Cinnamon and cognitive function: a systematic review of preclinical and clinical studies.

Cinnamon is the inner bark of trees named Cinnamomum. Studies have shown that cinnamon and its bioactive compounds can influence brain function and affect behavioral characteristics. This study aimed to systematically review studies about the relationship between cinnamon and its key components in memory and learning. Two thousand six hundred five studies were collected from different databases (PubMed, Scopus, Google Scholar, and Web of Science) in September 2021 and went under investigation for eligibility. As a result, 40 studies met our criteria and were included in this systematic review. Among the included studies, 33 were In vivo studies, five were In vitro, and two clinical studies were also accomplished. The main outcome of most studies (n = 40) proved that cinnamon significantly improves cognitive function (memory and learning). In vivo studies showed that using cinnamon or its components, such as eugenol, cinnamaldehyde, and cinnamic acid, could positively alter cognitive function. In vitro studies also showed that adding cinnamon or cinnamaldehyde to a cell medium can reduce tau aggregation, Amyloid ß and increase cell viability. For clinical studies, one study showed positive effects, and another reported no changes in cognitive function. Most studies reported that cinnamon might be useful for preventing and reducing cognitive function impairment. It can be used as an adjuvant in the treatment of related diseases. However, more studies need to be done on this subject.

Using a decision tree algorithm to distinguish between repeated supra-therapeutic and acute acetaminophen exposures.

BACKGROUND: This study aimed to compare clinical and laboratory characteristics of supra-therapeutic (RSTI) and acute acetaminophen exposures using a predictive decision tree (DT) algorithm. METHODS: We conducted a retrospective cohort study using the National Poison Data System (NPDS). All patients with RSTI acetaminophen exposure (n = 4,522) between January 2012 and December 2017 were included. Additionally, 4,522 randomly selected acute acetaminophen ingestion cases were included. After that, the DT machine learning algorithm was applied to differentiate acute acetaminophen exposure from supratherapeutic exposures. RESULTS: The DT model had accuracy, precision, recall, and F1-scores of 0.75, respectively. Age was the most relevant variable in predicting the type of acetaminophen exposure, whether RSTI or acute. Serum aminotransferase concentrations, abdominal pain, drowsiness/lethargy, and nausea/vomiting were the other most important factors distinguishing between RST and acute acetaminophen exposure. CONCLUSION: DT models can potentially aid in distinguishing between acute and RSTI of acetaminophen. Further validation is needed to assess the clinical utility of this model.

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.

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.

Outcome prediction of methadone poisoning in the United States: implications of machine learning in the National Poison Data System (NPDS).

Methadone is an opioid receptor agonist with a high potential for abuse. The current study aimed to compare different machine learning models to predict the outcomes following methadone poisoning. This six-year retrospective longitudinal study utilizes National Poison Data System (NPDS) data. The severity of outcomes was derived from the NPDS Coding Manual. Our database was divided into training (70%) and test (30%) sets. We used a light gradient boosting machine (LGBM), extreme gradient boosting (XGBoost), random forest (RF), and logistic regression (LR) to predict the outcomes of methadone poisoning. A total of 3847 patients with methadone exposures were included. Our results demonstrated that machine learning models conferred high accuracy and reliability in determining the outcomes of methadone poisoning cases. The performance evaluation showed all models had high accuracy, precision, specificity, recall, and F1-score values. All models could reach high specificity (more than 96%) and high precision (80% or more) for predicting major outcomes. The models could also achieve a high sensitivity to predict minor outcomes. Finally, the accuracy of all models was about 75%. However, XGBoost and LGBM models achieved the best performance among all models. This study showcased the accuracy and reliability of machine learning models in the outcome prediction of methadone poisoning.

Decision tree algorithm can determine the outcome of repeated supratherapeutic ingestion (RSTI) exposure to acetaminophen: review of 4500 national poison data system cases.

