Enhanced ophthalmic bioavailability and stability of atropine sulfate via sustained release particles using polystyrene sulfonate resin.

Atropine sulfate (ATS) eye drops at low concentrations constitute a limited selection for myopia treatment, with challenges such as low ophthalmic bioavailability and inadequate stability. This study proposes a novel strategy by synthesizing ophthalmic sodium polystyrene sulfonate resin (SPSR) characterized by a spherical shape and uniform size for cationic exchange with ATS. The formulation of ATS@SPSR suspension eye drops incorporates xanthan gum and hydroxypropyl methylcellulose (HPMC) as suspending agents. In vitro studies demonstrated that ATS@SPSR suspension eye drops exhibited sustained release characteristics, and tropic acid, its degradation product, remained undetected for 30 days at 40 °C. The ATS levels in the tear fluids and aqueous humor of New Zealand rabbits indicated a significant increase in mean residence time (MRT) and area under the drug concentration-time curve (AUC0-12h) for ATS@SPSR suspension eye drops compared to conventional ATS eye drops. Moreover, safety assessment confirmed the non-irritating nature of ATS@SPSR suspension eye drops in rabbit eyes. In conclusion, the cation-responsive sustained-release ATS@SPSR suspension eye drops enhanced the bioavailability and stability of ATS, offering a promising avenue for myopia treatment.

Role of Phenylethanolamine-N-methyltransferase on Nicotine-Induced Vasodilation in Rat Cerebral Arteries.

OBJECTIVE: The sympathetic-parasympathetic (or axo-axonal) interaction mechanism mediated that neurogenic relaxation, which was dependent on norepinephrine (NE) releases from sympathetic nerve terminal and acts on ß2-adrenoceptor of parasympathetic nerve terminal, has been reported. As NE is a weak ß2-adrenoceptor agonist, there is a possibility that synaptic NE is converted to epinephrine by phenylethanolamine-N-methyltransferase (PNMT) and then acts on the ß2-adrenoceptors to induce neurogenic vasodilation. METHODS: Blood vessel myography technique was used to measure relaxation and contraction responses of isolated basilar arterial rings of rats. RESULTS: Nicotine-induced relaxation was sensitive to propranolol, guanethidine (an adrenergic neuronal blocker), and Nω-nitro-l-arginine. Nicotine- and exogenous NE-induced vasorelaxation was partially inhibited by LY-78335 (a PNMT inhibitor), and transmural nerve stimulation depolarized the nitrergic nerve terminal directly and was not inhibited by LY-78335; it then induced the release of nitric oxide (NO). Epinephrine-induced vasorelaxation was not affected by LY-78335. However, these vasorelaxations were completely inhibited by atenolol (a ß1-adrenoceptor antagonist) combined with ICI-118,551 (a ß2-adrenoceptor antagonist). CONCLUSIONS: These results suggest that NE may be methylated by PNMT to form epinephrine and cause the release of NO and vasodilation. These results provide further evidence supporting the physiological significance of the axo-axonal interaction mechanism in regulating brainstem vascular tone.

Limited impact of lifting universal masks on SARS-CoV-2 transmission in schools: The crucial role of outcome measurements.

Amid the COVID-19 pandemic, education systems globally implemented protective measures, notably mandatory mask wearing. As the pandemic's dynamics changed, many municipalities lifted these mandates, warranting a critical examination of these policy changes' implications. This study examines the effects of lifting mask mandates on COVID-19 transmission within Massachusetts school districts. We first replicated previous research that utilized a difference-in-difference (DID) model for COVID-19 incidence. We then repeated the DID analysis by replacing the outcome measurement with the reproductive number (Rt ), reflecting the transmissibility. Due to the data availability, the Rt we estimated only measures the within school transmission. We found a similar result in the replication using incidence with an average treatment effect on treated (ATT) of 39.1 (95% CI: 20.4 to 57.4) COVID-19 cases per 1,000 students associated with lifting masking mandates. However, when replacing the outcome measurement to Rt , our findings suggest that no significant association between lifting mask mandates and reduced Rt (ATT: 0.04, 95% CI: -0.09 to 0.18), except for the first 2 weeks postintervention. Moreover, we estimated Rt below 1 at 4 weeks before lifting mask mandates across all school types, suggesting nonsustainable transmission before the implementation. Our reanalysis suggested no evidence of lifting mask mandates in schools impacted the COVID-19 transmission in the long term. Our study highlights the importance of examining the transmissibility outcome when evaluating interventions against transmission.

