RESUMEN
Tracking droplets in microfluidics is a challenging task. The difficulty arises in choosing a tool to analyze general microfluidic videos to infer physical quantities. The state-of-the-art object detector algorithm You Only Look Once (YOLO) and the object tracking algorithm Simple Online and Realtime Tracking with a Deep Association Metric (DeepSORT) are customizable for droplet identification and tracking. The customization includes training YOLO and DeepSORT networks to identify and track the objects of interest. We trained several YOLOv5 and YOLOv7 models and the DeepSORT network for droplet identification and tracking from microfluidic experimental videos. We compare the performance of the droplet tracking applications with YOLOv5 and YOLOv7 in terms of training time and time to analyze a given video across various hardware configurations. Despite the latest YOLOv7 being 10% faster, the real-time tracking is only achieved by lighter YOLO models on RTX 3070 Ti GPU machine due to additional significant droplet tracking costs arising from the DeepSORT algorithm. This work is a benchmark study for the YOLOv5 and YOLOv7 networks with DeepSORT in terms of the training time and inference time for a custom dataset of microfluidic droplets.
RESUMEN
Chemical hydrolysis assisted by microwave irradiation has been proposed as an alternative method for the analysis of proteins in highly insoluble matrices. In this work, chemical hydrolysis was applied for the first time to detect degraded proteins from paintings and polychromies. To evaluate the performance of this approach, the number of identified peptides, protein sequence coverage (%), and PSMs were compared with those obtained using two trypsin-based proteomics procedures used for the analysis of samples from cultural heritage objects. It was found that chemical hydrolysis allowed the successful identification of all proteinaceous materials in all paint samples analyzed except for egg proteins in one extremely degraded sample. Moreover, in one sample, casein was only identified by chemical digestion. In general, chemical hydrolysis identified more peptides, more PSM's, and greater sequence coverage in the samples containing caseins, and often also in animal glue, highlighting the great potential of this approach for the rapid digestion and identification of insoluble and degraded proteins from the field of the cultural heritage.
Asunto(s)
Pintura/análisis , Péptidos/análisis , Proteínas/análisis , Animales , Caseínas/análisis , Bovinos , Pollos , Colágeno/análisis , Proteínas del Huevo/análisis , Modelos Moleculares , Pinturas , Proteolisis , Proteómica/métodos , Espectrometría de Masas en Tándem/métodosRESUMEN
An analytical protocol based on optical microscopy, Fourier transforms infrared spectroscopy (FTIR), analytical pyrolysis in the presence of hexamethyldisilazane followed by gas chromatographic/mass spectrometric analysis (Py-GC/MS) and gas chromatography/mass spectrometry after alkaline hydrolysis, solvent extraction and trimethylsilylation (GC/MS) was used in the chemical characterisation of the original adhesives used to fix monochrome and mosaic glass and stone plaques coming from the Late Roman archaeological site of Antinoopolis (Egypt). FTIR analysis demonstrated the presence of calcite fragments, and Py-GC/MS and GC/MS analyses provided detailed molecular compositions, highlighting the presence of a wide range of compound classes including diterpenoid acids, tricyclic abietanes with a high degree of aromatisation, mid- and long-chain monocarboxylic fatty acids, mono- and di-hydroxy acids, alpha,omega-dicaboxylic fatty acids, n-alkanols, and n-alkanes. Characteristic biomarkers and their distribution patterns indicated the presence of pine pitch in all the adhesives, which in some cases was admixed with beeswax and brassicaceae seed oil. The results provided new insights into the complex recipes used by artisans in ancient Egypt in the production of adhesives and in the sophisticated manufacture of opus sectile decorations.