi-slice fast spin echo. The datasets were resolution-matched to the high-field data, and acquired with the following parameters: effective TE, 25 ms; TR, 2s; 3 averages; total acquisition time, 25 minutes. As with the acquisition at 9.4T, these parameter values were chosen on the basis of a numerical optimisation that used the following relaxation times, which were characterised previously in-house: liver  ± 28 ms .3) across the whole liver, using respiratory gating; total scan time of approximately 5 minutes.US imaging was performed on days 2, 9, 16 and 23 with a Vevo 2100 system  with an MS550D transducer. Mice were anaesthetised and placed supine on the handling table, where ECG and respiration were monitored using conductive strips built in to the imaging platform. The temperature was maintained using a heating lamp and monitored using a rectal probe. The abdomen of each mouse was covered with warmed acoustic coupling jelly. The transducer was placed in a sagittal orientation and a stepper motor was used to acquire a three-dimensional data set  using M3Vision software . All data sets acquired with US, low-field MRI and high-field MRI were manually segmented into tumour and normal liver tissue by two researchers with at least four years of preclinical imaging experience, using Amira 5.4 . Segmentation was performed blind, following randomisation of the day and mouse number.Whole liver volumes from low- and high-field MRI data were analysed. However, whole liver analysis wasn’t practically feasible for US images: the three-dimensional acquisition provided a very fine step thickness, and sagittal coverage of the whole liver typically yielded in excess of 250 slices. To enable segmentation within a reasonable timeframe, the data were compressed such that every three slices were averaged into one to yield a final slice thickness of 0.228 mm. In order to match the number of slices segmented by MRI, three representative samples of ten consecutive slices were chosen by each user, to account for heterogeneity of tumour engraftment. The relative tumour burden was resultantly used to compare the MRI and US for analysis of model development, calculated as the ratio of observed tumour to observed liver volume:V = V0 exp(Rt) to estimates of tumour burden V  was used to estimate the rate constant R, and the doubling time τ was then given by τ = ln(2)/R. Tumour burden and flux were fitted for each mouse and for each modality, using data from day 9 to day 23, thus the same group size (n = 8) was maintained for all modalities. Day 2 BLI data was excluded from this analysis, as the signal included non-engrafted tumour cells.Doubling times for tumour growth were estimated by fitting an exponential function of the form n V from , as a fuThe coefficient of variability was used to assess intra- and inter-user variability of segmentation for the US, low- and high-field MRI:CVU) and inter-user variability (CVA) to be calculated. CVU measures the user’s repeatability in assessing the data, and the CVA gives the estimate of agreement between user segmentation of matching data. A separate dataset was performed blind in a given region to remove the possibility of user choice of analysed slices contributing to the variation in the US data.Where σ is the standard deviation and μ is the mean. Five duplicate datasets were included within both user’s blinded segmentation, allowing intra-user variability  and standard deviation  of the signal within each region were then used in the following equation:The ability to discern tumour from normal liver is dependent on the difference in signal from the two tissue types and how this compares to the noise variance inherent in the data. The contrast-to-noise ratio (CNR) for MRI and US was calculated by defining two regions corresponding to tumour or normal-appearing liver. The mean  at weeks 2–4, for low-field MRI and US, was calculated using: S = TP(TP + FN), using the high-field MRI data to determine true positives (TP) and false negatives (FN).A sensitivity measure was used to quantify the ability of each modality to detect tumours within the liver, compared with high-field MRI, taken as the gold-standard. Data sets from all time points and from each modality were denoted as either exhibiting tumours, or devoid of tumours. Sensitivity . ANOVA was used in order to compare group-wise doubling times, choosing time points which ensure a consistent group size of eight. Pearson’s linear correlation was used to compare between the modalities estimation of tumour burden within the smallest period between imaging, omitting 0% burden values from all correlation calculations: high-field MRI  vs. BLI , high-field MRI  vs. low-field MRI , high-field MRI  vs. US .Three mice were removed from the study at day 24 due to excessive tumour burden. All other mice (n = 5) remained in the study until the final time point at day 28.For the US, high and low-field MRI, the liver has been outlined (red dash), example tumours have been demarcated by an orange arrow, and example vasculature has been delineated with a white arrow. In the 3D visualisations, the liver volume has been rendered in red and the segmented tumours as yellow. Liver metastases increased in volume with time in all mice, starting as small, localised deposits often located at the periphery of the liver.In the high-field (9.4T) MRI images, tumours appeared bright relative to the normal liver and blood vessels were dark. Images from low-field (1T) MRI were similar to high-field images, but with observably lower signal-to-noise characteristics, although tumours could still be discerned from liver. Some artefacts due to respiratory motion were evident (star), as shown in The change in the log bioluminescence flux is shown in For comparison, the mean growth curves for high-field MRI, low-field MRI and US are shown in 2 = 0.98, p < 0.001, Pearson’s). Tumour burden measured by US , as was tumour burden from low-field MRI .Correlating BLI photon flux with high-field MRI estimates of tumour burden from the same time points  showed aed by US  was signield MRI   MRI as a gold standard, revealed that both modalities were able to detect tumours by the week 3, though US was more sensitive at this time . The twoU) and inter-user (CVA) variability during segmentation; these measures for low-field MRI and US segmentations were similar, most likely reflecting the trade-off between the CNR and resolution associated with each modality.Data acquired with high-field MRI, proposed as the gold-standard in this study, produced the smallest intra-user  MRI has not previously been assessed for its suitability to image liver tumour volumes, and was here evaluated alongside high-field (9.4T) MRI, ultrasound imaging (US) and bioluminescence (BLI). When comparing different technologies, a challenge exists to find a robust gold-standard to provide a set of data that is as close to a ground truth as possible. For the current study, in which the ability of several small animal imaging platforms to detect tumours and quantify their volume was evaluated in a mouse model of colorectal liver metastasis, high-field MRI was chosen as the gold-standard, and yielded the smallest variations in user assessment.MRI signal increases with magnetic field, which is reflected in the reduced experimental time and greater CNR measured in this study with high-field MRI compared with low-field MRI. Though a good correlation was observed between the low-field and high-field MRI, the low-field MRI estimation of tumour doubling time was non-significantly shorter compared to the high-field MRI and US, suggesting a reduced sensitivity of the low-field MRI to the presence of smaller metastases. A non-significant, but consistent underestimation was observed in measurements of tumour burden by low-field MRI, largely due to the difficulty in distinguishing the inferior liver from the intestines with the acquired contrast: a 12% overestimation of liver volume was measured with the low-field MRI (data not shown), where the absolute tumour volumes were not significantly different, suggesting that measurements of absolute volume may be more suitable for the benchtop system.The slice thickness of the US data was compressed by a factor of three to one, rather than matched to the slice thickness of the MRI data, in order to maintain the advantage of the fine step resolution offered by the 3D imaging. For a full quantification of tumour volume, manual segmentation is required, which can be time-consuming, although automated segmentation approaches can be developed for both this and MRI data . HoweverIndividual BLI log flux growths exhibited a similar trend and produced a small variation in doubling time, suggestive that this technique is not sensitive to the variability in tumour burden. The significant overestimation in the doubling time measured in the BLI is likely to be due to the log flux signal plateau curve and may be better characterised by increasing the number of acquisitions earlier on in the study. In addition, a sigmoid function may be a better fit than a simple exponential, although this prevents straightforward comparison between modalities . A limitThe disadvantage of the BLI system is that it requires Luciferin to produce the light, whereas the other modalities used in this study did not require injected contrasts. The CNR of the MRI data could potentially be improved with the use of Gadolinium-based contrast agents, which may also shorten the acquisition time, though will require repeated intra-venous or intra-peritoneal administration.A limitation of this study was that the sensitivity of the imaging modalities to measure tumour burden changes due to a therapy was not investigated. However, using the coefficients of variations reported here, future studies can be designed accordingly: to best appreciate the estimated coefficients of variation, they can be input into a two-sample, two-sided equality power calculation to predict each modalities utility in assessing tumour shrinkage following therapy. To measure a 10% change the high-field MRI, low-field MRI and ultrasound imaging will respectively require 4, 20 and 33 animals, using the intra-user CVs, a power of 80% and 5% type I error and assuming no significant contrast changes. Furthermore, studies that have measured on the variability of calliper estimations of tumour volume report CVs between 12–35%, and generally more varied than imaging such MRI, US and CT ;35;47. T3, which is typical for preclinical MRI. This could be made smaller, but with the compromise of decreased signal-to-noise or increased imaging time, and the parameters used in this study aimed to provide a compromise between both of these factors. There is currently limited literature comparing US and MRI in application to pre-clinical tumour volumes, and a strong correlation was measured here between tumour burden estimations of high-field MRI and US. The results of the sensitivity analysis showed that US (pixel resolution approximately 7 x10-5 mm3) was more sensitive than low-field MRI. As such, US offers a particularly attractive, low-cost, and rapid platform for tumour burden assessment, even in the presence of artefacts such as rib shadowing, which may obscure tumours in the superior liver.A key parameter when evaluating the ability of each modality to detect tumours is the minimum tumour size that can be detected. This is primarily limited by the resolution of each of the imaging modality, alongside its signal-to-noise and contrast-to-noise characteristics. BLI was able to detect the presence of micro-metastases beyond the resolution of the MRI acquisition and sub-palpable volumes: viable cells within the liver at day 2, and successfully engrafted “micro-metastases” at day 9. For both MRI techniques used in this study, voxel volume was approximately 0.017 mmAlthough available, X-ray CT and nuclear imaging were not incorporated into this study. This was principally due to the limited number of scanning time points that could be performed, but also to avoid the use of modalities that require ionising radiation, particularly as there is some evidence that repeated exposure may impact on tumour growth .An interesting observation was the variability found in doubling times associated with the growth of tumours in the liver, which, according to measurements with high-field MRI, varied between 1.7 and 4.4 days. This is consistent with results obtained from orthotopic liver metastasis models derived from other colorectal cancer cell lines ;48;49, wTranslational cancer research using orthotopic and transgenic models requires the non-invasive characterisation of tumour volume. Benchtop MRI has not been extensively reported in its utility, and here demonstrated that low-field MRI is an accurate, low cost method relative to high-field MRI and could offer straightforward application to tumour growth and potentially shrinkage measurements. Each of the comparison imaging modalities investigated in this study offer a complex array of advantages and challenges, thus it isn’t clear which technique is ‘best’ for assessing the presence of tumours and quantifying their volume. Such decisions will depend on the practical and scientific requirements of individual studies and will, we hope, be guided by the data presented in this study.A combination of the applied modalities may provide the most complimentary data for assessing tumour models: BLI offers a highly specific and efficient method to screen for successful tumour engraftment and spread, where the other imaging modalities can then later be used for precise volumetric imaging. Such a workflow would be particularly advantageous for spontaneous transgenic models developed for optical imaging. A key observation from this study was the range of growth rates observed in the metastasis model was identified using each of the imaging modalities, suggesting that novel low field MRI and high-resolution US are suitable for characterising a range of liver tumour volumes.S1 Fig(TIF)Click here for additional data file.S1 Table(XLSX)Click here for additional data file.S1 Video(MP4)Click here for additional data file.


