DETAILED ACTION
Response to Arguments
Applicant has amended claims 1, 3, 4, 6, 14, 19, and 24; with claims 1, 3-4, 6, 11, 14, 17, 19-20, 22-24, and 26 the elected and currently pending claims.
Applicant's arguments filed 12/16/2025 have been fully considered but they are not persuasive. Applicant argues that the PMT assisted sorting in Marois (Marois E, Scali C, Soichot J, Kappler C, Levashina EA, Catteruccia F. High-throughput sorting of mosquito larvae for laboratory studies and for future vector control interventions. Malaria Journal. 2012 Dec;11:1-9.) does not constitute an image because a PMT outputs a single pixel value. However, Examiner contends that the broadest reasonable interpretation of an image would include a single pixel. The claim does not require a specific resolution, just that the image provide enough information to sort larvae into categories. In the case of the PMTs in Marois levels of yellow, green and red are detected, which can be thought of as a single pixel multicolor channel image, that is then utilized to categorize larvae (Marois Section Methods – COPAS-assisted larval sorting - ¶1- found on p. 3 and Fig. 2- found on p. 2). Applicant further argues that image features could not be detected, but claim 3, 6, and 19 are to color-related features which is what the Green, Yellow, and Red PMTs of Marois is measuring. The broad claim language of “and/or” does not require structures or organs of interest of the pre-adult organism, therefore the color features provided by the PMTs are considered to teach the disjunctive “or” features limitation. Examiner would like to point out that independent claim 4 is even more broad and does not require the classification of the organism be based on detected features. Furthermore, the trained neural network claimed in claim 17 is broadly claimed with no details as to what steps the network performs, its inputs or outputs, or what it is trained with. Additional details found in the application’s published specification ¶169, 293, 295, 298, and 300 would likely overcome the reference. Therefore this action is made FINAL.
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, 3-4, 6, 11, 19, 20, and 26 is/are rejected under 35 U.S.C. 103 as being unpatentable over Du (Pub. No. US2020/0359608 A1) in view of Marois (Marois E, Scali C, Soichot J, Kappler C, Levashina EA, Catteruccia F. High-throughput sorting of mosquito larvae for laboratory studies and for future vector control interventions. Malaria Journal. 2012 Dec;11:1-9.).
Regarding claim 1, Du discloses A computer implemented method for automated detection of features, structures and/or organs in pre-adult organisms being shrimp, fish or insects, the method (Du ¶[0047]-[0048]; a method where larvae are sent through a larvae counter that can compare size and length of a desired larvae implemented on a processor.) is performed in a flow-system comprising a fluidic channel with an inlet, (Du ¶[0048] and Fig. 4; an inlet for the channel can be seen as element 162. ) a detection region and at least one outlet, an electro-optical module for monitoring the detection region and a processor; (Du ¶[0044] and Fig. 4; a detector is positioned to detect (capture an image) larvae above the water outlet valve, element 184. An image capture device is listed as a possibility of detectors.) wherein the pre-adult organisms flow via a fluidic channel towards the detection region, while suspended in liquid media (Du ¶[0042]-[0043] and Fig. 4; a funnel with larvae to be counted is above the fluidic channel. A water inlet and outlet valve are places to help the specimens flow to the fluidic channel. Specimens flow between the upper and lower portion while in fluid (i.e. suspended in liquid media).) a) imaging an individual organism in the detection region while suspended in the liquid media by one or more sensors of the electro-optical module, thereby acquiring at least one image of the pre-adult organism, (Du ¶[0044]; an image sensor is used to take an image of a larva.) b) transmitting the acquired at least one image of the pre-adult organism to the processor, (Du ¶ [0048]; the processor is passed information from the detector to count the larva.) c) analyzing the obtained at least one image of the pre-adult organism by the processor, for detecting presence of one or more of said features of the pre-adult organism in the acquired at least one image, structures and/or organs of interest.(Du ¶[0044] and [0047]; comparing (analyzing) features of size and length are disclosed.)
Du does not explicitly disclose based on the presence of one or more of said features of the pre-adult organism in the acquired at least one image, classifying the pre-adult organisms being shrimp, fish or insects at least into two classes, wherein at least one of the at least two classes is associated with one of said one or more outlets, wherein said two classes being selected from at least the following pairs: male and non-male, female and non-female, male and female, alive and dead, healthy and sick, strong and weak, quickly developing or retarded; wherein the pre-adult organisms are in the larval stage.
