DETAILED ACTION
The amendment filed on 04/21/2026 has been entered and fully considered. Claim 2 and 5-9 are canceled. Claims 1, 3-4, 10-14, 16-18 and 20-22 are pending, of which claim 1, 3-4, 10-14 and 16 are is amended.
Response to Amendment
In response to amendment, the examiner maintains rejection under 35 U.S.C. 101 and 35 U.S.C. 112(b), and rejection over the prior art established in the previous Office 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 .
Claim Rejections - 35 USC § 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.
Claim 1, 3-4, 10-14 and 16 are rejected under 35 U.S.C. 101 the claimed invention is directed to abstract idea without significantly more.
Claim 1 recites a method for estimating molecular complexity of a sample including: (a) performing MS/MS on a sample; (b) determining unique peaks in the resulting MS2 spectrum for a parent ion in the MS1 spectrum; and (c) calculating the molecular assembly index of the sample based on the number of unique peaks in the resulting MS2 spectrum, wherein the molecular assembly index is calculated by scaling the number of unique peaks in the MS2 spectrum by a magnitude (m) in the range of 0.3 to 0.7.
Under Step 2A, Prong One, claim 1 recites an abstract idea. In particular, claim 1 recites collecting spectral data, analyzing the spectral data by determining/counting unique peaks, and calculating a numerical index by applying a mathematical relationship to the counted peaks. The limitation of calculating the molecular assembly index by scaling the number of unique peaks by a magnitude in the range of 0.3 to 0.7 is a mathematical calculation. The additional peak-processing limitations, including disregarding low-intensity peaks, merging peaks within specified mass ranges, and disregarding peaks not present in a specified percentage of multiple spectra, are rules for analyzing data.
Under Step 2A, Prong Two, the claim does not integrate the abstract idea into a practical application. Although claim 1 recites performing MS/MS on a sample, this merely gathers the data used in the calculation. The claim does not recite an improvement to the mass spectrometer, an improvement to MS/MS technology, a new detector, a new ionization method, or any change in how the instrument operates. The claim also does not require any particular treatment, manufacture, transformation, or control step based on the calculated molecular assembly index. Rather, the claim ends with calculating/estimating a numerical value from spectral data.
Marshall teaches that “The concept of complexity is itself curious since even discussion about its nature is complicated. This is because there is currently no consensus on a single unambiguous definition [11]. In addition, descriptions of complexity and randomness are intrinsically related and many definitions of complexity are specific to certain fields or applications, as well as needing an often-biased observer which can end up comparing intrinsically different things.” (page 2, par 2). The different types of complexity discussed in Marshall are differentiated by the input used in their calculation - in other words, what the complexity is based on. For example, pathway complexity is based on the number of operators needed to construct an object from subunits. Therefore, a complexity of a sample or molecule can describe different aspects of a molecule, which are not necessarily physical properties of the molecule.
The recitation that the method estimates molecular complexity “based on the intrinsic properties of the sample and without external input” does not integrate the exception into a practical application. This language merely characterizes the source of the data used in the calculation and does not impose a meaningful technological limitation or require a practical application of the calculated value.
Under Step 2B, the claim does not include additional elements that amount to significantly more than the abstract idea. The additional elements, including performing MS/MS, selecting a parent ion, determining peaks, disregarding peaks, merging peaks, and calculating a scaled numerical value, amount to routine data collection and data analysis steps performed to obtain and process spectral information. Considered individually and as an ordered combination, the elements do not transform the abstract idea into patent-eligible subject matter.
Accordingly, claim 1 is directed to the abstract idea of collecting and analyzing spectral data and calculating a numerical index using mathematical rules, without significantly more. Therefore, claim 1 is rejected under 35 U.S.C. §101.
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 1, 3-4, 10, 12-14 and 16 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.
