Light is an important environmental signal for all organisms on earth because it is essential for physiological signalling and the regulation of most biological systems. Halophiles found in salt-saturated ponds encode various archaeal rhodopsins and thereby harvest various wavelengths of light either for ion transportation or as sensory mediators. HR (halorhodopsin), one of the microbial rhodopsins, senses yellow light and transports chloride or other halides into the cytoplasm to maintain the osmotic balance during cell growth, and it exists almost ubiquitously in all known halobacteria. To date, only two HRs, isolated from HsHR (Halobacterium salinarum HR) and NpHR (Natronomonas pharaonis HR), have been characterized. In the present study, two new HRs, HmHR (Haloarcula marismortui HR) and HwHR (Haloquadratum walsbyi HR), were functionally overexpressed in Escherichia coli, and the maximum absorbance (λmax) of the purified proteins, the light-driven chloride uptake and the chloride-binding affinity were measured. The results showed them to have similar properties to two HRs reported previously. However, the λmax of HwHR is extremely consistent in a wide range of salt/chloride concentrations, which had not been observed previously. A structural-based sequence alignment identified a single serine residue at 262 in HwHR, which is typically a conserved alanine in all other known HRs. A Ser262 to alanine replacement in HwHR eliminated the chloride-independent colour tuning, whereas an Ala246 to serine mutagenesis in HsHR transformed it to have chloride-independent colour tuning similar to that of HwHR. Thus Ser262 is a key residue for the mechanism of chloride-dependent colour tuning in HwHR.
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http://dx.doi.org/10.1042/BSR20120054 | DOI Listing |
Taiwan J Ophthalmol
November 2024
Sirindhorn International Institute of Technology, Thammasat University, Bangkok, Thailand.
Recent advances of artificial intelligence (AI) in retinal imaging found its application in two major categories: discriminative and generative AI. For discriminative tasks, conventional convolutional neural networks (CNNs) are still major AI techniques. Vision transformers (ViT), inspired by the transformer architecture in natural language processing, has emerged as useful techniques for discriminating retinal images.
View Article and Find Full Text PDF[This retracts the article DOI: 10.1039/D0RA03793A.].
View Article and Find Full Text PDFOphthalmol Sci
November 2024
Liverpool Ocular Oncology Research Group, Department of Eye and Vision Science, Institute of Life Course and Medical Sciences (ILCaMS), University of Liverpool, Liverpool, United Kingdom.
Purpose: Testing the validity of a self-supervised deep learning (DL) model, RETFound, for use on posterior uveal (choroidal) melanoma (UM) and nevus differentiation.
Design: Case-control study.
Subjects: Ultrawidefield fundoscopy images, both color and autofluorescence, were used for this study, obtained from 4255 patients seen at the Liverpool Ocular Oncology Center between 1995 and 2020.
Sensors (Basel)
December 2024
Department of Electrical Engineering, Lunghwa University of Science and Technology, Taoyuan 333326, Taiwan.
The proliferation of sophisticated counterfeiting poses critical challenges to global security and commerce, with annual losses exceeding $2.2 trillion. This paper presents a novel physics-constrained deep learning framework for high-precision security ink colorimetry, integrating three key innovations: a physics-informed neural architecture achieving unprecedented color prediction accuracy (CIEDE2000 (ΔE00): 0.
View Article and Find Full Text PDFJ Org Chem
January 2025
Department of Chemistry, IIT Dharwad, Dharwad, Karnataka 580007, India.
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