Quantification of the novel N-methyl-D-aspartate receptor ligand [11C]GMOM in man

[11C]GMOM (carbon-11 labeled N-(2-chloro-5-thiomethylphenyl)-N0-(3-[11C]methoxy-phenyl)-N0-methylguanidine) is a PET ligand that binds to the N-methyl-D-aspartate receptor with high specificity and affinity. The purpose of this first in human study was to evaluate kinetics of [11C]GMOM in the healthy human brain and to identify the optimal pharmacokinetic model for quantifying these kinetics, both before and after a pharmacological dose of S-ketamine. Dynamic 90 min [11C]GMOM PET scans were obtained from 10 subjects. In six of the 10 subjects, a second PET scan was performed following an S-ketamine challenge. Metabolite corrected plasma input functions were obtained for all scans. Regional time activity curves were fitted to various single- and two-tissue compartment models. Best fits were obtained using a two-tissue irreversible model with blood volume parameter. The highest net influx rate (Ki) of [11C]GMOM was observed in regions with high N-methyl-D-aspartate receptor density, such as hippocampus and thalamus. A significant reduction in the Ki was observed for the entire brain after administration of ketamine, suggesting specific binding to the N-methyl-D-aspartate receptors. This initial study suggests that the [11C]GMOM could be used for quantification of N-methyl-D-aspartate receptors

In vivo (R)-[(11)C]PK11195 PET imaging of 18kDa translocator protein in recent onset psychosis

Evidence is accumulating that immune dysfunction is involved in the pathophysiology of schizophrenia. It has been hypothesized that microglia activation is present in patients with schizophrenia. Various in vivo and post-mortem studies have investigated this hypothesis, but as yet with inconclusive results. Microglia activation is associated with elevations in 18 kDa translocator protein (TSPO) levels, which can be measured with the positron emission tomography (PET) tracer (R)-[11C]PK11195. The purpose of the present study was to investigate microglia activation in psychosis in vivo at an early stage of the disease. (R)-[11C]PK11195 binding potential (BP ND) was measured in 19 patients with recent onset psychosis and 17 age and gender-matched healthy controls. Total gray matter, as well as five gray matter regions of interest (frontal cortex, temporal cortex, parietal cortex, striatum, and thalamus) were defined a priori. PET data were analysed using a reference tissue approach and a supervised cluster analysis algorithm to identify the reference region. No significant difference in (R)-[11C]PK11195 BP ND between patients and controls was found in total gray matter, nor one of the regions of interest. These findings suggest that microglia activation is not present in recent onset psychosis or that it is a subtle phenomenon that could not be detected using the design of the present study

In vivo (R)-[(11)C]PK11195 PET imaging of 18kDa translocator protein in recent onset psychosis

Evidence is accumulating that immune dysfunction is involved in the pathophysiology of schizophrenia. It has been hypothesized that microglia activation is present in patients with schizophrenia. Various in vivo and post-mortem studies have investigated this hypothesis, but as yet with inconclusive results. Microglia activation is associated with elevations in 18 kDa translocator protein (TSPO) levels, which can be measured with the positron emission tomography (PET) tracer (R)-[(11)C]PK11195. The purpose of the present study was to investigate microglia activation in psychosis in vivo at an early stage of the disease. (R)-[(11)C]PK11195 binding potential (BPND) was measured in 19 patients with recent onset psychosis and 17 age and gender-matched healthy controls. Total gray matter, as well as five gray matter regions of interest (frontal cortex, temporal cortex, parietal cortex, striatum, and thalamus) were defined a priori. PET data were analysed using a reference tissue approach and a supervised cluster analysis algorithm to identify the reference region. No significant difference in (R)-[(11)C]PK11195 BPND between patients and controls was found in total gray matter, nor one of the regions of interest. These findings suggest that microglia activation is not present in recent onset psychosis or that it is a subtle phenomenon that could not be detected using the design of the present stud

Effectiveness of nutritional interventions in older adults at risk of malnutrition across different health care settings: Pooled analyses of individual participant data from nine randomized controlled trials

