66 research outputs found
Experience of Nursing and Pipeline Maintenance before and after Implantation ECMO in Patients with Acute Respiratory Distress Syndrome (A Case)
Objective: experience in post-implantation care and pipeline maintenance in patients with acute respiratory distress syndrome. Methods:2020Admitted on 27 July1 Cases of severe pneumonia were transferred to severe ventilator on August 6 and to critical ECMO on August 10. Results: after active treatment, especially for the late stage of ECMO pipeline, the vital signs of the patients improved obviously and the condition gradually stabilized. Conclusion: The nursing care before and after the establishment of ECMO pipeline in patients with acute respiratory distress syndrome, the matters needing attention and the working experience after the establishment, It can provide a reference for the treatment of severe infectious diseases in the future
DropMessage: Unifying Random Dropping for Graph Neural Networks
Graph Neural Networks (GNNs) are powerful tools for graph representation
learning. Despite their rapid development, GNNs also faces some challenges,
such as over-fitting, over-smoothing, and non-robustness. Previous works
indicate that these problems can be alleviated by random dropping methods,
which integrate noises into models by randomly masking parts of the input.
However, some open-ended problems of random dropping on GNNs remain to solve.
First, it is challenging to find a universal method that are suitable for all
cases considering the divergence of different datasets and models. Second,
random noises introduced to GNNs cause the incomplete coverage of parameters
and unstable training process. In this paper, we propose a novel random
dropping method called DropMessage, which performs dropping operations directly
on the message matrix and can be applied to any message-passing GNNs.
Furthermore, we elaborate the superiority of DropMessage: it stabilizes the
training process by reducing sample variance; it keeps information diversity
from the perspective of information theory, which makes it a theoretical upper
bound of other methods. Also, we unify existing random dropping methods into
our framework and analyze their effects on GNNs. To evaluate our proposed
method, we conduct experiments that aims for multiple tasks on five public
datasets and two industrial datasets with various backbone models. The
experimental results show that DropMessage has both advantages of effectiveness
and generalization
In vitro evaluation of a novel fluoride-coated clear aligner with antibacterial and enamel remineralization abilities
Antibacterial and fluorescent clear aligner attachment resin modified with chlorhexidine loaded mesoporous silica nanoparticles and zinc oxide quantum dots
The knowledge, experience, and attitude on artificial intelligence-assisted cephalometric analysis: Survey of orthodontists and orthodontic students
Case Report: Chlamydia psittaci pneumonia complicated by Guillain-Barré syndrome detected using metagenomic next-generation sequencing
Psittacosis and Guillain-Barré syndrome are both rare clinical diseases with low incidence, and their combination has rarely been reported. Here, we report a case of Chlamydia psittaci pneumonia combined with Guillain-Barré syndrome. The patient initially presented with high fever, difficulty breathing, and fatigue. Chest computerised tomography indicated large consolidation opacities in both lungs. Metagenomic next-generation sequencing clearly identified the pathogen as C. psittaci. The patient’s fever subsided after targeted antibiotic treatment, but difficulty breathing and fatigue worsened, and the patient developed symmetric limb numbness and weakness. Lumbar puncture, electrophysiological examination, and clinical characteristics were suggestive of Guillain-Barré syndrome, and the symptoms improved after treatment with human immunoglobulin. The results of this study suggest that metagenomic next-generation sequencing is useful for the rapid diagnosis of pulmonary infectious agents. Psittacosis is closely associated with the development of Guillain-Barré syndrome; however, more cases are needed to support this conclusion, and early targeted antibiotic treatment, immunotherapy, and basic supportive treatment are essential for improving outcomes
Robust estimation of bacterial cell count from optical density
Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data
Nanodelivery of STING agonists against cancer and infectious diseases
Vaccination is a modality that has been widely explored for the treatment of various diseases. To increase the potency of vaccine formulations, immunostimulatory adjuvants have been regularly exploited, and the stimulator of interferon genes (STING) signaling pathway has recently emerged as a remarkable therapeutic target. STING is an endogenous protein on the endoplasmic reticulum that is a downstream sensor to cytosolic DNA. Upon activation, STING initiates a series of intracellular signaling cascades that ultimately generate potent type I interferon-mediated immune responses. Both natural and synthetic agonists have been used to stimulate the STING pathway, but they are usually administered locally due to low bioavailability, instability, and difficulty in bypassing the plasma membrane. With excellent pharmacokinetic profiles and versatility, nanocarriers can address many of these challenges and broaden the application of STING vaccines. Along these lines, STING-inducing nanovaccines are being developed to address a wide range of diseases. In this review, we discuss the recent advances in STING nanovaccines for anticancer, antiviral, and antibacterial applications
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