Escherichia coli produces two major porins, OmpF and OmpC. MicF and MicC are small non-coding RNAs (sRNAs) that modulate the expression of OmpF and OmpC, respectively. In this work, we investigated factors that lead to increased production of MicC. micC promoter region was fused to lacZ, and the reporter plasmid was transformed into E. coli MC4100 and derivative mutants. The response of micC–lacZ to antimicrobials was measured during growth over a 6 h time period. The data showed that the expression of micC was increased in the presence of β-lactam antibiotics and in an rpoE depleted mutant. Interestingly, the same conditions enhanced the activity of an ompN–lacZ fusion, suggesting a dual transcriptional regulation of micC and the quiescent adjacent ompN. Increased levels of OmpN in the presence of sub-inhibitory concentrations of chemicals could not be confirmed by Western blot analysis, except when analyzed in the absence of the sigma factor σE. We suggest that the MicC sRNA acts together with the σE envelope stress response pathway to control the OmpC/N levels in response to β-lactam antibiotics.Antibiotic resistant Gram-negative bacteria are a serious threat for public health. The permeation of antibiotics through their outer membrane is largely dependent on porin, changes in which cause reduced drug uptake and efficacy.  Escherichia coli, the channels of the general porins OmpF and OmpC, are size restricted, and show a preference for passage of hydrophilic charged compounds, including antibiotics such as β-lactams and fluoroquinolones. Second, constitutive tripartite RND (resistance–nodulation–cell division) efflux pumps, such as the AcrAB–TolC pump of E. coli, play a major role in removing antibiotics from the periplasm [Enterobacteriaceae generally exhibit porin loss and/or increased efflux, which both contribute to reduce the intracellular accumulation of antibiotics below the threshold that would be efficient for activity [Antibacterial resistance is broadly recognized as a growing threat for human health ,2,3. As eriplasm . Importaeriplasm . Not suractivity ,10,11.ompF transcription, whereas at high osmolarity, OmpR-P represses ompF transcription and activates ompC transcription. This differential regulation of OmpF and OmpC is consistent with that in high osmolarity environments, such as in a host where nutrients are abundant, the small pore porin OmpC is predominant, thus limiting the uptake of toxic bile salts; whereas in low osmolarity environments where nutrients are scarce, the large pore porin OmpF is expressed [Given the importance of the OM in controlling the uptake of beneficial as well as toxic compounds, one can expect that the expression of porins depends on environmental factors, and is well-coordinated at the transcriptional and post-transcriptional levels. Best studied transcriptional regulators are the IM sensor kinase EnvZ and its cognate response regulator OmpR . EnvZ auxpressed . EnvZ–Omxpressed  and CpxAxpressed  are the xpressed , and mutxpressed   and the start codon of the ompF mRNA, thus preventing translation initiation [ompC mRNA [ompN gene that encodes a quiescent porin homologous to OmpF and OmpC [ompN–micC and ompC–micF, and the co-induction of ompC and micF under specific conditions , it has been suggested that ompN and micC could also be subjected to dual regulation [ompC mRNA is targeted by multiple sRNAs MicC [The post-transcriptional repression of OmpF by the small regulatory RNA (sRNA) MicF has been discovered in 1984 ,17,18. Titiation . Positivitiation , SoxS initiation , and Maritiation . The 109mpC mRNA . Interesand OmpC . Due to gulation . With thNAs MicC , RybB [2NAs MicC , RseX [2NAs MicC , and IpeNAs MicC ,29,30. TmicC and ompN in E. coli MC4100 cells grown under a series of external conditions by using lacZ transcriptional fusions and β-galactosidase assays. We optimized the assay by using 96-well microtiter plates, and screened the entire collection of compounds provided by the Biolog Phenotype MicroArraysTM for bacterial chemical susceptibility, in order to extend the range of putative inducing cues. Results showed that high concentrations of carbapenems and cephalosporins, two clinically relevant classes of β-lactams, induce both micC and ompN. Then, the impact of carefully chosen inducing conditions on the expression levels of OmpC and OmpN was tested by Western blotting with appropriate antisera. Because the OmpN protein was undetectable in the presence of mild antibiotic stress conditions, we reasoned to investigate the transcription of micC and ompN in a series of MC4100 derivatives carrying null mutations or multicopy plasmids in order to identify putative transcriptional regulators. Interestingly, we found that OmpN was specifically expressed when the envelope stress sigma factor σE was depleted by the overexpression of the anti-sigma RseA, or when the hns gene encoding the histone nucleoid structuring protein, H-NS, was inactivated. Finally, we examined the functional relevance of OmpN as compared to OmpC and OmpF, with respect to drug translocation.In this work, we first examined the transcription of All these data are discussed considering the current knowledge on the Gram-negative envelope stress response pathways.micC–lacZ transcriptional fusion in MC4100 cells grown under a series of growth conditions and β-galactosidase assays. First, we selected a number of representative growth conditions, some of which are sensed by known regulatory factors: growth phase (stationary phase accumulates RpoS), exposure to heat shock, high osmolarity (activates EnvZ–OmpR), iron or nitrogen starvation, or exposure to chemicals, such as salicylate (activates MarA), paraquat (activates SoxR/S), or different classes of antibiotics (β-lactams and fluoroquinolones). To determine whether MicC and OmpN are co-regulated, the β-galactosidase activity of an ompN–lacZ transcriptional fusion was also tested in MC4100 grown under the same conditions. These preliminary assays showed that growth conditions that are known to induce specific regulatory factors, such as RpoS, EnvZ–OmpR, MarA and SoxR/S, do not significantly affect the activity of the micC– and ompN–lacZ fusions, suggesting that the expression of MicC and OmpN is not controlled by these regulators. Instead, these assays allowed the identification of β-lactams potent inducers of both the micC– and ompN–lacZ fusions. As an example, TM plates (Biolog PM11 to PM19) for bacterial chemical susceptibility  or cephalosporins   b. Intereefepime) b.ompC expression was first examined by monitoring OmpC protein levels directly. MC4100 was transformed with the MicC overexpression plasmid (pSD01) and the corresponding empty vector (pDrive). Cultures were induced with IPTG to allow MicC expression, OM extracts were prepared, and levels of OmpC were analyzed by Western blot (WB) with specific anti-peptide antibodies. As shown in ompC expression. As noted in the section above, high micC–lacZ activities were obtained in the presence of high concentrations of compounds, which were detrimental for the cell growth. Therefore, MC4100 was cultured in the presence of sub-inhibitory concentrations of inducing compounds—namely biapenem, imipenem, ertapenem, ceftazidime, cefepime, and chlorpromazine HCl—in order to obtain exponentially grown cells and examine their effect on OmpC protein levels. As shown in The effect of MicC overexpression on micC and ompN, we also tested whether OmpN expression was increased in the same samples. As a control, MC4100 was transformed with the OmpN overexpression plasmid (pSD04) and the corresponding empty vector (pTrc99A). Cultures were induced with IPTG to allow OmpN expression; OM extracts were prepared and tested for OmpN expression by WB. For this, we generated antibodies against a peptide in loop 7 present in OmpN, but absent in OmpF and OmpC. A single protein of about 39 kDa was detected in the OM extracts of MC4100 (pSD04), but not in that of MC4100 (pTrc99A), suggesting that the detected band is OmpN without cross-reactivity to other porins, and that OmpN production from the chromosome is undetectable  was opposite to that of MicC (repressor of OmpC) under most of the tested conditions . Becauseses MicC a. WhetheE. coli and Salmonella. Examples include the RyhB sRNA as a member of the iron-responsive Fur regulon [E [2+-responsive PhoP/Q regulon [S [E on micC and ompN induction. Constitutive activation of the Cpx stress response, by multicopy plasmids expressing an autoactivated CpxA [E upon the overexpression of its cognate anti-sigma RseA, the activity of both the micC– and ompN–lacZ fusions resulted in a 3–4-fold increase  in an hns mutant  (OmpF− OmpC+), W3100ΔompC(pTrc99A) (OmpF+ OmpC−), W3100ΔompFΔompC(pTrc99A) (OmpF− OmpC−) and W3100ΔompFΔompC(pSD04) (OmpF+ OmpC− OmpN+) was monitored in the absence and in presence of representative β-lactams added at inhibitory concentrations, with regards to their capacity to inhibit the reduction of the viability dye resazurin [E. coli expressing either OmpF or OmpC, but not OmpN, was significantly inhibited upon exposure to β-lactams, suggesting that OmpN is not competent for translocation of this class of antibiotics , suggesting that OmpN channels are able to bind and transport porin-dependent group A colicins across the OM of E. coli (data not shown). This also points to the different mechanism of antibiotic versus colicin translocation through OM porin channels.OmpF and OmpC channels are also used for the translocation of various colicins across the OM of E. coli . We examE. coli, the majority of which are conserved in Salmonella and other closely related species. About one-third of the reported sRNAs repress synthesis of OM proteins. Evidence for important roles of sRNAs in this post-transcriptional regulation was previously established by the fact that the loss of Hfq, the sRNA chaperone [sRNAs have become important players in bacterial gene regulation. To date, systematic genome-wide searches have led to the identification of approximately 80 sRNAs in haperone , resultshaperone ,36,37,41E. coli, the conserved Hfq-associated sRNA, MicC, was identified as a repressor of the synthesis of OmpC [ompC mRNA [omp target sequences in Salmonella, K. pneumoniae, and Enterobacter spp. However, major questions such as (i) environmental conditions and/or intracellular regulatory pathways that promote maximal expression of MicC; (ii) the co-regulation of MicC and OmpN; (iii) the impact of such regulation on antibiotic susceptibility; and (iv) the prevalence of MicC/OmpN in MDR clinical isolates remain unanswered. In this work, we used lacZ transcriptional fusions and β-galactosidase assays to show that the expression of micC and ompN is co-regulated in response to antibiotic stress. In particular, β-lactam antibiotics are among the most potent inducers of both micC and ompN. Interestingly, we found that expression of OmpN from a plasmid could not restore the susceptibility of an E. coli porin-less strain to β-lactams. In addition, other studies have demonstrated that strains expressing OmpN, but not OmpF or OmpC, were less susceptible to β-lactams [In  of OmpC ,54. MicCmpC mRNA . Many pa-lactams ,55.E and H-NS are two major negative regulators of MicC/OmpN. σE is widespread among pathogenic and