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EXERCISES TOPIC 1 EXERCISE 1 In the article of Hafid et al, the authors compared three qualitative methods for the detection of Toxoplasma gondii infection in mice. The aim was to determine sensitivity and specificity of the methods at different timepoints post-infection 1A. WHAT WAS THE SENSITIVITY...

EXERCISES TOPIC 1 EXERCISE 1 In the article of Hafid et al, the authors compared three qualitative methods for the detection of Toxoplasma gondii infection in mice. The aim was to determine sensitivity and specificity of the methods at different timepoints post-infection 1A. WHAT WAS THE SENSITIVITY OF EACH METHOD AT THE DIFFERENT TIME POINTS ANALYZED? Sensitivity refers to the ability of a test to correctly identify individuals who have the disease. It is a measure of how well a test can detect true positive cases among those who are actually infected. Higher sensitivity indicates a test's ability to minimize false negatives, ensuring that individuals with the condition are correctly identified by the diagnostic method. In this case the sensitivity would be a measure of the ability to correctly identify mice that were infected with T. gondii at different time points for each method (PCR, capture ELISA, and immunoblotting) Which test was most sensitive? Time 3-15 hours 18 h 21 h 1-7 days Number of sera tested 25 5 5 35 Capture ELISA 0/25*100 = 0% 0/5*100 = 0% 0/5*100 = 0% 35/35*100 = 100% Immunoblotting 0/25*100 = 0% 0/5*100 = 0% 0/5*100 = 0% 35/35*100 = 100% PCR 0/25*100 = 0% 3/5*100 = 60% 5/5*100 = 100% 35/35*100 = 100% Conclusion PCR had an earlier and higher sensitivity compared to capture ELISA and immunoblotting in the experimental model of T. gondii infection in mice. PCR detected parasite DNA as early as 18 hours post-infection, while capture ELISA and immunoblotting were positive only at 24 hours or later. 1B. WHAT WAS THE SPECIFICITY OF EACH OF THE THREE METHODS? The specificity of a diagnostic test is the ability of the test to correctly identify individuals without the condition or disease as true negatives. 13 Control information: Sera from five uninfected mice were used as negative controls. Implication: If these control five mice were truly uninfected (true negative) and all diagnostic tests (capture ELISA, immunoblotting and PCR) yielded negative results for these control mice, it would indicate a high specificity for each method. Specificity calculation: Assuming that the control mice were indeed uninfected and all tests were negative for them, then: 𝑇𝑟𝑢𝑒 𝑛𝑒𝑔𝑎𝑡𝑖𝑣𝑒𝑠 𝑆𝑝𝑒𝑐𝑖𝑓𝑖𝑐𝑖𝑡𝑦 = × 100 𝑇𝑟𝑢𝑒 𝑛𝑒𝑎𝑡𝑖𝑣𝑒𝑠 + 𝐹𝑎𝑙𝑠𝑒 𝑝𝑜𝑠𝑖𝑡𝑖𝑣𝑒𝑠 In this case, false positives would be 0, and true negatives would be the number (5) of control mice. 𝑆𝑝𝑒𝑐𝑖𝑓𝑖𝑐𝑖𝑡𝑦 = 5 × 100 = 100% 5+0 That gives a specificity of 100% This implies that the tests were specific in correctly identifying non-infected mice. EXERCISE 2 In the article of Tassignon et al, the authors compare four different methods to detect T-cell mediated immune responses in human subjects. 2A. OUTLINE THE BASIC PRINCIPLE OF THE FOUR DIFFERENT METHODS Enzyme-linked immunosorbent assay (ELISA) Principle ELISA is a plate-based assay technique used for detecting and quantifying substances, in this case, IFN-gamma. It involves the use of antibodies and enzymes to measure the concentration of a specific antigen. Steps 1. Coating: A microplate is coated with an antigen (in this case, likely IFN-gamma) or an antibody specific to the cytokine of interest. The antigen or antibody is immobilized on the surface of the plate. 