A Thorough Examination of the Variables Affecting the Quantum Efficiency of Radiative Decay of Trichlorotriphenylmethyl Radicals.

Fluorescence quantum efficiency is determined by the competition between radiation and nonradiation processes of the excited states. Understanding the factors affecting the radiation and nonradiative decay rates is of great significance for the design of luminescent materials. The excitation state deactivation mechanisms of singlet and triplet states have been extensively studied, providing a comprehensive understanding of the processes involved in the relaxation of these states. However, research on free radical systems involving doublet states is relatively scarce. Therefore, in this study, radiation and nonradiative decay rates and the mechanism of a series of trichlorotriphenylmethyl-based radicals were investigated theoretically. The results indicate that the relative rotations of electron donor and acceptor, as well as the internal rotations of trichlorotriphenylmethyl moiety, play important roles in energy dissipation through nonradiative channels. The effect of a solid-state environment on the radiation and nonradiative decay rates of radicals was investigated using a combination of quantum mechanics and molecular mechanics methods. The results indicate that the solid-state environment restricts the expansion of the conjugated system in the excited state of radicals, leading to a slight decrease in radiative decay rate. In addition, the solid-state environment reduces the reorganization energy and also affects the adiabatic excitation energy of radicals. The reduction in reorganization energy results in a decrease in nonradiative rate, while the opposite effect is observed for adiabatic excitation energy. The nonradiative rate of radicals in a solid-state environment is thus inflected by a combination of molecular geometric structure relaxation and ground-excited state energy gap.

Targeting Cyclophilin A and CD147 to Inhibit Replication of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) and SARS-CoV-2-Induced Inflammation.

Identification and development of effective therapeutics for coronavirus disease 2019 (COVID-19) are still urgently needed. The CD147-spike interaction is involved in the severe acute respiratory syndrome coronavirus (SARS-CoV)-2 invasion process in addition to angiotensin-converting enzyme 2 (ACE2). Cyclophilin A (CyPA), the extracellular ligand of CD147, has been found to play a role in the infection and replication of coronaviruses. In this study, our results show that CyPA inhibitors such as cyclosporine A (CsA) and STG-175 can suppress the intracellular replication of SARS-CoV-2 by inhibiting the binding of CyPA to the SARS-CoV-2 nucleocapsid C-terminal domain (N-CTD), and the IC50 is 0.23 µM and 0.17 µM, respectively. Due to high homology, CsA also had inhibitory effects on SARS-CoV and Middle East respiratory syndrome coronavirus (MERS-CoV), and the IC50 is 3.2 µM and 2.8 µM, respectively. Finally, we generated a formulation of phosphatidylserine (PS)-liposome-CsA for pulmonary drug delivery. These findings provide a scientific basis for identifying CyPA as a potential drug target for the treatment of COVID-19 as well as for the development of broad-spectrum inhibitors for coronavirus via targeting CyPA. Highlights: 1) SARS-CoV-2 infects cells via the binding of its S protein and CD147; 2) binding of SARS-CoV-2 N protein and CyPA is essential for viral replication; 3) CD147 and CyPA are potential therapeutic targets for SARS-CoV-2; and 4) CsA is a potential therapeutic strategy by interrupting CD147/CyPA interactions. SIGNIFICANCE STATEMENT: New severe acute respiratory syndrome coronavirus (SARS-CoV)-2 variants and other pathogenic coronaviruses (CoVs) are continually emerging, and new broad-spectrum anti-CoV therapy is urgently needed. We found that binding sites of cyclophilin A/cyclosporin A (CyPA/CsA) overlap with CyPA/N-CTD (nucleocapsid C-terminal domain), which shows the potential to target CyPA during SARS-CoV-2 infection. Here, we provide new evidence for targeting CyPA in the treatment of coronavirus disease 2019 (COVID-19) as well as the potential of developing CyPA inhibitors for broad-spectrum inhibition of CoVs.

