Aim An in silico pathway analysis was performed in an attempt to identify new biomarkers for cervical carcinoma. Methods Three publicly available Affymetrix gene expression data sets (GSE5787, GSE7803, GSE9750) were retrieved, vouching for a total 9 cervical cancer cell lines, 39 normal cervical samples, 7 CIN3 samples and 111 cervical cancer samples. An Agilent data set (GSE7410; 5 normal cervical samples, 35 samples from invasive cervical cancer) was selected as a validation set. Predication analysis of microarrays was performed in the Affymetrix sets to identify cervical cancer biomarkers. We compared the lists of differentially expressed genes between normal and CIN3 samples on the one hand (n=1923) and between CIN3 and invasive cancer samples on the other hand (n=628).
levels were determined by immunoturbidimetric, creatinine levels were determined by enzyme- Trinder method traceable from the National Institute of Standards and Technology (NIST) and urea (plasma and urine) by UV enzymatic test (urease). AP and GGT plasma and urine activity were determined by the kinetic method (Bowers and Mc Comb modified and Szasz modified, respectively). Albumin plasma levels were determined by the colorimetric method (Bromocresol green) and urine levels by the immunoturbidimetric method. The urinary levels of each biomarker were corrected by creatinine urinary levels. Plasma/urine ratio of biomarkers was also calculated.
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Dilated Cardiomyopathy (DCM) is a complex heart disease affecting the heart musculature and vasculature, involving one or several underlying pathophysi- ological mechanisms. Identifying potential biomarkers for dilated cardio- myopathy is a challenge owing to various aetiologies involved. Studying the biomarkers involved in DCM will ultimately give a better insight about which pathophysiological pathways are involved in the onset of the disease. Owing to its multifactorial aetiologies, response to treatment is usually poor. If we can find the exact underlying causes, a better treatment approach could be implemented. One way to obtain better insight of DCM is to study the bio- markers released. Through biomarkers, we can know which underlying mechanisms are involved. Biomarkers can provide us with clinical informa- tion such as diagnostic, prognostic, risk stratification as well as response to treatment. Underlying mechanisms such as inflammation, stress/strain, myo- cyte injury, matrix remodelling, oxidative stress, neurohormones involve- ment, among others, can contribute to the onset of DCM. Different mecha- nisms will yield different biomarkers. So it would be wise to classify those biomarkers involving in DCM based on their respective pathogenesis. More- over, most importantly is to be able to make use of the information that bio- marker pertains. However, specificity of those biomarkers poses a problem. One way of making these biomarkers clinically useful is to make use of a bio- marker modelling score system.
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Sepsis in leukaemic patients is a leading killer of both adult and pediatric patients, and delays in recognition and treatment significantly increase the risk of morbidity and mortality. The concept of early detection serves as the foundation of the search for clinically viable indicators of severe sepsis – hence the interest in sepsis biomarkers. Biomarker is defined as the biological parameter associated with the presence and severity of specific disease states.
bloodstream. Consistent with this hypothesis was the demonstration that exosomes, which carry miRNAs out- side cells, are able to cross the blood-brain barrier . In addition, disruption of the blood-brain barrier has been shown after cerebral ischemia, which may facilitate the re- lease of neuron-derived miRNAs into the bloodstream . Sheinerman and colleagues  identified brain- enriched miRNAs in the blood of patients with mild cognitive impairment, an early stage of multiple neurode- generative diseases. Thus, brain-derived miRNAs present in the bloodstream after cardiac arrest may indicate neurological damage. Since the extent of neurological damage is a critical determinant of post-cardiac arrest re- covery, it is expected that circulating miRNAs may have an interesting prognostic value in this setting. A recent study from our group showing that brain-enriched miR- 124 is associated with neurological outcome after cardiac arrest confirmed this assumption . In future studies, the added value of this novel category of biomarkers over existing tools will have to be determined. Also, the sensi- tivity and specificity of miRNAs, as well as their usefulness for early prediction, will have to outperform current elec- trophysiological and neuroimaging tools. Finally, the techniques used to quantify miRNAs, which are still time-consuming, will have to be improved, both in terms of reproducibility, rapidity, cost, and standardization.
