A detailed kinetic model of glycolysis in Plasmodium falciparum-infected red blood cells for antimalarial drug target identification.

Upon infection by the malaria parasite Plasmodium falciparum, the glycolytic rate of a red blood cell increases up to 100-fold, possibly contributing to lactic acidosis and hypoglycemia in patients with severe malaria. This dramatic increase in glucose uptake and metabolism was correctly predicted by a newly constructed detailed enzyme kinetic model of glucose metabolism in the trophozoite-infected red blood cell. Subsequently, we expanded the model to simulate an infected red blood cell culture, including the different asexual blood-stage forms of the malaria parasite. The model simulations were in good agreement with experimental data, for which the measured parasitic volume was an important parameter. Upon further analysis of the model, we identified glucose transport as a drug target that would specifically affect infected red blood cells, which was confirmed experimentally with inhibitor titrations. This model can be a first step in constructing a whole-body model for glucose metabolism in malaria patients to evaluate the contribution of the parasite's metabolism to the disease state.

Factors associated with patellofemoral pain in recreational road cyclists: A cross-sectional study in 59953 cyclists - SAFER XXXIII.

OBJECTIVE: Patellofemoral pain (PFP) is a common cycling-related injury, and independent factors need to be identified to enable effective injury prevention strategies. We aim to determine factors associated with PFP in cyclists entering mass community-based events. DESIGN: Cross-sectional study. SETTING: 2016-2020 Cape Town Cycle Tour. PARTICIPANTS: Consenting race entrants. MAIN OUTCOME MEASURES: 62758 consenting race entrants completed a pre-race medical questionnaire, and 323 reported PFP. Selected factors associated with PFP (demographics, cycling experience and training, chronic disease history) were explored using multivariate analyses. RESULTS: Prevalence ratio (PR) of PFP was similar for sex and age groups. Independent factors associated with PFP (adjusted for sex and age) were history of chronic disease [Composite Chronic Disease Score (0-10)(PR = 2.0, p < 0.0001) and any allergies (PR = 2.0, p < 0.0001)]. CONCLUSION: A history of chronic diseases and allergies is associated with PFP in cyclists. Practical clinical recommendations are: 1) that prevention programs for PFP be considered when cycling is prescribed as a physical activity intervention for patients with chronic disease, and 2) that older cyclists presenting with PFP be assessed for the presence of risk factors or existing chronic disease.

Clinical characteristics of gradual onset injuries in recreational road cyclists - SAFER XXVII study over 5 years in 62758 race entrants.

OBJECTIVE: Gradual onset injuries (GOIs) in recreational cyclists are common but not well described. The aim of this study is to describe the clinical characteristics of GOIs (main anatomical regions, specific anatomical sites, specific GOIs, tissue type, severity of GOIs, and treatment modalities) of GOIs among entrants participating in a community-based mass participation-cycling event over 5 years. METHODS: During the 2016-2020 Cape Town Cycle Tour, 62,758 consenting race entrants completed an online pre-race medical screening questionnaire. 1879 reported GOIs in the previous 12 months. In this descriptive epidemiological study, we report frequency (% entrants) of GOIs by anatomical region/sites, specific GOI, tissue type, GOI severity, and treatment modalities used. RESULTS: The main anatomical regions affected by GOIs were lower limb (47.4%), upper limb (20.1%), hip/groin/pelvis (10.0%), and lower back (7.8%). Specifically, GOI were common in the knee (32.1%), shoulder (10.6%), lower back (7.8%) and the hip/buttock muscles (5.2%). The most common specific GOI was anterior knee pain (17.2%). 57.0% of GOIs were in soft tissue. Almost half (43.9%) of cyclists with a GOI reported symptom duration >12 months, and 40.3% of GOIs were severe enough to reduce/prevent cycling. Main treatment modalities used for GOIs were rest (45.9%), physiotherapy (43.0%), stretches (33.2%), and strength exercises (33.1%). CONCLUSION: In recreational cyclists, >50% of GOIs affect the knees, shoulders, hip/buttock muscles and lower back, and 40% are severe enough to reduce/prevent cycling. Almost 45% of cyclists with GOIs in the lower back; or hip/groin/pelvis; or lower limbs; or upper limb reported a symptom duration of >12 months. Risk factors associated with GOIs need to be determined and preventative programs for GOIs need to be designed, implemented, and evaluated.

Generating Douglas-fir Breeding Value Estimates Using Airborne Laser Scanning Derived Height and Crown Metrics.

