Growth of two-dimensional covalent organic frameworks on substrates: insight from microsecond atomistic simulations.

While growing two-dimensional covalent organic frameworks (2D COFs) on substrates holds promise for producing functional monolayers, the presence of many defects in the resulting crystals often hinders their practical applications. Achieving structural order while suppressing defect formation necessitates a detailed atomic-level understanding. The key lies in understanding the polymerization process with high nano-scale accuracy, which presents significant challenges. Here, we perform microsecond atomistic molecular dynamics simulations to describe the deposition and polymerization of cyclohexa-m-phenylene on metal substrates, closely mimicking experimental conditions. Our improved approach highlights that 2D polymerization occurs through monomer addition and island coalescence, with a pre-bonding stage allowing monomers/oligomers to dynamically adjust their configurations to the expanding island structures. Our results elucidate the mechanisms underlying the formation of vacancy and dislocation defects during 2D polymerization as well as their healing processes. Overall, our findings underscore the significant roles that high surface mobility, effective monomer-substrate anchoring, high framework rigidity, moderate monomer coordination, and low bonding rate play in forming large, extended 2D crystals while suppressing vacancy and dislocation defects. We demonstrate how these factors can be tuned through substrate selection, deposition rate modulation, and temperature control, thereby offering valuable insight for strategically optimizing on-surface 2D polymerizations.

Research on Efficient Electromagnetic Shielding Performance and Modulation Mechanism of Aero/Organo/Hydrogels with Gravity-Induced Asymmetric Gradient Structure.

To eliminate electromagnetic pollution, it is a challenging task to develop highly efficient electromagnetic shielding materials that integrate microwave absorption (MA) performance with high shielding capability and achieve tunability in shielding performance. Asymmetrically structured aero/organo/hydrogels with a progressively changing concentration gradient of liquid metal nanoparticles (LMNPs), induced by gravity, are prepared by integrating the conductive fillers Ti3C2Tx MXene and LMNPs into a dual-network structure composed of polyvinyl alcohol and cellulose nanofibers. Benefiting from the unique structure, which facilitates the absorption-reflection-reabsorption process of electromagnetic waves along with conductive fillers and the porous structure, three types of gels demonstrate efficient shielding performance. HPCML achieves a total shielding effectiveness (SET) of up to 86.9 dB and a reflection shielding effectiveness (SER) of as low as 2.85 dB. Especially, APCML, with an ultra-low reflection coefficient (R) of 6.4%, achieves compatibility between shielding performance and MA properties. The relationship between dispersing media (air, water, and glycerol/water) and the shielding performance of aero/organo/hydrogels is explored, thereby achieving modulation of the shielding performance of the gel system. The work has paved a clear path for integrating absorption and shielding capabilities into a composite material, thereby providing a prototype of a highly efficient shielding material with MA performance.

TEMPO as Hydrogen Atom Transfer Catalyst in Enhancing Iminyl Radical Cyclization of O-Acetyl Oxime toward Phenanthridines and Isoquinolines.

Herein, we present a strategy for promoting the cyclization of ortho-aryl or ortho alkenyl arylketone oxime ethers C-N bonds using TEMPO as a direct hydrogen atom transfer (HAT) catalyst. The reaction employs a green solvent and requires no introduction of metal additives. It only needs catalytic amount of TEMPO to drive the reaction. Gram-scale reaction yields the corresponding products with satisfactory yields, providing a novel and efficient method for the synthesis of phenanthridine and isoquinoline derivatives.

ADAM8 promotes alcoholic liver fibrosis through the MAPK signaling pathway.

The effect and molecular regulatory mechanism of A Disintegrin and Metalloproteinase 8 (ADAM8) were explored in alcoholic liver fibrosis (ALF). C57BL/6N male mice were randomly divided into control, alcohol, and ADAM8-sgRNA3 plasmid groups. The control group received control liquid diet, while the alcohol and ADAM8-sgRNA3 plasmid groups were given alcohol liquid feed diet combined with ethanol gavage treatment for 8 weeks to induce ALF modeling. In addition, the ADAM8-sgRNA3 plasmid group was injected with the effective ADAM8-sgRNA3 plasmid, while the alcohol and control group mice were injected with an equivalent amount of physiological saline. LX-2 human hepatic stellate cells were divided into control, alcohol, si-ADAM8-2, and si-ADAM8-NC groups and induced for 48 h for model establishment in vitro. Serological detection, pathological staining, Western blotting, qRT-PCR and CCK8 assay were performed for experiments. Compared with the alcohol group, ADAM8 mRNA, protein and, positive area rate, serological indicators, pathological changes, and the expression of liver fibrosis marker and MAPK signaling pathway-related factors in the ADAM8-sgRNA3 plasmid group significantly decreased in vivo. Compared with the alcohol group, ADAM8 mRNA and protein expression, cell viability, and the expression of liver fibrosis markers and MAPK signaling pathway-related factors (p-ERK1/2, PCNA, Bcl-2, p-c-Jun, TGFß1, p-p38 MAPK and HSP27) reduced significantly in the si-ADAM8-2 group. Therefore, ADAM8 promotes ALF through the MAPK signaling pathway, a promising target for treating ALF.

