Synthesis of Ru(II) and Os(II) photosensitizers bearing one 9,10-diamino-1,4,5,8-tetraazaphenanthrene scaffold.

The synthesis of eight Ru(II) and Os(II) photosensitizers bearing a common 9,10-disubstituted-1,4,5,8-tetraazaphenanthrene backbone is reported. With Os(II) photosensitizers, the 9,10-diNH2-1,4,5,8-tetraazaphenanthrene could be directly chelated onto the metal center via the heteroaromatic moiety, whereas similar conditions using Ru(II) resulted in the formation of an o-quinonediimine derivative. Hence, an alternative route, proceeding via the chelation of 9-NH2-10-NO2-1,4,5,8-tetraazaphenanthrene and subsequent ligand reduction of the corresponding photosensitizers was developed. Photosensitizers chelated via the polypyridyl-type moiety exhibited classical photophysical properties whereas the o-quinonediimine chelated Ru(II) analogues exhibited red-shifted absorption (520 nm) and no photoluminescence at room temperature in acetonitrile. The most promising photosensitizers were investigated for excited-state quenching with guanosine-5'-monophosphate in aqueous buffered conditions where reductive excited-state electron transfer was observed by nanosecond transient absorption spectroscopy.

Unlocking the genomic landscape: Results of the Beyond 1 Million Genomes (B1MG) pilot in Belgium towards Genomic Data Infrastructure (GDI).

Genomic medicine has great potential to offer insights into how humans' genetic variation can affect their health, prevention options and treatment responses. The Beyond 1 Million Genomes (B1MG) project was kicked off in 2020 with the aim of building a federated network of genomic data in Europe, in which Belgium took part as a piloting country. B1MG developed a framework to enable all interested countries to self-evaluate the level of maturity of national genomic medicine practices following a common matrix, called Maturity Level Model (MLM), that contained 49 indicators across eight domains: I. Governance and strategy; II. Investment and economic model; III. Ethics, legislation and policy; IV. Public awareness and acceptance; V. Workforce skills and organisation; VI. Clinical organisation, infrastructure and tools; VII. Clinical genomics guidelines and infrastructure; and VIII. Data management, standards and infrastructure. The ongoing Genomic Data Infrastructure (GDI) project aims to capitalise on the experience of B1MG piloting countries and their MLM results. In this paper, we present the qualitative and quantitative outcomes of B1MG MLM assessment in Belgium and discuss their relevance to GDI. The insights gained from this study can be helpful for steering future policy directions and interventions on genomics in Belgium and beyond.

Contextual factors influencing the equitable implementation of precision medicine in routine cancer care in Belgium.

BACKGROUND: Precision medicine represents a paradigm shift in health systems, moving from a one-size-fits-all approach to a more individualized form of care, spanning multiple scientific disciplines including drug discovery, genomics, and health communication. This study aims to explore the contextual factors influencing the equitable implementation of precision medicine in Belgium for incorporating precision medicine into routine cancer care within the Belgian health system. METHODS: As part of a foresight study, our approach evaluates critical factors affecting the implementation of precision oncology. The study scrutinizes contextual, i.e. demographic, economic, societal, technological, environmental, and political/policy-related (DESTEP) factors, identified through a comprehensive literature review and validated by a multidisciplinary group at the Belgian Cancer Center, Sciensano. An expert survey further assesses the importance and likelihood of these factors, illuminating potential barriers and facilitators to implementation. RESULTS: Based on the expert survey, five key elements (rising cancer rates, dedicated healthcare reimbursement budgets, increasing healthcare expenditures, advanced information technology solutions for data transfer, and demand for high-quality data) are expected to influence the equitable implementation of precision medicine in routine cancer care in Belgium in the future. CONCLUSIONS: This work contributes to the knowledge base on precision medicine in Belgium and public health foresight, exploring the implementation challenges and suggesting solutions with an emphasis on the importance of comparative analyses of health systems, evaluation of health technology assessment methods, and the exploration of ethical issues in data privacy and equity.

