retention time comes up often in conversation and rarely with the context attached. Here we lay out the basics in order, then work through the practical considerations.
Updated 2025-10-07. Numbers and descriptions here follow the published literature rather than marketing material.
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.
Documentation and traceability are central to regulated HPLC testing. Records typically include instrument logs, column history, mobile-phase preparation, sample preparation, injection sequences, raw chromatograms, and audit trails. Electronic systems may require user access controls, time-stamped changes, and backup procedures. Training records show that analysts are qualified for assigned methods. Audits and inspections check whether written procedures match actual practice and whether deviations are documented. These controls support reproducibility and allow results to be reconstructed if questions arise later.
Method validation establishes that an HPLC procedure is suitable for its intended purpose. Typical parameters include accuracy, precision, specificity, linearity, range, limit of detection, limit of quantitation, robustness, and solution stability. Accuracy reflects closeness to a reference value, while precision reflects agreement among repeated measurements. Specificity shows whether the method can measure the analyte without interference from matrix components. Validation is documented through protocols and reports, and the required extent depends on the method's use and regulatory context.
Routine quality control uses system suitability, blank injections, check standards, and control samples to detect drift or contamination. System suitability criteria may specify minimum resolution, maximum tailing factor, and a permitted range for repeated injections. Blank injections reveal carryover or solvent contamination, while check standards confirm calibration accuracy over a batch. Control samples with known analyte levels can show whether results remain within statistical limits. When a control result falls outside limits, the analyst investigates the cause and may invalidate affected results before repeating the batch.
| 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 |
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.
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.
Detection in HPLC testing commonly relies on ultraviolet-visible absorbance, fluorescence, refractive index, or mass spectrometry. A diode array detector records full spectra across a wavelength range, which helps identify co-eluting peaks. Mass spectrometry provides mass-to-charge ratios and can confirm molecular identity at low concentrations. The choice of detector depends on analyte structure, required sensitivity, and whether quantitation or identification is the goal. No single detector works for every compound, and method development often compares responses before selecting one.
High-performance liquid chromatography is an analytical technique that separates components of a liquid sample by passing it 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 interaction with the stationary phase cause analytes to migrate at different rates. Detectors record elution as peaks, and a data system converts signals into a chromatogram. The method is suited to compounds that dissolve in a liquid and are not volatile enough for gas chromatography.
Reversed-phase chromatography dominates modern HPLC testing, using a nonpolar stationary phase such as chemically bonded octadecyl groups and a polar mobile phase of water mixed with organic solvent. Analytes partition between the mobile and stationary phases according to hydrophobicity. Gradient elution changes the mobile phase composition over time to separate compounds with a wide range of retention. Isocratic elution keeps the composition constant and is simpler for routine assays. Column temperature, pH, and flow rate influence selectivity, peak shape, and retention time, so these parameters are controlled during a validated method.
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.
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.
In the first decade of the 21st century, what was called "age management medicine" was considered a field of alternative medicine, and, as of 2007, was not recognized by the American Medical Association. Other names at this time included "antiaging medicine" and "regenerative medicine". Age management medicine is controversial. The field is underregulated and supported by insufficient scientific evidence. People who practice it open themselves up to legal liability on grounds of negligence–malpractice, warranty issues, and product liability. The use of growth hormone has been frequently recommended; however, such use is associated with cancer. Age management medicine is often promoted by anti-aging practitioners specializing in nutritional supplements and hormone-replacement, a practice that may lead to harmful side-effects.
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
This enzyme is the extracellular nuclease of Staphylococcus aureus. Two strains, V8 and Foggi, yield almost identical enzymes. A common source is E.coli cells carrying a cloned nuc gene encoding Staphylococcus aureus extracellular nuclease (micrococcal nuclease). The 3-dimensional structure of micrococcal nuclease (then called Staphyloccal nuclease) was solved very early in the history of protein crystallography, in 1969. Higher-resolution, more recent crystal structures are available for the apo form and for the thymidine-diphosphate-inhibited form. As seen in the ribbon diagram above, the nuclease molecule has 3 long alpha helices and a 5-stranded, barrel-shaped beta sheet, in an arrangement known as the OB-fold (for oligonucleotide-binding fold) as classified in the SCOP database.
