Alzheimer’s disease is linked to amyloid β (Aβ) peptide aggregation in the brain, and a detailed understanding of the molecular mechanism of Aβ aggregation may lead to improved diagnostics and therapeutics. While previous studies have been performed in pure buffer, we approach the mechanism in vivo using cerebrospinal fluid (CSF). We investigated the aggregation mechanism of Aβ42 in human CSF through kinetic experiments at several Aβ42 monomer concentrations (0.8–10 µM). The data were subjected to global kinetic analysis and found consistent with an aggregation mechanism involving secondary nucleation of monomers on the fibril surface. A mechanism only including primary nucleation was ruled out. We find that the aggregation process is composed of the same microscopic steps in CSF as in pure buffer, but the rate constant of secondary nucleation is decreased. Most importantly, the autocatalytic amplification of aggregate number through catalysis on the fibril surface is prevalent also in CSF. in vitro. They find evidence consistent with an aggregation mechanism involving secondary nucleation of monomers on the fibril surface.Rebecca Frankel, Mattias Törnquist et al. report the aggregation mechanism of Aβ42 in human cerebrospinal fluid  The sequence of events leading to the initiation and propagation of this neurodegenerative disease is still largely unknown; however, in addition to aging and the major genetic risk gene apolipoprotein E (APOE), possible mechanisms including inflammation3, altered endosomal sorting5, and tau spreading6 are gaining increasing awareness. There is ample evidence linking the self-assembly of the amyloid β peptide (Aβ) to the disease8. According to the amyloid cascade hypothesis, Aβ self-assembly is followed by truncation, phosphorylation and aggregation of tau, and subsequent neuronal death11.Alzheimer’s disease (AD) is a devastating neurodegenerative disease, which affects a large and increasing number of individuals world-wide12 and its complete amino acid sequence in plaques was determined in 198513. Several length variants of this peptide have been found to coexist in body fluids, including cerebrospinal fluid (CSF) and blood serum17. Typical Aβ42 concentration in CSF are around 250 pM in healthy humans, with a large variation between individuals. Around 50% lower average Aβ42 concentration is measured in CSF from AD patients, which is thought to arise from sequestration of Aβ42 into plaques in the brain18. Evidence for the association between Aβ and AD largely come from the early onset of AD-type pathology in individuals with extra dosage due to chromosome 21 trisomy20, as well as from familial AD cases with mutations close to the γ secretase cleavage site of amyloid precursor protein (APP)22 and before the β secretase cleavage site at the N-terminus of Aβ23, or with Aβ variants that are more aggregation-prone or follow an altered aggregation pathway27.Aβ was discovered in 198429, whereas smaller aggregates—oligomers—formed during the process seem to be responsible for the emergence of neurotoxicity30. Oligomers are transient species and a range of definitions has been used in the literature, including aggregates with lower growth rate than fibrils, aggregates in a discrete size range, or aggregates that are toxic, as reviewed31. One route towards future diagnostics and treatment of AD involves finding the mechanism of Aβ aggregation in terms of the microscopic steps in the process32 and the molecular driving forces of each step33. Such knowledge can be used to search for inhibitors of particular steps, most importantly those steps leading to toxicity35.Self-assembly of Aβ leads to the formation of elongated fibrillar aggregates of highly ordered structure32. The result is a double nucleation mechanism compatible with the aggregation of Aβ4232, Aβ4036 as well as several point mutations27 and variants with N-terminal extensions37. Primary nucleation in solution is accompanied with a very high energy barrier compared to elongation of existing aggregates38. Once fibrillar aggregates have formed, these present a catalytic surface for secondary nucleation of monomers. This secondary nucleation process is associated with a much lower energy barrier than primary nucleation38 and leads to an autocatalytic process with rapid multiplication of the number of aggregates. Although secondary nucleation of Aβ monomers on fibril surface was not discovered until 2013, this type of process, leading to autocatalytic amplification of aggregate mass, has been known in crystallization and other self-assembly processes for more than a century, as reviewed42.Recent investigations of highly purified peptide in buffer have revealed a mechanism that is compatible both with a large set of aggregation kinetics data at multiple peptide concentrations and with experiments using isotope-enrichment to decipher the origin of oligomeric species43 and pH26. In a top-down approach, as in the current work, Aβ aggregation is studied in a full body fluid. This approach is the fastest route towards the aggregation mechanism in a complex environment, but does not provide a clear understanding of the connection between effects and effectors due to multiple simultaneous effects.Aβ aggregation in vivo occurs in complex fluids containing many thousands types of proteins in addition to phospholipids, metabolites, salts, and other components. At least two approaches are possible to understand any changes in the mechanism compared to the pure buffer system. In a bottom-up approach, components from relevant fluids are added one at a time and the effect on the Aβ aggregation mechanism is quantified to find the effects on each of the underlying microscopic steps. This approach is the fastest route towards a detailed physico-chemical understanding of the effects from each component and was recently used to understand the effects of ionic strength44. We also use cryo-EM to confirm that the end stage consists of fibrils very similar to those seen in pure buffer systems. The kinetic data generated by the ThT assay remains reproducible and amenable to kinetic analysis over a wide span of CSF concentrations. Pure monomer, or pure monomer supplemented with pre-formed seeds, was combined with CSF at multiple peptide concentrations and a model was globally fitted to the data as a function of concentration and time45 to find the minimal mechanism compatible with all data. Our conclusion is that although CSF has a generally retarding effect on Aβ aggregation, the same mechanism, including a double step secondary nucleation process, remains dominant in the presence of CSF.In this study, we investigate the aggregation of Aβ42 in the presence of CSF using the amyloid-binding dye thioflavin T (ThT), which, when used in a fluorescence assay, produces remarkably reproducible data over a range of peptide concentrations in a pure buffer systemThe pipetting robot used for all dilution series in this work was validated by dispensing different concentrations of a fluorescent dye solution and measuring the resulting fluorescent signals. The same concentration was dispensed four times within each experiment and three separate experiments were made. The results show a high degree of linearity between expected concentration and fluorescence intensity and high reproducibility both within and between the independent experiments . Four separately mixed replicates of each solution were placed in separate wells of a 96-well plate  and the ThT fluorescence measured through the bottom of the plate. The whole experiment was repeated twice. The aggregation curves from one experiment are shown in Fig. t1/2, was extracted from each curve and plotted versus Aβ42 concentration in Fig. γ is the scaling exponent, c the Aβ42 concentration, and α a proportionality constant. We obtain an overall average of γ = −0.3 for the two experiments shown in Fig. γ = −0.8 was recently found in phosphate buffer at similar ionic strength and pH .Since CSF contains ca. 140 mM NaCl and 1 mM CaCl2, pH 8.0. Each experiment was repeated twice with three replicates of each solution per repeat. Examples of data with 3 µM Aβ42 are shown in Fig. Next, the overall effect of CSF on Aβ42 aggregation kinetics was investigated at constant Aβ42 concentration as a function of CSF concentration. As several pools of CSF were used, all datasets with CSF have been marked with a hexagonal symbol representing the pool used in the experiment, where L is a pool from Lund and G is a pool from Gothenburg. Solutions of freshly isolated monomeric recombinant Aβ42 were complemented with buffer, salts, ThT, and CSF to obtain a series of samples with varying CSF concentration (0–80%) at constant Aβ42 concentration 3 or 5 µM), and constant concentration of all other components: 10 µM ThT, 20 mM HEPES/NaOH, 140 mM NaCl, 1 mM CaCl or 5 µM,t1/2 value was extracted from each curve for 3 µM Aβ42 in Fig. t1/2 versus CSF concentration follows a hyperbolic trend, suggesting that the retarding effect is due to one or more components in CSF interacting with some Aβ42 species along the aggregation pathway. This CSF concentration-dependent retardation was found for two other pools of CSF, one yielding a similar hyperbolic trend , one concentration where ca. 80% of the maximum effect is observed (32%), and one concentration close to full effect (66%).This was used to guide the choice of CSF concentrations for a further detailed mechanistic study, to represent one concentration where half maximal effect on The maximum ThT fluorescence intensity between initial baseline and final plateau was evaluated at 3 and 5 µM Aβ42 and shows a small and non-systematic dependence on the CSF concentration  at constant concentration of CSF , two different pools of CSF were used in a comparative fashion. The pools, originating from two different clinics, were characterized in terms of total protein concentration, ionic strength, and pH  than for Aβ42 in the HEPES buffer with physiological salt, but similar to phosphate buffer at the same ionic strength33 and higher (less negative) than the value found at moderate ionic strength 33.The half-time, ion Fig. , and a p45 to find the minimal model that can reproduce all data. As shown in the Fig. To further study the aggregation mechanism of Aβ42—specifically, whether the double nucleation mechanism discovered in pure buffer Fig.  exists a2, pH 8.0. The low dependence on monomer concentration indicates that the reaction order of the secondary process is very low. We therefore chose a model which includes primary nucleation, elongation, and a secondary nucleation process that is explicitly treated as a multi-step mechanism and can thus saturate and lose its monomer concentration-dependence at high monomer concentrations36. This model was then used to successfully fit all other CSF concentrations as well; the parameters extracted from this model can be found in Supplementary Table First, we analyzed the aggregation kinetics data as a function of Aβ42 monomer concentration in 20 mM HEPES/NaOH, 140 mM NaCl, 1 mM CaCl33. In 