Everything below concerns system suitability. We keep the language plain, cite what the science says, and separate well-supported claims from open questions.
Last reviewed on 2026-08-01. Where a claim depends on a specific study, the study is described rather than over-claimed.
Separation performance depends on particle size, pore size, column length, and the chemistry of the stationary phase. Smaller particles generally improve efficiency but require higher pressure and suitable instrumentation. The mobile phase often contains buffers and organic solvents that influence retention and selectivity. Testing labs select conditions based on the analytes, sample matrix, and required sensitivity. Method development frequently involves screening several columns and solvent mixtures before a final set of conditions is chosen.
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.
Separation modes differ by the chemistry of the stationary phase and the composition of the mobile phase. Reversed-phase testing uses a nonpolar column and polar solvents, making it common for pharmaceutical, environmental, and food analytes. Normal-phase testing uses a polar column and nonpolar solvents for compounds that are poorly retained in reversed-phase systems. Ion-exchange and ion-pair methods separate charged species, while size-exclusion methods sort molecules by hydrodynamic volume. Gradient elution changes solvent strength over time to resolve complex mixtures, and isocratic elution holds solvent composition constant for simpler assays.
Key performance measures include retention time, peak area, peak height, resolution, tailing factor, and plate count. Retention time helps identify a peak under fixed conditions, but confirmation often requires a second method or detector. Peak area and height relate to concentration through calibration curves, which may be linear or nonlinear depending on the detector response. Resolution describes separation between adjacent peaks, while tailing factor and plate count describe peak shape and column efficiency. Performance checks verify these values before and during a run to confirm that the instrument is performing within limits.
High-performance liquid chromatography testing separates components of a liquid sample by forcing a mobile phase through a packed column. The stationary phase inside the column interacts with analytes to different degrees, so each compound exits at a characteristic retention time. A pump delivers solvent at controlled flow and pressure, while an injector introduces a precise sample volume. Detectors such as ultraviolet-visible, fluorescence, refractive index, or mass spectrometric instruments record the separated bands. The resulting chromatogram provides qualitative and quantitative information about the mixture.
| Property | Value | Notes |
|---|---|---|
| Separation principle | Differential partitioning | Analytes distribute between mobile and stationary phases. |
| Mobile phase | Liquid solvent mixture | Composition controls retention and selectivity. |
| Stationary phase | Packed column particles | Often chemically bonded silica. |
| Typical detector | UV-Vis or photodiode array | Mass spectrometry is also common. |
| Common synonym | High-performance liquid chromatography | Abbreviated as HPLC. |
Data handling and documentation are central to HPLC quality control. Electronic systems should have audit trails that record changes to methods, sequences, and results. Integration parameters, such as peak baseline and threshold, can affect reported areas and must be defined in advance. Out-of-specification results trigger a structured investigation that may include reanalysis, instrument checks, and review of sample preparation. Regulatory inspections often examine raw data, audit trails, and training records to verify that reported results are traceable and reliable.
Method validation establishes that an HPLC procedure is suitable for its intended use. Key parameters include accuracy, precision, specificity, linearity, range, limit of detection, limit of quantitation, and robustness. Accuracy measures agreement with a true or accepted value, while precision describes repeatability and intermediate precision. Specificity confirms that the method measures the analyte without interference from impurities, degradants, or excipients. Validation is documented in a protocol and report, and acceptance criteria are set before experiments begin. Regulatory guidance varies by region, but the general principles are widely harmonized.
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.
Quality control samples are inserted at intervals to monitor accuracy and precision throughout a batch. Blank samples detect contamination, while spiked samples assess recovery from the sample matrix. Calibration standards establish the relationship between detector response and concentration, and control samples are prepared independently from them whenever possible. Laboratories also participate in proficiency testing and maintain audit trails, instrument logs, and reagent records. Ongoing review of control charts can reveal trends before they cause out-of-specification results.
Method validation demonstrates that an HPLC procedure is suitable for its intended purpose. Common validation parameters include accuracy, precision, specificity, linearity, range, limit of detection, limit of quantification, and robustness. Accuracy reflects agreement with a reference value, while precision describes repeatability under defined conditions. Specificity shows whether the method can measure the analyte in the presence of impurities or matrix components. Validation documents are reviewed before a method is used for routine testing or regulatory submissions.
System suitability testing is performed before and during analytical runs to confirm that the instrument and method are working as expected. Typical checks include retention time, peak area precision, resolution between critical pairs, tailing factor, and theoretical plate count. Acceptance criteria are set in the method or pharmacopeial monograph. If a suitability check fails, the run may be rejected and the instrument or sample preparation may need investigation. This practice helps prevent release of data from a system that has drifted out of control.