Claim 1 recites “wherein the molecular assembly index is the length of the shortest pathway required to construct molecules in the sample,” and further recites that the molecular assembly index is calculated by “scaling the number of unique peaks in the MS2 spectrum by a magnitude (m) in the range 0.3 to 0.7.” However, it is unclear whether the claimed “molecular assembly index” is the actual length of the shortest pathway required to construct molecules in the sample, or whether it is an estimated value obtained by scaling the number of unique peaks in the MS2 spectrum. The claim does not provide objective boundaries for determining how the scaled number of unique peaks corresponds to the “length of the shortest pathway.” Therefore, the metes and bounds of “molecular assembly index” are unclear.
Claim 1 is further indefinite because the term “unique peaks” lacks clear objective boundaries. Claim 1 recites multiple optional alternatives for determining unique peaks, including: (1) disregarding peaks having a maximum intensity of 0.5% or less than the highest recorded intensity in the MS1 spectrum; (2) merging all peaks within ±0.01 Da in the MS2 spectrum; (3) merging any peak within ±1.0 Da of an adjacent peak in the MS2 spectrum; and/or (4) disregarding all peaks not present in at least 25% of multiple MS2 spectra from the chosen parent ion. Because these alternatives are recited using “and/or,” it is unclear which rule or combination of rules must be applied to determine the unique peaks. Different alternatives may produce different numbers of unique peaks for the same MS2 spectrum, thereby producing different molecular assembly index values. Accordingly, the scope of the claim changes depending on which optional criterion is selected, and one of ordinary skill in the art would not be able to determine the metes and bounds of the claimed “unique peaks” with reasonable certainty.
Claim 1 is further indefinite because limitation (1) recites “disregarding peaks in the MS2 spectrum having a maximum intensity of 0.5% or less than the highest recorded intensity in the MS1 spectrum.” It is unclear how a peak intensity in the MS2 spectrum is to be compared to the highest recorded intensity in the MS1 spectrum, since MS1 and MS2 spectra may be acquired under different conditions and may have different intensity scales. Thus, the claim does not clearly define the objective threshold for disregarding MS2 peaks.
Claim 1 is further indefinite because the phrase “without external input” lacks clear objective boundaries. It is unclear what information or processing is excluded by “without external input.” For example, the claim does not clarify whether instrument calibration, peak-picking algorithms, user selection of the parent ion, user selection of the magnitude (m), threshold selection, or other processing parameters constitute “external input.” Therefore, one of ordinary skill in the art would not understand the scope of this phrase with reasonable certainty.
For at least these reasons, claim 1 fails to particularly point out and distinctly claim the subject matter regarded as the invention.
Claim Rejections - 35 USC § 103
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
Claim(s) 1, 3-4, 10, 12-14, 16-18 and 20-22 is/are rejected under 35 U.S.C. 103 as being unpatentable over Marshall et al. (ARXIV, 2017, IDS) (Marshell) in view of Merwin et al. (US 2018/0373833, IDS) (Merwin).
Regarding claim 1, Marshell teaches a method for estimating the molecular complexity of a sample (pathway complexity) (abstract), the method comprising:
(a) performing one of detection on a sample (Fig. 2, page 4-5);
(b) determining the unique peaks (unique substructures) (Fig. 2, page 4-5); and
(c) calculating the molecular assembly index of the sample based on the number of unique peaks (unique substructures) (Fig. 2, page 4-5),
wherein the method enables an estimation of the molecular complexity of the sample based on the intrinsic properties of the sample and without external input (Fig. 2, page 4-5).
Marshall discloses the core concept of quantifying the complexity of an object based on objective criteria. Specifically, Marshall teaches that complexity can be reduced to a quantifiable metric (pathway complexity) derived from features of the object itself, without requiring knowledge of the object’s function or external context (page 2, 6, 10-15). This directly corresponds to the applicant’s claimed concept of generating a molecular assembly index from features (unique peaks) of an analytical spectrum.
While Marshall does not explicitly disclose spectral peaks, Marshall’s framework teaches the general concept of deriving a complexity index from constituent features of an object.
