An <i>in vitro</i> human 3D co-culture model to study endothelial-astrocyte interactions

At the gliovascular interface, reciprocal inductive influences between brain microvascular endothelial cells (BMVEC) and astrocytes occur. Most of the knowledge in this area of research is derived from in vitro eo-culture models in which astrocytes are cultured on a stiff, two-dimensional (2D) surface. Three-dimensional (3D) culture models closely mimic the in lJZVO cellular architecture and they bridge the gap between 2D culture models and animal models. Hence, an in vitro 3D eo-culture model was developed and characterised, to study the interactions between BMVEC and astrocytes. In this model, human astrocytes (HA) were seeded inside a collagen type--I gel while human immortalised cerebral microvascular endothelial cells (hCMEC/D3) were cultured on the gel surface. Both cell types were of human origin to improve the translatability of findings to humans in vivo. Additional important features of the model are the culture of endothelial cells on a soft matrix, and the simulation of the geometric relationship that exists in vivo i.e., the interaction of astrocytes with BMVEC from their ab luminal side. To determine the effect of the 3D environment on the HA, the proliferation rate and expression of four molecules namely, glial fibrillary acidic protein (GF AP), aquaporin-4 (AQP4), endothelin-l (Et-l) and endothelin receptor type-B (EDNRB), were compared between 3D and 2D cultured HA. The decreased expression of AQP4 and EDNRB and the much-decreased proliferation rate of 3D HA suggested their reduced reactivity and a similarity to their in lJiVO counterparts. However, 3D HA did not differ from the 2D HA in their ability to release soluble factors that induce barrier properties on BMVEC, as observed by similar levels of three expression markers of barrier phenotype on hCMEC/D3 cells namely, zonula occludens-l, claudin-5, and P-glycoprotein and similar paracellular permeability coefficients to fluorescent-dextrans (70 kDa).Using the developed model, the effect of endothelial cells on the AQP4 expression in HA was investigated. While the localisation of astrocytic AQP4 did not change, its total, cellular expression levels were decreased as analysed by flow cytometry and fluorescence microscopy. The results could not be explained by physical-contact and therefore may be mediated by soluble factors released by the endothelial cells. Further investigation showed that Et-l, at least by itself, is not the mediator of this effect. The endothelial-astrocyte physical contact points were too few, as revealed by transmission electron microscopy, to study its effect on the localisation of AQP4 in HA. The developed 3D co-culture model is usable and amenable to various analytical techniques such as fluorescence microscopy, electron microscopy, flow cytometry, and enzyme linked immunosorbent assay. The two-step collagenase digestion method developed in this study further broadens the model's utility to standard molecular and cellular biology techniques. The model has some advantages as well as limitations compared to the existing 2D and 3D co-culture models. The model may be used as an in vitro BBB model to study the transcytosis of nanoparticles, leukocytes, and possibly pathogens across the endothelial barrier and their interactions with astrocytes. In addition, the alterations in phenotype of astrocytes and endothelium in situ, in response to the soluble factors released by the other cell type can be studied. Further work is needed to validate some of the supposed unique features of the model. With the proposed modifications, it can be made physiologically more relevant, and the usability can be widened

CFD ANALYSIS OF THE UNDER HOOD OF A CAR FOR PACKAGING CONSIDERATIONS

In recent years, there has been an increase in demand towards the improvement of car design for achieving better performance and increasing passenger comfort. Improving the design of individual components to meet the customer needs for improved vehicle performance alone is not enough. Interactions of these components with the surrounding components and their placement should also be investigated. Placement of these components in the under hood space forms a 3-Dimensional packaging problem. In the past, a multi objective optimization process was setup to determine the optimal placement of these components in the car under hood space. Three main objectives were taken into account namely, minimizing center of gravity height, maximizing vehicle maintainability and maximizing survivability in the optimization process. However, minimizing the overall under hood temperature and ensuring the temperature of heat sensitive components to be below its critical value, is not added as an objective to the optimization problem. This study makes an assessment of the need for including the thermal objective into the optimization process and also presents an efficient way of performing CFD simulation over the under hood geometry. The under hood geometry used included radiator, engine, exhaust manifold, coolant tank, air filter, brake booster, front grille geometry and battery. These components were included as heat source, heat exchangers etc. A standard k-ɛ turbulence model with upward differencing convection scheme is used on a well refined computational mesh. The work also describes in detail the way of accurately and effectively modeling the radiator as an ungrouped macro heat exchanger model available in Ansys FLUENT. The results obtained from the CFD simulations illustrate the importance of the under hood vehicle configuration optimization process on its thermal behavior. The temperature attained by the coolant flowing through the radiator with constant heat rejection, when placed behind the engine is very high, when compared to the temperature it attained with the radiator placed in front of the engine. The CFD analysis presented in this study is performed using Ansys FLUENT while the initial geometry preparation is done using SolidWorks. The CFD analysis presented in this work is then used to build an approximation by my research mate, which is later tied to an optimizer based on Genetic Algorithm. Thus, including the thermal objective to the multi objective optimization problem stated above

Natural Frequency based delamination estimation in GFRP beams using RSM and ANN

The importance of delamination detection can be understood from aircraft components like Vertical Stabilizer, which is subjected to heavy vibration during the flight movement and it may lead to delamination and finally even flight crash can happen because of that. Any solid structure's vibration behaviour discloses specific dynamic characteristics and property parameters of that structure. This research investigates the detection of delamination in composites using a method based on vibration signals.&nbsp; The composite material's flexural stiffness and strength are reduced as a result of delaminations, and vibration properties such as natural frequency responses are altered. In inverse problems involving vibration response, the response signals such as natural frequencies are utilized to find the location and magnitude of delaminations. For different delaminated beams with varying position and size, inverse approaches such as Response Surface Methodology (RSM) and Artificial Neural Network (ANN) are utilized to address the inverse problem, which aids in the prediction of delamination size and location

