The Scientific Basis for High-Intensity Interval Training: Optimising Training Programmes and Maximising Performance in Highly Trained Endurance Athletes

While the physiological adaptations that occur following endurance training in previously sedentary and recreationally active individuals are relatively well understood, the adaptations to training in already highly trained endurance athletes remain unclear. While significant improvements in endurance performance and corresponding physiological markers are evident following submaximal endurance training in sedentary and recreationally active groups, an additional increase in submaximal training (i.e. volume) in highly trained individuals does not appear to further enhance either endurance performance or associated physiological variables [e.g. peak oxygen uptake (V-dot O2peak), oxidative enzyme activity]. It seems that, for athletes who are already trained, improvements in endurance performance can be achieved only through high-intensity interval training (HIT). The limited research which has examined changes in muscle enzyme activity in highly trained athletes, following HIT, has revealed no change in oxidative or glycolytic enzyme activity, despite significant improvements in endurance performance (p < 0.05). Instead, an increase in skeletal muscle buffering capacity may be one mechanism responsible for an improvement in endurance performance. Changes in plasma volume, stroke volume, as well as muscle cation pumps, myoglobin, capillary density and fibre type characteristics have yet to be investigated in response to HIT with the highly trained athlete. Information relating to HIT programme optimisation in endurance athletes is also very sparse. Preliminary work using the velocity at which V-dot O2max is achieved (Vmax) as the interval intensity, and fractions (50 to 75%) of the time to exhaustion at Vmax (Tmax) as the interval duration has been successful in eliciting improvements in performance in long-distance runners. However, Vmax and Tmax have not been used with cyclists. Instead, HIT programme optimisation research in cyclists has revealed that repeated supramaximal sprinting may be equally effective as more traditional HIT programmes for eliciting improvements in endurance performance. Further examination of the biochemical and physiological adaptations which accompany different HIT programmes, as well as investigation into the optimal HIT programme for eliciting performance enhancements in highly trained athletes is required.

Interval breast cancers in an Australian mammographic screening program

Objective: To determine the incidence of interval cancers which occurred in the first 12 months after mammographic screening at a mammographic screening service. Design: Retrospective analysis of data obtained by crossmatching the screening Service and the New South Wales Central Cancer Registry databases. Setting: The Central & Eastern Sydney Service of BreastScreen NSW. Participants: Women aged 40-69 years at first screen, who attended for their first or second screen between 1 March 1988 and 31 December 1992. Main outcome measures: Interval-cancer rates per 10 000 screens and as a proportion of the underlying incidence of breast cancer (as estimated by the underlying rate in the total NSW population). Results: The 12-month interval-cancer incidence per 10 000 screens was 4.17 for the 40-49 years age group (95% confidence interval [CI], 1.35-9.73) and 4.64 for the 50-69 years age group (95% CI, 2.47-7.94). Proportional incidence rates were 30.1% for the 40-49 years age group (95% CI, 9.8-70.3) and 22% for the 50-69 years age group (95% CI, 11.7-37.7). There was no significant difference between the proportional incidence rate for the 50-69 years age group for the Central & Eastern Sydney Service and those of major successful overseas screening trials. Conclusion: Screening quality was acceptable and should result in a significant mortality reduction in the screened population. Given the small number of cancers involved, comparison of interval-cancer statistics of mammographic screening programs with trials requires age-specific or age-adjusted data, and consideration of confidence intervals of both program and trial data.

Impact of increasing the re-supply interval on the seasonality of subsidised prescription use in Australia

Objective: To evaluate the impact of increasing the minimum resupply period for prescriptions on the Pharmaceutical Benefits Scheme (PBS) in November 1994. The intervention was designed to reduce the stockpiling of medicines used for chronic medical conditions under the PBS safety net. Methods: Interrupted times series regression analyses were performed on 114 months of PBS drug utilisation data from January 1991 to June 2000. These analyses assessed whether there had been a significant interaction between the onset of the intervention in November 1994 and the extreme levels of drug utilisation in the months of December (peak utilisation) and January (lowest utilisation) respectively. Both serial and 12-month lag autocorrelations were controlled for. Results: The onset of the intervention was associated with a significant reduction in the December peak in drug utilisation; after the introduction of the policy there were 1,150,196 fewer proscriptions on average or that month (95% Cl 708,333-1,592,059). There was, however, no significant change in the low level of utilisation in January. The effect of the policy appears to be decreasing across successive postintervention years. though the odds of a prescription being dispensed in December remained significantly lower in 1999 compared to each of the pre-intervention years (11% vs. 14%) Conclusion: Analysis of the impact of increasing the re-supply period for PBS prescriptions showed that the magnitude of peak utilisation in December had been markedly reduced by the policy, though this effect appears to be decreasing over time. Continued monitoring and policy review is warranted in order to ensure that the initial effect of the intervention be maintained.