Photosensitized Activation of Diazonium Derivatives for C-B Bond Formation.

Aryl diazonium salts are ubiquitous building blocks in chemistry, as they are useful radical precursors in organic synthesis as well as for the functionalization of solid materials. They can be reduced electrochemically or through a photo-induced electron transfer reaction. Here we provide a detailed picture of the ground and excited-state reactivity of a series of 9 rare and earth abundant photosensitizers with 13 aryl diazonium salts, which also included 3 macrocyclic calix[4]arene tetradiazonium salts. Nanosecond transient absorption spectroscopy confirmed the occurrence of excited-state electron transfer and was used to quantify cage-escape yields, i.e. the efficiency with which the formed radicals separate and escape the solvent cage. Cage-escape yields were large; increased when the driving force for photo-induced electron transfer increased and also tracked with the C-N2 + bond cleavage propensity, amongst others. A photo-induced borylation reaction was then investigated with all the photosensitizers and proceeded with yields between 9 and 74%.

Homologous and Heterologous Prime-Boost Vaccination: Impact on Clinical Severity of SARS-CoV-2 Omicron Infection among Hospitalized COVID-19 Patients in Belgium.

We investigated effectiveness of (1) mRNA booster vaccination versus primary vaccination only and (2) heterologous (viral vector-mRNA) versus homologous (mRNA-mRNA) prime-boost vaccination against severe outcomes of BA.1, BA.2, BA.4 or BA.5 Omicron infection (confirmed by whole genome sequencing) among hospitalized COVID-19 patients using observational data from national COVID-19 registries. In addition, it was investigated whether the difference between the heterologous and homologous prime-boost vaccination was homogenous across Omicron sub-lineages. Regression standardization (parametric g-formula) was used to estimate counterfactual risks for severe COVID-19 (combination of severity indicators), intensive care unit (ICU) admission, and in-hospital mortality under exposure to different vaccination schedules. The estimated risk for severe COVID-19 and in-hospital mortality was significantly lower with an mRNA booster vaccination as compared to only a primary vaccination schedule (RR = 0.59 [0.33; 0.85] and RR = 0.47 [0.15; 0.79], respectively). No significance difference was observed in the estimated risk for severe COVID-19, ICU admission and in-hospital mortality with a heterologous compared to a homologous prime-boost vaccination schedule, and this difference was not significantly modified by the Omicron sub-lineage. Our results support evidence that mRNA booster vaccination reduced the risk of severe COVID-19 disease during the Omicron-predominant period.

Evaluating methodological approaches to assess the severity of infection with SARS-CoV-2 variants: scoping review and applications on Belgian COVID-19 data.

BACKGROUND: Differences in the genetic material of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants may result in altered virulence characteristics. Assessing the disease severity caused by newly emerging variants is essential to estimate their impact on public health. However, causally inferring the intrinsic severity of infection with variants using observational data is a challenging process on which guidance is still limited. We describe potential limitations and biases that researchers are confronted with and evaluate different methodological approaches to study the severity of infection with SARS-CoV-2 variants. METHODS: We reviewed the literature to identify limitations and potential biases in methods used to study the severity of infection with a particular variant. The impact of different methodological choices is illustrated by using real-world data of Belgian hospitalized COVID-19 patients. RESULTS: We observed different ways of defining coronavirus disease 2019 (COVID-19) disease severity (e.g., admission to the hospital or intensive care unit versus the occurrence of severe complications or death) and exposure to a variant (e.g., linkage of the sequencing or genotyping result with the patient data through a unique identifier versus categorization of patients based on time periods). Different potential selection biases (e.g., overcontrol bias, endogenous selection bias, sample truncation bias) and factors fluctuating over time (e.g., medical expertise and therapeutic strategies, vaccination coverage and natural immunity, pressure on the healthcare system, affected population groups) according to the successive waves of COVID-19, dominated by different variants, were identified. Using data of Belgian hospitalized COVID-19 patients, we were able to document (i) the robustness of the analyses when using different variant exposure ascertainment methods, (ii) indications of the presence of selection bias and (iii) how important confounding variables are fluctuating over time. CONCLUSIONS: When estimating the unbiased marginal effect of SARS-CoV-2 variants on the severity of infection, different strategies can be used and different assumptions can be made, potentially leading to different conclusions. We propose four best practices to identify and reduce potential bias introduced by the study design, the data analysis approach, and the features of the underlying surveillance strategies and data infrastructure.

