Biochemical Properties and Crystal Structure of a β-Phenylalanine Aminotransferase from Variovorax paradoxus

By selective enrichment, we isolated a bacterium that can use β-phenylalanine as a sole nitrogen source. It was identified by 16S rRNA gene sequencing as a strain of Variovorax paradoxus. Enzyme assays revealed an aminotransferase activity. Partial genome sequencing and screening of a cosmid DNA library resulted in the identification of a 1,302-bp aminotransferase gene, which encodes a 46,416-Da protein. The gene was cloned and overexpressed in Escherichia coli. The recombinant enzyme was purified and showed a specific activity of 17.5 U mg⁻¹ for (S)-β-phenylalanine at 30°C and 33 U mg⁻¹ at the optimum temperature of 55°C. The β-specific aminotransferase exhibits a broad substrate range, accepting ortho-, meta-, and para-substituted β-phenylalanine derivatives as amino donors and 2-oxoglutarate and pyruvate as amino acceptors. The enzyme is highly enantioselective toward (S)-β-phenylalanine (enantioselectivity [E], >100) and derivatives thereof with different substituents on the phenyl ring, allowing the kinetic resolution of various racemic β-amino acids to yield (R)-β-amino acids with >95% enantiomeric excess (ee). The crystal structures of the holoenzyme and of the enzyme in complex with the inhibitor 2-aminooxyacetate revealed structural similarity to the β-phenylalanine aminotransferase from Mesorhizobium sp. strain LUK. The crystal structure was used to rationalize the stereo- and regioselectivity of V. paradoxus aminotransferase and to define a sequence motif with which new aromatic β-amino acid-converting aminotransferases may be identified.     

Noninvasive Assessment of Losartan-Induced Increase in Functional Microvasculature and Drug Delivery in Pancreatic Ductal Adenocarcinoma

PURPOSE: Losartan, an angiotensin II receptor blocker, can reduce desmoplasia and enhance drug delivery and efficacy through improving interstitial transport and vascular perfusion in pancreatic ductal adenocarcinoma (PDAC) models in mice. The purpose of this study was to determine whether magnetic resonance imaging (MRI) of magnetic iron oxide nanoparticles (MNPs) and micro–positron emission tomography (PET) measurements could respectively detect improvements in tumor vascular parameters and drug uptake in orthotopic PDAC in mice treated with losartan. METHOD AND MATERIALS: All experiments were approved by the local Institutional Animal Care and Use Committee. FVB mice with orthotopic PDAC were treated daily with an i.p. injection of losartan (70 mg/kg) or saline (control vehicle) for 5 days. In order to calculate the fractional blood volume, vessel size index, and vessel density index, MRI was performed at 4.7 T following the injection of 3 mg/kg iron ferumoxytol (i.v.). Dynamic PET images were also acquired for 60 minutes using an ¹⁸F-5FU tracer dose of 200 μCi and analyzed for time activity curves normalized to muscle. Statistical analyses compared both cohorts using an unpaired two-tailed t test. RESULTS: In comparison to the control treatment, the losartan administration significantly increased the fractional blood volume (mean ± SEM) [12.1 ± 1.7 (n = 19) vs 6.7 ± 1.1 (n = 20); P < .02] and vessel size index (128.2 ± 35.6 vs 57.5 ± 18; P < .05). Losartan also induced a significant increase in the intratumoral uptake of ¹⁸F-5FU by 53% (P < .0001). CONCLUSION: MRI using FDA-approved MNPs provides a noninvasive, translatable means of assaying microvascular parameters induced by losartan in pancreatic cancer. PET measurements demonstrated that losartan significantly increased the uptake of ¹⁸F-5FU.     

Adjustment uncertainty in effect estimation

Often there is substantial uncertainty in the selection of confounderswhen estimating the association between an exposure and health.We define this type of uncertainty as `adjustment uncertainty'.We propose a general statistical framework for handling adjustmentuncertainty in exposure effect estimation for a large numberof confounders, we describe a specific implementation, and wedevelop associated visualization tools. Theoretical resultsand simulation studies show that the proposed method providesconsistent estimators of the exposure effect and its variance.We also show that, when the goal is to estimate an exposureeffect accounting for adjustment uncertainty, Bayesian modelaveraging with posterior model probabilities approximated usinginformation criteria can fail to estimate the exposure effectand can over- or underestimate its variance. We compare ourapproach to Bayesian model averaging using time series dataon levels of fine particulate matter and mortality.     

Organic osmolyte permeabilities of the malaria-induced anion conductances in human erythrocytes

Infection of human erythrocytes with the malaria parasite Plasmodium falciparum induces new permeability pathways (NPPs) in the host cell membrane. Isotopic flux measurements demonstrated that the NPP are permeable to a wide variety of molecules, thus allowing uptake of nutrients and release of waste products. Recent patch-clamp recordings demonstrated the infection-induced up-regulation of an inwardly and an outwardly rectifying Cl(-) conductance. The present experiments have been performed to explore the sensitivity to cell volume and the organic osmolyte permeability of the two conductances. It is shown that the outward rectifier has a high relative lactate permeability (P(lactate)/P(Cl) = 0.4). Sucrose inhibited the outward-rectifier and abolished the infection-induced hemolysis in isosmotic sorbitol solution but had no or little effect on the inward-rectifier. Furosemide and NPPB blocked the outward-rectifying lactate current and the sorbitol hemolysis with IC(50)s in the range of 0.1 and 1 microM, respectively. In contrast, the IC(50)s of NPPB and furosemide for the inward-rectifying current were >10 microM. Osmotic cell-shrinkage inhibited the inwardly but not the outwardly rectifying conductance. In conclusion, the parasite-induced outwardly-rectifying anion conductance allows permeation of lactate and neutral carbohydrates, whereas the inward rectifier seems largely impermeable to organic solutes. All together, these data should help to resolve ongoing controversy regarding the number of unique channels that exist in P. falciparum-infected erythrocytes.     

