The cystic fibrosis transmembrane conductance regulator (CFTR) attenuates sphingosine-1-phosphate (S1P) signaling in resistance arteries and has emerged as a prominent regulator of myogenic vasoconstriction. This investigation demonstrates that S1P inhibits CFTR activity via adenosine monophosphate-activated kinase (AMPK), establishing a potential feedback link. In Baby Hamster Kidney (BHK) cells expressing wild-type human CFTR, S1P (1μmol/L) attenuates forskolin-stimulated, CFTR-dependent iodide efflux. S1P’s inhibitory effect is rapid (within 30 seconds), transient and correlates with CFTR serine residue 737 (S737) phosphorylation. Both S1P receptor antagonism (4μmol/L VPC 23019) and AMPK inhibition (80μmol/L Compound C or AMPK siRNA) attenuate S1P-stimluated (i) AMPK phosphorylation, (ii) CFTR S737 phosphorylation and (iii) CFTR activity inhibition. In BHK cells expressing the ΔF508 CFTR mutant (CFTRΔF508), the most common mutation causing cystic fibrosis, both S1P receptor antagonism and AMPK inhibition enhance CFTR activity, without instigating discernable correction. In summary, we demonstrate that S1P/AMPK signaling transiently attenuates CFTR activity. Since our previous work positions CFTR as a negative S1P signaling regulator, this signaling link may positively reinforce S1P signals. This discovery has clinical ramifications for the treatment of disease states associated with enhanced S1P signaling and/or deficient CFTR activity (e.g. cystic fibrosis, heart failure). S1P receptor/AMPK inhibition could synergistically enhance the efficacy of therapeutic strategies aiming to correct aberrant CFTR trafficking.

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This paper reviews the NTIRE 2022 challenge on night photography rendering. The challenge solicited solutions that processed RAW camera images captured in night scenes to produce a photo-finished output image encoded in the standard RGB (sRGB) space. Given the subjective nature of this task, the proposed solutions were evaluated based on the mean opinions of viewers asked to judge the visual appearance of the results. Michael Freeman, a world-renowned photographer, further ranked the solutions with the highest mean opinion scores. A total of 13 teams competed in the final phase of the challenge. The proposed methods provided by the participating teams represent state-of-the-art performance in nighttime photography. Results from the various teams can be found here: https://nightimaging.org/

Illumination estimation is the essential step of computational color constancy, one of the core parts of various image processing pipelines of modern digital cameras. Having an accurate and reliable illumination estimation is important for reducing the illumination influence on the image colors. To motivate the generation of new ideas and the development of new algorithms in this field, two challenges on illumination estimation were conducted. The main advantage of testing a method on a challenge over testing it on some of the known datasets is the fact that the ground‐truth illuminations for the challenge test images are unknown up until the results have been submitted, which prevents any potential hyperparameter tuning that may be biased. The First illumination estimation challenge (IEC#1) had only a single task, global illumination estimation. The second illumination estimation challenge (IEC#2) was enriched with two additional tracks that encompassed indoor and two‐illuminant illumination estimation. Other main features of it are a new large dataset of images (about 5000) taken with the same camera sensor model, a manual markup accompanying each image, diverse content with scenes taken in numerous countries under a huge variety of illuminations extracted by using the SpyderCube calibration object, and a contest‐like markup for the images from the Cube++ dataset. This article focuses on the description of the past two challenges, algorithms which won in each track, and the conclusions that were drawn based on the results obtained during the first and second challenge that can be useful for similar future developments.