32% and 66% CSF the data again display a low monomer dependence as for the buffer case. The fits reflect this; the saturation concentration for secondary nucleation lies well below any of the sampled concentrations, meaning this process is saturated at all concentrations studied. For all three CSF concentrations, the model including primary nucleation, elongation, and fragmentation also gave improved fits compared to models including only primary nucleation and elongation; however, when investigating the mean residual error (MRE) as calculated by Amylofit, we found that a model including fragmentation instead of multi-step secondary nucleation had a higher MRE for all CSF concentrations, namely 165% increase for 15% CSF over 24,188 data points; 3.2% increase for 32% CSF over 36,988 data points; and 6.7% increase for 66% CSF over 36,096 data points  leads to a considerable shortening of the lag phase, as shown also in the t1/2-plots. Even at the highest seed concentration the aggregation does not start immediately creating an apparent lag phase, which may be partly due to the time it takes for the solution to reach 37 °C.To further verify the presence of a secondary pathway, the effect of preformed fibrils on aggregation time was investigated Fig. . Seed fiWe attempted to make fits to the seeded data using models and rate constants that were consistent with the results from the unseeded experiments . The cryo-EM images clearly show that fibrils are formed in samples containing 15% or 66% CSF, with a morphology resembling those formed in buffer at similar ionic strength33. Curiously, in several fields of the images, small particles seem to be associated with the surface of the fibrils and these features are more prevalent in images taken at the higher concentration of CSF. This is interesting in light of the identification of HDL-like components in the retarding fraction of size-separated CSF49. However, the cryo-EM images alone do not allow for identification of the bound species and further investigation would be required.Aβ42 forms fibrils in CSF. Although the presence of CSF certainly delays fibril formationnet effect of all these components and a variation in the composition of the CSF may modulate this net effect. Five CSF pools from healthy donors collected at two different clinics were used in the current study. The data in Figs. t1/2 versus Aβ42 concentrations superimpose closely , good global fits to the data could be achieved by a double nucleation model including primary nucleation of monomers in solution and multi-step secondary nucleation of monomers on fibril surface  with the main difference being that both primary and secondary nucleation seemed to follow a reaction order of two in the latter case. The effects of adding premade fibrils to the reaction mixture, i.e. shortening of the lag phase in a manner that can only be explained by the presence of secondary processes, further supporting this.The autocatalytic nature of the process, including a double nucleation mechanism originally found in pure buffer, is prevalent in CSF. In HEPES buffer with physiological salt  to a concentration of 2 µM in 50 mM bicine–HCl, pH 9.0. Buffer B consisted of pure 50 mM bicine–HCl, pH 9.0. The pipetting robot was used to dispense 24 different combinations of the two buffers, ranging from 100 µL A + 0 µL B to 0 µL A + 100 µL B into separate wells in a 96-well plate. Each set contained four replicates of every concentration and three independent sets were made. The fluorescence intensities of the resulting dye solutions were recorded at 510 nm with an excitation light at 450 nm in a CLARIOstar plate reader (BMG Labtech).2, pH 8.0. The CSF pool was prepared from de-identified left-over aliquots from clinical routine analyses, following a procedure approved by the Ethics Committee at University of Gothenburg (EPN 140811).De-identified pooled CSF from healthy donors was used in all experiments. Five different pools were used: one from the Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Gothenburg, and four from Lund University Hospital. Each pool was frozen at −80 °C as multiple identical 1 mL aliquots. Upon thawing, the CSF sample was supplemented with 20 mM HEPES from a 30× concentrated stock to adjust pH to 8.0. Assuming literature values of salt concentrations, the CSF stock was then assumed to contain 97% CSF, 20 mM HEPES/NaOH, 140 mM NaCl, 1 mM CaCl53, with human IgG as standard.A comparison between one pool of CSF from the Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital and one pool from Lund University Hospital was made, in terms of pH, conductivity (ionic strength), and overall protein content. The pH was measured using a Mettler Toledo MP225 pH-meter; the conductivity was measured using a CONSORT C830 pH/mV/Conductivity/°C-meter; finally, the total protein content was determined using the Bradford assayE. coli optimized codons for Aβ(M1-42) was produced by PCR from overlapping oligonucleotides and cloned into PetSac, a derivative of Pet3a plasmid54. The peptides were expressed in E. coli strain BL21 DE3 PLyS star (Invitrogen) in LB medium with 50 mg L−1 ampicillin and 30 mg L−1 chloramphenicol. Well-isolated small colonies from bacteria freshly transformed with vector were used to inoculate 50 mL overnight cultures grown in 250 mL baffled flasks at 37 °C with 125 rpm shaking. These were diluted 1:100 into 500 mL day cultures grown in 2500 mL baffled flasks at 37 °C with 125 rpm shaking. 0.4 mM IPTG was added at OD 0.6–1.0 and the cells were harvested after another 3.5–4 h by centrifugation for 10 min at 6000 × g.A synthetic gene with g for 10 min. Two more rounds of sonication and centrifugation were performed. The inclusion bodies were dissolved in 40 mL 8 M urea in buffer A, and diluted four-fold in buffer A. 20 mL DEAE cellulose  was added and the slurry was left on ice for 30 min (with stirring now and then using a glass rod). The solution was removed and the resin was washed with buffer A in a Büchner funnel on a vacuum flask, followed by two washes with 30 mL buffer A with 25 mM NaCl and elution in buffer A with 50 mM NaCl, 6× 30 mL or 125 mM NaCl 3× 30 mL. The ion-exchange purification was performed in batch mode to avoid concentration of the peptide on the resin. The eluted fractions were examined using agarose gel electrophoresis and SDS–PAGE. Fractions containing Aβ42 were pooled, lyophylized, dissolved in 6 M GuHCL and again purified by SEC on a 2.6 × 60 cm Superdex 75 column in 20 mM NaP, 0.2 mM EDTA, pH 8.5. The eluted fractions were examined using UV absorbance and SDS–PAGE. Pure fractions were pooled, aliquoted, lyophylized, and stored at −20 °C.Cell pellet from 2 L culture was sonicated in 40 mL 10 mM Tris/HCl, 1 mM EDTA, pH 8.5 (buffer A) using a sonicator tip . This step was performed in a glass beaker surrounded by an ice–water slurry. Inclusion bodies were isolated by centrifugation at 4 °C, 15,000 × All chemicals were of analytical grade. Buffers were extensively degassed.ε280 = 1400 L mol−1cm−1 as calibrated using quantitative amino acid analysis. The concentration determined by this method is correct within ± 20% or better. The monomer generated in this way was diluted with buffer to 10 µM and supplemented with 10 μM thioflavinT  from a 2 mM stock . All samples were prepared in low-binding Eppendorf tubes  on ice using careful pipetting to avoid introduction of air bubbles. The monomer sample was supplemented with 140 mM NaCl and 1 mM CaCl2. The CSF concentration series was prepared from a monomer stock, buffer, and CSF to yield samples with none or 1.2–80% CSF. The Aβ42 concentration series were prepared from samples with CSF concentrations of either 0%, 15%, 32%, or 66% along with buffer, and Aβ42 to yield samples with 10–0.8 µM Aβ42. Each sample was pipetted into three or four wells of a 96-well half-area plate of black polystyrene with a clear bottom and PEG coating , 100 μL per well, using the pipetting robot.Aliquots of purified Aβ42 were dissolved in 6 M GuHCl, and monomer isolated by gel filtration on a Superdex 75 column in 20 mM HEPES/NaOH, pH 8.0. The gel filtration steps remove traces of pre-existent aggregates and exchanges the buffer to the one used in the fibril formation experiments. The peptide concentration was determined from the absorbance of the integrated peak area using Assays were initiated by placing the 96-well plate at 37 °C under quiescent conditions in a plate reader . The ThT fluorescence was measured through the bottom of the plate every 60 s with a 440 nm excitation filter and a 480 nm emission filter.2, pH 8.0, 10 µM ThT, as above) supplemented with 0% or 66% CSF and incubated at 37 °C under quiescent conditions in a plate reader until the ThT fluorescence reached a plateau value. The seed fibrils were added to monomer solutions . The final seed concentrations were 30%, 10%, 3%, 1%, and 0% of the monomer concentration in monomer equivalents. Each mixture was then pipetted into three different wells in a 96-well plate.The seed fibrils were prepared from 3 µM monomer solutions  to ensure stable temperature and to avoid loss of solution during sample preparation. The specimens were prepared as thin liquid films, <300 nm thick, on lacey carbon-filmed copper grids and plunged into liquid ethane at −180 °C. This leads to vitrified specimens, avoiding component segmentation and rearrangement, and the formation of water crystals, thereby preserving original microstructures. The vitrified specimens were stored under liquid nitrogen until measured. A Fischione Model 2550 cryo transfer tomography holder was used to transfer the specimen into the electron microscope, JEM 2200FS, equipped with an in-column energy filter (Omega filter), which allows zero-loss imaging. The acceleration voltage was 200 kV and zero-loss images were recorded digitally with a TVIPS F416 camera using SerialEM under low dose conditions with a 30 eV energy selecting slit in place.Samples containing 10 µM Aβ42 in either 15% or 66% CSF, 10 µM ThT, 20 mM HEPES/NaOH, 140 mM NaCl, 1 mM CaClt1/2 plots. This was done by using the power function in KaleidaGraph, ver. 4.1.1.Determination of the scaling factor was done by fitting the described equation to the 45. At each condition  fits were made to the data using the following integrated rate law for the normalized aggregate concentrationGlobal analysis of Aβ42 aggregation kinetics to extract the rate constants for primary nucleation, secondary nucleation, and elongation was performed using the online Amylofit platformm]0 is the initial monomer concentration, [P]0 is aggregate number at the start of the reaction, [P]∞ is the aggregate number at equilibrium, that is, after reaction completion, [M]0 is the mass concentration of fibrils at the start of the reaction and [M]∞ is the mass concentration of fibrils at equilibrium. kn, k2, k+ are the rate constants for primary nucleation, secondary nucleation, and elongation, respectively. KM is the saturation constant for secondary nucleation and nc and n2 are the monomer scalings of primary and secondary nucleations, respectively. The values nc = 0.00001, and n2 = 2 were used for fitting of the kinetics in buffer, and the values nc = 3 and n2 = 2 for the fitting of all aggregation kinetics in the presence of CSF.In these relations, [The effective rate of formation of new aggregates through secondary nucleation at a given concentration was calculated using the following relation:In this work each experiment consists of a dilution series created by the pipetting robot by dispensing different volumes of stock solution containing Aβ42 and/or CSF and buffer into a 96-well plate to achieve the desired concentrations. Replicates within one experiment are created by dispensing the same volumes in several consecutive wells. Independent repeats of experiments were made always made using new stock solutions, when new CSF pools were used this has been indicated. All error bars are showing the standard deviation of such replicates within one experiment. Separate repeats of the same experiments are always shown in separate figures or panels.Further information on research design is available in the Supplementary informationDescription of additional supplementary dataSupplementary Data 1Supplementary Data 2Supplementary Data 3Supplementary Data 4Supplementary Data 5Reporting SummaryPeer Review File