In addition to cell signaling, the mTOR pathway also plays a role in beta cell growth leading to insulin secretion. High glucose in the blood begins the process of the mTOR signaling pathway, in which leucine plays an indirect role. The combination of glucose, leucine, and other activators cause mTOR to start signaling for the proliferation of beta cells and the secretion of insulin. Higher concentrations of leucine cause hyperactivity in the mTOR pathway, and S6 kinase is activated leading to inhibition of insulin receptor substrate through serine phosphorylation. In the cell the increased activity of mTOR complex causes eventual inability of beta cells to release insulin and the inhibitory effect of S6 kinase leads to insulin resistance in the cells, contributing to development of type 2 diabetes. Metformin is able to activate AMP kinase which phosphorylates proteins involved in the mTOR pathway, as well as leads to the progression of mTOR complex from its inactive state to its active state. It is suggested that metformin acts as a competitive inhibitor to the amino acid leucine in the mTOR pathway.
Angiogenesis, the formation of new blood vessels, is often critical for tumour cells to survive and grow in nutrient-depleted conditions. Akt is activated downstream of vascular endothelial growth factor (VEGF) in endothelial cells in the lining of blood vessels, promoting survival and growth. Akt also contributes to angiogenesis by activating endothelial nitric oxide synthase (eNOS), which increases production of nitric oxide (NO). This stimulates vasodilation and vascular remodelling. Signaling through the PI3K-Akt pathway increases translation of hypoxia-inducible factor α (HIF1α and HIF2α) transcription factors via mTOR. HIF promotes gene expression of VEGF and glycolytic enzymes, allowing metabolism in oxygen-depleted environments.
In 1930, safety glass became standard on all Ford cars. In the 1930s, plastic surgeon Claire L. Straith and physician C. J. Strickland advocated the use of seat belts and padded dashboards. Strickland founded the Automobile Safety League of America. In 1934, GM performed the first barrier crash test. In 1936, the Hudson Terraplane came with the first back-up brake system. Should the hydraulic brakes fail, the brake pedal would activate a set of mechanical brakes for the back wheels. In 1937, Chrysler, Plymouth, DeSoto, and Dodge added such items as a flat, smooth dash with recessed controls, rounded door handles, a windshield wiper control made of rubber, and the back of the front seat heavily padded to provide protection for rear passengers.
Aminoacyl-tRNA synthetase enzymes consume ATP in the attachment tRNA to amino acids, forming aminoacyl-tRNA complexes. Aminoacyl transferase binds AMP-amino acid to tRNA. The coupling reaction proceeds in two steps: aa + ATP ⟶ aa-AMP + PPi aa-AMP + tRNA ⟶ aa-tRNA + AMP The amino acid is coupled to the penultimate nucleotide at the 3′-end of the tRNA (the A in the sequence CCA) via an ester bond (roll over in illustration). Transporting chemicals out of a cell against a gradient is often associated with ATP hydrolysis. Transport is mediated by ATP binding cassette transporters. The human genome encodes 48 ABC transporters, that are used for exporting drugs, lipids, and other compounds.
Sources: en.wikipedia.org
ADAM (A Database of Anti-Microbial peptides) Archived 2015-06-17 at the Wayback Machine at ntou.edu.tw AntiFP Prediction of antifungal peptides AntiMPmod Prediction of antimicrobial potential of modified peptides Antimicrobial+Cationic+Peptides at the U.S. National Library of Medicine Medical Subject Headings (MeSH) AntiTbPred Prediction of anti-tuberculosis peptides Antimicrobial Peptide Database Archived 2011-07-20 at the Wayback Machine at University of Nebraska Medical Center Antimicrobial Peptide Scanner Deep Learning based AMP prediction server AntiTbPdb Anti Tubercular Peptide Database BioPD[link removed] at Peking University Health Science Center CAMP:Collection of Anti-Microbial Peptides at National Institute for Research in Reproductive Health (NIRRH) DBAASP - Database of Antimicrobial Activity and Structure of Peptides] LAMP at Fudan University PeptideLocator Prediction of functional peptides, including antimicrobial peptides, in a protein sequence PeptideRanker Bioactive peptide, including antimicrobial peptide, prediction modlAMP Python package for computational work with antimicrobial peptides, including sequence handling, -design, -prediction, descriptor calculation and plotting
2,5-Diketopiperazine is an organic compound with the formula (NHCH2C(O))2. The compound features a six-membered ring containing two amide groups at opposite positions in the ring. It was first compound containing a peptide bond to be characterized by X-ray crystallography in 1938. It is the parent of a large class of 2,5-Diketopiperazines (2,5-DKPs) with the formula (NHCH2(R)C(O))2 (R = H, CH3, etc.). They are ubiquitous peptides in nature. They are often found in fermentation broths and yeast cultures as well as embedded in larger more complex architectures in a variety of natural products as well as several drugs. In addition, they are often produced as degradation products of polypeptides, especially in foods and beverages. They have also been found in extraterrestrial objects such as comets and asteroids.
In pharmacology, relative bioavailability measures the bioavailability (estimated as the AUC) of a formulation (A) of a certain drug when compared with another formulation (B) of the same drug, usually an established standard, or through administration via a different route. When the standard consists of intravenously administered drug, this is known as absolute bioavailability (see above). F r e l = 100 ⋅ A U C A ⋅ D B A U C B ⋅ D A {\displaystyle F_{\mathrm {rel} }=100\cdot {\frac {AUC_{\mathrm {A} }\cdot D_{\mathrm {B} }}{AUC_{\mathrm {B} }\cdot D_{\mathrm {A} }}}}
Aβ is the main component of the kind of amyloid plaques that form in the brains of people with Alzheimer's disease. Aβ can also form the deposits that line cerebral blood vessels in cerebral amyloid angiopathy. The plaques are composed of aggregated Aβ oligomers called amyloid fibrils, a protein fold shared by other peptides such as the prions associated with protein misfolding disease, also known as proteinopathy.