This study is aimed at establishing the outcome of RSTI exposure to acetaminophen based on a decision tree algorithm for the first time. This study used the National Poison Data System (NPDS) to conduct a six-year retrospective cohort analysis, which included 4522 individuals. The patients had a mean age of 26.75 ± 16.3 years (1-89). 3160 patients (70%) were females. Most patients had intentional exposure to acetaminophen. Almost all the patients had acetaminophen exposure via ingestion. In addition, 400 (8.8%) experienced major outcomes, 1500 (33.2%) experienced moderate outcomes, and 2622 (58%) of the patients experienced mild ones. The decision tree model performed well in the training and test groups. In the test group, the accuracy was 0.813, precision of 0.827, recall being 0.798, specificity 0.898, and an F1 score 0.80. In the training group, accuracy was 0.831, recall was 0.825, precision was 0.837, specificity was 0.90, and F1 score was 0.829. Our results showed that serum liver enzymes being present at elevated levels (Alanine aminotransferase (ALT), Aspartate aminotransferase (AST) greater than 1000 U/L followed by ALT, AST between 100 and 1000 U/L), prothrombin time (PT) prolongation, bilirubin increase, renal failure, confusion, age, hypotension, other coagulopathy (such as partial thromboplastin time (PTT) prolongation), acidosis, and electrolyte abnormality were the effective factors in determining the outcomes in these patients. The decision tree algorithm is a dependable method for establishing the prognosis of patients who have been exposed to RSTI acetaminophen and can be used throughout the patients' hospitalization period.

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.

How much natural ventilation rate can suppress COVID-19 transmission in occupancy zones?

Background: Previous research has emphasized the importance of efficient ventilation in suppressing COVID-19 transmission in indoor spaces, yet suitable ventilation rates have not been suggested. Materials and Methods: This study investigated the impacts of mechanical, natural, single-sided, cross-ventilation, and three mask types (homemade, surgical, N95) on COVID-19 spread across eight common indoor settings. Viral exposure was quantified using a mass balance calculation of inhaled viral particles, accounting for initial viral load, removal via ventilation, and mask filtration efficiency. Results: Results demonstrated that natural cross-ventilation significantly reduced viral load, decreasing from 10,000 to 0 viruses over 15 minutes in a 100 m2 space by providing ~1325 m3/h of outdoor air via two 0.6 m2 openings at 1.5 m/s wind speed. In contrast, single-sided ventilation only halved viral load at best. Conclusion: Natural cross-ventilation with masks effectively suppressed airborne viruses, lowering potential infections and disease transmission. The study recommends suitable ventilation rates to reduce COVID-19 infection risks in indoor spaces.

Distinguishing characteristics of exposure to biguanide and sulfonylurea anti-diabetic medications in the United States.

OBJECTIVES: Biguanides and sulfonylureas are anti-hyperglycemic drugs commonly used in the United States. Poisoning with these drugs may lead to serious consequences. The diagnosis of biguanide and sulfonylurea poisoning is based on history, clinical manifestations, and laboratory studies. METHODS: This study is a six-year retrospective cohort analysis based on the National Poison Data System. Clinical effects of 6183 biguanide and sulfonylurea exposures were identified using binary logistic regression. RESULTS: The mean age of patients with biguanide and sulfonylurea exposure was 39.27 ± 28.91 and 28.91 ± 30.41 years, respectively. Sulfonylurea exposure is most commonly seen via unintentional exposure, while biguanide exposure frequently occurs as a result of intentional ingestion. Minor and moderate outcomes commonly developed following biguanide and sulfonylurea exposure, respectively. Sulfonylurea exposure was less likely to develop clinical effects abdominal pain, metabolic acidosis, diarrhea, nausea, vomiting, and elevated creatinine than patients ingesting biguanides. However, sulfonylurea exposure was more likely to cause dizziness or vertigo, tremor, drowsiness or lethargy, agitation, diaphoresis, and hypoglycemia. CONCLUSIONS: Our study is the first to use a wide range of national data to describe the clinical characteristics that differentiate the toxicologic exposure to biguanides and sulfonylureas. Sulfonylurea exposure is commonly seen via unintentional exposure, while metformin exposure is frequently seen via intentional exposure. Sulfonylurea toxicity is more likely to cause agitation, dizziness or vertigo, tremor, diaphoresis, and hypoglycemia, while metformin exposure induces abdominal pain, acidosis, diarrhea, nausea, vomiting, and elevated creatinine.

Risk assessment of elevated blood lead concentrations in the adult population using a decision tree approach.

