Deep Learning Neural Modelling as a Precise Method in the Assessment of the Chronological Age of Children and Adolescents Using Tooth and Bone Parameters

Dental age is one of the most reliable methods for determining a patient’s age. The timing of teething, the period of tooth replacement, or the degree of tooth attrition is an important diagnostic factor in the assessment of an individual’s developmental age. It is used in orthodontics, pediatric dentistry, endocrinology, forensic medicine, and pathomorphology, but also in scenarios regarding international adoptions and illegal immigrants. The methods used to date are time-consuming and not very precise. For this reason, artificial intelligence methods are increasingly used to estimate the age of a patient. The present work is a continuation of the work of Zaborowicz et al. In the presented research, a set of 21 original indicators was used to create deep neural network models. The aim of this study was to verify the ability to generate a more accurate deep neural network model compared to models produced previously. The quality parameters of the produced models were as follows. The MAE error of the produced models, depending on the learning set used, was between 2.34 and 4.61 months, while the RMSE error was between 5.58 and 7.49 months. The correlation coefficient R2 ranged from 0.92 to 0.96.

Mycotoxin detoxification of food by lactic acid bacteria

Today, a few hundred mycotoxins have been identified and the number is rising. Mycotoxin detoxification of food and feed has been a technically uphill task for the industry. In the twenty-first century, the public demand is healthy food with minimum use of chemicals and preservatives. Among all the fungal inhibition and mycotoxin detoxification methods so far developed for food, biopreservation and biodetoxification have been found safe and reliable. Nowadays, lactic acid bacteria (LAB) are of great interest as biological additives in food owing to their Generally Recognized as Safe (GRAS) classification and mycotoxin detoxification capability. The occurrence of fungul growth in the food chain can lead to health problems such as mycotoxicosis and cancer to humans due to producing mycotoxins such as aflatoxins. Biopreservation is among the safest and most reliable methods for inhibition of fungi in food. This review highlights the great potential of LAB as biodetoxificant by summarizing various reported detoxification activities of LAB against fungal mycotoxins released into foods. Mechanisms of mycotoxin detoxification, also the inherent and environmental factors affecting detoxifying properties of LAB are also covered.

Rational Development and Characterization of a Ubiquitin Variant with Selectivity for Ubiquitin C-Terminal Hydrolase L3

There is currently a lack of reliable methods and strategies to probe the deubiquitinating enzyme UCHL3. Current small molecules reported for this purpose display reduced potency and selectivity in cellular assays. To bridge this gap and provide an alternative approach to probe UCHL3, our group has carried out the rational design of ubiquitin-variant activity-based probes with selectivity for UCHL3 over the closely related UCHL1 and other DUBs. The approach successfully produced a triple-mutant ubiquitin variant activity-based probe, UbVQ40V/T66K/V70F-PRG, that was ultimately 20,000-fold more selective for UCHL3 over UCHL1 when assessed by rate of inactivation assays. This same variant was shown to selectively form covalent adducts with UCHL3 in MDA-MB-231 breast cancer cells and no reactivity toward other DUBs expressed. Overall, this study demonstrates the feasibility of the approach and also provides insight into how this approach may be applied to other DUB targets.

Design and simulation of liquid infiltrated photonic crystal fibre in terahertz frequencies

Ethanol, methanol and water are polar solvents with similar physical properties albeit contrasting chemical properties. Therefore, it is essential to provide accurate and reliable methods for detecting these liquids. In this paper, a novel liquid infiltrated photonic crystal fibre for ethanol, methanol and water sensing is introduced. The novel structure is modelled, simulated and analysed in the terahertz (THz) region using a full vectorial finite element method. It is shown that the THz light, which is guided using modified total internal reflection, is confined within the infiltrated analytes with negligible losses. For the detection of infiltrated liquids at 1.6 THz operating frequency, the proposed fibre demonstrates high sensitivities up to 99.73% and confinement losses in the order of 10−4 dB/m. Manufacturing of the proposed fibre is feasible using existing fabrication technologies and it is envisaged that the fibre may provide a solution to existing challenges in detecting common polar solvents.

Reliably Assessing Duration of Protection for COVID-19 Vaccines

Decision-making about booster dosing for COVID-19 vaccine recipients hinges on reliable methods for evaluating the longevity of vaccine protection. We show that modeling of protection as a piecewise linear function of time since vaccination for the log hazard ratio of the vaccine effect provides more reliable estimates of vaccine effectiveness at the end of an observation period and also more reliably detects plateaus in protective effectiveness as compared with the traditional method of estimating a constant vaccine effect over each time period. This approach will be useful for analyzing data pertaining to COVID-19 vaccines and other vaccines where rapid and reliable understanding of vaccine effectiveness over time is desired.

