This study was conducted at Ades forest in West Hararghe Zone, Ethiopia, for determining vegetations composition and structure. Systematic sampling method was used to collect vegetation data from 48 (20 m × 20 m) main sample plots for woody species that was established along a transect line. Sample plots were spaced at 10 m altitudinal drop from top to the bottom of the natural forest. Diameter at breast height and height of all woody species were measured. Species abundance, vernacular name and environmental variables were recorded in each sample plot. A total of 48 woody plants belonging to 42 genera and 29 families were recorded and identified. Fabaceae family had the highest number of taxa followed by Rosaceae and Flacourtiaceae families. Although the overall population structure of woody plants of the Forest revealed good regeneration status, the presence of anthropogenic disturbance in the area necessitates the need for conservation action in order to ensure sustainable utilization and management of the Forest.
The purpose of the study is to examine the role and impacts of growth hormone in maximizing animal products. Growth hormones are biological stimulants that are found either naturally in the organism or synthetically manufactured. Phytoestrogens, phytoprogestrons and Phenolic compounds are hormones from plants. Drugs from of placenta and colostrums of cow`s contain progesterone, estrogene, gonadotropin, and prostaglandins hormones. Growth hormones have got popular applications in dairy, beef, feed improvement and Biopharmaceutical productions with the aim of producing valuable products: fat free meat (Porcine Somatotropin hormone in pigs), nutritionally and medicinally reach milk (Bovine Somatotropin hormone in cattle), palatable and disease and insect pest resistant forage crop production. They have got also contribution in maximizing livestock production by involving in adjusting animals’ reproductive process such as oestrus synchronization and superovulation mainly during artificial insemination and embryo transfer. Controversially, these hormones have wide impacts on human being, animal welfare, environment and etc. Contamination of ground water by hormones that are found in the animals` excreta will cause deleterious effects such as cancer, loss of fertility, and some imbalance of minerals in the water and soil.
Microbial genes and their product were diverse and beneficial for heavy metal bioremediation from the contaminated sites. Screening of genes and gene products plays a significant role in the detoxification of pollutants. Understanding of the promoter region and its regulatory elements is a vital implication of microbial genes. To the best of our knowledge, there is no in silico study reported so far on mer gene families used for heavy metal bioremediation. The motif distribution was observed densely upstream of the TSSs (transcription start sites) between +1 and -350 bp and sparsely distributed above -350 bp, according to the current study. MEME identified the best common candidate motifs of TFs (transcription factors) binding with the lowest e value (7.2 e -033) and is the most statistically significant candidate motif. The EXPREG output of the 11 TFs with varying degrees of function such as activation, repression, transcription, and dual purposes was thoroughly examined. Data revealed that transcriptional gene regulation in terms of activation and repression was observed at 36.4% and 54.56%, respectively. This shows that most TFs are involved in transcription gene repression rather than activation. Likewise, EXPREG output revealed that transcriptional conformational modes, such as monomers, dimers, tetramers, and other factors, were also analyzed. The data indicated that most of the transcriptional conformation mode was dual, which accounts for 96%. CpG island analysis using online and offline tools revealed that the gene body had fewer CpG islands compared to the promoter regions. Understanding the common candidate motifs, transcriptional factors, and regulatory elements of the mer operon gene cluster using a machine learning approach could help us better understand gene expression patterns in heavy metal bioremediation.
Background: Microbial gene and gene production were diverse and beneficial for heavy metal bioremediation from the contaminated sites. Screening of genes and gene products plays an important role in the detoxification of pollutants. Understanding of promoter region and its regulatory elements is a vital implication of microbial genes. To the best of our knowledge, there is no in silico analysis report so far on mer genes families used for heavy metal bioremediation. Results: The motif distribution was observed densely upstream of the TSS from +1 to -400bp and sparsely distributed above -500bp, according to the current study. MEME identified the best common candidate motifs of TFs binding with the lowest e value (7.2e 033) and is the most statistically significant candidate motif. The EXPREG output of the 11 TFs with varying degrees of function as activation, repression transcriptions, and dual purposes was thoroughly examined. Data revealed that transcriptional gene regulation in terms of activation and repression was observed at 36.4% and 54.56% respectively. This shows that the vast majority of TFs are involved in the transcription gene repression rather than activation. Likewise, EXPREG output revealed that transcriptional conformational modes, such as monomer, dimer, tetramer, and other factors, were also analyzed. The data indicated that the majority of transcriptional conformation mode was dual which accounts for 96%. CpG island analysis using online and offline tools revealed that the gene body had fewer CpG islands as compared with the promoter regions. Conclusion: Understanding the common candidate motifs, transcriptional factors binding sites, and regulatory elements of the mer operon gene cluster using a machine learning approach could help us better understand gene expression patterns in heavy metal bioremediation.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.