Background & aims: Protein-energy malnutrition is a health concern among older adults. Improving nutritional status by increasing energy and protein intake likely benefits health. We therefore aimed to investigate effects of nutritional interventions in older adults (at risk of malnutrition) on change in energy intake and body weight, and explore if the intervention effect was modified by study or participants’ characteristics, analysing pooled individual participant data. Methods: We searched for RCTs investigating the effect of dietary counseling, oral nutritional supplements (ONS) or both on energy intake and weight. Principle investigators of eligible studies provided individual participant data. We investigated the effect of nutritional intervention on meaningful increase in energy intake (>250 kcal/day) and meaningful weight gain (>1.0 kg). Logistic generalized estimating equations were performed and ORs with 95% CIs presented. Results: We included data of nine studies with a total of 990 participants, aged 79.2 ± 8.2 years, 64.5% women and mean baseline BMI 23.9 ± 4.7 kg/m2. An non-significant intervention effect was observed for increase in energy intake (OR:1.59; 95% CI 0.95, 2.66) and a significant intervention effect for weight gain (OR:1.58; 95% CI 1.16, 2.17). Stratifying by type of intervention, an intervention effect on increase in energy intake was only observed for dietary counseling in combination with ONS (OR:2.28; 95% CI 1.90, 2.73). The intervention effect on increase in energy intake was greater for women, older participants, and those with lower BMI. Regarding weight gain, an intervention effect was observed for dietary counseling (OR:1.40; 95% CI 1.14, 1.73) and dietary counseling in combination with ONS (OR:2.48; 95% CI 1.92, 3.31). The intervention effect on weight gain was not influenced by participants’ characteristics. Conclusions: Based on pooled data of older adults (at risk of malnutrition), nutritional interventions have a positive effect on energy intake and body weight. Dietary counseling combined with ONS is the most effective intervention.</p

Effectiveness of nutritional interventions in older adults at risk of malnutrition across different health care settings: Pooled analyses of individual participant data from nine randomized controlled trials

Background & aims: Protein-energy malnutrition is a health concern among older adults. Improving nutritional status by increasing energy and protein intake likely benefits health. We therefore aimed to investigate effects of nutritional interventions in older adults (at risk of malnutrition) on change in energy intake and body weight, and explore if the intervention effect was modified by study or participants’ characteristics, analysing pooled individual participant data. Methods: We searched for RCTs investigating the effect of dietary counseling, oral nutritional supplements (ONS) or both on energy intake and weight. Principle investigators of eligible studies provided individual participant data. We investigated the effect of nutritional intervention on meaningful increase in energy intake (>250 kcal/day) and meaningful weight gain (>1.0 kg). Logistic generalized estimating equations were performed and ORs with 95% CIs presented. Results: We included data of nine studies with a total of 990 participants, aged 79.2 ± 8.2 years, 64.5% women and mean baseline BMI 23.9 ± 4.7 kg/m2. An non-significant intervention effect was observed for increase in energy intake (OR:1.59; 95% CI 0.95, 2.66) and a significant intervention effect for weight gain (OR:1.58; 95% CI 1.16, 2.17). Stratifying by type of intervention, an intervention effect on increase in energy intake was only observed for dietary counseling in combination with ONS (OR:2.28; 95% CI 1.90, 2.73). The intervention effect on increase in energy intake was greater for women, older participants, and those with lower BMI. Regarding weight gain, an intervention effect was observed for dietary counseling (OR:1.40; 95% CI 1.14, 1.73) and dietary counseling in combination with ONS (OR:2.48; 95% CI 1.92, 3.31). The intervention effect on weight gain was not influenced by participants’ characteristics. Conclusions: Based on pooled data of older adults (at risk of malnutrition), nutritional interventions have a positive effect on energy intake and body weight. Dietary counseling combined with ONS is the most effective intervention

Effects of Nutritional Interventions in Older Adults with Malnutrition or at Risk of Malnutrition on Muscle Strength and Mortality: Results of Pooled Analyses of Individual Participant Data from Nine RCTs

Nutritional intervention studies in older adults with malnutrition aim to improve nutritional status. Although these studies show a significant gain in body weight, there is inconsistent evidence of clinical effectiveness on muscle strength and mortality. This study aimed to examine the effects of nutritional interventions on muscle strength and risk of mortality in older adults (malnourished or at risk) and explore whether these effects are influenced by participant characteristics. Individual participant data were used from nine RCTs (community setting, hospital and long-term care; duration 12–24 weeks and included oral nutritional supplements, dietary counseling, or both). Handgrip strength (HGS) was measured in seven RCTs and six RCTs obtained mortality data. A ≥3 kg increase in HGS was considered clinically relevant. Logistic generalized estimating equations analyses (GEE) were used to test intervention effectiveness. GEE showed no overall treatment effect (OR 1.11, 95% CI 0.78–1.59) on HGS. A greater, but not statistically significant, effect on HGS was observed for older (>80 years) versus younger participants. No significant treatment effect was observed for mortality (OR 0.78, 95% CI 0.42–1.46). The treatment effect on mortality was greater but remained non-significant for women and those with higher baseline energy or protein intake. In conclusion, no effects of nutritional interventions were observed on HGS and mortality in older adults (malnourished or at risk). While the treatment effect was modified by some baseline participant characteristics, the treatment also lacked an effect in most subgroups