U.S. patent application number 10/758761 was filed with the patent office on 2004-07-29 for trace level detection of analytes using artificial.
Invention is credited to Kelso, David M., Lewis, Nathan S., Munoz, Beth C., Severin, Erik J., Wong, Bernard.
Application Number | 20040147038 10/758761 |
Document ID | / |
Family ID | 26781295 |
Filed Date | 2004-07-29 |
United States Patent
Application |
20040147038 |
Kind Code |
A1 |
Lewis, Nathan S. ; et
al. |
July 29, 2004 |
Trace level detection of analytes using artificial
Abstract
The present invention provides methods for detecting the
presence of an analyte indicative of various medical conditions,
including halitosis, periodontal disease and other diseases are
also disclosed.
Inventors: |
Lewis, Nathan S.; (La
Canada, CA) ; Severin, Erik J.; (San Marino, CA)
; Wong, Bernard; (Los Angeles, CA) ; Kelso, David
M.; (Wilmette, IL) ; Munoz, Beth C.;
(Pasadena, CA) |
Correspondence
Address: |
TOWNSEND AND TOWNSEND AND CREW, LLP
TWO EMBARCADERO CENTER
EIGHTH FLOOR
SAN FRANCISCO
CA
94111-3834
US
|
Family ID: |
26781295 |
Appl. No.: |
10/758761 |
Filed: |
January 15, 2004 |
Related U.S. Patent Documents
|
|
|
|
|
|
Application
Number |
Filing Date |
Patent Number |
|
|
10758761 |
Jan 15, 2004 |
|
|
|
09855277 |
May 14, 2001 |
|
|
|
09855277 |
May 14, 2001 |
|
|
|
09336428 |
Jun 17, 1999 |
|
|
|
6319724 |
|
|
|
|
60091179 |
Jun 30, 1998 |
|
|
|
60090012 |
Jun 19, 1998 |
|
|
|
Current U.S.
Class: |
436/149 |
Current CPC
Class: |
Y10T 436/214 20150115;
A61B 5/00 20130101; G01N 33/497 20130101; G01N 33/0044 20130101;
G01N 33/0034 20130101; Y10T 436/143333 20150115; Y10T 436/200833
20150115; Y10S 436/90 20130101; Y10S 977/879 20130101; A61B 5/4547
20130101; Y10T 436/17 20150115; G01N 33/0031 20130101; A61B 5/082
20130101; Y10T 436/212 20150115; G01N 1/405 20130101; G01N 1/22
20130101; Y10T 436/216 20150115 |
Class at
Publication: |
436/149 |
International
Class: |
G01N 027/00 |
Goverment Interests
[0002] The research carried out in the subject application was
sponsored, in part, by grants from: ARO (DAAG-55-97-1-0187); DARPA
(DAAK60-97-K-9503); and NASA (49-244-30002-O-8280), and is subject
to the provisions of Public Law 96-517 (35 U.S.C. .sctn. 202). The
government may have certain rights in any patents issuing on this
application.
Claims
What is claimed is:
1. A method for detecting halitosis, said method comprising:
contacting an array of sensors with mammalian breath suspected of
containing a marker gas indicative of halitosis; and detecting said
marker gas to determine the presence of halitosis.
2. A method in accordance with claim 1, wherein said array of
sensors comprises a member selected from the group consisting of a
surface acoustic wave sensor, a quartz microbalance sensor; a
conductive composite; a chemiresistor; a metal oxide gas sensor and
a conducting polymer sensor, a dye-impregnated polymer film on
fiber optic detector, a polymer-coated micromirror, an
electrochemical gas detector, a chemically sensitive field-effect
transistor, a carbon black-polymer composite, a
micro-electro-mechanical system device and a
micro-opto-electro-mechanica- l system device.
3. A method in accordance with claim 1, wherein said marker gas is
a member selected from the group consisting of alkanes, alkenes,
alkynes, dienes, alicyclic hydrocarbons, arenes, alcohols, ethers,
ketones, aldehydes, carbonyls, carbanions, polynuclear aromatics,
biomolecules, sugars, isoprenes isoprenoids, VOC, VOA, indoles,
skatoles, diamines, pyridines, picolines, an off-gas of a
microorganism and fatty acids.
4. A method in accordance with claim 1, further comprising
generating a response from said sensors and inputting said response
to a neural net trained against known marker gases.
5. A method in accordance with claim 1, wherein said marker gas is
an off gas of a member selected from the group consisting of
Prevotella intermedia, Fusobacterium nucleatum, Porphyromonas
gingivalis, Porphyromonas endodontalis, Prevotella loescheii,
Hemophilus parainfluenzae, Stomatococcus muci, Treponema denticola,
Veillonella species, Peptostreptococcus anaerobius, Micros
prevotii, Eubacterium limosum, Centipeda periodontii, Selemonad
aremidis, Eubacterium species, Bacteriodes species, Fusobacterium
periodonticum, Prevotella melaninogenica, Klebsiella pneumoniae,
Enterobacter cloacae, Citrobacter species and Stomatococcus
mucilaginus.
6. A method for detecting periodontal disease, said method
comprising: contacting an array of sensors with mammalian breath
suspected of containing a marker gas indicative of periodontal
disease; and detecting said marker gas to determine the presence of
periodontal disease.
7. A method in accordance with claim 6, wherein said array of
sensors comprises a member selected form the group consisting of a
surface acoustic wave sensor, a quartz microbalance sensor; a
conductive composite; a chemiresistor; a metal oxide gas sensor and
a conducting polymer sensor, a dye-impregnated polymer film on
fiber optic detector, a polymer-coated micromirror, an
electrochemical gas detector, a chemically sensitive field-effect
transistor, a carbon black-polymer composite, a
micro-electro-mechanical system device and a
micro-opto-electro-mechanica- l system device.
8. A method in accordance with claim 6, wherein said marker gas is
a member selected from the group consisting of alkanes, alkenes,
alkynes, dienes, alicyclic hydrocarbons, arenes, alcohols, ethers,
ketones, aldehydes, carbonyls, carbanions, polynuclear aromatics,
biomolecules, sugars, isoprenes isoprenoids, VOC, VOA, indoles,
skatoles, diamines, pyridines, picolines, an off-gas of a
microorganism and fatty acids.
9. A method in accordance with claim 6, further comprising
generating a response from said sensors and inputting said response
to a neural net trained against known marker gases.
10. A method for detecting pneumonia, said method comprising:
contacting an array of sensors with mammalian breath suspected of
containing a marker gas indicative of pneumonia; and detecting said
marker gases to determine the presence of pneumonia.
11. A method in accordance with claim 10, wherein said array of
sensors comprises a member selected from the group consisting of a
surface acoustic wave sensor, a quartz microbalance sensor; a
conductive composite; a chemiresistor; a metal oxide gas sensor and
a conducting polymer sensor, a dye-impregnated polymer film on
fiber optic detector, a polymer-coated micromirror, an
electrochemical gas detector, a chemically sensitive field-effect
transistor, a carbon black-polymer composite, a
micro-electro-mechanical system device and a
micro-opto-electro-mechanica- l system device.
12. A method in accordance with claim 10, wherein said marker gas
is a member selected from the group consisting of alkanes, alkenes,
alkynes, dienes, alicyclic hydrocarbons, arenes, alcohols, ethers,
ketones, aldehydes, carbonyls, carbanions, polynuclear aromatics,
biomolecules, sugars, isoprenes isoprenoids, VOC, VOA, indoles,
skatoles, diamines, pyridines, picolines, an off-gas of a
microorganism and fatty acids.
13. A method in accordance with claim 10, further comprising
generating a response from said sensors and inputting said response
to a neural net trained against known marker gases.
14. A method for detecting vaginitis, said method comprising:
contacting an array of sensors with vaginal vapor suspected of
containing a marker gas indicative of vaginitis; and detecting said
marker gas to determine the presence of vaginitis.
15. A method in accordance with claim 14, wherein said array of
sensors comprises a member selected form the group consisting of a
surface acoustic wave sensor, a quartz microbalance sensor; a
conductive composite; a chemiresistor; a metal oxide gas sensor and
a conducting polymer sensor, a dye-impregnated polymer film on
fiber optic detector, a polymer-coated micromirror, an
electrochemical gas detector, a chemically sensitive field-effect
transistor, a carbon black-polymer composite, a
micro-electro-mechanical system device and a
micro-opto-electro-mechanica- l system device.
