Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
1. This action is responsive to communications: Application filed on March 18, 2024, and Drawings filed on March 18, 2024.
2. Claims 1–18 are pending in this case. Claim 1, 7 are independent claims.
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
Allowable Subject Matter
Claims 2-4, 10 and 16 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
With regard to claim 2, the prior arts do not disclose the aspect wherein the dedicated algorithm detects a center point of the NK cell in the lens-free shadow image, secures the WSM of the at least some region determined from the center point in the lens-free shadow image, and calculates at least one of the WSM_SD, the WSM_Min, or the PPD in the region.
With regard to claim 10 and 16, the prior arts do not disclose the aspect wherein the securing of the WSM comprises: generating a virtual line in a predetermined number of pixels in one direction at the center point, and securing the WSM having 360 degrees with respect to the region by repeatedly obtaining the WSM from the pixels on the line by rotating the line at a predetermined angle.
Claim Rejections - 35 U.S.C. § 101
35 U.S.C. § 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 7, 8, 9, 11, 13, 14, 15, 17 are rejected under 35 U.S.C. § 101 because the claimed invention is directed to an abstract idea without significantly more.
As to claim 7:
Step 1 Analysis: Is the claim to a process, machine, manufacture or composition of matter? See MPEP § 2106.03.
Yes, the claim is to a process.
Step 2A Prong One Analysis: Does the claim recite an abstract idea, law of nature, or natural phenomenon? See MPEP § 2106.04(II)(A)(1).
Yes, the limitation “detecting at least one shadow parameter in at least some region of a lens-free shadow image of an NK cell;” is the abstract idea of a mental process that can practically be performed in the human mind, with or without the use of a physical aid such as pen and paper (including an observation, evaluation, judgment, opinion). See MPEP § 2106.04(a)(2)(III).
Yes, the limitation “and analyzing an activity of the NK cell by using the shadow parameter, wherein the shadow parameter comprises at least one of a peak-to-peak distance (PPD) indicative of a distance between peaks in the region, a width of secondary maxima (WSM) indicative of a width having maximum brightness in the region, a standard deviation of WSM (WSM_SD) indicative of a standard deviation of the WSM, or minima of WSM (WSM_Min) indicative of a minimum value of the WSM.” is the abstract idea of a mental process that can practically be performed in the human mind, with or without the use of a physical aid such as pen and paper (including an observation, evaluation, judgment, opinion). See MPEP § 2106.04(a)(2)(III).
Step 2A Prong Two Analysis: Does the claim recite additional elements that integrate the judicial exception into a practical application? See MPEP § 2106.04(d).
No the claim does not recite additional elements that integrate the judicial exception into a practical application.
Step 2B Analysis: Does the claim recite additional elements that amount to significantly more than the judicial exception? See MPEP § 2106.05.
No the claim does not recite additional elements that amount to significantly more than the judicial exception.
As to claim 8:
Step 1 Analysis: Is the claim to a process, machine, manufacture or composition of matter? See MPEP § 2106.03.
Yes, the claim is to a process (method)
Step 2A Prong One Analysis: Does the claim recite an abstract idea, law of nature, or natural phenomenon? See MPEP § 2106.04(II)(A)(1).
Yes, the limitation “ detecting a center point of the NK cell in the lens-free shadow image;” is the abstract idea of a mental process that can practically be performed in the human mind, with or without the use of a physical aid such as pen and paper (including an observation, evaluation, judgment, opinion). See MPEP § 2106.04(a)(2)(III).
Yes, the limitation “securing the WSM of some region that is determined from the center point in the lens-free shadow image;” is the abstract idea of a mental process that can practically be performed in the human mind, with or without the use of a physical aid such as pen and paper (including an observation, evaluation, judgment, opinion). See MPEP § 2106.04(a)(2)(III).
Yes, the limitation “and calculating at least one of the WSM_SD, the WSM_Min, or the PPD in the region.” is the abstract idea of a mental process that can practically be performed in the human mind, with or without the use of a physical aid such as pen and paper (including an observation, evaluation, judgment, opinion). See MPEP § 2106.04(a)(2)(III).
