Food perception and postprandial lipid metabolism

A comprehensive review on impact of non-thermal processing on the structural changes of food components

Non-thermal food processing is a viable alternative to traditional thermal processing to meet customer needs for high-quality, convenient and minimally processed foods. They are designed to eliminate elevated temperatures during processing and avoid the adverse effects of heat on food products. Numerous thermal and novel non-thermal technologies influence food structure at the micro and macroscopic levels. They affect several properties such as rheology, flavour, process stability, texture, and appearance at microscopic and macroscopic levels. This review presents existing knowledge and advances on the impact of non-thermal technologies, for instance, cold plasma treatment, irradiation, high-pressure processing, ultrasonication, pulsed light technology, high voltage electric field and pulsed electric field treatment on the structural changes of food components. An extensive review of the literature indicates that different non-thermal processing technologies can affect the food components, which significantly affects the structure of food. Applications of novel non-thermal technologies have shown considerable impact on food structure by altering protein structures via free radicals or larger or smaller molecules. Lipid oxidation is another process responsible for undesirable effects in food when treated with non-thermal techniques. Non-thermal technologies may also affect starch properties, reduce molecular weight, and change the starch granule's surface. Such modification of food structure could create novel food textures, enhance sensory properties, improve digestibility, improve water-binding ability and improve mediation of gelation processes. However, it is challenging to determine these technologies' influence on food components due to differences in their primary operation and equipment design mechanisms and different operating conditions. Hence, to get the most value from non-thermal technologies, more in-depth research about their effect on various food components is required.

Fatty acid transporter CD36 mediates hypothalamic effect of fatty acids on food intake in rats

Variations in plasma fatty acid (FA) concentrations are detected by FA sensing neurons in specific brain areas such as the hypothalamus. These neurons play a physiological role in the control of food intake and the regulation of hepatic glucose production. Le Foll et al. previously showed in vitro that at least 50% of the FA sensing in ventromedial hypothalamic (VMH) neurons is attributable to the interaction of long chain FA with FA translocase/CD36 (CD36). The present work assessed whether in vivo effects of hypothalamic FA sensing might be partly mediated by CD36 or intracellular events such as acylCoA synthesis or β-oxidation. To that end, a catheter was implanted in the carotid artery toward the brain in male Wistar rats. After 1 wk recovery, animals were food-deprived for 5 h, then 10 min infusions of triglyceride emulsion, Intralipid +/− heparin (IL, IL_H, respectively) or saline/heparin (S_H) were carried out and food intake was assessed over the next 5 h. Experimental groups included: 1) Rats previously injected in ventromedian nucleus (VMN) with shRNA against CD36 or scrambled RNA; 2) Etomoxir (CPT1 inhibitor) or saline co-infused with IL_H/S_H; and 3) Triacsin C (acylCoA synthase inhibitor) or saline co-infused with IL_H/S_H. IL_H significantly lowered food intake during refeeding compared to S_H (p<0.001). Five hours after refeeding, etomoxir did not affect this inhibitory effect of IL_H on food intake while VMN CD36 depletion totally prevented it. Triacsin C also prevented IL_H effects on food intake. In conclusion, the effect of FA to inhibit food intake is dependent on VMN CD36 and acylCoA synthesis but does not required FA oxidation.

Effects of oral and gastric stimulation on appetite and energy intake

Appetite is regulated by many factors, including oro-sensory and gastric signals. There are many studies on contributions of and possible interaction between sensory and gastric stimulation, but there are few studies in humans using simultaneous oral and gastric stimulation. We investigated the effect of simultaneous, but independently manipulated, oral and gastric stimulation on appetite ratings and energy intake. We hypothesized that compared with no stimulation, oral and gastric stimulation would equally and additively decrease appetite ratings and energy intake. Healthy men (n = 26, 21 ± 2 years, BMI 22 ± 3 kg/m(2)) participated in a randomized crossover trial with four experimental conditions and a control condition. Experimental conditions consisted of oral stimulation, with either 1 or 8 min modified sham feeding (MSF), and gastric stimulation, with either 100 or 800 ml intragastrically infused liquid (isocaloric, 99 kcal, 100 ml/min). The control condition consisted of no oral or gastric stimulation. Outcome measures were energy intake 30 min after the treatment and appetite ratings. Compared with the control condition, energy intake decreased significantly after the 8 min/100 ml (19% lower, P = 0.001) and 8 min/800 ml conditions (15% lower, P = 0.02), but not after the 1 min/100 ml (14% lower, P = 0.06) and 1 min/800 ml conditions (10% lower, P = 0.39). There was no interaction of oral and gastric stimulation on energy intake. Hunger and fullness differed across all conditions (P ≤ 0.01). In conclusion, duration of oral exposure was at least as important in decreasing energy intake as gastric filling volume. Oral and gastric stimulation did not additively decrease energy intake. Longer oro-sensory stimulation, therefore, may be an important contributor to a lower energy intake.

