Cell senescence is a driver of ageing, frailty, age-associated disease and functional decline. In oncology, tumour cell senescence may contribute to the effect of adjuvant therapies, as it blocks tumour growth. However, this is frequently incomplete, and tumour cells that recover from senescence may gain a more stem-like state with increased proliferative potential. This might be exaggerated by the induction of senescence in the surrounding niche cells. Finally, senescence will spread through bystander effects, possibly overwhelming the capacity of the immune system to ablate senescent cells. This induces a persistent system-wide senescent cell accumulation, which we hypothesize is the cause for the premature frailty, multi-morbidity and increased mortality in cancer survivors.Senolytics, drugs that selectively kill senescent cells, have been developed recently and have been proposed as second-line adjuvant tumour therapy. Similarly, by blocking accelerated senescence following therapy, senolytics might prevent and potentially even revert premature frailty in cancer survivors.Adjuvant senostatic interventions, which suppress senescence-associated bystander signalling, might also have therapeutic potential. This becomes pertinent because treatments that are senostatic in vitro (e.g. dietary restriction mimetics) persistently reduce numbers of senescent cells in vivo, i.e. act as net senolytics in immunocompetent hosts. Although cancer remains a common disease, affecting an estimated 18 million of the world population in 2018, cancer-specific mortality has dropped sharply in the last few decades in developed countries. For example >70% of patients with breast cancer can now expect to live >10 years from diagnosis and many haematological and paediatric cancers have high cure rates ,4. Althoalways significant residual disease post surgery. It is also well established that the brain represents an immune privileged site, where immune-mediated removal of microscopic disease is limited, leaving a large number of cells that can only be ablated by chemo-radiotherapy. Mechanisms of treatment resistance are still poorly understood, but a pool of cells with stem like features associated with up-regulated DNA repair mechanisms and a highly migratory phenotype are thought to represent a resistant population that survive and re-populate the tumour after cytotoxic treatments . G. Gmax lepatients .In older diabetic men, metformin usage was associated with a reduction in age-related co-morbidity and frailty, with considerable effects in patients clustered as High Cancer and High Frailty risk . A meta-NCT02570672, NCT03451006, NCT02325245). Large clinical studies in which metformin is being tested for its capacity to reduce the onset of age-related multi-morbidity  clinical studies on the effects of metformin on frailty are now coming underway  will pr7Combination tumour therapies with senolytics as second-line adjuvant therapeutics show significant promise. However, specificity and sensitivity of senolytics are not sufficiently well known. This is already so for senescent cells arising from different normal tissues, and will be more pertinent for senescent tumour cells harbouring multiple genetic and epigenetic aberrations, frequently in genes highly relevant for efficient apoptosis induction.An important and so far essentially un-tackled issue for combination therapies involving senolytics will be the question of timing. Obviously, for senolytic interventions to be most effective, cells should have reached a mature senescent phenotype following first-line therapy, and tumour cells should not yet have escaped from senescence. Patients should have sufficiently recovered from first line therapies. A starting point to address this question might be that both the induction of a mature senescent phenotype following irradiation  and recoThe type(s) of tumour that should primarily be tested in combination therapies with senolytics is another important issue. We suggest diffuse high-grade glioblastoma because they are not amenable to surgery and success rates for conventional combined radio-and chemotherapy are very low and have not improved for decades. It seems very well possible that therapy-induced tumour and niche cell senescence is a significant driver of the essential limiting factor, tumour relapse.In the context of senostatic interventions, clarification of the relevant mechanism(s) of action appears to be the most relevant issue. While it appears that DR, mTOR inhibitors or metformin reduce local and/or systemic inflammation, it is far from clear whether this is their primary mode of action or a secondary consequence of, for instance, reduction of senescence. Do they actually reduce numbers of senescent cells in a tumour therapy context as suggested in Finally, if anti-senescence interventions are ever to become relevant in acute tumour therapy and long-term post-tumour care, the availability of senescence markers that can be assessed in humans will be crucial. At present, this is largely an unmet need. It is unclear whether and to what extent blood-based biomarkers for immunosenescence or inflammation might be informative for the senescence status in other tissues, and non-invasive markers for cell senescence do not exist to our knowledge.Data for this Review were identified by searches of MEDLINE, PubMed, and references from relevant articles using the search terms “senescence”, “senolytic”, “senostatic”, “cancer”, “suvivor” and related search terms as well as by searching based on names of investigators in the field. Abstracts and reports from meetings were not included. Only articles published in English between 1980 and 2019 were included.CRUK Pioneer Grant C12161/A24009 to TvZ and a MRC- Arthritis Research UK Centre for Integrated Research into Musculoskeletal Ageing (CIMA) Translational Grant to SM.Work leading to this review has been funded by


De), and we found that, under the prescribed waveform, the swimming speed decayed with the Deborah number in the small-De regime (De < 1.0). The swimming efficiency was independent of the Deborah number, and the decrease in the swimming speed was not significantly affected by the wave pattern.It has been suggested that the swimming mechanism used by spermatozoa could be adopted for self-propelled micro-robots in small environments and potentially applied to biomedical engineering. Mammalian sperm cells must swim through a viscoelastic mucus layer to find the egg cell. Thus, understanding how sperm cells swim through viscoelastic liquids is significant not only for physiology, but also for the design of micro-robots. In this paper, we developed a numerical model of a sperm cell in a linear Maxwell fluid based on the boundary element slender-body theory coupling method. The viscoelastic properties were characterized by the Deborah number ( O(10−5) to O(10−4) m/s [The swimming of spermatozoa is responsible for the reproduction process, especially for finding egg cells. The human spermatozoon is about 50–100 μm [0−4) m/s . Recentl0−4) m/s ,4. Thus,Over small scales, the viscous effect can dominate when the inertial effects become sufficiently small. Thus, the locomotion of sperm cells is governed by micro-fluid dynamics. Several researchers have studied how sperm swim from the perspective of fluid mechanics. Smith et al.  numericaMammalian sperm cells must swim through mucus layers in the genitals, such as the oviduct and the uterus. Mucus has viscoelastic properties . IshimotIn this study, we carried out a numerical investigation of sperm cells swimming through viscoelastic fluid. The viscoelastic fluid was modeled by a linear Maxwell fluid. We evaluated the swimming speed and efficiency whilst varying the Deborah number. In In this section, we explain the equations governing the motion of the sperm as well as our numerical methods. Details of the fluid mechanics of a Maxwell fluid in the low-Reynolds number regime can be found in ,15, and τ is the deviatoric stress of the fluid, λ is the relaxation time, and μ is the viscosity. D is the rate of deformation tensor, which is defined as:v is the velocity of the fluid. By introducing the invertible linear operator F can be written as [p is the pressure and δ is the delta distribution function in space and time, so that the point force F is concentrated at a certain point xs and time st. By using Green’s functions, the singularity solution of Equation (3) is given by [x,t; xs,st) and J are the pressure kernel and the Stokeslet for the Maxwell fluid, respectively, which are singular at xs and st:x; xs) and J0  are the Green’s functions of a Newtonian fluid:r = |r| and r = x – xs.We assumed that a sperm cell was immersed in an unbounded linear Maxwell fluid. We estimated the Reynolds number of the sperm swimming through the fluid to be much smaller than unity . Hence, itten as :(3)−∂p∂xgiven by :(4)−∂Pj∂t < 0 and that we had Stokes dynamics for t = 0 [t = st (> 0), the flow field was calculated by integrating the singularity solution with respect to time and space:q is the traction force per unit area, and S represents the surface of the cell.To describe the fluid dynamics of a sperm cell in viscoelastic fluid, we now introduce the boundary integral equation. We were required to define an initial condition due to the presence of the time derivative in Equation (4). We assumed, as a starting condition, that the dynamics were trivial for or t = 0 . For t =a/L = 3.57 × 10−3 [a is the flagellar radius and L is the length. Then, the flow field can be described by the following boundary integral—the slender-body coupling formulation:f is the force per unit length of the flagellum, and K0 is the slender-body kernel [In this study, the slender-body theory  was apply kernel . The deliξ, with the origin at the head–tail junction. We assumed a rigid connection between the head and the flagellum, and the minus ξ1-axis was set to coincide with the orientation vector. The waveform was specified a priori for a given transformation in terms of the following sinusoidal function [T is the period of the flagellar waveform, η is the wavelength (which can vary with respect to ξ1), and α is the chirality parameter. These parameters were selected such that they coincided with experimental observations.To accurately describe the flagellar waveform, we introduce an orthonormal body frame, function :(12)ξ2=Aη [η = 1 for Mode 1, and η = 0.9613 − 0.038 tan−1(5ξ1 − 4) for Mode 2. The amplitudes of the two waves were adjusted to match the swimming speed in a Newtonian fluid. If the chirality parameter, α, is also set to α = 0.25 [An experimental study of the waveform of the human sperm flagellum was reported in ,19. In lη : η = 1 fα = 0.25 , then thspX is a point on the head of the sperm, X is a point on the sphere with radius c1, c2, and c3 are non-dimensional shape parameters. The parameters were set to −2, c1 = 3.0, c2 = 2.0, and c3 = 4.0 to ensure that the morphology accurately reflected a human sperm cell.Both human and bull sperm are similar to asymmetric ellipsoids . We mimisx on the cell can be decomposed as:V is the translational velocity, Ω is the angular velocity, xg is the center-of-mass of the head. The velocity of the flagellum wave is vfla , a function of the point of interest and time. When xs is located on the cell head, then vfla is equal to zero. When xs is located on the flagellum, then vfla is determined by the time derivative of Equation (12).To express the locomotion of the sperm cell, we assumed that the cell moves rigidly. One motion of the flagellum is defined by Equation (12). The velocity at a point V, Ω and the tractions q and f. The head and flagellum were discretized into 1280 triangular meshes and 200 curved segments by spline interpolation. The surface integral of Equation (11) was solved using Gaussian numerical integration, while the finite time difference scheme was applied to the time derivative. We assumed the following force-free and torque-free conditions so that we could express the free-swimming sperm cell as:V and Ω were determined, the point of interest was updated using the second-order Runge–Kutta method. For more detail about the numerical method, please refer to our previous study [We solved the resistance problem defined in Equations (11) and (14) with respect to the unknowns us study .λ. In this study, the Deborah number is defined as De = ωλ, where ω is the angular frequency of the flagellar beat. In the small-Deborah number regime, De << 1, the mechanical properties of a Maxwell fluid asymptotically approach those of a Newtonian fluid. Due to the numerical instability, the maximum Deborah number is limited to be smaller than unity in this study. Although maximum De is limited, a weak viscoelastic liquid can be easily found in vitro situations [De ≈ 0.2. We thus decided to vary De in the range 0 ≤ De ≤ 1.We then introduced an important parameter, the Deborah number, which represents the elasticity and viscosity ratio of the viscoelastic fluid, and is characterized by the relaxation time tuations ,12. For μ to be unity without loss of generality. Cell profiles from one period, with different flagellar beats, are shown in x,y)-plane are shown for 20 beats in y-direction were opposite in the two modes. This difference was caused by the initial condition. To facilitate quantitative discussion of the swimming speed, we define two types of average swimming speed. The swimming speed n represents the number of periods T. The latter swimming speed Firstly, we investigated a sperm cell swimming through a Newtonian fluid. In the Stokes flow regime, the viscosity of the fluid simply functions as a multiplier for the force and traction. We can then take The swimming speeds λ, we limit our discussion to the physical values observed after the first period T, t ≥ T, which was sufficiently large for the initial conditions to decay.Next, we considered a sperm cell swimming through a linear Maxwell liquid. Since the impact of the initial conditions decays over the timescale of the relaxation time t = T with De = 0.0 and De = 1.0 are shown in De = 0.0 , as shown in μfL2U/P, where μ is the viscosity, f is the beat frequency, and L is the flagellar length. The results are shown in De, and the value became constant. When the efficiency was fixed, the tendency of the swimming speed to decay with De was less dependent on the wave pattern. Thus, the swimming speed varied in the same way in both wave modes.The time-averaged powers for the different wave modes are shown in De regime (De < 1.0). We found that, for the given waveform, the efficiency of the motion remained constant as the Deborah number varied. The fixed efficiency diminished the effect of the wave pattern on the decrease in swimming speed with De. These findings could be relevant to one-way fluid–structure interaction and may be helpful to researchers designing micro-swimmers in viscoelastic fluids with prescribed velocity conditions. For further study, to understand the physiology of sperm swimming, we must consider full fluid–structure interactions by developing a mechanical model of the inner structure of the flagellum.In this study, we numerically investigated a sperm cell swimming in a linear Maxwell fluid in the small-


