Challenges for future directions for artificial intelligence integrated nursing simulation education

Artificial intelligence (AI) has tremendous potential to change the way we train future health professionals. Although AI can provide improved realism, engagement, and personalization in nursing simulations, it is also important to address any issues associated with the technology, teaching methods, and ethical considerations of AI. In nursing simulation education, AI does not replace the valuable role of nurse educators but can enhance the educational effectiveness of simulation by promoting interdisciplinary collaboration, faculty development, and learner self-direction. We should continue to explore, innovate, and adapt our teaching methods to provide nursing students with the best possible education

High-Power Hybrid Solid-State Lithium-Metal Batteries Enabled by Preferred Directional Lithium Growth Mechanism

Solid electrolytes are revolutionizing the field of lithium-metal batteries; however, their practical implementa-tion has been impeded by the interfacial instability between lithium metal electrodes and solid electrolytes. While various interlayers have been suggested to address this issue in recent years, long-term stability with repeated lithium deposition/ stripping has been challenging to attain. Herein, we successfully operate a high-power lithium-metal battery by inducing the preferred directional lithium growth with a rationally designed interlayer, which employs (i) crystalline-direction-controlled carbon material providing isotropic lithium transports, with (ii) prelithium deposits that guide the lithium nucleation direction toward the current collector. This combination ensures that the morphology of the interlayer is mechanically robust while regulating the preferred lithium growth underneath the interlayer without disrupting the initial interlayer/electrolyte interface, enhancing the durability of the interface. We illustrate how these material/geometric optimizations are conducted from the thermodynamic considerations, and its applicability is demonstrated for the garnet-type Li7-xLa3-aZr2-bO12 (LLZO) solid electrolytes paired with the capacity cathode. It is shown that a lithium-metal cell with the optimized amorphous carbon interlayer with prelithium deposits exhibits outstanding room-temperature cycling performance (99. 6% capacity retention after 250 cycles), delivering 4.0 mAh cm-2 at 2.5 mA cm-2 without significant degradation of the capacity. The successful long-term operation of the hybrid solid-state cell at room temperature (approximately a cumulative deliverable capacity of over 1000 mAh cm-2) is unprecedented and records the highest performance reported for lithium-metal batteries with LLZO electrolytes until date

Direct calibration of PICKY-designed microarrays

Abstract Background Few microarrays have been quantitatively calibrated to identify optimal hybridization conditions because it is difficult to precisely determine the hybridization characteristics of a microarray using biologically variable cDNA samples. Results Using synthesized samples with known concentrations of specific oligonucleotides, a series of microarray experiments was conducted to evaluate microarrays designed by PICKY, an oligo microarray design software tool, and to test a direct microarray calibration method based on the PICKY-predicted, thermodynamically closest nontarget information. The complete set of microarray experiment results is archived in the GEO database with series accession number GSE14717. Additional data files and Perl programs described in this paper can be obtained from the website http://www.complex.iastate.edu under the PICKY Download area. Conclusion PICKY-designed microarray probes are highly reliable over a wide range of hybridization temperatures and sample concentrations. The microarray calibration method reported here allows researchers to experimentally optimize their hybridization conditions. Because this method is straightforward, uses existing microarrays and relatively inexpensive synthesized samples, it can be used by any lab that uses microarrays designed by PICKY. In addition, other microarrays can be reanalyzed by PICKY to obtain the thermodynamically closest nontarget information for calibration

A Case of Hypertrophic Osteoarthropathy Associated with Epithelioid Hemangioendothelioma

Epithelioid hemangioendothelioma is a rare vascular tumor, which occurs in the lung, liver, bone, and soft tissue. Hypertrophic osteoarthropathy is a syndrome characterized by subperiosteal new bone formation, joint effusion and clubbing, and may be associated with cyanotic heart disease, chronic pulmonary disease, liver disease, and other miscellaneous diseases. The activation of endothelium and platelets has been suggested to be involved in the development of hypertrophic osteoarthropathy. We report a rare case of hypertrophic osteoarthropathy, which developed in association with hepatic epithelioid hemangioendothelioma with pulmonary metastasis. We also discuss the role of vascular endothelial growth factor in its pathogenesis