Devices and methods for analyzing and filtering light scattering data from a sample potentially containing a non-target compound

Abstract

Methods of analyzing and filtering light scattering data from a sample potentially containing a non-target compound, for example a contaminant. The presence of contaminants result in outliers in the scattering intensity data that increase both symmetry and width of photon counts obtained via analysis. After identification, various outliers are discarded to account for the non-target compounds and thereafter the remaining light scattering data is analyzed. Preferably, analyzing the light scattering data or photon counts involves determining a level to discard an outlier. In particular, the method includes the steps of identifying and quantifying the mode of photon count distribution and using the peak of the mode of distribution to eliminate outliers.

Claims

1. A method of analyzing and filtering light scattering data from a sample potentially containing a non-target compound, comprising the steps of: A) obtaining a sample solution comprising a biological material comprising a target compound, the target compound preferably able to one or more of precipitate from solution or dissolve in solution; B) performing a light scattering measurement on the sample solution and obtaining light scattering data; C) analyzing the light scattering data to determine if an outlier is present; D) when at least one outlier s present, discarding at least one outlier to account for the non-target compound, and; E) after step D), analyzing the remaining light scattering data, wherein analyzing the light scattering data to determine a level to discard the at least one outlier includes the steps of analyzing photon counts, identifying and quantifying the mode of the photon count distribution, defined as the most likely value to find in a sample of a given set of photon counts, and using the mode of the photon count distribution to eliminate the at least one outlier.

2. The method according to claim 1, further including the step of combining a test compound to be studied for one or more of an inhibiting and enhancing effect on one or more of precipitation and dissolution of the target compound.

3. The method according to claim 2, further including establishing a probability interval, preferably greater than or equal to 0.95, and/or less than or equal to 0.99 and the corresponding value of n is defined as the threshold, wherein the cumulative distribution function of $P\left(\alpha ,\beta ,n\right)\left(=1-\frac{\mathrm{Gamma}\left[\alpha ,\frac{n}{\beta }\right]}{\mathrm{Gamma}\left[\alpha \right]}\right)$ is used and any value of the time series above the threshold is discarded, wherein any remaining values are fit with P(α,β,n) to obtain a ‘true’ M and ncorresponding to coherent fluctuations and Brownian motion, wherein analyzing the photon counts distributions to determine a level to discard at least one outlier includes the steps of: power transforming the photon counts: y=n.sup.F, wherein F is a real number, wherein wherein analyzing the photon count distribution to determine a level to discard at least one outlier includes the steps of: power transforming the photon counts: y=n.sup.F, wherein F is a real number, wherein $P\left(\alpha ,\beta ,y\right)=\frac{e^{-\frac{y^{\frac{1}{F}}}{\beta }}{y}^{-1+\frac{\alpha }{F}}{\beta }^{-\alpha }}{F\mathrm{Gamma}\left[\alpha \right]}$ where Gamma[α] is the gamma function with argument α, a and β are $\alpha =\frac{M.Math.n.Math.}{M+.Math.n.Math.}\mathrm{and}\beta =\frac{M+.Math.n.Math.}{M};$ when (n)»M, α=M and $\beta =\frac{.Math.n.Math.}{M},$ the mode of this distribution is y=M.sup.−F(M (n)−F(M+(n))).sup.F, wherein when (n)» M» F, y=(n).sup.F, wherein F is chosen such that the skewness of the distribution of y becomes zero, and fitting a symmetric function against distribution of y determines the mode, wherein n is calculated from the mode, and thereafter fitting P(α,β,n) against a distribution of photon counts, constrained by knowing the value of (n), which is used to establish a probability interval, such as at least 0.95, or 0.99 value >0.95 and the corresponding value of n is defined as the threshold, wherein the cumulative distribution function of $P\left(\alpha ,\beta ,n\right)\left(=1-\frac{\mathrm{Gamma}\left[\alpha ,\frac{n}{\beta }\right]}{\mathrm{Gamma}\left[\alpha \right]}\right)$ is used and any value of the time series above the threshold is discarded.

4. The method according to claim 3, wherein performing the light scattering measurement utilizes static light scattering or dynamic light scattering.

5. The method according to claim 4, further including the step of observing, over a period of real-time, precipitation or dissolution of the target compound in the sample.

6. The method according to claim 5, wherein the target compound is one or more of heme, hemozoin, monosodium urate, a glass-like proteinaceous material, amyloid fibrils, crystallites, phosphate crystals, cholesterol, and Charcot-Leyden crystals.

7. The method according to claim 6, when the target compound is heme, and further including the step of initiating crystallization of heme by adding an initiator to the sample solution.

