Spread in climate policy scenarios unravelled.

Analysis of climate policy scenarios has become an important tool for identifying mitigation strategies, as shown in the latest Intergovernmental Panel on Climate Change Working Group III report1. The key outcomes of these scenarios differ substantially not only because of model and climate target differences but also because of different assumptions on behavioural, technological and socio-economic developments2-4. A comprehensive attribution of the spread in climate policy scenarios helps policymakers, stakeholders and scientists to cope with large uncertainties in this field. Here we attribute this spread to the underlying drivers using Sobol decomposition5, yielding the importance of each driver for scenario outcomes. As expected, the climate target explains most of the spread in greenhouse gas emissions, total and sectoral fossil fuel use, total renewable energy and total carbon capture and storage in electricity generation. Unexpectedly, model differences drive variation of most other scenario outcomes, for example, in individual renewable and carbon capture and storage technologies, and energy in demand sectors, reflecting intrinsic uncertainties about long-term developments and the range of possible mitigation strategies. Only a few scenario outcomes, such as hydrogen use, are driven by other scenario assumptions, reflecting the need for more scenario differentiation. This attribution analysis distinguishes areas of consensus as well as strong model dependency, providing a crucial step in correctly interpreting scenario results for robust decision-making.

Reducing societal impacts of SARS-CoV-2 interventions through subnational implementation.

To curb the initial spread of SARS-CoV-2, many countries relied on nation-wide implementation of non-pharmaceutical intervention measures, resulting in substantial socio-economic impacts. Potentially, subnational implementations might have had less of a societal impact, but comparable epidemiological impact. Here, using the first COVID-19 wave in the Netherlands as a case in point, we address this issue by developing a high-resolution analysis framework that uses a demographically stratified population and a spatially explicit, dynamic, individual contact-pattern based epidemiology, calibrated to hospital admissions data and mobility trends extracted from mobile phone signals and Google. We demonstrate how a subnational approach could achieve similar level of epidemiological control in terms of hospital admissions, while some parts of the country could stay open for a longer period. Our framework is exportable to other countries and settings, and may be used to develop policies on subnational approach as a better strategic choice for controlling future epidemics.

Comparing energy system optimization models and integrated assessment models: Relevance for energy policy advice.

Background: The transition to a climate neutral society such as that envisaged in the European Union Green Deal requires careful and comprehensive planning. Integrated assessment models (IAMs) and energy system optimisation models (ESOMs) are both commonly used for policy advice and in the process of policy design. In Europe, a vast landscape of these models has emerged and both kinds of models have been part of numerous model comparison and model linking exercises. However, IAMs and ESOMs have rarely been compared or linked with one another. Methods: This study conducts an explorative comparison and identifies possible flows of information between 11 of the integrated assessment and energy system models in the European Climate and Energy Modelling Forum. The study identifies and compares regional aggregations and commonly reported variables. We define harmonised regions and a subset of shared result variables that enable the comparison of scenario results across the models. Results: The results highlight how power generation and demand development are related and driven by regional and sectoral drivers. They also show that demand developments like for hydrogen can be linked with power generation potentials such as onshore wind power. Lastly, the results show that the role of nuclear power is related to the availability of wind resources. Conclusions: This comparison and analysis of modelling results across model type boundaries provides modellers and policymakers with a better understanding of how to interpret both IAM and ESOM results. It also highlights the need for community standards for region definitions and information about reported variables to facilitate future comparisons of this kind. The comparison shows that regional aggregations might conceal differences within regions that are potentially of interest for national policy makers thereby indicating a need for national-level analysis.

Hidden dependence of spreading vulnerability on topological complexity.

