Positron emission tomography, most commonly with 18F-fluorodeoxyglucose, is being used for evaluation of tumour response to therapy. Limitations of this method are associated with (1) fluorodeoxyglucose pharmacokinetic properties, (2) the detection system, (3) discrepancies between metabolic and anatomic images, and (4) acquisition standardization. Response to therapy may be evaluated with qualitative (Deauville score), semiquantitative , and quantitative methods . Methods under evaluation include metabolic tumour volume, total lesion glycolysis, and heterogeneity of fluorodeoxyglucose uptake. The development of positron emission tomography scanners that have larger fields of view may facilitate tumour assessment based on kinetic modelling. Increased clinical use of these methods will depend on the development and validation of intuitive and simple analytic tools. Most malignancies incorporate glucose much more than normal tissues. The glucose analogue fluorodeoxyglucose (FDG) labelled with the positron emitter fluorine 18 is the basis of positron emission tomography (PET) scanning in oncological imaging. Glucose and FDG enter the cell via the membrane glucose transporter, and phosphorylation at position number six prevents glucose and FDG from escaping the cell. Unlike glucose, FDG cannot be catabolised in the glycolytic pathway and remains in the form FDG-6-phosphate for the duration that the molecule remains radioactive and visible on PET. The distribution of radiolabelled FDG reflects the biodistribution of glucose and its phosphorylation in the different regions of the body.In 1931, the German scientist Otto Heinrich Warburg showed a relation between the degree of conversion of glucose to lactic acid and tumour growth, and this became the basis of cancer imaging with FDG. The Warburg effect is a complex of biochemical alterations in the neoplastic cell that includes markedly increased aerobic glycolysis in the cytosol and impaired mitochondrial oxidative phosphorylation. The production of adenosine triphosphate by the metabolism of glucose to lactate is caused by up-regulation of several enzymes and transporters  .A small amount of FDG, much lower than obtained with pharmacological doses, may cause a concentration of radioactivity within a tumour that may be detected easily with modern PET computed tomography (PET-CT) or PET magnetic resonance imaging (PET-MRI) devices. The degree of FDG accumulation in healthy tissues may enable the identification of pathological areas in most body regions, with some restriction for organs that have exclusively glucose-based metabolism such as the brain or that participates in FDG excretion such as the kidneys and urinary system.The most common applications of FDG-PET in oncology involve the evaluation of disease extent. For tumours that have high accumulation of FDG, most tumours that exceed the resolution of the acquisition system are visible on PET images except for artefacts. This fact is very important for lymph node localisation, and diagnostic accuracy is greater for FDG-PET scanning than CT or MRI scanning without PET , 7.False negative results with PET scanning may occur with tumour pathologies that have low levels of FDG accumulation such as prostate, stomach, or neuroendocrine tumours. False negative results also may occur with lesions that are below the limits of resolution of the PET scanner  or lesions that are anatomically close to a structure that is moving during the PET examination such as the diaphragm. However, false negative results may be minimised with careful patient selection and awareness of the inherent limitations of the method.False positive results are currently a greater clinical problem than false negative results because many non-neoplastic diseases may have a high level of glucose metabolism, such as infections or inflammatory conditions with lymph node involvement. In addition, physiological activation of muscles, bowels, brown fat, and other normal tissues may cause misleading findings on PET scans. However, false positive results may be minimised with careful patient preparation and experience of the nuclear medicine specialist.Imaging with FDG-PET is useful because of the early and marked reduction in tumour metabolism in response to chemotherapy or radiation therapy. The evaluation of the response to therapy involves the comparison of tests before and after treatment. The FDG-PET scan may detect a treatment response in a very early phase of treatment, and this may enable the identification of chemoresistant tumours that may benefit from alternative treatments. In addition, it may be important to detect residual disease after treatment is completed.Current PET scans are usually performed with PET-CT scanning, but PET-MRI scanners are becoming available. The clinical value of PET-CT is well established, but the benefits of PET-MRI are being evaluated. The ability to detect the photons emitted from the patient is similar, and the quality of metabolic imaging is comparable, between PET-CT and PET-MRI devices. These methods differ primarily in the morphological method of imaging. The PET-MRI scan may provide greater inherent contrast to visualise soft tissues, which could be advantageous in evaluating pelvic tumours and sarcomas, but PET-CT is better for oncological imaging of the lungs. In children, PET-MRI is preferred because of the lower radiation dose than with PET-CT scanning .Nuclear medicine techniques including PET scanning have limitations that differ from other radiographic studies. These limitations are associated with (1) FDG pharmacokinetic properties, (2) the detection system, (3) discrepancies between metabolic and anatomic images, and (4) acquisition standardization.The pharmacokinetic properties of FDG enable a dynamic method of image acquisition. The most important mathematical model to analyse the dynamic PET data is compartmental analysis. The sequential data obtained after administration of the radiotracer,  enable determination of the concentration of radiotracer in the body region. To interpret the PET data, it is assumed that the measured radiotracer can be considered in physiologically distinct compartments. The most common compartmental model for the analysis of PET data is the Patlak plot, a graphical analysis technique that assumes three compartments: the arterial blood compartment, the compartment of radiotracer-free distribution, and the compartment of specific and irreversible binding . QuantitClinical evaluation of dynamic data may be limited because of the need to shorten the time of image acquisition for each patient, the difficulty of arterial blood sampling to evaluate the input function, and the small field of view of the PET scanner (approximately 20 cm). In addition, small differences in time between FDG administration and PET scanning for different scans (before and after treatment) may cause major errors in interpreting radiotracer accumulation.Current PET scanners have a spatial resolution of approximately 4 mm. Radiotracer uptake in lesions that have diameter <3 times the scanner resolution is affected by partial volume effect, which causes loss of apparent activity. For example, in a PET scanner that has spatial resolution 4 mm, the image of a radioactive phantom with 6-mm diameter may show a maximum measured 60 % real activity concentration .Modern PET-CT devices typically require ≥10 min between the initial CT scan and PET image acquisition in more distal body parts. Therefore, misalignment is usually present between metabolic and anatomical images. Furthermore, the acquisition of each PET image requires ≥90 s, and breathing movements make it impossible to quantify accurately the metabolism of lesions near the diaphragm. Acquisition techniques such as PET gating for breathing may be helpful, but these methods lengthen the time of acquisition and data processing and are not used frequently in clinical settings .Standardised acquisition protocols of the European Society for Therapeutic Radiology and Oncology and European Association of Nuclear Medicine include information about the calibration of the PET scanner, radiotracer uptake time, and approach for definition of regions of interests. These protocols are used to derive quantitative parameters from calculated values such as standardised uptake value (SUV) . In contComparative visual assessment of PET images is commonly practised and frequently enables reliable judgements about decreased tumour metabolism after therapy. The correct reconstruction of PET images should be checked in advance. The projected data are detected on every pair of photons originated from positron annihilation forms. A sinogram is a graphic expression of the raw data that enables detection of abnormalities and verification of consistency between pretreatment and control PET scans . HoweverEarly investigation of malignancy by PET was performed with lymphoma, and the earliest systems to assess treatment were proposed for these neoplasms. A variable portion of a lymphoma mass consists of malignant cells, and many patients have residual masses after completion of therapy. Morphological examination is insufficient to exclude the presence of disease in residual masses or early recurrence in normal sized lymph nodes. In addition, the shrinkage of the tumour may occur late after treatment and is a not a proper criterion in early evaluation. In contrast, the metabolic response may be detected after 1–3 cycles of chemotherapy and is correlated with overall and disease-free survival –17.The Deauville score is a popular method for the evaluation of qualitative response to treatment of Hodgkin lymphoma. This score is based on a simple classification of the degree of pathological FDG uptake at the tumour compared with the liver and mediastinum Table  18]. Le. Le18]. In contrast, PET scanning is unsuitable for assessing the activity and extent of tumours that have moderate radiotracer accumulation, such as renal clear cell carcinoma, primary liver tumours, and adenocarcinoma of the prostate .C is the activity at a pixel within the tissue identified by regions of interest, and ID is the injected dose per kilogram of the patient’s body weight (w). The SUVmax may be measured quickly and easily and is affected less by the partial volume effect than mean tumour SUV (SUVmean)  from initial (SUVmax1) to later scans (SUVmax2) may be calculated as:In addition, the SUV is normalised to a reference activity, typically the FDG uptake by the liver.The reliability of SUVmax measurement is affected by many factors including attenuation correction, scatter correction, respiratory motion, partial volume effect, and tomographic reconstruction. The problem of reliability necessitates highly standardised protocols for PET imaging to provide the same conditions of acquisition and data processing between PET examinations for proper comparisons .The first quantitative criteria to monitor tumours were proposed by the European Organization for Research and Treatment of Cancer (EORTC) in 1999. The EORTC criteria defined tumour response to treatment as changes in SUV > 15 % after the first cycle of chemotherapy; changes in SUV > 25 % afte >1 cycle of chemotherapy; changes in FDG accumulation >20 %; or new foci of pathological FDG uptake .The PET response criteria in solid tumours (PERCIST) is a more detailed classification and requires a more rigorous standardisation for data acquisition and analysis than the EORTC criteria Table  24]. Th. Th24]. Several systems have been proposed to correct for the partial volume effect. These techniques are based on image deconvolution, model-based reconstructions, or the simultaneous assessment of radiographic CT or MR images that are properly coregistered with PET. No system completely eliminates the partial volume effect, but some are valid for improving the precision of SUV measurement in small tumours. These models still are being validated and were not considered in the definition of the EORTC and PERCIST criteria. However, it is important to quantify tumours <2 cm correctly, and partial volume correction methods are being developed –28.Several methodological errors may confound the quantification of tumour metabolism when using the SUV parameter. Therefore, other metabolic indices have been proposed that consider the radiotracer uptake in the entire tumour mass. Radiographic morphological methods cannot quantify the number of malignant cells because there is structural inhomogeneity in neoplastic tissue. However, the uptake of FDG is indicative of the presence of viable tumour cells. Therefore, PET may be used to estimate the volume of biologically active tumour (metabolic tumour volume).The main problem in quantifying metabolic tumour volume is the definition of the threshold SUV between the viable tumour and background tissue. Tumour contours may be defined manually, but manual segmentation is time consuming and lacks repeatability. Alternatively, the SUV threshold may be calculated as the percent maximal tumour uptake of FDG in tissues surrounding the tumour or other reference organs such as the liver –32. In aThe calculation of metabolic tumour volume is based on the definition of tumour boundaries. Therefore, metabolic tumour volume does not indicate possible differences in the density of neoplastic cells within the tumour. The total lesion glycolysis is the product of the average tumour SUV (which is an index of the density of neoplastic cells) and metabolic tumour volume. The total lesion glycolysis may correlate with overall survival in patients who have lung cancer, colon cancer with liver metastasis, and non-Hodgkin lymphoma Fig.  40–43].–43.40–43In addition to the volumetric parameters, additional features may be extracted from PET images by computational methods such as tumour texture and heterogeneity . The hetIt is feasible to perform early measurement of the effect of therapy on cancer, and functional tomographic techniques such as FDG-PET may be useful in addition to morphological imaging methods. The accuracy in measuring tumour response is limited by the difficulty in performing dynamic analysis of tumour metabolism after the radiopharmaceutical agent is given. Tumour activity may be affected by many variables about the patient and conditions of data acquisition. The development of PET scanners that have larger fields of view may facilitate tumour assessment based on kinetic modelling. In addition, signal degradation because of the partial volume effect may limit the evaluation of small lesions. Measurement error may be decreased by validating correction algorithms and integrating these algorithms with response criteria such as EORTC and PERCIST. Models that are based on total lesion glycolysis or tumour heterogeneity may be useful in selected patients. Increased clinical use of these methods will depend on the development and validation of intuitive and simple analytic tools.


