Analysis of tumour-immune evasion with chemo-immuno therapeutic treatment with quadratic optimal control

A simple mathematical model for the growth of tumour with discrete time delay in the immune system is considered. The dynamical behaviour of our system by analysing the existence and stability of our system at various equilibria is discussed elaborately. We set up an optimal control problem relative to the model so as to minimize the number of tumour cells and the chemo-immunotherapeutic drug administration. Sensitivity analysis of tumour model reveals that parameter value has a major impact on the model dynamics. We numerically illustrate how does these delay can change the stability region of the immune-control equilibrium and display the different impacts to the control of tumour. Finally, epidemiological implications of our analytical findings are addressed critically.     

Staphylococcal infections and infertility: mechanisms and management

Molecular and Cellular Biochemistry - Membrane lipids regulate the structure and function of G protein-coupled receptors (GPCRs). Previously we have shown that membrane cholesterol regulates the...     

Identifying the Basal Ganglia Network Model Markers for Medication-Induced Impulsivity in Parkinson's Disease Patients

Impulsivity, i.e. irresistibility in the execution of actions, may be prominent in Parkinson''s disease (PD) patients who are treated with dopamine precursors or dopamine receptor agonists. In this study, we combine clinical investigations with computational modeling to explore whether impulsivity in PD patients on medication may arise as a result of abnormalities in risk, reward and punishment learning. In order to empirically assess learning outcomes involving risk, reward and punishment, four subject groups were examined: healthy controls, ON medication PD patients with impulse control disorder (PD-ON ICD) or without ICD (PD-ON non-ICD), and OFF medication PD patients (PD-OFF). A neural network model of the Basal Ganglia (BG) that has the capacity to predict the dysfunction of both the dopaminergic (DA) and the serotonergic (5HT) neuromodulator systems was developed and used to facilitate the interpretation of experimental results. In the model, the BG action selection dynamics were mimicked using a utility function based decision making framework, with DA controlling reward prediction and 5HT controlling punishment and risk predictions. The striatal model included three pools of Medium Spiny Neurons (MSNs), with D1 receptor (R) alone, D2R alone and co-expressing D1R-D2R. Empirical studies showed that reward optimality was increased in PD-ON ICD patients while punishment optimality was increased in PD-OFF patients. Empirical studies also revealed that PD-ON ICD subjects had lower reaction times (RT) compared to that of the PD-ON non-ICD patients. Computational modeling suggested that PD-OFF patients have higher punishment sensitivity, while healthy controls showed comparatively higher risk sensitivity. A significant decrease in sensitivity to punishment and risk was crucial for explaining behavioral changes observed in PD-ON ICD patients. Our results highlight the power of computational modelling for identifying neuronal circuitry implicated in learning, and its impairment in PD. The results presented here not only show that computational modelling can be used as a valuable tool for understanding and interpreting clinical data, but they also show that computational modeling has the potential to become an invaluable tool to predict the onset of behavioral changes during disease progression.     

Sialic Acid Linkage in Glycosphingolipids Is a Molecular Correlate for Trafficking and Delivery of Extracellular Cargo

Gangliosides, glycosphingolipids containing sialic acid moieties, are well known mediators of transmembrane signaling and endocytosis at the plasma membrane. However, little is known about their precise regulatory role at the cell periphery for intracellular sorting of extracellular cargo. Here we inspected published scientific literature for two types of cargoes, namely bacterial toxins and viruses, regarding their usage of gangliosides. We derived a rather simple yet surprisingly consistent framework to classify 20 viruses from 12 different families and five type AB bacterial toxins into two broad categories. We propose that gangliosides with terminally attached sialic acids classify cargo for uptake and trafficking early in the endocytic pathway while gangliosides with internally attached sialic acids associate with uptake and trafficking of cargo late in the endocytic system. Our study provides a testable hypothesis for future investigations into a wide range of trafficking events. It could be utilized as a framework for other intracellular pathogens where lipids are known to be involved in recognition and trafficking. For instance, predictions can be put forward and evaluated based on ganglioside binding patterns and intracellular trafficking routes. Finally, incorporation of our classifier into large scale systems‐biology studies could help reveal related molecular determinants in subcellular sorting .     

BIOETHANOL PRODUCTION FROM LEAFY BIOMASS OF MANGO (Mangifera indica) INVOLVING NATURALLY ISOLATED AND RECOMBINANT ENZYMES

The present study describes the usage of dried leafy biomass of mango (Mangifera indica) containing 26.3% (w/w) cellulose, 54.4% (w/w) hemicellulose, and 16.9% (w/w) lignin, as a substrate for bioethanol production from Zymomonas mobilis and Candida shehatae. The substrate was subjected to two different pretreatment strategies, namely, wet oxidation and an organosolv process. An ethanol concentration (1.21 g/L) was obtained with Z. mobilis in a shake-flask simultaneous saccharification and fermentation (SSF) trial using 1% (w/v) wet oxidation pretreated mango leaves along with mixed enzymatic consortium of Bacillus subtilis cellulase and recombinant hemicellulase (GH43), whereas C. shehatae gave a slightly higher (8%) ethanol titer of 1.31 g/L. Employing 1% (w/v) organosolv pretreated mango leaves and using Z. mobilis and C. shehatae separately in the SSF, the ethanol titers of 1.33 g/L and 1.52 g/L, respectively, were obtained. The SSF experiments performed with 5% (w/v) organosolv-pretreated substrate along with C. shehatae as fermentative organism gave a significantly enhanced ethanol titer value of 8.11 g/L using the shake flask and 12.33 g/L at the bioreactor level. From the bioreactor, 94.4% (v/v) ethanol was recovered by rotary evaporator with 21% purification efficiency.     

Myricetin: versatile plant based flavonoid for cancer treatment by inducing cell cycle arrest and ROS–reliant mitochondria-facilitated apoptosis in A549 lung cancer cells and in silico prediction

Molecular and Cellular Biochemistry - Myricetin is categorized under the secondary metabolite flavonoid which includes a diverse range of consumable plant parts, and it has a potential against...