2. Blocking: Any remaining surface on the microplate is blocked to prevent nonspecific binding. Common blocking agents include bovine serum albumin (BSA) or non-fat milk. 3. Incubation with Samples: Samples containing the cytokine of interest are added to the plate. If the antigen is coated, the samples may contain antibodies against the cytokine. If an antibody is coated, the samples may contain the cytokine itself. 4. Binding: If the cytokine is present in the samples, it binds to the coated antibody or antigen on the plate, forming an immune complex. 5. Washing: The plate is washed to remove unbound substances. This step helps reduce background noise and ensures specificity. 6. Enzyme-Conjugated Antibodies: An enzyme-linked antibody specific to the cytokine is added. This secondary antibody binds to the cytokine if it is part of the immune complex. Common enzymes used are horseradish peroxidase (HRP) or alkaline phosphatase. 7. Substrate Addition: A substrate specific to the enzyme is added. The enzyme catalyzes a reaction with the substrate, producing a detectable signal. Common substrates include chromogenic substrates (yielding color changes) or chemiluminescent substrates (emitting light). 8. Signal Detection: The intensity of the signal is proportional to the amount of cytokine present in the sample. The reaction is stopped, and the absorbance or luminescence is measured using a spectrophotometer or a luminometer. 9. Data Analysis: The measured signal is compared to a standard curve generated using known concentrations of the cytokine. This allows for the quantification of the cytokine concentration in the original sample. Application in the Study In the study, ELISA was used to measure the bulk amount of IFN-gamma secreted in the culture supernatant. 14 EnzymeLinked Immunospot Assay (ELISPOT) Intra-Cellular Cytokine Detection (ICCD) Quantitative Real-Time Reverse Transcription Polymerase Chain Reaction (q-PCR) ELISPOT is a technique for detecting and quantifying the frequency of cytokinesecreting cells. It involves capturing the secreted cytokines on a solid support, forming spots that can be counted. Steps 1. Cell capture: Cells, usually peripheral blood mononuclear cells (PBMCs), are isolated from the sample of interest. These cells are then added to a microtiter plate that has been pre-coated with a capture antibody specific for the cytokine of interest. The plate is incubated to allow the cells to settle and adhere to the plate, with each well capturing the secretions of an individual cell. 2. Stimulation: Cells are stimulated with specific antigens or mitogens to induce cytokine production. In the context of the study you provided, the cells are likely stimulated with tetanus toxoid (TT) to elicit an immune response. 3. Cytokine Secretion: Activated cells secrete cytokines such as interferon-gamma (IFN-g) into the surrounding environment. 4. Detection: Unbound cells are removed by washing, leaving behind the captured cytokines on the plate. A detection antibody specific for the cytokine is added. This antibody is typically conjugated to an enzyme (e.g., alkaline phosphatase or horseradish peroxidase). 5. Enzyme Substrate Reaction: A substrate for the enzyme is then added. If the cytokine is present (indicating a cytokine-secreting cell), the enzyme catalyzes a reaction that produces a visible spot or "dot" at the location of the cytokinesecreting cell. 6. Spot Enumeration: The spots represent individual cells that have secreted the cytokine of interest. The spots can be counted, and the number of spots correlates with the frequency of cytokine-secreting cells in the original sample. ICCD involves the detection of cytokines within individual cells by using flow cytometry. Cells are stained with antibodies against specific cytokines, allowing the identification of cytokine-producing cell populations. Steps 1. Cell Stimulation: Peripheral blood mononuclear cells (PBMCs) or other cell populations are isolated from the sample. Cells are typically stimulated with specific antigens, mitogens, or other activating agents to induce cytokine production. In the study you provided, the cells may be stimulated with tetanus toxoid (TT) to trigger an immune response. 