Treatment with small-molecule inhibitors, guided by precision medicine has improved patient outcomes in multiple cancer types. However, these compounds are often not effective against central nervous system (CNS) tumors. The failure of precision medicine approaches for CNS tumors is frequently attributed to the inability of these compounds to cross the blood-brain barrier (BBB), which impedes intratumoral target engagement. This is complicated by the fact that information on CNS penetration in CNS-tumor patients is still very limited. Herein, we evaluated cerebrospinal fluid (CSF) drug penetration, a well-established surrogate for CNS-penetration, in pediatric brain tumor patients. We analyzed 7 different oral anti-cancer drugs and their metabolites by high performance liquid chromatography mass spectrometry (HPLC-MS) in 42 CSF samples obtained via Ommaya reservoirs of 9 different patients. Moreover, we related the resulting data to commonly applied predictors of BBB-penetration including ABCB1 substrate-character, physicochemical properties and in silico algorithms. First, the measured CSF drug concentrations depicted good intra- and interpatient precision. Interestingly, ribociclib, vorinostat and imatinib showed high (> 10 nM), regorafenib and dasatinib moderate (1–10 nM) penetrance. In contrast, panobinostat und nintedanib were not detected. In addition, we identified active metabolites of imatinib and ribociclib. Comparison to well-established BBB-penetrance predictors confirmed low molecular weight, high proportion of free-drug and low ABCB1-mediated efflux as central factors. However, evaluation of diverse in silico algorithms showed poor correlation within our dataset. In summary, our study proves the feasibility of measuring CSF concentration via Ommaya reservoirs thus setting the ground for utilization of this method in future clinical trials. Moreover, we demonstrate CNS presence of certain small-molecule inhibitors and even active metabolites in CSF of CNS-tumor patients and provide a potential guidance for physicochemical and biological factors favoring CNS-penetration. Brain tumors are the most frequent solid tumors in childhood and the leading cause of cancer-related death in this age group . This faThis gap is widely attributed to the fact that penetrance of anti-cancer drugs to the central nervous system (CNS) is limited by the blood-brain barrier (BBB) and blood-CSF-barrier, which prevent potentially effective drugs from engaging their targets within the tumor tissue . The BBBBased on the above-mentioned facts, it is indispensable for an effective anti-brain-tumor treatment that the respective remedies cross the BBB. Consequently, it is generally considered that preclinical as well as pharmacokinetic assessment of novel small molecule inhibitors against brain tumors should include evaluation of BBB penetration , 17. As Besides, plasma protein binding is a key parameter for sufficient CNS penetration –24. ProtIn contrast to the identification of multiple tumor targets across pediatric brain tumors for precision medicine-guided treatment , informaSamples were obtained from patients treated at the Department of Pediatrics and Adolescent Medicine at the General Hospital of Vienna and the study was approved by the ethics committee of the Medical University of Vienna. Patient characteristics  and clinical data  were retrieved from patient charts. Clinical and serum parameters were measured within the same treatment cycle, CSF protein levels at the same date and sample collection time point. Samples were collected and snap frozen within routine clinical sampling during intraventricular chemotherapy administration.We included samples of patients who received oral small molecule inhibitors and concomitant intraventricular therapy. The investigated substances included dasatinib , imatinib , nintedanib , panobinostat , regorafenib , ribociclib , and vorinostat . As backbone therapy the majority of patients were treated according to the MEMMAT protocol (NCT01356290)  with sliWithin the scope of this work, in silico based metabolite prediction was performed using ADMET Predictor 9.0 , Pallas 3.8 , and Smartcyp 2.4.2 –43, reveIn addition, ADMET Predictor 9.0 was utilized to predict brain exposition via its integrated algorithm that binary (high or low) estimates BBB penetration and quantitatively predicts the logarithm of the brain to blood partition coefficient. As complementary approach we used the SwissADME predictor , which gWe first compared interaction of the investigated drugs with ABCB1 by measuring fluorescent substrate drug accumulation in the parental KB-3-1 (a HeLa cell derivative) cell model and its isogenic ABCB1-overexpressing KB-C1 cell model, as previously published . As a knDirectly measuring free drug levels in CSF may be impossible due to low drug concentrations. Besides the experimental quantitation, if feasible, also the law of mass action can be used to predict protein-unbound drug levels . Accordi− 1 to 250 μg L− 1).In a first step, we determined whether CSF samples from Ommaya reservoirs analyzed with HPLC-QqQ MS or HPLC-IMS-Q-TOF MS allow reliable detection of orally administered drugs and the respective metabolites. For that purpose, special focus was on the improvement of an HPLC-QqQ MS multi-method to quantitate the respective substances in CSF samples. The applied chromatographic gradient as well as the sensitivity of the MS detection were optimized to allow a quantitation of all mentioned analytes within one run and over a broad range of analyte concentration levels  of the method was determined to be well below 1 μg L− 1 for all analytes, . The determination of CCS was performed by the means of HPLC-IMS-Q-TOF MS showing highly reproducible results with intra-day precisions ≤0.1% relative standard deviation (RSD) of 5 consecutive measurements and inter-day precisions ≤0.2% RSD for all analytes, .For each analyte, the recovery of the method was tested, including sample preparation and HPLC-QqQ MS analysis, and matrix-matched calibration was used to compensate possible matrix-induced electrospray ionization suppression/enhancement effects, thereby assuring the accuracy of the quantitation. Intra-day and inter-day precision were determined to be ≤8.6% relative standard deviation for all analytes on the basis of five consecutive measurements of artificial samples containing 5 μg LIn total, 42 CSF samples of 9 pediatric patients  receiving 7 different drugs were analyzed Fig. . DetaileAs a next step, free drug levels were calculated using the law of mass action approach stated in the supplementary, showing that protein binding may be neglected for most of the investigated compounds see Fig. b. In casUsing high performance liquid chromatography ion mobility quadrupole time-of-flight mass spectrometry (HPLC-IMS-Q-TOF MS) measurements in combination with prediction software and in-house generated databases, it was also possible to evaluate the metabolic fate of the examined substances in a semi-automated way. ADMET Predictor 9.0 and Pallas 3.8 were used to predict metabolites of parent drugs qualitatively, as both software packages provide molecular structure output of P450 metabolized substances. In contrast, Smartcyp 2.4.2 calculates the likelihood of a certain molecular moiety to be metabolized by P450 cytochromes based on characteristics within the molecule’s 2D structure. Detected metabolites and potential biological activity are summarized in Table − 1) was not detected in CSF, in line with the finding that larger molecules are less frequently found to cross the BBB [As preclinical prediction of BBB penetration remains essential for development of improved anti-cancer therapies for brain tumor patients, we sought to validate commonly applied methods for BBB penetrance prediction with our dataset. Figure  the BBB . Convers the BBB . Within  the BBB , 19. ConLast, we aimed at the evaluation of commonly applied in silico methods for the prediction of BBB penetration. These algorithms integrate multiple of the aforementioned parameters and are therefore generally considered as more advanced and reliable tools for evaluation of BBB penetrance , 51. A cThe integration of molecular tumor profiling to detect oncogenic dependencies and the availability of multiple targeted compounds for the respective alterations has widely improved anti-cancer treatment. However, low CNS penetration of small molecule inhibitors caused by the BBB poses a major obstacle for the clinical use of improved and innovative therapies against brain tumors. Although various in vitro, in silico and in vivo models have been developed to predict BBB drug penetration in the past decades, the true nature of the BBB in CNS tumors and the actual penetrance of drugs into the malignant tissue is still difficult to assess. Consequently, it frequently remains difficult to clarify whether the failure of promising in vitro approaches in clinical trials is owed to a poor anti-tumor effect or limited CNS penetration. As the blood-CSF barrier is composed of similar structures as the BBB and CSF is directly connected to the CNS tissue, measuring CSF levels is widely considered as feasible way to indicate BBB penetration . HoweverIn detail, we could detect significant levels of dasatinib, imatinib, regorafenib, ribociclib, and vorinostat in CSF of brain tumor patients. In contrast, nintedanib and panobinostat were not detected albeit only one case was available for panobinostat sampling. With respect to panobinostat, it is also worth noting that due to the age of the patient  the treatment dosing was chosen according to the regimen approved for hematological malignancies in adults . Consequently, the chosen dose was lower than in recent studies within the pediatric population . Corrobo50 determined for high-grade glioma [50 for germ cell tumors are still lacking.The CSF-levels of dasatinib were in the low nM range which is well in agreement with CSF levels described for this tyrosine kinase inhibitor in acute lymphoblastic leukemia (ALL) patients . These re glioma . The same glioma  but prec50 for certain high-grade glioma models [Similarly, levels of imatinib were in the same magnitude as described for an ALL patient . In conta models . Interes50 previously determined for other pediatric tumor models [Regorafenib, another kinase inhibitor with promising clinical activity against brain tumors , also rer models .Ribociclib, a CDK4/6 inhibitor was also detected at clinically relevant levels in CSF. The magnitude was comparable, albeit lower compared to recently published studies , 65 inve50 values in preclinical models of medulloblastoma [We further show that the histone deacetylase inhibitor vorinostat penetrates the CSF. The concentration, however, was about 10-fold lower as compared to ICblastoma .Using in silico based metabolite prediction approaches and high-resolution mass spectrometry, the metabolic fate of the target analytes in CSF was monitored for the first time. Although predominantly phase I metabolites such as oxidation, hydroxylation and hydrolysis products were detected, their existence in CSF