DETAILED ACTION
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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 8/17/2026 has been entered.
Response to Arguments
Claim Objection
The objection to the claim is overcome by amendment.
Claim Interpretation
The limitations previously interpreted under 35 U.S.C. § 112(f) have been removed, removing said interpretation and broadening the scope of the claims.
Rejections under 35 U.S.C. § 103
Applicant’s first argument is that replacing the spiral flow channel of Howell with a straight flow channel would render Howell unsatisfactory for its intended purpose; however, this argument is not persuasive. The purpose of Howell is “High-speed particle detection and tracking in microfluidic devices using event-based sensing” (title) with a device that “1) is compatible with standard microscopes, 2) does not rely on high-power pulsed illumination sources, 3) is significantly less data consuming and less expensive than traditional, frame-based cameras and 4) is attractive for both bright-field and fluorescence imaging” and “reveals the unique capabilities of event-based sensing for overcoming some of the commonly encountered challenges in microfluidics imaging.” (page 3025, final paragraph) The use of a spiral microfluidic channel is introduced merely as a way of proving the principle of event-based sensing in microfluidics imaging. Nothing in Howell implies that event-based imaging is only helpful for use with inertial focusing devices or with spiral channels or unsuitable for use with other microfluidic devices. Further, none of the four advantages extolled by Howell regarding the disclosed event-based particle detection and tracking are unique to inertial microfluidic devices or spiral flow channels. Finally, one of ordinary skill in the art, when considering FIG. 2A of Howell, would have found it obvious to contemplate other kinds of microfluidic devices in an otherwise similar setup, not just the spiral flow channel of FIG. 2C.
Applicant’s second argument is that replacing the spiral flow channel of Howell with a straight flow channel would change the principle of operation of Howell; however, this argument is not persuasive. In particular, Howell’s principle of operation is “High-speed particle detection and tracking in microfluidic devices using event-based sensing” (title). The use of a spiral flow channel is not an inherent part of the principle of operation for high-speed particle detection and tracking in microfluidic devices using event-based sensing, and Howell does not assert otherwise. Finally, it may be noted that Ortyn does provide motivations to sort cells based on imaging rather than inertially, as pointed out in paragraphs 9-10 of the previous action.
The grounds of rejection are maintained.
Since the arguments regarding claim 1 are not persuasive, the other independent claims are not made allowable for similar reasons, and the dependent claims are not automatically allowable.
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 1-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Howell (Non-Patent Literature “High-speed particle detection and tracking in microfluidic devices using event-based sensing”) in view of Ortyn (US Patent 6608682), further in view of Kaduchak (US patent publication 20180284009).
Regarding claim 1, Howell teaches a biological sample analysis system including:
at least one processor (section Imaging setup, third paragraph, running the MATLAB imaging pipeline) configured to:
irradiate a particle in a sample with light (FIG. 2 A, illumination, depicted as a green light bulb.);
detect, using a plurality of pixels of the sample analysis system (FIG. 2 A, Event-based camera), as an event, a luminance change of light emitted from the particle by irradiation with the light (FIG. 1 demonstrates the function of an event-based camera); and
generate particle information regarding the particle on a basis of the event detected by each of the pixels (section Imaging setup, third paragraph, running the MATLAB imaging pipeline); and
the plurality of pixels (FIG. 2 B, in the chip visible in the event-based camera); and
a predetermined flow channel (FIG. 2 C) wherein the predetermined flow channel is with a width of 1 mm or less (section Results, first paragraph, specifies a channel with widths of 360 µm and 60 µm along its two cross-sectional axes. Also see FIG. 3, which has a 200 µm scale bar. Comparing the length of the scale bar to the width of the channel even at the right-hand edge of the region of interest, the channel is only about half a mm wide).
While Howell does not explicitly describe the samples used as biological samples, nor the micrometer-scale polystyrene beads therein as bioparticles, Howell does explicitly state that their results “confirm that event-based cameras can be used to track individual particle behaviours in the size range of commonly used biological cells” (section Particle tracking and velocity mapping, fourth paragraph). Further, a claim for an apparatus generally does not distinguish patentably over the prior art due to recitations of the material or article worked upon by the apparatus. See MPEP 2115.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have used the event-based imaging flow cytometer of Howell with bioparticles, such as cells, in the manner that Howell contemplated.
