Development of a CT radiomics prognostic model for post renal tumor resection overall survival based on transformer enhanced K-means clustering.

Background: Kidney tumors, common in the urinary system, have widely varying survival rates post-surgery. Current prognostic methods rely on invasive biopsies, highlighting the need for non-invasive, accurate prediction models to assist in clinical decision-making.

Purpose: This study aimed to construct a K-means clustering algorithm enhanced by Transformer-based feature transformation to predict the overall survival rate of patients after kidney tumor resection and provide an interpretability analysis of the model to assist in clinical decision-making.

Global transcriptome changes during growth of a novel Penicillium coffeae isolate on the wheat stripe rust fungus, Puccinia striiformis f. sp. tritici.

Wheat stripe rust caused by the fungus Puccinia striiformis f. sp. tritici (Pst) is currently the most destructive disease of wheat.

Development of a neoadjuvant chemotherapy efficacy prediction model for nasopharyngeal carcinoma integrating magnetic resonance radiomics and pathomics: a multi-center retrospective study.

Objective: This study aimed to develop and validate a predictive model for assessing the efficacy of neoadjuvant chemotherapy (NACT) in nasopharyngeal carcinoma (NPC) by integrating radiomics and pathomics features using a particle swarm optimization-supported support vector machine (PSO-SVM).

Methods: A retrospective multi-center study was conducted, which included 389 NPC patients who received NACT from three institutions. Radiomics features were extracted from magnetic resonance imaging scans, while pathomics features were derived from histopathological images.

The regulatory mechanisms of cerium oxide nanoparticles in oxidative stress and emerging applications in refractory wound care.

Cerium oxide nanoparticles (CeNPs) have emerged as a potent therapeutic agent in the realm of wound healing, attributing their efficacy predominantly to their exceptional antioxidant properties. Mimicking the activity of endogenous antioxidant enzymes, CeNPs alleviate oxidative stress and curtail the generation of inflammatory mediators, thus expediting the wound healing process. Their application spans various disease models, showcasing therapeutic potential in treating inflammatory responses and infections, particularly in oxidative stress-induced chronic wounds such as diabetic ulcers, radiation-induced skin injuries, and psoriasis.

Artificial intelligence in ischemic stroke images: current applications and future directions.

This paper reviews the current research progress in the application of Artificial Intelligence (AI) based on ischemic stroke imaging, analyzes the main challenges, and explores future research directions. This study emphasizes the application of AI in areas such as automatic segmentation of infarct areas, detection of large vessel occlusion, prediction of stroke outcomes, assessment of hemorrhagic transformation risk, forecasting of recurrent ischemic stroke risk, and automatic grading of collateral circulation. The research indicates that Machine Learning (ML) and Deep Learning (DL) technologies have tremendous potential for improving diagnostic accuracy, accelerating disease identification, and predicting disease progression and treatment responses.

Improved automatic segmentation of brain metastasis gross tumor volume in computed tomography images for radiotherapy: a position attention module for U-Net architecture.

Background: Brain metastases present significant challenges in radiotherapy due to the need for precise tumor delineation. Traditional methods often lack the efficiency and accuracy required for optimal treatment planning. This paper proposes an improved U-Net model that uses a position attention module (PAM) for automated segmentation of gross tumor volumes (GTVs) in computed tomography (CT) simulation images of patients with brain metastases to improve the efficiency and accuracy of radiotherapy planning and segmentation.

iGenSig-Rx: an integral genomic signature based white-box tool for modeling cancer therapeutic responses using multi-omics data.

Multi-omics sequencing is poised to revolutionize clinical care in the coming decade. However, there is a lack of effective and interpretable genome-wide modeling methods for the rational selection of patients for personalized interventions. To address this, we present iGenSig-Rx, an integral genomic signature-based approach, as a transparent tool for modeling therapeutic response using clinical trial datasets.

The effect of mindfulness-based cognitive therapy on the Clinical efficacy and psychological state in patients with functional dyspepsia.

Background And Aim: To observe the clinical therapeutic effect and mental state of mindfulness-based cognitive therapy (MBCT) in patients with functional dyspepsia (FD).

Methods: In this study, 80 patients suffering from FD in an outpatient clinic were enrolled from January to December 2020. Patients were randomly allocated into the control group (conventional treatment) and observation group (MBCT treatment).

Advances in research and application of artificial intelligence and radiomic predictive models based on intracranial aneurysm images.

Intracranial aneurysm is a high-risk disease, with imaging playing a crucial role in their diagnosis and treatment. The rapid advancement of artificial intelligence in imaging technology holds promise for the development of AI-based radiomics predictive models. These models could potentially enable the automatic detection and diagnosis of intracranial aneurysms, assess their status, and predict outcomes, thereby assisting in the creation of personalized treatment plans.

iGenSig-Rx: an integral genomic signature based white-box tool for modeling cancer therapeutic responses using multi-omics data.

Multi-omics sequencing is expected to become clinically routine within the next decade and transform clinical care. However, there is a paucity of viable and interpretable genome-wide modeling methods that can facilitate rational selection of patients for tailored intervention. Here we develop an integral genomic signature-based method called iGenSig-Rx as a white-box tool for modeling therapeutic response based on clinical trial datasets with improved cross-dataset applicability and tolerance to sequencing bias.

