Progressing From Disparity to Equity: Untangling the Complexities of Timely Care and the Rural Cancer Experience.

Richard L. Martin III, MD, MPH, and Stephen Schleicher, MD, MBA, share a perspective on rural cancer care.

Forming the Hematology-Oncology Collaborative Videoconferencing (CO-VID) Learning Initiative: Experiential Lessons Learned From a Novel Trainee-Led Multidisciplinary Virtual Learning Platform.

PURPOSE: COVID-19 challenged medical practice and graduate medical education. Building on previous initiatives, we describe and reflect on the formative process and goals of the Hematology-Oncology Collaborative Videoconferencing Learning Initiative, a trainee-led multi-institutional virtual COVID-19 learning model. METHODS: Clinical fellows and faculty from 13 US training institutions developed consensus needs, goals, and objectives, recruited presenters, and generated a multidisciplinary COVID-19 curriculum. Weekly Zoom conferences consisted of two trainee-led instructional segments and a trainee-moderated faculty Q&A panel. Hematology-oncology training program faculty and trainees were the targeted audience. Leadership evaluations consisted of anonymized baseline and concluding mixed methods surveys. Presenter evaluations consisted of session debriefs and two structured focus groups. Conference evaluations consisted of attendance, demographics, and pre- or postmultiple-choice questions on topic learning objectives. RESULTS: In 6 weeks, the initiative produced five conferences: antivirals, anticoagulation, pulmonology, provider resilience, and resource scarcity ethics. The average attendance was 100 (range 57-185). Among attendees providing both pre- and postconference data, group-level knowledge appeared to increase: antiviral (n = 46) pre-/postcorrect 82.6%/97.8% and incorrect 10.9%/2.2%, anticoagulation (n = 60) pre-/postcorrect 75%/93.3% and incorrect 15%/6.7%, and pulmonary (n = 21) pre-/postcorrect 66.7%/95.2% and incorrect 33.3%/4.8%. Although pulmonary management comfort appeared to increase, comfort managing of antivirals and anticoagulation was unchanged. At the conclusion of the pilot, leadership trainees reported improved self-confidence organizing multi-institutional collaborations, median (interquartile range) 58.5 (50-64) compared with baseline 34 (26-39), but did not report improved confidence in other educational or leadership skills. CONCLUSION: During crisis, trainees built a multi-institutional virtual education platform for the purposes of sharing pandemic experiences and knowledge. Accomplishment of initiative goals was mixed. Lessons learned from the process and goals may improve future disaster educational initiatives.

Colorectal cancer adjuvant chemotherapy trends among a nonelderly veteran cohort at a southern veterans health administration.

BACKGROUND: For patients with high-risk stage II or stage III colorectal cancer (CRC), adjuvant chemotherapy (AC) improves survival, yet use varies substantially across medical oncology settings. AIM: Utilization of guideline concordant CRC AC was assessed at a Veterans Health Administration (VHA) facility to determine quality improvement initiatives. METHODS AND RESULTS: The study was a retrospective review of CRC surgeries from January 1, 2000 to December 31, 2015 at a South Regional VHA. Inclusion criteria consisted of pathologic high-risk stage II or stage III CRC, with exclusion for age ≥80, age ≥75 hospitalized with major co-morbidity in the prior year, and death or discharge to hospice within 30 days of the index surgery. The primary predictor was year-group; partitioned 2000-2005, 2006-2010, 2011-2015 to account for changes in NCCN high risk stage II definitions. Primary outcome was AC receipt. Secondary outcome was reason for chemotherapy omission. Among 180 eligible surgeries (121 colon and 59 rectal cancers), patients were mostly male (96%), white (79%) and with median age 64 years. Overall, 117 (65%) received AC. Compared to 2000-2005, patients undergoing surgery between 2011 and 2015 were less likely to receive AC (odds ratio 0.35; 95% confidence interval [CI] 0.14-0.82), due to more patients declining AC (27% vs. 6%, p < .01) in the NCCN eligible cohort (N = 180), and (32% vs. 8%, p < .01) in an analysis of patients who completed appointments and had AC recommended by providers (N = 146). CONCLUSIONS: Survival benefitting AC decreased over time among a nonelderly Veteran cohort eligible for AC. Evaluating care decisions and trends within other VHA facilities and outside the VHA are warranted.

