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Automated segmentation of the fibula from CT imaging using two-stepped deep learning in 3D U-Net architectures
Abstract This study proposes a fully automatic segmentation of the fibula bone from CT images for application in pre-operative planning of reconstructive surgery. The objective is to make use of new developments in the image segmentation field to optimize and reduce the costs of patient-specific surgery planning. Two different approaches are proposed to perform the fibula bone segmentation, both based on a two-step segmentation method using a 3D-UNet architecture. To account for the symmetry of the left and right fibula bones, input images of the right fibula are mirrored to the left side. The accuracy of the trained models is measured using common evaluation metrics, together with specific metrics focused on facial reconstructive surgery. Both of the described approaches achieve high-accuracy results. For the best-trained model, an average Dice score of 0.95 and Average Surface Distances below 0.31 mm is measured on the test set in the region of interest for the surgery. Both approaches are robust segmentation techniques and permit data pre-processing for further application in the context of preoperative surgical planning of procedures for facial reconstruction with bony transplants.
Microengineered patient-derived endometrium-on-a-chip for the evaluation of endometrial receptivity and personalised translational medicine
Temporal dynamics of the resistome in gilts raised in an organic operation in which semen used for artificial insemination is the primary source of antimicrobial exposure
Azimuthal sensitivity and spatio-temporal decimation of data from distributed acoustic sensing on submarine cables for offshore earthquake early warning systems
Abstract Offshore earthquakes can cause widespread destruction due to directly propagating seismic vibrations and/or the generation of tsunamis. Early warning of offshore earthquakes is vital, but their location complicates identification of clear early warning (EW) signatures. Distributed acoustic sensing (DAS), applied to offshore fibre-optic cables offers the prospect to improve early warning of offshore events. We use a DAS dataset acquired from a 30 km submarine cable spanning a complex bathymetry, offshore Sicily, to contribute to a proof-of-concept using five regional earthquakes to investigate factors impacting incident body wave detection capabilities. We demonstrate observations for P- and S-waves incident parallel and perpendicular to the cable, and that cable coupling to the surrounding medium exerts far more control on signal quality than incidence azimuth. Compared to the nearest land station, an EW signal for a Mw5.8 earthquake was triggered 1.59 seconds earlier using P-wave arrivals on the fibre, and 3.89 seconds earlier using S-waves. We show that effective warnings can be made despite spatially decimating data by factors of 10 and 100 for P-waves and S-waves, respectively. This data volume reduction allows DAS on legacy seafloor cables to be integrated with EW systems for offshore earthquakes and other geohazards which threaten coastal populations.
Regioselective and site-divergent synthesis of tetrahydropyridines by controlled reductive-oxidative dearomative hydroarylation of pyridinium salts
The choline chloride/hydroquinone carboxylic acid-based DES as a novel catalyst for the green synthesis of dihydrochromeno[4,3-d]pyrimidinediones
Optimization of biochar production from Rumex abyssinicus using response surface methodology and its application in amending degraded soil
Context-dependent serotonin signaling links dietary quality to foraging decisions
Abstract Animals sense their metabolic needs to guide adaptive behaviors partly through serotonin, a neurotransmitter associated with feeding in many species. Here we investigate the ability of the serotonin system to evaluate and interpret diverse diets by studying long-term foraging behaviors of the nematode C. elegans on bacteria. Behavioral screens on a genome-wide collection of E coli strains identified 22 metabolic mutants that induce behavioral aversion and stress responses in C. elegans . We show that different classes of serotonergic neurons promote aversion to non-preferred E. coli diets and retention on preferred E. coli diets, respectively, through different serotonin receptors. Serotonin is integrated with dopamine and octopamine signals across distributed circuits to direct opposing behavioral responses to preferred and aversive diets. These results reveal interacting neuromodulatory circuits that guide context-dependent evaluation of dietary quality.
Tracheal meandering may predict prognosis in idiopathic pleuroparenchymal fibroelastosis: a retrospective observational study
A survey of bacterial and fungal community structure and functions in two long-term metalliferous soil habitats
A foundation machine learning potential with polarizable long-range interactions for materials modelling
Abstract Long-range interactions are essential determinants of chemical system behavior across diverse environments. We present a foundation framework that integrates explicit polarizable long-range physics with an equivariant graph neural network potential. It employs a physically motivated polarizable charge equilibration scheme that directly optimizes electrostatic interaction energies rather than partial charges. The foundation model, trained across the periodic table up to Pu, demonstrates strong performance across key materials modeling challenges. It effectively captures long-range interactions that are challenging for traditional message-passing mechanisms and accurately reproduces polarization effects under external electric fields. We have applied the model to mechanical properties, ionic diffusivity in solid-state electrolytes, ferroelectric phase transitions, and reactive dynamics at electrode-electrolyte interfaces, highlighting the model’s capacity to balance accuracy and computational efficiency. Furthermore, we show that as a foundation model, it can be efficiently finetuned to achieve high-level accuracy for specific challenging systems.
An interval-valued Pythagorean fuzzy TOPSIS approach for service quality evaluation of bike-sharing providers under uncertain environment
Facemasks reduce face trustworthiness perceived by deaf individuals
Selective CO2 reduction to acetate via controlled sp2/sp3 carbon hybridization
Moderate mortality of groundwater copepods Diacyclops humphreysi after exposure to perfluorooctane sulfonate (PFOS)
Validation of mid-upper arm circumference against to body mass index-for-age for assessing nutritional status among school adolescents in Ethiopia
Synaptic proteome diversity is shaped by the levels of glutamate receptors and their regulatory proteins
Age disparities in adverse reactions of drugs used in pain therapies in Switzerland
Abstract Pain therapies are prescribed to a significant proportion of the population but also associated with adverse drug reactions (ADRs). The prescription of pain therapies requires careful consideration of their safety profiles in the context of patient-specific characteristics, such as age-specific vulnerabilities, which are, however, still understudied so far. The aim of this study was to describe ADRs reported for drugs used in pain therapies and investigate age disparities. We conducted a descriptive comparative analysis of individual case safety reports (ICSRs) of drugs used in pain therapies from the global ADR database VigiBase between September 29, 1991, and December 31, 2022, from Switzerland. Comparisons were drawn between younger and older adults (18–74 years vs. 75 + years). Disproportionality (reporting odds ratio, ROR) of serious ADRs was assessed between age groups. A total of 17,228 ICSRs were analysed (58% female, 24% age 75 +). Across both age groups, the most frequently reported ADRs were related to the nervous system (23%), gastrointestinal system (20%), and general health and administration site conditions (20%). Serious ADRs were more common in the older population compared to younger adults (69% vs. 54%) with an ROR of 1.9. Fatal ADRs were also disproportionally higher in older adults (ROR 1.9). Hemorrhage was the most frequent fatal reaction. Commonly used pain therapies can lead to ADRs with a pronounced impact, especially in older adults. A deeper understanding of the safety profiles of these drugs should aid healthcare professionals in making more informed, safer treatment decisions.