A practical reference on Method validation: what it is, how it behaves, what the literature reports, and where the honest uncertainties sit.
Reviewed 2025-04-21. Anything still debated is marked as such rather than presented as settled.
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.
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.
Quality control laboratories use HPLC to check identity, purity, concentration, and stability of raw materials and finished products. A validated method specifies the column, mobile phase, flow rate, detection wavelength, injection volume, and run time. Samples are prepared and compared against reference standards of known concentration. The resulting chromatogram provides quantitative data, such as assay values and impurity levels. This approach is common in pharmaceutical, food, environmental, and industrial testing where consistent measurements are required.
| Property | Value | Notes |
|---|---|---|
| Separation mode | Reversed-phase | Common for polar and moderately polar analytes |
| Typical column length | 100-250 mm | Shorter columns can reduce run time |
| Particle size | 3-5 micrometers | Smaller particles improve efficiency but raise pressure |
| Flow rate | 0.5-2.0 mL/min | Depends on column dimensions and pressure limits |
| Detection | UV-Vis absorbance | Widely used for compounds with chromophores |
System suitability testing is performed before and during analytical runs to confirm that the instrument and method are working as expected. Common checks include retention time, peak area, resolution between critical pairs, tailing factor, and theoretical plate count. Results are compared with predefined limits, and a failed check requires investigation before sample results are reported. Quality control samples at low, middle, and high concentrations are injected at intervals to monitor accuracy and precision. Blank injections detect carryover and contamination, while control charts track performance over time.
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.
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.
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.
Developing an HPLC test begins with defining the analytes, matrix, and required reporting limits. Chemists select a separation mode, column chemistry, mobile phase composition, flow rate, and detection wavelength or mass transition. Experiments then adjust these variables to achieve adequate retention, resolution, and peak shape. System suitability tests confirm that the instrument and method perform consistently before sample analysis. Without suitable resolution, quantitative results may be unreliable. Preliminary runs often use scouting gradients to locate retention windows.
Validation establishes that a method is suitable for its intended purpose. Typical parameters include accuracy, precision, specificity, linearity, range, limit of detection, limit of quantification, robustness, and stability of standards and samples. Acceptance criteria are defined in advance, and results are documented in a validation report. Regulatory guidance for pharmaceuticals, foods, and environmental testing differs, so the applicable framework must be identified. Ongoing verification uses control samples and trend charts after validation. Method transfer to another laboratory may require partial revalidation.
Routine quality control includes blanks, duplicates, spiked samples, and certified reference materials. Calibration curves are prepared with standards at several concentrations, and the detector response is checked for linearity. Carryover, column aging, mobile phase evaporation, and temperature drift can shift retention times or peak areas. Maintenance such as replacing seals, filters, and columns helps prevent failures. Records of injections, integration, and deviations support traceability. Audits may request raw data and instrument logs for each batch.
Degradation of an amino acid often begins with transamination, in which its amino group is transferred to α-ketoglutarate, forming glutamate. This process involves transaminases, often the same enzymes used in amino acid synthesis. In many vertebrates, the amino group is subsequently released as ammonia and converted to urea via the urea cycle for excretion. However, amino acid degradation can result in uric acid or ammonia instead, depending on the organism. For example, serine dehydratase converts serine directly to pyruvate and ammonia. After removal of one or more amino groups, the remaining carbon skeleton of an amino acid can serve as a precursor for synthesizing other amino acids, be further metabolized for energy after conversion into intermediates of glycolysis (typically via gluconeogenesis) or of the citric acid cycle, or be used for fatty acid synthesis and storage as triacylglycerol. Amino acids are bidentate ligands, forming transition metal amino acid complexes.