While the flow channel disclosed by Howell is spiraled rather than straight, Howell does contemplate the use of sensor systems like the one Howell used with other channel designs (COL. 3, sentences 1-2), and the main purpose of Howell appears to be developing event-based imaging as a means to study microfluidics, describing the experiments presented as a “proof-of-principle” (abstract, sentence 6), rather than in inertially separating polystyrene beads with a spiral-shaped flow channel.
In the same field of endeavor of imaging and analyzing small moving objects, such as cells, Ortyn does teach a straight flow cell (FIG. 25, flow cell 306). By not including the spiral like that of Howell, Ortyn avoids the inertial separation of the particles across the fluid stream, allowing the whole width of the flow channel to be used for all sizes of particles. Note that it is generally considered obvious, when a particular function is not desired, to remove both an element (such as the curvature of a flow channel) and its undesired function (such as inertial particle separation). See MPEP 2144.04 II A.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the event-based imaging flow cytometer of Howell without straight the spiral of the flow cell, following the example of Ortyn, to avoid inertial particle separation if one does not consider inertial particle separation to be a desired function, for example, to more efficiently use the entire width of the flow cell for imaging of particles of all sizes. Note that Ortyn also describes the use of cells, a type of bioparticle, in the sample (abstract).
While Howell does discuss sorting of particles, it is in the context of using a spiral-shaped or otherwise curved flow channel to perform inertial separation of the particles, which is different from using bioparticle information generated by a processor to perform sorting in a straight channel as claimed, so Howell does not teach a claimed way to sort the bioparticle on the basis of the generated bioparticle information. Likewise, Ortyn provides a motivation to sort cells (a type of bioparticle) as background to their invention, but does not teach a particular way of doing the sorting itself (even if the imaging techniques of Ortyn would be useful as part of a cell sorting device).
In the same field of endeavor of imaging flow cytometry, Kaduchak teaches a device to sort the bioparticle on the basis of the generated bioparticle information (FIG. 7, sorting module 790, positioned downstream of the image detector 774 and described in paragraph 82). By including a sorting module, Kaduchak is able to separate the particles based on information gathered about them, such as cellular functions (paragraph 82).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the event-based imaging flow cytometer of Howell, as modified by Ortyn, to sort the particles after they are imaged in the manner of Kaduchak, to gain the predictable benefit of being able to perform high-speed sorting of cells or other bioparticles as motivated by Ortyn.
Regarding claim 2, Howell, as modified by Ortyn and Kaduchak, teaches or renders obvious the biological sample analysis system according to claim 1 (as described above).
Howell further teaches that the bioparticle moves in a first direction (FIG. 3, generally parallel to the x axis),
the plurality of pixels include two or more first pixels arranged adjacent to or separated from each other in the first direction (FIG. 3, multiple pixels exist along the x direction),
the at least one processor is further configured to output event data including information of time at which an event has been detected in each of the pixels (section titled Event-data collection and pre-processing, first paragraph), and
the at least one processor is further configured to align the pieces of information of time of a series of event data for each of the first pixels by detecting the luminance change of light emitted from the bioparticle by each of the first pixels (FIG. 7 shows data for several specific particles aligned across time as they move through the pixels), and generate the bioparticle information by processing the series of event data from each of the first pixels with the pieces of information of time aligned (FIG. 7 shows some of that information).
Regarding claim 3, Howell, as modified by Ortyn and Kaduchak, teaches or renders obvious the biological sample analysis system according to claim 2 (as described above).
Howell further teaches that the event data further includes at least one of position information of a pixel that has detected the event (FIG. 3. Note that the events are plotted based on their position) and polarity information of the event detected in the pixel (FIG. 1).
Regarding claim 4, Howell, as modified by Ortyn and Kaduchak, teaches or renders obvious the biological sample analysis system according to claim 2 (as described above).
Howell further teaches that the at least one processor is further configured to align the pieces of information of time of the series of event data for each of the first pixels on a basis of a relative speed of the bioparticle (FIG. 8 B aligns information based on speed to produce the probability density function) and an interval between the first pixels in the first direction (section titled Imaging setup, first paragraph. Also see scale bars in FIG. 3.).
Regarding claim 5, Howell, as modified by Ortyn and Kaduchak, teaches or renders obvious the biological sample analysis system according to claim 4 (as described above).
