Trace inorganic analysis is an essential part of analytical testing. In many cases, contamination can alter or skew elemental analysis, which leads to inaccurate results. Another way in which contaminants can alter results in a detrimental fashion is in regard to proficiency testing and laboratory audits. Proficiency testing (PT) is a series or schemes of samples that are intended to assess the performance of individuals or laboratories in specific areas or for specific analytical tests. PT is also designed to be used to improve processes and methods. If contamination and error enter into the analysis process, then the results can be altered, causing the analyst or laboratory to perform poorly in a PT scheme. In this two-part article, we examine the development, rationale, and best practices for PT, including how contamination can enter inorganic samples and how to eliminate or control those sources.

Proficiency testing (PT) is a phrase that often solicits groans or resigned sighs. Most of us on the receiving end of a proficiency test dislike even the thought of being “evaluated” despite the fact that testing is our “business” in many cases. The truth is that PT is not a tool to trick analysts or put them on the spot. Laboratories use PT to comply with their accreditation requirements and evaluate analyst performance. PT is an integral part of a quality management system (QMS) under quality assurance and control (QA/QC).

A QMS contains the practices and processes a business follows to meet customer requirements. The International Organization for Standardization (ISO) has become one of the world’s largest developers of voluntary international standards for all manufactured, agricultural, and technological products and services. The standards issued by ISO are the framework for the quality management systems of ISO accredited companies and laboratories (1).

In the 1990s, ISO began creating standards for laboratories to standardize procedures and ensure competency and accuracy. Throughout the years, laboratories, reference materials, and PT providers have pursued ISO accreditation for their facilities as a mark of quality and reliability (2).

A QMS includes components such as a mission statement, goals, and objectives through all the processes for organizational structure, data management, manufacturing processes, and QA/QC. Many laboratory practices fall under the heading of QA/QC while still being part of the overall quality system. Laboratory QA/QC has may processes routinely included in standard operating procedures (SOP). Some of the key processes for analytical laboratories are the use of certified reference materials (CRMs) or standards, the use of validated or verified methods, and the use of PT to ensure quality.

In PT, one uses characterized samples that are created to represent the types of samples, matrices, and targets being analyzed in laboratories. Most of the time, these samples contain measured values that are not disclosed to the PT participants and are treated like blind samples—samples in which the nature and quantities are unknown. Some proficiency tests may give information in regard to the target identity, quantitative range, and other information, which directs the analyst in how to perform sample preparation or analyses. PT samples can come in many different forms, from solid or liquid native matrices to extracted oils, liquids, and solids. The analyst is expected to prepare and treat the PT sample in the same way similar types of samples would be routinely processed.

PT participants confidentially share their results with the PT provider for final evaluation and grading. In this way, PT serves as an indicator for the competency of an individual laboratory staff and its analytical performance. Results reported to the PT provider are compared to the reference values established for that PT, which are either established by a reference laboratory or determined by averaging the values reported by the PT participants. Participating PT laboratories can report their values either as individual values or as a composite average value determined by the results obtained by all their individually tested analysts.

PT participants that achieve passing PT results are ensuring the validity and reliability of their laboratory test results. PT is an external quality assessment tool. PT should be an integral part of the testing laboratory’s quality system. In the evaluation of a PT program, the laboratory must consider some critical points: the qualifications of the PT administrator; the quality and qualifications of the PT provider; and the accessibility of data. Within most QMS systems, such as those based on the ISO guidelines, laboratories are required to use certified providers for their analytical standards, methods, and PT. For ISO 17025 laboratories, PT providers must be accredited to ISO 17043 and CRM providers to ISO 17034.

PT is not a means of method validation. Methods used for PT should have previously been validated by the laboratories or standards organizations that have issued those methodologies—that is, the United States Pharmacopeial Convention (USP) (3) and the American Society for Testing and Materials (ASTM) International. PT serves to measure the ongoing proficiency of independent laboratories through interlaboratory comparison of test results for the same sample. Some regulatory bodies stipulate the frequency of PT participation, requiring laboratories to participate in PT on an annual basis. Other laboratories participate in accordance with their accreditation audit schedule. Some accreditation audits only occur once every other year. Thus, the laboratories would participate in PT once every two years.

Understanding the key components of the QMS a laboratory operates under is an important part of passing any PT test. Some of the issues with PT results are not the result itself but the way the statistics, standards, and methods of the QMS have been applied, leading to error.

Evaluating Methods for Regular Use and Proficiency Testing 

Analytical methods intended for use in an accredited laboratory (for regular use or in PT) must either be validated or verified under the laboratory’s QMS. Method validation is the process in which a new method undergoes testing and statistical analysis to determine if it is fit for the intended purpose. Method validation occurs either when a new method is created, or when an existing method is changed so significantly that all the statistical parameters need to be reestablished. Method verification occurs when a method is transferred from one type of process to another similar type of process, such as transferring an atomic absorption (AA) method to an inductively coupled plasma (ICP) method.

Passing a proficiency test can serve as method verification because PT is used to check an already validated method. For example, standard methods and compendial methods are verified, whereas in-house–developed methods are validated. After an in-house method has been validated, it can be verified by successfully passing a proficiency test from an accredited third-party provider. In this example, PT is integral to the QMS of the participant laboratory (4).

All methods must undergo statistical evaluations and must establish the method dynamic range as part of the quality management program, including the statistical concepts of true value, error, bias, uncertainty, accuracy, and precision, which are all interrelated concepts.

Understanding the Basis of Laboratory Statistics

The goal for all analytical analyses is to have measured values close to the true value. 

 is a measurement of how close measured values get to the true value; precision indicates how close a group of results are to one another.

Factors that move the measured value away from the true value are called 

 is the partiality or systematic deviation from the true value that results in over or underestimation. 

 is the difference between the measurement and the true value. Error causes values to differ when measurement is repeated. It is impossible to completely eliminate error, but it can be controlled and documented.

Errors are characterized as random or systematic. Random errors are fluctuations and variances in even the most tightly controlled systems that produce anomalies. Random errors are often impossible to eliminate. Precision is often associated with the statistical measurement of random error. The second type of error is systematic error, which appears from a traceable source, such as instrument malfunction, record-keeping errors, or measurable repeated variants, that affects result outcomes. Systematic errors can often be eliminated by routine maintenance, procedure changes, or record keeping (Figure 1).

The final important concept for laboratory analyses is uncertainty. Uncertainty is a statistical estimate attached to a value that characterizes the range of values where the true value lies within a stated confidence interval. Uncertainty estimates the effect of short-term fluctuations, variables in the performance of an analyst or piece of instrumentation, or accounts for bias or drift that can be corrected or calculated (Figure 2).

