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Cenostigma pyramidale: Ethnomedicinal Properties and Perspectives on A Legume Tree Highly Adapted to Semiarid ‘Caatinga’ Region
Published in Mahendra Rai, Shandesh Bhattarai, Chistiane M. Feitosa, Ethnopharmacology of Wild Plants, 2021
Livia Maria Batista Vilela, Carlos André dos Santos-Silva, Ricardo Salas Roldan Filho, Silvany de Sousa Araújo, José Ribamar Costa Ferreira-Neto, Wilson Dias de Oliveira, Lidiane Lindinalva Barbosa Amorim, Valesca Pandolfi, Ana Maria Benko-Iseppon
The first study was performed by Mendes et al. (2014), who analyzed ten accessions [eight of C. pyramidale and two of Poincianella bracteosa (Tul.) L.P.Queiroz] from a semiarid zone in the state of Piauí (northeastern Brazil). The similarity coefficient between accessions was low (mean value 0.59) but presented a wide variation (from 0.443 to 0.748). The dendrogram constructed using the UPGMA (Unweighted Pair Group Method with Arithmetic Mean) based on a similarity matrix allowed the separation of the accessions into two major clusters represented by the two distinct species, while the accessions of C. pyramidale could be further separated into three subgroups. The second study was carried out by Belarmino et al. (2017) that evaluated the genetic diversity among 20 C. pyramidale individuals collected in the state of Paraíba (Brazil). The mean genetic diversity among the genotypes was 63.28%, ranging from 30.9 to 97.7%. The population evaluated in this study showed high genetic diversity, and formed twelve clusters based on the UPGMA analysis. The third article was published by Rodrigues et al. (2014), who analyzed the karyomorphology and karyotype asymmetry of species of the South American Caesalpinia (a previous generic epithet of C. pyramidale), including C. pyramidale individuals collected from Bom Jesus da Lapa (Bahia state, Brazil). It was reported that the mentioned species is diploid and has 24 chromosomes, all metacentric, with a size variation of 49.2% between the largest and the smallest chromosomal pair.
Methods for Outbreaks Using Genomic Data
Published in Leonhard Held, Niel Hens, Philip O’Neill, Jacco Wallinga, Handbook of Infectious Disease Data Analysis, 2019
Don Klinkenberg, Caroline Colijn, Xavier Didelot
A NJ tree is a binary tree built with the NJ algorithm, which iteratively connects clusters (which are single samples or groups of samples connected in previous steps) by selecting the pair of least distant clusters, until all samples are connected. If possible, this algorithm returns the tree where all distances between pairs of leaves are equal to the distances in the distance matrix, which is the case with the FMD outbreak data (Figures 13.2b and c). NJ trees are unrooted, but they can be used as the basis to make (rooted) phylogenies, where the direction of evolution is known for each branch, and the internal nodes represent ancestors. The root can be defined as the midpoint of the tree, but more often it is defined by including samples known to be well separated from the sequences under study, called outgroups. Figure 13.2c shows such a tree for the FMD outbreak, where four reference genomes that are not part of the outbreak were used to root the tree. NJ trees are examples of phylogenetic trees which describe the inferred evolutionary relationships between the samples (or taxa). There are many more approaches to infer phylogenetic trees, for example UPGMA, maximum parsimony, maximum likelihood, and various Bayesian approaches [1, 3].
The Role of the Computer in Estimates of DNA Nucleotide Sequence Divergence
Published in S. K. Dutta, DNA Systematics, 2019
Tateno et al.74 use molecular data to test the accuracy of the UPGMA (unweighted pair group method),39 the Fitch and Margoliash62 (F/M), and a modification of the Farris63 method, as proposed by them. Implicit in their analyses was the assumption that sequence changes were proportional to evolutionary time, an assumption that has, as yet, not been proven to a certainty.50 They used computer simulations to follow the evolutionary change of 300 nucleotides over as many as 32 operational taxonomic units, according to the several models. Nucleotide substitution was assumed to occur according to a Poisson distribution. They found that the Farris and modified Farris methods were better than UPGMA and F/M when the coefficient of variation of the branch lengths was large. However, their modification gave better results when calculating estimates of the number of nucleotide substitutions for each branch. The UPGMA approach was found to be the best when the coefficient of variation of the branch lengths was small. No mention was made of the language used for the program or of the hardware used.
