Everything below concerns Resolution. We keep the language plain, cite what the science says, and separate well-supported claims from open questions.
Last reviewed on 2025-11-26. Where a claim depends on a specific study, the study is described rather than over-claimed.
Routine HPLC testing compares a sample result with a calibration curve prepared from known reference standards. Peak area or peak height is plotted against concentration, and the curve is used to estimate unknown amounts. Retention time supports tentative identification when compared with a standard, though mass spectrometry or another confirmatory method may be needed for definitive identification. Pre-run checks verify repeatability, resolution, and peak symmetry before sample analysis. Limits of detection and quantification describe the smallest amounts that can be reliably observed or measured. Sample preparation, filtration, and degassing help prevent column damage and inconsistent results.
High-performance liquid chromatography is an analytical technique that separates components in a liquid sample. A pump moves a liquid mobile phase through a column packed with a solid stationary phase. Compounds interact differently with both phases and travel at different rates, leaving the column at distinct retention times. A detector records these arrivals as peaks on a chromatogram. The resulting pattern supports identification and quantification of substances in mixtures. Modern instruments use high pressure to force solvent through small particles, which improves speed and resolution compared with older low-pressure liquid chromatography methods.
Separation in HPLC depends on the chemistry of the stationary phase, the composition of the mobile phase, and the physical properties of the column. Reverse-phase separations use a nonpolar stationary phase and a polar mobile phase, and they are common for many organic compounds. Ion-exchange, size-exclusion, and normal-phase modes serve other classes of analytes. Gradient elution changes solvent strength over time, while isocratic elution holds it constant. Flow rate, temperature, particle size, and column length all influence peak shape and resolution. Detection may use ultraviolet absorbance, fluorescence, refractive index, or mass spectrometry, depending on the analyte and the required sensitivity.
Validation demonstrates that a method is suitable for its intended use. Typical performance characteristics include accuracy, precision, specificity, linearity, range, limit of detection, limit of quantitation, and robustness. Regulators and standards organizations provide frameworks, but specific requirements depend on the application and jurisdiction. System suitability tests are run before sample analysis to confirm resolution, peak symmetry, retention time repeatability, and sensitivity. A validated method is not permanently fixed; changes may require partial or full revalidation.
Routine HPLC testing depends on controlled reagents, calibrated instruments, and documented procedures. Columns degrade over time, so retention times and peak shapes are monitored for drift. Mobile phases are filtered and degassed to prevent pump damage and detector noise. Reference standards must be traceable and stored under suitable conditions. Data handling systems record injections, calculations, and audit trails. Quality control samples interspersed with unknowns help detect errors during a run.
Developing an HPLC method begins with defining the purpose, such as quantifying a main component, measuring impurities, or confirming identity. Analysts select separation mode, column, mobile phase, detection, and sample preparation based on analyte properties and matrix. Experiments vary solvent strength, pH, buffer type, and temperature to achieve resolution between critical peaks. The goal is a robust method that produces reliable results across instruments and operators. Method development often involves trial runs and statistical optimization.
| Property | Value | Notes |
|---|---|---|
| Common abbreviation | HPLC | High-performance liquid chromatography |
| Separation basis | Differential partitioning | Between liquid mobile phase and solid stationary phase |
| Common mode | Reverse phase | Nonpolar column, polar mobile phase |
| Typical detector | UV-Vis absorbance | Widely used for compounds with chromophores |
| Typical column particle size | 2–5 µm | Smaller particles can improve resolution |
High-performance liquid chromatography is an analytical technique that separates components in a liquid sample by passing them through a packed column under pressure. A pump delivers a mobile phase at a controlled flow rate, and an injector introduces the sample into the stream. Differences in how analytes partition between the mobile phase and the stationary phase cause them to exit the column at different times. Detection then records a signal proportional to the amount of each separated substance. The resulting chromatogram provides retention times and peak areas for identification and quantification.
Instrumentation includes a solvent delivery system, an autosampler, a column oven, and one or more detectors. Reversed-phase columns with chemically modified silica are widely used, but normal-phase, ion-exchange, size-exclusion, and affinity modes exist for specific separations. Detectors may rely on ultraviolet absorbance, fluorescence, refractive index, or mass spectrometry. Column temperature, mobile phase composition, and flow rate are adjusted to improve resolution. System pressure is monitored because rising pressure can indicate column blockage or deteriorating packing.
Quality control for HPLC testing combines scheduled checks, documented procedures, and review of results. Before sample analysis, system suitability testing confirms that the instrument, column, and method meet predefined criteria. Common criteria include resolution between critical peaks, retention time precision, peak tailing, and theoretical plate count. Failure triggers investigation before results are reported. Records link raw data, calculations, instrument logs, and analyst identity to each batch, supporting audits and repeat analysis.
Method validation evaluates accuracy, precision, specificity, linearity, range, detection limit, quantitation limit, and robustness. Regulatory guidance for pharmaceuticals, foods, and environmental testing defines expected documentation and acceptance criteria. Verification confirms that a validated method works in a specific laboratory with its own instruments and reagents. Calibration curves use reference standards with known purity and traceability, while measurement uncertainty is estimated from validation data, control charts, and collaborative studies. The scope of validation depends on the method's intended use.