Uncertainty can be calculated in many different ways depending on the type of instrument, equipment, or processes being evaluated. However, all the possible factors that can influence or change the range of expected values must be included in an uncertainty calculation. A suitable QC-known certified reference material or reference standard should be employed for calculating statistics and validating an analytical method.

Standards are a critical key in all analytical analyses. In the case of conducting a PT study or scheme, standards play a critical role in obtaining passing results. The first step in using standards as a part of an analytical process is to understand what standards or reference materials are and how they are used. Standards can be used for qualitative analysis (identity), quantitative analysis (numerical results), or both. They can also aid in identifying or eliminating errors, or be used to determine statistical variables, such as uncertainty, accuracy, and precision.

As a result, questions often arise regarding which standards are used and at what point standards are introduced into a sample preparation and analysis process. One of the most important considerations for choosing a standard (for both general analyses and PT schemes) is whether the standards fit for the purpose in which they will be used (Figure 3). Some questions to ask are: Does the standard reflect the identity or type of sample that is going to be tested? Are the forms (oil, power, solid, among others) of the standards or samples significantly different in a way that will affect the outcome of testing? In the same vein, is the matrix of all the samples, standards, and PT schemes the same or different, and will that change the results or processing? Are the standards amenable to the type of instrumentation being used? Will the samples and standards fall into the analytical range of those instruments? Will changes have to be made to the methods or instruments? The choice of standards can also be difficult to navigate because there are often many choices between reference materials, CRMs, standards, and QC samples.

Often, the highest level of commercially produced reference materials are certified standards or CRMs produced by primary or secondary standards providers under a QMS such as ISO. These suppliers produce CRMs that have one or more certified values with uncertainty established using validated methods and are accompanied by a certificate of analysis. The uncertainty characterizes the range of the dispersion of values that occur through the determinate variation of all the components that are part of the process for creating the standard.

CRMs have a number of uses, including validation of methods, standardization or calibration of instrument or materials, and for use in QA/QC procedures. A calibration procedure establishes the relationship between a concentration of an analyte and the instrumental or procedural response to that analyte.

 is the plotting of multiple points within a dynamic range to establish the elemental response within a system during the collection of data points. The matrix effect can be responsible for either elemental suppression or enhancement. In analyses where a matrix can influence the response of target, it is common to match the matrix of analytical standards or reference materials to the matrix of the target sample to compensate for matrix effects.

Calibration curves are the practical application or function of standards in analyses. Standards are diluted to points on the curve that reflect the range of target concentrations and are often affected by the limitations of the instrumentation. Data can become biased by calibration points biased by instrument limits of detection, quantitation, and linearity and by the response of the system versus its baseline (signal-to-noise).

The limit of detection (LOD) is the lower limit of a method or system at which the target can be detected as different from a blank with a high confidence level (usually over three standard deviations from the blank response). The limit of quantitation (LOQ) is another lower limit of a method or system in which the target can be calculated, where two distinct values between the target and blank can be observed, usually over 10 standard deviations from the blank response (Figure 1). The signal-to-noise ratio (S/N) is a measurement of the ratio between response of an analyte to the baseline variation (noise) of the system. LOD values are often recognized as target responses that have three times the response of baseline noise or S/N ≥ 3. LOQs are recognized as target responses that have 10 times the response of baseline noise or S/N ≥ 10. Limits of linearity (LOL) are the upper limits of a system or calibration curve where the linearity of the calibration curve starts to be skewed, creating a loss of linearity. This loss of linearity can be a sign that the instrumental detection source is approaching saturation. Finally, dynamic range is the array of values between the LOQ and the LOL where the greatest potential for accurate measurements will occur. Dynamic range can be established for instruments and analytical methodologies. Effective calibrations are created within the system‘s and method’s dynamic range.

The establishment of an instrument’s dynamic range is most often designated by the type of instrumentation. The dynamic range for a method is most commonly established during the method validation or verification process (Table I and Figure 4).

Changes to methods or policies should all be completed and validated prior to any PT.

Updated copies of those policies and procedures should be reviewed with all staff members participating in the PT.

Train staff for proper handling of PT samples, results, and reports.

Make sure all maintenance and repairs of systems are completed well in advance of a PT round.

Calibration and linearity checks should be performed by analysts on equipment and instruments prior to starting PT.

Replace all consumable chemicals with fresh materials.

Complete any statistical evaluations of precision and accuracy needed for the intended method or systems before PT.

Check calibration and cleanliness of equipment, volumetrics, and labware.

Derailing PT with Contamination and Error

The fastest way to significantly deviate from a result’s true value is by error and contamination. As we discussed earlier, there are some forms of error (random error) that are difficult to eliminate entirely. Then, there is systematic error, in which some mistakes or deviations in systems or procedures can be corrected. First, let us look at common sources of error in the laboratory: calculation, measurement and dilution mistakes, errors, and contamination.

Calibration curves are a key element of analytical procedures. These curves are created by diluting standards into several target points along the dynamic range to cover the possible target results. Proper dilution of standards and samples is based on the understanding of basic dilution and volumetric procedures and dilution factors. Volumetric measurement is a common repeated daily activity in most analytical laboratories. Many processes in the laboratory, from sample preparation to standards calculation, depend on accurate and contamination-free volumetric measurements. Unfortunately, laboratory volumetric labware, syringes, and pipettes are common sources of misuse, contamination, carryover, and error in the laboratory.

The root of these errors is based on the four “I” errors of volumetrics: incorrect choice, inadequate cleaning, infrequent calibration, and improper use. These four “I”s can lead to error and contamination, which negates all intent of careful measurement processes.

Incorrect choice can be seen in the choice of grades of labware or the selection of pipettes and syringes for analytical measurements. Many errors can be avoided by understanding the markings displayed on the volumetric containers and choosing the proper tool for the job. There is a lot of information displayed on volumetric labware. Most labware, especially glassware, is designated as either Class A (analytical or quantitative) or Class B (general use) labware. If a critical measurement process is needed, then only Class A glassware should be used for measurement.

As for syringes and pipettes, many manufacturers recommend a minimum dispensing volume of approximately 10% of the total volume of the syringe or pipette. Spex studies showed that dispensing such a small percentage of the syringe’s total volume created a large amount of error (5). Dispensing 20% of a 10 μL syringe created over 20% error. The error only dropped down below 5% once the volume dispensed approached 100%.

Larger syringes were able to get closer to the 10% manufacturer’s dispensing minimum without a large amount of error, but the error did drop as the dispensed volume approached 100%. The better choice for measuring materials using a syringe or pipette is to select a pipette closest to the targeted amount to be dispensed to reduce error.

