Man versus machine: Automatic pedicle screw planning using registration-based techniques compared with manual screw planning for thoracolumbar fusion surgeries.

OBJECTIVE: This study evaluates the precision of a commercially available spine planning software in automatic spine labelling and screw-trajectory proposal. METHODS: The software uses automatic segmentation and registration of the vertebra to generate screw proposals. 877 trajectories were compared. Four neurosurgeons assessed suggested trajectories, performed corrections, and manually planned pedicle screws. Additionally, automatic identification/labelling was evaluated. RESULTS: Automatic labelling was correct in 89% of the cases. 92.9% of automatically planned trajectories were in accordance with G&R grade A + B. Automatic mode reduced the time spent planning screw trajectories by 7 s per screw to 20 s per vertebra. Manual mode yielded differences in screw-length between surgeons (largest distribution peak: 5 mm), automatic in contrast at 0 mm. The size of suggested pedicle screws was significantly smaller (largest peaks in difference between 0.5 and 3 mm) than the surgeon's choice. CONCLUSION: Automatic identification of vertebrae works in most cases and suggested pedicle screw trajectories are acceptable. So far, it does not substitute for an experienced surgeon's assessment.

Smaller is better? Unduly nice accuracy assessments in roof detection using remote sensing data with machine learning and k-fold cross-validation.

Deriving the thematic accuracy of models is a fundamental part of image classification analyses. K-fold cross-validation (KCV), as an accuracy assessment technique, can be biased because existing built-in algorithms of software solutions do not handle the high autocorrelation of remotely sensed images, leading to overestimation of accuracies. We aimed to quantify the magnitude of the overestimation of KCV-based accuracies and propose a method to overcome this problem with the example of rooftops using a WorldView-2 (WV2) satellite image, and two orthophotos. Random split to training/testing subsets, independent testing and different types of repeated KCV sampling strategies were used to generate input datasets for classification. Results revealed that applying the random splitting of reference data to training/testing subsets and KCV methods had significantly biased the accuracies by up to 17%; overall accuracies (OAs) can incorrectly reach >99%. We found that repeated KCV can provide similar results to independent testing when spatial sampling is applied with a sufficiently large distance threshold (in our case 10 m). Coarser resolution of WV2 ensured more reliable results (up to a 5-9% increase in OA) than orthophotos. Object-based pixel purity of buildings showed that when using a majority filter for at least of 50% of objects the final accuracy approached 100% with each sampling method. The final conclusion is that KCV-based modelling ensures better accuracy than single models (with better pixel purity on the object level), but the accuracy metrics without spatially filtered sampling are not reliable.

Comparison and Intercorrelation of Various Bentonite Products for Oenological Properties, Elemental Compositions, Volatile Compounds and Organoleptic Attributes of White Wine.

Bentonite fining is one of the generally applied wine-making technological elements that may seriously affect wine components. The aim of this study was (i) to investigate the effect of 21 bentonite products on eight oenological parameters, 19 elements, 21 volatile organic compounds (VOCs) and 10 organoleptic properties of white wine; and (ii) to quantify intercorrelations among the parameters separately for each of the four quality attributes. Among oenological parameters, sugar, acidity, malic-, lactic-, citric acid and total phenol contents were significant among several bentonite products. The amounts of elements were the lowest in the control wine treatments (with exceptions of, e.g., Ni and Cu); and these values were significantly different from several bentonite products. The relative presence of the VOCs was above 100% for most VOCs, but it was below 100% for 1-propanol, 4-amino-1,5-pentandioic acid and butane-dioic acid, and diethyl ester in all treatments. For organoleptic parameters, the values of clearness, colour, flavour intensity and taste persistency was the lowest in the control wine treatment, while the values of flavour character, flavour quality, taste intensity, taste character, and overall harmony were the highest for the bentonite products of AP, EBE, M-SA, EBE, EBE, respectively. Results of correlation and factor analyses showed strong intercorrelative effects of bentonite fining on the four quality attributes. In conclusion, this study can help in the proper choice of a specific bentonite product in relation to complexity effects of bentonite fining.

Tree species composition mapping with dimension reduction and post-classification using very high-resolution hyperspectral imaging.