The ability of EtCO2 variation after a fluid challenge to detect FR in the context of general anaesthesia has not been investigated. Forty patients were prospectively studied. They underwent general anaesthesia for major surgeries. CO was measured by transoesophageal Doppler, and EtCO2 was recorded as well as other haemodynamic parameters  at baseline, after 100-ml fluid load over 1 min, and at the end of the 500-ml fluid load. We measured the variation of EtCO2 at 100 (ΔEtCO2100) and 500 ml (ΔEtCO2500), and ROC curves were generated. A threshold for ΔEtCO2 to predict FR was determined with receiver operating curves (ROC) analysis. The primary end point was the ability of EtCO2 variation after a 500-ml fluid load to diagnose FR. EtCO2500), sensitivity was 0.6 IC 95 %  and specificity was 1.0 IC 95 % . An absolute increase of more than 2 mmHg of EtCO2 is specific to diagnose fluid responsiveness . HR, MAP, and PP variations and ΔEtCO2100 did not bring information to predict or diagnose FR. During fluid challenge, the correlation between CI variation and EtCO2 variation was r = 0.566, p < 0.001.Fifteen patients (38 %) were fluid responders. ROC analysis showed that for a threshold of 5.8 % . Distribution of EtCO8 % were 2 in the responders group and the Ftc increased in both groups (Table p = 0.9).Baseline haemodynamic and respiratory parameters were not significantly different between fluids responders and non-responders Table . No sign2 was not significant . However, there was a significant correlation  between CI variation (ΔCI) and EtCO2 variation (ΔEtCO2). The slope of the linear regression was 0.172.The Spearman correlation test between CI and EtCO2 variation and CI variation after a 100-ml fluid challenge was significant: r = 0.39, p = 0.013. The change in EtCO2 after a 100-ml infusion provided an AUC-ROC = 0.74 ; threshold = 3.0 %; sens = 33 [13–60] %, spe = 100 [100–100] %.The correlation between EtCOΔEtCO2 after a 500-ml expansion (ΔEtCO2500) was able to diagnose fluid responsiveness with a threshold of 5.8 %. In a pragmatic approach, an absolute increase of more than 2 mmHg of EtCO2 can diagnose fluid responsiveness . The AUC-ROC for heart rate variation (ΔHR500), MAP variation (ΔMAP500), and PP variation (ΔPP500) was not significantly different from 0.5. ROC curve of ΔHR500, ΔMAP500 and ΔEtCO2500 is shown in Fig. The area under the receiver operating characteristic curve (ROC-AUC), sensitivity, specificity, positive predictive value, and negative predictive value likelihood ratios are given in Table 2 variation within the population can be classified as follows: 10 patients had a negative test, 10 patients had a positive test, and 20 patients had an inconclusive test.After a 500-ml fluid load, EtCO2 production are constant, the change in EtCO2 provides information to assess the CI changes during a 500-ml volume expansion. EtCO2 variation after a mini-fluid challenge is probably not usable to predict the response to a fluid bolus of 500 ml.This study shows that in a context where alveolar ventilation and CO2: pulmonary blood flow , CO2 metabolic production, and alveolar ventilation [2. Two mechanisms can also explain EtCO2 variation. First, a fluid challenge increases venous return and pulmonary blood flow; thus, a greater amount of CO2 delivery to the lungs and removal by alveolar ventilation should be observed. Second, a fluid challenge recruits collapsed pulmonary blood capillaries and, therefore, reduces West zones 1 and 2 and increases zone 3 [2 to be extracted by alveolar ventilation.Three factors can explain a change in EtCOtilation . Naturals zone 3 . Consequ2 has been described to be able to track CI changes in experimental [2 have been used in many clinical situations as cardiac resuscitation for monitoring blood flow generated by precordial compression [2 and CI. Some anaesthesiologists already assess fluid responsiveness by measuring EtCO2 variation during a fluid challenge, though this strategy has not been specifically evaluated [2 and CI was not significant. This is explained by the fact that except for very low CI, EtCO2 is mainly influenced by many other factors than CI. Of course, during the short meantime of a volume expansion, these factors can be considered as unchanged.Our results are consistent with previously published studies. EtCOrimental  and clinrimental . Additiopression  or assespression , 26. Twovaluated . As prev2 variation after 500-ml volume infusion was 5.8 %, or an increase of 2 mmHg, which is low, but EtCO2 is a very stable variable if no modification of ventilation or cell metabolism occurs, so even a small change can be significant. This idea is reinforced by the fact that the least significant change (LSC) is smaller than the best threshold for a 500-ml load. Moreover, this is about the same threshold as the previously published one [The threshold value of the EtCOshed one , 12. Aga2 and CI was stronger during PLR than during volume expansion [In previous studies, the correlation between changes in EtCOxpansion , 12. ThrFirst, a passive leg raising is shorter than a fluid challenge. This increases the risk of a confounding factor such as ventilation or metabolism variation to be present.2 and CI is predicted to be weaker when there is no circulatory insufficiency [Second, the study protocol was applied during anaesthesia for a surgery and not in a context of circulatory insufficiency. The link between EtCOficiency .2 could be used as a surrogate for CO changes.Third, the preload increase induced by a mini-fluid challenge is inferior compared with a passive leg raising. Our results concerning the mini-fluid challenge are consistent with a study performed recently in a population of septic patients . From ouAs expected, HR, PP, and MAP variations were unable to predict fluid responsiveness. In a pragmatic approach, with a clinical 10 % tolerance of sensitivity and specificity, as in the grey zone model, we can only conclude for half of the patients. Of course, these results are poorly discriminant. Nevertheless, the discrimination is higher than with parameters mostly used to assess fluid responsiveness as MAP and HR.2 could be explained by variation in VCO2 due to variation in the depth of anaesthesia, but we did not find a significant difference between both groups in the end-tidal anaesthetic agent concentration. We did not use a specific device to monitor the depth of anaesthesia. Nevertheless, end-tidal anaesthetic agent concentration remains the reference to assess depth of anaesthesia [We acknowledge that there are some limitations. The variation of EtCOesthesia .2 variation, and CI variation after a mini-fluid challenge was largely explained by the imprecision of both measurements: in fact, at that same time the mean variation of CI and EtCO2 in the responder group is under the least significant change in the EtCO2 and CI.The weak correlation between EtCOOur patients benefited from protective mechanical ventilation with positive end-expiratory pressure and low tidal volumes for its positive effect . Consequ2 variation after a 500-ml fluid load could be of limited clinical interest according to Ray et al. [The AUC-ROC after a 500-ml fluid load has a lower confidence interval which is below 0.75. Accordingly, our study has not sufficient power to exclude the fact that the AUC in the population is below this limit. Therefore, we cannot exclude the fact that EtCOy et al. .2 production, if no data on cardiac output or pulse pressure variation are available, EtCO2 is the only parameter that was discriminant to assess fluid responsiveness. When the variation of EtCO2 is >5.8 %, all patients were responders, but no conclusion could be done when this variation was <5.8 %. A 100-ml mini-fluid challenge was not discriminant and cannot be used to predict fluid responsiveness regarding the least significant change in the EtCO2. Conversely to widespread belief, MAP, PP, and HR variations were not accurate in predicting fluid responsiveness. The strategy of fluid expansion based on EtCO2 variation could be a part of a haemodynamic optimisation protocol regarding its high specificity and its tremendous advantage upon classical cardiac output monitoring to be non-invasive, at no additional cost, and available in all operating rooms.To conclude in a setting with a constant alveolar ventilation and CO


Antibody drug conjugates (ADCs) are emerging as powerful treatment strategies with outstanding target specificity and high therapeutic activity in cancer patients. Brentuximab vedotin represents a first-in-class ADC directed against CD30-positive malignancies. We hypothesised that its sustained clinical responses could be related to the stimulation of an anti-cancer immune response. We here demonstrate that the dolastatin family of microtubule inhibitors, from which the cytotoxic component of brentuximab vedotin is derived, comprises potent inducers of phenotypic and functional DC maturation. In addition to the direct cytotoxic effect on tumour cells, dolastatins efficiently promoted antigen uptake and migration of tumour-resident DCs to tumour-draining lymph nodes. Exposure of murine and human DCs to dolastatins significantly increased their capacity to prime T cells. Underlining the requirement of an intact host immune system for the full therapeutic benefit of dolastatins, the anti-tumour effect was far less pronounced in immune-compromised mice. When combining dolastatins with tumour-antigen-specific vaccination or blockade of the PD-1/PD-L1 and CTLA-4 co-inhibitory pathways, we observed substantial therapeutic synergies. Ultimately, ADCs using dolastatins induce DC homing and activate cellular anti-tumour immune responses in patients. Our data reveal a novel mechanism of action for dolastatins and provide a strong rationale for clinical treatment regimens combining dolastatin-based therapies, such as brentuximab vedotin, with immune-based therapies.