Visible Light-Induced 6π-Heterocyclization/Dehydroaromatization for Synthesis of Indoloquinolinone Skeletons.

In this work, we report a protocol for the synthesis of an indoloquinolinone skeleton using visible light-induced energy transfer. This method avoids the premodification of substrates and exhibits high yields. For gram-scale reactions, only 0.01 mol % (100 ppm) of photosensitizer is required for rapid conversion. Mechanistic studies revealed that this reaction differs from conventional 6π photocyclization reactions; undergoing a process involving 6π cyclization due to energy transfer and dehydrogenation due to product self-catalysis has been experienced.

Two decades of progress in glioma methylation research: the rise of temozolomide resistance and immunotherapy insights.

Aims: This study aims to systematically analyze the global trends in glioma methylation research using bibliometric methodologies. We focus on identifying the scholarly trajectory and key research interests, and we utilize these insights to predict future research directions within the epigenetic context of glioma. Methods: We performed a comprehensive literature search of the Web of Science Core Collection (WoSCC) to identify articles related to glioma methylation published from January 1, 2004, to December 31, 2023. The analysis included full-text publications in the English language and excluded non-research publications. Analysis and visualization were performed using GraphPad Prism, CiteSpace, and VOSviewer software. Results: The search identified 3,744 publications within the WoSCC database, including 3,124 original research articles and 620 review articles. The research output gradually increased from 2004 to 2007, followed by a significant increase after 2008, which peaked in 2022. A minor decline in publication output was noted during 2020-2021, potentially linked to the coronavirus disease 2019 pandemic. The United States and China were the leading contributors, collectively accounting for 57.85% of the total research output. The Helmholtz Association of Germany, the German Cancer Research Center (DKFZ), and the Ruprecht Karls University of Heidelberg were the most productive institutions. The Journal of Neuro-Oncology led in terms of publication volume, while Neuro-Oncology had the highest Impact Factor. The analysis of publishing authors revealed Michael Weller as the most prolific contributor. The co-citation network analysis identified David N. Louis's article as the most frequently cited. The keyword analysis revealed "temozolomide," "expression," "survival," and "DNA methylation" as the most prominent keywords, while "heterogeneity," "overall survival," and "tumor microenvironment" showed the strongest citation bursts. Conclusions: The findings of this study illustrate the increasing scholarly interest in glioma methylation, with a notable increase in research output over the past two decades. This study provides a comprehensive overview of the research landscape, highlighting the importance of temozolomide, DNA methylation, and the tumor microenvironment in glioma research. Despite its limitations, this study offers valuable insights into the current research trends and potential future directions, particularly in the realm of immunotherapy and epigenetic editing techniques.

Solvent-mediated oxide hydrogenation in layered cathodes.

Self-discharge and chemically induced mechanical effects degrade calendar and cycle life in intercalation-based electrochromic and electrochemical energy storage devices. In rechargeable lithium-ion batteries, self-discharge in cathodes causes voltage and capacity loss over time. The prevailing self-discharge model centers on the diffusion of lithium ions from the electrolyte into the cathode. We demonstrate an alternative pathway, where hydrogenation of layered transition metal oxide cathodes induces self-discharge through hydrogen transfer from carbonate solvents to delithiated oxides. In self-discharged cathodes, we further observe opposing proton and lithium ion concentration gradients, which contribute to chemical and structural heterogeneities within delithiated cathodes, accelerating degradation. Hydrogenation occurring in delithiated cathodes may affect the chemo-mechanical coupling of layered cathodes as well as the calendar life of lithium-ion batteries.

Heptacyclic aromatic hydrocarbon isomers with two azulene units fused.

