Capacity for the management of kidney failure in the International Society of Nephrology North and East Asia region:Report from the 2023 ISN Global Kidney Health Atlas (ISN-GKHA)

Globally, there remain significant disparities in the capacity and quality of kidney care, as evidenced by the 3rd edition of the International Society of Nephrology -Global Kidney Health Atlas. In the ISN North and East Asia region, the chronic kidney disease (CKD) burden varied widely; Taiwan had the heaviest burden of treated kidney failure [3679 per million population (pmp)] followed by Japan and South Korea. Except in Hong Kong, hemodialysis (HD) was the main dialysis modality for all other countries in the region and was much higher than the global median prevalence. Kidney transplantation services were generally available in the region, but the prevalence was much lower than that of dialysis. Most countries had public funding for kidney replacement therapy (KRT). The median prevalence of nephrologists was 28.7 pmp, higher than that of any other ISN region, with variation across countries. Home HD was available in only 17% of the countries while conservative kidney management was available in 50%. All countries had official registries for dialysis and transplantation; however only China and Japan had CKD registries. Advocacy groups for CKD, kidney failure, and KRT were uncommon throughout the region. Overall, all countries in the region had capacity for KRT, albeit with some shortages in their kidney care workforce. These data are useful for stakeholders to address gaps in kidney care and to reduce workforce shortages through increased use of multidisciplinary teams and telemedicine, policy changes to promote prevention and treatment of kidney failure, and increased advocacy for kidney disease in the region

Prospects in computational molecular medicine: a millennial mega-project on peptide folding

During the second half of the 20th century, Molecular Computations have reached to a level that can revolutionize chemistry. The next target will be structural biology, which will be followed soon by Molecular Medicine. The present paper outlines where we are at, in this field, at the end of the 20th century, and in what direction the development may take in the new millennium. In view of the gigantic nature of the problem, it is suggested that a suitably designed cooperative Millennial Mega-project might accelerate our schedule. (C) 2000 Elsevier Science B.V. All rights reserved

Detection of human MCP-4/CCL13 isoforms by SELDI immunoaffinity capture

Monocyte Chemoattractant Proteins 4 (MCP-4/CCL13) is a member of a distinct, structurally-related subclass of CC chemokines mainly involved in recruitment of eosinphils to inflammatory sites. Recent evidence demonstrates that serum level of this protein strongly increases following high dose IL-2 immunotherapy. The physiological form of human MCP-4/CCL13 has yet to be purified. Therefore, the primary structure of the biologically relevant (mature) form has not been established. By using SELDI immunoaffinity capture technology we describe two mature isoforms both present in serum before and after high-dose IL-2 immunotherapy

Discriminating Active from Latent Tuberculosis in Patients Presenting to Community Clinics

BACKGROUND Because of the high global prevalence of latent TB infection (LTBI), a key challenge in endemic settings is distinguishing patients with active TB from patients with overlapping clinical symptoms without active TB but with co-existing LTBI. Current methods are insufficiently accurate. Plasma proteomic fingerprinting can resolve this difficulty by providing a molecular snapshot defining disease state that can be used to develop point-of-care diagnostics. METHODS Plasma and clinical data were obtained prospectively from patients attending community TB clinics in Peru and from household contacts. Plasma was subjected to high-throughput proteomic profiling by mass spectrometry. Statistical pattern recognition methods were used to define mass spectral patterns that distinguished patients with active TB from symptomatic controls with or without LTBI. RESULTS 156 patients with active TB and 110 symptomatic controls (patients with respiratory symptoms without active TB) were investigated. Active TB patients were distinguishable from undifferentiated symptomatic controls with accuracy of 87% (sensitivity 84%, specificity 90%), from symptomatic controls with LTBI (accuracy of 87%, sensitivity 89%, specificity 82%) and from symptomatic controls without LTBI (accuracy 90%, sensitivity 90%, specificity 92%). CONCLUSIONS We show that active TB can be distinguished accurately from LTBI in symptomatic clinic attenders using a plasma proteomic fingerprint. Translation of biomarkers derived from this study into a robust and affordable point-of-care format will have significant implications for recognition and control of active TB in high prevalence settings

Comparison of normalisation methods for surface-enhanced laser desorption and ionisation (SELDI) time-of-flight (TOF) mass spectrometry data