Many dynamical phenomena in complex systems concern spreading that plays out on top of networks with changing architecture over time-commonly known as temporal networks. A complex system's proneness to facilitate spreading phenomena, which we abbreviate as its "spreading vulnerability," is often surmised to be related to the topology of the temporal network featured by the system. Yet, cleanly extracting spreading vulnerability of a complex system directly from the topological information of the temporal network remains a challenge. Here, using data from a diverse set of real-world complex systems, we develop the "entropy of temporal entanglement" as a quantity to measure topological complexities of temporal networks. We show that this parameter-free quantity naturally allows for topological comparisons across vastly different complex systems. Importantly, by simulating three different types of stochastic dynamical processes playing out on top of temporal networks, we demonstrate that the entropy of temporal entanglement serves as a quantitative embodiment of the systems' spreading vulnerability, irrespective of the details of the processes. In being able to do so, i.e., in being able to quantitatively extract a complex system's proneness to facilitate spreading phenomena from topology, this entropic measure opens itself for applications in a wide variety of natural, social, biological, and engineered systems.

Quantifying agent impacts on contact sequences in social interactions.

Human social behavior plays a crucial role in how pathogens like SARS-CoV-2 or fake news spread in a population. Social interactions determine the contact network among individuals, while spreading, requiring individual-to-individual transmission, takes place on top of the network. Studying the topological aspects of a contact network, therefore, not only has the potential of leading to valuable insights into how the behavior of individuals impacts spreading phenomena, but it may also open up possibilities for devising effective behavioral interventions. Because of the temporal nature of interactions-since the topology of the network, containing who is in contact with whom, when, for how long, and in which precise sequence, varies (rapidly) in time-analyzing them requires developing network methods and metrics that respect temporal variability, in contrast to those developed for static (i.e., time-invariant) networks. Here, by means of event mapping, we propose a method to quantify how quickly agents mingle by transforming temporal network data of agent contacts. We define a novel measure called contact sequence centrality, which quantifies the impact of an individual on the contact sequences, reflecting the individual's behavioral potential for spreading. Comparing contact sequence centrality across agents allows for ranking the impact of agents and identifying potential 'behavioral super-spreaders'. The method is applied to social interaction data collected at an art fair in Amsterdam. We relate the measure to the existing network metrics, both temporal and static, and find that (mostly at longer time scales) traditional metrics lose their resemblance to contact sequence centrality. Our work highlights the importance of accounting for the sequential nature of contacts when analyzing social interactions.

Geographic delay characterization of railway systems.

Railway systems provide pivotal support to modern societies, making their efficiency and robustness important to ensure. However, these systems are susceptible to disruptions and delays, leading to accumulating economic damage. The large spatial scale of delay spreading typically make it difficult to distinguish which regions will ultimately affected from an initial disruption, creating uncertainty for risk assessment. In this paper, we identify geographical structures that reflect how delay spreads through railway networks. We do so by proposing a graph-based, hybrid schedule and empirical-based model for delay propagation and apply spectral clustering. We apply the model to four European railway systems: the Netherlands, Germany, Switzerland and Italy. We characterize these geographical delay structures in the railway systems of these countries and interpret these regions in terms of delay severity and how dynamically disconnected they are from the rest. The method also allows us to point out important differences between these countries' railway systems. For practitioners, such geographical characterization of railways provides natural boundaries for local decision-making structures and risk assessment.

Characterizing neural phase-space trajectories via Principal Louvain Clustering.

BACKGROUND: With the growing size and richness of neuroscience datasets in terms of dimension, volume, and resolution, identifying spatiotemporal patterns in those datasets is increasingly important. Multivariate dimension-reduction methods are particularly adept at addressing these challenges. NEW METHOD: In this paper, we propose a novel method, which we refer to as Principal Louvain Clustering (PLC), to identify clusters in a low-dimensional data subspace, based on time-varying trajectories of spectral dynamics across multisite local field potential (LFP) recordings in awake behaving mice. Data were recorded from prefrontal cortex, hippocampus, and parietal cortex in eleven mice while they explored novel and familiar environments. RESULTS: PLC-identified subspaces and clusters showed high consistency across animals, and were modulated by the animals' ongoing behavior. CONCLUSIONS: PLC adds to an important growing literature on methods for characterizing dynamics in high-dimensional datasets, using a smaller number of parameters. The method is also applicable to other kinds of datasets, such as EEG or MEG.