Azulene, known for its unique electronic properties and structural asymmetry, serves as a promising building block for the design of novel non-benzenoid polycyclic aromatic hydrocarbons (PAHs). Herein, we present the synthesis, characterization, and physical properties of three diazulene-fused heptacyclic aromatic hydrocarbons, 8,17-dioctyldiazuleno[2,1-a:2',1'-h]anthracene (trans configuration), 16,18-dioctyldiazuleno[2,1-a:1',2'-j]anthracene (cis configuration) and 3,18-dioctyldiazuleno[2,1-a:1',2'-i]phenanthrene (zigzag configuration). Three compounds are configurational isomers with different fusing patterns of aromatic rings. All three isomers exhibit pronounced aromaticity, as revealed by nuclear magnetic resonance spectroscopy and theoretical calculations. They exhibit characteristics of both azulene and benzenoid PAHs and are much more stable than their all-benzene analogues. The optical and electrochemical properties of these three isomers were investigated through UV-vis absorption spectra and cyclic voltammetry, revealing distinct behaviors influenced by their molecular configurations. Furthermore, the isomer in trans configuration exhibits promising semiconducting properties with a hole mobility of up to 0.22 cm2 V-1 s-1, indicating its potential in organic electronics applications.

LKLPDA: A Low-Rank Fast Kernel Learning Approach for Predicting piRNA-Disease Associations.

Piwi-interacting RNAs (piRNAs) are increasingly recognized as potential biomarkers for various diseases. Investig-ating the complex relationship between piRNAs and diseases through computational methods can reduce the costs and risks associated with biological experiments. Fast kernel learning (FKL) is a classical method for multi-source data fusion that is widely employed in association prediction research. However, biological networks are noisy due to the limitations of measurement technology and inherent natural variation, which can hamper the effectiveness of the network-based ideal kernel. The conventional FKL method does not address this issue. In this study, we propose a low-rank fast kernel learning (LRFKL) algorithm, which consists of low-rank representation (LRR) and the FKL algorithm. The LRFKL algorithm is designed to mitigate the effects of noise on the network-based ideal kernel. Using LRFKL, we propose a novel approach for predicting piRNA-disease associations called LKLPDA. Specifically, we first compute the similarity matrices for piRNAs and diseases. Then we use the LRFKL to fuse the similarity matrices for piRNAs and diseases separately. Finally, the LKLPDA employs AutoGluon-Tabular for predictive analysis. Computational results show that LKLPDA effectively predicts piRNA-disease associations with higher accuracy compared to previous methods. In addition, case studies confirm the reliability of the model in predicting piRNA-disease associations. Availability and implementation: The LKLPDA software and data are freely available at https://github.com/Shiqzz/LKLPDA-master.git.

Global Tendencies and Frontier Topics in Cervical Laminoplasty: A Bibliometric Analysis from 1982 to 2023.

BACKGROUND: This bibliometric analysis aimed to map the knowledge network of laminoplasty research. METHODS: Studies on laminoplasty published from 1982 to 2023 were retrieved from the Web of Science Core Collection (WoSCC). The contributions of countries, institutions, authors, and journals were identified using VOSviewer, Scimago Graphica, and Microsoft Excel. Tendencies, hotspots, and knowledge networks were analyzed and visualized using VOSviewer and CiteSpace. RESULTS: We identified 2577 publications on laminoplasty. The annual number of publications exhibited an overall increasing trend since 2004. Among these, Japan, China, and the United States were the 3 major contributing countries. Keio University, Nagoya University, and Tokyo Medical & Dental University were the 3 most productive institutions. Shiro Imagama ranked first among authors regarding the number of articles, while K Hirabayashi was first among co-cited authors. Spine was the top journal in terms of the number of publications, citations, and co-citations. In addition, the research topics can be divided into 3 clusters: (1) Comparison between laminoplasty and other surgery in outcomes and complications; (2) Axial symptoms in laminoplasty; (3) Sagittal alignment and sagittal balance in laminoplasty. Emerging topics sagittal alignment and sagittal balance in degenerative cervical spondylosis are identified as current research frontiers. CONCLUSIONS: This study drew a knowledge map of the top countries, institutions, authors, publications, and journals on laminoplasty over the past 4 decades. The current and future hotspots of laminoplasty focus on sagittal balance, comparison between other surgery in outcomes and complication, and axial symptoms in laminoplasty.

Albumin-Based Microneedles for Spatiotemporal Delivery of Temozolomide and Niclosamide to Resistant Glioblastoma.

