171 research outputs found
Quantitative analysis of new generation antidepressants using gas chromatography-mass spectrometry : applications inclinical and forensic toxicology
Semiquantitative activity-based detection of JWH-018, a synthetic cannabinoid receptor agonist, in oral fluid after vaping
The rapid proliferation of new synthetic cannabinoid receptor agonists (SCRAs) has initiated considerable interest in the development of so-called “untargeted” screening strategies. One of these new screening technologies involves the activity-based detection of SCRAs. In this study, we evaluated whether (synthetic) cannabinoid activity can be detected in oral fluid (OF) and, if
so, whether it correlates with SCRA concentrations. OF was collected at several time points in a placebo-controlled JWH-018 administration study. The outcome of the cell-based cannabinoid reporter system, which monitored the cannabinoid receptor activation, was compared to the quantitative data for JWH-018, obtained via a validated liquid chromatography-tandem mass
spectrometry (LC-MS/MS) method. A total of 175 OF samples were collected and analyzed via both methods. The cannabinoid reporter assay correctly classified the vast majority of the samples as either negative (<0.25 ng/mL; 74/75 = 99%) or having low
(0.25−1.5 ng/mL; 16/16 = 100% and 1.5−10 ng/mL; 37/41 = 90%), mid (10−100 ng/mL; 23/25 = 92%) or high (>100 ng/mL; 16/18 = 89%) JWH-018 concentrations. Passing−Bablok regression analysis yielded a good linear correlation, with no proportional difference between both methods (slope 0.97; 95% confidence interval 0.86−1.14) and only a small systematic difference. This is the first study to demonstrate the applicability of an untargeted, activity-based approach for SCRA detection in OF. Additionally, the outcome of the cannabinoid reporter assay was compared to the gold standard (LC-MS/MS), showing a good correlation between
both methods, indicating that the cannabinoid reporter assay can be used for an estimation of drug concentrations
Quantification of phosphatidylethanol 16:0/18:1, 18:1/18:1, and 16:0/16:0 in venous blood and venous and capillary dried blood spots from patients in alcohol withdrawal and control volunteers
Phosphatidylethanol species (PEths) are promising biomarkers of alcohol consumption. Here, we report on the set-up, validation, and application of a novel UHPLC-ESI-MS/MS method for the quantification of PEth 16:0/18:1, PEth 18:1/18:1, and PEth 16:0/16:0 in whole blood (30 mu L) and in venous (V, 30 mu L) or capillary (C, 3 punches (3 mm)) dried blood spots (DBS). The methods were linear from 10 (LLOQ) to 2000 ng/mL for PEth 16:0/18:1, from 10 (LLOQ) to 1940 ng/mL for PEth 18:1/18:1, and from 19 (LLOQ) to 3872 ng/mL for PEth 16:0/16:0. Extraction efficiencies were higher than 55 % (RSD < 18 %) and matrix effects compensated for by IS were between 77 and 125 % (RSD < 10 %). Accuracy, repeatability, and intermediate precision fulfilled acceptance criteria (bias and RSD below 13 %). Validity of the procedure for determination of PEth 16:0/18:1 in blood was demonstrated by the successful participation in a proficiency test. The quantification of PEths in C-DBS was not significantly influenced by the hematocrit, punch localization, or spot volume. The stability of PEths in V-DBS stored at room temperature was demonstrated up to 6 months. The method was applied to authentic samples (whole blood, V-DBS, and C-DBS) from 50 inpatients in alcohol withdrawal and 50 control volunteers. Applying a cut-off value to detect inpatients at 221 ng/mL for PEth 16:0/18:1 provided no false positive results and a good sensitivity (86 %). Comparison of quantitative results (Bland-Altman plot, Passing-Bablok regression, and Wilcoxon signed rank test) revealed that V-DBS and C-DBS were valid alternatives to venous blood for the detection of alcohol consumption
Quantitation of phosphatidylethanol in dried blood after volumetric absorptive microsampling
Background: Stimulated by the increased recognition of phosphatidylethanol (PEth) as sensitive direct marker of alcohol intake, the Ghent University's Laboratory of Toxicology and the National Institute of Criminalistics and Criminology combined their efforts to develop a quantitative method. To facilitate implementation the focus was on the use of a sampling technique which allows quick and easy blood collection, without the need of dedicated personnel at any place/any time. In the meantime the cooperation of the two labs should also allow to initiate a Belgian network of laboratories capable of quantifying PEth.
