METHOD FOR CALCULATING THE CHANGE OF TEMPORAL SIGNALS

Abstract

The present invention relates to a method for calculating the change of signals starting from the originally detected temporal signals (_102 ), comprising the following steps: (a) eliminating the drift in the originally detected temporal signals with time to get .sub.i signals; (b) removing the xi signals existing outside the range of 80% to 120% of the averaged value of all the .sub.i signals to get residual signals as x .sub.2 signals; (c) dividing the .sub.2 signals into 14-100 sections; (d) finding the averaged value of the .sub.2 signals in each section to get .sub.3 signals; (e) optionally neglecting one or two of the first .sub.3 signals and selecting six to nine .sub.3 signals with the smallest value of standard deviation in initial sections, wherein the initial sections are the first one-fourth part to half part of all sections; (f) eliminating the drift in the selected .sub.3 signals of step (e) with time to get .sub.4 signals; (g) selecting six to nine .sub.3 signals with the smallest value of standard deviation in terminal sections, wherein the terminal sections are the last one-fourth part to half part of all sections; (h) eliminating the drift in the selected .sub.3 signals of step (g) with time to get .sub.5 signals; and (i) finding the difference between the mean values of the .sub.4 and .sub.5 signals.

Claims

1. A method for calculating the change of signals starting from the originally detected temporal signals (), comprising the following steps: (a) eliminating the drift in the originally detected temporal signals with time to get .sub.i signals; (b) removing the .sub.i signals existing outside the range of 80% to 120% of the averaged value of all the .sub.i signals to get residual signals as .sub.2 signals; (c) dividing the .sub.2 signals into 14-100 sections; (d) finding the averaged value of the .sub.2 signals in each section to get .sub.3 signals; (e) optionally neglecting one or two of the first .sub.3 signals and selecting six to nine .sub.3 signals with the smallest value of standard deviation in initial sections, wherein the initial sections are the first one-fourth part to half part of all sections; (f) eliminating the drift in the selected .sub.3 signals of step (e) with time to get .sub.4 signals; (g) selecting six to nine .sub.3 signals with the smallest value of standard deviation in terminal sections, wherein the terminal sections are the last one-fourth part to half part of all sections; (h) eliminating the drift in the selected .sub.3 signals of step (g) with time to get .sub.5 signals; and (i) finding the difference between the mean values of the .sub.4 and .sub.5 signals.

2. The method of claim 1, wherein the temporal signals are time dependent ac magnetic signals.

3. The method of claim 1, wherein the change of signals is the reduction in ac magnetic susceptibility of materials.

4. The method of claim 1, wherein the steps of eliminating the drift in the signals with time are done by subtracting each signal by the value lying in the correspondingly linear function.

5. The method of claim 1, wherein the step (b) is removing the .sub.1 signals existing outside the range of 90% to 110% of the averaged value of all the .sub.1 signals to get residual signals as .sub.2 signals.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

[0004] FIG. 1A: The ac magnetic susceptibility of reagent before nanoparticle-bio-molecule associations.

[0005] FIG. 1B: The ac magnetic susceptibility of reagent after nanoparticle-bio-molecule associations.

[0006] FIG. 2: Time dependent ac magnetic susceptibility .sub.ac of reagent mixing with a detected sample.

[0007] FIG. 3: Time dependent ac magnetic susceptibility .sub.ac,2 of reagent mixing with a detected sample.

[0008] FIG. 4: Time dependent ac magnetic susceptibility .sub.ac,3 of reagent mixing with a detected sample.

[0009] FIG. 5: Time dependent ac magnetic susceptibility .sub.ac,4 and .sub.ac,5 of reagent at initials and terminals after mixing with a detected sample.

SUMMARY OF THE INVENTION

[0010] The present invention relates to a method for calculating the change of signals starting from the originally detected temporal signals (), comprising the following steps: (a) eliminating the drift in the originally detected temporal signals with time to get .sub.1 signals; (b) removing the xi signals existing outside the range of 80% to 120% of the averaged value of all the .sub.1 signals to get residual signals as .sub.2 signals; (c) dividing the .sub.2 signals into 14-100 sections; (d) finding the averaged value of the .sub.2 signals in each section to get .sub.3 signals; (e) optionally neglecting one or two of the first .sub.3 signals and selecting six to nine .sub.3 signals with the smallest value of standard deviation in initial sections, wherein the initial sections are the first one-fourth part to half part of all sections; (f) eliminating the drift in the selected .sub.3 signals of step (e) with time to get .sub.4 signals; (g) selecting six to nine .sub.3 signals with the smallest value of standard deviation in terminal sections, wherein the terminal sections are the last one-fourth part to half part of all sections; (h) eliminating the drift in the selected .sub.3 signals of step (g) with time to get .sub.5 signals; and (i) finding the difference between the mean values of the .sub.4 and .sub.5 signals.