Mini-fluid challenge is a well tested and effective tool to predict fluid responsiveness under various clinical conditions. However, mini-fluid challenge has never been tested in patients with end-stage liver disease. This study investigated whether infusion of 150 ml albumin 5% can predict fluid responsiveness in cirrhotic patients following liver transplant.Fifty patients receiving living donor liver transplant were included in the analysis. Mini-fluid challenge composed of 150 ml of albumin 5% administered over 1 min in three consecutive 50-ml fluid boluses. An additional 350 ml was then infused at a constant rate over 15 min . Stroke volume (SV) was measured as the product of the subaortic velocity time integral (VTI) and left ventricular outflow tract (LVOT) area. Fluid responsiveness was defined as an increase in SV by ≥15% after the infusion.P = 0.005). In subgroup analysis, the SV increased significantly after mini fluid challenge in the Child A group (P = 0.017) but not Child B or C groups . The AUROC for mini-fluid challenge in the Child A group was 0.86 , while mini-fluid challenge failed to discriminate between responders and non-responders in Child B and C groups.Fifty patients were enrolled in the study. Fourteen patients were classified with Child A, 15 patients with Child B, and 21 patients with Child C cirrhosis. Thirty four patients were fluid responders and 16 patients were fluid non-responders. After 150 ml of albumin 5%, the SV increased significantly in our cohort. The area under receiver operating curve (AUROC) was 0.7 . Initial registration date was 10/01/2018. Hemodynamic derangements are frequently observed during and after liver transplantation, mainly due to major blood loss, decreased venous return, and (or) reperfusion injury-induced vasodilatation. Fluid therapy is the cornerstone of hemodynamic management for unstable patients. The main goals of fluid therapy are to increase cardiac output (CO) and improve tissue perfusion.The concept of fluid responsiveness has been suggested as a guide for fluid administration in critically ill patients to avoid over- and under-fluid resuscitation. Fluid responsiveness is defined as the ability of the left ventricle to increase stroke volume (SV) after fluid administration , 2. SeveSeveral studies have investigated the value of mini-fluid challenge as a predictor of subsequent fluid infusion under different clinical conditions , 5. HoweThe primary objective of the present study was to investigate the validity of mini-fluid challenge as a predictor of fluid responsiveness in patients with ESLD after liver transplantation. The seconadry objective was to examine the consistency of this validity among different Child classification. Our hypothesis was that mini-fluid challenge would not be a valid tool to predict fluid responsiveness in cirrhotic patients after liver transplant.trial.gov (NCT03396159) and conducted from January 2018 to May 2018. Patients < 18 years of age, poor echocardiographic window, patient with CVP > 12 or lung congestion or those with acute fulminant liver failure were excluded from the study.This prospective observational study was designed to enroll 50 consecutive living donor liver transplant (LDLT) patients. The indications for LDLT in our center include; patients with decompensated liver cirrhosis, liver cirrhosis with MELD score more than 15, and patients with hepatocellular carcinoma within transplant criteria. The study protocol was approved by the Research Ethics Committee of Cairo University Hospital and informed consent was obtained from all patients. The study is registered at clinical Before ICU admission, a 20G radial artery catheter was inserted to measure arterial pressure and a triple lumen central venous catheter was inserted into the right jugular vein to measure central venous pressure (CVP). We typically used a fast track protocol, and all patients were extubated at the end of the operation inside the operating room.Upon admission to the intensive care unit (ICU), patients were maintained in a supine position and pressure transducers were referenced to the level of the tricuspid valve and zeroed to atmospheric pressure after calibration.All measurements were performed in the supine position within 1 h after arrival in the ICU. Hemodynamic measurements were performed at baseline. The fluid challenge was administered intravenously via a specific venous line. Mini-fluid challenge consisted of 150 ml albumin 5% delivered over 1 min as three consecutive 50-ml fluid boluses with no time delay between them. The remaining 350 ml was infused at a constant rate using preset electrical infusion pump over 15 min . Three sets of SV measurements were obtained: The first set was obtained before the mini-fluid challenge, the second set 1 min after the mini-fluid challenge, and the third set immediately after the infusion of the remaining 350 ml  given over 15 min. Fluid responsiveness was defined as an increase in SV by 15% after the infusion of 500 ml albumin 5%, thus separating the studied population into responders and non-responders. This cut of value was chosen as described previously [Echocardiographic assessment was performed by an accredited physician (level 3) using a GE Vivid E9 echocardiographer. The assessor was blinded to Child-Pugh class of the patients. Stroke volume was measured as the product of the subaortic velocity time integral (VTI) and left ventricular outflow tract (LVOT) diameter. The VTI was obtained by placing the pulse wave Doppler sampling cursor in the middle of the LVOT immediately proximal to the aortic valve in the apical five-chamber view. For each step of the study, VTI was measured in triplicate and averaged for the determination of the VTI value. The LVOT diameter was measured for each patient as the distance between the inflection points at the base of the aortic valve cusps from the left parasternal long-axis view during systole. Finally, SV was calculated as VTI × LVOT area.Primary endpoint in this study was the sensitivity and specificity of minifluid challenge to assess fluid responsiveness in cirrhotic patients.Sample size was calculated to detect an area under the receiver operating curve (AUROC) of 0.75 with null hypothesis AUROC = 0.5. Considering that the ratio of responders admitted to our unit is about half that of non-responders, a minimum of 42 patients including at least 14 responders are needed for a study power of 80% and an alpha error of 0.05.2 test. Paired variables within each group  were compared using the Wilcoxon matched-pairs test. To compare the performance of mini-fluid challenge for assessing fluid responsiveness among subgroups (Child cirrhosis classes), receiver operating characteristic (ROC) curves were constructed and the area under the curve (AUC) calculated. MedCalc version 12.1.4.0  generated values with the highest sensitivity and specificity (Youden index). All statistical analyses were performed using SPSS for Windows version 15.0 .Data are expressed as mean (with standard deviation) unless specified otherwise. Continuous variables were compared by one-way ANOVA and post hoc Tukey tests, while categorical variables were compared by χP = 0.005). and the optimum cut-off value for predicting fluid responsiveness was ≥10%. This cut-off value had 56% sensitivity and 87% specificity for distinghishing responders from non-responders. In subgroup analysis, the SV increased significantly in the Child A group (P = 0.017) but not Child B or C groups  after mini fluid challenge. All other hemodynamic variables remained unchanged during and following mini-fluid challenge and after completion of 500 cc albumin 5% (Tables P = 0.0004) and the optimum cut-off value for predicting fluid responsiveness was ≥10%. This cut-off value had 70% sensitivity and 100% specificity for distinghishing responders from non-responders. In contrast to the Child A group, mini-fluid challenge failed to discriminate between responders and non-responders in the Child B and C groups  score was significantly lower in the Child A group compared to both Child B and C groups  is sufficient to assess fluid responsiveness in patients with Child A cirrhosis but not Child B or C cirrhosis.We found that a SV change > 10% during mini-fluid challenge following liver transplant asess fluid responsiveness in Child A cirrhosis patients with 70% sensitivity and 100% specificity. To the best of our knowledge, this is the first study to investigate mini-fluid challenge testing in patients with ESLD. Patients with ESLD not only have an abnormally high blood volume, but also an abnormal blood volume distribution. However, not all patients with ESLD exhibit the same response to changes in blood volume. Healthy individuals and patients with Child A cirrhosis differ in their response to blood volume expansion compared to patients with Child B and C cirrhosis. Volume expansion resulted in significantly increased central blood volume in patients with Child A cirrhosis compared to patients with Child B or C cirrhosis,  which maIn the early stages of our liver transplant program, we typically extubated the patient 6–8 h after admission to the ICU . However7 More recently, Aya et al. found that 4 ml/kg was the minimum volume required to evoke a significant hemodynamic effect [There is currently great interest in using fluid responsiveness as determined by mini-fluid challenge to guide transfusion, particularly to avoid volume overloading. While several studies have tested the concept of mini-fluid challenge, these investigations used different volumes and fluid types , 11, 12.c effect . Smorenbc effect . In our The concept of using predefined criteria for increase of CO after fluid challenge to differentiate between responder and non-responder depends on the starling mechanism. However, it is worth mentioning that CO changes during fluid bolus is affected not only by preload but also by afterload. Rapid fluid infusion decrease systemic vascular resistance by hemodilution. One study found that infusion of 1 l of colloid caused 20% increase in blood volume, 20% decrease in hemoglobin, and 40% increase in CO . The incIn our study, we defined fluid responsiveness as an increase in SV by 15% after infusion of 500 ml albumin 5%. Despite that the concept of fluid responsiveness has been emerged 20 years ago, there are still considerable variabilities in the definition, implementation, and assessment of fluid challenge. Recent systematic review found that 60% of the studies defined fluid responsiveness as an increase of ≥15% of CI or CO immediately after fluid challenge [Albumin 5% infusion was chosen to test fluid responsiveness instead of hydroxyethyl starch because we have previously shown that this solution is as effective for volume expansion . MoreoveOur study had several limitations. First, all our patients had excellent cardiac function during the early. Postoperative period, so we cannot extrapolate our findings to patients with poor cardiac function. Second, assessment of minifluid using echocardiography is challenging because the minifluid challenge induces small changes in cardiac output which may miss some true responders, however, we used single operator to limit the effect of interobserver variability.A mini-fluid challenge of 150 ml albumin 5% can predict fluid responsiveness in liver transplant patients with fair sensitivity and specifiicty. Subgroup analyis revealed that minifluid challenge can predict fluid responsiveness in patients with Child A cirrhosis but not in patients with Child B or C cirrhosis.