Methods: Dried blood microsamples were collected via volumetric absorptive microsampling (VAMS). PEth 16:0/ 18:1 was quantified after liquid-liquid extraction using two independent isotope dilution - liquid chromatography - tandem mass spectrometry methods. A systematic review of the entire process at both sites was performed before the final method comparison using samples from 59 routine toxicology cases collected within a one-year time interval.
Results: Initial differences between both laboratories were solved by focusing on important methodological aspects: (i) trueness verification of the calibration protocol focusing on the primary material, preparation of the stock solutions and adequate equilibration of calibrators and QCs, and (ii) verification of comparability of results obtained with different m/z transitions. Several of these aspects could only be verified by critically assessing spiked and native samples. After a final validation good average comparability of the two methods was observed. The average bias was -0.4%, with 85% of the differences within 20%. Moreover, the methods proved to be reproducible and robust within a one-year time interval.
Conclusion: This study is the first to develop a quantitative volumetric absorptive microsampling based method for PEth measurements, in addition it is the first to perform a systematic comparison of PEth measurements between two laboratories. From the discussion on the encountered pitfalls it is clear that also on a global scale, more efforts are needed to improve interlaboratory agreement
Towards automatic pulmonary nodule management in lung cancer screening with deep learning
The introduction of lung cancer screening programs will produce an
unprecedented amount of chest CT scans in the near future, which radiologists
will have to read in order to decide on a patient follow-up strategy. According
to the current guidelines, the workup of screen-detected nodules strongly
relies on nodule size and nodule type. In this paper, we present a deep
learning system based on multi-stream multi-scale convolutional networks, which
automatically classifies all nodule types relevant for nodule workup. The
system processes raw CT data containing a nodule without the need for any
additional information such as nodule segmentation or nodule size and learns a
representation of 3D data by analyzing an arbitrary number of 2D views of a
given nodule. The deep learning system was trained with data from the Italian
MILD screening trial and validated on an independent set of data from the
Danish DLCST screening trial. We analyze the advantage of processing nodules at
multiple scales with a multi-stream convolutional network architecture, and we
show that the proposed deep learning system achieves performance at classifying
nodule type that surpasses the one of classical machine learning approaches and
is within the inter-observer variability among four experienced human
observers.Comment: Published on Scientific Report
Development of Neuronal Guidance Fibers for Stimulating Electrodes: Basic Construction and Delivery of a Growth Factor
State-of-the-art treatment for sensorineural hearing loss is based on electrical stimulation of residual spiral ganglion neurons (SGNs) with cochlear implants (CIs). Due to the anatomical gap between the electrode contacts of the CI and the residual afferent fibers of the SGNs, spatial spreading of the stimulation signal hampers focused neuronal stimulation. Also, the efficiency of a CI is limited because SGNs degenerate over time due to loss of trophic support. A promising option to close the anatomical gap is to install fibers as artificial nerve guidance structures on the surface of the implant and install on these fibers drug delivery systems releasing neuroprotective agents. Here, we describe the first steps in this direction. In the present study, suture yarns made of biodegradable polymers (polyglycolide/poly-ε-caprolactone) serve as the basic fiber material. In addition to the unmodified fiber, also fibers modified with amine groups were employed. Cell culture investigations with NIH 3T3 fibroblasts attested good cytocompatibility to both types of fibers. The fibers were then coated with the extracellular matrix component heparan sulfate (HS) as a biomimetic of the extracellular matrix. HS is known to bind, stabilize, modulate, and sustainably release growth factors. Here, we loaded the HS-carrying fibers with the brain-derived neurotrophic factor (BDNF) which is known to act neuroprotectively. Release of this neurotrophic factor from the fibers was followed over a period of 110 days. Cell culture investigations with spiral ganglion cells, using the supernatants from the release studies, showed that the BDNF delivered from the fibers drastically increased the survival rate of SGNs in vitro. Thus, biodegradable polymer fibers with attached HS and loaded with BDNF are suitable for the protection and support of SGNs. Moreover, they present a promising base material for the further development towards a future neuronal guiding scaffold. Copyright © 2022 Wille, Harre, Oehmichen, Lindemann, Menzel, Ehlert, Lenarz, Warnecke and Behrens
Medical emergencies related to ethanol and illicit drugs at an annual, nocturnal, indoor, electronic dance music event
Introduction: Medical problems are frequently encountered during electronic dance music (EDM) events.
