The therapeutic properties of plants have been recognised since time immemorial. Many pathological conditions have been treated using plant-derived medicines. These medicines are used as concoctions or concentrated plant extracts without isolation of active compounds. Modern medicine however, requires the isolation and purification of one or two active compounds. There are however a lot of global health challenges with diseases such as cancer, degenerative diseases, HIV/AIDS and diabetes, of which modern medicine is struggling to provide cures. Many times the isolation of “active compound” has made the compound ineffective. Drug discovery is a multidimensional problem requiring several parameters of both natural and synthetic compounds such as safety, pharmacokinetics and efficacy to be evaluated during drug candidate selection. The advent of latest technologies that enhance drug design hypotheses such as Artificial Intelligence, the use of ‘organ-on chip’ and microfluidics technologies, means that automation has become part of drug discovery. This has resulted in increased speed in drug discovery and evaluation of the safety, pharmacokinetics and efficacy of candidate compounds whilst allowing novel ways of drug design and synthesis based on natural compounds. Recent advances in analytical and computational techniques have opened new avenues to process complex natural products and to use their structures to derive new and innovative drugs. Indeed, we are in the era of computational molecular design, as applied to natural products. Predictive computational softwares have contributed to the discovery of molecular targets of natural products and their derivatives. In future the use of quantum computing, computational softwares and databases in modelling molecular interactions and predicting features and parameters needed for drug development, such as pharmacokinetic and pharmacodynamics, will result in few false positive leads in drug development. This review discusses plant-based natural product drug discovery and how innovative technologies play a role in next-generation drug discovery.

https://www.mdpi.com/1422-0067/19/6/1578/pdf/1

Natural Products for Drug Discovery in the 21st Century: Innovations for Novel Drug Discovery.

Objective We performed a systematic review, meta-analysis and meta-regression to determine if dietary protein supplementation augments resistance exercise training (RET)-induced gains in muscle mass and strength. Data sources A systematic search of Medline, Embase, CINAHL and SportDiscus. Eligibility criteria Only randomised controlled trials with RET ≥6 weeks in duration and dietary protein supplementation. Design Random-effects meta-analyses and meta-regressions with four a priori determined covariates. Two-phase break point analysis was used to determine the relationship between total protein intake and changes in fat-free mass (FFM). Results Data from 49 studies with 1863 participants showed that dietary protein supplementation significantly (all p 2 (51, 570)) and mid-femur CSA (7.2 mm 2 (0.20, 14.30)) during periods of prolonged RET. The impact of protein supplementation on gains in FFM was reduced with increasing age (−0.01 kg (−0.02,–0.00), p=0.002) and was more effective in resistance-trained individuals (0.75 kg (0.09, 1.40), p=0.03). Protein supplementation beyond total protein intakes of 1.62 g/kg/day resulted in no further RET-induced gains in FFM. Summary/conclusion Dietary protein supplementation significantly enhanced changes in muscle strength and size during prolonged RET in healthy adults. Increasing age reduces and training experience increases the efficacy of protein supplementation during RET. With protein supplementation, protein intakes at amounts greater than ~1.6 g/kg/day do not further contribute RET-induced gains in FFM.

https://bjsm.bmj.com/content/bjsports/52/6/376.full.pdf

A systematic review, meta-analysis and meta-regression of the effect of protein supplementation on resistance training-induced gains in muscle mass and strength in healthy adults

Because of the dearth of biomarkers of aging, it has been difficult to test the hypothesis that obesity increases tissue age. Here we use a novel epigenetic biomarker of aging (referred to as an "epigenetic clock") to study the relationship between high body mass index (BMI) and the DNA methylation ages of human blood, liver, muscle, and adipose tissue. A significant correlation between BMI and epigenetic age acceleration could only be observed for liver (r = 0.42, P = 6.8 × 10(-4) in dataset 1 and r = 0.42, P = 1.2 × 10(-4) in dataset 2). On average, epigenetic age increased by 3.3 y for each 10 BMI units. The detected age acceleration in liver is not associated with the Nonalcoholic Fatty Liver Disease Activity Score or any of its component traits after adjustment for BMI. The 279 genes that are underexpressed in older liver samples are highly enriched (1.2 × 10(-9)) with nuclear mitochondrial genes that play a role in oxidative phosphorylation and electron transport. The epigenetic age acceleration, which is not reversible in the short term after rapid weight loss induced by bariatric surgery, may play a role in liver-related comorbidities of obesity, such as insulin resistance and liver cancer.