Streptococcus pneumoniae (S. pneumoniae) in paediatric bacterial meningitis.There is currently no research on the diagnostic value of metagenomic next-generation sequencing (mNGS) for a single pathogens in CSF. The aim of this study was to analyse the value of mNGS for identifying Bacterial meningitis (BM) cases from October 23, 2014, to December 31, 2016, and December 1, 2017, to July 31, 2018 at Beijing Children’s Hospital were reviewed. Clinical features and pathogens were analysed.S. pneumoniae were identified by combination methods. 26/135 (19.3%) patients had positive results in S. pneumoniae by blood and/or cerebrospinal fluid (CSF) culture. Alere BinaxNow®Streptococcus pneumoniae Antigen test was positive in 35/135(25.9%) cases. 32/135 (23.7%) S. pneumoniae were identified by mNGS. Six CSF samples were identified as S. pneumoniae only by mNGS technology. Taking culture as the gold standard, the sensitivity and specificity of mNGS for diagnosing S. pneumoniae meningitis were 73.1 and 88.1%, respectively. The positive predictive value (PPV) and negative predictive value (NPV) of diagnosing S. pneumoniae meningitis by mNGS were 59.4 and 93.2%, respectively. When comparison between mNGS and combined tests (culture and Alere BinaxNow®Streptococcus pneumoniae Antigen test), the sensitivity and specificity of mNGS for S. pneumoniae identification were 70.3 and 93.9%, the PPV and NPV in the identification of S. pneumoniae by mNGS were 81.4 and 89.3%, respectively. The difference in number of unique reads of S. pneumoniaein from CSF sample (< 14 days onset) and CSF sample (> 14 days from onset) was statistically significant . The difference in the collected time of CSF for culture and mNGS was statistically significant .We diagnosed 135 patients with BM in this study. A total of 43 S. pneumoniae identification. The pathogen load (number of unique reads) of S. pneumonia is related to the CSF collection time. mNGS was less affected than culture by the use of antibiotics before CSF collection.mNGS has high sensitivity and specificity for  S. pneumoniae identification in CSF specimens.Metagenomic Next-generation sequencing (mNGS) had high sensitivity and specificity for mNGS was less affected than culture by the use of antibiotics before CSF collection.S. pneumoniae detected by mNGS was related to the duration from onset to the sample collection time.The number of unique reads of Streptococcus pneumoniae (S. pneumoniae) meningitis can reach 20–37% in high-income countries and up to 51% in low-income countries  were recorded.All BM patients aged 29 days to 18 years were admitted to the Department of Infectious Diseases at Beijing Children’s Hospital from October 23, 2014, to December 31, 2016, and December 1, 2017, to July 31, 2018. The diagnosis criteria for BM were consistent with the World Health Organization (WHO), as follows: (1) acute fever ; (2) headache, meningeal irritation, or altered consciousness; (3) at least one of the following in the cerebrospinal fluid: leukocytes > 100 cells/mm [One millilitre of CSF was collected for mNGS when the lumbar puncture was performed after admission. This study was approved by the Ethics Committee of Beijing Children’s Hospital affiliated to Capital Medical University (No. 2017–74). Written informed consent was obtained from the patient’s parents or other legal representatives.DNA was extracted directly from the 300ul CSF sample (each patient and negative “no-template” control) using the TIANamp Micro DNA Kit . The sample was added proteinase K (10 ml) and 300 ml buffer GB (with carrier RNA) and then incubated at 56 °C (10 min). After 300 ul cold absolute ethyl alcohol was added and the tube was incubated at room temperature (5 min). Transferring the liquid to a new adsorption column and the liquid was washed with buffer GD and buffer PW. The DNA was dissolved in 40ul of Tris–ethylenediaminetetraacetic acid buffer.The extracted DNA was sonicated with a Bioruptor Pico device to generate 200–300 bp fragments. According to the standard protocol of the BGISEQ-500 sequencing platform , DNA libraries were constructed through end repaired, adapter added overnight and polymerase chain reaction amplification to the extracted DNA. Quality control was carried out using a bioanalyser  combined with quantitative PCR to measure the adapters before sequencing. DNA sequencing was then performed using the BGISEQ-500 platform  [ftp://ftp.ncbi.nlm.nih.gov/genomes/), which included the genome sequences of 3446 bacterial species (104 species of Mycobacterium tuberculosis and 45 species of mycoplasma/chlamydia), 1515 viral species, 206 fungal species and 140 parasites connected to human diseases. The mapped data were used for further analysis. The depth and coverage of each species was calculated using Soap Coverage on the SOAP website (http://soap.genomics.org.cn/).High quality sequencing data was generated after removal of short (< 35 bp) reads, low quality and low complexity reads. The readings were then mapped to the human reference genome (hg19 and YH sequences) using the Burrows-Wheeler Aligner . The remS. pneumonia qPCR to validate the mNGS results. The DNA was extracted using the QIAamp cador Pathogen Mini Kit . qPCR was carried out on the ViiATM 7 real-time PCR system using cycling conditions comprising 2 min at 50 °C and 10 min at 95 °C followed by 45 two-step cycles of 15 min at 95 °C and 1 min at 60 °C. The sequences of the primers and probes are as follows: F: ACGCAATCTAGCAGATGAAGCA, R: TCGTGCGTTTTAATTCCAGCT and P: FAM-AACGCTTGATACAGGGAG-MGB [We performed GGAG-MGB .U test for non-parametric data. Continuous variables with P-values < 0.05 were considered statistically significant, and all tests were 2-tailed. Based on the extracted data, a 2 × 2 contingency table was used to determine sensitivity, specificity, PPV, and NPV. All of the statistical analyses were conducted using SPSS 23.0 software (SPSS Inc. USA).Continuous variables were expressed as the mean ± standard deviation or as the median. Two groups were compared using the independent t-test for parametric data and the Mann-Whitney S. pneumoniae was identified in 43/135 (31.9%) patients by all microbiology tests. A total of 26/43 (60.5%) cases were male, and the median age was 11.5  months. A total of 37/135 (27.4%) cases were identified as S. pneumonia infection by clinical microbiology tests (culture and/or Alere BinaxNow® Streptococcus pneumoniae Antigen test). S. pneumonia was identified by blood and/or CSF culture in 26/135 (19.3%) cases. A total of 35/135 (25.9%) patients had positive results on the Alere BinaxNow® Streptococcus pneumoniae Antigen test. S. pneumoniae was identified in 32/135 (23.7%) patient CSF specimens by mNGS. Six CSF samples were identified as S. pneumoniae only by mNGS.A total of 135 children with BM were included in this study. S. pneumoniae meningitis by mNGS, the number of unique reads of S. pneumonia ranged from 4 to 341,303. The coverage of S. pneumonia ranged from 0.011 to 86.68%, with a depth value of 1–36.57 (Table S. pneumoniae in the different groups (CSF collection time < 14 days and > 14 days from onset) was statistically significant   patients, while the unique reads > 100 group comprised 15 patients. Comparing the two groups, patients in the unique reads > 100 group had a generally shorter duration from disease onset to sample collection than patients in the mNGS unique reads ≤100 group . There was a significant difference in the simultaneous CSF white blood cell count and protein level between the two groups   days. The median collection time of CSF specimens for mNGS that had positive S. pneumoniae results was 14  days from onset. The difference in the collected time of CSF for culture and mNGS was statistically significant .The median collection time of CSF specimens for culture that had positive Streptococcus pneumoniae Antigen test) were both positive for S. pneumonia in 26 (19.3%) samples and were both negative for S. pneumonia in 92 (68.1%) samples. The accordance rate of mNGS and clinical microbiology tests (culture and/or Alere BinaxNow® Streptococcus pneumoniae Antigen test) for the identification of S. pneumoniae was 87.4% (118/135).Among the 135 BM patients, mNGS and clinical microbiology tests (culture and/or Alere BinaxNow® Streptococcus pneumoniae Antigen test) was shown in Table S. pneumoniae identification by mNGS were73.1 and 88.1%, respectively. The PPV and NPV of diagnosing S. pneumoniae meningitis by mNGS were59.4 and 93.2%, respectively. Comparing mNGS and the combined tests (culture and Alere BinaxNow® Streptococcus pneumoniae Antigen test), the sensitivity and specificity of mNGS for S. pneumoniae identification were70.3 and 93.9%, respectively, and the PPV and NPV for the identification of S. pneumoniae by mNGS were 81.4 and 89.3%, respectively.The comparison between mNGS and clinical microbiology tests  were positive for S. pneumonia in 4 (4/6) cases . One (1/6) case (unique reads: 4) was negative for S. pneumonia in the clinical microbiology tests (blood and/or CSF culture and Alere BinaxNow® Streptococcus pneumoniae Antigen test). Another case (1/6)  was positive for Staphylococcus aureus (S. aureus) in the blood culture. However, the result of specific PCR from CSF specimens was negative for both S. pneumoniae and S. aureus in P28.In total, we performed qPCR validation for 15 CSF specimens, while insufficient CSF sample was available for qPCR validation in the other cases. These 15 CSF specimens were collected for mNGS and qPCR at the same time. The qPCR results were positive in 9  cases  and negative in 6  cases. The latter 6 cases had fewer unique reads of Escherichia coli (E. coli) (unique reads 30) and S. pneumoniae (unique reads 4). In terms of clinical microbiology, P14 had a