Previous simulations have revealed that an increase in the number of 90Y labelled to each antibody or nanoobject could be a solution to improve treatment output. It now seems important to assess the treatment output and toxicity when radionuclides such as 90Y, 177Lu, 131I, 124I, and 188Re are used. Tumour control probability (TCP) and normal tissue complication probability (NTCP) curves versus the number of radionuclides per nanoobject were computed with MCNPX to evaluate treatment efficacy for solid tumours and to predict the incidence of surrounding side effects. Analyses were carried out for two solid tumour sizes of 0.5 and 1.0 cm radius and for nanoobject  distributed uniformly or nonuniformly throughout a solid tumour ). 90Y and 188Re are the best candidates for solid tumour treatment when only one radionuclide is coupled to one carrier. Furthermore, regardless of the radionuclide properties, high values of TCP can be reached without toxicity if the number of radionuclides per nanoobject increases.Radioimmunotherapy has shown that the use of monoclonal antibodies combined with a radioisotope like  If this technique is well adapted to treat radiosensitive hematopoietic malignancies, clinical studies have always shown poor therapeutic effects on solid and radioresistant tumours. Almost no clinical trials on patients with colorectal, ovarian, gastric, pancreatic, prostate, and breast cancer went beyond phase II :(1):(1)90Y ir centre , 15. Theablished , the bioablished . The rat mAb/cm² . Finallye tumour .D(r) is first converted into the biologically effective dose BED(r) according to formula ) from the tumour centre (r = 0) to the tumour surface (r = rT)r) gives the probability that no tumour cell cluster inside each spherical mesh located at a distance r from the tumour centre survives irradiation. Kr is the number of TCC within the concentric spherical shell located at a distance “r” from the tumour centre and PTCC is the probability to kill a TCC determined by the Poisson expression:α is the tumour cell radiosensitivity and NCells is the number of tumour cells inside each TCC before irradiation obtained by multiplying the density ρ from TCP, defined as the probability that no tumour cell cluster inside the NSCLC tumour survives irradiation, is obtained by multiplying all the shell control probability values  model expressed by m = 0.37 . For thes” is the degree of seriality for the lung organ. Usually, its value is close to zero with s = 0.0061. KLg equals 76 394 192 and represents the total number of FSUs in the whole lung. This value was obtained by dividing a mean lung volume of 5000 cm³ by the volume of one FSU. pFSU is the probability of damaging one FSU, calculated with a similar expression to (NCell is the number of cells in one FSU before its irradiation and α is the lung tissue radiosensitivity. NCell and α are given in r) in expression , initially proposed by Källman et al. , 37(7)NTNr gives the initial number of TRU in each spherical shell located at a distance “r” from the tumor center and α describes FSU radiosensitivity; BED(r) is the biological effective dose at a distance “r” from the tumour centre; c reflects the volume effects; v is the fractional partial volume defined by the ratio Ntot/NLg ; Nr is the number of TRUs at a distance “r” from the tumour centre; rLg is the distance from the tumor center of the last spherical lung tumor shell, and c = −0.98.Finally, TCP curves will also be compared to a third NTCP model for which a minimum number of FSUs  exist and maintain the whole organ function. So, in this last model, we assume that complication rises when all TRUs within the lungs are killed: D(r), and shell control probability, SCP(r), as functions of the distance “r” from the tumour centre have been compared for the five different radionuclides: 90Y, 177Lu, 131I, 124I, and 188Re. We assume here that only one radionuclide is coupled to each antibody and that the five radionuclides are separately conjugated to antibodies with similar biological properties, such as binding affinity, covering fraction, and biological half-life. Results will be investigated to treat two small NSCLC tumour sizes (0.5 and 1.0 cm radii) filled with uniform, linear, or exponential antibody distribution. Rapid and slow antibody clearances from the tumour are taken into consideration by assuming two different biological half-lives of 2 and 6 days. Tables DTot), in Gy, absorbed by the 0.5 and 1.0 cm radii tumours, respectively. These total absorbed doses were obtained according to formula (Ei(r) was calculated with the MCNPX software by considering a virtual sphere with a diameter equivalent to the tumour size. Deposited doses in the centre (DCent) and at the surface (DSurf) of the NSCLC tumour were also presented in these tables. DLung represents the average dose deposited in the 4.0 cm thick lung tissue shell around the tumour. This value enables treatment impact assessment on the healthy lung FSUs surrounding the tumour. By extension, we assume that it is the average dose deposited in the whole organ. This assumption probably overestimates the absorbed doses in lungs because the highest doses in RIT are mainly localized in the tumour vicinity. Finally, the three first columns of Tables A), in kBq, calculated according to formula  and in the tumour centre for low-energy β-emitters (131I and 177Lu).The lowest values of the deposited doses inside the tumour are located at the tumour surface or in the tumour centre, depending on the radionuclide and the mAb distribution. If we look at DCent and DSurf appear between the three different antibody distributions, Dtot seems to remain constant for each radionuclide type. Consequently, values of Dtot strongly depend on the radionuclide choice and not on the antibody distribution type. The largest DTot is given for 188Re-labelled antibodies. However, it does not exceed 35 Gy in the best conditions of treatment, that is, a long biological half-life of 6 days and a uniform antibody distribution throughout the tumour. Such a dose clearly remains insufficient to treat 0.5 cm radius NSCLC tumours.Whereas strong variations of r” for the five different radionuclides. These curves give a representation of cell cluster-killing efficacy at different distances “r” from the tumour centre and give an idea about NSCLC treatment output. For all types of antibody distributions, SCP values for 177Lu, 124I, or 131I at different distances “r” from the tumour centre remain null, indicating that these three radionuclides are not adequate to treat this solid and vascularized 0.5 cm radius tumour. By looking at the SCP curves of 188Re and 90Y from Dtot for uniform, linear, and exponential distribution of 188Re-labelled antibodies is almost the same whereas the shape of SCP curves varies strongly according to the type of antibody distribution. A similar conclusion can be drawn for 90Y-labelled antibodies. For both radionuclides, only a small difference of about 3 Gy is calculated between the total doses deposited by the radiolabelled antibodies distributed uniformly and exponentially, although strong differences appear in the shape of SCP curves. The slight decrease of 5 Gy when antibody distribution becomes more heterogeneous is explained by the fact that a part of the radiation is transferred from the tumour surface into healthy tissues by crossfire effects. However, with values lower than 3 Gy for the different radionuclides  labelled to antibodies with a slow clearance (Tbio = 6 days) and a good penetration (uniform distributions) within the tumour.Consequently, when only one radionuclide is labelled to each antibody, the highest tumour-to-lung deposited dose ratios for both tumour sizes are achieved for low-energy 9 mAbs/cm², a long biological half-life of 6 days, and a good intratumoural penetration of the radiolabelled antibodies, results from 90Y, 177Lu, 131I, 124I, and 188Re. For this purpose, the tumour control probability (TCP) versus the number of radioactive atoms per NO will be analysed. Its value represents the probability that a tumour will be locally controlled for a given dose of radiation. A TCP value of 0% implies that doses deposited inside the tumour remain insufficient, while a TCP value of 100% predicts that the tumour will be eradicated. Our TCP curves will then be compared to NTCP values. Indeed, the latter limits our ability to administrate the dose necessary to control the tumour.Even with a covering fraction of 10DTot, in Gy), doses in the tumour centre , and doses deposited at the tumour surface , required to have a TCP value of 100%. An increase in the deposited doses inside tumours is often associated with an increase in toxicity for healthy tissues surrounding the tumour. To assess the negative effects these nanoobjects could have on the surrounding healthy tissues in 4.0 cm thick shells when TCP has reached 100%, the average doses deposited beyond the tumour surface (DLung) are calculated for each radionuclide. To avoid lung diseases like pneumonitis, it is preferable that their values do not exceed the mean radiation dose of 20 Gy usually tolerated by healthy lung tissues. The fourth and fifth columns in Tables 9 mAbs/cm² covering fraction and an antibody biological half-life within the tumor of 6 days: a less specific antibody with a covering fraction of 108 mAb/cm² would require the number of radioactive atoms to be multiplied by ten to obtain the same TCP. The fourth and fifth columns indicate, respectively, the number of radionuclides when the uptake is supposed to be instantaneous (direct uptake) and the number of radionuclides when 2 days are required to obtain the maximum accumulation of radiolabelled antibodies within the tumour after intravenous administration (2 days uptake) [A) required to achieve a TCP of 100%.Results reported in Tables  uptake) . For theDtot for a TCP of 100%. For 90Y, 188Re, and 124I, a total deposited dose lower than 110 Gy inside the whole tumour is sufficient to achieve a TCP of 100%. This value further decreases when the antibodies are distributed linearly and uniformly throughout the tumour until about 65 and 70 Gy. With 177Lu- or 131I-nanoobjects, doses required to completely kill the tumour are higher for the three types of distribution. The total deposited doses required for a TCP of 100% remain unchanged when the biological half-life increases or decreases but the number of radioactive atoms per NO is different. The smaller the biological half-life is, the higher the required number of radioactive atoms per NO is.188Re and 90Y require a lower number of radioactive atoms per NO to reach a maximal TCP of 100%. Note that if a direct uptake was assumed, the number of radionuclides per NO requested for a TCP of 100% would be slightly larger for 188Re than for 90Y despite a lower mean energy of β-particles emitted by the 188Re. The situation is quite different if we consider that 2 days are required to obtain a maximum accumulation of radiolabelled antibodies within the tumour  calculated for the five different radionuclides and the three antibody distributions are similar to those previously determined for a tumour when only one radionuclide is coupled to each antibody. So, the largest values for the DTot/DLung