One of the fascinating aspects of the history of life is the apparent increase in morphological complexity through time, a well known example being mammalian cheek tooth evolution. In contrast, experimental studies of development more readily show a decrease in complexity, again well exemplified by mammalian teeth, in which tooth crown features called cusps are frequently lost in mutant and transgenic mice. Here we report that mouse tooth complexity can be increased substantially by adjusting multiple signalling pathways simultaneously. We cultured teeth in vitro and adjusted ectodysplasin (EDA), activin A and sonic hedgehog (SHH) pathways, all of which are individually required for normal tooth development. We quantified tooth complexity using the number of cusps and a topographic measure of surface complexity. The results show that whereas activation of EDA and activin A signalling, and inhibition of SHH signalling, individually cause subtle to moderate increases in complexity, cusp number is doubled when all three pathways are adjusted in unison. Furthermore, the increase in cusp number does not result from an increase in tooth size, but from an altered primary patterning phase of development. The combination of a lack of complex mutants, the paucity of natural variants with complex phenotypes, and our results of greatly increased dental complexity using multiple pathways, suggests that an increase may be inherently different from a decrease in phenotypic complexity.
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Sci Rep
December 2024
Hy-Line International, 2583 240th St, PO Box 310, Dallas Center, 50063, IA, USA.
Marek's Disease (MD), which can result in neurological damage and tumour formation, has large effects on the economy and animal welfare of the poultry industry worldwide. Previously, we mapped autosomal MD QTL regions (QTLRs) by individual genotyping of an F population from a full-sib advanced intercross line. We further mapped MD QTLRs on the chicken Z chromosome (GGZ) using the same F population, and by selective DNA pooling (SDP) of 8 elite egg production lines.
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December 2024
College of Economics and Management, Huazhong Agricultural University, Wuhan, 430070, Hubei, China.
In light of the Chinese government's dual carbon goals, achieving cleaner production activities has become a central focus, with regional environmental collaborative governance, including the management of agricultural carbon reduction, emerging as a mainstream approach. This study examines 268 prefecture-level cities in China, measuring the carbon emission efficiency of city agriculture from 2001 to 2022. By integrating social network analysis and a modified gravity model, the study reveals the characteristics of the spatial association network of city agricultural carbon emission efficiency in China.
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December 2024
KAUST Center of Excellence for Smart Health (KCSH), King Abdullah University of Science and Technology, Thuwal, 23955, Saudi Arabia.
Analyzing microbial samples remains computationally challenging due to their diversity and complexity. The lack of robust de novo protein function prediction methods exacerbates the difficulty in deriving functional insights from these samples. Traditional prediction methods, dependent on homology and sequence similarity, often fail to predict functions for novel proteins and proteins without known homologs.
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December 2024
Merchant Marine College, Shanghai Maritime University, Shanghai, 201306, China.
The intelligent identification of wear particles in ferrography is a critical bottleneck that hampers the development and widespread adoption of ferrography technology. To address challenges such as false detection, missed detection of small wear particles, difficulty in distinguishing overlapping and similar abrasions, and handling complex image backgrounds, this paper proposes an algorithm called TCBGY-Net for detecting wear particles in ferrography images. The proposed TCBGY-Net uses YOLOv5s as the backbone network, which is enhanced with several advanced modules to improve detection performance.
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December 2024
School of Electrical Engineering, Vellore Institute of Technology, Chennai, 600127, India.
Spherical tanks have been predominantly used in process industries due to their large storage capability. The fundamental challenges in process industries require a very efficient controller to control the various process parameters owing to their nonlinear behavior. The current research work in this paper aims to propose the Approximate Generalized Time Moments (AGTM) optimization technique for designing Fractional-Order PI (FOPI) and Fractional-Order PID (FOPID) controllers for the nonlinear Single Spherical Tank Liquid Level System (SSTLLS).
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