Collagen Peptides in Urine: A New Promising Biomarker for the Detection of Colorectal Liver Metastases

Introduction

For both patients and the outpatient clinic the frequent follow-up visits after a resection of colorectal cancer (CRC) are time consuming and due to large patient numbers expensive. Therefore it is important to develop an effective non-invasive test for the detection of colorectal liver metastasis (CRLM) which could be used outside the hospital. The urine proteome is known to provide detailed information for monitoring changes in the physiology of humans. Urine collection is non-invasive and urine naturally occurring peptides (NOPs) have the advantage of being easily accessible without labour-intensive sample preparation. These advantages make it potentially useful for a quick and reliable application in clinical settings. In this study, we will focus on the identification and validation of urine NOPs to discriminate patients with CRLM from healthy controls.

Materials and Methods

Urine samples were collected from 24 patients with CRLM and 25 healthy controls. In the first part of the study, samples were measured with a nano liquid chromatography (LC) system (Thermo Fisher Scientific, Germaring, Germany) coupled on-line to a hybrid linear ion trap/Orbitrap mass spectrometer (LTQ-Orbitrap-XL, Thermo Fisher Scientific, Bremen, Germany). A discovery set was used to construct the model and consecutively the validation set, being independent from the discovery set, to check the acquired model. From the peptides which were selected, multiple reaction monitoring (MRM''s) were developed on a UPLC-MS/MS system.

Results

Seven peptides were selected and applied in a discriminant analysis a sensitivity of 84.6% and a specificity of 92.3% were established (Canonical correlation:0.797, Eigenvalue:1.744, F:4.49, p:0.005). The peptides AGPP(-OH)GEAGKP(-OH)GEQGVP(-OH)GDLGA P(-OH)GP and KGNSGEP(-OH)GAPGSKGDTGAKGEP(-OH)GPVG were selected for further quantitative analysis which showed a sensitivity of 88% and a specificity of 88%.

Conclusion

Urine proteomic analysis revealed two very promising peptides, both part from collagen type 1, AGPP(-OH)GEAGKP(-OH)GEQGVP(-OH)GDLGAP(-OH)GP and KGNSGEP(-OH)GAPGSKGDTGAKGEP(-OH)GPVG which could detect CRLM in a non-invasive manner.     

Structural basis for RNA-genome recognition during bacteriophage Qβ replication

Upon infection of Escherichia coli by bacteriophage Qβ, the virus-encoded β-subunit recruits host translation elongation factors EF-Tu and EF-Ts and ribosomal protein S1 to form the Qβ replicase holoenzyme complex, which is responsible for amplifying the Qβ (+)-RNA genome. Here, we use X-ray crystallography, NMR spectroscopy, as well as sequence conservation, surface electrostatic potential and mutational analyses to decipher the roles of the β-subunit and the first two oligonucleotide-oligosaccharide-binding domains of S1 (OB_1–2) in the recognition of Qβ (+)-RNA by the Qβ replicase complex. We show how three basic residues of the β subunit form a patch located adjacent to the OB₂ domain, and use NMR spectroscopy to demonstrate for the first time that OB₂ is able to interact with RNA. Neutralization of the basic residues by mutagenesis results in a loss of both the phage infectivity in vivo and the ability of Qβ replicase to amplify the genomic RNA in vitro. In contrast, replication of smaller replicable RNAs is not affected. Taken together, our data suggest that the β-subunit and protein S1 cooperatively bind the (+)-stranded Qβ genome during replication initiation and provide a foundation for understanding template discrimination during replication initiation.     

Energy-dispersive X-ray fluorescence spectrometry as a tool for zinc, iron and selenium analysis in whole grain wheat

Background and aims

Crop biofortification programs require fast, accurate and inexpensive methods of identifying nutrient dense genotypes. This study investigated energy-dispersive X-ray fluorescence spectrometry (EDXRF) for the measurement of zinc (Zn), iron (Fe) and selenium (Se) concentrations in whole grain wheat.