8. The method according to claim 2, wherein the biological material is one or more of blood, synovial fluid, tissue (including, but not limited to, brain, liver, muscle, kidney, gall bladder) and urine.

9. The method according to claim 1, further including establishing a probability interval, preferably greater than or equal to 0.95 and/or less than or equal to 0.99 and the corresponding value of n is defined as the threshold, wherein a cumulative distribution function of $P\left(\alpha ,\beta ,n\right)\left(=1-\frac{\mathrm{Gamma}\left[\alpha ,\frac{n}{\beta }\right]}{\mathrm{Gamma}\left[\alpha \right]}\right)$ is used and any value of the time series above the threshold is discarded.

10. The method according to claim 9, wherein any remaining values are fit with P(α,β,n) to obtain a ‘true’ M and (n) corresponding to coherent fluctuations and Brownian motion.

11. The method according to claim 10, wherein analyzing the photon count distributions to determine a level to discard the at least one outlier includes the steps of: power transforming the photon counts: y=n.sup.F, wherein F is a real number, wherein $P\left(\alpha ,\beta ,y\right)=\frac{e^{-\frac{y^{\frac{1}{F}}}{\beta }}{y}^{-1+\frac{\alpha }{F}}{\beta }^{-\alpha }}{F\mathrm{Gamma}\left[\alpha \right]}$ where Gamma[α] is the gamma function with argument α, a and β are $\alpha =\frac{M.Math.n.Math.}{M+.Math.n.Math.}\mathrm{and}\beta =\frac{M+.Math.n.Math.}{M};$ when (n)» M, α=M and $\beta =\frac{.Math.n.Math.}{M},$ the mode of this distribution is y=M.sup.−F(M (n)−F(M+(n))).sup.F, wherein when (n)» M» F, y=(n).sup.F, wherein F is chosen such that the skewness of the distribution of y becomes zero, and fitting a symmetric function against distribution of y determines the mode, wherein (n) is calculated from the mode, and thereafter fitting P(α,β,n) against a distribution of photon counts, constrained by knowing the value of n, which is used to establish a probability interval, such as at least 0.95, or 0.99≥value >0.95 and the corresponding value of n is defined as the threshold, wherein the cumulative distribution function of $P\left(\alpha ,\beta ,n\right)\left(=1-\frac{\mathrm{Gamma}\left[\alpha ,\frac{n}{\beta }\right]}{\mathrm{Gamma}\left[\alpha \right]}\right)$ is used and any value of the time series above the threshold is discarded.

12. The method according to claim 1, wherein the biological material is one or more of blood, synovial fluid, tissue (including, but not limited to, brain, liver, muscle, kidney, gall bladder) and urine.

13. The method according to claim 1, wherein performing the light scattering measurement utilizes static light scattering or dynamic light scattering.

14. The method according to claim 1, further including the step of observing, over a period of real-time, precipitation or dissolution of the target compound in the sample.

15. The method according to claim 14, wherein the target compound is one or more of heme, hemozoin, monosodium urate, a glass-like proteinaceous material, amyloid fibrils, crystallites, phosphate crystals, cholesterol, and Charcot-Leyden crystals.

16. The method according to claim 15, when the target compound is heme, and further including the step of initiating crystallization of heme by adding an initiator to the sample solution.

17. The method according to claim 15, wherein analyzing the data includes the step of determining if the test compound inhibits formation of at least one of heme, hemozoin, monosodium urate, a glass-like proteinaceous material, amyloid fibrils, crystallites, phosphate crystals, cholesterol, and Charcot-Leyden crystals.

18. The method according to claim 1, wherein the sample solution includes at least one test compound to be studied for the ability to inhibit precipitation or dissolution of a crystal that is one or more heme, hemozoin, monosodium urate, a glass-like proteinaceous material, amyloid fibrils, crystallites, phosphate crystals, cholesterol, and Charcot-Leyden crystals, and analyzing the data includes the step of observing an effect of the test compound on crystal precipitation or dissolution.

19. The method according to claim 1, wherein the non-target compound is an impurity, dust or a non-target substance.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

(1) The invention will be better understood and other features and advantages will become apparent by reading the detailed description of the invention, taken together with the drawings, wherein:

(2) FIG. 1 illustrates biocrystallization of heme through dimerization and self-assembly into hemozoin. The heme molecule has a planar structure, and produces centrosymmetric μ-propionate dimers to generate the basic unit of hemozoin crystals. Then, β-hematin is formed by reciprocal hydrogen bonds between carboxylic acid groups, forming a supramolecular polymer which self-assembles by regular π-stacking.