Utilizing image and caption information for biomedical document classification.

MOTIVATION: Biomedical research findings are typically disseminated through publications. To simplify access to domain-specific knowledge while supporting the research community, several biomedical databases devote significant effort to manual curation of the literature-a labor intensive process. The first step toward biocuration requires identifying articles relevant to the specific area on which the database focuses. Thus, automatically identifying publications relevant to a specific topic within a large volume of publications is an important task toward expediting the biocuration process and, in turn, biomedical research. Current methods focus on textual contents, typically extracted from the title-and-abstract. Notably, images and captions are often used in publications to convey pivotal evidence about processes, experiments and results. RESULTS: We present a new document classification scheme, using both image and caption information, in addition to titles-and-abstracts. To use the image information, we introduce a new image representation, namely Figure-word, based on class labels of subfigures. We use word embeddings for representing captions and titles-and-abstracts. To utilize all three types of information, we introduce two information integration methods. The first combines Figure-words and textual features obtained from captions and titles-and-abstracts into a single larger vector for document representation; the second employs a meta-classification scheme. Our experiments and results demonstrate the usefulness of the newly proposed Figure-words for representing images. Moreover, the results showcase the value of Figure-words, captions and titles-and-abstracts in providing complementary information for document classification; these three sources of information when combined, lead to an overall improved classification performance. AVAILABILITY AND IMPLEMENTATION: Source code and the list of PMIDs of the publications in our datasets are available upon request.

Figure and caption extraction from biomedical documents.

MOTIVATION: Figures and captions convey essential information in biomedical documents. As such, there is a growing interest in mining published biomedical figures and in utilizing their respective captions as a source of knowledge. Notably, an essential step underlying such mining is the extraction of figures and captions from publications. While several PDF parsing tools that extract information from such documents are publicly available, they attempt to identify images by analyzing the PDF encoding and structure and the complex graphical objects embedded within. As such, they often incorrectly identify figures and captions in scientific publications, whose structure is often non-trivial. The extraction of figures, captions and figure-caption pairs from biomedical publications is thus neither well-studied nor yet well-addressed. RESULTS: We introduce a new and effective system for figure and caption extraction, PDFigCapX. Unlike existing methods, we first separate between text and graphical contents, and then utilize layout information to effectively detect and extract figures and captions. We generate files containing the figures and their associated captions and provide those as output to the end-user.We test our system both over a public dataset of computer science documents previously used by others, and over two newly collected sets of publications focusing on the biomedical domain. Our experiments and results comparing PDFigCapX to other state-of-the-art systems show a significant improvement in performance, and demonstrate the effectiveness and robustness of our approach. AVAILABILITY AND IMPLEMENTATION: Our system is publicly available for use at: https://www.eecis.udel.edu/~compbio/PDFigCapX. The two new datasets are available at: https://www.eecis.udel.edu/~compbio/PDFigCapX/Downloads.

Compound image segmentation of published biomedical figures.

Motivation: Images convey essential information in biomedical publications. As such, there is a growing interest within the bio-curation and the bio-databases communities, to store images within publications as evidence for biomedical processes and for experimental results. However, many of the images in biomedical publications are compound images consisting of multiple panels, where each individual panel potentially conveys a different type of information. Segmenting such images into constituent panels is an essential first step toward utilizing images. Results: In this article, we develop a new compound image segmentation system, FigSplit, which is based on Connected Component Analysis. To overcome shortcomings typically manifested by existing methods, we develop a quality assessment step for evaluating and modifying segmentations. Two methods are proposed to re-segment the images if the initial segmentation is inaccurate. Experimental results show the effectiveness of our method compared with other methods. Availability and implementation: The system is publicly available for use at: https://www.eecis.udel.edu/~compbio/FigSplit. The code is available upon request. Contact: shatkay@udel.edu. Supplementary information: Supplementary data are available online at Bioinformatics.