Volume expansion is aimed at increasing cardiac output (CO), but this variable is not always directly measured. We assessed the ability of changes in arterial pressure, pulse pressure variation (PPV) and heart rate (HR) or of a combination of them to detect a positive response of cardiac output (CO) to fluid administration.We retrospectively included 491 patients with circulatory failure. Before and after a 500-mL normal saline infusion, we measured CO (PiCCO device), HR, systolic (SAP), diastolic (DAP), mean (MAP) and pulse (PP) arterial pressure, PPV, shock index (HR/SAP) and the PP/HR ratio.r < 0.4. The best detection was provided by increases in PP, but it was rough . Neither the decrease in shock index nor the changes in other indices combining changes in HR, shock index, PPV and PP provided a better detection of a positive fluid response than changes in PP.The fluid-induced changes in HR were not correlated with the fluid-induced changes in CO. The area under the receiver operating characteristic curve (AUROC) for changes in HR as detectors of a positive fluid response (CO increase ≥ 15%) was not different from 0.5. The fluid-induced changes in SAP, MAP, PP, PPV, shock index (HR/SAP) and the PP/HR ratio were correlated with the fluid-induced changes in CO, but with A positive response to fluid was roughly detected by changes in PP and not detected by changes in HR. Changes in combined indices including the shock index and the PP/HR ratio did not provide a better diagnostic accuracy. Volume expansion is primarily aimed at increasing cardiac output (CO), with the expectation that oxygen delivery and tissue perfusion will improve consequently . NeverthCO is not directly monitored in every patient . Its resAlthough changes in each of these variables may not accurately reflect the changes in CO, their combination may do so. The shock index (heart rate divided by SAP), or the ratio of PP over heart rate, which has demonstrated a strong relationship with stroke volume , have beIs it reasonable to use the changes in indices combining arterial pressure, heart rate or PPV in order to assess the effects of a fluid bolus on CO when the latter is not measured? This was the question we would like to answer in the present study. Taking the advantage of a large database of volume expansions performed in critically ill patients, we investigated whether combining the changes in heart rate, arterial pressure, PPV, shock index and the PP/heart rate ratio is useful for this purpose.This study was conducted in the medical intensive care unit of a university hospital. All patients (or next of kin) were informed about the study and agreed to participate. We retrospectively examined the data of 491 non-consecutive patients with acute circulatory failure, who had been included in previous studies –19. AcutAll patients were monitored by a transpulmonary thermodilution device . All patients had an internal jugular vein catheter and a thermistor-tipped arterial catheter inserted through the femoral artery.CO was measured by transpulmonary thermodilution . The aveBefore fluid infusion, transpulmonary thermodilution was performed. Heart rate, CO (obtained from thermodilution), SAP, diastolic arterial pressure (DAP), MAP, PP and PPV (PiCCO device) were recorded.Then, a 500-mL bolus of normal saline was infused over 10 to 30 min . Immediat test or a Wilcoxon test. Comparisons between fluid responders vs. fluid non-responders were assessed through a two-sample Student’s t test or a Mann–Whitney U test. Correlations were assessed by the Pearson coefficient and correlation coefficients were compared using the Fisher transformation  or mean . Comparisons between before vs. after fluid administration were assessed through a paired Student’s ormation .Receiver operating characteristic (ROC) curves  were constructed for testing the ability of the relative changes in heart rate, SAP, MAP, DAP, PP, PPV, the shock index and the PP/heart rate ratio to detect a positive response to fluid. For PPV, absolutes values were taken into account, while for heart rate, SAP, MAP, DAP, PP, the shock index and the PP/heart rate ratio, both absolute values and percent changes were considered. The best diagnostic thresholds were defined as those providing the highest Youden index. The areas under the ROC curves (AUROC) were compared using a Hanley–McNeil test.For testing the diagnostic ability of combined indices, we performed two different analyses. First, we built a combined index, which was considered as positive if the value taken by changes in heart rate, in PP and in PPV were all above their respective best diagnostic threshold found by the previous ROC curve analysis, and negative if one or more of the variables was below its best diagnostic threshold. This combined index was submitted to a ROC curve analysis. Second, we performed a stepwise logistic regression, with a positive response to fluid as the dependent variable and the percent changes in heart rate, PP and PPV as independent variables.p value ≤ 0.05 was considered statistically significant. The statistical analysis was performed by using MedCalc8.1.0.0 .The primary analysis was performed after excluding the far outliers of the database. A far-out value was defined as a value that was smaller than the lower quartile minus 3 times the interquartile range, or larger than the upper quartile plus 3 times the interquartile range . The anaThe characteristics at baseline of the 491 included patients are summarised in Table In the whole population, volume expansion increased CO by 22 ± 23%. It increased by more than 15% in 275 (56%) “fluid-responders”. In fluid responders, CO increased by 36 ± 21% and heart rate decreased by 2 ± 9%. In these patients, SAP, MAP, PP and DAP increased by 19 ± 22%, 16 ± 21%, 27 ± 35% and 14 ± 38%, respectively (Table n = 101)  compared to the other ones. The AUROC for changes in PP to detect a positive fluid response was similar in patients in whom fluid was infused over 10 min and those in whom it was infused over 30 min . It was also similar in patients older and younger than 60 years old .The coefficient of correlation between the fluid-induced changes in arterial pressure values and changes in CO after exclusion of outliers is provided in Table Considering all the 358 patients in whom PPV had been measured, after exclusion of outliers, the correlation between fluid-induced changes in PPV  and changes in CO (in %) was significant but lower than for the fluid-induced changes in PP (Table n = 37) are shown in Table n = 37) is reported in Additional file p = 0.40).The fluid-induced changes in PPV  were able to detect a positive fluid response Table  and 2. TThe correlation between fluid-induced changes in heart rate (in %) and changes in CO (in %) after exclusion of outliers was not significant Table . The flun = 99), the patients with sinus rhythm (n = 390) or the patients without sedation (n = 169) . It was also similar in patients older and younger than 60 years old , and after excluding the 35 patients with previous administration of beta-blockers (AUROC: 0.525 ± 0.03). The diagnostic ability was also similar in patients with tachycardia before fluid administration (n = 197) (AUROC: 0.547 ± 0.41). The AUROC for changes in heart rate to detect a positive fluid response was similar in patients in whom fluid was infused over 10 min and those in whom it was infused over 30 min .The diagnostic ability of the fluid-induced decrease in heart rate was not different when taking into account only the patients with hypovolemic shock (The correlation between the fluid-induced changes in shock index (in %) and the fluid-induced changes in CO (in %) after exclusion of outliers was significant, but the correlation coefficient was significantly lower than for the fluid-induced changes in PP Table .p = 0.17).Considering the whole population, the fluid-induced changes in shock index (in %) were able to detect a positive fluid response Table . The besThe correlation between the fluid-induced changes in the PP/heart rate ratio (in %) and the fluid-induced changes in CO (in %) after exclusion of outliers was significant, but the correlation coefficient was the same as for the fluid-induced changes in PP Table .p = 0.37).Considering the whole population, the fluid-induced changes in the PP/heart rate ratio (in  %) were able to detect a positive fluid response Table . The besUsing logistic regression, only the changes in PP were independently associated with a positive response to fluid infusion (odds ratio: 1.038 [1.025–1.052]). The analysis performed by considering each variable as either positive or negative by taking the threshold found at univariate analysis, the only combination that provided a significant AUROC was a decrease in heart rate > 2% coupled with an increase in PP ≥ 10%. It was inferior to the one provided by the changes in PP , on the arterial compliance (relationship between stroke volume and PP) and on the pulse wave amplification from the aorta to the periphery. The changes in heart rate were small in our study on average, suggesting that this phenomenon plays a minor role. The arterial blood pressure measurements were performed at the level of the femoral artery, which minimises the importance of the pulse wave amplification phenomenon. It is thus likely that the arterial compliance must explain the discrepancy we observed. As a matter of fact, fluid infusion may change the arterial compliance and this phenomenon might be independent from the arterial properties at baseline . For a sThese results corroborate previous observations during fluid infusion , 5 or paThe changes in MAP tended to have a lower accuracy than those in PP to detect the fluid effects. The changes in MAP are dissociated from the changes in CO due to the sympathetic modulation, which tends to maintain MAP constant while CO varies . SurprisOf note, we observed that the rate of cases in which PPV was valid was 10%. It is higher than the 1%  or 2% 3 prevalenFinally, taking advantage of the large number of cases, we could explore indices combining the changes in several variables. Neither the shock index nor the PP/heart rate ratio was better than PP for detecting the fluid effects on CO. It was either not better for other combinations of changes in haemodynamic variables and, using logistic regression, no model could be found for detecting a positive response to fluid from heart rate, PP and PPV. Some of these combined indices did even not provide any significant relationship with changes in CO.The implications of the present study for the practice are important. It shows that monitoring the effects of a fluid challenge on CO through blood pressure, as reported in 67% of cases in the Fenice survey , is not This study has limitations. First, it was retrospective. Nevertheless, the population was made of patients included into prospective trials. Second, using data from different studies inevitably introduces the problem of heterogeneity. In particular, the time over which fluid administration was performed was different between patients, while the efficacy of a fluid bolus is only transient . NeverthThe effects of a fluid challenge on CO cannot at all be detected by the changes in heart rate. The changes in PP and in PPV only provide a rough estimation. A reliable assessment of the effects of volume expansion on CO requires a direct measurement of it. These data argue for monitoring CO in patients who require a precise haemodynamic assessment.Additional file 1. Tables S1–S12 and Figure S1.


