scholarly journals Treatable metabolic and inflammatory abnormalities in Post COVID Syndrome (PCS) define the transcriptomic basis for persistent symptoms: Lessons from CIRS

2021 ◽  
Vol 9 (7) ◽  
Author(s):  
Ryan Shoemaker ◽  
S. McMahon ◽  
A. Heyman ◽  
D. Lark ◽  
M. Westhuizen ◽  
...  

Within three months of the onset of acute SARS-CoV-2 (COVID-19) infections, new and persistent symptoms were noted in survivors. While the world’s medical and research communities focus on saving lives following COVID-19 infection, a relentless march of new cases of Post-COVID Syndrome (PCS) continues to spread around the globe as a second COVID-related pandemic. Efforts to define the physiology of PCS, a multisystem, multi-symptom illness, continue without success, in part due to the markedly different case presentations. Using a transcriptomic assessment of persistently ill cases of PCS, we show the presence of (i) molecular hypometabolism (MHM) and proliferative physiology; (ii) elevated levels of ribosomal stress responses and a concomitant increase in gene activation of TGFBR; and (iii) common co-expression of CD14 and Toll Receptor 4, correlated to exposure of amplified microbial growth in a water-damaged environment, specifically Actinobacteria and endotoxin, respectively, compared to recovered PCS cases. Total symptom scores and visual contrast sensitivity (VCS) results showed statistically significant differences. The data reported here supports the concept that PCS occurs in patients with additional environmental exposures and enhanced TGF signaling. In a strikingly similar condition called Chronic Inflammatory Response Syndrome (CIRS), named in 2010, the transcriptomic abnormalities were identified to respond to treatment with FDA-cleared medications, with salutary benefits for affected cases. Though sparsely reported, PCS cases share proteomic findings with CIRS. While additional studies are indicated, a new approach to the treatment of PCS is suggested.

2016 ◽  
Vol 57 (13) ◽  
pp. 5696 ◽  
Author(s):  
Wendy Ming ◽  
Dimitrios J. Palidis ◽  
Miriam Spering ◽  
Martin J. McKeown

2004 ◽  
Vol 126 (1) ◽  
pp. 15-21 ◽  
Author(s):  
Zoltán Szabó ◽  
Andrea Antal ◽  
Zsolt Tokaji ◽  
János Kálmán ◽  
Szabolcs Kéri ◽  
...  

Author(s):  
Michael A. Nelson ◽  
Ronald L. Halberg

Threshold contrasts for red, green, and achromatic sinusoidal gratings were measured. Spatial frequencies ranged from 0.25 to 15 cycles/deg. No significant differences in contrast thresholds were found among the three grating types. From this finding it was concluded that, under conditions of normal viewing, no significant differences should be expected in the acquisition of spatial information from monochromatic or achromatic displays of equal resolution.


Author(s):  
Muhammad Adeel ◽  
Yinglei Song

Background: In many applications of image processing, the enhancement of images is often a step necessary for their preprocessing. In general, for an enhanced image, the visual contrast as a whole and its refined local details are both crucial for achieving accurate results for subsequent classification or analysis. Objective: This paper proposes a new approach for image enhancement such that the global and local visual effects of an enhanced image can both be significantly improved. Methods: The approach utilizes the normalized incomplete Beta transform to map pixel intensities from an original image to its enhanced one. An objective function that consists of two parts is optimized to determine the parameters in the transform. One part of the objective function reflects the global visual effects in the enhanced image and the other one evaluates the enhanced visual effects on the most important local details in the original image. The optimization of the objective function is performed with an optimization technique based on the particle swarm optimization method. Results: Experimental results show that the approach is suitable for the automatic enhancement of images. Conclusion: The proposed approach can significantly improve both the global and visual contrasts of the image.


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