After synthesizing and purifying the core, the carbohydrate layer is added to its surface. Common coating materials are typically polyhydroxy oligomers such as cellobiose, citrate, lactose, and sucrose. This layer seems to be important for the properties of aquasomes, as it influences several drug characteristics including adsorption, molecular stability, and conformation (shape), and acts as a dehydroprotectant. The addition of the carbohydrate layer to the surface of the nanocrystalline core is commonly carried out by passive adsorption through incubation and sonication. Similar to the processing of the core, the carbohydrate layer is subjected to centrifugation, washing, and further sonification followed by heated air drying. Finally, the bioactive molecule of interest is loaded into the carbohydrate layer. This process typically occurs through either lyophilization or passive adsorption, and the fully functionalized aquasome is then characterized.
National teams April 29 – May 1: 2018 FIBA 3x3 Asia Cup in Shenzhen Men: Australia defeated Mongolia, 17–16, in the final. Japan took third place. Women: New Zealand defeated China, 14–11, in the final. Australia took third place. August 5 – 11: 2018 FIBA Under-18 Asian Championship in Thailand In the final, Australia defeated New Zealand, 73–62, to win their 1st title. China took third place. Note: All teams mentioned here, plus Philippines, have qualified to compete at the 2019 FIBA Under-19 Basketball World Cup. October 28 – November 3: 2018 FIBA Under-18 Women's Asian Championship in Bangalore China defeated Japan, 89–76, to win their fifth consecutive and 16th overall FIBA Under-18 Women's Asian Championship title. Australia took third place. Note: All teams mentioned here, plus South Korea, have qualified to compete at the 2019 FIBA Under-19 Women's Basketball World Cup. Clubs teams November 17, 2017 – May 2: 2017–18 ABL season San Miguel Alab Pilipinas defeated Mono Vampire, 3–2 in games played in a 5-legged final, to win their first ABL title. July 17 – 22: Summer Super 8 in Macau Guangzhou Long-Lions defeated Seoul Samsung Thunders, 78–72, to win their first title. Incheon Electroland Elephants took third place.
National teams June 3 – 9: 2019 FIBA Under-16 Americas Championship in Belém The United States defeated Canada, 94–77, to win their sixth consecutive FIBA Under-16 Americas Championship title. The Dominican Republic took third place. Argentina took fourth place. Note: All teams mentioned above have qualified to compete at the 2020 FIBA Under-17 Basketball World Cup. June 16 – 22: 2019 FIBA Under-16 Women's Americas Championship in Puerto Aysén The United States defeated Canada, 87–37, to win their second consecutive and fifth overall FIBA Under-16 Women's Americas Championship title. Chile took third place. Puerto Rico took fourth place. Note: All teams mentioned above have qualified to compete at the 2020 FIBA Under-17 Women's Basketball World Cup. September 22 – 29: 2019 FIBA Women's AmeriCup in San Juan The United States defeated Canada, 67–46, to win their third FIBA Women's AmeriCup title. Brazil took third place. Note: The first eight teams have qualified to compete at the Americas 2020 Olympic pre-qualifying tournaments. Club teams January 18 – March 31: 2019 FIBA Americas League San Lorenzo defeated Guaros, 64–61, to win their second consecutive FIBA Americas League title.
detailed family history conducting a detailed physical examination to document morphological features testing for genetic defect in FGDY1 x-rays can identify skeletal abnormalities echo cardiogram can screen for heart abnormalities CT scan of the brain for cystic development X-ray of the teeth Ultrasound of abdomen to identify undescended testis Similar to all genetic diseases Aarskog–Scott syndrome cannot be cured, although numerous treatments exist to increase the quality of life. Surgery may be required to correct some of the anomalies, and orthodontic treatment may be used to correct some of the facial abnormalities. Trials of growth hormone have been effective to treat short stature in this disorder. Some people may have some mental slowness, but children with this condition often have good social skills. Some males may have problems with fertility. The syndrome is named for Dagfinn Aarskog, a Norwegian pediatrician and human geneticist who first described it in 1970, and for Charles I. Scott, Jr., an American medical geneticist who independently described the syndrome in 1971.