This aroreana.” . Paulownia Siebold & Zucc. (1835) officially recognized in China and Korea are Paulownia catalpifolia T. Gong ex D.Y. Hong, Paulownia elongata S.Y. Hu, Paulownia fargesii Franch., Paulownia fortunei (Seem.) Hemsl., Paulownia kawakamii T. Itô, Paulownia taiwaniana T.W. Hu & H.J. Chang and Paulownia tomentosa (Thunb.) Steud. [Paulownia coreana does not exist and therefore cannot be medicinal nor the source of the phytochemical described in [et al. is incomplete as regards to carbon numbering and the class of sesquiterpene to which this molecule belongs is not specified. Prompt revision of the name assigned to this plant  is required to ensure the accuracy of the scientific record.I have been studying the pharmacotoxicological properties of the medicinal plants of Asia and the Pacific for the last 15 years ,4,5,6,7 & Zucc. 135 offici


Circa 1983, transfection of mouse NIH3T3 cells with genomic DNA isolated from human tumours had already yielded the first three human cancer genes, all members of the RAS family. It was Friday evening and nobody else was in the lab. A fresh tumour biopsy obtained from a surgically removed colorectal carcinoma arrived at the lab of Stuart Aaronson. Since there was nobody to try to grow cells from this specimen, I decided to freeze it. Yet, before doing so, I could not resist the temptation to isolate DNA to ask whether fresh tumour samples might yield different cancer genes than cell lines or frozen tumour samples. Hence, I took a small piece, isolated its DNA and used it to transfect NIH3T3 cells shortly thereafter. It worked! But it was pure luck. Later, it became clear that “fresh” tumour samples contained the same oncogenes as those that were previously frozen.NTRK1, NTRK2 and NTRK3, respectively.This colorectal carcinoma contained an inversion within chromosome 1 that fused the amino-terminal domain of tropomyosin with the catalytic domain of a novel tyrosine protein kinase receptor. The resulting fusion oncogene was named TRK for tropomyosin receptor kinase, the first non-RAS oncogene isolated from a human tumour. Unfortunately, it never happened again, at least in our hands. Thus, we considered the TRK oncogene an oddity, a curiosity whose main contribution to science would be to serve as a probe to identify, a few years later, the signalling receptors for the NGF family of neurotrophins. These receptors, originally designated as TRKA, TRKB and TRKC, are now known as NTRK oncogenic fusions in human tumours, had limited impact in the cancer field. However, the generation of two potent inhibitors of TRK fusions, larotrectinib and entrectinib, has changed not only the clinical relevance of these oncogenes, but the way in which clinical oncologists must approach their patients.However, the power of the new generation of sequencing techniques revealed that the TRK oncogene was not such an oddity after all. Although infrequent, TRK oncogenes formed by gene fusion events of each of the family members that result in their constitutive activation were identified in other common tumour types such as lung, breast and pancreatic carcinomas. In addition, they also occur with high frequency in some rare adult and paediatric tumours, such as secretory breast sarcomas and certain forms of thyroid cancer. These observations, despite expanding interest in the role of ALK) fusion for which there are selective inhibitors.Precision medicine has relied on the identification of selective mutations in tumours defined according to classical clinical parameters of tissue and cell type of origin followed by the identification of selective driver mutations. Lung cancer could be considered a classical paradigm of how clinicians carry out tumour stratification today. Once the tumour is classified according to histopathological parameters as a non-small-cell lung carcinoma, treatment selection is guided by the presence of known driver oncogenes such as mutant epidermal growth factor receptor or anaplastic lymphoma kinase (NTRK fusions: not a trivial task considering their low incidence in common malignancies. Yet, this diagnostic exercise can save lives. Clinical trials have revealed that more than two-thirds of patients carrying NTRK fusions treated with these inhibitors achieve high levels of tumour regression, regardless of tumour origin. In short, patients with certain tumour types, such as non-small-cell lung carcinomas or pancreatic adenocarcinomas, have a much higher chance of survival if they harbour NTRK gene fusions.Availability of the TRK inhibitors larotrectinibNTRK fusions using sequencing platforms. Identification of EGFR mutations or ALK fusions in lung adenocarcinomas only benefits 12% or 4% of patients, respectively. The incidence of NTRK fusions is a log lower. However, the therapeutic benefits provided by current TRK inhibitors certainly outweigh the increased expense of identifying NTRK fusions derived from their lower incidence. Development of potent and selective inhibitors against other oncogenic alterations is likely to lead to more instances of the use of tumour-agnostic strategies. Finally, for those of us who are still struggling to identify suitable therapies for RAS mutant tumours, the anecdote of isolation of the TRK oncogene provides comfort by reminding us that basic scientific discoveries will, sooner or later, serve to benefit patients with cancer. These observations underscore the need to carry out routine molecular identification of This paper was published as part of a supplement financially supported by Bayer AG and Loxo Oncology, Inc., a wholly owned subsidiary of Eli Lilly and Company.


Annals of Oncology, Spiteri et al. [The evolution of divergent subpopulations of cancer cells within the same tumour has been proposed to underlie the development of treatment resistance and the recurrence of malignancy across multiple tumour types . In thisi et al.  utilise GBM is the most common primary brain malignancy in adults characterised by a devastating prognosis and a lack of effective therapeutic options. Since the 1970s, treatment has consisted of maximal resection followed by focal external beam radiotherapy , and morFollowing initial radical therapy, tumour recurrence inevitably occurs and is the predominant source of mortality in these patients . ClinicaThe genomic architecture of untreated GBM was revealed through genomic sequencing studies such as The Cancer Genome Atlas (TCGA) , 10 idenInsights into the temporal evolution of GBM have been revealed by profiling matched therapy naive and recurrent tumours, revealing significant heterogeneity in both somatic mutations and copy number alterations at relapse . Thus, sIDH1 wildtype GBM and 1 patient with IDH1 mutant anaplastic astrocytoma. They performed multi-region whole-exome sequencing from the primary tumour mass, SVZ and infiltrative margin collected using fluorescent guided resection and, in two cases, matched tissue from a second surgery at local relapse were available for comparison  and PEACE  which afford the highest resolution sampling to better understand the evolutionary history underlying this devastating disease and inform future therapeutic targets both molecular and immunogenic.