These data confirm the temperature-dependent Li isotopic fractionation between hydrothermal quartz and fluid  + 22.22), which suggests that the fluid inclusions are in equilibrium with their hosted quartz, thus allowing to determine the composition of the fluids by using δ7Liquartz data. Accordingly, we estimate that the ore-forming fluids have a δ7Li range from −0.7‰ to +18.4‰ at temperatures of 175–340 °C. This δ7Li range, together with Li–O modeling , suggest that magmatic fluid played a significant role in the ore formation. This study demonstrates that Li isotope can be effectively used to trace magmatic fluids in a seafloor hydrothermal system and has the potential to monitor fluid mixing and ore-forming process.Lithium isotopic compositions of fluid inclusions and hosted gangue quartz from a giant volcanogenic massive sulfide deposit in China provide robust evidence for inputting of magmatic fluids into a Triassic submarine hydrothermal system. The δ Lithium isotope has proven to be an important geochemical tracer for fluid-related processes, particularly aqueous fluids, volatiles, and metals in magma-hydrothermal systems, because of chloride-complexed behavior of lithium in aqueous fluids6The submarine hydrothermal fluids affect mass balance of the hydrosphere2In this study we first report Li isotopic compositions of the Gacun Zn-Pb-Cu deposit, a giant volcanogenic massive sulfide deposit in the Yindun arc-basin system10We have assessed a submarine hydrothermal system by a study of Li isotope on quartz and hosted fluid inclusions from the Gacun deposit, formed by Triassic submarine hydrothermal fluids107Li range from +1.0‰ to +2.3‰, similar to continental crust (δ7Li = +1.2 ~ +1.7‰)7Li values from a rhyolitic dome (+1.2‰) and the LSO host rock (+3.4‰) to MSO host rock (+8.8‰) upwards  yield a range of δ7Li values from +3.7‰ to +15.0‰ , the corresponding fluids (n = 12) have relatively high δ7Li varying from +1.3‰ to +10.2‰  of fluid inclusions in analyzed quartz 18O values of the fluids were estimated to vary from +0.9‰ to +8.7‰, showing a gradual decrease from a rhyolitic dome (av. +7.6‰), through the LSO (av. +7.1‰) and MSO (av. +5.4‰), to the UMO (av. +2.8‰).All analyzed quartz samples (n = 53) were measured for O isotopic compositions, which yield δd +16.4‰ . Based od quartz , using t7Li values of both fluid inclusions and host quartz were obtained for 17 pure-quartz samples, which yield Δδ7Liquartz-fluid values of +1.1 − +7.6‰  + 22.22 . The Δδ7Liquartz-fluid shows a strong temperature- dependent fractionation.The δ − +7.6‰ . Extensio +13.8‰ , and sho and 1/T , which cet al. (2005)21et al. (2005)et al. (2006)Recent experiments on distinct mineral-fluid systems give conflicting results on Li isotopic fractionation between fluids and minerals. Lynton et al. 05202122.7Li difference should exist in both hosted quartz and fluid after the entrapment of fluid inclusions, and the measured results  should be consistent with the traditional theory of stable isotopes: heavier isotope tending to enter into the liquid phase, due to diffusive transport in millions of years. Moreover, as this difference is often uncertain, a good correlation with the temperature is lacking. However, our data indicate that fluid inclusions were strongly lighter than their hosted quartz, and show a strong correlation between Δδ7Liquartz-fluid and 1/T  that contain secondary inclusions and failed in δsured Th , using ad +18.4‰ .7Liquartz-fluid, varying from −6.7‰ to −0.5‰ (7Liquartz’ of quartz + sericte group (n = 12) is a mixing value, due to intermingling with minor sericite. The ‘δ7Liquartz’ tends to lighter than that of pure-quartz, because δ7Li of micas tends to lighter7Li (+1.3 to +10.2‰) of the fluids extraced from quartz-sercite samples, therefore, could represent the δ7Li values of the ore-forming fluids at Gacun.It is noteworthy that the quartz + sericte group (n = 12) yields distinct Δδto −0.5‰ . The ‘δ77Li (–0.7‰ to +18.5‰) than active vent fluids in 11°–13° EPR (+8.1‰ to +10.9‰)Our data above indicate that the Gacun ore-forming fluids are estimated to have a wider range of δ7Li with increasing in interaction depths and fluid temperatures, and predicts that the seawater reacted at the lowest water/rock ratios has the lightest δ7Li values7Li signature (<4‰) of the Gacun fluids, because experiment7Li down to <4‰. Moreover, the lightest δ7Lifluid values mostly cluster within or near a feeder zone at Gacun  hot fluid or brine interacted with the subvolcanic rock. The formation of such low-δ7Li brine (fluid) requires an anomalously high temperature (>500 °C)18O enrichment of the Gacun hydrothermal systemThe sources of these vent fluids have been attributed to (1) progressively interacting seawater, passed through the hot rocks downward and heated by magma chamber20at Gacun , where nat Gacun , and th 7Li of both residual melts and exsolving fluids do not change significantly with progressive fluid exsolution7Li: +1.0‰ to +2.3‰), we estimate that the δ7Li values of initial fluid exsolving from a rhyolitic melt vary from +1.0‰ to +3.0, close to the lowest measured δ7Li values for the LSO. This means that variation in δ7Lifluid (- 0.7 to +18.5‰) observed at Gacun may be caused by other processes, such as interacting with marine sediments (δ7Li = −1.0 ∼ +24‰)327Li = +31.5‰)247Lifluid data may be interpreted by a binary mixing between magmatic fluid and seawater, which is supported by Li–O isotopic system at Gacun  and low δ18Ofluid (+0.9‰ to +4.9‰), implying more seawater contribution, whereas the LSO within the dome yields lower δ7Lifluid (0 to +6.5‰) and higher δ18Ofluid (+6.9‰ to +8.7‰), recording the footprint of magmatic fluids (magmatic/Liseawater mass mixing ratios (magmatic/Liseawater mixing ratio for the UMO (1.5:1 to 5:1), much lower than those for the LSO (5:1 to 20:1). The highly variable ratios are probably controlled by the chemical compositions of the degassed magmatic fluids, which changes with the magma evolutionDfluid/melt) increases with temperature, the mole fraction of H2O, and the concentration of Cl in the fluids2-rich multiphase inclusions, whereas ones from the UMO (av. 200 °C) host liquid-vapor two-phase aqueous inclusions at Gacun2 with H2O to H2O-dominated with time, which is consistent with compositional trend produced by successively degassing of the evolving magma42/H2O ratios in the fluid for the LSO likely resulted in low Li concentrations in the magmatic fluid, whereas higher concentrations of H2O and Cl in the fluid for the UMO probably lead to stronger Li partitioning into the fluid (7Li of +3‰ and δ18O of +8‰7Li (~ + 26‰) of Mesozoic seawater than modern seawater37ore zone . The UMOc fluids . Li–O mig ratios . This twid 0 to +.5‰ and hhe fluid . Assuminseawater) in the ore-forming fluid system shows the outline of a Triassic submarine hydrothermal system at Gacun . The estimated δ7Li values (−0.7‰ to +18.4‰) for the ore-forming fluids suggest a significant role of magmatic fluids in the ore formation. Our data show that combination of δ7Li with δ18O data could monitor the mixing of fluids associated with ore formation and help to locate the particularly mineralized horizons.The Gacun deposit yields δet al. (2004)et al. (2012)Li concentrations and isotopic ratios of quartz and hosted fluid inclusions were measured using an atomic absorption spectrophotometer (AAS) and a double focusing multicollector inductively coupled plasma mass spectrometer (MC–ICP–MS) at the MLR Key Laboratory of Metallogeny and Mineral Assessment, Institute of Mineral Resources, CAGS, China, following Rudnick 3) on a hot plate (T < 120 °C) for 3 hours. Then distilled-deionized water is used to clean quartz grains, until the conductivity of leachates is consistent with that of deionized water (>18.2 MΩ cm resistivity). The cleaned quartz grains were dried and grinded to be fine powders  using an agate mortar in ultraclean cabinet. The leachates were extracted by fine powders in 30 ml of deionized water , centrifuged, and then filtered using nylon filters with 0.22 μm pores (remove silica powder). Based on traditional textural analysis of fluid inclusion populations and homogenization temperatures, primary inclusions of magmatic origin dominate the quartz samples selected for the grind-leach analysis (>90%). The fluid inclusion leachates were dried and re-dissolved in 4 M HCl, in preparation for chromatographic separation.Fluid inclusions were extracted by the crush and leach