16. A method in accordance with claim 14, wherein said marker gas
is a member selected from the group consisting of alkanes, alkenes,
alkynes, dienes, alicyclic hydrocarbons, arenes, alcohols, ethers,
ketones, aldehydes, carbonyls, carbanions, polynuclear aromatics,
biomolecules, sugars, isoprenes isoprenoids, VOC, VOA, indoles,
skatoles, diamines, pyridines, picolines, an off-gas of a
microorganism, methylamine, isobutylamine, putrescine, cadaverine,
histamine, tyramine, phenethylamine and fatty acids.
17. A method in accordance with claim 14, further comprising
generating a response from said sensors and inputting said response
to a neural net trained against known marker gases.
18. A method for detecting ovulation, said method comprising:
contacting an array of sensors with vaginal vapor suspected of
containing a marker gas indicative of ovulation; and detecting said
marker gas to determine ovulation.
19. A method in accordance with claim 18, wherein said array of
sensors comprises a member selected from the group consisting of a
surface acoustic wave sensor, a quartz microbalance sensor; a
conductive composite; a chemiresistor; a metal oxide gas sensor and
a conducting polymer sensor, a dye-impregnated polymer film on
fiber optic detector, a polymer-coated micromirror, an
electrochemical gas detector, a chemically sensitive field-effect
transistor, a carbon black-polymer composite, a
micro-electro-mechanical system device and a
micro-opto-electro-mechanica- l system device.
20. A method in accordance with claim 18, wherein said marker gas
is a member selected from the group consisting of alkanes, alkenes,
alkynes, dienes, alicyclic hydrocarbons, arenes, alcohols, ethers,
ketones, aldehydes, carbonyls, carbanions, polynuclear aromatics,
biomolecules, sugars, isoprenes isoprenoids, VOC, VOA, indoles,
skatoles, diamines, pyridines, picolines, an off-gas of a
microorganism, androstenol, dehydroepiandrosterone sulfate and
fatty acids.
21. A method in accordance with claim 18, further comprising
generating a response from said sensors and inputting said response
to a neural net trained against known marker gases.
22. A method for detecting a medical condition, said method
comprising: contacting an array of sensors with mammalian body
fluid suspected of containing a marker gas indicative of said
medical condition; and detecting said marker gas to determine the
presence of the medical condition.
23. A method in accordance with claim 22, wherein said array of
sensors comprises a member selected from the group consisting of a
surface acoustic wave sensor, a quartz microbalance sensor; a
conductive composite; a chemiresistor; a metal oxide gas sensor and
a conducting polymer sensor, a dye-impregnated polymer film on
fiber optic detector, a polymer-coated micromirror, an
electrochemical gas detector, a chemically sensitive field-effect
transistor, a carbon black-polymer composite, a
micro-electro-mechanical system device and a
micro-opto-electro-mechanica- l system device.
Description
CROSS-REFERENCES TO RELATED APPLICATIONS
[0001] This application claims priority to U.S. Provisional
Applications Serial No. 60/090,012, filed Jun. 19, 1998, and
60/091,179, filed Jun. 30, 1998, the disclosures of which are
incorporated herein by reference in their entirety.
BACKGROUND OF THE INVENTION
[0003] An artificial olfactory system is a device that is capable
of detecting a wide variety of analytes in fluids such as vapors,
gases and liquids. The device comprises an array of sensors that in
the presence of an analyte produces a response. The device produces
a unique signature output for a particular analyte. Using pattern
recognition algorithms, the output signature, such as an electrical
response, can be correlated and compared to a particular analyte or
mixture of substances that are known. By comparing the unknown
signature with the stored or known signatures, the analyte can be
detected, identified and quantified.
[0004] There are many instances where it is desirable to measure
trace amounts of analytes. However, in certain instances, the
analytes are found at levels that are too low to register a robust
signal by direct exposure to currently available sensors. In
headspace analysis of applications in agricultural, wine, tobacco,
perfume, plastics, and the food industries, the detection and
classification of trace levels of gases are present in the sub part
per million (ppm) range, making detection difficult. Moreover, in
residue analysis of pesticides on crops, the trace levels of
certain herbicides must meet federal guidelines. For certain crops,
these residues are present on the crops in the part per billion
levels (ppb).
[0005] Another potential application wherein the detection of trace
levels of analytes is important is the diagnosis of patients'
conditions from an analysis of their breath. Marker gases such as
hydrogen sulfide and methyl mercaptan, which are important in
diagnosing the presence of oral or lung conditions from the breath
of human patients, often exist in concentrations of 0.01-1 parts
per million (or lower). However, the threshold detection levels of
currently known sensors are in the range of 1-100 parts per
million.
[0006] Currently, the most widely used device for detecting oral
malodors is the Halimeter, which is commercially available from
Interscan Corp. (Chatsworth, Calif.). Using an electrochemical cell
that is sensitive to volatile sulfur compounds (VSC), the device
can oxidize the VSC at the anode according to the following
reactions:
H.sub.2S.fwdarw.S+2H.sup.++2e.sup.-
2CH.sub.3--SH.fwdarw.CH.sub.3--S--S--CH.sub.3+S+2H.sup.++2e.sup.-
CH.sub.3--S--CH.sub.3+2H.sub.2O.fwdarw.2CH.sub.3OH+S+2H.sup.++2e.sup.-
[0007] However, one obvious drawback is that the Halimeter cannot
distinguish between volatile sulfur compounds. Similarly, other
volatile substances can interfere with the readings of the VSC.
[0008] A second device for the detection of breath and odors
associated therewith is based on zinc-oxide thin film semiconductor
technology and has recently been developed for measuring VSC (see,
Shimura M et al., J. Periodontol. 67:396-402 (1994)). New Cosmos
Electric Co. (Osaka, Japan) manufactures this device. This device,
however, is limited because it is susceptible to interference from
organic vapors unrelated to oral malodor (see, Yaegaki K, In
Rosenberg, "Bad Breath: Research Perspectives," Proceedings of the
First International Workshop on Oral Malodor, Ramot Publishing, Tel
Aviv University pp. 41-54 (1993)) 87-108 (1995)).
[0009] Another analysis for breath detection is a test based on the
enzyme substrate benzoyl-DL-arginine-naphthylamine (BANA) (see,
Loesche et al., J. Clin. Microbiol. 28:1551-1559 (1991); and
Loesche et al. J. Periodontol., 61:189-196 (1991)). This test is
marketed under the brand name Peroscan and is available from Oral-B
Laboratories (Redwood City, Calif.). Scrapings from the tongue,
saliva, or plaque samples are deposited directly on a reagent card.
Following substrate addition, a blue spot develops if anaerobes are
present. Studies have shown that BANA results are not highly
correlated with VSC measurements and that the test is often
detecting other analytes (see, Kozlovsky et al., J. Dent. Res., 73:
1036-1042 (1994)).
[0010] It has been estimated that at least 50% of the population
suffers from chronic oral malodor (see, Bosy, J. Can. Dent. Assoc.
63:196-201 (1997)). A significant fraction of the population is
worried about bad breath, even though there is usually no
underlying disease (see, Iwakura et al., J. Dent. Res. 7:1568-15741
(1994)). Food, of course, is another cause of oral malodors.
However, there are many people who have an unwarranted phobia of
bad breath. The size of the market for breath fresheners, chewing
gums, and mouth rinses is an indicator of this propensity.
[0011] In addition to mammalian breath measurements, respiratory
devices for anesthetic and respiratory gas mixtures must be
monitored at very low concentrations of analytes. Medical devices
mix the anesthetic with breathing gas prior to delivery to the
patient. In an anesthetic device, it is imperative that the
concentration of the anesthetic, gas flow and amounts of the
mixture and starting gases be known with certainty. In most
instances, the anesthetic amounts are at very low concentration
levels.
[0012] One approach to increase sensitivity to certain analytes is
to use selective filters or membranes. For instance, U.S. Pat. No.
5,841,021, which issued to De Castro et al., discloses an
electrochemical gas sensor that has a catalytically active sensor
electrode, a reference electrode and a permselective filter or
membrane layer. The filter is made of a material that provides for
molecular specificity of certain gases, such as carbon monoxide.
The membrane allows the sensors to be selective to the chemical
analyte of interest. The filter only allows the analytes of
interest to contact the sensor. By removing interfering substances
through filtration, the sensor becomes more selective and thus
sensitive to the analyte of interest.
[0013] In addition, U.S. Pat. No. 5,057,436, which issued to Ball,
discloses a method and apparatus for detection of toxic gases, such
as ammonia, using a metal oxide semiconductor and an
electrochemical sensor. Disposed between the two sensors is an
absorber having an absorbent that reacts with ammonia.
