Premise: Increasing aridity in the Mediterranean region affects ecosystems and plant life. Various anatomical changes in plants help them cope with dry conditions. This study focused on anatomical differences in leaves and xylem of five co-occurring Mediterranean plant species namely Quercus calliprinos, Pistacia palaestina, Pistacia lentiscus, Rhamnus lycioides, and Phillyrea latifolia in wet and dry sites.
Methods: Stomatal density, stomatal length, leaf mass area, lamina composition, percentage of intercellular air spaces, and mesophyll cell area in leaves of plants in wet and dry sites were analyzed. Xylem anatomy was assessed through vessel length and area in branches.
Results: In the dry site, three species had increased stomatal density and decreased stomatal length. Four species had increased palisade mesophyll and reduced air space volume. In contrast, phenotypic changes in the xylem were less pronounced; vessel length was unaffected by site conditions, but vessel diameter decreased in two species. Intercellular air spaces proved to be the most dynamic anatomical feature. Quercus calliprinos had the most extensive anatomical changes; Rhamnus lycioides had only minor changes. All these changes were observed in comparison to the species in the wet site.
Conclusions: This study elucidated variations in anatomical responses in leaves among co-occurring Mediterranean plant species and identified the most dynamic traits. Understanding these adaptations provides valuable insights into the ability of plants to thrive under changing climate conditions.
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http://dx.doi.org/10.1002/ajb2.16407 | DOI Listing |
Neuroinformatics
January 2025
Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, USA.
This paper introduces the Automated Lesion and Feature Extraction (ALFE) pipeline, an open-source, Python-based pipeline that consumes MR images of the brain and produces anatomical segmentations, lesion segmentations, and human-interpretable imaging features describing the lesions in the brain. ALFE pipeline is modeled after the neuroradiology workflow and generates features that can be used by physicians for quantitative analysis of clinical brain MRIs and for machine learning applications. The pipeline uses a decoupled design which allows the user to customize the image processing, image registrations, and AI segmentation tools without the need to change the business logic of the pipeline.
View Article and Find Full Text PDFCancer Causes Control
January 2025
Epidemiology Department, College of Public Health, University of Nebraska Medical Center, Omaha, NE, 68198, USA.
Purpose: To examine incidence trends and patterns for early- and late-onset liver cancer.
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Graefes Arch Clin Exp Ophthalmol
January 2025
Department of Oculoplastic, Orbital & Lacrimal Surgery, Aichi Medical University Hospital, 1-1 Yazako-Karimata, Nagakute, Aichi, 480-1195, Japan.
Purpose: To define the anatomical variance between orbital floor and medial orbital wall blowout fractures, and its change with age.
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Neuro Oncol
December 2024
Department of Neurological Surgery, Mayo Clinic; Rochester, MN, USA.
Background: While serial sampling of glioma tissue is rarely performed prior to recurrence, cerebrospinal fluid (CSF) is an underutilized longitudinal source of candidate glioma biomarkers for understanding therapeutic impacts. However, the impact of key variables to consider in longitudinal CSF samples for monitoring biomarker discovery, including anatomical location and post-surgical changes, remains unknown.
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Background: The Amyloid-Tau-Neurodegeneration (ATN) biomarker framework for Alzheimer's disease (AD) indicates binary (presence/absence) designations for each type of pathology, without regard for anatomical distribution. Neurodegeneration is designated as positive if atrophy or hypometabolism are found on imaging. However, Clifford Jack et al.
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