non-pathogenic bacteria, and becomes activated when bacterial envelope homeostasis is perturbed due to misfolding of OM proteins in the periplasm, or severe OM damage by external stresses [omp mRNAs upon activation of the σE envelope stress response [E envelope stress response, RybB nor any other Hfq-dependent sRNA could be responsible for ompN silencing. This suggests that ompN is not subjected to sRNA post-transcriptional regulation. On the other hand, H-NS is a major component of the bacterial nucleoid, and has pleiotropic effects on gene expression, genome stability, and DNA recombination. Previous work has shown that H-NS was required for full expression of OmpF, and that this involves a role for H-NS in repressing the expression of MicF sRNA [Our results also identified that envelop stress sigma factor σstresses . In bothresponse ,57. AlthicF sRNA . Our resE. coli strains and plasmids used in this study are listed in E. coli MC4100 and derivatives were used for lacZ reporter gene assays and protein expression analysis. Knockout mutants were generated by P1 transduction from different sources and cured by using the FLP helper plasmid pCP20 to remove the kanamycin resistance cassette [E. coli W3110 and derivatives were used for translocation assays.All the cassette . Strains® Genomic purification kit  according to the manufacturer’s instructions, and used as a template for all PCR-amplifications. micC– and ompN–lacZ transcriptional fusions were constructed in the promoter-less lacZ containing vector pFus2K [TTACGTATCGGATCCTCGGGGAGTGAAAACATCCT-3′) and SD2 (5′-GCGGATCCCCGCGCAGAATAACGTAT-3′), which contain BamHI restriction sites (underlined) for classic restriction/ligation cloning into BamHI restricted pFus2K (micC–lacZ (pSD02). Because the transcription start of ompN is only based on promoter prediction, the entire intergenic region between MicC and OmpN was PCR-amplified by using the primer pair SD3 (5′-GAGCTCGCATGCGGATCCTGAATAAATCCTTTAGTTATT-3′) and SD4 (5′-CAGGACTCTAGAGGATCCCCGCGCAGAATAACGTAT-3′). This generated a 227 nt fragment, which contained BamHI restriction sites (underlined) and extension homologous to BamHI restricted pFus2K for cloning using the In-Fusion ™ cloning kit , in the orientation of ompN–lacZ (pSD03) (AGGCTCGAGAAGCTT AGATGCTGCAGCTGAATTTG-3′) inserted into the pDrive vector restricted with BamHI and HindIII under the control of an IPTG inducible promoter by using the In-Fusion ™ cloning kit (pSD01) (CATGGAATTCATGAAAAGCAAAGTACTGGCAC-3′) and SD7 (5′-CGACTCAGAGGATCCTTAGAACTGATAAACCAGACCTAAAGCG-3′) that contain the EcoRI and BamHI restriction sites respectively. pSD05 contains rseA, which was PCR-amplified by using the primer pair SD8 (5′-GGTATTAGCCATGGAGAAAG-3′) and SD9 (5′-CTGTGCCGCCCCGGGTACTTTCTG-3′) that contain the NcoI and SmaI restriction sites, respectively. All the plasmid constructs were confirmed by sequencing.Genomic DNA was extracted from MC4100 by using the Wizardr pFus2K . A 184 nd pFus2K  in the o (pSD03) . For ove (pSD01) . Recombiβ-Galactosidase activity was routinely assayed on log-phase bacterial cultures, as described by Miller .5 cfu in 200 µL containing two-fold serial dilutions of each compound. The MIC was defined as the lowest concentration of each compound for which no visible growth was observed after 18 h of incubation at 37 °C. Each assay was systematically performed in triplicate. The average of three independent assays was considered in μg/mL.MIC values of antibiotics were determined by the microdilution method in Mueller Hinton II broth (MHIIB) (Sigma). Susceptibilities were determined in 96-well microtiter plates with an inoculum of 2 × 10TM Tecan for absorbance readings. Briefly, strains were grown to an OD600 of 0.6. Cultures were diluted to an OD600 of 0.2, and added (200 µL) to the Phenotype MicroArrays ™ test plates (Biolog plates PM11 to PM19)  (4 mg/mL). Curves of OD420 were plotted over the time (30 min) to identify optimal inducers (600 of 0.2) were added. The plates were incubated at 37 °C inside the reader, and curves of OD420 were plotted over the time (6 h). The obtained readings in presence of ONPG were used to calculate Miller units and for determining the fold change in lacZ activity, relatively to standard growth conditions. Experiments were independently repeated at least three times.The standard β-galactosidase assay was adapted for compound screening by using 96-well microtiter plates and a SUNRISEto PM19) . After oinducers . Similarinducers , then cemicC/ompN induction conditions determined by the β-galactosidase assay. The cells were washed and concentrated 12.5 fold in 20 mM sodium phosphate buffer (pH 7.4), and lysed by one passage through a cell disruptor (Constant Systems) at 2 kbar. After removal of cell debris by centrifugation  the supernatant was ultracentrifuged  to collect the whole cell envelopes. These were resuspended in 0.3% N-laurylsarcosinate, and incubated for 30 min at room temperature to solubilize the IM. The insoluble OM extracts were pelleted by centrifugation .Bacterial cultures (50 mL), grown in the presence or absence of stress, were incubated according to the optimum OM were prepared as described above, resuspended in 20 mM sodium phosphate buffer (pH 7.4), and kept at −20 °C until use. All samples were diluted in Laemmli buffer  and heated for 5 min at 100 °C before loading. Samples corresponding to 0.2 OD units were separated on 10% SDS-PAGE. To better resolve OmpF and OmpC, 4 M urea was added to the running gel. Proteins were either visualized after straining with Coomassie Brilliant Blue R250 or transferred onto nitrocellulose blotting membranes . Primary rabbit antibodies and dilutions were: TolC (1:5000), OmpFd (1:5000), OmpC1 (1:5000), and OmpN (1:1000). Goat anti-rabbit HRP-conjugated secondary antibodies and Clarity Max™ Western ECL Blotting substrates  were used for detection. Protein bands were visualized with a molecular imager Chemidoc-XRS System (Bio-Rad) and quantified using the Image Lab software (Bio-Rad) by using the TolC band as a standard. Peptide-specific antibodies were used to avoid cross-detection of OmpC and OmpN: OmpC1 antibodies are directed against KNGNPSGEGTSGVTNNG amino acid sequence present in loop 4 , and Omp® Cell Viability Assay (Promega) was used to determine the metabolic inhibition of cells expressing single porins in the presence of clinically relevant antibiotics as an indicator of porin permeation properties [ompN (expressing OmpN). Overnight cultures were diluted to 1:100 and grown until mid-log phase in MHIIB. Strain containing pTrc99A-ompN was grown in the presence of Amp, and OmpN expression was induced with 0.1 mM IPTG for 1 h at 37 °C. When tested for β-lactam permeation, cultures were diluted to 107 cells/mL in fresh MHIIB containing 10% of CellTiter Viability Reagent. For strains containing pTrc99A-ompN, MHIIB was supplemented with 0.1 mM IPTG, and β-lactamase inhibitors tazobactam and clavulanic acid (4 µg/mL each), to inhibit the activity of the plasmidic AmpC, but not Amp. Microtiter plates (96 well) with black sides and a clear bottom were preloaded with 10 μL of 20× concentrated antibiotic solutions. For each antibiotic, the final concentration in the wells was defined as the maximal concentration that did not alter the metabolism of the porin-less strain, i.e., ertapenem, 0.125 µg/mL; meropenem, 0.125 µg/mL; cefotaxime, 0.0625 µg/mL. Cells (190 µL) were then added to separate wells. Control wells also contained cells with resazurin, but no antibiotic, and resaruzin with antibiotics without cells. Fluorescent signals of resorufin were measured with a TECAN Infinite Pro M200 spectrofluorometer (excitation wavelength 530 nm and emission wavelength 590 nm). Kinetic readings were taken at 37 °C every 10 min for 300 min. The % of metabolic inhibition for each strain exposed to each antibiotic was calculated from the measured difference of relative fluorescence units (RFUs) in the presence (RFUATB) as compared to in the absence (RFUMAX) of antibiotic. All experiments were performed at least four times.Resazurin-based CellTiter-Blueoperties . These aE. coli overnight cultures. Serial two-fold dilutions of ColE2 or ColE3 (laboratory collection), were spotted in 5 µL drops onto the lawns, and the plates were incubated overnight at 37 °C. Efficiencies of killing were taken as the reciprocal of the highest dilution that gave complete clearing of the lawn.LB agar plates were overlaid with 4 mL of soft agar  containing 100 µL of Enterobacteriaceae. Further work will analyze how external stresses, such as β-lactams, interact with the σE envelope stress response and H-NS in laboratory strains, as well as in MDR clinical isolates.Altogether, these data suggest that exposure to β-lactams induce a complex stress response to reduce the translocation of these antibiotics across the OM in


The composition of the cerebrospinal fluid (CSF) is not homogeneous, and concentrations of proteins from different origins diverge among ventricular, cisternal and lumbar CSF fractions. Concentrations of blood-derived proteins increase and of brain-derived proteins decrease from ventricular to lumbar fractions. We studied whether the origin of the CSF portion analysed may affect results in CSF analysis for dementia.In 16 geriatric patients with suspected normal pressure hydrocephalus  a lumbar spinal tap of 40 ml was performed. The CSF was sequentially collected in 8 fractions of 5 ml with the 1st fraction corresponding to lumbar CSF, the 8th to cisterna magna-near CSF. Fractions were analysed for total protein, albumin, Tau protein (Tau), phosphorylated Tau (pTau), Amyloid beta 1–42 (Aβ1–42), Amyloid beta 1–40 (Aβ1–40), and the Aβ1–42/Aβ1–40 ratio.The concentrations of total protein and albumin increased from cisternal to lumbar fractions due to diffusion-related accumulation from blood to CSF with significantly higher concentrations in fraction 1 compared to fraction 8. The concentrations of Tau showed a non-significant trend towards decreased values in lumbar samples, and pTau was slightly, but significantly decreased in the lumbar fraction 1 [26.5 (22.5/35.0) pg/ml] compared to the cistern-near fraction 8 [27.0 (24.2/36.3) pg/ml] . Aβ1-42, Aβ1-40, and the Aβ1-42/Aβ1-40 ratio remained almost constant.According to the flow-related diverging dynamics of blood-derived and brain-derived proteins in CSF, the concentrations of Tau and pTau tended to be lower in lumbar compared to cisternal CSF fractions after a spinal tap of 40 ml. The differences reached statistical significance for pTau only. The small differences will not affect clinical interpretation of markers of dementia in the vast majority of cases.The online version of this article (doi:10.1186/s12987-016-0039-9) contains supplementary material, which is available to authorized users. Normal pressure hydrocephalus (NPH) is characterized clinically by the triad of gait disturbance, bladder incontinence, and later dementia. Cerebral imaging shows ventricular dilation, whereas the subarachnoid space on both sides of the superior sagittal sinus is comparatively small . Unlike Many compounds do not distribute homogeneously in the CSF spaces, but have ventriculo-lumbar or lumbo-ventricular gradients. Compounds originating in the brain  generally have higher ventricular than lumbar