Similar results were obtained in neuropathologically confirmed cases. Using a biomarker index to evaluate whether CSF Ng contributed diagnostic information to the core AD CSF biomarkers (amyloid β (Aβ), t-tau, and p-tau), we show that Ng significantly increased the discrimination between AD and several other disorders. Higher CSF Ng levels were positively associated with greater Aβ neuritic plaque (Consortium to Establish a Registry for Alzheimer’s Disease (CERAD) neuritic plaque score, p = 0.0002) and tau tangle pathology  scores. In the hippocampus and amygdala, two brain regions heavily affected in ADD with high expression of Ng, CSF Ng was associated with plaque (p = 0.0006 and p < 0.0001), but not with tangle, α-synuclein, or TAR DNA-binding protein 43 loads. These data support that CSF Ng is increased specifically in ADD, that high CSF Ng concentrations likely reflect synaptic dysfunction and that CSF Ng is associated with β-amyloid plaque pathology.Neurogranin (Ng) is a post-synaptic protein that previously has been shown to be a biomarker for synaptic function when measured in cerebrospinal fluid (CSF). The CSF concentration of Ng is increased in Alzheimer’s disease dementia (ADD), and even in the pre-dementia stage. In this prospective study, we used an enzyme-linked immunosorbent assay that quantifies Ng in CSF to test the performance of Ng as a marker of synaptic function. In 915 patients, CSF Ng was evaluated across several different neurodegenerative diseases. Of these 915 patients, 116 had a neuropathologically confirmed definitive diagnosis and the relation between CSF Ng and topographical distribution of different pathologies in the brain was evaluated. CSF Ng was specifically increased in ADD compared to eight other neurodegenerative diseases, including Parkinson’s disease (The online version of this article (10.1007/s00401-018-1851-x) contains supplementary material, which is available to authorized users. Synaptic density, and thus synaptic protein expression, is highest in the associative cortical areas, probably reflecting cognitive processing . In AlzhNeurogranin (Ng) is a neuronal protein that is highly expressed in the cortex, hippocampus, and amygdala, with the highest concentrations at the dendritic spines , 42. SinRecently, we showed that CSF Ng concentrations can predict the rate of cognitive decline in prodromal ADD and conversion from MCI to ADD . AccordiIn CSF, Ng is present as several endogenous peptides of different lengths, as well as full-length protein (78 amino acids) . To furthttp://www.adni-info.org/). Out of the 915 subjects included in the study, 116 had a definitive diagnosis by neuropathology. The definitive diagnostic groups included ADD (n = 75), DLB (n = 16), FTD (n = 12), ALS (n = 7), and PSP (n = 6) subjects. The neuropathological data and criteria have been described elsewhere , 68 ALS, 37 Parkinson’s disease with normal cognition (PD), 19 PD with MCI (PD MCI), 29 PD with dementia (PDD), 33 DLB, 21 corticobasal syndrome (CBS), and 20 PSP patients. Recruitment of the patients and diagnostic criteria for the groups have been described previously in detail , 55. Demlsewhere , 52. SeeAPOE allele status was defined using two SNPs (rs7412 and rs429358) which were genotyped by TaqMan allelic discrimination assays .Genomic DNA was extracted from peripheral blood before death or frozen brain samples postmortem as described elsewhere . APOE aln = 114) was performed as described elsewhere [Braak tau neurofibrillary tangle staging (PHF-1) and the Consortium to Establish a Registry for Alzheimer’s Disease (CERAD) neuritic plaque score (thioflavin stain) were used to classify ADD neuropathology into four groups as described previously , 21: no lsewhere . An ABC lsewhere .Postmortem examination and scoring of tau, Aβ, α-synuclein, and TAR DNA-binding protein 43 (TDP-43) pathology were performed on amygdala and cornu ammonis/subiculum-hippocampus as described elsewhere .The Alzheimer’s Disease Core Center (ADCC), Penn Memory Center, the Frontotemporal Degeneration Center, the ALS Center, the Parkinson’s Disease and Movement Disorder Clinic, and the Penn Udall Center for Parkinson’s Research each have protocols approved by the institutional review board to recruit patients, along with their clinical data, into research studies. In addition, these centers invite patients to participate in the brain donation program.d-glucopyranoside, 1% BSA in PBS). The samples, blanks, and calibrators were incubated overnight at + 4 °C. Next day the plates were washed and then incubated for 1 h at 350 rpm (room temperature) with the detector antibody, biotinylated NG2 (2.7 µg/mL) in 1% BSA in PBS–Tween (100 µL/well). After another washing step, the plates were incubated for 30 min (room temperature) with 100 µL/well of enhanced streptavidin–HRP (Kem En Tech #4740 N) diluted 1:20 000 in 1% BSA in PBS–Tween. The plates were then washed and color reaction was started using 100 µL/well of substrate . After 20 min in dark the reaction was stopped using 100 µL/well of 0.2 M of H2SO4 and the absorbance was measured at 450 nm (reference wavelength 650 nm) using an ELISA plate reader . A fitted four-parameter logistic model was used as the calibration curve . The analyses were performed by board-certified laboratory technicians blinded to clinical information.The generation and purification of the anti-Ng monoclonal antibodies (Mab) NG22 (epitope 63–75) and NG2 (epitope 52–63) were performed as described previously . 96-well42 < 192 pg/mL, CSF t-tau > 93 pg/mL) that maximized the separation of autopsy-confirmed ADD cases with Aβ pathology from controls without Aβ pathology as described by Shaw et al. [CSF collection, processing, and storage procedures have been described previously . CSF Aβ4w et al. .p values were adjusted using Holm–Bonferroni procedure to control the family-wise error rate. The associations of Ng with the other CSF biomarkers Aβ42, t-tau and p-tau were investigated with Spearman’s rank correlation (rhos). All tests were two sided and significance threshold was set at p < 0.05. We investigated the relationship between CSF Ng and MMSE change per year while adjusting for age, sex, and disease duration using partial Spearman’s rank correlation. We tested this relationship in the whole study population, only the MCI group, and only the ADD group. Additionally, a biomarker index model was developed with the goal of accurately discriminating between two disease groups on the basis of their CSF biomarker measurements. The baseline model included CSF Aβ42, CSF t-tau and CSF p-tau, and the Ng model included CSF Ng in addition to the three aforementioned CSF measurements. The discriminator itself is a support vector machine (SVM), see Online Resource 2 for a detailed description.Statistical analyses were performed using GraphPad Prism 7 and the R programming language (version 3.4.3), while the biomarker index model was developed using Python 3.6. Because biomarker values were skewed, non-parametric tests were used. Differences between groups were assessed using the non-parametric Kruskal–Wallis test followed by Dunn’s multiple-comparison test if significant. Because post hoc analysis involved a large number of comparisons, reported p < 0.0001) and CTRL (p = 0.0001) while the concentrations were similar in CTRL and MCI  had significantly higher CSF Ng concentrations than the AD biomarker-negative CTRL group subjects   were excluded from the control group, as they were considered having preclinical AD pathology. Similarly, the AD biomarker-positive ADD and MCI groups both had significantly increased CSF Ng concentrations compared to the biomarker-negative group (p < 0.0001 for both)  .CSF Ng concentrations were significantly higher in ADD compared to both MCI p < 0.000 and CTRLp < 0.0001), PD MCI (p = 0.005), PDD (p < 0.0001), DLB (p = 0.002), CBS (p = 0.03), and PSP (p = 0.004)  and ALS (p < 0.0001)   and similar CSF Ng concentrations as ADD . We found that Ng significantly increased the SVM model’s ability to discriminate between numerous pairs of disorders. More specifically, the inclusion of Ng led to an increase in 24% accuracy in distinguishing between CTRL and bvFTD, 3.6% increase for MCI vs bvFTD, and 9.5% increase for PD vs bvFTD. Including Ng also led to a 7.7% increase in accuracy in distinguishing between MCI and PD, 6.4% increase for MCI vs PD MCI, and 4.3% increase for MCI vs PDD (see Online Resource 3).s and p values). p-tau correlated with CSF Ng in CTRL (rhos = 0.39), MCI (rhos = 0.60), and ADD (rhos = 0.56)  as well in PD MCI , DLB , and bvFTD  but not in the other diagnoses  while a stronger positive correlation with CSF Aβ42 was found in ALS    which was no longer observed after covariate adjustment    Fig. a. In the.3) Fig. b. There APOE ε4 alleles, CSF Ng increased in a gene dose-dependent manner with the highest Ng concentrations in the group homozygous for the ε4 allele   Fig. b. There nce Fig. c.Fig. 5Sp = 0.03), frontotemporal lobar degeneration FTLD (p = 0.006), and ALS (p = 0.03)  and Aβ plaque (p = 0.0002) pathology compared to no (or negligible) AD pathology   , as well as in the Braak stage , and in the CERAD score   and between stages 1 and 3 (p = 0.02) in Thal staging, along with a significant difference between stages 2 and 3 which was no longer significant after multiple comparisons correction . For Braak staging, there was a significant difference in CSF Ng between stages 0 and 3 (p < 0.0001) and between stages 1 and 3 (p = 0.002), along with a significant difference between stages 0 and 2 which was no longer significant after multiple comparisons correction . Finally, in the CERAD scheme there was a significant difference in CSF Ng between stages 0 and 3 (p < 0.0001) and a nearly significant difference between stages 1 and 3 (p = 0.054).Next we averaged CSF Ng values for subjects with postmortem evaluation of AD pathology according to a pathology classification table as previously described . We thenHere, we report on CSF Ng concentrations in both clinically diagnosed and in neuropathologically confirmed subjects, and show that CSF Ng concentrations were significantly higher in ADD compared to DLB, FTD and ALS. Further, increased CSF Ng concentrations correlated with increased Aβ plaque load, specifically in the hippocampus and amygdala, probably reflecting synaptic damage induced