Tree species' composition of forests is essential in forest management and nature conservation. We aimed to identify the tree species structure of a floodplain forest area using a hyperspectral image. We proposed an efficient novel strategy including the testing of three dimension reduction (DR) methods: Principal Component Analysis, Minimum Noise Fraction (MNF) and Indipendent Component Analysis with five machine learning (ML) algorithms (Maximum Likelihood Classifier, Support Vector Classification, Support Vector Machine, Random Forest and Artificial Neural Network) to find the most accurate outcome; altogether 300 models were calculated. Post-classification was applied by combining the multiresolution segmentation and filtering. MNF was the most efficient DR technique, and at least 7 components were needed to gain an overall accuracy (OA) of > 75%. Forty-five models had > 80% OAs; MNF was 43, and the Maximum Likelihood was 19 times among these models. Best classification belonged to MNF with 10 components and Maximum Likelihood classifier with the OA of 83.3%. Post-classification increased the OA to 86.1%. We quantified the differences among the possible DR and ML methods, and found that even > 10% worse model can be found using popular standard procedures related to the best results. Our workflow calls the attention of careful model selection to gain accurate maps.

Effects of Four Different EEG-Neurofeedback Reinforcement Types in Healthy Individuals - A Pilot Study.

EEG neurofeedback (EEG-NFB) is a promising tool for the treatment of depressive disorders. However, many methods for the presentation of neurobiological reactions are available and it is widely unknown which of these feedback options are preferrable. Moreover, the influence of motivation on NFB training success is insufficiently studied. This study analyzed the efficacy of a novel EEG protocol (FC3/Pz) based on findings for NFB in depression. The role of four feedback options (Rumination, Anxiety, Meditation Master, Moving Art) from the NFB software "Brain Assistant" and motivation in EEG-based NFB performance was studied. Regarding "Anxiety" and "Rumination" visual feedback was used to evoke emotions; reinforcement (both negative and positive operant conditioning) was continuous. Regarding "Meditation Master" visual feedback was combined with continuous positive reinforcement. Regarding "Moving Art" 20-min calm nature films with neutral character were used; both visual and auditive feedback were applied. The reinforcement was positive and continuous. 13 healthy participants completed 15 EEG sessions over four months combining simultaneous frontal (aims: reduction of theta-, alpha- and high beta-activity, increase of low and mid beta-activity) and parietal training (aims: reduction of theta-, alpha 1-, mid and high beta-activity, increase of alpha 2- and low beta-activity). We observed significantly more pronounced percentage change in the expected direction for Anxiety than Moving Art (mean difference = 3.32; p = 0.003). The association between motivation and performance was non-significant. Based on these results we conclude that feedback with both negative and positive operant conditioning and emotion evoking effects should be preferred.

Temporal Dynamics of Incidence of Shot Hole Disease Affected by Training Systems and Cultivar Susceptibilities in an Integrated Plum Orchard.

Shot hole disease (SHD) can cause severe epidemics in plum orchards, depending on cultivar susceptibility and training system; however, the combined effect on the progress of temporal disease and on the possible reduction in SHD in the disease management was not investigated. The aim of this 3-year study was (i) to monitor and analyze the temporal dynamics of SHD progress under four training systems (4 × 1.5, 4 × 2, 5 × 2.5 and 6 × 3 m) and on four plum cultivars ('Cacanska lepotica', 'Bluefre', 'Stanley' and 'President') in an integrated plum orchard; (ii) to identify those time periods when training system and cultivar combinations can reduce the disease development. Both SHD incidences and the area under the disease progress curves (AUDPC) were significantly affected by the training system, cultivar and year. Plum cultivars with high or mid-high susceptibility to SHD showed continuous SHD development from May to November, while cultivars with low susceptibility to SHD showed no symptoms until mid-summer and then progressed slowly until November. High (4 × 1.5 m) vs. low (6 × 3 m) density training systems reduced SHD incidence and AUDPC consistently for three cultivars ('Cacanska lepotica', 'Stanley' and 'President') in September, October and November, compared to the high-density training system. Only cv. 'Bluefre' showed no effect either on disease incidence or AUDPC, due to very high disease incidences in all training systems from September to November. In conclusions, combinations of training system and cultivar can significantly reduce SHD incidence, which may be successfully used as a part of the integrated pest management approach during the establishment new plantations.

Usefulness of Tree Species as Urban Health Indicators.

