Selective and Continuous Oil Removal from Oil-Water Mixtures Using a Superhydrophobic and Superoleophilic Stainless Steel Mesh Tube.

The development of continuous oil-water separation processes has applications in the treatment of industrial oily wastewater and effective management of oil spills. In this research, the performance of a superhydrophobic-superoleophilic (SHSO) membrane in oil-water separation is investigated through dynamic tests. We investigate the effects of the total flow rate and oil concentration on the separation efficiency using an as-fabricated SHSO mesh tube. To construct the SHSO membrane, a tubular stainless steel mesh is dip-coated into a solution, containing a long-chain alkyl silane (Dynasylan F8261) and functionalized silica nanoparticles (AEROSIL R812). The as-prepared SHSO mesh tube illustrates a water contact angle of 164° and an oil contact angle of zero for hexane. A maximum oil separation efficiency (SE) of 97% is obtained when the inlet oil-water mixture has the lowest flow rate (5 mL/min) with an oil concentration of 10 vol %, while the minimum oil SE (86%) is achieved for the scenario with the highest total flow rate (e.g., 15 mL/min) and the highest oil concentration (e.g., 50 vol %). The water SE of about 100% in the tests indicates that the water separation is not affected by the total flow rate and oil concentration, due to the superhydrophobic state of the fabricated mesh. The clear color of water and oil output streams also reveals the high SE of both phases in dynamic tests. The outlet oil flux increases from 314 to 790 (L/m2·h) by increasing the oil permeate flow rate from 0.5 to 7.5 (mL/min). The linear behavior of the cumulative amounts of collected oil and water with time demonstrates the high separation performance of a single SHSO mesh, implying no pore blocking during dynamic tests. The significant oil SE (97%) of the fabricated SHSO membrane with robust chemical stability shows its promising potential for industrial-scale oil-water separation applications.

Investigation of the effects of oxidative stress-inducing factors on culturing and productivity of Bordetella pertussis.

The stress response of Bordetella pertussis during fermentation was assessed by means of fluorescence-based techniques. During the manufacturing of vaccines, B. pertussis is subjected to stress during adaptation to a new environment and operating conditions in the bioreactor, which can have harmful consequences on growth and protein yield. In this study, stress was imposed by varying the percentage of dissolved oxygen (DO) and inoculum size, and by adding rotenone and hydrogen peroxide. In this study, fluorescence spectroscopy is used as a tool for measuring oxidative stress. High levels of DO during fed-batch operation had no detrimental effect on growth, but the specific productivity of pertactin (PRN) decreased. Cultures that were started with an inoculum size that was 10 times smaller than the control resulted in significantly less PRN as compared to controls where reduction was more significant in flasks as compared to bioreactors. A comparison of filtered to heat-sterilized media revealed that filtered media offered a protective effect against H2 O2 . Heat sterilization of the media might result in the destruction of components that offer protection against oxidative stress. Nonetheless, filter sterilization on its own would be insufficient for large-scale manufacturing. It should be emphasized that the effects of these stressors while investigating for other microorganisms have not been studied for B. pertussis.

Towards real-time detection of wastewater in surface waters using fluorescence spectroscopy.

The presence of municipal wastewater at the intake of a major drinking water treatment facility located on Lake Ontario was examined using fluorescence data collected during a period of continuous monitoring. In addition, controlled mixing of lake water and wastewater sampled from a local treatment facility were conducted using a bench-scale fluorescence system to quantify observed changes in natural organic matter. Multivariate linear regression was applied to components derived from parallel factors analysis. The resulting mean absolute error for predicted wastewater level was 0.22% (V/V, wastewater/lake water), indicating that wastewater detection at below 1.0% (V/V) was possible. Analyses of sucralose, a wastewater indicator, were conducted for treated wastewater as well as surface water collected at two intake locations on Lake Ontario. Results suggested minimal wastewater contribution at the drinking water intake. A wastewater detection model using a moving baseline was developed and applied to continuous fluorescence data collected at one of the drinking water intakes, which agreed well with sucralose results. Furthermore, the simulated addition of 1.0% (V/V) of wastewater/wastewater was detectable in 89% of samples analyzed, demonstrating the utility of fluorescence-based wastewater monitoring.

Functional properties of navy bean (Phaseolus vulgaris) protein concentrates obtained by pneumatic tribo-electrostatic separation.

