UHPLC-ESI-MS/MS assay for quantification of endocannabinoids in cerebrospinal fluid using surrogate calibrant and surrogate matrix approaches.

Endocannabinoids are endogenous lipids with the main function recognized to act as neuromodulators through their cannabinoid receptors. Dysregulation of the endocannabinoid system is implicated in various pathologies, such as inflammatory and neurodegenerative diseases. In this study we describe a sensitive UHPLC-MS/MS method for the analysis of trace levels of 7 endocannabinoids in cerebrospinal fluid samples. The analytes covered comprised 1- and 2-arachidonoylglycerol 1- and 2-AG (which were analysed as sum due to their interconversion), 2-arachidonylglycerol ether 2-AGE, anandamide AEA, N-linoleoyl ethanolamide LEA, N-palmitoyl ethanolamide PEA and N-oleoyl ethanolamide OEA. Analytes were extracted from the biofluid by a simple monophasic procedure involving protein precipitation with acetonitrile (MeCN). The analytical method is based on chromatographic separation of the analytes with solid-core (core-shell, superficially porous) particle column Cortecs C18+ . Gradient elution with changing proportion of water and acetonitrile and constant concentration of formic acid provided reasonable separation of analytes, close elution of analytes and their internal standards and minimized matrix effects in biological samples. For specific detection of the endocannabinoids a triple-quadrupole tandem mass spectrometer with electrospray ionisation (ESI) and selected reaction monitoring (SRM) mode was used, and it provided good assay selectivity. The developed method required a minute volume of the biological samples (50 µL) and achieved excellent sensitivity (the lower limit of detection was between 4.15 and 30.18 pM of the biological sample). Linear calibration was achieved in the range from 25 to 10,545 pM for AEA, 90-3802 pM for 1-AG, 90-724 pM for 2-AG, 12-5226 pM for LEA, 33-13,942 for OEA, 34-23,850 pM for 2-AGE, 72-30,190 for PEA and 10-4218 for AEA-d4 in CSF. The method was validated and revealed relative errors in the range of - 14.7 to + 12.3% at LLOQ and - 14.1 to + 14.2% for the remaining validation range. Precisions were in the acceptable range (< 20% RSD at LLOQ, and <15% for the remaining levels) as well. It was finally used to quantify endocannabinoids in human cerebrospinal fluid obtained from 118 donors. Accurate quantification of endogenous compounds in biological samples was achieved by using two different principal approaches (surrogate matrix for AEA, 2-AG, OEA, 2-AGE, LEA and PEA, and surrogate calibrant for AEA only) and they were evaluated by use of the Passing-Bablok regression. Concentrations (median) of CSF samples of patients suffering from CNS infection and controls were found to be around 160 pM for 1- and 2-AG, 86 pM for AEA, 62 for 2-AGE, 58 for LEA, 93 pM for PEA, and 83 pM for OEA.

Specific Point-of-Care Testing of Coagulation in Patients Treated with Dabigatran.

BACKGROUND AND PURPOSE: Accurate and rapid assessment of coagulation status is necessary to guide thrombolysis or reversal of anticoagulation in stroke patients, but commercially available point-of-care (POC) assays are not suited for coagulation testing in patients treated with direct oral anticoagulants (DOACs). We aimed to evaluate the direct thrombin monitoring (DTM) test card by Helena Laboratories (Texas, United States) for anti-IIa-specific POC coagulation testing, hypothesizing that its POC-ecarin clotting time (POC-ECT) accurately reflects dabigatran plasma concentrations. METHODS: A prospective single-center diagnostic study (ClinicalTrials.gov-identifier: NCT02825394) was conducted enrolling patients receiving a first dose of dabigatran and patients already on dabigatran treatment. Blood samples were collected before drug intake and 0.5, 1, 2, 8, and 12 hours after intake. POC-ECT was performed using whole blood (WB), citrated blood (CB), and citrated plasma (CP). Dabigatran plasma concentrations were determined by mass spectrometry. RESULTS: In total, 240 blood samples from 40 patients contained 0 to 275 ng/mL of dabigatran. POC-ECT with WB/CB/CP ranged from 20 to 186/184/316 seconds. Pearson's correlation coefficient showed a strong correlation between dabigatran concentrations and POC-ECT with WB/CB/CP (R2 = 0.78/0.90/0.92). Dabigatran concentrations >30 and >50 ng/mL (thresholds for thrombolysis, surgery, and reversal therapy according to clinical guidelines) were detected by POC-ECT with WB/CB/CP (>36/35/45 and >43/45/59 seconds) with 95/97/97 and 96/98/97% sensitivity, and 81/87/94 and 74/60/91% specificity. CONCLUSION: This first study evaluating DOAC-specific POC coagulation testing revealed an excellent correlation of POC-ECT with actual dabigatran concentrations. Detecting clinically relevant dabigatran levels with high sensitivity/specificity, the DTM assay represents a suitable diagnostic tool in acute stroke, hemorrhage, and urgent surgery.