positive result for S. pneumoniae in the CSF culture and a positive Alere BinaxNow® Streptococcus pneumoniae Antigen test in the CSF. However, the Sanger validation of the CSF sample was negative for both S. pneumoniae and E. coli.In addition, we identified multiple pathogens in the CSF sample of P14 by mNGS, including Streptococcus pneumoniae Antigen test) were compared with an emerging pathogen detection method (mNGS). When the combined culture and pneumococcal antigen test were regarded as the gold standard, mNGS showed high sensitivity and specificity for the diagnosis of S. pneumonia meningitis. Previous studies have reported that mNGS has different sensitivities and specificities for the identification of different types of pathogens . The sensitivity and specificity of mNGS for the identification of bacteria had a wide range, with sensitivity ranging from 50.7 to 100% and specificity ranging from 76.5 to 87.5% [In this study, clinical microbiology tests  samples by both mNGS and clinical microbiology tests (blood and/or CSF culture and Alere BinaxNow®Streptococcus pneumoniae Antigen test). This result showed that mNGS appears to have a higher sensitivity than qPCR in the test cases. S. pneumonia (unique reads 27) was identified in P28 CSF sample by mNGS, while S. aureus was detected by blood culture. The P28 CSF sample was found to be negative for both S. pneumoniae and S. aureus by qPCR. In many mNGS systems, short read sequences lead to difficulties in assembling and matching to the reference sequence, especially in repeat regions, resulting in difficulties defining the final pathogen. Therefore, when the number of unique reads is very small, the interpretation of pathogen data needs to be very careful and cautious [Among the 6 CSF samples that were negative for S. pneumoniae. There were significant differences in the simultaneous CSF white blood cell counts and protein levels between the two groups. These results suggested that the inflammation status during simultaneous mNGS detection might determine the number of unique reads of the pathogen. The number of unique reads may indirectly monitor disease progression.We compared groups with ≤100 unique reads and groups with > 100 unique reads and analysed factors that could affect the number of unique reads of Currently, the criteria for diagnosing single pathogens by mNGS are unclear. Different studies have reported different diagnostic criteria, mainly based on the coverage rate, the relative abundance of pathogens or unique reads of pathogens , 29.S. pneumoniae was 4, and the clinical microbiology test was also positive for S. pneumoniae. Therefore, the positive criteria for single pathogen identification by mNGS testing require further research by a larger sample size.In this study, the minimum number of unique reads of There were several limitations in this study. First, the collection time of some CSF samples for mNGS and clinical microbiology tests was different. The collection time of CSF was later for mNGS than for the clinical microbiology tests, which may affect the positive identification rate of mNGS. Some of the CSF specimens were collected at the convalescence stage. Second, this study was retrospective and had a limited number of BM cases, and thus large-scale research is needed. Third, mNGS still has low sequencing depth, and the pathogen database is imperfect . HoweverS. pneumoniae). mNGS has high sensitivity and specificity for S. pneumoniae identification. Our study also demonstrated the relationship between the pathogen load (unique reads) and CSF collection time. Although there are no uniform criteria for pathogen identification by mNGS, there are many difficulties in interpreting the mNGS results. With the development of mNGS technology, mNGS could be a promising alternative diagnostic tool for pathogen detection.This study is the first to analyse the diagnostic value of mNGS for the identification of a single pathogen (


Despite advances in medical and electrical therapies for heart failure, morbidity and mortality remain high and patients often progress to end-stage heart failure. Over the last five decades, heart transplantation is considered a standard therapy for select patients with end-stage heart failure. However, while heart transplantation has become a treatment of choice for end-stage heart failure, challenges still exist for improvement in the short- and long-term outcomes. While there is an increase in the number of patients with end-stage heart failure, the number of donor organs remains a major limiting factor. Heart transplantation candidates in the current era are also more complex: older, antigen-sensitized, and on mechanical circulatory support at the time of listing and transplant. Such potential heart transplant recipients have an increased chance of problems, including antibody-mediated rejection and primary graft dysfunction. Recent advances could address the current challenges and include: 1) attempts to expand the pool of donor hearts; 2) changes in heart transplantation allocation policy allowing for more equitable organ distribution; and 3) advances in the management of antibody sensitization. Developments in these areas could result in improved survival and quality of life for heart transplantation recipients. Over the last five decades, heart transplantation is considered a standard therapy for select patients with end-stage heart failure. In the present era, one-year survival after heart transplantation is almost 90% and has a conditional half-life of 13 years2. Heart transplant (HTx) candidates of the current era are also more complex. Increasing numbers are aged 65 years or more3, have mechanical circulatory support3, and have higher levels of antibodies to human leukocyte antigens (HLA), i.e. “sensitization”4. Due to all these issues, these HTx candidates of the modern era are at increased risk for poor outcomes, including primary graft dysfunction and antibody-mediated rejection5. The latest developments might be able to counter existing problems: 1) attempts to expand the pool of potential organ donors; 2) changes in the heart transplant donor allocation policy to allow for more equitable organ distribution; and 3) management of sensitized HTx candidates. Such advances could produce an increase in and a fairer allocation of donor organs and improved quality of life and survival for HTx recipients.The number of patients with heart failure requiring advanced therapies is growing, while the number of donor organs remains a constant and limiting factor6. Initiatives have been taken to increase the utilization rate7. Using less-than pristine donor hearts, so-called extended criteria donors, is one option to expand the donor pool. These hearts may be used for higher-risk recipients, such as those who are older, over age 65, with diabetes, renal dysfunction, or peripheral vascular disease. Considerable evidence shows that extended criteria donor hearts that may result in favorable post-HTx survival continue to be underutilized. In a retrospective review in California from 2001 to 2008 looking at 1872 possible organ donors found predictors of non-use to be age >50 years, female gender, fatal cerebrovascular accident, hypertension, diabetes mellitus, an elevated troponin, left ventricular dysfunction (ejection fraction <50%), left ventricular hypertrophy, and regional wall motion abnormalities. However, when such so-called extended criteria donor hearts are used for transplantation, outcomes are generally comparable11.Currently, fewer than 50% of potential donors in the United States become actual organ donorsex vivo perfusion platform would allow the donor heart to be kept in a warm, beating state while being transported until the time of implantation. Small registry studies have demonstrated its safety12. In a randomized trial examining the safety of anex vivo platform, donor hearts managed with either the Organ Care System or standard cold storage were randomized to 130 patients. There was no difference in 30-day patient survival rates, 30-day graft survival rates, or serious adverse events13.The donor pool could be expanded by limiting cold ischemic time. Anex vivo perfusion platform may be particularly beneficial when used in conjunction with extended criteria donor hearts. Such donors, including those of older age, with left ventricular hypertrophy or moderately reduced ejection fraction, are more susceptible to injury with long ischemic time. Further study is needed to demonstrate the specific benefit of anex-vivo perfusion platform in this population.The15: there is an imbalance between candidates awaiting transplantation and available donors, the sickest patients have unacceptably high mortality, and advances in mechanical circulatory support have decreased mortality in these transplant candidates.The allocation of donor hearts in the United States appears to be fair, as those patients who are sickest and who have been waiting the longest are the first to be considered in the event of a donor heart becoming available . However15.These alterations have uncovered two significant difficulties with the present status criteria. First, the system offers inadequate resolution. Status 1A includes the following groups with equal urgency: patients who receive extracorporeal membrane oxygenation (ECMO) and continuous intravenous inotropic support and hemodynamic monitoring. However, potential HTx recipients on ECMO support have increased mortality compared with candidates on inotropic support with continuous hemodynamic monitoring. Thus, these two groups of patients should not have the same priority, though they do under the current three-tiered system. The current system also makes no allowance for tenuous transplant candidates who do not qualify for Status 1A listing, including candidates with complex congenital heart disease, restrictive or infiltrative cardiomyopathies, or refractory ventricular tachycardia16. Proposed statuses 1–3 are generally defined by current Status 1A criteria, proposed Status 4 is generally defined by current Status 1B, and proposed Status 5 and 6 are covered by current Status 2 criteria. The most significant alteration is the classification of patients within the current 1A status into three groups of decreasing acuity. In addition, the suggested policy tackles potentially underserved groups, such as adults with congenital heart disease, restrictive/hypertrophic cardiomyopathy, and re-transplantation in a separate tier above current Status 2 patients.There are seven statuses in the new allocation policy 16. PropThe novel allocation system deals with geographical inequality in organ distribution  by broadThis system was approved by the United Network of Organ Sharing Board and Organ Procurement and Transplant Network in December 2016. It will go into effect in the last quarter of 2018. No system can be perfect, but these efforts allow for more equitable distribution of this scarce resource and achieve the primary goal, whereby the most critically ill patients can receive transplantation before