Alterations in microbial community composition, biomass, and function in the Florida Everglades impacted by cultural eutrophication reflect a new physicochemical environment associated with monotypic stands of Typha domingensis. Phospholipid fatty acid (PLFA) biomarkers were used to quantify microbial responses in detritus and surface soils in an active management experiment in the eutrophic Everglades. Creation of open plots through removal of Typha altered the physical and chemical characteristics of the region. Mass of PLFA biomarkers increased in open plots, but magnitude of changes differed among microbial groups. Biomarkers indicative of Gram-negative bacteria and fungi were significantly greater in open plots, reflective of the improved oxic environment. Reduction in the proportion of cyclopropyl lipids and the ratio of Gram-positive to Gram-negative bacteria in open plots further suggested an altered oxygen environment and conditions for the rapid growth of Gram-negative bacteria. Changes in the PLFA composition were greater in floc relative to soils, reflective of rapid inputs of new organic matter and direct interaction with the new physicochemical environment. Created open plot microbial mass and composition were significantly different from the oligotrophic Everglades due to differences in phosphorus availability, plant community structure, and a shift to organic peat from marl-peat soils. PLFA analysis also captured the dynamic inter-annual hydrologic variability, notably in PLFA concentrations, but to a lesser degree content. Recently, use of concentration has been advocated over content in studies of soil biogeochemistry, and our results highlight the differential response of these two quantitative measures to similar pressures.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1007/s00248-012-0090-2 | DOI Listing |
Toxicology
January 2025
Deparment of clinical pharmacy, Jieyang People's Hospital, 522000, China. Electronic address:
Drug-induced autoimmunity (DIA) is a non-IgE immune-related adverse drug reaction that poses substantial challenges in predictive toxicology due to its idiosyncratic nature, complex pathogenesis, and diverse clinical manifestations. To address these challenges, we developed InterDIA, an interpretable machine learning framework for predicting DIA toxicity based on molecular physicochemical properties. Multi-strategy feature selection and advanced ensemble resampling approaches were integrated to enhance prediction accuracy and overcome data imbalance.
View Article and Find Full Text PDFPhys Eng Sci Med
January 2025
Amrita School of Artificial Intelligence, Amrita Vishwa Vidyapeetham, Bangalore, India.
Parkinson Disease (PD) is a complex neurological disorder attributed by loss of neurons generating dopamine in the SN per compacta. Electroencephalogram (EEG) plays an important role in diagnosing PD as it offers a non-invasive continuous assessment of the disease progression and reflects these complex patterns. This study focuses on the non-linear analysis of resting state EEG signals in PD, with a gender-specific, brain region-specific, and EEG band-specific approach, utilizing recurrence plots (RPs) and machine learning (ML) algorithms for classification.
View Article and Find Full Text PDFBJPsych Open
January 2025
Physical Performance and Sports Research Centre, Universidad Pablo de Olavide, Seville, Spain.
Background: In individuals with severe mental illness (SMI), low muscle strength heightens the risk of mortality and chronic disease development. Routine muscle strength assessments could identify vulnerabilities, thereby reducing the growing burden associated with SMI. However, integration into clinical settings faces obstacles because of limited resources and inadequate healthcare staff training.
View Article and Find Full Text PDFR Soc Open Sci
January 2025
Sustainable Soils and Crops, Rothamsted Research, Harpenden AL5 2JQ, UK.
Seed germination is a crucial stage in plant development, intricately regulated by various environmental stimuli. Understanding these interactions is essential for optimizing planting and seedling management but remains challenging due to the trade-off effects of environmental factors on the germination process. We proposed a new conceptual model by viewing seed germination as a dynamic process in a physiological dimension, with the influence of environmental factors and seed heterogeneity characterized by a germination speed and a dispersion coefficient.
View Article and Find Full Text PDFBehav Res Methods
January 2025
School of Psychology, University of New South Wales, Sydney, Australia.
With recent technical advances, many cognitive and sensory tasks have been adapted for smartphone testing. This study aimed to assess the criterion validity of a subset of self-administered, open-source app-based cognitive and sensory tasks by comparing test performance to lab-based alternatives. An in-person baseline was completed by 43 participants (aged 21 to 82) from the larger Labs without Walls project (Brady et al.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!