[0014] In view of the foregoing, what is needed in the art is a
vapor concentrator for an array of sensors, especially for an
electronic nose sensor array. In addition, methods are needed to
detect odors and diagnose medical conditions. The present invention
fulfills these and other needs.
SUMMARY OF THE INVENTION
[0015] In certain instances, it is desirable to measure trace
amounts of analytes using sensor array technology. The present
invention increases the sensitivity to such analytes by a large
factor, and thus allows for the use of existing sensor systems for
applications where an increase in sensitivity renders them more
effective. As such, in certain aspects, the present invention
provides a device for detecting the presence of an analyte, the
device comprising: a sample chamber having a fluid inlet port for
the influx of the analyte; a fluid concentrator in flow
communication with the sample chamber, wherein the fluid
concentrator has an absorbent material capable of absorbing the
analyte and capable of desorbing a concentrated analyte; and an
array of sensors in fluid communication with the concentrated
analyte. In certain preferred embodiments, the device further
includes a detector operatively associated with each sensor that
provides a response in the presence of the analyte.
[0016] The absorbent material of the fluid concentrator can be, but
is not limited to, a nanoporous material, a microporous material, a
chemically reactive material, a nonporous material and combinations
thereof. In certain instances, the absorbent material can
concentrate the analyte by a factor that exceeds a factor of about
10.sup.5, and more preferably by a factor of about 10.sup.2 to
about 10.sup.4. Using the device of the present invention, the
analyte can be concentrated from an initial sample volume of about
10 liters and then desorbed into a concentrated volume of about 10
milliliters or less, before being presented to the sensor
array.
[0017] In another embodiment, removal of background water vapor is
conducted in conjunction, such as concomitantly, with the
concentration of the analyte. Once the analyte is concentrated, it
can be desorbed using a variety of techniques, such as heating,
purging, stripping, pressuring or a combination thereof.
[0018] In yet another aspect, the present invention provides
methods for detecting or diagnosing, for example, infections, lung
cancer, oral infections and halitosis using a breath sample of a
mammal. Preferably, the mammal is a human being. In other
embodiments, the present invention provides methods for other
medical applications, such as those involving the detection of
marker gas(es) in mammalian breath as well as odors from
potentially infected areas of the skin.
[0019] In still yet another aspect, the present invention provides
methods and devices for the process control of anesthetic gases of
clinical interest. Using the apparatus of the present invention,
monitoring and quantitating anesthetics is readily
accomplished.
[0020] These and other embodiments and advantages will be readily
apparent when read with the accompany drawings and the detailed
description of the invention which follows.
BRIEF DESCRIPTION OF THE DRAWINGS
[0021] FIG. 1 is a cross-sectional view of a breath collector and
concentrator of the present invention.
[0022] FIG. 2 is a cross-sectional view of a breath collector and
concentrator of the present invention.
[0023] FIG. 3 is a head space analyzer of the present
invention.
[0024] FIG. 4 is a block diagram of a vaporizing system of the
present invention.
[0025] FIG. 5 illustrates various response patterns obtained using
the devices of the present invention. Panel A illustrates the
responses of 32 sensors to anerobius (Bac1), gingivalis (Bac2) and
a control; Panel B illustrates responses of 32 sensors to anerobius
(Bac1), gingivalis (Bac2) and a control (Expanded y-axis).
[0026] FIG. 6 illustrates the results of principle component
analysis on a data set of Ps anerobius (Bac1) and P gingivalis
bacteria (Bac2) plus the control (the medium in which the bacteria
were grown).
[0027] FIG. 7 illustrates the response of sensors in the presence
of 3 percent halothane.
[0028] FIG. 8 illustrates the results of the response of sensor
array in the presence of halothane.
DETAILED DESCRIPTION OF THE INVENTION AND PREFERRED EMBODIMENTS
[0029] I. The Device
[0030] In one aspect, the present invention allows existing sensor
systems to be more effective and efficient by providing
enhancements in the detection sensitivity to trace analytes. As
such, in one embodiment, the present invention provides a device
for detecting the presence of an analyte in a fluid, comprising
[0031] a) a sample chamber having a fluid inlet port for the influx
of the analyte;
[0032] b) a fluid concentrator in flow communication with the
sample chamber, the fluid concentrator having an absorbent material
capable of absorbing the analyte and capable of desorbing a
concentrated analyte; and
[0033] c) an array of sensors in fluid communication with the
concentrated analyte.
[0034] In preferred embodiments, the device further comprising a
detector operatively associated with each sensor that provides a
response in the presence of an analyte. In certain embodiments, the
sample chamber is designed for the collection of mammalian breath.
Under certain conditions, mammalian breath contains marker gases
indicative of certain infections, disorders and medical conditions
and the devices of the present invention can be used to detect such
marker gases. In certain aspects, the sample chamber is a breath
collector and concentrator (BCC) and is fabricated to collect the
breath of a mammal. Preferably, the mammal is a human being,
although the BCC can be fabricated to collect the breath of other
mammals such as cows, sheep, horses, dogs, cats, hogs, etc. The BCC
is convenient to use and in certain instances is a portable
handheld device with a suitable handle portion for convenient
use.
[0035] With reference to FIG. 1, in certain embodiments, the sample
chamber is a cylindrical reservoir having an inlet port (10) for
the influx of gas, such as breath, and an outlet port (19) for the
exhaust of breath. The BCC has a first end and a second end. The
cylindrical container (12) extends between the first end and the
second end, and the cylindrical container has an open interior
chamber (13).
[0036] The first end of the body is open for access to the interior
chamber and functions as a breath inlet port and is vented by a
breath exhaust. The breath inlet port optionally contains a
disposable adapter for multiple use. A concentrator portal (14)
opens into the interior chamber and is in flow communication with
the fluid concentrator. The fluid concentrator (15) comprises an
absorbent material capable of absorbing the analyte and capable of
desorbing a concentrated analyte. In certain embodiments, valves
control the breath flow so the sample of breath within the chamber
can be directed to the fluid concentrator. The fluid concentrator
optionally contains a second exhaust or exit port.
[0037] A valve (16) is mounted anterior to the outlet port with
sufficient force to maintain the vent closed except when the mammal
is exhaling into the chamber. Optionally, the fluid concentrator is
jacketed (17) with a heater for the purpose of desorbing a
concentrated analyte. As illustrated in FIG. 1, the BCC has a
sensor array portal (18) that opens into the interior chamber and
is in fluid communication with the desorbed concentrated analyte
and the sensor array (11). In certain embodiments, the sensor array
is disposed downstream of the inlet port and the concentrator
portal. In other embodiments, the sensor array is disposed between
the inlet port and the concentrator portal (not shown). In certain
embodiments, the BCC has an adapter to provide breath from the
nostril(s) to avoid cross-contamination from the mouth.
[0038] In certain aspects, the BCC can be a desktop model. As
illustrated in FIG. 2, the first end (24) of the BCC (20) is open
for access to the interior chamber (22) and functions as a breath
inlet port and is vented by a breath exhaust (25). A fluid
concentrator (23) opens into the interior chamber (27) and is in
flow communication (28) with the breath exhaust (25). In this
embodiment, the breath is circulated through the chamber using a
fan (21). The sensor array (26) is in flow communication with the
desorbed analyte.
[0039] In various embodiments, the fluid concentrator can be
disposed within the sample chamber or outside the sample chamber.
In addition, the sensor array can be disposed within the sample
chamber or outside the sample chamber. Moreover, the sensor array
can be configured to be external from the BCC and to extend into
the mouth or nasal cavity. The present invention embodies all such
variations.
[0040] Although the device of FIG. 1 is shown as a handheld breath
collector and concentrator, those of skill in the art will
appreciate that in certain other embodiments, the device and
methods of the present invention can be adapted and configured to
detect within or around various other areas of interest including,
but not limited to, mucous membranes, nose, nasal passages, eye,
skin, ear, inner ear, mouth, tongue, throat, colon, duodenum, body
cavities, stomach, vagina and penis. Moreover, the device and
methods of the present invention can be configured to detect all
body fluids including, but not limited to, urine, perspiration,
tears, blood, mucus, pus, salvia, feces, menstruation fluid, sperm,
eggs, spinal fluid and mammary gland discharge.
[0041] In another embodiment, the sample chamber is a head space
analyzer (HSA) and can be fabricated from an inert material, such
as a molded fiberglass, or in certain embodiments can be fabricated
from plastic and can be configured like a box. As illustrated in
FIG. 3, the sample chamber (32) optionally has a glass-viewing
window and the box can contain pressure and temperature gauges (37)
to allow pressure and temperature monitoring. Moreover, the sample
chamber optionally contains valves for gas input and exhaust of the
box. Optionally, the sample chamber comprises a heater and a
pressure control means for an internally controlled atmosphere.