Methods

Grain samples were obtained from existing biofortification programs. Reference Zn, Fe and Se concentrations were obtained using inductively coupled plasma optical emission spectrometry (ICP-OES) and/or inductively coupled plasma mass spectrometry (ICP-MS). One set of 25 samples was used to calibrate for Zn (19–60?mg?kg^–1) and Fe (26–41?mg?kg^–1), with 25 further samples used to calibrate for Se (2–31?mg?kg^–1 ). Calibrations were validated using an additional 40–50 wheat samples.

Results

EDXRF limits of quantification (LOQ) were estimated as 7, 3 and 2?mg?kg^–1 for Zn, Fe, and Se, respectively. EDXRF results were highly correlated with ICP-OES or -MS values. Standard errors of EDXRF predictions were ±2.2?mg Zn kg^–1, ±2.6?mg Fe kg^–1, and ±1.5?mg Se kg^–1.

Conclusion

EDXRF offers a fast and economical method for the assessment of Zn, Fe and Se concentration in wheat biofortification programs.     

Design Pattern Mining Using Distributed Learning Automata and DNA Sequence Alignment

Context

Over the last decade, design patterns have been used extensively to generate reusable solutions to frequently encountered problems in software engineering and object oriented programming. A design pattern is a repeatable software design solution that provides a template for solving various instances of a general problem.

Objective

This paper describes a new method for pattern mining, isolating design patterns and relationship between them; and a related tool, DLA-DNA for all implemented pattern and all projects used for evaluation. DLA-DNA achieves acceptable precision and recall instead of other evaluated tools based on distributed learning automata (DLA) and deoxyribonucleic acid (DNA) sequences alignment.

Method

The proposed method mines structural design patterns in the object oriented source code and extracts the strong and weak relationships between them, enabling analyzers and programmers to determine the dependency rate of each object, component, and other section of the code for parameter passing and modular programming. The proposed model can detect design patterns better that available other tools those are Pinot, PTIDEJ and DPJF; and the strengths of their relationships.

Results

The result demonstrate that whenever the source code is build standard and non-standard, based on the design patterns, then the result of the proposed method is near to DPJF and better that Pinot and PTIDEJ. The proposed model is tested on the several source codes and is compared with other related models and available tools those the results show the precision and recall of the proposed method, averagely 20% and 9.6% are more than Pinot, 27% and 31% are more than PTIDEJ and 3.3% and 2% are more than DPJF respectively.

Conclusion

The primary idea of the proposed method is organized in two following steps: the first step, elemental design patterns are identified, while at the second step, is composed to recognize actual design patterns.     

CD64 and Group II Secretory Phospholipase A2 (sPLA2-IIA) as Biomarkers for Distinguishing Adult Sepsis and Bacterial Infections in the Emergency Department

Introduction

Early diagnosis of sepsis and bacterial infection is imperative as treatment relies on early antibiotic administration. There is a need to develop new biomarkers to detect patients with sepsis and bacterial infection as early as possible, thereby enabling prompt antibiotic treatment and improving the survival rate.

Methods

Fifty-one adult patients with suspected bacterial sepsis on admission to the Emergency Department (ED) of a teaching hospital were included into the study. All relevant cultures and serology tests were performed. Serum levels for Group II Secretory Phospholipase A2 (sPLA2-IIA) and CD64 were subsequently analyzed.