is an exciting finding, since especially phase one metabolites, which we detected for imatinib and ribociclib, might still be pharmacologically active , 74. AddLast, we sought to evaluate the obtained patient data with respect to physicochemical properties of the respective small molecules and commonly applied predictors of BBB penetration comprehensively. We confirm that low MW, low protein binding and low ABCB1-affinity as in case of vorinostat and ribociclib are favorable predictors of BBB-penetration. It has to be noted that unfavorable characteristics for only one of the parameters may already lead to significantly lower CSF concentrations as in case of panobinostat, which exhibits low MW and moderate protein binding but high ABCB1-affinity. Moreover, we evaluated the in silico tools SwissADME and ADMET Predictor which integrate multiple physicochemical properties to predict BBB penetration of molecules. Interestingly, there was no or only a poor correlation to the findings in our data. This highlights the overall complexity of prediction BBB penetration as multiple physicochemical and biological factors determine the permeability of the BBB barrier. It might also reflect that ABCB1-affinity is difficult to predict in silico and that preclinical evaluation should be based on a combination of physicochemical and biological tests. Taken together, our comparative analyzes emphasize the necessity to evaluate the BBB barrier penetration in clinical studies.In summary, we present CSF-sampling via Ommaya-reservoirs as a feasible, reliable and safe strategy to investigate CSF-concentrations of small molecule inhibitors in brain tumor patients. This method could open new opportunities to evaluate BBB penetration in patients with brain tumors in future clinical trials. Finally, our correlations of patient-derived data to established predictors of CNS-penetration emphasize the importance of a comprehensive approach for preclinical assessments, taking into account both biological and physicochemical properties.Additional file 1:Table S1. Supplementary information on clinical parameters and sample collection. Table S2. Sequential therapies of the investigated drugs in the study cohort. Figure S1. Depiction of the used HPLC gradient for sample analysis. Table S3. Overview of the used mass spectrometer parameters. Figure S2. Normalized chromatogram of a standard solution of dasatinib, imatinib, nintedanib, panobinostat, regorafenib, ribociclib, and vorinostat obtained with the developed HPLC-QqQ MS method. Table S4. Overview of the corresponding method performance parameters. Figure S3. Depiction of measured CCS values of dasatinib, imatinib, nintedanib, panobinostat, regorafenib, ribociclib, and vorinostat. Figure S4. Depiction of the quantitation results for imatinib CSF samples sorted by patient. Figure S5. Depiction of the quantitation results for vorinostat CSF samples sorted by patient. Figure S6. Depiction of the correlation between imatinib levels and CSF protein amounts. Figure S7. Matched CSF protein concentrations of all investigated CSF samples stratified for drug and individual patients. Figure S8. ABCB1 testing. Table S5. Supplementary description of the color-coding used in the Fig.


Cerebral autosomal dominant arteriopathy with subcortical infarct and leukoencephalopathy (CADASIL) is a Notch3 mutation-induced cerebral small vessel disease, leading to recurrent ischemic stroke and vascular dementia. There is currently no treatment that can stop or delay CADASIL progression. We have demonstrated the efficacy of treatment with combined stem cell factor (SCF) and granulocyte colony-stimulating factor (G-CSF) (SCF+G-CSF) in reducing cerebral small vessel thrombosis in a TgNotch3R90C mouse model of CADASIL. However, it remains unknown whether SCF+G-CSF treatment protects neurons from microvascular thrombosis-induced ischemic damage. Using bone marrow transplantation to track thrombosis, we observed that capillary thrombosis was widely distributed in the cortex, striatum and hippocampus of 22-month-old TgNotch3R90C mice. However, the capillary thrombosis mainly occurred in the cortex. Neuron loss was seen in the area next to the thrombotic capillaries, and severe neuron loss was found in the areas adjacent to the thrombotic capillaries with bifurcations. SCF+G-CSF repeated treatment significantly attenuated neuron loss in the areas next to the thrombotic capillaries in the cortex of the 22-month-old TgNotch3R90C mice. Neuron loss caused by capillary thrombosis in the cerebral cortex may play a crucial role in the pathogenesis of CADASIL. SCF+G-CSF treatment ameliorates the capillary thrombosis-induced ischemic neuron loss in TgNotch3R90C mice. This study provides new insight into the understanding of CADASIL progression and therapeutic potential of SCF+G-CSF in neuroprotection under microvascular ischemia in CADASIL. Cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) is the most common monogenic cause of stroke and vascular dementia in adults . CurrentCADASIL is caused by mutations in the NOTCH3 gene . NOTCH3-Cerebral microcirculation plays a vital role in brain health. Cerebral capillaries with a total length of ∼400 miles in humans are the primary site of oxygen, nutrient and metabolic exchange . CerebraStem cell factor (SCF) and granulocyte colony-stimulating factor (G-CSF) are the essential hematopoietic growth factors regulating blood cell production and bone marrow stem cell survival . RecentlThis study aims to determine the distribution of capillary thrombosis in the brain, the existence of cerebral capillary thrombosis-caused ischemic neuron loss, and the efficacy of SCF+G-CSF treatment in reducing microvascular ischemic damage in TgNotch3R90C mice.All procedures in this study were approved by Institutional Animal Care and Use Committee at SUNY Upstate Medical University and LSUHSC.n = 5/group) (Transgenic mice (TgNotch3R90C) carrying a full-length human NOTCH3 gene with the Arginine-to-Cysteine (Arg90Cys) mutation driven by the SM22α promoter were used as a mouse model of CADASIL . The ori5/group) .7 bone marrow cells in 0.6 ml HBSS per mouse).The bone marrow of UBC-GFP mice (C57BL/6 background) was transplanted into the TgNotch3R90C mice (C57BL/6 background) to track blood clots (thrombosis) in the cerebral capillaries of TgNotch3R90C mice. UBC-GFP mice  were anesthetized with Avertin   and euthanized. The femur bones were dissected and placed into a cell culture dish with ice-cold sterile Hanks Balanced Salt Solution (HBSS) . Bone marrow cells were flushed out, gently triturated, and filtered through a 70 μm nylon mesh . Harvested cells were centrifuged, re-suspended with HBSS into single cell suspension and then transplanted to the irradiated TgNotch3R90C mice by tail vein injection , mice were euthanized by transcardiac perfusion of phosphate-buffered saline (PBS)  containing heparin  followed by 10% neutral buffered formalin . Brains were removed and post-fixed in the same fixative solution overnight at 4°C, and then dehydrated in 30% sucrose solution  in PBS for 2 days at 4°C. Brains were sectioned at a thickness of 30 μm using a Cryostat . All brain sections were stored at −20°C with anti-freeze buffer containing 30% ethylene glycol and 30% glycerol  prepared in PBS until used for immunohistochemistry.TM, Vectashield, Vector Laboratories, Burlingame, CA, United States). Brain sections were incubated with rat anti-mouse CD31 (1:50) , mouse anti-mouse NeuN (1:600)  and goat anti-mouse GFP (1:600)  primary antibodies at 4°C overnight. The next day, brain sections were washed with PBS and then incubated with the appropriate secondary antibody for 2 h at room temperature in the dark. The secondary antibodies used were Alexa Fluor 594-conjugated donkey anti-rat (1:500), Alexa Fluor 594-conjugated donkey anti-mouse (1:500) and Alexa Fluor 488-conjugated donkey anti-goat (1:500) . The antibodies were all diluted in PBS containing 1% BSA and 0.3% TritonX-100. Nuclei were stained with mounting medium (VECTASHIELD) containing DAPI . Images were taken with a Zeiss 780 confocal microscope .Two brain sections per mouse (bregma 0.02 mm to −1.82 mm) were used for immunohistochemistry. After brain sections were rinsed with PBS, nonspecific binding was blocked with 10% donkey serum prepared in 1% bovine serum albumin  and 0.3% Triton X-100  solution for 1 h at room temperature. For the primary antibodies from mouse origin, brain sections were further blocked with mouse-on-mouse blocking reagent  followed by LSD post hoc multiple comparison tests were used to analyze two factor comparisons. All the data are presented as mean ± standard error of mean (SEM), and results were considered significantly different when a p-value was less than 0.05. Analyses were performed, and data were displayed using Prism software .Data analysis was performed in a blinded manner. Two-group comparisons were analyzed using a student We first examined the distribution of the capillary thrombosis in the brains of TgNotch3R90C mice by detecting bone marrow-derived GFP positive blood cells that occluded the capillaries (capillaries: <10 μm in diameter) through immunofluorescence double staining of CD31 (EC marker) and GFP (bone marrow-derived blood cells). We observed that capillary thrombosis was randomly located in the brain. The most capillary thrombosis was seen in the cortex, which accounted for 62.3% of total occluded capillaries. The frequency of capillary thrombosis in the striatum and hippocampus was 26.1% and 11.6%, respectively, . To furtp < 0.05). In the areas next to the thrombotic capillaries with non-bifurcation, SCF+G-CSF treatment significantly increased the number of NeuN positive neurons (p < 0.01). Moreover, the number of NeuN positive neurons was also significantly increased in the areas adjacent to the thrombotic capillaries with the bifurcation after SCF+G-CSF treatment (p < 0.05). However, SCF+G-CSF treatment-enhanced neuron survival was more robust in the microareas next to thrombotic capillaries without bifurcation than in the microareas next to thrombotic capillaries with bifurcation (p < 0.05). These data indicate that the structure of cortical capillaries may influence the microenvironment in the brains of the TgNotch3R90C mice, which affects the severity of capillary thrombosis-caused ischemic neuron damage. The findings also demonstrate that SCF+G-CSF treatment protects neurons from ischemic injury caused by capillary thrombosis in the cortex of TgNotch3R90C mice. The extent of SCF+G-CSF-enhanced neuron survival in the microareas next to the thrombotic capillaries is also influenced by the structure of the thrombotic capillary.Next, we sought to determine the involvement of capillary thrombosis in neuronal damage and the effect of SCF+G-CSF treatment in neuroprotection in the brains of TgNotch3R90C mice. First, we quantified the number of neurons in the cortex, striatum and hippocampus through NeuN immunostaining. We observed that the number of NeuN positive neurons was not significantly different between the SCF+G-CSF-treated and non-treated TgNotch3R90C mice in the cortex, striatum