(3) FIG. 2 illustrates a) UV-Vis optical extinction spectrum of β-hematin suspended in water. To collect DDLS data, we used a laser wavelength of λ=660 nm, where light absorption is low. b) Stream of photon counts recorded consecutively at different scattering angles. c) The corresponding photon count distributions. d) The q.sup.2-dependence of the Brownian dynamics of the β-hematin crystals, determined from the photon counts. The data points define a straight line with a nonzero intercept. The solid line is the best linear fit that determines a hydrodynamic radius of R.sub.H=309±10 nm (estimate±standard error).

(4) FIG. 3 illustrates TEM micrographs of β-hematin samples. The scale-bars mark 500 nm.

(5) FIG. 4 illustrates a) The traces of photon counts recorded during recrystallization of β-hematin with and without CQ. b) A 30-second-long period of the photon count trace (with CQ) divided into three equal parts. c) The corresponding photon count distributions, and d) their first two raw moments.

(6) FIG. 5 illustrates: The crystallization kinetics of β-hematin without and in the presence of CQ. a) The natural logarithm of the mean scattering intensity as a function of crystallization time. b) The natural logarithm of the relaxation rate as a function of crystallization time. c) The natural logarithm of the hydrodynamic radius as a function of crystallization time. d) The natural logarithm of the relative number of β-hematin crystals: N=C.sub.with CQ/C.sub.wo CQ, where C denotes the concentration of the crystal nuclei formed without and in the presence of CQ. For the sake of clarity, the data points on each panel present the average of five measurements, and the error bars present the standard errors.

(7) FIG. 6 illustrates a schematic diagram of one embodiment of a device that can be utilized to perform the methods of the invention.

(8) FIG. 7 illustrates a flow diagram of a sequence of actions that can be utilized to perform the methods of the invention.

(9) FIG. 8 graphically illustrates identifying the mode of distribution and accounting for outliers.

(10) FIG. 9 illustrates various graphs wherein A represents good data, B represents outliers, and A∪B represents the union of good and outlier data. The goal is to retrieve the parameters of A, after running the algorithm on A∪B, and the corresponding PDFs. The level of noise is 30%.

(11) FIG. 10 is a graph illustrating the search for zero skewness via power transformation.

(12) FIG. 11 illustrates the power transform of A∪B, using F, and the corresponding symmetric distribution and Gaussian fit.

(13) FIG. 12 illustrates the fit A∪B using the mode-defined mean value (n), and defining the confidence interval.

(14) FIG. 13 illustrates filtering the time series, and fitting the corresponding PDF (green: original clean data, magenta: filtered colored data), wherein the analysis of the clean data (A) results in (M, n)=(10, 50522), and wherein the analysis of the data (A∪B) after the algorithm/filter results in (9.55, 51634).

(15) FIG. 14 is a flow chart showing one process used to identify, classify and remove one or more outliers.

DETAILED DESCRIPTION OF THE INVENTION

(16) In the following section, procedures and devices used to screen potential drugs, e.g. antimalarial drugs, are described. Variations in steps and/or components may be utilized by one of ordinary skill in the art.

(17) The methods of the present invention analyze statistical properties of light scattered from a given sample and identifies and removes one or more outliers in the light scattering data. In order to perform the methods of the present invention, a device or system that includes a coherent light source, a sample holder, a light collection device and a photon counter is obtained or fabricated, as known in the art. See FIG. 6 for one embodiment of a screening system of the present invention. In one embodiment, a sample in the sample holder is illuminated with the light source. Photons of the scattered light are coupled into the photon counter by the light collection device and counted at a desired angle, for example at 90° as illustrated in FIG. 6, perpendicular to the light source and perpendicular to the long axis of the sample holder. Photons are counted at a given integration time, consecutively for a period of time, for example about 10 seconds. Statistical properties of the obtained data are analyzed in order to describe crystallization.

(18) The light source preferably produces a spatially and temporally coherent light. In a preferred embodiment, the light source is a laser that produces a stable and collimated laser beam. In a preferred embodiment, the wavelength of the light is chosen so that the light absorption of the crystallizing substance is low. A suitable laser is available as a Cobolt 05-01 diode pumped solid state laser.

(19) The sample holder utilized in the present invention can accommodate single or multiple samples. The sample holder in one embodiment is a glass tube. Laminar flow (for example, in flow cells) can be used, where, ideally, the velocity vector of the flow is perpendicular to the plane defined by the axes of the laser beam and scattering (as indicated in FIG. 6). Other suitable sample holders allowing desired measurements to be performed on the solution can be utilized.

