The effect of carbohydrate-loading and carbohydrate ingestion on fuel substrate kinetics during prolonged cycling

It has been well established that both carbohydrate-loading before and carbohydrate ingestion during exercise can enhance endurance performance by supplying carbohydrate for oxidation. However, the precise mechanism(s) underlying the proposed ergogenic effects of these procedures remain to be established. The studies in this thesis were therefore designed to examine the effects of carbohydrate-loading and carbohydrate ingestion on fuel substrate kinetics

A comparative study of acute responses to running in elite black and white marathon athletes

Experienced male marathon runners, 9 black and 10 white, with marathon times of 2 hours 45 minutes or faster, acted as subjects for the study, the purpose of which was to determine whether black runners are better suited to marathon running than whites. Body composition was determined by anthropometry. Maximal oxygen uptake (VO₂ max) and other physiological variables were measured during a continuous, speed-incremented treadmill protocol using a computer-aided data acquisition system. Subjects also ran a simulated marathon at 92.5% of the running speed at which the ventilatory threshold (VT) occurred. Physiological, gait and RPE variables were measured at 10 minute intervals during the marathon. Major findings are detailed below:- The VO₂, max averaged 60.4 ∓ 6.5 and 63.2 ∓ 2.9 mI. kg⁻¹.min⁻¹ in the black and white runners respectively and was highly correlated with best marathon race time (r = 0.86 and 0.85 respectively) and VT (r = 0.84 and 0.60 respectively) (p < 0.05). No significant differences existed between the groups in submaximal oxygen uptake (VO₂,) or % VO₂ max utilised at 16 km.hr⁻¹, but the estimated % VO₂ max utilised during a marathon race was higher in the black (89.0 ∓ 5.5%) than the white runners (81. 5 ∓ 3.1%) {p .( 0.05). The % VO₂ max utilised at 16 km.hr⁻¹ (84.8 ∓ 9.1 and 78.6 ∓ 5.8% in the black and white runners respectively) was significantly correlated with the % VO₂, max utilised while racing in the white (81.5 ∓ 3.1%) (r = 0.70) (p < 0.05), but not the black runners (89.0 ∓ 5.5%). The VT occurred at 82.7 ∓ 7.7 and 75.6 :∓ 6.2% VO₂; max in the black and white groups respectively (p < 0.05). Post-marathon blood lactic acid levels were lower in the black (1.30 ∓ 0.26 mmo1.l⁻¹) than the white runners (1.59 ∓ 0.20 mmol.l⁻¹). The respiratory exchange ratio (R) was higher in the blacks than whites when running at 16 km.hr ⁻¹ (1.03 ∓ 0.07 and 0.98 ∓ 0.03 respectively) and during the marathon (p < 0.05). There was no significant difference in pulmonary minute ventilation (Vı) between the groups, but breathing frequency (f) was higher in the black (59 ∓ 12 breaths.min⁻¹) than the white runners (45 ∓ 8 breaths. min⁻¹ ) and tidal volume (V⊤) lower in the black ( 1.33 ∓ 0.16 l.breath⁻¹) than the white runners (1.75 ∓ 0.36 I.breath⁻¹) during submaximal running at 16 km. hr⁻¹ (p < 0.05). The same trend was observed during the marathon run. During the time-course of the marathon f increased and V⊤ decreased In both groups (p < 0.05). Stroke volume decreased and heart rate increased In both groups during the time-course of the marathon (p< 0.05). Cardiac output was therefore maintained. Thermal responses were similar in the two groups. A significant increase in rectal temperature coincided with a decrease in skin temperature and may have been related to an increase in f (r = 0.86 and 0.67 in the blacks and whites respectively), H/R (r = 0.70 and 0.67 respectively) and "local" (leg) RPE (r = 0.84 and 0.82 respectively). It was concluded that black runners were able to run marathon races at a higher % VO₂ more than whites due to the blacks having lower blood lactic acid levels when running at a similar % VO₂ max. Given similar maximal oxygen uptakes, this would enable blacks to run faster. Cardiopulmonary adjustments occur during the time-course of a marathon which maintains Q and V

Non-Standard Errors

In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty: Non-standard errors (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for better reproducible or higher rated research. Adding peer-review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants

Effects of hospital facilities on patient outcomes after cancer surgery: an international, prospective, observational study

Background Early death after cancer surgery is higher in low-income and middle-income countries (LMICs) compared with in high-income countries, yet the impact of facility characteristics on early postoperative outcomes is unknown. The aim of this study was to examine the association between hospital infrastructure, resource availability, and processes on early outcomes after cancer surgery worldwide.Methods A multimethods analysis was performed as part of the GlobalSurg 3 study-a multicentre, international, prospective cohort study of patients who had surgery for breast, colorectal, or gastric cancer. The primary outcomes were 30-day mortality and 30-day major complication rates. Potentially beneficial hospital facilities were identified by variable selection to select those associated with 30-day mortality. Adjusted outcomes were determined using generalised estimating equations to account for patient characteristics and country-income group, with population stratification by hospital.Findings Between April 1, 2018, and April 23, 2019, facility-level data were collected for 9685 patients across 238 hospitals in 66 countries (91 hospitals in 20 high-income countries; 57 hospitals in 19 upper-middle-income countries; and 90 hospitals in 27 low-income to lower-middle-income countries). The availability of five hospital facilities was inversely associated with mortality: ultrasound, CT scanner, critical care unit, opioid analgesia, and oncologist. After adjustment for case-mix and country income group, hospitals with three or fewer of these facilities (62 hospitals, 1294 patients) had higher mortality compared with those with four or five (adjusted odds ratio [OR] 3.85 [95% CI 2.58-5.75]; p&lt;0.0001), with excess mortality predominantly explained by a limited capacity to rescue following the development of major complications (63.0% vs 82.7%; OR 0.35 [0.23-0.53]; p&lt;0.0001). Across LMICs, improvements in hospital facilities would prevent one to three deaths for every 100 patients undergoing surgery for cancer.Interpretation Hospitals with higher levels of infrastructure and resources have better outcomes after cancer surgery, independent of country income. Without urgent strengthening of hospital infrastructure and resources, the reductions in cancer-associated mortality associated with improved access will not be realised

Automated Discovery of Novel Drug Formulations Using Predictive Iterated High Throughput Experimentation

BACKGROUND: We consider the problem of optimizing a liposomal drug formulation: a complex chemical system with many components (e.g., elements of a lipid library) that interact nonlinearly and synergistically in ways that cannot be predicted from first principles. METHODOLOGY/PRINCIPAL FINDINGS: The optimization criterion in our experiments was the percent encapsulation of a target drug, Amphotericin B, detected experimentally via spectrophotometric assay. Optimization of such a complex system requires strategies that efficiently discover solutions in extremely large volumes of potential experimental space. We have designed and implemented a new strategy of evolutionary design of experiments (Evo-DoE), that efficiently explores high-dimensional spaces by coupling the power of computer and statistical modeling with experimentally measured responses in an iterative loop. CONCLUSIONS: We demonstrate how iterative looping of modeling and experimentation can quickly produce new discoveries with significantly better experimental response, and how such looping can discover the chemical landscape underlying complex chemical systems

Selected high-response formulations.

<p>Selected high-response formulations.</p

Lipid library.

<p>Lipid library.</p

Aqueous phase library.

<p>Aqueous phase library.</p