MGUPGMA: A Fast UPGMA Algorithm With Multiple Graphics Processing Units Using NCCL

Hua, Guan; Hung, Che Lun; Lin, Chun Yuan; Wu, Fu Che; Chan, Yu Wei; Tang, Chuan Yi

doi:10.1177/1176934317734220

Cited by 16 publications

(10 citation statements)

References 10 publications

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“…Then, the relative abundances at the phylum and genus levels, Shannon, and Chao1 indices were calculated using QIIME (1.9.1) [28][29][30]. The two groups were clustered based on the Bray-Curtis distance matrix, followed by principal co-ordinates analysis (PCoA) and unweighted pair group method with arithmetic mean (UPGMA) using R software (2.15.3) [31][32][33][34]. To further investigate the differences in the community structures between lung and intestine bacteria, Anosim analysis was performed via R software (2.15.3) [35,36].…”

Section: Discussionmentioning

confidence: 99%

Bacterial association and comparison between lung and intestine in rats

et al. 2020

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The association between lung and intestine has already been reported, but the differences in community structures or functions between lung and intestine bacteria yet need to explore. To explore the differences in community structures or functions, the lung tissues and fecal contents in rats were collected and analyzed through 16S rRNA sequencing. It was found that intestine bacteria was more abundant and diverse than lung bacteria. In intestine bacteria, Firmicutes and Bacteroides were identified as major phyla while Lactobacillus was among the most abundant genus. However, in lung the major identified phylum was Proteobacteria and genus Pseudomonas was most prominent genus. On the other hand, in contrast the lung bacteria was more concentrated in cytoskeleton and function in energy production and conversion. While, intestine bacteria were enriched in RNA processing, modification chromatin structure, dynamics and amino acid metabolism. The study provides the basis for understanding the relationships between lung and intestine bacteria.

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Section: Discussionmentioning

confidence: 99%

Bacterial association and comparison between lung and intestine in rats

et al. 2020

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“…PCoA analysis was conducted by WGCNA package, stat packages, and ggplot2 package in the R software (Version 2.15.3). Arithmetic Means (UPGMA) Clustering analysis was used for a type of hierarchical clustering method (to interpret the distance matrix using average linkage) called unweighted pair-group, which is basing on QIME software [17].…”

Section: Fecal Fluid Content Determinationmentioning

confidence: 99%

Protein Level and Infantile Diarrhea in a Postweaning Piglet Model

Gao

Yin

et al. 2020

Mediators of Inflammation

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Infantile diarrhea is a serious public health problem around worldwide and results in millions of deaths each year. The levels and sources of dietary protein are potential sources of diarrhea, but the relationship between the pathogenesis causes of infantile diarrhea and protein intake remains poorly understood. Many studies have indicated that the key to understanding the relationship between the protein in the diet and the postweaning diarrhea of piglets is to explore the influences of protein sources and levels on the mammalian digestion system. The current study was designed to control diarrhea control by choosing different protein levels in the diet and aimed at providing efficient regulatory measures for infantile diarrhea by controlling the protein levels in diets using a postweaning piglets model. To avoid influences from other protein sources, casein was used as the only protein source in this study. Fourteen piglets (7.98±0.14 kg, weaned at 28 d) were randomly allotted to two dietary treatments: a control group (Cont, containing 17% casein) and a high protein group (HP, containing 30% casein). The experiment lasted for two weeks and all animals were free to eat and drink water ad libitum. The diarrhea score (1=normal; 3=watery diarrhea) and growth performance were recorded daily. The results showed that the piglets in HP group had persistent diarrhea during the whole study, while no diarrhea was noticed in the control groups. Also, the feed intake and body weights were reduced in the HP groups compared with the other group (P<0.05). The diarrhea-related mRNA abundances were analyzed by real-time PCR; the results showed that HP treatment markedly decreased the expression of aquaporin (AQP, P<0.05) and the tight junction protein (P<0.05), but increased inflammatory cytokines (P<0.01) than those in control group. In addition, the Adenosine 5′-monophosphate (AMP)-activated protein kinase (AMPK) signaling pathway (P<0.01) was inhibited in the HP group. Intestinal microbiota was tested by 16S sequencing, and we found that the HP group had a low diversity compared the other group. In conclusion, despite being highly digestible, a high casein diet induced postweaning diarrhea and reduced the growth performance of the postweaning piglets. Meanwhile, AQP, tight junction protein, and intestinal immune were compromised. Thus, the mechanism of how a highly digestible protein diet induces diarrhea might be associated with the AMPK signaling pathway and intestinal microbiome.

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“…All data were analyzed using BioNumerics (version 5.1; Applied Maths, Sint-Martens-Latem, Belgium). Clustering analysis was based on the categorical coefficient and the unweighted pair group method using the arithmetic averages (UPGMA) method [ 15 ].…”

Section: Methodsmentioning

confidence: 99%

Molecular characteristics of Brucella melitensis isolates from humans in Qinghai Province, China

Zhao

Li²,

et al. 2021

Infect Dis Poverty

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Background The prevalence of human brucellosis in Qinghai Province of China has been increasing rapidly, with confirmed cases distributed across 31 counties. However, the epidemiology of brucellosis transmission has not been fully elucidated. To characterize the infecting strains isolated from humans, multiple-locus variable-number tandem repeats analysis (MLVA) and whole-genome single-nucleotide polymorphism (SNP)-based approaches were employed. Methods Strains were isolated from two males blood cultures that were confirmed Brucella melitensis positive following biotyping and MLVA. Genomic DNA was extracted from these two strains, and whole-genome sequencing was performed. Next, SNP-based phylogenetic analysis was performed to compare the two strains to 94 B. melitensis strains (complete genome and draft genome) retrieved from online databases. Results The two Brucella isolates were identified as B. melitensis biovar 3 (QH2019001 and QH2019005) following conventional biotyping and were found to have differences in their variable number tandem repeats (VNTRs) using MLVA-16. Phylogenetic examination assigned the 96 strains to five genotype groups, with QH2019001 and QH2019005 assigned to the same group, but different subgroups. Moreover, the QH2019005 strain was assigned to a new subgenotype, IIj, within genotype II. These findings were then combined to determine the geographic origin of the two Brucella strains. Conclusions Utilizing a whole-genome SNP-based approach enabled differences between the two B. melitensis strains to be more clearly resolved, and facilitated the elucidation of their different evolutionary histories. This approach also revealed that QH2019005 is a member of a new subgenotype (IIj) with an ancient origin in the eastern Mediterranean Sea.

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MGUPGMA: A Fast UPGMA Algorithm With Multiple Graphics Processing Units Using NCCL

Cited by 16 publications

References 10 publications

Bacterial association and comparison between lung and intestine in rats

Bacterial association and comparison between lung and intestine in rats

Protein Level and Infantile Diarrhea in a Postweaning Piglet Model

Molecular characteristics of Brucella melitensis isolates from humans in Qinghai Province, China

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