Effects of iodinated contrast agent, xylocaine and gadolinium concentration on the signal emitted in magnetic resonance arthrography: a samples study

Objective:To investigate the effects of dilution of paramagnetic contrast agent with iodinated contrast and xylocaine on the signal intensity during magnetic resonance arthrography, and to improve the paramagnetic contrast agent concentration utilized in this imaging modality.Materials and Methods:Samples specially prepared for the study with three different concentrations of paramagnetic contrast agent diluted in saline, iodinated contrast agent and xylocaine were imaged with fast spin echo T1-weighted sequences with fat saturation. The samples were placed into flasks and graphical analysis of the signal intensity was performed as a function of the paramagnetic contrast concentration.Results:As compared with samples of equal concentrations diluted only with saline, the authors have observed an average signal intensity decrease of 20.67% for iodinated contrast agent, and of 28.34% for xylocaine. However, the increased gadolinium concentration in the samples caused decrease in signal intensity with all the dilutions.Conclusion:Minimizing the use of iodinated contrast media and xylocaine and/or the use of a gadolinium concentration of 2.5 mmol/L diluted in saline will improve the sensitivity of magnetic resonance arthrography.

Gadolinium increases the vascular reactivity of rat aortic rings

Gadolinium (Gd) blocks intra- and extracellular ATP hydrolysis. We determined whether Gd affects vascular reactivity to contractile responses to phenylephrine (PHE) by blocking aortic ectonucleoside triphosphate diphosphohydrolase (E-NTPDase). Wistar rats of both sexes (260-300 g, 23 females, 7 males) were used. Experiments were performed before and after incubation of aortic rings with 3 µM Gd. Concentration-response curves to PHE (0.1 nM to 0.1 mM) were obtained in the presence and absence of endothelium, after incubation with 100 µM L-NAME, 10 µM losartan, or 10 µM enalaprilat. Gd significantly increased the maximum response (control: 72.3 ± 3.5; Gd: 101.3 ± 6.4%) and sensitivity (control: 6.6 ± 0.1; Gd: 10.5 ± 2.8%) to PHE. To investigate the blockade of E-NTDase activity by Gd, we added 1 mM ATP to the bath. ATP reduced smooth muscle tension and Gd increased its relaxing effect (control: -33.5 ± 4.1; Gd: -47.4 ± 4.1%). Endothelial damage abolished the effect of Gd on the contractile responses to PHE (control: 132.6 ± 8.6; Gd: 122.4 ± 7.1%). L-NAME + Gd in the presence of endothelium reduced PHE contractile responses (control/L-NAME: 151.1 ± 28.8; L-NAME + Gd: 67.9 ± 19% AUC). ATP hydrolysis was reduced after Gd administration, which led to ATP accumulation in the nutrient solution and reduced ADP concentration, while adenosine levels remained the same. Incubation with Gd plus losartan and enalaprilat eliminated the pressor effects of Gd. Gd increased vascular reactivity to PHE regardless of the reduction of E-NTPDase activity and adenosine production. Moreover, the increased reactivity to PHE promoted by Gd was endothelium-dependent, reducing NO bioavailability and involving an increased stimulation of angiotensin-converting enzyme and angiotensin II AT1 receptors.

Toxic effects of mercury, lead and gadolinium on vascular reactivity

Heavy metals have been used in a wide variety of human activities that have significantly increased both professional and environmental exposure. Unfortunately, disasters have highlighted the toxic effects of metals on different organs and systems. Over the last 50 years, the adverse effects of chronic lead, mercury and gadolinium exposure have been underscored. Mercury and lead induce hypertension in humans and animals, affecting endothelial function in addition to their other effects. Increased cardiovascular risk after exposure to metals has been reported, but the underlying mechanisms, mainly for short periods of time and at low concentrations, have not been well explored. The presence of other metals such as gadolinium has raised concerns about contrast-induced nephropathy and, interestingly, despite this negative action, gadolinium has not been defined as a toxic agent. The main actions of these metals, demonstrated in animal and human studies, are an increase of free radical production and oxidative stress and stimulation of angiotensin I-converting enzyme activity, among others. Increased vascular reactivity, highlighted in the present review, resulting from these actions might be an important mechanism underlying increased cardiovascular risk. Finally, the results described in this review suggest that mercury, lead and gadolinium, even at low doses or concentrations, affect vascular reactivity. Acting via the endothelium, by continuous exposure followed by their absorption, they can increase the production of free radicals and of angiotensin II, representing a hazard for cardiovascular function. In addition, the actual reference values, considered to pose no risk, need to be reduced.