Artificial neural network based delamination prediction in composite plates using vibration signals

Dynamic loading on composite components may induce damages such as cracks, delaminations, etc. and development of an early damage detection technique for delaminations is one of the most important aspects in ensuring the integrity and safety of composite components. The presence of damages such as delaminations on the composites reduces its stiffness and further changes the dynamic behaviour of the structures. As the loss in stiffness leads to changes in the natural frequencies, mode shapes, and other aspects of the structure, vibration analysis may be the ideal technique to employ in this case. In this research work, the supervised feed-forward multilayer back-propagation Artificial Neural Network (ANN) is used to determine the position and area of delaminations in GFRP plates using changes in natural frequencies as inputs. The natural frequencies were obtained by finite element analysis and results are validated by experimentation. The findings show that the suggested technique can satisfactorily estimate the location and extent of delaminations in composite plates

Spatial heterogeneities in the mass concentration of near surface aerosols over the Arabian Sea during ICARB

This article does not have an abstract

Biodiesel Production By Using Native Micro Algae From Food Processing Wastewater In Shake Flask Cultures

The present study describes the biodiesel production from food processing wastewater by using Chlorella vulgaris, Botryococcus braunii and mixed algae (Chlorella vulgaris, Botryococcus braunii, Nostoc  and Anaebena).  Continuous monitoring of parameters like pH, Volatile fatty acid, Chemical oxygen demand,  Biochemical oxygen demand, Alkalinity, Sulphates were carried out to asses the efficiency of the treatment process. The micro algal oil was extracted with different solvents like hexane, benzyl alcohol, Iso amyl alcohol, dichloro methane, dichloro ethane, proponal and methanol using distillation. The catalyst concentration (0.00, 0.50, 1.00, 1.50, 1.50 and 2.00%) and Catalyst type (sodium hydroxide, potassium hydroxide, sodium methoxide and potassium methoxide) were studied for the production of biodiesel. The experimental results showed that more than 88% of COD and BOD were removed. Benzyl alcohol and hexane were found to be the best solvents for extraction of algal oil. The biodiesel was characterized by using gas chromatography with mass spectrophotometer. Sodium and potassium hydroxide offered the higher yields when compared to their corresponding methoxides. The results clearly indicated that the optimum concentration of NaOH required for effective transesterification of algal oil was 1.00% for the production of biodiesel. The properties of FAME investigated in this study satisfied nearly all prescribed ASTM D6751

FABRICATION OF DRUG DELIVERY SYSTEM FOR CONTROLLED RELEASE OF CURCUMIN, INTERCALATED WITH MAGNETITE NANOPARTICLES THROUGH SODIUM ALGINATE/POLYVINYLPYRROLIDONE-CO-VINYL ACETATE SEMI IPN MICROBEADS

Objective: The aim of the present work is to fabricate curcumin (CUR) encapsulated microbeads in the polymer matrix of sodium alginate (SA)/poly(vinylpyrrolidone)-co-vinyl acetate (PVP-co-VAc) intercalated with magnetite nanoparticles (MNPs) using glutaraldehyde (GA)/calcium chloride CaCl2 as the crosslinker. Methods: Magnetite nanoparticles (MNPs) were synthesized by a modified co-precipitation method. Curcumin encapsulated SA/PVP-co-VAc microbeads, intercalated with MNPs were prepared by simple ionotropic gelation technique. The formation of microbeads and uniform distribution of curcumin were characterized using spectroscopic methods. In addition, swelling and drug release kinetic studies of the microbeads were performed in simulated intestinal fluid (pH 7.4) and simulated gastric fluid (pH 1.2) at 37 °C. Results: Microbeads formation was confirmed by Fourier Transform Infrared (FTIR). Differential Scanning Calorimetry (DSC) studies reveal that the peak at 181 °C of CUR was not observed in CUR loaded microbeads, which confirms that CUR was encapsulated at the molecular level in the polymer matrix. The X-Ray diffraction (X-RD) diffractograms of CUR shows 2Ө peaks between 12-28 °, which indicated the crystalline nature of CUR, these peaks are not found in CUR loaded microbeads, suggesting that the drug has been molecularly dispersed in the polymer matrix. The X-RD 2Ө peaks of MNPs are observed in the MNPs loaded microbeads, which confirms that MNPs are successfully loaded in the microbeads. The swelling studies and in vitro release studies were performed at pH 1.2 and 7.4. The results reveal that at pH 7.4 highest swelling and release was observed, which confirms that the developed microbeads are pH sensitive and are suitable for intestinal drug delivery. The drug release kinetics fit into the Korsmeyer-Peppas equation, indicating non-Fickian diffusion. Conclusion: The results concluded that the present system as dependent on pH of the test medium and hence suggest suitability for intestinal drug delivery

Bulk viscosity in hyperonic star and r-mode instability

We consider a rotating neutron star with the presence of hyperons in its core, using an equation of state in an effective chiral model within the relativistic mean field approximation. We calculate the hyperonic bulk viscosity coefficient due to nonleptonic weak interactions. By estimating the damping timescales of the dissipative processes, we investigate its role in the suppression of gravitationally driven instabilities in the $r$-mode. We observe that $r$-mode instability remains very much significant for hyperon core temperature of around $10^8$K, resulting in a comparatively larger instability window. We find that such instability can reduce the angular velocity of the rapidly rotating star considerably upto $\sim0.04 \Omega_K$, with $\Omega_K$ as the Keplerian angular velocity.Comment: 10 pages including 7 figure