DETAILED DESCRIPTION OF THE INVENTION

[0011] The present invention provides a method for calculating the change of signals starting from the originally detected temporal signals (), comprising the following steps: (a) eliminating the drift in the originally detected temporal signals with time to get .sub.1 signals; (b) removing the xi signals existing outside the range of 80% to 120% (or 90% to 110%) of the averaged value of all the .sub.1 signals to get residual signals as .sub.2 signals; (c) dividing the .sub.2 signals into 14-100 sections; (d) finding the averaged value of the .sub.2 signals in each section to get .sub.3 signals; (e) optionally neglecting one or two of the first .sub.3 signals and selecting six to nine .sub.3 signals with the smallest value of standard deviation in initial sections, wherein the initial sections are the first one-fourth part to half part of all sections; (f) eliminating the drift in the selected .sub.3 signals of step (e) with time to get .sub.4 signals; (g) selecting six to nine .sub.3 signals with the smallest value of standard deviation in terminal sections, wherein the terminal sections are the last one-fourth part to half part of all sections; (h) eliminating the drift in the selected .sub.3 signals of step (g) with time to get .sub.5 signals; and (i) finding the difference between the mean values of the .sub.4 and .sub.5 signals.

[0012] In an embodiment, the temporal signals are time dependent ac magnetic signals. In an embodiment, the change of signals is the reduction in ac magnetic susceptibility of materials. In an embodiment, the steps of eliminating the drift in the signals with time are done by subtracting each signal by the value lying in the correspondingly linear function.

EXAMPLES

[0013] The examples below are non-limiting and are merely representative of various aspects and features of the present invention.

Example 1

[0014] One of the IMR assays was given. The magnetic nanoparticles each encompassed a Fe.sub.3O.sub.4 core and coated with dextran. Antibodies against carcinoembryonic antigen (CEA), which was a biomarker for the risk evaluation of colorectal cancer, were immobilized onto magnetic nanoparticles via covalent binding between antibodies and dextran. The mean diameter of magnetic nanoparticles was 53 nm. Antibody-functionalized magnetic nanoparticles were dispersed in pH-7.4 phosphate buffered saline (PBS) solution to form the reagent for IMR. The magnetic concentration of the reagent was 8-mg-Fe/ml. The to-be-detected bio-molecule in this example was carcinoembryonic antigen (CEA). The CEA concentration of the test sample was 2.5 ng/ml. 40-l reagent was mixed with 60-l sample for the IMR measurement. The reader of IMR measurement was a magnetically labeled immuno-analyzer (XacPro-E, MagQu) to record the time dependent ac magnetic susceptibility of reagent after being mixed with the sample. The time dependent ac magnetic susceptibility, i.e. .sub.ac-t curve, of reagent was shown in FIG. 2

[0015] It should be noted that bio-molecules can not bind with nanoparticles at the same instant. Instead, bio-molecules finish binding with nanoparticles during a period of time. Hence, the ac magnetic susceptibility .sub.ac of reagent gradually decreased during the association period of time.

[0016] In FIG. 2, most of .sub.ac's were distributed between 45 and 52. The variations in temporal .sub.ac masked the reduction in the ac magnetic susceptibility of reagent due to the nanoparticle-bio-molecule associations. Thus, the reduction in the ac magnetic susceptibility of reagent was not so obvious. In addition, some points were extremely high or low, which might be caused with ambient noises. Such signals were not true and should be removed. Moreover, the .sub.ac in FIG. 2 might drift with time once the temperature around reagent raised or went down. In order to find the true reduction in the ac magnetic susceptibility of reagent due to the nanoparticle-bio-molecule associations, the effects of the signal variation, the ambient noise and temperature drift on the .sub.ac of reagent must be removed. Therefore, a method was developed to be applied in this work to remove these effects and to find the true reduction in the .sub.ac of reagent, as described below.