Results: Univariate analysis detected various risk factors for fDGF. Dialysis dependent recipients were more likely to develop fDGF compared to pre-emptively transplanted patients (p < 0.001). Recipients developing fDGF received less intraoperative fluid (36 (25.9–50.0) mL/kg BW vs. 47 (37.3–55.6) mL/kg BW (p = 0.007)). The GDFT protocol resulted in a reduction of intraoperative fluid administration on average by 850 mL in total volume and 21% in mL/kg BW compared to our old protocol (p < 0.001). In the unadjusted analysis, a higher intraoperative fluid volume in mL/kg BW was associated with a lower risk for the developing fDGF ). After adjustment for the confounders, prior dialysis and the use of intraoperative noradrenaline, the relationship of fDGF with fluid volume was still apparent ). Conclusion: Implementation of a GDFT protocol led to reduced intraoperative fluid administration in the LDKT recipients. This intraoperative fluid restriction was associated with the development of fDGF.Background: In 2016 we observed a marked increase in functional delayed graft function (fDGF) in our living donor kidney transplantation (LDKT) recipients from 8.5% in 2014 and 8.8% in 2015 to 23.0% in 2016. This increase coincided with the introduction of a goal-directed fluid therapy (GDFT) protocol in our kidney transplant recipients. Hereupon, we changed our intraoperative fluid regimen to a fixed amount of 50 mL/kg body weight (BW) and questioned whether the intraoperative fluid regimen was related to this increase in fDGF. Methods: a retrospective cohort analysis of all donors and recipients in our LDKT program between January 2014–February 2017 ( During the procedure of organ donation and transplantation a number of potentially harmful processes will inevitably occur, affecting the viability of the kidney graft. Both donor and recipient are subjected to anesthesia and surgery, which will produce a sequence of systemic and local changes, including a significant proinflammatory and procoagulatory response . The donDGF, a form of acute kidney injury post-transplantation, is an uncommon complication after living donor kidney transplantation (LDKT), most likely due to very short ischemia times and healthy living donors. Incidences reported vary between 1%–8% ,4. In trRegarding the intraoperative period, several studies suggest that an adequate/supranormal fluid state is associated with a reduced risk of DGF ,12,13,14p = 0.039 and p = 0.021, respectively). Since the incidence of fDGF in this population has been stable over the past two decades and no protocol changes were implemented with the exception of the GDFT protocol, we questioned whether this increase in fDGF was due to the altered fluid regimen. To our surprise, a retrospective analysis revealed that the implementation of GDFT protocol had resulted in a reduced intraoperative fluid administration which seemed associated with the increase in fDGF. Based on these results, we promptly changed the intraoperative fluid protocol in September 2016 to a fixed amount of 50 mL/kg BW with a lower limit of 2500 mL and upper limit of 6000 mL (50 kg–120 kg), unless patients comorbidity determined otherwise. After six months the incidence of fDGF was back to baseline at 8.2%. Recently, goal directed fluid therapy (GDFT) has been shown to improve patient outcomes after major  surgery ,19,20. DSince we were interested in whether the amount of fluid administered intraoperatively was indeed an independent factor predicting fDGF in this LDKT population, we performed a retrospective cohort analysis of all donors and recipients in our living donor program between January 2014–February 2017.This retrospective cohort analysis comprised all consecutive donor and recipient pairs of the LDKT program of the University Medical Centre of Groningen (UMCG) between January 2014 and February 2017. The Institutional Review Board approved the study (METc 201600968), which was conducted in adherence to the Declaration of Helsinki. Due to the observational and retrospective character of the analysis, the requirement for informed consent was waived. Twenty-two definitions of DGF were identified in literature based on dialysis, serum creatinine levels, urine output or a combination of these 3 , Most coAnesthetic management was according to local protocol. Propofol was used for induction of anesthesia and either propofol or sevoflurane were used for maintenance of anesthesia. Sufentanil or remifentanil were used to control nociception and rocuronium or cis-atracurium for muscle relaxation. Until the implementation of the GDFT protocol, donors and recipients were given 4–5 L of balanced crystalloids throughout the procedure unless their comorbidity determined otherwise. During 2015, a GDFT protocol was gradually implemented in the recipients (not in the donors). For a detailed description of this protocol, see below. From September 2016 fluid protocol in recipients was changed to a fixed amount of 50 mL/kg BW intraoperatively. Timeline of fluid management in recipients is given in GDFT was performed with the use of the FloTrac® in combination with the EV1000® monitor . The system was used according to manufacturer’s instructions. A standard institutional GDFT protocol was used with adjustment of the goal. Instead of a stroke volume variation (SVV) < 12%, commonly used in abdominal surgery, we aimed for a SVV < 10% throughout the procedure. When the SVV was >10% additional fluid was given until SVV was <10%. If SVV < 10%, fluid administration was left to the discretion of the attending anesthesiologist, however, when cardiac index (CI) was below age-adjusted normal values, a noradrenaline infusion was started. If measurement of the SVV was not possible  a protocol based on stroke volume (SV) was used. In this case, if a fluid bolus of 250 mL resulted in an increase of the SV of 10%, additional fluid was given, if not, the trend of the SV was monitored and fluid administration was left to the discretion of the attending anesthesiologist. When SV decreased >10%, additional fluid was given. The FloTrac® was used with the EV1000 monitor, which does not communicate with our digital PDMS. Therefore SV, SVV, and CI values could not be retrieved for this analysis.Demographic and postoperative data were obtained from digital patient medical records. The following variables were taken into account: age, gender, BMI, smoking, hypertension, use of antihypertensive drugs, measured glomerular filtration rate (mGFR) with use of iodine 125-iothalamate in the donor, blood pressure , difference in blood pressure between donor and recipient measured by systolic/diastolic/mean of the recipient minus systolic/diastolic/mean of the donor, underlying kidney disease, number of HLA mismatches, history of dialysis, related or unrelated donor transplantation. For all recipients, the age-adjusted Charlson comorbidity index (CCI)  and lengp-values are two-sided. A p-value of 0.05 or less was considered significant.For the statistical analysis SPSS version 23  and GraphPad Prism version 7.02  were used. We performed univariate analyses to identify factors associated with fDGF. Categorical data were analyzed by chi-square or Fisher’s exact tests. Continuous data were analyzed with an unpaired t-test in the case of normally distributed values. If variables were not normally distributed Mann–Whitney test was applied. Multivariate analysis was performed by means of binary logistic regression. We adjusted the amount of fluid administered intraoperatively in recipients for potentially relevant confounders with high significance in the univariate analysis. Additionally, we were interested in the impact of implementation of our GDFT protocol on the incidence of fDGF and on the amount of fluid administered intraoperatively. We therefore analyzed these data between the different time periods 1–3 (described above) with the use of Fisher’s exact test and Kruskal–Wallis test. Post-hoc analysis with Mann–Whitney was used. Values are given as number (%), mean ± standard deviation (SD) or median with interquartile range (IQR). All reported p < 0.001). The composition of the group of dialysis dependent patients did not differ between nofDGF and fDGF recipients. In the nofDGF group 76 (72%) patients were on hemodialysis at the time of transplantation and 29 (28%) on peritoneal dialysis. In the fDGF group, this was the case for 19 (76%) and six (24%), respectively. All patients on hemodialysis were dialyzed the day before transplantation to 1 kg above dry weight.Between January 2014 and February 2017, 275 living donor kidney transplant procedures were performed in our center. Of the 275 recipients, 31 patients experienced fDGF and 244 recipients did not (nofDGF). Donor and recipients characteristics of fDGF and nofDGF kidneys are listed in p = 0.050) and mL/kg BW (45 mL/kg BW (10.3) vs. 49 mL/kg BW (11.4), p = 0.053). Intraoperative data of donors of fDGF and nofDGF kidneys showed no differences with exception of the total amount of fluid, in which donors of fDGF kidneys received less fluid intraoperatively, which was the case for total volume (3545 mL (778.2) vs. 3845 mL (799.1), p = 0.023) and mL kg-1BW (36 mL/kg BW (25.9–50.0) vs. 47 mL/kg BW (37.3–55.6), p = 0.007). Predominantly RL was given, but in case of hyponatremia RL was partially replaced by saline. This was the case in 48 (20%) of the recipients without fDGF and in 8 (26%) of the patients with fDGF (p = 0.477). Median volume replaced by saline was 1000 mL (500–2000) in the nofDGF group and 800 mL (500–1075) in the fDGF group (p = 0.865). Blood loss was comparable between groups and transfusion of red blood cells was applied in 10 (4.1%) of the patients in the noFDGF group and two (6.4%) of the fDGF group. Patients showed no difference in hypotensive periods, but recipients experiencing fDGF were treated more frequently with noradrenaline continuous infusion (p = 0.034), which was only the case for low dose infusion with a maximum of 0.1 mg/h. For noradrenaline administered at higher dosage (>0.1 mg/h), there was no difference between the two groups. fDGF was associated with a lower urine output during the first two hours after transplantation (p = 0.005 for the first hour and p = 0.002 for the second hour). Ten patients in the fDGF group were dialyzed after transplantation versus zero patients in the nofDGF group (p < 0.001). Eight of these kidneys