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Record W4400764737 · doi:10.1021/acs.inorgchem.4c02418

Capturing Mercury-197m/g for Auger Electron Therapy and Cancer Theranostic with Sulfur-Containing Cyclen-Based Macrocycles

2024· article· en· W4400764737 on OpenAlexafffund
Marianna Tosato, Parmissa Randhawa, Mattia Asti, Lars Hemmingsen, Catriona Ann O’Shea, Pravena Thaveenrasingam, Stephan P. A. Sauer, Shaohuang Chen, Claudia Graiff, Ileana Menegazzo, Marco Baron, Valery Radchenko, Caterina F. Ramogida, Valerio Di Marco

Bibliographic record

VenueInorganic Chemistry · 2024
Typearticle
Languageen
FieldMedicine
TopicRadiopharmaceutical Chemistry and Applications
Canadian institutionsUniversity of British ColumbiaSimon Fraser UniversityTRIUMF
FundersNational Research Council CanadaCanadian Cancer Society Research InstituteCanadian Institutes of Health ResearchMinistero della SaluteDipartimento di Scienze Chimiche, Università degli Studi di PadovaNatural Sciences and Engineering Research Council of CanadaCanada Research Coordinating Committee
KeywordsChemistryCyclenSulfurCancer therapyMercury (programming language)Combinatorial chemistryNanotechnologyComputational chemistryOrganic chemistryCancer

Abstract

fetched live from OpenAlex

The interest in mercury radioisotopes, 197m Hg ( t 1/2 = 23.8 h) and 197g Hg ( t 1/2 = 64.14 h), has recently been reignited by the dual diagnostic and therapeutic nature of their nuclear decays. These isotopes emit γ-rays suitable for single photon emission computed tomography imaging and Auger electrons which can be exploited for treating small and metastatic tumors. However, the clinical utilization of 197m/g Hg radionuclides is obstructed by the lack of chelators capable of securely binding them to tumor-seeking vectors. This work aims to address this challenge by investigating a series of chemically tailored macrocyclic platforms with sulfur-containing side arms, namely, 1,4,7,10-tetrakis[2-(methylsulfanyl)ethyl]-1,4,7,10-tetraazacyclododecane (DO4S), 1,4,7-tris[2-(methylsulfanyl)ethyl]-1,4,7,10-tetraazacyclododecane (DO3S), and 1,7-bis[2-(methylsulfanyl)ethyl]-1,4,7,10-tetraazacyclododecane-4,10-diacetic acid (DO2A2S). 1,4,7,10-Tetrazacyclododecane-1,4,7,10-tetracetic acid (DOTA), the widest explored chelator in nuclear medicine, and the nonfunctionalized backbone 1,4,7,10-tetrazacyclododecane (cyclen) were considered as well to shed light on the role of the sulfanyl arms in the metal coordination. To this purpose, a comprehensive experimental and theoretical study encompassing aqueous coordination chemistry investigations through potentiometry, nuclear magnetic resonance (NMR) spectroscopy, X-ray crystallography, and density functional theory (DFT) calculations, as well as concentration- and temperature-dependent [ 197m/g Hg]Hg 2+ radiolabeling and in vitro stability assays in human serum was conducted. The obtained results reveal that the investigated chelators rapidly complex Hg 2+ in aqueous media, forming extremely thermodynamically stable 1:1 metal-to-ligand complexes with superior stabilities compared to those of DOTA or cyclen. These complexes exhibited 6- to 8-fold coordination environments, with donors statically bound to the metal center, as evidenced by the presence of 1 H– 199 Hg spin-spin coupling via NMR. A similar octacoordinated environment was also found for DOTA in both solution and solid state, but in this case, multiple slowly exchanging conformers were detected at ambient temperature. The sulfur-rich ligands quantitatively incorporate cyclotron-produced [ 197m/g Hg]Hg 2+ under relatively mild reaction conditions (pH = 7 and T = 50 °C), with the resulting radioactive complexes exhibiting decent stability in human serum (up to 75% after 24 h). By developing viable chelators and understanding the impact of structural modifications, our research addresses the scarcity of suitable chelating agents for 197m/g Hg, offering promise for its future in vivo application as a theranostic Auger-emitter radiometal.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.663

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.022
GPT teacher head0.309
Teacher spread0.287 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations13
Published2024
Admission routes2
Has abstractyes

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