Crotonylation of NAE1 Modulates Cardiac Hypertrophy via Gelsolin Neddylation.

Background: Cardiac hypertrophy and its associated remodeling are among the leading causes of heart failure. Lysine crotonylation is a recently discovered posttranslational modification whose role in cardiac hypertrophy remains largely unknown. NAE1 (NEDD8 [neural precursor cell expressed developmentally downregulated protein 8]-activating enzyme E1 regulatory subunit) is mainly involved in the neddylation modification of protein targets.

PET radiomics-based lymphovascular invasion prediction in lung cancer using multiple segmentation and multi-machine learning algorithms.

The current study aimed to predict lymphovascular invasion (LVI) using multiple machine learning algorithms and multi-segmentation positron emission tomography (PET) radiomics in non-small cell lung cancer (NSCLC) patients, offering new avenues for personalized treatment strategies and improving patient outcomes. One hundred and twenty-six patients with NSCLC were enrolled in this study. Various automated and semi-automated PET image segmentation methods were applied, including Local Active Contour (LAC), Fuzzy-C-mean (FCM), K-means (KM), Watershed, Region Growing (RG), and Iterative thresholding (IT) with different percentages of the threshold.

Forme fruste keratoconus detection with OCT corneal topography using artificial intelligence algorithms.

Purpose: To differentiate a normal cornea from a forme fruste keratoconus (FFKC) with the swept-source optical coherence tomography (SS-OCT) topography CASIA 2 using machine learning artificial intelligence algorithms.

Setting: Monocentric, performed in CHU Bordeaux, Bordeaux, France.

Design: Retrospective case-control.

Individualized prediction of non-sentinel lymph node metastasis in Chinese breast cancer patients with ≥ 3 positive sentinel lymph nodes based on machine-learning algorithms.

Background: Axillary lymph node dissection (ALND) is a standard procedure for early-stage breast cancer (BC) patients with three or more positive sentinel lymph nodes (SLNs). However, ALND can lead to significant postoperative complications without always providing additional clinical benefits. This study aims to develop machine-learning (ML) models to predict non-sentinel lymph node (non-SLN) metastasis in Chinese BC patients with three or more positive SLNs, potentially allowing the omission of ALND.

Bilateral Perisylvian Polymicrogyria, Intellectual Disability and Nephronophthisis Associated With Compound Heterozygous Pathogenic Variants in the CEP83 Gene.

The centrosomal protein 83 (CEP83) is a centriolar protein involved in primary cilium assembly, an early and critical step in ciliogenesis. Bi-allelic pathogenic variants in the CEP83 gene have been associated with infantile nephronophthisis and, in a few patients, retinitis pigmentosa. We describe a 5-year-old boy with bilateral perisylvian polymicrogyria, intellectual disability, and nephronophthisis in whom, using exome sequencing, we identified the c.

Magnetic resonance imaging (MRI)-based intratumoral and peritumoral radiomics for prognosis prediction in glioma patients.

Aim: The purpose of this study was to identify robust radiological features from intratumoral and peritumoral regions, evaluate MRI protocols, and machine learning methods for overall survival stratification of glioma patients, and explore the relationship between radiological features and the tumour microenvironment.

Material And Methods: A retrospective analysis was conducted on 163 glioma patients, divided into a training set (n=113) and a testing set (n=50). For each patient, 2135 features were extracted from clinical MRI.

A combination model of CT-based radiomics and clinical biomarkers for staging liver fibrosis in the patients with chronic liver disease.

A combined model was developed using contrast-enhanced CT-based radiomics features and clinical characteristics to predict liver fibrosis stages in patients with chronic liver disease (CLD). We retrospectively analyzed multiphase CT scans and biopsy-confirmed liver fibrosis. 160 CLD patients were randomly divided into 7:3 training/validation ratio.

Effect of sequential delivery of 1- and 2-MHz bipolar microneedling radiofrequency energy on thermal tissue reactions in a minipig model.

Background: Bipolar microneedling radiofrequency (RF) treatment generates different patterns of thermal reactions, depending on the skin impedance and RF treatment parameters, including the frequency, power, conduction time, settings of sub-pulse packs, and penetrating depth and type of microneedles used. We compared the effect of sequential delivery of 1- and 2-MHz bipolar RF energy to in vivo minipig skin on thermal tissue reaction.

Methods: RF treatments at frequencies of 1 and 2 MHz were sequentially delivered to minipigs' skin in vivo.

Muscle reoxygenation is slower after higher cycling intensity, and is faster and more reliable in locomotor than in accessory muscle sites.

Introduction: Wearable near-infrared spectroscopy (NIRS) can be used during dynamic exercise to reflect the balance of muscle oxygen delivery and uptake. This study describes the behaviour and reliability of postexercise reoxygenation with NIRS as a function of exercise intensity at four muscle sites during an incremental cycling test. We discuss physiological components of faster and slower reoxygenation kinetics in the context of sport science and clinical applications.

