Aquatic invertebrates are common reservoirs of a rapidly expanding group of circular Rep-encoding ssDNA (CRESS-DNA) viruses. This study identified and explored the phylogenetic relationship between novel CRESS-DNA viral genotypes associated with Pacific intertidal isopods , , and . One genotype associated with , IWaV278, shared sequence similarity and genomic features with Tombusviridae (ssRNA) and Circoviridae (ssDNA) genomes and was putatively assigned to the Cruciviridae clade comprising chimeric viruses. The complete genome of IWaV278 (3478 nt) was computationally completed, validated via Sanger sequencing, and exhibited sequence conservation and codon usage patterns analogous to other members of the Cruciviridae. Viral surveillance (qPCR) indicated that this virus was temporally transient (present in 2015, but not 2017), specific to at a single collection site (Washington, DC, USA), more prevalent among male specimens, and frequently detected within exoskeletal structures. 18S rRNA sequences identified two alveolate protists associated with IWaV278-positive tissues and mechanical epibiont removal of ciliated exoskeletal structures eliminated viral detection, suggesting that the putative host of IWaV278 may be an epibiont of . This investigation provides additional phylogenetic evidence to resolve Cruciviridae evolution and offers insight into the biogeography, specificity, and potential host of a crucivirus genotype.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5744136 | PMC |
| http://dx.doi.org/10.3390/v9120361 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Improved Transfer Learning for Detecting Upper-Limb Movement Intention Using Mechanical Sensors in an Exoskeletal Rehabilitation System.
IEEE Trans Neural Syst Rehabil Eng
November 2024
The objective of this study was to propose a novel strategy for detecting upper-limb motion intentions from mechanical sensor signals using deep and heterogeneous transfer learning techniques. Three sensor types, surface electromyography (sEMG), force-sensitive resistors (FSRs), and inertial measurement units (IMUs), were combined to capture biometric signals during arm-up, hold, and arm-down movements. To distinguish motion intentions, deep learning models were constructed using the CIFAR-ResNet18 and CIFAR-MobileNetV2 architectures.
View Article and Find Full Text PDFProsthetic Componentry in Lower Limb Prosthetic Restoration.
Phys Med Rehabil Clin N Am
November 2024
Regional Amputation Center, Rehabilitation Care Services, VA Puget Sound Health Care System, 1660 South Columbian Way, Seattle, WA 98108, USA.
This article describes fundamental lower limb prosthesis concepts and componentry, including skeletal structure (endoskeletal vs exoskeletal), transtibial and transfemoral sockets, prosthetic suspension and interfaces, prosthetic knees, and prosthetic foot and ankle systems.
View Article and Find Full Text PDFWhen the Host Encounters the Cell Wall and Vice Versa.
Annu Rev Microbiol
November 2024
Institut Pasteur, Université Paris Cité, CNRS UMR 6047, Integrative and Molecular Microbiology, INSERM U1306, Host-Microbe Interactions and Pathophysiology, Unit of Biology and Genetics of the Bacterial Cell Wall, Paris, France; email:
Article Synopsis
- Peptidoglycan (PGN) is crucial for bacterial cell structure and survival, as it helps maintain shape and withstand internal pressure during growth and division.
- The regulation of PGN assembly impacts bacterial fitness across different environments and plays a key role in their interaction with hosts.
- Disruptions in the communication between PGN and host systems can lead to chronic diseases, while pathogens exploit these interactions to promote their own survival.
Clinical machine learning predicting best stroke rehabilitation responders to exoskeletal robotic gait rehabilitation.
NeuroRehabilitation
June 2024
Department of Physical Therapy, Sports·Movement Artificial-Intelligence Robotics Technology (SMART) Institute, Yonsei University, Wonju, South Korea.
Background: Although clinical machine learning (ML) algorithms offer promising potential in forecasting optimal stroke rehabilitation outcomes, their specific capacity to ascertain favorable outcomes and identify responders to robotic-assisted gait training (RAGT) in individuals with hemiparetic stroke undergoing such intervention remains unexplored.
Objective: We aimed to determine the best predictive model based on the international classification of functioning impairment domain features (Fugl- Meyer assessment (FMA), Modified Barthel index related-gait scale (MBI), Berg balance scale (BBS)) and reveal their responsiveness to robotic assisted gait training (RAGT) in patients with subacute stroke.
Methods: Data from 187 people with subacute stroke who underwent a 12-week Walkbot RAGT intervention were obtained and analyzed.
Behavior and morphology combine to influence energy dissipation in mantis shrimp (Stomatopoda).
J Exp Biol
April 2024
UC Santa Barbara, Ecology, Evolution, and Marine Biology, Santa Barbara, CA 93106, USA.
Animals deliver and withstand physical impacts in diverse behavioral contexts, from competing rams clashing their antlers together to archerfish impacting prey with jets of water. Though the ability of animals to withstand impact has generally been studied by focusing on morphology, behaviors may also influence impact resistance. Mantis shrimp exchange high-force strikes on each other's coiled, armored telsons (tailplates) during contests over territory.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!