CSF concentrations, whereas compounds originating from the meninges  have higher lumbar than ventricular levels, and the concentrations of blood-derived proteins such as albumin increase from the ventricular to the lumbar CSF space –8. In paA diagnostic or therapeutic lumbar spinal tap of 40 ml was performed on 16 patients with suspected or documented normal pressure hydrocephalus . All patients suffered from cognitive impairment. In 15 of the 16 patients an abnormal gait, and in 10 patients bladder incontinence were documented. All patients had an abnormal cranial computer tomography (CCT) scan with wide ventricles compared to the width of the sulci. Moreover, 14 patients had crowding of the gyri at the vertex with small sulci close to the superior sagittal sinus, and 14 patients had a corpus callosum angle below 90°. Four patients (including a patient who received three lumbar punctures) clearly improved after the spinal taps, and in three patients a small clinically non-significant improvement of either gait or cognition were noted. None of the patients studied had a ventriculoperitoneal shunt or external ventriculostomy. The treating physicians recommended ventriculoperitoneal shunting to the 4 patients with clear clinical improvement after the spinal tap. Because of their advanced age, these patients and/or their relatives refused surgery, as they feared the risks.The CSF was sequentially collected in eight fractions of 5 ml in polypropylene tubes and was transported to the laboratory within 1 h for analysis. One set of CSF fractions was available from 15 patients. Three sets of CSF fractions were available from one patient with documented normal pressure hydrocephalus, who underwent repeated lumbar punctures as part of his therapy.g, aliquots of each fraction were stored at −80 °C for the determination of markers of dementia, protein and albumin concentrations.Albumin, immunoglobulins IgG, IgA and IgM were determined by nephelometry, and CSF leukocytes were counted manually in a Fuchs-Rosenthal chamber. Albumin and immunoglobulin CSF/serum quotients  were calculated in fraction 1. The CSF protein contents were measured by nephelometry using Gesamteiweiß UC Standard FS . After centrifugation at 200×Tau protein (Tau), tau protein phosphorylated at threonine 181 (pTau), Amyloid beta 1–42 and Amyloid beta 1–40 (Aβ1–42 and Aβ1–40) were measured by commercially-available immunoassays , and the Aβ1–42/Aβ1–40 ratio was calculated. The raw data were uploaded as Additional file rS. The concentrations of the compounds measured in fractions 1 and 8 were compared by the two-tailed non-parametric paired Wilcoxon signed rank test using Gaph Pad Prism software, as most parameters were not normally distributed. P values <0.05 were considered statistically significant. The study was approved by the Ethics Committee of the Medical Faculty of the Georg-August University Göttingen, Germany, and each participant gave written informed consent to participate in this study.Correlation of measured values between fraction 1 and fraction 8 of each individual patient was assessed by Spearman's rank correlation coefficient −3) probably because of an impaired circulation of the CSF in the spinal canal: one of these patients had prior surgery because of stenosis of the lumbar spinal canal, one had a history of two fractures of lumbar vertebrae, and one suffered from lower back pain with hardening of muscles, suggesting degenerative spine disease. The concentrations of the parameters measured in fractions 1 and 8 of each individual patient were strongly correlated . The CSF protein contents were lower in the cistern-near fraction 8 than in the lumbar fraction 1  .The CSF leukocyte counts were normal in all patients studied, and the Reiber–Felgenhauer diagrams of albumin- and immunoglobulin-CSF/serum quotients  indicated absence of inflammation in all patients studied. Three patients had an elevated CSF-serum albumin ratio  indicating a small decrease of pTau from cisternal to lumbar CSF. Tau concentrations also were slightly higher in CSF fraction 8 than in lumbar CSF, the difference, however, failed to reach statistical significance (Table pTau concentrations in the CSF fraction 8 were slightly, but significantly higher than in lumbar CSF (medians 27.0 versus 26.5 pg/ml, ce Table . No diffIn the patient with 3 consecutive spinal taps in 11 months the intra-individual variation of the determined markers of neurodegenerative disease was low. Concentrations of Tau in the lumbar fraction 1 ranged from 148 to 176 pg/ml, of pTau from 25.5 to 28.0 pg/ml, of Aβ1–42 from 859 to 933 pg/ml, of Aβ1–40 from 8815 to 9731 pg/ml, and the Aβ1–42/Aβ1–40 ratio ranged from 0.088 to 0.106.The total volume of CSF in adults is approximately 140 ml with a wide variation dependent on age, and volume of the brain and medulla spinalis in relation to the size of the cranial cavity and the spinal canal. The volume of the spinal subarachnoid fluid is 30–80 ml , 10, i.eIn agreement with flow-related diverging dynamics of blood-derived and brain-derived proteins in CSF , we founThe median total protein content and the albumin concentrations were 1.23- and 1.25-fold higher, respectively, in fraction 1 than in fraction 8. This reflects a relevant influx of proteins from non-neuronal sources into the CSF in the spinal canal. In a previous study of 21 patients with NPH, 10 fractions of approximately 3 ml were drawn, and the albumin concentrations were 1.5-fold higher in fraction 1 than in fraction 10 . Since tThe rostro-caudal gradient of pTau and Tau in this and other studies on NPH suggests that both proteins are mainly brain-derived. This gradient, however, may not be present in all diseases. The differences between pTau and Tau concentrations in lumbar and cistern-near CSF were small, and the Aβ1–42 and Aβ1–40 concentrations and Aβ1–40/Aβ1–42 ratios in lumbar and cistern-near CSF were almost equal. Therefore, all fractions of CSF after a spinal tap of 40 ml appear to be equally suitable for the assessment of markers of dementia in CSF.


Posidonia oceanica (PO), a dominant Mediterranean seagrass, were produced by simple melt mixing and characterized in terms of thermal stability, morphology and rheological/mechanical properties. In view of their potential application in marine environments, degradation of the developed composites was evaluated under simulated and real marine environmental conditions for 1 year. Using 10 wt % of acetyl tributyl citrate (ATBC) as a plasticizer, smooth processing was achieved for up to 30 wt % of PO fibers, despite the reduction of the melt fluidity observed with increasing fiber loading. The tensile modulus slightly increased (from 2 to 2.4 GPa) while the tensile strength and the elongation decreased  by increasing the PO fiber content from 0 to 30 wt %. Interestingly, the impact resistance of the composites increased with the increasing of the PO content: the Charpy’s impact energy increased from 3.6 (without fiber) to 4.4 kJ/m2 for the composite with 30 wt %. The results of the aerobic biodegradation under simulated marine conditions showed that the presence of PO fibers favored the physical disintegration of the composite increasing the biodegradation rate of the polymeric matrix: after 216 days, the composite with 20 wt % PO fibers showed a biodegradability of about 30% compared to 20% of the composite without fibers. Under real marine conditions, the specimens containing PO fibers showed higher weight losses and deterioration of tensile properties compared to those without fibers. Presumably, biodegradation occurred after colonization of the specimen, and the specimens with 20 wt % PO fibers showed well-developed biofilm consisting of bacteria and fungi on the surface after only 3 months of incubation in marine sediments, unlike the no-fiber specimens. Consequently, the persistence of an adequate mechanical performance for a relatively long period (1 year), due to a moderate rate of biodegradation in the marine environment, make the developed PHBV/PO composites particularly suitable for the production of relatively low-cost and biodegradable items which are usable in the sea and/or sand dunes, increasing the market opportunities for biopolymers such as PHBV and, at the same time, finding an eco-sustainable valorization for the PO fibrous residues accumulated in large quantities on Mediterranean beaches, which represents a problem for coastal municipalities.In order to produce sustainable, bio-based and highly biodegradable materials, composites based on poly (PHBV) and fibers of  Posidonia oceanica (PO), have also been used as filler in the production of “green” composites [Posidonia oceanica is a Mediterranean endemic species that covers 60% of the seabed from 0 to 40 m depth [Posidonia oceanica fibers is similar to that of lignocellulosic materials from terrestrial plants consisting mainly of cellulose, hemicellulose and lignin. Large amounts of this material in the form of balls (egagropili) as well as whole plant fragments are deposited along many coastal beaches after storms. Stranded Posidonia oceanica residues play an important ecological role for the protection of coasts from erosion [Posidonia oceanica wastes in compost production, up to a maximum of 20 wt % by fresh weight of the composting mixture. However, the high content of sand and salinity represent the main obstacles to the large use of this biomass for composting. Thus, the search for sustainable and cost-competitive alternatives to landfilling or composting is strongly encouraged.The world petro-plastic production reached about 335 million tons (Mt) in 2016 and is expected to double again over the next 20 years ,5. Polyhmposites ,25,26,27mposites . Posidon m depth . The che erosion , but thePosidonia oceanica were produced by melt mixing, processed by injection extrusion and characterized in terms of processability, rheological properties, thermal stability and mechanical performance. In order to improve the processability and the ductility of PHBV the addition of a plasticizer was necessary. For this reason, acetyl-tri-n-butyl citrate (ATBC) was used, being one of the most efficient plasticizers proposed for poly(hydroxybutyrate) (PHB) and its blends with PLA [In the present work, composites based on poly and fibers of with PLA ,32,33,34with PLA , acceptewith PLA  and is d® . It is a poly (PHBV), with 5 wt % valerate content. PHBV is characterized by a melting point of 145–150 °C, a density of 1.25 g/cm3, and a melt flow index of 10–20 g/10 min . Posidonia oceanica (PO) balls (egagropili) were collected on a beach of the Ligurian Sea . They were washed with tap water to eliminate sand and other contaminants and then dried at 50 °C in an electric oven for 24 h. The ensuing material was milled using a lab-scale mill and sieved with a 500 µm sieve. The final length of the fibers was in a 1.5–2 mm range and the aspect ratio was in the 7–10 range. ATBC from Sigma Aldrich  was selected as plasticizer for PHBV. In addition, it is a bio-based, biodegradable and an almost colorless/odorless oily liquid. Calcium carbonate OMYACARB®2 provided by OMNYA®  with fine grain size distribution (12 μm) was used as filler in order to reduce the cost of the final product and facilitate the removal of the product from