Image Quality of CT Angiography of Supra-Aortic Arteries : Comparison Between Advanced Modelled Iterative Reconstruction (ADMIRE), Sinogram Affirmed Iterative Reconstruction (SAFIRE) and Filtered Back Projection (FBP) in One Patients' Group.

PURPOSE: To evaluate the potential benefit in image quality of the iterative reconstruction (IR) technique advanced modelled iterative reconstruction (ADMIRE) in CT angiography (CTA) of supra-aortic arteries compared to sinogram affirmed iterative reconstruction (SAFIRE) and standard filtered back projection (FBP) in one patients' group. METHODS: In this study 29 patients underwent standard CTA of supra-aortic arteries. Images were reconstructed using three different reconstruction algorithms, FBP, and IR techniques ADMIRE and SAFIRE. General image quality was assessed by two radiologists in different arterial segments using a 5-point Likert scale. Mean attenuation and noise were measured at different levels of each vessel and signal-to-noise ratio (SNR) was calculated. Interrater variability was determined. RESULTS: Regarding total image quality IR showed only excellent, very good and good results and was more often graded excellent and very good than FBP reconstruction. Image noise levels and SNR were significantly (p < 0.01) improved in IR at the bilateral subclavian arteries (only in SAFIRE), vertebral V1 and V3 segments, common carotid arteries and proximal and distal internal carotid arteries. No significant differences in image quality were found when comparing SAFIRE and ADMIRE reconstructions except for V1 and V3. In these regions ADMIRE showed significantly better image quality than SAFIRE (p < 0.001 and p < 0.01). Interrater agreement was almost perfect (κ = 0.88) for different image quality parameters. CONCLUSION: The CTA of supra-aortic arteries using the IR techniques SAFIRE and ADMIRE was superior to FBP when comparing the objective and subjective image quality and ADMIRE has the potential to overcome SAFIRE.

Predicting tick-borne encephalitis using Google Trends.

Data generated through public Internet searching offers a promising alternative source of information for monitoring and forecasting of infectious disease. Here future cases of tick-borne encephalitis (TBE) were predicted using traditional weekly case reports, both with and without Google Trends data (GTD). Data on the weekly number of acute, confirmed TBE cases in Germany were obtained from the Robert Koch Institute. Data relating to the volume of Internet searching on TBE was downloaded from the Google Trends website. Data were split into training and validation parts. A SARIMA (0,1,1) (1,1,1) [52] model was used to describe the weekly TBE case number time series. Google Trends Data was used as an external regressor in a second, as optimal identified SARIMA (4,1,1) (1,1,1) [52] model. Predictions for the number of future cases were made with both models and compared with the validation dataset. GTD showed a significant correlation with reported weekly case numbers of TBE (p < 0.0001). A comparison of forecasted values with reported ones resulted in an RMSE (residual mean squared error) of 0.71 for the model without Google search values, and an RMSE of 0.70 for the Google Trends values enhanced model. However, difference between predictive performances was not significant (Diebold Mariano test, p-value = 0.14).

Can Google Trends data improve forecasting of Lyme disease incidence?