Fluid administration is always important and difficult during the therapy of patients with sepsis. Accurately predicting fluid responsiveness and thus estimating whether the patient will benefit from fluid therapy seems particularly important. The present study intended to predict fluid responsiveness in patients with sepsis using a bioreactance-based passive leg raising test, and to compare this approach with the commonly used central venous pressure (CVP) approach.This prospective, single-center study included 80 patients with sepsis from the Department of Critical Care Medicine of Zhejiang Hospital. Patients were randomly assigned to either Group A or Group B, with patients of in Group A first taking the passive leg raising test and then taking the fluid infusion test, while patients in Group B followed the opposite protocol. NICOM was used to continuously record hemodynamic parameters such as cardiac output (CO), heart rate (HR) and central venous pressure (CVP), at baseline1, PLR, baseline2, and volume expansion (VE). Fluid responsiveness was defined as the change in CO (ΔCO) ≥10% after VE.P < 0.05); and after VE . The PLR-induced change in CO (ΔCOPLR) and the VE-induced change in CO (ΔCOVE) were highly correlated (r = 0.80 (0.64 to 0.90)), while the CVP and ΔCOVE were uncorrelated (r = 0.12 (-0.16 to 0.32)). The areas under the ROC curves of ΔCOPLR and ΔCVP for predicting fluid responsiveness were 0.868 and 0.514 respectively. ΔCOPLR ≥10% was found to predict fluid responsiveness with a sensitivity of 86% and a specificity of 79%.CO increased during PLR (from 5.21 ± 2.34 to 6.03 ± 2.73 l/ minute, Bioreactance-based PLR could predict fluid responsiveness in patients with sepsis, while CVP could not.


Flow properties of the viscoelastic fluid are discussed through graphs.This study aims to investigate the unsteady boundary-layer flow of a viscoelastic non-Newtonian fluid over a flat surface. The plate is suddenly jerked to move with uniform velocity in a uniform stream of non-Newtonian fluid. Purely analytic solution to governing nonlinear equation is obtained. The solution is highly accurate and valid for all values of the dimensionless time 0 ≤  Boundary-layer flows over flat surfaces are fundamental for the understanding of aerodynamical properties of the flow such as wall friction and the dynamical drag. Due to the boundary-layer theory proposed by Prandtl in 1904  investigBoundary-layer flows over moving surfaces find important industrial applications such as in the manufacturing of food and paper, plastic sheet extrusion, application of coating of paints layers on surfaces, and many other activities . InIn all the abovementioned studies for non-Newtonian fluids, the authors considered steady flow. However, there are many practical applications in which the flow is essentially unsteady. For unsteady problems governed by nonlinear equations, it is very difficult to obtain an analytic solution valid for all time. Perturbation methods are sometimes used to get analytic solution valid for small time –18. CurrIn the present study, we extend the work of Mehmood and Ali  for the y = 0. The fluid occupies the half space y > 0 and at infinity it is assumed that fluid is flowing with the constant free-stream velocity U. Initially, fluid is at rest; then at time t ≥ 0, suddenly plate starts its motion with the constant velocity λU, where λ is the ratio of plate velocity to the free-stream velocity. For an incompressible homogeneous fluid of second-grade type, the Cauchy stress tensor T is related to the deformation field throughp is the pressure, I is the identity tensor, μ is the dynamic viscosity, α1 and α2 are the viscoelastic parameters, and the kinematical tensors A1 and A2 are given byd/dt is the material time derivative and L is velocity gradient. This rheological model was first introduced by Rivlin and Ericksen [Consider the unsteady incompressible flow of second-grade fluid over an infinite plate at Ericksen .Experimental data available for the large number of viscoelastic fluids suggests that, in order to satisfy the thermodynamical analysis, some restrictions must be put on the signs and magnitudes of the material parameters (3)μ≥0, Txx and Txy are the components of the stress tensor given byUnder the above assumptions and conditions, the boundary layer equations governing the unsteady laminar flow of an incompressible viscoelastic fluid due to an impulsive motion of plate are given byt ≥ 0)ν is the kinematic viscosity, ρ is the fluid density, and u and v are the velocity components in the x- and y-directions, respectively. The initial condition (when t < 0) is given byUsing  and 7)  7) in 55 and assf is the dimensionless stream function, α = α1U/ρxν is the local Deborah number, and ′ denotes differentiation with respect to η. Notice that, for α = 0, the above equation reduces to that of the viscous fluid [Introducing the similarity transformations (11)η=Uνequation  readily us fluid .f by the base functionsam,nk are coefficients involved in the solution series. According to the solution expression 13) analyng form:f=∑ked. From , we defiℏ as nonzero auxiliary parameter, we construct the zero-order deformation equation [p is the embedding parameter and obviously, when p = 0 and p = 1,  from f0 to f. Expanding F in Taylor's series with respect to p, and using (Taking equation 20)=ℏ is chosen so properly such that the series (p = 1. Using (Assume that e series  is conve1. Using  and 23)ℏ is chosm-times with respect to p, at p = 0 and then dividing by m!, we obtain the mth-order deformation equation Mathematica.Differentiating the zero-order deformation equations  and 21)21) m-timequationL[fmnditionsfm=0fm* represent a special solution; then the general solution fm can be determined as follows:Ci   are constants of integration which can be determined with the help of boundary conditions  is an approximate solution of the system f ie system . As mentinstance ). In Figf′ is plotted for different values of the viscoelastic parameter α. Clearly, strong non-Newtonian behavior of the fluid results in large skin friction at the solid wall. However, large values of α help in reducing the thickness of the boundary layer. In f′ is plotted for different values of the parameter λ  ). The velocity increases at the plate which causes the skin friction at the plate to reduce. This is due to the fact that, for λ > 0, the plate and the free stream progress in the same direction, but, for λ < 0 when the plate and free stream have opposite direction of progression, the skin friction increases considerably. Finally, the present HAM solution is shown to be uniformly valid for all time 0 ≤ τ < ∞ in the whole spatial domain 0 ≤ η < ∞ in τ = 5 (roughly). This shows that the vorticity diffusion takes place in a very short interval of time.To understand the physics of flow phenomenon, we have investigated the solution through graphs. In α on the boundary layer thickness δ is shown in δ, has a declining behavior with an increase in α. For the low value of α, this drop in δ is less as compared with the high value of α. Such kind of result can be expected because at low values of α our governing equation behaves like that of Newtonian fluid [α, shear stress produced in the flow is not so large so the boundary layer thickness increases. By increasing α, the shear stress will grow more and more and results in the reduction of boundary layer thickness. We can observe such kind of results from the theory of polymeric liquid as well as experimental observations.The effect of viscoelastic parameter an fluid . At the δ decreases by increasing second-grade parameter α.It is noticed that the boundary layer thickness It is observed that as the time passes by, the unsteady velocity reaches the steady state showing that our analytic solution is valid for all the time throughout the spatial domain.λ ) reduces the drag at the plate whereas for λ < 0 the skin friction at the plate increases by increasing |λ|.It is observed that increasing In this study, we have considered the unsteady boundary-layer flow of a viscoelastic fluid over an impulsively started moving flat plate. Fluid at infinity was assumed to be flowing with a uniform free stream velocity. The governing nonlinear equations of an incompressible second-grade fluid are modelled using the similarity transformations. The resulting nonlinear problem is solved analytically with the help of HAM. The influence of various parameters of interest on the velocity profile is graphically illustrated. We find the following observations.