Classification of multiple primary lung cancer in patients with multifocal lung cancer: assessment of a machine learning approach using multidimensional genomic data.

Background: Multiple primary lung cancer (MPLC) is an increasingly well-known clinical phenomenon. However, its molecular characterizations are poorly understood, and still lacks of effective method to distinguish it from intrapulmonary metastasis (IM). Herein, we propose an identification model based on molecular multidimensional analysis in order to accurately optimize treatment. Methods: A total of 112 Chinese lung cancers harboring at least two tumors (n = 270) were enrolled. We retrospectively selected 74 patients with 121 tumor pairs and randomly divided the tumor pairs into a training cohort and a test cohort in a 7:3 ratio. A novel model was established in training cohort, optimized for MPLC identification using comprehensive genomic profiling analyzed by a broad panel with 808 cancer-related genes, and evaluated in the test cohort and a prospective validation cohort of 38 patients with 112 tumors. Results: We found differences in molecular characterizations between the two diseases and rigorously selected the characterizations to build an identification model. We evaluated the performance of the classifier using the test cohort data and observed an 89.5% percent agreement (PA) for MPLC and a 100.0% percent agreement for IM. The model showed an excellent area under the curve (AUC) of 0.947 and a 91.3% overall accuracy. Similarly, the assay achieved a considerable performance in the independent validation set with an AUC of 0.938 and an MPLC predictive value of 100%. More importantly, the MPLC predictive value of the classification achieved 100% in both the test set and validation cohort. Compared to our previous mutation-based method, the classifier showed better κ consistencies with clinical classification among all 112 patients (0.84 vs. 0.65, p <.01). Conclusion: These data provide novel evidence of MPLC-specific genomic characteristics and demonstrate that our one-step molecular classifier can accurately classify multifocal lung tumors as MPLC or IM, which suggested that broad panel NGS may be a useful tool for assisting with differential diagnoses.

A novel plant type, leaf disease and severity identification framework using CNN and transformer with multi-label method.

The growth of plants is threatened by numerous diseases. Accurate and timely identification of these diseases is crucial to prevent disease spreading. Many deep learning-based methods have been proposed for identifying leaf diseases. However, these methods often combine plant, leaf disease, and severity into one category or treat them separately, resulting in a large number of categories or complex network structures. Given this, this paper proposes a novel leaf disease identification network (LDI-NET) using a multi-label method. It is quite special because it can identify plant type, leaf disease and severity simultaneously using a single straightforward branch model without increasing the number of categories and avoiding extra branches. It consists of three modules, i.e., a feature tokenizer module, a token encoder module and a multi-label decoder module. The LDI-NET works as follows: Firstly, the feature tokenizer module is designed to enhance the capability of extracting local and long-range global contextual features by leveraging the strengths of convolutional neural networks and transformers. Secondly, the token encoder module is utilized to obtain context-rich tokens that can establish relationships among the plant, leaf disease and severity. Thirdly, the multi-label decoder module combined with a residual structure is utilized to fuse shallow and deep contextual features for better utilization of different-level features. This allows the identification of plant type, leaf disease, and severity simultaneously. Experiments show that the proposed LDI-NET outperforms the prevalent methods using the publicly available AI challenger 2018 dataset.

Glycyrrhetinic acid loaded in milk-derived extracellular vesicles for inhalation therapy of idiopathic pulmonary fibrosis.