We used the Air Pollution Tolerance Index (APTI), the amount of PM5 and PM10, and the elemental analysis of leaves to explore the sensitivity of tree species to air pollution. We assessed the tolerance of Robinia pseudoacacia, Acer saccharinum, Tilia × europaea, Acer platanoides, Fraxinus excelsior, Betula pendula, Celtis occidentalis, and Platanus × acerifolia to the amount of dust, APTI, and the elemental concentration of leaves. Leaves were collected in Debrecen (Hungary), which has a high intensity of vehicular traffic. The highest amount of PM (both PM10 and PM5) was found on the leaves of A. saccharinum and B. pendula. Our results demonstrated that A. saccharinum was moderately tolerant, while P. acerifolia was intermediate, based on the APTI value. There was a significant difference in the parameters of APTI and the elemental concentration of leaves among species. We found that tree leaves are reliable bioindicators of air pollution in urban areas. Based on the value of APTI, A. saccharinum and P. acerifolia, and based on PM, A. saccharinum and B. pendula are recommended as pollutant-accumulator species, while other studied species with lower APTI values are useful bioindicators of air pollution. The results support landscape engineers and urban developers in finding the best tree species that are tolerant to pollution and in using those as proxies of urban environmental health.

Assessing the WEPP model performance for predicting daily runoff in three terrestrial ecosystems in western Syria.

Soil erosion is one of the main threats facing the agriculture and natural resources sector all over the world, and the same is true for Syria. Several empirical and physically based tools have been proposed to assess erosion induced soil losses and runoff driving the processes, from plot to regional spatial scales. The main goal of this research is to evaluate the performance of the Water Erosion Prediction Project (WEPP) model in predicting runoff in comparison with field experiments in the Al-Sabahia region of Western Syria in three ecosystems: agricultural lands (AG), burned forest (BF) and forest (FO). To achieve this, field experimental plots (2∗1.65∗0.5 m) were prepared to obtain runoff observation data between September 2012 and December 2013. In addition, the input data (atmospheric forcing, soil, slope, land management) were prepared to run the WEPP model to estimate the runoff. The results indicate that the average observed runoffs in the AG, BF and FO were 12.54 ± 1.17, 4.81 ± 0.97 and 1.72 ± 0.16 mm/event, respectively, while the simulated runoffs in the AG, BF and FO were 15.15 ± 0.89, 9.23 ± 1.48 and 2.61 ± 0.47mm/event, respectively. The statistical evaluation of the model's performance showed an unsatisfactory performance of the WEPP model for predicting the run-offs in the study area. This may be caused by the structural flaws in the model, and/or the insufficient site-specific input parameters. So, to achieve good performance and reliable results of the WEPP model, more observation data is required from different ecosystems in Syria. These findings can provide guidance to planners and environmental engineers for proposing environmental protection and water resources management plans in the Coastal Region in Syria.

Temporal Patterns and Inter-Correlations among Physical and Antioxidant Attributes and Enzyme Activities of Apricot Fruit Inoculated with Monilinia laxa under Salicylic Acid and Methyl Jasmonate Treatments under Shelf-Life Conditions.

Monilinia laxa causes serious postharvest damage on apricot fruits under shelf-life storage conditions. Plant elicitors of methyl jasmonate (MeJA) and salicylic acid (SA) can reduce this damage, and their research can explain the background of the plant defense physiological processes in M. laxa-infected fruits. The aims of this study were: (i) to evaluate the effect of various concentrations of MeJA and SA on brown rot incidence (BRI) and lesion diameter (LD) of apricot fruits; (ii) to measure the temporal patterns for the effect of 0.4 mmol L-1 MeJA and 2 mmol L-1 SA treatments on BRI, LD and seven fruit measures (fruit firmness (FF), lignin content (LC), total soluble phenol content (TSPC), total antioxidant capacity (TAC) and enzyme activities of PAL, POD and SOD) in treatments of M. laxa-inoculated versus (vs.) non-inoculated fruits over an eight-day shelf-life storage period; and (iii) to determine inter-correlations among the seven fruit measures for MeJA and SA treatments. Both MeJA and SA significantly reduced BRI and LD. LC, FF, TAC, TSPC, as well as SOD and PAL activities in the MeJA and SA treatments were higher than the water-treated control in most assessment days and both inoculation treatments. In both inoculation treatments, the activity of POD in the SA-treated fruits was higher than MeJA-treated and control fruits at all dates. In MeJA vs. SA and inoculated vs. non-inoculated treatments, six variable pairs (FF vs. TSPC, FF vs. TAC, TAC vs. PAL, PAL vs. POD, PAL vs. SOD, and POD vs. SOD) showed significant inter-correlation values. Principal component analyses explained 96% and 93% of the total variance for inoculated and non-inoculated treatments, respectively. In inoculated treatments, both PC1 and PC2 explained 41% of the total variance and correlated with FF, TSPC and TAC and with PAL, SOD and POD, respectively. In non-inoculated treatments, PC1 and PC2 explained 49% and 44% of the total variance and correlated with LC, PAL, POD and SOD and with FF, TSPC and TAC, respectively. It can be concluded that MeJA and SA are useful in the practice to enhance the plant defense system against brown rot by reducing fungal growth and by improving physical and antioxidant attributes (FF, LC, TAC and TSPC) and the activity of defense-related enzymes (PAL, POD and SOD) in apricot fruits during shelf-life storage conditions.