BACKGROUND: Online activity-based epidemiological surveillance and forecasting is getting more and more attention. To date, Google search volumes have not been assessed for forecasting of tick-borne diseases. Thus, we performed an analysis of forecasting of the Lyme disease incidence based on the traditional data extended with Google Trends. METHODS: Data on the weekly incidence of Lyme disease in Germany from 16 June 2013 to 27 May 2018 were obtained from the database of the Robert Koch Institute. Data of Internet searches were obtained from Google Trends searching "Borreliose" in Germany for the "last 5 years" as a timespan category. Data were split into the training (from 16 June 2013 to 11 June 2017) and validation (from 12 June 2017, to 27 May 2018) data sets. A seasonal autoregressive moving average model, SARIMA (0,1,1) (0,1,1) [52] model was selected to describe the time series of the weekly Lyme incidence. After this, we added the Google Trends data as an external regressor and identified the SARIMA (0,1,1) (0,1,1) [52] model as optimal. We made predictions for the validation interval using these two models and compared predictions with the values of the validation data set. RESULTS: Forecasting for the validation timespan resulted in similar values for the models. Comparing the forecasted values with the reported ones resulted in an residual mean squared error (RMSE) of 0.3763; the mean absolute percentage error (MAPE) was 8.233 for the model without Google searches with an RMSE of 0.3732; and the MAPE was 8.17495 for the Google Trends values-expanded model. The difference between the predictive performances was insignificant (Diebold-Mariano Test, p-value = 0.4152). CONCLUSION: Google Trends data are a good correlate of the reported incidence of Lyme disease in Germany, but it failed to significantly improve the forecasting accuracy in models based on traditional data.

Diffusion kurtosis imaging histogram parameter metrics predicting survival in integrated molecular subtypes of diffuse glioma: An observational cohort study.

PURPOSE: The aim of the study was to assess the predictive value of preoperatively assessed diffusion kurtosis imaging (DKI) metrics as prognostic factors in the 2016 World Health Organization Classification of Tumors of the Central Nervous System integrated glioma groups. MATERIAL AND METHODS: Seventy-seven patients with histopathologically confirmed treatment-naïve glioma were retrospectively assessed between 08/2013 and 10/2017 using mean kurtosis (MK) and mean diffusivity (MD) histogram parameters from DKI, overall and progression-free survival, and relevant prognostic molecular data (isocitrate dehydrogenase, [IDH]; alpha-thalassemia/mental retardation syndrome X-linked, [ATRX]; chromosome 1p/19q loss of heterozygosity). Receiver operating characteristic (ROC) analysis was performed on metric variables to determine the optimal cutoff-values. The Kaplan-Meier method was used to assess univariate survival data. A multivariate Cox proportional hazards model was performed on significant results from the univariate analysis. RESULTS: There were significant differences in overall and progression-free survival between patient age (p = 0.001), resection statuses (p = 0.002), WHO glioma grades (p < 0.0001), and integrated molecular profiles (p < 0.0001). Survival was significantly better in patients with lower MK and higher MD values globally (p = 0.009), in gliomas without chromosome 1p/19q LOH (p < 0.0001), and those with retained ATRX expression (p = 0.008). CONCLUSIONS: Patient age and MK from DKI from DKI are relevant factors for preoperatively predicting overall and progression-free survival. Regarding the molecular subgroups, they seem to be predictive in gliomas with ATRX retention, representing a feature of IDH wild-type gliomas.

Cardiac Myxoma and Cerebrovascular Events: A Retrospective Cohort Study.

Background: Cardiac myxoma (CM) is the most frequent, cardiac benign tumor and is associated with enhanced risk for cerebrovascular events (CVE). Although surgical CM excision is the only curative treatment to prevent CVE recurrence, in recent reports conservative treatment with antiplatelet or anticoagulant agents in high-risk patients with CM-related CVE has been discussed. Methods: Case records at the University Hospital of Tübingen between 2005 and 2017 were screened to identify patients with CM-related CVE. Clinical features, brain and cardiac imaging findings, histological reports, applied treatments and long-term neurological outcomes were assessed. Results: 52 patients with CM were identified and among them, 13 patients with transient ischemic attack, ischemic stroke or retinal ischemia were included to the (to our knowledge) largest reported retrospective study of CM-related CVE. In all identified patients, CVE was the first manifestation of CM; 61% suffered ischemic stroke, 23% transient ischemic attack and 15% retinal ischemia. In 46% of the patients, CVE occurred under antiplatelet or anticoagulation treatment, while 23% of the patients developed recurrent CVE under bridging-antithrombotic-therapy prior to CM surgical excision. Prolonged time interval between CVE and CM-surgery was significantly associated with CVE recurrence (p = 0.021). One patient underwent i.v. thrombolysis, followed by thrombectomy, with good post-interventional outcome and no signs of hemorrhagic transformation. Discussion: Our results suggest that antiplatelet or anticoagulation treatment is no alternative to cardiac surgery in patients presenting with CM-related CVE. We found significantly prolonged time-intervals between CVE and CM surgery in patients with recurrent CVE. Therefore, we suggest that the waiting- or bridging-interval with antithrombotic therapy until curative CM excision should be kept as short as possible. Based on our data and review of the literature, we suggest that in patients with CM-related CVE, i.v. thrombolysis and/or endovascular interventions may present safe and efficacious acute treatments.