Marois, however, discloses based on the presence of one or more of said features of the pre-adult organism in the acquired at least one image, classifying the pre-adult organisms being shrimp, fish or insects at least into two classes, (Marois Results – Rapid and precise establishment of homozygous transgenic Anopheles gambia lines by COPAS sorting - ¶1 – found on p. 3-4; Larvae are distinguished as males or females (classified) based on fluorescent markers. Marois Section Methods – COPAS-assisted larval sorting - ¶1- found on p. 3 and Fig. 2- found on p. 2; wherein the PMT outputs can be thought of as a multichannel single pixel image.) wherein at least one of the at least two classes is associated with one of said one or more outlets, (Marois Results – Rapid and precise establishment of homozygous transgenic Anopheles gambia lines by COPAS sorting - ¶1 – found on p. 3-4; Larvae are separated based on sex and therefore associated with an outlet.) wherein said two classes being selected from at least the following pairs: male and non-male, female and non-female, male and female, alive and dead, healthy and sick, strong and weak, quickly developing or retarded (Marois Results – Rapid and precise establishment of homozygous transgenic Anopheles gambia lines by COPAS sorting - ¶1 – found on p. 3-4; Larvae are separated based on sex and classified as male or female.); wherein the pre-adult organisms are in the larval stage. (Marois Methods – Flurescence microscopy; larvae are imaged and sorted (see also Results – Rapid and precise establishment of homozygous transgenic Anopheles gambia lines by COPAS sorting - ¶1 – found on p. 3-4).)
It would have been obvious, before the effective filing date of the claimed invention, to one of ordinary skill in the art to modify the method of Du with teachings of Marois by including the classification of mosquito sex using detected image features and sorting the mosquitos based on the classification from Marois in order to control vector-borne infectious diseases (Marois Abstract- Background).
Regarding claim 3, the combination of Du and Marois discloses the claim limitations with regards to claim 1, as described above. They further disclose further performing sorting of the organisms by the following steps : performing classification of the individual organism, using the acquired at least one image of the pre-adult organism, wherein said classification being based on one or more morphologic features of the pre-adult organisms and/or one or more color-related features of the pre-adult organisms and/or one or more sex-related features of the pre-adult organisms included in the at least one image of the pre-adult organism, and (Marois Results – Rapid and precise establishment of homozygous transgenic Anopheles gambia lines by COPAS sorting - ¶1 – found on p. 3-4 and Figs. 1 and 3; fluorescence markers (based on color features of microscopic images see Figs. 1 and 3) indicate sex of the larvae. Wherein it would have been obvious to include the classification of mosquito sex using detected image features and sorting the mosquitos based on the classification from Marois in order to control vector-borne infectious diseases.) sorting said organism based on its classification. (Marois Results – Rapid and precise establishment of homozygous transgenic Anopheles gambia lines by COPAS sorting - ¶1 – found on p. 3-4; Larvae are separated based on sex and classified as male or female.)
Regarding claim 4, Du discloses A system for automated detection of one or more features, structures and/or organs in pre-adult organisms being shrimp, fish or insects, the system comprising: (Du ¶[0047]-[0048]; a system where larvae are sent through a larvae counter that can compare size and length of a desired larvae implemented on a processor.) a) a fluidic channel comprising an inlet, , (Du ¶[0048] and Fig. 4; an inlet for the channel can be seen as element 162. ) a detection region and at least one outlet, said channel is configured to allow flowing there-through of the pre-adult organisms suspended in liquid media; (Du ¶[0044] and Fig. 4; a detector is positioned to detect (capture an image) larvae above the water outlet valve, element 184. An image capture device is listed as a possibility of detectors.) b) an electro-optical module for monitoring the detection region, (Du ¶[0044]; an image sensor is used to take an image of a larva.) c) a processor in communication with the electro-optical module, wherein said electro-optical module comprises at least one sensor and is configured to acquire at least one image of the pre-adult organisms by imaging an individual organism while suspended in the liquid media, to transmit said at least one image of the organism to the processor, and(Du ¶ [0048]; the processor is passed information from the detector to count the larva. Du ¶[0042]-[0043] and Fig. 4; a funnel with larvae to be counted is above the fluidic channel. A water inlet and outlet valve are places to help the specimens flow to the fluidic channel. Specimens flow between the upper and lower portion while in fluid (i.e. suspended in liquid media).) the processor is configured to receive, process and analyze the at least one image of the pre-adult organisms acquired by the electro-optical module so as to detect said features of the pre-adult organism, structures and/or organs of interest in the organism. .(Du ¶[0044] and [0047]; comparing (analyzing) features of size and length are disclosed.)