Inadequate cleaning of syringes and pipettes can lead to crossover and contamination, which can skew your results. Many volumetric containers can be subject to memory effects and carryover. In critical laboratory experiments, labware sometimes needs to be separated by purpose and use. Labware subject to elevated levels of organic compounds or persistent inorganic compounds can develop chemical interactions and memory effects. It is sometimes difficult to eliminate carryover from labware and syringes even when using a manufacturer’s stated instructions. For example, many syringes are cleaned by several repeated solvent rinses prior to use. A study of syringe carryover by Spex showed that some syringes are subject to elevated levels of chemical carryover despite repeated rinses (5).

Infrequent calibration happens when a laboratory does not follow a quality plan or is lacking in its routine maintenance. Many laboratories have schedules of maintenance for equipment such as balances and automatic pipettes, but often overlook calibration of reusable burettes, pipettes, syringes, and labware. Under most normal use, labware often does not need frequent calibration, but there are some instances where a schedule of recalibration should be employed. Any glassware or labware in continuous use for years should be checked for calibration. Glass manufacturers suggest that any glassware used or cleaned at high temperatures, used for corrosive chemicals, or autoclaved, should be recalibrated more frequently. It is also suggested that under normal conditions, soda-lime glass should be checked or recalibrated every five years, and borosilicate glass should be checked after it has been in use for 10 years.

Inorganic analysts know that glassware is a source of contamination. Even clean glassware can contaminate samples with elements such as boron, silicon, and sodium. If glassware, such as pipettes and beakers, are reused, the potential for contamination escalates. At Spex, a study was conducted to measure the residual contamination of pipettes after being manually and automatically cleaned using a pipette washer (5). An aliquot of 5% nitric acid was drawn through a 5 mL pipette after the pipette was manually cleaned according to standard procedures. The aliquots were analyzed by ICP-mass spectrometry (MS). The results showed significant residual contamination still persisted in the pipettes despite a thorough manual cleaning procedure but was reduced when an automated washer was employed.

Finally, improper use can apply to the actual way in which the labware is to be used. If a volumetric is designed to contain liquid, it will be marked by either the letters TC or IN. Labware that is designated to deliver liquid would be marked by either the letters TD or EX. Sometimes, there are additional designations, such as wait time or delivery time, inscribed on the labware. The delivery time refers to a period of time required for the meniscus to flow from the upper volume mark to the lower volume mark. The wait time refers to the time needed for the meniscus to come to rest after the residual liquid has finished flowing down from the wall of the pipette or vessel. An analyst should wait for the liquid to stabilize before attempting to dispense for other dilutions.

The first dilution many laboratories make is a stock solution or starting solution. This type of working standard is made to create a higher concentration stock from raw materials or concentrated material from which other standards will be made.

For this calculation, one needs the concentration of the target stock, the final weight or volume of the total stock and the purity of the raw material (or concentration of the concentrate being used).

Another type of dilution is a simple dilution using a dilution factor as seen in the below equations:

To make calibration curves, most people employ a mixture of simple dilutions separate from each other or use a serial dilution which is a series of dilutions, where each dilution is cumulative. Although this type of dilution is typical in some situations, if an error occurs during early dilutions, then subsequent dilutions can also be in error; therefore, bias could be created in the calibration curve. In preparing for a PT scheme, it is best to create a checklist of all the steps, equipment, supplies, and materials that could be needed for the testing. It is important to check equipment calibration and cleanliness before starting the PT (6,7).

Best Practices for Planning for Proficiency Testing

Use only calibrated volumetrics to create dilutions and allow sufficient time for equilibration of the volumetrics as noted by the equipment.

Check the quality of all volumetric labware and chemical materials to reduce contamination.

Plan ahead for ordering standards, chemicals, and consumable supplies needed for the study.

Check and recheck all calculations for calibration curves and dilutions.

Check the study dates and plan ahead for sufficient time to complete the PT study.

Make sure to order PT schemes well ahead of study start date to ensure enough time.

The function and reputation of a laboratory is based on producing accurate results that are above reproach and often can be legally defensible. A QMS dictates within its policies a set of checks and balances to provide validation that the results are valid. A part of this checks and balance system is the use of PT to document the ability of the laboratory and its employees to produce quality results. In some laboratories, such as in the case of a trace inorganic laboratory, routine issues, such as contamination and error, can severely alter results and cause bias. These biases can lead to erroneous results or PT failures. By recognizing all the possible sources of error and contamination in the inorganic laboratory environment, one can actively try to eliminate contamination and error, thereby producing more accurate results. Part 2 of this article, which will be published in the July “Atomic Perspectives” column, will examine the planning, running, and reporting of a PT scheme and the possible impact of error and contamination.

(1) International Organization for Standardization, 

Conformity Assessment – General Requirements for Proficiency

 (ISO/IEC Standard No. 17043) (2010) Retrieved from: 

(2) International Organization for Standardization, 

General Requirements For the Competence of Testing and Calibration Laboratories

 (ISO/IEC: Standard No. 17025) (2017). Retrieved from: 

https://www.iso.org/publication/PUB100424.html

(3) United States Pharmacopeial Convention, USP Proficiency Testing Program. 

(4) NSI Laboratory Solutions, Proficiency Testing. 

www.nsilabsolutions.com/proficiency-testing/

(5) SPEX, CertiPrep Webinar Clean Laboratory Techniques. 

https://www.spexcertiprep.com/webinar/clean-laboratory-techniques 

(6) American Society for Testing and Materials, ASTM D1193-06(2018), Standard Specification for Reagent Water. 

(7) Spex, Knowledge Base for White Papers on Dilutions, Calibrations, and Standards. 

www.spex.com/Knowledge-Base/AppNotesWhitepaper

Articles

Column: Atomic Perspectives

Proficiency testing (PT) can assess the performance of individuals or laboratories, but it’s important to understand how to do it properly.

What Does Your Proficiency Testing (PT) Prove? A Look at Inorganic Analyses, Proficiency Tests, and Contamination and Error, Part I

This column series has been organized into sections based on the infrared (IR) spectroscopy of specific chemical bonds. We have discussed functional groups containing C-H, C-O, and C=O bonds. Here, in the sixth installment of our survey of the IR spectra of polymers, we discuss polymers that contain C-O bonds. The spectra we will examine include polyvinyl alcohol, cellulose, starch, and copolymers that contain C-O bonds such as polyethetherketone, polyurethanes, and polyimides. The unifying theme of all these spectra is that they all contain one or more large C-O stretching peaks between 1300–1000 cm

We covered the spectroscopy of the C-O bond in earlier columns (1–4). In those installments, the functional groups we studied were alcohols and ethers. Recall that the overriding spectral feature of C-O bonds are one or more large C-O stretching peaks between 1300–1000 cm

 (1) (going forward, assume all peak positions are in cm

 units unless otherwise noted). Usually, the C-O stretch is the most intense peak in this wavenumber region.