We investigated the role that linguistic abstraction may play in people’s perceptions of gender in spoken language. In the first experiment, participants told stories about their best friend and romantic partner. Variations in linguistic abstraction and gender-linked adjectives for describing their close others were examined. Participants used significantly more abstract language to describe men compared to women, possibly reflecting a gender stereotype associated with the dispositionality factor of linguistic abstraction. In a second experiment, a new group of participants judged the gender of the protagonists from the stories generated in Experiment 1, after the explicit linguistic gender cues were removed. Consistent with the dispositionality factor, linguistic abstraction moderated the effects of the gender stereotypicality of the context  on participants’ gender judgments. Discussion focuses on the implications of the results for the communication of gender stereotypes and the effects of linguistic abstraction in more naturalistic language. For example, some occupations are associated with a particular gender regardless of whether or not the occupation is explicitly gender-linked by adding man to the end of the title  as well as a wider range of implicit, albeit stereotypically gender-linked terms. Implicitly gender-linked adjectives reflect traditional gender-role norms and personality traits on which men and women are expected to differ  to psychological states  to more abstract qualities, such as traits or dispositions  applies to the behavior of groups. Thus, if people perceive one gender’s behavior as more stable or predictable than the other gender’s behavior , then this may be reflected in a direct association between linguistic abstraction and gender in person descriptions and perceptions.Linguistic abstraction can reflect communicators’ thinking, and contribute to recipients’ inferences in two different ways, indicating compliments Y) also tends to be interpreted by listeners as the actor or sentence subject initiating events, whereas the use of the more abstract state verbs , which describe feeling states, tends to make the object in the sentence the causal agent , who were unknown to the recipients, in the same way  linguistic abstraction is used to indicate how expected the information communicated is for the person being described. Linguistic abstraction could be concrete because the protagonist did not conform to gender-role norms, act in line with his or her personality, or behave according to cultural customs in the event described. For various reasons , the recipient may then erroneously use linguistic abstraction to make inferences about some other general attribute of the person—one that is unrelated to linguistic abstraction, because the speaker used a different attribute as the reference point. When the recipient assumes an inappropriate reference point for linguistic abstraction, as is possible in natural language, LEB effects may not be “picked up” by the recipient in a clear-cut way. To our knowledge, no study has examined the effects of linguistic abstraction in more natural language without requesting, and, thus, cuing for particular norm-referenced descriptions, such as gender stereotypes. Further, spoken language is more spontaneous, less carefully considered, and characterized by a smaller degree of complexity in terms of structure than written language  much of the effect of expectation conformity on recipients’ dispositional attributions about groups or individuals, it may also alter, or moderate, the effect of information pertaining to other attributes not used as a reference point for linguistic abstraction on recipients’ inferences. As discussed, linguistic abstraction may also transmit meaning directly, considering the two distinct types of inference  it can elicit.In contrast to previous research into the effects of linguistic abstraction, more natural, spoken language elicited in Experiment 1 provided the basis for text stimuli to be interpreted in Experiment 2. We asked speakers to tell stories about their romantic partner and best friend, expecting that in most cases one of them would be a woman and the other a man . Precisely, the effect of close-other gender on linguistic abstraction should be non-significant, or at least weaker, after controlling for the stories’ level of gender stereotypicality. The LEB holds that linguistic abstraction varies depending on how stereotypical the information communicated is for the group or person being described. As discussed, stereotypical information is described more abstractly than atypical information. Differences in the extent to which men and women are described in gender-stereotypical ways could, therefore, elicit systematic differences in the level of abstraction used in descriptions between these two groups. A direct effect of close-other gender on linguistic abstraction, unmediated by the level of gender stereotypicality, would suggest that the LEB does not explain this effect. Rather, it would be indicative of a gender stereotype implicit in either of the two inferences linked to linguistic abstraction: dispositionality or event instigation.Gender-linked adjectives may also influence the inferences made by the recipients in Experiment 2 about the gender of the person described. Since they fall into one of the categories of linguistic abstraction (the most abstract one), they represent a potential confound in regards to the aims of the experiment, given the focus on gender. Therefore, we also examined the natural occurrence of gender-linked adjectives in the close-other descriptions in this experiment, categorizing them based on their association with traditional gender stereotypes and gender-linked personality traits.Twenty-one undergraduate and seven graduate students, ranging in age between 18 to 41 years, were recruited from various disciplines at two eastern Canadian universities. The majority of participants (82 %) were between 21 and 29 years old. Eighteen of the participants were female and the other ten were male. Both graduate  and undergraduate students  were recruited to provide a greater range of exposure to egalitarian values, which can be expected to vary with the level of education. Even though such education-based exposure may influence the amount of overt sexist language, it is less clear that it will influence more subtle gender distinctions in language. As an incentive, participants’ names were entered into a drawing for a gift certificate.p levels. The length of relationships ranged from 1 to 23 years, with a mean length of 4.79 years (SD = 3.17) for romantic partners and 11.26 years (SD = 5.59) for best friends.All participants were in a close relationship for at least one year with both their best friend and romantic partner, who had to be of different sexes. Data from two additional participants  were not included, as their romantic partners and best friends were of the same sex and, therefore, their use of language to describe female and male close others could not be compared. One male participant’s romantic partner was of the same sex but his best friend was of the other sex. His data were included in the results reported as they met the inclusion criterion of having a best friend and a romantic partner of different sexes. Also, including this case did not affect the observed patterns and significance of Question 1: “How long have you known your partner/best friend?”Question 2: “Tell me what your best friend/partner is like. List a few of their qualities.”Question 3: “How did you meet your partner/best friend?”Question 4: “Tell me a story about your romantic partner/best friend that is a good example of the type person they are.” If necessary: “Can you think of a particular instance as an example of ?”Participants were asked to tell stories about their best friend and romantic partner , thereby eliciting one story of the other sex and one of the same sex. A female experimenter interviewed each participant individually.The purpose of Question 2 was to warm up each participant, to elicit some adjectives for later comparison, and to provide qualities to prompt the participant if necessary in Question 4. Question 3 was asked to elicit a more gender-neutral story, whereas Question 4 was more open-ended. The session took approximately 20 min was videotaped for later transcription.Two independent coders  scored all transcriptions of the interviews. Interpersonal verbs and adjectives pertaining to the close other of the story only  were identified. To look at the more overt referencing of gender, total numbers of the different adjective types  were derived from the answers to both the stories and the request to list qualities of the close others . For the more subtle references to gender, a linguistic abstraction score was obtained from the stories told about the best friend and romantic partner only . Frequently, more than one story was told for Question 4 and even sometimes for Question 3, in which case all stories were examined and included within the different linguistic aggregates. To be able to examine linguistic abstraction in relation to the level of gender stereotypicality, separate abstraction scores were also derived for each story. Only verbs and adjectives associated with a close other were included in the scoring where the close other was a sentence subject. Participants narratives consistently depicted close others as the sentence subject.affectionate, emotional), or neutral . Available classifications of gender-linked adjectives , feminine , interpretive action verbs , state action verbs , state verbs , and adjectives . Thus, descriptive action verbs represent the most concrete word category, and adjectives represent the most abstract word category. Consistent with the “Linguistic Category Model Manual” , and atypical (n = 10) they are, relative to the gender-role norms pertaining to the close other’s gender. Again, the available classifications of gender-linked adjectives , neutral (ives Bem  were usep > 0.05). Therefore, this variable was not included in further analyses. As the number of graduate students recruited was small, data were also collapsed across level of education. Although both women and men share stereotypical beliefs about gender-role behavior  = 26.05, p < 0.001. Hence, the degrees of freedom were corrected using Greenhouse-Geisser estimates of sphericity (ε = 0.61). A significant main effect appeared for adjective type, F = 99.34, p < 0.001, partial η2 = 0.79. Post hoc analyses indicated that participants produced significantly more neutral adjectives in comparison to feminine and masculine adjectives when discussing both men and women (p < 0.05). There were no other significant effects.Table F = 5.35, p = 0.03, partial η2 = 0.17, indicating