Browse Articles

LC–MS/MS quantification of 20(S)-protopanaxadiol in complex biological matrices for bioanalytical method validation and pharmacokinetic analysis

Laser driven FLASH radiobiology using a high dose and ultra high dose rate single pulse proton source

Abstract Laser-driven proton sources have long been developed with an eye on their potential for medical application to radiation therapy. These sources are compact, versatile, and show peculiar characteristics such as extreme instantaneous dose rates, short duration and broad energy spectrum. Typical temporal modality of laser-driven irradiation, the so-called fast-fractionation, results from the composition of multiple, temporally separated, ultra-short dose fractions. In this paper we present the use of a high-energy laser system for delivering the target dose in a single nanosecond pulse, for ultra-fast irradiation of biological samples. A transport line composed by two permanent-magnet quadrupoles and a scattering system is used to improve the dose profile and to control the delivered dose-per-pulse. A single-shot dosimetry protocol for the broad-spectrum proton source using Monte Carlo simulations was developed. Doses as high as 20 Gy could be delivered in a single shot, lasting less than 10 ns over a 1 cm diameter biological sample, at a dose-rate exceeding $$10^{9}\hbox { Gy s}^{-1}$$ . Exploratory application of extreme laser-driven irradiation conditions, falling within the FLASH irradiation protocol, are presented for irradiation in vitro and in vivo. A reduction of radiation-induced oxidative stress in vitro and radiation-induced developmental damage compatible with the onset of FLASH effect were observed in vivo, whereas anti-tumoral efficacy was confirmed by cell survival assay.

Methodological framework for three-way statistical analysis of cost of living and quality of life indices: a case study in the American continent

Leveraging explainable artificial intelligence with ensemble of deep learning model for dementia prediction to enhance clinical decision support systems

Influence of short video content on consumers purchase intentions on social media platforms with trust as a mediator

Responses of grassland soil mesofauna to induced climate change

Therapeutic limitations of oncolytic VSVd51-mediated miR-199a-5p delivery in triple negative breast cancer models

Factorial scope of ingestion and the potential functional response of puff adders (Bitis arietans) to high prey abundance

Ultrasound assisted magnetic dispersive solid phase microextraction for Hg determination in fuel oils using inductively coupled plasma optical emission spectroscopy

Abstract Mercury is considered a global pollutant, and its quantification in fuel oils remains a priority for public health and the ecosystem. Functionalized graphene oxide has gained popularity for heavy metal adsorption in various matrices. Herein we present a highly selective and efficient magnetic graphene oxide coated with gold (Fe3O4/GO-Au) nano adsorbent and its application to a dispersive solid-phase microextraction of mercury in fuel oils. The synthesized Fe3O4/GO-Au nanocomposite was characterized using Fourier Transform Infra-Red spectroscopy (FT-IR), powder X-ray diffraction (P-XRD), Scanning electron microscopy (SEM/EDS), Transmission electron microscopy (TEM), Thermogravimetric (TGA), Brunauer-Emmett-Teller (BET), and vibration sample magnetometer (VSM) analysis. The multivariate optimum conditions for the extraction method were 20 min, 30 mg, pH 7, and 1.75 mol/L, for adsorption time, sorbent mass, pH, and eluent concentration, respectively. Under the optimized conditions, the dynamic linear range of 0.1 to 100 µg/L (R2 = 0.999) was obtained. The limit of detection (LOD) and preconcentration factor obtained were 0.035 µg/L and 255, respectively. Intra- and inter-day precision of the method were calculated to be 3.5% and 4.0%, respectively. The newly developed method was successfully applied in real crude oil, diesel oil, gasoline, and kerosene samples. The environmental impact of the newly developed procedure was evaluated and a total score of 0.64 was obtained.

Suppressed DNA repair capacity in flight attendants after air travel

Uncovering the integral spectral characteristics of the planetary nebula IC 4642

Bufei Yishen formula alleviates airway epithelial cell senescence in COPD by activating AMPK-Sirt1-FoxO3a pathway and promoting autophagy

Characteristics and potential diagnostic value of gut microbiota in ovarian tumor patients

Revolutionizing sleep disorder diagnosis: A Multi-Task learning approach optimized with genetic and Q-Learning techniques

Correction: Surgical specialists face higher a risk for malpractice compared to their non-surgical colleagues

Microbial diversity of high-elevated fumarole fields, low-biomass communities on the boundary between ice and fire

Dynamics of plasma reconfiguration after pellet injection in Heliotron J

Abstract Because of the many degrees of freedom in magnetized plasmas, the plasma is largely reconfigured when the plasma achieves a non-equilibrium steady state in response to changes in the internal environment. Here we report observations of a plasma reconfiguration process when the density is increased by pellet injection in Heliotron J. The plasma shows no adiabatic response to pellet injection and achieves an improved confinement during the reconfiguration process. It was found that plasma shrinking and expansion arose and the magnetic field line structure in the divertor region also changed in the plasma reconfiguration process.

Correction: Visual impairment prevention by early detection of diabetic retinopathy based on stacked auto-encoder

The MAMBAT framework for acoustic tracking of multiple animals

Approaches for handling imbalanced data used in machine learning in the healthcare field: A case study on Chagas disease database prediction

Machine learning has increasingly gained prominence in the healthcare sector due to its ability to address various challenges. However, a significant issue remains unresolved in this field: the handling of imbalanced data. This process is crucial for ensuring the efficiency of algorithms that utilize classification techniques, which are commonly applied in risk management, monitoring, diagnosis, and prognosis of patient health. This study conducts a comparative analysis of techniques for handling imbalanced data and evaluates their effectiveness in combination with a set of classification algorithms, specifically focusing on stroke prediction. Additionally, a new approach based on Particle Swarm Optimization (PSO) and Naive Bayes was proposed. This approach was applied to the real problem of Chagas disease. The application of these techniques aims to improve the quality of life for individuals, reduce healthcare costs, and allocate available resources more efficiently, making it a preventive action.