ratios are obtained for 177Lu-NPs, which indicates that the treatment with 177Lu-NOs maximizes the radiation dose to the tumour while minimizing normal tissues irradiation. However, as the number of radioactive atoms per NO is high and as 177Lu has a longer physical half-life compared to 90Y and 188Re, it is very important to avoid high concentrations of these 177Lu-nanoobjects accumulating in the nontargeted normal organs. Indeed, one isolated NO containing hundreds of atoms of 177Lu is harmless for the patient but an accumulation of these nanoobjects in healthy radiosensitive organs such as the red marrow may be very dangerous.Furthermore, the tumour-to-lung deposited dose ratios  and for a biological half-life of 6 days were considered. TCP curves differ according to the radionuclide used for RIT and the type of antibody distribution, showing that treatment efficacy depends on the choice of β-emitters but also on the localization of the activity inside the tumour. NTCP curves were added to assess the risk of pneumonitis for RIT treatments. As illustrated in 90Y, 188Re, and 124I, a maximum TCP of 100% could still be reached without too many risks of pneumonitis. Inversely, for the two low-energy β-emitters 131I and 177Lu, it is impossible to apply an effective treatment without causing strong lung complications. Indeed, TCP curves for both these radionuclides in 177Lu and 131I. Consequently, for 124I-nanoobjects distributed exponentially within the tumour, TCP and NTCP curves become too close to one another to insure safe treatment if the antibody biological half-life within the tumor decreases.Dtot  for a TCP of 100%. By comparing 124I, 188Re, and 90Y range from 86 and 106 Gy for a biological half-life of 6 days. Due to the low-energy of β emitted by 131I, a minimum Dtot of 135 Gy is required to obtain a TCP of 100%. Such values can be explained by the lack of crossfire effect which implies a higher difficulty to kill all the cell clusters located at the tumour surface. With values larger than 180 Gy, the total deposited dose to achieve a TCP of 100% when antibodies are distributed uniformly or linearly throughout the tumour still increases for 177Lu, although this radionuclide has the same mean β-particle range in soft tissues as 131I. When the antibodies are distributed exponentially throughout the tumour, the deposited doses required for a TCP of 100% greatly increase, particularly for 90Y, 188Re, and 177Lu which require a Dtot up to, respectively, 1320 Gy, 4220 Gy, and 3430 Gy. As previously seen in 90Y, 131I, 124I, 188Re, and 177Lu was located in the tumour centre when antibodies are distributed exponentially throughout the 1.0 cm radius tumour. For the five radionuclides, doses in the tumour centre range from 52 to 56 Gy, meaning that a minimum dose of about 55 Gy is required everywhere inside the tumour to achieve a TCP of 100%. So, the important increase of Dtot for the three radionuclides 90Y, 188Re, and 177Lu is mainly explained by the great difficulty to irradiate all the cell clusters located in the tumour centre at about 55 Gy. Smaller increases of Dtot are observed for 124I and 131I. This probably results from the higher contribution of γ emissions in the total deposited energy. Indeed, γ-rays have a larger range in soft tissues compared to β-particles and favour dose depositions at a greater distance from the radionuclide. In this way, all the cell clusters located in the tumour centre, as well as those located at the tumour surface, are easier to irradiate when the 124I- or 131I-nanoobjects are exponentially distributed within the tumour.β-emitters , the number of radionuclides per NO does not really vary compared to smaller tumours of 0.5 cm radius. The larger activities observed in 90Y- and 188Re-nanoobjects are coupled to antibodies distributed exponentially throughout the tumour. The strong activity increase calculated for exponential antibody distribution comes from a larger number of cell clusters within the tumour but also from a larger number of radioactive atoms per NO. Such a result could be explained by a great difficulty to irradiate all the cell clusters localized in the tumour centre. Consequently, the exponential distribution of both 188Re- and 90Y-nanoobjects represents a disadvantage in the treatment of solid tumours with radii equal to or larger than 1.0 cm. The latter problem is even more striking when the low-energy β-emitter 177Lu is used for internal radiation. Independently of the antibody distribution type, the larger number of radionuclides per NO observed when the tumour size increases could be explained by a great difficulty to kill all the cell clusters located at the tumour surface. A problem for irradiating cell clusters located in the tumour centre also appears when antibodies are distributed exponentially. Compared with 177Lu, the second low-energy β-emitter 131I seems to be less affected by this increase in the tumour size. Indeed, the shift towards larger values for the number of radionuclides per NO is smaller for 131I than for 177Lu. When the antibody distribution becomes exponential, this number even appears lower than that of 188Re. Such results are explained by a greater contribution of gamma rays for 131I and show that, for our MCNPX simulations, it is really important to consider the total (β and γ) energy deposition to determine TCP values. A similar conclusion is reached for the radionuclide 124I for which the lowest number of radioactive atoms per NO required to get a good treatment output is calculated when the antibody distribution is exponential. For uniform and linear distributions of high-energy DSurf and DCent for a TCP of 100%. For the three types of antibody distributions, the minimum doses deposited in the tumour centre or at the tumour surface are quite similar to the results calculated for a 0.5 cm radius tumour. Their values ranged from 51 Gy to 57 Gy, meaning that, once again, a minimum value of 55 Gy everywhere inside the tumour is required to treat NSCLC correctly. To preserve such a dose in the tumour centre when antibodies are distributed exponentially throughout the 1.0 cm radius tumour, DSurf drastically increases to doses larger than 1450 Gy and 3800 Gy for high-energy β-emitters such as 90Y and 188Re, respectively. For iodine radionuclides, DSurf decreases to lower values such as 240 Gy for 124I and 440 Gy for 131I.DLung for a TCP of 100%. For the 5 different radionuclides, the deposited doses in the surrounding lung tissues are higher than the values calculated for a 0.5 cm radius NSCLC tumour, independently of antibody distribution. However, for uniform and linear antibody distributions, DLung remains lower than 20 Gy. When the antibodies are distributed exponentially throughout a 1.0 cm radius NSCLC tumour, the doses deposited in lung tissues are too high and NSCLC tumours cannot be treated by a single injection of radiolabelled antibodies. The best result is obtained for the 124I for which doses in lung tissues reached 35 Gy for a 6-day biological half-life. The surrounding healthy tissues are less affected by the radiation when the radioisotopes 177Lu, 124I, or 131I are used despite a large amount of radioactive atoms per NO required for a TCP of 100%. However, the synthesis of nanoobjects able to assemble such an important number of radioactive atoms remains very difficult experimentally. Furthermore, this high number of radionuclides, mixed with other nonradioactive organic or inorganic atoms and surrounded by additional macromolecules, could form nanoobjects too large to prevent uptake by the reticuloendothelial system and to promote their diffusion throughout the target tissue. This problem would be even more important if the covering fraction is decreased. TCP Curves. To analyze how tumour size may influence the number of radioactive atoms per antibody required to maximize the treatment efficacy, TCP distributions have been plotted for 1.0 cm radius tumours. In 90Y, 177Lu, 131I, 124I, and 188Re distributed uniformly and nonuniformly throughout the tumour. As previously stated, a biological half-life of 6 days for antibodies located inside the tumour was considered. Firstly, we can see that uniform and linear distributions of 90Y-, 124I-, or 188Re-nanoobjects from 90Y- and 188Re-nanoobjects are coupled to antibodies distributed exponentially throughout a 1.0 cm radius tumour are to the right of those for complications, whereas those for smaller tumours are to the left. Note that TCP curves are localized too far away from the left of the NTCP curves to be plotted on 124I-NPs radiolabelled antibodies distributed exponentially throughout the tumour, maximal TCP could not be reached without lung complications.β-emitters 131I and 177Lu, TCP curves for uniform and linear distributions shift to the right whereas NTCP curves remain unchanged when the tumour size increases. This shift towards higher numbers of radionuclides still increases when the biological half-life decreases, meaning that the risk of pneumonitis increases.By comparing DTot/DLung is calculated for the 177Lu-NO, independently of the antibody distribution or tumor size. However, after TCP and NTCP analyses, 90Y and 188Re seem the best candidates for the treatment of NSCLC tumour when antibodies are distributed uniformly or linearly. For exponential antibody distribution, the radionuclide 124I becomes a more adequate candidate, especially for tumours equal to or larger than 1.0 cm radius.To conclude, the tumour-to-lung deposited dose ratios for both tumour sizes are similar to those obtained when only one radioactive atom is attached to each antibody. So, the highest β-emitters which could be used in radioimmunotherapy. NSCLC was selected as tumour model as its biological parameters are well reported in literature. TCP and NTCP were calculated according to tumour and normal surrounding tissue deposited doses resulting from MCNPX, a Monte Carlo electron, and photon and particles transport code. Dosimetric studies were performed for the five radioisotopes 90Y, 177Lu, 131I, 124I, and 188Re, for two spherical tumour sizes of 0.5 and 1.0 cm radii and for two biological half-lives. Moreover, these nanoobjects can be distributed uniformly, linearly, or exponentially throughout the tumours according to a new vascularized tumour model previously developed for MCNPX.This work presents the tumour control probability analysis for solid tumours when nanoobjects  contain one or several 188Re and 90Y show the highest deposited doses within the solid tumour.When nanoobjects contain only one radionuclide, simulations show that the dose absorbed by the solid tumour is insufficient for solid tumour treatment, regardless of the radionuclide used for RIT treatment or the biokinetics and spatial distributions of antibodies; even so β-emitters. The required number of atoms per nanoobject to get TCP = 100% changes according to numerous radionuclide physical properties such as the physical half-life, abundance of γ emissions, and energies of the emitted β-particles and γ particles, but also according to the biological properties of the nanoobjects such as their concentration inside the tumour, their spatial distribution, or their biological half-life. These results confirm the importance of performing individual treatment for each patient. The total absorbed doses to obtain excellent tumour control vary between 60 Gy and more than 5000 Gy depending on the radionuclide choice, tumour size, and nanoobjects spatial distribution. 90Y and 188Re are the choice if one wants to minimize the number of radioisotopes per nanoobject.Higher total absorbed doses can easily be achieved when single radionuclides radiolabelled-mAbs are replaced by nanoobjects containing several 90Y and 188Re remain the best candidates because they require the lowest number of radionuclides per nanoobject to reach a TCP of 100%. On the other hand, for larger 1.0 cm radius tumours, toxicity to the surrounding healthy tissue is observed when the nanoobjects are distributed exponentially throughout the tumour. This toxicity increases strongly for high-energy β-emitters and 124I becomes more appropriate to cure solid tumours. Such results indicate the importance of finding new strategies to insure the penetration of nanoobjects inside tumours.Finally, higher absorbed doses are often synonymous with higher toxicity. Consequently, NTCP usually limits our ability to administer the doses required to control the tumour. For small 0.5 cm radius tumours, simulations do not show any toxicity problems. In this case,


