U.S. patent application number 14/798709 was filed with the patent office on 2016-02-11 for systems and methods for baseline correction using non-linear normalization.
The applicant listed for this patent is APPLIED BIOSYSTEMS, LLC. Invention is credited to Stephen J. Gunstream.
Application Number | 20160040222 14/798709 |
Document ID | / |
Family ID | 39666424 |
Filed Date | 2016-02-11 |
United States Patent
Application |
20160040222 |
Kind Code |
A1 |
Gunstream; Stephen J. |
February 11, 2016 |
Systems And Methods For Baseline Correction Using Non-Linear
Normalization
Abstract
Systems and methods are provided for calibrating emission data
or other information signals collected during a polymerase chain
reaction (PCR), amplification reaction, assay, process, or other
reaction. Calibration of multiple detectable materials can be
achieved during a single cycle or run, or during a plurality of
runs of the reaction. A reading from every well, container, or
other support region of a sample support does not have to be taken.
Interpolation can be used to determine values for emission data or
other information signals that were not taken, or are unknown,
using detected emission data, or other detected information
signals. By calibrating the detected emission data and the
interpolated data, a more accurate reading of emission data or
information signal can be obtained.
Inventors: |
Gunstream; Stephen J.; (Iowa
City, IA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
APPLIED BIOSYSTEMS, LLC |
Carlsbad |
CA |
US |
|
|
Family ID: |
39666424 |
Appl. No.: |
14/798709 |
Filed: |
July 14, 2015 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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13584950 |
Aug 14, 2012 |
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14798709 |
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13070273 |
Mar 23, 2011 |
8265883 |
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13584950 |
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12022087 |
Jan 29, 2008 |
8005628 |
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13070273 |
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60898064 |
Jan 29, 2007 |
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Current U.S.
Class: |
702/19 |
Current CPC
Class: |
G01N 2021/6441 20130101;
C12Q 1/6851 20130101; G01N 21/274 20130101; C12Q 1/6851 20130101;
G01N 21/6486 20130101; G01N 21/6428 20130101; G01N 2021/6439
20130101; G16B 30/00 20190201; G01N 2201/12746 20130101; C12Q
2545/101 20130101; G01N 2201/12 20130101; C12Q 2545/113
20130101 |
International
Class: |
C12Q 1/68 20060101
C12Q001/68; G06F 19/22 20060101 G06F019/22; G01N 21/64 20060101
G01N021/64 |
Claims
1. A computer-implemented method for generating a normalized
amplification profile, the method comprising: receiving emission
data detected in an amplification reaction; identifying a baseline
signal in the emission data; generating a normalization quantity
based on the emission data and the identified baseline signal;
generating the normalized amplification profile based on a ratio of
the emission data to the normalization quantity; generating a
threshold cycle based on the normalized amplification profile; and
quantifying an original sample amount based on the threshold
cycle.
2. The computer-implemented method of claim 5, wherein the
instructions further comprise instructions for subtracting an
offset from the normalized amplification profile.
3. The computer program product of claim 5, wherein the
instructions further comprise instructions for generating a
plurality of normalized amplification profiles, and performing a
uniformity calibration based on the plurality of normalized
amplification profiles.
4. A system for generating a normalized amplification profile,
comprising: a processor; and a memory for storing instructions
executable by the processor, the instructions including
instructions for: receiving emission data detected in an
amplification reaction, identifying a baseline signal in the
emission data, generating a normalization quantity based on the
emission data and the identified baseline signal, generating the
normalized amplification profile based on a ratio of the emission
data to the normalization quantity, generating a threshold cycle
based on the normalized amplification profile, and quantifying an
original sample amount based on the threshold cycle.
5. The system of claim 4, wherein identifying a baseline signal
comprises identifying a baseline signal based on a derivative of
the emission data.
6. The system of claim 4, wherein the instructions further include
instructions for subtracting an offset from the normalized
amplification profile.
7. The system of claim 4, wherein the instructions further include
instructions for generating a plurality of normalized amplification
profiles.