their window of viability closes.17 and is noninvasive. In randomized trials, gene expression profile was non-inferior to an endomyocardial biopsy in the diagnosis of cellular rejection18 and also useful early post-transplant19. One role of the gene expression profile is to screen patients at low risk for cellular rejection at pre-determined intervals with biopsies performed only in cases in which the gene expression profile score is abnormal. However, patients with risk factors for antibody-mediated rejection cannot be tested with gene expression profile screening as the technique can only be used to assess cellular rejection.Despite the fact that endomyocardial biopsy is usually a simple procedure, the morbidity associated has motivated development of other means to diagnose rejection. The gene expression profile test , an 11-gene expression signature from peripheral blood mononuclear cells, has a high negative predictive value for cellular rejection21 This cell-free DNA may be a potential marker for noninvasive diagnosis of graft injury, as cellular and antibody-mediated rejection events are associated with increased levels of cell-free donor-derived DNA22.One more novel technique that can be used for noninvasive diagnosis of rejection uses cell-free DNA. Cell-free donor-derived DNA can be detected in the blood and urine of organ transplant recipients23. This advance has the potential to refine diagnostic accuracy and may in the future provide insight into the management of AMR24.As mentioned above, the Allomap relies on peripheral blood gene expression profiling to refine diagnostic accuracy and does not detect antibody-mediated rejection (AMR). A recent study, however, studied mRNA extracted from endomyocardial biopsy samples and hybridized to a microarray system. Differences in AMR-selective gene expression classified AMR were linked with disease activity and ISHLT AMR gradein vitro are potentially more cytotoxicin vivo. The presence of high-level anti-HLA antibodies  are considered potentially cytotoxic24.The detection and measurement of anti-HLA antibodies is accomplished using solid phase assays . Quantif26. The classical complement pathway is activated first by C1q binding to antibodies, as C1q is the first component of the pathway. After C1q activation, the complement cascade results in formation of the membrane attack complex and ultimately leads to cell lysis and death. In fact, antibodies with the ability to bind C1q are more likely to be cytotoxic27. The C1q assay is not currently available in all centers, so considering only antibodies that are strong binding by MFI after a 1:8 or 1:16 dilution may offer comparable information26.However, not all high-intensity antibodies are detrimental to graft function and the fact that donor-specific antibodies have the ability to fix complement might be a superior way of signifying cytotoxicityPrior to transplantation, the detection of anti-HLA antibodies is important to avoid hyperacute rejection: one would avoid donors with HLA correlating with high-level anti-HLA antibodies in the prospective recipient. One way to prevent hyperacute rejection is a prospective crossmatch, in which the potential recipient’s serum and donor cells are mixed to evaluate for complement-dependent cytotoxicity. However, this restricts the donor pool based on the location of the candidate’s serum, and so decreasing the number of possible donors.29.Thus, the virtual crossmatch has essentially replaced the prospective crossmatch. HLA correlating with the candidate’s high-level anti-HLA antibodies are recorded as “avoids” in the United Network of Organ Sharing (UNOS) database. In this manner, potential donors with such HLA are not considered. This method has proven feasible in HTx30. The cPRA is the frequency of HLA defined as unacceptable in the donor population. For example, a HTx candidate with multiple anti-HLA antibodies might have a cPRA of 90%. This would mean that of all potential donors only 10% would be a match. cPRA highlights the fact that some high-level anti-HLA antibodies, the more common ones, will impact the ability to identify a suitable donor heart more than less common anti-HLA antibodies31. If the cPRA is above 50–70%, therapies to reduce antibody levels may be administered.The identity and the intensity score (given by Luminex single-antigen bead assay) of anti-HLA antibodies is also valuable information for deciding which potential heart transplant recipients require desensitization, as expressed as the calculated PRA (cPRA)32), removal (plasmapheresis), and reduced production (rituximab32) and bortezomib33). At our center, the desensitization process usually starts with a modified protocol built around one established for desensitization of kidney transplant recipients , then one may use bortezomib, a proteasome inhibitor targeting plasma cellsheresis .Eculizumab. Pre-transplant interventions with IV Ig, rituximab, and bortezomib can reduce antibody levels so that it is possible to find an acceptable donor. However, for some patients such measures are not effective. Hyperacute rejection can still occur at the time of transplantation due to cytotoxic anti-HLA antibodies. This can happen if donor-specific antibodies were mistakenly classified as not cytotoxic by virtual crossmatch or if such antibodies were not present at the time banked blood was stored for a prospective crossmatch. Plasmapheresis may be used in the operating room at the time of transplantation in this setting. We have also found that eculizumab offers further insurance and protection against hyperacute rejection.34.The monoclonal antibody eculizumab blocks the last component of the complement cascade. This cascade is triggered by antigen-antibody complexes and results in formation of the membrane attack complex and ultimately cell death. Eculizumab specifically binds to the terminal complement component 5 (C5), and thus eventually blocks the production of the terminal complement complex C5b-9. Eculizumab is FDA-approved for use in two complement-mediated conditions, paroxysmal nocturnal hemoglobunuria and atypical hemolytic-uremic syndrome. However, it also has benefit in sensitized kidney transplant recipientsThe boundaries of HTx continue to expand to higher-risk candidates—older, on mechanical circulatory support, and with HLA antibody sensitization—and our goal remains to maintain favorable outcomes utilizing this scarce resource. The advances outlined here, from efforts to expand the donor pool, revision of the HTx allocation policy, newer ways to diagnose rejection, to developments in the detection and care of sensitized HTx candidates, will bring about improvements in survival and quality of life of end-stage patients who have HTx.AMR, antibody-mediated rejection; cPRA, calculated panel reactive antibodies; ECMO, extracorporeal membrane oxygenation; HTx, heart transplantation; IV Ig, intravenous immune globulin; MFI, median fluorescent intensity; PRA, panel reactive antibodies.


Cytokines play multiple roles during neuro-inflammatory processes and several cytokines have been studied in the context of specific diseases. This study provides a comprehensive picture of cerebrospinal fluid (CSF) changes during neuro-inflammation by analyzing multiple cytokines in combination with immune cell subsets and standard CSF parameters.n = 18), secondary progressive MS (n = 8), neuro-syphilis (n = 6), Lyme neuro-borreliosis (n = 13), bacterial and viral meningitis (n = 20), and patients with non-inflammatory neurological diseases . Cytokine concentrations were correlated with CSF standard parameters and CSF immune cell subsets  quantified by flow cytometry.Using multiplex assays, we simultaneously measured 36 cytokines  in the CSF and serum of 75 subjects. Diagnoses included clinically isolated syndrome and relapsing-remitting multiple sclerosis . Within the CSF compartment, CXCL13 showed a strong association with B cells when analyzing all patients, as well as patients with an intact blood-brain barrier (BBB). NK cells positively correlated with CSF concentrations of multiple cytokines (22/36) when analyzing all patients. These correlations were maintained when looking at patients with a disrupted BBB but not detectable in patients with an intact BBB.We observed increased levels of multiple cytokines (26/36) in patients with neuro-inflammatory diseases when compared to NIND that consistently correlated with CSF cell count and QUnder conditions of neuro-inflammation, multiple CSF cytokines are regulated in parallel and most likely produced locally. A combined increase of CSF CXCL13 levels and B cells occurs under conditions of an intact BBB. Under conditions of a disrupted BBB, CSF NK cells show significantly increased values and seem to have a major contribution to overall inflammatory processes, reflected by a strong correlation with multiple cytokines. Future studies are necessary to address the exact kinetics of these cytokines during neuro-inflammation and their relation to specific diseases phenotypes. Cytokines are small proteins that are secreted by various cell types and play multiple roles during development, homeostasis, and immune regulation . AccordiSeveral studies on CSF cytokines are available in patients with multiple sclerosis (MS). CSF levels of TNF-α, IL12, CXCL9, CXCL10, CCL17, CCL21, CCL22, IL10, IL6, IL23, IL17, IL8, CXCL13, CCL19, and CCL5  have been shown to be consistently upregulated , 41. LatAlbumin), and immunoglobulin (Ig) indices. In addition, we also performed correlation analyses with different CSF immune cell subsets including CD4 and CD8 T cells, B cells, plasmablasts, NK cells, and monocytes that have been routinely quantified by flow cytometric analyses.In order to obtain a more comprehensive picture of CSF cytokine profiles in neurological diseases, we measured the concentrations of 36 cytokines in the CSF and serum of 75 patients using multiplex assays. Diagnoses included non-inflammatory controls (NIND), multiple sclerosis (RRMS) and clinically isolated syndrome (CIS), secondary progressive MS (SPMS), neuro-syphilis (Lues), Lyme neuro-borreliosis (LNB), and bacterial and viral meningitis. Cytokine values were correlated with CSF standard parameters such as CSF cell count, albumin quotient (Qn = 10), relapsing-remitting multiple sclerosis , clinically isolated syndrome , secondary progressive MS , neuro-syphilis , Lyme neuro-borreliosis (n = 13), and bacterial (n = 10) and viral meningitis (n = 10) were included in our analysis. Patients with NIND suffered from normal pressure hydrocephalus (n = 3) and pseudotumor cerebri (n = 7). In patients with bacterial meningitis (n = 10), the following specific pathogens were identified: Streptococcus pneumonia (n = 2), Haemophilus influencae (n = 2), Listeria monocytogenes (n = 1), suspicion of Mycobacterium tuberculosis (n = 3), and undetermined, presumably bacterial pathogens (n = 2). In viral meningoencephalitis (n = 10), varicella zoster virus (n = 2), herpes simplex virus (n = 3) and undetermined presumably viral pathogen (n = 5) were detected. Further details are displayed in Table All patients were recruited at the Department of Neurology of the Technical University of Munich. CSF samples were obtained for routine diagnostic work-up, and patients consented to the scientific use of their biosamples. The ethics committee of the Technische Universität München approved the scientific use of CSF biosamples. Patients with non-inflammatory diseases  to obtain CSF cell count. Total protein, albumin, IgG, IgM, and IgA concentrations in CSF and serum were determined by nephelometry according to the manufacturer’s instructions . Oligoclonal bands were investigated by isoelectric focusing followed by silver staining.