Institute of Organic Chemistry

The aggregation behavior of dipyrrolonaphthyridinedione (DPND) chromophores in the solid state critically determines their optoelectronic properties. Here, we investigate how systematic variation in the side-chain geometry─specifically the branching point and steric profile─governs molecular packing and excitonic coupling. Using crystal structure prediction (CSP) combined with experimental GIWAXS and solid-state NMR, we obtain the packing geometry and crystal structure for three DPND derivatives (DPND-iPr, DPND-EtPr, and DPND-iBu). The results reveal that side-chain branching at the first carbon atom promotes herringbone packing and J-type behavior, while branching at the second carbon induces brick-wall stacking and H-type behavior in the solid state. Optical simulations based on the Holstein exciton-vibrational Hamiltonian reproduce experimental absorption and photoluminescence spectra, confirming the transition from J-like to H-like photophysics as the side-chain branching position shifts. This study demonstrates that fine-tuning alkyl side-chain geometry enables rational control of aggregation and excitonic behavior in cross-conjugated DPNDs, providing new design principles for functional organic semiconductors.

Integration of multiple photoswitches into a single multi-responsive system is a promising strategy toward achieving high information density, complex logic operations, and large-amplitude motion. However, such systems typically suffer from poor efficiency. Here, we present a general concept for efficient multi-site photoswitching that is based on realizing forward and reverse transformations along thermodynamically favorable pathways. We show that tetra-E-oxindole-resorcinarene undergoes effective multi-site photoswitching to form a tetra-Z-isomer, which is more stable due to the intramolecular hydrogen-bonding network. To achieve a reverse transformation, modulation of the relative stability of the isomers is required. Here, deprotonation under mechanochemical conditions effectively swaps the stability, enabling effective back transformation to the tetra-E-isomer. Mechanochemistry is indispensable for this transformation, as swapping the stability of isomers is ineffective in solutions. By DFT calculations, we demonstrate that a network of hydrogen bonds is crucial for the modulation of isomers' stability and multiplication of energetic effects. Finally, gas-phase ion mobility mass spectrometry provided a complementary picture, confirming the all-E ↔ all-Z interconversions and their charge-dependent direction.

Abstract Key Results In an independent test set, a longitudinal DBT-based deep learning model achieved higher 5-year risk discrimination than the FFDM-based Mirai model (AUC, 0.720 vs 0.687; p < 0.001) and, in a matched case-control cohort, higher discrimination than the Tyrer–Cuzick model (AUC, 0.676 vs 0.567; p < 0.001). Importance Longitudinal DBT-based AI improves individualized breast cancer risk assessment beyond FFDM-based AI and clinical risk models. Background Imaging-based breast cancer risk prediction models primarily use full-field digital mammography (FFDM). As digital breast tomosynthesis (DBT) has become a predominant screening modality in the United States, its potential for long-term breast cancer risk prediction remains under-explored. Objective To develop and evaluate a deep learning model that uses longitudinal DBT exams to predict long-term breast cancer risk. Methods This retrospective study included 313,531 DBT exams from 161,165 women (mean age, 58.5 ± 11.7 years) between January 2016 and August 2020 at Institute A. A risk prediction (DRP) model was developed to estimate 2–5 year breast cancer risk using longitudinal DBT exams, patient age and breast density. Model performance was compared with a single-time point DBT model, the Mirai model using same-day FFDM, and the Tyrer-Cuzick model using the area under the receiver operating characteristic curve (AUC), time-dependent concordance index, and integrated Brier score. Results In an independent test set (n = 34,580), the longitudinal DRP model achieved a 5-year AUC of 0.720 (95% CI, 0.703–0.738), improving on the single time point DRP model (AUC, 0.706; 95% CI, 0.687–0.724; p < 0.001) and the Mirai model (AUC, 0.687; 95% CI, 0.668–0.705; p < 0.001). In a matched case-control cohort (n=432), the DRP model achieved a 5-year AUC of 0.676 (95% CI, 0.626–0.727), compared with 0.567 (95% CI, 0.514–0.621; p < 0.001) for the Tyrer-Cuzick model. The model reclassified 37.6% (705/1,877) of women with extremely dense breasts as average risk, with a 5-year cancer incidence of 0.7% (5/705), and identified 15.5% (404/2,605) of women with fatty breasts as high risk, with a 5-year cancer incidence of 2.5% (10/404). Conclusion A deep learning model using longitudinal DBT examinations improved long-term breast cancer risk prediction compared with FFDM-based and clinical risk models. Clinical Impacts Longitudinal DBT-based risk prediction may enable dynamic risk assessment using screening images, supporting personalized screening strategies and more targeted use of supplemental imaging.