that participants’ abstraction scores were significantly higher for their descriptions of male close others  compared to their descriptions of female close others .To examine participants’ use of interpersonal verbs and adjectives, a 2 (speaker gender) x 2 (close-other gender) mixed-design ANOVA was conducted on participants’ linguistic abstraction scores. There was a significant main effect for close-other gender, χ2 = 0.63, p = 0.73. Hence, participants did not describe one gender in more stereotypical contexts than the other.Next, it was examined whether the LEB might explain the observed relationship between close-other gender and linguistic abstraction. In particular, we aimed to test whether gender stereotypicality mediates this relationship, with male close others being described more abstractly than female close others due to men being depicted in stereotypical contexts more often. As the stereotypicality of the story was a nominal variable, a chi-square test was used to examine the relationship between the independent variable (gender) and the potential mediator . No significant relationship was found, F = 6.68, p = 0.01, η2 = 0.08, but no other significant main effects or interactions emerged. In total, the level of gender stereotypicality did not mediate the relationship between close-other gender and linguistic abstraction, as it was unrelated to either of these two variables. The final step of the mediation analysis  was therefore redundant.A last 2 (speaker gender) x 2 (close-other gender) x 3  between-design ANOVA was conducted on the stories’ linguistic abstraction scores, to explore if there was a relationship between the possible mediator and the dependent variable . A linguistic abstraction score was not derived for 27 stories, as they contained a limited number interpersonal verbs and adjectives associated with the protagonist or none at all. This analysis was therefore based on the data of 90 stories. The main effect for close-other gender was replicated , The transcripts generated in the present experiment were examined for implicit gender indices manifested in the use of interpersonal verbs and adjectives. Participants did not make overt gender distinctions in terms of their use of gender-linked adjectives, which were unrelated to the gender of their close others. This finding decreases the likelihood of gender-linked adjectives confounding the effects in Experiment 2. As gender-linked adjectives represent a more overt way of indicating gender, participants may have been more careful about their use to avoid appearing sexist, particularly as university students. This possibility may also contribute to the significantly higher number of neutral, rather than gender-linked adjectives in their descriptions of female and male close others. Moreover, there was a possible floor effect for masculine and feminine adjectives, providing additional evidence that people might be more careful about making overt gender distinctions.Other factors to consider may indicate that participants were not trying to control their language. First, there are many more neutral than gender-linked adjectives with which to describe individuals. Second, people are more likely to see familiar people as individuals, rather than in stereotypical ways, as is the case with strangers  had no effect on linguistic abstraction. As the level of gender stereotypicality was unrelated to linguistic abstraction, there was also no evidence that the LEB reflected the consistency of close-other descriptions with gender-role norms .It must be remembered that the LEB has typically been studied at the sentence level, whereas we focused on stories. Thus, linguistic abstraction scores were averages of the occurrence of weighted interpersonal verbs and adjectives in a story, as used by Wigboldus et al. , 2006. IThe gender effect on linguistic abstraction is most likely accounted for by a gender stereotype implicit in one of the two distinct types of inference associated with linguistic abstraction. The present experiment was not designed to assess their relative impact on linguistic abstraction. Nevertheless, since male close others were described in more abstract language than female close others, a stereotype associated with the event instigation factor is an unlikely explanation for this effect. According to this inference, abstract language depicts the protagonist as passive, in contrast to concrete language, which assigns the protagonist a more active role. However, traditional gender stereotypes portray women as being more passive than men and more likely to react to situations, rather than to be the causal agent; men are more likely to display instrumental traits  would provide converging evidence for the presence of such a gender stereotype. Furthermore, linguistic abstraction may not only account for but also influence the effects of protagonist behavior on recipients’ inferences about the person being described. When communicators were asked to provide person descriptions varying in expectancy  on recipients’ perception of that person’s gender. It may be used as an indicator for how typical the information is for the protagonist’s gender, whether intended or not. Theoretically, people may be less inclined to perceive a protagonist of an unknown gender who is described in a feminine or masculine context as female or male, respectively, when the language used is relatively concrete. These possibilities were examined in Experiment 2.protagonists). For this purpose, all explicit gender cues of the protagonist and the speaker were removed from the stories. Participants were given the edited transcripts to read and asked to judge how likely the protagonist’s gender is male versus female, using a single continuous scale. The relationship of these gender judgments with linguistic abstraction, the gender stereotypicality of the context, and gender-linked adjectives used was determined. Additionally we wanted to test whether linguistic abstraction had an incremental predictive effect over gender-stereotypical content and gender-linked adjectives. This observation would indicate that linguistic abstraction is directly associated with gender judgments, reflecting a possible gender stereotype. Consistent with the effect observed in Experiment 1, we made the following hypothesis:Hypothesis 1: On the gender-judgment scale, participants will be more likely to rate the gender of a protagonist described in relatively abstract interpersonal language as male rather than female. Conversely, linguistic abstraction in protagonist descriptions should correlate negatively with participants’ likelihood of rating the protagonist’s gender as female.The second experiment investigated how linguistic abstraction might be related to recipients’ perception of the close others’ gender  on participants’ gender judgments: Participants’ gender judgments will be less likely to match the stereotypicality of the story context for stories described at a lower level of abstraction. By contrast, for stories described in more abstract language, participants’ gender judgments will be more likely to correspond to the story context’s gender stereotypicality.We also examined if linguistic abstraction influences the effect that gender stereotypicality of context had on participants’ gender judgments. Although a moderation effect of this kind can be inferred from the impact of linguistic abstraction on recipients’ inferences  identified themselves as female and 52 participants ranged in age from 18 to 20 years (87 %). Participants were also predominately Caucasian and middle-class. They participated in exchange for partial course credit.N = 117 stories) were randomly divided into one of three questionnaires, as there were too many stories for a participant to read through them all. The numbers of stories per questionnaire were 33, 40, and 44, as speakers rather than individual stories were randomized across questionnaires. A check on the gender stereotypicality of story context across the three questionnaires revealed a relatively even distribution, χ2 = 1.67, p = 0.80. The respective numbers of readers, or judges, per questionnaire were 21, 21, and 18. All explicit gender-identifying language indices for the protagonist and speaker were changed to make the information gender-neutral. For example, the most common changes were to replace proper names with an X and pronouns with either an X or he/she. After reading each story, participants were asked to rate the gender of the protagonist on a 5-point Likert scale, with 1 being obviously male, 3 being could be male or female, and 5 being obviously female. Participants took approximately 45 min to complete a questionnaire.All of the stories told by speakers during Experiment 1 , 2 , and 3 . The linguistic abstraction scores derived for each story in Experiment 1 (possible range: 1–4) were used in the present experiment. As explained in Experiment 1, a linguistic abstraction score was not derived for 27 stories and, therefore, the main analysis involving linguistic abstraction was based on the data of 90 stories. Linguistic abstractions scores had an average that was near the scale midpoint of 2.5  and ranged from 1.25 to 4.00. The role of participant gender and other participant characteristics could not be examined, since the gender-judgment scores of the stories were averages across the participants who read the stories.The typicality classifications from Experiment 1 were recoded into three types of gender stereotypicality: 1 (r(90) = −0.12, p = 0.26. In terms of adjectives types, participants’ gender judgments were significantly associated with the total of masculine adjectives, r(117) = −0.33, p < 0.001, whereas they did not correlate with the total of feminine, r(117) = −0.06, p = 0.53, or neutral adjectives, r(117) = 0.06, p = 0.49. Chi-square tests were executed to explore for possible relationships between gender stereotypicality with the other categorical variables of protagonist and speaker gender. This allowed us to evaluate the validity of our gender stereotypicality classifications and assess speaker gender for any confounding effects. These analyses indicated a significant association of gender stereotypicality with protagonist gender, χ2 = 23.79, p < 0.001, but not with speaker gender, χ2 = 1.85, p = 0.40. Male protagonists were more likely to be depicted in masculine contexts (n = 27) than female protagonists (n = 5), whereas female protagonists (n = 20) were more depicted in stereotypically feminine stories than male protagonists (n = 5). The same numbers of female (n = 30) and male (n = 30) protagonists were depicted in gender-neutral contexts.There was no significant zero-order correlation between linguistic abstraction and gender judgments, F = 28.30, p < 0.0001, partial η2 = 