A Functional Magnetic Resonance Imaging Predictor of Treatment Response to Venlafaxine in Generalized Anxiety Disorder

Background: Functional magnetic resonance imaging (fMRI) holds promise as a noninvasive means of identifying neural responses that can be used to predict treatment response before beginning a drug trial. Imaging paradigms employing facial expressions as presented stimuli have been shown to activate the amygdala and anterior cingulate cortex (ACC). Here, we sought to determine whether pretreatment amygdala and rostral ACC (rACC) reactivity to facial expressions could predict treatment outcomes in patients with generalized anxiety disorder (GAD).Methods: Fifteen subjects (12 female subjects) with GAD participated in an open-label venlafaxine treatment trial. Functional magnetic resonance imaging responses to facial expressions of emotion collected before subjects began treatment were compared with changes in anxiety following 8 weeks of venlafaxine administration. In addition, the magnitude of fMRI responses of subjects with GAD were compared with that of 15 control subjects (12 female subjects) who did not have GAD and did not receive venlafaxine treatment.Results The magnitude of treatment response was predicted by greater pretreatment reactivity to fearful faces in rACC and lesser reactivity in the amygdala. These individual differences in pretreatment rACC and amygdala reactivity within the GAD group were observed despite the fact that 1) the overall magnitude of pretreatment rACC and amygdala reactivity did not differ between subjects with GAD and control subjects and 2) there was no main effect of treatment on rACC-amygdala reactivity in the GAD group.Conclusions: These findings show that this pattern of rACC-amygdala responsivity could prove useful as a predictor of venlafaxine treatment response in patients with GAD.

Damage rate is a predictor of fatigue life and creep strain rate in fatigue of tensile human cortical bone samples

We present results on the growth of damage in 29 fatigue tests of human femoral cortical bone from four individuals, aged 53–79. In these tests we examine the interdependency of stress, cycles to failure, rate of creep strain, and rate of modulus loss. The behavior of creep rates has been reported recently for the same donors as an effect of stress and cycles (Cotton, J. R., Zioupos, P., Winwood, K., and Taylor, M., 2003, "Analysis of Creep Strain During Tensile Fatigue of Cortical Bone," J. Biomech. 36, pp. 943–949). In the present paper we first examine how the evolution of damage (drop in modulus per cycle) is associated with the stress level or the "normalized stress" level (stress divided by specimen modulus), and results show the rate of modulus loss fits better as a function of normalized stress. However, we find here that even better correlations can be established between either the cycles to failure or creep rates versus rates of damage than any of these three measures versus normalized stress. The data indicate that damage rates can be excellent predictors of fatigue life and creep strain rates in tensile fatigue of human cortical bone for use in practical problems and computer simulations.

Verification and FPGA circuits of a block-2 fast path-based predictor

This paper formally derives a new path-based neural branch prediction algorithm (FPP) into blocks of size two for a lower hardware solution while maintaining similar input-output characteristic to the algorithm. The blocked solution, here referred to as B2P algorithm, is obtained using graph theory and retiming methods. Verification approaches were exercised to show that prediction performances obtained from the FPP and B2P algorithms differ within one mis-prediction per thousand instructions using a known framework for branch prediction evaluation. For a chosen FPGA device, circuits generated from the B2P algorithm showed average area savings of over 25% against circuits for the FPP algorithm with similar time performances thus making the proposed blocked predictor superior from a practical viewpoint.

A new organization for a perceptron-based branch predictor and its FPGA implementation

An unaltered rearrangement of the original computation of a neural based predictor at the algorithmic level is introduced as a new organization. Its FPGA implementation generates circuits that are 1.7 faster than a direct implementation of the original algorithm. This faster clock rate allows to implement predictors with longer history lengths using the nearly the same hardware budget.

FPGA organization for the fast path-based neural branch predictor

This paper develops cycle-level FPGA circuits of an organization for a fast path-based neural branch predictor Our results suggest that practical sizes of prediction tables are limited to around 32 KB to 64 KB in current FPGA technology due mainly to FPGA area of logic resources to maintain the tables. However the predictor scales well in terms of prediction speed. Table sizes alone should not be used as the only metric for hardware budget when comparing neural-based predictor to predictors of totally different organizations. This paper also gives early evidence to shift the attention on to the recovery from mis-prediction latency rather than on prediction latency as the most critical factor impacting accuracy of predictions for this class of branch predictors.

Lipoprotein (a) as a predictor of myocardial infarction in middle-aged men

We found that a high Lp(a) level was an independent predictor of the development of coronary heart disease in middle-aged men.

