One-Step Synthesis of Dynamically Shaped Stiff Nanorods Using Soft Silicone Materials to Control Water Repulsion and Collection

One-dimensional silicone nanostructures, such as filaments, wires, and tubes, have attracted significant attention, owing to their remarkable application capabilities in a large range of material and surface science. However, the soft mechanical properties of silicone cause vulnerability and irregularity in the synthesized structures, which limits their applications. Herein, a simple, solvent-free, and efficient dynamic Droplet Assisted Growth and Shaping (d-DAGS) strategy is proposed for the one-step synthesis and in situ control of the shape of silicone nanostructures. The special designed bamboo-shaped silicone nanorods (SNRs) that are produced by the repetitive dynamic regulation of growth conditions, concomitant with the periodic purging and injection of precursors, exhibit highly-regular and tunable structure with a specific number of segments, indicating that they can be tailor-made according to the requirements of various properties. The enhanced mechanical stiffness and chemical durability strongly support their excellent performances in water-resistance under both static and dynamic wetting conditions. The SNRs significantly promote buoyancy and self-cleaning properties; and exhibit very high water-harvesting efficiency compared with existing designs. Notably, the well-structured ultra-long rods with an ultrahigh aspect ratio (≈176) can also be fabricated by the d-DAGS method, and they can remain standing straight upwards and regular, even though they consist of flexible silicone

Silicone Nanofilament Coatings as Flexible Catalyst Supports for a Knoevenagel Condensation Reaction in Batch and Flow Systems

In this work, silicone nanofilament (SNF) coatings were prepared via a droplet-assisted growth and shaping (DAGS) approach, where the preparation of the coatings is allowed under ambient conditions. The application of SNF coatings as catalyst supports for amino moieties from (3-aminopropyl)triethoxysilane (APTES) was investigated. With the optimized coating conditions identified, the Brunauer–Emmett–Teller surface areas of a bare glass filter substrate and bare glass beads after the coating have increased by 5-fold and 16-fold, respectively. The SNF-coated filters were readily functionalized with amino groups via a liquid-phase deposition process, and their catalytic activities for a Knoevenagel reaction were evaluated using a batch reactor and a packed bed reactor. In both reactors, the as-prepared filters demonstrated superior catalytic performance over the functionalized filters without SNF coatings. Notably, the unique flexibility of the SNF coatings allowed the facile preparation of a packed bed reactor and a scalable catalytic system. It is expected that the packed bed system established in this study will support the development and the use of various SNF-supported organocatalysts and catalytic materials

Printable and Versatile Superhydrophobic Paper via Scalable Nonsolvent Armor Strategy

Despite great scientific and industrial interest in waterproof cellulosic paper, its real world application is hindered by complicated and costly fabrication processes, limitations in scale-up production, and use of organic solvents. Furthermore, simultaneously achieving nonwetting properties and printability on paper surfaces still remains a technical and chemical challenge. Herein, we demonstrate a nonsolvent strategy for scalable and fast fabrication of waterproofing paper through in situ surface engineering with polysilsesquioxane nanorods (PSNR). Excellent superhydrophobicity is attained on the functionalized paper surface with water contact angle above 160˚. Notably, the engineered paper features outstanding printability and writability, as well as greatly enhanced strength and integrity upon prolonged exposure to water (tensile strength ≈ 9.0 MPa). Additionally, the PSNR concurrently armors paper-based printed items and artwork with waterproofing, self-cleaning and antimicrobial functionalities without compromising their appearance, readability and mechanical properties. We also demonstrate that the engineered paper holds the additional advantages of easy processing, low cost and mechanochemical robustness, which makes it particularly promising for real world applications

Mol-Instructions: A Large-Scale Biomolecular Instruction Dataset for Large Language Models

Large Language Models (LLMs), with their remarkable task-handling capabilities and innovative outputs, have catalyzed significant advancements across a spectrum of fields. However, their proficiency within specialized domains such as biomolecular studies remains limited. To address this challenge, we introduce Mol-Instructions, a meticulously curated, comprehensive instruction dataset expressly designed for the biomolecular realm. Mol-Instructions is composed of three pivotal components: molecule-oriented instructions, protein-oriented instructions, and biomolecular text instructions, each curated to enhance the understanding and prediction capabilities of LLMs concerning biomolecular features and behaviors. Through extensive instruction tuning experiments on the representative LLM, we underscore the potency of Mol-Instructions to enhance the adaptability and cognitive acuity of large models within the complex sphere of biomolecular studies, thereby promoting advancements in the biomolecular research community. Mol-Instructions is made publicly accessible for future research endeavors and will be subjected to continual updates for enhanced applicability.Comment: Project homepage: https://github.com/zjunlp/Mol-Instructions. Add quantitative evaluation

A universal method for depositing patterned materials in-situ

Current techniques of patterned material deposition require separate steps for patterning and material deposition. The complexity and harsh working conditions post serious limitations for fabrication. Here, we introduce a novel single-step and easy-to-adapt method that can deposit materials in-situ. Its unique methodology is based on the semiconductor nanoparticle assisted photon-induced chemical reduction and optical trapping. This universal mechanism can be used for depositing a large selection of materials including metals, insulators and magnets, with quality on par with current technologies. Patterning with several materials together with optical-diffraction-limited resolution accuracy can be achieved from macroscopic to microscopic scale. Furthermore, the setup is naturally compatible with optical microscopy based measurements, thus sample characterisation and material deposition can be realised in-situ. Various devices fabricated with this method in 2D or 3D show it is ready for deployment in practical applications. This revolutionary method will provide a distinct tool in material technology

