Mapping nitro-tyrosine modifications in fibrinogen by mass spectrometry as a biomarker for inflammatory disease

There is a growing awareness that inflammatory diseases have an oxidative pathology, which can result in specific oxidation of amino acids within proteins. It is known that patients with inflammatory disease have higher levels of plasma protein nitro-tyrosine than healthy controls. Fibrinogen is an abundant plasma protein, highly susceptible to such oxidative modifications, and is therefore a potential marker for oxidative protein damage. The aim of this study was to map tyrosine nitration in fibrinogen under oxidative conditions and identify susceptible residues. Fibrinogen was oxidised with 0.25mM and 1mM SIN-1, a peroxynitrite generator, and methionine was used to quench excess oxidant in the samples. The carbonyl assay was used to confirm oxidation in the samples. The carbonyl levels were 2.3, 8.72 and 11.5nmol/mg protein in 0, 0.25mM and 1mM SIN-1 samples respectively. The samples were run on a SDS-PAGE gel and tryptically digested before analysis by HPLC MS-MS. All 3 chains of fibrinogen were observed for all treatment conditions. The overall sequence coverage for fibrinogen determined by Mascot was between 60-75%. The oxidised samples showed increases in oxidative modifications in both alpha and beta chains, commonly methionine sulfoxide and tyrosine nitration, correlating with increasing SIN-1 treatment. Tyrosines that were most susceptible were Tyr135 (tryptic peptide YLQEIYNSNNQK) and Tyr277 (tryptic peptide GGSTSYGTGSETESPR), but several other nitrated tyrosines were also identified with high confidence. Identification of these susceptible peptides will allow design of sequences-specific biomarkers of oxidative and nitrative damage to plasma protein in inflammatory conditions.

Nonlinear speech analysis algorithms mapped to a standard metric achieve clinically useful quantification of average Parkinson's disease symptom severity

The standard reference clinical score quantifying average Parkinson's disease (PD) symptom severity is the Unified Parkinson's Disease Rating Scale (UPDRS). At present, UPDRS is determined by the subjective clinical evaluation of the patient's ability to adequately cope with a range of tasks. In this study, we extend recent findings that UPDRS can be objectively assessed to clinically useful accuracy using simple, self-administered speech tests, without requiring the patient's physical presence in the clinic. We apply a wide range of known speech signal processing algorithms to a large database (approx. 6000 recordings from 42 PD patients, recruited to a six-month, multi-centre trial) and propose a number of novel, nonlinear signal processing algorithms which reveal pathological characteristics in PD more accurately than existing approaches. Robust feature selection algorithms select the optimal subset of these algorithms, which is fed into non-parametric regression and classification algorithms, mapping the signal processing algorithm outputs to UPDRS. We demonstrate rapid, accurate replication of the UPDRS assessment with clinically useful accuracy (about 2 UPDRS points difference from the clinicians' estimates, p < 0.001). This study supports the viability of frequent, remote, cost-effective, objective, accurate UPDRS telemonitoring based on self-administered speech tests. This technology could facilitate large-scale clinical trials into novel PD treatments.

Cognitive systems associated with the hippocampus of the human brain and their role in behaviour and neurodegenerative disease

Cognitive systems research involves the synthesis of ideas from natural and artificial systems in the analysis, understanding, and design of all intelligent systems. This chapter discusses the cognitive systems associated with the hippocampus (HC) of the human brain and their possible role in behaviour and neurodegenerative disease. The hippocampus (HC) is concerned with the analysis of highly abstract data derived from all sensory systems but its specific role remains controversial. Hence, there have been three major theories concerning its function, viz., the memory theory, the spatial theory, and the behavioral inhibition theory. The memory theory has its origin in the surgical destruction of the HC, which results in severe anterograde and partial retrograde amnesia. The spatial theory has its origin in the observation that neurons in the HC of animals show activity related to their location within the environment. By contrast, the behavioral inhibition theory suggests that the HC acts as a ‘comparator’, i.e., it compares current sensory events with expected or predicted events. If a set of expectations continues to be verified then no alteration of behavior occurs. If, however, a ‘mismatch’ is detected then the HC intervenes by initiating appropriate action by active inhibition of current motor programs and initiation of new data gathering. Understanding the cognitive systems of the hippocampus in humans may aid in the design of intelligent systems involved in spatial mapping, memory, and decision making. In addition, this information may lead to a greater understanding of the course of clinical dementia in the various neurodegenerative diseases in which there is significant damage to the HC.

The Aston Medication Adherence Study:mapping the adherence patterns of an inner-city population

Background: The Aston Medication Adherence Study was designed to examine non-adherence to prescribed medicines within an inner-city population using general practice (GP) prescribing data. Objective: To examine non-adherence patterns to prescribed oralmedications within three chronic disease states and to compare differences in adherence levels between various patient groups to assist the routine identification of low adherence amongst patients within the Heart of Birmingham teaching Primary Care Trust (HoBtPCT). Setting: Patients within the area covered by HoBtPCT (England) prescribed medication for dyslipidaemia, type-2 diabetes and hypothyroidism, between 2000 and 2010 inclusively. HoBtPCT's population was disproportionately young,with seventy per cent of residents fromBlack and Minority Ethnic groups. Method: Systematic computational analysis of all medication issue data from 76 GP surgeries dichotomised patients into two groups (adherent and non-adherent) for each pharmacotherapeutic agent within the treatment groups. Dichotomised groupings were further analysed by recorded patient demographics to identify predictors of lower adherence levels. Results were compared to an analysis of a self-reportmeasure of adherence [using the Modified Morisky Scale© (MMAS-8)] and clinical value data (cholesterol values) from GP surgery records. Main outcome: Adherence levels for different patient demographics, for patients within specific longterm treatment groups. Results: Analysis within all three groups showed that for patients with the following characteristics, adherence levels were statistically lower than for others; patients: younger than 60 years of age; whose religion is coded as "Islam"; whose ethnicity is coded as one of the Asian groupings or as "Caribbean", "Other Black" and "African"; whose primary language is coded as "Urdu" or "Bengali"; and whose postcodes indicate that they live within the most socioeconomically deprived areas of HoBtPCT. Statistically significant correlations between adherence status and results from the selfreport measure of adherence and of clinical value data analysis were found. Conclusion: Using data fromGP prescribing systems, a computerised tool to calculate individual adherence levels for oral pharmacotherapy for the treatment of diabetes, dyslipidaemia and hypothyroidism has been developed.The tool has been used to establish nonadherence levels within the three treatment groups and the demographic characteristics indicative of lower adherence levels, which in turn will enable the targeting of interventional support within HoBtPCT. © Koninklijke Nederlandse Maatschappij ter bevordering der Pharmacie 2013.