+CD3+CD4+), CD8 T cells (CD45+CD3+CD8+), monocytes (CD45+CD14+), NK cells (CD45+CD56+), B cells (CD45+CD19+CD138−), and plasmablasts (CD45 CD19+CD138+).Flow cytometric analysis of immune cell subsets was performed as described previously . ShortlyIn order to measure several cytokines in parallel, we performed multiplex assays (BioRad #171304070 M (10-Plex), #171AK99MR2 (40-Plex)) according to the manufacturers’ instructions. The 40-Plex kit contained the following cytokines: CCL1, CCL11, CCL13, CCL15, CCL17, CCL19, CCL2, CCL20, CCL21, CCL22, CCL23, CCL24, CCL25, CCL26, CCL27, CCL3, CCL7, CCL8, CX3CL1, CXCL1, CXCL10, CXCL11, CXCL12, CXCL13, CXCL16, CXCL2, CXCL5, CXCL6, CXCL8, CXCL9, GM-CSF, IFNγ, IL10, IL16, IL1β, IL2, IL4, IL6, MIF, and TNF-α. The 10-Plex Kit included the cytokine antibodies GCSF, IL12, IL17A, IL2, IL4, IL5, IFNγ, MIB1β, CCL5 (RANTES), and TNF-α. In order to enable an optimal comparability between different patient groups within one compartment, all CSF samples were measured on a single multiplex plate; all serum samples were measured on a single multiplex plate for each kit, respectively. CSF samples were applied undiluted; serum was pre-diluted 1:4. Multiplex plates were measured on a Luminex MAGPIX®. Standard curves and values were calculated using xPONENT 4.2 software for MAGPIX®. The required amount of 50 beads per analyte was consistently detectable for all analytes in the 40-Plex Kit. Although the 10-Plex Kit was used according to the manufacturer’s instructions, less than the required 50 beads per analyte were detectable for most cytokines. For this reason, only MIB1β from the 10-Plex Kit  was used for further analyses in order to ensure good data quality. Standard curve ranges with upper and lower limits of cytokine concentrations are displayed in Additional file p values below 0.05 were considered significant. Bonferroni’s correction (correction for multiple testing of cytokine/immune cell subsets) was systematically used during statistical testing to reduce false positives.All analyses and figures were done in R (version 3.5.3), using packages ggplot2 (3.3.1) and dplyr (0.8.1). The non-parametric Mann-Whitney rank sum test was used to compare cytokine concentrations in different conditions. The Shapiro-Wilk normality test was used to test the normal distribution of the data. In case of normality, Pearson’s correlation test was used; otherwise, Spearman’s non-parametric correlation test was used to test for correlation between cytokine concentrations. Albumin), IgG, IgA, and IgM index showed disease-specific changes within expected limits .In order to obtain a more detailed picture, we also analyzed changes in percentage distributions for the different diseases, using NIND as a control group Table . An elevCSF concentrations of all cytokines were analyzed by comparing values from different neuro-inflammatory diseases with NIND. Multiple cytokines 26/36) showed significantly elevated CSF concentrations under conditions of neuro-inflammation Fig. , Table 26/36 showp value < 0.05). CXCL16 and GM-CSF showed significantly lower concentrations  whereas IL4, CCL2, CXCL5, MIF, and MIB1β values did not show significant differences. We found no evidence that gender nor freezing time had an impact on overall cytokine levels in the serum or CSF. However, MIF serum concentrations correlated with freezing time  in patients with LNB and age correlated with CCL27 CSF concentrations  in patients with CIS-RRMS.Patients with a disrupted blood-brain barrier (BBB) defined by albumin quotient ≥ 8 showed significantly higher cytokine levels within CSF for 29 out of 36 (81%) cytokines when compared to patients with albumin quotient < 8 . Interestingly, CXCL16 and GM-CSF showed a negative correlation with QAlbumin. Multiple negative correlations were observed between CSF cytokines and glucose levels (21/36), and positive correlations between CSF cytokines and lactate levels (23/36). In regard to an intrathecal immunoglobulin synthesis, IgA index significantly correlated with 29 out of 36 cytokines , and IgG with 28 out of 36 cytokines ; IgM index showed a significant correlation with 22 out of 36 cytokines   and QAlbumin < 8  into two different groups for further analyses . Under conditions of a disrupted BBB, NK cells significantly increased and seemed to have a major contribution to inflammatory processes, which was reflected by a strong correlation with multiple pro-inflammatory cytokines.Albumin (31/36), indicating that an upregulation of CSF immune cells and disruption of the blood-brain barrier are associated with numerous pro-inflammatory cytokines. However, the cytokines CCL2, CXCL5, IL4, MIF, and MIB1β did not show a significant elevation or correlation with CSF cell count and QAlbumin, so that these cytokines are most likely not involved in inflammatory CSF processes. In patients with a disrupted blood-brain barrier, only CCL27 concentrations correlated between CSF and serum. Thus, a passive exchange of cytokines across the BBB does not seem to be the major source of CSF cytokines in neuro-inflammation. Instead, a local production and parallel upregulation of cytokines seem more plausible. These results suggest that a cascade of intrathecal cytokine production and immune cell recruitment in combination with a disruption of the BBB occurs during neuro-inflammation. The chronology of cytokine expression during these neuro-inflammatory processes cannot be determined by correlation analyses, but certain hints can be drawn from further detailed analyses.Analyzing all samples together, the majority of measured cytokines (26/36) showed elevated CSF values under certain inflammatory conditions. Most of these CSF cytokines correlated with each other (31/36) and with routine CSF parameters such as CSF cell count (29/36) and QAlbumin. Possible chemotactic factors for intrathecal NK cell recruitment are CXCL8, CCL3, and CX3CL1 [Regarding the different immune cell subtypes, NK cells turned out to be a prominent cell population that might support neuro-inflammatory processes especially under conditions of a disrupted BBB. Both NK cell percentage and cytokine concentrations in the CSF were significantly higher in patients with a disrupted BBB. Consequently, NK cells showed a strong correlation with multiple CSF cytokines in those patients whereas patients with an intact BBB did not show any correlations at all. Pro-inflammatory cytokines such as TNF-α and IL6 have been shown to be involved in BBB breakdown , 24, 33 d CX3CL1 . Indeed,d CX3CL1 , 30. We Another strong association could be found between CSF B cells and CXCL13 values which is in line with previous results . In contWhen analyzing our data according to disease-specific changes, the following conclusions can be drawn for certain cytokines. The CSF milieu in multiple sclerosis has been intensively studied , and we Albumin was used as a clinically pragmatic way to define a disrupted BBB but might not accurately reflect the actual barrier for cytokines, which are small molecules and might show transfer kinetics different from albumin. Fourth, we used Bonferroni’s correction for all analyses to reduce the number of false positives at the cost of having more false negatives. This strict correction for multiple testing can possibly explain differences to previous studies that measured smaller subsets of cytokines.The following limitations of our study have to be discussed. First, we limited the total number of patients to 75, so that they fitted on 1 plate for CSF and 1 plate for serum samples, along with the standard curve, in order to avoid interplate variation for the multiplex assays that was observed in preliminary experiments with the same samples on different plates. Second, correlations between different CSF parameters do not prove causality, so that direct conclusions on functional aspects remain speculative. Thus, multiple correlations in our studies have to be interpreted at a descriptive level. Third, an elevated QWe could show that B cell activation with an upregulation of CXCL13 can occur under conditions of a grossly intact blood-brain barrier. After break down of this barrier, NK cells significantly increased and seemed to have a major contribution to inflammatory processes, which was reflected by a strong correlation with multiple cytokines. From a clinical point of view, CXCL13 was again confirmed as a reliable marker for CSF B cell recruitment and might be used as a clinical marker to predict disease activity in MS, confirming the diagnosis of LNB and CNS lymphoma . HoweverAdditional file 1: Figure S1. Boxplot diagrams of all serum cytokine concentrations including all patient groups . Diagrams are further grouped according to ranges of concentrations with 0–25 pg/mL (A), 0–100 pg/mL (B), 0–200 pg/mL (C), 0–500 pg/mL (D), 0–1000 (E) and 0–5000 pg/mL (F).Additional file 2: Figure S2. Heatmap representing correlations between different CSF cytokines among each other. Positive correlations are given in red, negative correlations in blue. Only correlations with p-value < 0.05 after Bonferroni correction are displayed.Additional file 3: Figure S3. Heatmap representing correlations between CSF and serum cytokine concentrations. Positive correlations are given in red, negative correlations in blue. Only correlations with p-value < 0.05 after Bonferroni correction are displayed.Additional file 4: Figure S4. Heatmap representing correlations between different CSF cytokines among each other for patients with Qalbumin ≥ 8. Positive correlations are given in red, negative correlations in blue.Additional file 5: Figure S5. Heatmap representing correlations between different CSF cytokines among each other for patients with Qalbumin < 8. Positive correlations are given in red, negative correlations in blue. Only correlations with p-value < 0.05 after Bonferroni correction are displayed.Additional file 6: Table S1. Measured standard curves in CSF and serum and sensitivity values provided by the manufacturer. Measured standard curves above had a wide linear range and showed very close values to the ranges provided for serum values by the manufacturer. N.A. not provided by manufacturer.Additional file 7: Table S2. Routine CSF parameters including CSF cell count, glucose, lactate, QAlbumin and Ig indices are shown for different diseases. Average values with ± standard deviations are displayed.


