Combination antifungal therapy is widely used but not well understood. We analyzed the spectrophotometric readings from a multicenter study conducted by the New York State Department of Health to further characterize the in vitro interactions of the major classes of antifungal agents against Candida spp. Loewe additivity-based fractional inhibitory concentration index (FICi) analysis and Bliss independence-based response surface (BIRS) analysis were used to analyze two-drug inter- and intraclass combinations of triazoles (AZO) (voriconazole, posaconazole), echinocandins (ECH) (caspofungin, micafungin, anidulafungin), and a polyene (amphotericin B) against Candida albicans, C. parapsilosis, and C. glabrata. Although mean FIC indices did not differ statistically significantly from the additivity range of 0.5−4, indicating no significant pharmacodynamic interactions for all of the strain−combinations tested, BIRS analysis showed that significant pharmacodynamic interactions with the sum of percentages of interactions determined with this analysis were strongly associated with the FIC indices (Χ2 646, p < 0.0001). Using a narrower additivity range of 1−2 FIC index analysis, statistically significant pharmacodynamic interactions were also found with FICi and were in agreement with those found with BIRS analysis. All ECH+AB combinations were found to be synergistic against all Candida strains except C. glabrata. For the AZO+AB combinations, synergy was found mostly with the POS+AB combination. All AZO+ECH combinations except POS+CAS were synergistic against all Candida strains although with variable magnitude; significant antagonism was found for the POS+MIF combination against C. albicans. The AZO+AZO combination was additive for all strains except for a C. parapsilosis strain for which antagonism was also observed. The ECH+ECH combinations were synergistic for all Candida strains except C. glabrata for which they were additive; no antagonism was found.
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http://dx.doi.org/10.3390/jof8090967 | DOI Listing |
Healthcare (Basel)
November 2024
Department of Radiology, College of Medicine and Health Sciences, United Arab Emirates University, Al Ain P.O. Box 15551, United Arab Emirates.
Sensors (Basel)
August 2024
Department of Electromechanics, System and Metal Engineering, Ghent University, Tech Lane Science Park 125, 9052 Ghent, Belgium.
Tissue hysteresivity is an important marker for determining the onset and progression of respiratory diseases, calculated from forced oscillation lung function test data. This study aims to reduce the number and duration of required measurements by combining multivariate data from various sensing devices. We propose using the Forced Oscillation Technique (FOT) lung function test in both a low-frequency prototype and the commercial RESMON device, combined with continuous monitoring from the Equivital (EQV) LifeMonitor and processed by artificial intelligence (AI) algorithms.
View Article and Find Full Text PDFSensors (Basel)
March 2024
Department of Anesthesia, Ghent University Hospital, Corneel Heymanslaan 10, 9000 Ghent, Belgium.
In this paper, we present the development and the validation of a novel index of nociception/anti-nociception (N/AN) based on skin impedance measurement in time and frequency domain with our prototype AnspecPro device. The primary objective of the study was to compare the Anspec-PRO device with two other commercial devices (Medasense, Medstorm). This comparison was designed to be conducted under the same conditions for the three devices.
View Article and Find Full Text PDFObjective: The problem of reliable and widely accepted measures of pain is still open. It follows the objective of this work as pain estimation through post-surgical trauma modeling and classification, to increase the needed reliability compared to measurements only.
Methods: This article proposes (i) a recursive identification method to obtain the frequency response and parameterization using fractional-order impedance models (FOIM), and (ii) deep learning with convolutional neural networks (CNN) classification algorithms using time-frequency data and spectrograms.
Sci Educ (Dordr)
April 2023
Department of Biological Sciences, Purdue University, West Lafayette, IN USA.
Unlabelled: Science educators report that students struggle with understanding, using, and evaluating the evidence underpinning scientific knowledge. However, there are not many studies focused on helping instructors address those difficulties. Here, we report on a laboratory instructor's scaffolding of students' evidentiary reasoning with and about evidence for evolutionary trees with guidance from the Conceptual Analysis of Disciplinary Evidence (CADE) framework, which links biological knowledge with epistemic considerations.
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