Endocannabinoids in neuroendopsychology: multiphasic control of mitochondrial function

The endocannabinoid system (ECS) is a construct based on the discovery of receptors that are modulated by the plant compound tetrahydrocannabinol and the subsequent identification of a family of nascent ligands, the 'endocannabinoids'. The function of the ECS is thus defined by modulation of these receptors-in particular, by two of the best-described ligands (2-arachidonyl glycerol and anandamide), and by their metabolic pathways. Endocannabinoids are released by cell stress, and promote both cell survival and death according to concentration. The ECS appears to shift the immune system towards a type 2 response, while maintaining a positive energy balance and reducing anxiety. It may therefore be important in resolution of injury and inflammation. Data suggest that the ECS could potentially modulate mitochondrial function by several different pathways; this may help explain its actions in the central nervous system. Dose-related control of mitochondrial function could therefore provide an insight into its role in health and disease, and why it might have its own pathology, and possibly, new therapeutic directions.

Metabolic phenotype modulation by caloric restriction in a lifelong dog study

Modeling aging and age-related pathologies presents a substantial analytical challenge given the complexity of gene−environment influences and interactions operating on an individual. A top-down systems approach is used to model the effects of lifelong caloric restriction, which is known to extend life span in several animal models. The metabolic phenotypes of caloric-restricted (CR; n = 24) and pair-housed control-fed (CF; n = 24) Labrador Retriever dogs were investigated by use of orthogonal projection to latent structures discriminant analysis (OPLS-DA) to model both generic and age-specific responses to caloric restriction from the 1H NMR blood serum profiles of young and older dogs. Three aging metabolic phenotypes were resolved: (i) an aging metabolic phenotype independent of diet, characterized by high levels of glutamine, creatinine, methylamine, dimethylamine, trimethylamine N-oxide, and glycerophosphocholine and decreasing levels of glycine, aspartate, creatine and citrate indicative of metabolic changes associated largely with muscle mass; (ii) an aging metabolic phenotype specific to CR dogs that consisted of relatively lower levels of glucose, acetate, choline, and tyrosine and relatively higher serum levels of phosphocholine with increased age in the CR population; (iii) an aging metabolic phenotype specific to CF dogs including lower levels of liproprotein fatty acyl groups and allantoin and relatively higher levels of formate with increased age in the CF population. There was no diet metabotype that consistently differentiated the CF and CR dogs irrespective of age. Glucose consistently discriminated between feeding regimes in dogs (≥312 weeks), being relatively lower in the CR group. However, it was observed that creatine and amino acids (valine, leucine, isoleucine, lysine, and phenylalanine) were lower in the CR dogs (<312 weeks), suggestive of differences in energy source utilization. 1H NMR spectroscopic analysis of longitudinal serum profiles enabled an unbiased evaluation of the metabolic markers modulated by a lifetime of caloric restriction and showed differences in the metabolic phenotype of aging due to caloric restriction, which contributes to longevity studies in caloric-restricted animals. Furthermore, OPLS-DA provided a framework such that significant metabolites relating to life extension could be differentiated and integrated with aging processes.

Hydrophilic interaction chromatography–mass spectrometry for anionic metabolic profiling of urine from antibiotic-treated rats

Hydrophilic interaction chromatography–mass spectrometry (HILIC–MS) was used for anionic metabolic profiling of urine from antibiotic-treated rats to study microbial–host co-metabolism. Rats were treated with the antibiotics penicillin G and streptomycin sulfate for four or eight days and compared to a control group. Urine samples were collected at day zero, four and eight, and analyzed by HILIC–MS. Multivariate data analysis was applied to the urinary metabolic profiles to identify biochemical variation between the treatment groups. Principal component analysis found a clear distinction between those animals receiving antibiotics and the control animals, with twenty-nine discriminatory compounds of which twenty were down-regulated and nine up-regulated upon treatment. In the treatment group receiving antibiotics for four days, a recovery effect was observed for seven compounds after cessation of antibiotic administration. Thirteen discriminatory compounds could be putatively identified based on their accurate mass, including aconitic acid, benzenediol sulfate, ferulic acid sulfate, hippuric acid, indoxyl sulfate, penicillin G, phenol and vanillin 4-sulfate. The rat urine samples had previously been analyzed by capillary electrophoresis (CE) with MS detection and proton nuclear magnetic resonance (1H NMR) spectroscopy. Using CE–MS and 1H NMR spectroscopy seventeen and twenty-five discriminatory compounds were found, respectively. Both hippuric acid and indoxyl sulfate were detected across all three platforms. Additionally, eight compounds were observed with both HILIC–MS and CE–MS. Overall, HILIC–MS appears to be highly complementary to CE–MS and 1H NMR spectroscopy, identifying additional compounds that discriminate the urine samples from antibiotic-treated and control rats.