Cognitive analysis of metabolomics data for systems biology.

Cognitive computing is revolutionizing the way big data are processed and integrated, with artificial intelligence (AI) natural language processing (NLP) platforms helping researchers to efficiently search and digest the vast scientific literature. Most available platforms have been developed for biomedical researchers, but new NLP tools are emerging for biologists in other fields and an important example is metabolomics. NLP provides literature-based contextualization of metabolic features that decreases the time and expert-level subject knowledge required during the prioritization, identification and interpretation steps in the metabolomics data analysis pipeline. Here, we describe and demonstrate four workflows that combine metabolomics data with NLP-based literature searches of scientific databases to aid in the analysis of metabolomics data and their biological interpretation. The four procedures can be used in isolation or consecutively, depending on the research questions. The first, used for initial metabolite annotation and prioritization, creates a list of metabolites that would be interesting for follow-up. The second workflow finds literature evidence of the activity of metabolites and metabolic pathways in governing the biological condition on a systems biology level. The third is used to identify candidate biomarkers, and the fourth looks for metabolic conditions or drug-repurposing targets that the two diseases have in common. The protocol can take 1-4 h or more to complete, depending on the processing time of the various software used.

Association of Adherence to Quality Metrics with Recurrence or Mortality among Veterans with Colorectal Cancer.

BACKGROUND: The National Comprehensive Cancer Network has defined metrics for colorectal cancer; however, the association of metric adherence with patient clinical outcomes remains underexplored. The study aim was to evaluate the association of National Comprehensive Cancer Network metric adherence with recurrence and mortality in Veterans with nonmetastatic colorectal cancer. METHODS: Veterans with stage I-III colorectal cancer who underwent non-emergent resection from 2001 to 2015 at a single Veterans Affairs Medical Center were included. The primary predictor was completion of eligible National Comprehensive Cancer Network metrics. The primary outcome was a composite of recurrence or all-cause death in three phases of care: surgical (up to 6 months after resection), treatment (6-18 months after resection), and surveillance (18 months-3 years after resection). Hazard ratios were estimated via Cox proportional hazards regression in a propensity score-weighted cohort. RESULTS: A total of 1107 electronic medical records of patients undergoing colorectal surgery were reviewed, and 379 patients were included (301 colon and 78 rectal cancer). In the surgical phase, the weighted analysis yielded a hazard ratio of 0.37 (95% confidence interval 0.12-1.13) for metric-adherent patients compared with non-adherent patients. In the treatment and surveillance phases, the hazard ratios for metric-adherent care were 0.68 (95% confidence interval 0.25-1.85) and 0.91 (95% confidence interval 0.31-2.68), respectively. CONCLUSIONS: The National Comprehensive Cancer Network guideline metric adherence was associated with a lower rate of recurrence and death in the surgical phase of care among stage I-III patients with resected colorectal cancer.

Virtual Colorectal Cancer Surveillance: Bringing Scope Rate to Target.

BACKGROUND: Although endoscopy is recommended at 1 year after colorectal cancer (CRC) resection to detect locally recurrent CRC, earlier work at our Veterans Affairs (VA) facility demonstrated that 35% of patients achieve this metric. STUDY DESIGN: The interdisciplinary team used quality improvement methods to standardize processes and implement a gastroenterology-managed virtual surveillance clinic. The intervention clinic was implemented in August 2014. Veterans who underwent resection for stage I to III CRC at a single VA facility from January 2010 to December 2017 were included, with those undergoing resection between January 2010 and July 2014 considered pre-intervention and those undergoing resection between August 2014 and December 2017 considered post-intervention. The primary endpoint was the proportion of eligible patients for whom endoscopy was completed within 1 year of resection. Secondary outcomes were the proportion of patients who completed endoscopy within 18 months of resection or at any time post-resection and time to surveillance endoscopy. RESULTS: A total of 186 patients underwent resection for stage I to III CRC from 2010 to 2017; of these, 160 (86%) were eligible for endoscopy at 1-year post-resection (98 pre-intervention and 62 post-intervention). In the pre-intervention period, 30 of 98 patients (30.6%) underwent surveillance endoscopy within 1 year vs 31 of 62 (50.0%) post-intervention (p = 0.031). When evaluated at 18 months after resection, 56 of 98 patients (57.1%) in the pre-intervention group vs 52 of 62 (83.9%) in the post-intervention group underwent surveillance endoscopy (p = 0.001). Median time from resection to endoscopy decreased during the study period, from 1.19 years pre-intervention (interquartile range 0.93 to 1.74 years) to 1.0 years post-intervention (interquartile range 0.93 to 1.09 years) (p = 0.006). CONCLUSIONS: Implementation of a virtual surveillance clinic with standardized processes was associated with increased guideline-concordant endoscopic surveillance after CRC resection.