and hippocampus . We thenIn the present study, we have identified that the majority of capillary thrombosis in the brain of TgNotch3R90C mice occurs in the cortex. We have also, for the first time, demonstrated that (1) microscopically detectable neuron loss exists in the area next to the thrombotic capillary, (2) the neuron loss becomes more severe in the areas adjacent to the thrombotic capillaries with bifurcations, and (3) SCF+G-CSF treatment ameliorates the neuron loss adjacent to the thrombotic capillaries in the cerebral cortex of 22-month-old TgNotch3R90C mice .We employed the bone marrow transplantation in this study to track blood cells in the cerebral capillary thrombosis. Before the bone marrow transplantation, all the mice received a lethal dose (900 rad) of radiation to ablate their bone marrow. This bone marrow transplantation approach has been successfully used for tracking bone marrow-derived cells in our previous studies . It has Our data show that capillary thrombosis is widely distributed in the cerebral cortex, striatum and hippocampus of 22-month-old TgNotch3R90C mice. These findings are consistent with our earlier study  revealinIn TgNotch3R90C mice, degenerating ECs and impaired cerebrovascular function are found as early as 10 months of age . Our preOur data have also revealed that the majority of blood-occluded capillaries are located in the cerebral cortex, and that neuron loss occurs in the areas next to the thrombotic capillaries in TgNotch3R90C mice. These observations are in line with clinical findings revealing microinfarcts in the cortex of CADASIL patients . These fIt remains unclear why the capillary thrombosis is mainly located in the cortex, instead of the striatum and hippocampus. It has been documented that the topological distribution of the capillary network is different throughout the brain to match the regional metabolism . The vasVascular occlusion and hemorrhage are the vascular events that lead to regional neuronal death  . Here weIn the present study, SCF+G-CSF treatment-reduced neuronal loss has been observed in the areas adjacent to the thrombotic capillaries, demonstrating the neuroprotective efficacy of SCF+G-CSF on capillary thrombosis-induced ischemic damage in the brains of TgNotch3R90C mice. The effects of SCF and G-CSF in neuroprotection have been reported in focal cerebral ischemia. Focal cerebral ischemia is produced by occlusion of a relatively large artery, the middle cerebral artery (MCA), leading to massive brain tissue loss  in the territory of the occluded MCA. In rodent models of focal cerebral ischemia, systemic administration of SCF , G-CSF , and SCFThe mechanism underlying SCF+G-CSF-enhanced neuroprotection in different phases of cerebral ischemia remains unclear. Expression of receptors for SCF  and G-CSin vitro studies, many in vivo studies have revealed that SCF and G-CSF may protect the brain from post-ischemic neuron loss through an indirect way. It has been shown that brain ischemia-triggered neuroinflammation in both the acute and subacute phases leads to secondary neuron loss including apoptotic neuron death (in vitro hypoxia models (In addition to the direct effects of SCF and G-CSF in neuroprotection demonstrated in on death . G-CSF ton death , reduceson death , inhibiton death  and reduon death . SCF+G-Con death . In our on death . Intracea models . It woulOur previous studies have demonstrated that repeated treatments with SCF+G-CSF reduce cerebral capillary thrombosis, attenuate capillary thrombosis in the bifurcation regions , enhanceIn conclusion, this study provides new and important evidence demonstrating that capillary thrombosis-caused microvascular ischemic damage exists in the brains of 22-month-old TgNotch3R90C mice. The thrombotic capillaries are mainly located in the cortex, and the capillary thrombosis leads to local neuron loss. Systematic administration of SCF+G-CSF attenuates neuron loss in the areas next to the thrombotic capillaries. These findings advance toward an understanding of the pathological role of cortical capillary thrombosis-caused microvascular ischemia in the pathogenesis of CADASIL and reveal a new therapeutic target for developing treatment to ameliorate microvascular ischemia in CADASIL.The original contributions presented in the study are included in the article, and further inquiries can be directed to the corresponding author.The animal study was reviewed and approved by the Institutional Animal Care and Use Committee at SUNY Upstate Medical University and LSUHSC.SP, MG-T, and XL performed the experiment. SP prepared the first draft of the manuscript. XQ provided assistance in the data analysis. LRZ conceived the study, supervised the experiment, and revised the manuscript. All authors reviewed and approved the submitted version of the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Previous research shows that countries with opt-out consent systems for organ donation conduct significantly more deceased-donor organ transplantations than those with opt-in systems. This paper investigates whether the higher transplantation rates in opt-out systems translate into equally lower death rates among organ patients registered on a waiting list . We show that the difference between consent systems regarding kidney- and liver-patient mortality rates is significantly smaller than the difference in deceased-donor transplantation rates. This is likely due to different incentives between the consent systems. We find empirical evidence that opt-out systems reduce incentives for living donations, which explains our findings for kidneys. The results imply that focusing on deceased-donor transplantation rates alone paints an incomplete picture of opt-out systems’ benefits, and that there are important differences between organs in this respect. Organ failure is a widely occurring medical condition with lethal consequences if left untreated. The most important treatment for end-stage organ failure is the transplantation of a donor organ. However, due to a shortage of donor organs, many patients die while waiting for an organ transplant . DecAlmost every country has a system to formalize the default consent for deceased-donor organ donation. Systems in which the default is to become a donor after death are called “opt-out” or “presumed consent” systems. Systems in which the default is not to become a donor after death are “opt-in” or “informed consent” systems. Earlier research has shown that the number of transplantations from deceased donors is substantially higher in countries with opt-out systems than those with opt-in systems –8. A posThe relationship between consent systems for organ donation and organ-patient mortality rates is not as obvious as it may seem, because a substantial difference in deceased-donor transplantation rates between consent systems also changes incentives. For example, a larger supply of organs from deceased donors reduces individuals’ incentives to become a living donor This paper is the first to analyze whether organ-patient mortality rates are indeed lower in countries with opt-out consent systems for organ donation compared to those with opt-in systems. We study between-country differences, using data from newsletters from the Organización Nacional de Trasplantes on the number of kidney, liver, heart, and lung transplantations performed and the number of patients who died while registered on a waiting list to receive a donation of one of those organs. We gathered data from several other sources to determine whether a country has an opt-out or opt-in system. Combining these data, we create the largest data set available on organ-patient mortality and organ transplantations; our sample consists of 69 countries across a period of 15 years . Additionally, we obtained data on several potentially confounding factors from the World Bank, the World Health Organization, and the World Values Survey.There is a considerable difference between a patient with kidney disease , a patient with heart disease , a patient with lung disease (who may choose a ventilator), and a patient with liver disease . We therefore show separate analyses for each organ and do not pool the organs. We estimate two regressions for kidneys, livers, hearts, and lungs separately, while controlling for year fixed-effects as well as for a country’s GDP, general mortality rates, health expenditures, and religious denomination. The first regression shows the relationship between countries’ consent systems for organ donation and the number of deceased-donor transplantations per million population . The second regression shows the relationship between consent systems and patients who died while on a waiting list for a donor organ per million population . By estimating the two equations as seemingly unrelated regressions, we can analyze whether the correlation between opt-out systems and deceased-donor transplantation rates is significantly different from the correlation between opt-out systems and organ-patient mortality rates.For hearts, we find that opt-out systems have a small but statistically significant advantage in terms of deceased-donor transplantation rates, and that this translates into similarly lower heart-patient mortality rates compared to opt-in systems. For lungs, however, deceased-donor transplantation rates do not differ significantly between consent systems; this is reflected in the mortality rates, which are also not significantly different from each other between consent systems. Although the advantages of opt-out systems are by far the largest for deceased-donor kidney and liver transplantation rates, these are also the organs for which the differences in organ-patient mortality rates are significantly smaller  than the differences in deceased-donor transplantation rates between consent systems.We investigate which incentives could explain the surprisingly small differences between consent systems regarding kidney- and liver-patient mortality rates. For kidneys, we find empirical evidence that lower incentives to become a living donor in opt-out systems, reflected by lower rates of living donations, can explain our findings: the difference between consent systems in kidney-patient mortality rates is similar to what could be expected from the total kidney transplantation rates . For livers, differences in organ-patient mortality rates between consent systems remain significantly smaller than the differences in transplantation rates, even when transplantations from living donors are considered. We do not find empirical evidence that opt-out systems are related to different incentives for kidney and liver patients to purchase an organ on the black market : excluding countries with reports of organ trade as either a donor or recipient country does not change our main results.th percentile.We investigate the robustness of our results in various sensitivity checks. One potential measurement issue is related to the earlier stated hypothesis that incentives to enter, keep, or remove patients from the waiting list may differ between consent systems. More lenient policies regarding