8. A computer-readable storage medium encoded with instructions,
executable by a processor, for generating a normalized
amplification profile, the instructions comprising instructions
for: receiving emission data detected in an amplification reaction,
identifying a baseline signal in the emission data, generating a
normalization quantity based on the emission data and the
identified baseline signal, generating the normalized amplification
profile based on a ratio of the emission data to the normalization
quantity, generating a threshold cycle based on the normalized
amplification profile, and quantifying an original sample amount
based on the threshold cycle.
9. The computer-readable storage medium of claim 8, wherein the
instructions further comprise instructions for subtracting an
offset from the normalized amplification profile.
10. The computer program product of claim 8, wherein the
instructions further comprise instructions for generating a
plurality of normalized amplification profiles, and performing a
uniformity calibration based on the plurality of normalized
amplification profiles.
Description
RELATED APPLICATION
[0001] This application is a continuation of U.S. patent
application Ser. No. 13/584,950 filed Aug. 14, 2012, which is a
continuation of U.S. patent application Ser. No. 13/070,273 filed
Mar. 23, 2011, which is a continuation of U.S. patent application
Ser. No. 12/022,087 filed Jan. 29, 2008, which claims priority to
U.S. Provisional Patent Application No. 60/898,064 filed Jan. 29,
2007, all of which are incorporated herein by reference.
BACKGROUND
[0002] Real-time polymerase chain reaction (RT-PCR) technology, as
presently practiced, relies upon the accurate detection of
fluorescent emission signals above an initial baseline. The
baseline signal can represent a combination of spurious or unwanted
signal contributions such as the residual fluorescence contributed
by the plastic or other material of a sample plate, the
fluorescence of a running buffer or other non-reactant liquid
material, noise in the optical detector or detection electronics,
or some other source of background signal noise or detection floor
that is not a product of the amplification or other reaction. In
various known RT-PCR implementations, better accuracy in the
detection of the amplification signal, and hence original sample
quantity, is frequently sought by characterizing the baseline floor
over the first few PCR cycles, or pre-signal detection cycles, and
then subtracting the baseline from the detected emissions once an
inflection point into the exponential region has been reached. In
general, a RT-PCR emission or other amplification graph, chart, or
profile typically displays three sections or regions: an initial
baseline region, an exponential region, and a plateau region. An
example of this is shown in the illustration in FIG. 1. The
baseline region can display a linear, or approximately linear, or
other form over the first several cycles, as reaction chemistries
have not liberated enough marker dye to rise over the detected
background. The next, exponential region represents the rise of
amplification product over the noise or background floor, as the
PCR reaction kinetics come into force. The plateau region typically
exhibits a final flattening or tapering of detected emission
intensities, as reagents are exhausted. The combined amplification
profile usually resembles a sigmoid or S-shape. Typically, RT-PCR
systems determine a threshold cycle (C.sub.T) which represents the
cycle point at which the exponential threshold is reached. From
that parameter the original sample quantity can be back-calculated,
using standard curves.
[0003] Known baselining techniques involve the adjustment or
normalization of the detected emission signal by subtracting the
identified baseline in the first few cycles from the detected
fluorescent intensities of the RT-PCR marker dyes in later cycles,
to sharpen the accuracy of the absolute value of detected emission
data in the exponential and/or plateau regions of the amplification
profile. Baselining that relies upon a subtraction operation to
perform normalization can, however, cause certain effects in the
resulting modified or normalized data. For one, if a baselining
operation is performed on a per-filter or per-dye wavelength basis,
the baselining operation can determine different baselines for
different filters or dyes, which after subtraction from the
emission data lead to differing results for different detected
channels. For another, if individual wells of a sample plate or
other support or container are individually processed to create
separate baselines on a per-well basis, the set of resulting
baselined signals can be at a different scale or level.
Furthermore, known baselining techniques involve the initial
computation of baseline levels over the first few cycles, before
exponential or plateau-region reactions takes place. Subtracting
those baseline levels from a set of exponential or plateau-region
data captured at a later point can introduce inaccuracies, for
instance if the baseline level drifts over later cycles. A need
exists for baseline and related techniques that address these and
other issues.
