Variable-temperature, variable-field magnetic circular dichroism spectroscopic study of NifEN-bound precursor and “FeMoco”

NifEN plays a key role in the biosynthesis of the iron–molybdenum cofactor (FeMoco) of nitrogenase. A scaffold protein that hosts the conversion of a FeMoco precursor to a mature cofactor, NifEN can assume three conformations during the process of FeMoco maturation. One, designated ΔnifB NifEN, contains only two permanent [Fe4S4]-like clusters. The second, designated NifENPrecursor, contains the permanent clusters and a precursor form of FeMoco. The third, designated NifEN“FeMoco”, contains the permanent [Fe4S4]-like clusters and a fully complemented, “FeMoco”-like structure. Here, we report a variable-temperature, variable-field magnetic circular dichroism spectroscopic investigation of the electronic structure of the metal clusters in the three forms of dithionite-reduced NifEN. Our data indicate that the permanent [Fe4S4]-like clusters are structurally and electronically conserved in all three NifEN species and exhibit spectral features of classic [Fe4S4]+ clusters; however, they are present in a mixed spin state with a small contribution from the S > ½ spin state. Our results also suggest that both the precursor and “FeMoco” have a conserved Fe/S electronic structure that is similar to the electronic structure of FeMoco in the MoFe protein, and that the “FeMoco” in NifEN“FeMoco” exists, predominantly, in an S = 3/2 spin state with spectral parameters identical to those of FeMoco in the MoFe protein. These observations provide strong support to the outcome of our previous EPR and X-ray absorption spectroscopy/extended X-ray absorption fine structure analysis of the three NifEN species while providing significant new insights into the unique electronic properties of the precursor and “FeMoco” in NifEN

Data Stream Clustering for Real-Time Anomaly Detection: An Application to Insider Threats

Insider threat detection is an emergent concern for academia, industries, and governments due to the growing number of insider incidents in recent years. The continuous streaming of unbounded data coming from various sources in an organisation, typically in a high velocity, leads to a typical Big Data computational problem. The malicious insider threat refers to anomalous behaviour(s) (outliers) that deviate from the normal baseline of a data stream. The absence of previously logged activities executed by users shapes the insider threat detection mechanism into an unsupervised anomaly detection approach over a data stream. A common shortcoming in the existing data mining approaches to detect insider threats is the high number of false alarms/positives (FPs). To handle the Big Data issue and to address the shortcoming, we propose a streaming anomaly detection approach, namely Ensemble of Random subspace Anomaly detectors In Data Streams (E-RAIDS), for insider threat detection. E-RAIDS learns an ensemble of p established outlier detection techniques [Micro-cluster-based Continuous Outlier Detection (MCOD) or Anytime Outlier Detection (AnyOut)] which employ clustering over continuous data streams. Each model of the p models learns from a random feature subspace to detect local outliers, which might not be detected over the whole feature space. E-RAIDS introduces an aggregate component that combines the results from the p feature subspaces, in order to confirm whether to generate an alarm at each window iteration. The merit of E-RAIDS is that it defines a survival factor and a vote factor to address the shortcoming of high number of FPs. Experiments on E-RAIDS-MCOD and E-RAIDS-AnyOut are carried out, on synthetic data sets including malicious insider threat scenarios generated at Carnegie Mellon University, to test the effectiveness of voting feature subspaces, and the capability to detect (more than one)-behaviour-all-threat in real-time. The results show that E-RAIDS-MCOD reports the highest F1 measure and less number of false alarm = 0 compared to E-RAIDS-AnyOut, as well as it attains to detect approximately all the insider threats in real-time

Lack of robustness of textural measures obtained from 3D brain tumor MRIs impose a need for standardization