A hypothesis for the geochemical anomaly in the North Creek Watershed /

A regional geochemical reconnaissance by bottom stream sediment sampling, has delineated an area of high metal content in the north central sector of the North Creek Watershed. Development of a geochemical model, relating to the relative chemical concentrations derived from the chemical analyses of bottom sediments, suspended sediments, stream waters and well waters collected from the north central sector, was designed to discover the source of the anomaly. Samples of each type of material were analysed by the A.R.L. Direct Reading Multi-element Emission Spectrograph Q.A. 137 for elements: Na, K, Ca, Sr, Si, As, Pb, Zn, Cd, Ni, Ti, Ag, Mo, Be, Fe, AI, Mn, Cu, Cr, P and Y. Anomalous results led to the discovery of a spring, the waters of which carried high concentrations of Zn, Cd, Pb, As, Ni, Ti, Ag, Sr and Si. In addition, the spring waters had high concentrations of Na, Ca, Mg, 504 , alkalinity, N03' and low concentrations of K, Cl and NH3. Increased specific conductivity (up to 2500 ~mho/cm.) was noted in the spring waters as well as increased calculated total dissolved solids (up to 2047 mg/l) and increased ionic strength (up to 0.06). On the other hand, decreases were noted in water temperature (8°C), pH (pH 7.2) and Eh (+.154 volts). Piezometer nests were installed in the anomalous north central sector of the watershed. In accordance with the slope of the piezometric surface from wells cased down to the till/bedrock interface, groundwater flow is directed from the recharge area (northwest of the anomaly) towards the artesian spring via the highly fractured dolostone aquifer of the Upper Eramosa Member. The bedrock aquifer is confined by the overlying Halton till and the underlying Lower Eramosa Member (Vinemount Shale). The oxidation of sphalerite and galena and the dissolution of gypsum, celestite, calcite, and dolomite within the Eramosa Member, contributed its highly, dissolved constituents to the circulating groundwaters, the age of which is greater than 20 years as determined by tritium dating. Groundwater is assumed to flow along the Vinemount Shale and discharge as an artesian spring where the shale unit becomes discontinuous. The anomaly is located on a topographic low where bedrock is close to the surface. Thermodynamic evaluation of the major ion speciation from the anomalous spring and surface waters, showed gypsum to be supersaturated in these spring waters. Downstream from the spring, the loss of carbon dioxide from the spring waters resulted in the supersaturation with respect to calcite, aragonite, magnesite and dolomite. This corresponded with increases in Eh (+.304 volts) and pH (pH 8.5) in the anomalous surface waters. In conclusion, the interaction of groundwaters within the highly, mineralized carbonate source (Eramosa Member) resulted in the characteristic Ca*Mg*HC03*S04 spring water at the anomalous site, which appeared to be the principle effect upon controlling the anomalous surface water chemistry.

Infrared Spectroscopy of Gadolinium

Measurements of the optical reflectivity of the normal incident light along c-axis [0001] have been made on a Gadolinium single crystal, for temperatures between 50 K and room temperature just above the Curie temperature of Gd, which is 293 K. And covering the spectrum range between 100 -11000 cm-I . This work is the first study of Gd in the far infrared range. In fact it fills the gap below 0.2 eV which has never been measured before. Extreme attention was paid to the fact that Gadolinium is a very reactive metal with air. Thus, the sample was mechanically polished and carefully handled during the measurement. However, temperature dependent optical measurements have been made in the same frequency range for a sample of Gd2O3. For comparison, both samples of Gd and Gd2O3 were examined by X-Ray diffraction. XRD analysis showed that the sample was pure gadolinium and the oxide layer either does not exist, or is very thin. Furthermore, this fact was supported by the absence of any of Gd2O3 features in the Gd sample reflectivity. Kramers Kronig analysis was applied to extract the optical functions from the reflectance data. The optical conductivity shows a strong temperature dependence feature in the mid-infrared. This feature disappears completely at room temperature which supports a magnetic origin.

