Lipopolysaccharide induces acute lung injury and alveolar haemorrhage in association with the cytokine storm, coagulopathy and AT1R/JAK/STAT augmentation in a rat model that mimics moderate and severe Covid-19 pathology.

Progress in the study of Covid-19 disease in rodents has been hampered by the lack of angiotensin-converting enzyme 2 (ACE2; virus entry route to the target cell) affinities for the virus spike proteins across species. Therefore, we sought to determine whether a modified protocol of lipopolysaccharide (LPS)-induced acute respiratory distress syndrome in rats can mimic both cell signalling pathways as well as severe disease phenotypes of Covid-19 disease. Rats were injected via intratracheal (IT) instillation with either 15 mg/kg of LPS (model group) or saline (control group) before being killed after 3 days. A severe acute respiratory syndrome (SARS)-like effect was observed in the model group as demonstrated by the development of a "cytokine storm" (>2.7 fold increase in blood levels of IL-6, IL-17A, GM-CSF, and TNF-α), high blood ferritin, demonstrable coagulopathy, including elevated D-dimer (approximately 10-fold increase), PAI-1, PT, and APTT (p < 0.0001). In addition, LPS increased the expression of lung angiotensin II type I receptor (AT1R)-JAK-STAT axis (>4 fold increase). Chest imaging revealed bilateral small patchy opacities of the lungs. Severe lung injury was noted by the presence of both, alveolar collapse and haemorrhage, desquamation of epithelial cells in the airway lumen, infiltration of inflammatory cells (CD45+ leukocytes), widespread thickening of the interalveolar septa, and ultrastructural alterations similar to Covid-19. Thus, these findings demonstrate that IT injection of 15 mg/kg LPS into rats, induced an AT1R/JAK/STAT-mediated cytokine storm with resultant pneumonia and coagulopathy that was commensurate with moderate and severe Covid-19 disease noted in humans.

Resveratrol Pretreatment Ameliorates p53-Bax Axis and Augments the Survival Biomarker B-Cell Lymphoma 2 Modulated by Paracetamol Overdose in a Rat Model of Acute Liver Injury.

BACKGROUND: The potential protective effects of resveratrol (RES) on the modulation of hepatic biomarkers of apoptosis and survival, p53-Bax axis, and B-cell lymphoma 2 (Bcl-2) in an animal model of paracetamol-induced acute liver injury have not been investigated before. METHODS: The model group of rats received a single dose of paracetamol (2 g/kg, orally), whereas the protective group of rats were pretreated for 7 days with RES (30 mg/kg, i.p.) before they were given a single dose of paracetamol. All rats were then sacrificed 24-h post paracetamol ingestion. RESULTS: Histology images showed that paracetamol overdose induced acute liver injury, which was substantially protected by RES. Paracetamol significantly (p < 0.05) modulated p53, apoptosis regulator Bax, Bcl-2, tumor necrosis factor-alpha, interleukin-6, inducible nitric oxide synthase, malondialdehyde, superoxide dismutase, glutathione peroxidase, alanine aminotransferase, and aspartate aminotransferase, which were significantly protected by RES. We further demonstrated a significant (p< 0.01) correlation between either p53 or Bcl-2 scoring and the levels of inflammatory, nitrosative stress, and liver injury biomarkers. CONCLUSION: We demonstrate a substantial protection by RES pretreatment against paracetamol-induced modulation of p53-Bax axis, Bcl-2, and other acute liver injury biomarkers in rats.

Metformin inhibits mTOR-HIF-1α axis and profibrogenic and inflammatory biomarkers in thioacetamide-induced hepatic tissue alterations.

