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Spring, L.

Publications and source records attributed to Spring, L..

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Intubation and mechanical ventilation lead to an extensive expansion of VAP-associated bacterial species in respiratory secretions of ventilated pigs

Ventilator associated pneumonia (VAP) remains one of the most critical nosocomial infections in intensive care medicine. Between 20-50% of ventilated patients develop VAP during treatment, often leading to long term sequelae and death, despite successful therapy of their underlying disease. VAP is typically caused by Gram-negative bacteria that can previously be detected on the mucosal membranes of the oral and upper respiratory tract. To assess and quantify bacterial colonization of the respiratory tract following intubation and ventilation a well-established pig model was used. Methods: After induction of anaesthesia and endotracheal intubation pigs underwent mechanical ventilation continuously for up to three days. To assess bacterial colonization of the upper respiratory tract, samples of respiratory secretions were taken at day 0, 1 and 2 directly above the cuff outside of the endotracheal tube (ETT) and by aspiration of tracheal secretions through the ETT. Quantification of bacteria was carried out by serial dilutions and CFU/ml determinations on sheep blood agar and MacConkey agar plates. Species identification was achieved by 16S-RNA gene sequencing. Results: Respiratory samples of 19 pigs were analysed and showed a sharp increase of predominantly Gram-negative organisms in the respiratory material sampled above the cuff from day 0 to 1. Starting at a median of 7.3 x 103 immediately after intubation numbers increased to a median of 2.0 x 107 Gram-negative bacteria at day 1 and 3.2 x 107 at day 2. Gram-negative species that were detected included Pseudomonas aeruginosa, Acinetobacter baumanii, Enterobacter aerogenes, Klebsiella pneumoniae and other Enterobacteriaceae. Tracheal secretions contained much less bacteria. While no Gram-negative bacteria could be cultured at the beginning of the experiment in 18 of 19 animals, colonization with Gram-negative bacteria gradually increased and was found in 7 of 19 and 9 of 14 animals on day 1 and day 2 respectively. Interestingly, in the vast majority of colonized tracheal secretions the identical Gram-negative species had previously been detected in secretions collected > 24h earlier at the cuff. Conclusion: A massive increase of the concentration of Gram-negative bacteria occurred at 24h of ventilation in mucosal secretions above the cuff. Detected species were the same Gram-negative bacteria that are frequently responsible for human infections, suggesting that especially the accumulation of bacteria in secretions above the cuff may be crucial in the development of VAP.

microbiology↗

Reconstructing tumor trajectories during therapy through integration of multiple measurement modalities.

BackgroundAccurately determining changes in tumor size during therapy is essential to evaluating response or progression. However, individual imaging methodologies often poorly reflect pathologic response and long-term treatment efficacy in patients with estrogen receptor positive (ER+) early-stage breast cancer. Mathematical models that measure tumor progression over time by integrating diverse imaging and tumor measurement modalities are not currently used but could increase accuracy in measuring response and provide biological insights into cancer evolution. MethodsFor ER+ breast cancer patients enrolled on a neoadjuvant clinical trial, we reconstructed their tumor size trajectories during therapy by combining all available information on tumor size, including different imaging modalities, physical examinations and pathological assessment data. Tumor trajectories during six months of treatment were generated, using a Gaussian process and the most probable trajectories were evaluated, based on clinical data, using measurement models that account for biases and differences in precision between tumor measurement methods, such as MRI, ultrasound and mammograms. ResultsReconstruction of tumor trajectories during treatment identified five distinct patterns of tumor size changes, including rebound growth not evident from any single modality. These results increase specificity to distinguish innate or acquired resistance compared to using any single measurement alone. The speed of therapeutic response and extent of subsequent rebound tumor growth quantify sensitivity or resistance in this patient population. ConclusionsTumor trajectory reconstruction integrating multiple modalities of tumor measurement accurately describes tumor progression on therapy and reveals various patterns of patient responses. Mathematical models can integrate diverse response assessments and account for biases in tumor measurement, thereby providing insights into the timing and rate at which resistance emerges.

systems biology↗