method at the MLR Key Laboratory of Metallogeny and Mineral Assessment, Insititute of Mineral Resources, CAGS. Before extracting fluid inclusions, approximately 4 g of handpicked quartz grains  were heated in chloroazotic acid (a ~3:1 mixture of HCl-HNO3-HF (about 1g sample in 0.5 mL HNO3 +5 mL HF) in savillex screw-top beakers overnight on a hot plate (T < 120 °C), followed by replenishment of the dried residua with concentrated HNO3 overnight and dried again, then picked up in concentrated HCl until solutions were clear. The solutions were then dried down and re-dissolved in 4M HCl, in preparation for chromatographic separation. Purification procedures with three columns were described by Tian et al. (2012)7Li value of each unknown was calculated relative to the average of two bracketing IRMM-016 runs. Results of IRMM-016  agree with previously published data et al., 2006b)Dried quartz fine powders were dissolved in a mixture of concentrated HNOet al. (2014)5 to produce O2, SiF4 and BrF5 were separated from O2 by liquid nitrogen. At 700 °C, the O2 reacted with kryptol and was converted into CO2, which was collected in a sample tube. Oxygen isotope ratios were measured using a Thermo Finnigan MAT 253 mass spectrometer. The results are expressed in δ with V-SMOW as standards, as follows: δ18OV-SMOW = [(18O/16O)sample/(18O/18O)V-SMOW −1] × 1000. The analytical precisions of δ18O measurements were 0.2‰ (1SD), based on repeated measurements of standard samplesThe O isotopic compositions of quarz were analyzed at the Laboratory of Isotope, CAGS (Beijing). Single quartz grains were separated for oxygen isotope measurements. The analytical procedures of O isotopes are following Clayton and Mayeda (1963)How to cite this article: Yang, D. et al. Lithium isotope traces magmatic fluid in a seafloor hydrothermal system. Sci. Rep. 5, 13812; doi: 10.1038/srep13812 (2015).


Patients who are potential candidates for breast conservation surgery following neoadjuvant chemotherapy have their tumours marked with a maker clip to guide surgery. Some of the breast cancers are associated with microcalcification. So far we have not seen any publication showing the potential use of tumour-associated microcalcification, which could be used as marker of the tumour bed instead of a marker clip. We present prospective case series where microcalcification associated with tumour had been used to guide surgeryThirty-eight patients with breast cancers underwent neoadjuvant chemotherapy between 1 December 2012 and 7 May 2014 at a single institute. At the end of chemotherapy 16 patients underwent successful breast-conserving surgery (BCS). Nineteen patients' tumours were associated with microcalcification.Of the patients who underwent successful BCS, seven had tumour-associated microcalcification. In six of these patients the tumour-associated microcalcification was solely used as a marker of the tumour bed. In one case, due to the presence of few tiny eccentric specks of microcalcification associated with the tumour, it was decided to place a maker clip. In all seven cases, tumour-associated microcalcification was readily apparent during localisation.Traditionally, placement of commercially available markers clips (costs around £55 per clip) is recommended for patients considered suitable for BCS following neoadjuvant chemotherapy. Albeit a small series, our experience demonstrates that tumour-associated microcalcification will still be apparent after completion of neoadjuvant chemotherapy and as such can be used as a marker of the tumour bed, thus saving costs associated with clip placement.


The publisher apologizes for this error.The first and last names for the second and the fifth authors were inadvertently switched. The first name appears as the last name and the last name appears as the first name. Zhao Xinwang should be Xinwang Zhao and Tu Jinxing should be Jinxing Tu. The correct citation is: Bu SH, Zhao X, Yi C, Wen J, Tu J, Zhang YM (2015) Interacted QTL Mapping in Partial NCII Design Provides Evidences for Breeding by Design. PLoS ONE 10(3): e0121034. doi:There are errors in the author contributions. The initials for Xinwang Zhao should be XZ and the initials for Jinxing Tu should be JT.soyzhang@mail.hzau.edu.cn.An additional email address for the corresponding author is missing. The additional email address is:


Fluid resuscitation is a key intervention in patients with sepsis and circulatory impairment. The recommendations for continued fluid therapy in sepsis are vague, which may result in differences in clinical practice. We aimed to evaluate associations between hospital and patient characteristics and fluid resuscitation volumes in ICU patients with severe sepsis.We explored the 6S trial database of ICU patients with severe sepsis needing fluid resuscitation randomised to hydroxyethyl starch 130/0.42 vs. Ringer’s acetate. Our primary outcome measure was fluid resuscitation volume and secondary outcome total fluid input administered from 24 hours before randomisation until the end of day 3 post-randomisation. We performed multivariate analyses with hospital and patient baseline characteristics as covariates to assess associations with fluid volumes given.We included 654 patients who were in the ICU for 3 days and had fluid volumes available. Individual trial sites administered significantly different volumes of fluid resuscitation and total fluid input after adjusting for baseline variables (P<0.001). Increased lactate, higher cardiovascular and renal SOFA subscores, lower respiratory SOFA subscore and surgery were all independently associated with increased fluid resuscitation volumes.Hospital characteristics adjusted for patient baseline values were associated with differences in fluid resuscitation volumes given in the first 3 days of severe sepsis. The data indicate variations in clinical practice not explained by patient characteristics emphasizing the need for RCTs assessing fluid resuscitation volumes fluid in patients with sepsis. For decades fluid resuscitation has been considered a pivotal intervention in the treatment of patients with sepsis and circulatory impairment. The hemodynamic consequences of sepsis are complex and several pathophysiological characteristics serve as rationale for fluid administration including dehydration, increased vascular permeability leading to decreased intravascular fluid volume  and decrThe optimal volume of fluid and indications for fluid resuscitation in severe sepsis are not established. Fluid resuscitation guided by central venous pressure in the first six hours of septic shock was a part of the protocol in the landmark trial of Early Goal-Directed Therapy (EGDT) in sepsis by Rivers et al that showed significantly increased survival with EGDT . Since tThe lack of firm evidence and vague recommendations may infer differences in clinical practice. The aim of this study was to investigate whether hospital characteristics adjusted for patient baseline characteristics were associated with differences in fluid resuscitation volumes in a multicentre randomised clinical trial in patients with severe sepsis needing fluid resuscitation. Furthermore, we aimed to describe patient baseline characteristics’ association with fluid resuscitation volumes.This was a retrospective analysis of data from the Scandinavian Starch for Severe Sepsis and Septic Shock (6S) trial. In the 6S trial adult patients with severe sepsis and need of fluid resuscitation were randomised to resuscitation with hydroxyethyl starch (HES) 130/0.42  or Ringer’s acetate . Patients were randomised in 26 ICUs in Denmark, Finland, Norway and Iceland between December 2009 and November 2011. All non-Danish hospitals were university hospitals and all ICUs were located at different hospitals. Exclusion criteria were: Age < 18 years, treatment with > 1000 ml of any synthetic colloid within the last 24 h prior to randomisation; any form of renal replacement therapy (RRT), severe hyperkalaemia (p-K > 6 mmol/l) within the last 6 h and acute burn injury > 10% of body surface area, previously randomised in the 6S trial, allergy towards HES or malic acid, liver or kidney transplantation during that hospitalization, intracranial bleeding within that hospitalization, enrolment into another ICU trial of drugs with potential action on circulation, renal function or coagulation, and withdrawal of active therapy. Appropriate approvals and written consent from patients and/or legal substitutes