Antibody purification by concanavalin A affinity chromatography

Concanavalin A (Con A) immobilized poly(2‐hydroxyethyl methacrylate) (PHEMA) beads in a spherical form (100–150 μm in diameter) were used for the affinity chromatography purification of human immunoglobulin G (IgG) from aqueous solutions and human plasma. PHEMA adsorbents were prepared by suspension polymerization. Bioligand Con A was then immobilized by covalent binding onto PHEMA beads. The maximum IgG adsorption on the PHEMA/Con A beads was observed at pH 6.0. The nonspecific IgG adsorption onto the plain PHEMA adsorbents was very low (ca. 0.17 mg/g). Higher adsorption values (up to 54.3 mg/g) were obtained when the PHEMA/Con A beads were used from aqueous solutions. A higher adsorption capacity was observed for human plasma (up to 69.4 mg/g) with a purity of 82.5%. The adsorption capacities of other blood proteins were 2.0 mg/g for fibrinogen and 4.2 mg/g for albumin. The total protein adsorption was determined to be 76.0 mg/g. IgG molecules could be repeatedly adsorbed and desorbed with the PHEMA/Con A beads without noticeable loss in the IgG adsorption capacity. © 2005 Wiley Periodicals, Inc. J Appl Polym Sci 97: 1202–1208, 2005     

Adsorption of lead and copper on bentonite and grapeseed activated carbon in single- and binary-ion systems

In this study, bentonite originating from Turkey (Eski?ehir province) and activated carbon obtained from grapeseed were used as adsorbents for the removal of lead (Pb²⁺) and copper (Cu²⁺) ions from aqueous solutions. Experiments were performed in single- and binary-ion systems at constant temperature of 298 K and pH value of 5. In order to describe the adsorption mechanism Langmuir, Freundlich and Temkin isotherms were used. The total adsorption capacity values of adsorbents were compared. It was observed that the total adsorption capacity values were changed depending on the type of adsorbent used, type of metal ion and interaction between metal ions.     

Oriented immobilized anti-LDL antibody carrying poly(hydroxyethyl methacrylate) cryogel for cholesterol removal from human plasma

Low density lipoprotein (LDL) cholesterol is a major ingredient of the plaque that collects in the coronary arteries and causes coronary heart diseases. Among the methods used for the extracorporeal elimination of LDL from intravasal volume, immunoaffinity technique using anti-LDL antibody as a ligand offers superior selectivity and specificity. Proper orientation of the immobilized antibody is the main issue in immunoaffinity techniques. In this study, anti-human β-lipoprotein antibody (anti-LDL antibody) molecules were immobilized and oriented through protein A onto poly(2-hydroxyethyl methacrylate) (PHEMA) cryogel in order to remove LDL from hypercholesterolemic human plasma. PHEMA cryogel was prepared by free radical polymerization initiated with N,N,N′,N′-tetramethylene diamine (TEMED). PHEMA cryogel with a swelling degree of 8.89 g H₂O/g and 67% macro-porosity was characterized by swelling studies, scanning electron microscope (SEM) and blood compatibility tests. All the clotting times were increased when compared with control plasma. The maximum immobilized anti-LDL antibody amount was 63.2 mg/g in the case of random antibody immobilization and 19.6 mg/g in the case of oriented antibody immobilization (protein A loading was 57.0 mg/g). Random and oriented anti-LDL antibody immobilized PHEMA cryogels adsorbed 111 and 129 mg LDL/g cryogel from hypercholesterolemic human plasma, respectively. Up to 80% of the adsorbed LDL was desorbed. The adsorption–desorption cycle was repeated 6 times using the same cryogel. There was no significant loss of LDL adsorption capacity.     

Simultaneous MSMR and SSM/I observations and analysis of sea‐ice characteristics over the Antarctic region

Polar sea ice has been monitored quasi‐continuously over the last 30 years using passive microwave radiometers onboard three satellites in polar orbit, namely Nimbus‐5, Nimbus‐7 and Defense Meteorological Satellite Program (DMSP) series. A short overlap between Scanning Multichannel Microwave Radiometer (SMMR) on Nimbus‐7 and Special Sensor Microwave Imager (SSM/I) onboard DMSP allowed inter‐calibration of the two sensors leading to a consistent series of long‐term sea‐ice measurements since 1978. With the launch of Multifrequency Scanning Microwave Radiometer (MSMR) onboard OCEANSAT‐1 in the polar sun‐synchronous orbit during 1999, India developed the capability to monitor the polar sea ice on a regular basis. The concurrent availability of SSM/I and MSMR over the last few years presents a valuable opportunity to attempt an inter‐comparison of MSMR with SSM/I measurements and derived sea‐ice parameters.

In this paper, we present an indirect validation of the brightness temperatures (T _b) observed by MSMR with near‐simultaneous measurements from SSM/I over the Antarctic and Southern Polar Ocean regions. Simultaneous MSMR and SSM/I data from two contrasting seasons—summer and winter—for the 1999–2000 period have been used. Analysis includes a comparison of T _b scatterograms to achieve confidence in the quantitative use of the T _b data to derive various geophysical parameters, e.g. sea‐ice concentration and extent. Additionally, the T _b images produced by the two sensors are compared to establish the capability of MSMR in reliable two‐dimensional portrayal of all the sea and continental ice features over the Antarctic Region. Based on a regression analysis between MSMR observed T _b in different frequency channels and polarizations, and SSM/I‐derived sea‐ice concentration (SIC) values, we have developed algorithms to estimate SIC over the Southern Polar Ocean from MSMR data. The MSMR algorithms allow estimation of SIC with better than 10% rms error. MSMR SIC images faithfully capture the observed distribution of sea ice in all the sectors of the Southern Ocean both during summer and winter periods. Using the MSMR‐derived SIC, we have also derived monthly sea‐ice extent (SIE) estimates for a period extending for about 20 months from the beginning of the launch of MSMR. These estimates show excellent agreement with values derived from SSM/I. These analyses bring out the very high level of compatibility in the measurements and derived sea‐ice parameters produced by the two sensors.     

