[Using Lean Management to Improve the Nursing Admission Process for COVID-19 Patients in the Intensive Care Unit].

Background & Problems: Safe and efficient operational workflows in nursing care can alleviate workloads, enhance quality of care, and improve job satisfaction. A recent survey indicates that the admission process for patients with COVID-19 in nursing care is excessively lengthy due primarily to the waiting time for physicians to enter the ward, external support, and frequent reorganization of medical materials. Inadequate organization measures have resulted in requisite materials not being centralized, leading to increased travel times, interruptions in nursing records maintenance, unprofessional explanations, and time-consuming consent form signing processes.

Revolutionizing Oxygen Delivery: The Adjustable Oxygen Adapter for Uninterrupted Therapy and Enhanced Patient Safety.

This study introduces the "Adjustable Oxygen Adapter," designed to address interruptions in oxygen supply for patients transitioning from oxygen spray bottles, particularly in wards with single-outlet flowmeters. Inspired by the "Three-Way Piston Rotating Adapter," this innovative design, operated by a single switch, ensures uninterrupted oxygen supply during equipment changes. Stability testing, conducted with a flow monitor by a respiratory therapist, confirms that the adapter provides a stable flow rate and oxygen concentration, offering a practical solution for seamless transitions between oxygen devices in clinical settings.

Dual-Sensitive Gold-Nanocubes Platform with Synergistic Immunotherapy for Inducing Immune Cycle Using NIR-Mediated PTT/NO/IDO.

Currently, the combination therapies based on immunotherapy have been rapidly developed, but the response rate has not always increased as expected. Nano-platform has become a potential strategy which can trigger multi-functions to increase immunotherapeutic efficacy via activating T-cells and photothermal effect. Herein, to avoid the self-degradation and provide pH-sensitive property, S-nitrosoglutathione (GSNO) was loaded in gold nanocubes (AuNCs) with polyacrylic acid (PAA) coating.

Ansamitocin P3-Loaded Gold-NanoCage Conjugated with Immune Checkpoint Inhibitor to Enhance Photo-Chemo-Thermal Maturation of Dendritic Cells for Hepatocellular Carcinoma.

Immunotherapy is a newly developed method for cancer treatment, but still generates limited response in partial patients for hepatocellular carcinoma (HCC) because the immunity cycle is limited by the tumor microenvironment (TME). Herein, we introduce multifunctional gold nanocages (AuNCs)-based nanocarriers with Ansamitocin P3 (AP3) loaded and anti-PDL1 binding (AP3-AuNCs-anti-PDL1) which can combine photothermal therapy, chemotherapeutic agent-triggered DCs maturation, and checkpoint immunotherapy in one platform. The AP3-AuNCs-anti-PDL1 using Avidin-biotin to bind anti-PDL1 on the surface of AP3-AuNCs showed specifically cellular targeting compared to AuNCs, which can increase the immune responses.

Advances in Magnetic Nanoparticle-Mediated Cancer Immune-Theranostics.

Cancer immunotherapy is a cutting-edge strategy that eliminates cancer cells by amplifying the host's immune system. However, the low response rate and risks of inducing systemic toxicity have raised uncertainty in the treatment. Magnetic nanoparticles (MNPs) as a versatile theranostic tool can be used to target delivery of multiple immunotherapeutics and monitor cell/tissue responses.

Predicting diabetic retinopathy and identifying interpretable biomedical features using machine learning algorithms.

Background: The risk factors of diabetic retinopathy (DR) were investigated extensively in the past studies, but it remains unknown which risk factors were more associated with the DR than others. If we can detect the DR related risk factors more accurately, we can then exercise early prevention strategies for diabetic retinopathy in the most high-risk population. The purpose of this study is to build a prediction model for the DR in type 2 diabetes mellitus using data mining techniques including the support vector machines, decision trees, artificial neural networks, and logistic regressions.