[0042] Similar to the BCC, the HSA has a first end (34) that is
open for access to the interior chamber (32) and functions as an
inlet port (30) and is vented by an exhaust (35). A fluid
concentrator (33) is disposed outside the sample chamber and is in
flow communication (36) with the exhaust (35). The sensor array
(39) is in flow communication with the desorbed analyte.
[0043] Optionally, the HSA contains appropriate connections for
high throughput screening (HTS). High throughput screening includes
a robotic armature system. In general, these systems include
automated workstations like the automated apparatus developed by
Takeda Chemical Industries, LTD. (Osaka, Japan) and many robotic
systems utilizing robotic arms (Zymate II, Zymark Corporation,
Hopkinton, Mass.; Orca, Hewlett-Packard, Palo Alto, Calif.), which
mimic the manual operations performed by a technician. The nature
and implementation of modifications to these devices (if any) so
that they can operate will be apparent to persons skilled in the
relevant art.
[0044] In operation, a volume of the gas to be sampled, such as
human breath, is introduced into a sample chamber where it is
transported by means of convention into the vicinity of the sorbent
material. Suitable transporting means include, but are not limited
to, a fan, an air pump, or it can be means for heating the
cylindrical container (12) to create a convective air flow between
the inlet and the outlet. The sorbent material is chosen from known
materials designed for the purpose of sorbing gases, vapors, and
the like. In certain embodiments, the sorbent material includes,
but is not limited to, a nanoporous material, a microporous
material, a chemically reactive material, a nonporous material and
combinations thereof. Such absorbents include, for example,
activated carbon, silica gel, activated alumina, molecular sieve
carbon, molecular sieve zeolites, silicalite, AlPO.sub.4, a
polymer, a co-polymer, alumina and mixtures thereof. In certain
embodiments, the absorbent has a pore size from about 1 nm to about
100 nm and, preferably, from about 1 nm to about 50 nm.
[0045] Suitable commercially available adsorbent materials are
disclosed in U.S. patent application Ser. No. 09/271,873, filed
Mar. 18, 1999, and include, but are not limited to, Tenax TA, Tenax
GR, Carbotrap, Carbopack B and C, Carbotrap C, Carboxen, Carbosieve
SIII, Porapak, Spherocarb, and combinations thereof. Preferred
adsorbent combinations include, but are not limited to, Tenax GR
and Carbopack B; Carbopack B and Carbosieve SIII; and Carbopack C
and Carbopack B and Carbosieve SIII or Carboxen 1000. Those skilled
in the art will know of other suitable absorbent materials.
[0046] After sometime period that is chosen to be adequate for
sorbing the desired analytes from the vapor phase onto the
material, the circulation is stopped and then the material is
desorbed from the sorbent phase and released into the sensor
chamber. The desorbing of the concentrated analyte for the sorbent
can be by accomplished by thermal means, mechanical means or a
combination thereof. Desorption methods include, but are not
limited to, heating, purging, stripping, pressuring or a
combination thereof.
[0047] In certain embodiments, the sample concentrator is wrapped
with a wire through which current can be applied to heat and thus,
desorb the concentrated analyte. The analyte is thereafter
transferred to the sensor array.
[0048] The process of sorbing the material onto the sorbent phase
not only can be used to concentrate the material, but also can be
advantageously used to remove water vapor. The water vapor is
preferably removed prior to concentrating the analyte; however, in
various embodiments, the vapor can be removed concomitantly or
after the analyte is concentrated. In a preferred embodiment, the
water vapor is removed prior to presenting the desired analyte gas
mixture to the sensor array. Thus, in certain embodiments, the
fluid concentrator contains additional absorbent material to not
only concentrate the analyte, but to remove unwanted materials such
gas contaminates and moisture.
[0049] In certain instances and depending on the absorbent used,
the concentration factor can exceed a factor of 10.sup.5, and more
preferably by a factor of about 10.sup.2 to about 10.sup.4. Thus,
the analyte gases can be concentrated from an initial sample volume
of about 10 liters and then desorbed into a volume of about 10
milliliters or less when they are presented to the sensor
array.
[0050] The array of sensors is present in fluid communication with
the concentrated analyte. Various sensors suitable for detection of
analytes include, but are not limited to: surface acoustic wave
(SAW) sensors; quartz microbalance sensors; conductive composites;
chemiresitors; metal oxide gas sensors, such as tin oxide gas
sensors; organic gas sensors; metal oxide field effect transistor
(MOSFET); piezoelectric devices; infrared sensors; temperature
sensors, humidity sensors, sintered metal oxide sensors; Pd-gate
MOSFET; metal FET structures; metal oxide sensors, such as a
Tuguchi gas sensors; phthalocyanine sensors; electrochemical cells;
conducting polymer sensors; catalytic gas sensors; organic
semiconducting gas sensors; solid electrolyte gas sensors;
piezoelectric quartz crystal sensors; dye-impregnated polymer films
on fiber optic detectors; polymer-coated micromirrors;
electrochemical gas detectors; chemically sensitive field-effect
transistors; carbon black-polymer composite chemiresistors;
micro-electro-mechanical system devices; and
micro-opto-electro-mechanical system devices and Langmuir-Blodgett
film sensors.
[0051] In a preferred embodiment, the sensors used in the present
invention are disclosed in U.S. Pat. No. 5,571,401, which is
incorporated herein by reference. Briefly, the sensors described
therein are conducting materials and nonconducting materials
arranged in a matrix of conducting and nonconducting regions. The
nonconductive material can be a nonconducting polymer such as
polystyrene. The conductive material can be a conducting polymer,
carbon black, an inorganic conductor and the like. The sensor
arrays comprise at least two sensors, typically about 32 sensors,
and in certain instances 1000 or more sensors up to about 10.sup.6
sensors. In a preferred embodiment, at least two sensors are
compositionally different. The array of sensors can be formed on an
integrated circuit using semiconductor technology methods, an
example of which is disclosed in PCT Patent Publication No.
WO99/08105, entitled "Techniques and Systems for Analyte
Detection," published Feb. 19, 1999, and incorporate herein by
reference. Another preferred sensor system is disclosed in PCT
Patent Publication No. WO99/27357, published Jun. 6, 1999.
[0052] In certain embodiments, the temporal response of each sensor
(response as a function of time) is recorded and can be displayed.
Various responses include, but are not limited to, resistance,
impedance, capacitance, inductance, magnetic, optical, etc. The
temporal response of each sensor can be normalized to a maximum
percent increase and percent decrease that produces a response
pattern associated with the exposure of the analyte. By iterative
profiling of known analytes, a structure-function database
correlating analytes and response profiles is generated. Unknown
analytes can then be characterized or identified using response
pattern comparison and recognition algorithms. Accordingly, analyte
detection systems comprising sensor arrays, a measuring device for
detecting responses across each sensor, a computer, a display, a
data structure of sensor array response profiles, and a comparison
algorithm(s) or comparison tables are provided. In another
embodiment, the electrical measuring device or detector is an
integrated circuit comprising neural network-based hardware and a
digital-analog converter (DAC) multiplexed to each sensor, or a
plurality of DACs, each connected to different sensor(s).
[0053] In certain embodiments, a method for using the sensors for
detecting the presence of an analyte in a fluid involves sensing
the presence of an analyte in a fluid with a chemical sensor
comprising first and second conductive leads electrically coupled
to and separated by a chemically sensitive sensor as described
above by measuring a first response between the conductive leads
when the sensor is contacted with a first fluid comprising an
analyte at a first concentration and a second different response
when the sensor is contacted with a second fluid comprising the
analyte at a second different concentration. As discussed above,
suitable responses include, but are not limited to, resistance,
impedance, capacitance, inductance, magnetic, optical, etc.
[0054] II. Medical Applications
[0055] The methods and apparatus of the present invention are
extremely useful and can be advantageously used for the detection,
identification, and classification of trace gas components, and are
extremely useful in a variety of applications, including medical
applications. In certain aspects, the methods and devices of the
present invention are useful and very effective for the detection
and diagnosis of diseases. In general, certain volatile marker gas
(es) characterizes the detection or diagnosis of a disease state or
medical condition. The methods and apparatus of the present
invention can advantageously by used to detect volatile marker
gases and compounds indicative of medical conditions, disease
processes, infections, illness and well-being. Using these marker
gases and compounds, clinicians can use the diagnostic instruments
and methods of the present invention to make diagnoses and
formulate appropriate treatments. The methods as described can
optionally be performed using a fluid concentrator as described
herein.
