PI3K/Akt and Nrf2/HO-1 pathways involved in the hepatoprotective effect of verapamil against thioacetamide toxicity in rats

Liver is a precious organ to maintain body life. Hepatotoxicity is a worldwide health problem that is still a challenge for research. Although countless pharmaceutical drugs and herbal compounds were screened for their hepatoprotective effects, the death from hepatotoxicity is increasing. Thus, there is continuous necessity of searching for the hepatoprotective effect of commonly used drugs. Accordingly, our aim was to examine a hepatoprotective potential for the antihypertensive drug, verapamil, and searching for new insights underlie its protective mechanism. Four groups of adult male rats were randomly arranged as controls, thioacetamide (TAA) hepatotoxic, and TAA + verapamil treated. Serum liver enzyme, hepatic antioxidant, lipid peroxidation, and inflammatory parameters were assessed. Gene relative expression for heme oxygenase-1 (HO-1), nuclear factor-erythroid 2-related factor 2 (Nrf2), phosphoinositide 3-kinase (PI3K), and serine/threonine-specific protein kinase (Akt) were quantified in hepatic tissue. TAA caused hepatic injury evident both histopathologically and biochemically by a decrease in all gene expressions. Verapamil alleviated the injury via its antioxidant and anti-inflammatory effects that were suggested to be via upregulation of the previous gene expressions. In conclusion, the calcium channel blocker, verapamil, that is used widely as antihypertensive exhibits a valuable hepatoprotective effect. The protection partially rests on activation of Nrf2/HO-1 and PI3K/Akt pathways.

Perception and utilization of tetanus toxoid immunization among pregnant women attending a tertiary centre in North-West Nigeria

Background: Despite the availability of inexpensive and effective tetanus-toxoid-containing vaccines, elimination of maternal and neonatal tetanus worldwide has become a herculean task, particularly in low-income countries, due to poor immunization coverage. This study aimed to assess the perception and utilization of tetanus toxoid immunization among pregnant women attending a tertiary centre in North-West Nigeria. Materials and Methods: A cross-sectional study was conducted among 254 pregnant women (selected by systematic sampling technique) attending the antenatal clinic of Specialist Hospital, Sokoto, Nigeria. A structured interviewer-administered questionnaire was used to collect data on the research variables. Data were analyzed using IBM SPSS version 20 statistical computer software package. Results: Most, 221 (87.0%) of the 254 respondents had heard of tetanus toxoid immunization. Of these, only about half (51.1%) believed that it protects both mother and newborn baby from tetanus. Majority of respondents considered TT immunization to be effective in protecting against tetanus infection (73.3%) and also safe for both mother and baby (79.2%). About two-thirds of respondents (68.8%) had the misconception that a single dose of TT immunization protects from tetanus infection. Less than a quarter of respondents (23.6%) had received two or more doses of the vaccine. The main barriers to utilization of vaccines were lack of awareness of the vaccine (41.8%), not being aware of its benefits (36.7%), and fear of side effects (21.5%) Conclusion: Despite high levels of perception of the effectiveness and safety of TT immunization, the respondents in this study had low levels of perception and utilization of the protective doses of the vaccine. Government and healthcare workers should scale-up education of the populace on TT immunization schedule and implement community based vaccination of women of child bearing age in North-West Nigeria. Keywords: Perception, utilization, tetanus toxoid immunization, pregnant women

Finding Novel Anti-carcinomas Compounds by Targeting SFRP4 Through Molecular Modeling, Docking and Dynamic Simulation Studies

BACKGROUND

Secreted Frizzled-Related Protein 4 (SFRP4) is a glycoprotein that acts as a competitor of both canonical and non-canonical Wnt pathways. SFRP4 is mostly expressed in ovary and plays a significant role as a target molecule to cure ovarian carcinoma.

OBJECTIVE

Multiple chemical agonists are being used to cure ovary melanoma. We are interested in theoretically analyzing the compounds through computational approaches for their potential inhibitory effects against SFRP4.

METHODS

Compounds were sketched in Chemsketch drawing tool and minimized through chimera tool. Because the crystal structure of SFRP4 is not available in Protein Data Bank, homology modeling approach was used to predict Three-Dimensional (3D) crystal structure of SFRP4. Moreover, multiple computational approaches such as molecular docking and Molecular Dynamic (MD) simulations along with various online tools were employed to screen the best inhibitor against ovary melanoma.

RESULTS

The docking results showed that 1d and 1e compounds revealed significant binding energy values (-9.10 and -9.00 kcal/mol, respectively) compared with the standard drugs such as cis-platin and docetaxel (-3.30, -10.80 kcal/mol), respectively. Moreover, MD simulation results showed that 1d has little fluctuations throughout the simulation period as depicted by the root mean square deviation and root mean square fluctuation graphs.

CONCLUSION

The present in-silico study provides a deeper insight into the structural attributes of 1d compound and its overall molecular interactions against SFRP4 and gives a hypothetical gateway to use this compound as a potential inhibitor against ovarian carcinoma.

Dynamic reshaping of functional brain networks during visual object recognition

OBJECTIVE

Emerging evidence shows that the modular organization of the human brain allows for better and efficient cognitive performance. Many of these cognitive functions are very fast and occur in a sub-second time scale such as the visual object recognition.