A sustainable, chemical-free dry tribo-electrostatic separation approach was employed to fractionate navy bean flour. The resulting protein-enriched fractions had 36-38% protein on a moisture free basis, accounting for 43% of the total available protein. SDS-PAGE analysis of the dry-enriched protein fractions showed a similar protein profile to that of the original navy bean flour. The functional properties of these fractions were examined and compared with the commercial soybean protein concentrate as well as navy bean protein isolate obtained by a conventional wet fractionation process. These electrostatically separated protein fractions exhibited superior solubility at their intrinsic pH as well as superior emulsion stability (ES), foam expansion (FE) and foam volume stability (FVS) compared to the wet-fractionated navy bean protein isolate that was almost depleted of albumins, exhibiting poor solubility and foaming properties. These results suggest electrostatic separation as a promising route to deliver functional protein concentrates as novel food formulation ingredients.

New insight into the allosteric effect of L-tyrosine on mushroom tyrosinase during L-dopa production.

Kinetics studies of L-tyrosine (LTy) ortho-hydroxylation by mushroom tyrosinase (MT) confirmed that MT was severely, but not completely, inhibited at higher concentrations of LTy. Despite the availability of the crystal structure reports, no allosteric site has been identified on MT. To examine the assumption that a non-specific binding site works as a regulatory site, docking simulations were run for the second molecule of L-tyrosine (LTy2) on the complexes of the first L-tyrosine molecule (LTy1) with the heavy chain (H) of MT (LTy1/HMT) and its dimer with the light chain (Ty1/LHMT). In both, LTy2 occupied a non-specific binding site (MTPc). MD simulations revealed LTy2/HMT/LTy1 and LTy2/LHMT/LTy1 were stable. Binding free-energy analysis supported the formation of LTy2/HMT/LTy1 and LTy2/LHMT/LTy1 at higher concentrations of LTy and disclosed the importance of ΔEelec and ΔGpolar during binding of LTy2 to MTPc. Upon LTy2 binding to MTPc, the Cu-Cu distance remained unchanged while the spatial position of LTy1 in the active site (MTPa) changed so that it would not be able to participate in ortho-hydroxylation. This study suggests a tuning role for L chain during binding of the ligands to MTPa and MTPc. Given these results, a plausible mechanism was proposed for the MT substrate inhibition.

Neural networks for dimensionality reduction of fluorescence spectra and prediction of drinking water disinfection by-products.

The use of fluorescence data coupled with neural networks for improved predictability of drinking water disinfection by-products (DBPs) was investigated. Novel application of autoencoders to process high-dimensional fluorescence data was related to common dimensionality reduction techniques of parallel factors analysis (PARAFAC) and principal component analysis (PCA). The proposed method was assessed based on component interpretability as well as for prediction of organic matter reactivity to formation of DBPs. Optimal prediction accuracies on a validation dataset were observed with an autoencoder-neural network approach or by utilizing the full spectrum without pre-processing. Latent representation by an autoencoder appeared to mitigate overfitting when compared to other methods. Although DBP prediction error was minimized by other pre-processing techniques, PARAFAC yielded interpretable components which resemble fluorescence expected from individual organic fluorophores. Through analysis of the network weights, fluorescence regions associated with DBP formation can be identified, representing a potential method to distinguish reactivity between fluorophore groupings. However, distinct results due to the applied dimensionality reduction approaches were observed, dictating a need for considering the role of data pre-processing in the interpretability of the results. In comparison to common organic measures currently used for DBP formation prediction, fluorescence was shown to improve prediction accuracies, with improvements to DBP prediction best realized when appropriate pre-processing and regression techniques were applied. The results of this study show promise for the potential application of neural networks to best utilize fluorescence EEM data for prediction of organic matter reactivity.

Characterization of UF foulants and fouling mechanisms when applying low in-line coagulant pre-treatment.