waiting list entry not only affect the probability of patients dying from other factors than organ failure ; they also increase the number of patients registered on the waiting lists and thereby, by construction, the number of deaths on the waiting lists. However, the empirical evidence does not support these hypotheses: taking the conservative approach of assuming that if an organ patient was removed from the waiting list because (s)he was too sick to receive a transplant implies that the organ patient died, does not change our results. Our results also remain unchanged when we control for waiting list length, indicating that countries with different consent systems do not have substantially different policies regarding waiting list entry. These two robust results indicate that, although fatal co-morbid conditions affect the number of deaths on the waiting lists, it is unlikely that they substantially affect the difference in organ-patient mortality rates between consent systems. The results also remain robust when we reduce country heterogeneity by only including Europe, North America, Australia, and New Zealand, when we use different methods to deal with zero values , and when we deal with potential outliers by truncating the data at the 99The findings provide an important contribution to the literature on organ donation and thereby provide new insights for the discussion on the advantages and disadvantages of the two consent systems for organ donation. First, they highlight that the advantages and disadvantages differ substantially by organ. This is an important addition to the current literature on the topic, which often focuses on one single organ . Second, we find empirical evidence that opt-out systems decrease the incentives to become a living kidney donor. Although we are not the first to find this result This paper proceeds as follows: Section 2 discusses the empirical strategy, Section 3 discusses the data, and Section 4 gives the results. Section 5 concludes.The aim of this paper is to analyze whether organ-patient mortality rates differ between countries with opt-out or opt-in consent systems for organ donation. In our main specifications, we estimate the following model for kidneys, livers, hearts, and lungs separately:c indexes the country, and t indexes time in years. For simplicity, organ-specific subscripts are suppressed from the equation. Mortality is the organ-patient mortality rate, i.e., the number of people who died throughout year t while on a waiting list to receive either a donor kidney, liver, heart, or lung, divided by the size of the population (in millions) of that person’s country of residence. The variable optout is an indicator variable with a value of 1 if a country has an opt-out consent system for organ donation and 0 if that country has an opt-in system. In our main specification, we exclude countries that changed their consent system within our data window (see more about this in Section 2.4). Therefore, the opt-out dummy variable does not vary over time. We also control for year fixed effects δ as well as for X’; a vector of country characteristics, i.e., the country’s GDP, health expenditures, age-standardized death rates , and religious denomination  to the relationship between consent systems and deceased-donor transplantation rates. We estimate the following model for each organ separately :DDTXct stands for the deceased-donor transplantation rate in country c in year t, i.e., the number of transplantations from deceased donors divided by the size of the population (in millions). Based on previous findings in the literature, we expect δ as well as X’, which is a vector of variables that are identical to those in Eq  and  is equalAlthough it is tempting to try to exploit the fact that some countries in our data changed their consent system for organ donation within our data window, this would be inappropriate for several reasons. First, a country’s decision to change its consent system is likely to be endogenous, i.e., related to previous trends in organ-patient mortality rates, the population’s attitudes toward organ donation, or technological advances in increasing organ-patient longevity, for instance. Therefore, estimates based on within-country analyses do not necessarily reveal causal effects of a consent system change but rather pick up the continuation of a previously existing trend.α1 and β1 that is biased toward zero. However, trying to take into account the lagged effects poses problems as well because it is uncertain how big the lag would be and because the size of the lag may vary from one country/consent system change to another. Moreover, even if the size of the lag would be known, the fact that there is a lag makes it substantially less likely that nothing else changed that may affect transplantation or organ-patient mortality rates since the consent system changed, again leading to biased estimates of α1 and β1.Second, even if the decision to change the consent system was exogenous, implementing this change may have lagged effects on transplantation rates and therefore on organ-patient mortality rates: it may take several years before countries have sufficiently increased their health care capacity  to use the entire additional supply of organ donors. Therefore, merely adjusting the opt-out dummy from the year of the consent system change onward, thereby ignoring any lagged effects, would likely lead to an estimation of α1 and β1.Finally, only a few countries in our sample switched from one consent system to another within our data window. Therefore, the statistical power to study within-country differences is limited, which may lead to biased estimates of We obtained the data from a great variety of sources, leading to the largest data set available to study the relationships between consent systems and organ-patient mortality rates and transplantation rates. In this section, we briefly introduce the data. In Appendix 1 and Appendix 2 in Our main data source is newsletters from the Organización Nacional de Trasplantes. From Newsletter Transplant 2002  onward, the newsletters include data on the number of kidney, liver, heart, and lung transplantations performed, as well as the number of patients who died while on a waiting list to receive a donor kidney, liver, heart, or lung. For each organ, we divide both variables by the size of the population (in millions) to obtain the rates of organ-patient mortality and transplantations.Between 2001 and 2015, the number of countries included in our sample increased from 35 to 66. In Table B in the From other sources, we obtained information on whether countries have opt-in or opt-out consent systems (see Table C in the Most deceased-donor transplantations (per million population: pmp) are kidney transplantations, and most patients who died while on the waiting list (pmp) were waiting for a kidney transplant , 9.3 (7.0) for liver transplantations, 3.6 (2.9) for heart transplantations, and 2.9 (3.9) for lung transplantations. Although there are minor fluctuations and differences between consent systems, every year the organ-patient mortality rate is around 5 pmp among patients who were on a kidney waiting list, 2 pmp among those who were waiting for a liver transplant, 1 pmp among those who were waiting for a heart transplant, and less than 1 patient pmp among those who were on the waiting list for a lung transplant.The second set of estimates in 2 tests, for which the p-values are given in the bottom of the table. The results show that, for kidneys and livers, the difference between opt-out and opt-in systems in terms of patient mortality rates is smaller than the difference in terms of deceased-donor transplantation rates. For hearts and lungs, on the other hand, the differences in terms of patient mortality and deceased-donor transplantation rates are similar, which is what one would expect if there is a one- to-minus-one relationship between deceased-donor transplantations and organ-patient mortality.However, the more important question is whether the difference between consent systems regarding organ-patient mortality rates is similar to what could be expected based on the difference in deceased-donor transplantation rates, i.e., whether if The results in total transplantation rates . We can indeed analyze this with our data.One important example of potential differences in incentives between consent systems is that the larger supply of organs from deceased donors in opt-out systems may reduce people’s incentives to become a living donor. Considering that transplantations from living donors almost exclusively apply to kidneys and livers because living heart transplantations are not medically possible and living lung transplantations are still extremely rare, this is a particularly likely mechanism for our findings. Moreover,  and 13]13] alreap = 0.20 for kidneys). This means that the lower incentive to become a living kidney donor in opt-out systems (reflected by lower living kidney transplantation rates) can explain why kidney-patient mortality rates are not as low in opt-out systems as one would expect based on the deceased-donor kidney transplantation rates alone.Similar to the result in our main analysis, In contrast to the advantage of receiving a kidney from a living donor relative to receiving one from a deceased donor , live liThe smaller deceased-donor and total supply of donor organs in opt-in systems creates incentives for organ-patients in countries with opt-in systems to try to speed up the process by purchasing an organ. However, despite the worldwide shortage of organs, the commercial trade of organs is illegal in almost all countries. When there is a black market for organ transplantations, the true number of transplantations in the donor’s country may be higher than what is reported in our data. At the same time, organ patients who consider purchasing their organ may not even enter the waiting list. If the purchase was successful in the sense that the recipient (who did not enter the waiting list) does not die, we overestimate the organ-patient mortality rates in the recipient’s country. However, if the  recipient who did not enter the waiting list dies either before or after having purchased the organ, we underestimate the organ-patient mortality rates in the  recipient’s country. Both mechanisms may lead to biased estimates of the opt-out effects on transplantation rates and organ-patient mortality rates.Despite the illegality of commercial organ trade, there have been reports of organ sales in the following countries in our data : Bolivia, Brazil, Colombia, Egypt, Iran, Moldova, Peru, and Turkey . Accordip-values in the bottom of the table, the conclusions are identical to those in In total transplantation rates and organ-patient mortality rates.This section discusses the results of a variety of robustness checks. As we established in Section 4.2 that it is inappropriate to focus on deceased-donor transplantation rates alone when comparing transplantation rates between consent systems, we focus on robustness checks of the results presented in Patients who are too