Red Absorbing Cyclometalated Ir(III) Diimine Photosensitizers Competent for Hydrogen Photocatalysis.

Two new cyclometalated Ir(III) diimine complexes were used as photosensitizers for homogeneous hydrogen evolution reaction (HER). These complexes were characterized by electrochemistry, ultraviolet-visible absorption, time-resolved and steady-state photoluminescence spectroscopy as well as by theoretical methods. The metal-ligand-to-ligand charge transfer character of their lowest excited state was shown to be competent for efficient H2 photoproduction in the presence of [Co(dmgH)2(py)Cl] as the hydrogen evolution catalyst, triethanolamine as the sacrificial electron donor, and HBF4 as the proton source. Under optimized experimental conditions, both complexes displayed HER over a period of more than 90 h, with turnover numbers reaching up to 11,650, 10,600, and 174 molH2 molPS-1 under blue-, green-, and red-light irradiation, respectively. Both complexes showed higher stability and efficiency vs HER than most of the previously described systems of the same kind.

Accessing Photoredox Transformations with an Iron(III) Photosensitizer and Green Light.

Efficient excited-state electron transfer between an iron(III) photosensitizer and organic electron donors was realized with green light irradiation. This advance was enabled by the use of the previously reported iron photosensitizer, [Fe(phtmeimb)2]+ (phtmeimb = {phenyl[tris(3-methyl-imidazolin-2-ylidene)]borate}, that exhibited long-lived and luminescent ligand-to-metal charge-transfer (LMCT) excited states. A benchmark dehalogenation reaction was investigated with yields that exceed 90% and an enhanced stability relative to the prototypical photosensitizer [Ru(bpy)3]2+. The initial catalytic step is electron transfer from an amine to the photoexcited iron sensitizer, which is shown to occur with a large cage-escape yield. For LMCT excited states, this reductive electron transfer is vectorial and may be a general advantage of Fe(III) photosensitizers. In-depth time-resolved spectroscopic methods, including transient absorption characterization from the ultraviolet to the infrared regions, provided a quantitative description of the catalytic mechanism with associated rate constants and yields.

Tuning the excited-state deactivation pathways of dinuclear ruthenium(ii) 2,2'-bipyridine complexes through bridging ligand design.

A detailed photophysical investigation of two dinuclear ruthenium(ii) complexes is reported. The two metallic centers were coordinated to a bis-2,2'-bipyridine bridging ligand, connected either through the para (Lp, Dp) or the meta position (Lm, Dm). The results obtained herein were compared to the prototypical [Ru(bpy)3]2+ parent compound. The formation of dinuclear complexes was accompanied by the expected increase in molar absorption coefficients, i.e. 12 000 M-1 cm-1, 17 000 M-1 cm-1, and 22 000 M-1 cm-1 at the lowest energy MLCTmax transition for [Ru(bpy)3]2+, Dm and Dp respectively. The Lp bridging ligand resulted in a ruthenium(ii) dinuclear complex that absorbed more visible light, and had a longer-lived and more delocalized excited-state compared to a complex with the Lm bridging ligand. Variable temperature measurements provided valuable information about activation energies to the uppermost 3MLCT state and the metal-centered (3MC) state, often accompanied by irreversible ligand-loss chemistry. At 298 K, 48% of [Ru(bpy)3]2+* excited-state underwent deactivation through the 3MC state, whereas this deactivation pathway remained practically unpopulated (<0.5%) in both dinuclear complexes.

