Acute Toxicity of Aluminum, Cobalt, and Lithium Chlorides in Albino wistar Mice: Determination of Lethal Doses
Bibliographic record
Abstract
Chlorides are considered one of the dangerous pollutants that pose a threat to human and animal health.The study aims to determine the acute lethal doses (LD50) of aluminum, cobalt, and lithium chlorides in Albino wistar mice.Albino wistar mice were divided into four groups with the mice were randomly divided into 4 groups, 8 mice for experimental group and 6 mice for control group.Short tests were conducted to determine the acute lethal dose of the metals under study.Over 168 hours, mice were exposed to four different concentrations of (AlCl2) metal in concentrations of 40, 50, 60 and 70 mg/kg per liter of water, where 1 liter of water was placed in each bottle, while the second group was exposed to cobalt chloride (CoCl2) in concentrations 75, 100, 125 and 150 mg/kg per liter of water, where 1 liter of water was placed in each bottle.As well as, the third group, it was exposed to (LiCl2) at concentrations 75, 100, 125 and 150 mg/kg per liter of water, while the fourth group included the control group. 1 liter of water was placed in each bottle and it was given orally.LC50 was calculated by use Finney's probit analysis method where LC50 it is abbreviation "lethal concentration 50%" or "intermediate lethal concentration".It is the concentration of a material (in the water) which it killed a half the members of populations after a specific during of exposed to toxic metal.This value is so importance in toxicology because it gives an indicated of materials poisoning.The LC50 is inverse proportionate to toxicity.The current study concluded the dose that killed 50% of the Albino wistar mice was 50mg/kg of AlCl2, 100mg/kg of CoCl2, while it was 125mg/kg of lithium chloride.Long-term use of greater doses of chlorides can have varying degrees of negative impact on various organs in mice.This study provides context for a more thorough investigation of the toxicity of chlorides compounds on humans, which may be significant for public health.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".