How accurately do drivers evaluate their own driving behavior? An on-road observational study

Self-assessment of driving skills became a noteworthy research subject in traffic psychology, since by knowing one's strenghts and weaknesses, drivers can take an efficient compensatory action to moderate risk and to ensure safety in hazardous environments. The current study aims to investigate drivers’ self-conception of their own driving skills and behavior in relation to expert evaluations of their actual driving, by using naturalistic and systematic observation method during actual on-road driving session and to assess the different aspects of driving via comprehensive scales sensitive to different specific aspects of driving. 19–63 years old male participants (N = 158) attended an on-road driving session lasting approximately 80 min (45 km). During the driving session, drivers’ errors and violations were recorded by an expert observer. At the end of the driving session, observers completed the driver evaluation questionnaire, while drivers completed the driving self-evaluation questionnaire and Driver Behavior Questionnaire (DBQ). Low to moderate correlations between driver and observer evaluations of driving skills and behavior, mainly on errors and violations of speed and traffic lights was found. Furthermore, the robust finding that drivers evaluate their driving performance as better than the expert was replicated. Over-positive appraisal was higher among drivers with higher error/violation score and with the ones that were evaluated by the expert as “unsafe”. We suggest that the traffic environment might be regulated by increasing feedback indicators of errors and violations, which in turn might increase the insight into driving performance. Improving self-awareness by training and feedback sessions might play a key role for reducing the probability of risk in their driving activity.     

A regularized pan-sharpening approach based on self-similarity and Gabor prior

In this article, we propose a new regularization-based approach for pan-sharpening based on the concepts of self-similarity and Gabor prior. The given low spatial resolution (LR) and high spectral resolution multi-spectral (MS) image is modelled as degraded and noisy version of the unknown high spatial resolution (HR) version. Since this problem is ill-posed, we use regularization to obtain the final solution. In the proposed method, we first obtain an initial HR approximation of the unknown pan-sharpened image using self-similarity and sparse representation (SR) theory. Using self-similarity, we obtain the HR patches from the given LR observation by searching for matching patches in its coarser resolution, thereby obtaining LR–HR pairs. An SR framework is used to obtain the patch pairs for which no matches are available for the patches in LR observation. The entire set of matched HR patches constitutes initial HR approximation (initial estimate) to the final pan-sharpened image which is used to estimate the degradation matrix as used in our model. A regularization framework is then used to obtain the final solution in which we propose to use a new prior which we refer as Gabor prior that extracts the bandpass details from the registered panchromatic (Pan) image. In addition, we also include Markov random field (MRF) smoothness prior that preserves the smoothness in the final pan-sharpened image. MRF parameter is derived using the initial estimate image. The final cost function consists of data fitting term and two prior terms corresponding to Gabor and MRF. Since the derived cost function is convex, simple gradient-based method is used to obtain the final solution. The efficacy of the proposed method is evaluated by conducting the experiments on degraded as well as on un-degraded datasets of three different satellites, i.e., Ikonos-2, Quickbird, and Worldview-2. The results are compared on the basis of traditional measures as well as recently proposed quality with no reference (QNR) measure, which does not require the reference image.     

Experimental and modeling study for the removal of formic acid through bulk ionic liquid membrane using response surface methodology

Abstract

In this study, formic acid removal from its aqueous solutions through bulk ionic liquid membrane (BILM) was investigated. Tributyl phosphate (TBP) as a carrier in imidazolium-based ionic liquids was used. D-optimal design based on response surface methodology has been applied to investigate the effect of various operating factors. Initial formic acid concentration, TBP concentration, and NaOH concentration were selected as numerical factors, and ionic liquid type was chosen as a categorical factor. The model equations were obtained to determine BILM process behavior. The removal efficiencies, represented by the extraction and stripping efficiencies, were calculated from the experimental data. The highest removal efficiencies were determined at higher concentration values of TBP and NaOH. All ionic liquids studied in this study had good transport selectivity for the removal of formic acid. The design study showed that BILM is an effective method for the removal of formic acid from the water.     

Enzymatic hydrolysis of cellulose part II: Population balance modelling of hydrolysis by exoglucanase and universal kinetic model

In this work, a concise review on enzymatic hydrolysis of cellulose by endoglucanase is presented. In addition a novel population balance based kinetic model for the action of endoglucanase has been developed. One important feature in the proposed model is a new approach to consider the evolution of cellulose chain length. In addition, a new mechanism for hydrolysis of cellulose by endoglucanase is proposed in which bond breakage is a function of position in the chain as well as the susceptibility to enzymatic attack. In the first part, the focus is on developing a mechanistic model for the action of endoglucanase and then in part II a mechanistic model for the action of exoglucanase has been developed together with a holistic model considering all the major steps involved in enzymatic hydrolysis. In the case of endoglucanase action, the model prediction is very close to the experimental results presented by Kurakake et al. [12]. Using the estimated values for the parameters (confidence interval = 98%), the evolution of size distribution for cellulose polymers during the course of hydrolysis has been presented.