Effect of Zeta Potential on the Properties of Nano-Drug Delivery Systems - A Review (Part 1)

Zeta potential is a scientific term for electrokinetic potential in colloidal systems which has a major effect on the various properties of nano-drug delivery systems. Presently, colloidal nano-carriers are growing at a remarkable rate owing to their strong potential for overcoming old challenges such as poor drug solubility and bioavailability. Furthermore, they show an unlimited capacity in the field of drug targeting. The properties of nano-medicines such as release from dosage forms at specific sites as well as drug circulation and absorption into body membranes are dramatically affected by some physical and chemical characteristics of nano-drugs. Particle size and charge are two major factors which could play key roles in this regard. In this paper, the effect of zeta potential on different properties of nano-drug delivery systems is reviewed.Keywords: Nano-drug delivery, Zeta potential, Drug targeting, Particle size, Particle charg

Effect of Zeta Potential on the Properties of Nano-Drug Delivery Systems - A Review (Part 2)

The zeta potential (ZP) of colloidal systems and nano-medicines, as well as their particle size exert a major effect on the various properties of nano-drug delivery systems. Not only the stability of dosage forms and their release rate are affected but also their circulation in the blood stream and absorptioninto body membranes are dramatically altered by ZP. In this paper the effect of ZP on the various properties of nano-medicines are reviewed. Furthermore, the ability of employing zeta potential to target drug delivery systems to, and drug release at specific sites of the body are discussed.Keywords: Nano-medicines, Zeta potential, Drug targeting, Site-specific release, Dosage form stabilit

Properties of Hardened Concrete Containing CBA Ash and FCS as Partial Sand Replacement

A large amount of coal bottom ash (CBA) is being discharged from thermal power plants and has been making serious environmental pollution. Meanwhile, fine coconut shell (FCS) is an agricultural waste and is available in plentiful quantities throughout tropical countries worldwide. In many countries, coconut shell is subjected to open burning which contributes significantly to CO2 and methane emissions. Both of these materials are essential to utilize the CBA and FCS to reduce environmental pollution. Therefore, this study aims to determine the properties of combination of these materials as partial sand replacement. CBA is slow in pozzolanic activity of coal bottom ash which is suitable for partial replacement sand. Meanwhile, FCS is lightweight material with high density in porous filler.  Concrete designed for 30 MPa strength at 28 days curing age and 0.50 of water-cement ratio in this study. The percentage of CBA used is 5%, 10%, 15% and 20%, while the percentage of FCS is 2%, 4%, 6% and 8% where it has been replaced by volume replacement. The specimens were cured in water for 7, 28, 56 and 90 days curing ages before compressive and splitting tensile strength test are conducted. It can be concluded that the density of the concrete decreased, compressive and splitting tensile strength show the improvement with the utilization of CBA and FCS in concrete. In addition, the percentage of water absorption increased as both of CBA and FCS absorb the water. This study shows that an optimum percentage of CBA found is 10% and FCS is 6% for this study

An entropy-histogram approach for image similarity and face recognition

Image similarity and image recognition are modern and rapidly growing technologies because of their wide use in the field of digital image processing. It is possible to recognize the face image of a specific person by finding the similarity between the images of the same person face and this is what we will address in detail in this paper. In this paper, we designed two new measures for image similarity and image recognition simultaneously. The proposed measures are based mainly on a combination of information theory and joint histogram. Information theory has a high capability to predict the relationship between image intensity values. The joint histogram is based mainly on selecting a set of local pixel features to construct a multidimensional histogram. The proposed approach incorporates the concepts of entropy and a modified 1D version of the 2D joint histogram of the two images under test. Two entropy measures were considered, Shannon and Renyi, giving a rise to two joint histogram-based, information-theoretic similarity measures: SHS and RSM. The proposed methods have been tested against powerful Zernike-moments approach with Euclidean and Minkowski distance metrics for image recognition and well-known statistical approaches for image similarity such as structural similarity index measure (SSIM), feature similarity index measure (FSIM) and feature-based structural measure (FSM). A comparison with a recent information-theoretic measure (ISSIM) has also been considered. A measure of recognition confidence is introduced in this work based on similarity distance between the best match and the second-best match in the face database during the face recognition process. Simulation results using AT&T and FEI face databases show that the proposed approaches outperform existing image recognition methods in terms of recognition confidence. TID2008 and IVC image databases show that SHS and RSM outperform existing similarity methods in terms of similarity confidence

An information-theoretic image quality measure: Comparison with statistical similarity

We present an information-theoretic approach for structural similarity for assessing gray scale image quality. The structural similarity measure SSIM, proposed in 2004, has been successflly used and verfied. SSIM is based on statistical similarity between the two images. However, SSIM can produce confusing results in some cases where it may give a non-trivial amount of similarity for two different images. Also, SSIM cannot perform well (in detecting similarity or dissimilarity) at low peak signal to noise ratio (PSNR). In this study, we present a novel image similarity measure, HSSIM, by using information - theoretic technique based on joint histogram. The proposed method has been tested under Gaussian noise. Simulation results show that the proposed measure HSSIM outperforms statistical similarity SSIM by ability to detect similarity under very low PSNR. The average difference is about 20dB

A feature-based structural measure: an image similarity measure for face recognition