Colloidal Gas Aphron as a mobility control in enhanced oil recovery is becoming attractive; it is also designed to block porous media with micro-bubbles. In this paper, the effects of surfactant concentration, polymer concentration, temperature and salinity on the bubble size of the Colloidal Gas Aphron were studied. Effects of injection rates, Colloidal Gas Aphron fluid composition, heterogeneity of reservoir on the resistance to the flow of Colloidal Gas Aphron fluid through porous media were investigated. Effects of Colloidal Gas Aphron fluid composition and temperature on residual oil recovery were also studied. The results showed that bubble growth rate decreased with increasing surfactant concentration, polymer concentration, and decreasing temperature, while it decreased and then increased slightly with increasing salinity. The obvious increase of injection pressure was observed as more Colloidal Gas Aphron fluid was injected, indicating that Colloidal Gas Aphron could block the pore media effectively. The effectiveness of the best blend obtained through homogeneous sandpack flood tests was modestly improved in the heterogeneous sandpack. The tertiary oil recovery increased 26.8 % by Colloidal Gas Aphron fluid as compared to 20.3 % by XG solution when chemical solution of 1 PV was injected into the sandpack. The maximum injected pressure of Colloidal Gas Aphron fluid was about three times that of the XG solution. As the temperature increased, the Colloidal Gas Aphron fluid became less stable; the maximum injection pressure and tertiary oil recovery of Colloidal Gas Aphron fluid decreased. The film can decrease the transfer rate of the surfactant molecules between the viscous water layer and the bulk phase. The second performance of CGA is low diffusivity, which is the ability of the air that is in the core to transfer to the aqueous shell  is prepared by stirring a surfactant-xanthan gum solution at high speeds . The average bubble diameter of CGA can be about 10–100 μm; the behavior is that of a colloidal dispersion of a gas in a liquid  of the CGA were recorded as a measure of the stability. The effect of surfactant concentration, polymer concentration, temperature and salinity on the CGA bubble size was investigated. The effects of the CGA formulations and formation heterogeneity on pressure drop were examined by CGA fluid injection. The effects of CGA formulations and temperature on the performance of CGA fluid on oil recovery were also studied.6 (XG) provided by Changxing Chemical Company, China, and the surfactant was hydroxyl sulfobetaine (SL1) provided by Shengli Oilfield, with a purity of 33 %; the water used in experiments was tap water or simulated formation water. The simulated formation water consisted of sodium chloride and calcium chloride; the total dissolved solid value of the simulated formation water ranged from 20,000 to 160,000 mg/L and the mass ratio of Na+ and Ca2+ was 19:1. Oil was collected from Changqing Oilfield in China; the oil had a viscosity of 15.5 mPa s and a density of 0.835 g/cm3 at 20 °C. The acid number value of the oil was analyzed to be 0.21 mg KOH/g of sample. All of these tests were conducted at the 20 °C, except where otherwise specified.The chemical agents used in this study included polymer and surfactant. The polymer was xanthan gum with a molecular weight of 3.4 × 10The base fluid was prepared as XG and SL1 in tap water, and then the base fluid was stirred at 3500 rpm for 2 min by a blender ; the initial foam volume and the time required for the foam to drain one-half of initial volume solution were recorded. The formed CGA was also observed using a microscope . Microscopic pictures were taken at 10 min intervals depending on the formulation of the CGA fluid. The diameters of the CGA bubbles were determined by measuring the sizes of at least 200 bubbles from recorded pictures using custom-made image-analysis software.−1 by MCR 302 coaxial cylinder rheometer .The apparent viscosity of the fluid was measured by using the Brookfield DV II Digital Cone Viscometer . The LSRV of CGA was measured at the shear rate of 0.1 sThe homogeneous and heterogeneous sandpacks used for tests were 2.5 cm in diameter and 20 cm in length. There was a screen with a 1.0 cm diameter, which was placed at the center of the heterogeneous sandpack. The coarse sand was packed in the channel and the fine sand was packed in the annulus between the screen and the inner wall. The screen allows the communication of the fluid between the high and low permeable zones during the injection process. The schematic diagram of the heterogeneous sandpack is shown in Fig. The homogeneous sandpacks used for tests were 2.5 cm in diameter and 40 cm in length. The experimental procedure was as follows: First, the sandpack was saturated with simulated formation water; the permeability and porous volume of the sandpack were measured; crude oil of 2 PV was injected into the sandpack followed by a 72 h aging stage at 20 °C. After the initial oil saturation was set, the simulated formation water was continued until the oil production became negligible (oil cut less than 2 %). After the water flooding, 1 PV of CGA fluid or 1 PV of XG solution was injected to compare their performances as recovery fluids, followed by extended water flooding until the oil production became negligible. The data collected from the sandpack flood tests consisted of produced fluid volumes and pressures. The tests were conducted at 20 to 60 °C. The water, CGA fluid and XG solution were injected at a rate of 2 mL/min and they were prepared in 120,000 mg/L simulated formation water.The increase of the CGA bubble with time is an important element for determining the ability of the bubble to block pore media. Figure The effect of surfactant concentration on increasing in average bubble size with time is shown in Fig. Figure Figure Figure The change in bubble size of CGA fluid with time was studied at different salinity levels and the result is shown in Fig. The CGA fluid injection tests were investigated at different injection rates, surfactant concentrations, polymer concentrations, and reservoir heterogeneity. Table −1. This shear rate range represents the flow conditions experienced in water flooding experiments in typical reservoirs (Samuel et al. Figure The effect of SL1 concentration on the pressure drop is shown in Fig. The change in pressure drop caused by the injection of CGA fluid with 4000 mg/L surfactant concentration and different XG concentration is shown in Fig. The stability of the CGA fluid decreased with the XG concentration decreased. It was, therefore, significant to have a XG concentration greater than 1000 mg/L to form a stable CGA fluid for an extended period of time. However, the greater the XG concentration brought about base solution with higher viscosity, the more difficult it became to generate stable CGA. Therefore, it was vital to determine a critical XG concentration that would give the optimum CGA formulation. For the system used in this study, the maximum XG concentration was 6000 mg/L and the minimum XG concentration was 1000 mg/L.Using the chemical blend 6000 mg/L XG + 4000 mg/L SL1 to generate CGA, a heterogeneous sandpack displacement test, He1, was conducted to examine the effectiveness of this blend. The pressure drop curves both Ho4 and He1 as a function of pore volume of the injection fluid are shown in Fig. The designed sandpack with a screen enables the study of the impact of heterogeneities on pressure drop in CGA fluid injection process. Even the injection process without any oil, the experimental result would also explain effectiveness of CGA for blocking the porous media in heterogeneous reservoirs.To further assess the performance of the CGA fluid as an enhanced oil recovery technique, four sandpack flood tests were conducted, and efficiency of oil recovery using the CGA fluid was compared to that of the XG solution. Using the chemical blend 6000 mg/L XG + 4000 mg/L SL1 to generate CGA, XG solution was prepared using the same procedure with 6000 mg/L XG. Table Figure Figure The results displayed in Table As XG or surfactant concentration increased, initial average bubble diameter and bubble growth rate with time decreased. When XG concentration was above 6000 mg/L, or surfactant concentration was above 4000 mg/L, it did not have any significant effect on retarding the bubble growth rate and initial average bubble diameter. Between 40 and 60 °C, bubble sizes of CGA fluid changed at a faster rate than that of the temperature interval from 20 to 40 °C. While the salinity was in the range 0–160,000 mg/L, bubble growth rate decreased and then increased slightly with increasing salinity.A high-pressure drop through the sandpack was observed when injecting CGA fluid continuously, which indicated that porous media were effectively blocked by stable CGA fluid. When XG or surfactant concentration decreased, the quantity and flow resistance of CGA in the system decreased. For the most effective CGA blocking, an XG concentration greater than 1000 mg/L but less than 6000 mg/L and a surfactant concentration of 4000 mg/L or greater, was observed. The effectiveness of the chemical blend selected through the homogeneous sandpack flood tests was modestly improved in the heterogeneous sandpack. The high permeability channel zone was blocked, and the low permeability zone obtained a further use because of increased pressure drop in the course of CGA fluid injection process. CGA fluid was found to improve oil recovery after water flooding in sandpack. The tertiary oil recovery increased 26.8 % by CGA fluid as compared to 20.3 % by XG solution when chemical solution of 1 PV was injected into the sandpack. The maximum injected pressure of CGA fluid was about three times that of the XG solution. The tertiary oil recovery by CGA fluid decreased from 26.8 to 21.1 % when temperature increased from 20 to 60 °C.


