Formulating a New Pharmaceutical Drug; Acetaminophen Tablet Containing N-acetyl Cysteine, To Alleviate the Severity of Liver Damage in Rats: Phase I, Animal Study

Background and Aim: Acetaminophen (APAP) is a commonly used analgesic and also the leading cause of medication-induced liver damage. On the other hand, N-acetylcysteine (NAC) is a medication widely used to treat APAP overdose. Despite this interest, a few studies have investigated the co-administration effects of these medications. Therefore, this study aimed to evaluate the effects of NAC and APAP on renal and liver functions in rats when they use concurrently. Methods: Male Wistar rats were orally treated with a single dose of APAP (700 mg/kg) alone or in combination of NAC at the three different doses (200, 500, and 700 mg/kg). After 24 hours, the blood and liver samples were collected for biochemical and histopathological evaluations. Results: Liver damage was well established in the 700 mg/kg APAP-treated rats, as evidenced by elevated the plasma levels of aspartate transaminase (AST) and alanine transaminase (ALT). In addition, the plasma level of blood urea nitrogen (BUN) was significantly increased in the APPA group compared to the control group.   Moreover, histological examinations revealed that liver degeneration was evident in APAP-treated animals. NAC only at the highest dose (700 mg/kg) could inhibit ALT elevation, but had no effect on AST and BUN levels. Interestingly, co-administration of NAC (700 mg/kg) with APAP (700 mg/kg) could slightly shift liver histological alterations from the irreversible stage (fibrosis) toward reversible lesions such as necrosis and hemorrhage. Conclusion: The study findings indicate that co-administration of NAC and APAP can reduce the severity of APAP-induced liver damage in rats. *Corresponding Author: Mehran Hosseini; Email: [email protected]; ORCID: https://orcid.org/0000-0002-6793-2035 Please cite this article as: Mehrpour O, Dastjerdi M, Nakhaee S, Amirabadizadeh A, Bijari B, Roomi H, Hosseini M. Formulating a New Pharmaceutical Drug; Acetaminophen Tablet Containing N-acetyl Cysteine, To Alleviate the Severity of Liver Damage in Rats: Phase I, Animal Study. Arch Med Lab Sci. 2021;7:1-8 (e14). https://doi.org/10.22037/amls.v7.3552

Impact of Metformin on Cancer Biomarkers in Non-Diabetic Cancer Patients: A Systematic Review and Meta-Analysis of Clinical Trials

Introduction: Our aim was to investigate and evaluate the influence of metformin on cancer-related biomarkers in clinical trials. Methods: This systematic study was conducted according to Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. Major databases, including Scopus, Web of Sciences, PubMed, Ovid-Medline, and Cochrane, were systematically reviewed by February 2020. Clinical trials investigating metformin effects on the evaluation of homeostatic models of insulin resistance (HOMA-IR), Ki-67, body mass index (BMI), fasting blood sugar (FBS), and insulin were selected for further analysis. Quality assessment was performed with version 2 of the Cochrane tool for determining the bias risk for randomized trials (RoB 2). Heterogeneity among the included studies was assessed using the Chi-square test. After quality assessment, a random effects model was performed to summarize the data related to insulin, HOMA-IR, Ki-67, and a fixed-effect model for FBS and BMI in a meta-analysis. Results: Nine clinical trials with 716 patients with operable breast and endometrial cancer and 331 with primary breast cancer were involved in the current systematic and meta-analysis study. Systematic findings on the nine publications indicated metformin decreased insulin levels in four studies, FBS in one, BMI in two, Ki-67 in three studies, and HOMA-IR in two study. The pooled analysis indicated that metformin had no significant effect on the following values: insulin (standardized mean differences (SMD) = −0.87, 95% confidence intervals (CI) (−1.93, 0.19), p = 0.11), FBS (SMD = −0.18, 95% CI (−0.30, −0.05), p = 0.004), HOMA-IR (SMD = −0.17, 95% CI (−0.52, 0.19), p = 0.36), and BMI (SMD = −0.13, 95% CI (−0.28, 0.02), p = 0.09). Metformin could decrease Ki-67 in patients with operable endometrial cancer versus healthy subjects (SMD = 0.47, 95% CI (−1.82, 2.75), p = 30.1). According to Egger’s test, no publication bias was observed for insulin, FBS, BMI, HOMA-IR, and Ki-67. Conclusions: Patients with operable breast and endometrial cancer under metformin therapy showed no significant changes in the investigated metabolic biomarkers in the most of included study. It was also found that metformin could decrease Ki-67 in patients with operable endometrial cancer. In comparison to the results obtained of our meta-analysis, due to the high heterogeneity and bias of the included clinical trials, the present findings could not confirm or reject the efficacy of metformin for patients with breast cancer and endometrial cancer