the mold.The thermoplastic matrix used in this work is PHI002™ supplied in pellets from Naturplastw/w PHBV/CaCO3 as polymeric matrix and 10 wt % ATBC on the total weight. The nomenclature of the samples was as follows: PCA for the composite without PO fibers (PHBV/CaCO3/ATBC) and PCA10, PCA20 and PCA30 for the composites containing the different fiber loadings: 10, 20 and 30 wt % of PO fibers, on the total composite weight, respectively. The composites were prepared by mixing the different components and then the ensuing mixtures were processed in a Thermo Scientific Haake Minilab Micro-compounder (Minilab), a co-rotating conical twin-screw extruder. The extruder operating conditions adopted for all the formulations are reported in Composites containing 10, 20, and 30 wt % PO fibers, with respect to the total weight, were produced using 95/5 The extruded composite filaments were cut to obtain pellets used for the subsequent thermal characterization and the lab-scale aerobic biodegradation test in seawater. For each formulation, specimens for the tensile test  and for the Charpy’s impact test (bars 80 × 10 × 4 mm) were produced by feeding the molten material directly from the Minilab to a Thermo Scientific HAAKE MiniJet II . Dog-bone specimens were also used for the degradation test in natural marine mesocosms.3 s−1. The energy which is dissipated during fracture is calculated from the height of the pendulum weight before and after impact. The dissipated energy is reported as the impact toughness per unit fracture cross-section (J/m2).Thermal properties of the starting materials and PHBV/PO composites in the form of pellets were evaluated by thermogravimetric analysis (TGA). Thermogravimetric measurements were carried out on about 20 mg of sample using a Q500 TGA , under nitrogen flow (100 mL/min), at a heating speed of 10 °C/min from room temperature to 600 °C. In addition, the isothermal stability of the raw materials at the processing conditions (170 °C) under nitrogen for 5 min has been also evaluated using an isothermal mode. The TGA measurements were carried out in duplicate. Tensile tests were performed on the injection molded Haake Type 3 (557–2290) dog-bone tensile bars of composites in accordance with ASTM D 638. Stress–strain tests were carried out at room temperature, at a crosshead speed of 10 mm/min, by an Instron 5500R universal testing machine  equipped with a 10 kN load cell and interfaced with a computer running the Testworks 4.0 software . Impact test was carried out on V-notched specimens using a 15 J Charpy pendulum  following the standard method ISO 179:1993. In the Charpy test, the load is provided by the impact of a weight at the end of a pendulum. A crack starts at the tip of the V-notch and runs through the specimen. The material deforms at a strain rate of typically 10For each mechanical test, at least five replicates were tested for each sample. Morphological analysis was carried out by scanning electron microscopy (SEM), using a JEOL JSM-5600LV  both on the cross-section of the dog-bone tensile specimens fractured in liquid nitrogen and on the cross-section of the specimens fractured after the tensile tests in order to evaluate the dispersion of the fibers into the polymeric matrix and the fiber/matrix interactions, respectively.In view of the possible application of the PHBV/PO composites in marine environments, aerobic biodegradation and degradation tests were performed under simulated marine conditions and in real marine mesocosms.2 evolved from bioreactors containing the sample (pellets) placed at the seawater/marine sediment interface. The setup of the system used is shown in The aerobic biodegradation of the composites in simulated marine conditions was evaluated in accordance with a modified version of the ASTM D6691 method based on the measurement of the COa and b contained 250 mL of a 5 M NaOH solution to remove CO2 from the air and the flask c 200 mL of a 0.04 M Ba(OH)2 solution, used to indicate the complete removal of CO2 from the air. The flask e contained 40 mL of a 0.1 M Ba(OH)2 solution to absorb the CO2 developed in the bioreactor during the degradation process. The amount of CO2 developed was calculated by the consumption of Ba(OH)2 in the flask e, determined by titration, carried out twice a week, with 0.1 M HCl using phenolphthalein as indicator. The amount of CO2 developed in each bioreactor was calculated according to the following equation:CO2 is the CO2 evolved from the bioreactor, VBa(OH)2 is the volume in L of Ba(OH)2 (40 mL) in flask e at the beginning of the run, VHCl is the volume in L of HCl needed for titration of Ba(OH)2 at the end of run, CBa(OH)2 and CHCl are the concentration of Ba(OH)2 and HCl, respectively, in mol/L, 44 is molecular weight of CO2. Filter cellulose paper (Whatman n.40) was used as positive control and flasks containing only seawater and sediment as blanks. The biodegradability of each sample was calculated as percentage (corrected for the blank flask emissions) of the overall theoretical amount of CO2 (ThCO2) that could be released, calculated on the basis of the initial organic carbon content of the sample, as shown below:The bioreactor contained 100 g of marine sediment (fine sand), 150 mL of sea-water and about 300 mg of composite sample (pellets). Seawater and the marine sandy sediment were collected in a coastal area near Rosignano Solvay , at 50 cm depth . The test was conducted at room temperature in 300 mL flasks connected to each other with tubes where an air-flow rate of about 100–120 mL/min was fed through a pump. The flasks Being an innovative natural fiber for composites production, and in order to evaluate the effect of fiber on composite degradation, the test in marine water was carried out even on PO fibers. For each type of sample, the test was quadrupled and the mean values were considered.3) with continuous natural seawater flow equipped following a protocol, previously established for successfully growing seagrasses [The changes in the weight and in the mechanical properties of dog-bone tensile specimens were evaluated over the time in an outdoor marine culture system, located at the Mariculture Center of Rosignano Solvay  . The system consisted of tanks  and a scanning electron microscope  to check for the formation of biofilm and the presence of degradation signs and microorganisms on their surface. For the SEM analysis, the samples were fixed in 2% OsOIn the processing of a polymeric composite, it is important to know how much energy is required to bring the mixture from an initial state to a homogeneous melt and how much time this process requires. The processing behavior of the investigated composites was quantified by the torque at the different mixing times and the end of mixing. The average torque–time curves obtained at 170 °C and a rotor speed 100 rpm for the PCA and PHBV/PO composites are reported in w/w of ATBC/ PHBV increased from 0.13 to 0.175 compensating for the effect of the fiber content increase.The curves give indications on the mixing behavior and on the energetic effects of the process. The incorporation of the PO fibers in the PHBV based polymeric matrix increased the torque and consequently the energy required for the melt mixing. All the PHBV/PO composites showed the same final torque value of about 66.5 Nm: this can be attributed to the fact that, going from PCA10 to PCA30, the ratio The thermal stability of PO fibers, PHBV, ATBC and the developed composites in terms of thermogravimetric (TG) and their derivative (DTG) curves is shown in The thermal stability of the PHBV, PO fibers and ATBC at the composite processing temperature (170 °C) is shown in The mechanical properties of the composites, evaluated by tensile and Charpy’s impact tests, are reported in Posidonia oceanica fibers. The observed behavior is typical of particle-filled polymeric matrices with poor or no compatibility between the components, meaning that stress transfer phenomena cannot occur and the filler particle becomes a stress concentrator leading to brittle fracture [As shown, the Young’s modulus slightly increased and the elongation at break significantly decreased with increasing fiber loading, due to the stiffening effect induced by lignocellulosic fillers , while tfracture ,41.In order to better analyze the tensile results, SEM analysis was performed on the cross-section of the specimens before the tensile test and on the fractured section after tensile test. As example, the SEM images of the PCA and PCA20 specimens are reported in As shown, in the unbroken PC20 specimen, the PO fibers are quite homogeneously distributed within the thermoplastic matrix. The interfacial interactions between the fibers and the matrix were not sufficiently strong to maintain the cohesion during the tensile tests, as shown in the broken specimen section where a significant fiber pullout is evident. The same results were observed also for the samples PCA10 and PCA30, which are not shown here for brevity.As shown in The aerobic biodegradation curves obtained from the lab-scale test under simulated marine environmental conditions and the temperature recorded during the test are reported in 2 (ThCO2) based only on the carbon content of PHBV and ATBC. In this way, the effect of the PO fibers on the biodegradation rate of the polymeric matrix was more evident, as shown in At the end of the test (216 days), the biodegradation of the filter paper was about 70%, while the composite PCA20 reached a value of about 30% higher than that without PO fiber (PCA) and still growing. Therefore, the “relative biodegradation”, i.e., the biodegradation of the test material relative to the positive benchmark , was about 40%. Considering the slow degradation rate of lignocellulosic PO fibers in natural environments that was confirmed also by this test , and also showed a well-developed biofilm consisting of diatoms, bacteria and fungi on the PCA20 specimen surface. The Posidonia oceanica fibers were incorporated in a thermoplastic matrix based on PHBV and ATBC to produce melt processable and biodegradable composites for specialized applications in marine environments. The resultant composites were characterized in terms of processability, thermal/mechanical/morphological properties and biodegradability under simulated and real marine environmental conditions.Different amounts  of Posidonia oceanica fibers in the composites accelerated the biodegradation of polymeric matrix. After about 7 months in marine sediment, pellets with 20 wt % of PO fibers showed a biodegradability of 30%, corresponding to a relative biodegradability, with respect to cellulose, of 40%. The degradation test in marine mesocosm showed that after 3 incubation months in marine sediments, an evident microbial community consisting of bacteria and fungi colonized the surface of the composite specimens containing PO fibers. During the 12 months of testing, the specimens without fibers maintained their tensile properties almost constantly, while those with 20 wt % PO fibers showed a strong decay of their mechanical performance, and after 10 months it was not possible to determine them. These findings confirm that the presence of PO fibers, due the poor matrix/fiber adhesion, favored the physical degradation of the specimens accelerating the biological attack with a consequent decay of the mechanical properties, and that the degradation process is influenced by the seawater temperature: higher temperatures led to higher degradation rates.The processing of the composites at up to 30 wt % of PO fiber content did not create any difficulty, and the obtained composites showed good thermal stability and mechanical properties, especially in terms of stress at break and impact resistance. The biodegradation test results in the simulated marine environment showed that the presence of Posidonia oceanica is technically feasible by conventional extrusion and represents an eco-sustainable valorization of these residues which accumulate on sandy beaches, contributing to solving a real environmental and management problem. In addition, the maintenance of the mechanical properties for a relatively long period (a year) makes the developed composites particularly suitable for the production of biodegradable and relatively low-cost items usable in the seawater such as restoration tools and, after the disintegration of the polymeric matrix, the residual PO fibers would return to their native habitat.On the basis of the results, it can be concluded that the production of composites based on PHBV and fibrous wastes of


