Uncovering the genetic variation spectrum of colorectal polyposis from a multicentre cohort in China.

This multicentre study addresses the genetic spectrum of colorectal polyposis in China. We analyzed 120 patients with over 10 adenomas using a 139-gene next-generation sequencing panel and multiplex ligation-dependent probe amplification. Findings revealed that 89 patients carried pathogenic germline variants, primarily in the APC gene.

Marine Heatwaves and Iceberg Melting in Polar Areas Intensify Phytoplankton Blooms.

Climate change has led to increases in the intensity and frequency of marine heatwaves (MHWs). However, the impact of MHWs on phytoplankton at the global scale remains unclear. The metaheuristic superlearner proposed in this research indicates that the occurrence of MHWs weakens the Fe limitation of phytoplankton growth, leading to intensified phytoplankton blooms.

Prediction of Flares in Systemic Lupus Erythematosus During Post-Remission Follow-up.

Purpose: Patients at high risk of SLE flares benefit from being identified before flares; this can be done by predictors of flares. This study aimed to explore the predictive factors and model of SLE flares after remission, providing basis for clinical decision-making.

Patients And Methods: SLE patients recruited at the Peking Union Medical College Hospital (PUMCH), were all registered in the Chinese SLE treatment and research (CSTAR) registry cohort and had experienced at least one remission before December 31, 2020.

Design, synthesis, and biological evaluation of novel PROTACs compounds with good ERα degradation ability.

A series of ER-PROTACs compounds were designed, synthesized and tested for their ability to degrade estrogen receptor proteins and exhibit Human breast cancer cells (MCF-7) inhibition activity. Molecular docking simulations were performed using Discovery studio. Among these compounds, QDE-003-W had the highest estrogen receptor protein degradation ability and cellular activity, with a DC value of 95 nM, for estrogen receptor protein degradation and an IC value of 30.

Diagnostic value of deep learning of multimodal imaging of thyroid for TI-RADS category 3-5 classification.

Background: Thyroid nodules classified within the Thyroid Imaging Reporting and Data Systems (TI-RADS) category 3-5 are typically regarded as having varying degrees of malignancy risk, with the risk increasing from TI-RADS 3 to TI-RADS 5. While some of these nodules may undergo fine-needle aspiration (FNA) biopsy to assess their nature, this procedure carries a risk of false negatives and inherent complications. To avoid the need for unnecessary biopsy examination, we explored a method for distinguishing the benign and malignant characteristics of thyroid TI-RADS 3-5 nodules based on deep-learning ultrasound images combined with computed tomography (CT).

Energy evolution and damage ontology modeling of coal destruction at different water contents.

The aim of this study was to investigate the energy evolution characteristics and an ontological model of the deformation of coal under different water contents. Uniaxial compression tests were conducted for coal with different water contents, and the analyses were based on the energy principle and the principle of minimum energy dissipation. The results showed that the physical properties of the coal specimens were different under different water contents, the peak strain was positively correlated with water content, and the compressive strength and elastic modulus were negatively correlated with water content.

SVGDreamer++: Advancing Editability and Diversity in Text-Guided SVG Generation.

Recently, text-guided scalable vector graphics (SVG) synthesis has shown great promise in domains like iconography and sketching. However, existing Text-to-SVG methods often face challenges in editability, visual quality, and diversity. To address these issues, we propose a novel framework for text-guided SVG synthesis that significantly enhances editability, quality, and diversity.

Two Emerging Providencia Species from Clinical Samples: Providencia zhejiangensis and Providencia xihuensis sp. nov.

Members of the genus Providencia are typically opportunistic pathogens that can cause severe infections in immunocompromised hosts. This study identified two Providencia strains, SKLX146130 and SKLX074055, representing novel species designated as Providencia zhejiangensis sp. nov.

A deep learning based ultrasound diagnostic tool driven by 3D visualization of thyroid nodules.

Recognizing the limitations of computer-assisted tools for thyroid nodule diagnosis using static ultrasound images, this study developed a diagnostic tool utilizing dynamic ultrasound video, namely Thyroid Nodules Visualization (TNVis), by leveraging a two-stage deep learning framework that involved three-dimensional (3D) visualization. In this multicenter study, 4569 cases were included for framework development, and data from seven hospitals were employed for diagnostic validation. TNVis achieved a Dice similarity coefficient of 0.