sick to receive an organ may be taken off the waiting list . If thiTable J in the t by taking the number of organ patients registered on the waiting list on December 31 in yeart-1, and adding to this the number of patients who entered the waiting list throughout the current yeart. These data are obtained from the Newsletters Transplant.By construction, there are fewer patients who can die while on the waiting list when waiting lists are shorter. Therefore, if waiting lists are generally longer (shorter) in opt-out systems, our estimated opt-out effects on organ-patient mortality rates will be biased. We measure waiting list length in yearOn average, the number of patients who receive a kidney transplant from either a living or deceased donor is equal to 29.2% of the number of patients registered on a kidney waiting list  co-morbid conditions than in others, and that this may systematically differ between consent systems.This method works best if organ patients have a similar probability of dying from other factors than organ failure as their fellow countrymen. If organ patients have an increased probability of developing co-morbid conditions, controlling for general mortality rates might not be sufficient. It is important to keep in mind that this can only change our conclusions if the probability of having  co-morbid conditions is different between countries with opt-out and opt-in systems. The main reasons why one consent system would systematically have more kidney patients who die from co-morbid conditions than the other are (1) longer waiting time, e.g. due to smaller transplantation rates or more inefficient systems , and (2) unhealthier kidney patients are allowed to enter or remain on the waiting list, thereby increasing their probability to have or develop co-morbid conditions that ultimately become fatal. We do not have data to investigate these points, so we need to leave this point for future research.Both the data on deceased-donor and living transplantations and on organ-patient mortality are heavily right-skewed with many zero values. This may pose two problems in the data. First, although we already set all country-organ observations to missing when only zeros and missing values are reported for that organ across years, it is possible that not all remaining zeros are “true zeros.” Some countries might, for instance, have reported a zero when there were no (reliable) data in a specific year. That means that there might be different mechanisms driving the increase from zero to one transplantation or death on the waiting list, than those driving the increase from one to two or infinity. We therefore run the same analyses as in Second, because the data are censored at zero with many zero values, a Tobit regression might better fit our data than OLS. However, Table M in the We also analyze whether the non-significant relationship between consent systems and organ-patient mortality rates is due to the potentially large heterogeneity in organ-patient mortality among countries that have the same consent system. To decrease heterogeneity within consent systems, we run the same analyses as in th percentile leads to the same results  among heart patients are indeed as low in countries with opt-out systems as could be expected based on the higher deceased-donor transplantation rates in these countries. For lungs, deceased-donor transplantation rates do not differ significantly between consent systems, and this is reflected in the mortality rates that are also not significantly different from each other. However, the difference between consent systems with respect to kidney- and liver-patient mortality rates is significantly different from the difference in deceased-donor transplantation rates. While deceased-donor kidney and liver transplantations are significantly higher in opt-out systems compared to opt-in systems, the number of patients (per million population) who died while on the waiting list for one of these organs is similar between consent systems. For kidneys, an explanation for this surprising result is that opt-out consent systems create fewer incentives to become living donors. Transplantations from living donors do not explain the findings for livers. These results are robust for various specifications.Our results indicate that focusing on the deceased-donor transplantation rates alone paints an incomplete picture of the benefits of opt-out systems compared to opt-in systems. For kidneys and livers, consent systems for organ donation apparently do not affect organ-patient mortality rates through deceased-donor transplantation rates alone; there are other factors related to consent systems that affect the number of deaths for people on the kidney and liver waiting lists. We find that the number of living transplantations can explain the findings regarding kidneys, but not for livers. Waiting list removals and the length of the waiting lists appear to be unlikely mechanisms.Moreover, it is worth noting that the number of kidney patients who died while on the waiting list is similar between consent systems, even though kidney transplantations from living donors are lower in opt-out systems compared to opt-in systems. Previous research shows that graft and patient survival rates are higher among those who received a kidney from a living donor than among those who received one from a deceased donor . This inMore research is needed to identify determinants of organ-patient mortality rates. One potentially important topic for future research concerns the fact that countries with large organ shortages also have an incentive to participate in legal organ trade within a so-called “transplant network.” Examples are Eurotransplant or Scandiatransplant, where organs that cannot be allocated within the donor’s country because there is no matching recipient are allocated to a matching recipient from another country within the network. If countries with opt-in systems could acquire more organs (and particularly more kidneys and livers) through such networks than countries with opt-out systems, it might explain why the difference in kidney- and liver-patient mortality rates is so small between consent systems. Unfortunately, we cannot empirically test whether this hypothesis holds, because (1) almost every country in our data participates in a transplant network, either formally or through bilateral agreements, and (2) we do not have data on countries of origin of organ donors or recipients. A second potentially important topic for future research concerns investments in medical technology to decrease organ-patient mortality. The smaller supply of donor organs in countries with opt-in systems provides an incentive for these countries’ governments and researchers to invest in research and technology to increase organ-patients’ longevity or search for alternative sources of organs such as xenotransplants  or synthetic organs. If successful (for kidneys and livers), these investments would, in turn, decrease organ-patient mortality rates in opt-in systems, which would explain the surprisingly small differences between consent systems with respect to kidney- and liver-patient mortality rates. Although we do control for countries’ overall health expenditures, we unfortunately do not have data on the size of the investments in these specific medical technologies that may decrease organ-patient mortality nor on the share of the overall health expenditures that are allocated to them. It is therefore not possible to provide empirical evidence for the hypothesis that differences between consent systems with respect to the incentives for investing in organ-patient mortality-decreasing medical technology may explain our findings.The main implication of our analyses is that it is not evident that opt-out consent systems reduce kidney and liver-patient mortality rates. For kidneys and livers—by far the most commonly transplanted organs—the higher deceased-donor transplantation rates in opt-out systems give a false impression that presumed consent is related to lower organ-patient mortality rates.S1 File(DOCX)Click here for additional data file.


Dear Editor,The mechanisms leading to the appearance of acute myeloid leukemia (AML) in the donor cells after allogeneic hematopoietic stem cell transplantation  are barely understood , 2. ThisKMT2A [MLL] gene) following myelodysplastic syndrome (MDS) was referred to our center for induction therapy and alloHSCT in 2010. After standard “7+3” induction chemotherapy with cytarabine and daunorubicin, the patient received conditioning with fludarabine, busulfane, and anti-thymocyte globuline (ATG) and proceeded to alloHSCT using bone marrow from a male HLA-mismatched unrelated donor. Cyclosporine and methotrexate were used as immunosuppression.A 56-year-old male patient with secondary AML , the patient received a CD34-selected peripheral blood stem cell graft. Neutrophil engraftment appeared on day +17 followed by platelet engraftment on day +50.The post-transplant period was unspectacular showing stable hematopoiesis, donor-chimerism > 99 % in granulocytes, and between 12 and 75% in T cells and no detectable cells from the first donor.+ cells showed also a complete donor chimerism. Moreover, FACS analysis revealed a new blastic phenotype and coinciding with this cytogenetic and molecular analysis documented novel aberrations including trisomy 8, trisomy 11, and KMT2A-PTD, not present at primary diagnosis of the leukemia. Chromosome banding analysis and FISH revealed the blasts to be of female origin  estimated a frequency of 80.5 DCLs per 100,000 alloHSCTs . Since pKMT2A-PTD could be detected which had not been present at primary diagnosis of AML. A previous case of DCL involving KMT2A gene translocation has been reported after umbilical cord blood transplantation [In the current case, detection of donor’s gender in leukemic blasts left no doubt as the haplo-donor was the only female donor used . In otheantation .KMT2A-PTD, no FLT3-ITD, no FLT3-TKD, and no mutations of ASXL1, CBL, CEBPA, IDH1R132, IDH2, KIT, KRAS, NPM1, NRAS, RUNX1, TET2, TP53, and WT1. Next-generation sequencing was not performed at that time. However, the absence of KMT2A-PTD made pre-existing occult leukemia in the donor cells unlikely. In the current case, the lack of lymphocytes in the CD34-selected haploidentical stem cell allograft may have indeed hampered the immune surveillance of rising genetic instability. Nowadays, CD34-selected haploidentical stem cell sources which are more likely to be followed by adoptive transfer of selected or manipulated lymphocytes or T-replete procedures such us post-transplant cyclophosphamide are applied [The exact underlying mechanisms leading to DCL development remain unclear. Clonal hematopoiesis has been reported in several cases, especially from older and mostly related donors . Genetic applied .Taken together, it appears to remain important to inform the readership continuously about the barely understood phenomenon of DCL development alerting everybody to consider the rare in situations when relapse is present in context of full donor chimerism.