DBS) electrodes into the subthalamic nucleus (STN‐DBS) for the treatment of Parkinson's disease (PD) frequently relies on subjective correspondence between kinesthetic response and multiunit activity. However, recent work suggests that local field potentials (LFP) could be used as a more robust signal to objectively differentiate subcortical structures. The goal of this study was to analyze the spectral properties of LFP collected during STN‐DBS in order to objectively identify commonly traversed brain regions and improve our understanding of aberrant oscillations in the PD‐related pathophysiological cortico‐basal ganglia network. In 21 PD patients, LFP were collected and analyzed during STN‐DBS implantation surgery. Spectral power for delta‐, theta‐, alpha‐, low‐beta‐, and high‐beta‐frequency bands was assessed at multiple depths throughout the subcortical structures traversed on the trajectory to the ventral border of STN. Similar to previous findings, beta‐band oscillations had an increased magnitude within the borders of the motor‐related area of STN, however, across several subjects, we also observed increased high‐beta magnitude within the borders of thalamus. Comparing across all patients using relative power, we observed a gradual increase in the magnitude of both low‐ and high‐beta‐frequency bands as the electrode descended from striatum to STN. These results were also compared with frequency bands below beta, and similar trends were observed. Our results suggest that LFP signals recorded during the implantation of a DBS electrode evince distinct oscillatory signatures that distinguish subcortical structures.Identification of brain structures traversed during implantation of deep brain‐stimulating ( Parkinson's disease (PD), a movement disorder characterized by bradykinesia, rigidity, and tremor, results from progressive loss of nigrostriatal dopaminergic innervation . All LFP analyses were conducted on de‐identified data collected during the standard‐of‐care procedures for routine STN‐DBS implantation surgery in patients with idiopathic PD, using a retrospective chart review IRB‐approved protocol. Study population consisted of 21 PD patients .The operative procedure for DBS implantation surgery has been described in detail previously  was collected, along with a digital stamp of the depth with respect to the stereotactic target, in micrometer resolution. For each depth, a neurosurgeon and neurophysiologist, well‐experienced with intraoperative electrophysiological assessment, determined the approximate location of the recording within the brain, based on auditory and visual analysis of single‐neuron activity profile. The standard trajectory used for targeting STN traversed striatum, thalamus, and STN. Intraoperative assessment of brain localization was recorded and used to annotate recording depths. All subsequent analyses were computed offline. Data used in this analysis were derived from 81 electrode trajectories, recorded during 27 DBS implant surgeries, from 21 unique patients. Within each trajectory, only traces recorded for longer than 10 sec were stored for further postprocessing and analysis.All recorded data were imported into MATLAB . Raw signals were visualized within the time domain, and individual traces with clear recording artifacts were excluded. To confirm that the time domain signals collected for each LFP electrode were unique and distinct, we computed the magnitude‐squared signal coherence for each pair of electrodes, at each depth  by concurrently driven electrodes, offset by 2 mm, are not expected to occur at the same depths. In order to compare across multiple patients, the relative power was calculated. Relative power was normalized on a per‐patient and per‐electrode basis, using the average power for each frequency bin collected from samples identified in the striatum. All signals within each structure from a given electrode were then normalized to that value to compare signals across patients. We noted that outliers remained in the data when looking at relative power using this calculation method, so any resulting values outside of 3 standard deviations from the mean were defined as outliers, and removed prior to any statistical testing.All statistical analyses were computed using Matlab 2016b . In order to compare across all three brain structures—striatum, thalamus, and STN— for multiple patients, a one‐way analysis of variance (ANOVA) or nonparametric ANOVA  was computed on group (brain structure) means for relative power data. Post hoc (Tukey's Honest Significance Difference Criterion or Dunn's test) comparisons were used to compare between structures for different frequency bands lower (13–20 Hz) and higher (21–30 Hz) beta frequencies along with the frequency bands below beta: delta (<3 Hz), theta (4–7 Hz), and alpha (8–12).We analyzed LFP data from 1454 intraoperative isolated recordings, acquired from 81 electrode tracks, in 27 STN‐DBS surgeries (14 Left and 13 Right STN implantations), conducted in 21 PD patients. For each surgery, three parallel electrode trajectories, spaced 2 mm apart, afforded recording epochs at multiple depths  per‐electrode track. A schematic of the common trajectory for STN‐DBS implantation is provided in Figure H test, χ2(2) = 25.26, P = 3.2 × 10−6 striatum vs. thalamus, P = 0.02; striatum vs. STN, P < 0.0001; thalamus vs. STN, P = 0.001). Beta‐frequency band power is noted to increase as the recording depth descends from striatum to thalamus, and from thalamus to STN, across all three electrodes. The mean rank of the signal across the trajectory through STN is higher than the signal mean for thalamus or striatum, with a mean striatal signal of 4.5 dB, thalamic of 21.12 dB, and STN of 37.13 dB (mean ± STD).Previous reports in the literature have documented significant increases in LFP oscillatory activity and power magnitude within STN for the beta‐frequency band, recorded in patients undergoing DBS implantation  = 7.4, P = 0.02 striatum vs. thalamus, P = 0.99; striatum vs. STN, P = 0.051; thalamus vs. STN, P = 0.047). In Figure In order to confirm that the findings were not specific only to certain depths along the trajectory, we computed the PSD for all recordings confirmed within the striatum, thalamus, and STN, for each individual electrode trajectory. Figure H test, χ2(2) = 23.04, P = 9.91 × 10−6; striatum vs. thalamus, P = 0.01; striatum vs. STN, P < 0.0001; thalamus vs. STN, P = 0.12; mean ranks: 87.35, 117.05, 138.70, striatum, thalamus, STN, respectively). In Figure H test, χ2(2) = 19.35, P = 6.27 × 10−5; striatum vs. thalamus, P = 0.007; striatum vs. STN, P = 0.0001; thalamus vs. STN, P = 0.37) . However, for high beta we found that across all patients all three structures were differentiable from each other. STN had the highest expression of high beta, followed by thalamus and, finally, striatum exhibited the lowest high‐beta power  = 28.68, P = 5.91 × 10−7; striatum vs. thalamus, P = 0.008; striatum vs. STN, P < 0.0001; thalamus vs. STN, P = 0.04) .We next sought to assess whether the discrete brain areas traversed during STN‐DBS implantation surgery would differ in their expression of beta‐band power across patients. Focusing on each specific structure, we compared the average relative power for total (13–30 Hz), low‐ (13–20 Hz), and high‐ (21–30 Hz) beta frequency in the striatum, thalamus, and STN, for all patients Fig. A–C. To cH test, χ2(2) = 25.26, P = 3.2 × 10−6 striatum vs. thalamus, P = 0.01; striatum vs. STN, P < 0.0001; thalamus vs. STN, P = 0.03). Among the lower‐frequency bands, all three structures are clearly distinguishable within the θ and α bands. The mean rank of the signal across the trajectory through STN is higher than the signal mean for thalamus or striatum, with a mean striatal signal of 4.63 dB, thalamic of 21.92 dB, and STN of 34.50 dB (mean ± STD).Studies of abnormal cortico‐BG oscillations have focused extensively on the beta band, which can be therapeutically modulated by L‐DOPA therapy  = 3.2, P = 0.2). In Figure To assess whether increased lower‐band power typified any of the three structures under investigation with respect to the implanted trajectory, we examined the relative power averaged for each structure within the electrode trajectory selected for implantation for all surgeries Fig. D. We obsH test, χ2(2) = 52.95, P = 3.17 × 10−12; striatum vs. thalamus, P < 0.0001; striatum vs. STN, P < 0.0001; thalamus vs. STN, P = 0.6; mean ranks: 71.06, 130.91, 142.21, striatum, thalamus, STN, respectively). In Figure H test, χ2(2) = 29.25, P = 4.4 × 10−7; striatum versus thalamus, P = 0.002; striatum versus STN, P < 0.0001; thalamus versus STN, P = 0.1; mean ranks: 83.75, 118.68, 141.25, striatum, thalamus, STN, respectively. Statistical results for alpha: Kruskal–Wallis H test, χ2(2) = 33.04, P = 6.7 × 10−8; striatum versus thalamus, P = 0.0001; striatum versus STN, P < 0.0001; thalamus versus STN, P = 0.33; mean ranks: 80.45, 123.72, 139.20, striatum, thalamus, STN, respectively.Finally, we again compared the relative band power across structures by normalizing power for each patient based on the average band‐specific magnitude in striatum for each electrode. In Figure δ, θ, α, and β), could consistently distinguish between BG structures  routinely traversed during STN‐DBS implantation surgery. Notably, all structures were differentiable based on high‐beta activity (21–32), but all other bands were only sufficient to differentiate striatum from thalamus and striatum from STN  revealed differences in power between STN and striatum, as well as thalamus and striatum, but did not distinguish STN from thalamus  as well as both low and high beta differentiated striatum from thalamus and striatum from STN, however, only high beta separated thalamus from STN. These results indicate that resting‐state LFP signatures from deep brain structures might be used to provide objective classification of electrode location in PD patients.The authors declare no conflicts of interests.


