We previously reported that CP12 formed a complex with GAPDH and PRK and regulated the activities of these enzymes and the Calvin-Benson cycle under dark conditions as the principal regulatory system in cyanobacteria. More interestingly, we found that the cyanobacterial CP12 gene-disrupted strain was more sensitive to photo-oxidative stresses such as under high light conditions and paraquat treatment. When a mutant strain that grew normally under low light was subjected to high light conditions, decreases in chlorophyll and photosynthetic activity were observed. Furthermore, a large amount of ROS was accumulated in the cells of the CP12 gene-disrupted strain. These data suggest that CP12 also functions under light conditions and may be involved in protection against oxidative stress by controlling the flow of electrons from Photosystem I to NADPH.
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http://dx.doi.org/10.3390/plants10071275 | DOI Listing |
BMC Genom Data
January 2025
School of Epidemiology and Public Health, University of Ottawa, 600 Peter Morand Crescent, Office 101E, Ottawa, Ontario, K1G 5Z3, Canada.
High intraocular pressure (IOP) is an important risk factor for glaucoma, which is influenced by genetic and environmental factors. However, the etiology of high IOP remains uncertain. Metabolites are compounds involved in metabolism which provide a link between the internal (genetic) and external environments.
View Article and Find Full Text PDFBMC Public Health
January 2025
Centre for Healthcare Management, Administrative Staff College of India (ASCI), Hyderabad, India.
Background: Substantial out-of-pocket (OOP) expenditures push a large portion of the population below the poverty line, especially those residing in rural areas having low incomes. Individuals from economically disadvantaged states in India incur higher healthcare costs for hospitalization in public health centers than do those from more developed states. Economically poorer households in states such as Bihar and Odisha face significantly higher OOP expenditures for hospitalization in public health centers than do those in economically developed states such as Tamil Nadu.
View Article and Find Full Text PDFBMC Public Health
January 2025
Sefako Makgatho University, Ground Floor, Clin Path Building, Room No. 37. Garankuwa, Pretoria, South Africa.
Background: Femicides, defined as the gender-based killing of women, are a pressing public health issue worldwide, with South Africa experiencing some of the highest rates globally. This study focuses on the North-west region of Tshwane, particularly the Garankuwa area, aiming to address gaps in understanding the epidemiology, demographics, circumstances, and pathology associated with femicides. The Garankuwa mortuary serves as the primary site for this investigation, providing a detailed analysis over a ten-year period, shedding light on contributing risk factors in the context of systemic gender inequality.
View Article and Find Full Text PDFJ Clin Monit Comput
January 2025
Department of Electrical Engineering, Eindhoven University of Technology, Groene Loper 3, 5612 AZ, Eindhoven, the Netherlands.
Unobtrusive pulse rate monitoring by continuous video recording, based on remote photoplethysmography (rPPG), might enable early detection of perioperative arrhythmias in general ward patients. However, the accuracy of an rPPG-based machine learning model to monitor the pulse rate during sinus rhythm and arrhythmias is unknown. We conducted a prospective, observational diagnostic study in a cohort with a high prevalence of arrhythmias (patients undergoing elective electrical cardioversion).
View Article and Find Full Text PDFSci Rep
January 2025
Department of Computer Science, American International University-Bangladesh (AIUB), Dhaka, 1229, Bangladesh.
The transportation industry contributes significantly to climate change through carbon dioxide ( ) emissions, intensifying global warming and leading to more frequent and severe weather phenomena such as flooding, drought, heat waves, glacier melting, and rising sea levels. This study proposes a comprehensive approach for predicting emissions from vehicles using deep learning techniques enhanced by eXplainable Artificial Intelligence (XAI) methods. Utilizing a dataset from the Canadian government's official open data portal, we explored the impact of various vehicle attributes on emissions.
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