<p>Abstract</p> <p>Background</p> <p>Mass spectrometry for biological data analysis is an active field of research, providing an efficient way of high-throughput proteome screening. A popular variant of mass spectrometry is SELDI, which is often used to measure sample populations with the goal of developing (clinical) classifiers. Unfortunately, not only is the data resulting from such measurements quite noisy, variance between replicate measurements of the same sample can be high as well. Normalisation of spectra can greatly reduce the effect of this technical variance and further improve the quality and interpretability of the data. However, it is unclear which normalisation method yields the most informative result.</p> <p>Results</p> <p>In this paper, we describe the first systematic comparison of a wide range of normalisation methods, using two objectives that should be met by a good method. These objectives are minimisation of inter-spectra variance and maximisation of signal with respect to class separation. The former is assessed using an estimation of the coefficient of variation, the latter using the classification performance of three types of classifiers on real-world datasets representing two-class diagnostic problems. To obtain a maximally robust evaluation of a normalisation method, both objectives are evaluated over multiple datasets and multiple configurations of baseline correction and peak detection methods. Results are assessed for statistical significance and visualised to reveal the performance of each normalisation method, in particular with respect to using no normalisation. The normalisation methods described have been implemented in the freely available MASDA R-package.</p> <p>Conclusion</p> <p>In the general case, normalisation of mass spectra is beneficial to the quality of data. The majority of methods we compared performed significantly better than the case in which no normalisation was used. We have shown that normalisation methods that scale spectra by a factor based on the dispersion (e.g., standard deviation) of the data clearly outperform those where a factor based on the central location (e.g., mean) is used. Additional improvements in performance are obtained when these factors are estimated locally, using a sliding window within spectra, instead of globally, over full spectra. The underperforming category of methods using a globally estimated factor based on the central location of the data includes the method used by the majority of SELDI users.</p

Normalization in MALDI-TOF imaging datasets of proteins: practical considerations

Normalization is critically important for the proper interpretation of matrix-assisted laser desorption/ionization (MALDI) imaging datasets. The effects of the commonly used normalization techniques based on total ion count (TIC) or vector norm normalization are significant, and they are frequently beneficial. In certain cases, however, these normalization algorithms may produce misleading results and possibly lead to wrong conclusions, e.g. regarding to potential biomarker distributions. This is typical for tissues in which signals of prominent abundance are present in confined areas, such as insulin in the pancreas or β-amyloid peptides in the brain. In this work, we investigated whether normalization can be improved if dominant signals are excluded from the calculation. Because manual interaction with the data (e.g., defining the abundant signals) is not desired for routine analysis, we investigated two alternatives: normalization on the spectra noise level or on the median of signal intensities in the spectrum. Normalization on the median and the noise level was found to be significantly more robust against artifact generation compared to normalization on the TIC. Therefore, we propose to include these normalization methods in the standard “toolbox” of MALDI imaging for reliable results under conditions of automation

Accurate peak list extraction from proteomic mass spectra for identification and profiling studies

<p>Abstract</p> <p>Background</p> <p>Mass spectrometry is an essential technique in proteomics both to identify the proteins of a biological sample and to compare proteomic profiles of different samples. In both cases, the main phase of the data analysis is the procedure to extract the significant features from a mass spectrum. Its final output is the so-called peak list which contains the mass, the charge and the intensity of every detected biomolecule. The main steps of the peak list extraction procedure are usually preprocessing, peak detection, peak selection, charge determination and monoisotoping operation.</p> <p>Results</p> <p>This paper describes an original algorithm for peak list extraction from low and high resolution mass spectra. It has been developed principally to improve the precision of peak extraction in comparison to other reference algorithms. It contains many innovative features among which a sophisticated method for managing the overlapping isotopic distributions.</p> <p>Conclusions</p> <p>The performances of the basic version of the algorithm and of its optional functionalities have been evaluated in this paper on both SELDI-TOF, MALDI-TOF and ESI-FTICR ECD mass spectra. Executable files of MassSpec, a MATLAB implementation of the peak list extraction procedure for Windows and Linux systems, can be downloaded free of charge for nonprofit institutions from the following web site: <url>http://aimed11.unipv.it/MassSpec</url></p