Velocity Map Imaging Photoelectron Spectroscopy of Silver Iodide Aerosol Particles.

The valence band electronic structure of isolated silver iodide nanoparticles (AgI NP) was investigated by vacuum-ultraviolet aerosol photoelectron spectroscopy using the velocity map imaging technique (VUV VMI-PES). The VUV VMI-PES results were obtained for polydisperse aerosol produced by aggregation of hydrocolloid of silver iodide particles 8-15 nm in size. The ionization energy of the AgI particles was found to be 6.0±0.1 eV with respect to the vacuum level. The DFT calculations showed that the main contribution to the density of AgI electronic states in the valence region originates from I 5p orbitals. The dependence of the asymmetry parameter on the electron energy showed that the value of the characteristic energy loss of excited photoelectrons was 2.7 eV, which coincided with the band gap of the nanomaterial.

Continuing professional development in general dentistry-experiences of an online flipped classroom.

INTRODUCTION: Continuing professional development is a lifelong learning process. One pedagogical approach that can be used is active learning. Flipped classroom is a method that has been shown to improve deeper conceptual understanding. In an online setting, the method saves travel, time, and costs. To our knowledge, flipped classroom is rarely used in continuing professional education. This study in general dentistry explored experiences of an online flipped classroom course in continuing professional development. MATERIALS AND METHODS: Fifteen dental hygienists, clinically active in general dental care, were interviewed. They were recruited from an online course on the latest classification system for periodontal diseases. The course had been conducted using an active learning and flipped classroom model. The interviews were semi-structured. Data were extracted using qualitative content analysis. RESULTS: The experiences of the dental hygienists could be summarized in three themes: Stimulation of knowledge gain through self-paced studies, The ease of virtual networking among colleagues, and Fostering of direct practical application through collaboration. CONCLUSION: New and emerging communication technology seems to open new possibilities for continuing professional development in general dentistry. Study participants felt that, in an online environment, mixing asynchronous and synchronous communication in a flipped classroom model facilitated learning in continuing professional development. Online active learning seems to work well in continuous professional development in general dentistry. After the course, the participating dental hygienists stated that they were able to use their new knowledge clinically and felt confident doing so.

Automated identification of aquatic insects: A case study using deep learning and computer vision techniques.

Deep learning techniques have recently found application in biodiversity research. Mayflies (Ephemeroptera), stoneflies (Plecoptera) and caddisflies (Trichoptera), often abbreviated as EPT, are frequently used for freshwater biomonitoring due to their large numbers and sensitivity to environmental changes. However, the morphological identification of EPT species is a challenging but fundamental task. Morphological identification of these freshwater insects is therefore not only extremely time-consuming and costly, but also often leads to misjudgments or generates datasets with low taxonomic resolution. Here, we investigated the application of deep learning to increase the efficiency and taxonomic resolution of biomonitoring programs. Our database contains 90 EPT taxa (genus or species level), with the number of images per category ranging from 21 to 300 (16,650 in total). Upon completion of training, a CNN (Convolutional Neural Network) model was created, capable of automatically classifying these taxa into their appropriate taxonomic categories with an accuracy of 98.7 %. Our model achieved a perfect classification rate of 100 % for 68 of the taxa in our dataset. We achieved noteworthy classification accuracy with morphologically closely related taxa within the training data (e.g., species of the genus Baetis, Hydropsyche, Perla). Gradient-weighted Class Activation Mapping (Grad-CAM) visualized the morphological features responsible for the classification of the treated species in the CNN models. Within Ephemeroptera, the head was the most important feature, while the thorax and abdomen were equally important for the classification of Plecoptera taxa. For the order Trichoptera, the head and thorax were almost equally important. Our database is recognized as the most extensive aquatic insect database, notably distinguished by its wealth of included categories (taxa). Our approach can help solve long-standing challenges in biodiversity research and address pressing issues in monitoring programs by saving time in sample identification.

Photodissociation of leucine-enkephalin protonated peptide: an experimental and theoretical perspective.

Understanding the competing processes that govern far ultraviolet photodissociation (FUV-PD) of biopolymers such as proteins is a challenge. Here, we report a combined experimental and theoretical investigation of FUV-PD of protonated leucine-enkephalin pentapeptide ([YGGFL + H]+) in the gas-phase. Time-dependent density functional theory (TD-DFT) calculations in combination with experiments and previous results for amino acids and shorter peptides help in rationalizing the evolution of the excited states. The results confirm that fragmentation of [YGGFL + H]+ results mainly from vibrationally excited species in the ground electronic state, populated after internal conversion. We also propose fragmentation mechanisms for specific photo-fragments such as tyrosine side chain loss (with an extra hydrogen) or hydrogen loss. In general, we observe the same mechanisms as for smaller peptides or protonated Tyr and Phe, that are not quenched by the presence of other amino acids. Nevertheless, we also found some differences, as for H loss, in part due to the fact that the charge is solvated by the peptide chain and not only by the COOH terminal group.

Mapping MAVE data for use in human genomics applications.

The large-scale experimental measures of variant functional assays submitted to MaveDB have the potential to provide key information for resolving variants of uncertain significance, but the reporting of results relative to assayed sequence hinders their downstream utility. The Atlas of Variant Effects Alliance mapped multiplexed assays of variant effect data to human reference sequences, creating a robust set of machine-readable homology mappings. This method processed approximately 2.5 million protein and genomic variants in MaveDB, successfully mapping 98.61% of examined variants and disseminating data to resources such as the UCSC Genome Browser and Ensembl Variant Effect Predictor.

Generating Clinical-Grade Gene-Disease Validity Classifications Through the ClinGen Data Platforms.

Clinical genetic laboratories must have access to clinically validated biomedical data for precision medicine. A lack of accessibility, normalized structure, and consistency in evaluation complicates interpretation of disease causality, resulting in confusion in assessing the clinical validity of genes and genetic variants for diagnosis. A key goal of the Clinical Genome Resource (ClinGen) is to fill the knowledge gap concerning the strength of evidence supporting the role of a gene in a monogenic disease, which is achieved through a process known as Gene-Disease Validity curation. Here we review the work of ClinGen in developing a curation infrastructure that supports the standardization, harmonization, and dissemination of Gene-Disease Validity data through the creation of frameworks and the utilization of common data standards. This infrastructure is based on several applications, including the ClinGen GeneTracker, Gene Curation Interface, Data Exchange, GeneGraph, and website.

International Society for Extracellular Vesicles Workshop. QuantitatEVs: multiscale analyses, from bulk to single extracellular vesicle.

The 'QuantitatEVs: multiscale analyses, from bulk to single vesicle' workshop aimed to discuss quantitative strategies and harmonized wet and computational approaches toward the comprehensive analysis of extracellular vesicles (EVs) from bulk to single vesicle analyses with a special focus on emerging technologies. The workshop covered the key issues in the quantitative analysis of different EV-associated molecular components and EV biophysical features, which are considered the core of EV-associated biomarker discovery and validation for their clinical translation. The in-person-only workshop was held in Trento, Italy, from January 31st to February 2nd, 2023, and continued in Milan on February 3rd with "Next Generation EVs", a satellite event dedicated to early career researchers (ECR). This report summarizes the main topics and outcomes of the workshop.