SUMMARY
[0004] Systems and methods according to various embodiments of the
present teachings relate to techniques and platforms to capture,
identify, and characterize the baseline level of detected emission
data of an amplification reaction, and to normalize the detected
intensity data in an identified exponential region, plateau region,
or other region of the detected data. According to various
embodiments, the adjustment or normalization of the emission data
can be performed by dividing the raw detected emission signal by
the identified baseline, resulting in a normalized, scaled, or
weighted representation of the emission signal. According to
various embodiments, because each normalized signal can increase
from a normalized background level of unity or close to unity
(since the initial amplification cycles show a detected signal
equal to the background or baseline signal), a uniform or
consistent scale can be created across different dyes, filters,
wells, or plates. According to various embodiments, the division of
the detected signal by the identified baseline can be performed in
real-time, so that the resulting adjusted or normalized signal is
output as the RT-PCR operation or other analysis takes place.
FIGURES
[0005] FIG. 1 illustrates an exemplary PCR amplification profile or
curve, according to various embodiments of the present
teachings.
[0006] FIG. 2 illustrates a schematic of a PCR detection system,
according to various embodiments of the present teachings.
[0007] FIG. 3 illustrates a normalized or adjusted PCR
amplification profile or curve, according to various embodiments of
the present teachings.
[0008] FIG. 4 illustrates a flowchart of baseline processing,
according to various embodiments of the present teachings.
DESCRIPTION
[0009] Various embodiments of the present teachings relate to
systems and methods for baseline correction or adjustment of RT-PCR
or other amplification curves, signatures, graphs, profiles, or
data, using a non-linear or non-subtractive normalization process.
According to various embodiments, an amplification curve,
signature, graph, profile, or data can be received from detection
of fluorescent emissions in a RT-PCR or other instrument. According
to various embodiments, the calibration systems and methods can be
implemented in or applied to RT-PCR scanning systems or RT-PCR
imaging systems, or other systems or platforms. In some
embodiments, systems and methods according to the present teachings
can be applied to non-real-time PCR instruments.
[0010] According to various embodiments, RT-PCR or other processing
can take place using a standard sample plate, such as a 96-well or
other capacity microtitre well or plate. In some embodiments, each
well or other container or location in a plate or other platform
can contain samples, for example, samples of DNA fragments or other
material, to which one or more spectrally distinct dye is attached
for detection and analysis. According to various embodiments, a
calibration, normalization, or other adjustment can be performed to
normalize, adjust, or otherwise increase the consistency and/or
accuracy of the readings taken from the sample wells. According to
various embodiments, the normalization or calibration can correct
or compensate for variations due to or affected by factors which
include, for example, differences in signal strength, dye or sample
concentrations, contaminations, spectral or amplitude distortions,
deviations in optical path, plate geometry, fluorescent noise
floor, sample population or size, or other variations or anomalies
that can arise from dye-to-dye, well-to-well, plate-to-plate, or
instrument-to-instrument variations.
[0011] According to various embodiments, the normalization or
calibration can comprise adjusting detected emission signals to
compensate for identified background or baseline signal or signals
in a RT-PCR amplification, or other reaction. According to various
embodiments, this can permit correction or adjustment for
background optical uniformity, utilizing a normalized amplification
profile, signature, graph, curve, or data, based upon the baseline
of the detected PCR or other readings. According to various
embodiments, the normalization can be carried out using an endpoint
of the PCR emission data, in addition to, or instead of, the
initial baseline. According to various embodiments, calibration or
normalization can be conducted in real-time, as the emission data
from the PCR or other amplification or other process is detected.
Herein, the term "emission" is used to exemplify a signal detected
and/or calibrated according to various embodiments of the present
teachings. It is to be understood that by "emission" the present
teachings are referring to not only electromagnetic radiation but
rather are also referring to any physical or chemical signal or
other data that can be read, detected, imaged, or surmised from one
or more area of interest, for example, a support region such as a
well of a multi-well plate. "Emission" herein is intended to
encompass electromagnetic radiation, optical signals,
chemiluminescent signals, fluorescent signals, radiation
transmission values, and radiation absorption values.