0.34. Bonferroni-adjusted pairwise comparisons revealed significant differences between all types of gender stereotypicality (p < 0.001). Specifically, stereotypically feminine stories had significantly higher scores  indicating that the protagonist was rated as more likely to be a woman compared neutral  or male stereotypical stories . Likewise, male stereotypical stories had significantly lower judgment scores, indicating that, on average, participants rated the protagonists as more likely to be men. Repeating the analysis with speaker gender in place of protagonist gender revealed no additional main or interaction effects. One-sample t tests showed that the gender-judgment scale means were significantly different from the scale midpoint of 3 for all story types: stereotypically male, t(31) = −10.00, p < 0.0001, neutral, t(59) = −3.05, p = 0.003, and female stories, t(24) = 5.09, p < 0.0001.Table F = 25.38, p < 0.0001, R2 = 0.60, the only significant predictors were protagonist gender and the interaction term of gender stereotypicality and linguistic abstraction. The significant change in R2 explained by the interaction was 0.03 (F = 7.20).Table t = −0.46, p = 0.64.t = 3.04, p = 0.003, and feminine stories, β = −0.71, t = 3.68, p < 0.001, which were significantly more likely to be rated as having a female protagonist when linguistic abstraction was high.Figure The present experiment examined if linguistic abstraction (a) is directly associated with the perceptions of the protagonists’ gender in spoken language, and (b) moderates the effects of context gender stereotypicality on gender judgments. The results confirm our gender stereotypicality classifications from Experiment 1. Participants rated protagonists of female-stereotypical stories as more likely to be female, whereas protagonists of male-stereotypical stories were rated more likely to be male. In a preliminary analysis of variance, protagonist gender did not have a significant incremental effect on participants’ gender judgments over gender stereotypicality and did not interact with gender stereotypicality. Protagonist gender was only significant in the regression analysis, as the effects of gender stereotypicality were moderated by linguistic abstraction and possibly also affected by the inclusion of masculine adjectives. These initial results suggest that participants based their gender judgments largely on the overall story context, also supporting our decision to code the stories’ context for gender stereotypicality rather than isolated behaviors of the protagonists.Based on the finding in Experiment 1 that men were described using more abstract language than women, it was hypothesized that participants in Experiment 2 might use linguistic abstraction alone to help judge the gender of the story protagonists. However, linguistic abstraction did not predict incremental variance in gender judgments, let alone correlate significantly with gender judgments in the expected direction. The results, therefore, do not provide converging evidence for a gender stereotype directly implicit in linguistic abstraction, either in the dispositionality or event-instigation factor. A possible explanation is that, unlike the speakers, recipients were specifically cued for gender. Consequently, they may have directed their attention to a multitude of gender indices, many of which may be heuristically more reliable and convenient than linguistic abstraction.Although linguistic abstraction by itself seemed to have no independent effect on the perception of gender, it interacted with gender stereotypicality to influence gender judgments. This result provides general support for Hypothesis 2, indicating that linguistic abstraction moderated the effects of gender-stereotypical content on participants’ inferences. However, there were important differences between the predicted and observed structure of the interaction. An unpredicted observation is that, for stories described in very concrete language, participants seemed to be less certain that the gender of the protagonists matched the gender stereotypicality of the stories’ context. This result is in line with Hypothesis 2 and research demonstrating that individuals use linguistic abstraction to indicate certainty about what a person is like and make dispositional inferences , it is uncertain to what extent these gender-based variations in linguistic abstraction shape recipients’ perceptions of the semantic content, as linguistic abstraction had no independent effect on their inferences. Still, recipients used linguistic abstraction as a means to judging the protagonist’s gender for stereotypically feminine, but not masculine stories. Therefore, people may use subtle linguistic features differentially in forming their impression about men and women, which speaks to the persistence of gender-biased processing of information in Western culture. Possibly, these gendered and therefore schematic ways of processing information operate below the level of awareness of the speaker or the recipients.The moderating effect of linguistic abstraction also has implications for understanding its role in everyday language. Previous research has shown that linguistic abstraction can explain how expectation conformity is indicated, and the inferences drawn by recipients  and if people view men’s behaviors as more stable and predictable than that of women. More generally, further research is needed to investigate the use and effects of linguistic abstraction in natural language. It remains relatively uncertain under what circumstances and through which particular mechanisms linguistic abstraction shapes the impressions of the perceiver.In regards to future research designs, it will be important to address the issue of independence amongst stories when examining their effects on recipients’ inferences. In addition, future studies in this area should also address the implications of recipient gender and the potential role of the gender of the interviewer. People’s language changes depending on the gender of their conversational partner (Fitzpatrick et al.


Taiwan). Recently, cancer screening based on multiple serum tumour markers has been frequently discussed. However, the risk–benefit outcomes appear to be unfavourable for patients because of the low sensitivity and specificity. In this study, cancer screening models based on multiple serum tumour markers were designed using machine learning methods, namely support vector machine (SVM), AFP, CEA, CA19-9, CYFRA21-1, and SCC were determined for 20 696 eligible individuals. PSA was measured in men and CA15-3 and CA125 in women. A variable selection process was applied to select robust variables from these serum tumour markers to design cancer detection models. The sensitivity, specificity, positive predictive value (PPV), negative predictive value, area under the curve, and Youden index of the models based on single tumour markers, combined test, and machine learning methods were compared. Moreover, relative risk reduction, absolute risk reduction (ARR), and absolute risk increase (ARI) were evaluated.To design cancer detection models using machine learning methods, CYFRA21-1 and SCC were selected for women, and all tumour markers were selected for men. SVM and KNN models significantly outperformed the single tumour markers and the combined test for men. All 3 studied machine learning methods outperformed single tumour markers and the combined test for women. For either men or women, the ARRs were between 0.003–0.008; the ARIs were between 0.119–0.306.Machine learning methods outperformed the combined test in analysing multiple tumour markers for cancer detection. However, cancer screening based solely on the application of multiple tumour markers remains unfavourable because of the inadequate PPV, ARR, and ARI, even when machine learning methods were incorporated into the analysis. Several tools based on tumour markers have been developed for cancer risk management. However, each tumour marker test has been developed and validated for a specific category of anticipated cancer. In clinical practice, such tests are widely used in monitoring response to cancer treatment, but there is a lack of evidence supporting their use for screening multiple cancers. However, in certain areas of the world (e.g. Taiwan), people who fear of getting cancer often ask their clinicians to perform a combined set of common tumour marker tests to determine the likelihood of cancer development. In most cases, screening tests reveal no serologic sign of malignancy; however, some tests reveal suspicious results requiring further cancer surveying, with some patients were finally receiving a cancer diagnosis. In the literature, though lacking of evidence to be a screening tool, several studies have proposed that a panel of multiple serum tumour markers is probably more convenient and cost-effective for screening cancers in certain contexts because the cost of testing kits has decreased and the automated panel of testing has improved in recent years –8. The tConventionally, according to the individual threshold value of tumour markers, the algorithm of the combined test would alarm patients with any one elevation of such tumour markers , 2, 7, 8k-nearest neighbour (KNN), and logistic regression (LR) models, have received considerable attention in various medical applications over the past decades. Supervised machine learning methods can predict the class of an unknown case by generating a classification model from a set of training samples with a known class label. Multiple tumour markers subjected to the aforementioned machine learning methods have been proven to be superior to the combined test for diagnosing specific cancer types [Recent studies have explored the application of machine learning methods in medical decision fields, including cancer risk prediction and aiding medical diagnosis , 9. Seveer types . Severaler types , 11. HowTherefore, we proposed that computational analysis techniques using the supervised learning methods SVM, KNN, and LR could probably develop classifiers for screening cancers by multiple tumour markers test. In this paper, we elucidate their efficiency and compare the performance of SVM, KNN, and LR models.This retrospective study was approved by the Ethics Committee of Chang Gung Memorial Hospital IRB no. 104-4097B). Patient records were anonymised and de-identified prior to the analysis. We included 21 614 (9710 men and 11 904 women) apparently asymptomatic individuals who had at least once voluntarily undergone an out-of-pocket tumour marker panel test between March 2003 and December 2012 consecutively at the Linkou branch of Chang Gung Memorial Hospital [04-4097B.Subsequently, a ratio of 2:1  was used to randomly allocate individuals to the training or validation