Anomaly Detection Using System Call Sequence Sets.

This paper discusses our research in developing a generalized and systematic method for anomaly detection. The key ideas are to represent normal program behaviour using system call frequencies and to incorporate probabilistic techniques for classification to detect anomalies and intrusions. Using experiments on the sendmail system call data, we demonstrate that concise and accurate classifiers can be constructed to detect anomalies. An overview of the approach that we have implemented is provided.

Adaptive Real-time Anomaly-based Intrusion Detection using Data Mining and Machine Learning Techniques

Die zunehmende Vernetzung der Informations- und Kommunikationssysteme führt zu einer weiteren Erhöhung der Komplexität und damit auch zu einer weiteren Zunahme von Sicherheitslücken. Klassische Schutzmechanismen wie Firewall-Systeme und Anti-Malware-Lösungen bieten schon lange keinen Schutz mehr vor Eindringversuchen in IT-Infrastrukturen. Als ein sehr wirkungsvolles Instrument zum Schutz gegenüber Cyber-Attacken haben sich hierbei die Intrusion Detection Systeme (IDS) etabliert. Solche Systeme sammeln und analysieren Informationen von Netzwerkkomponenten und Rechnern, um ungewöhnliches Verhalten und Sicherheitsverletzungen automatisiert festzustellen. Während signatur-basierte Ansätze nur bereits bekannte Angriffsmuster detektieren können, sind anomalie-basierte IDS auch in der Lage, neue bisher unbekannte Angriffe (Zero-Day-Attacks) frühzeitig zu erkennen. Das Kernproblem von Intrusion Detection Systeme besteht jedoch in der optimalen Verarbeitung der gewaltigen Netzdaten und der Entwicklung eines in Echtzeit arbeitenden adaptiven Erkennungsmodells. Um diese Herausforderungen lösen zu können, stellt diese Dissertation ein Framework bereit, das aus zwei Hauptteilen besteht. Der erste Teil, OptiFilter genannt, verwendet ein dynamisches "Queuing Concept", um die zahlreich anfallenden Netzdaten weiter zu verarbeiten, baut fortlaufend Netzverbindungen auf, und exportiert strukturierte Input-Daten für das IDS. Den zweiten Teil stellt ein adaptiver Klassifikator dar, der ein Klassifikator-Modell basierend auf "Enhanced Growing Hierarchical Self Organizing Map" (EGHSOM), ein Modell für Netzwerk Normalzustand (NNB) und ein "Update Model" umfasst. In dem OptiFilter werden Tcpdump und SNMP traps benutzt, um die Netzwerkpakete und Hostereignisse fortlaufend zu aggregieren. Diese aggregierten Netzwerkpackete und Hostereignisse werden weiter analysiert und in Verbindungsvektoren umgewandelt. Zur Verbesserung der Erkennungsrate des adaptiven Klassifikators wird das künstliche neuronale Netz GHSOM intensiv untersucht und wesentlich weiterentwickelt. In dieser Dissertation werden unterschiedliche Ansätze vorgeschlagen und diskutiert. So wird eine classification-confidence margin threshold definiert, um die unbekannten bösartigen Verbindungen aufzudecken, die Stabilität der Wachstumstopologie durch neuartige Ansätze für die Initialisierung der Gewichtvektoren und durch die Stärkung der Winner Neuronen erhöht, und ein selbst-adaptives Verfahren eingeführt, um das Modell ständig aktualisieren zu können. Darüber hinaus besteht die Hauptaufgabe des NNB-Modells in der weiteren Untersuchung der erkannten unbekannten Verbindungen von der EGHSOM und der Überprüfung, ob sie normal sind. Jedoch, ändern sich die Netzverkehrsdaten wegen des Concept drif Phänomens ständig, was in Echtzeit zur Erzeugung nicht stationärer Netzdaten führt. Dieses Phänomen wird von dem Update-Modell besser kontrolliert. Das EGHSOM-Modell kann die neuen Anomalien effektiv erkennen und das NNB-Model passt die Änderungen in Netzdaten optimal an. Bei den experimentellen Untersuchungen hat das Framework erfolgversprechende Ergebnisse gezeigt. Im ersten Experiment wurde das Framework in Offline-Betriebsmodus evaluiert. Der OptiFilter wurde mit offline-, synthetischen- und realistischen Daten ausgewertet. Der adaptive Klassifikator wurde mit dem 10-Fold Cross Validation Verfahren evaluiert, um dessen Genauigkeit abzuschätzen. Im zweiten Experiment wurde das Framework auf einer 1 bis 10 GB Netzwerkstrecke installiert und im Online-Betriebsmodus in Echtzeit ausgewertet. Der OptiFilter hat erfolgreich die gewaltige Menge von Netzdaten in die strukturierten Verbindungsvektoren umgewandelt und der adaptive Klassifikator hat sie präzise klassifiziert. Die Vergleichsstudie zwischen dem entwickelten Framework und anderen bekannten IDS-Ansätzen zeigt, dass der vorgeschlagene IDSFramework alle anderen Ansätze übertrifft. Dies lässt sich auf folgende Kernpunkte zurückführen: Bearbeitung der gesammelten Netzdaten, Erreichung der besten Performanz (wie die Gesamtgenauigkeit), Detektieren unbekannter Verbindungen und Entwicklung des in Echtzeit arbeitenden Erkennungsmodells von Eindringversuchen.

