Introduction: Model-based methods can be used to characterise patient-specific condition and response to mechanical ventilation (MV) during treatment for acute respiratory distress syndrome (ARDS). Conventional metrics of respiratory mechanics are based on inspiration only, neglecting data from the expiration cycle. However, it is hypothesised that expiratory data can be used to determine an alternative metric, offering another means to track patient condition and guide positive end expiratory pressure (PEEP) selection.
Methods: Three fully sedated, oleic acid induced ARDS piglets underwent three experimental phases. Phase 1 was a healthy state recruitment manoeuvre. Phase 2 was a progression from a healthy state to an oleic acid induced ARDS state. Phase 3 was an ARDS state recruitment manoeuvre. The expiratory time-constant model parameter was determined for every breathing cycle for each subject. Trends were compared to estimates of lung elastance determined by means of an end-inspiratory pause method and an integral-based method. All experimental procedures, protocols and the use of data in this study were reviewed and approved by the Ethics Committee of the University of Liege Medical Faculty.
Results: The overall median absolute percentage fitting error for the expiratory time-constant model across all three phases was less than 10 %; for each subject, indicating the capability of the model to capture the mechanics of breathing during expiration. Provided the respiratory resistance was constant, the model was able to adequately identify trends and fundamental changes in respiratory mechanics.
Conclusion: Overall, this is a proof of concept study that shows the potential of continuous monitoring of respiratory mechanics in clinical practice. Respiratory system mechanics vary with disease state development and in response to MV settings. Therefore, titrating PEEP to minimal elastance theoretically results in optimal PEEP selection. Trends matched clinical expectation demonstrating robustness and potential for guiding MV therapy. However, further research is required to confirm the use of such real-time methods in actual ARDS patients, both sedated and spontaneously breathing.
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http://dx.doi.org/10.1186/1475-925X-12-57 | DOI Listing |
Biosens Bioelectron
January 2025
Lab of Biosystem and Microanalysis, State Key Laboratory of Bioreactor Engineering, Shanghai Collaborative Innovation Center for Biomanufacturing Technology, East China University of Science and Technology, Shanghai, 200237, China; School of Chemistry and Chemical Engineering, Shihezi University, Xinjiang, 832000, China. Electronic address:
RNA imaging technology is essential for understanding the complex RNA regulatory mechanisms and serves as a powerful tool for disease diagnosis. However, conventional RNA imaging methods often require multiple fluorescent tags for the specific labeling of individual targets, complicating both the imaging process and subsequent analysis. Herein, we develop an RNA sensor that integrates a blocked CRISPR RNA (crRNA)-based conformational switch with a controllable CRISPR activation (CRISPRa) system and apply for RNA imaging.
View Article and Find Full Text PDFJMIR Form Res
January 2025
Institute of Social Medicine, Occupational Health and Public Health, Leipzig University, Leipzig, Germany.
Background: eHealth interventions constitute a promising approach to disease prevention, particularly because of their ability to facilitate lifestyle changes. Although a rather recent development, eHealth interventions might be able to promote brain health and reduce dementia risk in older adults.
Objective: This study aimed to explore the perspective of general practitioners (GPs) on the potentials and barriers of eHealth interventions for brain health.
Am J Respir Crit Care Med
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AstraZeneca, BioPharmaceuticals R&D, Gaithersburg, Maryland, United States.
Diabetes Care
February 2025
Division of Blood Disorders and Public Health Genomics, Centers for Disease Control and Prevention, Atlanta, GA.
Objective: The goal of this study was to assess the additive value of considering type 2 diabetes (T2D) polygenic risk score (PRS) in addition to family history for T2D prediction.
Research Design And Methods: Data were obtained from the All of Us (AoU) research database. First-degree T2D family history was self-reported on the personal family history health questionnaire.
Purpose: To provide updated guidance regarding neoadjuvant chemotherapy (NACT) and primary cytoreductive surgery (PCS) among patients with stage III-IV epithelial ovarian, fallopian tube, or primary peritoneal cancer (epithelial ovarian cancer [EOC]).
Methods: A multidisciplinary Expert Panel convened and updated the systematic review.
Results: Sixty-one studies form the evidence base.
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