Small Methods最新文献

Achieving predictable and reproducible outcomes is a central challenge across synthetic workflows. Design of Experiments (DoE) offers a structured, multivariate framework for exploring complex parameter spaces, yet its wider adoption has been limited by statistical complexity, licensing costs, and steep learning curves. To address these barriers, we introduce DoEIY.app, an open-access web application that streamlines the experimental design process. The software supports guided design generation, data entry and analysis, and interactive model exploration through an intuitive interface. We illustrate its use in two case studies on gold nanoparticle synthesis, focusing on minimizing size dispersity and controlling mean particle diameter. These examples demonstrate how DoEIY.app enables efficient, reproducible process optimization and highlight its potential to democratize DoE implementation across a broad range of scientific domains.

Spatially transcriptomics (ST) has revolutionized our ability to profile gene expression within the architectural complexity of tissue microenvironments. However, decoding spatial heterogeneity requires robust multimodal data integration that unifies gene expression, spatial positions, and histopathological images to overcome modality-specific biases. Here, we propose M-STGCN, a multimodal unsupervised framework that constructs a spatial weight matrix from spatial coordinates to simultaneously refine both gene expression profiles and image features, by which we establish position-aware feature enhancement served as a core innovation before graph fusion. Verified on human brain and breast cancer datasets, M-STGCN significantly improves the accuracy of spatial domain identification. Ablation studies confirm the importance of its position-aware and image modality integration. For ST platforms lacking images and at diverse resolutions, M-STGCN maintains robust performance utilizing only gene expression and spatial coordinates. By effectively denoising raw spatial transcriptomic profiles, our approach identifies more significant spatial domain marker genes, as well as potential prognostic biomarkers for breast cancer. Moreover, M-STGCN reveals that image features and spatial information contribute equally to breast cancer analysis, underscoring the critical role of image features. As a versatile and scalable tool, M-STGCN enables unbiased integration of multimodal data, facilitating the deciphering of spatial heterogeneous in complex tissues.

Phonon polaritons (PhPs) are hybrid excitations arising from the coupling of optical phonons and electromagnetic waves, providing a versatile platform for exploring strong light-matter interaction studies and engineering the infrared response of polar materials. Their capability to confine and manipulate light well below the diffraction limit, combined with low losses, has enabled breakthroughs in subwavelength waveguiding, hyperlensing, infrared imaging, and molecular sensing. While far-field spectroscopy and scanning near-field optical microscopy have been widely used to characterize PhPs, these photon-based techniques often suffer from limited spatial resolution, momentum mismatch, and a scarcity of suitable light sources and detectors in the infrared region. In contrast, scanning transmission electron microscopy coupled with electron energy-loss spectroscopy (STEM-EELS) has recently emerged as a powerful method for probing PhPs, offering broadband excitation and detection, access to large momentum transfers, sub-nanometer spatial resolution, and substrate-free measurements. Looking ahead, STEM-EELS holds promise for exploring PhPs under in situ conditions-including electrostatic gating, variable temperatures, and mechanical strain-as well as for validating next-generation polaritonic device concepts. When combined with emerging ultrafast electron techniques, STEM-EELS further offers the potential to access polaritonic dynamics, enabling real-time tracking of PhP propagation and damping processes. Addressing challenges such as radiation damage, low signal-to-noise ratios at meV losses, and complex data interpretation will further establish STEM-EELS as an indispensable tool for guiding the design of infrared nanophotonic devices.

Lithium-sulfur batteries are poised as next-generation energy storage systems but remain constrained by sluggish redox kinetics and severe polysulfide shuttling. The liquid-solid Li₂S₄-to-Li₂S conversion governs the reaction rate, underscoring the importance of electrocatalysts in accelerating polysulfide conversion. Here, we report a defective ZIF-67 catalyst, designed through controlled ligand removal, to simultaneously regulate the electronic structure and induce confinement-driven active site densification. The partial removal of ligands exposed unsaturated Co sites, forming "enzyme-like catalytic pockets" to immobilize polysulfides. The remaining ligands surrounding the metal centers tuned the local electronic environment, optimizing intermediate stabilization and catalytic activity. This synergistic regulation enhanced polysulfide adsorption, reduced steric hindrance, and accelerated the critical Li₂S deposition/dissolution processes. Consequently, the sulfur cathode incorporating defective ZIF-67 exhibited improved cycling stability, delivering a capacity fade rate of 0.11 % per cycle over 200 cycles at 5 C, and maintaining a fade rate of 0.075 % per cycle over 150 cycles at 1 C with a sulfur loading of 4 mg cm^-2. Our findings highlight the pivotal role of defect engineering in tailoring both site density and electronic structure within MOFs, offering a rational strategy for boosting polysulfide catalysis and advancing the practical application of lithium-sulfur batteries.