Scaling or weighting features to generate a numerical index is a routine mathematical operation and would have been an obvious implementation choice to a person of ordinary skill in the art when applying Marshall’s complexity framework to experimentally obtained features, such as spectral peaks. For example, Merwin teaches scaling the number of unique peaks in the resulting MS2, NMR or IR spectrum by a magnitude (m) (par [0155]).
Thus, Marshall teaches the concept of calculating a complexity index from object features, and the scaling of feature counts by a magnitude represents an obvious mathematical modification.
Marshall teaches a framework for estimating the complexity of an object by analyzing features inherent to the object itself, rather than relying on external reference databases, prior classifications, or knowledge of origin or function.
1. Complexity in Marshall Is Derived from Intrinsic Structure
Marshall’s pathway complexity is determined by examining the internal composition and structure of the object—specifically, how the object can be decomposed into fundamental units and reassembled through a minimal sequence of operations.
Although Marshall uses illustrative examples (letters, shapes, graphs), the key teaching is not tied to the illustrative domain, but rather to the general principle that:
complexity is a function of the object’s intrinsic structural organization.
In Marshall, the complexity value is derived solely from the object’s internal features, not from:
reference libraries,
known identities,
biological function,
origin (natural vs synthetic), or
prior labeling.
Thus, Marshall teaches estimating complexity based on intrinsic properties of the object itself.
2. “Without External Input” Does Not Mean “Without Any Parameters”
Under patent law, selection of analytical parameters does not constitute disqualifying external input.
In Marshall:
The choice of basic units (e.g., nodes, components, primitives) is analogous to:
selecting m/z resolution,
selecting peak thresholds,
selecting fragmentation rules.
These are routine analytical design choices, not external informational inputs about the object.
Critically, Marshall does not require:
prior knowledge of the object’s identity,
external training data,
comparison to known objects, or
reference libraries.
Once the rules are set, the complexity is computed solely from the object itself, satisfying the “without external input” limitation as properly construed.
3. Marshall’s Framework Is Object-Agnostic
Marshall expressly emphasizes that its framework applies to unknown objects, not just known or classified ones. Complexity is computed without regard to:
chemical name,
biological role,
synthetic pathway,
empirical labels.
This directly aligns with Applicant’s claimed advantage of being agnostic to molecular origin and structure.
Thus, Marshall teaches that:
complexity can be estimated for previously unknown entities, based only on their internal composition.
Thus, Marshall teaches estimating the complexity of an object by deriving a numerical complexity measure from features inherent to the object itself, without reliance on external reference information, object identity, or prior classification. Although Marshall illustrates this concept using abstract examples, the underlying teaching is general and would have motivated a person of ordinary skill in the art to apply the same intrinsic-feature-based complexity estimation to molecular samples using experimentally obtained structural features, such as spectral peaks.
Marshall explicitly teaches that its probabilistic framework is intended to be generalized to biological and molecular systems (page 18). The absence of worked chemical examples does not negate the teaching that complexity may be quantified from measurable system characteristics. A person of ordinary skill in the art would have been motivated to apply Marshall’s framework to molecular data, including spectroscopic features, in order to obtain a quantitative index of complexity.
Marshall does not explicitly teach performing MS/MS on a sample, determining unique peaks in the resulting MS2 spectrum for a parent ion in the MS1 spectrum, and calculating the molecular assembly index by scaling the number of unique peaks in the MS2 spectrum by a magnitude in the range of 0.3 to 0.7. However, in the analogous art of natural product data analysis, Merwin teaches (a) performing MS/MS on a sample; and (b) determining the unique peaks in the resulting MS2 spectrum for a parent ion in the MS1 spectrum (Fig. 40, par [0145][0150] [0161] [0163]), scaling the number of unique peaks in the resulting MS2 by a magnitude (m) (par [0155]).