Idiopathic pulmonary fibrosis (IPF) is a chronic, progressive, and life-threatening lung disease for which treatment options are limited. Glycyrrhetinic acid (GA) is a triterpenoid with multiple biological effects, such as anti-inflammatory and anti-fibrotic properties. Herein, inhalable milk-derived extracellular vesicles (mEVs) encapsulating GA (mEVs@GA) were screened and evaluated for IPF treatment. The results indicated that the loading efficiency of GA in mEVs@GA was 8.65%. Therapeutic effects of inhalable mEVs@GA were investigated in vitro and in vivo. The mEVs@GA demonstrated superior anti-inflammatory effects on LPS-stimulated MHS cells. Furthermore, repeated noninvasive inhalation delivery of mEVs@GA in bleomycin-induced IPF mice could decrease the levels of transforming growth factors ß1 (TGF-ß1), Smad3 and inflammatory cytokines IL-6, IL-1ß and TNF-α. The mEVs@GA effectively diminished the development of fibrosis and improved pulmonary function in the IPF mice model at a quarter of the dose compared with the pirfenidone oral administration group. Additionally, compared to pirfenidone-loaded mEVs, mEVs@GA demonstrated superior efficacy at the same drug concentration in the pharmacodynamic study. Overall, inhaled mEVs@GA have the potential to serve as an effective therapeutic option in the treatment of IPF.

Controlled release of vitamin A palmitate from crosslinked cyclodextrin organic framework for dry eye disease therapy.

Controlled release drug delivery systems of eye drops are a promising ophthalmic therapy with advantages of good patient compliance and low irritation. However, the lack of a suitable drug carrier for ophthalmic use limits the development of the aforementioned system. Herein, the crosslinked cyclodextrin organic framework (COF) with a cubic porous structure and a uniform particle size was synthesized and applied to solidify vitamin A palmitate (VAP) by using the solvent-free method. The VAP@COF suspension eye drops were formulated by screening co-solvents, suspending agents, and stabilizing agents to achieve a homogeneous state and improve stability. According to the in vitro release study, the VAP@COF suspension exhibited a controlled release of VAP within 12 h. Both the ex vivo corneal contact angle and in vivo fluorescence tracking indicated that the VAP@COF suspension prolonged the VAP residence time on the ocular surface. This suspension accelerated the recovery of the dry eye disease (DED) model in New Zealand rabbits. Furthermore, the suspension was non-cytotoxic to human corneal epithelial cells and non-irritation to rabbit eyes. In summary, the particulate COF is an eye-acceptable novel carrier that sustains release and prolongs the VAP residence time on the ocular surface for DED treatment.

Teachers' Emotional Intelligence and Organizational Commitment: A Moderated Mediation Model of Teachers' Psychological Well-Being and Principal Transformational Leadership.

Given the global challenge of increasing teacher attrition and turnover rates, the exploration of factors and mechanisms that improve teachers' organizational commitment has become a pivotal topic in educational research. In this context, the present study examines the influence of teachers' emotional intelligence on their organizational commitment, with a specific inquiry into the mediating role of teachers' psychological well-being and the moderating role of principal transformational leadership, as informed by the broaden-and-build theory of positive emotions and the trait activation theory. We verified this study's hypotheses based on 768 valid questionnaires collected from Chinese primary and secondary school teachers. The results reveal that teachers' emotional intelligence can predict their organizational commitment both directly and indirectly through the mediating role of psychological well-being. Additionally, principal transformational leadership amplifies the positive effect of teachers' emotional intelligence on psychological well-being and, subsequently, organizational commitment. These findings theoretically deepen our understanding of the psychological pathways and the boundary conditions linking teachers' emotional intelligence to their organizational commitment, while also offering valuable practical implications for building a stable and effective teaching workforce.

Macrophage hitchhiking for systematic suppression in postablative multifocal HCC.