Use of Leaves as Bioindicator to Assess Air Pollution Based on Composite Proxy Measure (APTI), Dust Amount and Elemental Concentration of Metals.

Monitoring air pollution and environmental health are crucial to ensure viable cities. We assessed the usefulness of the Air Pollution Tolerance Index (APTI) as a composite index of environmental health. Fine and coarse dust amount and elemental concentrations of Celtis occidentalis and Tilia × europaea leaves were measured in June and September at three sampling sites (urban, industrial, and rural) in Debrecen city (Hungary) to assess the usefulness of APTI. The correlation between APTI values and dust amount and elemental concentrations was also studied. Fine dust, total chlorophyll, and elemental concentrations were the most sensitive indicators of pollution. Based on the high chlorophyll and low elemental concentration of tree leaves, the rural site was the least disturbed by anthropogenic activities, as expected. We demonstrated that fine and coarse dust amount and elemental concentrations of urban tree leaves are especially useful for urban air quality monitoring. Correlations between APTI and other measured parameters were also found. Both C. occidentalis and T. europaea were sensitive to air pollution based on their APTI values. Thus, the APTI of tree leaves is an especially useful proxy measure of air pollution, as well as environmental health.

Pollution Assessment Based on Element Concentration of Tree Leaves and Topsoil in Ayutthaya Province, Thailand.

Atmospheric aerosol particles containing heavy metal contaminants deposit on the surface of plant leaves and the topsoil. Our aim was to reveal the pollution along an industrial-urban-rural gradient (IURG) in the central provinces of Thailand. Leaf samples from Ficus religiosa and Mimusops elengi were collected along with topsoil samples under the selected trees. Al, Ba, Ca, Cr, Cu, Fe, K, Mg, Mn, Na, Ni, Pb, and Zn concentrations were determined by ICP-OES in soil and plant samples. Soils were not polluted according to the critical value; furthermore, the elemental composition did not differ among the sampling sites of the IURG. The rural site was also polluted due to heavy amounts of untreated wastewater of the adjacent Chao Phraya River. Bioaccumulation factors of Ba, Cu, and Mn was higher than 1, suggesting active accumulation of these elements in plant tissue. Our findings proved that the deposition of air pollutants and the resistance to air pollutants in the case of plant leaves were different and that humus materials of the soils had relevant role in bioaccumulation of Al, Ba, and Cu. At the same time, the geochemical background, the source of pollution, and the local plant species greatly influence the metal content of any given environmental compartment.

Sequential Presentation Protects Working Memory From Catastrophic Interference.