[0017] First of all, the drift in the detected .sub.ac signals of reagent with time shown in FIG. 2 due to the temperature drift was eliminated via

.sub.ac,1=.sub.acst (Equation 1),

where s denoted the slope of the time dependence of the detected .sub.ac signals of reagent shown in FIG. 2, t is time. The s in Equation 1 was obtained by fitting the time dependent detected .sub.ac signals in FIG. 2 to a linear function. The slope of the linear function was s. The fitted linear function was plotted with the dashed line in FIG. 2. The slope of the fitted linear function in FIG. 2 was 5.8810.sup.4. Thus, the drift in .sub.ac with time due to temperature drift around reagent was eliminated.

[0018] Secondly, the .sub.ac,1's far from the averaged value of temporal .sub.ac,1 were removed to neglect some points extremely high or low caused with ambient noises. For example, the .sub.ac,1's lower than 0.9 <.sub.ac,1> and higher than 1.1 <.sub.ac,1> were removed, where <.sub.ac,1> was the averaged value of temporal .sub.ac,1. The resultant time dependent .sub.ac signals of reagent were shown in FIG. 3. The .sub.ac signal of reagent was now denoted with .sub.ac,2.

[0019] The time dependent .sub.ac,2 in FIG. 3 showed a reduction after 300 minutes. However, the .sub.ac,2 signals showed variations between 45 and 52. Such variation was mainly due to the noises of analyzer, and could be suppressed by averaging .sub.ac,2 within a suitable time interval. Thus, the third step was to suppress the variations in .sub.ac,2 by averaging .sub.ac,2's with a suitable time interval. For example, the whole period of detecting time was divided into m sections. The numbers n.sub.i of .sub.ac,2 signal points in the ith section were

[00001]$\begin{array}{cc}{n}_i=\left[N/m\right]+f_i.Math..Math.\mathrm{with}.Math..Math.f_i=\{\begin{array}{c}1,iN.Math..Math.\%.Math..Math.m\\ 0,i>N.Math..Math.\%.Math..Math.m\end{array},& \left(\mathrm{Equation}.Math..Math.2\right)\end{array}$

where N was the total numbers of .sub.ac,2, [ ] denoted Floor function, and N % m was the residue of N divided by m. For the case in FIG. 3, the N was 2916. All the .sub.ac,2 signals were divided into 30 sections, i.e. m=30. In case, i=1 to 30. Thus, the numbers of .sub.ac.2 signal points in the first to the sixth section were 98, and were 97 in the other sections. Then, the averaged value of .sub.ac,2 signals in each section was calculated. The time-evolution averaged .sub.ac,2 signal, denoted as .sub.ac,3, in each section was plotted in FIG. 4.

[0020] The data points at initials in FIG. 4 denoted the ac magnetic susceptibility of reagent before the association between nanoparticles and to-be-detected biomolecules. Whereas, the data points at terminals in FIG. 4 corresponded to the ac magnetic susceptibility of reagent after the association between nanoparticles and to-be-detected biomolecules. Thus, the data points at initials and terminals in FIG. 4 were interested.

[0021] The fourth step was to select .sub.ac,3 signals at initial sections. To do this, several .sub.ac,3 signals were picked up at initials. The initial sections were the first one-fourth part to half part of all sections. Optionally, one or two of the first .sub.ac,3 signals would be neglected due to the initial un-stability of the measurement, and the following X.sub.ac,3 signals at initials were taken into account. Then, some picked .sub.ac,3 signals, which led to higher standard deviation of these picked .sub.ac,3 signals, would be neglected. The mean value of the residual .sub.ac,3 signals at initials was calculated as the .sub.ac,o in FIG. 1. For example, two of the first .sub.ac,3 signals in FIG. 4 were neglected and the following eleven .sub.ac,3 signals were pick up. Then, the standard deviations of ten of the eleven .sub.ac,3 signals were calculated by sequentially neglecting one .sub.ac,3 signal. In this case, 11 values for the standard deviations were gotten. The .sub.ac,3 signal which would lead to the highest value of the standard deviations was removed. Thus, the ten .sub.ac,3 signals from the first eleven .sub.ac,3 signals with the smallest value of standard deviation were picked up. Following the same processes, six to nine .sub.ac,3 signals from the eleven .sub.ac,3 signals were finally picked up. In this example, eight .sub.ac,3 signals from the eleven .sub.ac,3 signals were picked up.