Lead is a common toxin which has detrimental effects on human health. Since lead poisoning is not associated with specific symptoms, diagnosing elevated blood lead concentration (EBLC) should be taken seriously. The purpose of this study was to propose a prediction model for EBLC based on demographic and clinical variables through a decision-tree model.In this cross-sectional study, 630 subjects (above 40 years old) living in South Khorasan Province, Iran in 2017 were selected via cluster random sampling method. From among the 630 participants who met the inclusion criteria, 70% (N = 456) were chosen randomly to achieve a set for developing the decision tree and multiple logistic regression (MLR). The other 30% (N = 174) were placed in a holdout sample to examine the function of the decision tree and MLR models. The predictive performance for various models was studied using the Receiver Operating Characteristic (ROC) curve.In the decision tree model, the parameters of hematocrit (HCT), White Blood Cell (WBC), Red Blood Cell (RBC), Mean corpuscular volume (MCV), creatinine concentration, abdominal pain, gender, route of administration, and history of cigarette smoking were the most critical factors in identifying people at risk of EBLC. The HCT concentration was the most critical variable, which was chosen as the root node of the tree. Based on the ROC curve, the decision tree model had better predictive accuracy than the logistic regression model.Our results indicated that the decision tree model offers far greater predictive precision than the logistic regression model. Doctors should pay more attention to some factors including the hematological parameters such as MCV, RBC, HCT, leukocytosis, creatinine levels, male sex, history of cigarette, and opium consumption for the screening of EBLCs.

A systematic review of clinical and laboratory findings of lead poisoning: lessons from case reports.

Lead is one of the most toxic heavy metals in the environment. The present review aimed to highlight hazardous pollution sources, management, and review symptoms of lead poisonings in various parts of the world. The present study summarized the information available from case reports and case series studies from 2009 to March 2020 on the lead pollution sources and clinical symptoms. All are along with detoxification methods in infants, children, and adults. Our literature compilation includes results from 126 studies on lead poisoning. We found that traditional medication, occupational exposure, and substance abuse are as common as previously reported sources of lead exposure for children and adults. Ayurvedic medications and gunshot wounds have been identified as the most common source of exposure in the United States. However, opium and occupational exposure to the batteries were primarily seen in Iran and India. Furthermore, neurological, gastrointestinal, and hematological disorders were the most frequently occurring symptoms in lead-poisoned patients. As for therapeutic strategies, our findings confirm the safety and efficacy of chelating agents, even for infants. Our results suggest that treatment with chelating agents combined with the prevention of environmental exposure may be an excellent strategy to reduce the rate of lead poisoning. Besides, more clinical studies and long-term follow-ups are necessary to address all questions about lead poisoning management.

The effects of naloxone, diazepam, and quercetin on seizure and sedation in acute on chronic tramadol administration: an experimental study.

BACKGROUND: Tramadol is a widely used synthetic opioid. Substantial research has previously focused on the neurological effects of this drug, while the efficacy of various treatments to reduce the associated side effects has not been well studied. This study aimed to evaluate the protective effects of naloxone, diazepam, and quercetin on tramadol overdose-induced seizure and sedation level in male rats. METHODS: The project was performed with 72 male Wistar rats with an average weight of 200-250 g. The rats were randomly assigned to eight groups. Tramadol was administered intraperitoneally at an initial dose of 25 mg/kg/day. On the 14th day, tramadol was injected at 75 mg/kg, either alone or together with naloxone, diazepam, and quercetin (acute and chronic) individually or in combination. The rats were monitored for 6 h on the last day, and the number, the duration, and the severity of seizures (using the criteria of Racine) were measured over a 6-h observation period. The sedation level was also assessed based on a 4-point criterion, ranging from 0 to 3. Data were analyzed in SPSS software using Kruskal-Wallis, Chi-square, regression analysis, and generalized estimating equation (GEE) tests. The significance level was set at P < 0.05. RESULTS: The naloxone-diazepam combination reduced the number, severity, and cumulative duration of seizures compared to tramadol use alone and reduced the number of higher-intensity seizures (level 3, 4) to a greater extent than other treatments. Naloxone alone reduced the number and duration of seizures but increased the number of mild seizures (level 2). Diazepam decreased the severity and duration of seizures. However, it increased the number of mild seizures (level 2). In comparison with the tramadol alone group, the acute quercetin group exhibited higher numbers of mild (level 2) and moderate (level 3) seizures. Chronic quercetin administration significantly increased the number of mild seizures. In the GEE model, all groups had higher sedation levels than the saline only group (P < 0.001). None of the protocols had a significant effect on sedation levels compared to the tramadol group. CONCLUSION: The combined administration of naloxone and diazepam in acute-on-chronic tramadol poisoning can effectively reduce most seizure variables compared to tramadol use alone. However, none of the treatments improved sedation levels.

