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The uptake of the current concept of chronic kidney disease (CKD) by the public, physicians and health authorities is low. Physicians still mix up CKD with chronic kidney insufficiency or failure. In a recent manuscript, only 23% of participants in a cohort of persons with CKD had been diagnosed by their physicians as having CKD while 29% has a diagnosis of cancer and 82% had a diagnosis of hypertension. For the wider public and health authorities, CKD evokes kidney replacement therapy (KRT). In Spain, the prevalence of KRT is 0.13%. A prevalent view is that for those in whom kidneys fail, the problem is ``solved'' by dialysis or kidney transplantation. However, the main burden of CKD is accelerated aging and all-cause and cardiovascular premature death. CKD is the most prevalent risk factor for lethal COVID-19 and the factor that most increases the risk of death in COVID-19, after old age. Moreover, men and women undergoing KRT still have an annual mortality which is 10-100-fold higher than similar age peers, and life expectancy is shortened by around 40 years for young persons on dialysis and by 15 years for young persons with a functioning kidney graft. CKD is expected to become the fifth global cause of death by 2040 and the second cause of death in Spain before the end of the century, a time when 1 in 4 Spaniards will have CKD. However, by 2022, CKD will become the only top-15 global predicted cause of death that is not supported by a dedicated well-funded CIBER network research structure in Spain. Leading Spanish kidney researchers grouped in the kidney collaborative research network REDINREN have now applied for the RICORS call of collaborative research in Spain with the support of the Spanish Society of Nephrology, ALCER and ONT: RICORS2040 aims to prevent the dire predictions for the global 2040 burden of CKD from becoming true. However, only the highest level of research funding through the CIBER will allow to adequately address the issue before it is too late. (C) 2021 Sociedad Espanola de Nefrologia. Published by Elsevier Espana, S.L.U.

For time series forecasting, obtaining models is based on the use of past observations from the same sequence. In those cases, when the model is learning from data, there is not an extra information that discuss about the quantity of noise inside the data available. In practice, it is necessary to deal with finite noisy datasets, which lead to uncertainty about the propriety of the model. For this problem, the employment of the Bayesian inference tools are preferable. A modified algorithm used for training a long-short term memory recurrent neural network for time series forecasting is presented. This approach was chosen to improve the forecasting of the original series, employing an implementation based on the minimization of the associated Kullback-Leibler Information Criterion. For comparison, a nonlinear autoregressive model implemented with a feedforward neural network was also presented. A simulation study was conducted to evaluate and illustrate results, comparing this approach with Bayesian neural-networks-based algorithms for artificial chaotic time-series and showing an improvement in terms of forecasting errors.

Background. Acute interstitial nephritis (AIN) is an emerging cause of acute kidney disease. While this disease usually follows an acute course, it may occasionally recur, representing a major challenge for the clinician. Methods. We performed a retrospective, observational cohort study in 13 nephrology departments belonging to the Spanish Group for the Study of Glomerular Diseases. Patients with biopsy-proven AIN between 1996 and 2018 were included. Results. The study group consisted of 205 patients with AIN, 22 of which developed recurrent AIN (RAIN) after a median of 111 days from diagnosis. RAIN was due to a surreptitious reintroduction of a previously known implicated drug or toxic in six patients (27%), sarcoidosis in two (9%), Sjogren's syndrome in three (14%), light-chain-mediated AIN in two (9%) and tubulointerstitial nephritis and uveitis syndrome in two (9%), while in the rest of cases (32%), no precise cause could be identified. Microscopic haematuria was more frequent in patients with underlying systemic diseases. The first RAIN episode was treated with a repeated course of corticosteroids in 21 patients (95%). In six cases (27%), azathioprine and mycophenolate mofetil were added as corticosteroid-sparing agents. During a median follow-up of 30 months, 50 patients (27%) with no recurrences and 12 patients (55%) with RAIN reached Stages 4 and 5 chronic kidney disease (CKD). By multivariable logistic regression analysis, RAIN was independently associated with the risk of reaching Stages 4 and 5 CKD, even after adjusting for potential covariables. Conclusions. RAIN is infrequent but is associated with poor kidney survival. RAIN should prompt clinicians to search for an underlying aetiology other than drug induced. However, in a large percentage of cases, no precise cause can be identified.

Made available in DSpace on 2021-06-25T10:44:50Z (GMT). No. of bitstreams: 0 Previous issue date: 2020-12-01 Universidade Estadual Paulista Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Fingerprints have been used in forensic investigations as a powerful tool for human identification. However, it is desirable to find new sustainable sources and synthesis for fingerprint developers, in order to reduce the production costs, to improve the sensitivity and to reduce environment impact after the disposal. This report describes a study involving the production of acetylated cashew-gum-based silver nanoparticles (ACG-AgNPs), using three concentrations of ACG (0.5, 1.0 and 5.0 mg/mL). The nanoparticles were characterized by UV-VIS spectroscopy, AFM (atomic force microscopy) and TEM (transmission electron microscopy). In addition, computer simulations and evaluation of their effect as a potential fingerprint developer on paper were studied, using ninhydrin as a positive control. The results showed that samples were able to reveal the lines contained in the fingerprint residues on paper. Positive results were obtained for all the samples in tests performed 1, 6 and 24 h after application. Howeverthe best performance was observed with the sample containing ACG 0.5 mg/mL. ACG-AgNPs have potential for practical and rapid latent fingerprint development on porous surfaces, which allows the development of a product to be used even at the crime scene. Another advantage was the synthesis process: simple, fast, low-cost and using a biocompatible and biodegradable material as stabilizer, providing a non-toxic material. In addition, this material, is likely to cause less environmental damage than the reagents used by conventional techniques. Faculdade de Medicina do ABC FMABC Departamento de Polícia Técnico-Científica do Piauí DPTC-PI Núcleo de Pesquisa em Biodiversidade e Biotecnologia Biotec Universidade Federal do Delta do Parnaíba UFDPar LAQV-REQUIMTE Department of Chemistry and Biochemistry Faculdade de Ciências da Universidade do Porto Bioprospectum Lda UPTEC Identification Institute Civil Police of the Federal District Núcleo de Pesquisa em Morfologia e Imunologia Aplicada NuPMIA Area de Morfologia Faculdade de Medicina FM Universidade de Brasília UnB Instituto Federal de Educação Ciência e Tecnologia de São Paulo Universidade Estadual Paulista UNESP Campus Experimental de Itapeva Universidade Estadual Paulista UNESP Campus Experimental de Itapeva CNPq: 420449/2018-3 CNPq: 428211/2018-6