Everything below concerns RP-HPLC. We keep the language plain, cite what the science says, and separate well-supported claims from open questions.
Updated 2026-01-11. Numbers and descriptions here follow the published literature rather than marketing material.
Mass spectrometry provides complementary information about molecular identity and certain impurities. Electrospray ionization and matrix-assisted laser desorption/ionization are common ionization techniques for peptides. A measured mass close to the expected value supports correct sequence length and modifications, while extra mass signals can reveal truncations, adducts, or incomplete deprotection. Mass spectrometry alone is not a quantitative purity assay, because ionization efficiency varies between compounds. Coupling liquid chromatography to mass spectrometry links retention time with mass and helps assign peaks that ultraviolet detection records.
Orthogonal separation methods address impurities that RP-HPLC may not resolve. Size-exclusion chromatography detects aggregates and higher-order species, while ion-exchange chromatography separates charge variants. Capillary electrophoresis can assess charge-to-mass ratios and, in some formats, size-based impurities. Amino acid analysis and nitrogen determination estimate peptide content rather than chromatographic purity. Because each technique has a different selectivity, a complete purity profile usually combines results from more than one method. The choice of method depends on the impurity classes of concern.
Regulatory and accreditation expectations depend on the peptide's intended use. Research reagents may be tested with in-house methods, while pharmaceutical development follows validated procedures and pharmacopeial chapters where applicable. Method validation commonly examines accuracy, precision, specificity, linearity, range, and limits of detection and quantitation. Laboratories accredited to ISO/IEC 17025 must document competence, equipment calibration, and uncertainty. Comparing purity results across laboratories remains difficult because different columns, gradients, detection wavelengths, and integration rules can change reported values; open questions include how best to standardize impurity identification and reporting for diverse peptide products.
Quality control for peptides places purity testing within a documented system that includes specifications, test methods, and acceptance criteria. A certificate of analysis typically reports appearance, chromatographic purity, mass confirmation, and storage conditions. System suitability checks, blank injections, and reference standards help ensure that an analytical run is valid. Traceability requires records of sample preparation, instrument settings, and data processing. No single purity threshold applies to all peptides or uses, so specifications are set according to the intended application and risk assessment.
Sampling and sample preparation influence measured purity. Peptides are often hygroscopic, so weighing should occur quickly under controlled humidity to avoid water uptake. Complete dissolution in a suitable solvent is necessary before injection; undissolved material can block columns or distort results. Filtration removes particulates but may also remove aggregates if the filter pore size is too small. Impurities can originate from synthesis, cleavage, purification, or storage, and forced degradation under heat, light, oxidation, or pH extremes can help identify degradation pathways.
| Property | Value | Notes |
|---|---|---|
| Common separation technique | Reversed-phase HPLC | Separates mainly by hydrophobicity; gradient elution is typical. |
| Typical detection wavelength | 214 nm | Peptide bond absorbance; also detects many organic impurities. |
| Identity confirmation method | LC-MS or MALDI-MS | Provides molecular mass; not a stand-alone quantitative purity measure. |
| Aggregate assessment method | Size-exclusion chromatography | Detects dimers, oligomers, and larger species. |
| Content assessment method | Amino acid analysis | Estimates peptide mass fraction after hydrolysis and separation. |
Impurity profiling identifies and quantifies substances that coexist with the target peptide. These include deletion sequences, truncated peptides, oxidized variants, and residual protecting groups from synthesis. Reversed-phase chromatography can separate many of these impurities, but co-elution remains a challenge for closely related species. Mass spectrometry helps assign identities to impurity peaks, and impurity limits are often set as area percentages relative to the main peak. Regulatory guidelines for research-grade peptides are less strict than those for therapeutic products, so specifications vary by supplier.
Quality control for peptides involves setting specifications for identity, purity, and counterion content. Batches are tested against these specifications before release. Purity specifications often require a minimum area percentage by high-performance liquid chromatography, such as 95% or 98%, depending on the intended application. Additional tests may include water content, acetate or trifluoroacetate content, and residual solvents. These parameters affect the net peptide content and the accuracy of subsequent laboratory experiments.
Sample handling influences measured purity. Lyophilized peptides are hygroscopic and can absorb water, changing weight-based calculations, while repeated freeze-thaw cycles may promote aggregation or degradation. Dissolved samples should be prepared fresh when possible and protected from light and heat. In purity testing, the same handling conditions should apply to standards and samples. Stability-indicating methods are designed to separate degradation products from the parent peptide, though open questions remain about how accelerated stability data predict long-term behavior for every sequence.
Peptide purity testing distinguishes several impurity classes. Related substances include truncated sequences, deletion peptides, and diastereomers formed during synthesis, while residual solvents, counterions, and water are not peptide-related but affect mass balance. Aggregates and oxidation products can arise during storage. Each class requires different analytical approaches, and a complete purity profile combines separation, mass measurement, and orthogonal assays. Reporting only a single percentage can obscure which impurities are present, so the profile should name the methods and limits used.
