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The COVID-19 pandemic has had direct and indirect effects on daily life. In hospitals, the impact of the pandemic was observed in the diagnostic and therapeutic workflow. In this work, we explored potential changes in activities related to the treatment of foreign body injuries (FBIs) in children and the behavioral habits of physicians during the first wave of the pandemic. An online survey was conducted among physicians of the Susy Safe network. The survey comprised items related to respondent information, reference center characteristics, the treatment of FBIs during the COVID-19 pandemic, and a modified COVID-19 Anxiety Scale (CAS). The survey was distributed among the Susy Safe project international network surveillance registry for FBIs. A total of 58 physicians responded to the survey, including 18 (32%) from Europe and 16 (28%) from South America. The respondents indicated that the estimated number of aspirated foreign bodies during the pandemic was lower than or the same as that before the pandemic (43, 74%), and the same was observed for ingested foreign bodies (43, 74%). In univariable logistic regression, no single predictor was associated with a delay in routine care for children or an increasing tendency of medical personnel to avoid procedures. The workflow of physicians involved in the management of FBIs in children has not changed drastically during the COVID-19 pandemic, especially in emergency departments.

Inverting seismic data to build 3D geological structures is a challenging task due to the overwhelming amount of acquired seismic data, and the very-high computational load due to iterative numerical solutions of the wave equation, as required by industry-standard tools such as Full Waveform Inversion (FWI). For example, in an area with surface dimensions of 4.5 km × 4.5 km, hundreds of seismic shot-gather cubes are required for 3D model reconstruction, leading to Terabytes of recorded data. This paper presents a deep learning solution for the reconstruction of realistic 3D models in the presence of field noise recorded in seismic surveys. We implement and analyze a convolutional encoder–decoder architecture that efficiently processes the entire collection of hundreds of seismic shot-gather cubes. The proposed solution demonstrates that realistic 3D models can be reconstructed with a structural similarity index measure (SSIM) of 0.9143 (out of 1.0) in the presence of field noise at 10 dB signal-to-noise ratio.

Minimally invasive exodontia is among the long-sought-for development aims of safe dental medicine. In this paper, we aim, for the first time, to examine whether the enzymatic disruption of the periodontal ligament fibers reduces the force required for tooth extraction. To this end, recombinantly expressed clostridial collagenase G variant purified from Escherichia coli was injected into the periodontal ligament of mesial and distal roots of the first and second split porcine mandibular premolars. The vehicle solution was injected into the corresponding roots on the contralateral side. Following sixteen hours, the treated mandibles were mounted on a loading machine to measure the extraction force. In addition, the effect of the enzyme on the viability of different cell types was evaluated. An average reduction of 20% in the applied force (albeit with a large variability of 50 to 370 newton) was observed for the enzymatically treated roots, reaching up to 50% reduction in some cases. Importantly, the enzyme showed only a minor and transient effect on cellular viability, without any signs of toxicity. Using an innovative model enabling the analytical measurement of extraction forces, we show, for the first time, that the enzymatic disruption of periodontal ligament fibers substantially reduces the force required for tooth extraction. This novel technique brings us closer to atraumatic exodontia, potentially reducing intra- and post-operative complications and facilitating subsequent implant placement. The development of novel enzymes with enhanced activity may further simplify the tooth extraction process and present additional clinical relevance for the broad range of implications in the oral cavity.

The initial discovery phase of protein modulators, which consists of filtering molecular libraries and in vitro direct binding validation, is central in drug discovery. Thus, virtual screening of large molecular libraries, together with the evaluation of binding affinity by isothermal calorimetry, generates an efficient experimental setup. Herein, we applied virtual screening for discovering small molecule inhibitors of MDM2, a major negative regulator of the tumor suppressor p53, and thus a promising therapeutic target. A library of 20 million small molecules was screened against an averaged model derived from multiple structural conformations of MDM2 based on published structures. Selected molecules originating from the computational filtering were tested in vitro for their direct binding to MDM2 via isothermal titration calorimetry. Three new molecules, representing distinct chemical scaffolds, showed binding to MDM2. These were further evaluated by exploring structure-similar chemical analogues. Two scaffolds were further evaluated by de novo synthesis of molecules derived from the initial molecules that bound MDM2, one with a central oxoazetidine acetamide and one with benzene sulfonamide. Several molecules derived from these scaffolds increased wild-type p53 activity in MCF7 cancer cells. These set a basis for further chemical optimization and the development of new chemical entities as anticancer drugs.

Copper is an essential metal ion that is involved in critical cellular processes, but which can also exhibit toxic effects through its ability to catalyze reactive oxygen species (ROS) formation. Dysregulation of copper homeostasis has been implicated in the progression of several diseases, including cancer. A novel therapeutic approach, extensively studied in recent years, is to capitalize on the increased copper uptake and dependency exhibited by cancer cells and to promote copper-associated ROS production within the tumor microenvironment, leading to the apoptosis of cancer cells. Such an effect can be achieved by selectively chelating copper from copper-bearing metalloproteins in cancer cells, thereby forming a copper-chelator complex that produces ROS and, through this, induces oxidative stress and initiates apoptosis. Herein, we describe a peptoid chelator, TB , that is highly suitable to carry this task. Peptoids are N-substituted glycine oligomers that can be efficiently synthesized on a solid support and are also biocompatible; thus, they are considered promising drug candidates. We show, by rigorous spectroscopic techniques, that TB is not only selective for Cu(II) ions, but can also effectively extract copper from metallothionein-2, and the formed complex Cu TB can promote ROS production. Our findings present a promising first example for the future development of peptoid-based chelators for applications in anti-cancer chelation therapy, highlighting the potential for the prospect of peptoid chelators as therapeutics.