Several potential drivers of avian tooth loss have been proposed, although consensus remains elusive as fully toothless jaws arose independently numerous times among Mesozoic avialans and dinosaurs more broadly. The origin of crown bird edentulism has been discussed in terms of a broad-scale selective pressure or trend toward toothlessness, although this has never been quantitatively tested. Here, we find no evidence for models whereby iterative acquisitions of toothlessness among Mesozoic Avialae were driven by an overarching selective trend. Instead, our results support modularity among jaw regions underlying heterogeneous tooth loss patterns and indicate a substantially later transition to complete crown bird edentulism than previously hypothesized (∼90 mya). We show that patterns of avialan tooth loss adhere to Dollo's law and suggest that the exclusive survival of toothless birds to the present represents lineage-specific selective pressures, irreversibility of tooth loss, and the filter of the Cretaceous-Paleogene (K-Pg) mass extinction.Cell heterogeneity, such as antibiotic heteroresistance and cancer cell heterogeneity, has been increasingly observed. To probe the underlying molecular mechanisms in the dynamically changing heterogeneous cells, a high throughput platform is urgently needed to establish single cell genotype-phenotype correlations. Herein, we report a platform combining single-cell viability phenotypic analysis with digital molecular detection for bacterial cells. The platform utilizes polyethylene glycol hydrogel that cross-links through a thiol-Michael addition, which is biocompatible, fast, and spontaneous. To generate uniform nanoliter-sized hydrogel beads (Gelbeads), we developed a convenient and disposable device made of needles and microcentrifuge tubes. Gelbead-based single cell viability and molecular detection assays were established. Enhanced thermal stability and uncompromised efficiency were achieved for digital polymerase chain reaction (PCR) and digital loop-mediated isothermal amplification (LAMP) within the Gelbeads. Reagent exchange for in situ PCR following viability phenotypic analyses was demonstrated. The combined analyses may address the genotypic differences between cellular subpopulations exhibiting distinct phenotypes. The platform promises unique perspectives in mechanism elucidation of environment-evolution interaction that may be extended to other cell types for medical research.Femoroplasty is a proposed alternative therapeutic method for preventing osteoporotic hip fractures in the elderly. Previously developed navigation system for femoroplasty required the attachment of an external X-ray fiducial to the femur. We propose a fiducial-free 2D/3D registration pipeline using fluoroscopic images for robot-assisted femoroplasty. Intraoperative fluoroscopic images are taken from multiple views to perform registration of the femur and drilling/injection device. The proposed method was tested through comprehensive simulation and cadaveric studies. Performance was evaluated on the registration error of the femur and the drilling/injection device. In simulations, the proposed approach achieved a mean accuracy of 1.26±0.74 mm for the relative planned injection entry point; 0.63±0.21° and 0.17±0.19° for the femur injection path direction and device guide direction, respectively. In the cadaver studies, a mean error of 2.64 ± 1.10 mm was achieved between the planned entry point and the device guide tip. Sapogenins Glycosides cell line The biomechanical analysis showed that even with a 4 mm translational deviation from the optimal injection path, the yield load prior to fracture increased by 40.7%. This result suggests that the fiducial-less 2D/3D registration is sufficiently accurate to guide robot assisted femoroplasty.
Alert fatigue is a common issue with off-the-shelf clinical decision support. Most warnings for drug-drug interactions (DDIs) are overridden or ignored, likely because they lack relevance to the patient's clinical situation. Existing alerting systems for DDIs are often simplistic in nature or do not take the specific patient context into consideration, leading to overly sensitive alerts. The objective of this study is to develop, validate, and test DDI alert algorithms that take advantage of patient context available in electronic health records (EHRs) data.
Data on the rate at which DDI alerts were triggered but for which no action was taken over a 3-month period (override rates) from a single tertiary care facility were used to identify DDIs that were considered a high-priority for contextualized alerting. A panel of DDI experts developed algorithms that incorporate drug and patient characteristics that affect the relevance of such warnings. The algorithms were then implemented as computable artifacts, validated using a synthetic health records data, and tested over retrospective data from a single urban hospital.
Algorithms and computable knowledge artifacts were developed and validated for a total of 8 high priority DDIs. Testing on retrospective real-world data showed the potential for the algorithms to reduce alerts that interrupt clinician workflow by more than 50%. Two algorithms (citalopram/QT interval prolonging agents, and fluconazole/opioid) showed potential to filter nearly all interruptive alerts for these combinations.
The 8 DDI algorithms are a step toward addressing a critical need for DDI alerts that are more specific to patient context than current commercial alerting systems. Data commonly available in EHRs can improve DDI alert specificity.
The 8 DDI algorithms are a step toward addressing a critical need for DDI alerts that are more specific to patient context than current commercial alerting systems. Data commonly available in EHRs can improve DDI alert specificity.The recent development of liquid cell (scanning) transmission electron microscopy (LC-(S)TEM) has opened the unique possibility of studying the chemical behavior of nanomaterials down to the nanoscale in a liquid environment. Here, we show that the chemically induced etching of three different types of silica-based silica nanoparticles can be reliably studied at the single particle level using LC-(S)TEM with a negligible effect of the electron beam, and we demonstrate this method by successfully monitoring the formation of silica-based heterogeneous yolk-shell nanostructures. By scrutinizing the influence of electron beam irradiation, we show that the cumulative electron dose on the imaging area plays a crucial role in the observed damage and needs to be considered during experimental design. Monte-Carlo simulations of the electron trajectories during LC-(S)TEM experiments allowed us to relate the cumulative electron dose to the deposited energy on the particles, which was found to significantly alter the silica network under imaging conditions of nanoparticles.Sapogenins Glycosides cell line
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