Recall that alcohols hydrogen bond strongly to each other similar to water (1,2). An example of alcohols hydrogen bonding is seen in Figure 1.

The effect of hydrogen bonding on the spectra of alcohols is that any peaks from O-H stretching and bending motions are unusually broadened, which is illustrated in the spectrum of ethanol seen in Figure 2.

Note in the figure that the O-H stretching peak labeled A at 3492 is approximately 1000 cm

 wide at its base, and the O-H wagging peak labeled E at 667 is approximately 500 cm

 wide at its base. These peaks are significantly broader than the peaks from other functional groups seen in this spectrum. In general, the O-H stretching peaks of alcohols fall at 3350±50, whereas the O-H wag is normally seen at 650±50. The C-O stretching feature of alcohols falls from 1260 to 1000, with the range being determined as to whether the alcohol is primary, secondary, tertiary, or a phenol. The C-O stretching peak of ethyl alcohol, a primary alcohol, is labeled C at 1050, which is in the range expected. A summary of the group wavenumbers for alcohols is seen in Table I.

In addition to alcohols, another functional group containing C-O bonds found in polymers is ethers. The chemical structure of ethers is characterized by two C-O bonds, which is why two ether carbons can be seen in Figure 3.

If both ether carbons are saturated, the ether is said to be saturated. If both ether carbons are aromatic, the ether is aromatic. And finally, if one ether carbon is saturated and the other is aromatic, we have a mixed ether. Note that ethers do not contain O-H bonds. Therefore, they do not hydrogen bond, do not contain broadened peaks, and do not have O-H stretching and bending vibrations like alcohols. In fact, the only useful group wavenumber that ethers have is a C-O stretch, which is typically one or two peaks that fall from 1300 to 1070. A summary of the group wavenumbers for ethers is seen in Table II.

Note in Table II that saturated ethers have one C-O stretching peak from 1140–1070, aromatic ethers have one peak from 1300–1200, and mixed ethers have two C-O stretching peaks—one at 1050–1010 and the other at 1300–1200. The reason mixed ethers have two C-O stretching peaks is that the two ether carbons are bonded to different types of carbon so are chemically different, have different C-O stretching force constants, and hence have different peak positions (5). For mixed ethers then, the aromatic C-O stretching vibration gives the peak from 1300 to 1200, whereas the saturated ether C-O stretching peak falls from 1050 to 1010. Note that for both mixed and aromatic ethers, the aromatic C-O stretch has the same range of 1300–1200. As a general rule, if an ether exhibits a C-O stretching peak from 1300 to 1200, then at least one of the ether carbons is aromatic.

The Infrared (IR) Spectra of O-H Containing Polymers

The way in which polyvinyl alcohol is synthesized is unusual in that rather than being made from an O-H containing monomer, one of the reactants is a polymer. This reaction is shown in Figure 4.

The reactant is polyvinyl acetate, which contains a pendant acetate moiety, which is an ester. Polyvinyl acetate is hydrolyzed with aqueous acid to give polyvinyl alcohol while splitting off a molecule of acetic acid. The IR spectrum of polyvinyl alcohol is seen in Figure 5.

We have the classic broad, intense O-H stretch at 3353, and the C-O stretch of a secondary alcohol at 1094. This particular spectrum cuts off at approximately 700, so the expected O-H wag at ~650 is not visible. Another thing to notice in Figure 5 is the presence of peaks from unreacted acetate, giving us the classic ester “Rule of 3” peaks (6) at 1736, 1251, and 1094. Note how the peak at 1094 is broadened. My interpretation of this peak is that it is an overlap of the alcohol and ester C-O stretching peaks. Despite the ester peaks, polyvinyl alcohol is easily identifiable because it contains an alcohol group, courtesy of the broadened peaks at 3353 and 1094.

The IR Spectra of Polymers Containing Ether Linkages

The polyacetal molecule is made by polymerizing formaldehyde, which has the formula H

-C=O. The C=O bond in formaldehyde is opened up, forming polyacetal, whose structure and spectrum are seen in Figure 6. Note the C-O stretching peak of polyacetal at 1090, as expected for a saturated ether.

The fact that the name of this polymer contains the word ether twice just might make you think that it contains ether linkages, which it does. This material is, in fact, a copolymer made from monomers that form ketone and ether linkages upon the polymer’s formation. We will talk about polymers containing ketones in a future column. The structure and spectrum of PEEK are shown in Figure 7.

This structure contains aromatic ether linkages only, and the aromatic C-O stretching peak falls at 1227 as expected.

Foam rubber, the bouncy stuff that we often sit and jump on, contains a urethane linkage whose structure is seen in Figure 8 (we will cover polyurethanes in a future column). However, the urethane is often copolymerized with a monomer that gives a saturated ether linkage. We know this because the spectrum of a foam rubber sample seen in Figure 8 has a C-O stretching peak at 1050, consistent with the presence of a saturated ether linkage.

Kapton is the trade name for an engineering polymer that contains the imide functional group, which we will cover in a future column. However, note from the structure of Kapton in Figure 9 that it contains aromatic ether linkages as well.

Note that the spectrum of Kapton contains a peak at 1241 assigned as the aromatic C-O stretching peak of its aromatic ether linkages. This peak is in the middle of the range where it should fall, which is from 1300 to 1200 cm

Polymers that Contain Both Alcohol and Ether Groups 

Carbohydrates are biological molecules that contain both alcohol and ether link- ages, which means their C-O stretching regions are complex. The building blocks of carbohydrates are sugar units or monosaccharides. When we build a polymer out of these sugar units, we get a polysaccharide. We covered the spectra of carbohydrates in a previous column (4).

A common polysaccharide is cellulose, which makes up the cell walls of plants and is otherwise known as wood, paper, or cotton. Cellulose is a high polymer of the monosaccharide glucose—the product of photosynthesis. The structure and IR spectrum of cellulose are seen in Figure 10.

The glucose units in cellulose are stitched together by saturated ether linkages. There is so much hydrogen bonding in cellulose that the complex -O-H stretching peak is a broad blob. The C-H stretches are similarly blobby, and the C-O stretching region is best characterized as an envelope with any number of shoulder peaks on top of it.