[0056] A. Oral Infections
[0057] In certain aspects, the present invention is extremely
useful for the detection of infections, such as oral infections and
dental cares. For example, bacteria cause two widespread dental
problems --halitosis and periodontal disease--and, as disclosed
herein, the methods and apparatus of the present invention can
detect the off-gases produced by such bacteria.
[0058] 1. Halitosis
[0059] Halitosis is caused by the breakdown of proteins by microbes
on the back of the tongue. The tongue coating is comprised of
epithelial cells from the oral mucosa, leukocytes from periodontal
pockets, and microorganisms. While the mouth is resident to over
300 bacterial species (see, Loesche et al., In Rosenberg M.,
Editor, "Bad Breath: Research Perspectives," Proceedings of the
First International Workshop on Oral Malodor, Ramot Publishing, Tel
Aviv University pp. 41-54 (1993)), the relative size of each
population is a function of many factors. Bad breath has been
associated with the expansion of anaerobic species (see, Loesche et
al., In Rosenberg Ed., "Bad Breath: Research Perspectives,"
Proceedings of the First International Workshop on Oral Malodor,
Ramot Publishing, Tel Aviv University pp. 41-54 (1993); de Boveri H
E et al., J. Am. Dent. Assoc., 126:1384-1393 (1995)). The
underlying cause of the increase in anaerobes can be poor oral
hygiene, aging, deep crevices in the tongue, post-nasal drip, or
numerous other conditions.
[0060] The chemical markers of bad breath have been identified and
include, but are not limited to, volatile sulfur compounds (VSC)
(see, Richter et al., Arch. Oral Biol., 9:47-53. (1964); Tonzetich,
Arch. Oral Biol., 16:587-597 (1971); Tonzetich, J. Periodontol.
48:13-20 (1977); Tonztich J, J. Int. Dent. J. 28:309-319 (1978),
and Tonzetich, Arch. Oral Biol., 16:587-597 (1971)).
[0061] As such, the present invention provides a method for the
detection of halitosis, the method comprising: contacting an array
of sensors with mammalian breath suspected of containing a marker
gas indicative of halitosis; and detecting the marker gas to
determine the presence of halitosis. In preferred embodiments, the
marker gases being detected by the sensors are volatile sulfur
compounds.
[0062] 2. Periodontal Disease
[0063] A far more serious consequence of oral infections is
periodontal disease. Gingivitis is the inflammation of the gums and
periodontitis is when the gum infection damages the bone and
supporting tissues. These conditions are the result of the
expansion of certain species of bacteria. If a piece of food is
trapped between the teeth, the bacterial types that can utilize the
various nutrients present will multiply. In addition, some of their
metabolic products can give rise to a second array of organisms.
And finally, if the population explosion of bacteria is sufficient
to elicit an inflammatory response, a third wave of bacteria can
arise that prefers the gingival crevicular fluid (see, Loesche W J
et al, In Rosenberg, Bad Breath Research Perspectives, Ramot
Publishing, Tel Aviv, pp. 41-54 (1993)).
[0064] VSC are also an indicator of periodontal disease (see,
Loesche et al, In Rosenberg, Bad Breath: Research Perspectives,
Ramat Publishing, Tel Aviv, (1995); Yaegaki et al, J. Periodontia.
Res. 27:233-238 (1992); Tonzetich et al., J. Dent Res 58:175
(1979); Frostell et al, Dent. J. 20:436-450 (1970); Sato et al,
Bull. Tokyo Dent. Coll., 21:171-178 (1980); Kostelc et al, J.
Periodontal Res. 15:185-192 (1980)). In addition, a number of other
compounds can be indicative of various bacterial populations (see,
Bosy et al., J. Periodontal. 65:37-46 (1994); McCulloch et al., In
Rosenberg, Bad Breath Research Perspectives, Ramat Publishing, Tel
Aviv, pp. 109-117 (1995)).
[0065] A significant development in recent years has been the use
of anti-microbials to treat periodontitis instead of surgery. It
has been shown that 80% of patients scheduled for surgery or
extractions could be successfully treated with a course of
metronidazole, doxycycline, or chlorhecidine. Overall, only about
10% of the teeth required the conventional surgery or extraction.
Surprisingly, by using the apparatus of the present invention, it
is possible to make a quick diagnosis, thereby alleviating
unnecessary surgery.
[0066] As such, the methods and apparatus of the present invention
can be used for the detection of periodontal disease. Thus, the
present invention provides a method for the detection of
periodontal disease, the method comprising: contacting an array of
sensors with mammalian breath suspected of containing a marker gas
indicative of periodontal disease; and detecting the marker gas to
determine the presence of periodontal disease. As explained above,
and detailed hereinbelow, numerous marker gases can be used to
detect and evaluate the severity of periodontal disease.
[0067] B. Pneumonia Detection
[0068] In certain instances, it currently takes two to three days
to culture the bacteria and determine whether the species that
cause pneumonia are present. Often, rather than waiting for this
determination, medical personnel prescribe broad-spectrum
antibiotics. Unfortunately, this prophylactic procedure can promote
the emergence of antibiotic-resistant strains.
[0069] The methods and devices of the present invention can
alleviate the unnecessary prescribing of antibiotic(s) by providing
rapid accurate detection and diagnosis of bacteria attributable to
pneumonia. Thus, the present invention provides a method for the
detection of pneumonia, the method comprising: contacting an array
of sensors with mammalian breath suspected of containing a marker
gases indicative of pneumonia; and detecting the marker gas to
determine the presence of pneumonia.
[0070] C. Wound Healing
[0071] One of the major reasons for slow healing wounds can be a
high level of bacteria. Frequently, wound healing is largely
undetected due to lack of tests for detecting microorganisms. Slow
wound healing is a problem that effects more than a million people
each year and costs billions of dollars to treat. Unfortunately,
one of the standard techniques of wound assessment is to smell the
exudate on the dressing. Nurses are advised to be aware of a
"repulsive" odor that may be associated with necrotic tissue and
"acrid or putrid" smells that are associated with anaerobic
bacteria.
[0072] However, these methods suffer from lack of specificity.
While the absence of odor is indicative of a clean wound, the
presence of odor does not necessarily signal an infection The
switch in recent years to moisture-retaining "wet dressings" has
further complicated the problem of wound assessment. Most dressings
have strong odors, but often times the odor is due entirely to the
materials in the dressings.
[0073] While there is a quantitative culture methodology that can
be employed to eliminate human errors, it is very expensive and
time consuming As such, it is only used routinely in burn centers
where patients are in much more serious conditions. Advantageously,
the present invention provides a method for diagnosing wound
healing comprising: contacting the vapors associated with the wound
with an array of sensors, thereby assessing the wound healing
process.
[0074] D. Vaginitis
[0075] The vaginal discharge of women with bacterial vaginitis
often has a prominent fishy odor. The presence of methylamine,
isobutylamine, putrescine, cadaverine, histamine, tyramine, and
phenethylamine are marker gases of vaginitis (see, Brand et al.,
Obstetrics and Gynecology, 68, 682-685 (1985)). Thus, the present
invention provides a method for the detection of vaginitis, the
method comprising: contacting an array of sensors with vaginal
vapors or discharge suspected of containing a marker gas indicative
of vaginitis; and detecting the marker gas to determine the
presence of vaginitis.
[0076] E. Fertility
[0077] In yet another aspect, the present invention provides
methods and apparatus for the detection of ovulation. The fertile
period of a female mammal, such as a human being, can be detected
by measuring axillary secretions. The markers are androstenol
and/or dehydroepiandrosterone sulfate. Thus, the present invention
provides a method for detecting ovulation, the method comprising:
contacting an array of sensors with vaginal vapor for the presence
of a marker gas indicative of ovulation; and detecting the marker
gas to determine ovulation.
[0078] F. Other Applications
[0079] In addition to the foregoing applications, other
applications for the methods and devices of the present invention
include, but are not limited to, environmental toxicology,
remediation, biomedicine, material quality control, food
monitoring, agricultural monitoring, heavy industrial
manufacturing, ambient air monitoring, worker protection, emissions
control, product quality testing, oil/gas petrochemical
applications, combustible gas detection, H.sub.2S monitoring,
hazardous leak detection, emergency response and law enforcement
applications, explosives detection, utility and power applications,
food/beverage/agriculture applications, freshness detection, fruit
ripening control, fermentation process monitoring and control,
flavor composition and identification, product quality and
identification, refrigerant and fumigant detection,
cosmetic/perfume applications, fragrance formulation,
chemical/plastics/pharmaceuticals applications, fugitive emission
identification, solvent recovery effectiveness, hospital/medical
applications, anesthesia and sterilization gas detection,
infectious disease detection, breath analysis and body fluids
analysis.
