Isolation and characterization of potent antifungal strains of the Streptomyces violaceusniger clade active against Candida albicans

Streptomyces strains were isolated from a sagebrush rhizosphere soil sample on humic acid vitamin (HV) agar and water yeast extract (WYE) agar supplemented with 1.5% (w/w) phenol as a selective medium. Acidic, neutral and alkaline pH conditions were also used in the isolation procedures. The phenol treatment reduced the numbers of both actinomycetes and non-actinomycetes on plates under all three pH conditions. From phenol-amended HV and WYE agar, 16 strains were isolated in pure culture; 14 from the HV agar and two from the WYE agar. All the isolates were tested for their antifungal activities against Pythium ultimum P8 and five yeast strains, including two antifungal drug-resistant Candida albicans strains. HV isolates that showed broad-spectrum antifungal antibiotic activities were all found to be members of the Streptomyces violaceusniger clade, while those that did not were non-clade members. The phenol treatment was not selective for S. violaceusniger clade members. Therefore, we tested the spores of both S. violaceusniger clade and non-clade members using two biocides, phenol and hydrogen peroxide, as selection agents. Spores of non-clade members, such as S. coelicolor M145 and S. lividans TK 21, survived these two biocides just as well as S. violaceusniger clade members. Thus, in our hands, biocide resistance was not S. violaceusniger clade specific as previously reported. However, isolates showing broad-spectrum antifungal and antiyeast activity were all members of the clade. We conclude that screening of isolates for broad-spectrum antifungal/antiyeast activity is the preferred method of isolating S. violaceusniger clade strains rather than biocide-based selection. Phylogenetic analysis of the phenol-resistant isolates revealed that the HV isolates that exhibited broad-spectrum antifungal antibiotic activity were all clustered and closely related to the S. violaceusniger clade, while the isolates that did not exhibit antifungal antibiotic activity were all non-clade members

Human papillomavirus (HPV) screening and cervical cancer burden. A Brazilian perspective

This review tackles the issues related to disease burden caused by cervical cancer (CC) and its precursor (CIN) lesions in Brazil. A special focus is given to new technologies with potential to interfere with the development of CC by reducing the high-risk human papillomavirus (hr-HPV)-induced lesions that remain a major public health burden in all developing countries where organized screening programs do not exist. Globally, 85 % of all incident CC and 50 % of CC deaths occur in the developing countries. Unfortunately, most regions of Brazil still demonstrate high mortality rates, ranking CC as the second most common cancer among Brazilian women. Recently, CC screening programs have been tailored in the country to enable early detection of CC precursor lesions and thereby reduce cancer mortality. A combination of HPV testing with liquid-based cytology (LBC) seems to be a promising new approach in CC screening, with high expectation to offer an adequate control of CC burden in this country

A practitioner's guide to Bayesian estimation of discrete choice dynamic programming models

This paper provides a step-by-step guide to estimating infinite horizon discrete choice dynamic programming (DDP) models using a new Bayesian estimation algorithm (Imai et al., Econometrica 77:1865–1899, 2009a) (IJC). In the conventional nested fixed point algorithm, most of the information obtained in the past iterations remains unused in the current iteration. In contrast, the IJC algorithm extensively uses the computational results obtained from the past iterations to help solve the DDP model at the current iterated parameter values. Consequently, it has the potential to significantly alleviate the computational burden of estimating DDP models. To illustrate this new estimation method, we use a simple dynamic store choice model where stores offer “frequent-buyer” type rewards programs. Our Monte Carlo results demonstrate that the IJC method is able to recover the true parameter values of this model quite precisely. We also show that the IJC method could reduce the estimation time significantly when estimating DDP models with unobserved heterogeneity, especially when the discount factor is close to 1

Altered Error Processing following Vascular Thalamic Damage: Evidence from an Antisaccade Task

Event-related potentials (ERP) research has identified a negative deflection within about 100 to 150 ms after an erroneous response – the error-related negativity (ERN) - as a correlate of awareness-independent error processing. The short latency suggests an internal error monitoring system acting rapidly based on central information such as an efference copy signal. Studies on monkeys and humans have identified the thalamus as an important relay station for efference copy signals of ongoing saccades. The present study investigated error processing on an antisaccade task with ERPs in six patients with focal vascular damage to the thalamus and 28 control subjects. ERN amplitudes were significantly reduced in the patients, with the strongest ERN attenuation being observed in two patients with right mediodorsal and ventrolateral and bilateral ventrolateral damage, respectively. Although the number of errors was significantly higher in the thalamic lesion patients, the degree of ERN attenuation did not correlate with the error rate in the patients. The present data underline the role of the thalamus for the online monitoring of saccadic eye movements, albeit not providing unequivocal evidence in favour of an exclusive role of a particular thalamic site being involved in performance monitoring. By relaying saccade-related efference copy signals, the thalamus appears to enable fast error processing. Furthermore early error processing based on internal information may contribute to error awareness which was reduced in the patients

Rasch model analysis of the Depression, Anxiety and Stress Scales (DASS)