gained function after a mean of 10.3 (3.1) days. Two kidneys suffered primary nonfunction due to a combination of ATN and mild antibody-mediated rejection  and non-HLA-mediated hyperacute rejection . Recipients experiencing fDGF showed a longer hospital stay (14 (10–20) vs. 9 (7–13) days p < 0.001)  vs. 3500 mL (2900–4075), < 0.001) . In the unadjusted analysis, a higher intraoperative administered fluid volume was associated with 3% lower odds for the development of fDGF per mL/kg BW , model 1). We adjusted for potentially relevant confounders with high significance in the univariate analysis, i.e., a history of dialysis and the use of intraoperative noradrenaline, after which the relationship was still apparent , model 2). Since the intraoperative amount of fluid in the donors approached significance in the univariate analysis with lower volumes given in the fDGF group, we also adjusted for amount of fluid in the donor, after which the relationship was still apparent , model 3) .n = 84, old protocol) to patients transplanted between January 2016–June 2016  and patients transplanted between September 2016–February 2017 .Additionally, we were interested in the impact of implementation of our GDFT protocol on the incidence of fDGF and on the amount of fluid administered intraoperatively. The GDFT protocol was gradually implemented during 2015 and in 2016 (up to September) all recipients were treated following this protocol . Data ofp = 0.029).Incidence of fDGF during the different periods are shown in p < 0.001, p < 0.001). Implementation of the GDFT (period 2) resulted in a decrease of intraoperative fluid administration compared to our old protocol (period 1), which was the case for total volume (2775 mL (2313–3500) vs. 3625 mL (3213–4000), p < 0.001) and mL/kg BW (38 mL/kg BW (30.3–45.3) vs. 48 mL/kg BW (40–60), p < 0.001). The implementation of the new protocol (period 3) resulted in an increase in intraoperative fluid administration to 4150 mL (3475–4575) mL and 54 mL/kg BW (47.4–60.1) compared to the old  and GDFT . Total amount of intraoperative administered fluid and mL/kg BW in recipients in the different time periods are shown in This retrospective cohort analysis study shows that intraoperative fluid restriction in recipients is associated with fDGF in living donor kidney transplantation. Additionally, we showed that the implementation of a GDFT with a goal set at SVV < 10% led to a reduction of intraoperative fluid administration, on average by 850 mL in total and 21% in mL/kg BW, compared to our old protocol of 4–5 L of RL. In our opinion, this analysis provides valuable information for other centers when changes in intraoperative fluid management during kidney transplantation are considered.Four to five liters of RL was the standard intraoperative fluid protocol in kidney transplantation in our center for over 15 years. This may seem rather liberal, but problems due to hypervolemia were rarely seen. However, following new trends on GDFT , a persoThe debate on perioperative fluid management is still ongoing. Controversy exists regarding assessment of the intravascular volume state, which goals to aim for, how to measure these goals, and what type of fluid should be used. Hypovolemia leads to a decreased oxygen supply to organs and tissues and may cause hypoxia, which can lead to organ dysfunction. Hypervolemia, on the other hand, can damage the endothelial glycocalyx resulting in a fluid shift from the intravascular compartment to the interstitial space and tissue edema . Shin anThe most important predictor of fDGF in our analysis was dialysis dependency at the time of transplantation. A history of dialysis and especially hemodialysis prior to transplantation is a known risk factor of DGF ,7,35,36.p = 0.001) due to the implementation of the GDFT. In period 3, the use of noradrenaline decreased to 50% of the patients. In the univariate analysis, the use of noradrenaline was correlated with development of fDGF, but after multivariate logistic regression this was no longer the case. However, Morita and coworkers showed that in a rat model, transplanted kidneys responded to sympaticomimetics with a reduction in renal blood flow (RBF) in contrast to the increase in RBF seen in native rat kidneys [In our GDFT protocol, noradrenaline was used when CI was below an age-adjusted value. Therefore, an increased use of noradrenaline was seen in period 2 compared to period 1  and are unable to present information or draw any conclusions regarding actual SV, SVV, CO or CI values and their relation to the observed increase of fDGF. Other limitations are those of a retrospective observational trial. There is the potential of confounding by unmeasured factors. Regarding postoperative fluid volume, the exact amount of fluid given could not be retrieved in a reliable way from our PDMS and is therefore not implemented in this analysis. Postoperative fluid management was according to a standardized protocol and comprised of 1 L NaCl 0.45%-Glucose 2.5% per 24 h, complemented with the volume of diuresis in the former hour. This means that when the kidney produces less urine the patient will be given less fluid postoperatively. Since fDGF was associated with a lower urinary output the first two hours, it is very likely that patients experiencing fDGF received less fluid postoperatively. Whether this contributed to development of fDGF or is more of a symptom remains unknown. Backpressure from congested tubules obstructed with cellular debris may contribute to a reduction in GFR ,40. A hiFinally, due to the fact that there are only 31 events there is always the possibility of overestimating the strength of associations using a multivariate analysis. A strong argument, however, is that no policy changes were implemented during the study period with the exception of the intraoperative fluid regimen. Furthermore the incidence of fDGF in our LDKT population has been stable over many years and after changing the fluid regimen back to a more liberal fixed amount of 50 mL/kg BW the incidence of fDGF instantly returned to baseline.DGF after transplantation is a clinically relevant problem. It is associated with an increase in morbidity, patient anxiety, increased risk of acute rejection, and additional diagnostic procedures and costs. In our population the median hospital stay in patients experiencing fDGF was prolonged by five days. Furthermore, this study shows that strict protocols for perioperative fluid management are needed when studies in kidney transplantation are designed. Fluid restriction can be an important risk factor for DGF, a frequently used primary end point, even in the setting of LDKT.Implementation of a goal-directed approach to fluid administration with a goal set at a SVV < 10% throughout the procedure led to reduced intraoperative fluid administration in the LDKT recipients in our center. This intraoperative fluid restriction was associated with the development of more fDGF. A thorough validation of GDFT protocols in patients with renal insufficiency is warranted before these are implemented in this population.


China (e-mail


Jennifer Rhodes (FCCC) and Wesley Rose  for constructive criticism during manuscript preparation. This work was supported by R01 grants CA-083859 and CA-100226 (K.S.C.), training grant CA009035-32 (A.K.P.) and partially by Centers of Research Excellence grant CA06927 (FCCC) from the National Institutes of Health. The research was also supported in part by an appropriation from the Commonwealth of Pennsylvania. Its contents are solely the responsibility of the authors and do not necessarily represent the official views of the National Cancer Institute.


The higher ratios are similar to seawater strontium ratios in the Neogene. 87Sr/86Sr ratios lower 0.7084 indicate exchange of Sr with the igneous host rock. The calcite veins hosted by the sedimentary rocks are showing more primitive 87Sr/86Sr ratios <0.706396. The isotopic compositions indicate seawater, modified into a hydrothermal fluid by subsequent heating, as the main fluid source. Low‐temperature alteration and the presence of a high‐temperature fluid resulted in different carbonate precipitates forming up to several cm thick veins. The geochemical data combined with age data of the sedimentary rocks suggest intraplate seamount volcanism in the area between the Galapagos hot spot and the Cocos Island as an additional heating source, after the formation of the Cocos Ridge at the Galapagos hot spot.Carbonate veins in the igneous basement and in the lithified sedimentary cover of the Cocos Ridge at International Ocean Discovery Program (IODP) Hole 344‐U1414A reveal the hydrologic system and fluid‐rock interactions. IODP Hole 344‐U1414A was drilled on the northern flank of the Cocos Ridge and is situated 1 km seaward from the Middle America Trench offshore Costa Rica. Isotopic and elemental compositions were analyzed to constrain the fluid source of the carbonate veins and to reveal the thermal history of Hole 344‐U1414A. The formation temperatures (oxygen isotope thermometer) of the carbonate veins in the lithified sedimentary rocks range from 70 to 92 °C and in the basalt from 32 to 82 °C.  