Correspondence analysis, spectral clustering and graph embedding: applications to ecology and economic complexity.

Identifying structure underlying high-dimensional data is a common challenge across scientific disciplines. We revisit correspondence analysis (CA), a classical method revealing such structures, from a network perspective. We present the poorly-known equivalence of CA to spectral clustering and graph-embedding techniques. We point out a number of complementary interpretations of CA results, other than its traditional interpretation as an ordination technique. These interpretations relate to the structure of the underlying networks. We then discuss an empirical example drawn from ecology, where we apply CA to the global distribution of Carnivora species to show how both the clustering and ordination interpretation can be used to find gradients in clustered data. In the second empirical example, we revisit the economic complexity index as an application of correspondence analysis, and use the different interpretations of the method to shed new light on the empirical results within this literature.

Trends in Vitamin C Consumption in the United States: 1999-2018.

Low intakes of fruits and vegetables have resulted in suboptimal intakes of several micronutrients, including vitamin C. This cross-sectional study used data from 84,902 children/adults (≥1 y) who completed a 24-h dietary recall as part of the United States National Health and Nutrition Examination Survey (1999-2018). Mean vitamin C intakes from foods/beverages were calculated as were trends in major food/beverage sources of vitamin C. Percentages below the Estimated Average Requirement (EAR) were estimated. Overall, mean vitamin C consumption declined by 23% (97-75 mg/d; p-value for trend < 0.001). 100% fruit juice was the leading source of vitamin C (25.6% of total or 21.7mg/d), but this declined by 48% (25-13 mg/d; p-value for trend < 0.001). Whole fruit increased among children/adolescents (+75.8%;10-17 mg/d; p-value for trend < 0.001), but not adults, while the vegetable contribution was generally unchanged. The proportion of the population below the EAR increased by 23.8% on a relative scale or 9 percentage points on an absolute scale (38.3-47.4%). Declines in vitamin C intake is driven largely by decreases in fruit juice coupled with modest increases in whole fruit. Due to associations between vitamin C intake and numerous health outcomes these trends warrant careful monitoring moving forward.

Cascading dominates large-scale disruptions in transport over complex networks.

The core functionality of many socio-technical systems, such as supply chains, (inter)national trade and human mobility, concern transport over large geographically-spread complex networks. The dynamical intertwining of many heterogeneous operational elements, agents and locations are oft-cited generic factors to make these systems prone to large-scale disruptions: initially localised perturbations amplify and spread over the network, leading to a complete standstill of transport. Our level of understanding of such phenomena, let alone the ability to anticipate or predict their evolution in time, remains rudimentary. We approach the problem with a prime example: railways. Analysing spreading of train delays on the network by building a physical model, supported by data, reveals that the emergence of large-scale disruptions rests on the dynamic interdependencies among multiple 'layers' of operational elements (resources and services). The interdependencies provide pathways for the so-called delay cascading mechanism, which gets activated when, constrained by local unavailability of on-time resources, already-delayed ones are used to operate new services. Cascading locally amplifies delays, which in turn get transported over the network to give rise to new constraints elsewhere. This mechanism is a rich addition to some well-understood ones in, e.g., epidemiological spreading, or the spreading of rumours and opinions over (contact) networks, and stimulates rethinking spreading dynamics on complex networks. Having these concepts built into the model provides it with the ability to predict the evolution of large-scale disruptions in the railways up to 30-60 minutes up front. For transport systems, our work suggests that possible alleviation of constraints as well as a modular operational approach would arrest cascading, and therefore be effective measures against large-scale disruptions.

Predicting transitions across macroscopic states for railway systems.