2. Cell Fixation and Permeabilization: Following stimulation, cells are fixed and permeabilized to allow antibodies to penetrate the cell membrane and access intracellular compartments. Fixation locks the cellular structures in place, and permeabilization allows antibodies to reach the cytokines inside the cells. 3. Antibody Staining: Fluorescently labeled antibodies specific to the cytokine of interest are added to the fixed and permeabilized cells. In the case of the study, antibodies against interferon-gamma (IFN-g) are likely used. 4. Flow Cytometry Analysis: The stained cells are passed through a flow cytometer, a specialized instrument that can detect and quantify fluorescent signals. As cells pass through the cytometer, lasers excite the fluorochromes attached to the antibodies, and detectors capture the emitted fluorescence. 5. Identification and Enumeration: The flow cytometer analyzes the fluorescent signals, allowing for the identification and enumeration of cells expressing the intracellular cytokine (e.g., IFN-g). Different subpopulations of cells, such as CD4+ T cells, CD8+ T cells, etc., can be distinguished based on additional surface marker staining. q-PCR is a molecular biology technique used to quantify the amount of specific RNA molecules in a sample. It involves reverse transcription of RNA into cDNA, followed by PCR amplification with real-time monitoring. Steps 1. RNA Extraction: Total RNA is extracted from the biological sample, often using specialized kits or methods that preserve the integrity of the RNA. 2. Reverse Transcription (cDNA Synthesis): The extracted RNA is reverse transcribed into complementary DNA (cDNA) using a reverse transcriptase enzyme. This step converts RNA into a stable DNA form, allowing for subsequent amplification. 3. Primer Design: Specific primers are designed to target the gene or RNA of interest. Primers are short DNA sequences that flank the region to be amplified. ELISPOT in this study enumerated the number of cells secreting IFN-gamma in response to the antigen. ICCD in this study focused on detecting intracellular IFN-gamma in CD4+ T cells, providing a more detailed analysis of the immune response. q-PCR in this study assessed the levels of IFNgamma mRNA, providing information about the transcriptional activity related to IFN-gamma. 15 One primer binds to the forward (sense) sequence, and the other primer binds to the reverse (antisense) sequence of the target gene. 4. Polymerase Chain Reaction (PCR): The q-PCR reaction mixture includes the cDNA template, primers, DNA polymerase, and fluorescent DNA-binding dyes or probes. The reaction goes through multiple cycles of denaturation, annealing, and extension, resulting in the exponential amplification of the target cDNA. 5. Fluorescent Detection: As the PCR progresses, the fluorescent signal increases proportionally to the amount of amplified DNA. The fluorescence can be monitored in real-time during each PCR cycle using a specialized instrument called a q-PCR machine. 6. Threshold Cycle (Ct): The cycle number at which the fluorescence signal crosses a defined threshold is called the threshold cycle (Ct). Ct values are inversely proportional to the initial amount of target RNA in the sample—the fewer cycles needed to reach the threshold, the higher the initial RNA concentration. 