Comprehensive stability analysis of 13 ß-lactams and ß-lactamase inhibitors in in vitro media, and novel supplement dosing strategy to mitigate thermal drug degradation.

Non-clinical antibiotic development relies on in vitro susceptibility and infection model studies. Validating the achievement of the targeted drug concentrations is essential to avoid under-estimation of drug effects and over-estimation of resistance emergence. While certain ß-lactams (e.g., imipenem) and ß-lactamase inhibitors (BLIs; clavulanic acid) are believed to be relatively unstable, limited tangible data on their stability in commonly used in vitro media are known. We aimed to determine the thermal stability of 10 ß-lactams and 3 BLIs via LC-MS/MS in cation-adjusted Mueller Hinton broth at 25 and 36°C as well as agar at 4 and 37°C, and in water at -20, 4, and 25°C. Supplement dosing algorithms were developed to achieve broth concentrations close to their target over 24 h. During incubation in broth (pH 7.25)/agar, degradation half-lives were 16.9/21.8 h for imipenem, 20.7/31.6 h for biapenem, 29.0 h for clavulanic acid (studied in broth only), 23.1/71.6 h for cefsulodin, 40.6/57.9 h for doripenem, 46.5/64.6 h for meropenem, 50.8/97.7 h for cefepime, 61.5/99.5 h for piperacillin, and >120 h for all other compounds. Broth stability decreased at higher pH. All drugs were ≥90% stable for 72 h in agar at 4°C. Degradation half-lives in water at 25°C were >200 h for all drugs except imipenem (14.7 h, at 1,000 mg/L) and doripenem (59.5 h). One imipenem supplement dose allowed concentrations to stay within ±31% of their target concentration. This study provides comprehensive stability data on ß-lactams and BLIs in relevant in vitro media using LC-MS/MS. Future studies are warranted applying these data to antimicrobial susceptibility testing and assessing the impact of ß-lactamase-related degradation.

Next generation antibiotic combinations to combat pan-drug resistant Klebsiella pneumoniae.

Antimicrobial resistance has emerged as one of the leading public health threats of the twenty-first century. Gram-negative pathogens have been a major contributor to the declining efficacy of antibiotics through both acquired resistance and tolerance. In this study, a pan-drug resistant (PDR), NDM-1 and CTX-M-15 co-producing isolate of K. pneumoniae, CDC Nevada, (Kp Nevada) was exposed to the clinical combination of aztreonam + ceftazidime/avibactam (ATM/CAZ/AVI) to overcome metallo-ß-lactamases. Unexpectedly, the ß-lactam combination resulted in long filamentous cell formation induced by PBP3 inhibition over 168 h in the hollow fiber infection model experiments with eventual reversion of the total population upon drug removal. However, the addition of imipenem to the two drug ß-lactam combination was highly synergistic with suppression of all drug resistant subpopulations over 5 days. Scanning electron microscopy and fluorescence microscopy for all imipenem combinations in time kill studies suggested a role for imipenem in suppression of long filamentous persisters, via the formation of metabolically active spheroplasts. To complement the imaging studies, salient transcriptomic changes were quantified using RT-PCR and novel cassette assay evaluated ß-lactam permeability. This showed significant upregulation of both spheroplast protein Y (SPY), a periplasmic chaperone protein that has been shown to be related to spheroplast formation, and penicillin binding proteins (PBP1, PBP2, PBP3) for all combinations involving imipenem. However, with aztreonam alone, pbp1, pbp3 and spy remained unchanged while pbp2 levels were downregulated by > 25%. Imipenem displayed 207-fold higher permeability as compared with aztreonam (mean permeability coefficient of 17,200 nm/s). Although the clinical combination of aztreonam/avibactam and ceftazidime has been proposed as an important treatment of MBL Gram-negatives, we report the first occurrence of long filamentous persister formation. To our knowledge, this is the first study that defines novel ß-lactam combinations involving imipenem via maximal suppression of filamentous persisters to combat PDR CDC Nevada K. pneumoniae.

Machine Learning-Led Optimization of Combination Therapy: Confronting the Public Health Threat of Extensively Drug Resistant Gram-Negative Bacteria.

