Small Methods最新文献

Assessing metastatic potential is crucial for cancer treatment strategies. However, current methods are time-consuming, labor-intensive, and have limited sample accessibility. Therefore, this study aims to investigate the urgent need for rapid and accurate approaches by proposing a Ramanome-based metastasis index (RMI) using machine learning of single-cell Raman spectra to rapidly and accurately assess tumor cell metastatic potential. Validation with various cultured tumor cells and a mouse orthotopic model of pancreatic ductal adenocarcinoma show a Kendall rank correlation coefficient of 1 compared to Transwell experiments and histopathological assessments. Significantly, lipid-related Raman peaks are most influential in determining RMI. The lipidomic analysis confirmed strong correlations between metastatic potential and phosphatidylcholine, phosphatidylethanolamine, cholesteryl ester, ceramide, and bis(monoacylglycero)phosphate, crucial in cell membrane composition or signal transduction. Therefore, RMI is a valuable tool for predicting tumor metastatic potential and providing insights into metastasis mechanisms.

DNA methylation discrimination is often challenged by complicated pretreatment, insufficient sensitivity, and suboptimal accuracy. Here, single-molecule readout of DNA methylation is reported using single-layer MoS₂ nanopores. By tuning pore dimension, the sensitivity of MoS₂ nanopores is manipulated, empowering both labeling and labeling-free strategies for DNA methylation discrimination. With methyl-CpG-binding domain protein 1 (MBD1)-labeled methylated DNA translocation in customized nanopores, multiple methylated sites with distance as short as 70 bp in double strand DNA can be resolved. To further improve spatial resolution, small MoS₂ nanopores are engineered with single-nucleotide sensitivity, realizing labeling-free methylation detection with single-nucleotide resolution to recognize two nucleotides with only one methyl difference. This study demonstrates the availability of engineered MoS₂ nanopores in DNA methylation detection, underscoring their potential for epigenetic alteration research at the single-molecule level.

Here, integrated functional components into a hybrid heterostructure via highly stabilized network-like interconnected electronic nanoarchitecture of 1D N-doped holey-carbon nanotube (NHCNT) with 2D nickel─metal-organic framework (Ni─MOF) nanosheets are developed as high-performance electrocatalyst for overall water splitting. The NHCNT promoting electron transport pathways in electrocatalyst, and formation of holes in nanotubes further enables excellent diffusion of ions for promoting the overall reaction rate. An excellent combination of 1D/2D structure of NHCNT/Ni─MOF-4 electrocatalyst exhibits excellent oxygen evolution reaction (η₁₀ = 207.8 mV, and Tafel = 62.6 mV dec^-1) and reasonable hydrogen evolution reaction (η₁₀ = 159.8 mV, and Tafel = 107.69 mV dec^-1) activity with consistent and stable performance in a 1 m KOH. The highly interconnected network structure contains Ni²⁺ and Ni³⁺ species in the NHCNT/Ni─MOF-4 electrocatalyst, which possesses high specific surface area (SSA) (235.53 m² g^-1), electrochemically active surface area (ECSA) (796.2 cm²), mass activity (4.76 mA mg^-1), and turnover frequency (3.99 × 10^-2 s^-1), which provide remarkable electrocatalytic performance via generating synergy between the NHCNT and Ni─MOF. For overall water splitting, NHCNT/Ni─MOF-4 attains a low cell voltage (1.77 V@10 mA cm^-2).

Toward high-density single atom catalysts (SACs), the interaction between neighboring SACs and the induced non-linear loading effect become crucial for their intrinsic catalytic performance. Despite recent investigations on homonuclear SACs, understanding such effect in heteronuclear SACs remains limited. Using Fe and Co SACs co-supported on the nitrogen-doped graphene as a model system, the loading effect on the site-specific activity of heteronuclear SACs toward oxygen reduction reaction (ORR) is here reported by density functional theory calculations. The Fe site exhibits an oscillatory decrease in activity with the loading. In contrast, the Co site has a volcano-like activity with the optimum performance achieved at ≈16.8 wt.% (average inter-site distance: ≈7 Å). At the ultra-high loading of 38.4 wt.% (inter-site distance: ≈4 Å), the Co site is the only ORR active site, whereas Fe sites turn into spectators. This distinct loading-dependent activity between the Fe and Co sites can be ascribed to their difference in the binding capability with the substrate and the d_xz and d_yz orbitals' occupation. These findings highlight the importance of the loading effect in heteronuclear SACs, which could be useful for the development of high-performance heteronuclear and high-entropy SACs toward various catalytic reactions in the high-loading regime.

Live-cell imaging of RNA in specific subcellular compartments is essential for elucidating the rich repertoire of cellular functions, but it has been limited by a lack of simple, precisely controlled methods. Here such an approach is presented via the combination of hybridization chain reaction and spatially restricted enzymatic activation with organelle-targeted delivery. The system can localize engineered DNA hairpins in the mitochondria, where target RNA-initiated chain reaction of hybridization events is selectively activated by a specific enzyme, enabling amplified RNA imaging with high precision. It is demonstrated that the approach is compatible with live cell visualization and enables the regulatable imaging of microRNA in mitochondria. Since in situ activation of the signal amplification with enzyme eliminates the need for genetically encoded protein overexpression, it is envisioned that this simple platform will be broadly applicable for precise RNA imaging with subcellular resolution in a variety of biological processes.

