A self-powered temperature sensor based on Seebeck effect transduction was designed for photothermal−thermoelectric coupled immunoassay of α-fetoprotein (AFP). In this system, glucose oxidase (GOx)-conjugated detection antibody was first captured onto the microplate by target-induced sandwich-type immunoreaction. Thereafter, the as-generated hydrogen peroxide via the GOx−glucose system oxidized 3,3′,5,5′-tetrametylbenzidine (TMB) into photothermal product oxidized TMB (ox-TMB). Under near-infrared (NIR) laser irradiation, the temperature change of ox-TMB was read out in an electrical signal by the flexible thermoelectric module in a 3D-printed integrated detection device. Under optimal conditions, the photothermal−thermoelectric coupled immunoassay exhibited a limit of detection of 0.39 ng mL −1 AFP over a dynamic linear range from 0.5 to 60 ng mL −1 . Impressively, such a strategy presented herein offers tremendous potentials for applying many other high-efficiency thermoelectric materials in ultrasensitive biosensors.
Background: Dysbiosis of human gut microbiota is associated with a wide range of metabolic disorders, including gestational diabetes mellitus (GDM). Yet whether gut microbiota dysbiosis participates in the etiology of GDM remains largely unknown.Objectives: Our study was initiated to determine whether the alternations in gut microbial composition during early pregnancy linked to the later development of GDM, and explore the feasibility of microbial biomarkers for the early prediction of GDM.
Study design:This nested case-control study was based upon an early pregnancy follow-up cohort (ChiCTR1900020652). Gut microbiota profiles of 98 subjects with GDM and 98 matched healthy controls during the early pregnancy (10-15 weeks) were assessed via 16S rRNA gene amplicon sequencing of V4 region. The data set was randomly split into a discovery set and a validation set, the former was used to analyze the differences between GDM cases and controls in gut microbial composition and functional annotation, and to establish an early identification model of GDM, then the performance of the model was verified by the external validation set.Results: Bioinformatic analyses revealed changes to gut microbial composition with significant differences in relative abundance between the groups. Specifically, Eisenbergiella, Tyzzerella 4, and Lachnospiraceae NK4A136 were enriched in the GDM group, whereas Parabacteroides, Megasphaera, Eubacterium eligens group, etc. remained dominant in the controls. Correlation analysis revealed that GDM-enriched genera Eisenbergiella and Tyzzerella 4 were positively correlated with fasting blood glucose levels, while three control-enriched genera (Parabacteroides, Parasutterella, and Ruminococcaceae UCG 002) were the opposite. Further, GDM functional annotation modules revealed enrichment of modules for sphingolipid metabolism, starch and sucrose metabolism, etc., while lysine biosynthesis and nitrogen metabolism were reduced. Finally, five genera and two clinical indices were included in the linear discriminant analysis model for the prediction of GDM; the areas under receiver operating characteristic curves of the training and validation sets were 0.736 (95% confidence interval: 0.663-0.808) and 0.696 (0.575-0.818), respectively. Ma et al.
Gut Bacterial Dysbiosis Before GDMConclusions: Gut bacterial dysbiosis in early pregnancy was found to be associated with the later development of GDM, and gut microbiota-targeted biomarkers might be utilized as potential predictors of GDM.
This
work reports a contactless photoelectrochemical biosensor
based on an ultraviolet-assisted gas sensor (UV–AGS) with a
homemade three-dimensional (3D)-SnS2 nanosheet-functionalized
interdigitated electrode. After rigorous examination, it was found
that the gas responsiveness accelerated and the sensitivity increased
using the UV irradiation strategy. The effects of the interlayer structure
and the Schottky heterojunction on the gas-sensitive response of O2 and NH3 under UV irradiation were further investigated
theoretically by 3D electrostatic field simulations and first-principles
density functional theory to reveal the mechanism. Finally, a UV–AGS
device was developed to quantify the blood ammonia bioassay in a small-volume
whole blood sample by alkalizing blood to release gas-phase ammonia
with a linear range of 25–5000 μM with a limit of detection
(LOD) of 29.5 μM. The device also enables a rapid immunoassay
of human cardiac troponin I (cTnI) with a linear range of 0.4–25.6
ng/mL and an LOD of 0.37 ng/mL using a urease-labeled antibody as
the immune recognition molecule. Both analyses showed satisfying specificity
and stability, suggesting that the device can be applied to practical
assays and is of great potential to increase the value of gas-sensitive
sensors in chemical biosensing.
An innovative photoelectrochemical biosensor was designed for the quantitative monitoring of microRNA with horseradish peroxidase-single stranded DNA-encoded magnetic beads cleaved by the catalytic hairpin assembly-mediated CRISPR-Cas12a system by using yolk-in-shell Au@CdS as a photoactive material.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.