The intelligence paradox; will ET get the metabolic syndrome? Lessons from and for Earth

Mankind is facing an unprecedented health challenge in the current pandemic of obesity and diabetes. We propose that this is the inevitable (and predictable) consequence of the evolution of intelligence, which itself could be an expression of life being an information system driven by entropy. Because of its ability to make life more adaptable and robust, intelligence evolved as an efficient adaptive response to the stresses arising from an ever-changing environment. These adaptive responses are encapsulated by the epiphenomena of “hormesis”, a phenomenon we believe to be central to the evolution of intelligence and essential for the maintenance of optimal physiological function and health. Thus, as intelligence evolved, it would eventually reach a cognitive level with the ability to control its environment through technology and have the ability remove all stressors. In effect, it would act to remove the very hormetic factors that had driven its evolution. Mankind may have reached this point, creating an environmental utopia that has reduced the very stimuli necessary for optimal health and the evolution of intelligence – “the intelligence paradox”. One of the hallmarks of this paradox is of course the rising incidence in obesity, diabetes and the metabolic syndrome. This leads to the conclusion that wherever life evolves, here on earth or in another part of the galaxy, the “intelligence paradox’” would be the inevitable side-effect of the evolution of intelligence. ET may not need to just “phone home” but may also need to “phone the local gym”. This suggests another possible reason to explain Fermi’s paradox; Enrico Fermi, the famous physicist, suggested in the 1950s that if extra-terrestrial intelligence was so prevalent, which was a common belief at the time, then where was it? Our suggestion is that if advanced life has got going elsewhere in our galaxy, it can’t afford to explore the galaxy because it has to pay its healthcare costs.

Insulin resistance determines a differential response to changes in dietary fat modification on metabolic syndrome risk factors: the LIPGENE study

Background: Previous data support the benefits of reducing dietary saturated fatty acids (SFAs) on insulin resistance (IR) and other metabolic risk factors. However, whether the IR status of those suffering from metabolic syndrome (MetS) affects this response is not established. OBJECTIVE: Our objective was to determine whether the degree of IR influences the effect of substituting high-saturated fatty acid (HSFA) diets by isoenergetic alterations in the quality and quantity of dietary fat on MetS risk factors. DESIGN: In this single-blind, parallel, controlled, dietary intervention study, MetS subjects (n = 472) from 8 European countries classified by different IR levels according to homeostasis model assessment of insulin resistance (HOMA-IR) were randomly assigned to 4 diets: an HSFA diet; a high-monounsaturated fatty acid (HMUFA) diet; a low-fat, high-complex carbohydrate (LFHCC) diet supplemented with long-chain n-3 polyunsaturated fatty acids (1.2 g/d); or an LFHCC diet supplemented with placebo for 12 wk (control). Anthropometric, lipid, inflammatory, and IR markers were determined. RESULTS: Insulin-resistant MetS subjects with the highest HOMA-IR improved IR, with reduced insulin and HOMA-IR concentrations after consumption of the HMUFA and LFHCC n-3 diets (P < 0.05). In contrast, subjects with lower HOMA-IR showed reduced body mass index and waist circumference after consumption of the LFHCC control and LFHCC n-3 diets and increased HDL cholesterol concentrations after consumption of the HMUFA and HSFA diets (P < 0.05). MetS subjects with a low to medium HOMA-IR exhibited reduced blood pressure, triglyceride, and LDL cholesterol levels after the LFHCC n-3 diet and increased apolipoprotein A-I concentrations after consumption of the HMUFA and HSFA diets (all P < 0.05). CONCLUSIONS: Insulin-resistant MetS subjects with more metabolic complications responded differently to dietary fat modification, being more susceptible to a health effect from the substitution of SFAs in the HMUFA and LFHCC n-3 diets. Conversely, MetS subjects without IR may be more sensitive to the detrimental effects of HSFA intake. The metabolic phenotype of subjects clearly determines response to the quantity and quality of dietary fat on MetS risk factors, which suggests that targeted and personalized dietary therapies may be of value for its different metabolic features.