Effects of naloxone and diazepam on blood glucose levels in tramadol overdose using generalized estimating equation (GEE) model; (an experimental study).

BACKGROUND: Tramadol is a synthetic opioid and poisoning is increasing around the world day by day. Various treatments are applied for tramadol poisoning. Due to the unknown effects of tramadol poisoning and some of its treatments on blood glucose levels, this study was conducted to investigate the overdose of tramadol and its common treatments (naloxone, diazepam), and their combination on blood glucose levels in male rats. METHODS: This study was conducted in 45 male Wistar rats. The animals were randomly divided into five groups of 9. They received a 75 mg/kg dose of tramadol alone with naloxone, diazepam, and a combination of both of these two drugs. On the last day, animals' tail vein blood glucose levels (BGL) were measured using a glucometer at different times, including before the tramadol injection (baseline) and 1 hour, 3 hours, and 6 hours after wards. The rats were anesthetized and sacrificed 24 h after the last injection. Blood samples were then taken, and the serum obtained was used to verify the fasting glucose concentration. Data were analyzed using SPSS software at a significance level of 0.05 using a one-way analysis of variance (ANOVA) and a generalized estimating equation (GEE). RESULTS: According to the GEE model results, the diazepam-tramadol and naloxone-diazepam-tramadol groups showed blood glucose levels five units higher than the tramadol group (p < 0.05). The diazepam-tramadol group had significantly higher blood glucose levels than the naloxone-tramadol group (p < 0.05). The mean blood glucose levels before the intervention, 3 hours and 6 hours after the injection of tramadol did not differ between the groups, but the blood glucose levels 1 hour after the injection of tramadol in the group of naloxone-tramadol were significantly lower than in the control group (p < 0.05). Blood glucose levels did not differ between the groups 24 h after injection of tramadol. CONCLUSION: The results of the present study showed tramadol overdose does not affect blood glucose levels. The diazepam-tramadol combination and the diazepam-naloxone-tramadol combination caused an increase in blood glucose levels.

Opium use and cardiovascular diseases: a systematic review and meta-analysis.

The effects of opium on cardiovascular diseases (CVDs) have been extensively studied. However, there are few studies that summarize this research comprehensively; thus, this systematic review and meta-analysis is a collection of the newest information combined with previous findings to furthermore illuminate the effects of opium on CVDs. In this systematic review, all observational studies were systematically searched using the main international databases such as PubMed/Medline, Web of Sciences, and Scopus until October 2018. After the quality assessment of the articles, the fixed or random model meta-analysis was used to pool the results. I-square test was used to assess the heterogeneity of the studies. Overall, 41 studies were identified. Based on the random model, the pooled odds ratio (OR) (95% confidence interval (CI)) of opium use and coronary artery diseases (CAD) was estimated at 2.75 (95% CI = 2.04-3.75; I2=47%). The pooled OR of opium use and CVD in-hospital mortality was not statistically significant (OR: 1.44, 95% CI = 0.88-2.36, I2 = 51%). In the stratified analysis, in the patients who had undergone heart surgery, the average of ejection fraction (EF) in the opium users was significantly lower than those not using opium (mean differences: -3.06, CI 95% = -4.40 to -1.71, I2 = 60%) but in the patients with acute myocardial infarction undergoing angiography, the average EF was not significantly different in the opium users compared to non-users (mean difference: 0.30, CI: -0. 55 to 1.15). The results of this meta-analysis revealed that opium might be a risk factor for CAD and EF but not in-hospital mortality.

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 µg/dL (median 1.85 µg/dL). Thirty-two (8%) children had a BLC > 5 µg/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.

Effects of bentonite nanoparticles inhalation on lung tissue and blood antioxidant indices in a rat model.

