Methods and Protocols最新文献

The increasing frequency, duration, and intensity of wildfires over the past decade have raised significant concerns about widespread exposure to wildfire smoke. Inhalation of wildfire smoke poses a substantial risk to human health, with epidemiological studies linking exposure to cardiovascular, respiratory, and neurological dysfunction. Wildfire smoke contains hundreds of chemical compounds across diverse classes, with concentrations varying by fuel type and combustion conditions. Phenolic compounds are prominent constituents of wood smoke, and catechol is especially abundant under smoldering conditions that produce dense smoke. In this study, ¹⁴C-labeled catechol was spiked into smoldering eucalyptus wood smoke extract (WSE) and administered to rats via intranasal instillation. Plasma was collected at 5 min and 2 h post-exposure. Samples were analyzed using parallel accelerator and molecular mass spectrometry (PAMMS). Major catechol-derived metabolites identified included benzene oxide, catechol-cysteine conjugate, and catechol-glutamine conjugate; the parent compound was not detected. These results indicate that inhaled catechol in wood smoke is quickly metabolized upon entry into circulation. PAMMS enabled both identification and relative quantification of circulating catechol metabolites, demonstrating feasibility for biomarker discovery and exposure assessment.

A straightforward whole-mount approach has been developed that uses fluorescence imaging, mouse trachea, and a range of off-the-shelf reagents for rapidly evaluating substance toxicity within the ciliated respiratory epithelium. Using this protocol, the lumen of control trachea samples displays a typical cobblestone epithelial structure, a high density of ciliated cells, and minimal evidence of cell death, as visualized by phalloidin, acetylated tubulin, and fixable live/dead staining, respectively. In contrast, trachea subjected to treatments that induce injury show disrupted epithelial architecture and increased cell death, indicating substance toxicity. These results support the utility of this protocol for rapidly detecting and quantifying respiratory epithelial toxicity and differential cell-type susceptibility.

Drug discovery remains a time-consuming and costly process, necessitating innovative computational approaches to accelerate early stage target identification and compound development. We introduce AgentMol, a modular multimodel AI system that integrates large language models, chemical language modeling, and deep learning-based affinity prediction to automate the discovery pipeline. AgentMol begins with disease-related queries processed through a Retrieval-Augmented Generation system using the Large Language Model to identify protein targets. Protein sequences are then used to condition a GPT-2-based chemical language model, which generates corresponding small-molecule candidates in SMILES format. Finally, a regression convolutional neural network (RCNN) predicts the drug-target interaction by estimating binding affinities (pKi). Models were trained and validated on 470,560 ligand-protein pairs from the BindingDB database. The chemical language model achieved high validity (1.00), uniqueness (0.96), and diversity (0.89), whereas the RCNN model demonstrated robust predictive performance with R² > 0.6 and Pearson's R > 0.8. By leveraging LangGraph for orchestration, AgentMol delivers a scalable, interpretable pipeline, effectively enabling the end-to-end generation and evaluation of drug candidates conditioned on protein targets. This system represents a significant step toward practical AI-driven molecular discovery with accessible computational demands.

We previously developed a bead-coupled ligase detection reaction (LDR) assay that enables simple and rapid detection of single-nucleotide variations (SNVs) using synthetic oligonucleotide templates. In the present study, this approach was extended to genomic DNA extracted from colorectal cancer cell lines to evaluate its applicability to clinically relevant samples. Targeting codon 12 of the KRAS gene, PCR-amplified products served as templates for bead-coupled LDR, and fluorescence excitation-emission matrix (EEM) analysis was employed for signal readout. The four fluorophores used in the assay exhibited distinct spectral properties, allowing their signals to be clearly resolved within the EEM profiles. This mapping provided characteristic fluorescence signatures that revealed the underlying genotypes, enabling not only the distinction between homozygous and heterozygous states but also the precise identification of allele compositions, as exemplified by G/A, T/T, G/G, and G/C in colorectal cancer cell lines. The single-tube workflow, integrating magnetic bead capture with fluorescence-based detection, demonstrated robustness, speed, and cost-effectiveness compared with conventional mutation detection methods. These findings confirm that the LDR-EEM platform can be successfully applied to genomic DNA analysis, underscoring its potential as an accessible and reliable tool for SNV detection in both research and diagnostic contexts.

Investigation of molecular mechanisms that underlie the toxicity of reactive oxidants requires the usage of reductionist cellular models, where laboratory cultures are treated by known doses of the target compounds in strictly controlled conditions. In recent years, much attention has been focused on hypothiocyanous acid (HOSCN), a pseudohypohalous acid that is one of the main products of chordata heme peroxidases. Due to its instability, HOSCN cannot be purchased and stored, so it has to be enzymatically synthesized before each experiment. For the first time, we systematically classified the published protocols for HOSCN synthesis, compared them by product yield, and found that the highest achievable concentration was about 1.9 mM. This value is not convenient for large-scale experiments with high cell density. Therefore, we developed an improved protocol for HOSCN preparation by optimizing reagent ratios, incubation times, and temperature. The current paper describes all steps from scratch, namely lactoperoxidase purification via a combination of cation exchange, hydrophobic interaction, and size exclusion chromatography, HOSCN synthesis from SCN^- and H₂O₂, as well as HOSCN concentration measurement. The main advantage of the current protocol is that the product yield reaches 2.9 mM, which is 60% higher than published alternatives.