set. All randomisations were performed using Matlab . For the men, 67 cases of newly diagnosed cancer and 6128 noncancer cases were randomised to the training set. Moreover, for the training set, random undersampling was applied  because P < .05 were considered statistically significant.To evaluate the importance of each tumour marker in the screening of cancers, a multivariate LR analysis of the tumour markers was performed for both sexes. Analyses were performed using SPSS . The continuous variables of all individuals were input to evaluate the significance. Results with 26− 1 = 63) were evaluated for men and 127 (27− 1 = 127) for women. Each combination was evaluated using an LR classifier. To evaluate the performance of the classifiers, training and validation data sets were randomly constructed with a ratio of 2:1. The evaluation was repeated 100 times for each combination, and the Youden index values for each combination were averaged and compared. Only combinations with the highest averaged Youden index for each specific number of tumour markers were listed and compared. The appropriate combination of tumour markers for men and women were then used in the following experiments.Using multiple variables in machine learning methods does not necessarily improve the prediction performance. The Youden index was used as a performance indicator for selecting the variables used in the classifier models in this study. The Youden index, which is among the most widely used performance indicators in biomedical studies, is calculated using the following formula: Youden index = Sensitivity + Specificity − 1. In this study, 6 and 7 tumour markers were analytically measured for the men and women, respectively. Therefore, 63 tumour marker combinations  and γ . In this study, the RBF kernel was selected. Previous research has proven that the RBF is superior to the linear kernel or sigmoid kernel in nonlinear classification problems such as cancer diagnosis [c and γ were determined through an iterative grid search by 5-fold cross-validation in the training set, as detailed in previous studies [In this study, we considered the binary classification problem. The discrimination ability of an SVM classifier is determined by generating a hyperplane in a high-dimensional space to discriminate the cancer group from the noncancer group. The SVM models used in this study were constructed using a Matlab version of the LIBSVM 3.20 software package, which is the most well-known and widely applied SVM software tool . An effeiagnosis . This wa studies , 16.KNN is an instance-based algorithm used for classification. The KNN models used in this study were constructed using Matlab (MathWorks). In this study, the number of the nearest number was set to 7 according to our preliminary trial. For each case in the validation set, the Euclidean distances from the cases in the training set were calculated. The class categories of the 7 cases with Euclidean distances closest to the validation case were recorded. The class of the validation case was accordingly predicted on the basis of the major class categories of these 7 closest cases.p and q respectively, where p + q = 1. Subsequently, the odds (p divided by q) was used to predict the label of the validation cases. The cases were classified as cancer when the odds were one or more. Otherwise, the cases were classified as noncancer.LR is a widely used and well-established methodology and is one of the most reliable classification methods for binary classification problems. The LR-based classifier was also constructed using Matlab (MathWorks). Training samples were used to determine the coefficients of each variable for the regression function, which was then used to further classify the validation cases. The probabilities of each validation case being classified as cancer and noncancer were set to The receiver operating characteristic (ROC) curve was used to evaluate the performance of the SVM-, KNN-, LR-based cancer screening models and the single tumour markers in panels. ROC curves for all machine learning methods and tumour markers were generated using SPSS . Furthermore, the area under the curve (AUC) was calculated to compare the discrimination abilities of machine learning methods and single tumour markers. Moreover, the performance of these machine learning methods was tested using the validation set. The performance of the combined test was also evaluated. The algorithm of the combined test was based on the threshold of each tumour marker. The thresholds of the tumour markers used in this study were 15 ng/mL for AFP, 5 ng/mL for CEA, 37 U/mL for CA19-9, 3.3 ng/mL for CYFRA21-1, 2.5 ng/mL for SCC, 4 ng/mL for PSA, 35 U/mL for CA125, and 30 U/mL for CA15-3. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and Youden index of the cancer screening models were calculated for the machine learning methods and the combined tests. The 95% confidence interval (CI) of the Youden indices of each method was calculated for further analysis, as detailed in previous studies , 18. Mort test was used to compare the training and validation sets. The Fisher exact test was used to analyse the tumour types of occult cancer cases in the training and validation sets. Results with P < .05 were considered statistically significant. To evaluate the importance of each tumour marker, the standard error (SE) of the coefficients and the mean and 95% CI of odds ratios were calculated for each tumour marker. One-way analysis of variance (ANOVA) with a statistical significance level of 0.05 was used to examine the effects of the different tumour markers combinations on the Youden index values, AUC values of various machine learning methods and single tumour markers, and Youden index values of machine learning methods and the combined tests. The Tukey honestly significant difference post hoc test was used to determine the differences when the null hypothesis of ANOVA was rejected. Results with P < .05 or < .01 were labelled separately. All statistical analyses were performed using SPSS .Data from the training and validation sets were analysed and are represented as the mean (median) ± standard deviation. An unpaired Of 21 614 individuals, 918 individuals were excluded; the remaining 20 696 eligible individuals were included in this study. In the step of random under-sampling, the training sets comprised 134 and 116 cases for men and women, respectively. Moreover, 3097 and 3801 cases for men and women, respectively, were randomly allocated to the validation set at a ratio of 2:1 , as shown in Multivariate LR analysis was performed to evaluate the significance of each variable. Tables Six  and 7  tumour markers were measured for the men and women, respectively. Accordingly, 63 combinations of tumour markers for men and 127 for women were evaluated using the Youden index to select an appropriate combination of variables for constructing effective cancer classification models with the highest sensitivity and specificity. As shown in P < .01), CEA (P < .01), CA19-9 (P < .01), CYFRA21-1 (P < .01), SCC (P < .01), and PSA (P < .01). For the women, the various machine learning methods used in the analysis of CYFRA21-1 and SCC also outperformed the single tumour markers (P < .01), except for CYFRA21-1, as shown in ROC curves and AUC values were used to assess the performance of the various machine learning methods and each tumour marker for cancer surveying  and 6. FP < .01). Moreover, the SVM model attained higher Youden index values compared with the KNN and LR models and the combined test (P < .01). By contrast, for the women (P < .01) compared with the combined tests. Moreover, the SVM model outperformed both the KNN and LR model, as indicated by the significantly higher Youden index (P < .01). Additionally, the ARR, RRR, and ARI are reported in Tables For the men , the SVMhe women , the KNNScreening of cancers has received considerable attention in developed and developing countries owing to the heavy economic and quality-of-life burden caused by cancers. Although testing for multiple tumour markers in cancer screening lacks sufficient evidence for evaluating its effectiveness and it is associated with adverse risk–benefit outcomes, it is widely used in certain areas (e.g. Taiwan). The present study focused on determining whether machine learning methods can improve the discrimination ability of multiple tumour markers for cancer screening. In Taiwan, more than 96% of the population is covered by the National Health Insurance (NHI) program . PatientBecause of the extremely unbalanced data set used in this study, in which the noncancer cases outnumbered the cancer cases by a ratio of approximately 100:1, using an appropriate method for partitioning the data set into the training and validation sets was crucial. Given that most machine learning methods are generally developed for balanced data sets, improved results might be obtained when pre-analysis processing is performed for original data –14. In tThe distribution of a few variables differed between the training and validation sets, as shown in Appropriate variable selection can reduce the number of tumour markers in cancer screening models constructed using machine learning methods. In addition, variable reduction would result in less calculation, leading to less computation-intensive models. For variable selection, multivariate LR analysis and the Youden index were used and compared in this study. Variables significantly associated with the cancer screening outcomes would be selected as appropriate variables in multivariate LR analysis . In thisThe performance of the machine learning methods evaluated in this study was generally higher than that of all single tumour markers Tables  and 6 anBy contrast, for the women, the performance of the machine learning methods, single tumour markers, and combined test was not as high as those for the men. The underlying reasons might be complicated. First, the menstrual cycle may cause fluctuations in multiple endocrines. Studies have described the effect of endocrine levels on the tumour marker levels –27. The The NPVs of all the machine learning methods and the combined test were high Tables  and 8. CSeveral other studies have applied machine learning methods to analyse data from microarrays to screen or diagnose cancers , 30. TheFor clinical consideration, however, the ARRs and ARIs Tables  and 10 iThe machine learning methods investigated in this study outperformed the combined tests in the analysis of multiple tumour markers for discriminating cancer cases from noncancer cases. However, cancer screening based solely on the use of multiple tumour markers remains unfavourable because of the inadequate PPVs, ARRs, and ARIs, even after incorporating the machine learning methods into the analysis.