Design and validation of a clinical scale for prehospital stroke recognition, severity grading and prediction of large vessel occlusion: the shortened NIH Stroke Scale for emergency medical services.

OBJECTIVE: To develop an NIH Stroke Scale (NIHSS)-compatible, all-in-one scale for rapid and comprehensive prehospital stroke assessment including stroke recognition, severity grading and progression monitoring as well as prediction of large vessel occlusion (LVO). METHODS: Emergency medical services (EMS) personnel and stroke physicians (n=326) rated each item of the NIHSS regarding suitability for prehospital use; best rated items were included. Stroke recognition was evaluated retrospectively in 689 consecutive patients with acute stroke or stroke mimics, prediction of LVO in 741 consecutive patients with ischaemic stroke with acute vessel imaging independent of admission NIHSS score. RESULTS: Nine of the NIHSS items were rated as 'suitable for prehospital use.' After excluding two items in order to increase specificity, the final scale (termed shortened NIHSS for EMS, sNIHSS-EMS) consists of 'level of consciousness', 'facial palsy', 'motor arm/leg', 'sensory', 'language' and 'dysarthria'. Sensitivity for stroke recognition of the sNIHSS-EMS is 91% (95% CI 86 to 94), specificity 52% (95% CI 47 to 56). Receiver operating curve analysis revealed an optimal cut-off point for LVO prediction of ≥6 (sensitivity 70% (95% CI 65 to 76), specificity 81% (95% CI 76 to 84), positive predictive value 70 (95% CI 65 to 75), area under the curve 0.81 (95% CI 0.78 to 0.84)). Test characteristics were non-inferior to non-comprehensive scales. CONCLUSIONS: The sNIHSS-EMS may overcome the sequential use of multiple emergency stroke scales by permitting parallel stroke recognition, severity grading and LVO prediction. Full NIHSS-item compatibility allows for evaluation of stroke progression starting at the prehospital phase.

Presynaptic α2-adrenoceptors control the inhibitory action of presynaptic CB1 cannabinoid receptors on prefrontocortical norepinephrine release in the rat.

Endocannabinoids play a crucial neuromodulator role in both physiological and pathological states in various brain regions including the prefrontal cortex (PFC). We examined, whether presynaptic cannabinoid receptors are involved in the modulation of basal and electrical field stimulation-evoked [³H]norepinephrine ([³H]NE) release from rat PFC slices. WIN55,212-2, a nonselective CB1 receptor (CB1R) agonist, inhibited the electrical stimulation-evoked efflux of [³H]NE in a concentration-dependent fashion, which was antagonized by the CB1R antagonist/inverse agonist, AM251 (1 µM). Idazoxan, a selective α2-adrenoceptor antagonist, augmented the evoked [³H]NE release. In the presence of idazoxan, the effect of WIN55,212-2 was exacerbated or attenuated, depending on the applied concentration and stimulation frequency. Moreover their combined, but not individual application elicited a depressive-like phenomenon in the forced-swim test. These data were bolstered with fluorescent and confocal microscopy analysis, which revealed that CB1R immunoreactivity co-localized with dopamine-ß-hydroxylase positive (i.e. noradrenergic) fibers and the inhibitory α(2A) adrenergic autoreceptors (α(2A)R) in the PFC. Furthermore, idazoxan triggered a decrease in CB1R density in the PFC, suggesting that high extracellular level of norepinephrine downregulates CB1Rs.