Another important and well-known polysaccharide is starch. Starch is also a high polymer of glucose, but the saturated ether linkages that connect the glucose molecules in starch have a different orientation than in cellulose, which can be seen by comparing the structure of cellulose in Figure 10 to the structure of starch in Figure 11. Figure 11 also shows the IR spectrum of starch.

One of the maxims about IR spectroscopy is that if two molecules have different chemical structures, they will have different IR spectra (5). Cellulose and starch are similar but not identical molecules; therefore, they have similar but not identical IR spectra. For example, note that the O-H stretching envelopes of cellulose and starch top out at 3350 and 3258, respectively, and that their complex C-O stretching envelopes peak out at 1027 and 998, respectively. Additionally, the shoulders on the C-O stretching envelope in both spectra are at distinct positions, which means that one can readily distinguish between cellulose and starch via IR spectroscopy.

This article was devoted to polymers containing C-O bonds that are not epoxies. We reviewed the spectroscopy and group wavenumbers of alcohols and ethers, two significant functional groups that contain C-O bonds. We examined the spectrum of polyvinyl alcohol, found that its O-H stretching and bending peaks are broadened because of hydrogen bonding, and that its C-O stretching peaks falls as expected. Then, we looked at the spectra of polymers containing ether linkages, and examined the spectra of polyacetal, polyetheretherketone, urethane foam, and Kapton. Lastly, we examined the spectra of polysaccharides that contain both alcohol and ether groups and found that we can use IR spectroscopy to distinguish cellulose from starch.

Column: IR Spectral Interpretation Workshop

An examination of polymers with C-O bonds, focusing on the spectra of polyvinyl alcohol, cellulose, starch, and copolymers.

The Infrared Spectra of Polymers, VI: Polymers With C-O Bonds

We present our annual review of products introduced at Pittcon or during the previous year, broken down by the following categories: atomic spectroscopy, ultraviolet and visible (UV-vis), near-infrared (NIR), infrared (mid-IR), Raman, imaging, nuclear magnetic resonance (NMR), mass spectrometry (MS), accessories, and components.

Between the online Pittcon event of 2021 and the time this review was written, a lot has changed. We all anticipated an in-person Pittcon for 2022; unfortunately, that did not happen because of a surge in Covid cases in the southeastern United States where the event was going to be held. As a result, Pittcon 2022 was converted into a virtual conference. But the fact that one of the “introduction points” for new spectroscopy instruments did not happen live did not stop the launch of exciting new spectroscopic instruments in the past year.

However, it does seem that the Covid pandemic may have reduced the number of recent new product introductions. In our 2021 review, we reported on almost 100 products introduced by more than 50 companies. This year, the number of both companies and products was significantly smaller. Table I lists the companies that responded to our request for information about new products introduced over the past 12 months.

Considering the volume of products usually covered in these reviews, it seems clear that we have the pandemic to blame for the lower number of products we see this year. Over the past two years, engineering teams have had to cope with product development in either a socially distanced or remote way. The ability of such product development teams to function during the pandemic is remarkable, and it especially impressive that some teams were able to introduce several new instruments to the market.

A few live analytical chemistry and spectroscopy conferences were held in the latter half of 2021 as we thought the pandemic was winding down. For those who attended, it was gratifying to speak face-to-face with each other. Some of the products mentioned here and some in our 2021 review were available to see in person at those shows. So far this year, one in-person conference has occurred, the American Chemical Society (ACS) Spring 2022 conference in San Diego, and some of the new equipment mentioned in this year’s review was shown at that event.

Over the last few years, we have seen more analyzer tools entering the market, looking to solve specific questions. Several new products this year are extending this approach to agricultural and environmental applications. Additionally, we noted in the last few years how software is evolving into a true laboratory partner. By integrating more artificial intelligence (AI) and by targeting specific applications, such as microplastics analysis, software is becoming a more powerful tool, especially when directed at one application even when the core hardware technology may be similar to that of previous generations. Even the visualization of data is being used powerfully to extract trends and subtle changes.

In this year’s review, we have taken a somewhat different approach than in years past. The tables contain a significant amount of information about the products, but the text only highlights the unique products or trends. As a result, our discussion does not cover every product in detail. For detailed information regarding the individual products, refer to the tables throughout this review.

Our discussion is broken into four sections: instrumentation, accessories, components, and software. The difference between an accessory and a component is that an accessory is designed to be used with a completed instrument whereas a component can be used to construct an instrument. The tables associated with this article are grouped (when possible) by spectral range and application.

Although some of the new instruments introduced in the past year are more general in their application, many of the new products are geared to special applications. We have seen this trend toward specific task-oriented tools in recent years, as we have noted previously.

Table II contains information on all the atomic products that were submitted. On the instrument side of the “Atomic Spectroscopy” category, Radom Corporation has introduced a new inductively coupled plasma (ICP)–optical emission spectroscopy (OES) instrument that is argon-free, operating with microwave-sustained atmospheric plasma. This device is so small that it is considered portable. Another laboratory-based ICP instrument is the Solation ICP-mass spectrometry (MS) system from Advion Interchim Scientific. The design appears to be good for complex samples, which could broaden the utility of the instrument and minimize sample preparation. Applied Rigaku Technologies, Inc. introduced a new X-ray fluorescence (XRF) instrument.

Agilent Technologies has introduced an environmentally friendly coolant fluid, and Hübner has introduced a new laser source for laser-induced breakdown spectroscopy (LIBS).

In the “UV-vis” category (Table III), several interesting products have been introduced into the market this past year. Although all of them are full instruments, they can be divided by form factor and application.

PerkinElmer and Thermo Fisher Scientific have both introduced laboratory-based UV-vis instruments. Perkin Elmer’s Lambda 365 and the Thermo Fisher Scientific Evolution products are designed for general spectroscopy applications and provide flexibility because they can use various accessories for maximum problem-solving capability. Other instruments, like the Thermo Fisher Scientific Nanodrop, are designed for laboratories where the sample volumes are very small, and the applications are typically customized to the life sciences.

Technobis Crystallization Systems BV has introduced a system, the Crystal16 version 3, with a single application: to measure changes in crystallization and crystallization behavior.

On the other end of the form factor consideration, Ocean Insight and Watersight have introduced small-form-factor devices. The Ocean Insight SR spectrometer continues in the same way as most of Ocean Insight’s products, with a high speed, compact design.

An interesting new entry in the market from Watersight is a self-contained visible and very near-infrared (NIR) device, called Aquaring, that can continuously monitor water quality by collecting spectral data and sending it to the cloud for analysis.

