Image-Based Phenotypic Profiling Enables Rapid and Accurate Assessment of EGFR-Activating Mutations in Tissues from Lung Cancer Patients.

Determining mutations in the kinase domain of the epidermal growth factor receptor (EGFR) is critical for the effectiveness of EGFR tyrosine kinase inhibitors (TKIs) in lung cancer. Yet, DNA-based sequencing analysis of tumor samples is time-consuming and only provides gene mutation information on EGFR, making it challenging to design effective EGFR-TKI therapeutic strategies. Here, we present a new image-based method involving the rational design of a quenched probe based on EGFR-TKI to identify mutant proteins, which permits specific and "no-wash" real-time imaging of EGFR in living cells only upon covalent targeting of the EGFR kinase.

Multiple-image authentication method based on phase-only holograms and a logistic map.

An interesting security method for a multiple-image authentication scheme is proposed based on computer-generated holograms and a logistic map. First, each original image is encoded as the complex-valued hologram under the point light source model. The resulting hologram is then converted to a phase-only hologram using the Floyd-Steinberg dithering algorithm.

PD-1/PD-L1 and coronary heart disease: a mendelian randomization study.

Introduction: It has been found that programmed cell death protein-1 (PD-1) or its ligand PD-L1 may play an important role in the onset and progression of coronary heart disease (CHD). Thus, we conducted this mendelian randomization analysis (MR) to estimate the causal relationship between PD-1/PD-L1 and 5 specific CHDs (chronic ischemic heart disease, acute myocardial infarction, angina pectoris, coronary atherosclerosis, and unstable angina pectoris), complemented by gene set enrichment analysis (GSEA) for further validation.

Methods: Publicly available summary-level data were attained from the UK Biobank with genetic instruments obtained from the largest available, nonoverlapping genome-wide association studies (GWAS).

Environment-Sensitive Fluorescent Probe Enables Assessment of Anaplastic Lymphoma Kinase Activity in Nonsmall Cell Lung Cancer.

Anaplastic lymphoma kinase () rearrangements have been identified as key oncogenic drivers of a subset of nonsmall cell lung cancer (NSCLC). The final chimeric protein of the fusion gene can be constitutively activated, which accounts for the growth and proliferation of ALK-rearranged tumors and thus strongly associates with cancer invasion and metastasis. Diagnostic tools enabling the visualization of ALK activity in a structure-function-based approach are highly desirable to determine ALK status and guide ALK tyrosine kinase inhibitor (ALK-TKI) treatment making.

A modified U-Net convolutional neural network for segmenting periprostatic adipose tissue based on contour feature learning.

Objective: This study trains a U-shaped fully convolutional neural network (U-Net) model based on peripheral contour measures to achieve rapid, accurate, automated identification and segmentation of periprostatic adipose tissue (PPAT).

Methods: Currently, no studies are using deep learning methods to discriminate and segment periprostatic adipose tissue. This paper proposes a novel and modified, U-shaped convolutional neural network contour control points on a small number of datasets of MRI T2W images of PPAT combined with its gradient images as a feature learning method to reduce feature ambiguity caused by the differences in PPAT contours of different patients.

Therapeutic potential of targeting polo-like kinase 4.

Polo-like kinase 4 (PLK4), a highly conserved serine/threonine kinase, masterfully regulates centriole duplication in a spatiotemporal manner to ensure the fidelity of centrosome duplication and proper mitosis. Abnormal expression of PLK4 contributes to genomic instability and associates with a poor prognosis in cancer. Inhibition of PLK4 is demonstrated to exhibit significant efficacy against various types of human cancers, further highlighting its potential as a promising therapeutic target for cancer treatment.

Optical multiple-image authentication method based on Fourier single-pixel imaging and multiple logistic maps.

As a promising technique, the spatial information of an object can be acquired by employing active illumination of sinusoidal patterns in the Fourier single-pixel imaging. However, the major challenge in this field is that a large number of illumination patterns should be generated to record measurements in order to avoid the loss of object details. In this paper, an optical multiple-image authentication method is proposed based on sparse sampling and multiple logistic maps.

Optical multiple-image authentication based on computational ghost imaging and hybrid non-convex second-order total variation.

An optical security method for multiple-image authentication is proposed based on computational ghost imaging and hybrid non-convex second-order total variation. Firstly, each original image to be authenticated is encoded to the sparse information using computational ghost imaging, where illumination patterns are generated based on Hadamard matrix. In the same time, the cover image is divided into four sub-images with wavelet transform.

Developing non-invasive 3D quantificational imaging for intelligent coconut analysis system with X-ray.

Background: As one of the largest drupes in the world, the coconut has a special multilayered structure and a seed development process that is not yet fully understood. On the one hand, the special structure of the coconut pericarp prevents the development of external damage to the coconut fruit, and on the other hand, the thickness of the coconut shell makes it difficult to observe the development of bacteria inside it. In addition, coconut takes about 1 year to progress from pollination to maturity.

A Light Field FDL-HCGH Feature in Scale-Disparity Space.

Many computer vision applications rely on feature detection and description, hence the need for computationally efficient and robust 4D light field (LF) feature detectors and descriptors. In this paper, we propose a novel light field feature descriptor based on the Fourier disparity layer representation, for light field imaging applications. After the Harris feature detection in a scale-disparity space, the proposed feature descriptor is then extracted using a circular neighborhood rather than a square neighborhood.

Expanded Application of a Photoaffinity Probe to Study Epidermal Growth Factor Receptor Tyrosine Kinase with Functional Activity.

The abnormal activation of the epidermal growth factor receptor (EGFR) is strongly associated with cancer invasion and metastasis. Tools and methods are required to study and visualize EGFR activation under (patho)physiological conditions. Here, we report the development of a two-step photoaffinity probe (HX101) by incorporation of a diazirine as a photoreactive group and an alkyne as a ligation handle to quantitively study EGFR kinase activity in native cellular contexts and human tissue slices.

Classification for Human Balance Capacity Based on Visual Stimulation under a Virtual Reality Environment.

The normal and disordered people balance ability classification is a key premise for rehabilitation training. This paper proposes a multi-barycentric area model (MBAM), which can be applied for accurate video analysis based classification. First, we have invited fifty-three subjects to wear an HTC (High Tech Computer Corporation) VIVE (Very Immersive Virtual Experience) helmet and to walk ten meters while seeing a virtual environment.

Aliasing Detection and Reduction Scheme on Angularly Undersampled Light Fields.

When using plenoptic camera for digital refocusing, angular undersampling can cause severe (angular) aliasing artifacts. Previous approaches have focused on avoiding aliasing by pre-processing the acquired light field via prefiltering, demosaicing, reparameterization, and so on. In this paper, we present a different solution that first detects and then removes angular aliasing at the light field refocusing stage.