A mild and efficient method for the synthesis of β ‐carbolines has been developed, based on a visible‐light‐induced cascade cyclization and aromatization of tryptophan derivatives, enabling the key C‐ring formation within the tricyclic core structure. Instead of traditional acid‐promoted conditions, a neutral photoredox catalyst is employed, and the reaction is carried out under mild, acid‐ and base‐free conditions. A variety of β ‐carboline frameworks can be efficiently accessed through this streamlined one‐pot strategy employing a ruthenium‐based photocatalyst.

In this study, we aimed to compare metabolomic profiles, biodistribution, and detoxification patterns of the novel SN-38 derivative NMe with irinotecan (IR), and to identify NMe-specific metabolites to evaluate its preclinical pharmacokinetic advantages. In vivo ADME studies were conducted for NMe, a 9-aminomethyl SN-38 derivative, and IR following a single intraperitoneal dose of 40 mg/kg in mice. Additionally, ADMET properties were predicted using ADMETlab and SwissADME tools for comparison. Levels of NMe and irinotecan absorbed into plasma, distributed to tissues, and metabolized were monitored in liver, lung, spleen, kidney, and stool samples at 15, 30, and 60 min post-administration. Tissue extracts were analysed using high-performance liquid chromatography (HPLC), liquid chromatography-electrospray ionization quadrupole time-of-flight-tandem mass spectrometry (LC-ESI-QTOF-MS), and nuclear magnetic resonance (NMR) techniques after lyophilization and reconstitution. We compared the metabolomic profiles of irinotecan and NMe. We identified and confirmed NMe-specific metabolites, including 9-CH2-S-cysteine conjugate, 9-CH2OH, and NMe-formyl. Notably, novel irinotecan metabolites (IR-OH and IR-ΔE) were detected in small amounts in kidney samples. In some cases, two literature-known photodegradation products of irinotecan were present. NMe was found to quickly metabolize with different distribution to tissues, significantly greater to kidney and liver. Two SN-38 glucuronides, SN-38G(α) and SN-38G(β), were detected corresponding to α- and β-anomers. Where it was possible, NMe, IR and SN-38 were quantified using external calibration curves. In IR group, controlled and prolonged release of SN-38 was confirmed in all samples, yet SN-38G was observed in minority only in plasma, kidney, or lungs. In NMe groups, great relative amounts of SN-38 and SN-38G were detected. Greater content of SN-38G in NMe group than in irinotecan is expected to contribute to modulation and alleviation of some side effects in irinotecan-involved therapies, such as gastrointestinal toxicities (GIT). NMe shows a distinct metabolic profile characterized by rapid biotransformation, higher systemic glucuronidation of SN-38, and formation of unique metabolites, suggesting a potentially wider therapeutic window and reduced toxicity compared with IR.

