Nanostructure-mediated glucose oxidase biofunctionalization for monitoring gestational diabetes

Gold nanourchin on multiple-point dielectrode for glucose biosensing by current-potential measurement

Gestational diabetes (GD) is a condition characterized by elevated blood sugar levels during pregnancy. GD poses various health risks, such as serious birth injuries, the need for cesarean delivery, and the necessity of newborn care. Monitoring glucose levels is essential for ensuring safe delivery and reducing the risks to both the mother and fetus. Various sensors are readily available for monitoring glucose levels, and researchers are continually working to develop highly sensitive glucose sensors. This research aimed to develop a gold nanourchin (AuNU)-hybrid biosensor for quantifying glucose on a multi-point electrode sensor. Glucose oxidase (GOx) was attached to the AuNU and seeded on the sensing surface using an amine linker. The current-potential (1-2 V at 0.1 V sweep) was recorded for the GOx-glucose interaction, with a limit of detection of 560 μM and a regression coefficient (R2) of 0.9743 [y = 0.9106x - 0.9953] on the linear curve. The sensitivity was estimated to be 3.5 mAcm-2M-1. Furthermore, control experiments with galactose, sucrose, and fructose did not yield an increase in current-potential, confirming specific glucose detection. This experiment helps in monitoring glucose levels to manage conditions associated with GD.

Accelerating adverse pregnancy outcomes research amidst rising medication use: parallel retrospective cohort analyses for signal prioritization

BACKGROUND

Pregnant women are significantly underrepresented in clinical trials, yet most of them take medication during pregnancy despite the limited safety data. The objective of this study was to characterize medication use during pregnancy and apply propensity score matching method at scale on patient records to accelerate and prioritize the drug effect signal detection associated with the risk of preterm birth and other adverse pregnancy outcomes.

METHODS

This was a retrospective study on continuously enrolled women who delivered live births between 2013/01/01 and 2022/12/31 (n = 365,075) at Providence St. Joseph Health. Our exposures of interest were all outpatient medications prescribed during pregnancy. We limited our analyses to medication that met the minimal sample size (n = 600). The primary outcome of interest was preterm birth. Secondary outcomes of interest were small for gestational age and low birth weight. We used propensity score matching at scale to evaluate the risk of these adverse pregnancy outcomes associated with drug exposure after adjusting for demographics, pregnancy characteristics, and comorbidities.

RESULTS

The total medication prescription rate increased from 58.5 to 75.3% (P < 0.0001) from 2013 to 2022. The prevalence rate of preterm birth was 7.7%. One hundred seventy-five out of 1329 prenatally prescribed outpatient medications met the minimum sample size. We identified 58 medications statistically significantly associated with the risk of preterm birth (P ≤ 0.1; decreased: 12, increased: 46).

CONCLUSIONS

Most pregnant women are prescribed medication during pregnancy. This highlights the need to utilize existing real-world data to enhance our knowledge of the safety of medications in pregnancy. We narrowed down from 1329 to 58 medications that showed statistically significant association with the risk of preterm birth even after addressing numerous covariates through propensity score matching. This data-driven approach demonstrated that multiple testable hypotheses in pregnancy pharmacology can be prioritized at scale and lays the foundation for application in other pregnancy outcomes.

A Review on Non-Enzymatic Electrochemical Biosensors of Glucose Using Carbon Nanofiber Nanocomposites

Diabetes mellitus has become a worldwide epidemic, and it is expected to become the seventh leading cause of death by 2030. In response to the increasing number of diabetes patients worldwide, glucose biosensors with high sensitivity and selectivity have been developed for rapid detection. The selectivity, high sensitivity, simplicity, and quick response of electrochemical biosensors have made them a popular choice in recent years. This review summarizes the recent developments in electrodes for non-enzymatic glucose detection using carbon nanofiber (CNF)-based nanocomposites. The electrochemical performance and limitations of enzymatic and non-enzymatic glucose biosensors are reviewed. Then, the recent developments in non-enzymatic glucose biosensors using CNF composites are discussed. The final section of the review provides a summary of the challenges and perspectives, for progress in non-enzymatic glucose biosensors.

Electrospun nanofiber-based glucose sensors for glucose detection

Diabetes is a chronic, systemic metabolic disease that leads to multiple complications, even death. Meanwhile, the number of people with diabetes worldwide is increasing year by year. Sensors play an important role in the development of biomedical devices. The development of efficient, stable, and inexpensive glucose sensors for the continuous monitoring of blood glucose levels has received widespread attention because they can provide reliable data for diabetes prevention and diagnosis. Electrospun nanofibers are new kinds of functional nanocomposites that show incredible capabilities for high-level biosensing. This article reviews glucose sensors based on electrospun nanofibers. The principles of the glucose sensor, the types of glucose measurement, and the glucose detection methods are briefly discussed. The principle of electrospinning and its applications and advantages in glucose sensors are then introduced. This article provides a comprehensive summary of the applications and advantages of polymers and nanomaterials in electrospun nanofiber-based glucose sensors. The relevant applications and comparisons of enzymatic and non-enzymatic nanofiber-based glucose sensors are discussed in detail. The main advantages and disadvantages of glucose sensors based on electrospun nanofibers are evaluated, and some solutions are proposed. Finally, potential commercial development and improved methods for glucose sensors based on electrospinning nanofibers are discussed.