BACKGROUND AND AIMS: HCC, particularly the multifocal HCC, features aggressive invasion and dismal prognosis. Locoregional treatments were often refractory to eliminate tumor tissue, resulting in residual tumor cells persisting and subsequent progression. Owing to problematic delivery to the tumor tissue, systemic therapies, such as lenvatinib (LEN) therapy, show limited clinical benefit in preventing residual tumor progression. Therefore, more advanced strategies for postablative multifocal HCC are urgently needed. APPROACH AND RESULTS: Motivated by the chemotaxis in tumor penetration of macrophages, we report a strategy named microinvasive ablation-guided macrophage hitchhiking for the targeted therapy toward HCC. In this study, the strategy leverages the natural inflammatory gradient induced by ablation to guide LEN-loaded macrophages toward tumor targeting, which increased by ~10-fold the delivery efficiency of LEN in postablative HCC in vivo. Microinvasive ablation-guided macrophage hitchhiking has demonstrated significant antitumor activity in various HCC models, including the hydrodynamic tail vein injection multifocal HCC mouse model and the orthotopic xenograft HCC rabbit model, systematically inhibiting residual tumor progression after ablation and prolonging the median survival of tumor-bearing mice. The potential antitumor mechanism was explored using techniques such as flow cytometry, ELISA, and immunohistochemistry. We found that the strategy significantly suppressed tumor cell proliferation and neovascularization, and such enhanced delivery of LEN stimulated systemic immune responses and induced durable immune memory. CONCLUSIONS: The macrophage hitchhiking strategy demonstrates exceptional therapeutic efficacy and biosafety across various species, offering promising prospects for clinical translation in controlling residual tumor progression and improving outcomes following HCC ablation.

Exploring the Super-Relaxed State of Human Cardiac ß-Myosin by Molecular Dynamics Simulations.

Human ß-cardiac myosin plays a critical role in generating the mechanical forces necessary for cardiac muscle contraction. This process relies on a delicate dynamic equilibrium between the disordered relaxed state (DRX) and the super-relaxed state (SRX) of myosin. Disruptions in this equilibrium due to mutations can lead to heart diseases. However, the structural characteristics of SRX and the molecular mechanisms underlying pathogenic mutations have remained elusive. To bridge this gap, we conducted molecular dynamics simulations and free energy calculations to explore the conformational changes in myosin. Our findings indicate that the size of the phosphate-binding pocket can serve as a valuable metric for characterizing the transition from the DRX to SRX state. Importantly, we established a global dynamic coupling network within the myosin motor head at the residue level, elucidating how the pathogenic mutation E483K impacts the equilibrium between SRX and DRX through allosteric effects. Our work illuminates molecular details of SRX and offers valuable insights into disease treatment through the regulation of SRX.

A Study of the Adsorption Properties of Individual Atoms on the Graphene Surface: Density Functional Theory Calculations Assisted by Machine Learning Techniques.

In this research, the adsorption performance of individual atoms on the surface of monolayer graphene surface was systematically investigated using machine learning methods to accelerate density functional theory. The adsorption behaviors of over thirty different atoms on the graphene surface were computationally analyzed. The adsorption energy and distance were extracted as the research targets, and the basic information of atoms (such as atomic radius, ionic radius, etc.) were used as the feature values to establish the dataset. Through feature engineering selection, the corresponding input feature values for the input-output relationship were determined. By comparing different models on the dataset using five-fold cross-validation, the mathematical model that best fits the dataset was identified. The optimal model was further fine-tuned by adjusting of the best mathematical ML model. Subsequently, we verified the accuracy of the established machine learning model. Finally, the precision of the machine learning model forecasts was verified by the method of comparing and contrasting machine learning results with density functional theory. The results suggest that elements such as Zr, Ti, Sc, and Si possess some potential in controlling the interfacial reaction of graphene/aluminum composites. By using machine learning to accelerate first-principles calculations, we have further expanded our choice of research methods and accelerated the pace of studying element-graphene interactions.

Allosteric pathways of SARS and SARS-CoV-2 spike protein identified by neural relational inference.

