42 research outputs found
Protective films on complex substrates of thermoplastic and cellular elastomers:Prospective applications to rubber, nylon and cork
Deposition of thin films is an appropriate methodology to enhance the performance of a material by modification of its surface, while keeping the properties of the bulk largely unaffected. However, a practical implementation becomes less straightforward when dealing with sensitive or complex substrates, for instance, those which cannot be subjected to harsh treatments, such as cleaning and etching, or extreme deposition conditions, like high temperatures, and ion impingement et cetera. This paper concentrates on deposition processing of complex substrates. In particular, it discusses the deposition of two types of protective coatings (diamond-like carbon (DLC) films against friction and wear, and TiO2 films against UV light) on three types of thermoplastic and cellular elastomers (rubber, nylon and cork). It is demonstrated that a successful protection of thermoplastic elastomers against wear with DLC films can be attained, after a thorough adaptation of the procedure to the characteristics of the specific substrate. In addition, the paper reports the very first depositions on a cellular elastomer like cork by vapor deposition methods, including Atomic Layer Deposition (ALD)
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Biomarker discovery and redundancy reduction towards classification using a multi-factorial MALDI-TOF MS T2DM mouse model dataset
Diabetes like many diseases and biological processes is not mono-causal. On the one hand multifactorial studies with complex experimental design are required for its comprehensive analysis. On the other hand, the data from these studies often include a substantial amount of redundancy such as proteins that are typically represented by a multitude of peptides. Coping simultaneously with both complexities (experimental and technological) makes data analysis a challenge for Bioinformatics
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Early Detection of Ovarian Cancer in Samples Pre-Diagnosis Using CA125 and MALDI-MS Peaks
Aim: A nested case-control discovery study was undertaken 10 test whether information within the serum peptidome can improve on the utility of CA125 for early ovarian cancer detection. Materials and Methods: High-throughput matrix-assisted laser desorption ionisation mass spectrometry (MALDI-MS) was used to profile 295 serum samples from women pre-dating their ovarian cancer diagnosis and from 585 matched control samples. Classification rules incorporating CA125 and MS peak intensities were tested for discriminating ability. Results: Two peaks were found which in combination with CA125 discriminated cases from controls up to 15 and 11 months before diagnosis, respectively, and earlier than using CA125 alone. One peak was identified as connective tissue-activating peptide III (CTAPIII), whilst the other was putatively identified as platelet factor 4 (PF4). ELISA data supported the down-regulation of PF4 in early cancer cases. Conclusion: Serum peptide information with CA125 improves lead time for early detection of ovarian cancer. The candidate markers are platelet-derived chemokines, suggesting a link between platelet function and tumour development
A simpler method of preprocessing MALDI-TOF MS data for differential biomarker analysis: stem cell and melanoma cancer studies
<p>Abstract</p> <p>Introduction</p> <p>Raw spectral data from matrix-assisted laser desorption/ionisation time-of-flight (MALDI-TOF) with MS profiling techniques usually contains complex information not readily providing biological insight into disease. The association of identified features within raw data to a known peptide is extremely difficult. Data preprocessing to remove uncertainty characteristics in the data is normally required before performing any further analysis. This study proposes an alternative yet simple solution to preprocess raw MALDI-TOF-MS data for identification of candidate marker ions. Two in-house MALDI-TOF-MS data sets from two different sample sources (melanoma serum and cord blood plasma) are used in our study.</p> <p>Method</p> <p>Raw MS spectral profiles were preprocessed using the proposed approach to identify peak regions in the spectra. The preprocessed data was then analysed using bespoke machine learning algorithms for data reduction and ion selection. Using the selected ions, an ANN-based predictive model was constructed to examine the predictive power of these ions for classification.</p> <p>Results</p> <p>Our model identified 10 candidate marker ions for both data sets. These ion panels achieved over 90% classification accuracy on blind validation data. Receiver operating characteristics analysis was performed and the area under the curve for melanoma and cord blood classifiers was 0.991 and 0.986, respectively.</p> <p>Conclusion</p> <p>The results suggest that our data preprocessing technique removes unwanted characteristics of the raw data, while preserving the predictive components of the data. Ion identification analysis can be carried out using MALDI-TOF-MS data with the proposed data preprocessing technique coupled with bespoke algorithms for data reduction and ion selection.</p
Mapping the binding site of snurportin 1 on native U1 snRNP by cross-linking and mass spectrometry
Mass spectrometry allows the elucidation of molecular details of the interaction domains of the individual components in macromolecular complexes subsequent to cross-linking of the individual components. Here, we applied chemical and UV cross-linking combined with tandem mass-spectrometric analysis to identify contact sites of the nuclear import adaptor snurportin 1 to the small ribonucleoprotein particle U1 snRNP in addition to the known interaction of m3G cap and snurportin 1. We were able to define previously unknown sites of protein–protein and protein–RNA interactions on the molecular level within U1 snRNP. We show that snurportin 1 interacts with its central m3G-cap-binding domain with Sm proteins and with its extreme C-terminus with stem-loop III of U1 snRNA. The crosslinking data support the idea of a larger interaction area between snurportin 1 and U snRNPs and the contact sites identified prove useful for modeling the spatial arrangement of snurportin 1 domains when bound to U1 snRNP. Moreover, this suggests a functional nuclear import complex that assembles around the m3G cap and the Sm proteins only when the Sm proteins are bound and arranged in the proper orientation to the cognate Sm site in U snRNA
Conformal predictors in early diagnostics of ovarian and breast cancers
The paper describes an application of a recently
developed machine learning technique called Mondrian
predictors to risk assessment of ovarian and breast
cancers. The analysis is based on mass spectrometry
profiling of human serum samples that were collected
in the United Kingdom Collaborative Trial of Ovarian
Cancer Screening. The paper describes the technique
and presents the results of classification (diagnosis)
and the corresponding measures of confidence of
the diagnostics. The main advantage of this approach
is a proven validity of prediction. The paper also describes
an approach to improve early diagnosis of ovarian
and breast cancers since the data in the United
Kingdom Collaborative Trial of Ovarian Cancer Screening
were collected over a period of seven years and do
allow to make observations of changes in human serum
over that period of time. Significance of improvement is
confirmed statistically (for up to 11 months for Ovarian
Cancer and 9 months for Breast Cancer). In addition,
the methodology allowed us to pinpoint the same mass
spectrometry peaks as previously detected as carrying
statistically significant information for discrimination
between healthy and diseased patients. The results are
discussed
Improved blood tests for cancer screening: general or specific?