Purpose Textural measures have been widely explored as imaging biomarkers in cancer. However, their robustness under dynamic range and spatial resolution changes in brain 3D magnetic resonance images (MRI) has not been assessed. The aim of this work was to study potential variations of textural measures due to changes in MRI protocols. Materials and methods Twenty patients harboring glioblastoma with pretreatment 3D T1-weighted MRIs were included in the study. Four different spatial resolution combinations and three dynamic ranges were studied for each patient. Sixteen three-dimensional textural heterogeneity measures were computed for each patient and configuration including co-occurrence matrices (CM) features and run-length matrices (RLM) features. The coefficient of variation was used to assess the robustness of the measures in two series of experiments corresponding to (i) changing the dynamic range and (ii) changing the matrix size. Results No textural measures were robust under dynamic range changes. Entropy was the only textural feature robust under spatial resolution changes (coefficient of variation under 10% in all cases). Conclusion Textural measures of three-dimensional brain tumor images are not robust neither under dynamic range nor under matrix size changes. Standards should be harmonized to use textural features as imaging biomarkers in radiomic-based studies. The implications of this work go beyond the specific tumor type studied here and pose the need for standardization in textural feature calculation of oncological images

Spectroscopic evidence for an all-ferrous [4Fe–4S]0 cluster in the superreduced activator of 2-hydroxyglutaryl-CoA dehydratase from Acidaminococcus fermentans

The key enzyme of the fermentation of glutamate by Acidaminococcus fermentans, 2-hydroxyglutarylcoenzyme A dehydratase, catalyzes the reversible syn-elimination of water from (R)-2-hydroxyglutaryl-coenzyme A, resulting in (E)-glutaconylcoenzyme A. The dehydratase system consists of two oxygen-sensitive protein components, the activator (HgdC) and the actual dehydratase (HgdAB). Previous biochemical and spectroscopic studies revealed that the reduced [4Fe–4S]+ cluster containing activator transfers one electron to the dehydratase driven by ATP hydrolysis, which activates the enzyme. With a tenfold excess of titanium(III) citrate at pH 8.0 the activator can be further reduced, yielding about 50% of a superreduced [4Fe–4S]0 cluster in the all-ferrous state. This is inferred from the appearance of a new Mössbauer spectrum with parameters δ = 0.65 mm/s and ΔEQ = 1.51–2.19 mm/s at 140 K, which are typical of Fe(II)S4 sites. Parallel-mode electron paramagnetic resonance (EPR) spectroscopy performed at temperatures between 3 and 20 K showed two sharp signals at g = 16 and 12, indicating an integer-spin system. The X-band EPR spectra and magnetic Mössbauer spectra could be consistently simulated by adopting a total spin St = 4 for the all-ferrous cluster with weak zero-field splitting parameters D = −0.66 cm−1 and E/D = 0.17. The superreduced cluster has apparent spectroscopic similarities with the corresponding [4Fe–4S]0 cluster described for the nitrogenase Fe-protein, but in detail their properties differ. While the all-ferrous Fe-protein is capable of transferring electrons to the MoFe-protein for dinitrogen reduction, a similar physiological role is elusive for the superreduced activator. This finding supports our model that only one-electron transfer steps are involved in dehydratase catalysis. Nevertheless we discuss a common basic mechanism of the two diverse systems, which are so far the only described examples of the all-ferrous [4Fe–4S]0 cluster found in biology

Reperfusion injury following cerebral ischemia: pathophysiology, MR imaging, and potential therapies

INTRODUCTION: Restoration of blood flow following ischemic stroke can be achieved by means of thrombolysis or mechanical recanalization. However, for some patients, reperfusion may exacerbate the injury initially caused by ischemia, producing a so-called “cerebral reperfusion injury”. Multiple pathological processes are involved in this injury, including leukocyte infiltration, platelet and complement activation, postischemic hyperperfusion, and breakdown of the blood–brain barrier. METHODS/RESULTS AND CONCLUSIONS: Magnetic resonance imaging (MRI) can provide extensive information on this process of injury, and may have a role in the future in stratifying patients’ risk for reperfusion injury following recanalization. Moreover, different MRI modalities can be used to investigate the various mechanisms of reperfusion injury. Antileukocyte antibodies, brain cooling and conditioned blood reperfusion are potential therapeutic strategies for lessening or eliminating reperfusion injury, and interventionalists may play a role in the future in using some of these therapies in combination with thrombolysis or embolectomy. The present review summarizes the mechanisms of reperfusion injury and focuses on the way each of those mechanisms can be evaluated by different MRI modalities. The potential therapeutic strategies are also discussed