Evaluation of Systemic Risk Factors in Patients with Diabetes Mellitus for Detecting Diabetic Retinopathy with Random Forest Classification Model.

Background: This study aims to assess systemic risk factors in diabetes mellitus (DM) patients and predict diabetic retinopathy (DR) using a Random Forest (RF) classification model.

Methods: We included DM patients presenting to the retina clinic for first-time DR screening. Data on age, gender, diabetes type, treatment history, DM control status, family history, pregnancy history, and systemic comorbidities were collected.

Randomized, Double-Blind, Placebo-Controlled Study of Anti-Mycobacterial Therapy (RHB-104) in Active Crohn's Disease.

This study, conducted between 4 October 2013, and 30 November 2018, tested the hypothesis that triple antimicrobial therapy, targeting subspecies (MAP), long considered a putative cause, would favorably affect Crohn's disease. A double-blind multicenter study of adults with active Crohn's disease, (i.e.

A CLRN3-Based CD8 T-Related Gene Signature Predicts Prognosis and Immunotherapy Response in Colorectal Cancer.

Background: Colorectal cancer (CRC) ranks among the most prevalent malignancies affecting the gastrointestinal tract. The infiltration of CD8 T cells significantly influences the prognosis and progression of tumor patients.

Methods: This study establishes a CRC immune risk model based on CD8 T cell-related genes.

Combined High-Throughput Proteomics and Random Forest Machine-Learning Approach Differentiates and Classifies Metabolic, Immune, Signaling and ECM Intra-Tumor Heterogeneity of Colorectal Cancer.

Colorectal cancer (CRC) is a frequent, worldwide tumor described for its huge complexity, including inter-/intra-heterogeneity and tumor microenvironment (TME) variability. Intra-tumor heterogeneity and its connections with metabolic reprogramming and epithelial-mesenchymal transition (EMT) were investigated with explorative shotgun proteomics complemented by a Random Forest (RF) machine-learning approach. Deep and superficial tumor regions and distant-site non-tumor samples from the same patients (n = 16) were analyzed.

Label-Free Surface-Enhanced Raman Spectroscopy with Machine Learning for the Diagnosis of Thyroid Cancer by Using Fine-Needle Aspiration Liquid Samples.

The incidence of thyroid cancer is increasing worldwide. Fine-needle aspiration (FNA) cytology is widely applied with the use of extracted biological cell samples, but current FNA cytology is labor-intensive, time-consuming, and can lead to the risk of false-negative results. Surface-enhanced Raman spectroscopy (SERS) combined with machine learning algorithms holds promise for cancer diagnosis.

Single- and multi-site radiomics may improve overall survival prediction for patients with metastatic lung adenocarcinoma.

Purpose: The purpose of this study was to assess whether single-site and multi-site radiomics could improve the prediction of overall survival (OS) of patients with metastatic lung adenocarcinoma compared to clinicopathological model.

Materials And Methods: Adults with metastatic lung adenocarcinoma, pretreatment whole-body contrast-enhanced computed tomography examinations, and performance status (WHO-PS) ≤ 2 were included in this retrospective single-center study, and randomly assigned to training and testing cohorts. Radiomics features (RFs) were extracted from all measurable lesions with volume ≥ 1 cm.

The Effect of Riboflavin on Neurological Rehabilitation after Traumatic Brain Injury in Children.

Background: Traumatic brain injury (TBI), which is the brain impairment and lesion caused by the external force injuring the head and the underlying brain, can cause pediatric death, disability, neurological disorders, and even lifelong disability. This study was to explore the effect of riboflavin (RF) on neurological rehabilitation and functional recovery after TBI.

Methods: The rat models of TBI were constructed by treating rats with controlled cortical impact (CCI).

Preoperative Prediction of Lymph Node Metastases in Nonfunctional Pancreatic Neuroendocrine Tumors Using a Combined CT Radiomics-Clinical Model.

Background: PanNETs are a rare group of pancreatic tumors that display heterogeneous histopathological and clinical behavior. Nodal disease has been established as one of the strongest predictors of patient outcomes in PanNETs. Lack of accurate preoperative assessment of nodal disease is a major limitation in the management of these patients, in particular those with small (< 2 cm) low-grade tumors.

Comparative analysis of features and classification techniques in breast cancer detection for Biglycan biomarker images.

Background: Breast cancer (BC) is considered the world's most prevalent cancer. Early diagnosis of BC enables patients to receive better care and treatment, hence lowering patient mortality rates. Breast lesion identification and classification are challenging even for experienced radiologists due to the complexity of breast tissue and variations in lesion presentations.