Thus, it would have been obvious to one of ordinary skill in the art to a) performing one of MS/MS, NMR or IR on a sample; and (b) determining the unique peaks in the resulting MS2 spectrum for a parent ion in the MS1 spectrum, NMR spectrum, or IR spectrum, and c) calculating the molecular assembly index of the sample based on the number of unique peaks in the resulting MS2, NMR or IR spectrum, because Merwin teaches that MS2 peaks is the real detected data relating to the substructures.
While Merwin is directed to natural product discovery, it explicitly discloses the use of MS/MS spectral analysis to characterize chemical structures (par [0018][0145][0150][0161][0163]). Merwin teaches the importance of spectral data, including the identification of unique peaks, in distinguishing and characterizing chemical compounds (Fig. 40, par [0163]). Marshall, in turn, teaches a framework for quantifying the complexity of an object by reference to features that define its structure.
A person of ordinary skill in the art, seeking to quantify molecular complexity, would have been motivated to apply Marshall’s framework of complexity quantification to the spectral features disclosed in Merwin, since both references are directed to extracting structural information from objects (molecules or otherwise) and reducing that information to a quantifiable measure.
Regarding claim 3, Merwin teaches that wherein step (a) comprises selecting a parent ion in the MS1 spectrum having a mass of 250 Da or more (Table 5).
Regarding claim 4, Merwin teaches that wherein step (a) comprises selecting a parent ion in the MS1 spectrum having a mass of 1000 Da or less (Fig. 40, Table 5).
Regarding claim 10, offsetting a number is a conventional mathematical manipulation.
Regarding claim 12, Merwin teaches selecting most intense peaks in the MS1 spectrum and recording MS2 spectra for each peak (Fig. 42). It would have been obvious to one of ordinary skill in the art to optimize the number of peaks by routine experimentation.
Regarding claim 13, it is conventional to exclude parent ions appearing twice in a set time interval, for example using dynamic exclusion (Methods of temporarily excluding parent ions from analysis are known) (see instant spec, page 11, lines 3-4).
Regarding claim 14, it is conventional to disregard all peaks with a relative intensify below 10% of the highest recorded intensity in each MS2 spectrum, in order to reduce the noise.
Regarding claim 16, it is conventional to calculate the molecular assembly index of the sample from the parent ion having the largest number of unique peaks in the MS2 spectrum, because the largest number of unique peaks in the MS2 spectrum contains the most information.
Regarding claim 17, Marshall teaches a method for the detection of life (abstract), the method comprising:
(a) estimating the molecular complexity of a sample according to the method of claim 1 (see claim 1 above); and
(b) comparing the calculated molecular assembly index of the sample to a threshold value (page 5).
Regarding claim 18, Marshall fairly suggests that wherein the sample is a sample of extraterrestrial material or the sample is a sample of terrestrial material, such as terrestrial soil, water, ice or rock (page 2).
Regarding claim 20, Marshall-Merwin teaches a method for identifying a candidate pharmaceutical or agrochemical molecule, the method comprising:
(a) estimating the molecular complexity of a sample in a molecular library using the method of claim 1 (see claim 1 above); and
(b) selecting a sample having a molecular assembly index greater than a threshold value as a candidate agrochemical or pharmaceutical molecule (Merwin, par [0178]).
Regarding claim 21, Merwin teaches that wherein the method comprises:
(c) separating the sample constituents (par [0195]); and optionally
(d) screening the sample constituents for biological activity (par [0256]).
Regarding claim 22, Merwin teaches that wherein the sample is an extract from a biological source, such as an extract from a fermentation broth or a plant extract (par [0181]).
Allowable Subject Matter
Claim 11 is 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 and with additional elements applies or uses the abstract idea in a meaningful way such that the claim as a whole is more than a drafting effort designed to monopolize the exception
Response to Arguments
Applicant's arguments filed 04/21/2026 have been fully considered but they are not persuasive.
Regarding 101 rejection
Applicant argues that the claims are not directed to an abstract idea because the claimed method estimates a physical property of a sample, namely molecular complexity, and because the molecular assembly index is allegedly analogous to a measured property such as melting point or binding affinity.