7. Standard Curve and Absolute Quantification: A standard curve is generated using known concentrations of a reference RNA or synthetic cDNA. The Ct values of the unknown samples are then compared to the standard curve to quantify the initial amount of the target RNA in the original sample. 8. Data Analysis: The q-PCR machine software analyzes the data, providing information on the expression level of the target gene in the sample. Normalization using internal reference genes helps correct for variations in RNA input and reverse transcription efficiency. 2B. CLASSIFY THE METHOD AS CELLULAR OR MOLECULAR. ARE THE METHODS QUANTITATIVE OR QUALITATIVE? Method ELISA Cellular/molecular ELISA is a molecular technique because it relies on the detection of molecules (usually proteins) using antibodies. ELISPOT ELISPOT is primarily cellular, as it detects individual cells secreting a particular cytokine. However, it also involves molecular components in the detection process. ICCD is primarily a cellular method as it assesses cytokine production within specific cell populations. ICCD q-PCR q-PCR is a molecular method that involves the amplification and quantification of nucleic acids (RNA in this case). Quantitative/qualitative ELISA is quantitative because it measures the concentration of a specific protein. This is achieved by comparing the signal from the sample to a standard curve generated from known concentrations. ELISPOT is quantitative because it counts the number of spots, representing individual cells producing a cytokine. ICCD is quantitative because it measures the percentage of cells within a population that produce a particular cytokine. q-PCR is quantitative, providing precise measurements of the amount of specific RNA in a sample. 2C. ANALYZE THE SENSITIVITIES OF THE METHODS FOR BOTH TIMEPOINTS (BEFORE AND AFTER BOOSTER VACCINATION). WHICH OF THE FOUR METHODS SHOULD BE PREFERABLY USED TO ACHIEVE OPTIMAL SENSITIVITY AND WHY? 16 Time Before booster vaccination After booster vaccination ELISA 57% ELISpot 93% ICCD 50% RT-qPCR 71% 43% 29% 79% 0% Before booster vaccination, ELISPOT demonstrated the highest sensitivity (93%), followed by q-PCR (71%), ELISA (57%), and ICCD (50%). After the booster vaccination at day +7, ICCD showed the highest sensitivity (79%), followed by ELISA (43%), ELISPOT (29%), and q-PCR (0%). Preference for optimal sensitivity: Before Booster Vaccination: ELISPOT showed the highest sensitivity, making it preferable for assessing the memory response before in vivo challenge with TT. After Booster Vaccination (Day +7): ICCD demonstrated the highest sensitivity, making it preferable for visualizing the vaccine effects at the cellular level after in vivo challenge with TT. Reasoning: ELISPOT is highly sensitive in detecting the memory response before vaccination, possibly due to its ability to capture low levels of cytokine secretion from individual cells. ICCD, which measures cell frequencies and captures the cellular response at a specific time point, showed high sensitivity after booster vaccination, making it suitable for assessing the cellular effects. In conclusion, the choice of the optimal method depends on the specific goal of the analysis— ELISPOT for memory response assessment before vaccination and ICCD for visualizing cellular effects after booster vaccination. EXERCISE 3 A study aims to compare two methods for detection for glucose in serum. The results of six measurements are given below: Measurements (in mmoL/L) Replicate number 1 2 3 4 5 6 Method A 2,5 2,6 2,3 2,3 2,4 2,5 Method B 2,8 3,0 3,1 2,4 2,1 2,2 3A. WHICH OF THE TWO METHODS IS MORE PRECISE? To determine which method is more precise, you can calculate the standard