Spatiotemporal dynamics of self-generated imagery reveal a reverse cortical hierarchy from cue-induced imagery.

Visual imagery allows for the construction of rich internal experience in our mental world. However, it has remained poorly understood how imagery experience derives volitionally as opposed to being cue driven. Here, using electroencephalography and functional magnetic resonance imaging, we systematically investigate the spatiotemporal dynamics of self-generated imagery by having participants volitionally imagining one of the orientations from a learned pool.

Proteins released into the plant apoplast by the obligate parasitic protist Albugo selectively repress phyllosphere-associated bacteria.

Biotic and abiotic interactions shape natural microbial communities. The mechanisms behind microbe-microbe interactions, particularly those protein based, are not well understood. We hypothesize that released proteins with antimicrobial activity are a powerful and highly specific toolset to shape and defend plant niches.

Learning Representative Features by Deep Attention Network for 3D Point Cloud Registration.

Three-dimensional point cloud registration, which aims to find the transformation that best aligns two point clouds, is a widely studied problem in computer vision with a wide spectrum of applications, such as underground mining. Many learning-based approaches have been developed and have demonstrated their effectiveness for point cloud registration. Particularly, attention-based models have achieved outstanding performance due to the extra contextual information captured by attention mechanisms.

Survey on Exact kNN Queries over High-Dimensional Data Space.

nearest neighbours (kNN) queries are fundamental in many applications, ranging from data mining, recommendation system and Internet of Things, to Industry 4.0 framework applications. In mining, specifically, it can be used for the classification of human activities, iterative closest point registration and pattern recognition and has also been helpful for intrusion detection systems and fault detection.

De novo genome assembly of the medicinal plant Gentiana macrophylla provides insights into the genomic evolution and biosynthesis of iridoids.

Gentiana macrophylla is a perennial herb in the Gentianaceae family, whose dried roots are used in traditional Chinese medicine. Here, we assembled a chromosome-level genome of G. macrophylla using a combination of Nanopore, Illumina, and Hi-C scaffolding approaches.

WheatCENet: A Database for Comparative Co-expression Networks Analysis of Allohexaploid Wheat and Its Progenitors.

Genetic and epigenetic changes after polyploidization events could result in variable gene expression and modified regulatory networks. Here, using large-scale transcriptome data, we constructed co-expression networks for diploid, tetraploid, and hexaploid wheat species, and built a platform for comparing co-expression networks of allohexaploid wheat and its progenitors, named WheatCENet. WheatCENet is a platform for searching and comparing specific functional co-expression networks, as well as identifying the related functions of the genes clustered therein.

A recent burst of gene duplications in Triticeae.

Gene duplication provides raw genetic materials for evolution and potentially novel genes for crop improvement. The two seminal genomic studies of both mentioned the large number of genes independently duplicated in recent years, but the duplication mechanism and the evolutionary significance of these gene duplicates have not yet been investigated. Here, we found that a recent burst of gene duplications (hereafter abbreviated as the RBGD) has probably occurred in all sequenced Triticeae species.

Physical separation of haplotypes in dikaryons allows benchmarking of phasing accuracy in Nanopore and HiFi assemblies with Hi-C data.

Background: Most animals and plants have more than one set of chromosomes and package these haplotypes into a single nucleus within each cell. In contrast, many fungal species carry multiple haploid nuclei per cell. Rust fungi are such species with two nuclei (karyons) that contain a full set of haploid chromosomes each.

The complete chloroplast genome of (Nymphaeaceae) from Rwanda, Africa.

is classified in the Nymphaeaceae, and is the smallest water lily in the world. It has been extinct its native environment and needs urgent protection. Here, we report and characterize the complete chloroplast genome of .

Precise Control of Radial Catenane Synthesis via Clipping and Pumping.

An unprecedented molecular pumping cassette was designed and implemented for the construction of molecular necklaces, that is, radial []catenanes. The mechanism was fully confirmed on a model [2]pseudorotaxane, and the novel clipping-followed-by-pumping strategy was used to prepare a series of []catenanes ( = 2-5). A pair of [3]catenane diastereomers sequentially threaded with two different wheels was also accomplished.

Long-Reads-Based Metagenomics in Clinical Diagnosis With a Special Focus on Fungal Infections.

Identification of the causative infectious agent is essential in the management of infectious diseases, with the ideal diagnostic method being rapid, accurate, and informative, while remaining cost-effective. Traditional diagnostic techniques rely on culturing and cell propagation to isolate and identify the causative pathogen. These techniques are limited by the ability and the time required to grow or propagate an agent and the facts that identification based on morphological traits are non-specific, insensitive, and reliant on technical expertise.

Whole-Genome Sequencing of Acer catalpifolium Reveals Evolutionary History of Endangered Species.

Acer catalpifolium is an endangered species restricted to remote localities of West China. Understanding the genomic content and evolution of A. catalpifolium is essential to conservation efforts of this rare and ecologically valuable plant.