Camurus AB (publ) is a Swedish research-based pharmaceutical and biotechnology company specialising in the commercialization of medicines for treating serious and chronic diseases. Established in 1991 and based in the southern university city of Lund, in the Medicon Valley region, the company is listed on Nasdaq Stockholm, Mid Cap. Camurus was founded by scientists in biophysical, food, and pharmaceutical chemistry with expertise in lipid phase structures. The company provides nanoscale drug-delivery systems for development of high-value therapeutics.
Sources: en.wikipedia.org
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.
The first definition of the term bioinformatics was coined by Paulien Hogeweg and Ben Hesper in 1970, to refer to the study of information processes in biotic systems. This definition placed bioinformatics as a field parallel to biochemistry (the study of chemical processes in biological systems). Bioinformatics and computational biology involved the analysis of biological data, particularly DNA, RNA, and protein sequences. The field of bioinformatics experienced explosive growth starting in the mid-1990s, driven largely by the Human Genome Project and by rapid advances in DNA sequencing technology. Analyzing biological data to produce meaningful information involves writing and running software programs that use algorithms from graph theory, artificial intelligence, soft computing, data mining, image processing, and computer simulation. The algorithms in turn depend on theoretical foundations such as discrete mathematics, control theory, system theory, information theory, and statistics.
Asparagine peptide lyase are one of the seven groups in which proteases, also termed proteolytic enzymes, peptidases, or proteinases, are classified according to their catalytic residue. The catalytic mechanism of the asparagine peptide lyases involves an asparagine residue acting as nucleophile to perform a nucleophilic elimination reaction, rather than hydrolysis, to catalyse the breaking of a peptide bond. The existence of this seventh catalytic type of proteases, in which the peptide bond cleavage occurs by self-processing instead of hydrolysis, was demonstrated with the discovery of the crystal structure of the self-cleaving precursor of the Tsh autotransporter from E. coli. These enzymes are synthesized as precursors or propeptides, which cleave themselves by an autoproteolytic reaction. The self-cleaving nature of asparagine peptide lyases contradicts the general definition of an enzyme given that the enzymatic activity destroys the enzyme. However, the self-processing is the action of a proteolytic enzyme, notwithstanding the enzyme is not recoverable from the reaction.
As the salt of a weak base (ammonium) and a weak acid (acetic acid), is often used to create a buffer solution. Ammonium acetate is volatile at low pressures. Because of this, it has been used to replace cell buffers that contain non-volatile salts in preparing samples for mass spectrometry. It is also popular as a buffer for mobile phases for HPLC with ELSD and CAD-based detection for this reason. Other volatile salts that have been used for this include ammonium formate. When dissolving ammonium acetate in pure water, the resulting solution typically has a pH of 7, because the equal amounts of acetate and ammonium neutralize each other. However, ammonium acetate is a dual component buffer system, which buffers around pH 4.75 ± 1 (acetate) and pH 9.25 ± 1 (ammonium), but it has no significant buffer capacity at pH 7, contrary to common misconception.
Even with all the precautions taken by medical professionals, infection reportedly occurs in up to 13.9% of patients after stabilization of an open fracture, and in about 0.5-2% of patients who receive joint prostheses. To reduce these numbers, the surfaces of the devices used in these procedures have been altered in hopes of preventing the growth of the bacteria that leads to these infections. This has been achieved by coating titanium devices with an antiseptic combination of chlorhexidine and chloroxylenol. This antiseptic combination successfully prevents the growth of the five main organisms that cause medical-related infections, which include Staphylococcus epidermidis, Methicillin-resistant Staphylococcus aureus, Pseudomonas aeruginosa, Escherichia coli and Candida albicans. Peptide-based gel coating with intrinsic antibacterial activity against Methicillin-resistant Staphylococcus aureus, was also shown to inhibit colonization of titanium implants in mice.
Sources: en.wikipedia.org
HPLC separates and detects individual compounds in a liquid sample, producing peaks at characteristic retention times. Peak area or height can be used to estimate concentration when calibrated with known standards. It does not identify unknown compounds with certainty unless additional detectors or reference materials are used.
Pressure drives the liquid mobile phase through a column packed with small particles. Without pressure, flow would be very slow or stop because the packed bed resists liquid movement. Modern pumps maintain a steady flow despite the resistance.
A chromatogram is a plot of detector signal against time after sample injection. Each peak represents a compound or group of compounds eluting from the column. Retention time and peak area are the main measurements read from the plot.
It measures the amounts and identities of compounds in liquid samples by separation and detection. Depending on the detector and reference standards, results can be qualitative or quantitative. The technique is used in fields such as pharmaceutical analysis, food safety, and environmental monitoring.