Developing optimized regimens for combination antibiotic therapy is challenging and often performed empirically over many clinical studies. Novel implementation of a hybrid machine-learning pharmacokinetic/pharmacodynamic/toxicodynamic (ML-PK/PD/TD) approach optimizes combination therapy using human PK/TD data along with in vitro PD data. This study utilized human population PK (PopPK) of aztreonam, ceftazidime/avibactam, and polymyxin B along with in vitro PDs from the Hollow Fiber Infection Model (HFIM) to derive optimal multi-drug regimens de novo through implementation of a genetic algorithm (GA). The mechanism-based PD model was constructed based on 7-day HFIM experiments across 4 clinical, extensively drug resistant Klebsiella pneumoniae isolates. GA-led optimization was performed using 13 different fitness functions to compare the effects of different efficacy (60%, 70%, 80%, or 90% of simulated subjects achieving bacterial counts of 102 CFU/mL) and toxicity (66% of simulated subjects having a target polymyxin B area under the concentration-time curve [AUC] of 100 mg·h/L and aztreonam AUC of 1,332 mg·h/L) on the optimized regimen. All regimens, except those most heavily weighted for toxicity prevention, were able to achieve the target efficacy threshold (102 CFU/mL). Overall, GA-based regimen optimization using preclinical data from animal-sparing in vitro studies and human PopPK produced clinically relevant dosage regimens similar to those developed empirically over many years for all three antibiotics. Taken together, these data provide significant insight into new therapeutic approaches incorporating ML to regimen design and treatment of resistant bacterial infections.

Urinary biomarkers as indicators of acute kidney injury in critically ill children exposed to vancomycin.

STUDY OBJECTIVE: The standard of care for detecting acute kidney injury (AKI) is change in serum creatinine (SCr) and urine output, which are limited. This study aimed to compare urinary biomarkers neutrophil gelatinase-associated lipocalin (uNGAL) with kidney injury molecule-1 (uKIM-1) in critically ill children exposed to vancomycin who did and did not develop AKI as defined by changes in SCr. DESIGN: Single-center, prospective, clinical, observational cohort study. SETTING: Tertiary care children's hospital in an urban setting. PATIENTS: Children aged 0 (corrected gestational age 42 weeks) to 18 years admitted to the intensive care unit who received vancomycin were included. INTERVENTION: None. MEASUREMENTS: The primary outcome was mean change in uNGAL and uKIM-1 between AKI and no-AKI groups. AKI was defined as a minimum 50% increase in SCr from baseline over a 48 h period, within 7 days of first vancomycin exposure. Three urine samples were collected: baseline (between 0 and 6 h of first vancomycin dose), second (18-24 h after the "baseline"), and third (18-24 h after the second sample). Concentrations of uKIM-1 and uNGAL were measured in each sample. MAIN RESULTS: Forty-eight children (52% male; median age 6 years) were included. Eight (16.7%) children developed AKI. Mean changes in uNGAL (713.196 ± 1,216,474 vs. 16.101 ± 37.812 pg/mL; p = 0.0004) and uKIM-1 (6060 ± 11.165 vs. 340 ± 542 pg/mL; p = 0.0015) were greater in children with AKI versus no-AKI, respectively. CONCLUSIONS: uNGAL and uKIM-1 concentrations increased significantly more in critically ill children with AKI compared with those with no-AKI during the first 48-72 h of vancomycin exposure and may be useful as prospective biomarkers of AKI.

A mechanism-based pathway toward administering highly active N-phage cocktails.

Bacteriophage (phage) therapy is being explored as a possible response to the antimicrobial resistance public health emergency. Administering a mixture of different phage types as a cocktail is one proposed strategy for therapeutic applications, but the optimal method for formulating phage cocktails remains a major challenge. Each phage strain has complex pharmacokinetic/pharmacodynamic (PK/PD) properties which depend on the nano-scale size, target-mediated, self-dosing nature of each phage strain, and rapid selection of resistant subpopulations. The objective of this study was to explore the pharmacodynamics (PD) of three unique and clinically relevant anti-Pseudomonas phages after simulation of dynamic dosing strategies. The Hollow Fiber Infection Model (HFIM) is an in vitro system that mimics in vivo pharmacokinetics (PK) with high fidelity, providing an opportunity to quantify phage and bacteria concentration profiles over clinical time scales with rich sampling. Exogenous monotherapy-bolus (producing max concentrations of Cmax = 7 log10 PFU/mL) regimens of phages LUZ19, PYO2, and E215 produced Pseudomonas aeruginosa nadirs of 0, 2.14, or 2.99 log10 CFU/mL after 6 h of treatment, respectively. Exogenous combination therapy bolus regimens (LUZ19 + PYO2 or LUZ19 + E215) resulted in bacterial reduction to <2 log10 CFU/mL. In contrast, monotherapy as a continuous infusion (producing a steady-state concentration of Css,avg = 2 log10PFU/mL) was less effective at reducing bacterial densities. Specifically, PYO2 failed to reduce bacterial density. Next, a mechanism-based mathematical model was developed to describe phage pharmacodynamics, phage-phage competition, and phage-dependent adaptive phage resistance. Monte Carlo simulations supported bolus dose regimens, predicting lower bacterial counts with bolus dosing as compared to prolonged phage infusions. Together, in vitro and in silico evaluation of the time course of phage pharmacodynamics will better guide optimal patterns of administration of individual phages as a cocktail.