Cerebrospinal fluid (CSF) protein analysis is an important element in the diagnostic chain for various central nervous system (CNS) pathologies. Among multiple existing approaches to interpreting measured protein levels, the Reiber diagram is particularly robust with respect to physiologic inter-individual variability, as it uses multiple subject-specific anchoring values. Beyond reliable identification of abnormal protein levels, the Reiber diagram has the potential to elucidate their pathophysiologic origin. In particular, both reduction of CSF drainage from the cranio-spinal space as well as blood–CNS barrier dysfunction have been suggested ρas possible causes of increased concentration of blood-derived proteins. However, there is disagreement on which of the two is the true cause.We designed two computational models to investigate the mechanisms governing protein distribution in the spinal CSF. With a one-dimensional model, we evaluated the distribution of albumin and immunoglobulin G (IgG), accounting for protein transport rates across blood–CNS barriers, CSF dynamics (including both dispersion induced by CSF pulsations and advection by mean CSF flow) and CSF drainage. Dispersion coefficients were determined a priori by computing the axisymmetric three-dimensional CSF dynamics and solute transport in a representative segment of the spinal canal.Our models reproduce the empirically determined hyperbolic relation between albumin and IgG quotients. They indicate that variation in CSF drainage would yield a linear rather than the expected hyperbolic profile. In contrast, modelled barrier dysfunction reproduces the experimentally observed relation.High levels of albumin identified in the Reiber diagram are more likely to originate from a barrier dysfunction than from a reduction in CSF drainage. Our in silico experiments further support the hypothesis of decreasing spinal CSF drainage in rostro-caudal direction and emphasize the physiological importance of pulsation-driven dispersion for the transport of large molecules in the CSF. Despite continued advances in non-invasive medical imaging, cerebrospinal fluid (CSF) analysis in general and CSF protein analysis in particular have remained important tools for the diagnosis of various disorders of the central nervous system (CNS) . Yet whiWhile some proteins found in the CSF are synthesized within the CNS  or the meninges, most of them originate in the blood serum under normal conditions –4. They Since protein levels in the CSF show normal fluctuations as serum protein concentrations change, and since there are inter-individual variations, it is helpful to use relative values for diagnostic purposes. The Reiber diagram constitutes a standardized approach to assessing such values. Should, for example, the immunoglobulin G (IgG) concentration in a patient’s CSF sample be analyzed, its relative value with respect to serum IgG concentration (IgG quotient) is compared to the corresponding relative concentration of albumin . Since albumin is not synthesized in the mature CNS , a higheOf the four possible causes for changes in CSF protein concentration listed above, the Reiber diagram corrects for variations in serum protein levels and identifies intrathecal protein synthesis see Fig. a. HoweveTo this end, we have analysed how changes in barrier function, CSF drainage rates and pulsatility translate to changes of albumin and IgG quotients in the Reiber diagram, where IgG was chosen from the family of immunoglobulins arbitrarily as a common biomarker for inflammatory neurological disorders . Our modWe designed two computational models Fig.  to invesDispersion as the combined effect of diffusion and advection by pulsatile fluid motion with zero net flow is the governing mechanism for the faster transport of solutes in the CSF compared to pure diffusion –14. To dThe geometry of the spinal canal is idealized as an axisymmetric annular pipe Fig. c with diThe model domain is treated as porous, with permeability and porosity metrics according to literature values for the subarachnoid space . A velocThe time-dependent equations governing fluid motion and solute transport, namely modified Navier–Stokes with Darcy’s law for the porous medium, continuity and advection–diffusion equations, are solved numerically using the open source finite volume code OpenFOAM :1\documea et al. . The par−4 s and spatial resolution of 100 μm in both axial and radial directions. Grid and time-step independence were confirmed.Equations  to 3) a a3) are The dispersion coefficient may be derived from the above three-dimensional model by fitting the simulated axial concentration with the analytical solution of the dispersion equation in a semi-infinite domain :4\documens small . The vali, represents the influx of serum proteins into the CSF, while the sink term, So, represents protein efflux due to CSF drainage [Our one-dimensional domain represents protein transport in the spinal CSF between the lumbar and cervical regions. The model domain is illustrated in Fig. drainage . The dimmentclass2pt{minimThe dispersion coefficient depends on both the solute considered and the amplitude of the CSF pulsations. The latter has been shown to increase from zero in the lumbar space  to a maxb stands for the diffusive permeability of the blood-CNS barriers for the protein under consideration and In absence of active transporters in the blood vessel wall for albumin and immunoglobulins, the only transport mechanism for these larger proteins through the barrier is slow paracellular diffusion . Therefo studies . Howevermentclass2pt{minimF is the CSF drainage rate. The total CSF turn-over rate has been estimated to 500 ml/day in humans [Since protein efflux occurs by CSF drainage , the pron humans . Howevern humans , let aloAl, in a given CSF compartment [Al is known, namely the cisterns, cortical or spinal subarachnoid spaces, Pbc stands for the barrier permeability in that compartment and At steady state, the average concentration in a given compartment can be derived from Eq. partment :9\documeAl was observed from the first 0–3 ml of CSF to the last 27–30 ml of CSF obtained by lumbar puncture [Having calculated the mean CSF drainage rate for the spinal compartment, we determine its local value by making use of reported albumin concentration gradients along the neuraxis. Due to the low CSF turnover rate, sequential sampling of CSF through a lumbar puncture allows one to sequentially access CSF portions from the lumbar, thoracic and finally cervical subarachnoid spaces. Using this method, a decrease of Qpuncture . Having puncture . AccordiEquation  for soluReiber showed that a hyperbolic function can describe the relationship between albumin and immunoglobulin quotients seen in a population of patients without intrathecal production of immunoglobulins :10\documReiber further showed that the population variation coefficient, CV, stays constant as the albumin quotient changes. CV is defined as the ratio of the IgG variation to its mean value :11\docum−11 and 2.4 · 10−11 m2/s, respectively. A peak CSF velocity of 10 mm/s was considered as Ref. [We interrogated the 3D axisymmetric model to evaluate protein transport resulting from pulsatile spinal CSF motion. The diffusion coefficients of albumin and IgG in CSF are 6 · 10 as Ref. . The res as Ref. , we also as Ref. , demonstWe first determined the distribution of CSF drainage between cortical and spinal spaces as outlined in the "We employed the 1D model of albumin distribution in conjunction with the dispersion rates obtained using the 3D model of protein transport in the spinal space to assess the effect of changes in CSF pulsation amplitude. We investigated the effect of a fourfold increase in CSF pulsation amplitude observed in chronic hydrocephalus patients  and usedWe used the 1D model to investigate the effect of changes in blood-CNS barrier permeability and CSF drainage on albumin and IgG quotients in the lumbar cerebrospinal fluid. Figure Figure Figure The biochemical analysis of the cerebrospinal fluid is an important diagnostic tool for pathologies of the CNS. For example, changes in CSF immunoglobulin content can be indicative of inflammatory reactions in the brain. To account for inter-individual and normal intra-individual variability, it is advantageous to assess relative rather than absolute values of protein concentration as done in the Reiber diagram. While the Reiber diagram can indicate intrathecal synthesis of proteins, it is debated whether higher than normal readings of relative albumin concentrations are indicative of CNS barrier dysfunction or reduction in CSF drainage. Here we have employed a set of computational models to assess which one of these two changes is the more likely cause of increased albumin concentration in CSF relative to that in the blood plasma.The Reiber diagram features a hyperbolic relationship between albumin quotient and, for example, IgG quotient, where ‘quotient’ refers to the concentration of the respective protein in CSF relative to its concentration in blood plasma. Reiber derived this empirical relationship from measurements in a large set of patients in which intrathecal synthesis of the protein of interest could be excluded. He hypothesized that this non-linear relationship was caused by inter-patient variability in CSF drainage rates . HoweverOthers have attributed increased albumin quotients to blood-CNS barrier dysfunction. Indeed, as shown in Fig. Our calculations of the distribution of CSF efflux indicate 18% drainage in the spinal compartment and 82% drainage in the cranial compartment. This distribution matches well with the measurements of Marmarou et al.  in cats,Seyfert et al. measured albumin and immunoglobulin concentration gradients in the spinal CSF by sequential CSF sampling through lumbar puncture. They showed a decreasing protein concentration profile from lumbar to cervical space . It was Puy et al. correlated the magnitude of CSF pulsation with protein distribution in different CSF compartments . We calcThe two computational models developed in this study have the following main limitations: First and foremost, we have simplified the spinal canal anatomy substantially to a 3D axisymmetric annular conduit and a 1D representation, respectively, considering the spinal subarachnoid space as a porous medium. Both the macroscopic anatomy as well as the microanatomy of the CSF spaces as defined by, e.g. arachnoid trabeculae, could play an important role in fluid and solute dynamics. Neglecting the microanatomy can lead to discrepancies between computed and measured metrics of spinal CSF dynamics . In our The second main limitation pertains to the issue of parameter uncertainty. For instance, we have considered the overall CSF drainage rate to be equal to the estimated value of CSF production, which itself is only known approximatively . We have


A classification of cardiac- and respiratory-driven components of cerebrospinal fluid (CSF) motion has been demonstrated using echo planar imaging and time-spatial labeling inversion pulse techniques of magnetic resonance imaging (MRI). However, quantitative characterization of the two motion components has not been performed to date. Thus, in this study, the velocities and displacements of the waveforms of the two motions were quantitatively evaluated based on an asynchronous two-dimensional (2D) phase-contrast (PC) method followed by frequency component analysis.The effects of respiration and cardiac pulsation on CSF motion were investigated in 7 healthy subjects under guided respiration using asynchronous 2D-PC 3-T MRI. The respiratory and cardiac components in the foramen magnum and aqueduct were separated, and their respective fractions of velocity and amount of displacement were compared.For velocity in the Sylvian aqueduct and foramen magnum, the fraction attributable to the cardiac component was significantly greater than that of the respiratory component throughout the respiratory cycle. As for displacement, the fraction of the respiratory component was significantly greater than that of the cardiac component in the aqueduct regardless of the respiratory cycle and in the foramen magnum in the 6- and 10-s respiratory cycles. There was no significant difference between the fractions in the 16-s respiratory cycle in the foramen magnum.To separate cardiac- and respiratory-driven CSF motions, asynchronous 2D-PC MRI was performed under respiratory guidance. For velocity, the cardiac component was greater than the respiratory component. In contrast, for the amount of displacement, the respiratory component was greater. Intracranial cerebrospinal fluid (CSF) motion changes with cardiac and respiratory rhythms . In clinWe consider that quantitative analysis of velocity and displacement, the integral of velocity over time, is required to ascertain the dynamics of CSF motion as water, and this study was conceived on the assumption that quantitative analysis of CSF motion by 2D-PC, a development building on previous techniques, is appropriate for this purpose. To separate the cardiac and respiratory components of CSF motion, the asynchronous real-time 2D-PC technique was used in seven healthy volunteers under controlled respiration. The velocity and the amount of displacement of the cardiac and respiratory components of CSF motion were quantified. The velocity and displacement were then compared in each respiratory cycle, and the effects of respiratory and cardiac components on CSF motion were quantitatively investigated.Our institutional review board approved this research. All volunteers were examined after providing appropriate informed consent, consistent with the terms of approval from the institutional review board of our institution.2; velocity encoding (VENC) 10 cm/s; acquisition matrix 89 × 128 ; reconstruction matrix 256 × 256; and slice thickness 7 mm. These conditions yielded a frame rate of 4.6 images/s . The total duration of data acquisition for each subject was 55 s. After obtaining the color-coded velocity vector images, rough outlines of the ROI were specified around the Sylvian aqueduct and the foramen of Monro. The partial volume effect arising from the relatively large voxel size (approximately 2 mm) used in the present experiment made a simple threshold-based segmentation of the T2-weighted image difficult. To segment the CSF regions on the images with a reduced partial volume effect and to apply these images to the velocity and pressure images as masks for the quantitative analyses, a novel segmentation technique, called spatial-based fuzzy clustering, was applied. The details of this technique are explained elsewhere [Asynchronous 2D-PC technique under controlled respiration was performed in 7 healthy volunteers  aged 21–31 years. The respiratory cycle