The purpose of this study was to assess the predictive value of urine NaWe conducted a prospective multicenter observational study in five university ICUs. Patients with urine output (UO) <0.5 ml/kg/h for 3 consecutive hours with a mean arterial pressure >65 mmHg received a fluid challenge. Cardiac fluid responsiveness was defined by an increase in stroke volume >15 % after fluid challenge. Urine and plasma biochemistry samples were examined before fluid challenge. We examined renal fluid responsiveness (defined as UO >0.5 ml/kg/h for 3 consecutive hours) after fluid challenge as a secondary endpoint.+  and fractional excretion of sodium (FENa+)  were not statistically different between those who did and those who did not respond to the fluid challenge. Areas under the receiver operating characteristic (AUROC) curves were 0.51 (95 % CI 0.35–0.68) and 0.56 (95 % CI 0.39–0.73) for uNa+ and FENa+, respectively. Fractional excretion of urea had an AUROC curve of 0.70  for CRs. Baseline UO was higher in RRs than in renal nonresponders . The AUROC curve for RRs was 0.65 (95 % CI 0.53–0.78) for uNa+.Fifty-four patients  were included. Most patients (72 %) were not cardiac responders (CRs), and 50 % were renal responders (RRs) to fluid challenge. Patient characteristics were similar between CRs and cardiac nonresponders. uNaIn the present study, most oliguric patients were not CRs and half were not renal responders to fluid challenge. Routine urinary biomarkers were not predictive of fluid responsiveness in oliguric normotensive ICU patients. In the intensive care unit (ICU), oliguria is one of the first variables leading to a fluid challenge . Althoug+ concentration (uNa+) has long been considered a biomarker of a low intravascular volume state [+ independently of intravascular volume [+ has never been assessed in ICU patients. We therefore conducted this study to evaluate the value of uNa+ for cardiac fluid responsiveness in normotensive, oliguric ICU patients. We also examined the renal responsiveness  after a fluid challenge as a secondary endpoint.A positive cumulative fluid balance has been associated with poor outcome, especially in patients with acute kidney injury (AKI) . Hence, me state . Howeverr volume . HoweverBecause this study was observational and did not change daily practice, the institutional review board of the University Hospital of Paris North (IRB00003835) approved the present study (protocol 2013/47NICB) and waived the requirement for obtaining written consent. However, the patients’ next of kin were systematically orally informed and could refuse patient participation. Moreover, the patients were later, and as soon as possible, systematically informed and could refuse use of their data.They met criteria for oliguria, defined by urine output <0.5 ml/kg/h for 3 consecutive hours .The administration of a fluid challenge  was indicated by the physician in charge.Their mean arterial pressure was >65 mmHg and without significant change in norepinephrine dose (<20 %) during the last 3 h.They did not receive diuretics on the day of inclusion.This study was performed in five university hospital ICUs. Patients were included if they met the following criteria:Physicians were asked to explain the indications for fluid challenge. The exclusion criteria were patients under 18 years old, patients treated with diuretics, patients with stage 3 AKI, pregnancy, patients in whom a decision to withhold or withdraw treatment had been made, moribund patients, and patients who refused to participate.The main endpoint of the study was fluid responsiveness, defined as an increase in stroke volume >15 % at the end of the fluid challenge. Patients were classified as cardiac responders (CRs) or cardiac nonresponders (CNRs) accordingly. Secondary endpoints included renal fluid responsiveness, defined as a post-fluid challenge urine output >0.5 ml/kg/h for more than 3 h . Patient characteristics, Simplified Acute Physiology Score II (SAPS II) at admission, and reasons for ICU admission were recorded. At inclusion , we collected blood and urine samples, performed routine laboratory measurements, and recorded urine output during the previous 3 and 6 h.2. New onset of AKI was defined as (1) an increase in Screat level 26.5 mol/L within 48 h or increase in SCreat to 1.5 times baseline ≥26 μmol/L or >50 % compared with baseline value or (2) need for renal replacement therapy (RRT) [Baseline serum creatinine (Screat) level was determined from blood samples taken on admission. In cases where the baseline creatinine plasma level or estimated glomerular filtration rate (eGFR) was not available, the baseline creatinine plasma level was estimated by using the Modification of Diet in Renal Disease equation with a normal eGFR value of 75 ml/minute/1.73 m+, urine creatinine concentration, urine urea concentration (uUrea), and potassium concentration. Screat, Na+, potassium, urea, and chloride were measured at the same time, allowing calculation of fractional excretion of sodium (FENa+), fractional excretion of urea (FEurea), and urine/plasma creatinine.Urine samples were immediately analyzed in the central laboratory of each participating center for uNa+ would be clinically relevant if the 95 % CI of its AUROC curve was >0.75, corresponding to a good AUROC [+ >0.85 with 95 % CI >0.75 based on an estimation of 50 % of patients being fluid responders.Using fluid responsiveness as the main endpoint, we estimated that an area under the receiver operating characteristic (AUROC) curve of uNaod AUROC . Inclusi2 test. The marginal association of biomarkers with fluid responsiveness was studied using the Mann-Whitney U test. The AUROC curve to predict fluid responsiveness was built for urine biochemistry biomarkers. We determined the optimal threshold value using the “closest top left” method. All analyses were performed using IBM SPSS Statistics software . All p values were two-tailed, and a p value <0.05 was considered significant. Values are expressed as number and percentage or median and interquartile range accordingly.Categorical variables were compared using a χn = 22 females, SAPS II score 38 ± 17) between March 2014 and March 2015. The patient features are shown in Table Fifty-four patients were included , ultrasound-derived analysis , or echocardiography (n = 24). Before fluid challenge, only cardiac output and central venous oxygen saturation were lower in the CRs than in the CNRs (Table p = 0.18). During the inclusion day, the CRs and the CNRs received 1543 ± 1415 ml and 2253 ± 2381 ml of fluid, respectively (p = 0.28).Stroke volume was measured using calibrated pulse pressure signal analysis n = 3, ultrasp = 0.55), Urine soidium , and FENa+  were similar in the CRs and the CNRs, corresponding to AUROC curves for predicting fluid responsiveness of 0.51 (95 % CI 0.35–0.68) and 0.56 (95 % CI 0.39-0.73), respectively, for uNai and FENa+  and uUrea  were less in the CRs than in the CNRs  and 0.68 , respectively  were CRs to the fluid challenge. Baseline urine output . The AUROC curves for predicting renal fluid responsiveness were 0.65 (95 % CI 0.53–0.78) for uNa+, 0.57 (95 % CI 0.41–0.73) for FENa+, and 0.61 (95 % CI 0.45–0.77) for FEUrea. Urine output increased to 1.03 ± 1.67 ml/kg/3 h in CRs and to 1.81 ± 1.38 ml/kg/3 h in CNRs  compared with baseline during the 3 h after the fluid challenge  were RRs to the fluid challenge. These changes persisted 6 h after the fluid challenge. Baseline urine output was 1.07 ± 0.78 ml/kg/3 h in the RRs and 0.65 ± 0.53 ml/kg/3 h in the renal nonresponders (p > 0.05 between fluid responders and fluid nonresponders). Eleven patients (21 %) died during their ICU stay (p > 0.05 between CRs and CNRs).Twenty-one patients developed AKI, including seven patients (13 %) requiring RRT  in our patients. Clinicians should therefore rely on other markers of fluid responsiveness when deciding whether to initiate a fluid challenge in patients with oliguria. Nevertheless, we acknowledge that our definition of renal responsiveness was arbitrary, relying on the Kidney Disease: Improving Global Outcomes  definit+ was not strongly associated with fluid responsiveness. A poor predictive value for fluid responsiveness was observed.Our study has several limitations. First, the sample size was small. However, the sample size was sufficient to detect a good predictive value of the biomarker. This hypothesis can be rejected on the basis of our results. The low rate of inclusion could be explained by several factors. Our patients had to be both oliguric and hemodynamically stabilized, which may have limited the number of patients eligible for inclusion. Second, they had to be off drugs that interact with renal sodium handling . Third, monitoring of cardiac output or an echocardiography-certified physician was required to monitor stroke volume during the fluid challenge. Altogether, these points may limit the external validity of the results. Nevertheless, urine NaStroke volume was evaluated with different tools. These tools have been used with acceptable accuracy in monitoring stroke volume . Most imIn the present study, most oliguric patients were not cardiac responders and half were not renal responders to fluid challenge. Routine urinary biomarkers were not predictive of fluid responsiveness in oliguric, normotensive ICU patients.Most ICU normotensive patients with oliguria do not respond to fluid challenge.+ and urea concentration are not reliable biomarkers of fluid responsiveness in oliguric ICU patients.Urine Na Excessive reliance on oliguria and urine biomarkers may lead to excessive fluid loading with potentially harmful consequences.


To prospectively evaluate the predictive value of pre-treatment histogram analysis of apparent diffusion coefficients (ADC) at whole body diffusion-weighted imaging (WB-DWI/MRI) for patient outcome in primary ovarian cancers.2), T2-weighted and contrast-enhanced T1-weighted sequences prior to treatment. The primary tumour was delineated using semi-automated software and was analysed by using an ADC histogram approach: mean and median ADC, standard deviation (SD), coefficient of variation , kurtosis and skewness were calculated. Kaplan-Meier with log-rank statistics were used to correlate baseline ADC parameters to disease free survival (DFS). Effects of confounding patients- and tumour-related factors were taken into consideration using Cox proportional hazard model.Institutional review board approval and informed consent were obtained for this prospective study. Forty-four women diagnosed with FIGO stage III or IV ovarian carcinoma underwent 3-Tesla WB-DWI/MRI using 2 b-values . After multivariable analysis, CoV remained an independent prognostic biomarker for DFS (p=0.003) when taking patient’s age, FIGO stage, tumour grade and cancer antigen (CA)-125 level into consideration as clinical prognostic factors.In this pilot study, pre-treatment ADC histogram analysis of primary ovarian cancer using the CoV was an independent predictive marker of DFS suggesting a correlation between tumour heterogeneity and treatment resistance. Further research should elucidate the correlation with overall survival.