Step 2A Prong Two Analysis: Does the claim recite additional elements that integrate the judicial exception into a practical application? See MPEP § 2106.04(d).
The analysis of the parent claim is incorporated.
Step 2B Analysis: Does the claim recite additional elements that amount to significantly more than the judicial exception? See MPEP § 2106.05.
The analysis of the parent claim is incorporated.
As to claim 9:
Step 1 Analysis: Is the claim to a process, machine, manufacture or composition of matter? See MPEP § 2106.03.
Yes, the claim is to a process (method)
Step 2A Prong One Analysis: Does the claim recite an abstract idea, law of nature, or natural phenomenon? See MPEP § 2106.04(II)(A)(1).
Yes, the limitation “wherein the analyzing of the activity of the NK cell comprises analyzing the activity by using at least one of the PPD, the WSM, the WSM_SD, or the WSM_Min when a product of the WSM_SD and the WSM_Min is a predetermined value or more.” is the abstract idea of a mental process that can practically be performed in the human mind, with or without the use of a physical aid such as pen and paper (including an observation, evaluation, judgment, opinion). See MPEP § 2106.04(a)(2)(III).
Step 2A Prong Two Analysis: Does the claim recite additional elements that integrate the judicial exception into a practical application? See MPEP § 2106.04(d).
The analysis of the parent claim is incorporated.
Step 2B Analysis: Does the claim recite additional elements that amount to significantly more than the judicial exception? See MPEP § 2106.05.
The analysis of the parent claim is incorporated.
As to claim 11:
Step 1 Analysis: Is the claim to a process, machine, manufacture or composition of matter? See MPEP § 2106.03.
Yes, the claim is to a process (method)
Step 2A Prong One Analysis: Does the claim recite an abstract idea, law of nature, or natural phenomenon? See MPEP § 2106.04(II)(A)(1).
Yes, the limitation “the method is performed by an NK cell activity analysis-dedicated algorithm mounted on the apparatus for analyzing the activity of NK cells, and the dedicated algorithm analyzes the NK cell without using a reagent.” is the abstract idea of a mental process that can practically be performed in the human mind, with or without the use of a physical aid such as pen and paper (including an observation, evaluation, judgment, opinion). See MPEP § 2106.04(a)(2)(III).
Step 2A Prong Two Analysis: Does the claim recite additional elements that integrate the judicial exception into a practical application? See MPEP § 2106.04(d).
The analysis of the parent claim is incorporated.
Step 2B Analysis: Does the claim recite additional elements that amount to significantly more than the judicial exception? See MPEP § 2106.05.
The analysis of the parent claim is incorporated.
Claim 13 is the medium claim and is rejected for the same reason as claim 7.
Claim 14 is the medium claim and is rejected for the same reason as claim 8.
Claim 15 is the medium claim and is rejected for the same reason as claim 9.
Claim 17 is the medium claim and is rejected for the same reason as claim 11.
Claims 8, 9, 14, 15 would be allowable if rewritten or amended to overcome the rejection(s) under 35 U.S.C. 101 rejections.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claim 11 and 12 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
With regard to claim 11, applicant claims the limitation wherein: the method is performed by an NK cell activity analysis-dedicated algorithm mounted on the apparatus for analyzing the activity of NK cells, and the dedicated algorithm analyzes the NK cell without using a reagent.
It is unclear how an algorithm can be mounted on an apparatus. It is unclear whether the applicant meant that it is physically mounted on the apparatus or that some kind of computer code is mounted on the apparatus. Claims 12 is rejected for the same reason. For the purpose of a compact prosecution, it is interpreted that the NK cell is mounted on the apparatus.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1, 5, 7, 11, 13, 17 is/are rejected under 35 U.S.C. 103 as being unpatentable over Geonsoo, Lens-free shadow image based high-throughput continuous cell monitoring technique (2012), in view of Fulton, Pub. No.: WO 2020205998 A1, and further in view of Wang, Pub. No.: 20210041418 A1.