L-Carnitine (L-CAR) and acetyl-L-carnitine (Acetyl L-CAR) are the essential cofactor compounds in lipid metabolism and are used in the treatment of various diseases. The European Food Safety Authority (EFSA) has reported that Acetyl-L-CAR contributes to normal cognitive function and has a beneficial physiological effect. Therefore, the sensitive separation and determination of L-CAR and Acetyl-L-CAR in foodstuffs can provide critical information. A notable trend in modern food analysis is the increasing use of miniaturized analytical columns with a narrow inner diameter (ID). In this study, a new, green analytical method for food analysis was developed to analyze L-CAR and Acetyl-L-CAR in food samples by nano-LC/UV with a hydrophilic monolithic 100 µm ID capillary. This is the first time that the preparation and application of a hydrophilic monolithic nano-column for the analysis of L-CAR and Acetyl-L-CAR in food samples by nano LC/UV has been reported. The hydrophilic monolith was prepared using in situ co-polymerization of glyceryl methacrylate (GMM) and ethylene dimethacrylate (EDMA). Following preparation and characterization, the hydrophilic monolith was used to analyze L-CAR and Acetyl-L-CAR in food samples, including three infant powdered milk samples and five supplements using nano LC/UV. The developed method was validated in terms of precision, sensitivity, linearity, recovery, and repeatability. The LOD and LOQ values were found to be in the range of 0.04-0.09 µg/kg, respectively. In short, the proposed method proved to be suitable for the routine analysis of L-CAR and Acetyl-L-CAR in food samples.

Retinal detachment (RD) disrupts the eye's immune-privileged status, causing a local inflammatory response that contributes to adverse clinical outcomes, including proliferative vitreoretinopathy and suboptimal visual recovery. Comprehensive profiling of intraocular immune cells will offer mechanistic insights and support the development of personalized immunomodulatory strategies. Here, we describe a robust and standardized protocol for the collection and high-dimensional analysis of the intraocular immune infiltrate from patients undergoing RD surgery, using state-of-the-art spectral cytometry. Vitreous and retinal tissue samples were obtained during standard surgical procedures, without the need for additional invasive interventions. Our approach integrates two complementary protocols: one that enables selective isolation of immune cells by sorting for CD45⁺ populations, and a second one that applies a 39-color spectral cytometry panel to profile the general landscape of immune subpopulations. The panel can identify up to 62 distinct viable immune subsets per sample, along with their functional status, as it includes expression of 13 functional markers. Hence, we hereby detail sample preparation, staining, and acquisition workflow, as well as the gating strategy and essential steps necessary for reproducible immunophenotyping. Our protocol, which enables high-dimensional immune profiling from minimal biological material, provides a valuable platform for studying ocular inflammation in RD and other retinal diseases.

We have developed a method for in vivo quantitation of lung delivery of inhaled nebulized drugs by measuring a fluorescent-labeled analog in bronchioalveolar lavage fluid (BALF) collected immediately after inhalation dosing. The effectiveness of delivery of an aerosolized formulation of our proprietary water-miscible vitamin A product to the deep lung (target organ) was studied; the product is being developed for prevention of bronchopulmonary dysplasia (BPD) in preterm infants. The fluorescent retinol analog was incorporated by spiking into a standard formulation, remaining fully compatible with existing nebulizer administration procedures for animal exposure. The method provides quantitation of the delivered dose (DD) to the lung within a few minutes after dosing; fluorescence in BAL in a plate reader allows for simple rapid quantitation of the delivered drug, while avoiding the complexities of other labeling methods (e.g., heavy labels or radioactivity). Data from newborn rat and lamb models showed linear dose responses, validating the method. Approximately 5-10% of the inhaled drug was recovered in BALF in both models, consistent with reports in the literature. The ease of use of the method facilitated various aspects of our project, including the transition to more clinically relevant animal models and aerosol exposure systems. The formulation of this approach could be spiked into other formulations, allowing application of the method to other aerosol drug development programs.

The presence of antioxidants in food contributes to the preservation of its taste and technological qualities, preventing its spoilage for a longer time, which is important at all stages of production and storage. The major antioxidants are vitamins, proteins (primarily, enzymes), peptides, amino acids, fatty acid residues of lipids, etc. There is currently an explosive growth in the development of methods for assessing the content and effectiveness of particular antioxidants but not the total antioxidant activity (AOA) in raw milk and food systems. This article provides a critical overview of the most important AOA methods, their mechanisms and applicability, advantages, and limitations (primarily, for antioxidants of milk and dairy products). Among all the antioxidant indicators of milk, the simplest and sufficiently informative is the detection of the total amount of water-soluble antioxidant (TAWSA), which is confirmed by comparison of numerous publications and practical results of various methods (as summarized in this review). It is important to emphasize that the TAWSA of milk is an "integral characteristic" of the most valuable biosubstances (possessing AOA) together. Therefore, the TAWSA method is recommended for assessing AOA in raw milk as an "integrated indicator" in dairy husbandry.

For many therapeutic agents to be effective against intracellular targets, they must first be able to penetrate the cell membrane. Current methodologies for assessing internalization, such as confocal microscopy and conventional flow cytometry, are limited by low throughput or an inability to provide precise spatial information on signal localization. Here, we present a comprehensive, semi-automated analytical pipeline for investigating compound internalization based on imaging flow cytometry, which is designed to address these limitations. Our workflow details the procedure from sample preparation and data acquisition on an Amnis FlowSight cytometer to analysis using IDEAS 6.2 software with a custom-designed template. Key features of our approach include the automated discrimination of signal between the plasma membrane and cytoplasmic compartments, the calculation of an internalization coefficient, and the introduction of a novel parameter-signal distribution entropy-to quantify the uniformity of the compound distribution within cells. For the statistical analysis, we developed FluoSta v1.0, a software tool that automates descriptive statistics and analysis of variance (ANOVA with Tukey's post hoc test) and facilitates data visualization. The pipeline's utility was demonstrated in a series of model experiments, including a comparative assessment of the internalization efficiency of PS- versus PS/LNA-modified compounds in MT-4 cell cultures.