<p>Abstract</p> <p>Background</p> <p>There is a growing awareness of the need for easily administered, psychometrically sound screening tools to identify individuals with elevated levels of psychological distress. Although support has been found for the psychometric properties of the Depression, Anxiety and Stress Scales (DASS) using classical test theory approaches it has not been subjected to Rasch analysis. The aim of this study was to use Rasch analysis to assess the psychometric properties of the DASS-21 scales, using two different administration modes.</p> <p>Methods</p> <p>The DASS-21 was administered to 420 participants with half the sample responding to a web-based version and the other half completing a traditional pencil-and-paper version. Conformity of DASS-21 scales to a Rasch partial credit model was assessed using the RUMM2020 software.</p> <p>Results</p> <p>To achieve adequate model fit it was necessary to remove one item from each of the DASS-21 subscales. The reduced scales showed adequate internal consistency reliability, unidimensionality and freedom from differential item functioning for sex, age and mode of administration. Analysis of all DASS-21 items combined did not support its use as a measure of general psychological distress. A scale combining the anxiety and stress items showed satisfactory fit to the Rasch model after removal of three items.</p> <p>Conclusion</p> <p>The results provide support for the measurement properties, internal consistency reliability, and unidimensionality of three slightly modified DASS-21 scales, across two different administration methods. The further use of Rasch analysis on the DASS-21 in larger and broader samples is recommended to confirm the findings of the current study.</p

SPR imaging biosensor for the 20S proteasome: sensor development and application to measurement of proteasomes in human blood plasma

The 20S proteasome is a multicatalytic enzyme complex responsible for intracellular protein degradation in mammalian cells. Its antigen level or enzymatic activity in blood plasma are potentially useful markers for various malignant and nonmalignant diseases. We have developed a method for highly selective determination of the 20S proteasome using a Surface Plasmon Resonance Imaging (SPRI) technique. It is based on the highly selective interaction between the proteasome’s catalytic β5 subunit and immobilized inhibitors (the synthetic peptide PSI and epoxomicin). Inhibitor concentration and pH were optimized. Analytical responses, linear ranges, accuracy, precision and interferences were investigated. Biosensors based on either PSI and epoxomicin were found to be suitable for quantitative determination of the proteasome, with a precision of ±10% for each, and recoveries of 102% and 113%, respectively, and with little interference by albumin, trypsin, chymotrypsin, cathepsin B and papain. The proteasome also was determined in plasma of healthy subjects and of patients suffering from acute leukemia. Both biosensors gave comparable results (2860 ng·mL-1 on average for control, and 42300 ng·mL-1 on average for leukemia patients)

Data-driven approach for creating synthetic electronic medical records

<p>Abstract</p> <p>Background</p> <p>New algorithms for disease outbreak detection are being developed to take advantage of full electronic medical records (EMRs) that contain a wealth of patient information. However, due to privacy concerns, even anonymized EMRs cannot be shared among researchers, resulting in great difficulty in comparing the effectiveness of these algorithms. To bridge the gap between novel bio-surveillance algorithms operating on full EMRs and the lack of non-identifiable EMR data, a method for generating complete and synthetic EMRs was developed.</p> <p>Methods</p> <p>This paper describes a novel methodology for generating complete synthetic EMRs both for an outbreak illness of interest (tularemia) and for background records. The method developed has three major steps: 1) synthetic patient identity and basic information generation; 2) identification of care patterns that the synthetic patients would receive based on the information present in real EMR data for similar health problems; 3) adaptation of these care patterns to the synthetic patient population.</p> <p>Results</p> <p>We generated EMRs, including visit records, clinical activity, laboratory orders/results and radiology orders/results for 203 synthetic tularemia outbreak patients. Validation of the records by a medical expert revealed problems in 19% of the records; these were subsequently corrected. We also generated background EMRs for over 3000 patients in the 4-11 yr age group. Validation of those records by a medical expert revealed problems in fewer than 3% of these background patient EMRs and the errors were subsequently rectified.</p> <p>Conclusions</p> <p>A data-driven method was developed for generating fully synthetic EMRs. The method is general and can be applied to any data set that has similar data elements (such as laboratory and radiology orders and results, clinical activity, prescription orders). The pilot synthetic outbreak records were for tularemia but our approach may be adapted to other infectious diseases. The pilot synthetic background records were in the 4-11 year old age group. The adaptations that must be made to the algorithms to produce synthetic background EMRs for other age groups are indicated.</p

Performance of the CMS Cathode Strip Chambers with Cosmic Rays

The Cathode Strip Chambers (CSCs) constitute the primary muon tracking device in the CMS endcaps. Their performance has been evaluated using data taken during a cosmic ray run in fall 2008. Measured noise levels are low, with the number of noisy channels well below 1%. Coordinate resolution was measured for all types of chambers, and fall in the range 47 microns to 243 microns. The efficiencies for local charged track triggers, for hit and for segments reconstruction were measured, and are above 99%. The timing resolution per layer is approximately 5 ns

Implementation of 3 T Lactate-Edited 3D 1H MR Spectroscopic Imaging with Flyback Echo-Planar Readout for Gliomas Patients

The purpose of this study was to implement a new lactate-edited 3D 1H magnetic resonance spectroscopic imaging (MRSI) sequence at 3 T and demonstrate the feasibility of using this sequence for measuring lactate in patients with gliomas. A 3D PRESS MRSI sequence incorporating shortened, high bandwidth 180° pulses, new dual BASING lactate-editing pulses, high bandwidth very selective suppression (VSS) pulses and a flyback echo-planar readout was implemented at 3 T. Over-prescription factor of PRESS voxels was optimized using phantom to minimize chemical shift artifacts. The lactate-edited flyback sequence was compared with lactate-edited MRSI using conventional elliptical k-space sampling in a phantom and volunteers, and then applied to patients with gliomas. The results demonstrated the feasibility of detecting lactate within a short scan time of 9.5 min in both phantoms and patients. Over-prescription of voxels gave less chemical shift artifacts allowing detection of lactate on the majority of the selected volume. The normalized SNR of brain metabolites using the flyback encoding were comparable to the SNR of brain metabolites using conventional phase encoding MRSI. The specialized lactate-edited 3D MRSI sequence was able to detect lactate in brain tumor patients at 3 T. The implementation of this technique means that brain lactate can be evaluated in a routine clinical setting to study its potential as a marker for prognosis and response to therapy