In recent years, the discovery of non-coding RNAs (ncRNAs) has provided new tools for the understanding of cancer biology . ncRNAs are functional transcripts that do not code for proteins, but indeed play a major role in regulating gene expression at virtually all levels. Among these, small nucleolar RNAs (snoRNAs) are molecules of 60–300 nucleotides in length that function as guide RNAs for the post-transcriptional methylation and/or pseu- douridylation of ribosomal RNAs. Unlike snoRNAs, small Cajal body-specific RNAs (scaRNAs) accumulate within the Cajal bodies (i.e. conserved subnuclear organelles that are present in the nucleoplasm) and can guide both post- transcriptional modifications of small nuclear RNAs. sno/ scaRNAs can also target other RNAs including mRNAs. However, a subgroup of so-called “orphan” sno/scaRNAs exists whose function remain to be clarified. Notably, in vertebrates most sno/scaRNAs reside in the introns of protein-coding host genes and are processed out of the ex- cised introns .
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The following characteristics argue for the potential of EMVs as a promising source for new biomarkers: (1) EMVs are identifiable and isolatable on the basis of typical intrinsic and well-defined properties, such as phosphatidylserine content, size, sedimentation behavior; (2) EMVs are specific with regard to the expression of cell-lineage markers as well as the overall molecular composition and patterns of their luminal and surface contents; (3) EMV signatures critically depend on the stimulation and micro-environment of the donor cells; (4) EMVs are initial and rapid “responders” since they are released early during stimulatory or micro-environmental changes and in the pathogenic cascade of a disease; (5) EMVs are noninvasive since they are detectable in many body fluids; (6) EMVs are “translatable” since their release is not limited to one cell type or one species; and (7) EMVs act as vectors since they transport and protect biological messages, ie, mRNAs, microRNAs, proteins, and phospholipids, which are normally confined to cells/tissues.
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The sputum block preparation is feasible and non-invasive, can be useful to identify new biomarkers of exposure or susceptibility in patients with lung pathology to enhance the understanding of airways changes due to different etiological factors and may be useful to find new biomarkers in order to assess and monitor early lung damage initiated by inducers in order to prevent the progression of lung disease.
Rheumatoid arthritis (RA) is a common autoimmune disease in which a heterogeneous course and different pathogenic mechanisms are implicated in chronic inflammation and joint destruction. Despite the diagnostic contribution of anti-citrullinated protein/peptide antibodies (ACPAs) and rheumatoid factors, about one-third of RA patients remain seronegative. ACPAs belong to a heterogeneous family of autoantibodies targeting citrullinated proteins, including myelin-basic protein, several histone proteins, filaggrin and fibrin, fibrinogen or vimentin. In addition to ACPAs, antibodies directed against other post-translationally modified-carbamylated proteins (anti-CarP) were detected in up to 30% of ACPA-negative patients. Using phage display technology, further autoantibodies were recently discovered as candidate biomarkers for seronegative RA patients. Furthermore, in clinical practice, ultrasound may reveal subclinical synovitis and radiographically undetected bone erosions. To improve diagnostic certainty in undifferentiated arthritis and seronegative patients, ultrasound imaging and several new biomarkers may help to identify at risk patients and those with early disease. In this commentary we summarize recent advances in joint ultrasound and future potential of serological biomarkers to improve diagnosis of RA.
In Saudi Arabia AFP considered the main serum marker for diagnostic Hepatocellular carcinoma (HCC), due to the continuous detection of HCC in Saudi Arabia, using new biomarkers for early surveillance are essential to control in prevalence of HCC. The present study depend oncompare the significant between serum and mRNA Glypican-3 (GPC-3) as newly identified diagnostic and prognostic biomarkers for HCC between study cases.And combined sensitivity of AFP and GPC-3. Three hundred study cases, divided into: 250 blood samples were 145 samples from HCC , 105 samples from chronic liver cirrhosis (CLC) and 50normal controls were investigated for serum GPC-3 (sGPC-3) bySandwich ELISA. Glypican-3 mRNA from whole blood cells was detected by quantitative RT-PCR. The comparison between two techniques was by sensitivity and specificity. The results of sGPC-3showedhigher significant in HCC group than CLC and normal controls (p<0.001). sGPC-3 sensitivity was 95% and specificity was100%, while inGPC-3 mRNA were 100% and 94% respectively. The combination ofsensitivity between AFP and sGPC-3 was 80% and 95% respectively. The data demonstrated that, can depend on sGPC-3 and Glypican-3 mRNA as tumor biomarkers fordetection and surveillance of Hepatocellular carcinoma in Saudi patients. The sensitivity of Reverse Transcriptase-PCR is high accurate (100%) than estimating sGPC-3 by ELISA (95%).