Howell further teaches that the at least one processor is further configured to measure the relative speed of the bioparticle using at least one of an optical method and an electromagnetic method (used to determine average fluid velocity in FIG. 5 and individual particle velocity in FIG. 7. The caption of FIG. 5 notes that the it is a distribution of particles detected in a video recorded with an event-based camera. Recording a video is an optical technique. Note that optical techniques are inherently electromagnetic, as optical signals (i.e., light) are a form of electromagnetic radiation.).
Regarding claim 6, Howell, as modified by Ortyn and Kaduchak, teaches or renders obvious the biological sample analysis system according to claim 2 (as described above).
Howell further teaches that the at least one processor is further configured to align the pieces of information of time of the series of event data for each of the first pixels on a basis of a difference in time at which each of the first pixels has detected the luminance change of light emitted from the bioparticle (FIG. 4).
Regarding claim 7, Howell, as modified by Ortyn and Kaduchak, teaches or renders obvious the biological sample analysis system according to claim 6 (as described above).
Howell further teaches that the at least one processor is further configured to align the pieces of information of time of the series of event data for each of the first pixels on a basis of a difference in time at which each of the first pixels has detected the luminance change of light emitted from the bioparticle in two or more pixel columns parallel to the first direction (note in FIG. 4 C that each of the three particles is shown as multiple pixels tall).
Regarding claim 8, Howell, as modified by Ortyn and Kaduchak, teaches or renders obvious the biological sample analysis system according to claim 2 (as described above).
Howell further teaches that the biological sample containing the bioparticle is delivered to the predetermined flow channel (FIG. 2 C), and
the at least one processor is further configured to align the pieces of information of time of the series of event data for each of the first pixels on a basis of a control value of a liquid delivery system that delivers the biological sample to the predetermined flow channel (section Microfluidic setup, first paragraph, describes how experiments were performed for varying flow rates with their corresponding velocities and Reynolds numbers. FIG. 6 shows data aligned based on those values.).
Regarding claim 9, Howell, as modified by Ortyn and Kaduchak, teaches or renders obvious the biological sample analysis system according to claim 2 (as described above).
Howell further teaches that the at least one processor is further configured to generate the bioparticle information on a basis of a result of adding or dividing the series of event data for each of the first pixels in which the pieces of information of time are aligned on a time axis (FIG. 4 shows a process of dividing the relatively continuous time of the asynchronous event data into discrete frames.).
Regarding claim 10, Howell, as modified by Ortyn and Kaduchak, teaches or renders obvious the biological sample analysis system according to claim 9 (as described above).
Howell further teaches that the at least one processor is further configured to reconstruct the luminance change of light emitted from the bioparticle on a basis of the result of adding or dividing the series of event data for each of the first pixels in which the pieces of information of time are aligned on a time axis, and generates the bioparticle information on a basis of the reconstructed luminance change (section Event-data collection and pre-processing, second paragraph, describes doing analysis after the process of dividing the relatively continuous time of the asynchronous event data into discrete frames.).
Regarding claim 11, Howell, as modified by Ortyn and Kaduchak, teaches or renders obvious the biological sample analysis system according to claim 10 (as described above).
Howell further teaches that the at least one processor is further configured to reconstruct the luminance change of light emitted from the bioparticle for each of the first pixels for each of two or more pixel columns parallel to the first direction, and generate the bioparticle information on a basis of the luminance change for each of the first pixels in each of the two or more reconstructed pixel columns (FIG. 3. Note that the data comprises multiple rows and multiple columns of pixels, and that each of the particles is multiple pixels across.).
Regarding claim 12, Howell, as modified by Ortyn and Kaduchak, teaches or renders obvious the biological sample analysis system according to claim 1 (as described above).
Howell further teaches that the at least one processor is further configured to generate the bioparticle information using machine learning (section Particle tracking and velocity mapping, determining the particle tracks includes a training step, which is used to track which particle is which from one frame to the next and thereby determine the particle information) from a series of event data for each of the pixels by detecting the luminance change of light emitted from the bioparticle by each of the pixels (FIG. 1).
Regarding claim 13, Howell, as modified by Ortyn and Kaduchak, teaches or renders obvious the biological sample analysis system according to claim 1 (as described above).
Howell further teaches that the bioparticle information includes at least one of image data of the bioparticle reconstructed on a basis of the detected event (FIG. 3 and elsewhere), a feature amount of the bioparticle extracted from at least one of the detected event and the image data, and attribute information of the bioparticle generated from at least one of the event, the image data, and the feature amount (FIG. 6 B shows distance to inner wall, an attribute of a particle at a given time, based on reconstructed image data).