Mycobacterium tuberculosis infection remains unclear. This is because studies related to the role of GM-CSF so far have been carried out in murine models of experimental TB, which is inherently susceptible to TB as compared to humans, who exhibit a resolution of infection in majority of cases. We found a significantly higher amount of GM-CSF production by human macrophages, compared to mouse macrophages, after infection with M. tuberculosis in vitro. The higher levels of GM-CSF produced by human macrophages were also directly correlated with their increased life span and ability to control M. tuberculosis infection. Other evidence from recent studies also support that M. tuberculosis infected human macrophages display heterogeneity in their antibacterial capacity, and cells with increased expression of genes involved in GM-CSF signaling pathway can control intracellular M. tuberculosis growth more efficiently. Collectively, these emerging evidence indicate that GM-CSF produced by lung resident macrophages could be vital for the host resistance against M. tuberculosis infection in humans. Identification of GM-CSF dependent key cellular pathways/processes that mediate intracellular host defense can lay the groundwork for the development of novel host directed therapies against TB as well as other intracellular infections.Although classically associated with myelopoiesis, granulocyte-macrophage colony-stimulating factor (GM-CSF) is being increasingly recognized for its potential role in innate resistance against tuberculosis (TB). While the GM-CSF is produced by a variety of host cells, including conventional and non-conventional T cells, macrophages, alveolar epithelial cells, the cell population that promotes GM-CSF mediated innate protection against  However, many population-based immunological and genetic studies support the belief that innate immunity is equally important in TB immunopathogenesis (Mycobacterium tuberculosis (MTB)  is primarily mediated by T cells, with CD4ogenesis –3. Macrois (MTB) . Currentis (MTB) –8. The id others , 10. Howd others . A recend others . While MMurine macrophages are also known to produce GM-CSF in the lung compartment during MTB infection . HoweverWe thus examined the level of GM-CSF produced by mouse MDMs (monocyte-derived macrophages) compared to human MDMs before and after infection with MTB . While iInterestingly, the viability decreased significantly, while the bacterial burden increased, with time in mouse MDMs . In contin vitro and examined their viability before and after MTB infection. As expected, the addition of GM-CSF to mouse MDMs significantly increased the longevity of both uninfected and MTB-infected mouse MDMs  upon overlay to infected human MDMs, indicating a role for GM-CSF in improving antigen processing and presentation . The GM-an cells . Remarkaan cells .These results indicate that GM-CSF helped macrophage control MTB by decreasing bacterial load, while also preventing host cell death. These findings on human vs. murine monocyte-derived macrophages also indicate that the ability of macrophages to contain MTB infection could be due to the dual role of GM-CSF in prolonging the host cell survival as well as stimulating intracellular anti-MTB effector functions. Though not studied during MTB infection, GM-CSF has been known to modulate the developmental as well as effector functions of different lung macrophage populations . GM-CSF in vivo . Ma. Main viin vivo  16). Di. Diin viin vivo  17–19).–19.in viin vivo  26). We. Wein viin vivo . It is trophages  11, 22), 22in virophages , 28, therophages –31. It iAll datasets generated for this study are included in the article/The studies involving human participants were reviewed and approved by UTHSC-Houston IRB. Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements.AK designed the study. AM and VS led the project, conducted the experiments and analyzed the data. AK wrote the manuscript. SS edited the manuscript. CJ, JA, and RH provided the feedback on the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Pythium insidiosum. The pathogen inhabits ubiquitously in a wet environment, and direct exposure to the pathogen initiates the infection. Most patients with pythiosis require surgical removal of the affected organ, and many patients die from the disease. Awareness of pythiosis among healthcare personnel is increasing. In this review, we summarized and updated information on the diagnosis and treatment of human pythiosis. Vascular and ocular pythiosis are common clinical manifestations. Recognition of the typical clinical features of pythiosis is essential for early diagnosis. The definitive diagnosis of the disease requires laboratory testing, such as microbiological, serological, molecular, and proteomic assays. In vascular pythiosis, surgical intervention to achieve the organism-free margin of the affected tissue, in combination with the use of antifungal drugs and P. insidiosum immunotherapy, remains the recommended treatment. Ocular pythiosis is a serious condition and earliest therapeutic penetrating keratoplasty with wide surgical margin is the mainstay treatment. Thorough clinical assessment is essential in all patients to evaluate the treatment response and detect an early sign of the disease recurrence. In conclusion, early diagnosis and proper management are the keys to an optimal outcome of the patients with pythiosis.Human pythiosis is an infectious condition with high morbidity and mortality. The causative agent is the oomycete microorganism  Pythium insidiosum, is a member of the unique group of aquatic fungus-like microorganisms, called oomycetes . Based on the keywords, ‘pythiosis’ and ‘Pythium insidiosum’ articles extracted were summarized to identify clinical information that was relevant to diagnosis and management of human pythiosis and grouped into sections  and key notes . Our team, as healthcare professions in the fields of infectious diseases, ophthalmology, and pathology, performed a literature search using the PubMed database  and the eye   . Unusualthiosis) .P. insidiosum attaches and germinates to invade arteries and surrounding tissue. Typical patients have an underlying hematological disorder and an agriculture-related occupation. Most patients present with chronic non-healing skin lesions, arterial insufficiency syndrome , gangrenous ulcer, and pulsatile mass   . Skin chneurysm) . There aneurysm) , and devP. insidiosum infection. Specimen handling is a critical step to enhance the success rate of the laboratory investigation. Specimens such as blood clot, pus, and vessel tissue , should be sent, without formalin preservation, to a clinical microbiology laboratory for culture identification, staining, and/or molecular testing. Resected vessel and soft tissue specimen sent for histological examination should be labelled—proximal or distal—in order to identify the disease-free surgical margin by Grocott-Gömöri methenamine silver (GMS) staining  is essential for the identification of the staining . Furtherpathogen .Pythium keratitis) usually have a history of predisposing factors (see the “Predisposing factors” section), and present with ocular pain, irritation, photophobia, decreased visual acuity, conjunctival redness, and eyelid swelling, similar to another microbial keratitis. Clinical onset of ocular pythiosis could range from two days to over a month. Pythium keratitis is often clinically indistinguishable from fungal keratitis, because the causative agents share some clinical features  and microscopic findings . However, the natural history and clinical clues at the margin or surrounding areas of the main infiltrates would help to differentiate Pythium keratitis from fungal keratitis.Patients with ocular pythiosis , and DNA sequencing; see the “Laboratory diagnosis” section) to establish a definitive diagnosis. An ocular specimen is usually obtained in a minimal amount, which could lead to a false-negative result by such laboratory tests. Serological tests are not useful because the serum anti-tectable . Repeatetectable .In vivo confocal microscopy (IVCM) is an emerging, non-invasive, real-time imaging technique that enables morphological and quantitative analysis of ocular surface microstructure in both health and disease. Clinically, IVCM is a useful diagnostic tool for the early diagnosis of microbial particularly fungal and Acanthamoeba keratitis , septate linear branching structures resembling fungal filaments, and irregular filaments arranged in a sinuous, various branching pattern, forming “X”,” Y”, and” S” shapes as seen by IVCM   . If leftlulitis) . Cranioflulitis) . Rarely,ortality , which iortality .P. insidiosum zoospore, peripheral blood mononuclear cells collected from thalassemic patients showed lower level of granulocyte-macrophage colony-stimulating factor (GM-CSF) and interferon gamma (IFN-γ) production, compared with the non-thalassemic controls , which resulted in poor clinical outcomes   .P. insidiosum inhabits stagnant water and soil, and colonizes aquatic vegetation .Clinical specimens  obtained from a lesion are subjected to direct wet mount examination, using 10% KOH preparation . AlthougP. insidiosum. Temperature control is essential to ensure viability, and failure to isolate P. insidiosum is linked to storage of clinical specimen in low-temperature containers, such as icebox, refrigerator, or freezer , with a radial growth rate of ∼5 mm/day  hyphae  hyphae . Zoosporlsewhere . Althougpathogen . Of lateic assay .P. insidiosum antibody can facilitate the diagnosis of pythiosis. Several methods have been developed to detect serum P. insidiosum-specific antibodies. Two types of crude proteins, (i) culture filtrate antigen (CFA) and (ii) soluble antigen from broken hyphae (SABH)  is a simple, cost-effective, and specific assay that is designed to observe in-gel immunoprecipitation lines generated by anti-P. insidiosum antibodies in patient serum and the P. insidiosum crude protein extract (P. insidiosum (P. insidiosum antibodies within 30–60 min (Detection of anti-e (SABH) , extract extract . Major d extract . An enzy extract . Westernsidiosum  has been0–60 min . HoweverP. insidiosum antibodies in patients with ocular pythiosis  and ICT  outperform ID  and HA  . Evaluatythiosis . TherefoP . insidiosum antibodies can be monitored using one of the serological tests. A gradual decrease in anti-P. insidiosum antibody levels over the course of months, in association with clinical improvement, indicate favorable prognosis (P. insidiosum immunotherapeutic antigen (PIA) vaccine, prepared from crude protein extracts of the pathogen, in clinically-cured pythiosis patients . Hematoxylin and eosin (H&E) staining shows tissue reactions, such as infiltration of eosinophils, purulent granuloma, and giant cells at the P. insidiosum infection site  demonstrate the presence and extent of  tissues . Howeverion site .P. insidiosum , mouse or bovine anti-rabbit IgG (secondary antibody) tagged with peroxidase, and enzymatic substrates. These immunostaining assays require careful examination under a light microscope to confirm the presence of P. insidiosum in infected tissues. Interpretation of results may be complicated by false-positive staining of other fungi, such as Conidiobolus and Fusarium species , several immunohistological staining assays have been developed to facilitate microscopic detection of sidiosum . These aocyanate . Brown e species . Thus, che tests .P. insidiosum . The rDNA contains 18S ribosomal RNA, internal transcribed spacer 1, 5.8S ribosomal RNA, internal transcribed spacer 2, and 28S ribosomal RNA  was used in a simplified one round-PCR reaction  of P. insidiosum as an alternative PCR target, and designed exo 1-specific primers, Dx3 and Dx4, for a conventional PCR assay. Based on a head-to-head comparison for PCR-based detection of 35 Thai P. insidiosum strains, the primers, Dx3 and Dx4, showed higher detection sensitivity than with ITSpy1 and ITSpy2 (100% vs. 91%)  . Besidessidiosum . The detsidiosum , but shoP. insidiosum MSPs aiding the identification of P. insidiosum (P. insidiosum if the MSP generated significantly matched its corresponding mass spectrum deposited in the reference database.Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) is a powerful diagnostic tool  that cansidiosum . The micP. insidiosum is usually resistant to both systemic and traditional topical antifungal agents. Since aggressive medical treatment often fails to cure the infection, prompt surgical intervention is the key treatment to control the disease. Potential therapeutic options for patients with vascular and ocular pythiosis are presented below:The treatment of pythiosis can be categorized into surgical intervention, medications , and immunotherapy. Based on the experiences of our center and that of other groups, Urgent preoperative assessment determined by computerized tomography angiogram (CTA) of affected vessel  up to the proximal origin of vessels  is recommended. Abnormal radiography showing thickening of the vessel wall with enhancement, thrombosis, and aneurysmal dilation may indicate arteritis . The CTAPrompt radical surgery leading to amputation to achieve pathogen-free surgical margin is the mainstay of successful treatment of vascular pythiosis . The sugP. insidiosum as they do not target enzymes in the ergosterol biosynthetic pathway  data revealed amphotericin B had the highest MIC, followed in order by voriconazole, fluconazole, anidulafungin, caspofungin, itraconazole, and terbinafine  in vitro including azithromycin, tigecycline, clarithromycin, linezolid, nitrofurantoin, chloramphenicol, quinupristin/dalfopristin, clindamycin, josamycin, miltefosine, sutezolid, retapamulin, tiamulin, and valnemulin  has been used to successfully treat localized skin/subcutaneous disease . Severallnemulin . Azithroythiosis . In a reythiosis . Both paythiosis .In vitrc effect .P. insidiosum possesses the gene encoding ferrochelatase, which indicates role of iron in the pathogenesis  represent residual disease that necessitates investigation and aggressive management . NeutropP. insidiosum-specific antibody are potential biomarkers of vascular pythiosis after treatment initiation  (As mentioned earlier (see vascular pythiosis section), inafine) .Pythium keratitis, recent advances in therapeutics are encouraging. Several studies showed in vitro susceptibility of various strains of P. insidiosum to antibacterial agents that inhibit protein synthesis including tigecycline, macrolides, tetracyclines, and linezolid, either as monotherapy or as adjunct therapy to antifungal agents   . Disease tissue) . Delay i tissue) . A recenl margin . Patientl margin . There al margin . Recentll margin . OverallPythium keratitis demonstrated that the rate of recurrence after penetrating keratoplasty was 55% and the evisceration rate was reduced to 15% of the cases  remains uncertain, early therapeutic penetrating keratoplasty with clear surgical margins is the gold standard for achieving global salvage. To prevent recurrence after eye surgery, adjunct strategies including perioperative cryotherapy and absolute alcohol application may be beneficial.Human pythiosis is a life-threatening condition with high morbidity and mortality. Vascular and ocular pythiosis are common clinical manifestations. Early diagnosis and timely intervention are the keys to an optimal outcome. Although diligent records of patient medical history and physical examination provide diagnostic clues on “pythiosis”, definitive disease diagnosis requires laboratory testing. In addition to traditional microbiological methods, diagnostic assays  have been developed to aid diagnosis of pythiosis. Selection of the diagnostic tests relies on assay availability, detection efficiency, and experience of laboratory personnel. Regarding the management of vascular pythiosis, surgical intervention that achieves a


The hypothesis of our study is that donor/recipient HLA mismatches assessed at the molecular level may also influence a higher susceptibility to the development of posttransplant primary T-cell alloimmunity. In this prospective observational study, 169 consecutive kidney transplant recipients without preformed donor-specific antibodies (DSA) and with high resolution donor/recipient HLA typing were evaluated for HLA molecular mismatch scores using different informatic algorithms . Primary donor-specific alloimmune activation over the first 2 years posttransplantation was assessed by means of both dnDSA and dnDST using single antigen bead (SAB) and IFN-γ ELISPOT assays, respectively. Also, the predominant alloantigen presenting pathway priming DST alloimmunity and the contribution of main alloreactive T-cell subsets were further characterized in vitro. Pretransplantation, 78/169 (46%) were DST+ whereas 91/169 (54%) DST−. At 2 years, 54/169 (32%) patients showed detectable DST responses: 23/54 (42%) dnDST and 31/54 (57%) persistently positive (persistDST+). 24/169 (14%) patients developed dnDSA. A strong correlation was observed between the three distinct molecular mismatch scores and they all accurately predicted dnDSA formation, in particular at the DQ locus. Likewise, HLA molecular incompatibility predicted the advent of dnDST, especially when assessed by PIRCHE-II score . While pretransplant DST predicted the development of posttransplant BPAR  and particularly T cell mediated rejection , patients developing dnDST were at significantly higher risk of subsequent dnDSA formation . In vitro experiments showed that unlike preformed DST that is predominantly primed by CD8+ direct pathway T cells, posttransplant DST may also be activated by the indirect pathway of alloantigen presentation, and predominantly driven by CD4+ alloreactive T cells in an important proportion of patients. De novo donor-specific cellular alloreactivity seems to precede subsequent humoral alloimmune activation and is influenced by a poor donor/recipient HLA molecular matching.Donor/recipient molecular human leukocyte antigen (HLA) mismatch predicts primary B-cell alloimmune activation, yet the impact on  Thisns (HLA) .in vitro and since this process is ongoing, newer versions of the calculator are periodically released including the last updates on the eplets’ repertoire. An increasing number of eplet MM has been shown to identify kidney transplant recipients at higher risk of developing dnDSA, antibody-mediated rejection (ABMR) and worse allograft survival  after kidney transplantation and its association with donor/recipient HLA molecular matching. Hence, we here investigated the association of distinct donor/recipient HLA molecular mismatch algorithms with the risk of dnDST activation as well as its influence on subsequent dnDSA formation. While there are no readily available tests to monitor the presence of donor-specific T-cell responses in the clinical setting, we used one of the most sensitive immune assays tracking circulating frequencies of donor-reactive memory/effector T cells, the IFN-γ Enzyme-Linked ImmunoSpot (ELISPOT), which has been validated between different research consortiums  and class-II  antigens with NGS technology. Exons 2, 3, 4 for class I and exons 2 and 3 for class II were amplified by multiplex PCR. NGS was performed on a MiSeq platform . DRB3/4/and DPA1 could not be assessed in all donor/recipient pairs because of insufficient biological material, thus HLA mismatch scores were performed at A, B, C, DRB1, DQB1 and DPB1 loci. Notably, since all recipients could be typed for DQA1, we evaluated PIRCHE score also taking into account the alloantigen presentation by recipients’ DQ(B1/A1)+DRB1 molecules.http://www.HLA-EMMA.com.The HLA epitope mismatch algorithm (HLA‐EMMA) was used to assess polymorphic amino acids on mismatched donor HLA molecules as previously described . Both tohttp://www.epitopes.net/downloads.html) was used to calculate eplet scores as previously described . All beads showing a normalized MFI>500 were considered positive if (MFI/MFI lowest bead)>5.Recipient and donor PBMCs from living donors or splenocytes from deceased donors were harvested and isolated by Ficoll density gradient centrifugation. Donor samples were depleted from T-Cells using either anti-CD3  or anti-CD2 kits , in living or deceased donors, respectively, to avoid any donor T-cell alloimmune response. All samples were frozen in liquid nitrogen at −80°C until their use.5 responder PBMC were placed in each Elispot well plate coated with primary IFN-γ antibody wells