Bayesian optimization of tacrolimus exposure in stable kidney transplant patients.

STUDY OBJECTIVE: The objective was to compare tacrolimus AUC0-12 determined by Non-Compartmental Analysis (NCA) using intensive sampling to Maximum a Posteriori-Bayesian (MAP-Bayesian) estimates from robust (n = 9 samples/subject) and sparse (n = 2 samples/subject) sampling in 67 stable KTRs and a validation group of similar patients. DESIGN: This open-label, prospective, single center 12-h PK study included nine serial samples collected in KTRs to determine steady-state NCA tacrolimus AUC0-12 . SETTING: This study was conducted at a single site within a large, urban hospital in the western New York area. PATIENTS: This study described tacrolimus pharmacokinetics in stable kidney transplant recipients on maintenance tacrolimus therapy. INTERVENTION: Robust and sparse AUC0-12 estimates by a MAP-Bayesian approach were obtained using the Advanced Dosing Solutions (AdDS) and ADAPT5 freeware. Limited sampling strategies were evaluated using the original population PK model (n = 67), which was also assessed using a validation group (n = 15). AUC0-12 agreement was tested by paired t-tests with intraclass correlation coefficient (ICC) and Bland Altman analysis. MEASUREMENTS AND MAIN RESULTS: A total of 35 Black and 32 White stable KTRs (estimated glomerular filtration rate [eGFR] = 55.2 ± 15.7 mL/min/1.73m2 ) received the tacrolimus dose of 3.4 ± 1.7 mg/study with troughs of 6.8 ± 1.8 ng/mL. The NCA-AUC0-12 was 123.8 ± 33.6 µg·h/L compared to MAP-Bayesian estimates for Robust-AUC0-12 of 124.7 ± 33.3 µg·h/L and optimal 2-specimen Sparse-AUC0-12 of 119.7 ± 32.7 µg·h/L for the training group. Comparison of Robust-AUC0-12 to NCA-AUC0-12 had an ICC of 0.96 (p = 0.99) while comparison of Robust-AUC0-12 to Sparse-AUC0-12 using Pre-dose trough [C(t0h )] and 1 h [C(t1h )] resulted in an ICC of 0.93 (p = 0.014). In the validation group, 5 Black and 10 White KTRs (eGFR = 56.4 ± 16.8 mL/min/1.73m2 ) received a mean tacrolimus dose of 1.9 ± 1.2 mg/study with a trough of 6.0 ± 1.7 ng/mL. The validation group's NCA-AUC0-12 (88.4 ± 33.1 µg·h/L) was comparable to Robust-AUC0-12 (85.1 ± 33.8 µg·h/L, ICC = 0.93; p = 0.12) and Sparse-AUC0-12 determined from C(t0h ) and C(t4h ) (86.7 ± 33.9 µg·h/L, ICC = 0.91; p = 0.61). CONCLUSION: MAP-Bayesian estimation for patient-specific AUC0-12 using sparse, two-specimen sampling is comparable to NCA and may enhance tacrolimus TDM in stable KTRs.

Computed cardiopulmonography and the idealized lung clearance index, iLCI2.5, in early-stage cystic fibrosis.