The potential inhibitory effect of the antidiabetic and anti-inflammatory drug, metformin on thioacetamide (TAA)-induced hepatotoxicity associated with the inhibition of mammalian target of rapamycin (mTOR)-hypoxia-inducible factor-1α (HIF-1α) axis has not been investigated before. Therefore, we tested whether metformin can protect against liver injuries including fibrosis induced by TAA possibly via the downregulation of mTOR-HIF-1α axis and profibrogenic and inflammatory biomarkers. Rats either injected with TAA (200 mg/kg; twice a week for 8 weeks) before being killed after 10 weeks (model group) or were pretreated with metformin (200 mg/kg) daily for 2 weeks before TAA injections and continued receiving both agents until the end of the experiment, at Week 10 (protective group). Using light and electron microscopy examinations, we observed in the model group substantial damage to the hepatocytes and liver tissue such as collagen deposition, infiltration of inflammatory cells, and degenerative cellular changes with ballooned mitochondria that were substantially ameliorated by metformin. Metformin also significantly ( p < 0.05) inhibited TAA-induced HIF-1α, mTOR, the profibrogenic biomarker α-smooth muscle actin, tissue inhibitor of metalloproteinases-1, tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6), alanine aminotransferase (ALT) and aspartate aminotransferase in harvested liver homogenates and blood samples. In addition, a significant ( p < 0.01) positive correlation between hypoxia scoring (HIF-1α) and the serum levels of TNF-α ( r = 0.797), IL-6 ( r = 0.859), and ALT ( r = 0.760) was observed. We conclude that metformin protects against TAA-induced hepatic injuries in rats, which is associated with the inhibition of mTOR-HIF-1α axis and profibrogenic and inflammatory biomarkers; thus, may offer therapeutic potential in humans.

Cardioprotective effect of ghrelin against myocardial infarction-induced left ventricular injury via inhibition of SOCS3 and activation of JAK2/STAT3 signaling.

The molecular mechanisms through which ghrelin exerts its cardioprotective effects during cardiac remodeling post-myocardial infarction (MI) are poorly understood. The aim of this study was to investigate whether the cardioprotection mechanisms are mediated by modulation of JAK/STAT signaling and what triggers this modulation. Rats were divided into six groups (n = 12/group): control, sham, sham + ghrelin (100 µg/kg, s.c., daily, starting 1 day post-MI), MI, MI+ ghrelin, and MI+ ghrelin+ AG490, a potent JAK2 inhibitor (5 mg/kg, i.p., daily). All treatments were administered for 3 weeks. Administration of ghrelin to MI rats improved left ventricle (LV) architecture and restored cardiac contraction. In remote non-infarcted areas of MI rats, ghrelin reduced cardiac inflammation and lipid peroxidation and enhanced antioxidant enzymatic activity. In addition, independent of the growth factor/insulin growth factor-1 (GF/IGF-1) axis, ghrelin significantly increased the phosphorylation of JAK2 and Tyr702 and Ser727 residues of STAT3 and inhibited the phosphorylation of JAK1 and Tyr701 and Ser727 residues of STAT1, simultaneously increasing the expression of BCL-2 and decreasing in the expression of BAX, cleaved CASP3, and FAS. This effect coincided with decreased expression of SOCS3. All these beneficial effects of ghrelin, except its inhibitory action on IL-6 expression, were partially and significantly abolished by the co-administration of AG490. In conclusion, the cardioprotective effect of ghrelin against MI-induced LV injury is exerted via activation of JAK2/STAT3 signaling and inhibition of STAT1 signaling. These effects were independent of the GF/IGF-1 axis and could be partially mediated via inhibition of cardiac IL-6.

Acylated ghrelin protects aorta damage post-MI via activation of eNOS and inhibition of angiotensin-converting enzyme induced activation of NAD(P)H-dependent oxidase.

