Simulation of Preterm Neonatal Brain Metabolism During Functional Neuronal Activation Using a Computational Model.

We present a computational model of metabolism in the preterm neonatal brain. The model has the capacity to mimic haemodynamic and metabolic changes during functional activation and simulate functional near-infrared spectroscopy (fNIRS) data. As an initial test of the model's efficacy, we simulate data obtained from published studies investigating functional activity in preterm neonates. In addition we simulated recently collected data from preterm neonates during visual activation. The model is well able to predict the haemodynamic and metabolic changes from these observations. In particular, we found that changes in cerebral blood flow and blood pressure may account for the observed variability of the magnitude and sign of stimulus-evoked haemodynamic changes reported in preterm infants.

Simulating NIRS and MRS measurements during cerebral hypoxia-ischaemia in piglets using a computational model.

We present a group analysis of the changes in cerebral haemodynamics, and the oxidation state of cytochrome-c-oxidase measured using broadband near-infrared spectroscopy (NIRS) and intracellular pH measured by phosphorous ((31)P) magnetic resonance spectroscopy (MRS) during and after cerebral hypoxia-ischaemia (HI) in 15 piglets. We use a previously published computational model of cerebral metabolism in the piglet [1] to integrate these measurements and simulate HI. We successfully simulate changes in cellular metabolism including shifts in intracellular pH observed in the piglet brain during HI. In this process, we optimise physiological parameters in the model identified through sensitivity analysis (such as the rate of glucose metabolism and intracellular lactate concentration), to fit simulated and measured data. The model fits the data reasonably and suggests a 20 % drop in glucose consumption, a ~65 % increase in lactate concentration and ~35 % drop in the cerebral metabolic rate of oxygen (CMRO2) during HI.

Advanced Cancer Patients' Prognostic Awareness and Its Association With Anxiety, Depression and Spiritual Well-Being: A Multi-Country Study in Asia.

AIMS: The associations between prognostic awareness, acceptance of illness and psychological outcomes (anxiety, depression and spiritual well-being) remain unclear. This study examined the associations between prognostic awareness and various psychological outcomes and how they can be moderated by patient acceptance of illness (cancer). MATERIALS AND METHODS: In total, 1184 patients with stage IV solid cancer were recruited at major public hospitals across four Asian countries (China, India, Sri Lanka, Vietnam). Prognostic awareness and acceptance of illness were assessed through self-reported understanding of treatment intent and acceptance of illness, respectively. Anxiety and depression were assessed using the Hospital Anxiety and Depression Scale, whereas spiritual well-being was measured using the Functional Assessment of Chronic Illness Therapy - Spiritual Well-Being Scale. Multivariate regressions were used to estimate the associations while controlling for patient characteristics. RESULTS: Compared with being unaware of their prognosis (i.e. believing that their cancer is curable), being aware or unsure of their prognosis was associated with higher anxiety and depressive symptoms, and lower spiritual well-being scores. Acceptance of illness moderated these relationships and improved the psychological outcomes. CONCLUSIONS: The results suggest that disclosure of prognostic information should be provided in conjunction with psychological interventions that focus on acceptance of illness.