Fluorescence spectroscopy was used as a characterization method to examine organic fouling of single ultrafiltration (UF) fibres at bench-scale. Low doses of coagulant were applied to modify organic properties, without significant formation of precipitates. This approach compliments previous studies investigating coagulation as a pre-treatment method for UF fouling control, which have principally focused on reduction of foulant concentrations. Using a continuous system, short time-scale fluorescence results demonstrated significant adsorption of humic components to virgin membrane fibres. Following an initial adsorption phase, protein-like material was the only organic component to be significantly removed by UF. Low doses of coagulant (<1 mg/L as alum; < 0.043 mg/L as Al3+) were observed to significantly reduce irreversible fouling rates for two different surface waters. Paralleling reduced irreversible fouling, surface tryptophan fluorescence resulting from material adsorbed to the fouled membrane increased, as measured using a fibre optic probe. Analysis of peak shifts in the protein-like component revealed a red-shift at low coagulant dose, possibly indicative of greater exposure of tryptophan residues resulting from conformational changes in the protein structure. It is hypothesized that low coagulant doses modified membrane-foulant interactions, resulting in increased adsorption of protein-like matter to the surface. Subsequent interactions of bulk foulants with the adsorbed organic monolayer discouraged further adsorption and reduced irreversible fouling potential.

Investigation of ozone and peroxone impacts on natural organic matter character and biofiltration performance using fluorescence spectroscopy.

Impacts of ozonation alone as well as an advanced oxidation process of ozone plus hydrogen peroxide (H2O2 + O3) on organic matter prior to and following biofiltration were studied at pilot-scale. Three biofilters were operated in parallel to assess the effects of varying pre-treatment types and dosages. Conventionally treated water (coagulation/flocculation/sedimentation) was fed to one control biofilter, while the remaining two received water with varying applied doses of O3 or H2O2 + O3. Changes in organic matter were characterized using parallel factors analysis (PARAFAC) and fluorescence peak shifts. Intensities of all PARAFAC components were reduced by pre-oxidation, however, individual humic-like components were observed to be impacted to varying degrees upon exposure to O3 or H2O2 + O3. While the control biofilter uniformly reduced fluorescence of all PARAFAC components, three of the humic-like components were produced by biofiltration only when pre-oxidation was applied. A fluorescence red shift, which occurred with the application of O3 or H2O2 + O3, was attributed to a relative increase in carbonyl-containing components based on previously reported results. A subsequent blue shift in fluorescence caused by biofiltration which received pre-oxidized water indicated that biological treatment readily utilized organics produced by pre-oxidation. The results provide an understanding as to the impacts of organic matter character and pre-oxidation on biofiltration efficiency for organic matter removal.

Investigation of fluorescence methods for rapid detection of municipal wastewater impact on drinking water sources.

Fluorescence spectroscopy as a means to detect low levels of treated wastewater impact on two source waters was investigated using effluents from five wastewater facilities. To identify how best to interpret the fluorescence excitation-emission matrices (EEMs) for detecting the presence of wastewater, several feature selection and classification methods were compared. An expert supervised regional integration approach was used based on previously identified features which distinguish biologically processed organic matter including protein-like fluorescence and the ratio of protein to humic-like fluorescence. Use of nicotinamide adenine dinucleotide-like (NADH) fluorescence was found to result in higher linear correlations for low levels of wastewater presence. Parallel factors analysis (PARAFAC) was also applied to contrast an unsupervised multiway approach to identify underlying fluorescing components. A humic-like component attributed to reduced semiquinone-like structures was found to best correlate with wastewater presence. These fluorescent features were used to classify, by volume, low (0.1-0.5%), medium (1-2%), and high (5-15%) levels by applying support vector machines (SVMs) and logistic regression. The ability of SVMs to utilize high-dimensional input data without prior feature selection was demonstrated through their performance when considering full unprocessed EEMs (66.7% accuracy). The observed high classification accuracies are encouraging when considering implementation of fluorescence spectroscopy as a water quality monitoring tool. Furthermore, the use of SVMs for classification of fluorescence data presents itself as a promising novel approach by directly utilizing the high-dimensional EEMs.

Kinetics of natural organic matter (NOM) removal during drinking water biofiltration using different NOM characterization approaches.