We investigate new DMAC-TRZ analogues having an aza-embedded DMAC derivative donor structure to reduce donor strength, yielding 0.31 eV blue-shifted emission. The presence/absence of a bridging phenylene unit between the donor and acceptor moieties was found to be pivotal in defining the equilibrium conformational geometry of the emitters investigated, controlling the charge-transfer (CT) state energy and balance between radiative decay and reverse intersystem crossing (rISC). With a phenylene bridge, a quasi-equatorial (QE) conformation in both the ground and excited state is stabalised, leading to well-defined CT absorption and fluorescence bands. Without the phenylene bridge, a quasi-axial (QA) conformation ground state is adopted, pushing the CT state to higher energy. CT fluorescence is, however, observed having a large Stokes shift indicative of excited state reorganization to the QE conformation. Computational modelling highlighted that the phenylene bridge introduces conformational disorder, inducing strong D-A communication giving high absorption and fluorescence intensities. Without the bridge, this communication is lost reducing fluorescence quantum yield but gives rISC rates reaching 10 6 s-1. Our findings demonstrate that phenylene bridge mediated conformational control provides a powerful tool to modulate excited-state dynamics. Our new azaDMAC weak donor is a very promising design of high-performance deep blue TADF emitters.

In this paper, we report the construction of chiral ferrocene-containing supramolecular platforms with high symmetry and well-defined geometry via dynamic covalent chemistry. Starting from amino-acid trihydrazides and ferrocene dialdehyde precursors, we obtained C₂-symmetric motifs Fc(L-1)₂ with hydrogen-bond-stabilized conformations, that display intense circular dichroism (CD) signals in the visible region associated with ferrocene-centered electronic transitions. CD and UV-Vis spectroscopy, supported by computational analysis, reveal efficient transfer of chirality from the remote stereogenic centers to the Fc unit and a robust correlation between amino acid configuration, Fc helicity, and CD sign (L-amino acid → (P)-Fc → (-)CD at 470 nm). Exploiting the dynamic character of the acylhydrazone linker, L-2 was further assembled into D₃-symmetric doubledecker trigonal platform Fc3(L-2)2 with high synthetic efficiency (>90%). Under these conditions, narcissistic chiral self-sorting occurs via dynamic covalent exchange, which results in the formation of homochiral platforms from racemic precursors. The combination of conformationally locked axial chirality, reversible covalent connectivity, and inherent redox activity establishes new amino acid-based motifs as promising modules for constructing chiral Fc-containing porous architectures such as molecular cages, MOFs, and COFs, with potential for asymmetric electrochemical applications.

In preparation for Issue 2, the Journal’s editorial board reached out to its network of organizers to invite short statements on their current work. We asked that these reflections address the guiding questions for this issue, including how their work intersects with social movements, unions or electoral politics, their experiences of working in and against authoritarianism, and their efforts to defend or promote democracy. The following statements from colleagues across three continents offer insights from diverse organizing networks and roles: an organizer turned local official in Hungary; a director of Faith in Action affiliates for Central America; an immigration organizer for the African diaspora in Detroit, and a lead organizer for Berlin, representing one of the largest German organizing networks.

Plasmonic nanostructures with photothermal effect have emerged as a powerful tool for optofluidic systems. Many studies have explored the photothermal application of Ti3C2Tx MXene in micro- or nanoscale devices, while its plasmonic potential in photothermal-induced fluid convection remains unexplored. Here, we numerically investigate a Ti3C2Tx MXene-based plasmonic metasurface capable of photoinduced heat generation and driving nanoscale fluid convection. By combining optics, thermodynamics, and hydrodynamics simulations, we demonstrate that the arrays of Ti3C2Tx MXene nanodisks exhibit localized surface plasmonic resonances in an aqueous medium in the near-infrared frequencies. The wavelength-dependent photoinduced temperature profile of the structure closely follows the absorption spectra in a wide wavelength region of visible and near-infrared incident illumination, indicating efficient photothermal conversion. The photothermal-induced fluid convection across the incident wavelength also shows strong qualitative agreement with the spectral-dependent photoinduced heat profile and absorption spectra, which points to its significant practical application in nanophotonics and optofluidics.