deviation for each method and compare them. The standard deviation is a measure of the dispersion of values in a set of data. A smaller standard deviation indicates greater precision. Method A Formula to use: 17 Σ(𝑥A − 𝑥̅ )E 𝑆< = = 𝑛−1 First calculate the mean (x̄ ) for method A: (2,5 + 2,6 + 2,3 + 2,3 + 2,4 + 2,5) 𝑚𝑚𝑜𝑙 𝑥̅ = = 2,433 6 𝐿 Calculate the standard deviation (SD) for method A: (2,5 − 2,433)E + (2,6 − 2,433)E + (2,3 − 2,433)E + (2,3 − 2,433)E + (2,4 − 2,433)E + (2,5 − 2,433)E 𝑆𝐷 = = 6−1 𝑆𝐷 = 0,1211 Find the coefficient of variation (CV): 𝐶𝑉 (%) = 𝐶𝑉 (%) = P 𝑆𝐷 × 100 𝑥̅ 0,1211 Q × 100 = 4,9773% 2,433 Method B: Calculate the mean (x̄ ) for method B: (2,8 + 3,0 + 3,1 + 2,4 + 2,1 + 2,2) 𝑥̅ = = 2,6 𝑚𝑚𝑜𝑙/𝐿 6 Calculate the standard deviation (SD) for method B: (2,8 − 2,6)E + (3,0 − 2,6)E + (3,1 − 2,6)E + (2,4 − 2,6)E + (2,1 − 2,6)E + (2,2 − 2,6)E 𝑆𝐷 = = 6−1 𝑆𝐷 = 0,4242 Find the coefficient of variation (CV): 𝐶𝑉 (%) = 𝐶𝑉 (%) = P 𝑆𝐷 × 100 𝑥̅ 0,4242 Q × 100 = 16,32% 2,6 Conclusion In terms of precision, Method A appears to be more precise because it has a smaller standard deviation (0,12), indicating less variability in the measured values. Method B, with a larger standard deviation (0,42), shows more variability among its measurements, suggesting lower precision compared to Method A. 18 3B. WHICH OF THE TWO METHODS IS MORE ACCURATE AT THE 95% INTERVAL? EXERCISE 4 A group of researchers has developed the “Albumin Tester”, a portable testing device for patients suffering hypertension. The device could be used to monitor the levels of albumin in urine, to help detecting early occurrence of kidney disease. As part of the assessment of the device’s performance, the researchers have measured the concentration of albumin in six replicates from a urine sample. A desktop device was used to perform control measurements. For both devices, six blank measurements were also performed using a saline solution. The results are summarized in the following table: Albumin tester Blank Urine sample Control instrument Blank Urine sample 1 Measurements (in µg/mL) Replicate number 2 3 4 5 6 0,5 205,1 0,4 213,2 0,2 191,4 0,3 196,4 0,4 210,9 0,5 206,3 0,2 199,1 0,2 202,2 0,1 198,8 0,3 202,3 0,3 202,2 0,1 198,3 Based on the results of these measurements, calculate and compare the instruments in terms of: 4A. THE LOWER LIMIT OF DETECTION (LLOD) AND THE LOWER LIMIT OF QUANTIFICATION (LLOQ) Lower Limit of Detection (LLOD): The LLOD is the lowest concentration of an analyte that can be reliably detected but not necessarily quantified. It is typically calculated as three times the standard deviation of the blank divided by the slope of the calibration curve. Lower Limit of Quantification (LLOQ): The LLOQ is the lowest concentration of an analyte that can be 19 reliably quantified with acceptable precision and accuracy. It is often calculated as ten times the standard deviation of the blank divided by the slope of the calibration curve. For the Albumin tester: LLOD Calculate the mean (x̄ ) of blank: 𝑥̅ = 0,5 + 0,4 + 0,2 + 0,3 + 0,4 + 0,5 6 = 0,383 Calculate the standard deviation (SD): (2,8 − 2,6)E + (3,0 − 2,6)E + (3,1 − 2,6)E + (2,4 − 2,6)E + (2,1 − 2,6)E + (2,2 − 2,6)E 𝑆𝐷 = = 6−1 𝑆𝐷 = 0,117 𝑳𝑳𝑶𝑫 = 𝟎, 𝟑𝟖𝟑 + 𝟑 ∗ 𝟎, 𝟏𝟏𝟕 = 𝟎, 𝟕𝟑𝟒 LLOQ: Calculate the mean (x̄ ) of blank: 𝑥̅ = 0,5 + 0,4 + 0,2 + 0,3 + 0,4 + 0,5 6 = 0,383 Calculate the standard deviation (SD): (2,8 − 2,6)E + (3,0 − 2,6)E + (3,1 − 2,6)E + (2,4 − 2,6)E + (2,1 − 2,6)E + (2,2 − 2,6)E 𝑆𝐷 = = 6−1 𝑆𝐷 = 0,117 𝑳𝑳𝑶𝑸 = 𝟎, 𝟑𝟖𝟑 + 𝟏𝟎 ∗ 𝟎, 𝟏𝟏𝟕 = 𝟏, 𝟓𝟓𝟑 For the control instrument LLOD: Calculate the mean (x̄ ) of blank: 𝑥̅ = 0,2 + 0,2 + 0,1 + 0,3 + 0,3 + 0,1 6 = 0,2 Calculate the standard deviation (SD): (0,2 − 0,2)E + (0,2 − 0,2)E + (0,1 − 0,2)E + (0,3 − 0,2)E + (0,3 − 0,2)E + (0,1 − 0,2)E 𝑆𝐷 = = 6−1 𝑆𝐷 = 0,0894 𝑳𝑳𝑶𝑫 = 𝟎, 𝟐 + 𝟑 ∗ 𝟎, 𝟎𝟖𝟗𝟒 = 𝟎, 𝟒𝟔𝟖𝟐 20 LLOQ: Calculate the mean (x̄ ) of blank: 𝑥̅ = 0,2 + 0,2 + 0,1 + 0,3 + 0,3 + 0,1 6 = 0,2 Calculate the standard deviation (SD): (0,2 − 0,2)E + (0,2 − 0,2)E + (0,1 − 0,2)E + (0,3 − 0,2)E + (0,3 − 0,2)E + (0,1 − 0,2)E 𝑆𝐷 = = 6−1 𝑆𝐷 = 0,0894 𝑳𝑳𝑶𝑸 = 𝟎, 𝟐 + 𝟏𝟎 ∗ 𝟎, 𝟎𝟖𝟗𝟒 = 𝟏, 𝟎𝟗𝟒𝟎 4B. PRECISION For the Albumin tester: First calculate the mean (x̄ ) for urine sample: (205,1 + 213,2 + 191,4 + 196,4 + 210,9 + 206,3) 𝑥̅ = = 203,883 6 Calculate the standard deviation (SD): 𝑆𝐷 = = (205,1 − 203,883)E + (213,2 − 203,883)E + (191,4 − 203,883)E + (196,4 − 203,883)E + (210,9 − 203,883)E + (206,3 − 203,883)E 6−1 𝑆𝐷 = 8,428 Find the coefficient of variation (CV): 𝐶𝑉 (%) = P 8,428 Q × 100 = 4,13% 203,883 For the control instrument First calculate the mean (x̄ ) for urine sample: (199,1 + 202,2 + 198,8 + 202,3 + 202,2 + 198,3) 𝑥̅ = = 200,483 6 Calculate the standard deviation (SD): 𝑆𝐷 = = (199,1 − 200,483)E + (202,2 − 200,483)E + (198,8 − 200,483)E + (202,3 − 200,483)E + (202,2 − 200,483)E + (198,3 − 200,483)E 6−1 𝑆𝐷 = 1,934 Find the coefficient of variation (CV): 𝐶𝑉 (%) = P 1,934 Q × 100 = 0,9646% 200,483 21 4C. ACCURACY AT THE 95% INTERVAL For the Albumin tester: Degrees of freedom = n-1 Degree of freedom = 6-1 = 5 Look at Student’s t values for the desired confidence interval For 95% confidence interval is t = 2,571 𝐶𝑜𝑛𝑓𝑖𝑑𝑒𝑛𝑐𝑒 𝑖𝑛𝑡𝑒𝑟𝑣𝑎𝑙 = 𝑥̅ ± 𝐶𝑜𝑛𝑓𝑖𝑑𝑒𝑛𝑐𝑒 𝑖𝑛𝑡𝑒𝑟𝑣𝑎𝑙 = 203,883 ± 𝑡 ∗ 𝑆𝐷 √𝑛 2,571 ∗ 8,428 √6 𝑪𝒐𝒏𝒇𝒊𝒅𝒆𝒏𝒄𝒆 𝒊𝒏𝒕𝒆𝒓𝒗𝒂𝒍 = 𝟐𝟎𝟑, 𝟖𝟖𝟑 ± 𝟖, 𝟖𝟒𝟔 For the control instrument Degree of freedom = 6-1 = 5 For 95% confidence interval is t = 2,571 𝐶𝑜𝑛𝑓𝑖𝑑𝑒𝑛𝑐𝑒 𝑖𝑛𝑡𝑒𝑟𝑣𝑎𝑙 = 𝑥̅ ± 𝐶𝑜𝑛𝑓𝑖𝑑𝑒𝑛𝑐𝑒 𝑖𝑛𝑡𝑒𝑟𝑣𝑎𝑙 = 200,483 ± 𝑡 ∗ 𝑆𝐷 √𝑛 2,571 ∗ 1,934 √6 𝑪𝒐𝒏𝒇𝒊𝒅𝒆𝒏𝒄𝒆 𝒊𝒏𝒕𝒆𝒓𝒗𝒂𝒍 = 𝟐𝟎𝟎, 𝟒𝟖𝟑 ± 𝟐, 𝟎𝟐𝟗𝟗 EXERCISE 5 Read the application note from the NanoVue spectrophotometer. 5A. WHAT ARE THE WORKING RANGES OF THE INSTRUMENT FOR EACH OF THE PROTEIN ASSAY METHODS? 22 5B. WHAT COULD BE THE REASON WHY THE NANOVUE HAS A SMALLER LLOQ THAN THE NANODROP IN THE BIURET ASSAY? NanoVue may have a higher sensitivity to changes in absorbance at lower concentrations of proteins. This increased sensitivity allows for accurate measurements at concentrations lower than those achievable by NanoDrop. 5C. HOW IS THE ANALYTICAL SENSITIVITY OF THE NANOVUE AS COMPARED TO THE NANODROP INSTRUMENT? PROVIDE AN ANSWER FOR EACH OF THE FIVE ASSAYS REPORTED IN THE DOCUMENT. The analytical sensitivity is related to the coefficient of the slope on the curve, meaning how steep or flat the curves are on concentration-absorbance graphs. Steeper curves indicate higher sensitivity, allowing for precise measurements at lower concentrations. o Low analytical sensitivity = flat curves o High analytical sensitivity = steep curves Graphs in spectrophotometry: in spectrophotometry, a graph typically represents the relationship between the concentration of a substance (analyte) and the measured absorbance. This relationship is often depicted as a curve on a graph. Steepness of curves: the steepness or slope of the curve on the graph indicates how rapidly the absorbance changes with respect to changes in concentration. Steeper curves suggest a more rapid increase in absorbance for each incremental change in concentration. Analytical sensitivity: analytical sensitivity refers to the ability of the instrument to detect and respond to changes in concentration. A more sensitive instrument can effectively capture small variations in absorbance, especially at lower concentrations. o High analytical sensitivity: a spectrophotometer with a steeper curve is considered to have high analytical sensitivity. This means that even small changes in concentration