by aggregation of Aβ and accumulation in plaques.http://www.alzforum.org/alzbiomarker). As Ng is expressed in dendrites and as CSF Ng concentrations correlate with memory impairment and reduced cerebral glucose metabolism in ADD-affected brain regions [CSF Ng is a well-replicated biomarker for ADD , tangles (tau) and Lewy bodies (α-synuclein), and neuropathological studies have shown that ADD patients often have other concomitant pathologies, besides plaques and tangles , 24, 37.APOE ε4 allele compared to non-carriers. The same trend was observed for the MCI group but there was no statistically significant difference between the groups, which may be due to low number of patients included. This is in agreement with a previous study and shows that the number of copies of the ε4 allele may be associated with synaptic dysfunction which is reflected in the CSF as higher Ng concentrations [We found that CSF Ng concentrations in ADD were higher in patients having one or two copies of the trations . One exptrations . Thus, tThere was a significant association between the CSF Ng concentration and rate of cognitive decline, as measured by drop in MMSE scores per year in the MCI group. This is in agreement with previous studies  again shWe show that increased CSF Ng concentration occurs only in ADD and not in the other neurodegenerative disorders investigated in this study. One exception was lvPPA which displayed similar CSF Ng concentrations as those found in ADD. A plausible explanation is that a large number of lvPPA patients actually have ADD pathology , 33. HowThe CSF Ng concentrations were significantly increased in ADD compared to svPPA and nfvPNFA but also increased in lvPPA compared to bvFTD. This may be explanted by that svPPA and nfvPNFA are more predictive of FTLD-TDP and FTLD-tau, respectively. Thus, the finding reflects that lvPPA patients are likely atypical variants of ADD . In addibvFTD and PPA are diagnosed according the appearance of the symptoms. In the present study, CSF Ng concentrations in bvFTD were significantly lower than in ADD and lvPPA but also lower compared to CTRL which is in agreement with a previous study . In addiInterestingly, there was a strong positive correlation between CSF Aβ42 and Ng levels in the ALS group and at the same time, CSF Ng concentrations were significantly lower in ALS compared to ADD and even slightly lower than in CTRL. It is known that a small percentage of ALS patients have ADD pathology  and it wWhen evaluating novel CSF biomarkers for ADD, it is important to consider that concomitant pathologies are common, especially in elderly patients with dementia. To test CSF Ng as a specific biomarker for ADD, we investigated its performance in ADD and other neurodegenerative disease cases with definitive diagnoses determined by postmortem examination. However, the number of patients was low in some groups. Thus, larger studies including neuropathology confirmed patients are warranted.The study has a number of limitations that should be acknowledged. First, the sample size in some subgroups was small and the risk of false-positive statistical test warrants replication of the most interesting findings. Therefore, interpretation should be made with caution. Second, although our study replicates the specificity of CSF Ng for ADD, a number of novel findings regarding what CSF Ng may add to other markers need to be replicated in independent cohorts. Thus, in the future, we will seek verification of these results in other, independent datasets to investigate their clinical relevance.Some of the highest CSF Ng levels were found in two individuals in the CTRL group. Data from neuropathological examination were not available and, therefore, it is unknown whether these high levels are due to that these individuals have AD, or possibly other forms of pathology, a change in the overall clearance and production of Ng, or possibly if the very high values have analytical or technical explanations.In conclusion, CSF Ng is a biomarker specifically reflecting synaptic pathology in ADD and its concentration is linked to the extent of plaque pathology in the hippocampus and amygdala. The findings support the use of CSF Ng as a biomarker for diagnosing ADD and also for treatment trials, where disease-modifying drugs are evaluated, to monitor if treatment restores synaptic function in the patients.Supplementary material 1 (XLSX 11 kb)Supplementary material 2 (PDF 61 kb)Supplementary material 3 (XLSX 10 kb)Below is the link to the electronic supplementary material.


The aim of this study was to compare the intranasal premedication effect of newly introduced dexmedetomidine (DEX) versus midazolam on the behavior of uncooperative children in the dental clinic.This crossover double-blind clinical trial was conducted on 20 uncooperative children aged 2–6 years who required at least two similar dental treatment visits. The subjects were randomly given 1 μg/kg of DEX and 0.5 mg/kg of midazolam via the intranasal route. For the sedation protocol in the two groups, 0.25 mg/kg of atropine in combination with 0.5 mg/kg of midazolam added to 1–2 mg/kg of ketamine were used 30 minutes after premedication and transferring the patient to the operating room. Dental treatments were carried out by a pediatric dentist blinded to the type of the administered premedication. The sedative efficacy  of the agents was assessed by two independent pediatric dentists based on the Houpt scale. Data analyses were carried out according to Wilcoxon signed-rank test and paired t-test.There were no significant differences in the premedication efficacy of intranasal DEX and midazolam according to the Houpt scale (P>0.05).Intranasal midazolam and DEX are satisfactory and effective premedication regimens for uncooperative children. Sedation is one of the most common methods practiced in dentistry for the treatment of children and adults who are anxious or fearful towards dental procedures to make the process as painless as possible . One of Intranasal drug delivery bypasses the classic BBB obstacles by penetrating into the cribriform plate and by exploiting the paracellular and active neuronal pathways . For manHowever, this drug was introduced to dentistry after 2005 –14. DEX This randomized crossover double-blind clinical trial (IRCT No: 201601281882N7) was conducted on 20 children aged 2–6 years who were referred to the department of pediatric dentistry of school of dentistry of Shahid Beheshti University of Medical Sciences. Uncooperative 2–6-year-old children with negative or definitely negative behaviors according to the Frankl behavioral rating scale and with health classification of ASA I in the American Society of Anesthesiologists (ASA) physical status classification system were included in this study for dental treatments under deep sedation . We used2), respiratory rate (RR), heart rate (HR), and blood pressure (BP) were recorded at the start and at the end of the treatment session. All the subjects were kept at NPO (nothing by mouth) status for 6 hours (solid foods) and 4 hours (water and liquids) before the operation. The children were randomly assigned to two groups of A: intranasal sedation with midazolam, and B: intranasal sedation with DEX. A questionnaire was used to record the medical and dental histories. In group A, 0.5 mg/kg of midazolam  was dropped into the nostrils, while in group B, 0.1 μg/kg of DEX  was dropped into the nostrils by a blinded pediatric dentist by using an insulin syringe [2 was administered to all the patients throughout the procedure. The SpO2 was monitored at various stages of the study, starting with the premedication time (the baseline), by using a multipurpose monitoring unit . All the measurements were made at the baseline, at the IV puncture time, and at the end of the dental treatment. The Houpt scale was used to record the changes in the children’s behavior according to the following categories: the amount of crying (C), sleeping (S), movement (M), and overall behavior (O) [The primary vital signs of oxygen saturation  . Video rData related to the twenty 2–6-year-old children (12 boys and 8 girls) were recorded. The mean age of the patients was 4.1±11.14 years, and the mean weight was 14.51±3.09 kg. The initial evaluation of the Frankl behavioral rating scale revealed that 14 cases (70%) were definitely negative, while 6 cases (30%) were judged to be negative. Overall, no significant differences were found between the administered drugs (P=0.250). The comparison of sleep (S), movement (M), crying (C), and overall behavior (O) parameters showed no significant differences between the two groups at the IV puncture time P>0.05,  to 4. As2 (P=0.534), RR (P=0.337), and maximum and minimum BP .According to the parents, the most common postoperative complicatios were nausea, vomiting, drowsiness, and reduced activity during the initial 24 hours after the sessions involving midazolam or DEX premedication with no significant differences. The total amount of ketamine administered through the IV line for deep sedation was higher in the midazolam group compared to the DEX group; however, the difference was not significant (P=0.140). There were no significant statistical differences between the two groups with regard to the HR (P=0.150), SpOBased on the results of the present research, sedation techniques show a promising potential for resolving the children’s interfering behaviors in the dental office. Both intranasal midazolam and DEX regimens could provide certain levels of calmness for the child and dentist during dental procedures. Based on the results of this investigation, it appears that certain children with different degrees of fear and anxiety will take advantages of various sedation levels, while the others would enjoy current behavioral modification techniques . The besThe comparable sedative effects of midazolam and DEX according to the Houpt scale were similar to the results of many other studies such as the study by Sheta et al . Post-seDEX and midazolam showed comparable premedication efficacies.Both premedication regimens were efficient according to the Houpt scale.All the vital signs remained within the normal range during the procedure, and no interventions were needed.The most common side effects during the first 24 hours were vomiting and dizziness for both premedication regimens.