[0080] Various other medical conditions and associated pathogens
are set forth in Table 1
1TABLE 1 INFECTIONS AND PATHOGENS Area of Infection Pathogen
Interest Acute sinusitis Strep. pneumoniae, H. flu, Sinus Moraxella
catarrhalis, Group A strep., G(+) anaerobes, Staph. aureus
Pharyngitis Group A, C, G strep. Pharynx Pneumonia Strep.
pneumoniae, Lungs Mycoplasma, Chlamydia pneumoniae, H. flu
Bronchitis Strep. pneumoniae, H. Flu, Lungs Moraxella American
Thoracic Strep. pneumoniae, H. Lung Society (ATS) Class III CAP
influenzae, Klebsiella, Staph. Severe CAP aureus, Legionella Sp.,
ATS Class IV-ICU Pseudomonas aerug., other gram-negative bacteria;
Strep. pneumoniae, Staph. aureus, Legionella Sp., Pseudomonas
aerug., other gram negative bacteria Cystitis in females;
Enterobacteriaceae; Urinary Pyelonephritis; Prostatitis or
Enterobacteriaceae & Tract Epididymoorchitis Enterococcus sp.
Acute Meningitis Hemophilus influenzae, CNS Meningitis(post
surgical); Pneumococci, N. meningitidis Brain abscess
Staphylococcus sp., gram- negative bacteria; Streptococcus sp.,
anaerobes, Staph. sp. Biliary tract; Peritonitis or
Enterobacteriaceae, Abdo- Diverticular abscess Enterococcus sp.,
anaerobes men Cellulitis; Lymphangitis Streptococcus sp.; Skin Cat
bite, Dog bite, Decubitus Staphylococcus sp.; Pasturella ulcers,
(uncomplicated) or multicida, Staph & Strep., Diabetic foot
ulcer anaerobes; Gram negative (uncomplicated); Toxic Shock
bacteria; Gram-positive bacteria; Anaerobes
Endometritis/Endomyometritis Enterobacteriaceae, Pelvis Pelvic
Inflammatory Disease; Chlamydia sp., Streptococcus Septic
Thrombophlebitis sp. (group B Streptococcus), (postpartum)
Neiserria gonorrhoeae Endocarditis (IE) Streptococci sp. Heart
Prosthetic valve Staphylococcus sp. Staphylococcus epi. Septic
arthritis, Prosthetic Staphylococcus sp. & Strep. Bone &
joint, Osteomyelitis sp., Neisseria gonorrhoeae, Joint
Staphylococcus sp., Staphylococcus sp., Staph & Strep.sp.,
Enterobacteriaceae, anaerobes
[0081] G. Markers
[0082] As explained above, volatile sulfur compounds (e.g.,
H.sub.2S, CH.sub.3--SH, CH.sub.3--S--CH.sub.3) are the marker gases
implicated in halitosis and periodontal diseases (see, Tonzetich,
Arch. Oral Biol., 16:587-597 (1971); Rizzo, Periodontics, 5:233-236
(1967)). Other analytes that have been shown to correlate with such
clinical findings include, but are not limited to, volatile organic
acids (VOA), indole/skatole (indole), and diamines (see, Goldberg
et al., J. Dent. Res., 73:1168-1172 (1994); Goldberg et al., In
Rosesberg M Bad Breath Research Perspectives, Ramat Publishing, Tel
Aviv, pp. 71-85 (1995)).
[0083] In addition, several other analytes have been reported to be
associated with oral infections including pyridines/picolines (see,
Kostelc et al, J. Periodont. Res., 15:185-192 (1981); Kostelc et
al., Clin. Chem., 27:842-845 (1981)). Overall, more than 80
volatile compounds have been shown to be associated with saliva or
tongue scrapings (see, Claus et al., J. High Resol. Chromatogr.,
20:94-98 (1997)) and the methods and apparatus of the present
invention can be used to advantageously detect such marker
compounds and gases.
[0084] Using the methods and apparatus of the present-invention it
is also possible to detect the off-gasses associated with bacteria
associated with oral maladies including, but not limited to,
Prevotella intermedia; Fusobacterium nucleatum; Porphyromonas
gingivalis; Porphyromonas endodontalis; Prevotella loescheii;
Hemophilus parainfluenzae; Stomatococcus muci; Treponema denticola;
Veillonella species; Peptostreptococcus anaerobius; Micros
prevotii; Eubacterium limosum; Centipeda periodontii; Selemonad
aremidis; Eubacterium species; Bacteriodes species; Fusobacterium
periodonticum; Prevotella melaninogenica; Klebsiella pneumoniae;
Enterobacter cloacae; Citrobacter species and Stomatococcus
mucilaginus.
[0085] Moreover, a wide variety of analytes and fluids can be
detected and analyzed using the disclosed sensors arrays and
electronic noses so long as the subject analyte(s) and fluids are
capable of generating a differential response across a plurality of
sensors of the array. Analyte applications include broad ranges of
chemical classes including, but not limited to, organics such as
alkanes, alkenes, alkynes, dienes, alicyclic hydrocarbons, arenes,
alcohols, ethers, ketones, aldehydes, carbonyls, carbanions,
polynuclear aromatics and derivatives of such organics, e.g.,
halide derivatives, etc.; biomolecules such as sugars, isoprenes
and isoprenoids; VOC; VOA; indoles; skatoles; diamines; pyridines;
picolines; fatty acids; and derivatives of the forgoing, etc.
[0086] In addition to breath, the sensor arrays of the present
invention can be used to identify various analytes in other
biological fluids. These fluids include, but are not limited to,
urine, perspiration, tears, blood, mucus, pus, salvia, feces,
menstruation fluid, sperm, eggs, spinal fluid and mammary gland
discharge.
[0087] In general, most conditions and diseases listed herein have
microorganisms associated with them. The presence of marker gases
and compounds associated with the microorganism is in turn,
indicative of the presence of the disease or condition. In a
preferred embodiment, the off-gas of the microorganism is the
marker that is detected by methods and devices of the present
invention.
[0088] III. Anesthetics
[0089] In certain anesthetic vaporizers, a carrier gas, such as
air, oxygen or nitrous oxide, is divided between a first stream
directed to a chamber, wherein an anesthetic liquid is resident and
a second stream or bypass stream. The first and second streams are
recombined before delivery to the patient. Another version of an
anesthetic vaporizer is embodied in a device wherein the anesthetic
agent is injected directly into the carrier gas stream.
[0090] In either instance, it is imperative that the concentration
of volatile anesthetic liquid be known. The present invention
provides methods and an apparatus for the process control of
anesthetic gases. Using the methods and apparatus of the present
invention, a fluid concentrator is optionally used when monitoring
and quantitating anesthetic concentration.
[0091] By using the apparatus and sensors described herein, it is
possible to detect and quantitate the concentration of volatile
anesthetics including, but not limited to, halothane, isoflurane,
servoflurane, desflurane and enflurane. As such, the present
invention provides an anesthetic vaporizing system for quantitating
the concentration of the anesthetic, comprising: a carrier gas
source for delivering a carrier gas stream to a bypass valve,
wherein the bypass valve splits the carrier gas stream into a first
carrier gas stream for delivery to an inlet port and a second
carrier gas stream for delivery to a joining valve;
[0092] a vaporizing chamber for an anesthetic agent, comprising the
inlet port, an outlet port, a vaporizing means and a conduit for
delivery of vaporized anesthetic from the outlet port to the
joining valve; and
[0093] an array of sensors in flow communication with the joining
valve to quantitate the anesthetic. In preferred embodiments, the
system further comprising a detector operatively associated with
each sensor that provides a response in the presence of an
anesthetic vapor.
[0094] With reference to FIG. 4, the carrier gas source (41)
delivers the carrier gas to a bypass valve (44), wherein the
carrier gas is split between a first carrier gas stream for
delivery to the inlet port (45) of the anesthetic vaporizer (40)
and a second carrier gas stream which connects to a joining valve
(46). The anesthetic vaporizer contains a vaporizing means, such as
a heater, pressure souce or aspirator (48). The vaporizer includes
an outlet port (42) for delivery of the vaporized anesthetic
through a conduit (43) to the joining valve. The sensor array (49)
is in flow communication with the joining valve.