Comparative Genomics of : Structural Conservation and Gene Transfer Between Chloroplast and Mitochondrial Genomes.

, a unicellular multinucleate green alga in the genus , plays vital ecological roles and represents a key evolutionary link between unicellular and multicellular algae. However, its weak genetic baseline data have constrained the progress of evolutionary research. In this study, we successfully assembled and annotated the complete circular chloroplast and mitochondrial genomes of .

Bibliometric insights into systemic sclerosis with renal involvement: trends, contributions, and future directions.

Background: Renal involvement is not uncommon in patients with systemic sclerosis (SSc) and presents in various forms, particularly progressing to scleroderma renal crisis (SRC), which is associated with poor prognosis. Therefore, understanding the research trends in this field is critical for advancing clinical management and therapeutic strategies.

Methods: A bibliometric analysis was conducted using the Web of Science Core Collection, examining publications related to SSc and renal involvement from January 2000 to November 2024.

The Value of NLR and PLR in the Diagnosis of Rheumatoid Arthritis Combined with Interstitial Lung Disease and Assessment of Treatment Effect: A Retrospective Cohort Study.

Objective: This retrospective cohort study investigated the value of neutrophil-lymphocyte ratio (NLR) and platelet-lymphocyte ratio (PLR) in the diagnosis and treatment of rheumatoid arthritis complicated with interstitial lung disease (RA-ILD).

Methods: A total of 163 patients with newly diagnosed rheumatoid arthritis (RA) were enrolled, with 122 patients in the RA group and 41 patients in the RA-ILD group. The mean age of the RA group was 63.

New insights into the salt-responsive regulation in eelgrass at transcriptional and post-transcriptional levels.

Introduction: The adaptation mechanisms of marine plants to the environments have garnered significant attention in recent years. Eelgrass (), a representative marine angiosperm, serves as an ideal model for investigating the mechanisms underlying salt tolerance.

Methods: This study integrated mRNA, sRNA, and degradome sequencing data to identify key genes associated with salt tolerance in eelgrass.

Leveraging Large Language Models for Infectious Disease Surveillance-Using a Web Service for Monitoring COVID-19 Patterns From Self-Reporting Tweets: Content Analysis.

Background: The emergence of new SARS-CoV-2 variants, the resulting reinfections, and post-COVID-19 condition continue to impact many people's lives. Tracking websites like the one at Johns Hopkins University no longer report the daily confirmed cases, posing challenges to accurately determine the true extent of infections. Many COVID-19 cases with mild symptoms are self-assessed at home and reported on social media, which provides an opportunity to monitor and understand the progression and evolving trends of the disease.

scBSP: A fast and accurate tool for identifying spatially variable features from high-resolution spatial omics data.

Emerging spatial omics technologies empower comprehensive exploration of biological systems from multi-omics perspectives in their native tissue location in two and three-dimensional space. However, sparse sequencing capacity and growing spatial resolution in spatial omics present significant computational challenges in identifying biologically meaningful molecules that exhibit variable spatial distributions across different omics. We introduce scBSP, an open-source, versatile, and user-friendly package for identifying spatially variable features in high-resolution spatial omics data.

A nomogram for diagnosis of BI-RADS 4 breast nodules based on three-dimensional volume ultrasound.

Objectives: The classification of malignant breast nodules into four categories according to the Breast Imaging Reporting and Data System (BI-RADS) presents significant variability, posing challenges in clinical diagnosis. This study investigates whether a nomogram prediction model incorporating automated breast ultrasound system (ABUS) can improve the accuracy of differentiating benign and malignant BI-RADS 4 breast nodules.

Methods: Data were collected for a total of 257 nodules with breast nodules corresponding to BI-RADS 4 who underwent ABUS examination and for whom pathology results were obtained from January 2019 to August 2022.

A hybrid magnetic reset design for the high voltage pulse generator based on forward circuit and magnetic superposition.

