Metabolic biomarkers of neonatal sepsis: identification using metabolomics combined with machine learning.

Background: Sepsis is a common disease associated with neonatal and infant mortality, and for diagnosis, blood culture is currently the gold standard method, but it has a low positivity rate and requires more than 2 days to develop. Meanwhile, unfortunately, the specific biomarkers for the early and timely diagnosis of sepsis in infants and for the determination of the severity of this disease are lacking in clinical practice.

Methods: Samples from 18 sepsis infants with comorbidities, 25 sepsis infants without comorbidities, and 25 infants with noninfectious diseases were evaluated using a serum metabolomics approach based on liquid chromatography‒mass spectrometry (LC‒MS) technology.

Preoperative Ki-67 proliferation index prediction with a radiomics nomogram in stage T1a-b lung adenocarcinoma.

Objectives: To establish a radiomics nomogram for preoperative prediction of Ki-67 proliferation index in stage T1a-b lung adenocarcinoma.

Methods: A total of 206 patients with pathologically confirmed lung adenocarcinoma who underwent CT scans within 2 weeks preoperatively from January 2016 to June 2020 were retrospectively included. Ki-67 index ≤ 10% was considered low expression, and Ki-67 index > 10% was considered high expression.

A Nomogram Combined Radiomics and Clinical Features as Imaging Biomarkers for Prediction of Visceral Pleural Invasion in Lung Adenocarcinoma.

Objectives: To develop and validate a nomogram model based on radiomics features for preoperative prediction of visceral pleural invasion (VPI) in patients with lung adenocarcinoma.

Methods: A total of 659 patients with surgically pathologically confirmed lung adenocarcinoma underwent CT examination. All cases were divided into a training cohort (n = 466) and a validation cohort (n = 193).

A Combination of Radiomic Features, Imaging Characteristics, and Serum Tumor Biomarkers to Predict the Possibility of the High-Grade Subtypes of Lung Adenocarcinoma.

Rationale And Objectives: Lung adenocarcinomas (LADC) containing high-grade subtypes have a poorer prognosis. And some studies have shown that high-grade subtypes have been identified as an independent predictor of local recurrence in patients treated with limited resection. The aim of this study was to construct a combined model based on radiomic features, imaging characteristics and serum tumor biomarkers to predict the possibility of preoperative high-grade subtypes.

Dynamics and Concordance Abnormalities Among Indices of Intrinsic Brain Activity in Individuals With Subjective Cognitive Decline: A Temporal Dynamics Resting-State Functional Magnetic Resonance Imaging Analysis.

Individuals with subjective cognitive decline (SCD) are more likely to develop into Alzheimer disease (AD) in the future. Resting-state functional magnetic resonance imaging (rs-fMRI) studies have shown alterations of intrinsic brain activity (IBA) in SCD individuals. However, rs-fMRI studies to date have mainly focused on static characteristics of IBA, with few studies reporting dynamics- and concordance-related changes in IBA indices in SCD individuals.