Beano contains the enzyme α-Galactosidase, specifically one derived from the fungus Aspergillus niger. The enzyme works in the digestive tract to break down the complex or branching sugars (polysaccharides and oligosaccharides) in foods such as legumes (beans and peanuts) and cruciferous vegetables (cauliflower, broccoli, cabbage, and brussels sprouts, among others). The enzyme breaks those complex sugars into simple sugars, making these foods somewhat more digestible. The polysaccharides and oligosaccharides found in these foods might otherwise pass through the small intestine unaffected. Once in the large intestine, those sugars may be metabolized by intestinal flora, fermenting to produce the gases that cause discomfort and flatulence. Two randomized controlled trials show reduction in gas by subjects taking oral α-GAL. Another study indicates it may interfere with the diabetic medication acarbose, though it also reduces the bloating associated with the drug.
CKLF-like MARVEL transmembrane domain-containing 5 (CMTM5), previously termed chemokine-like factor superfamily 5 (i.e. CKLFSF5), designates any one of the six protein isoforms (termed CMTM5-v1 to CMTM5-v6) encoded by six different alternative splices of its gene, CMTM5; CMTM5-v1 is the most studied of these isoforms. The CMTM5 gene is located in band 11.2 on the long (i.e. "q") arm of chromosome 14. The CMTM5 isoforms are members of the CKLF-like MARVEL transmembrane domain-containing family (CMTM). This family consists of 9 proteins although most of them are known to have one or more isoforms. These proteins are: chemokine-like factor (i.e. CLF, the founding member of the family) and CEF-like marvel transmembrane domain-containing 1 through 8 (i.e. CMTM1 through CMTM8). All of these proteins as well as the genes responsible for their production (i.e. CKLF and CMTM1 to CMTM8, respectively) have similar structures but vary in their apparent physiological and pathological functions. Preliminary studies suggest that CMTM5-v1 (which cells commonly secrete to the extracellular spaces such as the blood) or an unspecified CMTM5 isoform has various functions including involvements in regulating the autoimmune system, the development of numerous types of cancers, and the cardiovascular system.
Sources: en.wikipedia.org
Amylopectin is a key component in the crystallization of starch's final configuration, accounting for 70-80% of the final mass. Composed of α-glucose, it is formed in plants as a primary measure of energy storage in tandem with this structural metric. Amylopectin bears a straight/linear chain along with a number of side chains which may be branched further. Glucose units are linked in a linear way with α(1→4) glycosidic bonds. Branching usually occurs at intervals of 25 residues. At the places of origin of a side chain, the branching that takes place bears an α(1→6) glycosidic bond, resulting in a soluble molecule that can be quickly degraded as it has many end points onto which enzymes can attach. Wolform and Thompson (1956) have also reported α(1→3)linkages in case of amylopectin. Amylopectin contains a larger number of glucose units (2000 to 200,000) as compared to amylose containing 200 to 1000 α-glucose units. In contrast, amylose contains very few α(1→6) bonds, or even none at all. This causes amylose to be hydrolyzed more slowly, but also creates higher density and insolubility. Amylopectin is divided into A and B helical chains of α-glucose. A chains are chains that carry no other chains, resulting in an eventual terminus, whereas B chains are chains that do carry other chains, perpetuating the amylopectin polymer. The ratio between these is usually between 0.8 and 1.4.