Development of colour and firmness in strawberry crops is UV light sensitive, but colour is not a good predictor of several quality parameters

BACKGROUND: Strawberry (Fragaria × ananassa Duchesne var. Elsanta) plants were grown in polytunnels covered with three polythene films that transmitted varying levels of ultraviolet (UV) light. Fruit were harvested under near-commercial conditions and quality and yield were measured. During ripening, changes in the colour parameters of individual fruit were monitored, and the accuracy of using surface colour to predict other quality parameters was determined by analysing the correlation between colour and quality parameters within UV treatments. RESULTS: Higher exposure to UV during growth resulted in the fruit becoming darker at harvest and developing surface colour more quickly; fruit were also firmer at harvest, but shelf life was not consistently affected by the UV regime. Surface colour measurements were poorly correlated to firmness, shelf life or total phenolics, anthocyanins and ellagic acid contents. CONCLUSION: Although surface colour of strawberry fruits was affected by the UV regime during growth, and this parameter is an important factor in consumer perception, we concluded that the surface colour at the time of harvest was, contrary to consumer expectations, a poor indicator of firmness, potential shelf life or anthocyanin content. Copyright © 2011 Society of Chemical Industry

Receptor binding profiles of avian influenza virus hemagglutinin subtypes on human cells as a predictor of pandemic potential

The host adaptation of influenza virus is partly dependent on the sialic acid (SA) isoform bound by the viral hemagglutinin (HA). Avian influenza viruses preferentially bind the α-2,3 SA and human influenza viruses the α-2,6 isoform. Each isoform is predominantly associated with different surface epithelial cell types of the human upper airway. Using recombinant HAs and human tracheal airway epithelial cells in vitro and ex vivo, we show that many avian HA subtypes do not adhere to this canonical view of SA specificity. The propensity of avian viruses to adapt to human receptors may thus be more widespread than previously supposed.

Is fatty acid intake a predictor of arterial stiffness and blood pressure in men? Evidence from the Caerphilly Prospective Study

Background and aims: Arterial stiffness is an independent predictor of cardiovascular disease (CVD) events and all-cause mortality and may be differentially affected by dietary fatty acid (FA) intake. The aim of this study was to investigate the relationship between FA consumption and arterial stiffness and blood pressure in a community-based population. Methods and results: The Caerphilly Prospective Study recruited 2398 men, aged 45-59 years, who were followed up at 5-year intervals for a mean of 17.8-years (n 787). A semi-quantitative food frequency questionnaire estimated intakes of total, saturated, mono- and poly-unsaturated fatty acids (SFA, MUFA, PUFA). Multiple regression models investigated associations between intakes of FA at baseline with aortic pulse wave velocity (aPWV), augmentation index (AIx), systolic and diastolic blood pressure (SBP, DBP) and pulse pressure after a 17.8-year follow-up - as well as cross-sectional relationships with metabolic markers. After adjustment, higher SFA consumption at baseline was associated with higher SBP (P = 0.043) and DBP (P = 0.002) and after a 17.8-year follow-up was associated with a 0.51 m/s higher aPWV (P = 0.006). After adjustment, higher PUFA consumption at baseline was associated with lower SBP (P = 0.022) and DBP (P = 0.036) and after a 17.8-year follow-up was associated with a 0.63 m/s lower aPWV (P = 0.007). Conclusion: This study suggests that consumption of SFA and PUFA have opposing effects on arterial stiffness and blood pressure. Importantly, this study suggests that consumption of FA is an important risk factor for arterial stiffness and CVD.

Recovery based on plot experiments is a poor predictor of landscape-level population impacts of agricultural pesticides

Current European Union regulatory risk assessment allows application of pesticides provided that recovery of nontarget arthropods in-crop occurs within a year. Despite the long-established theory of source-sink dynamics, risk assessment ignores depletion of surrounding populations and typical field trials are restricted to plot-scale experiments. In the present study, the authors used agent-based modeling of 2 contrasting invertebrates, a spider and a beetle, to assess how the area of pesticide application and environmental half-life affect the assessment of recovery at the plot scale and impact the population at the landscape scale. Small-scale plot experiments were simulated for pesticides with different application rates and environmental half-lives. The same pesticides were then evaluated at the landscape scale (10 km × 10 km) assuming continuous year-on-year usage. The authors' results show that recovery time estimated from plot experiments is a poor indicator of long-term population impact at the landscape level and that the spatial scale of pesticide application strongly determines population-level impact. This raises serious doubts as to the utility of plot-recovery experiments in pesticide regulatory risk assessment for population-level protection. Predictions from the model are supported by empirical evidence from a series of studies carried out in the decade starting in 1988. The issues raised then can now be addressed using simulation. Prediction of impacts at landscape scales should be more widely used in assessing the risks posed by environmental stressors.