Reiteration is the process whereby architectural units are replicated within a tree. Both immediate (from apical buds) and delayed (from suppressed or adventitious buds) reiteration can be seen in many tree species where architectural units ranging from clusters of shoots to entire branches and stems are replicated. In large old trees and suppressed trees, delayed reiteration occurs without an obvious external stimulus such as defoliation or traumatic loss of the branch apex. This suggests that, in trees that are growth-limited, reiteration is an adaptive mechanism for crown maintenance. We discuss theories about the aging process and how delayed adaptive reiteration may help maintain crown productivity and increase longevity. These include: (1) reducing the respiration/photosynthesis ratio; (2) increasing hydraulic conductance to newly developing foliage; (3) reducing nutrient loss from the tree; and (4) rejuvenating the apical meristem. The ability to reiterate various architectural units may contribute to increasing lifetime reproductive output by prolonging tree longevity. Further studies on the physiological and ecological implications of reiteration are needed to understand its adaptive significance in the life history of trees.
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http://dx.doi.org/10.1093/treephys/27.3.455 | DOI Listing |
Cell Discov
January 2025
Department of Liver Surgery and Transplantation, and Key Laboratory of Carcinogenesis and Cancer Invasion (Ministry of Education), Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China.
Dissecting the spatial heterogeneity of cancer-associated fibroblasts (CAFs) is vital for understanding tumor biology and therapeutic design. By combining pathological image analysis with spatial proteomics, we revealed two stromal archetypes in hepatocellular carcinoma (HCC) with different biological functions and extracellular matrix compositions. Using paired single-cell RNA and epigenomic sequencing with Stereo-seq, we revealed two fibroblast subsets CAF-FAP and CAF-C7, whose spatial enrichment strongly correlated with the two stromal archetypes and opposing patient prognosis.
View Article and Find Full Text PDFEnviron Microbiol
January 2025
Institute of New Energy and Low-Carbon Technology, Sichuan University, Chengdu, China.
Anaerobic digestion (AD) of organic wastes relies on the interaction and cooperation of various microorganisms. Phages are crucial components of the microbial community in AD systems, but their diversity and interactions with the prokaryotic populations are still inadequately comprehended. In this study, 2121 viral operational taxonomic units (vOTUs) were recovered from 12 anaerobic fatty acid-fed reactors.
View Article and Find Full Text PDFClin Epigenetics
January 2025
Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK.
Alcohol consumption is an important risk factor for multiple diseases. It is typically assessed via self-report, which is open to measurement error through recall bias. Instead, molecular data such as blood-based DNA methylation (DNAm) could be used to derive a more objective measure of alcohol consumption by incorporating information from cytosine-phosphate-guanine (CpG) sites known to be linked to the trait.
View Article and Find Full Text PDFJ Environ Manage
January 2025
Department of Civil, Environmental and Architectural Engineering, University of Padova, Via Marzolo 9, 35131, Padova, Italy.
The materials removed in the oil separation units of wastewater treatment plants can be referred to as fat, oil and grease (FOG) waste. FOG waste accumulation in treatment plants can cause clogging of pipes, production of excessive scums and foams, and negatively affect air/liquid oxygen transfer. While conventional disposal routes of this material can be limited by its water and organic content, FOG can represent a source of bio-energy other than bio-diesel production.
View Article and Find Full Text PDFMicromachines (Basel)
December 2024
Institute of Information Science, Beijing Jiaotong University, Beijing 100044, China.
Reconfigurable processor-based acceleration of deep convolutional neural network (DCNN) algorithms has emerged as a widely adopted technique, with particular attention on sparse neural network acceleration as an active research area. However, many computing devices that claim high computational power still struggle to execute neural network algorithms with optimal efficiency, low latency, and minimal power consumption. Consequently, there remains significant potential for further exploration into improving the efficiency, latency, and power consumption of neural network accelerators across diverse computational scenarios.
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