Motion of the Zinc Ions in Catalysis by a Dizinc Metallo-β-Lactamase

We report rapid-freeze-quench X-ray absorption spectroscopy of a dizinc metallo-β-lactamase (MβL) reaction intermediate. The Zn(II) ions in the dinuclear active site of the S. maltophilia Class B3 MβL move away from each other, by ∼0.3 Å after 10 ms of reaction with nitrocefin, from 3.4 to 3.7 Å. Together with our previous characterization of the resting enzyme and its nitrocefin product complex, where the Zn(II) ion separation relaxes to 3.6 Å, these data indicate a scissoring motion of the active site that accompanies the ring-opening step. The average Zn(II) coordination number of 4.5 in the resting enzyme appears to be maintained throughout the reaction with nitrocefin. This is the first direct structural information available on early stage dizinc metallo-β-lactamase catalysis

The Promise of Information and Communication Technology In Health Care: Extracting Value from the Chaos

Healthcare is an information business with expanding use of information and communication technologies (ICTs). Current ICT tools are immature, but a brighter future looms. We examine 7 areas of ICT in healthcare: electronic health records (EHRs), health information exchange (HIE), patient portals, telemedicine, social media, mobile devices and wearable sensors and monitors, and privacy and security. In each of these areas, we examine the current status and future promise, highlighting how each might reach its promise. Steps to better EHRs include a universal programming interface, universal patient identifiers, improved documentation and improved data analysis. HIEs require federal subsidies for sustainability and support from EHR vendors, targeting seamless sharing of EHR data. Patient portals must bring patients into the EHR with better design and training, greater provider engagement and leveraging HIEs. Telemedicine needs sustainable payment models, clear rules of engagement, quality measures and monitoring. Social media needs consensus on rules of engagement for providers, better data mining tools and approaches to counter disinformation. Mobile and wearable devices benefit from a universal programming interface, improved infrastructure, more rigorous research and integration with EHRs and HIEs. Laws for privacy and security need updating to match current technologies, and data stewards should share information on breaches and standardize best practices. ICT tools are evolving quickly in healthcare and require a rational and well-funded national agenda for development, use and assessment

Graphics for uncertainty

Graphical methods such as colour shading and animation, which are widely available, can be very effective in communicating uncertainty. In particular, the idea of a ‘density strip’ provides a conceptually simple representation of a distribution and this is explored in a variety of settings, including a comparison of means, regression and models for contingency tables. Animation is also a very useful device for exploring uncertainty and this is explored particularly in the context of flexible models, expressed in curves and surfaces whose structure is of particular interest. Animation can further provide a helpful mechanism for exploring data in several dimensions. This is explored in the simple but very important setting of spatiotemporal data

A Five-coordinate Metal Center in Co(II)-substituted VanX

In an effort to structurally probe the metal binding site in VanX, electronic absorption, EPR, and extended x-ray absorption fine structure (EXAFS) spectroscopic studies were conducted on Co(II)-substituted VanX. Electronic spectroscopy revealed the presence of Co(II) ligand field transitions that had molar absorptivities of ∼100 m–1 cm–1, which suggests that Co(II) is five-coordinate in Co(II)-substituted VanX. Low temperature EPR spectra of Co(II)-substituted VanX were simulated using spin Hamiltonian parameters of M = |±½〉, E/D = 0.14, greal(x,y) = 2.37, and grealS(z) = 2.03. These parameters lead to the prediction that Co(II) in the enzyme is five-coordinate and that there may be at least one solvent-derived ligand. Single scattering fits of EXAFS data indicate that the metal ions in both native Zn(II)-containing and Co(II)-substituted VanX have the same coordination number and that the metal ions are coordinated by 5 nitrogen/oxygen ligands at ∼ 2.0 Å. These data demonstrate that Co(II) (and Zn(II) from EXAFS studies) is five-coordinate in VanX in contrast to previous crystallographic studies (Bussiere, D. E., Pratt, S. D., Katz, L., Severin, J. M., Holzman, T., and Park, C. H. (1998) Mol. Cell 2, 75–84). These spectroscopic studies also demonstrate that the metal ion in Co(II)-substituted VanX when complexed with a phosphinate analog of substrate d-Ala-d-Ala is also five-coordinate

Differential Binding of Co(II) and Zn(II) to Metallo-β-Lactamase Bla2 from \u3cem\u3eBacillus anthracis\u3c/em\u3e