The receptor binding domain (RBD) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein must undergo a crucial conformational transition to invade human cells. It is intriguing that this transition is accompanied by a synchronized movement of the entire spike protein. Therefore, it is possible to design allosteric regulators targeting non-RBD but hindering the conformational transition of RBD. To understand the allosteric mechanism in detail, we establish a computational framework by integrating coarse-grained molecular dynamic simulations and a state-of-the-art neural network model called neural relational inference. Leveraging this framework, we have elucidated the allosteric pathway of the SARS-CoV-2 spike protein at the residue level and identified the molecular mechanisms involved in the transmission of allosteric signals. The movement of D614 is coupled with that of Q321. This interaction subsequently influences the movement of K528/K529, ultimately coupling with the movement of RBD during conformational changes. Mutations that weaken the interactions within this pathway naturally block the allosteric signal transmission, thereby modulating the conformational transitions. This observation also offers a rationale for the distinct allosteric patterns observed in the SARS-CoV spike protein. Our result provides a useful method for analyzing the dynamics of potential viral variants in the future.

The discrepancy distribution of macrophage subsets in preeclampsia placenta with or without fetal growth restriction from a small cohort.

OBJECTIVES: To identify the effect of distribution characteristic of macrophages on placental function and angiogenesis in pregnancies with preeclampsia (PE) in presence of fetal growth restriction (FGR) or preeclampsia without FGR. MATERIAL AND METHODS: The study tested the hypothesis that there was association between distribution characteristic of macrophage subsets (marked by CD68, CD163, respectively) and placental capillary development, leading to placental dysfunction in PE pregnancies with FGR (n = 36). Changes in placental parameters related with efficiency and angiogenesis and macrophage phenotypes (CD68 and CD163) were evaluated by immunohistochemistry. Pearson correlation analysis was performed to analysis the association between macrophage phenotype and placental function as well the CD34 staining, respectively. Additionally, the localization of CD68 and CD163 was assessed by using immunoflurorescence staining. RESULTS: Pearson correlation analysis had shown the positive association between CD68 expression and microvessel formation and the reverse linear relationship between CD163 staining and placental sufficiency in PE + FGR placenta. The co-localization of CD163 and CD34 may pointed to the compensatory role of CD163 distribution involved in prompting neovascularization. CONCLUSIONS: The association between disturbed distribution of macrophages and placental efficiency and angiogenesis were only found in PE with FGR not in PE pregnancies without FGR, underlying the discrepancy role of macrophage subsets depending on the clinical phenotype of PE pregnancies.

Preparation and characterization of nisin-loaded chitosan nanoparticles functionalized with DNase I for the removal of Listeria monocytogenes biofilms.

Listeria monocytogenes biofilms represent a continuous source of contamination, leading to serious food safety concerns and economic losses. This study aims to develop novel nisin-loaded chitosan nanoparticles (CSNPs) functionalized with DNase I and evaluate its antibiofilm activity against L. monocytogenes on food contact surfaces. Nisin-loaded CSNPs (CS-N) were first prepared by ionic cross-linking, and DNase I was covalently grafted on the surface (DNase-CS-N). The NPs were subsequently characterized by Zetasizer Nano, transmission electron microscopy, Fourier transform infrared (FT-IR), and X-ray diffraction (XRD). The antibiofilm activity of NPs was evaluated against L. monocytogenes on polyurethane (PU). The DNase-CS-N was fabricated and characterized with quality attributes (particle size-427.0 ± 15.1 nm, polydispersity [PDI]-0.114 ± 0.034, zeta potential-+52.5 ± 0.2 mV, encapsulation efficiency-46.5% ± 3.6%, DNase conjugate rate-70.4% ± 0.2). FT-IR and XRD verified the loading of nisin and binding of DNase I with chitosan. The DNase-CS-N caused a 3 log colony-forming unit (CFU)/cm2 reduction of L. monocytogenes biofilm cells, significantly higher than those in CSNPs (1.4 log), CS-N (1.8 log), and CS-N in combination with DNase I (2.2 log) treatment groups. In conclusion, nisin-loaded CSNPs functionalized with DNase I were successfully prepared and characterized with smooth surface and nearly spherical shape, high surface positive charge, and good stability, which is effective to eradicate L. monocytogenes biofilm cells on food contact surfaces, exhibiting great potential as antibiofilm agents in food industry. PRACTICAL APPLICATION: Listeria monocytogenes biofilms are a common safety hazard in food processing. In this study, novel nanoparticles were successfully constructed and are expected to be a promising antibiofilm agent in the food industry.

