Hepatic Potentials of Xylopia Aethiopica Leaves in Adult Wistar Rats

This study investigates the possible toxic effect of Xylopia aethiopica on liver function via the evaluation of someserum biochemical parameters. The study involved 24 adult rats with weight ranging from 150 to 300g and dividedinto four groups of 6 rats each (A, B, C and D). For 21 days, varying doses of 1.2g/kg, 3.0g/kg and 6.0g/kg per body weight of Xylopia aethiopica  leaves powder were administered daily to test groups B, C and D respectively. Group A however served as control that received normal feed and water only. At the end of the experiment, the animals were sacrificed under light anesthesia to obtain blood samples for the estimation of liver enzyme activities. The results showed that there was a significant increase (P<0.05) in the activities of Aspartate amino transferase (AST) and Alkaline Phosphates (ALP) but a significant decrease (P<0.05) in the levels of total protein, albumin and globulin levels in the test groups as compared to the control. On the other hand, the activities of Gamma glutamyl transferase (GGT) and Alanine amino transferase (ALT) of the test groups were not significantly different (P>0.05) from that of the control.  Therefore,  the observed changes in the parameters accessed, signifies the hepatotoxic impact of Xylopia aethiopica leaves.Keywords: Xylopia aethiopica, hepatoxicity, Herbs, Nigeria

Process Algebra with Layers: Multi-scale Integration Modelling applied to Cancer Therapy

We present a novel Process Algebra designed for multi-scale integration modelling: Process Algebra with Layers (PAL). The unique feature of PAL is the modularisation of scale into integrated layers: Object and Population. An Object can represent a molecule, organelle, cell, tissue, organ or any organism. Populations hold specific types of Object, for example, life stages, cell phases and infectious states. The syntax and semantics of this novel language are presented. A PAL model of the multi-scale system of cell growth and damage from cancer treatment is given. This model allows the analysis of different scales of the system. The Object and Population levels give insight into the length of a cell cycle and cell population growth respectively. The PAL model results are compared to wet laboratory survival fractions of cells given different doses of radiation treatment [1]. This comparison shows how PAL can be used to aid in investigations of cancer treatment in systems biology

Neglected Tropical Diseases in Sub-Saharan Africa: Review of Their Prevalence, Distribution, and Disease Burden

The neglected tropical diseases (NTDs) are the most common conditions affecting the poorest 500 million people living in sub-Saharan Africa (SSA), and together produce a burden of disease that may be equivalent to up to one-half of SSA's malaria disease burden and more than double that caused by tuberculosis. Approximately 85% of the NTD disease burden results from helminth infections. Hookworm infection occurs in almost half of SSA's poorest people, including 40–50 million school-aged children and 7 million pregnant women in whom it is a leading cause of anemia. Schistosomiasis is the second most prevalent NTD after hookworm (192 million cases), accounting for 93% of the world's number of cases and possibly associated with increased horizontal transmission of HIV/AIDS. Lymphatic filariasis (46–51 million cases) and onchocerciasis (37 million cases) are also widespread in SSA, each disease representing a significant cause of disability and reduction in the region's agricultural productivity. There is a dearth of information on Africa's non-helminth NTDs. The protozoan infections, human African trypanosomiasis and visceral leishmaniasis, affect almost 100,000 people, primarily in areas of conflict in SSA where they cause high mortality, and where trachoma is the most prevalent bacterial NTD (30 million cases). However, there are little or no data on some very important protozoan infections, e.g., amebiasis and toxoplasmosis; bacterial infections, e.g., typhoid fever and non-typhoidal salmonellosis, the tick-borne bacterial zoonoses, and non-tuberculosis mycobaterial infections; and arboviral infections. Thus, the overall burden of Africa's NTDs may be severely underestimated. A full assessment is an important step for disease control priorities, particularly in Nigeria and the Democratic Republic of Congo, where the greatest number of NTDs may occur

Minimal Symptom Expression' in Patients With Acetylcholine Receptor Antibody-Positive Refractory Generalized Myasthenia Gravis Treated With Eculizumab

The efficacy and tolerability of eculizumab were assessed in REGAIN, a 26-week, phase 3, randomized, double-blind, placebo-controlled study in anti-acetylcholine receptor antibody-positive (AChR+) refractory generalized myasthenia gravis (gMG), and its open-label extension

A Novel Method to Verify Multilevel Computational Models of Biological Systems Using Multiscale Spatio-Temporal Meta Model Checking

Insights gained from multilevel computational models of biological systems can be translated into real-life applications only if the model correctness has been verified first. One of the most frequently employed in silico techniques for computational model verification is model checking. Traditional model checking approaches only consider the evolution of numeric values, such as concentrations, over time and are appropriate for computational models of small scale systems (e.g. intracellular networks). However for gaining a systems level understanding of how biological organisms function it is essential to consider more complex large scale biological systems (e.g. organs). Verifying computational models of such systems requires capturing both how numeric values and properties of (emergent) spatial structures (e.g. area of multicellular population) change over time and across multiple levels of organization, which are not considered by existing model checking approaches. To address this limitation we have developed a novel approximate probabilistic multiscale spatio-temporal meta model checking methodology for verifying multilevel computational models relative to specifications describing the desired/expected system behaviour. The methodology is generic and supports computational models encoded using various high-level modelling formalisms because it is defined relative to time series data and not the models used to generate it. In addition, the methodology can be automatically adapted to case study specific types of spatial structures and properties using the spatio-temporal meta model checking concept. To automate the computational model verification process we have implemented the model checking approach in the software tool Mule (http://mule.modelchecking.org). Its applicability is illustrated against four systems biology computational models previously published in the literature encoding the rat cardiovascular system dynamics, the uterine contractions of labour, the Xenopus laevis cell cycle and the acute inflammation of the gut and lung. Our methodology and software will enable computational biologists to efficiently develop reliable multilevel computational models of biological systems