were obtained according to national laws. The 6S trial was approved by the Danish Committee on Health Research Ethics. Patient information in the 6S trial database was anonymized and de-identified. No additional patient data were obtained for the present study and an ethics approval for the present study was not required according to Danish law. The protocol and the outcomes have been published –14.In the present study we included all patients randomised into the 6S trial who had available fluid data from 24 hours before randomisation until day 3 post-randomisation, i.e. patients that had not died, had not been discharged and had no missing daily fluid data until day 3 after randomisation. As this was a post hoc study, a convenience sample was used and a sample size calculation was not performed.The primary outcome measure was fluid resuscitation volume and the secondary outcome measure was total fluid input. Fluid resuscitation volume was defined as all masked and open-label trial fluids given in the first 3 days after randomisation in the 6S trial combined with crystalloids (not including fluids with medication) and colloids given from 24 hours before randomisation (day 0). Open label trial fluid (Ringer’s acetate) was administered in case of the maximum dose of 33 ml/kg/24h masked trial fluid was exceeded. If a patient was withdrawn from the trial intervention, then all crystalloids (not including fluids with medication) and colloids given from time of withdrawal to the end of day 3 after randomisation were regarded as fluid resuscitation. Reasons for withdrawal were described in the published protocol . Fluid da priori to include the following patient baseline characteristics in the multivariate analyses: Simplified Acute Physiology Score (SAPS II) [We decided SAPS II) , age, weSAPS II) . The CNSSAPS II) .We performed analyses using a generalised linear model with fluid volumes as outcome. The following model builds were used:Model 1. Hospital characteristics:Fluid volumes ~ Danish hospital (yes/no) + University hospital (yes/no) + patient baseline characteristics .Model 2. Individual trial site :Fluid volumes ~ Trial site (as a factor) + patient baseline characteristicsModel 3. Patient baseline characteristics:Fluid volumes ~ Patient baseline characteristics + Trial site .The patterns of residuals were evaluated for each analysis to ensure adequate goodness of fit. If > 5% of baseline values were missing, multiple imputations of the missing values were performed, which has been reported to reduce risk of bias . For eaca priori to include trial site as a fixed-effect variable. To investigate the impact of this choice, we performed mixed model analyses with trial site analysed as a random-effects variable.Fluids given in the 24 hours prior to randomisation might include fluids given in the general ward where fluid registration was not as meticulous as in the ICU. Therefore, we conducted a sensitivity analysis excluding fluids given prior to randomisation, and another sensitivity analysis including the patients who had been discharged or had died within the first 3 days of randomisation. To investigate the impact of patients who were withdrawn from the intervention during the first 3 days after randomisation, we performed sensitivity analyses excluding these patients. We chose Statistical analyses were performed using SAS version 9.4 . Two-sided P-values of less than 0.05 were considered statistically significant.Of the trial cohort of 798 patients, we included the 654 (82%) patients who had fluid volumes registered from day 0 to 3 . Of the The fluid resuscitation volume given from day 0 to day 3 was median 7,300 ml (interquartile range (IQR) 5,000–10,000 ml); total fluid input was median 16,912 ml . Daily fluid volumes are presented in Individual trial sites administered significantly different fluid resuscitation volumes and total fluid input adjusted by patient baseline characteristics  needed multiple imputations. Complete case analyses did not change results noticeably  in addition to the differences in fluid resuscitation volumes already described. Excluding fluids given prior to randomisation noticeably changed the results for the cardiovascular SOFA subscore and surgery. These findings indicate that these patient baseline characteristics primarily affected the fluid resuscitation administered in the early phase of septic shock, whereas the strong association between higher lactate at baseline and increased fluid resuscitation volume persisted when excluding fluids given prior to randomisation.The present study had several strengths. First, the 6S trial had relatively detailed daily registration of fluid input, which enabled us to differentiate between types of administered fluids. Fluids given with nutrition and medication constitute a large proportion of the fluid input during the first days of severe sepsis, and we were able to exclude these non-resuscitation fluids in our analyses. Second, the 6S trial randomised patients in different types of hospitals in four countries and thus increasing the external validity of our results. Third, the meticulous registration of fluid data resulted in only 0.4% of patients eligible for this study had missing fluid data.There were also limitations. First, patients who had died or had been discharged were not included in the present analyses, which decrease the generalizability of the results. However, the sensitivity analysis including these patients did not change the results noticeably. Second, it is possible that hospitals participating in a randomised clinical trial of fluid therapy (in this case type of fluid) may have a different clinical practice as compared to non-participating hospitals in Scandinavia, thus introducing a potential selection bias. Third, all non-Danish hospitals were university hospitals which makes analyses of potential interaction unfeasible. Fourth, although the statistical assessments of model fits were adequate, there may be clinical considerations when interpreting the results. Especially the renal SOFA subscore should be interpreted with caution as extreme values (e.g. established anuria) might have led the clinicians to withhold further fluid resuscitation.Hospital characteristics adjusted for patient baseline values were associated with differences in the administered fluid resuscitation volumes within the first 3 days of severe sepsis. Increased cardiovascular and renal SOFA subscores and decreased respiratory SOFA subscore at baseline were associated with increased fluid resuscitation volumes. Our data indicate variations in clinical practice not explained by patient characteristics emphasizing the need for RCTs of fluid resuscitation volumes in patients with severe sepsis.S1 Appendix(DOCX)Click here for additional data file.S1 Dataset(SAS7BDAT)Click here for additional data file.


Dr David B. Donner was incorrectly listed as fifth author of this article. The editors have followed up with the authors' institutions, the Universidad de Concepción and the University of California San Francisco, in relation to the contributions to this work.In line with the recommendation by the University of California San Francisco, where the work described in this article was initiated, Dr Donner should be listed as co-corresponding author and placed before Dr Pincheira's name. The author list should be revised to read as follows:☯*, Roxana Pincheira☯*Carlos Farkas, Carla P. Martins, David Escobar, Matias I. Hepp, Ariel F. Castro, Gerard Evan, José L. Gutiérrez, Robert Warren, David B. Donner*Corresponding Authors: donnerd@surgery.ucsf.edu (DBD); ropincheira@udec.cl (RP)In addition, the Funding statement should be revised to acknowledge support to Dr Warren and Dr Donner, the Funding statement should read as below:This work was supported by Academic Senate Individual Investigator Grant from University of California, San Francisco to RP, DIUC grant from Universidad de Concepcion-Chile, and Regular Fondecyt Grant 1110821-Chile to RP. CF was supported by the Regular Fondecyt Grant 1110821-Chile to RP. DE was supported by a PhD fellowship from CONICYT-Chile. RW was supported by a grant by the Edmund Wattis Littlefield Foundation, DD was supported by the National Institutes of Health (NIH) Grant CA67891, a grant from the Cancer Research Coordinating Committee of the University of California and a grant from the Lehman Brothers Research Foundation.The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.