(20) The light collection device of the invention is utilized to couple scattered light into the photon counter. Light collection device can comprise an assembly of various optical lenses and fibers, a polarization filter/analyzer and collector. A suitable light spectrometer (3D LS Spectrometer) is available from LS Instruments AG, of Switzerland. Scattered light may be collected utilizing single-mode optical fibers equipped with integrated collimation optics and a laser-line filter corresponding to the wavelength of the laser. Depolarized scattering can be observed via cross-polarizes. In one embodiment, the incoming beam passes through an intensity filter, a polarizer, such as a Glan-Thomson polarizer with an extinction ratio of 10.sup.−6 and another Glan-Thompson polarizer with an extinction ratio of 10.sup.−6 is mounted in front of the collection optics as illustrated in FIG. 6.

(21) The photons are counted with a photon counter, such as an avalanche photo diode detector, for example a Single Photon Counting Module (SPCM-AQR) available from Perkin and Elmer. In one embodiment the photon counts are obtained at a sampling rate of 19 Hz, however the sampling rate may be varied on a wide range, typically between 10.sup.−6 and 1 s.

(22) FIG. 7 presents a flow diagram describing a sequence of actions relating to the manner of analyzing the statistical properties of the light scattered from a particular sample. The following steps can be utilized after the scattered light has been collected and coupled by optical means into the photon detector and counter. As set forth in box A, time-resolved sampling of photon counts can be performed with a given integration time (τ). Sampling of the photon counts may be continuous or intermittent. With intermittent sampling, multiplexing, for example between multiple scattering angles, can be performed.

(23) The data provided by sampling of photon counts is a set of non-negative integers. The elements of the set may be rearranged by permutation and subsets may be constructed by random combinations. The elements of such sets and subsets may or may not be summed and are analyzed in terms of expected accuracy and precision governed by the cardinality of the set/subsets (measure of the number of elements of the set). Such sets and subsets are analyzed regarding the shape of full count distribution and its statistical moments. Sets and subsets are analyzed in regard to anomalies and the presence of the outliers as described herein.

(24) As noted in box C, quantitative data or information from the sampling of photon counts is provided by the analysis described in boxes A and B. Information obtained may include one or more of i) the size and/or dimensions of the light scattering compound, ii) shape and/or morphology of the light scattering compound, and iii) concentration of the scattering compound; each as a function of time on the basis of the multiple measurements performed.

(25) As further characterized in box D, the physical properties of the light scattering compounds described in box C are used to derive quantitative information about kinetics, such as nucleation and growth rate of the light scattering compounds, assembly of the light scattering compounds from solution into a suspension/dispersion as well as disassembly or dissolution of the light scattering compounds from a suspension or dispersion into a solution.

(26) The steps performed on the scattered light and properties determined from the analysis thereof may be used, for example as described in box E, to quantitatively describe how the light scattering compound, which can be a molecular substance, particulate substance or material or a combination thereof, may or may not affect nucleation and growth, e.g. inhibit vs accelerate and thus assembly and/or disassembly kinetics.

(27) Hemozoin Crystallization Analysis

(28) The methods of the present invention are illustrated, using a specific, non-limiting embodiment, to determine the capacity of one or more compounds to inhibit the formation of hemozoin crystals. Successful compounds may be suitable candidates for use as antimalarial drugs.

(29) The screening process is started by obtaining a solution comprising heme.

(30) In one embodiment, heme is prepared by dissolving biocrystals resulting from heme dimerization and self-assembly as known in the art and described herein below in the example section. The solution must be of high optical transmittance, so that multiple light scattering occurs with a low probability. Concentration range of heme in solution can vary depending upon the technical parameters of the testing system or device utilized, for example light source power, sample holder size, etc.

(31) A desired quantity of the solution including heme is placed in a suitable sample holder described above.

(32) In a further step, one or more compounds to be tested for ability to inhibit formation of hemozoin crystals are combined with the sample solution including heme. The amount of the compound utilized can vary depending upon the arrangement of the testing device.

(33) Thereafter an initiator known in the art to be capable of initiating crystallization of heme to hemozoin is added to the sample solution. Acetic acid is utilized in one embodiment.

(34) The sample holder is placed in a desired location within the testing device. As described hereinabove, the light source illuminates the sample or samples in a sequential manner and the photons of the scattered light are coupled into the photon counter by the light collection assembly and counted. Thereafter, the statistical properties are analyzed in order to characterize the crystallization.