This study explored the use of computed cardiopulmonography (CCP) to assess lung function in early-stage cystic fibrosis (CF). CCP has two components. The first is a particularly accurate technique for measuring gas exchange. The second is a computational cardiopulmonary model where patient-specific parameters can be estimated from the measurements of gas exchange. Twenty-five participants (14 healthy controls, 11 early-stage CF) were studied with CCP. They were also studied with a standard clinical protocol to measure the lung clearance index (LCI2.5). Ventilation inhomogeneity, as quantified through CCP parameter σlnCl, was significantly greater (P < 0.005) in CF than in controls, and anatomical deadspace relative to predicted functional residual capacity (DS/FRCpred) was significantly more variable (P < 0.002). Participant-specific parameters were used with the CCP model to calculate idealized values for LCI2.5 (iLCI2.5) where extrapulmonary influences on the LCI2.5, such as breathing pattern, had all been standardized. Both LCI2.5 and iLCI2.5 distinguished clearly between CF and control participants. LCI2.5 values were mostly higher than iLCI2.5 values in a manner dependent on the participant's respiratory rate (r = 0.46, P < 0.05). The within-participant reproducibility for iLCI2.5 appeared better than for LCI2.5, but this did not reach statistical significance (F ratio = 2.2, P = 0.056). Both a sensitivity analysis on iLCI2.5 and a regression analysis on LCI2.5 revealed that these depended primarily on an interactive term between CCP parameters of the form σlnCL*(DS/FRC). In conclusion, the LCI2.5 (or iLCI2.5) probably reflects an amalgam of different underlying lung changes in early-stage CF that would require a multiparameter approach, such as potentially CCP, to resolve.NEW & NOTEWORTHY Computed cardiopulmonography is a new technique comprising a highly accurate sensor for measuring respiratory gas exchange coupled with a cardiopulmonary model that is used to identify a set of patient-specific characteristics of the lung. Here, we show that this technique can improve on a standard clinical approach for lung function testing in cystic fibrosis. Most particularly, an approach incorporating multiple model parameters can potentially separate different aspects of pathological change in this disease.

The Lognormal Lung: A new approach to quantifying lung inhomogeneity in COPD.

Early diagnosis and disease phenotyping in COPD are currently limited by the use of spirometry, which may remain normal despite significant small-airways disease and which may not fully capture a patient's underlying pathophysiology. In this study we explored the use of a new non-invasive technique that assesses gas-exchange inhomogeneity in patients with COPD of varying disease severity (according to GOLD Stage), compared with age-matched healthy controls. The technique, which combines highly accurate measurement of respiratory gas exchange using a bespoke molecular flow sensor and a mechanistic mathematical model of the lung, provides new indices of lung function: the parameters σCL, σCd, and σVD represent the standard deviations of distributions for alveolar compliance, anatomical deadspace and vascular conductance relative to lung volume, respectively. It also provides parameter estimates for total anatomical deadspace and functional residual capacity (FRC). We demonstrate that these parameters are robust and sensitive, and that they can distinguish between healthy individuals and those with mild-moderate COPD (stage 1-2), as well as distinguish between mild-moderate COPD (stage 1-2) and more severe (stage 3-4) COPD. In particular, σCL, a measure of unevenness in lung inflation/deflation, could represent a more sensitive non-invasive marker of early or mild COPD. In addition, by providing a multi-dimensional assessment of lung physiology, this technique may also give insight into the underlying pathophysiological phenotype for individual patients. These preliminary results warrant further investigation in larger clinical research studies, including interventional trials.

Altered lung physiology in two cohorts after COVID-19 infection as assessed by computed cardiopulmonography.

The longer-term effects of COVID-19 on lung physiology remain poorly understood. Here, a new technique, computed cardiopulmonography (CCP), was used to study two COVID-19 cohorts (MCOVID and C-MORE-LP) at both ∼6 and ∼12 mo after infection. CCP is comprised of two components. The first is collection of highly precise, highly time-resolved measurements of gas exchange with a purpose-built molecular flow sensor based around laser absorption spectroscopy. The second component is estimation of physiological parameters by fitting a cardiopulmonary model to the data set. The measurement protocol involved 7 min of breathing air followed by 5 min of breathing pure O2. One hundred seventy-eight participants were studied, with 97 returning for a repeat assessment. One hundred twenty-six arterial blood gas samples were drawn from MCOVID participants. For participants who had required intensive care and/or invasive mechanical ventilation, there was a significant increase in anatomical dead space of ∼30 mL and a significant increase in alveolar-to-arterial Po2 gradient of ∼0.9 kPa relative to control participants. Those who had been hospitalized had reductions in functional residual capacity of ∼15%. Irrespectively of COVID-19 severity, participants who had had COVID-19 demonstrated a modest increase in ventilation inhomogeneity, broadly equivalent to that associated with 15 yr of aging. This study illustrates the capability of CCP to study aspects of lung function not so easily addressed through standard clinical lung function tests. However, without measurements before infection, it is not possible to conclude whether the findings relate to the effects of COVID-19 or whether they constitute risk factors for more serious disease.NEW & NOTEWORTHY This study used a novel technique, computed cardiopulmonography, to study the lungs of patients who have had COVID-19. Depending on severity of infection, there were increases in anatomical dead space, reductions in absolute lung volumes, and increases in ventilation inhomogeneity broadly equivalent to those associated with 15 yr of aging. However, without measurements taken before infection, it is unclear whether the changes result from COVID-19 infection or are risk factors for more severe disease.

