PROTECTIVE EFFECTS OF BLUE GREEN ALGAE SPIRULINA FUSIFORMIS AGAINST GALACTOSAMINE-INDUCED HEPATOTOXICITY IN MICE

Objective:The present investigation was carried out to assess the protective properties of Spirulina fusiformis against galactosamine induced toxicity in swiss albino mice. Methods:Evaluation of serum glutamate oxaloacetate transferase (SGOT), serum glutamate pyruvate transferase (SGPT), alkaline phosphatase (ALP), serum bilirubin (SBLN), antioxidant status and TNF-α was done and was compared with the standard reference drug silymarin. Results: Galactosamine injection significantly increased the levels of SGOT, SGPT, SBLN and TNF–α in the serum and caused depletion in the antioxidant status in the liver. Administration of Spirulina fusiformis altered these parameters and brought them to normal levels in the control and experimental mice. Conclusion:Hence results of this study clearly indicate that Spirulina fusiformis has hepatoprotective activity against galactosamine induced toxicity in mice. Keywords: Spirulina, antioxidant, galactosamine, hepatoprotective, silymari

In vitro and In vivo study on the effect of Scoparia Dulcis in inhibiting the growth of urinary crystals.

Urolithiasis is a very common and highly recurring painful disease both in developing and developed nations due to the change in lifestyle and food habits. Scoparia Dulcis is herbal plant which has been used as a traditional medicine for dissolving urinary stones by the tribal group of people in Western Ghats, India. This experimental study gives a scientific awareness about the effect of Scoparia Dulcis in dissolving the urinary crystals and will confirm the drug’s effect on the organs like kidney and liver. The invitro testing was done by developing urinary crystals using single diffusion gel growth technique and the water extract of the drug is incorporated to monitor the growth of the crystal. The statistical analysis was done for the in vitro study and has proved 2ml dosage shows the highest significance in variation. In invivo testing, the urinary crystals were induced in Wistar Rats and the drug was fed to monitor its effect on the growth of crystals as well as on nearby organs.  The urine and serum samples were tested for all the group of rats and parameters analysis proved the significance of the drug. The histopathology analysis gives the sectional view and report of diseased and treated groups. In both the invitro as well as invivo testing, the drug showed a significant effect in inhibiting the growth of urinary crystals

Ontological Analysis of Coronavirus Associated Human Genes at the COVID-19 Disease Portal

The COVID-19 pandemic stemmed a parallel upsurge in the scientific literature about SARS-CoV-2 infection and its health burden. The Rat Genome Database (RGD) created a COVID-19 Disease Portal to leverage information from the scientific literature. In the COVID-19 Portal, gene-disease associations are established by manual curation of PubMed literature. The portal contains data for nine ontologies related to COVID-19, an embedded enrichment analysis tool, as well as links to a toolkit. Using these information and tools, we performed analyses on the curated COVID-19 disease genes. As expected, Disease Ontology enrichment analysis showed that the COVID-19 gene set is highly enriched with coronavirus infectious disease and related diseases. However, other less related diseases were also highly enriched, such as liver and rheumatic diseases. Using the comparison heatmap tool, we found nearly 60 percent of the COVID-19 genes were associated with nervous system disease and 40 percent were associated with gastrointestinal disease. Our analysis confirms the role of the immune system in COVID-19 pathogenesis as shown by substantial enrichment of immune system related Gene Ontology terms. The information in RGD’s COVID-19 disease portal can generate new hypotheses to potentiate novel therapies and prevention of acute and long-term complications of COVID-19

The Gene Ontology knowledgebase in 2023

The Gene Ontology (GO) knowledgebase (http://geneontology.org) is a comprehensive resource concerning the functions of genes and gene products (proteins and noncoding RNAs). GO annotations cover genes from organisms across the tree of life as well as viruses, though most gene function knowledge currently derives from experiments carried out in a relatively small number of model organisms. Here, we provide an updated overview of the GO knowledgebase, as well as the efforts of the broad, international consortium of scientists that develops, maintains, and updates the GO knowledgebase. The GO knowledgebase consists of three components: (1) the GO-a computational knowledge structure describing the functional characteristics of genes; (2) GO annotations-evidence-supported statements asserting that a specific gene product has a particular functional characteristic; and (3) GO Causal Activity Models (GO-CAMs)-mechanistic models of molecular "pathways" (GO biological processes) created by linking multiple GO annotations using defined relations. Each of these components is continually expanded, revised, and updated in response to newly published discoveries and receives extensive QA checks, reviews, and user feedback. For each of these components, we provide a description of the current contents, recent developments to keep the knowledgebase up to date with new discoveries, and guidance on how users can best make use of the data that we provide. We conclude with future directions for the project

The Gene Ontology Knowledgebase in 2023

: The Gene Ontology (GO) knowledgebase (http://geneontology.org) is a comprehensive resource concerning the functions of genes and gene products (proteins and non-coding RNAs). GO annotations cover genes from organisms across the tree of life as well as viruses, though most gene function knowledge currently derives from experiments carried out in a relatively small number of model organisms. Here, we provide an updated overview of the GO knowledgebase, as well as the efforts of the broad, international consortium of scientists that develops, maintains and updates the GO knowledgebase. The GO knowledgebase consists of three components: 1) the Gene Ontology - a computational knowledge structure describing functional characteristics of genes; 2) GO annotations - evidence-supported statements asserting that a specific gene product has a particular functional characteristic; and 3) GO Causal Activity Models (GO-CAMs) - mechanistic models of molecular "pathways" (GO biological processes) created by linking multiple GO annotations using defined relations. Each of these components is continually expanded, revised and updated in response to newly published discoveries, and receives extensive QA checks, reviews and user feedback. For each of these components, we provide a description of the current contents, recent developments to keep the knowledgebase up to date with new discoveries, as well as guidance on how users can best make use of the data we provide. We conclude with future directions for the project