NAD(P)H dependent oxidase derived-reactive oxygen species (ROS) due to activation of the renin-angiotensin-aldosterone system (RAAS) in blood vessels postmyocardial infarction MI or during the HF leads to endothelium dysfunction and enhanced apoptosis. Acylated ghrelin (AG) is a well-reported cardioprotective and antiapoptotic agent for the heart. AG receptors are widely distributed in most of blood vessels, suggesting a role in the regulation of endothelial function and survival. This study investigated if AG can protect aorta of rats' postmyocardial infarction (MI)-induced damage and endothelial dysfunction. Adult male rats were divided into four groups of (1) Sham, (2) Sham + AG, (3) MI, and (4) MI + AG. Vehicle (normal saline) or AG (100 µ/kg) was administered to rats for 21 consecutive days, after which, numerous biochemical markers were detected by blot. Both histological and electron microscope studies were carried on aortic samples from MI-induced rats. AG increased protein levels of both total and phosphorylated forms of endothelial nitric oxide synthase (eNOS and p-eNOS, respectively). Only in MI-treated rats, AG prevented the decreases in the levels of reduced glutathione (GSH) and superoxide dismutase (SOD) and lowered levels of malondialdehyde (MDA) and glutathione disulfide (GSSG). Concomitantly, it lowered the increased protein levels of angiotensin-converting enzyme (ACE), p22phox and cleaved caspase-3 and prevented the aorta histological and ultrustructural abnormalities induced by MI.

Exercise protects against insulin-dependent diabetes-induced osteoarthritis in rats: A scanning electron microscopy study.

We tested the hypothesis that swim exercise can protect the articular cartilage from damages induced secondary to insulin-dependent diabetes mellitus in rats using the scanning electron microscopy and to monitor the blood levels of oxidative and antioxidative stress biomarkers that are known to be modulated in osteoarthritis (OA). A profound damage to the cartilage was observed in the diabetic rats. Our findings also show that swim exercise protects the knee joints from damage induced by diabetes as well as significantly inhibiting OA-induced upregulation of thiobarbituric acid reactive substances (TBARS) and tumor necrosis factor alpha (TNF-α) and augmented superoxide dismutase (SOD) inhibition by OA. Thus, we demonstrated an effective protection by swim exercise against diabetes-induced OA in a rat model of the disease.

Preventive roles of swimming exercise and pioglitazone treatment on hepatic dysfunction in a rat model of metabolic syndrome.

Pioglitazone (Pio) and swimming exercise (SE) are insulin sensitisers. This investigation was suggested because of the significant side effects associated with Pio treatment in metabolic syndrome (MetS). This study was, therefore, designed to investigate the preventive role of Pio treatment and SE in terms of efficiency and pathological changes in MetS in a rat model. Sixty male Sprague-Dawley rats were distributed equally among 6 groups: (i) control group (C), (ii) exercised control group (C+E), (iii) Pio-treated control group (C+Pio), (iv) group with MetS, (v) group with MetS treated with Pio (MetS+Pio), and (vi) exercised MetS group (MetS+E). Systolic blood pressure and heart rate were measured at the end of the experiments (16 weeks). Retro-orbital blood samples were used to determine the serum levels of glucose, insulin, lipids, gamma glutamyl transferase, alanine transaminase, aspartate transaminase, alkaline phosphatase, fetuin-A, and adiponectin. Semiquantitative reverse transcriptase - PCR insulin gene expression assays and hepatic histopathological examination were conducted. Swimming exercise significantly improved all of the aforementioned parameters, more so than the Pio treatment. In particular, the serum hepatic enzyme levels and hepatic histopathological changes were improved compared with the MetS group. These results suggested that swimming exercise might be an alternative physiological preventive tool against hepatic dysfunction to avoid the side effects associated with Pio treatment, and this could be demonstrated in a rat model of metabolic syndrome.

Pilot-Study to Explore Metabolic Signature of Type 2 Diabetes: A Pipeline of Tree-Based Machine Learning and Bioinformatics Techniques for Biomarkers Discovery.

