Early detection of bloodstream infection in critically ill children using artificial intelligence.

Background: Despite the high mortality associated with bloodstream infection (BSI), early detection of this condition is challenging in critical settings. The objective of this study was to create a machine learning tool for rapid recognition of BSI in critically ill children.

Methods: Data were extracted from a derivative cohort comprising patients who underwent at least one blood culture during hospitalization in the pediatric intensive care unit (PICU) of a tertiary hospital from January 2020 to June 2023 for model development.

Development of a machine learning model to identify intraventricular hemorrhage using time-series analysis in preterm infants.

Although the prevalence of intraventricular hemorrhage (IVH) has remained high, no optimal strategy has been established to prevent it. This study included preterm newborns born at a gestational age of < 32 weeks admitted to the neonatal intensive care unit of a tertiary hospital between January 2013 and June 2022. Infants who had been observed for less than 24 h were excluded.

Individualized estimation of arterial carbon dioxide partial pressure using machine learning in children receiving mechanical ventilation.

Background: Measuring arterial partial pressure of carbon dioxide (PaCO) is crucial for proper mechanical ventilation, but the current sampling method is invasive. End-tidal carbon dioxide (EtCO) has been used as a surrogate, which can be measured non-invasively, but its limited accuracy is due to ventilation-perfusion mismatch. This study aimed to develop a non-invasive PaCO estimation model using machine learning.

Hemophagocytic Lymphohistiocytosis as Initial Presentation of Malignancy in Pediatric Patients: Rare but Not to Be Ignored.

It is complicated to establish a consensus on the management and diagnosis of malignancy-triggered hemophagocytic lymphohistiocytosis (M-HLH) in children, as an initial presentation of malignancy is complicated. In this paper, we analyze the clinical characteristics and outcomes of eight pediatric patients in which M-HLH was the initial presentation of malignancy. All patients had hematologic malignancies: three subcutaneous panniculitis-like T-cell lymphomas, two acute lymphoblastic leukemias, two anaplastic large cell lymphomas, and a systemic EBV + T-cell lymphoma of childhood.

Uniform Ag Nanocubes Prepared by AgCl Particle-Mediated Heterogeneous Nucleation and Disassembly and Their Mechanism Study by DFT Calculation.

Uniform Ag nanocubes are reproducibly synthesized by a AgCl particle-mediated heterogeneous nucleation and disassembly process in polyol chemistry. By introducing N,N-dimethylformamide (DMF) in a conventional polyol method with HCl etchant, Ag nanocrystals (NCs) begin to be nucleated on the surface of AgCl-precipitated particles due to the promoted reduction reaction by DMF. The nucleated Ag NCs on the AgCl particles are grown to Ag nanocubes in shape by consuming Ag sources from the AgCl mother particles.

Pyrene-Tagged Ionic Liquids: Separable Organic Catalysts for S2 Fluorination.

We prepared pyrene-substituted imidazolium-based ionic liquids (PILs) as organic catalysts for the S2 fluorination using alkali metal fluoride (MF). In this system, the PIL significantly enhanced the reactivity of MF due to the phase-transfer catalytic effect of the imidazolium moiety as well as the metal cation-π (pyrene) interactions. Furthermore, this homogeneous catalyst PIL was easily separated from the reaction mixture using reduced graphene oxide by π-π stacking with the pyrene of PIL.

Uniform Microgels Containing Agglomerates of Silver Nanocubes for Molecular Size-Selectivity and High SERS Activity.

Surface-enhanced Raman scattering (SERS) is a promising technique for molecular analysis as the molecular fingerprints (Raman spectra) are amplified to detectable levels compared with common spectroscopy. Metal nanostructures localize electromagnetic field on their surfaces, which can lead to dramatic increase of Raman intensity of molecules adsorbed. However, the metal surfaces are prone to contamination, thereby requiring pretreatment of samples to remove adhesive molecules.