Premature infants are at risk for severe sepsis and meningitis, both infections associated with high mortality and morbidity. Cerebro-spinal fluid (CSF) culture is the gold standard method for meningitis diagnosis, but interpretation of biochemical parameters of CSF is essential at the moment of the analysis in order to start the appropriate treatment. The main objective of this study was to determine whether levels of CSF beta-2-microglobulin (B2M) were elevated in preterm infants with CNS infections or other inflammatory processes, and to establish if there were differences in B2M concentrations amongst various inflammatory settings ).This is a retrospective study of all very preterm and extremely preterm infants (< 32 weeks of gestation) admitted to our NICU between 2012 and 2017. All those who underwent a lumbar puncture during their stay as part of a sepsis work-up or PHVD were considered for inclusion. CSF biochemical parameters and B2M were tested in all of the patients.Fifty-nine patients were included in the study. In patients with CNS infections, the median value of B2M was 8.69 mg/L (3.92–18.5). B2M levels above 3.92 mg/L showed greater sensitivity and specificity than leukocyte levels in discriminating between patients with CNS infections or other inflammatory processes and those without CNS inflammation.In this population, CSF B2M proved to be an effective biomarker to discriminate between patients with CNS infections and other inflammatory processes and those without CNS inflammation. Premature infants are at increased risk of sepsis and meningitis . Five peReference values of white blood cells (WBC), CSF protein and glucose in the CSF of healthy term newborns are widely described in the literature ,6,7. HowTo improve the utility of LPs, several cytokines have been used to discriminate between bacterial and viral infections , 9. HoweBeta-2-microglobulin (B2M) is a low molecular weight protein 11800D) that constitutes the light chain of the class I major histocompatibility complex . Its pre800D thatHigh CSF B2M levels have been reported in neonates with CNS infections ,14. HoweWith this study, we sought to assess CSF B2M concentrations in very preterm and extremely preterm infants in the setting of different clinical conditions.The objectives of this study were: (1) to determine whether levels of CSF B2M were elevated in very preterm and extremely preterm infants with CNS infections or other inflammatory processes, and (2) to determine if there were differences in CSF B2M concentrations between various inflammatory settings ) in very preterm and extremely preterm infants.3 in the CSF in patients without intracerebral hemorrhage, were excluded.Medical records of all very preterm (28–32 weeks of gestation) and extremely preterm infants (<28 weeks of gestation) who were admitted to the NICU at Hospital Sant Joan de Déu, Barcelona between 2012 and 2017 were reviewed. All preterm infants who underwent an LP during their stay as part of a septic work-up or PHVD evaluation were considered for inclusion. Patients with traumatic lumbar punctures, defined as the presence of >500 red blood cells (RBC)/mmData were obtained from the medical records of enrolled subjects and stored in an electronic database. Information collected included demographics, vital signs, birth histories, and other clinical variables related to the NICU clinical course.Included subjects were classified into three groups based on the final diagnosis and the reason for the LP:Patients with normal CSF and no CNS infection. In these patients, an LP was performed to rule out infection because of clinical or analytical suspicion or positive blood culture. All of these patients had negative CSF cultures and polymerase chain reactions (PCRs), WBC < 20mm3, and normal glucose and protein levels.3) and/or microbiologic confirmation of a CSF infection based on a positive CSF culture or PCR.Patients with pleocytosis  or >15/mm3 (for infants aged 29–56 days).Post-hemorrhagic ventricular dilatation was defined as either a rapid severe increase in lateral ventricle size on cranial ultrasound within seven days of IVH or the continued progression of ventricular dilatation identified on cranial ultrasound for more than 14 days after IVH, characterized by a change in qualitative classification. PHVD was monitored using ventricular index and anterior horn width [rn width .CNS inflammation was defined as increased WBCs in the CNS due to an infection or an inflammatory process after an IVH.CSF evaluations included a standard cytochemical analysis with quantification of WBC, RBC, protein and glucose levels, and quantification of B2M concentration. In our center, B2M concentration is routinely performed in newborn CSF evaluations. All biochemical CSF parameters, including B2M levels, are reported within two hours.CSF gram-stains and cultures were performed. If a viral infection was suspected, viral PCR was also performed.Continuous variables were described using mean, median, SD and range. The comparison between numerical variables was performed by an analysis of variance test (one-way ANOVA) and Kruskal-Wallis test. The Spearman correlation method was used to calculate the correlation between continuous variables. Multivariable analysis was performed and logistic regressions were used. ROC curves were obtained to evaluate the efficacy of the tests. Statistical significance was met when the P value was less than 0.05. Statistical analyses were processed with statistical software STATA13.All data used in this study were collected from patient medical records and de-identified. Informed consent was not obtained because the study was retrospective. Declaration of Helsinki  was considered for the research. The project was approved by the local Ethics Committee Table 1.Of 73 very preterm and extremely preterm infants with at least one CSF B2M measurement, 6 were excluded due to an unclear diagnosis of meningitis and 8 were excluded due to traumatic lumbar puncture. Mean gestational age at birth was 27.25 weeks with a range between 23–32 with a mean birth weight of 1026.37g with a range of 430g-1780g. The main clinical characteristics of our patients are included in There were 59 CSF samples. In 45 patients, an LP was performed to rule out sepsis. The remaining 14 patients suffered from PHVD, and therefore an LP was performed to reduce CSF pressure. Six of these patients with PHVD had ventricular reservoir tapping following an LP.Table 2).WBC, glucose, protein and B2M in CSF were significantly different between the 3 groups (p<0.05) (There was an increase in WBC and protein levels in the CNS infection group when compared to the others (p = 0.001). PHVD and CNS infection groups exhibited significantly higher CSF B2M levels when compared to the control group (p = 0.0001). In the post-hoc analysis, CSF B2M levels between PHVD and CNS infection groups were also different (p = 0.02), with the highest levels in infected patients.Fig 1).In the CSF, B2M had a strong direct correlation with WBC  and a moderate direct correlation with protein levels . There was a moderate inverse correlation between B2M and glucose . There was a weak direct correlation between B2M and RBC  (36 patients were included in the control group. Patients in this group included those with a “suspected infection” (n = 7), “infection without culture confirmation” (n = 10) and “sepsis with positive blood cultures but without CNS involvement” (n = 19).Median levels of B2M were 2.45 mg/L (2.1–3.14), 2.64 mg/L (1.87–3.47) and 3.05 mg/L (1.16–4.63) in the three sub-groups respectively, without statistically significant differences. There were no differences in protein, WBC or glucose levels amongst these sub-groups.Klebsiella oxytoca, Escherichia coli, Serratia marcencens, CMV). The mean level of B2M in this group was 9.03mg/L (5). The mean WBC level was 2263.33/mm3, and the mean glucose level was 34.2mg/dL (28.2).There were 9 patients in the meningitis group, 5 of them with a positive culture or positive viral detection  were also elevated, with the highest levels in those patients with a ventriculostomy catheter reservoir.These results are shown in In order to evaluate whether or not B2M is a useful tool to identify patients with CNS inflammation (including those with a CNS infection or PHVD), the main biochemical parameters in CSF were analyzed.WBC, the most commonly used parameter to identify patients with CNS inflammation, had a relatively low sensitivity of 77.27%, despite a high specificity of 100% (AUC = 0.8955). Using a ROC curve, we determined the optimal cut-off point for the detection of CNS inflammation to be 25 WBC/mm3. Overall, the WBC count was not the most effective marker of CNS inflammation.B2M as an indicator of inflammation had a sensitivity of 86.96% and a specificity of 94.44%, with an AUC = 0.9330. The optimal cut-off point obtained using a ROC curve was 4.04 mg/L.Sensitivity, specificity, positive predictive value, negative predictive value and false negative percentage of these parameters utilizing these cut-off values are summarized in Multivariable logistic regression analysis was used to assess the best predictive model for CNS inflammation. The combination of B2M levels and glucose was the best equation to predict inflammation , however, this combination was not significantly better than B2M alone (p = 0.2188). Other equations including WBC or protein levels did not improve the predictive model.Fig 2.ROC curves for CSF B2M levels and WBC as a means of screening for CNS inflammation are shown in A similar process was utilized to identify the best CNS infection biomarker. We excluded all patients with PHVD in the analysis to avoid confounding variables.WBC as an indicator of CNS infection had a sensitivity of 100% and a specificity of 78.4%, with an AUC of 0.9505. The optimal cut-off value to diagnose a CNS infection was 30 WBC/mm3.B2M as a biomarker for CNS infection had a sensitivity of 88.89% and a specificity of 100%, with an AUC of 0.9938. The optimal cut-off point to diagnose a CNS infection was 3.92 mg/L.Sensitivity, specificity, positive predictive value, negative predictive value and false negative percentage of these parameters utilizing these cut-off values are summarized in Multivariable logistic regression analysis was also used to assess the best predictive model for CNS infection. The best equations to predict infection were the combination of WBC with B2M and B2M alone. The comparison of two ROC curves was not statistically different  and infection (17%). The combination of B2M with other CSF biomarkers did not improve the ability of B2M to predict inflammation in this population. It would be beneficial to perform a prospective study in order to determine a better cut-off point for B2M that excluded all false negatives to improve meningitis diagnosis in very preterm and extremely preterm infants.B2M is significantly increased in the CSF of very preterm and extremely preterm newborns with cerebral infections and other CNS inflammatory processes, such as PHVD. It seems to not be altered by moderate amounts of blood in the CSF (up to 500 RBCs), which is especially important when considering a biomarker in newborn infants given the technical challenges of performing lumbar punctures in this population. B2M has the potential to aid in the early and accurate diagnosis of meningitis, which can result in more timely and appropriate antibiotic administration.S1 File(XLS)Click here for additional data file.