Quality control relies on predefined specifications rather than a single purity number. A certificate of analysis typically lists the test method, acceptance limit, and measured result for each attribute. Common specifications include appearance, peptide content, water content, counterion identity, and related substances. Limits are set according to the peptide's intended use and the capability of the analytical method. A result outside a limit triggers investigation, not automatic rejection, because method variability and sample handling can affect outcomes.
== Career == Thomsen worked as a pharmacologist at Leo Pharma from 1989 to 1991 and was thereafter employed by Novo Nordisk in as head of Growth Hormone Research. He became senior vice president for diabetes R&D in 1994 and was appointed senior vice president of Health Care Discovery in 1995. In November 2000, he was appointed executive vice president of Global R&D and chief scientific officer (CSO). As chief scientific officer, he was responsible for the research and development of 20 medicine products within diabetes, obesity and biopharmaceuticals. He led the development of GLP-1 therapies that today are among the leading treatments within type 2 diabetes and obesity. He left the position as executive vice president of R&D on February 28, 2021, and took the role as CEO of the Novo Nordisk Foundation on March 1, 2021. He has been the president of the Danish Academy of Technical Sciences and has been on the board of directors at the Technical University of Denmark (DTU) and University of Copenhagen. From 2017 to 2020, Thomsen was the chairman of the board of directors at University of Copenhagen. Mads Krogsgaard Thomsen received the royal decoration of Knight of the Order of the Dannebrog by the Danish Royal House on 12 December 2022. In 2024, Thomsen received the Golden Plate Award of the American Academy of Achievement, presented by Awards Council member Robert S. Langer.
=== Displacement === After the entire sample is loaded, the feed is switched to the displacer, chosen to have higher affinity than any sample component. The displacer forms a sharp-edged zone at the head of the column, pushing the other components downstream. Each sample component now acts as a displacer for the lower-affinity solutes, and the solutes sort themselves out into a series of contiguous bands (a "displacement train"), all moving downstream at the rate set by the displacer. The size and loading of the column are chosen to let this sorting process reach completion before the components reach the bottom of the column. The solutes appear at the bottom of the column as a series of contiguous zones, each consisting of one purified component, with the concentration within each individual zone effectively uniform.
=== Therapeutic opportunities === The ribosome is a prominent drug target for antibacterials, which interfere with translation at different stages of the elongation cycle Most clinically relevant translation compounds are inhibitors of bacterial translation, but inhibitors of eukaryotic translation may also hold therapeutic potential for application in cancer or antifungal chemotherapy. Elongation inhibitors show antitumor activity 'in vivo' and 'in vitro'. One toxic inhibitor of eukaryotic translation elongation is the glutarimide antibiotic cycloheximide (CHX), which has been co-crystallized with the eukaryotic 60S subunit and binds in the ribosomal E site. The structural characterization of the eukaryotic ribosome may enable the use of structure-based methods for the design of novel antibacterials, wherein differences between the eukaryotic and bacterial ribosomes can be exploited to improve the selectivity of drugs and therefore reduce adverse effects.
"In it, the distress, caused by thirst, to travellers, was alleviated by clusters of rays of the bright eyes of the girls; the rays that were shaming the currents of light, sweet and cold water charged with the strong fragrance of cardamom, clove, saffron, camphor and musk and flowing out of the pitchers (held in) the lotus-like hands of maidens (seated in) the beautiful water-sheds, made of the thick roots of vetiver mixed with marjoram, (and built near) the foot, covered with heaps of couch-like soft sand, of the clusters of newly sprouting mango trees, which constantly darkened the intermediate space of the quarters, and which looked all the more charming on account of the trickling drops of the floral juice, which thus caused the delusion of a row of thick rainy clouds, densely filled with abundant nectar."
==== Blood stains ==== There are several reddish stains on the shroud suggesting blood. McCrone (see painting hypothesis) showed that these contain iron oxide, and theorized that its presence was likely due to simple pigment materials used in medieval times. While the forensic doctor Pierluigi Baima Bollone initially claimed in 1983 to have identified type AB human blood along with traces of serum, aloes, and myrrh, this conclusion was later challenged by researchers like Alan Adler and more recently Kelly Kearse, who noted that early testing methods could not definitively confirm ancient human blood due to degradation and potential contamination. Skeptics cite forensic blood tests whose results dispute the authenticity of the Shroud, and point to the possibility that the blood could belong to a person who handled the shroud, and that the apparent blood flows on the shroud are unrealistically neat. As of 2025, it has not been scientifically demonstrated that the blood is of human, or even primate, origin.
Sources: en.wikipedia.org
== Taxonomy == Carl Linnaeus described the species in 1771, the specific epithet biloba derived from the Latin bis, "twice" and loba, "lobed", referring to the shape of the leaves. Two names for the species recognise the botanist Richard Salisbury, a placement by Nelson as Pterophyllus salisburiensis and the earlier Salisburia adiantifolia proposed by James Edward Smith. The epithet of the latter may have been intended to denote a characteristic resembling Adiantum, the genus of maidenhair ferns. The generic name Ginkgo can be traced to recordings done by Engelbert Kaempfer, the first Westerner to investigate the species in 1690 in Nagasaki, for the Amoenitates Exoticae (1712): it is regarded as a mistranscription of Japanese 銀杏 ginkyō ([ɡiŋkʲoː]). Taking his spelling of other Japanese words containing the syllable [kʲoː] (present romanization: kyō) into account, an expected transcription would have been "ginkio" or "ginkjo". Thus, his curious "–kgo" spelling has long been considered to be an error Kaempfer made in his notes, but Nagata et al. showed that it was the spelling of his interpreter, Genemon Imamura, who spoke the local Nagasaki dialect. Linnaeus adopted the ginkgo spelling based on Kaempfer's compilation of Japanese flora in Amoenitates while writing Mantissa plantarum II (Amoenitates Exoticae, p. 811) thus becoming the tree's generic name. Kaempfer's drawing can be found in Hori's article.