Regarding claim 14, Howell, as modified by Ortyn and Kaduchak, teaches or renders obvious the biological sample analysis system according to claim 1 (as described above).
Howell further teaches that the bioparticle is a cell or a non-cellular bioparticle (the setup is usable with non-cellular bioparticles as evidenced by its use with non-cellular particles. Note that intended use of a claimed device only limits the claim insofar as it restricts the structure of the device itself. See MPEP 2115. Additionally, the particles used are explicitly characterized as being in the size range of cells commonly studied by such devices.).
Also see claim 1 above regarding the biological nature of the bioparticle, where the kind of bioparticle Howell references is a cell.
Regarding claim 15, Howell, as modified by Ortyn and Kaduchak, teaches or renders obvious the biological sample analysis system according to claim 1 (as described above).
Howell further teaches that the at least one processor is further configured to irradiate a predetermined spot on the predetermined flow channel with the light (FIG. 2 C, region of interest labeled ROI), and the bioparticle moves in the predetermined flow channel so as to pass through the predetermined spot (the flow has to pass through the ROI to get from the input port of the flow channel located at the center of the spiral to the output ports. Also note that measurements are made there.).
Regarding claim 16, Howell, as modified by Ortyn and Kaduchak, teaches or renders obvious the biological sample analysis system according to claim 1 (as described above).
Howell further teaches that the bioparticle is labeled with one or more fluorescent dyes (section Bead preparation), the at least one processor is further configured to irradiate the bioparticle with the light including excitation light in one or more wavelength ranges (abstract, a microscope arc lamp of a standard fluorescence microscope is used for fluorescence imaging. Fluorescence imaging requires irradiating the image target with excitation light in one or more wavelength ranges.) and detect a luminance change as an event (FIG. 1).
Howell does not explicitly teach a spectroscopic optical system that disperses light emitted from the bioparticle.
In the same field of endeavor of fluorescent imaging flow cytometry, Ortyn teaches a spectroscopic optical system that disperses light emitted from the bioparticle (FIG. 25, dichroic filters 301-305) and a detection unit detecting each of the beams of light dispersed by the spectroscopic optical system (FIG. 25, detectors 321-325 collectively). By using dispersive optics, Ortyn distinguishes between multiple fluorescence colors, which can come from multiple dyes.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the event-based imaging flow cytometer of Howell with the dispersive optics of Ortyn to gain the benefit of using multiple fluorescent dyes to mark particles under study to distinguish them.
Regarding claim 17, Howell, as modified by Ortyn and Kaduchak, teaches or renders obvious the biological sample analysis system according to claim 16 (as described above).
Howell does not explicitly teach the use of a plurality of sensors.
In the same field of endeavor of fluorescent imaging flow cytometry, Ortyn teaches a plurality of sensors disposed for the beams of light dispersed by the spectroscopic optical system on a one-to-one basis (FIG. 25, detectors 321-325). Using multiple detectors allows Ortyn to detect images independently for each of the dispersed beams.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the event-based imaging flow cytometer of Howell with the multiple sensors of Ortyn to gain the benefit of capturing multiple images simultaneously.
Regarding claim 18, Howell teaches an information processing device including at least one processor (section Imaging setup, third paragraph, the computer running MATLAB) configured to:
generate subject information regarding a subject (by running MATLAB) on a basis of an event detected in each of a plurality of pixels that detects a luminance change of light from the subject as the event (FIG. 1); and
a flow channel (FIG. 2 C) wherein the flow channel is with a width of 1 mm or less (section Results, first paragraph, specifies a channel with widths of 360 µm and 60 µm along its two cross-sectional axes. Also see FIG. 3, which has a 200 µm scale bar. Comparing the length of the scale bar to the width of the channel even at the right-hand edge of the region of interest, the channel is only about half a mm wide).
While the flow channel disclosed by Howell is spiraled rather than straight, Howell does contemplate the use of sensor systems like the one Howell used with other channel designs (COL. 3, sentences 1-2), and the main purpose of Howell appears to be developing event-based imaging as a means to study microfluidics, describing the experiments presented as a “proof-of-principle” (abstract, sentence 6), rather than in inertially separating polystyrene beads with a spiral-shaped flow channel.