3. Biomarker development is a phased process [16-18]. At the early phase, the patient sample may be limited such that a simple linear model such as the logistic regression is most appropriate. The purpose at this phase is mainly to assess whether the new biomarkers are promising, but the limited data may not allow for reliable assessment of how much value they actually add. Potentially the statistical significance tests for new predictor variables could serve the purpose. The diagnostic accuracy can also be assessed typically in a cross-validation fashion. At the later phases of development and evaluation, however, a more complex classification model could be adopted and the primary purpose is to assess how much diagnostic accuracy the new biomarkers can add to existing ones. Then an independent training and testing of the model and a rigorous assessment of the added diagnostic accuracy (e.g., AUC) is necessary.
The move to multiplex assays has significant implications for the business models of diagnostic developers. Today, many companion diagnostics are initially developed under the ASR approval pathway and conducted in Clinical Laboratory Improvement Amendment of 1988 (CLIA) laboratories. The diagnostic developer often establishes a dedicated laboratory to which all diagnostic samples must be shipped, and results are sent back to the ordering physician. While this business model can be successful in a market environment where a single diagnostic is tied to a single therapeutic, it breaks down if payers and health care providers start to demand panels that compare companion diagnostics against each other. In this new multiplex environment, it is unlikely that a single test companion diagnostic laboratory can provide the needed tests.
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We would like to thank all the volunteers who took part in this study and the companies who generously supplied food for the study, New Zealand King Salmon, Venerdi, Red Seal Natural Health, Plant & Food Research, Cereal Partners Worldwide: Nestle & General Mills, Fonterra, New Zealand Avocado, Matiatia Grove, Vegetables.co.nz and The New Zealand Merino Company. Nutrigenomics New Zealand is a collaboration between The University of Auckland and AgResearch Limited and Plant & Food Research and is funded by the Ministry of Business, Innovation and Employment. The microbota work was supported by REINFORCE and was conducted in Professor Patrizia Brigidi's laboratory at the University of Bologna, Italy.
MicroRNAs (miRNAs) refer to a class of noncoding single-stranded RNA molecules 19 to 22 nucleotides in length . MiRNAs play significant roles in inhibiting mRNA translation and mRNA degradation, and they are involved in regulating many cellular processes both physiologically and pathologically . MiRNA expression profiling of tissue and serum have been widely carried out. Dysregulated miRNAs have been proved to be predictor of disease progression, prognosis and metastasis and may serve as molecular biomarkers for disease detection [29– 31]. Tissue miRNAs are invasive, and both tissue- and serum-derived miRNAs present poor stability in the pres- ence of interference factors. However, exosomal miRNAs in serum are thought to be more stable, and thus could be used in medical applications . Here, we explored the application significance of exosomal miRNAs as bio- markers for the diagnosis of OC.
On a routine site inspection of a petroleum product terminal, hydrocarbon staining was observed in soil along the perimeter of a diesel fuel tank. As the observation was made a few days after a magnitude 5.1 earthquake in the general area, the hydrocarbon staining in the soil was suspected to be a result of a leak from the tank. How- ever, the preliminary inspection did not reveal any issues with the tank. This, combined with the knowledge that oil seeps induced by earthquake seismic waves occur often in the general area, leads to a belief that the staining is likely due to seismic wave-induced soil compaction and light non-aqueous liquid (LNAPL) remobilization. Before more vigorous and more disruptive inspections were conducted, chemical fingerprinting was conducted to assess the nature of soil staining and potential connection with the “suspected” tank leak. This paper presents the approach and findings of initial site investigation and chemical fingerprinting. As the soil staining was proved not to be caused by suspected tank leak, the paper also provides a case study that demonstrates avoidance of an unnecessary remedial investigation through identification of suspected diesel source using hydrocarbon fingerprints and biomarkers.
Biomarkers such as methylated DNA are present in very small amounts in blood which makes them less attractive for detection of early stage cancers and adenomas . No single biomarker has yet yielded perfect sensitivity to CRC and advanced adenomas due to the heterogeneity of the tumours . Use of a panel of biomarkers will in- crease sensitivity while potentially maintaining specificity . Three tests (products 54, 56 and 60) identified in this study detect a panel of biomarkers but this further increases the complexity and the cost of the test. Lack of large scale population-based validation studies and the uncertainty about the frequency of administration of these tests has further limited their clinical utility , . Since the review was conducted, US investigators have reported on the performance of FIT versus a panel of stool DNA markers for CRC plus FIT and concluded that the panel of CRC markers showed higher single-applica- tion sensitivity than FIT alone for both CRC and advanced precancerous lesions (including sessile serrated ad- enomas), although with lower specificity . The panel test requires a complete stool sample, which introduces extra cost and impracticality to an already expensive testing procedure. Research will continue to identify either a sensitive single biomarker or a panel of biomarkers that simplify and automate the testing and do so at an afford- able cost .
