High-Strength Amorphous Silicon Carbide for Nanomechanics

For decades, mechanical resonators with high sensitivity have been realized using thin-film materials under high tensile loads. Although there have been remarkable strides in achieving low-dissipation mechanical sensors by utilizing high tensile stress, the performance of even the best strategy is limited by the tensile fracture strength of the resonator materials. In this study, a wafer-scale amorphous thin film is uncovered, which has the highest ultimate tensile strength ever measured for a nanostructured amorphous material. This silicon carbide (SiC) material exhibits an ultimate tensile strength of over 10 GPa, reaching the regime reserved for strong crystalline materials and approaching levels experimentally shown in graphene nanoribbons. Amorphous SiC strings with high aspect ratios are fabricated, with mechanical modes exceeding quality factors 10^8 at room temperature, the highest value achieved among SiC resonators. These performances are demonstrated faithfully after characterizing the mechanical properties of the thin film using the resonance behaviors of free-standing resonators. This robust thin-film material has significant potential for applications in nanomechanical sensors, solar cells, biological applications, space exploration and other areas requiring strength and stability in dynamic environments. The findings of this study open up new possibilities for the use of amorphous thin-film materials in high-performance applications

Growth Pattern Analysis of Murine Lung Neoplasms by Advanced Semi-Automated Quantification of Micro-CT Images

Computed tomography (CT) is a non-invasive imaging modality used to monitor human lung cancers. Typically, tumor volumes are calculated using manual or semi-automated methods that require substantial user input, and an exponential growth model is used to predict tumor growth. However, these measurement methodologies are time-consuming and can lack consistency. In addition, the availability of datasets with sequential images of the same tumor that are needed to characterize in vivo growth patterns for human lung cancers is limited due to treatment interventions and radiation exposure associated with multiple scans. In this paper, we performed micro-CT imaging of mouse lung cancers induced by overexpression of ribonucleotide reductase, a key enzyme in nucleotide biosynthesis, and developed an advanced semi-automated algorithm for efficient and accurate tumor volume measurement. Tumor volumes determined by the algorithm were first validated by comparison with results from manual methods for volume determination as well as direct physical measurements. A longitudinal study was then performed to investigate in vivo murine lung tumor growth patterns. Individual mice were imaged at least three times, with at least three weeks between scans. The tumors analyzed exhibited an exponential growth pattern, with an average doubling time of 57.08 days. The accuracy of the algorithm in the longitudinal study was also confirmed by comparing its output with manual measurements. These results suggest an exponential growth model for lung neoplasms and establish a new advanced semi-automated algorithm to measure lung tumor volume in mice that can aid efforts to improve lung cancer diagnosis and the evaluation of therapeutic responses

Distribution of Suitable Habitats for Soft Corals (Alcyonacea) Based on Machine Learning

The soft coral order Alcyonacea is a common coral found in the deep sea and plays a crucial role in the deep-sea ecosystem. This study aims to predict the distribution of Alcyonacea in the western Pacific Ocean using four machine learning-based species distribution models. The performance of these models is also evaluated. The results indicate a high consistency among the prediction results of the different models. The soft coral order is primarily distributed in the Thousand Islands Basin, Japan Trench, and Thousand Islands Trench. Water depth and silicate content are identified as important environmental factors influencing the distribution of Alcyonacea. The RF, Maxent, and XGBoost models demonstrate high accuracies, with the RF model exhibiting the highest prediction accuracy. However, the Maxent model outperforms the other three models in data processing. Developing a high-resolution, high-accuracy, and high-precision habitat suitability model for soft corals can provide a scientific basis and reference for China’s exploration and research in the deep sea field and aid in the planning of protected areas in the high seas

Efficacy and safety of oropharyngeal muscle strength training on poststroke oropharyngeal dysphagia: a systematic review and meta-analysis

Objectives To investigate how oropharyngeal muscle strength training affected the safety and performance of swallowing in patients with poststroke oropharyngeal dysphagia.Design Systematic review and meta-analysis.Data sources Cochrane Central Register of Controlled of Trials, Web of Science, PubMed, Embase databases and ClinicalTrials.gov were systematically searched, for publications in English, from database inception to December 2022.Eligibility criteria Studies comparing the effect of oropharyngeal muscle strength training with conventional dysphagia therapy in patients with poststroke. Penetration-Aspiration Scale (PAS) and Functional Oral Intake Scale (FOIS) were assessed as the main outcomes.Data extraction and synthesis Two researchers independently screened the literature, extracted data and evaluated the quality of the included studies, with disagreements resolved by another researcher. The Cochrane risk-of-bias tool was used to assess the risk of bias. Review Manager V.5.3 was employed for the meta-analysis. Random effect models were used for meta-analysis.Results Seven studies with 259 participants were included in this meta-analysis. The results showed that oropharyngeal muscle strength training could reduce PAS score compared with conventional dysphagia therapy (mean difference=−0.98, 95% CI −1.34 to −0.62, p<0.0001, I2=28%). The results also showed that oropharyngeal muscle strength training could increase FOIS score (mean difference=1.04, 95% CI 0.55 to 1.54, p<0.0001, I2=0%) and the vertical displacement of the hyoid bone (mean difference=0.20, 95% CI 0.01 to 0.38, p=0.04, I2=0%) compared with conventional dysphagia therapy.Conclusion In patients with poststroke oropharyngeal dysphagia, oropharyngeal muscle strength training can improve swallowing safety and performance.PROSPERO registration number CRD42022302471

Chiral <i>N</i>‑Phosphonyl Imines for an Aza-Morita–Baylis–Hillman Reaction via Group-Assisted Purification (GAP) Chemistry

Seventeen examples of aza-Morita–Baylis–Hillman (aza-MBH) adducts have been synthesized by reacting chiral <i>N</i>-phosphonyl imines with acrylonitrile in good to excellent yields (up to 96%) and high diastereoselectivity (up to 99:1 dr). The synthesis of these adducts followed the method of group-assisted purification (GAP) chemistry, in which the pure aza-MBH products were readily obtained by washing the crude products with cosolvents of hexane and ethyl acetate