EXAMPLES

(35) Synthetic hemozoin (sHz) was purchased from InvivoGen (San Diego, Calif.) and was used as received. Sodium hydroxide (≥98%), chloroquine diphosphate salt (≥98%) (CQ), and acetic acid (≥99.7%) were purchased from Sigma Aldrich. sHz was suspended in ultrapure water. Ultrapure water was obtained from a Purelab Flex II (Veolia water system) with a resistance of 18.2 mΩ, and an LC208 purification pack. The ultrapure water was filtered with a Nylon 66 syringe filter with a pore size of 0.22 μm (BGB Analytik, Switzerland). 0.10 mg (0.15 mmol) of sHz were weighted in a glass vial and were suspended in 3 mL of the filtered water. To a standard cell culture glass tube, 3 mL of the filtered water were introduced, and 200 μL of the sHz suspension were added yielding a suspension with a concentration of 2.22 μg mL.sup.−1 (3.44 nmol mL.sup.−1). The suspension was sonicated for three minutes in a sonicator bath (Sonoswiss SW3) to yield a homogeneous suspension of non-aggregated crystals. The crystallization of hemozoin was achieved by employing the procedure described in Blauer, G.; Akkawi, M., On the preparation of β-haematin. Biochemical Journal 2000, 346 (2), 249-250, herein fully incorporated by reference..sup.22 Briefly, a stock solution of hemozoin was prepared by dissolving 0.10 mg (0.15 μmol) sHz in 1 mL of 0.4 M sodium hydroxide. The latter was diluted ten times in 0.4 M sodium hydroxide to generate a second stock solution. Individually, 0.7 mL of each stock solution was aliquoted into two different cell culture glass tubes. To each test tube, 0.62 mL of ultrapure water was added. The crystallization of heme to form hemozoin was initiated by the addition of 0.68 mL of acetic acid. The final pH of the solution was 2.9. To observe the influence of CQ in the crystallization kinetics, the same procedure as for the crystallization of isolated heme was employed, but pure acetic acid was substituted by a solution of 20.60 mg mL-1 (64.41 μmol mL-1) of CQ. The final CQ concentration in the crystallization reactions was 0.66 mg ml-1 (2.08 μmol mL-1).

(36) The UV-Vis measurement was performed on an Analytik Jena Specord 50 Plus spectrophotometer, using a disposable semi-micro poly(methyl methacrylate) cuvette (path length: 1 cm).

(37) Transmission electron microscopy (TEM) images were obtained using a FEI Tecnai Spirit at 120 kV. The images were recorded at a resolution of 2048×2048 pixels (Veleta CCD camera, Olympus). In the case of the imaging of hemozoin yielded from the crystallization reactions, the same conditions as in the DDLS experiments were employed. Then, the reaction volume was filtered with a syringe filter, and the filtrate was extensively washed with ultrapure water. Then, the crystals were retrieved by smearing the filter with 1 mL of ultrapure water. 5 μl of the hemozoin suspensions were drop-casted onto a carbon-film square mesh copper grid (Electron Microscopy Sciences, CF-300-Cu) and the solvent was allowed to dry overnight.

(38) Light scattering data were collected at constant temperature (21° C.) using a commercial goniometer instrument (3D LS Spectrometer, LS Instruments AG, Switzerland). The primary beam was formed by a linearly polarized and collimated laser beam (Cobolt 05-01 diode pumped solid state laser, λ=660 nm, P.sub.max=500 mW), and the scattered light was collected by single-mode optical fibers equipped with integrated collimation optics. With respect to the primary beam, depolarized scattering was observed via cross-polarizers. The incoming laser beam passed through a Glan-Thompson polarizer with an extinction ratio of 10.sup.−6, and another Glan-Thompson polarizer, with an extinction ratio of 10.sup.−8, was mounted in front of the collection optics. The collected light was coupled into an avalanche photo diode detector (Perkin Elmer, Single Photon Counting Module) via laser-line filters. The photon counts were obtained at a sampling rate of 19 Hz, which corresponded to an integration time of ˜0.05 s, and defined the lower limit of the available integration times.

(39) For the avoidance of doubt, the compositions of the present invention encompass all possible combinations of the components, including various ranges of said components, disclosed herein. It is further noted that the term “comprising” does not exclude the presence of other elements. However, it is to also be understood that a description of a product or composition comprising certain components also discloses a product consisting of said components. Similarly, it is also to be understood that a description of a process comprising certain steps also discloses a process consisting of the steps.

(40) In accordance with the patent statutes, the best mode and preferred embodiment have been set forth; the scope of the invention is not limited thereto, but rather by the scope of the attached claims.

REFERENCES

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