An object-oriented neural network approach to short-term traffic forecasting

This paper discusses an object-oriented neural network model that was developed for predicting short-term traffic conditions on a section of the Pacific Highway between Brisbane and the Gold Coast in Queensland, Australia. The feasibility of this approach is demonstrated through a time-lag recurrent network (TLRN) which was developed for predicting speed data up to 15 minutes into the future. The results obtained indicate that the TLRN is capable of predicting speed up to 5 minutes into the future with a high degree of accuracy (90-94%). Similar models, which were developed for predicting freeway travel times on the same facility, were successful in predicting travel times up to 15 minutes into the future with a similar degree of accuracy (93-95%). These results represent substantial improvements on conventional model performance and clearly demonstrate the feasibility of using the object-oriented approach for short-term traffic prediction. (C) 2001 Elsevier Science B.V. All rights reserved.

Acute high-intensity interval training improves T-vent and peak power output in highly trained males.

This study examined the effects of four high-intensity interval-training (HIT) sessions performed over 2 weeks on peak volume of oxygen uptake (VO2peak), the first and second ventilatory thresholds (UT VT2) and peak power output (PPO) in highly trained cyclists. Fourteen highly trained male cyclists (VO2peak = 67.5 +/- 3.7 ml . kg(-1) . min(-1)) performed a ramped cycle test to determine VO2peak VT1 VT2, and PPO. Subjects were divided equally into a HIT group and a control group. The HIT group performed four HIT sessions (20 x 60 s at PPO, 120 s recovery); the V-02peak test was repeated <I wk after the HIT program. Control subjects maintained their regular training program and were reassessed under the same timeline. There was no change in V0(2peak) for either group; however, the HIT group showed a significantly greater increase in VT1, (+22% vs. -3%), VT2 (+15% vs. -1%), and PPO (+4.3 vs. -.4%) compared to controls (all P <.05). This study has demonstrated that HIT can improve VT1, VT2,, and PPO, following only four HIT sessions in already highly trained cyclists.

The relationship between prepulse inhibition and perceived intensity of the blink-eliciting stimulus: Stimulus intensity and lead interval effects

The hypothesis that prepulse inhibition of the blink reflex reflects a transient process that protects preattentive processing of the prepulse was investigated. Participants were presented with pairs of blink-eliciting noises, with some noises preceded by a prepulse, and were asked to rate the intensity of the second noise relative to the first. Inhibition of blink amplitude was greater for a 110 dB(A) noise than for a 95 dB(A) noise with a 120 ms lead interval, whereas there was no difference with a 30 ms lead interval. The reduction in perceived intensity was greater for the 110 dB(A) noise than for the 95 dB(A) noise with the 120 ms lead interval, but not with the 30 ms lead interval. The parallel results support an association between prepulse inhibition and perceived intensity. However, the prepulse did not reduce intensity ratings relative to control trials in some conditions, suggesting that prepulse inhibition is not always associated with an attenuation of the impact of the blink-eliciting stimulus.

Forecasting regional crop production using SOI phases: an example for the Australian peanut industry

Using peanuts as an example, a generic methodology is presented to forward-estimate regional crop production and associated climatic risks based on phases of the Southern Oscillation Index (SOI). Yield fluctuations caused by a highly variable rainfall environment are of concern to peanut processing and marketing bodies. The industry could profitably use forecasts of likely production to adjust their operations strategically. Significant, physically based lag-relationships exist between an index of ocean/atmosphere El Nino/Southern Oscillation phenomenon and future rainfall in Australia and elsewhere. Combining knowledge of SOI phases in November and December with output from a dynamic simulation model allows the derivation of yield probability distributions based on historic rainfall data. This information is available shortly after planting a crop and at least 3-5 months prior to harvest. The study shows that in years when the November-December SOI phase is positive there is an 80% chance of exceeding average district yields. Conversely, in years when the November-December SOI phase is either negative or rapidly falling there is only a 5% chance of exceeding average district yields, but a 95% chance of below average yields. This information allows the industry to adjust strategically for the expected volume of production. The study shows that simulation models can enhance SOI signals contained in rainfall distributions by discriminating between useful and damaging rainfall events. The methodology can be applied to other industries and regions.

An adaptive neural-wavelet model for short term load forecasting

This paper proposed a novel model for short term load forecast in the competitive electricity market. The prior electricity demand data are treated as time series. The forecast model is based on wavelet multi-resolution decomposition by autocorrelation shell representation and neural networks (multilayer perceptrons, or MLPs) modeling of wavelet coefficients. To minimize the influence of noisy low level coefficients, we applied the practical Bayesian method Automatic Relevance Determination (ARD) model to choose the size of MLPs, which are then trained to provide forecasts. The individual wavelet domain forecasts are recombined to form the accurate overall forecast. The proposed method is tested using Queensland electricity demand data from the Australian National Electricity Market. (C) 2001 Elsevier Science B.V. All rights reserved.

An extended interval dosing method for gentamicin in neonates

Traditional gentamicin dosing every 8–24 h depending on age and weight in neonates does not provide the ideal concentration–time profile to both optimize the concentration-dependent killing by aminoglycosides and minimize toxicity. Fifty-three neonates were audited prospectively while receiving gentamicin 2.5 mg/kg every 8–24 h, aiming for peak concentrations (Cmax) of 6–10 mg/L and trough concentrations (Cmin) 10 mg/L after the first dose. The mean area under the concentration versus time curve AUC0–24 was 93 mg•h/L (target = 100 mg•h/L). The extended interval dosing achieved higher Cmax values while ensuring that overall exposure per 24 h was acceptable. Prospective testing of the method demonstrated good predictive ability.