This is a working overview of reversed-phase, written for readers who want more than a one-paragraph summary but less than a textbook.
Reviewed 2026-03-01. Anything still debated is marked as such rather than presented as settled.
HPLC testing separates dissolved compounds by passing a liquid sample through a column packed with stationary phase. A pump delivers mobile phase at controlled flow, and the sample components interact differently with stationary and mobile phases. Compounds that spend more time in mobile phase elute earlier; those retained by stationary phase elute later. Detectors record elution as peaks, and peak area or height relates to amount. This mechanism underpins quantitative analysis of mixtures.
Most routine HPLC testing uses reversed-phase columns, where the stationary phase is nonpolar and the mobile phase is a polar mixture such as water with an organic solvent. Analytes partition between the two phases according to polarity, size, and charge. Gradients that change solvent composition over time can separate compounds with broad retention ranges. Isocratic conditions keep solvent composition constant and suit simpler mixtures. The choice of column chemistry, pH, and temperature affects selectivity and peak shape.
Detection in HPLC testing commonly relies on ultraviolet-visible absorbance, fluorescence, refractive index, or mass spectrometry. UV detection is widely used because many organic compounds absorb light, but it requires a chromophore. Mass spectrometry provides mass-based identification and high sensitivity for trace analytes. Each detector has trade-offs in selectivity, cost, and compatibility with mobile phases. Quantification typically uses calibration curves prepared from reference standards. Results are reported as concentration, purity, or presence above a limit.
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.
| Property | Value | Notes |
|---|---|---|
| Separation mode | Reversed-phase | Nonpolar stationary phase with polar mobile phase |
| Typical column particle size | 3–5 µm | Smaller particles improve resolution but raise pressure |
| Typical flow rate | 0.5–2.0 mL/min | Depends on column dimensions and pressure limits |
| Common detection | UV-Vis absorbance | Requires analytes with chromophores |
| Typical run time | 5–30 min | Varies with method, gradient, and sample complexity |
In quality control laboratories, HPLC testing supports batch release, raw material checks, stability studies, and impurity profiling. A validated method defines sample preparation, instrument settings, calibration, and acceptance criteria. Analysts compare results with specifications and investigate out-of-specification outcomes before a batch is approved. Documentation includes chromatograms, integration records, audit trails, and reagent details. Because results influence product decisions, laboratories follow formal quality systems and data integrity rules. The exact tests and limits depend on the material, its intended use, and the applicable regulatory framework.
Method validation examines whether an HPLC procedure is suitable for its intended purpose. Common parameters include accuracy, precision, specificity, linearity, range, detection limit, quantification limit, and robustness. Accuracy describes closeness to a true or accepted value, while precision describes agreement among repeated measurements. Specificity shows whether the method can measure the analyte without interference from related substances. Robustness tests small deliberate changes in flow, temperature, or solvent composition. Validation is not a one-time event; methods may need partial revalidation after changes to instruments, columns, sample handling, or specification limits. Regulatory guidance provides frameworks, but some details remain method-specific.
Several separation modes exist, including reversed-phase, normal-phase, ion-exchange, size-exclusion, and hydrophilic interaction liquid chromatography. Reversed-phase uses a nonpolar stationary phase with a polar mobile phase and is widely applied to small organic molecules. Gradient elution changes mobile phase composition during the run, while isocratic elution keeps it constant. Column chemistry, particle size, temperature, flow rate, and mobile phase pH all influence retention and resolution. Method development selects conditions that separate analytes from matrix components and from each other.
Detection commonly uses ultraviolet-visible absorbance, fluorescence, refractive index, or mass spectrometry. Ultraviolet detection depends on molecular chromophores that absorb light at specific wavelengths. Mass spectrometry provides mass information and sensitive quantification, often after electrospray ionization. Before sample batches, performance checks examine resolution, elution time repeatability, peak symmetry, and plate count. Matrix effects and co-elution remain recognized uncertainties; formal validation studies and orthogonal detection help address them. Detector choice depends on analyte properties and required sensitivity.
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.
An insulin pump delivers insulin subcutaneously. The insulin pump body itself can also contain the algorithm used in an AID system, or it can connect via Bluetooth with a separate mobile device (such as a phone) to send data and receive commands to adjust insulin delivery. Algorithm The algorithm for each AID system differs. In commercial systems (see below), little is known about the details of how the control algorithm works. In open source systems, the code and algorithm are openly available. In general, all algorithms do the same basic functionality of taking in CGM data and based on predicted glucose level's and the user's personal settings (for basal rates, insulin sensitivity, and carbohydrate ratio, for example) then recommends insulin dosing to help bring or maintain glucose levels in target range. Depending on the system, users may have the ability to adjust the target for the system, and may have different settings to ask the system to give more or less insulin in general.
On the other hand, loss of control of cell death (resulting in excess apoptosis) can lead to neurodegenerative diseases, hematologic diseases, and tissue damage. Neurons that rely on mitochondrial respiration undergo apoptosis in neurodegenerative diseases such as Alzheimer's and Parkinson's. (an observation known as the "Inverse Warburg hypothesis"). Moreover, there is an inverse epidemiological comorbidity between neurodegenerative diseases and cancer. The progression of HIV is directly linked to excess, unregulated apoptosis. In a healthy individual, the number of CD4+ lymphocytes is in balance with the cells generated by the bone marrow; however, in HIV-positive patients, this balance is lost due to an inability of the bone marrow to regenerate CD4+ cells. In the case of HIV, CD4+ lymphocytes die at an accelerated rate through uncontrolled apoptosis, when stimulated. At the molecular level, hyperactive apoptosis can be caused by defects in signaling pathways that regulate the Bcl-2 family proteins. Increased expression of apoptotic proteins such as BIM, or their decreased proteolysis, leads to cell death and can cause a number of pathologies, depending on the cells where excessive activity of BIM occurs. Cancer cells can escape apoptosis through mechanisms that suppress BIM expression or by increased proteolysis of BIM.