Treatments of severe rheumatic conditions in children are increasingly based on biologics. The most common adverse events on all kind of biologics are mild infections in ENT, pulmonary and urinary systems. The number of cases of varicella-zoster-virus (VZV) manifestations while being on biologics is constantly growing. No consensus exists about what to do when facing this situation yet.The aim of this work is to describe the French experience of VZV infection/reactivation management in children affected with chronic inflammatory rheumatisms and treated with available biologics in a real life setting.French pediatric rheumatologists were asked through the web site of the Société Francophone des rhumatismes et maladies inflammatoires de l'enfant -SOFREMIP- by phone and/or e-mail to report their cases of VZV manifestations on biologics using a standardized and anonymized e-CRF.21 cases of VZV infection/reactivation were reported in children less than 18 yrs, followed for rheumatic conditions treated with biotherapies. 19 had JIAs of which 9 had systemic JIAs, 1 had SLE, 1 had polyarthritis with immune deficiency. Biologics-associated treatments were NSAIDs in 5 cases, steroids in 9 cases, DMARDs in 14 . Biologics were anti-TNFs in 13 children , anti-IL1 in 6 , 1 had TCZ, and 1 RTX. A long delay was observed between the initiation of biologics and the VZV manifestations in the majority of patients, whatever the biologic. None of our cases was vaccinated against VZV. 12 children had varicella  and 9 patients had herpes zoster . 2 patients had a complicated clinical picture of VZV infection/reactivation: 1 had an ophthalmic zoster and 1 had a systemic dissemination of VZV with severe hepatic involvement and pancytopenia. NSAIDs were stopped 4 times out of 5 continuous treatment, steroids were stopped in 1/9 patients, DMARDs were interrupted in 8/14, and biologics in 15/21 cases. 16/21 patients received a specific anti-herpetic drug despite a common non-complicated outcome, whereas 5 children were not treated in the same situation . All patients had favorable outcomes.This study shows an overrepresentation of systemic JIAs among patients infected by or reactivating the VZV. This group of patients may be more immunosuppressed than others. In spite of the great heterogeneity of VZV management in France in children treated with biologics, the outcome was invariably good. This suggests 2 important points (i) VZV control may not need any of the cytokines/pathways targeted by the biologics we use, (ii) VZV management on biologics should be rationalized.None declared.


Tumour budding (TB) and Tumour Stroma Ratio (TSR) may be rewarding in the treatment stratification of patients with stage II colon cancer. However, lack of standardization may exclude these parameters from being used in a clinical setting. The purpose of this methodologic study was to compare stereology with semi-quantitative estimations of TSR, to investigate the intra-tumoural heterogeneity of TB and TSR, and to assess the intra- and inter-observer agreement.Three paraffin embedded tumour blocks, one of them representing the deepest invasive front, were selected from each of 43 patients treated for stage II colon cancer. TSR was estimated in H&E sections semi-quantitatively using conventional microscopy, and stereologically on scanned slides, using the newCAST stereology platform. TB was scored across 10 high power fields at the invasive front in cytokeratin AE1/AE3 stained sections.p < 0.001). Inter-observer agreement was moderate to substantial for both TB (Κappa = 0.46–0.73) and TSR (Κappa = 0.70–0.75).Subjective, semi-quantitative estimates of TSR significantly correlated to the stereological estimates, with the best correlation found for sections with the deepest invasive tumour penetration  for TSR varied from 0.322 based on stereological hotspot estimation to 0.648 for the semi-quantitative evaluation. For TB, ICC varied from 0.646 based on continuous data to 0.698 based on categorical data (cut-off: 10 buds). Thus, the intra-tumoural heterogeneity for both TB and the semi-quantitative estimation of TSR was low.We recommend using only one tissue section representing the deepest invasive tumour area for estimation of TSR. For TB we recommend using one tissue section; however due to low representation of high-budding tumours, results must be considered with caution.The online version of this article (10.1186/s13000-018-0697-9) contains supplementary material, which is available to authorized users. Tumour Stroma Ratio (TSR) and Tumour Budding (TB) to provide prognostic information.Colon cancer (CC) is among the most frequent cancers in the Western World . SurvivaTSR is an estimate of the proportion of malignant epithelial cells and stroma, evaluated in a hematoxylin and eosin (H&E) stained tissue section, representing the deepest invasive area of the primary tumour . High TS, highest stroma fraction). Heterogeneity of TSR in CC needs to be further investigated from the methodological point of view for future clinical, diagnostic implementation.Heterogeneity of TSR has been described in individual tumours , 6. To cepithelial mesenchymal transition (EMT) at the invasive tumour front and thus represent the cell-biological correlate of the tumour-stroma-interphase. Tumour buds are defined as single tumour cells, or clusters of up to 4 tumour cells, in the stroma at the invasive tumour margin [www.cap.org/cancerprotocols). Also, the International Tumor Budding Consensus Conference Group [TB may reflect the r margin . Severalr margin –12 and fr margin –15, and ce Group  stronglyce Group , 13–15, ce Group . Recent ce Group . Intra-tce Group , but thece Group , and intce Group . This chThe aim of this methodological study was to investigate the heterogeneity of TSR and TB in stage II CC, and to address the issue of whether the histologic section representing the deepest invasive tumour margin is representative of the whole tumour regarding TSR and TB. We compare semi-quantitative estimation of TSR by conventional microscopy with the quantitative gold standard represented by stereology. Finally, we provide data on intra- and inter-observer reproducibility.per patient varied from three to 24 (mean = 5.3). Histologic sections of 4 μm thickness were cut from all blocks (N = 229) and stained with H&E. Each tumour was represented by three sections.Archival, formalin fixed, paraffin embedded tumour tissue samples from 43 consecutive patients, operated for stage II CC at the Department of Surgery, Vejle Hospital, Denmark in 2002, were retrieved. None of the patients had received preoperative chemo- or radiotherapy. The study population consisted of six mucinous adenocarcinomas and 37 adenocarcinomas (NOS). Mean age was 72.7 years (range 48–70). According to the 7th edition of American Joint Committee (AJCC) TNM classification, 34 of the tumours were classified as T3 and nine as T4. The total number of tumour-containing tissue blocks Using a 2.5× or 5× objective the section representing the deepest invasive front of the tumour was selected. Two additional sections were selected using a random number table.We estimated TSR in H&E stained sections by two different approaches: a) subjective, manual (semi-quantitative) by conventional microscopy, and b) stereology (quantitative), using computer assisted software.a) Using a 2,5× or 5× objective with field size area 78.5mm2 and 19.6 mm2, respectively, the invasive area with the highest representation of tumour stroma was selected. Subsequently, using a 10× objective with field size area 4.9 mm2 the part of the sample with the highest fraction of stroma (hot-spot sampling) was subjectively selected. Tumour cells were present at all borders of the image field (north-east-south-west) as described by Huijbers et al. [per microscopic field and scored into four groups . Whenever a score was difficult to settle in the selected area, the decision was guided by the overall impression of the stromal fraction in the tumour. Areas with necrosis were avoided. In mucinous tumours, the area with mucin was visually excluded for the scoring. Major vascular structures and smooth muscle tissue were also visually excluded, whereas nerves, smaller vascular structures and lymphocytic infiltration were not excluded from the stromal compartment.b) The stereological analysis was performed to obtain unbiased, absolute estimates of the TSR, using the computer assisted stereology system newCAST . All H&E stained sections were scanned at 40× magnification by a NanoZoomer XR scanner . The image format was NanoZoomer Digital Pathology Image (*.ndpi) with a resolution of 226 nm/pixel , i.e. 4.4 × 4.4 pixels/μm, corresponding to a final magnification of × 1.558). First, at low magnification (2×) we estimated TSR in the whole tumour area, which was manually outlined as the region of interest (ROI), and superimposed a grid with 5 × 5 points (25 points). We used systematic random, uniform sampling and a sample fraction of 100%. A point (i.e. a cross) was counted as tumour, whenever the upper right corner of a cross hit a viable tumour cell, and as stroma, whenever the upper right corner of a cross hit a stromal area. Points hitting areas of smooth muscle, adenoma, tumour lumen, necrosis, mucin, and large vessels were not counted. Subsequently, the area representing the highest density of stroma (the hotspot sampling) was investigated at × 10 magnification, using a grid with 4 groups and 6 × 7 points (42 points per group) superimposed on the selected area  and mounted on FLEX IHC Microscope Slides . The pretreatment processes were performed using PT Link (DAKO). Heat-induced epitope retrieval was achieved with Envision Target Retrieval Solution (DAKO) at pH 9 and 97 °C for 20 min. Staining was performed using a DAKO Autostainer Link 48 (DAKO). Endogenous peroxidase activity was blocked by Envision FLEX Peroxidase-Blocking Reagent (DAKO). The primary antibody was mouse monoclonal cytokeratin AE1/AE3  diluted 1:250 with Envision Flex antibody diluent (code S2022 DAKO). Primary antibody was incubated for 30 min. at room temperature, and for amplification Envision Flex+ Mouse (Linker) (DAKO) was used for 20 min. Bound antibodies were detected by Envision FLEX/HRP (DAKO) and visualised by Envision FLEX DAB (DAKO) with chromogen diluted in Envision Flex Substrate Buffer (DAKO). Meyer’s hematoxylin  was used as counterstain and finally, the histological slides were cover slipped with Tissue-Tek PERTEX .Serial sections were cut from the selected tumour blocks  stained sections. First, the sections were examined at low magnification, and the area of the invasive margin representing the highest density of TB was subjectively selected (hot-spot sampling). The number of tumour buds were then counted in 10 HPFs using 40× objective with field size area 0.3 mmIntra-observer analysis was performed on all sections for both TB and the semi-quantitative estimation of TSR with a four-week washout period as count A1 and A2, respectively. For inter-observer analysis a subset of 50 randomly selected sections was chosen, and TSR and TB were estimated by an independent observer as count B. The stereological, quantitative evaluation of TSR was not reproduced according to the high reliability of stereological methods.Data were summarized and inspected by standard statistical methods. Inter- and intra-tumoural variability was assessed by calculation of intra-class correlation coefficients (ICC) , using a2-test to compare the estimates of TSR obtained by stereology and conventional microscopy. The