Moving to the “NIR” spectral region (Table IV), we again see two types of devices, dedicated analyzers, and small sensors that can be applied in a variety of situations.

Nanosens AS has introduced three NIR devices, a feed analyzer, a milk analyzer, and an on-line process monitor for industrial use. Norsk Elektro Optikk AS has introduced an NIR hyperspectral imager designed for drone applications that operates in a very wide spectral range from 400 to 2500 nm.

For the smaller NIR engines, there are a number of interesting devices. Ibsen Photonics introduced the Pebble, a vis-NIR device that operates out to 1100 nm and is designed for original equipment manufacturer (OEM) applications. InnoSpectra has extended the range of its NIRScan device, based on the TI digital light processor out to 2150 nm. Manti Spectra has two new offerings: the MantiSpectra SpectraPod and the MantiSpectra OEM solution, both based on the MantiSpectra ChipSense technology and meant for investigation and OEM applications. These four devices illustrate a trend in the NIR world, which is that the development of such devices can be incorporated into monitoring systems to take advantage of the growing NIR applications, and the cloud-based data analysis approach to move the spectroscopy directly to the location of the sample.

In the “mid-infrared (mid-IR)” category (Table V), the traditional suppliers have been busy, and there are several interesting new products. There is a dedicated Silica Analyzer from PerkinElmer, a new general-purpose Fourier-transform infrared (FT-IR) spectrophotometer from Shimadzu, and a nanoscale IR system from Bruker.

The Bruker mid-IR instrument addresses the growing market to gain IR information from samples that are well below the optical diffraction limit. It incorporates atomic force microscopy (AFM)-IR modes, along with modes typically found in scanning probe microscopy.

A particularly interesting device from the company NLIR Aps is the S2050-130 kHz. This device is a mid-IR grating spectrometer that works in the 2.0–5.0 μm (5000–2000 cm

) region of the spectrum. It is designed for fast processes and uses the NLIR upconversion technology and a silicon charge-coupled device (CCD) to provide a unique device that can provide data in the mid-IR region.

Thermo Fisher Scientific has introduced the RaptIR for traditional FT-IR microscope analyses. One could debate whether this device belongs here or in the “Accessories” category because you would still need to buy an FT-IR spectrometer for this device to function effectively. However, it is designed to be a workhorse microscope that one would expect to find in a well-equipped industrial spectroscopy laboratory. It also incorporates task-specific workflows (such as microplastic analysis).

Over the past few years, the growth in Raman spectroscopy has been noted multiple times. This continued growth accelerated this year, as Table VI shows, with some exciting new entries. For laboratory-based research instruments, there are two entries that can expand applications into new areas. IS-Instruments has introduced a deep UV Raman system with excitation at 228 nm, capitalizing on the increased Raman scatter (and fluorescence avoidance) with short wavelength excitation. WITec Gmbh has a new cryogenic Raman imaging microscope.

Elodiz, Ltd. and Ocean Insight have introduced devices that are more geared to field and process applications. The two introductions by Elodiz use multiple laser lines and fiber optic probes, whereas the Ocean Insight product continues in the small footprint vein and is designed to detect Raman shifts from 150 to 3400 cm

Moving on to the “Imaging” category (Table VII) of instruments and components, we have a broad set of products, including several cameras. Greateyes GmbH, Horiba Scientific, Nireos SRL, and Princeton Infrared Technologies, Inc. have all introduced new cameras for imaging applications. EDAX has introduced a new backscatter diffraction detector. Spectrolight Inc. has a new broadband tunable filter that can cover from the UV through to the NIR.

As a complete imaging system, Monstr Sense Technologies has introduced a laser scanning microscope called the Nessie.

The one new product in the nuclear magnetic resonance (NMR) category (Table VIII) is a smaller-footprint NMR spectrometer from JEOL USA.

In the “Mass Spectrometry” category (Table IX), two new devices introduced by Refeyn, Ltd, capitalize on the mass photometry technique developed at Oxford University. One of the new instruments is designed to provide automation to the mass photometry technique, whereas the other is optimized for adeno-associated virus characterization.

In the “Accessories” category, new products have been introduced to simplify sample analysis. REFLEX Analytical Corp. and Nanosens AS have both introduced new cells and cuvettes (Table X). S.T. Japan-Europe GmbH has introduced an improved MicroVice while Specac now provides a heated puck for the Quest. An interesting new product from Specac is the Arrow, which is a disposable silicon ATR accessory.

 as products that would be part of a complete instrument; with that definition, as Table XI indicates, the category includes a disparate set of items.

Armadillo SIA has introduced two new optical fiber products while Trace Matters Scientific has a new flexible ion guide. Sources are one type of component where there have been a number of new entries, including products from Pyroistech S.L, Micro X-Ray, Inc., and Edinburgh Instruments.

Anyone who uses instruments recognizes that software is the human interface to the devices. Typically, discussions about new products tend to minimize the effort to develop instrument control software—especially for tried-and-true analytical techniques—in comparison to the focus on the hardware. Many of the instruments mentioned above have new software platforms in addition to the hardware. Both Ocean Insight and Optiwave Systems have introduced driver and instrument control software for their products (Table XII). We are also including spectral libraries in the software category. S.T. Japan-Europe GmbH has introduced three new libraries, a microplastics IR library, and a Raman microplastics database. They also have introduced a Raman database for psychoactive and illicit drugs.

Many of the products discussed in this review seem to follow trends that we have seen in analytical instruments in recent years. The products are becoming smaller, easier to use, and, in many cases, specific to a particular application rather than for a general purpose. Likewise, tools that are making data easier to acquire or interpret are a major thrust of instrument companies and those approaches will increase the productivity of users in the laboratories. Although we applaud these trends, we hope that the audiences for these products are cognizant of how each device works, what data it should deliver, and how to interpret the data—rather than relying on a “black box” approach. The real danger with such easy-to-use tools lies in relying on the vendor to supply the analytical result; a critical part of integrating any analytical instrument into a laboratory is validation.

With the pandemic waning (we hope), in the coming year we believe that the pace of product introductions will pick up. We look forward to seeing new devices in person at conferences.

If your organization introduces a new product in the coming months, please tell us right away by submitting the 2023 Spectroscopy New Product form, which can be found at 

https://www.spectroscopyonline.com/view/spectroscopy-new-product-review

. We will accept submissions as products are introduced and will include the appropriate products in the 2023 review.

 is a consultant in vibrational spectroscopy and spectroscopy education. She is the past president of both the Coblentz Society and the Society for Applied Spectroscopy, and serves on the 

’s Editorial Advisory Board and is a Product Manager at Thermo Fisher Scientific in Madison, Wisconsin. Direct correspondence to: 

Feature Article

Our annual review of new products for atomic and molecular spectroscopy, including details by category and highlights of overarching trends.