With regard to claim 1:
Geonsoo discloses an analysis for analyzing an activity of cells by using a lens-free shadow imaging technique (the experiment is performed within a custom built incubator integrated with the lens-free shadow imaging platform, Abstract: “A high-throughput continuous cell monitoring technique which does not require any labeling reagents or destruction of the specimen is demonstrated. More than 6000 human alveolar epithelial A549 cells are monitored for up to 72 h simultaneously and continuously with a single digital image within a cost and space effective lens-free shadow imaging platform. In an experiment performed within a custom built incubator integrated with the lens-free shadow imaging platform, the cell nucleus division process could be successfully characterized by calculating the signal-to-noise ratios (SNRs) and the shadow diameters (SDs) of the cell shadow patterns. The versatile nature of this platform also enabled a single cell viability test followed by live cell counting. This study firstly shows that the lens-free shadow imaging technique can provide a continuous cell monitoring without any staining/labeling reagent and destruction of the specimen. This high-throughput continuous cell monitoring technique based on lensfree shadow imaging may be widely utilized as a compact, low-cost, and high-throughput cell monitoring tool in the fields of drug and food screening or cell proliferation and viability testing.”), the apparatus comprising: a cell chip in which an cell is disposed (see fig. a under 2.1 Cell preparation for cell chip, 2.1. Cell preparation: “To demonstrate the high-throughput continuous cell monitoring technique, we used A549 (human alveolar epithelial) cells at a concentration of 250,000 cells/ml maintained in an RPMI-1640 (HyClone) medium. The medium was supplemented with 10% fetal bovine serum (HyClone), penicillin (100 units/ml), and) streptomycin (0.1 mg/ml). The cells were initially cultured on the surface of a type 1 (h¼0.15 mm) cover glass within a commercial air-jacketed CO2 incubator for 24 h at 37 1C. Before the cell preparation, all the components directly contacting the cells in Fig. 1(a), including the cover glass, petri dish, polydimethylsiloxane (PDMS) wall, silicon tubes, and quartz flow cell, were autoclaved at 121 1C for 30 min to sterilize them.”); an LED configured to radiate light to the cell (see fig. A under 2.1. Cell preparation for LED light, paragraph 3 under Introduction: “Recently, a lens-free imaging modality, which does not utilize any conventional optical lenses or scanning stage, was successfully demonstrated (Seo et al., 2008, 2009; Su et al., 2009). In this approach, the cells or micro-objects are located close to an optoelectronic device, e.g. a CCD (Charge-Coupled Device) or CMOS (Complementary Metal-Oxide-Semiconductor) image sensor, and illuminated with a low-cost partially coherent light source, e.g. an LED (Light Emitting Diode) conjugated with a micro pin-hole. The shadow or diffraction patterns of the cells or any other micro-objects that were generated by this simple imaging platform were recorded with the optoelectronic device and analyzed to detect and characterize various biological cells or molecules including yeasts (Seo et al., 2009), human blood cells (Seo et al., 2010), and antibodies (Stybayeva et al., 2010). This lens-free imaging platform, of course, has low optical resolution due to the lack of the optical lenses; however, the resulting shadow or diffraction patterns of the target cells can provide”); a CMOS image sensor configured to photograph a lens-free shadow image of the cell (the cells or micro-objects are located close to an optoelectronic device, e.g. a CCD (Charge-Coupled Device) or CMOS (Complementary Metal-Oxide-Semiconductor) image sensor, paragraph 3 and 4 and Introduction: “Recently, a lens-free imaging modality, which does not utilize any conventional optical lenses or scanning stage, was successfully demonstrated (Seo et al., 2008, 2009; Su et al., 2009). In this approach, the cells or micro-objects are located close to an optoelectronic device, e.g. a CCD (Charge-Coupled Device) or CMOS (Complementary Metal-Oxide-Semiconductor) image sensor, and illuminated with a low-cost partially coherent light source, e.g. an LED (Light Emitting Diode) conjugated with a micro pin-hole. The shadow or diffraction patterns of the cells or any other micro-objects that were generated by this simple imaging platform were recorded with the optoelectronic device and analyzed to detect and characterize various biological cells or molecules including yeasts (Seo et al., 2009), human blood cells (Seo et al., 2010), and antibodies (Stybayeva