Reduction of cardiac ischemia-reperfusion injury by curcumin in high-fat diet-fed rats

Background and Aims: Curcumin has potential anti-inflammatory effects. The aim of this study was to investigate the protective effect of curcumin against cardiac ischemia -reperfusion injury in rats fed a high-fat diet. Materials and Methods: In this experimental study, male Wistar rats were divided into four groups: control (C), high-fat diet (H), curcumin 100 (HyperC100, 100 mg/kg) and curcumin 200 (HyperC200), with the last two groups receiving oral curcumin daily for 3 weeks. The rats were fed a high-fat diet for 7 weeks to induce obesity. After anesthesia, hearts were removed and placed on the Langendorff perfusion system andbegan beating. After 20 minutes of stabilization, 35 minutes of ischemia and 60 minutes of nutrient fluid reflux were performed. During this interval, ventricular (LV) functional indices including LVSP, LVDP, LVEDP and +dp/dt were recorded. The relative size of the infarction was measured by using 2,3,5-triphenyltetrazolium chloride staining. Results: Hyperlipidemia caused dysfunction with changes in ventricular parameters, but curcumin could to improve some LV contractile parameters such as systolic pressure and increase diastolic pressure (P≤0.05). Curcumin could not significantly reduce the infarct size. Conclusion: Curcumin may have an cardio protection effects against ischemia/reperfusion injury in normal and hyperlipidemic rats

The effect of metformin therapy on serum thyrotropin and free thyroxine concentrations in patients with type 2 diabetes: a meta-analysis

Abstract Type 2 diabetes and thyroid function disorders are two common chronic endocrine disorders with the high prevalence in various populations. Metformin is well established as the first-line drug therapy for managing diabetes mellitus. In this meta-analysis, we aimed to determine the effect of metformin on serum TSH and FT4 concentrations in patients with type 2 diabetes. We searched PubMed, Scopus, web of science, Cochrane library, and google scholar to collect information on the effect of metformin on serum TSH and FT4 levels. Demographic and clinical information and serum TSH and FT4 concentrations before and after metformin treatment were extracted. Studies on patients over 18 years of age were included. A total of 11 studies including 1147 patients were selected for the final analysis. In hypothyroid patients, the TSH level decreased significantly after treatment with metformin (Hedges’s g:1.55, 95%CI 0.93–2.16, p-value < 0.001); FT4 level increased slightly after taking metformin, but the increase was not significant (Heddges’s g: − 0.30, 95%CI  − 0.90,0.31, p-value = 0.34). In euthyroid subjects, the slight decrease found in TSH and FT4 concentrations was not statistically significant. Metformin reduces TSH levels in hypothyroid patients; however, it has no effect on TSH levels in euthyroid patients. Metformin does not affect serum FT4 levels in euthyroid and hypothyroid patients

The value of machine learning for prognosis prediction of diphenhydramine exposure: National analysis of 50,000 patients in the United States

Background: Diphenhydramine (DPH) is an antihistamine medication that in overdose can result in anticholinergic symptoms and serious complications, including arrhythmia and coma. We aimed to compare the value of various machine learning (ML) models, including light gradient boosting machine (LGBM), logistic regression (LR), and random forest (RF), in the outcome prediction of DPH poisoning. Materials and Methods: We used the National Poison Data System database and included all of the human exposures of DPH from January 01, 2017 to December 31, 2017, and excluded those cases with missing information, duplicated cases, and those who reported co-ingestion. Data were split into training and test datasets, and three ML models were compared. We developed confusion matrices for each, and standard performance metrics were calculated. Results: Our study population included 53,761 patients with DPH exposure. The most common reasons for exposure, outcome, chronicity of exposure, and formulation were captured. Our results showed that the average precision-recall area under the curve (AUC) of 0.84. LGBM and RF had the highest performance (average AUC of 0.91), followed by LR (average AUC of 0.90). The specificity of the models was 87.0% in the testing groups. The precision of models was 75.0%. Recall (sensitivity) of models ranged between 73% and 75% with an F1 score of 75.0%. The overall accuracy of LGBM, LR, and RF models in the test dataset was 74.8%, 74.0%, and 75.1%, respectively. In total, just 1.1% of patients (mostly those with major outcomes) received physostigmine. Conclusion: Our study demonstrates the application of ML in the prediction of DPH poisoning

Blood lead concentration and its associated factors in preschool children in eastern Iran: a cross-sectional study