The duality of electron localization and covalency in lanthanide and actinide metallocenes.

Previous magnetic, spectroscopic, and theoretical studies of cerocene, Ce(C8H8)2, have provided evidence for non-negligible 4f-electron density on Ce and implied that charge transfer from the ligands occurs as a result of covalent bonding. Strong correlations of the localized 4f-electrons to the delocalized ligand π-system result in emergence of Kondo-like behavior and other quantum chemical phenomena that are rarely observed in molecular systems. In this study, Ce(C8H8)2 is analyzed experimentally using carbon K-edge and cerium M5,4-edge X-ray absorption spectroscopies (XAS), and computationally using configuration interaction (CI) calculations and density functional theory (DFT) as well as time-dependent DFT (TDDFT). Both spectroscopic approaches provide strong evidence for ligand → metal electron transfer as a result of Ce 4f and 5d mixing with the occupied C 2p orbitals of the C8H8 2- ligands. Specifically, the Ce M5,4-edge XAS and CI calculations show that the contribution of the 4f1, or Ce3+, configuration to the ground state of Ce(C8H8)2 is similar to strongly correlated materials such as CeRh3 and significantly larger than observed for other formally Ce4+ compounds including CeO2 and CeCl6 2-. Pre-edge features in the experimental and TDDFT-simulated C K-edge XAS provide unequivocal evidence for C 2p and Ce 4f covalent orbital mixing in the δ-antibonding orbitals of e2u symmetry, which are the unoccupied counterparts to the occupied, ligand-based δ-bonding e2u orbitals. The C K-edge peak intensities, which can be compared directly to the C 2p and Ce 4f orbital mixing coefficients determined by DFT, show that covalency in Ce(C8H8)2 is comparable in magnitude to values reported previously for U(C8H8)2. An intuitive model is presented to show how similar covalent contributions to the ground state can have different impacts on the overall stability of f-element metallocenes.

Indication of Measures of Uncertainty for Statistical Significance in Abstracts of Published Oncology Trials: A Systematic Review and Meta-analysis.

IMPORTANCE: There is growing consensus that reliance on P values, particularly a cutoff level of .05 for statistical significance, is a factor in the challenges in scientific reproducibility. Despite this consensus, publications describing clinical trial results with P values near .05 anecdotally use declarative statements that do not express uncertainty. OBJECTIVES: To quantify uncertainty expression in abstracts describing the results of cancer randomized clinical trials (RCTs) with P values between .01 and .10 and examine whether trial features are associated with uncertainty expression. DATA SOURCES: A total of 5777 prospective trials indexed on HemOnc.org, as of September 15, 2019. STUDY SELECTION: Two-arm RCTs with a superiority end point with P values between .01 and .10. DATA EXTRACTION AND SYNTHESIS: Abstracts were evaluated based on an uncertainty expression algorithm. Ordinal logistic regression modeling with multiple imputation was performed to identify whether characteristics of study design, results, trial authors, and context P values were normalized by dividing by prespecified α value. MAIN OUTCOMES AND MEASURES: Uncertainty expression in abstracts as determined by the algorithm and its association with trial and publication characteristics. RESULTS: Of 5777 trials screened, 556 met analysis criteria. Of these, 222 trials (39.9%) did not express uncertainty, 161 trials (29.0%) expressed some uncertainty, and 173 trials (31.1%) expressed full uncertainty. In ordinal logistic regression with multiple imputation, trial features with statistically significant associations with uncertainty expression included later year of publication (odds ratio [OR], 1.70; 95% CI, 1.24-2.32; P < .001), normalized P value (OR, 1.36; 95% CI, 1.11-1.67; P = .003), noncooperative group studies (OR, 1.72; 95% CI, 1.12-2.63; P = .01), and reporting an end point other than overall survival (OR, 1.41; 95% CI, 1.01-1.96; P = .047). Funding source, number of authors, journal impact tier, author nationality, study of unapproved drugs, abstract word count, whether the marginal end point was a primary or coprimary end point, and effect size (in subgroup analysis) did not have statistically significant associations with uncertainty expression. CONCLUSIONS AND RELEVANCE: Published oncology articles with marginally significant results may often incompletely convey uncertainty. Although it appears that more uncertainty is expressed in recent abstracts, full uncertainty expression remains uncommon, and seemingly is less common when reporting overall survival, results with P values lower than α levels, and cooperative group studies.