=== Applications === (Q)SAR models have been used for risk management. QSARS are suggested by regulatory authorities; in the European Union, QSARs are suggested by the REACH regulation, where "REACH" abbreviates "Registration, Evaluation, Authorisation and Restriction of Chemicals". Regulatory application of QSAR methods includes in silico toxicological assessment of genotoxic impurities. Commonly used QSAR assessment software such as DEREK or CASE Ultra (MultiCASE) is used to genotoxicity of impurity according to ICH M7. The chemical descriptor space whose convex hull is generated by a particular training set of chemicals is called the training set's applicability domain. Prediction of properties of novel chemicals that are located outside the applicability domain uses extrapolation, and so is less reliable (on average) than prediction within the applicability domain. The assessment of the reliability of QSAR predictions remains a research topic, as a unified strategy has yet to be adopted by modellers and regulatory authorities. The QSAR equations can be used to predict biological activities of newer molecules before their synthesis. Examples of machine learning tools for QSAR modeling include:
Dinosaurs diverged from their archosaur ancestors during the Middle to Late Triassic epochs, roughly 20 million years after the devastating Permian–Triassic extinction event wiped out an estimated 96% of all marine species and 70% of terrestrial vertebrate species approximately 252 million years ago. The oldest dinosaur fossils known from substantial remains date to the Carnian epoch of the Triassic period and have been found primarily in the Ischigualasto and Santa Maria Formations of Argentina and Brazil, and the Pebbly Arkose Formation of Zimbabwe. The Ischigualasto Formation (radiometrically dated at 231–230 million years old) has produced the early saurischian Eoraptor, originally considered a member of the Herrerasauridae but now considered to be an early sauropodomorph, along with the herrerasaurids Herrerasaurus and Sanjuansaurus, and the sauropodomorphs Chromogisaurus, Eodromaeus, and Panphagia. Eoraptor's likely resemblance to the common ancestor of all dinosaurs suggests that the first dinosaurs would have been small, bipedal predators. The Santa Maria Formation (radiometrically dated to be older, at 233.23 million years old) has produced the herrerasaurids Gnathovorax and Staurikosaurus, along with the sauropodomorphs Bagualosaurus, Buriolestes, Guaibasaurus, Macrocollum, Nhandumirim, Pampadromaeus, Saturnalia, and Unaysaurus. The Pebbly Arkose Formation, which is of uncertain age but was likely comparable to the other two, has produced the sauropodomorph Mbiresaurus, along with an unnamed herrerasaurid.
Agmatine is a cationic amine formed by decarboxylation of L-arginine by the mitochondrial enzyme arginine decarboxylase (ADC). Agmatine degradation occurs mainly by hydrolysis, catalyzed by agmatinase into urea and putrescine, the diamine precursor of polyamine biosynthesis. An alternative pathway, mainly in peripheral tissues, is by diamine oxidase-catalyzed oxidation into agmatine-aldehyde, which is in turn converted by aldehyde dehydrogenase into guanidinobutyrate and secreted by the kidneys.
== External links == Media related to Romanian Revolution of 1989 at Wikimedia Commons Article on justice failing for 942 killed in Revolution on eve of 20th anniversary Video of Nicolae Ceaușescu's final speech in Republican Square Anonymous Photo Essay about the Romanian Revolution of 1989 TV broadcasts from 22 and 23 December 1989 Live TV Broadcast from 22 December 1989 on Hungarian TV (with English subtitles) The Romanian Revolution of December 1989 Academic Article on Feature Films about 1989 Academic Article on Documentaries about 1989
Sources: en.wikipedia.org
RP-HPLC purity is the relative area of the main peptide peak compared with the total integrated peak area. It reflects ultraviolet-absorbing species under one set of separation conditions. It does not identify every impurity or measure biological activity.
Chromatographic conditions such as column chemistry, gradient slope, mobile-phase additives, and detection wavelength affect peak resolution. Sample preparation and integration rules also influence area percent values. Without a shared reference standard and validated method, direct comparisons remain uncertain.
Purity describes the proportion of the main peak among detected components. Peptide content measures the amount of the target peptide in a sample after accounting for counterions, water, and residual salts. A sample can have high chromatographic purity but lower net peptide content.
A certificate of analysis reports test results, methods, and specifications for a peptide lot. It often includes appearance, purity by chromatography, mass confirmation, and storage recommendations. It supports quality assessment but does not by itself guarantee suitability for every application.