Methodologies based on (15)N enrichment (E) and (15)N natural abundance (NA) have been used to obtain quantitative estimates of the response of biological N2 fixation (BNF) of legumes (woody, grain and forage) and actinorhizal plants grown in artificial media or in soil exposed to elevated atmospheric concentrations of carbon dioxide e[CO2] for extended periods of time, in growth rooms, greenhouses, open top chambers or free-air CO2 enrichment (FACE) facilities. (15)N2 has also been used to quantify the response of endophytic and free-living diazotrophs to e[CO2]. The primary criterion of response was the proportional dependence of the N2-fixing system on the atmosphere as a source of N. i.e. the symbiotic dependence (Patm). The unique feature of (15)N-based methods is their ability to provide time-integrated and yield-independent estimates of Patm. In studies conducted in artificial media or in soil using the E methodology there was either no response or a positive response of Patm to e[CO2]. The interpretation of results obtained in artificial media or with (15)N2 is straight forward, not being subject to the assumptions on which the E and NA soil-cultured methods are based. A variety of methods have been used to estimate isotopic fractionation attendant on the NA technique, the so-called 'B value', which attaches a degree of uncertainty to the results obtained. Using the NA technique, a suite of responses of Patm to e[CO2] has been published, from positive to neutral to sometimes negative effects. Several factors which interact with the response of N2-fixing species to e[CO2] were identified.
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http://dx.doi.org/10.1016/j.scitotenv.2016.07.030 | DOI Listing |
BMC Med Educ
January 2025
Faculty of Medicine, King Abdulaziz University, Jeddah, Saudi Arabia.
Background: Although artificial intelligence (AI) has gained increasing attention for its potential future impact on clinical practice, medical education has struggled to stay ahead of the developing technology. The question of whether medical education is fully preparing trainees to adapt to potential changes from AI technology in clinical practice remains unanswered, and the influence of AI on medical students' career preferences remains unclear. Understanding the gap between students' interest in and knowledge of AI may help inform the medical curriculum structure.
View Article and Find Full Text PDFAm J Vet Res
January 2025
Center for Animal Health and Food Safety, Department of Veterinary Population Medicine, College of Veterinary Medicine, University of Minnesota, Saint Paul, MN.
Objective: Antimicrobial resistance (AMR), a global threat driven by factors such as improper antimicrobial use in humans and animals, is projected to cause 10 million annual deaths by 2050. For behavior change, public health messages must be tailored for diverse audiences. Generative AI may have the potential to create culturally and linguistically suited AMR awareness messages.
View Article and Find Full Text PDFElectromagn Biol Med
January 2025
Department of Mathematics, University of Gour Banga, Malda, India.
In cardiovascular research, electromagnetic fields generated by Riga plates are utilized to study or manipulate blood flow dynamics, which is particularly crucial in developing treatments for conditions such as arterial plaque deposition and understanding blood behavior under varied flow conditions. This research predicts the flow patterns of blood enhanced with gold and maghemite nanoparticles (gold-maghemite/blood) in an electromagnetic microchannel influenced by Riga plates with a temperature gradient that decays exponentially, under sudden changes in pressure gradient. The flow modeling includes key physical influences like radiation heat emission and Darcy drag forces in porous media, with the flow mathematically represented through unsteady partial differential equations solved using the Laplace transform (LT) method.
View Article and Find Full Text PDFJ Mater Chem B
January 2025
Ningbo Key Laboratory of Biomedical Imaging Probe Materials and Technology, Laboratory of Advanced Theranostic Materials and Technology, Chinese Academy of Sciences (CAS) Key Laboratory of Magnetic Materials and Devices, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo 315201, China.
The critical need for rapid cancer diagnosis and related illnesses is growing alongside the current healthcare challenges, unfavorable prognosis, and constraints in diagnostic timing. As a result, emphasis on surface-enhanced Raman spectroscopy (SERS) diagnostic methods, including both label-free and labelled approaches, holds significant promise in fields such as analytical chemistry, biomedical science, and physics, due to the user-friendly nature of SERS. Over time, the SERS detection sensitivity and specificity with nanostructured materials for SERS applications (NMs-SERS) in different media have been remarkable.
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