BACKGROUND: This study aims to identify unique metabolomics biomarkers associated with Type 2 Diabetes (T2D) and develop an accurate diagnostics model using tree-based machine learning (ML) algorithms integrated with bioinformatics techniques. METHODS: Univariate and multivariate analyses such as fold change, a receiver operating characteristic curve (ROC), and Partial Least-Squares Discriminant Analysis (PLS-DA) were used to identify biomarker metabolites that showed significant concentration in T2D patients. Three tree-based algorithms [eXtreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (LightGBM), and Adaptive Boosting (AdaBoost)] that demonstrated robustness in high-dimensional data analysis were used to create a diagnostic model for T2D. RESULTS: As a result of the biomarker discovery process validated with three different approaches, Pyruvate, D-Rhamnose, AMP, pipecolate, Tetradecenoic acid, Tetradecanoic acid, Dodecanediothioic acid, Prostaglandin E3/D3 (isobars), ADP and Hexadecenoic acid were determined as potential biomarkers for T2D. Our results showed that the XGBoost model [accuracy = 0.831, F1-score = 0.845, sensitivity = 0.882, specificity = 0.774, positive predictive value (PPV) = 0.811, negative-PV (NPV) = 0.857 and Area under the ROC curve (AUC) = 0.887] had the slight highest performance measures. CONCLUSIONS: ML integrated with bioinformatics techniques offers accurate and positive T2D candidate biomarker discovery. The XGBoost model can successfully distinguish T2D based on metabolites.

Combining the Strengths of the Explainable Boosting Machine and Metabolomics Approaches for Biomarker Discovery in Acute Myocardial Infarction.

Acute Myocardial Infarction (AMI), a common disease that can have serious consequences, occurs when myocardial blood flow stops due to occlusion of the coronary artery. Early and accurate prediction of AMI is critical for rapid prognosis and improved patient outcomes. Metabolomics, the study of small molecules within biological systems, is an effective tool used to discover biomarkers associated with many diseases. This study intended to construct a predictive model for AMI utilizing metabolomics data and an explainable machine learning approach called Explainable Boosting Machines (EBM). The EBM model was trained on a dataset of 102 prognostic metabolites gathered from 99 individuals, including 34 healthy controls and 65 AMI patients. After a comprehensive data preprocessing, 21 metabolites were determined as the candidate predictors to predict AMI. The EBM model displayed satisfactory performance in predicting AMI, with various classification performance metrics. The model's predictions were based on the combined effects of individual metabolites and their interactions. In this context, the results obtained in two different EBM modeling, including both only individual metabolite features and their interaction effects, were discussed. The most important predictors included creatinine, nicotinamide, and isocitrate. These metabolites are involved in different biological activities, such as energy metabolism, DNA repair, and cellular signaling. The results demonstrate the potential of the combination of metabolomics and the EBM model in constructing reliable and interpretable prediction outputs for AMI. The discussed metabolite biomarkers may assist in early diagnosis, risk assessment, and personalized treatment methods for AMI patients. This study successfully developed a pipeline incorporating extensive data preprocessing and the EBM model to identify potential metabolite biomarkers for predicting AMI. The EBM model, with its ability to incorporate interaction terms, demonstrated satisfactory classification performance and revealed significant metabolite interactions that could be valuable in assessing AMI risk. However, the results obtained from this study should be validated with studies to be carried out in larger and well-defined samples.

Metabolomics Biomarker Discovery to Optimize Hepatocellular Carcinoma Diagnosis: Methodology Integrating AutoML and Explainable Artificial Intelligence.