Mechanistic Insights to Combating NDM- and CTX-M-Coproducing Klebsiella pneumoniae by Targeting Cell Wall Synthesis and Outer Membrane Integrity.

Metallo-ß-lactamase (MBL)-producing Gram-negative bacteria cause infections associated with high rates of morbidity and mortality. Currently, a leading regimen to treat infections caused by MBL-producing bacteria is aztreonam combined with ceftazidime-avibactam. The purpose of the present study was to evaluate and rationally optimize the combination of aztreonam and ceftazidime-avibactam with and without polymyxin B against a clinical Klebsiella pneumoniae isolate producing NDM-1 and CTX-M by use of the hollow fiber infection model (HFIM). A novel de-escalation approach to polymyxin B dosing was also explored, whereby a standard 0-h loading dose was followed by maintenance doses that were 50% of the typical clinical regimen. In the HFIM, the addition of polymyxin B to aztreonam plus ceftazidime-avibactam significantly improved bacterial killing, leading to eradication, including for the novel de-escalation dosing strategy. Serial samples from the growth control and monotherapies were explored in a Galleria mellonella virulence model to assess virulence changes. Weibull regression showed that low-level ceftazidime resistance and treatment with monotherapy resulted in increased G. mellonella mortality (P < 0.05). A neutropenic rabbit pneumonia model demonstrated that aztreonam plus ceftazidime-avibactam with or without polymyxin B resulted in similar bacterial killing, and these combination therapies were statistically significantly better than monotherapies (P < 0.05). However, only the polymyxin B-containing combination therapy produced a statistically significant decrease in lung weights (P < 0.05), indicating a decreased inflammatory process. Altogether, adding polymyxin B to the combination of aztreonam plus ceftazidime-avibactam for NDM- and CTX-M-producing K. pneumoniae improved bacterial killing effects, reduced lung inflammation, suppressed resistance amplification, and limited virulence changes.

Different Genes are Recruited During Convergent Evolution of Pregnancy and the Placenta.

The repeated evolution of the same traits in distantly related groups (convergent evolution) raises a key question in evolutionary biology: do the same genes underpin convergent phenotypes? Here, we explore one such trait, viviparity (live birth), which, qualitative studies suggest, may indeed have evolved via genetic convergence. There are >150 independent origins of live birth in vertebrates, providing a uniquely powerful system to test the mechanisms underpinning convergence in morphology, physiology, and/or gene recruitment during pregnancy. We compared transcriptomic data from eight vertebrates (lizards, mammals, sharks) that gestate embryos within the uterus. Since many previous studies detected qualitative similarities in gene use during independent origins of pregnancy, we expected to find significant overlap in gene use in viviparous taxa. However, we found no more overlap in uterine gene expression associated with viviparity than we would expect by chance alone. Each viviparous lineage exhibits the same core set of uterine physiological functions. Yet, contrary to prevailing assumptions about this trait, we find that none of the same genes are differentially expressed in all viviparous lineages, or even in all viviparous amniote lineages. Therefore, across distantly related vertebrates, different genes have been recruited to support the morphological and physiological changes required for successful pregnancy. We conclude that redundancies in gene function have enabled the repeated evolution of viviparity through recruitment of different genes from genomic "toolboxes", which are uniquely constrained by the ancestries of each lineage.

Age- and size-corrected kicking speed and accuracy in elite junior soccer players.