However, Examiner respectfully disagrees. Claim 1 is still directed to an abstract idea because the focus of the claim is collecting spectral data, identifying/counting peaks in the data, and calculating a numerical index using a mathematical relationship. The alleged physical nature of the sample does not change the character of the claimed advance, because the claim does not recite a new mass spectrometer, a new ionization technique, a new detector, or any improvement to the operation of the MS/MS instrument. Instead, the claim uses conventional MS/MS data as input to a calculation.
Applicant further argues that the molecular assembly index is an intrinsic property of the sample and is not merely a numerical result. Examiner is not persuaded. Even assuming the molecular assembly index corresponds to an intrinsic molecular characteristic, claim 1 still recites determining that characteristic by applying mathematical rules to spectral peak data. The claim expressly requires determining unique peaks and calculating the molecular assembly index by scaling the number of unique peaks by a magnitude in the range of 0.3 to 0.7. This is a mathematical calculation performed on collected data.
Besides, Marshall teaches that “The concept of complexity is itself curious since even discussion about its nature is complicated. This is because there is currently no consensus on a single unambiguous definition [11]. In addition, descriptions of complexity and randomness are intrinsically related and many definitions of complexity are specific to certain fields or applications, as well as needing an often-biased observer which can end up comparing intrinsically different things.” (page 2, par 2). The different types of complexity discussed in Marshall are differentiated by the input used in their calculation - in other words, what the complexity is based on. For example, pathway complexity is based on the number of operators needed to construct an object from subunits. Therefore, a complexity of a sample or molecule can describe different aspects of a molecule, which are not necessarily physical properties of the molecule.
Applicant also argues that the claimed method solves the technical problem of characterizing molecular complexity without external input. However, the claim does not integrate the calculation into a practical application. The claim ends with calculating/estimating the molecular assembly index and does not require any particular treatment, manufacture, transformation of the sample, control of an instrument, or other technological action based on the calculated value. The statement that the method is performed “without external input” merely limits the type of information used in the calculation and does not add significantly more than the abstract idea itself.
Applicant further points to claims 17 and 20 as examples of practical uses of the molecular assembly index. However, claim 1 is not limited to those applications. Claim 1 broadly covers estimating molecular complexity by processing spectral data and calculating a numerical index. Therefore, the alleged downstream uses in other claims do not show that claim 1 itself integrates the abstract idea into a practical application.
Accordingly, the claims remain directed to collecting spectral data, analyzing the data, and calculating/reporting a numerical index using a mathematical relationship. The additional limitations amount to data-gathering and routine data-processing steps and do not add significantly more than the abstract idea. Therefore, the rejection under 35 U.S.C. 101 is maintained.
Regarding 112 rejection
Applicant argues that the §112(b) rejection should be withdrawn because claim 1 has been amended to define “molecular assembly index,” limit the magnitude (m) to a range of 0.3 to 0.7, recite criteria for determining “unique peaks,” limit the method to MS/MS, and explain “without external input” in view of the specification.
Examiner respectfully acknowledges the amendments. The rejection regarding the lack of a numerical range for the magnitude (m) and the objection to multiple analytical modalities are withdrawn because claim 1 now recites a magnitude (m) in the range of 0.3 to 0.7 and is limited to MS/MS.
However, the §112(b) rejection is maintained at least with respect to the terms “molecular assembly index,” “unique peaks,” and “without external input.” Although claim 1 now states that the molecular assembly index is “the length of the shortest pathway required to construct molecules in the sample,” the claim does not provide objective boundaries for determining that shortest pathway from the claimed MS2 peak-counting method. Claim 1 calculates the molecular assembly index by scaling the number of unique peaks in the MS2 spectrum by a magnitude, but does not explain how the resulting scaled peak count objectively corresponds to the “shortest pathway required to construct molecules in the sample.” Thus, the claim remains unclear as to whether the molecular assembly index is the theoretical shortest assembly pathway, the experimentally scaled peak count, or an estimated value correlated with that pathway.
