Rapid and Online Microvolume Flow-Through Dialysis Probe for Sample Preparation in Veterinary Drug Residue Analysis.

A rapid and online microvolume flow-through dialysis probe designed for sample preparation in the analysis of veterinary drug residues is introduced. This study addresses the need for efficient and green sample preparation methods that reduce chemical waste and reagent use. The dialysis probe integrates with liquid chromatography and mass spectrometry (LC-MS) systems, facilitating automated, high-throughput analysis. The dialysis method utilizes minimal reagent volumes per sample, significantly reducing the generation of solvent waste compared to traditional sample preparation techniques. Several veterinary drugs were spiked into tissue homogenates and analyzed to validate the probe's efficacy. A diagnostic sensitivity of >97% and specificity of >95% were obtained for this performance evaluation. The results demonstrated the effective removal of cellular debris and particulates, ensuring sample integrity and preventing instrument clogging. The automated dialysis probe yielded recovery rates between 27 and 77% for multiple analytes, confirming its potential to streamline veterinary drug residue analysis, while adhering to green chemistry principles. The approach highlights substantial improvements in both environmental impact and operational efficiency, presenting a viable alternative to conventional sample preparation methods in regulatory and research applications.

Characterization of a Nonselective Opioid Receptor Functional Antagonist: Implications for Development as a Novel Opioid Dependence Medication.

Opioids represent the most extensive category of abused substances in the United States, and the number of fatalities caused by these drugs exceeds those associated with all other drug overdoses combined. The administration of naltrexone, a potent pan-opioid receptor antagonist, to an individual dependent on opioids can trigger opioid withdrawal and induce severe side effects. There is a pressing demand for opioid antagonists free of opioid withdrawal effects. In our laboratory, we have identified a compound with affinity to mu, delta, and kappa opioid receptors in the range of 150-250 nM. This blood-brain barrier (BBB)-permeant compound was metabolically stable in vitro and in vivo. Our in vivo work demonstrated that 1-10 mg/kg intraperitoneal administration of our compound produces moderate efficacy in antagonizing morphine-induced antiallodynia effects in the chemotherapy-induced peripheral neuropathy (CIPN) model. The treatment was well-tolerated and did not cause behavioral changes. We have observed a fast elimination rate of this metabolically stable molecule. Furthermore, no organ toxicity was observed during the chronic administration of the compound over a 14-day period. Overall, we report a novel functional opioid antagonist holds promise for developing an opioid withdrawal therapeutic.

Effect of Tryptic Digestion on Sensitivity and Specificity in MALDI-TOF-Based Molecular Diagnostics through Machine Learning.

The digestion of protein into peptide fragments reduces the size and complexity of protein molecules. Peptide fragments can be analyzed with higher sensitivity (often > 102 fold) and resolution using MALDI-TOF mass spectrometers, leading to improved pattern recognition by common machine learning algorithms. In turn, enhanced sensitivity and specificity for bacterial sorting and/or disease diagnosis may be obtained. To test this hypothesis, four exemplar case studies have been pursued in which samples are sorted into dichotomous groups by machine learning (ML) software based on MALDI-TOF spectra. Samples were analyzed in 'intact' mode in which the proteins present in the sample were not digested with protease prior to MALDI-TOF analysis and separately after the standard overnight tryptic digestion of the same samples. For each case, sensitivity (sens), specificity (spc), and the Youdin index (J) were used to assess the ML model performance. The proteolytic digestion of samples prior to MALDI-TOF analysis substantially enhanced the sensitivity and specificity of dichotomous sorting. Two exceptions were when substantial differences in chemical composition between the samples were present and, in such cases, both 'intact' and 'digested' protocols performed similarly. The results suggest proteolytic digestion prior to analysis can improve sorting in MALDI/ML-based workflows and may enable improved biomarker discovery. However, when samples are easily distinguishable protein digestion is not necessary to obtain useful diagnostic results.

Microplastic Pollution: Chemical Characterization and Impact on Wildlife.

Microplastics are small pieces of plastic that are less than 5 mm in size and can be found in most environments, including the oceans, rivers, and air. These small plastic particles can have negative impacts on wildlife and the environment. In this review of the literature, we analyze the presence of microplastics in various species of wildlife, including fish, birds, and mammals. We describe a variety of analytical techniques, such as microscopy and spectrometry, which identify and quantify the microplastics in the samples. In addition, techniques of sample preparation are discussed. Summary results show that microplastics are present in all the wildlife species studied, with the highest concentrations often found in fish and birds. The literature suggests that microplastics are widely distributed in the environment and have the potential to affect a wide range of species. Further research is required to fully understand the impacts of microplastics on wildlife and the environment.