2022 Review of Spectroscopic Instrumentation

This study examines the fluorescence enhancement effects of forsythoside E, one of metabolites of 

, on human serum albumin (HSA) and bovine serum albumin (BSA) under simulated physiological conditions. The increase in protein fluorescence induced by forsythoside E are approximately the same in slightly acidic and neutral solutions, whereas the protein fluorescence intensities barely change in the alkaline solution after adding forsythoside E. The fluorescence increase of proteins caused by forsythoside E are significantly bigger in ethanol than in the other two solvents. The enhancement effects of forsythoside E on protein fluorescence were weakened when Cu

 were pre-added to the solution. Forsythoside E had little effect on the fluorescence of glycosylated BSA (gBSA) but increased the fluorescence of glycosylated HSA (gHSA) in a concentration-dependent manner because BSA was significantly more glycosylated than HSA. These findings can help us to understand the delivering efficiency, absorption, toxicity, and the metabolic process of forsythoside E in vivo.

Serum proteins, the most abundant carrier proteins in plasma, are synthesized in the liver and can play a major role in delivering many endogenous and exogenous ligands by binding with them (1,2).

Human serum albumin (HSA) consists of 585 amino acids with a molecular weight of 66 kDa and contains only one tryptophan (Trp) residue (in this case, Trp 213). HSA, a monomeric globulin, has a heart-shaped stable structure of 17 pairs of disulfide bonds and one free cysteine residue. There are three domains (I, II, III) in HSA that encompass amino acid residues at positions 1–195, 196–383, and 384–585, respectively. Each domain includes two subunits (named A and B) that are connected by a long extended loop. The tertiary structure of HSA is composed of α-helix and a loop, forming pockets of binding sites at domains I–II and II–III to allow various endogenous and exogenous substances to bind strongly (3–6). The calculated net charges for HSA at a pH of 7 are −9, −8, and +2 in domains I, II, and III, respectively (7).

As a homologous protein with HSA, bovine serum albumin (BSA) has a 76% sequence resemblance with HSA and is widely used to study protein–drug interactions because of its well-known protein structure. BSA consists of 583 amino acid residues, including 20 tyrosine (Tyr) residues and two Trp residues (Trp 134 and Trp 213) that are responsible for the intrinsic fluorescence of BSA. Three specific homologous domains (I–III) form its main structure, known as 1–195, 196–383, and 384–583 amino acid residues, each of which is further divided into A and B subdomains. The BSA binding sites for ligands may be located in hydrophobic cavities in subdomains IIA and IIIA, known as Sudlow’s sites I and II, respectively. Trp 134 is situated on the surface of the protein, and Trp 213 is located within a hydrophobic binding pocket of the protein (8–11). The structures of HSA (6) and BSA (2) are shown in Figure S1 (Figures S1–S8 and Tables SI and SII can be accessed through the QR code found at the end of this article).

The binding ability of serum proteins to drugs directly affects the delivery efficiency, distribution, absorption, excretion, stability, toxicity, and metabolism of drugs (1). Studying their mechanisms of action and interactions is important in understanding the pharmacokinetics of drugs. However, the presence of coexisting endogenous or exogenous substances and complicated internal environments often affect the ability of drugs to bind to proteins, which affects the free concentration and efficacy of drugs. Metal ions bind directly to serum proteins to weaken or enhance the binding of drugs to proteins. Cu

 reduced the quenching efficacy of rutin on BSA, increased the binding constant, and changed the binding distance between rutin and BSA that resulted from the formation of metal ion-BSA complex in regard to a combination of static quenching and nonradiative energy transfer (12). Thus, the increasing binding constant of rutin-BSA in the presence of the above ions prolonged the storage period of rutin in blood plasma and weakened its maximum effects (13). Glycation is a spontaneous nonenzymatic aminocarbonyl reaction between reducing sugars and long-lived proteins. Glycation is a major chemical modification in biomolecules and impairs the structural and functional characteristics of native serum proteins (14,15). Thus, the transportation, distribution, and function of drugs are affected strongly by the glycation of serum proteins (16). Differences in the pH environment have proven to have a great influence on the interaction between BSA and the compound (17).

Forsythoside E (18) is one of two metabolites of 

 that has been used as a traditional Chinese medicine to treat inflammation, based on its antioxidant, antibacterial, and antiviral activities (19). The structure of forsythoside E is shown in Figure S2. The interactions of forsythoside E and the two isoforms (forsythoside A and forsythoside I) from 

 with BSA have been investigated in our group (20). Forsythoside E displayed results completely different from those of the other two isoforms; forsythoside E enhanced BSA fluorescence but the two isoformers quenched it. These novel results led us to further study the interactions of forsythoside E with serum albumin. Drugs intended for human use are first studied in simulated human body physiological conditions. Because proteins are denaturalized under specific conditions, they lose their original solubility and their physiological function is weakened. Proteins may behave differently in the body than they do outside the body, and the effect of drugs may be different. This study investigated and compared the interactions between forsythoside E, BSA, and HSA under minimal physiological conditions by using spectroscopic methods.

Forsythoside E (with a purity of 98.6%) was purchased from Must Bio-Technology and was dissolved in purified water to prepare the stock solution. The final concentration of forsythoside E in the spectroscopic measurements was kept at 30 μM unless otherwise specified. BSA, HSA, CuCl

, and glucose were purchased from Solarbio and were made into a stock solution in purified water. The final concentrations of serum proteins in the spectroscopic measurements were kept at 1 μM unless otherwise specified. All other chemicals are analytical grade. All experiments were conducted in a Tris buffer with a pH of 7.4 except where designated.

The fluorescence experiments were performed on a fluorescence spectrophotometer (Fluromax-4, Horiba Scientific). The temperature of the solution in the fluorescence cup was controlled at 27 ± 0.5 °C by a temperature holder, except where designated. The fluorescence between 290 and 500 nm was recorded at an excitation wavelength of 280 nm, with the fixed excitation and emission slit width of 10 nm each. Every time forsythoside E was added into the protein solution, the corresponding spectra were recorded 5 min later (the same protocol was carried out for all titration experiments).

on the enhanced fluorescence of serum, proteins induced by forsythoside E, Cu

 were pre-added into the protein solution. After incubation, forsythoside E was gradually added to the mixture.

The synchronous fluorescence was recorded on the fluorescence spectrophotometer with the initial excitation wavelength of 220 nm and scanned up to 500 nm. The excitation and emission slit widths were fixed at 10 nm.