The Centiloid scale has been developed to standardize measurements of amyloid PET imaging. Reference cut-off values of this continuous measurement enable the consistent operationalization of decision-making for multicentre research studies and clinical trials. In this study, we aimed at deriving reference Centiloid thresholds that maximize the agreement against core Alzheimer’s disease (AD) cerebrospinal fluid (CSF) biomarkers in two large independent cohorts.N = 205) and ADNI (N = 311) underwent amyloid PET imaging  and core AD CSF biomarker determination using Elecsys® tests. Tracer uptake was quantified in Centiloid units (CL). Optimal Centiloid cut-offs were sought that maximize the agreement between PET and dichotomous determinations based on CSF levels of Aβ42, tTau, pTau, and their ratios, using pre-established reference cut-off values. To this end, a receiver operating characteristic analysis (ROC) was conducted, and Centiloid cut-offs were calculated as those that maximized the Youden’s J Index or the overall percentage agreement recorded.A total of 516 participants of the ALFA+ Study  contains supplementary material, which is available to authorized users. In the clinical setting, PET scans are visually read by trained specialists and are categorized as either positive or negative flutemetamol and CSF core AD biomarkers [ALFA+ is a nested longitudinal long-term study of the ALFA (for ALzheimer’s and FAmilies) cohort . In brieomarkers . The fir18F]florbetapir.In order to have generalizable results reflecting the whole AD continuum, 311 participants from ADNI were also included in this study selected according to the following inclusion criteria: (1) AD CSF core biomarkers analysed with the Elecsys® tests available, (2) amyloid PET scan acquired in less than a year from CSF collection available, and (3) MRI acquired with a difference from the time of the PET acquisition of less than a year. All ADNI PET images included were acquired with flutemetamol PET scan was acquired in all participants . The T1-weighted 3D-TFE sequence was acquired in a Philips 3 T Ingenia CX scanner with a voxel size of 0.75 × 0.75 × 0.75 mm3, FOV 240 × 240 × 180 mm3, sagittal acquisition, flip angle 8°, TR = 9 .9ms, TE = 4 .6ms, TI = 900 ms. PET imaging was conducted in a Siemens Biograph mCT, following a cranial CT scan for attenuation correction. Participants were injected with 185 MBq (range 166.5–203.5 Mbq) of [18F]flutemetamol, and 4 frames of 5 min each were acquired 90 min post-injection. Images were reconstructed with an OSEM3D algorithm using 8 iterations and 21 subsets and with point spread function (PSF) and time of flight (TOF) corrections into a matrix size of 1.02 × 1.02 × 2.03 mm.Each cohort had its own acquisition protocol. For ALFA+, a T1-weighted MRI and an florbetapir, which consisted of 4 frames of 5 min each, acquired at 50 to 70 min post injection. Most of the T1 sequences used for normalization were magnetization-prepared rapid acquisition gradient echo (MPRAGE), acquired with 1 .5T or 3 T scanners. All images, ALFA+ and ADNI, were visually inspected for quality control.The methods for ADNI PET and MRI acquisition methods are described in more detail elsewhere (https://www.fil.ion.ucl.ac.uk/spm/software/spm12/). In brief, PET frames were coregistered. Averaged images were then coregistered to corresponding MRI scans. MRIs were then segmented and normalized to the MNI space together with PET images. We calculated the SUVr in MNI space using the target region provided in the GAAIN website (www.gaain.org) and the whole cerebellum as reference region. SUVr values were then transformed to the Centiloid scale as explained in Additional file All PET images were preprocessed following the Centiloid  pipelineT test for independent samples was used with continuous variables and χ2 with dichotomous variables. To be able to directly compare Aβ42 measures from both cohorts, we had to transform ADNI data to account for pre-analytical conditions [Demographic characteristics of both cohorts were first compared. nditions . This tr42, phosphorylated tau (pTau), total tau (tTau), and pTau/Aβ42 and tTau/Aβ42 ratios. For each CSF biomarker as binary outcome, optimal cut-offs were selected as those showing the maximum value of one of the statistics after minimally smoothing true-positive, true-negative, false-positive and false-negative curves using the ‘smooth’ function in Matlab (v2018b) with the ‘lowess’ method and a span value of 0.1.Optimal Centiloid cut-offs were calculated as those that maximized the Youden’s J Index (YI) or the overall percentage agreement . YI statistic consists of the summation of the sensitivity and specificity , and then = 5000).On top of YI and OPA, we also calculated the positive percentage agreement  and negative percentage agreement  and the area under the curve (AUC) of the receiver operating characteristic (ROC) analysis. All 95% confidence intervals (95% CI) for all statistics were derived using bootstrapping methods . PPA and NPA values for these CL cut-offs are shown in Table Derivation of Centiloid cut-off against Aβ42 was higher in the ADNI cohort than in ALFA+  to plateau between 10 and 40 CL . In this study, this was achieved by pooling the ADNI and ALFA+ datasets.In this paper, we sought to calculate the optimal Centiloid cut-off values from amyloid PET data to maximize the agreement against previously established thresholds for positivity on core AD CSF biomarkers. At a first glance, this might be regarded as a circular exercise, since these CSF cut-offs were originally derived to maximally concord with positive visual reading of PET scans. Under this rationale, all resulting Centiloid cut-offs would have be expected to fall in the range that optimally discriminates negative from positive visual reads, which is between 25 and 35 CL . On the reported . Almost 42 cut-offs in the two cohorts confirmed this rationale. In the ADNI sample, optimal values fell in the expected range of visual reads (between 33 and 36 CL) whereas the optimal threshold in the ALFA+ sample is closer to that in the pooled sample (between 5 and 11 CL). This result confirms that the derivation of optimal cut-offs is very sensitive to the recruitment strategy of the reference sample, with clinical ones rendering higher cut-offs than population based ones with a better representation around the range of values where cut-offs are expected to lay. Previous literature has suggested that CSF Aβ42 values become positive before amyloid PET [The independent derivation of optimal CSF Aβloid PET , 22. ThiAlthough 12 CL may initially be regarded as a low value for amyloid positivity, it matches recent reports of Centiloid cut-offs against postmortem measures of AD neuropathology showing that 12.2 CL optimally detected Consortium to Establish a Registry for Alzheimer’s Disease (CERAD) moderate-to-frequent neuritic plaques, whereas 24.4 CL identified intermediate-to-high AD neuropathologic change (ADNC) differences . Another42, for tau/CSF Aβ42 ratios, the optimal CL cut-offs fell within the expected range (28–30 CL) given the linear relationship between this biomarker and amyloid PET Centiloids. Indeed, tau/CSF Aβ42 ratios showed higher AUC versus amyloid PET Centiloids than CSF Aβ42, in agreement with the previous reports [42 ratios to predict Centiloids may be accounted for by two different factors. On the one hand, CSF ratios may provide a more stable measurement than absolute values since they provide an inherent normalization against protein production and release to the CSF, between-individual variations in CSF dynamics, and pre-analytical conditions. Therefore, the lower variability in the CSF ratios may account for better AUCs. On the other hand, CSF Aβ42 has been proposed to become abnormal prior to amyloid PET [continuum [42.Unlike CSF Aβ reports , 30, 31.loid PET , 41. ThiTogether with previous studies, the observed thresholds might be useful to flag two different inflection points in preclinical AD stages. A cut-off below 12 CL might be optimal to rule out-amyloid pathology, whereas a cut-off over 29 CL might be denoting established pathology. These kinds of thresholds have typically been used to dichotomize continuous values into two categories for clarity and ease of use. However, alternatives have also been considered and include the score of the severity of each biomarker on a semi-continuous scale as considered, for instance, in the A/T/N scheme . Therefocontinuum would be needed. This is a relevant effect because in previous similar works, the Youden’s Index has been typically selected as the reference measurement of agreement [Two goodness criteria have been used here to derive optimal cut-offs: the Youden’s Index, which balances sensitivity and specificity, and the overall percentage agreement, which is sensitive to the percentages of positives versus negatives in the test sample. Both rendered very similar values and the Centiloid cut-offs proposed here are robust against variations in the threshold values for CSF positivity. Still, the Youden’s index showed a more noisy behaviour than the overall percentage agreement, particularly in the analysis of the two individual samples. In order to obtain more robust estimates of classification performance, more subjects across the full AD greement , 30, 31.Irrespective of the approach to counter the effect of noisy agreement estimates, additional analysis with larger samples might be needed to yield more robust and generalizable cut-offs. To this end, future work will focus on pooling additional samples. In addition to a limited sample size, we rely on the comparability of PET and CSF measures across the two studied samples. While agreement on CSF data is certainly improved with the Elecsys® tests and with the use of the Centiloid method on PET scans, we cannot rule out the presence of a certain degree of sample-dependent bias in the data analysed. Still, when computing the cut-offs solely using the ALFA+ cohort results were very similar, thus suggesting that any remaining bias is small and did not have a significant impact on our results. Another limitation may stem from the somewhat limited sample analysed here may not be sufficient to derive robust generalizable cut-off values. Additional analysis with bigger sample sizes and more amyloid PET tracers that the two used here may overcome this limitation.42 positivity, in line with Centiloid thresholds derived against post-mortem measures of AD neuropathology. On the other hand, CSF tau/Aβ42 ratios were better predicted by a higher Centiloid cut-off of 29 CL, which is in line with those optimally discriminating positive from negative visual reads on PET scans. In agreement with previous reports, CSF tau/Aβ42 ratios showed a higher capacity to predict amyloid PET Centiloids than CSF Aβ42. Overall, our results provide reference values in the Centiloid scale and suggest two relevant inflection points the development of early AD pathology across the full AD continuum.In summary, we have derived optimal Centiloid values to maximize the agreement against core AD CSF biomarkers. Regarding Aβ, a relatively low value of 12 CL optimally corresponded to CSF AβAdditional file 1:Supplementary data including supplementary methods and results. (DOCX 1010 kb)