Oxygen and strontium isotope ratios of carbonate veins suggest seawater and hydrothermally modified seawater as fluid sourceIsotopic and elemental compositions reveal fluid‐rock interactions in the Cocos Ridge basalt and in the lithified sedimentary rocksIntraplate seamount volcanism in the area between the Galapagos hot spot and the Cocos Island acted as an additional heating source Drilling on the subducting and overriding plate was achieved as part of the Costa Rica Seismogenesis Project (CRISP) during International Ocean Discovery Program (IODP) Expedition 344. CRISP has the main objective to clarify processes that control nucleation and seismic rupture of large earthquakes at erosional subduction zones  trapped over a wide temperature range from 40 to approximately 400 °C. These fluid inclusions reveal multiple fluid entrapment stages suggesting that fluid flow occurred over several episodes , to define the fluid source and pathways of paleofluids through the sedimentary cover and the igneous basement, and to reveal fluid‐rock interaction processes.In this study, we present analyses of the elemental and isotopic composition of calcite and aragonite veins (CCV) and of the surrounding host rocks to unravel the thermal and fluid history at IODP Hole 344‐U1414A and to clarify the temperature variations derived from fluid inclusions. Oxygen and strontium isotopic compositions of CCV provide useful constraints on fluid sources and reflect the extent of the chemical exchange between seawater and the host rocks of the upper oceanic crust , subducts beneath the Caribbean Plate Figure . The comIODP Hole U1414A was drilled during IODP Expedition 344 (CRISP 2A) and serves as a reference site to constrain the lithostratigraphy and the hydrologic system of the subducting CCR. The recovered cores of Hole U1414A comprise 375.50 m of sediment and 96.35 m of igneous basement , calcium carbonates, quartz, and pyrite. All four minerals occur in centimeter‐thick veins, in some cases with several generations of calcium carbonate. Pyrite is present in veins and in both host rocks. Veins in the basalt are more or less surrounded by a brown selvage of predominantly clay minerals resulting from basalt alteration. The veins in the basalt occur within different growth morphologies: syntaxial, antitaxial, and composite veins  relative to the Vienna‐PeeDee Belemnite (V‐PDB) standard. For each sample two to five measurements were carried out with an analytical precision of 1σ < 0.05‰ for δ13C, < 0.1‰ for δ18O. Additionally, δ13C and δ18O values of four sedimentary host rock powder samples and three CCV‐S and two CCV‐B were measured by a Finnigan DELTAplusXP mass spectrometer at the Institute of Water Resources Management, Hydrogeology and Geophysics, Joanneum Research, Graz. The overall error of reproducibility is <0.1‰ (VPDB) for both δ13C and δ18O values. Formation temperatures of calcite and aragonite are calculated assuming equilibrium with seawater (0‰ Vienna SMOW standard mean ocean water [VSMOW]), using the fraction equations of Kim and O'Neil  from the basalt were reacted with 100% phosphoric acid at 70 °C in a Kiel II automated reaction system. The evolved carbon dioxide gas was analyzed with a Finnigan Delta Plus mass spectrometer at the Institute of Earth Sciences, NAWI Graz Geocenter, University of Graz. The δd O'Neil  for calcd O'Neil  for arag3.23. Trace and selected major elements were measured by inductively coupled plasma‐mass spectrometry using a Thermo Scientific X‐Series II. Samples and standards were spiked with internal standard elements and corrected for interferences and blank and then calibrated using a suite of international rock standards  for 300 ratios. Fractionation was corrected using an exponential correction normalized to 86Sr/88Sr = 0.1194. NIST 987 was run as a reference standard and the long‐term average  on this instrument is 0.710245 ± 0.000025 (2SD).Ten CCV‐S from sedimentary Unit III and seven CCV‐B  from the basalt, the corresponding host rocks as well as the extracted carbonate phase of the siliceous and calcareous cemented sedimentary host rock, were analyzed for elemental composition and strontium isotopes in the Isotope Geochemistry Laboratories of the National Oceanography Centre Southampton, University of Southampton. Carbonate samples were dissolved in 5% acetic acid, the carbonate phases were leached from the sedimentary host rocks with 5% acetic acid, and the whole rocks were digested using HF/HNO3 to avoid dissolution of clay minerals. Sr was separated using Sr‐specific extraction chromatographic resin (Eichrom) columns. About 5 ml of 3 M HNO3 were used for element elution and 1 ml 0.1 M HNO3 for Sr collection. Strontium isotopic ratios were determined on a Nu Instruments Plasma II multicollector‐inductively coupled plasma‐mass spectrometry at the NAWI Graz Central Lab for Water, Minerals and Rocks, Graz University of Technology. NIST SRM 987 yielded 87Sr/86Sr ratios of 0.710253 ± 0.000067  and all samples were corrected relative to the value of 0.710250 for NIST SRM 987.Additionally five samples, two fibrous calcite vesicles, and three veins with fibrous calcite and blocky quartz were dissolved by dilute (2%) HNO413C of dissolved CO2 , whereby the lower values indicate low‐temperature interaction of seawater or pore fluids with the basalt , in contrast to the CCV‐B that show a much wider range of values from 18.5 to 28.2‰ SMOW, indicating various formation temperatures of CCV‐B .The analyzed vein material of sedimentary Unit III obtained 87Sr/86Sr ratios for altered basalt  and trace elements . Mg/Ca and Sr/Ca ratios from the CCV give indications about precipitation phases and the composition of the fluid from which the carbonates were precipitated, with due regard to the temperature of vein formation and the knowledge about the temperature dependence of element partitioning between mineral and fluid /NdSN; Lawrence et al., SN/EuSN* = 2*EuSN/(SmSN + GdSN); Lawrence et al., SN/LaSN* = LaSN/(PrSN*(PrSN/NdSN)^2); Lawrence et al., SN/GdSN* = GdSN/((2*TbSN)‐DySN); Bolhar et al., REE + Y (REY) data of all carbonate rocks is presented in Post‐Archean Australian Shale (PAAS)‐normalized diagrams , the La anomaly (La/La*) SN yields a positive mean value of 1.96, and the Eu anomaly (Eu/Eu*) SN shows slight positive values , the same for the Gd anomaly (Gd/Gd*)SN with a mean value of 1.23. The Y/Ho values show a range from 33.9 to 39.1. The sedimentary host rock shows enrichment of HREE relative to LREE and MREE ((Pr/Yb)SN = 0.31, (Sm/Yb)SN = 0.45; Table Elemental composition and calculated anomalies of the strongly lithified calcareous and siliceous cemented sedimentary host rock and the extracted carbonate phase can be found in the electronic data supplement. The ratios of the major elements Sr/Ca and Mg/Ca of the carbonate phase yield mean values of 0.32 and 92.87 mmol/mol, respectively (Table 4.2.2SN = 0.91) and more strongly depleted LREE and MREE relative to HREE (mean (Pr/Yb)SN = 0.34; mean (Sm/Yb)SN = 0.37), with insignificant negative Ce anomalies (mean (Ce/Ce*)SN = 0.92). The PAAS‐normalized REY‐patterns of the CCV‐S show similarities with the sedimentary host rock and seawater , slight positive Eu anomaly (mean (Eu/Eu*)SN = 1.41), and weak Gd anomaly (mean (Gd/Gd*)SN = 1.16. Y/Ho ratios cluster at a mean value of 47.85  compared to calcium veins . The ratios of Mg/Ca ratios of the calcite veins are higher (51.25 mmol/mol) than the ratios for the aragonite veins SN = 0.51), similar to E‐type MORB and the igneous host rock , more pronounced positive La anomaly (mean (La/La*)SN = 1.60), slight positive Eu anomaly (mean (Eu/Eu*)SN = 1.34) and also weak Gd anomaly (mean (Gd/Gd*)SN = 1.06 (Table. The CCV‐B show a strong to moderate depletion of LREE and MREE relative to HREE (mean (Pr/Yb)n = 14), except of two aragonite veins with much higher values of 2904 to 4541 ppm.The Sr concentrations of all vein samples are in average ~113 ppm . The corresponding host rocks show similar results, the sedimentary host rocks have high concentrations of U (2.4 to 5.5 ppm), and the basalt shows lower U concentrations (0.1 to 0.3 ppm).55.1transitional samples (from 53R‐1‐W 126/131 to 61R‐1‐W 45/49), which are composite CCV with quartz yielding similar oxygen isotope values like the CCV‐S and less radiogenic 87Sr/86Sr ratios than the other CCV‐B  and Pacific Plate (Site 801) show generally positive δ87Sr/86Sr and lower Y/Ho ratio veins indicate formation from fluids that had undergone more basalt hydrothermal exchange.To constrain the fluid source and fluid‐rock interaction, the calculated REY anomalies were plotted against the strontium isotopic composition to discriminate the CCV‐S from CCV‐B Figure . The strModern seawater contains a large range of Y/Ho from 33 to 40 in near shore or restricted settings to 40–70 in open marine settings  and low formation temperatures. Due to their localized occurrence in the upper part of the igneous basement, the time of formation is not clear but could be around 17 Ma according to the strontium seawater curve.First fibrous calcite and clay mineral vein formation in the CCR basalt occurred shortly after the basalt formation close to the Cocos‐Nazca spreading center. Veins were formed, due to temperature differences between the basalt and the seawater, resulting in thermal contraction and seawater invasion near or off‐axis Figure . The sim18O values) of the CCV‐S (60 °C to 90 °C) and CCV‐B (32 °C to 82 °C). Bach et al.  to 72 mm/a (<10 Ma), Hole 344‐U1414A was between the Cocos Island and the spreading center 12 Ma ago (Schindlbeck et al., 687Sr/86Sr ratios. These differences are mainly attributed to different fluid sources and to the corresponding host rock and the interaction with the fluid. The isotopic and elemental composition of aragonite and fibrous calcite veins in the CCR basalt indicate that invading seawater from restricted marine setting was the fluid source and/or precipitation occurred under restricted conditions. The chemical composition of the CCV‐B in highly altered basalt corresponds rather to the geochemistry of the basaltic host rock and to a hydrothermal fluid, than to seawater. The high Y/Ho ratios and positive La and Gd anomalies suggest that CCV‐S were precipitated from seawater of more likely open marine setting or from a fluid chemical changed by fluid‐host rock interaction. The positive Eu anomaly indicates that all CCV were hydrothermally influenced and the strontium and oxygen isotopic composition of the CCV‐S and of the composite CCV‐B samples imply that seawater was modified into a hot, hydrothermal fluid. Fibrous calcite veins in the basalt were precipitated from invaded seawater near the ridge axis. These veins in the CCR basalt, as well as lithified sedimentary rocks, were penetrated by a hot and chemically modified fluid, resulting in vein formation in the sedimentary rocks and quartz and calcite precipitation in the CCV‐B. The lack of high‐temperature alteration in the basalt could be attributed to a high fluid flow rate, evidenced by hydrofracturing in the sedimentary rocks of Unit III. The geochemical results combined with the age data of Unit III and the models for formation of the Cocos Plate Seamounts after Herbrich et al. (The differences between the CCV‐S and the CCV‐B are most pronounced in their REY patterns, especially Y/Ho ratios, Mn, Fe, Sc, Na, Zr, Hf, Th, and U content, in their Mg/Ca ratios, oxygen isotopic composition and in their h et al.  and Schih et al.  constraiSupporting Information S1Click here for additional data file.Data Set S1Click here for additional data file.