[0012] According to various embodiments, a background reading can
be taken with no dyes, samples, background samples, or other
material present in the sample plate or other support. In some
embodiments, a background sample is used that comprises the same
PCR mixture as is used on actual runs, but without the dyes. The
background sample can mimic the actual run time background. For
example, the background emission of a plate having dry or empty
wells can be detected to determine baseline signal or signals
caused by residual fluorescent contributions from the material of
the plate itself, for example, from plastic or other material.
Knowledge of the dry-plate contribution can also be used to
determine if any other factors are contributing to the noise floor
or detectable background which can be present in the system, or to
quantify that remaining contribution.
[0013] According to various embodiments, background normalization
and correction can be performed in connection with a RT-PCR system,
such as, for instance, an overall system schematically illustrated
in FIG. 2. According to embodiments as shown, a RT-PCR system can
comprises a detector system 184, such as a scanning or whole-plate
imaging optical detection element which can comprise, for example,
a photomultiplier tube, CCD device, or other optical or other
detection element. According to various embodiments, the detector
system 184 can communicate with a processor 186 which can
communicate with an input module 188, an output module 190, and/or
storage 192, such as local or networked disk storage. According to
various embodiments, the detector system 184 can scan or image a
sample plate 180, to detect the optical emission from a set of
sample wells 194, such as wells arranged in a standard 96, 384, or
other capacity array. According to various embodiments, sample
wells 194 can contain samples in mixture with reagents to conduct a
RT-PCR run. In some embodiments, the RT-PCR processing can comprise
operating the system at a series of RT-PCR temperatures regulated
by thermal cycler block 182 and other electronic and thermal
components, to subject the reactants in sample wells 194 to a
desired sequence of denaturing, annealing, extension, and other
steps.
[0014] According to various embodiments, and as illustrated, for
instance, in FIG. 3, the output of a RT-PCR run can comprise a set
of detected emission data 210, generally representing detecting
intensities of fluorescent or other markers identifying PCR
amplification products. According to various embodiments, emission
data 210 can comprise discrete values. In some embodiments,
emission data 210 can comprise discrete values that are
interpolated, re-sampled or oversampled, to produce a more dense,
or differently-spaced, collection of data points. In some
embodiments, emission data 210 can comprise a continuous curve or
trace. According to various embodiments, emission data can extend
over a total number of cycles from 1 to N, where N can be the
endpoint of a RT-PCR run, such as 30, 35, 40, or another number of
cycles. According to various embodiments, the horizontal axis of
the illustrative emission signature or profile shown in FIG. 3 can
comprise cycle numbers, or it can comprise time units. According to
various embodiments, the vertical axis can comprise absolute or
relative amplitude or intensity units, or other measures. In some
embodiments, the vertical axis can, for example, reflect detected
emission or intensity values a on a logarithmic scale.
[0015] According to various embodiments, the baseline correction
can comprise the amplitude readings detected and received in the
first few cycles of a RT-PCR or other reaction, to isolate the
initial cycles in which amplification product is not yet
detectable. According to various embodiments, in the context of
RT-PCR processes, the beginning and end cycles, which can form a
candidate interval for defining the baseline region, can be on the
order of cycles 1 through 8, respectively, or lower or higher
cycles. According to various embodiments, mathematical tests can be
applied to the detected signal in the first several cycles of
RT-PCR operation to determine the baseline region 212, such as
determining a set of cycles over which the first derivative of the
detected signal remains below a predetermined threshold, or some
other threshold. According to various embodiments, techniques such
as those described in U.S. Pat. No. 7,228,237 to Woo et al., which
is incorporated herein in its entirety by reference, or others, can
be used to isolate and identify the baseline region 212 and
baseline signal 202 located in the baseline region 212 of emission
data 210.
[0016] According to various embodiments of the present teachings in
one regard, and as, for example, also illustrated in FIG. 3, once
the interval of baseline region 212 is identified and baseline
signal 202 isolated, further normalization or adjustment of
emission data 210 located in the remaining regions of emission data
210 can be performed. According to various embodiments in one
regard, the normalization or other adjustment can comprise a
division of the detected RT-PCR or other emission data 210 in
exponential region 214 (and/or plateau region 216) by the detected
baseline signal 202. According to various embodiments, this can
generate a normalized amplification profile 204 in which the
detected emission signals in exponential region 214 and/or plateau
region 216 are scaled, normalized, or otherwise adjusted to
represent the ratio of the detected signal in the respective region
to the baseline signal 202. According to various embodiments,
baseline signal 202 can comprise a constant, non-varying, or scalar
value. According to various embodiments, normalized amplification
profile 204 can be generated by dividing emission data 210 with
constant 206, where baseline signal 202 is determined to be a
scalar or constant value.