Sources: en.wikipedia.org
Carlos Outeiral, CASP14: what Google DeepMind's AlphaFold 2 really achieved, and what it means for protein folding, biology and bioinformatics, Oxford Protein Informatics Group. (3 December) Mohammed AlQuraishi, AlphaFold2 @ CASP14: "It feels like one's child has left home." (blog), 8 December 2020 Mohammed AlQuraishi, The AlphaFold2 Method Paper: A Fount of Good Ideas (blog), 25 July 2021 AlphaFold-3 web server AlphaFold v2.1 code and links to model on GitHub Open access to protein structure predictions for the human proteome and 20 other key organisms at European Bioinformatics Institute (AlphaFold Protein Structure Database) CASP 14 website AlphaFold: The making of a scientific breakthrough, DeepMind, via YouTube. ColabFold, version for homooligomeric prediction and complexes
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.
Network analysis seeks to understand the relationships within biological networks such as metabolic or protein–protein interaction networks. Although biological networks can be constructed from a single type of molecule or entity (such as genes), network biology often attempts to integrate many different data types, such as proteins, small molecules, gene expression data, and others, which are all connected physically, functionally, or both. Systems biology involves the use of computer simulations of cellular subsystems (such as the networks of metabolites and enzymes that comprise metabolism, signal transduction pathways and gene regulatory networks) to both analyze and visualize the complex connections of these cellular processes. Artificial life or virtual evolution attempts to understand evolutionary processes via the computer simulation of simple (artificial) life forms.
. 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
Many different amino acid side chains have been described as ADP-ribose acceptors. From a chemical perspective, this modification represents protein glycosylation: the transfer of ADP-ribose occurs onto amino acid side chains with a nucleophilic oxygen, nitrogen, or sulfur, resulting in N-, O-, or S-glycosidic linkage to the ribose of the ADP-ribose. Originally, acidic amino acids (glutamate and aspartate) were described as the main sites of ADP-ribosylation. However, many other ADP-ribose acceptor sites such as serine, arginine, cysteine, lysine, diphthamide, phosphoserine, and asparagine have been identified in subsequent works.
The increasing amount of genomic and molecular information is the basis for understanding higher-order biological systems, such as the cell and the organism, and their interactions with the environment, as well as for medical, industrial and other practical applications. The KEGG resource provides a reference knowledge base for linking genomes to biological systems, categorized as building blocks in the genomic space (KEGG GENES), the chemical space (KEGG LIGAND), wiring diagrams of interaction networks and reaction networks (KEGG PATHWAY), and ontologies for pathway reconstruction (BRITE database). The KEGG PATHWAY database is a collection of manually drawn pathway maps for metabolism, genetic information processing, environmental information processing such as signal transduction, ligand–receptor interaction and cell communication, various other cellular processes and human diseases, all based on extensive survey of published literature.
A third, only marginally related concept was proposed in 1923 by Gilbert N. Lewis, which includes reactions with acid–base characteristics that do not involve a proton transfer. A Lewis acid is a species that accepts a pair of electrons from another species; in other words, it is an electron pair acceptor. Brønsted acid–base reactions are proton transfer reactions while Lewis acid–base reactions are electron pair transfers. Many Lewis acids are not Brønsted–Lowry acids. Contrast how the following reactions are described in terms of acid–base chemistry:
Sources: en.wikipedia.org
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.
Performance checks confirm that the chromatographic system works within preset limits before results are accepted. They examine factors such as peak resolution, tailing, and repeatability. If criteria fail, the run may need correction or repetition.
Retention time alone is not definitive proof because other compounds can elute at similar times. Confirmation usually uses a second method, a different column, or a detector such as mass spectrometry. Authentic standards strengthen identification.
Method validation is the documented process of confirming that an HPLC procedure is suitable for its intended use. It evaluates accuracy, precision, specificity, linearity, range, detection limits, and robustness. Validation criteria depend on the regulatory context and the sample type.