Effect of extended morning fasting upon ad libitum lunch intake and associated metabolic and hormonal responses in obese adults

Background/Objectives: Breakfast omission is positively associated with obesity and increased risk of disease. However, little is known about the acute effects of extended morning fasting upon subsequent energy intake and associated metabolic/regulatory factors in obese adults. Subjects/Methods: In a randomised cross-over design, 24 obese men (n=8) and women (n=16) extended their overnight fast by omitting breakfast consumption or ingesting a typical carbohydrate-rich breakfast of 2183±393 kJ (521±94 kcal), before an ad libitum pasta lunch 3 h later. Blood samples were obtained throughout the day until 3 h post lunch and analysed for hormones implicated in appetite regulation, along with metabolic outcomes and subjective appetite measures. Results: Lunch intake was unaffected by extended morning fasting (difference=218 kJ, 95% confidence interval −54 kJ, 490 kJ; P=0.1) resulting in lower total intake in the fasting trial (difference=−1964 kJ, 95% confidence interval −1645 kJ, −2281 kJ; P<0.01). Systemic concentrations of peptide tyrosine–tyrosine and leptin were lower during the afternoon following morning fasting (Pless than or equal to0.06). Plasma-acylated ghrelin concentrations were also lower following the ad libitum lunch in the fasting trial (P<0.05) but this effect was not apparent for total ghrelin (Pgreater than or equal to0.1). Serum insulin concentrations were greater throughout the afternoon in the fasting trial (P=0.05), with plasma glucose also greater 1 h after lunch (P<0.01). Extended morning fasting did not result in greater appetite ratings after lunch, with some tendency for lower appetite 3 h post lunch (P=0.09). Conclusions: We demonstrate for the first time that, in obese adults, extended morning fasting does not cause compensatory intake during an ad libitum lunch nor does it increase appetite during the afternoon. Morning fasting reduced satiety hormone responses to a subsequent lunch meal but counterintuitively also reduced concentrations of the appetite-stimulating hormone-acylated ghrelin during the afternoon relative to lunch consumed after breakfast

Insights on meat quality from combining traditional studies and proteomics

peer-reviewedFollowing a century of major discoveries on the mechanisms determining meat colour and tenderness using traditional scientific methods, further research into complex and interactive factors contributing to variations in meat quality is increasingly being based on data-driven “omics” approaches such as proteomics. Using two recent meta-analyses of proteomics studies on beef colour and tenderness, this review examines how knowledge of the mechanisms and factors underlying variations in these meat qualities can be both confirmed and extended by data-driven approaches. While proteomics seems to overlook some sources of variations in beef toughness, it highlights the role of post-mortem energy metabolism in setting the conditions for development of meat colour and tenderness, and also points to the complex interplay of energy metabolism, calcium regulation and mitochondrial metabolism. In using proteomics as a future tool for explaining variations in meat quality, the need for confirmation by further hypothesis-driven experimental studies of post-hoc explanations of why certain proteins are biomarkers of beef quality in data-driven studies is emphasised

Fibre Distribution and the Process-Property Dilemma

The options for the fibre reinforcement of polymer matrix composites cover a range from short-fibre chopped strand mat, through woven fabric to unidirectional pre-impregnated (prepreg) reinforcements. The modelling of such materials may be simplified by assumptions such as perfect regular packing of fibres and the total absence of fibre waviness. However, these and other features such as the crimp or waviness in woven fabrics make real materials more complex than the simplified models. Clustering of fibres creates fibre-rich and resin-rich volumes (FRV and RRV respectively) in the composites. Prior to impregnation, large RRV will be pore-space that can expedite the flow of resin in liquid composite moulding processes (especially resin transfer moulding (RTM) and resin infusion under flexible tooling (RIFT). In the composite, the clustering of fibres tends to reduce the mechanical properties. The use of image processing and analysis can permit micro-/meso-structural characterisation which may correlate to the respective properties. This chapter considers the quantification of microstructure images in the context of the process-property dilemma for woven carbon-fibre reinforced composites with the aim of increasing understanding of the balance between processability and mechanical performance

Meat tenderness: advances in biology, biochemistry, molecular mechanisms and new technologies