correlations were evaluated by Spearman’s correlation coefficients, and the differences were tested using Wilcoxon signed rank test. The correlations of TB obtained in the deepest invasive section and the two randomly selected sections were evaluated by Pearson’s correlation coefficient, while Wilcoxon signed rank test was used to investigate differences in the mean number of buds between the three sections. Simple and weighted kappa (K) values were generated to compare intra- and inter-observer variability [P-values less than 0.05 considered significant. The statistical analysis was performed using the software STATA version 14.0 .We used chiiability , and agriability  as moderp < 0.001), and there was a trend towards overestimation of TSR compared to the stereological estimate within the whole tumour area (p = 0.291)  for the whole tumour area and 0.56 range: 0.12–0.94) for the hot-spot sampling area. We found the semi-quantitative method to underestimate TSR compared to stereological estimates of the hot-spot sampled area (2–0.94 foN = 129) and for each of the three individual sections from each tumour, i.e. the section with the deepest tumour penetration and the two randomly selected sections A and B  and improved to almost perfect (Kappa range 0.78–0.83), when categorizing the four tiered TSR-data into high (TSR > 50%) or low (TSR ≤ 50%). Also, the inter-observer agreement increased, when categorized into two groups (Kappa range 0.70–0.75)  was 2.7 buds per HPF. Using 10 buds per HPF as cut-off, we defined high-budding as an average of ≥10 buds across 10 HPFs, as proposed by Karamitopoulou et al. [Including all sections we found a mean of 3.55 buds (range 0–32) u et al. . We founper HPF was 3.5 for the sections representing the deepest invasive tumour margin and 3.8 and 3.3 for the randomly selected sections A and B, respectively. The Pearson correlation coefficients for the correlation between the deepest invasive tumour section and the random sections A or B ranged from 0.674 for the correlation between the former and random section A (count A1) to 0.812 for the correlation with random section B (count A2) (p < 0.001).The mean number of buds The magnitude of ICCs for TB was similar to that obtained for TSR Table  and withOverall, the intra-observer agreement was in a clinically useful range varying from moderate to substantial Table . The kapIn this methodological study we investigated the heterogeneity of TSR and TB in 43 consecutive stage II adenocarcinomas of the colon and found that the intra-tumoural variation of both TSR and TB was considerably lower than the biological variation. We also compared semi-quantitative estimates of TSR based on conventional microscopy with unbiased, stereological estimates and found a significant correlation between semi-quantitative estimates and stereological estimates in hot-spot sampled areas, especially when only considering the deepest invasive tumour section.We investigated the heterogeneity using three sections, well aware that this only represents a minor part of the whole tumour. Because of the retrospective design, it was impossible to overcome sampling bias, as the investigated tissue had already been sampled and prepared for diagnostic purposes. ICCs estimated by conventional microscopy for both TB and TSR are comparable. The similarity in intratumoral heterogeneity may reflect TB as the cell-biological correlate of the tumour stroma interphase.We found ICCs for the stereological estimates of TSR to be considerably lower than the ICCs calculated for the semi-quantitative estimates. Moreover, the stereological estimates of TSR in the hot-spot sampled areas revealed a considerably lower ICC than those obtained from the whole tumour area. This reflects the differences in technical approach and may be explained by the higher degree of detail and precision afforded by stereology. The level of detail is highest in the stereological hot-spot sampled estimation of TSR, and as expected this results in the highest level of intratumoral heterogeneity.Stereology is considered the gold standard for obtaining quantitative, histopathological data, but only one other study has measured the relative proportion of tumour cells using virtual slides and point counting . CompariWe found significant correlations for TSR obtained by stereology in the hot-spot sampled areas and by the semi-quantitative technique. Nevertheless, there were discrepancies. Part of the explanation might be the use of different study fields for the stereological hot-spot estimation and the semi-quantitative estimation, as these were not aligned but chosen subjectively for each method, guided by the highest stromal fraction. The ‘borderline’ cases were characterized by difficulty in distinguishing stroma and smooth muscle tissue. Morphologically, these two types of tissue can be distinguished by careful inspection of the cell nuclei. The smooth muscle cells have nuclei with rounded ends (cigar-shaped), while fibroblasts have more spindle shaped nuclei. Also, the smooth muscle fibres are often more eosinophilic in H&E stained sections than the collagenous, fibroblastic stroma. For some troublesome cases one may use Masson’s Trichrome, which stains smooth muscle fibres red and collagen fibres blue. Another option is immunohistochemical stain for desmin, which identifies smooth muscle fibres Fig. . Both meDistinguishing fibrous stroma from smooth muscle tissue was problematic for both the stereological and the semi-quantitative approach. However, when in doubt using the semi-quantitative technique we had the possibility to find and compare the area of interest with the area of tunica muscularis, and the final decision was made “eye-balling” the overall representation of stroma in the whole tumour area. This was not an option for the stereological approach, and some variation was expected due to the subjectivity in deciding on fibrous stroma or smooth muscle. We have not investigated intra- and inter-observer variation for the stereological estimation, but studies using a similar approach report excellent inter-observer agreement with kappa values of 0.97  and 0.98For the semi-quantitative method we found a moderate to substantial intra- and inter-observer agreement, which was optimized by using a dichotomized categorization. This is in accordance with previous studies using the same method, but results vary. In a recent study, TSR was evaluated using both a “global” method, estimating TSR in the whole available tumour area, and a “focal” method evaluating TSR in one single field (× 10 magnification) in the deepest invasive region of the tumour. The authors found method-dependent kappa values for intra-observer agreement of 0.45  and 0.84 , and the inter-observer kappa values were reported in the range 0.13–0.53  and 0.48–1.00  . The finn = 18). This resulted in almost unchanged correlation coefficients for correlations between the subjective, semi-quantitative estimates of TSR and the stereological estimates; 0.431 for whole section and 0.571 for hotspot area .Estimation of TSR in mucinous tumours is debated. We investigated the impact of the mucinous component in the six mucinous adenocarcinomas included in our study by performing a sensitivity analysis excluding the sections of mucinous CC  stained sections as recommended in a recent review . We founKoelzer V H et al.  selectedOverall we found acceptable intra- and inter-observer agreement, which is in accordance with earlier studies using the same method , 18. HowWe also detected AE1/AE3 positive staining of endothelial cells of vascular neoangiogenesis, which could be difficult to distinguish from TB cells. However, strict criteria demanding a discernible nucleus in the tumour cell or a lumen in a vessel were helpful in most cases.A number of other structures can have a budding-like appearance: fragmentation of tumour glands induced by abundant inflammatory infiltrate; retraction artifacts around fragmented tumour glands; fragments of tumour tissue surrounded by abundant mucinous extracellular matrix. Cytoplasmic fragments were also disturbing elements, but the strict rule of a visible tumour cell nucleus proved useful, as reported earlier in a multicenter study .This study of adenocarcinomas of the colon documents visual, subjective, semi-quantitative estimates of TSR to be correlated to stereological estimates of TSR with the best correlation afforded using the histological section with the deepest invasive tumour penetration. For both TSR and TB we found moderate to substantial inter-observer agreement, minor intra-tumoral heterogeneity, and high correlation among sections from the same tumour. For future studies of TSR we recommend the easy, cost efficient, and fast semi-quantitative technique and the use of one tissue section representing the deepest invasive tumour area of the adenocarcinoma. Regarding TB, we recommend using one tissue section. Considering the low proportion of high-budding tumours, further methodological studies are needed for evaluation of TB heterogeneity in rectal adenocarcinoma and CC in more advanced clinical stage of disease.Additional file 1:Table S1. Tumour stroma ratio estimated semi-quantitatively by conventional microscopy and stereology. Table S2. Correlation coefficient for correlations between tumour stroma ratio in the deepest invasive tumour section and random sections A and B. (DOCX 40 kb)


PDGFA, PDGFB and PDGFRA were >5-fold higher in KI2367 than in KI2368 and the expression levels of 994 genes were > 5-fold higher in KI2368 than in KI2367. These results suggest the presence of intra-tumour molecular heterogeneity in this patient. This heterogeneity may influence the response to targeted therapies. Multiple biopsy, liquid biopsy and genomic analysis of intra- tumour molecular heterogeneity may help guide a more precise and effective plan in selecting targeted therapies for ccRCC patients.Inter- and intra-tumour molecular heterogeneity is increasingly recognized in clear cell renal cell carcinoma (ccRCC). It may partially explain the diversity of responses to targeted therapies and the various clinical outcomes. In this study, a 56-year-old male ccRCC patient with multiple metastases received radical nephrectomy and resection of the metastatic tumour in chest wall. The surgical specimens were implanted into nude mice to establish patient-derived xenograft (PDX) models with KI2367 model derived from the primary tumour and KI2368 model from the metastastic tumour. The two modles were treated with Sorafenib, Sunitinib, Axitinib, combined Sorafenib/Sunitinib, or alternating therapy of Sorafenib and Sunitinib. Significant anti-tumour activity was found in KI2367 treated with Sorafenib/Sunitinib monotherapy, combined Sorafenib/Sunitinib, and alternating therapy of Sorafenib/Sunitinib (P<0.05) but not in that treated with Axitinib monotherapy. In contrast, KI2368 was significantly responsive to Sunitinib monotherapy, combined Sorafenib/Sunitinib therapy and alternating therapy of Sorafenib/Sunitinib but not responsive to Sorafenib and Axitinib monotherapy (P<0.05). RNAseq of the two models demonstrated that the expression levels of 1,725 genes including the drug targeted genes of  HER2-positive breast cancer, anti-EGFR therapy for KRAS wild-type colon cancer, and BRAF inhibitor for BRAF mutant melanoma [Over the past decade, the high-throughput deter-mination of biological molecules such as whole genome sequencing, transcriptome sequencing and proteomics has increased our knowledge about the molecular mechanism of tumourigenesis. On