Kicking powerfully and accurately is essential in soccer, and players who kick proficiently with both feet are highly sought after. Assessing performance in youth players is often confounded by more physically developed players outperforming their smaller peers. To alleviate such bias, we present a testing protocol and normative data developed with an elite Brazilian soccer academy that controls for players' age and size to assess kick performance with both feet. We measured kick speed and kick accuracy of 178 players and recorded their age (10-20 years), height, and mass. Combining age, height, and mass into an age and size index (ASI), we developed equations describing the relationship between ASI and performance. To determine the underlying predictors of performance, we also measured sprint ability and soccer-specific motor control of each foot with ball dribbling tasks. Kicking speed with the dominant foot was predicted by ASI, sprint speed, and motor control of the nondominant foot, while kicking speed with the nondominant foot was predicted by ASI and motor control of the nondominant foot. Kick accuracy with each foot was predicted by ASI and motor control of the corresponding foot. To improve kicking performance, we suggest training programs focus on motor control.

Open-source maximum a posteriori-bayesian dosing AdDS to current therapeutic drug monitoring: Adapting to the era of individualized therapy.

Recent updates in the therapeutic drug monitoring (TDM) guidelines for vancomycin have rekindled interest in maximum a posteriori-Bayesian (MAP-Bayesian) estimation of patient-specific pharmacokinetic parameters. To create a versatile infrastructure for MAP-Bayesian dosing of vancomycin or other drugs, a freely available, R-based software package, Advanced Dosing Solutions (AdDS), was created to facilitate clinical implementation of these improved TDM methods. The objective of this study was to utilize AdDS for pre- and post-processing of data in order to streamline the therapeutic management of vancomycin in healthy and obese veterans. Patients from a local Veteran Affairs hospital were utilized to compare the process of full re-estimation versus Bayesian updating of priors on healthy adult and obese patient populations for use with AdDS. Twenty-four healthy veterans were utilized to train (14/24) and test (10/24) the base pharmacokinetic model of vancomycin while comparing the effects of updated and fully re-estimated priors. This process was repeated with a total of 18 obese veterans for both training (11/18) and testing (7/18). Comparison of MAP objective function between the original and re-estimated models for healthy adults indicated that 78.6% of the subjects in the training and 70.0% of the subjects in the testing datasets had similar or improved predictions by the re-estimated model. For obese veterans, 81.8% of subjects in the training dataset and 85.7% of subjects in the testing dataset had similar or improved predictions. Re-estimation of model parameters provided more significant improvements in objective function compared with Bayesian updating, which may be a useful strategy in cases where sufficient samples and subjects are available. The generation of bespoke regimens based on patient-specific clearance and minimal sampling may improve patient care by addressing fundamental pharmacokinetic differences in healthy and obese veteran populations.

Prospects in Connecting Genetic Variation to Variation in Fertility in Male Bees.

Bees are economically and ecologically important pollinating species. Managed and native bee species face increasing pressures from human-created stressors such as habitat loss, pesticide use, and introduced pathogens. There has been increasing attention towards how each of these factors impacts fertility, especially sperm production and maintenance in males. Here, we turn our attention towards another important factor impacting phenotypic variation: genetics. Using honey bees as a model, we explore the current understanding of how genetic variation within and between populations contributes to variation in sperm production, sperm maintenance, and insemination success among males. We conclude with perspectives and future directions in the study of male fertility in honey bees and non-Apis pollinators more broadly, which still remain largely understudied.

Simple and reliable protocol for identifying talented junior players in team sports using small-sided games.

We designed and tested a protocol for measuring the performance of individuals in small-sided soccer games. We tested our protocol on three different groups of youth players from elite Brazilian football academies. Players in each group played a series of 3v3 games, in which individuals were randomly assigned into new teams and against new opponents for each game. We calculated each individual's average individual goals scored, goals scored by teammates, goals conceded, and net team goals per game. Our protocol was consistent across days and repeatable across groups, with intraclass correlation coefficients (ICCs) of 0.57-0.69 for average net goals per game across testing days. Players could achieve high success by scoring goals or ensuring their team concede few goals. We also calculated the first and second dimension of a principal component analysis based on each player's number of goals scored, goals scored by teammates, and number of goals conceded per game. Players that were overall high performers had higher PC1 scores, while PC2 scores represented the type of contribution made by a player to overall performance. Positive PC2 values were indicative of high number of individual goals while negative values were associated with more goals from teammates and fewer conceded goals. Our design allows coaches and scouts to easily collect a robust metric of individual performance using randomly designed, small-sided games. We also provide simulations that allow one to apply our methodology for individual talent identification to other small-sided games in any team sport.