Railways are classic instances of complex socio-technical systems, whose defining characteristic is that they exist and function by integrating (continuous-time) interactions among technical components and human elements. Typically, unlike physical systems, there are no governing laws for describing their dynamics. Based purely on micro-unit data, here we present a data-driven framework to analyze macro-dynamics in such systems, leading us to the identification of specific states and prediction of transitions across them. It consists of three steps, which we elucidate using data from the Dutch railways. First, we form a dimensionally reduced phase-space by extracting a few relevant components, wherein relevance is proxied by dominance in terms of explained variance, as well as by persistence in time. Secondly, we apply a clustering algorithm to the reduced phase-space, resulting in the revelation of states of the system. Specifically, we identify 'rest' and 'disrupted' states, for which the system operations deviates respectively little and strongly from the planned timetable. Third, we define an early-warning metric based on the probability of transitions across states, predict whether the system is likely to transit from one state to another within a given time-frame and evaluate the performance of this metric using the Peirce skill score. Interestingly, using case studies, we demonstrate that the framework is able to predict large-scale disruptions up to 90 minutes beforehand with significant skill, demonstrating, for the railway companies, its potential to better track the evolution of large-scale disruptions in their networks. We discuss that the applicability of the three-step framework stretches to other systems as well-i.e., not only socio-technical ones-wherein real-time monitoring can help to prevent macro-scale state transitions, albeit the methods chosen to execute each step may depend on specific system-details.

New Insights Into the Kinetics and Variability of Egg Excretion in Controlled Human Hookworm Infections.

Four healthy volunteers were infected with 50 Necator americanus infective larvae (L3) in a controlled human hookworm infection trial and followed for 52 weeks. The kinetics of fecal egg counts in volunteers was assessed with Bayesian multilevel analysis, which revealed an increase between weeks 7 and 13, followed by an egg density plateau of about 1000 eggs/g of feces. Variation in egg counts was minimal between same-day measurements but varied considerably between days, particularly during the plateau phase. These analyses pave the way for the controlled human hookworm model to accelerate drug and vaccine efficacy studies.

Frequency and Duration of Infusion Pump Alarms: Establishing National Benchmarks.

Reduction of clinical alarms is a priority due to alarm fatigue and the high incidence of nonactionable alarms, especially those generated from physiological monitors. However, research on infusion pump alarm types and frequencies is limited. The purpose of this study was to establish a baseline for infusion pump alarm frequencies and duration in the hospital setting. Frequency and duration of alarms across 29 hospitals using 11,410 infusion pumps revealed 987,240 alarms associated with 568,164 infusions during a consecutive 60-day period. Pump alarms accounted for only 0.8% of infusion time, with an average of 1.74 alarms per delivery and 0.18 alarms per hour. Average alarm duration was 0:02:38 (h:min:s), with 60% of alarms being addressed within 0:01:08. The most frequent alarms were keep vein open (33.77%), hold expired (27.18%), and downstream occlusion (22.94%). The medical/surgical and intensive care unit (ICU) care areas had the highest number of alarms (41.66% and 39.70% of total alarms, respectively), but pediatrics/neonatal ICU had the highest frequency of alarms per delivery (4.91). Intravenous fluids accounted for 47.16% of total alarms, with an average of 3.03 alarms per delivery, whereas parenteral nutrition and propofol had 6.77 and 6.74 average alarms per delivery, respectively. A higher average number of alarms per delivery occurred on Saturdays (1.74) and Sundays (1.73) compared with weekdays. Infusion pump alarm data collected and analyzed were sufficient to establish a reasonable baseline of infusion pump alarm types and relative frequencies for the device.

Inhibition of sphingolipid synthesis improves dyslipidemia in the diet-induced hamster model of insulin resistance: evidence for the role of sphingosine and sphinganine in hepatic VLDL-apoB100 overproduction.