Glioblastoma (GBM) is the most common and aggressive malignant brain tumor. Standard therapy includes maximal surgical resection, radiotherapy, and adjuvant temozolomide (TMZ) administration. However, the rapid development of TMZ resistance and the impermeability of the blood-brain barrier (BBB) significantly hinder the therapeutic efficacy. Herein, we developed spatiotemporally controlled microneedle patches (BMNs) loaded with TMZ and niclosamide (NIC) to overcome GBM resistance. We found that hyaluronic acid (HA) increased the viscosity of bovine serum albumin (BSA) and evidenced that concentrations of BSA/HA exert an impact degradation rates exposure to high-temperature treatment, showing that the higher BSA/HA concentrations result in slower drug release. To optimize drug release rates and ensure synergistic antitumor effects, a 15% BSA/HA solution constituting the bottoms of BMNs was chosen to load TMZ, showing sustained drug release for over 28 days, guaranteeing long-term DNA damage in TMZ-resistant cells (U251-TR). Needle tips made from 10% BSA/HA solution loaded with NIC released the drug within 14 days, enhancing TMZ's efficacy by inhibiting the activity of O6-methylguanine-DNA methyltransferase (MGMT). BMNs exhibit superior mechanical properties, bypass the BBB, and gradually release the drug into the tumor periphery, thus significantly inhibiting tumor proliferation and expanding median survival in mice. The on-demand delivery of BMNs patches shows a strong translational potential for clinical applications, particularly in synergistic GBM treatment.

A 3D-printed acinar-mimetic silk fibroin-collagen-astragalus polysaccharide scaffold for tissue reconstruction and functional repair of damaged parotid glands.

Salivary glands are the principal organs responsible for secreting saliva in the oral cavity. Tumors, trauma, inflammation, and other factors can cause functional or structural damage to the glands, leading to reduced saliva secretion. In this study, we innovatively prepared a acinar-mimetic silk fibroin-collagen-astragalus polysaccharide (SCA) scaffold using low-temperature three-dimensional (3D) printing and freeze-drying techniques. We evaluated the material properties and cell compatibility of the scaffold in vitro and implanted it into the damaged parotid glands (PG) of rats to assess its efficacy in tissue reconstruction and functional repair. The results demonstrated that the SCA scaffold featured a porous structure resembling natural acini, providing an environment conducive to cell growth and orderly aggregation. It exhibited excellent porosity, water absorption, mechanical properties, and biocompatibility, fulfilling the requirements for tissue engineering scaffolds. In vitro, the scaffold facilitated adhesion, proliferation, orderly polarization, and spherical aggregation of PG cells. In vivo, the SCA scaffold effectively recruited GECs locally, forming gland-like acinar structures that matured gradually, promoting the regeneration of damaged PGs. The SCA scaffold developed in this study supports tissue reconstruction and functional repair of damaged PGs, making it a promising implant material for salivary gland regeneration.

Genome-Wide Identification of the WRKY Gene Family in Four Cotton Varieties and the Positive Role of GhWRKY31 in Response to Salt and Drought Stress.

The WRKY gene family is ubiquitously distributed in plants, serving crucial functions in stress responses. Nevertheless, the structural organization and evolutionary dynamics of WRKY genes in cotton have not been fully elucidated. In this study, a total of 112, 119, 217, and 222 WRKY genes were identified in Gossypium arboreum, Gossypium raimondii, Gossypium hirsutum, and Gossypium barbadense, respectively. These 670 WRKY genes were categorized into seven distinct subgroups and unequally distributed across chromosomes. Examination of conserved motifs, domains, cis-acting elements, and gene architecture collectively highlighted the evolutionary conservation and divergence within the WRKY gene family in cotton. Analysis of synteny and collinearity further confirmed instances of expansion, duplication, and loss events among WRKY genes during cotton evolution. Furthermore, GhWRKY31 transgenic Arabidopsis exhibited heightened germination rates and longer root lengths under drought and salt stress. Silencing GhWRKY31 in cotton led to reduced levels of ABA, proline, POD, and SOD, along with downregulated expression of stress-responsive genes. Yeast one-hybrid and molecular docking assays confirmed the binding capacity of GhWRKY31 to the W box of GhABF1, GhDREB2, and GhRD29. The findings collectively offer a systematic and comprehensive insight into the evolutionary patterns of cotton WRKYs, proposing a suitable regulatory framework for developing cotton cultivars with enhanced resilience to drought and salinity stress.

Exploring explainable AI features in the vocal biomarkers of lung disease.