Identification of pharmacodynamic biomarker hypotheses through literature analysis with IBM Watson.

BACKGROUND: Pharmacodynamic biomarkers are becoming increasingly valuable for assessing drug activity and target modulation in clinical trials. However, identifying quality biomarkers is challenging due to the increasing volume and heterogeneity of relevant data describing the biological networks that underlie disease mechanisms. A biological pathway network typically includes entities (e.g. genes, proteins and chemicals/drugs) as well as the relationships between these and is typically curated or mined from structured databases and textual co-occurrence data. We propose a hybrid Natural Language Processing and directed relationships-based network analysis approach using IBM Watson for Drug Discovery to rank all human genes and identify potential candidate biomarkers, requiring only an initial determination of a specific target-disease relationship. METHODS: Through natural language processing of scientific literature, Watson for Drug Discovery creates a network of semantic relationships between biological concepts such as genes, drugs, and diseases. Using Bruton's tyrosine kinase as a case study, Watson for Drug Discovery's automatically extracted relationship network was compared with a prominent manually curated physical interaction network. Additionally, potential biomarkers for Bruton's tyrosine kinase inhibition were predicted using a matrix factorization approach and subsequently compared with expert-generated biomarkers. RESULTS: Watson's natural language processing generated a relationship network matching 55 (86%) genes upstream of BTK and 98 (95%) genes downstream of Bruton's tyrosine kinase in a prominent manually curated physical interaction network. Matrix factorization analysis predicted 11 of 13 genes identified by Merck subject matter experts in the top 20% of Watson for Drug Discovery's 13,595 ranked genes, with 7 in the top 5%. CONCLUSION: Taken together, these results suggest that Watson for Drug Discovery's automatic relationship network identifies the majority of upstream and downstream genes in biological pathway networks and can be used to help with the identification and prioritization of pharmacodynamic biomarker evaluation, accelerating the early phases of disease hypothesis generation.

Energy-Degeneracy-Driven Covalency in Actinide Bonding.

Evaluating the nature of chemical bonding for actinide elements represents one of the most important and long-standing problems in actinide science. We directly address this challenge and contribute a Cl K-edge X-ray absorption spectroscopy and relativistic density functional theory study that quantitatively evaluates An-Cl covalency in AnCl62- (AnIV = Th, U, Np, Pu). The results showed significant mixing between Cl 3p- and AnIV 5f- and 6d-orbitals (t1u*/t2u* and t2 g*/eg *), with the 6d-orbitals showing more pronounced covalent bonding than the 5f-orbitals. Moving from Th to U, Np, and Pu markedly changed the amount of M-Cl orbital mixing, such that AnIV 6d - and Cl 3p-mixing decreased and metal 5f - and Cl 3p-orbital mixing increased across this series.

A hybrid approach for automated mutation annotation of the extended human mutation landscape in scientific literature.

As the cost of DNA sequencing continues to fall, an increasing amount of information on human genetic variation is being produced that could help progress precision medicine. However, information about such mutations is typically first made available in the scientific literature, and is then later manually curated into more standardized genomic databases. This curation process is expensive, time-consuming and many variants do not end up being fully curated, if at all. Detecting mutations in the literature is the first key step towards automating this process. However, most of the current methods have focused on identifying mutations that follow existing nomenclatures. In this work, we show that there is a large number of mutations that are missed by using this standard approach. Furthermore, we implement the first mutation annotator to cover an extended mutation landscape, and we show that its F1 performance is the same performance as human annotation (F1 78.29 for manual annotation vs F1 79.56 for automatic annotation).