2D transition metal dichalcogenides (TMDs) have attracted considerable interest for next-generation optoelectronics owing to their layer-tunable bandgap and strong light-matter interaction. Indeed, 2D TMDs-based photodetectors are facing an intrinsic trade-off between responsivity and response speed, as well as the unexpectedly large dark current. Particularly, customizing P-i-N structures through incorporating an insulating interlayer between p-type and n-type semiconductors simultaneously suppresses dark current and enables faster response. Nevertheless, preparing insulating layer typically requires complex epitaxial growth techniques that exhibit poor compatibility with 2D TMDs materials. Although the P-i-N structure also can be achieved more readily by dry- or wet-transfer, yet leaving contaminants and defects at the interface. Here, we report an innovative strategy for realizing high-performance HfS₂-HfO_X-WSe₂ P-i-N photodetectors through controlled self-limiting surface oxidation to form an insulating interlayer HfO_X. The introduction of HfO_X effectively reduces dark current through the high potential barrier, while transfers the carrier transport mechanism to tunneling. Consequently, the HfS₂-HfO_X-WSe₂ photodetector exhibits markedly enhanced performance, with the light switching ratio increasing from 22 to 10⁵ and the responsivity rising from 0.034 A/W to 0.245A/W. Our study offers a novel and exceptionally simple route to 2D P-i-N photodetectors that is compatible with 2D semiconductor technology.

Effective combination therapy requires targeted co-delivery of multiple therapeutic agents via a well-defined and controllable assembly mechanism, which most reported strategies struggle to achieve. In this study, we designed a tumor acidity-driven transformable nanoparticle self-assembly using a drug-conjugated amphiphilic polymer (mPEG-PLA-Ce6), an acidity-sensitive polymer (PAEMA), and the CSF-1R inhibitor, sotuletinib (BLZ-945), by regulating the pKa and ratio of the acidity-sensitive material (denoted as ^Ce6SNP/B). The obtained tumor acidity-driven transformable ^Ce6SNP/B released BLZ-945 to deplete immunosuppressive M2-type tumor-associated macrophages predominantly localized in the perivascular regions of blood vessels. Simultaneously, tumor acidity-driven size shrinkage of ^Ce6SNP/B facilitated the deep penetration and tumor accumulation of photosensitizer Ce6 to enhance phototherapy, resulting in enhanced immunogenic cell death of tumor cells. Additionally, the acidity-sensitive material PAEMA has the potential to induce dendritic cell maturation. Thereby, the tumor acidity-driven transformable ^Ce6SNP/B achieved cancer photoimmunotherapy by targeting tumor cells and activating antigen-presenting cell-mediated anti-tumor immune effect.

Nanopore sensors offer exceptional sensitivity for detecting single molecules, making them ideal for early disease diagnostics. In this study, we present a multiplexed nanopore-based assay that combines DNA-barcoded probes with advanced computational analysis to detect microRNAs (miRNAs) with high specificity and accuracy. Each probe selectively binds its target biomarker and induces a characteristic delay in the ionic current signal upon translocation through the nanopore. We evaluated three analytical strategies for classifying delayed versus non-delayed events: (1) moving standard deviation (MSD), (2) spectral entropy (SE), and (3) a convolutional neural network (CNN). While MSD and SE rely on manually defined thresholds and exhibit limited sensitivity, the CNN model, trained on image representations of raw current traces, achieved near-perfect classification performance across all metrics (accuracy = 0.99, precision = 0.99, recall = 0.99). Grad-CAM visualization confirmed that the CNN model focused on relevant signal regions, enhancing interpretability and generalizability. All methods produced sigmoidal concentration-response curves consistent with expected binding kinetics, and nanopore-derived delay metrics closely matched RT-qPCR validation data. All three methods were capable of distinguishing between signal classes; however, the CNN model demonstrated superior sensitivity and robustness. This work highlights the importance of data interpretation in nanopore sensing and presents a comparative framework for binary event classification. The findings pave the way for the development of machine learning-driven nanopore diagnostics capable of detecting diverse biomarker types at the single-molecule level.