EasyEdit: An Easy-to-use Knowledge Editing Framework for Large Language Models

Large Language Models (LLMs) usually suffer from knowledge cutoff or fallacy issues, which means they are unaware of unseen events or generate text with incorrect facts owing to the outdated/noisy data. To this end, many knowledge editing approaches for LLMs have emerged -- aiming to subtly inject/edit updated knowledge or adjust undesired behavior while minimizing the impact on unrelated inputs. Nevertheless, due to significant differences among various knowledge editing methods and the variations in task setups, there is no standard implementation framework available for the community, which hinders practitioners to apply knowledge editing to applications. To address these issues, we propose EasyEdit, an easy-to-use knowledge editing framework for LLMs. It supports various cutting-edge knowledge editing approaches and can be readily apply to many well-known LLMs such as T5, GPT-J, LlaMA, etc. Empirically, we report the knowledge editing results on LlaMA-2 with EasyEdit, demonstrating that knowledge editing surpasses traditional fine-tuning in terms of reliability and generalization. We have released the source code on GitHub at https://github.com/zjunlp/EasyEdit, along with Google Colab tutorials and comprehensive documentation for beginners to get started. Besides, we present an online system for real-time knowledge editing, and a demo video at http://knowlm.zjukg.cn/easyedit.mp4.Comment: The project website is https://github.com/zjunlp/EasyEdi

Theoretical and experimental study of dual-fiber laser ablation for prostate cancer.

Single-fiber laser treatment of the prostate has been widely accepted in the clinic due to its minimal invasiveness and high controllability. However, for large tumors, multiple insertions of the laser probe would be needed to achieve full coverage of the tumor, increasing the complexity of the treatment and occasionally resulting in the incomplete killing of tumor cells due to a mismatch between the planned insertion location and the actual probe insertion location. Treatment with a dual-fiber laser results in greater lesion coverage following a single insertion of the probe, with the lesion coverage being even greater than the sum of the coverage of two sequential insertion of a single-fiber laser probe, potentially reducing treatment time and clinical complications. Both theoretical and experimental analyses have been performed to evaluate the proposed dual-fiber laser treatment. A finite element model was established to simulate the treatment process. The simulation results indicated that there is a clear difference between the ablation coverage created using dual-fiber laser ablation and that created using the superposition of sequential single-fiber laser ablation. In addition, the coverage is dependent on the spacing distance between the two fibers. Both ex vivo and in vivo canine prostate tissues were treated by dual-fiber laser ablation, with lesions analyzed by magnetic resonance imaging (MRI), ultrasound imaging, and pathology. The results demonstrate that dual-fiber laser ablation can markedly increase the range of the ablation zone when compared with single-fiber modes. The safety and feasibility of dual-fiber laser treatment has been confirmed, and a treatment plan using dual-fiber laser ablation has also been proposed

MiR-206 may regulate mitochondrial ROS contribute to the progression of Myocardial infarction via TREM1

Abstract Myocardial infarction (MI) is a leading cause of mortality. To better understand its molecular and cellular mechanisms, we used bioinformatic tools and molecular experiments to explore the pathogenesis and prognostic markers. Differential gene expression analysis was conducted using GSE60993 and GSE66360 datasets. Hub genes were identified through pathway enrichment analysis and PPI network construction, and four hub genes (AQP9, MMP9, FPR1, and TREM1) were evaluated for their predictive performance using AUC and qRT-PCR. miR-206 was identified as a potential regulator of TREM1. Finally, miR-206 was found to induce EC senescence and ER stress through upregulating mitochondrial ROS levels via TREM1. These findings may contribute to understanding the pathogenesis of MI and identifying potential prognostic markers

Single-Cell Transcriptomic Profiling in Inherited Retinal Degeneration Reveals Distinct Metabolic Pathways in Rod and Cone Photoreceptors

The cellular mechanisms underlying hereditary photoreceptor degeneration are still poorly understood. The aim of this study was to systematically map the transcriptional changes that occur in the degenerating mouse retina at the single cell level. To this end, we employed single-cell RNA-sequencing (scRNA-seq) and retinal degeneration-1 (rd1) mice to profile the impact of the disease mutation on the diverse retinal cell types during early post-natal development. The transcriptome data allowed to annotate 43,979 individual cells grouped into 20 distinct clusters. We further characterized cluster-specific metabolic and biological changes in individual cell types. Our results highlight Ca2+-signaling as relevant to hereditary photoreceptor degeneration. Although metabolic reprogramming in retina, known as the ‘Warburg effect’, has been documented, further metabolic changes were noticed in rd1 mice. Such metabolic changes in rd1 mutation was likely regulated through mitogen-activated protein kinase (MAPK) pathway. By combining single-cell transcriptomes and immunofluorescence staining, our study revealed cell type-specific changes in gene expression, as well as interplay between Ca2+-induced cell death and metabolic pathways