Sphingolipids have emerged as important bioactive lipid species involved in the pathogenesis of type 2 diabetes and cardiovascular disease. However, little is known of the regulatory role of sphingolipids in dyslipidemia of insulin-resistant states. We employed hamster models of dyslipidemia and insulin resistance to investigate the role of sphingolipids in hepatic VLDL overproduction, induction of insulin resistance, and inflammation. Hamsters were fed either a control chow diet, a high fructose diet, or a diet high in fat, fructose and cholesterol (FFC diet). They were then treated for 2 weeks with vehicle or 0.3 mg/kg myriocin, a potent inhibitor of de novo sphingolipid synthesis. Both fructose and FFC feeding induced significant increases in hepatic sphinganine, which was normalized to chow-fed levels with myriocin (P < 0.05); myriocin also lowered hepatic ceramide content (P < 0.05). Plasma TG and cholesterol as well as VLDL-TG and -apoB100 were similarly reduced with myriocin treatment in all hamsters, regardless of diet. Myriocin treatment also led to improved insulin sensitivity and reduced hepatic SREBP-1c mRNA, though it did not appear to ameliorate the activation of hepatic inflammatory pathways. Importantly, direct treatment of primary hamster hepatocytes ex vivo with C2 ceramide or sphingosine led to an increased secretion of newly synthesized apoB100. Taken together, these data suggest that a) hepatic VLDL-apoB100 overproduction may be stimulated by ceramides and sphingosine and b) inhibition of sphingolipid synthesis can reduce circulating VLDL in hamsters and improve circulating lipids--an effect that is possibly due to improved insulin signaling and reduced lipogenesis but is independent of changes in inflammation.

Hepatocyte-specific deletion of Janus kinase 2 (JAK2) protects against diet-induced steatohepatitis and glucose intolerance.

Non-alcoholic fatty liver disease (NAFLD) is becoming the leading cause of chronic liver disease and is now considered to be the hepatic manifestation of the metabolic syndrome. However, the role of steatosis per se and the precise factors required in the progression to steatohepatitis or insulin resistance remain elusive. The JAK-STAT pathway is critical in mediating signaling of a wide variety of cytokines and growth factors. Mice with hepatocyte-specific deletion of Janus kinase 2 (L-JAK2 KO mice) develop spontaneous steatosis as early as 2 weeks of age. In this study, we investigated the metabolic consequences of jak2 deletion in response to diet-induced metabolic stress. To our surprise, despite the profound hepatosteatosis, deletion of hepatic jak2 did not sensitize the liver to accelerated inflammatory injury on a prolonged high fat diet (HFD). This was accompanied by complete protection against HFD-induced whole-body insulin resistance and glucose intolerance. Improved glucose-stimulated insulin secretion and an increase in ß-cell mass were also present in these mice. Moreover, L-JAK2 KO mice had progressively reduced adiposity in association with blunted hepatic growth hormone signaling. These mice also exhibited increased resting energy expenditure on both chow and high fat diet. In conclusion, our findings indicate a key role of hepatic JAK2 in metabolism such that its absence completely arrests steatohepatitis development and confers protection against diet-induced systemic insulin resistance and glucose intolerance.

Hepatic autophagy mediates endoplasmic reticulum stress-induced degradation of misfolded apolipoprotein B.