Grooving is widely used to improve airport runway pavement skid resistance during wet weather. However, runway grooves deteriorate over time due to the combined effects of traffic loading, climate, and weather, which brings about a potential safety risk at the time of the aircraft takeoff and landing. Accordingly, periodic measurement and evaluation of groove performance are critical for runways to maintain adequate skid resistance. Nevertheless, such evaluation is difficult to implement due to the lack of sufficient technologies to identify shallow or worn grooves and slab joints. This paper proposes a new strategy to automatically identify airport runway grooves and slab joints using high resolution laser profiling data. First, K-means clustering based filter and moving window traversal algorithm are developed to locate the deepest point of the potential dips . Subsequently the improved moving average filter and traversal algorithms are used to determine the left and right endpoint positions of each identified dip. Finally, the modified heuristic method is used to separate out slab joints from the identified dips, and then the polynomial support vector machine is introduced to distinguish out noises from the candidate grooves (including noises and true grooves), so that PCC slab-based runway safety evaluation can be performed. The performance of the proposed strategy is compared with that of the other two methods, and findings indicate that the new method is more powerful in runway groove and joint identification, with the F-measure score of 0.98. This study would be beneficial in airport runway groove safety evaluation and the subsequent maintenance and rehabilitation of airport runway. Since the early 1960s, grooving has been increasingly used on airfield pavements and roadways to improving tire-pavement friction through efficient water-run-off and prevent airplanes or vehicles from accidents . The purPast studies indicate that groove dimensions can be automatically measured using point laser ranger-based profiling equipment and 3D laser imaging sensor-based instruments ,13,14,15Currently there are four methods for the potential dip identification ,12,14,16The determination of the two endpoint positions of grooves is critical for the computation of groove dimension. Previous studies indicate there are three methods for the determination of two endpoints of grooves ,12,13,14Although the groove identification algorithm in ProGroove can identify out grooves and joints, the unsatisfactory results are obtained. The authors of  presenteIn summary, current studies on groove identification and measurement still have three limitations: (1) they cannot avoid the presence of fake grooves or noises in the process of attempting to find more true grooves; (2) they may miss some grooves and joints if these thresholds are inappropriately set, and the number of identified grooves and joints has a large variation or fluctuation with the change of parameter settings; (3) they cannot exactly localize the slab joints in the scenarios that have more identified dips within a possible range of next slab joint if the heuristic method is used to determine the slab joint location. To address these issues, the more promising and powerful algorithms should be investigated. To accomplish this goal, the point laser-based profiling equipment developed by the U.S. Federal Aviation Administration (FAA) is employed to collect grooving data on a full-scale runway. Subsequently the slab joint and true grooves are separated out from the identified dips that are produced with the K-mean clustering method and moving window traversal method. Finally, the identification and measurement results from the new method is compared with the algorithm in the ProGroove software  and Li’sFAA point-based laser profiling equipment was developed to conduct the rapid measurement of surface elevation profiles on airport runways, in which an accelerometer and vertical distance sensor are used to measure true changes in concrete or bituminous pavement elevation. With the high-power point laser system, this profiling system can work at highway speeds during daytime and nighttime and maintain data quality and consistency. That means the profiling data can be acquired at any time of the day, regardless of lighting conditions. Even though this system has been designed to accommodate all dynamic and static conditions incurred during normal driving conditions, it cannot collect data on wet runways in rainy days. In addition, the contaminants on runway surface should be cleaned off before data collection, i.e. removal of rubber deposits, removal of sand, dust, mud, etc. It is strongly recommended parking the profiling system either indoors or under certain type of shelter in case of inclement weather since it is not dust-proof and water-tight.When the profiling system is used for data collection, its parameters or settings should be properly configured, and then the user can open the collection screen and start data collection. The collected data can be plotted in real time in the main widow. The collected data (.dat file) are saved to the designated directory for post-processing. Airport runway surveys are usually conducted at after midnight without any traffic interruption. Typically, each single measurement or pass needs about two minutes depending on airport runway length and the driving speed. The total time for accomplishing the entire runway survey needs about 40 to 60 min depending on the number of measurements or passes.In previous studies, a four-stage method is proposed for automated groove measurement and evaluation, in which runway grooves can be identified out with Li’s method . HoweverIdentification of runway grooves is dependent on the elevation difference between the raw grooving data and the low-pass filtered data (termed the base curve). A potential dip or candidate groove can be determined if the corresponding elevation difference are greater than a prescribed threshold. Two key problems need to be addressed for the identification of potential dips: (1) the determination of the base curve; (2) the selection of the threshold. For grooving data, the generation of base curve is susceptible to impacts of narrow and deep dips, which would lead to the elevation difference at dips are less than the actual dip depths. This phenomenon would bring in the difficulty in identifying shallow or worn grooves if the threshold is given. To solve this issue, K-means clustering based filter is proposed and used to determine the base curve.The basic idea behind the new filter is to partition n observations into k clusters or groups in which each group belongs to the cluster with the nearest mean ,20. In tx2,⋯,xn) a can be (1)Assign an initial set of 3-means (2)Assign each observation to the cluster whose mean has the least squared Euclidean distance, as mathematically described in Equation (1):(3)Calculate the new means to be the centroids of the observations in the new clusters, as mathematically described in Equation (2):The implementation proceeds by alternating between two steps (2) and (3), and is converged when the within-cluster sum of squares for the chosen set of grooving data are minimized. Finally, the three clusters and their centroids can be determined, as mathematically described in Equation (3):The new grooving data can be calculated by using raw grooving data to subtract base curve, as mathematically described in Equation (4): In previous studies, a prescribed threshold is used to identify the potential dips. Usually true grooves may be not successfully identified out if the given threshold is too large, while more fake grooves or noises would be introduced if the given threshold is too small. Accordingly, the selection of threshold is critical for the accurate identification of potential dips. To address this issue, moving window traversal algorithm is proposed to locate the deepest point within each potential dip across the window length (BL). Practically the moving window length is dependent on groove space. For each point The calculation of dip dimension is dependent on the three elements of a dip, namely the deepest point, left endpoint, right endpoint. Therefore, the following task is to find out the two endpoints of a dip once the deepest point is located.In this study backward traversal technique is used to locate the left endpoint of a dip. Its implementation starts at the deepest point of a dip until the traversed gradient is no smaller than zero, and simultaneously the current pixel value is larger than the corresponding pixel value of the auxiliary curve. The calculation of gradient of a point can be mathematically described in Equation (6):Similarly, the forward traversal technique is used to find the right end point of a dip, starting at the deepest point of a dip until the traversed gradient is no larger than zero and the current pixel value is larger than the corresponding pixel value of the auxiliary curve. Once the deepest point inside dips and the two endpoints of dips are determined, dip dimension can be computed based on the procedure specified in the FAA Advisory Circular No. 150/5320-12C [Groove volume, an important statistical index associated with wet pavement safety, is initially proposed to describe the drainage capacity of measured grooves. Grooving volume equals to the sum of elevation difference between the base curve and raw grooving data for all points inside each groove, as the right plot in The identified dips consist of true grooves, slab joints, and other noises . Therefore, true grooves should be distinguished out from the identified dips firstly before they are used for airport runway safety evaluation. This goal can be implemented in two phases: (1) use the modified heuristic method to separate out slab joints from the identified dips, in which the naïve Bayesian classifier is introduced; (2) use the polynomial support vector machine to distinguish true grooves with noises. Finally, the slab-based groove performance evaluation can be performed.To separate out slab joints from the identified dips, the