A wear-resistant metastable CoCrNiCu high-entropy alloy with modulated surface and subsurface structures

Sliding friction-induced subsurface structures and severe surface oxidation can be the major causes influencing the wear resistance of ductile metallic materials. Here, we demonstrated the role of subsurface and surface structures in enhancing the wear resistance of an equiatomic metastable CoCrNiCu high-entropy alloy (HEA). The CoCrNiCu HEA is composed of a CoCrNi-rich face-centered cubic (FCC) dendrite phase and a Cu-rich FCC inter-dendrite phase. Copious Cu-rich nano-precipitates are formed and distributed uniformly inside the dendrites after tuning the distribution and composition of the two phases by thermal annealing. Although the formation of nano-precipitates decreases the hardness of the alloy due to the loss of solid solution strengthening, these nano-precipitates can be deformed to form continuous Cu-rich nanolayers during dry sliding, leading to a self-organized nano-laminated microstructure and extensive hardening in the subsurface. In addition, the nano-precipitates can facilitate the formation of continuous and compacted glaze layers on the worn surface, which are also beneficial for the reduction of the wear rate of CoCrNiCu. The current work can be extended to other alloy systems and might provide guidelines for designing and fabricating wear-resistant alloys in general

I. Pedagogy

本研究では, 慣性を例にして物理学習観が実験や解説への興味・関心, 事後テストにどのように影響しているのかを共分散構造分析でモデル化した。その結果, 「実験への興味」が「解説への関心」に強く影響し, 「事後テストの成績」にも影響していた。また, 解き方よりも答えを重視したり, 公式を丸暗記したりする「過程無視」という学習観が, 「実験への興味」に負の影響を及ぼしていることが明らかになった。これらのことから, 従来から取り組まれてきた実験開発に加えて, 「過程無視」のような物理学習観を見直させることにより, 物理学習への興味・関心を引き, 成績も改善させる可能性があることを示唆した

Bounds for the Combinations of Neuman-Sándor, Arithmetic, and Second Seiffert Means in terms of Contraharmonic Mean

We give the greatest values r1, r2 and the least values s1, s2 in (1/2, 1) such that the double inequalities C(r1a+(1-r1)b,r1b+(1-r1)a)0 with a≠b, where A(a,b), M(a,b), C(a,b), and T(a,b) are the arithmetic, Neuman-Sándor, contraharmonic, and second Seiffert means of a and b, respectively

Synergistic Anticancer Activity of Combined Use of Caffeic Acid with Paclitaxel Enhances Apoptosis of Non-Small-Cell Lung Cancer H1299 Cells in Vivo and in Vitro

Background/Aims: Caffeic acid (CA) is known to possess multiple biological activities including anti-cancer activities. However, the molecular mechanisms underlying these activities in non-small-cell lung cancer (NSCLC) cells are not fully understood. We attempted to clarify whether CA could enhance paclitaxel (PTX)-induced cytotoxicity in H1299 cells. Methods: First, we tested the cytotoxic effects in both H1299 cells and normal human Bease-2b cells by cell proliferation experiments. Next, we use Annexin V/propidium iodide apoptosis analysis and flow cytometric analysis to investigate apoptosis and cell cycle arrest under the treatments mentioned above. To further pinpoint changes in apoptosis, we tested the caspase-associated apoptotic pathway, which involves the activities of caspase-3 and caspase-9. Moreover, apoptosis-related proteins and MAPK pathway proteins were examined by western blot. An H1299 xenograft nude mice model was used to further evaluate the tumor-suppressing effects of CA and PTX in vivo. Results: Combination treatment with low-dose CA and PTX decreased the proliferation of NSCLC H1299 cells but not normal Beas-2b cells. Flow cytometry showed that H1299 cells were arrested in the sub-G1 phase and apoptosis was significantly increased in H1299 cells after CA treatment. Caspase-3 and caspase-9 activities were both increased after CA treatment. Furthermore, CA increased the PTX-induced activation of Bax, Bid, and downstream cleaved PARP, and phosphorylation of extracellular signal regulated kinase1/2 and c-Jun NH2-terminal protein kinase1/2. An in vivo tumor-suppression assay demonstrated that CA and PTX combined treatment exerted a more effective suppressive effect on tumor growth in H1299 xenografts without causing significant adverse effects. Conclusions: Our results indicated that CA inhibited NSCLC H1299 cell growth by inducing apoptosis and CA and PTX combined produced a synergistic anti-cancer effect in H1299 cells

Constructing a nomogram based on the distribution of thyroid nodules and suspicious lateral cervical lymph nodes in fine-needle aspiration biopsies to predict metastasis in papillary thyroid carcinoma

PurposeElevated concentrations of thyroglobulin eluent is a risk factor for lateral cervical lymph node metastasis (LLNM) in patients with papillary thyroid cancer (PTC). We aimed to develop a practical nomogram based on the distribution of thyroid nodules and the presence of suspicious lateral cervical lymph nodes in fine-needle aspiration biopsies (LN-FNABs), including the cytopathology and the suspicious lateral cervical lymph node (LLN) thyroglobulin eluent (Tg), to predict the possibility of LLNM preoperatively in patients with PTC.MethodsThe clinical data of PTC patients who were admitted to the Third Affiliated Hospital of Soochow University from January 2022 to May 2023 to undergo fine-needle aspiration biopsy (FNAB) were included in this study. A total of 208 patients in 2022 served as the training set (70%), and 89 patients in 2023 served as the validation set (30%). The clinical characteristics and LN-FNAB results were collected to determine the risk factors of LLNM. A preoperative nomogram was developed for predicting LLNM based on the results of the univariate and multivariate analyses. Internal calibration, external calibration, and decision curve analysis (DCA) were performed for these models.ResultsThe multivariate logistic regression analysis showed that the maximum thyroid nodule diameter (Odds Ratio (OR) 2.323, 95% CI 1.383 to 3.904; p = 0.001), Tg level (OR 1.007, 95% CI 1.005 to 1.009; p = 0.000), Tg divided by serum thyroglobulin, (Tg/sTg) [odds ratio (OR) 1.005, 95% CI 1.001 to 1.008; p = 0.009], and cytopathology (OR 9.738, 95% CI 3.678 to 25.783; p = 0.000) (all p <  0.05) had a significant impact on the LLNM of patients with suspicious LLNs. The nomogram showed a better predictive value in both the training cohort [area under the curve, (AUC) 0.937, 95% CI 0.895 to 0.966] and the validation cohort (AUC 0.957, 95% CI 0.892 to 0.989). The nomogram also showed excellent internal and external calibration in predicting LLNM. According to the DCA, the diagnostic performance of this model was dependent on the following variables: maximum thyroid nodule diameter, Tg level, Tg/sTg, and cytopathology.ConclusionBased on the aforementioned risk factors, we believe that it is necessary to establish a personalized LLNM model for patients with PTC. Using this practical nomogram, which combines clinical and Tg risk factors, surgeons could accurately predict the possibility of LLNM preoperatively. The nomogram will also help surgeons to establish personalized treatment plans before surgery