Problem: There are uncertainties about the frequencies and severity of intoxications with different types of recreational drugs: ethanol, "classical" illicit party drugs, and new psychoactive substances (NPS).
Methods: Statistical data on the medical problems encountered during two editions of an indoor electronic dance event with around 30,000 attendants were retrieved from the Belgian Red Cross (Mechelen, Belgium) database. Data on drug use were prospectively collected from the patient (or a bystander), the clinical presentation, and/or toxicological screening.
Results: In the on-site medical station, 487 patients were treated (265 in 2013 and 222 in 2014). The most frequent reasons were trauma (n = 171), headache (n = 36), gastro-intestinal problems (n = 44), and intoxication (n = 160). Sixty-nine patients were transferred to a hospital, including 53 with severe drug-related symptoms. Analysis of blood samples from 106 intoxicated patients detected ethanol in 91.5%, 3,4-methylenedioxymethamphetamine (MDMA) in 34.0%, cannabis in 30.2%, cocaine in 7.5%, amphetamine in 2.8%, and gamma-hydroxybutyric acid (GHB) in 0.9% of patients (alone or in combination). In only six of the MDMA-positive cases, MDMA was the sole substance found. In 2014, the neuroleptic drug clozapine was found in three cases and ketamine in one. Additional analyses for NPS were performed in 20 cases. Only in one agitated patient, the psychedelic phenethylamines 25B-NBOMe and 25C-NBOMe were found.
Conclusions: At this particular event, recreational drug abuse necessitated on-site medical treatment in one out of 350 attendants and a hospital transfer in one out of 1,000. Ethanol remains the most frequently abused (legal) drug, yet classical illicit recreational drugs are also frequently (co-) ingested. The most worrying observation was high-risk poly-drug use, especially among MDMA users. Regarding NPS, the number of cases was low and the clinical presentations were rather mild. It should be stressed that these observations only apply to this particular event and cannot be generalized to other EDM events
Analytical performance of eight enzymatic assays for ethanol in serum evaluated by data from the Belgian external quality assessment scheme
Abstract
Objectives
Fast and reliable ethanol assays analysis are used in a clinical context for patients suspected of ethanol intoxication. Mostly, automated systems using an enzymatic reaction based on ethanol dehydrogenase are used. The manuscript focusses on the evaluation of the performance of these assays.
Methods
Data included 30 serum samples used in the Belgian EQA scheme from 2019 to 2021 and concentrations ranged from 0.13 to 3.70 g/L. A regression line between target concentrations and reported values was calculated to evaluate outliers, bias, variability and measurement uncertainty.
Results
A total of 1,611 results were taken into account. Bias was the highest for Alinity c over the whole concentration range and the lowest for Vitros for low concentrations and Cobas 8000 using the c702 module for high concentrations. The Architect and Cobas c501/c502 systems showed the lowest variability over the whole concentration range. Highest variability was observed for Cobas 8000 using the 702 module, Thermo Scientific and Alinity c. Cobas 8000 using the c702 module showed the highest measurement uncertainty for lower concentrations. For higher concentrations, Alinity c, Thermo Scientific and Vitros were the methods with the highest measurement uncertainty.