et al., 2010). This lens-free imaging platform, of course, has low optical resolution due to the lack of the optical lenses; however, the resulting shadow or diffraction patterns of the target cells can provide enough information for their detection and characterization. Also, the FOV of this platform can be extended up to several thousand times greater than that of the conventional microscope by simply selecting a suitable optoelectronic device. Furthermore, due to the simple and compact physical structure of this platform, this technique could be also useful in developing a point-of-care (POC) microscope (Mudanyali et al., 2010) or a miniaturized portable photospectrometer (Kim et al., 2011). In this study, we firstly demonstrate a high-throughput continuous cell monitoring technique based on lens-free shadow imaging. This technique does not require any labeling reagents or destruction of the specimen. More than 6000 human alveolar epithelial A549 cells are monitored simultaneously and continuously for up to 72 h within a custom built cell incubator integrated with the lens-free shadow imaging platform. In this manuscript, single cell viability and nucleus division are quantified and characterized by calculating the signal-to-noise ratio (SNR) and shadow diameter (SD) of the cell shadow patterns. All the experimental procedures and results for the cell preparation, cell culture, lens-free shadow imaging platform, quantification of cell shadow images, and live cell count are described in the following sections.”); and a processor comprising a dedicated algorithm configured to analyze an activity of the cell based on the lens-free shadow image, wherein the dedicated algorithm detects at least one shadow parameter in at least some region of the lens-free shadow image and analyzes the activity of the cell by using the shadow parameter (wherein shadow parameter is used to analyze cell viability and other cell related properties, paragraph 2 under the heading 3. Results and discussion: “shown in Fig. 4(c). While Fig. 4 provides the qualitative image information for the cell of interest, Fig. 5 illustrates the quantitative results for the same cell. The SNR and SD values, calculated from the shadow patterns of the cell of interest, changed remarkably during the time frame of T¼4–10 h (the SNR decreased by45 dB and SD increased by 48 mm). These rapid variations of the SNR and SD values are in good agreement with the morphology changes observed with the 400 microscope in Fig. 4. To evaluate the feasibility of the shadow imaging platform as a cell viability testing tool, a small region of the normal A549 cells, grown in the quartz flow cell over 48 h, was exposed to a relatively high temperature by turning on the CMOS image sensor continuously to maintain a temperature of 45 1C for 12 h. The result of this was that at the boundary of the exposure, a heterogeneous condition, where live and dead cells co-existed, could be observed, as in the shadow image shown in Fig. 2(a). In Fig. 2(a), the live cell region (left) was filled with numerous healthy A549 cells, while the dead cell region (right) showed a significant decrease in cell density. To confirm the viability of the cells in the shadow image, the specimen was also inspected by a conventional microscope 100), and these images are given in Fig. 2(b, c). The SNR and SD parameters previously employed to indicate the nucleus division process in Fig. 5 were still effective for cell viability evaluation. The SNR and SD values measured from ten randomly selected A549 cells were relatively constant with a low variation, i.e. SNRave¼26.957 dB and SDave¼12.179 mm, for the normal cell culture condition, i.e. 37 1C for 0–48 h. However, after the short high temperature exposure, i.e. 45 1C for a further 12 h, these values were remarkably reduced or extended, i.e. SNR¼9.616 dB and SD¼36.278 mm, as plotted in Fig. 6(a, b). These abrupt SNR and SD changes of the cells were easily distinguishable and one set of the representative shadow image variations is illustrated in Fig. 6(c). It is regrettable that we could not record more shadow images at the time frame of T¼48–60 h when the cell of interest traversed on the border of live and dead due to the accumulated fatigue on the researchers.”).
Geonsoo does not disclose the aspect wherein the shadow parameter comprises at least one of a peak-to-peak distance (PPD) indicative of a distance between peaks in the region, a width of secondary maxima (WSM) indicative of a width having maximum brightness in the region, a standard deviation of WSM (WSM_SD) indicative of a standard deviation of the WSM, or minima of WSM (WSM_Min) indicative of a minimum value of the WSM.