Photo-CIDNP Reveals Different Protonation Sites Depending on the Primary Step of the Photoinduced Electron-/Proton-Transfer Process with Ru(II) Polyazaaromatic Complexes.

The excited-state quenching of [Ru(TAP)2(HAT)]2+ (TAP = 1,4,5,8-tetraazaphenanthrene, HAT= 1,4,5,8,9,12-hexaazatriphenylene) by hydroquinone (H2Q), N-acetyl-tyrosine (N-Ac-Tyr) or guanosine-5'-monophosphate (GMP) was investigated at various pH values. The quenching occurs via electron/proton transfer, as evidenced by transient absorption spectroscopy and confirmed by 1H photochemically induced dynamic nuclear polarization (photo-CIDNP). Reductive quenching also occurs in strongly acidic solution despite a much shorter lifetime of the protonated excited-state complex. Photo-CIDNP revealed a different mechanism at low pH, involving protonation before electron transfer and yielding a distinct protonated monoreduced complex. The experimental photo-CIDNP patterns are consistent with density functional theory calculations. This work highlights the power of 1H photo-CIDNP for characterizing, at the atomic level, transient species involved in electron-transfer processes.

How Can Viral Dynamics Models Inform Endpoint Measures in Clinical Trials of Therapies for Acute Viral Infections?

Acute viral infections pose many practical challenges for the accurate assessment of the impact of novel therapies on viral growth and decay. Using the example of influenza A, we illustrate how the measurement of infection-related quantities that determine the dynamics of viral load within the human host, can inform investigators on the course and severity of infection and the efficacy of a novel treatment. We estimated the values of key infection-related quantities that determine the course of natural infection from viral load data, using Markov Chain Monte Carlo methods. The data were placebo group viral load measurements collected during volunteer challenge studies, conducted by Roche, as part of the oseltamivir trials. We calculated the values of the quantities for each patient and the correlations between the quantities, symptom severity and body temperature. The greatest variation among individuals occurred in the viral load peak and area under the viral load curve. Total symptom severity correlated positively with the basic reproductive number. The most sensitive endpoint for therapeutic trials with the goal to cure patients is the duration of infection. We suggest laboratory experiments to obtain more precise estimates of virological quantities that can supplement clinical endpoint measurements.

Using Clinical Trial Simulators to Analyse the Sources of Variance in Clinical Trials of Novel Therapies for Acute Viral Infections.

BACKGROUND: About 90% of drugs fail in clinical development. The question is whether trials fail because of insufficient efficacy of the new treatment, or rather because of poor trial design that is unable to detect the true efficacy. The variance of the measured endpoints is a major, largely underestimated source of uncertainty in clinical trial design, particularly in acute viral infections. We use a clinical trial simulator to demonstrate how a thorough consideration of the variability inherent in clinical trials of novel therapies for acute viral infections can improve trial design. METHODS AND FINDINGS: We developed a clinical trial simulator to analyse the impact of three different types of variation on the outcome of a challenge study of influenza treatments for infected patients, including individual patient variability in the response to the drug, the variance of the measurement procedure, and the variance of the lower limit of quantification of endpoint measurements. In addition, we investigated the impact of protocol variation on clinical trial outcome. We found that the greatest source of variance was inter-individual variability in the natural course of infection. Running a larger phase II study can save up to $38 million, if an unlikely to succeed phase III trial is avoided. In addition, low-sensitivity viral load assays can lead to falsely negative trial outcomes. CONCLUSIONS: Due to high inter-individual variability in natural infection, the most important variable in clinical trial design for challenge studies of potential novel influenza treatments is the number of participants. 100 participants are preferable over 50. Using more sensitive viral load assays increases the probability of a positive trial outcome, but may in some circumstances lead to false positive outcomes. Clinical trial simulations are powerful tools to identify the most important sources of variance in clinical trials and thereby help improve trial design.

Understanding the within-host dynamics of influenza A virus: from theory to clinical implications.

