Positive correlation of airway resistance and serum asymmetric dimethylarginine (ADMA) in bronchial asthma patients lacking evidence for systemic inflammation.

BACKGROUND: Contribution of nitric-oxide (NO) pathway to the pathogenesis of bronchial asthma (asthma) is ambiguous as NO may confer both protective and detrimental effects depending on the NO synthase (NOS) isoforms, tissue compartments and underlying pathological conditions (e.g. systemic inflammation). Asymmetric dimethylarginine (ADMA) is an endogenous inhibitor and uncoupler of NOS with distinct selectivity for NOS isoforms. In a cross-sectional study, we assessed whether ADMA is an independent predictor of airway resistance (Raw) in therapy-controlled asthma. METHODS: 154 therapy-controlled asthma patients were recruited. ADMA, symmetric dimethylarginine and arginine were quantitated by HPLC with fluorescent detection. Pulmonary function test was done using whole-body plethysmography, quality of life via St. George's Respiratory questionnaire (SGRQ). Multiple linear regression was used to identify independent determinants of Raw. The final model was stratified based on therapy control. RESULTS: Evidence for systemic inflammation indicated by CRP and procalcitonin was lacking in our sample. Log Raw showed significant positive correlation with log ADMA in the whole data set and well-controlled but not in the not well-controlled stratum (Spearman correlation coefficients: 0.27, p < 0.001; 0.30, p < 0.001; 0.12, p = 0.51 respectively). This relationship remained significant after adjusting for confounders by multiple linear regression (ß = 0.22, CI 0.054, 0.383 p = 0.01). FEF 25-75% % predicted and SGRQ Total score showed significant negative while SGRQ Activity score showed significant positive correlation with Raw in the final model. CONCLUSIONS: Positive correlation between Raw and ADMA in the absence of systemic inflammation implies that higher ADMA has detrimental effect on NO homeostasis and can contribute to a poor outcome in asthma.

Positive correlation of airway resistance and serum asymmetric dimethylarginine level in COPD patients with systemic markers of low-grade inflammation.

The major feature of COPD is a progressive airflow limitation caused by chronic airway inflammation and consequent airway remodeling. Modified arginase and nitric oxide synthase (NOS) pathways are presumed to contribute to the inflammation and fibrosis. Asymmetric dimethylarginine (ADMA) may shunt L-arginine from the NOS pathway to the arginase one by uncoupling and competitive inhibition of NOS and by enhancing arginase activity. To attest the interplay of these pathways, the relationship between ADMA and airflow limitation, described by airway resistance (Raw), was investigated in a cohort of COPD patients. Every COPD patient willing to give consent to participate (n=74) was included. Case history, laboratory parameters, serum arginine and ADMA, pulmonary function (whole-body plethysmography), and disease-specific quality of life (St George's Respiratory Questionnaire) were determined. Multiple linear regression was used to identify independent determinants of Raw. The final multiple model was stratified based on symptom control. The log Raw showed significant positive correlation with log ADMA in the whole sample (Pearson's correlation coefficient: 0.25, P=0.03). This association remained significant after adjusting for confounders in the whole data set (ß: 0.42; confidence interval [CI]: 0.06, 0.77; P=0.022) and in the worse-controlled stratum (ß: 0.84; CI: 0.25, 1.43; P=0.007). Percent predicted value of forced expiratory flow between 25% and 75% of forced vital capacity showed that significant negative, elevated C-reactive protein exhibited significant positive relationship with Raw in the final model. Positive correlation of Raw with ADMA in COPD patients showing evidence of a systemic low-grade inflammation implies that ADMA contributes to the progression of COPD, probably by shunting L-arginine from the NOS pathway to the arginase one.

'Proactive' use of cue-context congruence for building reinforcement learning's reward function.

BACKGROUND: Reinforcement learning is a fundamental form of learning that may be formalized using the Bellman equation. Accordingly an agent determines the state value as the sum of immediate reward and of the discounted value of future states. Thus the value of state is determined by agent related attributes (action set, policy, discount factor) and the agent's knowledge of the environment embodied by the reward function and hidden environmental factors given by the transition probability. The central objective of reinforcement learning is to solve these two functions outside the agent's control either using, or not using a model. RESULTS: In the present paper, using the proactive model of reinforcement learning we offer insight on how the brain creates simplified representations of the environment, and how these representations are organized to support the identification of relevant stimuli and action. Furthermore, we identify neurobiological correlates of our model by suggesting that the reward and policy functions, attributes of the Bellman equitation, are built by the orbitofrontal cortex (OFC) and the anterior cingulate cortex (ACC), respectively. CONCLUSIONS: Based on this we propose that the OFC assesses cue-context congruence to activate the most context frame. Furthermore given the bidirectional neuroanatomical link between the OFC and model-free structures, we suggest that model-based input is incorporated into the reward prediction error (RPE) signal, and conversely RPE signal may be used to update the reward-related information of context frames and the policy underlying action selection in the OFC and ACC, respectively. Furthermore clinical implications for cognitive behavioral interventions are discussed.