naïve Bayesian classifier is introduced to modify the heuristic method in this study. Its implementation can be described using Naïve Bayes is a simple technique for constructing classifiers: models that assign class labels to problem instances, represented as vectors of feature values, where the class labels are drawn from some finite dataset ,22,23. TThe identified dips falling inside the possible range of the next joint can be divided into two classes: the groove or noise In practice, the identified dip depth, width and volume belongs to a continuous dataset, so a typical assumption is that the continuous values associated with each class are distributed according to a Gaussian distribution. For instance, the training feature In Equation (7) there is interest only in the numerator, because the denominator does not depend on classes In addition, the percentage of the cases where the joints fall or not in the PLRoNG is examined based on the twenty concrete slabs. In this study the NSL equals to the mean (4.46 m) of the measured slab lengths in fields, and SLTR (0.054 m) equals to two times the standard deviation. The findings indicates the chosen twenty slabs all fall in the PLRoNG since the maximal and slab lengths are 4.51 m and 4.41 m, respectively. Once slab joints are distinguished from the identified dips, the following task is to separate out noises and true grooves using Support Vector Machine (SVM) based on the three variables or vectors namely dip depth  is used to replace Assume the optimal Lagrange multiplier is {As a result, the category that contouring box belongs to can be determined based on Equation (19). If the sign of The FAA AC No. 150-5320-12C provides standard groove configuration and the tolerable range in depth, width, and spacing for the entire airport runway or each PCC slab [One small section of the grooving data, made of 100,000 discrete points, are chosen to illustrate the implementation of automated groove identification, measurement and evaluation. The chosen grooving data provided by FAA has been in service for several years, with a length of approximately 95 m, as shown in The implementation of groove measurement and evaluation is organized as follows: (1) the potential dips are identified out with the three approaches namely the algorithm in ProGroove software, Li’s method, and the newly proposed method. The comparison results are analyzed based on identification results; (2) the slab joints are distinguished from the identified dips using the modified heuristic method, and then the true grooves are separated out from the candidate grooves using polynomial SVM method. In this study the identified dips include true groove, slab joint, and other noises, whilst the candidate groove contains true groove and other noises; (3) the slab-based groove performance is evaluated, and the corrective measures can be taken on each concrete slab to improve runway skid resistance.To position the potential dips along runway grooving data, the K-means clustering based filter and moving window traversal algorithm are initially used to locate the deepest point of each potential dip. Each deepest point that is identified represents one potential dip. Subsequently, adaptive forward and backward traversal algorithms are used to find the left and right endpoints of each identified dip based on the location of the deepest points that are identified. Once the locations of the three elements  of a dip are determined, each potential dip dimension can be computed. The number of identified dips and from the three methods are summarized in As mentioned above, the identified dips with the three methods contain true grooves, slab joints, and other noises. To analyze the groove dimension distribution on each PCC slab and perform slab-based groove performance evaluation, the slab joint should be determined first.According to the heuristic method used in the paper , the slaIn this experiment, the number of identified joints with the algorithm in ProGroove software is about 319, which is 298 more than the ground truth. Accordingly, the algorithm in ProGroove software is inappropriate for slab joint identification. In light of joint locations, all the slab joints at the test section are identified with the proposed algorithm, and the identified joint locations correspond to the joint locations in field. Li’s method fails to detect two joints. As a result, the newly proposed method is more suitable for the slab-based groove performance evaluation.Once the slab joint is determined, the subsequent work is to separate out noises or fake grooves from the candidate grooves on each individual slab, and the polynomial SVM is used to achieve this goal. To quantitatively describe identification results of candidate grooves, three evaluation metrics namely precision, recall, and F-score are presented in this study . For eacOnce the TP, TN, FP, and FN are determined, three evaluation metrics can be calculated, as described in Equations (20)–(22). Generally, the larger the evaluation metrics is, the better the performance of the test algorithm is. An ideal or robust algorithm would have values of all evaluation metric approximating to one:The goal of the test algorithm is to be the precision and recall close to 1.0. However, the three methods produce the lower recalls when compared with their respective precisions. To conduct groove performance evaluation on each individual slab, it needs to report the statistical groove information for each individual slab based on classification results of grooves and joints. The measured groove dimension  and the three-evaluation index  with the proposed approach are summarized in According to the FAA AC No. 150-5320-12C guideline, there are no slabs that conform to the guideline requirement. For Slab3, although the percentages of grooved depths larger than 4.76 mm is over 90% and that larger than 6.35 mm is over 60%, the percentage of groove depths larger than 7.94 mm is more than 10%, which do not meet guideline requirement. For other slabs, the percentages of groove depths larger than 6.35 mm are less than 60%, which do not meet guideline requirements. To make grooves on each slab meet the FAA guideline requirement, part of grooves on each slab need to be corrected, as illustrated in The corrective activity aims to increase groove depths at test runways except for the Slab No 3, and to ensure groove depths are above the low limit of acceptable range. If the slabs after maintenance have the standard groove configuration, all evaluation indices comply with the FAA standard, which means the groove performance on this section is able to conform to the FAA guidelines once the 21 slabs (exclusive of Slab No 3) are maintained with corrective measures. Accordingly slab based evaluation method is able to provide airport authority with the slab number and also the percentage of slabs that need corrective actions. 3, which is computed as the product of the lower limit of groove depth by the design value of groove width. The design value of groove volume is 40.32 mm3, which is computed as the product of the standard groove width by the standard groove depth. However, groove depth cannot efficiently reflect the drainage ability of the test grooves. For instance, if two grooves have the same depths, they should have the same performance in accordance with the FAA groove evaluation guideline, but actually the two grooves could have the different drainage capacity due to the different groove volumes. As a result, the groove volume-based evaluation method is initially proposed for groove performance evaluation in this paper. 3), for Slabs No. 14, 16, 18–20, and 22, indicating the test runway grooves are not efficient for rapid discharge of the rainy water on the pavement surface during wet weather. Before any corrective measures are taken, the groove depths should be investigated. If the groove depth distribution does not meet the FAA guideline requirement, the corrective measures are taken to increase groove depth. If the groove depth distribution satisfies the guideline requirement, the cleaning work should be taken to sweep away the surface debris or loosened aggregate inside grooves and to ensure runway surface grooves have the good drainage ability during wet weather.Note that the measured groove volume is less than the acceptable volume value (30.23 mmIn this study a new methodology for automatic groove identification, measurement, and evaluation is proposed. First, experimental data are collected using the FAA point laser-based profiling equipment. The K-means cluster filter and moving window traversal algorithm are developed to identify the deepest point of each potential dip, and then the backward and forward transversal methods are used to position the left and right endpoints of the potential dip. Once the three elements of a dip are determined, the dip dimension is computed. Subsequently, the modified heuristic method is initially used to separate out slab joints from the identified dips, and the polynomial SVM is proposed to distinguish out the true grooves from the candidate grooves. The groove identification results with the new method are compared with that of the algorithm in ProGroove and the Li’s method, findings show the new method is more powerful in groove and slab identification, with the precision of 1.0, the recall of 0.96, and the F-measure of 0.98. Eventually, slab-based groove dimension performance can be evaluated in accordance with the FAA Advisory Circular AC 150-5320-12C. In addition, the groove volume-based evaluation approach is also proposed in this study, which would be beneficial in complimenting the existing runway groove performance methods. Runway pavement engineers can use the evaluation results as basis to take corrective measures on slabs with poor groove performance. Even though the new method produces the better precision and recall in groove identification than other existing methods, computation cost is expensive in k-means clustering, and usually it would take a longer time than other methods to process the same amount of data. Moreover, the point laser profiling instruments only collect one line-of-sight profile, which cannot reflect the entire runway groove information due to the limited quantity of profiles. In the future the line-scan imaging data can be used in lieu of point laser-based profiling system to conduct full runway measurement. To increase the computational efficiency, a new filter can be developed to replace the k-mean clustering-based filter in this method. The method presented in the paper can also be extended to the longitudinal or transverse groove performance evaluation for highway applications.