Progeny test trials in British Columbia are essential in assessing the genetic performance via the prediction of breeding values (BVs) for target phenotypes of parent trees and their offspring. Accurate and timely collection of phenotypic data is critical for estimating BVs with confidence. Airborne Laser Scanning (ALS) data have been used to measure tree height and structure across a wide range of species, ages and environments globally. Here, we analyzed a Coastal Douglas-fir [Pseudotsuga menziesii var. menziesii (Mirb.)] progeny test trial located in British Columbia, Canada, using individual tree high-density Airborne Laser Scanning (ALS) metrics and traditional ground-based phenotypic observations. Narrow-sense heritability, genetic correlations, and BVs were estimated using pedigree-based single and multi-trait linear models for 43 traits. Comparisons of genetic parameter estimates between ALS metrics and traditional ground-based measures and single- and multi-trait models were conducted based on the accuracy and precision of the estimates. BVs were estimated for two ALS models (ALSCAN and ALSACC) representing two model-building approaches and compared to a baseline model using field-measured traits. The ALSCAN model used metrics reflecting aspects of vertical distribution of biomass within trees, while ALSACC represented the most statistically accurate model. We report that the accuracy of both the ALSCAN (0.8239) and ALSACC (0.8254) model-derived BVs for mature tree height is a suitable proxy for ground-based mature tree height BVs (0.8316). Given the cost efficiency of ALS, forest geneticists should explore this technology as a viable tool to increase breeding programs' overall efficiency and cost savings.

Epidemiology, clinical characteristics and severity of gradual onset injuries in recreational road cyclists: A cross-sectional study in 21,824 cyclists - SAFER XIII.

OBJECTIVES: Prevalence, clinical characteristics and severity of gradual onset injuries (GOIs) in cyclists are poorly documented. We determine the prevalence, anatomical regions/sites affected and severity of GOIs among entrants in a community-based mass participation event. DESIGN: Cross-sectional study; SETTING: Cape Town Cycle Tour; PARTICIPANTS: Race entrants. MAIN OUTCOME MEASURES: Of 35,914 entrants, 27,349 completed pre-race medical questionnaires. We studied 21,824 consenting cyclists (60.8% of entrants). Crude lifetime prevalence, retrospective annual incidence, anatomical region/sites, specific GOI, tissue type and GOI severity is reported. RESULTS: The lifetime prevalence of GOIs was 2.8%, with an annual incidence of 2.5%. More common anatomical regions affected by GOIs were lower limb (43.4%), upper limb (19.8%), and lower back (11.5%). The knee (26.3%), shoulder (13%), and lower back (11.5%) regions were mostly affected. The most common GOI was anterior knee pain (14.2%). Of the GOIs, 55% were in soft tissue. 50% of cyclists reported symptom duration >12 months, and 37.3% of GOIs were severe enough to reduce/prevent cycling. CONCLUSION: 2.5% recreational cyclists report a GOI annually. >50% of GOIs affect the knee, lower back and shoulder. GOIs negatively affect cycling. Risk factors related to GOIs in cyclists need to be determined to develop and implement prevention programs.

History of chronic disease is a novel intrinsic risk factor associated with gradual onset injuries in recreational road cyclists: A cross-sectional study in 21,824 cyclists - SAFER XIV.

OBJECTIVES: Risk factors related to Gradual onset injuries (GOIs) in cyclists need to be identified to enable effective injury prevention strategies. We aim to determine risk factors related to GOIs in cyclists participating in mass community-based events. DESIGN: Cross-sectional study. SETTING: Cape Town Cycle Tour. PARTICIPANTS: Race entrants (n = 35,914) MAIN OUTCOME MEASURES: Completion of pre-race medical questionnaires. 21,824 consenting cyclists (60.8%) were studied. 617 cyclists reported GOIs. Selected risk factors associated with GOIs: demographics, training/racing history, chronic disease history, and medication use, were explored using multi-variate analyses. RESULTS: Prevalence ratio (PR) of GOIs was similar in males and females, but higher in older age categories [>50 yrs vs. categories: ≤30yrs (PR = 1.6); 31 to ≤40yrs (PR = 1.5); 41 to <50yrs (PR = 1.4)] (p < 0.0001). Intrinsic risk factors associated with GOIs (adjusted for gender and age) were: 1) increased weekly training/racing frequency (PR = 1.1, p = 0.0003), 2) chronic disease history [cardiovascular disease symptoms (PR = 2.3, p = 0.0026), respiratory disease (PR = 1.6, p < 0.0001), nervous system/psychiatric disease (PR = 1.5, p = 0.0082)], and 3) history of analgesic/anti-inflammatory medication (AAIM) used before/during racing (PR = 5.1, p < 0.0001). CONCLUSION: Increased training frequency, chronic disease and AAIM use are risk factors associated with GOIs in cyclists. A novel finding is that in recreational cyclists, chronic disease history could be considered when managing GOIs and implementing prevention programs.