In the same field of endeavor of imaging and analyzing small moving objects, such as cells, Ortyn does teach a straight flow cell (FIG. 25, flow cell 306). By not including the spiral like that of Howell, Ortyn avoids the inertial separation of the particles across the fluid stream, allowing the whole width of the flow channel to be used for all sizes of particles. Note that it is generally considered obvious, when a particular function is not desired, to remove both an element (such as the curvature of a flow channel) and its undesired function (such as inertial particle separation). See MPEP 2144.04 II A.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the event-based imaging flow cytometer of Howell without straight the spiral of the flow cell, following the example of Ortyn, to avoid inertial particle separation if one does not consider inertial particle separation to be a desired function, for example, to more efficiently use the entire width of the flow cell for imaging of particles of all sizes. Note that Ortyn also describes the use of cells, a type of bioparticle, in the sample (abstract).
While Howell does discuss sorting of particles, it is in the context of using a spiral-shaped or otherwise curved flow channel to perform inertial separation of the particles, which is different from using bioparticle information generated by a processor to perform sorting in a straight channel as claimed, so Howell does not teach a claimed way to sort the bioparticle on the basis of the generated bioparticle information. Likewise, Ortyn provides a motivation to sort cells (a type of bioparticle) as background to their invention, but does not teach a particular way of doing the sorting itself (even if the imaging techniques of Ortyn would be useful as part of a cell sorting device).
In the same field of endeavor of imaging flow cytometry, Kaduchak teaches a device to sort the bioparticle on the basis of the generated bioparticle information (FIG. 7, sorting module 790, positioned downstream of the image detector 774 and described in paragraph 82). By including a sorting module, Kaduchak is able to separate the particles based on information gathered about them, such as cellular functions (paragraph 82).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the event-based imaging flow cytometer of Howell, as modified by Ortyn, to sort the particles after they are imaged in the manner of Kaduchak, to gain the predictable benefit of being able to perform high-speed sorting of cells or other bioparticles as motivated by Ortyn.
Regarding claim 19, Howell teaches an information processing method including generating subject information regarding a subject (section Imaging setup, third paragraph, running the MATLAB imaging pipeline) as the subject flows through a predetermined flow channel (FIG. 2 C), on a basis of an event detected in each of a plurality of pixels that detects a luminance change of light from the subject as the event (FIG. 1).
While the flow channel disclosed by Howell is spiraled rather than straight, Howell does contemplate the use of sensor systems like the one Howell used with other channel designs (COL. 3, sentences 1-2), and the main purpose of Howell appears to be developing event-based imaging as a means to study microfluidics, describing the experiments presented as a “proof-of-principle” (abstract, sentence 6), rather than in inertially separating polystyrene beads with a spiral-shaped flow channel.
In the same field of endeavor of imaging and analyzing small moving objects, such as cells, Ortyn does teach a straight flow cell (FIG. 25, flow cell 306). By not including the spiral like that of Howell, Ortyn avoids the inertial separation of the particles across the fluid stream, allowing the whole width of the flow channel to be used for all sizes of particles. Note that it is generally considered obvious, when a particular function is not desired, to remove both an element (such as the curvature of a flow channel) and its undesired function (such as inertial particle separation). See MPEP 2144.04 II A.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the event-based imaging flow cytometry method of Howell without straight the spiral of the flow cell, following the example of Ortyn, to avoid inertial particle separation if one does not consider inertial particle separation to be a desired function, for example, to more efficiently use the entire width of the flow cell for imaging of particles of all sizes. Note that Ortyn also describes the use of cells, a type of bioparticle, in the sample (abstract).
While Howell does discuss sorting of particles, it is in the context of using a spiral-shaped or otherwise curved flow channel to perform inertial separation of the particles, which is different from using bioparticle information generated by a processor to perform sorting in a straight channel as claimed, so Howell does not teach a claimed way to sort the bioparticle on the basis of the generated bioparticle information. Likewise, Ortyn provides a motivation to sort cells (a type of bioparticle) as background to their invention, but does not teach a particular way of doing the sorting itself (even if the imaging techniques of Ortyn would be useful as part of a cell sorting device).
In the same field of endeavor of imaging flow cytometry, Kaduchak teaches a device to sort the bioparticle on the basis of the generated bioparticle information (FIG. 7, sorting module 790, positioned downstream of the image detector 774 and described in paragraph 82). By including a sorting module, Kaduchak is able to separate the particles based on information gathered about them, such as cellular functions (paragraph 82).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the event-based imaging flow cytometer of Howell, as modified by Ortyn, to sort the particles after they are imaged in the manner of Kaduchak, to gain the predictable benefit of being able to perform high-speed sorting of cells or other bioparticles as motivated by Ortyn.