The correlation between serum total bile acid and alanine aminotransferase of pregnant women and the disorders of neonatal hyperbilirubinemia-related amino acid metabolism.

BACKGROUND: To explore the association between liver metabolism-related indicators in maternal serum and neonatal hyperbilirubinemia (NHB), and further investigate the predictive value of these indicators in NHB-related amino acid metabolism disorders. METHODS: 51 NHB and 182 No-NHB newborns and their mothers who treated in the Fourth Hospital of Shijiazhuang from 2018 to 2022 were participated in the study. The differences in clinical data were compared by the Mann-Whitney U test and Chi-square test. Multivariate logistic regression was used to analyze the relationship between maternal serum indicators and the occurrence of NHB. The correlation analysis and risk factor assessment of maternal serum indicators with NHB-related amino acid metabolic disorders were performed using Spearman correlation analysis and multivariate logistic regression. RESULTS: Compared to the non NHB group, the NHB group had higher maternal serum levels of alanine aminotransferase (ALT), aspartate aminotransferase (AST), ALT/AST, and total bile acid (TBA), while lower levels of serum albumin (ALB), total cholesterol (TC) and high-density lipoprotein (HDL). The levels of alanine (ALA), valine (VAL), ornithine (ORN), and proline (PRO) in the newborns were reduced in NHB group, while arginine (ARG) showed a tendency to be elevated. Multiple logistic regression analysis showed that maternal ALT, AST, ALT/AST, and TBA levels were all at higher risk with the development of NHB, whereas ALB, TC, and HDL levels were negatively associated with NHB development. Increasing maternal TBA level was associated with lower ALA (r=-0.167, p = 0.011), VAL (r=-0.214, p = 0.001), ORN (r=-0.196, p = 0.003), and PRO in the newborns (r=-0.131, p = 0.045). Maternal ALT level was negatively associated with ALA (r=-0.135, p = 0.039), VAL (r=-0.177, p = 0.007), ORN (r=-0.257, p < 0.001), while ALT/AST was positively correlated with ARG (r = 0.133, p = 0.013). After adjustment for confounding factors, maternal serum TBA and ALT were the independent risk factor for neonatal ORN metabolic disorders [(adjusted odds ratio (AOR) = 0.379, 95%CI = 0.188-0.762, p = 0.006), (AOR = 0.441, 95%CI = 0.211-0.922, p = 0.030)]. Maternal ALT level was an independent risk factor for neonatal VAL metabolic disorders (AOR = 0.454, 95%CI = 0.218-0.949, p = 0.036). CONCLUSIONS: The levels of high TBA, ALT, AST, and low HDL, TC of maternal were associated with the risk of NHB. Maternal TBA and ALT levels were independent risk factors for NHB-related amino acid disturbances which have value as predictive makers.

A Scalable Method for Readable Tree Layouts.