In an effort to probe the structure, mechanism, and biochemical properties of metallo-β-lactamase Bla2 from Bacillus anthracis, the enzyme was overexpressed, purified, and characterized. Metal analyses demonstrated that recombinant Bla2 tightly binds 1 equiv of Zn(II). Steady-state kinetic studies showed that mono-Zn(II) Bla2 (1Zn-Bla2) is active, while di-Zn(II) Bla2 (ZnZn-Bla2) was unstable. Catalytically, 1Zn-Bla2 behaves like the related enzymes CcrA and L1. In contrast, di-Co(II) Bla2 (CoCo-Bla2) is substantially more active than the mono-Co(II) analogue. Rapid kinetics and UV−vis, 1H NMR, EPR, and EXAFS spectroscopic studies show that Co(II) binding to Bla2 is distributed, while EXAFS shows that Zn(II) binding is sequential. To our knowledge, this is the first documented example of a Zn enzyme that binds Co(II) and Zn(II) via distinct mechanisms, underscoring the need to demonstrate transferability when extrapolating results on Co(II)-substituted proteins to the native Zn(II)-containing forms

Structure and Metal Binding Properties of ZnuA, a Periplasmic Zinc Transporter from \u3cem\u3eEscherichia coli\u3c/em\u3e

ZnuA is the periplasmic Zn2+-binding protein associated with the high-affinity ATP-binding cassette ZnuABC transporter from Escherichia coli. Although several structures of ZnuA and its homologs have been determined, details regarding metal ion stoichiometry, affinity, and specificity as well as the mechanism of metal uptake and transfer remain unclear. The crystal structures of E. coli ZnuA (Eco-ZnuA) in the apo, Zn2+-bound, and Co2+-bound forms have been determined. ZnZnuA binds at least two metal ions. The first, observed previously in other structures, is coordinated tetrahedrally by Glu59, His60, His143, and His207. Replacement of Zn2+ with Co2+ results in almost identical coordination geometry at this site. The second metal binding site involves His224 and several yet to be identified residues from the His-rich loop that is unique to Zn2+ periplasmic metal binding receptors. Electron paramagnetic resonance and X-ray absorption spectroscopic data on CoZnuA provide additional insight into possible residues involved in this second site. The second site is also detected by metal analysis and circular dichroism (CD) titrations. Eco-ZnuA binds Zn2+ (estimated K d \u3c 20 nM), Co2+, Ni2+, Cu2+, Cu+, and Cd2+, but not Mn2+. Finally, conformational changes upon metal binding observed in the crystal structures together with fluorescence and CD data indicate that only Zn2+ substantially stabilizes ZnuA and might facilitate recognition of ZnuB and subsequent metal transfer

Physician-estimated disease severity in patients with chronic heart or lung disease: a cross-sectional analysis

BACKGROUND: We evaluated how well physicians' global estimates of disease severity correspond to more specific physician-rated disease variables as well as patients' self-rated health and other patient variables. METHODS: We analyzed baseline data from 1662 primary care patients with chronic cardiac or pulmonary disease who were enrolled in a longitudinal study of health-related quality of life (HRQoL). Each patient's primary physician rated overall disease severity, estimated the two-year risk of hospitalization and mortality, and reported the use of disease-specific medications, tests, and subspecialty referrals. Patient variables included sociodemographic characteristics, psychosocial factors, self-rated health, and both generic and disease-specific HRQoL. RESULTS: Physicians rated 40% of their patients "about average", 30% "worse", and 30% "better" than the typical patient seen with the specific target disorder. The physician's global estimate of disease severity was strongly associated (P < 0.001) with each of the five more specific elements of physician-rated disease severity, but only marginally associated with patient self-rated health. Multivariable regression identified a set of patient variables that explained 16.4% of the variance in physician-rated disease severity. CONCLUSION: Physicians' global ratings may provide disease severity and prognostic information unique from and complementary to patient self-rated health and HRQoL measures. The elements influencing physician-rated disease severity and its predictive validity for clinical outcomes warrant prospective investigation

Probabilistic classification of acute myocardial infarction from multiple cardiac markers

Logistic regression and Gaussian mixture model (GMM) classifiers have been trained to estimate the probability of acute myocardial infarction (AMI) in patients based upon the concentrations of a panel of cardiac markers. The panel consists of two new markers, fatty acid binding protein (FABP) and glycogen phosphorylase BB (GPBB), in addition to the traditional cardiac troponin I (cTnI), creatine kinase MB (CKMB) and myoglobin. The effect of using principal component analysis (PCA) and Fisher discriminant analysis (FDA) to preprocess the marker concentrations was also investigated. The need for classifiers to give an accurate estimate of the probability of AMI is argued and three categories of performance measure are described, namely discriminatory ability, sharpness, and reliability. Numerical performance measures for each category are given and applied. The optimum classifier, based solely upon the samples take on admission, was the logistic regression classifier using FDA preprocessing. This gave an accuracy of 0.85 (95% confidence interval: 0.78–0.91) and a normalised Brier score of 0.89. When samples at both admission and a further time, 1–6 h later, were included, the performance increased significantly, showing that logistic regression classifiers can indeed use the information from the five cardiac markers to accurately and reliably estimate the probability AMI