Routine quality control monitors retention time shifts, baseline noise, system pressure, and peak shape. Trends can reveal column aging, mobile phase preparation errors, detector drift, or sample degradation. Corrective actions may include replacing the column, preparing fresh mobile phase, or recalibrating the detector. Stability testing often uses HPLC to measure parent compound loss and degradation product formation. Open questions remain about how accelerated stability results extrapolate to long-term storage under varied conditions.
Method validation demonstrates that an analytical procedure is suitable for its intended purpose. Typical validation characteristics include accuracy, precision, specificity, linearity, range, limit of detection, limit of quantitation, and robustness. Regulatory guidance from bodies such as the International Council for Harmonisation and the United States Pharmacopeia outlines expectations, though specific criteria depend on the product and method. System suitability tests are run before sample analysis to confirm resolution, peak symmetry, column efficiency, and injection repeatability. Failure of these checks can invalidate a batch of measurements.
Practical HPLC testing depends on careful sample preparation and instrument maintenance. Samples may require filtration, dilution, pH adjustment, or extraction to avoid column damage and matrix interference. Mobile phases are degassed and filtered, and columns are equilibrated before injection. Common problems include peak tailing, baseline drift, ghost peaks, carryover, and co-elution of analytes. Documentation of instrument logs, calibration records, and electronic audit trails supports data integrity and traceability. Ongoing training and routine maintenance help reduce variability between analysts and laboratories.
The cellular response in signal transduction cascades involves alteration of the expression of effector genes or activation/inhibition of targeted proteins. Regulation of protein activity mainly involves phosphorylation/dephosphorylation events, leading to its activation or inhibition. It is the case for the vast majority of responses as a consequence of the binding of the primary messengers to membrane receptors. This response is quick, as it involves regulation of molecules that are already present in the cell. On the other hand, the induction or repression of the expression of genes requires the binding of transcriptional factors to the regulatory sequences of these genes. The transcriptional factors are activated by the primary messengers, in most cases, due to their function as nuclear receptors for these messengers. The secondary messengers like DAG or Ca2+ could also induce or repress gene expression, via transcriptional factors. This response is slower than the first because it involves more steps, like transcription of genes and then the effect of newly formed proteins in a specific target. The target could be a protein or another gene.
The terms "active" and "passive" are simple but important terms in the world of automotive safety. "Active safety" is used to refer to technology assisting in the prevention of a crash and "passive safety" to components of the vehicle (primarily airbags, seatbelts and the physical structure of the vehicle) that help to protect occupants during a crash. Crash avoidance systems and devices help the driver — and, increasingly, help the vehicle itself — to avoid a collision. This category includes: The vehicle's headlamps, reflectors, and other lights and signals The vehicle's mirrors The vehicle's brakes, steering, and suspension systems A subset of crash avoidance is driver assistance systems, which help the driver to detect obstacles and to control the vehicle. Driver assistance systems include:
The amino acids that make up a particular helix can be plotted on a helical wheel, a representation that illustrates the orientations of the constituent amino acids (see the article for leucine zipper for such a diagram). Often in globular proteins, as well as in specialized structures such as coiled-coils and leucine zippers, an α-helix will exhibit two "faces" – one containing predominantly hydrophobic amino acids oriented toward the interior of the protein, in the hydrophobic core, and one containing predominantly polar amino acids oriented toward the solvent-exposed surface of the protein. Changes in binding orientation also occur for facially-organized oligopeptides. This pattern is especially common in antimicrobial peptides, and many models have been devised to describe how this relates to their function. Common to many of them is that the hydrophobic face of the antimicrobial peptide forms pores in the plasma membrane after associating with the fatty chains at the membrane core.
Kunitz-type serine protease inhibitor APEKTx1 is a peptide toxin derived from the sea anemone Anthopleura elegantissima. This toxin has a dual function, acting both as a serine protease inhibitor and as a selective and potent pore blocker of Kv1.1, a shaker related voltage-gated potassium channel. APEKTx1 is a potent toxin purified from the sea anemone A. elegantissima. Besides APEKTx1, other toxins such as APETx1, APE1-1, APE1-2, APE2-2, ApC, and APETx2 have been identified in A. elegantissima. This peptide has 65 amino acids crosslinked by 3 disulphide bridges, and has a molecular mass of 7475 Da. It acts as a monomer. The toxin belongs to the type 2 sea anemone peptides targeting voltage-gated K channels. Other type 2 toxins are the kalicludines from Anemonia sulcata, which selectively block Kv1.2 channels, and SHTX II from Stichodactyla haddoni. Structural homology is also shared with the basic pancreatic trypsin inhibitor (BPTI), a very potent Kunitz-type protease inhibitor, and dendrotoxins (DTX I and α-DTX), which are potent inhibitors of voltage-gated potassium channels.