To better understand biofiltration, concentration profiles of various natural organic matter (NOM) components throughout a pilot-scale drinking water biofilter were investigated using liquid chromatography - organic carbon detection (LC-OCD) and fluorescence excitation and emission matrices (FEEM). Over a 2 month period, water samples were collected from six ports at different biofilter media depths. Results showed substantial removal of biopolymers (i.e. high molecular weight (MW) NOM components as characterized by LC-OCD) and FEEM protein-like materials, but low removal of humic substances, building blocks and low MW neutrals and low MW acids. For the first time, relative biodegradability of different NOM components characterized by LC-OCD and FEEM approaches were investigated across the entire MW range and for different fluorophore compositions, in addition to establishing the biodegradation kinetics. The removal kinetics for FEEM protein-like materials were different than for the LC-OCD-based biopolymers, illustrating the complementary nature of the LC-OCD and FEEM approaches. LC-OCD biopolymers (both organic carbon and organic nitrogen) and FEEM protein-like materials were shown to follow either first or second order biodegradation kinetics. Due to the low percent removal and small number of data points, the performance of three kinetic models was not distinguishable for humic substances. Pre-filtration of samples for FEEM analyses affected the removal behaviours and/or kinetics especially of protein-like materials which was attributed to the removal of the colloidal/particulate materials.

Physicochemical characterization of a navy bean (Phaseolus vulgaris) protein fraction produced using a solvent-free method.

A solvent-free electrostatic separation method was employed to separate navy bean flour (NBF) into protein-rich (PR) and starch-rich (SR) fractions. The physicochemical properties of NBF and separated fractions were compared to proteins (navy bean isolate (NBI) and 7S globulin) prepared using a wet process. Gel electrophoresis confirmed that the protein distribution in the isolated fractions was similar to that of NBF. The protein profile of NBI and 7S globulin was found to be devoid of certain proteins that were found in the NBF and PR fraction. Amino acid analysis revealed that the NBI and 7S globulin had a lower content of sulfur-containing amino acids compared to NBF and the electrostatically isolated fractions. CD and fluorescence spectroscopy confirmed that denaturation of the proteins during the acid precipitation is likely. This novel solvent-free electrostatic separation process preserves the native protein structure found in NBF and improves the recovery of some of the smaller MW proteins.

Fluorescence spectroscopy for monitoring reduction of natural organic matter and halogenated furanone precursors by biofiltration.

The application of fluorescence spectroscopy to monitor natural organic matter (NOM) reduction as a function of biofiltration performance was investigated. This study was conducted at pilot-scale where a conventional media filter was compared to six biofilters employing varying enhancement strategies. Overall reductions of NOM were identified by measuring dissolved organic carbon (DOC), and UV absorbance at 254 nm, as well as characterization of organic sub-fractions by liquid chromatography-organic carbon detection (LC-OCD) and parallel factors analysis (PARAFAC) of fluorescence excitation-emission matrices (FEEM). The biofilter using granular activated carbon media, with exhausted absorptive capacity, was found to provide the highest removal of all identified PARAFAC components. A microbial or processed humic-like component was found to be most amenable to biodegradation by biofilters and removal by conventional treatment. One refractory humic-like component, detectable only by FEEM-PARAFAC, was not well removed by biofiltration or conventional treatment. All biofilters removed protein-like material to a high degree relative to conventional treatment. The formation potential of two halogenated furanones, 3-chloro-4(dichloromethyl)-2(5H)-furanone (MX) and mucochloric acid (MCA), as well as overall treated water genotoxicity are also reported. Using the organic characterization results possible halogenated furanone and genotoxicity precursors are identified. Comparison of FEEM-PARAFAC and LC-OCD results revealed polysaccharides as potential MX/MCA precursors.

Rapid and direct spectrophotometric method for kinetics studies and routine assay of peroxidase based on aniline diazo substrates.

Peroxidases are ubiquitous enzymes that play an important role in living organisms. Current spectrophotometrically based peroxidase assay methods are based on the production of chromophoric substances at the end of the enzymatic reaction. The ambiguity regarding the formation and identity of the final chromophoric product and its possible reactions with other molecules have raised concerns about the accuracy of these methods. This can be of serious concern in inhibition studies. A novel spectrophotometric assay for peroxidase, based on direct measurement of a soluble aniline diazo substrate, is introduced. In addition to the routine assays, this method can be used in comprehensive kinetics studies. 4-[(4-Sulfophenyl)azo]aniline (λmax = 390 nm, ɛ = 32 880 M(-1) cm(-1) at pH 4.5 to 9) was introduced for routine assay of peroxidase. This compound is commercially available and is indexed as a food dye. Using this method, a detection limit of 0.05 nmol mL(-1) was achieved for peroxidase.

Intrinsic fluorescence-based at situ soft sensor for monitoring monoclonal antibody aggregation.