UNLABELLED: Induction of endoplasmic reticulum (ER) stress was previously shown to impair hepatic apolipoprotein B100 (apoB) production by enhancing cotranslational and posttranslational degradation of newly synthesized apoB. Here, we report the involvement of autophagy in ER stress-induced degradation of apoB and provide evidence for a significant role of autophagy in regulating apoB biogenesis in primary hepatocyte systems. Induction of ER stress following short-term glucosamine treatment of McA-RH7777 cells resulted in significantly increased colocalization of apoB with green fluorescent protein-microtubule-associated protein 1 light chain 3 (GFP-LC3), referred to as apoB-GFP-LC3 puncta, in a dose-dependent manner. Colocalization with this autophagic marker correlated positively with the reduction in newly synthesized apoB100. Treatment of McA-RH7777 cells with 4-phenyl butyric acid, a chemical ER stress inhibitor, prevented glucosamine- and tunicamycin-induced increases in GRP78 and phosphorylated eIF2α, rescued newly synthesized [(35) S]-labeled apoB100, and substantially blocked the colocalization of apoB with GFP-LC3. Autophagic apoB degradation was also observed in primary rat and hamster hepatocytes at basal conditions as well as upon the induction of ER stress. In contrast, this pathway was inactive in HepG2 cells under ER stress conditions, unless proteasomal degradation was blocked with N-acetyl-leucinyl-leucinyl-norleucinal and the medium was supplemented with oleate. Transient transfection of McA-RH7777 cells with a wild-type protein kinase R-like ER kinase (PERK) complementary DNA resulted in dramatic induction of apoB autophagy. In contrast, transfection with a kinase inactive mutant PERK gave rise to reduced apoB autophagy, suggesting that apoB autophagy may occur via a PERK signaling-dependent mechanism. CONCLUSION: Taken together, these data suggest that induction of ER stress leads to markedly enhanced apoB autophagy in a PERK-dependent pathway, which can be blocked with the chemical chaperone 4-phenyl butyric acid. ApoB autophagy rather than proteasomal degradation may be a more pertinent physiological mechanism regulating hepatic lipoprotein production in primary hepatocytes.

Fructose: a highly lipogenic nutrient implicated in insulin resistance, hepatic steatosis, and the metabolic syndrome.

As dietary exposure to fructose has increased over the past 40 years, there is growing concern that high fructose consumption in humans may be in part responsible for the rising incidence of obesity worldwide. Obesity is associated with a host of metabolic challenges, collectively termed the metabolic syndrome. Fructose is a highly lipogenic sugar that has profound metabolic effects in the liver and has been associated with many of the components of the metabolic syndrome (insulin resistance, elevated waist circumference, dyslipidemia, and hypertension). Recent evidence has also uncovered effects of fructose in other tissues, including adipose tissue, the brain, and the gastrointestinal system, that may provide new insight into the metabolic consequences of high-fructose diets. Fructose feeding has now been shown to alter gene expression patterns (such as peroxisome proliferator-activated receptor-γ coactivator-1α/ß in the liver), alter satiety factors in the brain, increase inflammation, reactive oxygen species, and portal endotoxin concentrations via Toll-like receptors, and induce leptin resistance. This review highlights recent findings in fructose feeding studies in both human and animal models with a focus on the molecular and biochemical mechanisms that underlie the development of insulin resistance, hepatic steatosis, and the metabolic syndrome.

Exercise prior to fat ingestion lowers fasting and postprandial VLDL and decreases adipose tissue IL-6 and GIP receptor mRNA in hypertriacylglycerolemic men.

Fasting and postprandial triacylglycerol (TAG) concentrations are risk factors for cardiovascular disease. This study evaluated whether interleukin-6 (IL-6) and incretin hormones [gastric inhibitory peptide (GIP) and glucagon-like peptide-1 (GLP-1) (active)] were associated with fasting and postprandial TAG in response to an oral lipid load, including very-low-density lipoprotein (VLDL) and chylomicron (CM) TAG, following one bout of exercise in nine men (age, 59 ± 2 years; body mass index, 34 ± 2 kg/m2; waist circumference, 113 ± 3 cm) with high fasting TAG (2.9 ± 0.2 mmol/L). Subjects completed two oral fat tolerance tests (OFTTs), randomized 1 week apart, that consisted of 1g fat/kg body weight emulsified lipids in the absence of carbohydrate and protein. Approximately 16 h prior to one OFTT, subjects completed 60 min of treadmill walking (estimated 55% VO2 peak; heart rate, 122 ± 4 beats/min). No exercise was performed on the day before the other OFTT. Fasted (0 h) and postprandial (1, 2, 3, 4, 5 and 6 h) blood samples were taken for analysis of TAG, IL-6 and incretins. Subcutaneous adipose tissue biopsies were taken at 0 and 6 h after OFTT ingestion for IL-6 and GIP receptor (GIPr) mRNA quantification. Exercise lowered fasting and postprandial TAG (P<.05) and VLDL TAG (P<.05), while postprandial CM TAG were similar in both OFTT trials (P>.05). Fasting and postprandial plasma IL-6, GIP and GLP-1 did not differ between rest and exercise OFTT trials (P>.05). Exercise reduced IL-6 and GIPr mRNA (P<.05) in adipose tissue. Our results suggest that the reduction in VLDL TAG following an acute bout of exercise is not associated with circulating IL-6 or incretin concentrations, despite reductions in the adipose tissue expression of IL-6 and GIPr.