Sources: en.wikipedia.org
People can also develop CJD because they carry a mutation of the gene that codes for the prion protein (PRNP), located on chromosome 202p12-pter. This occurs in only 10–15% of all CJD cases. In sporadic cases, the misfolding of the prion protein is a process that is hypothesized to occur as a result of the effects of aging on cellular machinery, explaining why the disease often appears later in life. An EU study determined that "87% of cases were sporadic, 8% genetic, 5% iatrogenic and less than 1% variant." Testing for CJD has historically been problematic, due to the nonspecific nature of early symptoms and difficulty in safely obtaining brain tissue for confirmation. The diagnosis may initially be suspected in a person with rapidly progressing dementia, particularly when it is also found with the characteristic medical signs and symptoms such as involuntary muscle jerking, difficulty with coordination/balance and walking, and visual disturbances. Further testing can support the diagnosis and may include:
As anti-angiogenic cancer therapies have achieved widespread use, there has been increased interest in non-invasive monitoring of angiogenesis. One of the most extensively examined targets of angiogenesis is integrin αVβ3. Radiolabeled peptides containing RGD show high affinity and selectivity for integrin αVβ3 and are being investigated as tools to monitor treatment response of tumors via PET imaging. These include 18F-Galacto-RGD, 18F-Fluciclatide-RGD, 18F-RGD-K5, 68Ga-NOTA-RGD, 68Ga-NOTA-PRGD2, 18F-Alfatide, 18F-Alfatide II, and 18F-FPPRGD2. In a meta-analysis of studies using PET/CT in patients with cancer, it was shown that this diagnostic method may be very useful for detecting malignancies and predicting short-term outcomes, although larger-scale studies are needed.
Gingras research focuses on the development of experimental and bioinformatics approaches for functional proteomics, with a focus on protein-protein and proximity interactions. She applies these tools to the study of signaling pathways in health and disease and in mapping the physical organization of the dynamic proteome. Some of her work focuses on the consequence of disease-associated mutations on the interactions established by proteins. In addition to proteomics, Gingras laboratory has interest in studying human protein phosphatase and their systematic interactions and has now expanded into the field of systems biology.
Sources: en.wikipedia.org
The Shrake–Rupley algorithm is a numerical method that draws a mesh of points equidistant from each atom of the molecule and uses the number of these points that are solvent accessible to determine the surface area. The points are drawn at a water molecule's estimated radius beyond the van der Waals radius, which is effectively similar to 'rolling a ball' along the surface. All points are checked against the surface of neighboring atoms to determine whether they are buried or accessible. The number of points accessible is multiplied by the portion of surface area each point represents to calculate the ASA. The choice of the 'probe radius' does have an effect on the observed surface area, as using a smaller probe radius detects more surface details and therefore reports a larger surface. A typical value is 1.4Å, which approximates the radius of a water molecule. Another factor that affects the results is the definition of the VDW radii of the atoms in the molecule under study. For example, the molecule may often lack hydrogen atoms, which are implicit in the structure. The hydrogen atoms may be implicitly included in the atomic radii of the 'heavy' atoms, with a measure called the 'group radii'. In addition, the number of points created on the van der Waals surface of each atom determines another aspect of discretization, where more points provide an increased level of detail.
The Bergmann degradation makes use of the azide degradation described by the Curtius rearrangement. Curtius also attempted to degrade benzoylated amino acids; however, his method involved splitting the carbamate with strongly energetic treatment with acids, which lead to decomposition of the resultant aldehyde and acid amides. This convinced Bergmann that Curtius' azide degradation could be followed by treatment with benzyl alcohol (his carbobenzoxy method) to isolate the resultant amino acid aldehyde and residual peptide amide for sequencing purposes.
ADAMTS7 was identified as a protease that binds and cleaves COMP in a yeast two-hybrid screen using the epidermal growth factor (EGF) domain of COMP as the bait. However, this initial finding has been contested; a 2025 study demonstrated that purified ADAMTS7 does not exhibit proteolytic cleavage activity toward purified COMP. Furthermore, three independent unbiased N-terminal amine isotopic labeling of substrates (N-TAILS) proteomic studies identified a number of candidate substrates for ADAMTS7 but did not identify COMP as a potential substrate. Consequently, there is as yet no scientific consensus on the physiological function of ADAMTS7. Tissue inhibitor of metalloproteinases 4 (TIMP-4) appears to be the physiological inhibitor of ADAMTS7.
Sources: en.wikipedia.org
HPLC testing measures the presence and amount of one or more compounds in a liquid sample. It separates mixture components and records detector responses as peaks, which are compared with reference standards. Results are usually reported as concentrations or relative percentages.
Retention time is the interval between sample injection and the detector response for a given compound. It depends on the compound's interactions with the stationary and mobile phases under set conditions. Matching a retention time to a standard supports tentative identification but is not always unique.
HPLC alone can separate unknown compounds and provide retention times, but it often cannot identify them with certainty. Coupling HPLC to mass spectrometry gives mass information that improves identification. Confirmation usually requires comparison with reference standards or complementary techniques.
It is a set of checks performed before or during an HPLC run to confirm the system works as expected. Parameters may include resolution, tailing factor, theoretical plates, and retention time precision. Failure can trigger maintenance, method adjustment, or repeat analysis.