Intrinsic fluorescence spectroscopy, in conjunction with partial least squares regression (PLSR), was investigated as a potential technique for online quality control and quantitative monitoring of Immunoglobulin G (IgG) aggregation that occurs following exposure to conditions that emulate those that can occur during protein downstream processing. Initially, the impact of three stress factors (temperature, pH, and protein concentration) on the degree of aggregation determined using size exclusion chromatography data, was investigated by performing a central composite designexperiment and applying a fitting response surface model. This investigation identified the influence of the factors as well as the operating regions with minimum propensity to induce protein aggregation. Spectral changes pertinent to the stressed samples were also investigated and found to corroborate the high sensitivity of the intrinsic fluorescence to conformational changes of the proteins under study. Ultimately, partial least squares regression was implemented to formulate two fluorescence-based soft sensors for quality control--product classification--and quantitative monitoring--concentration of monomer. The resulting regression models exhibited accurate prediction ability and good potential for in situ monitoring of monoclonal antibody downstream purification processes.

Development of a soft-sensor based on multi-wavelength fluorescence spectroscopy and a dynamic metabolic model for monitoring mammalian cell cultures.

A soft-sensor based on an Extended Kalman Filter (EKF) that combines data obtained using a fluorescence-based soft-sensor with a dynamic mechanistic model, was investigated as a tool for continuous monitoring of a Chinese hamster ovary (CHO) cell cultivation process. A standalone fluorescence based soft-sensor, which uses a combination of an empirical multivariate statistical model and measured spectra, was designed for predicting key culture variables including viable and dead cells, recombinant protein, glucose, and ammonia concentrations. The standalone fluorescence sensor was then combined with a dynamic mechanistic model within an EKF framework, for improving the prediction accuracy and generating predictions in-between sampling instances. The dynamic model used for the EKF framework was based on a structured metabolic flux analysis and mass balances. In order to calibrate the fluorescence-based empirical model and the dynamic mechanistic model, cells were grown in batch mode with different initial glucose and glutamine concentrations. To mitigate the uncertainty associated with the model structure and parameters, non-stationary disturbances were accounted for in the EKF by parameter-adaptation. It was demonstrated that the implementation of the EKF along with the dynamic model could improve the accuracy of the fluorescence-based predictions at the sampling instances. Additionally, it was shown that the major advantage of the EKF-based soft-sensor, compared to the standalone fluorescence-based counterpart, was its capability to track the temporal evolution of key process variables between measurement instances obtained by the fluorescence-based soft-sensor. This is crucial for designing control strategies of CHO cell cultures with the aim of guaranteeing product quality.

Fluorescence-based soft sensor for at situ monitoring of Chinese hamster ovary cell cultures.

Multi-wavelength fluorescence spectroscopy was investigated as a potential tool for use in monitoring key process variables that include: viable and dead cells, recombinant protein, glucose, and ammonia concentrations for Chinese hamster ovary (CHO) cells during cultivation.For the purpose of calibrating the fluorescence-based empirical model, cells were grown in batch mode with different initial glucose and glutamine concentrations.Spectrofluorometer settings were optimized to ensure reproducibility and accuracy of the acquired spectra. With the purpose of gaining qualitative insight into the evolution of the spectra, the trajectories of individual fluorophore peaks were studied during the cultivation process. Spectral changes related to biomass and secreted proteins were investigated by comparing the spectra at various stages during the downstream processing. A partial least square regression (PLSR) was used to formulate empirical models that related the input data set, i.e., the fluorescence excitation-emission matrix, to the actual state of the system including viable cell and dead cells and recombinant protein, glucose, and ammonia concentrations. The models exhibited accurate prediction ability for the process variables of interest.

Pilot-scale investigation of drinking water ultrafiltration membrane fouling rates using advanced data analysis techniques.