Land surface anomaly simulations and predictions with a climate model: an El Nino Southern Oscillation case study

The ability of climate models to reproduce and predict land surface anomalies is an important but little-studied topic. In this study, an atmosphere and ocean assimilation scheme is used to determine whether HadCM3 can reproduce and predict snow water equivalent and soil moisture during the 1997–1998 El Nino Southern Oscillation event. Soil moisture is reproduced more successfully, though both snow and soil moisture show some predictability at 1- and 4-month lead times. This result suggests that land surface anomalies may be reasonably well initialized for climate model predictions and hydrological applications using atmospheric assimilation methods over a period of time.

Can desert dust explain the outgoing longwave radiation anomaly over the Sahara during July 2003?

Measurements of the top‐of‐the‐atmosphere outgoing longwave radiation (OLR) for July 2003 from Meteosat‐7 are used to assess the performance of the numerical weather prediction version of the Met Office Unified Model. A significant difference is found over desert regions of northern Africa where the model emits too much OLR by up to 35 Wm−2 in the monthly mean. By cloud‐screening the data we find an error of up to 50 Wm−2 associated with cloud‐free areas, which suggests an error in the model surface temperature, surface emissivity, or atmospheric transmission. By building up a physical model of the radiative properties of mineral dust based on in situ, and surface‐based and satellite remote sensing observations we show that the most plausible explanation for the discrepancy in OLR is due to the neglect of mineral dust in the model. The calculations suggest that mineral dust can exert a longwave radiative forcing by as much as 50 Wm−2 in the monthly mean for 1200 UTC in cloud‐free regions, which accounts for the discrepancy between the model and the Meteosat‐7 observations. This suggests that inclusion of the radiative effects of mineral dust will lead to a significant improvement in the radiation balance of numerical weather prediction models with subsequent improvements in performance.

Observation and origin of an interannual salinity anomaly in the Mozambique Channel

A positive salinity anomaly of 0.2 PSU was observed between 50 and 200 m over the years 2000–2001 across the Mozambique Channel at a section at 17°S which was repeated in 2003, 2005, 2006, and 2008. Meanwhile, a moored array is continued from 2003 to 2008. This anomaly was most distinct showing an interannual but nonseasonal variation. The possible origin of the anomaly is investigated using output from three ocean general circulation models (Estimating the Circulation and Climate of the Ocean, Ocean Circulation and Climate Advanced Modeling, and Parallel Ocean Program). The most probable mechanism for the salinity anomaly is the anomalous inflow of subtropical waters caused by a weakening of the northern part of the South Equatorial Current by weaker trade winds. This mechanism was found in all three numerical models. In addition, the numerical models indicate a possible salinization of one of the source water masses to the Mozambique Channel as an additional cause of the anomaly. The anomaly propagated southward into the Agulhas Current and northward along the African coast.