New opportunities for identification of precursors of sea earthquakes

In many publications, as well as in media statements, prominent foreign and Bulgarian seismologists admit that seismology still does not have reliable methods and technical means for the identification of earthquake precursors in marine conditions (short-term forecast). Several facts, circumstances, and considerations are presented, motivating the need to immediately start experimental research in this area. A Bulgarian patent of a device for capturing underwater gas sources is offered for transmitting characteristics of the underwater gas source to a receiving device on land, indicating an impending earthquake. A strategy for experimentation and application of the device through the implementation of a new European project, uniting the forces and capabilities of the South European countries, is being proposed.

A Robust Training Method for Pathological Cellular Detector via Spatial Loss Calibration

Computer-aided diagnosis of pathological images usually requires detecting and examining all positive cells for accurate diagnosis. However, cellular datasets tend to be sparsely annotated due to the challenge of annotating all the cells. However, training detectors on sparse annotations may be misled by miscalculated losses, limiting the detection performance. Thus, efficient and reliable methods for training cellular detectors on sparse annotations are in higher demand than ever. In this study, we propose a training method that utilizes regression boxes' spatial information to conduct loss calibration to reduce the miscalculated loss. Extensive experimental results show that our method can significantly boost detectors' performance trained on datasets with varying degrees of sparse annotations. Even if 90% of the annotations are missing, the performance of our method is barely affected. Furthermore, we find that the middle layers of the detector are closely related to the generalization performance. More generally, this study could elucidate the link between layers and generalization performance, provide enlightenment for future research, such as designing and applying constraint rules to specific layers according to gradient analysis to achieve “scalpel-level” model training.

EFFECTS OF MARINE CONDITION ON THE SPEED AND FUEL CONSUMPTION OF A FULLY – LOADED VLCC

Minimizing fuel consumption is a priority for ship-owners seeking to reduce their vessel costs due to sea conditions. One of the most reliable methods used to estimate fuel consumption is to identify field investigations for future voyages. The VLCC Salina was used based on daily field data collected over a proper period and year of 2014 was identified as a period of optimal performance after its periodic dry dock repair. According to verified results for Beaufort scales of 2, 3 and 4, the vessel exhibited an average speed loss of 2.2% due to wind and wave effects for a Froude number of 0.15 while its greatest speed loss was observed at angles of 30‒60° relative to its longitudinal axis. The results were finally used to develop a methodology for estimating fuel consumption of Salina and 3 other sister-ships, during future voyages, in the fleet of the National Iranian tanker company.

Characterization of Extracellular Vesicles from Bronchoalveolar Lavage Fluid and Plasma of Patients with Lung Lesions Using Fluorescence Nanoparticle Tracking Analysis

The current lack of reliable methods for quantifying extracellular vesicles (EVs) isolated from complex biofluids significantly hinders translational applications in EV research. The recently developed fluorescence nanoparticle tracking analysis (FL-NTA) allows for the detection of EV-associated proteins, enabling EV content determination. In this study, we present the first comprehensive phenotyping of bronchopulmonary lavage fluid (BALF)-derived EVs from non-small cell lung cancer (NSCLC) patients using classical EV-characterization methods as well as the FL-NTA method. We found that EV immunolabeling for the specific EV marker combined with the use of the fluorescent mode NTA analysis can provide the concentration, size, distribution, and surface phenotype of EVs in a heterogeneous solution. However, by performing FL-NTA analysis of BALF-derived EVs in comparison to plasma-derived EVs, we reveal the limitations of this method, which is suitable only for relatively pure EV isolates. For more complex fluids such as plasma, this method appears to not be sensitive enough and the measurements can be compromised. Our parallel presentation of NTA-based phenotyping of plasma and BALF EVs emphasizes the great impact of sample composition and purity on FL-NTA analysis that has to be taken into account in the further development of FL-NTA toward the detection of EV-associated cancer biomarkers.

Generation of mutant pigs by lipofection-mediated genome editing in embryos

The specificity and efficiency of CRISPR/Cas9 gene-editing systems are determined by several factors, including the mode of delivery, when applied to mammalian embryos. Given the limited time window for delivery, faster and more reliable methods to introduce Cas9-gRNA ribonucleoprotein complexes (RNPs) into target embryos are needed. In pigs, somatic cell nuclear transfer using gene-modified somatic cells and the direct introduction of gene editors into the cytoplasm of zygotes/embryos by microinjection or electroporation have been used to generate gene-edited embryos; however, these strategies require expensive equipment and sophisticated techniques. In this study, we developed a novel lipofection-mediated RNP transfection technique that does not require specialized equipment for the generation of gene-edited pigs and produced no detectable off-target events. In particular, we determined the concentration of lipofection reagent for efficient RNP delivery into embryos and successfully generated MSTN gene-edited pigs (with mutations in 7 of 9 piglets) after blastocyst transfer to a recipient gilt. This newly established lipofection-based technique is still in its early stages and requires improvements, particularly in terms of editing efficiency. Nonetheless, this practical method for rapid and large-scale lipofection-mediated gene editing in pigs has important agricultural and biomedical applications.