Background Lead is a toxic metal that affects almost every organ in the body. Children are more susceptible to lead toxicity because they ingest non-food items (pica), have oral exploratory habits, absorb more substantial amounts of ingested lead compared to adults, and have a developing central nervous system. This study describes venous blood lead concentrations (BLC) in young children living in Birjand, Iran. Methods A cross-sectional study was performed in 2016 on children 1-7 years of age who were referred to healthcare centers in Birjand City. Demographic information was obtained, and their BLC was tested using atomic absorption spectrometry (AAS). Results Four hundred children were tested. Their mean age was 52.37 +/- 23.77 months; their mean BLC was 2.49 +/- 2.64 mu g/dL (median 1.85 mu g/dL). Thirty-two (8%) children had a BLC > 5 mu g/dL. A logistic regression model revealed that per one unit of increase in age, the chance of an elevated BLC decreased by 3% (OR (95%CI): 0.97 (0.96-0.99),p < 0.01). The risks of an elevated BLC was 61% lower in girls compared to boys (OR (95%CI): 0.39 (0.17-0.92),p = 0.03). Further, per one rate of increase in the BMI, the chance of an elevated BLC was higher (OR (95%CI): 1.13 (1.02-1.24),p = 0.01). Children whose fathers were laborers had higher BLC than those with employee fathers (p = 0.01). Conclusion Of 400 children aged 1-7 years old living in Birjand, Iran, 8% had elevated BLC. BLC correlated with the child 's age, gender, body mass index, and father's occupation.Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Comparison of decision tree with common machine learning models for prediction of biguanide and sulfonylurea poisoning in the United States: an analysis of the National Poison Data System

Abstract Background Biguanides and sulfonylurea are two classes of anti-diabetic medications that have commonly been prescribed all around the world. Diagnosis of biguanide and sulfonylurea exposures is based on history taking and physical examination; thus, physicians might misdiagnose these two different clinical settings. We aimed to conduct a study to develop a model based on decision tree analysis to help physicians better diagnose these poisoning cases. Methods The National Poison Data System was used for this six-year retrospective cohort study.The decision tree model, common machine learning models multi layers perceptron, stochastic gradient descent (SGD), Adaboosting classiefier, linear support vector machine and ensembling methods including bagging, voting and stacking methods were used. The confusion matrix, precision, recall, specificity, f1-score, and accuracy were reported to evaluate the model’s performance. Results Of 6183 participants, 3336 patients (54.0%) were identified as biguanides exposures, and the remaining were those with sulfonylureas exposures. The decision tree model showed that the most important clinical findings defining biguanide and sulfonylurea exposures were hypoglycemia, abdominal pain, acidosis, diaphoresis, tremor, vomiting, diarrhea, age, and reasons for exposure. The specificity, precision, recall, f1-score, and accuracy of all models were greater than 86%, 89%, 88%, and 88%, respectively. The lowest values belong to SGD model. The decision tree model has a sensitivity (recall) of 93.3%, specificity of 92.8%, precision of 93.4%, f1_score of 93.3%, and accuracy of 93.3%. Conclusion Our results indicated that machine learning methods including decision tree and ensembling methods provide a precise prediction model to diagnose biguanides and sulfonylureas exposure

Epidemiological and clinical profiles of acute poisoning in patients admitted to the intensive care unit in eastern Iran (2010 to 2017)

Abstract Background Acute poisoning is a common chief complaint leading to emergency department visits and hospital admissions in developing countries such as Iran. Data describing the epidemiology of different poisonings, characteristics of the clinical presentations, and the predictors of outcome are lacking. Such data can help develop more efficient preventative and management strategies to decrease morbidity and mortality related to these poisonings. This manuscript describes the epidemiology of acute poisoning among patients admitted to the intensive care unit (ICU) in Birjand, Iran. Methods This retrospective, cross-sectional study was conducted to characterize acute poisonings managed in the ICU during a 7-year period from March 2010 to March 2017 in a single center in Birjand, Iran. Patient characteristics, suspected exposure, the route of exposure, and outcome data were collected from hospital medical records. Results During the study period, 267 (64% male and 36% female) patients met inclusion criteria. Pharmaceutical medication (36.6%), opioids (26.2%) followed by pesticides (13.9%) were the most common exposures 38.2% of these cases were identified as suicide attempts. There were different frequencies in terms of xenobiotic exposure in relation to gender (p = 0.04) and the survival (p = 0.001). There was a significant difference between various xenobiotics identified as the cause of poisoning (p = 0.001). Mortality rate in our study was 19.5%. The incidence of outcomes was significantly higher in patients poisoned with opioids, pesticides, benzodiazepines, and tricyclic antidepressants (p < 0.05). The median length of hospital stay was higher in pesticide-poisoned patients (p = 0.04). Conclusion Opioids and pesticides were the most common exposures. The mortality rate of the poisoned patients in the ICU was proportionately high. The mortality rate due to opioid poisoning is a major concern and the most significant cause death due to poisoning in the region. Further monitoring and characterization of acute poisoning in Birjand, Iran is needed. These data can help develop educational and preventative programs to reduce these exposures and improve management of exposures in the prehospital and hospital settings