Meat tenderness is an important quality trait critical to consumer acceptance, and determines satisfaction, repeat purchase and willingness-to-pay premium prices. Recent advances in tenderness research from a variety of perspectives are presented. Our understanding of molecular factors influencing tenderization are discussed in relation to glycolysis, calcium release, protease activation, apoptosis and heat shock proteins, the use of proteomic analysis for monitoring changes, proteomic biomarkers and oxidative/nitrosative stress. Each of these structural, metabolic and molecular determinants of meat tenderness are then discussed in greater detail in relation to animal variation, postmortem influences, and changes during cooking, with a focus on recent advances. Innovations in postmortem technologies and enzymes for meat tenderization are discussed including their potential commercial application. Continued success of the meat industry relies on ongoing advances in our understanding, and in industry innovation. The recent advances in fundamental and applied research on meat tenderness in relation to the various sectors of the supply chain will enable such innovation

Proteomic biomarkers of beef colour

peer-reviewedBackground Implementation of proteomics over the last decade has been an important step toward a better understanding of the complex biological systems underlying the conversion of muscle to meat. These sophisticated analytical tools have helped to reveal the biochemical pathways involved in fresh meat colour and have identified key protein biomarkers. Scope and approach Until recently, there have been no detailed or critical studies on the role of protein biomarkers in determining meat colour. This review presents an integromics of recent muscle proteomic studies to investigate pathways and mechanisms of beef colour. A database was created from 13 independent proteomic-based studies including data on five muscles and a list of 79 proteins which were significantly correlated with colour traits. The database was subjected to a multistep analysis including Gene Ontology annotations, pathway analysis and literature mining. This report discusses the key protein biomarkers and the biological pathways associated with fresh beef colour. Biomarkers were prioritised by the frequency of identification and the need for future validation experiments is discussed. Key findings and conclusions This review identifies six pathways involved in beef colour including energy metabolism, heat shock and oxidative stress, myofibril structure, signalling, proteolysis and apoptosis. The data-mining of the list of the putative biomarkers showed that certain proteins, such as β-enolase (ENO3), Peroxiredoxin 6 (PRDX6), HSP27 (HSPB1), Phosphoglucomutase 1 (PGM1), Superoxide Dismutase [Cu-Zn] (SOD1) and μ-calpain (CAPN1) were consistently reported by multiple studies as being differentially expressed and having a significant role in beef colour. This integromics work proposes a list of 27 putative biomarkers of beef colour for validation using adapted high-throughput methods.FI

Towards global spaceborne lidar biomass: Developing and applying boreal forest biomass models for ICESat-2 laser altimetry data

Space-based laser altimetry has revolutionized our capacity to characterize terrestrial ecosystems through the direct observation of vegetation structure and the terrain beneath it. Data from NASA's ICESat-2 mission provide the first comprehensive look at canopy structure for boreal forests from space-based lidar. The objective of this research was to create ICESat-2 aboveground biomass density (AGBD) models for the global entirety of boreal forests at a 30 m spatial resolution and apply those models to ICESat-2 data from the 2019–2021 period. Although limited in dense canopy, ICESat-2 is the only space-based laser altimeter capable of mapping vegetation in northern latitudes. Along each ICESat-2 orbit track, ground and vegetation height is captured with additional modeling required to characterize biomass. By implementing a similar methodology of estimating AGBD as GEDI, ICESat-2 AGBD estimates can complement GEDI's estimates for a full global accounting of aboveground carbon. Using a suite of field measurements with contemporaneous airborne lidar data over boreal forests, ICESat-2 photons were simulated over many field sites and the impact of two methods of computing relative height (RH) metrics on AGBD at a 30 m along-track spatial resolution were tested; with and without ground photons. AGBD models were developed specifically for ICESat-2 segments having land cover as either Evergreen Needleleaf or Deciduous Broadleaf Trees, whereas a generalized boreal-wide AGBD model was developed for ICESat-2 segments whose land cover was neither. Applying our AGBD models to a set of over 19 million ICESat-2 observations yielded a 30 m along-track AGBD product for the pan-boreal. The ability demonstrated herein to calculate ICESat-2 biomass estimates at a 30 m spatial resolution provides the scientific underpinning for a full, spatially explicit, global accounting of aboveground biomass