Neural network models of memory are notorious for catastrophic interference: Old items are forgotten as new items are memorized (French, 1999; McCloskey & Cohen, 1989). While working memory (WM) in human adults shows severe capacity limitations, these capacity limitations do not reflect neural network style catastrophic interference. However, our ability to quickly apprehend the numerosity of small sets of objects (i.e., subitizing) does show catastrophic capacity limitations, and this subitizing capacity and WM might reflect a common capacity. Accordingly, computational investigations (Knops, Piazza, Sengupta, Eger & Melcher, 2014; Sengupta, Surampudi & Melcher, 2014) suggest that mutual inhibition among neurons can explain both kinds of capacity limitations as well as why our ability to estimate the numerosity of larger sets is limited according to a Weber ratio signature. Based on simulations with a saliency map-like network and mathematical proofs, we provide three results. First, mutual inhibition among neurons leads to catastrophic interference when items are presented simultaneously. The network can remember a limited number of items, but when more items are presented, the network forgets all of them. Second, if memory items are presented sequentially rather than simultaneously, the network remembers the most recent items rather than forgetting all of them. Hence, the tendency in WM tasks to sequentially attend even to simultaneously presented items might not only reflect attentional limitations, but also an adaptive strategy to avoid catastrophic interference. Third, the mean activation level in the network can be used to estimate the number of items in small sets, but it does not accurately reflect the number of items in larger sets. Rather, we suggest that the Weber ratio signature of large number discrimination emerges naturally from the interaction between the limited precision of a numeric estimation system and a multiplicative gain control mechanism.

Aerial Laser Scanning Data as a Source of Terrain Modeling in a Fluvial Environment: Biasing Factors of Terrain Height Accuracy.

Airborne light detection and ranging (LiDAR) scanning is a commonly used technology for representing the topographic terrain. As LiDAR point clouds include all surface features present in the terrain, one of the key elements for generating a digital terrain model (DTM) is the separation of the ground points. In this study, we intended to reveal the efficiency of different denoising approaches and an easy-to-use ground point classification technique in a floodplain with fluvial forms. We analyzed a point cloud from the perspective of the efficiency of noise reduction, parametrizing a ground point classifier (cloth simulation filter, CSF), interpolation methods and resolutions. Noise filtering resulted a wide range of point numbers in the models, and the number of points had moderate correlation with the mean accuracies (r = -0.65, p < 0.05), indicating that greater numbers of points had larger errors. The smallest differences belonged to the neighborhood-based noise filtering and the larger cloth size (5) and the smaller threshold value (0.2). The most accurate model was generated with the natural neighbor interpolation with the cloth size of 5 and the threshold of 0.2. These results can serve as a guide for researchers using point clouds when considering the steps of data preparation, classification, or interpolation in a flat terrain.

Dataset for landscape pattern analysis from a climatic perspective.

Revealing the driving forces of changes in landscape pattern is a key question of landscape ecology and landscape analysis. Temperature and precipitation as climatic variables have a dominant role in triggering vegetation changes; thus, a database, which contain their interaction, can support the understanding of spatio-temporal changes in vegetation patterns even on a large scale. The dataset provided in this article contain the R-squared values of bivariate linear regression analysis between the Normalized Difference Vegetation Index (target variable; as a general quantitative descriptor of surface greenness) of the TERRA satellite's MODIS sensor and the climatic variables of the CarpatClim database (predictor variables; maximum monthly temperature, aridification index, evapotranspiration and precipitation). Environmental variables are also included to support further analysis: terrain height, macro regions, land cover classes. The dataset has a spatial projection (i.e. maps) and covers the area of Hungary. Tabular version provides the possibility of traditional statistical analysis, while maps allow the investigation to involve the spatial characteristics of absolute and relative position of the data points. This data article is related to the paper "NDVI dynamics as reflected in climatic variables: spatial and temporal trends - a case study of Hungary" (Szabo et al., 2019).

Detailed assessment of spatial and temporal variations in river channel changes and meander evolution as a preliminary work for effective floodplain management. The example of Sajó River, Hungary.