the other hand, the overall incidence of cancers is gradually increasing . The modmelanoma .Renal cell carcinoma (RCC) can be divided into several subtypes according to its histology and molecular differentiation –8. In reAlthough a large number of molecular changes in hundreds of renal tumours have been obtained by genome-wide analyses, the effects of these changes on the characteristics of the tumour and clinical presentations have not been clearly elucidated , 24. TheHere we investigated the intra-tumour heterogeneity of gene expression and mutation load in primary and metastatic clear cell renal cell carcinoma (ccRCC) and analyzed the diverse responses to targeted therapies using the patient-derived xenograft (PDX) models. Surgical samples of primary and metastatic ccRCC were collected from a patient. Two PDX models were established to test their responses to targeted therapies. Transcriptome sequencing (RNA-seq) of PDXs was performed to detect the genetic diversity between the primary and metastatic ccRCC.The patient was discharged 6 days after the operation. His general status was well after the operation for one month. Afterwards, the patient began to take Sorafenib . Partial response was obtained for his pulmonary metastasis, brain metastasis progressed . The patThe KI2367 PDX model was derived from the primary ccRCC tumour. We treated this model with three monotherapies , Sorafenib and Sunitinib combined therapy, and Sorafenib/Sunitinib alternating therapy. The results showed that there was obvious anti-tumour activity from Sorafenib/Sunitinib monotherapy and from combined and alternating treatment of Sorafenib and Sunitinib, with the ΔT/ΔC% values of -66.91%, −46.57%, −238.03% and -60.24% respectively. However, Axitinib showed no significant anti-tumour activity to KI2367, with the ΔT/ΔC% value of 82.11%. A statistically significant difference was observed between vehicle/Axitinib and other treatment groups (P<0.05). No significant difference or synergistic tumour growth inhibition was observed between the 4 effective treatment groups . Synergistic tumour growth inhibition was observed in the Sorafenib and Sunitinib combined therapy groups compared with the monotherapy groups (P<0.05)  and anti-VEGF antibodies, such as Sorafenib, Sunitinib, Pazopanib and Axitinib are now recommended as the first- or second-line treatment for RCC. Sunitinib has been approved by the United States Food and Drug Administration (FDA) and European Medicines Agency as a first-line treatment for RCC . The mamUnfortunately, it is difficult to achieve complete and long-term tumour control with targeted therapy. Tumours may adapt to chronic drug use and escape from drug-mediated growth control . Only a Another hypothesis for the poor long-term effect of targeted therapies is the heterogeneity of RCC. The high-throughput sequencing have identified significant genetic diversity and screened out several important driver mutations and multiple of passenger changes in RCC , 54. Theet al. applied next-generation sequencing to characterize intra-tumour heterogeneity in primary and metastatic ccRCC [et al. also compared the genetic alterations between primary and metastatic RCCs, and demonstrated that metastatic RCC had genetic features different from those of primary tumour [Inter- and intra-tumour molecular heterogeneity are intriguing and important characteristics of tumours. Intra-tumour heterogeneity with diverse genetic subclones in a single tumour has been gradually recognized in RCC . Nowell ic ccRCC , 24. Geny tumour , 24. They tumour –59.received Sorafenib therapy. During the follow-up period, metastases in lung became stable but metastases in brain progressed. Finally, the patient died of brain metastases. Subsequently, Sorafenib had a diverse effect on metastases at different locations in the same patient. The PDX models of KI2367 and KI2368 showed different responses to Sorafenib monotherapy (in group 2), also indicating that metastases in different locations may have different molecular changes that may relate to the diverse responses to targeted therapies. Consequently, metastatic tumours could have diverse responses and some may become resistant to the targeted therapies[Our results also indicate that molecular heterogeneity especially the intra-tumour heterogeneity is an important factor for the diversity of response to targeted therapies. This patient had multiple metastases in brain, lung, and skin and underwent right radical nephrectomy. After the operation, the patient therapies.We observed that KI2367 and KI2368 had different response to the TKIs, indicating that primary and metastatic tumours have different genomic profiles. RNAseq analysis reveals that PDGFRA is highly expressed in KI2367 but not expressed in KI2368. The expression of PDGFRB is higher in KI2367 than in KI2368. Conversely, KIT is expressed in KI2368 but not expressed in KI2367. HIF1 is known to induce the transcription of many angiogenesis-related genes. The frameshift insertion in HIF1A may impact on the expression of PDGFRB and other genes in KI2368. The frameshift mutation of RICTOR in KI2368 may also affect the function of HIF1A and subsequently PDGFR expression. It is possible that the difference in PDGFR expression affects the drug responses in KI2367 and KI2368. We also found a VEGFB frameshift mutation in KI2368 but not in KI2367. VEGFB is dispensable for blood vessel growth but is critical for their survival of blood vessels. The VEGFB mutation may reduce the effectiveness of drugs such as Axitinib on VEGF receptors. Sorafenib, Sunitinib and Axitinib target the PDGFR and VEGFR. Axitinib is reported to inhibit KIT and the BCR-ABL fusion protein. Sorafenib also inhibits RAF family kinases, and Sunitinib inhibits KIT, RET, CD114 and CD135. It is likely that the activation of kinases other than PDGFR and VEGFR influences the different efficacy of the three drugs. In KI2368, we observed that the anti-tumour activity of combined or alternating therapies was stronger than monotherapy. The combined or alternating therapies can inhibit more targets and block the tumour growth.Taken together, these findings confirm again that there is intra-tumour molecular heterogeneity in ccRCC. The intra-tumour heterogeneity could influence the clinical outcome of targeted therapies and explain the diverse drug response among metastatic tumours at different sites from a ccRCC patient. Therefore, intra-tumour heterogeneity may lead to tumour evolution and becomes a huge challenge to the development of personalized therapy for RCC. A single tumour-biopsy may not be able to accurately reflect the features of a tumour. Multiple biopsy, liquid biopsy and genomic analysis could further identity intra-tumour molecular heterogeneity. Multiple biopsies in patients with multiple metastases are not clinically feasible. However, with the development of minimally invasive technology and imaging technology, it will be possible to collect multiple biopsies. Furthermore, liquid biopsy is also a very popular method and may be used in the future. Thereafter, precise and comprehensive results could help us more effectively plan targeted therapies. Further studies are needed to understand the cause of intra-tumour heterogeneity in ccRCC to guide the clinical treatment of patients.Female BALB/c nude mice  were supplied by Beijing FuKang Bioscience . Procedures related to animal handling, care, and treatment in this study were performed according to the guidelines approved by the Institutional Animal Care and Use Committee (IACUC) of Crown Bioscience following the guidance of the Association for Assessment and Accreditation of Laboratory Animal Care (AAALAC).The patient was diagnosed with ccRCC at the Department of Urological Oncology of Peking University Cancer Hospital. All protocols in this study were reviewed and approved by the Institutional Medical Ethics Committee, and written informed consent was obtained from the patient. After operation the specimens were examined by pathologists, and some of the samples were used for laboratory study. The specimens for PDX models were preserved in HTK solution  at 4°C and treated within 6 hours..3 fragments (n=20), and 5 mice were implanted with 4 blocks each. The dorsal surface of the mouse was prepped with betadine solution, and the specimens were subcutaneously inoculated into the flanks of mice with a 16-G needle. The tumour growth was monitored twice weekly using a calliper. The established tumour models (passage 0 or P0) were serially re-engrafted to maintain the tumours in vivo. These subsequent passages were called P1, P2, P3, etc. When the tumours reached 500–700 mm3 (1/2 length x width2), they were harvested for the next round of engraftment for serial passage or conducting studies of efficacy and molecular analyses.Methods and parameters regarding PDX and tumour inhibition assay using the PDX have been described previously , 62. TheThis 56 years old male patient had a right renal tumour Figure  with a s3 to 150 mm3. The established PDX models were KI2367 from the primary tumour and KI2368 from the subcutaneous metastatic tumour of the chest wall. Each PDX model was divided into 6 experimental groups with 4 mice in every group. The control group (Group 1) was treated orally with vehicle daily (QD)*4 weeks, and the treatment groups were treated with one of following dosing regimens: Sorafenib , Sunitinib , Axitinib , Sorafenib 50 mg/kg+sunitinib 60 mg/kg p.o.  and Sorafenib 50 mg/kg and Sunitinib 60 mg/kg in alternation . The %ΔT/ΔC value was calculated for assessing the tumour response to the treatment. (%ΔT/ΔC= (mean(T)-mean(T0))/(mean(C)-mean(C0)) *100%, T- Treatment group value, T0 - Treatment group initial value, C - control group value, and C0 - control group initial value). The tumour growth inhibition (TGI) = (1-%ΔT/ΔC))*100.Treatment for mice was initiated when the tumours from 2 ccRCC PDX models reached 100 mm2. Samples of mice treated with vehicle were stored for future analysis. Any remaining tumour was re-implanted for maintenance of a PDX model.The mice were kept in individually ventilated cage (IVC) systems at constant temperature and humidity, with 4 animals in each cage. The data for tumour growth and normal behaviour including mobility, visual estimation of food and water consumption, body weight gain/loss measured twice weekly, eye/hair matting and any other abnormal effects, were collected every 3 to 4 days. Tumour sizes were measured every 3 to 4 days using the formula: V = 0.5 length x width2(FPKM). SNP and INDELs were detected by STAR [Snap frozen PDX tumour samples were used to extract RNA for transcriptome sequencing (RNA-seq). The purity and integrity were checked with an Agilent Bioanalyzer prior to RNA sequencing. Only RNA samples with RIN >7, 28S/18S >1 and mouse content <10% were used for library construction and sequencing. The sequencing was performed at PE125 on an Illumina HiSeq2500 platform (KI2367) and PE100 on an Illumina HiSeq2500 platform (KI2368) by certified Illumina service providers. The RNAseq raw data were first cleaned by removing reads that were preferentially mapped to a mouse genome (UCSC MM9). Transcript expression was estimated by MMSEQ  and repr by STAR  mapping  by STAR  variant  by STAR  and deFu by STAR .All statistical analyses were performed using SPSS . Two sample t-tests were used to check the equality of means between two groups. One-way ANOVA was used to check the equality of means among 3 and more groups. Differences were considered statistically significant at P< 0.05.