Results and Discussion

Sepsis was confirmed in 42 patients from a total of 51 recruited subjects. Twenty-one patients had culture-confirmed bacterial infections. Both biomarkers were shown to be good in distinguishing sepsis from non-sepsis groups. CD64 and sPLA2-IIA also demonstrated a strong correlation with early sepsis diagnosis in adults. The area under the curve (AUC) of both Receiver Operating Characteristic curves showed that sPLA2-IIA was better than CD64 (AUC = 0.93, 95% confidence interval (CI) = 0.83–0.97 and AUC = 0.88, 95% CI = 0.82–0.99, respectively). The optimum cutoff value was 2.13μg/l for sPLA2-IIA (sensitivity = 91%, specificity = 78%) and 45 antigen bound cell (abc) for CD64 (sensitivity = 81%, specificity = 89%). In diagnosing bacterial infections, sPLA2-IIA showed superiority over CD64 (AUC = 0.97, 95% CI = 0.85–0.96, and AUC = 0.95, 95% CI = 0.93–1.00, respectively). The optimum cutoff value for bacterial infection was 5.63μg/l for sPLA2-IIA (sensitivity = 94%, specificity = 94%) and 46abc for CD64 (sensitivity = 94%, specificity = 83%).

Conclusions

sPLA2-IIA showed superior performance in sepsis and bacterial infection diagnosis compared to CD64. sPLA2-IIA appears to be an excellent biomarker for sepsis screening and for diagnosing bacterial infections, whereas CD64 could be used for screening bacterial infections. Both biomarkers either alone or in combination with other markers may assist in decision making for early antimicrobial administration. We recommend incorporating sPLA2-IIA and CD64 into the diagnostic algorithm of sepsis in ED.     

Studies on ram acrosin. Isolation from spermatozoa, activation by cations and organic solvents, and influence of cations on its reaction with inhibitors

1. A simple method is given for isolating from ram spermatozoa a water-soluble form of acrosin (a trypsin-like enzyme) which is about 25% pure. It is free from an acrosin inhibitor which is located in the spermatozoa. 2. In the hydrolysis of N-alpha-benzoyl-l-arginine ethyl ester the degree of activation of acrosin by Ca(2+), and by some other cations, is dependent on the extent of contamination by the inhibitor. In 50mm-Tris-HCl buffer (pH8.2) activation by Ca(2+) did not exceed 40%, but acrosin that is partially inhibited may be activated by up to 300%: this is due to cation-mediated protection of acrosin against the inhibitor. 3. Increasing concentrations of buffers (e.g. Tris) also activate acrosin but at above certain buffer concentrations Ca(2+) no longer exerts an activating effect and may become inhibitory. Ca(2+) is also inhibitory when added to assay systems involving anionic buffers with chelating properties. This is due to a fall in pH. 4. The above results suggest reasons for conflicting conclusions in papers dealing with the effects of Ca(2+) on acrosin activity. 5. Inhibition of acrosin by the Kunitz pancreatic trypsin inhibitor is increased on addition of Ca(2+). Inhibitions of trypsin by the acrosin inhibitor and by the Kunitz inhibitor are insensitive to Ca(2+). 6. Like trypsin, acrosin is activated, up to 60%, by 2-methyl-propan-2-ol, dimethyl sulphoxide, and some other water-miscible solvents. Effects of cations and solvents tend to be additive and a common maximum acrosin activity can be achieved with various concentrations of solvent, salts and buffer in the assay system. Activation by solvents is increased when low concentrations of the acrosin inhibitor are present. 7. Activations of acrosin by salts and by solvents are more pronounced when the substrate is N-alpha-benzoyl-dl-arginine 2-naphthylamide. 8. K(m) values for ram acrosin (about 0.2mm) are much higher than those for trypsin, and k(cat.) values are slightly higher than those for trypsin. Considerations of the influences of ions and dimethyl sulphoxide on the activities and kinetic constants of acrosin and trypsin suggest that conformational changes are the factors mainly responsible for the reported activations of acrosin. 9. The following conclusions are reached. (a) Acrosin plays a role in the penetration of the sperm cell into the egg without becoming detached from the acrosomal membrane. (b) The enzyme is a peripheral membrane protein which may be classed as a cathepsin. (c) The susceptibility of the activity of soluble acrosin to cations and solvents points to a flexible molecule, i.e. one lacking conformational restraints imposed by association (presumably ionic) with the acrosomal membrane.