The results showed that a well-distributed crack network was formed on the Ti/Ta2O5-IrO2 electrode and Ti/Ta2O5-SnO2-IrO2 electrode due to the different coefficients of thermal expansion between the Ti substrate and oxide coatings. The oxygen evolution potential (OEP) increased according to the order of Ti/RuO2-IrO2 < Ti/Ta2O5-SnO2-IrO2 < Ti/Ta2O5-IrO2. Among the three electrodes, the Ti/Ta2O5-IrO2 electrode showed the highest efficiency and was chosen as the experimental electrode. Single factor experiments were carried out to obtain the optimum electrolysis condition, shown as follows: currency intensity 0.8 A; electrode spacing 3 cm, electrolyte pH 3. Under the optimum conditions, the degradation of nicosulfuron followed first-order kinetics and was mainly due to indirect electrochemical oxidation. It was a typical diffusion-controlled electrochemical process. On the basis of the intermediate identified by high performance liquid chromatograph-mass spectrometry (HPLC-MS), two possible degradation routes were proposed.The widely used sulfonylurea herbicides have caused negative effects on the environment and human beings. Electrochemical degradation has attracted much attention in the treatment of refractory organic compounds due to its advantage of producing no secondary pollution. Three kinds of IrO Sulfonylurea herbicides have been considered as “new formulation pesticides” because of their high selectivity and low persistence in the environment. They have been widely used to control a variety of broad-leafed weeds and grasses ,2. In reNicosulfuron, as one kind of widely used sulfonylurea herbicide, is characterized by the presence of the pyridine and pyrimidine rings connected with a sulfonylurea bridge in the molecule. It is a selective systemic herbicide and can be absorbed by the foliage and roots of plants and rapidly transferred to the meristematic tissues in xylem and phloem . Nicosul−1 to 0.002 d−1 as pH increased from 4 to 8, then remained stable under alkaline condition +)  .+), derived from the cleavage of the C–N bond of sulfonylureic bridge and from the loss of the N–CH2–CH3 group. It was identified as 2-aminosulfonyl-N,N-dimethylnicotinamide (C8H11N3O3S)(The intermediate product with retention time from 4.767 min to 4.850 min gave a molecular ion at m/z 213 ([M+H]H11N3O3S) and was +). The speculative substance was identified as 4,5-dimethoxypyrimidin-2-amine (C6H9N3O2)  . The oth6H9N3O2)  was deriFrom the speculated degradation product information, two degradation pathways of nicosulfuron under the electrolysis conditions were proposed, as shown in 2-based DSA electrodes were used to electrolyze nicosulfuron by a batch process. A well-distributed crack network was formed on the Ti/Ta2O5-IrO2 electrode and Ti/Ta2O5-SnO2-IrO2 electrode. Their OEPs increased according to the order of Ti/RuO2-IrO2 < Ti/Ta2O5-SnO2-IrO2 < Ti/Ta2O5-IrO2. Nicosulfuron was used as the model pollutant to choose the electrode with the highest performance. The Ti/Ta2O5-IrO2 electrode showed the highest efficiency and was chosen for use as the anode in the electrochemical experiment. The obtained optimum electrolysis conditions were: currency intensity 0.8 A, electrode spacing 3 cm, electrolyte pH 3. Under the optimum conditions, the degradation of nicosulfuron followed first-order kinetics and was mainly due to indirect oxidation. The redox reaction on the Ti/Ta2O5-IrO2 electrode was a typical diffusion-controlled electrochemical process. On the basis of the intermediates identified by HPLC-MS, two possible degradation routes of nicosulfuron were proposed, including the cleavage of the C–N bond of the sulfonylureic bridge and the opening of the pyridinic ring.The electrochemical method was chosen to degrade nicosulfuron due to its controllability and environmental friendliness. Three kinds of IrO


Alzheimer’s disease (AD) remains a clinical diagnosis but biomarkers from cerebrospinal fluid (CSF) and more lately amyloid imaging with positron emission tomography (PET), are important to support a diagnosis of AD.To compare amyloid-β (Aβ) PET imaging with biomarkers in CSF and evaluate the prediction of Aβ PET on diagnosis in a memory clinic setting.18F-Flutemetamol performed within 190 days. PET was binary classified (Flut+ or Flut-) and logistic regression analyses for correlation to each CSF biomarker; Aβ 42 (Aβ42), total tau (T-tau) and phosphorylated tau (P-tau), were performed. Cut-off values were assessed by receiver operating characteristic (ROC) curves. Logistic regression was performed for prediction of clinical AD diagnosis. We assessed the interrater agreement of PET classification as well as for diagnoses, which were made both with and without knowledge of PET results.We included 64 patients who had lumbar puncture and Aβ PET with 42 showed the highest correlation with 18F-Flutemetamol PET with a cut-off value of 706.5 pg/mL, corresponding to sensitivity of 88% and specificity of 87%. 18F-Flutemetamol PET was the best predictor of a clinical AD diagnosis. We found a very high interrater agreement for both PET classification and diagnosis.Thirty-two of the 34 patients (94%) in the Flut+ group and nine of the 30 patients (30%) in the Flut- group had a clinical AD diagnosis. There were significant differences in all CSF biomarkers in the Flut+ and Flut- groups. Aβ42 in CSF and 18F-Flutemetamol PET and the presented cut-off value for Aβ42 yields high sensitivity and specificity for 18F-Flutemetamol PET. 18F-Flutemetamol PET was the best predictor of clinical AD diagnosis.The present study showed an excellent correlation of Aβ Previous studies have shown a good correlation between 18F-Flutemetamol binding and neuropathological evidence of Aβ neuritic plaques [18F-Flutemetamol PET and CSF measurements of Aβ42 [Alzheimer´s disease (AD) is a progressive degenerative disease of the brain that mainly affect older people. It is the most common form of dementia and as the population grows older the prevalence is increasing. , 2. Ther plaques , 10 whil plaques –13. Elevallmarks . Evaluatallmarks –8. 18F-F plaques –17, as w of Aβ42 . Consequ of Aβ42 . However18F-Flutemetamol PET with CSF biomarkers to assess the optimal cut-off values, to evaluate the effect of the newly implemented cut-off value for Aβ42 and to investigate the prediction of 18F-Flutemetamol PET on a clinical AD diagnosis.The aim of this study was to correlate 18F-Flutemetamol PET and lumbar puncture for CSF sampling as a part of clinical routine in the workup of cognitive complaints between February 2015 and October 2018. Patients with less than 190 days between the two biomarker examinations were included from the memory clinic at Oslo University hospital (OUH), Ullevål. All included patients had signed a written consent form for inclusion in the Norwegian Register of Persons assessed for Cognitive symptoms (NorCog). At the time of inclusion in NorCog, all patients were deemed to have sufficient cognitive capacity to consent. Clinical data was extradited from the NorCog registry. In cases of inadequate information in the registry, the patients’ medical record was consulted. The study, as well as the consent procedures, were approved by the regional Ethics Committee for medical research in the South-East of Norway (REK 2017/1929) and the Data Protector Officer at our institution.This was an observational cross-sectional study consisting of 64 patients who had undergone both 18F-Flutemetamol. First a low-dose CT scan was performed for attenuation correction and anatomic information for the PET images. The low-dose CT was performed without contrast enhancement . PET data were acquired for 20 minutes (four frames of 5 minutes each), except for in one patient where the acquisition time was prolonged to 30 minutes to compensate for a lower amount of activity given (94 MBq). 3D dynamic emission data were reconstructed using a resolution recovery algorithm with time of flight . The slice thickness of the reconstructed image series was 2 mm, giving a voxel size of 2 x 2 x 2 mm3.All patients were examined using the same PET scanner, Siemens Biograph40 mCT . Image acquisition started 90 minutes (range 75–117 minutes) after patients received a bolus injection of 185 MBq 18F-Flutemetamol PET images were qualitatively classified using a Siemens SyngoVia workstation . Images were classified by visual assessment as positive if one of the following 5 regions, in either hemisphere, showed increased cortical uptake; frontal lobe, posterior cingulate and precuneus combined, lateral parietal lobe, lateral temporal lobe or striatum. This was performed according to the validated image reader program [18F-Flutemetamol PET had completed the validated online electronic training program course supplied by the vendor [ program . An expee vendor .42, T-tau and P-tau using the ELISA technique with the Innotest kit  was performed for all patients. The analysis was done at the laboratory at Akershus University Hospital, Norway. The laboratory is a part of the Alzheimer´s Association QC program for CSF biomarkers [42. As of October 2018, when these data were collected, the recommended cut-off values for a normal test from the laboratory were Aβ42 >700 pg/mL [A lumbar puncture with measurement of the CSF core biomarkers Aβomarkers . The rec00 pg/mL , P-tau <All patients were assessed according to a standardized and comprehensive research protocol including detailed information from the patients and the caregivers about symptoms, previous disorders, use of medication and demographic information . The cog18F-Flutemetamol PET. A third experienced physician was consulted in equivocal cases. All patients were assessed for clinical etiology (AD or non-AD), hereafter referred to as clinical diagnosis, and stage (subjective cognitive decline (SCD), mild cognitive impairment (MCI) or dementia). SCD was diagnosed using the criteria from the Subjective Cognitive Decline Initiative [Diagnosis and staging of cognitive impairment were made by two experienced memory clinic physicians. Diagnoses were made retrospectively based on all available information in medical records, in time-proximity to the PET examination. One of the physicians was blinded for the results of itiative . MCI or itiative , 8. All 42, T-tau and P-tau in CSF, as well as age and sex, with 18F-Flutemetamol PET. The same variables were included as independent variables in a multivariate logistic regression analysis with 18F-Flutemetamol PET as dependent variable. We created receiver operating characteristic (ROC) curves of 18F-Flutemetamol PET against Aβ42, T-tau and P-tau in CSF as well as the ratios of T-tau/Aβ42 and P-tau/Aβ42 for comparing the performance of the CSF biomarkers and ratios with 