Why liquid energy results in overconsumption

Liquids have been shown to have a low satiating efficiency. The may be related to the high rate of consumption for liquids which may be higher than 200 g/min. In a number of studies, we showed that the positive relationship between eating rate and energy intake is mediated by oro-sensory exposure time. Longer sensory exposure times are consistently associated with lower food intakes. This observation maybe linked to the role of cephalic phase responses to foods. Cephalic phase responses are a set of physiological responses, which are conceived to prepare the digestive system for the incoming flow of nutrients after ingestion, with the aim of maintaining homeostasis. Results from various studies suggest that cephalic phase responses are much smaller (absent) for liquids compared to solids. It is hypothesised that the absence of cephalic phase responses to liquid foods may be one of the causes why liquid energies enter the body undetected and lead to weak energy intake compensation. This idea fits with the concept of the taste system as a nutrient-sensing system that informs the brain and the gastro-intestinal system about what is coming into our body. With liquids, this system is bypassed. Slower eating may help the human body to associate the sensory signals from food with their metabolic consequences. Foods that are eaten quickly may impair this association, and may therefore lead to overconsumption of energy, and ultimately to weight gain.

Dopamine counteracts octopamine signalling in a neural circuit mediating food response in C. elegans

Animals assess food availability in their environment by sensory perception and respond to the absence of food by changing hormone and neurotransmitter signals. However, it is largely unknown how the absence of food is perceived at the level of functional neurocircuitry. In Caenorhabditis elegans, octopamine is released from the RIC neurons in the absence of food and activates the cyclic AMP response element binding protein in the cholinergic SIA neurons. In contrast, dopamine is released from dopaminergic neurons only in the presence of food. Here, we show that dopamine suppresses octopamine signalling through two D2-like dopamine receptors and the G protein Gi/o. The D2-like receptors work in both the octopaminergic neurons and the octopamine-responding SIA neurons, suggesting that dopamine suppresses octopamine release as well as octopamine-mediated downstream signalling. Our results show that C. elegans detects the absence of food by using a small neural circuit composed of three neuron types in which octopaminergic signalling is activated by the cessation of dopamine signalling.

NEFA minimal model parameters estimated from the oral glucose tolerance test and the meal tolerance test

The kinetics of nonesterified fatty acid (NEFA) metabolism in humans requires quantification to facilitate understanding of diseases like type 1 and 2 diabetes, metabolic syndrome, and obesity, and the mechanisms underpinning various interventions. Oral glucose tolerance tests (OGTT) and glucose meal tolerance tests (MTT) are potentially useful procedures for enabling quantification of NEFA kinetics because they both cause transitory, but substantial, declines and then rebounds in plasma NEFA concentrations in response to physiologically relevant increases in plasma glucose. The Boston MINIMAL model of NEFA kinetics was developed to analyze data from the intravenous glucose tolerance test (IVGTT), but in this work, we present for the first time its application to modeling NEFA data from both OGTT and MTT studies. This model enables estimation of SFFA (micromol.l(-1).min(-1)) (a parameter describing the maximum rate of lipolysis), and KFFA (%/min) (a parameter related to NEFA oxidation rate). The model could well describe the trajectories of NEFA concentrations following an OGTT (R2 in excess of 0.97) but was not as successful with the MTT (R2>0.65). Model parameters derived from analysis of OGTT and MTT data were well identified with coefficients of variation generally less than 15%. Type 2 diabetes, body mass index, and dietary treatment (high-fat vs. high-glycemic-index diets) were all shown to have significant effects on model parameters. Modeling plasma NEFA concentrations over 24 h has helped to identify and quantify the extent that periprandial NEFA peaks and nocturnal elevation in plasma NEFA can be accounted for by our model.