Background: This study aims to assess the efficacy of combining automated machine learning (AutoML) and explainable artificial intelligence (XAI) in identifying metabolomic biomarkers that can differentiate between hepatocellular carcinoma (HCC) and liver cirrhosis in patients with hepatitis C virus (HCV) infection. Methods: We investigated publicly accessible data encompassing HCC patients and cirrhotic controls. The TPOT tool, which is an AutoML tool, was used to optimize the preparation of features and data, as well as to select the most suitable machine learning model. The TreeSHAP approach, which is a type of XAI, was used to interpret the model by assessing each metabolite's individual contribution to the categorization process. Results: TPOT had superior performance in distinguishing between HCC and cirrhosis compared to other AutoML approaches AutoSKlearn and H2O AutoML, in addition to traditional machine learning models such as random forest, support vector machine, and k-nearest neighbor. The TPOT technique attained an AUC value of 0.81, showcasing superior accuracy, sensitivity, and specificity in comparison to the other models. Key metabolites, including L-valine, glycine, and DL-isoleucine, were identified as essential by TPOT and subsequently verified by TreeSHAP analysis. TreeSHAP provided a comprehensive explanation of the contribution of these metabolites to the model's predictions, thereby increasing the interpretability and dependability of the results. This thorough assessment highlights the strength and reliability of the AutoML framework in the development of clinical biomarkers. Conclusions: This study shows that AutoML and XAI can be used together to create metabolomic biomarkers that are specific to HCC. The exceptional performance of TPOT in comparison to traditional models highlights its capacity to identify biomarkers. Furthermore, TreeSHAP boosted model transparency by highlighting the relevance of certain metabolites. This comprehensive method has the potential to enhance the identification of biomarkers and generate precise, easily understandable, AI-driven solutions for diagnosing HCC.

Platelet Metabolites as Candidate Biomarkers in Sepsis Diagnosis and Management Using the Proposed Explainable Artificial Intelligence Approach.

Background: Sepsis is characterized by an atypical immune response to infection and is a dangerous health problem leading to significant mortality. Current diagnostic methods exhibit insufficient sensitivity and specificity and require the discovery of precise biomarkers for the early diagnosis and treatment of sepsis. Platelets, known for their hemostatic abilities, also play an important role in immunological responses. This study aims to develop a model integrating machine learning and explainable artificial intelligence (XAI) to identify novel platelet metabolomics markers of sepsis. Methods: A total of 39 participants, 25 diagnosed with sepsis and 14 control subjects, were included in the study. The profiles of platelet metabolites were analyzed using quantitative 1H-nuclear magnetic resonance (NMR) technology. Data were processed using the synthetic minority oversampling method (SMOTE)-Tomek to address the issue of class imbalance. In addition, missing data were filled using a technique based on random forests. Three machine learning models, namely extreme gradient boosting (XGBoost), light gradient boosting machine (LightGBM), and kernel tree boosting (KTBoost), were used for sepsis prediction. The models were validated using cross-validation. Clinical annotations of the optimal sepsis prediction model were analyzed using SHapley Additive exPlanations (SHAP), an XAI technique. Results: The results showed that the KTBoost model (0.900 accuracy and 0.943 AUC) achieved better performance than the other models in sepsis diagnosis. SHAP results revealed that metabolites such as carnitine, glutamate, and myo-inositol are important biomarkers in sepsis prediction and intuitively explained the prediction decisions of the model. Conclusion: Platelet metabolites identified by the KTBoost model and XAI have significant potential for the early diagnosis and monitoring of sepsis and improving patient outcomes.

Vanillylacetone attenuates cadmium chloride-induced hippocampal damage and memory loss through up-regulation of nuclear factor erythroid 2-related factor 2 gene and protein expression.

