Strength Enhancement of Polyurethane Film by Solution Annealing.

Recently, polyurethane elastomer (TPU) has attracted more and more attention depending on its excellent optical, mechanical, and retreatment properties. The high strength of polyurethane has always been pursued, which can enable its application in more fields. In this work, an aliphatic polyurethane elastomer membrane (HRPU6) was successfully synthesized, and its strength was obviously improved by solvent annealing technology. The tensile strength and adhesion strength can reach 64.56 and 2.58 MPa, but 36.55 and 1.57 MPa only before solvent annealing, respectively. The impact strength of laminated glass based on HRPU has also been significantly improved after solvent annealing, confirmed through drop ball impact testing. It has been confirmed that the increase in strength of HRPU6 is attributed to the enhancement of hydrogen bonding and the improvement of the phase separation degree.

US of thyroid nodules: can AI-assisted diagnostic system compete with fine needle aspiration?

OBJECTIVES: Artificial intelligence (AI) systems can diagnose thyroid nodules with similar or better performance than radiologists. Little is known about how this performance compares with that achieved through fine needle aspiration (FNA). This study aims to compare the diagnostic yields of FNA cytopathology alone and combined with BRAFV600E mutation analysis and an AI diagnostic system. METHODS: The ultrasound images of 637 thyroid nodules were collected in three hospitals. The diagnostic efficacies of an AI diagnostic system, FNA-based cytopathology, and BRAFV600E mutation analysis were evaluated in terms of sensitivity, specificity, accuracy, and the κ coefficient with respect to the gold standard, defined by postsurgical pathology and consistent benign outcomes from two combined FNA and mutation analysis examinations performed with a half-year interval. RESULTS: The malignancy threshold for the AI system was selected according to the Youden index from a retrospective cohort of 346 nodules and then applied to a prospective cohort of 291 nodules. The combination of FNA cytopathology according to the Bethesda criteria and BRAFV600E mutation analysis showed no significant difference from the AI system in terms of accuracy for either cohort in our multicenter study. In addition, for 45 included indeterminate Bethesda category III and IV nodules, the accuracy, sensitivity, and specificity of the AI system were 84.44%, 95.45%, and 73.91%, respectively. CONCLUSIONS: The AI diagnostic system showed similar diagnostic performance to FNA cytopathology combined with BRAFV600E mutation analysis. Given its advantages in terms of operability, time efficiency, non-invasiveness, and the wide availability of ultrasonography, it provides a new alternative for thyroid nodule diagnosis. CLINICAL RELEVANCE STATEMENT: Thyroid ultrasonic artificial intelligence shows statistically equivalent performance for thyroid nodule diagnosis to FNA cytopathology combined with BRAFV600E mutation analysis. It can be widely applied in hospitals and clinics to assist radiologists in thyroid nodule screening and is expected to reduce the need for relatively invasive FNA biopsies. KEY POINTS: • In a retrospective cohort of 346 nodules, the evaluated artificial intelligence (AI) system did not significantly differ from fine needle aspiration (FNA) cytopathology alone and combined with gene mutation analysis in accuracy. • In a prospective multicenter cohort of 291 nodules, the accuracy of the AI diagnostic system was not significantly different from that of FNA cytopathology either alone or combined with gene mutation analysis. • For 45 indeterminate Bethesda category III and IV nodules, the AI system did not perform significantly differently from BRAFV600E mutation analysis.

Blood immune indexes can predict lateral lymph node metastasis of thyroid papillary carcinoma.

Objective: To explore the clinical significance of blood immune indexes in predicting lateral lymph node metastasis (LLNM) of thyroid papillary carcinoma (PTC). Methods: The pathological data and preoperative blood samples of 713 patients that underwent thyroid surgery at affiliated Hangzhou First People's Hospital Zhejiang University School of Medicine from January 2013 to June 2021 were collected as the model group. The pathological data and preoperative blood samples of 177 patients that underwent thyroid surgery in the same hospital from July 2021 to October 2021 were collected as the external validation group. Univariate and multivariate logistic regression analyses were used to determine the independent risk factors of LLNM in PTC patients. A predictive model for assessing LLNM in PTC patients was established and externally validated using the external data. Results: According to univariate and multivariate logistic regression analyses, tumor diameter (P < 0.001, odds ratios (OR): 1.205, 95% confidence interval (CI): 1.162-1.249) and the preoperative systemic immune-inflammation index (SII) (P = 0.032, OR: 1.001, 95% CI: 1.000-1.002) were independent risk factors for distinguishing LLNM in PTC patients. When the Youden index was the highest, the area under the curve (AUC) was 0.860 (P < 0.001, 95% CI: 0.821-0.898). The externally validated AUC was 0.827 (P < 0.001, 95% CI: 0.724-0.929), the specificity was 86.4%, and the sensitivity was 69.6%. The calibration curve and the decision curve indicated that the model had good diagnostic value. Conclusion: Blood immune indexes can reflect the occurrence of LLNM and the biological behavior of PTC. The predictive model established in combination with SII and tumor diameter can effectively predict the occurrence of LLNM in PTC patients.

Tribological Behavior of Copper⁻Graphite Composites Reinforced with Cu-Coated or Uncoated SiO2 Particles.

Copper⁻graphite composites reinforced with SiO2 particles were fabricated by powder metallurgy technique. Electroless copper plating was introduced to improve the interfacial bonding between SiO2 particles and copper matrix. The microstructure, density, and hardness of the composites were characterized. The tribological properties, such as friction coefficient and wear rate of the composites, were studied using a pin-on-ring tribometer. The results show that the hard SiO2 can restrict the severe plastic deformation and adhesion contact in the process of wear. At the same time, parts of SiO2 particles can be broken into fine particles during wear process, which is helpful for decreasing adhesion wear and abrasive wear. Therefore, the addition of SiO2 leads to increasing friction stability and friction coefficient, and decreasing wear rate. In addition, the electroless copper plating improves the interfacial bonding between SiO2 and copper matrix, which prevents separation of SiO2 from copper matrix and further increase tribological properties of the composites.