Conclusions
The bias of the enzymatic techniques is nearly negligible for all methods except Alinity c. Variability differs strongly between measurement procedures. This study shows that the Alinity c has a worse measurement uncertainty than other systems for concentrations above 0.5 g/L. Overall, we found the differences in measurement uncertainty to be mainly influenced by the differences in variability
Berufliche Stabilitäts- und Flexibilitätsorientierungen in Ostdeutschland: Ergebnisse eines Forschungspraktikums
Das im folgenden vorgestellte Projekt Stabilitäts- und Flexibilitätsorientierungen in ostdeutschen Lebensverläufen wurde am Institut für Soziologie der Universität Leipzig im Rahmen eines Lehrpraktikums durchgeführt. In dem Projekt wurden berufliche Stabilitäts- und Flexibilitätsorientierungen ostdeutscher Beschäftigter vor dem Hintergrund individueller Ressourcen und Gelegenheitsstrukturen untersucht. Anhand von 68 biographischen Interviews älterer und jüngerer Kohorten sollte gezeigt werden, in welchem Maße individuelle Merkmale sowie familiäre, arbeitsmarktliche, sozialpolitische und betriebliche Gelegenheitsstrukturen die individuellen Handlungsorientierungen beeinflussen. Vor dem Hintergrund der \"Entstandardisierung\" von Lebenslaufmustern und der \"Flexibilisierung\" von Erwerbsverläufen wurde dabei nach den Ursachen und Veränderungen kohortenspezifischer Unterscheidungen berufsbiographischer Entwürfe gefragt.:Vorbemerkung; Stabilität und Flexibilität im Lebensverlauf; Analytisches Modell und methodisches Vorgehen; Ergebnisse; Bewältigungsstrategien – Eine Zusammenfassung; Literatur, Anhan
Upscaling Wetland Methane Emissions From the FLUXNET-CH4 Eddy Covariance Network (UpCH4 v1.0): Model Development, Network Assessment, and Budget Comparison
Wetlands are responsible for 20%-31% of global methane (CH4) emissions and account for a large source of uncertainty in the global CH4 budget. Data-driven upscaling of CH4 fluxes from eddy covariance measurements can provide new and independent bottom-up estimates of wetland CH4 emissions. Here, we develop a six-predictor random forest upscaling model (UpCH4), trained on 119 site-years of eddy covariance CH4 flux data from 43 freshwater wetland sites in the FLUXNET-CH4 Community Product. Network patterns in site-level annual means and mean seasonal cycles of CH4 fluxes were reproduced accurately in tundra, boreal, and temperate regions (Nash-Sutcliffe Efficiency similar to 0.52-0.63 and 0.53). UpCH(4) estimated annual global wetland CH4 emissions of 146 +/- 43 TgCH4 y(-1) for 2001-2018 which agrees closely with current bottom-up land surface models (102-181 TgCH4 y(-1)) and overlaps with top-down atmospheric inversion models (155-200 TgCH4 y -1). However, UpCH4 diverged from both types of models in the spatial pattern and seasonal dynamics of tropical wetland emissions. We conclude that upscaling of eddy covariance CH4 fluxes has the potential to produce realistic extra-tropical wetland CH4 emissions estimates which will improve with more flux data. To reduce uncertainty in upscaled estimates, researchers could prioritize new wetland flux sites along humid-to-arid tropical climate gradients, from major rainforest basins (Congo, Amazon, and SE Asia), into monsoon (Bangladesh and India) and savannah regions (African Sahel) and be paired with improved knowledge of wetland extent seasonal dynamics in these regions. The monthly wetland methane products gridded at 0.25 degrees from UpCH4 are available via ORNL DAAC (https://doi.org/10.3334/ ORNLDAAC/2253).Plain Language Summary Wetlands account for a large share of global methane emissions to the atmosphere, but current estimates vary widely in magnitude (similar to 30% uncertainty on annual global emissions) and spatial distribution, with diverging predictions for tropical rice growing (e.g., Bengal basin), rainforest (e.g., Amazon basin), and floodplain savannah (e.g., Sudd) regions. Wetland methane model estimates could be improved by increased use of land surface methane flux data. Upscaling approaches use flux data collected across globally distributed measurement networks in a machine learning framework to extrapolate fluxes in space and time. Here, we train and evaluate a methane upscaling model (UpCH4) and use it to generate monthly, globally gridded wetland methane emissions estimates for 2001-2018. The UpCH4 model uses only six predictor variables among which temperature is dominant. Global annual methane emissions estimates and associated uncertainty ranges from upscaling fall within state-of-the-art model ensemble estimates from the Global Carbon Project (GCP) methane budget. In some tropical regions, the spatial pattern of UpCH4 emissions diverged from GCP predictions, however, inclusion of flux measurements from additional ground-based sites, together with refined maps of tropical wetlands extent, could reduce these prediction uncertainties
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