Faculty Opinions recommendation of Characterization of the haematological profile of 21 days of tedizolid in healthy subjects.

Author(s):  
Stan Deresinski
2016 ◽  
Vol 71 (9) ◽  
pp. 2553-2558 ◽  
Author(s):  
Thomas P. Lodise ◽  
Monique R. Bidell ◽  
Shawn D. Flanagan ◽  
Evan J. Zasowski ◽  
Sonia L. Minassian ◽  
...  

Author(s):  
Piero Sciavilla ◽  
Francesco Strati ◽  
Monica Di Paola ◽  
Monica Modesto ◽  
Francesco Vitali ◽  
...  

Abstract Studies so far conducted on irritable bowel syndrome (IBS) have been focused mainly on the role of gut bacterial dysbiosis in modulating the intestinal permeability, inflammation, and motility, with consequences on the quality of life. Limited evidences showed a potential involvement of gut fungal communities. Here, the gut bacterial and fungal microbiota of a cohort of IBS patients have been characterized and compared with that of healthy subjects (HS). The IBS microbial community structure differed significantly compared to HS. In particular, we observed an enrichment of bacterial taxa involved in gut inflammation, such as Enterobacteriaceae, Streptococcus, Fusobacteria, Gemella, and Rothia, as well as depletion of health-promoting bacterial genera, such as Roseburia and Faecalibacterium. Gut microbial profiles in IBS patients differed also in accordance with constipation. Sequence analysis of the gut mycobiota showed enrichment of Saccharomycetes in IBS. Culturomics analysis of fungal isolates from feces showed enrichment of Candida spp. displaying from IBS a clonal expansion and a distinct genotypic profiles and different phenotypical features when compared to HS of Candida albicans isolates. Alongside the well-characterized gut bacterial dysbiosis in IBS, this study shed light on a yet poorly explored fungal component of the intestinal ecosystem, the gut mycobiota. Our results showed a differential fungal community in IBS compared to HS, suggesting potential for new insights on the involvement of the gut mycobiota in IBS. Key points • Comparison of gut microbiota and mycobiota between IBS and healthy subjects • Investigation of cultivable fungi in IBS and healthy subjects • Candida albicans isolates result more virulent in IBS subjects compared to healthy subjects


2017 ◽  
Vol 128 (6) ◽  
pp. 1328-1334 ◽  
Author(s):  
Lara Ferris ◽  
Mistyka Schar ◽  
Lisa McCall ◽  
Sebastian Doeltgen ◽  
Ingrid Scholten ◽  
...  

2019 ◽  
Vol 10 ◽  
Author(s):  
Johann Guillemot ◽  
Marlène Guérin ◽  
Anne-Françoise Cailleux ◽  
Antoine-Guy Lopez ◽  
Jean-Marc Kuhn ◽  
...  
Keyword(s):  

1981 ◽  
Vol 27 (10) ◽  
pp. 1690-1697 ◽  
Author(s):  
T Nishino ◽  
T Kodaira ◽  
S Shin ◽  
K Imagawa ◽  
K Shima ◽  
...  

Abstract In this pancreatic-glucagon-specific radioimmunoassay we used C-terminal-region-specific antiserum. OAL-123, produced against a 19-29 C-terminal fragment of porcine glucagon. On measurement of pooled plasma the ranges for intra- and inter-assay coefficients of variation were 4.8-8.1% and 7.5-10.7%, respectively. The concentration of immunoreactive glucagon in plasma of healthy subjects, as measured with the OAL-123 assay system, was 87.9 (SD 23.8) ng/L. Measurement of the same plasma samples with the 30K assay system (30K being an antiserum highly specific for pancreatic glucagon) showed a comparable value, 86.2 (SD 26.3) ng/L. We followed changes in human and dog plasma immunoreactive glucagon concentrations on arginine infusion and after glucose load, using the OAL-123 and the 30K assay systems, with identical results. Combining other results of comparative immunochemical characterization of the OAL-123 and 30K assay systems, we confirmed that the antisera raised against the C-terminal fragment of glucagon can be used in radioimmunoassay of pancreatic glucagon.


2011 ◽  
Vol 89 (s248) ◽  
pp. 0-0 ◽  
Author(s):  
G FUCHSJAGER‐MAYRL ◽  
L SCHMETTERER

2009 ◽  
Vol 25 (4) ◽  
pp. 369-376 ◽  
Author(s):  
Peter Wolf ◽  
Renate List ◽  
Thomas Ukelo ◽  
Christian Maiwald ◽  
Alex Stacoff

Before conclusions can be drawn with respect to the quality of adaptations in human gait, the day-to-day consistency of the variables of interest must be known. The present study estimated the day-to-day consistency of kinematic variables collected during barefoot walking and running. Sixteen healthy subjects performed two gait analysis sessions based on skin markers. Test sessions were at least 1 week apart. In total, 48 ranges of motion were monitored for the hip, knee, ankle, and midfoot joint. Based on differences between the repeated gait analysis sessions, the day-to-day consistency was estimated. It was found that the day-to-day consistency was of the magnitude of 3 to 4 degrees for almost all ranges of motion independently of the test condition, the investigated joints, or the cardinal body plane. It was concluded that future studies on effects of interventions or on the characterization of pathological versus normative gait should consider the provided values of day-to-day consistency to improve their interpretation and conclusions.


2014 ◽  
Vol 19 (3) ◽  
pp. 037003 ◽  
Author(s):  
Ramu Rajasekaran ◽  
Prakasa Rao Aruna ◽  
Dornadula Koteeswaran ◽  
Ganesan Bharanidharan ◽  
Munusamy Baludavid ◽  
...  

2014 ◽  
Vol 2014 ◽  
pp. 1-14 ◽  
Author(s):  
Yogendra Narain Singh

This paper presents a novel method to use the electrocardiogram (ECG) signal as biometrics for individual identification. The ECG characterization is performed using an automated approach consisting of analytical and appearance methods. The analytical method extracts the fiducial features from heartbeats while the appearance method extracts the morphological features from the ECG trace. We linearly project the extracted features into a subspace of lower dimension using an orthogonal basis that represent the most significant features for distinguishing heartbeats among the subjects. Result demonstrates that the proposed characterization of the ECG signal and subsequently derived eigenbeat features are insensitive to signal variations and nonsignal artifacts. The proposed system utilizing ECG biometric method achieves the best identification rates of 85.7% for the subjects of MIT-BIH arrhythmia database and 92.49% for the healthy subjects of our IIT (BHU) database. These results are significantly better than the classification accuracies of 79.55% and 84.9%, reported using support vector machine on the tested subjects of MIT-BIH arrhythmia database and our IIT (BHU) database, respectively.


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