Global prevalence and years lived with disability (YLDs) of cataract in 204 countries and territories: findings from the Global Burden of Disease Study 2021.

Background: Cataracts, the leading cause of blindness globally, significantly impair vision and quality of life, particularly among the elderly. Despite advancements in cataract surgery, challenges in accessibility and economic disparities hinder the reduction of cataract burden, especially in low-income regions. This study examines the global prevalence and years lived with disability (YLDs) due to cataracts from 1990 to 2021, providing insights to inform public health strategies.

Molecular characterization of a novel non-segmented double-stranded RNA mycovirus isolated from the phytopathogenic fungus Lasiodiplodia pseudotheobromae.

In this study, we isolated a novel mycovirus from Lasiodiplodia pseudotheobromae strain YY-1, which we named "Lasiodiplodia pseudotheobromae mycovirus 1" (LpMyV1). The complete genome of LpMyV1 is 2877 bp in length and contains two non-overlapping open reading frames (ORF1 and ORF2). ORF1 encodes a putative protein of 316 amino acids with a molecular weight of 34.

Pixel2Pixel: A Pixelwise Approach for Zero-Shot Single Image Denoising.

We propose Pixel2Pixel, a novel zero-shot image denoising framework that leverages the non-local self-similarity of images to generate a large number of training samples using only the input noisy image. This framework employs a compact convolutional neural network architecture to achieve high-quality image denoising. Given a single observed noisy image, we first aim to obtain multiple images with different noise versions.

Grid-Guided Sparse Laplacian Consensus for Robust Feature Matching.

Feature matching is a fundamental concern widely employed in computer vision applications. This paper introduces a novel and efficacious method named Grid-guided Sparse Laplacian Consensus, rooted in the concept of smooth constraints. To address challenging scenes such as severe deformation and independent motions, we devise grid-based adaptive matching guidance to construct multiple transformations based on motion coherence.

MaeFuse: Transferring Omni Features With Pretrained Masked Autoencoders for Infrared and Visible Image Fusion via Guided Training.

In this paper, we introduce MaeFuse, a novel autoencoder model designed for Infrared and Visible Image Fusion (IVIF). The existing approaches for image fusion often rely on training combined with downstream tasks to obtain high-level visual information, which is effective in emphasizing target objects and delivering impressive results in visual quality and task-specific applications. Instead of being driven by downstream tasks, our model called MaeFuse utilizes a pretrained encoder from Masked Autoencoders (MAE), which facilities the omni features extraction for low-level reconstruction and high-level vision tasks, to obtain perception friendly features with a low cost.

Learning Feature Matching via Matchable Keypoint-Assisted Graph Neural Network.

Accurately matching local features between a pair of images corresponding to the same 3D scene is a challenging computer vision task. Previous studies typically utilize attention-based graph neural networks (GNNs) with fully-connected graphs over keypoints within/across images for visual and geometric information reasoning. However, in the background of local feature matching, a significant number of keypoints are non-repeatable due to factors like occlusion and failure of the detector, and thus irrelevant for message passing.

Copper-Mediated Enantioselective C-H Thiolation of Ferrocenes Enabled by the BINOL Ligand.

Transition-metal-catalyzed enantioselective C-H activation has transformed the landscape of asymmetric synthesis, enabling the efficient conversion of C-H bonds into C-C and carbon-heteroatom (C-X) bonds. However, the formation of C-S bonds through enantioselective C-H thiolation remains underdeveloped due to challenges such as catalyst deactivation and competitive coordination of sulfur-containing compounds with chiral ligands. Herein, we report an unprecedented approach to constructing sulfur-substituted planar chiral ferrocenes (PCFs) through copper-mediated enantioselective C-H thiolation enabled by only a 2.

Survival outcomes, multidimensional prediction and subsequent therapy in patients with hormone receptor-positive advanced breast cancer receiving palbociclib: a real-world analysis.

Background: To date, the overall survival (OS) of hormone receptor-positive advanced breast cancer (ABC) treated with palbociclib has not been reported in Chinese patients. It still remains unclear what kind of patients may benefit in OS from palbociclib treatment and what the optimal sequential antineoplastic regimen is for those progressing on palbociclib. Therefore, we aimed to investigate the OS outcome of ABC patients receiving palbociclib, establish a predictive model to identify the potential candidates who may benefit from palbociclib and explore the ideal subsequent treatment strategy after palbociclib.

[Research progress on mechanisms and pharmacokinetics of ligustilide in treatment of locomotor system diseases].

Ligustilide, a phthalide compound extracted from Umbelliferae plants such as Angelica sinensis and Ligusticum chuanxiong, has been proven to possess various pharmacological activities, such as anti-inflammatory, anti-tumor, anti-atherosclerosis, anti-ischemic stroke injury, and anti-Alzheimer's disease properties. In recent years, it has shown great potential, particularly in the treatment of locomotor system diseases. Studies have shown that ligustilide has significant therapeutic effects on various locomotor system diseases, including osteoporosis, osteoarthritis, femoral head necrosis, osteosarcoma, and muscle aging and injury.

Adverse events of 20-22G second-generation endoscopic ultrasound-guided fine-needle biopsy needles for solid lesions in the upper gastrointestinal tract and adjacent organs: Systematic review and meta-analysis.