Diagnosis of cancer at an early stage leads to improved survival. However, most current blood tests detect single biomarkers that are of limited suitability for screening, and existing screening programmes look only for cancers of one particular type. A new approach is needed. Recent developments suggest the possibility of blood-based screening for multiple tumour types. It may be feasible to develop a high-sensitivity general screen for cancer using multiple proteins and nucleic acids present in the blood of cancer patients, based on the biological characteristics of cancer. Positive samples in the general screen would be submitted automatically for secondary screening using tests to help define the likelihood of cancer and provide some indication of its type. Only those at high risk would be referred for further clinical assessment to permit early treatment and mitigate potential overdiagnosis. While the assays required for each step exist, they have not been used in this way. Recent experience of screening for breast, cervical and ovarian cancers suggest that there is likely to be widespread acceptance of such a strategy
Proteomic Analysis of Polypeptides Captured from Blood during Extracorporeal Albumin Dialysis in Patients with Cholestasis and Resistant Pruritus
Albumin dialysis using the molecular adsorbent recirculating system (MARS) is a new therapeutic approach for liver diseases. To gain insight into the mechanisms involved in albumin dialysis, we analyzed the peptides and proteins absorbed into the MARS strong anion exchange (SAX) cartridges as a result of the treatment of patients with cholestasis and resistant pruritus. Proteins extracted from the SAX MARS cartridges after patient treatment were digested with two enzymes. The resulting peptides were analyzed by multidimensional liquid chromatography coupled to tandem mass spectrometry. We identified over 1,500 peptide sequences corresponding to 144 proteins. In addition to the proteins that are present in control albumin-derived samples, this collection includes 60 proteins that were specific to samples obtained after patient treatment. Five of these proteins (neutrophil defensin 1 [HNP-1], secreted Ly-6/uPAR-related protein 1 [SLURP1], serum amyloid A, fibrinogen alpha chain and pancreatic prohormone) were confirmed to be removed by the dialysis procedure using targeted selected-reaction monitoring MS/MS. Furthermore, capture of HNP-1 and SLURP1 was also validated by Western blot. Interestingly, further analyses of SLURP1 in serum indicated that this protein was 3-fold higher in cholestatic patients than in controls. Proteins captured by MARS share certain structural and biological characteristics, and some of them have important biological functions. Therefore, their removal could be related either to therapeutic or possible adverse effects associated with albumin dialysis
Electrical transport of sprayed In2S3:Ag thin films
Silver doped indium sulfide (In2S3:Ag) thin layers were prepared by spray pyrolysis. The Ag concentration varies in the range of 0–6 at%. The X-ray diffraction (XRD) indicates the presence of cubic phase of β-In2S3 and the crystallite size values exhibit a maximum at an Ag concentration of 4%. In addition, morphological analysis by atomic force microscopy (AFM) shows that the film surface is continuous, compact, free of cracks and depends on the Ag concentration. This observation is remarkable by evolution of surface roughness values. The films reveal a semiconductor behavior. This is observed because the electrical conductance increases with the increase of measurement temperature and the analysis of the Nyquist diagram shows the appearance of half circles, whose radius decreases by increasing the temperature from 300 K to 600 K. The electrical equivalent circuit of undoped In2S3 and In2S3:Ag4% at 460 K and 470 K contains two components connected in serial. The first is composed of a resistance R1, an inductance L and a constant phase element CPE1 in parallel and the other covers R2 and a constant phase element CPE2 that are connected in parallel. Inductive and capacitive effects exist in these materials and they depend on frequency. For Ag concentration equal or greater than 4%, the equivalent circuit is a parallel association of a resistor with a constant phase element. The activation energy is minimum for an Ag concentration of 4%.This work was supported by Spanish Ministry of Science and Innovation, Spain - Grant ID: CTQ2016-79561-R (MODENA), Fundacion Ramon Areces, Spain -Grant ID: CIVP18A3940 and Xunta de Galicia, Spain - Grant IDs: Galician Competitive Research Group ED431C-2017/22, AEMAT Strategic Partnership ED431E-2018/08. Authors would like to thank the use of RIAIDT - USC analytical facilities