Du does not explicitly disclose wherein the pre-adult organisms being shrimp, fish or insects are classified at least into two classes, wherein at least one of the at least two classes is associated with one of said one or more outlets, wherein said two classes being selected from at least the following pairs: male and non-male, female and non-female, male and female, alive and dead, healthy and sick, strong and weak, quickly developing or retarded; wherein the pre-adult organisms are in the larval stage.
Marois, however, discloses wherein the pre-adult organisms being shrimp, fish or insects are classified at least into two classes, (Marois Results – Rapid and precise establishment of homozygous transgenic Anopheles gambia lines by COPAS sorting - ¶1 – found on p. 3-4; Larvae are distinguished as males or females (classified) based on fluorescent markers.) wherein at least one of the at least two classes is associated with one of said one or more outlets, (Marois Results – Rapid and precise establishment of homozygous transgenic Anopheles gambia lines by COPAS sorting - ¶1 – found on p. 3-4; Larvae are separated based on sex and therefore associated with an outlet.) wherein said two classes being selected from at least the following pairs: male and non-male, female and non-female, male and female, alive and dead, healthy and sick, strong and weak, quickly developing or retarded (Marois Results – Rapid and precise establishment of homozygous transgenic Anopheles gambia lines by COPAS sorting - ¶1 – found on p. 3-4; Larvae are separated based on sex and classified as male or female.); wherein the pre-adult organisms are in the larval stage. (Marois Methods – Flurescence microscopy; larvae are imaged and sorted (see also Results – Rapid and precise establishment of homozygous transgenic Anopheles gambia lines by COPAS sorting - ¶1 – found on p. 3-4).)
It would have been obvious, before the effective filing date of the claimed invention, to one of ordinary skill in the art to modify the method of Du with teachings of Marois by including the classification of mosquito sex using detected image features and sorting the mosquitos based on the classification from Marois in order to control vector-borne infectious diseases (Marois Abstract- Background).
Regarding claim 6, the combination of Du and Marois discloses the claim limitations with regards to claim 4, as described above. They further disclose configured for sorting of said pre-adult organisms, further comprising a controller in-communication with said processor, wherein the processor being further configured to classify the organism based on the analysis results, on one or more morphologic features of the pre-adult organisms and/or one or more color-related features of the pre-adult organisms and/or one or more sex-related features of the pre-adult organisms, (Marois Results – Rapid and precise establishment of homozygous transgenic Anopheles gambia lines by COPAS sorting - ¶1 – found on p. 3-4 and Figs. 1 and 3; fluorescence markers (based on color features of microscopic images see Figs. 1 and 3) indicate sex of the larvae. Wherein it would have been obvious to include the classification of mosquito sex using detected image features and sorting the mosquitos based on the classification from Marois in order to control vector-borne infectious diseases.) and to instruct the controller to sort said organism based on the classification. (Marois Results – Rapid and precise establishment of homozygous transgenic Anopheles gambia lines by COPAS sorting - ¶1 – found on p. 3-4; Larvae are separated based on sex and classified as male or female.)
Regarding claim 11, the combination of Du and Marois the claim limitations with regards to claim 1, as described above. They further disclose wherein the organisms flow through the fluidic channel one at a time. (Du ¶[0013]; larvae are directed through a passage one at a time.)