Rapid identification of the quality decoction pieces by partial least squares -based pattern recognition: grade classification of the decoction pieces of Saposhnikovia divaricata.

Herbal medicines are commonly used in many countries after they undergo processing. Quality decoction pieces are a guarantee of the efficacy and safety of the herbal medical products. Here, a strategy based on chemical analysis combined with chemometric techniques was proposed for the classification and prediction of the different grades of the decoction pieces. Considering the necessity for a shared and simple method for the grade classification for the public, in this paper, the characterization of the chemical constituents was determined by utilizing high-performance liquid chromatography (HPLC)/diode array detection. HPLC was first established for the characterization of the chemical constituents of the different grade decoction pieces. Furthermore, a simultaneous quantification of several of the marker compounds in these decoction pieces was obtained. Finally, a partial least squares-based pattern recognition method was utilized to obtain a predictive model for the grade classification of the decoction pieces. Saposhnikovia divaricata (Turcz.) Schischk was used as a case study. The partial least squares -based pattern recognition for the grade classification of the decoction pieces of S. divaricata demonstrated good sensitivity, specificity and prediction performance, which may efficiently validate the identification results of appearance assessment. The proposed strategy is expected to provide a new insight for the grade classification and quality control of the decoction pieces. Copyright © 2016 John Wiley & Sons, Ltd.

Release property study on the novel divalproex sodium enteric-coated capsules.

In the present study, a novel divalproex sodium (DS) enteric-coated capsule was prepared, and high performance liquid chromatography (HPLC) assay method for DS was developed. Their uniformity, release curve and release characteristics in different solvents were examined. The release studies were performed using marketed sample as a reference and data were analyzed in terms of cumulative release amounts as a function of time. It was demonstrated by the results that assay developed was specific, rapid and reliable, which can be used to determine DS in vitro accurately, and our developed samples were similar to reference preparation in in vitro release characteristics. The release characteristics of different batches of samples were quite similar to each other, and the total release percents of DS from enteric-coated capsule were within 0-10% in HCl, and reached close to 100% in phosphate buffer. Similarity factors (f 2) of three batches between two preparations were all higher than 50. The developed enteric-coated capsule may be a promising alternative dosage form for treatment of related diseases.

Establishment of a novel cell-based assay for screening small molecule antagonists of human interleukin-6 receptor.

AIM: Blockade of interleukin-6 (IL-6) or its receptor (IL-6R) is effective in preventing the progression of autoimmune diseases, such as systemic lupus erythematosus and rheumatoid arthritis. In the present study, we established a novel cell-based assay for identifying small molecule IL-6R antagonists. METHODS: HEK293A cells were transfected with recombinant plasmids pTaglite-SNAP-IL6R and pABhFc-IL6 to obtain membrane-bound IL-6R and recombinant human IL-6 coupled with human Fc fragment (rhIL-6), respectively. A novel screening assay based on the interaction between IL-6R and rhIL-6 was established, optimized and validated. The stability of the assay was also assessed by calculating the Z'-factor. RESULTS: RhIL-6 dose-dependently bound to IL-6R expressed at HEK293A cell surface. The IC50 value of the known antagonist ab47215 was 0.38±0.08 µg/mL, which was consistent with that obtained using the traditional method (0.36±0.14 µg/mL). The value of Z'-factor was 0.68, suggesting that the novel assay was stable for high throughput screening. A total of 474 compounds were screened using the novel screening assay, and 3 compounds exhibited antagonistic activities (IC50=8.73±0.28, 32.32±9.08, 57.83±4.24 µg/mL). Furthermore, the active compounds dose-dependently inhibited IL-6-induced proliferation of 7TD1 cells, and reduced IL-6-induced STAT3 phosphorylation in U937 cells. CONCLUSION: A novel cell-based screening assay for identifying small molecule IL-6R antagonists was established, which simplifies the procedures in traditional cellular ELISA screening and profiling and reduces the costs.

