A fluorescent sensor array based on antibiotic-stabilized metal nanoclusters for the multiplex detection of bacteria.

To address the need for facile, rapid detection of pathogens in water supplies, a fluorescent sensing array platform based on antibiotic-stabilized metal nanoclusters was developed for the multiplex detection of pathogens. Using five common antibiotics, eight different nanoclusters (NCs) were synthesized including ampicillin stabilized copper NCs, cefepime stabilized gold and copper NCs, kanamycin stabilized gold and copper NCs, lysozyme stabilized gold NCs, and vancomycin stabilized gold/silver and copper NCs. Based on the different interaction of each NC with the bacteria strains, unique patterns were generated.

Synthesis of cuttlebone/ carbon quantum dots/nickel oxide nanocomposite for visible light photodegradation of malachite green used for environmental remediation.

In recent years, the development of light-driven nanophotocatalysts has focused on efficiently eliminating organic pollutants. In this regard, the present work focuses on the photocatalytic removal of malachite green (MG) dye using cuttlebone powder (CB) modified with carbon quantum dots (CQDs)/nickel oxide (NiO) under visible light irradiation. Various techniques were used to characterize the proposed composite, including X-ray diffraction (XRD) and field emission scanning electron microscopy (FE-SEM) images.

Detection of COVID-19: A Smartphone-Based Machine-Learning-Assisted ECL Immunoassay Approach with the Ability of RT-PCR CT Value Prediction.

The unstoppable spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has severely threatened public health over the past 2 years. The current ubiquitously accepted method for its diagnosis provides sensitive detection of the virus; however, it is relatively time-consuming and costly, not to mention the need for highly skilled personnel. There is a clear need to develop novel computer-based diagnostic tools to provide rapid, cost-efficient, and time-saving detection in places where massive traditional testing is not practical.

Smartphone image analysis-based fluorescence detection of tetracycline using machine learning.

Tetracycline (TC) is vastly used as a veterinary drug, making its detection highly important. We have aimed to develop a rapid detection method for TC. For this, BSA-protected Au/Ag bimetallic nanoclusters (BSA-BMNCs) were synthesized for the detection of TC in water and milk.

Untargeted Metabolomics Analysis of subsp. (Herb.) B. Mathew Stigmas and Their Anticarcinogenic Effect on Breast Cancer Cells.

Safranal, crocin, crocetin, and picrocrocin are major known compounds in the stigma extract of with various medicinal properties. is another species that grows extensively in Iran's various regions, such as the Kurdistan province. The predominant metabolites and biological properties of .

Multiplex Detection of Antibiotic Residues in Milk: Application of MCR-ALS on Excitation-Emission Matrix Fluorescence (EEMF) Data Sets.

The presence of antibiotics and their metabolites in milk and dairy products is a serious concern because of their harmful effects on human health. In the current study, a novel synergistic bimetallic nanocluster with gold and silver as an emission fluorescence probe was investigated for the simultaneous determination of tetracycline (TC), ampicillin (AMP), and sulfacetamide (SAC) antibiotics in the milk samples using excitation-emission matrix fluorescence (EEMF) spectroscopy. The multivariate curve resolution-alternating least squares (MCR-ALS) method was implemented to analyze augmented EEMF data sets to quantify the multicomponent systems in the presence of interferences with considerable spectral overlap.

Untargeted metabolomics changes on Gammarus pulex induced by propranolol, triclosan, and nimesulide pharmaceutical drugs.

The presence of pharmaceuticals and personal care products (PPCPs) in natural water resources due to incomplete removal in Wastewater Treatment Plants (WWTPs) is a serious environmental concern at present. In this work, the effects of three pharmaceuticals (propranolol, triclosan, and nimesulide) on Gammarus pulex metabolic profiles at different doses and times of exposure have been investigated by liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS). The complex data sets generated in the different exposure experiments were analyzed with the ROIMCR procedure, based on the selection of the MS regions of interest (ROI) data and on their analysis by the Multivariate Curve-Resolution Alternating Least Squares (MCR-ALS) chemometrics method.