Human polo-like kinase 1 (PLK1) expression has been associated with inferior outcomes in colorectal cancer. Our aims were to analyse PLK1 in rectal cancer, and its association with clinicopathological variables, overall survival as well as tumour regression to neoadjuvant treatment.PLK1 expression was quantified with immunohistochemistry in the centre and periphery (invasive front) of rectal cancers, as well as in the involved regional lymph nodes from 286 patients. Scores were based on staining intensity and percentage of positive cells, multiplied to give weighted scores from 1–12, dichotomised into low (0–5) or high (6–12).PLK1 scores in the tumour periphery were significantly different to adjacent normal mucosa. Survival analysis revealed that low PLK1 score in the tumour periphery had a hazard ratio of death of 0.59 in multivariate analysis. Other predictors of survival included age, tumour depth, metastatic status, vascular and perineural invasion and adjuvant chemotherapy. There was no statistically significant correlation between PLK1 score and histological tumour regression in the neoadjuvant cohort.Low PLK1 score was an independent predictor of superior overall survival, adjusting for multiple clinicopathological variables including treatment. Colorectal cancer is one of the leading causes of mortality in the developed world. Rectal cancers comprise a third of these cases and carry a worse prognosis than colon cancers. In the locally advanced setting, they are treated differently to colon cancers, with trimodality therapy consisting of neoadjuvant chemoradiation, surgery and adjuvant chemotherapy . Rectosiin-vitro and in-vivo models. PLK1 activity is necessary in repair from DNA damage resulting from chemo- and radiotherapy [Recently, Rodel and colleagues reported polo-like kinase 1 (PLK1) to be a novel predictive biomarker for radiation sensitivity in rectal cancer . We hypootherapy . Hence Pnd June 2012 from the Sydney South-West Area Health Service Ethics Review Committee, reference number HREC/12/LPOOL/102. The institutional review board waived the need for written informed consent from the participants as the project was deemed to be in the low or negligible risk category. Information was de-identified prior to analysis.Ethics approval was obtained on 22Specimens from primary surgery for rectal or rectosigmoid cancers were obtained from the South-Western Area Pathology database, Australia from 2000–2010. Surgery consisted of total mesorectal excision, with anterior or abdominoperineal resection. Variables of interest included age, gender, pathological stage of tumour, grade, vascular invasion, perineural invasion, tumour-infiltrating lymphocytes and treatment. Staging was based on the American Joint Committee on Cancer (AJCC) tumour-node-metastases (TNM) system. Outcomes of interest were overall survival (OS) and histological tumour regression (TRG) in the resected bowel for cases treated with neoadjuvant chemoradiation. OS was defined as the time from diagnosis to last follow-up or death. TRG was graded based on the AJCC criteria, modified from Ryan : completFor each patient, donor blocks of paraffin embedded tissue were retrieved from the anatomical pathology department. Two cores, each one millimetre in diameter, were obtained from each sampling site which included the tumour centre (TC), tumour periphery (TP), normal mucosa close to tumour (NCT) and normal mucosa away from tumour (NAT). Two tissue cores from lymph nodes (LN) in the node-positive cases were also obtained. TC was taken from centre of tumour mass, TP from the infiltrating/invasive tumour periphery, NCT from normal mucosa immediately adjacent to tumour and NAT from normal mucosa well away from tumour, usually at the end margins of the resected bowel. These were transferred into the pre-drilled wells in the tissue microarray (TMA) block using the Beecher Manual tissue arrayer-1 . The TMA blocks were heated for 5 minutes in 60°C oven to seal the gaps between tissue cores and surrounding paraffin.2O2, prior to incubation with PLK1 primary monoclonal mouse antibody . The antibody was sourced and stained as per previously published method [Slide sections taken from the TMAs were deparaffinised with xylene, followed by absolute alcohol, then re-hydrated in alcohol gradient. Antigen was retrieved in heat in 98°C water bath with Tris EDTA (pH 9.0) buffer. Endogenous peroxidase activity was blocked with Hd method . Linker The immunostained sections were examined by manual counting of cells in each TMA dot, with the observer blinded to clinical outcomes. Percentage of positive cells and staining intensity of PLK1 were scored . Intensip<0.05. Variables with a univariate p-value ≤0.2 were included in the initial multivariate model. Non-significant variables were removed iteratively and coefficients checked to determine whether removal of a variable resulted in a large effect change for any of the remaining variables. This was repeated until significant variables remained. Two way interactions between the remaining variables were checked for significance and included in the model if they were significant. The supremum test for proportional hazards assumption was used to determine whether the hazard functions over time were constant. For variables that did not satisfy the proportional hazards assumption, an interaction term between time and that variable was included into the model to account for non-proportionality. Subgroup analyses were performed using a similar procedure for patients in the lymph node positive group to determine if PLK1 in the involved node correlated with node number (Fisher’s exact test) and with survival (Cox regression). Another subgroup analysis (Fisher’s exact test) was performed for patients who had undergone neoadjuvant therapy to determine if there was a correlation between PLK1 and TRG. Ki67 was correlated with PLK1 scores using logistic regression. Data analysis was generated using SAS Enterprise Guide software, Version 6.1 of the SAS System for Windows .Paired t-test was used to compare PLK1 in TC and TP, Fisher’s exact test for associations between PLK1 and clinicopathologic variables, and Cox regression for OS. Only cases with complete data on all the variable domains were included in the univariate and multivariate analyses. Significance was set at 2/day).Two hundred and eighty-six cases were identified, with a median age of 73 years . The cohp<0.001). Staining in TP and TC had similar proportions of >75% staining (i.e. 35%) however the proportions of 3+ staining was 14% in TC and 25% in TP. Mean PLK1 score was 3.4 for NCT and 3.0 for NAT, and these scores were significantly different (p = 0.025). NAT was significantly different to TP (p = 0.011) but not to TC (0.08), hence TP was deemed to be a more accurate representation of tumour staining, and will be used herein for analyses. The distribution of the TP scores is illustrated in Mean weighted PLK1 score was 2.5 for tumour centre (TC) and 3.4 for tumour periphery (TP). The breakdown of TC and TP weighted scores is shown in An association was found between TP scores and metastatic status, in that patients with metastatic disease had a low TP PLK1 score in 95% of the cases compared to 72% in the non-metastatic disease group . There wThe 12 variables of interest included TP PLK1 weighted score, age, gender, TNM stage, histological grade, vascular invasion, perineural invasion, presence of tumour-infiltrating lymphocytes, adjuvant chemotherapy and neoadjuvant treatment. There were 219 cases with complete data on all these domains. Cox regression univariate analyses showed higher TP PLK1 score, higher age, higher tumour T stage, metastatic status, presence of vascular and perineural invasion and absence of adjuvant chemotherapy to be significant predictors of worse OS , Fig 3. p = 0.097). However there appeared to be a trend between higher LN PLK1 scores and greater number of positive nodes, with 68% of high PLK1 scores having N2 compared to N1 status. There were borderline associations between LN PLK1 scores and vascular invasion (p = 0.064), perineural invasion (p = 0.070) and histological grade (p = 0.057).Mean LN PLK1 score in the 105 node-positive cases was 3.1. There was no statistically significant association between LN PLK1 scores and number of nodes involved (p = 0.114). In multivariate analyses (n = 78), LN PLK1 was not significantly associated with survival (p = 0.7083) after adjusting for adjuvant chemotherapy and vascular invasion interaction; as well as adjuvant chemotherapy and time interaction.In univariate analyses (n = 78), LN PLK1 was not significantly associated with survival (p = 0.096).Out of the 57 patients who underwent neoadjuvant chemoradiation. Twenty-three percent had TRG grades 1 to 2 (responders) and 77% had TRG3 (non-responders). There was no significant association between TP PLK1 score and TRG (p = 0.539), TP (p = 0.406) and LN (p = 0.413).Ki67 mean scores in TC, TP and LN were 9%, 8% and 4% respectively. cores in NAT and NCT were <1%. Logistic regression revealed no significant associations between PLK1 and Ki67 in TC , the clinical utility of PLK1 will need to be explored further in this patient population. It may be hypothesized that the majority of metastatic cases did not allow for the collection of resected tissue, hence limiting the ability to detect cases with high PLK1 staining. Larger studies are needed to define the interaction between PLK1 score and metastatic status with regard to outcomes.We also performed corroborative staining with Ki67, and demonstrated no significant association between PLK1 and Ki67 staining. Hence PLK1, though important in cell cycle regulation, is not simply a surrogate for cell proliferation.Our findings are consistent with observations from cell line studies, where re-instatement of PLK1 activity is essential in recovery from G2/M checkpoint arrest following DNA damage. The latter inhibits PLK1 which normally requires phosphorylation in its activation loop threonine 210 by Bora in collation with upstream kinase. Threonine 210 phosphorylation of PLK1 peaks with the normal accumulation of Bora in G2 phase. PLK1 subsequently activates downstream targets and cells progress through mitosis . ContinuK-ras is a predictive marker for response to EGFR inhibitor therapy [Current therapeutic management of rectal cancer can be improved by the availability of better predictive and prognostic biomarkers. Carcinoembryonic antigen (CEA) is currently the only biomarker in the National Comprehensive Cancer Network (NCCN) guidelines, as part of baseline staging and in post treatment surveillance. In the metastatic setting,  therapy . Our res therapy ,25. Othe therapy . FurtherS1 Fig(TIF)Click here for additional data file.S1 Table(XLS)Click here for additional data file.