A simulation-based network analysis of intervention targets for adolescent depressive and anxiety symptoms.

Although previous research has well explored central and bridge symptoms of mental health problems, little examined whether these symptoms can serve as effective targets for intervention practices. Based on the Ising model, this study constructed a network structure of depressive and anxiety symptoms. The NodeIdentifyR algorithm (NIRA) was used to simulate interventions within this network, examining the effects of alleviating or aggravating specific symptoms on the network's sum scores. In this study, a total of 15,569 participants were recruited from China (50.87 % females, Mage = 13.44; SD = 0.97). The Ising model demonstrated that "sad mood" had the highest expected influence, and "irritability" had the highest bridge expected influence. Alleviating interventions suggested that decreasing the symptom value of "nervousness" resulted in the greatest projected reduction in network symptom activation, which may be a potential target symptom for treatment. Aggravating interventions indicated that elevating the symptom value of "sad mood" had the most projected increase in network activation, which may be a potential target for prevention. Additionally, network structure indices (e.g., central or bridge symptoms) need to be interpreted with more caution as intervention targets, since they may not be exactly the same. These findings enriched the comprehension of the depressive and anxiety network in Chinese adolescents, offering valuable insights for designing effective interventions.

A bibliometric analysis of research on organizational resilience.

Organizational resilience is a key concept in the study of sustainable corporate growth and indicates an organization's capacity to recover from adversity. It plays a crucial role in responding to uncertain crises. In recent years, academic interest in organizational resilience has increasingly gained prominence. This research uses CiteSpace and VOSviewer to provide a thorough visual analysis of pertinent international literature based on 342 pieces of closely linked literature about organizational resilience. The findings suggest that organizational resilience research is currently experiencing a development phase. Within this field, there is a substantial number of scholars involved, with the most prolific among them including Aleksic Aleksandar, Prayag Girish, and Griffiths Andrew. The networks of collaboration among these authors, nevertheless, are very scattered. Co-citation network research reveals the academics with the biggest sway in the field. Organizational resilience, conservation of resources theory, crisis management, corporate social responsibility, and emergency management are identified as research hotspots within the keyword co-citation network. Furthermore, to determine which countries and regions are the most influential, this study has created a cooperative network among them. China, the United States, and England are the top three nations with articles published. Not only are the highly cited journals respected in the management sector, but they also showcase noteworthy research accomplishments within the field. The purpose of this study is to investigate potential avenues for future research and offer helpful sources for choosing research subjects and developing theoretical frameworks in this area. The analysis is highly valuable as a reference for research on organizational resilience in different settings in the future.

Solvent-Promoted Catalyst-Free Recycling of Waste Polyester and Polycarbonate Materials.

Polymeric materials are indispensable in our daily lives. However, the generation of vast amounts of waste polymers poses significant environmental and ecological challenges. Instead of resorting to landfilling or incineration, strategies for polymer recycling offer a promising approach to mitigate environmental pollution. Pioneering studies have demonstrated the alcoholysis of waste polyesters and polycarbonates; however, these processes typically require the use of catalysts. Moreover, the development of strategies for catalyst removal and recycling is crucial, particularly in some industrial applications. In contrast, we present a catalyst-free method for the alcoholysis of common polyester and polycarbonate materials into small organic molecules. Certain polar organic solvents exhibit remarkable efficiency in polymer degradation under catalyst-free conditions. Employing these polar solvents, both polymer resins and commercially available products could be effectively degraded via alcoholysis. Our design contributes a straightforward route for recycling waste polymeric materials.

Porphyrin photosensitizer molecules as effective medicine candidates for photodynamic therapy: electronic structure information aided design.

