Prognostic factors among patients with Shiga toxin-producing Escherichia coli hemolytic uremic syndrome: A retrospective cohort study using a nationwide inpatient database in Japan

Myojin, Shota; Michihata, Nobuaki; Shoji, Kensuke; Takanashi, Jun‐ichi; Matsui, Hiroki; Fushimi, Kiyohide; Miyairi, Isao; Yasunaga, Hideo

doi:10.1016/j.jiac.2023.02.016

Journal of Infection and Chemotherapy

2023

DOI: 10.1016/j.jiac.2023.02.016

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Prognostic factors among patients with Shiga toxin-producing Escherichia coli hemolytic uremic syndrome: A retrospective cohort study using a nationwide inpatient database in Japan

Shota Myojin

Nobuaki Michihata

Kensuke Shoji

et al.

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Optical Spectroscopy Based Microfluidic Platform for Detecting Pathogens Using Immunomagnetic Separation

Hussain,

He,

Chen

et al. 2023

Journal of Nanoelectronics and Optoelectronics

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Rapid detection of pathogens is crucial for controlling pathogenic diseases and improving the quality of food industry. This paper presents a microfluidic platform integrated with optical detection module to rapidly detect Pseudomonas aeruginosa (P. aeruginosa) and Escherichia coli (E. coli). The detection module comprises a microfluidic chip embedded with fiber optics connected to photosensors and a laser source. Initially, the immunomagnetic separation technique was applied to isolate specific pathogens out of testing sample using magnetic particles coated with antibodies. The separated sample containing magnetic beads was loaded into the chip and passed by the monochromatic light in the detection module. The scattered light signals from the passing magnetic beads were collected by the photosensors coupled with fiber optics. The acquired raw data were pre-processed by removing noise and distortions for further analysis. A new calibration model known as the Optical Transformer (OptiTr) structure was used for classification of acquired data. Convolution-based classical model (ResNeXt) was used as baseline comparison. The system provided higher classification results using the OptiTr model for classifying P. aeruginosa and E. coli, with accuracy values of 99.57% and 94.59%, respectively. The blank samples without P. aeruginosa and E. coli showed a classification accuracy of 94.73%. The microfluidic platform has the capability to identify P. aeruginosa and E. coli with a detection limit of 101 CFU/mL. The technique does not require complex sample preparation methods or complicated laboratory tools. The developed technique has a 15-minute detection time with a 40-minute sample preparation duration.

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Optical Spectroscopy Based Microfluidic Platform for Detecting Pathogens Using Immunomagnetic Separation

Hussain,

He,

Chen

et al. 2023

Journal of Nanoelectronics and Optoelectronics

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Deletion of Sphingosine Kinase 2 Attenuates Acute Kidney Injury in Mice with Hemolytic-Uremic Syndrome

Müller,

Krieg,

Lange-Polovinkin

et al. 2024

IJMS

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Typical hemolytic uremic syndrome (HUS) can occur as a severe systemic complication of infections with Shiga toxin (Stx)-producing Escherichia coli. Its pathology can be induced by Stx types, resulting in toxin-mediated damage to renal barriers, inflammation, and the development of acute kidney injury (AKI). Two sphingosine kinase (SphK) isozymes, SphK1 and SphK2, have been shown to be involved in barrier maintenance and renal inflammatory diseases. Therefore, we sought to determine their role in the pathogenesis of HUS. Experimental HUS was induced by the repeated administration of Stx2 in wild-type (WT) and SphK1 (SphK1−/−) or SphK2 (SphK2−/−) null mutant mice. Disease severity was evaluated by assessing clinical symptoms, renal injury and dysfunction, inflammatory status and sphingolipid levels on day 5 of HUS development. Renal inflammation and injury were found to be attenuated in the SphK2−/− mice, but exacerbated in the SphK1−/− mice compared to the WT mice. The divergent outcome appeared to be associated with oppositely altered sphingolipid levels. This study represents the first description of the distinct roles of SphK1−/− and SphK2−/− in the pathogenesis of HUS. The identification of sphingolipid metabolism as a potential target for HUS therapy represents a significant advance in the field of HUS research.

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Prognostic factors among patients with Shiga toxin-producing Escherichia coli hemolytic uremic syndrome: A retrospective cohort study using a nationwide inpatient database in Japan

Cited by 2 publications

References 23 publications

Optical Spectroscopy Based Microfluidic Platform for Detecting Pathogens Using Immunomagnetic Separation

Optical Spectroscopy Based Microfluidic Platform for Detecting Pathogens Using Immunomagnetic Separation

Deletion of Sphingosine Kinase 2 Attenuates Acute Kidney Injury in Mice with Hemolytic-Uremic Syndrome

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