Pulsed power technology has found widespread application in environmental governance, biomedicine, food processing, and other fields. This study proposes a pulse generator using forward topology and magnetic superposition to get high-voltage outputs. This design could adjust the pulse width in a relatively larger range by optimizing the coil structure and turns.

A multicenter diagnostic study of thyroid nodule with Hashimoto's thyroiditis enabled by Hashimoto's thyroiditis nodule-artificial intelligence model.

Objective: This study aimed to develop a Hashimoto's thyroiditis nodule-artificial intelligence (HTN-AI) model to optimize the diagnosis of thyroid nodules with Hashimoto's thyroiditis (HT) of which the efficiency and accuracy remain challenging.

Design And Methods: This study included 5709 patients from 10 hospitals between January 2014 and March 2024. Among them, 5053 thyroid nodules were divided into training and testing sets in a 9:1 ratio.

Identifying Receptor Kinase Substrates Using an 8000 Peptide Kinase Client Library Enriched for Conserved Phosphorylation Sites.

In eukaryotic organisms, protein kinases regulate diverse protein activities and signaling pathways through phosphorylation of specific protein substrates. Isolating and characterizing kinase substrates is vital for defining downstream signaling pathways. The kinase-client (KiC) assay is an in vitro synthetic peptide LC-MS/MS phosphorylation assay that has enabled identification of protein substrates (i.

The impact of artificial intelligence on corporate green innovation: Can "increasing quantity" and "improving quality" go hand in hand?

In the current era of digitalization and greenization, it is of great importance to explore how enterprises utilize artificial intelligence (AI) to promote green innovation. This paper explores the green innovation effects of AI and its underlying mechanisms from the perspective of corporate governance, using a sample of Chinese A-share listed companies from 2007 to 2021. Our results show that AI has a significant positive impact on corporate green innovation, in terms of both quantity and quality.

Clinical characteristics and clinical risk model of the lower gastrointestinal involvement in systemic sclerosis.

Objectives: Systemic sclerosis (SSc) is a systemic autoimmune disease that could involve multiple organs. The lower gastrointestinal involvement (LGIT) in systemic sclerosis (SSc-LGIT) is a serious manifestation and has a poor prognosis. This study aims to explore the related risk factors of SSc-LGIT that require hospitalisation and build a clinical risk model.

A Meta-Analysis of Artificial Intelligence Technologies Use and Loneliness: Examining the Influence of Physical Embodiment, Age Differences, and Effect Direction.

Recent research has investigated the connection between artificial intelligence (AI) utilization and feelings of loneliness, yielding inconsistent outcomes. This meta-analysis aims to clarify this relationship by synthesizing data from 47 relevant studies across 21 publications. Findings indicate a generally significant positive correlation between AI use and loneliness ( = 0.

Age-stratified deep learning model for thyroid tumor classification: a multicenter diagnostic study.

Objectives: Thyroid cancer, the only cancer that uses age as a specific predictor of survival, is increasing in incidence, yet it has a low mortality rate, which can lead to overdiagnosis and overtreatment. We developed an age-stratified deep learning (DL) model (hereafter, ASMCNet) for classifying thyroid nodules and aimed to investigate the effect of age stratification on the accuracy of a DL model, exploring how ASMCNet can help radiologists improve diagnostic performance and avoid unnecessary biopsies.

Methods: In this retrospective study, we used ultrasound images from three hospitals, a total of 10,391 images of 5934 patients were used for training, validation, and testing.

Monocyte-macrophage dynamics as key in disparate lung and peripheral immune responses in severe anti-melanoma differentiation-associated gene 5-positive dermatomyositis-related interstitial lung disease.

Background: Anti-melanoma differentiation-associated gene 5-positive dermatomyositis (anti-MDA5+ DM) is a rare inflammatory autoimmune disorder often complicated by life-threatening rapidly progressive interstitial lung disease (RP-ILD). The underlying mechanisms driving immune dysfunction and lung injury, however, remain poorly understood. The study aims to gain insights into the disrupted immune landscape in peripheral and pulmonary compartments of severe anti-MDA5+ DM and explore potential therapeutic targets.