with 3x105 donor cells, in triplicates. A negative control  and a positive control  were also tested in duplicates. Incubation time was 22 h at 37°C, 5% CO2. Results were expressed as frequencies of IFN-γ producing T-cells/3x105 PBMCs, subtracting responses from negative donor and recipient control wells. As previously reported, a cut off of ≥25 spots/3x105 PBMCs was considered positive  assay as previously described . Brieflypositive , 29.in vitro, 22 donor-recipient pairs with remaining available samples  were tested in a T-cell receptor (TCR)-dependent Activation-Induced T-Cell Markers (AIM) assay as previously described , 3x105 T-cell depleted donor cells  or 50μl of phytohemagluttinin-PHA (positive control). After incubation, cells were stained with the following antibodies: CD4-FITC, CD8-APC-H7, CD134 (OX-40Antigen)-PE, CD69 (very early activation antigen)-PE-Cy7, CD137 (4-1BB)-APC, 7-AAD . Donor Cells after 22 h incubation with medium were stained with CD4-FITC, CD8-APC-H7 antibodies to test effective T-cell depletion. After 22 h incubation with T-cell depleted donor cells, we assessed by flow cytometry analysis the % of AIM+ cells defined as the % of (CD69+CD137+) cells for CD8+ T cells, and (CD134-OX40+ CD137+) for CD4+. T-cell activation results are presented by subtracting the percentage of AIM+ cells after stimulation with medium (negative control) from % of AIM+ cells after allogenic stimulation.Cells were cultured in 96-wells round bottom plates at 3x10Flow cytometry was performed on a FACS-Canto flow cytometer and analyzed using the FACS-Diva Software .in vitro, a subset of DST+ patients with available cell samples, either prior and/or after transplantation were functionally re-evaluated . For these experiments we modified the functional immune assay by evaluating in the same patient DST responses with the following conditions: 1) using total recipient PBMC as responder cells co-cultured with T-cell depleted donor stimulating cells and, 2) using recipient T-Cells only after being selectively isolated as responder cells co-cultured with donor stimulating cells. In the first assay, both directly and indirectly primed DST frequencies are detected, since recipient PBMCs include T cells (CD3+), B cells (CD19+), monocytes (CD14+) and dendritic cells (HLADR+CD14− CD3− CD19−CD56−) .In order to characterize the predominant alloantigen-presenting pathways of circulating DST 2 test for categorical variables and student t-test for normally distributed data, and non-parametric Kruskal-Wallis or Mann-Whitney U test for non-normally distributed variables. Bivariate correlation analyses were performed by Pearson or Spearman test (non-parametric variables). Univariate and multivariate logistic regression analyses were used to determine the variables associated with the risk of developing BPAR and dnDST. The time-dependent association of the variables assessed on graft survival and dnDSA development was studied with Cox proportional hazard, Kaplan–Meier plots, and log-rank test. The statistical significance level was defined as 2-tailed p<0.05. Statistical analyses were performed with IBM SPSS Statistics, version 26  and GraphPad Prism version6.0 .All continuous data are presented as mean ± SD or median and interquartile-range. Different groups were compared using XAs illustrated in As shown in Forty-six (27%) patients developed delayed graft function (DGF) and 19 (11%) biopsy-proven acute rejection (BPAR) . 24/169 (14%) patients developed dnDSA: 6 (25%) class-I only , 19 (80%) class-II only , and 1(5%) patient against both class-I and II. Five (21%) patients developed dnDSA against both donor DQ molecules, thus the majority of dnDSA were directed against DQ antigens . Mean time until first dnDSA detection was 24± 20 months (range 6–60). Mean dnDSA mean fluorescence intensity (MFI) was 8,685 .Death-censored graft loss occurred in 9 (6%) patients, being main causes BPAR , interstitial fibrosis/tubular atrophy , primary glomerulonephritis recurrence . Eleven (6%) patients died with a functioning graft because of malignancies , infections , and cardiovascular events .A detailed description of the different HLA mismatch (MM) scores of the study population is depicted in vs. 63±22, p=0.08); global PIRCHE-II  and higher eplet MM load . There was no effect of molecular MM scores on graft function progression, death-censored graft survival, and patient death (data not shown).No direct association was observed between BPAR and the HLA allelic, amino acid, and eplet MM scores , but for global PIRCHE-II score . Patients developing ABMR during follow-up showed a trend towards higher amino acid MM . We did not study the impact of the different molecular algorithms in the two solely anti-DP and anti-DR dnDSA. A positive correlation with anti DQ dnDSA MFI was observed for DQB1 amino acid MM , DQB1 eplet MM , and DQB1 PIRCHE-II score .As shown in Despite the absence of preformed DSA, 78/169 (46%) showed high frequencies of pretransplant DST (preDST+), whereas 91 (54%) did not (preDST−). No association was found between preDST+ and main clinical, demographic characteristics nor with different HLA molecular MM scores  patients showed DST responses at some timepoint (postDST+), being 23 (42%) dnDST and 31 (57%) persistently positive (persistDST+), whereas 115/169 (68%) were postDST− (68 preDST− and 47 preDST+) . When assessing the PIRCHE-II score presented by DRB1+DQ molecules, similar results were observed, being the count of DRB1 donor-derived peptides similarly associated to dnDST activation . However, the difference in global PIRCHE-II score presented by both DRB1+ DQ molecules was not statistically different . The relationship between PIRCHE-II and dnDST for different peptide affinity thresholds , revealed that PIRCHE-II was significantly associated to dnDST especially at less stringent IC50 intervals (While none of the different HLA MM scores associated with postDST+ (persistDST+ and/or dnDST+) (data not shown), a significantly higher global PIRCHE-II score was observed among dnDST+ than within postDST− patients . Kaplan-Meier dnDSA-free survival curves illustrate the cumulative dnDSA rates among different postDST groups , when stratifying postDST in either persistent or vs. 78.9±38, p=0.04). No differences were observed with any of the other HLA molecular MM algorithms at this level.In addition, transplant patients with both dnDST+ and dnDSA+ showed significantly higher PIRCHE-II global score as compared to patients with either dnDST or dnDSA or those without dnDSA nor dnDST , a weak but statistically significant inverse correlation with 12 and 24-month graft function was observed .The contribution of CD8+ and CD4+ T cells to donor-reactive T-cell responses were investigated using the TCR dependent activation-induced cell marker (AIM) assay in a subset of patients. CD4+ and CD8+ AIM+ T cells varied among different DST groups, which were detected both within preDST+ and dnDST+ patients  and indirect (IP), priming circulating donor-reactive T cells, we functionally characterized them While most circulating preDST+ responses  were driven by donor-reactive T cells primed by the DP, an important proportion of patients with postDST+ responses, either dnDST+ or persistDST+, were also primed by the IP   against donor antigens might also occur, subsequently driving anti-donor humoral immune activation.Primary humoral alloimmune activation through dnDSA production is a well-characterized deleterious factor inducing chronic ABMR and accelerated graft loss , 2 and rde novo DST, display high frequencies of donor-reactive CD4+ T cells primed by the indirect antigen presentation pathway, which contributes to their global DST response. Most interestingly, and similarly to dnDSA, our data suggest that patients at risk of dnDST seem to also show a poor donor/recipient HLA molecular matching, and in particular, at the Predicted indirectly Recognizable HLA Epitopes II (PIRCHE-II) score level, emphasize the contribution of the indirect antigen presenting pathway driving DST development. These data highlight a continuous increased risk of dnDST and dnDSA for each individual predicted peptide presented by recipient APC through indirect presentation. This is, to our knowledge, the first report showing the impact of HLA molecular incompatibility on the development of primary adaptive alloimmunity, not only at the humoral but also at the cellular level in solid organ transplantation.In our study, we first confirm that HLA matching at the molecular level using distinct algorithms outperforms allelic MM assessment predicting primary humoral alloimmunity by means of dnDSA formation. Furthermore, we report that a relevant number of kidney transplant recipients develop dnDST after transplantation, which ultimately predicts the advent of dnDSA. Notably, unlike pretransplant DST, an important proportion of posttransplant DST patients, either those with persistent or de novo T-cell activation. Although intuitively, a specific threshold would be of high relevance to help stratifying patients into high or low risk for either dnDSA or dnDST, from the biological point of view these thresholds might not represent the potential impact for alloimmune activation. Indeed, despite the strong correlation between the load of molecular MM and risk of de novo alloimmunity, even a small amount of mismatched antigens may be sufficient to activate an immune response, thus application of specific cut-offs may be misleading in clinical practice    ant the Biomarker-Driven Immunosuppression Minimization (BIO-DRIM) Consortium . Also, this work was partly supported by the SLT002/16/00183 grant, from the Department of Health of the Generalitat de Catalunya by the call “Acció instrumental de programes de recerca orientats en l’àmbit de la recerca i la innovació en salut.” The authors thank the Research Centers of Catalonia (CERCA) Programme/Generalitat de Catalunya for institutional support. OB was awarded with an intensification grant from the “Instituto de Salud Carlos III” [INT19/00051]. MM received a fellowship grant from ESOT (European Society for Organ Transplantation).MN is an employee of PIRCHE AG that runs the PIRCHE web-portal.The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.