JOURNAL/nrgr/04.03/01300535-202412000-00030/figure1/v/2024-04-08T165401Z/r/image-tiff Memory loss and dementia are major public health concerns with a substantial economic burden. Oxidative stress has been shown to play a crucial role in the pathophysiology of hippocampal damage-induced memory impairment. To investigate whether the antioxidant and anti-inflammatory compound vanillylacetone (zingerone) can protect against hippocampal damage and memory loss induced by cadmium chloride (CdCl2) administration in rats, we explored the potential involvement of the nuclear factor erythroid 2-related factor 2 (Nrf2) signaling pathway, which is known to modulate oxidative stress and inflammation. Sixty healthy male Wistar rats were divided into five groups: vehicle-treated (control), vanillylacetone, CdCl2, vanillylacetone + CdCl2, vanillylacetone + CdCl2 + brusatol (a selective pharmacological Nrf2 inhibitor) groups. Vanillylacetone effectively attenuated CdCl2-induced damage in the dental gyrus of the hippocampus and improved the memory function assessed by the Morris Water Maze test. Additionally, vanillylacetone markedly decreased the hippocampal tissue levels of inflammatory biomarkers (interleukin-6, tumor necrosis factor-α, intracellular cell adhesive molecules) and apoptosis biomarkers (Bax and cleaved caspase-3). The control and CdCl2-treated groups treated with vanillylacetone showed reduced generation of reactive oxygen species, decreased malondialdehyde levels, and increased superoxide dismutase and glutathione activities, along with significant elevation of nuclear Nrf2 mRNA and protein expression in hippocampal tissue. All the protective effects of vanillylacetone were substantially blocked by the co-administration of brusatol (a selective Nrf2 inhibitor). Vanillylacetone mitigated hippocampal damage and memory loss induced by CdCl2, at least in part, by activating the nuclear transcription factor Nrf2. Additionally, vanillylacetone exerted its potent antioxidant and anti-inflammatory actions.

Predictive biomarkers of mortality in patients with severe COVID-19 hospitalized in intensive care unit.

Objectives: This study was performed to identify predictive markers of worse outcomes in patients with severe COVID-19 in an intensive care unit. Methods: Sixty patients with severe COVID-19, hospitalized in the Intensive Care Unit (ICU) between March and July 2021, were stratified into two groups according to the outcome survivors and non-survivors. After admission to the ICU, blood samples were collected directly for biomarker analysis. Routine hematological and biochemical biomarkers, as well as serum levels of cytokines, chemokines, and immunoglobulins, were investigated. Results: Lymphopenia, neutrophilia, and thrombocytopenia were more pronounced in non-surviving patients, while the levels of CRP, AST, creatinine, ferritin, AST, troponin I, urea, magnesium, and potassium were higher in the non-surviving group than the survival group. In addition, serum levels of IL-10, CCL2, CXCL9, and CXCL10 were significantly increased in patients who did not survive. These changes in the biomarkers evaluated were associated with increased mortality in patients with severe COVID-19. Conclusion: The present study confirmed and expanded the validity of laboratory biomarkers as indicators of mortality in severe COVID-19.

Vitamin E protects against the modulation of TNF-α-AMPK axis and inhibits pancreas injury in a rat model of L-arginine-induced acute necrotising pancreatitis.

BACKGROUND: Acute pancreatitis (AP) associated with the modulation of TNF-α-AMPK axis in the presence and absence of vitamin E has not been investigated before. MATERIAL AND METHODS: Rats were either injected with L-arginine (2.5 gm/kg) before being sacrificed after 48 h or were pre-treated with vitamin E (60 mg/kg) and continued receiving vitamin E until the end of the experiment. RESULTS: AP was developed as demonstrated by infiltration of inflammatory cells and profound pancreas tissue damage, which were substantially protected by vitamin E. In addition, L-arginine injections significantly (p < .0001) increased the expression of TNF-α mRNA and protein, and decreased phospho-AMPK and IL-10 mRNA and protein that was significantly (p < .0001) protected by vitamin E. Furthermore, vitamin E inhibited L-arginine-induced blood levels of LDH, amylase, and myeloperoxidase. CONCLUSIONS: L-arginine-induced acute pancreatitis modulates TNF-α-AMPK axis, IL-10 and other AP biomarkers, which is protected by vitamin E; thus, may offer therapeutic potential in humans.

Metformin ameliorates ROS-p53-collagen axis of fibrosis and dyslipidemia in type 2 diabetes mellitus-induced left ventricular injury.