Macroscopic substrate surface errors and microscopic groove parameters influence the optical performance of curved diffractive microstructures. However, existing profile measurement techniques face a trade-off between large-area coverage and high resolution, which limits the ability of conventional two-dimensional (2D) line-profile methods to capture the global grating morphology. To address existing limitations, this study proposes a three-dimensional (3D) profile characterization method for curved gratings across macro- and micro-scales. Seamless reconstruction of full-aperture 3D topography with submicron-scale features was achieved using laser scanning confocal microscopy-based stitching measurements. Preprocessing for feature extraction was then performed using frequency-domain separation and the iterative closest point algorithm. The 2D Gabor filter bank, traditionally used for image texture feature extraction, was extended to 3D space to precisely characterize the period distribution of the microstructures. When combined with local planar least-squares fitting, the method enables precise characterization of the 3D spatial distribution of the grating blaze angle. Experimental results demonstrate close agreement between 3D and 2D characterization, with deviations below 0.01 µm in mean period and 0.05° in mean blaze angle, confirming the accuracy and reliability of the method. This study overcomes the limitations of conventional 2D line-profile analysis by enabling high-precision, cross-scale 3D global characterization of curved diffractive microstructures, supporting process optimization and quality control in advanced optical manufacturing.

Atomic force microscopy (AFM) cantilevers are essential components that function both as force sensors and nanoscale interaction tools that play a critical role in AFM capabilities, sensitivity, and precision. Conventional fabrication techniques for probes, that rely on silicon or silicon nitride bulk micro-machining, generally requires complex fabrication processes associated to low throughput and limited geometric flexibility. Here the development of innovative AFM cantilevers made of silica glass through a novel approach based on selective laser etching is explored, which offers cantilever and tip design flexibility, condense the process into three steps, and reduces the fabrication time and cost while minimizing reliance on complex equipment and clean room facilities. The fabrication and characterization of functional glass cantilevers with thicknesses ranging from 1 to 50 µm and spring constants spanning from 0.02 to 80 N m^-1 is demonstrated. The fabricated glass probes show excellent performance in both AFM imaging and force spectroscopy applications. The simple and fast fabrication approach, highlights the potential of selective laser etching to produce innovative versatile silica-based probes for AFM.

Pivotal in inflammation and tissue homeostasis, monocytes and macrophages have become attractive therapeutic targets for modulating the tumor microenvironment. Enhancing their potency often requires genetic modification. This is traditionally achieved using viral transduction, but vector development is expensive, and safety concerns hinder its clinical implementation. Photoporation is an emerging alternative non-viral delivery method that is based on laser irradiation of sensitizing nanoparticles. The resulting photothermal effects induce transient membrane permeabilization, allowing the influx of external molecules into the cell. In this study, the applicability of polydopamine nanoparticle (PDNP)-sensitized photoporation to monocyte and macrophage cell lines for the delivery of model macromolecules (FITC-dextran 500 kDa and eGFP-mRNA), with physicochemical properties resembling those of clinically relevant macromolecules, is investigated. Moreover, a direct comparison is made to a state-of-the-art electroporation platform. Several PDNP sizes, PDNP concentrations, and laser fluences are tested to identify optimal delivery conditions. Once optimized, it is found that, for similar transfection yields, neither technique strongly affects canonical cell surface markers and secreted cytokines. However, unlike photoporation, electroporation affects cell proliferation and morphology considerably. Thus, these findings confirm that PDNP-sensitized photoporation is a gentle intracellular delivery technology for monocytes and macrophages, making it a promising approach for therapeutic applications.