Mathematical models have provided important insights into acute viral dynamics within individual patients. In this paper, we study the simplest target cell-limited models to investigate the within-host dynamics of influenza A virus infection in humans. Despite the biological simplicity of the models, we show how these can be used to understand the severity of the infection and the key attributes of possible immunotherapy and antiviral drugs for the treatment of infection at different times post infection. Through an analytic approach, we derive and estimate simple summary biological quantities that can provide novel insights into the infection dynamics and the definition of clinical endpoints. We focus on nine quantities, including the area under the viral load curve, peak viral load, the time to peak viral load and the level of cell death due to infection. Using Markov chain Monte Carlo methods, we fitted the models to data collected from 12 untreated volunteers who participated in two clinical studies that tested the antiviral drugs oseltamivir and zanamivir. Based on the results, we also discuss various difficulties in deriving precise estimates of the parameters, even in the very simple models considered, when experimental data are limited to viral load measures and/or there is a limited number of viral load measurements post infection.

Sequence dependence of electron-induced DNA strand breakage revealed by DNA nanoarrays.

The electronic structure of DNA is determined by its nucleotide sequence, which is for instance exploited in molecular electronics. Here we demonstrate that also the DNA strand breakage induced by low-energy electrons (18 eV) depends on the nucleotide sequence. To determine the absolute cross sections for electron induced single strand breaks in specific 13 mer oligonucleotides we used atomic force microscopy analysis of DNA origami based DNA nanoarrays. We investigated the DNA sequences 5'-TT(XYX)3TT with X = A, G, C and Y = T, BrU 5-bromouracil and found absolute strand break cross sections between 2.66 · 10(-14) cm(2) and 7.06 · 10(-14) cm(2). The highest cross section was found for 5'-TT(ATA)3TT and 5'-TT(ABrUA)3TT, respectively. BrU is a radiosensitizer, which was discussed to be used in cancer radiation therapy. The replacement of T by BrU into the investigated DNA sequences leads to a slight increase of the absolute strand break cross sections resulting in sequence-dependent enhancement factors between 1.14 and 1.66. Nevertheless, the variation of strand break cross sections due to the specific nucleotide sequence is considerably higher. Thus, the present results suggest the development of targeted radiosensitizers for cancer radiation therapy.

On the coupling of solvent characteristics to the electronic structure of solute molecules.

We present the results of a theoretical investigation focusing on the solvent structure surrounding the -1, 0 and +1 charged species of F, Cl, Br and I halogen atoms and F2, Cl2, Br2 and I2 di-halogen molecules in a methanol solvent and its influence on the electronic structure of the solute molecules. Our results show a large stabilizing effect arising from the solute-solvent interactions. Well-formed first solvation shells are observed for all species, the structure of which is strongly influenced by the charge of the solute species. Detailed analysis reveals that coordination number, CN, solvent orientation, θ, and solute-solvent distance, d, are important structural characteristics which are coupled to changes in the electronic structure of the solute. We propose that the fundamental chemistry of any solute species is generally regulated by these solvent degrees of freedom.

Benchmarking DFT and TD-DFT Functionals for the Ground and Excited States of Hydrogen-Rich Peptide Radicals.