[0095] The present invention also provides a method of quantitating
an anesthetic vapor, comprising: containing the anesthetic vapor
with a sensor array to produce a response; detecting the response
with a detector, thereby quantitating the anesthetic vapor.
[0096] The following examples are meant to illustrate and not limit
the present invention.
IV. EXAMPLES
Example 1
[0097] In this Example, the detection and identification of
bacteria was conducted by measuring the metabolic products produced
from plate bacteria cultures carried out using an electronic nose
(a 32-sensor array) and a Fisher Linear Discrimination (FLD)
algorithm.
[0098] As shown herein, the data was also examined using principal
component analysis (PCA) and statistical isolinear multicategory
analysis (SIMCA). The results carried out on two very distinct
bacteria, i.e., peptostreptococcus anerobius and porphyromonas
gingivalis, show that the two bacteria were clearly discriminated
by the sensors as shown by PCA. The metabolites of additional an 11
bacteria and one fungus plus controls were tested and the data was
examined using PCA, SIMCA and FLD and discrimination among the
bacteria was demonstrated.
[0099] The objective of these experiments was to evaluate the
discriminating capability of a thirty-two sensor array composed of
mixtures of polymers and carbon black for metabolites produced by a
variety of bacteria. Fourteen fresh cultures were tested for the 20
most commonly suspected malodor producing, oral and pharyngeal
anaerobic and facultative bacteria including a fungus using a
32-sensor array. The experiment was done in two phases. The first
phase consisted of testing two very distinct bacteria,
peptostreptococcus anerobius and porphyromonas gingivalis, plus a
control (the media in which the bacteria were independently grown).
Four sample tubes of each bacterium and the control were tested to
investigate reproducibility. The results from the first test
indicated that gingivalis and anerobius could be discriminated from
each other and the control using a sensor array discussed
herein.
[0100] Ten samples of eleven bacteria, a fungus and ten controls
were tested with the same sensor array used described above. Table
3 lists the bacteria plus the main metabolite known to be produced
by these bacteria. Various statistical and mathematical techniques
were used to analyze the data obtained with chemiresistors on these
microorganisms. One of the methods used to classify the metabolites
produced from the various bacteria was principal component
analysis, an unsupervised pattern recognition technique. PCA
transforms multidimensional data sets into a lower dimensional
graphical representation, which describes a majority of the
variation in a data set. PCA defines a new set of axes to plot the
samples, they are constructed so that a maximum amount of variation
is described with a minimum number of axes, and the data is hence
readily visualized in this transformed data space (see, K. R.
Beebe, R. J. Pell, M. B. Seasholtz, Chemometrics: A Practical
Guide, Wiley, New York, 1998.)
[0101] Another algorithm used to analyze the data set was Fisher
Linear Discrimination (FLD). FLD seeks a linear combination of the
variables, which maximizes the ratio of its between-group variance
to its within-group variance (see, B. D. Ripley, Pattern
Recognition and Neural Networks, University Press, Cambridge, 1996,
Chapter 3, p 93.).
[0102] Other algorithms used to analyze the data were K-nearest
neighbor (KNN) and statistical isolinear multicategory analysis,
SIMCA. Both of these algorithms are supervised pattern recognition
methods used for predicting the class of unknown samples given a
training set of samples with known class membership. With KNN, a
classification is always made, whether or not the unknown is a
member of the class in the training set. KNN is a much simpler
algorithm than SIMCA because unlike SIMCA it makes no assumptions
about the size or shape of the class. SIMCA can detect if an
unknown sample is not a member of any class in the training set.
SIMCA uses the shape and position of the object formed by the
samples in a class for class definition (see, K. R. Beebe, R. J.
Pell, M. B. Seasholtz, Chemometrics: A Practical Guide, Wiley, New
York, 1998). The results obtained using all the described
algorithms are set forth below.
[0103] A. Experimental
[0104] 1. Testing Protocol
[0105] Thirty polymers were chosen based both on structural
differences and on solubility to generate a thirty two sensor
array. The testing protocol used for all the bacteria was the same
and is described below. Anerobius and gingivalis were tested in one
day, whereas the rest of the bacteria were tested over several
days.
[0106] Testing instrument: A Keithley electrometer and scanner were
used to scan the resistances of 32 sensors during the
experiment.
[0107] Sampling: the headspace above the bacteria was sampled using
nitrogen gas as the carrier. The flow rate used was 100 mL/minute.
No dilution with air was done. The flow rate of the background air
used to purge the sensors was 10 L/minute. No preconcentration was
preformed.
[0108] Temperature: The temperature of the substrates was not
controlled and the measurements were done at room temperature for
the first phase study. The temperature of the substrates was
maintained at 28.+-.0.1.degree. C. for the second phase study.
[0109] Purge and Exposure times: For each sample test, there were
60 seconds of background recording (purged with air), 120 seconds
of exposure time, 120 seconds of recovery time (purged with air
with RH level of about 3%), 180 seconds of recovery without
recording the data (purged with air), and 30 seconds of final
recording time (purged with air).
[0110] B. Results and Discussion
[0111] 1. Sensor Array Response
[0112] The response pattern of the 32-sensor array described above
to anerobius, gingivalis, and the control is shown in FIG. 5. Note
that the reproducibility of the sensor array was very good. The
response (the normalized resistance change,
(R.sub.max-R.sub.o)/R.sub.o), where R.sub.max and R.sub.o are the
maximum and base (initial) resistance, respectively) of the sensor
array to each sample tested is employed to form a covariance
matrix, which is used to do principal component analysis. PCA of
the two bacteria plus control (data not shown) were clearly
discriminated by the sensor array. SIMCA was also used to evaluate
the data. The model was built with all the data as the training set
and the data from the first test was used as the unknown. A
classification rate of 100% was obtained using the SIMCA algorithm.
KNN was also used to examine the data set. A model was built using
the data from three sample tubes of each bacteria plus the control.
One of the samples was used as the unknown. Using 3 or 5 nearest
neighbors in the KNN algorithm gave a classification rate of 66%.
The FLD algorithm was not used on this data set.
[0113] In the second phase study, ten samples of 11 bacteria and
one fungus were tested. The temperature of the substrates was
controlled at 28.+-.0.1.degree. C. for all tests. The sample tubes
were not temperatures controlled. As described in the experimental
section, each bacterium was tested 19 times among 9 test tubes.
Thirty-two sensors responded to 11 bacteria and one fungus, 19
times for each. A covariance matrix that contained 32 columns (one
column for each sensor response) and 12.times.19 rows (bacteria
tested at different times) was formed. This matrix was used to do
principal component analysis.
[0114] A different algorithm, Fisher Linear Discrimination, was
introduced to process the data set. To construct a model using the
FLD method, it is required that the data take the form of a square
matrix. The columns and rows in the matrix correspond to the number
of sensors and the number of test samples, respectively. Hence, to
use FLD, the number of sensors needs to be equal to the number of
sample tests. Each of the 11 bacteria and one fungus were tested 19
times thus, only 19 sensors could be used to construct the FLD
model. Hence, a square matrix was formed using each of the bacteria
tested 19 times and choosing 19 sensors out of the 32. The very
first test (tube 1) and the last test (tube 5) of each bacterium
were used as unknowns. The first 19 sensors out of the 32-sensor
array were found to give the highest prediction rate out of other
sensor combinations. Twenty-four unknowns were predicted from the
FLD model. The results provided a classification rate of 91.7%
(see, Gibson, T. D., Prosser, O., Hulbert, J. N., Marshall, R. W.,
Corcoran, P., Lowery, P., Ruck-Keene, E. A., Heron, S., Sensors and
Actuators (B) 44, 413-422, 1997).
[0115] As a comparison, a SIMCA model was built with the same
training set used for the FLD analysis. The same 24 unknowns was
used for SIMCA prediction. The results provided a classification
rate of 75%. The KKN algorithm was also used and the classification
rate was 66%.