This review delves into the burgeoning field of explainable artificial intelligence (XAI) in the detection and analysis of lung diseases through vocal biomarkers. Lung diseases, often elusive in their early stages, pose a significant public health challenge. Recent advancements in AI have ushered in innovative methods for early detection, yet the black-box nature of many AI models limits their clinical applicability. XAI emerges as a pivotal tool, enhancing transparency and interpretability in AI-driven diagnostics. This review synthesizes current research on the application of XAI in analyzing vocal biomarkers for lung diseases, highlighting how these techniques elucidate the connections between specific vocal features and lung pathology. We critically examine the methodologies employed, the types of lung diseases studied, and the performance of various XAI models. The potential for XAI to aid in early detection, monitor disease progression, and personalize treatment strategies in pulmonary medicine is emphasized. Furthermore, this review identifies current challenges, including data heterogeneity and model generalizability, and proposes future directions for research. By offering a comprehensive analysis of explainable AI features in the context of lung disease detection, this review aims to bridge the gap between advanced computational approaches and clinical practice, paving the way for more transparent, reliable, and effective diagnostic tools.

Taming Two-Dimensional Polymerization by a Machine-Learning Discovered Crystallization Model.

Rapidly synthesizing high-quality two-dimensional covalent organic frameworks (2D COFs) is crucial for their practical applications. While strategies such as slow monomer addition have been developed based on an empirical understanding of their formation process, quantitative guidance remains absent, which prohibits precise optimizations of the experimental conditions. Here, we use a machine-learning approach that overcomes the challenges associated with bottom-up model derivation for the non-classical 2D COF crystallization processes. The resulting model, referred to as NEgen1, establishes correlations among the induction time, nucleation rate, growth rate, bond-forming rate constants, and common solution synthesis conditions for 2D COFs that grow by a nucleation-elongation mechanism. The results elucidate the detailed competition between the nucleation and growth dynamics in solution, which has been inappropriately described previously by classical, empirical models with assumptions invalid for 2D COF polymerization. By understanding the dynamic processes at play, the NEgen1 model reveals a simple strategy of gradually increasing monomer addition speed for growing large 2D COF crystals. This insight enables us to rapidly synthesize large COF-5 colloids, which could only be achieved previously by prolonged reaction times or by introducing chemical modulators. These results highlight the potential for systematically improving the crystal quality of 2D COFs, which has wide-reaching relevance for many of the applications where 2D COFs are speculated to be valuable.

Role of mitochondria-associated membranes in the hippocampus in the pathogenesis of depression.

BACKGROUND: Pathological changes, such as microglia activation in the hippocampus frequently occur in individuals with animal models of depression; however, they may share a common cellular mechanism, such as endoplasmic reticulum (ER) stress and mitochondrial dysfunction. Mitochondria associated membranes (MAMs) are communication platforms between ER and mitochondria. This study aimed to investigate the role of intracellular stress responses, especially structural and functional changes of MAMs in depression. METHODS: We used chronic social defeat stress (CSDS) to mimic depression in C57 mice to investigate the pathophysiological changes in the hippocampus associated with depression and assess the antidepressant effect of electroacupuncture (EA). Molecular, histological, and electron microscopic techniques were utilized to study intracellular stress responses, including the ER stress pathway reaction, mitochondrial damage, and structural and functional changes in MAMs in the hippocampus after CSDS. Proteomics technology was employed to explore protein-level changes in MAMs caused by CSDS. RESULTS: CSDS caused mitochondrial dysfunction, ER stress, closer contact between ER and mitochondria, and enrichment of functional protein clusters at MAMs in hippocampus along with depressive-like behaviors. Also, EA showed beneficial effects on intracellular stress responses and depressive-like behaviors in CSDS mice. LIMITATION: The cellular specificity of MAMs related protein changes in CSDS mice was not explored. CONCLUSIONS: In the hippocampus, ER stress and mitochondrial damage occur, along with enriched mitochondria-ER interactions and MAM-related protein enrichment, which may contribute to depression's pathophysiology. EA may improve depression by regulating intracellular stress responses.

Sulfur-Vacancy Engineering Accelerates Rapid Surface Reconstruction in Ni-Co Bimetal Sulfide Nanosheet for Urea Oxidation Electrocatalysis.