However Fulton discloses the aspect wherein the parameter comprises at least one of a peak-to-peak distance (PPD) indicative of a distance between peaks in the region, a width of secondary maxima (WSM) indicative of a width having maximum brightness in the region, a standard deviation of WSM (WSM_SD) indicative of a standard deviation of the WSM, or minima of WSM (WSM_Min) indicative of a minimum value of the WSM ( The parameter comprises peak to peak distance, “In one alternative, the three-dimensional shape of electrode imprints at the weld W may be analyzed by machine learning/artificial intelligence to discern correlations between topographical parameters and empirically determined weld strength to assess welds based upon the 3D shape of the weld dimple. In one example, topographical parameters can include, but are not limited to, those indicative of roughness, skewness, root mean square (RMS), peak-to-peak distance, valley depth, peak height, and combinations thereof. In one example, a subset of 100+ topographical parameters (Sa, etc. - Development of Methods for Characterization of Roughness in Three Dimensions Ken Sout et ah, May 1, 2000) or an innovative feature prescribed by an algorithm can be used with Machine Learning to detect & predict weld failures/size. The learned correlation may be binary (good or discrepant weld) or continuous (an inferred strength approximation or a weld quality measure, such as a categorization by numbers 1 to 10 with 1 being a poor weld and 10 being an excellent weld).”). It would have been obvious to one of ordinary skill in the art, at the time the filing was made to apply Fulton to Geonsoo so the user would be able to better understand the attribute of the cell using shadow parameter such PPD and WSM attributes.
Geonsoo and Fulton do not disclose the cells are natural killer (NK) cells. However Wang discloses the aspect wherein the cells are natural killer (NK) cells (human and murine NK cell lines were each tested for their cytolytic activities paragraph 284: “Using the RT-CES system, human and murine NK cell lines were each tested for their cytolytic activities using 9 different target cell lines, including cancer cell lines commonly used in the field. The quantitative and dynamic measurement of NK-cell mediated cytolysis was performed on RT-CES system without any labeling steps and reagents. The experimental results are consistent. Moreover, RT-CES system offers fully automated measurement of the cytolysis in real time, which enables a large scale screening of chemical compounds or genes responsible for the regulation of NK cell-mediated cytolytic activity”). It would have been obvious to one of ordinary skill in the art, at the time the filing was made to apply Wang to Geonsoo and Fulton so the method can be applied to NK cells to help the user learn more about the attribute of NK cells.
With regard to claim 5:
Geonsoo and Fulton and Wang disclose the apparatus of claim 1, wherein the dedicated algorithm analyzes the NK cell without using a reagent (Wang paragraph 284: “Using the RT-CES system, human and murine NK cell lines were each tested for their cytolytic activities using 9 different target cell lines, including cancer cell lines commonly used in the field. The quantitative and dynamic measurement of NK-cell mediated cytolysis was performed on RT-CES system without any labeling steps and reagents. The experimental results are consistent. Moreover, RT-CES system offers fully automated measurement of the cytolysis in real time, which enables a large scale screening of chemical compounds or genes responsible for the regulation of NK cell-mediated cytolytic activity”). It would have been obvious to one of ordinary skill in the art, at the time the filing was made to apply Wang to Geonsoo and Fulton so the analysis can be done without using reagent saving time, efforts and resources.