UV-vis absorption spectra were recorded on a UV-vis spectrophotometer. The spectra were scanned between 200–350 nm. All the absorbance spectra were corrected by the blank.

Glycosylated BSA (gBSA) and glycosylated HSA (gHSA) were prepared following a published method (14) with some changes. Serum proteins (the final concentration of 1 μM) were incubated with glucose (the final concentration of 1.1 mM) in a Tris buffer solution that had a pH of 7.4 and was kept at 37 °C for 10 days, with or without forsythoside E. After being dialyzed with the Tris buffer to remove the unbound glucose, the mixture was then used for spectrum measurement.

Circular dichroism (CD) spectra were measured with a spectropolarimeter, which is equipped with a Quantum Northwest temperature controller.

All data were expressed as means ± standard deviation. Each experiment was performed three times.

The Intrinsic Fluorescence of BSA and HSA in Different Environments 

With the excitation wavelength of 280 nm, BSA and HSA have maximum emission peaks at approximately 348 nm, which is the characteristic emission wavelength of the Trp residue (21). Here, the intrinsic fluorescence of BSA and HSA in different environments was studied, and the fluorescence spectra are shown in Figure 1. The pH values vary greatly in the different organs and tissues in living systems, so the intrinsic fluorescence of BSA and HSA under different pH environments were investigated. The final concentrations of serum proteins were kept at 1 μM. Figure 1a shows that the fluorescence intensity of BSA changed little in a slightly acidic or neutral solution (pH 6.5, 7.0, and 7.4). Fluorescence intensities of BSA in an alkaline solution (pH 8.0, 8.5, and 9.0) were much lower than those in a slightly acidic and neutral solution and decreased gradually with the increase in alkalinity. HSA (Figure 1b) produced similar results. The position of the fluorescence emission peaks barely moved. Under the strongly basic conditions, proteins may denature and hydrolyze to amino acids.

There are many metal ions in living systems that affect the structure and properties of proteins. Cu

 are the most common metal ions that are found in many organs and tissues. Cu

, one of the unique and effective catalysts in biological systems, is the active component in more than 30 enzymes and plays an important role in metabolism of living systems (22). The effects of Cu

 on the intrinsic fluorescence of BSA and HSA were studied by adding metal ions into protein solution. As seen in Figure S3, Cu

 (0.5–10 μM) reduced the fluorescence intensities of BSA and HSA in a dose-dependent manner, and the reduction rate of BSA was higher than that of HSA (Figures 1c and 1d), which was consistent with the reported results (23). It suggested that the two metal ions may interact with BSA and HSA and the combination with the former was stronger than with the latter. Furthermore, the fluorescence of BSA may also be quenched by different concentrations of zinc (24), magnesium, or calcium ions (25).

Fluorescence Enhancement of BSA and HSA Induced by Forsythoside E

The change of intrinsic fluorescence of proteins induced by compounds is a signal to explore the interactions between compounds and proteins. The fluorescence of BSA and HSA was recorded after adding forsythoside E to serum protein solution. The final concentrations of serum proteins were kept at 1 μM in a Tris buffer with a pH of 7.4, and the final concentrations of forsythoside E were 5, 10, 15 . . . 40, 90, and 140 μM, respectively. The results were shown in Figures 2a and 2b. As the concentration of forsythoside E increased, the fluorescence intensities of BSA and HSA gradually increased, indicating that the compound interacted with the serum proteins. At the same time, the emission peak was blue-shifted, which suggested that the combination of the compound with the protein caused the protein peptide chain to fold further, strengthening its hydrophobic structure. As a result, the polarity around Trp decreased and hydrophobicity increased (24). The fluorescence enhancement rate of HSA induced by forsythoside E was much more than that of BSA (Figure 2c).

The Enhancement Effects of Forsythoside E on BSA and HSA Fluorescence Under Different Conditions 

The exogenous or endogenous nature of substances and different physiological environments in living systems may affect how drugs bind with serum albumin and are transported (12,13). The effects of forsythoside E on the intrinsic fluorescence of BSA and HSA were studied under the simulated physiological conditions. The data are listed in Table I.

It was found that the increases in BSA fluorescence induced by forsythoside E were almost the same in slightly acidic and neutral solution (pH 6.5, 7.0, and 7.4). The fluorescence intensities of BSA in alkaline solution (pH 8.5 and 9.0) barely changed after adding forsythoside E to the solution. Similar results were found with HSA. However, the increases of HSA fluorescence that were induced by forsythoside E were much greater than the increases in BSA fluorescence under the same conditions. The fluorescence spectra are shown in Figure S4.

The change of protein fluorescence caused by forsythoside E in the different solvents was studied (Figure S5). The BSA fluorescence intensities increased with the addition of forsythoside E at the final concentration of 30 μM. The increase in BSA fluorescence induced by forsythoside E in the three solvents was the greatest in ethanol. HSA had similar results.

Many metal ions in living systems affect the structures and properties of proteins. Cu

 are the most common metal ions in many organs and tissues. The effects of Cu

 (Figure S7) on the fluorescence enhancement of BSA and HSA induced by forsythoside E were studied by adding metal ions to a protein solution. The results showed that the enhancement effect of forsythoside E on protein fluorescence was weakened after Cu

 was pre-added to the protein solution. The intrinsic fluorescence of BSA barely changed at Cu

 of 30 μM. We speculated several possible reasons. Serum protein has a limited number of binding sites. When Cu

 combined with BSA and induced the conformational changes of BSA. Therefore, it was more difficult for forsythoside E to bind to BSA (12,13). The weakening effect of 

 of 0.5–30 μM. With the increase of Fe

 concentration, the enhancement effect of HSA fluorescence induced by forsythoside E gradually diminished and eventually disappeared. The study is helpful in understanding the effects of metal ions on the transportation, absorption, and release of forsythoside E in vivo.

This study examines the fluorescence enhancement effects of forsythoside E, one of metabolites of Forsythia suspensa, on human serum albumin (HSA) and bovine serum albumin (BSA) under simulated physiological conditions.

May 2022

What Does Your Proficiency Testing (PT) Prove? A Look at Inorganic Analyses, Proficiency Tests, and Contamination and Error, Part I

The Infrared Spectra of Polymers, VI: Polymers With C-O Bonds

2022 Review of Spectroscopic Instrumentation

The Enhancement Effects of Forsythoside E on Serum Albumin Fluorescence Under Simulated Physiological Conditions

Applications of Raman Spectroscopy in Solvent Distillation and Exchange During Early-Phase Chemical Synthesis