Large tree structures are ubiquitous and real-world relational datasets often have information associated with nodes (e.g., labels or other attributes) and edges (e.g., weights or distances) that need to be communicated to the viewers. Yet, scalable, easy to read tree layouts are difficult to achieve. We consider tree layouts to be readable if they meet some basic requirements: node labels should not overlap, edges should not cross, edge lengths should be preserved, and the output should be compact. There are many algorithms for drawing trees, although very few take node labels or edge lengths into account, and none optimizes all requirements above. With this in mind, we propose a new scalable method for readable tree layouts. The algorithm guarantees that the layout has no edge crossings and no label overlaps, and optimizes one of the remaining aspects: desired edge lengths and compactness. We evaluate the performance of the new algorithm by comparison with related earlier approaches using several real-world datasets, ranging from a few thousand nodes to hundreds of thousands of nodes. Tree layout algorithms can be used to visualize large general graphs, by extracting a hierarchy of progressively larger trees. We illustrate this functionality by presenting several map-like visualizations generated by the new tree layout algorithm.

Biallelic truncating TTN variants in M-band encoding exons cause a fetal lethal titinopathy.

To report two novel TTN variants associated with fetal recessive titinopathy, thereby broadening the range of TTN variants that can lead to titinopathy. Clinical information on the fetus and parents was gathered, and genomic DNAs were extracted from the fetal tissue and family members' peripheral blood samples. Exome sequencing on fetal DNA was performed and following bioinformatics analysis, the suspected pathogenic variants were confirmed through Sanger sequencing. Prenatal ultrasound performed at 29 weeks of gestation revealed hydrops fetalis, decreased fetal movements, multiple joint contractures and polyhydramnios. Intrauterine fetal death was noted in the third trimester. Exome sequencing revealed compound heterozygous variants in the TTN gene: a paternally inherited allele c.101227C>T (p.Arg33743Ter) and a maternally inherited c.104254C>T (p.Gln34752Ter) allele. These variants have not been previously reported and are evaluated to be likely pathogenic according to the American College of Medical Genetics and Genomics guidelines. We report a fetus with hydrops fetalis and arthrogryposis multiplex congenita associated with a compound heterozygote in the TTN gene. Our report broadens the clinical and genetic spectrum associated with the TTN-related conditions.

Dipyridyl-Fused Quinoxalineimide (DPQI): A Strong Electron-Withdrawing Building Block for n-Type Polymer Semiconductors.

Exploration of new electron-withdrawing building blocks plays a key role in the development of n-type organic semiconductors. Herein, a strong electron-withdrawing building block, dipyridyl-fused quinoxalineimide (DPQI), was successfully designed and synthesized. Single-crystal structure reveals that DPQI molecule possesses a completely planar backbone, which is beneficial for charge transport. For comparison, dibenzo-fused quinoxalineimide (DBQI) was also synthesized. The frontier molecular orbital (FMO) energy levels downshift with the incorporation of nitrogen atoms onto the π-conjugated backbone of quinoxalineimide. Two acceptor-acceptor (or all-acceptor) polymers P(BTI-DBQI) and P(BTI-DPQI) based on DBQI and DPQI were synthesized, respectively. Two polymers exhibit deep lowest-unoccupied molecular orbital (LUMO) levels (~-3.5 eV). Additionally, P(BTI-DPQI) exhibits unipolar n-type charge transport with µe of 1.4×10-4  cm2  V-1 s-1 in the organic field-effect transistors (OFET), which render them highly attractive for developing n-type semiconductors device. This work demonstrates that DPQI is a promising building block for constructing n-type polymer semiconductors.

Binding asymmetry and conformational studies of the AtGSDA dimer.

Guanosine deaminase (GSDA) is an important deaminase that converts guanosine to xanthosine, a key intermediate in nitrogen recycling in plants. We previously solved complex structures of Arabidopsis thaliana GSDA bound by various ligands and examined its catalytic mechanism. Here, we report cocrystal structures of AtGSDA bound by inactive guanosine derivatives, which bind relatively weakly to the enzyme and mostly have poor binding geometries. The two protomers display unequal binding performances, and molecular dynamics simulation identified diverse conformations during the enzyme-ligand interactions. Moreover, intersubunit, tripartite salt bridges show conformational differences between the two protomers, possibly acting as "gating" systems for substrate binding and product release. Our structural and biochemical studies provide a comprehensive understanding of the enzymatic behavior of this intriguing enzyme.