[0017] According to various embodiments, baseline signal 202 can be
represented, encoded, or characterized by a time-varying function
208. According to various embodiments, function 208 can be or
include a linear function, for instance, a linear function
generated by performing a least-squares or other fitting operation
on the data points in the first several cycles of the emission
data. According to various embodiments, function 208 can be or
include a non-linear function, such as a polynomial or other
function. According to various embodiments, the division of the
detected emission signals in exponential region 214 (and/or plateau
region 216) by baseline signal 202, which is characterized by a
function 208, can produce normalized amplification profile 204
reflecting that ratio of functions. According to various
embodiments, the raw emission data 210, the baseline signal 202,
the normalized amplification profile 204, and other signals can
each be a continuous graph, function, or data set, or can be a
discrete graph, function, or data set. According to various
embodiments, normalization generated by computing a ratio of
emission data 210 over function 208 can produce a normalized
amplification profile 204, whose degree of scaling varies along the
cycle number (or time) axis, depending upon the varying values of
baseline signal 202 along that axis.
[0018] According to various embodiments, the normalized
amplification profile 204 can provide a compactly-scaled
representation of the underlying emission data when compared to the
subtraction of a baseline value, since division of the emission
data 210 by function 208 can reduce the overall normalized range.
According to various embodiments, normalized amplification profile
204 can in one regard represent a more consistent basis upon which
to compare or calibrate different RT-PCR or other runs, because the
dynamic range of each is expressed in terms of a ratio over
baseline.
[0019] According to various embodiments, the division of the
detected emission data 210 from RT-PCR or other sources by baseline
signal 202, in either the form of constant 206 or function 208, can
be performed in real-time, while emission data 210 are being
detected, collected, and stored. According to various embodiments,
the division or other normalization operation giving rise to
normalized amplification profile 204 can be performed after
emission data 210 has been collected. According to various
embodiments, the correction for baseline signal noise can also
include other mathematical functions, treatments, computations or
operations, in addition to generating a ratio of emission data 210
over baseline signal 202.
[0020] According to various embodiments, for example, after
normalization by division of emission data 210 by baseline signal
202 as described herein, normalized amplification profile 204 can
be further normalized or adjusted by, for example, subtracting a
constant value, such as 1 or some other value, from normalized
amplification profile 204. According to various embodiments, at the
point that the detected emission data 210 first rises above
baseline signal 202, the ratio of those two quantities can be 1 or
substantially close to 1. Subtracting 1 or some other offset, from
the ratio initially generated by normalized amplification profile
204, can result in an overall amplification profile with detected
values increasing from a level of zero. According to various
embodiments, other further or alternative adjustments to normalized
amplification profile 204 can be made. According to various
embodiments in one regard, because the normalized amplification
profile 204 can be consistently scaled to starting points of 0, 1,
or other desired levels, comparison, averaging, and other aggregate
manipulation of the profiles generated by different wells, filters,
dyes, samples, machines, or other entities, can be uniformly
performed. Therefore, a set of multiple normalized amplification
profiles generated according to the present teachings can be
employed to generate more useful and accurate comparisons, make
uniformity corrections, and other calibration or operational
measurements, between diverse machines, chemistries, or
processes.
[0021] FIG. 4 illustrates a flowchart of overall baseline and
emission normalization processing, according to various embodiments
of the present teachings. In step 402, processing can begin. In
step 404, emission data 210 from a RT-PCR or other amplification,
or other machine, instrument, or system can be detected or
received. In step 406, a baseline region 212 in the emission data
210 can be identified, for instance, based, for example, upon the
greatest first derivative point or other technique. In step 408, a
constant 206 and/or function 208 characterizing baseline signal 202
can be generated. In step 410, a normalized amplification profile
204 can be generated for the exponential region 214 and/or plateau
region 216 of emission data 210. According to various embodiments,
the normalized amplification profile 204 can be generated by
dividing emission data 210 by constant 206, function 208, a
combination of the two, or some other quantity or parameter. In
step 412, additional sets of emission data 210, for example,
emission intensities detected in additional RT-PCR or other runs,
can be normalized using the same techniques.