Quantitative Evidence for Lanthanide-Oxygen Orbital Mixing in CeO2, PrO2, and TbO2.

Understanding the nature of covalent (band-like) vs ionic (atomic-like) electrons in metal oxides continues to be at the forefront of research in the physical sciences. In particular, the development of a coherent and quantitative model of bonding and electronic structure for the lanthanide dioxides, LnO2 (Ln = Ce, Pr, and Tb), has remained a considerable challenge for both experiment and theory. Herein, relative changes in mixing between the O 2p orbitals and the Ln 4f and 5d orbitals in LnO2 are evaluated quantitatively using O K-edge X-ray absorption spectroscopy (XAS) obtained with a scanning transmission X-ray microscope and density functional theory (DFT) calculations. For each LnO2, the results reveal significant amounts of Ln 5d and O 2p mixing in the orbitals of t2g (σ-bonding) and eg (π-bonding) symmetry. The remarkable agreement between experiment and theory also shows that significant mixing with the O 2p orbitals occurs in a band derived from the 4f orbitals of a2u symmetry (σ-bonding) for each compound. However, a large increase in orbital mixing is observed for PrO2 that is ascribed to a unique interaction derived from the 4f orbitals of t1u symmetry (σ- and π-bonding). O K-edge XAS and DFT results are compared with complementary L3-edge and M5,4-edge XAS measurements and configuration interaction calculations, which shows that each spectroscopic approach provides evidence for ground state O 2p and Ln 4f orbital mixing despite inducing very different core-hole potentials in the final state.

Exposome-Scale Investigations Guided by Global Metabolomics, Pathway Analysis, and Cognitive Computing.

Concurrent exposure to a wide variety of xenobiotics and their combined toxic effects can play a pivotal role in health and disease, yet are largely unexplored. Investigating the totality of these exposures, i.e., the "exposome", and their specific biological effects constitutes a new paradigm for environmental health but still lacks high-throughput, user-friendly technology. We demonstrate the utility of mass spectrometry-based global exposure metabolomics combined with tailored database queries and cognitive computing for comprehensive exposure assessment and the straightforward elucidation of biological effects. The METLIN Exposome database has been redesigned to help identify environmental toxicants, food contaminants and supplements, drugs, and antibiotics as well as their biotransformation products, through its expansion with over 700 000 chemical structures to now include more than 950 000 unique small molecules. More importantly, we demonstrate how the XCMS/METLIN platform now allows for the readout of the biological effect of a toxicant through metabolomic-derived pathway analysis, and further, artificial intelligence provides a means of assessing the role of a potential toxicant. The presented workflow addresses many of the methodological challenges current exposomics research is facing and will serve to gain a deeper understanding of the impact of environmental exposures and combinatory toxic effects on human health.

Increasing Colorectal Cancer Screening at an Urban FQHC Using iFOBT and Patient Navigation.

INTRODUCTION: Colorectal cancer is the second leading cause of cancer death in the United States. Black Americans suffer even higher incidence and death rates than the general population. Genetics and patient perceptions explain some of this difference, however, modifiable health care system factors such as lack of access to colon cancer screening also contribute. Partnering an academic health center with local community groups, we piloted a colorectal cancer screening program at a Federally Qualified Health Center (FQHC) serving predominately low socioeconomic status Black Americans. The program was designed to identify and remove barriers to screening and improve screening rates. METHOD: At a single center FQHC, we developed an outreach program centered around (1) patient and provider education, (2) immunochemical fecal occult blood test (iFOBT) distribution, and (3) patient navigation. We identified 402 eligible patients, of which 228 (56.7%) completed screening. RESULTS: Our 56.7% screening rate represented a twofold increase above prepilot levels at the clinic. Nine (4%) iFOBT returned positive. Three of these nine patients completed colonoscopy. Screening rates and follow through were higher under a single navigator model. CONCLUSIONS: Our academic-community partnership provided an effective, evidence based, and sustainable model for increasing colorectal cancer screening in a high risk, low resource community.

Oxidation and hydration of U3O8 materials following controlled exposure to temperature and humidity.

