Improved Strength Recovery and Reduced Fatigue with Suppressed Plasma Myostatin Following Supplementation of a Vicia faba Hydrolysate, in a Healthy Male Population.

Delayed onset muscle soreness (DOMS) due to intense physical exertion can negatively impact contractility and performance. Previously, NPN_1 (PeptiStrong™), a Vicia faba hydrolysate derived from a protein concentrate discovered through artificial intelligence (AI), was preclinically shown to help maintain muscle health, indicating the potential to mediate the effect of DOMS and alter molecular markers of muscle damage to improve recovery and performance. A randomised double-blind placebo-controlled trial was conducted on 30 healthy male (30-45 years old) volunteers (NCT05159375). Following initial strength testing on day 0, subjects were administered either placebo or NPN_1 (2.4 g/day). On day 14, DOMS was induced using resistance exercise. Strength recovery and fatigue were measured after 48 and 72 h. Biomarker analysis was performed on blood samples collected prior to DOMS induction and 0, 2, 48 and 72 h post-DOMS induction. NPN_1 supplementation significantly improved strength recovery compared to placebo over the 72 h period post-resistance exercise (p = 0.027), measured by peak torque per bodyweight, but not at individual timepoints. Muscle fatigue was significantly reduced over the same 72 h period (p = 0.041), as was myostatin expression (p = 0.006). A concomitant increase in other acute markers regulating muscle protein synthesis, regeneration and myoblast differentiation was also observed. NPN_1 significantly improves strength recovery and restoration, reduces fatigue and positively modulates alterations in markers related to muscle homeostasis.

Artificial Intelligence in Functional Food Ingredient Discovery and Characterisation: A Focus on Bioactive Plant and Food Peptides.

Scientific research consistently demonstrates that diseases may be delayed, treated, or even prevented and, thereby, health may be maintained with health-promoting functional food ingredients (FFIs). Consumers are increasingly demanding sound information about food, nutrition, nutrients, and their associated health benefits. Consequently, a nutrition industry is being formed around natural foods and FFIs, the economic growth of which is increasingly driven by consumer decisions. Information technology, in particular artificial intelligence (AI), is primed to vastly expand the pool of characterised and annotated FFIs available to consumers, by systematically discovering and characterising natural, efficacious, and safe bioactive ingredients (bioactives) that address specific health needs. However, FFI-producing companies are lagging in adopting AI technology for their ingredient development pipelines for several reasons, resulting in a lack of efficient means for large-scale and high-throughput molecular and functional ingredient characterisation. The arrival of the AI-led technological revolution allows for the comprehensive characterisation and understanding of the universe of FFI molecules, enabling the mining of the food and natural product space in an unprecedented manner. In turn, this expansion of bioactives dramatically increases the repertoire of FFIs available to the consumer, ultimately resulting in bioactives being specifically developed to target unmet health needs.

An Artificial-Intelligence-Discovered Functional Ingredient, NRT_N0G5IJ, Derived from Pisum sativum, Decreases HbA1c in a Prediabetic Population.

The prevalence of prediabetes is rapidly increasing, and this can lead to an increased risk for individuals to develop type 2 diabetes and associated diseases. Therefore, it is necessary to develop nutritional strategies to maintain healthy glucose levels and prevent glucose metabolism dysregulation in the general population. Functional ingredients offer great potential for the prevention of various health conditions, including blood glucose regulation, in a cost-effective manner. Using an artificial intelligence (AI) approach, a functional ingredient, NRT_N0G5IJ, was predicted and produced from Pisum sativum (pea) protein by hydrolysis and then validated. Treatment of human skeletal muscle cells with NRT_N0G5IJ significantly increased glucose uptake, indicating efficacy of this ingredient in vitro. When db/db diabetic mice were treated with NRT_N0G5IJ, we observed a significant reduction in glycated haemoglobin (HbA1c) levels and a concomitant benefit on fasting glucose. A pilot double-blinded, placebo controlled human trial in a population of healthy individuals with elevated HbA1c (5.6% to 6.4%) showed that HbA1c percentage was significantly reduced when NRT_N0G5IJ was supplemented in the diet over a 12-week period. Here, we provide evidence of an AI approach to discovery and demonstrate that a functional ingredient identified using this technology could be used as a supplement to maintain healthy glucose regulation.

Characterising the efficacy and bioavailability of bioactive peptides identified for attenuating muscle atrophy within a Vicia faba-derived functional ingredient.

Characterising key components within functional ingredients as well as assessing efficacy and bioavailability is an important step in validating nutritional interventions. Machine learning can assess large and complex data sets, such as proteomic data from plants sources, and so offers a prime opportunity to predict key bioactive components within a larger matrix. Using machine learning, we identified two potentially bioactive peptides within a Vicia faba derived hydrolysate, NPN_1, an ingredient which was previously identified for preventing muscle loss in a murine disuse model. We investigated the predicted efficacy of these peptides in vitro and observed that HLPSYSPSPQ and TIKIPAGT were capable of increasing protein synthesis and reducing TNF-α secretion, respectively. Following confirmation of efficacy, we assessed bioavailability and stability of these predicted peptides and found that as part of NPN_1, both HLPSYSPSPQ and TIKIPAGT survived upper gut digestion, were transported across the intestinal barrier and exhibited notable stability in human plasma. This work is a first step in utilising machine learning to untangle the complex nature of functional ingredients to predict active components, followed by subsequent assessment of their efficacy, bioavailability and human plasma stability in an effort to assist in the characterisation of nutritional interventions.