[0022] In step 414, the set of one or more normalized amplification
profile 204 can be compared, calibrated, or otherwise processed,
for example, to perform uniformity calibration or analysis across
different sample plates, wells, dyes, samples, filters, machines,
or other entities. In step 416, any one or more normalized
amplification profile 204, emission data 210, constant 206,
function 208, or other data or information can be stored, for
example, to a local hard disk, network storage site, or other
location or data store. In step 418, processing can repeat, return
to a prior processing point, proceed to a further processing point,
or end.
[0023] Various embodiments of the present teachings can be
implemented, in whole or part, in digital electronic circuitry, or
in computer hardware, firmware, software, or in combinations
thereof. Apparatus of the invention can be implemented in a
computer program, software, code, or algorithm embodied in
machine-readable media, such as electronic memory, CD-ROM or DVD
discs, hard drives, or other storage device or media, for execution
by a programmable processor. Various method steps according to the
present teachings can be performed by a programmable processor
executing a program of instructions to perform functions and
processes according to the present teachings, by operating on input
data and generating output. The present teachings can, for example,
be implemented in one or more computer programs that are executable
on a programmable system including at least one programmable
processor coupled to receive data and instructions from, and to
transmit data and instructions to, a data storage system or memory,
at least one input device such as a keyboard and mouse, and at
least one output device, such as, for example, a display or
printer. Each computer program, algorithm, software, or code can be
implemented in a high-level procedural or object-oriented
programming language, or in assembly, machine, or other low-level
language if desired. According to various embodiments, the code or
language can be a compiled, interpreted, or otherwise processed for
execution.
[0024] Various processes, methods, techniques, and algorithms can
be executed on processors that can include, by way of example, both
general and special purpose microprocessors, such as, for example,
general-purpose microprocessors such as those manufactured by Intel
Corp. or AMD Inc., digital signal processors, programmable
controllers, or other processors or devices. According to various
embodiments, generally a processor will receive instructions and
data from a read-only memory and/or a random access memory.
According to various embodiments, a computer implementing one or
more aspects of the present teachings can generally include one or
more mass storage devices for storing data files, such as magnetic
disks, such as internal hard disks and removable disks,
magneto-optical disks, and CD-ROM DVD, Blu-Ray, or other optical
disks or media.
[0025] According to various embodiments, memory or storage devices
suitable for storing, encoding, or embodying computer program
instructions or software and data can include, for instance, all
forms of volatile and non-volatile memory, including for example
semiconductor memory devices, such as random access memory,
electronically programmable memory (EPROM), electronically erasable
programmable memory, EEPROM, and flash memory devices, as well as
magnetic disks such as internal hard disks and removable disks,
magneto-optical disks, and optical disks. Any of the foregoing can
be supplemented by, or incorporated in, ASICs. According to various
embodiments, processors, workstations, personal computers, storage
arrays, servers, and other computer, information, or communication
resources used to implement features of the present teachings can
be networked or network-accessible.
[0026] It will be appreciated that while various embodiments
described above involve the calibration of one or more aspects of
instrument reading, dye selection or preparation, or other factors,
according to various embodiments, more than one type of
normalization or calibration can be performed, together or in
sequence. While the foregoing description has generally described
the normalization of the emission data as involving generating a
ratio of data to a baseline signal according to various
embodiments, the normalization can comprise, for example, dividing
the emission data in the exponential region 214 and/or plateau
region 216 by the endpoint value of the RT-PCR run, after the
amplification reaction is complete.
[0027] Other embodiments will be apparent to those skilled in the
art from consideration of the present specification and practice of
the present teachings disclosed herein. It is intended that the
present specification and examples be considered as exemplary
only.
* * * * *