Objectives: Previous research has conducted meta-analyses on the diagnostic accuracy of endoscopic ultrasound-guided fine-needle biopsy (EUS-FNB). However, studies on adverse events (AEs) have been limited and sporadic and have included a highly diverse group of patients (with upper and lower gastrointestinal tract issues) and needles of varying sizes (19-22-25G). The purpose of this systematic review and meta-analysis was to determine the incidence of AEs related to the utilization of 20-22G second-generation EUS-FNB needles subsequent to puncture of the upper gastrointestinal tract and adjacent organs.

The GhANT-GoPGF module regulates pigment gland development in cotton leaves.

Gossypium spp. pigment glands are a good model for studying plant secretory cavity structures. GoPGF (GOSSYPIUM PIGMENT GLAND FORMATION) is a well-characterized master transcription factor that controls gland formation in cotton; however, little is known about its transcriptional regulation.

Label-free discrimination analysis of breast cancer tumor and adjacent tissues of patients after neoadjuvant treatment using Raman spectroscopy: a diagnostic study.

Background And Objective: Breast-conserving surgery (BCS) plays a crucial role in breast cancer treatment, with a primary focus on ensuring cancer-free surgical margins, particularly for patients undergoing neoadjuvant treatment. After neoadjuvant treatment, tumor regression can complicate the differentiation between breast cancer tumor and adjacent tissues. Raman spectroscopy, as a rapid and non-invasive optical technique, offers the advantage of providing detailed biochemical information and molecular signatures of internal molecular components in tissue samples.

Co-targeting TMEM16A with a novel monoclonal antibody and EGFR with Cetuximab inhibits the growth and metastasis of esophageal squamous cell carcinoma.

The chloride channel transmembrane protein 16A (TMEM16A) possesses a calcium-activated property linked to tumor-promoting malignant phenotype and electrophysiological stability. Numerous studies have shown that TMEM16A exhibits aberrant amplification in various squamous cell carcinomas such as esophageal squamous cell carcinoma (ESCC) and is correlated with unfavorable outcomes of ESCC patients. Therefore, TMEM16A is considered as a promising therapeutic target for ESCC.

Spatiotemporal modeling of molecular holograms.

Quantifying spatiotemporal dynamics during embryogenesis is crucial for understanding congenital diseases. We developed Spateo (https://github.com/aristoteleo/spateo-release), a 3D spatiotemporal modeling framework, and applied it to a 3D mouse embryogenesis atlas at E9.

DHM-Net: Deep Hypergraph Modeling for Robust Feature Matching.

We present a novel deep hypergraph modeling architecture (called DHM-Net) for feature matching in this paper. Our network focuses on learning reliable correspondences between two sets of initial feature points by establishing a dynamic hypergraph structure that models group-wise relationships and assigns weights to each node. Compared to existing feature matching methods that only consider pair-wise relationships via a simple graph, our dynamic hypergraph is capable of modeling nonlinear higher-order group-wise relationships among correspondences in an interaction capturing and attention representation learning fashion.

Polyenylphosphatidylcholine alleviates cardiorenal fibrosis, injury and dysfunction in spontaneously hypertensive rats by regulating Plpp3 signaling.

Objective: Polyenylphosphatidylcholine (PPC), a significant therapeutic agent for liver repair, exhibits potent antioxidant and anti-inflammatory properties. Nonetheless, its impact on hypertension and hypertensive vascular diseases requires clarification. Our objective was to elucidate the protective role and mechanism of PPC in a spontaneously hypertensive rat model.

Exploring the Spectral Prior for Hyperspectral Image Super-Resolution.

In recent years, many single hyperspectral image super-resolution methods have emerged to enhance the spatial resolution of hyperspectral images without hardware modification. However, existing methods typically face two significant challenges. First, they struggle to handle the high-dimensional nature of hyperspectral data, which often results in high computational complexity and inefficient information utilization.

Progressive Learning With Cross-Window Consistency for Semi-Supervised Semantic Segmentation.

Semi-supervised semantic segmentation focuses on the exploration of a small amount of labeled data and a large amount of unlabeled data, which is more in line with the demands of real-world image understanding applications. However, it is still hindered by the inability to fully and effectively leverage unlabeled images. In this paper, we reveal that cross-window consistency (CWC) is helpful in comprehensively extracting auxiliary supervision from unlabeled data.

Learning a Non-Locally Regularized Convolutional Sparse Representation for Joint Chromatic and Polarimetric Demosaicking.

Division of focal plane color polarization camera becomes the mainstream in polarimetric imaging for it directly captures color polarization mosaic image by one snapshot, so image demosaicking is an essential task. Current color polarization demosaicking (CPDM) methods are prone to unsatisfied results since it's difficult to recover missed 15 or 14 pixels out of 16 pixels in color polarization mosaic images. To address this problem, a non-locally regularized convolutional sparse regularization model, which is advantaged in denoising and edge maintaining, is proposed to recall more information for CPDM task, and the CPDM task is transformed into an energy function to be solved by ADMM optimization.

Chemometric-based analysis and bioassay guided identification of potent compounds with intestinal motility promoting effects from Dalitong Granules.

Ethnopharmacological Relevance: Dalitong Granules (DLT), a potent Traditional Chinese Medicine known for its ability to promote gastrointestinal motility, is widely used in clinical practice for the treatment of Functional Dyspepsia (FD). Despite the remarkable clinical efficacy of DLT, the specific components responsible for its effectiveness remains unclear.

Aim Of The Study: The study aimed to identify potential active ingredients of DLT for treating FD through spectrum-effect relationship analysis, multivariate statistical analysis and network pharmacology analysis.