A variety of methods are used for estimating pituitary tumour size in clinical practice and in research. Quantitative methods, such as maximum tumour dimension, and qualitative methods, such as Hardy and Knosp grades, are well established but do not give an accurate assessment of the tumour volume. We therefore sought to compare existing measures of pituitary tumours with more quantitative methods of tumour volume estimation.Magnetic resonance imaging was reviewed for 99 consecutive patients with pituitary adenomas awaiting surgery between 2010 and 2013. Maximal tumour diameter, Hardy and Knosp grades were compared with tumour volume estimates by the ellipsoid equation, [R2 = 0.99, p < 0.0001). However the correlation was less strong with increasing tumour size, with the ellipsoid method slightly underestimating. The mean differences were −0.11 , −0.74  and −1.4  for micro-tumours, macro-tumours and giant tumours respectively. Tumour volume correlated with maximal diameter, following a cubic distribution. Correlations of tumour volume with Hardy and Knosp grades was less strong.Ellipsoid and perimeter methods of tumour volume estimation strongly correlated (Perimeter and ellipsoid methods give a good estimation of tumour volume, whereas Knosp and Hardy grades may offer other clinically relevant information, such as cavernous sinus invasion or chiasmal compression. Thus the different methods of estimating tumour size are likely to have different clinical utilities. Pituitary tumours are common intracranial lesions, with an estimated prevalence of 10–17 % , 4. PituVarious methods for reporting pituitary adenoma size and shape exist. Current convention across oncology RECIST 1.1] recommends that a maximal dimension is adequate for the reporting of tumour size, and this is also commonplace in the clinical management of pituitary tumours . However.1 recommAssessment of pituitary tumour volume is an attractive and likely more accurate alternative . Optionserimetry , 13.Our aim was to compare these methods of tumour volume estimation in pituitary tumours and to consider their relationship with the existing descriptive measures; namely, maximal tumour diameter, Hardy grade and Knosp grade. To our knowledge, this has not previously been considered.Consecutive patients undergoing endoscopic trans-sphenoidal surgery for a pituitary adenoma under a single neurosurgeon, between 2010 and 2013 were identified from the departmental database, compiled prospectively. Patient sex, age and tumour histology were noted. Given the potential difficulty in identifying residual tumour from postoperative changes on MR, patients undergoing revision surgery were excluded in this initial study.a, b and c are the maximal orthogonal diameters in each dimension  to ascertain the tumour’s maximal diameter, ellipsoid and perimeter volumes, Hardy and Knosp grades Figs.  and 3 5. Perimetion Fig. .Fig. 1Pi3), macro-tumour  or giant tumour  in size.Tumours were subcategorised as micro-tumour  were also graded by a second observer, to assess inter-observer variability.p < 0.05. Tumour grades were compared as a single group and in their separate subcategories. Pearson’s correlation coefficient was used to study correlations between continuous variables and Spearman’s rho for ordinal variables. The Bland-Altman method was used to assess agreement, firstly between the perimeter and ellipsoid estimates of volume and secondly between the two observers.Statistical analysis was performed using SPSS version 20.0 . Significance was set at n = 57]. Functioning tumours included acromegaly (n = 21) and Cushing’s disease (n = 11). The remaining pathology were pituitary apoplexy (n = 4), prolactinomas (n = 3) or cystic pituitary lesions (n = 3). These tumours had a wide range of tumour size and grades  with a mean age of 55 ± 15 years were included. The majority were non-functioning pituitary adenomas [NFPAs, R2 = 0.99, p < 0.0001). Bland-Altman analysis found their mean difference overall to be −0.82 , although the analysis also demonstrated that the magnitude of difference increased with tumour size; −0.11 , −0.74  and −1.4  for micro-tumours, macro-tumours and giant tumours respectively  the perimeter method calculated a slightly larger volume than the ellipsoid method  was less than for the perimeter volume , with coefficients of variation of 8.2 % compared with 11.3 %.Inter-observer error for estimation of the ellipsoid volume  and perimeter  estimation of volumes correlated with maximal diameter, following a cubic distribution , Hardy letters  and the Knosp grades  also correlated with tumour volume, although correlations were less strong  is recommended for use across oncology to assess tumour size and to monitor response to treatment. With advances in technology, tumour volume calculation continues to gather greater focus as it more accurately measures tumour size. It is also recognised that small changes in diameter can grossly underestimate tumour growth. However, the time-consuming calculation required for tumour volume had limited its translation into clinical practice , 6.In this surgical series of pituitary adenomas, both the ellipsoid and perimeter methods of tumour volume estimation closely correlated. Pre-existing measures of pituitary tumours  also correlated with tumour volume, although the relationship was less strong.In this study, the perimeter method identified slightly larger volumes than the ellipsoid method, consistent with the findings of Sorenson et al. . The disVarious automated methods have also been evaluated to estimate tumour volume, but at present are considered less accurate when compared with manual planimetry, although advances continue to be made , 6, 16.The clinical importance of pituitary tumour volume in patient management is not always absolute. As a typically benign tumour, intervention is usually guided by development of clinical symptoms as opposed to tumour volume specifically. Therefore, quantitative methods may have a greater role in those pituitary adenomas under radiological surveillance. The additional information provided by the Hardy and Knosp grades, such as the extent of chiasm compression and cavernous sinus invasion, may be as equally if not more important in influencing the need for intervention and the surgical options.In the present study, we excluded patients previously operated on. In such cases, the interpretation of the MR images with respect to identifying residual adenoma can be challenging due to the presence of post-surgical changes, leading to greater inter-observer bias. Nevertheless, surveillance of pituitary tumours may benefit from volumetric analysis, since a simple diameter may under-represent a change in tumour volume in response to therapy or watchful waiting –10, 12. Pituitary tumour volume can be estimated by a variety of methods. Pituitary tumour volume can be quantitated by the perimeter method or, slightly less accurately, by the ellipsoid method. Qualitative methods such as the Hardy or Knosp grades may provide other clinically important information, such as chiasmal compression or cavernous sinus invasion. In clinical practice, these different methods of assessing pituitary tumour size would likely provide different and potentially equally useful information.


By considering the outcomes given individual tumour kinetics, our results indicate that the subpopulation of patients who would receive the greatest benefit from bevacizumab and radiation combination therapy are those with large, aggressive tumours and who are not eligible for GTR.Recently, two phase III studies of bevacizumab, an anti-angiogenic, for newly diagnosed glioblastoma (GBM) patients were released. While they were unable to statistically significantly demonstrate that bevacizumab in combination with other therapies increases the overall survival of GBM patients, there remains a question of potential benefits for subpopulations of patients. We use a mathematical model of GBM growth to investigate differential benefits of combining surgical resection, radiation and bevacizumab across observed tumour growth kinetics. The differential hypoxic burden after gross total resection (GTR) was assessed along with the change in radiation cell kill from bevacizumab-induced tissue re-normalization when starting therapy for tumours at different diagnostic sizes. Depending on the tumour size at the time of treatment, our model predicted that GTR would remove a variable portion of the hypoxic burden ranging from 11% to 99.99%. Further, our model predicted that the combination of bevacizumab with radiation resulted in an additional cell kill ranging from 2.6×10 The current standard of care involves surgical resection followed by concurrent radiotherapy and chemotherapy. Despite this aggressive treatment protocol, median survival remains about 14 months ,3. Recen1.1.et al.  fluoromisonidazole (FMISO), have been proposed [A primary reason why the state of tumour oxygenation during and post-AA therapy remains unclear is the difficulty in actually assessing levels of hypoxia. Only invasive techniques allow for direct measurement of the oxygen tension within the tissue, but even if measurements of relative hypoxia within the tumour are obtained, the spatial heterogeneity may result in the sampled regions not being adequate for defining the true hypoxic burden. To directly measure the spatial distribution of hypoxia proposed . While tuch as F- fluoromiproposed ,20, it iproposed .The failure of the RTOG 0825 and AVAglio trials to demonstrate a survival benefit from the combination of radiation and bevacizumab can be considered surprising as the transient normalization of the vasculature within and around the tumour is hypothesized to increase the efficacy of both radiation and chemotherapy. Photon radiotherapy, the standard of care, depends on oxygen molecules for maximum DNA damage and it is thought that the normalized vasculature may re-oxygenate many regions of the tumour increasing overall efficacy . AdditioBy modelling similar therapies to those used in the two phase III clinical trials described above, this study aims to provide some initial hypothesis exploration with a mathematical model of GBM growth in the hopes of highlighting a potential subpopulation for whom bevacizumab may be able to provide an increased overall survival. We have developed a spatio-temporal biomathematical model for glioma proliferation and invasion incorporating the role of the angiogenic cascade. In a case study, this model was capable of reproducing a patient-specific PET image of hypoxia , and thu2.2.1.The mathematical model is built around a simple model based solely on the proliferation and invasion rates of a tumour cell population, the proliferation invasion (PI) model –30. To cc), hypoxic (h) and necrotic (n). The vasculature cells (v) are also considered as a separate cell population as is the concentration of generic angiogenic factors (a). In words, it assumes the level of nutrients present in the local microenvironment, as inferred from the vessel density, determines whether the tumour cells exhibit normoxic or hypoxic phenotypes. That is, if there is a sufficient level of nutrients present, the cells will be well oxygenated, or normoxic, but if the nutrient level falls below a given threshold, the cells will become hypoxic. If the nutrients fall below an even lower threshold, the hypoxic cells will undergo necrosis. Normoxic tumour cells are allowed to move (invade) and divide while hypoxic cells are only allowed to move owing to restricted nutrients. Hypoxic cells produce a high concentration of angiogenic factors, which triggers an increase in the vessel density (i.e. angiogenesis).In brief, the PIHNA model assumes the tumour is comprised of three different phenotypic tumour cells, normoxic  will correspond to the entire T1Gd abnormality and 16% will correspond to the T2 abnormality.GBMs are generally monitored via MRI, specifically with contrast-enhancing T1-weighted (T1Gd) and T2-weighted scans. As we have done previously ,30,31, w2.3.The definition of GTR is that the entire abnormality seen on T1-weighted post-contrast (T1Gd) MRI is removed. To define the impact of surgery from our model perspective, we assume the modelled T1Gd portion of the tumour is removed and consider the remaining tumour cells for the following analysis.2.4.To model the effects of bevacizumab, we capture the two phenomena of inhibiting angiogenesis and normalizing pre-existing vasculature by requiring higher