Targeting pathogen metabolism without collateral damage to the host.

The development of drugs that can inactivate disease-causing cells (e.g. cancer cells or parasites) without causing collateral damage to healthy or to host cells is complicated by the fact that many proteins are very similar between organisms. Nevertheless, due to subtle, quantitative differences between the biochemical reaction networks of target cell and host, a drug can limit the flux of the same essential process in one organism more than in another. We identified precise criteria for this 'network-based' drug selectivity, which can serve as an alternative or additive to structural differences. We combined computational and experimental approaches to compare energy metabolism in the causative agent of sleeping sickness, Trypanosoma brucei, with that of human erythrocytes, and identified glucose transport and glyceraldehyde-3-phosphate dehydrogenase as the most selective antiparasitic targets. Computational predictions were validated experimentally in a novel parasite-erythrocytes co-culture system. Glucose-transport inhibitors killed trypanosomes without killing erythrocytes, neurons or liver cells.

Targeting glycolysis in the malaria parasite Plasmodium falciparum.

UNLABELLED: Glycolysis is the main pathway for ATP production in the malaria parasite Plasmodium falciparum and essential for its survival. Following a sensitivity analysis of a detailed kinetic model for glycolysis in the parasite, the glucose transport reaction was identified as the step whose activity needed to be inhibited to the least extent to result in a 50% reduction in glycolytic flux. In a subsequent inhibitor titration with cytochalasin B, we confirmed the model analysis experimentally and measured a flux control coefficient of 0.3 for the glucose transporter. In addition to the glucose transporter, the glucokinase and phosphofructokinase had high flux control coefficients, while for the ATPase a small negative flux control coefficient was predicted. In a broader comparative analysis of glycolytic models, we identified a weakness in the P. falciparum pathway design with respect to stability towards perturbations in the ATP demand. DATABASE: The mathematical model described here has been submitted to the JWS Online Cellular Systems Modelling Database and can be accessed at http://jjj.bio.vu.nl/database/vanniekerk1. The SEEK-study including the experimental data set is available at DOI 10.15490/seek.1. INVESTIGATION: 56 (http://dx.doi.org/10.15490/seek.1. INVESTIGATION: 56).

Quantitative analysis of drug effects at the whole-body level: a case study for glucose metabolism in malaria patients.

We propose a hierarchical modelling approach to construct models for disease states at the whole-body level. Such models can simulate effects of drug-induced inhibition of reaction steps on the whole-body physiology. We illustrate the approach for glucose metabolism in malaria patients, by merging two detailed kinetic models for glucose metabolism in the parasite Plasmodium falciparum and the human red blood cell with a coarse-grained model for whole-body glucose metabolism. In addition we use a genome-scale metabolic model for the parasite to predict amino acid production profiles by the malaria parasite that can be used as a complex biomarker.

Construction and validation of a detailed kinetic model of glycolysis in Plasmodium falciparum.

UNLABELLED: The enzymes in the Embden-Meyerhof-Parnas pathway of Plasmodium falciparum trophozoites were kinetically characterized and their integrated activities analyzed in a mathematical model. For validation of the model, we compared model predictions for steady-state fluxes and metabolite concentrations of the hexose phosphates with experimental values for intact parasites. The model, which is completely based on kinetic parameters that were measured for the individual enzymes, gives an accurate prediction of the steady-state fluxes and intermediate concentrations. This is the first detailed kinetic model for glucose metabolism in P. falciparum, one of the most prolific malaria-causing protozoa, and the high predictive power of the model makes it a strong tool for future drug target identification studies. The modelling workflow is transparent and reproducible, and completely documented in the SEEK platform, where all experimental data and model files are available for download. DATABASE: The mathematical models described in the present study have been submitted to the JWS Online Cellular Systems Modelling Database (http://jjj.bio.vu.nl/database/penkler). The investigation and complete experimental data set is available on SEEK (10.15490/seek.1. INVESTIGATION: 56).