Monitoring the efficiency of iron chelation therapy: the potential of nontransferrin-bound iron.

The major ligands of nontransferrin-bound iron (NTBI) are suggested to be citrate and albumin. The proportion of iron binding to albumin is influenced by the degree of oxidation and glycation of the protein. LC-ICP-MS is demonstrated to be a useful technique for the speciation of NTBI, with unprocessed serum being subjected to analysis. Ferritin iron, citrate iron, and ferrioxamine can be quantified using this technique. This review describes the use of a new fluorescent probe for NTBI quantification

Target score—a proteomics data selection tool applied to esophageal cancer identifies glut1-sialyl tn glycoforms as biomarkers of cancer aggressiveness

Esophageal cancer (EC) is a life-threatening disease, demanding the discovery of new biomarkers and molecular targets for precision oncology. Aberrantly glycosylated proteins hold tremendous potential towards this objective. In the current study, a series of esophageal squamous cell carcinomas (ESCC) and EC-derived circulating tumor cells (CTCs) were screened by immunoassays for the sialyl-Tn (STn) antigen, a glycan rarely expressed in healthy tissues and widely observed in aggressive gastrointestinal cancers. An ESCC cell model was glycoengineered to express STn and characterized in relation to cell proliferation and invasion in vitro. STn was found to be widely present in ESCC (70% of tumors) and in CTCs in 20% of patients, being associated with general recurrence and reduced survival. Furthermore, STn expression in ESCC cells increased invasion in vitro, while reducing cancer cells proliferation. In parallel, an ESCC mass spectrometry-based proteomics dataset, obtained from the PRIDE database, was comprehensively interrogated for abnormally glycosylated proteins. Data integration with the Target Score, an algorithm developed in-house, pinpointed the glucose transporter type 1 (GLUT1) as a biomarker of poor prognosis. GLUT1-STn glycoproteoforms were latter identified in tumor tissues in patients facing worst prognosis. Furthermore, healthy human tissues analysis suggested that STn glycosylation provided cancer specificity to GLUT1. In conclusion, STn is a biomarker of worst prognosis in EC and GLUT1-STn glycoforms may be used to increase its specificity on the stratification and targeting of aggressive ESCC forms.The authors wish to acknowledge the Portuguese Foundation for Science and Technology (FCT) for the human resources grants: PhD grant SFRH/BD/111242/2015 (AP), SFRH/BD/146500/2019 (MRS), SFRH/BD/142479/2018 (JS), SFRH/BD/105355/2014 (RA) and FCT assistant researcher grant CEECIND/03186/2017 (JAF). FCT is co-financed by European Social Fund (ESF) under Human Potential Operation Programme (POPH) from National Strategic Reference Framework (NSRF). The authors also acknowledge FCT the funding for CI-IPOP research unit (PEst-OE/SAU/UI0776/201) and LAQV-REQUIMTE research unit (UIDB/50006/2020), the Portuguese Oncology Institute of Porto Research Centre (CI-IPOP-29-2016-2020; CI-IPOP-58-2016-2020; CI-IPOP-Proj.70-bolsa2019-GPTE) and PhD Program in Biomedical Sciences of ICBAS-University of Porto. The author also thanks “Early stage cancer treatment, driven by context of molecular imaging (ESTIMA)” framework (NORTE-01-0145-FEDER-000027) and IPO-Score (DSAIPA/DS/0042/2018) for financial support. This work was financed by FEDER—Fundo Europeu de Desenvolvimento Regional funds through the COMPETE 2020—Operacional Programme for Competitiveness and Internationalisation (POCI), Portugal 2020 and by Portuguese funds through FCT/MCTES—Fundação para a Ciência e a Tecnologia/Ministério da Ciência, Tecnologia e Ensino Superior. The authors also acknowledge support from the Portuguese League against Cancer grant LPCC-NRN-2020 (DF)

Use of multidimensional item response theory methods for dementia prevalence prediction: an example using the Health and Retirement Survey and the Aging, Demographics, and Memory Study.

BACKGROUND: Data sparsity is a major limitation to estimating national and global dementia burden. Surveys with full diagnostic evaluations of dementia prevalence are prohibitively resource-intensive in many settings. However, validation samples from nationally representative surveys allow for the development of algorithms for the prediction of dementia prevalence nationally. METHODS: Using cognitive testing data and data on functional limitations from Wave A (2001-2003) of the ADAMS study (n = 744) and the 2000 wave of the HRS study (n = 6358) we estimated a two-dimensional item response theory model to calculate cognition and function scores for all individuals over 70. Based on diagnostic information from the formal clinical adjudication in ADAMS, we fit a logistic regression model for the classification of dementia status using cognition and function scores and applied this algorithm to the full HRS sample to calculate dementia prevalence by age and sex. RESULTS: Our algorithm had a cross-validated predictive accuracy of 88% (86-90), and an area under the curve of 0.97 (0.97-0.98) in ADAMS. Prevalence was higher in females than males and increased over age, with a prevalence of 4% (3-4) in individuals 70-79, 11% (9-12) in individuals 80-89 years old, and 28% (22-35) in those 90 and older. CONCLUSIONS: Our model had similar or better accuracy as compared to previously reviewed algorithms for the prediction of dementia prevalence in HRS, while utilizing more flexible methods. These methods could be more easily generalized and utilized to estimate dementia prevalence in other national surveys

Advanced glycoxidation and lipoxidation end products (AGEs and ALEs): an overview of their mechanisms of formation

Advanced lipoxidation end products (ALEs) and advanced glycation end products (AGEs) have a pathogenetic role in the development and progression of different oxidative-based diseases including diabetes, atherosclerosis, and neurological disorders. AGEs and ALEs represent a quite complex class of compounds that are formed by different mechanisms, by heterogeneous precursors and that can be formed either exogenously or endogenously. There is a wide interest in AGEs and ALEs involving different aspects of research which are essentially focused on set-up and application of analytical strategies (1) to identify, characterize, and quantify AGEs and ALEs in different pathophysiological conditions ; (2) to elucidate the molecular basis of their biological effects ; and (3) to discover compounds able to inhibit AGEs/ALEs damaging effects not only as biological tools aimed at validating AGEs/ALEs as drug target, but also as promising drugs. All the above-mentioned research stages require a clear picture of the chemical formation of AGEs/ALEs but this is not simple, due to the complex and heterogeneous pathways, involving different precursors and mechanisms. In view of this intricate scenario, the aim of the present review is to group the main AGEs and ALEs and to describe, for each of them, the precursors and mechanisms of formation

Melanoides tuberculata as intermediate host of Philophthalmus gralli in Brazil

Melanoides tuberculata that naturally harbored trematode larvae were collected at the Pampulha dam, Belo Horizonte (Minas Gerais, Brazil), during malacological surveys conducted from 2006 to 2010. From 7,164 specimens of M. tuberculata collected, 25 (0.35%) were infected by cercariae, which have been morphologically characterized as belonging to the Megalurous group, genus Philophthalmus. Excysted metacercariae were used for successful experimental infection of Gallus gallus domesticus, and adult parasites recovered from the nictitating membranes of chickens were identified as Philophthalmus gralli. This is the first report of P. gralli in M. tuberculata in Brazil