levels of angiogenic factor to be present to have the same level of ‘action’ in the contexts of both vessel proliferation and vessel permeability. Additionally, because the treatment is increasing the vessel efficiency, the level of vasculature needed for a cell to be normoxic will decrease, which we can capture by modifying the cell conversion rates from hypoxic to normoxic and from normoxic to hypoxic. Further details can be found in  and in t2.5.d in units (Gy) delivered to the tissue in n fractions to the percentage of cells killed, FCK, using two parameters related to dose–response, α (Gy−1) and β (Gy−2), through the relationship α/β = 10 Gy for early responding tumour tissue. The standard of care for delivering radiation to GBM patients involves delivering a total dose of 60 Gy delivered in fractions of 2 Gy, 5 days a week, for six weeks. While the concept of fractionation will be accounted for via the n in the definition of FCK, in this study, the cell kill is computed at a single time point, and whole-brain irradiation is assumed.There are many different models of radiation cell kill of varying levels of complexity . Here, wferences ,34, we aα in a patient-specific context and found that it varied linearly with the parameter in the PI model for the net rate of proliferation, ρ. To capture the heterogeneity of radiation efficacy, we use this linear relationship when applying radiation for the individual simulations. It should be noted that this study did not explicitly separate cell kill owing to radiation and chemotherapy, thus the net radiosensitivity parameter (α) from Rockne [Rockne  studied m Rockne  is also α and β, so that poorly oxygenated tissue would be associated with a scale factor reduction in radiation efficacy αh = α/OER and βh = β/OER. This is of particular interest in this paper as it is expected that AA therapy will reduce the hypoxic/poorly oxygenated portion of the tumour. Each grid cell will be associated with an effective OER, OERe, taken as the following weighted sum based on the relative hypoxia within that cell: c, h and n are the variables in the PIHNA model representing the normoxic, hypoxic and necrotic cell populations, respectively. We note that in regions entirely composed of normoxic cells OERe = 1 and in regions entirely composed of hypoxic cells OERe = 3, representing the most optimistic increase in radiation efficacy from re-normalization of the vasculature. Putting all these things together, for a given dose d delivered in n fractions, the radiation cell kill fraction is modelled asic and ih are the total number of normoxic and hypoxic cells in grid cell i, respectively, i, the radiosensitivity parameter α will be calculated through the linear relationship with the pre-treatment net proliferation rate, ρ, determined in [α/β = 10.It is known that photon radiation delivered to well-oxygenated tissue is more effective at killing cells than when delivered to poorly oxygenated tissue. This increase in efficacy is quantified through the oxygen enhancement ratio (OER) which has been seen to range between 1 and 3 ,33. In omined in  and α/β 2.6.D = 305 mm2 yr−1 and net proliferation rate ρ = 83 1 yr−1). We then simulated tumour growth under three different scenarios of AA treatment: starting therapy when the tumour had reached 1.5, 2.5 or 3.5 cm as visible on T2/FLAIR MRI and continuing for 42 days, the typical length of a treatment session. For numerical details, see the electronic supplementary material. These starting sizes will be considered in all of the following simulations.Patients were accepted to both RTOG 0825 and the AVAglio trial with minimal consideration of the size of their tumour. We hypothesize that the percentage of the tumour that is hypoxic will depend on the size of the tumour. To investigate the impact of varying tumour sizes at the start of AA treatment on hypoxic levels, we first chose parameter values that represented a patient with a very aggressive GBM (net invasion rate 2.7.ρ (−1), and invasion rates, D (2 yr−1). The specific combinations that were run correspond to a Cartesian product of 11 ρ-values and 13 D-values spaced logarithmically within these ranges. The three tumour sizes, 1.5, 2.5 and 3.5 cm, were again considered as starting points for therapy to capture the heterogeneity in sizes at presentation seen clinically.As the range of radiographic response patterns seen clinically is broad, it should be expected that the re-oxygenation response would also be varied. Previous work has shown patient-specific values of proliferation and invasion range over several orders of magnitude ,35. To iR1 defined as the absolute change in the number of hypoxic cells between the two time points of just prior to AA therapy, t1 and 14 days into therapy, t2. The 14-day time point was chosen to correspond with the time of overlap of these therapies in the RTOG 0825 trial. Mathematically, this is written asTo capture the response in terms of a single number for each tumour, we used a metric of therapeutic re-oxygenation efficacy, h is representative of the number of hypoxic cells at location r and time it.Here, 2.8.R2, is defined as the difference in the total number of hypoxic cells seen in a tumour not having received therapy and the same tumour having received AA therapy for 14 days. Mathematically, this can be written asA major benefit of using mathematical models to investigate questions such as those regarding treatment is that one can not only assess precisely what the difference is between the tumour pre-treatment and post-treatment, but one can also assess the difference between the tumour post-treatment and the tumour at the same time point without therapy. In essence, the model provides an untreated virtual control. Thus, experiment 2 is a two-armed version of experiment 1 where the two arms are tumours treated with AA therapy and tumours receiving no treatment. For this experiment, the response metric, 2.9.FCK, was assessed two weeks after the tumour reached the particular size of interest. For the treated arm, when the tumour reached the size of interest, AA therapy was started and continued for two weeks at the end of which the radiation cell kill was similarly computed as FCK.To more fully address the question of the efficacy of combination therapy involving AA and radiation therapy, we tested how many cells would be killed as a result of combination therapy both after two weeks of AA therapy, allowing some time for vascular renormalization, and the virtual control at the same time point. Specifically, the control arm did not have any AA therapy administered, but cell kill, computed as 2.10.All previous results are working from the assumption that no GTR has been performed. However, for many patients, the reality is that they undergo GTR prior to additional therapies. It seems very likely that GTR would alter the number of hypoxic cells in the system by removing the central necrotic core. We therefore consider how GTR, when performed at different tumour sizes, would impact the potential efficacy of combining AA therapy with radiation as defined through the number of remaining hypoxic cells.3.3.1.a shows two snapshots of the tumour simulation with treatment starting when the tumour's size was 2.5 cm. The first snapshot is of the tumour just prior to AA therapy, and the second snapshot is two weeks into therapy. The tumour continues to grow during treatment both in terms of radial outgrowth and in terms of higher total cell densities, suggesting no therapeutic effect. However, treatment does impact the relative proportions of the tumour populations, as the hypoxic population is at a higher density towards the centre of the tumour prior to treatment in contrast to post-treatment.Figure 1b shows the evolution of the absolute number of cells in each population throughout the simulation (top row) and the fraction of the total tumour that the population composes. The solid lines show the results from the treated tumour, and the dashed lines show how these curves would have evolved without treatment. Generally, both rows show that AA therapy increases the number of normoxic cells compared with when left untreated and that the hypoxic and necrotic populations are reduced through therapy from where they would have been otherwise. The absolute deviation from the untreated curves, however, is more dramatic when treatment is started at later time points. Specifically, when treatment is started when the tumour size is 1.5 cm, the normoxic cell count within the tumour is predicted to be 1.4 × 1010 at the end of therapy versus 9.3 × 109 for the corresponding time point of an untreated tumour. Similarly, for treatment started when the tumour radius is 2.5 cm, the normoxic cell count is 3.5 × 1010 at the end of therapy versus 2.2 × 1010 for an untreated tumour. Finally, if the treatment is started when the tumour size is 3.5 cm, the normoxic cell count is 6.6 × 1010 versus 3.9 × 1010. When thought of in terms of percentage of the tumour, however, one can see in figure 1b that if treatment is given when the tumour is small, the hypoxic population is minimized, and the vast majority of the tumour is normoxic and thus more susceptible to radiation. In contrast, when treatment is given to a larger tumour, even though the hypoxic percentage does decrease, the resulting normoxic percentage of the tumour is ultimately smaller as the necrotic population has begun to grow.Figure 1These simulations certainly support the hypothesis that AA treatment does re-oxygenate the tumour but that the benefit of combination therapy with radiation and chemotherapy is complicated to tease apart and will vary depending on the size of the tumour at the time of treatment.3.2.The simulations illustrated in R1, is not uniform and thus would not be expected to be uniform across patients. While these results are suggestive of some patients receiving no benefit from re-normalization, they are insufficient to quantify how much ‘better off’ the patient is due to treatment. That is, these images only show the difference between the pre-treatment tumour and the two-weeks-into-treatment tumour. While this is the type of data available for comparison in the clinic, the question that should be of even more importance is the difference between the two-weeks-into-treatment tumour and the tumour if left untreated, the control.These results again demonstrate that the hypoxic percentage of the tumour is diminished under AA therapy. However, there are certain tumours that still have more hypoxia, in terms of absolute cell count two weeks into therapy than prior. This is particularly true for the smaller tumours with larger net rates of diffusion; when treatment is administered to larger tumours, it is still predicted that the slowly proliferating very diffuse tumours will ultimately have more hypoxic cells after two weeks of therapy. By looking across parameter space, we are also able to see that the re-normalization efficacy, defined by 3.3.R2, between the two-weeks-into-treatment tumour and its virtual control at the same time point, that is the tumour grown with the same parameters but never receiving treatment. Comparing figures3.4.7 to 2.4 × 109 cells for treatment starting when the tumour size is 1.5 cm, 8.5 × 107 to 5.4 × 109 cells for a tumour size 2.5 cm and 1.8 × 108 to 1.1 × 1010 cells for a tumour size 3.5 cm. The general trend observed is that the highly proliferative and highly invasive tumours appear to have the most additional cells being killed, however, as the tumours get larger in size, the range of tumour kinetics receiving an appreciable change also increases.The top row of 3.5.Results are illustrated in 4.D and ρ, a wide range of image responses, analogous to what is seen clinically, were possible [Building on our previous work with our biomathematical model, this work aims to address how AA therapy may impact levels of hypoxia and the implications this has for combination therapy for different tumour growth and treatment response kinetics. Previously, we showed that by holding the modelling effects of treatment constant and only varying possible . Here, wWhile the parameters in our model regarding the effects of AA therapy have been estimated from literature and not rigorously fit to data, we believe it represents a useful framework to begin exploring such questions as how the net effects of AA therapy would re-normalize tumours given their expected hypoxic burden. Our work here is based on the assumption that AA therapy increases the