A pilot-scale investigation of the performance of biofiltration as a pre-treatment to ultrafiltration for drinking water treatment was conducted between 2008 and 2010. The objective of this study was to further understand the fouling behaviour of ultrafiltration at pilot scale and assess the utility of different foulant monitoring tools. Various fractions of natural organic matter (NOM) and colloidal/particulate matter of raw water, biofilter effluents, and membrane permeate were characterized by employing two advanced NOM characterization techniques: liquid chromatography - organic carbon detection (LC-OCD) and fluorescence excitation-emission matrices (FEEM) combined with principal component analysis (PCA). A framework of fouling rate quantification and classification was also developed and utilized in this study. In cases such as the present one where raw water quality and therefore fouling potential vary substantially, such classification can be considered essential for proper data interpretation. The individual and combined contributions of various NOM fractions and colloidal/particulate matter to hydraulically reversible and irreversible fouling were investigated using various multivariate statistical analysis techniques. Protein-like substances and biopolymers were identified as major contributors to both reversible and irreversible fouling, whereas colloidal/particulate matter can alleviate the extent of irreversible fouling. Humic-like substances contributed little to either reversible or irreversible fouling at low level fouling rates. The complementary nature of FEEM-PCA and LC-OCD for assessing the fouling potential of complex water matrices was also illustrated by this pilot-scale study.

Effect of gold nanoparticles and ciprofloxacin on microbial catabolism: a community-based approach.

The effect of gold nanoparticles (AuNPs) and ciprofloxacin on the catabolism of microbial communities was assessed. This was accomplished through an ex situ methodology designed to give a priori knowledge on the potential for nanoparticles, or other emerging contaminants, to affect the catabolic capabilities of microbial communities in the environment. Microbial communities from a variety of sources were incubated with 31 prespecified carbon sources and either National Institute of Standards and Technology reference material 10-nm AuNPs or ciprofloxacin on 96-well microtiter plates. From the ciprofloxacin study, dose-response curves were generated and exemplified how this method can be used to assess the effect of a toxicant on overall catabolic capabilities of microbial communities. With 10-nm AuNPs at concentrations ranging from 0.01 µg/mL to 0.5 µg/mL, rhizosphere communities from Typha roots were only slightly catabolically inhibited at a single concentration (0.05 µg/mL); no effects were seen on wetland water communities, and a minor positive (i.e., enhanced catabolic capabilities) effect was observed for loamy soil communities. This positive effect might have been because of a thin layer of citrate found on these AuNPs that initiated cometabolism with some of the carbon sources studied. Under the conditions considered, the possible adverse effects of AuNPs on the catabolic capabilities of microbial communities appears to be minimal.

Comparison of the catabolic activity and catabolic profiles of rhizospheric, gravel-associated and interstitial microbial communities in treatment wetlands.

Microbial communities play a critical role in degrading organic contaminants in treatment wetlands; however, an understanding of the different roles played by rhizospheric, gravel-associated and interstitial microbial communities is deficient due to a lack of data directly comparing these microbial communities. Community level physiological profiling (CLPP) was used to compare the catabolic capabilities of rhizospheric, gravel-associated and interstitial microbial communities in vertical-flow planted and unplanted wetland mesocosms. Wetland mesocosms were decommissioned to gather microbial community samples associated with the roots and gravel bed media taken from the top (10 cm depth), middle (30 cm depth) and bottom (60 cm depth). The catabolic capabilities of the rhizospheric microbial communities were seen to be much greater than those of the gravel-associated communities. A decrease in catabolic capability was seen with increasing depth, suggesting that communities near the surface play a larger role in the degradation of carbon-based compounds. A general difference in catabolic profiles based on plant presence/absence was observed for the interstitial water and all gravel-associated samples at all depths, suggesting that the presence of roots within part of the mesocosm not only has a localized effect on the attached microbial population, but also on gravel-associated microbial communities throughout the mesocosms.

Characterizing natural colloidal/particulate-protein interactions using fluorescence-based techniques and principal component analysis.

Characterization of the interactions between natural colloidal/particulate- and protein-like matter is important for understanding their contribution to different physiochemical phenomena like membrane fouling, adsorption of bacteria onto surfaces and various applications of nanoparticles in nanomedicine and nanotoxicology. Precise interpretation of the extent of such interactions is however hindered due to the limitations of most characterization methods to allow rapid, sensitive and accurate measurements. Here we report on a fluorescence-based excitation-emission matrix (EEM) approach in combination with principal component analysis (PCA) to extract information related to the interaction between natural colloidal/particulate- and protein-like matter. Surface plasmon resonance (SPR) analysis and fiber-optic probe based surface fluorescence measurements were used to confirm that the proposed approach can be used to characterize colloidal/particulate-protein interactions at the physical level. This method has potential to be a fundamental measurement of these interactions with the advantage that it can be performed rapidly and with high sensitivity.