Developing a highly efficient catalyst for electrocatalytic urea oxidation reaction (UOR) is not only beneficial for the degradation of urea pollutants in wastewater but also provides a benign route for hydrogen production. Herein, a sulfur-vacancy (Sv) engineering is proposed to accelerate the formation of metal (oxy)hydroxide on the surface of Ni-Co bimetal sulfide nanosheet arrays on nickel foam (Sv-CoNiS@NF) for boosting the urea oxidation electrocatalysis. As a result, the obtained Sv-CoNiS@NF demonstrates an outstanding electrocatalytic UOR performance, which requires a low potential of only 1.397 V versus the reversible hydrogen electrode to achieve the current density of 100 mA cm-2. The ex situ Raman spectra and density functional theory calculations reveal the key roles of the Sv site and Co9S8 in promoting the electrocatalytic UOR performance. This work provides a new strategy for accelerating the transformation of electrocatalysts to active metallic (oxy)hydroxide for urea electrolysis via engineering the surface vacancies.

Role of polyferric sulphate in hydration regulation of phosphogypsum-based excess-sulphate slag cement: A multiscale investigation.

Current demand for waste recycling, phosphogypsum-based excess-sulphate slag cement (PESSC) as a sustainable cement prepared by solid wastes, urges enhancing its performance development based on microstructure optimisation. For the purpose of improving the performance and durability of PESSC used in normal or corrosive environments, it is deemed an efficient technique to produce iron-doped compounds with high thermodynamic stability. This paper presents a systematic study of the effect of iron modification on PESSC binders by introducing 0%-2% polyferric sulphate (PFS) from a multiscale viewpoint. XPS, 29Si and 27Al NMR, and TEM were used to characterise the nanostructure of solid particles firstly at Level I. Then, the chemical composition and phase assemblage of PESSC binders were revealed at Level II in terms of ICC, ICP, DTG-DSC, FTIR, BSE-EDS and XRD. Finally, setting time and strength development were determined at Level III. Results indicated that the soluble FeOH4- supplied by the hydrolysis of PFS promotes the generation of iron-doped ettringite with a greater length-to-diameter ratio and thermodynamic stability. Seeding effect of iron doping also promotes the production of spherical and retiform gels with a slight influence on the chemical components and polymerisation. Despite the fact that iron doping weakens the early strength of PESSC mortars, it promotes the persistent hydration rate by retarding precipitation and encapsulation of hydrates on the surface of the slag, showing excellent strength in the later stages. In view of microstructure evolution and performance development during each stage, PFS supplementation within 1.0% is considered a feasible modification of PESSC relying on the formation control of iron-doped hydrates.

DIAS: A dataset and benchmark for intracranial artery segmentation in DSA sequences.

The automated segmentation of Intracranial Arteries (IA) in Digital Subtraction Angiography (DSA) plays a crucial role in the quantification of vascular morphology, significantly contributing to computer-assisted stroke research and clinical practice. Current research primarily focuses on the segmentation of single-frame DSA using proprietary datasets. However, these methods face challenges due to the inherent limitation of single-frame DSA, which only partially displays vascular contrast, thereby hindering accurate vascular structure representation. In this work, we introduce DIAS, a dataset specifically developed for IA segmentation in DSA sequences. We establish a comprehensive benchmark for evaluating DIAS, covering full, weak, and semi-supervised segmentation methods. Specifically, we propose the vessel sequence segmentation network, in which the sequence feature extraction module effectively captures spatiotemporal representations of intravascular contrast, achieving intracranial artery segmentation in 2D+Time DSA sequences. For weakly-supervised IA segmentation, we propose a novel scribble learning-based image segmentation framework, which, under the guidance of scribble labels, employs cross pseudo-supervision and consistency regularization to improve the performance of the segmentation network. Furthermore, we introduce the random patch-based self-training framework, aimed at alleviating the performance constraints encountered in IA segmentation due to the limited availability of annotated DSA data. Our extensive experiments on the DIAS dataset demonstrate the effectiveness of these methods as potential baselines for future research and clinical applications. The dataset and code are publicly available at https://doi.org/10.5281/zenodo.11401368 and https://github.com/lseventeen/DIAS.

Intramolecular Dehydrogenative Photocyclization of N-Phenyl-1-naphthamides.

Here, we explore a dehydrogenative 6π photocyclization method for N-substituted naphthalene carboxamides, which can be conducted in air. This method employs DMSO as both the reaction solvent and oxidant while also stabilizing the excited state of the substrate. Furthermore, the addition of photosensitizer enables the reaction to proceed under a 440-445 nm LED source via energy transfer. The proposed mechanism is initially validated through DFT calculations.