https://www.pnas.org/content/pnas/111/43/15538.full.pdf

Obesity accelerates epigenetic aging of human liver

Schoenfeld, BJ, Grgic, J, Ogborn, D, and Krieger, JW. Strength and hypertrophy adaptations between low- vs. high-load resistance training: a systematic review and meta-analysis. J Strength Cond Res 31(12): 3508-3523, 2017-The purpose of this article was to conduct a systematic review of the current body of literature and a meta-analysis to compare changes in strength and hypertrophy between low- vs. high-load resistance training protocols. Searches of PubMed/MEDLINE, Cochrane Library, and Scopus were conducted for studies that met the following criteria: (a) an experimental trial involving both low-load training [≤60% 1 repetition maximum (1RM)] and high-load training (>60% 1RM); (b) with all sets in the training protocols being performed to momentary muscular failure; (c) at least one method of estimating changes in muscle mass or dynamic, isometric, or isokinetic strength was used; (d) the training protocol lasted for a minimum of 6 weeks; (e) the study involved participants with no known medical conditions or injuries impairing training capacity. A total of 21 studies were ultimately included for analysis. Gains in 1RM strength were significantly greater in favor of high- vs. low-load training, whereas no significant differences were found for isometric strength between conditions. Changes in measures of muscle hypertrophy were similar between conditions. The findings indicate that maximal strength benefits are obtained from the use of heavy loads while muscle hypertrophy can be equally achieved across a spectrum of loading ranges.

Strength and Hypertrophy Adaptations Between Low- vs. High-Load Resistance Training: A Systematic Review and Meta-analysis.

Aim Investigate whether acute workload (1 week total distance) and chronic workload (4-week average acute workload) predict injury in elite rugby league players. Methods Data were collected from 53 elite players over two rugby league seasons. The 'acute:chronic workload ratio' was calculated by dividing acute workload by chronic workload. A value of greater than 1 represented an acute workload greater than chronic workload. All workload data were classified into discrete ranges by z-scores. Results Compared with all other ratios, a very-high acute:chronic workload ratio (2.11) demonstrated the greatest risk of injury in the current week (16.7% injury risk) and subsequent week (11.8% injury risk). High chronic workload (>16 095 m) combined with a veryhigh 2-week average acute:chronic workload ratio (1.54) was associated with the greatest risk of injury (28.6% injury risk). High chronic workload combined with a moderate workload ratio (1.02-1.18) had a smaller risk of injury than low chronic workload combined with several workload ratios (relative risk range from 0.3 to 0.7×/1.4 to 4.4; likelihood range=88-94%, likely). Considering acute and chronic workloads in isolation (ie, not as ratios) did not consistently predict injury risk. Conclusions Higher workloads can have either positive or negative influences on injury risk in elite rugby league players. Specifically, compared with players who have a low chronic workload, players with a high chronic workload are more resistant to injury with moderate-low through moderate-high (0.85-1.35) acute:chronic workload ratios and less resistant to injury when subjected to 'spikes' in acute workload, that is, very-high acute:chronic workload ratios 1.5.

https://bjsm.bmj.com/content/bjsports/50/4/231.full.pdf

The acute:chronic workload ratio predicts injury: high chronic workload may decrease injury risk in elite rugby league players

The purpose of this paper was to systematically review the current literature and elucidate the effects of total weekly resistance training (RT) volume on changes in measures of muscle mass via met...

Dose-response relationship between weekly resistance training volume and increases in muscle mass: A systematic review and meta-analysis

The purpose of this study was to compare the effect of low- versus high-load resistance training (RT) on muscular adaptations in well-trained subjects. Eighteen young men experienced in RT were matched according to baseline strength and then randomly assigned to 1 of 2 experimental groups: a low-load RT routine (LL) where 25-35 repetitions were performed per set per exercise (n = 9) or a high-load RT routine (HL) where 8-12 repetitions were performed per set per exercise (n = 9). During each session, subjects in both groups performed 3 sets of 7 different exercises representing all major muscles. Training was performed 3 times per week on nonconsecutive days, for a total of 8 weeks. Both HL and LL conditions produced significant increases in thickness of the elbow flexors (5.3 vs. 8.6%, respectively), elbow extensors (6.0 vs. 5.2%, respectively), and quadriceps femoris (9.3 vs. 9.5%, respectively), with no significant differences noted between groups. Improvements in back squat strength were significantly greater for HL compared with LL (19.6 vs. 8.8%, respectively), and there was a trend for greater increases in 1 repetition maximum (1RM) bench press (6.5 vs. 2.0%, respectively). Upper body muscle endurance (assessed by the bench press at 50% 1RM to failure) improved to a greater extent in LL compared with HL (16.6 vs. -1.2%, respectively). These findings indicate that both HL and LL training to failure can elicit significant increases in muscle hypertrophy among well-trained young men; however, HL training is superior for maximizing strength adaptations.