The quasi-natural meandering type of alluvial rivers is quite unusual in Central European watersheds. The lack of extensive regulation allows such rivers to shift along their floodplain and cause erosion of natural and agricultural lands. Description of channel morphometric parameters over decadal timescales allows a better understanding of such river systems like Sajó River (Slovakia-Hungary) where no preliminary work is available regarding channel dynamics. In addition, to just describing the geomorphic processes, the environmental management implications of these meandering rivers need to be investigated as well. Thus, this study represents a bend-scale morphological analysis on the 124 km long section of the Sajó River in the Hungarian territory in eight different periods between 1952 and 2011. Archive aerial imagery, orthophotographs and topographical maps were organized into a database, then GIS-based analyses were performed to quantify the rate and extent of channel shifts, bend development and the area of erosion/accretion. On the bend scale, we have calculated several morphometric parameters (bend length, chord, amplitude, the radius of curvature) to quantify the evolutionary trajectory of reaches. Hydrological time series data were evaluated to reveal its possible role in the processes. Based on the available GIS-data of natural elements and anthropogenic intervention, we delineated 12 different reaches showing similar characteristics, from which six reaches were defined as natural. According to the morphometric parameters of the natural reaches, channel widths became narrower and the planform became more concentrated spatially in most of the reaches while the overall sinuosity of almost all natural reaches increased. Although artificial cutoffs mainly reduced the reach complexity, in some cases, they have accelerated the bend development downstream in the following few years. Erosion and accretion activity were higher in the periods when the discharge was higher than the effective discharge but its effect became less apparent in the second half of the investigated time period. By 1980, major artificial cutoffs and bank protection works were carried out that could have an impact in reducing the potential channel shifting. Based on our results, we propose a possible preservation and some modifications along the Hungarian part of the Sajó River reaches to be carried out by the local river management authorities. We conclude that this study provides a detailed demonstration of the Sajó River morphodymanics which can be used for further land planning to avoid harmful consequences of recent bank erosion processes not only along the Sajó River, but other similar rivers in Europe.

Establishment of Fascioloides magna in a new region of Hungary: case report.

During the monitoring of red deer (N = 124) and fallow deer (N = 13) populations in four neighbouring areas, the presence of Fascioloides magna was confirmed in southwestern Hungary. The prevalence and the mean intensity of the infection within the host populations ranged between 0 and 100% and 0-36.3, respectively. The determined prevalences are similar to that observed earlier in other European natural foci. The authors hypothesise that the appearance of F. magna in this region should have been a partly natural- and partly human-influenced process.

[Colon reconstruction after the Hartmann procedure. Laparoscopy or laparotomy?] / Colonrekonstrukció Hartmann-mutét után. Laparoszkópia vagy laparotomia?

The Hartmann procedure - primarily - was introduced for the treatment of cancerous diseases of sigmoid colon and rectum. In the last few years it was performed in cases with complicated inflammation of the left colon, colon cancers with bowel obstruction or perforation, or in the case of insufficiency of the anastomoses, or in urgent operations after traumatics bowel injuries, when making the anastomosis is at very high risk. Later on the restoration of the continuity of the GI tract can be done traditionally (by laparotomy) or laparoscopically. We present our experiences with the above technique, and also compare our results with traditional open surgeries in our patients.

Interference and memory capacity limitations.

Working memory (WM) is thought to have a fixed and limited capacity. However, the origins of these capacity limitations are debated, and generally attributed to active, attentional processes. Here, we show that the existence of interference among items in memory mathematically guarantees fixed and limited capacity limits under very general conditions, irrespective of any processing assumptions. Assuming that interference (a) increases with the number of interfering items and (b) brings memory performance to chance levels for large numbers of interfering items, capacity limits are a simple function of the relative influence of memorization and interference. In contrast, we show that time-based memory limitations do not lead to fixed memory capacity limitations that are independent of the timing properties of an experiment. We show that interference can mimic both slot-like and continuous resource-like memory limitations, suggesting that these types of memory performance might not be as different as commonly believed. We speculate that slot-like WM limitations might arise from crowding-like phenomena in memory when participants have to retrieve items. Further, based on earlier research on parallel attention and enumeration, we suggest that crowding-like phenomena might be a common reason for the 3 major cognitive capacity limitations. As suggested by Miller (1956) and Cowan (2001), these capacity limitations might arise because of a common reason, even though they likely rely on distinct processes. (PsycINFO Database Record

Multiple Forms of Endocannabinoid and Endovanilloid Signaling Regulate the Tonic Control of GABA Release.