89. Mymensingh Med J. 2026 Oct;35(4):1312-1316. Diagnosis of Rhinoentomophthoromycosis in a 55 Years Old Male: A Case Report. Shawrave SA(1), Zoheb SJM, Galib GI, Tanni RZ, Shawon MMR, Bhuiyan MJT. Author information: (1)Dr Shaharior Arafat Shawrave, Associate Professor, Department of ENT and Head Neck Surgery, Dhaka Medical College (DMC), Dhaka, Bangladesh; E-mail: shawrave77@gmail.com. Entomophthoromycosis is a chronic fungal infection characterized by a diverse range of manifestations, including subcutaneous, mucocutaneous and visceral infections. The majority of subcutaneous infections caused by entomophthoralean fungi are attributed to Basidiobolus spp, C. coronatus or C. incongruous. In this report, we present a case of rhinoentomophthoromycosis in a middle-aged, immunocompetent male, primarily affecting the nasopharynx. Initially, the diagnosis posed a dilemma, but it was ultimately confirmed through meticulous examination of microscopy and histopathology of the aspirate. The patient's response to antifungal therapy was favorable. We hereby provide a comprehensive account of this case and discuss the efficacy of Posaconazole in the treatment of rhinoentomophthoromycosis in a 55-year-old male patient with diabetes.
A/B tests are sensitive to variance; they require a large sample size in order to reduce standard error and produce a statistically significant result. In applications in which active users are abundant, such as with popular online social-media platforms, obtaining a large sample size is trivial. In other cases, large sample sizes are obtained by increasing the experiment enrollment period. However, using a technique coined by Microsoft as Controlled Experiment Using Pre-Experiment Data (CUPED), variance from before the experiment start can be taken into account so that fewer samples are required to produce a statistically significant result. Because of its nature as an experiment, running an A/B test introduces the risk of wasted time and resources if the test produces unwanted or unhelpful results. In December 2018, representatives with experience in large-scale A/B testing from 13 organizations (Airbnb, Amazon, Booking.com, Facebook, Google, LinkedIn, Lyft, Microsoft, Netflix, Twitter, Uber and Stanford University) summarized the top challenges in a paper. The challenges were grouped into four areas: analysis, engineering and culture, deviations from traditional A/B tests and data quality.
Where b is binding rate, and k is processing rate. Since the dissociation rate of the substrate-SU complex to (unchanged) substrate and (unbounded) SU is assumed to be small, d θ . d t {\displaystyle {\frac {d\theta _{.}}{dt}}} and d θ S d t {\displaystyle {\frac {d\theta _{S}}{dt}}} are assumed to be zero. This system of equation suggests the free SU percentage is θ . = k b S + k {\displaystyle \theta _{.}={\frac {k}{bS+k}}} and the product of flux is J p = k S S + S / b {\displaystyle J_{p}={\frac {kS}{S+S/b}}} The first modification is an extension of the classic theory; if arrival fluxes are taken proportional to substrate concentrations, the classic theory results. This extension allows application in spatially heterogeneous environments (such as in living cells), and to treat photons and molecules in the same framework (important in photosynthesis).
The hepatocyte is a complex and multifunctional differentiated cell whose cell response will be influenced by the zone in hepatic lobule, because concentrations of oxygen and toxic substances present in the hepatic sinusoids change from periportal zone to centrilobular zone10. The hepatocytes of the intermediate zone have the appropriate morphological and functional features since they have the environment with average concentrations of oxygen and other substances. This specialized cell is capable of:
Sources: en.wikipedia.org
Subfamily ABCC contains thirteen members and nine of these transporters are referred to as the Multidrug Resistance Proteins (MRPs). The MRP proteins are found throughout nature and they mediate many important functions. They are known to be involved in ion transport, toxin secretion, and signal transduction. Of the nine MRP proteins, four of them, MRP4, 5, 8, 9, (ABCC4, 5, 11, and 12), have a typical ABC structure with four domains, comprising two membrane spanning domains, with each spanning domain followed by a nucleotide binding domain. These are referred to as short MRPs. The remaining 5 MRP's (MRP1, 2, 6, 7) (ABCC1, 2, 3, 6 and 10) are known as long MRPs and feature an additional fifth domain at their N terminus. CFTR, the transporter involved in the disease cystic fibrosis, is also considered part of this subfamily. Cystic fibrosis occurs upon mutation and loss of function of CFTR. The sulfonylurea receptors (SUR), involved in insulin secretion, neuronal function, and muscle function, are also part of this family of proteins. Mutations in SUR proteins are a potential cause of Neonatal diabetes mellitus. SUR is also the binding site for drugs such as sulfonylureas and potassium-channel openers activators such as diazoxide.