Traditional photosensitizers (PS) in photodynamic therapy (PDT) have restricted tissue penetrability of light and a lack of selectivity for tumor cells, which diminishes the efficiency of PDT. Our aim is to effectively screen porphyrin-based PS medication through computational simulations of large-scale design and screening of PDT candidates via a precise description of the state of the light-stimulated PS molecule. Perylene-diimide (PDI) shows an absorption band in the near-infrared region (NIR) and a great photostability. Meanwhile, the insertion of metal can enhance tumor targeting. Therefore, on the basis of the original porphyrin PS segments, a series of metalloporphyrin combined with PDI and additional allosteric Zn-porphyrin-PDI systems were designed and investigated. Geometrical structures, frontier molecular orbitals, ultraviolet-visible (UV-vis) absorption spectra, adiabatic electron affinities (AEA), especially the triplet excited states and spin-orbit coupling matrix elements (SOCME) of these expanded D-A porphyrin were studied in detail using the density functional theory (DFT) and time-dependent density functional theory (TDDFT) methods. PS candidates, conforming type I or II mechanism for PDT, have been researched carefully by molecular docking which targeted Factor-related apoptosis (Fas)/Fas ligand (Fasl) mediated signaling pathway. It was found that porphyrin-PDI, Fe2-porphyrin-PDI, Zn-porphyrin-PDI, Mg-porphyrin-PDI, Zn-porphyrin combined with PDI through single bond (compound 1), and two acetylenic bonds (compound 2) in this work would be proposed as potential PS candidates for PDT process. This study was expected to provide PS candidates for the development of novel medicines in PDT.

Structural analysis of global mineral governance system from the perspective of country.

The uneven spatial distribution of mineral resources necessitates the construction of mature global mineral governance system to ensure rational allocation of mineral resources. To this end, it is essential to analyze the structure of the global mineral governance system to provide a theoretical basis for the construction. The governance actor is the crucial element in driving the governance process, and country serves as the most central actor. Therefore, clarifying the roles and statuses of different countries in the governance system will be helpful to analyze the structure of the governance system. In the context of advancing globalization, a complex cooperative relationship has been presented between countries based on international organizations. Thus, we establish a national cooperation network based on the principle of the co-existence of countries in international organizations, to quantify these relationships between countries and identify the role and status of different countries, as well as the country communities in the cooperation network, by combining the characteristics of the countries in the network with the actual performance in the organizations. The research findings are as follow: (1) The UK, Germany, France, Sweden, and Canada play pivotal roles in promoting international cooperation as well as leading governance in the governance system. (2) Emerging economies are more actively engaged in these organizations and can promote international cooperation, but lack the capacity to assume leadership roles in governance. (3) The U.S. and China have a stronger ability to lead than to cooperate in the governance system. (4) Most African and South American countries, as well as some European nations, are marginalized in the governance system. (5) Countries with the same needs and similar economic and political conditions belong to the same community: The European countries and the U.S., consumer with a high level of economic and political development but low mineral resource endowment are in the first community. Canada, Australia, and certain African and South American countries, producers with high mineral resource endowments are in the second community. Most African and South American countries with lower levels of economic and political development are in the third group.

Ruptured liquid metal microcapsules enabling hybridized silver nanowire networks towards high-performance deformable transparent conductors.

Extensive studies have been carried out on silver nanowires (AgNWs) in view of their impressive conductivity and highly flexible one-dimensional structure. They are seen as a promising choice for producing deformable transparent conductors. Nonetheless, the widespread adoption of AgNW-based transparent conductors is hindered by critical challenges represented by the significant contact resistance at the nanowire junctions and inadequate interfacial adhesion between the nanowires and the substrate. This study presents a novel solution to tackle the aforementioned challenges by capitalizing on liquid metal microcapsules (LMMs). Upon exposure to acid vapor, the encapsulated LMMs rupture, releasing the fluid LM which then forms a metallic overlay and hybridizes with the underlying Ag network. As a result, a transparent conductive film with greatly enhanced electrical and mechanical properties was obtained. The transparent conductor displays negligible resistance variation even after undergoing chemical stability, adhesion, and bending tests, and ultrasonic treatment. This indicates its outstanding adhesion strength to the substrate and mechanical flexibility. The exceptional electrical properties and robust mechanical stability of the transparent conductor position it as an ideal choice for direct integration into flexible touch panels and wearable strain sensors, as evidenced in this study. By resolving the critical challenges in this field, the proposed strategy establishes a compelling roadmap to navigate the development of high-performance AgNW-based transparent conductors, setting a solid foundation for further advancement in the field of deformable electronics.