BACKGROUND: The link between oxidative stress (ROS), apoptosis (p53) and fibrosis (collagen) in type 2 diabetes mellitus (T2DM)-induced cardiac injury in the presence and absence of the antidiabetic drug, metformin has not been investigated before. MATERIAL AND METHODS: T2DM was induced in rats by a combination of high carbohydrate and fat diets (HCFD) and streptozotocin (50 mg/kg) injection. The protection group started metformin (200 mg/kg) treatment 14 days prior to the induction of diabetes and continued on metformin and HCFD until being sacrificed at week 12. RESULTS: Diabetes significantly induced blood levels of ROS and left ventricular p53 and collagen expression that was inhibited by metformin. Metformin also significantly reduced glycated haemoglobin and dyslipidemia induced by diabetes. In addition, a significant correlation between ROS-p53-collagen axis and glycaemia and hyperlipidaemia was observed. CONCLUSIONS: These findings show that metformin provides substantial protection against diabetic cardiomyopathy-induced ROS-p53 mediated fibrosis and dyslipidemia.

Insulin protects against type 1 diabetes mellitus-induced aortopathy associated with the inhibition of biomarkers of vascular injury in rats.

BACKGROUND: We sought to investigate the protective effect of insulin against type 1 diabetes mellitus (T1DM)-induced aortic injury (aortopathy) associated with the inhibition of biomarkers of vascular injury. MATERIAL AND METHODS: T1DM was induced in rats by streptozotocin (STZ) (65 mg/kg), and the protection group started insulin treatment 2 days post diabetic induction and continued until being sacrificed at week 8. RESULTS: Aortopathy was developed in the diabetic rats as demonstrated by profound alterations to the aorta ultrastructure, which was substantially protected by insulin. In addition, insulin significantly inhibited diabetes-induced dyslipidaemia, soluble vascular cell adhesion molecule-1 (sVCAM-1) and soluble intercellular adhesion molecule-1 (sICAM-1), oxidative stress, and inflammation. However, blood levels of these biomarkers in the insulin-treated group were still significant (p < .05) compared with the control group, whereas insulin treatment returned blood glucose and triglyceride to control levels. CONCLUSIONS: We demonstrate effective protection by insulin against T1DM-induced aortopathy in rats, which is associated with the inhibition of vascular injury biomarkers.

Captopril suppresses hepatic mammalian target of rapamycin cell signaling and biomarkers of inflammation and oxidative stress in thioacetamide-induced hepatotoxicity in rats.

BACKGROUND: The potential inhibitory effects of captopril, the angiotensin-converting enzyme inhibitor, on thioacetamide (TAA)-induced hepatic mammalian target of rapamycin (mTOR), liver injury enzymes, blood pressure, and biomarkers of inflammation and oxidative stress have not been investigated before. MATERIALS AND METHODS: Rats were either injected with TAA (200 mg/kg; twice a week for 8 weeks) before being sacrificed after 10 weeks (model group) or were pretreated with captopril (150 mg/kg) daily for two weeks prior to TAA injections and continued receiving both agents until the end of the experiment (protective group). RESULTS: Captopril significantly (p < .05) inhibited TAA-induced hypertension, liver tissue levels of mTOR, TIMP-1, TNF-α, IL-6, MDA; and blood levels of lipids, ALT, and AST. We further demonstrated a significant (p < .01) positive correlation between mTOR scoring and the levels of inflammatory, oxidative and liver injury biomarkers. CONCLUSIONS: Captopril protects against TAA-induced mTOR, liver injury enzymes, dyslipidemia, hypertension, inflammation, and oxidative stress.

Ghrelin prevents cardiac cell apoptosis during cardiac remodelling post experimentally induced myocardial infarction in rats via activation of Raf-MEK1/2-ERK1/2 signalling.