In cerebrospinal fluid (CSF) the lymphocytic pleocytosis and CD4+/CD8+ ratios at diagnosis of reactivation and after nine days of fingolimod discontinuation remained unchanged. During this time CCR7+ T cells were not observed in CSF. Further research into fingolimod-associated VZV reactivation and immune reconstitution is mandatory to prevent morbidity and mortality associated with this potentially life-threatening condition.Fingolimod, an oral sphingosine 1-phosphate (S1P) receptor modulator, is approved for the treatment of relapsing forms of multiple sclerosis (MS). The interference with S1P signaling leads to retention particularly of chemokine receptor-7 (CCR7) expressing T cells in lymph nodes. The immunological basis of varicella zoster virus (VZV) infections during fingolimod treatment is unclear. Here, we studied the dynamics of systemic and intrathecal immune responses associated with symptomatic VZV reactivation including cessation of fingolimod and initiation of antiviral therapy. Key features in peripheral blood were an about two-fold increase of VZV-specific IgG at diagnosis of VZV reactivation as compared to the previous months, a relative enrichment of effector CD4+ T cells (36%  Varicella-zoster virus (VZV) is a neurotropic α-herpes virus which can cause clinically distinct presentations. Primary infection with VZV occurs naturally during childhood and is characterized by a self-limiting generalized vesicular rash. Reactivation of latent VZV infection in cells of the cranial nerve, dorsal root and autonomic ganglia comprises the second manifestation . The corFingolimod  is a sphingosine-1-phosphate (S1P) receptor modulator, which is approved as oral therapy for relapsing forms of multiple sclerosis (MS). The drug inhibits the egress of C-C chemokine receptor 7 (CCR7)-positive lymphocytes from secondary lymphatic organs including lymph nodes . As a coHere, we report the time course of antibody responses against VZV and immune cell phenotypes in a patient with MS who developed herpes zoster reactivation during treatment with fingolimod. This report provides insights into the dynamics of systemic immune responses during VZV reactivation and immune reconstitution after treatment cessation and antiviral treatment.We report a 30-year-old man who presented with vesicular rash, erythema, pain and allodynia in the dermatome supplied by the first trigeminal nerve in May 2014. He had been suffering from severe holocranial headache for about one week and was taking oral valacyclovir (3.000 mg per day) and cefuroxime (1000 mg per day) since the previous day. Meningeal signs and fever were absent. The diagnosis of relapsing-remitting MS was made in April 2011 according to McDonald criteria after two relapses with dissemination in space . NatalizAfter two months of fingolimod treatment he developed symptoms of herpes zoster reactivation. Probable VZV meningitis was diagnosed on the basis of the clinical syndrome in combination with CSF findings. CSF analysis showed an increased albumin quotient  and a lymphomononuclear pleocytosis of 7 cells/µL. Red blood cells (RBCs) were absent. PCR for the detection of herpes simplex virus (HSV) and VZV in the CSF was negative. Anti-VZV IgG was detected in the serum (3.000 mIU/mL) and CSF (290 mIU/mL), whereas the VZV antibody index (0.7) was negative. He tested negative for antibodies against HSV and Cytomegalovirus (CMV) and positive for anti-Epstein-Barr-Virus IgG in serum and CSF. Fingolimod was discontinued and antiviral treatment was changed to intravenous acyclovir (10 mg/kg body weight tid). Headache, pain and allodynia responded to a combination of acetaminophen and mefenamic acid. CSF re-tap 9 days later revealed persistent pleocytosis (11 cells/µL) and QAlb increase (7.7). Testing for oligoclonal bands (OCBs) was not performed. He was discharged with oral valacyclovir (3000 mg per day) for another two weeks and analgesics. At follow-up in 9/2014 he had remained clinically stable (EDSS 2.0), whereas MRI disclosed several new lesions when compared to April 2014. Treatment with dimethyl-fumarate was initiated in January 2015. An overview of the clinical course, sequential treatments, and sample collection time points is shown in versus DxVZV: 3.000 mIU/mL), and remained increased four months later (2.800 mIU/mL). Serum IgG, serum albumin, and total serum protein assessed from the same samples were unchanged (data not shown).In our patient, changes in the humoral response to VZV reactivation were investigated from frozen serum samples collected on eight occasions. Anti-VZV serum IgG remained stable  ± 259) over a period of almost two years until he developed zoster reactivation B. At thiAbsolute lymphocyte numbers and the CD4+/CD8+ T cell ratio before initiation of fingolimod treatment, after four and eight weeks on fingolimod, and at diagnosis of VZV reactivation did not reveal changes other than those attributable to S1P receptor modulation C. After p = 0.053) and of TEM frequencies in the CD4+ T cell population . The fingolimod-induced T cell redistributions of our case were in line with those from controls with one exception (CD4+ and CD8+ T cells were subtyped according to their expression of CD45R0 and CCR7 into naïve (CD45R0 − CCR7+), central memory , memory effector , and effector (CD45R0 − CCR7−) T cells. After four weeks of fingolimod treatment CCR7+ T cells were reduced in the blood (CD8+CCR7+: 19% (T0)→1% (T1); CD4+CCR7+: 46%→14%) and remained low until diagnosis of VZV reactivation B. T cellxception C,D: the 3/µL compared to 2.2 × 103/µL prior to and 0.5 × 103/µL after one and two months of fingolimod treatment  with a CD4+/CD8+ T cell ratio of 2.4 and 2.7, respectively. B cells were below 3% and NK/NKT cells below 7% at both examinations. Subtyping according to the expression of CCR7 and CD45R0 was only performed at the control tap. CSF T cells consisted exclusively of TEM and effector cells. Nine days after discontinuation of fingolimod CCR7+ T cells were not detected in the CSF which was in contrast to the findings in peripheral blood  before fingolimod treatment was initiated (T0), after four (T1) and eight (T2) weeks of fingolimod treatment, at diagnosis of VZV reactivation (DxVZV), and nine days (DxVZV/9d), four weeks (DxVZV/4w), and four months (DxVZV/4m) post diagnosis of VZV infection. Time points of CSF analysis were DxVZV and DxVZV/9d.For flow cytometry, PBMC were enriched by density centrifugation from venous blood collected in cell preparation tubes . PBMC were stained for 30 min on ice with saturating amounts of antibodies in phosphate buffered saline (PBS) supplemented with 2.5% fetal calf serum. CSF samples were stained with identical concentrations of antibodies. The antibody panel included FITC-labeled anti-CD45 (J33); PE-labeled anti-CD56 (NKH-1) and anti-CCR7 ; ECD-labeled anti-CD3 (UCTH1) and anti-CD45R0 (UCHL1); PC5-labeled anti-CD8 (B9.11); and PC7-labeled anti-CD3 (UCTH1) and anti-CD19 (J3-119). Isotype controls were PE-labeled rat IgG2a  and ECD-labeled IgG1 (P3.6.2.8.1). Unless otherwise specified, all antibodies were purchased from Beckman Coulter . Natural Killer (NK) T cells were identified as CD56+CD3+ lymphocytes and CD4+ T cells as CD3+CD8− T cells. Cells were acquired on a Cytometrics FC500 and analyzed using the Kaluza software .Results of our patient were compared at T0, T1, and T2 with those of four to five other fingolimod-treated MS patients  who had discontinued natalizumab treatment after mean 51 months (range 29–71) because of a positive JC virus (JCV) serostatus (controls). All patients participated in a local scientific study for monitoring immunological changes in MS  and gave written informed consent for publication of results.Our findings show that VZV reactivation in fingolimod-treated patients is associated with a low level systemic VZV-specific antibody response and increased number of effector CD4+ T cells. The immune reconstitution upon fingolimod discontinuation was unexpectedly fast and may have been driven by infection-related triggers counteracting lymph node retention signals. If so, this is of relevance concerning treatment decisions for cessation of fingolimod in case of VZV infection. However, whether these findings from a single case can be generalized remains unclear. Further research into fingolimod-associated VZV reactivation and immune reconstitution dynamics are mandatory to prevent morbidity and mortality associated with this potentially life-threatening condition.


Nature Communications6 Article number: 748110.1038/ncomms8481 (2015); Published 06262015; Updated 02052016The financial support for the work described in this Article was not fully acknowledged. The Acknowledgements should have included the following:This work was supported in part by a grant to H.J.G., B.H. and N.T. (European Union's Seventh Framework Program (FP/2007/2013)/European Research Council (ERC) Grant Agreement 322820).


Epidural analgesia is highly recommended in cancer anorectal surgery. In addition to the fight against pain it provides some benefit in allowing early rehabilitation of patients. One of the risks of this practice is the dural tear creating a cerebrospinal fluid leak (CSF) in the epidural space (EPD). Clinical features the typical positional headache, a procession of various more or less severe symptoms: nausea, vomiting, dizziness, visual or hearing impairment or radicular pain. We report a dural of unusual cause secondary of the obstruction of tuohy catheter by vertebral cartilage. The lumbar post puncture syndrome (LPPS) occurs after a break duro subarachnoid during an epidural puncture creating a cerebrospinal fluid leak (CSF) in the epidural space (EPD). Clinical features the typical positional headache, a procession of various more or less severe symptoms: nausea, vomiting, dizziness, visual or hearing disturbances or radicular pain. The occurrences of circumstances are numerous, we report the case of a dural breach occurred when performing epidural analgesia for digestive cancer surgery of an unusual cause.It is a 46 year old patient without significant medical history and normal weight, admitted to visceral surgery block for sigmoid tumor resection. Epidural analgesia was used for the management of perioperative pain. After installation and commissioning requirement in this kind of anesthetic practice, the realization of the puncture was at L2-L3 by an experienced anesthetist. After introducing the catheter 2-3 cm and removing the plastic core research epidural space using against fluid pressure was started. Bone obstacle was felt and the needle was redirected in a cephalic direction. To the failure of catheterization despite the introduction of the needle tuohy over its entire length, the latter was withdrawn for verification. It was then that we discovered the obstruction of the catheter by a piece of bone cartilage  dural teThe dural tear is one of the most common complications of locating the epidural space. The operator experience is a commonly recognized risk factor. so, if a frequency of about 1% is generally accepted in the research of the lumbar epidural space , 3 have After accidental dural tear, analgesia may be continued by epidural (obstetrics). In case of epidural analgesia, a prophylactic blood patch seems desirable. This observation highlights the importance of greater caution in the progression of the needle tuohy and the verification of permeability of the needle every each bone contact.