With regard to claim 7:
Geonsoo discloses a method of an apparatus for analyzing an activity of cells by using a lens-free shadow imaging technique (the experiment is performed within a custom built incubator integrated with the lens-free shadow imaging platform, Abstract: “A high-throughput continuous cell monitoring technique which does not require any labeling reagents or destruction of the specimen is demonstrated. More than 6000 human alveolar epithelial A549 cells are monitored for up to 72 h simultaneously and continuously with a single digital image within a cost and space effective lens-free shadow imaging platform. In an experiment performed within a custom built incubator integrated with the lens-free shadow imaging platform, the cell nucleus division process could be successfully characterized by calculating the signal-to-noise ratios (SNRs) and the shadow diameters (SDs) of the cell shadow patterns. The versatile nature of this platform also enabled a single cell viability test followed by live cell counting. This study firstly shows that the lens-free shadow imaging technique can provide a continuous cell monitoring without any staining/labeling reagent and destruction of the specimen. This high-throughput continuous cell monitoring technique based on lensfree shadow imaging may be widely utilized as a compact, low-cost, and high-throughput cell monitoring tool in the fields of drug and food screening or cell proliferation and viability testing.”), the method comprising: detecting at least one shadow parameter in at least some region of a lens-free shadow image of an cell; (the cells or micro-objects are located close to an optoelectronic device, e.g. a CCD (Charge-Coupled Device) or CMOS (Complementary Metal-Oxide-Semiconductor) image sensor, paragraph 3 and 4 and Introduction: “Recently, a lens-free imaging modality, which does not utilize any conventional optical lenses or scanning stage, was successfully demonstrated (Seo et al., 2008, 2009; Su et al., 2009). In this approach, the cells or micro-objects are located close to an optoelectronic device, e.g. a CCD (Charge-Coupled Device) or CMOS (Complementary Metal-Oxide-Semiconductor) image sensor, and illuminated with a low-cost partially coherent light source, e.g. an LED (Light Emitting Diode) conjugated with a micro pin-hole. The shadow or diffraction patterns of the cells or any other micro-objects that were generated by this simple imaging platform were recorded with the optoelectronic device and analyzed to detect and characterize various biological cells or molecules including yeasts (Seo et al., 2009), human blood cells (Seo et al., 2010), and antibodies (Stybayeva et al., 2010). This lens-free imaging platform, of course, has low optical resolution due to the lack of the optical lenses; however, the resulting shadow or diffraction patterns of the target cells can provide enough information for their detection and characterization. Also, the FOV of this platform can be extended up to several thousand times greater than that of the conventional microscope by simply selecting a suitable optoelectronic device. Furthermore, due to the simple and compact physical structure of this platform, this technique could be also useful in developing a point-of-care (POC) microscope (Mudanyali et al., 2010) or a miniaturized portable photospectrometer (Kim et al., 2011). In this study, we firstly demonstrate a high-throughput continuous cell monitoring technique based on lens-free shadow imaging. This technique does not require any labeling reagents or destruction of the specimen. More than 6000 human alveolar epithelial A549 cells are monitored simultaneously and continuously for up to 72 h within a custom built cell incubator integrated with the lens-free shadow imaging platform. In this manuscript, single cell viability and nucleus division are quantified and characterized by calculating the signal-to-noise ratio (SNR) and shadow diameter (SD) of the cell shadow patterns. All the experimental procedures and results for the cell preparation, cell culture, lens-free shadow imaging platform, quantification of cell shadow images, and live cell count are described in the following sections.”).
Geonsoo does not disclose the aspect wherein the shadow parameter comprises at least one of a peak-to-peak distance (PPD) indicative of a distance between peaks in the region, a width of secondary maxima (WSM) indicative of a width having maximum brightness in the region, a standard deviation of WSM (WSM_SD) indicative of a standard deviation of the WSM, or minima of WSM (WSM_Min) indicative of a minimum value of the WSM.