CONTEXT: Mechanisms by which ghrelin affords its cardioprotection in mammals remained unclear. OBJECTIVE: To examine if ghrelin confers cardio-protection during cardiac remodelling post-MI by modulating the RAF-1-MEK1/2-ERK1/2 signalling pathway. MATERIALS AND METHODS: Rats were divided into control, sham, sham + ghrelin, myocardial infarction (MI), and MI + ghrelin groups. Ghrelin (100 µg/kg) was administered for 21 days, starting one-day post-MI. RESULTS: Ghrelin enhanced cardiac contractility and the activities of antioxidant enzymes, lowered serum levels of enzyme markers of cardiac dysfunction, and lowered inflammatory mediator levels. Ghrelin increased levels of phospho-Raf-1 (Ser338), phospho-MEK1/2 (Ser217/221), phospho-ERK1/2 (Thr202/Tyr204), and of their downstream target p-BAD (Ser112) and inhibited the cleavage of caspase-3. Concomitantly, ghrelin prevented the increases in the levels of fibrotic markers, including α-smooth muscle actin (α-SMA), metalloproteinase-9 (MPP-9), and type III collagen. CONCLUSION: Post-MI in rats, ghrelin stimulated Raf-1-MEK1/2-ERK1/2-BAD signalling in the LV infarct areas, accounting for its anti-apoptotic effect, enhancing cardiac function, and inhibiting cardiac fibrosis during cardiac remodelling.

The prevalence of malnutrition among high and low altitude preschool children of southwestern Saudi Arabia.

OBJECTIVE: To assess the current status of protein energy malnutrition (PEM) in the high and low altitude preschool children aged 12-71 months. METHODS: A cross-sectional study conducted during the year of 2003 and involved 572 and 469 preschool children of Southwestern Saudi Arabia born and living permanently at high and low altitude areas. Anthropometric measurements were carried out to assess the prevalence of PEM using 3 indicators such as underweight, wasting and stunting following World Health Organization standards. Prevalence differences were examined by age, gender, altitude, and parental socioeconomic status. RESULTS: The prevalence of the 3 types of PEM was significantly higher at low altitude than at high altitude and significantly higher among children born to illiterate than to educated parents. Older children were more underweight and stunted than younger children and underweight and wasting were significantly more common in boys than girls. Annual family income per person was negatively and significantly associated with underweight and stunting, but not with wasting. Multivariate analysis showed that after controlling for all sociobiological factors, low altitude remained a strong risk factor. CONCLUSION: The difference in PEM between high and low altitude preschool children could be related to the milder environmental conditions at high altitude and the higher incidence of tropical infections in lowland children. Future studies are required to verify these speculations, and to establish programs to control and prevent PEM in preschool children at low altitude.

The effect of long-term use of computer mouse devices on median nerve entrapment.

OBJECTIVE: To assess the effect of long-term use of computer mouse devices on the median nerves. METHODS: A cross-section prospective study conducted during the year 2004 involved 41 male secretaries employed in the Health Colleges of King Khalid University in Abha, Kingdom of Saudi Arabia. A questionnaire describing sociodemographic and computer use was completed. The electrophysiological study included measurements of motor latencies, motor conduction velocities, and amplitudes of compound muscle action potential of the right median nerve and compared these with those of the left median nerve (control). All of our subjects were right handed. Terminal latency index (TLI) was calculated for each nerve tested. Entrapment neuropathy of the median nerve at the wrist was defined as TLI <0.30. RESULTS: The mean TLI of the median nerve in the right hand was significantly lower than that in the left hand. Eight of the 23 asymptomatic participants (34.8%), 6 of the 12 who reported hand discomfort (50%), and all the 6 participants who met clinical criteria for carpal tunnel syndrome showed electrophysiological evidence suggestive of right median nerve entrapment neuropathy at the wrist. Test of association showed a negative and significant correlation between TLI of the right median nerve and weekly hours mouse device use while no significant correlation was found between TLI in the same hand and weekly hours keyboard use. CONCLUSION: Frequent computer mouse device users are at high risk of developing median nerve entrapment neuropathy at the wrist.