2TABLE 2 SENSOR COMPOSITION AND DEPOSITION CONDITIONS P'er CHIP
ENX-1-070798 Sensor Dilution # Polymer # Solvent Ratio 19
Hydroxypropyl cellulose Sr 1 water 150 to 1 22 Methyl vinyl
ether-co-maleic acid, Sr 2 water 151 to 1 50/50 34 Polyacrylamide
Sr 3 water 150 to 1 35 Polyacrylamide, carboxyl modified Sr 4 water
150 to 1 (LC) 36 Polyacrylamide, carboxyl modified Sr 5 water 150
to 1 (HC) 55 Poly(ethylene oxide) Sr 6 water 150 to 1 73 Poly(vinyl
alcohol), Sr 7 water 150 to 1 100% hydrolyzed 74 Poly(vinyl
alcohol), 98% hydrolyzed Sr 8 water 150 to 1 CHIP ENX-2-070798 3
Alginic acid, sodium salt Sr 9 toluene 25 to 1 10 Ethylene-co-ethyl
acrylate, 82/18 Sr 10 toluene 25 to 1 12 Ethylene-co-vinyl acetate,
86/14 Sr 11 toluene 25 to 1 39 1,2-Polybutadiene Sr 12 toluene 25
to 1 42 Polycaprolactone Sr 13 toluene 25 to 1 41 Poly(n-butyl
methacrylate) Sr 14 toluene 25 to 1 48 Poly(n-ethyl methacrylate)
Sr 15 toluene 25 to 1 50 Polyethylene, chlorinated (42& Cl) Sr
16 toluene 25 to 1 CHIP ENX-3-070798 54 Polyethylene,
chlorosulfonated Sr 17 toluene 25 to 1 59 Poly(isobutyl
methacrylate) Sr 18 toluene 25 to 1 63 Poly(.alpha.-methyl styrene)
Sr 19 toluene 25 to 1 68 Polystyrene Sr 20 toluene 25 to 1 80
Poly(vinyl stearate) Sr 21 toluene 25 to 1 87
Styrene/ethylene/butylene, Sr 22 toluene 25 to 1 ABA block 95 Vinyl
chloride/vinyl acetate/ Sr 23 toluene 25 to 1 hydroxypropyl 79
Poly(vinyl pyrrolidone) Sr 24 water 150 to 1 CHIP ENX-4-070798 63
Poly(.alpha.-methyl styrene) Sr 25 toluene 25 to 1 79 Poly(vinyl
pyrrolidone) Sr 26 water 150 to 1 86 Styrene-co-butyl methacrylate
Sr 27 toluene 25 to 1 82 Styrene-co-acylonitryle, 75/25 Sr 28 THF
100 to 1 90 Vinyl alcohol-co-vinyl butyral; 20/80 Sr 29 THF 100 to
1 104 Poly (4-methoxy styrene) Sr 30 THF 100 to 1 105 Poly methyl
hydrosiloxane Sr 31 THF 100 to 1 102 Poly diphenoxyphosphazene Sr
32 THF 100 to 1 carbon black was used in each sensor at a
concentration between 20-25 wt %
[0116]
3TABLE 3 LIST OF BACTERIA AND THEIR METABOLIC PRODUCTS BACTERIA
NOMENCLATURE METABOLIC PRODUCTS OR OFF-GASES Enterobacter cloacae
Bac 1 Isobutyric and isovaleric acid Cit. Koseri Bac 2 N/A
Psuedomonas Aeruginosa Bac 3 N/A Veilonella species Bac 4 Acetic
and propionic acid and isoamyl alcohol Prevotella melaninogenica
Bac 5 Isovaleric acid Escherichia coli Bac 6 Acetic and propionic
acid Klebseilla Pneumoniae Bac 7 Methyl ethyl ketone,
methylbutanal, 2-butanol, pentanone, dimethyl sulfide, isobutanol,
isopentylacetate, 2-heptanone isopentanol, 2-nonanone, 2-undecanone
Streptococcus mutans Bac 8 Acetic acid, propionic acid *Candida
albicans Bac 9 N/A Prevotella intermedia Bac 10 Isovaleric acid
Fusobacterium nucleatum Bac 11 Acetic, propionic and butyric acid
Staph. aureus Bac 12 Acetic, 2-butanone, 2-butanol, pentanone,
methyl butanol, toluene, 2-heptanone, isopentanol, 2-nonanone,
2-undecanone, acetone, 2-nondecagon Peptostreptococcus anerobius
Acetic, isobutyric, butyric, isovaleric and isocaproic acid
Porphyromonas gingivalis Isovaleric acid *This is a fungus
Example 2
[0117] This Example illustrates that the apparatus and methods
comprising the sensor arrays of the present invention are suitable
for process control of anesthetic gases. As disclosed herein, a
method for monitoring anesthetic gases in order to establish
reliable monitoring of a patient's condition while under
anesthetics is possible. Conducting-polymer composite sensors
change resistance when exposed to an analyte in the vapor phase,
and the pattern of such resistance changes across an array allows
identification of a concentration of an analyte. The pattern height
allows identification of the concentration of an analyte. The
experiments show that these arrays are suitable for process control
over the concentration of anesthetic gases at levels that are
clinically of interest.
[0118] Using a 18-sensor array a suitable concentration of
halothane was delivered. The flow rate of the carbon dioxide
carrier gas was 10 mL/min. The anesthetic gas flow rate was 0.2
mL/min, thus the ratio of carrier gas flow over the summation of
the carrier gas flow and the anesthetic gas flow was 2%. FIG. 7
illustrates the response of 2% halothane on the sensor array. FIG.
8 illustrates the linear response for sensor 10 with halothane
concentration.
4TABLE 4 18 SENSOR ARRAYS Sensor Polymer and carbon black Carbon
black 1. Poly(4-vinyl phenol) [24979-70-2] 40 mg Carbon black MW
1500-7000 Polysciences Cat #06527 (soluble in THF) 0.160 g in 20 ml
THF 2. Poly(Styrene-co-alkyl/alcohol) 46 mg carbon black
Polysciences Cat #03773 (soluble in THF) 5.7% hydroxyl, MW 1500
0.156 g in 20 ml THF 3. Poly (.alpha.-methylstyrene) [25014-31-7]
41 mg carbon black Aldrich 0.164 g in 20 ml THF 4. Poly(vinyl
chloride - vinylacetate) [9003-22-9] 39 mg carbon black 10% vinyl
acetate Polysciences Cat #07058 0.164 g in 20 ml THF 5. Poly(vinyl
pyrrolidone) [9003-39-8] 41 mg carbon black Aldrich Average Mw
10,000 (both in TFSH @ 6 mg/ml) 0.160 g in 20 ml THF 6. Poly(vinyl
acetate) [9003-20-7] 42 mg carbon black Polysciences MW: 500,000
0.163 g in 20 ml 7. Poly(methyl vinyl ether - maleic 39 mg carbon
black anhydride) [9011-16-9] Polysciences Cat #0303 0.162 g in THF
8. Poly(bisphenol A carbonate) [24936-68-3] 39 mg carbon black MW
32,000-36,000 Polysciences Cat #00962 0.169 g in 20 ml THF 9.
Poly(styrene) [9003-53-6] 41 mg carbon black MW 125,000-250,000
beads Polysciences Cat #00574 0.160 g in THF 10. Poly(styrene -
maleic anhydride) [9011-13-6] 40 mg carbon black 50% of each Mw
1600 Polysciences Cat #0316 0.160 g in 20 ml THF 11. Poly(vinyl
butyral) [63148-65-2] 41 mg carbon black Mw 100,000-150,000
Polysciences Cat #06100 0.160 g in 20 ml THF 12. Poly(sulfone)
[25135-51-3] 40 mg carbon black 0.166 g in 20 ml THF Mw 30,000
Polysciences Cat #07074 13. Poly(methyl methacrylate) [9101-14-7]
41 mg carbon black Aldrich Average Mw .about.120,000 Contains
<5.0% toulene 0.162 g in 20 ml THF 14. Poly(vinylidene chloride
- acrylonetrile) [9010- 40 mg carbon black 76-8] 0.161 g in THF
(80:20) Polysciences cat. #09747 15. Poly(caprolactone)
[24980-41-4] 42 mg carbon black Polysciences cat. #07039
Biodegradable polymer 0.159 g in 20 ml benzene 16. Poly(ethylene -
vinyl acetate) [24937-78-8] 39 mg carbon black 0.168 g in 20 ml
benzene 82% ethylene Polysciences cat. #02309 17.
Poly(ethyleneoxide) [25322-68-3] 42 mg carbon black Aldrich Arc Mw
100000 0.162 g in benzene * Sonicated each suspension for 5 min.
18. Poly(9-vinyl carbazole) .about.40 mg carbon black Aldrich
[25067-59-3] 18,260-5 Ave. Mw CQ 1,100,000 0.162 g polymer
[0119] It is understood that the examples and embodiments described
herein are for illustrative purposes only and that various
modifications or changes in light thereof will be suggested to
persons skilled in the art and are to be included within the spirit
and purview of this application and scope of the appended claims.
All publications, patents, and patent applications cited herein are
hereby incorporated by reference for all purposes in their
entirety.
* * * * *