In addition to the “gold standard” of therapy—steroids and gene therapy–there are experimental trials using granulocyte-colony stimulating factor (G-CSF) for patients with Duchenne muscular dystrophy (DMD). The aim of this study was to present the biochemical changes in blood after repeating cycles of granulocyte-colony stimulating factor G-CSF therapy in children with DMD.μg/kg/day) was given subcutaneously for five days during five nonconsecutive months over the course of a year. Nineteen patients, aged 5 to 15 years, with diagnosed DMD confirmed by genetic tests, participated; nine were in wheelchairs, and ten were mobile and independent. Patients had a clinical assessment and laboratory tests to evaluate hematological parameters and biochemistry. G-CSF  and alanine transaminase (ALT) of the G-CSF treatment was noted. After each five days of therapy, the level of cholesterol was significantly lowered. Also, glucose concentration significantly decreased after the fourth cycle. G-SCF decreased the aminotransferases activity, cholesterol level, and glucose level in patients with DMD, which may be important for patients with DMD and metabolic syndrome. Granulocyte-colony stimulating factor (G-CSF) is a glycoprotein produced by endothelium, macrophages, and lymphocytes . G-CSF sTriglycerides and free fatty acids were decreased in the experimental study of hepatic steatosis rats after G-CSF treatment . G-CSF hIn healthy donors who received G-CSF in different doses per day, changes in serum chemistries were observed . SignifiIn a 2018 study, Hatfield et al. [μg/kg/body/day) subcutaneously for five consecutive days during the 1st, 2nd, 3rd, 6th, and 12th month. We found an increase of physical activity and muscle strength in patients with DMD treated with G-CSF during one year of therapy [In our previous prospective, nonrandomized clinical trial, we assessed the efficacy and safety of G-CSF treatment in patients with DMD . Each pa therapy . Also, wDMD is a one of the more frequent genetic disorders in children, characterized by progressive muscle weakness and wasting , 11. TheG-CSF was tested in the animal model of DMD, the mdx mouse . It was The “gold standard” of DMD therapy is steroids, which slow the course of the illness . ContempIt is worth emphasizing that most children and adolescents with DMD have symptoms of metabolic syndrome. Hypertriglyceridemia is prevalent in 46% of children and adolescents with DMD. For example, the prevalence of metabolic syndrome varies between 7% and 24% .This study aimed to present the biochemical changes in blood after repeating cycles of G-CSF treatment in patients with DMD.A retrospective, nonrandomized clinical trial evaluated the safety of G-CSF therapy in patients with DMD: biochemical changes in the blood after repeating cycles of treatment.The following inclusion criteria were used in this study: children and adolescents aged 5-15 years with diagnosed DMD; the disease had to be confirmed by genetic test or biopsy. Nineteen subjects were included in the study. Fourteen patients took steroids. Nine children used wheelchairs and ten were mobile. Details are described in our previous article .Patients were clinically monitored by neurological assessment. Laboratory tests included full blood count and biochemistry  made by laboratory at the Medical University Children Hospital, Bialystok. Blood was drawn before G-CSF application and on the fifth day of each treatment cycle.μg/kg/body/day) was given subcutaneously for five days during the first, second, third, sixth, and twelfth month during hospitalisation. All patients received rehabilitation procedures.Granulocyte-colony stimulating factor (5NCT02814110).The bioethics committee of the Medical University of Bialystok, Poland, approved this study (R-I-002/375/2013). The parents and patients gave written informed consent to participate in the study before participation. The clinical trial was registered at the website Clinicaltrials.gov . Pairedμg/kg/day).A total of 19 children and adolescents, boys aged 5-15 years (9.4±2.6), were treated with G-CSF. Sixteen participants (84.2%) completed the study, obtaining five cycles of five days' treatment (G-CSF in dose 5Blood samples were collected before and after each cycle of therapy. We found a significant increase p<0.001) in the white blood cell count after each cycle of G-CSF, but no changes in the red blood cell, hemoglobin, platelet, and C-reactive protein levels. The level of leucocytes returned to normal after each cycle. Details are presented in Tables  in the wThe coagulation system was monitored by prothrombin time, prothrombin index, kaolin-cephalin time and fibrinogen assay. There was no deterioration in these parameters .As shown in We found decreases in aminotransferases activity and cholesterol level. We observed significantly lower AST activity after the first, second, third (each p=0.001), and fifth (p=0.023) cycle treatments. ALT activity decreased after the first (p=0.011) and third (p=0.006) cycles of G-CSF treatment. After each cycle, we observed significant (p<0.001) lowering of the total cholesterol level. These results are presented in We also found a significant decrease in glucose level after fourth cycle treatment. Details are shown in In our previous article, we described an increase in physical activity and muscle strength in our study group patients treated with G-CSF during one year of therapy. As to laboratory parameters, we found a statistically significant decrease in the activity of muscle enzymes creatine kinase after each cycle of treatment .In the present study, we did not detect significant changes in red blood cell, hemoglobin and platelet levels, or coagulation parameters. We found a significant elevation of uric acid, with normalization after finishing each cycle of treatment with G-CSF. We also observed decreased aminotransferases activity, cholesterol level, and glucose level in patients with DMD, which may be important for patients with DMD and metabolic syndrome.Our findings are in agreement with earlier reports , 23. In Possible mechanisms of the general effect of G-CSF on various liver diseases have been suggested. Stem cells of the bone marrow may accelerate the regeneration of damaged liver cells by differentiation or paracrine effect . AdditioIn an animal model of atherosclerosis, G-CSF reduced atherosclerotic plaque formation in cholesterol-fed rabbits . Adminisα), which increase insulin resistance [α and decreases the harmful effects of inflammatory reactions [It is known that, in obese subjects, chronic inflammation is observed, with increased levels of proinflammatory cytokines, including IL-6 and tumor necrosis factor-n . Statistically significant effects applied to (1) the increase of white blood count level after each treatment cycle, with following normalization and no change in CRP level, (2) elevation of uric acid and following normalization during therapy, and (3) diminution of AST, ALT activity and cholesterol level. We observed no alterations in hematological and coagulation system parameters. The G-CSF therapy was safe and well tolerated. These results are associated with the multidirectional, stimulating impacts of G-CSF on the organism, and show the safety of this type of treatment for patients with muscular dystrophies. However, because of the limited group size, the findings of the present study must be interpreted with great caution.In summary, our study shows changes in laboratory parameters, biochemical and hematological, in children with DMD during repeated cycles of treatment with G-CSF (5


Hypertension is an important risk factor for cerebrovascular disease, including stroke and dementia. Both in humans and animal models of hypertension, neuropathological features such as brain atrophy and oedema have been reported. We hypothesised that cerebrovascular damage resulting from chronic hypertension would manifest itself in a more permeable blood–brain barrier and blood–cerebrospinal fluid barrier. In addition, more leaky barriers could potentially contribute to an enhanced interstitial fluid and cerebrospinal fluid formation, which could, in turn, lead to an elevated intracranial pressure.To study this, we monitored intracranial pressure and estimated the cerebrospinal fluid production rate in spontaneously hypertensive (SHR) and normotensive rats  at 10 months of age. Blood–brain barrier and blood–cerebrospinal fluid barrier integrity was determined by measuring the leakage of fluorescein from the circulation into the brain and cerebrospinal fluid compartment. Prior to sacrifice, a fluorescently labelled lectin was injected into the bloodstream to visualise the vasculature and subsequently study a number of specific vascular characteristics in six different brain regions.Blood and brain fluorescein levels were not different between the two strains. However, cerebrospinal fluid fluorescein levels were significantly lower in SHR. This could not be explained by a difference in cerebrospinal fluid turnover, as cerebrospinal fluid production rates were similar in SHR and WKY, but may relate to a larger ventricular volume in the hypertensive strain. Also, intracranial pressure was not different between SHR and WKY. Morphometric analysis of capillary volume fraction, number of branches, capillary diameter, and total length did not reveal differences between SHR and WKY.In conclusion, we found no evidence for blood–brain barrier or blood–cerebrospinal fluid barrier leakage to a small solute, fluorescein, in rats with established hypertension.The online version of this article (10.1186/s12987-018-0112-7) contains supplementary material, which is available to authorized users. Chronic hypertension is a well-established risk factor for cerebrovascular disease, including haemorrhagic stroke, vascular dementia and Alzheimer’s disease. It is associated with alterations in the structure and function of cerebral blood vessels, which may contribute to hypoperfusion, microinfarcts, brain atrophy, oedema, and ultimately, cognitive impairment , 2. AlthDysfunction at the blood–brain barrier (BBB) is often regarded as an early and common denominator in cerebrovascular disease. Hypertension could be envisioned to enhance loss of BBB integrity, leading to increased solute permeability of this barrier and leakage of water into the brain parenchyma , 2. The Recent work by our group showed that the ISF drainage towards the ventricular system is enhanced in the hippocampus of spontaneously hypertensive rats (SHR) . This anIn the current study, we determined the effects of hypertension on the BBB and blood–CSF barrier (BCSFB) integrity. We hypothesised that increased leakage across the BBB may lead to enhanced ISF formation, resulting in a greater extra-choroidal contribution to the total CSF production. Apart from this, a more leaky BCSFB may in itself lead to an increased CSF production. Both increased ISF and CSF formation could potentially elevate intracranial pressure (ICP). Therefore, we monitored the ICP and estimated the rate of CSF production in SHR and normotensive controls . As a second approach, we assessed the penetration of fluorescein, a relatively small molecule, into the brain parenchyma and CSF compartment as an indicator of subtle BBB and BCSFB dysfunction, in the same animals. Since all measurements could be affected by vascular parameters such as the total surface of capillaries, we also examined a number of specific vascular characteristics that may be related to the fluid balance in the brain. Lastly, we determined the ionic composition of the CSF, as this may reflect possible alterations in the ISF electrolyte balance associated with dysfunction of the BBB.In this study, a total of 20 rats were used. Male spontaneously hypertensive rats (SHR/NCrl) (n = 10) and Wistar Kyoto rats (WKY/NCrl) (n = 10) were purchased from Charles River Laboratories at 12 weeks of age. Animals were kept until 42 ± 1 weeks old. All rats were housed in groups and were fed standard laboratory food and water ad libitum. The animals were kept at room temperature on a 12-h light, 12-h dark schedule. All experiments were conducted in accordance with the ARRIVE guidelines and European Union guidelines for the care laboratory animals (Directive 2010/63/EU), and were approved by the Academic Medical Center Animal Ethics Committee.ex 460 nm; λem 515 nm) was used as a tracer to study blood–brain and blood–cerebrospinal fluid barrier leakage. The dye was dissolved in artificial cerebrospinal fluid  to a concentration of 40 mg/ml. DyLight®594 labelled Lycopersicon Esculentum (Tomato) Lectin (Vector Laboratories) was used to label the vascular endothelium.Fluorescein sodium salt  prior to the experiments in conscious rats. As blood pressures in SHR are known to increase from 6 weeks of age and are maintained during adulthood , the blo®, Alcon) was applied to prevent dryness during the surgical procedure. To study blood–brain and blood–cerebrospinal fluid barrier leakage, fluorescein sodium salt (0.5 kDa) was injected in the dorsal penile vein (40 mg/kg). The animal was turned in the prone position and the head was fixed in a stereotaxic frame (Stoelting). Subsequently, a small longitudinal skin incision was made at the animal’s back of the neck and 10% xylocaine (AstraZeneca B.V.) was applied as additional local anaesthesia. The subcutaneous tissues were removed and the neck muscles were separated in order to reach the cisterna magna. To measure the intracranial pressure (ICP), a 29-gauge stainless steel needle was inserted in the cisterna magna, which was connected to a pressure transducer (Edwards) by stiff polythene tubing. After monitoring the physiological baseline ICP, a second 29-gauge needle was inserted that was connected to a polythene catheter and a U-100 insulin syringe (BD Micro-Fine™). 