MiRNAs roles in the diagnosis,prognosis and treatment of colorectal cancer

ABSTRACT

Introduction: The liver is the main location for metastasization in stage IV colorectal cancers.

Areas covered: This review intends to comprehensively present the most important studies conducted in the past few years concerning the role of miRNAs in colorectal cancer liver metastases, trying to clarify some aspects regarding tumor biology and favorite liver metastasization site.

Expert commentary: Recent advances in tissue and serum RNA extraction has considerably improved the field of microRNAs studies. These molecules known to play a crucial role in the metastatic stage indicate a starting point in the development of clinical biomarkers with a possible role in the stratification of high-risk patients for adequate treatment.     

Estimating Energy Expenditure from Heart Rate in Older Adults: A Case for Calibration

Background

Accurate measurement of free-living energy expenditure is vital to understanding changes in energy metabolism with aging. The efficacy of heart rate as a surrogate for energy expenditure is rooted in the assumption of a linear function between heart rate and energy expenditure, but its validity and reliability in older adults remains unclear.

Objective

To assess the validity and reliability of the linear function between heart rate and energy expenditure in older adults using different levels of calibration.

Design

Heart rate and energy expenditure were assessed across five levels of exertion in 290 adults participating in the Baltimore Longitudinal Study of Aging. Correlation and random effects regression analyses assessed the linearity of the relationship between heart rate and energy expenditure and cross-validation models assessed predictive performance.

Results

Heart rate and energy expenditure were highly correlated (r = 0.98) and linear regardless of age or sex. Intra-person variability was low but inter-person variability was high, with substantial heterogeneity of the random intercept (s.d. = 0.372) despite similar slopes. Cross-validation models indicated individual calibration data substantially improves accuracy predictions of energy expenditure from heart rate, reducing the potential for considerable measurement bias. Although using five calibration measures provided the greatest reduction in the standard deviation of prediction errors (1.08 kcals/min), substantial improvement was also noted with two (0.75 kcals/min).

Conclusion

These findings indicate standard regression equations may be used to make population-level inferences when estimating energy expenditure from heart rate in older adults but caution should be exercised when making inferences at the individual level without proper calibration.     

A Comparison of Supervised Machine Learning Algorithms and Feature Vectors for MS Lesion Segmentation Using Multimodal Structural MRI

Machine learning is a popular method for mining and analyzing large collections of medical data. We focus on a particular problem from medical research, supervised multiple sclerosis (MS) lesion segmentation in structural magnetic resonance imaging (MRI). We examine the extent to which the choice of machine learning or classification algorithm and feature extraction function impacts the performance of lesion segmentation methods. As quantitative measures derived from structural MRI are important clinical tools for research into the pathophysiology and natural history of MS, the development of automated lesion segmentation methods is an active research field. Yet, little is known about what drives performance of these methods. We evaluate the performance of automated MS lesion segmentation methods, which consist of a supervised classification algorithm composed with a feature extraction function. These feature extraction functions act on the observed T1-weighted (T1-w), T2-weighted (T2-w) and fluid-attenuated inversion recovery (FLAIR) MRI voxel intensities. Each MRI study has a manual lesion segmentation that we use to train and validate the supervised classification algorithms. Our main finding is that the differences in predictive performance are due more to differences in the feature vectors, rather than the machine learning or classification algorithms. Features that incorporate information from neighboring voxels in the brain were found to increase performance substantially. For lesion segmentation, we conclude that it is better to use simple, interpretable, and fast algorithms, such as logistic regression, linear discriminant analysis, and quadratic discriminant analysis, and to develop the features to improve performance.     

microRNAs Expression as Novel Genetic Biomarker for Early Prediction and Continuous Monitoring in Pulmonary Cancer

One of the main causes of death in the world is lung cancer. According to the World Health Organization, the annual incidence of lung cancer increases significantly. Moreover, lung cancer accounts for one of the highest mortality rates, mainly due to late detection. Numerous studies have been conducted in order to identify new biomarkers for early diagnosis and for monitoring and evaluation of lung cancer stages. An ideal biomarker candidate is represented by the analysis of microRNAs expression. In this paper, we want to summarize microRNAs expressions in lung cancer. We also want to present the expression of microRNAs depending on the evolution of lung cancer. For this study, we analyzed the studies available in scientific databases, such as PubMed and Scopus. The studies were selected using the search keywords “microRNAs expression,” “lung cancer,” and “genetic biomarkers.” The most significant articles were selected for the study, following rigorous analysis. To evaluate and monitor lung cancer, the expression of microRNAs may be used successfully due to increased specificity and selectivity. However, further studies are needed on the assignment and validation of microRNAs for each type of lung cancer, respectively, for each stage of evolution.