The term “unique peaks” also remains indefinite. Claim 1 recites several alternative criteria separated by “and/or,” including disregarding low-intensity peaks, merging peaks within ±0.01 Da, merging peaks within ±1.0 Da of an adjacent peak, and disregarding peaks not present in at least 25% of multiple MS2 spectra. Because these alternatives may produce different numbers of unique peaks for the same MS2 spectrum, the scope of the claim changes depending on which optional criterion is selected. The claim does not require a single objective rule or define how the alternatives are to be applied when they conflict. Therefore, one of ordinary skill in the art would not be able to determine the metes and bounds of the claimed “unique peaks” with reasonable certainty.
The phrase “without external input” also remains unclear. Applicant argues that the specification explains avoiding external information such as known molecular structures, databases, external weightings, ring counts, functional groups, or heteroatom counts. However, claim 1 does not positively define what information is excluded or what information may still be used. For example, the claim does not clarify whether instrument calibration data, user-selected parent ions, intensity thresholds, peak-picking algorithms, or user-selected values of the magnitude (m) constitute “external input.” Accordingly, the phrase does not provide clear objective boundaries for the scope of the claim.
For these reasons, although some issues have been rendered moot by amendment, claim 1 still fails to particularly point out and distinctly claim the subject matter regarded as the invention. Therefore, the rejection under 35 U.S.C. §112(b) is maintained.
Regarding 103 rejection
Applicant argues that neither Marshall nor Merwin teaches determining "unique peaks" as presently claimed, and that the claimed method estimates molecular complexity because the unique peak count reflects distinct building blocks and structural heterogeneity. Applicant further argues that Marshall is directed only to a theoretical complexity analysis and that Merwin merely identifies compounds using spectral data.
However, Examiner disagrees. Marshall expressly teaches that molecular complexity may be quantified as the length of the shortest assembly pathway required to construct a molecule, i.e., a molecular assembly index. Marshall further teaches that complexity is derived from intrinsic features of the molecule rather than external reference information. Merwin teaches obtaining MS/MS spectra from selected parent ions and processing spectral peaks obtained from the spectra. It is well known in the mass spectrometry art to merge nearby peaks, disregard low-intensity peaks, and otherwise process spectral data to remove noise and improve the quality of extracted spectral features. Therefore, the claimed peak-processing operations represent routine optimization of known spectral analysis techniques applied to known MS/MS data.
Applicant's argument that the claimed unique peak count reflects distinct building blocks is not commensurate with the scope of the claims. Claim 1 merely requires determining unique peaks in an MS2 spectrum and calculating a molecular assembly index based on the number of unique peaks. Claim 1 does not require that each unique peak correspond to a distinct building block, distinct substructure, or any verified measure of structural heterogeneity. Rather, the claim broadly encompasses calculating the index from a processed count of unique peaks. The combination of Marshall and Merwin teaches or suggests using experimentally obtained spectral features as intrinsic molecular information and would have rendered it obvious to use the processed peak count as an input to Marshall's complexity framework, with a reasonable expectation of success.
Applicant further argues that Merwin is directed to compound identification rather than complexity estimation. However, a reference is not limited to the particular purpose for which it was designed. Merwin teaches the relevant spectral acquisition and feature extraction techniques relied upon in the rejection. One of ordinary skill in the art would have recognized that the spectral features extracted by Merwin are suitable intrinsic molecular characteristics that could be used within Marshall's complexity framework. Substituting one known source of intrinsic molecular information for another constitutes the predictable use of prior-art elements according to their established functions.
Accordingly, the combination of Marshall and Merwin does not rely on impermissible hindsight, but rather on the application of known mass spectrometric feature extraction techniques to Marshall's known molecular complexity framework. Therefore, the rejection under 35 U.S.C. 103 is maintained.
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 XIAOYUN R XU, Ph. D. whose telephone number is (571)270-5560. The examiner can normally be reached M-F 8am-5pm.
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/XIAOYUN R XU, Ph.D./ Primary Examiner, Art Unit 1797
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