vascular efficiency. We recognize that a possible limitation to our findings is that we consider only vascular normalization as there have been some reports of AA therapy increasing hypoxia in animal models . This hyα's used in the radiation model was taken from a paper where the effect of chemotherapy was implicitly incorporated into the estimate. Thus, while we are not modifying the effect of bevacizumab on the two therapies, radiation and chemotherapy, independently, we are still implicitly accounting for the total effect on cell kill. For this reason, we believe our results are still meaningful in answering questions related to the expected efficacy of such combined therapies. These analyses combined hint at possible explanations for the negative results of the AVAglio and RTOG 0825 phase III clinical trials.What is clear from our results is that the re-oxygenation effect is different not only for tumours with different growth kinetics, but also for tumours with the same growth kinetics with treatment started at different sizes. We showed this in the context of comparing the levels of hypoxia pre-treatment and two weeks into treatment as well as when comparing the hypoxic levels in tumours two weeks into treatment and their virtual control. We further explored the potential efficacy of combining radiation with AA therapy by testing the change in cell kill owing to the change in the hypoxic population. We note the omission of chemotherapy in our models is a possible limitation to our analysis. However, the formula for the A large percentage of the patients in both the RTOG 0825 and the AVAglio clinical trials underwent some level of debulking surgery. The RTOG 0825 reported that 63% of their patients on the bevacizumab arm and 59% on the placebo arm underwent GTR and the vast majority of the other patients underwent partial resection. Similarly, the AVAglio trial reported 41% of the patients on the bevacizumab arm and 42% on the placebo arm underwent GTR with the majority of the others undergoing partial resection. Our exploration of remaining hypoxic tissue after GTR, Similarly, smaller tumours and tumours with lower proliferation rates do not have significant hypoxic populations. Our results here indicate that for patients with these low hypoxic tumours, combination therapy of AAs and radiation would not result in a greater cell kill and would thus not likely lengthen these patients' overall survival.While none of our simulation experiments here directly predict the overall survival expected from the various therapies, the combined results suggest some general guidelines when considering what class of patients would likely benefit. If GTR is performed, the combination therapy should be reserved for larger tumours only (2.5 cm or greater prior to surgery) with emphasis on the tumours with less proliferative more invasive tumour kinetics. This comes from the observation that small tumours and larger, more proliferative tumours would have had the vast majority of their hypoxic burden removed during surgery and would have only minimally increased radiation induced cell kill owing to the addition of bevacizumab. If no GTR is performed, combination therapy should still be reserved for larger tumours but this time with emphasis on the highly proliferative and invasive tumours.in silico analysis highlights the importance of focusing on individual patients' tumour growth kinetics and tumour size at presentation. As the analysis will be retrospective, assessment of the patient's hypoxic burden will not be available, but our methods of assessing rates of proliferation and invasion can be done using standard pre-treatment MRI images and can act as a surrogate marker for the amount of hypoxia individual tumours are experiencing.In the coming years, we expect many retrospective analyses will be performed using the data from both the AVAglio and RTOG 0825 clinical trials looking for subgroups that benefit from the combination therapy. This 5.Results from simulation studies using a mathematical model of tumour growth provide a testable hypothesis that there is a subpopulation of patients who could benefit from combination therapy including bevacizumab and radiation, namely those with large, aggressive tumours, and who are not eligible for GTR. These results may explain why the AVAglio and RTOG 0825 studies did not find a significant increase in overall survival, as approximately 50% of the patients on these trials underwent GTR. If retrospective analysis of the AVAglio and RTOG 0825 trial data is performed using individual patient characteristics, the criteria developed here may allow a quantitative classification of patients with a significant increase in overall survival. With so few treatment options available to GBM patients, it is important that options not be disregarded when no benefit on a population level is observed if there may be a subgroup of patients that would receive benefit. We believe this study represents a first step in identifying such subgroups.


Insects use either hairy or smooth adhesive pads to safely adhere to various kinds of surfaces. Although the two types of adhesive pads are morphologically different, they both form contact with the substrate via a thin layer of adhesive fluid. To model adhesion and friction forces generated by insect footpads often a simple “wet adhesion” model is used, in which two flat undeformable substrates are separated by a continuous layer of fluid. This review summarizes the key physical and tribological principles that determine the adhesion and friction in such a model. Interestingly, such a simple wet-adhesion model falls short in explaining several features of insect adhesion. For example, it cannot predict the observed high static friction forces of the insects, which enable them to cling to vertical smooth substrates without sliding. When taking a closer look at the “classic” attachment model, one can see that it is based on several simplifications, such as rigid surfaces or continuous layers of Newtonian fluids. Recent experiments show that these assumptions are not valid in many cases of insect adhesion. Future tribological models for insect adhesion thus need to incorporate deformable adhesive pads, non-Newtonian properties of the adhesive fluid and/or partially “dry” or solid-like contact between the pad and the substrate. More than 80% of the animal species in the world are arthropods , and amoFor a long time the ability of insects and other arthropods to effortlessly walk up and down all kinds of natural and artificial surfaces has fascinated scientists and the underlying mechanisms have been debated since the early days of light microscopy. From “gluten-filled sponges”, the interlocking of fine hairs, suction cups and adhesive secretions, many hypotheses about insect adhesion have been proposed over the last two centuries –7.In recent years more elaborate microscopes and better analytical tools have become available and the interest of biologists and engineers in biological and biomimetic adhesives has increased –13. ImagIn a previous paper we have discussed the general principles of insect adhesion and highlighted recent advances and open questions . This reOne of the most basic biological micro-scale structures for mechanical interlocking to a substrate seems to be a claw. However, the potential use of claws is limited to compliant surfaces in which the claws can insert, or rough surfaces with asperities larger than the diameter of the claw tip . Hence, In general, the hairy adhesive pads on the feet of flies, beetles and spiders are densely covered with dense arrays of flexible setae see  16–22].–22.16–22Despite the large number of species, only two types of adhesive systems have evolved in insects and other arthropods: “hairy” (fibrillar) and “smooth” pads . Both syDespite their different morphology, hairy and smooth adhesive pads of insects have in common that they both secrete an adhesive fluid into the contact zone ,16. For To understand the physical principles that enable the attachment of such fluid-mediated insect foot pads onto various substrates, one has to start with a simple model. In general, the fluid-mediated smooth and hairy adhesive organs of insects have to generate both adhesion forces perpendicular to the substrate and friction forces parallel to the substrate. The tribological models for both “types” of attachment forces will be considered separately in the following.For simplicity, the contact zones of both smooth and hairy adhesive pads are often modeled by using a “wet-adhesion model” consisting of a smooth, undeformable disk and substrate with a mediating continuous fluid-layer  and the viscous forces, often called “Stefan adhesion” –44 see .Based on a few assumptions and further simplifications , the adhesive forces generated by such a “wet adhesion” model in By using a few experimentally accessible parameters such as mediating fluid height, viscosity, and contact angle , this mEquation 2h between adhesive pad and surface would result in decreasing capillary adhesive forces. As a consequence, insects and all organisms with fluid-mediated attachment organs should minimize the secretion of adhesive fluid into the contact area to increase capillary adhesion on smooth surfaces.one can predict that an increasing fluid height However, and this is where the simple “wet adhesion model” starts to fall short when used to model insect attachment, only very few natural surfaces are actually smooth. Experimental studies indeed show that the adhesive fluid actually plays a more important role in increasing adhesion on rough surfaces by filling gaps between the pad and the surface, thereby maximizing contact area and adhesion to rough substrates –46. ThisBesides the “smooth vs rough” limitation, the simple model also bears several additional notable problems, in particular in light of the stiffness and deformability of the adhesive pads. For example, the capillary term in It should also be noted that in particular in the context of insect adhesion the mechanics described by the third viscous forces, or “Stefan adhesion” term, are a rather substantial simplification of the processes determining the viscous adhesion between the adhesive pad and the substrate. The mechanism proposed by Stefan also assumes undeformable surfaces and uniform centripetal flow of the mediating fluid . Both asIn a fluid mediated system with a continuous Newtonian fluid film, the friction forces between the substrates can in general be described by using two basic principles: the surface tension of the mediating fluid and the laws of hydrodynamic lubrication –56.r, and α1 and α2 as the leading and trailing edge contact angles [F acting on the mercury can be described by usingThe contribution of the surface tension of the mediating fluid to friction forces can be estimated by using a simple model of a mercury thread moving through a glass tube . For a st angles , the retCarausius morosus with an estimated surface tension of 27 mNm−1 [2 [1 − cos α2 ≤ 2) would be only approx. 0.38 kPa. This value  is several orders of magnitude smaller than the shear stresses measured in smooth adhesive pads of the stick insects, cockroaches and ants [However, the contribution of surface tension towards the generation of friction forces is very limited. Looking at the adhesive fluid secreted by the Indian stick insect 27 mNm−1  and a comNm−1 [2 , the maxand ants ,46,57,59h sliding at a velocity v relative to each other generate the friction forceSimilar to the viscous forces in adhesion, the “hydrodynamic lubrication” friction model takes into account the viscosity of the mediating fluid layer. Two parallel smooth surfaces with a distance of ηeff is the effective viscosity of the mediating fluid layer and A the size of the contact area. Again, similar to the time-dependent viscous adhesion  the “classic” models of friction and adhesion to incorporate for example deformable pads or non-Newtonian properties of the adhesive fluid. In particular in respect to friction forces one has also take into account possible more complex nano-tribological models, with boundary lubrication or other mechanisms resulting in points of “dry” contact between the pad and the surface.Further fundamental experimental work, in particular a more accurate in vivo measurement of the height of the mediating fluid and high-resolution single-leg force measurements on smooth substrates with well known physical properties are required to answer these questions .