Effects of Low- vs. High-Load Resistance Training on Muscle Strength and Hypertrophy in Well-Trained Men.

A number of resistance training (RT) program variables can be manipulated to maximize muscular hypertrophy. One variable of primary interest in this regard is RT frequency. Frequency can refer to the number of resistance training sessions performed in a given period of time, as well as to the number of times a specific muscle group is trained over a given period of time. We conducted a systematic review and meta-analysis to determine the effects of resistance training frequency on hypertrophic outcomes. Studies were deemed eligible for inclusion if they met the following criteria: (1) were an experimental trial published in an English-language refereed journal; (2) directly compared different weekly resistance training frequencies in traditional dynamic exercise using coupled concentric and eccentric actions; (3) measured morphologic changes via biopsy, imaging, circumference, and/or densitometry; (4) had a minimum duration of 4 weeks; and (5) used human participants without chronic disease or injury. A total of ten studies were identified that investigated RT frequency in accordance with the criteria outlined. Analysis using binary frequency as a predictor variable revealed a significant impact of training frequency on hypertrophy effect size (P = 0.002), with higher frequency being associated with a greater effect size than lower frequency (0.49 ± 0.08 vs. 0.30 ± 0.07, respectively). Statistical analyses of studies investigating training session frequency when groups are matched for frequency of training per muscle group could not be carried out and reliable estimates could not be generated due to inadequate sample size. When comparing studies that investigated training muscle groups between 1 to 3 days per week on a volume-equated basis, the current body of evidence indicates that frequencies of training twice a week promote superior hypertrophic outcomes to once a week. It can therefore be inferred that the major muscle groups should be trained at least twice a week to maximize muscle growth; whether training a muscle group three times per week is superior to a twice-per-week protocol remains to be determined.

Effects of Resistance Training Frequency on Measures of Muscle Hypertrophy: A Systematic Review and Meta-Analysis

A decline in skeletal muscle mass and function with aging is well recognized, but remains poorly characterized at the molecular level. Here, we report for the first time a genome-wide study of DNA methylation dynamics in skeletal muscle of healthy male individuals during normal human aging. We predominantly observed hypermethylation throughout the genome within the aged group as compared to the young subjects. Differentially methylated CpG (dmCpG) nucleotides tend to arise intragenically and are underrepresented in promoters and are overrepresented in the middle and 3′ end of genes. The intragenic methylation changes are overrepresented in genes that guide the formation of the junction of the motor neuron and myofibers. We report a low level of correlation of gene expression from previous studies of aged muscle with our current analysis of DNA methylation status. For those genes that had both changes in methylation and gene expression with age, we observed a reverse correlation, with the exception of intragenic hypermethylated genes that were correlated with an increased gene expression. We suggest that a minimal number of dmCpG sites or select sites are required to be altered in order to correlate with gene expression changes. Finally, we identified 500 dmCpG sites that perform well in discriminating young from old samples. Our findings highlight epigenetic links between aging postmitotic skeletal muscle and DNA methylation.

https://onlinelibrary.wiley.com/doi/pdf/10.1111/acel.12180

Dan Ogborn

Papers

Strength and Hypertrophy Adaptations Between Low- vs. High-Load Resistance Training: A Systematic Review and Meta-analysis.

Dose-response relationship between weekly resistance training volume and increases in muscle mass: A systematic review and meta-analysis

Effects of Low- vs. High-Load Resistance Training on Muscle Strength and Hypertrophy in Well-Trained Men.

Effects of Resistance Training Frequency on Measures of Muscle Hypertrophy: A Systematic Review and Meta-Analysis

Genome-wide DNA methylation changes with age in disease-free human skeletal muscle.