Chemical signatures correlated with uranium oxide processing are of interest to forensic science for inferring sample provenance. Identification of temporal changes in chemical structures of process uranium materials as a function of controlled temperatures and relative humidities may provide additional information regarding sample history. In this study, a high-purity α-U3O8 sample and three other uranium oxide samples synthesized from reaction routes used in nuclear conversion processes were stored under controlled conditions over 2-3.5 years, and powder X-ray diffraction analysis and X-ray absorption spectroscopy were employed to characterize chemical speciation. Signatures measured from the α-U3O8 sample indicated that the material oxidized and hydrated after storage under high humidity conditions over time. Impurities, such as uranyl fluoride or schoepites, were initially detectable in the other uranium oxide samples. After storage under controlled conditions, the analyses of the samples revealed oxidation over time, although the signature of the uranyl fluoride impurity diminished. The presence of schoepite phases in older uranium oxide material is likely indicative of storage under high humidity and should be taken into account for assessing sample history. The absence of a signature from a chemical impurity, such as uranyl fluoride hydrate, in an older material may not preclude its presence at the initial time of production. LA-UR-15-21495.

In silico prediction of MOFs with high deliverable capacity or internal surface area.

Metal-organic frameworks (MOFs) offer unprecedented atom-scale design and structural tunability, largely due to the vast number of possible organic linkers which can be utilized in their assembly. Exploration of this space of linkers allows identification of ranges of achievable material properties as well as discovery of optimal materials for a given application. Experimental exploration of the linker space has to date been quite limited due to the cost and complexity of synthesis, while high-throughput computational studies have mainly explored MOF materials based on known or readily available linkers. Here an evolutionary algorithm for de novo design of organic linkers for metal-organic frameworks is used to predict MOFs with either high methane deliverable capacity or methane accessible surface area. Known chemical reactions are applied in silico to a population of linkers to discover these MOFs. Through this design strategy, MOF candidates are found in the ten symmetric networks acs, cds, dia, hxg, lvt, nbo, pcu, rhr, sod, and tbo. The correlation between deliverable capacities and surface area is network dependent.

Covalency in lanthanides. An X-ray absorption spectroscopy and density functional theory study of LnCl6(x-) (x = 3, 2).

Covalency in Ln-Cl bonds of Oh-LnCl6(x-) (x = 3 for Ln = Ce(III), Nd(III), Sm(III), Eu(III), Gd(III); x = 2 for Ln = Ce(IV)) anions has been investigated, primarily using Cl K-edge X-ray absorption spectroscopy (XAS) and time-dependent density functional theory (TDDFT); however, Ce L3,2-edge and M5,4-edge XAS were also used to characterize CeCl6(x-) (x = 2, 3). The M5,4-edge XAS spectra were modeled using configuration interaction calculations. The results were evaluated as a function of (1) the lanthanide (Ln) metal identity, which was varied across the series from Ce to Gd, and (2) the Ln oxidation state (when practical, i.e., formally Ce(III) and Ce(IV)). Pronounced mixing between the Cl 3p- and Ln 5d-orbitals (t2g* and eg*) was observed. Experimental results indicated that Ln 5d-orbital mixing decreased when moving across the lanthanide series. In contrast, oxidizing Ce(III) to Ce(IV) had little effect on Cl 3p and Ce 5d-orbital mixing. For LnCl6(3-) (formally Ln(III)), the 4f-orbitals participated only marginally in covalent bonding, which was consistent with historical descriptions. Surprisingly, there was a marked increase in Cl 3p- and Ce(IV) 4f-orbital mixing (t1u* + t2u*) in CeCl6(2-). This unexpected 4f- and 5d-orbital participation in covalent bonding is presented in the context of recent studies on both tetravalent transition metal and actinide hexahalides, MCl6(2-) (M = Ti, Zr, Hf, U).

Evaluation of nitrogen-rich macrocyclic ligands for the chelation of therapeutic bismuth radioisotopes.