Fasting triacylglycerol status, but not polyunsaturated/saturated fatty acid ratio, influences the postprandial response to a series of oral fat tolerance tests.

Elevated postprandial lipemia is emerging as a risk factor for obesity-related chronic diseases, such as type 2 diabetes and cardiovascular disease, and is associated with alterations in several metabolic biomarkers of disease. Our goal was to examine the effects of specific polyunsaturated/saturated fatty acid (P/S) ratios on postprandial triacylglycerol (TAG) concentrations and metabolic biomarkers in men with different fasting TAG concentrations through a series of oral fat tolerance tests (OFTT) consisting solely of emulsified lipid. Otherwise healthy men with high (>1.69 mmol/L) fasting TAG (HTAG, n=8) and low fasting TAG (LTAG, n=8) underwent three OFTTs with specific P/S ratios of 0.2, 1.0 and 2.0, respectively, and a total lipid load of 1 g/kg subject body mass. All subjects received each treatment separated by at least 1 week. Postprandial plasma TAG fatty acid composition reflected fatty acids present in the OFTT. All other metabolic responses were independent of the P/S ratio ingested. An accelerated increase in postprandial TAGs was observed in HTAG compared to LTAG. Interleukin (IL)-6 and soluble intercellular adhesion molecule (sICAM)-1 were significantly elevated in HTAG at baseline (P<.05). IL-6 increased significantly following each OFTT (P<.05) in both groups. Postprandial glucose and CRP were significantly exaggerated (P<.05) in HTAG. Overall, HTAG subjects had an accelerated postprandial TAG response and increased concentrations of several inflammatory markers following an OFTT, in the absence of an insulin response. However, P/S ratio had no influence on postprandial lipid and inflammatory parameters.

New oral fat tolerance tests feature tailoring of the polyunsaturated/saturated fatty acid ratio to elicit a specific postprandial response.

The impact of dietary fat on postprandial metabolic biomarkers for obesity-related chronic diseases, such as type-2 diabetes and cardiovascular disease, has received significant recent attention. However, there is no standard method to evaluate the postprandial response to dietary fat alone. Our goals were to develop a novel oral fat tolerance test (OFTT) consisting solely of emulsified lipids tailored for specific fatty acid compositions and to evaluate the functionality of specific ratios of polyunsaturated/saturated fatty acid (P/S) loading on postprandial triacylglyceride (TAG) concentrations. Two OFTTs of emulsified lipids were prepared with specific P/S ratios of 0.2 and 2.0. Physical characteristics of the fat blends, including TAG composition, melting point, and emulsion droplet size were quantified. Healthy, older (age>45 y) men (n=8) underwent an 8 h postprandial study wherein they received the OFTT treatment (either the P/S ratio of 0.2 or 2.0), with a total lipid load of 1 g/kg subject body mass. All subjects received both treatments separated by at least 1 week. Both the P/S 0.2 and 2.0 OFTT significantly elevated (p<0.05) blood TAG and free fatty acid concentrations for 8 h without increasing blood glucose or serum insulin concentrations. The predominant fatty acids contained in the P/S 0.2 (palmitic acid, 16:0) and 2.0 (linoleic acid, 18:2(n-6)) OFTT blends were significantly elevated in the blood (p<0.05) during their respective postprandial periods. We concluded that blood TAGs are elevated in a specific pattern through the administration of novel OFTTs with specific P/S blends without eliciting an insulin or glucose response.