Demand on high-performance ion exchangers is ever-increasing in energy and environment applications. Among many cation exchangers, layered alkali titanates generally show larger cation exchange capacity, but slower cation exchange rate due to their 2D micrometer-size particle morphologies, which limits their practical applications. Here, a rational conversion of a layered sodium titanate, Na₂Ti₃O₇, is reported to the corresponding 1D ultra-narrow nanowires via hydrothermal treatment under basic conditions. The formation of nanowires is thought to involve the partial exfoliation of Na₂Ti₃O₇ to form thin plate-like particles that subsequently split into nanowires along a crystallographically defined, chemically selective weakness in the Na₂Ti₃O₇ crystals. This process is similar to a recently burgeoning materials design using atomic-level weakness in solids, such as zeolites and metal-organic frameworks. The proposed formation scheme is further supported by comparative experiments performed on another layered alkali titanate, K_0.8Ti_1.73Li_0.27O₄, which possesses randomly distributed defects at the Ti sites. Thanks to the shortening of diffusion path lengths of the interlayer cations, the resulting Na₂Ti₃O₇ nanowires show an excellent cation exchange performance toward Cd²⁺ in aqueous solution, exceeding several existing cation exchangers such as zeolites and organic resins.

The accumulation of ice on surface has caused great harm to lots of fields such as transportation or aerospace. Nowadays, various equipment or tools used in low-temperature environments, which face the risk of interface icing, usually have irregular shapes. Traditional rigid anti-icing materials are difficult to meet practical application requirements. Thus, it is crucial to develop flexible anti-icing materials that can be applied to various shape surfaces (curved surfaces, flat surfaces). In this paper, a photoelectric synergistic flexible solid slippery surface (FSSS) is prepared by using flexible basalt fiberglass cloth, flexible copper foil, flexible polyurethane/carbon nanotubes mixture, and flexible solid lubricant (the mixture of coconut wax and coconut oil). Even under harsh conditions of the temperature as low as -80 °C, the FSSS exhibits excellent all-day anti/de-icing performance whether on flat or curved surface. Moreover, the FSSS shows long-term stability both on flat and curved surface: situated in air for 60 days, submerged in water for 60 days, kept in acid environment (pH 1) and base environment (pH 13) for 30 days. Besides, the FSSS can also achieve self-healing function under -80 °C. This flexible surface provides a novel approach for de-icing/frosting of multi-shaped objects in the future.

Electrically conductive hydrogels are highly hydrated 3D networks consisting of a hydrophilic polymer skeleton and electrically conductive materials. Conductive hydrogels have excellent mechanical and electrical properties and have further extensive application prospects in biomedical treatment and other fields. Whereas numerous electrically conductive hydrogels have been fabricated, a set of general principles, that can rationally guide the synthesis of conductive hydrogels using different substances and fabrication methods for various application scenarios, remain a central demand of electrically conductive hydrogels. This paper systematically summarizes the processing, performances, and applications of conductive hydrogels, and discusses the challenges and opportunities in this field. In view of the shortcomings of conductive hydrogels in high electrical conductivity, matchable mechanical properties, as well as integrated devices and machines, it is proposed to synergistically design and process conductive hydrogels with applications in complex surroundings. It is believed that this will present a fresh perspective for the research and development of conductive hydrogels, and further expand the application of conductive hydrogels.

Silicon heterojunction (SHJ) solar cell is an advanced and mature photovoltaic cell. Development of photoelectrochemical (PEC) water splitting devices for hydrogen fuel production using SHJ solar cells is considered as a promising approach to address energy crisis. To achieve this goal, it is necessary to deposit passivation layer and cocatalyst layer on the photoelectrode. However, the development of low-cost and scalable preparation methods for high-quality passivation and cocatalyst layer continues to be a significant challenge. Herein, an efficient passivation layer and hydrogen evolution reaction (HER) catalyst are successfully fabricated via solution processed methods. To improve the HER activity of Ni₃S₂, a Ni₃S₂-based nanoheterostructure of crystalline Ni₃S₂, Ni, and amorphous Y(OH)₃ is constructed. The optimized photocathode exhibits excellent PEC-HER performance, which achieves a saturated photocurrent of -35.5 mA cm^-2 and an applied bias photon-to-current efficiency (ABPE) of 8.4 ± 0.1% under simulated AM1.5G one-sun illumination and more than 120 h of continuous water splitting. This study paves a way for the design and large-scale manufacturing of cost-efficient SHJ photocathode devices.

Spatially resolved transcriptomics (SRT) has become the method of choice for characterising the complexity of biomedical tissue samples. Until recently, scientists were restricted to SRT methods that can profile a limited set of target genes at high spatial resolution or transcriptome-wide but at a low spatial resolution. Through recent developments, there are now methods that offer both subcellular spatial resolution and full transcriptome coverage. However, utilising these new methods' high spatial resolution and gene resolution remains elusive due to several factors, including low detection efficiency and high computational costs. Here, we present Sainsc (Segmentation-free analysis of in situ capture data), which combines a cell-segmentation-free approach with efficient data processing of transcriptome-wide nanometre-resolution spatial data. Sainsc can generate cell-type maps with accurate cell-type assignment at the nanometre scale, together with corresponding maps of the assignment scores that facilitate interpretation of the local confidence of cell-type assignment. We demonstrate its utility and accuracy for different tissues and technologies. Compared to other methods, Sainsc requires lower computational resources and has scalable performance, enabling interactive data exploration. Sainsc is compatible with common data analysis frameworks and is available as open-source software in multiple programming languages.