Discovery through Machine Learning and Preclinical Validation of Novel Anti-Diabetic Peptides.

While there have been significant advances in drug discovery for diabetes mellitus over the past couple of decades, there is an opportunity and need for improved therapies. While type 2 diabetic patients better manage their illness, many of the therapeutics in this area are peptide hormones with lengthy sequences and a molecular structure that makes them challenging and expensive to produce. Using machine learning, we present novel anti-diabetic peptides which are less than 16 amino acids in length, distinct from human signalling peptides. We validate the capacity of these peptides to stimulate glucose uptake and Glucose transporter type 4 (GLUT4) translocation in vitro. In obese insulin-resistant mice, predicted peptides significantly lower plasma glucose, reduce glycated haemoglobin and even improve hepatic steatosis when compared to treatments currently in use in a clinical setting. These unoptimised, linear peptides represent promising candidates for blood glucose regulation which require further evaluation. Further, this indicates that perhaps we have overlooked the class of natural short linear peptides, which usually come with an excellent safety profile, as therapeutic modalities.

An Artificial Intelligence Characterised Functional Ingredient, Derived from Rice, Inhibits TNF-α and Significantly Improves Physical Strength in an Inflammaging Population.

Food-derived bioactive peptides offer great potential for the treatment and maintenance of various health conditions, including chronic inflammation. Using in vitro testing in human macrophages, a rice derived functional ingredient natural peptide network (NPN) significantly reduced Tumour Necrosis Factor (TNF)-α secretion in response to lipopolysaccharides (LPS). Using artificial intelligence (AI) to characterize rice NPNs lead to the identification of seven potentially active peptides, the presence of which was confirmed by liquid chromatography tandem mass spectrometry (LC-MS/MS). Characterization of this network revealed the constituent peptides displayed anti-inflammatory properties as predicted in vitro. The rice NPN was then tested in an elderly "inflammaging" population with a view to subjectively assess symptoms of digestive discomfort through a questionnaire. While the primary subjective endpoint was not achieved, analysis of objectively measured physiological and physical secondary readouts showed clear significant benefits on the ability to carry out physical challenges such as a chair stand test that correlated with a decrease in blood circulating TNF-α. Importantly, the changes observed were without additional exercise or specific dietary alterations. Further health benefits were reported such as significant improvement in glucose control, a decrease in serum LDL concentration, and an increase in HDL concentration; however, this was compliance dependent. Here we provide in vitro and human efficacy data for a safe immunomodulatory functional ingredient characterized by AI.

Preclinical Evaluation of a Food-Derived Functional Ingredient to Address Skeletal Muscle Atrophy.

Skeletal muscle is the metabolic powerhouse of the body, however, dysregulation of the mechanisms involved in skeletal muscle mass maintenance can have devastating effects leading to many metabolic and physiological diseases. The lack of effective solutions makes finding a validated nutritional intervention an urgent unmet medical need. In vitro testing in murine skeletal muscle cells and human macrophages was carried out to determine the effect of a hydrolysate derived from vicia faba (PeptiStrong: NPN_1) against phosphorylated S6, atrophy gene expression, and tumour necrosis factor alpha (TNF-α) secretion, respectively. Finally, the efficacy of NPN_1 on attenuating muscle waste in vivo was assessed in an atrophy murine model. Treatment of NPN_1 significantly increased the phosphorylation of S6, downregulated muscle atrophy related genes, and reduced lipopolysaccharide-induced TNF-α release in vitro. In a disuse atrophy murine model, following 18 days of NPN_1 treatment, mice exhibited a significant attenuation of muscle loss in the soleus muscle and increased the integrated expression of Type I and Type IIa fibres. At the RNA level, a significant upregulation of protein synthesis-related genes was observed in the soleus muscle following NPN_1 treatment. In vitro and preclinical results suggest that NPN_1 is an effective bioactive ingredient with great potential to prolong muscle health.

Human milk and infant formulae: Peptide differences and the opportunity to address the functional gap.

Bovine-derived formula milk (FM) is a common substitute to human milk (HM), but lacks key functional benefits associated with HM. Accordingly, there have been significant efforts to humanise FM. Recent research has demonstrated that HM-derived peptides convey an array of beneficial bioactivities. Given that peptides serve as important signalling molecules offering high specificity and potency, they represent a prime opportunity to humanise FM. To further understand how HM-derived peptides contribute to infant health, we used peptidomics and bioinformatics to compare the peptide profile of HM to commercially available FM. We found clear and substantial differences between HM and FM in terms of peptide physicochemical properties, protein coverage and abundance. We additionally identified 618 peptides specific to HM that represent an important untapped source to be explored for novel bioactivities. While further study is required, our findings highlight the potential of a peptide-based approach to address the functional gap in FM.