BRAF mutations. Therefore, we understand that the correct evaluation of tumours requires a system that integrates both morphological, molecular and protein information in a clinical and pathological context, where intratumoral heterogeneity can be assessed. Thus, we propose the term ‘tissunomics’, where the diagnosis will be contextualised in each tumour based on the complementation of the pathological, molecular, protein expression, environmental cells and clinical data.Malignant tumours show a marked degree of morphological, molecular and proteomic heterogeneity. This variability is closely related to microenvironmental factors and the location of the tumour. The activation of genetic alterations is very tissue‐dependent and only few tumours have distinct genetic alterations. Importantly, the activation state of proteins and signaling factors is heterogeneous in the primary tumour and in metastases and recurrences. The molecular diagnosis based only on genetic alterations can lead to treatments with unpredictable responses, depending on the tumour location, such as the tumour response in melanomas versus colon carcinomas with  Despite constant progress in cancer research, mortality rates remain high.Inter‐ and intratumour heterogeneity (ITH)The paradigm of cancer as a genetic disease has existed since the early 1970s. For the last 50 years, cancer has been explained according to the somatic mutation theory (SMT),Other theories include the tissue organisation field theory (TOFT), which postulates that neoplasia arises from a local tissue disorder and may be due to a defect in interaction between cells and other tissue components,Certain genetic alterations are only observed in the context of specific cell or tissue types;The specific morphological patterns observed in human tumours have helped to identify distinct genetic changes: for example, characteristic chromosomal translocations have been identified in desmoplastic round‐cell tumours, clear‐cell sarcoma, synovial sarcoma and rhabdoid tumours.In contrast, other molecular alterations have been associated with tumours whose morphological characteristics are strikingly distinct, such as (i) the ETV6–NTRK3 translocation, detected in diverse tumour types including infantile fibrosarcoma, cellular mesoblastic nephroma and secretory breast carcinoma;Thus, the association between genetic alterations and specific tumour types is not clear, but some histopathological patterns suggest certain genetic alterations and hereditary tumour syndromes.Intratumour heterogeneity at the morphological, molecular and proteomic level is seen in most tumours. In melanoma, intratumour heterogeneity of BRAF mutations is described in more than 10% of casesin‐situ carcinomas (with no basement membrane invasion), which are observed in most carcinomas. It is noteworthy that some early neoplastic lesions such as colon adenomas and skin naevi are polyclonal. Progression to cancer probably involves the accumulation of multiple field cancerisation driver mutations among synergistically acting groups of mutations.Until now, tumour diagnosis has focused on histological and molecular features, yet it is well known that the surrounding cells and other areas of the tissue may display premalignant histological changes such as dysplasia; furthermore, many genetic alterations occur without cytological changes. These environmental changes can affect tumour progression by exerting evolutionary pressure on tumour cells and ultimately determining which mutations are selected.Mixed tumours provide the most extreme examples of intratumour heterogeneity. They are composed of two or more histological components, each with a different natural history, and are occasionally detected in every organ of the human body.In most cases, the two biologically distinct tumour components are clonally related, and it is thought that the more aggressive component arises from the more indolent one and is usually responsible for the aggressiveness of the tumour. The amount of each component is also closely related to outcome.In a small proportion of cases the two components are not clonally related: they are not true mixed tumours, but collision tumours in which two distinct neoplasms have developed independently, with a different natural history.In a high proportion of mixed tumours, morphological appearance correlates with molecular diversity. For example, mixed endometrioid and serous carcinomas of the endometrium contain elements with the microscopic characteristics of endometrioid and serous carcinoma, and molecular analysis of microdissected tumour tissue shows that the two components have a different mutational profile. Other mixed tumours are ambiguous, and different microscopic features develop in tumour components with similar molecular alterations, probably as a result of interaction with the microenvironment.In some mixed tumours the microscopic diversity is extreme. This is the case in biphasic synovial sarcoma, carcinosarcomas and some mesotheliomas. In carcinosarcomas  the malignant epithelial component gives rise to mesenchymal elements, and may even contain fully developed sarcomatoid features, such as malignant skeletal muscle, cartilage or bone elements. Integration of the molecular features into the appropriate microscopic context is essential to understand these tumours and accurately assess prognosis.Currently, precision oncology is based on the existence of alterations in certain specific therapeutic targets regardless of tumour location or type. Tumours with somatic mutations such as BRAF, EGFR or gene rearrangements such as ALK are considered therapeutic options regardless of tumour type or location, and tumours may even be characterised as BRAFomas or ALKomas. However, some clinical data have shown that, while BRAF inhibitors are effective in melanoma, the same inhibitors of the same BRAF mutations in colorectal cancer induce feedback loops in signalling pathways that can have a detrimental effect.in‐situ hybridisation or IHC probes in most molecular cancer subtypes ], transcriptomics and RNA array: proximal proliferative, proximal inflammatory and terminal respiratory unit.in‐situ hybridisation or immunohistochemistry for the expression of BRAF V600E, ALK, ROS, HER2, RET and MET.Nevertheless, druggable genetic alterations can be observed in the different molecular subtypes, and current oncology guidelines follow a reasonable scheme based on druggable genes, combining polymerase chain reaction (PCR)‐based methods to identify EGFR and BRAF mutations, and in‐situ hybridisation (FISH) or PCR: IDH1/IDH2, ATRX, TP53, FGFR, NF1, H3.1 and H3.3 mutations, EGFR and PDGFR amplifications, BRAF V600 mutation or translocations and CDKN2A/CDKN2B deletion.Four molecular subtypes have been described based on gene expression profile: proneural, mesenchymal, mixed and unknown,Medulloblastomas have four molecular subtypes with clear clinical differences . These subtypes can be assessed by immunohistochemistry or FISH, studying β‐catenin, GAB1, YAP1, Filamin A, p53, Glki1, 17q+ (group 3), MYC and CDK6 amplification.Two types of endometrial carcinoma have been described based on a combination of epidemiological, clinical, histological and molecular genetic data, distinguishing type I endometrioid endometrial carcinoma (EEC) and type II non‐endometrioid endometrial carcinoma (NEEC).Different molecular classifications are currently being explored. One of them, based on RNA genomewide studies, has characterised two main molecular groups of bladder cancer with prognostic and predictive impact.Molecular tumour subtypes based on mRNA expression profiles often show discordance with protein expression levels, depending on the RNA stability and the area sampled. It is well known that RNA studies are problematic regarding reproducibility, and that protein expression shows the real functional status of the targets. A classic example is breast cancer, in which mRNA profiles can define at least six different molecular categories. While this can be used as a general classification scheme, only IHC or FISH analysis of proteins in tumour cells within the individual subgroup can provide the exact diagnosis to guide treatment and prognosis. Some reportsThe relation between tissue context and protein expression has recently been reported in an extensive gene expression study of 17 different tumour types in more than 8000 patients.Currently, the most robust readout for ITH assessment comes from IHC. A classic example is ITH of oestrogen receptors, which may be positive in just 1% of cells; in fact, this ITH has been reported to be associated with long‐term risk of fatal breast cancer.Within an entire tumour, protein expression often depends on local factors such as hypoxia, nutrient starvation or oxidative stress, independently of the cell's genetic background. These environmental cues can alter entire signalling pathways downstream of well‐established oncogenic alterations.+, CD8+ cells, and tumour mutational burden (TMB) can also be helpful in clinical decision‐making. TMB has recently been proposed as a new biomarker to quantify the potential tumoral neoantigenicity, with the aim of predicting patients who will benefit from immunocheckpoint inhibitors. Nevertheless, different technologies and different thresholds have been proposed to define high versus low TMB in different tissue samples.Primary tumours have heterogeneous epithelial cell content, and form an ecosystem with the environmental cells, including stromal cells, endothelial cells, leucocytes, lymphocytes, histiocytes and their secreted factors. In a pathological context, we can quantify and evaluate the expression of the immune checkpoints programmed cell death ligand 1 (PD‐L1) and programmed cell death‐1 (PD‐1) in epithelial and inflammatory parts of the tumour and use this information for clinical correlation studies. Similar to cell signalling pathways, key components of immune checkpoints, such as PD‐L1, can also have heterogeneous expression throughout the tumour.Finally, the role of the microenvironment in carcinogenesis is gaining importance, although in small biopsies it is impossible to integrate the role of leucocytes, stromal cells and lymphocytes and the assessment of immune checkpoints.We postulate that cancer formation is a consortium of tumour cell clones, microenvironmental cells and local stressors (such as hypoxia) that alter protein expression and enhance tumour heterogeneity. Therefore, we believe that cancer must be considered within the context of tissue type. The correct diagnosis of a tumour should assimilate the clinical, radiological, histopathological, molecular and proteomic data.As intratumour protein and molecules are highly heterogeneous and diagnostic biopsies are small, we envision that correlation with radiological imaging and nuclear medicine will be crucial to select areas that are more representative of the whole tumour.Determination of the exact histological type is crucial for an exact diagnosis; for example, in lung carcinoma there is a huge difference in prognosis and treatment between diagnoses of small‐cell carcinoma, adenocarcinoma or large‐cell carcinoma. Similarly, in ovarian carcinoma, prognosis and survival varies widely between types: high‐ or low‐grade serous carcinoma, endometrioid carcinoma, clear‐cell carcinoma or mucinous adenocarcinoma. Most tumours can be diagnosed according to histological criteria as high‐ or low‐grade. The distinction is based on the degree of cell differentiation, the intensity of cellular atypia and cell proliferation. A proliferation index, such as Ki67, can be used to quantify the percentage of replicative cells within a tumour. This simple protein can be detected regardless of which genetic alterations are inducing the proliferation. The above‐mentioned classical factors have all been validated by RNA and molecular data.As described above, cellular stress can alter gene expression in tumour cells at several levels modifying biochemical signalling pathways and feedback loops,Because of the huge amount of data and complex positive and negative feedback regulating the final signal and the biological effect, systems biology is becoming essential for the understanding and identification of the real nodes or factors which are drivers in specific tumours in individual patients. The proto‐oncogene myc in Burkitt lymphoma and the canonical nuclear factor kappa B heterodimer in diffuse large B cell lymphoma are classic examples of so‐called master genes.Advances in digital pathology (whole slide imaging) now allow interpretation of digital slides on computer stations and integration of molecular features into the microscopic context. The differential expression of genes in different areas of the tumour can be interpreted precisely, and haematoxylin and eosin‐stained microscopic sections can be merged with multiple immunohistochemical stains for different proteins. Digital pathology also allows tumour annotation for microdissection for different tumour components, with appropriate cellularity assessment of tumour elements and the non‐neoplastic microenvironment. Digital pathology is essential to establish computerised algorithms to correlate molecular alterations with tumour phenotype.in situ, to allow the study and quantification of several dozen markers. Also, new next‐generation sequencing technologies are being implemented in routine testing combining DNA and RNA analysis from the same slide reducing the amount of tissue and also the ITH.Given the numerous alterations in genes, protein expression and mRNA, it is clear that we will have to implement multiplex technologies that will allow us to study multiple factors simultaneously on the same histological sections. With this approach we can minimise the amount of tissue needed for molecular and protein studies and for quantification of the expression of different factors and their inter‐relationship. Different platforms are emerging, with different quantitative multispectral fluorescence approaches, or with mass spectrometry The main objective for the use of deep learning in pathology is to improve existing algorithms for biomarker quantification and to develop smart and robust algorithms. It can be based on three main areas or objectives: (i) tumour type classification, (ii) tumour prognosis  and (iii) personalised treatment allocation system . In fact, deep learning is already being applied in various tumour types, including breast, lung, melanoma and glioblastoma.in silico and predicting the best targets for each patient and tumour .Systems biology encompasses tools that hold great promise for deciphering the vulnerabilities of the tumour ecosystem as a whole. Studies are based on the premise that multiple oncogenic events converge on a number of cellular networks that may contain essential or synthetically lethal clinically targetable hubs or factors,As biopsies are associated with a degree of invasiveness and cannot always be repeated, new approaches have been proposed, such as the analysis of circulating tumour cells (CTCs), plasma‐derived cell‐free tumour DNA (cfDNA) or RNA and, more recently, DNA from circulating tumour exosomes in blood.tissunomics.Tumours show such a degree of morphological, molecular and proteomic heterogeneity, and a close relationship with microenvironmental factors, that for the accurate pathological evaluation of tumours an integrated approach seems essential: all genomic and proteomic data should be evaluated taking into account the heterogeneity and tissue type Figure . We propAll authors declare no conflicts of interest.


The ninth author’s name is spelled incorrectly. The correct name is: Jun Nyung Lee.In the Funding Statement, one of the grant numbers from the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIP) is missing: 2019R1F1A1062343 for SS.