Bentonite is an inorganic clay material that is often easily dispersed as fine particles by air and water circulation, and most people are exposed to different concentrations of bentonite particles. Therefore, the inhaled effects of bentonite nanoparticles (BNPs) were studied in Wistar rats. Seventy-five rats were divided into five groups of 15: four exposure groups (0.1, 0.5, 2, and 10 mg/m3 of BNPs) and one control group. The rats were exposed for 30, 60, and 90 days to BNPs for 5 days a week (6 h/day) in whole-body inhalation chambers. Blood samples were collected to measure the levels of antioxidant activity of the contents such as total antioxidant capacity (TAC) and malondialdehyde (MDA). X-ray diffraction and scanning electron microscopy were used to identify nanoparticles. The results showed no significant difference in the effect of nanoparticles on levels of TAC and MDA in the studied groups based on the concentrations of nanoparticles. However, the level of MDA increased significantly with extending exposure time; there was a significant increase in the level of MDA content 90 days postexposure compared to 30 days postexposure at concentrations of 0.5, 2, and 10 mg/m3. Histopathological examination showed that inhalation exposure of rats to BNPs led to different histopathologic responses in the lung tissue, such as inflammatory infiltration, granulomatous inflammation, acute neutrophilic reaction in the early stages, and lung fibrosis. At the lowest concentration, BNPs have low or no toxicity, and inhalation of these nanoparticles at low concentrations does not affect the levels of MDA and TAC content. However, increased concentration and exposure time caused correspondingly greater increases in MDA and more damage to lung tissue.

Organophosphorus Compounds and MAPK Signaling Pathways.

The molecular signaling pathways that lead to cell survival/death after exposure to organophosphate compounds (OPCs) are not yet fully understood. Mitogen-activated protein kinases (MAPKs) including the extracellular signal-regulated protein kinase (ERK), the c-Jun NH2-terminal kinase (JNK), and the p38-MAPK play the leading roles in the transmission of extracellular signals into the cell nucleus, leading to cell differentiation, cell growth, and apoptosis. Moreover, exposure to OPCs induces ERK, JNK, and p38-MAPK activation, which leads to oxidative stress and apoptosis in various tissues. However, the activation of MAPK signaling pathways may differ depending on the type of OPCs and the type of cell exposed. Finally, different cell responses can be induced by different types of MAPK signaling pathways after exposure to OPCs.

Tramadol and the occurrence of seizures: a systematic review and meta-analysis.

Introduction: Tramadol is a synthetic opioid which is commonly used around the world to relieve moderate to severe pain. One of the serious possible complications of its use is seizures. The present study aims to investigate and summarize the studies related to tramadol and occurrences of seizures after tramadol use and factors influencing these seizures.Methodology: Our systematic review is compliant with PRISMA guidelines. Two researchers systematically searched PubMed/Medline, Web of Sciences, and Scopus. Cohort, case-control, cross-sectional studies, and clinical trials. The risk of bias was assessed using the Newcastle-Ottawa Scale After article quality assessment, a fixed or random model, as appropriate, was used to pool the results in a meta-analysis. Heterogeneity between the studies was assessed with using I-square and Q-test. Forest plots demonstrating the point and pooled estimates were drawn.Results: A total of 51 articles with total sample size of 101 770 patients were included. The results showed that seizure event rate in the subgroups of tramadol poisoning, therapeutic dosage of tramadol, and tramadol abusers was 38% (95% CI: 27-49%), 3% (95% CI: 2-3%), 37% (95% CI: 12-62%), respectively. Tramadol dose was significantly higher in the patients with seizures than those without (mean differences: 0.82, CI 95%: 0.17-1.46). The odds for occurrence of seizures were significantly associated with male gender (pooled OR: 2.24, CI 95%: 1.80-2.77). Naloxone administration was not associated to the occurrence of seizures (pooled OR: 0.47, 95% CI: 0.15-1.49).Conclusions: Our results demonstrate that the occurrence of seizures in patients exposed to tramadol are dose-dependent and related to male gender, but not related to naloxone administration. Given that, most of the evidence derives from studies utilizing a cross-sectional design, the association of tramadol with seizures should not be considered to be definitively established.

Prevention of kidney cell damage in hyperglycaemia condition by adiponectin.