Regarding claim 19, the combination of Du and Marois discloses the claim limitations with regards to claim 1, as described above. They further disclose wherein said features of the pre-adult organism for analyzing the organisms include one or more features of the pre-adult organism from at least one of the following non-exhaustive groups : a first group of morphologic features comprising: overall size of the organism, morphology of the organism, shape, segment size ratio, - a second group of color-related features comprising: absorption, transmission, IR (Infrared) absorption, IR transmission, color, fluorescence, - a third group of sex-related features comprising: gonad disc morphology, secondary sex organ morphology, gonad size; gonad morphology, gonad autofluorescence, size of testes, size of male accessory glands, morphology of testes, morphology of male accessory glands, autofluorescence of testes, autofluorescence of male accessory glands, size of the developing male and female primary or secondary reproductive structures, primitive sex organs, morphology of the developing male and female primary or secondary reproductive structures, autofluorescence of the developing male and female primary or secondary reproductive structures and any combination thereof. (Du ¶ [0047]; larvae are compared using size and length (overall size of the organism).)
Regarding claim 20, the combination of Du and Marois discloses the claim limitations with regards to claim 4, as described above. They further disclose wherein the electro-optical module comprises at least one of one or more light sources configured to illuminate the detection region, (Du ¶[0045]; a light source opposite the detector is disclosed.) one or more image sensors, (Du ¶[0044] and Fig. 4; An image capture device is listed as a possibility of detectors.)
Regarding claim 26, the combination of Du and Marois discloses the claim limitations with regards to claim 4, as described above. They further discloses wherein the fluidic channel is a transparent capillary having a square or rectangular cross-section (Du ¶ [0035]; a cylindrical pipe that is transparent is disclosed. The lengthwise cross-section of a cylinder is a rectangle.)
Claim(s) 14, 17, and 22 is/are rejected under 35 U.S.C. 103 as being unpatentable over Du (Pub. No. US2020/0359608 A1) in view of Marois (Marois E, Scali C, Soichot J, Kappler C, Levashina EA, Catteruccia F. High-throughput sorting of mosquito larvae for laboratory studies and for future vector control interventions. Malaria Journal. 2012 Dec;11:1-9.) and Lepek (Pub. No. WO2019/008591 A2).
Regarding claim 14, the combination of Du and Marois discloses the claim limitations with regards to claim 4, as described above.
The combination of Du and Marois does not explicitly disclose wherein images not containing the organisms of interest are used for adjusting and pre-processing the images containing said organisms.
Lepek, however, discloses wherein images not containing the organisms of interest are used for adjusting and pre-processing the images containing said organisms. (Lepek p. 15 lines 14-19 and p. 15 line 30 -p. 16 line 4; background images can be used to train a neural network which outputs detection and classification of mosquitos.)
It would have been obvious, before the effective filing date of the claimed invention, to one of ordinary skill in the art to modify the method of the combination of Du and Marois with teachings of Lepek by including the classification of mosquito sex using detected image features (including using the neural network trained using background images) from Lepek in order provide a region of detected specimens that need to be destroyed, giving the system range rather than just a center point as a target. (Lepek p. p. 15 line 30 -p. 16 line 4).
Regarding claim 17, the combination of Du and Marois discloses the claim limitations with regards to claim 1, as described above.
The combination of Du and Marois does not explicitly disclose wherein said steps of detecting and/or sorting comprise using a trained neural network.
Lepek, however, discloses wherein said steps of detecting and/or sorting comprise using a trained neural network. (Lepek p. 14 line 27 - p. 15 line 4; detection and classification (part of sorting) are disclosed as being performed using a neural network. P. 15 lines 14-22 explain some training details.)
It would have been obvious, before the effective filing date of the claimed invention, to one of ordinary skill in the art to modify the method of the combination of Du and Marois with teachings of Lepek by including the classification of mosquito sex using detected image features (including using the neural network trained using background images) from Lepek in order provide a region of detected specimens that need to be destroyed, giving the system range rather than just a center point as a target. (Lepek p. p. 15 line 30 -p. 16 line 4).
Regarding claim 22, the combination of Du and Marois disclose the claim limitations with regards to claim 6, as described above.
the combination of Du and Marois does not explicitly disclose wherein the fluidic channel further comprises a separation region, wherein said separation region is located between the detection region and the at least one outlet; and wherein said separation region comprises at least one guiding tool controlled by the controller and configured to guide said organism to an outlet associated with the organism's classification.