APPROACH

Here, we investigate brain network modularity while controlling stimuli meaningfulness and measuring a participant's reaction time. We particularly raised two questions: i) does the dynamic brain network modularity change during the recognition of meaningful and meaningless visual images? And (ii) is there a correlation between network modularity and the reaction time of the participants? To tackle these issues, we collected dense-electroencephalography (EEG, 256 channels) data from 20 healthy human subjects performing a cognitive task consisting of naming meaningful (tools, animals…) and meaningless (scrambled) images. Functional brain networks in both categories were estimated at the sub-second time scale using the EEG source connectivity method. By using multislice modularity algorithms, we tracked the reconfiguration of functional networks during the recognition of both meaningful and meaningless images.

MAIN RESULTS

Results showed a difference in the module's characteristics of both conditions in term of integration (interactions between modules) and occurrence (probability on average of any two brain regions to fall in the same module during the task). Integration and occurrence were greater for meaningless than for meaningful images. Our findings revealed also that the occurrence within the right frontal regions and the left occipito-temporal can help to predict the ability of the brain to rapidly recognize and name visual stimuli.

SIGNIFICANCE

We speculate that these observations are applicable not only to other fast cognitive functions but also to detect fast disconnections that can occur in some brain disorders.

Identification of epileptogenic networks from dense EEG: A model-based study

Epilepsy is a network disease. Identifying the epileptogenic networks from noninvasive recordings is a challenging issue. In this context, M/EEG source connectivity is a promising tool to identify brain networks with high temporal and spatial resolution. In this paper, we analyze the impact of the two main factors that intervene in EEG source connectivity processing: i) the algorithm used to solve the EEG inverse problem and ii) the method used to measure the functional connectivity. We evaluate three inverse solutions algorithms (dSPM, wMNE and cMEM) and three connectivity measures (r(2), h(2) and MI) on data simulated from a combined biophysical/physiological model able to generate realistic interictal epileptic spikes reflected in scalp EEG. The performance criterion used here is the similarity between the network identified by each of the inverse/connectivity combination and the original network used in the source model. Results show that the choice of the combination has a high impact on the identified network. Results suggest also that nonlinear methods (nonlinear correlation coefficient and mutual information) for measuring the connectivity are more efficient than the linear one (the cross correlation coefficient). The dSPM as inverse solution shows the lowest performance compared to cMEM and wMNE.

Classification of pregnancy and labor contractions using a graph theory based analysis

In this paper, we propose a new framework to characterize the electrohysterographic (EHG) signals recorded during pregnancy and labor. The approach is based on the analysis of the propagation of the uterine electrical activity. The processing pipeline includes i) the estimation of the statistical dependencies between the different recorded EHG signals, ii) the characterization of the obtained connectivity matrices using network measures and iii) the use of these measures in clinical application: the classification between pregnancy and labor. Due to its robustness to volume conductor, we used the imaginary part of coherence in order to produce the connectivity matrix which is then transformed into a graph. We evaluate the performance of several graph measures. We also compare the results with the parameter mostly used in the literature: the peak frequency combined with the propagation velocity (PV +PF). Our results show that the use of the network measures is a promising tool to classify labor and pregnancy contractions with a small superiority of the graph strength over PV+PF.

Correlation of Troponin-I Level with Left Ventricular Ejection Fraction and In-hospital outcomes after First Attack of Non-ST Segment Elevation Myocardial Infarction

Coronary heart disease (CHD) is the most common cause of heart disease and is the single most important cause of premature death in developed world. Recognizing a patient with ACS is important because the diagnosis triggers both triage and management. cTnI is 100% tissue-specific for the myocardium and it has been shown to be a very sensitive and specific marker for acute myocardial infarction (AMI). Ventricular function is the best predictor of death after an acute coronary syndrome. It serves as a marker of myocardial damage, provides information on systolic function as well as diagnosis and prognosis. The study aimed at investigating the impact of elevated Troponin-I level on LV ejection fraction and in-hospital outcomes in patients with first attack of Non ST-segment Elevation Myocardial Infarction (NSTEMI). This prospective analytical study was conducted in the Department of Cardiology in Mymensingh Medical College Hospital from December 2015 to November 2016. Total 130 first attack of NSTEMI patients were included considering inclusion and exclusion criteria. The sample population was divided into two groups: Group I - Patients with first attack of NSTEMI with good LV function (LVEF: ≥55%). Group II - Patients with first attack of NSTEMI with LV systolic dysfunction (LVEF: <55%). Then Troponin-I and LVEF levels were correlated using Pearson's correlation coefficient test. In this study mean Troponin-I of Group I and Group II were 5.53±7.43 and 16.46±15.79ng/ml respectively. It was statistically significant (p<0.05). Echocardiography showed that patients with high Troponin-I level had low ejection fraction (LVEF) and patients with low Troponin-I level had preserved ejection fraction (LVEF). Analysis showed that patients with severe left ventricular systolic dysfunction (LVEF <35%) had the highest level of Troponin-I with worse in-hospital outcomes and vice versa-the patients with the preserved systolic function (LVEF ≥55%) had the lowest levels of Troponin-I with better in-hospital outcomes. In our study, it also showed that the levels of Troponin-I had negative correlation with LV ejection fraction levels, with medium strength of association (r= -0.5394, p=0.001). The study enabled us to conclude that, the higher was the Troponin-I level, the lower was the LV ejection fraction level and thus worse in-hospital outcomes in first attack of NSTEMI patients.