Idealized SST anomaly regional climate model experiments: a note of caution

To date, a number of studies have focused on the influence of sea surface temperature (SST) on global and regional rainfall variability, with the majority of these focusing on certain ocean basins e.g. the Pacific, North Atlantic and Indian Ocean. In contrast, relatively less work has been done on the influence of the central South Atlantic, particularly in relation to rainfall over southern Africa. Previous work by the authors, using reanalysis data and general circulation model (GCM) experiments, has suggested that cold SST anomalies in the central southern Atlantic Ocean are linked to an increase in rainfall extremes across southern Africa. In this paper we present results from idealised regional climate model (RCM) experiments forced with both positive and negative SST anomalies in the southern Atlantic Ocean. These experiments reveal an unexpected response of rainfall over southern Africa. In particular it was found that SST anomalies of opposite sign can cause similar rainfall responses in the model experiments, with isolated increases in rainfall over central southern Africa as well as a large region of drying over the Mozambique Channel. The purpose of this paper is to highlight this finding and explore explanations for the behaviour of the climate model. It is suggested that the observed changes in rainfall might result from the redistribution of energy (associated with upper level changes to Rossby waves) or, of more concern, model error, and therefore the paper concludes that the results of idealised regional climate models forced with SST anomalies should be viewed cautiously.

Support for global climate reorganization during the "Medieval Climate Anomaly"

Widely distributed proxy records indicate that the Medieval Climate Anomaly (MCA; *900–1350 AD) was characterized by coherent shifts in large-scale Northern Hemisphere atmospheric circulation patterns. Although cooler sea surface temperatures in the central and eastern equatorial Pacific can explain some aspects of medieval circulation changes, they are not sufficient to account for other notable features, including widespread aridity through the Eurasian sub-tropics, stronger winter westerlies across the North Atlantic and Western Europe, and shifts in monsoon rainfall patterns across Africa and South Asia. We present results from a full-physics coupled climate model showing that a slight warming of the tropical Indian and western Pacific Oceans relative to the other tropical ocean basins can induce a broad range of the medieval circulation and climate changes indicated by proxy data, including many of those not explained by a cooler tropical Pacific alone. Important aspects of the results resemble those from previous simulations examining the climatic response to the rapid Indian Ocean warming during the late twentieth century, and to results from climate warming simulations—especially in indicating an expansion of the Northern Hemisphere Hadley circulation. Notably, the pattern of tropical Indo-Pacific sea surface temperature (SST) change responsible for producing the proxy-model similarity in our results agrees well with MCA-LIA SST differences obtained in a recent proxy-based climate field reconstruction. Though much remains unclear, our results indicate that the MCA was characterized by an enhanced zonal Indo-Pacific SST gradient with resulting changes in Northern Hemisphere tropical and extra-tropical circulation patterns and hydroclimate regimes, linkages that may explain the coherent regional climate shifts indicated by proxy records from across the planet. The findings provide new perspectives on the nature and possible causes of the MCA—a remarkable, yet incompletely understood episode of Late Holocene climatic change.

Evidence for a widespread climatic anomaly at around 9.2 ka before present.

The 8.2 ka event was triggered by a meltwater pulse (MWP) into the North Atlantic and resultant reduction of the thermohaline circulation (THC). This event was preceded by a series of at least 14 MWPs; their impact on early Holocene climate has remained almost unknown. A set of high-quality paleoclimate records from across the Northern Hemisphere shows evidence for a widespread and significant climatic anomaly at ∼9.2 ka B.P. This event has climatic anomaly patterns very similar to the 8.2 ka B.P. event, cooling occurred at high latitudes and midlatitudes and drying took place in the northern tropics, and is concurrent with an MWP of considerable volume (∼8100 km3). As the 9.2 ka MWP occurs at a time of enhanced baseline freshwater flow into the North Atlantic, this MWP may have been, despite its relatively small volume, sufficient to weaken THC and to induce the observed climate anomaly pattern.