INTRODUCTION: The use of α-emitting isotopes for radionuclide therapy is a promising treatment strategy for small micro-metastatic disease. The radioisotope (213)Bi is a nuclide that has found substantial use for targeted α-therapy (TAT). The relatively unexplored aqueous chemistry of Bi(3+), however, hinders the development of bifunctional chelating agents that can successfully deliver these Bi radioisotopes to the tumor cells. Here, a novel series of nitrogen-rich macrocyclic ligands is explored for their potential use as Bi-selective chelating agents. METHODS: The ligands, 1,4,7,10-tetrakis(pyridin-2-ylmethyl)-1,4,7,10-tetraazacyclododecane (L(py)), 1,4,7,10-tetrakis(3-pyridazylmethyl)-1,4,7,10-tetraazacyclododecane (L(pyd)), 1,4,7,10-tetrakis(4-pyrimidylmethyl)-1,4,7,10-tetraazacyclododecane (L(pyr)), and 1,4,7,10-tetrakis(2-pyrazinylmethyl)-1,4,7,10-tetraazacyclododecane (L(pz)), were prepared by a previously reported method and investigated here for their abilities to bind Bi radioisotopes. The commercially available and commonly used ligands 1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid (DOTA) and N-[(R)-2-amino-3-(p-isothiocyanato-phenyl)propyl]-trans-(S,S)- cyclohexane-1,2-diamine-N,N,N',N",N"-pentaacetic acid (CHX-A''-DTPA) were also explored for comparative purposes. Radio-thin-layer chromatography (TLC) was used to measure the binding kinetics and stabilities of the complexes formed. The long-lived isotope, (207)Bi (t(1/2)=32 years), was used for these studies. Density functional theory (DFT) calculations were also employed to probe the ligand interactions with Bi(3+) and the generator parent ion Ac(3+). RESULTS: In contrast to DOTA and CHX-A''-DTPA, these nitrogen-rich macrocycles selectively chelate Bi(3+) in the presence of the parent isotope Ac(3+). Among the four tested, L(py) was found to exhibit optimal Bi(3+)-binding kinetics and complex stability. L(py) complexes Bi(3+) more rapidly than DOTA, yet the resulting complexes are of similar stability. DFT calculations corroborate the experimentally observed selectivity of these ligands for Bi(3+) over Ac(3+). CONCLUSION: Taken together, these data implicate L(py) as a valuable chelating agent for the delivery of (213)Bi. Its selectivity for Bi(3+) and rapid and stable labeling properties warrant further investigation and biological studies.

Synthesis and characterization of nitrogen-rich macrocyclic ligands and an investigation of their coordination chemistry with lanthanum(III).

Derivatives of the ligand 1,4,7,10-tetraazacyclododecane (cyclen) containing pendant N-heterocyclic donors were prepared. The heterocycles pyridine, pyridazine, pyrimidine, and pyrazine were conjugated to cyclen to give 1,4,7,10-tetrakis(pyridin-2-ylmethyl)-1,4,7,10-tetraazacyclododecane (L(py)), 1,4,7,10-tetrakis(3-pyridazylmethyl)-1,4,7,10-tetraazacyclododecane (L(pyd)), 1,4,7,10-tetrakis(4-pyrimidylmethyl)-1,4,7,10-tetraazacyclododecane (L(pyr)), and 1,4,7,10-tetrakis(2-pyrazinylmethyl)-1,4,7,10-tetraazacyclododecane (L(pz)), respectively. The coordination chemistry of these ligands was explored using the La(3+) ion. Accordingly, complexes of the general formula [La(L)(OTf)](OTf)2, where OTf = trifluoromethanesulfonate and L = L(py) (1), L(pyd) (2), L(pyr) (3), and L(pz) (4), were synthesized and characterized by NMR spectroscopy. Crystal structures of 1 and 2 were also determined by X-ray diffraction studies, which revealed 9-coordinate capped, twisted square-antiprismatic coordination geometries for the central La(3+) ion. The conformational dynamics of 1-4 in solution were investigated by variable-temperature NMR spectroscopy. Dynamic line-shape and Eyring analyses enabled the determination of the activation parameters for the interconversion of enantiomeric forms of the complexes. Unexpectedly, the different pendant N-heterocycles of 1-4 give rise to varying values for the enthalpies and entropies of activation for this process. Density functional theory calculations were carried out to investigate the mechanism of this enantiomeric interconversion. Computed activation parameters were consistent with those experimentally determined for 1 but differed somewhat from those of 2-4.