Shock may complicate several acute childhood illnesses in hospitals within low-income countries and has a high case fatality. Hypovolemic shock secondary to diarrhoea/dehydration and septic shock are thought to be common, but there are few reliable data on prevalence or treatment that differ for the two major forms of shock. Examining prevalence and treatment practices has become important since reports suggest high risks from liberal use of fluid boluses in African children. The present study aims to estimate the prevalence, fluid management practices and outcomes of shock among hospitalised children.We analysed paediatric in-patient data collected using discharge case record review between October 2013 and February 2016 from 14 hospitals in Kenya which are part of a network  using similar tools for standardised clinical records with care directed by the local clinical team leaders. Data are from a period after dissemination of national guidance seeking to limit use of bolus fluids.A total of 74,402 children were admitted between October 2013 and February 2016. Children aged < 30 days or > 5 years, with severe acute malnutrition, surgical/burns, or cases with pre-defined minimum data sets were excluded from analysis. This resulted in 42,937 patients meeting the inclusion criteria. Prevalence of clinically diagnosed shock was 1.5 % (n = 622) and overall bolus use was 0.9 % (n = 366); 41 % (256/622) of children with clinically diagnosed shock did not receive a fluid bolus (but had a fluid plan for management of dehydration). Identified cases appeared mostly to be hypovolaemic shock secondary to dehydration/diarrhoea , with a high case fatality . Overall mortality for all admitted children was 5 %  and was 7.9 %  in children with dehydration/diarrhoea. The diagnosis of hypovolaemic shock was nearly always accompanied by additional clinical diagnosis (99 %), most often pneumonia or malaria. Where bolus fluids were used, they were prescribed in accordance with guidelines (isotonic fluid at correct volume) in 92 % of cases. Inappropriate use of bolus fluids to treat milder forms of impaired circulation appeared very rarely.A diagnosis of shock is uncommon at admission and use of fluid bolus is rare in admissions to Kenyan hospitals. A fluid bolus, when prescribed, is mostly used in children with hypovolemic shock secondary to dehydration and case fatality in these cases is high. We found little evidence of liberal use of fluid bolus that might cause harm in a period following dissemination of national guidelines suggesting very strict criteria for fluid bolus use. Shock, defined as relative or absolute reduction of circulatory volume with consequent impaired tissue perfusion, oxygen delivery and waste removal, has a high risk of mortality and requires prompt appropriate intervention , 2. HoweData for analysis was routinely obtained from the 14 hospitals in Kenya that form the CIN, which is a collaborative effort between the Kenya Medical Research Institute (KEMRI), the Kenya Paediatric Association, and Kenya’s Ministry of Health that aims to improve the availability of data for decision making and to help improve quality of care. A detailed description of the CIN hospitals, their selection process, management and geographical spread has been previously provided . Data isData collection from the initiation of the network up to February 2016 were analysed. Children with severe acute malnutrition, aged < 30 days, with surgical/burns, those with minimal data sets, and those aged > 5 years were excluded. Severe malnutrition cases were excluded as they have distinct management fluid guidelines. Neonates (<30 days old) were excluded because there is lack of consensus on fluid management guidance with no clear policy in Kenya, while children > 5 years old are not covered by the Kenyan guidance that is the main focus of the CIN. Otherwise, all cases with comprehensive data not meeting exclusion criteria were included in the analyses. To examine the prevalence of shock amongst admissions, shock was defined as a child with any of the following: a clinician’s indication that the child had shock as a problem accompanying diarrhoea and dehydration (an indication of the severity of fluid loss); a diagnosis of shock associated with an underlying cause (e.g. septic shock); or use of rapid bolus fluid therapy in a child irrespective of diagnosis. When attributing a probable cause for an admission with shock (as defined above) we considered it to be hypovolaemic (hypovolaemic shock) in nature in children with a diagnosis of diarrhoea and dehydration and non-hypovolaemic (other) in the absence of this diagnosis. We examined the fluids prescribed for the treatment of shock and calculated the volume per kilogram body weight based on the fluid therapy plan and the recorded admission weight. We also examined the recording of key clinical features used in guidelines to support the diagnosis of shock. Children fulfilled locally adapted WHO criteria for shock  if they had all four of the following: impaired consciousness (AVPU score < V), weak/absent pulse, cold hands and temperature gradient, and capillary refill > 3 seconds, plus sunken eyes and slow skin pinch. The presence of shock plus diarrhoea symptoms classified such cases as diarrhoea-related hypovolaemic shock. Impaired circulation was defined as presence of any one of weak/absent pulse, cold hands and temperature gradient, or capillary refill > 3 seconds. Information on prevalence is summarised as proportions with shock or impaired circulation among those admitted. Fluid treatment of shock, number of boluses, types of shock noted, and case fatality are summarised as frequencies and proportions. Children with diarrhoea/dehydration and shock were defined to have comorbidity if there was another clinical diagnosis in addition to diarrhoea/dehydration. No imputation for missing data was done and because this affects denominators, all numerators and denominators are reported.A total 74,402 children were admitted between October 2013 to February 2016 and 42,937 records  were analysed after applying the exclusion criteria above. Characteristics for the 42,937 participants are summarised in Table Fluid bolus was prescribed in only 0.85 %  of all admissions. Most boluses  were given for hypovolaemic shock and only 11 % (40/366) were given for non-diarrhoeal shock (other shock). Forty four percent (256/582) of children with diarrhoea/dehydration identified as having shock (hypovolaemia) did not receive rapid fluid bolus but received recommended fluid management of dehydration (WHO plan C). All the children with shock who did not receive a rapid fluid bolus (but other recommended fluid management) had hypovolaemia.When a fluid bolus was prescribed, it was defined as correctly prescribed if an isotonic fluid  was used at a volume of 20 mL/kg (±4 mL/kg) and was correct in 92 % of cases. In a small number of cases , fluids such as Half Strength Darrow’s/5 % Dextrose mix, Ringer’s/5 % Dextrose mix, or 5 % Dextrose were used for fluid boluses. One bolus was infused in 88 % of recipients, 10 % received two boluses , and only one patient each received 3 and 4 boluses .P = 0.12). Among children with hypovolaemic shock, mortality in children who received rapid fluid bolus was 32.5 % (106/326) compared to 37.5 % (96/256) in those who only received WHO plan C .Five percent of all admission  died and 10 % (211/2115) of these deaths were associated with clinically diagnosed shock. Mortality in children identified with shock was 34 % (211/622), and mortality was 31 % (115/366) in the rapid bolus subgroup and 37.5 % (96/256) in the no bolus subgroup (odds ratio (OR) = 0.76; 95 % confidence interval (CI), 0.55–1.07; P = 0.008). Mortality in those with hypovolaemia plus malaria was 29 % (54/186) and in those with hypovolemia plus pneumonia it was 42 % (111/267).Most children with hypovolaemic shock had a second diagnosis (referred to as comorbidity) and this was seen in 99 % 579/582) of cases. Additional diagnoses in patients with shock are outlined in Table  of casesWe analysed data from CIN hospitals for prevalence of shock and use of bolus fluids in order to give an estimation of the prevalence of shock at admission and the use of rapid fluid bolus. The study was undertaken in the period immediately after dissemination of national guidelines suggesting rapid bolus fluids should only be used in children with four clinical features indicating shock who also had a history of diarrhoea and two signs of dehydration (sunken eyes and prolonged skin pinch). The data suggest shock is uncommonly diagnosed at admission in children aged 1 month to 59 months and that most cases are diagnosed in the context of multiple signs of hypovolaemia secondary to diarrhoea/dehydration. Thus, while just under 1.5 % of admissions were diagnosed with shock, approximately 7.5 % of admissions were noted to have at least one of the four clinical signs associated with impaired perfusion. Use of fluid bolus is rare (<1 % admissions) and is mostly used in those children with clinically identified hypovolaemia and dehydration (most with hypovolaemic shock).Although shock is identified rarely, it has a high case fatality and 10 % of all deaths were associated with the clinical syndrome. Nearly all cases of shock secondary to diarrhoea/dehydration also had a second diagnosis (comorbidities) and having an additional diagnosis was associated with an increased risk of death. Clinicians mostly prescribed the guidance recommended bolus type and volumes  and in 9These data from 14 Kenyan hospitals suggest that clinicians rarely use fluid bolus to treat non-hypovolaemic shock and extremely rarely use such boluses in those with signs of impaired circulation only. As the FEAST trial showed increased risk of mortality in children with shock (defined more broadly than in this study) from non-diarrhoeal cases and those who only have impaired circulation, these data are therefore reassuring and perhaps allay fears that considerable harm is being done through widespread use of bolus fluids . These dThere have been concerns that there is a high prevalence of severe sepsis in LICs with higher case fatality than in high-income countries , 11. HigThese findings need to be interpreted with consideration for known limitations pertinent in registry research such as ascertainment, selection and analytical biases . HoweverImproved use of simple bedside physiological measures together with biomarkers might improve the diagnosis of shock, help subclassify the clinical presentation by cause and assist in management including targeted anti-microbial or inotropic use. While fewer than 10 % of the deaths amongst the cohort studied could be directly associated with a diagnosis of shock on admission, in these cases, case fatality was very high and some cases may go unidentified. Comorbidity further increases the risk of mortality in hypovolaemic shock. This constellation of results suggests that the saving of lives associated with shock will likely require detection and intervention earlier in the disease course, more rapid referral where needed and improved supportive care. It is also possible that different treatment approaches are needed in children with different patterns of comorbidity. For example, less aggressive fluid regimens might perhaps be tested, particularly in children with hypovolaemic shock and signs of pneumonia. Such research will require large scale collaborative efforts that could benefit from initiatives such as the clinical information network in Kenya.The diagnosis of shock is uncommon at admission and use of fluid bolus is rare. Fluid bolus is mostly used in children with hypovolemic shock secondary to dehydration and clinicians mostly prescribe the fluid and amounts recommended in current guidance. Further improvements can be made in identifying and treating children with shock, perhaps particularly to improve availability of simple bedside monitoring devices.


This article has been corrected: The correct Grant Support information is given below:GRANT SUPPORTThis work was supported by the Wellcome Trust Research Career Development fellowship 090090/Z/09/Z (to A Hergovich); the BBSRC grant BB/102124811 (to A. Hergovich); the National Institute for Health Research University College London Hospitals Biomedical Research Centre; the Ministry of National Education of the Republic of Turkey (to R. Gundogdu); the Ligue Nationale contre le cancer (LNCC) grants RD14/75-80 (to J. Camonis) and RS14/75-54 (to M.C. Parrini); the Fondation ARC grant SFI20121205710 (to M.C. Parrini); the ARC grant SFI20111203931 (to J. Camonis); the ANR grant ANR-13-CESA-0010-001 (to P. Codogno); the Association Christelle Bouillot; INCA; and institutional INSERM and CNRS funding. Work was suported also by grantANR-08-NLAN-0290-01 to J. Camonis.44142-44160. https://doi.org/10.18632/oncotarget.9875Original article: Oncotarget. 2016; 7: