Intraoperative Modulation of Alveolar Macrophage Function during Isoflurane and Propofol Anesthesia 

1998 ◽  
Vol 89 (5) ◽  
pp. 1125-1132 ◽  
Author(s):  
Naoki Kotani ◽  
Hiroshi Hashimoto ◽  
Daniel I. Sessler ◽  
Atsuhiro Kikuchi ◽  
Akiko Suzuki ◽  
...  
Keyword(s):  
Alveolar Macrophage ◽  
Alveolar Macrophages ◽  
Orthopedic Surgery ◽  
Pulmonary Infection ◽  
Time Dependent ◽  
Critical Part ◽  
Isoflurane Anesthesia ◽  
Immunologic Function ◽  
Over Time ◽  
Number Of Particles

Background Alveolar macrophages are a critical part of the defense against pulmonary infection. Thus the authors determined time-dependent changes in alveolar macrophage functions in patients having surgery who were anesthetized with isoflurane or propofol. Methods Patients anesthetized with propofol (n = 30) or isoflurane (n = 30) during orthopedic surgery were studied. Alveolar macrophages were harvested by bronchoalveolar lavage immediately, and 2, 4, and 6 h after induction anesthesia and at the end of surgery. The fraction of aggregated and nonviable macrophages was determined. Then phagocytosis was measured by ingestion of opsonized and unopsonized particles. Finally, microbicidal activity was determined as the ability of the macrophages to kill Listeria monocytogenes directly. Results Demographic and morphometric characteristics of the patients given propofol and isoflurane were similar, as were their levels of pulmonary function and hemodynamic responses. The fraction of alveolar macrophages ingesting opsonized and unopsonized particles, and the number of particles ingested, decreased significantly over time, with the decrease slightly but significantly greater during isoflurane anesthesia. Microbicidal function decreased progressively during anesthesia and surgery, with the decrease almost twice as great during isoflurane compared with propofol anesthesia. The fraction of aggregated macrophages and recovered neutrophils increased over time in the patients given each anesthetic. Conclusions Pulmonary immunologic function changed progressively during anesthesia and surgery. The data from this study suggest that pulmonary defenses are modulated by the type of anesthesia and by the duration of anesthesia and surgery.

scholarly journals Detection of Acetaminophen and Its Glucuronide in Fingerprint by SALDI Mass Spectrometry Using Zeolite and Study of Time-Dependent Changes in Detected Ion Amount

Analytica ◽  
2021 ◽  
Vol 2 (3) ◽  
pp. 66-75
Author(s):  
Toshiki Horikoshi ◽  
Chihiro Kitaoka ◽  
Yosuke Fujii ◽  
Takashi Asano ◽  
Jiawei Xu ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Glucuronic Acid ◽  
Laser Desorption ◽  
The Body ◽  
Time Dependent ◽  
Laser Desorption Ionization ◽  
Fingerprint Analysis ◽  
Desorption Ionization ◽  
Acid Conjugate ◽  
Over Time

The ingredients of an antipyretic (acetaminophen, AAP) and their metabolites excreted into fingerprint were detected by surface-assisted laser desorption ionization (SALDI) mass spectrometry using zeolite. In the fingerprint taken 4 h after AAP ingestion, not only AAP but also the glucuronic acid conjugate of AAP (GAAP), caffeine (Caf), ethenzamide (Eth), salicylamide (Sala; a metabolite of Eth), and urea were detected. Fingerprints were collected over time to determine how the amounts of AAP and its metabolite changed with time, and the time dependence of the peak intensities of protonated AAP and GAAP was measured. It was found that the increase of [GAAP+H]+ peak started later than that of [AAP+H]+ peak, reflecting the metabolism of AAP. Both AAP and GAAP reached maximum concentrations approximately 3 h after ingestion, and were excreted from the body with a half-life of approximately 3.3 h. In addition, fingerprint preservation was confirmed by optical microscopy, and fingerprint shape was retained even after laser irradiation of the fingerprint. Our method may be used in fingerprint analysis.

scholarly journals A novel procedure for the rapid isolation of surfactant protein A with retention of its alveolar-macrophage-stimulating properties

1995 ◽  
Vol 309 (2) ◽  
pp. 551-555 ◽  
Author(s):  
J F van Iwaarden ◽  
F Teding van Berkhout ◽  
J A Whitsett ◽  
R S Oosting ◽  
L M G van Golde
Keyword(s):  
Alveolar Macrophage ◽  
Alveolar Macrophages ◽  
Protein A ◽  
Surfactant Protein ◽  
Surfactant Protein A ◽  
Normal Rat ◽  
Normal Human ◽  
Novel Method ◽  
Alveolar Proteinosis ◽  
Simplex Virus

Previous studies have shown that surfactant protein A (SP-A) derived from alveolar-proteinosis patients activates rat alveolar macrophages. However, it is not known if normal rat, dog and human SP-A can also stimulate alveolar macrophages. As alveolar-proteinosis SP-A has a slightly different structure from ordinary SP-A, it would be possible that the ascribed alveolar-macrophage-stimulating properties of SP-A are restricted to alveolar-proteinosis SP-A. To clarify this issue, we isolated SP-A from normal rat and dog pulmonary surfactants, using the same isolation technique commonly used for the isolation of alveolar-proteinosis SP-A, i.e. by butanol precipitation. In contrast with human alveolar-proteinosis SP-A, rat and dog SP-A obtained thus could not activate rat alveolar macrophages to produce oxygen radicals or enhance the phagocytosis of fluorescein isothiocyanate-labelled herpes simplex virus. However, rat, dog and normal human SP-A isolated by a novel method, involving extraction from pulmonary surfactant by using n-octyl beta-D-glucopyranoside and subsequent purification by cation-exchange chromatography, were able to elicit an oxidative burst in rat as well as normal human alveolar macrophages. In addition, dog and rat SP-A obtained thus stimulated the phagocytosis of herpes simplex virus by rat alveolar macrophages. These findings indicate that normal human, rat and dog SP-A have the same alveolar-macrophage-stimulating properties as human alveolar proteinosis SP-A. Dog and rat SP-A isolated by this novel method had the same Ca(2+)-dependent self-aggregation and lipid-aggregation properties as SP-A isolated by butanol precipitation. The new and milder isolation procedure yielded SP-A of high purity, as judged by SDS/PAGE and ELISA.

scholarly journals Risk Factors for Prostate Cancer Detection After a Negative Biopsy: A Novel Multivariable Longitudinal Approach

2010 ◽  
Vol 28 (10) ◽  
pp. 1714-1720 ◽  
Author(s):  
Peter H. Gann ◽  
Angela Fought ◽  
Ryan Deaton ◽  
William J. Catalona ◽  
Edward Vonesh
Keyword(s):  
Prostate Cancer ◽  
Risk Factors ◽  
Specific Antigen ◽  
Time Dependent ◽  
Negative Biopsy ◽  
Gland Volume ◽  
Piecewise Exponential ◽  
Over Time ◽  
Negative Biopsies

Purpose To introduce a novel approach for the time-dependent quantification of risk factors for prostate cancer (PCa) detection after an initial negative biopsy. Patients and Methods Data for 1,871 men with initial negative biopsies and at least one follow-up biopsy were available. Piecewise exponential regression models were developed to quantify hazard ratios (HRs) and define cumulative incidence curves for PCa detection for subgroups with specific patterns of risk factors over time. Factors evaluated included age, race, serum prostate-specific antigen (PSA) concentration, PSA slope, digital rectal examination, dysplastic glands or prostatitis on biopsy, ultrasound gland volume, urinary symptoms, and number of negative biopsies. Results Four hundred sixty-five men had PCa detected, after a mean follow-up time of 2.8 years. All of the factors were independent predictors of PCa detection except for PSA slope, as a result of its correlation with time-dependent PSA level, and race. PSA (HR = 3.90 for > 10 v 2.5 to 3.9 ng/mL), high-grade prostatic intraepithelial neoplasia/atypical glands (HR = 2.97), gland volume (HR = 0.39 for > 50 v < 25 mL), and number of repeat biopsies (HR = 0.36 for two v zero repeat biopsies) were the strongest predictors. Men with high-risk versus low-risk event histories had a 20-fold difference in PCa detection over 5 years. Conclusion Piecewise exponential models provide an approach to longitudinal analysis of PCa risk that allows clinicians to see the interplay of risk factors as they unfold over time for individual patients. With these models, it is possible to identify distinct subpopulations with dramatically different needs for monitoring and repeat biopsy.

scholarly journals A Tutorial on Evaluating the Time-Varying Discrimination Accuracy of Survival Models Used in Dynamic Decision Making

2018 ◽  
Vol 38 (8) ◽  
pp. 904-916 ◽  
Author(s):  
Aasthaa Bansal ◽  
Patrick J. Heagerty
Keyword(s):  
Decision Making ◽  
Statistical Methods ◽  
Sensitivity And Specificity ◽  
Prognostic Model ◽  
Dynamic Decision Making ◽  
Time Dependent ◽  
Survival Models ◽  
Biliary Cirrhosis ◽  
Time Varying ◽  
Over Time

Many medical decisions involve the use of dynamic information collected on individual patients toward predicting likely transitions in their future health status. If accurate predictions are developed, then a prognostic model can identify patients at greatest risk for future adverse events and may be used clinically to define populations appropriate for targeted intervention. In practice, a prognostic model is often used to guide decisions at multiple time points over the course of disease, and classification performance (i.e., sensitivity and specificity) for distinguishing high-risk v. low-risk individuals may vary over time as an individual’s disease status and prognostic information change. In this tutorial, we detail contemporary statistical methods that can characterize the time-varying accuracy of prognostic survival models when used for dynamic decision making. Although statistical methods for evaluating prognostic models with simple binary outcomes are well established, methods appropriate for survival outcomes are less well known and require time-dependent extensions of sensitivity and specificity to fully characterize longitudinal biomarkers or models. The methods we review are particularly important in that they allow for appropriate handling of censored outcomes commonly encountered with event time data. We highlight the importance of determining whether clinical interest is in predicting cumulative (or prevalent) cases over a fixed future time interval v. predicting incident cases over a range of follow-up times and whether patient information is static or updated over time. We discuss implementation of time-dependent receiver operating characteristic approaches using relevant R statistical software packages. The statistical summaries are illustrated using a liver prognostic model to guide transplantation in primary biliary cirrhosis.

TIME-DEPENDENT APOPTOSIS OF ALVEOLAR MACROPHAGES FROM RATS EXPOSED TO BLEOMYCIN: INVOLVEMENT OF TNF RECEPTOR 2

2004 ◽  
Vol 67 (17) ◽  
pp. 1391-1406 ◽  
Author(s):  
H. W. Zhao ◽  
S. Y. Hu ◽  
M. W. Barger ◽  
J. K. H. Ma ◽  
V. Castranova ◽  
...  
Keyword(s):  
Alveolar Macrophages ◽  
Time Dependent ◽  
Tnf Receptor

scholarly journals Passive Immunization of Neonatal Mice against Pneumocystis carinii f. sp. muris Enhances Control of Infection without Stimulating Inflammation

2004 ◽  
Vol 72 (11) ◽  
pp. 6211-6220 ◽  
Author(s):  
Kerry M. Empey ◽  
Melissa Hollifield ◽  
Kevin Schuer ◽  
Francis Gigliotti ◽  
Beth A. Garvy
Keyword(s):  
Alveolar Macrophage ◽  
Specific Antibody ◽  
Alveolar Macrophages ◽  
Macrophage Activation ◽  
Pneumocystis Carinii ◽  
Passive Immunization ◽  
Activation Markers ◽  
Effector Cells ◽  
Macrophage Activity ◽  
Neonatal Mice

ABSTRACT Pneumocystis carinii is an opportunistic fungal pathogen that causes life-threatening pneumonia in immunocompromised individuals. Infants appear to be particularly susceptible to infection with Pneumocystis. We have previously shown that there is a significant delay in clearance of the organisms from the lungs of neonatal mice compared to adults. Since alveolar macrophages are the effector cells responsible for killing and clearance of Pneumocystis, we have examined alveolar macrophage activity in neonatal mice. We found that alveolar macrophage activation is delayed about 1 week in Pneumocystis-infected neonates compared to adults. Opsonization of the organism by Pneumocystis-specific antibody resulted in increased clearance of the organism in neonatal mice; however, there was decreased expression of activation markers on neonatal alveolar macrophages and reduced levels of cytokines associated with macrophage activation. Mice born to immunized dams had significant amounts of Pneumocystis-specific immunoglobulin G in their lungs and serum at day 7 postinfection, whereas mice born to naïve dams had merely detectable levels. This difference correlated with enhanced Pneumocystis clearance in mice born to immunized dams. The increase in specific antibody, however, did not result in significant inflammation in the lungs, as no differences in numbers of activated CD4+ cells were observed. Furthermore, there was no difference in cytokine or chemokine concentrations in the lungs of pups born to immune compared to naïve dams. These findings indicate that specific antibody plays an important role in Pneumocystis clearance from lungs of infected neonates; moreover, this process occurs without inducing inflammation in the lungs.

scholarly journals A joint modeling approach for longitudinal microbiome data improves ability to detect microbiome associations with disease

2020 ◽  
Vol 16 (12) ◽  
pp. e1008473
Author(s):  
Pamela N. Luna ◽  
Jonathan M. Mansbach ◽  
Chad A. Shaw
Keyword(s):  
Joint Modeling ◽  
Mixed Effects ◽  
Mixed Effects Model ◽  
Time Dependent ◽  
Time To Event ◽  
Modeling Framework ◽  
Microbial Composition ◽  
Disease Outcomes ◽  
Microbiome Data ◽  
Over Time

Changes in the composition of the microbiome over time are associated with myriad human illnesses. Unfortunately, the lack of analytic techniques has hindered researchers’ ability to quantify the association between longitudinal microbial composition and time-to-event outcomes. Prior methodological work developed the joint model for longitudinal and time-to-event data to incorporate time-dependent biomarker covariates into the hazard regression approach to disease outcomes. The original implementation of this joint modeling approach employed a linear mixed effects model to represent the time-dependent covariates. However, when the distribution of the time-dependent covariate is non-Gaussian, as is the case with microbial abundances, researchers require different statistical methodology. We present a joint modeling framework that uses a negative binomial mixed effects model to determine longitudinal taxon abundances. We incorporate these modeled microbial abundances into a hazard function with a parameterization that not only accounts for the proportional nature of microbiome data, but also generates biologically interpretable results. Herein we demonstrate the performance improvements of our approach over existing alternatives via simulation as well as a previously published longitudinal dataset studying the microbiome during pregnancy. The results demonstrate that our joint modeling framework for longitudinal microbiome count data provides a powerful methodology to uncover associations between changes in microbial abundances over time and the onset of disease. This method offers the potential to equip researchers with a deeper understanding of the associations between longitudinal microbial composition changes and disease outcomes. This new approach could potentially lead to new diagnostic biomarkers or inform clinical interventions to help prevent or treat disease.

scholarly journals Mortality Risk and The Progression of The Electronic Frailty Index and Hospital Frailty Risk Score Over Time

2020 ◽  
Vol 5 (5) ◽  
Author(s):  
Joe Hollinghurst ◽  
Alan Watkins
Keyword(s):  
Risk Score ◽  
Frailty Index ◽  
Time Frame ◽  
Time Dependent ◽  
Cox Models ◽  
Hazard Ratios ◽  
Increased Risk ◽  
The Matrix ◽  
Time Dependent Covariates ◽  
Over Time

IntroductionThe electronic Frailty Index (eFI) and the Hospital Frailty Risk Score (HFRS) have been developed in primary and secondary care respectively. Objectives and ApproachOur objective was to investigate how frailty progresses over time, and to include the progression of frailty in a survival analysis.To do this, we performed a retrospective cohort study using linked data from the Secure Anonymised Information Linkage Databank, comprising 445,771 people aged 65-95 living in Wales (United Kingdom) on 1st January 2010. We calculated frailty, using both the eFI and HFRS, for individuals at quarterly intervals for 8 years with a total of 11,702,242 observations. ResultsWe created a transition matrix for frailty states determined by the eFI (states: fit, mild, moderate, severe) and HFRS (states: no score, low, intermediate, high), with death as an absorbing state. The matrix revealed that frailty progressed over time, but that on a quarterly basis it was most likely that an individual remained in the same state. We calculated Hazard Ratios (HRs) using time dependent Cox models for mortality, with adjustments for age, gender and deprivation. Independent eFI and HFRS models showed increased risk of mortality as frailty severity increased. A combined eFI and HFRS revealed the highest risk was primarily determined by the HFRS and revealed further subgroups of individuals at increased risk of an adverse outcome. For example, the HRs (95% Confidence Interval) for individuals with an eFI as fit, mild, moderate and severe with a high HFRS were 18.11 [17.25,19.02], 20.58 [19.93,21.24], 21.45 [20.85,22.07] and 23.04 [22.34,23.76] respectively with eFI fit and no HFRS score as the reference category. ConclusionFrailty was found to vary over time, with progression likely in the 8-year time-frame analysed. We refined HR estimates of the eFI and HFRS for mortality by including time dependent covariates.

scholarly journals Solvable Model of a Generic Driven Mixture of Trapped Bose–Einstein Condensates and Properties of a Many-Boson Floquet State at the Limit of an Infinite Number of Particles

Entropy ◽  
2020 ◽  
Vol 22 (12) ◽  
pp. 1342
Author(s):  
Ofir E. Alon
Keyword(s):  
Angular Momentum ◽  
Infinite Number ◽  
Mean Field ◽  
Solvable Model ◽  
Time Dependent ◽  
Angular Momentum Operator ◽  
Many Body ◽  
The Many ◽  
Bose Einstein ◽  
Number Of Particles

A solvable model of a periodically driven trapped mixture of Bose–Einstein condensates, consisting of N1 interacting bosons of mass m1 driven by a force of amplitude fL,1 and N2 interacting bosons of mass m2 driven by a force of amplitude fL,2, is presented. The model generalizes the harmonic-interaction model for mixtures to the time-dependent domain. The resulting many-particle ground Floquet wavefunction and quasienergy, as well as the time-dependent densities and reduced density matrices, are prescribed explicitly and analyzed at the many-body and mean-field levels of theory for finite systems and at the limit of an infinite number of particles. We prove that the time-dependent densities per particle are given at the limit of an infinite number of particles by their respective mean-field quantities, and that the time-dependent reduced one-particle and two-particle density matrices per particle of the driven mixture are 100% condensed. Interestingly, the quasienergy per particle does not coincide with the mean-field value at this limit, unless the relative center-of-mass coordinate of the two Bose–Einstein condensates is not activated by the driving forces fL,1 and fL,2. As an application, we investigate the imprinting of angular momentum and its fluctuations when steering a Bose–Einstein condensate by an interacting bosonic impurity and the resulting modes of rotations. Whereas the expectation values per particle of the angular-momentum operator for the many-body and mean-field solutions coincide at the limit of an infinite number of particles, the respective fluctuations can differ substantially. The results are analyzed in terms of the transformation properties of the angular-momentum operator under translations and boosts, and as a function of the interactions between the particles. Implications are briefly discussed.

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