However Fulton discloses the aspect wherein the parameter comprises at least one of a peak-to-peak distance (PPD) indicative of a distance between peaks in the region, a width of secondary maxima (WSM) indicative of a width having maximum brightness in the region, a standard deviation of WSM (WSM_SD) indicative of a standard deviation of the WSM, or minima of WSM (WSM_Min) indicative of a minimum value of the WSM (“In one alternative, the three-dimensional shape of electrode imprints at the weld W may be analyzed by machine learning/artificial intelligence to discern correlations between topographical parameters and empirically determined weld strength to assess welds based upon the 3D shape of the weld dimple. In one example, topographical parameters can include, but are not limited to, those indicative of roughness, skewness, root mean square (RMS), peak-to-peak distance, valley depth, peak height, and combinations thereof. In one example, a subset of 100+ topographical parameters (Sa, etc. - Development of Methods for Characterization of Roughness in Three Dimensions Ken Sout et ah, May 1, 2000) or an innovative feature prescribed by an algorithm can be used with Machine Learning to detect & predict weld failures/size. The learned correlation may be binary (good or discrepant weld) or continuous (an inferred strength approximation or a weld quality measure, such as a categorization by numbers 1 to 10 with 1 being a poor weld and 10 being an excellent weld).”). It would have been obvious to one of ordinary skill in the art, at the time the filing was made to apply Fulton to Geonsoo so the user would be able to better understand the attribute of the cell using shadow parameter such PPD and WSM attributes.
Geonsoo and Fulton do not disclose the cells are natural killer (NK) cells. However Wang discloses the aspect wherein the cells are natural killer (NK) cells (paragraph 284: “Using the RT-CES system, human and murine NK cell lines were each tested for their cytolytic activities using 9 different target cell lines, including cancer cell lines commonly used in the field. The quantitative and dynamic measurement of NK-cell mediated cytolysis was performed on RT-CES system without any labeling steps and reagents. The experimental results are consistent. Moreover, RT-CES system offers fully automated measurement of the cytolysis in real time, which enables a large scale screening of chemical compounds or genes responsible for the regulation of NK cell-mediated cytolytic activity”). It would have been obvious to one of ordinary skill in the art, at the time the filing was made to apply Wang to Geonsoo and Fulton so the method can be applied to NK cells to help the user learn more about the attribute of the NK cells.
With regard to claims 11 and 17:
Geonsoo and Fulton and Wang disclose aspect wherein: the method is performed by an NK cell activity analysis-dedicated algorithm mounted on the apparatus for analyzing the activity of NK cells, and the dedicated algorithm analyzes the NK cell without using a reagent (Wang paragraph 284: “Using the RT-CES system, human and murine NK cell lines were each tested for their cytolytic activities using 9 different target cell lines, including cancer cell lines commonly used in the field. The quantitative and dynamic measurement of NK-cell mediated cytolysis was performed on RT-CES system without any labeling steps and reagents. The experimental results are consistent. Moreover, RT-CES system offers fully automated measurement of the cytolysis in real time, which enables a large scale screening of chemical compounds or genes responsible for the regulation of NK cell-mediated cytolytic activity”). It would have been obvious to one of ordinary skill in the art, at the time the filing was made to apply Wang to Geonsoo and Fulton so the analysis can be done without using reagent saving time, efforts and resources.
Claim 13 is rejected for the same reason as claim 7.
Claims 6, 12, 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Geonsoo, in view of Fulton and Wang, and further in view of De Poly, Pub. No.: 20220012879 A1.
With regard to claim 6:
Geonsoo and Fulton and Wang do not disclose the aspect wherein the dedicated algorithm analyzes the NK cell according to an automated image analysis technique.
However De Poly discloses the aspect wherein the dedicated algorithm analyzes the NK cell (paragraph 59: “The ability to combine information about (1) structural cell details, e.g., morphology and phenotype, (2) metabolic activity, e.g., cells demonstrating higher than normal metabolic activities which can be classified as cancerous or otherwise diseased, and (3) spatial relationship with respect to each identifiable cell type or phenotype, can be used powerfully to diagnose disease states, identify suitable therapeutic interventions, and evaluate novel therapeutic agents and modalities of treatment. For example, biopsy samples may be analyzed to determine whether an immune cell, such as a T lymphocyte (T cell), dendritic cell (CD), Natural Killer cell (NK) and the like, are present within a sample of cells, within the same region as the diseased, e.g., cancerous, cell. Determining that, for example, T cells are being recruited to the vicinity of the diseased cells may provide guidance on the success of current therapeutic intervention or, in the case, of therapeutic development, that a potential therapeutic agent is capable of enhancing the T cell response.”) according to an automated image analysis technique (paragraph 123: “Segmentation, as shown in box 720 of FIG. 7 was performed as follows: The first step of the automatic analysis was to perform cell segmentation in the images, box 720. To do so ilastik, a free, relatively intuitive, a machine-learning tool segmentation software was used. ilastik is based on random forest classifiers. The labels were manually drawn on the DCI images in a user interface, e.g., a manual thresholded approach. Each pixel neighborhood was characterized by a set of generic nonlinear spatial transformations applied to each channel, e.g., R, G, or B, of the DCI image. Image transformations that empirically gave the best contrast were used, and the learning process was performed for about 20-30 minutes.”). It would have been obvious to one of ordinary skill in the art, at the time the filing was made to apply De Poly to Geonsoo and Fulton and Wang so the analysis can be done automatically, saving time and efforts.
