Illuminating RNA through fluorescent light-up RNA aptamers.

Visualizing RNA is critical for understanding RNA expression patterns and spatial organization within cells, offering valuable insights into gene regulation and cellular functions. High-resolution RNA imaging techniques are therefore indispensable for revealing the complexities of cellular pathways and physiological processes. Traditional RNA imaging methods, however, face significant limitations, such as high background noise resulting from labeling or cell fixation, which can impede the accurate tracking of RNA dynamics in live cells.

One-Base-Gap Circular Probe-Mediated Dual Amplification for Isothermal Detection of N-Methyladenosine Modifications.

N-Methyladenosine (mA) stands out as the predominant internal modification in mammalian RNA, exerting crucial regulatory functions in the metabolism of mRNA. Currently available methods have been limited by an inability to quantify mA modification at precise sites. In this work, we screened a Bst 2.

Visual genetic typing of glioma using proximity-anchored in situ spectral coding amplification.

Gliomas are histologically and genetically heterogeneous tumors. However, classical histopathological typing often ignores the high heterogeneity of tumors and thus cannot meet the requirements of precise pathological diagnosis. Here, proximity-anchored in situ spectral coding amplification (ProxISCA) is proposed for multiplexed imaging of RNA mutations, enabling visual typing of brain gliomas with different pathological grades at the single-cell and tissue levels.

Combination of RCA and DNAzyme for Dual-Signal Isothermal Amplification of Exosome RNA.

The RNA contained in exosomes plays a crucial role in information transfer between cells in various life activities. The accurate detection of low-abundance exosome RNA (exRNA) is of great significance for cell function studies and the early diagnosis of diseases. However, their intrinsic properties, such as their short length and high sequence homology, represent great challenges for exRNA detection.

Depth-assisted calibration on learning-based factorization for a compressive light field display.

Due to the widespread applications of high-dimensional representations in many fields, the three-dimension (3D) display technique is increasingly being used for commercial purpose in a holographic-like and immersive demonstration. However, the visual discomfort and fatigue of 3D head mounts demonstrate the limits of usage in the sphere of marketing. The compressive light field (CLF) display is capable of providing binocular and motion parallaxes by stacking multiple liquid crystal screens without any extra accessories.

Dual-Functional Nanocluster Probe-Based Single-Cell Analysis of RNA Splice Variants.

Differential expression of RNA splice variants among individual cells accounts for cell heterogeneity of gene expression, which plays a key role in the regulation of the immune system. However, currently available techniques face difficulties in achieving single-cell analysis of RNA splice variants with high base resolution, high spatial resolution and accurate quantification. Herein, we constructed DNA-templated dual-functional nanocluster probes to achieve in situ imaging and accurate quantification of RNA splice variants at the single-cell level.

Advancing Imbalanced Domain Adaptation: Cluster-Level Discrepancy Minimization With a Comprehensive Benchmark.

Unsupervised domain adaptation methods have been proposed to tackle the problem of covariate shift by minimizing the distribution discrepancy between the feature embeddings of source domain and target domain. However, the standard evaluation protocols assume that the conditional label distributions of the two domains are invariant, which is usually not consistent with the real-world scenarios such as long-tailed distribution of visual categories. In this article, the imbalanced domain adaptation (IDA) is formulated for a more realistic scenario where both label shift and covariate shift occur between the two domains.

Advancing Image Understanding in Poor Visibility Environments: A Collective Benchmark Study.

Existing enhancement methods are empirically expected to help the high-level end computer vision task: however, that is observed to not always be the case in practice. We focus on object or face detection in poor visibility enhancements caused by bad weathers (haze, rain) and low light conditions. To provide a more thorough examination and fair comparison, we introduce three benchmark sets collected in real-world hazy, rainy, and low-light conditions, respectively, with annotated objects/faces.

One-stop measurement model for fast and accurate tensor display characterization.

Many light field displays are fundamentally different from other displays in that they do not have quantized pixels, quantized angular outputs, or a physical screen position, which can make definitions and characterization problematic. We have determined that it is more appropriate to express the spatial resolution in terms of spatial cutoff frequency rather than a physical distance as in the case of a display with actual quantized pixels. This concept is then extended to also encompass angular resolution.