Oxysterole-binding protein targeted by SARS-CoV-2 viral proteins regulates coronavirus replication.

Introduction: Oxysterol-binding protein (OSBP) is known for its crucial role in lipid transport, facilitating cholesterol exchange between the Golgi apparatus and endoplasmic reticulum membranes. Despite its established function in cellular processes, its involvement in coronavirus replication remains unclear. Methods: In this study, we investigated the role of OSBP in coronavirus replication and explored the potential of a novel OSBP-binding compound, ZJ-1, as an antiviral agent against coronaviruses, including SARS-CoV-2. We utilized a combination of biochemical and cellular assays to elucidate the interactions between OSBP and SARS-CoV-2 non-structural proteins (Nsps) and other viral proteins. Results: Our findings demonstrate that OSBP positively regulates coronavirus replication. Moreover, treatment with ZJ-1 resulted in reduced OSBP levels and exhibited potent antiviral effects against multiple coronaviruses. Through our investigation, we identified specific interactions between OSBP and SARS-CoV-2 Nsps, particularly Nsp3, Nsp4, and Nsp6, which are involved in double-membrane vesicle formation-a crucial step in viral replication. Additionally, we observed that Nsp3 a.a.1-1363, Nsp4, and Nsp6 target vesicle-associated membrane protein (VAMP)-associated protein B (VAP-B), which anchors OSBP to the ER membrane. Interestingly, the interaction between OSBP and VAP-B is disrupted by Nsp3 a.a.1-1363 and partially impaired by Nsp6. Furthermore, we identified SARS-CoV-2 orf7a, orf7b, and orf3a as additional OSBP targets, with OSBP contributing to their stabilization. Conclusion: Our study highlights the significance of OSBP in coronavirus replication and identifies it as a promising target for the development of antiviral therapies against SARS-CoV-2 and other coronaviruses. These findings underscore the potential of OSBP-targeted interventions in combating coronavirus infections.

Switching Anti-Windup Synthesis for Linear Systems With Asymmetric Actuator Saturation.

This article proposes a switching anti-windup strategy for linear, time-invariant (LTI) systems subject to asymmetric actuator saturation and L2 -disturbances, the core idea behind which is to make full use of the available range of control input space by switching among multiple anti-windup gains. The asymmetrically saturated LTI system is converted to a switched system with symmetrically saturated subsystems, and a dwell time switching rule is presented to govern the switching between different antiwindup gains. Based on multiple Lyapunov functions, we derive sufficient conditions for guaranteeing the regional stability and weighted L2 performance of the closed-loop system. The switching anti-windup synthesis that designs a separate anti-windup gain for each subsystem is cast as a convex optimization problem. In comparison with the design of a single anti-windup gain, our method can induce less conservative results since the asymmetric character of the saturation constraint is fully utilized in the switching anti-windup design. Two numerical examples, and an application to aeroengine control (the experiments are conducted on a semiphysical test bench), demonstrate the superiority and practicality of the proposed scheme.

DAUF: A disease-related attentional UNet framework for progressive and stable mild cognitive impairment identification.