Facial recognition is one of the most challenging and interesting problems within the field of computer vision and pattern recognition. During the last few years, it has gained special attention due to its importance in relation to current issues such as security, surveillance systems and forensics analysis. Despite this high level of attention to facial recognition, the success is still limited by certain conditions; there is no method which gives reliable results in all situations. In this paper, we propose an efficient similarity index that resolves the shortcomings of the existing measures of feature and structural similarity. This measure, called the Feature-Based Structural Measure (FSM), combines the best features of the well-known SSIM (structural similarity index measure) and FSIM (feature similarity index measure) approaches, striking a balance between performance for similar and dissimilar images of human faces. In addition to the statistical structural properties provided by SSIM, edge detection is incorporated in FSM as a distinctive structural feature. Its performance is tested for a wide range of PSNR (peak signal-to-noise ratio), using ORL (Olivetti Research Laboratory, now AT&T Laboratory Cambridge) and FEI (Faculty of Industrial Engineering, São Bernardo do Campo, São Paulo, Brazil) databases. The proposed measure is tested under conditions of Gaussian noise; simulation results show that the proposed FSM outperforms the well-known SSIM and FSIM approaches in its efficiency of similarity detection and recognition of human faces

Bilateral stellate neuroretinitis revealing a pheochromocytoma

Neuroretinitis (NR) is an inflammatory disorder characterized by optic disc  edema and subsequent formation of a macular star. We present a case of a 33 year old woman patient admitted for a progressive bilateral visual loss since two weeks. Fundus examination showed bilateral stellate neuroretinitis. Physical examination revealed a malignant hypertension of 210/150mmHg. Magnetic resonance imaging identified a left suprarenal mass, whereas urinary catecholamine level was abnormally high which supported a diagnosis of pheochromocytoma.The patient underwent a laparoscopic left suprarenal adrenalectomy after successful control of blood pressure. histopathologic examination confirmed the diagnosis of pheochromocytoma. Visual acuity was restored and the retinal alterations disappeared 7 months after surgery

Making sense of rework and its unintended consequence in projects: the emergence of uncomfortable knowledge

YesTo make sense of the rework phenomena that plagues construction projects a longitudinal exploration and mixed-method approach was undertaken to understand its causal setting and why it remained an on-going issue for organizations contracted to deliver an asset. The research reveals that rework was an zemblanity (i.e., being an unpleasant un-surprise) that resulted in: (1) project managers ignoring established organisation-wide procedures and, at their discretion, amend them to suit their own goals while denouncing the importance of recording and learning from non-conformances; (2) a deficiency of organisational controls and routines to contain and reduce rework; and (3) an absence of an organisation-project dyad that supported and promoted an environment of psychological safety. A new theoretical conceptualization of error causation that is intricately linked to rework and safety incidents is presented. The research provides managers with ‘uncomfortable knowledge’, which is needed to provide insights into the determinants of rework that form part of their everyday practice.Australian Research Council (DP130103018

Duplications of the critical Rubinstein-Taybi deletion region on chromosome 16p13.3 cause a novel recognisable syndrome

Background The introduction of molecular karyotyping technologies facilitated the identification of specific genetic disorders associated with imbalances of certain genomic regions. A detailed phenotypic delineation of interstitial 16p13.3 duplications is hampered by the scarcity of such patients. Objectives To delineate the phenotypic spectrum associated with interstitial 16p13.3 duplications, and perform a genotype-phenotype analysis. Results The present report describes the genotypic and phenotypic delineation of nine submicroscopic interstitial 16p13.3 duplications. The critically duplicated region encompasses a single gene, CREBBP, which is mutated or deleted in Rubinstein-Taybi syndrome. In 10 out of the 12 hitherto described probands, the duplication arose de novo. Conclusions Interstitial 16p13.3 duplications have a recognizable phenotype, characterized by normal to moderately retarded mental development, normal growth, mild arthrogryposis, frequently small and proximally implanted thumbs and characteristic facial features. Occasionally, developmental defects of the heart, genitalia, palate or the eyes are observed. The frequent de novo occurrence of 16p13.3 duplications demonstrates the reduced reproductive fitness associated with this genotype. Inheritance of the duplication from a clinically normal parent in two cases indicates that the associated phenotype is incompletely penetrant

Preliminary study on phosphate solubilizing Bacillus subtilis strain Q3 and Paenibacillus sp. strain Q6 for improving cotton growth under alkaline conditions

Background Low phosphorus availability limits crop production in alkaline calcareous soils in semi-arid regions including Pakistan. Phosphate solubilizing bacteria may improve crop growth on alkaline calcareous soils due to their ability to enhance P availability. Methods Twenty rhizobacterial isolates (Q1–Q20) were isolated from rhizosphere of cotton and characterized for their growth promoting attributes in vitro. The selected phosphate solubilizing isolates were further screened for their ability to improve cotton growth under axenic conditions (jar trial). The phosphorus solubilization capacities of selected strains were quantified and these strains were identified through 16S rDNA sequencing. Results Isolates Q2, Q3, Q6, Q7, Q8, Q13 and Q14 were able to solubilize phosphate from insoluble sources. Most of these isolates also possessed other traits including catalase activity and ammonia production. The growth promotion assay showed that Q3 was significantly better than most of the other isolates followed by Q6. Maximum root colonization (4.34 × 106 cfu g−1) was observed in case of isolate Q6 followed by Q3. The phosphorus solubilization capacities of these strains were quantified, showing a maximum phosphorus solubilization by Q3 (optical density 2.605 ± 0.06) followed by the Q6 strain. The strain Q3 was identified as Bacillus subtilis (accession # KX788864) and Q6 as Paenibacillus sp. (accession # KX788865) through 16S rDNA sequencing. Discussion The bacterial isolates varied in their abilities for different growth promoting traits. The selected PGPR Bacillus subtilis strain Q3 and Paenibacillus sp. strain Q6 have multifarious growth promoting traits including ability to grow at higher EC and pH levels, and phosphorus solubilizing ability. These strains can efficiently colonize cotton roots under salt affected soils and help plants in phosphorus nutrition. It is concluded that both strains are potential candidates for promoting cotton growth under alkaline conditions, however further investigation is required to determine their potential for field application