was set to 6, 10, and 16 s, to cover the range of the normal respiratory cycle. Volunteers were requested to control their respiration according to audio guidance for inhalation and exhalation timing. To monitor respiration, a bellows-type pressure sensor was placed around the abdomen of the subject, and an electrocardiogram (ECG) was monitored to identify the frequency distribution of individual cardiac motion. Asynchronous 2D-PC steady-state-free precession (SSFP) was performed on a 3-T MR scanner with the following conditions: flow encode direction foot–head (FH); data points 256; repetition time (TR) 6.0 ms; echo time (TE) 3.9 ms; flip angle (FA) 10°; field of view (FOV) 28 × 28 cmlsewhere .The waveform in the individual voxels was separated into respiratory and cardiac components based on frequency range, and the maximum velocity was determined for the respective components. The technical details of the procedure were explained in our previous study , 14.Fr, of the velocity of the respiratory component to the sum of the velocities for the respiratory and cardiac components.vr is the respiratory component of the velocity, while vc is the cardiac component.The ratio of the individual velocity of the respiratory or cardiac component to the sum of the velocities of the respiratory and cardiac components was calculated for both velocity and displacement. The results of the above calculations for the cerebral aqueduct and the foramen magnum were compared statistically. Equation v(m∙ Δt) is the velocity at the mth time point of the observation with a sampling period of Δt, and M is the number of time points in the cranial or caudal direction. For example, when the velocity was positive, its direction was regarded as cranial, and the number of corresponding data points was set to M. N is the number of voxels in a region of interest (ROI) for the displacement measurement. Fractions of cardiac- and respiratory-induced displacements were calculated in a similar manner with equation [The mean CSF displacement of each component in the cranial and caudal directions was calculated from the velocity waveform based on the following equation,mentclass2pt{minimU test were used to compare the respiratory and cardiac components of the velocity and the amount of displacement.The Kolmogorov–Smirnov test and the Mann–Whitney p = 0.002) regardless of the respiratory period. A similar plot for the fractions at the foramen magnum is shown in Fig. p = 0.002) throughout the three different respiratory cycles. There was no significant difference between the fractions of the different respiratory periods for both the respiratory and cardiac components.Figure p = 0.002). No significant difference was found between the fractions of the different respiratory periods. A similar plot for the displacement fraction at the foramen magnum is shown in Fig. p = 0.02). However, no significant difference was observed at 16 s (p = 0.85). Significant differences between the respiratory cycles of 6 and 16 s were observed in both the respiratory and cardiac components (p = 0.004). No differences were observed in the other respiratory cycles.The fraction of the displacement of the CSF for the respiratory and cardiac components at the Sylvian aqueduct is shown in Fig. To understand the driving force of CSF motion, researchers have investigated animals and humans using a variety of techniques . Many coIn the present study, CSF motion was separated into respiratory and cardiac components. The amount of CSF displacement was found to be larger in the respiratory component than in the cardiac component in both cranial and caudal directions. Simultaneously, while the cardiac component showed a smaller displacement, the velocity was higher compared to the respiratory component. In other words, the movement of CSF due to the cardiac component was rapid and small, and that due to the respiratory component was slow and large. These results are consistent with those of the visual analysis of CSF reported by Yamada et al.  demonstrTime-SLIP enables changes in spin to be visualized. This approximates the results for displacement shown in the present study, showing that CSF moves long distances in accordance with respiratory variations. In the present results, the velocity indicated the rapid movement of CSF with a short period associated with the heartbeat. To summarize CSF motion on the basis of these results, although CSF moves fast as it spreads around the vessels with the heartbeat, it moves over comparatively long distances in accordance with the slower movements of breathing, and this fast movement and movement over long distances may be responsible for physical exchanges in the brain and spinal cord.However, the physical quantity measured in the present study is the displacement calculated by integrating the CSF velocity in the cranial or caudal direction, unlike the spin traveling distance, which the spin-labeling technique measures. Another important point is that the temporal resolution for data sampling (217 ms/frame) was not high enough to sample the cardiac-driven motion. Assuming a heart rate of 1 Hz, only 4–5 points can cover a cycle of cardiac-driven CSF motion resulting in a lack of waveform sampling accuracy, although the present technique is a quantitative measurement based on the 2D-PC technique, which can measure the fluid velocity with 10% accuracy .In this study the asynchronous 2D-PC method was used under respiratory guidance, which also enabled the evaluation of the respiratory movement element. This was done by performing 2D-PC scanning continuously without a trigger in order to evaluate the slow, long-period motion of CSF and then carrying out quantitative analysis. The feature of the PC method in combining the time element with velocity and direction makes it possible to observe the complex motion of the CSF, providing the next step forward in elucidating the physiological functions of the CSF in vivo. The cardiac-related CSF motion is predominant over the respiratory-related motion, which maintains CSF pressure in the CSF cavity. However, the CSF moves a long distance, as shown by our analysis of displacement. The displacement of CSF in different cavities is important to exchange substances between the parenchyma and the CSF space. During surgery, neurosurgeons frequently see powerful short-range cardiac-related CSF waves and long range, large-wave rhythmical pulsations related to the ventilator. Furthermore, at the tip of external ventricular drainage, clinicians always see the short-range, short-distance CSF pulsation and the long-range, long-distance CSF pulsation, and this alternate CSF pulsation can be identified using the present technique non-invasively. Our final goal was to identify the pathogenesis of CSF circulatory disturbances, as in hydrocephalus and Alzheimer dementia. Using quantitative analysis, we were able to differentiate the subgroup of disease or do a pre- and post-treatment analysis. One of the limitations is that the present MR technique is vulnerable to changes in the position of the human body. Such a position change makes the CSF motion more complex, resulting in failure to assess the association between human movements and CSF motion in daily life.


Postural changes are related to changes in cerebrospinal fluid (CSF) dynamics. While sitting up leads to a decrease in cranial CSF pressure, it also causes shifts in the craniospinal CSF volume and compliance distribution. We hypothesized that jugular vein collapse in upright posture is a major contributor to these shifts in CSF volume and compliance.To test this hypothesis, we implemented a mathematical lumped-parameter model of the CSF system and the relevant parts of the cardiovascular system. In this model, the CSF and the venous system are each divided into a cranial and a spinal part. The pressures in these cranial and spinal portions differ by the posture-dependent hydrostatic pressure columns in the connecting vessels. Jugular collapse is represented by a reduction of the hydrostatic pressure difference between cranial and spinal veins. The CSF pressure–volume relationship is implemented as a function of the local CSF to venous pressure gradient. This implies that an increase in CSF volume leads to a simultaneous displacement of blood from adjacent veins. CSF pulsations driven by the cardiovascular system are introduced through a pulsating cranial arterial volume.In upright posture, the implemented CSF pressure–volume relationship shifts to lower cranial CSF pressures compared to the horizontal position, leading to a decrease in cranial CSF pressure when sitting up. Concurrently, the compliance of the spinal compartment decreases while the one of the cranial compartment increases. With this, in upright posture only 10% of the CSF system’s compliance is provided by the spinal compartment compared to 35% in horizontal posture. This reduction in spinal compliance is accompanied by a caudal shift of CSF volume. Also, the ability of the spinal CSF compartment to compensate for cerebral arterial volume pulsations reduces in upright posture, which in turn reduces the calculated craniospinal CSF flow pulsations.The mathematical model enabled us to isolate the effect of jugular collapse and quantify the induced shifts of compliance and CSF volume. The good concordance of the modelled changes with clinically observed values indicates that jugular collapse can be considered a major contributor to CSF dynamics in upright posture. Several pathologies of the central nervous system, like hydrocephalus and syringomyelia, are caused or characterized by altered cerebrospinal fluid (CSF) dynamics. Therefore, the treatment of these conditions typically aims at restoring physiological circulation of CSF and requires profound knowledge of the underlying pathophysiology. However, CSF dynamics are mostly studied in horizontal posture, even though we spend most of our time upright and CSF dynamics fundamentally change with posture. For example, sitting up not only leads to changes in intracranial pressure (ICP), but also to a caudal shift of CSF volume and an inversion of the compliance distribution between the cranial and the spinal part of the CSF system. This inversion of the craniospinal compliance was first observed by Magnaes in a small number of subjects . In a reWhat we do know is that CSF pressure in equilibrium conditions is a function of venous pressure through Davson’s equation , and thaWe hypothesized that the collapse of the jugular veins when upright not only affects mean ICP, but that it also causes the aforementioned caudal shift of CSF volume: interruption of the venous hydrostatic pressure column decreases the cranial CSF to venous pressure gradient by diminishing the reduction in cranial venous pressure when sitting up. Due to the exponential nature of the CSF system’s pressure–volume relationship , this inWe aimed at testing this hypothesis by implementing a mathematical model of the CSF system and the relevant parts of the cardiovascular system. This has enabled us to isolate the effect of jugular vein collapse and quantify the induced shifts of compliance and CSF volume. These estimated changes in CSF dynamics were then compared to the measurements of Magnaes . TestingWe used a lumped parameter description of the interaction between the CSF and cardiovascular systems as shown in Fig. Cerebrospinal fluid pulsations driven by the cardiovascular system were accounted for through a pulsating cranial arterial volume. The pulsations of this arterial volume were based on recorded flow rates in the internal carotid and vertebral arteries. As CSF competes with the arterial pulsations for the available compliance, the arterial volume was added to the cranial CSF volume. Instantaneous flow rates for CSF and venous blood between cranial and spinal compartments were calculated based on a volume balance, assuming constant cranial volume (Monroe–Kelly doctrine).The pressure gradient mentclass2pt{minimmentclasspt{minimament}pvs . DescribIn horizontal posture, where cranial and spinal CSF as well as venous pressures can be assumed equal  within the cranium has to be compensated, respectively, by an equivalent volume decrease or increase of the other entities (Monroe–Kelly doctrine) . Therefo}ΔVa Eq.  has to bSolving this equation for the cranial CSF pressure The CSF volume and the cranial CSF pressure during a cardiac cycle were computed by solving this system of differential–algebraic equations Eqs. , 22 usinBased on these computations, the CSF flow rate into the spinal compartment was calculated as the change in spinal CSF volume:After calculating the local and total pressure–volume relationships of the CSF space in horizontal and upright posture, these correlations were used to derive the local and total compliances. Based on this, CSF volume and pressure in upright posture were determined under the assumption of unchanged CSF volume Eq.  or underIn horizontal position, cranial and spinal CSF and venous pressures are equal. The overall pressure–volume relationship was thus described by Eq. hips Eq. .Fig. 2CSIn Fig. kR = 0.10. In other words, the spinal resistance to CSF outflow was around nine times the cranial resistance to CSF outflow , the effect of posture increased as the initial volume shift increased to 2.0 mL . However, for sufficiently decreased CSF volume, it implies infinite compliance. This attribute of the exponential pressure–volume relationship becomes especially problematic when applied to the cranial compliance in upright posture, because negative CSF to venous pressure gradients could easily be reached here. However, as such gradients were not reached in this study this limitation does not affect the results or conclusions reported herein. Nonetheless, extrapolation to low CSF pressures would be invalid Fig. . TherefoOnly considering the mean venous pressure as counter-pressure for the pressure–volume relationship might seem simplistic, as venous pressure varies over the different generations of venous vessels. However, the implemented pressure–volume relationship captures this venous pressure variation and distribution with its exponential shape .The only mechanism of compliance included in the model is the displacement of venous blood. While this mechanism is accepted as the main contributor to compliance in the cranium , this isBefore Magnaes  determinPulsatile arterial inflow into the cranium were compensated by simultaneous craniospinal outflow of CSF and venous blood. Stroke volume and amplitude of the calculated CSF pulsations Figs. , 4 were Our results support the hypothesis that the jugular veins play an important role in posture-related changes of CSF dynamics, as their collapse in upright posture induces substantial changes in CSF pressure and compliance.