Regarding claim 20, Howell teaches a biological sample analysis method including:
irradiating a bioparticle in a biological sample with light (FIG. 2 A, Illumination. Note that intending to use an irradiation unit to illuminate a bioparticle in a biological sample does not impose a structural requirement on the irradiation unit that would distinguish that irradiation unit from one used to illuminate a nonbiological particle of similar size in a non-biological fluid) wherein the bioparticle flows through a flow channel wherein the flow channel is with a width of 1 mm or less (section Results, first paragraph, specifies a channel with widths of 360 µm and 60 µm along its two cross-sectional axes. Also see FIG. 3, which has a 200 µm scale bar. Comparing the length of the scale bar to the width of the channel even at the right-hand edge of the region of interest, the channel is only about half a mm wide);
detecting, as an event, a luminance change of light emitted from the bioparticle by irradiation with the light in each of a plurality of pixels (FIG. 1 demonstrates the function of an event-based camera); and
generating bioparticle information regarding the bioparticle on a basis of the event detected by each of the pixels (section Imaging setup, third paragraph, running the MATLAB imaging pipeline).
While Howell does not explicitly describe the samples used as biological samples, nor the micrometer-scale polystyrene beads therein as bioparticles, Howell does explicitly state that their results “confirm that event-based cameras can be used to track individual particle behaviours in the size range of commonly used biological cells” (section Particle tracking and velocity mapping, fourth paragraph).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have used the event-based imaging flow cytometer of Howell with bioparticles, such as cells, in the manner that Howell contemplated.
While the flow channel disclosed by Howell is spiraled rather than straight, Howell does contemplate the use of sensor systems like the one Howell used with other channel designs (COL. 3, sentences 1-2), and the main purpose of Howell appears to be developing event-based imaging as a means to study microfluidics, describing the experiments presented as a “proof-of-principle” (abstract, sentence 6), rather than in inertially separating polystyrene beads with a spiral-shaped flow channel.
In the same field of endeavor of imaging and analyzing small moving objects, such as cells, Ortyn does teach a straight flow cell (FIG. 25, flow cell 306). By not including the spiral like that of Howell, Ortyn avoids the inertial separation of the particles across the fluid stream, allowing the whole width of the flow channel to be used for all sizes of particles. Note that it is generally considered obvious, when a particular function is not desired, to remove both an element (such as the curvature of a flow channel) and its undesired function (such as inertial particle separation). See MPEP 2144.04 II A.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the event-based imaging flow cytometry method of Howell without straight the spiral of the flow cell, following the example of Ortyn, to avoid inertial particle separation if one does not consider inertial particle separation to be a desired function, for example, to more efficiently use the entire width of the flow cell for imaging of particles of all sizes. Note that Ortyn also describes the use of cells, a type of bioparticle, in the sample (abstract).
While Howell does discuss sorting of particles, it is in the context of using a spiral-shaped or otherwise curved flow channel to perform inertial separation of the particles, which is different from using bioparticle information generated by a processor to perform sorting in a straight channel as claimed, so Howell does not teach a claimed way of sorting the bioparticle on the basis of the generated bioparticle information. Likewise, Ortyn provides a motivation to sort cells (a type of bioparticle) as background to their invention, but does not teach a particular way of doing the sorting itself (even if the imaging techniques of Ortyn would be useful as part of a cell sorting device).
In the same field of endeavor of imaging flow cytometry, Kaduchak teaches a device for sorting the bioparticle on the basis of the generated bioparticle information (FIG. 7, sorting module 790, positioned downstream of the image detector 774 and described in paragraph 82). By including a sorting module, Kaduchak is able to separate the particles based on information gathered about them, such as cellular functions (paragraph 82).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the event-based imaging flow cytometry method of Howell, as modified by Ortyn, to sort the particles after they are imaged in the manner of Kaduchak, to gain the predictable benefit of being able to perform high-speed sorting of cells or other bioparticles as motivated by Ortyn.
Conclusion
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/PAUL SCHNASE/Examiner, Art Unit 2877
/TARIFUR R CHOWDHURY/Supervisory Patent Examiner, Art Unit 2877
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