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Secondly, we apply an Oaxaca-Blinder decomposition at various quantiles of the biomarker distributions to analyse gender differentials in biomarkers and to measure the contribution of income (and other covariates) to these differentials. Oaxaca-Blinder decomposition assesses to what extent gender differentials in biomarkers are explained by compositional differences, due to differences in observed covariates, or by differences in the elasticity of health with respect to income and other factors. More generally, decomposition analysis is useful for drawing policy implications because it helps to delineate the role of health policies, that operate on the health-gradient, from the role of fiscal policy, that operates on compositional differences (see Van Doorslaer and Koolman (2004) for a discussion of the policy implications of decomposition analysis). Jones and Lopez (2006) found that there is considerable heterogeneity in the association of health with explanatory variables across genders and they have shown that this has important consequences on the measurement of income- related inequalities in health. Our paper contributes to this literature by performing the decomposition analysis of gender differentials in health along the entire distribution of health status.
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Taken together, we identified CRIP1 as a new and promising biomarker in osteosarcoma. Although a significant correlation with long-term survival and metastatic spread was identified, an association with response to chemotherapy was not. This phenomenon might be influenced by a relatively high drop out of cases due to technical issues and available response data in only 66% of cases. Consequently, CRIP1 should be validated prospectively to proof its prognostic reliability and, nonetheless, a potential role in response prediction in osteosarcoma patients.
An interesting study from Verdoia et al. evaluated the effect of diabetes in PMI and myonecrosis after PCI treat- ment . Using the release of CK-MB and troponin to define PMI and myonecrosis, the authors found that diabe- tes is not associated with increased risk of cardiac damage after PCI therapy. Thus, their findings agree with the results from the present study. However, adding to the information from that study, the present one also assessed the release of biomarkers after on-pump and off-pump bypass surgery and the evaluation of cardiac magnetic resonance.
Dilated cardiomyopathy (DCM), occurring mostly in adults 20 to 60, is the most prevalent form of cardiomyopathy occurring in 1 in 2,500 individuals.(2, 5, 6) The ratio of incidence between male and female is approximately 3:1.(7, 8) The reason for this discrepancy between male and female remains unclear but it can be explained by sex hormones that may have an effect on cardiac structure and function.(8) DCM is usually diagnosed from patient’s history and by echocardiography or cardiac magnetic resonance showing evidence of both dilation and poor contraction of the left ventricle (EF <40%) or both ventricles.(1, 9-12) Enlarged ventricular sizes and impaired systolic functions are the characteristics of DCM.(1) An increased in left ventricular mass with structural changes manifest macroscopically.(13) A histological triad of myocyte hypertrophy, myocyte degradation, and interstitial fibrosis features microscopically.(14) Main phenotypes manifesting in DCM are ventricular chambers enlargement and thinning of ventricular walls. As the heart chambers dilate, there is deterioration of muscular structure resulting in abnormal contraction of the heart that has a high correlation with heart failure and mortality. (2) After developing symptoms of DCM, 50% of people with DCM die within five years. (15, 16) The phenotype of DCM can be accounted to many causes. It is classified as primary if of unknown etiology, also known as idiopathic DCM. Among the idiopathic cases, one third can be attributed to familial DCM that is transmitted autosomally either in a recessive or dominant manner though maternal mitochondrial DNA, or as an X-linked mutation.(17, 18) At least 50 genes have been linked to familial DCM.(19-22) Secondary causes of DCM includes diseases and conditions such as coronary heart disease, hypertension, viral infections of the heart, alcohol, drugs, toxins and so on. Biomarkers of DCM can be different based on the different causes, pathophysiology, and severity of the disease. Different biomarkers seen in DCM are described according to different mechanisms and hence it is quite challenging to categorize these biomarkers. In this review, we will concentrate more on different type of useful potential biomarkers that can aid in the screening, diagnosis or response to therapy in DCM patients. Biomarkers of Heart Failure in DCM Patients