Identifying progressive mild cognitive impairment (pMCI) and stable mild cognitive impairment (sMCI) plays a significant role in early Alzheimer's disease (AD) diagnosis, which can effectively boost the life quality of patients. Recently, convolutional neural network (CNN)- based methods using structural magnetic resonance imaging (sMRI) images have shown effective for AD identification. However, these CNN-based methods fail to effectively explore the feature extraction of disease-related multi-scale tissues, such as ventricles, hippocampi and cerebral cortex. To address this issue, we propose an end-to-end disease-related attentional UNet framework (DAUF) for identifying pMCI and sMCI, by embedding a devised dual disease-related attention module (D2AM) and a novel tree-structured feature fusion classifier (TFFC). Specifically, D2AM leverages the complementarity between feature maps and attention maps and the complementary features from the encoder and decoder, so as to highlight discriminative semantic and detailed features. Additionally, TFFC is a powerfully joint multi-scale feature fusion and classification head, by employing the homogeneity among multi-scale features, so that the discriminative features of the multi-scale tissues are adequately fused for enhancing classification performance. Finally, extensive experiments demonstrate the superior performance of DAUF, with the effectiveness of D2AM and TFFC on identifying pMCI and sMCI subjects.

Mechanical Properties, Radiation Resistance Performances, and Mechanism Insights of Nitrile Butadiene Rubber Irradiated with High-Dose Gamma Rays.

The radiation effect of materials is very important and directly related to the safety and reliability of nuclear reactors. Polymer materials, one of the indispensable materials in nuclear power equipment, must withstand the ordeal of high-energy ionizing rays. In this work, through screening different γ-ray dose irradiation conditions, we systematically and comprehensively study the changes in the structure and properties of nitrile butadiene rubber (NBR) before and after γ-ray static irradiation at a high dose rate, and master the rule and mechanism of the γ-ray static irradiation effect of these polymer materials. The mapping relationship between the macroscopic properties, microstructure, and irradiation dose of NBR is accurately characterized. With an increase in total irradiation dose, the C=C double bond reaction occurs, and the C≡N bond, C=C, and C=O participate in the hyper crosslinking reaction. The glass transition temperature (Tg) increases with the cumulative irradiation amount. With the increased total irradiation amount, the degree of rubber cross-linking increases, causing an increased crystallinity and decomposition temperature. A growing amount of gamma irradiation causes the mechanical properties of the rubber to degrade simultaneously, increasing the shore hardness while decreasing the tensile strength and ultimate elongation at break. When the cumulative amount reaches 1 MGy, the ultimate elongation at break decreases significantly. A cumulative dose of radiation resistance of 4 MGy can be achieved by the samples. This work can provide theoretical and experimental support for the long-term stability of nitrile butadiene rubber and its derivatives in nuclear radiation fields and space radiation conditions.

Steric hindrance effect on the excited-state proton transfer process: TDDFT study on the fluorescent sensing mechanism of a fluoride sensor.

An understanding of the excited-state process and the sensing mechanism for specific anions can be helpful for the design and synthesis of fluorescent sensors in analytical chemistry and biotechnology. Here, we theoretically investigated the fluorescent response mechanism of a reported acylhydrazone-based fluorescent sensor (Soft Matter, 2019, 15, 6690) for fluoride recognition using the time-dependent density functional theory approach. At the M06/TZVP/SCM level, the vertical excitation energies, which were calculated based on the ground state and first singlet-state geometries of the sensor molecule, agreed well with the experimental ultraviolet-visible and fluorescence spectra. Therefore, the time-dependent density functional theory method was considered reasonable and effective. According to the frontier orbital analysis and an excited-state potential energy scan, we proposed an excited-state proton transfer mechanism for the sensor-fluorine complex, where the steric hindrance leads to a high potential barrier. The excited-state proton transfer process facilitates sensor molecule deprotonation, alleviates its steric hindrance effect and expands its conjugated system. As a result, the fluorescence emission band of the sensor molecule was red-shifted significantly with the addition of fluoride anion. Based on this fluorescence difference, the sensor could be used for fluoride anion identification. This work provides a strategy to study sensor-analyte interactions in the excited state and offers an approach to tune the fluorescence emission wavelength of sensor molecules in anionic environments.