Exploring the extent of mental health practice: content and cluster analysis of techniques used in HIV testing and counselling sessions in Uganda
Published in AIDS Care, 2023
Faith Martin, Eleanor Clowes, Winifred Nalukenge, Cain Clark, Oucul Lazarus, Josephine Birungi, Janet Seeley
To address whether techniques tended to occur in any pattern, hierarchical cluster analysis was conducted. Checklist techniques appearing in at least 10% of the transcripts (and therefore were not rare), were subjected to unweighted group method with arithmetic mean (UPGMA) cluster analysis, based on the Jaccard Similarity Coefficient (Sokal, 1958). The UPGMA cluster analysis is a distance-matrix method, employing sequential clustering to build a dendrogram. First, all sequences were compared via pairwise alignment to compute the Jaccard Similarity Coefficient matrix. The two sequences with the minimum distance were identified and clustered as a singular pair. Subsequently, the distance between this pair and all other sequences was recalculated to form a new matrix. Then, the sequence that was closest to the first pair was identified and clustered. This process was repeated until all sequences were incorporated into the cluster. The height of the link joining observations on the dendrogram was joined was assessed using the Jaccard Similarity Coefficient, to demonstrate the similarity between two clusters. Briefly, where similarity approaches the maxima, “1”, this indicates items occurred together 100% of the time, whilst at the minima, “0”, items occurred together 0% of the time (Saraçli et al., 2013). All data analyses were conducted using R (R Core Team), and dendrogram was drawn using PAleontological Statistics (Hammer et al., 2001).
The Impact of Migration on the Gut Metagenome of South Asian Canadians
Published in Gut Microbes, 2021
Julia K. Copeland, Gary Chao, Shelley Vanderhout, Erica Acton, Pauline W. Wang, Eric I. Benchimol, Ahmed El-Sohemy, Ken Croitoru, Jennifer L. Gommerman, David S. Guttman
We used the presence of the enzyme families of interest to cluster the species into hierarchical groups by UPGMA (Figure 6, Figure S6). Many Bacteroides species harbored multiple gene families involved in these fermentation processes within a single species, while Negativicutes species and P. copri often contained only a single-gene family per fermentation process; missing many of the genes required to complete the fermentation pathway. We examined the average normalized Copies Per Million of these carbohydrate degradation gene families by generation (Table S6C), specifically focusing on the potential for cellulose, pectin, and xylan degradation. Although the differences were not significant, we observed a greater potential for xylan degradation in GEN1 and a greater potential for pectin and mucin glycan degradation in GEN2. P. copri was the most abundant endo-1,4-B-xylanase containing species, followed by B. uniformis. Potential mucin degrading enzymes were identified across the metagenome, present in B. longum and many Bacteroides, Alistipes, Clostridia, and Negativicutes species. Pectinesterase was present in P. copri but not in B. uniformis or B. longum.
Differences in the oral and intestinal microbiotas in pregnant women varying in periodontitis and gestational diabetes mellitus conditions
Published in Journal of Oral Microbiology, 2021
Xin Zhang, Pei Wang, Liangkun Ma, Rongjun Guo, Yongjing Zhang, Peng Wang, Jizhi Zhao, Juntao Liu
UPGMA analysis based on weighted UniFrac distances was performed to investigate the influence of GDM and periodontitis on the beta diversity of the oral and intestinal communities. From the results, all samples were separated into two groups with all oral samples in one cluster and all intestinal samples in the other cluster. Oral samples were sub-grouped into two clusters according to periodontal status, and groups with and without GDM were gathered together for both periodontitis and non-periodontitis conditions. With regard to the intestinal samples, two major clusters were found, with periodontitis + GDM in one group and healthy controls, periodontitis and GDM in the other group (Figure 3). The differences in microbial community structure among groups were also evaluated by AMOVA analysis (Table S3). Significant differences were found between healthy controls and the periodontitis group in oral samples (p < 0.001), while no significant differences between any other two groups in oral samples were found (p> 0.05). A significant difference in microbial structure was also found between the periodontitis + GDM group and healthy controls in intestinal samples (p = 0.043).