18F-Flutemetamol PET and to evaluate the optimal cut-off values. Youden´s indexes were calculated to find the optimal thresholds.The statistics were performed using IBM SPSS, version 25. Group differences were explored using t-test if the data was normally distributed, Mann-Whitney test if data were not normally distributed and Chi-square test if there were two categorical variables to be analyzed. Univariate binary logistic regression analyses were performed to assess the correlation of Aβ18F-Flutemetamol PET, Aβ42, age, sex and CDR as independent variables and clinical diagnosis as dependent variable. These independent variables were also included in a multivariate logistic regression analysis to assess their prediction on clinical diagnosis. Multiple models with different combinations of independent variables were tested. The odds ratios from the regression analyses account for a 1 unit increase for each variable. Furthermore, with an increase of x units in the independent variables, the odds ratio is given by Odds ratiox. Cohen κ analysis was used to assess the interrater agreement of the qualitative classification of 18F-Flutemetamol PET between the study-specific and clinical classifications. Cohen κ analysis was also used for assessing the interrater agreement of the combined stage and clinical diagnosis categories with and without knowledge of 18F-Flutemetamol PET classification.Univariate binary logistic regression analyses were performed with Patient characteristics, CSF biomarker levels, distribution of diagnoses and cognitive measures for the patient population are listed in 18F-Flutemetamol PET images (53%) were classified Flut+ and 30 images (47%) were classified Flut-. Differences in CSF biomarkers and ratios, diagnoses and cognitive measures in the Flut+ and Flut- groups are listed in Thirty-four 42: p <0.0001, P-tau: p = 0.006, T-tau: p = 0.0047) as well as age (p = 0.021) and sex (p = 0.014) had a significant correlation to 18F-Flutemetamol PET. The odds-ratios presented below account for a 1 unit increase in each of the independent variables. The univariate analysis shows that the likelihood of a positive 18F-Flutemetamol PET is lower with increasing Aβ42 (odds ratio 0.366 for a 100 unit increase) and higher with increasing P-tau (odds ratio 2.499 for a 30 unit increase), T-tau (odds ratio 1.221 for a 100 unit increase), age and female gender. See The univariate logistic regression analyses showed that all three biomarkers in CSF (Aβ42 (p < 0.0001) and P-tau (p = 0.006) demonstrated the strongest correlation with 18F-Flutemetamol PET. The multivariate regression analysis showed that Aβ42 (p = 0.001) and age (p = 0.029) were the only significant predictors in the selected prediction model. The ROC curve for Aβ42 yielded an area under the curve (AUC) of 0.91. The highest Youden´s index (0.75) applied to an Aβ42 cut-off of 706.5 pg/mL (sensitivity 88% and specificity 87%). When applying the old cut-off value of 550 pg/mL this yielded a sensitivity of 41% and specificity of 97%, corresponding to a Youden´s index of 0.38. Summary of results from the ROC curves for CSF biomarkers and ratios are shown in Aβ18F-Flutemetamol PET and nine of the 30 patients (30%) with a negative 18F-Flutemetamol PET had a clinical AD diagnosis. Results of the logistic regression analysis for predicting the likelihood for clinical AD diagnosis are listed in Thirty-two of the 34 patients (94%) with a positive 18F-Flutemetamol PET (p < 0.0001), Aβ42 (p = 0.001) and age (p = 0.008) were significant, however, sex and CDR were not significant predictors of diagnosis. The odds ratios presented in 42 (odds-ratio 0.670 for a 100 unit increase) and higher with increasing age (2.763 with a 10 unit increase). Multiple models with different combinations of independent variables were tested in the multivariate analysis, among them also models including all CSF biomarkers together with 18F-Flutemetamol PET. 18F-Flutemetamol PET remained the most significant predictor in all the tested models. In the multivariate analysis of the selected prediction model, we found that 18F-Flutemetamol PET (p < 0.0001) was the only significant predictor, probably also due to collinearity of several parameters. The explained variance (R2) of this model was just slightly higher (0.59), compared to the R2 in the univariate analysis (0.54) for 18F-Flutemetamol PET on clinical diagnosis.The univariate analysis showed that p < 0.001) and in clinical diagnoses with and without knowledge of the 18F-Flutemetamol PET classification .Cohens κ showed a very good agreement between the readers classification of images  [18F-Flutemetamol PET and Innotest for CSF analysis found a cut-off value of 647 pg/mL (sensitivity 95% and specificity 90%) [18F-Flutemetamol PET than Aβ42, not surprisingly, as these are biomarkers of pathological processes that are not directly evaluated with 18F-Flutemetamol PET. The ratios performed better, understandingly, as they include Aβ42. Our cut-off values for T-tau, P-tau and the ratios were within the range found in other studies [42 shown across studies. We did not have available Aβ40 in CSF. This would have been favorable to explore as the Aβ42/Aβ40 ratio is found to have better diagnostic accuracy as well as being a better predictor of abnormal Aβ PET than Aβ42 alone [The significant correlation between the three CSF biomarkers and  studies . The lab00 pg/mL . Our res00 pg/mL . A previity 82%) . Other sity 90%)  and a cuity 90%) . For the studies , 38, 39,42 alone .18F-Flutemetamol-PET is a better predictor of a clinical AD diagnosis than Aβ42, however we suggest they can be used interchangeably for evaluating Aβ load in a memory clinic setting, due to the high correlation between 18F-Flutemetamol PET and Aβ42. This high correlation may have influenced the significance level of Aβ42 in the multivariate analysis, however 18F-Flutemetamol PET demonstrated a lower p-value as well as a higher explained variance than Aβ42 in the univariate analyses. 18F-Flutemetamol was also the most significant variable in all the tested prediction models. Which biomarker examination is used in clinical practice will vary depending on availability, tradition, patient comfort as well as confidence in performing and contraindications (e.g anticoagulative medications) for a lumbar puncture. However, Aβ42 level in CSF and Aβ PET does not provide identical information. The level of Aβ42 provides information about the Aβ42 epitopes that may be in either soluble or protofibrillar forms in CSF and reflects the balance between Aβ42 production and clearance at the time of lumbar puncture. It is further an indirect measure which is associated with the accumulation of Aβ in the form of plaques [18F-Flutemetamol-PET, on the other hand, provides information of the amount of insoluble Aβ fibrils and consequently the Aβ burden in the brain which has accumulated over time [42 which supports the hypothesis that the two methods show different aspects of Aβ pathology [42 (using cut-off of 706.5 pg/mL), in seven of these there was concordance between PET and clinical diagnosis which explains the better performance of 18F-Flutemetamol PET as a predictor of clinical AD diagnosis (see We found that  plaques . 18F-Fluathology –45. In tosis see .42 (using cut-off of 706.5 pg/mL), in which eight had no evidence of Aβ pathology combined with a clinical AD diagnosis and two had evidence of Aβ pathology combined with a clinical non-AD diagnosis. One review reported a proportion of 2–32% of patients with a clinical AD diagnosis with a negative Aβ PET [There were 11 patients (15%) with discordance between Aβ PET and clinical diagnosis see . All exce Aβ PET , while oe Aβ PET . The NIAe Aβ PET . The sene Aβ PET . Whether18F-Flutemetamol PET as this study reflects clinical practice in which qualitative classification is used, which is currently the only validated method [18F-Flutemetamol can detect also diffuse Aβ plaques [et al included both qualitative and quantitative classification of images and found similar results using the two methods [Another explanation for a negative Aβ PET with a clinical AD diagnosis is the possibility of a false-negative PET. This is thought to occur if non-fibrillar, smaller or less dense Aβ species are dominating, which may be challenging to detect by qualitative Aβ PET . We did d method , 21. Alt plaques , 51, the methods . In prec methods .The women included in this study had more evidence of Aβ pathology. There were no significant differences in age, MMSE, CDR, T-tau or P-tau between females and males. However, a larger proportion of women also had a clinical AD diagnosis. Whether this indicate more severe disease at the time of diagnostic workup in women remains unclear. Sex differences have been reported previously , the occ18F-Flutemetamol PET in this study have been reported to be similarly high in other studies [18F-Flutemetamol PET result, the interrater agreement of diagnoses was excellent. However, both physicians had the Aβ42 level in CSF available, suggesting that these methods for evaluating Aβ load may be used interchangeably to support a clinical diagnosis.The demonstrated excellent interrater agreement of  studies , 52, whiAPOE genotype nor did we have a control group, both which would have strengthened the study. We did not perform semi-quantification of 18F-Flutemetamol PET, mainly due to lack of an appropriate MRI for such purposes. Semi-quantification could have provided an objective evaluation of amyloid burden as well as improved the correlations to CSF biomarkers further and is consequently a limitation of this study. All CSF analyses were performed according to the same routine, analyzed in the same laboratory and all PET images were acquired at the same PET scanner with the same standardized protocol, which are considered strengths of this study.A limitation of this study is the rather low number of patients included, which is partly a consequence of excluding patients with more than 190 days between PET and lumbar puncture. All data was collected from clinical practice which may be regarded as both a strength and a limitation. The inclusion was performed through a memory clinic with a preselected population with typically younger patients with most likely more challenging diagnoses. We did not include information about the 18F-Flutemetamol PET and Aβ42 in CSF in patients referred from a memory clinic and 18F-Flutemetamol PET was the best predictor of clinical AD diagnosis. Thus, 18F-Flutemetamol PET is a valuable tool to refine confidence that a patients’ cognitive impairment is caused by pathophysiological changes in the AD continuum.In the present study we found a high correlation between qualitative