Tumor-derived cell free DNA (cfDNA) can be detected in plasma. We hypothesized that mutated BRAF V600 cfDNA could be quantified in the cerebrospinal fluid (CSF) of patients with central nervous system (CNS) metastases. We collected CSF from patients with BRAF V600E or K-mutated melanoma (N=8) or BRAF V600E mutated Erdheim-Chester Disease (ECD) (N=3) with suspected central nervous system (CNS) involvement on the basis of neurological symptoms (10/11), MRI imaging (8/11), or both. Tumor-derived cfDNA was quantified by digital PCR in the CSF of 6/11 patients (range from 0.15-10.56 copies/μL). Conventional cytology was negative in all patients except in the two patients with markedly elevated levels of tumor-derived cfDNA. In 2 patients with serial measurements, CSF tumor-derived cfDNA levels reflected response to treatment or progressive disease. CSF tumor-derived cfDNA has the potential to serve as a diagnostic tool that complements MRI and may be more sensitive than conventional cytology. It has been known that cell free DNA (cfDNA) is released into the intravascular circulation  at low lBRAF mutated cfDNA has been identified in the plasma of patients with both BRAF mutated metastatic melanoma and systemic histiocytoses including Langerhans Cell Histiocytosis and Erdheim-Chester disease (ECD), a form of non-Langerhans cell histiocytosis characterized by multi-system tissue infiltration of cells derived from monocyte/macrophage lineage [BRAF mutations, tumor-derived cfDNA could be quantified in the CSF in these patients with CNS involvement and that the level of tumor-derived cfDNA would correlate with disease burden. lineage , 12, 13.BRAF V600E or K somatic tumor mutation and all underwent lumbar puncture (LP) because of suspected central nervous system (CNS) involvement on the basis of neurological symptoms, MRI imaging, or both.We used DigPCR to quantify tumor-derived cfDNA in the CSF from patients with melanoma or ECD. All patients had a V600E and 1 patient with BRAFV600K) and 3 patients had a diagnosis of BRAFV600E mutated ECD ; 5 were men and 6 were women. Eight patients had metastatic melanoma (7 patients with mutated BRAFTen of the 11 patients had neurologic symptoms suggestive of CNS metastases Table . MRI imaV600E mutation and 1 patient with a BRAFV600K mutation) including all 3 patients with radiographically evident leptomeningeal disease. Interestingly, tumor-derived cfDNA was detected in the CSF of 2 patients who had brain parenchymal metastases without radiographic evidence of leptomeningeal disease  and in one ECD patient who had neurologic symptoms ultimately thought not to be due to ECD .Tumor-derived cfDNA was detected and quantified in the CSF of 6/11 (55%) patients , tumor derived cfDNA was undetectable in the CSF. Three of these 5 patients had brain parenchymal metastases, 1 did not have radiographic evidence of CNS metastases, and 1 ECD patient had dural disease. None had radiographically evident leptomeningeal disease and conventional CSF cytology was negative in all 5 patients. Tumor-derived cfDNA was quantifiable in plasma or urine from 4 of the patients  indicating that non-CNS tumor burden was sufficient to detect tumor-derived cfDNA in the periphery. Plasma cfDNA was not detectable in patient #4 (data previously published) , 13.These data show that tumor-derived cfDNA was quantifiable in 3/3 patients with radiographic evidence of leptomeningeal metastases but in only 2/5 patients who had radiographic evidence of only brain parenchymal metastases. The highest level of tumor-derived cfDNA in CSF was seen in patients with leptomeningeal metastases. Conventional CSF cytology was less sensitive.Although the specificity of CSF cytology is >95%, the sensitivity of CSF cytology is known to be low (<50%) . PossiblThree patients had no radiographic evidence of CNS involvement; cfDNA was undetectable in the CSF of two of these patients. In patient #10 with ECD and neurological symptoms, we detected low levels of tumor-derived cfDNA in the CSF even though the neurological symptoms were ultimately attributed to nutritional deficiency (see below). Leptomeningeal disease is not known to occur in ECD. We suspect that in this patient, cfDNA from the plasma may have “leaked” into the CSF. Almost all of the protein in CSF  is derived from serum. It is known that in the setting of infection, inflammation, or malignancy, the blood-brain-barrier and the blood-CSF barrier can be compromised –20. FurtBRAF mutated cfDNA CSF level was measured at 0.512 copies/μL. The patient underwent treatment with dabrafenib but this had to be discontinued due toxicities. The patient then completed a course of immunotherapy with ipilimumab but developed worsening neurologic symptoms. A repeat brain MRI was notable for worsening parenchymal and leptomeningeal disease. This patient was not available for follow-up until 4 months later when a repeat lumbar puncture was performed and showed malignant cells on cytologic examination. BRAF mutated cfDNA in the CSF collected at that time had increased to 0.806 copes/μL. Patient #10 with ECD presented with gait imbalance and underwent CNS imaging and lumbar puncture as part of initial assessment. These were unrevealing and ultimately symptoms were found to be due to peripheral neuropathy which improved with nutritional (vitamin B12 and copper) repletion. Interestingly, CSF tumor-derived BRAF mutant cfDNA was detected pre-treatment (0.329 copies/μL). The patient was then treated with vemurafenib as part of a clinical trial. PET scan imaging showed overall improvement in hypermetabolic activity in the known ECD-related osseous lesions. During this time, the patient's disease related symptoms of bone pain and night sweats markedly improved. A repeat lumbar puncture one month into the course of treatment showed a decrease in mutant cfDNA level to 0.146 copies/μL. Both of these cases indicate that the levels of tumor-derived cfDNA in the CSF reflected response (or lack of response) to therapy.In two patients , we measured tumor-derived cfDNA in the CSF at two time points: before and during treatment  for a diagnostic lumbar puncture as part of standard of care practice. Patients signed written consent to a MSKCC biospecimen research protocol. It is standard of practice at our institution to run a standard sequenom panel that includes both BRAFStored CSF samples were delivered on dry ice to the MSKCC Integrated Genomics Operation Core Lab. cfDNA was isolated from the samples using the Qiagen QiAamp Circulating Nucleic Acid Kit according to the manufacturer's instructions and the concentration was assessed using BioAnalyzer 100-300nt). The DNA was evaluated for BRAF V600E (1799T>A) mutation and BRAF V600K (1798_1799GT>AG) mutations using a droplet DigPCR system . Negative controls used water instead of cfDNA; the positive control used genomic DNA from a BRAF mutated cell line. The experiments were performed using the following protocol: 1 cycle at 95°C for 10 minutes, 40 cycles at 94°C for 30 seconds and 55°C for 1 minute, 1 cycle at 98°C for 10 minutes, then 1 cycle at 4°C infinite, all at a ramp rate of 2°C/second. Bio-Rad's T100 thermal cycler was used for the PCR step. The assay kits for BRAF V600E and BRAF wild-type  and BRAF V600K and wild-type  are commercially available and were purchased from Biorad and used following the manufacturer's directions. When available, 5ng of DNA was assessed in a 20μl PCR reaction, partitioned into approximately 20,000 droplets. A total of two replicates were used per sample. Droplets were quantified using the BioRad Quantasoft Software (version 7.0). For each sample, the droplet reader will read out the number of positive droplets for each florescent assay  and the software applies the Poisson distribution on the droplet count (Figure 00nt. The