Persistent CB1 cannabinoid receptor activity limits neurotransmitter release at various synapses throughout the brain. However, it is not fully understood how constitutively active CB1 receptors, tonic endocannabinoid signaling, and its regulation by multiple serine hydrolases contribute to the synapse-specific calibration of neurotransmitter release probability. To address this question at perisomatic and dendritic GABAergic synapses in the mouse hippocampus, we used a combination of paired whole-cell patch-clamp recording, liquid chromatography/tandem mass spectrometry, stochastic optical reconstruction microscopy super-resolution imaging, and immunogold electron microscopy. Unexpectedly, application of the CB1 antagonist and inverse agonist AM251 [N-1-(2,4-dichlorophenyl)-5-(4-iodophenyl)-4-methyl-N-1-piperidinyl-1H-pyrazole-3-carboxamide], but not the neutral antagonist NESS0327 [8-chloro-1-(2,4-dichlorophenyl)-N-piperidin-1-yl-5,6-dihydro-4H-benzo[2,3]cyclohepta[2,4-b]pyrazole-3-carboxamine], significantly increased synaptic transmission between CB1-positive perisomatic interneurons and CA1 pyramidal neurons. JZL184 (4-nitrophenyl 4-[bis(1,3-benzodioxol-5-yl)(hydroxy)methyl]piperidine-1-carboxylate), a selective inhibitor of monoacylglycerol lipase (MGL), the presynaptic degrading enzyme of the endocannabinoid 2-arachidonoylglycerol (2-AG), elicited a robust increase in 2-AG levels and concomitantly decreased GABAergic transmission. In contrast, inhibition of fatty acid amide hydrolase (FAAH) by PF3845 (N-pyridin-3-yl-4-[[3-[5-(trifluoromethyl)pyridin-2-yl]oxyphenyl]methyl]piperidine-1-carboxamide) elevated endocannabinoid/endovanilloid anandamide levels but did not change GABAergic synaptic activity. However, FAAH inhibitors attenuated tonic 2-AG increase and also decreased its synaptic effects. This antagonistic interaction required the activation of the transient receptor potential vanilloid receptor TRPV1, which was concentrated on postsynaptic intracellular membrane cisternae at perisomatic GABAergic symmetrical synapses. Interestingly, neither AM251, JZL184, nor PF3845 affected CB1-positive dendritic interneuron synapses. Together, these findings are consistent with the possibility that constitutively active CB1 receptors substantially influence perisomatic GABA release probability and indicate that the synaptic effects of tonic 2-AG release are tightly controlled by presynaptic MGL activity and also by postsynaptic endovanilloid signaling and FAAH activity. SIGNIFICANCE STATEMENT: Tonic cannabinoid signaling plays a critical role in the regulation of synaptic transmission. However, the mechanistic details of how persistent CB1 cannabinoid receptor activity inhibits neurotransmitter release have remained elusive. Therefore, electrophysiological recordings, lipid measurements, and super-resolution imaging were combined to elucidate those signaling molecules and mechanisms that underlie tonic cannabinoid signaling. The findings indicate that constitutive CB1 activity has pivotal function in the tonic control of hippocampal GABA release. Moreover, the endocannabinoid 2-arachidonoylglycerol (2-AG) is continuously generated postsynaptically, but its synaptic effect is regulated strictly by presynaptic monoacylglycerol lipase activity. Finally, anandamide signaling antagonizes tonic 2-AG signaling via activation of postsynaptic transient receptor potential vanilloid TRPV1 receptors. This unexpected mechanistic diversity may be necessary to fine-tune GABA release probability under various physiological and pathophysiological conditions.

Cell-specific STORM super-resolution imaging reveals nanoscale organization of cannabinoid signaling.

A major challenge in neuroscience is to determine the nanoscale position and quantity of signaling molecules in a cell type- and subcellular compartment-specific manner. We developed a new approach to this problem by combining cell-specific physiological and anatomical characterization with super-resolution imaging and studied the molecular and structural parameters shaping the physiological properties of synaptic endocannabinoid signaling in the mouse hippocampus. We found that axon terminals of perisomatically projecting GABAergic interneurons possessed increased CB1 receptor number, active-zone complexity and receptor/effector ratio compared with dendritically projecting interneurons, consistent with higher efficiency of cannabinoid signaling at somatic versus dendritic synapses. Furthermore, chronic Δ(9)-tetrahydrocannabinol administration, which reduces cannabinoid efficacy on GABA release, evoked marked CB1 downregulation in a dose-dependent manner. Full receptor recovery required several weeks after the cessation of Δ(9)-tetrahydrocannabinol treatment. These findings indicate that cell type-specific nanoscale analysis of endogenous protein distribution is possible in brain circuits and identify previously unknown molecular properties controlling endocannabinoid signaling and cannabis-induced cognitive dysfunction.