Acute hypoxic exposure and prolyl-hydroxylase inhibition improves synaptic transmission recovery time from a subsequent hypoxic insult in rat hippocampus.

In the CNS short episodes of acute hypoxia can result in a decrease in synaptic transmission which may be fully reversible upon re-oxygenation. Stabilization of hypoxia-inducible factor (HIF) by inhibition of prolyl hydroxylase domain (PHD) enzymes has been shown to regulate the cellular response to hypoxia and confer neuroprotection both in vivo and in vitro. Hypoxic preconditioning has become a novel therapeutic target to induce neuroprotection during hypoxic insults. However, there is little understanding of the effects of repeated hypoxic insults or pharmacological PHD inhibition on synaptic signaling. In this study we have assessed the effects of hypoxic exposure and PHD inhibition on synaptic transmission in the rat CA1 hippocampus. Field excitatory postsynaptic potentials (fEPSPs) were elicited by stimulation of the Schaffer collateral pathway. 30 min hypoxia (gas mixture 95% N2/5% CO2) resulted in a significant and fully reversible decrease in fEPSP slope associated with decreases in partial pressures of tissue oxygen. 15-30 min of hypoxia was sufficient to induce stabilization of HIF in hippocampal slices. Exposure to a second hypoxic insult after 60 min resulted in a similar depression of fEPSP slope but with a significantly greater rate of recovery of the fEPSP. Prior single treatment of slices with the PHD inhibitor, dimethyloxalylglycine (DMOG) also resulted in a significantly greater rate of recovery of fEPSP post hypoxia. These results suggest that hypoxia and 'pseudohypoxia' preconditioning may improve the rate of recovery of hippocampal neurons to a subsequent acute hypoxia.

Tumor necrosis factor-α potentiates long-term potentiation in the rat dentate gyrus after acute hypoxia.

An inadequate supply of oxygen in the brain may lead to an inflammatory response through neuronal and glial cells that can result in neuronal damage. Tumor necrosis factor-α (TNF-α) is a proinflammatory cytokine that is released during acute hypoxia and can have neurotoxic or neuroprotective effects in the brain. Both TNF-α and interleukin-1ß (IL-1ß) have been shown by a number of research groups to alter synaptic scaling and also to inhibit long-term potentiation (LTP) in the hippocampus when induced by specific high-frequency stimulation (HFS) protocols. This study examines the effects of TNF-α on synaptic transmission and plasticity in hippocampal slices after acute hypoxia using two HFS protocols. Field excitatory postsynaptic potentials were elicited in the medial perforant pathway of the dentate gyrus. Exogenous TNF-α (5 ng/ml) attenuated LTP induced by theta burst stimulation but had no effect on LTP induced by a more prolonged HFS. Pretreatment with lipopolysaccharide (100 ng/ml) or TNF-α but not IL-1ß (4 ng/ml) prior to a 30-min hypoxic insult resulted in a significant enhancement of LTP post hypoxia when induced by the HFS. Anti-TNF, 3,6'-dithiothalidomide (a TNF-α synthesis inhibitor), and SB203580 (a p38 MAPK inhibitor) significantly reduced this effect. These results indicate an important modulatory role for elevated TNF-α levels on LTP in the hippocampus after an acute hypoxic event.

Effects of prolyl-hydroxylase inhibition and chronic intermittent hypoxia on synaptic transmission and plasticity in the rat CA1 and dentate gyrus.

Chronic intermittent hypoxia (CIH) is an underlying component of obstructive sleep apnoea and has been shown to have deleterious and damaging effects on central neurons and to impair synaptic plasticity in the CA1 region of the rat hippocampus. CIH has previously been shown to impair synaptic plasticity and working memory. CIH is a potent inducer of hypoxia inducible factor (HIF), a key regulator in a cell's adaptation to hypoxia that plays an important role in the fate of neurons during ischemia. Levels of HIF-1α are regulated by the activity of a group of enzymes called HIF-prolyl 4-hydroxylases (PHDs) and these have become potential pharmacological targets for preconditioning against ischemia. However little is known about the effects of prolyl hydroxylase inhibition and CIH on synaptic transmission and plasticity in sub-regions of the hippocampus. Male Wistar rats were treated for 7-days with either saline, CIH or PHD inhibition (dimethyloxaloylglycine, DMOG; 50mg/kg, i.p.). At the end of treatment all three groups showed no change in synaptic excitability using paired pulse paradigms. However long-term potentiation (LTP) was impaired in the CA1 region of the hippocampus in both CIH and DMOG treated animals. LTP induced in the dentate gyrus was not significantly affected by either CIH or DMOG treatment. We also investigated the effect of 7-day CIH and DMOG treatment on the recovery of synaptic transmission following an acute 30min hypoxic insult. CIH treated animals showed an improved rate of recovery of synaptic transmission following re-oxygenation in both the CA1 and the dentate gyrus. These results suggest that LTP induction in the CA1 region is more sensitive to both CIH and DMOG treatments than the dentate gyrus.