result in a noticeable and significant change in absorbance. It can accurately measure low concentrations of analytes with precision. o Low analytical sensitivity: a flatter curve indicates lower analytical sensitivity. In this case, larger changes in concentration are needed to produce noticeable differences in absorbance. Such instruments may be less effective at quantifying lower concentrations with precision. Bradford NanoVue and NanoDrop are very close to each other - not a significant difference in sensitivity 23 Micro BCA NanoVue is slightly steeper = a bit more analytical sensitivity Lowry NanoVue has a steeper slope (going up to approximately 2.5, while NanoDrop only goes up to approximately 1) - Thus, higher sensitivity with NanoVue. 24 Biuret assay NanoVue is slightly steeper = a bit more analytical sensitivity Direct UV measurement NanoVue is slightly steeper = a bit more analytical sensitivity 25 EXERCISE 6 A researcher wants to evaluate the performance of a new microliter-based spectrophotometer in comparison to the well-established NanoDrop from Thermo Scientific. To do this, the researcher performs measurements on a set of diluted protein standards using a Bradford assay. After performing absorbance measurements at 595 nm, the following average values are obtained: The following figure is the graphical representation of the data: The researcher performs some calculations to determine the lower and upper limits of quantification. The lower limits of quantification (LLOQ) were 50 µg/mL for the NanoDrop and 125 µg/mL for the new instrument, while the upper limits were the same for both instruments (1500 µg/mL) 6A. FOR BOTH INSTRUMENTS, INDICATE THE WORKING RANGES OF PROTEIN CONCENTRATION THAT THEY CAN MEASURE USING THE BRADFORD ASSAY The working range is defined as from the lower limits of quantification (LLOQ) to the upper limits of detection (ULOQ) The working range for Nanodrop is 50 µg/mL to 1500 µg/mL The working range for the new instrument is 125 µg/mL to 1500 µg/mL 26 6B. USING THE REGRESSION EQUATIONS IN THE GRAPH, ANALYZE AND COMPARE THE ANALYTICAL SENSITIVITY OF THE INSTRUMENTS The analytical sensitivity is the coefficient of the slope. For Nanodrop the analytical sensitivity is 0.0004 while the analytical sensitivity for the new instrument is 0.0002. That means that Nanodrop is more sensitive than the new instrument because it can both detect a smaller sample and a more precise result, than the new instrument. 6C. IF THE PRICE OF THE NEW INSTRUMENT IS COMPARABLE TO THE NANODROP, WHICH INSTRUMENT WOULD YOU RECOMMEND THE RESEARCHER PURCHASE? JUSTIFY YOUR ANSWER If the price is comparable to NanoDrop, then they should keep the NanoDrop because its more sensitive and with a larger working range than the new instrument. The new instrument would have to be a lot cheaper to compensate for the poorer performance to make any argument for buying that over NanoDrop. EXERCISE 7 A researcher would like to compare the performance of a new microliter-based spectrophotometer against the well-established NanoDrop from Thermo Scientific. For that purpose, a BCA protein quantification assay was set up. The following measurements were obtained after performing a series of measurements from known albumin standards: 7A. FOR EACH DATASET PLOT THE STANDARD CURVES AND PERFORM A LINEAR REGRESSION USING A SPREADSHEET PROGRAM (E.G. MS EXCEL) 7B. ACCORDING TO THE STANDARD CURVE, WHAT IS THE ANALYTICAL SENSITIVITY OF THE NEW INSTRUMENT? IS THE ANALYTICAL SENSITIVITY OF THE NEW INSTRUMENT BETTER OR WORSE, AS COMPARED TO THAT OF THE NANODROP? 7C. OUTLINE WHICH PROCEDURE WOULD YOU FOLLOW TO QUANTIFY THE LOWER LIMIT OF DETECTION (LLOD) OF THE INSTRUMENTS. 27