The circadian oscillators in eukaryotes that have been studied function using a negative feedback loop in which proteins inhibit their own transcription in a cycle that takes approximately 24 hours. This is known as a transcription-translation-derived oscillator (TTO).(2) Without a nucleus, prokaryotic cells must have a different mechanism of keeping circadian time. In 1998, Ishiura et al. determined that the KaiABC protein complex was responsible for the circadian negative feedback loop in Synechococcus by mapping 19 clock mutants to the genes for these three proteins.(3) An experiment by Nakajima et al., in 2005, was able to demonstrate the circadian oscillation of the Synechococcus KaiABC complex in vitro. They did this by adding KaiA, KaiB, KaiC, and ATP into a test tube in the approximate ratio recorded in vivo. They then measured the levels of KaiC phosphorylation and found that it demonstrated circadian rhythmicity for three cycles without damping. This cycle was also temperature compensating. They also tested incubating mutant KaiC protein with KaiA, KaiB, and ATP. They found that the period of KaiC phosphorylation matched the intrinsic period of the cyanobacterium with the corresponding mutant genome. These results led them to conclude that KaiC phosphorylation is the basis for circadian rhythm generation in Synechococcus. (2)
Sources: en.wikipedia.org
Amivantamab, sold under the brand name Rybrevant, is a bispecific monoclonal antibody used to treat non-small cell lung cancer. Amivantamab is a bispecific epidermal growth factor (EGF) receptor-directed and MET receptor-directed antibody. It is the first treatment for adults with non-small cell lung cancer whose tumors have specific types of genetic mutations: epidermal growth factor receptor (EGFR) exon 20 insertion mutations. The most common side effects include rash, infusion-related reactions, skin infections around the fingernails or toenails, muscle and joint pain, shortness of breath, nausea, fatigue, swelling in the lower legs or hands or face, sores in the mouth, cough, constipation, vomiting and changes in certain blood tests. Amivantamab was approved for medical use in the United States in May 2021, and in the European Union in December 2021. The US Food and Drug Administration considers it to be a first-in-class medication.
Because protein chains are open, AlphaKnot uses closure procedures before applying knot invariants. Its probabilistic method repeatedly closes the chain using randomly selected points on a large surrounding sphere and assigns the dominant topology obtained from the ensemble of closures. Deterministic alternatives connect the chain termini using prescribed geometries, including a direct closure and a closure constructed using the centre of mass. Knot identification uses the HOMFLY polynomial to distinguish knot types. AlphaKnot recognizes knots with minimal representations containing up to 12 crossings. In large-scale database calculations, structures that exhibit evidence of a nontrivial knot are subsequently analysed to determine the corresponding knot core, the smallest portion of the protein chain required to retain the detected topology. The database primarily reports the topology of the complete protein chain. More detailed information about subchain topologies can be obtained by calculating a knot map, which records the topology of different portions of the sequence. Because producing full knot maps for hundreds of thousands of structures would require substantial computational resources, these calculations are performed on demand rather than precomputed for the entire AlphaFold DB v4 dataset.
. It is used as a measure of affinity, with higher values indicating a lower affinity. For the given equation (E = enzyme, S = substrate, P = product), E + S ⟺ k − 1 k 1 E S ⟺ k 2 E + P {\displaystyle E+S{\overset {k_{1}}{\underset {k_{-}{1}}{\Longleftrightarrow }}}ES{\overset {k_{2}}{\Longleftrightarrow }}E+P} k d {\displaystyle k_{d}} would be equivalent to k − 1 / k 1 {\displaystyle k_{-1}/k_{1}} , where k 1 {\displaystyle k_{1}} and k − 1 {\displaystyle k_{-1}} are the rates of the forward and backward reaction, respectively in the conversion of individual E and S to the enzyme substrate complex. Information theory allows for a more quantitative definition of specificity by calculating the entropy in the binding spectrum. The chemical specificity of an enzyme for a particular substrate can be found using two variables that are derived from the Michaelis-Menten equation. k m {\displaystyle k_{m}} approximates the dissociation constant of enzyme-substrate complexes. k c a t {\displaystyle k_{cat}}
Sources: en.wikipedia.org
It separates components in a liquid sample and measures their amounts using a detector. Results can indicate concentration, purity, or identity based on retention time and detector response. The technique works for mixtures that can be dissolved and filtered.
It offers high resolution, reproducibility, and compatibility with many sample types. A single run can separate and quantify multiple analytes. It is common in pharmaceutical, food, environmental, and industrial laboratories.
Samples must be soluble in a suitable mobile phase and free of particles that can block the column. Detector response depends on analyte structure, so some compounds need derivatization or alternative detection. Complex matrices may require extensive sample preparation.
System suitability is typically performed before each batch or according to the validated method and laboratory procedure. Some long runs include periodic checks during analysis. The required frequency depends on regulatory expectations and method performance.