Development of in-airway laser absorption spectroscopy for respiratory based measurements of cardiac output.

Respiratory approaches to determining cardiac output in humans are securely rooted in mass balance and therefore potentially highly accurate. To address existing limitations in the gas analysis, we developed an in-airway analyser based on laser absorption spectroscopy to provide analyses every 10 ms. The technique for estimating cardiac output requires both a relatively soluble and insoluble tracer gas, and we employed acetylene and methane for these, respectively. A multipass cell was used to provide sufficient measurement sensitivity to enable analysis directly within the main gas stream, thus avoiding errors introduced by sidestream gas analysis. To assess performance, measurements of cardiac output were made during both rest and exercise on five successive days in each of six volunteers. The measurements were extremely repeatable (coefficient of variation ~ 7%). This new measurement technology provides a stable foundation against which the algorithm to calculate cardiac output can be further developed.

Interaction of Staphylococcus aureus and Acinetobacter baumannii during In Vitro ß-Lactam Exposure.

We sought to determine if Acinetobacter baumannii is capable of altering the pharmacodynamics of an antistaphylococcal ß-lactam. Two strains of methicillin-susceptible Staphylococcus aureus (MSSA) and two A. baumannii isolates were studied in 24-h static time-killing experiments under monoculture or coculture conditions. Bacterial killing of meropenem was described using an empirical pharmacokinetics/pharmacodynamics model that was developed using Hill functions. A mechanism-based pharmacodynamic model was also used to describe the effect of meropenem on each species of bacterium, interspecies interactions, and strain-based covariate effects. Monte Carlo simulations of bacterial killing effects were generated based on the population pharmacokinetics of meropenem in 2,500 simulated critically ill subjects over 48 h. Against one of the two MSSA isolates, the magnitude of bacterial killing (EΔ) decreased from -4.61 (95% confidence interval [CI], -5.85 to -3.38) to -2.23 (95% CI, -2.85 to -1.61) when cultured in the presence of carbapenem-resistant A. baumannii (CRAB). Similarly, the data were best described by a mechanism-based model where the number of A. baumannii cells produced a systematic increase in the S. aureus concentration for a 50% maximum killing effect (KC50) of 3.53-fold, thereby decreasing MSSA sensitivity to meropenem. A covariate effect by the CRAB isolate resulted in a more pronounced increase in the MSSA KC50 for meropenem (31.8-fold increase). However, Monte Carlo simulations demonstrated that a high-intensity meropenem regimen is capable of sustained killing against both MSSA isolates despite protection from A. baumannii Thus, A. baumannii and MSSA engage in complex interactions during ß-lactam exposure, but optimal antimicrobial dosing is likely capable of killing MSSA despite the potentially beneficial interplay with A. baumannii.

Bacterial Mixology: Combining Pharmacodynamic Models to Predict In Vitro Competition of MCR-1-Harboring E. coli.

The emergence of mobile colistin resistance (mcr)-mediated polymyxin resistance has resulted in a significant detriment to the utility of the polymyxins in the clinical setting. Though the risk for horizontal transfer of an mcr-containing plasmid is a major component of the transmissibility, selection of polymyxin resistant subpopulations is still a major risk factor for developing polymyxin-resistant infections. Using static time-kills over 24 h (h), we performed competition studies by mixing known inocula of isogenic Escherichia coli strains (wildtype [WT] and mcr-1-harboring) and treating with a concentration array of polymyxin B. These results were then compared to a priori predictions of bacterial-killing effects by polymyxin B on a mixed population of E. coli cells using a previously published mechanism-based model. The data showed that both selective pressure between WT and mcr-1-harboring strains as well as underlying polymyxin B heteroresistance within each of the two strains contributed to bacterial regrowth despite treatment with high concentration polymyxin B. Moreover, the simulations showed that when mcr-1-harboring cells were 1% or 10% of the total population, regrowth by 24 h was still observed in ≥50% of the simulated subjects for both a 106 and 108 inoculum. These results indicate that at lower inoculums with a low proportion of mcr-1-harboring cells, selective pressure from a pharmacokinetic-optimized regimen of polymyxin B still results in regrowth and selection of polymyxin-resistant cells.