With regard to claims 12 and 18:
Geonsoo and Fulton and Wang do not disclose the aspect wherein: the method is performed by an NK cell activity analysis-dedicated algorithm mounted on the apparatus for analyzing the activity of NK cells, and the dedicated algorithm analyzes the NK cell according to an automated image analysis technique.
However De Poly discloses the aspect wherein: the method is performed by an NK cell activity analysis-dedicated algorithm mounted on the apparatus for analyzing the activity of NK cells (paragraph 59: “The ability to combine information about (1) structural cell details, e.g., morphology and phenotype, (2) metabolic activity, e.g., cells demonstrating higher than normal metabolic activities which can be classified as cancerous or otherwise diseased, and (3) spatial relationship with respect to each identifiable cell type or phenotype, can be used powerfully to diagnose disease states, identify suitable therapeutic interventions, and evaluate novel therapeutic agents and modalities of treatment. For example, biopsy samples may be analyzed to determine whether an immune cell, such as a T lymphocyte (T cell), dendritic cell (CD), Natural Killer cell (NK) and the like, are present within a sample of cells, within the same region as the diseased, e.g., cancerous, cell. Determining that, for example, T cells are being recruited to the vicinity of the diseased cells may provide guidance on the success of current therapeutic intervention or, in the case, of therapeutic development, that a potential therapeutic agent is capable of enhancing the T cell response.”), and the dedicated algorithm analyzes the NK cell according to an automated image analysis technique (paragraph 123: “Segmentation, as shown in box 720 of FIG. 7 was performed as follows: The first step of the automatic analysis was to perform cell segmentation in the images, box 720. To do so ilastik, a free, relatively intuitive, a machine-learning tool segmentation software was used. ilastik is based on random forest classifiers. The labels were manually drawn on the DCI images in a user interface, e.g., a manual thresholded approach. Each pixel neighborhood was characterized by a set of generic nonlinear spatial transformations applied to each channel, e.g., R, G, or B, of the DCI image. Image transformations that empirically gave the best contrast were used, and the learning process was performed for about 20-30 minutes.”). It would have been obvious to one of ordinary skill in the art, at the time the filing was made to apply De Poly to Geonsoo and Fulton and Wang so the analysis can be done automatically, saving time and efforts.
Pertinent Arts
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Lee J M, Pub. No.: 20220170842 A1; Performing real-time quantification of cell viability through supravital dye uptake using a lens-free imaging system involves incubating sample cell in cell culture medium, detecting light penetrating the culture medium by lens-free image sensor included in lens-free imaging system, and identifying boundary region of sample cell at preset time interval based on detected light, and staining the incubated sample cell with supravital dye. The method involves analyzing viability of sample cell by calculating absorbance of stained sample cell at preset time interval by lens-free imaging system. The analyzing is performed by detecting intensity of light penetrating the cell culture medium at preset time interval by lens-free image sensor, calculating absorbance of sample cell included in cell culture medium at preset time interval based on boundary region and detected intensity of light by lens-free image sensor, and analyzing viability of sample cell based on the calculated absorbance.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DI XIAO whose telephone number is (571)270-1758. The examiner can normally be reached 9Am-5Pm est M-F.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Stephen Hong can be reached at (571) 272-4124. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/DI XIAO/Primary Examiner, Art Unit 2178