Many drugs are metabolised by a set of liver enzymes called CYP450s. The activity of these enzymes would determine the rate of pro-drug activation and the rate of inactivation of active drugs. For example, warfarin, a commonly used anticoagulant drug in atrial fibrillation, is metabolised by an enzyme called CYP2C9. Phenytoin, a CYP2C9 inducer, would increase its activity and the rate of warfarin breakdown, thereby reducing its efficacy. Patients should avoid the co-administration of warfarin and phenytoin. In cases where both drugs must be used together, warfarin dosing may be titrated up to cope with the reduced efficacy. The kidney excretes most drugs through urine. Since urine is weakly alkaline in nature, weakly acid drugs would ionise in urine, making it difficult for them to be reabsorbed. Therefore, in cases of aspirin (weak acid) toxicity, injecting intravenous sodium bicarbonate could increase urine pH, thereby increasing the excretion of aspirin through urine. A similar approach can be used in other weakly acidic drug toxicity.
Lectin affinity chromatography is a form of affinity chromatography where lectins are used to separate components within the sample. Lectins, such as concanavalin A are proteins which can bind specific alpha-D-mannose and alpha-D-glucose carbohydrate molecules. Some common carbohydrate molecules that is used in lectin affinity chromatography are Con A-Sepharose and WGA-agarose. Another example of a lectin is wheat germ agglutinin which binds D-N-acetyl-glucosamine. The most common application is to separate glycoproteins from non-glycosylated proteins, or one glycoform from another glycoform. Although there are various ways to perform lectin affinity chromatography, the goal is extract a sugar ligand of the desired protein.
A particular challenge in analysing AlphaFold models is distinguishing genuine topology from structural prediction artefacts. A high confidence score does not by itself guarantee that a predicted chain crossing is correct, and incorrect modelling of termini or flexible regions may change the calculated topology. AlphaKnot 2.0 therefore provides several measures intended to help evaluate a predicted knot, including the pLDDT values of the complete chain and knot core, the confidence near the boundaries of the knot core, and detection of unusually close contacts between Cα atoms. Users can also compare AlphaFold predictions with independently generated ESMFold models for shorter proteins. Because automated analysis at the scale of the AlphaFold database cannot be manually verified structure by structure, AlphaKnot 2.0 introduced a user annotation system. Database entries can be assessed by users as a knot, artifact, or unsure, allowing potentially incorrect predictions to be flagged for further consideration.
Physiologic antagonism refers to the behaviour in which an antagonist behaves the opposite of the agonist but does not bind to the same active site as the agonist does. A physiologic antagonist binds to a different receptor but not the original agonist receptor. Both insulin and glucagon are synthesised naturally in the human body to regulate blood glucose levels at homeostasis. Insulin binds to insulin receptors to decrease blood glucose levels, whilst glucagon binds to glucagon receptors to increase blood glucose levels. In cases of insulin-induced hypoglycaemia, glucagon injection could help increase blood glucose levels. Another example is epinephrine (a bronchodilator) and histamine (a bronchoconstrictor). Epinephrine binds to adrenergic receptors to promote bronchodilation whilst histamine binds to histamine receptors which leads to bronchoconstriction. Since they have opposite effects in different pathways, they are considered physiological antagonists, and they are not advised to be taken together.
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.
Validation establishes suitability for a new method, while verification confirms that a method works in a specific laboratory. Verification is often used when a validated method is adopted with existing equipment and staff. Both rely on documented acceptance criteria.