Lepek, however, discloses wherein the fluidic channel further comprises a separation region, wherein said separation region is located between the detection region and the at least one outlet; and wherein said separation region comprises at least one guiding tool controlled by the controller and configured to guide said organism to an outlet associated with the organism's classification. (Lepek p. 21 line 31- p.22 line 9; insects are mechanically sorted based on their classification. P. 11 lines 30-35, a robotic arm (guiding tool) for handling during sorting is described.)
It would have been obvious, before the effective filing date of the claimed invention, to one of ordinary skill in the art to modify the system of the combination of Du and Marois with teachings of Lepek by including a robotic arm for sorting from Lepek in order provide a way to easily sort specimens that are completely submerged in water.
8. Claim(s) 23 is/are rejected under 35 U.S.C. 103 as being unpatentable over Du (Pub. No. US2020/0359608 A1) in view of Marois (Marois E, Scali C, Soichot J, Kappler C, Levashina EA, Catteruccia F. High-throughput sorting of mosquito larvae for laboratory studies and for future vector control interventions. Malaria Journal. 2012 Dec;11:1-9.) and Herranz (Pub. No. EP3430900 A1 from applicants admitted prior art).
Regarding claim 23, the combination of Du and Marois discloses the claim limitations with regards to claim 4, as described above.
the combination of Du and Marois does not explicitly disclose wherein the fluidic channel further comprises a destruction region; wherein said destruction region comprises at least one destroying tool in-communication with the controller; and wherein said destroying region has "on" and "off' configurations operated by the controller.
Herranz, however, discloses wherein the fluidic channel further comprises a destruction region; wherein said destruction region comprises at least one destroying tool in-communication with the controller; and wherein said destroying region has "on" and "off' configurations operated by the controller. (Herranz ¶18; pupae that are classified in the correct size group are eliminated, by laser or series of suction nozzles and pupae are then removed form conveyance system. The system eliminated pupae that are above or below the threshold (“on” configuration) and doesn’t eliminate the other group (“off configuration).)
It would have been obvious, before the effective filing date of the claimed invention, to one of ordinary skill in the art to modify the system of the combination of Du and Marois with teachings of Herranz to include the classification of mosquito sex using detected image features and sorting the mosquitos based on the classification from Herranz in order effectively perform elimination of mosquitos in pest control.
Claim(s) 24 is/are rejected under 35 U.S.C. 103 as being unpatentable over Du (Pub. No. US2020/0359608 A1) in view of Marois (Marois E, Scali C, Soichot J, Kappler C, Levashina EA, Catteruccia F. High-throughput sorting of mosquito larvae for laboratory studies and for future vector control interventions. Malaria Journal. 2012 Dec;11:1-9.) and Yamaguchi (Pub. No. WO2019035346 A1 see attached translation for line numbers).
Regarding claim 24, the combination of Du and Marois discloses the claim limitations with regards to claim 4, as described above.
Du discloses the use of lights to control the movement of larvae (Du ¶ [0049]) and that larvae are directed to the counting module “one at a time” (Du ¶ [0013]) but the combination of Du and Marois does not explicitly further comprising an additional sensor in communication with the controller, wherein the controller is further configured to control the amount of organisms at the entrance to the fluidic channel based on the data acquired by said additional sensor, to thereby allow passage of single organism at a time to the fluidic channel.
Yamaguchi, however, discloses further comprising an additional sensor in- communication with the controller, wherein the controller is further configured to control the amount of organisms at the entrance to the fluidic channel based on the data acquired by said additional sensor, to thereby allow passage of single organism at a time to the fluidic channel. (Yamaguchi ¶[0007]; a system is described with an ultrasonic sensor to sense when fish pass one at a time.)
It would have been obvious, before the effective filing date of the claimed invention, to one of ordinary skill in the art to modify the system of the combination of Du and Marois with teachings of Yamaguchi by including the ultrasonic sensor to sense when specimens pass one by one from Yamaguchi in order to supply an indicator of when frequency of light should be changed in Du.
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MEREDITH TAYLOR whose telephone number is (571)270-5805. The examiner can normally be reached M-Th 7:30-5.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Vincent Rudolph can be reached on (571)272-8243. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/MEREDITH TAYLOR/Examiner, Art Unit 2671
/VINCENT RUDOLPH/Supervisory Patent Examiner, Art Unit 2671
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