We assess the pros and cons of a large panel of DFT exchange-correlation functionals for the prediction of the electronic structure of hydrogen-rich peptide radicals formed after electron attachment on a protonated peptide. Indeed, despite its importance in the understanding of the chemical changes associated with the reduction step, the question of the attachment site of an electron and, more generally, of the reduced species formed in the gas phase through electron-induced dissociation (ExD) processes in mass spectrometry is still a matter of debate. For hydrogen-rich peptide radicals in which several positive groups and low-lying π* orbitals can capture the incoming electron in ExD, inclusion of full Hartree-Fock exchange at long-range interelectronic distance is a prerequisite for an accurate description of the electronic states, thereby excluding several popular exchange-correlation functionals, e.g., B3LYP, M06-2X, or CAM-B3LYP. However, we show that this condition is not sufficient by comparing the results obtained with asymptotically correct range-separated hybrids (M11, LC-BLYP, LC-BPW91, ωB97, ωB97X, and ωB97X-D) and with reference CASSCF-MRCI and EOM-CCSD calculations. The attenuation parameter ω significantly tunes the spin density distribution and the excited states vertical energies. The investigated model structures, ranging from methylammonium to hexapeptide, allow us to obtain a description of the nature and energy of the electronic states, depending on (i) the presence of hydrogen bond(s) around the cationic site(s), (ii) the presence of π* molecular orbitals (MOs), and (iii) the selected DFT approach. It turns out that, in the present framework, LC-BLYP and ωB97 yields the most accurate results.

Peculiar properties of homoleptic Cu complexes with dipyrromethene derivatives.

In view of preparing Cu polynuclear complexes with dipyrromethene ligands, the mononuclear complexes [Cu(II)(dipy)2] (dipyH = 5-phenyldipyrromethene) and [Cu(II)(dpdipy)2] (dpdipyH = 1,5,9-triphenyldipyrromethene) have been prepared and characterized by X-ray crystallography, mass spectrometry and EPR spectroscopy. Their peculiar redox and spectroscopic (absorption/emission) behaviours are discussed. In contrast to Cu(II) complexes of 1,1'-bidypyrrin, the reduction electrolysis of [Cu(II)(dpdipy)2] leads to decomposition products on a time scale of a few hours. Moreover in relation to this observation, [Cu(I)(dpdipy)2](-) could not be synthesized in spite of the Cu(I) core protection by the phenyl substituents in ortho position of the nitrogen atoms. Theoretical calculations provide some explanations for this instability. Interestingly [Cu(II)(dipy)2] and [Cu(II)(dpdipy)2] display weak luminescence at room temperature, attributed to a ligand centered emission.

Rydberg electron capture by neutral Al hydrolysis products.

We predict that electron attachment may be used with ESI-MS techniques to observe neutral Al metal aqua-oxo-hydroxo species and the complex polymerization and precipitation reactions in which they participate. Neutral aqueous metal species have, so far, been invisible to ESI-MS techniques.

Electron-attachment-induced DNA damage: instantaneous strand breaks.

Low energy electron-attachment-induced damage in DNA, where dissociation channels may involve multiple bonds including complex bond rearrangements and significant nuclear motions, is analyzed here. Quantum mechanics/molecular mechanics (QM/MM) calculations reveal how rearrangements of electron density after vertical electron attachment modulate the position and dynamics of the atomic nuclei in DNA. The nuclear motions involve the elongation of the P-O (P-O(3') and P-O(5')) and C-C (C(3')-C(4') and C(4')-C(5')) bonds for which the acquired kinetic energy becomes high enough so that the neighboring C(3')-O(3') or C(5')-O(5') phosphodiester bond may break almost immediately. Such dynamic behavior should happen on a very short time scale, within 15-30 fs, which is of the same order of magnitude as the time scale predicted for the excess electron to localize around the nucleobases. This result indicates that the C-O phosphodiester bonds can break before electron transfer from the backbone to the base.

Improved DFT-based interpretation of ESI-MS of aqueous metal cations.

We present results showing that our recently developed density functional theory (DFT)-based speciation model of the aqueous Al(3+) system has the potential to improve the interpretations of ESI-MS studies of aqueous metal cation hydrolytic speciation. The main advantages of our method are that (1) it allows for the calculation of the relative abundance of a given species which may be directly assigned to the signal intensity in a mass spectrum; (2) in cases where species with identical m/z ratios may coexist, the assignment can be unambiguously assigned based on their theoretical relative abundances. As a demonstration of its application, we study four pairs of monomer and dimer aqueous Al(3+) species, each with identical m/z ratio. For some of these pairs our method predicts that the dominant species changes from the monomer to the dimer species under varying pH conditions.