Adiponectin (APN) is an adipocytokine, secreted from adipose tissue and has anti-inflammatory, anti-ageing, and antidiabetic properties. Hyperglycaemia can damage the renal cells, and mammalian target of rapamycin (mTOR), along with Sirtuin 1 (SIRT1), have an important role in kidney cell response to hyperglycaemia. Therefore, understanding the relationship between adiponectin, mTOR, and SIRT1 proteins is beneficial for deciphering the mechanism of adiponectin function. In this study, Human Embryonic Kidney-293 (HEK-293) cells were cultured under normal and high-glucose condition, with and without APN (1, 10, and 100 ng/mL) for 48 hours. mTOR protein expression was evaluated by western blot analysis, and SIRT1 protein was assessed using ELISA method. To evaluate hyperglycaemia-mediated cytotoxicity, cell viability was determined using MTT assay. Data showed that APN in high dose (100 ng/mL) significantly reduced the expression of mTOR and p-mTOR, increased SIRT1 protein, and also improved cell viability compared with the control high glucose (p ≤ 0.05). According to this results, APN can be useful in preventing renal cell damage, by affecting on the expression of mTOR and SIRT1 proteins, as well as increasing the survival of kidney cells in hyperglycaemia conditions. SIGNIFICANCE OF THE STUDY: Adiponectin triggered mTOR/p-mTOR/SIRT1 pathway and decreased cell death in human kidney cells. Our findings provide preliminary experimental data that support further studies on the potential therapeutic role of adiponectin in diabetes and diabetic-induced metabolic complications.

Increasing the Risk of Stroke by Opium Addiction.

INTRODUCTION: Stroke is among the leading causes of mortality and morbidity in the world. Besides the identified risk factor, Ischemic stroke evidence show drug use develops or exacerbates the atherosclerotic process. The current study aimed at comparing cerebrovascular ultrasounds' changes in addicted and nonaddicted people who developed ischemic stroke. METHODS: In the current cross-sectional study, a total of 133 patients with ischemic stroke who were admitted to Vali-Asr hospital from June 2016 to April 2017 were enrolled. For obtaining the quantitative data, t test or Mann-Whitney test was employed to compare the addict or no-addict groups, as well as, categorical data testing was performed using chi-square test. Also, the multiple logistic regression was used for identifying the factors and the significance level was set at 5%. RESULTS: The current study was performed on 133 patients, among them 41 patients (30.8%) were opium addicted, and 92 patients (69.2%) were nonaddict. The mean [IQR] number of atherosclerotic plaques were significantly higher in opium addicted group in comparison with the nonaddicted group (3.0 [1.0-4.0] versus 1.5 [0.0-3.0], P = .008). The possibility of increasing the number of plaques in addicted patients was 1.42 times higher than the nonaddicted patients (odds ratio (95% confidence interval): 1.42 (1.11-1.81), P = .005). CONCLUSION: The findings demonstrated a significant difference in the vessel stenosis pattern between the addict and nonaddict ischemic stroke groups. To investigate the possible effects of opium use and its associated parameters, ie, dosage, duration of use, and the way of opium use on ischemic stroke, further studies are required.

The reference value of blood lead level among the general adult population of eastern Iran.

The aim of this study to the estimate the lead concentrations in the blood of the adult population in South Khorasan Province, evaluate factors related to high lead blood concentrations and establish lead reference values (RVs) in our study population. In cross-sectional study, 400 people who lived in the province of South Khorasan in 2017 were selected. Demographic information was collected and clinical examinations were performed. As the geometric means, blood lead concentration (BLC) was expressed, 10th, 50th, 90th, and 95th percentiles, and 95% confidence intervals (CI) of the 95th percentile. The upper limits rounded values of the 95% CI with the 95th percentile were applied to calculate RVs. Mean BLC was 6.02 ± 7.41 µg dL-1, median of BLC was 4.4 µg dL-1 (IQR: 2.9-6.5; range 0.9-54.7 µg dL-1). One hundred and twenty-five (31.2%) participants had BLCs between 5 and 10.0 µg dL-1, 40 (10.0%) between 10 and 20.0 µg dL-1, and 15 (3.8%%) over 20 µg dL-1. The RVs for BLC for men and women were 16 [95% CI: 10.13-15.96] µg dL-1 and 15 [95% CI: 9.81-14.45] µg dL-1, respectively. Higher BLCs were significantly associated with age, gender, hemoglobin, white blood cell count, and serum phosphorus concentration. This bio-monitoring study of BLCs in the general population of South Khorasan Province offers important demographic and lifestyle factors-stratified reference data. It is essential to continue efforts to reduce lead exposure.