[0022] Fifthly, the drift in the picked eight .sub.ac,3 signals with time was eliminated via

.sub.ac,4=.sub.ac,3s.sub.int (Equation 3),

where s.sub.in was the slope of the time dependent picked eight .sub.ac,3 signals at initials. The value of s.sub.in was obtained by fitting the time dependent picked eight .sub.ac,3 signals at initials to a linear function. The slope of the linear function was s.sub.in.

[0023] In addition, the time dependent .sub.ac,3 signals at terminal sections, which were the last one-fourth part to half part of all sections, were also picked up through a similar way as described above in the fourth step for obtaining .sub.ac,4 signals at initials. For example, the last eleven .sub.ac,3 signals in FIG. 4 were pick up. Then, the standard deviations of ten of the eleven .sub.ac,3 signals were calculated by sequentially neglecting one .sub.ac,3 signal. In this case, eleven values for the standard deviations were gotten. The .sub.ac,3 signal which would lead to the highest value of the standard deviations was removed. Thus, the ten .sub.ac,3 signals from the last eleven .sub.ac,3 signals with the smallest value of standard deviation were picked up. Following the same processes, six to nine .sub.ac,3 signals from the last eleven .sub.ac,3 signals were finally picked up. In this example, eight .sub.ac,3 signals from the last eleven .sub.ac,3 signals were picked up, and were converted to .sub.ac,5 signals via

.sub.ac,5=.sub.ac,3s.sub.tet (Equation 4)

to eliminate the drift in the picked eight .sub.ac,3 signals with time, where s.sub.te was the slope of the time dependent picked eight .sub.ac,3 signals at terminals. The value of s.sub.te was obtained by fitting the time dependent picked eight .sub.ac,3 signals at terminals to a linear function. The slope of the linear function was s.sub.te.

[0024] The selected .sub.ac,4's and .sub.ac,5's in FIG. 4 were circled, as shown in FIG. 5. The mean values of selected .sub.ac,4's and .sub.ac,5's were calculated and denoted as <.sub.ac,4> and <.sub.ac,5> respectively. As compared with FIG. 1, <.sub.ac,4> was .sub.ac,o and <.sub.ac,5> stood for .sub.ac,o. Thus, the last step was to calculate the IMR signal, IMR(%), via

[00002]$\begin{array}{cc}\mathrm{IMR}\left(\%\right)=\frac{{}_{a.Math..Math.c,4}-{}_{a.Math..Math.c,5}}{{}_{a.Math..Math.c,4}}100.Math.\%.& \left(\mathrm{Equation}.Math..Math.5\right)\end{array}$

[0025] For example, the <.sub.ac,4> in FIG. 5 was 50.35 and <.sub.ac,5> was 49.64. The IMR signal equaled 1.41%.

[0026] One skilled in the art readily appreciates that the present invention is well adapted to carry out the objects and obtain the ends and advantages mentioned, as well as those inherent therein. The methods and uses thereof are representative of preferred embodiments, are exemplary, and are not intended as limitations on the scope of the invention. Modifications therein and other uses will occur to those skilled in the art. These modifications are encompassed within the spirit of the invention and are defined by the scope of the claims.

[0027] It will be readily apparent to a person skilled in the art that varying substitutions and modifications may be made to the invention disclosed herein without departing from the scope and spirit of the invention.

[0028] All patents and publications mentioned in the specification are indicative of the levels of those of ordinary skill in the art to which the invention pertains. All patents and publications are herein incorporated by reference to the same extent as if each individual publication was specifically and individually indicated to be incorporated by reference.

[0029] The invention illustratively described herein suitably may be practiced in the absence of any element or elements, limitation or limitations, which are not specifically disclosed herein. The terms and expressions which have been employed are used as terms of description and not of limitation, and there is no intention that in the use of such terms and expressions of excluding any equivalents of the features shown and described or portions thereof, but it is recognized that various modifications are possible within the scope of the invention claimed. Thus, it should be understood that although the present invention has been specifically disclosed by preferred embodiments and optional features, modification and variation of the concepts herein disclosed may be resorted to by those skilled in the art, and that such modifications and variations are considered to be within the scope of this invention as defined by the appended claims.