Results 221 to 230 of about 517,992 (346)

Microbiota humanization drives human‐like metabolic and immune transcriptomic shifts in pigs

iMetaOmics, EarlyView.
This study successfully established gut microbiota‐humanized pigs, achieved human‐like remodeling of the serum metabolome, and uncovered transcriptional alterations in immune cell subsets. These findings advance our understanding of how human gastrointestinal microorganisms affect host metabolism and the immune function in a porcine model.
Zhaoqi Zhang, Yanan Xu, Kun Pang, Changhong Wu, Chenxu Zhao, Tong Lei, Jiayu Zhang, Tang Hai, Fangqing Zhao, Yong Zhao   +9 more
wiley   +1 more source

Learning microbiology and virology from the cinema. [PDF]

J Microbiol Biol Educ
Schildgen O, Smetana J, Ehlers J, Dreckmann K.   +3 more
europepmc   +1 more source

Real-time PCR in virology.

Nucleic Acids Research, 2002
I. Mackay, K. Arden, A. Nitsche
semanticscholar   +1 more source

Electroacupuncture reshapes the microbial co‐occurrence networks related to the behavioral and psychological symptoms of dementia in Alzheimer's disease

iMetaOmics, EarlyView.
Microbial keystone species and gut microbiota composition are highly variable during the pathological development of the behavioral and psychological symptoms of dementia (BPSD) in Alzheimer's disease (AD). Age stratification reveals stage‐specific gut microbial signatures in AD‐related BPSD.
Fu‐You Su, Chia‐Min Lin, Chao Liu, Yiqin Yao, Hui Wang, Chunxue Zhang, Wei Yi, Nenggui Xu   +7 more
wiley   +1 more source

Progress in Medical Virology [PDF]

, 1978

openalex   +1 more source

Physical, chemical, and synthetic virology: Reprogramming viruses as controllable nanodevices.

Wiley Interdisciplinary Reviews: Nanomedicine and Nanobiotechnology, 2019
Maria Y. Chen, Susan Butler, Weitong Chen, J. Suh   +3 more
semanticscholar   +1 more source

BioMGCore: A toolkit for detection of biological metabolites in microbiome

iMetaOmics, EarlyView.
The keyword matching and gene proximity principles were used to accurately identify core gene clusters in microbial genomes. The metabolic gene clusters can be classified into different taxonomic groups according to Domain, Phylum, Class, Order, Family, Genus, and Species. BioMGCore can achieve batch statistics for secondary metabolites prediction.
Guang Yang, Guohao Yu, Qian Cui, Xueping Huang, Kexin Guo, Shulei Jia   +5 more
wiley   +1 more source

Virologist Opinions: An Important Component for the Governance of the Convergence of Artificial Intelligence and Dual-Use Research of Concern. [PDF]

Appl Biosaf
Walsh ME, Gronvall GK.
europepmc   +1 more source

Diagnostic Methods in Clinical Virology [PDF]

, 1976
J. A. Dudgeon
openalex   +1 more source

Modular automated high‐throughput isolation and phylogenetic identification of bacteria from complex microbiomes

iMetaOmics, EarlyView.
Metagenomic analysis can generate hypotheses about microbiome interactions and function, yet mechanistic understanding is only possible through precise experimentation manipulating its microbiota composition. The high‐throughput isolation of microbiome members thus represents a core resource in this field of research.
Rubén Chaboy‐Cansado, Silvia Talavera‐Marcos, Ramón Gallego‐Simón, Paula Cobeta, Gabriel Roscales, Alberto Rastrojo, Daniel Aguirre de Cárcer   +6 more
wiley   +1 more source