30 min after intravenous injection of fluorescein, the first cerebrospinal fluid (CSF) sample was collected by gentle aspiration until an ICP of 0.5 mmHg was reached. A third 29-gauge needle connected to a polythene catheter and syringe was inserted into the cisterna magna. A second CSF sample was then collected 60 min after the fluorescein injection. After this, all needles were quickly removed from the cisterna magna and the CSF samples were stored at − 80 °C. The animal was turned into the supine position. DyLight®594-labelled L. esculentum lectin (1 mg/kg) was injected into the bloodstream via the dorsal penile vein and was allowed to circulate and bind the vascular endothelium for 3 min. Prior to the perfusion fixation, 200 µl of heparin solution (LEO®) was injected intravenously to prevent the formation of blood clots. The chest was opened and a blood sample was taken from the vena cava. The blood samples were centrifuged for 3 min at 3000 rpm and the plasma was stored at − 80 °C. Animals were then transcardially perfused with 60 ml heparinised phosphate buffered saline (PBS) and subsequently with 60 ml 4% paraformaldehyde (PFA). The brains were carefully dissected from the skull, weighed, and cut into three coronal pieces using a rat brain slicer matrix (Zivic Instruments). The front part, containing the olfactory bulb and part of the cortex, and cerebellum were snap frozen in liquid nitrogen and stored at − 80 °C until use. The middle part, containing the cortex and hippocampus, was post-fixed overnight in 4% PFA at 4 °C, and subsequently incubated in 30% sucrose for at least 3 days.Animals were weighed prior to the experimental procedure. All surgical procedures were performed under isoflurane inhalation anaesthesia (2–3.5%). After induction of general anaesthesia, animals were placed on a heating pad to maintain the core body temperature, which was monitored using a rectal thermometer (Greisinger Electronics). Ophthalmic ointment , which was subsequently placed in a LAMBDA Bio + spectrophotometer (PerkinElmer). Samples were considered as blood contaminated when the absorbance spectra of haemoglobin were above the detection limit of the spectrophotometer, and were excluded from further studies.® 8000, Roche Diagnostics). Calcium concentrations were measured by spectrophotometry, IgG levels by immunoturbidimetry, and total protein concentrations by turbidimetry .Undiluted CSF samples were used to determine concentrations of electrolytes, immunoglobulin G (IgG), glucose, and total protein. Sodium, potassium, and chloride concentrations were analysed using an ion-selective electrode, and glucose levels by hexokinase/glucose-6-phosphate dehydrogenase  in the refill phase.After insertion of a 29-gauge needle connected to a pressure transducer into the cisterna magna, the ICP was recorded using a PowerLab acquisition system. Chart™ software (ADInstruments) was used to visualise and analyse the data. To measure the baseline ICP, a stable ICP of at least 40 s was selected and averaged. The CSF production rate was determined by calculating the rate of refilling after withdrawal of the first CSF sample. For this, the following equation was used:Fluorescence spectrometry was used to quantify the amount of fluorescein in plasma, brain parenchyma and CSF. Plasma and CSF samples were diluted 10,000 and 50 times respectively, in order to be able to measure fluorescence within the range of the spectrophotometer . Brain samples comprised the front part of the brain, consisting of the olfactory bulb, cortex and striatum. Care was taken not to include the choroid plexus tissues from the third and lateral ventricle as these tissues may contain high concentrations of fluorescein, thereby interfering with the fluorescein measurements for the brain parenchyma. Brain samples were homogenised in RIPA buffer  using a Potter–Elvehjem tissue grinder, and an automated homogeniser (Kinematica) to obtain a fully homogenous suspension. Brain homogenates were centrifuged at 7800 rpm for 20 min, the supernatant was removed and used for fluorescence spectrometry.After incubation in 30% sucrose, brains were mounted on a cryostat specimen object disc and subsequently frozen at − 80 °C. Coronal slices of 100 µm were cut on a cryostat (Microm HM 560), transferred to a 48-well plate containing cryoprotectant solution  and stored at − 20 °C until use. Selected sections were collected on SuperFrost glass slides and were allowed to dry for 15 min. Slides were incubated in bisbenzimide  for 10 min to visualise the cell nuclei, and coverslipped using fluorescent mounting medium (DAKO). A confocal laser scanning microscope (Leica TCS SP8) was used to acquire brain overview and detailed z-stack images of 70 µm with respectively 10 and 20× objectives. Images were analysed in ImageJ using the automated ‘Blood vessel segmentation and network analysis’ macro developed by S. Tosi.p  < 0.05. All statistical analyses were done using GraphPad Prism software (version 7.03).All data values were reported as mean ± SEM. Data sets were tested for normality by the Shapiro–Wilk test. The group means of parametric data were compared using an unpaired Student’s t-test. The Mann–Whitney U test was applied to test differences between groups in non-parametric data sets. Fluorescein levels were measured in CSF at 30 min and 60 min. Since several samples were contaminated with blood, these data could not be tested with a repeated measurements ANOVA. Therefore, an unpaired Student’s t-test was used. Quantifications of a number of vascular parameters were analysed using repeated measurements ANOVA, followed by Bonferroni’s post hoc tests. Differences between WKY and SHR were considered significant at At 42 ± 1 weeks of age, spontaneously hypertensive rats (SHR) had significantly lower brain wet weights than normotensive Wistar Kyoto rats (WKY) (p ≤ 0.01). The body weight did not differ between these strains. Both systolic and diastolic blood, as well as the heart rate, were significantly elevated in SHR as compared to WKY (p ≤ 0.0001) . In addition, we found a small (< 1%), but statistically significant difference in sodium concentrations between SHR and WKY (p ≤ 0.05), and lower total protein concentrations in SHR (p ≤ 0.05). IgG levels in both strains were below the detection limit of 0.3 g/l. All other solutes were not different between the two groups Table .Table 2IIncreased fluid leakage from parenchymal and choroidal capillaries as a consequence of hypertension could potentially elevate intracranial pressure (ICP) and CSF formation. Therefore, we recorded the ICP prior to and during withdrawal of CSF from the cisterna magna. Figure The CSF production rate was estimated from the rate of refilling after withdrawal of CSF. Since the CSF is formed by the choroid plexus, together with a possible contribution from ISF formed across the BBB, both an increased BBB and BCSFB permeability could lead to an enhanced CSF formation. However, CSF production rates did not significantly differ between WKY and SHR, with values of 1.02 ± 0.21 µl/min for WKY and 1.21 ± 0.10 µl/min for SHR  into the bloodstream. The tracer was allowed to circulate for 60 min. After 30 and 60 min, CSF samples were collected from the cisterna magna, while plasma and brain samples were only obtained 60 min after infusion of fluorescein. Spectrophotometric analysis revealed that there were no significant differences in the fluorescein concentrations in both plasma (10.56 ± 0.34 mg/l in WKY vs. 9.80 ± 0.74 mg/l in SHR) and brain (0.11 ± 0.012 mg/l in WKY vs. 0.090 ± 0.013 mg/l in SHR) samples . In case differences in ventricular volume play a role, this is reflected herein. Yet, the compliance was the same in WKY and SHR (data not shown). Thus, refilling of the CSF induces the same gradual increase in pressure in both rat strains, irrespective of the ventricle volume. Another potential limitation is that withdrawal of a CSF sample might lead to a redistribution between ISF and CSF that affects the estimation of CSF production. Thus, the refilling of the CSF compartment after fluid withdrawal might to some extent have originated from the ISF compartment rather than the choroid plexus. Estimation of this contribution would require data on interstitial compliance and resistance for ISF-CSF fluid flow. There are two extreme cases: first, the ISF volume might not change at all in the time course of the experiment, because of low compliance or high resistance. Second, resistance is low enough to allow a rapid equilibrium between these compartments. In either case the presence of the ISF compartment would not affect the estimation of CSF production, although the interpretation of compliance differs. Yet, in intermediate cases of ISF-CSF convection dynamics, a two-compartment model would be needed to more carefully interpret these findings.14C-sucrose, which has been criticised [BBB and BCSFB integrity was further studied by measuring sodium fluorescein passage across these barriers using spectrophotometry. For the brain tissue samples, care was taken not to include choroid plexus tissue, as preliminary experiments showed that the choroid vascular and stromal tissue contained high concentrations of fluorescein. We used sodium fluorescein as it is described as the most suitable marker to detect more subtle changes in BBB and BCSF integrity because of its low molecular weight of 0.4 kDa. Fluorescein is also less toxic and only weakly binds to plasma proteins such as albumin when compared to Evans blue, which is still the most commonly used dye in BBB permeability studies . One houiticised , may plaiticised . In a stiticised , whole bCerebrospinal fluid fluorescein concentrations were significantly lower in SHR as compared to WKY, with roughly a twofold difference at the first collection point. As CSF production rates were similar in the two strains, the latter finding could not be explained by an elevated CSF turnover. While the data might seem to suggest actually a higher leakage of fluorescein in the WKY, a more likely explanation is the increased ventricle volume by about a factor of two in SHR in which the fluorescein dilutes , 20, 29.Chronic hypertension is associated with changes in the structure of the cerebral arteries both in humans and animal models such as the inward remodelling mentioned above , but datIn summary, we found no evidence for increased BBB and BCSFB permeability to a small compound in hypertensive rats. This was based on quantification of fluorescein leakage from blood into brain parenchyma and CSF. Also indirect consequences of increased fluid leakage, such as elevated ICP or CSF formation, were not evident. However, it remains to be established whether these barriers show differences in permeability to even smaller molecules, such as water, in hypertension. Finally, the brain microvasculature of SHR was not affected in terms of vessel volume, vessel diameter, and the number of branches. From this we conclude that several established features of mature SHR, including the lower brain weight, larger ventricular volume , 20, smaAdditional file 1: Figure S1. Number of branches, mean vessel diameter, and total length of cerebral capillaries. Number of branches per tissue volume imaged and mean vessel diameter did not differ between WKY (n=10) and SHR (n=10) in six different brain regions (panels A and B). Panel C shows the total length in SHR as compared to WKY. Values are mean ± SEM . cc, corpus callosum; Cx, cerebral cortex; CA3, field CA3 of the hippocampus; VM, ventromedial thalamic nucleus; VMH, ventromedial hypothalamic nucleus; Pir, piriform cortex.